vvEPA Inventory of U.S. Greenhouse Gas
Emissions and Sinks: 1990 -2004
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How to obtain copies
You can electronically download this document on the U.S. EPA's homepage at . To request free copies of this report, call the National Service Center for Environmental Publications
(NSCEP) at (800) 490-9198, or visit the web site above and click on "order online" after selecting an edition.
All data tables of this document are available for the full time series 1990 through 2004, 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. LisaHanle, Environmental Protection Agency, (202) 343-9434, hanle.lisa@epa.gov.
For more information regarding climate change and greenhouse gas emissions, see the EPA web site at .
Released for printing: April 15, 2006
Higher Tiered, Innovative Approaches for Estimating of U.S. Greenhouse Gas Emissions and Sinks
The photos on the front and back cover of this report depict some of the source categories for which the United States as
developed higher tiered or innovative approaches for estimate greenhouse gas emissions or sinks. For these source categories,
the United States applies sophisticated modeling approaches, often combined with detailed, bottom-up data. A selection
of source categories, representing every sector of the 1990-2004 U.S. Inventory, is presented in these cover photos.
HFC and RFC Consumption from ODS Substitutes: Vintaging Model: The Vintaging Model, used for estimating
emissions from the consumption of HFCs and PFCs used as substitutes for ozone depleting substances, is a
bottom-up model that independently estimates emissions over the lifecycle of over 50 unique end-uses. The
model estimates emissions from refrigeration, air-conditioning, foam manufacturing, solvent use, aerosol use,
and fire protection. Using information in end-use growth rates, consumption and emission profiles, lifetimes,
and transitions away from ozone depleting substances, the Vintaging Model creates a time profile of HFCs
and PFCs emissions, by gas, for the years 1985 through 2030.
Forest Carbon Stock Change: FORCARB2: FORCARB2 is a carbon stock change model that estimates carbon
density for live trees, understory vegetation, standing dead trees, down dead wood, forest floor, and soil organic
matter. Carbon estimates are based on tree species, dimensions, stand age, region, forest type, and growing
stock volume. FORCARB2 carbon coefficients are applied to U.S. forest survey data within each state and
summed over all states to estimate net forest carbon stock change for the conterminous United States.
Enteric Fermentation: CEFM: The Cattle Enteric Fermentation Model (CEFM) calculates methane emissions
from cattle enteric fermentation based on a "rolling herd" population characterization that tracks cattle
energy demand through different growth stages, and addresses the complex problem of simulating the cattle
population from birth to slaughter while accounting for the variability in methane emissions associated with
each life stage. The model simulates monthly growth stages by cattle type (e.g., beef versus dairy) in a cattle
population transition matrix and correlates the energy demands with methane production based on regional
diet and animal characteristics.
Non-Energy Uses Of Fossil Fuels: A significant proportion of fossil fuels is not burned for energy, but used for
petrochemical synthesis, reductants (e.g., for metallurgical processes), and non-fuel products (e.g., asphalt,
lubricants, waxes). The U. S. Inventory employs several country-specific mass balance approaches to estimate
final emissions from these processes and products. These approaches characterize the fates for each non-energy
use of fossil fuels to determine the amount of carbon emissions, or storage, associated with each use.
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INVENTORY OF U.S. GREENHOUSE GAS
EMISSIONS AND SINKS:
199O-2OO4
April 15, 2006
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, N.W.
Washington, DC 20460
U.S.A.
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Acknowledgments
The Environmental Protection Agency would like to acknowledge the many individual and organizational con-
tributors to this document, without whose efforts this report would not be complete. Although the complete list
of researchers, government employees, and consultants who have provided technical and editorial support is too long to
list here, EPA's Office of Atmospheric Programs would like to thank some key contributors and reviewers whose work
has significantly improved this year's report.
Work on fuel combustion and industrial process emissions was led by Leif Hockstad and Jonathan Lubetsky. Work
on methane emissions from the energy sector was directed by Lisa Hanle. Calculations for the waste sector were led by
Melissa Weitz. Work on agriculture sector emissions was directed by Tom Wirth and Kathryn Bickel. Tom Wirth led the
preparation of the chapter on Land Use, Land-Use Change, and Forestry. Work on emissions of HFCs, PFCs, and SF6
was directed by Deborah Ottinger and Dave Godwin. John Davies directed the work on mobile combustion.
Within the EPA, other Offices also contributed data, analysis and technical review for this report. The Office of
Transportation and Air Quality and the Office of Air Quality Planning and Standards provided analysis and review for
several of the source categories addressed in this report. The Office of Solid Waste and the Office of Research and Devel-
opment 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 High-
way Administration, the Department of Transportation, the Bureau of Transportation Statistics, the Department of Com-
merce, the National Agricultural Statistics Service, the Federal Aviation Administration, and the Department of Defense.
We would also like to thank Marian Martin Van Pelt, Randall Freed, and their staff at ICF Consulting's Energy
Policy and Programs Practice, including John Venezia, Don Robinson, Diana Pape, Susan Asam, Michael Grant, Ravi
Kantamaneni, Robert Lanza, Chris Steuer, Lauren Flinn, Kamala Jayaraman, Dan Lieberman, Jeremy Scharfenberg,
Daniel Karney, Zephyr Taylor, Beth Moore, Mollie Averyt, Sarah Shapiro, Carol Wingfield, Brian Gillis, Zachary Schaf-
fer, Vineet Aggarwal, Colin McGroarty, Hemant Mallya, Lauren Pederson, Erin Fraser, Joseph Herr, Victoria Thompson,
and Toby Mandel for synthesizing this report and preparing many of the individual analyses. Eastern Research Group,
RTI International, Raven Ridge Resources, and Arcadis also provided significant analytical support.
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The United States Environmental Protection Agency (EPA) prepares the official U.S. Inventory of Greenhouse Gas
Emissions and Sinks to comply with existing commitments under the United Nations Framework Convention on
Climate Change (UNFCCC).1 Under decision 3/CP.5 of the UNFCCC Conference of the Parties, national inventories for
UNFCCC Annex I parties should be provided to the UNFCCC Secretariat each year by April 15.
In an effort to engage the public and researchers across the country, the EPA has instituted an annual public review
and comment process for this document. The availability of the draft document is announced via Federal Register Notice
and is posted on the EPA web site.2 Copies are also mailed upon request. The public comment period is generally limited
to 30 days; however, comments received after the closure of the public comment period are accepted and considered for
the next edition of this annual report.
1 See Article 4{l)(a) of the United Nations Framework Convention on Climate Change .
2 See .
Mi
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Table of Contents
Acknowledgments i
Table of Contents v
List of Tables, Figures, and Boxes viii
Tables viii
Figures xvii
Boxes xix
Executive Summary ES-1
ES.l. Background Information ES-2
ES.2. Recent Trends in U.S. Greenhouse Gas Emissions and Sinks ES-3
ES.3. Overview of Sector Emissions and Trends ES-10
ES.4. Other Information ES-13
1. Introduction 1-1
1.1. Background Information 1-2
1.2. Institutional Arrangements 1-7
1.3. Inventory Process 1-7
1.4. Methodology and Data Sources 1-10
1.5. Key Categories 1-10
1.6. Quality Assurance and Quality Control (QA/QC) 1-11
1.7. Uncertainty Analysis of Emission Estimates 1-13
1.8. Completeness 1-14
1.9. Organization of Report 1-14
2. Trends in Greenhouse Gas Emissions 2-1
2.1. Recent Trends in U.S. Greenhouse Gas Emissions 2-1
2.2. Emissions by Economic Sector 2-22
2.3. Indirect Greenhouse Gas Emissions (CO, NOX, NMVOCs, and SO2) 2-26
3. Energy 3-1
3.1. Carbon Dioxide Emissions from Fossil Fuel Combustion (IPCC Source Category 1A) 3-3
3.2. Carbon Emitted from Non-Energy Uses of Fossil Fuels (IPCC Source Category 1A) 3-20
3.3. Stationary Combustion (excluding C02) (IPCC Source Category 1 A) 3-25
3.4. Mobile Combustion (excluding C02) (IPCC Source Category 1A) 3-30
3.5. Coal Mining (IPCC Source Category IBla) 3-39
3.6. Abandoned Underground Coal Mines (IPCC Source Category IBla) 3-41
3.7. Petroleum Systems (IPCC Source Category lB2a) 3-45
3.8. Natural Gas Systems (IPCC Source Category lB2b) 3-49
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3.9. Municipal Solid Waste Combustion (IPCC Source Category 1A5) 3-52
3.10. Natural Gas Flaring and Indirect Greenhouse Gas Emissions from Oil and
Gas Activities (IPCC Source Category 1B2) 3-56
3.11. International Bunker Fuels (IPCC Source Category 1: Memo Items) 3-58
3.12. Wood Biomass and Ethanol Consumption (IPCC Source Category 1A) 3-63
4. Industrial Processes 4-1
4.1. Iron and Steel Production (IPCC Source Category 2C1) 4-4
4.2. Cement Manufacture (IPCC Source Category 2A1) 4-8
4.3. Ammonia Manufacture and Urea Application (IPCC Source Category 2B1) 4-10
4.4. Lime Manufacture (IPCC Source Category 2A2) 4-14
4.5. Limestone and Dolomite Use (IPCC Source Category 2A3) 4-17
4.6. Soda Ash Manufacture and Consumption (IPCC Source Category 2A4) 4-20
4.7. Titanium Dioxide Production (IPCC Source Category 2B5) 4-22
4.8. Phosphoric Acid Production (IPCC Source Category 2A7) 4-23
4.9. Ferroalloy Production (IPCC Source Category 2C2) 4-27
4.10. Carbon Dioxide Consumption (IPCC Source Category 2B5) 4-29
4.11. Zinc Production 4-32
4.12. Lead Production 4-35
4.13. Petrochemical Production (IPCC Source Category 2B5) 4-36
4.14. Silicon Carbide Production (IPCC Source Category 2B4) and Consumption 4-39
4.15. Nitric Acid Production (IPCC Source Category 2B2) 4-41
4.16. Adipic Acid Production (IPCC Source Category 2B3) 4-42
4.17. Substitution of Ozone Depleting Substances (IPCC Source Category 2F) 4-45
4.18. HCFC-22 Production (IPCC Source Category 2E1) 4-48
4.19. Electrical Transmission and Distribution (IPCC Source Category 2F7) 4-49
4.20. Semiconductor Manufacture (IPCC Source Category 2F6) 4-52
4.21. Aluminum Production (IPCC Source Category 2C3) 4-56
4.22. Magnesium Production and Processing (IPCC Source Category 2C4) 4-60
4.23. Industrial Sources of Indirect Greenhouse Gases 4-64
5. Solvent and Other Product Use 5-1
5.1. Nitrous Oxide Product Usage (IPCC Source Category 3D) 5-1
5.2. Indirect Greenhouse Gas Emissions from Solvent Use 5-4
6. Agriculture 6-1
6.1. Enteric Fermentation (IPCC Source Category 4A) 6-1
6.2. Manure Management (IPCC Source Category 4B) 6-6
6.3. Rice Cultivation (IPCC Source Category 4C) 6-13
6.4. Agricultural Soil Management (IPCC Source Category 4D) 6-18
6.5. Field Burning of Agricultural Residues (IPCC Source Category 4F) 6-27
vi
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7. Land Use, Land-Use Change, and Forestry 7-1
7.1. Forest Land Remaining Forest Land 7-2
7.2. Land Converted to Forest Land (IPCC Source Category 5A2) 7-14
7.3. Cropland Remaining Cropland (IPCC Source Category 5B1) 7-14
7.4. Land Converted to Cropland (IPCC Source Category 5B2) 7-27
7.5. Grassland Remaining Grassland (IPCC Source Category 5C1) 7-31
7.6. Land Converted to Grassland (IPCC Source Category 5C2) 7-37
7.7. Settlements Remaining Settlements 7-41
7.8. Land Converted to Settlements (Source Category 5E2) 7-51
8. Waste 8-1
8.1. Landfills (IPCC Source Category 6A1) 8-1
8.2. Wastewater Treatment (IPCC Source Category 6B) 8-6
8.3. Human Sewage (Domestic Wastewater) (IPCC Source Category 6B) 8-10
8.4. Waste Sources of Indirect Greenhouse Gases 8-13
9. Other 9-1
10. Recalculations and Improvements 10-1
11. References 11-1
List of Annexes (Annexes available on CD version only)
ANNEX. 1 Key Category Analysis
ANNEX 2. Methodology and Data for Estimating C02 Emissions from Fossil Fuel Combustion
2.1. Methodology for Estimating Emissions of C02 from Fossil Fuel Combustion
2.2. Methodology for Estimating the Carbon Content of Fossil Fuels
2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil Fuels
ANNEX 3. Methodological Descriptions for Additional Source or Sink Categories
3.1. Methodology for Estimating Emissions of CH4, N20, and Indirect Greenhouse Gases from
Stationary Combustion
3.2. Methodology for Estimating Emissions of CH4, N20, and Indirect Greenhouse Gases from
Mobile Combustion and Methodology for and Supplemental Information on Transportation-Related
GHG Emissions
3.3. Methodology for Estimating CH4 Emissions from Coal Mining
3.4. Methodology for Estimating CH4 Emissions from Natural Gas Systems
3.5. Methodology for Estimating CH4 Emissions from Petroleum Systems
3.6. Methodology for Estimating C02 and N20 Emissions from Municipal Solid Waste Combustion
3.7. Methodology for Estimating Emissions from International Bunker Fuels used by the U.S. Military
3.8. Methodology for Estimating HFC and PFC Emissions from Substitution of
Ozone Depleting Substances
3.9. Methodology for Estimating CH4 Emissions from Enteric Fermentation
vii
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3.10. Methodology for Estimating CH4 and N20 Emissions from Manure Management
3.11. Methodology for Estimating N20 Emissions from Agricultural Soil Management
3.12. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands
3.13. Methodology for Estimating Net Changes in Carbon Stocks in Mineral and Organic Soils
3.14. Methodology for Estimating CH4 Emissions from Landfills
ANNEX 4. IPCC Reference Approach for Estimating C02 Emissions from Fossil Fuel Combustion
ANNEX 5. Assessment of the Sources and Sinks of Greenhouse Gas Emissions Excluded
ANNEX 6. Additional Information
6.1. Global Warming Potential Values
6.2. Ozone Depleting Substance Emissions
6.3. Sulfur Dioxide Emissions
6.4. Complete List of Source Categories
6.5. Constants, Units, and Conversions
6.6. Abbreviations
6.7. Chemical Formulas
ANNEX 7. Uncertainty
7.1. Overview
7.2. Methodology and Results
7.3. Planned Improvements
List of Tables, Figures, and Boxes
Tables
Table ES-1: Global Warming Potentials (100-Year Time Horizon) Used in this Report ES-3
Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.) ES-5
Table ES-3: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.) ES-8
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by
Chapter/IPCC Sector (Tg C02 Eq.) ES-11
Table ES-5: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) ES-13
Table ES-6: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq.) ES-14
Table ES-7: U.S Greenhouse Gas Emissions by Economic Sector with Electricity-Related
Emissions Distributed (Tg C02 Eq.) ES-15
Table ES-8: Recent Trends in Various U.S. Data (Index 1990 = 100) and
Global Atmospheric C02 Concentration ES-16
Table ES-9: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) ES-17
Table 1-1: Global Atmospheric Concentration (ppm unless otherwise specified), Rate of Concentration
Change (ppb/year), and Atmospheric Lifetime (years) of Selected Greenhouse Gases 1-3
Table 1-2: Global Warming Potentials and Atmospheric Lifetimes (Years) Used in this Report 1-7
Table 1-3: Comparison of 100-Year GWPs 1-8
Table 1-4: Key Categories for the United States (1990-2004) Based on Tier 1 Approach 1-12
Table 1-5: Estimated Overall Inventory Quantitative Uncertainty (Tg CO2 Eq. and Percent) 1-15
Table 1-6: IPCC Sector Descriptions 1-15
viii
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Table 1-7: List of Annexes 1-16
Table 2-1: Annual Change in CO2 Emissions from Fossil Fuel Combustion for
Selected Fuels and Sectors (Tg C02 Eq. and Percent) 2-2
Table 2-2: Recent Trends in Various U.S. Data (Index 1990 = 100) and Global
Atmospheric C02 Concentration 2-4
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.) 2-6
Table 2-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg) 2-7
Table 2-5: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by
Chapter/IPCC Sector (Tg C02 Eq.) 2-8
Table 2-6: Emissions from Energy (Tg CO2 Eq.) 2-9
Table 2-7: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.) 2-10
Table 2-8: Emissions from Industrial Processes (Tg CO2 Eq.) 2-14
Table 2-9: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq.) 2-17
Table 2-10: Emissions from Agriculture (Tg CO2 Eq.) 2-18
Table 2-11: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) 2-20
Table 2-12: N20 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) 2-20
Table 2-13: Emissions from Waste (Tg CO2 Eq.) 2-21
Table 2-14: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq. and
Percent of Total in 2004) 2-22
Table 2-15: Electricity Generation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-24
Table 2-16: U.S Greenhouse Gas Emissions by "Economic Sector" and Gas with
Electricity-Related Emissions Distributed (Tg CO2 Eq.) and Percent of Total in 2004 2-25
Table 2-17: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.) 2-28
Table 2-18: Emissions of NOX, CO, NMVOCs, and SO2 (Gg) 2-29
Table 3-1: CO2, CH4, and N20 Emissions from Energy (Tg C02 Eq.) 3-2
Table 3-2: CO2, CH4, and N20 Emissions from Energy (Gg) 3-2
Table 3-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg C02 Eq.) 3-4
Table 3-4: Annual Change in CO2 Emissions from Fossil Fuel Combustion for
Selected Fuels and Sectors (Tg C02 Eq. and Percent) 3-5
Table 3-5: CO2 Emissions from International Bunker Fuels (Tg C02 Eq.) 3-7
Table 3-6: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.) 3-7
Table 3-7: CO2 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector
(Tg C02 Eq.) 3-9
Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO2 Eq./QBtu) 3-13
Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg CO2 Eq./QBtu) 3-14
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Energy-related
Fossil Fuel Combustion by Fuel Type and Sector (Tg C02 Eq. and Percent) 3-18
Table 3-11: CO2 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO2 Eq.) 3-21
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu) 3-21
Table 3-13: 2004 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions 3-22
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Table 3-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Non-Energy Uses of Fossil Fuels (Tg CO2 Eq. and Percent) 3-23
Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of
Non-Energy Uses of Fossil Fuels (Percent) 3-23
Table 3-16: CH4 Emissions from Stationary Combustion (Tg C02 Eq.) 3-26
Table 3-17: N20 Emissions from Stationary Combustion (Tg C02 Eq.) 3-26
Table 3-18: CH4 Emissions from Stationary Combustion (Gg) 3-27
Table 3-19: N20 Emissions from Stationary Combustion (Gg) 3-27
Table 3-20: NOX, CO, and NMVOC Emissions from Stationary Combustion in 2004 (Gg) 3-28
Table 3-21: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from
Energy-Related Stationary Combustion, Including Biomass (Tg CO2 Eq. and Percent) 3-29
Table 3-22: CH4 Emissions from Mobile Combustion (Tg C02 Eq.) 3-31
Table 3-23: N20 Emissions from Mobile Combustion (Tg C02 Eq.) 3-31
Table 3-24: CH4 Emissions from Mobile Combustion (Gg) 3-32
Table 3-25: N20 Emissions from Mobile Combustion (Gg) 3-32
Table 3-26: NOX, CO, and NMVOC Emissions from Mobile Combustion in 2004 (Gg) 3-33
Table 3-27: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from
Mobile Sources (Tg C02 Eq. and Percent) 3-37
Table 3-28: CH4 Emissions from Coal Mining (Tg C02 Eq.) 3-39
Table 3-29: CH4 Emissions from Coal Mining (Gg) 3-39
Table 3-30: Coal Production (Thousand Metric Tons) 3-40
Table 3-31: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Coal Mining (Tg C02 Eq. and Percent) 3-41
Table 3-32: CH4 Emissions from Abandoned Coal Mines (Tg C02 Eq.) 3-42
Table 3-33: CH4 Emissions from Abandoned Coal Mines (Gg) 3-42
Table 3-34: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Abandoned Underground Coal Mines (Tg C02 Eq. and Percent) 3-45
Table 3-35: CH4 Emissions from Petroleum Systems (Tg C02 Eq.) 3-46
Table 3-36: CH4 Emissions from Petroleum Systems (Gg) 3-46
Table 3-37: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Petroleum Systems (Tg C02 Eq. and Percent) 3-48
Table 3-38: CH4 Emissions from Natural Gas Systems (Tg CO2 Eq.) 3-49
Table 3-39: CH4 Emissions from Natural Gas Systems (Gg) 3-49
Table 3-40: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from
Natural Gas Systems (Tg CO2 Eq. and Percent) 3-51
Table 3-41: CO2 and N20 Emissions from Municipal Solid Waste Combustion (Tg C02 Eq.) 3-52
Table 3-42: CO2 and N20 Emissions from Municipal Solid Waste Combustion (Gg) 3-52
Table 3-43: NOX, CO, and NMVOC Emissions from Municipal Solid Waste Combustion (Gg) 3-53
Table 3-44: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted 3-53
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Table 3-45: Tier 2 Quantitative Uncertainty Estimates for CO2 and N20 from
Municipal Solid Waste Combustion (Tg C02 Eq. and Percent) 3-54
Table 3-46: U.S. Municipal Solid Waste Combusted, as Reported by EPA and BioCycle (Metric Tons) 3-55
Table 3-47: CO2 Emissions from On-Shore and Off-Shore Natural Gas Flaring (Tg CO2 Eq.) 3-56
Table 3-48: CO2 Emissions from On-Shore and Off-Shore Natural Gas Flaring (Gg) 3-56
Table 3-49: NOX, NMVOCs, and CO Emissions from Oil and Gas Activities (Gg) 3-57
Table 3-50: Total Natural Gas Reported Vented and Flared (Million Ft3) and
Thermal Conversion Factor (Btu/Ft3) 3-57
Table 3-51: Volume Flared Offshore (MMcf) and Fraction Vented and Flared (Percent) 3-58
Table 3-52: CO2, CH4, and N20 Emissions from International Bunker Fuels (Tg C02 Eq.) 3-59
Table 3-53: CO2, CH4, N20, and Indirect Greenhouse Gas Emissions from
International Bunker Fuels (Gg) 3-60
Table 3-54: Aviation Jet Fuel Consumption for International Transport (Million Gallons) 3-60
Table 3-55: Marine Fuel Consumption for International Transport (Million Gallons) 3-61
Table 3-56: CO2 Emissions from Wood Consumption by End-Use Sector (Tg C02 Eq.) 3-63
Table 3-57: CO2 Emissions from Wood Consumption by End-Use Sector (Gg) 3-64
Table 3-58: CO2 Emissions from Ethanol Consumption (Tg C02 Eq. and Gg) 3-64
Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu) 3-64
Table 3-60: Ethanol Consumption (Trillion Btu) 3-64
Table 3-61: CH4 Emissions from Non-Combustion Fossil Sources (Gg) 3-65
Table 3-62: Formation of CO2 through Atmospheric CH4 Oxidation (Tg C02 Eq.) 3-66
Table 4-1: Emissions from Industrial Processes (Tg CO2 Eq.) 4-2
Table 4-2: Emissions from Industrial Processes (Gg) 4-3
Table 4-3: CO2 and CH4 Emissions from Iron and Steel Production (Tg C02 Eq.) 4-5
Table 4-4: CO2 and CH4 Emissions from Iron and Steel Production (Gg) 4-5
Table 4-5: CH4 Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg) 4-6
Table 4-6: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions
from Iron and Steel Production (Thousand Metric Tons) 4-6
Table 4-7: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from
Iron and Steel Production (Tg. C02 Eq. and Percent) 4-7
Table 4-8: CO2 Emissions from Cement Production (Tg C02 Eq. and Gg) 4-8
Table 4-9: Cement Production (Gg) 4-9
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Cement Manufacture (Tg C02 Eq. and Percent) 4-10
Table 4-11: CO2 Emissions from Ammonia Manufacture and Urea Application (Tg C02 Eq.) 4-11
Table 4-12: CO2 Emissions from Ammonia Manufacture and Urea Application (Gg) 4-11
Table 4-13: Ammonia Production, Urea Production, and Urea Net Imports (Gg) 4-12
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Ammonia Manufacture and Urea Application (Tg C02 Eq. and Percent) 4-13
Table 4-15: Net CO2 Emissions from Lime Manufacture (Tg C02 Eq.) 4-14
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Table 4-16: CO2 Emissions from Lime Manufacture (Gg) 4-15
Table 4-17: Lime Production and Lime Use for Sugar Refining and PCC (Gg) 4-15
Table 4-18: Hydrated Lime Production (Gg) 4-16
Table 4-19: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lime Manufacture
(Tg C02 Eq. and Percent) 4-17
Table 4-20: CO2 Emissions from Limestone & Dolomite Use (Tg C02 Eq.) 4-17
Table 4-21: CO2 Emissions from Limestone & Dolomite Use (Gg) 4-18
Table 4-22: Limestone and Dolomite Consumption (Thousand Metric Tons) 4-18
Table 4-23: Dolomitic Magnesium Metal Production Capacity (Metric Tons) 4-19
Table 4-24: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Limestone and
Dolomite Use (Tg C02 Eq. and Percent) 4-20
Table 4-25: CO2 Emissions from Soda Ash Manufacture and Consumption (Tg C02 Eq.) 4-20
Table 4-26: CO2 Emissions from Soda Ash Manufacture and Consumption (Gg) 4-20
Table 4-27: Soda Ash Manufacture and Consumption (Gg) 4-21
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Soda Ash Manufacture and
Consumption (Tg C02 Eq. and Percent) 4-21
Table 4-29: CO2 Emissions from Titanium Dioxide (Tg C02 Eq. and Gg) 4-22
Table 4-30: Titanium Dioxide Production (Gg) 4-23
Table 4-31: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Titanium Dioxide Production (Tg C02 Eq. and Percent) 4-23
Table 4-32: CO2 Emissions from Phosphoric Acid Production (Tg C02 Eq. and Gg) 4-24
Table 4-33: Phosphate Rock Domestic Production, Exports, and Imports (Gg) 4-25
Table 4-34: Chemical Composition of Phosphate Rock (percent by weight) 4-25
Table 4-35: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from
Phosphoric Acid Production (Tg C02 Eq. and Percent) 4-26
Table 4-36: CO2 Emissions from Ferroalloy Production (Tg C02 Eq. and Gg) 4-27
Table 4-37: Production of Ferroalloys (Metric Tons) 4-28
Table 4-38: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ferroalloy Production
(Tg C02 Eq. and Percent) 4-28
Table 4-39: CO2 Emissions from C02 Consumption (Tg C02 Eq. and Gg) 4-30
Table 4-40: CO2 Consumption (Metric Tons) 4-31
Table 4-41: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from C02 Consumption
(Tg C02 Eq. and Percent) 4-31
Table 4-42: CO2 Emissions from Zinc Production (Tg C02 Eq. and Gg) 4-32
Table 4-43: Zinc Production (Metric Tons) 4-34
Table 4-44: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Zinc Production
(Tg C02 Eq. and Percent) 4-34
Table 4-45: CO2 Emissions from Lead Production (Tg C02 Eq. and Gg) 4-35
Table 4-46: Lead Production (Metric Tons) 4-35
xii
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Table 4-47: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lead Production
(Tg C02 Eq. and Percent) 4-36
Table 4-48: CO2 and CH4 Emissions from Petrochemical Production (Tg C02 Eq.) 4-37
Table 4-49: CO2 and CH4 Emissions from Petrochemical Production (Gg) 4-37
Table 4-50: Production of Selected Petrochemicals (Thousand Metric Tons) 4-37
Table 4-51: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock
(Secondary Feedstock) Consumption (Thousand Metric Tons) 4-38
Table 4-52: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical
Production and C02 Emissions from Carbon Black Production (Tg C02 Eq. and Percent) 4-39
Table 4-53: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg C02 Eq.) 4-39
Table 4-54: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg) 4-39
Table 4-55: Production and Consumption of Silicon Carbide (Metric Tons) 4-40
Table 4-56: Tier 2 Quantitative Uncertainty Estimates for CH4 and C02 Emissions from
Silicon Carbide Production and Consumption (Tg C02 Eq. and Percent) 4-40
Table 4-57: N2O Emissions from Nitric Acid Production (Tg CO2 Eq. and Gg) 4-41
Table 4-58: Nitric Acid Production (Gg) 4-41
Table 4-59: Sources of Uncertainty in N2O Emissions from Nitric Acid Production 4-42
Table 4-60: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions From Nitric Acid Production
(Tg C02 Eq. and Percent) 4-42
Table 4-61: N20 Emissions from Adipic Acid Production (Tg C02 Eq. and Gg) 4-43
Table 4-62: Adipic Acid Production (Gg) 4-44
Table 4-63: Sources of Uncertainty in N20 Emissions from Adipic Acid Production 4-45
Table 4-64: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Adipic Acid Production
(Tg C02 Eq. and Percent) 4-45
Table 4-65: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) 4-46
Table 4-66: Emissions of HFCs and PFCs from ODS Substitution (Mg) 4-46
Table 4-67: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes
(Tg C02 Eq. and Percent) 4-47
Table 4-68: HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and Gg) 4-48
Table 4-69: HCFC-22 Production (Gg) 4-48
Table 4-70: Tier 1 Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production
(Tg C02 Eq. and Percent) 4-49
Table 4-71: SF6 Emissions from Electric Power Systems and Original Equipment Manufactures
(Tg C02 Eq.) 4-49
Table 4-72: SF6 Emissions from Electric Power Systems and Original Equipment Manufactures (Gg) 4-50
Table 4-73: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg C02 Eq. and Percent) 4-52
Table 4-74: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg C02 Eq.) 4-53
Table 4-75: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg) 4-53
xiii
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Table 4-76: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from
Semiconductor Manufacture (Tg C02 Eq. and Percent) 4-55
Table 4-77: CO2 Emissions from Aluminum Production (Tg C02 Eq. and Gg) 4-56
Table 4-78: PFC Emissions from Aluminum Production (Tg CO2 Eq.) 4-57
Table 4-79: PFC Emissions from Aluminum Production (Gg) 4-57
Table 4-80: Production of Primary Aluminum (Gg) 4-58
Table 4-81: Tier 2 Quantitative Uncertainty Estimates for CO2 and PFC Emissions from
Aluminum Production (Tg C02 Eq. and Percent) 4-60
Table 4-82: SF6 Emissions from Magnesium Production and Processing (Tg C02 Eq. and Gg) 4-60
Table 4-83: SF6 Emission Factors (kg SF6 per metric ton of magnesium) 4-61
Table 4-84: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and
Processing (Tg C02 Eq. and Percent) 4-62
Table 4-85: 2004 Potential and Actual Emissions of HFCs, PFCs, and SF6 from Selected Sources
(Tg C02 Eq.) 4-63
Table 4-86: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg) 4-64
Table 5-1: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq. and Gg) 5-1
Table 5-2: Indirect Greenhouse Gas Emissions from Solvent and Other Product Use (Gg) 5-1
Table 5-3: N20 Emissions from N20 Product Usage (Tg C02 Eq. and Gg) 5-2
Table 5-4: N20 Production (Gg) 5-3
Table 5-5: Sources of Uncertainty in N2O Emissions from N20 Product Usage 5-3
Table 5-6: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions From N20 Product Usage
(Tg C02 Eq. and Percent) 5-4
Table 5-7: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg) 5-5
Table 6-1: Emissions from Agriculture (Tg CO2 Eq.) 6-2
Table 6-2: Emissions from Agriculture (Gg) 6-2
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg C02 Eq.) 6-3
Table 6-4: CH4 Emissions from Enteric Fermentation (Gg) 6-3
Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation
(Tg C02 Eq. and Percent) 6-5
Table 6-6: CH4 and N20 Emissions from Manure Management (Tg C02Eq.) 6-7
Table 6-7: CH4 and N20 Emissions from Manure Management (Gg) 6-8
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Manure Management
(Tg C02 Eq. and Percent) 6-10
Table 6-9: CH4 Emissions from Puce Cultivation (Tg CO2 Eq.) 6-14
Table 6-10: CH4 Emissions from Puce Cultivation (Gg) 6-14
Table 6-11: Rice Areas Harvested (Hectares) 6-16
Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Puce Cultivation
(Tg C02 Eq. and Percent) 6-17
Table 6-13: N20 Emissions from Agricultural Soils (Tg C02 Eq.) 6-19
Table 6-14: N20 Emissions from Agricultural Soils (Gg) 6-20
xiv
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Table 6-15: Direct N20 Emissions from Agricultural Soils (Tg C02 Eq.) 6-20
Table 6-16: Indirect N20 Emissions from all Land Use Types* (Tg C02 Eq.) 6-20
Table 6-17: Tier 1 Quantitative Uncertainty Estimates of N20 Emissions from Agricultural Soil
Management in 2004 (Tg C02 Eq. and Percent) 6-25
Table 6-18: Changes and Percent Difference in N20 Emission Estimates for Agricultural Soil
Management (Tg C02 Eq. and Percent) 6-26
Table 6-19: CH4 and N2O Emissions from Field Burning of Agricultural Residues (Tg CO2 Eq.) 6-28
Table 6-20: CH4, N2O, CO, and NOX Emissions from Field Burning of Agricultural Residues (Gg) 6-29
Table 6-21: Agricultural Crop Production (Gg of Product) 6-30
Table 6-22: Percentage of Rice Area Burned by State 6-30
Table 6-23: Percentage of Rice Area Burned in California, 1990-1998 6-30
Table 6-24: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues 6-31
Table 6-25: Greenhouse Gas Emission Ratios 6-31
Table 6-26: Tier 2 Uncertainty Estimates for CH4 and N20 Emissions from Field Burning of
Agricultural Residues (Tg CO2 Eq. and Percent) 6-32
Table 7-1: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) 7-2
Table 7-2: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg C) 7-3
Table 7-3: N20 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) 7-3
Table 7-4: N20 Emissions from Land Use, Land-Use Change, and Forestry (Gg) 7-4
Table 7-5: Net Annual Changes in Carbon Stocks (Tg CO2/yr) in Forest and Harvested Wood Pools 7-6
Table 7-6: Net Annual Changes in Carbon Stocks (Tg C/yr) in Forest and Harvested Wood Pools 7-6
Table 7-7: Carbon Stocks (Tg C) in Forest and Harvested Wood Pools 7-7
Table 7-8: Tier 2 Quantitative Uncertainty Estimates for Net CO2 Flux from Forest Land Remaining
Forest land: Changes in Forest Carbon Stocks (Tg CO2 Eq. and Percent) 7-10
Table 7-9: N2O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO2 Eq. and Gg) 7-12
Table 7-10: Tier 1 Quantitative Uncertainty Estimates of N20 Fluxes from Soils in Forest Land
Remaining Forest Land (Tg CO2 Eq. and Percent) 7-13
Table 7-11: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland
(Tg C02 Eq.) 7-15
Table 7-12: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland (Tg C) . . . . 7-15
Table 7-13: Applied Minerals (Million Metric Tons) 7-21
Table 7-14: Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils
Occurring within Cropland Remaining Cropland that were Estimated Using the Tier 3 Approach
(Tg C02 Eq. and Percent) 7-22
Table 7-15: Tier 2 Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring
within Cropland Remaining Cropland that were Estimated Using the Tier 2 Approach
(Tg C02 Eq. and Percent) 7-23
Table 7-16: Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within
Cropland Remaining Cropland that were Estimated Using the Tier 1 Approach
(Tg C02 Eq. and Percent) 7-24
Table 7-17: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Organic Soils Occurring
within Cropland Remaining Cropland (Tg CO2 Eq. and Percent) 7-24
XV
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Table 7-18: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Liming of
Agricultural Soils (Tg C02 Eq. and Percent) 7-25
Table 7-19: Net Soil C Stock Changes in Land Converted to Cropland (Tg CO2 Eq.) 7-28
Table 7-20: Net Soil C Stock Changes in Land Converted to Cropland (Tg C) 7-28
Table 7-21: Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within
Land Converted to Cropland, which were Estimated Using the Tier 3 Approach
(Tg C02 Eq. and Percent) 7-31
Table 7-22: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg CO2 Eq.) 7-32
Table 7-23: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C) 7-32
Table 7-24: Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within
Grassland Remaining Grassland, which were Estimated Using the Tier 3 Approach
(Tg C02 Eq. and Percent) 7-36
Table 7-25: Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within
Grassland Remaining Grassland, which were Estimated Using the Tier 2 Approach
(Tg C02 Eq. and Percent) 7-36
Table 7-26: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Organic Soils Occurring
within Grassland Remaining Grassland (Tg CO2 Eq. and Percent) 7-37
Table 7-27: Net Soil C Stock Changes for Land Converted to Grassland (Tg CO2 Eq.) 7-38
Table 7-28: Net Soil C Stock Changes for Land Converted to Grassland (Tg C) 7-38
Table 7-29: Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within
Land Converted to Grassland, which were Estimated Using the Tier 3 Approach
(Tg C02 Eq. and Percent) 7-41
Table 7-30: Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within
Land Converted to Grassland that were Estimated Using the Tier 2 Inventory Approach
(Tg C02 Eq. and Percent) 7-41
Table 7-31: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO2 Eq.) 7-42
Table 7-32: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C) 7-42
Table 7-33: Moisture Content (%), Carbon Storage Factor, Initial Carbon Content (%), Proportion of
Initial Carbon Sequestered (%), and Half-Life (years) for Landfilled Yard Trimmings and
Food Scraps in Landfills 7-43
Table 7-34: Carbon Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C) 7-44
Table 7-35: Tier 2 Quantitative Uncertainty Estimates for CO2 Flux from Yard Trimmings and
Food Scraps in Landfills (Tg CO2 Eq. and Percent) 7-45
Table 7-36: Net C Flux from Urban Trees (Tg CO2 Eq. and Tg C) 7-46
Table 7-37: Carbon Stocks (Metric Tons C), Annual Carbon Sequestration (Metric Tons C/yr),
Tree Cover (Percent), and Annual Carbon Sequestration per Area of Tree Cover (kg C/m2 cover-yr)
for Ten U.S. Cities 7-48
Table 7-38: Tier 1 Quantitative Uncertainty Estimates for Net C Flux from Changes in Carbon Stocks
in Urban Trees (Tg C02 Eq. and Percent) 7-49
Table 7-39: N2O Fluxes from Soils in Settlements Remaining Settlements (Tg CO2 Eq. and Gg) 7-49
Table 7-40: Tier 1 Quantitative Uncertainty Estimates of N20 Emissions from Soils in
Settlements Remaining Settlements (Tg CO2 Eq. and Percent) 7-50
xvi
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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 CO2 Eq.) 8-3
Table 8-4: CH4 Emissions from Landfills (Gg) 8-3
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills
(Tg C02 Eq. and Percent) 8-5
Table 8-6: CH4 Emissions from Domestic and Industrial Wastewater Treatment (Tg C02 Eq.) 8-7
Table 8-7: CH4 Emissions from Domestic and Industrial Wastewater Treatment (Gg) 8-7
Table 8-8: U.S. Population (Millions) and Domestic Wastewater BOD5 Produced (Gg) 8-7
Table 8-9: U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg) 8-8
Table 8-10: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Wastewater Treatment
(Tg C02 Eq. and Percent) 8-9
Table 8-11: N20 Emissions from Human Sewage (Tg C02 Eq. and Gg) 8-10
Table 8-12: U.S. Population (Millions) and Average Protein Intake [kg/(person-year)] 8-11
Table 8-13: Sources of Uncertainty in N20 Emissions from Human Sewage 8-12
Table 8-14: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Human Sewage
(Tg C02 Eq. and Percent) 8-12
Table 8-15: Emissions of NOX, CO, and NMVOC from Waste (Gg) 8-13
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO2 Eq.) 10-2
Table 10-2: Revisions to Net Flux of CO2 to the Atmosphere from Land Use, Land-Use Change,
and Forestry (Tg C02 Eq.) 10-3
Figures
Figure ES-1: U.S. Greenhouse Gas Emissions by Gas ES-4
Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions ES-4
Figure ES-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990 ES-4
Figure ES-4: 2004 Greenhouse Gas Emissions by Gas ES-4
Figure ES-5: 2004 Sources of CO2 ES-6
Figure ES-6: 2004 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type ES-7
Figure ES-7: 2004 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion ES-7
Figure ES-8: 2004 U.S. Sources of CH4 ES-9
Figure ES-9: 2004 U.S. Sources of N20 ES-9
Figure ES-10: 2004 U.S. Sources of HFCs, PFCs, and SF6 ES-10
Figure ES-11: U.S. Greenhouse Gas Emissions by Chapter/IPCC Sector ES-10
Figure ES-12: 2004 U.S. Energy Consumption by Energy Source ES-11
Figure ES-13: Emissions Allocated to Economic Sectors ES-14
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors ES-15
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product ES-16
Figure ES-16: 2004 Key Categories—Tier 1 Level Assessment ES-18
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas 2-1
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions 2-2
Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990 2-2
Figure 2-4: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product 2-4
xvii
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Figure 2-5: U.S. Greenhouse Gas Emissions by Chapter/IPCC Sector 2-8
Figure 2-6: 2004 Energy Sector Greenhouse Gas Sources 2-8
Figure 2-7: 2004 U.S. Fossil Carbon Hows (Tg CO2 Eq.) 2-9
Figure 2-8: 2004 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 2-10
Figure 2-9: 2004 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion 2-10
Figure 2-10: 2004 Industrial Processes Chapter Greenhouse Gas Sources 2-13
Figure 2-11: 2004 Agriculture Chapter Greenhouse Gas Sources 2-18
Figure 2-12: 2004 Waste Chapter Greenhouse Gas Sources 2-21
Figure 2-13: Emissions Allocated to Economic Sectors 2-24
Figure 2-14: Emissions with Electricity Distributed to Economic Sectors 2-26
Figure 3-1: 2004 Energy Chapter Greenhouse Gas Sources 3-1
Figure 3-2: 2004 U.S. Fossil Carbon Flows (Tg CO2 Eq.) 3-3
Figure 3-3: 2004 U.S. Energy Consumption by Energy Source 3-5
Figure 3-4: U.S. Energy Consumption (Quadrillion Btu) 3-5
Figure 3-5: 2004 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 3-5
Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950-2004) 3-6
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2004) 3-6
Figure 3-8: Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the United States
(1974-2004) 3-6
Figure 3-9: 2004 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion 3-8
Figure 3-10: Motor Gasoline Retail Prices (Real) 3-8
Figure 3-11: Personal Vehicle Fuel Economy 3-10
Figure 3-12: Industrial Production Indexes (Index 1997=100) 3-10
Figure 3-13: Heating Degree Days 3-11
Figure 3-14: Cooling Degree Days 3-11
Figure 3-15: Electricity Generation Retail Sales by End-Use Sector 3-12
Figure 3-16: U.S. Energy Consumption and Energy-Related CO2 Emissions Per Capita and
Per Dollar GDP 3-14
Figure 3-17: Mobile Source CH4 and N20 Emissions 3-33
Figure 4-1: 2004 Industrial Processes Chapter Greenhouse Gas Sources 4-1
Figure 6-1: 2004 Agriculture Chapter Greenhouse Gas Emission Sources 6-1
Figure 6-2: Direct and Indirect N20 Emissions from Agricultural Soils 6-19
Figure 7-1: Forest Sector Carbon Pools and Hows 7-5
Figure 7-2: Estimates of Net Annual Changes in Carbon Stocks for Major Carbon Pools 7-7
Figure 7-3: Average Carbon Density in the Forest Tree Pool in the Conterminous U.S.
During 2005 7-8
Figure 7-4: Net C Stock Change for Mineral Soils in Cropland Remaining Cropland, 1990-1992 7-16
Figure 7-5: Net C Stock Change for Mineral Soils in Cropland Remaining Cropland, 1993-2004 7-16
Figure 7-6: Net C Stock Change for Organic Soils in Cropland Remaining Cropland, 1990-1992 7-17
Figure 7-7: Net C Stock Change for Organic Soils in Cropland Remaining Cropland, 1993-2004 7-17
Figure 7-8: Net C Stock Change for Mineral Soils in Land Converted to Cropland, 1990-1992 7-29
Figure 7-9: Net C Stock Change for Mineral Soils in Land Converted to Cropland, 1993-2004 7-29
xviii
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Figure 7-10: Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 1990-1992 7-32
Figure 7-11: Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 1993-2004.... 7-33
Figure 7-12: Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 1990-1992. . . . 7-33
Figure 7-13: Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 1993-2004. . . . 7-34
Figure 7-14: Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 1990-1992 7-38
Figure 7-15: Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 1993-2004 7-39
Figure 8-1: 2004 Waste Chapter Greenhouse Gas Sources 8-1
Boxes
Box ES- 1: Recalculations of Inventory Estimates ES-2
Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data ES-16
Box 1-1
Box 1-2
Box 2-1
Box 2-2
Box 2-3
Box 3-1
Box 3-2
Box 3-3
Box 4-1
Box 6-1
Box 8-1
The IPCC Third Assessment Report and Global Warming Potentials 1-8
IPCC Reference Approach 1-11
Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data
2-4
Methodology for Aggregating Emissions by Economic Sector 2-27
Sources and Effects of Sulfur Dioxide
2-30
3-6
Weather and Non-Fossil Energy Effects on CO2 from Fossil Fuel Combustion Trends ...........
Carbon Intensity of U.S. Energy Consumption .......................................... 3-13
Formation of C02 through Atmospheric CH4 Oxidation .................................. 3-65
Potential Emission Estimates of HFCs, PFCs, and SF6 .................................... 4-63
Tier 1 vs. Tier 3 Approach for Estimating N20 Emissions ................................. 6-26
Biogenic Emissions and Sinks of Carbon
8-6
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Executive Summary
Central to any study of climate change is the development of an emissions inventory that identifies and quantifies
a country's primary anthropogenic1 sources and sinks of greenhouse gases. This inventory adheres to both
(1) a comprehensive and detailed methodology 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
2004. To ensure that the U.S. emissions inventory is comparable to those of other UNFCCC Parties, the estimates presented
here were calculated using methodologies consistent with those recommended in the Revised 1996 IPCC Guidelines for
National Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997), the IPCC Good Practice Guidance and Uncertainty
Management in National Greenhouse Gas Inventories (IPCC 2000), and the IPCC Good Practice Guidance for Land Use,
Land-Use Change, and Forestry (IPCC 2003). The structure of this report is consistent with the UNFCCC guidelines for
inventory reporting.4 For most source categories, the Intergovernmental Panel on Climate Change (IPCC) methodologies were
expanded, resulting in a more comprehensive and detailed estimate of emissions.
1 The term "anthropogenic," in this context, refers to greenhouse gas emissions and removals that are a direct result of human activities or are the result
of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).
2 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate Change. See .
3 Article 4( 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 .
4 See .
Executive Summary ES-1
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Box ES-1: Recalculations of Inventory Estimates
Each year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S. Greenhouse Gas Emissions and
Sinks, as attempts are made to improve both the analyses themselves, through the use of better methods or data, and the overall usefulness
of this report. In this effort, the United States follows the IPCC Good Practice Guidance (IPCC 2000), which states, regarding recalculations
of the time series, "It is good practice to recalculate historic emissions when methods are changed or refined, when new source categories
are included in the national inventory, or when errors in the estimates are identified and corrected."
In 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 has been recalculated to reflect the
change, per IPCC Good Practice Guidance. Changes in historical data are generally the result of changes in statistical data supplied by
other agencies. References for the data are provided for additional information.
ES.1. Background Information
Naturally occurring greenhouse gases include water
vapor, carbon dioxide (CO2), methane (CH4), nitrous oxide
(N2O), and ozone (O3). Several classes of halogenated
substances that contain fluorine, chlorine, or bromine are also
greenhouse gases, but they are, for the most part, solely a
product of industrial activities. Chlorofluorocarbons (CFCs)
and hydrochlorofluorocarbons (HCFCs) are halocarbons that
contain chlorine, while halocarbons that contain bromine
are referred to as bromofluorocarbons (i.e., halons). As
stratospheric ozone depleting substances, CFCs, HCFCs,
and halons are covered under the Montreal Protocol on
Substances that Deplete the Ozone Layer. The UNFCCC
defers to this earlier international treaty. Consequently,
Parties are not required to include these gases in their national
greenhouse gas emission inventories.5 Some other fluorine-
containing halogenated substances—hydrofluorocarbons
(HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride
(SF6)—do not deplete stratospheric ozone but are potent
greenhouse gases. These latter substances are addressed by
the UNFCCC and accounted for in national greenhouse gas
emission inventories.
There are also several gases that do not have a direct
global warming effect but indirectly affect terrestrial and/or
solar radiation absorption by influencing the formation or
destruction of greenhouse gases, including tropospheric and
stratospheric ozone. These gases include carbon monoxide
(CO), oxides of nitrogen (NOX), and non-CFLj volatile organic
compounds (NMVOCs). Aerosols, which are extremely
small particles or liquid droplets, such as those produced by
sulfur dioxide (SO2) or elemental carbon emissions, can also
affect the absorptive characteristics of the atmosphere.
Although the direct greenhouse gases CO2, CFLj, and
N2O occur naturally in the atmosphere, human activities
have changed their atmospheric concentrations. From
the pre-industrial era (i.e., ending about 1750) to 2004,
concentrations of these greenhouse gases have increased
globally by 35, 143, and 18 percent, respectively (IPCC
2001, Hofmann 2004).
Beginning in the 1950s, the use of CFCs and other
stratospheric ozone depleting substances (ODS) increased
by nearly 10 percent per year until the mid-1980s, when
international concern about ozone depletion led to the
entry into force of the Montreal Protocol. Since then, the
production of ODS is being phased out. In recent years, use
of ODS substitutes such as HFCs and PFCs has grown as
they begin to be phased in as replacements for CFCs and
HCFCs. Accordingly, atmospheric concentrations of these
substitutes have been growing (IPCC 2001).
Global Warming Potentials
Gases in the atmosphere can contribute to the
greenhouse effect both directly and indirectly. Direct
effects occur when 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
5 Emissions estimates of CFCs, HCFCs, halons and other ozone-depleting substances are included in the annexes of this report for informational
purposes.
ES-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
or albedo).6 The IPCC developed the Global Warming
Potential (GWP) concept to compare the ability of each
greenhouse gas to trap heat in the atmosphere relative to
another gas.
The GWP of a greenhouse gas is defined as the ratio of
the time-integrated radiative forcing from the instantaneous
release of 1 kg of a trace substance relative to that of 1 kg of a
reference gas (IPCC 2001). Direct radiative effects occur when
the gas itself is a greenhouse gas. The reference gas used is
CO2, and therefore GWP-weighted emissions are measured in
teragrams of CO2 equivalent (Tg CO2 Eq.).7 All gases in this
Executive Summary are presented in units of Tg CO2 Eq.
The UNFCCC reporting guidelines for national
inventories were updated in 2002,8 but continue to require
the use of GWPs from the IPCC Second Assessment Report
(SAR). This requirement ensures that current estimates of
aggregate greenhouse gas emissions for 1990 to 2004 are
consistent with estimates developed prior to the publication
of the IPCC Third Assessment Report (TAR). Therefore,
to comply with international reporting standards under the
UNFCCC, official emission estimates are reported by the
United States using SAR GWP values. All estimates are
provided throughout this report in both CO2 equivalents and
unweighted units. A comparison of emission values using the
SAR GWPs versus the TAR GWPs can be found in Chapter
1 and, in more detail, in Annex 6.1 of this report. The GWP
values used in this report are listed below in Table ES-1.
Global warming potentials are not provided for CO,
NOX, NMVOCs, SO2, and aerosols because there is no
agreed-upon method to estimate the contribution of gases that
are short-lived in the atmosphere, spatially variable, or have
only indirect effects on radiative forcing (IPCC 1996).
ES.2. Recent Trends in U.S.
Greenhouse Gas Emissions
and Sinks
Table ES-1: Global Warming Potentials (100-Year Time
Horizon) Used in this Report
Gas
C02
CH4*
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C^FIO
C6Fi4
SF6
GWP
1
21
310
11,700
650
2,800
1,300
3,800
140
2,900
6,300
1,300
6,500
9,200
7,000
7,400
23,900
In 2004, total U.S. greenhouse gas emissions were
7,074.4 Tg CO2 Eq. Overall, total U.S. emissions have
risen by 15.8 percent from 1990 to 2004, while the U.S.
Source: IPCC (1996)
* The CH4 GWP includes the direct effects and those indirect effects
due to the production of tropospheric ozone and stratospheric water
vapor. The indirect effect due to the production of C02 is not included.
gross domestic product has increased by 51 percent over
the same period (BEA 2005). Emissions rose from 2003 to
2004, increasing by 1.7 percent (115.3 Tg CO2 Eq.). The
following factors were primary contributors to this increase:
(1) robust economic growth in 2004, leading to increased
demand for electricity and fossil fuels, (2) expanding
industrial production in energy-intensive industries, also
increasing demand for electricity and fossil fuels, and (3)
increased travel, leading to higher rates of consumption of
petroleum fuels.
Figure ES-1 through Figure ES-3 illustrate the overall
trends in total U.S. emissions by gas, annual changes, and
cumulative change since 1990. Table ES-2 provides a
detailed summary of U.S. greenhouse gas emissions and
sinks for 1990 through 2004.
Figure ES-4 illustrates the relative contribution of the
direct greenhouse gases to total U.S. emissions in 2004.
The primary greenhouse gas emitted by human activities
in the United States was CO2, representing approximately
85 percent of total greenhouse gas emissions. The largest
6 Albedo is a measure of the Earth's reflectivity, and is defined as the fraction of the total solar radiation incident on a body that is reflected by it.
7 Carbon comprises 12144th" of carbon dioxide by weight.
8 See .
Executive Summary ES-3
-------
Figure ES-1
U.S. Greenhouse Gas Emissions by Gas
8,000 -
7,000 -
6,000 -
5,000 -
4,000 -
3,000 -
2,000 -
1,000 -
o-
HFCs, PFCs, &SFE Methane
Nitrous Oxide
Carbon Dioxide
Figure ES-2
Annual Percent Change in U.S. Greenhouse Gas Emissions
3.5-
3.0-
2.5-
2.0-
1.5-
I 1.0-
S.
0.5-
0.0-
-0.5-
-1.0-
-1.5-
12.5%
1.7% I 1.7%
ill-Ill ail
source of CO2, and of overall greenhouse gas emissions,
was fossil fuel combustion. CH4 emissions, which have
steadily declined since 1990, resulted primarily from
decomposition of wastes in landfills, natural gas systems,
and enteric fermentation associated with domestic livestock.
Agricultural soil management and mobile source fossil fuel
combustion were the major sources of N2O emissions. The
emissions of substitutes for ozone depleting substances and
emissions of HFC-23 during the production of HCFC-22
were the primary contributors to aggregate HFC emissions.
Electrical transmission and distribution systems accounted
for most SF6 emissions, while PFC emissions resulted from
semiconductor manufacturing and as a by-product of primary
aluminum production.
Overall, from 1990 to 2004, total emissions of CO2
increased by 982.7 Tg CO2 Eq. (20 percent), while CH4 and
N2O emissions decreased by 61.3 Tg CO2 Eq. (10 percent)
and 8.2 Tg CO2 Eq. (2 percent), respectively. During the
same period, aggregate weighted emissions of HFCs, PFCs,
and SF6 rose by 52.2 Tg CO2 Eq. (58 percent). Despite being
emitted in smaller quantities relative to the other principal
greenhouse gases, emissions of HFCs, PFCs, and SF6 are
significant because many of them have extremely high
global warming potentials and, in the cases of PFCs and SF6,
long atmospheric lifetimes. Conversely, U.S. greenhouse
gas emissions were partly offset by carbon sequestration in
forests, trees in urban areas, agricultural soils, and landfilled
yard trimmings and food scraps, which, in aggregate, offset
11 percent of total emissions in 2004. The following sections
Figure ES-3
Figure ES-4
Cumulative Change in U.S. Greenhouse Gas
Emissions Relative to 1990
1,000 -
800 -
600 -
S
o 400 -
o
ff
200 -
0
-200 -1
1— CM CO
2004 Greenhouse Gas Emissions by Gas
HFCs, PFCs, & SF6
N20
CH4
CO,
84.6%
ES-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Iron and Steel Production
Cement Manufacture
Municipal Solid Waste Combustion
Ammonia Manufacture and Urea Application
Lime Manufacture
Limestone and Dolomite Use
Natural Gas Flaring
Aluminum Production
Soda Ash Manufacture and Consumption
Petrochemical Production
Titanium Dioxide Production
Phosphoric Acid Production
Ferroalloy Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Consumption
Net CO 2 Flux from Land Use, Land-Use
Change and Forestry3
International Bunker Fuelsb
Wood Biomass and Ethanol Consumption*1
CH4
Landfills
Natural Gas Systems
Enteric Fermentation
Coal Mining
Manure Management
Wastewater Treatment
Petroleum Systems
Rice Cultivation
Stationary Combustion
Abandoned Underground Coal Mines
Mobile Combustion
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural Residues
Silicon Carbide Production
International Bunker Fue/sb
N20
Agricultural Soil Management
Mobile Combustion
Manure Management
Nitric Acid Production
Human Sewage
Stationary Combustion
Settlements Remaining Settlements
Adipic Acid Production
N20 Product Usage
Municipal Solid Waste Combustion
Field Burning of Agricultural Residues
Forest Land Remaining Forest Land
International Bunker Fuelsb
MFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing
Total
Net Emissions (Sources and Sinks)
1990
5,005.3
4,696.6
117.2
85.0
33.3
10.9
19.3
11.2
5.5
5.8
7.0
4.1
2.2
1.3
1.5
2.0
0.9
0.9
0.3
0.1
(910.4)
113.5
216.7
618.1
172.3
126.7
117.9
81.9
31.2
24.8
34.4
7.1
7.9
6.0
4.7
1.2
1.3
0.7
+
0.2
394.9
266.1
43.5
16.3
17.8
12.9
12.3
5.6
15.2
4.3
0.5
0.4
0.1
1.0
90.8
0.4
35.0
28.6
2.9
18.4
5.4
6,109.0
5,198.6
1998
5,620.2
5,271.8
152.8
67.7
39.2
17.1
21.9
13.9
7.4
6.6
6.4
4.3
3.0
1.8
1.6
2.0
0.9
1.1
0.3
0.2
(744.0)
114.6
217.2
579.5
144.4
125.4
116.7
62.8
38.8
32.6
29.7
7.9
6.8
6.9
3.8
1.7
1.2
0.8
+
0.2
440.6
301.1
54.8
17.4
20.9
14.9
13.4
6.2
6.0
4.8
0.4
0.5
0.4
1.0
133.4
54.5
40.1
16.7
7.1
9.1
5.8
6,773.7
6,029.6
1999
5,695.0
5,342.4
160.6
63.8
40.0
17.6
20.6
13.5
8.1
6.9
6.5
4.2
3.1
1.9
1.5
2.0
0.8
1.1
0.3
0.1
(765.7)
105.2
222.3
569.0
141.6
121.7
116.8
58.9
38.1
33.6
28.5
8.3
7.0
6.9
3.6
1.7
1.2
0.8
+
0.1
419.4
281.2
54.1
17.4
20.1
15.4
13.4
6.2
5.5
4.8
0.4
0.4
0.5
0.9
131.5
62.8
30.4
16.1
7.2
9.0
6.0
6,814.9
6,049.2
2000
5,864.5
5,533.7
140.7
65.3
41.2
17.9
19.6
13.3
6.0
5.8
6.2
4.2
3.0
1.9
1.4
1.7
1.0
1.1
0.3
0.1
(759.5)
101.4
226.8
566.9
139.0
126.7
115.6
56.3
38.0
34.3
27.8
7.5
7.3
7.2
3.5
1.7
1.2
0.8
+
0.1
416.2
278.2
53.1
17.8
19.6
15.5
13.9
6.0
6.0
4.8
0.4
0.5
0.4
0.9
134.7
71.2
29.8
15.3
6.3
9.0
3.2
6,982.3
6,222.8
2001
5,795.2
5,486.9
131.0
57.8
41.4
18.6
16.7
12.8
5.7
6.1
4.5
4.1
2.8
1.9
1.3
1.3
0.8
1.0
0.3
0.1
(768.0)
97.8
200.5
560.3
136.2
125.6
114.6
55.5
38.9
34.7
27.4
7.6
6.6
6.6
3.3
1.4
1.1
0.8
+
0.1
412.8
282.9
50.0
18.1
15.9
15.6
13.5
5.8
4.9
4.8
0.5
0.5
0.4
0.9
124.9
78.6
19.8
15.3
4.5
4.0
2.6
6,893.1
6,125.1
2002
5,815.9
5,501.8
136.5
54.6
42.9
18.9
18.5
12.3
5.9
6.2
4.6
4.1
2.9
2.0
1.3
1.2
1.0
0.9
0.3
0.1
(768.6)
89.5
194.4
559.8
139.8
125.4
114.7
52.5
39.3
35.8
26.8
6.8
6.2
6.0
3.2
1.5
1.0
0.7
+
0.1
407.4
277.8
47.5
18.0
17.2
15.6
13.2
6.0
5.9
4.8
0.5
0.4
0.4
0.8
132.7
86.2
19.8
14.5
4.4
5.3
2.6
6,915.8
6,147.2
2003
5,877.7
5,571.1
133.5
53.3
43.1
19.4
15.3
13.0
4.7
6.1
4.6
4.1
2.8
2.0
1.4
1.2
1.3
0.5
0.3
0.1
(774.8)
84.1
202.1
564.4
142.4
124.7
115.1
54.8
39.2
36.6
25.9
6.9
6.5
5.8
3.0
1.5
1.0
0.8
+
0.1
386.1
259.2
44.8
17.5
16.7
15.8
13.6
6.2
6.2
4.8
0.5
0.4
0.4
0.8
131.0
93.5
12.3
14.0
4.3
3.8
3.0
6,959.1
6,184.3
2004
5,988.0
5,656.6
153.4
51.3
45.6
19.4
16.9
13.7
6.7
6.0
4.3
4.2
2.9
2.3
1.4
1.3
1.2
0.5
0.3
0.1
(780. 1)
94.5
211.2
556.7
140.9
118.8
112.6
56.3
39.4
36.9
25.7
7.6
6.4
5.6
2.9
1.6
1.0
0.9
+
0.1
386.7
261.5
42.8
17.7
16.6
16.0
13.7
6.4
5.7
4.8
0.5
0.5
0.4
0.9
143.0
103.3
15.6
13.8
4.7
2.8
2.7
7,074.4
6,294.3
+ Does not exceed 0.05 Tg C02 Eq.
a Parentheses indicate negative values or sequestration. The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the
United States. Sinks are only included in net emissions total.
b Emissions from International Bunker Fuels and Wood Biomass and Ethanol Consumption are not included in totals.
Note: Totals may not sum due to independent rounding.
Executive Summary ES-5
-------
describe each gas's contribution to total U.S. greenhouse gas Figure ES-5
emissions in more detail.
2004 Sources of CO,
Carbon Dioxide Emissions
The global carbon cycle is made up of large carbon
flows and reservoirs. Billions of tons of carbon in the form of
CO2 are absorbed by oceans and living biomass (i.e., sinks)
and are emitted to the atmosphere annually through natural
processes (i.e., sources). When in equilibrium, carbon fluxes
among these various reservoirs are roughly balanced. Since
the Industrial Revolution (i.e., about 1750), global atmospheric
concentrations of CO2 have risen about 35 percent (IPCC 2001,
Hofmann 2004), principally due to the combustion of fossil
fuels. Within the United States, fuel combustion accounted for
94 percent of CO2 emissions in 2004. Globally, approximately
25,575 Tg of CO2 were added to the atmosphere through the
combustion of fossil fuels in 2002, of which the United States
accounted for about 23 percent.9 Changes in land use and
forestry practices can also emit CO2 (e.g., through conversion
of forest land to agricultural or urban use) or can act as a sink
for CO2 (e.g., through net additions to forest biomass).
U.S. anthropogenic sources of CO2 are shown in
Figure ES-5. As the largest source of U.S. greenhouse gas
emissions, CO2 from fossil fuel combustion has accounted
for approximately 80 percent of GWP weighted emissions
since 1990, growing slowly from 77 percent of total
GWP-weighted emissions in 1990 to 80 percent in 2004.
Emissions of CO2 from fossil fuel combustion increased at
an average annual rate of 1.3 percent from 1990 to 2004.
The fundamental factors influencing this trend include (1) a
generally growing domestic economy over the last 14 years,
and (2) significant growth in emissions from transportation
activities and electricity generation. Between 1990 and 2004,
CO2 emissions from fossil fuel combustion increased from
4,696.6 Tg CO2 Eq. to 5,656.6 Tg CO2 Eq.— a 20 percent
total increase over the fourteen-year period. Historically,
changes in emissions from fossil fuel combustion have been
the dominant factor affecting U.S. emission trends.
From 2003 to 2004, these emissions increased by 85.5
Tg CO2 Eq. (1.5 percent). A number of factors played a
major role in the magnitude of this increase. Strong growth
in the U.S. economy and industrial production, particularly
in energy-intensive industries, caused an increase in the
5,656.6
Fossil Fuel Combustion
Iron and Steel Production •
Cement Manufacture •
Municipal Solid Waste Combustion •
Ammonia Manufacture and Urea Application •
Lime Manufacture •
Limestone and Dolomite Use •
Natural Gas Flaring •
Aluminum Production •
Soda Asb Manufacture and Consumption •
Titanium Dioxide Production I
PbospboricAcid Production I
Ferroalloy Production I
Carbon Dioxide Consumption I
Zinc Production |
Lead Production
Silicon Carbide Consumption
C02 as a Portion
of all Emissions
o
10 20 30 40 50 60
TgCO,Eq.
demand for electricity and fossil fuels. Demand for travel
was also higher, causing an increase in petroleum consumed
for transportation. In contrast, the warmer winter conditions
led to decreases in demand for heating fuels in both the
residential and commercial sectors. Moreover, much of the
increased electricity demanded was generated by natural gas
consumption and nuclear power, rather than more carbon
intensive coal, moderating the increase in CO2 emissions
from electricity generation. Use of renewable fuels rose very
slightly due to increases in the use of biofuels.
The four major end-use sectors contributing to CO2
emissions from fossil fuel combustion are industrial,
transportation, residential, and commercial. Electricity
generation also emits CO2, although these emissions are
produced as fossil fuel is consumed to provide electricity to
one of the four end-use sectors. For the discussion below,
electricity generation emissions have been distributed to each
end-use sector on the basis of each sector's share of aggregate
electricity consumption. This method of distributing
emissions assumes that each end-use sector consumes
electricity that is generated from the national average mix
of fuels according to their carbon intensity. Emissions from
electricity generation are also addressed separately after the
end-use sectors have been discussed.
Note that emissions from U.S. territories are calculated
separately due to a lack of specific consumption data for the
individual end-use sectors.
9 Global CO2 emissions from fossil fuel combustion were taken from Marland et al. (2005) .
ES-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure ES-6, Figure ES-7, and Table ES-3 summarize CO2
emissions from fossil fuel combustion by end-use sector.
Transportation End- Use Sector. Transportation activities
(excluding international bunker fuels) accounted for 33
percent of CO2 emissions from fossil fuel combustion in
2004.10 Virtually all of the energy consumed in this end-use
sector came from petroleum products. Over 60 percent of the
emissions resulted from gasoline consumption for personal
vehicle use. The remaining emissions came from other
transportation activities, including the combustion of diesel
fuel in heavy-duty vehicles and jet fuel in aircraft.
Industrial End-Use Sector. Industrial CO2 emissions,
resulting both directly from the combustion of fossil fuels and
indirectly from the generation of electricity that is consumed
by industry, accounted for 28 percent of CO2 from fossil fuel
combustion in 2004. About half of these emissions resulted
from direct fossil fuel combustion to produce steam and/or
heat for industrial processes. The other half of the emissions
resulted from consuming electricity for motors, electric
furnaces, ovens, lighting, and other applications.
Residential and Commercial End-Use Sectors. The
residential and commercial end-use sectors accounted for
21 and 17 percent, respectively, of CO2 emissions from
fossil fuel combustion in 2004. Both sectors relied heavily
Figure ES-7
Figure ES-6
2,500 -|
2,000 -
. 1,500 -
1,000 -
500 -
2004 C02 Emissions from Fossil Fuel
Combustion by Sector and Fuel Type
Petroleum
Natural Gas
Relative Contribution
by Fuel Type
0 -1
Residential Commercial Industrial Transportation Electricity U.S.
Generation Territories
Note: Electricity generation also includes emissions of less than
1 Tg C02 Eq. from geothermal-based electricity generation.
2004 End-Use Sector Emissions of C02 from
Fossil Fuel Combustion
2,000 -|
1,500 -
o 1,000 -
500 -
0 -1
From Electricity
Consumption
| From Direct Fossil
Fuel Combustion
Residential Commercial Industrial Transportation U.S.
Territories
on electricity for meeting energy demands, with 68 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.
Electricity Generation. The United States relies on
electricity to meet a significant portion of its energy demands,
especially for lighting, electric motors, heating, and air
conditioning. Electricity generators consumed 34 percent of
U.S. energy from fossil fuels and emitted 40 percent of the
CO2 from fossil fuel combustion in 2004. The type of fuel
combusted by electricity generators has a significant effect
on their emissions. For example, some electricity is generated
with low CO2 emitting energy technologies, particularly non-
fossil options such as nuclear, hydroelectric, or geothermal
energy. However, electricity generators rely on coal for over
half of their total energy requirements and accounted for 94
percent of all coal consumed for energy in the United States
in 2004. Consequently, changes in electricity demand have
a significant impact on coal consumption and associated
CO2 emissions.
Other significant CO2 trends included the following:
• CO2 emissions from iron and steel production decreased
to 51.3 Tg CO2 Eq. in 2004, and have declined by 33.7
Tg CO2 Eq. (40 percent) from 1990 through 2004, due
10 If emissions from international bunker fuels are included, the transportation end-use sector accounted for 34 percent of U. S. emissions from fossil fuel
combustion in 2004.
Executive Summary ES-7
-------
Table ES-3: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity Generation
1990
1,464.4
1,461.4
3.0
1,528.3
851.1
677.2
922.8
338.0
584.8
753.1
222.6 1
530.5 1
28.0
4,696.6
1,795.5
1 1998
1,663.4
1,660.3
3.1
1,634.5
871.9
762.6
1,044.5
333.5
711.0
895.9
217.7
678.2
33.5
5,271.8
2,154.9
1999
1,725.6
1,722.4
3.2
1,613.5
849.0
764.5
1,064.0
352.3
711.7
904.8
218.6
686.2
34.5
5,342.4
2,165.6
2000
1,770.3
1,766.9
3.4
1,642.8
862.6
780.3
1,123.2
369.9
753.3
961.6
229.3
732.4
35.8
5,533.7
2,269.3
2001
1,757.0
1,753.6
3.5
1,574.9
861.2
713.7
1,123.2
361.5
761.7
983.3
224.9
758.4
48.5
5,486.9
2,237.3
2002
1,802.2
1,798.8
3.4
1,542.8
842.1
700.7
1,139.8
360.0
779.8
973.9
224.3
749.6
43.1
5,501.8
2,233.5
2003
1,805.4
1,801.0
4.3
1,572.4
844.6
727.7
1,166.6
378.8
787.9
978.1
235.8
742.2
48.7
5,571.1
2,262.2
2004
1,860.2
1,855.5
4.7
1,595.0
863.5
731.5
1,166.8
369.6
797.2
983.1
226.0
757.2
51.4
5,656.6
2,290.6
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.
to reduced domestic production of pig iron, sinter, and
coal coke.
• CO2 emissions from cement production increased to 45.6
Tg CO2 Eq. in 2004, a 37 percent increase in emissions
since 1990. Emissions mirror growth in the construction
industry. In contrast to many other manufacturing
sectors, demand for domestic cement remains strong
because it is not cost-effective to transport cement far
from its point of manufacture.
• CO2 emissions from municipal solid waste combustion
(19.4 Tg CO2 Eq. in 2004) increased by 8.4 Tg CO2 Eq.
(77 percent) from 1990 through 2004, as the volume of
plastics and other fossil carbon-containing materials in
municipal solid waste grew.
• Net CO2 sequestration from Land Use, Land-Use
Change, and Forestry decreased by 130.3 Tg CO2 Eq.
(14 percent) from 1990 through 2004. This decline
was primarily due to a decline in the rate of net carbon
accumulation in forest carbon stocks. Annual carbon
accumulation in landfilled yard trimmings and food
scraps also slowed over this period, while the rate of
carbon accumulation in agricultural soils and urban trees
increased.
Methane Emissions
According to the IPCC, CFL, is more than 20 times as
effective as CO2 at trapping heat in the atmosphere. Over
the last two hundred and fifty years, the concentration of
CH4 in the atmosphere increased by 143 percent (IPCC
2001, Hofmann 2004). Experts believe that over half
of this atmospheric increase was due to emissions from
anthropogenic sources, such as landfills, natural gas and
petroleum systems, agricultural activities, coal mining,
wastewater treatment, stationary and mobile combustion,
and certain industrial processes (see Figure ES-8).
Some significant trends in US . emissions of CH4 include
the following:
• Landfills are the largest anthropogenic source of CH4
emissions in the United States. In 2004, landfill CFL,
emissions were 140.9 Tg CO2 Eq. (approximately 25
percent of total CH4 emissions), which represents a
decline of 31.4 Tg CO2Eq., or 18 percent, since 1990.
Although the amount of solid waste landfilled each year
continues to climb, the amount of CH4 captured and
burned at landfills has increased dramatically, countering
this trend.
j emissions from natural gas systems were 118.8 Tg
CO2 Eq. in 2004; emissions have declined by 7.9 Tg CO2
Eq. (6 percent) since 1990. This decline has been due to
improvements in technology and management practices ,
as well as some replacement of old equipment.
Enteric fermentation was also a significant source of
CH4, accounting for 112.6 Tg CO2 Eq. in 2004. This
amount has declined by 5.3 Tg CO2 Eq. (4 percent) since
ES-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure ES-8
2004 U.S. Sources of CH,
Landfills
Natural Gas Systems
Enteric Fermentation
Coal Mining
Manure Management
Wastewater Treatment
Petroleum Systems
Rice Cultivation
Stationary Combustion
Abandoned Underground Coal Mines
Mobile Combustion
Petrocbemical Production
Iron and Steel Production
Field Burning of Agricultural Residues
Silicon Carbide Production
CH, as a Portion
of all Emissions
<0.05
30 60 90
Tg C02 Eq.
120 150
1990,andby 10.4TgCO2Eq. (8 percent) from a high in
1995. Generally, emissions have been decreasing since
1995, mainly due to decreasing populations of both beef
and dairy cattle and improved feed quality for feedlot
cattle.
Nitrous Oxide Emissions
N2O is produced by biological processes that occur in
soil and water and by a variety of anthropogenic activities
in the agricultural, energy-related, industrial, and waste
management fields. While total N2O emissions are much
lower than CO2 emissions, N2O is approximately 300 times
more powerful than CO2 at trapping heat in the atmosphere.
Since 1750, the global atmospheric concentration of N2O has
risen by approximately 18 percent (IPCC 2001, Hofmann
2004). The main anthropogenic activities producing N2O
in the United States are agricultural soil management,
fuel combustion in motor vehicles, manure management,
nitric acid production, human sewage, and stationary fuel
combustion (see Figure ES-9).
Some significant trends in U.S. emissions of N2O include
the following:
• Agricultural soil management activities such as fertilizer
application and other cropping practices were the largest
source of U.S. N2O emissions, accounting for 68 percent
(261.5 Tg CO2 Eq.) of 2004 emissions. N2O emissions
from this source have not shown any significant long-
term trend, as they are highly sensitive to such factors
as temperature and precipitation, which have generally
outweighed changes in the amount of nitrogen applied
to soils.
• In 2004, N2O emissions from mobile combustion were
42.8 Tg CO2 Eq. (approximately 11 percent of U. S. N2O
emissions). From 1990 to 2004, N2O emissions from
mobile combustion decreased by 1 percent. However,
from 1990 to 1998 emissions increased by 26 percent,
due to control technologies that reduced CH4 emissions
while increasing N2O emissions. Since 1998, new
control technologies have led to a steady decline in N2O
from this source.
HFC, PFC, and SF6 Emissions
HFCs and PFCs are families of synthetic chemicals
that are being used as alternatives to the ODSs, which are
being phased out under the Montreal Protocol and Clean Air
Act Amendments of 1990. HFCs and PFCs do not deplete
the stratospheric ozone layer, and are therefore acceptable
alternatives under the Montreal Protocol.
These compounds, however, along with SF6, are
potent greenhouse gases. In addition to having high
global warming potentials, SF6 and PFCs have extremely
long atmospheric lifetimes, resulting in their essentially
irreversible accumulation in the atmosphere once emitted.
Sulfur hexafluoride is the most potent greenhouse gas the
IPCC has evaluated.
Figure ES-9
2004 U.S. Sources of N,0
Agricultural Soil Management
Mobile Combustion
Manure Management
Nitric Acid Production
Human Sewage
Stationary Combustion
Settlements Remaining Settlements |
Adipic Acid Production |
N,0 Product Usage |
Municipal Solid Waste Combustion |
Field Burning of Agricultural Residues |
Forest Land Remaining Forest Land
10
20 30
Tg C02 Eq.
40 50
Executive Summary ES-9
-------
Other emissive sources of these gases include HCFC-22
production, electrical transmission and distribution systems,
semiconductor manufacturing, aluminum production, and
magnesium production and processing (see Figure ES-10).
Some significant trends in U.S. HFC, PFC, and SF6
emissions include the following:
• Emissions resulting from the substitution of ozone
depleting substances (e.g., CFCs) have been increasing
from small amounts in 1990 to 103.3 Tg CO2 Eq. in
2004. Emissions from substitutes for ozone depleting
substances are both the largest and the fastest growing
source of HFC, PFC and SF6 emissions. These emissions
have been increasing as phase-outs required under the
Montreal Protocol come into effect, especially after
1994 when full market penetration was made for the
first generation of new technologies featuring ODS
substitutes.
• The increase in ODS emissions is offset substantially
by decreases in emission of HFCs, PFCs, and SF6 from
other sources. Emissions from aluminum production
decreased by 85 percent (15.6 Tg CO2 Eq.) from 1990
to 2004, due to both industry emission reduction efforts
and lower domestic aluminum production.
• Emissions from the production of HCFC-22 decreased
by 55 percent (19.4Tg CO2 Eq.), 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.
Figure ES-10
2004 U.S. Sources of HFCs, PFCs, and SF6
Substitution of Ozone
Depleting Substances
HCFC-22 Production I
Electrical Transmission •
and Distribution |
Semiconductor •
Manufacture m
Aluminum Production I
Magnesium Production I
and Processing |
HFCs, PFCs, and
SF6 as a Portion of
all Emissions
20
40 60 80
Tg C02 Eq.
100 120
• Emissions from electric power transmission and
distribution systems decreased by 52 percent (14.8 Tg
CO2 Eq.) from 1990 to 2004, primarily because of higher
purchase prices for SF6 and efforts by industry to reduce
emissions.
ES.3. Overview of Sector Emissions
and Trends
In accordance with the Revised 1996 IPCC Guidelines
for National Greenhouse Gas Inventories (IPCC/UNEP/
OECD/IEA 1997), and the 2003 UNFCCC Guidelines on
Reporting and Review (UNFCCC 2003), the Inventory of U.S.
Greenhouse Gas Emissions and Sinks report is segregated
into six sector-specific chapters. Figure ES-11 and Table ES -4
aggregate emissions and sinks by these chapters.
Energy
The Energy chapter contains emissions of all greenhouse
gases resulting from stationary and mobile energy activities
including fuel combustion and fugitive fuel emissions. Energy-
related activities, primarily fossil fuel combustion, accounted
for the vast majority of U.S. CO2 emissions for the period
of 1990 through 2004. In 2004, approximately 86 percent
of the energy consumed in the United States was produced
through the combustion of fossil fuels. The remaining 14
percent came from other energy sources such as hydropower,
Figure ES-11
U.S. Greenhouse Emissions by Chapter/IPCC Sector
Industrial Processes
Agriculture
Land Use, Land-Use Change, and Forestry (sink)
(1,000) -1
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the
Land-Use Change and Forestry sector and the Solvent and Other Product Use sector.
ES-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)
Chapter/IPCC Sector
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Land Use, Land-Use Change, and
Forestry (Emissions)
Waste
Total
1990
5,148,
301
4,
439,
5,
210.
6,109.
.3
.1
3
.6
.7
,0
,0
1998
5,752.3
335.1
4.8
483.2
6.5
191.8
6,773.7
1999
5,822,
327,
4.
463.
6.
190.
6,814.
.3
.5
8
,1
,7
,7
.9
2000
5,994.3
329.6
4.8
458.4
6.4
188.8
6,982.3
2001
5,931.6
300.7
4.8
463.4
6.2
186.4
6,893.1
2002
5,944.6
310.9
4.8
457.8
6.4
191.3
6,915.8
2003
6,009.8
304.1
4.8
439.1
6.6
194.8
6,959.1
2004
6,108.2
320.7
4.8
440.1
6.8
193.8
7,074.4
Net C02 Flux from Land Use,
Land-Use Change, and Forestry* (910.4)
(744.0) (765.7) (759.5) (768.0) (768.6) (774.8) (780.1)
Net Emissions
(Sources and Sinks)
5,198.6
6,029.6 6,049.2 6,222.8 6,125.1 6,147.2 6,184.3 6,294.3
* The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions
total.
Note: Totals may not sum due to independent rounding.
Figure ES-12
2004 U.S. Energy Consumption by Energy Source
Renewable
Nuclear
Natural Gas
Coal
Petroleum
6.1%
8.2%
23.0%
22.5%
40.1%
biomass, nuclear, wind, and solar energy (see Figure ES-12).
Energy related activities are also responsible for CELj and N2O
emissions (39 percent and 15 percent of total U.S. emissions
of each gas, respectively). Overall, emission sources in the
Energy chapter account for a combined 86 percent of total
U.S. greenhouse gas emissions in 2004.
Industrial Processes
The Industrial Processes chapter contains by-product
or fugitive emissions of greenhouse gases from industrial
processes not directly related to energy activities such as
fossil fuel combustion. For example, industrial processes
can chemically transform raw materials, which often release
waste gases such as CO2 CFLj and N2O. The processes include
iron and steel production, lead and zinc production, cement
manufacture, ammonia manufacture and urea application, lime
manufacture, limestone and dolomite use (e.g., flux stone,
flue gas desulfurization, and glass manufacturing), soda ash
manufacture and use, titanium dioxide production, phosphoric
acid production, ferroalloy production, CO2 consumption,
aluminum production, petrochemical production, silicon
carbide production, nitric acid production, and adipic acid
production. Additionally, emissions from industrial processes
release HFCs, PFCs and SF6. Overall, emission sources in
the Industrial Process chapter account for 4.5 percent of U.S.
greenhouse gas emissions in 2004.
Solvent and Other Product Use
The Solvent and Other Product Use chapter contains
greenhouse gas emissions that are produced as a by-product
of various solvent and other product uses. In the United
States, emissions from N2O product usage, the only source
of greenhouse gas emissions from this sector, accounted for
less than 0.1 percent of total U.S. anthropogenic greenhouse
gas emissions on a carbon equivalent basis in 2004.
Agriculture
The Agriculture chapter contains anthropogenic
emissions from agricultural activities (except fuel combustion,
Executive Summary ES-11
-------
which is addressed in the Energy chapter). Agricultural
activities contribute directly to emissions of greenhouse
gases through a variety of processes, including the following
source categories: enteric fermentation in domestic livestock,
livestock manure management, rice cultivation, agricultural
soil management, and field burning of agricultural residues.
CH4 and N2O were the primary greenhouse gases emitted
by agricultural activities. CH4 emissions from enteric
fermentation and manure management represented about
20 percent and 7 percent of total CH4 emissions from
anthropogenic activities, respectively, in 2004. Agricultural
soil management activities such as fertilizer application
and other cropping practices were the largest source of U.S.
N2O emissions in 2004, accounting for 68 percent. In 2004,
emission sources accounted for in the Agriculture chapter
were responsible for 6.2 percent of total U.S. greenhouse
gas emissions.
Land Use, Land-Use Change, and Forestry
The Land Use, Land-Use Change, and Forestry chapter
contains emissions and removals of CO2 from forest
management, other land-use activities, and land-use change.
Forest management practices, tree planting in urban areas,
the management of agricultural soils, and the landfilling
of yard trimmings and food scraps have resulted in a net
uptake (sequestration) of carbon in the United States. Forests
(including vegetation, soils, and harvested wood) accounted
for approximately 82 percent of total 2004 sequestration,
urban trees accounted for 11 percent, agricultural soils
(including mineral and organic soils and the application
of lime) accounted for 6 percent, and landfilled yard
trimmings and food scraps accounted for 1 percent of the
total sequestration in 2004. The net forest sequestration is a
result of net forest growth and increasing forest area, as well
as a net accumulation of carbon stocks in harvested wood
pools. The net sequestration in urban forests is a result of net
tree growth in these areas. In agricultural soils, mineral soils
account for a net carbon sink that is almost two times larger
than the sum of emissions from organic soils and liming. The
mineral soil carbon sequestration is largely due to 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
2004 resulted in a net carbon sequestration of 780.1 Tg CO2
Eq. (Table ES-5). This represents an offset of approximately
13 percent of total U.S. CO2 emissions, or 11 percent of total
greenhouse gas emissions in 2004. Total land use, land-use
change, and forestry net carbon sequestration declined by
approximately 14 percent between 1990 and 2004, which
contributed to an increase in net U.S. emissions (all sources
and sinks) of 21 percent from 1990 to 2004. This decline
was primarily due to a decline in the rate of net carbon
accumulation in forest carbon stocks. Annual carbon
accumulation in landfilled yard trimmings and food scraps
and agricultural soils also slowed over this period. However,
the rate of annual carbon accumulation increased in both
agricultural soils and urban trees.
Land use, land-use change, and forestry activities in
2004 also resulted in emissions of N2O (6.8 Tg CO2 Eq.).
Total N2O emissions from the application of fertilizers
to forests and settlements increased by approximately 20
percent between 1990 and 2004.
Waste
The Waste chapter contains emissions from waste
management activities (except municipal solid waste
incineration, which is addressed in the Energy chapter).
Landfills were the largest source of anthropogenic CH4
emissions, accounting for 25 percent of total U.S. CH4
emissions.11 Additionally, wastewater treatment accounts
for 7 percent of U.S. CH4 emissions. N2O emissions from
the discharge of wastewater treatment effluents into aquatic
environments were estimated, as were N2O emissions from
the treatment process itself, using a simplified methodology.
Wastewater treatment systems are a potentially significant
source of N2O emissions; however, methodologies are
not currently available to develop a complete estimate.
N2O emissions from the treatment of the human sewage
11 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 this report.
ES-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table ES-5: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
Forest Land Remaining Forest Land
Changes in Forest Carbon Stocks
Cropland Remaining Cropland
Changes in Agricultural Soil Carbon
Stocks and Liming Emissions
Land Converted to Cropland
Changes in Agricultural Soil Carbon Stocks
Grassland Remaining Grassland
Changes in Agricultural Soil Carbon Stocks
Land Converted to Grassland
Changes in Agricultural Soil Carbon Stocks
Settlements Remaining Settlements
Urban Trees
Landfilled Yard Trimmings and Food Scraps
Total
1990
(773.4)
(773.4)
(33.1)
(33.1)
1.5
1.5
(4.5)
(4.5)
(17.6)
(17.6)
(83.2)
(58.7)
(24.5)
(910.4)
1998
(618.8)
(618.8)
(24.6)
(24.6)
(2.8)
(2.8)
7.5
7.5
(21.1)
(21.1)
(84.2)
(73.3)
(10.9)
(744.0)
1999
(637.9)
(637.9)
(24.6)
(24.6)
(2.8)
(2.8)
7.5
7.5
(21.1)
(21.1)
(86.8)
(77.0)
(9.8)
(765.7)
2000
(631.0)
(631.0)
(26.1)
(26.1)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(85.9)
(77.0)
(8.9)
(759.5)
2001
(634.0)
(634.0)
(27.8)
(27.8)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(89.7)
(80.7)
(9.0)
(768.0)
2002
(634.6)
(634.6)
(27.5)
(27.5)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(89.9)
(80.7)
(9.3)
(768.6)
2003
(635.8)
(635.8)
(28.7)
(28.7)
(2.8)
(2.8)
7.3
7.3
(21.1)
(21.1)
(93.8)
(84.3)
(9.4)
(774.8)
2004
(637.2)
(637.2)
(28.9)
(28.9)
(2.8)
(2.8)
7.3
7.3
(21.1)
(21.1)
(97.3)
(88.0)
(9.3)
(780.1)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
component of wastewater were estimated, however, using a
simplified methodology. Overall, in 2004, emission sources
accounted for in the Waste chapter generated 2.7 percent of
total U.S. greenhouse gas emissions.
ES.4. Other Information
Emissions by Economic Sector
Throughout this report, emission estimates are grouped
into six sectors (i.e., chapters) defined by the IPCC: Energy;
Industrial Processes; Solvent Use; Agriculture; Land Use,
Land-Use Change, and Forestry; and Waste. While it is
important to use this characterization for consistency with
UNFCCC reporting guidelines, it is also useful to allocate
emissions into more commonly used sectoral categories. This
section reports emissions by the following economic sectors:
residential, commercial, industrial, industry, transportation,
electricity generation, agriculture, and U.S. territories.
Table ES-6 summarizes emissions from each of these
sectors, and Figure ES-13 shows the trend in emissions by
sector from 1990 to 2004.
Using this categorization, emissions from electricity
generation accounted for the largest portion (33 percent)
of U.S. greenhouse gas emissions in 2004. Transportation
activities, in aggregate, accounted for the second largest
portion (28 percent). Emissions from industry accounted
for 19 percent of U.S. greenhouse gas emissions in 2004.
In contrast to electricity generation and transportation,
emissions from industry have in general declined over the
past decade, although there was an increase in industrial
emissions in 2004 (up 3 percent from 2003 levels). 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 about 6 percent, and primarily consisted
of CO2 emissions from fossil fuel combustion. Activities
related to agriculture accounted for roughly 7 percent of
U.S. emissions; unlike other economic sectors, agricultural
sector emissions were dominated by N2O emissions from
agricultural soil management and CH4 emissions from
enteric fermentation, rather than CO2 from fossil fuel
combustion. The commercial sector accounted for about
7 percent of emissions, while U.S. territories accounted
for 1 percent.
CO2 was also emitted and sequestered by a variety
of activities related to forest management practices, tree
planting in urban areas, the management of agricultural soils,
and landfilling of yard trimmings.
Electricity is ultimately consumed in the economic
sectors described above. Table ES-7 presents greenhouse
gas emissions from economic sectors with emissions related
Executive Summary ES-13
-------
Table ES-6: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq.)
Economic Sector
Electricity Generation
Transportation
Industry
Agriculture
Commercial
Residential
U.S. Territories
Total
Net C02 Flux from Land Use,
Land-Use Change, and Forestry*
Net Emissions (Sources and Sinks)
1990
1,846.4
1,520.3
1,438.9
486.3
433.6
349.4
33.8
6,109.0
(910.4)
5,198.6
1998
2,202.4
1,753.4
1,452.4
541.6
428.0
353.3
42.7
6,773.7
(744.0)
6,029.6
1999
2,213.3
1,819.3
1,411.0
523.9
430.6
372.6
44.2
6,814.9
(765.7)
6,049.2
2000
2,315.9
1,866.9
1,409.7
509.5
443.0
390.4
46.9
6,982.3
(759.5)
6,222.8
2001
2,284.4
1,852.7
1,366.6
514.4
439.5
381.6
54.0
6,893.1
(768.0)
6,125.1
2002
2,280.1
1,898.0
1,346.7
511.0
447.5
380.1
52.4
6,915.8
(768.6)
6,147.2
2003
2,308.5
1,898.9
1,342.7
484.2
466.5
399.8
58.6
6,959.1
(774.8)
6,184.3
2004
2,337.8
1,955.1
1,377.3
491.3
459.9
391.1
61.9
7,074.4
(780.1)
6,294.3
* The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions
total.
Note: Totals may not sum due to independent rounding. Emissions include C02, CH4, N20, MFCs, PFCs, and SF6.
See Table 2-14 for more detailed data.
Figure ES-13
Emissions Allocated to Economic Sectors
2,500-
2,000-
ri- 1,500"
LLJ
<=>
CJ
° _l
1,000-
500-
S 5 S S 3 S &
O) O) O) O) O) O) O)
Note: Does not include U.S. territories.
Electricity Generation
Transportation
Industry
' Agriculture
- Commercial
Residential
§ 5 S
to electricity generation distributed into end-use categories
(i.e., emissions from electricity generation are allocated to
the economic sectors in which the electricity is consumed).
To distribute electricity emissions among end-use sectors,
emissions from the source categories assigned to electricity
generation were allocated to the residential, commercial,
industry, transportation, and agriculture economic sectors
according to retail sales of electricity.12 These source
categories include CO2 from fossil fuel combustion and the
use of limestone and dolomite for flue gas desulfurization,
CO2 and N2O from waste combustion, CK4 and N2O from
stationary sources, and SF6 from electrical transmission and
distribution systems.
When emissions from electricity are distributed among
these sectors, industry accounts for the largest share of U.S.
greenhouse gas emissions (30 percent) in 2004. Emissions
from the residential and commercial sectors also increase
substantially when emissions from electricity are included,
due to their relatively large share of electricity consumption
(e.g., lighting, appliances, etc.). Transportation activities
remain the second largest contributor to total U.S. emissions
(28 percent). In all sectors except agriculture, CO2 accounts
for more than 80 percent of greenhouse gas emissions,
primarily from the combustion of fossil fuels. Figure ES-14
shows the trend in these emissions by sector from 1990 to
2004.
Indirect Greenhouse Gases (CO, NOX,
NMVOCs, and S02)
The reporting requirements of the UNFCCC13 request
that information be provided on indirect greenhouse gases,
which include CO, NOX, NMVOCs, and SO2. These gases do
not have a direct global warming effect, but indirectly affect
terrestrial radiation absorption by influencing the formation
and destruction of tropospheric and stratospheric ozone, or,
in the case of SO2, by affecting the absorptive characteristics
12 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.
13 See .
ES-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table ES-7: U.S Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions Distributed (Tg
C02 Eq.)
Economic Sector
Industry
Transportation
Commercial
Residential
Agriculture
U.S. Territories
Total
Net C02 Flux from Land Use,
Land-Use Change, and Forestry*
Net Emissions (Sources and Sinks)
2,
1,
6,
1990
074.6
523.4
979.2
950.8
547.2
33.8
109.0
(910.4) |
5,
198.6
1998
2,210.3
1,756.5
1,102.0
1,060.0
602.4
42.7
6,773.7
(744.0)
6,029.6
1999
2,174.4
1,822.5
1,115.8
1,083.2
575.0
44.2
6,814.9
(765.7)
6,049.2
2000
2,186.1
1,870.3
1,171.8
1,140.0
567.2
46.9
6,982.3
(759.5)
6,222.8
2001
2,073.6
1,856.2
1,190.8
1,136.2
582.6
54.0
6,893.1
(768.0)
6,125.1
2002
2,042.0
1,901.4
1,191.4
1,154.1
574.5
52.4
6,915.8
(768.6)
6,147.2
2003
2,066.0
1,903.2
1,204.3
1,182.9
544.3
58.6
6,959.1
(774.8)
6,184.3
2004
2,103
1,959
1,211
1,181
556
61
7,074
(780.
6,294
.0
.8
.0
.9
.9
.9
.4
1)
.3
* The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions
total.
See Table 2-16 of this report for more detailed data.
of the atmosphere. Additionally, some of these gases may
react with other chemical compounds in the atmosphere to
form compounds that are greenhouse gases.
Since 1970, the United States has published estimates
of annual emissions of CO, NOX, NMVOCs, and SO2 (EPA
2005),14 which are regulated under the Clean Air Act. Table
ES-9 shows that fuel combustion accounts for the majority
of emissions of these indirect greenhouse gases. Industrial
Figure ES-14
Emissions with Electricity Distributed
to Economic Sectors
2,500-i
2,000-
S
o 1,500-
1,000-
500-
Commercial
.
Residential
Agriculture
iiiiliiiiiiiiii
Note: Does not include U.S. territories.
processes—such as the manufacture of chemical and allied
products, metals processing, and industrial uses of solvents —
are also significant sources of CO, NOX, and NMVOCs.
Key Categories
The IPCC's Good Practice Guidance (IPCC 2000)
defines a key category as a "[source or sink category] that
is prioritized within the national inventory system because
its estimate has a significant influence on a country's total
inventory of direct greenhouse gases in terms of the absolute
level of emissions, the trend in emissions, or both."15 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 2004 emission estimates for the
2004 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
14 NO,, and CO emission estimates from field burning of agricultural residues were estimated separately, and therefore not taken from EPA (2005).
15 See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
Executive Summary ES-15
-------
Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data
Total emissions can be compared to other economic and social indices to highlight changes over time. These comparisons include: (1)
emissions per unit of aggregate energy consumption, because energy-related activities are the largest sources of emissions; (2) emissions
per unit of fossil fuel consumption, because almost all energy-related emissions involve the combustion of fossil fuels; (3) emissions per
unit of electricity consumption, because the electric power industry—utilities and nonutilities combined—was the largest source of U.S.
greenhouse gas emissions in 2004; (4) emissions per unit of total gross domestic product as a measure of national economic activity; or
(5) emissions per capita.
Table ES-8 provides data on various statistics related to U.S. greenhouse gas emissions normalized to 1990 as a baseline year. Greenhouse
gas emissions in the United States have grown at an average annual rate of 1.1 percent since 1990. This rate is slower than that for total
energy or fossil fuel consumption and much slower than that for either electricity consumption or overall gross domestic product. Total U.S.
greenhouse gas emissions have also grown more slowly than national population since 1990 (see Figure ES-15). Overall, global atmospheric
C02 concentrations—a function of many complex anthropogenic and natural processes—are increasing at 0.4 percent per year.
Table ES-8: Recent Trends in Various U.S. Data (Index 1990 = 100) and Global Atmospheric C02 Concentration
Variable
Greenhouse Gas Emissions3
Energy Consumption"
Fossil Fuel Consumption"
Electricity Consumption"
GDP<=
Population
Atmospheric C02 Concentration6
1991
99
100
99
102
100
101
100
1998
111
112
113
121
127
110
| 103
1999
112
114
114
123
133
112
104
2000
114
117
117
127
138
113
104
2001
113
114
115
125
139
114
105
2002
113
116
116
128
141
115
105
2003
114
116
117
129
145
116
106
2004
116
118
118
131
151
117
106
Growth
Rate'
1.1%
1.2%
1.2%
2.0%
3.0%
1.1%
0.4%
a GWP weighted values
b Energy content weighted values (EIA 2004)
c Gross Domestic Product in chained 2000 dollars (BEA 2005)
11 U.S. Census Bureau (2005)
o Hofmann (2004)
f Average annual growth rate
Figure ES-15
U.S. Greenhouse Gas Emissions Per Capita
and Per Dollar of Gross Domestic Product
160
150"
= 130"
| 110-
7T100-
I 90"
80"
70-
60-
50 ^
Real GDP
Population
Emissions
per capita
Emissions per $GDP
999999999900000
Source: BEA (2005), U.S. Census Bureau (2005), and emission estimates in this report.
ES-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table ES-9: Emissions of NOX, CO, NMVOCs, and S02 (Gg)
Gas/Activity
1990
1998 1999
2000 2001
2002
2003
2004
NO,
Stationary Fossil Fuel Combustion
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Solvent Use
Agricultural Burning
Waste
CO
Stationary Fossil Fuel Combustion
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Solvent Use
Agricultural Burning
Waste
NMVOCs
Stationary Fossil Fuel Combustion
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Solvent Use
Agricultural Burning
Waste
S02
Stationary Fossil Fuel Combustion
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Solvent Use
Agricultural Burning
Waste
22,860
9,884
12,134
139
82
591
1
28
0
130,580
4,999
119,482
302
978
4,124
4
689
1
20,937
912
10,933
555
222
2,426
5,217
NA
673
20,936
18,407
793
390
39
1,306
0
NA
0
21,964
9,419
11,592
130
145
637
3
35
3
98,984
3,927
87,940
332
2,826
3,163
1
789
5
16,403
1,016
7,742
440
326
2,047
4,671
NA
161
17,189
15,191
665
310
30
991
1
NA
1
20,530
8,344
11,300
109
143
595
3
34
3
94,361
5,024
83,484
145
2,725
2,156
46
767
13
15,869
1,045
7,586
414
302
1,813
4,569
NA
140
15,917
13,915
704
283
30
984
1
NA
1
20,288
8,002
11,395
111
114
626
3
35
2
92,895
4,340
83,680
146
1,670
2,217
46
790
8
15,228
1,077
7,230
389
257
1,773
4,384
NA
119
14,829
12,848
632
286
29
1,031
1
NA
1
19,414
7,667
10,823
113
114
656
3
35
2
89,329
4,377
79,972
147
1,672
2,339
45
770
8
15,048
1,080
6,872
400
258
1,769
4,547
NA
122
14,452
12,461
624
289
30
1,047
1
NA
1
18,850
7,522
10,389
135
134
630
6
33
2
87,428
4,020
78,574
116
1,672
2,286
46
706
8
14,217
923
6,560
340
281
1,723
4,256
NA
133
13,928
11,946
631
315
24
1,009
1
NA
1
17,995
7,138
9,916
135
134
631
6
34
2
87,518
4,020
78,574
116
1,672
2,286
46
796
8
13,877
922
6,212
341
282
1,725
4,262
NA
134
14,208
12,220
637
315
24
1,009
1
NA
1
17,076
6,662
9,465
135
134
632
6
39
2
87,599
4,020
78,574
116
1,672
2,286
46
877
8
13,556
922
5,882
341
282
1,727
4,267
NA
134
13,910
11,916
644
315
24
1,009
1
NA
1
Source: (EPA 2005) except for estimates from field burning of agricultural residues.
+ Does not exceed 0.5 Gg
NA (Not Available)
Note: Totals may not sum due to independent rounding.
category names which differ from those used elsewhere in
this report. For more information regarding key categories,
see section 1.5 and Annex 1 of this report.
Quality Assurance and Quality Control
(QA/QC)
The United States seeks to continually improve the
quality, transparency, and credibility of the Inventory of
U.S. Greenhouse Gas Emissions and Sinks. To assist in these
efforts, the United States implemented a systematic approach
to QA/QC. While QA/QC has always been an integral part
of the U.S. national system for inventory development, the
procedures followed for the current inventory, as described in
the Introduction chapter of this report, have been formalized
in accordance with the QA/QC plan and the UNFCCC
reporting guidelines.
Uncertainty Analysis of Emission
Estimates
While the current U.S. emissions inventory provides a
solid foundation for the development of a more detailed and
comprehensive national inventory, there are uncertainties
Executive Summary ES-17
-------
Figure ES-16
2004 Key Categories - Tier 1 Level Assessment
C02 Emissions from Stationary Combustion - Coal
C02 Emissions from Mobile Combustion: Road & Other
C02 Emissions from Stationary Combustion - Gas
C02 Emissions from Stationary Combustion - Oil
C02 Emissions from Mobile Combustion: Aviation
Direct N20 Emissions from Agricultural Soils
C02 Emissions from Non-Energy Use of Fuels
CH4 Emissions from Solid Waste Disposal Sites
CH4 Fugitive Emissions from Natural Gas Operations
CH4 Emissions from Enteric Fermentation in Domestic Livestock
Emissions from Substitutes for Ozone Depleting Substances
Indirect N20 Emissions from Nitrogen Used in Agriculture
CH4 Fugitive Emissions from Coal Mining and Handling
C02 Emissions from Mobile Combustion: Marine
C02 Emissions from Iron and Steel Production
C02 Emissions from Cement Production
N,0 Emissions from Mobile Combustion: Road & Other
Note: For a complete discussion of the key category analysis see Annex 1.
I
500
1,000 1,500
2004 Emissions (Tg C02 Eq.)
2,000
2,500
associated with the emission estimates. Some of the current
estimates, such as those for CO2 emissions from energy-
related activities and cement processing, are considered
to have low uncertainties. For some other categories
of emissions, however, a lack of data or an incomplete
understanding of how emissions are generated increases
the uncertainty associated with the estimates presented.
Acquiring a better understanding of the uncertainty
associated with inventory estimates is an important step
in helping to prioritize future work and improve the
overall quality of the inventory. Recognizing the benefit of
conducting an uncertainty analysis, the UNFCCC reporting
guidelines follow the recommendations of the IPCC Good
Practice Guidance (IPCC 2000) and require that countries
provide single estimates of uncertainty for source and sink
categories.
Currently, a qualitative discussion of uncertainty is
presented for all source and sink categories in Annex 7 of
this report. Within the discussion of each emission source,
specific factors affecting the uncertainty surrounding
the estimates are discussed. Most sources also contain a
quantitative uncertainty assessment, in accordance with
UNFCCC reporting guidelines.
ES-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
1. Introduction
This report presents estimates by the United States government of U.S. anthropogenic greenhouse gas emissions and
sinks for the years 1990 through 2004. A summary of these estimates is provided in Table 2-3 and Table 2-4 by gas and
source category in the Trends in Greenhouse Gas Emissions chapter. The emission estimates in these tables are presented
on both a full molecular mass basis and on a Global Warming Potential (GWP) weighted basis in order to show the relative
contribution of each gas to global average radiative forcing.1 This report also discusses the methods and data used to calculate
these emission estimates.
In June of 1992, the United States signed, and later ratified in October, the United Nations Framework Convention on
Climate Change (UNFCCC). As stated in Article 2 of the UNFCCC, 'The ultimate objective of this Convention and any
related legal instruments that the Conference of the Parties may adopt is to achieve, in accordance with the relevant provisions
of the Convention, stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous
anthropogenic interference with the climate system. Such a level should be achieved within a time-frame sufficient to allow
ecosystems to adapt naturally to climate change, to ensure that food production is not threatened, and to enable economic
development to proceed in a sustainable manner."2'3
Parties to the Convention, by ratifying, "shall develop, periodically update, publish and make available...national
inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by the
Montreal Protocol, using comparable methodologies.... "4 The United States views this report as an opportunity to fulfill
these commitments under the UNFCCC.
In 1988, preceding the creation of the UNFCCC, the World Meteorological Organization (WMO) and the United
Nations Environment Programme (UNEP) jointly established the Intergovernmental Panel on Climate Change (IPCC). The
role of the IPCC is to assess on a comprehensive, objective, open, and transparent basis the scientific, technical, and socio-
economic information relevant to understanding the scientific basis of risk of human-induced climate change, its potential
impacts, and options for adaptation and mitigation (IPCC 2003). Under Working Group 1 of the IPCC, nearly 140 scientists
and national experts from more than thirty countries collaborated in the creation of the Revised 1996 IPCC Guidelines for
National Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) to ensure that the emission inventories submitted to
the UNFCCC are consistent and comparable between nations. The IPCC accepted the Revised 1996 IPCC Guidelines at its
Twelfth Session (Mexico City, September 11-13,1996). This report presents information in accordance with these guidelines.
1 See the section below entitled Global Warming Potentials for an explanation of GWP values.
2 The term "anthropogenic," in this context, refers to greenhouse gas emissions and removals that are a direct result of human activities or are the result
of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).
3 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate Change. See . (UNEP/WMO 2000)
4 Article 4(1 )(a) of the United Nations Framework Convention on Climate Change (also identified in Article 12). Subsequent decisions by the Conference
of the Parties elaborated the role of Annex I Parties in preparing national inventories. See .
Introduction 1-1
-------
In addition, this inventory is in accordance with the IPCC
Good Practice Guidance and Uncertainty Management
in National Greenhouse Gas Inventories, which further
expanded upon the methodologies in the Revised 1996IPCC
Guidelines. The IPCC has also accepted the Good Practice
Guidance for Land Use, Land-Use Change, and Forestry at
its Twenty-First Session (Vienna, November 3-7, 2003), as
an elaboration of the Revised 1996 Guidelines.
Overall, this inventory of anthropogenic greenhouse gas
emissions provides a common and consistent mechanism
through which Parties to the UNFCCC can estimate emissions
and compare the relative contribution of individual sources,
gases, and nations to climate change. The structure of this
report is consistent with the current UNFCCC Guidelines
on Reporting and Review (UNFCCC 2003).
1.1. Background Information
Greenhouse Gases
Although the Earth's atmosphere consists mainly of
oxygen and nitrogen, neither plays a significant role in
enhancing the greenhouse effect because both are essentially
transparent to terrestrial radiation. The greenhouse effect is
primarily a function of the concentration of water vapor,
carbon dioxide (CO2), and other trace gases in the atmosphere
that absorb the terrestrial radiation leaving the surface
of the Earth (IPCC 2001). Changes in the atmospheric
concentrations of these greenhouse gases can alter the balance
of energy transfers between the atmosphere, space, land, and
the oceans.5 A gauge of these changes is called radiative
forcing, which is a measure of the influence a factor has in
altering the balance of incoming and outgoing energy in the
Earth-atmosphere system (IPCC 2001). Holding everything
else constant, increases in greenhouse gas concentrations in
the atmosphere will produce positive radiative forcing (i.e.,
a net increase in the absorption of energy by the Earth).
Climate change can be driven by changes in
the atmospheric concentrations of a number of
radiatively active gases and aerosols. We have
clear evidence that human activities have affected
concentrations, distributions and life cycles of these
gases. (IPCC 1996)
Naturally occurring greenhouse gases include water
vapor, CO2, methane (CH4), nitrous oxide (N2O), and
ozone (O3). Several classes of halogenated substances that
contain fluorine, chlorine, or bromine are also greenhouse
gases, but they are, for the most part, solely a product
of industrial activities. Chlorofluorocarbons (CFCs) and
hydrochlorofluorocarbons (HCFCs) are halocarbons that
contain chlorine, while halocarbons that contain bromine
are referred to as bromofluorocarbons (i.e., halons). As
stratospheric ozone depleting substances, CFCs, HCFCs,
and halons are covered under the Montreal Protocol on
Substances that Deplete the Ozone Layer. The UNFCCC
defers to this earlier international treaty. Consequently,
Parties are not required to include these gases in national
greenhouse gas inventories.6 Some other fluorine-containing
halogenated substances—hydrofluorocarbons (HFCs),
perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)—do
not deplete stratospheric ozone but are potent greenhouse
gases. These latter substances are addressed by the UNFCCC
and accounted for in national greenhouse gas inventories.
There are also several gases that, although they do
not have a commonly agreed upon direct radiative forcing
effect, do influence the global radiation budget. These
tropospheric gases include carbon monoxide (CO), nitrogen
dioxide (NO2), sulfur dioxide (SO2), and tropospheric
(ground level) O3. Tropospheric ozone is formed by two
precursor pollutants, volatile organic compounds (VOCs)
and nitrogen oxides (NOjj) in the presence of ultraviolet
light (sunlight). Aerosols are extremely small particles or
liquid droplets that are often composed of sulfur compounds,
carbonaceous combustion products, crustal materials
and other human induced pollutants. They can affect the
absorptive characteristics of the atmosphere. Comparatively,
however, the level of scientific understanding of aerosols is
still very low (IPCC 2001).
CO2, CH4, and N2O are continuously emitted to
and removed from the atmosphere by natural processes
on Earth. Anthropogenic activities, however, can cause
additional quantities of these and other greenhouse gases
5 For more on the science of climate change, see NRC (2001).
6 Emissions estimates of CFCs, HCFCs, halons and other ozone-depleting substances are included in this document for informational purposes.
1-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
to be emitted or sequestered, thereby changing their global
average atmospheric concentrations. Natural activities such
as respiration by plants or animals and seasonal cycles of
plant growth and decay are examples of processes that only
cycle carbon or nitrogen between the atmosphere and organic
biomass. Such processes, except when directly or indirectly
perturbed out of equilibrium by anthropogenic activities,
generally do not alter average atmospheric greenhouse gas
concentrations over decadal timeframes. Climatic changes
resulting from anthropogenic activities, however, could
have positive or negative feedback effects on these natural
systems. Atmospheric concentrations of these gases, along
with their rates of growth and atmospheric lifetimes, are
presented in Table 1-1.
A brief description of each greenhouse gas, its sources,
and its role in the atmosphere is given below. The following
section then explains the concept of GWPs, which are
assigned to individual gases as a measure of their relative
average global radiative forcing effect.
Water Vapor (H2O). Overall, the most abundant and
dominant greenhouse gas in the atmosphere is water vapor.
Water vapor is neither long-lived nor well mixed in the
atmosphere, varying spatially from 0 to 2 percent (IPCC
1996). In addition, atmospheric water can exist in several
physical states including gaseous, liquid, and solid. Human
activities are not believed to affect directly the average
global concentration of water vapor, but, the radiative
forcing produced by the increased concentrations of other
greenhouse gases may indirectly affect the hydrologic cycle.
While a warmer atmosphere has an increased water holding
capacity, increased concentrations of water vapor affects the
formation of clouds, which can both absorb and reflect solar
and terrestrial radiation. Aircraft contrails, which consist of
water vapor and other aircraft emittants, are similar to clouds
in their radiative forcing effects (IPCC 1999).
Carbon Dioxide. In nature, carbon is cycled between
various atmospheric, oceanic, land biotic, marine biotic,
and mineral reservoirs. The largest fluxes occur between the
atmosphere and terrestrial biota, and between the atmosphere
and surface water of the oceans. In the atmosphere,
carbon predominantly exists in its oxidized form as CO2.
Atmospheric CO2 is part of this global carbon cycle, and
therefore its fate is a complex function of geochemical and
biological processes. CO2 concentrations in the atmosphere
increased from approximately 280 parts per million by
volume (ppmv) inpre-industrial times to 376.7 ppmv in 2004,
a 35 percent increase (IPCC 2001 and Hofmann 2004).78
The IPCC definitively states that "the present atmospheric
CO2 increase is caused by anthropogenic emissions of CO2"
(IPCC 2001). The predominant source of anthropogenic CO2
emissions is the combustion of fossil fuels. Forest clearing,
other biomass burning, and some non-energy production
processes (e.g., cement production) also emit notable
quantities of CO2.
In its second assessment, the IPCC also stated that "[t]he
increased amount of CO2 [in the atmosphere] is leading
Table 1-1: Global Atmospheric Concentration (ppm unless otherwise specified), Rate of Concentration Change
(ppb/year), and Atmospheric Lifetime (years) of Selected Greenhouse Gases
Atmospheric Variable
Pre-industrial atmospheric concentration
Atmospheric concentration"
Rate of concentration change0
Atmospheric lifetime
C02
280
376.7
1.6
50-200"
CH4
0.722
1.756
0.005
12"
N20
0.270
0.319
0.0007
114"
SF6«
0
5.4
0.23
3,200
CF4a
40
80
1.0
>50,000
Source: Current atmospheric concentrations and rate of concentration changes for all gases but CF4 are from Hofmann (2004), data for CF4 are from IPCC
(2001). Pre-industrial atmospheric concentration and atmospheric lifetime taken from IPCC (2001).
a Concentrations in parts per trillion (ppt) and rate of concentration change in ppt/year.
b Concentration for CF4 was measured in 2000. Concentrations for all other gases were measured in 2004.
c Rate is calculated over the period 1990 to 2004 for C02, CH4, and N20; 1996 to 2004 for SF6; and 1990 to 1999 for CF4.
11 No single lifetime can be defined for C02 because of the different rates of uptake by different removal processes.
e This lifetime has been defined as an "adjustment time" that takes into account the indirect effect of the gas on its own residence time.
7 The pre-industrial period is considered as the time preceding the year 1750 (IPCC 2001).
8 Carbon dioxide concentrations during the last 1,000 years of the pre-industrial period (i.e., 750-1750), a time of relative climate stability, fluctuated by
about ±10 ppmv around 280 ppmv (IPCC 2001).
Introduction 1-3
-------
to climate change and will produce, on average, a global
warming of the Earth's surface because of its enhanced
greenhouse effect—although the magnitude and significance
of the effects are not fully resolved" (IPCC 1996).
Methane. CH4 is primarily produced through anaerobic
decomposition of organic matter in biological systems.
Agricultural processes such as wetland rice cultivation,
enteric fermentation in animals, and the decomposition
of animal wastes emit CH4, as does the decomposition
of municipal solid wastes. CH4 is also emitted during the
production and distribution of natural gas and petroleum, and
is released as a by-product of coal mining and incomplete
fossil fuel combustion. Atmospheric concentrations of CH4
have increased by about 143 percent since 1750, from a
pre-industrial value of about 722 ppb to 1,756 ppb in 2004,
although the rate of increase has been declining. The IPCC
has estimated that slightly more than half of the current
CH4 flux to the atmosphere is anthropogenic, from human
activities such as agriculture, fossil fuel use, and waste
disposal (IPCC 2001).
CH4 is removed from the atmosphere through a reaction
with the hydroxyl radical (OH) and is ultimately converted
to CO2. Minor removal processes also include reaction
with chlorine in the marine boundary layer, a soil sink, and
stratospheric reactions. Increasing emissions of CH4 reduce
the concentration of OH, a feedback that may increase the
atmospheric lifetime of CH4 (IPCC 2001).
Nitrous Oxide. Anthropogenic sources of N2O emissions
include agricultural soils, especially production of nitrogen-
fixing crops and forages, the use of synthetic and manure
fertilizers, and manure deposition by livestock; fossil fuel
combustion, especially from mobile combustion; adipic
(nylon) and nitric acid production; wastewater treatment and
waste combustion; and biomass burning. The atmospheric
concentration of N2O has increased by 18 percent since
1750, from a pre-industrial value of about 270 ppb to 319
ppb in 2004, a concentration that has not been exceeded
during the last thousand years. N2O is primarily removed
from the atmosphere by the photolytic action of sunlight in
the stratosphere (IPCC 2001).
Ozone. Ozone is present in both the upper stratosphere,9
where it shields the Earth from harmful levels of ultraviolet
radiation, and at lower concentrations in the troposphere,10
where it is the main component of anthropogenic
photochemical "smog." During the last two decades,
emissions of anthropogenic chlorine and bromine-containing
halocarbons, such as CFCs, have depleted stratospheric
ozone concentrations. This loss of ozone in the stratosphere
has resulted in negative radiative forcing, representing
an indirect effect of anthropogenic emissions of chlorine
and bromine compounds (IPCC 1996). The depletion of
stratospheric ozone and its radiative forcing was expected to
reach a maximum in about 2000 before starting to recover,
with detection of such recovery not expected to occur much
before 2010 (IPCC 2001).
The past increase in tropospheric ozone, which is also
a greenhouse gas, is estimated to provide the third largest
increase in direct radiative forcing since the pre-industrial
era, behind CO2 and CH4. Tropospheric ozone is produced
from complex chemical reactions of volatile organic
compounds mixing with NOX in the presence of sunlight.
The tropospheric concentrations of ozone and these other
pollutants are short-lived and, therefore, spatially variable.
Halocarbons, Perfluorocarbons, and Sulfur Hexafluoride.
Halocarbons are, for the most part, man-made chemicals
that have both direct and indirect radiative forcing effects.
Halocarbons that contain chlorine (CFCs, HCFCs, methyl
chloroform, and carbon tetrachloride) and bromine (halons,
methyl bromide, and hydrobromofluorocarbons [HBFCs])
result in stratospheric ozone depletion and are therefore
controlled under the Montreal Protocol on Substances that
Deplete the Ozone Layer. Although CFCs and HCFCs include
potent global warming gases, their net radiative forcing
effect on the atmosphere is reduced because they cause
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
9 The stratosphere is the layer from the troposphere up to roughly 50 kilometers. In the lower regions the temperature is nearly constant but in the upper
layer the temperature increases rapidly because of sunlight absorption by the ozone layer. The ozone-layer is the part of the stratosphere from 19 kilometers
up to 48 kilometers where the concentration of ozone reaches up to 10 parts per million.
10 The troposphere is the layer from the ground up to 11 kilometers near the poles and up to 16 kilometers in equatorial regions (i.e., the lowest layer of
the atmosphere where people live). It contains roughly 80 percent of the mass of all gases in the atmosphere and is the site for most weather processes,
including most of the water vapor and clouds.
1-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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placed on the production and importation of HCFCs by non-
Article 5n countries beginning in 1996, and then followed
by a complete phase-out by the year 2030. While ozone
depleting gases covered under the Montreal Protocol and
its Amendments are not covered by the UNFCCC; they are
reported in this inventory under Annex 6.2 of this report for
informational purposes.
HFCs, PFCs, and SF6 are not ozone depleting substances,
and therefore are not covered under the Montreal Protocol.
They are, however, powerful greenhouse gases. HFCs
are primarily used as replacements for ozone depleting
substances but also emitted as a by-product of the HCFC-
22 manufacturing process. Currently, they have a small
aggregate radiative forcing impact, but it is anticipated that
their contribution to overall radiative forcing will increase
(IPCC 2001). PFCs and SF6 are predominantly emitted from
various industrial processes including aluminum smelting,
semiconductor manufacturing, electric power transmission
and distribution, and magnesium casting. Currently, the
radiative forcing impact of PFCs and SF6 is also small,
but they have a significant growth rate, extremely long
atmospheric lifetimes, and are strong absorbers of infrared
radiation, and therefore have the potential to influence
climate far into the future (IPCC 2001).
Carbon Monoxide. Carbon monoxide has an indirect
radiative forcing effect by elevating concentrations of CH4
and tropospheric ozone through chemical reactions with
other atmospheric constituents (e.g., the hydroxyl radical,
OH) that would otherwise assist in destroying CH4 and
tropospheric ozone. Carbon monoxide is created when
carbon-containing fuels are burned incompletely. Through
natural processes in the atmosphere, it is eventually oxidized
to CO2. Carbon monoxide concentrations are both short-lived
in the atmosphere and spatially variable.
Nitrogen Oxides. The primary climate change effects of
nitrogen oxides (i.e., NO and NO2) are indirect and result
from their role in promoting the formation of ozone in the
troposphere and, to a lesser degree, lower stratosphere,
where it has positive radiative forcing effects.12 Additionally,
NOX emissions from aircraft are also likely to decrease CH4
concentrations, thus having a negative radiative forcing
effect (IPCC 1999). Nitrogen oxides are created from
lightning, soil microbial activity, biomass burning (both
natural and anthropogenic fires), fuel combustion, and,
in the stratosphere, from the photo-degradation of N2O.
Concentrations of NOX are both relatively short-lived in the
atmosphere and spatially variable.
Nonmethane Volatile Organic Compounds (NMVOCs).
Non-CH4 volatile organic compounds include substances
such as propane, butane, and ethane. These compounds
participate, along with NOX, in the formation of tropospheric
ozone and other photochemical oxidants. NMVOCs
are emitted primarily from transportation and industrial
processes, as well as biomass burning and non-industrial
consumption of organic solvents. Concentrations of
NMVOCs tend to be both short-lived in the atmosphere
and spatially variable.
Aerosols. Aerosols are extremely small particles or liquid
droplets found in the atmosphere. They can be produced by
natural events such as dust storms and volcanic activity,
or by anthropogenic processes such as fuel combustion
and biomass burning. Aerosols affect radiative forcing
differently than greenhouse gases, and their radiative effects
occur through direct and indirect mechanisms: directly by
scattering and absorbing solar radiation; and indirectly
by increasing droplet counts that modify the formation,
precipitation efficiency, and radiative properties of clouds.
Aerosols are removed from the atmosphere relatively
rapidly by precipitation. Because aerosols generally have
short atmospheric lifetimes, and have concentrations and
compositions that vary regionally, spatially, and temporally,
their contributions to radiative forcing are difficult to quantify
(IPCC 2001).
The indirect radiative forcing from aerosols is typically
divided into two effects. The first effect involves decreased
droplet size and increased droplet concentration resulting
from an increase in airborne aerosols. The second effect
involves an increase in the water content and lifetime
11 Article 5 of the Montreal Protocol covers several groups of countries, especially developing countries, with low consumption rates of ozone depleting
substances. Developing countries with per capita consumption of less than 0.3 kg of certain ozone depleting substances (weighted by their ozone depleting
potential) receive financial assistance and a grace period of ten additional years in the phase-out of ozone depleting substances.
12 NOX emissions injected higher in the stratosphere, primarily from fuel combustion emissions from high altitude supersonic aircraft, can lead to
stratospheric ozone depletion.
Introduction 1-5
-------
of clouds due to the effect of reduced droplet size on
precipitation efficiency (IPCC 2001). Recent research has
placed a greater focus on the second indirect radiative forcing
effect of aerosols.
Various categories of aerosols exist, including
naturally produced aerosols such as soil dust, sea salt,
biogenic aerosols, sulfates, and volcanic aerosols, and
anthropogenically manufactured aerosols such as industrial
dust and carbonaceous13 aerosols (e.g., black carbon, organic
carbon) from transportation, coal combustion, cement
manufacturing, waste incineration, and biomass burning.
The net effect of aerosols on radiative forcing is believed
to be negative (i.e., net cooling effect on the climate),
although because they remain in the atmosphere for only days
to weeks, their concentrations respond rapidly to changes in
emissions.14 Locally, the negative radiative forcing effects
of aerosols can offset the positive forcing of greenhouse
gases (IPCC 1996). "However, the aerosol effects do not
cancel the global-scale effects of the much longer-lived
greenhouse gases, and significant climate changes can still
result" (IPCC 1996).
The IPCC's Third Assessment Report notes that "the
indirect radiative effect of aerosols is now understood to also
encompass effects on ice and mixed-phase clouds, but the
magnitude of any such indirect effect is not known, although
it is likely to be positive "(IPCC 2001). Additionally, current
research suggests that another constituent of aerosols, black
carbon, may have a positive radiative forcing (Jacobson
2001). The primary anthropogenic emission sources of black
carbon include diesel exhaust and open biomass burning.
Global Warming Potentials
A global warming potential is a quantified measure of
the globally averaged relative radiative forcing impacts of
a particular greenhouse gas (see Table 1-2). It is defined as
the ratio of the time-integrated radiative forcing from the
instantaneous release of 1 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 produces a gas or gases that are
greenhouse gases, or when a gas influences other radiatively
important processes such as the atmospheric lifetimes of
other gases. The reference gas used is CO2, and therefore
GWP weighted emissions are measured in teragrams of CO2
equivalent (Tg CO2Eq.)15 The relationship between gigagrams
(Gg) of a gas and Tg CO2 Eq. can be expressed as follows:
Tg CO2 Eq = (Gg of gas) x (GWP) x
Tg
l.OOOGg
where,
Tg CO2 Eq. = Teragrams of Carbon Dioxide
Equivalents
Gg = Gigagrams (equivalent to a thousand
metric tons)
GWP = Global Warming Potential
Tg = Teragrams
GWP values allow for a comparison of the impacts of
emissions and reductions of different gases. According to the
IPCC, GWPs typically have an uncertainty of ±35 percent.
The parties to the UNFCCC have also agreed to use GWPs
based upon a 100-year time horizon although other time
horizon values are available.
Greenhouse gas emissions and removals should be
presented on a gas-by-gas basis in units of mass...
In addition, consistent with decision 2/CP.3, Parties
should report aggregate emissions and removals
of greenhouse gases, expressed in CO2 equivalent
terms at summary inventory level, using GWP values
provided by the IPCC in its Second Assessment
Report. ..based on the effects of greenhouse gases
over a 100-year time horizon.16
13 Carbonaceous aerosols are aerosols that are comprised mainly of organic substances and forms of black carbon (or soot) (IPCC 2001).
14 Volcanic activity can inject significant quantities of aerosol producing sulfur dioxide and other sulfur compounds into the stratosphere, which can result
in a longer negative forcing effect (i.e., a few years) (IPCC 1996).
15 Carbon comprises 12/44ths of carbon dioxide by weight.
16 Framework Convention on Climate Change; ; 1 November 2002; Report of the Conference of the Parties at
its eighth session; held at New Delhi from 23 October to 1 November 2002; Addendum; Part One: Action taken by the Conference of the Parties at its eighth
session; Decision -/CR8; Communications from Parties included in Annex I to the Convention: Guidelines for the Preparation of National Communications
by Parties Included in Annex I to the Convention, Part 1: UNFCCC reporting guidelines on annual inventories; p. 7. (UNFCCC 2003).
1-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 1-2: Global Warming Potentials and Atmospheric
Lifetimes (Years) Used in this Report
Gas Atmospheric Lifetime
C02
CH4"
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C^FIO
C6Fi4
SF6
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
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)
a 100-year time horizon
b The GWP of CH4 includes the direct effects and those indirect effects
due to the production of tropospheric ozone and stratospheric water
vapor. The indirect effect due to the production of C02 is not included.
Greenhouse gases with relatively long atmospheric
lifetimes (e.g., CO2, CH4, N2O, HFCs, PFCs, and SF6)
tend to be evenly distributed throughout the atmosphere,
and consequently global average concentrations can be
determined. The short-lived gases such as water vapor,
carbon monoxide, tropospheric ozone, ozone precursors
(e.g., NOX, and NMVOCs), and tropospheric aerosols
(e.g., SO2 products and carbonaceous particles), however,
vary regionally, and consequently it is difficult to quantify
their global radiative forcing impacts. No GWP values are
attributed to these gases that are short-lived and spatially
inhomogeneous in the atmosphere.
1.2. Institutional Arrangements
The U.S. Environmental Protection Agency (EPA), in
cooperation with other U.S. government agencies, prepares
the Inventory of U.S. Greenhouse Gas Emissions and Sinks.
A wide range of agencies and individuals are involved in
supplying data to, reviewing, or preparing portions of the
U.S. Inventory—including federal and state government
authorities, research and academic institutions, industry
associations, and private consultants.
Within EPA, the Office of Atmospheric Programs (GAP)
is the lead office responsible for the emission calculations
provided in the Inventory, as well as the completion of the
National Inventory Report and the Common Reporting Format
tables. The Office of Transportation and Air Quality (OTAQ)
is also involved in calculating emissions for the Inventory.
While the U.S. Department of State officially submits the
annual Inventory to the UNFCCC, EPA's 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 data.
Informal relationships also exist with other U.S. agencies to
provide activity data for use in EPA's emission calculations.
These include: the U.S. Department of Agriculture, the U.S.
Geological Survey, the Federal Highway Administration, the
Department of Transportation, the Bureau of Transportation
Statistics, the Department of Commerce, the National
Agricultural Statistics Service, and the Federal Aviation
Administration. Academic and research centers also provide
activity data and calculations to EPA, as well as individual
companies participating in voluntary outreach efforts with
EPA. Finally, the U.S. Department of State officially submits
the Inventory to the UNFCCC each April.
1.3. Inventory Process
EPA has a decentralized approach to preparing the
annual U.S. Inventory, which consists of a National
Inventory Report (NIR) and Common Reporting Format
(CRF) tables. The Inventory coordinator at EPA is
responsible for compiling all emission estimates, and
ensuring consistency and quality throughout the NIR and
Introduction 1-7
-------
Box 1-1: The IPCC Third Assessment Report and Global Warming Potentials
In 2001, the IPCC published its Third Assessment Report (TAR), which provided an updated and more comprehensive scientific
assessment of climate change. Within this report, the GWPs of several gases were revised relative to the IPCC's Second Assessment Report
(SAR), and new GWPs have been calculated for an expanded set of gases. Since the SAR, the IPCC has applied an improved calculation of
C02 radiative forcing and an improved C02 response function (presented in WMO 1999). The GWPs are drawn from WMO (1999) and the
SAR, with updates for those cases where significantly different new laboratory or radiative transfer results have been published. Additionally,
the atmospheric lifetimes of some gases have been recalculated. Because the revised radiative forcing of C02 is about 12 percent lower
than that in the SAR, the GWPs of the other gases relative to C02 tend to be larger, taking into account revisions in lifetimes. In addition, the
values for radiative forcing and lifetimes have been calculated for a variety of halocarbons, which were not presented in the SAR. Table 1 -3
presents the new GWPs, relative to those presented in the SAR.
Table 1-3: Comparison of 100-Year GWPs
Gas
C02
CH4*
N20
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F6
C^FIO
CeF-14
SF6
SAR
1
21
310
11,700
650
2,800
1,300
3,800
140
2,900
6,300
1,300
6,500
9,200
7,000
7,400
23,900
TAR
1
23
296
12,000
550
3,400
1,300
4,300
120
3,500
9,400
1,500
5,700
11,900
8,600
9,000
22,200
Change
NC
2
(14)
300
(100)
600
NC
500
(20)
600
3,100
200
(800)
2,700
1,600
1,600
(1,700)
NC
10%
(5%)
3%
(15%)
21%
NC
13%
(14%)
21%
49%
15%
(12%)
29%
23%
22%
(7%)
Source: (IPCC 2001)
NC (No Change)
Note: Parentheses indicate negative values.
* The GWP of CH4 includes the direct effects and those indirect effects due
to the production of tropospheric ozone and stratospheric water vapor. The
indirect effect due to the production of C02 is not included.
To comply with international reporting standards under the UNFCCC, official emission estimates are reported by the United States using SAR
GWP values. The UNFCCC reporting guidelines for national inventories17 were updated in 2002 but continue to require the use of GWPs from the SAR
so that current estimates of aggregate greenhouse gas emissions for 1990 through 2004 are consistent and comparable with estimates developed
prior to the publication of the TAR. For informational purposes, emission estimates that use the updated GWPs are presented below and in even more
detail in Annex 6.1 of this report. All estimates provided throughout this report are also presented in unweighted units.
CRF tables. Emission calculations for individual sources calculations, based upon their expertise in the source
are the responsibility of individual source leads, who are category, as well as coordinating with researchers and
most familiar with each source category and the unique contractors familiar with the sources. A multi-stage process
characteristics of its emissions profile. The individual for collecting information from the individual source leads
source leads determine the most appropriate methodology and producing the Inventory is undertaken annually to
and collect the best activity data to use in the emission compile all information and data.
17 See .
1-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Methodology Development, Data
Collection, and Emissions and Sink
Estimation
Source leads at EPA collect input data and, as necessary,
evaluate or develop the estimation methodology for the
individual source categories. For most source categories,
the methodology for the previous year is applied to the
new "current" year of the Inventory, and inventory analysts
collect any new data or update data that have changed from
the previous year. If estimates for a new source category are
being developed for the first time, or if the methodology is
changing for an existing source category (e.g., the United
States is implementing a higher Tiered approach for that
source category), then the source category lead will develop
a new methodology, gather the most appropriate activity
data and emission factors (or in some cases direct emission
measurements) for the entire time series, and conduct a
special source-specific peer review process involving relevant
experts from industry, government, and universities.
Once the methodology is in place and the data are
collected, the individual source leads calculate emissions and
sink estimates. The source leads then update or create the
relevant text and accompanying Annexes for the Inventory.
Source leads are also responsible for completing the relevant
sectoral background tables of the Common Reporting
Format, conducting quality assurance and quality control
(QA/QC) checks, and uncertainty analyses.
Summary Spreadsheet Compilation and
Data Storage
The inventory coordinator at EPA collects the source
categories' descriptive text and Annexes, and also aggregates
the emission estimates into a summary spreadsheet that
links the individual source category spreadsheets together.
This summary sheet contains all of the essential data in
one central location, in formats commonly used in the
Inventory document. In addition to the data from each source
category, national trend and related data are also gathered
in the summary sheet for use in the Executive Summary,
Introduction, and Recent Trends sections of the Inventory
report. Electronic copies of each year's summary spreadsheet,
which contains all the emission and sink estimates for the
United States, are kept on a central server at EPA under the
jurisdiction of the Inventory coordinator.
National Inventory Report Preparation
The NIR is compiled from the sections developed
by each individual source lead. In addition, the inventory
coordinator prepares a brief overview of each chapter that
summarizes the emissions from all sources discussed in the
chapters. The inventory coordinator then carries out a key
category analysis for the Inventory, consistent with the IPCC
Good Practice Guidance,IPCC Good Practice Guidance for
Land Use, Land Use Change and Forestry, and in accordance
with the reporting requirements of the UNFCCC. Also at
this time, the Introduction, Executive Summary, and Recent
Trends sections are drafted, to reflect the trends for the most
recent year of the current Inventory. The analysis of trends
necessitates gathering supplemental data, including weather
and temperature conditions, economic activity and gross
domestic product, population, atmospheric conditions, and
the annual consumption of electricity, energy, and fossil
fuels. Changes in these data are used to explain the trends
observed in greenhouse gas emissions in the United States.
Furthermore, specific factors that affect individual sectors
are researched and discussed. Many of the factors that affect
emissions are included in the Inventory document as separate
analyses or side discussions in boxes within the text. Text
boxes are also created to examine the data aggregated in
different ways than in the remainder of the document, such
as a focus on transportation activities or emissions from
electricity generation. The document is prepared to match
the specification of the UNFCCC reporting guidelines for
National Inventory Reports.
Common Reporting Format Table
Compilation
The CRF tables are compiled from individual tables
completed by each individual source lead, which contain
source emissions and activity data. The inventory coordinator
integrates the source data into the complete CRF tables 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 tables, as well as reviews by the
source leads, are completed for the entire time series of CRF
tables before submission.
Introduction 1-9
-------
QA/QC and Uncertainty
QA/QC and uncertainty analyses are supervised by
the QA/QC coordinator, who has general oversight over
the implementation of the QA/QC plan and the overall
uncertainty analysis for the Inventory (see sections on
QA/QC and Uncertainty, below). The QA/QC coordinator
works closely with the source leads to ensure a consistent
QA/QC plan and uncertainty analysis is implemented across
all inventory sources. The inventory QA/QC plan, detailed in
a following section, is consistent with the quality assurance
procedures outlined by EPA.
Expert and Public Review Periods
During the Expert Review period, a first draft of the
document is sent to a select list of technical experts outside
of EPA. The purpose of the Expert Review is to encourage
feedback on the methodological and data sources used in
the current Inventory, especially for sources which have
experienced any changes since the previous Inventory.
Once comments are received and addressed, a second
draft of the document is released for public review by
publishing a notice in the U.S. Federal Register and posting
the document on the EPA Web site. The Public Review
period allows for a 30 day comment period and is open to
the entire U.S. public.
Final Submittal to UNFCCC and Document
Printing
After the final revisions to incorporate any comments
from the Expert Review and Public Review periods, EPA
prepares the final National Inventory Report and the
accompanying Common Reporting Format Tables. The U.S.
Department of State sends the official submission of the U.S.
Inventory to the UNFCCC. The document is then formatted
for printing, posted online, printed by the U.S. Government
Printing Office, and made available for the public.
1.4. Methodology and Data Sources
Emissions of greenhouse gases from various source and
sink categories have been estimated using methodologies
that are consistent with the Revised 1996IPCC Guidelines
for National Greenhouse Gas Inventories (IPCC/UNEP/
OECD/IEA 1997). In addition, the United States references
the additional guidance provided in the IPCC Good Practice
Guidance and Uncertainty Management in National
Greenhouse Gas Inventories (IPCC 2000) and IPCC Good
Practice Guidance for Land Use, Land-Use Change, and
Forestry (IPCC 2003). To the extent possible, the present
report relies on published activity and emission factor data.
Depending on the emission source category, activity data
can include fuel consumption or deliveries, vehicle-miles
traveled, raw material processed, etc. Emission factors are
factors that relate quantities of emissions to an activity.
The IPCC methodologies provided in the Revised
1996 IPCC Guidelines represent baseline methodologies
for a variety of source categories, and many of these
methodologies continue to be improved and refined as new
research and data become available. This report uses the
IPCC methodologies when applicable, and supplements them
with other available methodologies and data where possible.
Choices made regarding the methodologies and data sources
used are provided in conjunction with the discussion of each
source category in the main body of the report. Complete
documentation is provided in the annexes on the detailed
methodologies and data sources utilized in the calculation
of each source category.
1.5. Key Categories
The IPCC's Good Practice Guidance (IPCC 2000)
defines a key category as a "[source or sink category] that
is prioritized within the national inventory system because
its estimate has a significant influence on a country's total
inventory of direct greenhouse gases in terms of the absolute
level of emissions, the trend in emissions, or both."18 By
definition, key categories include those sources that have
the greatest contribution to the absolute level of national
emissions. In addition, when an entire time series of emission
estimates is prepared, a thorough investigation of key
categories must also account for the influence of trends of
individual source and sink categories. This analysis culls out
source and sink categories that diverge from the overall trend
in national emissions. Finally, a qualitative evaluation of key
categories is performed to capture any categories that were
not identified in either of the quantitative analyses.
! See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
1-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Box 1-2: IPCC Reference Approach
The UNFCCC reporting guidelines require countries to complete a "top-down" reference approach for estimating C02 emissions from
fossil fuel combustion in addition to their "bottom-up" sectoral methodology. This estimation method uses alternative methodologies and
different data sources than those contained in that section of the Energy chapter. The reference approach estimates fossil fuel consumption
by adjusting national aggregate fuel production data for imports, exports, and stock changes rather than relying on end-user consumption
surveys (see Annex 4 of this report). The reference approach assumes that once carbon-based fuels are brought into a national economy,
they are either saved in some way (e.g., stored in products, kept in fuel stocks, or left unoxidized in ash) or combusted, and therefore the
carbon in them is oxidized and released into the atmosphere. Accounting for actual consumption of fuels at the sectoral or sub-national
level is not required.
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, Uand-Use Change, and Forestry
(LULUCF) sector, the other analysis did not include the
UUUUCF categories.
In addition to conducting Tier 1 level and trend
assessments, a qualitative assessment of the source
categories, as described in the IPCC's Good Practice
Guidance (IPCC 2000), was conducted to capture any key
categories that were not identified by either quantitative
method. One additional key category, international bunker
fuels, was identified using this qualitative assessment.
International bunker fuels are fuels consumed for aviation
or marine international transport activities, and emissions
from these fuels are reported separately from totals in
accordance with IPCC guidelines. If these emissions were
included in the totals, bunker fuels would qualify as a key
category according to the Tier 1 approach. The amount of
uncertainty associated with estimation of emissions from
international bunker fuels also supports the qualification
of this source category as key.
Table 1-4 presents the key categories for the United
States based on the Tier 1 approach (including and excluding
LULUCF categories) using emissions data in this report,
and ranked according to their sector and global-warming
potential-weighted emissions in 2004. The table also
indicates the criteria used in identifying these categories
(i.e., level, trend, and/or qualitative assessments). Annex 1
of this report provides additional information regarding the
key categories in the United States and the methodologies
used to identify them.
1.6. Quality Assurance and Quality
Control (QA/QC)
As part of efforts to achieve its stated goals for inventory
quality, transparency, and credibility, the United States has
developed a quality assurance and quality control plan
designed to check, document, and improve the quality of
its inventory over time. QA/QC activities on the Inventory
are undertaken within the framework of the U.S. QA/QC
plan, Quality Assurance/Quality Control and Uncertainty
Management Plan for the U.S. Greenhouse Gas Inventory:
Procedures Manual for QA/QC and Uncertainty Analysis.
In particular, key attributes of the QA/QC plan
include:
• The plan includes specific detailed procedures (or
protocols) and templates (or forms) that serve to
standardize the process of documenting and archiving
information, as well as to guide the implementation
of QA/QC and the analysis of the uncertainty of the
inventory estimates.
• The plan includes 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.
• The QC process includes both Tier 1 (general) and
Tier 2 (source-specific) quality controls and checks, as
recommended by IPCC Good Practice Guidance.
• Investigations of secondary data quality and source-
specific quality checks (Tier 2 QC) are considered in
parallel and coordination with the uncertainty assessment;
the development of protocols and templates provides for
Introduction 1-11
-------
Table 1-4: Key Categories for the United States (1990-2004) Based on Tier 1 Approach
IPCC Source Category
Level Trend Level Trend
Without Without With With 2004 Emissions
Gas LULUCF LULUCF LULUCF LULUCF dual" (Tg C02 Eq.)
Energy
C02 Emissions from Stationary Combustion-
Coal
C02 Emissions from Mobile Combustion: Road & Other
C02 Emissions from Stationary Combustion—
Gas
C02 Emissions from Stationary Combustion—
C02
C02
CO,
2,027.0
1,621.5
1,153.8
Oil
C02 Emissions from Mobile Combustion: Aviation
CH4 Fugitive Emissions from Natural Gas Operations
C02 Emissions from Non-Energy Use of Fuels
International Bunker Fuels"
CH4 Fugitive Emissions from Coal Mining and
Handling
C02 Emissions from Mobile Combustion: Marine
N20 Emissions from Mobile Combustion: Road & Other
CH4 Fugitive Emissions from Oil Operations
Industrial Processes
Emissions from Substitutes for Ozone Depleting
Substances
C02 Emissions from Iron and Steel Production
C02 Emissions from Cement Production
C02 Emissions from Ammonia Manufacture and
Urea Application
SF6 Emissions from Electrical Equipment
HFC-23 Emissions from HCFC-22 Manufacture
N20 Emissions from Adipic Acid Production
PFC Emissions from Aluminum Production
Agriculture
Direct N20 Emissions from Agricultural Soils
CH4 Emissions from Enteric Fermentation in
Domestic Livestock
Indirect N20 Emissions from Nitrogen Used in
Agriculture
CH4 Emissions from Manure Management
Waste
CH4 Emissions from Solid Waste Disposal Sites
CH4 Emissions from Wastewater Handling
C02 Emissions from Waste Incineration
Land Use, Land Use Change, and Forestry
C02 Emissions from Forest Land Remaining
Forest Land
C02 Emissions from Settlements Remaining
Settlements
C02 Emissions from Cropland Remaining
Cropland
Subtotal Without LULUCF
Total Emissions Without LULUCF'
Percent of Total Without LULUCF
Subtotal With LULUCF
Total Emissions With LULUCF
Percent of Total With LULUCF
C02 / / /
rn xxx
L*U2 v v v
CH4
-------
more structured communication and integration with
the suppliers of secondary information.
• The plan contains record-keeping provisions to track
which procedures have been followed, and the results
of the QA/QC and uncertainty analysis, and contains
feedback mechanisms for corrective action based on
the results of the investigations, thereby providing for
continual data quality improvement and guided research
efforts.
• The plan is designed so that QA/QC procedures
are implemented throughout the whole
inventory-development process—from initial data
collection, through preparation of the emission
estimates, to publication of the Inventory.
• The plan includes a schedule for multi-year
implementation.
• The plan promotes and involves coordination and
interaction within the EPA, across Federal agencies
and departments, state government programs, and
research institutions and consulting firms involved in
supplying data or preparing estimates for the inventory.
The QA/QC plan itself is intended to be revised and
reflect new information that becomes available as the
program develops, methods are improved, or additional
supporting documents become necessary.
In addition, based on the national QA/QC plan for
the Inventory, source-specific QA/QC plans have been
developed for a number of sources. These plans follow the
procedures outlined in the national QA/QC plan, tailoring
the procedures to the specific text and spreadsheets of the
individual sources. For the current Inventory, source-specific
plans have been developed and implemented for the majority
of sources within the Energy and Industrial Process sectors.
Throughout this inventory, a minimum of a Tier 1 QA/QC
analysis has been undertaken. Where QA/QC activities for
a particular source go beyond the minimum Tier 1 level,
further explanation is provided within the respective source
category text.
The quality checking and control activities described
in the U.S. QA/QC plan occur throughout the inventory
process; QA/QC is not separate from, but is an integral part
of, preparing the inventory. Quality control—in the form of
both good practices (such as documentation procedures) and
checks on whether good practices and procedures are being
followed—is applied at every stage of inventory development
and document preparation. In addition, quality assurance
occurs at two stages—an expert review and a public review.
While both phases can significantly contribute to inventory
quality, the public review phase is also essential for promoting
the openness of the inventory development process and the
transparency of the inventory data and methods.
QA/QC procedures guide the process of ensuring
inventory quality by describing data and methodology
checks, developing processes governing peer review and
public comments, and developing guidance on conducting
an analysis of the uncertainty surrounding the emission
estimates. The QA/QC procedures also include feedback
loops and provide for corrective actions that are designed to
improve the inventory estimates over time.
1.7. Uncertainty Analysis of
Emission Estimates
Uncertainty estimates are an essential element of a
complete and transparent emissions inventory. Uncertainty
information is not intended to dispute the validity of the
inventory estimates, but to help prioritize efforts to improve
the accuracy of future inventories and guide future decisions
on methodological choice. While the U.S. Inventory calculates
its emission estimates with the highest possible accuracy,
uncertainties are associated to a varying degree with the
development of emission estimates for any inventory. Some
of the current estimates, such as those for CO2 emissions
from energy-related activities and cement processing, are
considered to have minimal uncertainty associated with them.
For some other categories of emissions, however, a lack of
data or an incomplete understanding of how emissions are
generated increases the uncertainty surrounding the estimates
presented. Despite these uncertainties, the UNFCCC
reporting guidelines follow the recommendation in the
1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997)
and require that countries provide single point estimates of
uncertainty for each gas and emission or removal source
category. Within the discussion of each emission source,
specific factors affecting the uncertainty associated with the
estimates are discussed.
Additional research in the following areas could help
reduce uncertainty in the U.S. Inventory:
Introduction 1-13
-------
• Incorporating excluded emission sources. Quantitative
estimates for some of the sources and sinks of greenhouse
gas emissions are not available at this time. In particular,
emissions from some land-use activities and industrial
processes are not included in the Inventory either
because data are incomplete or because methodologies
do not exist for estimating emissions from these source
categories. See Annex 5 of this report for a discussion
of the sources of greenhouse gas emissions and sinks
excluded from this report.
• Improving the accuracy of emission factors. Further
research is needed in some cases to improve the accuracy
of emission factors used to calculate emissions from a
variety of sources. For example, the accuracy of current
emission factors applied to CH4 and N2O emissions from
stationary and mobile combustion is highly uncertain.
• Collecting detailed activity data. Although methodologies
exist for estimating emissions for some sources,
problems arise in obtaining activity data at a level
of detail in which aggregate emission factors can be
applied. For example, the ability to estimate emissions
of SF6 from electrical transmission and distribution is
limited due to a lack of activity data regarding national
SF6 consumption or average equipment leak rates.
The overall uncertainty estimate for the U.S. greenhouse
gas emissions inventory was developed using the IPCC
Tier 2 uncertainty estimation methodology. A preliminary
estimate of the overall quantitative uncertainty is shown
below, in Table 1-5.
The IPCC provides good practice guidance on two
approaches—Tier 1 and Tier 2—to estimating uncertainty
for individual source categories. Tier 2 uncertainty analysis,
employing the Monte Carlo Stochastic Simulation technique,
was applied wherever data and resources permitted; further
explanation is provided within the respective source category
text. Consistent with the IPCC Good Practice Guidance, over
a multi-year timeframe, the United States expects to continue
to improve the uncertainty estimates presented in this report
and add a quantitative estimates of uncertainty for the one
remaining source for which a quantitative estimate does not
exist—CO2 from Natural Gas Flaring.
Emissions calculated for the U.S. Inventory reflect
current best estimates; in some cases, however, estimates
are based on approximate methodologies, assumptions, and
incomplete data. As new information becomes available in
the future, the United States will continue to improve and
revise its emission estimates. See Annex 7 of this report for
further details on the U.S. process for estimating uncertainties
associated with emission estimates and for a more detailed
discussion of the limitations of the current analysis and plans
for improvement.
1.8. Completeness
This report, along with its accompanying CRP 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 2004. Although this report
is intended to be comprehensive, certain sources have been
identified yet excluded from the estimates presented for
various reasons. Generally speaking, sources not accounted
for in this inventory are excluded due to data limitations or
a lack of thorough understanding of the emission process.
The United States is continually working to improve upon the
understanding of such sources and seeking to find the data
required to estimate related emissions. As such improvements
are made, new emission sources are quantified and included
in the Inventory. For a complete list of sources excluded, see
Annex 5 of this report.
1.9. Organization of Report
In accordance with the Revised 1996 IPCC Guidelines
for National Greenhouse Gas Inventories (IPCC/UNEP/
OECD/IEA 1997), and the 2003 UNFCCC Guidelines on
Reporting and Review (UNFCCC 2003), this Inventory of
U.S. Greenhouse Gas Emissions and Sinks is segregated
into six sector-specific chapters, listed below in Table 1 -6. In
addition, chapters on Trends in Greenhouse Gas Emissions
and Other information to be considered as part of the U.S.
Inventory submission are included.
Within each chapter, emissions are identified by
the anthropogenic activity that is the source or sink
of the greenhouse gas emissions being estimated (e.g.,
Coal Mining).
Overall, the following organizational structure is consistently
applied throughout this report:
Chapter/IPCC Sector: Overview of emission trends for each
IPCC-defined sector.
1-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 1-5. Estimated Overall Inventory Quantitative Uncertainty (Tg C02 Eq. and Percent)
Gas
C02
CH4
N20
PFC, HFC&SF6d
Total
2004 Emission
Estimate
(Tg C02 Eq.)
5,988.0
556.7
386.7
143.2
7,074.7
Uncertainty Range Relative to Emission Estimate3
(Tg C02
Lower Bound6
5,920.5
495.3
235.1
130.1
6,966.8
Eq.)
Upper Bound6
6,329.8
620.2
571.5
164.8
7,518.9
(%)
Lower Bound6
-1.1%
-11.0%
-39.2%
-9.2%
-1.5%
Upper Bound6
5.7%
11.4%
47.7%
15.1%
6.3%
Mean"
6,120.6
556.5
403.1
147.2
7,245.2
Standard
Deviation
(Tg C02 Eq.)
105.3
31.8
88.3
8.9
142.2
a Range of emission estimates for a 95 percent confidence interval.
b Mean value indicates the arithmetic average of the simulated emission estimates; Standard deviation indicates the extent of deviation of the simulated
values from the mean.
c The low and high estimates for total emissions were separately calculated through simulations and, hence, the low and high emission estimates for the
sub-source categories do not add up to total emissions.
11 The overall uncertainty estimate did not take into account the uncertainty in the GWP values for CH4, N20 and high GWP gases used in the inventory
emission calculations for 2004.
Table 1-6: IPCC Sector Descriptions
Chapter/IPCC Sector
Activities Included
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Emissions of all greenhouse gases resulting from stationary and mobile energy activities
including fuel combustion and fugitive fuel emissions.
By-product or fugitive emissions of greenhouse gases from industrial processes not directly
related to energy activities such as fossil fuel combustion.
Emissions, of primarily NMVOCs, resulting from the use of solvents and N20 from product
usage.
Anthropogenic emissions from agricultural activities except fuel combustion, which is
addressed under Energy.
Land Use, Land-Use Change, and Forestry Emissions and removals of C02 from forest management, other land-use activities, and
land-use change.
Waste Emissions from waste management activities.
Source: (IPCC/UNEP/OECD/IEA 1997)
Source Category: Description of source pathway and
emission trends.
Methodology: Description of analytical methods
employed to produce emission estimates and
identification of data references, primarily for activity
data and emission factors.
Uncertainty: A discussion and quantification of the
uncertainty in emission estimates and a discussion
of time-series consistency.
QA/QC and Verification: A discussion on steps taken
to QA/QC and verify the emission estimates, where
beyond the overall U.S. QA/QC plan, and any key
findings.
Recalculations: A discussion of any data
or methodological changes that necessitate a
recalculation of previous years' emission estimates,
and the impact of the recalculation on the emission
estimates, if applicable.
Planned Improvements: A discussion on any source
specific planned improvements, if applicable.
Special attention is given to CO2 from fossil fuel
combustion relative to other sources because of its share of
emissions and its dominant influence on emission trends.
For example, each energy consuming end-use sector (i.e.,
residential, commercial, industrial, and transportation),
as well as the electricity generation sector, is described
individually. Additional information for certain source
categories and other topics is also provided in several
Annexes listed in Table 1-7.
Introduction 1-15
-------
Table 1-7: List of Annexes
ANNEX 1 Key Category Analysis
ANNEX 2 Methodology and Data for Estimating C02 Emissions from Fossil Fuel Combustion
2.1. Methodology for Estimating Emissions of C02 from Fossil Fuel Combustion
2.2. Methodology for Estimating the Carbon Content of Fossil Fuels
2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil Fuels
ANNEX 3 Methodological Descriptions for Additional Source or Sink Categories
3.1. Methodology for Estimating Emissions of CH4, N20, and Indirect Greenhouse Gases from Stationary Combustion
3.2. Methodology for Estimating Emissions of CH4, N20, and Indirect Greenhouse Gases from Mobile Combustion and
Methodology for and Supplemental Information on Transportation-Related Greenhouse Gas Emissions
3.3. Methodology for Estimating CH4 Emissions from Coal Mining
3.4. Methodology for Estimating CH4 Emissions from Natural Gas Systems
3.5. Methodology for Estimating CH4 Emissions from Petroleum Systems
3.6. Methodology for Estimating C02 and N20 Emissions from Municipal Solid Waste Combustion
3.7. Methodology for Estimating Emissions from International Bunker Fuels used by the U.S. Military
3.8. Methodology for Estimating HFC and RFC Emissions from Substitution of Ozone Depleting Substances
3.9. Methodology for Estimating CH4 Emissions from Enteric Fermentation
3.10. Methodology for Estimating CH4 and N20 Emissions from Manure Management
3.11. Methodology for Estimating N20 Emissions from Agricultural Soil Management
3.12. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands
3.13. Methodology for Estimating Net Changes in Carbon Stocks in Mineral and Organic Soils
3.14. Methodology for Estimating CH4 Emissions from Landfills
ANNEX 4 IPCC Reference Approach for Estimating C02 Emissions from Fossil Fuel Combustion
ANNEX 5 Assessment of the Sources and Sinks of Greenhouse Gas Emissions Excluded
ANNEX 6 Additional Information
6.1. Global Warming Potential Values
6.2. Ozone Depleting Substance Emissions
6.3. Sulfur Dioxide Emissions
6.4. Complete List of Source Categories
6.5. Constants, Units, and Conversions
6.6. Abbreviations
6.7. Chemical Formulas
ANNEX 7 Uncertainty
7.1. Overview
7.2. Methodology and Results
7.3. Uncertainty Estimation as a Process
7.4. Planned Improvements
1-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
2. Trends in Greenhouse Gas
Emissions
2.1. Recent Trends in U.S. Greenhouse Gas Emissions
In 2004, total U.S. greenhouse gas emissions were 7,074.4 teragrams of carbon dioxide equivalents (Tg C02 Eq.).1
Overall, total U.S. emissions have risen by 15.8 percent from 1990 to 2004, while the U.S. gross domestic product
has increased by 51 percent over the same period (BEA 2005). Emissions rose from 2003 to 2004, increasing by
1.7 percent (115.3 Tg C02 Eq.). The following factors were primary contributors to this increase: (1) robust economic
growth in 2004, leading to increased demand for electricity and fossil fuels, (2) expanding industrial production in energy-
intensive industries, also increasing demand for electricity and fossil fuels, and (3) increased travel, requiring higher rates
of consumption of petroleum fuels.2 Figure 2-1 through Figure 2-3 illustrate the overall trends in total U.S. emissions by
gas, annual changes, and absolute changes since 1990.
As the largest source of U.S. greenhouse gas emissions, carbon dioxide (CO^ from fossil fuel combustion has accounted
for approximately 80 percent of global warming potential (GWP) weighted emissions since 1990, growing slowly from 77
percent of total GWP-weighted emissions in 1990 to 80 percent in 2003 and 2004. Emissions from this source category grew by
20.4 percent (960.0 Tg C02 Eq.) from 1990 to 2004 and were
responsible for most of the increase in national emissions
during this period. From 2003 to 2004, these emissions
increased by 85.5 Tg C02 Eq. (1.5 percent), slightly greater
than the source's average annual growth rate of 1.3 percent
from 1990 through 2004. Historically, changes in emissions
from fossil fuel combustion have been the dominant factor
affecting U.S. emission trends.
Changes in C02 emissions from fossil fuel combustion
are influenced by many long-term and short-term factors,
including population and economic growth, energy
price fluctuations, technological changes, and seasonal
temperatures. On an annual basis, the overall consumption
of fossil fuels in the United States generally fluctuates in
Figure 2-1
U.S. Greenhouse Gas Emissions by Gas
MFCs, PFCs, & SF6
Nitrous Oxide
Methane
Carbon Dioxide
8,000-
7,000-
6,000-
5 5,000-
° 4,000-
"~ 3,000-
2,000-
1,000-
o-'
1 Estimates are presented in units of teragrams of carbon dioxide equivalent (Tg C02 Eq.), which weight each gas by its Global Warming Potential, or
GWP, value. (See section on Global Warming Potentials, Chapter 1.)
2 See the following section for an analysis of emission trends by general economic sector.
Trends in Greenhouse Gas Emissions 2-1
-------
Figure 2-2
Figure 2-3
Annual Percent Change in U.S. Greenhouse Gas Emissions
Cumulative Change in U.S. Greenhouse Gas
Emissions Relative to 1990
1,000 -
800 -
S 600 '
o1
u
ff 400 -
200 -
0
-37
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 longer-term, energy consumption patterns
respond to changes that affect the scale of consumption (e.g.,
population, number of cars, and size of houses), the efficiency
with which energy is used in equipment (e.g., cars, power
plants, steel mills, and light bulbs) and consumer behavior
(e.g., walking, bicycling, or telecommuting to work instead
of driving).
Energy-related C02 emissions also depend on the type of
fuel or energy consumed and its carbon intensity. Producing
a unit of heat or electricity using natural gas instead of coal,
for example, can reduce the C02 because of the lower carbon
content of natural gas. Table 2-1 shows annual changes in
emissions during the last five years for coal, petroleum, and
natural gas in selected sectors.
In 2001, economic growth in the United States slowed
considerably for the second time since 1990, contributing
to a decrease in C02 emissions from fossil fuel combustion,
also for the second time since 1990. A significant reduction
in industrial output contributed to weak economic growth,
primarily in manufacturing, and led to lower emissions from
the industrial sector. Several other factors also played a role
in this decrease in emissions. Warmer winter conditions
compared to 2000, along with higher natural gas prices,
reduced demand for heating fuels. Additionally, nuclear
Table 2-1: Annual Change in C02 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors
(Tg C02 Eq. and Percent)
Sector
Electricity Generation
Electricity Generation
Electricity Generation
Transportation3
Residential
Commercial
Industrial
Industrial
All Sectors"
Fuel Type
Coal
Natural Gas
Petroleum
Petroleum
Natural Gas
Natural Gas
Coal
Natural Gas
All Fuels"
2000to
-50.7
8.2
10.5
-11.7
-10.2
-6.9
-1.1
-36.8
-46.8
2001
-3%
3%
12%
-1%
-4%
-4%
-1%
-8%
-1%
2001
3.8
16.1
-23.7
42.0
6.6
5.9
-9.7
6.3
14.9
to 2002
0%
6%
-23%
2%
3%
4%
-8%
1%
0%
2002to
37.5
-28.0
19.2
2.0
11.4
4.6
1.4
-15.0
69.3
2003
2%
-9%
25%
0%
4%
3%
1%
-3%
1%
2003 to
9.9
18.2
0.3
54.3
-11.4
-12.7
-0.7
12.3
85.5
2004
1%
7%
0%
3%
-4%
-7%
-1%
3%
2%
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table.
2-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
facilities operated at a very high capacity, offsetting electricity
produced from fossil fuels. Since there are no greenhouse
gas emissions associated with electricity production from
nuclear plants, this substitution reduces the overall carbon
intensity of electricity generation.
Emissions from fuel combustion resumed a modest
growth in 2002, slightly less than the average annual growth
rate since 1990. There were a number of reasons behind this
increase. The U.S. economy experienced moderate growth,
recovering from weak conditions in 2001. Prices for fuels
remained at or below 2001 levels; the cost of natural gas,
motor gasoline, and electricity were all lower—triggering an
increase in demand for fuel. In addition, the United States
experienced one of the hottest summers on record, causing a
significant increase in electricity use in the residential sector
as the use of air-conditioners increased. Partially offsetting
this increased consumption of fossil fuels, however, were
increases in the use of nuclear and renewable fuels. Nuclear
facilities operated at the highest capacity on record in 2002.
Furthermore, there was a considerable increase in the use
of hydroelectric power in 2002 after a very low output the
previous year.
Emissions from fuel combustion continued growing in
2003, at about the average annual growth rate since 1990. A
number of factors played a major role in the magnitude of this
increase. The U.S. economy experienced moderate growth
from 2002, causing an increase in the demand for fuels. The
price of natural gas escalated dramatically, causing some
electric power producers to switch to coal, which remained
at relatively stable prices. Colder winter conditions brought
on more demand for heating fuels, primarily in the residential
sector. Though a cooler summer partially offset demand for
electricity as the use of air-conditioners decreased, electricity
consumption continued to increase in 2003. The primary
drivers behind this trend were the growing economy and the
increase in U.S. housing stock. Use of nuclear and renewable
fuels remained relatively stable. Nuclear capacity decreased
slightly, and for the first time since 1997. Use of renewable
fuels rose slightly due to increases in the use of hydroelectric
power and biofuels.
From 2003 to 2004, these emissions increased at a
rate slightly higher than the average growth rate since
1990. A number of factors played a major role in the
magnitude of this increase. A primary reason behind this
trend was strong growth in the U.S. economy and industrial
production, particularly in energy-intensive industries,
causing an increase in the demand for electricity and
fossil fuels. Demand for travel was also higher, causing
an increase in petroleum consumed for transportation. In
contrast, the warmer winter conditions led to decreases in
demand for heating fuels, principally natural gas, in both
the residential and commercial sectors. Moreover, much of
the increased electricity demanded was generated by natural
gas consumption and nuclear power, which moderated the
increase in C02 emissions from electricity generation. Use
of renewable fuels rose very slightly due to increases in the
use biofuels.
Other significant trends in emissions from additional
source categories over the fourteen-year period from 1990
through 2004 included the following:
• C02 emissions from waste combustion increased by 8.4
Tg C02 Eq. (77 percent), as the volume of plastics and
other fossil carbon-containing materials in municipal
solid waste grew.
• Net C02 sequestration from land use, land-use change,
and forestry decreased by 130.3 Tg C02 Eq. (14
percent), primarily due to a decline in the rate of net
carbon accumulation in forest carbon stocks. This
decline largely resulted from a decrease in the estimated
rate of forest soil sequestration caused by a slowing rate
of increase in forest area after 1997.
• Methane (CH4) emissions from coal mining declined by
25.6 Tg C02 Eq. (31 percent) from 1990 to 2004, as a
result of the mining of less gassy coal from underground
mines and the increased use of CH4 collected from
degasification systems.
• From 1990 to 2004, nitrous oxide (N20) emissions from
mobile combustion decreased by 1 percent. However,
from 1990 to 1998 emissions increased by 26 percent,
due to control technologies that reduced CH4 emissions
while increasing N20 emissions. Since 1998, new
control technologies have led to a steady decline in N20
from this source.
• Emissions resulting from the substitution of ozone
depleting substances (ODS, e.g., chlorofluorocarbons
[CFCs]) have increased dramatically from small amounts
in 1990 to 102.9 Tg C02 Eq. in 2004. These emissions
have been increasing as phase-outs of ODS required
under the Montreal Protocol come into effect.
Trends in Greenhouse Gas Emissions 2-3
-------
Box 2-1: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data
Total emissions can be compared to other economic and social indices to highlight changes over time. These comparisons include: (1)
emissions per unit of aggregate energy consumption, because energy-related activities are the largest sources of emissions; (2) emissions
per unit of fossil fuel consumption, because almost all energy-related emissions involve the combustion of fossil fuels; (3) emissions per
unit of electricity consumption, because the electric power industry—utilities and nonutilities combined—was the largest source of U.S.
greenhouse gas emissions in 2004; (4) emissions per unit of total gross domestic product as a measure of national economic activity; or
(5) emissions per capita.
Table 2-2 provides data on various statistics related to U.S. greenhouse gas emissions normalized to 1990 as a baseline year. Greenhouse
gas emissions in the United States have grown at an average annual rate of 1.1 percent since 1990. This rate is slower than that for total
energy or fossil fuel consumption and much slower than that for either electricity consumption or overall gross domestic product. Total U.S.
greenhouse gas emissions have also grown more slowly than national population since 1990 (see Figure 2-4). Overall, global atmospheric
C02 concentrations—a function of many complex anthropogenic and natural processes—are increasing at 0.4 percent per year.
Table 2-2: Recent Trends in Various U.S. Data (Index 1990 = 100) and Global Atmospheric C02 Concentration
Variable
Greenhouse Gas Emissions3
Energy Consumption"
Fossil Fuel Consumption"
Electricity Consumption"
GDP<=
Population
Atmospheric C02 Concentration6
1991
99
100
99
102
100
101
100
1998
111
112
113
121
127
110
| 103
1999
111
114
114
123
133
112
104
2000
114
117
117
127
138
113
104
2001
112
114
115
125
139
114
105
2002
113
116
116
128
141
115
105
2003
114
116
117
129
145
116
106
2004
116
118
118
131
151
117
106
Growth
Rate'
1.1%
1.2%
1.2%
2.0%
3.0%
1.1%
0.4%
a GWP weighted values
b Energy content weighted values (EIA 2004a)
c Gross Domestic Product in chained 2000 dollars (BEA 2005)
" (U.S. Census Bureau 2005)
e Hofmann (2004)
f Average annual growth rate
Figure 2-4
U.S. Greenhouse Gas Emissions Per Capita
and Per Dollar of Gross Domestic Product
160
150
_
= 130
s 110 1
I100
I 90
80
70
60
50
Real GDP
Population
Emissions
per capita
Emissions per $GDP
i— CM co
Source: BEA (2005), U.S. Census Bureau (2005), and emission estimates in this report.
2-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
• The increase in ODS emissions is offset substantially
by decreases in emission of hydrofluorocarbons (HFCs),
perfluorocarbons (PFCs), and sulfur hexafluoride
(SF6) from other sources. Emissions from aluminum
production decreased by 85 percent (15.6 Tg C02
Eq.) from 1990 to 2004, due to both industry emission
reduction efforts and lower domestic aluminum
production. Emissions from the production of HCFC-
22 decreased by 55 percent (19.4 Tg C02 Eq.) from
1990 to 2004, due to a steady decline in the emission
rate of HFC-23 (i.e., the amount of HFC-23 emitted
per kilogram of HCFC-22 manufactured) and the use
of thermal oxidation at some plants to reduce HFC-23
emissions. Emissions from electric power transmission
and distribution systems decreased by 52 percent (14.8
Tg C02 Eq.) from 1990 to 2004, primarily because of
higher purchase prices for SF6 and efforts by industry
to reduce emissions.
Overall, from 1990 to 2004, total emissions of C02
increased by 982.7 Tg C02 Eq. (20 percent), while CH4 and
N20 emissions decreased by 61.3 Tg C02 Eq. (10 percent)
and 8.2 Tg C02 Eq. (2 percent), respectively. During the
same period, aggregate weighted emissions of HFCs, PFCs,
and SF6 rose by 52.2 Tg C02 Eq. (58 percent). Despite being
emitted in smaller quantities relative to the other principal
greenhouse gases, emissions of HFCs, PFCs, and SF6 are
significant because many of them have extremely high global
warming potentials and, in the cases of PFCs and SF6, long
atmospheric lifetimes. Conversely, U.S. greenhouse gas
emissions were partly offset by carbon sequestration in
forests, trees in urban areas, agricultural soils, and landfilled
yard trimmings, which was estimated to be 11 percent of
total emissions in 2004.
As an alternative, emissions of all gases can be totaled
for each of the Intergovernmental Panel on Climate Change
(IPCC) sectors. Over the fourteen year period of 1990 to
2004, total emissions in the Energy, Industrial Processes,
Agriculture, and Solvent and Other Product Use sectors
climbed by 959.9 TgC02Eq. (19 percent), 19.5TgC02Eq.
(6 percent), 0.6 Tg C02 Eq. (less than 1 percent), and 0.5 Tg
C02 Eq. (11 percent), respectively, while emissions from the
Waste sector decreased 16.2 Tg C02 Eq. (8 percent). Over
the same period, estimates of net carbon sequestration in the
Land Use, Land-Use Change, and Forestry sector declined
by 130.3 Tg C02 Eq. (14 percent).
Table 2-3 summarizes emissions and sinks from all U.S.
anthropogenic sources in weighted units of Tg C02 Eq., while
unweighted gas emissions and sinks in gigagrams (Gg) are
provided in Table 2-4. Alternatively, emissions and sinks are
aggregated by sector/chapter in Table 2-5 and Figure 2-5.
Energy
Energy-related activities, primarily fossil fuel combustion,
accounted for the vast majority of U.S. C02 emissions for the
period of 1990 through 2004. In 2004, approximately 86 percent
of the energy consumed in the United States was produced
through the combustion of fossil fuels. The remaining 14 percent
came from other energy sources such as hydropower, biomass,
nuclear, wind, and solar energy (see Figure 2-6 and Figure
2-7). A discussion of specific trends related to CO2 as well as
other greenhouse gas emissions from energy consumption is
presented below. Energy related activities are also responsible
for CH4 and N20 emissions (39 percent and 15 percent of total
U.S. emissions of each gas, respectively). Table 2-6 presents
greenhouse gas emissions from the Energy sector, by source
and gas.
Fossil Fuel Combustion (5,656.6 Tg C02 Eq.)
As fossil fuels are combusted, the carbon stored in them
is emitted almost entirely as C02. The amount of carbon
in fuels per unit of energy content varies significantly by
fuel type. For example, coal contains the highest amount of
carbon per unit of energy, while petroleum and natural gas
have about 25 percent and 45 percent less carbon than coal,
respectively. From 1990 through 2004, petroleum supplied
the largest share of U.S. energy demands, accounting for
an average of 39 percent of total energy consumption with
natural gas and coal accounting for 24 and 23 percent of
total energy consumption, respectively. Petroleum was
consumed primarily in the transportation end-use sector, the
vast majority of coal was used by electric power generators,
and natural gas was consumed largely in the industrial and
residential end-use sectors.
Emissions of C02 from fossil fuel combustion increased
at an average annual rate of 1.3 percent from 1990 to 2004.
The fundamental factors influencing this trend include (1) a
generally growing domestic economy over the last 14 years,
and (2) significant growth in emissions from transportation
activities and electricity generation. Between 1990 and 2004,
C02 emissions from fossil fuel combustion increased from
Trends in Greenhouse Gas Emissions 2-5
-------
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Iron and Steel Production
Cement Manufacture
Municipal Solid Waste Combustion
Ammonia Manufacture and Urea Application
Lime Manufacture
Limestone and Dolomite Use
Natural Gas Flaring
Aluminum Production
Soda Ash Manufacture and Consumption
Petrochemical Production
Titanium Dioxide Production
Phosphoric Acid Production
Ferroalloy Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Consumption
Net CO 2 Flux from Land Use, Land-Use
Change, and Forestry3
International Bunker Fuels13
Wood Biomass and Ethanol Consumption13
CH4
Landfills
Natural Gas Systems
Enteric Fermentation
Coal Mining
Manure Management
Wastewater Treatment
Petroleum Systems
Rice Cultivation
Stationary Combustion
Abandoned Underground Coal Mines
Mobile Combustion
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural Residues
Silicon Carbide Production
International Bunker Fuels13
N20
Agricultural Soil Management
Mobile Combustion
Manure Management
Nitric Acid Production
Human Sewage
Stationary Combustion
Settlements Remaining Settlements
Adipic Acid Production
N20 Product Usage
Municipal Solid Waste Combustion
Field Burning of Agricultural Residues
Forest Land Remaining Forest Land
International Bunker Fuels13
MFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing
Total
Net Emissions (Sources and Sinks)
1990
5,005.3
4,696.6
117.2
85.0
33.3
10.9
19.3
11.2
5.5
5.8
7.0
4.1
2.2
1.3
1.5
2.0
0.9
0.9
0.3
0.1
(910.4)
113.5
216.7
618.1
172.3
126.7
117.9
81.9
31.2
24.8
34.4
7.1
7.9
6.0
4.7
1.2
1.3
0.7
+
0.2
394.9
266.1
43.5
16.3
17.8
12.9
12.3
5.6
15.2
4.3
0.5
0.4
0.1
1.0
90.8
0.4
35.0
28.6
2.9
18.4
5.4
6,109.0
5,198.6
1998
5,620.2
5,271.8
152.8
67.7
39.2
17.1
21.9
13.9
7.4
6.6
6.4
4.3
3.0
1.8
1.6
2.0
0.9
1.1
0.3
0.2
(744.0)
114.6
217.2
579.5
144.4
125.4
116.7
62.8
38.8
32.6
29.7
7.9
6.8
6.9
3.8
1.7
1.2
0.8
+
0.2
440.6
301.1
54.8
17.4
20.9
14.9
13.4
6.2
6.0
4.8
0.4
0.5
0.4
1.0
133.4
54.5
40.1
16.7
7.1
9.1
5.8
6,773.7
6,029.6
1999
5,695.0
5,342.4
160.6
63.8
40.0
17.6
20.6
13.5
8.1
6.9
6.5
4.2
3.1
1.9
1.5
2.0
0.8
1.1
0.3
0.1
(765.7)
105.2
222.3
569.0
141.6
121.7
116.8
58.9
38.1
33.6
28.5
8.3
7.0
6.9
3.6
1.7
1.2
0.8
+
0.1
419.4
281.2
54.1
17.4
20.1
15.4
13.4
6.2
5.5
4.8
0.4
0.4
0.5
0.9
131.5
62.8
30.4
16.1
7.2
9.0
6.0
6,814.9
6,049.2
2000
5,864.5
5,533.7
140.7
65.3
41.2
17.9
19.6
13.3
6.0
5.8
6.2
4.2
3.0
1.9
1.4
1.7
1.0
1.1
0.3
0.1
(759.5)
101.4
226.8
566.9
139.0
126.7
115.6
56.3
38.0
34.3
27.8
7.5
7.3
7.2
3.5
1.7
1.2
0.8
+
0.1
416.2
278.2
53.1
17.8
19.6
15.5
13.9
6.0
6.0
4.8
0.4
0.5
0.4
0.9
134.7
71.2
29.8
15.3
6.3
9.0
3.2
6,982.3
6,222.8
2001
5,795.2
5,486.9
131.0
57.8
41.4
18.6
16.7
12.8
5.7
6.1
4.5
4.1
2.8
1.9
1.3
1.3
0.8
1.0
0.3
0.1
(768.0)
97.8
200.5
560.3
136.2
125.6
114.6
55.5
38.9
34.7
27.4
7.6
6.6
6.6
3.3
1.4
1.1
0.8
+
0.1
412.8
282.9
50.0
18.1
15.9
15.6
13.5
5.8
4.9
4.8
0.5
0.5
0.4
0.9
124.9
78.6
19.8
15.3
4.5
4.0
2.6
6,893.1
6,125.1
2002
5,815.9
5,501.8
136.5
54.6
42.9
18.9
18.5
12.3
5.9
6.2
4.6
4.1
2.9
2.0
1.3
1.2
1.0
0.9
0.3
0.1
(768.6)
89.5
194.4
559.8
139.8
125.4
114.7
52.5
39.3
35.8
26.8
6.8
6.2
6.0
3.2
1.5
1.0
0.7
+
0.1
407.4
277.8
47.5
18.0
17.2
15.6
13.2
6.0
5.9
4.8
0.5
0.4
0.4
0.8
132.7
86.2
19.8
14.5
4.4
5.3
2.6
6,915.8
6,147.2
2003
5,877.7
5,571.1
133.5
53.3
43.1
19.4
15.3
13.0
4.7
6.1
4.6
4.1
2.8
2.0
1.4
1.2
1.3
0.5
0.3
0.1
(774.8)
84.1
202.1
564.4
142.4
124.7
115.1
54.8
39.2
36.6
25.9
6.9
6.5
5.8
3.0
1.5
1.0
0.8
+
0.1
386.1
259.2
44.8
17.5
16.7
15.8
13.6
6.2
6.2
4.8
0.5
0.4
0.4
0.8
131.0
93.5
12.3
14.0
4.3
3.8
3.0
6,959.1
6,184.3
2004
5,988.0
5,656.6
153.4
51.3
45.6
19.4
16.9
13.7
6.7
6.0
4.3
4.2
2.9
2.3
1.4
1.3
1.2
0.5
0.3
0.1
(780. 1)
94.5
211.2
556.7
140.9
118.8
112.6
56.3
39.4
36.9
25.7
7.6
6.4
5.6
2.9
1.6
1.0
0.9
+
0.1
386.7
261.5
42.8
17.7
16.6
16.0
13.7
6.4
5.7
4.8
0.5
0.5
0.4
0.9
143.0
103.3
15.6
13.8
4.7
2.8
2.7
7,074.4
6,294.3
+ Does not exceed 0.05 Tg C02 Eq.
a The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions
total. Parentheses indicate negative values or sequestration.
b Emissions from International Bunker Fuels and Wood Biomass and Ethanol Consumption are not included in totals.
Note: Totals may not sum due to independent rounding.
2-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 2-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Iron and Steel Production
Cement Manufacture
Municipal Solid Waste Combustion
Ammonia Manufacture and Urea Application
Lime Manufacture
Limestone and Dolomite Use
Natural Gas Flaring
Aluminum Production
Soda Ash Manufacture and Consumption
Petrochemical Production
Titanium Dioxide Production
Phosphoric Acid Production
Ferroalloy Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Consumption
Net CO 2 Flux from Land Use, Land-Use
Change, and Forestry3
International Bunker Fuels"
Wood Biomass and Ettiano! Consumption"
CH4
Landfills
Natural Gas Systems
Enteric Fermentation
Coal Mining
Manure Management
Wastewater Treatment
Petroleum Systems
Rice Cultivation
Stationary Combustion
Abandoned Underground Coal Mines
Mobile Combustion
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural Residues
Silicon Carbide Production
International Bunker Fuels"
N20
Agricultural Soil Management
Mobile Combustion
Manure Management
Nitric Acid Production
Human Sewage
Stationary Combustion
Settlements Remaining Settlements
Adipic Acid Production
N20 Product Usage
Waste Combustion
Field Burning of Agricultural Residues
Forest Land Remaining Forest Land
International Bunker Fuels"
MFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing11
S02
NOX
CO
NMVOCs
1990
5,005,255
4,696,571
117,168
85,023
33,278
10,919
19,306
11,242
5,533
5,805
7,045
4,141
2,221
1,308
1,529
1,980
860
939
285
100
(910,373)
1 13,503
216,702
29,432
8,206
6,034
5,612
3,900
1,484
1,180
1,640
339
374
286
224
56
63
33
1
8
1,274
858
140
52
58
42
40
18
49
14
2
1
+
3
M
M
3
1
M
M
+
20,936
22,860
130,580
20,937
1998
5,620,176
5,271,819
152,800
67,689
39,218
17,094
21,934
13,919
7,449
6,566
6,359
4,325
3,015
1,819
1,593
2,027
912
1,140
308
190
(744,042)
114,557
217,201
27,594
6,874
5,973
5,559
2,990
1,848
1,550
1,414
376
325
328
181
80
57
38
1
7
1,421
971
177
56
67
48
43
20
19
15
1
1
1
3
M
M
3
1
M
M
+
17,189
21,964
98,984
16,403
1999
5,695,039
5,342,446
160,569
63,821
39,991
17,632
20,615
13,473
8,057
6,943
6,458
4,217
3,054
1,853
1,539
1,996
849
1,080
310
137
(765,692)
105,228
222,340
27,094
6,743
5,797
5,563
2,807
1,816
1,602
1,358
395
335
330
173
81
56
37
1
6
1,353
907
174
56
65
50
43
20
18
15
1
1
2
3
M
M
3
1
M
M
+
15,917
20,530
94,361
15,869
2000
5,864,465
5,533,710
140,687
65,316
41,190
17,921
19,616
13,322
5,960
5,769
6,244
4,181
3,004
1,918
1,382
1,719
957
1,129
311
130
(759,507)
101,366
226,765
26,997
6,619
6,033
5,507
2,679
1,811
1,635
1,325
357
346
343
167
80
57
38
1
6
1,343
897
171
58
63
50
45
19
19
15
1
1
1
3
M
M
3
1
M
M
+
14,829
20,288
92,895
15,228
2001
5,795,192
5,486,908
131,028
57,822
41,357
18,634
16,719
12,828
5,733
6,094
4,505
4,147
2,787
1,857
1,264
1,329
818
976
293
94
(767,987)
97,815
200,479
26,679
6,484
5,981
5,459
2,644
1,850
1,651
1,303
364
316
313
159
68
51
37
+
5
1,332
913
161
58
51
50
44
19
16
15
1
1
1
3
M
M
2
1
M
M
+
14,452
19,414
89,329
15,048
2002
5,815,889
5,501,763
136,455
54,550
42,898
18,862
18,510
12,309
5,885
6,204
4,596
4,139
2,857
1,997
1,338
1,237
968
927
290
105
(768,639)
89,489
194,351
26,657
6,659
5,971
5,463
2,500
1,871
1,705
1,274
325
295
288
152
72
48
34
+
4
1,314
896
153
58
56
50
43
19
19
15
2
1
1
3
M
M
2
1
M
M
+
13,928
18,850
87,428
14,217
2003
5,877,677
5,571,088
133,489
53,335
43,082
19,360
15,278
12,987
4,720
6,091
4,608
4,111
2,777
2,013
1,382
1,159
1,293
502
289
111
(774,848)
84,083
202,111
26,875
6,782
5,939
5,481
2,611
1,865
1,742
1,236
328
311
277
144
72
49
38
+
4
1,245
836
144
57
54
51
44
20
20
15
2
1
1
2
M
M
1
1
M
M
+
14,208
17,995
87,518
13,877
2004
5,987,984
5,656,554
153,386
51,334
45,559
19,360
16,894
13,698
6,702
6,034
4,346
4,205
2,895
2,259
1,395
1,287
1,183
502
259
133
(780,094)
94,499
211,230
26,511
6,709
5,658
5,362
2,682
1,875
1,758
1,222
360
307
269
140
77
50
42
+
5
1,247
844
138
57
54
52
44
21
19
15
2
2
1
3
M
M
1
1
M
M
+
13,910
17,076
87,599
13,556
+ Does not exceed 0.5 Gg.
M Mixture of multiple gases
a Sinks are not included in C02 emissions total, and are based partially on
projected activity data.
b Emissions from International Bunker Fuels and Wood Biomass and Ethanol
Consumption are not included in totals.
° HFC-23 emitted
"SF6 emitted
Note: Totals may not sum due to independent rounding.
Note: Parentheses indicate negative values or sequestration.
Trends in Greenhouse Gas Emissions 2-7
-------
Table 2-5: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)
Chapter/IPCC Sector
Energy
Industrial Processes
Solvent and Other Product Use
Agriculture
Land Use, Land-Use Change, and Forestry
(Emissions)
Waste
Total
Net C02 Flux from Land Use, Land-Use
Change, and Forestry*
Net Emissions (Sources and Sinks)
1990
5
6
,148.
301.
4.
439.
5.
210.
,109.
,3
,1
,3
,6
,7
,0
.0
(910.4) •
5
,198.
.6
1998
5,752.3
335.1
4.8
483.2
6.5
191.8
6,773.7
(744.0)
6,029.6
1999
5,822.3
327.5
4.8
463.1
6.7
190.7
6,814.9
(765.7)
6,049.2
2000
5,994.3
329.6
4.8
458.4
6.4
188.8
6,982.3
(759.5)
6,222.8
2001
5,931.6
300.7
4.8
463.4
6.2
186.4
6,893.1
(768.0)
6,125.1
2002
5,944.6
310.9
4.8
457.8
6.4
191.3
6,915.8
(768.6)
6,147.2
2003
6,009.8
304.1
4.8
439.1
6.6
194.8
6,959.1
(774.8)
6,184.3
2004
6,108.2
320.7
4.8
440.1
6.8
193.8
7,074.4
(780.1)
6,294.3
* The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions total.
Note: Totals may not sum due to independent rounding.
Note: Parentheses indicate negative values or sequestration.
4,696.6 Tg C02 Eq. to 5,656.6 Tg C02 Eq.—a 20.4 percent
total increase over the fourteen-year period.
The four major end-use sectors contributing to C02
emissions from fossil fuel combustion are industrial,
transportation, residential, and commercial. Electricity
generation also emits C02, although these emissions are
produced as they consume fossil fuel to provide electricity
to one of the four end-use sectors. For the discussion below,
electricity generation emissions have been distributed to each
end-use sector on the basis of each sector's share of aggregate
electricity consumption. This method of distributing
emissions assumes that each end-use sector consumes
electricity that is generated from the national average mix
of fuels according to their carbon intensity. Emissions from
electricity generation are also addressed separately after the
end-use sectors have been discussed.
Note that emissions from U.S. territories are calculated
separately due to a lack of specific consumption data for the
individual end-use sectors.
Table 2-7, Figure 2-8, and Figure 2-9 summarize C02
emissions from fossil fuel combustion by end-use sector.
Transportation End-Use Sector. Transportation
activities (excluding international bunker fuels) accounted
for 33 percent of C02 emissions from fossil fuel combustion
Figure 2-5
U.S. Greenhouse Gas Emissions by Chapter/IPCC Sector
Industrial Processes
Agriculture
Land Use, Land-Use Change, and Forestry (sink)
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Land Use,
Land-Use Change, and Forestry sector and the Solvent and Other Product Use sector.
Figure 2-6
2004 Energy Sector Greenhouse Gas Sources
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Combustion
Petroleum Systems
Stationary Combustion J
Municipal Solid
Waste Combustion •
Natural Gas Flaring |
Abandoned Underground |
Coal Mines
5,656.6
Energy as a Portion
of all Emissions
50
100
Tg C02 Eq.
150
200
2-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 2-7
2004 U.S. Fossil Carbon Flows (Tg C02 Eq.)
NED Emissions
22
Natural Gas Emissions
1,191
NEU Emissions 124
Note: Totals may not sum due to independent rounding.
The "Balancing Item" above accounts for the statistical imbalances
and unknowns in the reported data sets combined here.
NEU = Non-Energy Use
NG = Natural Gas
Table 2-6: Emissions from Energy (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Municipal Solid
Waste Combustion
Natural Gas Flaring
Biomass-Wood*
International Bunker Fuels*
Biomass-Ethanol*
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground
Coal Mines
Mobile Combustion
International Bunker Fuels*
N20
Mobile Combustion
Stationary Combustion
Municipal Solid
Waste Combustion
International Bunker Fuels*
Total
1990
4,830.5
4,696.6
117.2
10.9
5.8 I
212.5
113.5
4.2
261.6
126.7
81.9
34.41
7.9
6.0 I
4.7
0.2|
56.2
43.5
12.3
0.5 I
1.0
5,148.3
1998
5,448.3
5,271.8
152.8
1 17.1
6.6
209.5
114.6
7.7
235.4
125.4
62.8
29.7
6.8
1 6.9
3.8
1 0.2
68.6
54.8
13.4
1 0.4
1 1.0
5,752.3
1999
5,527.6
5,342.4
160.6
17.6
6.9
214.3
105.2
8.0
226.8
121.7
58.9
28.5
7.0
6.9
3.6
0.1
67.9
54.1
13.4
0.4
0.9
5,822.3
2000
5,698.1
5,533.7
140.7
17.9
5.8
217.6
101.4
9.2
228.7
126.7
56.3
27.8
7.3
7.2
3.5
0.1
67.5
53.1
13.9
0.4
0.9
5,994.3
2001
5,642.7
5,486.9
131.0
18.6
6.1
190.8
97.8
9.7
225.0
125.6
55.5
27.4
6.6
6.6
3.3
0.1
63.9
50.0
13.5
0.5
0.9
5,931.6
2002
5,663.3
5,501.8
136.5
18.9
6.2
182.9
89.5
11.5
220.1
125.4
52.5
26.8
6.2
6.0
3.2
0.1
61.3
47.5
13.2
0.5
0.8
5,944.6
2003
5,730.0
5,571.1
133.5
19.4
6.1
186.3
84.1
15.8
220.9
124.7
54.8
25.9
6.5
5.8
3.0
0.1
58.9
44.8
13.6
0.5
0.8
6,009.8
2004
5,835.3
5,656.6
153.4
19.4
6.0
191.7
94.5
19.5
215.8
118.8
56.3
25.7
6.4
5.6
2.9
0.1
57.0
42.8
13.7
0.5
0.9
6,108.2
* These values are presented for informational purposes only and are not included in totals or are already accounted for in other source categories.
Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-9
-------
Table 2-7: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity Generation
1990
1,464.4
1,461.4
3.0
1,528.3
851.1
677.2
922.8
338.0
584.8
753.1
222.6
530.5
28.0
4,696.6
1,795.5
1 1998
1,663.4
1,660.3
3.1
1,634.5
871.9
762.6
1,044.5
333.5
711.0
895.9
217.7
678.2
33.5
5,271.8
2,154.9
1999
1,725.6
1,722.4
3.2
1,613.5
849.0
764.5
1,064.0
352.3
711.7
904.8
218.6
686.2
34.5
5,342.4
2,165.6
2000
1,770.3
1,766.9
3.4
1,642.8
862.6
780.3
1,123.2
369.9
753.3
961.6
229.3
732.4
35.8
5,533.7
2,269.3
2001
1,757.0
1,753.6
3.5
1,574.9
861.2
713.7
1,123.2
361.5
761.7
983.3
224.9
758.4
48.5
5,486.9
2,237.3
2002
1,802.2
1,798.8
3.4
1,542.8
842.1
700.7
1,139.8
360.0
779.8
973.9
224.3
749.6
43.1
5,501.8
2,233.5
2003
1,805.4
1,801.0
4.3
1,572.4
844.6
727.7
1,166.6
378.8
787.9
978.1
235.8
742.2
48.7
5,571.1
2,262.2
2004
1,860.2
1,855.5
4.7
1,595.0
863.5
731.5
1,166.8
369.6
797.2
983.1
226.0
757.2
51.4
5,656.6
2,290.6
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.
in 2004.3 Virtually all of the energy consumed in this end-
use sector came from petroleum products. Over 60 percent
of the emissions resulted from gasoline consumption for
personal vehicle use. The remaining emissions came from
other transportation activities, including the combustion of
diesel fuel in heavy-duty vehicles and jet fuel in aircraft.
Industrial End-Use Sector. Industrial C02 emissions,
resulting both directly from the combustion of fossil fuels and
indirectly from the generation of electricity that is consumed
by industry, accounted for 28 percent of C02 emissions from
fossil fuel combustion in 2004. About half of these emissions
resulted from direct fossil fuel combustion to produce steam
and/or heat for industrial processes. The other half of the
emissions resulted from consuming electricity for motors,
electric furnaces, ovens, lighting, and other applications.
Residential and Commercial End-Use Sectors. The
residential and commercial end-use sectors accounted for
21 and 17 percent, respectively, of C02 emissions from
fossil fuel combustion in 2004. Both sectors relied heavily
on electricity for meeting energy demands, with 68 and
Figure 2-8
Figure 2-9
2004 C02 Emissions from Fossil Fuel
Combustion by Sector and Fuel Type
2004 End-Use Sector Emissions of C02
from Fossil Fuel Combustion
Relative Contribution
by Fuel Type
2,500 -i
2,000 -
- 1,500 -
1,000 -
500 -
0 -1
Residential Commercial Industrial Transportation Electricity U.S.
Generation Territories
Note: Electricity generation also includes emissions of less than 1 Tg C02 Eq.
from geothermal-based electricity generation.
2,000 -i
1,500 -
o 1,000 -
500 -
From Electricity
Consumption
I From Direct Fossil
Fuel Combustion
o-1
Residential Commercial Industrial Transportation U.S.
Territories
3 If emissions from international bunker fuels are included, the transportation end-use sector accounted for 34 percent of U.S. emissions from fossil fuel
combustion in 2004.
2-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
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.
Electricity Generation. The United States relies on
electricity to meet a significant portion of its energy demands,
especially for lighting, electric motors, heating, and air
conditioning. Electricity generators consumed 34 percent of
U.S. energy from fossil fuels and emitted 40 percent of the
C02 from fossil fuel combustion in 2004. The type of fuel
combusted by electricity generators has a significant effect
on their emissions. For example, some electricity is generated
with low-C02-emitting energy technologies, particularly
non-fossil fuel options such as nuclear, hydroelectric, or
geothermal energy. However, electricity generators rely
on coal for over half of their total energy requirements
and accounted for 94 percent of all coal consumed for
energy in the United States in 2004. Consequently, changes
in electricity demand have a significant impact on coal
consumption and associated C02 emissions.
Non-Energy Use of Fossil Fuels (153.4 Tg C02 Eq.)
In addition to being combusted for energy, fossil fuels
are also consumed for non-energy uses (NEUs). Fuels are
used in the industrial and transportation end-use sectors
for a variety of NEUs, including application as solvents,
lubricants, and waxes, or as raw materials in the manufacture
of plastics, rubber, and synthetic fibers. CO2 emissions arise
from non-energy uses via several pathways. Emissions may
occur during the manufacture of a product, as is the case in
producing plastics or rubber from fuel-derived feedstocks.
Additionally, emissions may occur during the product's
lifetime, such as during solvent use. Where appropriate
data and methodologies are available, NEUs of fossil fuels
used for industrial processes are reported in the Industrial
Processes sector. Emissions in 2004 for non-energy uses
of fossil fuels were 153.4 Tg C02 Eq., which constituted 3
percent of overall fossil fuel C02 emissions and 3 percent
of total national C02 emissions, approximately the same
proportion as in 1990.
Municipal Solid Waste Combustion (19.4 Tg C02 Eq.)
Combustion is used to manage about 7 to 17 percent of
the municipal solid wastes generated in the United States.
The burning of garbage and non-hazardous solids, referred to
as municipal solid waste, as well as the burning of hazardous
waste, is usually performed to recover energy from the waste
materials. C02 and N20 emissions arise from the organic
materials found in these wastes. The C02 emissions from
municipal solid waste containing carbon of biogenic origin
(e.g., paper, yard trimmings) are not accounted for in this
inventory, since they are presumed to be offset by regrowth
of the original living source, and are ultimately accounted
for in the Land Use, Land-Use Change, and Forestry
sector. Several components of municipal solid waste, such
as plastics, synthetic rubber, synthetic fibers, and carbon
black, are of fossil fuel origin, and are included as sources
of C02 and N20 emissions. In 2004, C02 emissions from
waste combustion amounted to 19.4TgC02 Eq., while N20
emissions amounted to 0.5 Tg C02 Eq.
Natural Gas Flaring (6.0 Tg C02 Eq.)
The flaring of natural gas from oil wells results in the
release of C02 emissions. Natural gas is flared from both on-
shore and off-shore oil wells to relieve rising pressure or to
dispose of small quantities of gas that are not commercially
marketable. In 2004, flaring accounted for approximately 0.1
percent of U.S. C02 emissions (6.0 Tg C02 Eq.).
Natural Gas Systems (118.8 Tg C02 Eq.)
CH4 is the major component of natural gas. Fugitive
emissions of CH4 occur throughout the production,
processing, transmission, and distribution of natural gas.
Because natural gas is often found in conjunction with
petroleum deposits, leakage from petroleum systems is
also a source of emissions. Emissions vary greatly from
facility to facility and are largely a function of operation and
maintenance procedures and equipment conditions. In 2004,
CH4 emissions from U.S. natural gas systems accounted for
approximately 21 percent of U.S. CH4 emissions.
Coal Mining (56.3 Tg C02 Eq.)
Produced millions of years ago during the formation of
coal, CH4 trapped within coal seams and surrounding rock
strata is released when the coal is mined. The quantity of CH4
released to the atmosphere during coal mining operations
depends primarily upon the type of coal and the method
and rate of mining.
CH4 from surface mines is emitted directly to the
atmosphere as the rock strata overlying the coal seam are
removed. Because CH4 in underground mines is explosive
Trends in Greenhouse Gas Emissions 2-11
-------
at concentrations of 5 to 15 percent in air, most active
underground mines are required to vent this CH4, typically
to the atmosphere. At some mines, CH4-recovery systems
may supplement these ventilation systems. During 2004, coal
mining activities emitted 10 percent of U.S. CH4 emissions.
From 1990 to 2004, emissions from this source decreased
by 31 percent due to increased use of the CH4 collected
by mine degasification systems and a general shift toward
surface mining.
Petroleum Systems (25.7 Tg C02 Eq.)
Petroleum is often found in the same geological structures
as natural gas, and the two are often retrieved together. Crude
oil is saturated with many lighter hydrocarbons, including
CH4. When the oil is brought to the surface and processed,
many of the dissolved lighter hydrocarbons (as well as
water) are removed through a series of high-pressure and
low-pressure separators. The remaining hydrocarbons in
the oil are emitted at various points along the system. CH4
emissions from the components of petroleum systems
generally occur as a result of system leaks, disruptions, and
routine maintenance. In 2004, emissions from petroleum
systems were about 5 percent of U.S. CH4 emissions.
Mobile Combustion (45.8 Tg C02 Eq.)
Mobile combustion results in N20 and CH4 emissions.
N20 is a product of the reaction that occurs between nitrogen
and oxygen during fuel combustion. The quantity emitted
varies according to the type of fuel, technology, and pollution
control device used, as well as maintenance and operating
practices. For example, some types of catalytic converters
installed to reduce motor vehicle pollution can promote the
formation of N20. In 2004, N20 emissions from mobile
combustion were 42.8 Tg C02 Eq. (11 percent of U.S. N20
emissions). From 1990 to 2004, N20 emissions from mobile
combustion decreased by about 1 percent.
In 2004, CH4 emissions were estimated to be 2.9 Tg
C02 Eq. The combustion of gasoline in highway vehicles
was responsible for the majority of the CH4 emitted from
mobile combustion.
Stationary Combustion (20.1 Tg C02 Eq.)
Stationary combustion results in N20 and CH4
emissions. In 2004, N20 emissions from stationary
combustion accounted for 13.7 Tg C02 Eq. (4 percent of
U.S. N20 emissions). From 1990 to 2004, N20 emissions
from stationary combustion increased by 11 percent, due to
increased fuel consumption. In 2004, CH4 emissions were 6.4
Tg C02 Eq. (1 percent of U.S. CH4 emissions). The majority
of CH4 emissions from stationary combustion resulted from
the burning of wood in the residential end-use sector.
Abandoned Underground Coal Mines (5.6 Tg C02 Eq.)
Coal mining activities result in the emission of CH4 into
the atmosphere. However, the closure of a coal mine does
not correspond with an immediate cessation in the release of
emissions. Following an initial decline, abandoned mines can
liberate CH4 at a near-steady rate over an extended period
of time, or, if flooded, produce gas for only a few years. In
2004, the emissions from abandoned underground coal mines
constituted 1 percent of U.S. CH4 emissions.
C02 from Wood Biomass and Ethanol Consumption
(211.2TgC02Eq.)
Biomass refers to organically-based carbon fuels (as
opposed to fossil-based). Biomass in the form of fuel wood
and wood waste was used primarily in the industrial sector,
while the transportation sector was the predominant user of
biomass-based fuels, such as ethanol from corn and woody
crops.
Although these fuels do emit C02, in the long run
the C02 emitted from biomass consumption does not
increase atmospheric C02 concentrations if the biogenic
carbon emitted is offset by the growth of new biomass. For
example, fuel wood burned one year but re-grown the next
only recycles carbon, rather than creating a net increase in
total atmospheric carbon. Net carbon fluxes from changes
in biogenic carbon reservoirs in wooded or croplands are
accounted for in the estimates for the Land Use, Land-Use
Change, and Forestry sector. As a result, C02 emissions from
biomass combustion have been estimated separately from
fossil-fuel-based emissions and are not included in the U.S.
totals. CH4 emissions from biomass combustion are included
in the stationary combustion source described above.
The consumption of wood biomass in the industrial,
residential, electric power, and commercial end-use sectors
accounted for 64,16, 8, and 2 percent of gross C02 emissions
from biomass combustion, respectively. Ethanol consumption
in the transportation end-use sector accounted for the
remaining 9 percent.
2-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
International Bunker Fuels (95.5 Tg C02 Eq.)
Greenhouse gases emitted from the combustion of
fuels used for international transport activities, termed
international bunker fuels under the UNFCCC, include
C02, CH4, and N20. Emissions from these activities are
currently not included in national emission totals, but are
reported separately based upon location of fuel sales. The
decision to report emissions from international bunker
fuels separately, instead of allocating them to a particular
country, was made by the Intergovernmental Negotiating
Committee in establishing the Framework Convention on
Climate Change. These decisions are reflected in the Revised
1996IPCC Guidelines, in which countries are requested to
report emissions from ships or aircraft that depart from their
ports with fuel purchased within national boundaries and are
engaged in international transport separately from national
totals (IPCC/UNEP/OECD/IEA 1997).
Two transport modes are addressed under the IPCC
definition of international bunker fuels: aviation and
marine. Emissions from ground transport activities—by
road vehicles and trains, even when crossing international
borders—are allocated to the country where the fuel was
loaded into the vehicle and, therefore, are not counted as
bunker fuel emissions. Emissions of C02, CH4, and N20
from international bunker fuel combustion were 94.5, 0.1,
and 0.9 Tg C02 Eq. in 2004, respectively.
Industrial Processes
Emissions are produced as a by-product of many non-
energy-related industrial process activities. For example,
industrial processes can chemically transform raw materials,
which often release waste gases such as C02, CH4, and N20.
The processes include iron and steel production, cement
manufacture, ammonia manufacture and urea application,
lime manufacture, limestone and dolomite use (e.g., flux
stone, flue gas desulfurization, and glass manufacturing),
soda ash manufacture and use, titanium dioxide production,
phosphoric acid production, ferroalloy production, C02
consumption, silicon carbide production and consumption,
aluminum production, petrochemical production, nitric acid
production, adipic acid production, lead production, and zinc
production (see Figure 2-10). Additionally, emissions from
industrial processes release HFCs, PFCs and SF6. Table 2-8
presents greenhouse gas emissions from Industrial Processes
by source category.
Iron and Steel Production (52.4 Tg C02 Eq.)
Pig iron is the product of combining iron oxide (i.e., iron
ore) and sinter with metallurgical coke in a blast furnace.
The pig iron production process, as well as the thermal
processes used to create sinter and metallurgical coke,
resulted in emissions of C02 and CH4. In 2004, iron and steel
production resulted in 1.0 Tg C02 Eq. of CH4 emissions,
with the majority of the emissions coming from the pig iron
production process. The majority of C02 emissions from
iron and steel processes come from the production of coke
for use in pig iron creation, with smaller amounts evolving
from the removal of carbon from pig iron used to produce
steel. C02 emissions from iron and steel amounted to 51.3
Tg C02 Eq. in 2004. From 1990 to 2004, overall emissions
from this source decreased by 39 percent.
Cement Manufacture (45.6 Tg C02 Eq.)
Clinker is an intermediate product in the formation of
finished Portland and masonry cement. Heating calcium
carbonate (CaC03) in a cement kiln forms lime and C02. The
lime combines with other materials to produce clinker, and
the C02 is released into the atmosphere. From 1990 to 2004,
emissions from this source increased by 37 percent.
Figure 2-10
2004 Industrial Processes Chapter Greenhouse
Gas Sources
Substitution of Ozone Depleting Substances
Iron and Steel Production
Cement Manufacture
Ammonia Manufacture and Urea Application ^H
Nitric Acid Production ^|
HCFC-22 Production •
Electrical Transmission and Distribution •
Lime Manufacture ^|
Aluminum Production |
Limestone and Dolomite Use |
Adipic Acid Production |
Semiconductor Manufacture |
Petrochemical Production |
Soda Ash Manufacture and Consumption |
Magnesium Production and Processing |
Titanium Dioxide Production |
Phosphoric Acid Production |
Ferroalloy Production |
Carbon Dioxide Consumption |
Zinc Production |
Lead Production |
Silicon Carbide Consumption | <0.5
Silicon Carbide Production I <0.1
Industrial Processes
as a Portion of
all Emissions
0 20 40 60 80 100 120
Trends in Greenhouse Gas Emissions 2-13
-------
Table 2-8: Emissions from Industrial Processes (Tg C02 Eq.)
Gas/Source
C02
Iron and Steel Production
Cement Manufacture
Ammonia Manufacture & Urea Application
Lime Manufacture
Limestone and Dolomite Use
Aluminum Production
Soda Ash Manufacture and Consumption
Petrochemical Production
Titanium Dioxide Production
Phosphoric Acid Production
Ferroalloy Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Consumption
CH4
Petrochemical Production
Iron and Steel Production
Silicon Carbide Production
N20
Nitric Acid Production
Adipic Acid Production
MFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing
Total
1990
174,
85,
33,
19,
11
5,
7,
4,
2,
1,
1
2,
0,
0,
0,
0,
2
1,
1
33,
17,
15,
90,
0,
35,
28
2,
18,
5,
301,
.8
.0
.3
3
.2
.5
.0
1
.2
.3
5
•0
•9
.9
.3
1
•5
.2
.3
f
.0
.8
.2
.8
.4
.0
!
.1
1998
171.9
67.7
39.2
21.9
13.9
7.4
6.4
4.3
3.0
1.8
1.6
2.0
0.9
1.1
0.3
0.2
2.9
1.7
1.2
+
26.9
20.9
6.0
133.4
54.5
40.1
16.7
7.1
9.1
5.8
335.1
1999
167,
63,
40,
20,
13,
8,
6,
4,
3,
1,
1
2,
0,
1,
0,
0,
2
1,
1
25,
20,
5,
131.
62,
30,
16,
7,
9,
6,
327,
.5
.8
.0
.6
.5
.1
.5
.2
.1
.9
.5
.0
.8
.1
.3
.1
.9
.7
.2
f
.6
.1
.5
.5
.8
.4
.1
.2
.0
.0
.5
2000
166.4
65
41
19
13
6
6
4
3
1
1
1
1
1
0
0
2
1
1
25
19
6
134
71
29
15
6
9
3
329
.3
.2
.6
.3
.0
.2
.2
.0
.9
.4
.7
.0
.1
.3
.1
.9
.7
.2
•f
.6
.6
.0
.7
.2
.8
.3
.3
.0
.2
.6
2001
152.5
57.8
41.4
16.7
12.8
5.7
4.5
4.1
2.8
1.9
1.3
1.3
0.8
1.0
0.3
0.1
2.5
1.4
1.1
+
20.8
15.9
4.9
124.9
78.6
19.8
15.3
4.5
4.0
2.6
300.7
2002
152.6
54.6
42.9
18.5
12.3
5.9
4.6
4.1
2.9
2.0
1.3
1.2
1.0
0.9
0.3
0.1
2.5
1.5
1.0
+
23.1
17.2
5.9
132.7
86.2
19.8
14.5
4.4
5.3
2.6
310.9
2003
147.6
53.3
43.1
15.3
13.0
4.7
4.6
4.1
2.8
2.0
1.4
1.2
1.3
0.5
0.3
0.1
2.5
1.5
1.0
+
22.9
16.7
6.2
131.0
93.5
12.3
14.0
4.3
3.8
3.0
304.1
2004
152.6
51.3
45.6
16.9
13.7
6.7
4.3
4.2
2.9
2.3
1.4
1.3
1.2
0.5
0.3
0.1
2.7
1.6
1.0
+
22.4
16.6
5.7
143.0
103.3
15.6
13.8
4.7
2.8
2.7
320.7
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Ammonia Manufacture and Urea Application (16.9 Tg C02 Eq.)
In the United States, roughly 98 percent of synthetic
ammonia is produced by catalytic steam reforming of natural
gas, and the remainder is produced using naphtha (i.e., a
petroleum fraction) or the electrolysis of brine at chlorine
plants (EPA 1997). The two fossil fuel-based reactions
produce carbon monoxide and hydrogen gas. This carbon
monoxide is transformed into C02 in the presence of a
catalyst. The C02 is generally released into the atmosphere,
but some of the C02, together with ammonia, is used as a
raw material in the production of urea [CO(NH2)2], which
is a type of nitrogenous fertilizer. The carbon in the urea
that is produced and assumed to be subsequently applied
to agricultural land as a nitrogenous fertilizer is ultimately
released into the environment as C02.
Lime Manufacture (13.7 Tg C02 Eq.)
Lime is used in steel making, construction, flue
gas desulfurization, and water and sewage treatment. It
is manufactured by heating limestone (mostly calcium
carbonate, CaC03) in a kiln, creating quicklime (calcium
oxide, CaO) and C02, which is normally emitted to the
atmosphere.
Limestone and Dolomite Use (6.7 Tg C02 Eq.)
Limestone (CaC03) and dolomite (CaMg(C03)2) are
basic raw materials used in a wide variety of industries,
including construction, agriculture, chemical, and metallurgy.
For example, limestone can be used as a purifier in refining
metals. In the case of iron ore, limestone heated in a blast
furnace reacts with impurities in the iron ore and fuels,
2-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
generating C02 as a by-product. Limestone is also used in
flue gas desulfurization systems to remove sulfur dioxide
from the exhaust gases.
Aluminum Production (7.2 Tg C02 Eq.)
Aluminum production results in emissions of C02, CF4
and C2F6. C02 is emitted when alumina (aluminum oxide,
A1203) is reduced to aluminum. The reduction of the alumina
occurs through electrolysis in a molten bath of natural or
synthetic cryolite. The reduction cells contain a carbon lining
that serves as the cathode. Carbon is also contained in the
anode, which can be a carbon mass of paste, coke briquettes,
or prebaked carbon blocks from petroleum coke. During
reduction, some of this carbon is oxidized and released to the
atmosphere as C02. In 2004, C02 emissions from aluminum
production amounted to 4.3 Tg C02 Eq.
During the production of primary aluminum, CF4 and
C2F6 are emitted as intermittent by-products of the smelting
process. These PFCs are formed when fluorine from the
cryolite bath combines with carbon from the electrolyte
anode. PFC emissions from aluminum production have
decreased by 85 percent between 1990 and 2004 due to
emission reduction efforts by the industry and falling
domestic aluminum production. In 2004, CF4 and C2F6
emissions from aluminum production amounted to 2.8 Tg
C02 Eq.
Soda Ash Manufacture and Consumption (4.2 Tg C02 Eq.)
Commercial soda ash (sodium carbonate, Na2C03)
is used in many consumer products, such as glass, soap
and detergents, paper, textiles, and food. During the
manufacturing of soda ash, some natural sources of sodium
carbonate are heated and transformed into a crude soda ash,
in which C02 is generated as a by-product. In addition, C02
is often released when the soda ash is consumed.
Petrochemical Production (4.5 Tg C02 Eq.)
The production process for carbon black results in the
release C02 emissions to the atmosphere. Carbon black is
a black powder generated by the incomplete combustion of
an aromatic petroleum or coal-based feedstock production.
The majority of carbon black produced in the United States
is consumed by the tire industry, which adds it to rubber to
increase strength and abrasion resistance. Small amounts
of CH4 are also released during the production of five
petrochemicals: carbon black, ethylene, ethylene dichloride,
styrene, and methanol. These production processes resulted
in emissions of 2.9 Tg C02 Eq. of C02 and 1.6 Tg C02 Eq.
ofCH4in2004.
Titanium Dioxide Production (2.3 Tg C02 Eq.)
Titanium dioxide (Ti02) is a metal oxide manufactured
from titanium ore, and is principally used as a pigment. It is
used in white paint and as a pigment in the manufacture of
white paper, foods, and other products. Two processes, the
chloride process and the sulfate process, are used for making
Ti02. C02 is emitted from the chloride process, which uses
petroleum coke and chlorine as raw materials.
Phosphoric Acid Production (1.4 Tg C02 Eq.)
Phosphoric acid is a basic raw material in the production
of phosphate-based fertilizers. The phosphate rock consumed
in the United States originates from both domestic mines,
located primarily in Florida, North Carolina, Idaho, and Utah,
and foreign mining operations in Morocco. The primary use
of this material is as a basic component of a series of chemical
reactions that lead to the production of phosphoric acid, as
well as the by-products C02 and phosphogypsum.
Ferroalloy Production (1.3 Tg C02 Eq.)
C02 is emitted from the production of several ferroalloys.
Ferroalloys are composites of iron and other elements such
as silicon, manganese, and chromium. When incorporated
in alloy steels, ferroalloys are used to alter the material
properties of the steel.
Carbon Dioxide Consumption (1.2 Tg C02 Eq.)
Many segments of the economy consume C02, including
food processing, beverage manufacturing, chemical
processing, and a host of industrial and other miscellaneous
applications. C02 may be produced as a by-product from
the production of certain chemicals (e.g., ammonia), from
select natural gas wells, or by separating it from crude oil
and natural gas. The majority of the C02 used in these
applications is eventually released to the atmosphere.
Zinc Production (0.5 Tg C02 Eq.)
C02 emissions from the production of zinc in the United
States occur through the primary production of zinc in the
Trends in Greenhouse Gas Emissions 2-15
-------
electro-thermic production process, or through the secondary
production of zinc using a Waelz Kiln furnace or the electro-
thermic production process. Both the electro-thermic and
Waelz Kiln processes are emissive due to the use of a
carbon-based material (often metallurgical coke); however,
zinc is also produced in the United States using non-emissive
processes. Due to the closure of an electro-thermic plant in
2003, the only emissive zinc production process remaining
occurs through the recycling of electric-arc-furnace (EAF)
dust in a Waelz Kiln furnace (secondary production) at a
plant in Palmerton, Pennsylvania.
Lead Production (0.3 Tg C02 Eq.)
Primary and secondary production of lead in the
United States results in C02 emissions when carbon-based
materials (often metallurgical coke) are used as a reducing
agent. Primary production involves the direct smelting
of lead concentrates while secondary production largely
occurs through the recycling of lead-acid batteries. In
2004, emissions from primary lead production decreased
by 40 percent due to the closure of one of two primary
lead production plants located in Missouri. Secondary lead
production accounted for 85 percent of total lead production
emissions in 2004.
Silicon Carbide Production and Consumption (0.1 Tg C02
Eq.)
Small amounts of CH4 are released during the production
of silicon carbide (SiC), a material used as an industrial
abrasive. Additionally, small amounts of C02 are released
when SiC is consumed for metallurgical and other non-
abrasive purposes (e.g., iron and steel production). Silicon
carbide is made through a reaction of quartz (Si02) and
carbon (in the form of petroleum coke). CH4 is produced
during this reaction from volatile compounds in the petroleum
coke. CH4 emissions from silicon carbide production have
declined significantly due to a 67 percent decrease in silicon
carbide production since 1990. C02 emissions from SiC
consumption have fluctuated significantly between years
dependent on consumption, but overall have increased by
33 percent since 1990.
Nitric Acid Production (16.6 Tg C02 Eq.)
Nitric acid production is an industrial source of N20
emissions. Used primarily to make synthetic commercial
fertilizer, this raw material is also a major component in the
production of adipic acid and explosives.
Virtually all of the nitric acid manufactured in the United
States is produced by the oxidation of ammonia, during
which N20 is formed and emitted to the atmosphere. In
2004, N20 emissions from nitric acid production accounted
for 4 percent of U.S. N20 emissions. From 1990 to 2004,
emissions from this source category decreased by 7 percent
with the trend in the time series closely tracking the changes
in production.
Adipic Acid Production (5.7 Tg C02 Eq.)
Most adipic acid produced in the United States is used
to manufacture nylon 6,6. Adipic acid is also used to produce
some low-temperature lubricants and to add a "tangy" flavor
to foods. N20 is emitted as a by-product of the chemical
synthesis of adipic acid.
In 2004, U.S. adipic acid plants emitted 1.5 percent of
U.S. N20 emissions. Even though adipic acid production has
increased in recent years, by 1998 all three major adipic acid
plants in the United States had voluntarily implemented N20
abatement technology. As a result, emissions have decreased
by 62 percent since 1990.
Substitution of Ozone Depleting Substances (103.3 Tg C02
Eq.)
The use and subsequent emissions of HFCs and PFCs
as substitutes for ODSs have increased from small amounts
in 1990 to account for 72 percent of aggregate HFC, PFC,
and SF6 emissions. This increase was in large part the result
of efforts to phase-out CFCs and other ODSs in the United
States, especially the introduction of HFC-134a as a CFC
substitute in refrigeration and air-conditioning applications.
In the short term, this trend is expected to continue, and will
likely accelerate over the coming decade as HCFCs, which
are interim substitutes in many applications, are themselves
phased-out under the provisions of the Copenhagen
Amendments to the Montreal 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.
HCFC-22 Production (15.6 Tg C02 Eq.)
HFC-23 is a by-product of the production of HCFC-22.
Emissions from this source have decreased by 55 percent
2-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
since 1990. The HFC-23 emission rate (i.e., the amount of
HFC-23 emitted per kilogram of HCFC-22 manufactured)
has declined significantly since 1990, although production
has been increasing.
Electrical Transmission and Distribution Systems (13.8 Tg
C02 Eq.)
The primary use of SF6 is as a dielectric in electrical
transmission and distribution systems. Fugitive emissions
of SF6 occur from leaks in and servicing of substations
and circuit breakers, especially from older equipment. The
gas can also be released during equipment manufacturing,
installation, servicing, and disposal. Estimated emissions
from this source decreased by 52 percent since 1990,
primarily due to higher SF6 prices and industrial efforts to
reduce emissions.
Semiconductor Manufacture (4.7 Tg C02 Eq.)
The semiconductor industry uses combinations of
HFCs, PFCs, SF6, and other gases for plasma etching and
to clean chemical vapor deposition tools. Emissions from
this source category have increased 62 percent since 1990
with the growth in the semiconductor industry and the
rising intricacy of chip designs. However, the growth rate
in emissions has slowed since 1997, and emissions actually
declined between 1999 and 2004. This later reduction is due
to the implementation of PFC emission reduction methods,
such as process optimization.
Magnesium Production (2.7 Tg C02 Eq.)
Sulfur hexafluoride is also used as a protective cover
gas for the casting of molten magnesium. Emissions from
primary magnesium production and magnesium casting
have decreased by 50 percent since 1990. This decrease has
primarily taken place since 1999, due to a decline in the
quantity of magnesium die cast and the closure of a U.S.
primary magnesium production facility.
Solvent and Other Product Use
Greenhouse gas emissions are produced as a by-product
of various solvent and other product uses. In the United
States, emissions from N20 product usage, the only source
of greenhouse gas emissions from this sector, accounted for
4.8 Tg C02 Eq. of N20, or less than 0.1 percent of total U.S.
emissions in 2004 (see Table 2-9).
N20 Product Usage (4.8 Tg C02 Eq.)
N20 is used in carrier gases with oxygen to administer
more potent inhalation anesthetics for general anesthesia and
as an anesthetic in various dental and veterinary applications.
As such, it is used to treat short-term pain, for sedation in
minor elective surgeries and as an induction anesthetic. The
second main use of N20 is as a propellant in pressure and
aerosol products, the largest application being pressure-
packaged whipped cream. In 2004, N20 emissions from
product usage constituted approximately 1 percent of U.S.
N20 emissions. From 1990 to 2004, emissions from this
source category increased by 11 percent.
Agriculture
Agricultural activities contribute directly to emissions of
greenhouse gases through a variety of processes, including
the following source categories: enteric fermentation in
domestic livestock, livestock manure management, rice
cultivation, agricultural soil management, and field burning
of agricultural residues.
In 2004, agricultural activities were responsible for
emissions of 440.1 Tg C02 Eq., or 6.2 percent of total U.S.
greenhouse gas emissions. CH4 and N20 were the primary
greenhouse gases emitted by agricultural activities. CH4
emissions from enteric fermentation and manure management
represented about 20 percent and 7 percent of total CH4
emissions from anthropogenic activities, respectively, in
2004. Agricultural soil management activities, such as
Table 2-9: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq.)
Gas/Source
N20
N20 Product
Total
Usage
1990
4.3
4.3
4.3
1998
4.8
4.8
4.8
1999
4.8
4.8
4.8
2000
4.8
4.8
4.8
2001
4.8
4.8
4.8
2002
4.8
4.8
4.8
2003
4.8
4.8
4.8
2004
4.8
4.8
4.8
Trends in Greenhouse Gas Emissions 2-17
-------
fertilizer application and other cropping practices, were the
largest source of U.S. N20 emissions in 2004, accounting
for 68 percent. Figure 2-11 and Table 2-10 present emission
estimates for the Agriculture sector.
Enteric Fermentation (112.6 Tg C02 Eq.)
During animal digestion, CH4 is produced through the
process of enteric fermentation, in which microbes residing
in animal digestive systems break down food. Ruminants,
which include cattle, buffalo, sheep, and goats, have the
highest CH4 emissions among all animal types because they
have a rumen, or large fore-stomach, in which CH4-producing
fermentation occurs. Non-ruminant domestic animals, such
as pigs and horses, have much lower CH4 emissions. In 2004,
enteric fermentation was the source of about 20 percent of
U.S. CH4 emissions, and more than 70 percent of the CH4
emissions from agriculture. From 1990 to 2004, emissions
Figure 2-11
2004 Agriculture Chapter Greenhouse Gas Sources
Agricultural Soil Management
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
Agriculture
as a Portion of
all Emissions
0 50 100 150 200 250 300
Tg C02 Eq.
Table 2-10: Emissions from Agriculture (Tg C02 Eq.)
from this source decreased by 4 percent. Generally, emissions
have been decreasing since 1995, mainly due to decreasing
populations of both beef and dairy cattle and improved feed
quality for feedlot cattle.
Manure Management (57.1 Tg C02 Eq.)
Both CH4 and N20 result from manure management.
The decomposition of organic animal waste in an anaerobic
environment produces CH4. The most important factor
affecting the amount of CH4 produced is how the manure
is managed, because certain types of storage and treatment
systems promote an oxygen-free environment. In particular,
liquid systems tend to encourage anaerobic conditions and
produce significant quantities of CH4, whereas solid waste
management approaches produce little or no CH4. Higher
temperatures and moist climatic conditions also promote
CH4 production.
Emissions from manure management were 39.4 Tg
C02 Eq., or about 7 percent of U.S. CH4 emissions in 2004
and 25 percent of the CH4 emissions from the agriculture
sector. From 1990 to 2004, emissions from this source
increased by 26 percent. The bulk of this increase was
from swine and dairy cow manure, and is attributed to
the shift of the swine and dairy industries towards larger
facilities. Larger swine and dairy farms tend to use liquid
management systems.
N2O is also produced as part of microbial nitrification
and denitrification processes in managed and unmanaged
manure. Emissions from unmanaged manure are accounted
for within the agricultural soil management source category.
Total N20 emissions from managed manure systems in 2004
accounted for 17.7 Tg C02 Eq., or 5 percent of U.S. N20
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
156
117
31
7
0
282
266
16
.8
9
.2
.1
.7
.7
.1
.3
0.4 H
439,
.6
1998
164.2
116.7
38.8
7.9
0.8
319.0
301.1
17.4
0.5
483.2
1999
164.0
116.8
38.1
8.3
0.8
299.1
281.2
17.4
0.4
463.1
2000
162.0
115.6
38.0
7.5
0.8
296.5
278.2
17.8
0.5
458.4
2001
161
114
38
7
0
301
282
18
0
463,
.9
5
.9
.6
.8
.5
.9
.1
.5
.4
2002
161.5
114.7
39.3
6.8
0.7
296.2
277.8
18.0
0.4
457.8
2003
161.8
115.1
39.2
6.9
0.8
277.1
259.2
17.5
0.4
439.1
2004
160.4
112.6
39.4
7.6
0.9
279.7
261.5
17.7
0.5
440.1
Note: Totals may not sum due to independent rounding.
2-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
emissions. From 1990 to 2004, emissions from this source
category increased by 9 percent, primarily due to increases
in swine and poultry populations over the same period.
Rice Cultivation (7.6 Tg C02 Eq.)
Most of the world's rice, and all of the rice in the United
States, is grown on flooded fields. When fields are flooded,
anaerobic conditions develop and the organic matter in the
soil decomposes, releasing CH4 to the atmosphere, primarily
through the rice plants. In 2004, rice cultivation was the
source of 1 percent of U.S. CH4 emissions, and about 5
percent of U.S. CH4 emissions from agriculture. Emission
estimates from this source have increased about 6 percent
since 1990.
Field Burning of Agricultural Residues (1.4Tg C02 Eq.)
Burning crop residue releases N20 and CH4. Because
field burning is not a common debris clearing method in the
United States, it was responsible for only 0.2 percent of U.S.
CH4 (0.9 Tg C02 Eq.) and 0.1 percent of U.S. N20 (0.5 Tg
C02 Eq.) emissions in 2004.
Agricultural Soil Management (261.5 Tg C02 Eq.)
N20 is produced naturally in soils through microbial
nitrification and denitrification processes. A number of
anthropogenic activities add to the amount of nitrogen
available to be emitted as N20 by microbial processes.
These activities may add nitrogen to soils either directly or
indirectly. Direct additions occur through the application
of synthetic and organic fertilizers; production of nitrogen-
fixing crops and forages; the application of livestock
manure, crop residues, and sewage sludge; cultivation of
high-organic-content soils; and direct excretion by animals
onto soil. Indirect additions result from volatilization and
subsequent atmospheric deposition, and from leaching and
surface run-off of some of the nitrogen applied to or deposited
on soils as fertilizer, livestock manure, and sewage sludge.
In 2004, agricultural soil management accounted for 68
percent of U.S. N20 emissions. From 1990 to 2004, emissions
from this source decreased slightly as fertilizer consumption,
manure production, and production of nitrogen-fixing and
other crops rose. Year-to-year fluctuations are largely a
reflection of annual variations in climate, synthetic fertilizer
consumption, and crop production.
Land Use, Land-Use Change, and Forestry
When humans alter the terrestrial biosphere through land
use, changes in land use, and land management practices,
they also alter the background carbon fluxes between
biomass, soils, and the atmosphere. Forest management
practices, tree planting in urban areas, the management of
agricultural soils, and the landfilling of yard trimmings and
food scraps have resulted in a net uptake (sequestration) of
carbon in the United States, which offset about 11 percent
of total U.S. greenhouse gas emissions in 2004. Forests
(including vegetation, soils, and harvested wood) accounted
for approximately 82 percent of total 2004 sequestration,
urban trees accounted for 11 percent, agricultural soils
(including mineral and organic soils and the application
of lime) accounted for 6 percent, and landfilled yard
trimmings and food scraps accounted for 1 percent of the
total sequestration in 2004. The net forest sequestration is a
result of net forest growth and increasing forest area, as well
as a net accumulation of carbon stocks in harvested wood
pools. The net sequestration in urban forests is a result of net
tree growth in these areas. In agricultural soils, mineral soils
account for a net carbon sink that is almost two times larger
than the sum of emissions from organic soils and liming. The
mineral soil carbon sequestration is largely due to 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
2004 resulted in a net carbon sequestration of 780.1 Tg C02
Eq. (Table 2-11). This represents an offset of approximately
13 percent of total U.S. C02 emissions. Total land use, land-
use change, and forestry net carbon sequestration declined
by approximately 14 percent between 1990 and 2004,
which contributed to an increase in net U.S. emissions (all
sources and sinks) of 21 percent from 1990 to 2004. This
decline was primarily due to a decline in the rate of net
carbon accumulation in forest carbon stocks. Annual carbon
accumulation in landfilled yard trimmings and food scraps
Trends in Greenhouse Gas Emissions 2-19
-------
and agricultural soils also slowed over this period, while the
rate of carbon accumulation in agricultural soils and urban
trees increased.
Land use, land-use change, and forestry activities in
2004 also resulted in emissions of N20 (6.8 Tg C02 Eq., Table
2-12). Total N20 emissions from the application of fertilizers
to forests and settlements increased by approximately 20
percent between 1990 and 2004.
Forest Land Remaining Forest Land (0.4 Tg C02 Eq.)
As with other agricultural applications, forests may be
fertilized to stimulate growth rates. The relative magnitude
of the impact of this practice is limited, however, because
forests are generally only fertilized twice during their life
cycles, and applications account for no more than one percent
of total U.S. fertilizer applications annually. In terms of
trends, however, N20 emissions from forest soils for 2004
were almost 7 times higher than in 1990, primarily the result
of an increase in the fertilized area of pine plantations in the
southeastern U.S. This source accounts for approximately
0.1 percent of total U.S. N20 emissions.
Settlements Remaining Settlements (6.4 Tg C02 Eq.)
Of the fertilizers applied to soils in the United States,
approximately 10 percent are applied to lawns, golf courses,
and other landscaping within settled areas. In 2004, N20
emissions from settlement soils constituted approximately 1.7
percent of total U.S. N20 emissions. There has been an overall
increase in emissions of 15 percent since 1990, a result of a
general increase in the applications of synthetic fertilizers.
Waste
Waste management and treatment activities are sources
of greenhouse gas emissions (see Figure 2-12). Landfills
were the largest source of anthropogenic CH4 emissions,
accounting for 25 percent of total U.S. CH4 emissions.4
Table 2-11: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
Forest Land Remaining Forest Land
Changes in Forest Carbon Stocks
Cropland Remaining Cropland
Changes in Agricultural Soil Carbon
and Liming Emissions
Land Converted to Cropland
Changes in Agricultural Soil Carbon
Grassland Remaining Grassland
Changes in Agricultural Soil Carbon
Land Converted to Grassland
Changes in Agricultural Soil Carbon
Settlements Remaining Settlements
Urban Trees
Landfilled Yard Trimmings and Food
Total
Stocks
Stocks
Stocks
Stocks
Scraps
1990
(773.4)
(773.4)
(33.1)
(33.1)
15|
(4.5)
(4.5)
(17.6)
(17.6)
(83.2)
(58.7)
(24.5)
(910.4)
1998
(618.8)
(618.8)
(24.6)
(24.6)
(2.8)
(2.8)
7.5
7.5
(21.1)
(21.1)
(84.2)
(73.3)
(10.9)
(744.0)
1999
(637.9)
(637.9)
(24.6)
(24.6)
(2.8)
(2.8)
7.5
7.5
(21.1)
(21.1)
(86.8)
(77.0)
(9.8)
(765.7)
2000
(631.0)
(631.0)
(26.1)
(26.1)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(85.9)
(77.0)
(8.9)
(759.5)
2001
(634.0)
(634.0)
(27.8)
(27.8)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(89.7)
(80.7)
(9.0)
(768.0)
2002
(634.6)
(634.6)
(27.5)
(27.5)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(89.9)
(80.7)
(9.3)
(768.6)
2003
(635.8)
(635.8)
(28.7)
(28.7)
(2.8)
(2.8)
7.3
7.3
(21.1)
(21.1)
(93.8)
(84.3)
(9.4)
(774.8)
2004
(637.2)
(637.2)
(28.9)
(28.9)
(2.8)
(2.8)
7.3
7.3
(21.1)
(21.1)
(97.3)
(88.0)
(9.3)
(780.1)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
Table 2-12: N20 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
Forest Land Remaining Forest Land
N20 Fluxes from Soils
Settlements Remaining Settlements
N20 Fluxes from Soils
Total
1990
0.1
0.1
5.6
5.6
5.7
1998
0.4
0.4
6.2
6.2
6.5
1999
0.5
0.5
6.2
6.2
6.7
2000
0.4
0.4
6.0
6.0
6.4
2001
0.4
0.4
5.8
5.8
6.2
2002
0.4
0.4
6.0
6.0
6.4
2003
0.4
0.4
6.2
6.2
6.6
2004
0.4
04
6.4
6.4
6.8
Note: Totals may not sum due to independent rounding.
4 Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as described in the Land-
Use, Land-Use Change, and Forestry chapter.
2-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 2-12
2004 Waste Chapter Greenhouse Gas Sources
Landfills
Waste as a
Portion ol
all Emissions
Human Sewage
3.1%
30 60 90 120 150
Tg C02 Eq.
Additionally, wastewater treatment accounts for 7 percent
of U.S. CH4 emissions. N20 emissions from the discharge
of wastewater treatment effluents into aquatic environments
were estimated, as were N20 emissions from the treatment
process itself, using a simplified methodology. Wastewater
treatment systems are a potentially significant source of
N20 emissions; however, methodologies are not currently
available to develop a complete estimate. N20 emissions from
the treatment of the human sewage component of wastewater
were estimated, however, using a simplified methodology.
Nitrogen oxides (NOJ, carbon monoxide (CO), and non-CH4
volatile organic compounds (NMVOCs) are also emitted by
waste activities. A summary of greenhouse gas emissions
from the Waste sector is presented in Table 2-13.
Overall, in 2004, waste activities generated emissions
of 193.8 Tg C02 Eq., or 2.7 percent of total U.S. greenhouse
gas emissions.
Landfills (140.9 TgC02Eq.)
Landfills are the largest anthropogenic source of CH4
emissions in the United States, accounting for approximately
25 percent of total CH4 emissions in 2004. In an environment
where the oxygen content is low or zero, anaerobic bacteria
can decompose organic materials, such as yard waste,
household waste, food waste, and paper, resulting in the
generation of CH4 and biogenic C02. Site-specific factors,
such as waste composition, moisture, and landfill size,
influence the level of CH4 generation.
From 1990 to 2004, net CH4 emissions from landfills
decreased by approximately 18 percent, with small increases
occurring in some interim years. This downward trend in
overall emissions is the result of increases in the amount of
landfill gas collected and combusted by landfill operators,
which has more than offset the additional CH4 emissions
resulting from an increase in the amount of municipal solid
waste landfilled.
Wastewater Treatment (36.9 Tg C02 Eq.)
Wastewater from domestic sources (i.e., municipal sewage)
and industrial sources is treated to remove soluble organic
matter, suspended solids, pathogenic organisms and chemical
contaminants. Soluble organic matter is generally removed
using biological processes in which microorganisms consume
the organic matter for maintenance and growth. Microorganisms
can biodegrade soluble organic material in wastewater under
aerobic or anaerobic conditions, with the latter condition
producing CH4. During collection and treatment, wastewater
may be accidentally or deliberately managed under anaerobic
conditions. In addition, the sludge may be further biodegraded
under aerobic or anaerobic conditions. Untreated wastewater
may also produce CH4 if contained under anaerobic conditions.
In 2004, wastewater treatment was the source of approximately
7 percent of U.S. CH4 emissions.
Human Sewage (Domestic Wastewater) (16.0 Tg C02 Eq.)
Domestic human sewage is usually mixed with other
household wastewater, which includes drainage from showers
and sinks, washing machine effluent, etc., and transported by
a collection system to either a direct discharge, or an on-site,
decentralized, or centralized wastewater treatment system.
Table 2-13: Emissions from Waste (Tg C02 Eq.)
Gas/Source
CH4
Landfills
Wastewater Treatment
N20
Human Sewage
Total
1990
197,
172,
24,
12,
12,
210.
.1
3
.8
.9
.9
,0
1998
176.9
144.4
32.6
14.9
14.9
191.8
1999
175,
141
33,
15,
15,
190.
.3
6
.6
.4
.4
,7
2000
173.3
139.0
34.3
15.5
15.5
188.8
2001
170.8
136.2
34.7
15.6
15.6
186.4
2002
175.6
139.8
35.8
15.6
15.6
191.3
2003
179.0
142.4
36.6
15.8
15.8
194.8
2004
177.8
140.9
36.9
16.0
16.0
193.8
Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-21
-------
After processing, treated effluent may be discharged to a
receiving water environment (e.g., river, lake, estuary, etc.),
applied to soils, or disposed of below the surface. N20 may
be generated during both nitrification and denitrification of
the nitrogen present, usually in the form of urea, ammonia,
and proteins. Emissions of N20 from treated human sewage
discharged into aquatic environments accounted for 4 percent
of U.S. N20 emissions in 2004. From 1990 to 2004, emissions
from this source category increased by 24 percent.
2.2. Emissions by Economic Sector
Throughout this report, emission estimates are grouped
into six sectors (i.e., chapters) defined by the IPCC: Energy;
Industrial Processes; Solvent Use; Agriculture; Land Use,
Land-Use Change, and Forestry; and Waste. While it is
important to use this characterization for consistency with
UNFCCC reporting guidelines, it is also useful to allocate
emissions into more commonly used sectoral categories.
This section reports emissions by the following "economic
sectors": residential, commercial, industry, transportation,
electricity generation, and agriculture, as well as U.S.
territories. Using this categorization, emissions from
electricity generation accounted for the largest portion
(33 percent) of U.S. greenhouse gas emissions in 2004.
Transportation activities, in aggregate, accounted for the
second largest portion (28 percent). Additional discussion
and data on these two economic sectors is provided
below.
Emissions from industry accounted for 19 percent of U.S.
greenhouse gas emissions in 2004. In contrast to electricity
generation and transportation, emissions from industry have
in general declined over the past decade, although there was
an increase in industrial emissions in 2004 (up 3 percent from
2003 levels). 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 residential, agriculture, and
commercial economic sectors, and U.S. territories, contributed
the remaining 20 percent of emissions. The residential economic
sector accounted for approximately 6 percent, and primarily
consisted of C02 emissions from fossil fuel combustion. Activities
related to agriculture accounted for roughly 7 percent of U.S.
emissions, but unlike all other economic sectors these emissions
were dominated by non-C02 emissions. The commercial sector
accounted for about 7 percent of emissions, while U.S. territories
accounted for 1 percent of total emissions.
C02 was also emitted and sequestered by a variety
of activities related to forest management practices, tree
planting in urban areas, the management of agricultural soils,
and landfilling of yard trimmings.
Table 2-14 presents a detailed breakdown of emissions
from each of these economic sectors by source category, as
Table 2-14: U.S. Greenhouse Gas Emissions Allotted to Economic Sectors (Tg C02 Eq. and Percent of Total in 2004)
Sector/Source
Electricity Generation
C02 from Fossil Fuel Combustion
Municipal Solid Waste
Combustionb
Electrical Transmission and
Distribution0
Stationary Combustion"1
Limestone and Dolomite Use
Transportation
C02 from Fossil Fuel Combustion
Substitution of ODSe
Mobile Combustiond
Non-Energy Use of Fuels
Industry
C02 from Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Iron and Steel Production'
Cement Manufacture
Petroleum Systems
Ammonia Manufacture and
Urea Application
Nitric Acid Production
19<
1,846
1,795.
11
28
8
2
1,520
1,461
47
11
1,438
804
99
126
81
86
33
34
19
17
10
•4
5
.4
.6
.1
.8
•3
•4
+
.1
.9
.9
.8
.6
.7
.9
.3
.3
.4
1998
2,202.4
2,154.9
17.5
16.7
9.6
3.7
1,753.4
1,660.3
23.5
57.4
12.1
1,452.4
814.5
131.6
125.4
62.8
68.9
39.2
29.7
21.9
20.9
1999
2,213.3
2,165.6
18.0
16.1
9.6
4.0
1,819.3
1,722.4
28.2
56.4
12.3
1,411.0
789.2
138.8
121.7
58.9
65.0
40.0
28.5
20.6
20.1
2000
2,315.9
2,269.3
18.3
15.3
10.0
3.0
1,866.9
1,766.9
32.6
55.4
12.1
1,409.7
812.3
117.7
126.7
56.3
66.5
41.2
27.8
19.6
19.6
2001
2,284.4
2,237.3
19.1
15.3
9.8
2.9
1,852.7
1,753.6
36.1
52.0
11.1
1,366.6
811.0
114.7
125.6
55.5
58.9
41.4
27.4
16.7
15.9
2002
2,280.1
2,233.5
19.4
14.5
9.8
2.9
1,898.0
1,798.8
38.9
49.4
10.9
1,346.7
789.8
116.4
125.4
52.5
55.6
42.9
26.8
18.5
17.2
2003
2,308.5
2,262.2
19.9
14.0
10.0
2.4
1,898.9
1,801.0
41.2
46.5
10.1
1,342.7
800.3
113.7
124.7
54.8
54.4
43.1
25.9
15.3
16.7
20C
2,337
2,290.
19
13
10
3
1,955
1,855
45
44
10
1377
813
132
118
56
52
45
25
16
16
14
.8
6
.9
.8
.1
.4
.1
.5
.0
.4
.2
3
.1
.8
.8
.3
.4
.6
.7
.9
.6
Percent3
33.0%
32.4%
0.3%
0.2%
0.1%
+
27.6%
26.2%
0.6%
0.6%
0.1%
19.5%
11.5%
1.9%
1.7%
0.8%
0.7%
0.6%
0.4%
0.2%
0.2%
2-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 2-14: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq. and Percent of Total in 2004)
(continued)
Sector/Source
HCFC-22 Productions
Lime Manufacture
Substitution of ODSe
Aluminum Production11
Natural Gas Flaring
Adipic Acid Production
Abandoned Underground Coal
Mines
Stationary Combustion
N20 Product Usage
Semiconductor Manufacture6
Petrochemical Production
Soda Ash Manufacture and
Consumption
Limestone and Dolomite Use
Magnesium Production and
Processing0
Titanium Dioxide Production
Phosphoric Acid Production
Ferroalloy Production
Carbon Dioxide Consumption
Mobile Combustion
Zinc Production
Lead Production
Silicon Carbide Consumption
Silicon Carbide Production
Agriculture
Agricultural Soil Management
Enteric Fermentation
Manure Management11
C02 from Fossil Fuel Combustion
Rice Cultivation
Field Burning of Agricultural
Residuesd
Mobile Combustiond
Forest Soil Fertilization
Stationary Combustion
Commercial
C02 from Fossil Fuel Combustion
Landfills
Substitution of ODS6
Wastewater Treatment
Human Sewage
Stationary Combustiond
Residential
C02 from Fossil Fuel Combustion
Substitution of ODSe
Settlement Soil Fertilization
Stationary Combustiond
U.S. Territories
U.S. Territories
Total Emissions
Sinks
Forests
Urban Trees
Agricultural Soils
Landfilled Yard Trimmings
Net Emissions
1990
35.0
11.2
0.1
25.5
5.8
15.2
6.0
5.3
4.3
2.9
3.4
4.1
2.8
5.4
1.3
1.5
2.0
0.9
0.6
0.9
0.3
0.1
+
486.3
266.1
117.9
47.4
46.3
7.1
1.1
0.4
0.1
+
433.6
222.6
172.3
+
24.8
12.9
1.1
349.4
338.0
0.3
5.6
5.5
33.8
33.8
6,109.0
(910.4)
(773.4)
(58.7)
(53.8)
(24.5)
5.198.6
1998
40.1
13.9
3.9
15.4
6.6
6.0
6.9
5.4
4.8
7.1
4.7
4.3
3.7
5.8
1.8
1.6
2.0
0.9
0.7
1.1
0.3
0.2
+
541.6
301.1
116.7
56.2
57.4
7.9
1.2
0.5
0.4
+
428.0
217.7
144.4
17.4
32.6
14.9
1.1
353.3
333.5
9.6
6.2
4.0
42.7
42.7
6,773.7
(744.0)
(618.8)
(73.3)
(41.0)
(10.9)
6,029.6
1999
30.4
13.5
4.4
15.4
6.9
5.5
6.9
5.4
4.8
7.2
4.8
4.2
4.0
6.0
1.9
1.5
2.0
0.8
0.7
1.1
0.3
0.1
+
523.9
281.2
116.8
55.6
59.8
8.3
1.2
0.5
0.5
+
430.6
218.6
141.6
20.3
33.6
15.4
1.1
372.6
352.3
9.8
6.2
4.2
44.2
44.2
6,814.9
(765.7)
(637.9)
(77.0)
(41.1)
(9.8)
6,049.2
2000
29.8
13.3
4.7
15.2
5.8
6.0
7.2
5.5
4.8
6.3
4.7
4.2
3.0
3.2
1.9
1.4
1.7
1.0
0.8
1.1
0.3
0.1
+
509.5
278.2
115.6
55.9
50.2
7.5
1.2
0.4
0.4
+
443.0
229.3
139.0
23.8
34.3
15.5
1.1
390.4
369.9
10.1
6.0
4.4
46.9
46.9
6,982.3
(759.5)
(631.0)
(77.0)
(42.6)
(8.9)
6,222.8
2001
19.8
12.8
5.1
8.5
6.1
4.9
6.6
5.1
4.8
4.5
4.2
4.1
2.9
2.6
1.9
1.3
1.3
0.8
0.9
1.0
0.3
0.1
+
514.4
282.9
114.6
56.9
50.2
7.6
1.2
0.4
0.4
+
439.5
224.9
136.2
27.1
34.7
15.6
1.0
381.6
361.5
10.3
5.8
3.9
54.0
54.0
6,893.1
(768.0)
(634.0)
(80.7)
(44.3)
(9.0)
6,125.1
2002
19.8
12.3
5.7
9.9
6.2
5.9
6.0
4.9
4.8
4.4
4.4
4.1
2.9
2.6
2.0
1.3
1.2
1.0
0.9
0.9
0.3
0.1
+
511.0
277.8
114.7
57.3
52.3
6.8
1.1
0.5
0.4
+
447.5
224.3
139.8
30.9
35.8
15.6
1.0
380.1
360.0
10.6
6.0
3.5
52.4
52.4
6,915.8
(768.6)
(634.6)
(80.7)
(44.1)
(9.3)
6,147.2
2003
12.3
13.0
6.5
8.4
6.1
6.2
5.8
4.9
4.8
4.3
4.3
4.1
2.4
3.0
2.0
1.4
1.2
1.3
0.9
0.5
0.3
0.1
+
484.2
259.2
115.1
56.7
44.3
6.9
1.2
0.4
0.4
+
466.5
235.8
142.4
34.8
36.6
15.8
1.1
399.8
378.8
11.0
6.2
3.9
58.6
58.6
6,959.1
(774.8)
(635.8)
(84.3)
(45.3)
(9.4)
6,184.3
2004
15.6
13.7
7.9
7.2
6.0
5.7
5.6
5.1
4.8
4.7
4.5
4.2
3.4
2.7
2.3
1.4
1.3
1.2
1.0
0.5
0.3
0.1
+
491.3
261.5
112.6
57.1
50.3
7.6
1.4
0.4
0.4
+
459.9
226.0
140.9
39.0
36.9
16.0
1.1
391.1
369.6
11.3
6.4
3.7
61.9
61.9
7,074.4
(780.1)
(637.2)
(88.0)
(45.6)
(9.3)
6,294.3
Percent3
0.2%
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
+
+
+
+
+
+
+
+
+
+
+
6.9%
3.7%
1.6%
0.8%
0.7%
0.1%
+
+
+
+
6.5%
3.2%
2.0%
0.6%
0.5%
0.2%
+
5.5%
5.2%
0.2%
0.1%
0.1%
0.9%
0.9%
100.0%
(11.0%)
(9.0%)
(1.2%)
(0.6%)
(0.1%)
89.0%
Note: Includes all emissions of C02, CH4, N20, MFCs, PFCs, and SF6.
Parentheses indicate negative values or sequestration. Totals may not sum
due to independent rounding.
ODS (Ozone Depleting Substances)
+ Does not exceed 0.05 Tg C02 Eq. or 0.05%.
a Percent of total emissions for year 2004.
b Includes both C02 and N20.
c SF6 emitted.
11 Includes both CFL, and N20.
e May include a mixture of MFCs, PFCs, and SF6,
f Includes both CFL, and C02.
a HFC-23 emitted.
11 Includes both C02 and PFCs.
Trends in Greenhouse Gas Emissions 2-23
-------
Figure 2-13
Emissions Allocated to Economic Sectors
2,50(T
2,000"
S 1'500~
o'
CJ
"~ 1,000-
500-
o-
Electricity Generation
Transportation
Industry
- Agriculture
- Commercial
Residential
§ § § § §
they are defined in this report. Figure 2-13 shows the trend
in emissions by sector from 1990 to 2004.
Emissions with Electricity Distributed to
Economic Sectors
It can also be useful to view greenhouse gas emissions
from economic sectors with emissions related to electricity
generation distributed into end-use categories (i.e.,
emissions from electricity generation are allocated to the
economic sectors in which the electricity is consumed).
The generation, transmission, and distribution of electricity,
which is the largest economic sector in the United States,
accounted for 33 percent of total U.S. greenhouse gas
emissions in 2004. Emissions increased by 27 percent since
1990, as electricity demand grew and fossil fuels remained
the dominant energy source for generation. The electricity
generation sector in the United States is composed of
traditional electric utilities as well as other entities, such
as power marketers and nonutility power producers. The
majority of electricity generated by these entities was
through the combustion of coal in boilers to produce high-
pressure steam that is passed through a turbine. Table 2-15
provides a detailed summary of emissions from electricity
generation-related activities.
To distribute electricity emissions among economic
end-use sectors, emissions from the source categories
assigned to the electricity generation sector were allocated
to the residential, commercial, industry, transportation,
and agriculture economic sectors according to retail sales
of electricity (EIA 2005a and Duffield 2005). These three
source categories include C02 from fossil fuel combustion,
CH4 and N20 from stationary combustion, and SF6 from
electrical transmission and distribution systems.5
When emissions from electricity are distributed
among these sectors, industry accounts for the largest
Table 2-15: Electricity Generation-Related Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Fuel Type or Source
C02
C02from Fossil Fuel Combustion
Coal
Natural Gas
Petroleum
Geothermal
Municipal Solid Waste Combustion
Limestone and Dolomite Use
CH4
Stationary Combustion*
N20
Stationary Combustion*
Municipal Solid Waste Combustion
SF6
Electrical Transmission and Distribution
Total
1990
1,809.2
1,795.5
1,517.3
176.9
100.9
0.4
10.9
2.8
0.6
0.6
8.0
7.6
0.5
28.6
28.6
1,846.4
1998
2,175.7
2,154.9
1,801.2
249.1
104.2
0.4
17.1
3.7
0.7
0.7
9.3
8.9
0.4
16.7
16.7
2,202.4
1999
2,187.2
2,165.6
1,807.7
260.9
96.6
0.4
17.6
4.0
0.7
0.7
9.3
8.9
0.4
16.1
16.1
2,213.3
2000
2,290.2
2,269.3
1,896.6
281.4
91.0
0.4
17.9
3.0
0.7
0.7
9.7
9.3
0.4
15.3
15.3
2,315.9
2001
2,258.8
2,237.3
1,845.9
289.5
101.6
0.4
18.6
2.9
0.7
0.7
9.6
9.1
0.5
15.3
15.3
2,284.4
2002
2,255.3
2,233.5
1,849.6
305.6
77.8
0.4
18.9
2.9
0.7
0.7
9.6
9.1
0.5
14.5
14.5
2,280.1
2003
2,283.9
2,262.2
1,887.2
277.6
97.0
0.4
19.4
2.4
0.7
0.7
9.8
9.3
0.5
14.0
14.0
2,308.5
2004
2,313.3
2,290.6
1,897.1
295.8
97.3
0.4
19.4
3.4
0.7
0.7
9.9
9.4
0.5
13.8
13.8
2,337.8
Note: Totals may not sum due to independent rounding.
* Includes only stationary combustion emissions related to the generation of electricity.
5 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.
2-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 2-16: U.S Greenhouse Gas Emissions by "Economic Sector" and Gas with Electricity-Related Emissions
Distributed (Tg C02 Eq.) and Percent of Total in 2004
Sector/Gas
Industry
Direct Emissions
C02
CH4
N20
MFCs, PFCs, and SF6
Electricity-Related
C02
CH4
N20
SF6
Transportation
Direct Emissions
C02
CH4
N20
MFCs"
Electricity-Related
C02
CH4
N20
SF6
Commercial
Direct Emissions
C02
CH4
N20
MFCs
Electricity-Related
C02
CH4
N20
SF6
Residential
Direct Emissions
C02
CH4
N20
MFCs
Electricity-Related
C02
CH4
N20
SF6
Agriculture
Direct Emissions
C02
CH4
N20
Electricity-Related
C02
CH4
N20
SF6
U.S. Territories
C02
Total
19S
2,074.
1,438.
1,082.
253.
41.
61.
635.
622.
0.
2.
9.
1,523.
1,520.
1,473.
4.
42.
3.
3.
979.
433.
222.
197.
13.
545.
534.
0.
2.
8.
950.
349.
338.
4.
6.
0.
601.
589.
0.
2.
9.
547.
486.
46.
157.
283.
60.
59.
0.
0.
33.
33.
6,109.
10
.6
,9
,3
,8
,1
,8
,7
,9
,2
,8
,9
.4
,3
,2
,5
,6
f
,1
,0
f
f
f
2
,6
,6
,8
,3
f
,6
,6
,2
,4
,5
.8
4
,0
,4
,7
,3
,4
2
,2
,6
,3
,1
,3
,3
,0
1
,7
,5
f
,3
,9
.8
,8
.0
1998
2,210.3
1,452.4
1,120.8
230.0
35.5
66.1
757.9
748.7
0.2
3.2
5.8
1,756.5
1,753.4
1,672.5
3.6
53.8
23.5
3.1
3.1
+
+
+
1,102.0
428.0
217.7
177.7
15.2
17.4
674.0
665.9
0.2
2.8
5.1
1,060.0
353.3
333.5
3.1
7.0
9.6
706.7
698.1
0.2
3.0
5.4
602.4
541.6
57.4
164.4
319.7
60.7
59.9
+
0.3
0.5
42.7
42.7
6,773.7
1999
2,174.4
1,411.0
1,098.4
221.3
34.2
57.1
763.4
754.4
0.2
3.2
5.5
1,822.5
1,819.3
1,734.6
3.4
53.0
28.2
3.2
3.1
+
+
+
1,115.8
430.6
218.6
176.0
15.7
20.3
685.1
677.1
0.2
2.9
5.0
1,083.2
372.6
352.3
3.3
7.1
9.8
710.7
702.3
0.2
3.0
5.2
575.0
523.9
59.8
164.2
299.9
50.9
50.3
+
0.2
0.4
44.2
44.2
6,814.9
2000
2,186.1
1,409.7
1,099.2
223.2
34.3
53.0
776.5
767.9
0.2
3.3
5.1
1,870.3
1,866.9
1,778.9
3.3
52.1
32.57
3.38
3.3
+
+
+
1,171.8
443.0
229.3
174.1
15.8
23.8
728.8
720.7
0.2
3.1
4.8
1,140.0
390.4
369.9
3.5
7.0
10.1
749.6
741.3
0.2
3.2
4.9
567.2
509.5
50.2
162.1
297.2
57.6
56.9
+
0.2
0.4
46.9
46.9
6,982.3
2001
2,073.6
1,366.6
1,081.4
219.7
29.4
36.0
707.0
699.1
0.2
3.0
4.7
1,856.2
1,852.7
1,764.6
3.1
48.9
36.10
3.44
3.4
+
+
+
1,190.8
439.5
224.9
171.6
15.9
27.1
751.3
742.9
0.2
3.2
5.0
1,136.2
381.6
361.5
3.1
6.7
10.3
754.6
746.1
0.2
3.2
5.1
582.6
514.4
50.2
162.1
302.2
68.0
67.3
+
0.3
0.5
54.0
54.0
6,893.1
2002
2,042.0
1,346.7
1,062.0
215.3
31.6
37.7
695.4
687.8
0.2
2.9
4.4
1,901.4
1,898.0
1,809.7
2.9
46.4
38.95
3.38
3.3
+
+
+
1,191.4
447.5
224.3
176.4
15.9
30.9
743.9
735.8
0.2
3.1
4.7
1,154.1
380.1
360.0
2.7
6.8
10.6
773.9
765.5
0.2
3.3
4.9
574.5
511.0
52.3
161.7
297.0
63.4
62.8
+
0.3
0.4
52.4
52.4
6,915.8
2003
2,066.0
1,342.7
1,065.4
216.0
31.4
30.0
723.3
715.6
0.2
3.1
4.4
1,903.2
1,898.9
1,811.1
2.8
43.7
41.22
4.30
4.3
+
+
+
1,204.3
466.5
235.8
179.7
16.1
34.8
737.8
729.9
0.2
3.1
4.5
1,182.9
399.8
378.8
3.0
7.0
11.0
783.1
774.8
0.2
3.3
4.8
544.3
484.2
44.3
162.1
277.8
60.0
59.3
+
0.3
0.4
58.6
58.6
6,959.1
2004
2,103.0
1,377.3
1,101.3
211.3
31.0
33.7
725.7
718.1
0.2
3.1
4.3
1,959.8
1,955.1
1,865.7
2.7
41.7
45.03
4.69
4.6
+
+
+
1,211.0
459.9
226.0
178.5
16.3
39.0
751.1
743.3
0.2
3.2
4.4
1,181.9
391.1
369.6
2.9
7.3
11.3
790.8
782.6
0.2
3.3
4.7
556.9
491.3
50.3
160.6
280.4
65.4
64.7
+
0.3
0.4
61.9
61.9
7,074.4
Percent3
29.7%
19.5%
15.6%
3.0%
0.4%
0.5%
10.3%
10.2%
0.1%
27.7%
27.6%
26.4%
0.0%
0.6%
0.6%
0.1%
0.1%
+
+
+
17.1%
6.5%
3.2%
2.5%
0.2%
0.6%
10.6%
10.5%
+
+
0.1%
16.7%
5.5%
5.2%
+
0.1%
0.2%
11.2%
11.1%
0.1%
7.9%
6.9%
0.7%
2.3%
4.0%
0.9%
0.9%
+
+
+
0.9%
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 C02 Eq. or 0.05%.
aPercents for year 2004.
b Includes primarily HFC-134a.
Trends in Greenhouse Gas Emissions 2-25
-------
share of U.S. greenhouse gas emissions (30 percent).
Emissions from the residential and commercial sectors also
increase substantially when emissions from electricity are
included, due to their relatively large share of electricity
consumption. Transportation activities remain the second
largest contributor to total U.S. emissions (28 percent). In
all sectors except agriculture, C02 accounts for more than
80 percent of greenhouse gas emissions, primarily from the
combustion of fossil fuels.
Table 2-16 presents a detailed breakdown of emissions
from each of these economic sectors, with emissions from
electricity generation distributed to them. Figure 2-14 shows
the trend in these emissions by sector from 1990 to 2004.
Transportation
Transportation activities accounted for 28 percent
of U.S. greenhouse gas emissions in 2004. Table 2-17
provides a detailed summary of greenhouse gas emissions
from transportation-related activities. Total emissions in
Table 2-17 differ slightly from those shown in Table 2-16
primarily because the table below excludes a few minor
non-transportation mobile sources, such as construction and
industrial equipment.
From 1990 to 2004, transportation emissions rose by
29 percent due, in part, to increased demand for travel and
the stagnation of fuel efficiency across the U.S. vehicle
fleet. Since the 1970s, the number of highway vehicles
registered in the United States has increased faster than
the overall population, according to the Federal Highway
Administration (FHWA). Likewise, the number of miles
driven (up 38 percent from 1990 to 2004) and the gallons
of gasoline consumed each year in the United States have
increased steadily since the 1980s, according to the FHWA
and Energy Information Administration, respectively. These
increases in motor vehicle usage are the result of a confluence
of factors including population growth, economic growth,
urban sprawl, low fuel prices, and increasing popularity of
sport utility vehicles and other light-duty trucks that tend
to have lower fuel efficiency. A similar set of social and
economic trends has led to a significant increase in air travel
and freight transportation by both air and road modes during
the time series.
Figure 2-14
Emissions with Electricity Distributed to Economic Sectors
2,500-i
2,000-
1,500-
1,000-
500-
Transportation
Commercial
^^^^—
Residential
Agriculture
Almost all of the energy consumed for transportation
was supplied by petroleum-based products, with nearly two-
thirds 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 C02 from fossil fuel combustion, which
increased by 27 percent from 1990 to 2004. This rise in C02
emissions, combined with an increase of 45.0 Tg C02 Eq.
in HFC emissions over the same period, led to an increase
in overall emissions from transportation activities of 29
percent.
2.3. Indirect Greenhouse Gas
Emissions (CO, NOX, NMVOCs,
and S02)
The reporting requirements of the UNFCCC6 request
that information be provided on indirect greenhouse gases,
which include CO, NOX, NMVOCs, and S02. 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 S02, by affecting the absorptive
characteristics of the atmosphere. Additionally, some of
these gases may react with other chemical compounds in the
6 See
2-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Box 2-2: Methodology for Aggregating Emissions by Economic Sector
In orderto aggregate emissions by economic sector, source category emission estimates were generated according to the methodologies
outlined in the appropriate sections of this report. Those emissions were then simply reallocated into economic sectors. In most cases,
the IPCC subcategories distinctly fit into an apparent economic sector category. Several exceptions exist, and the methodologies used to
disaggregate these subcategories are described below:
• Agricultural C02 Emissions from Fossil Fuel Combustion, and non-C02 emissions from Stationary and Mobile Combustion.
Emissions from on-farm energy use were accounted for in the Energy chapter as part of the industrial and transportation end-use
sectors. To calculate agricultural emissions related to fossil fuel combustion, energy consumption estimates were obtained from
economic survey data from the U.S. Department of Agriculture (Duffield 2005) and fuel sales data (EIA 1991 through 2005). To
avoid double-counting, emission estimates of C02 from fossil fuel combustion and non-C02 from stationary and mobile combustion
were subtracted from the industrial economic sector, although some of these fuels may have been originally accounted for under
the transportation end-use sector.
• Landfills, Wastewater Treatment, and Human Sewage. CH4 emissions from landfills and wastewater treatment, as well as N20
emissions from human sewage, were allocated to the commercial sector.
• Waste Combustion. C02 and N20 emissions from waste combustion were allocated completely to the electricity generation sector
since nearly all waste combustion occurs in waste-to-energy facilities.
• Limestone and Dolomite Use. C02 emissions from limestone and dolomite use are allocated to the electricity generation (50
percent) and industrial (50 percent) sectors, because 50 percent of the total emissions for this source are due to flue gas
desulfurization.
Substitution of Ozone Depleting Substances. All greenhouse gas emissions resulting from the substitution of ozone depleting
substances were placed in the industrial economic sector, with the exception of emissions from domestic, commercial, mobile,
and transport refrigeration/air-conditioning systems, which were placed in the residential, commercial, and transportation sectors,
respectively. Emissions from non-MDI aerosols were attributed to the residential economic sector.
• Settlement Soil Fertilization, Forest Soil Fertilization. Emissions from settlement soil fertilization were allocated to the residential
economic sector; forest soil fertilization was allocated to the agriculture economic sector.
atmosphere to form compounds that are greenhouse gases. ozone formation. They can also alter the atmospheric
Carbon monoxide is produced when carbon-containing fuels lifetimes of other greenhouse gases. Another example
are combusted incompletely. Nitrogen oxides (i.e., NO and of indirect greenhouse gas formation into greenhouse
N02) are created by lightning, fires, fossil fuel combustion, gases is CD's interaction with the hydroxyl radical—the
and in the stratosphere from nitrous oxide (N20). Non-CH4 major atmospheric sink for CH4 emissions—to form C02.
volatile organic compounds—which include hundreds of Therefore, increased atmospheric concentrations of CO
organic compounds that participate in atmospheric chemical limit the number of hydroxyl molecules (OH) available to
reactions (i.e., propane, butane, xylene, toluene, ethane, and destroy CH4.
many others)—are emitted primarily from transportation, Since 1970; the United States has published estimates
industrial processes, and non-industrial consumption of of annual emissions of C0, NOX, NMVOCs, and S02
organic solvents. In the United States, S02 is primarily (EPA 2005) ,7 which are regulated under the Clean Air Act.
emitted from coal combustion for electric power generation Table 2_i8 shows that fuel combustion accounts for the
and the metals industry. Sulfur-containing compounds emitted majority of emissions of these indirect greenhouse gases.
into the atmosphere tend to exert a negative radiative forcing Industrial prOcesses-^uch as the manufacture of chemical
(i.e., cooling) and therefore are discussed separately. and allied productS; metals processing, and industrial uses
One important indirect climate change effect of of solvents—are also significant sources of CO, NOX and
NMVOCs and NOX is their role as precursors for tropospheric NMVOCs.
7 NOX and CO emission estimates from field burning of agricultural residues were estimated separately, and therefore not taken from EPA (2005).
Trends in Greenhouse Gas Emissions 2-27
-------
Table 2-17: Transportation-Related Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Vehicle Type
C02
Passenger Cars
Light-Duty Trucks
Other Trucks
Buses
Aircraft3
Ships and Boats
Locomotives
Other"
International Bunker Fuels0
CH4
Passenger Cars
Light-Duty Trucks
Other Trucks and Buses
Aircraft
Ships and Boats
Locomotives
Motorcycles
International Bunker Fuels0
N20
Passenger Cars
Light-Duty Trucks
Other Trucks and Buses
Aircraft
Ships and Boats
Locomotives
Motorcycles
International Bunker Fuels0
MFCs
Mobile Air Conditioned
Refrigerated Transport
Total
1990
1,476.2
618.9
315.8
225.3
8.2
177.2
43.6
37.8
49.5
93.6
4.5
2.6
1.4
0.2
0.2
1
0.2
42.7
25.4
14.1
0.8
1.7
0.4
0.3
I
1,523.4 |
1998
1,675.6
621.5
437.3
306.5
9.8
181.3
27.3
43.0
48.8
103.3
3.6
1.8
1.3
0.2
0.1
+
0.1
+
0.2
53.9
26.7
23.7
1.2
1.8
0.2
0.3
+
1.0
23.5
16.5
7.0
1,756.6
1999
1,737.8
631.2
455.0
322.4
11.0
186.8
37.5
44.6
49.4
102.6
3.4
1.7
1.2
0.2
0.2
0.1
0.1
+
0.1
53.1
25.9
23.5
1.2
1.8
0.3
0.3
+
0.9
28.2
19.7
8.5
1,822.6
2000
1,782.3
633.4
458.3
337.9
10.8
193.2
55.1
44.6
48.9
102.2
3.3
1.6
1.1
0.2
0.2
0.1
0.1
+
0.1
52.1
25.1
23.1
1.2
1.9
0.4
0.3
+
0.9
32.6
22.8
9.8
1,870.3
2001
1,768.1
636.5
462.2
337.0
9.9
183.5
48.1
44.8
46.2
98.5
3.1
1.5
1.1
0.2
0.1
0.1
0.1
+
0.1
48.9
23.9
21.2
1.3
1.8
0.4
0.3
+
0.9
36.1
25.3
10.8
1,856.2
2002
1,813.1
651.6
474.8
351.0
9.5
174.9
57.0
45.2
49.0
89.5
2.9
1.4
1.0
0.2
0.1
0.1
0.1
+
0.1
46.4
22.9
19.7
1.3
1.7
0.5
0.3
+
0.8
38.9
27.4
11.5
1,901.4
2003
1,815.5
631.3
509.6
347.3
10.3
171.8
49.7
47.1
48.4
84.1
2.8
1.3
0.9
0.2
0.1
0.1
0.1
+
0.1
43.7
21.8
18.1
1.3
1.7
0.4
0.3
+
0.8
41.2
28.9
12.3
1,903.1
2004
1,870.4
636.4
526.0
365.3
10.3
179.6
54.4
49.8
48.7
94.5
2.7
1.3
0.9
0.2
0.1
0.1
0.1
+
0.1
41.6
21.0
16.7
1.3
1.8
0.4
0.4
+
0.9
45.0
31.9
13.1
1,959.8
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
a Aircraft emissions consist of emissions from all jet fuel (less bunker fuels) and aviation gas consumption.
b "Other" C02 emissions include motorcycles, pipelines, and lubricants.
c Emissions from International Bunker Fuels include emissions from both civilian and military activities, but are not included in totals.
11 Includes primarily HFC-134a.
2-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 2-18: Emissions of NOX, CO, NMVOCs, and S02 (Gg)
Gas/Activity
NO,
Stationary Fossil Fuel Combustion
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Solvent Use
Agricultural Burning
Waste
CO
Stationary Fossil Fuel Combustion
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Solvent Use
Agricultural Burning
Waste
NMVOCs
Stationary Fossil Fuel Combustion
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Solvent Use
Agricultural Burning
Waste
S02
Stationary Fossil Fuel Combustion
Mobile Fossil Fuel Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Solvent Use
Agricultural Burning
Waste
1990
22,860
9,884
12,1341
139
82 1
591 1
1 1
28 I
+ 1
130,580
4,999
119,482
302
978
4,124
4I
689
1 1
20,937
912
10,9331
555
222
2,426
5,217
NA|
673
20,936
18,4071
793
390
39l
1,306
+ 1
NA|
+
1 1998
21,964
9,419
11,592
130
145
1 637
3
1 35
3
98,984
3,927
87,940
332
2,826
3,163
1
1 789
5
16,403
1,016
7,742
440
326
2,047
4,671
NA
161
17,189
15,191
665
310
30
991
1
NA
| 1
1999
20,530
8,344
11,300
109
143
595
3
34
3
94,361
5,024
83,484
145
2,725
2,156
46
767
13
15,869
1,045
7,586
414
302
1,813
4,569
NA
140
15,917
13,915
704
283
30
984
1
NA
1
2000
20,288
8,002
11,395
111
114
626
3
35
2
92,895
4,340
83,680
146
1,670
2,217
46
790
8
15,228
1,077
7,230
389
257
1,773
4,384
NA
119
14,829
12,848
632
286
29
1,031
1
NA
1
2001
19,414
7,667
10,823
113
114
656
3
35
2
89,329
4,377
79,972
147
1,672
2,339
45
770
8
15,048
1,080
6,872
400
258
1,769
4,547
NA
122
14,452
12,461
624
289
30
1,047
1
NA
1
2002
18,850
7,522
10,389
135
134
630
6
33
2
87,428
4,020
78,574
116
1,672
2,286
46
706
8
14,217
923
6,560
340
281
1,723
4,256
NA
133
13,928
11,946
631
315
24
1,009
1
NA
1
2003
17,995
7,138
9,916
135
134
631
6
34
2
87,518
4,020
78,574
116
1,672
2,286
46
796
8
13,877
922
6,212
341
282
1,725
4,262
NA
134
14,208
12,220
637
315
24
1,009
1
NA
1
2004
17,076
6,662
9,465
135
134
632
6
39
2
87,599
4,020
78,574
116
1,672
2,286
46
877
8
13,556
922
5,882
341
282
1,727
4,267
NA
134
13,910
11,916
644
315
24
1,009
1
NA
1
Source: (EPA 2005) except for estimates from field burning of agricultural residues.
+ Does not exceed 0.5 Gg
NA (Not Available)
Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-29
-------
Box 2-3: Sources and Effects of Sulfur Dioxide
Sulfur dioxide (S02) emitted into the atmosphere through natural and anthropogenic processes affects the Earth's radiative budget
through its photochemical transformation into sulfate aerosols that can (1) scatter radiation from the sun back to space, thereby reducing
the radiation reaching the Earth's surface; (2) affect cloud formation; and (3) affect atmospheric chemical composition (e.g., by providing
surfaces for heterogeneous chemical reactions). The indirect effect of sulfur-derived aerosols on radiative forcing can be considered in
two parts. The first indirect effect is the aerosols' tendency to decrease water droplet size and increase water droplet concentration in the
atmosphere. The second indirect effect is the tendency of the reduction in cloud droplet size to affect precipitation by increasing cloud lifetime
and thickness. Although still highly uncertain, the radiative forcing estimates from both the first and the second indirect effect are believed
to be negative, as is the combined radiative forcing of the two (IPCC 2001). However, because S02 is short-lived and unevenly distributed
in the atmosphere, its radiative forcing impacts are highly uncertain.
Sulfur dioxide is also a major contributor to the formation of regional haze, which can cause significant increases in acute and chronic
respiratory diseases. Once S02 is emitted, it is chemically transformed in the atmosphere and returns to the Earth as the primary source of acid
rain. Because of these harmful effects, the United States has regulated S02 emissions in the Clean Air Act.
Electricity generation is the largest anthropogenic source of S02 emissions in the United States, accounting for 86 percent in 2004.
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.
2-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
3. Energy
Energy-related activities were the primary sources of U.S. anthropogenic greenhouse gas emissions, accounting
for 86 percent of total emissions on a carbon equivalent basis in 2004. This included 97, 39, and 15 percent of
the nation's carbon dioxide (C02), methane (CH4), and nitrous oxide (N20) emissions, respectively. Energy-
related C02 emissions alone constituted 82 percent of national emissions from all sources on a carbon equivalent basis,
while the non-C02 emissions from energy-related activities represented a much smaller portion of total national emissions
(4 percent collectively).
Emissions from fossil fuel combustion comprise the vast majority of energy-related emissions, with C02 being the
primary gas emitted (see Figure 3-1). Globally, approximately 25,575 Tg of C02 were added to the atmosphere through the
combustion of fossil fuels in 2002, of which the United States accounted for about 23 percent.1 Due to the relative importance
of fossil fuel combustion-related C02 emissions, they are considered separately, and in more detail than other energy-related
emissions (see Figure 3-2). Fossil fuel combustion also emits CH4 and N20, as well as indirect greenhouse gases such as
nitrogen oxides (NOJ, carbon monoxide (CO), and non-CH4 volatile organic compounds (NMVOCs). Mobile fossil fuel
combustion was the second largest source of N20 emissions in the United States, and overall energy-related activities were
collectively the largest source of these indirect greenhouse gas emissions.
Energy-related activities other than fuel combustion, such as the production, transmission, storage, and distribution
of fossil fuels, also emit greenhouse gases. These emissions consist primarily of fugitive CH4 from natural gas systems,
petroleum systems, and coal mining. Smaller quantities of C02, CO, NMVOCs, and NOX are also emitted.
The combustion of biomass and biomass-based fuels Figure 3-1
also emits greenhouse gases. C02 emissions from these
activities, however, are not included in national emissions
totals because biomass fuels are of biogenic origin. It is
assumed that the carbon released during the consumption
of biomass is recycled as U.S. forests and crops regenerate,
causing no net addition of C02 to the atmosphere. The net
impacts of land-use and forestry activities on the carbon cycle
are accounted for within the Land Use, Land-Use Change,
and Forestry chapter. Emissions of other greenhouse gases
from the combustion of biomass and biomass-based fuels
are included in national totals under stationary and mobile
o so 100
combustion. Tg cq, Eq.
2004 Energy Chapter Greenhouse Gas Sources
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Combustion
Petroleum Systems
Stationary Combustion |
Municipal Solid Waste Combustion
Natural Gas Flaring |
Abandoned Underground Coal Mines |
0
5,656.6
Energy as a Portion
of all Emissions
150
200
1 Global C02 emissions from fossil fuel combustion were taken from Marland etal. (2003)
Energy 3-1
-------
Table 3-1: C02, CH4, and N20 Emissions from Energy (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Municipal Solid Waste Combustion
Natural Gas Flaring
Biomass-Wood*
International Bunker Fuels*
Biomass-Ethanol*
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground Coal Mines
Mobile Combustion
International Bunker Fuels*
N20
Mobile Combustion
Stationary Combustion
Municipal Solid Waste Combustion
International Bunker Fuels*
Total
1990
4,830.5
4,696.6
117.2
10.9
5.8
212.5
113.5
4.2
261.6
126.7
81.9
34.4
7.9
6.0
4.7
0.2
56.2
43.5
12.3
0.5
1.0
5,148.3
• 1998
5,448.3
5,271.8
152.8
17.1
«6.6
209.5
114.6
7.7
235.4
125.4
62.8
429.7
6.8
6.9
3.8
0.2
68.6
54.8
13.4
0.4
• 1.0
5,752.3
1999
5,527.6
5,342.4
160.6
17.6
6.9
214.3
105.2
8.0
226.8
121.7
58.9
28.5
7.0
6.9
3.6
0.1
67.9
54.1
13.4
0.4
0.9
5,822.3
2000
5,698.1
5,533.7
140.7
17.9
5.8
217.6
101.4
9.2
228.7
126.7
56.3
27.8
7.3
7.2
3.5
0.1
67.5
53.1
13.9
0.4
0.9
5,994.3
2001
5,642.7
5,486.9
131.0
18.6
6.1
190.8
97.8
9.7
225.0
125.6
55.5
27.4
6.6
6.6
3.3
0.1
63.9
50.0
13.5
0.5
0.9
5,931.6
2002
5,663.3
5,501.8
136.5
18.9
6.2
182.9
89.5
11.5
220.1
125.4
52.5
26.8
6.2
6.0
3.2
0.1
61.3
47.5
13.2
0.5
0.8
5,944.6
2003
5,730.0
5,571.1
133.5
19.4
6.1
186.3
84.1
15.8
220.9
124.7
54.8
25.9
6.5
5.8
3.0
0.1
58.9
44.8
13.6
0.5
0.8
6,009.8
2004
5,835.3
5,656.6
153.4
19.4
6.0
191.7
94.5
19.5
215.8
118.8
56.3
25.7
6.4
5.6
2.9
0.1
57.0
42.8
13.7
0.5
0.9
6,108.2
* These values are presented for informational purposes only and are not included or are already accounted for in totals.
Note: Totals may not sum due to independent rounding.
Table 3-2: C02, CH4, and N20 Emissions from Energy (Gg)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Municipal Solid Waste
Combustion
Natural Gas Flaring
Biomass-Wood*
International Bunker Fuels
Biomass-Ethanol*
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned Underground
Coal Mines
Mobile Combustion
International Bunker Fuels
N20
Mobile Combustion
Stationary Combustion
Municipal Solid Waste
Combustion
International Bunker Fuels
1990
4,830,464
4,696,571
117,168
10,919
5,805
212,547
* 113,503
4,155
12,459
6,034
3,900
1,640
374
286
224
8
181
140
40 I
1
3
1998
5,448,279
5,271,819
152,800
17,094
6,566
209,490
114,557
7,711
11,211
5,973
2,990
1,414
325
328
181
7
221
177
43
1
3
1999
5,527,589
5,342,446
160,569
17,632
6,943
214,323
105,228
8,017
10,800
5,797
2,807
1,358
335
330
173
6
219
174
43
1
3
2000
5,698,086
5,533,710
140,687
17,921
5,769
217,577
101,366
9,188
10,893
6,033
2,679
1,325
346
343
167
6
218
171
45
1
3
2001
5,642,664
5,486,908
131,028
18,634
6,094
190,778
97,815
9,701
10,715
5,981
2,644
1,303
316
313
159
5
206
161
44
1
3
2002
5,663,284
5,501,763
136,455
18,862
6,204
182,878
89,489
11,473
10,480
5,971
2,500
1,274
295
288
152
4
198
153
43
2
3
2003
5,730,029
5,571,088
133,489
19,360
6,091
186,339
84,083
15,771
10,517
5,939
2,611
1,236
311
277
144
4
190
144
44
2
2
2004
5,835,335
5,656,554
153,386
19,360
6,034
191,737
94,499
19,493
10,277
5,658
2,682
1,222
307
269
140
5
184
138
44
2
3
* These values are presented for informational purposes only and are not included or are already accounted for in totals.
Note: Totals may not sum due to
independent rounding.
3-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 3-2
2004 U.S. Fossil Carbon Flows (Tg C02 Eq.)
Fossil Fuel
Energy Exports
261
Coal Emissions
2,027
Natural Gas Emissions
1,191
NEU Emissions 124
Non-Energy Use
Carbon Seguestered
250
Fossil Fuel
Combustion Residual
(Not Oxidized Fraction)
53
Note: Totals may not sum due to independent rounding.
The "Balancing Item" above accounts for the statistical imbalances
and unknowns in the reported data sets combined here.
Table 3-1 summarizes emissions from the Energy sector
in units of teragrams of C02 equivalents (Tg C02 Eq.), while
unweighted gas emissions in gigagrams (Gg) are provided in
Table 3-2. Overall, emissions due to energy-related activities
were 6,108.2 Tg C02 Eq. in 2004, an increase of 19 percent
since 1990.
3.1. Carbon Dioxide Emissions from
Fossil Fuel Combustion (IPCC Source
Category 1 A)
C02 emissions from fossil fuel combustion in 2004
increased by 1.5 percent from the previous year. This
increase is primarily a result of increased demand for
fuels due to a growing economy, expanding industrial
production, and increased demand for transportation. In
2004, C02 emissions from fossil fuel combustion were
5,656.6TgC02 Eq., or 20 percent above emissions in 1990
(see Table 3-3).2
Trends in C02 emissions from fossil fuel combustion
are influenced by many long-term and short-term factors. On
a year-to-year basis, the overall demand for fossil fuels in
the United States and other countries generally fluctuates in
response to changes in general economic conditions, energy
prices, weather, and the availability of non-fossil alternatives.
For example, in a year with increased consumption of
goods and services, low fuel prices, severe summer and
winter weather conditions, nuclear plant closures, and lower
precipitation feeding hydroelectric dams, there would likely
be proportionally greater fossil fuel consumption than a
year with poor economic performance, high fuel prices,
mild temperatures, and increased output from nuclear and
hydroelectric plants.
Longer-term changes in energy consumption patterns,
however, tend to be more a function of aggregate societal
trends that affect the scale of consumption (e.g., population,
number of cars, and size of houses), the efficiency with which
energy is used in equipment (e.g., cars, power plants, steel
mills, and light bulbs), and social planning and consumer
2 An additional discussion of fossil fuel emission trends is presented in the Trends in U.S. Greenhouse Gas Emissions Chapter.
Energy 3-3
-------
Table 3-3: C02 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg C02 Eq.)
Fuel/Sector
Coal
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Natural Gas
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Petroleum
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Geothermal*
Total
1990
1,683.8
2.9
11.6
151.3
NE
1,517.3
0.6
1,006.9
238.6
142.4
413.2
35.9
176.9
NO I
2,005.5
96.5
68.5
286.7
1,425.5
100.9
27.4
0.40
4,696.6
1998
1,944.0
1.2
9.5
131.1
NE
1,801.2
1.0
1,168.4
246.6
163.6
474.1
35.1
249.1
NO
2,159.0
85.8
44.6
266.7
1,625.2
104.2
32.5
0.38
5,271.8
1999
1,946.2
1.3
9.6
126.7
NE
1,807.7
0.9
1,172.2
256.4
165.3
453.9
35.6
260.9
NO
2,223.7
94.6
43.7
268.4
1,686.8
96.6
33.6
0.38
5,342.4
2000
2,033.8
1.0
8.1
127.2
NE
1,896.6
0.9
1,220.2
269.2
171.8
461.7
35.5
281.4
0.7
2,279.3
99.7
49.3
273.7
1,731.4
91.0
34.2
0.36
5,533.7
2001
1,982.5
1.1
8.6
126.1
NE
1,845.9
0.9
1,173.4
259.0
164.9
424.8
33.9
289.5
1.2
2,330.6
101.4
51.4
310.2
1,719.7
101.6
46.4
0.35
5,486.9
2002
1,976.8
1.0
8.6
116.4
NE
1,849.6
1.2
1,211.4
265.6
170.8
431.2
37.1
305.6
1.2
2,313.2
93.3
45.0
294.6
1,761.7
77.8
40.7
0.37
5,501.8
2003
2,017.4
0.9
7.9
117.7
NE
1,887.2
3.6
1,184.8
276.9
175.4
416.1
37.3
277.6
1.4
2,368.5
100.9
52.5
310.8
1,763.8
97.0
43.7
0.37
5,571.1
2004
2,027.0
1.0
8.2
117.1
NE
1,897.1
3.6
1,191.2
265.5
162.7
428.4
37.4
295.8
1.3
2,438.0
103.0
55.1
318.0
1,818.1
97.3
46.5
0.37
5,656.6
NE (Not estimated)
NO (Not occurring)
+ Does not exceed 0.05 Tg C02 Eq.
* Although not technically a fossil fuel, geothermal energy-related C02 emissions are included for reporting purposes.
Note: Totals may not sum due to independent rounding.
behavior (e.g., walking, bicycling, or telecommuting to work
instead of driving).
C02 emissions also depend on the source of energy and
its carbon intensity. The amount of carbon in fuels varies
significantly by fuel type. For example, coal contains the
highest amount of carbon per unit of useful energy. Petroleum
has roughly 75 percent of the carbon per unit of energy as coal,
and natural gas has only about 55 percent.3 Producing a unit of
heat or electricity using natural gas instead of coal can reduce
the C02 emissions associated with energy consumption, and
using nuclear or renewable energy sources (e.g., wind) can
essentially eliminate emissions (see Box 3-2). Table 3-4 shows
annual changes in emissions during the last five years for coal,
petroleum, and natural gas in selected sectors.
In the United States, 86 percent of the energy consumed
in 2004 was produced through the combustion of fossil fuels
such as coal, natural gas, and petroleum (see Figure 3-3 and
Figure 3-4). The remaining portion was supplied by nuclear
electric power (8 percent) and by a variety of renewable
energy sources (6 percent), primarily hydroelectric power
and biofuels (EIA 2005a). Specifically, petroleum supplied
the largest share of domestic energy demands, accounting
for an average of 39 percent of total energy consumption
from 1990 through 2004. Natural gas and coal followed in
order of importance, accounting for 24 and 23 percent of
total consumption, respectively. Petroleum was consumed
primarily in the transportation end-use sector, the vast
majority of coal was used in electricity generation, and
natural gas was broadly consumed in all end-use sectors
except transportation (see Figure 3-5) (EIA 2005a).
Fossil fuels are generally combusted for the purpose
of producing energy for useful heat and work. During the
combustion process, the carbon stored in the fuels is oxidized
and emitted as C02 and smaller amounts of other gases,
3 Based on national aggregate carbon content of all coal, natural gas, and petroleum fuels combusted in the United States.
3-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-4: Annual Change in C02 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg C02 Eq.
and Percent)
Sector
Electricity Generation
Electricity Generation
Electricity Generation
Transportation3
Residential
Commercial
Industrial
Industrial
All Sectors11
Fuel Type
Coal
Natural Gas
Petroleum
Petroleum
Natural Gas
Natural Gas
Coal
Natural Gas
All Fuels"
2000 to
-50.7
8.2
10.5
-11.7
-10.2
-6.9
-1.1
-36.8
-46.8
2001
-3%
3%
12%
-1%
-4%
-4%
-1%
-8%
-1%
2001
3.8
16.1
-23.7
42.0
6.6
5.9
-9.7
6.3
14.9
to 2002
0%
6%
-23%
2%
3%
4%
-8%
1%
0%
2002 to
37.5
-28.0
19.2
2.0
11.4
4.6
1.4
-15.0
69.3
2003
2%
-9%
25%
0%
4%
3%
1%
-3%
1%
2003 to
9.9
18.2
0.3
54.3
-11.4
-12.7
-0.7
12.3
85.5
2004
1%
7%
0%
3%
-4%
-7%
-1%
3%
2%
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table.
Figure 3-3
6.1% Renewable
23.0% Natural Gas
22.5% Coal
Figure 3-4
U.S. Energy Consumption (Quadrillion Btu)
120
=" 100
QD
S
= 80
I 6°
o
£ 20 -
0 -
Total Energy
Renewable & Nuclear
including CH4, CO, and NMVOCs.4 These other carbon
containing non-C02 gases are emitted as a by-product of
incomplete fuel combustion, but are, for the most part,
eventually oxidized to C02 in the atmosphere. Therefore,
except for the soot and ash left behind during the combustion
process, all the carbon in fossil fuels used to produce energy
is eventually converted to atmospheric C02.
For the purpose of international reporting, the
Intergovernmental Panel on Climate Change (IPCC) (IPCC/
UNEP/OECD/IEA 1997) recommends that particular
Figure 3-5
2004 C02 Emissions from Fossil Fuel
Combustion by Sector and Fuel Type
Note: Expressed as gross calorific values
2,500 -i
2,000 -
Natural Gas
Petroleum
Coal
^^^^^H
Relative Contribution
by Fuel Type
.*! l_
Residential Commercial Industrial Transpor- Electricity U.S.
tation Generation Territories
Note: The electricity generation sector also includes emissions of less than 0.01 Tg
C02 Eq from geometrical-based electricity generation.
4 See the sections entitled Stationary Combustion and Mobile Combustion in this chapter for information on non-C02 gas emissions from fossil fuel
combustion.
Energy 3-5
-------
Box 3-1: Weather and Non-Fossil Energy Effects on C02 from Fossil Fuel Combustion Trends
In 2004, weather conditions became milder in both the winter and summer. Warmer winter conditions led to a decrease in demand for
heating fuels. Though the summer of 2004 was cooler than the previous year, demand for electricity still increased, likely due to the growing
economy. The winter was warmer than usual, with heating degree days in the United States 5 percent below normal (see Figure 3-6). Summer
temperatures were slightly warmer than usual, with cooling degree days 1 percent above normal (see Figure 3-7) (EIA 2005f).5
Figure 3-6
Annual Deviations from Normal Heating Degree Days for the United States (1950-2004)
— 15n
o'w
ll 10-
T3E 5-
I'l -10-
a
-15 -1
Note: Climatol
Normal (4,576 Heating Degree Days)
II • •
•III "• B ••
99% Confidence
0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)0)
:gical normal data are highlighted. Statistical confidence interval for "normal" climatology period of 1961 through 1990.
Figure 3-7
Annual Deviations from Normal Cooling Degree Days for the United States (1950-2004)
_ 20
o| 15
°,M ™
II 5
* o-U_
iliLl
99% Confidence
= .= -5
II -10
~t -15
-20
Normal (1,193 Cooling Degree Days)
Jlmill
8 I
Note: Climatological normal data are highlighted. Statistical confidence interval for "normal" climatology period of 1961 through 1990.
Although no new U.S. nuclear power plants have been
constructed in recent years, the utilization (i.e., capacity factors6)
of existing plants reached record levels in 2004, at over 90 percent.
Electricity output by hydroelectric power plants increased in 2004
by approximately 10 percent. Electricity generated by nuclear plants
in 2004 provided almost 3 times as much of the energy consumed
in the United States as hydroelectric plants (EIA 2005a). Aggregate
nuclear and hydroelectric power plant capacity factors since 1973
are shown in Figure 3-8.
Figure 3-8
Aggregate Nuclear and Hydroelectric Power Plant
Capacity Factors in the United States (1974-2004)
5 Degree days are relative measurements of outdoor air temperature. Heating degree days are deviations of the mean daily temperature below 65° F, while
cooling degree days are deviations of the mean daily temperature above 65° F. Heating degree days have a considerably greater affect on energy demand
and related emissions than do cooling degree days. Excludes Alaska and Hawaii. Normals are based on data from 1971 through 2000. The variation in these
normals during this time period was ±10 percent and ±14 percent for heating and cooling degree days, respectively (99 percent confidence interval).
6 The capacity factor is defined as the ratio of the electrical energy produced by a generating unit for a given period of time to the electrical energy that
could have been produced at continuous full-power operation during the same period (EIA 2005a).
3-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
adjustments be made to national fuel consumption statistics.
Certain fossil fuels can be manufactured into plastics,
asphalt, lubricants, or other products. A portion of the
carbon consumed for these non-energy products can be
stored (i.e., sequestered) indefinitely. To accountfor the fact
that the carbon in these fuels ends up in products instead
of being combusted (i.e., oxidized and released into the
atmosphere), consumption of fuels for non-energy purposes
is estimated and subtracted from total fuel consumption
estimates. Emissions from non-energy uses of fuels are
estimated in the Carbon Emitted and Stored in Products
from Non-Energy Uses of Fossil Fuels section in this
chapter.
According to the UNFCCC reporting guidelines,
C02 emissions from the consumption of fossil fuels for
aviation and marine international transport activities (i.e.,
international bunker fuels) should be reported separately,
and not included in national emission totals. Estimates of
international bunker fuel emissions for the United States are
provided in Table 3-5.
End-Use Sector Consumption
An alternative method of presenting C02 emissions is
to allocate emissions associated with electricity generation
to the sectors in which it is used. Four end-use sectors
were defined: industrial, transportation, residential, and
commercial. For the discussion below, electricity generation
emissions have been distributed to each end-use sector based
upon the sector's share of national electricity consumption.
This method of distributing emissions assumes that each
sector consumes electricity generated from an equally
carbon-intensive mix of fuels and other energy sources.
After the end-use sectors are discussed, emissions from
electricity generation are addressed separately. Emissions
from U.S. territories are also calculated separately due to
a lack of end-use-specific consumption data. Table 3-6 and
Table 3-5: C02 Emissions from International Bunker Fuels (Tg C02 Eq.)*
Vehicle Mode
Aviation
Marine
Total
1990
46.2
67.3
113.5
1998
56.7
57.9
114.6
1999
58.8
46.4
105.2
2000
60.5
40.9
101.4
2001
59.3
38.5
97.8
2002
61.8
27.7
89.5
2003
59.4
24.6
84.1
2004
59.9
34.6
94.5
* See International Bunker Fuels section for additional details.
Note: Totals may not sum due to independent rounding.
Table 3-6: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)
End-Use Sector
Transportation
Combustion
Electricity
Industrial
Combustion
Electricity
Residential
Combustion
Electricity
Commercial
Combustion
Electricity
U.S. Territories
Total
Electricity Generation
1,
1,
1,
4,
1,
1990
464.4
461.4
3.0
528.3
851 1
677.2
922.8
338.0
584.8
753.1
222.6
530.5
28.0
696.6
795.5
1,
1,
1,
1,
5,
2,
1998
663.4
660.3
3.1
634.5
871.9
762.6
044.5
333.5
711.0
895.9
217.7
678.2
33.5
271.8
154.9
1999
1,725.6
1,722.4
3.2
1,613.5
849.0
764.5
1,064.0
352.3
711.7
904.8
218.6
686.2
34.5
5,342.4
2,165.6
2000
1,770.3
1,766.9
3.4
1,642.8
862.6
780.3
1,123.2
369.9
753.3
961.6
229.3
732.4
35.8
5,533.7
2,269.3
2001
1,757.0
1,753.6
3.5
1,574.9
861.2
713.7
1,123.2
361.5
761.7
983.3
224.9
758.4
48.5
5,486.9
2,237.3
2002
1,802.2
1,798.8
3.4
1,542.8
842.1
700.7
1,139.8
360.0
779.8
973.9
224.3
749.6
43.1
5,501.8
2,233.5
2003
1,805.4
1,801.0
4.3
1,572.4
844.6
727.7
1,166.6
378.8
787.9
978.1
235.8
742.2
48.7
5,571.1
2,262.2
2004
1,860.2
1,855.5
4.7
1,595.0
863.5
731.5
1,166.8
369.6
797.2
983.1
226.0
757.2
51.4
5,656.6
2,290.6
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.
Energy 3-7
-------
Figure 3-9 summarize C02 emissions from direct fossil fuel
combustion and pro-rated electricity generation emissions
from electricity consumption by end-use sector.
Transportation End-Use Sector
Using this allocation method, the transportation end-use
sector accounted for 1,860.2 Tg C02 in 2004, or approximately
33 percent of total C02 emissions from fossil fuel combustion,
the largest share of any end-use economic sector.7 Between
1990 and 2004, transportation C02 emissions increased by
395.8 Tg C02, representing approximately 40 percent of the
growth in energy-related C02 emissions from all sectors.
Almost all of the energy consumed in the transportation sector
was petroleum-based, including motor gasoline, diesel fuel,
jet fuel, and residual oil.
Table 3-7 provides a detailed breakdown of C02
emissions by fuel category and vehicle type for the
transportation end-use sector. As detailed in the table, overall
transportation C02 emissions increased by 27 percent from
1990 to 2004, representing an average annual increase of
1.7 percent. Between 2003 and 2004 transportation C02
emissions increased by just over 3.0 percent.
Transportation fuel consumption is broadly affected
by travel activity and the amount of energy vehicles used
to move people and goods by various travel modes. In the
short-term, changes transportation energy consumption and
C02 emissions primarily reflect variation in travel activity
that accompanies year-to-year economic fluctuations. Long-
term factors, especially the cost of fuel (see Figure 3-10), can
impact travel patterns and vehicle energy efficiency. Since
1990, there has been a significant increase in vehicle miles
traveled (VMT) by light-duty trucks, freight trucks, and
aircraft. At the same time, the fuel economy of light-duty
trucks and freight trucks has remained roughly constant.
By contrast, commercial aircraft have become noticeably
more fuel efficient.
As shown in Table 3-7, automobiles and light-duty
trucks (consuming both gasoline and diesel) accounted for
approximately 63 percent of transportation C02 emissions
in 2004. From 1990 to 2004, carbon dioxide emissions
from automobiles and light-duty trucks increased roughly
24 percent (227.7 Tg C02). Over this period, VMT by
automobile and light-duty trucks increased by 37 percent,
outweighing a small increase in overall fleet fuel economy
(see Figure 3-11). Much of the small increase in overall fleet
fuel economy resulted from the retirement of older, less fuel
efficient vehicles.
Carbon dioxide emissions from freight trucks8 increased
by 62 percent (140 Tg) from 1990 to 2004, representing the
largest emissions rate increase of any major transportation
mode. Fuel economy for the freight truck fleet was relatively
constant over this period, while truck VMT increased by 53
Figure 3-9
Figure 3-10
2004 End-Use Sector Emissions of C02 from
Fossil Fuel Combustion
2,000-
1,800-
1,600-
1,400-
. 1,200-
O"
d11,000-
LJ
? 800-
600-
400-
200-
0-
From Electricity Consumption
From Direct Fossil Fuel
Combustion
Residential Commercial Industrial Transportation U.S.
Territories
120-
115-
110-
105-
§ 105-
o 90-
O)
£ 85-
| 80-
~ 75-
70-
65-
60 ^
Motor Gasoline Retail Prices (Real)
Cents per VMT
iiiiliiiiiiiiii
7 Note that electricity generation is actually the largest emitter of C02 when electricity is not distributed among end-use sectors.
8 Includes "other trucks" fueled by gasoline, diesel and LPG.
3-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
percent. Aircraft9 C02 emissions increased by just over one grew by approximately 10 percent (11.9 Tg C02) from 1990
percent (2.3 Tg C02) between 1990 and 2004, reflecting
a relatively small increase in emissions from commercial
aircraft emissions and a decrease in domestic military aircraft
emissions. While C02 emissions from commercial aircraft
to 2004, passenger miles traveled increased by 61 percent
over the same period, reflecting improvements in the fuel
efficiency of planes and an increasing percentage of occupied
seats per plane. For further information on all greenhouse
Table 3-7: C02 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg C02 Eq.)a
Fuel/Vehicle Type
Gasoline
Automobiles
Light-Duty Trucks
Other Trucks
Buses
Motorcycles
Boats (Recreational)
Distillate Fuel Oil (Diesel)
Automobiles
Light-Duty Trucks
Other Trucks
Buses
Locomotives
Ships & Boats
Ships (Bunkers)
Jet Fuel
Commercial Aircraft
Military Aircraft
General Aviation Aircraft
Other Aircraft"
Aircraft (Bunkers)
Aviation Gasoline
General Aviation Aircraft
Residual Fuel Oil
Ships & Boatsc
Ships (Bunkers)0
Natural Gas
Automobiles
Light Trucks
Buses
Pipeline
LPG
Light Trucks
Other Trucks
Buses
Electricity
Rail
Total (Including Bunkers)"
Total (Excluding Bunkers)"
1990
964.9
611.2
304.0
38.1
0.3 I
1.7
9.5
270.0
7.7
11.2
186.4
7.8
34.8
10.6
11.4
220.4
117.2
34.8
6.3
15.9
46.2
3.1
3.1
79.3
23.4
55.8
35.9
+
+
+ 1
35.9
1.4l
0.5
0.8
+ 1
3.0
3.0
1,577.9
1,464.4
1998
1,083.7
616.0
420.0
34.2
0.4
1.8
11.3
364.5
5.5
16.8
271.7
9.2
39.9
9.8
11.5
235.6
126.3
1 21.5
7.7
23.4
1 56.7
1 2.4
2.4
52.6
6.2
1 46.4
1 35.1
1 +
+
0.2
1 34.9
1.0
0.4
I 0.6
1 +
3.1
3.1
1,778.0
1,663.4
1999
1,111.1
626.9
436.3
34.4
0.4
1.8
11.3
382.6
4.3
18.4
287.5
10.3
41.4
12.5
8.2
242.9
136.4
20.6
9.2
17.9
58.8
2.7
2.7
51.9
13.7
38.2
35.6
+
+
0.3
35.3
0.8
0.3
0.5
+
3.2
3.2
1,830.8
1,725.6
2000
1,117.1
629.8
438.4
35.4
0.4
1.8
11.3
397.0
3.6
19.6
302.1
10.0
41.2
14.3
6.2
251.2
140.6
21.0
9.2
19.9
60.5
2.5
2.5
64.2
29.6
34.6
35.5
+
+
0.4
35.0
0.7
0.3
0.4
+
3.4
3.4
1,871.6
1,770.3
2001
1,122.1
632.9
441.5
34.4
0.3
1.7
11.3
397.6
3.6
20.3
302.1
9.1
41.4
15.8
5.2
240.4
132.8
22.8
9.0
16.4
59.3
2.4
2.4
54.2
21.0
33.2
33.9
+
+
0.5
33.4
0.8
0.3
0.5
+
3.5
3.5
1,854.9
1,757.0
2002
1,149.1
647.9
453.1
34.9
0.3
1.6
11.2
411.7
3.7
21.4
315.6
8.6
41.8
15.6
5.1
234.4
121.7
20.4
9.3
21.2
61.8
2.3
2.3
52.8
30.2
22.6
37.1
+
+
0.6
36.4
0.8
0.3
0.5
+
3.4
3.4
1,891.7
1,802.2
2003
1,152.9
627.2
482.7
30.0
0.3
1.6
11.1
418.4
4.1
26.6
316.7
9.4
42.8
12.7
6.0
229.1
122.8
20.5
9.3
17.1
59.4
2.1
2.1
44.5
25.9
18.6
37.3
+
+
0.6
36.7
0.8
0.3
0.5
+
4.3
4.3
1,889.4
1,805.4
2004
1,174.3
632.2
497.9
31.2
0.3
1.7
11.1
443.4
4.2
27.8
333.6
9.3
45.1
16.3
7.0
237.4
129.1
21.1
9.6
17.6
59.9
2.1
2.1
54.6
27.0
27.6
37.4
+
+
0.6
36.8
0.8
0.3
0.5
+
4.7
4.7
1,954.7
1,860.2
Note: Totals may not sum due to independent rounding.
a Emissions are no longer allocated to gasoline and diesel consumption from agriculture and construction, and electricity consumption from pipelines.
This is based on recognition that EIA statistics account for these activities in the industrial sector.
b This category represents all other jet fuel consumption, and may include some small commercial aircraft and jet fuel used for heating oil.
c Fluctuations in emission estimates from the combustion of residual fuel oil are currently unexplained, but may be related to data collection problems.
11 Official estimates exclude emissions from the combustion of both aviation and marine international bunker fuels; however, estimates including
international bunker fuel-related emissions are presented for informational purposes.
+ Less than 0.05 Tg C02 Eq.
3 Includes consumption of jet fuel and aviation gasoline. Does not include aircraft bunkers, which are not accounted for in national emission totals.
Energy 3-9
-------
Figure 3-11
Personal Vehicle Fuel Economy
24 -
I22:
& 20-
-------
Despite the growth in industrial output (51 percent) and
the overall U.S. economy (51 percent) from 1990 to 2004,
C02 emissions from the industrial end-use sector increased
by only 4 percent. A number of factors are believed to have
caused this disparity between rapid growth in industrial
output and stagnant growth in industrial emissions are not
entirely clear, including: (1) more rapid growth in output
from less energy-intensive industries relative to traditional
manufacturing industries, (2) improvements in energy
efficiency; and (3) a lowering of the carbon intensity of fossil
fuel consumption as industry shifts from its historical reliance
on coal and coke to heavier usage of natural gas. In 2004,
C02 emissions from fossil fuel combustion and electricity
use within the industrial end-use sectors were 1,595.0 Tg
C02 Eq., or 1.4 percent above 2003 emissions.
Residential and Commercial End-Use Sectors
The residential and commercial end-use sectors
accounted for an average 21 and 17 percent, respectively,
of C02 emissions from fossil fuel combustion. Both end-
use sectors were heavily reliant on electricity for meeting
energy needs, with electricity consumption for lighting,
heating, air conditioning, and operating appliances
contributing to about 68 and 77 percent of emissions
from the residential and commercial end-use sectors,
respectively. The remaining emissions were largely due
to the direct consumption of natural gas and petroleum
products, primarily for heating and cooking needs. Coal
consumption was a minor component of energy use in both
of these end-use sectors. In 2004, C02 emissions from fossil
fuel combustion and electricity use within the residential
and commercial end-use sectors were 1,166.8 Tg C02 Eq.
and 983.1 Tg C02 Eq., respectively.
Emissions from the residential and commercial
sectors have generally been increasing since 1990, and
are often correlated with short-term fluctuations in energy
consumption caused by weather conditions, rather than
prevailing economic conditions (see Table 3-6). In the long-
term, both end-use sectors are also affected by population
growth, regional migration trends, and changes in housing
and building attributes (e.g., size and insulation).
Emissions from natural gas consumption represent
over 70 percent of the direct (not including electricity)
fossil fuel emissions from the residential and commercial
sectors. In 2004, natural gas emissions decreased by 4 and 7
percent, respectively, in each of these sectors, due to warmer
conditions in the United States (see Figure 3-13).
Electricity sales to the residential and commercial end-use
sectors in 2004 increased by 1.6 and 2.4 percent, respectively.
This trend can largely be attributed to the growing economy
(4.2 percent), which led to increased demand for electricity.
Figure 3-13
120 -I
_ 110-
£ 100--
90-
80-1
Heating Degree Days1
Normal
(4,524 Heating Degree Days)
1— CMCO^mCOr-COCJJOl— CM CO
Note: Excludes Alaska and Hawaii
Figure 3-14
Cooling Degree Days1
120 -i
—110 -
E100 --
- 90 -
0 Normal
(1,215 Cooling Degree Days)
1— CM CO
Note: Excludes Alaska and Hawaii
12 Degree days are relative measurements of outdoor air temperature. Heating degree days are deviations of the mean daily temperature below 65° F.
Excludes Alaska and Hawaii. Normals are based on data from 1971 through 2000.
13 Degree days are relative measurements of outdoor air temperature. Cooling degree days are deviations of the mean daily temperature above 65° F.
Excludes Alaska and Hawaii. Normals are based on data from 1971 through 2000.
Energy 3-11
-------
Increased consumption due to these factors was somewhat
offset by decreases in air conditioning-related electricity
consumption due to the cooler summer (see Figure 3-14).
Electricity-related emissions in both the residential and
commercial sectors rose due to increased consumption. Total
emissions from the residential sector increased by less than 0.1
percent in 2004, with emissions from the commercial sector
0.5 percent higher than in 2003.
Electricity Generation
The process of generating electricity is the single largest
source of C02 emissions in the United States, representing 38
percent of total C02 emissions from all sources. Electricity
was consumed primarily in the residential, commercial,
and industrial end-use sectors for lighting, heating, electric
motors, appliances, electronics, and air conditioning (see
Figure 3-15). Electricity generation also accounted for the
largest share of C02 emissions from fossil fuel combustion,
approximately 40 percent in 2004.
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). The
Department of Energy categorizes electric power generation
into three functional categories: the electric power sector,
the commercial sector, and the industrial sector. The electric
power sector consists of electric utilities and independent
power producers whose primary business is the production
Figure 3-15
Electricity Generation Retail Sales by End-Use Sector
1,500 -i
1,200 -
900 -
600 -
300 -1
Residential
Industrial
Commercial
of electricity,14 while the other sectors consist of those
producers that indicate their primary business is other than
the production of electricity.
In 2004, the amount of electricity generated increased
by 1.8 percent, largely due to the growing economy and
expanding industrial production. However, C02 emissions
increased by only 1.3 percent, as a larger share of electricity
was generated by nuclear power and natural gas. While coal
consumption for electricity generation increased by just 0.5
percent in 2004, natural gas consumption increased by 6.6
percent and nuclear power increased by 3.4 percent. As a
result of this shift, carbon intensity from energy consumption
for electricity generation decreased in 2004 (see Table 3-9).
Coal is consumed primarily by the electric power sector in
the United States, which accounted for 94 percent of total
coal consumption for energy purposes in 2004. Electricity
generation from renewables increased slightly (by 1 percent)
in 2004.
Methodology
The methodology used by the United States for
estimating C02 emissions from fossil fuel combustion is
conceptually similar to the approach recommended by the
IPCC for countries that intend to develop detailed, sectoral-
based emission estimates (IPCC/UNEP/OECD/IEA1997). A
detailed description of the U.S. methodology is presented in
Annex 2.1, and is characterized by the following steps:
1. Determine total fuel consumption by fuel type and sector.
Total fossil fuel consumption for each year is estimated
by aggregating consumption data by end-use sector (e.g.,
commercial, industrial, etc.), primary fuel type (e.g.,
coal, petroleum, gas), and secondary fuel category (e.g.,
motor gasoline, distillate fuel oil, etc.). Fuel consumption
data for the United States were obtained directly from
the Energy Information Administration (EIA) of the
U.S. Department of Energy (DOE), primarily from the
Monthly Energy Review and unpublished supplemental
tables on petroleum product detail (EIA 2005b). The
United States does not include territories in its national
energy statistics, so fuel consumption data for territories
were collected separately from Grillot (2005).15
14 Utilities primarily generate power for the U.S. electric grid for sale to retail customers. Nonutilities produce electricity for their own use, to sell to large
consumers, or to sell on the wholesale electricity market (e.g., to utilities for distribution and resale to customers).
15 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 51 Tg C02 Eq. in 2004.
3-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Box 3-2: Carbon Intensity of U.S. Energy Consumption
Fossil fuels are the dominant source of energy in the United States, and C02 is emitted as a product from their combustion. Useful
energy, however, can be generated from many other sources that do not emit C02 in the energy conversion process. In the United States,
useful energy is also produced from renewable (i.e., hydropower, biofuels, geothermal, solar, and wind) and nuclear sources.16
Energy-related C02 emissions can be reduced by not only lowering total energy consumption (e.g., through conservation measures)
but also by lowering the carbon intensity of the energy sources employed (e.g., fuel switching from coal to natural gas). The amount of
carbon emitted from the combustion of fossil fuels is dependent upon the carbon content of the fuel and the fraction of that carbon that is
oxidized.17 Fossil fuels vary in their average carbon content, ranging from about 53 Tg C02 Eq./QBtu for natural gas to upwards of 95 Tg
C02 Eq./QBtu for coal and petroleum coke.18 In general, the carbon content per unit of energy of fossil fuels is the highest for coal products,
followed by petroleum, and then natural gas. Other sources of energy, however, may be directly or indirectly carbon neutral (i.e., 0 Tg C02
Eq./Btu). Energy generated from nuclear and many renewable sources does not result in direct emissions of C02. Biofuels such as wood
and ethanol are also considered to be carbon neutral; although these fuels do emit C02, in the long run the C02 emitted from biomass
consumption does not increase atmospheric C02 concentrations if the biogenic carbon emitted is offset by the growth of new biomass.19
The overall carbon intensity of the U.S. economy is thus dependent upon the quantity and combination of fuels and other energy sources
employed to meet demand.
Table 3-8 provides a time series of the carbon 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 carbon intensity for the residential sector does
not include the energy from or emissions related to the consumption of electricity for lighting or wood for heat. Looking only at this direct
consumption of fossil fuels, the residential sector exhibited the lowest carbon intensity, which is related to the large percentage of its energy
derived from natural gas for heating. The carbon 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 carbon intensities over this period. The carbon intensity of the transportation sector
was closely related to the carbon content of petroleum products (e.g., motor gasoline and jet fuel, both around 70 Tg C02 Eq./EJ), which
were the primary sources of energy. Lastly, the electricity generation sector had the highest carbon intensity due to its heavy reliance on
coal for generating electricity.
Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg C02 Eq./QBtu)
Sector
Residential3
Commercial3
Industrial3
Transportation3
Electricity Generation"
U.S. Territories0
All Sectors'
1990
57.
59.
63.
70.
86.
73.
72.
0
2
3
8
0
3
2
1998
56.3
57.0
62.1
70.6
85.6
56.3
72.3
1999
56.4
56.9
62.2
70.7
85.3
56.4
72.2
2000
56.4
56.9
62.0
70.8
85.1
56.4
72.2
2001
56.6
57.2
62.9
70.8
84.7
56.6
72.3
2002
56,
56,
6?
70,
84,
56,
72,
.2
.7
4
.8
.7
.2
.2
2003
56.4
57.0
62.8
70.7
85.4
56.4
72.4
2004
56.5
57.5
62.7
70.8
85.2
56.5
72.5
a Does not include electricity or renewable energy consumption.
b Does not include electricity produced using nuclear or renewable energy.
c Does not include nuclear or renewable energy consumption.
Note: Excludes non-energy fuel use emissions and consumption.
16 Small quantities of C02, however, are released from some geologic formations tapped for geothermal energy. These emissions are included with fossil
fuel combustion emissions from the electricity generation. Carbon dioxide emissions may also be generated from upstream activities (e.g., manufacture
of the equipment) associated with fossil fuel and renewable energy activities, but are not accounted for here.
17 Generally, more than 97 percent of the carbon in fossil fuel is oxidized to C02 with most carbon combustion technologies used in the United States.
18 One exajoule (EJ) is equal to 1018 joules or 0.9478 QBtu.
19 Net carbon fluxes from changes in biogenic carbon reservoirs in wooded or croplands are accounted for in the estimates for Land Use, Land-Use
Change, and Forestry.
Energy 3-13
-------
Box 3-2: Carbon Intensity of U.S. Energy Consumption (continued)
In contrast to Table 3-8, Table 3-9 presents carbon intensity values that incorporate energy consumed from all sources (i.e., fossil fuels,
renewables, and nuclear). In addition, the emissions related to the generation of electricity have been attributed to both electricity generation
and the end-use sectors in which that electricity was eventually consumed.20 This table, therefore, provides a more complete picture of the
actual carbon intensity of each end-use sector per unit of energy consumed. The transportation end-use sector in Table 3-9 emerges as the
most carbon intensive when all sources of energy are included, due to its almost complete reliance on petroleum products and relatively minor
amount of biomass-based fuels such as ethanol. The "other end-use sectors" (i.e., residential, commercial, and industrial) use significant
quantities of biofuels such as wood, thereby lowering the overall carbon intensity. The carbon intensity of the electricity generation sector
differs greatly from the scenario in Table 3-8, where only the energy consumed from the direct combustion of fossil fuels was included. This
difference is due almost entirely to the inclusion of electricity generation from nuclear and hydropower sources, which do not emit C02.
Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg C02 Eq./QBtu)
Sector
Transportation3
Other End-Use Sectors3- b
Electricity Generation0
All Sectors"
1990
70.5
57.2
58.5
60.8
1998
70.2
57.4
59.4
60.9
1999
70.3
56.8
58.5
60.6
2000
70.4
57.5
59.5
61.0
2001
70.3
58.1
59.7
61.5
2002
70.3
57.3
58.6
61.0
2003
70.1
57.8
59.3
61.3
2004
69.9
57.7
59.1
61.2
a Includes electricity (from fossil fuel, nuclear, and renewable sources) and direct renewable energy consumption.
b Other End-Use Sectors includes the residential, commercial, and industrial sectors.
c Includes electricity generation from nuclear and renewable sources.
11 Includes nuclear and renewable energy consumption.
Note: Excludes non-energy fuel use emissions and consumption.
By comparing the values in Table 3-8 and Table 3-9, a few observations can be made. The use of renewable and nuclear energy sources
has resulted in a significantly lower carbon intensity of the U.S. economy. Over the fourteen-year period of 1990 through 2004, however,
the carbon intensity of U.S. energy consumption has been fairly constant, as the proportion of renewable and nuclear energy technologies
have not changed significantly.
The carbon intensity of total energy consumption in the United States has remained fairly constant. Per capita energy consumption has
fluctuated, but is now roughly equivalent to levels in 1990 (see Figure 3-16). Due to a general shift from a manufacturing-based economy
to a service-based economy, as well as overall increases in efficiency, energy consumption and energy-related C02 emissions per dollar of
gross domestic product (GDP) have both declined since 1990.
Carbon intensity estimates were developed using nuclear and renewable energy data from EIA (2005a) and fossil fuel consumption
data as discussed above and presented in Annex 2.1.
Figure 3-16
U.S. Energy Consumption and Energy-Related C02
Emissions Per Capita and Per Dollar GDP
110
105
o 100
1i 95
| 90
I 85
~ 80
75
Energy
Consumption/
capita
C02/capita
C02/Energy Consumption
C02/$GDP
Energy Consumption/SGDP
20 In other words, the emissions from the generation of electricity are intentionally double counted by attributing them both to electricity generation and
the end-use sector in which electricity consumption occurred.
3-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
For consistency of reporting, the IPCC has recommended
that countries report energy data using the International
Energy Agency (IEA) reporting convention and/or
IEA data. Data in the IEA format are presented "top
down"—that is, energy consumption for fuel types
and categories are estimated from energy production
data (accounting for imports, exports, stock changes,
and losses). The resulting quantities are referred to
as "apparent consumption." The data collected in the
United States by EIA, and used in this inventory, are,
instead, "bottom up" in nature. In other words, they are
collected through surveys at the point of delivery or use
and aggregated to determine national totals.21
It is also important to note that U.S. fossil fuel energy
statistics are generally presented using gross calorific
values (GCV) (i.e., higher heating values). Fuel
consumption activity data presented here have not been
adjusted to correspond to international standard, which
are to report energy statistics in terms of net calorific
values (NCV) (i.e., lower heating values).22
Subtract uses accounted for in the Industrial Processes
chapter. Portions of the fuel consumption data for six
fuel categories—coking coal, industrial other coal,
petroleum coke, natural gas, residual fuel oil, and
other oil—were reallocated to the industrial processes
chapter, as they were consumed during non-energy
related industrial activity. To make these adjustments,
additional data were collected from Gambogi (2005),
EFMA (1995), U.S. Census Bureau (1991 through
1994), U.S. Census Bureau (1998 through2003), USITC
(2005), U.S. Census Bureau (2005), EIA (2005h), EIA
(2001b), USAA (2005), USGS (1998 through 2002),
USGS (1995), USGS (1995 through 2005), USGS
(1991 through 2005), USGS (1991 through 2004),
U.S. International Trade Commission (2004a), U.S.
International Trade Commission (2004b), Onder and
Bagdoyan (1993), and Johnson (2005).23
3. Adjust for biofuels, conversion of fossil fuels, and exports
ofCO2. Fossil fuel consumption estimates are adjusted
downward to exclude (1) fuels with biogenic origins, (2)
fuels created from other fossil fuels, and (3) exports of
C02. Fuels with biogenic origins are assumed to result
in no net C02 emissions, and must be subtracted from
fuel consumption estimates. These fuels include ethanol
added to motor gasoline and biomass gas used as natural
gas. Synthetic natural gas is created from industrial
coal, and is currently included in EIA statistics for
both coal and natural gas. Therefore, synthetic natural
gas is subtracted from energy consumption statistics.24
Since October 2000, the Dakota Gasification Plant has
been exporting C02 to Canada by pipeline. Since this
C02 is not emitted to the atmosphere in the United
States, energy used to produce this C02 is subtracted
from energy consumption statistics. To make these
adjustments, additional data for ethanol and biogas were
collected from EIA (2005b) and data for synthetic natural
gas were collected from EIA (2005e), and data for C02
exports were collected from the Dakota Gasification
Company (2004), Fitzpatrick (2002), Erickson (2003),
EIA (2001a), EIA (2002 through 2003), EIA (2005e),
and Kass (2005).
4. Adjust Sectoral Allocation of Distillate Fuel Oil.
EPA had conducted a separate bottom-up analysis of
transportation fuel consumption based on FHWA Vehicle
Miles Traveled (VMT) that indicated that the amount
of distillate consumption allocated to the transportation
sector in the EIA statistics should be adjusted. Therefore,
for these estimates, the transportation sector's distillate
fuel consumption was adjusted higher to match the
value obtained from the bottom-up analysis based on
VMT. As the total distillate consumption estimate from
EIA is considered to be accurate at the national level,
the distillate consumption totals for the residential,
commercial, and industrial sectors were adjusted
21 See IPCC Reference Approach for estimating C02 emissions from fossil fuel combustion in Annex 4 for a comparison of U.S. estimates using top-down
and bottom-up approaches.
22 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.
23 See sections on Iron and Steel Production, Ammonia Manufacture, Petrochemical Production, Titanium Dioxide Production, Ferroalloy Production,
and Aluminum Production in the Industrial Processes chapter.
24 These adjustments are explained in greater detail in Annex 2.1.
Energy 3-15
-------
downward proportionately. The data sources used in the
bottom-up analysis of transportation fuel consumption
include AAR (2005), Benson (2002 through 2004), DOE
(1993 through 2004), EIA (2005a), EIA (1991 through
2005), EPA (2004b), and FHWA (1996 through 2005).
5. Adjust for fuels consumed for non-energy uses. U.S.
aggregate energy statistics include consumption of fossil
fuels for non-energy purposes. Depending on the end-
use, this can result in storage of some or all of the carbon
contained in the fuel for a period of time. As the emission
pathways of carbon used for non-energy purposes are
vastly different than fuel combustion, these emissions
are estimated separately in the Carbon Emitted and
Stored in Products from Non-Energy Uses of Fossil
Fuels section in this chapter. Therefore, the amount of
fuels used for non-energy purposes was subtracted from
total fuel consumption. Data on non-fuel consumption
was provided by EIA (2005b).
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, determination of carbon
content, and adjustment for the fraction of carbon
not oxidized).25 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 2005) supplied data on military jet fuel use.
Commercial jet fuel use was obtained from BEA (1991
through 2005) and DOT (1991 through 2005); residual
and distillate fuel use for civilian marine bunkers was
obtained from DOC (1991 through 2005). Consumption
of these fuels was subtracted from the corresponding
fuels in the transportation end-use sector. Estimates of
international bunker fuel emissions are discussed further
in the section entitled International Bunker Fuels.
7. Determine the total carbon content of fuels consumed.
Total carbon was estimated by multiplying the amount
of fuel consumed by the amount of carbon in each
fuel. This total carbon estimate defines the maximum
amount of carbon that could potentially be released
to the atmosphere if all of the carbon in each fuel was
converted to C02. The carbon content coefficients
used by the United States were obtained from EIA's
Emissions of Greenhouse Gases in the United States
2004 (EIA 2005c) and EIA's Monthly Energy Review and
unpublished supplemental tables on petroleum product
detail EIA (EIA2005b). They are presented in Annexes
2.1 and 2.2.
8. Adjust for carbon that does not oxidize during
combustion. Because most combustion processes are not
100 percent efficient, some of the carbon contained in
fuels is not emitted to the atmosphere. Rather, it remains
behind as soot and ash. The estimated amount of carbon
not oxidized due to inefficiencies during the combustion
process was assumed to be 1 percent for petroleum26 and
coal and 0.5 percent for natural gas (see Annex 2.1).
Unoxidized or partially oxidized organic (i.e., carbon
containing) combustion products were assumed to have
eventually oxidized to C02 in the atmosphere.27 IPCC
provided fraction oxidized values for petroleum and
natural gas (IPCC/UNEP/OECD/IEA 1997). Bechtel
(1993) provided the fraction oxidation value for coal.
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.28 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 jet fuel, C02 emissions were calculated directly
based on reported consumption of fuel. For highway
25 See International Bunker Fuels section in this chapter for a more detailed discussion.
26 Based on an analysis of carbon mass balances, it is assumed that 100 percent of carbon is oxidized during combustion in light-duty gasoline cars and
trucks.
27 See Indirect C02 from CH4 Oxidation section in this chapter for a more detailed discussion.
28 Electricity generation is not considered a final end-use sector, because energy is consumed primarily to provide electricity to the other sectors.
3-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
vehicles, annual estimates of combined motor gasoline
and diesel fuel consumption by vehicle category were
obtained from FHWA (1996 through 2005); for each
vehicle category, the percent gasoline, diesel, and other
(e.g., CNG, LPG) fuel consumption are estimated using
data from DOE (1993 through 2004). For non-highway
vehicles, activity data were obtained from AAR (2005),
BEA (1991 through 2005), Benson (2002 through 2004),
DOE (1993 through 2004), DESC (2005), DOC (1991
through 2005), DOT (1991 through 2005), EIA (2002a),
EIA (2002b), EIA (2005a), EIA (2005d), EIA (2005g),
EIA (1991 through 2005), EPA (2004), and FAA (2005).
Heat contents and densities were obtained from EIA
(2005a) and USAF (1998).29 The difference between
total U.S. jet fuel consumption (as reported by EIA)
and civilian air carrier consumption for both domestic
and international flights (as reported by DOT and BEA)
plus militaryjet fuel consumption is reported as "other"
under the jet fuel category in Table 3-7, and includes
such fuel uses as blending with heating oils and fuel
used for chartered aircraft flights.
Uncertainty
For estimates of C02 from fossil fuel combustion, the
amount of C02 emitted is directly related to the amount of
fuel consumed, the fraction of the fuel that is oxidized, and
the carbon content of the fuel. Therefore, a careful accounting
of fossil fuel consumption by fuel type, average carbon
contents of fossil fuels consumed, and production of fossil
fuel-based products with long-term carbon storage should
yield an accurate estimate of C02 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 C02 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 C02 emission estimate from energy-
related fossil fuel combustion, the amount of fuels used in
these non-energy production processes were subtracted from
the total fossil fuel consumption for 2004. The amount of
C02 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. Additionally, inefficiencies in the combustion process,
which can result in ash or soot remaining unoxidized for long
periods, were also assumed. These factors all contribute to
the uncertainty in the C02 estimates. Detailed discussions
on the uncertainties associated with Carbon 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 C02 emissions from
the transportation end-use sector to individual vehicle types
and transport modes. In many cases, bottom-up estimates of
fuel consumption by vehicle type do not match aggregate
fuel-type estimates from EIA. Further research is planned to
improve the allocation into detailed transportation end-use
29 For a more detailed description of the data sources used for the analysis of the transportation end use sector see the Mobile Combustion (excluding
and International Bunker Fuels sections of the Energy chapter, Annex 3.2, and Annex 3.7.
Energy 3-17
-------
sector emissions. In particular, residual fuel consumption
data for marine vessels are highly uncertain, as shown by the
large fluctuations in emissions that do not mimic changes in
other variables such as shipping ton miles.
The uncertainty analysis was performed by primary fuel
type for each end-use sector, using the IPCC-recommended
Tier 2 uncertainty estimation methodology, Monte Carlo
Simulation technique, with @RISK software. For this
uncertainty estimation, the inventory estimation model for
C02 from fossil fuel combustion was integrated with the
relevant inventory variables from the inventory estimation
model for International Bunker Fuels, to realistically
characterize the interaction (or endogenous correlation)
between the variables of these two models. About 150 input
variables were modeled for C02 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.30 Triangular distributions were assigned for
the oxidization factors (or combustion efficiencies). The
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Energy-related Fossil Fuel Combustion
by Fuel Type and Sector (Tg C02 Eq. and Percent)
Fuel/Sector
Coal"
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Natural Gas"
Residential
Commercial
Industrial
Transportation
Electricity Generation
U.S. Territories
Petroleum"
Residential
Commercial
Industrial
Transportation
Electric Utilities
U.S. Territories
Total (excluding Geothermal)11
Geothermal
Total (including Geothermal)11 c
2004 Emission
Estimate
(Tg C02 Eq.)
2,027.0
1.0
8.2
117.1
NE
1,897.1
3.6
1,191.2
265.5
162.7
428.4
37.4
295.8
1.3
2,438.0
103.0
55.1
318.0
1,818.1
97.3
46.5
5,656.2
0.4
5,656.6
Uncertainty Range Relative to Emission Estimate3
(Tg
Lower Bound
1,974.8
1.0
7.8
113.3
NE
1,836.0
3.2
1,204.8
258.9
158.7
439.5
36.5
288.3
1.1
2,310.9
98.2
52.8
271.3
1,703.0
93.8
43.3
5,589.1
NE
5,589.5
C02 Eq.)
Upper Bound
2,232.2
1.2
9.5
137.2
NE
2,092.8
4.3
1,274.9
285.1
174.7
483.9
40.1
311.9
1.5
2,588.6
108.7
57.7
377.0
1,944.5
102.3
52.0
5,990.1
NE
5,990.5
("/
Lower Bound
-3%
-5%
-4%
-3%
NA
-3%
-12%
1%
-3%
-2%
3%
-2%
-3%
-12%
-5%
-5%
-4%
-15%
-6%
-4%
-7%
-1%
NE
-1%
'*)
Upper Bound
+10%
+ 16%
+ 16%
+ 17%
NA
+ 10%
+ 20%
+ 7%
+7%
+7%
+ 13%
+7%
+5%
+ 17%
+ 6%
+5%
+5%
+ 19%
+7%
+5%
+ 12%
+ 6%
NE
+ 6%
NA (Not Applicable)
NE (Not Estimated)
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
b The low and high estimates for total emissions were calculated separately through simulations and, hence, the low and high emission estimates for the
sub-source categories do not sum to total emissions.
c Geothermal emissions added for reporting purposes, but an uncertainty analysis was not performed for C02 emissions from geothermal production.
30 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.
3-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
uncertainty ranges were assigned to the input variables
based on the data reported in SAIC/EIA (2001) and on
conversations with various agency-personnel.31
The uncertainty ranges for the activity-related input
variables were typically asymmetric around their inventory
estimates; the uncertainty ranges for the emissions factors
were symmetric. Bias (or systematic uncertainties)
associated with these variables accounted for much of the
uncertainties associated with these variables (SAIC/EIA
2001).32 For purposes of this uncertainty analysis, each
input variable was simulated 10,000 times through Monte
Carlo Sampling.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-10. Fossil fuel combustion C02
emissions in 2004 were estimated to be between 5,589.5 and
5,990.5 Tg C02 Eq. at a 95 percent confidence level (or in 19
out of 20 Monte Carlo Simulations). This indicates a range
of 1 percent below to 6 percent above the 2004 emission
estimate of 5,656.6 Tg C02 Eq.
QA/QC and Verification
A source-specific QA/QC plan for CO2 from fossil fuel
combustion was developed and implemented. This effort
included a Tier 1 analysis, as well as portions of a Tier 2
analysis. The Tier 2 procedures that were implemented
involved checks specifically focusing on the activity data
and methodology used for estimating C02 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 most significant change affecting fuel combustion
estimates this year was to correct an error that resulted
in emissions to be estimated from some fuels that were
either exported or used in industrial processes. A portion
of industrial sector fuels are exported as petrochemical
feedstocks or used in industrial processes, and are subtracted
from the estimated fuel consumed for non-energy use
purposes, reported in Section 3.2 Carbon Emitted from
Non-Energy Uses of Fossil Fuels. However, these fuels
had not been subtracted from fuels consumed for energy
purposes, resulting in an overestimate of emissions from
the industrial sector.
Energy consumption of coking coal and industrial
other coal were adjusted due to revised consumption data
for metallurgical coke used in the production of iron and
steel, and new consumption data for metallurgical coal
used the production of lead and zinc. The amount of coking
coal used to manufacture the coke used in these processes
is estimated based on the amount of coke produced. These
coal consumption data are then subtracted from energy
consumption estimates, as emissions from the production of
iron and steel, lead, and zinc are estimated in the Industrial
Processes chapter.
The oxidation factor for motor gasoline used in light-
duty vehicles has been changed to 1.00 from the IPCC
default factor for petroleum of 0.99. An analysis of carbon
mass balances for light-duty gasoline cars and trucks
was conducted to assess the proper oxidation factor. The
results suggested that the amount of unoxidized carbon is
insignificant compared to the gaseous carbon fraction, and
that 1.00 should be used to represent the oxidized carbon
fraction in future inventories for gasoline fueled light-duty
vehicles.
The Energy Information Administration (EIA 2005b)
updated energy consumption data for all years. These
revisions primarily impacted the emission estimates for 2003.
EIA (2005b) now reports a small amount of consumption of
other liquids in the electricity generation sector. This fuel
type is similar to the composition of jet fuel.
Overall, changes resulted in an average annual decrease
of 42.9 Tg C02 Eq. (0.8 percent) in C02 emissions from fossil
fuel combustion for the period 1990 through 2003.
31 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.
32 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 3-19
-------
Planned Improvements
Several items are being evaluated to improve the
estimates of C02 emissions from fossil fuel combustion and
to reduce uncertainty:
• The carbon oxidation factor for diesel fuel consumed in
highway vehicles may be assessed to determine whether
the IPCC default of 0.99 is appropriate, or whether a
more representative factor can be determined.
• Efforts will be taken to work with EIA and other agencies
to improve the quality of the U.S. territories data.
These improvements are not all-inclusive, but are part
of an ongoing analysis and efforts to continually improve
the C02 from fossil fuel combustion estimates.
3.2. Carbon Emitted from Non-
Energy Uses of Fossil Fuels (IPCC
Source Category 1 A)
In addition to being combusted for energy, fossil fuels
are also consumed for non-energy uses (NED). These fuels
are used in the industrial and transportation end-use sectors
and are quite diverse, including natural gas, liquid petroleum
gases (LPG), asphalt (a viscous liquid mixture of heavy
crude oil distillates), petroleum coke (manufactured from
heavy oil), and coal coke (manufactured from coking coal).
The non-energy fuel uses are equally diverse, and include
application as solvents, lubricants, and waxes, or as raw
materials in the manufacture of plastics, rubber, synthetic
fibers and other materials.
C02 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 62 percent of the total carbon consumed for non-
energy purposes is stored in products, and not released to the
atmosphere; the remaining 38 percent is emitted.
There are several areas in which non-energy uses of
fossil fuels are closely related to other parts of the inventory.
For example, some of the NEU products release C02 at the
end of their commercial life when they are combusted; these
emissions are reported separately within the Energy chapter
in the Municipal Solid Waste Combustion source category. In
addition, there is some overlap between fossil fuels consumed
for non-energy uses and the fossil-derived C02 emissions
accounted for in the Industrial Processes chapter. To avoid
double-counting, the "raw" non-energy fuel consumption
data reported by EIA are modified to account for these
overlaps. There are also net exports of petrochemicals that
are not completely accounted for in the EIA data, and these
affect the mass of carbon in non-energy applications.
As shown in Table 3-11, fossil fuel emissions in 2004
from the non-energy uses of fossil fuels were 153.5 Tg C02
Eq., which constituted approximately 3 percent of overall
fossil fuel emissions, approximately the same proportion as
in 1990. In 2004, the consumption of fuels for non-energy
uses (after the adjustments described above) was 5,684 TBtu,
an increase of 27 percent since 1990 (see Table 3-12). About
68.2 Tg of the C (250.1 Tg C02 Eq.) in these fuels was stored,
while the remaining 41.8 Tg C (153.5 Tg C02 Eq.) was
emitted. The proportion of C emitted as C02 has remained
about constant since 1990, at about 31 to 37 percent of total
non-energy consumption (see Table 3-13).
Methodology
The first step in estimating carbon stored in products was
to determine the aggregate quantity of fossil fuels consumed
for non-energy uses. The carbon content of these feedstock
fuels is equivalent to potential emissions, or the product of
consumption and the fuel-specific carbon content values.
Both the non-energy fuel consumption and carbon content
data were supplied by the EIA (2004) (see Annex 2.1).
Consumption of natural gas, LPG, pentanes plus, naphthas,
other oils, and special naphtha were adjusted to account
for net exports of these products that are not reflected in
the raw data from EIA. Consumption values for industrial
coking coal, petroleum coke, other oils, and natural gas in
Table 3-12 and Table 3-13, have been adjusted to subtract
non-energy uses that are included in the source categories
of the Industrial Processes chapter.33
For the remaining non-energy uses, the amount of C
stored was estimated by multiplying the potential emissions
33 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, and Aluminum Production.
3-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-11: C02 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg C02 Eq.)
Year
Potential Emissions
Carbon Stored
Emissions
1990
312.9
195.7
117.2
1998
390.5
237.7
152.8
1999
415.1
254.6
160.6
2000
385.5
244.8
140.7
2001
364.8
233.8
131.0
2002
371.6
235.1
136.5
2003
361.2
227.7
133.5
2004
403.6
250.0
153.4
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu)
Year
Industry
Industrial Coking Coal
Industrial Other Coal
Natural Gas to Chemical
Plants, Other Uses
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Naphtha (<401°F)
Other Oil (>401°F)
Still Gas
Petroleum Coke
Special Naphtha
Distillate Fuel Oil
Waxes
Miscellaneous Products
Transportation
Lubricants
U.S. Territories
Lubricants
Other Petroleum
(Misc. Prod.)
Total
1990
4,223.4
0.0
8.2
278.0
1,170.2
1,117.7
186.3
77.3
325.3
676.5
21.3
83.6
100.8
7.0
33.3
137.8
176.0
176.0
86.7
0.7
86.0
4,486.1
1998
5,354.4
8.5
10.4
407.9
1,262.6
1,678.9
190.8
197.2
563.6
637.8
0.0
119.8
103.9
11.7
42.4
119.0
180.2
180.2
137.9
1.3
136.6
5,672.5
1999
5,652.1
45.7
11.1
419.4
1,324.4
1,755.1
192.8
252.8
485.3
658.6
16.1
189.0
141.0
11.7
37.4
111.9
182.1
182.1
143.8
1.4
142.4
5,977.9
2000
5,260.5
62.7
12.4
421.5
1,275.7
1,603.3
189.9
228.6
592.3
553.9
12.6
49.4
94.3
11.7
33.1
119.2
179.4
179.4
165.5
16.4
149.1
5,605.3
2001
5,044.9
25.5
11.3
410.6
1,256.9
1,537.1
174.0
199.6
488.9
525.2
35.8
129.4
77.8
11.7
36.3
124.9
164.3
164.3
80.3
+
80.3
5,289.5
2002
5,086.5
46.4
12.0
405.9
1,240.0
1,564.5
171.9
166.0
563.9
469.5
57.8
111.2
99.4
11.7
32.2
134.2
162.4
162.4
138.7
1.5
137.2
5,387.6
2003
4,922.6
72.0
11.9
389.6
1,219.5
1,439.0
159.0
158.4
573.9
515.0
59.0
80.8
75.8
11.7
31.0
126.0
150.1
150.1
146.6
1.6
145.0
5,219.3
2004
5,371.1
214.3
11.9
380.1
1,303.9
1,437.5
161.0
156.5
688.2
561.7
63.5
189.4
47.2
11.7
30.8
113.4
152.1
152.1
156.3
1.7
154.6
5,679.5
+ Does not exceed 0.05 TBtu
Note: To avoid double-counting, coal coke, petroleum coke, natural gas consumption, and other oils are adjusted for industrial process consumption
reported in the Industrial Processes sector. Natural gas, LPG, Pentanes Plus, Naphthas, Special Naphtha, and Other Oils are adjusted to account for
exports of chemical intermediates derived from these fuels. For residual oil (not shown in the table), all non-energy use is assumed to be consumed in
carbon black production, which is also reported in the Industrial Processes chapter.
Note: Totals may not sum due to independent rounding.
by a storage factor. For several fuel types—petrochemical
feedstocks (natural gas for non-fertilizer uses, LPG, pentanes
plus, naphthas, other oils, still gas, special naphtha, and
industrial other coal), asphalt and road oil, lubricants, and
waxes—U.S. data on C stocks and flows were used to develop
C storage factors, calculated as the ratio of (a) the C stored
by the fuel's non-energy products to (b) the total C content
of the fuel consumed. A lifecycle approach was used in the
development of these factors in order to account for losses
in the production process and during use. Because losses
associated with municipal solid waste management are
handled separately in this sector under the Municipal Solid
Waste Combustion source category, the storage factors do not
account for losses at the disposal end of the life cycle. For
industrial coking coal and distillate fuel oil, storage factors
were taken from the Revised IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA1997),
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 carbon in the respective NEU products.
Energy 3-21
-------
Table 3-13: 2004 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions
Sector/Fuel Type
Industry
Industrial Coking Coal
Industrial Other Coal
Natural Gas to Chemical Plants
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Naphtha (<401°F)
Other Oil (>401°F)
Still Gas
Petroleum Coke
Special Naphtha
Distillate Fuel Oil
Waxes
Miscellaneous Products
Transportation
Lubricants
U.S. Territories
Lubricants
Other Petroleum (Misc. Prod.)
Total
Adjusted
Consumption
(TBtu)
5,371.1
214.3
11.9
380.1
1,303.9
1,437.5
161.0
156.5
688.2
561.7
63.5
189.4
47.2
11.7
30.8
113.4
152.1
152.1
156.3
1.7
154.6
5,679.5
Carbon
Content
(TgC)
103.8
6.6
0.3
5.5
26.9
24.2
3.3
2.9
12.5
11.2
1.1
5.3
0.9
0.2
0.6
2.3
3.1
3.1
3.1
0.0
3.1
110.0
Storage
Factor
-
0.10
0.62
0.62
1.00
0.62
0.09
0.62
0.62
0.62
0.62
0.50
0.62
0.50
0.58
0.00
-
0.09
-
0.09
0.10
-
Carbon
Stored
(TgC)
67.5
0.7
0.2
3.4
26.9
15.1
0.3
1.8
7.8
7.0
0.7
2.6
0.6
0.1
0.4
0.0
0.3
0.3
0.3
0.0
0.3
68.1
Carbon
Emissions
(TgC)
36.2
6.0
0.1
2.1
0.0
9.1
3.0
1.1
4.7
4.2
0.4
2.6
0.4
0.1
0.3
2.3
2.8
2.8
2.8
0.0
2.78
41.8
Carbon
Emissions
(Tg C02 Eq.)
132.8
21.9
0.4
7.6
0.0
33.2
10.8
3.9
17.2
15.4
1.5
9.7
1.3
0.4
0.9
8.5
10.2
10.2
10.3
0.1
10.2
153.4
+ Does not exceed 0.05 Tg C or 0.05 Tg C02 Eq.
a To avoid double-counting, coal coke, petroleum coke, natural gas consumption, and other oils are adjusted for industrial process consumption
reported in the Industrial Processes sector. Natural gas, LPG, Pentanes Plus, Naphthas, Special Naphtha, and Other Oils are adjusted to account for
exports of chemical intermediates derived from these fuels. For residual oil (not shown in the table), all non-energy use is assumed to be consumed in
carbon black production, which is also reported in the Industrial Processes chapter.
- Not applicable.
Note: Totals may not sum due to independent rounding.
Lastly, emissions were estimated by subtracting the
carbon stored from the potential emissions (see Table 3-11).
More detail on the methodology for calculating storage
and emissions from each of these sources is provided in
Annex 2.3.
Where storage factors were calculated specifically for
the United States, data were obtained on (1) products such as
asphalt, plastics, synthetic rubber, synthetic fibers, cleansers
(soaps and detergents), pesticides, food additives, antifreeze
and deicers (glycols), and silicones; and (2) industrial
releases including volatile organic compound, solvent, and
non-combustion carbon monoxide emissions, Toxics Release
Inventory (TRI) releases, hazardous waste incineration, and
energy recovery. Data were taken from a variety of industry
sources, government reports, and expert communications.
Sources include EPA's compilations of air emission factors
(EPA 1995, 2001), National Air Quality and Emissions
Trends Report data (EPA 2005 ), Toxics Release Inventory,
1998 (2000a), Biennial Reporting System data (EPA 2004),
pesticide sales and use estimates (EPA 1998,1999,2002) and
hazardous waste data (EPA 2004); the EIA Manufacturer's
Energy Consumption Survey (MECS) (EIA 1994, 1997,
200Ib, 2005); the National Petrochemical & Refiners
Association (NPRA 2001); the National Asphalt Pavement
Association (Connolly 2000); the Emissions Inventory
Improvement Program (EIIP1998,1999); the U.S. Bureau of
the Census (1999,2003,2004); the American Plastics Council
(APC 2000, 2001, 2003, 2005; Eldredge-Roebuck 2000);
the Society of the Plastics Industry (SPI 2000); the Rubber
Manufacturers'Association (RMA 2002; STMC 2003); the
International Institute of Synthetic Rubber Products (IISRP
2000, 2003); the Fiber Economics Bureau (FEE 2001; FEE
2005); the Material Safety Data Sheets (Miller 1999); the
Chemical Manufacturer's Association (CMA 1999); and the
American Chemistry Council (ACC 2004.) Specific data
sources are listed in full detail in Annex 2.3.
3-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-14: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Non-Energy Uses of Fossil Fuels
(Tg C02 Eq. and Percent)
Source
Feedstocks
Asphalt
Lubricants
Waxes
Other
Total
Gas
C02
C02
C02
C02
C02
C02
2004 Emission
Estimate
(Tg C02 Eq.)
80.6
0.0
21.2
0.9
50.7
153.4
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound
65.3
NA
17.6
0.7
22.3
122.7
Upper Bound
96.7
NA
24.4
1.5
56.8
165.7
Lower Bound
-19%
NA
-17%
-24%
-56%
-20%
Upper Bound
+20%
NA
+ 15%
+56%
+ 12%
+ 8%
aRange of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
NA (Not Applicable)
Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels
(Percent)
2004 Storage Factor
Source
Gas
Uncertainty Range Relative to Inventory Factor3
(%) (%, Relative)
Feedstocks
Asphalt
Lubricants
Waxes
Other
C02
C02
C02
C02
C02
62%
100%
9%
58%
28%
Lower Bound
60%
99%
4%
44%
21%
Upper Bound
64%
100%
18%
69%
68%
Lower Bound
-3%
-1%
-58%
-24%
-25%
Upper Bound
+4%
+0%
+91%
+ 19%
+ 141%
aRange of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
Uncertainty
An uncertainty analysis was conducted to quantify the
uncertainty surrounding the estimates of emissions and storage
factors from non-energy uses. This analysis, performed
using @RISK software and the IPCC-recommended Tier 2
methodology (Monte Carlo Simulation technique), provides
for the specification of probability density functions for key
variables within a computational structure that mirrors the
calculation of the inventory estimate. The results presented
below provide the 95 percent confidence interval, the range
of values within which emissions are likely to fall, for this
source category.
As noted above, the non-energy use analysis is based
on U.S.-specific storage factors for (1) feedstock materials
(natural gas, LPG, pentanes plus, naphthas, other oils, still
gas, special naphthas, and other industrial coal), (2) asphalt,
(3) lubricants, and (4) waxes. For the remaining fuel types
(the "other" category), the storage factors were taken directly
from the IPCC Guidelines for National Greenhouse Gas
Inventories, where available, and otherwise assumptions
were made based on the potential fate of carbon in the
respective NEU products. To characterize uncertainty, five
separate analyses were conducted, corresponding to each of
the five categories. In all cases, statistical analyses or expert
judgments of uncertainty were not available directly from
the information sources for all the activity variables; thus,
uncertainty estimates were determined using assumptions
based on source category knowledge.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-14 (emissions) and Table 3-15
(storage factors). Carbon emitted from non-energy uses of
fossil fuels in 2004 was estimated to be between 112.8 and
153.7 Tg C02 Eq. at a 95 percent confidence level (or in 19
out of 20 Monte Carlo Simulations). This indicates a range
of 20 percent below to 8 percent above the 2004 emission
estimate of 141.7 Tg C02 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.
Energy 3-23
-------
In Table 3-15, feedstocks and asphalt contribute least
to overall storage factor uncertainty on a percentage basis.
Although the feedstocks category—the largest use category
in terms of total carbon flows—appears to have tight
confidence limits, this is to some extent an artifact of the
way the uncertainty analysis was structured. As discussed
in Annex 2.3, the storage factor for feedstocks is based on
an analysis of six fates that result in long-term storage (e.g.,
plastics production), and eleven that result in emissions (e.g.,
volatile organic compound emissions). Rather than modeling
the total uncertainty around all of these fate processes, the
current analysis addresses only the storage fates, and assumes
that all C that is not stored is emitted. As the production
statistics that drive the storage values are relatively well-
characterized, this approach yields a result that is probably
biased toward understating uncertainty.
As is the case with the other uncertainty analyses
discussed throughout this document, the uncertainty
results above address only those factors that can be readily
quantified. More details on the uncertainty analysis are
provided in Annex 2.3.
QA/QC and Verification
A source-specific QA/QC plan for non-energy uses of
fossil fuels was developed and implemented. This effort
included a Tier 1 analysis, as well as portions of a Tier
2 analysis for non-energy uses involving petrochemical
feedstocks. The Tier 2 procedures that were implemented
involved checks specifically focusing on the activity data
and methodology for estimating the fate of C (in terms
of storage and emissions) across the various end-uses of
fossil carbon. Emission and storage totals for the different
subcategories were compared, and trends across the time
series were carefully analyzed to determine whether any
corrective actions were needed. Corrective actions were
taken to rectify minor errors and to improve the transparency
of the calculations, facilitating future QA/QC.
Recalculations Discussion
This year's methodology reflects several refinements
and improvements. The methodology for calculating
emissions and storage for feedstocks has been revised in
several ways. First, some disparities in data for production
and consumption were reconciled. Production data relates
only to production within the country; consumption data
incorporates information on imports and exports as well
as production. Because many commodities are emissive in
their use, but not necessarily their production, consumption
data is appropriately used in calculations for emissive fates.
For purposes of developing an overall mass balance on U.S.
non-energy uses of carbon, for those materials that are non-
emissive (e.g., plastics), production data is most applicable.
And for purposes of adjusting the mass balance to incorporate
carbon flows associated with imports and exports, it was
necessary to carefully review whether the mass balance
already incorporated cross-boundary flows (through the use
of consumption data) or not, and to adjust the import/export
balance accordingly. This year's effort included a more
thorough review of the system boundaries on the mass
balance, addressing the use of production and consumption
data sets and making corresponding adjustments to the import
/ export calculations.
In an attempt to account for make the mass balance
for petrochemical feedstocks more comprehensive,
three additional NEU fates were incorporated into the
calculations: antifreeze and deicers, food additives, and
silicone rubber. Ethylene, diethylene, and propylene glycol
are used in antifreeze and aircraft deicing solutions and
generally have emissive fates; their consumption was tallied
and added to the emissive side of the mass balance ledger.
Many food additives such as acetic acid, maleic anhydride,
adipic acid, cresylic acid, triethylene glycol, propylene
glycol, dipropylene glycol, glycerin, propionic acid, and
benzole acid, are synthetic, i.e., derived from fossil sources.
These are generally metabolized to C02, and thus were
also counted as emissive uses. On the non-emissive side,
silicone rubber is now reflected in the calculations. The
results for petrochemicals reflect the additions of these
new categories in the attempt to "close" the mass balance
for fossil carbon. Compared to other fate categories, the
mass of carbon in these three newly added components
is small, comprising an average of 1.1 percent of annual
carbon flows since 1990.
In another change, one of the emissive fates—refinery
wastewaters—was dropped from the mass balance. This
change was precipitated by better information on the
boundaries for the EIA NEU data set used as the basis for
the analysis. Although a small amount of carbon is emitted
3-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
through refinery wastewater treatment, it is unlikely that this
carbon ever enters the NEU system.
Finally, there have been several updates to the data used
to calculate storage factors, not only by adding information
for 2004 (where available) but also for updating data sets
for earlier years. For example, the results reflect new data
for energy recovery (through 2002), cleansers, and imports
and exports. Overall, changes resulted in an average annual
increase in C02 emissions from non-energy use of fuels of
15.2 Tg C02 Eq. (13 percent) for the period 1990 through
2003.
Planned Improvements
There are several improvements planned for the
future:
• Collecting additional information on energy recovery
from Manufacturing Energy Consumption Surveys. An
effort is planned to carefully examine the "microdata"
from these surveys to determine the nature and quantity
of materials initially identified as being destined for
"non-energy use" that are actually combusted for energy
recovery.
• 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 carbon. Additional
"fates" may be researched, including the fossil carbon
load in organic chemical wastewaters, plasticizers,
adhesives, films, paints, and coatings. There is also a
need to further clarify the treatment of fuel additives
and backflows (especially methyl tert-butyl ether,
MTBE).
Finally, although U.S.-specific storage factors have been
developed for feedstocks, asphalt, lubricants, and waxes,
default values from IPCC are still used for two of the non-
energy fuel types (industrial coking coal and distillate oil),
and broad assumptions are being used for the remaining
fuels (petroleum coke, miscellaneous products, and other
petroleum). Over the long term, there are plans to improve
these storage factors by conducting analyses of C fate similar
to those described in Annex 2.3.
3.3. Stationary Combustion
(excluding C02) (IPCC Source
Category 1 A)
Stationary combustion encompasses all fuel combustion
activities from fixed sources (versus mobile combustion).
Other than C02, which was addressed in the previous
section, gases from stationary combustion include the
greenhouse gases CH4 and N20 and the indirect greenhouse
gases NOX, CO, and NMVOCs.34 Emissions of these gases
from stationary combustion sources depend upon fuel
characteristics, size and vintage, along with combustion
technology, pollution control equipment, and ambient
environmental conditions. Emissions also vary with
operation and maintenance practices.
N20 and NOX emissions from stationary combustion are
closely related to air-fuel mixes and combustion temperatures,
as well as the characteristics of any pollution control equipment
that is employed. Carbon monoxide emissions from stationary
combustion are generally a function of the efficiency of
combustion; they are highest when less oxygen is present in
the air-fuel mixture than is necessary for complete combustion.
These conditions are most likely to occur during start-up,
shutdown, and during fuel switching (e.g., the switching of
coal grades at a coal-burning electric utility plant). CH4 and
NMVOC emissions from stationary combustion are primarily
a function of the CH4 and NMVOC content of the fuel and
combustion efficiency.
Emissions of CH4 decreased 18 percent overall to
6.4 Tg C02 Eq. (307 Gg) in 2004. This decrease in CH4
emissions was primarily due to lower wood consumption
in the residential sector. Conversely, N20 emissions rose 11
percent since 1990 to 13.7 Tg C02 Eq. (44 Gg) in 2004. The
largest source of N20 emissions was coal combustion by
electricity generators, which alone accounted for 64 percent
of total N20 emissions from stationary combustion in 2004.
Overall, however, stationary combustion is a small source
of CH4 and N20 in the United States.
In contrast, stationary combustion is a significant
source of NOX emissions, though a smaller source of
CO and NMVOCs. In 2004, emissions of NOX from
stationary combustion represented 39 percent of national
34 Sulfur dioxide (SO^ emissions from stationary combustion are addressed in Annex 6.3.
Energy 3-25
-------
Table 3-16: CH4 Emissions from Stationary Combustion (Tg C02 Eq.)
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural gas
Wood
Industrial
Coal
Fuel Oil
Natural gas
Wood
Commercial
Coal
Fuel Oil
Natural gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
1990
0,
0,
0,
0,
0,
2
0,
0,
0,
0,
0,
0,
0,
0,
4,
0,
0,
0,
3,
7,
.6
.3
.1
.1
.1
.1
.3
.1
.8
.9
.7
•f
.2
.3
.2
.4
.2
.3
.5
.5
+
•f
•f
•f
•f
.9
1998
0,
0,
0,
0,
0,
2
0,
0,
0,
1
0,
0,
0,
0,
3,
0,
0,
0,
2,
6,
.7
.4
.1
.1
.1
.3
.3
.1
.9
.0
.8
•f
.1
.3
.3
.1
.1
.3
.5
.3
+
•f
•f
•f
•f
.8
1999
0,
0,
0,
0,
0,
2
0,
0,
0,
1
0,
0,
0,
0,
3,
0,
0,
0,
2,
7,
.7
.4
.1
.1
.1
.2
.3
.1
.9
.0
.8
•f
.1
.3
.3
.3
.1
.3
.5
.5
+
•f
•f
•f
•f
.0
2000
0.7
0.4
0.1
0.1
0.1
2.2
0.3
0.1
0.9
1.0
0.8
+
0.1
0.3
0.3
3.5
0.1
0.3
0.5
2.6
0.1
+
+
+
+
7.3
2001
0.7
0.4
0.1
0.1
0.1
2.1
0.3
0.1
0.8
0.9
0.7
+
0.2
0.3
0.2
3.1
0.1
0.3
0.5
2.2
0.1
+
0.1
+
+
6.6
2002
0.7
0.4
+
0.1
0.1
2.0
0.3
0.1
0.8
0.8
0.7
+
0.1
0.3
0.2
2.7
0.1
0.3
0.5
1.9
0.1
+
0.1
+
+
6.2
2003
0.7
0.4
0.1
0.1
0.1
2.0
0.3
0.1
0.8
0.8
0.7
+
0.2
0.3
0.2
3.0
0.1
0.3
0.5
2.1
0.1
+
0.1
+
+
6.5
2004
0.7
0.4
0.1
0.1
0.1
2.1
0.3
0.1
0.8
0.9
0.7
+
0.2
0.3
0.2
2.9
0.1
0.3
0.5
2.0
0.1
+
0.1
+
+
6.4
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 3-17: N20 Emissions from Stationary Combustion (Tg C02 Eq.)
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
1990
7.6
7.1
0.2
0.1
0.2
3.2
0.7
0.5
0.2
1.7
0.4
0.1
0.2
0.1
+
1.1
+
0.3
0.1
0.7
0.1
+
0.1
+
+
12.3
1998
8.9
8.4
0.2
0.1
0.2
3.2
0.6
0.5
0.3
1.9
0.3
+
0.1
0.1
0.1
0.8
+
0.2
0.1
0.5
0.1
+
0.1
+
+
13.4
1999
8.9
8.4
0.2
0.1
0.2
3.2
0.6
0.5
0.3
1.9
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.1
0.5
0.1
+
0.1
+
+
13.4
2000
9.3
8.8
0.2
0.2
0.2
3.3
0.6
0.5
0.3
1.9
0.3
+
0.1
0.1
0.1
0.9
+
0.3
0.2
0.5
0.1
+
0.1
+
+
13.9
2001
9.1
8.6
0.2
0.2
0.1
3.1
0.6
0.6
0.2
1.7
0.3
+
0.1
0.1
+
0.9
+
0.3
0.1
0.4
0.1
+
0.1
+
+
13.5
2002
9.1
8.6
0.1
0.2
0.2
2.9
0.5
0.5
0.2
1.6
0.3
+
0.1
0.1
+
0.8
+
0.3
0.1
0.4
0.1
+
0.1
+
+
13.2
2003
9.3
8.8
0.2
0.2
0.2
2.9
0.6
0.5
0.2
1.6
0.3
+
0.1
0.1
+
0.9
+
0.3
0.2
0.4
0.1
+
0.1
+
+
13.6
2004
9.4
8.8
0.2
0.2
0.2
3.0
0.6
0.5
0.2
1.7
0.3
+
0.1
0.1
+
0.8
+
0.3
0.1
0.4
0.1
+
0.1
+
+
13.7
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
3-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-18: CH4 Emissions from Stationary Combustion (Gg)
Sector/Fuel Type
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
1990
27
16
4
3
4
101
16
6
37
41
35
1
10
13
11
210
9
14
21
166
2
+
2
+
+
374
1998
31
19
4
4
4
107
14
5
43
46
36
1
6
15
14
149
4
12
22
110
2
+
2
+
+
325
1999
31
19
3
5
4
106
14
5
41
46
37
1
6
15
15
159
4
14
23
118
2
+
2
+
+
335
2000
32
20
3
5
4
107
14
5
42
47
38
1
7
15
15
165
3
15
24
123
2
+
2
+
+
346
2001
32
20
4
5
4
99
14
6
38
41
34
1
7
15
12
147
3
15
23
105
3
+
3
+
+
316
2002
32
20
2
5
4
97
13
5
39
40
34
1
6
15
11
130
3
14
24
89
3
+
3
+
+
295
2003
33
20
3
5
5
95
13
6
37
39
35
1
7
16
11
145
3
15
25
102
3
+
3
+
+
311
2004
33
20
3
5
5
98
13
6
39
41
35
1
8
15
12
137
3
15
24
95
3
+
3
+
+
307
+ Does not exceed 0.5 Gg
Note: Totals may not sum due to independent rounding.
Table 3-19: N20 Emissions from Stationary Combustion (Gg)
Sector/Fuel Type
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
1990
24
23
1
+
+
10
2
2
1
5
1
+
1
+
+
4
+
1
+
2
+
+
+
+
+
40
1998
29
27
1
+
1
10
2
1
1
6
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
43
1999
29
27
1
+
1
10
2
1
1
6
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
43
2000
30
28
1
1
1
11
2
2
1
6
1
+
+
+
+
3
+
1
+
2
+
+
+
+
+
45
2001
29
28
1
1
+
10
2
2
1
5
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
44
2002
29
28
+
1
1
9
2
2
1
5
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
43
2003
30
28
1
+
1
9
2
2
1
5
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
44
2004
30
28
1
1
1
10
2
2
1
6
1
+
+
+
+
3
+
1
+
1
+
+
+
+
+
44
+ Does not exceed 0.5 Gg
Note: Totals may not sum due to independent rounding.
Energy 3-27
-------
Table 3-20: NOX, CO, and NMVOC Emissions from
Stationary Combustion in 2004 (Gg)
Sector/Fuel Type
Electric Generation
Coal
Fuel Oil
Natural gas
Wood
Other Fuels3
Internal Combustion
Industrial
Coal
Fuel Oil
Natural gas
Wood
Other Fuels3
Internal Combustion
Commercial/Institutional
Coal
Fuel Oil
Natural gas
Wood
Other Fuels3
Residential
Coal"
Fuel Oil"
Natural Gas"
Wood
Other Fuels
Total
N08
3,393
2,886
113
252
NA
28
114
2,610
541
160
955
NA
121
833
243
19
49
154
NA
21
416
NA
NA
NA
20
396
6,662
CO
451
226
28
95
NA
33
69
1,303
143
52
419
NA
368
320
124
11
14
68
NA
31
2,142
NA
NA
NA
1,961
181
4,020
NMVOC
45
21
4
10
NA
1
9
155
10
8
53
NA
29
55
16
1
3
12
NA
9
697
NA
NA
NA
675
23
922
NA (Not Available)
a Includes LPG, waste oil, coke oven gas, and coke (EPA 2003, EPA
2005).
b Residential coal, fuel oil, and natural gas emissions are included in
"Other Fuels" (EPA 2003, EPA 2005).
Note: Totals may not sum due to independent rounding. See Annex
3.1 for emissions in 1990 through 2004.
NOX emissions, while CO and NMVOC emissions from
stationary combustion contributed approximately 5 and 7
percent, respectively, to the national totals. From 1990 to
2004, emissions of NOX and CO from stationary combustion
decreased by 33 and 20 percent, respectively, and emissions
of NMVOCs increased by 1 percent.
The decrease in NOX emissions from 1990 to 2004 are
mainly due to decreased emissions from electric power. The
decrease in CO and increase in NMVOC emissions over this
time period can largely be attributed to apparent changes in
residential wood use, which is the most significant source
of these pollutants from stationary combustion. Table 3-16
through Table 3-19 provide CH4 and N20 emission estimates
from stationary combustion by sector and fuel type. Estimates
of NOX, CO, and NMVOC emissions in 2004 are given in
Table 3-20.35
Methodology
CH4 and N20 emissions were estimated by multiplying
fossil fuel and wood consumption data by emission factors
(by sector and fuel type). National coal, natural gas, fuel
oil, and wood consumption data were grouped by sector:
industrial, commercial, residential, electric power, and U.S.
territories. For the CH4 and N20 estimates, fuel consumption
data for the United States were obtained from EIA's Monthly
Energy Review and unpublished supplemental tables on
petroleum product detail (EIA 2005). Because the United
States does not include territories in its national energy
statistics, fuel consumption data for territories were provided
separately by Grillot (2005).36 Fuel consumption for the
industrial sector was adjusted to subtract out construction and
agricultural use, which is reported under mobile sources.37
Construction and agricultural fuel use was obtained from EPA
(2004). Estimates for wood biomass consumption for fuel
combustion do not include wood wastes, liquors, municipal
solid waste, tires, etc. that are reported as biomass by EIA.
Emission factors for the four end-use sectors were
provided by the Revised 1996IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA
1997). U.S. territories' emission factors were estimated using
the U.S. emission factors for the primary sector in which
each fuel was combusted.
Emission estimates for NOX, CO, and NMVOCs in
this section were obtained from preliminary data (EPA
2005) 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. The major categories included in this section
35 See Annex 3.1 for a complete time series of indirect greenhouse gas emission estimates for 1990 through 2004.
36 U.S. territories data also include combustion from mobile activities because data to allocate territories' energy use were unavailable. For this reason,
CH4 and N20 emissions from combustion by U.S. territories are only included in the stationary combustion totals.
37 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.
3-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
are those reported in EPA (2003) and EPA (2005): coal,
fuel oil, natural gas, wood, other fuels (including LPG,
coke, coke oven gas, and others), and stationary internal
combustion. The EPA estimates emissions of NOX, CO,
and NMVOCs by sector and fuel source using a "bottom-
up" estimating procedure. In other words, emissions were
calculated either for individual sources (e.g., industrial
boilers) or for multiple sources combined, using basic
activity data as indicators of emissions. Depending on the
source category, these basic activity data may include fuel
consumption, fuel deliveries, tons of refuse burned, raw
material processed, etc.
The overall emission control efficiency of a source
category was derived from published reports, the 1985
National Acid Precipitation and Assessment Program
(NAPAP) emissions inventory, and other EPA databases.
The U.S. approach for estimating emissions of NOX, CO,
and NMVOCs from stationary combustion, as described
above, is consistent with the methodology recommended by
the IPCC (IPCC/UNEP/OECD/IEA 1997).
More detailed information on the methodology for
calculating emissions from stationary combustion, including
emission factors and activity data, is provided in Annex 3.1.
Uncertainty
CH4 emission estimates from stationary sources exhibit
high uncertainty, primarily due to difficulties in calculating
emissions from wood combustion (i.e., fireplaces and wood
stoves). The estimates of CH4 and N20 emissions presented
are based on broad indicators of emissions (i.e., fuel use
multiplied by an aggregate emission factor for different
sectors), rather than specific emission processes (i.e., by
combustion technology and type of emission control).
An uncertainty analysis was performed by primary fuel
type for each end-use sector, using the IPCC-recommended
Tier 2 uncertainty estimation methodology, Monte Carlo
Simulation technique, with @RISK software.
The uncertainty estimation model for this source
category was developed by integrating the CH4 and N20
stationary source inventory estimation models with the
model for C02 from fossil fuel combustion to realistically
characterize the interaction (or endogenous correlation)
between the variables of these three models. A total of 115
input variables were simulated for the uncertainty analysis
of this source category (85 from the C02 emissions from
fossil fuel combustion inventory estimation model and 30
from the stationary source inventory models).
In developing the uncertainty estimation model, uniform
distribution was assumed for all activity-related input
variables and N20 emission factors, based on the SAIC/EIA
(2001) report.38 For these variables, the uncertainty ranges
were assigned to the input variables based on the data reported
in SAIC/EIA (2001).39 However, the CH4 emission factors
differ from those used by EIA. Since these factors were
Table 3-21: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Energy-Related Stationary
Combustion, Including Biomass (Tg C02 Eq. and Percent)
Source Gas
Stationary Combustion CH4
Stationary Combustion N20
2004 Emission
Estimate
(Tg C02 Eq.)
6.4
13.7
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound
4.7
10.4
Upper Bound
12.5
39.4
Lower Bound
-26%
-24%
Upper Bound
+ 94%
+ 188%
! Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
38 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.
39 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.
Energy 3-29
-------
obtained from IPCC/UNEP/OECD/IEA (1997), uncertainty
ranges were assigned based on IPCC default uncertainty
estimates (IPCC Good Practice Guidance, 2000).
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-21. Stationary combustion CH4
emissions in 2004 (includingbiomass) were estimated to be
between 4.7 and 12.5 Tg C02 Eq. at a 95 percent confidence
level (or in 19 out of 20 Monte Carlo Simulations). This
indicates a range of 26 percent below to 94 percent above
the 2004 emission estimate of 6.4 Tg C02 Eq.40 Stationary
combustion N20 emissions in 2004 (including biomass)
were estimated to be between 10.4 and 39.4 Tg C02 Eq.
at a 95 percent confidence level (or in 19 out of 20 Monte
Carlo Simulations). This indicates a range of 24 percent
below to 188 percent above the 2004 emissions estimate of
13.7 Tg C02 Eq.
The uncertainties associated with the emission estimates of
CH4 and N20 are greater than those associated with estimates
of C02 from fossil fuel combustion, which mainly rely on the
carbon content of the fuel combusted. Uncertainties in both
CH4 and N20 estimates are due to the fact that emissions are
estimated based on emission factors representing only a limited
subset of combustion conditions. For the indirect greenhouse
gases, uncertainties are partly due to assumptions concerning
combustion technology types, age of equipment, emission
factors used, and activity data projections.
QA/QC and Verification
A source-specific QA/QC plan for stationary combustion
was developed and implemented. This effort included a
Tier 1 analysis, as well as portions of a Tier 2 analysis. The
Tier 2 procedures that were implemented involved checks
specifically focusing on the activity data and emission factor
sources and methodology used for estimating CH4, N20, and
the indirect greenhouse gases from stationary combustion in
the United States. Emission totals for the different sectors and
fuels were compared and trends were investigated.
Recalculations Discussion
Historical CH4 and N20 emissions from stationary
sources (excluding CO^ were revised due to several changes.
Slight changes to emission estimates for sectors are due to
revised data from EIA (2005). This revision is explained in
greater detail in the section on C02 Emissions from Fossil
Fuel Combustion within this sector. The combination of the
methodological and historical data changes resulted in an
average annual decrease of 0.1 Tg C02 Eq. (0.8 percent) in
CH4 emissions from stationary combustion and an average
annual decrease of 0.1 Tg C02 Eq. (0.4 percent) in N20
emissions from stationary combustion for the period 1990
through 2003.
Planned Improvements
Several items are being evaluated to improve the
CH4 and N20 emission estimates from stationary source
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. Currently, the exclusion of biomass
increases the uncertainty, although it was expected to reduce
the uncertainty. These improvements are not all-inclusive,
but are part of an ongoing analysis and efforts to continually
improve these stationary estimates.
3.4. Mobile Combustion (excluding
C02) (IPCC Source Category 1A)
Mobile combustion emits greenhouse gases other than
C02, including CH4, N20, and the indirect greenhouse gases
NOX, CO, and NMVOCs. As with stationary combustion, N20
and NOX emissions are closely related to fuel characteristics,
air-fuel mixes, combustion temperatures, as well as usage
of pollution control equipment. N20, 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
40 The low emission estimates reported in this section have been rounded down to the nearest integer values and the high emission estimates have been
rounded up to the nearest integer values.
3-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-22: CH4 Emissions from Mobile Combustion (Tg C02 Eq.)
Fuel Type/Vehicle Typea
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft
Other"
Total
1990
4.2
2.6
1.4
0.2
+
+
+
+
+
+
0.5
0.1
0.1
0.2
0.1
+
+
4.7
1998
3.3
1.8
1.3
0.1
+
+
+
+
+
0.1
0.5
+
0.1
0.1
0.1
0.1
+
3.8
1999
3.0
1.7
1.2
0.1
+
+
+
+
+
0.1
0.5
0.1
0.1
0.2
0.1
0.1
+
3.6
2000
2.9
1.6
1.1
0.1
+
+
+
+
+
0.1
0.5
0.1
0.1
0.2
0.1
0.1
+
3.5
2001
2.7
1.5
1.0
0.1
+
+
+
+
+
0.1
0.5
0.1
0.1
0.1
0.1
0.1
+
3.3
2002
2.5
1.4
1.0
0.1
+
+
+
+
+
0.1
0.5
0.1
0.1
0.1
0.1
0.1
0.1
3.2
2003
2.3
1.3
0.9
0.1
+
+
+
+
+
0.1
0.5
0.1
0.1
0.1
0.1
0.1
0.1
3.0
2004
2.2
1.3
0.9
0.1
+
+
+
+
+
0.1
0.6
0.1
0.1
0.1
0.1
0.1
0.1
2.9
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
aSee Annex 3.2 for definitions of highway vehicle types.
b "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport
equipment, commercial equipment, and industrial equipment.
Table 3-23: N20 Emissions from Mobile Combustion (Tg C02 Eq.)
Fuel Type/Vehicle Type
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft
Other*
Total
1990
40.1
25.4
14.1
0.6
+
0.2
+
+
0.2
+
3.1
0.4
0.3
1.7
0.2
0.3
0.2
43.5
1998
51.2
26.6
23.6
0.9
+
0.3
+
+
0.3
0.1
3.3
0.2
0.3
1.8
0.3
0.4
0.3
54.8
1999
50.3
25.9
23.5
0.9
+
0.3
+
+
0.3
0.1
3.4
0.3
0.3
1.8
0.3
0.4
0.3
54.1
2000
49.1
25.1
23.1
0.9
+
0.3
+
+
0.3
0.1
3.6
0.4
0.3
1.9
0.3
0.4
0.3
53.1
2001
46.0
23.9
21.2
0.9
+
0.3
+
+
0.3
0.1
3.6
0.4
0.3
1.8
0.3
0.4
0.3
50.0
2002
43.5
22.9
19.7
0.9
+
0.3
+
+
0.3
0.1
3.6
0.5
0.3
1.7
0.3
0.4
0.3
47.5
2003
40.8
21.8
18.1
0.9
+
0.3
+
+
0.3
0.1
3.5
0.4
0.3
1.7
0.3
0.5
0.3
44.8
2004
38.6
21.0
16.7
0.9
+
0.3
+
+
0.3
0.1
3.7
0.4
0.4
1.8
0.4
0.5
0.4
42.8
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
*"0ther" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport
equipment, commercial equipment, and industrial equipment.
Energy 3-31
-------
Table 3-24: CH4 Emissions from Mobile Combustion (Gg)
Fuel Type/Vehicle Type
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft
Other*
Total
1990
201
125
65
10
1
1
+
+
1
1
22
3
3
7
4
2
2
224
1998
155
87
60
7
1
1
+
+
1
3
22
2
3
7
5
3
2
181
1999
145
82
56
6
1
1
+
+
1
4
24
3
3
7
5
3
2
173
2000
137
77
54
5
1
1
+
+
1
4
25
4
3
7
5
3
2
167
2001
127
72
50
5
1
1
+
+
1
5
25
4
3
7
6
3
2
159
2002
120
68
47
5
1
1
+
+
1
5
26
4
3
7
6
3
2
152
2003
112
63
44
4
1
1
+
+
1
6
25
4
3
6
6
3
2
144
2004
106
60
41
4
1
1
+
+
1
6
27
4
4
7
6
3
3
140
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
* "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport
equipment, commercial equipment, and industrial equipment.
Table 3-25: N20 Emissions from Mobile Combustion (Gg)
Fuel Type/Vehicle Type
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft
Other*
Total
1990
129
82
45
2
+
1
+
+
1
+
10
1
1
6
1
1
1
140
1998
165
86
76
3
+
1
+
+
1
+
11
1
1
6
1
1
1
177
1999
162
83
76
3
+
1
+
+
1
+
11
1
1
6
1
1
1
174
2000
158
81
74
3
+
1
+
+
1
+
12
1
1
6
1
1
1
171
2001
148
77
68
3
+
1
+
+
1
+
12
1
1
6
1
1
1
161
2002
140
74
63
3
+
1
+
+
1
+
12
1
1
6
1
1
1
153
2003
132
70
58
3
+
1
+
+
1
+
11
1
1
5
1
1
1
144
2004
125
68
54
3
+
1
+
+
1
+
12
1
1
6
1
2
1
138
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
* "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport
equipment, commercial equipment, and industrial equipment.
3-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-26: NOX, CO, and NMVOC Emissions from Mobile
Combustion in 2004 (Gg)
Fuel Type/Vehicle Type
Gasoline Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Motorcycles
Diesel Highway
Passenger Cars
Light-Duty Trucks
Heavy-Duty Vehicles
Alternative Fuel Highway3
Non-Highway
Ships and Boats
Locomotives
Farm Equipment
Construction Equipment
Aircraft"
Otherc
Total
N08
3,206
1,749
1,109
336
12
2,881
5
5
2,871
IE
3,377
870
812
66
430
618
582
9,465
CO
55,541
30,945
22,107
2,361
129
851
6
5
840
IE
22,181
1,934
89
231
615
1,032
18,280
78,574
NMVOC
3,525
1,969
1,369
170
18
171
3
3
165
IE
2,186
671
32
18
67
115
1,284
5,882
IE (Included Elsewhere)
Note: Totals may not sum due to independent rounding.
a NOX emissions from alternative fuel highway vehicles are included
under gasoline and diesel highway vehicles.
b Aircraft estimates include only emissions related to landing and
take-off (LTD) cycles, and therefore do not include cruise altitude
emissions.
c "Other" includes gasoline- and diesel-powered recreational,
industrial, lawn and garden, light commercial, logging, airport service,
and other equipment.
Figure 3-17
Mobile Source CH, and N,0 Emissions
60 -
50 -
40 -
S
£30-1
20 -
10 -
0 -
Si-CMCo^-i«tor-ooa>oi-CMCo^-
O)O)O)O)O)O)O)O)O)OOOOO
idle, low speed, and cold start conditions. CH4 and NMVOC
emissions from motor vehicles are a function of the CH4
content of the motor fuel, the amount of hydrocarbons
passing uncombusted through the engine, and any post-
combustion control of hydrocarbon emissions, such as
catalytic converters.
Emissions from mobile combustion were estimated
by transport mode (e.g., highway, air, rail), fuel type (e.g.
motor gasoline, diesel fuel, jet fuel), and vehicle type (e.g.
passenger cars, light-duty trucks). Road transport accounted
for the majority of mobile source fuel consumption, and
hence, the majority of mobile combustion emissions.
Table 3-22 and Table 3-23 provide CH4 and N20 emission
estimates, respectively, inTg C02Eq.; Table 3-24 and Table
3-25 present these estimates in Gg of each gas. Estimates
of NOX, CO, and NMVOC emissions in 2004 are given in
Table 3-26.41
Mobile combustion was responsible for a small portion
of national CH4 emissions (0.5 percent) but was the second
largest source of N20 (11 percent) in the United States. From
1990 to 2004, CH4 emissions declined by 38 percent, to 2.9
Tg C02 Eq. (140 Gg), due largely to control technologies
employed on highway vehicles in the United States that
reduce CO, NOX, NMVOC, and CH4 emissions. The same
technologies, however, initially resulted in higher N20
emissions, causing a 26 percent increase in N20 emissions
from mobile sources between 1990 and 1998. N20 emissions
have subsequently declined 22 percent as improvements in
the emission control technologies installed on new vehicles
have reduced emission rates of both NOX and N20 per vehicle
mile traveled. As a result, N20 emissions in 2004 were 1
percent lower than in 1990, at 42.8 Tg C02 Eq. (138 Gg)
(see Figure 3-17). Overall, CH4 and N20 emissions were
predominantly from gasoline-fueled passenger cars and
light-duty trucks.
Mobile sources comprise the single largest source
category of NOX, CO, and NMVOC emissions in the United
States. In 2004, mobile combustion contributed 55 percent of
NOX emissions, 90 percent of CO emissions, and 43 percent
41 See Annex 3.2 for a complete time series of emission estimates for 1990 through 2004.
Energy 3-33
-------
of NMVOC emissions. Since 1990, emissions of NOX from
mobile combustion decreased by 22 percent, CO emissions
decreased 34 percent, and emissions of NMVOCs decreased
by 46 percent.
Methodology
Estimates of CH4 and N20 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). Depending upon
the category, activity data included such information as
fuel consumption, and vehicle miles traveled (VMT).
The activity data and emission factors used are described
in the subsections that follow. A complete discussion of
the methodology used to estimate emissions from mobile
combustion and the emission factors used in the calculations
is provided in Annex 3.2.
EPA (2005c) and EPA (2003) provided emission
estimates of NOX, CO, and NMVOCs for eight categories
of highway vehicles,42 aircraft, and seven categories of
non-highway vehicles.43 These emission estimates reflect
preliminary EPA data, which, in its final iteration, will be
published on the National Emission Inventory (NEI) Air
Pollutant Emission Trends web site. The methodology used to
develop these estimates can be found on EPA's Air Pollutant
Emission Trends website, at
-------
VMT was then allocated from FHWA's vehicle categories to
fuel-specific vehicle categories using information on shares of
vehicle fuel use for each vehicle category by fuel type reported
in DOE (1993 through 2004) and information on total motor
vehicle fuel consumption by fuel type from FHWA (1996
through 2005). VMT for AFVs were taken from Browning
(2003). The age distributions of the U.S. vehicle fleet were
obtained from EPA (2005d) and EPA (2000), and the average
annual age-specific vehicle mileage accumulation of U.S.
vehicles were obtained from EPA (2000).
Control technology and standards data for highway
vehicles were obtained from the EPA's Office of Transportation
and Air Quality (EPA2005a, 2005b, 2000, 1998, and 1997)
and Browning (2005). These technologies and standards are
defined in Annex 3.2, and were compiled from EPA (1993),
EPA (1994a), EPA (1994b), EPA (1998), EPA (1999), and
IPCC/UNEP/OECD/IEA (1997).
Preliminary estimates for NOX, CO, and NMVOCs were
obtained from EPA (2005c) and disaggregated based on EPA
(2003), which, in its final iteration, will be published on the
National Emission Inventory (NEI) Air Pollutant Emission
Trends web site.
Non-Highway Vehicles
Fuel consumption data were employed as a measure of
activity for non-highway vehicles, and fuel-specific emission
factors were applied.45 Activity data were obtained from
AAR (2005), BEA (1991 through 2005), Benson (2002
through 2004), DOE (1993 through 2004), DESC (2005),
DOC (1991 through 2005), DOT (1991 through 2005), EIA
(2002a), EIA (2002b), EIA (2005a), EIA (2005b), EIA (2003
through 2004), EIA (1991 through 2005), EPA (2004), and
FAA (2005). Emission factors for non-highway modes were
taken from IPCC/UNEP/OECD/IEA (1997).
Uncertainty
This section discusses the uncertainty of the emission
estimates for CH4 and N20. Uncertainty was analyzed
separately for highway vehicles and non-highway vehicles
due to differences in their characteristics and their
contributions to total mobile source emissions.
Uncertainty analyses were not conducted for NOX, CO,
or NMVOC emissions. Emission factors for these gases have
been extensively researched since these gases are regulated
emissions from motor vehicles in the United States, and
the uncertainty of these emission estimates is believed
to be relatively low. A much higher level of uncertainty
is associated with CH4 and N20 emission factors, since
emissions of these gases are not regulated in the United
States, and unlike C02 emissions, the emission pathways
of CH4 and N20 are also highly complex.
Highway Vehicles
A quantitative uncertainty analysis was conducted
for the highway portion of the mobile source sector using
the IPCC-recommended Tier 2 uncertainty estimation
methodology, Monte Carlo Simulation technique, using @
RISK software. The uncertainty analysis was performed on
2004 estimates of CH4 and N20 emissions, incorporating
probability distribution functions associated with the
major input variables. For the purposes of this analysis, the
uncertainty was modeled for the following two major sets
of input variables: (1) vehicle mile traveled (VMT) data, by
vehicle and fuel type and (2) emission factor data, by vehicle,
fuel, and control technology type.
Mobile combustion emissions of CH4 and N20 per
vehicle mile traveled vary significantly due to fuel type
and composition, technology type, operating speeds and
conditions, type of emission control equipment, equipment
age, and operating and maintenance practices. The primary
activity data, VMT, are collected and analyzed each year by
government agencies.
To determine the uncertainty associated with the activity
data used in the calculations of CH4 and N20 emissions,
the agencies and the experts that supply the data were
contacted. Because few of these sources were able to provide
quantitative estimates of uncertainty, expert quantitative
judgments were used to assess the uncertainty associated
with the activity data.
The emission factors for highway vehicles used in the
Inventory were obtained from ICF (2004). These factors
were based on laboratory testing of vehicles. While the
45 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
-------
controlled testing environment simulates real driving
conditions, emission results from such testing can only
approximate real world conditions and emissions. For
some vehicle and control technology types, the testing
did not yield statistically significant results within the 95
percent confidence interval, requiring expert judgments to
be used in developing the emission factors. In those cases,
the emission factors were developed based on comparisons
of fuel consumption between similar vehicle and control
technology categories.
The estimates of VMT for highway vehicles by vehicle
type in the United States were provided by FHWA (1996
through 2005), and were generated though the cooperation
of FHWA and state and local governments. These estimates
are subject to several possible sources of error, such as
unregistered vehicles, and measurement and estimation
errors. These VMT were apportioned by fuel type, based
on data from DOE (2004), and then allocated to individual
model years using temporal profiles of both the vehicle
fleet by age and vehicle usage by model year in the United
States provided by EPA (2005d) and EPA (2000). While the
uncertainty associated with total U.S. VMT is believed to
be low, the uncertainty within individual source categories
was assumed to be higher given uncertainties associated with
apportioning total VMT into individual vehicle categories,
by fuel type, by technology type, and equipment age. The
uncertainty of individual estimates was assumed to relate to
the magnitude of estimated VMT (i.e., itwas assumed smaller
sources had greater percentage uncertainty). A further source
of uncertainty occurs since FHWA and EPA use different
definitions of vehicle type and estimates of VMT by vehicle
type (provided by FHWA) are broken down by fuel type
using EPA vehicle categories.
Atotal of 69 highway data input variables were simulated
through Monte Carlo Simulation technique using @RISK
software. Variables included VMT and emission factors for
individual vehicle categories and technologies. In developing
the uncertainty estimation model, a normal distribution was
assumed for all activity-related input variables (e.g., VMT)
except in the case of buses, in which a triangular distribution
was used. The dependencies and other correlations among
the activity data were incorporated into the model to ensure
consistency in the model specification and simulation.
Emission factors were assigned uniform distributions, with
upper and lower bounds assigned to input variables based on
97.5 percent confidence intervals of laboratory test data. In
cases where data did not yield statistically significant results
within the 95 percent confidence interval, estimates of upper
and lower bounds were made using expert judgment. The
bounds for the emission factor-related input variables were
typically asymmetrical around their inventory estimates. Bias
(or systematic uncertainties) associated with the emission
factors was incorporated into the analysis when expert
judgments were applied to the laboratory test results in
determining the uncertainty characteristics and/or the bounds
of the emission factors.46 The results of this analysis are
reported in the section below, titled Quantitative Estimates
of Uncertainty.
Non-Highway Vehicles
Emissions from non-highway vehicles are a small
portion of total emissions from mobiles sources, representing
22 percent of CH4 emissions from mobile sources and 10
percent of N20 emissions from mobile sources in 2004. Since
they comprise a small share of mobile source emissions,
even large uncertainties in these estimates would have
a relatively small impact on the total emission estimate
for mobile sources. As a result, a quantitative analysis of
uncertainty of emissions from non-highway vehicles has
not been performed. However, sources of uncertainty for
non-highway vehicles are being investigated by examining
the underlying uncertainty of emission factors and fuel
consumption data.
Overall, a significant amount of uncertainty is associated
with the emission estimates for non-road sources. A primary
cause is a large degree of uncertainty surrounding emission
factors. The IPCC Good Practice Guidance reports that
CH4 emissions from aviation and marine sources may be
uncertain by a factor of two, while N20 emissions may be
uncertain by an order of magnitude for marine sources and
several orders of magnitude for aviation. No information
is provided on the uncertainty of emission factors for other
non-highway sources.
Fuel consumption data have a lower uncertainty than
emission factors, though large uncertainties do exist for
individual sources. Fuel consumption for off-highway
46 Random uncertainties are the main focus of statistical uncertainty analysis. Uncertainty estimates elicited from experts include both random and
systematic uncertainty. Hence, both these types of uncertainty are represented in this uncertainty analysis.
3-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-27: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Mobile Sources (Tg C02 Eq.
and Percent)
Source
Gas
(TgC02Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Mobile Sources
Mobile Sources
CH4
N20
2.9
42.8
2.7
36.1
3.0
55.3
-16%
+4%
+29%
aRange of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
vehicles (i.e., equipment used for agriculture, construction,
lawn and garden, railroad, airport ground support, etc.,
as well as recreational vehicles) was generated by EPA's
NONROAD model (EPA 2004). This model estimates fuel
consumption based on estimated equipment/vehicle use (in
hours) and average fuel consumed per hour of use. Since
the fuel estimates are not based upon documented fuel sales
or consumption, a fair degree of uncertainty accompanies
these estimates.
Estimates of distillate fuel sales for ships and boats were
obtained from EIAs Fuel Oil and Kerosene Sales (EIA 1991
through 2004). These estimates have a moderate level of
uncertainty since EIAs estimates are based on survey data and
reflect sales to economic sectors, which may include use by
both mobile and non-mobile sources within a sector. Domestic
consumption of residual fuel by ships and boats is obtained
from EIA (2005a). These estimates fluctuate widely from year
to year, and are believed to be highly uncertain. In addition,
estimates of distillate and residual fuel sales for ships and boats
are adjusted for bunker fuel consumption, which introduces an
additional (and much higher) level of uncertainty.
Jet fuel and aviation gasoline consumption data
are obtained from EIA (2005a). Estimates of jet fuel
consumption are also adjusted downward to account for
international bunker fuels, introducing a significant amount
of uncertainty. Additionally, all jet fuel consumption in the
transportation sector is assumed to be consumed by aircraft.
Some fuel purchased by airlines is not used in aircraft but
instead used to power auxiliary power units, in ground
equipment, and to test engines. Some jet fuel may also be
used for other purposes such as blending with diesel fuel
or heating oil.
In calculating CH4 emissions from aircraft, an average
emission factor is applied to total jet fuel consumption. This
average emission factor takes into account the fact that CH4
emissions occur only during the landing and take-off (LTO)
cycles, with no CH4 being emitted during the cruise cycle.
However, a better approach would be to apply emission
factors based on the number of LTO cycles.
Quantitative Estimates of Uncertainty
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-27. Mobile combustion CH4
emissions in 2004 were estimated to be between 2.7 and 3.0
Tg C02 Eq. at a 95 percent confidence level (or in 19 out
of 20 Monte Carlo Simulations). This indicates a range of 8
percent below to 4 percent above the 2004 emission estimate
of 2.9 Tg C02 Eq. Also at a 95 percent confidence level,
mobile combustion N20 emissions in 2004 were estimated
to be between 36.1 and 55.3 Tg C02 Eq., indicating a range
of 16 percent below to 29 percent above the 2004 emission
estimate of 42.8 Tg C02 Eq.
This uncertainty analysis is a continuation of a multi-
year process for developing credible quantitative uncertainty
estimates for this source category using the IPCC Tier 2
approach to uncertainty analysis. In the upcoming years, the
type and the characteristics of the actual probability density
functions underlying the input variables will be identified and
more credibly characterized. Accordingly, the quantitative
uncertainty estimates reported in this section should be
considered as preliminary and illustrative.
QA/QC and Verification
A source-specific QA/QC plan for mobile combustion
was developed and implemented. This effort included a
Tier 1 analysis, as well as portions of a Tier 2 analysis.
The Tier 2 procedures focused on the emission factor and
activity data sources, as well as the methodology used for
estimating emissions. These procedures included a qualitative
Energy 3-37
-------
assessment of the emission estimates to determine whether
they appear consistent with the most recent activity data
and emission factors available. A comparison of historical
emissions between this year's and last year's Inventories was
also conducted, and was qualitatively assessed to ensure that
the changes in estimates were consistent with the changes
in activity data and emission factors.
Recalculations Discussion
In order to ensure the highest quality estimates, the
methodology is continuously revised based on comments
from internal and external reviewers. This year, a number
of adjustments were made to the historical data. Vehicle age
distributions for 1999 forward were revised based on new
data obtained from EPA's MOVES model (EPA 2005d).
Diesel fractions for light trucks and medium-heavy trucks
for 1998 through 2003 were updated based on data obtained
from the Vehicle Inventory and Use Survey (Census 2000).
The value for diesel consumption by boats was adjusted to
remove all military bunker fuel consumption, which had
not been properly removed from the estimates in previous
version of the Inventory. Lastly, vehicle miles traveled
and fuel consumption estimates for non-highway vehicles
were revised for 2003 based on updated data from FHWA's
Highway Statistics (FHWA 2005).
As a result of these changes, average estimates of CH4
and N20 emissions from mobile combustion decreased less
than 0.1 Tg C02 Eq. (less than 1 percent) each year for the
period 1990 through 2003.
Planned Improvements
While the data used for this report represent the most
accurate information available, three areas have been
identified that could potentially be improved in the short
term given available resources:
1) Update CH4 andN2O Emission Factors for Highway
Vehicles—A number of recent efforts have focused on
improving the estimates of CH4 and N20 Emission Factors
for alternative fuel highway vehicles. These studies are
expected to be available next year, and will be reviewed
to determine whether the current emission factors can be
updated.
2) Continue the Reconciliation of Fuel Consumption
Estimates used for Calculating N2O/CH4 and CO2—
Estimates of transportation fuel consumption by fuel type
from EIA are used as the basis for estimating C02 emissions
from the transportation sector. These estimates are then
apportioned to mode and vehicle category based on "bottom
up" estimates of fuel consumption from sources such as
FHWA's Highway Statistics (FHWA 1996 through 2004)
and DOE's Transportation Energy Data Book (DOE 1993
through 2004). These sources are also used to develop N20
and CH4 estimates. The EPA fuel consumption estimates,
however, differ from the estimates derived using "bottom
up" sources. For this Inventory, estimates of distillate fuel
consumption have been reconciled. Potential improvements
include reconciling additional fuel consumption estimates
from EIA and other data sources, and revising the current
process of allocating C02 emissions to particular vehicle
types.
3) Improve consideration of emissions from trucks used
off-road—Some light- and heavy-duty trucks travel for a
portion of their mileage off-road. N20 and CH4 estimates for
highway vehicles are developed based on vehicle mileage
data from FHWA's Highway Statistics, which in turn, are
drawn from the Highway Performance Monitoring System
(HPMS). These emission estimates do not address travel
by trucks off-road. Gasoline fuel consumed by trucks used
off-road for construction, agriculture, and other industrial/
commercial uses is reported in Highway Statistics, and is
included as part of the non-road agriculture and construction
categories. However, diesel fuel consumed by trucks used
off-road is not addressed in the Inventory, and further work
should be conducted to develop estimates of off-road truck
use of diesel fuel. In addition, default emission factors from
IPCC are applied to the off-highway modes. As a result, the
emissions factors for agricultural equipment are applied both
to equipment and trucks used in agriculture, and emissions
factors for construction equipment are applied both to
equipment and trucks used in construction.
4) Improve estimation of VMT by vehicle/fuel type
category—The current Inventory process for estimating
VMT by vehicle/fuel type category involves apportioning
VMT by vehicle type to each fuel type on the basis of fuel
consumption. While this is a reasonable simplification,
this approach implicitly assumes the same average fuel
economy for gasoline and diesel vehicles. A more accurate
apportionment for VMT by fuel type for light-duty trucks and
medium/heavy-duty trucks could potentially be developed
3-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
using data on vehicle travel from the Vehicle Inventory and
Use Survey (Census 2000) and other publications, or using
VMT breakdowns by vehicle/fuel type combinations from
the MOBILES or MOVES models.
3.5. Coal Mining (IPCC Source
Category 1B1 a)
Three types of coal mining related activities release CH4
to the atmosphere: underground mining, surface mining, and
post-mining (i.e., coal-handling) activities. Underground coal
mines contribute the largest share of CH4 emissions. All 115
gassy underground coal mines employ ventilation systems
to ensure that CH4 levels remain within safe concentrations.
These systems can exhaust significant amounts of CH4 to
the atmosphere in low concentrations. Additionally, twenty-
one U.S. coal mines supplement ventilation systems with
degasification systems. Degasification systems are wells
drilled from the surface or boreholes drilled inside the mine
that remove large volumes of CH4 before, during, or after
mining. In 2004, eleven coal mines collected CH4 from
degasification systems and sold this gas to a pipeline, thus
reducing emissions to the atmosphere. In addition, one coal
mine used CH4 from its degasification system to heat mine
ventilation air on site. Two of the coal mines that sold gas
to pipelines also used CH4 to generate electricity or fuel a
thermal coal dryer. Surface coal mines also release CH4 as
the overburden is removed and the coal is exposed, but the
level of emissions is much lower than from underground
mines. Finally, some of the CH4 retained in the coal after
mining is released during processing, storage, and transport
of the coal.
Total CH4 emissions in 2004 were estimated to be 56.3
Tg C02 Eq. (2,682 Gg), a decline of 31 percent since 1990
(see Table 3-28 and Table 3-29). Of this amount, underground
mines accounted for 69 percent, surface mines accounted
for 17 percent, and post-mining emissions accounted for
14 percent. In 1993, CH4 generated from underground
mining dropped, primarily due to labor strikes at many
large underground mines. In 1994 and 1995, CH4 emissions
increased due to resumed production at high emitting mines
after the labor strike. The decline in CH4 emissions from
underground mines from 1996 to 2002 was the result of
the reduction of overall coal production, the mining of less
gassy coal, and an increase in CH4 recovered and used. CH4
emissions increased slightly in 2003 due to additional gas
Table 3-28: CH4 Emissions from Coal Mining (Tg C02 Eq.)
Activity
Underground Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (Underground)
Post-Mining (Surface)
Total
1990
62.1
67.6
(5.6)
10.4
7.7
1.7
81.9
1997
44.3
55.7
(11.4)
9.3
7.4
1.5
62.6
1998
44.5
58.6
(14.1)
9.4
7.4
1.5
62.8
1999
41.7
54.4
(12.7)
9.0
6.8
1.5
58.9
2000
39.4
54.0
(14.6)
8.8
6.7
1.4
56.3
2001
38.0
54.2
(16.1)
9.2
6.8
1.5
55.5
2002
35.9
53.3
(17.4)
8.8
6.4
1.4
52.5
2003
38.6
53.6
(15.0)
8.4
6.4
1.4
54.8
2004
38.9
52.8
(13.9)
9.3
6.6
1.5
56.3
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Table 3-29: CH4 Emissions from Coal Mining (Gg)
Activity
Underground Mining
Liberated
Recovered & Used
Surface Mining
Post-Mining (Underground)
Post-Mining (Surface)
Total
1990
2,956
3,220
(265)
497
367
81
3,900
1997
2,111
2,654
(543)
445
354
72
2,983
1998
2,118
2,791
(673)
448
352
73
2,990
1999
1,985
2,589
(605)
428
325
69
2,807
2000
1,878
2,573
(695)
417
317
68
2,679
2001
1,811
2,580
(769)
438
323
71
2,644
2002
1,708
2,538
(830)
420
304
68
2,500
2003
1,839
2,554
(716)
402
305
65
2,611
2004
1,851
2,512
(661)
444
315
72
2,682
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Energy 3-39
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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-one 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.
This calculation was complicated by the fact that most CH4
is not recovered and used during the same year in which
the particular coal seam is mined. In 2004, eleven active
coal mines sold recovered CH4 into the local gas pipeline
networks, while one coal mine used recovered CH4 on site.
Emissions avoided for these projects were estimated using
gas sales data reported by various state agencies. For most
mines with recovery systems, companies and state agencies
provided individual well production information, which
was used to assign gas sales to a particular year. For the few
remaining mines, coal mine operators supplied information
regarding the number of years in advance of mining that gas
recovery occurs.
Surface Mines and Post-Mining Emissions. Surface
mining and post-mining CH4 emissions were estimated by
multiplying basin-specific coal production, obtained from the
Energy Information Administration's Coal Industry Annual
(see Table 3-30) (EIA 2004), 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 (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
47 MSHA records coal mine methane readings with concentrations of greater than 50 ppm (parts per million) methane. Readings below this threshold are
considered non-detectable.
drainage being vented to the atmosphere and a reduction in
CH4 recovery. Recovery continued to decrease in 2004 with
reduced production from pre-drainage wells, increased use
of horizontal gob wells that are vented to the atmosphere,
and temporary closure of a major project due to a mine fire.
Surface mine emissions and post-mining emissions remained
relatively constant from 1990 to 2004.
Methodology
The methodology for estimating CH4 emissions from
coal mining consists of two parts. The first part involves
estimating CH4 emissions from underground mines. Because
of the availability of ventilation system measurements,
underground mine emissions can be estimated on a mine-by-
mine basis and then summed to determine total emissions.
The second step involves estimating emissions from surface
mines and post-mining activities by multiplying basin-
specific coal production by basin-specific emission factors.
Underground mines. Total CH4 emitted from
underground mines was estimated as the sum of CH4
liberated from ventilation systems and CH4 liberated by
means of degasification systems, minus CH4 recovered and
used. The Mine Safety and Heath Administration (MSHA)
samples CH4 emissions from ventilation systems for all
mines with detectable47 CH4 concentrations. These mine-
by-mine measurements are used to estimate CH4 emissions
from ventilation systems.
Table 3-30: Coal Production (Thousand Metric Tons)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Underground
384,250
368,635
368,627
318,478
362,065
359,477
371,816
381,620
378,964
355,433
338,173
345,305
324,219
320,047
333,424
Surface
546,818
532,656
534,290
539,214
575,529
577,638
593,315
607,163
634,864
642,877
635,592
676,142
667,619
651,251
687,497
Total
931,068
901,291
902,917
857,692
937,594
937,115
965,131
988,783
1,013,828
998,310
973,765
1,021,446
991,838
971,297
1,020,921
3-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 3-31: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg C02 Eq. and Percent)
Source
Coal Mining
Gas
CH4
2004 Emission
Estimate
(Tg C02 Eq.)
56.3
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound
54.1 58.6
Lower Bound Upper Bound
-4% +4%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
be 32.5 percent of the average in situ CH4 content of coals
mined in the basin.
Uncertainty
A quantitative uncertainty analysis was conducted for the
coal mining source category using the IPCC-recommended
Tier 2 uncertainty estimation methodology. Because emission
estimates from underground ventilation systems were
based on actual measurement data, uncertainty is relatively
low. A degree of imprecision was introduced because the
measurements used were not continuous but rather an
average of quarterly instantaneous readings. Additionally,
the measurement equipment used can be expected to have
resulted in an average of 10 percent overestimation of annual
CH4 emissions (Mutmansky and Wang 2000). Estimates
of CH4 liberated and recovered by degasification systems
are relatively certain because many coal mine operators
provided information on individual well gas sales and mined
through dates. Many of the recovery estimates use data on
wells within 100 feet of a mined area. Uncertainty also
exists concerning the radius of influence of each well. The
number of wells counted, and thus the avoided emissions,
may increase if the drainage area is found to be larger than
currently estimated.
Compared to underground mines, there is considerably
more uncertainty associated with surface mining and post-
mining emissions because of the difficulty in developing
accurate emission factors from field measurements. However,
since underground emissions comprise the majority of total
coal mining emissions, the uncertainty associated with
underground emissions is the primary factor that determines
overall uncertainty. The results of the Tier 2 quantitative
uncertainty analysis are summarized in Table 3-31. Coal
mining CH4 emissions in 2004 were estimated to be between
54.1 and 58.6 Tg C02 Eq. at a 95 percent confidence level
(or in 19 out of 20 Monte Carlo Simulations). This indicates
a range of 4 percent below to 4 percent above the 2004
emission estimate of 56.3 Tg C02 Eq.
Recalculations Discussion
Recalculations were performed on all years with negligible
changes in 1994,1996, and 1998-2002, as QA/QC of databases
uncovered that emissions avoided had been miscalculated.
Some recalculations were done in 2003 on Alabama mines
but were not linked retroactively. These recalculations either
led to no change in net emissions, or a change of 0.1 Tg C02
Eq. Emissions avoided for 2003 were adjusted downwardly
as a major operator reported in 2004 that double-counting of
some pre-drainage wells had previously occurred. Correction
of this error led to a reduction in emissions avoided of 1.0 Tg
C02 Eq. which changed total emissions for 2003 from 53.8
to 54.8 Tg C02 Eq.
Planned Improvements
To reduce the uncertainty associated with the radius of
influence of each well, the appropriate drainage radius will
be investigated for future inventories. Since the number of
wells counted may increase if the drainage area is found to
be larger than currently estimated, additional mines may be
included in future estimates of recovery.
3.6. Abandoned Underground Coal
Mines (IPCC Source Category 1B1 a)
All underground and surface coal mining liberates
CH4 as part of the normal mining operations. The amount
of CH4 liberated depends on the amount that resides in the
coal ("in situ") and surrounding strata when mining occurs.
The in-situ CH4 content depends upon the amount of CH4
created during the coal formation (i.e., coalification) process,
and the geologic characteristics of the coal seams. During
coalification, more deeply buried deposits tend to generate
Energy 3-41
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Table 3-32: CH4 Emissions from Abandoned Coal Mines (Tg C02 Eq.)
Activity
Abandoned Underground Mines
Recovered & Used
Total
1990
6.0
0.0
6.0
1998
8.6
1.7
6.9
1999
8.6
1.6
6.9
2000
8.7
1.5
7.2
2001
8.0
1.5
6.6
2002
7.6
1.6
6.0
2003
7.3
1.5
5.8
2004
7.1
1.5
5.6
Note: Totals may not sum due to independent rounding.
Table 3-33: CH4 Emissions from Abandoned Coal Mines (Gg)
Activity
Abandoned Underground Mines
Recovered & Used
Total
1990
287
0
287
1998
407
79
328
1999
407
77
330
2000
415
72
343
2001
383
70
313
2002
362
74
288
2003
349
72
277
2004
339
70
269
Note: Totals may not sum due to independent rounding.
more CH4 and retain more of the gas after uplift to minable
depths. Deep underground coal seams generally have higher
CH4 contents than shallow coal seams or surface deposits.
Underground coal mines contribute the largest share of
CH4 emissions, with active underground mines the leading
source of underground emissions. However, mines also
continue to release CH4 after closure. As mines mature
and coal seams are mined through, mines close and are
abandoned. Many are sealed and some flood through intrusion
of groundwater or surface water into the void. Shafts or
portals are generally filled with gravel and capped with a
concrete seal, while vent pipes and boreholes are plugged
in a manner similar to oil and gas wells. Some abandoned
mines are vented to the atmosphere to prevent the buildup
of CH4 that may find its way to surface structures through
overburden fractures. As work stops within the mines, the
CH4 liberation decreases but it does not stop completely.
Following an initial decline, abandoned mines can liberate
CH4 at a near-steady rate over an extended period of time,
or, if flooded, produce gas for only a few years. The gas
can migrate to the surface through the conduits described
above, particularly if they have not been sealed adequately. In
addition, diffuse emissions can occur when CH4 migrates to
the surface through cracks and fissures in the strata overlying
the coal mine. The following factors influence abandoned
mine emissions:
• Time since abandonment;
• Gas content and adsorption characteristics of coal;
• CH4 flow capacity of the mine;
• Mine flooding;
• Presence of vent holes; and
• Mine seals.
Gross abandoned mine CH4 emissions ranged from
6.0 to 9.0 Tg C02 Eq. from 1990 through 2004, varying,
in general, by approximately 1 to 18 percent from year to
year. Fluctuations were due mainly to the number of mines
closed during a given year as well as the magnitude of the
emissions from those mines when active. Abandoned mine
emissions peaked in 1996 (9.0 Tg C02 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 thirteen gassy
mine closures during each of the years from 1998 through
2004, with only one closure in 2004. By 2004, abandoned
mine emissions were reduced to 5.7 Tg C02 Eq. (see Table
3-32 and Table 3-33).
Methodology
Estimating CH4 emissions from an abandoned coal
mine requires predicting the emissions of a mine from the
time of abandonment through the inventory year of interest.
The flow of CH4 from the coal to the mine void is primarily
dependent on 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
3-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
of coal mining, and the flow capacity of the mine in much
the same way as the initial rate of a water-free conventional
gas well reflects the gas content of the producing formation
and the flow capacity of the well. Existing data on abandoned
mine emissions through time, although sparse, appear to
fit the hyperbolic type of decline curve used in forecasting
production from natural gas wells.
In order to estimate CH4 emissions over time for a
given mine, it is necessary to apply a decline function,
initiated upon abandonment, to that mine. In the analysis,
mines were grouped by coal basin with the assumption
that they will generally have the same initial pressures,
permeability and isotherm. As CH4 leaves the system, the
reservoir pressure, Pr, declines as described by the isotherm.
The emission rate declines because the mine pressure (Pw)
is essentially constant at atmospheric pressure, for a vented
mine, and the PI term is essentially constant at the pressures
of interest (atmospheric to 30 psia). A rate-time equation can
be generated that can be used to predict future emissions.
This decline through time is hyperbolic in nature and can be
empirically expressed as:
q = q1(l+bD1t)H/b)
Where:
• q is the gas rate at time t in mcf/d
• q( is the initial gas rate at time zero (t0) in million cubic
feet per day (mcfd)
• b is the hyperbolic exponent, dimensionless
• Dj is the initial decline rate, 1/yr
• t is elapsed time from t0 in years
This equation is applied to mines of various initial
emission rates that have similar initial pressures, permeability
and adsorption isotherms (EPA 2003).
The decline curves are also affected by both sealing
and flooding. Based on field measurement data, it was
assumed that most U.S. mines prone to flooding will
become completely flooded within 8 years and therefore no
longer have any measurable CH4 emissions. Based on this
assumption, an average decline rate for flooding mines was
established by fitting a decline curve to emissions from field
measurements. An exponential equation was developed from
emissions data measured at eight abandoned mines known to
be filling with water located in two of the five basins. Using
a least squares, curve-fitting algorithm, emissions data were
matched to the exponential equation shown below. There was
not enough data to establish basin-specific equations as was
done with the vented, non-flooding mines (EPA 2003).
q = qje<-Dt)
Where:
• q is the gas flow rate at time t in mcf/d
•• q( is the initial gas flow rate at time zero (tg) in mcfd
• D is the decline rate, 1/yr
• t is elapsed time from t0 in years
Seals have an inhibiting effect on the rate of flow of
CH4 into the atmosphere compared to the rate that would
be emitted if the mine had an open vent. The total volume
emitted will be the same, but will occur over a longer
period. The methodology, therefore, treats the emissions
prediction from a sealed mine similar to emissions from
a vented mine, but uses a lower initial rate depending on
the degree of sealing. The computational fluid dynamics
simulator was again used with the conceptual abandoned
mine model to predict the decline curve for inhibited flow.
The percent sealed is defined as 100 x (1 - initial emissions
from sealed mine / emission rate at abandonment prior to
sealing). Significant differences are seen between 50 percent,
80 percent and 95 percent closure. These decline curves
were therefore used as the high, middle, and low values for
emissions from sealed mines (EPA 2003).
For active coal mines, those mines producing over 100
mcfd account for 98 percent of all CH4 emissions. This
same relationship is assumed for abandoned mines. It was
determined that 438 abandoned mines closing after 1972
produced emissions greater than 100 mcfd when active.
Further, the status of 263 of the 438 mines (or 60 percent)
is known to be either 1) vented to the atmosphere, 2) sealed
to some degree (either earthen or concrete seals), or 3)
flooded (enough to inhibit CH4 flow to the atmosphere).
The remaining 40 percent of the mines were placed in one
of the three categories by applying a probability distribution
analysis based on the known status of other mines located in
the same coal basin (EPA 2003).
Inputs to the decline equation require the average
emission rate and the date of abandonment. Generally this
data is available for mines abandoned after 1972; however,
such data are largely unknown for mines closed before 1972.
Information that is readily available such as coal production
Energy 3-43
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by state and county are helpful, but do not provide enough
data to directly employ the methodology used to calculate
emissions from mines abandoned after 1971. It is assumed
that pre-1972 mines are governed by the same physical,
geologic, and hydrologic constraints that apply to post-1972
mines; thus, their emissions may be characterized by the
same decline curves.
During the 1970s, 78 percent of CH4 emissions from
coal mining came from seventeen counties in seven states.
In addition, mine closure dates were obtained for two states,
Colorado and Illinois, throughout the 20th century. The data
was 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 ventilation data
for the total CH4 liberation rate for fourteen mines that
closed between 1992 and 2004. Since the sample of gassy
mines (with active mine emissions greater than 100 mcfd)
is assumed to account for 78 percent of the pre-1971 and
98 percent of the post-1971 abandoned mine emissions,
the modeled results were multiplied by 1.22 and 1.02 to
account for all U.S. abandoned mine emissions. From 1993
through 2004, emission totals were downwardly adjusted to
reflect abandoned mine CH4 emissions avoided from those
mines. The inventory totals were not adjusted for abandoned
mine reductions in 1990 through 1992, because no data was
reported for abandoned coal mining CH4 recovery projects
during that time.
Uncertainty
A quantitative uncertainty analysis was conducted
to estimate the uncertainty surrounding the estimates
of emissions from abandoned underground coal mines.
The uncertainty analysis described below provides for
the specification of probability density functions for key
variables within a computational structure that mirrors the
calculation of the inventory estimate. The results provide
the range within which, with 95 percent certainty, emissions
from this source category are likely to fall.
As discussed above, the parameters for which values
must be estimated for each mine in order to predict its decline
curve are: 1) the coal's adsorption isotherm; 2) CH4 flow
capacity as expressed by permeability; and 3) pressure at
abandonment. Because these parameters are not available
for each mine, a methodological approach to estimating
emissions was used that generates a probability distribution
of potential outcomes based on the most likely value and
the probable range of values for each parameter. The range
of values is not meant to capture the extreme values, but
values that represent the highest and lowest quartile of the
cumulative probability density function of each parameter.
Once the low, mid, and high values are selected, they are
applied to a probability density function.
The emission estimates from underground ventilation
systems were based on actual measurement data, which
are believed to have relatively low uncertainty. A degree
of imprecision was introduced because the measurements
were not continuous, but rather an average of quarterly
instantaneous readings. Additionally, the measurement
equipment used may have resulted in an average of 10 percent
overestimation of annual CH4 emissions (Mutmansky and
Wang 2000). Estimates of CH4 liberated and recovered by
degasification systems are also relatively certain because
many coal mine operators provided information on individual
well gas sales and mined through dates.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-34. Abandoned coal mines CH4
emissions in 2004 were estimated to be between 4.7 and 7.0
Tg C02 Eq. at a 95 percent confidence level (or in 19 out of
20 Monte Carlo Simulations). This indicates a range of 18
percent below to 23 percent above the 2004 emission estimate
of 5.6 Tg C02 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
3-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-34: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal Mines
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Abandoned Underground
Coal Mines CH4 5.6
4.7 7.0 -18% +23%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
unknown status mines (which account for 40 percent of the
mines), with a +50 percent uncertainty.
QA/QC and Verification
As part of a Tier 2 analysis, the United States undertook
an effort to verify the model results used in the U.S. Inventory
with field measurements. Field measurements were used
to test the accuracy of the mathematical decline curves to
be used for basin-specific emissions estimates. A series of
field measurements were conducted at abandoned mine vent
locations across the United States. Between November 1998
and February 2000, EPA recorded measurements at five mines
that were not flooded. Measurements were recorded at two
abandoned mines located in Ohio and Virginia continuously
for 6 to 12 hours. As the methodology was finalized, EPA
measured emissions from three additional mines located in
Illinois and Colorado. These measurements were recorded
hourly for 3 to 4 days and were normalized to average
barometric pressures. Prior to these measurements, EPA's
Office of Research and Development initiated a field research
program in the early 1990s. Data for 21 abandoned mines
located throughout the Northern and Central Appalachian,
Black Warrior, and Illinois Basins were collected using
similar techniques.
Measurements for all field data recorded were plotted
against predicted emissions as part of the two studies from
1991 through 2000. Emission rates from nine of the ten
mines that were measured fall very close to the predicted
mid-case decline rate for their respective basins. For the
exponential decline curve fit to the flooding mines, six of nine
measurements fall within a 95 percent predictive confidence
interval of the mean.
Of the abandoned mines in the database, only about
12 percent of the mines maintain vents to the atmosphere.
Therefore, it is difficult to obtain field data. Additional field
measurements, however, would be beneficial to further
calibrate the equations defined above. Furthermore, it would
be useful to extend measurements of diffuse emissions
from sealed mines, since they comprise 44 percent of total
mines.
Recalculations Discussion
In 2005, CH4 emissions from abandoned mines
were recalculated for 1990-2003. QA/QC of the database
uncovered several mines that had been accounted for more
than once. Changes in MSHA's database regarding date of
abandonment for several mines led to adding them more than
once—once for each time reported abandoned. Also, sale of
mines and resultant renaming caused two mines to be added
twice with different names.
Emissions for 2003 were recalculated, as additional
recovery data for one mine was obtained, resulting in an
increase of 0.1 Tg C02 Eq. in the amount of CH4 recovered
and used. Recalculation of the CH4 emissions from flooded,
abandoned mines yielded a decrease of 0.1 Tg C02 Eq.
in CH4 emitted for 2003. Additionally, a research project
conducted on abandoned mine status yielded updates to the
status of 19 mines, ten of which were previously designated
"unknown." Recalculations led to a decrease in emissions
each inventory year. The total emissions for 2003 decreased
from 6.2 Tg C02 Eq. to 5.8 Tg C02 Eq. Data for other years
from 1990-2002 saw similar changes, the most significant
decrease occurring in total emissions for 2000 of 0.5 Tg
C02 Eq.
3.7. Petroleum Systems (IPCC
Source Category 1B2a)
CH4 emissions from petroleum systems are primarily
associated with crude oil production, transportation, and
Energy 3-45
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refining operations. During each of these activities, CH4
is released to the atmosphere as fugitive emissions, vented
emissions, emissions from operational upsets, and emissions
from fuel combustion. Total CH4 emissions from petroleum
systems in 2004 were 25.65 Tg C02 Eq. (1,222 Gg). Since
1990, emissions declined due to a decline in domestic oil
production and industry efforts to make emissions reductions
(see Table 3-38 and Table 3-39). The various sources of
emissions are detailed below.
Production Field Operations. Production field operations
account for over 97 percent of total CH4 emissions from
petroleum systems. Vented CH4 from field operations
account for approximately 90 percent of the emissions from
the production sector, fugitive emissions account for four
percent, combustion emissions six percent, and process
upset emissions just barely over one-tenth of a percent. The
most dominant sources of vented emissions are offshore oil
platforms (shallow and deep water platforms), field storage
tanks and natural-gas-powered pneumatic devices (low
bleed and high bleed). These five sources alone emit over
84 percent of the production field operations emissions.
Offshore platform emissions are a combination of fugitive,
vented, and combustion emissions from all equipment housed
on the platform. Emissions from storage tanks occur when
the CH4 entrained in crude oil under pressure volatilizes once
the crude oil is put into storage tanks at atmospheric pressure.
Emissions from high and low-bleed pneumatics occur when
pressurized gas that is used for control devices is bled to
the atmosphere as they cycle up and down to modulate the
system. Two additional large sources, chemical injection
pumps and gas engines, together account for 10 percent of
emissions from the production sector. The remaining eight
percent of the emissions are distributed among 26 additional
activities within the four categories: vented, fugitive,
combustion and process upset emissions.
Crude Oil Transportation. Crude oil transportation
activities account for less than one percent of total CH4
emissions from the oil industry. Venting from tanks and
marine vessel loading operations accounts for 66 percent
of CH4 emissions from crude oil transportation. Fugitive
Table 3-35: CH4 Emissions from Petroleum Systems (Tg C02 Eq.)
Activity
Production Field Operations
Pneumatic device venting
Tank Venting
Combustion & process
upsets
Misc. venting & fugitives
Wellhead fugitives
Crude Oil Transportation
Refining
Total
1990
33.8
11.5
3.8
1.8
16.2
0.5
0.1
0.5
34.4
1998
29.0
10.6
3.4
1.7
12.8
0.5
0.1
0.6
29.7
1999
27.8
10.2
3.2
1.6
12.3
0.5
0.1
0.6
28.5
2000
27.1
10.0
3.2
1.6
11.8
0.5
0.1
0.6
27.8
2001
26.7
10.0
3.2
1.6
11.4
0.5
0.1
0.6
27.4
2002
26.1
9.9
3.2
1.6
10.9
0.5
0.1
0.6
26.8
2003
25.3
9.8
3.1
1.5
10.3
0.5
0.1
0.6
25.9
2004
25.0
9.8
3.0
1.5
10.2
0.5
0.1
0.6
25.7
Table 3-36: CH4 Emissions from Petroleum Systems (Gg)
Activity
Total
1990
1,640
1998
1999
2000
2001
2002
1,414
1,358 1,325
1,303
2003
1,274 1,236
2004
Production Field Operations
Pneumatic device venting
Tank Venting
Combustion & process
upsets
Misc. venting & fugitives
Wellhead fugitives
Crude Oil Transportation
Refining
1,609
545
179
88
771
26
7
25
1,381
504
162
80
610
25
6
27
1,326
488
154
76
584
24
6
27
1,292
478
154
76
562
22
5
28
1,271
475
154
75
545
22
5
27
1,242
473
151
75
520
23
5
27
1,203
466
150
73
492
22
5
27
1,188
464
143
73
486
23
5
28
1,222
3-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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emissions, almost entirely from floating roof tanks, account
for 18 percent. The remaining 16 percent is distributed among
four additional sources within these two categories.
Crude Oil Refining. Crude oil refining processes and
systems account for only slightly over two percent of total
CH4 emissions from the oil industry because most of the
CH4 in crude oil is removed or escapes before the crude oil
is delivered to the refineries. There is an insignificant amount
of CH4 in all refined products. Within refineries, vented
emissions account for about 87 percent of the emissions,
while fugitive and combustion emissions account for
approximately six and seven percent respectively. Refinery
system blowdowns for maintenance and the process of
asphalt blowing—with air, to harden the asphalt—are the
primary venting contributors. Most of the fugitive 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 from unburned
CH4 in engine exhausts and flares.
Methodology
The methodology for estimating CH4 emissions
from petroleum systems is a bottom-up approach, based
on comprehensive studies of CH4 emissions from U.S.
petroleum systems (EPA 1999, Radian 1996e). These studies
combined emission estimates from 64 activities occurring
in petroleum systems from the oil wellhead through crude
oil refining, including 33 activities for crude oil production
field operations, 11 for crude oil transportation activities,
and 20 for refining operations. Annex 3.5 provides greater
detail on the emission estimates for these 64 activities. The
estimates of CH4 emissions from petroleum systems do
not include emissions downstream of oil refineries because
these emissions are very small compared to CH4 emissions
upstream of oil refineries.
The methodology for estimating CH4 emissions from the
64 oil industry activities employs emission factors initially
developed by EPA (1999) and activity factors that are based
on EPA (1999) and Radian (1996e) studies. Emissions are
estimated for each activity by multiplying emission factors
(e.g., emission rate per equipment item or per activity) by
their corresponding activity factor (e.g., equipment count or
frequency of activity). The report provides emission factors
and activity factors for all activities except those related to
offshore oil production. For offshore oil production, two
emission factors were calculated using data collected over
a one-year period for all federal offshore platforms (MMS
2005c). One emission factor is for oil platforms in shallow
water, and one emission factor is for oil platforms in deep
water. Emission factors are held constant for the period 1990
through 2004. The number of platforms in shallow water and
the number of platforms in deep water are used as activity
factors and are taken from Minerals Management Service
statistics (MMS 2005a,b,d).
Activity factors for years 1990 through 2004 were
collected from a wide variety of statistical resources. For
some years, complete activity factor data were not available.
In such cases, one of three approaches was employed. Where
appropriate, the activity factor was calculated from related
statistics using ratios developed for Radian (1996e). For
example, Radian (1996e) found that the number of heater
treaters (a source of CH4 emissions) is related to both number
of producing wells and annual production. To estimate the
activity factor for heater treaters, reported statistics for wells
and production were used, along with the ratios developed
for Radian (1996e). In other cases, the activity factor was
held constant from 1990 through 2004 based on EPA (1999).
Lastly, the previous year's data were used when data for the
current year were unavailable. See Annex 3.5 for additional
detail.
Nearly all emission factors were taken from Radian
(1996e) and EPA (1995, 1999). The remaining emission
factors were taken from the following sources: EPA default
values, MMS reports (MMS 2005c), the Exploration and
Production (E&P) Tank model (DB Robinson Research Ltd.
1997), and the consensus of industry peer review panels.
Among the more important references used to obtain
activity factors are the Energy Information Administration
annual and monthly reports (EIA 1990-2004, 1995-2004,
1995-2005), the API Basic Petroleum Data Book (API 2004),
Methane Emissions from the Natural Gas Industryby the Gas
Research Institute and EPA (Radian 1996a-d,f), consensus
of industry peer review panels, MMS reports (MMS 2001,
2005a,b,d), the Oil & Gas Journal (OGJ 2004a-b) and the
United States Army Corps of Engineers (1995-2003).
Uncertainty
This section describes the analysis conducted to quantify
uncertainty associated with the estimates of emissions from
petroleum systems. Performed using @RISK software and
Energy 3-47
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the IPCC-recommended Tier 2 methodology (Monte Carlo
Simulation technique), the method employed provides for
the specification of probability density functions for key
variables within a computational structure that mirrors the
calculation of the inventory estimate. The results provide
the range within which, with 95 percent certainty, emissions
from this source category are likely to fall.
The detailed, bottom-up inventory analysis used to
evaluate U.S. petroleum systems reduces the uncertainty
related to the CH4 emission estimates in comparison with
a top-down approach. However, some uncertainty still
remains. Emission factors and activity factors are based on
a combination of measurements, equipment design data,
engineering calculations and studies, surveys of selected
facilities and statistical reporting. Statistical uncertainties
arise from natural variation in measurements, equipment
types, operational variability and survey and statistical
methodologies. Published activity factors are not available
every year for all 64 activities analyzed for petroleum
systems; therefore, some are estimated. Because of the
dominance of five major sources, which account for 86
percent of the total emissions, the uncertainty surrounding
these five sources has been estimated most rigorously, and
serves as the basis for determining the overall uncertainty
of petroleum systems emission estimates.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 3-37. Petroleum systems CH4
emissions in 2004 were estimated to be between 17.2 and
61.8 Tg C02 Eq. at a 95 percent confidence level (or in 19
out of 20 Monte Carlo Simulations). This indicates a range
of 33 percent below to 141 percent above the 2004 emission
estimate of 25.7 Tg C02 Eq.
Recalculations Discussion
Estimates of CH4 from petroleum systems contain one
major change with respect to previous inventories. In previous
years, offshore production emissions were calculated as eight
separate sources (2 categories of fugitives, 2 categories of
venting, 2 categories of combustion, and 2 categories of
process upsets) but new analysis of the 2000 GOADS report
(MMS 2005c) yields comprehensive emissions factors for
shallow water and deep water gas platforms. The shallow
water and deep water sources from the GOADS analysis
account for all offshore emissions and have replaced the
eight sources from previous inventories.
The combination of these changes resulted in an average
annual increase of 11.8 Tg C02 Eq. (63 percent) in CH4
emissions from petroleum systems for the period 1990
through 2003. Emissions from offshore oil platforms account
for the entire change in emissions.
Planned Improvements
Several improvements to the emission estimates are
being evaluated that fine-tune and better track changes
in emissions. These include, but are not limited to, some
activity factors that are also accounted for in the Natural
Gas STAR Program emission reductions, some emission
factors for consistency between emission estimates from
Petroleum Systems and Natural Gas Systems, and new data
from recent studies that bear on both emission factors and
activity factors. The growing body of data in the Natural Gas
STAR Program, coupled with an increasing number of oil
and gas companies doing internal greenhouse gas emissions
inventories, provides an opportunity to reevaluate emission
and activity factors, as well as the methodology currently
used to project emissions from the base year.
Changes in state regulations, new facility construction,
and activities of natural gas industry entities outside of
the Natural Gas STAR program can lead to alterations in
emissions profile that are not specifically accounted for in the
current emissions inventory. Research of publicly available
data sources will be conducted to develop a methodology for
Table 3-37: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems (Tg C02 Eq. and
Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Petroleum Systems CH4 25.7
17.2 61.8 -33% +141%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
3-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
adjusting emissions factors over the inventory time series to
account for these fluctuations.
3.8. Natural Gas Systems (IPCC
Source Category 1B2b)
The U.S. natural gas system encompasses hundreds
of thousands of wells, hundreds of processing facilities,
and over a million miles of transmission and distribution
pipelines. Overall, natural gas systems emitted 118.8 Tg C02
Eq. (5,658 Gg) of CH4 in 2004, a slight decrease over 1990
emissions (see Table 3-38 and Table 3-39). Improvements
in management practices and technology, along with the
replacement of older equipment, have helped to stabilize
emissions.
CH4 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 combusting
engines and turbine 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 emissions are discussed.
Field Production. In this initial stage, wells are used to
withdraw raw gas from underground formations. Emissions
arise from the wells themselves, gathering pipelines, and
well-site gas treatment facilities such as dehydrators and
separators. Fugitive emissions and emissions from pneumatic
devices account for the majority of emissions. Emissions
from field production accounted for approximately 33 percent
of CH4 emissions from natural gas systems in 2004.
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 emissions from compressors, including
compressor seals, are the primary emission source from this
stage. Processing plants account for about 12 percent of CH4
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
Table 3-38: CH4 Emissions from Natural Gas Systems (Tg C02 Eq.)4
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
34.0
14.8
46.8
31.0
126.7
1998
38.2
14.8
44.3
28.2
125.4
1999
35.3
14.7
43.1
28.7
121.7
2000
39.2
14.9
43.1
29.6
126.7
2001
42.3
15.0
39.6
28.7
125.6
2002
43.5
14.5
41.3
26.0
125.4
2003
42.1
14.5
41.2
26.9
124.7
2004
39.3
14.0
38.4
27.1
118.8
including CH4 emission reductions achieved by the Natural Gas STAR program.
Note: Totals may not sum due to independent rounding.
Table 3-39: CH4 Emissions from Natural Gas Systems (Gg)4
Stage
Field Production
Processing
Transmission and Storage
Distribution
Total
1990
1,621
706
2,230
1,477
6,034
1998
1,819
704
2,110
1,341
5,973
1999
1,679
698
2,051
1,369
5,797
2000
1,865
708
2,052
1,407
6,033
2001
2,014
716
1,884
1,367
5,981
2002
2,073
691
1,968
1,239
5,971
2003
2,007
688
1,963
1,281
5,939
2004
1,873
667
1,827
1,291
5,658
including CH4 emission reductions achieved by the Natural Gas STAR program.
Note: Totals may not sum due to independent rounding.
Energy 3-49
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compressors, are used to move the gas throughout the
United States transmission system. Fugitive 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 exhaust are also sources
of 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 32 percent of emissions
from natural gas systems.
Distribution. Distribution pipelines take the high-
pressure gas from the transmission system at "city gate"
stations, reduce the pressure and distribute the gas through
primarily underground mains and service lines to individual
end users. There were over 1,135,000 miles of distribution
mains in 2004, an increase from just over 944,000 miles in
1990 (OPS 2005b). Distribution system emissions, which
account for approximately 23 percent of emissions from
natural gas systems, result mainly from fugitive emissions
from gate stations and non-plastic piping (cast iron,
steel).48 An increased use of plastic piping, which has lower
emissions than other pipe materials, has reduced the growth
in emissions from this stage. Distribution system emissions
in 2004 were 13 percent lower than 1990 levels.
Methodology
The primary basis for estimates of CH4 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 100 emission and activity factors to
characterize emissions from the various components within
the operating stages of the U.S. natural gas system. The study
was based on a combination of process engineering studies
and measurements at representative gas facilities. From this
analysis, a 1992 emission estimate was developed using the
emission and activity factors. For otheryears, a set of industry
activity factor drivers was developed that can be used to
update activity factors. These drivers include statistics on
gas production, number of wells, system throughput, miles
of various kinds of pipe, and other statistics that characterize
the changes in the U.S. natural gas system infrastructure and
operations.
See Annex 3.4 for more detailed information on the
methodology and data used to calculate CH4 emissions from
natural gas systems.
Activity factor data were taken from the following
sources: American Gas Association (AGA 1991-1998);
American Petroleum Institute (API 2005); Minerals and
Management Service (MMS 2005a-e); Monthly Energy
Review (EIA 2005e); Natural Gas Liquids Reserves Report
(ElA 2004b); Natural Gas Monthly (EIA 2005c,d,f); the
Natural Gas STAR Program annual emissions savings (EPA
2005); Oil and Gas Journal (OGJ 1999-2005); Office of
Pipeline Safety (OPS 2005a-b) and other Energy Information
Administration publications (EIA 2004a, 2005a,b,g). Data
from a program for estimating emissions from hydrocarbon
production tanks is incorporated (DB Robinson Research
Ltd. 1997). Coalbed CH4 well activity factors were taken
from the Wyoming Oil and Gas Conservation Commission
(Wyoming 2005) and the Alabama State Oil and Gas Board
(Alabama 2005). Other state well data was taken from:
American Association of Petroleum Geologists (AAPG
2204); Brookhaven College (Brookhaven 2004); Kansas
Geological Survey (Kansas 2005); Montana Board of Oil and
Gas Conservation (Montana 2005); Oklahoma Geological
Survey (Oklahoma 2005); Morgan Stanley (Morgan Stanley
2005)Rocky Mountain Production Report (Lippman (2003);
New Mexico Oil Conservation Division (New Mexico
2005a,b); Texas Railroad Commission (Texas 2005a-c); Utah
Division of Oil, Gas and Mining (Utah 2005). Emissions
factors were taken from EPA/GRI (1996).
Uncertainty
An quantitative uncertainty analysis was conducted to
determine the level of uncertainty surrounding inventory
estimates of emissions from natural gas systems. Performed
using @RISK software and the IPCC-recommended Tier
2 methodology (Monte Carlo Simulation technique), this
analysis provides for the specification of probability density
48 The percentages of total emissions from each stage may not sum to 100 percent due to independent rounding.
3-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 3-40: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Natural Gas Systems
(Tg C02 Eq. and Percent)
2004 Emission
Source Gas Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Natural Gas Systems CH4 118.8
84.3 155.5 -29% +31%
! Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
functions for key variables within a computational structure
that mirrors the calculation of the inventory estimate. The
results presented below provide with 95 percent certainty
the range within which emissions from this source category
are likely to fall.
The heterogeneous nature of the natural gas industry
makes it difficult to sample facilities that are completely
representative of the entire industry. Because of this, scaling
up from model facilities introduces a degree of uncertainty.
Additionally, highly variable emission rates were measured
among many system components, making the calculated
average emission rates uncertain. The results of the Tier 2
quantitative uncertainty analysis are summarized in Table
3-40. Natural gas systems CH4 emissions in 2004 were
estimated to be between 84.3 and 155.5 Tg C02 Eq. at a 95
percent confidence level (or in 19 out of 20 Monte Carlo
Simulations). This indicates a range of 29 percent below to
31 percent above the 2004 emission estimate of 118.8 Tg
C02 Eq.
Recalculations Discussion
Significant changes were made to the emission
calculations in the Production sector. The first change was a
restructuring of sources to follow the EIA's National Energy
Modeling System (NEMS) regions for oil and gas production
in the United States. The EIA's NEMS groups oil and gas
production into six distinct regions: North East, Mid-Central,
Rocky Mountains, South West, West Coast, and Gulf Coast.
The first step in the restructuring of the emissions from the
production sector was to divide emissions from each source
into NEMS regions using equivalent emissions factors but
localized activity data. The net effect of this restructuring
on the historical emission estimates is negligible, but did
involve changes in the uncertainty estimate calculations.
Several large sources from the previous year's inventory
were broken down into smaller regional sources and a new
set of top-ten sources that represent a major portion of the
total emissions from the natural gas industry have been
chosen to calculate the uncertainty of the estimate. A future
step in the restructuring of the production sector emissions
estimates will be to develop specific region emissions and
activity factors.
Another change in this year's estimates is the
methodology for calculating offshore natural gas production
emissions. In previous years, offshore production emissions
were calculated as five separate sources (2 categories of
fugitives, venting, flaring, and emergency shut-downs),
but analysis of new data in the 2000 Gulf-wide Offshore
Air Data System (GOADS) report (MMS 2005c) yields
comprehensive emissions factors for shallow water and
deep water gas platforms. The shallow water and deep water
sources from the GOADS analysis account for all offshore
emissions and have replaced the five sources from previous
inventories.
Finally, the emission factor for plastic pipelines (used
in the distribution sector) was changed this year from the
previous 11.40 scf/hr to 5.85scf/hr based on additional data
points from the Southern California Gas Company (1991).
The new emission factor reflects plastic pipeline produced
before 1982; a lower emission factor of 0.99 scf/hr is
estimated for plastic pipeline produced after 1982. Because
activity data can not be appropriately disaggregated into
these two time frames, the pre-1982 value is used for all
years. If activity data become available to distinguish pre-
and post-1982 plastic pipeline the emission estimates will
be subsequently revised.
The combination of these methodological and historical
data changes resulted in an average annual decrease of 4.5
Tg C02 Eq. (3 percent) in CH4 emissions from natural gas
systems for the period 1990 through 2003.
Energy 3-51
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Planned Improvements
Several improvements to the emission estimates are
being evaluated that fine-tune and better track changes
in emissions. These include, but are not limited to, some
activity factors that are also accounted for in the Natural
Gas STAR Program emission reductions, some emission
factors for consistency between emission estimates from
the Petroleum Systems and Natural Gas Systems source
categories, and new data from recent studies that bear on
both emission factors and activity factors. The growing
body of data in the Natural Gas STAR Program, coupled
with an increasing number of oil and gas companies doing
internal greenhouse gas emissions inventories, provides an
opportunity to reevaluate emission and activity factors, as
well as the methodology currently used to project emissions
from the base year.
Changes in state regulations, new facility construction,
and activities of natural gas industry entities outside of
the Natural Gas STAR program can lead to fluctuations
in emissions that are not specifically accounted for in the
current emissions inventory. Research of publicly available
data sources will be conducted to develop a methodology for
adjusting emissions factors over the inventory time series to
account for these fluctuations.
Improvements to emissions and activity factors in the
NEMS production regions will be a major focus in upcoming
inventories. This second step in the restructuring of the
production sector estimates requires the development of
unique regional factors to reflect the differences in the natural
gas industries' operations throughout the United States.
3.9. Municipal Solid Waste
Combustion (IPCC Source Category
1A5)
Combustion is used to manage about 7 to 17 percent
of the municipal solid wastes (MSW) generated in the
United States, depending on the source of the estimate and
the scope of materials included in the definition of solid
waste (EPA ZOOOc, Goldstein and Matdes 2001, Kaufman
et al. 2004). Almost all combustion of municipal solid
wastes in the United States occurs at waste-to-energy
facilities where energy is recovered, and thus emissions
from waste combustion are accounted for in the Energy
chapter. Combustion of municipal solid wastes results in
conversion of the organic inputs to C02. According to the
IPCC Guidelines, when the C02 emitted is of fossil origin,
Table 3-41: C02 and N20 Emissions from Municipal Solid Waste Combustion (Tg C02 Eq.)
Gas/Waste Product
C02
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
Synthetic Rubber in MSW
Synthetic Fibers
N20
Total
1990
10.9
8.0
0.2
0.2
1.3
1.2
0.5
11.4
1998
17.1
11.4
0.9
1.2
1.6
2.0
0.4
17.5
1999
17.6
12.0
0.9
1.2
1.6
2.0
0.4
18.0
2000
17.9
12.1
0.9
1.2
1.7
2.1
0.4
18.3
2001
18.6
12.6
0.9
1.2
1.8
2.2
0.5
19.1
2002
18.9
12.6
1.0
1.2
1.8
2.2
0.5
19.4
2003
19.4
12.9
1.0
1.3
1.8
2.3
0.5
19.9
2004
19.4
12.9
1.0
1.3
1.8
2.3
0.5
19.9
Table 3-42: C02 and N20 Emissions from Municipal Solid Waste Combustion (Gg)
Gas/Waste Product
C02
Plastics
Synthetic Rubber in Tires
Carbon Black in Tires
Synthetic Rubber in MSW
Synthetic Fibers
N20
1990
10,919
7,953
191
249
1,330
1,196
2
1998
17,094
11,427
887
1,160
1,627
1,992
1
1999
17,632
11,950
890
1,164
1,612
2,016
1
2000
17,921
12,095
893
1,167
1,682
2,085
1
2001
18,634
12,599
895
1,170
1,793
2,177
1
2002
18,862
12,630
952
1,245
1,804
2,231
2
2003
19,360
12,885
1,010
1,320
1,848
2,298
2
2004
19,360
12,885
1,010
1,320
1,848
2,298
2
3-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 3-43: NO,, CO, and NMVOC Emissions from Municipal Solid Waste Combustion (Gg)
Gas/Source 1990 1998
NOX 82 145
Waste Incineration 44 49
Open Burning 38 96
CO 978 2,826
Waste Incineration 337 69
Open Burning 641 2,757
NMVOCs 222 326
Waste Incineration 44 23
Open Burning 178 303
Note: Totals may not sum due to independent rounding.
it is counted as a net anthropogenic emission of C02 to the
atmosphere. Thus, the emissions from waste combustion are
calculated by estimating the quantity of waste combusted
and the fraction of the waste that is carbon 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 carbon flows accounted for under the Land Use,
Land-Use Change, and Forestry chapter. However, some
components— plastics, synthetic rubber, synthetic fibers, and
carbon black — are of fossil origin. Plastics in the U.S. waste
stream are primarily in the form of containers, packaging,
and durable goods. Rubber is found in durable goods, such
as carpets, and in non-durable goods, such as clothing and
footwear. Fibers in municipal solid wastes are predominantly
from clothing and home furnishings. Tires (which contain
rubber and carbon black) are also considered a "non-
hazardous" waste and are included in the municipal solid
waste combustion estimate, though waste disposal practices
for tires differ from the rest of municipal solid waste.
Approximately 30 million metric tons of municipal solid
wastes were combusted in the United States in 2003 (see
Table 3-46). C02 emissions from combustion of municipal
solid wastes rose 78 percent since 1990, to an estimated
19.4 Tg C02 Eq. (19,360 Gg) in 2004, as the volume of
plastics and other fossil carbon-containing materials in MSW
increased (see Table 3-41 and Table 3-42). Waste combustion
is also a source of N20 emissions (De Soete 1993). N20
emissions from municipal solid waste combustion were
estimated to be 0.5 Tg C02 Eq. (1 Gg) in 2004, and have
not changed significantly since 1990.
Indirect greenhouse gases are also emitted during waste
incineration and open burning, as shown in Table 3-43. These
1999 2000 2001 2002 2003 2004
143 114 114 134 134 134
48 38 38 45 45 45
95 76 76 89 89 89
2,725 1,670 1,672 1,672 1,672 1,672
66 40 41 41 41 41
2,659 1,630 1,631 1,631 1,631 1,631
302 257 258 281 282 282
19 15 16 18 18 18
284 242 242 264 264 264
emissions are a relatively small portion of the overall indirect
greenhouse gas emissions, comprising less than 5 percent for
each gas over the entire time series.
Methodology
Emissions of C02 from MSW combustion include C02
generated by the combustion of plastics, synthetic fibers, and
synthetic rubber, as well as the combustion of synthetic rubber
and carbon black in tires. These emissions were calculated
by multiplying the amount of each material combusted by
the carbon content of the material and the fraction oxidized
(98 percent). Plastics combusted in municipal solid wastes
were categorized into seven plastic resin types, each material
having a discrete carbon content. Similarly, synthetic rubber is
categorized into three product types, and synthetic fibers were
categorized into four product types, each having a discrete
Table 3-44: Municipal Solid Waste Generation (Metric
Tons) and Percent Combusted
Year Waste Generation Combusted (%)
1990 266,365,714 11.5
1991 254,628,360 10.0
1992 264,668,342 11.0
1993 278,388,835 10.0
1994 292,915,829 10.0
1995 296,390,405 10.0
1996 297,071,712 10.0
1997 308,870,755 9.0
1998 339,865,243 7.5
1999 347,089,277 7.0
2000 371,071,109 7.0
2001 404,002,786a 7.4a
2002 436,934,464 7.7
2003 436,934,464" 7.7"
2004 436,934,464" 7.7"
a Interpolated between 2000 and 2002 values.
Assumed equal to 2002 value.
Energy 3-53
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carbon content. Scrap tires contain several types of synthetic
rubber, as well as carbon black. Each type of synthetic rubber
has a discrete carbon content, and carbon black is 100 percent
carbon. Emissions of C02 were calculated based on the number
of scrap tires used for fuel and the synthetic rubber and carbon
black content of the tires.
More detail on the methodology for calculating
emissions from each of these waste combustion sources is
provided in Annex 3.6.
For each of the methods used to calculate C02 emissions
from municipal solid waste combustion, data on the quantity
of product combusted and the carbon content of the product
are needed. For plastics, synthetic rubber, and synthetic
fibers, the amount of material in municipal solid wastes and
its portion combusted were taken from the Characterization
of Municipal Solid Waste in the United States (EPA ZOOOc,
2002a, 2003, 2005a). For synthetic rubber and carbon black
in scrap tires, this information was provided by the U.S. Scrap
Tire Markets 2003 (RMA 2004) and Scrap Tires, Facts and
Figures (STMC 2000, 2001, 2002, 2003, 2004). Data were
not available for 2004, so the values were assumed to equal
the value for 2003.
Average carbon contents for the "Other" plastics
category, synthetic rubber in municipal solid wastes, and
synthetic fibers were calculated from 1998 production
statistics, which divide their respective markets by chemical
compound. For synthetic rubber in scrap tires information
about scrap tire composition was taken from the Scrap Tire
Management Council's internet site (STMC 2003).
The assumption that 98 percent of organic carbon
is oxidized (which applies to all municipal solid waste
combustion categories for C02 emissions) was reported in
the EPA's life cycle analysis of greenhouse gas emissions and
sinks from management of solid waste (EPA 2002b).
Combustion of municipal solid waste also results in
emissions of N20. These emissions were calculated as a
function of the total estimated mass of municipal solid
waste combusted and an emission factor. The N20 emission
estimates are based on different data sources. As noted above,
N20 emissions are a function of total waste combusted in
each year; for 1990 through 2003, these data were derived
from the information published in BioCycle (Kaufman et al
2004). As for the activity data for C02 emissions, data on total
waste combusted was not available for 2004, so the value
for this year was assumed to equal the most recent value
available (2003). Table 3-44 provides data on municipal
solid waste generation and percentage combustion for the
total waste stream. The emission factor of N20 emissions per
quantity of municipal solid waste combusted is an average of
values from IPCC's Good Practice Guidance (2000).
EPA (2005b) provided emission estimates for NOX, CO,
and NMVOCs from waste incineration and open burning,
which were determined using industry published production
data and applying average emission factors.
Uncertainty
ATier 2 Monte Carlo analysis was performed to determine
the level of uncertainty surrounding the estimates of C02
emissions and N20 emissions from municipal solid waste
combustion. IPCC Tier 2 analysis allows the specification
of probability density functions for key variables within a
computational structure that mirrors the calculation of the
inventory estimate. Uncertainty estimates and distributions
for waste generation variables (i.e., plastics, synthetic
rubber, and textiles generation) were obtained through a
conversation with one of the authors of the Municipal Solid
Waste in the United States reports. Statistical analyses or
expert judgments of uncertainty were not available directly
from the information sources for the other variables; thus,
Table 3-45: Tier 2 Quantitative Uncertainty Estimates for C02 and N20 from Municipal Solid Waste Combustion (Tg
C02 Eq. and Percent)
Source
2004 Emission
Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Municipal Solid Waste Combustion C02 19.4
Municipal Solid Waste Combustion N20 0.5
16.4
0.1
21.1
1.3
-15%
-73%
+ 10%
+ 157%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
3-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 3-46: U.S. Municipal Solid Waste Combusted, as
Reported by EPA and BioCycle (Metric Tons)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
EPA
28,855,809
27,773,783
29,568,442
28,696,188
29,532,844
32,182,194
32,831,450
33,597,844
31,205,358
30,859,134
30,571,624
30,416,919
30,340,252
29,995,479
NA
BioCycle
30,632,057
25,462,836
29,113,518
27,838,884
29,291,583
29,639,040
29,707,171
27,798,368
25,489,893
24,296,249
25,974,978
29,694,205="
33,643,954
NA
NA
NA (Not Available)
a Interpolated between 2000 and 2002 values.
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 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, carbon content of carbon black).
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 3-45. Municipal solid
waste combustion C02 emissions in 2004 were estimated
to be between 16.36 and 21.11 Tg C02 Eq. at a 95 percent
confidence level (or in 19 out of 20 Monte Carlo Simulations).
This indicates a range of 15 percent below to 9 percent above
the 2004 emission estimate of 19.36 Tg C02 Eq. Also at a 95
percent confidence level, municipal solid waste combustion
N20 emissions in 2004 were estimated to be between 0.14
and 1.34 Tg C02 Eq. This indicates a range of 73 percent
below to 157 percent above the 2004 emission estimate of
0.52 Tg C02 Eq.
The uncertainties in the waste combustion emission
estimates arise from both the assumptions applied to the data
and from the quality of the data.
• MSWCombustion Rate. A source of uncertainty affecting
both fossil C02 and N20 emissions is the estimate of
the MSW combustion rate. The EPA (2000c, 2002a,
2003) estimates of materials generated, discarded, and
combusted carry considerable uncertainty associated
with the material flows methodology used to generate
them. Similarly, the BioCycle (Glenn 1999, Goldstein
and Matdes 2000, Goldstein and Matdes 2001, Kaufman
et al. 2004) estimate of total waste combustion—used
for the N20 emissions estimate—is based on a survey
of state officials, who use differing definitions of solid
waste and who draw from a variety of sources of varying
reliability and accuracy. The survey methodology
changed significantly and thus the results reported for
2002 are not directly comparable to the earlier results
(Kaufman et al. 2004), introducing further uncertainty.
Despite the differences in methodology and data
sources, the two references—the EPA's Office of Solid
Waste (EPA 2000a, 2002b, 2003) and the BioCycle
series—provide estimates of total solid waste combusted
that are relatively consistent (see Table 3-46).
Fraction Oxidized. Another source of uncertainty
for the C02 emissions estimate is fraction oxidized.
Municipal waste combustors vary considerably in their
efficiency as a function of waste type, moisture content,
combustion conditions, and other factors. Despite this
variability in oxidation rates, a value of 98 percent was
assumed for this analysis.
Missing Data on Municipal Solid Waste Composition.
Disposal rates have been interpolated when there is an
incomplete interval within a time series. Where data are
not available for years at the end of a time series (1990,
2004), they are set equal to the most recent years for
which estimates are available.
Average Carbon Contents. Average carbon contents
were applied to the mass of "Other" plastics combusted,
synthetic rubber in tires and municipal solid waste,
and synthetic fibers. These average values were
estimated from the average carbon content of the known
products recently produced. The true carbon content
of the combusted waste may differ from this estimate
depending on differences in the chemical formulation
between the known and unspecified materials, and
differences between the composition of the material
disposed and that produced. For rubber, this uncertainty
is probably small since the major elastomers' carbon
contents range from 77 to 91 percent; for plastics, where
carbon contents range from 29 to 92 percent, it may
Energy 3-55
-------
be more significant. Overall, this is a small source of
uncertainty.
• Synthetic/Biogenic Assumptions. A portion of the fiber
and rubber in municipal solid waste is biogenic in
origin. Assumptions have been made concerning the
allocation between synthetic and biogenic materials
based primarily on expert judgment.
• Combustion Conditions Affecting N2O Emissions.
Because insufficient data exist to provide detailed
estimates of N20 emissions for individual combustion
facilities, the estimates presented exhibit high uncertainty.
The emission factor for N20 from municipal solid waste
combustion facilities used in the analysis is an average
of default values used to estimate N20 emissions from
facilities worldwide (Johnke 1999, UK: Environment
Agency 1999, Yasuda 1993). These factors span an order
of magnitude, reflecting considerable variability in the
processes from site to site. Due to a lack of information
on the control of N20 emissions from MSW combustion
facilities in the United States, the estimate of zero
percent for N2O emissions control removal efficiency
also exhibits uncertainty.
Recalculations Discussion
Historical waste combustion activity data were modified
according to the updated Characterization of Municipal
Solid Waste in the United States (EPA 2005a) report, which
affected estimates for C02 emissions in previous inventory
years. Additionally, historical estimates for N20 emissions
from waste combustion increased slightly due to an updated
emissions factor. Overall, changes resulted in an average
annual increase in C02 emissions from waste combustion
of less than 0.05 Tg C02 Eq. (0.2 percent) for the period
1990 through 2003, and an average annual increase in
N20 emissions of 0.1 Tg C02 Eq. (14 percent) over the
same period.
3.10. Natural Gas Flaring and
Indirect Greenhouse Gas Emissions
from Oil and Gas Activities (IPCC
Source Category 1B2)
The flaring of natural gas from on- and off-shore oil
wells is a small source of C02. In addition, oil and gas
activities also release small amounts of NOX, CO, and
NMVOCs. This source accounts for only a small proportion
of overall emissions of each of these gases. Emissions of
NOX, and CO from petroleum and natural gas production
activities were both less than 1 percent of national totals,
while NMVOC and S02 emissions were roughly 2 percent
of national totals.
The flaring (i.e., combustion) and venting of natural
gas during petroleum production result in the release of
C02 and CH4 emissions, respectively. Barns and Edmonds
(1990) noted that of total reported U.S. venting and flaring,
approximately 20 percent may be vented, with the remaining
80 percent flared, but it is now believed that flaring accounts
for an even greater proportion. Studies indicate that the
Table 3-47: C02 Emissions from On-Shore and Off-Shore Natural Gas Flaring (Tg C02 Eq.)
Location
On-Shore Flaring
Off-Shore Flaring
Total Flaring
1990
5.5
0.3
5.8
1998
6.3
0.3
6.6
1999
6.7
0.3
6.9
2000
5.5
0.2
5.8
2001
5.9
0.2
6.1
2002
6.0
0.2
6.2
2003
5.9
0.2
6.1
2004
5.9
0.2
6.0
Note: Totals may not sum due to independent rounding.
Table 3-48: C02 Emissions from On-Shore and Off-Shore Natural Gas Flaring (Gg)
Location
1990
1998
1999
2000
2001
2002
2003
2004
On-Shore Flaring
Off-Shore Flaring
5,509
296
6,250
316
6,679
264
5,525
244
5,858
236
6,001
203
5,936
155
5,872
162
Total Flaring
5,805
6,566
6,943
5,769
6,094
6,204
6,091
6,034
Note: Totals may not sum due to independent rounding.
3-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 3-49: NOX, NMVOCs, and CO Emissions from Oil
and Gas Activities (Gg)
Methodology
Year
1990
1998
1999
2000
2001
2002
2003
2004
N08
139
130
109
111
113
135
135
135
CO
302
332
145
146
147
116
116
116
NMVOCs
555
440
414
389
400
340
341
341
percentage of natural gas that is flared from off-shore
U.S. production is considerably lower (approximately 30
percent in 2003), due in part to differences in the legislation
governing on- and off-shore natural gas production. CH4
emissions from venting are accounted for in the Petroleum
Systems source category. For 2004, total C02 emissions from
flaring activities were estimated to be 6.0 Tg CO2 Eq. (6,034
Gg), an increase of 4 percent from 1990 levels. On-shore
flaring activities accounted for 5.9 Tg CO2 Eq. (5,872 Gg),
or 97 percent, of the total flaring emissions, while off-shore
flaring constituted 0.2 Tg CO2 Eq. (162 Gg), or 3 percent,
of the total (see Table 3-47).
In addition, oil and gas activities, including production,
transportation, and storage, result in the release of small
amounts of NOX, CO, and NMVOCs. Indirect greenhouse gas
emissions from this source from 1990 to 2004 are presented
below (see Table 3-49).
Estimates of C02 emissions from on- and off-shore
natural gas flaring were prepared using an emission factor of
54.71 Tg C02 Eq./QBtu of flared gas, and an assumed flaring
efficiency of 100 percent. Indirect greenhouse gas emission
estimates for NOX, CO, and NMVOCs were determined using
industry-published production data and applying average
emission factors.
Total on-shore natural gas vented and flared was taken
from EIA's Natural Gas Annual (EIA 2004); however,
there is a discrepancy in the time series. One facility in
Wyoming had been incorrectly reporting C02 vented as
CH4. EIA noted and corrected these data in the Natural Gas
Annual 2000 (EIA 2001) for the years 1998 and 1999 only.
Data for 1990 through 1997 were adjusted by assuming a
proportionate share of C02 in the flare gas for those years
as for 1998 and 1999. The adjusted values are provided in
Table 3-50. It was assumed that all reported vented and
flared gas was flared. This assumption is consistent with that
used by EIA in preparing their emission estimates, under
the assumption that many states require flaring of natural
gas (EIA 2000b). The emission and thermal conversion
factors were also provided by EIA (2001) and are included
in Table 3-50.
The total off-shore natural gas vented and flared was
obtained from the Minerals Management Service's OGOR-B
reports (MMS 2004). The percentage of natural gas flared
was estimated using data from a 1993 air quality study
Table 3-50: Total Natural Gas Reported Vented and Flared (Million Ft3) and Thermal Conversion Factor (Btu/Ft3)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Vented and Flared (original)
150,415
169,909
167,519
226,743
228,336
283,739
272,117
256,351
103,019
110,285
91,232
96,913
99,178
98,113
97,047
Vented and Flared (revised)*
91,130
92,207
83,363
108,238
109,493
144,265
135,709
124,918
103,019
110,285
91,232
96,913
99,178
98,113
97,047
Thermal Conversion Factor
1,105
1,108
1,110
1,106
1,105
1,106
1,109
1,107
1,109
1,107
1,107
1,105
1,106
1,106
1,106
* Wyoming venting and flaring estimates were revised. See text for further explanation.
Energy 3-57
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Table 3-51: Volume Flared Offshore (MMcf) and Fraction Vented and Flared (Percent)
Natural Gas Flaring
Total Gulf of Mexico (GOM) Vented
& Flared (MMcf)
Estimated Flaring Fraction of GOM
Vented & Flared
Total
1990
13
4
,610
36%
,900
1998
16
5
,280
32%
,210
1999
14,057
31%
4,358
2000
12
4
,971
31%
,021
2001
12,990
30%
3,897
2002
12,412
27%
3,351
2003
10,646
24%
2,555
2004
10,296
26%
2,677
and emissions inventory of the Gulf of Mexico (MOADS)
and a 2000 emissions inventory conducted for the Breton
National Wilderness Area Management Plan (BOADS).
See Table 3-51.
Emission estimates for NOX, CO, and NMVOCs from
petroleum refining, petroleum product storage and transfer,
and petroleum marketing operations were obtained from
preliminary data (EPA 2003), which, in its final iteration, will
be published on the National Emission Inventory (NEI) Air
Pollutant Emission Trends web site. Included are gasoline,
crude oil and distillate fuel oil storage and transfer operations,
gasoline bulk terminal and bulk plants operations, and retail
gasoline service stations operations.
Uncertainty
No quantitative uncertainty analysis was conducted to
determine the level of uncertainty associated with emissions
from natural gas flaring.
Uncertainties in C02 emission estimates primarily arise
from assumptions concerning the flaring efficiency and the
correction factor applied to 1990 through 1997 venting
and flaring data. Uncertainties in indirect greenhouse gas
emission estimates are partly due to the accuracy of the
emission factors used and projections of growth.
Recalculations Discussion
The historical data for natural gas flaring was adjusted
slightly, which resulted in an average annual decrease in C02
emissions from flaring of less than 0.05 Tg (0.1 percent) for
the period 1990 through 2003.
3.11. International Bunker Fuels (IPCC
Source Category 1: Memo Items)
Emissions resulting from the combustion of fuels used
for international transport activities, termed international
bunker fuels under the UNFCCC, are currently not included
in national emission totals, but are reported separately
based upon location of fuel sales. The decision to report
emissions from international bunker fuels separately, instead
of allocating them to a particular country, was made by the
Intergovernmental Negotiating Committee in establishing
the Framework Convention on Climate Change.49 These
decisions are reflected in the Revised 1996 IPCC Guidelines,
in which countries are requested to report emissions from
ships or aircraft that depart from their ports with fuel
purchased within national boundaries and are engaged in
international transport separately from national totals (IPCC/
UNEP/OECD/IEA1997).50
Greenhouse gases emitted from the combustion of
international bunker fuels, like other fossil fuels, include
C02, CH4, N20, CO, NOX, NMVOCs, particulate matter,
and S02.51 Two transport modes are addressed under the
IPCC definition of international bunker fuels: aviation and
marine.52 Emissions from ground transport activities—by
road vehicles and trains—even when crossing international
49 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).
5(1 Note that the definition of international bunker fuels used by the UNFCCC differs from that used by the International Civil Aviation Organization.
51 Sulfur dioxide emissions from jet aircraft and marine vessels, although not estimated here, are mainly determined by the sulfur content of the fuel. In
the United States, jet fuel, distillate diesel fuel, and residual fuel oil average sulfur contents of 0.05, 0.3, and 2.3 percent, respectively. These percentages
are generally lower than global averages.
52 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).
3-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
borders are allocated to the country where the fuel was
loaded into the vehicle and, therefore, are not counted as
bunker fuel emissions.
The IPCC Guidelines distinguish between different
modes of air traffic. Civil aviation comprises aircraft used
for the commercial transport of passengers and freight,
military aviation comprises aircraft under the control
of national armed forces, and general aviation applies
to recreational and small corporate aircraft. The IPCC
Guidelines further define international bunker fuel use
from civil aviation as the fuel combusted for civil (e.g.,
commercial) aviation purposes by aircraft arriving or
departing on international flight segments. However, as
mentioned above, and in keeping with the IPCC Guidelines,
only the fuel purchased in the United States and used by
aircraft taking-off (i.e., departing) from the United States
are reported here. The standard fuel used for civil aviation
is kerosene-type jet fuel, while the typical fuel used for
general aviation is aviation gasoline.53
Emissions of C02 from aircraft are essentially a
function of fuel use. CH4, N20, CO, NOX, and NMVOC
emissions also depend upon engine characteristics, flight
conditions, and flight phase (i.e., take-off, climb, cruise,
decent, and landing). CH4, CO, and NMVOCs are the
product of incomplete combustion and occur mainly during
the landing and take-off phases. In jet engines, N20 and
NOX are primarily produced by the oxidation of atmospheric
nitrogen, and the majority of emissions occur during the
cruise phase. The impact of NOX on atmospheric chemistry
depends on the altitude of the actual emission. The cruising
altitude of supersonic aircraft, near or in the ozone layer, is
higher than that of subsonic aircraft. At this higher altitude,
NOX emissions contribute to stratospheric ozone depletion.54
At the cruising altitudes of subsonic aircraft, however, NOX
emissions contribute to the formation of tropospheric ozone.
At these lower altitudes, the positive radiative forcing effect
of ozone has enhanced the anthropogenic greenhouse gas
forcing.55 The vast majority of aircraft NOX emissions occur
at these lower cruising altitudes of commercial subsonic
aircraft (NASA 1996).56
International marine bunkers comprise emissions
from fuels burned by ocean-going ships of all flags that
are engaged in international transport. Ocean-going ships
are generally classified as cargo and passenger carrying,
military (i.e., Navy), fishing, and miscellaneous support
ships (e.g., tugboats). For the purpose of estimating
greenhouse gas emissions, international bunker fuels are
solely related to cargo and passenger carrying vessels,
which is the largest of the four categories, and military
vessels. Two main types of fuels are used on sea-going
vessels: distillate diesel fuel and residual fuel oil. C02 is
the primary greenhouse gas emitted from marine shipping.
Table 3-52: C02, CH4, and N20 Emissions from International Bunker Fuels (Tg C02 Eq.)
Gas/Mode
C02
Aviation
Marine
CH4
Aviation
Marine
N20
Aviation
Marine
Total
1990
113.5
46.2
67.3
0.2
+
0.1
1.0
0.5
0.5
114.6
1998
114.6
56.7
57.9
0.2
+
0.1
1.0
0.6
0.4
115.7
1999
105.2
58.8
46.4
0.1
+
0.1
0.9
0.6
0.4
106.3
2000
101.4
60.5
40.9
0.1
+
0.1
0.9
0.6
0.3
102.4
2001
97.8
59.3
38.5
0.1
+
0.1
0.9
0.6
0.3
98.8
2002
89.5
61.8
27.7
0.1
+
0.1
0.8
0.6
0.2
90.4
2003
84.1
59.4
24.6
0.1
+
0.1
0.8
0.6
0.2
84.9
2004
94.5
59.9
34.6
0.1
+
0.1
0.9
0.6
0.3
95.5
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
53 Naphtha-type jet fuel was used in the past by the military in turbojet and turboprop aircraft engines.
54 Currently, only military supersonic aircraft fly at these altitudes.
55 However, at this lower altitude, ozone does little to shield the earth from ultraviolet radiation.
56 Cruise altitudes for civilian subsonic aircraft generally range from 8.2 to 12.5 km (27,000 to 41,000 feet).
Energy 3-59
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Table 3-53: C02, CH4, N20, and Indirect Greenhouse Gas Emissions from International Bunker Fuels (Gg)
Gas/Mode
C02
Aviation
Marine
CH4
Aviation
Marine
N20
Aviation
Marine
CO
Aviation
Marine
NO,
Aviation
Marine
NMVOCs
Aviation
Marine
1990
113,503
46,230
67,272
8
1
7
3
1
2
115
76
39
1,985
182
1,803
59
11
48
1998
114,557
56,657
57,900
7
2
6
3
2
1
127
93
34
1,778
224
1,554
55
14
41
1999
105,228
58,799
46,429
6
2
5
3
2
1
124
97
27
1,478
233
1,245
48
15
33
2000
101,366
60,507
40,859
6
2
4
3
2
1
124
100
24
1,334
240
1,095
44
15
29
2001
97,815
59,337
38,477
5
2
4
3
2
1
120
98
23
1,266
235
1,031
42
15
27
2002
89,489
61,787
27,701
4
2
3
3
2
1
118
102
16
988
245
743
35
15
20
2003
84,083
59,448
24,635
4
2
2
2
2
1
112
98
15
900
236
664
32
15
18
2004
94,499
59,912
34,587
5
2
3
3
2
1
119
99
20
1,167
237
930
40
15
25
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
Table 3-54: Aviation Jet Fuel Consumption for International Transport (Million Gallons)
Nationality
U.S. Carriers
Foreign Carriers
U.S. Military
Total
1990
1,954
2,051
862
4,867
1998
2,462
3,009
502
5,973
1999
2,625
3,086
488
6,199
2000
2,737
3,162
480
6,380
2001
2,619
3,113
524
6,255
2002
2,495
3,537
482
6,515
2003
2,418
3,377
473
6,268
2004
2,465
3,353
498
6,316
Note: Totals may not sum due to independent rounding.
In comparison to aviation, the atmospheric impacts of NOX
from shipping are relatively minor, as the emissions occur
at ground level.
Overall, aggregate greenhouse gas emissions in 2004
from the combustion of international bunker fuels from
both aviation and marine activities were 95.5 Tg C02 Eq.,
or 17 percent below emissions in 1990 (see Table 3-52).
Although emissions from international flights departing
from the United States have increased significantly (30
percent), emissions from international shipping voyages
departing the United States have decreased by 49 percent
since 1990. The majority of these emissions were in the
form of C02; however, small amounts of CH4 and N20
were also emitted. Emissions of NOX by aircraft during idle,
take-off, landing and at cruising altitudes are of primary
concern because of their effects on ground-level ozone
formation (see Table 3-53).
Methodology
Emissions of C02 were estimated by applying of carbon
content and fraction oxidized factors to fuel consumption
activity data. This approach is analogous to that described
under C02 from Fossil Fuel Combustion. Carbon content
and fraction oxidized factors for jet fuel, distillate fuel oil,
and residual fuel oil were taken directly from the EIA and
are presented in Annex 2.1, Annex 2.2, and Annex 3.7 of this
Inventory. Heat content and density conversions were taken
from EIA (2005) andUSAF (1998). A complete description of
the methodology and a listing of the various factors employed
can be found in Annex 2.1. See Annex 3.7 for a specific
discussion on the methodology used for estimating emissions
from international bunker fuel use by the U.S. military.
Emission estimates for CH4, N20, CO, NOX, and
NMVOCs were calculated by multiplying emission factors
by measures of fuel consumption by fuel type and mode.
3-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 3-55: 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
1998
3,974
627
518
5,119
1999
3,272
308
511
4,091
2000
2,967
290
329
3,586
2001
2,846
204
318
3,368
2002
1,937
158
348
2,443
2003
1,597
137
459
2,193
2004
2,363
167
530
3,059
Note: Totals may not sum due to independent rounding.
Emission factors used in the calculations of CH4, N20, CO,
NOX, and NMVOC emissions were obtained from the Revised
1996IPCC Guidelines QPCC/WEP/OECDflEA 1997). For
aircraft emissions, the following values, in units of grams
of pollutant per kilogram of fuel consumed (g/kg), were
employed: 0.09 for CH4, 0.1 for N20, 5.2 for CO, 12.5 for
NOX, and 0.78 for NMVOCs. For marine vessels consuming
either distillate diesel or residual fuel oil the following values,
in the same units, except where noted, were employed: 0.32
for CH4, 0.08 for N20, 1.9 for CO, 87 for NOX, and 0.052
g/MJ for NMVOCs. Activity data for aviation included
solely jet fuel consumption statistics, while the marine mode
included both distillate diesel and residual fuel oil.
Activity data on aircraft fuel consumption were collected
from three government agencies. Jet fuel consumed by U.S.
flag air carriers for international flight segments was supplied
by the Bureau of Transportation Statistics (DOT 1991 through
2005). It was assumed that 50 percent of the fuel used by U.S.
flagged carriers for international flights—both departing and
arriving in the United States—was purchased domestically
for flights departing from the United States. In other words,
only one-half of the total annual fuel consumption estimate
was used in the calculations. Data on jet fuel expenditures
by foreign flagged carriers departing U.S. airports was taken
from unpublished data collected by the Bureau of Economic
Analysis (BEA) under the U.S. Department of Commerce
(BEA 1991 through 2005). Approximate average fuel prices
paid by air carriers for aircraft on international flights was
taken from DOT (1991 through 2005) and used to convert
the BEA expenditure data to gallons of fuel consumed. Data
on U.S. Department of Defense (DoD) aviation bunker fuels
and total jet fuel consumed by the U.S. military was supplied
by the Office of the Under Secretary of Defense (Installations
and Environment), DoD. Estimates of the percentage of each
Services' 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 2004). 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 3-54.
See Annex 3.7 for additional discussion of military data.
Activity data on distillate diesel and residual fuel oil
consumption by cargo or passenger carrying marine vessels
departing from U.S. ports were taken from unpublished
data collected by the Foreign Trade Division of the U.S.
Department of Commerce's Bureau of the Census (DOC
1991 through 2005). Activity data on distillate diesel
consumption by military vessels departing from U.S. ports
were provided by DESC (2004). 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 3-55.
Uncertainty
Emission estimates related to the consumption
of international bunker fuels are subject to the same
uncertainties as those from domestic aviation and marine
mobile combustion emissions; however, additional
uncertainties result from the difficulty in collecting accurate
fuel consumption activity data for international transport
activities separate from domestic transport activities.57
57 See uncertainty discussions under Carbon Dioxide Emissions from Fossil Fuel Combustion.
Energy 3-61
-------
For example, smaller aircraft on shorter routes often carry
sufficient fuel to complete several flight segments without
refueling in order to minimize time spent at the airport gate or
take advantage of lower fuel prices at particular airports. This
practice, called tankering, when done on international flights,
complicates the use of fuel sales data for estimating bunker
fuel emissions. Tankering is less common with the type of
large, long-range aircraft that make many international flights
from the United States, however. Similar practices occur in
the marine shipping industry where fuel costs represent a
significant portion of overall operating costs and fuel prices
vary from port to port, leading to some tankering from ports
with low fuel costs.
Particularly for aviation, the DOT (1991 through
2005) international flight segment fuel data used for U.S.
flagged carriers does not include smaller air carriers and
unfortunately defines flights departing to Canada and some
flights to Mexico as domestic instead of international. As
for the BEA (1991 through 2005) data on foreign flagged
carriers, there is some uncertainty as to the average fuel price,
and to the completeness of the data. It was also not possible
to determine what portion of fuel purchased by foreign
carriers at U.S. airports was actually used on domestic flight
segments; this error, however, is believed to be small.58
Uncertainties exist with regard to the total fuel used by
military aircraft and ships, and in the activity data on military
operations and training that were used to estimate percentages
of total fuel use reported as bunker fuel emissions. Total
aircraft and ship fuel use estimates were developed from
DoD records, which document fuel sold to the Navy and
Air Force from the Defense Logistics Agency. These data
may slightly over or under estimate actual total fuel use in
aircraft and ships because each Service may have procured
fuel from, and/or may have sold to, traded with, and/or given
fuel to other ships, aircraft, governments, or other entities.
There are uncertainties in aircraft operations and training
activity data. Estimates for the quantity of fuel actually used
in Navy and Air Force flying activities reported as bunker
fuel emissions had to be estimated based on a combination
of available data and expert judgment. Estimates of marine
bunker fuel emissions were based on Navy vessel steaming
hour data, which reports fuel used while underway and fuel
used while not underway. This approach does not capture
some voyages that would be classified as domestic for a
commercial vessel. Conversely, emissions from fuel used
while not underway preceding an international voyage are
reported as domestic rather than international as would be
done for a commercial vessel. There is uncertainty associated
with ground fuel estimates for 1997 through 2001. Small fuel
quantities may have been used in vehicles or equipment other
than that which was assumed for each fuel type.
There are also uncertainties in fuel end-uses by fuel-
type, emissions factors, fuel densities, diesel fuel sulfur
content, aircraft and vessel engine characteristics and fuel
efficiencies, and the methodology used to back-calculate
the data set to 1990 using the original set from 1995. The
data were adjusted for trends in fuel use based on a closely
correlating, but not matching, data set. All assumptions used
to develop the estimate were based on process knowledge,
Department and military Service data, and expert judgments.
The magnitude of the potential errors related to the various
uncertainties has not been calculated, but is believed to be
small. The uncertainties associated with future military
bunker fuel emission estimates could be reduced through
additional data collection.
Although aggregate fuel consumption data have been
used to estimate emissions from aviation, the recommended
method for estimating emissions of gases other than C02 in
the Revised 1996IPCC Guidelines is to use data by specific
aircraft type (IPCC/UNEP/OECD/IEA 1997). The IPCC
also recommends that cruise altitude emissions be estimated
separately using fuel consumption data, while landing and
take-off (LTO) cycle data be used to estimate near-ground
level emissions of gases other than C02.59
58 Although foreign flagged air carriers are prevented from providing domestic flight services in the United States, passengers may be collected from
multiple airports before an aircraft actually departs on its international flight segment. Emissions from these earlier domestic flight segments should be
classified as domestic, not international, according to the IPCC.
59 U.S. aviation emission estimates for CO, NOX, and NMVOCs are reported by EPA's National Emission Inventory (NEI) Air Pollutant Emission Trends
web site, and reported under the Mobile Combustion section. It should be noted that these estimates are based solely upon LTO cycles and consequently
only capture near ground-level emissions, which are more relevant for air quality evaluations. These estimates also include both domestic and international
flights. Therefore, estimates reported under the Mobile Combustion section overestimate IPCC-defined domestic CO, NOX, and NMVOC emissions by
including landing and take-off (LTO) cycles by aircraft on international flights, but underestimate because they do not include emissions from aircraft
on domestic flight segments at cruising altitudes. The estimates in Mobile Combustion are also likely to include emissions from ocean-going vessels
departing from U.S. ports on international voyages.
3-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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There is also concern as to the reliability of the existing
DOC (1991 through 2005) data on marine vessel fuel
consumption reported at U.S. customs stations due to the
significant degree of inter-annual variation.
QA/QC and Verification
A source-specific QA/QC plan for international bunker
fuels was developed and implemented. This effort included
a Tier 1 analysis, as well as portions of a Tier 2 analysis. The
Tier 2 procedures that were implemented involved checks
specifically focusing on the activity data and emission
factor sources and methodology used for estimating C02,
CH4, and N20 from international bunker fuels in the United
States. Emission totals for the different sectors and fuels
were compared and trends were investigated. No corrective
actions were necessary.
Recalculations Discussion
Historical activity data for aviation was slightly revised
for both U.S. and foreign carriers. These changes were due
to revisions to international fuel cost for foreign carriers and
international jet fuel consumption for U.S. carriers, provided
by DOT (2005). These historical data changes resulted in
minimal changes to the emission estimates for 1999 through
2003, which averaged to an annual increase in emissions
from international bunker fuels of less than 0.1 Tg C02 Eq.
(0.2 percent) in C02 emissions, annual increase of less than
0.1 Tg C02 Eq. (less than 0.2 percent) in CH4 emissions, and
annual increase of less than 0.1 Tg C02 Eq. (0.2 percent) in
N20 emissions.
3.12. Wood Biomass and Ethanol
Consumption (IPCC Source Category 1 A)
The combustion of biomass fuels—such as wood,
charcoal, and wood waste—and biomass-based fuels—such
as ethanol from corn and woody crops—generates
C02. However, in the long run the C02 emitted from
biomass consumption does not increase atmospheric C02
concentrations, assuming the biogenic carbon emitted is
offset by the uptake of C02 resulting from the growth of
new biomass. As a result, C02 emissions from biomass
combustion have been estimated separately from fossil fuel-
based emissions and are not included in the U.S. totals. Net
carbon fluxes from changes in biogenic carbon reservoirs
in wooded or crop lands are accounted for in the Land Use,
Land-Use Change, and Forestry chapter.
In 2004, total C02 emissions from the burning of
woody biomass in the industrial, residential, commercial,
and electricity generation sectors were approximately 191.7
Tg C02 Eq. (191,737 Gg) (see Table 3-56 and Table 3-57).
As the largest consumer of woody biomass, the industrial
sector was responsible for 71 percent of the C02 emissions
from this source. The residential sector was the second
largest emitter, constituting 18 percent of the total, while
the commercial and electricity generation sectors accounted
for the remainder.
Biomass-derived fuel consumption in the United
States consisted primarily of ethanol use in the transportation
sector. Ethanol is primarily produced from corn grown in
the Midwest, and was used mostly in the Midwest and
South. Pure ethanol can be combusted, or it can be mixed
with gasoline as a supplement or octane-enhancing agent.
The most common mixture is a 90 percent gasoline, 10
percent ethanol blend known as gasohol. Ethanol and
ethanol blends are often used to fuel public transport
vehicles such as buses, or centrally fueled fleet vehicles.
These fuels burn cleaner than gasoline (i.e., lower in NOX
and hydrocarbon emissions), and have been employed in
urban areas with poor air quality. However, because ethanol
is a hydrocarbon fuel, its combustion emits C02.
Table 3-56: C02 Emissions from Wood Consumption by End-Use Sector (Tg C02 Eq.)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990
135.3
59.9
4.0
13.3
212.5
1998
150.5
39.9
5.0
14.1
209.5
1999
152
42.7
5.4
14.2
214.3
2000
153.6
44.7
5.5
13.9
217.6
2001
135.4
38.2
4.2
13.0
190.8
2002
131.1
32.3
4.0
15.5
182.9
2003
128
37.0
4.1
17.3
186.3
2004
135.9
34.3
4.2
17.3
191.7
Note: Totals may not sum due to independent rounding.
Energy 3-63
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Table 3-57: C02 Emissions from Wood Consumption by End-Use Sector (Gg)
End-Use Sector
Industrial
Residential
Commercial
Electricity Generation
Total
1990
135,347
59,911
4,037
13,252
212,547
1998
150,510
39,920
4,963
14,097
209,490
1999
152,019
42,677
5,394
14,233
214,323
2000
153,559
44,685
5,481
13,851
217,577
2001
135,413
38,153
4,175
13,034
190,776
2002
131,079
32,267
4,037
15,487
182,878
2003
127,970
37,019
4,100
17,250
186,339
2004
135,943
34,270
4,246
17,278
191,737
Note: Totals may not sum due to independent rounding.
Table 3-58: C02 Emissions from Ethanol Consumption
(Tg C02 Eq. and Gg)
Table 3-60: Ethanol Consumption (Trillion Btu)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
4.2
7.7
8.0
9.2
9.7
11.5
15.8
19.5
Gg
4,155
7,711
8,017
9,188
9,701
11,473
15,771
19,493
Year
1990
1998
1999
2000
2001
2002
2003
2004
Trillion Btu
63
117
122
139
147
174
239
296
Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Industrial
1,442
1,603
1,620
1,636
1,443
1,396
1,363
1,448
Residential
581
387
414
433
370
313
359
332
Commercial
39
48
52
53
40
39
40
41
Electricity Generation
129
137
138
134
126
150
167
168
In 2004, the United States consumed an estimated
2.96 trillion Btu of ethanol, and as a result, produced
approximately 19.5 Tg C02 Eq. (19,493 Gg) (see Table 3-58)
of C02 emissions. Ethanol production and consumption has
grown steadily every year since 1990, with the exception of
1996 due to short corn supplies and high prices in that year.
Methodology
Woody biomass emissions were estimated by taking
U.S. consumption data (EIA 2005) (see Table 3-59), provided
in energy units for the industrial, residential, commercial,
and electric generation sectors, and applying two EIA
gross heat contents (Lindstrom 2003). One heat content
(16.953114 MMBtu/MT Wood & Wood Waste) was applied
to the industrial sector's consumption, while the other heat
content (15.432359 MMBtu/MT Wood & Wood Waste) was
applied to the consumption data for the other sectors. An EIA
emission factor of 0.434 MT C/MT Wood (Lindstrom 2003)
was then applied to the resulting quantities of woody biomass
to obtain C02 emissions estimates. It was assumed that the
woody biomass contains black liquor and other wood wastes,
has a moisture content of 12 percent, and is converted into
C02 with 100 percent efficiency. The emissions from ethanol
consumption were calculated by applying an EIA emission
3-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
factor of 17.99 Tg C/QBtu (Lindstrom 2003) to U.S. ethanol heat content for all the different types of woody biomass
consumption data that were provided in energy units (EIA consumed within these sectors. Emission estimates
2005) (see Table 3-60). from ethanol production are more certain than estimates
from woody biomass consumption due to better activity
UnCBrtdJnty data collection methods and uniform combustion
It is assumed that the combustion efficiency for techniques.
woody biomass is 100 percent, which is believed to be an
overestimate of the efficiency of wood combustion processes nBCdlCllldtlOnS DISCUSS 10 H
in the United States. Decreasing the combustion efficiency The historical data for wood biomass consumption
would increase emission estimates. Additionally, the heat was adjusted slightly, which resulted in an average annual
content applied to the consumption of woody biomass in decrease in emissions from wood biomass and ethanol
the residential, commercial, and electric power sectors is consumption of 2.0 Tg C02 Eq. (0.9 percent) from 1990
unlikely to be a completely accurate representation of the through 2003.
Box 3-3: Formation of C02 through Atmospheric CH4 Oxidation
CH4 emitted to the atmosphere will eventually oxidize into C02, which remains in the atmosphere for up to 200 years. The global
warming potential (GWP) of CH4, however, does not account for the radiative forcing effects of the C02 formation that results from this CH4
oxidation. The IPCC Guidelines for Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) do not explicitly recommend a procedure
for accounting for oxidized CH4, but some of the resulting C02 is, in practice, included in the inventory estimates because of the intentional
"double-counting" structure for estimating C02 emissions from the combustion of fossil fuels. According to the IPCC Guidelines, countries
should estimate emissions of CH4, CO, and NMVOCs from fossil fuel combustion, but also assume that these compounds eventually oxidize
to C02 in the atmosphere. This is accomplished by using C02 emission factors that do not factor out carbon in the fuel that is released as in
the form of CH4, CO, and NMVOC molecules. Therefore, the carbon in fossil fuel is intentionally double counted, as an atom in a CH4 molecule
and as an atom in a C02 molecule.60 While this approach does account for the full radiative forcing effect of fossil fuel-related greenhouse
gas emissions, the timing is not accurate because it may take up to 12 years for the CH4 to oxidize and form C02.
There is no similar IPCC approach to account for the oxidation of CH4 emitted from sources other than fossil fuel combustion (e.g.,
landfills, livestock, and coal mining). CH4 from biological systems contains carbon that is part of a rapidly cycling biological system, and
therefore any carbon created from oxidized CH4 from these sources is matched with carbon removed from the atmosphere by biological
systems—likely during the same or subsequent year. Thus, there are no additional radiative forcing effects from the oxidation of CH4 from
biological systems. For example, the carbon content of CH4 from enteric fermentation is derived from plant matter, which itself was created
through the conversion of atmospheric C02 to organic compounds.
The remaining anthropogenic sources of CH4 (e.g., fugitive emissions from coal mining and natural gas systems, industrial process
emissions) do increase the long-term C02 burden in the atmosphere, and this effect is not captured in the inventory. The following tables
provide estimates of the equivalent C02 production that results from the atmospheric oxidation of CH4 from these remaining sources. The
estimates for CH4 emissions are gathered from the respective sections of this report, and are presented in Table 3-61. The C02 estimates
are summarized in Table 3-62.
Table 3-61: CH4 Emissions from Non-Combustion Fossil Sources (Gg)
Source
Coal Mining
Abandoned Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production
Iron and Steel Production
Total
1990
3,900
286
6,034
1,640
56
1
63
11,980
1998
2,990
328
5,973
1,414
80
1
57
10,842
1999
2,807
330
5,797
1,358
81
1
56
10,430
2000
2,679
343
6,033
1,325
80
1
57
10,518
2001
2,644
313
5,981
1,303
68
+
51
10,360
2002
2,500
288
5,971
1,274
72
+
48
10,153
2003
2,611
277
5,939
1,236
72
+
49
10,184
2004
2,682
269
5,658
1,222
77
+
50
9,957
Note: These emissions are accounted for under their respective source categories. Totals may not sum due to independent rounding.
Energy 3-65
-------
Box 3-3: Formation of C02 through Atmospheric CH4 Oxidation (continued)
Table 3-62: Formation of C02 through Atmospheric CH4 Oxidation (Tg C02 Eq.)
Source
Coal Mining
Abandoned Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production
Iron and Steel Production
Total
1990
10.7
0.8
16.6
4.5
0.2
+
0.2
32.9
1998
8.2
0.9
16.4
3.9
0.2
+
0.2
29.8
1999
7.7
0.9
15.9
3.7
0.2
+
0.2
28.7
2000
7.4
0.9
16.6
3.6
0.2
+
0.2
28.9
2001
7.3
0.9
16.4
3.6
0.2
+
0.1
28.5
2002
6.9
0.8
16.4
3.5
0.2
+
0.1
27.9
2003
7.2
0.8
16.3
3.4
0.2
+
0.1
28.0
2004
7.4
0.7
15.6
3.4
0.2
+
0.1
27.4
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg C02 Eq.
The estimates of C02 formation are calculated by applying a factor of 44/16, which is the ratio of molecular weight of C02 to
the molecular weight of CH4. For the purposes of the calculation, it is assumed that CH4 is oxidized to C02 in the same year that it is
emitted. As discussed above, this is a simplification, because the average atmospheric lifetime of CH4 is approximately 12 years.
C02 formation can also result from the oxidation of CO and NMVOCs. However, the resulting increase of C02 in the atmosphere is
explicitly included in the mass balance used in calculating the storage and emissions from non-energy uses of fossil fuels, with the carbon
components of CO and NMVOC counted as C02 emissions in the mass balance.61
61 See Annex 2.3 for a more detailed discussion on accounting for indirect emissions from CO and NMVOCs.
3-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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4. Industrial Processes
Figure 4-1
Greenhouse gas emissions are produced as a by-product of various non-energy-related industrial activities. That is,
these emissions are produced from an industrial process itself and are not directly a result of energy consumed
during the process. For example, raw materials can be chemically transformed from one state to another. This
transformation can result in the release of greenhouse gases such as carbon dioxide (C02), methane (CH4), or nitrous
oxide (N20). The processes addressed in this chapter include iron and steel production, cement manufacture, ammonia
manufacture and urea application, lime manufacture, limestone and dolomite use (e.g., flux stone, flue gas desulfurization,
and glass manufacturing), soda ash manufacture and consumption, titanium dioxide production, phosphoric acid production,
ferroalloy production, C02 consumption, aluminum production, petrochemical production, silicon carbide production and
consumption, lead production, zinc production, nitric acid production, and adipic acid production (see Figure 4-1).
In addition to the three greenhouse gases listed above, there are also industrial sources of man-made fluorinated compounds
called hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6). The present contribution of these
gases to the radiative forcing effect of all anthropogenic greenhouse gases is small; however, because of their extremely
long lifetimes, many of them will continue to accumulate in
the atmosphere as long as emissions continue. In addition,
many of these gases have high global warming potentials;
SF6 is the most potent greenhouse gas the Intergovernmental
Panel on Climate Change (IPCC) has evaluated. Usage of
HFCs for the substitution of ozone depleting substances is
growing rapidly, as they are the primary substitutes for ozone
depleting substances (ODSs), which are being phased-out
under the Montreal Protocol on Substances that Deplete the
Ozone Layer. In addition to their use as ODS substitutes,
HFCs, PFCs, SF6, and other fluorinated compounds are
employed and emitted by a number of other industrial
sources in the United States. These industries include
aluminum production, HCFC-22 production, semiconductor
manufacture, electric power transmission and distribution,
and magnesium metal production and processing.
In 2004, industrial processes generated emissions of
320.7 teragrams of C02 equivalent (Tg C02 Eq.), or 5 percent
of total U.S. greenhouse gas emissions. CO2 emissions from
all industrial processes were 152.6 Tg CO2 Eq. (152,650
Gg) in 2004. This amount accounted for only 3 percent of
2004 Industrial Processes Chapter Greenhouse
Gas Sources
Substitution of Ozone Depleting Substances
Iron and Steel Production
Cement Manufacture
Ammonia Manufacture and Urea Application H
Nitric Acid Production ••
HCFC-22 Production •
Electrical Transmission and Distribution H
Lime Manufacture H
Aluminum Production |
Limestone and Dolomite Use I
Adipic Acid Production |
Semiconductor Manufacture |
Petrochemical Production |
Soda Ash Manufacture and Consumption |
Magnesium Production and Processing |
Titanium Dioxide Production |
Phosphoric Acid Production
Ferroalloy Production
Carbon Dioxide Consumption
Zinc Production
Lead Production
Silicon Carbide Consumption | <0.5
Silicon Carbide Production I <0.1
Industrial Processes
as a Portion of
all Emissions
0 20 40 60 80 100 120
Industrial Processes 4-1
-------
national C02 emissions. CH4 emissions from petrochemical,
silicon carbide, and iron and steel production resulted in
emissions of approximately 2.7 Tg C02 Eq. (127 Gg) in 2004,
which was less than 1 percent of U.S. CH4 emissions. N20
emissions from adipic acid and nitric acid production were
22.4 Tg C02 Eq. (72 Gg) in 2004, or 6 percent of total U.S.
N2O emissions. In 2004, combined emissions of HFCs, PFCs
and SF6 totaled 143.0 Tg CO2 Eq. Overall, emissions from
industrial processes increased by 6.5 percent from 1990 to
2004 despite decreases in emissions from several industrial
processes, such as iron and steel, aluminum production,
ammonia manufacture and urea application, and electrical
transmission and distribution. The increase in overall
emissions was driven by a rise in the emissions originating
from cement manufacture and, primarily, the emissions from
the use of substitutes for ODSs.
Table 4-1 summarizes emissions for the Industrial
Processes chapter in units of Tg CO2 Eq., while unweighted
native gas emissions in gigagrams (Gg) are provided in
Table 4-2.
In order to ensure the quality of the emission estimates
from industrial processes, Tier 1 quality assurance and
quality control (QA/QC) procedures and checks have
been performed on all industrial process sources. Where
performed, Tier 2 procedures focused on the emission
factor and activity data sources and methodology used for
estimating emissions, and will be described within the QA/
QC and Verification Discussion of that source description.
In addition to the national QA/QC plan, a more detailed plan
was developed specifically for the CO2 and CH4 industrial
processes sources. This plan was based on the U.S. strategy,
Table 4-1: Emissions from Industrial Processes (Tg C02 Eq.)
Gas/Source
C02
Iron and Steel Production
Cement Manufacture
Ammonia Manufacture & Urea Application
Lime Manufacture
Limestone and Dolomite Use
Aluminum Production
Soda Ash Manufacture and Consumption
Petrochemical Production
Titanium Dioxide Production
Phosphoric Acid Production
Ferroalloy Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Consumption
CH4
Petrochemical Production
Iron and Steel Production
Silicon Carbide Production
N20
Nitric Acid Production
Adipic Acid Production
HFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production
Electrical Transmission and Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing
Total
1990
174.8
85.0
33.3
19.3
11.2
5.5
7.0
4.1
2.2
1.3
1.5
2.0
0.9
0.9
0.3
0.1
1
33.0
17.8
15.2
90.8
0.4
35.0
28.6
2.9
18.4
5.4
301.1
1998
171.9
67.7
39.2
21.9
13.9
7.4
6.4
4.3
3.0
1.8
1.6
2.0
0.9
1.1
0.3
0.2
2.9
1.7
1.2
+
26.9
20.9
6.0
133.4
54.5
40.1
16.7
7.1
9.1
5.8
335.1
1999
167.5
63.8
40.0
20.6
13.5
8.1
6.5
4.2
3.1
1.9
1.5
2.0
0.8
1.1
0.3
0.1
2.9
1.7
1.2
+
25.6
20.1
5.5
131.5
62.8
30.4
16.1
7.2
9.0
6.0
327.5
2000
166.4
65.3
41.2
19.6
13.3
6.0
6.2
4.2
3.0
1.9
1.4
1.7
1.0
1.1
0.3
0.1
2.9
1.7
1.2
+
25.6
19.6
6.0
134.7
71.2
29.8
15.3
6.3
9.0
3.2
329.6
2001
152.5
57.8
41.4
16.7
12.8
5.7
4.5
4.1
2.8
1.9
1.3
1.3
0.8
1.0
0.3
0.1
2.5
1.4
1.1
+
20.8
15.9
4.9
124.9
78.6
19.8
15.3
4.5
4.0
2.6
300.7
2002
152.6
54.6
42.9
18.5
12.3
5.9
4.6
4.1
2.9
2.0
1.3
1.2
1.0
0.9
0.3
0.1
2.5
1.5
1.0
+
23.1
17.2
5.9
132.7
86.2
19.8
14.5
4.4
5.3
2.6
310.9
2003
147.6
53.3
43.1
15.3
13.0
4.7
4.6
4.1
2.8
2.0
1.4
1.2
1.3
0.5
0.3
0.1
2.5
1.5
1.0
+
22.9
16.7
6.2
131.0
93.5
12.3
14.0
4.3
3.8
3.0
304.1
2004
152.6
51.3
45.6
16.9
13.7
6.7
4.3
4.2
2.9
2.3
1.4
1.3
1.2
0.5
0.3
0.1
2.7
1.6
1.0
+
22.4
16.6
5.7
143.0
103.3
15.6
13.8
4.7
2.8
2.7
320.7
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
4-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-2: Emissions from Industrial Processes (Gg)
Gas/Source
C02
Iron and Steel Production
Cement Manufacture
Ammonia Manufacture & Urea Application
Lime Manufacture
Limestone and Dolomite Use
Aluminum Production
Soda Ash Manufacture and Consumption
Petrochemical Production
Titanium Dioxide Production
Phosphoric Acid Production
Ferroalloy Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Consumption
CH4
Petrochemical Production
Iron and Steel Production
Silicon Carbide Production
N20
Nitric Acid Production
Adipic Acid Production
MFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
HCFC-22 Production3
Electrical Transmission and Distribution"
Semiconductor Manufacture
Aluminum Production
Magnesium Production and Processing"
N08
CO
NMVOCs
1990
174,
85,
33,
19,
11,
5,
7,
4,
2,
1,
1,
1,
4,
2,
791
023
278
306
242
533
045
141
221
308
529
980
860
939
285
100
120
56
63
1
107
58
49
M
M
3
1
M
M
+
591
124
426
1998
171,
67,
39,
21,
13,
7,
6,
4,
3,
1,
1,
2,
1,
3,
2,
897
689
218
934
919
449
359
325
015
819
593
027
912
140
308
190
138
80
57
1
87
67
19
M
M
3
1
M
M
+
637
163
047
1999
167,450
63,821
39,991
20,615
13,473
8,057
6,458
4,217
3,054
1,853
1,539
1,996
849
1,080
310
137
138
81
56
1
83
65
18
M
M
3
1
M
M
+
595
2,156
1,183
2000
166,379
65,316
41,190
19,616
13,322
5,960
6,244
4,181
3,004
1,918
1,382
1,719
957
1,129
311
130
138
80
57
1
83
63
19
M
M
3
1
M
M
+
626
2,217
1,773
2001
152,529
57,822
41,357
16,719
12,828
5,733
4,505
4,147
2,787
1,857
1,264
1,329
818
976
293
94
119
68
51
+
67
51
16
M
M
2
1
M
M
+
656
2,339
1,769
2002
152,605
54,550
42,898
18,510
12,309
5,885
4,596
4,139
2,857
1,997
1,338
1,237
968
927
290
105
120
72
48
+
75
56
19
M
M
2
1
M
M
+
630
2,286
1,723
2003
147,649
53,335
43,082
15,278
12,987
4,720
4,608
4,111
2,777
2,013
1,382
1,159
1,293
502
289
111
121
72
49
+
74
54
20
M
M
1
1
M
M
+
631
2,286
1,725
2004
152,650
51,334
45,559
16,894
13,698
6,702
4,346
4,205
2,895
2,259
1,395
1,287
1,183
502
259
133
127
77
50
+
72
54
19
M
M
1
1
M
M
+
632
2,286
1,727
+ Does not exceed 0.5 Gg
M (Mixture of gases)
a HFC-23 emitted
b SF6 emitted
Note: Totals may not sum due to independent rounding.
but was tailored to include specific procedures recommended
for these sources.
The general method employed to estimate emissions
for industrial processes, as recommended by the IPCC,
involves multiplying production data (or activity data) for
each process by an emission factor per unit of production.
The uncertainty of the emission estimates is therefore
generally a function of a combination of the uncertainties
surrounding the production and emission factor variables.
Uncertainty of activity data and the associated probability
density functions for industrial process C02 sources were
estimated based on expert assessment of available qualitative
and quantitative information. Uncertainty estimates and
probability density functions for the emission factors used
to calculate emissions from this source were devised based
on IPCC recommendations.
Activity data is obtained through a survey of manufacturers
conducted by various organizations (specified within each
source); the uncertainty of the activity data is a function of the
reliability of plant-level production data and is influenced by
the completeness of the survey response. The emission factors
used were either derived using calculations that assume precise
and efficient chemical reactions, or were based upon empirical
data in published references. As a result, uncertainties in
Industrial Processes 4-3
-------
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 2004 inventory estimates
from industrial processes continues a multi-year process
for developing credible quantitative uncertainty estimates
for these source categories using the IPCC Tier 2 approach.
As the process continues, the type and the characteristics
of the actual probability density functions underlying
the input variables are identified and better characterized
(resulting in development of more reliable inputs for the
model, including accurate characterization of correlation
between variables), based primarily on expert judgment.
Accordingly, the quantitative uncertainty estimates reported
in this section should be considered illustrative and as
iterations of ongoing efforts to produce accurate uncertainty
estimates. The correlation among data used for estimating
emissions for different sources can influence the uncertainty
analysis of each individual source. While the uncertainty
analysis recognizes very significant connections among
sources, a more comprehensive approach that accounts for
all linkages will be identified as the uncertainty analysis
moves forward.
4.1. Iron and Steel Production
(IPCC Source Category 2C1)
In addition to being an energy intensive process, the
production of iron and steel also generates process-related
emissions of C02 and CH4. Iron is produced by first reducing
iron oxide (iron ore) with metallurgical coke in a blast
furnace to produce pig iron (impure iron containing about
3 to 5 percent carbon by weight). Metallurgical coke is
manufactured in a coke plant using coking coal as a raw
material. Iron may be introduced into the blast furnace in the
form of raw iron ore, pellets, briquettes, or sinter. Pig iron is
used as a raw material in the production of steel (containing
about 0.4 percent carbon by weight). Pig iron is also used as
a raw material in the production of iron products in foundries.
The pig iron production process produces C02 emissions and
fugitive CH4 emissions.
The production of metallurgical coke from coking coal
and the consumption of the metallurgical coke used as a
reducing agent in the blast furnace are considered in the
inventory to be non-energy (industrial) processes, not energy
(combustion) processes. Coal coke is produced by heating
coking coal in a coke oven in a low-oxygen environment.
The process drives off the volatile components of the coking
coal and produces coal (metallurgical) coke. Coke oven
gas and coal tar are carbon containing by-products of the
coke manufacturing process. Coke oven gas is generally
burned as a fuel within the steel mill. Coal tar is used as a
raw material to produce anodes used for primary aluminum
production and other electrolytic processes, and also used
in the production of other coal tar products. The coke
production process produces C02 emissions and fugitive
CH4 emissions.
Sintering is a thermal process by which fine iron-bearing
particles, such as air emission control system dust, are baked,
which causes the material to agglomerate into roughly one-
inch pellets that are then recharged into the blast furnace for
pig iron production. Iron ore particles may also be formed
into larger pellets or briquettes by mechanical means, and
then agglomerated by heating prior to being charged into the
blast furnace. The sintering process produces C02 emissions
and fugitive CH4 emissions.
The metallurgical coke is a reducing agent in the blast
furnace. C02 is produced as the metallurgical coke used in
the blast furnace process is oxidized and the iron is reduced.
Steel is produced from pig iron in a variety of specialized
steel-making furnaces. The majority of C02 emissions from
the iron and steel process come from the use of coke in the
production of pig iron, with smaller amounts evolving from
the removal of carbon from pig iron used to produce steel.
Some carbon is also stored in the finished iron and steel
products.
Emissions of C02 and CH4 from iron and steel
production in 2004 were 51.3 Tg CO2 Eq. (51,334 Gg) and
1.0 Tg CO2 Eq. (50 Gg), respectively (see Table 4-3 and Table
4-4). Emissions have fluctuated significantly from 1990 to
2004 due to changes in domestic economic conditions and
changes in product imports and exports. In 2004, domestic
production of pig iron increased by 4.5 percent and coal coke
production decreased by 1.5 percent. Overall, domestic pig
iron and coke production have declined since the 1990s.
Pig iron production in 2004 was 11 percent lower than in
4-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-3: C02 and CH4 Emissions from Iron and Steel Production (Tg C02 Eq.)
Year
C02
CH4
Total
1990
85.0
1.3
86.3
1998
67.7
1.2
68.9
1999
63.8
1.2
65.0
2000
65.3
1.2
66.5
2001
57.8
1.1
58.9
2002
54.6
1.0
55.6
2003
53.3
1.0
54.3
2004
51.3
1.0
52.4
Table 4-4: C02 and CH4 Emissions from Iron and Steel Production (Gg)
Year
C02
CH4
1990
85,
,023
63
1998
67,
,689
57
1999
63,
,821
56
2000
65,316
57
2001
57,823
51
2002
54,550
48
2003
53,335
49
2004
51,334
50
2000 and 14 percent below 1990 levels. Coke production
in 2004 was 19 percent lower than in 2000 and 39 percent
below 1990 levels.
Methodology
Coking coal is used to manufacture metallurgical
(coal) coke that is used primarily as a reducing agent in
the production of iron and steel, but is also used in the
production of other metals including lead and zinc (see Lead
Production and Zinc Production in this chapter). The total
coking coal consumed at coke plants and the total amount
of coking coal produced were identified. These data were
used to estimate the emissions associated with producing
coke from coking coal and attributed to the production of
iron and steel. Additionally, the amount of coke consumed
to produce pig iron and the emissions associated with this
production were estimated. The carbon content of the coking
coal and coke consumed in these processes were estimated
by multiplying the energy consumption by material specific
carbon-content coefficients. The carbon content coefficients
used are presented in Annex 2.1.
Emissions from the re-use of scrap steel were also
estimated by assuming that all the associated carbon content
of the scrap steel, which has an associated carbon content
of approximately 0.4 percent, are released during the scrap
re-use process.
Lastly, emissions from carbon anodes, used during the
production of steel in electric arc furnaces (EAFs), were also
estimated. Emissions of C02 were calculated by multiplying
the annual production of steel in EAFs by an emission factor
(4.4 kg C02/ton steelEAF). It was assumed that the carbon
anodes used in the production of steel in EAFs are composed
of 80 percent petroleum coke and 20 percent coal tar pitch
(DOE 1997). Since coal tar pitch is a by-product of the
coke production process and its carbon-related emissions
have already been accounted for earlier in the iron and steel
emissions calculation as part of the process, the emissions
were reduced by the amount of carbon in the coal tar pitch
used in the anodes to avoid double counting.
Emissions associated with the production of coke from
coking coal, pig iron production, the re-use of scrap steel,
and the consumption of carbon anodes during the production
of steel were summed.
Additionally, the coal tar pitch component of carbon
anodes consumed during the production of aluminum are
accounted for in the aluminum production section of this
chapter. The emissions were reduced by the amount of
coal tar pitch used in aluminum production to avoid double
counting. The amount of coal tar pitch consumed for
processes other than the aluminum production and as EAF
anodes and net imports of coal tar were also estimated. A
storage factor was applied to estimate emissions associated
with other coal tar pitch consumption and net imports.
Carbon storage was accounted for by assuming that all
domestically manufactured steel had a carbon content of 0.4
percent. Furthermore, any pig iron that was not consumed
during steel production, but fabricated into finished iron
products, was assumed to have a carbon content of 4
percent.
The potential C02 emissions associated with carbon
contained in pig iron used for purposes other than iron and
steel production, stored in the steel product, stored as coal
Industrial Processes 4-5
-------
tar, and attributed to carbon anode consumption during
aluminum production were summed and subtracted from
the total emissions estimated above.
The production processes for coal coke, sinter, and pig
iron result in fugitive emissions of CH4, which are emitted
via leaks in the production equipment rather than through the
emission stacks or vents of the production plants. The fugitive
emissions were calculated by applying emission factors taken
from the 1995 IPCC Guidelines (IPCC/UNEP/OECD/IEA
1995) (see Table 4-5) to annual domestic production data for
coal coke, sinter, and pig iron.
Data relating to the amount of coal consumed at
coke plants, and for the production of coke for domestic
consumption in blast furnaces, were taken from the Energy
Information Administration (EIA), Monthly Energy Review
September 2005 (EIA 2005a); Quarterly Coal Report
October through December (EIA 1998, 1999, 2000, 2001,
2002, 2003, 2004a, 2005b). Data on total coke consumed
for pig iron production were taken from the American Iron
and Steel Institute (AISI), Annual Statistical Report (AISI
2001, 2002, 2003, 2004, 2005) and provided by the AISI
Annual Statistical Report (Larmoyeux 2005). Scrap steel
consumption data for 1990 through 2004 were obtained from
Annual Statistical Reports (AISI 1995, 2001, 2002, 2003,
Table 4-5: CH4 Emission Factors for Coal Coke, Sinter,
and Pig Iron Production (g/kg)
Material Produced
g CH4/kg produced
Coal Coke
Pig Iron
Sinter
0.5
0.9
0.5
Source: IPCC/UNEP/OECD/IEA 1997
2004, 2005) (see Table 4-6). Crude steel production, as well
as pig iron use for purposes other than steel production, was
also obtained from Annual Statistical Reports (AISI 1996,
2001, 2002, 2004, 2005). Carbon content percentages for
pig iron and crude steel and the C02 emission factor for
carbon anode emissions from steel production were obtained
from IPCC Good Practice Guidance (IPCC 2000). Data
on the non-energy use of coking coal were obtained from
EIAs Emissions of U.S. Greenhouse Gases in the United
States (EIA 2004b). Information on coal tar net imports was
determined using data from the U.S. Bureau of the Census's
U.S. International Trade Commission's Trade Dataweb
(U.S. Bureau of the Census 2005). Coal tar consumption
for aluminum production data was estimated based on
information gathered by EPA's Voluntary Aluminum
Industrial Partnership (VAIP) program and data from US AA
Primary Aluminum Statistics (USAA 2004, 2005) (see
Aluminum Production in this chapter). Annual consumption
of iron ore used in sinter production for 1990 through 2004
was obtained from the USGS Iron Ore Yearbook (USGS
1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002,
2003,2004,2005). The C02 emission factor for carbon anode
emissions from aluminum production was taken from the
Revised 1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA
1997). Estimates for the composition of carbon anodes used
during EAF steel and aluminum production were obtained
from Energy and Environmental Profile of the U.S. Aluminum
Industry (DOE 1997).
Uncertainty
The time series data sources for production of coal
coke, sinter, pig iron, steel, and aluminum upon which the
calculations are based are assumed to be consistent for the
Table 4-6: Production and Consumption Data for the Calculation of C02 and CH4 Emissions from Iron and Steel
Production (Thousand Metric Tons)
Gas/Activity Data
C02
Coal Consumption at Coke Plants
Coke Consumption for Pig Iron
Basic Oxygen Furnace Steel Production
Electric Arc Furnace Steel Production
CH4
Coke Production
Iron Ore Consumption for Sinter
Domestic Pig Iron Production for Steel
1990
35,
25,
56,
33,
25,
12,
49,
269
043
216
510
054
239
062
1998
25,
19,
45,
44,
18,
10,
573
966
147
514
181
791
47,471
1999
25,499
18,817
52,365
45,064
18,240
11,072
45,678
2000
26,254
19,307
53,965
47,860
18,877
10,784
47,400
2001
23,
17,
47,
42,
17,
9,
41,
655
236
359
774
191
234
741
2002
21,461
15,959
45,463
46,125
15,221
9,018
39,601
2003
21,998
15,482
45,874
47,804
15,579
8,984
40,487
2004
21,473
15,068
47,714
51,969
15,540
8,984
42,292
4-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
entire time series. The estimates of C02 emissions from the
production and utilization of coke are based on consumption
data, average carbon contents, and the fraction of carbon
oxidized. Uncertainty is associated with the total U.S. coke
consumption and coke consumed for pig iron production.
These data are provided by different data sources (EIA
and AISI) and comparisons between the two datasets
for net imports, production, and consumption identified
discrepancies; however, the data chosen are considered the
best available. These data and factors produce a relatively
accurate estimate of C02 emissions. However, there are
uncertainties associated with each of these factors. For
example, carbon oxidation factors may vary depending on
inefficiencies in the combustion process, where varying
degrees of ash or soot can remain unoxidized.
Simplifying assumptions were made concerning the
composition of carbon anodes (80 percent petroleum coke
and 20 percent coal tar). For example, within the aluminum
industry, the coal tar pitch content of anodes can vary
from 15 percent in prebaked anodes to 24 to 28 percent
in Soderberg anode pastes (DOE 1997). An average value
was assumed and applied to all carbon anodes utilized
during aluminum and steel production. The assumption is
also made that all coal tar used during anode production
originates as a by-product of the domestic coking process.
Similarly, it was assumed that all pig iron and crude
steel have carbon contents of 4 percent and 0.4 percent,
respectively. The carbon content of pig iron can vary
between 3 and 5 percent, while crude steel can have a carbon
content of up to 2 percent, although it is typically less than
1 percent (IPCC 2000). There is also uncertainty associated
with the total amount of coal tar products produced and
with the storage factor for coal tar.
Uncertainty surrounding the CO2 emission factor for
carbon anode consumption in aluminum production was
also estimated. Emissions vary depending on the specific
technology used by each plant (Prebake or Soderberg).
Emissions were estimated according to process and plant
specific methodology outlined in the aluminum production
section of this chapter. Based on expert elicitation, carbon
anodes were assumed to be 20 percent coal tar pitch for the
whole time series (Kantamaneni 2005). Similarly, the carbon
anode emission factor for steel production can vary between
3.7 and 5.5 kg C02/ton steel (IPCC 2000). For this analysis,
the upper bound value was used.
For the purposes of the CH4 calculation it is assumed
that none of the CH4 is captured in stacks or vents and that
all of the CH4 escapes as fugitive emissions. Additionally,
the C02 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 C02 and CH4.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-7. Iron and Steel CO2 emissions
were estimated to be between 45.8 and 74.5 Tg C02 Eq. at
the 95 percent confidence level (or in 19 out of 20 Monte
Carlo Stochastic Simulations). This indicates a range of
approximately 11 percent below and 45 percent above the
emission estimate of 51.3 Tg CO2 Eq. Iron and Steel CH4
emissions were estimated to be between 1.0 Tg CO2 Eq. and
1.1 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 7 percent below and 9 percent above
the emission estimate of 1.0 Tg CO2 Eq.
Recalculations Discussion
Elements of the methodology to estimate C02 emissions
from iron and steel production were revised for the entire
Table 4-7: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Iron and Steel Production (Tg.
C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Iron
Iron
and Steel Production C02 51.3
and Steel Production CH4 1.0
45.8 74.5 -11% +45%
1.0 1.1 -7% +9%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-7
-------
time series to include a more accurate dataset. Previously,
emissions associated with the carbon content of imported
pig iron were estimated and added to the total emissions
associated with iron and steel production. Imported pig iron
production was estimated as the difference between U.S.
pig iron production and U.S. pig iron consumption. These
estimates proved unreliable for 2004 warranting pursuit of
new methodology.
New methods utilize data on total coke consumed
for pig iron production as well as total coking coal used
for coke production. EIA reports minor inconsistencies in
the early years of the total U.S. coking coal datasets (EIA
1998); however, overall the datasets, which offset the need to
estimate imported pig iron and coke, are believed to provide
more accurate emission estimates. These changes resulted
in an average annual decrease of 1.2 Tg CO2 Eq. (2 percent)
in C02 emissions from iron and steel production for 1990
through 2003.
4.2. Cement Manufacture (IPCC
Source Category 2A1)
Cement manufacture is an energy- and raw-material
intensive process that results in the generation of C02 from
both the energy consumed in making the cement and the
chemical process itself.1 Cement production, at the most
recent estimation, accounted for about 2.4 percent of total
global industrial and energy-related C02 emissions (IPCC
1996, USGS 2003). Cement is manufactured in nearly 40
states. C02 emitted from the chemical process of cement
production represents one of the largest sources of industrial
C02 emissions in the United States.
During the cement production process, calcium
carbonate (CaC03) is heated in a cement kiln at a temperature
of about 1,300°C (2,400°F) to form lime (i.e., calcium oxide
or CaO) and C02. This process is known as calcination or
calcining. Next, the lime is combined with silica-containing
materials to produce clinker (an intermediate product), with
the earlier by-product C02 being released to the atmosphere.
The clinker is then allowed to cool, mixed with a small
amount of gypsum, and used to make Portland cement. The
production of masonry cement from Portland cement requires
additional lime and, thus, results in additional C02 emissions.
However, this additional lime is already accounted for in the
Lime Manufacture source category in this chapter; therefore,
the additional emissions from making masonry cement from
clinker are not counted in this source category's total. They
are presented here for informational purposes only.
In 2004, U.S. clinker production—including Puerto
Puco—totaled 88,104 thousand metric tons (Van Oss 2005).
The resulting emissions of C02 from 2004 cement production
were estimated to be 45.6 Tg C02 Eq. (45,559 Gg) (seeTable
4-8). Emissions from masonry production from clinker raw
material are accounted for under Lime Manufacture.
After falling in 1991 by two percent from 1990 levels,
cement production emissions have grown every year since.
Overall, from 1990 to 2004, emissions increased by 37
percent. Cement continues to be a critical component of the
construction industry; therefore, the availability of public
construction funding, as well as overall economic growth,
have had considerable influence on cement production.
Methodology
C02 emissions from cement manufacture are created
by the chemical reaction of carbon-containing minerals
(i.e., calcining limestone). While in the kiln, limestone is
broken down into C02 and lime with the C02 released to
the atmosphere. The quantity of C02 emitted during cement
production is directly proportional to the lime content of
the clinker. During calcination, each mole of CaC03 (i.e.,
Table 4-8: C02 Emissions from Cement Production (Tg
C02 Eq. and Gg)*
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
33.3
39.2
40.0
41.2
41.4
42.9
43.1
45.6
Gg
33,278
39,218
39,991
41,190
41,357
42,898
43,082
45,559
* Totals exclude C02 emissions from making masonry cement from
clinker, which are accounted for under Lime Manufacture.
1 The C02 emissions related to the consumption of energy for cement manufacture are accounted for under C02 from Fossil Fuel Combustion in the
Energy chapter.
4-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
limestone) heated in the clinker kiln forms one mole of lime
(CaO) and one mole of C02:
CaC03 + heat = CaO + C02
C02 emissions were estimated by applying an emission
factor, in tons of C02 released per ton of clinker produced,
to the total amount of clinker produced. The emission
factor used in this analysis is the product of the average
lime fraction for clinker of 64.6 percent (IPCC 2000) and
a constant reflecting the mass of CO2 released per unit of
lime. This calculation yields an emission factor of 0.507 tons
of C02 per ton of clinker produced, which was determined
as follows:
44.01 g/mole CO2
er = 0.646 CaO x
56.08 g/mole CaO
= 0.507 tons C02/ton clinker
During clinker production, some of the clinker precursor
materials remain in the kiln as non-calcinated, partially
calcinated, or fully calcinated cement kiln dust (CKD). The
emissions attributable to the calcinated portion of the CKD
are not accounted for by the clinker emission factor. The
IPCC recommends that these additional CKD CO2 emissions
should be estimated as two percent of the C02 emissions
calculated from clinker production. Total cement production
emissions were calculated by adding the emissions from
clinker production to the emissions assigned to CKD (IPCC
2000).
Masonry cement requires additional lime over and
above the lime used in clinker production. In particular,
non-plasticizer additives such as lime, slag, and shale are
added to the cement, increasing its weight by approximately
five percent. Lime accounts for approximately 60 percent of
Manufacture. Thus, the activity data for masonry cement
production are shown in this chapter for informational
purposes only, and are not included in the cement emission
totals.
The 1990 through 2004 activity data for clinker and
masonry cement production (see Table 4-9) were obtained
through a personal communication with Hendrick Van Oss
(Van Oss 2005) of the USGS and through the USGS Mineral
Yearbook: Cement (USGS 1992, 1993, 1994, 1995, 1996,
1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004). Data
for 2004 clinker production were obtained from the USGS
Mineral Industry Summary: Cement(VSGS 2005). The data
were compiled by USGS through questionnaires sent to
domestic clinker and cement manufacturing plants.
Uncertainty
The uncertainties contained in these estimates are
primarily due to uncertainties in the lime content of clinker
and in the percentage of CKD recycled inside the clinker
kiln. Uncertainty is also associated with the amount of lime
added to masonry cement, but it is accounted for under the
Lime Manufacture source category. The lime content of
clinker varies from 64 to 66 percent. CKD loss can range
from 1.5 to eight percent depending upon plant specifications.
Additionally, some amount of C02 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
C02 in the atmosphere to create calcium carbonate. This
reaction only occurs in roughly the outer 0.2 inches of surface
Table 4-9: Cement Production (Gg)
this added weight. Thus, the additional lime is equivalent to
roughly 2.86 percent of the starting amount of the product,
since:
0.6 x 0.05/(1 + 0.05) = 2.86%
An emission factor for this added lime can then be
calculated by multiplying this 2.86 percent by the molecular
weight ratio of C02 to CaO (0.785) to yield 0.0224 metric
tons of additional C02 emitted for every metric ton of
masonry cement produced.
As previously mentioned, the C02 emissions from the
additional lime added during masonry cement production are
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Clinker
64,355
62,918
63,415
66,957
69,787
71,257
71,706
74,112
75,842
77,337
79,656
79,979
82,959
83,315
88,104
Masonry
3,209
2,856
3,093
2,975
3,283
3,603
3,469
3,634
3,989
4,375
4,332
4,450
4,449
4,737
5,300
accounted for in the section on C02 emissions from Lime
Industrial Processes 4-9
-------
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Cement Manufacture (Tg C02 Eq. and
Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Cement Manufacture C02 45.6
39.7 51.8 -13% +14%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
area. Because the amount of CO2 reabsorbed is thought to
be minimal, it was not estimated.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-10. Cement Manufacture CO2
emissions were estimated to be between 39.7 and 51.8 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 13 percent below and 14 percent above the
emission estimate of 45.6 Tg C02 Eq.
Recalculations Discussion
Activity data for 2003 were revised to reflect data
released after the publication of the 1990 through 2003
report. The revisions resulted in a less than one percent
increase in 2003 emissions.
4.3. Ammonia Manufacture and
Urea Application (IPCC Source
Category 2B1)
Emissions of C02 occur during the production of
synthetic ammonia, primarily through the use of natural gas as
a feedstock. One nitrogen production plant located in Kansas
is producing ammonia from petroleum coke feedstock. The
natural gas-based, naphtha-based, and petroleum coke-based
processes produce C02 and hydrogen (1HQ, the latter of which
is used in the production of ammonia. In some plants the C02
produced is captured and used to produce urea. The brine
electrolysis process for production of ammonia does not lead
to process-based C02 emissions.
There are five principal process steps in synthetic
ammonia production from natural gas feedstock. The primary
reforming step converts CH4 to C02, 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 C02. The secondary reforming step converts the
remaining CH4 feedstock to CO and C02. The CO in the
process gas from the secondary reforming step (representing
approximately 15 percent of the process gas) is converted to
C02 in the presence of a catalyst, water, and air in the shift
conversion step. C02 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 C02 is
included in a waste gas stream with other process impurities
and is absorbed by a scrubber solution. In regenerating the
scrubber solution, C02 is released.
The conversion process for conventional steam reforming
of CH4, including primary and secondary reforming and the
shift conversion processes, is approximately as follows:
(catalyst)
0.88 CH4+ 1.26 Air + 1.24 H20 -* 0.88 C02
N2 + 3 H2 -» 2 NH3
N2 + 3 H2
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 C02 produced in the production of
ammonia is emitted directly to the atmosphere. Both
ammonia and C02 are used as raw materials in the production
of urea [CO(NH2)2], which is another type of nitrogenous
fertilizer that contains carbon as well as nitrogen. The
chemical reaction that produces urea is:
2NH3 + C02 = NH2COONH4 = CO(NH2)2 + H20
The carbon in the urea that is produced and assumed to
be subsequently applied to agricultural land as a nitrogenous
fertilizer is ultimately released into the environment as CO2;
therefore, the C02 produced by ammonia production and
4-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
subsequently used in the production of urea does not change
overall C02 emissions. However, the C02 emissions are
allocated to the ammonia and urea production processes in
accordance to the amount of ammonia and urea produced.
Net emissions of C02 from ammonia manufacture in
2004 were 9.6 Tg CO2 Eq. (9,571 Gg), and are summarized
in Table 4-11 and Table 4-12. Emissions of CO2 from urea
application in 2004 totaled 7.3 Tg C02 Eq. (7,323Gg), and
are summarized in Table 4-11 and Table 4-12.
Methodology
The calculation methodology for non-combustion
C02 emissions from production of nitrogenous fertilizers
from natural gas feedstock is based on a C02 emission
factor published by the European Fertilizer Manufacturers
Association (EFMA). The C02 emission factor (1.2 metric
tons C02/metric ton NH3) is applied to the percent of total
annual domestic ammonia production from natural gas
feedstock. Emissions of C02 from ammonia production
are then adjusted to account for the use of some of the C02
produced from ammonia production as a raw material in
the production of urea. For each ton of urea produced, 8.8
of every 12 tons of CO2 are consumed and 6.8 of every 12
tons of ammonia are consumed. The C02 emissions reported
for ammonia production are therefore reduced by a factor
of 0.73 multiplied by total annual domestic urea production,
and that amount of C02 emissions is allocated to urea
fertilizer application. Total CO2 emissions resulting from
nitrogenous fertilizer production do not change as a result of
this calculation, but some of the C02 emissions are attributed
to ammonia production and some of the C02 emissions are
attributed to urea application.
The calculation of the total non-combustion C02
emissions from nitrogenous fertilizers accounts for CO2
emissions from the application of imported and domestically
produced urea. For each ton of imported urea applied, 0.73
tons of C02 are emitted to the atmosphere. The amount of
imported urea applied is calculated based on the net of urea
imports and exports.
All ammonia production and subsequent urea production
are assumed to be from the same process—conventional
catalytic reforming of natural gas feedstock, with the
exception of ammonia production from petroleum coke
feedstock at one plant located in Kansas. The C02 emission
factor for production of ammonia from petroleum coke is
based on plant specific data, wherein all carbon contained
in the petroleum coke feedstock that is not used for urea
production is assumed to be emitted to the atmosphere as
C02 (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 C02 emission
factor (3.57 metric tons C02/metric ton NH3) is applied to
the percent of total annual domestic ammonia production
from petroleum coke feedstock.
The emission factor of 1.2 metric ton CO2/metric ton
NH3 for production of ammonia from natural gas feedstock
was taken from the EFMA Best Available Techniques
publication, Production of Ammonia (EFMA 1995). The
EFMA reported an emission factor range of 1.15 to 1.30
Table 4-11: C02 Emissions from Ammonia Manufacture and Urea Application (Tg C02 Eq.)
Source
Ammonia Manufacture
Urea Application
Total
1990
12.6
6.8
19.3
1998
14.2
7.7
21.9
1999
12.9
7.7
20.6
2000
12.1
7.5
19.6
2001
9.3
7.4
16.7
2002
10.5
8.0
18.5
2003
8.8
6.5
15.3
2004
9.6
7.3
16.9
Table 4-12: C02 Emissions from Ammonia Manufacture and Urea Application (Gg)
Source
Ammonia Manufacture
Urea Application
Total
1990
12,553
6,753
19,306
1998
14,215
7,719
21,934
1999
12,948
7,667
20,615
2000
12,128
7,488
19,616
2001
9,321
7,398
16,719
2002
10,501
8,010
18,511
2003
8,815
6,463
15,278
2004
9,571
7,323
16,894
Industrial Processes 4-11
-------
metric ton C02/metric ton NH3, with 1.2 metric ton CO2/
metric ton NH3 as a typical value. The EFMA reference also
indicates that more than 99 percent of the CH4 feedstock
to the catalytic reforming process is ultimately converted
to C02. The emission factor of 3.57 metric ton C02/metric
ton NH3 for production of ammonia from petroleum coke
feedstock was developed from plant-specific ammonia
production data and petroleum coke feedstock utilization
data for the ammonia plant located in Kansas (Bark 2004).
Ammonia and urea production data (see Table 4-13) were
obtained from Coffey ville Resources (Coffey ville 2005) and
the Census Bureau of the U.S. Department of Commerce
(U.S. Census Bureau 1991 through 2005) as reported in
Current Industrial Reports Fertilizer Materials and Related
Products annual and quarterly reports. Import and export data
for urea were obtained from the U.S. Census Bureau Current
Industrial Reports Fertilizer Materials and Related Products
annual reports (U.S. Census Bureau) for 1997 through 2004,
The Fertilizer Institute (TFI 2002) for 1993 through 1996,
and the United States International Trade Commission
Interactive Tariff and Trade DataWeb (U.S. ITC 2002) for
1990 through 1992 (see Table 4-13).
Uncertainty
The uncertainties presented in this section are primarily
due to how accurately the emission factor used represents
an average across all ammonia plants using natural gas
feedstock. The EFMA reported an emission factor range
of 1.15 to 1.30 ton CO2/ton NH3, with 1.2 ton CO2/ton
NH3 reported as a typical value. The actual emission factor
depends upon the amount of air used in the ammonia
production process, with 1.15 ton CO2/ton NH3 being the
approximate stoichiometric minimum that is achievable for
the conventional reforming process. By using natural gas
consumption data for each ammonia plant, more accurate
estimates of C02 emissions from ammonia production could
be calculated. However, these consumption data are often
considered confidential. Also, natural gas is consumed at
ammonia plants both as a feedstock to the reforming process
and for generating process heat and steam. Natural gas
consumption data, if available, would need to be divided
into feedstock use (non-energy) and process heat and steam
(fuel) use, as C02 emissions from fuel use and non-energy
use are calculated separately.2
Table 4-13: Ammonia Production, Urea Production, and Urea Net Imports (Gg)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Ammonia Production
15,425
15,576
16,261
15,599
16,211
15,788
16,260
16,231
16,761
15,728
14,342
11,092
12,577
10,279
10,939
Urea Production
8,124
7,373
8,142
7,557
7,584
7,363
7,755
7,430
8,042
8,080
6,969
6,080
7,038
5,783
5,755
Urea Net Imports
1,086
648
656
2,305
2,249
2,055
1,051
1,600
2,483
2,374
3,241
4,008
3,884
3,030
4,231
2 It appears that the IPCC emission factor for ammonia production of 1.5 ton CO2 per ton ammonia may include both C02 emissions from the natural
gas feedstock to the process and some C02 emissions from the natural gas used to generate process heat and steam for the process. Table 2-5, Ammonia
Production Emission Factors, in Volume 3 of the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories Reference Manual(lPCC 1997)
includes two emission factors, one reported for Norway and one reported for Canada. The footnotes to the table indicate that the factor for Norway does
not include natural gas used as fuel but that it is unclear whether the factor for Canada includes natural gas used as fuel. However, the factors for Norway
and Canada are nearly identical (1.5 and 1.6 tons CO2per ton ammonia, respectively) and it is likely that if one value does not include fuel use, the other
value also does not. For the conventional steam reforming process, however, the EFMA reports an emission factor range for feedstock C02 of 1.15 to
1.30 ton per ton (with atypical value of 1.2 ton per ton) and an emission factor for fuel CO2 of 0.5 tons per ton. This corresponds to a total C02 emission
factor for the ammonia production process, including both feedstock C02 and process heat C02, of 1.7 ton per ton, which is closer to the emission factors
reported in the IPCC 1996 Reference Guidelines than to the feedstock-only C02 emission factor of 1.2 ton CO2 per ton ammonia reported by the EFMA.
Because it appears that the emission factors cited in the IPCC Guidelines may actually include natural gas used as fuel, we use the 1.2 tons/ton emission
factor developed by the EFMA.
4-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Natural gas feedstock consumption data for the U.S.
ammonia industry as a whole is available from the Energy
Information Administration (EIA) Manufacturers Energy
Consumption Survey (MEGS) for the years 1985, 1988,
1991, 1994 and 1998 (EIA 1994, 1998). These feedstock
consumption data collectively correspond to an effective
average emission factor of 1.0 ton CO2/ton NH3, which
appears to be below the stoichiometric minimum that is
achievable for the conventional steam reforming process. The
EIA data for natural gas consumption for the years 1994 and
1998 correspond more closely to the CO2 emissions calculated
using the EFMA emission factor than do data for previous
years. The 1994 and 1998 data alone yield an effective
emission factor of 1.1 ton CO2/ton NH3, corresponding to
C02 emissions estimates that are approximately 1.5 Tg CO2
Eq. below the estimates calculated using the EFMA emission
factor of 1.2 ton CO2/ton NH3. Natural gas feedstock
consumption data are not available from EIA for other years,
and data for 1991 and previous years may underestimate
feedstock natural gas consumption, and therefore the EFMA
emission factor was used to estimate C02 emissions from
ammonia production, rather than EIA data.
All ammonia production and subsequent urea production
was assumed to be 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.
Research indicates that there is only one U.S. plant that
manufactures ammonia from petroleum coke. C02 emissions
from this plant are explicitly accounted for in the Inventory
estimates. No data for ammonia plants using naphtha or
other feedstocks other than natural gas have been identified.
Therefore, all other C02 emissions from ammonia plants are
calculated using the emission factor for natural gas feedstock.
However, actual emissions may differ because processes other
than catalytic steam reformation and feedstocks other than
natural gas may have been used for ammonia production. Urea
is also used for other purposes than as a nitrogenous fertilizer.
It was assumed that 100 percent of the urea production and net
imports are used as fertilizer or in otherwise emissive uses.
It is also assumed that ammonia and urea are produced at
collocated plants from the same natural gas raw material.
Such recovery may or may not affect the overall estimate
of C02 emissions depending upon the end use to which
the recovered C02 is applied. For example, research has
identified one ammonia production plant that is recovering
byproduct C02 for use in EOR. Such CO2 is currently
assumed to remain sequestered (see the section of this
chapter on C02 Consumption); however, time series data
for the amount of C02 recovered from this plant are not
available and therefore all of the C02 produced by this plant
is assumed to be emitted to the atmosphere and allocated
to Ammonia Manufacture. Further research is required to
determine whether byproduct C02 is being recovered from
other ammonia production plants for application to end uses
that are not accounted for elsewhere.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-14. Ammonia Manufacture and
Urea Application CO2 emissions were estimated to be between
15.5 and 18.3 Tg CO2 Eq. at the 95 percent confidence level
(or in 19 out of 20 Monte Carlo Stochastic Simulations). This
indicates a range of approximately 8 percent below and 8
percent above the emission estimate of 16.9 Tg CO2 Eq.
Recalculations Discussion
Estimates of C02 emissions from ammonia manufacture
and urea application for the years 2002 and 2003 were
revised to reflect updated data from the U.S. Census Bureau
and new data sources from the Coffeyville Nitrogen Plant.
These changes resulted in a decrease in C02 emissions from
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Ammonia Manufacture and Urea
Application (Tg C02 Eq. and Percent)
2004 Emission
Estimate Uncertainty Range Relative to Emission
Source Gas (Tg C02 Eq.) (Tg C02 Eq.)
Lower Bound Upper Bound Lower Bound
Ammonia Manufacture and
Urea Application C02 16.9 15.5 18.3 -8%
Estimate3
(%)
Upper Bound
+8%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-13
-------
ammonia manufacture of 0.1 Tg CO2 Eq. (1 percent) for 2002
and 0.3 Tg C02 Eq. (3 percent) for 2003.
Planned Improvements
The United States recognizes that the Tier 2 methodology
is preferred for estimating C02 emissions from ammonia
manufacture. Historically, efforts have been made to acquire
feedstock data for this source category however the relevant
data were not available. In addition to some of the future
work noted in the Uncertainty section, additional planned
improvements for this source category include developing
a plan to determine the feasibility of acquiring the relevant
data for the Tier 2 assessment. If successful, the results will
be included in future inventory submissions.
4.4. Lime Manufacture (IPCC
Source Category 2A2)
Lime is an important manufactured product with many
industrial, chemical, and environmental applications. Its
major uses are in steel making, flue gas desulfurization
(FGD) systems at coal-fired electric power plants,
construction, and water purification. Lime has historically
ranked fifth in total production of all chemicals in the
United States. For U.S. operations, the term "lime" actually
refers to a variety of chemical compounds. These include
calcium oxide (CaO), or high-calcium quicklime; calcium
hydroxide (Ca(OH)2), or hydrated lime; dolomitic quicklime
([CaOMgO]); and dolomitic hydrate ([Ca(OH)2«MgO] or
[Ca(OH)2-Mg(OH)2]).
Lime production involves three main processes: stone
preparation, calcination, and hydration. C02 is generated
during the calcination stage, when limestone—mostly
calcium carbonate (CaC03)—is roasted at high temperatures
in a kiln to produce CaO and C02. The C02 is given off as
a gas and is normally emitted to the atmosphere. Some of
the C02 generated during the production process, however,
is recovered at some facilities for use in sugar refining and
precipitated calcium carbonate (PCC)3 production. It is also
important to note that, for certain applications, lime reabsorbs
C02 during use (see Uncertainty, below).
Lime production in the United States—including
Puerto Puco—was reported to be 20,027 thousand metric
tons in 2004 (USGS 2005). This resulted in estimated CO2
emissions of 13.7 Tg CO2 Eq. (or 13,698 Gg) (see Table
4-15 and Table 4-16).
At the turn of the 20th century, over 80 percent of lime
consumed in the United States went for construction uses.
The contemporary lime market is distributed across four
end-use categories as follows: metallurgical uses, 37 percent;
environmental uses, 28 percent; chemical and industrial uses,
21 percent; construction uses, 13 percent; and refractory
dolomite, one percent. In the construction sector, hydrated
lime is still used to improve durability in plaster, stucco,
and mortars. In 2004, the amount of hydrated lime used for
traditional building remained unchanged from 2003 (USGS
2005).
Lime production in 2004 increased over four percent
from 2003, the second annual increase in production after four
Table 4-15: Net C02 Emissions from Lime Manufacture
(Tg C02 Eq.)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
11.2
13.9
13.5
13.3
12.8
12.3
13.0
13.7
Table 4-16: C02 Emissions from Lime Manufacture (Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Potential
11,735
14,980
14,651
14,554
13,946
13,360
14,136
14,823
Recovered*
(493)
(1,061)
(1,188)
(1,233)
(1,118)
(1,051)
(1,149)
(1,125)
Net Emissions
11,242
13,919
13,473
13,322
12,828
12,309
12,987
13,698
* For sugar refining and precipitated calcium carbonate production.
Note: Totals may not sum due to independent rounding. Parentheses
indicate negative values.
3 Precipitated calcium carbonate is a specialty filler used in premium-quality coated and uncoated papers.
4-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
years of decline. Overall, from 1990 to 2004, lime production
has increased by 26 percent. The increase in production is
attributed in part to growth in demand for environmental
applications, especially flue gas desulfurization technologies.
In 1993, EPA completed regulations under the Clean Air Act
capping sulfur dioxide (SO2) emissions from electric utilities.
Lime scrubbers' high efficiencies and increasing affordability
have allowed the flue gas desulfurization end-use to expand
significantly over the years. Phase II of the Clean Air Act
Amendments, which went into effect on January 1, 2000,
remains the driving force behind the growth in the flue gas
desulfurization market (USGS 2003).
Methodology
During the calcination stage of lime manufacture, C02
is given off as a gas and normally exits the system with
the stack gas. To calculate emissions, the amounts of high-
calcium and dolomitic lime produced were multiplied by
their respective emission factors. The emission factor is the
product of a constant reflecting the mass of CO2 released per
unit of lime and the average calcium plus magnesium oxide
(CaO • MgO) content for lime (95 percent for both types of
lime). The emission factors were calculated as follows:
For high-calcium lime:
[(44.01 g/mole CO2) +-
(56.08 g/mole CaO)] x (0.95 CaO/lime) =
0.75 g C02/g lime
For dolomitic lime:
[(88.02 g/mole C02) +-
(96.39 g/mole CaO)] x (0.95 CaO/lime) =
0.87 g C02/g lime
Production is adjusted to remove the mass of
chemically combined water found in hydrated lime, using
the midpoint of default ranges provided by the IPCC
Good Practice Guidance (IPCC 2000). These factors set
the chemically combined water content to 27 percent for
high-calcium hydrated lime, and 24 percent for dolomitic
hydrated lime.
Lime production in the United States was 20,027
thousand metric tons in 2004 (USGS 2005), resulting in
potential C02 emissions of 14.8 Tg CO2 Eq. Some of the
C02 generated during the production process, however, was
recovered for use in sugar refining and PCC production.
Combined lime manufacture by these producers was
1,887 thousand metric tons in 2004. It was assumed that
approximately 80 percent of the C02 involved in sugar
refining and PCC was recovered, resulting in actual CO2
emissions of 13.7 Tg CO2 Eq.
The activity data for lime manufacture and lime
consumption by sugar refining and PCC production for
1990 through 2004 (see Table 4-17) were obtained from
USGS (1992 through 2004). Hydrated lime production is
reported separately in Table 4-18. The CaO and CaO'MgO
contents of lime were obtained from the IPCC Good Practice
Guidance (IPCC 2000). Since data for the individual lime
types (high calcium and dolomitic) was not provided prior
Table 4-17: Lime Production and Lime Use for Sugar Refining and PCC (Gg)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
High-Calcium Production3
12,947
12,840
13,307
13,741
14,274
15,193
15,856
16,120
16,750
16,110
15,850
15,630
14,900
16,040
16,500
Dolomitic Production* "
2,895
2,838
2,925
3,024
3,116
3,305
3,434
3,552
3,423
3,598
3,621
3,227
3,051
3,124
3,527
Use for Sugar Refining and PCC
826
964
1,023
1,279
1,374
1,503
1,429
1,616
1,779
1,992
2,067
1,874
1,762
1,926
1,887
a Includes hydrated lime.
b Includes dead-burned dolomite.
Industrial Processes 4-15
-------
Table 4-18: Hydra ted Lime Production (Gg)
Year High-Calcium Hydrate
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
1,781
1,841
1,892
1,908
1,942
2,027
1,858
1,820
1,950
2,010
1,550
2,030
1,500
2,140
2,300
Dolomitic Hydrate
319
329
338
342
348
363
332
352
383
298
421
447
431
464
337
to 1997, total lime production for 1990 through 1996 was
calculated according to the three year distribution from
1997 to 1999. For sugar refining and PCC, it was assumed
that 100 percent of lime manufacture and consumption was
high-calcium, based on communication with the National
Lime Association (Males 2003).
Uncertainty
The uncertainties contained in these estimates can be
attributed to slight differences in the chemical composition
of these products. Although the methodology accounts for
various formulations of lime, it does not account for the
trace impurities found in lime, such as iron oxide, alumina,
and silica. Due to differences in the limestone used as a raw
material, a rigid specification of lime material is impossible.
As a result, few plants manufacture lime with exactly the
same properties.
In addition, a portion of the C02 emitted during lime
manufacture will actually be reabsorbed when the lime is
consumed. As noted above, lime has many different chemical,
industrial, environmental, and construction applications. In
many processes, C02 reacts with the lime to create calcium
carbonate (e.g., water softening). C02 reabsorption rates
vary, however, depending on the application. For example,
100 percent of the lime used to produce precipitated calcium
carbonate reacts with C02; whereas most of the lime used
in steel making reacts with impurities such as silica, sulfur,
and aluminum compounds. A detailed accounting of lime use
in the United States and further research into the associated
processes are required to quantify the amount of C02 that
is reabsorbed.4
In some cases, lime is generated from calcium carbonate
by-products at pulp mills and water treatment plants.5 The
lime generated by these processes is not included in the
USGS data for commercial lime consumption. In the
pulping industry, mostly using the Kraft (sulfate) pulping
process, lime is consumed in order to causticize a process
liquor (green liquor) composed of sodium carbonate and
sodium sulfide. The green liquor results from the dilution of
the smelt created by combustion of the black liquor where
biogenic carbon is present from the wood. Kraft mills
recover the calcium carbonate "mud" after the causticizing
operation and calcine it back into lime—thereby generating
C02—for reuse in the pulping process. Although
this re-generation of lime could be considered a lime
manufacturing process, the C02 emitted during this process
is mostly biogenic in origin, and therefore is not included
in Inventory totals.6
In the case of water treatment plants, lime is used in
the softening process. Some large water treatment plants
may recover their waste calcium carbonate and calcine it
into quicklime for reuse in the softening process. Further
research is necessary to determine the degree to which
lime recycling is practiced by water treatment plants in
the United States.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table4-19. Lime CO2 emissions
were estimated to be between 12.6 and 14.8 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 8 percent below and 8 percent above the
emission estimate of 13.7 Tg CO2 Eq.
4 Representatives of the National Lime Association estimate that CO2 reabsorption that occurs from the use of lime may offset as much as a quarter of the
C02 emissions from calcination (Males 2003).
5 Some carbide producers may also regenerate lime from their calcium hydroxide by-products, which does not result in emissions of CO2. In making calcium
carbide, quicklime is mixed with coke and heated in electric furnaces. The regeneration of lime in this process is done using a waste calcium hydroxide
(hydrated lime) [CaC2 + 2H20 -* C2H2 + Ca(OH) 2], not calcium carbonate [CaC03]. Thus, the calcium hydroxide is heated in the kiln to simply expel
the water [Ca(OH)2 + heat -* CaO + H20] and no C02 is released.
6 Based on comments submitted by and personal communication with Dr. Sergio F. Galeano, Geortia-Pacific Corporation.
4-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-19: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lime Manufacture (Tg C02 Eq. and
Percent)
Source
Lime Manufacture
Gas
C02
2004 Emission
Estimate
(Tg C02 Eq.)
13.7
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound
12.6 14.8
Lower Bound Upper Bound
-8% +8%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
An inconsistency with the appropriate number of
significant digits established by the IPCC for the water
contents of hydrated lime was identified and corrected for the
entire time series. The adjustment increased annual emission
estimates throughout the time series by less than one percent
relative to the previous Inventory report. The 2003 data used
to estimate C02 recovery from PCC and sugar refining were
updated to reflect revisions to USGS data, but the revision
did not result in a net change in C02 recovery, thus net lime
emissions were unchanged for 2003.
4.5. Limestone and Dolomite Use
(IPCC Source Category 2A3)
Limestone (CaCO3) and dolomite (CaC03MgC03)7
are basic raw materials used by a wide variety of industries,
including construction, agriculture, chemical, metallurgy,
glass manufacture, and environmental pollution control.
Limestone is widely distributed throughout the world
in deposits of varying sizes and degrees of purity. Large
deposits of limestone occur in nearly every state in the United
States, and significant quantities are extracted for industrial
applications. For some of these applications, limestone is
sufficiently heated during the process to generate CO2 as a
by-product. Examples of such applications include limestone
used as a flux or purifier in metallurgical furnaces, as a
sorbent in flue gas desulfurization systems for utility and
industrial plants, or as a raw material in glass manufacturing
and magnesium production.
In 2004, approximately 10,487 thousand metric tons
of limestone and 4,373 thousand metric tons of dolomite
were consumed for these applications. Overall, usage of
limestone and dolomite resulted in aggregate C02 emissions
of 6.7 Tg C02 Eq. (6,702 Gg) (see Table 4-20 and Table
4-21). Emissions in 2004 increased 42 percent from the
previous year and have increased 21 percent overall from
1990 through 2004.
Methodology
C02 emissions were calculated by multiplying the
quantity of limestone or dolomite consumed by the average
carbon content, approximately 12.0 percent for limestone
and 13.2 percent for dolomite (based on stoichiometry).
Table 4-20: C02 Emissions from Limestone & Dolomite Use (Tg C02 Eq.)
Activity
Flux Stone
Glass Making
FGD
Magnesium Production
Other Miscellaneous Uses
Total
1990
3.0
0.2
1.4
0.1
0.8
5.5
1998
5.1
0.2
1.2
0.1
0.9
7.4
1999
6.0
0
1.2
0.1
0.7
8.1
2000
2.8
0.4
1.8
0.1
0.9
6.0
2001
2.5
0.1
2.6
0.1
0.5
5.7
2002
2.4
0.2
2.8
0.0
0.7
5.9
2003
2.1
0.3
1.9
0.0
0.4
4.7
2004
4.1
0.4
1.9
0.0
0.4
6.7
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.
7 Limestone and dolomite are collectively referred to as limestone by the industry, and intermediate varieties are seldom distinguished.
Industrial Processes 4-17
-------
Table 4-21: C02 Emissions from Limestone & Dolomite Use (Gg)
Activity
Flux Stone
Limestone
Dolomite
Glass Making
Limestone
Dolomite
FGD
Magnesium Production
Other Miscellaneous Uses
Total
1990
2,999
2,554
446
217
189
28
1,433
64
819
5,533
1998
5,132
4,297
835
157
65
91
1,230
73
858
7,449
1999
6,030
4,265
1,765
0
0
0
1,240
73
713
8,057
2000
2,830
1,810
1,020
368
368
0
1,774
73
916
5,960
2001
2,514
1,640
874
113
113
0
2,551
53
501
5,733
2002
2,405
1,330
1,075
61
61
0
2,766
0
652
5,885
2003
2,072
904
1,168
337
337
0
1,932
0
380
4,720
2004
4,112
2,023
2,088
350
350
0
1,871
0
369
6,702
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.
This assumes that all carbon is oxidized and released. This
methodology was used for flux stone, glass manufacturing,
flue gas desulfurization systems, chemical stone, mine
dusting or acid water treatment, acid neutralization, and
sugar refining and then converting to CO2 using a molecular
weight ratio.
Traditionally, the production of magnesium metal
was the only other use of limestone and dolomite that
produced C02 emissions. At the start of 2001, there were
two magnesium production plants operating in the United
States and they used different production methods. One plant
produced magnesium metal using a dolomitic process that
resulted in the release of C02 emissions, while the other
plant produced magnesium from magnesium chloride using
a C02-emissions-free process called electrolytic reduction.
However, the plant utilizing the dolomitic process ceased its
operations prior to the end of 2001, so beginning in 2002
there were no emissions from this particular sub-use.
Consumption data for 1990 through 2004 of limestone
and dolomite used for flux stone, glass manufacturing, flue
gas desulfurization systems, chemical stone, mine dusting
or acid water treatment, acid neutralization, and sugar
refining (see Table 4-22) were obtained from personal
communication with Valentine Tepordei of the USGS
(Tepordei 2005) and in the USGS Minerals Yearbook:
Crushed Stone Annual Report (USGS 1993,1995a, 1995b,
1996a, 1997a, 1998a, 1999a, 2000a, 2001a, 2002a, 2003a,
2004a). The production capacity data for 1990 through
2003 of dolomitic magnesium metal (see Table 4-23) also
came from the USGS (1995c, 1996b, 1997b, 1998b, 1999b,
2000b, 2001b, 2002b, 2003b, 2004b, 2005). The last plant in
the United States that used the dolomitic production process
for magnesium metal closed in 2001. The USGS does
not mention this process in the 2004 Minerals Yearbook:
Magnesium', therefore, it is assumed that this process
continues to be non-existent in the United States (USGS
Table 4-22: Limestone and Dolomite Consumption (Thousand Metric Tons)
Activity
Flux Stone
Limestone
Dolomite
Glass Making
Limestone
Dolomite
FGD
Other Miscellaneous Uses
Total
1990
6,738
5,804
933
489
430
59
3,258
1,835
12,319
1998
11,514
9,767
1,748
340
149
191
2,795
1,933
16,582
1999
13,390
9,694
3,696
0
0
0
2,819
1,620
17,830
2000
6,249
4,114
2,135
836
836
0
4,031
2,081
13,197
2001
5,558
3,727
1,831
258
258
0
5,798
1,138
12,751
2002
5,275
3,023
2,252
139
139
0
6,286
1,483
13,183
2003
4,501
2,055
2,466
765
765
0
4,390
863
10,520
2004
8,971
4,599
4,373
796
796
0
4,253
840
14,859
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.
4-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-23: Dolomitic Magnesium Metal Production
Capacity (Metric Tons)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Production Capacity
35,000
35,000
14,909
12,964
21,111
22,222
40,000
40,000
40,000
40,000
40,000
29,167
0
0
0
Note: Production capacity for 2002, 2003, and 2004 amounts to
zero because the last U.S. production plant employing the dolomitic
process shutdown mid-2001 (USGS 2002).
2005). 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.
Finally, there is a large quantity of crushed stone
reported to the USGS under the category "unspecified uses."
A portion of this consumption is believed to be limestone
or dolomite used for emissive end uses. The quantity listed
for "unspecified uses" was, therefore, allocated to each
reported end-use according to each end uses fraction of total
consumption in that year.8
Uncertainty
The uncertainty levels presented in this section arise
in part due to variations in the chemical composition of
limestone. In addition to calcium carbonate, limestone may
contain smaller amounts of magnesia, silica, and sulfur. The
exact specifications for limestone or dolomite used as flux
stone vary with the pyrometallurgical process, the kind of
ore processed, and the final use of the slag. Similarly, the
quality of the limestone used for glass manufacturing will
depend on the type of glass being manufactured.
The estimates below also account for uncertainty
associated with activity data. Much of the limestone
consumed in the United States is reported as "other
unspecified uses;" therefore, it is difficult to accurately
allocate this unspecified quantity to the correct end-uses.
Also, some of the limestone reported as "limestone" is
believed to actually be dolomite, which has a higher carbon
content. Additionally, there is significant inherent uncertainty
associated with estimating withheld data points for specific
end uses of limestone and dolomite. Lastly, the uncertainty
of the estimates for limestone used in glass making is
especially high. Large fluctuations in reported consumption
exist, reflecting year-to-year changes in the number of survey
responders. The uncertainty resulting from a shifting survey
population is exacerbated by the gaps in the time series of
reports. However, since glass making accounts for a small
percent of consumption, its contribution to the overall
emissions estimate is low.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-24. Limestone and Dolomite Use
C02 emissions were estimated to be between 6.2 and 7.2 Tg
C02 Eq. at the 95 percent confidence level (or in 19 out of 20
Monte Carlo Stochastic Simulations). This indicates a range
of approximately 7 percent below and 8 percent above the
emission estimate of 6.7 Tg C02 Eq.
8 This approach was recommended by USGS.
Industrial Processes 4-19
-------
Table 4-24: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Limestone and Dolomite Use
(Tg C02 Eq. and Percent)
Source
2004 Emission
Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Limestone and Dolomite Use
CO,
6.7
6.2
7.2
-7%
+ 8%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4.6. Soda Ash Manufacture and
Consumption (IPCC Source Category
2A4)
Soda ash (sodium carbonate, Na2C03) is a white
crystalline solid that is readily soluble in water and strongly
alkaline. Commercial soda ash is used as a raw material in a
variety of industrial processes and in many familiar consumer
products such as glass, soap and detergents, paper, textiles,
and food. It is used primarily as an alkali, either in glass
manufacturing or simply as a material that reacts with and
neutralizes acids or acidic substances. Internationally, two
types of soda ash are produced—natural and synthetic. The
United States produces only natural soda ash and is second
only to China in total soda ash-production. Trona is the
principal ore from which natural soda ash is made.
Only three states produce natural soda ash: Wyoming,
California, and Colorado. Of these three states, only net
emissions of C02 from Wyoming were calculated. This
difference is a result of the production processes employed in
each state.9 During the production process used in Wyoming,
trona ore is treated to produce soda ash. C02 is generated as
a by-product of this reaction, and is eventually emitted into
the atmosphere. In addition, C02 may also be released when
soda ash is consumed.
In 2004, C02 emissions from the manufacture of soda
ash from trona were approximately 1.6 Tg CO2 Eq. (1,607
Gg). Soda ash consumption in the United States generated
2.6 Tg C02 Eq. (2,598 Gg) in 2004. Total emissions from
soda ash manufacture in 2004 were 4.2 Tg C02 Eq. (4,205
Gg) (see Table 4-25 and Table 4-26). Emissions have
fluctuated since 1990. These fluctuations were strongly
related to the behavior of the export market and the U.S.
economy. Emissions in 2004 increased by approximately 2
percent from the previous year, and have increased overall
by approximately 2 percent since 1990.
Table 4-25: C02 Emissions from Soda Ash Manufacture
and Consumption (Tg C02 Eq.)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Manufacture
1.4
1.6
1.5
1.5
1.5
1.5
1.5
1.6
Consumption
2.7
2.7
2.7
2.7
2.6
2.7
2.6
2.6
Total
4.1
4.3
4.2
4.2
4.1
4.1
4.1
4.2
Note: Totals may not sum due to independent rounding.
Table 4-26: C02 Emissions from Soda Ash Manufacture
and Consumption (Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Manufacture
1,431
1,607
1,548
1,529
1,500
1,470
1,509
1,607
Consumption
2,710
2,718
2,668
2,652
2,648
2,668
2,602
2,598
Total
4,141
4,324
4,217
4,181
4,147
4,139
4,111
4,205
Note: Totals may not sum due to independent rounding.
9 In California, soda ash is manufactured using sodium carbonate-bearing brines instead of trona ore. To extract the sodium carbonate, the complex brines
are first treated with CO2 in carbonation towers to convert the sodium carbonate into sodium bicarbonate, which then precipitates from the brine solution.
The precipitated sodium bicarbonate is then calcined back into sodium carbonate. Although C02 is generated as a by-product, the C02 is recovered and
recycled for use in the carbonation stage and is not emitted.
4-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
The United States represents about one-fourth of total
world soda ash output. The distribution of soda ash by
end-use in 2004 was glass making, 50 percent; chemical
production, 26 percent; soap and detergent manufacturing,
11 percent; distributors, 5 percent; flue gas desulfurization,
1 percent; water treatment, pulp and paper production, 2
percent each; and miscellaneous, 4 percent (USGS 2005).
Although the United States continues to be a major
supplier of world soda ash, China's soda ash production
surpassed the United States in 2003, and continued to be
higher than the United States in 2004. The trend is expected
to continue, as will the strict competition in Asian markets.
The world market for soda ash is expected to grow 2.0 to 2.5
percent annually (USGS 2005).
Methodology
During the production process, trona ore is calcined in a
rotary kiln and chemically transformed into a crude soda ash
that requires further processing. C02 and water are generated
Table 4-27: Soda Ash Manufacture and Consumption (Gg)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Manufacture*
14,700
14,700
14,900
14,500
14,600
16,500
16,300
17,100
16,500
15,900
15,700
15,400
15,100
15,500
16,500
Consumption
6,530
6,280
6,320
6,280
6,260
6,500
6,390
6,480
6,550
6,430
6,390
6,380
6,430
6,270
6,260
1 Soda ash manufactured from trona ore only.
as by-products of the calcination process. C02 emissions
from the calcination of trona can be estimated based on the
following chemical reaction:
2(Na3H(C03)2 x 2H20) -* 3Na2C03
[trona] [soda ash]
5H,0 + CO,
Based on this formula, approximately 10.27 metric tons
of trona are required to generate one metric ton of C02. Thus,
the 16.5 million metric tons of trona mined in 2004 for soda
ash production (USGS 2005) resulted in CO2 emissions of
approximately 1.6 Tg CO2 Eq. (1,607 Gg).
Once manufactured, most soda ash is consumed in
glass and chemical production, with minor amounts in soap
and detergents, pulp and paper, flue gas desulfurization and
water treatment. As soda ash is consumed for these purposes,
additional C02 is usually emitted. In these applications, it is
assumed that one mole of carbon is released for every mole
of soda ash used. Thus, approximately 0.113 metric tons of
carbon (or 0.415 metric tons of CO2) are released for every
metric ton of soda ash consumed.
The activity data for trona production and soda ash
consumption (see Table 4-27) were taken from USGS (1994
through 2004). Soda ash manufacture and consumption data
were collected by the USGS from voluntary surveys of the
U.S. soda ash industry.
Uncertainty
Emission estimates from soda ash manufacture
have relatively low associated uncertainty levels in that
reliable and accurate data sources are available for the
emission factor and activity data. The primary source of
uncertainty, however, results from the fact that emissions
from soda ash consumption are dependent upon the type of
processing employed by each end-use. Specific information
characterizing the emissions from each end-use is limited.
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Soda Ash Manufacture and
Consumption (Tg C02 Eq. and Percent)
Source
2004 Emission
Estimate
Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound
Lower Bound Upper Bound
Soda Ash Manufacture and
Consumption
CO,
4.2
3.9
4.5
+7%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-21
-------
Therefore, there is uncertainty surrounding the emission
factors from the consumption of soda ash.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-28. Soda Ash Manufacture and
Consumption C02 emissions were estimated to be between
3.9 and 4.5 Tg CO2 Eq. at the 95 percent confidence level (or
in 19 out of 20 Monte Carlo Stochastic Simulations). This
indicates a range of approximately 7 percent below and 7
percent above the emission estimate of 4.2 Tg C02 Eq.
Planned Improvements
Emissions from soda ash production in Colorado, which
is produced using the nahcolite production process, will be
investigated for inclusion in future inventories.
4.7. Titanium Dioxide Production
(IPCC Source Category 2B5)
Titanium dioxide (Ti02) is a metal oxide manufactured
from titanium ore, and is principally used as a pigment.
Titanium dioxide is a principal ingredient in white paint,
and is also used as a pigment in the manufacture of white
paper, foods, and other products. There are two processes for
making Ti02: the chloride process and the sulfate process.
The chloride process uses petroleum coke and chlorine as raw
materials and emits process-related C02. The sulfate process
does not use petroleum coke or other forms of carbon as a
raw material and does not emit C02.
The chloride process is based on the following chemical
reactions:
2FeTi03 + 7C12 + 3C -* 2TiCl4 + 2FeCl3 + 3C02
2TiCl4 + 202 -* 2Ti02 + 4C12
Table 4-29: C02 Emissions from Titanium Dioxide (Tg
C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
1.3
1,308
1998
1999
2000
2001
2002
2003
2004
1.8
1.9
1.9
1.9
2.0
2.0
2.3
1,819
1,853
1,918
1,857
1,997
2,013
2,259
The carbon in the first chemical reaction is provided
by petroleum coke, which is oxidized in the presence of
the chlorine and FeTi03 (the Ti-containing ore) to form
C02. The majority of U.S. TiO2 was produced in the United
States through the chloride process, and a special grade of
petroleum coke is manufactured specifically for this purpose.
Emissions of C02 from Ti02 production in 2004 were 2.3
Tg C02 Eq. (2,259 Gg), an increase of 11 percent from the
previous year and 73 percent from 1990, due to increasing
production within the industry (see Table 4-29).
Methodology
Emissions of C02 fromTi02 production were calculated
by multiplying annual Ti02 production by chloride-process-
specific emission factors.
Data were obtained for the total amount of Ti02 produced
each year, and it was assumed that 97 percent of the total
production in 2004 was produced using the chloride process.
It was assumed that Ti02 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. An
emission factor of 0.4 metric tons C/metric ton Ti02 was
applied to the estimated chloride process production. It was
assumed that all Ti02 produced using the chloride process
was produced using petroleum coke, although some Ti02
may have been produced with graphite or other carbon
inputs. The amount of petroleum coke consumed annually
in Ti02 production was calculated based on the assumption
that petroleum coke used in the process is 90 percent carbon
and 10 percent inert materials.
The emission factor for the Ti02 chloride process was
taken from the report, Everything You 've Always Wanted to
Know about Petroleum Coke (Onder and Bagdoyan 1993).
Titanium dioxide production data for 1990 through 2004 (see
Table 4-30) were obtained from personal communication
with Joseph Gambogi, USGS Commodity Specialist, of the
USGS (Gambogi 2005) and through the Minerals Yearbook:
Titanium Annual Report (USGS 1991 through 2003). Data
for the percentage of the total Ti02 production capacity
that is chloride-process for 1994 through 2002 were also
taken from the USGS Minerals Yearbook and from Joseph
Gambogi for 2004. Percentage chloride-process data were
not available for 1990 through 1993, and data from the
1994 USGS Minerals Yearbook were used for these years.
Because a sulfate-process plant closed in September 2001,
4-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 4-30: Titanium Dioxide Production (Gg)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Gg
979
992
1,140
1,160
1,250
1,250
1,230
1,340
1,330
1,350
1,400
1,330
1,410
1,420
1,540
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. The
composition data for petroleum coke were obtained from
Onder and Bagdoyan (1993).
Uncertainty
Although some Ti02 may be produced using graphite
or other carbon inputs, information and data regarding these
practices were not available. Titanium dioxide produced
using graphite inputs, for example, may generate differing
amounts of C02 per unit of Ti02 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 Ti02 produced, sufficient data were not available
to do so.
Also, annual Ti02 is not reported by USGS by the
type of production process used (chloride or sulfate). Only
the percentage of total production capacity by process is
reported. The percent of total Ti02 production capacity that
was attributed to the chloride process was multiplied by total
Ti02 production to estimate the amount of Ti02 produced using
the chloride process. This assumes that the chloride-process
plants and sulfate-process plants operate at the same level of
utilization. Finally, the emission factor was applied uniformly
to all chloride-process production, and no data were available
to account for differences in production efficiency among
chloride process plants. In calculating the amount of petroleum
coke consumed in chloride process Ti02 production, literature
data were used for petroleum coke composition. Certain grades
of petroleum coke are manufactured specifically for use in the
Ti02 chloride process; however, this composition information
was not available.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-31. Titanium dioxide consumption
C02 emissions were estimated to be between 1.9 and 2.6 Tg
C02 Eq. at the 95 percent confidence level (or in 19 out of 20
Monte Carlo Stochastic Simulations). This indicates a range
of approximately 16 percent below and 16 percent above the
emission estimate of 2.3 Tg C02 Eq.
4.8. Phosphoric Acid Production
(IPCC Source Category 2A7)
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 (CaSO4-2H20), 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
Table 4-31: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Titanium Dioxide Production (Tg C02
Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Titanium Dioxide Production C02 2.3
1.9 2.6 -16% +16%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-23
-------
contains inorganic carbon in the form of calcium carbonate
(limestone) and also may contain organic carbon. The
chemical composition of phosphate rock (francolite) mined
in Florida is:
Ca10_x_y Nax Mgy (PO4)6_x(C03)xF2+0.4x
The calcium carbonate component of the phosphate rock
is integral to the phosphate rock chemistry. Phosphate rock
can also contain organic carbon 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 C02 emissions, due
to the chemical reaction of the inorganic carbon (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) (EFMA1997). The
primary chemical reactions for the production of phosphoric
acid from phosphate rock are:
Ca3(P04)2 + 4H3P04 -* 3Ca(H2P04)2
3Ca(H2PO4)2 + 3H2SO4 + 6H20 -*
3CaS04 6H20 + 6H3PO4
The limestone (CaC03) component of the phosphate rock
reacts with the sulfuric acid in the phosphoric acid production
process to produce calcium sulfate (phosphogypsum) and
C02. The chemical reaction for the limestone-sulfuric acid
reaction is:
CaC03 + H2SO4 + H20 -* CaSO4 2H20 + C02
Total marketable phosphate rock production in 2004
was 39.0 million metric tons. Approximately 81 percent of
domestic phosphate rock production was mined in Florida
and North Carolina, while approximately 13 percent of
production was mined in Idaho and Utah. In addition, 2.5
million metric tons of crude phosphate rock was imported for
consumption in 2004. Marketable phosphate rock production,
including domestic production and imports for consumption,
increased by approximately 4.2 percent between 2003 and
2004. However, over the 1990 to 2004 period, production
decreased by 11 percent. The 35.3 million metric tons
produced in 2001 was the lowest production level recorded
since 1965 and was driven by a worldwide decrease in
demand for phosphate fertilizers. Total CO2 emissions from
phosphoric acid production were 1.4 Tg CO2 Eq. (1,395 Gg)
in 2004 (see Table 4-32).
Methodology
C02 emissions from production of phosphoric acid from
phosphate rock is calculated by multiplying the average
amount of calcium carbonate contained in the natural
phosphate rock by the amount of phosphate rock that is used
annually to produce phosphoric acid, accounting for domestic
production and net imports for consumption.
The USGS reports in the Minerals Yearbook, Phosphate
Rock, the aggregate amount of phosphate rock mined
annually in Florida and North Carolina and the aggregate
amount of phosphate rock mined annually in Idaho and Utah,
and reports the annual amounts of phosphate rock exported
and imported for consumption (see Table 4-33). Data for
domestic production of phosphate rock, exports of phosphate
rock, and imports of phosphate rock for consumption for
1990 through 2004 were obtained from USGS Minerals
Yearbook, Phosphate Rock (USGS 1994 through 2005). In
2004, the USGS reported no exports of phosphate rock from
U.S. producers (USGS 2005).
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 3.5 percent inorganic carbon (as
C02), and phosphate rock imported from Morocco contains
approximately 5 percent inorganic carbon (as C02). Calcined
phosphate rock mined in North Carolina and Idaho contains
Table 4-32: C02 Emissions from Phosphoric Acid
Production (Tg C02 Eq. and Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
1.5
1.6
1.5
1.4
1.3
1.3
1.4
1.4
Gg
1,529
1,593
1,539
1,382
1,264
1,338
1,382
1,395
4-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 4-33: Phosphate Rock Domestic Production, Exports, and Imports (Gg)
Location/Year
U.S. Production
FL&NC
ID&UT
Exports— FL & NC
Imports— Morocco
Total U.S. Consumption
1990
49,800
42,494
7,306
6,240
451
44,011
1998
43,640
38,000
5,640
378
1,760
45,022
1999
41,440
35,900
5,540
272
2,170
43,338
2000
37,370
31,900
5,470
299
1,930
39,001
2001
32,830
28,100
4,730
9
2,500
35,321
2002
34,720
29,800
4,920
62
2,700
37,358
2003
36,410
31,300
5,110
64
2,400
38,746
2004
36,530
31,600
4,930
2,500
39,030
Source: USGS 2005, 2004, 2003, 2002, 2001, 2000,1999,1998,1997,1996,1995.
- Assumed equal to zero.
approximately 1.5 percent and 1.0 percent inorganic carbon
(as C02), respectively (see Table 4-34).
Carbonate content data for phosphate rock mined
in Florida are used to calculate the C02 emissions from
consumption of phosphate rock mined in Florida and North
Carolina (81 percent of domestic production) and carbonate
content data for phosphate rock mined in Morocco are used
to calculate C02 emissions from consumption of imported
phosphate rock. The C02 emissions calculation is based
on the assumption that all of the domestic production of
phosphate rock is used in uncalcined form. The USGS
reported that one phosphate rock producer in Idaho is
producing calcined phosphate rock; however, no production
data were available for this single producer (USGS 2003).
Carbonate content data for uncalcined phosphate rock mined
in Idaho and Utah (13 percent of domestic production) were
not available, and carbonate content was therefore estimated
from the carbonate content data for calcined phosphate rock
mined in Idaho.
The C02 emissions calculation methodology is based
on the assumption that all of the inorganic carbon (calcium
carbonate) content of the phosphate rock reacts to C02 in the
phosphoric acid production process and is emitted with the
stack gas. The methodology also assumes that none of the
organic carbon content of the phosphate rock is converted
to C02 and that all of the organic carbon content remains in
the phosphoric acid product.
Uncertainty
Phosphate rock production data used in the emission
calculations are developed by the USGS through monthly
and semiannual voluntary surveys of the eleven companies
that owned phosphate rock mines during 2004. The
phosphate rock production data are not considered to be
a significant source of uncertainty because all eleven of
the domestic phosphate rock producers report their annual
production to the USGS. Data for imports for consumption
and exports of phosphate rock used in the emission
calculation are based on international trade data collected
by the U.S. Census Bureau. These U.S. government
economic data are not considered to be a significant source
of uncertainty.
One source of potentially significant uncertainty in
the calculation of C02 emissions from phosphoric acid
production is the data for 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. Only one set of data from the Florida
Table 4-34: Chemical Composition of Phosphate Rock (percent by weight)
Composition
Total Carbon (as C)
Inorganic Carbon (as C)
Organic Carbon (as C)
Inorganic Carbon (as C02)
Central Florida
1.60
1.00
0.60
3.67
North Florida
1.76
0.93
0.83
3.43
North Carolina
(calcined)
0.76
0.41
0.35
1.50
Idaho
(calcined)
0.60
0.27
1.00
Morocco
1.56
1.46
0.10
5.00
Source: FIPR 2003
- Assumed equal to zero.
Industrial Processes 4-25
-------
Institute of Phosphate Research (FIPR) was available for
the composition of phosphate rock mined domestically and
imported, and data for uncalcined phosphate rock mined
in North Carolina and Idaho were unavailable. Inorganic
carbon content (as C02) of phosphate rock could vary +1
percent from the data included in Table 4-34, resulting in a
variation in C02 emissions of+20 percent. Another source
of uncertainty is the disposition of the organic carbon content
of the phosphate rock. A representative of the FIPR indicated
that in the phosphoric acid production process the organic
carbon 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
carbon is therefore not included in the calculation of C02
emissions from phosphoric acid production. However, if,
for example, 50 percent of the organic carbon content of the
phosphate rock were to be emitted as C02 in the phosphoric
acid production process, the C02 emission estimate would
increase by on the order of 50 percent.
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 carbon in the phosphate rock into
C02. However, according to the USGS, only one producer in
Idaho is currently calcining phosphate rock, and no data were
available concerning the annual production of this single
producer (USGS 2005). Total production of phosphate rock
in Utah and Idaho combined amounts to approximately 15
percent of total domestic production in 2004 (USGS 2005).
If it is assumed that 100 percent of the reported domestic
production of phosphate rock for Idaho and Utah was first
calcined, and it is assumed that 50 percent of the organic
carbon content of the total production for Idaho and Utah was
converted to C02 in the calcination process, the C02 emission
estimate would increase on the order of 10 percent.
Finally, USGS indicated that 10 percent of domestically-
produced phosphate rock is used to manufacture elemental
phosphorus and other phosphorus-based chemicals, rather
than phosphoric acid (USGS 2004). 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 C02 in the
elemental phosphorus production process. The calculation
for C02 emissions is based on the assumption that phosphate
rock consumption, for purposes other than phosphoric acid
production, results in C02 emissions from 100 percent of the
inorganic carbon content in phosphate rock, but none from
the organic carbon content. This phosphate rock, consumed
for other purposes, constitutes approximately 10 percent of
total phosphate rock consumption. If it were assumed that
there are zero emissions from other uses of phosphate rock,
C02 emissions would fall 10 percent.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-35. Phosphoric acid production
C02 emissions were estimated to be between 1.1 and 1.7
Tg C02 Eq. at the 95 percent confidence level (or in 19 out
of 20 Monte Carlo Stochastic Simulations). This indicates
a range of approximately 18 percent below and 19 percent
above the emission estimate of 1.4 Tg CO2 Eq.
Planned Improvements
The estimate of C02 emissions from phosphoric
acid production could be improved through collection of
Table 4-35: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Phosphoric Acid Production
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Phosphoric Acid Production C02 1.4
1.1 1.7 -18% +19%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
additional data. Additional data is being collected concerning
the carbonate content of uncalcined phosphate rock mined
in various locations in the United States. Additional
research will also be conducted concerning the disposition
of the organic carbon content of the phosphate rock in the
phosphoric acid production process. Only a single producer
of phosphate rock is calcining the product, and only a single
producer is manufacturing elemental phosphorus. Annual
production data for these single producers will probably
remain unavailable.
4.9. Ferroalloy Production (IPCC
Source Category 2C2)
C02 is emitted from the production of several
ferroalloys. Ferroalloys are composites of iron and other
elements such as silicon, manganese, and chromium. When
incorporated in alloy steels, ferroalloys are used to alter
the material properties of the steel. Estimates from two
types of ferrosilicon (25 to 55 percent and 56 to 95 percent
silicon), silicon metal (about 98 percent silicon), and
miscellaneous alloys (36 to 65 percent silicon) have been
calculated. Emissions from the production of ferrochromium
and ferromanganese are not included here because of the
small number of manufacturers of these materials in the
United States. Subsequently, government information
disclosure rules prevent the publication of production
data for these production facilities. Similar to emissions
from the production of iron and steel, C02 is emitted when
metallurgical coke is oxidized during a high-temperature
reaction with iron and the selected alloying element. Due to
Table 4-36: C02 Emissions from Ferroalloy Production
(Tg C02 Eq. and Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
2.0
2.0
2.0
1.7
1.3
1.2
1.2
1.3
Gg
1,980
2,027
1,996
1,719
1,329
1,237
1,159
1,287
the strong reducing environment, CO is initially produced,
and eventually oxidized to CO2. A representative reaction
equation for the production of 50 percent ferrosilicon is
given below:
Fe203 + 2Si02 + 7C -* 2FeSi + 7CO
Emissions of C02 from ferroalloy production in 2004
were 1.3 Tg CO2 Eq. (1,287 Gg) (see Table 4-36), an 11
percent increase from the previous year and a 35 percent
reduction since 1990.
Methodology
Emissions of C02 from ferroalloy production were
calculated by multiplying annual ferroalloy production by
material-specific emission factors. Emission factors taken
from the Revised 1996 IPCC Guidelines (IPCC/UNEP/
OECD/IEA 1997) were applied to ferroalloy production.
For ferrosilicon alloys containing 25 to 55 percent silicon
and miscellaneous alloys (including primarily magnesium-
ferrosilicon, but also including other silicon alloys)
containing 32 to 65 percent silicon, an emission factor for
50 percent silicon ferrosilicon (2.35 tons C02/ton of alloy
produced) was applied. Additionally, for ferrosilicon alloys
containing 56 to 95 percent silicon, an emission factor for
75 percent silicon ferrosilicon (3.9 tons CO2 per ton alloy
produced) was applied. The emission factor for silicon
metal was assumed to be 4.3 tons C02/ton metal produced.
It was assumed that 100 percent of the ferroalloy production
was produced using petroleum coke using an electric arc
furnace process (IPCC/UNEP/OECD/IEA 1997), 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 carbon and 10 percent inert material.
Ferroalloy production data for 1990 through 2004 (see
Table 4-37) were obtained from the USGS through personal
communications with the USGS Silicon Commodity Specialist
(Corathers 2005) and through the Minerals Yearbook: Silicon
Annual Report (USGS 1991, 1992, 1993, 1994, 1995, 1996,
1997,1998,1999,2000,2001,2002,2003,2004). Until 1999,
the USGS reported production of ferrosilicon containing 25 to
55 percent silicon separately from production of miscellaneous
alloys containing 32 to 65 percent silicon; beginning in 1999,
the USGS reported these as a single category (see Table 4-37).
Industrial Processes 4-27
-------
Table 4-37: Production of Ferroalloys (Metric Tons)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Ferrosilicon
25%-55%
321,385
162,000
252,000
229,000
167,000
156,000
113,000
120,000
Ferrosilicon
56%-95%
109,566
147,000
145,000
100,000
89,000
98,000
75,800
92,300
Silicon Metal
145,744
195,000
195,000
184,000
137,000
113,000
139,000
150,000
Misc. Alloys
32-65%
72,442
99,800
NA
NA
NA
NA
NA
NA
NA (Not Available)
The composition data for petroleum coke was obtained from
Onder and Bagdoyan (1993).
Uncertainty
Although some ferroalloys may be produced using
wood or other biomass as a carbon source, information and
data regarding these practices were not available. Emissions
from ferroalloys produced with wood or other biomass
would not be counted under this source because wood-based
carbon is of biogenic origin.10 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 C02 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.
Also, annual ferroalloy production is now reported by
the USGS in three broad categories: ferroalloys containing
25 to 55 percent silicon (including miscellaneous alloys),
ferroalloys containing 56 to 95 percent silicon, and silicon
metal. It was assumed that the IPCC emission factors apply
to all of the ferroalloy production processes, including
miscellaneous alloys. Finally, production data for silvery
pig iron (alloys containing less than 25 percent silicon) are
not reported by the USGS to avoid disclosing company
proprietary data. Emissions from this production category,
therefore, were not estimated.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-38. Ferroalloy production CO2
emissions were estimated to be between 1.3 and 1.3 Tg CO2
Eq. at the 95 percent confidence level (or in 19 out of 20
Monte Carlo Stochastic Simulations). This indicates a range
of approximately 3 percent below and 3 percent above the
emission estimate of 1.3 Tg CO2 Eq.
Recalculations Discussion
Estimates of C02 emissions from ferroalloy production
for 2003 were revised to reflect updated data from the USGS.
This change resulted in a decrease in C02 emissions from
Table 4-38: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Ferroalloy Production
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (T9 C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Ferroalloy Production C02 1.3
1.3 1.3 -3% +3%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
10 Emissions and sinks of biogenic carbon are accounted for in the Land Use, Land-Use Change, and Forestry chapter.
4-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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ferroalloy production of 0.2 Tg C02 Eq. (16 percent) for
2003.
4.10. Carbon Dioxide Consumption
(IPCC Source Category 2B5)
C02 is used for a variety of commercial applications,
including food processing, chemical production, carbonated
beverage production, and refrigeration, and is also used in
petroleum production for enhanced oil recovery (EOR). CO2
used for EOR is injected into the underground reservoirs to
increase the reservoir pressure to enable additional petroleum
to be produced.
For the most part, C02 used in non-EOR applications
will eventually be released to the atmosphere, and for the
purposes of this analysis C02 used in commercial applications
other than EOR is assumed to be emitted to the atmosphere.
C02 used in EOR applications is considered for the purposes
of this analysis to remain sequestered in the underground
formations into which the C02 is injected.
It is unclear to what extent the C02 used for EOR will be
re-released to the atmosphere. C02 used in EOR applications
is compressed at the C02 production source, transported
by pipeline to the EOR field, and injected into wellheads.
Potential CO2 leakage pathways from C02 production,
transportation, and injection include fugitive emissions from
the compressors, pipeline equipment, and wellheads. Also,
the C02 used for EOR may migrate to the wellhead after a
few years of injection (Hangebrauk et al. 1992) or may be
partially recovered as a component of crude oil produced
from the wells (Denbury Resources 2003a). This CO2 may
be recovered and re-injected into the wellhead or separated
from the petroleum produced and vented to the atmosphere.
More research is required to determine the amount of C02
that may escape from EOR operations through leakage from
equipment, as a component of the crude oil produced, or as
leakage directly from the reservoir through geologic faults
and fractures or through improperly plugged or improperly
completed wells. For the purposes of this analysis, it is
assumed that all of the C02 produced for use in EOR
applications is injected into reservoirs (i.e., there is no loss of
C02 to the atmosphere during C02 production, transportation,
or injection for EOR applications) and that all of the injected
C02 remains sequestered within the reservoirs.
C02 is produced from naturally occurring C02 reservoirs,
as a by-product from the energy and industrial production
processes (e.g., ammonia production, fossil fuel combustion,
ethanol production), and as a by-product from the production
of crude oil and natural gas, which contain naturally occurring
C02 as a component. C02 produced from naturally occurring
C02 reservoirs and used in industrial applications other than
EOR is included in this analysis. Neither by-product CO2
generated from energy or industrial production processes nor
C02 separated from crude oil and natural gas are included in
this analysis for a number of reasons.
Depending on the raw materials that are used, by-product
C02 generated during energy and industrial production
processes may already be accounted for in the C02 emission
estimates from fossil fuel consumption (either from fossil
fuel combustion or from non-energy uses of fossil fuels). For
example, ammonia is primarily manufactured using natural
gas as both a feedstock and energy source. C02 emissions
from natural gas combustion for ammonia production are
accounted for in the C02 from Fossil Fuel Combustion
source category of the Energy sector and, therefore, are
not included under C02 Consumption. Likewise, CO2
emissions from natural gas used as feedstock for ammonia
production are accounted for in this chapter under the
Ammonia Manufacture source category and, therefore, are
not included here.11
C02 is produced as a by-product of crude oil and natural
gas production. This C02 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. The amount of C02 separated from crude
oil and natural gas has not been estimated.12 Therefore, the
only C02 consumption that is accounted for in this analysis
11 One ammonia manufacturer located in Oklahoma is reportedly capturing approximately 35 MMCF/day (0.67 Tg/yr) of by-product C02 for use in
EOR applications. According to the methodology used in this analysis, this amount of CO2 would be considered to be sequestered and not emitted to
the atmosphere. However, time series data for the amount of C02 captured from the ammonia plant for use in EOR applications are not available, and
therefore all of the C02 produced by the ammonia plant is assumed to be emitted to the atmosphere and is accounted for in this chapter under Ammonia
Manufacture.
12 The United States is in the process of developing a methodology to account for CO2 emissions from natural gas systems and petroleum systems for
inclusion in future Inventory submissions. For more information see Annex 5.
Industrial Processes 4-29
-------
is C02 produced from natural wells other than crude oil and
natural gas wells that is used in commercial applications
other than EOR.
There are currently two facilities, one in Mississippi
and one in New Mexico, producing C02 from natural C02
reservoirs for use in both EOR and in other commercial
applications (e.g., chemical manufacturing, food production).
There are other naturally occurring C02 reservoirs, mostly
located in the western U.S. Facilities are producing CO2 from
these natural reservoirs, but they are only producing C02 for
EOR applications, not for other commercial applications
(Allis et al. 2000). In 2004, the amount of C02 produced by
the Mississippi and New Mexico facilities for commercial
applications and subsequently emitted to the atmosphere
were 1.2 Tg CO2 Eq. (1,183 Gg) (see Table 4-39). This
amount represents a decrease of 9 percent from the previous
year and an increase of 29 percent from emissions in 1990.
This increase was due to an increase in the Mississippi
facility's reported production for use in other commercial
applications.
Methodology
C02 emission estimates for 2001 through 2004 were
based on production data for the two facilities currently
producing C02 from naturally-occurring C02 reservoirs.
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). C02 produced
from these two facilities that was used for EOR is assumed to
remain sequestered and is not included in the C02 emissions
totals. It is assumed that 100 percent of the CO2 production
used in commercial applications other than EOR is eventually
released into the atmosphere.
Table 4-39: C02 Emissions from C02 Consumption (Tg
C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
0.9
860
1998
1999
2000
2001
2002
2003
2004
0.9
0.8
1.0
0.8
1.0
1.3
1.2
912
849
957
818
968
1,293
1,183
C02 production data for the Jackson Dome, Mississippi
facility for 2001 through 2004 and the percentage of
total production that was used for EOR and in non-EOR
applications were obtained from the Annual Reports for
Denbury Resources, the operator of the facility (Denbury
Resources 2002, 2003b, 2004, 2005). Denbury Resources
reported the average C02 production in units of MMCF C02
per day for 2001 through 2004 and reported the percentage of
the total average annual production that was used for EOR.
C02 production data for the Bravo Dome, New Mexico
facility were obtained from the New Mexico Bureau of
Geology and Mineral Resources for the years 1990 through
2003 (Broadhead 2005). According to the New Mexico
Bureau, the amount of CO2 produced from Bravo Dome
for use in non-EOR applications is less than one percent
of total production (Broadhead 2003a). Production data for
2004 were not available for Bravo Dome, so it is assumed
that the production values for those years are equal to the
2003 value.
Denbury Resources acquired the Jackson Dome
facility in 2001 and CO2 production data for the Jackson
Dome facility are not available for years prior to 2001.
Therefore, for 1990 through 2000, CO2 emissions from C02
consumption in commercial applications other than EOR are
estimated based on the total annual domestic consumption
of C02 in commercial applications other than EOR in 2001
multiplied by the percentage of the total C02 consumed in
commercial applications other than EOR that originated
from C02 production at the Jackson Dome and Bravo Dome
facilities in 2001. The same procedure was followed in
2002, 2003, and 2004 with updated annual data. The total
domestic commercial consumption of C02 in commercial
applications other than EOR as reported by the U.S. Census
Bureau was about 13,542 thousand metric tons in 2004. The
total non-EOR CO2 produced from the Jackson Dome and
Bravo Dome natural reservoirs in 2004 was about 1,183
thousand metric tons, corresponding to 8.7 percent of the
total domestic non-EOR commercial CO2 consumption.
The remaining 91.3 percent of the total annual non-EOR
commercial C02 consumption is assumed to be accounted
for in the C02 emission estimates from other categories (e.g.,
Ammonia Manufacture, C02 from Fossil Fuel Combustion,
Wood Biomass and Ethanol Consumption).
Non-EOR commercial CO2 consumption data (see Table
4-40) for years 1991 and 1992 were obtained from Industry
4-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-40: C02 Consumption (Metric Tons)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Metric Tons
11,997,726
12,716,070
11,843,386
13,354,262
11,413,889
11,313,478
11,165,324
13,542,492
Report 1992 (U'.S. Census 1993). Consumption data are not
available for 1990, and therefore CO2 consumption data for
1990 is assumed to be equal to that for 1991. Consumption
data for 1993 and 1994 were obtained from U.S. Census
Bureau Manufacturing Profile, 1994 (U.S. Census 1995).
Consumption data for 1996 through 2004 were obtained
from the U.S. Census Bureau's Industry Report, 1996,1998,
2000, 2002, 2003, 2004 (U.S. Census 1997, 1999, 2001,
2003,2004,2005).
Uncertainty
Uncertainty is associated with the number of facilities
that are currently producing C02 from naturally occurring
reservoirs for commercial uses other than EOR, and for which
the C02 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 C02 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 C02 emissions
from that sector depending upon the end use to which the
recovered C02 is applied. For example, research has identified
one ammonia production facility that is recovering C02 for use
in EOR. Such CO2 would be assumed to remain sequestered;
however, time series data for the amount of recovered is not
available and therefore all of the C02 produced by this plant
is assumed to be emitted to the atmosphere and is allocated
to Ammonia Manufacture. Recovery of CO2 from ammonia
production facilities for use in EOR is further discussed in
this chapter under Ammonia Manufacture. Further research
is required to determine whether C02 is being recovered
from other facilities for application to end uses that are not
accounted for elsewhere.
There is also uncertainty associated with the assumption
that 100 percent of the CO2 used for EOR is sequestered.
Operating experience with EOR systems indicates that
100 percent of the CO2 used in EOR applications does not
remain sequestered, but rather that it may be emitted to
the atmosphere as leakage from equipment and reservoirs
or recovered as a component of the crude oil produced.
Potential sources of CO2 emissions from EOR applications
include leakage from equipment used to produce, transport,
compress, and inject the C02, leakage from equipment used
to process the crude oil produced, separate the C02 from
the crude oil and recompress and recycle (reinject) the C02
recovered from the crude oil. Other potential sources of
C02 emissions from EOR applications include leakage from
the reservoir itself, either through migration of the injected
C02 beyond the boundaries of the reservoir, chemical
interactions between the injected C02 and the reservoir rock,
and leakage via faults, fractures, oil and gas well bores, and
water wells.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-41. CO2 consumption
C02 emissions were estimated to be between l.Oand 1.4 Tg
C02 Eq. at the 95 percent confidence level (or in 19 out of 20
Monte Carlo Stochastic Simulations). This indicates a range
of approximately 14 percent below to 14 percent above the
emission estimate of 1.2 Tg CO2 Eq.
Table 4-41: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from C02 Consumption
(Tg C02 Eq. and Percent)
Source
2004 Emission Uncertainty Range Relative to Emission Estimate3
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
C02 Consumption
C02 1.2 1.0 1.4 -14% +14%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-31
-------
Recalculations Discussion
Total C02 consumption values were updated for 2003,
as was C02 production for Jackson Dome, based on revised
data in the Census Bureau's Industry Reports and Denbury
Resources' Annual Report, respectively. Data for the Bravo
Dome were updated for the entire time series based on new
production data from the facility. For Jackson Dome, revised
2003 production data resulted in a 33 percent increase in
emissions from the previous estimate. For Jackson Dome,
updated production data resulted in an approximate emissions
decrease of 1 percent for 2001, 17 percent for 2002, and 11
percent for 2003. Revisions to the datasets resulted in a 1
percent decrease in C02 emissions from C02 consumption
in 2002 and a 2 percent increase in C02 emissions from
C02 consumption in 2003 relative to data published in the
previous Inventory.
4.11. Zinc Production
Zinc production in the United States consists of both
primary and secondary processes. Primary production
techniques used in the United States are the electro-thermic
and electrolytic process while secondary techniques used
in the United States include a range of metallurgical,
hydrometallurgical, and pyrometallurgical processes.
Worldwide primary zinc production also employs a
pyrometallurgical process using the Imperial Smelting
Furnace process; however, this process is not used in the
United States (Sjardin 2003). Of the primary and secondary
processes used in the United States, the electro-thermic
process results in non-energy C02 emissions, as does the
Waelz Kiln process—a technique used to produce secondary
zinc from electric-arc furnace (EAF) dust (Viklund-White
2000). Total zinc production has decreased by 15 percent
in the United States since 1990 while world production
has increased by 38 percent over this same period (USGS
1995, 2004).
During the electro-thermic zinc production process,
roasted zinc concentrate and, when available, secondary
zinc products enter a sinter feed where they are burned to
remove impurities before entering an electric retort furnace.
Metallurgical coke added to the electric retort furnace reduces
the zinc oxides and produces vaporized zinc, which is then
captured in a vacuum condenser. This reduction process
produces non-energy C02 emissions (Sjardin 2003). The
electrolytic zinc production process does not produce non-
energy C02 emissions.
In the Waelz Kiln process, EAF dust, which is captured
during the recycling of galvanized steel, enters a kiln along
with a reducing agent—often metallurgical coke. When kiln
temperatures reach approximately 1100-1200°C, zinc fumes
are produced, which are combusted with air entering the kiln.
This combustion forms zinc oxide, which is collected in a
baghouse or electrostatic precipitator, and is then leached
to remove chloride and fluoride. Through this process,
approximately 0.33 tons of zinc are produced for every ton
of EAF dust treated (Viklund-White 2000).
In 2004, U.S. primary and secondary zinc production
totaled 567,900 metric tons (USGS 2004). The resulting
emissions of C02 from zinc production in 2004 were
estimated to be 0.5 Tg C02 Eq. (502 Gg) (see Table
4-42). All 2004 C02 emissions result from secondary zinc
production.
After a gradual increase in total emissions from 1990 to
2000, largely due to an increase in secondary zinc production,
2004 emissions have decreased by nearly half that of 1990
(47 percent) due to the closing of an electro-thermic-process
zinc plant in Monaca, PA (USGS 2004).
Methodology
Non-energy C02 emissions from zinc production
result from those processes that use metallurgical coke or
other carbon-based materials as reductants. Sjardin (2003)
provides an emission factor of 0.43 metric tons C02/ton zinc
produced for emissive zinc production processes; however,
this emission factor is based on the Imperial Smelting
Furnace production process. Because the Imperial Smelting
Furnace production process is not used in the United States,
Table 4-42: C02 Emissions from Zinc Production (Tg C02
Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
0.9
939
1998
1999
2000
2001
2002
2003
2004
1.1
1.1
1.1
1.0
0.9
0.5
0.5
1,140
1,080
1,129
976
927
502
502
4-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
emission factors specific to those emissive zinc production
processes used in the United States, which consist of the
electro-thermic and Waelz Kiln processes, were needed.
Due to the limited amount of information available for these
electro-thermic processes, only Waelz Kiln process-specific
emission factors were developed. These emission factors
were applied to both the Waelz Kiln process and the electro-
thermic zinc production processes. A Waelz Kiln emission
factor based on the amount of zinc produced was developed
based on the amount of metallurgical coke consumed for
non-energy purposes per ton of zinc produced, 1.19 metric
tons coke/metric ton zinc produced (Viklund-White 2000),
and the following equation:
EFW!
Waelz Kiln
1.19 metric tons coke
metric tons zinc
0.84 metric tons C v
/\
metric ton coke
3.67 metric tons C02
metric ton C
1.23 metric tons CO2
metric ton zinc
The USGS disaggregates total U.S. primary zinc
production capacity into zinc produced using the electro-
thermic process and zinc produced using the electrolytic
process; however, the USGS does not report the amount
of zinc produced using each process, only the total zinc
production capacity of the zinc plants using each process.
The total electro-thermic zinc production capacity is divided
by total primary zinc production capacity to estimate the
percent of primary zinc produced using the electro-thermic
process. This percent is then multiplied by total primary
zinc production to estimate the amount of zinc produced
using the electro-thermic process, and the resulting value
is multiplied by the Waelz Kiln process emission factor to
obtain total C02 emissions for primary zinc production.
According to the USGS, the only remaining plant producing
primary zinc using the electro-thermic process closed
in 2003 (USGS 2004). Therefore, CO2 emissions for
primary zinc production are reported only for years 1990
through 2002.
In the United States, secondary zinc is produced through
either the electro-thermic or Waelz Kiln process. In 1997,
the Horsehead Corporation plant, located in Monaca, PA,
produced 47,174 metric tons of secondary zinc using the
electro-thermic process (Queneau et al. 1998). This is the
only plant in the United States that uses the electro-thermic
process to produce secondary zinc, which, in 1997, accounted
for 13 percent of total secondary zinc production. This
percentage was applied to all years within the time series
up until the Monaca plant's closure in 2003 (USGS 2004) to
estimate the total amount of secondary zinc produced using
the electro-thermic process. This value is then multiplied by
the Waelz Kiln process emission factor to obtain total CO2
emissions for secondary zinc produced using the electro-
thermic process.
U.S. secondary zinc is also produced by processing
recycled EAF dust in a Waelz Kiln furnace. Due to the
complexities of recovering zinc from recycled EAF dust, an
emission factor based on the amount of EAF dust consumed
rather than the amount of secondary zinc produced is believed
to represent actual C02 emissions from the process more
accurately (Stuart 2005). An emission factor based on the
amount of EAF dust consumed was developed based on
the amount of metallurgical coke consumed per ton of
EAF dust consumed, 0.4 metric tons coke/metric ton EAF
dust consumed (Viklund-White 2000), and the following
equation:
EF
EAF Dust :
0.4 metric tons coke
metric tons EAF dust
0.84 metric tons C
x
metric ton coke
3.67 metric tons C02 x
metric ton C
1.23 metric tons CO2
metric ton EAF dust
The Horsehead Corporation plant, located in Palmerton,
PA, is the only large plant in the United States that produces
secondary zinc by recycling EAF dust (Stuart 2005). In
2003, this plant consumed 408,240 metric tons of EAF dust,
producing 137,169 metric tons of secondary zinc (Recycling
Today 2005). This zinc production accounted for 36 percent
of total secondary zinc produced in 2003. This percentage
was applied to the USGS data for total secondary zinc
production for all years within the time series to estimate
the total amount of secondary zinc produced by consuming
recycled EAF dust in a Waelz Kiln furnace. This value is
multiplied by the Waelz Kiln process emission factor for
EAF dust to obtain total C02 emissions.
Industrial Processes 4-33
-------
Table 4-43: Zinc Production (Metric Tons)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Primary
262,704
253,282
271,867
240,000
216,600
231,840
225,400
226,700
233,900
241,100
227,800
203,000
181,800
186,900
186,900
Secondary
341,400
351,457
365,623
358,000
361,000
353,000
378,000
374,000
426,000
398,000
440,000
375,000
366,000
381,000
381,000
The 1990 through 2003 activity data for primary and
secondary zinc production (see Table 4-43) were obtained
through the USGS Mineral Yearbook: Zinc (USGS 1994,
1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
2004). Because data for 2004 are not yet available, 2004
data are assumed to equal 2003 data.
Uncertainty
The uncertainties contained in these estimates are two-
fold, relating to activity data and emission factors used.
First, there are uncertainties associated with the percent
of total zinc production, both primary and secondary, that
is attributed to the electro-thermic and Waelz Kiln emissive
zinc production processes. For primary zinc production, the
amount of zinc produced annually using the electro-thermic
process is estimated from the percent of primary-zinc
production capacity that electro-thermic production capacity
constitutes for each year of the time series. This assumes
that each zinc plant is operating at the same percentage of
total production capacity, which may not be the case and
this calculation could either overestimate or underestimate
the percentage of the total primary zinc production that is
produced using the electro-thermic process. The amount of
secondary zinc produced using the electro-thermic process is
estimated from the percent of total secondary zinc production
that this process accounted for during a single year, 2003.
The amount of secondary zinc produced using the Waelz
Kiln process is estimated from the percent of total secondary
zinc production this process accounted for during a single
year, 1997. This calculation could either overestimate or
underestimate the percentage of the total secondary zinc
production that is produced using the electro-thermic
or Waelz Kiln processes. Therefore, there is uncertainty
associated with the fact that percents of total production
data estimated from production capacity, rather than actual
production data, are used for emission estimates.
Second, there are uncertainties associated with the
emission factors used to estimate C02 emissions from the
primary and secondary production processes. Because the
only published emission factors are based on the Imperial
Smelting Furnace, which is not used in the United States,
country-specific emission factors were developed for
the Waelz Kiln zinc production process. Data limitations
prevented the development of emission factors for the
electro-thermic process. Therefore, emission factors for the
Waelz Kiln process were applied to both electro-thermic and
Waelz Kiln production processes. Furthermore, the Waelz
Kiln emission factors are based on materials balances for
metallurgical coke and EAF dust consumed during zinc
production provided by Viklund-White (2000). Therefore,
the accuracy of these emission factors depend upon the
accuracy of these materials balances.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-44. Zinc production
C02 emissions were estimated to be between 0.4 and 0.6
Tg C02 Eq. at the 95 percent confidence level (or in 19 out
Table 4-44: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Zinc Production
(Tg C02 Eq. and Percent)
Source
2004 Emission Uncertainty Range Relative to Emission Estimate"
Estimate
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Zinc Production
C02 0.5 0.4 0.6 -12% +13%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
of 20 Monte Carlo Stochastic Simulations). This indicates
a range of approximately 12 percent below and 13 percent
above the emission estimate of 0.5 Tg C02 Eq.
4.12. Lead Production
Lead production in the United States consists of both
primary and secondary processes. In the United States,
primary lead production, in the form of direct smelting,
mostly occurs at a plant located in Missouri, while secondary
production largely involves the recycling of lead acid batteries
at 15 separate smelters located in 11 states throughout the
United States (USGS 2004). Secondary lead production has
increased in the United States over the past decade while
primary lead production has decreased, to where 2004
secondary lead production accounted for approximately 88
percent of total lead production (USGS 1995, 2004). Both
the primary lead and secondary lead production processes
used in the United States emit CO2 (Sjardin 2003).
Primary production of lead through the direct smelting
of lead concentrate produces C02 emissions as the lead
concentrates are reduced in a furnace using metallurgical
coke (Sjardin 2003). U.S. primary lead production decreased
by 40 percent from 2003 to 2004 due to the closing of one
of two primary lead production plants in Missouri and has
decreased by 63 percent since 1990 (USGS 1995, Gabby
2005)
In the United States, approximately 82 percent of
secondary lead is produced by recycling lead acid batteries in
either blast furnaces or reverberatory furnaces. The remaining
18 percent of secondary lead is produced from lead scrap.
Similar to primary lead production, CO2 emissions result
when a reducing agent, usually metallurgical coke, is added
to the smelter to aid in the reduction process (Sjardin 2003).
U.S. secondary lead production decreased by 3 percent from
2003 to 2004, but has increased by 17 percent since 1990.
In 2004, U.S. primary and secondary lead production
totaled 1,258,00 metric tons (USGS 2004). The resulting
emissions of C02 from 2004 production were estimated to
be 0.3 Tg C02 Eq. (259 Gg) (see Table 4-45). The majority
of 2004 lead production is from secondary processes, which
account for 85 percent of total 2004 C02 emissions.
After a gradual increase in total emissions from 1990
to 2000, total emissions have decreased by nine percent
since 1990, largely due a decrease in primary production
and a transition within the United States from primary lead
production to secondary lead production, which is less
emissive than primary production (USGS 2004).
Methodology
Non-energy C02 emissions from lead production
result from primary and secondary production processes
that use metallurgical coke or other carbon-based materials
as reductants. For primary lead production using direct
smelting, Sjardin (2003) provides an emission factor of 0.25
metric tons C02/ton lead. For secondary lead production,
Sjardin (2003) provides an emission factor of 0.2 metric tons
C02/ton lead produced. Both factors are multiplied by total
U.S. primary and secondary lead production, respectively,
to estimate C02 emissions.
The 1990 through 2003 activity data for primary and
secondary lead production (see Table 4-46) were obtained
through the USGS Mineral Yearbook: Lead (USGS 1994,
Table 4-45: C02 Emissions from Lead Production (Tg
C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
0.3
285
1998
1999
2000
2001
2002
2003
2004
0.3
0.3
0.3
0.3
0.3
0.3
0.3
308
310
311
293
290
289
259
Table 4-46: Lead Production (Metric Tons)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Primary
404,000
345,900
304,800
334,900
351,400
374,000
326,000
343,000
337,000
350,000
341,000
290,000
262,000
245,000
148,000
Secondary
922,000
885,000
916,000
893,000
931,000
1,020,000
1,070,000
1,110,000
1,120,000
1,110,000
1,130,000
1,100,000
1,120,000
1,140,000
1,110,000
Industrial Processes 4-35
-------
Table 4-47: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lead Production
(Tg C02 Eq. and Percent)
Source
2004 Emission Uncertainty Range Relative to Emission Estimate3
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Lead Production
C02 0.3 0.2 0.3 -11% +11%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
2004). Primary and secondary lead production data for 2004
were obtained from the USGS Lead Minerals Commodity
Specialist (Gabby 2005).
Uncertainty
Uncertainty associated with lead production relates
to the emission factors and activity data used. The direct
smelting emission factor used in primary production is taken
from Sjardin (2003) who averages the values provided by
three other studies (Dutrizac et al. 2000, Morris et al. 1983,
Ullman 1997). For secondary production, Sjardin (2003)
reduces this factor by 50 percent and adds a C02 emissions
factor associated with battery treatment. The applicability
of these emission factors to plants in the United States
is uncertain. There is also a smaller level of uncertainty
associated with the accuracy of primary and secondary
production data provided by the USGS.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-47. Lead production
C02 emissions were estimated to be between 0.2 and 0.3
Tg C02 Eq. at the 95 percent confidence level (or in 19 out
of 20 Monte Carlo Stochastic Simulations). This indicates
a range of approximately 11 percent below and 11 percent
above the emission estimate of 0.3 Tg C02 Eq.
4.13. Petrochemical Production
(IPCC Source Category 2B5)
The production of some petrochemicals results in
the release of small amounts of CH4 and C02 emissions.
Petrochemicals are chemicals isolated or derived from
petroleum or natural gas. CH4 emissions are presented here
from the production of carbon black, ethylene, ethylene
dichloride, styrene, and methanol, while C02 emissions are
presented here for only carbon black production. The C02
emissions from petrochemical processes other than carbon
black are currently included in the Carbon Stored in Products
from Non-Energy Uses of Fossil Fuels Section of the Energy
chapter. The C02 from carbon black production is included
here to allow for the direct reporting of C02 emissions from
the process and direct accounting of the feedstocks used in
the process.
Carbon black is an intensely 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. Ethylene is consumed in the production processes
of the plastics industry including polymers such as high,
low, and linear low density polyethylene (HDPE, LDPE,
LLDPE), polyvinyl chloride (PVC), ethylene dichloride,
ethylene oxide, and ethylbenzene. Ethylene dichloride is
one of the first manufactured chlorinated hydrocarbons with
reported production as early as 1795. In addition to being
an important intermediate in the synthesis of chlorinated
hydrocarbons, ethylene dichloride is used as an industrial
solvent and as a fuel additive. Styrene is a common precursor
for many plastics, rubber, and resins. It can be found in
many construction products, such as foam insulation, vinyl
flooring, and epoxy adhesives. Methanol is an alternative
transportation fuel as well as a principle ingredient in
windshield wiper fluid, paints, solvents, refrigerants, and
disinfectants. In addition, methanol-based acetic acid is used
in making PET plastics and polyester fibers.
Emissions of C02 and CH4 from petrochemical
production in 2004 were 2.9 Tg CO2 Eq. (2,895 Gg) and
1.6 Tg CO2 Eq. (77 Gg), respectively (see Table 4-48 and
Table 4-49). Emissions of CO2 from carbon black production
in 2004 increased four percent from the previous year, and
there has been an overall increase in C02 emissions from
carbon black production of 30 percent since 1990. CH4
4-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-48: C02 and CH4 Emissions from Petrochemical Production (Tg C02 Eq.)
Year
C02
CH4
Total
1990
2.2
1.2
3.4
1998
3.0
1.7
4.7
1999
3.1
1.7
4.8
2000
3.0
1.7
4.7
2001
2.8
1.4
4.2
2002
2.9
1.5
4.4
2003
2.8
1.5
4.3
2004
2.9
1.6
4.5
Table 4-49: C02 and CH4 Emissions from Petrochemical Production (Gg)
Year
C02
CH4
1990
2,
,221
56
1998
3,
,015
80
1999
3,
,054
81
2000
3,004
80
2001
2,787
68
2002
2,857
72
2003
2,777
72
2004
2,895
77
emissions from petrochemical production increased by seven
percent from the previous year and increased 38 percent
since 1990.
Methodology
Emissions of CH4 were calculated by multiplying
annual estimates of chemical production by the appropriate
emission factor, as follows: 11 kg CH4/metric ton carbon
black, 1 kg CH4/metric ton ethylene, 0.4 kg CH4/metric ton
ethylene dichloride,13 4 kg CH4/metric ton styrene, and 2 kg
CH4/metric ton methanol. Although the production of other
chemicals may also result in CH4 emissions, there were not
sufficient data available to estimate their emissions.
Emission factors were taken from the Revised 1996
IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997). Annual
production data for 1990 (see Table 4-50) were obtained
from the Chemical Manufacturer's Association Statistical
Handbook (CMA 1999). Production data for 1991 through
2004 were obtained from the American Chemistry Council's
Guide to the Business of Chemistry (kCC 2002, 2003, 2005)
and the International Carbon Black Association (Johnson
2003,2005).
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, and one U.S. carbon
black plant produces carbon black using the acetylene black
process (The Innovation Group 2004).
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
Table 4-50: Production of Selected Petrochemicals (Thousand Metric Tons)
Chemical
Carbon Black
Ethylene
Ethylene Dichloride
Styrene
Methanol
1990
1,307
16,542
6,282
3,637
3,785
1998
1,775
23,474
11,080
5,183
5,860
1999
1,798
25,118
10,308
5,410
5,303
2000
1,769
24,971
9,866
5,420
4,876
2001
1,641
22,521
9,294
4,277
3,402
2002
1,682
23,623
9,288
4,974
3,289
2003
1,635
22,957
9,952
5,239
3,166
2004
1,704
25,660
12,111
5,468
2,937
13 The emission factor obtained from IPCC/UNEP/OECD/IEA (1997), page 2.23 is assumed to have a misprint; the chemical identified should be ethylene
dichloride (C2H4Cl2) rather than dichloroethylene (C2H2Cl2).
Industrial Processes 4-37
-------
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 C02, 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 carbon lost during the production
process is the basis for determining the amount of C02
released during the process. The carbon content of national
carbon black production is subtracted from the total amount
of carbon contained in primary and secondary carbon black
feedstock to find the amount of carbon lost during the
production process. It is assumed that the carbon lost in
this process is emitted to the atmosphere as either CH4 or
C02. The carbon content of the CH4 emissions, estimated
as described above, is subtracted from the total carbon lost
in the process to calculate the amount of carbon emitted as
C02. The total amount of primary and secondary carbon
black feedstock consumed in the process (see Table 4-51)
is estimated using a primary feedstock consumption factor
and a secondary feedstock consumption factor estimated
from U.S. Census Bureau (1999 and 2004) data. The
average carbon black feedstock consumption factor for
U.S. carbon black production is 1.43 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 341 normal cubic meters
of natural gas consumed per metric ton of carbon black
produced. The amount of carbon contained in the primary and
secondary feedstocks is calculated by applying the respective
carbon contents of the feedstocks to the respective levels of
feedstock consumption.
For the purposes of emissions 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 89 percent elemental carbon
(Srivastava et al. 1999). 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 carbon (Othmer et al. 1992).
Uncertainty
The CH4 emission factors used for petrochemical
production are based on a limited number of studies. Using
plant-specific factors instead of average factors could
increase the accuracy of the emission estimates; however,
such data were not available. There may also be other
significant sources of CH4 arising from petrochemical
production activities that have not been included in these
estimates.
The results of the quantitative uncertainty analysis for
the C02 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 89 percent carbon gives rise to uncertainty.
Table 4-51: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)
Consumption (Thousand Metric Tons)
Activity
Primary Feedstock
Secondary Feedstock
1990
1,864
302
1998
2,530
410
1999
2,563
415
2000
2,521
408
2001
2,339
379
2002
2,398
388
2003
2,331
377
2004
2,430
393
4-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-52: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical Production and C02
Emissions from Carbon Black Production (Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Petrochemical Production CH4 1.6
Petrochemical Production C02 2.9
1.5 1.7 -8% +6%
2.5 3.1 -14% +5%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Also, no data are available concerning the consumption
of coal-derived carbon black feedstock, so C02 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 4-52. Petrochemical production
CH4 emissions were estimated to be between 1.5 and 1.7
Tg C02 Eq. at the 95 percent confidence level (or in 19 out
of 20 Monte Carlo Stochastic Simulations). This indicates a
range of approximately 8 percent below to 6 percent above
the emission estimate of 1.6 Tg CO2 Eq. Petrochemical
production C02 emissions were estimated to be between 2.5
and 3.1 Tg CO2 Eq. at the 95 percent confidence level (or
in 19 out of 20 Monte Carlo Stochastic Simulations). This
indicates a range of approximately 14 percent below to 5
percent above the emission estimate of 2.9 Tg CO2 Eq.
4.14. Silicon Carbide Production
(IPCC Source Category 2B4) and
Consumption
CH4 is emitted from the production of silicon carbide
(SiC), a material used as an industrial abrasive; CO2 is emitted
from the use of SiC for metallurgical and other non-abrasive
applications. To make SiC, quartz (SiO2) is reacted with carbon
in the form of petroleum coke. During this reaction, CH4 is
produced from volatile compounds in the petroleum coke.
While C02 is also emitted from the production process, the
requisite data were unavailable for these calculations. C02
emissions associated with the use of petroleum coke in the SiC
process are accounted for in the Non-Energy Uses of Fossil
Fuels section in the Energy Chapter. CH4 emissions from SiC
production in 2004 were 0.4 Gg CH4 (0.01 Tg CO2 Eq.) (see
Table 4-53 and Table 4-54).
Table 4-53: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg C02 Eq.)
Year
C02
CH4
Total
1990
0.1
+
0.1
1998
0.2
+
0.2
1999
0.1
+
0.2
2000
0.1
+
0.1
2001
0.1
+
0.1
2002
0.1
+
0.1
2003
0.1
+
0.1
2004
0.1
+
0.1
+ Does not exceed 0.05 Tg C02 Eq.
Table 4-54: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
C02
CH4
100
1
190
1
137
1
130
1
94
105
111
133
+ Does not exceed 0.5 Gg.
Industrial Processes 4-39
-------
The USGS reports that a portion (approximately 50
percent) of SiC is used in metallurgical and other non-abrasive
applications, primarily in iron and steel production (USGS
2005a). This consumption of SiC produces CO2 emissions.
Considering utilization of both domestically produced SiC
and imported SiC in such applications, the amount of CO2
emitted from SiC consumption in 2004 were 133 Gg CO2
(0.1 Tg CO2 Eq.) (see Table 4-53 and Table 4-54).
Methodology
Emissions of CH4 were calculated by multiplying annual
SiC production by an emission factor (11.6 kg CH4/metric
ton SiC). This emission factor was derived empirically from
measurements taken at Norwegian SiC plants (IPCC/UNEP/
OECD/IEA 1997).
Emissions of C02 were calculated by multiplying the
annual SiC consumption (production plus net imports) by
the percent used in metallurgical and other non-abrasive
Table 4-55: Production and Consumption of Silicon
Carbide (Metric Tons)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Production
105,000
78,900
84,300
74,900
84,700
75,400
73,600
68,200
69,800
65,000
45,000
40,000
30,000
35,000
35,000
Consumption
172,464
138,652
159,902
173,508
179,055
227,397
240,781
292,050
329,040
237,346
225,280
162,142
180,956
191,289
229,693
uses (50 percent) (USGS 2005a). The total SiC consumed
in metallurgical and other non-abrasive uses was multiplied
by the carbon content of SiC (31.5 percent), which was
determined according to the molecular weight ratio of SiC.
Production data for 1990 through 2004 were obtained
from the Minerals Yearbook: Volume I-Metals and Minerals,
Manufactured Abrasives (USGS 1991a, 1992a, 1993a,
1994a, 1995a, 1996a, 1997a, 1998a, 1999a, 2000a, 2001a,
2002a, 2003a, 2004a, 2005a). Silicon carbide consumption
by major end use was obtained from the Minerals Yearbook:
Silicon (USGS 1991b, 1992b, 1993b, 1994b, 1995b, 1996b,
1997b, 1998b, 1999b, 2000b, 2001b, 2002b, 2003b, 2004b,
2005b) (see Table 4-55). Net imports were obtained from
the U.S. Census Bureau (2005).
Uncertainty
The emission factor used for silicon carbide production
was based on one study of Norwegian plants. The
applicability of this factor to average U.S. practices at
silicon carbide plants is uncertain. 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. There is also some uncertainty associated with
production, net imports, and consumption data as well as the
percent of total consumption that is attributed to metallurgical
and other non-abrasive uses.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-56. Silicon carbide production
CH4 emissions were estimated to be between 0.0077 and
0.0094 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 10 percent below to 10
percent above the emission estimate of 0.0085 Tg C02 Eq.
Table 4-56: Tier 2 Quantitative Uncertainty Estimates for CH4 and C02 Emissions from Silicon Carbide Production
and Consumption (Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Silicon Carbide Production CH4 +
Silicon Carbide
Consumption C02 0.1
+ + -10% +10%
0.1 0.2 -17% +18%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
+ Does not exceed 0.05 Tg C02 Eq. or 0.5 Gg.
4-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Silicon carbide consumption CO2 emissions were estimated
to be between 0.1 and 0.2 Tg CO2 Eq. percent confidence
level. This indicates a range of approximately 17 percent
below to 18 percent above the emission estimate of 0.1 Tg
C02 Eq.
4.15. Nitric Acid Production (IPCC
Source Category 2B2)
Nitric acid (HN03) 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, N20 is formed as a by-product and is released
from reactor vents into the atmosphere.
Currently, the nitric acid industry controls for NO and
N02 (i.e., N0,j). As such, the industry uses a combination
of non-selective catalytic reduction (NSCR) and selective
catalytic reduction (SCR) technologies. In the process of
destroying NOX, NSCR systems are also very effective at
destroying N2O. However, NSCR units are generally not
preferred in modern plants because of high energy costs
and associated high gas temperatures. NSCRs were widely
installed in nitric plants built between 1971 and 1977.
Approximately 20 percent of nitric acid plants use NSCR
(Choe et al. 1993). The remaining 80 percent use SCR or
extended absorption, neither of which is known to reduce
N20 emissions.
N20 emissions from this source were estimated to be
from nitric acid production have decreased by 7 percent since
1990, with the trend in the time series closely tracking the
changes in production.
Methodology
N20 emissions were calculated by multiplying nitric
acid production by the amount of N20 emitted per unit of
nitric acid produced. The emission factor was determined as
a weighted average of 2 kg N20 / metric ton HN03 for plants
using non-selective catalytic reduction (NSCR) systems and
9.5 kg N20 / metric ton HN03 for plants not equipped with
NSCR (Choe et al. 1993). In the process of destroying NOX,
NSCR systems destroy 80 to 90 percent of the N20, which
is accounted for in the emission factor of 2 kg N20 / metric
ton HN03. An estimated 20 percent of HN03 plants in the
United States are equipped with NSCR (Choe et al. 1993).
Hence, the emission factor is equal to (9.5 x 0.80) + (2 x
0.20) = 8 kg N20 per metric ton HN03.
Nitric acid production data for 1990 (see Table 4-58)
was obtained from Chemical and Engineering News, "Facts
and Figures" (C&EN 2001). Nitric acid production data for
1991 through 1992 (see Table 4-58) were obtained from
Chemical and Engineering News, "Facts and Figures"
(C&EN 2002). Nitric acid production data for 1993 was
obtained from Chemical and Engineering News, "Facts and
Figures" (C&EN 2004). Nitric acid production data for 1994
through 2004 were obtained from Chemical and Engineering
News, "Facts and Figures" (C&EN 2005). The emission
factor range was taken from Choe et al. (1993).
Table 4-58: Nitric Acid Production (Gg)
Table 4-57: N20
(Tg
C02 Eq. and
Year
1990
1998
1999
2000
2001
2002
2003
2004
Emissions from Nitric Acid
Gg)
Tg C02 Eq.
17.8
20.9
20.1
19.6
15.9
17.2
16.7
16.6
Production
Gg
58
67
65
63
51
56
54
54
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Gg
7,196
7,191
7,379
7,486
7,904
8,018
8,349
8,556
8,421
8,113
7,898
6,416
6,939
6,747
6,703
Industrial Processes 4-41
-------
Table 4-59: Sources of Uncertainty in N20 Emissions from Nitric Acid Production
Variable
National Production (Gg)
Plants With NSCR (%)
Plants Without NSCR (%)
Emission Factor for Plants With
NSCR (kg N20/tonne HN03)
Emission Factor for Plants Without
NSCR (kg N20/tonne HN03)
Value
6,703
20%
80%
2.0
9.5
Distribution Type
Normal
Normal
Normal
Normal
Normal
Uncertainty Range3
Lower Bound Upper Bound
-10%
-10%
-10%
-10%
-10%
+ 10%
+ 10%
+ 10%
+ 10%
+ 10%
Reference
Expert Judgment
Expert Judgment
Expert Judgment
IPCC Good Practice
IPCC Good Practice
a Parameters presented represent upper and lower bounds as a percentage of the mean, based on a 95 percent confidence interval.
Table 4-60: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From Nitric Acid Production
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Nitric Acid Production N20 16.6
13.9 19.5 -16% +17%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Uncertainty
The overall uncertainty associated with the 2004 N20
emissions estimate from nitric acid production was calculated
using the IPCC Good Practice Guidanceliev 2 methodology.
Uncertainty associated with the parameters used to estimate
N20 emissions included that of production data, the share
of U.S. nitric acid production attributable to each emission
abatement technology, and the emission factors applied to
each abatement technology type. The activity data inputs
and their associated uncertainties and distributions are
summarized in Table 4-59.
The results of this Tier 2 quantitative uncertainty
analysis are summarized in Table 4-60. N20 emissions
from nitric acid production were estimated to be between
13.9 and 19.5 Tg CO2 Eq. at the 95 percent confidence level
(or in 19 out of 20 Monte Carlo Stochastic Simulations).
This indicates a range of approximately 16 percent below
to 17 percent above the 2004 emissions estimate of 16.6
Tg C02 Eq.
Recalculations Discussion
The nitric acid production value for 2003 has been
updated relative to the previous Inventory based on revised
production data presented in C&EN (2005). The updated
production data for 2003 resulted in an increase of 0.9 Tg CO2
Eq. (6 percent) in N20 emissions from nitric acid production
for that year relative to the previous Inventory.
Planned Improvements
Planned improvements are focused on assessing
the plant-by-plant implementation of NOX abatement
technologies to more accurately match plant production
capacities to appropriate emission factors, instead of using
a national profiling of abatement implementation.
4.16. Adipic Acid Production (IPCC
Source Category 2B3)
Adipic acid production is an anthropogenic source of
N20 emissions. Worldwide, few adipic acid plants exist. The
United States is the major producer, with three companies
in four locations accounting for approximately one-third
of world production (CW 2005). Adipic acid is a white
crystalline solid used in the manufacture of synthetic fibers,
coatings, plastics, urethane foams, elastomers, and synthetic
lubricants. Commercially, it is the most important of the
aliphatic dicarboxylic acids, which are used to manufacture
polyesters. Approximately 90 percent of all adipic acid
4-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
produced in the United States is used in the production of
nylon 6,6 (CMR 2001). Food grade adipic acid is also used
to provide some foods with a "tangy" flavor (Thiemens and
Trogler 1991).
Adipic acid is produced through a two-stage process
during which N2O is generated in the second stage. The first
stage of manufacturing usually involves the oxidation of
cyclohexane to form a cyclohexanone/cyclohexanol mixture.
The second stage involves oxidizing this mixture with nitric
acid to produce adipic acid. N20 is generated as a by-product
of the nitric acid oxidation stage and is emitted in the waste
gas stream (Thiemens and Trogler 1991). Process emissions
from the production of adipic acid vary with the types of
technologies and level of emission controls employed by a
facility. In 1990, two of the three major adipic acid-producing
plants had N20 abatement technologies in place and, as of
1998, the three major adipic acid production facilities had
control systems in place.14 Only one small plant, representing
approximately two percent of production, does not control
for N2O (Reimer 1999).
N20 emissions from this adipic acid production were
estimated to be 5.7 Tg C02 Eq. (19 Gg) in 2004 (see Table
4-61).
National adipic acid production has increased by
approximately 36 percent over the period of 1990 through
2004, to approximately one million metric tons. At the same
time, emissions have been significantly reduced due to the
widespread installation of pollution control measures.
Methodology
For two production plants, 1990 to 2002 emission
estimates were obtained directly from the plant engineer
and account for reductions due to control systems in place
at these plants during the time series (Childs 2002, 2003).
These estimates were based on continuous emissions
monitoring equipment installed at the two facilities. Reported
estimates for 2003 and 2004 were unavailable and, thus,
were calculated by applying a 4.4 and 4.2 percent production
growth rate, respectively. The production for 2003 was
obtained through linear interpolation between 2004 and
2002 reported production data. Subsequently, the growth
rate for 2004 was based on the change between the estimated
Table 4-61: N20 Emissions from Adipic Acid Production
(Tg C02 Eq. and Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
15.2
6.0
5.5
6.0
4.9
5.9
6.2
5.7
Gg
49
19
18
19
16
19
20
19
2003 production data and the reported 2004 production data
(see discussion below on sources of production data). For
the other two plants, N20 emissions were calculated by
multiplying adipic acid production by an emission factor
(i.e., N20 emitted per unit of adipic acid produced) and
adjusting for the percentage of N20 released as a result of
plant-specific emission controls. On the basis of experiments,
the overall reaction stoichiometry for N20 production in the
preparation of adipic acid was estimated at approximately 0.3
metric tons of N20 per metric tons of product (Thiemens and
Trogler 1991). Emissions are estimated using the following
equation:
N20 emissions = (production of adipic acid [metric tons
{MT} of adipic acid]) x (0.3 MTN20 / MT adipic acid) x (1 -
[N20 destruction factor x abatement system utility factor])
The "N2O destruction factor" represents the percentage
of N20 emissions that are destroyed by the installed abatement
technology. The "abatement system utility factor" represents
the percentage of time that the abatement equipment operates
during the annual production period. Overall, in the United
States, two of the plants employ catalytic destruction, one
plant employs thermal destruction, and the smallest plant
uses no N20 abatement equipment. The N20 abatement
system destruction factor is assumed to be 95 percent for
catalytic abatement and 98 percent for thermal abatement
(Reimer et al. 1999, Reimer 1999). For the one plant that uses
thermal destruction and for which no reported plant-specific
emissions are available, the abatement system utility factor
is assumed to be 98 percent.
14 During 1997, the N20 emission controls installed by the third plant operated for approximately a quarter of the year.
Industrial Processes 4-43
-------
For 1990 to 2003, plant-specific production data needed
to be estimated where direct emissions measurements were
not available. In order to calculate plant-specific production
for the two plants, national adipic acid production was
allocated to the plant level using the ratio of their known
plant capacities to total national capacity for all U.S. plants.
The estimated plant production for the two plants was then
used for calculating emissions as described above. For 2004,
actual plant production data were obtained for these two
plants and used for emissions calculations.
National adipic acid production data (see Table 4-62)
for 1990 through 2002 were obtained from the American
Chemistry Council (ACC 2003). Production Data for 2003
were estimated based on linear interpolation of 2002 and 2004
reported data. Production data for 2004 were obtained from
Chemical Week, Product Focus: Adipic Acid (CW 2005).
Plant capacity data for 1990 through 1994 were obtained
from Chemical and Engineering News, "Facts and Figures"
and "Production of Top 50 Chemicals" (C&EN 1992,1993,
1994,1995). Plant capacity data for 1995 and 1996 were kept
the same as 1994 data. The 1997 plant capacity data were
taken from Chemical Market Reporter "Chemical Profile:
Adipic Acid" (CMR 1998). The 1998 plant capacity data for
all four plants and 1999 plant capacity data for three of the
plants were obtained from Chemical Week, Product Focus:
Adipic Acid/Adiponitrile (CW 1999). Plant capacity data for
2000 for three of the plants were updated using Chemical
Market Reporter, "Chemical Profile: Adipic Acid" (CMR
Table 4-62: Adipic Acid Production (Gg)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Gg
735
708
724
769
821
830
839
871
862
907
925
835
921
961
1,002
2001). For 2001 through 2004, the plant capacities for these
three plants were kept the same as the year 2000 capacities.
Plant capacity data for 1999 to 2004 for the one remaining
plant was kept the same as 1998.
Uncertainty
The overall uncertainty associated with the 2004
N20 emissions estimate from adipic acid production was
calculated using the IPCC Good Practice Guidance Tier 2
methodology. Uncertainty associated with the parameters used
to estimate N2O emissions included that of company specific
production data, industry wide estimated production growth
rates, emission factors for abated and unabated emissions,
and company specific historical emissions estimates. The
activity data inputs and their associated uncertainties and
distributions are summarized in Table 4-63.
The results of this Tier 2 quantitative uncertainty analysis
are summarized in Table 4-64. N20 emissions from adipic
acid production were estimated to be between 3.2 and 8.3
Tg C02 Eq. at the 95 percent confidence level (or in 19 out
of 20 Monte Carlo Stochastic Simulations). This indicates a
range of approximately 45 percent below to 44 percent above
the 2004 emission estimate of 5.7 Tg C02 Eq.
Recalculations Discussion
The adipic acid industry-wide production value for 2003
was updated through linear interpolation between 2002 and
2004 reported production data. Newly published adipic acid
production figures for 2004 were obtained from Chemical
Week (CW 2005). The updated production data for 2003
resulted in an increase of 0.2 Tg C02 Eq. (3 percent) in N20
emissions from adipic acid production for that year relative
to the previous Inventory.
Planned Improvements
Improvement efforts will be focused on obtaining direct
measurement data from the remaining two plants when
and if they become available. If they become available,
cross verification with top-down approaches will provide a
useful Tier 2 level QC check. Also, additional information
on the actual performance of the latest catalytic and thermal
abatement equipment at plants with continuous emission
monitoring may support the re-evaluation of current default
abatement values.
4-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-63: Sources of Uncertainty in N20 Emissions from Adipic Acid Production
Variable
Value Distribution Type
Uncertainty Range3
Lower Bound Upper Bound
Reference
Company Specific Production (Gg):
Plant 1
Company Specific Production (Gg):
Plant 4
Estimated Production Growth Rates
(2002-2003) (%): Plants 2 and 3
Estimated Production Growth Rates
(2003-2004) (%): Plants 2 and 3
N20 Destruction Factor (%): Plant 4
Abatement System Utility Factor (%):
Plant 4
2002 Emission Estimate (Tg C02 Eq.):
Plant 2
2002 Emission Estimate (Tg C02 Eq.):
Plant 3
17
400
4%
4%
98%
98%
Confidential
Confidential
Normal
Normal
Normal
Normal
Normal
Normal
Normal
Normal
-10%
-10%
-25%
-25%
-5%
-5%
-5%
-5%
+ 10%
+ 10%
+ 25%
+ 25%
+5%
+5%
+5%
+5%
Expert Judgment
Expert Judgment
Expert Judgment
Expert Judgment
IPCC Good Practice
Expert Judgment
Expert Judgment
Expert Judgment
! Parameters presented represent upper and lower bounds as a percentage of the mean, based on a 95 percent confidence interval.
Table 4-64: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Adipic Acid Production
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Adipic Acid Production N20 5.7
3.2 8.3 -45% +44%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4.17. Substitution of Ozone Depleting
Substances (IPCC Source Category
2F)
Hydrofluorocarbons (HFCs) andperfluorocarbons (PFCs)
are used as alternatives to several classes of ozone-depleting
substances (ODSs) that are being phased out under the terms
of the Montreal Protocoland the Clean Air Act Amendments
of 1990.15 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
4-65 and Table 4-66.
In 1990 and 1991, the only significant emissions of
HFCs and PFCs as substitutes to ODSs were relatively small
amounts of HFC- 152a—a component of the refrigerant blend
R-500 used in chillers—and HFC- 134a in refrigeration end-
uses. Beginning in 1992, HFC-134a was used in growing
amounts as a refrigerant in motor vehicle air-conditioners
and in refrigerant blends suchasR-404A.16In 1993, the use
of HFCs in foam production and as an aerosol propellant
began, and in 1994 these compounds also found applications
15 [42 U.S.C § 7671, CAA § 601]
16 R-404A contains HFC-125, HFC-143a, and HFC-134a.
Industrial Processes 4-45
-------
Table 4-65: Emissions of MFCs and PFCs from ODS Substitutes (Tg C02 Eq.)
Gas
HFC-23
HFC-32
HFC-125
HFC-134a
HFC-143a
HFC-236fa
CF4
Others*
Total
1990
+
+
+
+
+
+
+
0.4
0.4
1998
+
0.3
8.8
35.2
5.2
0.4
+
4.6
54.5
1999
0.1
0.3
10.0
40.2
6.6
0.9
+
4.8
62.8
2000
0.1
0.3
11.2
45.4
8.2
1.4
+
4.6
71.2
2001
0.1
0.3
12.3
49.7
10.1
1.8
+
4.5
78.6
2002
0.1
0.3
13.4
53.5
12.2
2.1
+
4.6
86.2
2003
0.1
0.4
14.7
56.8
14.6
2.3
+
4.6
93.5
2004
0.1
0.4
16.3
61.6
17.3
2.3
+
5.3
103.3
+ Does not exceed 0.05 Tg C02 Eq.
* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee, and PFC/PFPEs, the latter being a proxy for a diverse collection of PFCs and
perfluoropolyethers (PFPEs) employed for solvent applications. For estimating purposes, the GWP value used for PFC/PFPEs was based upon C6F14.
Note: Totals may not sum due to independent rounding.
Table 4-66: Emissions of MFCs and PFCs from ODS Substitution (Mg)
Gas
HFC-23
HFC-32
HFC-125
HFC-1343
HFC-1433
HFC-236f3
CF4
Others*
1990 1998
+ 4
+ 430
+ 3,134
+ 27,058
+ 1,369
+ 64
+ 1
M M
1999
4
439
3,571
30,902
1,738
142
1
M
2000
5
443
4,006
34,927
2,162
214
1
M
2001
5
463
4,390
38,196
2,647
281
1
M
2002
6
501
4,787
41,170
3,203
341
2
M
2003
6
557
5,262
43,664
3,834
369
2
M
2004
7
631
5,821
47,391
4,543
367
3
M
M (Mixture of Gases)
+ Does not exceed 0.5 Mg
* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee and PFC/PFPEs, the latter being a proxy for a diverse collection of PFCs and
perfluoropolyethers (PFPEs) employed for solvent applications.
as solvents and sterilants. In 1995, ODS substitutes for
halons entered widespread use in the United States as halon
production was phased-out.
The use and subsequent emissions of HFCs and PFCs
as ODS substitutes has been increasing from small amounts
in 1990 to 103.3 Tg CO2 Eq. in 2004. This increase was in
large part the result of efforts to phase out CFCs and other
ODSs in the United States. In the short term, this trend is
expected to continue, and will likely accelerate over the next
decade as HCFCs, which are interim substitutes in many
applications, are themselves phased-out under the provisions
of the Copenhagen Amendments to the Montreal Protocol.
Improvements in the technologies associated with the use
of these gases and the introduction of alternative gases and
technologies, however, may help to offset this anticipated
increase in emissions.
The end-use sectors that contribute the most toward
emissions of HFCs and PFCs as ODS substitutes include
refrigeration and air-conditioning (88.4 Tg C02 Eq., or
approximately 85 percent), aerosols (11.1 Tg CO2 Eq., or
approximately 11 percent), and solvents (1.6 Tg CO2 Eq., or
approximately 2 percent). Within the refrigeration and air-
conditioning end-use sector, motor vehicle air-conditioning
was the highest emitting end-use (31.9 Tg CO2 Eq.), followed
by retail food and refrigerated transport. In the aerosols end-
use sector, non-metered-dose inhaler (MDI) emissions make
up a majority of the end-use sector emissions.
Methodology
A detailed Vintaging Model of ODS-containing
equipment and products was used to estimate the
actual—versus potential—emissions of various ODS
substitutes, including HFCs and PFCs. The name of the
model refers to the fact that the model tracks the use and
emissions of various compounds for the annual "vintages"
of new equipment that enter service in each end-use. This
4-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Vintaging Model predicts ODS and ODS substitute use
in the United States based on modeled estimates of the
quantity of equipment or products sold each year containing
these chemicals and the amount of the chemical required to
manufacture and/or maintain equipment and products over
time. Emissions for each end-use were estimated by applying
annual leak rates and release profiles, which account for the
lag in emissions from equipment as they leak over time. By
aggregating the data for more than 50 different end-uses,
the model produces estimates of annual use and emissions
of each compound. Further information on the Vintaging
Model is contained in Annex 3.8.
Uncertainty
Given that emissions of ODS substitutes occur from
thousands of different kinds of equipment and from millions
of point and mobile sources throughout the United States,
emission estimates must be made using analytical tools
such as the Vintaging Model or the methods outlined in
IPCC/UNEP/OECD/IEA (1997). Though the model is
more comprehensive than the IPCC default methodology,
significant uncertainties still exist with regard to the levels
of equipment sales, equipment characteristics, and end-
use emissions profiles that were used to estimate annual
emissions for the various compounds.
The Vintaging Model estimates emissions from over 50
end-uses. The uncertainty analysis, however, quantifies the
level of uncertainty associated with the aggregate emissions
resulting from the top 15 end-uses and 5 others. These end-
uses together account for 95 percent of emissions from this
source category. In an effort to improve the uncertainty
analysis, additional end-uses are added annually, with the
intention that over time uncertainty for all emissions from
the Vintaging Model will be fully characterized. This year,
an additional 5 end-uses were included in the uncertainty
estimate. Since the foams sector is not represented in the top
15, the two highest emitting foams end-uses were chosen to
represent this sector, and two MDI aerosols end-uses were
included to represent the MDI portion of the aerosols sector.
Any end-uses included in previous years' uncertainty analysis
were included in the current uncertainty analysis, whether
or not those end-uses were included in the top 95 percent of
emissions from ODS Substitutes.
In order to calculate uncertainty, functional forms were
developed to simplify some of the complex "vintaging"
aspects of some end-use sectors, especially with respect to
refrigeration and air-conditioning, and to a lesser degree,
fire extinguishing. These sectors calculate emissions based
on the entire lifetime of equipment, not just equipment put
into commission in the current year, thereby necessitating
simplifying equations. The functional forms used variables that
included growth rates, emission factors, transition from ODSs,
change in charge size as a result of the transition, disposal
quantities, disposal emission rates, and either stock for the
current year or original ODS consumption. Uncertainty was
estimated around each variable within the functional forms
based on expert judgment, and a Monte Carlo analysis was
performed. The most significant sources of uncertainty for
this source category include the emission factors for mobile
air-conditioning and retail food refrigeration, as well as the
stock (MT) of retail food refrigerant.
The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 4-67. Substitution of ozone
depleting substances HFC and PFC emissions were estimated
to be between 90.5 and 124.4 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 13
percent below to 20 percent above the emission estimate of
103.3 Tg C02 Eq.
Table 4-67: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes
(Tg C02 Eq. and Percent)
Source
2004 Emission
Estimate
Gases (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound
Lower Bound Upper Bound
Substitution of Ozone
Depleting Substances
MFCs and PFCs
103.3
90.5
124.4
-13%
+20%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-47
-------
Recalculations Discussion
An extensive review of the chemical substitution
trends, market sizes, growth rates, and charge sizes,
together with input from industry representatives, resulted
in updated assumptions for the Vintaging Model. These
changes resulted in an average annual net decrease of 2.0
Tg C02 Eq. (3 percent) in HFC and PFC emissions from the
substitution of ozone depleting substances for the period
1990 through 2003.
4.18. HCFC-22 Production (IPCC
Source Category 2E1)
Trifluoromethane (HFC-23 or CHF3) is generated as a
by-product during the manufacture of chlorodifluoromethane
(HCFC-22), which is primarily employed in refrigeration
and air conditioning systems and as a chemical feedstock
for manufacturing synthetic polymers. Between 1990
and 2000, U.S. production of HCFC-22 increased
significantly as HCFC-22 replaced chlorofluorocarbons
(CFCs) in many applications. Since 2000, however, U.S.
production has declined to levels near those of the early
to mid 1990s. 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.17
Feedstock production, however, is permitted to continue
indefinitely.
HCFC-22 is produced by the reaction of chloroform
(CHC13) and hydrogen fluoride (HF) in the presence of a
Table 4-68: HFC-23 Emissions from HCFC-22
Production (Tg C02 Eq. and Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
35.0
40.1
30.4
29.8
19.8
19.8
12.3
15.6
Gg
3
3
3
3
2
2
1
1
catalyst, SbCl5. The reaction of the catalyst and HF produces
SbClxFy, (where x + y = 5), which reacts with chlorinated
hydrocarbons to replace chlorine atoms with fluorine. The
HF and chloroform are introduced by submerged piping
into a continuous-flow reactor that contains the catalyst in a
hydrocarbon mixture of chloroform and partially fluorinated
intermediates. The vapors leaving the reactor contain HCFC-
21 (CHC12F), HCFC-22 (CHC1F2), HFC-23 (CHF3), HC1,
chloroform, and HF. The under-fluorinated intermediates
(HCFC-21) and chloroform are then condensed and returned
to the reactor, along with residual catalyst, to undergo further
fluorination. The final vapors leaving the condenser are
primarily HCFC-22, HFC-23, HC1 and residual HF. The HC1
is recovered as a useful byproduct, and the HF is removed.
Once separated from HCFC-22, the HFC-23 is generally
vented to the atmosphere as an unwanted by-product, but
it is sometimes captured for use in a limited number of
applications.
Emissions of HFC-23 in 2004 were estimated to be 15.6
Tg C02 Eq. (1.3 Gg) (Table 4-68). This quantity represents
a 26 percent increase from 2003 emissions and a 55 percent
decline from 1990 emissions. The increase from 2003
emissions is due to an increase in HCFC-22 production, while
the decline from 1990 emissions is primarily due to the steady
decline in the emission rate of HFC-23 (i.e., the amount of
HFC-23 emitted per kilogram of HCFC-22 manufactured).
Table 4-69: HCFC-22 Production (Gg)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Gg
139
143
150
132
147
155
166
165
183
166
187
152
144
138
155
17 As construed, interpreted, and applied in the terms and conditions of the Montreal Protocol on Substances that Deplete the Ozone Layer. [42 U.S.C.
§7671m(b), CAA §614]
4-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 4-70: Tier 1 Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
HCFC-22 Production HFC-23 15.6
14.0 17.2 -10% +10%
! Range of emission reflect a 95 percent confidence interval.
Three HCFC-22 production plants operated in the United
States in 2004, two of which used thermal oxidation to
significantly lower their HFC-23 emissions.
Methodology
The methodology employed for estimating emissions is
based upon measurements at individual HCFC-22 production
plants. Plants using thermal oxidation to abate their HFC-
23 emissions monitor the performance of their oxidizers to
verify that the HFC-23 is almost completely destroyed. The
other plants periodically measure HFC-23 concentrations
in the output stream using gas chromatography. This
information is combined with information on quantities of
critical feed components (e.g., HF) and/or products (HCFC-
22) to estimate HFC-23 emissions using a material balance
approach. HFC-23 concentrations are determined at the point
the gas leaves the chemical reactor; therefore, estimates also
include fugitive emissions.
Production data and emission estimates were prepared
in cooperation with the U.S. manufacturers of HCFC-22
(ARAP 1997, 1999, 2000, 2001, 2002, 2003, 2004; 2005;
RTI 1997). Annual estimates of U.S. HCFC-22 production
are presented in Table 4-69.
4.19. Electrical Transmission and
Distribution (IPCC Source Category
2F7)
The largest use of SF6, both in the United States and
internationally, is as an electrical insulator and interrupter in
equipment that transmits and distributes electricity (PsAND
2004). The gas has been employed by the electric power
industry in the United States since the 1950s because of its
dielectric strength and arc-quenching characteristics. It is
used in gas-insulated substations, circuit breakers, and other
switchgear. Sulfur hexafluoride has replaced flammable
insulating oils in many applications and allows for more
compact substations in dense urban areas.
Fugitive emissions of SF6 can escape from gas-insulated
substations and switch gear through seals, especially from
older equipment. The gas can also be released during
equipment manufacturing, installation, servicing, and
disposal. Emissions of SF6 from electrical transmission
and distribution systems were estimated to be 13.8 Tg CO2
Eq. (0.6 Gg) in 2004. This quantity represents a 52 percent
decrease from the estimate for 1990 (see Table 4-71 and
Table 4-71: SF6 Emissions from Electric Power Systems
Uncertainty
A high level of confidence has been attributed to the
HFC-23 concentration data employed because measurements
were conducted frequently and accounted for day-to-day
and process variability. The results of the Tier 1 quantitative
uncertainly analysis are summarized in Table 4-70. HFC-
23 emissions from HCFC-22 production were estimated
to be between 14.0 and 17.2 Tg CO2 Eq. at the 95 percent
confidence level. This indicates a range of 10 percent above
and 10 percent below the 2004 emission estimate of 15.6
Tg C02 Eq.
and Original Equipment Manufactures (Tg C02 Eq.)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Electric Power Systems
28.3
16.4
15.5
14.6
14.7
13.8
13.4
13.1
Original Equipment
Manufacturers
0.3
0.4
0.6
0.7
0.7
0.7
0.7
0.7
Total
28.6
16.7
16.1
15.3
15.3
14.5
14.0
13.8
Industrial Processes 4-49
-------
Table 4-72: SF6 Emissions from Electric Power Systems
and Original Equipment Manufactures (Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Emissions
1.2
0.7
0.7
0.6
0.6
0.6
0.6
0.6
Table 4-72). This decrease is believed to be a response to
increases in the price of SF6 during the 1990s and to growing
awareness of the environmental impact of SF6 emissions,
through programs such as the EPA's SF6 Emission Reduction
Partnership for Electric Power Systems.
Methodology
The estimates of emissions from electric transmission
and distribution are comprised of emissions from electric
power systems and emissions from the manufacture of
electrical equipment. The methodologies for estimating both
sets of emissions are described below.
1999 to 2004 Emissions from Electric Power Systems
Emissions from electric power systems from 1999 to
2004 were estimated based on: (1) reporting from utilities
participating in EPA's SF6 Emissions Reduction Partnership
for Electric Power Systems, which began in 1999; and, (2)
utilities' transmission miles as reported in the 2001 and 2004
Utility Data Institute (UDI) Directories of Electric Power
Producers and Distributors (UDI 2001,2004). (Transmission
miles are defined as the miles of lines carrying voltages above
34.5 kV.) Over the period from 1999 to 2004, participating
utilities represented between 31 percent and 39 percent of
total U.S. transmission miles. For each year, the emissions
reported by participating utilities were added to the emissions
estimated for utilities that do not participate in the EPA's SF6
Emission Reduction Partnership (i.e., non-partners).
Emissions from utilities participating in EPA's SF6
Emission Reduction Partnership were estimated using a
combination of reported data and, where reported data
were unavailable, interpolated or extrapolated data. If a
partner utility did not provide data for a historical year,
emissions were interpolated between years for which data
were available. For 2004, if no data was provided, estimates
were calculated based on historical trends or partner-specific
emission reduction targets (i.e., it was assumed that emissions
would decline linearly towards a partners' future stated goal).
In 2004, non-reporting partners account for approximately 2
percent of the total emissions attributable to utilities involved
in the SF6 Emission Reduction Partnership.
Emissions from non-partners in every year since 1999
were estimated using the results of a regression analysis
that showed that the emissions of reporting utilities were
most strongly correlated with their transmission miles. The
results of this analysis are not surprising given that, in the
United States, SF6 is contained primarily in transmission
equipment rated at or above 34.5 kV. The equations were
developed based on the 1999 SF6 emissions reported by 49
partner utilities (representing approximately 31 percent of
U.S. transmission miles), and 2000 transmission mileage
data obtained from the 2001 UDI Directory of Electric Power
Producers and Distributors (UDI 2001). Two equations were
developed, one for small and one for large utilities (i.e., with
less or more than 10,000 transmission miles, respectively).
The distinction between utility sizes was made because the
regression analysis showed that the relationship between
emissions and transmission miles differed for small and
large transmission networks. The same equations were used
to estimate non-partner emissions in 1999 and every year
thereafter because it was assumed that non-partners have
not implemented any changes that have resulted in reduced
emissions since 1999.
The regression equations are:
Non-partner small utilities (less than 10,000 transmission
miles, in kilograms):
Emissions = 0.874 x Transmission Miles
Non-partner large utilities (more than 10,000 transmission
miles, in kilograms):
Emissions = 0.558 x Transmission Miles
Data on transmission miles for each non-partner utility
for the years 2000 and 2003 was obtained from the 2001
and 2004 UDI Directories of Electric Power Producers and
Distributors, respectively (UDI 2001, 2004). Given that the
U.S. transmission system grew by over 14,000 miles between
2000 and 2003, and that this increase probably occurred
4-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
gradually, transmission mileage was assumed to increase
exponentially at an annual rate of 0.7 percent between 2000
and 2003. This growth rate is assumed to continue through
2004.
As a final step, total emissions were determined for
each year by summing the partner emissions (reported to
the EPA's SF6 Emission Reduction Partnership for Electric
Power Systems), and the non-partner emissions (determined
using the 1999 regression equation).
1990 to 1998 Emissions from Electric Power Systems
Because most participating utilities reported emissions
only for 1999 through 2004, modeling SF6 emissions from
electric power systems for the years 1990 through 1998
was necessary. To do so, it was assumed that during this
period, U.S. emissions followed the same trajectory as global
emissions from this source. To estimate global emissions,
the RAND survey of global SF6 sales to electric utilities was
used, together with the following equation, which is derived
from the equation for emissions in the IPCC Good Practice
Guidance (IPCC 2000):
Emissions (kilograms) =
SF6 purchased to refill existing equipment (kilograms) +
nameplate capacity of retiring equipment (kilograms)
Note that the above equation holds whether the gas from
retiring equipment is released or recaptured; if the gas is
recaptured, it is used to refill existing equipment, lowering
the amount of SF6 purchased by utilities for this purpose.
Sulfur hexafluoride purchased to refill existing
equipment in a given year was assumed to be approximately
equal to the SF6 purchased by utilities in that year. Gas
purchases by utilities and equipment manufacturers from
1961 through 2001 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 77.5 percent
of the amount of gas purchased by electrical equipment
manufacturers 30 years previous (e.g., in 1990, the nameplate
capacity of retiring equipment was assumed to equal 77.5
percent of the gas purchased in 1960). The remaining 22.5
percent was assumed to have been emitted at the time of
manufacture. The 22.5 percent emission rate is an average
of IPCC SF6 emission rates for Europe and Japan for years
before 1996 (IPCC 2000). The 30-year lifetime for electrical
equipment is also drawn from IPCC (2000). The results
of the two components of the above equation were then
summed to yield estimates of global SF6 emissions from
1990 through 1998.
To estimate U.S. emissions for 1990 through 1998,
estimated 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. To estimate historical U.S. emissions, the factor
for each year was multiplied by the estimated U.S. emissions
of SF6 from electric power systems in 1999 (estimated to be
15.5TgC02Eq.).
1990 to 2004 Emissions from Manufacture of Electrical
Equipment
The 1990 to 2004 emissions estimates for original
equipment manufacturers (OEMs) were derived by assuming
that manufacturing emissions equal 10 percent of the
quantity of SF6 charged into new equipment. The quantity
of SF6 charged into new equipment was estimated based on
statistics compiled by the National Electrical Manufacturers
Association (NEMA). These statistics were provided for 1990
to 2000; the quantities of SF6 charged into new equipment
for 2001 to 2004 were assumed to equal that charged into
equipment in 2000. The 10 percent emission rate is the
average of the "ideal" and "realistic" manufacturing emission
rates (4 percent and 17 percent, respectively) identified in
a paper prepared under the auspices of the International
Council on Large Electric Systems (CIGRE) in February
2002 (O'Connelletal. 2002).
Uncertainty
To estimate the uncertainty associated with emissions
of SF6 from electric transmission and distribution, EPA
estimated the uncertainties associated with three variables:
(1) emissions from electric power systems that participate
in EPA's SF6 Emission Reduction Partnership, (2) emissions
from electric power systems that do not participate in the
Partnership, and (3) emissions from manufacturers of
electrical equipment. A Monte Carlo analysis was then
applied to estimate the overall uncertainty of the emissions
estimate.
The cumulative uncertainty of all partner data was
estimated to be 5 percent, based on error propagation. There
are two sources of uncertainty associated with the regression
Industrial Processes 4-51
-------
Table 4-73: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Electrical Transmission
and Distribution SF6 13.8
12.0 15.7 -13% +13%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
equations used to estimate emissions in 2004 from non-
partners : (1) uncertainty in the coefficients (as defined by the
regression standard error estimate); and, (2) the uncertainty in
total transmission miles for non-partners, which is assumed to
be 10 percent. In addition, there is uncertainty associated with
the assumption that the emission factor used for non-partner
utilities (which accounted for approximately 65 percent of
U.S. transmission miles) will remain at levels defined by
partners who reported in 1999. However, the last source of
uncertainty was not modeled.
For OEMs, uncertainty estimates are based on the
assumption that SF6 statistics obtained from NEMA have
an uncertainty of 20 percent. Additionally, the OEMs SF6
emissions rate has an uncertainty bounded by the proposed
"actual" and "ideal" emission rates defined in O'Connell,
et al. (2002). That is, the uncertainty in the emission rate is
approximately 65 percent.
A Monte Carlo analysis was applied to estimate the
overall uncertainty of the 2004 emission estimate for SF6
from electrical transmission and distribution. For each
defined parameter (i.e., equation coefficient, transmission
mileage, and partner-reported and partner-estimated SF6
emissions data for electric power systems; and SF6 emission
rate and statistics for OEMs), random variables were selected
from probability density functions, all assumed to have
normal distributions about the mean. The results of the Tier
2 quantitative uncertainty analysis are summarized in Table
4-73. Electrical Transmission and Distribution SF6 emissions
were estimated to be between 12.0 and 15.7 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 13 percent below and 13 percent above the
emission estimate of 13.8 Tg CO2 Eq.
In addition to the uncertainty quantified above, there
is uncertainty associated with using global SF6 sales data
to estimate U.S. emission trends from 1990 through 1999.
However, the trend in global emissions implied by sales of
SF6 appears to reflect the trend in global emissions implied
by changing SF6 concentrations in the atmosphere. That
is, emissions based on global sales declined by 21 percent
between 1995 and 1998, and emissions based on atmospheric
measurements declined by 27 percent over the same period.
However, U.S. emission patterns may differ from global
emission patterns.
4.20. Semiconductor Manufacture
(IPCC Source Category 2F6)
The semiconductor industry uses multiple long-lived
fluorinated gases in plasma etching and plasma enhanced
chemical vapor deposition (PECVD) processes to produce
semiconductor products. The gases most commonly employed
are trifluoromethane (HFC-23 or CHF3), perfluoromethane
(CF4), perfluoroethane (C2F6), nitrogen trifluoride (NF3),
and sulfur hexafluoride (SF6), although other compounds
such as perfluoropropane (C3F8) and perfluorocyclobutane
(c^Fg) are also used. The exact combination of compounds
is specific to the process employed.
A single 300 mm silicon wafer that yields between
400 to 500 semiconductor products (devices or chips) may
require as many as 100 distinct fluorinated-gas-using process
steps, principally to deposit and pattern dielectric films.
Plasma etching (or patterning) of dielectric films, such as
silicon dioxide and silicon nitride, is performed to provide
pathways for conducting material to connect individual
circuit components in each device. The patterning process
uses plasma-generated fluorine atoms, which chemically
react with exposed dielectric film, to selectively remove
the desired portions of the film. The material removed as
well as undissociated fluorinated gases flow into waste
4-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
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 2004, total weighted emissions of all fluorinated
greenhouse gases by the U.S. semiconductor industry were
estimated to be 4.7 Tg C02 Eq. Combined emissions of all
fluorinated greenhouse gases are presented in Table 4-74 and
Table 4-75, below. The rapid growth of this industry and the
increasing complexity of semiconductor products which use
more PFCs in the production process have led to an increase
in emissions of 61 percent since 1990. The emissions growth
rate began to slow after 1997, and emissions declined by 35
percent between 1999 and 2004. The initial implementation
of PFC emission reduction methods such as process
optimization and abatement technologies is responsible for
this decline.
Methodology
Emissions from semiconductor manufacturing were
estimated using three distinct methods, one each for the
periods 1990 through 1994,1995 through 1999, and 2000 and
beyond. For 1990 through 1994, emissions were estimated
using the most recent version of EPA's PFC Emissions
Vintage Model (PEVM) (Burton and Beizaie 2001).18 PFC
emissions per square centimeter of silicon increase as the
number of layers in semiconductor devices increases. Thus,
PEVM incorporates information on the two attributes of
semiconductor devices that affect the number of layers: (1)
linewidth technology (the smallest feature size, which leads
Table 4-74: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg C02 Eq.)
Year
CF4
C2F6
C^FS
C4F8
HFC-23
SF6
NF3*
Total
1990
0.7
1.5
0.0
0.0
0.2
0.5
0.0
2.9
1998
1.8
3.6
0.0
0.0
0.4
1.3
0.1
7.1
1999
1.8
3.7
0.0
0.0
0.4
1.3
0.1
7.2
2000
1.8
3.0
0.1
0.0
0.3
1.1
0.1
6.3
2001
1.3
2.1
0.1
0.0
0.2
0.8
0.1
4.5
2002
1.1
2.2
0.1
0.0
0.2
0.7
0.3
4.4
2003
1.0
2.1
0.1
0.1
0.2
0.8
0.2
4.3
2004
1.2
2.2
0.0
0.1
0.2
0.9
0.3
4.7
Note: Totals may not sum due to independent rounding.
* NF3 emissions are presented for informational purposes, using a GWP of 8,000, and are not included in totals.
Table 4-75: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg)
Year
CF4
C2F6
C^FS
C4F8
HFC-23
SF6
NF3
1990
115
160
0
0
15
22
3
1998
277
391
0
0
37
54
9
1999
281
397
0
0
37
55
9
2000
281
324
17
0
23
46
11
2001
202
231
14
0
16
31
12
2002
175
244
9
5
15
28
32
2003
161
228
13
8
17
35
30
2004
185
245
6
9
20
38
31
18 The most recent version of this model is v.3.2.0506.0507, completed in September 2005.
Industrial Processes 4-53
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to an increasing number of layers),19 and (2) product type
(memory vs. logic) .20 PEVM derives historical consumption
of silicon (i.e., square centimeters) by linewidth technology
from published data on annual wafer starts and average
wafer size (Burton and Beizaie 2001). For each linewidth
technology, a weighted average number of layers is estimated
using VLSI product-specific worldwide silicon demand data
in conjunction with complexity factors (i.e., the number
of layers per integrated circuit) specific to product type
(Burton and Beizaie 2001; ITRS 2005). The distribution of
memory/logic devices ranges over the period covered from
52 percent logic devices in 1995 to 59 percent logic devices
in 2000. These figures were used to determine emission
factors that express emissions per average layer per unit
of area of silicon consumed during product manufacture.
The per-layer emission factor was based on the total annual
emissions reported by participants in EPA's PFC Reduction/
Climate Partnership for the Semiconductor Industry in 1995
and later years.
For 1995 through 1999, total U.S. emissions were
extrapolated from the total annual emissions reported by
the Partnership participants (Burton and Mallya 2005).
The emissions reported by the participants were divided by
the ratio of the total layer-weighted capacity of the plants
operated by the participants and the total layer-weighted
capacity of all of the semiconductor plants in the United
States; this ratio represents the share of layer-weighted
capacity attributable to partnership participants. The layer-
weighted capacity of a plant (or group of plants) consists of
the silicon capacity of that plant multiplied by the estimated
number of layers used to fabricate products at that plant.
This method assumes that participants and non-participants
have similar capacity utilizations and per-layer emission
factors. Plant capacity, linewidth technology, products
manufactured information is contained in the World Fab
Watch (WFW) database, which is updated quarterly (see
for example, Semiconductor Equipment and Materials
Industry 2005).
The U.S. estimate for the years 2000 through 2004—the
period during which partners began the consequential
application of PFC-reduction measures—used a different
estimation method. The emissions reported by Partnership
participants for each year were accepted as the quantity
emitted from the share of the industry represented by those
Partners. Remaining emissions (those from non-partners),
however, were estimated using PEVM and the method
described above. (Non-partners are assumed not to have
implemented any PFC-reduction measures, and PEVM
models emissions without such measures.) The portion
of the U.S. total attributed to non-Partners is obtained by
multiplying PEVM's total U.S. figure by the non-partner
share of total layer-weighted silicon capacity for each year (as
described above). Annual updates to PEVM reflect published
figures for actual silicon consumption from VLSI Research,
Inc. as well as revisions and additions to the world population
of semiconductor manufacturing plants (see Semiconductor
Equipment and Materials Industry 2005) .21
Two different approaches were also used to estimate
the distribution of emissions of specific PFCs. Before 1999,
when there was no consequential adoption of PFC-reducing
measures, a fixed distribution was assumed to apply to the
entire U.S. industry. This distribution was based upon the
average PFC purchases by semiconductor manufacturers
during this period and the application of IPCC default
emission factors for each gas (Burton and Beizaie 2001).
For the 2000 through 2004 period, the 1990 through 1999
distribution was assumed to apply to the non-Partners.
Partners, however, began to report gas-specific emissions
19 By decreasing features of 1C components, more components can be manufactured per device, which increases its functionality. However, as those
individual components shrink it requires more layers to interconnect them to achieve the functionality. For example, a microprocessor manufactured with
the smallest feature sizes (65 nm) might contain as many as 1 billion transistors and requires as many as 11 layers of component interconnects to achieve
functionality while a device manufactured with 130 nm feature size might contain a few hundred million transistors and require 8 layers of component
interconnects (ITRS, 2005).
20 Memory devices manufactured with the same feature sizes as microprocessors (a logic device) require approximately one-half the number of interconnect
layers (ITRS, 2005).
21 Special attention was given to the manufacturing capacity of plants that use wafers with 300 mm diameters because the actual capacity of these plants
in 2004 is below design capacity, the figure provided in WFW. To prevent overstating estimates of partner-capacity shares from plants using 300 mm
wafers, design capacities contained in WFW were replaced with estimates of actual installed capacities for 2004 published by Citigroup Smith Barney
(2005). Without this correction, the partner share of capacity would be overstated, by approximately 5 percentage points. For perspective, approximately
95 percent of all new capacity additions in 2004 used 300 mm wafers and by year-end those plants, on average, could operate at but approximately 70
percent of the design capacity.
4-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
during this period. Thus, gas specific emissions for 2000
through 2004 were estimated by adding the emissions
reported by the Partners to those estimated for the non-
Partners.22
Partners estimate their emissions using a range of
methods. For 2004, most participants cited a method at
least as accurate as the IPCC's Tier 2c Methodology,
recommended in the IPCC Good Practice Guidance (IPCC
2000). The partners with relatively high emissions typically
use the more accurate IPCC 2b or 2a methods, multiplying
estimates of their PFC consumption by process-specific
emission factors that they have either measured or obtained
from tool suppliers.
Data used to develop emission estimates were prepared
in cooperation with the Partnership. Estimates of operating
plant capacities and characteristics for participants and
non-participants were derived from the Semiconductor
Equipment and Materials Industry (SEMI) World Fab Watch
(formerly International Fabs on Disk) database (1996 to
2004). Estimates of silicon consumed by line-width from
1990 through 2004 were derived from information from
VLSI Research (2005), and the number of layers per line-
width was obtained from International Technology Roadmap
for Semiconductors: 1998-2004 (Burton and Beizaie 2001,
ITRS 2005).
Uncertainty
A quantitative uncertainty analysis of this source
category was performed using the IPCC-recommended Tier
2 uncertainty estimation methodology, the Monte Carlo
Stochastic Simulation technique. The equation used to
estimate both emissions and their uncertainty is:
U.S. emissions =
Non-partnership share of MSI-layer capacity x
PEVM estimate + Partnership submittal
The Monte Carlo analysis results presented below relied
on estimates of uncertainty attributed to the three variables
on the right side of the equation. Estimates of uncertainty for
the three variables were in turn developed using the estimated
uncertainties associated with the individual inputs to each
variable, error propagation analysis, and expert judgment.
For the first variable, the aggregate PFC emissions data
supplied to the partnership, EPA estimated an uncertainty
of approximately +10 percent (representing a 95 percent
confidence interval). For the second variable, the share of
U.S. layer-weighted silicon capacity accounted for by non-
Partners, an uncertainty of+10 percent was assumed based on
information from the firm that compiled the database (SMA
2003). For the third variable, the relative error associated with
the PEVM estimate in 2004, EPA estimated an uncertainty
of+20 percent, using the calculus of error propagation and
considering the aggregate average emission factor, world
silicon consumption, and the U.S. share of layer-weighted
silicon capacity.
Consideration was also given to the nature and
magnitude of the potential bias that PEVM might have in
its estimates of the number of layers associated with devices
manufactured at each technology node. The result of a brief
analysis indicated that PEVM overstates the average number
of layers across all product categories and all manufacturing
Table 4-76: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor
Manufacture (Tg C02 Eq. and Percent)
Source
Semiconductor Manufacture
Gas
HFC, PFC,
and SF6
2004 Emission Uncertainty Range Relative to Emission Estimate11
Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound
4.7 3.8
Upper Bound
6.1
Lower Bound
-23%
Upper Bound
+ 23%
a Because the uncertainty analysis covered all emissions (including NF3), the emission estimate presented here does not match that shown in Table
4-74.
b Range of emissions estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
22 In recent years, the Partnership started reporting gas-specific emissions using GWP values from the Third Assessment Report (TAR), while in previous
years the values were taken from the Second Assessment Report (SAR). The emissions reported here are restated using GWPs from the SAR.
Industrial Processes 4-55
-------
technologies for 2004by 0.12 layers or 2.9 percent. This bias
is represented in the uncertainty analysis by deducting the
absolute bias value from the PEVM emissions estimate when
it is incorporated into the Monte Carlo analysis.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 4-76. The emissions estimate for
total U.S. PFC emissions from semiconductor manufacturing
were estimated to be between 3.8 and 6.1 Tg CO2 Eq. at a
95 percent confidence level (or in 19 out of 20 Monte Carlo
Stochastic Simulations). This range represents 23 percent
below to 23 percent above the 2004 emission estimate of
4.7 Tg C02 Eq. This range and the associated percentages
apply to the estimate of total emissions rather than those of
individual gases. Uncertainties associated with individual
gases will be somewhat higher than the aggregate, but were
not explicitly modeled.
Planned Improvements
The method to estimate non-partner related emissions
(i.e., PEVM) is not expected to change (with the exception
of possible future updates to emission factors and added
technology nodes). Future improvements to the national
emission estimates will primarily be associated with
determining the portion of national emissions to attribute to
partner report totals (about 80 percent in recent years). As
the nature of the partner reports change through time and
industry-wide reduction efforts increase, consideration will
be given to what emission reduction efforts—if any—are
likely to be occurring at non-partner facilities (currently none
are assumed to occur).
4.21. Aluminum Production (IPCC
Source Category 2C3)
C02 is emitted during the aluminum smelting process
when alumina (aluminum oxide, A1203) is reduced to
aluminum using the Hall-Heroult reduction process. The
reduction of the alumina occurs through electrolysis in a
molten bath of natural or synthetic cryolite (Na3AlF6). The
reduction cells contain a 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 CO2.
Process emissions of CO2 from aluminum production
were estimated to be 4.3 Tg C02 Eq. (4,346 Gg) in 2004 (see
Table 4-77). 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 C02
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 C02 from Fossil Fuel Combustion
source category of the Energy sector. Similarly, the coal tar
pitch portion of these C02 process emissions is accounted
for here rather than in the Iron and Steel source category of
the Industrial Processes sector.
In addition to C02 emissions, the aluminum production
industry is also a source of PFC emissions. During the
smelting process, when the alumina ore content of the
electrolytic bath falls below critical levels required for
electrolysis, rapid voltage increases occur, which are termed
"anode effects." These anode effects cause carbon from the
anode and fluorine from the dissociated molten cryolite bath
to combine, thereby producing fugitive emissions of CF4
and C2F6. In general, the magnitude of emissions for a given
level of production depends on the frequency and duration
Table 4-77: CO? Emissions from Aluminum Production
Aluminum is a light-weight, malleable, and corrosion-
resistant metal that is used in many manufactured products,
including aircraft, automobiles, bicycles, and kitchen
utensils. In 2004, the United States was the fourth largest
producer of primary aluminum, with eight percent of the
world total (USGS 2005). 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 C02 and
two perfluorocarbons (PFCs): perfluoromethane (CF4) and
perfluoroethane (C2Fg) .
(Tg C02 Eq. and Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
7.0
6.4
6.5
6.2
4.5
4.6
4.3
Gg
7,045
6,359
6,458
6,244
4,505
4^609
4,346
4-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
of these anode effects. As the frequency and duration of the
anode effects increase, emissions increase.
Since 1990, emissions of CF4 and C2F6 have declined
85 percent and 81 percent, respectively, to 2.4 Tg CO2 Eq.
of CF4 (0.4 Gg) and 0.4 Tg C02 Eq. of C2F6 (0.05 Gg) in
2004, as shown in Table 4-78 and Table 4-79. 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 38 percent,
while the average CF4 and C2F6 emission rates (per metric
ton of aluminum produced) have been reduced by 76 and
69 percent respectively.
U.S. primary aluminum production for 2004—totaling
2.5 million metric tons—declined nearly 7 percent from
2003 production. Due to high electric power costs in various
regions of the country, aluminum production has been
curtailed at several U.S. smelters, which resulted in 2004
production levels that were approximately 31 percent lower
Table 4-78: PFC Emissions from Aluminum Production
(Tg C02 Eq.)
Year
CF4
C,F,
'2*6
Total
1990
16.2
2.2
18.4
1998
1999
2000
2001
2002
2003
2004
8.1
8.0
8.1
3.5
4.6
3.3
2.4
1.0
1.0
0.9
0.5
0.7
0.5
0.4
9.1
9.0
9.0
4.0
5.3
3.8
2.8
Note: Totals may not sum due to independent rounding.
Table 4-79: PFC Emissions from Aluminum Production
(Gg)
Year
CF4
C,F,
'2r6
1990
2.5
0.2
1998
1999
2000
2001
2002
2003
2004
1.2
1.2
1.2
0.5
0.7
0.5
0.4
0.1
0.1
0.1
0.1
0.1
0.1
+
+ Does not exceed 0.5 Gg
than 2000 levels. The transportation industry remained the
largest domestic consumer of primary aluminum, accounting
for about 38 percent of U.S. consumption (USGS 2005).
Methodology
C02 emissions released during aluminum production
were estimated using the combined application of process-
specific emissions estimates modeling with individual
partner reported data. These estimates are achieved through
information gathered by EPA's Voluntary Aluminum
Industrial Partnership (VAIP) program.
Most of the C02 emissions released during aluminum
production occur during the electrolysis reaction of the
carbon anode, as described by the following reaction.
2A1203 + 3C ^ 4A1 + 3C02
For prebake smelter technologies, C02 is also emitted
during the anode baking process. These emissions can
account for approximately 10 percent of total process CO2
emissions from prebake smelters. The C02 emission factor
employed was estimated from the production of primary
aluminum metal and the carbon consumed by the process.
Emissions vary depending on the specific technology used
by each plant (e.g., prebake or S0derberg). CO2 process
emissions were estimated using methodology recommended
by the Aluminum Sector Greenhouse Gas Protocol (IAI,
2003.
The prebake process specific formula recommended
by IAI (2003) accounts for various parameters, including
net carbon consumption, and the sulfur, ash, and impurity
content of the baked anode. For anode baking emissions,
process formulas account for packing coke consumption,
the sulfur and ash content of the packing coke, as well as
the pitch content and weight of baked anodes produced. The
S0derberg process formula accounts for the weight of paste
consumed per metric ton of aluminum produced, and pitch
properties, including sulfur, hydrogen, and ash content.
In 2002, VAIP expanded its voluntary reporting to
include direct C02 data. As agreed, process data have been
reported for 1990, 2000, 2003, and 2004. 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 IAI (2003). Smelter specific CO2 process
data were provided by 18 of the 23 operating smelters in 1990
Industrial Processes 4-57
-------
and 2000, and 15 out of 16 operating smelters in 2003 and
2004. For years where C02 process data were not reported
by these companies, estimates were developed through linear
interpolation, and/or assuming industry default values.
In the absence of any smelter specific process data (i.e.,
1 out of 16 smelters in 2004, and 5 out of 23 between 1990
and 2003), C02 emission estimates were estimated using
the Revised 1996 IPCC Guidelines (IPCC/UNEP/OECD/
IEA 1997), which provide CO2 emission factors for each
technology type. During alumina reduction in a prebake
anode cell process, approximately 1.5 metric tons of CO2
are emitted for each metric ton of aluminum produced
(IPCC/UNEP/OECD/IEA 1997). Similarly, during alumina
reduction in a Soderberg cell process, approximately 1.8
metric tons of C02 are emitted per metric ton of aluminum
produced (IPCC/UNEP/OECD/IEA 1997).
Aluminum production data for 15 out of the 16 operating
smelters were reported under the VAIP in 2004. For the non-
reporting smelter, production was estimated based on the
difference between reporting smelters and national aluminum
production levels. Between 1990 and 2003, production data
were provided by 21 of the 23 operating U.S. smelters.
PFC emissions from aluminum production were
estimated using a per-unit production emission factor that
is expressed as a function of operating parameters (anode
effect frequency and duration), as follows:
PFC (CF4 or C2F6) kg/metric ton Al = S x Anode Effect
Minutes/Cell-Day
slope coefficients from the IPCC Good Practice Guidance
(IPCC 2000) were applied. The slope coefficients were
combined with smelter-specific anode effect data collected
by aluminum companies and reported under the VAIP, to
estimate emission factors over time. In 2004, smelter-
specific anode effect data was available for 15 of the 16
operating smelters. Where smelter-specific anode effect
data were not available (i.e., 1 out of 16 smelters in 2004,
2 out of 23 smelters between 1990 and 2003), industry
averages were used. For all smelters, emission factors
were multiplied by annual production to estimate annual
emissions at the smelter level. In 2004, smelter-specific
production data was available for 15 of the 16 operating
smelters; production at the one remaining smelter was
estimated based on national aluminum production and
capacity data (USAA 2005). Between 1990 and 2004,
production data has been provided by 21 of the 23 U.S.
smelters. Emissions were then aggregated across smelters
to estimate national emissions. The methodology used to
estimate emissions is consistent with the methodologies
recommended by the IPCC Good Practice Guidance
(IPCC 2000).
National primary aluminum production data for 1990
through 2001 (see Table 4-80) obtained from USGS, Mineral
Industry Surveys: Aluminum Annual Report (USGS 1995,
1998,2000,2001,2002). For 2002,2003, and 2004, national
aluminum production data were obtained from the United
States Aluminum Association's Primary Aluminum Statistics
(USAA 2004, 2005). The CO2 emission factors were taken
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)
Smelter-specific slope coefficients that are based
on field measurements yield the most accurate results.
To estimate emissions between 1990 and 2003, smelter-
specific coefficients were available and were used for 12
out of the 23 U.S. smelters. To estimate 2004 emissions,
smelter-specific coefficients were available and were used
for 5 out of the 16 operating U.S. smelters, representing
approximately 35 percent of 2004 U.S. production. For
the remaining 11 operating smelters, technology- specific
Table 4-80: Production of
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Primary Aluminum (Gg)
Gg
4,048
4,121
3|695
3,299
3,375
3^577
3,603
3,713
3,779
3,668
2,637
2,705
2J05
2,517
4-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
from the Revised 1996 IPCC Guidelines (IPCC/UNEP/
OECD/IEA 1997).
Uncertainty
The overall uncertainties associated with the 2004 C02,
CF4, and C2F6 emission estimates were calculated using
the IPCC Good Practice Guidance Tier 2 methodology.
Uncertainty associated with the parameters used to estimate
C02 emissions included that associated with production data,
with the share of U.S. aluminum production attributable to
each smelter type, and with the emission factors applied
to production data to calculate emissions. Uncertainty
surrounding production data was assumed to be characterized
as described below, while other variables were modeled
assuming triangular distributions. Emission factors were
determined through expert elicitation to be 50 percent
certain at a 95 percent confidence level, while the share of
production attributed to smelter types were determined to
be associated with a 25 percent uncertainty. A Monte Carlo
analysis was applied to estimate the overall uncertainty of
the C02 emissions estimate for the U.S. aluminum industry
as a whole and the results are provided below.
To estimate the uncertainty associated with emissions
of CF4 and C2F6, EPA estimated the uncertainties associated
with three variables for each smelter: (1) the quantity of
aluminum produced, (2) the anode effect minutes per cell day
(which may be reported directly or calculated as the product
of anode effect frequency and anode effect duration), and
(3) the smelter- or technology-specific slope coefficient. A
Monte Carlo analysis was then applied to estimate the overall
uncertainty of the emissions estimate for each smelter and
for the U.S. aluminum industry as a whole.
All three types of data are assumed to be characterized
by a normal distribution. The uncertainty of aluminum
production estimates was assumed to be 1 percent or 25
percent, depending on whether a smelter's production
was reported or estimated (Kantamaneni et al., 2001). The
uncertainty of the anode effect frequency was assumed to
be 2 percent for data that was reported; however, for the
one smelter that did not report data, the uncertainty was
estimated to be 78 percent (Kantamaneni et al., 2001).
Similarly, the uncertainty in anode effect duration was
assumed to be 5 percent for data that was reported, but
70 percent for data that was estimated (Kantamaneni et
al., 2001). The uncertainties for estimated anode effect
frequency and duration are based on the standard deviations
of reported technology-specific anode-effect frequency and
duration in the International Aluminum Institute's anode
effect survey (IAI 2000).
For the three smelters that participated in the 2003 EPA-
funded measurement study, CF4 and C2F6 slope coefficient
uncertainties were calculated to be 10 percent. For the
remaining smelters, given the limited uncertainty data on site-
specific slope coefficients (i.e., those developed using IPCC
Tier 3b methodology), the overall uncertainty associated with
the slope coefficients is conservatively assumed to be similar
to that given by the IPCC guidance for technology-specific
slope coefficients. Consequently, the uncertainty assigned
to the slope coefficients ranged between 10 percent and 35
percent, depending upon the gas and the smelter technology
type. In general, where precise quantitative information was
not available on the uncertainty of a parameter, a conservative
(upper-bound) value was used.
The results of this Tier 2 quantitative uncertainty analysis
are summarized in Table 4-81. Aluminum production-related
C02 emissions were estimated to be between 3.0 and 5.6 Tg
C02 Eq. at the 95 percent confidence level (or in 19 out of 20
Monte Carlo Stochastic Simulations). This indicates a range
of approximately 30 percent below to 30 percent above the
emission estimate of 4.3 Tg C02 Eq. Also, production-related
CF4 emissions were estimated to be between 2.2 and 2.7 Tg
C02 Eq. at the 95 percent confidence level. This indicates
a range of approximately 10 percent below to 12 percent
above the emission estimate of 2.4 Tg C02 Eq. Finally,
aluminum production-related C2F6 emissions were estimated
to be between 0.4 and 0.5 Tg C02 Eq. at the 95 percent
confidence level. This indicates a range of approximately
16 percent below to 18 percent above the emission estimate
of0.43TgC02Eq.
This inventory may slightly underestimate greenhouse
gas emissions from aluminum production and casting
because it does not account for the possible use of SF6 as a
cover gas or a fluxing and degassing agent in experimental
and specialized casting operations. The extent of such use
in the U.S. is not known. Historically, SF6 emissions from
aluminum activities have been omitted from estimates of
global SF6 emissions, with the explanation that any emissions
would be insignificant (Ko et al. 1993, Victor and MacDonald
1998). The concentration of SF6 in the mixtures is small and
a portion of the SF6 is decomposed in the process (MacNeal
Industrial Processes 4-59
-------
Table 4-81: Tier 2 Quantitative Uncertainty Estimates for C02 and PFC Emissions from Aluminum Production
(Tg C02 Eq. and Percent)
Source
Aluminum Production
Aluminum Production
Aluminum Production
Gas
C02
CF4
C2F6
2004 Emission
Estimate
(Tg C02 Eq.)
4.3
2.4
0.4
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound
3.0
2.2
0.4
Upper Bound
5.6
2.7
0.5
Lower Bound
-30%
-10%
-16%
Upper Bound
+ 30%
+ 12%
+ 18%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
etal. 1990, Gariepy and Dube 1992,Koetal. 1993,TenEyck
and Lukens 1996, Zurecki 1996).
Recalculations Discussion
Relative to the previous Inventory report, CO2 emission
estimates for the period 1990 through 2003 were updated
based on revisions to the estimation methodology. Previous
C02 emission estimates were based on methodology and
default emission factors defined by the Revised 1996IPCC
GuA/e7.mes(IPCC/UNEP/OED/IEA 1997). Current estimates
were developed using a combination of process specific
formulas (IAI 2003) and default emission factors (IPCC/
UNEP/OED/IEA 1997). The former approach was used
where smelter-specific process data was available. Based on
this revision, C02 emissions from aluminum production have
increased by approximately 10 percent for each year during
the 1990 to 2003 period relative to the previous report.
The smelter-specific emission factors used for estimating
PFC emissions, as well as aluminum production levels, were
revised to reflect recently-reported data concerning smelter
operating parameters. The combination of these changes
resulted in an average annual increase of approximately of
less than 0.05 Tg C02 Eq. (0.4 percent) in PFC emissions
from aluminum production for the period 1990 through 2003
relative to the previous report.
blown over molten magnesium metal to induce and stabilize
the formation of a protective crust. A small portion of the
SF6 reacts with the magnesium to form a thin molecular
film of mostly magnesium oxide and magnesium fluoride.
The amount of SF6 reacting in magnesium production and
processing is assumed to be negligible and thus all SF6
used is assumed to be emitted into the atmosphere. Sulfur
hexafluoride has been used in this application around
the world for the last twenty years. It has largely replaced
salt fluxes and SO2, which are more toxic and corrosive
than SF6.
The magnesium industry emitted 2.7 Tg C02 Eq. (0.1
Gg) of SF6 in 2004, representing a decrease of approximately
10 percent from 2003 emissions (see Table 4-82). The
reduction in emissions compared to 2003 occurred despite
a 3 percent increase in the amount of metal processed
in 2004. There are currently plans to expand primary
magnesium production in the United States to meet demand
for magnesium metal by U.S. casting companies, which
are in turn meeting demand for magnesium parts by the
automotive sector. Recent antidumping duties imposed on
Chinese imports by the U.S. International Trade Commission
Table 4-82: SF6 Emissions from Magnesium Production
and Processing (Tg C02 Eq. and Gg)
4.22. Magnesium Production and
Processing (IPCC Source Category
2C4)
The magnesium metal production and casting industry
uses sulfur hexafluoride (SF6) as a cover gas to prevent the
rapid oxidation of molten magnesium in the presence of air.
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
5.4
5.8
6.0
3.2
2.6
2.6
3.0
2.7
Gg
0.2
0.2
0.3
0.1
0.1
0.1
0.1
0.1
4-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
have shifted some U. S. demand to Canadian imports (USGS
2005). Anticipated increases in domestic primary production
capacity combined with Canadian imports should be able to
meet near-term U.S. demand (USGS 2005).
Methodology
Emission estimates for the magnesium industry
incorporate information provided by industry participants
in EPA's SF6 Emission Reduction Partnership for the
Magnesium Industry. The Partnership started in 1999 and,
currently, participating companies represent 100 percent of
U.S. primary production and 90 percent of the casting sector
(i.e., die, sand, permanent mold, wrought, and anode casting).
Emissions for 1999 through 2004 from primary production,
some secondary production (i.e., recycling), and die casting
were reported by Partnership participants. Emission factors
for 2002 to 2004 for sand casting activities were also acquired
through the Partnership. The 1999 through 2004 emissions
from the remaining secondary production and casting were
estimated by multiplying industry emission factors (kg
SF6 per metric ton of Mg produced or processed) by the
amount of metal produced or consumed in the six major
processes (other than primary production) that require SF6
melt protection: (1) secondary production, (2) die casting,
(3) sand casting, (4) permanent mold, (5) wrought products,
and (6) anodes. The emission factors are provided below in
Table 4-83. The emission factors for primary production
and sand casting are withheld to protect company-specific
production information. However, the emission factor for
primary production has not risen above the 1995 value of
1.1 kg SF6 per metric ton.
Die casting emissions for 1999 through 2004, which
accounted for 48 to 75 percent of all SF6 emissions from
U.S. casting and recycling processes during this period,
were estimated based on information supplied by industry
Partners. From 2000 to 2004, Partners accounted for all U.S.
die casting that was tracked by USGS. In 1999, Partners
did not account for all die casting tracked by USGS,
and, therefore, it was necessary to estimate the emissions
of die casters who were not Partners. Die casters who
were not Partners were assumed to be similar to partners
who cast small parts. Due to process requirements, these
casters consume larger quantities of SF6 per metric ton of
processed magnesium than casters that process large parts.
Consequently, emissions estimates from this group of die
casters were developed using an average emission factor of
5.2 kg SF6 per metric ton of magnesium. The emission factors
for the other industry sectors (i.e., secondary production,
permanent mold, wrought, and anode casting) were based
on discussions with industry representatives.
Data used to develop these emission estimates were
provided by the Magnesium Partnership participants and
the USGS. U.S. magnesium metal production (primary
and secondary) and consumption (casting) data from 1990
through 2004 were available from the USGS (USGS 2002,
2003, 2005a, 2005b). Emission factors from 1990 through
1998 were based on a number of sources. Emission factors
for primary production were available from U.S. primary
producers for 1994 and 1995, and an emission factor for die
casting of 4.1 kg per metric ton was available for the mid-
1990s from an international survey (Gjestland & Magers
1996).
To estimate emissions for 1990 through 1998, industry
emission factors were multiplied by the corresponding metal
production and consumption (casting) statistics from USGS.
The primary production emission factors were 1.2 kg per
metric ton for 1990 through 1993, and 1.1 kg per metric
ton for 1994 through 1996. For die casting, an emission
Table 4-83: SF6 Emission Factors (kg SF6 per metric ton of magnesium)
Year
1999
2000
2001
2002
2003
2004
Secondary
1
1
1
1
1
1
Die Casting
2.14=>
0.73
0.77
0.70
0.84
0.78
Permanent Mold
2
2
2
2
2
2
Wrought
1
1
1
1
1
1
Anodes
1
1
1
1
1
1
aWeighted average that includes an estimated emission factor of 5.2 kg SF6 per metric ton of magnesium for die casters that do not participate in the
Partnership.
Industrial Processes 4-61
-------
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 2004). Sand casting
emission factors for 2002 through 2004 were provided by
the magnesium partnership participants and 1990 through
2001 emission factors for this process were assumed to have
been the same as the 2002 emission factor. The emission
factors for the other processes (i.e., secondary production,
and permanent mold, wrought, and anode casting), about
which less is known, were assumed to remain constant at
levels defined in Table 4-83.
Uncertainty
To estimate the uncertainty of the estimated 2004 SF6
emissions from magnesium production and processing, EPA
estimated the uncertainties associated with three variables
(1) emissions reported by magnesium producers and
processors that participate in the SF6 Emission Reduction
Partnership, (2) emissions estimated for magnesium
producers and processors that participate in the Partnership
but did not report this year, and (3) emissions estimated
for magnesium producers and processors that do not
participate in the Partnership. An uncertainty of 5 percent
was assigned to the data reported by each participant in the
SF6 Emission Reduction 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 uncertainty associated with the extrapolated emission
factor was assumed to be 25 percent, while that associated
with the extrapolated production was assumed to be 30
percent. Between 1999 and 2004, non-reporting partners have
accounted for between 0 and 17 percent of total estimated
sector emissions. For those industry processes that are not
represented in EPA's partnership, such as permanent mold,
anode, and wrought casting, SF6 emissions were estimated
using production and consumption statistics reported by
USGS and estimated process-specific emission factors (see
Table 4-83). The uncertainties associated with the emission
factors and USGS-reported statistics were assumed to be
75 percent and 25 percent, respectively. In general, where
precise quantitative information was not available on the
uncertainty of a parameter, a conservative (upper-bound)
value was used.
Additional uncertainties exist in these estimates, such as
the basic assumption that SF6 neither reacts nor decomposes
during use. The melt surface reactions and high temperatures
associated with molten magnesium could potentially cause
some gas degradation. Recent measurement studies have
identified SF6 cover gas degradation at hot-chambered die
casting machines on the order of 10 percent (Bartos et al.
2003). As is the case for other sources of SF6 emissions,
total SF6 consumption data for magnesium production and
processing in the United States were not available. Sulfur
hexafluoride may also be used as a cover gas for the casting
of molten aluminum with high magnesium content; however,
to what extent this technique is used in the United States is
unknown.
The results of this Tier 2 quantitative uncertainty analysis
are summarized in Table 4-84. SF6 emissions associated with
magnesium production and processing were estimated to be
between 2.4 and 3.1 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 11 percent below
to 13 percent above the 2004 emissions estimate of 2.7 Tg
C02 Eq.
Table 4-84: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and Processing
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Magnesium Production SF6 2.7
2.4 3.1 -11% +13%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Box 4-1: Potential Emission Estimates of MFCs, PFCs, and SF6
Emissions of MFCs, PFCs and SF6 from industrial processes can be estimated in two ways, either as potential emissions or as actual
emissions. Emission estimates in this chapter are "actual emissions," which are defined by the Revised 1996IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) as estimates that take into account the time lag between consumption and
emissions. In contrast, "potential emissions" are defined to be equal to the amount of a chemical consumed in a country, minus the amount
of a chemical recovered for destruction or export in the year of consideration. Potential emissions will generally be greater for a given year
than actual emissions, since some amount of chemical consumed will be stored in products or equipment and will not be emitted to the
atmosphere until a later date, if ever. Although actual emissions are considered to be the more accurate estimation approach for a single
year, estimates of potential emissions are provided for informational purposes.
Separate estimates of potential emissions were not made for industrial processes that fall into the following categories:
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 4-85 presents potential emission estimates for MFCs and PFCs from the substitution of ozone depleting substances, MFCs, PFCs,
and SF6 from semiconductor manufacture, and SF6 from magnesium production and processing and electrical transmission and distribution.23
Potential emissions associated with the substitution for ozone depleting substances were calculated using the EPA's Vintaging Model.
Estimates of MFCs, PFCs, and SF6 consumed by semiconductor manufacture were developed by dividing chemical-by-chemical emissions
by the appropriate chemical-specific emission factors from the IPCC Good Practice Guidance (Tier 2c). Estimates of CF4 consumption were
adjusted to account for the conversion of other chemicals into CF4 during the semiconductor manufacturing process, again using the default
factors from the IPCC Good Practice Guidance. Potential SF6 emissions estimates for electrical transmission and distribution were developed
using U.S. utility purchases of SF6 for electrical equipment. From 1999 through 2004, estimates were obtained from reports submitted by
participants in EPA's SF6 Emission Reduction Program for Electric Power Systems. U.S. utility purchases of SF6 for electrical equipment from
1990 through 1998 were backcasted based on world sales of SF6 to utilities. Purchases of SF6 by utilities were added to SF6 purchases by
electrical equipment manufacturers to obtain total SF6 purchases by the electrical equipment sector.
Table 4-85:2004 Potential and Actual Emissions of
MFCs, PFCs, and SF6 from Selected Sources
(Tg C02 Eq.)
Source
Substitution of Ozone Depleting
Substances
Aluminum Production
HCFC-22 Production
Semiconductor Manufacture
Magnesium Production and Processing
Electrical Transmission and Distribution
Potential
192.0
-
-
7.3
2.7
23.3
Actual
103.3
2.8
15.6
4.7
2.7
13.8
- Not applicable.
DiSCUSSiOn in a slight increase in historical emissions of about 1 percent
The emission calculation methodology was revised to or less depending on the year. The emission estimate for 2002
reflect more accurate emission factor data for sand casting was also adJusted downward slightly from the previously
activities. Sand casting activity data now utilizes partner rePorted values-This revision reflects m uPdate to historical
reported emission factors from 1990 through 2003 resulting secondary production data supplied by USGS. The change
23 See Annex 5 for a discussion of sources of SF6 emissions excluded from the actual emissions estimates in this report.
Industrial Processes 4-63
-------
resulted in a decrease of 0.1 Tg CO2 Eq. (5 percent) in SF6
emissions from magnesium production and processing for
2002 relative to the previous report.
Planned Improvements
As more work assessing the degree of cover gas
degradation and associated byproducts is undertaken and
published, results could potentially be used to refine the
emission estimates, which currently assume (per IPCC
Good Practice Guidance, IPCC 2000) that all SF6 utilized
is emitted to the atmosphere. EPA-funded measurements
of SF6 in hot chamber die casting have indicated that
the latter assumption may be incorrect, with observed
SF6 degradation on the order of 10 percent (Bartos et al.
2003). More recent EPA-funded measurement studies have
confirmed this observation for cold chamber die casting
(EPA 2004). Another issue that will be addressed in future
inventories is the likely adoption of alternate cover gases
by U.S. magnesium producers and processors. These cover
gases, which include Am-Cover™ (containing HFC-134a)
and Novec™ 612, have lower GWPs than SF6, and tend to
quickly decompose during their exposure to the molten metal.
Additionally, as more companies join the partnership, in
particular those from sectors not currently represented, such
as permanent mold and anode casting, emission factors will
be refined to incorporate these additional data.
4.23. Industrial Sources of Indirect
Greenhouse Gases
In addition to the main greenhouse gases addressed
above, many industrial processes generate emissions of
indirect greenhouse gases. Total emissions of nitrogen
oxides (NOJ, carbon monoxide (CO), and non-CH4 volatile
organic compounds (NMVOCs) from non-energy industrial
processes from 1990 to 2004 are reported in Table 4-86.
Methodology
These emission estimates were obtained from preliminary
data (EPA 2005), and disaggregated based on EPA (2003),
which, in its final iteration, will be published on the National
Emission Inventory (NEI) Air Pollutant Emission Trends
web site. Emissions were calculated either for individual
categories or for many categories combined, using basic
activity data (e.g., the amount of raw material processed)
as an indicator of emissions. National activity data were
Table 4-86: NOX, CO, and NMVOC Emissions from Industrial Processes (Gg)
Gas/Source
NO,
Chemical & Allied Product
Manufacturing
Metals Processing
Storage and Transport
Other Industrial Processes
Miscellaneous*
CO
Chemical & Allied Product
Manufacturing
Metals Processing
Storage and Transport
Other Industrial Processes
Miscellaneous*
NMVOCs
Chemical & Allied Product
Manufacturing
Metals Processing
Storage and Transport
Other Industrial Processes
Miscellaneous*
1990
591
152
88
3
343
5
4,124
1,074
2,395
69
487
101
2,426
575
111
1,356
364
20
1998
637
117
81
15
424
1
3,163
981
1,544
65
535
38
2,047
357
71
1,204
402
13
1999
595
93
78
13
409
2
2,156
317
1,138
148
518
35
1,813
228
60
1,122
398
6
2000
626
95
81
14
434
2
2,217
327
1,175
154
538
23
1,773
230
61
1,067
412
3
2001
656
97
86
15
457
1
2,339
338
1,252
162
558
30
1,769
238
65
1,082
381
4
2002
630
95
76
14
442
3
2,286
306
1,174
195
576
35
1,723
194
62
1,093
369
5
2003
631
96
76
14
442
3
2,286
306
1,174
195
576
35
1,725
195
63
1,094
369
5
2004
632
96
76
14
443
3
2,286
306
1,174
195
576
35
1,727
195
63
1,096
370
5
* Miscellaneous includes the following categories: catastrophic/accidental release, other combustion, health services, cooling towers, and fugitive dust.
It does not include agricultural fires or slash/prescribed burning, which are accounted for under the Field Burning of Agricultural Residues source.
Note: Totals may not sum due to independent rounding.
4-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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collected for individual categories from various agencies.
Depending on the category, these basic activity data may
include data on production, fuel deliveries, raw material
processed, etc.
Activity data were used in conjunction with emission
factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the
EPA's Compilation of Air Pollutant Emission Factors, AP-42
(EPA 1997). The EPA currently derives the overall emission
control efficiency of a source category from a variety of
information sources, including published reports, the 1985
National Acid Precipitation and Assessment Program
emissions inventory, and other EPA databases.
Uncertainty
Uncertainties in these estimates are partly due to the
accuracy of the emission factors used and accurate estimates
of activity data. A quantitative uncertainty analysis was not
performed.
Industrial Processes 4-65
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5. Solvent and Other Product Use
Greenhouse gas emissions are produced as a by-product of various solvent and other product uses. In the United States,
emissions from nitrous oxide (N20) product usage, the only source of greenhouse gas emissions from this sector, accounted
for less than 0.1 percent of total U.S. anthropogenic greenhouse gas emissions on a carbon equivalent basis in 2004 (see
Table 5-1). Indirect greenhouse gas emissions also result from solvent and other product use, and are presented in Table
5-2 in teragrams of C02 equivalent (Tg C02 Eq.) and gigagrams (Gg).
5.1. Nitrous Oxide Product Usage (IPCC Source Category 3D)
N2O is a clear, colorless, oxidizing liquefied gas, with a slightly sweet odor. N20 is produced by thermally decomposing
ammonium nitrate (NH4N03), a chemical commonly used in fertilizers and explosives. The decomposition creates steam
(H20) and N2O through a low-pressure, low-temperature (500°F) reaction. Once the steam is removed through condensation,
the remaining N2O is purified, compressed, dried, and liquefied for storage and distribution. Two companies operate a total
of five N20 production facilities in the United States (CGA 2002).
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 N20 is as a propellant in pressure and
aerosol products, the largest application being pressure-packaged whipped cream. Small quantities of N20 also are used
in the following applications:
Table 5-1: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq. and Gg)
Gas/Source 1990 1998 1999 2000 2001 2002 2003 2004
N20 Product Usage
TgC02Eq. 4.3 4.8 4.8 4.8 4.8 4.8 4.8 4.8
Gg 14 15 15 15 15 15 15 15
Table 5-2: Indirect Greenhouse Gas Emissions from Solvent and Other Product Use (Gg)
Gas/Source
NMVOCs
CO
NOX
1990
5,217
4
1
1998
4,671
1
3
1999
4,569
46
3
2000
4,384
46
3
2001
4,547
45
3
2002
4,256
46
6
2003
4,262
46
6
2004
4,267
46
6
Solvent and Other Product Use 5-1
-------
Table 5-3: N20 Emissions from N20 Product Usage (Tg
C02 Eq. and Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
4.3
4.8
4.8
4.8
4.8
4.8
4.8
4.8
Gg
14
15
15
15
15
15
15
15
• 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 2004 was approximately 17 Gg.
N2O emissions were 4.8 Tg CO2 Eq. (15 Gg) in 2004 (see
Table 5-3). Production of N20 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 N20. The use of N20 as a propellant
for whipped cream has also stabilized due to the increased
popularity of cream products packaged in reusable plastic
tubs (Heydorn 1997).
Methodology
Emissions from N2O product usage were calculated by
first multiplying the total amount of N20 produced in the
United States by the share of the total quantity of N20 that
is used by each sector. This value was then multiplied by the
associated emissions rate for each sector. After the emissions
were calculated for each sector, they were added together
to obtain a total estimate of N20 product usage emissions.
Emissions were determined using the following equation:
N20 Product Usage Emissions =
2i [Total U.S. Production of N20] x
[Share of Total Quantity of N20 Usage by Sector i] x
[Emissions Rate for Sector i],
where,
i = sector.
The share of total quantity of N20 usage by subcategory
represents the share of national N20 produced that is used
by the specific subcategory (i.e., anesthesia, food processing,
etc.). In 2004, the medical/dental industry used an estimated
86 percent of total N2O produced, followed by food
processing propellants at 6.5 percent. All other categories
combined used the remainder of the N20 produced. This
subcategory breakdown has changed only slightly over the
past decade. For instance, the small share of N20 usage in
the production of sodium azide has declined significantly
during the decade of the 1990s. Due to the lack of information
on the specific time period of the phase-out in this market
subcategory, most of the N20 usage for sodium azide
production is assumed to have ceased after 1996, with the
majority of its small share of the market assigned to the
larger medical/dental consumption subcategory. The N20
was allocated across these subcategories, a usage emissions
rate was then applied for each sector to estimate the amount
of N20 emitted.
Only the medical/dental and food propellant subcategories
were estimated to release emissions into the atmosphere,
and therefore these subcategories were the only usage
subcategories with emission rates. For the medical/dental
subcategory, due to the poor solubility of N20 in blood and
other tissues, approximately 97.5 percent of the N20 is not
metabolized during anesthesia and quickly leaves the body in
exhaled breath. Therefore, an emission factor of 97.5 percent
was used for this subcategory (Tupman 2002). For N20 used
as a propellant in pressurized and aerosol food products, none
of the N20 is reacted during the process and all of the N20
is emitted to the atmosphere, resulting in an emissions factor
of 100 percent for this subcategory (Heydorn 1997). For the
remaining subcategories, all of the N20 is consumed/reacted
during the process, and therefore the emissions rate was
considered to be zero percent (Tupman 2002).
5-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
The 1990 through 1992 and 1996 N20 production data
were obtained from SRI Consul ting's Nitrous Oxide, North
America report (Heydorn 1997). These data were provided as
a range. For example, in 1996, Heydorn (1997) estimates N20
production to range between 13.6 and 18.1 thousand metric
tons. Tupman (2003) provided a narrower range for 1996
that falls within the production bounds described by Heydorn
(1997). These data are considered more industry specific
and current. The midpoint of the narrower production range
(15.9 to 18.1 thousand metric tons) was used to estimate
N20 emissions for years 1993 through 2002 (Tupman 2003).
Production data for 2004 was assumed to equal 2002 data.
N20 production data for 1990 through 2004 are presented
in Table 5-4.
The 1996 share of the total quantity of N20 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 N20 used by
each subcategory was kept the same as the 1996 number
provided by SRI Consulting. The 1997 through 2002 share
of total quantity of N2O usage by sector was obtained from
communication with a N20 industry expert (Tupman 2002).
Due to unavailable data, the share of total quantity of N20
usage data for 2004 was assumed to equal that of 2002. The
emissions rate for the food processing propellant industry
was obtained from SRI Consul ting's Nitrous Oxide, North
America report (Heydorn 1997), and confirmed by a N20
industry expert (Tupman 2002). The emissions rate for all
other subcategories was obtained from communication with
a N20 industry expert (Tupman 2002). The emissions rate
Table 5-4: N20 Production (Gg)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Gg
16
15
15
17
17
17
17
17
17
17
17
17
17
17
17
for the medical/dental subcategory was substantiated by the
Encyclopedia of Chemical Technology (Othmer 1990).
Uncertainty
The overall uncertainty associated with the 2004 N20
emissions estimate from N2O product usage was calculated
using the Intergovernmental Panel on Climate Change
(IPCC) Good Practice Guidance Tier 2 methodology.
Uncertainty associated with the parameters used to estimate
N20 emissions included that of production data, total market
share of each end use, and the emission factors applied to
each end use, respectively. The activity data inputs and their
associated uncertainties and distributions are summarized
in Table 5-5.
Table 5-5: Sources of Uncertainty in N20 Emissions from N20 Product Usage
Variable
Production (Gg)
Market Share Medicine/Dentistry Anesthesia
(analgesic property) (%)
Market Share Food Processing Propellant (%)
Emission Rate Medicine/Dentistry Anesthesia
(analgesic property) (%)
Value
17
0.86
0.06
0.98
Distribution Type
Uniform
Uniform
Uniform
Uniform
Uncertainty Range3
Lower Bound Upper Bound
-7% +7%
-2% +2%
-23% +23%
-3% +3%
Reference
Expert Judgment
Expert Judgment
Expert Judgment
Expert Judgment
a Parameters presented represent upper and lower bounds as a percentage of the mean, based on a 95 percent confidence interval.
Solvent and Other Product Use 5-3
-------
Table 5-6: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From N20 Product Usage
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
N20 Product Usage N20 4.8
4.4 5.1 -7% +7%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
The results of this Tier 2 quantitative uncertainty
analysis are summarized in Table 5-6. N20 emissions from
N2O product usage were estimated to be between 4.4 and 5.1
Tg C02 Eq. at the 95 percent confidence level (or in 19 out
of 20 Monte Carlo Stochastic Simulations). This indicates a
range of approximately 7 percent below to 7 percent above
the 2004 emissions estimate of 4.8 Tg CO2 Eq.
Planned Improvements
Planned improvements include a continued evaluation
of alternative production statistics for cross verification and
a reassessment of subcategory usage to accurately represent
the latest trends in the product usage.
5.2. Indirect Greenhouse Gas
Emissions from Solvent Use
The use of solvents and other chemical products can
result in emissions of various ozone precursors (i.e., indirect
greenhouse gases). Non-methane volatile organic compounds
(NMVOCs), commonly referred to as "hydrocarbons," are
the primary gases emitted from most processes employing
organic or petroleum based solvents. As some of industrial
applications also employ thermal incineration as a control
technology, combustion by-products, such as carbon
monoxide (CO) and nitrogen oxides (NOjj), are also reported
with this source category. Surface coatings accounted for
approximately 41 percent of NMVOC emissions from
solvent use in 2004, while "non-industrial"2 uses accounted
for about 38 percent and degreasing applications for 7
percent. Overall, solvent use accounted for approximately
25 percent of total U.S. emissions of NMVOCs in 2004;
NMVOC emissions from solvent use have decreased 18
percent since 1990.
Although NMVOCs are not considered direct greenhouse
gases, their role as precursors to the formation of ozone—
which is a greenhouse gas—results in their inclusion in a
greenhouse gas inventory. Emissions from solvent use have
been reported separately by the United States to be consistent
with the inventory reporting guidelines recommended by the
IPCC. These guidelines identify solvent use as one of the
major source categories for which countries should report
emissions. 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 2004 are reported in Table 5-7.
Methodology
Emissions were calculated by aggregating solvent use
data based on information relating to solvent uses from
different applications such as degreasing, graphic arts, etc.
1 Solvent usage in the United States also results in the emission of small amounts of hydrofluorocarbons (HFCs) and hydrofluoroethers (HFEs), which
are included under Substitution of Ozone Depleting Substances in the Industrial Processes chapter.
2 "Non-industrial" uses include cutback asphalt, pesticide application, adhesives, consumer solvents, and other miscellaneous applications.
5-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 5-7: Emissions of NOX, CO, and NMVOC from Solvent Use (Gg)
Activity
NO,
Degreasing
Graphic Arts
Dry Cleaning
Surface Coating
Other Industrial Processes3
Non-Industrial Processes"
Other
CO
Degreasing
Graphic Arts
Dry Cleaning
Surface Coating
Other Industrial Processes3
Non-Industrial Processes"
Other
NMVOCs
Degreasing
Graphic Arts
Dry Cleaning
Surface Coating
Other Industrial Processes3
Non-Industrial Processes"
Other
1990
1
+
+
+
1
+
+
NA
4
+
+
+
+
4
+
NA
5,217
675
249
195
2,289
85
1,724
+
1998
3
+
1
+
2
+
+
+
1
+
+
+
1
+
+
+
4,671
337
272
151
1,989
101
1,818
3
1999
3
+
+
+
3
+
+
+
46
+
+
+
46
+
+
+
4,569
363
224
267
1,865
95
1,714
40
2000
3
+
+
+
3
+
+
+
46
+
+
+
46
+
+
+
4,384
316
222
265
1,767
98
1,676
40
2001
3
+
+
+
3
+
+
+
45
+
+
+
45
+
+
+
4,547
331
229
272
1,863
103
1,707
42
2002
6
+
+
+
6
+
+
+
46
+
+
+
46
+
+
+
4,256
310
214
254
1,744
97
1,598
40
2003
6
+
+
+
6
+
+
+
46
+
+
+
46
+
+
+
4,262
310
214
255
1,746
97
1,600
40
2004
6
+
+
+
6
+
+
+
46
+
+
+
46
+
+
+
4,267
311
214
255
1,748
97
1,602
40
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.
Emission factors for each consumption category were then
applied to the data to estimate emissions. For example,
emissions from surface coatings were mostly due to solvent
evaporation as the coatings solidify. By applying the
appropriate solvent-specific emission factors to the amount of
solvents used for surface coatings, an estimate of emissions
was obtained. Emissions of CO and NOX result primarily
from thermal and catalytic incineration of solvent-laden
gas streams from painting booths, printing operations, and
oven exhaust.
These emission estimates were obtained from preliminary
data (EPA 2005), and disaggregated based on EPA (2003),
which, in its final iteration, will be published on the National
Emission Inventory (NEI) Air Pollutant Emission Trends
web site. Emissions were calculated either for individual
categories or for many categories combined, using basic
activity data (e.g., the amount of solvent purchased) as an
indicator of emissions. National activity data were collected
for individual applications from various agencies.
Activity data were used in conjunction with emission
factors, which together relate the quantity of emissions to the
activity. Emission factors are generally available from the
EPA's Compilation of Air Pollutant Emission Factors, AP-42
(EPA 1997). The EPA currently derives the overall emission
control efficiency of a source category from a variety of
information sources, including published reports, the 1985
National Acid Precipitation and Assessment Program
emissions inventory, and other EPA databases.
Uncertainty
Uncertainties in these estimates are partly due to the
accuracy of the emission factors used and the reliability of
correlations between activity data and actual emissions.
Solvent and Other Product Use 5-5
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6. Agriculture
Agricultural activities contribute directly to emissions of greenhouse gases through a variety of processes. This
chapter provides an assessment of non-carbon dioxide emissions from the following source categories: enteric
fermentation in domestic livestock, livestock manure management, rice cultivation, agricultural soil management,
and field burning of agricultural residues (see Figure 6-1). Carbon dioxide (CO2) emissions and removals from agriculture-
related land-use activities, such as conversion of grassland to cultivated land, are presented in the Land Use, Land-Use
Change, and Forestry sector. CO2 emissions from on-farm energy use are accounted for in the Energy chapter.
In 2004, the agricultural sector was responsible for emissions of 440.1 teragrams of CO2 equivalent (Tg CO2 Eq.), or
6 percent of total U.S. greenhouse gas emissions. Methane (CH4) and nitrous oxide (N2O) were the primary greenhouse
gases emitted by agricultural activities. CH4 emissions from enteric fermentation and manure management represent about
20 percent and 7 percent of total CH4 emissions from anthropogenic activities, respectively. Of all domestic animal types,
beef and dairy cattle were by far the largest emitters of CH4. Rice cultivation and field burning of agricultural residues were
minor sources of CH4. Agricultural soil management activities such as fertilizer application and other cropping practices were
the largest source of U.S. N2O emissions, accounting for 68 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 2004, CH4 emissions
from agricultural activities increased by 2 percent while N2O emissions decreased by 1 percent. In addition to CH4 and N2O,
field burning of agricultural residues was also a minor source of the indirect greenhouse gases carbon monoxide (CO) and
nitrogen oxides (NOX).
Figure 6-1
6.1. Enteric Fermentation (IPCC
Source Category 4A)
CH4 is produced as part of normal digestive processes in
animals. During digestion, microbes resident in an animal's
digestive system ferment food consumed by the animal.
This microbial fermentation process, referred to as enteric
fermentation, produces CH4 as a by-product, which can be
exhaled or eructated by the animal. The amount of CH4
produced and excreted by an individual animal depends
primarily upon the animal's digestive system, and the amount
and type of feed it consumes.
Among domesticated animal types, ruminant animals
(e.g., cattle, buffalo, sheep, goats, and camels) are the major
2004 Agriculture Chapter Greenhouse Gas
Emission Sources
Agricultural Soil Management
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
Agriculture as a
Portion of all Emissions
7.0%
0 50 100 150 200 250 300
TgC02Eq.
Agriculture 6-1
-------
Table 6-1: Emissions from Agriculture (Tg C02 Eq.)
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
N20
Agricultural Soil
Management
Manure Management
Field Burning of
Agricultural Residues
Total
Note: Totals may not sum due to
Table 6-2: Emissions from
Gas/Source
CH4
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
N20
Agricultural Soil
Management
Manure Management
Field Burning of
Agricultural Residues
CO
NO,
1990
156.8
117.9
31.2
7.1
0.7
282.7
266.1
16.3
0.4
439.6
1998
164.2
116.7
38.8
7.9
0.8
319.0
301.1
17.4
0.5
483.2
1999
164.0
116.8
38.1
8.3
0.8
299.1
281.2
17.4
0.4
463.1
2000
162.0
115.6
38.0
7.5
0.8
296.5
278.2
17.8
0.5
458.4
2001
161.9
114.6
38.9
7.6
0.8
301.5
282.9
18.1
0.5
463.4
2002
161.5
114.7
39.3
6.8
0.7
296.2
277.8
18.0
0.4
457.8
2003
161.9
115.1
39.2
6.9
0.8
277.1
259.2
17.5
0.4
439.1
2004
160.4
112.6
39.4
7.6
0.9
279.7
261.5
17.7
0.5
440.1
independent rounding.
Agriculture (Gg)
1990
7,468
5,612
1,484
339
33
913
858
52
1
689
28
1998
7,821
5,559
1,848
376
38
1,029
971
56
1
789
35
1999
7,810
5,563
1,816
395
37
965
907
56
1
767
34
2000
7,713
5,507
1,811
357
38
956
897
58
1
790
35
2001
7,710
5,459
1,850
364
37
972
913
58
1
770
35
2002
7,693
5,463
1,871
325
34
956
896
58
1
706
33
2003
7,712
5,481
1,865
328
38
894
836
57
1
796
34
2004
7,640
5,362
1,875
360
42
902
844
57
2
877
39
Note: Totals may not sum due to independent rounding.
emitters of CH4 because of their unique digestive system.
Ruminants possess a rumen, or large "fore-stomach," in
which microbial fermentation breaks down the feed they
consume into products that can be absorbed and metabolized.
The microbial fermentation that occurs in the rumen enables
them to digest coarse plant material that non-ruminant
animals cannot. Ruminant animals, consequently, have the
highest CH4 emissions among all animal types.
Non-ruminant domesticated animals (e.g., swine,horses,
and mules) also produce CH4 emissions through enteric
fermentation, although this microbial fermentation occurs in
the large intestine. These non-ruminants emit significantly
less CH4 on a per-animal basis than ruminants because the
capacity of the large intestine to produce CH4 is lower.
In addition to the type of digestive system, an animal's
feed quality and feed intake also affects CH4 emissions. In
general, lower feed quality or higher feed intake lead to higher
CH4 emissions. Feed intake is positively related to animal
size, growth rate, and production (e.g., milk production, wool
growth, pregnancy, or work). Therefore, feed intake varies
among animal types as well as among different management
practices for individual animal types.
CH4 emission estimates from enteric fermentation are
provided in Table 6-3 and Table 6-4. Total livestock CH4
emissions in 2004 were 112.6 Tg CO2 Eq. (5,362 gigagrams
[Gg]), decreasing slightly since 2003 due to minor decreases
in some animal populations and dairy cow milk production
in some regions. Beef cattle remain the largest contributor
6-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg C02 Eq.)
Livestock Type
Beef Cattle
Dairy Cattle
Horses
Sheep
Swine
Goats
Total
1990
83.2
28.9
I
1.7
0.3
117.9
1998
85.0
26.3
2.0
1.3
2.0
0.2
116.7
1999
84.9
26.6
2.0
1.2
1.9
0.2
116.8
2000
83.4
27.0
2.0
1.2
1.9
0.3
115.6
2001
82.5
26.9
2.0
1.2
1.9
0.3
114.6
2002
82.4
27.1
2.0
1.1
1.9
0.3
114.7
2003
82.6
27.3
2.0
1.1
1.9
0.3
115.1
2004
80.4
27.0
2.0
1.0
1.9
0.3
112.6
Note: Totals may not sum due to independent rounding.
Table 6-4: CH4
Livestock Type
Beef Cattle
Dairy Cattle
Horses
Sheep
Swine
Goats
Total
Emissions from Enteric Fermentation (Gg)
1990 |
3,961
1,375
I
13
5,612
1998
4,047
1,251
94
63
93
12
5,559
1999
4,045
1,265
93
58
90
12
5,563
2000
3,973
1,283
94
56
88
12
5,507
2001
3,928
1,280
95
55
88
12
5,459
2002
3,923
1,288
95
53
90
13
5,463
2003
3,934
1,299
95
51
90
13
5,481
2004
3,830
1,285
95
49
91
13
5,362
Note: Totals may not sum due to independent rounding.
of CH4 emissions from enteric fermentation, accounting
for 71 percent in 2004. Emissions from dairy cattle in 2004
accounted for 24 percent, and the remaining emissions were
from horses, sheep, swine, and goats.
From 1990 to 2004, emissions from enteric fermentation
have decreased by 5 percent. Generally, emissions have been
decreasing since 1995, mainly due to decreasing populations
of both beef and dairy cattle and improved feed quality for
feedlot cattle. During this timeframe, populations of sheep
have decreased by an average annual rate of about 4 percent
per year while horse populations have remained relatively
constant and the population of goats has increased by an
average of 2 percent per year.
Methodology
Livestock emission estimates fall into two categories:
cattle and other domesticated animals. Cattle, due to their large
population, large size, and particular digestive characteristics,
account for the majority of CH4 emissions from livestock
in the United States. A more detailed methodology (i.e.,
Intergovernmental Panel on Climate Change [IPCC] Tier 2)
was therefore applied to estimating emissions for all cattle
except for bulls. Emission estimates for other domesticated
animals (horses, sheep, swine, goats, and bulls) were handled
using a less detailed approach (i.e., IPCC Tier 1).
While the large diversity of animal management
practices cannot be precisely characterized and evaluated,
significant scientific literature exists that describes the
quantity of CH4 produced by individual ruminant animals,
particularly cattle. A detailed model that incorporates this
information and other analyses of livestock population,
feeding practices and production characteristics was used
to estimate emissions from cattle populations.
National cattle population statistics were disaggregated
into the following cattle sub-populations:
• Dairy Cattle
• Calves
• Heifer Replacements
• Cows
• Beef Cattle
• Calves
• Heifer Replacements
• Heifer and Steer Stackers
• Animals in Feedlots (Heifers and Steers)
• Cows
• Bulls
Calf birth rates, end of year population statistics,
detailed feedlot placement information, and slaughter
Agriculture 6-3
-------
weight data were used to model cohorts of individual
animal types and their specific emissions profiles. The
key variables tracked for each of the cattle population
categories are described in Annex 3.9. These variables
include performance factors such as pregnancy and lactation
as well as average weights and weight gain. Annual cattle
population data were obtained from the U.S. Department
of Agriculture's National Agricultural Statistics Service
(1995a,b; 1999a,c,d,f; 2000a,c,d,e; 2001a,c,d,f; 2002a,c,d,f;
2003a,c,d,f; 2004a,c,d,f, 2005a-d).
Diet characteristics were estimated by region for
U.S. dairy, beef, and feedlot cattle. These estimates were
used to calculate Digestible Energy (DE) values and CH4
conversion rates (Ym) for each population category. The
IPCC recommends Ym values of 3.5 to 4.5 percent for
feedlot cattle and 5.5 to 6.5 percent for other well-fed
cattle consuming temperate-climate feed types. Given the
availability of detailed diet information for different regions
and animal types in the United States, DE and Ym values
unique to the United States were developed, rather than using
the recommended IPCC values. The diet characterizations
and estimation of DE and Ym values were based on
information from state agricultural extension specialists, a
review of published forage quality studies, expert opinion,
and modeling of animal physiology. The diet characteristics
for dairy cattle were from Donovan (1999), while beef cattle
were derived from NRC (2000). DE and Ym for dairy cows
were calculated from diet characteristics using a model
simulating ruminant digestion in growing and/or lactating
cattle (Donovan and Baldwin 1999). For feedlot animals, DE
and Ym values recommended by Johnson (1999) were used.
Values from EPA (1993) were used for dairy replacement
heifers. For grazing beef cattle, DE values were based on
diet information in NRC (2000) and Ym values were based on
Johnson (2002). Weight data were estimated from Feedstuffs
(1998), Western Dairyman (1998), and expert opinion. See
Annex 3.9 for more details on the method used to characterize
cattle diets in the United States.
To estimate CH4 emissions from cattle, the population
was divided into region, age, sub-type (e.g., dairy cows and
replacements, beef cows and replacements, heifer and steer
stackers, and heifer and steer in feedlots), and production
(e.g., pregnant, lactating) groupings to more fully capture
differences in CH4 emissions from these animal types.
Cattle diet characteristics were used to develop regional
emission factors for each sub-category. Tier 2 equations
from IPCC (2000) were used to produce CH4 emission
factors for the following cattle types: dairy cows, beef cows,
dairy replacements, beef replacements, steer stockers, heifer
stackers, steer feedlot animals, and heifer feedlot animals.
To estimate emissions from cattle, population data were
multiplied by the emission factor for each cattle type. More
details are provided in Annex 3.9.
Emission estimates for other animal types were based on
average emission factors representative of entire populations
of each animal type. CH4 emissions from these animals
accounted for a minor portion of total CH4 emissions from
livestock in the United States from 1990 through 2004.
Also, the variability in emission factors for each of these
other animal types (e.g., variability by age, production
system, and feeding practice within each animal type) is
less than that for cattle. Annual livestock population data
for these other livestock types, except horses and goats, as
well as feedlot placement information were obtained for all
years from the U.S. Department of Agriculture's National
Agricultural Statistics Service (USDA 1994a-b, 1995a,c,
1998a-b, 1999a,b,e, 2000b, 2004a,b,e,g,h, 2005a,d-h). Horse
population data were obtained from the FAOSTAT database
(FAO 2005), because USDA does not estimate U.S. horse
populations annually. Goat population data for 1992, 1997,
and 2002 were obtained from the Census of Agriculture
(USDA 2005i); these data were interpolated and extrapolated
to derive estimates for the other years. Information regarding
poultry turnover (i.e., slaughter) rate was obtained from
state Natural Resource Conservation Service personnel
(Lange 2000). Additional population data for different farm
size categories for dairy and swine were obtained from
the 1992 and 1997 Census of Agriculture (USDA 2005i).
CH4 emissions from sheep, goats, swine, and horses were
estimated by using emission factors utilized in Crutzen et
al. (1986, cited in IPCC/UNEP/OECD/IEA 1997). These
emission factors are representative of typical animal sizes,
feed intakes, and feed characteristics in developed countries.
The methodology is the same as that recommended by IPCC
(IPCC/UNEP/OECD/IEA 1997, IPCC 2000).
See Annex 3.9 for more detailed information on the
methodology and data used to calculate CH4 emissions from
enteric fermentation.
6-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Uncertainty
Quantitative uncertainty of this source category
was performed through the IPCC-recommended Tier 2
uncertainty estimation methodology, Monte Carlo Stochastic
Simulation technique. These estimates were developed
for the 2001 inventory estimates. No significant changes
occurred in the method of data collection, data estimation
methodology, or other factors that influence the uncertainty
ranges around the 2004 activity data and emission factor
input variables. Consequently, these uncertainty estimates
were directly applied to the 2004 emission estimates.
A total of 185 primary input variables (178 for cattle and
8 for non-cattle) were identified as key input variables for
uncertainty analysis. The normal distribution was assumed
for almost all activity- and emission factor-related input
variables. Triangular distributions were assigned to three
input variables (specifically, cow-birth ratios for the three
most recent years included in the 2001 model run). For
some key input variables, the uncertainty ranges around
their estimates (used for inventory estimation) were collected
from published documents and other public sources. In
addition, both endogenous and exogenous correlations
between selected primary input variables were modeled. The
exogenous correlation coefficients between the probability
distributions of selected activity-related variables were
developed as educated estimates.
The uncertainty ranges associated with the activity-
related input variables were plus or minus 10 percent or
lower. However, for many emission factor-related input
variables, the lower- and/or the upper-bound uncertainty
estimates were over 20 percent. The results of the quantitative
uncertainty analysis (Table 6-5) indicate that, on average,
in 19 out of 20 times (i.e., with 95 percent confidence), the
total greenhouse gas emissions estimate from this source
is within the range of approximately 100.2 to 132.9 Tg
CO2 Eq. (or that the actual CH4 emissions are likely to fall
within the range of approximately 11 percent below and 18
percent above the emission estimate of 112.6 Tg CO2 Eq.).
Among the individual sub-source categories, beef cattle
account for the largest amount of CH4 emissions as well as
the largest degree of uncertainty in the inventory emission
estimates. Consequently, the cattle sub-source categories
together contribute to the largest degree of uncertainty in
the inventory estimates of CH4 emissions from livestock
enteric fermentation. Among non-cattle, horses account for
the largest degree of uncertainty in the inventory emission
estimates.
QA/QC and Verification
In order to ensure the quality of the emission estimates
from enteric fermentation, the IPCC Tier 1 and Tier 2
Quality Assurance/Quality Control (QA/QC) procedures
were implemented consistent with the U.S. QA/QC plan.
Tier 2 QA procedures included independent peer review
of emission estimates. Particular emphasis was placed this
year on cattle population and growth data, and on evaluating
the effects of data updates as described in the recalculations
discussion below.
Recalculations Discussion
While there were no changes in the methodologies used
for estimating CH4 emissions from enteric fermentation,
emissions were revised slightly due to changes in data.
USDA published revised population estimates which affected
historical emissions estimated for swine, sheep, goats, and
poultry. Recent historical emission estimates also changed for
certain beef and dairy populations as a result USDA inputs
and the calving rate described below.
Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation (Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate1"1
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Enteric Fermentation CH4 112.6
100.2 132.9 -11% +18%
a Range of emissions estimates predicted by Monte Carlo Stochastic Simulation for a 95% confidence interval.
b Note that the relative uncertainty range was estimated with respect to the 2001 emission estimates and applied to 2004 estimates.
Agriculture 6-5
-------
The dairy cow calving rate represents the percentage of
dairy cows that produced live calves in a specific year (the
remainder either birthed dead calves or had reproductive
problems). This value is used to determine the percentage
of dairy cows that are pregnant during the specified month
as well as the portion of total calf births that are from dairy
cows. The previous model versions assumed a constant
calving rate of 93.4 percent (USDA:APHIS:VS 1996).
Research revealed more recent statistics (USDA:APHIS:
VS 2002), that revised this calving rate to 88.8 percent for
cows and heifers that produced live calves during 2001.
Modeling assumptions were thus revised to use the historic
(93.4 percent) calving rate for all years through 2000 and the
updated rate (88.8 percent) for subsequent periods.
Changes to previously reported emissions are summarized
by the following: year 2001 total (dairy and beef) cattle
CH4 emissions changed by just 0.1 percent. For 2002, beef
cattle CH4 emissions increased 4 Gg (0.1 percent) while
dairy cattle emissions decreased by 2 Gg (0.1 percent). An
upward revision in historical goat populations from 1995
through 2003 resulted in an increase in CH4 emissions for
each of those years. In 2003, this change affected emissions
by less than 3 Gg (0.05 percent of total enteric fermentation
emissions from all animals). Recent historical emission
estimates for sheep and swine both changed (each by less
than one half of one percent of respective 2003 emissions)
as a result of the USDA revisions described above.
Planned Improvements
Continued research and regular updates are necessary
to maintain a current model of cattle diet characterization,
feedlot placement data, rates of weight gain and calving,
among other data inputs. While EPA has no plans for
methodological changes in the modeling framework, the
opportunity exists to continue to refine the model's results
through identifying and improving individual data inputs.
Research is currently underway to identify updates of this
nature.
6.2. Manure Management (IPCC
Source Category 4B)
The management of livestock manure can produce
anthropogenic CH4 andN2O emissions. CH4 is produced by
the anaerobic decomposition of manure. N2O is produced
as part of the nitrogen cycle through the nitrification and
denitrification of the organic nitrogen in livestock manure
and urine.
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. A number of other
factors related to how the manure is handled also affect the
amount of CH4 produced. 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 example, CH4
production generally increases with rising temperature
and residency time. Also, for non-liquid-based manure
systems, moist conditions (which are a function of rainfall
and humidity) can promote CH4 production. Although the
majority of manure is handled as a solid, producing little
CH4, the general trend in manure management, particularly
for large dairy and swine producers, is one of increasing use
of liquid systems. In addition, use of daily spread systems at
smaller dairies is decreasing, due to new regulations limiting
the application of manure nutrients, which has resulted in
an increase of manure managed and stored on site at these
smaller dairies.
The composition of the manure also affects the amount
of CH4 produced. Manure composition varies by animal
type, including the animal's digestive system and diet. In
general, the greater the energy content of the feed, the greater
the potential for CH4 emissions. For example, feedlot cattle
fed a high-energy grain diet generate manure with a high
CH4-producing capacity. Range cattle fed a low energy diet
of forage material produce manure with about 50 percent
of the CH4-producing potential of feedlot cattle manure.
However, some higher energy feeds also are more digestible
than lower quality forages, which can result in less overall
waste excreted from the animal. Ultimately, a combination of
diet types and the growth rate of the animals will affect the
quantity and characteristics of the manure produced.
A very small portion of the total nitrogen excreted
is expected to convert to N2O in the waste management
system. The production of N2O from livestock manure
depends on the composition of the manure and urine, the
6-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
type of bacteria involved in the process, and the amount of
oxygen and liquid in the manure system. For N2O emissions
to occur, the manure must first be handled aerobically where
ammonia or organic nitrogen is converted to nitrates and
nitrites (nitrification), and then handled anaerobically where
the nitrates and nitrites are reduced to nitrogen gas (N2),
with intermediate production of N2O and nitric oxide (NO)
(denitrification) (Groffman et al. 2000). These emissions are
most likely to occur in dry manure handling systems that
have aerobic conditions, but that also contain pockets of
anaerobic conditions due to saturation. For example, manure
at cattle drylots is deposited on soil, oxidized to nitrite and
nitrate, and has the potential to encounter saturated conditions
following rain events.
Certain N2O emissions are accounted for and discussed
in the Agricultural Soil Management source category within
the Agriculture sector. These are emissions from livestock
manure and urine deposited on pasture, range, or paddock
lands, as well as emissions from manure and urine that is
spread onto fields either directly as "daily spread" or after
it is removed from manure management systems (e.g.,
lagoon, pit, etc.).
Table 6-6 and Table 6-7 provide estimates of CH4
and N2O emissions from manure management by animal
category. Estimates for CH4 emissions in 2004 were 39.4
Tg CO2 Eq. (1,875 Gg), 26 percent higher than in 1990.
The majority of this increase was from swine and dairy
cow manure, where emissions increased 32 and 38 percent,
respectively. The increase in emissions from these animal
types is primarily attributed to shifts by the swine and dairy
industries towards larger facilities. 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,
tend to utilize more liquid-based systems to manage (flush
or scrape) and store manure. Thus the shift toward larger
facilities is translated into an increasing use of liquid manure
management systems, which have higher potential CH4
emissions than dry systems. This shift was accounted for by
incorporating state-specific weighted CH4 conversion factor
(MCF) values in combination with the 1992 and 1997 farm-
size distribution data reported in the Census of Agriculture
(USDA 2005g). From 2003 to 2004, there was a 0.6 percent
increase in CH4 emissions, due to minor shifts in the animal
populations and the resultant effects on manure management
system allocations. A description of the emission estimation
methodology is provided in Annex 3.10.
Total N2O emissions from manure management systems
in 2004 were estimated to be 17.7 Tg CO2 Eq. (57 Gg). The
9 percent increase in N2O emissions from 1990 to 2004 can
be partially attributed to a shift in the poultry industry away
from the use of liquid manure management systems, in favor
of litter-based systems and high-rise houses. In addition,
Table 6-6: CH4 and N20 Emissions from Manure Management (Tg C02 Eq.)
Gas/Animal Type
CH4
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
N20
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
Total
1990
31.2
11.4
3.2
13.1
0.2
+
2.7
0.6
16.3
4.3
4.9
0.4
0.1
+
6.3
0.2
47.4
1998
38.8
13.9
3.1
18.4
0.1
+
2.7
0.6
17.4
3.9
5.5
0.4
0.1
+
7.2
0.2
56.2
1999
38.1
14.1
3.1
17.6
0.1
+
2.6
0.6
17.4
4.0
5.6
0.4
0.1
+
7.2
0.2
55.6
2000
38.0
14.5
3.1
17.0
0.1
+
2.6
0.6
17.8
3.9
5.9
0.4
0.1
+
7.2
0.2
55.9
2001
38.9
15.0
3.1
17.3
0.1
+
2.7
0.6
18.1
3.9
6.1
0.4
0.1
+
7.3
0.2
56.9
2002
39.3
15.1
3.1
17.7
0.1
+
2.7
0.6
18.0
3.9
5.9
0.4
0.1
+
7.4
0.2
57.3
2003
39.2
15.7
3.1
17.0
0.1
+
2.7
0.6
17.5
3.9
5.6
0.4
0.1
+
7.3
0.2
56.7
2004
39.4
15.7
3.1
17.2
0.1
+
2.7
0.6
17.7
3.8
5.7
0.4
0.1
+
7.4
0.2
57.1
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Agriculture 6-7
-------
Table 6-7: CH4 and N20 Emissions from Manure Management (Gg)
Gas/Animal Type
CH4
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
N20
Dairy Cattle
Beef Cattle
Swine
Sheep
Goats
Poultry
Horses
1990
1,484
544
153
622
9
1
128
27
52
14
16
1
+
+
20
1
1998
1,848
660
149
874
6
1
129
28
56
13
18
1
+
+
23
1
1999
1,816
672
148
837
6
1
125
28
56
13
18
1
+
+
23
1
2000
1,811
691
149
812
5
1
125
28
58
13
19
1
+
+
23
1
2001
1,850
713
148
826
5
1
129
29
58
13
20
1
+
+
24
1
2002
1,871
720
147
843
5
1
127
29
58
13
19
1
+
+
24
1
2003
1,865
746
146
811
5
1
127
29
57
13
18
1
+
+
24
1
2004
1,875
749
145
820
5
1
127
29
57
12
19
1
+
+
24
1
+ Does not exceed 0.5 Gg.
Note: Totals may not sum due to independent rounding.
there was an overall increase in the population of poultry
and swine from 1990 to 2004, although swine populations
periodically declined slightly throughout the time series.
N2O emissions showed a 0.9 percent increase from 2003 to
2004, due to minor shifts in animal population.
The population of beef cattle in feedlots increased
over the period of 1990 to 2004, resulting in increased N2O
emissions from this sub-category of cattle. Although dairy
cow populations decreased overall for the period 1990 to
2004, the population of dairies managing and storing manure
on-site—as opposed to using pasture, range, or paddock or
daily spread systems—increased. Over the same period,
dairies also experienced a shift to more liquid manure
management systems at large operations, which result in
lower N2O emissions then dry systems. The net result is a
slight decrease in dairy cattle N2O emissions over the period
1990 to 2004. As stated previously, N2O emissions from
livestock manure deposited on pasture, range, or paddock
land and manure immediately applied to land in daily
spread systems are accounted for in the Agricultural Soil
Management source category of the Agriculture sector.
Methodology
The methodologies presented in the IPCC Good Practice
Guidance (IPCC 2000) form the basis of the CH4 and N2O
emission estimates for each animal type. The calculation of
emissions requires the following information:
• Animal population data (by animal type and state);
• Amount of nitrogen produced (excretion rate by animal
type times animal population);
• Amount of volatile solids produced (excretion rate by
animal type times animal population);
• CH4 producing potential of the volatile solids (by animal
type);
• Extent to which the CH4 producing potential is realized
for each type of manure management system (by state
and manure management system, including the impacts
of any biogas collection efforts);
• Portion of manure managed in each manure management
system (by state and animal type); and
• Portion of manure deposited on pasture, range, or
paddock or used in daily spread systems.
This section presents a summary of the methodologies
used to estimate CH4 and N2O emissions from manure
management for this inventory. See Annex 3.10 for
more detailed information on the methodology and data
used to calculate CH4 and N2O emissions from manure
management.
Both CH4 and N2O emissions were estimated by first
determining activity data, including animal population, waste
characteristics, and manure management system usage. For
swine and dairy cattle, manure management system usage
was determined for different farm size categories using data
6-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
from USDA (USDA 1996b, 1998d, 2000b) and EPA (ERG
2000a, EPA 2002a, 2002b). For beef cattle and poultry, manure
management system usage data were not tied to farm size but
were based on other data sources (ERG 2000a, USDA 2000c,
UEP 1999). For other animal types, manure management
system usage was based on previous estimates (EPA 1992).
Next, MCFs andN2O emission factors were determined
for all manure management systems. MCFs for dry systems
and N2O emission factors for all systems were set equal to
default IPCC factors for temperate climates (IPCC 2000).
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 (see Annex
3.10 for detailed information on MCF derivations for liquid
systems). The MCF calculations model the average monthly
ambient temperature, a minimum system temperature, the
carryover of volatile solids in the system from month to
month due to long storage times exhibited by anaerobic
lagoon systems, and a factor to account for management
and design practices that result in the loss of volatile solids
from lagoon systems.
For each animal group, the base emission factors were
weighted to incorporate the distribution of management
systems used within each state to create an overall state-
specific weighted emission factor. To calculate this weighted
factor, the percent of manure for each animal group managed
in a particular system in a state was multiplied by the
emission factor for that system and state, and then summed
for all manure management systems in the state.
CH4 emissions were estimated using the volatile solids
(VS) production for all livestock. For poultry and swine
animal groups, for example, VS production was calculated
using a national average VS production rate from the
Agricultural Waste Management Field Handbook (USDA
1996a), which was then multiplied by the average weight
of the animal and the state-specific animal population. For
most cattle groups, regional animal-specific VS production
rates that are related to the diet of the animal for each year
of the inventory were used (Lieberman and Pape, 2005). The
resulting VS for each animal group were then multiplied by
the maximum CH4 producing capacity of the waste (B0) and
the state-specific MCFs.
N2O emissions were estimated by determining total
Kjeldahl nitrogen (TKN)1 production for all livestock wastes
using livestock population data and nitrogen excretion rates
based on measurements of excreted manure. For each animal
group, TKN production was calculated using a national
average nitrogen excretion rate from the Agricultural Waste
Management Field Handbook (USDA 1996a), which was
then multiplied by the average weight of the animal and the
state-specific animal population. State-specific weighted N2O
emission factors specific to the type of manure management
system were then applied to total nitrogen production to
estimate N2O emissions.
The data used to calculate the inventory estimates were
based on a variety of sources. Animal population data for
all livestock types, except horses and goats, were obtained
from the United States Department of Agriculture's National
Agricultural Statistics Service (USDA 1994a-b, 1995a-b,
1998a-b, 1999a-c, 2000a, 2004a-e, 2005a-f). Horse population
data were obtained from the FAOSTAT database (FAO 2005),
because USDA does not estimate U.S. horse populations
annually. Goat population data were obtained from the Census
of Agriculture (USDA 2005g). Information regarding poultry
turnover (i.e., slaughter) rate was obtained from state Natural
Resource Conservation Service (NRCS) personnel (Lange
2000). Dairy cow and swine population data by farm size for
each state, used for the weighted MCF and emission factor
calculations, were obtained from the Census of Agriculture,
which is conducted every five years (USDA 2005g).
Manure management system usage data for dairy and
swine operations were obtained from USDA's Centers for
Epidemiology and Animal Health (USDA 1996b, 1998d,
2000b) for small operations and from estimates for EPA's
Office of Water regulatory effort for large operations (ERG
2000a; EPA 2002a, 2002b). Data for layers were obtained
from a voluntary United Egg Producers' survey (UEP 1999),
previous EPA estimates (EPA 1992), and USDA's Animal
Plant Health Inspection Service (USDA 2000c). Data for
beef feedlots were also obtained from EPA's Office of Water
(ERG 2000a; EPA 2002a, 2002b). Manure management
system usage data for other livestock were taken from
previous estimates (EPA 1992). Data regarding the use of
daily spread and pasture, range, or paddock systems for dairy
cattle were obtained from personal communications with
1 Total Kjeldahl nitrogen is a measure of organically bound nitrogen and ammonia nitrogen.
Agriculture 6-9
-------
personnel from several organizations, and data provided by
those personnel. These organizations include state NRCS
offices, state extension services, state universities, USDA
National Agriculture Statistics Service (NASS), and other
experts (Deal 2000, Johnson 2000, Miller 2000, Poe et
al. 1999, Stettler 2000, Sweeten 2000, and Wright 2000).
Additional information regarding the percent of beef steer
and heifers on feedlots was obtained from contacts with the
national USDA office (Milton 2000).
MCFs for liquid systems were calculated based on
average ambient temperatures of the counties in which animal
populations were located. The average county and state
temperature data were obtained from the National Climate
Data Center (NOAA 2004). County population data were
calculated from state-level population data from NASS and
county-state distribution data from the 1992,1997, and 2002
Census data (USDA 2005g). County population distribution
data for 1990 and 1991 were assumed to be the same as
1992; county population distribution data for 1993 through
1996 were extrapolated based on 1992 and 1997 data; county
population data for 1998 through 2001 were extrapolated
based on 1997 and 2002 data; and county population data for
2003 to 2004 were assumed to be the same as 2002.
The maximum CH4 producing capacity of the VS, or B0,
was determined based on data collected in a literature review
(ERG 2000b). B0 data were collected for each animal type
for which emissions were estimated.
Nitrogen excretion rate data from the USDA Agricultural
Waste Management Field Handbook (USDA 1996a) were
used for all livestock except sheep, goats, and horses. Data
from the American Society of Agricultural Engineers (ASAE
1999) were used for these animal types. VS excretion rate
data from the USDA Agricultural Waste Management Field
Handbook (USDA 1996a) were used for swine, poultry, bulls,
and calves not on feed. In addition, VS production rates from
Lieberman and Pape (2005) were used for dairy and beef
cows, heifers, and steer for each year of the inventory. N2O
emission factors and MCFs for dry systems were taken from
Good Practice Guidance (IPCC 2000).
Uncertainty
An analysis was conducted for the manure management
emission estimates presented in EPA's Inventory of U.S.
Greenhouse Gas Emissions and Sinks: 1990-2001 (EPA
2003a) to determine the uncertainty associated with
estimating N2O and CH4 emissions from livestock manure
management. Because no substantial modifications were
made to the inventory methodology since the development of
these estimates, it is expected that this analysis is applicable
to the uncertainty associated with the current manure
management emission estimates.
The quantitative uncertainty analysis for this source
category was performed through the IPCC-recommended
Tier 2 uncertainty estimation methodology, Monte Carlo
Stochastic Simulation technique. The uncertainty analysis
was developed based on the methods used to estimate N2O
and CH4 emissions from manure management systems.
A normal probability distribution was assumed for each
source data category. The series of equations used were
condensed into a single equation for each animal type and
state. The equations for each animal group contained four
to five variables around which the uncertainty analysis was
performed for each state.
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 6-8. Manure management CH4
emissions in 2004 were estimated to be between 32.3 and
47.3 Tg CO2 Eq. at a 95 percent confidence level (or 19 of 20
Monte Carlo Stochastic Simulations). This indicates a range
of 18 percent below to 20 percent above the 2004 emission
estimate of 39.4 Tg CO2 Eq. At the 95 percent confidence
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Manure Management (Tg C02
Eq. and Percent)
Source
Manure Management
Manure Management
Gas
CH4
N20
2004 Emission
Estimate
(Tg C02 Eq.)
39.4
17.7
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound
32.3
14.9
Upper Bound
47.3
21.9
Lower Bound Upper Bound
-18% +20%
-16% +24%
aRange of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
6-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
level, N2O emissions were estimated to be between 14.9
and 21.9 Tg CO2 Eq. (or approximately 16 percent below
and 24 percent above the 2004 emission estimate of 17.7
Tg C02 Eq.).
The primary factors that contribute to the uncertainty
in emission estimates are a lack of information on the usage
of various manure management systems in each regional
location and the exact CH4 generating characteristics of each
type of manure management system. Because of significant
shifts in the swine and dairy sectors toward larger farms,
it is believed that increasing amounts of manure are being
managed in liquid manure management systems. The existing
estimates reflect these shifts in the weighted MCFs based
on the 1992, 1997, and 2002 farm-size data. However, the
assumption of a direct relationship between farm size and
liquid system usage may not apply in all cases and may vary
based on geographic location. In addition, the CH4 generating
characteristics of each manure management system type are
based on relatively few laboratory and field measurements,
and may not match the diversity of conditions under which
manure is managed nationally.
The IPCC Good Practice Guidance (IPCC 2000)
published a default range of MCFs for anaerobic lagoon
systems of 0 to 100 percent, which reflects the wide range
in performance that may be achieved with these systems.
There exist relatively few data points on which to determine
country-specific MCFs for these systems. In the United
States, many livestock waste treatment systems classified
as anaerobic lagoons are actually holding ponds that are
substantially organically overloaded and therefore not
producing CH4 at the same rate as a properly designed
lagoon. In addition, these systems may not be well operated,
contributing to higher loading rates when sludge is allowed
to enter the treatment portion of the lagoon or the lagoon
volume is pumped too low to allow treatment to occur. Rather
than setting the MCF for all anaerobic lagoon systems in the
United States based on data available from optimized lagoon
systems, a MCF methodology was developed that more
closely matches observed system performance and accounts
for the affect of temperature on system performance.
However, there is uncertainty related to this methodology.
The MCF methodology used in the inventory includes a factor
to account for management and design practices that result in
the loss of VS from the management system. This factor is
currently estimated based on data from anaerobic lagoons in
temperate climates, and from only three systems. However,
this methodology is intended to account for systems across
a range of management practices. Future work in gathering
measurement data from animal waste lagoon systems across
the country will contribute to the verification and refinement
of this methodology. It will also be evaluated whether lagoon
temperatures differ substantially from ambient temperatures
and whether the lower bound estimate of temperature
established for lagoons and other liquid systems should be
revised for use with this methodology.
The IPCC provides a suggested MCF for poultry waste
management operations of 1.5 percent. Additional study
is needed in this area to determine if poultry high-rise
houses promote sufficient aerobic conditions to warrant
a lower MCF.
The default N2O emission factors published in the IPCC
Good Practice Guidance (IPCC 2000) were derived using
limited information. The IPCC factors are global averages;
U.S.-specific emission factors may be significantly different.
Manure and urine in anaerobic lagoons and liquid/slurry
management systems produce CH4 at different rates, and
would in all likelihood produce N2O at different rates,
although a single N2O emission factor was used for both
system types. In addition, there are little data available to
determine the extent to which nitrification-denitrification
occurs in animal waste management systems. Ammonia
concentrations that are present in poultry and swine systems
suggest that N2O emissions from these systems may be
lower than predicted by the IPCC default factors. At this
time, there are insufficient data available to develop U.S.-
specific N2O emission factors; however, this is an area of
on-going research, and warrants further study as more data
become available.
Uncertainty also exists with the maximum CH4 producing
potential of VS excreted by different animal groups (i.e., B0).
The B0 values used in the CH4 calculations are published
values for U.S. animal waste. However, there are several
studies that provide a range of B0 values for certain animals,
including dairy and swine. The B0 values chosen for dairy
assign separate values for dairy cows and dairy heifers to
better represent the feeding regimens of these animal groups.
For example, dairy heifers do not receive an abundance of
high energy feed and consequently, dairy heifer manure will
not produce as much CH4 as manure from a milking cow.
However, the data available for B0 values are sparse, and do
Agriculture 6-11
-------
not necessarily reflect the rapid changes that have occurred
in this industry with respect to feed regimens.
QA/QC and Verification
Tier 1 and Tier 2 QA/QC activities were conducted
consistent with the U.S. QA/QC plan. Tier 2 activities
focused on comparing estimates for the 2003 and 2004
Inventories for N2O emissions from managed systems and
CH4 emissions from livestock manure. All errors identified
were corrected. Order of magnitude checks were also
conducted, and corrections made where needed. Manure
nitrogen data were quality assured by comparing state-level
data with bottom up estimates derived at the county level
and summed to the state level. Similarly, a comparison was
made by animal and waste management system type for
the full time series, between national level estimates for
nitrogen excreted and the sum of county estimates for the
full time series.
Recalculations Discussion
No changes have been incorporated into the overall
methodology for the manure management emission estimates.
However, changes were made to the 2004 calculations
involving animal population data. Animal population data
were updated to reflect the final estimates reports from USDA
NASS, and 2002 USDA Census of Agriculture data (USDA
1994a-b, 1995a-b, 1998a-b, 1999a-c, 2000a, 2004a-e, 2005a-
g). The population data in the most recent final estimates
reflect some adjustments due to USDA NASS review. For
horses, state-level populations were estimated using the
national FAO population data and the state distributions from
the 1992, 1997, and 2002 Census of Agriculture.
This change resulted in an average annual increase of
0.6 Tg CO2 Eq. (2 percent) in CH4 emissions and an average
annual increase of 0.1 Tg CO2 Eq. (0.6 percent) in N2O
emissions from manure management for the period 1990
through 2004.
Planned Improvements
Although an effort was made to introduce the variability
in VS production due to differences in diet for beef and dairy
cows, heifers, and steer, further research is needed to confirm
and track diet changes over time. A methodology to assess
variability in swine VS production would be useful in future
inventory estimates.
Research will be initiated into the estimation and
validation of the maximum CH4-producing capacity of
animal manure (B0), for the purpose of obtaining more
accurate data to develop emission estimates.
The American Society of Agricultural Engineers
proposed new standards for manure production characteristics
in 2004. These data will be investigated and evaluated for
incorporation into future estimates.
Currently, 2004 temperature data are not incorporated
into the 2004 model for the estimates of MCFs; 2003 data
were used for 2004. The temperature data will be updated
in the next year's inventory.
The methodology to calculate MCFs for liquid systems
will be examined to determine how to account for a maximum
temperature in the liquid systems. Additionally, available
research will be investigated to develop a relationship
between ambient air temperature and temperature in
liquid waste management systems in order to improve that
relationship in the MCF methodology.
Currently, temperate zone MCFs are used for non-liquid
waste management systems, including pasture, range, and
paddock, daily spread, solid storage, and drylot operations.
However, there are some states that have an annual average
temperature that would fall below 15°C (i.e., classified as
"cool" zones). Therefore, CH4 emissions from certain non-
liquid waste management systems may be overestimated;
however, the difference is expected to be relatively small
due to the low MCFs for all "dry" management systems.
The use of both cool and temperate MCFs for non-liquid
waste management systems will be investigated for future
inventories.
The 2002 Census of Agriculture data became available
in mid-2004 and have already been incorporated into animal
population estimates. EPA will also incorporate these
data into future estimates of waste management system
usage data for swine and dairy. For these animal groups,
the percent of waste by management system is estimated
using data broken out by geographic region and farm.
Farm-size distribution data reported in the 1992 and 1997
Census of Agriculture are currently used to determine
the percentage of animals utilizing the various manure
management systems; farm-size data from the 2002
Census of Agriculture will be incorporated into next year's
inventory.
6-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
The development of the National Ammonia Emissions
Inventory for the United States (EPA 2004) used similar data
sources to the current estimates of emissions from manure
management, and through the course of development of the
ammonia inventory, updated waste management distribution
data were identified. Future inventory estimates will
incorporate these updated data.
6.3. Rice Cultivation (IPCC Source
Category 4C)
Most of the world's rice, and all rice in the United States,
is grown on flooded fields. When fields are flooded, aerobic
decomposition of organic material gradually depletes the
oxygen present in the soil and floodwater, causing anaerobic
conditions in the soil to develop. Once the environment
becomes anaerobic, CH4 is produced through anaerobic
decomposition of soil organic matter by methanogenic
bacteria. As much as 60 to 90 percent of the CH4 produced
is oxidized by aerobic methanotrophic bacteria in the soil
(Holzapfel-Pschornetal. 1985,Sassetal. 1990). Some of the
CH4 is also leached away as dissolved CH4 in floodwater that
percolates from the field. The remaining un-oxidized CH4
is transported from the submerged soil to the atmosphere
primarily by diffusive transport through the rice plants. Minor
amounts of CH4 also escape from the soil via diffusion and
bubbling through floodwaters.
The water management system under which rice is
grown is one of the most important factors affecting CH4
emissions. Upland rice fields are not flooded, and therefore
are not believed to produce CH4. In deepwater rice fields
(i.e., fields with flooding depths greater than one meter),
the lower stems and roots of the rice plants are dead so
the primary CH4 transport pathway to the atmosphere is
blocked. The quantities of CH4 released from deepwater
fields, therefore, are believed to be significantly less than the
quantities released from areas with more shallow 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 that is available to decompose (i.e., organic fertilizer
use, soil type, rice variety,2 and cultivation practices) are the
most important variables influencing the amount of CH4
emitted over an entire growing season because 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.
Pvice is cultivated in eight states: Arkansas, California,
Florida, Louisiana, Mississippi, Missouri, Oklahoma, and
Texas. Soil types, rice varieties, and cultivation practices
for rice vary from state to state, and even from farm to
farm. However, most rice farmers utilize organic fertilizers
in the form of rice residue from the previous crop, which
is left standing, disked, or rolled into the fields. Most
farmers also apply synthetic fertilizer to their fields, usually
urea. Nitrate and sulfate fertilizers are not commonly
used in rice cultivation in the United States. In addition,
the climatic conditions of Arkansas, southwest Louisiana,
Texas, and Florida allow for a second, or ratoon, rice crop.
CH4 emissions from ratoon crops have been found to be
considerably higher than those from the primary crop. This
second rice crop is produced from regrowth of the stubble
2 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.
Agriculture 6-13
-------
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
for the stubble to decay aerobically), the amount of organic
material that is available for decomposition is considerably
higher than with the first (i.e., primary) crop.
Rice cultivation is a small source of CH4 in the United
States (Table 6-9 and Table 6-10). In 2004, CH4 emissions
from rice cultivation were 7.6 Tg CO2 Eq. (360 Gg).
Although annual emissions fluctuated unevenly between the
Table 6-9: CH4 Emissions from Rice Cultivation (Tg C02 Eq.)
years 1990 and 2004, ranging from an annual decrease of
11 percent to an annual increase of 17 percent, there was an
overall increase of 6 percent over the fourteen-year period,
due to an overall increase in primary crop area.3
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. Price is the primary factor affecting rice area.
in Arkansas, as farmers will plant more of what is most
lucrative amongst soybeans, rice, and cotton. Government
State
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
Total
1990
5.1
2.1
0.7
+
1.0
0.4
0.1
+
0.6
2.1
+
+
1.1
0.9
7.1
1998
5.8
2.7
0.8
+
1.1
0.5
0.3
+
0.5
2.1
+
0.1
1.2
0.8
7.9
1999
6.3
2.9
0.9
+
1.1
0.6
0.3
+
0.5
2.0
+
0.1
1.2
0.7
8.3
2000
5.5
2.5
1.0
+
0.9
0.4
0.3
+
0.4
2.0
+
0.1
1.3
0.7
7.5
2001
5.9
2.9
0.8
+
1.0
0.5
0.4
+
0.4
1.7
+
+
1.1
0.6
7.6
2002
5.7
2.7
0.9
+
1.0
0.5
0.3
+
0.4
1.1
+
+
0.5
0.5
6.8
2003
5.4
2.6
0.9
+
0.8
0.4
0.3
+
0.3
1.5
+
+
1.0
0.5
6.9
2004
6.0
2.8
1.1
+
1.0
0.4
0.3
+
0.4
1.6
+
+
1.1
0.5
7.6
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 6-10: CH4 Emissions from Rice Cultivation (Gg)
State
Primary
Arkansas
California
Florida
Louisiana
Mississippi
Missouri
Oklahoma
Texas
Ratoon
Arkansas
Florida
Louisiana
Texas
Total
1990
241
102
34
1
46
21
7
+
30
98
+
2
52
45
339
1998
279
126
39
2
53
23
12
+
24
98
+
3
59
36
376
1999
300
138
43
2
52
27
16
+
22
95
+
4
58
33
395
2000
260
120
47
2
41
19
14
+
18
97
+
2
61
34
357
2001
283
138
40
1
46
22
18
+
18
81
+
2
52
27
364
2002
274
128
45
1
45
22
15
+
18
52
+
2
25
24
325
2003
255
124
43
+
38
20
15
+
15
73
+
2
50
22
328
2004
284
132
50
1
45
20
17
+
19
77
+
2
50
24
360
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
3 The 11 percent decrease occurred between 1992 and 1993 and 2001 and 2002; the 17 percent increase happened between 1993 and 1994.
6-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
support programs have also been influential by affecting
the price received for a rice crop (Slaton 200 Ib, Mayhew
1997). California rice area is primarily influenced by price
and government programs, but is also affected by water
availability (Mutters 2001). In Florida, rice acreage is
largely a function of the price of rice relative to sugarcane
and corn. Most rice in Florida is rotated with sugarcane, but
sometimes it is more profitable for farmers to follow their
sugarcane crop with sweet corn or more sugarcane instead
of rice (Schueneman 1997, 2001b). In Louisiana, rice area
is influenced by government support programs, the price of
rice relative to cotton, soybeans, and corn, and in some years,
weather (Saichuk 1997, Linscombe 2001b). For example, a
drought in 2000 caused extensive saltwater intrusion along
the Gulf Coast, making over 32,000 hectares unplantable.
The dramatic decrease in ratooned area in Louisiana in 2002
was the result of hurricane damage to that state's rice-cropped
area. In Mississippi, rice is usually rotated with soybeans, but
if soybean prices increase relative to rice prices, then some of
the acreage that would have been planted in rice, is instead
planted in soybeans (Street 1997, 2001b). In Missouri, rice
acreage is affected by weather (e.g., rain during the planting
season may prevent the planting of rice), the price differential
between rice and soybeans or cotton, and government support
programs (Stevens 1997, Guethle 2001b). In Oklahoma, the
state having the smallest harvested rice area, rice acreage is
limited to the areas in the state with the right type of land
for rice cultivation. Acreage is limited to growers who can
afford the equipment, labor, and land for this intensive crop
(Lee 2003). Texas rice area is affected mainly by the price
of rice, government support programs, and water availability
(Klosterboer 1997, 200Ib).
Methodology
The Revised 1996 IPCC Guidelines (IPCC/UNEP/
OECD/IEA 1997) recommends utilizing harvested rice
areas and area-based seasonally integrated emission factors
(i.e., amount of CH4 emitted over a growing season per
unit harvested area) to estimate annual CH4 emissions from
rice cultivation. This methodology is followed with the use
of U.S.-specific emission factors derived from rice field
measurements. Seasonal emissions have been found to be
much higher for ratooned crops than for primary crops, so
emissions from ratooned and primary areas are estimated
separately using emission factors that are representative of
the particular growing season. This approach is consistent
with IPCC Good Practice Guidance (IPCC 2000).
The harvested rice areas for the primary and ratoon
crops in each state are presented in Table 6-11. Primary crop
areas for 1990 through 2004 for all states except Florida and
Oklahoma were taken from U.S. Department of Agriculture's
Field Crops Final Estimates 1987-1992 (USDA1994), Field
Crops Final Estimates 1992-1997 (USDA 1998), Field
Crops Final Estimates 1997-2002 (USDA 2003), and Crop
Production 2004 Summary (USDA 2005). Harvested rice
areas in Florida, which are not reported by USDA, were
obtained from Tom Schueneman (1999b, 1999c, 2000,
200la) and Arthur Kirstein (2003), Florida agricultural
extension agents, Dr. Chris Deren (2002) of the Everglades
Research and Education Centre at the University of Florida,
and Gaston Cantens (2004,2005), Vice President of Corporate
Relations of the Florida Crystals Company. Harvested rice
areas for Oklahoma, which also are not reported by USDA,
were obtained from Danny Lee of the Oklahoma Farm
Services Agency (2003,2004,2005). Acreages for the ratoon
crops were derived from conversations with the agricultural
extension agents in each state. In Arkansas, ratooning
occurred only in 1998 and 1999, when the ratooned area
was less than 1 percent of the primary area (Slaton 1999,
2000, 2001a; Wilson 2002, 2003, 2004, 2005). In Florida,
the ratooned area was 50 percent of the primary area from
1990 to 1998 (Schueneman 1999a), about 65 percent of the
primary area in 1999 (Schueneman 2000), around 41 percent
of the primary area in 2000 (Schueneman 2001a), about 60
percent of the primary area in 2001 (Deren 2002), about 54
percent of the primary area in 2002 (Kirstein 2003), about
100 percent of the primary area in 2003 (Kirstein 2004),
and about 77 percent of the primary area in 2004 (Cantens
2005). In Louisiana, the percentage of the primary area that
was ratooned was constant at 30 percent over the 1990 to
1999 period, increased to approximately 40 percent in 2000,
returned to 30 percent in 2001, dropped to 15 percent in 2002,
rose to 35 percent in 2003, and returned to 30 percent in 2004
(Linscombe 1999, 2001a, 2002, 2003, 2004, 2005; Bollich
2000). In Texas, the percentage of the primary area that was
ratooned was constant at 40 percent over the entire 1990 to
1999 period, increased to 50 percent in 2000 due to an early
primary crop, and then decreased to 40 percent in 2001, 37
percent in 2002,38 percent in 2003, and 35 percent in 2004
(Klosterboer 1999, 2000, 2001a, 2002, 2003; Stansel 2004,
Agriculture 6-15
-------
Table 6-11: Rice Areas Harvested (Hectares)
State/Crop
Arkansas
Primary
Ratoon*
California
Florida
Primary
Ratoon
Louisiana
Primary
Ratoon
Mississippi
Missouri
Oklahoma
Texas
Primary
Ratoon
Total Primary
Total Ratoon
Total
1990
485
159
4
2
220
66
101
32
142
57
1,148
125
1,273
,633
0
,854
,978
,489
,558
,168
,174
,376
617
,857
,143
,047
,799
,847
1998
600,971
202
185,350
8,094
4,047
250,911
75,273
108,458
57,871
19
114,529
45,811
1,326,203
125,334
1,451,536
1999
657,628
202
204,371
7,229
4,673
249,292
74,788
130,716
74,464
220
104,816
41,926
1,428,736
121,589
1,550,325
2000
570,
221,
7,
3,
194,
77,
88,
68,
86,
43,
1,237,
124,
1,362,
619
0
773
801
193
253
701
223
393
283
605
302
951
197
148
2001
656,010
0
190,611
4,562
2,752
220,963
66,289
102,388
83,772
265
87,414
34,966
1,345,984
104,006
1,449,991
2002
608
213
5
2
216
32
102
73
83
30
1,303
66
1,369
,256
0
,679
,077
,734
,512
,477
,388
,654
274
,367
,846
,206
,056
,262
2003
588,830
0
205,180
2,315
2,315
182,113
63,739
94,699
69,203
53
72,845
27,681
1,215,237
93,735
1,308,972
2004
629,300
0
238,770
5,077
2,734
215,702
64,711
94,699
78,915
158
88,223
30,878
1,350,844
98,323
1,449,167
* Arkansas ratooning occurred only in 1998 and 1999.
Note: Totals may not sum
due to independent rounding.
2005). California, Mississippi, Missouri, and Oklahoma have
not ratooned rice over the period 1990-2004 (Guethle 1999,
2000,2001a, 2002,2003,2004,2005; Lee 2003,2004,2005;
Mutters 2002, 2003, 2004, 2005; Street 1999, 2000, 2001a,
2002, 2003; Walker 2004, 2005).
To determine what seasonal CH4 emission factors
should be used for the primary and ratoon crops, CH4 flux
information from rice field measurements in the United
States was collected. Experiments which involved atypical or
nonrepresenative 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 results4 were
then sorted by season (i.e., primary and ratoon) and type
of fertilizer amendment (i.e., no fertilizer added, organic
fertilizer added, and synthetic and organic fertilizer added).
The experimental results from primary crops with added
synthetic and organic fertilizer (Bossio et al. 1999; Cicerone
etal. 1992;Sassetal. 1991a, 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 CH4/hectare-
season, and the resultant emission factor for the ratoon crop
is 780 kg CH4/hectare-season.
Uncertainty
The largest uncertainty in the calculation of CH4
emissions from rice cultivation is associated with the
emission factors. Seasonal emissions, derived from field
measurements in the United States, vary by more than
one order of magnitude. This inherent variability is due to
differences in cultivation practices, in particular, fertilizer
type, amount, and mode of application; differences in
cultivar type; and differences in soil and climatic conditions.
A portion of this variability is accounted for by separating
primary from ratooned areas. However, even within a
cropping season or a given management regime, measured
emissions may vary significantly. Of the experiments used to
derive the emission factors applied here, primary emissions
ranged from 22 to 479 kg CH4/hectare-season and ratoon
4 In some of these remaining experiments, measurements from individual plots were excluded from the analysis because of the reasons just mentioned. In
addition, one measurement from the ratooned fields (i.e., the flux of 2.041 g/m2/day in Lindau and Bollich 1993) was excluded since this emission rate is
unusually high compared to other flux measurements in the United States, as well as in Europe and Asia (IPCC/UNEP/OECD/IEA 1997).
6-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
emissions ranged from 481 to 1,490kg 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 were not normally distributed for
either primary or ratooned crops, but rather skewed, with a
tail trailing to the right of the mean, therefore a lognormal-
type statistical distribution was applied in the Tier 2 Monte
Carlo analysis.
Uncertainty regarding primary cropping area is an
additional consideration. Uncertainty associated with primary
rice-cropped area for each state was obtained from expert
judgment, and ranged from 1 percent to 5 percent of the mean
area. A normal distribution, truncated to avoid negative values,
of uncertainty was assumed about the mean for areas.
Another source of uncertainty lies in the ratooned
areas, which are not compiled regularly. Although ratooning
accounts for only 5 to 10 percent of the total rice-cropped
area, it is responsible for 15 to 30 percent of total emissions.
For states that have never reported any ratooning, it is
assumed that no ratooning occurred in 2004 with complete
certainty. For states that regularly report ratooning,
uncertainty is estimated to be between 3 percent and 5
percent (based on expert judgment) and is assumed to have
a normal distribution, truncated to avoid negative values.
For Arkansas, which reported ratooning in 1998 and 1999
only, a triangular distribution was assumed, with a lower
boundary of 0 percent ratooning and an upper boundary of
0.034 percent ratooning based on the maximum ratooned
area reported in 1998 and 1999.
A final source of uncertainty is in the practice of
flooding outside of the normal rice season. According to
agricultural extension agents, all of the rice-growing states
practice this on some part of their rice acreage. Estimates of
these areas range from 5 to 68 percent of the rice acreage.
Fields are flooded for a variety of reasons: to provide habitat
for waterfowl, to provide ponds for crawfish production,
and to aid in rice straw decomposition. To date, however,
CH4 flux measurements have not been undertaken over a
sufficient geographic range or under a broad enough range
of representative conditions to account for this source in the
emission estimates or its associated uncertainty.
To quantify the uncertainties for emissions from rice
cultivation, a Monte Carlo (Tier 2) uncertainty analysis
was performed using the information provided above. The
results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 6-12. Rice cultivation CH4 emissions
in 2004 were estimated to be between 2.5 and 19.4 Tg CO2
Eq. at a 95 percent confidence level (or 19 of 20 Monte Carlo
Stochastic Simulations). This indicates a range of 67 percent
below to 157 percent above the 2004 emission estimate of
7.6TgC02Eq.
QA/QC and Verification
A source-specific QA/QC plan for rice cultivation was
developed and implemented. This effort included a Tier 1
analysis, as well as portions of a Tier 2 analysis. The Tier 2
procedures focused on comparing trends across years, states,
and cropping seasons to attempt to identify any outliers or
inconsistencies. No problems were found. In addition, this
year calculation spreadsheets were linked directly to source
data spreadsheets to minimize transcription errors, and a
central, cross-cutting agricultural data spreadsheet was
created to prevent use of incorrect or outdated data.
Recalculations Discussion
For the previous Inventory report, 2000 data for rice
area harvested in Oklahoma were unavailable. Data were
updated for the current Inventory based on information
received from Lee (2005). This change resulted in a 0.02
Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation (Tg C02 Eq. and
Percent)
Source
2004 Emission
Estimate Uncertainty Range Relative to Emission Estimate3
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Rice Cultivation
CH4 7.6 2.5 19.4 -67% +157%
aRange of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Agriculture 6-17
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percent increase in emission estimates for 2000 relative to
the previous Inventory report.
6.4. Agricultural Soil Management
(IPCC Source Category 4D)
Nitrous oxide is produced naturally in soils through the
microbial processes of nitrification and denitrification.5 A
number of agricultural activities increase mineral nitrogen
(N) availability in soils, thereby increasing the amount
available for nitrification and denitrification, and ultimately
the amount of N2O emitted. These activities increase soil
mineral N either directly or indirectly (see Figure 6-2). Direct
increases occur through a variety of management practices
that add or lead to greater release of mineral N in the soil,
including fertilization; application of managed livestock
manure and other organic materials such as sewage sludge;
deposition of manure on soils by domesticated animals in
pastures, rangelands, and paddocks (PRP) (i.e., by grazing
animals and other animals whose manure is not managed);
production of N-fixing crops and forages; retention of crop
residues; and cultivation of organic soils (i .e., soils with a high
organic matter content, otherwise known as histosols).6 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. Indirect emissions occur through two pathways:
(1) volatilization and subsequent atmospheric deposition of
applied N;7 and (2) surface runoff and leaching of applied
N into groundwater and surface water. Direct emissions
from agricultural lands (i.e., croplands and grasslands) are
included in this section, while direct emissions from forest
lands and settlements are presented in the Land Use, Land-
Use Change, and Forestry chapter. However, indirect N2O
emissions due to anthropogenic activity on all land-use
types (croplands, grasslands, as well as forest lands and
settlements), are included in this section.
Agricultural soils are responsible for the majority of
U.S. N2O emissions. Estimated emissions from this source
in 2004 were 261.6 Tg CO2 Eq. (844 Gg N2O) (see Table
6-13 and Table 6-14). Annual agricultural soil management
N2O emissions fluctuated between 1990 and 2004; however,
overall emissions were 1.7 percent lower in 2004 than in
1990. Year-to-year fluctuations are largely a reflection of
annual variation in weather patterns, synthetic fertilizer use,
and crop production.
Estimated direct and indirect N2O emissions by sub-
source category are provided in Table 6-15 and Table 6-16.
Methodology
Current IPCC methods divide the N2O source category
into three components: (1) direct emissions from soils due to
N additions to cropland and grassland mineral soils and from
the drainage and cultivation of organic cropland soils; (2)
direct emissions from soils due to the deposition of manure by
livestock on PPJ3 grasslands; and (3) indirect emissions from
soils and water induced by N additions and manure deposition
to soils of all land-use types. The methodology used to
estimate emissions from agricultural soil management in the
United States is based on a combination of Tier 1 and Tier 3
approaches as defined in the Revised 1996 IPCC Guidelines
(IPCC/UNEP/OECD/IEA 1997), and later amended in the
IPCC Good Practice Guidance (IPCC 2000) and Good
Practice Guidance for Land Use, Land-Use Change, and
Forestry (IPCC 2003). Specifically, a Tier 3, process-based
model (DAYCENT) is used to estimate direct emissions
from major crops on mineral (i.e., non-organic) soils; as
well as most of the direct emissions from grasslands. The
DAYCENT-derived direct emissions from grasslands include
emissions from deposition of PRP manure as well as several
land management practices such as seeding with forage
legumes. The Tier 1 IPCC methodology is used to estimate
direct emissions from non-major crops on mineral soils;
the portion of the grassland direct emissions from PRP and
forage legume N additions that were not estimated with the
5 Nitrification and denitrification are driven by the activity of microorganisms in soils. Nitrification is the aerobic microbial oxidation of ammonium (NH4)
to nitrate (NO3), and denitrification is the anaerobic microbial reduction of nitrate to nitrogen gas (N2). Nitrous oxide is a gaseous intermediate product in
the reaction sequence of denitrification, which leaks from microbial cells into the soil and then into the atmosphere. Nitrous oxide is also produced during
nitrification, although by a less well understood mechanism (Nevison 2000).
6 Drainage and cultivation of organic soils in former wetlands enhances mineralization of N-rich organic matter, thereby enhancing N2O emissions from
these soils.
7 These processes entail volatilization of applied N as ammonia (NH3) and oxides of N (NOX), transformation of these gases within the atmosphere (or
upon deposition), and deposition of the N primarily in the form of particulate ammonium (NH4), nitric acid (HNO3), and NOX.
6-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Figure 6-2
Direct and Indirect N20 Emissions from Agricultural Soils
Volatilization
Commercial
Fertilizer
Application
This graphic illustrates the sources and pathways of nitrogen that result in direct and indirect N20 emissions from agricultural soils in the United States.
Sources of nitrogen applied to, or deposited on, soils are represented with arrows on the left-hand side of the graphic. Emission pathways are also shown
with arrows. On the lower right-hand side is a cut-away view of a representative section of a managed soil; histosol cultivation is represented here.
Table 6-13: N20 Emissions from Agricultural Soils (Tg C02 Eq.)
Activity
Direct
Cropland
Grassland
Indirect (All Land-Use Types)*
Total
1990
150,
108,
42,
115,
266.
.4
.2
.2
.7
1
1998
166,
129
36,
134,
301.
.6
.7
.9
.5
,1
1999
147,
117,
29
133,
281.
.6
.9
.6
.6
2
2000
165.4
124.9
40.5
112.8
278.2
2001
165.9
131.8
34.2
117.0
282.9
2002
169.9
121.7
48.2
107.9
277.8
2003
155.4
117.7
37.7
103.8
259.2
2004
170.9
133.8
37.2
90.6
261.5
Note: Totals may not sum due to independent rounding.
includes cropland, grassland, forest land, and settlements.
Agriculture 6-19
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Table 6-14: N20 Emissions from Agricultural Soils (Gg)
Activity
Direct
Cropland
Grassland
Indirect (All Land-Use Types)*
Total
1990
485
349
136
373
858
1998
538
418
119
434
971
1999
476
380
96
431
907
2000
534
403
131
364
897
2001
535
425
110
377
913
2002
548
392
155
348
896
2003
501
380
122
335
836
2004
551
431
120
292
844
Note: Totals may not sum due to independent rounding.
includes cropland, grassland, forest land, and settlements.
Table 6-15: Direct N20 Emissions from Agricultural Soils (Tg C02 Eq.)
Activity
Cropland
Mineral Soils
Organic Soils
Grassland
Total
1990
108,
105,
2,
42,
150,
.2
.3
.8
.2
.4
1998
129,
126,
2,
36,
166,
.7
.8
.9
.9
.6
1999
117,
115,
2,
29,
147,
.9
.1
.9
.6
.6
2000
124.9
122.0
2.9
40.5
165.4
2001
131.8
128.9
2.9
34.2
165.9
2002
121.7
118.8
2.9
48.2
169.9
2003
117.7
114.8
2.9
37.7
155.4
2004
133.8
130.8
2.9
37.2
170.9
Note: Totals may not sum due to independent rounding.
Table 6-16: Indirect N20 Emissions from all Land Use Types* (Tg C02 Eq.)
Activity
1990
1998 1999 2000 2001 2002 2003 2004
Volatilization and Atm. Deposition
Surface Leaching & Run-Off
16.2
99.5
17.8
116.7
17.2
116.5
18.0
94.8
17.5
99.5
17.7
90.2
17.7
86.0
17.3
73.3
Total
115.7
134.5 133.6 112.8 117.0 107.9 103.8
90.6
Note: Totals may not sum due to independent rounding.
includes cropland, grassland, forest land, and settlements.
Tier 3 DAY CENT model; and direct emissions from drainage
and cultivation of organic cropland soils. A combination of
DAYCENT and the IPCC Tier 1 method is used to estimate
indirect emissions from soils. Annex 3.11 provides more
detailed information on the methodologies and data used to
calculate N2O emissions from each component.
Direct N20 Emissions from Agricultural Soils
Major Crop Types on Mineral Cropland Soils
The DAYCENT ecosystem model (Del Grosso et al.
2001, Parton et al. 1998) was used to estimate direct N2O
emissions from mineral cropland soils producing major
crops, specifically corn, soybean, wheat, alfalfa hay, other
hay, sorghum, and cotton, which represent approximately 90
percent of total croplands in the United States. DAYCENT
simulated crop growth, soil organic matter decomposition,
greenhouse gas fluxes, and key biogeochemical processes
affecting N2O emissions, and the simulations were driven
by model input data generated from daily weather records
(Thornton et al. 1997, 2000; Thornton and Running 1999),
land management surveys (see citations below), and soil
physical properties determined in national soil surveys (Soil
Survey Staff 2005).
DAYCENT simulations were conducted for each
major crop at the county scale in the United States. The
county scale was selected because soil and weather data
were available for every county with more than 100 acres
of agricultural land. However, land management data (e.g.,
timing of planting, harvesting, and fertilizer application;
intensity of cultivation, rate of fertilizer application) were
6-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
only available at the agricultural region level as defined by
the Agricultural Sector Model (McCarl et al. 1993). There
are 63 agricultural regions in the contiguous United States;
most states correspond to one region, except for those with
greater heterogeneity in agricultural practices, in which there
are further subdivisions. Therefore, while several cropping
systems were simulated for each county in an agricultural
region, the model parameters that determined the influence
of management activities on soil N2O emissions (e.g., when
crops were planted/harvested, amount of fertilizer added), did
not differ among the counties in an agricultural region.
Nitrous oxide emission estimates from DAY CENT
include the influence of N additions, crop type, irrigation, and
other factors in aggregate, and therefore it is not possible to
partitionN2O emissions by anthropogenic activity (e.g., N2O
emissions from synthetic fertilizer applications cannot be
distinguished from those resulting from manure applications).
Consequently, emissions are not subdivided according to
activity (e.g., N fertilization, manure amendments), as is
suggested in the IPCC Guidelines, but the overall estimates
are still more accurate than the more simplistic IPCC method,
which is not capable of addressing the broader set of driving
variables influencing N2O emissions. Thus DAY CENT forms
the basis for a more complete estimation of N2O emissions
than is possible with the IPCC methodology.
Nitrous oxide emissions from managed agricultural
lands are the result of interactions between the combined
anthropogenic interventions that are implemented (e.g., N
fertilization and manure application) and natural background
emissions of N2O, which would occur regardless of
anthropogenic management. To isolate anthropogenic
emissions from natural background emissions of N2O,
DAY CENT was used to simulate emissions under potential
native conditions for lands used to produce major crops,
and the resulting estimates were subtracted from the N2O
emissions simulated under current crop management. The
reported estimates of emissions from managed soils therefore
represent the difference between simulated emissions from
potential native conditions and emissions from cropland
soils.
With these methods, DAY CENT was used to estimate
direct N2O emissions due to increased mineral N availability
for the following practices: (1) the application of synthetic
and organic commercial fertilizers, (2) the application of
livestock manure, (3) the production of N-fixing crops, and
(4) the retention of crop residues (i.e., leaving residues in
the field after harvest). For each of these practices, annual
increases in soil mineral N due to anthropogenic activity were
obtained or derived from the following sources:
• Crop-specific N-fertilization rates: Alexander and Smith
(1990), Anonymous (1924), Battaglin and Goolsby
(1994), Engle and Makela (1947), ERS (1994, 2003),
Fraps and Asbury (1931), Ibach and Adams (1967),
Ibach et al. (1964), NEA (1946), NRIAI (2003), Ross and
Mehring (1938), Skinner (1931), Smalley et al. (1939),
Taylor (1994), USDA (1966, 1957, 1954, 1946).
• Managed manure production and application to
croplands and grasslands: Manure N amendments
were determined using USDA Manure N Management
Databases for 1997 (Kellogg et al. 2000; Edmonds
et al. 2003). These values were adjusted for other
years based on manure N production. Data sources to
estimate manure production include USDA (1994b-
c, 1995a-b, 1998a, 1998c, 1999a-c, 2000a, 2004a-e,
2005a-g), FAO (2005), Lange (2000), Poe et al. (1999),
Anderson (2000), Deal (2000), Johnson (2000), Miller
(2000), Milton (2000), Stettler (2000), Sweeten (2000),
Wright (2000), Safley et al. (1992). Managed manure
N production was adjusted for the amount of manure
used for feed. Even with this adjustment, a portion of
the remaining managed manure N was not applied to
crop and grassland soils according to Edmonds et al.
(2003). The difference between manure N applied to
soils and remaining N in the managed manure was
assumed to be lost through volatilization of N species
during handling and storage. Instead of assuming that 10
percent of synthetic and 20 percent of organic N applied
to soils is volatilized and 30 percent of applied N was
leached/runoff as with IPCC methodology, volatilization
and N leaching/runoff from manure that was amended
to soils was internally calculated by the DAY CENT
process-based model.
• Nitrogen-fixing crops and forages and retention of crop
residue: The IPCC approach considers this information
as separate activity data. However, they are not
considered separate activity data for the DAY CENT
simulations because residue production and N fixation
are internally generated by the model. In other words,
Agriculture 6-21
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DAY CENT accounts for the influence of N fixation and
retention of crop residue on N2O emissions, but these
are not model inputs.
• Historical and modern crop rotation and management
information (e.g., timing and type of cultivation, timing
of planting/harvest, etc.): Kurd (1930, 1929), Latta
(1938), Iowa State College Staff Members (1946),
Bogue (1963), Hurt (1994), USDA (20041), USDA
(2000b) as extracted by Eve (2001) and revised by Ogle
(2002), CTIC (1998), Piper et al. (1924), Hardies and
Hume (1927), Holmes (1902, 1929), Spillman (1902,
1905, 1907, 1908), Chilcott (1910), Smith (1911),
Kezer (ca. 1917), Hargreaves (1993), ERS (2002),
Warren (1911), Langtson et al. (1922), Russell et al.
(1922), Elliot andTapp (1928), Elliot (1933), Ellsworth
(1929), Garey (1929), Hodges et al. (1930), Bonnen and
Elliot (1931), Brenner et al. (2002, 2001), Smith et al.
(2002).
DAY CENT was used to simulate the influence of
anthropogenic activity due to all of these activities, generating
the U. S. estimate of direct N2O emissions from mineral soils
producing major crop types. Because the model is sensitive
to actual interannual variability in weather patterns and other
controlling variables, emissions associated with individual
activities vary through time even if the management practices
remain the same (e.g., if N fertilization remains the same for
two years), rather than having a linear, monotonic response,
which would occur using the IPCC method. The ability of
DAY CENT to capture these interactions is largely the reason
for more accurate estimates of N2O emissions, compared to
the more simplistic IPCC Tier 1 approach.
Mineral N was subject to volatilization and leaching/
runoff according to the climatic conditions, soil type and
condition, crop type, and land management practices such
as cultivation and irrigation, as simulated by DAY CENT.
The resulting amounts were then applied in the calculation
of indirect emissions as described below (i.e., in the section
entitled Indirect N2O Emissions from Managed Soils of All
Land-Use Types).
Non-Major Crop Types on Mineral Cropland Soils
For mineral cropland soils producing non-major crop
types, the Tier 1 IPCC methodology was used to estimate
direct N2O emissions. Estimates of direct N2O emissions
from N applications to non-major crop types were based
on the annual increase in mineral soil N from the following
practices: (1) the application of synthetic commercial
fertilizers, (2) the production of N-fixing crops, and (3)
the retention of crop residues. No organic amendments
(i.e., manure N, other organic commercial fertilizers) were
considered here because they were assumed to be applied
to crops simulated by DAY CENT. This assumption is
reasonable because DAY CENT simulations included the
5 major cropping systems (corn, hay, sorghum, soybean,
wheat), which are the land management systems receiving
the vast majority (approximately 95 percent) of manure
applications to cropped land in the United States (Kellogg
et al. 2000, Edmonds et al. 2003), and manure accounts for
approximately 95 percent of total organic amendments.
Annual synthetic fertilizer N additions to non-major
crop types were calculated by process of elimination. For
each year, fertilizer amounts for each of the following were
summed: fertilizer applied to major crops (as simulated
by DAY CENT —approximately 75 percent of the U.S.
total), fertilizer applied to forest lands (less than 1 percent
of the U.S. total), and fertilizer applied in settlements
(approximately 10 percent of the U.S. total). The sum
was then subtracted from total fertilizer use in the United
States. This difference, approximately 15 percent of total
synthetic fertilizer N used in the United States, was assumed
to be applied to non-major crop types. Non-major crop
types include: (a) fruits, nuts, and vegetables, which were
estimated to receive approximately 5 percent of total U.S.
N fertilizer use (TFI 2000); and (b) other annual crops not
simulated by DAY CENT (barley, oats, tobacco, sugarcane,
sugar beets, sunflower, millet, peanuts, etc.), which account
for approximately 10 percent of total U.S. fertilizer use. The
non-volatilized portion was obtained by multiplying the
amount of fertilizer added to non-major crop types by the
default IPCC volatilization fraction (IPCC/UNEP/OECD/
IEA 1997, IPCC 2000). In addition to synthetic fertilizer
N, N in soils due to the cultivation of non-major N-fixing
crops (e.g., edible legumes) was included in these estimates.
Finally, crop residue N was derived from information on
crop production yields, residue management (retained vs.
burned or removed), mass ratios of aboveground residue
to crop product, dry matter fractions, and N contents
of the residues (IPCC/UNEP/OECD/IEA 1997). The
activity data for these practices were obtained from the
following sources:
6-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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• Annual production statistics for crops whose residues
are left on the field: USDA (1994a, 1998b, 2000c, 2001,
2002, 2003), Schueneman (1999,2001), Deren (2002),
Schueneman and Deren (2002), Cantens (2004), Lee
(2003, 2004).
• Mass ratios of aboveground residue to crop product,
dry matter fractions, and N contents for N-fixing crops:
Strehler and Stiitzle (1987), Barnard and Kristoferson
(1985), Karkosh (2000), Ketzis (1999), IPCC/UNEP/
OECD/IEA (1997).
• Aboveground residue to crop mass ratios, residue dry
matter fractions, and residue N contents of non-N
fixing crops: Strehler and Stiitzle (1987), Turn et al.
(1997), Ketzis (1999), Barnard and Kristoferson (1985),
Karkosh (2000).
The total increase in soil mineral N from applied
fertilizers, N-fixing crops, and crop residues was multiplied
by the IPCC default emission factor to derive an estimate of
cropland direct N2O emissions from non-major crop types.
Drainage and Cultivation of Organic Cropland Soils
The IPCC Tier 1 method was used to estimate direct
N2O emissions from the drainage and cultivation of organic
cropland soils. Estimates of the total U.S. acreage of
drained organic soils cultivated annually for temperate and
sub-tropical climate regions were obtained for 1982, 1992,
and 1997 from the Natural Resources Inventory (USDA
2000b, as extracted by Eve 2001 and amended by Ogle
2002), using temperature and precipitation data from Daly
et al. (1994, 1998). These areas were linearly interpolated
and extrapolated to estimate areas for the missing years. To
estimate annual emissions, the total temperate areas were
multiplied by the IPCC default emission factor for temperate
regions, and the total sub-tropical areas were multiplied
by the average of the IPCC default emission factors for
temperate and tropical regions.
Grassland Soils
As with N2O from croplands, the Tier 3 process-based
DAY CENT model and IPCC Tier 1 methods were combined
to estimate emissions from grasslands. Grasslands include
pastures and rangelands used for grass forage production,
where the primary use is livestock grazing. Rangelands
are typically extensive areas of native grasslands that are
not intensively managed, while pastures are often seeded
grasslands, possibly following tree removal, that may or
may not be improved with practices such as irrigation and
interseeding legumes.
DAY CENT was used to simulate N2O emissions
from grasslands at the county scale resulting from manure
deposited by livestock directly onto the pasture (i.e., Pasture/
Range/Paddock manure; which is simulated internally within
the model), N fixation from legume seeding, sewage sludge
amendments, managed manure amendments (i.e., manure
other than PRP manure), and synthetic fertilizer application.
The simulations used the same weather and soils data as
discussed under the section for Major Crop Types. Managed
manure N amendments to grasslands were estimated from
Edmonds et al. (2003) and adjusted for annual variation using
managed manure N production data according to methods
described under the Methodology Section for Major Crop
Types. Sewage sludge was assumed to be applied on grasslands
because of the heavy metal content and other pollutants in
human waste that limits its use as an amendment to croplands.
Sewage sludge was estimated from data compiled by EPA
(1993, 1997, 1999, 2003), Bastian (2002, 2003, 2005), and
Metcalf and Eddy (1991). DAYCENT generated per area
estimates of N2O emissions (g N2O-N nr2) from pasture and
rangelands, which were then scaled to the entire county by
multiplying the emissions estimate by reported pasture and
rangeland areas in the county; summing results across all
counties produced the national estimate. Grassland area data
were obtained from the National Resources Inventory (USDA
2000b). The 1997 NRI data for pastures and rangeland were
aggregated to the county level to estimate the grassland areas
for 1995 to 2004, and the 1992 NRI pasture and rangeland
data were aggregated to the county level to estimate areas
from 1990 to 1994.
Manure N additions from grazing animals are modeled
internally within the DAYCENT. Comparisons with estimates
of total manure deposited on PRP (see Annex 3.11) showed
that DAYCENT accounted for approximately 75 percent of
total PRP manure. It is reasonable that DAYCENT did not
account for all PRP manure because the NRI data do not
include all grassland areas, such as federal grasslands. N2O
emissions from the portion of PRP manure N not accounted
for by DAYCENT were estimated using the IPCC Tier 1
method with default emission factors (IPCC/UNEP/OECD/
IEA 1997). Fixed N additions from forage legumes are also
model outputs generated by DAYCENT. Comparisons with
Agriculture 6-23
-------
estimates of total N fixation by forage legumes showed
that DAY CENT accounted for approximately 52 percent
of total forage legume fixation. N2O emissions from the
portion of fixed legume N not accounted for by DAY CENT
were estimated using the IPCC Tier 1 method with default
emission factors (IPCC/UNEP/OECD/IEA 1997). Emission
estimates from DAY CENT and the IPCC method were
summed to provide total national emissions for grasslands
in the United States.
Total Direct N20 Emissions from Cropland and
Grassland Soils
Annual direct emissions from major and non-major crops
on mineral cropland soils, from drainage and cultivation of
organic cropland soils, and from grassland soils were summed
to obtain total direct N2O emissions from agricultural soil
management (see Table 6-13 and Table 6-14).
Indirect N20 Emissions from Managed Soils of all Land-Use
Types
This section describes methods for estimating indirect
soil N2O emissions from all land-use types (i.e., croplands,
grasslands, forest lands, and settlements). Indirect N2O
emissions occur when mineral N made available through
anthropogenic activity is transported from the soil either
in gaseous or aqueous forms and later converted into N2O.
There are two pathways leading to indirect emissions. The
first pathway results from volatilization of N as NOX and
NH3 following application of synthetic fertilizer or organic
amendments (e.g., manure, sewage sludge), or deposition
of PRP manure, or during storage, treatment, and transport
of managed manure. Through atmospheric deposition,
volatilized nitrogen can be returned to soils, and a portion
is emitted to the atmosphere as N2O. The second pathway
occurs via leaching and runoff of soil mineral N (primarily in
the form of nitrate [NO3 ]) that was made available through
anthropogenic activity. The nitrate is subject to denitrification
in water bodies, which leads to additional N2O emissions.
Regardless of the eventual location of the indirect N2O
emissions, the emissions are assigned to the original source of
the N for reporting purposes, which here includes agriculture,
forestry, and other land-use activities.
N Transport from Managed Soils
Similar to the direct emissions calculation, several
approaches were combined to estimate the amount of
applied N that was exported from application sites through
volatilization, and leaching and surface runoff. DAY CENT
was used to simulate the amount of N transported from
major cropland types and grasslands as NOX and NH3
through volatilization, and as NO3 in leachate and runoff.
N transport from non-major croplands, settlements, forest
lands, and grasslands not accounted for by DAY CENT (i.e.,
from land areas that were not simulated with DAY CENT)
were obtained by applying the IPCC default fractions for
volatilization and for leaching and runoff to total fertilizer
and manure N amounts applied or deposited on to these lands.
Manure N from managed systems assumed to be volatilized
during storage, treatment, and transport was also estimated
and included as a source of N for indirect emissions.
Indirect N20 Emissions from N Transport
The N transport from managed soils and from storage,
treatment, and transport of managed manure were summed
for both volatilization and leaching or surface runoff. The
IPCC default emission factors for indirect N2O were applied
to the respective total amounts of N for each pathway to
estimate emissions and then summed to obtain the total
indirect N2O emissions due to the use and management of
U.S. croplands, grasslands, forest lands, and settlements
(Table 6-16).
Uncertainty
Uncertainty was estimated differently for each of
the following three components of N2O emissions from
agricultural soil management: (1) Direct emissions
calculated by DAYCENT; (2) Direct emissions not calculated
by DAYCENT; and (3) Indirect emissions.
For direct emissions calculated using DAYCENT,
uncertainty was associated with the activity data, the model
inputs, and the structure of the model (i.e., underlying model
equations and parameterization). Uncertainties in activity
data were evaluated based on variation in weather patterns,
soil characteristics, and N application rates associated with
crop types, years, and agricultural regions. Total uncertainty
in N inputs was estimated to contribute 20 percent to the
uncertainty in N2O estimates (Mosier 2004); uncertainties
in weather patterns contributed 19 percent (Thornton et al.
2000), and variation in soil characteristics contributed an
additional 12 percent (Del Grosso 2005). Their combined
uncertainty is approximately 30.1 percent using the sum-
of-squares method. To estimate the uncertainty associated
with the model structure, an effective emission factor was
6-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
computed from DAY CENT outputs and compared with
N2O measurements from various cropped soils over the
annual cycle (Del Grosso et al. 2005). The uncertainty
associated with the effective emission factor was estimated
at 57 percent (Del Grosso 2005). Simple error propagation
led to an overall uncertainty for direct emissions of +64
percent. Direct N2O emissions not calculated by DAYCENT
were assumed to have similar uncertainties and assigned the
same value of +64 percent.
Indirect emissions from agricultural soil management,
which were calculated according to the default IPCC
methodology, were estimated to have an uncertainty of +286
percent (EPA 2004).
The results of the uncertainty analysis are summarized
in Table 6-17. Agricultural soil management N2O emissions
in 2004 were estimated to be between 47.1 and 475.9 Tg CO2
Eq. at a 95 percent confidence level. This indicates a range
of 82 percent above and below the 2004 emission estimate
of 261.6 TgCO2Eq.
Recalculations Discussion
Minor changes were made from previous reports,
including adjustments in activity data and the use of a revised
version of the DAYCENT model. The residue N fractions
for dry edible beans, dry edible peas, Austrian winter peas,
lentils, and wrinkled seed peas were revised to 0.0168.
The source of activity data for pasture and rangelands was
changed from NAS S, which only provides partial accounting
of pasture land area, to the National Resources Inventory,
which provides county-level estimates for both pasture and
rangelands for the entire country. This resulted in DAYCENT
accounting for a larger portion of total grassland than last
year. Also, a different soils database was used this year.
Last year, the VEMAP 0.5° resolution cell that contains the
geographic center of each county was identified, and the
dominant soil type was extracted and applied across the
county. This year, surface soil texture and depth from the
STATSGO soil map unit that intersected the geographical
center of the largest cluster of agricultural land in each county
was extracted and used for the simulations. Sewage sludge
was simulated as an application to croplands in the previous
year's inventory. However, croplands are less likely to be
amended with sewage sludge due to the heavy metal content
and other toxins associated with human waste. Therefore,
in the current inventory, sewage sludge amendments to
agricultural lands were simulated as an application to
grasslands. Regarding the model revision, DAYCENT was
modified to more realistically represent the grain filling
period for crops (anthesis), and different cultivars of corn
and soybean were simulated in various regions of the country
to better represent the life span of the plants, particularly the
days to maturity.
These changes, summarized in Table 6-18, resulted in
an increase in emissions estimates for all years, ranging from
an increase of 2 percent to 26 percent.
QA/QC and Verification
For quality control, DAYCENT results for N2O emissions
and NO3 leaching were compared with field data representing
various cropped/grazed systems, soils types, and climate
patterns. N2O measurement data were available for seven
sites in the United States and one in Canada, representing 25
different combinations of fertilizer treatments and cultivation
practices. NO3 leaching data were available for three sites in
the United States representing nine different combinations
fertilizer amendments. Linear regressions of simulated vs.
observed emission and leaching data yielded correlation
coefficients of 0.74 and 0.96 for annual N2O emissions and
NO3 leaching, respectively.
Spreadsheets containing input data required for
DAYCENT simulations of major croplands and grasslands
and unit conversion factors were checked and no errors were
found. Spreadsheets containing input data and emission
factors required for the Tier 1 approach used for non-major
Table 6-17: Tier 1 Quantitative Uncertainty Estimates of N20 Emissions from Agricultural Soil Management in 2004
(Tg C02 Eq. and Percent)
2004 Emission Uncertainty Range Relative to Emission Estimate
Estimate
Source Gas (Tg C02 Eq.) Uncertainty (%) (Tg C02 Eq.)
Lower Bound
Agricultural Soil Management N20 261.5 82% 47.1
Upper Bound
475.9
Agriculture 6-25
-------
Table 6-18: Changes and Percent Difference in N20
Emission Estimates for Agricultural Soil Management
(Tg C02 Eq. and Percent)
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
1990-2003
Inventory
253.0
247.6
233.2
247.6
238.3
244.7
267.3
252.0
267.7
243.4
263.9
257.1
252.6
253.5
1990-2004
Inventory
266.1
278.5
252.5
312.7
261.5
308.1
314.4
276.6
301.1
281.2
278.2
282.9
277.8
259.2
Percent
Difference
5.2
12.5
8.3
26.3
9.7
25.9
17.6
9.7
12.5
15.5
5.4
10.0
10.0
2.2
crops and grasslands not simulated by DAY CENT were
checked and no errors were found. However, assumptions on
the application of sewage sludge were questioned during the
review process. A corrective action was taken to apply sewage
sludge to grasslands in the simulations, rather than croplands,
which are unlikely to receive sewage sludge due its high
metal content and other toxins. Total emissions and emissions
from the different categories were compared with inventories
from previous years and differences were consistent with the
methodological differences (see Recalculations section for
further discussion).
Planned Improvements
Four major improvements are planned for the soil N2O
inventory. The first improvement will be to incorporate land
survey data from the National Resources Inventory (NRI)
(USDA 2000b) into the DAY CENT simulation analysis,
beyond the area estimates for rangeland and pasture which
are currently used to estimate emissions from grasslands.
NRI has a record of land-use activities since 1982 for all
U.S. agricultural land, which is estimated at about 386 Mha.
NASS is used as the basis for land-use records in the current
inventory; the major disadvantage to this land survey is that
most crops are grown in rotation, and NASS data provide
no information regarding rotation histories. In contrast, NRI
is designed to track rotation histories, and this is important
because emissions from any particular year can be influenced
Box 6-1. Tier 1 vs. Tier 3 Approach for Estimating N20 Emissions
The IPCC methodology used here is an example of a Tier 1 approach (IPCC/UNEP/OECD/IEA1997), in which activity data from different
N sources (e.g., synthetic fertilizer, manure, N fixation, etc.) are multiplied by the appropriate default IPCC emission factors to estimate N20
emissions on a source by source basis. The Tier 3 approach used here utilizes a process-based model (i.e., DAYCENT) and is based on
the environmental conditions at a specific location in addition to the N inputs. Consequently, it is necessary to not only know the amount of
N inputs but the conditions under which the anthropogenic activity is increasing mineral N in a soil profile. The Tier 1 approach requires a
minimal amount of activity data that is generally readily available in most countries (total N applied to crops), calculations are simple, and the
methodology is highly transparent. In contrast, the Tier 3 approach requires more refined activity data (e.g., crop specific N amendment rates,
daily climate, soil class, etc.), considerable computational resources and programming expertise, and the methodology is less transparent.
The advantage of the Tier 3 approach is that the accuracy of estimates is expected to be greater using the advanced model, which accounts
for land-use and management impacts and their interaction with environmental factors (i.e., weather patterns and soil characteristics).
Emissions due to anthropogenic activity may be enhanced or dampened, depending on the specific environmental conditions. Another
important difference between the Tier 1 and Tier 3 approaches relates to assumptions regarding N cycling. Tier 1 assumes that N added to
a system is subject to N20 emissions only during that year; e.g., N added as fertilizer or through fixation contributes to N20 emission for that
year, but cannot be stored in soils and contribute to N20 emission in subsequent years. In contrast, the process-based model used in the Tier
3 approach includes such legacy effects when N is mineralized from soil organic matter and emitted as N20 during subsequent years. The
Tier 1 approach also assumes that only N from fertilizer and organic matter additions contributes to indirect N20 emissions whereas the Tier
3 approach assumes that once N is in the plant/soil system, including residue N and soil organic matter, it can be cycled and lost through the
two indirect pathways which contribute to N20 emissions. Overall, the Tier 3 approach in this analysis (DAYCENT) estimates higher indirect
emissions and lower direct emissions than IPCC methodology, particularly for N-fixing crops. This was primarily because of greater losses
through volatilization and through leaching and surface runoff than was estimated using the IPCC Tier 1 methodology. For example, in 2004
direct soil N20 emissions from agricultural sources were 225 vs. 171 Tg C02 Eq. for IPCC and DAYCENT/IPCC methodologies while indirect
emissions from all sources were 80 and 91 Tg C02 Eq. for IPCC and DAYCENT/IPCC.
6-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
by the crop that was grown the previous year. Moreover,
the current inventory based on NASS does not quantify the
influence of land-use change on emissions, which can be
addressed using the NRI survey records. NRI also provides
additional information on pasture land management that
can be incorporated into the analysis (particularly the use of
irrigation). Using NRI data will also make the N2O inventory
methods more consistent with those used to estimate net C
fluxes for agricultural soils.
The second planned improvement will be to achieve
consistency in N fertilization rates and organic amendments
between the soil C and soil N2O inventories. Currently, each
inventory is using a combination of shared and different
sources to model these activities. As part of this activity,
manure amendments will be more realistically distributed
among major crops, non-major crop types, and grasslands,
according to methods used in the soil C inventory (see Annex
3.13). The goal will be to ensure that each is using the most
accurate information in a consistent manner.
The third planned improvement is to develop a more
rigorous uncertainty analysis. The current analysis is
incomplete because there are additional uncertainties in
activity data that were not addressed, such as N input
rates, variation in county level weather patterns, and soil
characteristics. For example, a single soil and climate type
were used in the simulations for each county, but there
can be considerable heterogeneity in these environmental
variables. Consequently, there is inherent uncertainty in
the current emission estimates which is not addressed. A
Monte Carlo approach will be used to capture uncertainty
in soil and weather input data at the county scale, as well
as further elaboration of uncertainties from N inputs due to
fertilization and organic amendments. The analysis will also
address uncertainties in other key soil management practices
such as irrigation and tillage histories. Uncertainties in the
DAY CENT model structure will be further evaluated to
address bias, which is not included in the effective emission
factor analysis. Also, a more rigorous methodology will be
developed for the IPCC Tier 1 calculations.
The fourth planned improvement deals with emissions
from native rangelands. Emissions from unimproved
rangelands with low to moderate grazing intensities are
not much higher than emissions under native conditions.
Subtracting the native land emissions is likely to underestimate
the anthropogenic influence on emissions rates from
rangelands, which are controlled by livestock grazing
regimes. Therefore, future inventories will be modified
to avoid subtracting native grassland emissions from
simulations of livestock grazing in rangelands.
6.5. Field Burning of Agricultural
Residues (IPCC Source Category 4F)
Large quantities of agricultural crop residues are
produced by farming activities. A variety of ways exist to
utilize or dispose of these residues. For example, agricultural
residues can be left on or plowed back into the field,
composted and then applied to soils, landfilled, or burned
in the field. Alternatively, they can be collected and used as
fuel, animal bedding material, supplemental animal feed, or
construction material. Field burning of crop residues is not
considered a net source of CO2, because the carbon released
to the atmosphere as CO2 during burning is assumed to be
reabsorbed during the next growing season. Crop residue
burning is, however, a net source of CH4, N2O, CO, and NOX,
which are released during combustion.
Field burning is not a common method of agricultural
residue disposal in the United States. The primary crop types
whose residues are typically burned in the United States are
wheat, rice, sugarcane, corn, barley, soybeans, and peanuts.
Of these residues, less than 5 percent is burned each year,
except for rice.8 Annual emissions from this source over the
period 1990 through 2004 have remained relatively constant,
averaging approximately 0.7 Tg CO2 Eq. (36 Gg) of CH4,
0.4 Tg CO2 Eq. (1 Gg) of N20,746 Gg of CO, and 32 Gg of
NOX (see Table 6-19 and Table 6-20).
Methodology
The methodology for estimating greenhouse gas
emissions from field burning of agricultural residues is
consistent with the Revised 1996 IPCC Guidelines (IPCC/
UNEP/OECD/IEA 1997).9 In order to estimate the amounts
8 The fraction of rice straw burned each year is significantly higher than that for other crops (see "Methodology" discussion below).
9 The IPCC Good Practice Guidance (IPCC 2000) provided no updates to the methodology for estimating field burning of agricultural residues.
Agriculture 6-27
-------
Table 6-19: CH4 and N20 Emissions from Field Burning of Agricultural Residues (Tg C02 Eq.)
Gas/Crop Type
CH4
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
N20
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
Total
1990
0.7
0.1
0.1
+
0.3
+
0.1
+
0.4
+
+
+
0.1
+
0.2
+
1.1
1998
0.8
0.1
0.1
+
0.3
+
0.2
+
0.5
+
+
+
0.1
+
0.3
+
1.2
1999
0.8
0.1
0.1
+
0.3
+
0.2
+
0.4
+
+
+
0.1
+
0.3
+
1.2
2000
0.8
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
+
0.1
+
0.3
+
1.2
2001
0.8
0.1
0.1
+
0.3
+
0.2
+
0.5
+
+
+
0.1
+
0.3
+
1.2
2002
0.7
0.1
0.1
+
0.3
+
0.2
+
0.4
+
+
+
0.1
+
0.3
+
1.1
2003
0.8
0.1
0.1
+
0.4
+
0.2
+
0.4
+
+
+
0.1
+
0.2
+
1.2
2004
0.9
0.1
0.1
+
0.4
+
0.2
+
0.5
+
+
+
0.1
+
0.3
+
1.4
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
of carbon and nitrogen released during burning, the following
equations were used:10
Carbon Released = (Annual Crop Production) x
(Residue/Crop Product Ratio) x
(Fraction of Residues Burned in situ) x
(Dry Matter Content of the Residue) x
(Burning Efficiency) x (Carbon Content of the Residue) x
(Combustion Efficiency)11
Nitrogen Released = (Annual Crop Production) x
(Residue/Crop Product Ratio) x
(Fraction of Residues Burned in situ) x
(Dry Matter Content of the Residue) x
(Burning Efficiency) x
(Nitrogen Content of the Residue) x
(Combustion Efficiency)
Emissions of CH4 and CO were calculated by multiplying
the amount of carbon released by the appropriate IPCC
default emission ratio (i.e., CH4-C/C or CO-C/C). Similarly,
N2O and NOX emissions were calculated by multiplying the
amount of nitrogen released by the appropriate IPCC default
emission ratio (i.e., N2O-N/N or NOX-N/N).
The crop residues that are burned in the United States
were determined from various state-level greenhouse gas
emission inventories (ILENR 1993, Oregon Department of
Energy 1995, Wisconsin Department of Natural Resources
1993) and publications on agricultural burning in the United
States (Jenkins et al. 1992, Turn et al. 1997, EPA 1992).
Crop production data for all crops except rice in
Florida and Oklahoma were taken from the USDA's Field
Crops, Final Estimates 1987-1992, 1992-1997, 1997-2002
(USDA 1994, 1998, 2003), and Crop Production 2004
Summary (USDA 2005). Rice production data for Florida
and Oklahoma, which are not collected by USDA, were
estimated by applying average primary and ratoon crop
yields for Florida (Schueneman and Deren 2002) to Florida
acreages (Schueneman 1999b, 2001; Deren 2002; Kirstein
2003, 2004; Cantens 2004, 2005) and for Arkansas (USDA
1994,1998,2003,2005) to Oklahoma acreages12 (Lee 2003,
10 Note: As is explained later in this section, the fraction of rice residues burned varies among states, so these equations were applied at the state level for
rice. These equations were applied at the national level for all other crop types.
11 Burning Efficiency is defined as the fraction of dry biomass exposed to burning that actually burns. Combustion Efficiency is defined as the fraction of
carbon in the fire that is oxidized completely to CO2. In the methodology recommended by the IPCC, the "burning efficiency" is assumed to be contained
in the "fraction of residues burned" factor. However, the number used here to estimate the "fraction of residues burned" does not account for the fraction
of exposed residue that does not burn. Therefore, a "burning efficiency factor" was added to the calculations.
12 Rice production yield data are not available for Oklahoma so the Arkansas values are used as a proxy.
6-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 6-20: CH4, N20, CO, and NO, Emissions from Field Burning of Agricultural Residues (Gg)
Gas/Crop Type
CH4
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
N20
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
CO
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
NO,
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
1990
33
7
4
1
13
1
7
+
1
+
+
+
+
+
1
+
689
137
86
18
282
16
148
2
28
4
3
+
7
1
14
+
1998
38
6
3
1
17
1
10
+
1
+
+
+
+
+
1
+
789
128
65
23
347
13
211
2
35
3
2
+
8
+
20
+
1999
37
5
4
1
16
+
10
+
1
+
+
+
+
+
1
+
767
115
77
23
336
10
204
2
34
3
3
+
8
+
19
+
2000
38
5
4
1
17
1
10
+
1
+
+
+
+
+
1
+
790
112
76
24
353
12
212
2
35
3
3
+
8
+
20
+
2001
37
5
4
1
16
+
11
+
1
+
+
+
+
+
1
+
770
98
77
23
338
9
222
3
35
3
3
+
8
+
21
+
2002
34
4
3
1
15
+
10
+
1
+
+
+
+
+
1
+
706
80
61
23
319
8
212
2
33
2
2
+
8
+
20
+
2003
38
6
5
1
17
+
9
+
1
+
+
+
+
+
1
+
796
117
96
22
359
10
189
3
34
3
3
+
9
+
18
+
2004
42
5
4
1
20
+
12
+
2
+
+
+
+
+
1
+
877
108
75
19
420
10
242
3
39
3
3
+
10
+
23
+
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
2004, 2005). The production data for the crop types whose
residues are burned are presented in Table 6-21.
The percentage of crop residue burned was assumed
to be 3 percent for all crops in all years, except rice, based
on state inventory data (ILENR 1993, Oregon Department
of Energy 1995, Noller 1996, Wisconsin Department of
Natural Resources 1993, and Cibrowski 1996). Estimates
of the percentage of rice residue burned were derived from
state-level estimates of the percentage of rice area burned
each year, which were multiplied by state-level, annual rice
production statistics. The annual percentages of rice area
burned in each state were obtained from the agricultural
extension agents in each state and reports of the California
Air Resources Board (Bollich 2000; California Air
Resources Board 1999, 2001; Cantens 2005; Deren 2002;
Fife 1999; Guethle 1999, 2000, 2001, 2002, 2003, 2004,
2005; Klosterboer 1999a, 1999b, 2000, 2001, 2002, 2003;
Lee 2005; Lindberg 2002, 2003, 2004, 2005; Linscombe
1999a, 1999b, 2001, 2002,2003, 2004, 2005; Najita 2000,
2001; Schueneman 1999a, 1999b, 2001; Stansel 2004,
2005; Street 2001,2002,2003; Walker 2004,2005; Wilson
2003, 2004, 2005) (see Table 6-22 and Table 6-23). The
estimates provided for Florida remained constant over the
entire 1990 through 2004 period, while the estimates for all
other states varied over the time series. For California, the
annual percentages of rice area burned in the Sacramento
Valley are assumed to be representative of burning in the
entire state, because the Sacramento Valley accounts for
over 95 percent of the rice acreage in California (Fife 1999).
These values declined between 1990 and 2004 because of a
legislated reduction in rice straw burning (Lindberg 2002)
(see Table 6-23).
Agriculture 6-29
-------
Table 6-21: Agricultural Crop Production (Gg of Product)
Crop
Wheat
Rice
Sugarcane
Corn*
Barley
Soybeans
Peanuts
1990
74,
7,
25,
201
9,
52,
1,
,292
,113
,525
,534
,192
,416
,635
1998
69
8,
31
247,
7,
74,
1,
,327
,414
,486
,882
,655
,598
,798
1999
62,
9,
32,
239
5,
72,
1,
,475
,392
,023
,549
,922
,223
,737
2000
60,641
8,705
32,762
251,854
6,919
75,055
1,481
2001
53,001
9,794
31,377
241,377
5,407
78,671
1,940
2002
43,705
9,602
32,253
227,767
4,940
75,010
1,506
2003
63,814
9,084
30,715
256,278
6,059
66,778
1,880
2004
58,738
10,495
26,576
299,917
6,080
85,484
1,933
*Corn for grain (i.e., excludes corn for silage).
Table 6-22: Percentage of Rice Area Burned by State
State
Arkansas
California
Florida"
Louisiana
Mississippi
Missouri
Oklahoma
Texas
1990-1998
13%
Variable3
0%
6%
10%
5%
90%
1%
1999
13%
27%
0%
0%
40%
5%
90%
2%
2000
13%
27%
0%
5%
40%
8%
90%
0%
2001
13%
23%
0%
4%
40%
5%
90%
0%
2002
16%
13%
0%
3%
8%
5%
90%
0%
2003
22%
14%
0%
3%
65%
4%
100%
0%
2004
17%
11%
0%
3%
28%
4%
88%
0%
aValues provided in Table 6-23.
b Although rice is cultivated in Florida, crop residue burning is illegal. Therefore, emissions remain 0 throughout the time series.
All residue/crop product mass ratios except sugar-
cane were obtained from Strehler and Stiitzle (1987).
The datum for sugarcane is from University of California
(1977). Residue dry matter contents for all crops except
soybeans and peanuts were obtained from Turn et al.
(1997). Soybean dry matter content was obtained from
Strehler and Stiitzle (1987). Peanut dry matter content was
obtained through personal communications with Jen Ketzis
(1999), who accessed Cornell University's Department of
Animal Science's computer model, Cornell Net Carbohydrate
and Protein System. The residue carbon contents and
nitrogen contents for all crops except soybeans and peanuts
Table 6-23: Percentage of Rice Area Burned in
California, 1990-1998
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
Percentage
75%
75%
66%
60%
69%
59%
63%
34%
35%
are from Turn et al. (1997). The residue carbon content
for soybeans and peanuts is the IPCC default (IPCC/
UNEP/OECD/IEA1997). The nitrogen content of soybeans
is from Barnard and Kristoferson (1985). The nitrogen
content of peanuts is from Ketzis (1999). These data are
listed in Table 6-24. The burning efficiency was assumed to
be 93 percent, and the combustion efficiency was assumed
to be 88 percent, for all crop types (EPA 1994). Emission
ratios for all gases (see Table 6-25) were taken from
the Revised 1996 IPCC Guidelines (IPCC/UNEP/OECD/
IEA 1997).
Uncertainty
A significant source of uncertainty in the calculation
of non-CO2 emissions from field burning of agricultural
residues is in the estimates of the fraction of residue of each
crop type burned each year. Data on the fraction burned, as
well as the gross amount of residue burned each year, are
not collected at either the national or state level. In addition,
burning practices are highly variable among crops, as well
as among states. The fractions of residue burned used in
these calculations were based upon information collected by
state agencies and in published literature. Based on expert
judgment, uncertainty in the fraction of crop residue burned
6-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 6-24: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues
_ Residue/Crop
Crop Ratio
Wheat
Rice
Sugarcane
Corn
Barley
Soybeans
Peanuts
1.3
1.4
0.8
1.0
1.2
2.1
1.0
Fraction of
Residue Burned
0.03
Variable
0.03
0.03
0.03
0.03
0.03
Dry Matter
Fraction
0.93
0.91
0.62
0.91
0.93
0.87
0.86
Carbon Fraction
0.4428
0.3806
0.4235
0.4478
0.4485
0.4500
0.4500
Nitrogen
Fraction
0.0062
0.0072
0.0040
0.0058
0.0077
0.0230
0.0106
Burning
Efficiency
0.93
0.93
0.93
0.93
0.93
0.93
0.93
Combustion
Efficiency
0.88
0.88
0.88
0.88
0.88
0.88
0.88
Table 6-25: Greenhouse Gas Emission Ratios
Gas
Emission Ratio
CH/
CO
0.005
0.060
0.007
0.121
a Mass of carbon compound released (units of C) relative to mass of
total carbon released from burning (units of C).
b Mass of nitrogen compound released (units of N) relative to mass of
total nitrogen released from burning (units of N).
ranged from zero to 100 percent, depending on the state and
crop type.
Based on expert judgment, the uncertainty in production
for all crops considered here is estimated to be 5 percent.
Residue/crop product ratios can vary among cultivars. For all
crops except sugarcane, generic residue/crop product ratios,
rather than ratios specific to the United States, have been
used. An uncertainty of 10 percent was applied to the residue/
crop product ratios for all crops. Based on the range given
for measurements of soybean dry matter fraction (Strehler
and Stiitzle 1987), residue dry matter contents were assigned
an uncertainty of 3.1 percent for all crop types. Burning and
combustion efficiencies were assigned an uncertainty of 5
percent based on expert judgment.
The N2O emission ratio was estimated to have an
uncertainty of 28.6 percent based on the range reported in
IPCC/UNEP/OECD/IEA (1997). The uncertainty estimated
for the CH4 emission ratio was 40 percent based on the range
of ratios reported in IPCC/UNEP/OECD/IEA (1997).
The results of the Tier 2 Monte Carlo uncertainty
analysis are summarized in Table 6-26. CH4 emissions
from field burning of agricultural residues in 2004 were
estimated to be between 0.2 and 1.7 Tg CO2 Eq. at a 95
percent confidence level. This indicates a range of 75 percent
below and 96 percent above the 2004 emission estimate of
0.9 Tg CO2 Eq. Also at the 95 percent confidence level, N2O
emissions were estimated to between 0.1 and 1.0TgCO2 Eq.
(or approximately 73 percent below and 85 percent above
the 2004 emission estimate of 0.5 Tg CO2 Eq.).
QA/QC and Verification
A source-specific QA/QC plan for field burning of
agricultural residues was 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 crops to attempt
to identify any outliers or inconsistencies. No problems
were found. In addition, this year, calculation spreadsheets
Table 6-26: Tier 2 Uncertainty Estimates for CH4 and N20 Emissions from Field Burning of Agricultural Residues
(Tg C02 Eq. and Percent)
2004 Emission
Estimate
Source Gas (Tg C02 Eq.)
Field Burning of Agricultural Residues CH4 0.9
Field Burning of Agricultural Residues N20 0.5
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound
0.2 1.7 -75%
0.1 1.0 -73%
Upper Bound
+ 96%
+ 85%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Agriculture 6-31
-------
were linked directly to source data spreadsheets to minimize
transcription errors, and a central, cross-cutting agricultural
data spreadsheet was created to prevent use of incorrect or
outdated data.
Recalculations Discussion
The crop production data for 1997 through 2001 and
for 2002 and 2003 were updated using USDA (2003) and
USDA (2005), respectively. Data on the rice area harvested
in 2000 in Oklahoma was previously unavailable so the area
was assumed to be zero last year; this was revised this year
based on new information (Lee 2005). Oklahoma rice data
on yields and percentage of harvested area burned were also
previously unavailable. Last year, the average rice yield for
Florida was used as a proxy. This year it was determined
that the average rice yield for Arkansas would be a more
appropriate proxy, due to similar geography (Lee 2005).
The IPCC default of three percent burned (used last year
for Oklahoma) was revised to 90 percent this year because
90 percent is an appropriate assumption when data are not
available (Lee 2005).
These changes resulted in a change in emissions
estimates estimates for CH4 and N2O for all years except
1992. From 1990 to 1997, emission estimates for both CH4
and N2O increased by less than 0.05 percent. From 1998 to
2001, emission estimates increased or decreased by less than
0.1 percent. From 2002 to 2003, emission estimates increased
or decreased by less than 1 percent.
Planned Improvements
Preliminary research on agricultural burning in the
United States indicates that residues from several additional
crop types (e.g., grass for seed, blueberries, and fruit and nut
trees) are burned. Whether sufficient information exists for
inclusion of these additional crop types in future inventories
is being investigated.
6-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
7. Land Use, Land-Use Change,
and Forestry
This chapter provides an assessment of the net greenhouse gas flux1 resulting from the uses and changes in land
types and forests in the United States. IPCC Good Practice Guidance for Land Use, Land-Use Change, and
Forestry (IPCC 2003) recommends reporting fluxes according to changes within and conversions between
certain land-use types, termed forest land, cropland, grassland, and settlements (as well as wetlands). Datasets available
for the United States allow greenhouse gas flux to be estimated for the following subset of the categories defined by IPCC
(2003): (1) Forest Land Remaining Forest Land; (2) Cropland Remaining Cropland; (3) Land Converted to Cropland,
(4) Grassland Remaining Grassland, (5) Land Converted to Grassland, and (6) Settlements Remaining Settlements. In
addition, fluxes from some categories are reported under other categories because U.S. data are insufficient for separating
these fluxes.
The greenhouse gas flux from Forest Land Remaining Forest Land is reported using estimates of changes in forest
carbon stocks and the application of synthetic fertilizers to forest soils. The greenhouse gas flux from agricultural lands
(i.e., cropland and grassland) includes changes in organic carbon stocks in mineral and organic soils due to land use
and management, and emissions of C02 due to the application of crushed limestone and dolomite to managed land
(i.e., soil liming). Fluxes are reported for four 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 landfilled yard trimmings and food scraps, urban trees, and soil
fertilization.
Unlike the assessments in other sectors, which are based on annual activity data, the flux estimates in this chapter, with
the exception of CO2 fluxes from wood products, urban trees, and liming, and N20 emissions from forest and settlement
soils, 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 carbon 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. The forest carbon stocks
are based on state surveys, so the estimated CO2 fluxes at the national level differ from year to year. Agricultural mineral
and organic soil carbon flux calculations are based primarily on national surveys, so these results are largely constant
over multi-year intervals, with large discontinuities between intervals. For the landfilled yard trimmings and food scraps
source, periodic solid waste survey data were interpolated so that annual storage estimates could be derived. In addition,
because the most recent national forest, land-use, and municipal solid waste surveys were completed prior to 2004, the
estimates of C02 flux from forests, agricultural soils, and landfilled yard trimmings and food scraps are based in part on
extrapolation. Carbon dioxide flux from urban trees is based on neither annual data nor periodic survey data, but instead
1 The term "flux " is used here to encompass both emissions of greenhouse gases to the atmosphere, and removal of carbon from the atmosphere. Removal
of carbon from the atmosphere is also referred to as "carbon sequestration."
Land Use, Land-Use Change, and Forestry 7-1
-------
Table 7-1: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Land-Use Category
Forest Land Remaining Forest Land
Changes in Forest Carbon Stocks3
Cropland Remaining Cropland
Changes in Agricultural Soil Carbon
and Liming Emissions"
Land Converted to Cropland
Changes in Agricultural Soil Carbon
Grassland Remaining Grassland
Changes in Agricultural Soil Carbon
Land Converted to Grassland
Changes in Agricultural Soil Carbon
Settlements Remaining Settlements'
Urban Trees
Landfilled Yard Trimmings and Food
Total
Stocks
Stocksc
Stocks11
Stocks6
Scraps
1990
(773.4)
(773.4)
(33.1)
(33.1)
1.5
1.5
(4.5)
(4.5)
(17.6)
(17.6)
(83.2)
(58.7)
(24.5)
(910.4)
1998
(618.8)
(618.8)
(24.6)
(24.6)
(2.8)
(2.8)
7.5
7.5
(21.1)
(21.1)
(84.2)
(73.3)
(10.9)
(744.0)
1999
(637.9)
(637.9)
(24.6)
(24.6)
(2.8)
(2.8)
7.5
7.5
(21.1)
(21.1)
(86.8)
(77.0)
(9.8)
(765.7)
2000
(631.0)
(631.0)
(26.1)
(26.1)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(85.9)
(77.0)
(8.9)
(759.5)
2001
(634.0)
(634.0)
(27.8)
(27.8)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(89.7)
(80.7)
(9.0)
(768.0)
2002
(634.6)
(634.6)
(27.5)
(27.5)
(2.8)
(2.8)
7.4
7.4
(21.1)
(21.1)
(89.9)
(80.7)
(9.3)
(768.6)
2003
(635.8)
(635.8)
(28.7)
(28.7)
(2.8)
(2.8)
7.3
7.3
(21.1)
(21.1)
(93.8)
(84.3)
(9.4)
(774.8)
2004
(637.2)
(637.2)
(28.9)
(28.9)
(2.8)
(2.8)
7.3
7.3
(21.1)
(21.1)
(97.3)
(88.0)
(9.3)
(780.1)
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
a Estimates include carbon stock changes on both Forest Land Remaining Forest Land, and Land Converted to Forest Land.
b Estimates include carbon stock changes in mineral soils and organic soils on Cropland Remaining Cropland, carbon stock changes in organic soils on
Land Converted to Cropland, and liming emissions from all managed land.
c Estimates includes carbon stock changes in mineral soils only; organic soil carbon stock changes and liming emissions for this land use/land-use
change category are reported under Cropland Remaining Cropland.
d Estimates include carbon stock changes in mineral soils and organic soils on Grassland Remaining Grassland, and carbon stock changes in organic
soils on Land Converted to Grassland. Liming emissions for this land use/land-use change category are reported under Cropland Remaining Cropland.
e Estimates include carbon stock changes in mineral soils only; organic soil carbon stock changes and liming emissions for this land use/land-use
change category are reported under Grassland Remaining Grassland and Cropland Remaining Cropland, respectively.
f Estimates include carbon stock changes on both Settlements Remaining Settlements, and Land Converted to Settlements. Liming emissions for this
land use/land-use change category are reported under Cropland Remaining Cropland.
on data collected over the period 1990 through 1999. This
flux has been applied to the entire time series, and periodic
U.S. census data on changes in urban area have been used
to develop annual estimates of C02 flux.
Land use, land-use change, and forestry activities in
2004 resulted in a net carbon sequestration of 780.1 Tg CO2
Eq. (212.8 Tg C) (Table 7-1 and Table 7-2). This represents
an offset of approximately 13 percent of total U.S. CO2
emissions. Total land use, land-use change, and forestry net
carbon sequestration declined by approximately 14 percent
between 1990 and 2004. This decline was primarily due to
a decline in the rate of net carbon accumulation in forest
carbon stocks. Net carbon accumulation in landfilled yard
trimmings and food scraps, cropland, and grassland also
slowed over this period. Net carbon accumulation in urban
trees increased.
The application of synthetic fertilizers to forest and
settlement soils in 2004 resulted in direct N20 emissions of
6.8 Tg CO2 Eq. (22 Gg) (Table 7-3 and Table 7-4). Direct
N2O emissions from fertilizer application increased by
approximately 20 percent between 1990 and 2004.
7.1. Forest Land Remaining Forest
Land
Changes in Forest Carbon Stocks
(IPCC Source Category 5A1)
For estimating carbon (C) stocks or stock change (flux),
C in forest ecosystems can be divided into the following five
storage pools (IPCC 2003):
• Aboveground biomass, which includes all living
biomass above the soil including stem, stump,
branches, bark, seeds, and foliage. This category
includes live understory.
• Belowground biomass, which includes all living
biomass of coarse living roots greater than 2 mm
diameter.
• Dead wood, which includes all non-living woody
biomass either standing, lying on the ground (but not
including litter), or in the soil.
7-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 7-2: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C)
Land-Use Category
Forest Land Remaining Forest Land
Changes in Forest Carbon Stocks3
Cropland Remaining Cropland
Changes in Agricultural Soil Carbon
and Liming Emissions"
Land Converted to Cropland
Changes in Agricultural Soil Carbon
Grassland Remaining Grassland
Changes in Agricultural Soil Carbon
Land Converted to Grassland
Changes in Agricultural Soil Carbon
Settlements Remaining Settlements'
Urban Trees
Landfilled Yard Trimmings and Food
Total
Stocks
Stocksc
Stocks11
Stocks6
Scraps
1990
(210.9)
(210.9)
(9.0)
(9.0)
0.4
0.4
(1.2)
(1.2)
(4.8)
(4.8)
(22.7)
(16.0)
(6.7)
(248.3)
1998
(168.8)
(168.8)
(6.7)
(6.7)
(0.8)
(0.8)
2.1
2.1
(5.8)
(5.8)
(23.0)
(20.0)
(3.0)
(202.9)
1999
(174.0)
(174.0)
(6.7)
(6.7)
(0.8)
(0.8)
2.0
2.0
(5.8)
(5.8)
(23.7)
(21.0)
(2.7)
(208.8)
2000
(172.1)
(172.1)
(7.1)
(7.1)
(0.8)
(0.8)
2.0
2.0
(5.8)
(5.8)
(23.4)
(21.0)
(2.4)
(207.1)
2001
(172.9)
(172.9)
(7.6)
(7.6)
(0.8)
(0.8)
2.0
2.0
(5.8)
(5.8)
(24.5)
(22.0)
(2.5)
(209.5)
2002
(173.1)
(173.1)
(7.5)
(7.5)
(0.8)
(0.8)
2.0
2.0
(5.8)
(5.8)
(24.5)
(22.0)
(2.5)
(209.6)
2003
(173.4)
(173.4)
(7.8)
(7.8)
(0.8)
(0.8)
2.0
2.0
(5.8)
(5.8)
(25.6)
(23.0)
(2.6)
(211.3)
2004
(173.8)
(173.8)
(7.9)
(7.9)
(0.8)
(0.8)
2.0
2.0
(5.8)
(5.8)
(26.5)
(24.0)
(2.5)
(212.8)
Note: 1 Tg C = 1 teragram carbon = 1 million metric tons carbon. Parentheses indicate net sequestration. Totals may not sum due to independent
rounding.
a Estimates include carbon stock changes on both Forest Land Remaining Forest Land, and Land Converted to Forest Land.
b Estimates include carbon stock changes in mineral soils and organic soils on Cropland Remaining Cropland, carbon stock changes in organic soils on
Land Converted to Cropland, and liming emissions from all managed land.
c Estimates includes carbon stock changes in mineral soils only; organic soil carbon stock changes and liming emissions for this land use/land-use
change category are reported under Cropland Remaining Cropland.
11 Estimates include carbon stock changes in mineral soils and organic soils on Grassland Remaining Grassland, and carbon stock changes in organic
soils on Land Converted to Grassland. Liming emissions for this land use/land-use change category are reported under Cropland Remaining Cropland.
e Estimates include carbon stock changes in mineral soils only; organic soil carbon stock changes and liming emissions for this land use/land-use
change category are reported under Grassland Remaining Grassland and Cropland Remaining Cropland, respectively.
f Estimates include carbon stock changes on both Settlements Remaining Settlements, and Land Converted to Settlements. Liming emissions for this
land use/land-use change category are reported under Cropland Remaining Cropland.
Table 7-3: N20 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Land-Use Category
Forest Land Remaining Forest Land
N20 Emissions from Soils3
Settlements Remaining Settlements
N20 Emissions from Soils"
Total
1990
0.1
0.1
5.6
5.6
5.7
1998
0.4
0.4
6.2
6.2
6.5
1999
0.5
0.5
6.2
6.2
6.7
2000
0.4
0.4
6.0
6.0
6.4
2001
0.4
0.4
5.8
5.8
6.2
2002
0.4
0.4
6.0
6.0
6.4
2003
0.4
0.4
6.2
6.2
6.6
2004
0.4
0.4
6.4
6.4
6.8
Note: These estimates include direct emissions only. Indirect N20 emissions are reported in section 6.4 of 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.
• Litter, which includes the litter, fumic, and humic layers,
and all non-living biomass with a diameter less than 7.5
cm at transect intersection, lying on the ground.
• Soil organic carbon (SOC), including all organic
material in soil to a depth of 1 meter but excluding the
coarse roots of the aboveground pools.
In addition, there are two harvested wood pools also
necessary for estimating C flux, which are:
• Harvested wood products in use.
• Harvested wood products in landfills.
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,
growth, mortality, decomposition, and disturbances such as
fires or pest outbreaks) and anthropogenic activities (e.g.,
harvesting, thinning, clearing, and replanting). As trees
Land Use, Land-Use Change, and Forestry 7-3
-------
Table 7-4: N20 Emissions from Land Use, Land-Use Change, and Forestry (Gg)
Land-Use Category
Forest Land Remaining Forest Land
N20 Emissions from Soils3
Settlements Remaining Settlements
N20 Emissions from Soils"
Total
1990
<1
<1
18
18
18
1998
1
1
20
20
21
1999
2
2
20
20
22
2000
1
1
19
19
21
2001
1
1
19
19
20
2002
1
1
19
19
21
2003
1
1
20
20
21
2004
1
1
21
21
22
Note: These estimates include direct emissions only. Indirect N20 emissions are reported in section 6.4 of 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.
photosynthesize and grow, C is removed from the atmosphere
and stored in living tree biomass. As trees age, they continue
to accumulate C until they reach maturity, at which point
they store a relatively constant amount of C. As trees die
and otherwise deposit litter and debris on the forest floor,
C is released to the atmosphere or transferred to the soil by
organisms that facilitate decomposition.
The net change in forest C is not equivalent to the
net flux between forests and the atmosphere because
timber harvests do not cause an immediate flux of C to the
atmosphere. Instead, harvesting transfers C to a "product
pool." Once in a product pool, the C is emitted over time as
C02 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 landfills, the C contained in the wood may be released
many years or decades later, or may be stored almost
permanently in the landfills.
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. Thus, the focus on C implies that all C-based
greenhouse gases are included, and the focus on stock change
suggests that specific ecosystem fluxes are not separately
itemized in this report. Disturbances from forest fires and
pest outbreaks are implicitly included in the net changes.
For instance, an inventory conducted after fire counts only
trees left. The change between inventories thus counts the
carbon changes due to fires; however, it may not be possible
to attribute the changes to the disturbance specifically. The
IPCC Good Practice Guidance for Land Use, Land-Use
Change, and Forestry (IPCC 2003) recommends reporting C
stocks according to several land-use types and conversions,
specifically Forest Land Remaining Forest Land and Land
Converted to Forest Land. Currently, consistent datasets are
not available for the entire United States to allow results to
be partitioned in this way. Instead, net changes in all forest-
related land, including non-forest land converted to forest
and forests converted to non-forest are reported here.
Forest C storage pools, and the flows between them via
emissions, sequestration, and transfers, are shown in Figure
7-1. In the figure, boxes represent forest C storage pools and
arrows represent flows between storage pools or between
storage pools and the atmosphere. Note that the boxes are
not identical to the storage pools identified in this chapter.
The storage pools identified in this chapter have been altered
in this graphic to better illustrate the processes that result in
transfers of C from one pool to another, and emissions to the
atmosphere as well as uptake from the atmosphere.
Approximately 33 percent (303 million hectares) of
the U.S. land area is forested. Approximately 250 million
hectares are located in the conterminous 48 states and form
the basis for the estimates provided in this chapter. Seventy-
nine percent of the 250 million hectares are classified
as timberland, meaning they meet minimum levels of
productivity and are available for timber harvest. Historically,
the timberlands in the conterminous 48 states have been more
frequently or intensively surveyed than other forestlands. Of
the remaining 51 million hectares, 16 million hectares are
7-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 7-1
Forest Sector Carbon Pools and Flows
Woody Debris,
Litter, and
Logging Residue
Decompostion Methane
Flaring
and
Utilization
Legend
Carbon Pool
Carbon transfer or flux
Combustion
Source: Heath et al. 2003
Note: Boxes represent forest C storage pools and arrows represent flows between storage pools or between storage pools and the atmosphere.
reserved forestlands (withdrawn by law from management
for production of wood products) and 35 million hectares
are lower productivity forestlands (Smith etal. 20Q4b). From
the early 1970s to the early 1980s, forest land declined by
approximately 2.4 million hectares. During the 1980s and
1990s, forest area increased by about 3.7 million hectares.
These net changes in forest area represent average annual
fluctuations of only about 0.1 percent. Given the low rate of
change in U.S. forest land area, the major influences on the
current net C flux from forest land are management activities
and the ongoing impacts of previous land-use changes. These
activities affect the net flux of C by altering the amount
of C stored in forest ecosystems. For example, intensified
management of forests can increase both the rate of growth
and the eventual biomass density of the forest, thereby
increasing the uptake of C. Harvesting forests removes much
of the aboveground C, but trees can grow on this area again
and sequester C. The reversion of cropland to forest land
increases C storage in biomass, forest floor, and soils. The
net effects of forest management and the effects of land-use
change involving forest land are captured in the estimates
of C stocks and fluxes presented in this chapter.
In the United States, improved forest management
practices, the regeneration of previously cleared forest areas,
as well as timber harvesting and use have resulted in net
uptake (i.e., net sequestration) of C each year from 1990
through 2004. Due to improvements in U.S. agricultural
productivity, the rate of forest clearing for crop cultivation
and pasture slowed in the late 19th century, and by 1920,
2 The term "biomass density "refers to the mass of vegetation per unit area. It is usually measured on a dry-weight basis. Dry biomass is 50 percent carbon
by weight.
Land Use, Land-Use Change, and Forestry 7-5
-------
this practice had all but ceased. As farming expanded in of the timber harvested from U.S. forests is used in wood
the Midwest and West, large areas of previously cultivated products, and many discarded wood products are disposed of
land in the East were taken out of crop production, primarily in landfills rather than by incineration, significant quantities
between 1920 and 1950, and were allowed to revert to of C in harvested wood are transferred to long-term storage
forests or were actively reforested. The impacts of these pools rather than being released rapidly to the atmosphere
land-use changes still affect C fluxes from forests in the (Skog and Nicholson 1998). The size of these long-term C
East. In addition, C fluxes from eastern forests have been storage pools has increased during the last century.
affected by a trend toward managed growth on private changes in C stocks in U.S. forests and harvested
land. Collectively, these changes have nearly doubled the wood were estimated to account for m average amai^ net
biomass density in eastern forests since the early 1950s. More sequestration of 62? Tg CO2 Eq. (171 Tg C) over the period
recently, the 1970s and 1980s saw a resurgence of federally- 1990 ^ough 2Q04 (Table 7-5, Table 7-6, and Figure 7-2).
sponsored forest management programs (e.g., the Forestry In addition to me net accumulation of C in harvested wood
Incentive Program) and soil conservation programs (e.g., pooK sequestration is a reflection of net forest growth and
the Conservation Reserve Program), which have focused increasing forest area over this period, particularly before
on tree planting, improving timber management activities, 199? The increase in forest sequestration is due more to
combating soil erosion, and converting marginal cropland to an increasing C density per area than to the increase in area
forests. In addition to forest regeneration and management, of forestland. Forestland in the conterminous United States
forest harvests have also affected net C fluxes. Because most was approximately 246, 250, and 251 million hectares for
Table 7-5. Net Annual Changes in Carbon Stocks (Tg C02/yr) in Forest and Harvested Wood Pools
Carbon Pool
Forest
Aboveground Biomass
Belowground Biomass
Dead Wood
Litter
Soil Organic Carbon
Harvested Wood
Wood Products
Landfilled Wood
Total Net Flux
1990
(563.3)
(338.5)
(64.8)
(43.5)
(82.9)
(33.6)
(210.1)
(47.6)
(162.4)
(773.4)
1998
(412.7)
(287.5)
(55.1)
(41.6)
(12.4)
(16.0)
(206.1)
(51.9)
(154.2)
(618.8)
1999
(423.2)
(306.6)
(59.5)
(35.5)
(24.9)
3.2
(214.7)
(61.5)
(153.1)
(637.9)
2000
(420.2)
(310.3)
(60.3)
(33.2)
(26.6)
10.1
(210.8)
(58.7)
(152.1)
(631.0)
2001
(420.2)
(310.3)
(60.3)
(33.2)
(26.6)
10.1
(213.8)
(59.0)
(154.8)
(634.0)
2002
(420.2)
(310.3)
(60.3)
(33.2)
(26.6)
10.1
(214.4)
(59.2)
(155.3)
(634.6)
2003
(420.2)
(310.3)
(60.3)
(33.2)
(26.6)
10.1
(215.6)
(60.4)
(155.1)
(635.8)
2004
(420.2)
(310.3)
(60.3)
(33.2)
(26.6)
10.1
(217.0)
(60.8)
(156.2)
(637.2)
Note: 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 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 7-6. Net Annual Changes in Carbon Stocks (Tg C/yr) in Forest and Harvested Wood Pools
Carbon Pool
Forest
Aboveground Biomass
Belowground Biomass
Dead Wood
Litter
Soil Organic Carbon
Harvested Wood
Wood Products
Landfilled Wood
Total Net Flux
1990
(153.6)
(92.3)
(17.7)
(11.9)
(22.6)
(9.2)
(57.3)
(13.0)
(44.3)
(210.9)
1998
(112.6)
(78.4)
(15.0)
(11.4)
(3.4)
(4.4)
(56.2)
(14.2)
(42.1)
(168.8)
1999
(115.4)
(83.6)
(16.2)
(9.7)
(6.8)
0.9
(58.5)
(16.8)
(41.8)
(174.0)
2000
(114.6)
(84.6)
(16.4)
(9.1)
(7.2)
2.8
(57.5)
(16.0)
(41.5)
(172.1)
2001
(114.6)
(84.6)
(16.4)
(9.1)
(7.2)
2.8
(58.3)
(16.1)
(42.2)
(172.9)
2002
(114.6)
(84.6)
(16.4)
(9.1)
(7.2)
2.8
(58.5)
(16.1)
(42.3)
(173.1)
2003
(114.6)
(84.6)
(16.4)
(9.1)
(7.2)
2.8
(58.8)
(16.5)
(42.3)
(173.4)
2004
(114.6)
(84.6)
(16.4)
(9.1)
(7.2)
2.8
(59.2)
(16.6)
(42.6)
(173.8)
Note: 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 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.
7-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 7-2
Estimates of Net Annual Changes in Carbon Stocks
for Major Carbon Pools
50 -,
_ o -
-50 -
-100 -
1 -150
-200 -
-250 J
Soil
Harvested Wood
Forest, Nonsoil
1987,1997, and 2002, respectively, only a 2 percent increase
over the period (Smith et al. 2004b). Continuous, regular
annual surveys are not available over the period for each
state; therefore, estimates for non-survey years were derived
by interpolation between known data points. Survey years
vary from state to state. National estimates are a composite
of individual state surveys. Total sequestration declined by
18 percent between 1990 and 2004. Estimated sequestration
in the litter carbon pool had the greatest effect on total
change; the net rate of accumulation in litter decreased
by 56 Tg CO2 Eq. Aboveground biomass and soil carbon
had the next largest effects on total change; the net rate of
accumulation in these pools decreased by 28 and 24 Tg CO2
Eq., respectively.
Stock estimates for forest and harvested wood C storage
pools are presented in Table 7-7. Together, the aboveground
live and forest soil pools account for a large proportion of
total forest C stocks. C stocks in all non-soil pools increased
over time. Therefore, C sequestration was greater than C
emissions from forests, as discussed above. Figure 7-3 shows
county-average carbon densities for live trees on forestland,
including both above- and belowground biomass.
Methodology
The methodology described herein is consistent with
IPCC Good Practice Guidance for Land Use, Land-Use
Change, and Forestry (IPCC 2003) and the Revised 1996
IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997). Estimates of net C flux
from forest pools were derived from periodic and annualized
inventories of forest stocks. Net changes in C stocks were
interpolated between survey years. Carbon emissions
from harvested wood were determined by accounting for
the variable rate of decay of harvested wood according to
its disposition (e.g., product pool, landfill, combustion).
Table 7-7. Carbon Stocks (Tg C) in Forest and Harvested Wood Pools
Carbon Pool
Forest
Aboveground Biomass
Belowground Biomass
Dead Wood
Litter
Soil Organic Carbon
Harvested Wood
Wood Products
Landfilled Wood
Total Carbon Stock
1990
39
14
2
2
4
15
1
1
41
,508
,334
,853
,409
,492
,420
,915
,134
781
,423
1998
40,417
14,938
2,967
2,488
4,565
15,460
2,365
1,248
1,117
42,782
1999
40,529
15,016
2,982
2,499
4,569
15,464
2,421
1,262
1,159
42,951
2000
40
15
2
2
4
15
2
1
1
43
,645
,100
,998
,509
,575
,463
,480
,279
,200
,125
2001
40,760
15,184
3,014
2,518
4,583
15,460
2,537
1,295
1,242
43,297
2002
40,874
15,269
3,031
2,527
4,590
15,458
2,595
1,311
1,284
43,470
2003
40,989
15,354
3,047
2,536
4,597
15,455
2,654
1,327
1,327
43,643
2004
41,103
15,438
3,064
2,545
4,604
15,452
2,713
1,344
1,369
43,816
2005
41,218
15,523
3,080
2,554
4,612
15,449
2,772
1,360
1,411
43,990
Note: Forest C stocks do not include forest stocks in Alaska, Hawaii, or U.S. territories, or trees on non-forest land (e.g., urban trees). Wood product
stocks include exports, even if the logs are processed in other countries, and exclude imports. Forest estimates are based on interpolation and
extrapolation of inventory data as described in the text and in Annex 3.12. Harvested wood estimates are based on results from annual surveys and
models. Totals may not sum due to independent rounding. Inventories are assumed to represent stocks as of January 1 of the inventory year. Flux is the
net annual change in stock. Thus, an estimate of flux for 2004 requires estimates of C stocks for 2004 and 2005.
3 The wood product stock and flux estimates presented here use the production approach, meaning that they do not account for C stored in imported wood
products, but do include C stored in exports, even if the logs are processed in other countries. This approach is used because it follows the precedent
established in previous reports (Heath et al. 1996).
Land Use, Land-Use Change, and Forestry 7-7
-------
Figure 7-3
Average Carbon Density in the Forest Tree Pool in the Conterminous U.S. During 2005
Average Forest Tree
Carbon (t C/ha)
•11-45
mm 46-71
mm 72-99
• 100-289
Note: This graphic shows county-average carbon densities for live trees on forestland, including both above- and belowground biomass. These data
are based on the most recent forest inventory survey in each state.
Different data sources were used to estimate the C stocks and
stock change in: (1) forests (aboveground and belowground
biomass, dead wood, and litter); (2) forest soils; and (3)
harvested wood products. Therefore, these pools are
described separately below.
Live Biomass, Dead Wood, and Litter Carbon
The estimates of non-soil forest C stocks are based on
data derived from forest surveys. Forest survey data were
obtained from the USDA Forest Service, Forest Inventory
and Analysis (FIA) program (Prayer and Furnival 1999,
Smith et al. 2001). Surveys provide estimates of the
merchantable volume of wood and other variables that are
used to estimate C stocks. Estimates of temporal change
such as growth, mortality, harvests, or area change are
derived from repeated surveys, which were conducted every
5 to 14 years, depending on the state. Historically, the FIA
program did not conduct detailed surveys of all forest land,
but instead focused on land capable of supporting timber
production (timberland).4 Over time, however, individual
state surveys gradually started to include reserved and less
productive forest land. The C stock estimates provided here
include all forest land. See Annex 3.12 for discussion of
how past data gaps on these lands were filled.
Temporal and spatial gaps in surveys were addressed
with the new national plot design and annualized sampling
(Alerich et al. 2005), which were recently introduced by
FIA. 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. Sampling is
designed such that partial inventory cycles provide usable,
unbiased samples of forest inventory. Thus, many states
have relatively recent partial inventories, yet not all states
are currently surveyed this way. All annualized surveys
initiated since 1998 have followed the new national plot
4 Forest land in the United States includes land that is at least 10 percent stocked with trees of any size. Timberland is the most productive type of forest
land, which is on unreserved land and is producing or capable of producing crops of industrial wood. Productivity is at a minimum rate of 20 cubic feet
of industrial wood per acre per year. The remaining portion of forest land is classified as either reserved forest land, which is forest land withdrawn from
timber use by statute or regulation, or other forest land, which includes less productive forests on which timber is growing at a rate less than 20 cubic feet
per acre per year. In 2002, there were about 199 million hectares of timberland in the conterminous United States, which represented 79 percent of all
forest land over the same area (Smith et al. 2004b).
7-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
design for all forestland, including reserved and less
productive land.
For each periodic or annualized inventory in each
state, each C pool was estimated using coefficients from the
FORCARB2 model (Birdsey and Heath 1995, Birdsey and
Heath 2001, Heath et al. 2003, Smith et al. 2004a). Estimates
of C stocks made by the FORCARB2 coefficients at the plot
level are organized somewhat differently than the standard
IPCC pools reported in Table 7-7. However, the estimators
are compatible with reorganizing the pools following IPCC
LULUCF Good Practice Guidance (2003). For example, the
biomass pools here include the FORCARB2 pools of live
trees and understory vegetation, each of which are divided
into aboveground versus belowgroundportions. Calculations
for the tree portion of the aboveground biomass C pool were
made using individual-tree or volume-to-biomass conversion
factors for different types of forests, depending on the data
available for each survey (Jenkins et al. 2003, Smith et al.
2003). Biomass was converted to C mass by dividing by two
because dry biomass is approximately 50 percent C (IPCC/
UNEP/OECD/IEA 1997). The other portion of aboveground
biomass, live understory C, was estimated from inventory
data using tables presented in Birdsey (1996). Litter C was
estimated from inventory data using the equations presented
in Smith and Heath (2002). Down dead wood was estimated
using a FORCARB2 simulation and U.S. forest statistics
(Smith etal. 2001).
Forest Soil Carbon
Estimates of soil organic carbon stocks are based solely
on forest area and on average soil C density for each broad
forest type group. Thus, any changes in soil C stocks are due
to changes in total forest area or the distribution of forest
types within that area. Estimates of the organic C content of
soils are based on the national STATS GO spatial database
(USDA1991) and follow methods of Amichev and Galbraith
(2004). These data were overlaid with FIA survey data to
estimate soil C on forest land by broad forest type group.
Forest Carbon Stocks and Fluxes
The overall approach for determining forest C stock
change was to estimate forest C stocks based on data from
two forest surveys conducted several years apart. Carbon
stocks were calculated separately for each state based on
inventories available since 1990 and for the most recent
inventory prior to 1990. For each pool in each state in each
year, C stocks were estimated by linear interpolation between
survey years. Similarly, fluxes were estimated for each pool in
each state by dividing the difference between two successive
stocks by the number of intervening years between surveys.
Stocks and fluxes since the most recent survey were based
on extrapolating estimates from the last two surveys. C stock
and flux estimates for each pool were summed over all states
to form estimates for the conterminous United States. Data
sources and methods for estimating individual C pools are
described more fully in Annex 3.12.
Harvested Wood Carbon
Estimates of C stock changes in wood products and
wood discarded in landfills were based on the methods
described by Skog and Nicholson (1998). Carbon stocks in
wood products in use and wood products stored in landfills
were estimated from 1910 onward based on historical data
from the USDA Forest Service (USDA 1964, Ulrich 1989,
Howard 2001), and historical data as implemented in the
framework underlying the North American Pulp and Paper
(NAPAP, Ince 1994), the Timber Assessment Market, and
the Aggregate Timberland Assessment System Timber
Inventory models (TAMM/ATLAS, Haynes 2003, Mills
and Kincaid 1992). Beginning with data on annual wood
and paper production, the fate of C in harvested wood was
tracked for each year from 1910 through 2004, and included
the change in C stocks in wood products, the change in C
in landfills, and the amount of C emitted to the atmosphere
(C02 and CH4) both with and without energy recovery. To
account for imports and exports, the production approach
was used, meaning that C in exported wood was counted as
if it remained in the United States, and C in imported wood
was not counted.
Uncertainty
The forest survey data that underlie the forest C
estimates are based on a statistical sample designed to
represent the wide variety of growth conditions present
over large territories. However, forest survey data that
are currently available generally exclude timber stocks on
most forest land in Alaska, Hawaii, and U.S. territories.
For this reason, estimates have been developed only for
the conterminous United States. Within the conterminous
United States, the USDAForest Service mandates that forest
area data are accurate within 3 percent at the 67 percent
confidence level (one standard error) per 405,000 ha (10
Land Use, Land-Use Change, and Forestry 7-9
-------
acres) of timberland (Aldrich et al. 2005). For larger areas,
the uncertainty in area is concomitantly smaller. For growing
stock volume data on timberland, the accuracy is targeted to
be 5 or 10 percent for each 28.3 million m (109 cubic feet)
at the same confidence level. An analysis of uncertainty in
growing stock volume data for timber producing land in the
Southeast by Phillips et al. (2000) found that nearly all of
the uncertainty in their analysis was due to sampling rather
than the regression equations used to estimate volume from
tree height and diameter. Standard errors for growing stock
volume ranged from 1 to 2 percent for individual states and
less than 1 percent for the 5-state region. However, the total
standard error for the change in growing stock volume was
estimated to be 12 to 139 percent for individual states, and 20
percent for the 5-state region. The high relative uncertainty
for growing stock volume change in some states was due
to small net changes in growing stock volume. However,
the uncertainty in volume change may be smaller than was
found in this study because estimates from samples taken
at different times on permanent survey plots are correlated,
and such correlation reduces the uncertainty in estimates
of changes in volume or C over time (Smith and Heath
2000).
In addition to uncertainty in data summarized for
inventory surveys, there is uncertainty associated with the
estimates of specific C stocks in those forest ecosystems.
Estimates for these pools are derived from extrapolations of
site-specific studies to all forest land since survey data on
these pools are not generally available. Such extrapolation
introduces uncertainty because available studies may
not adequately represent regional or national averages.
Uncertainty may also arise due to: (1) modeling errors
(e.g., relying on coefficients or relationships that are not
well known); and (2) errors in converting estimates from
one reporting unit to another (Birdsey and Heath 1995). An
important source of uncertainty is that there is little consensus
from available data sets on the effect of land-use change
and forest management activities (such as harvest) on soil C
stocks. For example, while Johnson and Curtis (2001) found
little or no net change in soil C following harvest, on average,
across a number of studies, many of the individual studies
did exhibit differences. Heath and Smith (2000a) noted that
the experimental design in a number of soil studies limited
their usefulness for determining effects of harvesting on soil
C. Because soil C stocks are large, estimates need to be very
precise, since even small relative changes in soil C sum to
large differences when integrated over large areas. The soil C
stock and stock change estimates presented herein are based
on the assumption that soil C density for each broad forest
type group stays constant over time. As more information
becomes available, the effects of land use and of changes
in land use and forest management will be better accounted
for in estimates of soil C (see "Planned Improvements"
below).
A quantitative uncertainty analysis was developed for
the estimates of C stock and flux presented here. The analysis
incorporated the information discussed above as well as
preliminary uncertainty analyses of previous C estimates
developed according to the same or similar methodologies
as applied here (Heath and Smith 2000b, Smith and Heath
2000, Skog et al. 2004). Some additional details on the
analysis are provided in Annex 3.12. The uncertainty
analysis was performed using the IPCC-recommended
Tier 2 uncertainty estimation methodology—Monte Carlo
Simulation technique. The results of the Tier 2 quantitative
uncertainty analysis are summarized in Table 7-8. The 2004
flux estimate for forest C stocks is estimated to be between
-794.7 and -476.3 Tg CO2 Eq. at a 95 percent confidence level
(i.e., 19 out of every 20 Monte Carlo stochastic simulations
fall within this interval). This indicates a relative range of
Table 7-8: Tier 2 Quantitative Uncertainty Estimates for Net C02 Flux from Forest Land Remaining Forest Land:
Changes in Forest Carbon Stocks (Tg C02 Eq. and Percent)
r ,. ,ux Uncertainty Range Relative to Flux Estimate3
Estimate
Source Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound
Forest Land Remaining Forest Land:
Changes in Forest Carbon Stocks C02 (637.2) (794.7) (476.3) -25%
Upper Bound
+ 25%
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.
7-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
24.7 percent below to 25.2 percent above the 2004 flux
estimate of -637.2 Tg CO2 Eq. The 95 percent confidence
intervals for the two principal components of total flux are
-546 to -294 Tg C02 Eq. for forest ecosystems and -297 to
-136 Tg C02 Eq. for harvested wood.
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 since 1952. The main purpose of the Forest
Inventory and Analysis program has been to estimate areas,
volume of growing stock, and timber products output and
utilization factors. The FIA program includes numerous
quality assurance and quality control procedures, including
calibration among field crews, duplicate surveys of some
plots, and systematic checking of recorded data. Because of
the statistically-based sampling, the large number of survey
plots, and the quality of the data, the survey databases
developed by the FIA program form a strong foundation
for C stock estimates. Field sampling protocols, summary
data, and detailed inventory databases are archived and are
publicly available on the Internet (FIA Database Retrieval
System).
Many key calculations for estimating current forest
C stocks based on FIA data are based on coefficients
from the FORCARB2 model (see additional discussion in
the Methodology section above and in Annex 3.12). The
model has been used for many years to produce national
assessments of forest C stocks and stock changes. General
quality control procedures were used in performing
calculations to estimate C stocks based on survey data. For
example, the derived C datasets, which include inventory
variables such as areas and volumes, were compared with
standard inventory summaries such as Resources Planning
Act (RPA) Forest Resource Tables or selected population
estimates generated from the FIA Database (FIADB),
which are available at an FIA Internet site (FIA Database
Retrieval System). 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).
Recalculations Discussion
The overall scheme for developing annualized estimates
of C stocks based on the individual state surveys is similar
to that presented in the previous Inventory (EPA 2005). The
change from the previous year's methods involves the use
of survey data. This year, the emphasis was on using all
available state surveys in the FIADB, with RPA data used
as necessary to estimate pre-1990 stocks. In the previous
inventory, the FIADB was used to supplement the RPA
datasets. Additionally, the FIADB has been updated over
the last year.
The modifications and updates to the forest inventory
data are detailed in Table A-180 in Annex 3.12 (the forest
carbon methodology annex) and can be compared with
forest inventories identified in a similar table in the previous
U.S. Greenhouse Gas Inventory (EPA 2005). These changes
are reflected in estimates of forest carbon stocks. Biomass
stocks prior to 1996 were revised upward slightly, and
biomass stocks after 1997 were revised downward. Stocks
of dead wood were revised downward throughout, with
greater changes in more recent years. The net effect is an
average decrease in estimated forest carbon stocks of less
than 1 percent for the period 1990 through 2003. These
comparisons can be independently calculated by referring
to Table A-183 in this Inventory and the analogous table in
the previous Inventory (EPA 2005). Overall, these changes
resulted in an average annual decrease of 206 Tg C02 Eq.
(24 percent) in the net change in forest carbon stocks for the
period 1990 through 2003.
Planned Improvements
The ongoing annualized surveys by the FIA Program
will improve precision of forest C estimates as new state
surveys become available (Gillespie 1999). In addition, the
more intensive sampling of down dead wood, litter, and soil
organic C on some of the permanent plots will substantially
improve resolution of C pools at the plot level.
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). Currently,
soil C estimates are based on the assumption that soil C
density depends only on broad forest type group, not on
land-use history. However, many forests in the Eastern
United States are re-growing on abandoned agricultural
Land Use, Land-Use Change, and Forestry 7-11
-------
land. During such regrowth, soil and forest floor C stocks
often increase substantially over many years or even
decades, especially on highly eroded agricultural land. In
addition, with deforestation, soil C stocks often decrease
over many years. A new methodology is being developed
to account for these changes in soil C over time. This
methodology includes estimates of area changes among
land uses (especially forest and agriculture), estimates of
the rate of soil C stock gain with afforestation, and estimates
of the rate of soil C stock loss with deforestation over time.
This topic is important because soil C stocks are large, and
soil C flux estimates contribute substantially to total forest
C flux, as shown in Table 7-6 and Figure 7-2.
The estimates of C stored in harvested wood products are
currently being revised using more detailed wood products
production and use data, and more detailed parameters on
disposition and decay of products.
An additional planned improvement is to develop
a consistent representation of the U.S. managed land
base. Currently, the forest C and the agricultural soil C
inventories are the two major analyses addressing land-use
and management impacts on C stocks. The forest inventory
relies on the activity data from the FIA Program to estimate
anthropogenic impacts on forest land, while the agricultural
soil C inventory relies on the USDA National Resources
Inventory (NRI). Recent research has revealed that the
classification of forest land is not consistent between the
FIA and NRI, leading to some double-counting and gaps in
the current forest C and agricultural soil C inventories (e.g.,
some areas classified as forest land in the FIA are considered
rangeland in the NRI). Consequently, the land bases are in
the process of being compared between the inventories to
determine where overlap or gaps occur, and then ensure
that the inventories are revised to have a consistent and
complete accounting of land-use and management impacts
across all managed land in the United States.
N20 Fluxes from Soils (IPCC Source
Category 5A1)
Of the 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 fertilizer. This is because forests are typically
fertilized only twice during their approximately 40-year
growth cycle (once at planting and once at approximately
20 years). Thus, although the rate of fertilizer application for
the area of forests that receives fertilizer in any given year
is relatively high, average annual applications, inferred by
dividing all forest land by the amount of fertilizer added to
forests in a given year, is quite low. Nitrous oxide (N20)
emissions from forest soils for 2004 were almost 7 times
higher than the baseline year (1990). The trend toward
increasing N20 emissions is a result of an increase in
fertilized area of pine plantations in the southeastern United
States. Total 2004 forest soil N20 emissions are roughly
equivalent to 3.9 percent of the total forest soil carbon flux,
and 0.06 percent of the total sequestration in standing forests,
and are summarized in Table 7-9.
Methodology
For soils within Forest Land Remaining Forest Land,
the IPCC Tier 1 approach was used to estimate N20 from
soils. According to U.S. Forest Service statistics for 1996
(USDA Forest Service 2001), approximately 75 percent of
trees planted for timber, and about 60 percent of national
total harvested forest area are in the Southeastern United
States. Consequently, it was assumed that southeastern pine
plantations represent the vast majority of fertilized forests
in the United States. Therefore, estimates of direct N20
emissions from fertilizer applications to forests were based
on the area of pine plantations receiving fertilizer in the
Table 7-9. N20 Fluxes from Soils in Forest Land Remaining Forest Land (Tg C02 Eq. and Gg)
Forest Land Remaining Forest Land:
N20 Fluxes from Soils
Tg C02 Eq.
eg
1990
0.1
<1
1998
0.4
1
1999
0.5
2
2000
0.4
1
2001
0.4
1
2002
0.4
1
2003
0.4
1
2004
0.4
1
Note: These estimates include direct N20 emissions from N fertilizer additions only. Indirect N20 emissions from fertilizer additions are reported in
section 6.4 of the Agriculture chapter. These estimates include emissions from both Forest Land Remaining Forest Land, and from Land Converted to
Forest Land.
7-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Southeastern United States and estimated application rates
(North Carolina Sate Forest Nutrition Cooperative 2002).
Not accounting for fertilizer applied to non-pine plantations
is justified because fertilization is routine for pine forests
but rare for hardwoods (Binkley et al. 1995). For each year,
the area of pine receiving N fertilizer was multiplied by
the midpoint of the reported range of N fertilization rates
(150 Ibs. N per acre). Data for areas of forests receiving
fertilizer outside the Southeastern United States were not
available, so N additions to non-southeastern forests are
not included here; however, it should be expected that
emissions from the small areas of fertilized forests in other
regions would be insubstantial because the majority of trees
planted and harvested for timber are in the Southeastern
United States (USDA Forest Service 2001). Area data
for pine plantations receiving fertilizer in the Southeast
were not available for 2002, 2003, and 2004, so data from
2001 were substituted for these years. The proportion of
N additions that volatilized from forest soils was assumed
to be 10 percent of total amendments, according to the
IPCC's default. The unvolatilized N applied to forests
was then multiplied by the IPCC default emission factor
of 1.25 percent to estimate direct N20 emissions. The
volatilization and leaching/runoff fractions, calculated
according to the IPCC default factors of 10 percent and
30 percent, respectively, were included with all sources
of indirect emissions in the Agricultural Soil Management
source category of the Agriculture sector.
Uncertainty
The amount of N20 emitted from forests depends not
only on N inputs, but also on a large number of variables,
including organic carbon availability, O2 partial pressure,
soil moisture content, pH, temperature, and tree planting/
harvesting cycles. The effect of the combined interaction of
these variables on N2O flux is complex and highly uncertain.
The IPCC default methodology used here does not incorporate
any of these variables and only accounts for variations in
estimated fertilizer application rates and estimated areas of
forested land receiving fertilizer. All forest soils are treated
equivalently under this methodology. Furthermore, only
synthetic fertilizers are captured, so applications of organic
fertilizers are not accounted for here.
Uncertainties exist in the fertilizer application rates, the
area of forested land receiving fertilizer, and the emission
factors used to derive emission estimates. Uncertainty was
calculated according to a modified IPCC Tier 1 methodology.
The 95 percent confidence interval of the IPCC default
emission factor for synthetic fertilizer applied to soil,
according to Chapter 4 of IPCC (2000), ranges from 0.25
to 6 percent. While a Tier 1 analysis should be generated
from a symmetrical distribution of uncertainty around the
emission factor, an asymmetrical distribution was imposed
here to account for the fact that the emission factor used
was not the mean of the range given by IPCC. Therefore, an
upper bound of 480 percent and a lower bound of 80 percent
were assigned to the emission factor. The higher uncertainty
percentage is shown below, but the lower bound reflects
a truncated distribution. The uncertainties in the area of
forested land receiving fertilizer and fertilization rates were
conservatively estimated to be +54 percent (Binkley 2004).
The results of the Tier 1 quantitative uncertainty analysis
are summarized in Table 7-10. N2O fluxes from soils were
estimated to be between 0.01 and 2.3 Tg CO2 Eq. at a 95
percent confidence level. This indicates a range of 96 percent
below and 483 percent above the 2004 emission estimate of
0.4 Tg C02 Eq.
Planned Improvements
Area data for southeastern pine plantations receiving
fertilizer will be updated with more recent datasets, and the
indirect N2O emissions from fertilization of forests, which
Table 7-10: Tier 1 Quantitative Uncertainty Estimates of N20 Fluxes from Soils in Forest Land Remaining Forest Land
(Tg C02 Eq. and Percent)
Source
Gas
2004 Emission
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Forest Land Remaining Forest Land:
N20 Fluxes from Soils
N,0
0.4
2.3
-96%
+483%
Note: This includes direct N20 emissions from N fertilizer additions to both Forest Land Remaining Forest Land and Land Converted to Forest Land.
Land Use, Land-Use Change, and Forestry 7-13
-------
are currently reported in the Agriculture chapter, will be
reported here.
7.2. Land Converted to Forest Land
(IPCC Source Category 5A2)
Land-use change is constantly occurring, and areas
under a number of differing land-use types are converted to
forest each year, just as forest land is converted to other uses.
However, the magnitude of these changes is not currently
known. Given the paucity of available land-use information
relevant to this particular IPCC source category, it is not
possible to separate CO2 or N2O fluxes on Land Converted
to Forest Land from fluxes on Forest Land Remaining Forest
Land at this time.
7.3. Cropland Remaining Cropland
(IPCC Source Category 5B1)
Soils contain both organic and inorganic forms of
carbon (C), but soil organic carbon (SOC) stocks are the
main source or sink for atmospheric CO2 in most soils.
Changes in inorganic carbon stocks are typically minor. In
addition, soil organic carbon 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. The Revised 1996 IPCC Guidelines for National
Greenhouse GasInventonesflPCCIVNEPIOECDIlEA 1997)
recommends reporting changes in soil organic C stocks due
to: (1) agricultural land-use and management activities on
mineral soils; and (2) agricultural land-use and management
activities on organic soils. In addition, the IPCC Guidelines
recommends reporting C02 emissions that result from liming
of soils with dolomite and limestone.
Typical well-drained mineral soils contain from 1 to 6
percent organic carbon by weight, although some mineral
soils that experience long-term saturation during the year
may contain significantly more C (NRCS 1999). When
mineral soils undergo conversion from their native state
to agricultural uses, as much as half the SOC can be lost
to the atmosphere. The rate and ultimate magnitude of C
loss will depend on pre-conversion conditions, conversion
method and subsequent management practices, climate,
and soil type. In the tropics, 40 to 60 percent of the C
loss generally occurs within the first 10 years following
conversion; after that, C stocks continue to decline 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 will 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 oxidation.
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 soils.
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 C02 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 C02 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/IEA1997).
C losses are estimated from drained organic soils under both
grassland and cropland management in this inventory.
The last category of the IPCC methodology addresses
emissions from lime additions (in the form of crushed
limestone (CaC03) and dolomite (CaMg(C03)2) to
agricultural soils. Lime and dolomite are added by
land managers to ameliorate acidification. When these
compounds come in contact with acid soils, they degrade,
thereby generating CO2. The rate and ultimate magnitude
of degradation of applied limestone and dolomite depends
on the soil conditions, climate regime, and the type of
mineral applied.
7-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
For U.S. agricultural soils, C02 emissions and removals5 about a 7 percent decline since the initial reporting year of
due to changes in mineral soil C stocks are estimated using 1990. Emissions from organic soils had the second largest
a Tier 3 approach employing a process-based model for flux, emitting about 30.3 Tg CO2 Eq. (8 Tg C) in 2004.
the majority of annual crops, Tier 2 IPCC method for the Liming emitted another 4.0 Tg C02 Eq. (1 Tg C) in 2004. In
remaining crops (vegetables, perennial/horticultural crops, total, U.S. agricultural soils in Cropland Remaining Cropland
tobacco and rice), andaTier 1 method for additional changes removed approximately 28.9 Tg CO2 Eq. (8 Tg C) in 2004,
in mineral soil C stocks that were not addressed with the Tier which was the average rate of change per year over the 1990
2or3 approaches (i.e., variation in manure N production and through 2004 reporting period.
thus areas amended with manure relative to 1997, as well as Net increase in soil carbon stocks was largely due
gains or losses in C sequestration after 1997 due to changes in to amual cropland enrolled in the Conservation Reserve
Conservation Reserve Program enrollment). Emissions from Pmgram, intensification of crop production by limiting the
organic soils are also estimated using a Tier 2 IPCC method. use of bare_summer fallow in semi-arid regions, increased
Emissions from liming are estimated using a Tier 2 IPCC hay production; and adoption of conservation tillage (i.e.,
method that relies on national aggregate statistics of lime reduced and no till practices)
application and newly published research on emissions from
The spatial variability in annual CO2 flux associated with
liming of agricultural soils (West and McBride 2005).
C stock changes in mineral and organic soils is displayed in
Of the three sub-source categories, land-use and land Figure 7-4 through Figure 7-7. The high rates of sequestration
management of mineral soils was the most important in mineral soils occurred in me Midwest, where there were
component of total net C stock change between 1990 through me largest ^^ of cropland managed with conservation
2004 (see Table 7-11 and Table 7-12). In 2004, mineral soils tillage adoption Rates were ^ Wgh in Great Plains due to
were estimated to remove about 63.2 Tg CO2 Eq. (17 Tg C). enrollment in the Conservation Reserve Program. Emission
However, this rate of C storage in mineral soils represented
Table 7-11: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland (Tg C02 Eq.)
Soil Type
Mineral Soils
Organic Soils3
Liming of Soils"
Total Net Flux
1990
(67.6)
29.9
4.7
(33.0)
1998
(59.6)
30.3
4.7
(24.6)
1999
(59.3)
30.3
4.5
(24.6)
2000
(60.7)
30.3
4.3
(26.1)
2001
(62.5)
30.3
4.4
(27.8)
2002
(62.8)
30.3
5.0
(27.5)
2003
(62.7)
30.3
3.7
(28.7)
2004
(63.2)
30.3
4.0
(28.9)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values
are based on historical data only.
a Also includes emissions due to drainage of organic soils on Land Converted to Cropland
b Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.
Table 7-12: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland (Tg C)
Soil Type
Mineral Soils
Organic Soils3
Liming of Soils"
Total Net Flux
1990
(18.4)
8.1
1.3
(9.0)
1998
(16.3)
8.3
1.3
(6.7)
1999
(16.2)
8.3
1.2
(6.7)
2000
(16.6)
8.3
1.2
(7.1)
2001
(17.0)
8.3
1.2
(7.6)
2002
(17.1)
8.3
1.4
(7.5)
2003
(17.1)
8.3
1.0
(7.8)
2004
(17.2)
8.3
1.1
(7.9)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values
are based on historical data only.
a Also includes emissions due to drainage of organic soils on Land Converted to Cropland
b Also includes emissions from liming in Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.
5 Note that removals occur through crop and forage uptake of CO2 into biomass C that is later incorporated into soils pools.
Land Use, Land-Use Change, and Forestry 7-15
-------
Figure 7-4
Net C Stock Change for Mineral Soils in Cropland Remaining Cropland, 1990-1992
Tg C02 Eq/yr
G 0 to 1.7
G-0.1 toO
G -0.5 to -0.1
n-1to-0.5
• -2to-1
n -e to -2
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes
associated with the Tier 2 and 3 inventory computations, but not the Tier 1 estimates. See Methodology for additional details.
This map shows the spatial variability in net carbon stock change for mineral soils for the years 1990 through 1992. The color assigned to each polygon
represents the total annual flux for the area of managed mineral soils in that polygon.
Figure 7-5
Net C Stock Change for Mineral Soils in Cropland Remaining Cropland, 1993-2004
Tg C02 Eq/yr
n 0 to 1.5
n-0.1 toO
• -0.5(0-0.1
H-1to-0.5
n-2to-i
H-14 to-2
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes
associated with the Tier 2 and 3 inventory computations, but not the Tier 1 estimates. See Methodology for additional details.
This map shows the spatial variability in net carbon stock change for mineral soils for the years 1993 through 2004. The color assigned to each polygon
represents the total annual flux for the area of managed mineral soils in that polygon.
7-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 7-6
Net C Stock Change for Organic Soils in Cropland Remaining Cropland, 1990-1992
Note: Values greater than zero represent emissions.
Tg C02 Eq/yr
H 2 to 22
• 1 to 2
H 0.5 to 1
G 0.1 to 0.5
DO to 0.1
G No organic soils
This map shows the spatial variability in net carbon stock change for organic soils for the years 1990 through 1992. The color assigned to each polygon
represents the total annual flux for the area of managed organic soils in that polygon.
Figure 7-7
Net C Stock Change for Organic Soils in Cropland Remaining Cropland, 1993-2004
Note: Values greater than zero represent emissions.
Tg C02 Eq/yr
G 2 to 22
|1 to 2
H 0.5 to 1
G 0.1 to 0.5
GO to 0.1
G No organic soils
This map shows the spatial variability in net carbon stock change for organic soils for the years 1993 through 2004. The color assigned to each polygon
represents the total annual flux for the area of managed organic soils in that polygon.
Land Use, Land-Use Change, and Forestry 7-17
-------
rates from drained organic soils were highest along the
southeastern coastal region, in the northeast central United
States surrounding the Great Lakes, and along the central
and northern portions of the west coast.
The estimates presented here are restricted to C stock
changes associated with land use and management of
agricultural soils. Agricultural soils are also important
sources of other greenhouse gases, particularly N20 from
application of fertilizers, manure, and crop residues and
from cultivation of legumes, as well as methane (CH4) from
flooded rice cultivation. These emissions are accounted for
under the Agriculture sector, along withnon-CO2 greenhouse
gas emissions from field burning of crop residues and CH4
and N2O emissions from livestock digestion and manure
management.
Methodology
The following section includes a description of the
methodology used to estimate changes in soil carbon stocks
due to: (1) agricultural land-use and management activities
on mineral soils; (2) agricultural land-use and management
activities on organic soils; and (3) C02 emissions that
result from liming of soils with dolomite and limestone for
Cropland Remaining Cropland.
Mineral and Organic Soil Carbon Stock Changes
Soil C stock changes were estimated for agricultural
land (i.e., Cropland Remaining Cropland, Land Converted
to Cropland, Grassland Remaining Grassland, and Land
Converted to Grassland), according to land use histories
recorded in the USDA National Resources Inventory (NRI)
survey (USDA-NRCS 2000). The NRI is a statistically-based
sample of all non-Federal land, and includes ca. 400,000 points
in agricultural land of the conterminous United States and
Hawaii.6 Each point is associated with an "expansion factor"
that allows scaling of C stock changes from NRI points to
the entire country (i.e., each expansion factor represents the
amount of area with the same land-use/management history
as the sample point). Land use and some management
information (e.g., crop type, soil attributes, and irrigation)
were collected for each NRI point on a 5-year cycle beginning
in 1982. Currently, the NRI is being revised to collect data
annually from a subset of points. However, at present, no
additional national-level data are available after 1997.
NRI points were classified as Cropland Remaining
Cropland if the land use had been cropland since the first
year of the NRI in 1982. Cropland includes all land used to
produce food or fiber, as well as forage that is harvested and
used as feed (e.g., hay and silage).
A new Tier 3 model-based approach was developed
to estimate C stock changes for soils used to produce a
majority of annual crops in the United States (i.e., all crops
except vegetables, tobacco, perennial/horticultural crops,
and rice). The Century biogeochemical model (Parton et
al. 1987, 1988, 1994; Metherell et al. 1993) was used to
simulate the changes in C stocks for this Tier 3 approach.
The model simulates carbon (C) dynamics and other elements
in cropland, grassland, forest and savanna ecosystems. It
uses monthly weather data as input, along with information
about soil physical properties. Input data on land use and
management can be specified at monthly resolution and
include land-use type, crop/forage type and management
activities (e.g., planting, harvesting, fertilization, manure
amendments, tillage, irrigation, residue removal, grazing, and
fire). The model computes net primary productivity and C
additions to soil, temperature and water dynamics; in addition
to turnover, stabilization, and mineralization of soil organic
matter carbon and nutrient (N, K, S) elements.
An IPCC Tier 2 method was used to estimate C stock
changes for cropland on mineral soils that were not addressed
with the Tier 3 method, in addition to emissions from drained
organic soils (Ogle et al. 2003). Emissions for liming were
computed using a Tier 2 methodology that relies on national
aggregate statistics of lime application and newly published
research on emissions from liming of agricultural soils (West
and McBride 2005).
Two additional stock change calculations were made for
mineral soils using Tier 1 (IPCC default) emission factors.
These calculations accounted for activities that were not
addressed by the Tier 3 or Tier 2 methods, including the
amount of area receiving manure amendments relative to
1997,7 and enrollment patterns in the Conservation Reserve
Program after 1997.
6 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
7 The Tier 2 and 3 portions of the inventory use manure amendments based on 1997 values because application rates and the amount of land amended
with manure have only been estimated for 1997 (Edmonds et al. 2003). However, manure N production and thus rates of application do vary from year
to year. The effect of this variation on soil C stocks is discussed further in Annex 3.13.
7-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Further elaboration on the methodology and data used
to estimate stock changes from mineral and organic soils are
described below and in Annex 3.13.
Mineral Soils
Tier 3 Approach
Mineral SOC stocks and stock changes were estimated
for the majority of crops (i.e., all crops except vegetable
crops, tobacco, perennial/horticultural crops, and rice) using
the Century biogeochemical model. National estimates were
obtained by using the model to simulate historical land-use
and management patterns as recorded in the USDA National
Resources Inventory (NRI) survey. For these simulations of
soil organic C dynamics, land-use, and management activities
were grouped into inventory time periods (i.e., time "blocks")
for 1980-84, 1985-89, 1990-94 and 1995-2000, using NRI
data from 1982, 1987, 1992, and 1997, respectively.
Additional sources of activity data were used to
supplement the land-use information from NRI. The
Conservation Technology Information Center (CTIC 1998)
provided annual data on tillage activity at the county level
since 1989, with adjustments for long-term adoption of no-till
agriculture (Towery 2001). Information on fertilizer use and
rates by crop type for different regions of the United States
were obtained primarily from the USDA Economic Research
Service Cropping Practices Survey (ERS 1997) with
additional data from other sources, including the National
Agricultural Statistics Service (NASS 1992, 1999, 2004).
Frequency and rates of manure application to cropland during
the inventory period were estimated from data compiled by
the USDANatural Resources Conservation Service for 1997
(Edmonds et al. 2003).
Monthly weather data, aggregated to county-scale
from the Parameter-elevation Regressions on Independent
Slopes Model (PRISM) database (Daly et al. 1994), were
used to drive the model simulations. Soil attributes were
obtained from an NRI database, which were assigned based
on field visits and soil series descriptions. Where more than
one inventory point was located in the same county (i.e.,
same weather) and having the same land-use/management
histories and soil type, data inputs to the model were identical
and, therefore, these points were clustered for simulation
purposes. For the 370,738 NRI points representing non-
federal cropland and grassland, there were a total of 170,279
clustered points that represent the unique combinations of
climate, soils, land use, and management in the modeled data
set. Each NRI cluster point was run 100 times as part of the
uncertainty assessment, yielding a total of over 14 million
simulation runs for the analysis. Carbon stock estimates
from Century were adjusted using a structural uncertainty
estimator accounting for uncertainty in model algorithms and
parameter values. Mean changes in C stocks and 95 percent
confidence intervals were estimated for 1990 to 1994 and
1995 to 2000 (see Uncertainty section for more details). C
stock changes from 2001 to 2004 were assumed to be similar
to the 1995 to 2000 block because no additional activity data
are currently available from the NRI for the latter years.
Tier 2 Approach
Mineral SOC stocks were estimated using a Tier 2
method for vegetable crops, tobacco, perennial/horticultural
crops and rice in 1982,1992, and 1997. In addition, the Tier
2 method was used to estimate C stock changes for crops that
were rotated with vegetables, tobacco, perennial/horticultural
crops and rice. The Century model has not been fully tested
to address its adequacy for estimating C stock changes
associated with these crops and rotations. Data on climate,
soil types, land-use, and land management activity were
used to classify land area to apply appropriate stock change
factors. Major Land Resource Areas (MLRA) formed the base
spatial unit for mapping climate regions in the United States;
each Major Land Resource Area represents a geographic
unit with relatively similar soils, climate, water resources,
and land uses (NRCS 1981).8 Major Land Resource Areas
were classified into climate regions according to the IPCC
categories using the PRISM climate-mapping program of
Daly etal. (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 the Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC/
UNEP/OECD/IEA1997) and IPCC Good Practice Guidance
for Land Use, Land-Use Change, and Forestry (IPCC 2003).
Changing the reference condition was necessary because
soil measurements under agricultural management are much
more common and easily identified in the National Soil
8 The polygons displayed in Figure 7-4 through Figure 7-7 are the Major Land Resource Areas.
Land Use, Land-Use Change, and Forestry 7-19
-------
Survey Characterization Database (NRCS 1997) than those
which are not considered cultivated cropland.
U.S.-specific stock change factors were derived from
published literature to determine the impact of management
practices on SOC storage, including changes in tillage,
cropping rotations and intensification, and land-use change
between cultivated and uncultivated conditions (Ogle et
al. 2003, Ogle et al. 2006b).9 U.S. factors associated with
organic matter amendments were not estimated because of
an insufficient number of studies to analyze those impacts.
Instead, factors from IPCC Good Practice Guidance for Land
Use, Land-Use Change, andForestry(lPCC2(X)3) were used
to estimate the effect of those activities. Euliss and Gleason
(2002) provided the data for computing the change in SOC
storage resulting from restoration of wetland enrolled in the
Conservation Reserve Program.
Similar to the Tier 3 Century Inventory, activity
data were primarily based on the historical land-use/
management patterns recorded in the NRI. Each NRI point
was classified by land use, soil type, climate region (using
PRISM data, Daly et al. 1994) and management condition.
Classification of cropland area by tillage practice was based
on data from the Conservation Tillage Information Center
(CTIC 1998, Towery 2000) as described above. Euliss
and Gleason (2002) provided activity data on wetland
restoration of Conservation Reserve Program Land. Manure
N amendments over the inventory time period were based
on application rates and areas amended with manure N from
Edmonds et al. (2003).
Combining information from these data sources, SOC
stocks for mineral soils were estimated 50,000 times for
1982, 1992, and 1997, using a Monte Carlo simulation
approach and the probability distribution functions for
U.S.-specific stock change factors, reference C stocks, and
land-use activity data (Ogle et al. 2002, Ogle et al. 2003).
The annual C flux for 1990 through 1992 was determined by
calculating the annual change in stocks between 1982 and
1992; annual C flux for 1993 through 2004 was determined
by calculating the annual change in stocks between 1992
and 1997.
Additional Mineral C Stock Change Calculations
Annual C flux estimates for mineral soils between 1990
and 2004 were adjusted to account for additional C stock
changes associated with variation in manure N production
and thus areas amended with manure relative to 1997, as
well as gains or losses in C sequestration after 1997 due to
changes in Conservation Reserve Program enrollment.
Manure N application rates and cropland areas receiving
manure amendments were based on 1997 estimates from
Edmonds et al. (2003) for the Tier 3 Century simulations
and the Tier 2 IPCC methods (described above). However,
manure N production^ varies from year to year (see Annex
3.13, Table A-204), and thus the amendment rates also vary
through time. Consequently, manure N production data were
used to approximate the relative amount of manure available
for application based on the difference between manure N
production in 1997 and other years in the reporting period.
Higher manure N production relative to 1997 was assumed to
increase the amount of area amended with manure, and thus
lead to more soil C storage, while less manure N production
relative to 1997 was assumed to reduce the amount of C
added to soils from this activity. The rate of increase or
decrease in soil C stocks was estimated at 0.22 metric tons
C per hectare per year for the net increase or decrease in
amended land area, which depended on the available manure
N for application relative to 1997. The stock change rate is
based on country-specific factors using the IPCC method
(see Annex 3.13 for further discussion).
To estimate the impact of enrollment in the Conservation
Reserve Program after 1997, the change in enrollment
acreage relative to 1997 was derived based on Barbarika
(2004) for 1998 through 2004, and the differences in mineral
soil areas were multiplied by 0.5 metric tons C per hectare per
year. Similar to manure amendments, the stock change rate
is based on country-specific factors using the IPCC method
(see Annex 3.13 for further discussion).
Organic Soils
Annual C emissions from drained organic soils in
cropland were estimated using methods provided in the
9 Stock change factors have been derived from published literature to reflect changes in tillage, cropping rotations and intensification, land-use change
between cultivated and uncultivated conditions, and drainage of organic soils.
10 Manure N production does not include the Pasture/Range/Paddock manure for this analysis. Also, the poultry manure production values have been
reduced by 4.8 percent that is used for feed.
7-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Revised 1996IPCCGuidelines for National Greenhouse Gas
Inventories (IPCC/UNEP/OECD/IEA 1997) and the IPCC
Good Practice Guidance for Land Use, Land-Use Change,
and Forestry (IPCC 2003), except that U.S.-specific C loss
rates were used in the calculations rather than default IPCC
rates (Ogle et al. 2003). Similar to mineral soils, the final
estimates included a measure of uncertainty as determined
from the Monte Carlo simulation with 50,000 iterations.
Emissions were based on the 1992 and 1997 cropland areas
from the 1997 National Resources Inventory(VSDA-NRCS
2000). The annual flux estimated for 1992 was applied to
1990 through 1992, and the annual flux estimated for 1997
was applied to 1993 through 2004.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone
and dolomite applied to agricultural soils were estimated
using a Tier 2 methodology. The annual amounts of limestone
and dolomite applied (see Table 7-13) were multiplied by
C02 emission factors from West and McBride (2005). These
emission factors (0.059 metric ton C/metric ton limestone,
0.064 metric ton C/metric ton dolomite) are lower than the
IPCC default emission factors, because they account for the
portion of agricultural lime that may leach through the soil
and travel by rivers to the ocean (West and McBride 2005).
The annual application rates of limestone and dolomite
were derived from estimates and industry statistics provided
in the Minerals Yearbook and Mineral Industry Surveys
(Tepordei 1993,1994, 1995,1996, 1997,1998,1999, 2000,
2001, 2002, 2003a, 2004, 2005; USGS 2005). To develop
these data, USGS (U.S. Bureau of Mines prior to 1997)
obtained production and use information by surveying
crushed stone manufacturers. Because some manufacturers
were reluctant to provide information, the estimates of total
crushed limestone and dolomite production and use were
divided into three components: (1) production by end-use,
as reported by manufacturers (i.e., "specified" production);
(2) production reported by manufacturers without end-uses
specified (i.e., "unspecified" production); and (3) estimated
additional production by manufacturers who did not respond
to the survey (i.e., "estimated" production).
The "unspecified" and "estimated" amounts of crushed
limestone and dolomite applied to agricultural soils were
calculated by multiplying the percentage of total "specified"
limestone and dolomite production applied to agricultural
soils by the total amounts of "unspecified" and "estimated"
limestone and dolomite production. In other words, the
proportion of total "unspecified" and "estimated" crushed
limestone and dolomite that was applied to agricultural
soils (as opposed to other uses of the stone) was assumed
to be proportionate to the amount of "specified" crushed
limestone and dolomite that was applied to agricultural
soils. In addition, data were not available for 1990, 1992,
and 2004 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 2004 data, the previous year's fractions were
applied to a 2004 estimate of total crushed stone presented
in the USGS Mineral Industry Surveys: Crushed Stone
and Sand and Gravel in the First Quarter of 2005 (USGS
2005).
The primary source for limestone and dolomite activity
data is the Minerals Yearbook, published by the Bureau of
Mines through 1994 and by the U.S. Geological Survey
from 1995 to the present. In 1994, the "Crushed Stone"
chapter in the Minerals Yearbook began rounding (to the
nearest thousand) quantities for total crushed stone produced
or used. It then reported revised (rounded) quantities for
each of the years from 1990 to 1993. In order to minimize
the inconsistencies in the activity data, these revised
production numbers have been used in all of the subsequent
calculations.
Table 7-13: Applied Minerals (Million Metric Tons)
Mineral
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Limestone 19.01 20.31 17.98 15.61 16.69 17.30 17.48 16.54 14.88 16.89 15.86 16.10 20.45 14.73 15.71
D Dolomite 2.36 2.62 2.23 1.74 2.26 2.77 2.50 2.99 6.39 3.42 3.81 3.95 2.35 2.25 2.40
Note: These numbers represent amounts applied to all agricultural land, not just Cropland Remaining Cropland.
Land Use, Land-Use Change, and Forestry 7-21
-------
Uncertainty
Uncertainty associated with the Cropland Remaining
Cropland category includes the uncertainty associated with
changes in agricultural soil carbon stocks (including both
mineral and organic soils) and soil liming emissions.
Mineral and Organic Soil Carbon Stock Changes
Uncertainties in Mineral Soil C Stock Changes
Tier 3 Approach
The uncertainty analysis for the Tier 3 Century inventory
had three components: (1) Monte-Carlo approach to address
uncertainties in model inputs, (2) an empirically-based
approach for quantifying uncertainty inherent in the structure
of the Century model, and (3) scaling uncertainty associated
with the NRI survey (i.e., scaling from the individual NRI
points to the entire U.S. agricultural land base using the
expansion factors).
For the model input uncertainty, probability distribution
functions (PDFs) were developed for fertilizer rates, manure
application, and tillage practices. PDFs for fertilizer were
based on survey data for major U.S. crops, both irrigated
and rainfed (ERS 1997; NASS 2004, 1999, 1992; Grant
and Krenz 1985). State-level PDFs were developed for
each crop if a minimum of 15 data points existed for each
of the two categories (irrigated and rainfed). Where data
were insufficient at the state-level, PDFs were developed
for multi-state Farm Production Regions. Uncertainty in
manure applications for specific crops was incorporated
in the analysis based on total manure available for use in
each county, a weighted average application rate, and the
crop-specific land area amended with manure (compiled
from USDA data on animal numbers, manure production,
storage practices, application rates and associated land areas
receiving manure amendments - see Edmonds et al. 2003).
Together with the total area for each crop within a county,
this yielded a probability that a given crop at a specific NRI
point would either receive manure or not in the Monte Carlo
analysis. If soils were amended with manure, a reduction
factor was applied to the N fertilization rate accounting for the
interaction between fertilization and manure N amendments
(i.e., producers often reduce mineral fertilization rates if
applying manure). Reduction factors were randomly selected
from probability distribution factors based on relationships
between manure N application and fertilizer rates (ERS
1997). For tillage uncertainty, transition matrices were
constructed from CTIC data to represent tillage changes for
two time periods, combining the first two and the second
two management blocks (i.e., 1980-1989, 1990-2000). A
Monte Carlo analysis was conducted with 100 iterations in
which inputs values were randomly drawn from the PDFs
to simulate the soil C stocks for each NRI cluster of points
(i.e., inventory points in the same county were grouped into
clusters if they had the same land-use/management history
and soil type) using the Century model.
An empirically-based uncertainty estimator was
developed to assess uncertainty in model structure associated
with the algorithms and parameterization. The estimator
was based on a linear mixed effect modeling analysis
comparing modeled soil C stocks with field measurements
from 45 long-term agricultural experiments with over 800
treatments, representing a variety of tillage, cropping, and
fertilizer management practices (Ogle et al. 2006a). The final
model included variables for organic matter amendments, N
fertilizer rates, inclusion of hay/pasture in cropping rotations,
use of no-till, setting-aside cropland from production,
and inclusion of bare fallow in the rotation. Each of these
variables met an alpha level of 0.05, and accounted for
significant biases in the modeled estimates from Century.
For example, Century tended to under-estimate the influence
of organic amendments on soil C storage, so a variable
was added to adjust the estimate from Century. Random
Table 7-14: Tier 2 Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils occurring within
Cropland Remaining Cropland that were Estimated Using the Tier 3 Approach (Tg C02 Eq. and Percent)
Source
Mineral Soil C Stocks: Cropland
Remaining Cropland
Change Estimate Uncertainty Range Relative to Stock Change Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound
(62.5) (60.9)
Upper Bound
(64.2)
Lower Bound
-3%
Upper Bound
+ 3%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
7-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
effects captured the dependence in time series and data
collected from the same long-term experimental site, which
were needed to estimate appropriate standard deviations
for parameter coefficients. For each carbon stock estimate
from the Monte Carlo analysis, the structural uncertainty
estimator was applied to adjust the value accounting for bias
and prediction error in the modeled values.
Finally, uncertainty in the land-use and management
statistics from the NRI were incorporated into the analysis
based on the sampling variance for the clusters of NRI
points. The emission estimate for 2004 and associated 95
percent confidence interval are provided in Table 7-14. The
uncertainty in the inventory estimate of 62.5 Tg C02Eq.
was +3 percent for Cropland Remaining Cropland that
were estimated using the Tier 3 model-based inventory
approach.
Tier 2 Approach
For the Tier 2 IPCC method, a Monte Carlo approach
was used to simulate a range of values with 50,000 iterations
by randomly selecting values from probability distribution
functions (Ogle et al. 2003). PDFs for stock change factors
were derived from a synthesis of 91 published studies,
which addressed the impact of management on SOC
storage. Uncertainties in land-use and management activity
data were also derived from a statistical analysis. The NRI
has a two-stage sampling design that allowed PDFs to be
constructed assuming a multivariate normal distribution
accounting for dependencies in activity data. PDFs for
the tillage activity data, as provided by the CTIC, were
constructed on a bivariate normal distribution with a log-
ratio scale, accounting for the negative dependence among
the proportions of land under conventional and conservation
tillage practices. PDFs for the agricultural areas receiving
manure were derived assuming a normal distribution from
county-scale area amendment estimates derived from the
USDA Census of Agriculture (Edmonds etal. 2003). Lastly,
enrollment in wetland restoration programs was estimated
from contract agreements, but due to a lack of information,
PDFs were constructed assuming a nominal +50 percent
uncertainty range.
The results of the uncertainty analysis for the Tier
2 portion of the analysis are summarized in Table 7-15.
Mineral soils in Cropland Remaining Cropland, which were
estimated using the Tier 2 approach, had a stock change
between a gain of 4.03 to a loss of 6.6 Tg CO2 Eq., at a
95 percent confidence level. This indicates a range of 430
percent below to 441 percent above the 2004 stock change
estimate of 1.22 Tg C02 Eq.
Additional Mineral C Stock Change Calculations
A +50 percent uncertainty was assumed for additional
adjustments to the mineral soil C stocks between 1990 and
2004, accounting for additional C stock changes associated
with variation in manure N production and thus areas
amended with manure relative to 1997, as well as gains
or losses in C sequestration after 1997 due to changes in
Conservation Reserve Program enrollment. The estimated
adjustment for 2004 and associated 95 percent confidence
interval are provided in Table 7-16.
Uncertainties in Organic Soil C Stock Changes
Uncertainty in carbon emissions from organic soils
were estimated in the same manner described for mineral
soil using the Tier 2 method and Monte Carlo Analysis.
PDFs for emission factors were derived from a synthesis
of 10 studies, and combined with uncertainties in the NRI
land use and management data for organic soils in the Monte
Carlo Analysis. See the Tier 2 section under Minerals Soils
(above) for additional discussion. Organic soils in cropland
were estimated to emit between 20.2 and 43.3 Tg CO2 Eq.
at a 95 percent confidence level (Table 7-17). This indicates
a range of 33 percent below to 43 percent above the 2004
stock change estimate of 30.3 Tg CO2 Eq.
Table 7-15: Tier 2 Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within
Cropland Remaining Cropland that were Estimated Using the Tier 2 Approach (Tg C02 Eq. and Percent)
Source
Mineral Soil C Stocks: Cropland
Remaining Cropland
Change Estimate Uncertainty Range Relative to Stock Change Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound
1.2 (4.0)
Upper Bound
6.6
Lower Bound
-430%
Upper Bound
+441%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Land Use, Land-Use Change, and Forestry 7-23
-------
Table 7-16: Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within Cropland Remaining
Cropland that were Estimated Using the Tier 1 Approach (Tg C02 Eq. and Percent)
Source
2004 Stock
Change Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Stock Change Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Mineral Soil C Stocks: Cropland
Remaining Cropland (Variation in
Manure Amendments Relative to 1997) (0.4)
Mineral Soil C Stocks: Cropland
Remaining Cropland (Change in CRP
enrollment relative to 1997) (1.5)
(0.6)
(2.3)
(0.2)
(0.8)
-50%
-50%
+50%
+50%
Table 7-17: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Organic Soils Occurring Within
Cropland Remaining Cropland (Tg C02 Eq. and Percent)
Source
Organic Soil C Stocks: Cropland
Remaining Cropland"
Chanqe Estimate Uncertainty Range Relative to Stock Change Estimate3
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound
30.3 20.2
Upper Bound
43.3
Lower Bound
-33%
Upper Bound
+43%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
b Cropland Remaining Cropland and Land Converted to Cropland are both reported in this section because cropland on organic soils has not been
subdivided into land use/land use-change categories.
Additional Uncertainties in Mineral and Organic Soil
C Stock Changes
The time-series calculations were consistent for each
reporting year of the inventory in terms of methodology,
with the only difference in reported values stemming from
the changes in land-use and management activities across
U.S. agricultural land. For the Tier 2 method, the same stock
change and organic soil emission factors (i.e., emission
factors) were used each year in order to calculate the impact
of land use and management on SOC stocks. Moreover,
parameterization of the Tier 3 model was not adjusted from
year to year. There is no evidence that changing management
practices has a quantitatively different impact on SOC stocks
over the inventory period as represented in each of these
models, and it was assumed the Tier 2 stock change/emission
factors and Tier 3 parameters were robust for addressing
land-use and management impacts over the time series.
The agricultural soil C inventory has undergone
several improvements during the past few years, such as
the development of the Tier 3 inventory method to estimate
mineral soil C stock changes for the majority of U.S.
cropland. However, some limitations remain in the analysis.
First, the current agricultural soil C inventory includes some
points designated as non-agricultural land-uses in the NRI if
the points were categorized as agricultural land use in either
1992 or 1997, but were urban, water, or miscellaneous non-
cropland (e.g., roads and barren areas) in the other year. The
impact on SOC storage that results from converting cropland
to non-agricultural uses is not well-understood, and therefore,
those points were not included in the calculations for mineral
soils (emissions from organic soils, however, were computed
for those points in the years that they were designated as an
agricultural use). Similarly, the effect of aquaculture (e.g.,
rice cultivation followed by crayfish production in flooded
fields) on soil C stocks has not been estimated due to a lack of
knowledge. Second, the current estimates may underestimate
losses of C from organic soils because the 1997 National
Resources Inventory was not designed as a soil survey and
organic soils frequently occur as relatively small inclusions
within major soil types. Lastly, this methodology does not
take into account changes in SOC stocks due to pre-1982
land use and land-use change.
7-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table 7-18: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Liming of Agricultural Soils
(Tg C02 Eq. and Percent)
Source
Gas
2004 Emissions
(Tg C02 Eq.)
Uncertainty Range Relative to Flux Estimate3
(Tg C02 Eq.) (%)
Lower
Bound Upper Bound
Lower Bound Upper Bound
Liming of Agricultural Soils"
CO?
4.0
0.3
7.8
+96%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
b Also includes emissions from liming in Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.
Uncertainties in C02 Emissions from Liming
Uncertainties in the estimates of emissions from liming
result from both the emission factors and the activity data.
The emission factors used for limestone and dolomite take
into account the fate of carbon following application to
soils, including: dissolution of liming constituents; leaching
of bicarbonates into the soil and transport to the ocean; and
emissions to the atmosphere (West and McBride 2005). The
carbon accounting behind these emission factors entails
assumptions about several uncertain factors. First, it is
uncertain what fraction of agricultural lime is dissolved
by nitric acid (HNO3)—a process that releases C02—and
what portion reacts with carbonic acid (H2C03), resulting
in the uptake of CO2. The fractions can vary depending
on soil pH and nitrogen fertilizer use. The second major
source of uncertainty is the fraction of bicarbonate (HCO3)
that leaches through the soil profile and is transported into
groundwater, which can eventually be transferred into rivers
and into the ocean. This fraction can vary depending on the
soil pH and whether calcium (Ca2+) and magnesium (Mg2+)
liming constituents that might otherwise accompany HCO3,
are taken up by crops, remain in the upper soil profile, or
are transported through or out of the soil profile. Finally, the
emission factors do not account for the time that is needed
for leaching and transport processes to occur.
There are several sources of uncertainty in the
limestone and dolomite activity data. When reporting data
to the USGS (or U.S. Bureau of Mines), some producers do
not distinguish between limestone and dolomite. In these
cases, data are reported as limestone, so this reporting
could lead to an overestimation of limestone and an
underestimation of dolomite. In addition, the total quantity
of crushed stone listed each year in the Minerals Yearbook
excludes American Samoa, Guam, Puerto Rico, and the
U.S. Virgin Islands.
Uncertainty regarding limestone and dolomite activity
data inputs were estimated at plus or minus 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
factors: 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
C02 emissions (West 2005). The uncertainty associated with
the fraction of agricultural lime dissolved by nitric acid and
the portion of bicarbonate that leaches through the soil were
each modeled as a smoothed triangular distribution between
ranges of 0 percent to 100 percent.
A Monte Carlo (Tier 2) uncertainty analysis was applied
to estimate the uncertainty of C02 emissions from liming.
The results of the Tier 2 quantitative uncertainty analysis are
summarized in Table 7-18. Carbon dioxide emissions from
Liming of Agricultural Soils in 2004 were estimated to be
between 0.3 and 7.8 Tg CO2 Eq. at the 95 percent confidence
level. This indicates a range of 94 percent below to 96 percent
above the 2004 emission estimate of 4.0 Tg CO2 Eq.
QA/QC and Verification
With the development of a Tier 3 inventory, there was
considerable effort required to review inventory procedures
and results. Quality control measures included checking
input data, model execution scripts, and results to ensure data
were properly handled through the inventory process. Errors
were found in these steps and corrective actions were taken.
Results were compared against field measurements and a
statistical relationship was developed to assess uncertainties
in the model's predictive capability (discussed under the
Land Use, Land-Use Change, and Forestry 7-25
-------
Uncertainty section). The comparisons included over 40
long-term experiments, representing about 800 combinations
of management treatments across all of the sites. Inventory
reporting forms and text were reviewed and revised as needed
to correct transcription errors.
Recalculations Discussion
The key difference in the current inventory compared
to previous years is in the implementation of the Tier 3
model-based approach for mineral soils, which was used
to estimate soil C stock changes in Agricultural Land (i.e.,
Cropland Remaining Cropland, Land Converted to Cropland,
Grassland Remaining Grassland, and Land Converted to
Grassland). This entails several fundamental differences
compared with the IPCC Tier 2 method, which is based on
a classification of land areas into a number of discrete states
based on a highly aggregated classification of climate, soil,
and management (i.e., only 6 climate regions and 7 soil
types and 11 management systems occur in U.S. agricultural
land. Input variables to the Tier 3 model, including climate,
soils, and management activities (e.g., fertilization, crop
species, tillage, etc.), are represented in considerably more
detail both temporally and spatially, and exhibit multi-
dimensional interactions through the more complex model
structure compared with the IPCC Tier 2 approach. The
spatial resolution of the analysis is also finer in the Tier 3
method compared to the Tier 2 inventory (3037 counties vs.
181 MLRAs, respectively).
In the Century model, soil C dynamics (and C02
emissions and uptake) are treated as continuous variables,
which change on a monthly time step. Carbon emissions
and removals are an outcome of plant production and
decomposition processes, which are simulated in the model
structure. Thus, changes in soil C stocks are influenced
by not only changes in land use and management but also
inter-annual climate variability and secondary feedbacks
between management activities, climate and soils as they
affect primary production and decomposition. This latter
characteristic constitutes one of the greatest differences
between the methods, and forms the basis for a more
complete accounting of soil C stock changes in the Tier 3
approach compared with Tier 2 methodology.
Because the Tier 3 model simulates a continuous time
period rather than as an equilibrium step change used in
the IPCC methodology (Tier 1 and 2), the Tier 3 model
addresses the delayed response of the soil to management
and land-use changes, which can occur due to variable
weather patterns and other environmental constraints that
interact with land use and management and affect the time
frame over which stock changes occur. Moreover, the Tier
3 method also accounts for the overall effect of increasing
yields and, hence, C input to soils that have taken place across
management systems and crop types within the United States.
Productivity has increased by 1 to 2 percent annually over
the past 4 to 5 decades for most major crops in the United
States (Reilly and Fuglie 1998), which is believed to have
led to increases in cropland soil C stocks (e.g., Allmaras et al.
2000). This is a major difference from the IPCC-based Tier
2 approach in which soil C stocks change only with discrete
changes in management and/or land use, rather than a longer
term trend such as gradual increases in crop productivity.
By addressing these additional management influences on
soil C stocks, the Tier 3 approach produced C stock change
estimates that were 27-50 percent greater than the Tier 2
inventory approach used to report agricultural soil C in the
previous year As noted above, these estimates include the
C stock changes for Cropland Remaining Cropland, Land
Converted to Cropland, Grassland Remaining Grassland,
and Land Converted to Grassland.
A small adjustment was also made in the estimation of
organic soils. There are some areas included in the land base
that were converted during the 1990s between agricultural
land and forest, miscellaneous non-agricultural, and urban
land. In past inventories, emissions from drained organic
soils were reported in this inventory even during the years
that the land parcels were under a non-agricultural land
use. These areas were removed in this year's inventory,
and a re-calculation was done to obtain a more accurate
C02 emissions estimate from drained organic soils under
agricultural management. Estimated values were reduced
by about 0.6 Tg CO2 Eq. in each reporting year.
The quantity of applied minerals reported in the previous
inventory for 2003 has been revised. Consequently, the
reported emissions resulting from liming in 2003 have also
changed. In the previous inventory, to estimate 2003 data, the
previous year's fractions were applied to a 2003 estimate of
total crushed stone presented in the USGS Mineral Industry
Surveys: Crushed Stone and Sand and Gravel in the First
Quarter of 2004 (USGS 2004). Since publication of the
previous inventory, the Minerals Yearbook has published
7-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
actual quantities of crushed stone sold or used by producers in
the United States in 2003. 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 emission factors used in the calculation of emissions
due to liming have changed since the previous inventory.
Previously, the default emission factor values from the
Revised 1996 IPCC Guidelines for National Greenhouse
Gas Inventories (IPCC/UNEP/OECD/IEA 1997) and the
IPCC Good Practice Guidance for Land Use, Land-Use
Change, and Forestry (IPCC 2003) formed the basis for
these calculations using the IPCC Tier 1 method. A study
published in 2005 provides new emission factors based on
a more detailed accounting of the fate of carbon following
application to soils (West and McBride 2005). The IPCC
Tier 1 approach assumes that all inorganic C in the applied
minerals evolves to C02. It is more likely, though, that
some of the carbon may leach through the soil and travel
by rivers to the ocean, where it precipitates as CaCO3. Use
of these new emission factors represents a Tier 2 approach
as described in IPCC (2003), which should result in a more
accurate accounting of emissions due to liming.
Overall, these changes resulted in an average annual
decrease of 35.7 Tg CO2 Eq. (224 percent) in agricultural
soil carbon stocks for the period 1990 through 2003.
Planned Improvements
Four major improvements are planned for the next
year. The first improvement is to incorporate new land-use
and management activity data from the NRI. In the current
inventory, NRI data only provide land-use and management
statistics through 1997, but it is anticipated that new statistics
will be released in the coming year for 2000 through 2003.
This will greatly improve the accuracy of land-use and
management influences on soil C in the latter part of the
time series.
The second planned improvement will be to achieve
consistency in N fertilization rates and organic amendments
between the soil C and soil N20 inventories. Currently, each
inventory is using a combination of shared and different
sources to model these activities. The goal will be to
ensure that each is using the most accurate information in a
consistent manner.
The third improvement is to develop a consistent
representation of the U.S. managed land base. More details
on this planned improvement are provided previously in
the chapter under Forest Land Remaining Forest Land. In
addition, agricultural areas on organic soils and the mineral
soils, which are estimated with the Tier 2 approach, will
be further subdivided into land use and land-use change
subcategories in order to achieve consistency with reporting
requirements.
The last improvement will be to further develop the
uncertainty analysis to address the uncertainty inherent in the
Century model results for agricultural land (i.e., Grassland
Remaining Grassland, Land Converted to Grassland, and
Land Converted to Cropland) in the Tier 3 method. In
addition, uncertainties need to be addressed in the simulation
of soil C stocks for the pre-NRI time period (i.e., before
1979). In the current analysis, inventory development
focused on uncertainties in the last two decades because the
management activity during the most recent time periods
will likely have the largest impact on current trends in soil
C storage. However, legacy effects of past management
can also have a significant effect on current C stock trends,
as well as trajectories of those C stocks in the near future.
Therefore, a planned improvement in the upcoming year is to
revise the inventory to address uncertainties in management
activity prior to 1979.
7.4. Land Converted to Cropland
(IPCC Source Category 5B2)
Background on agricultural carbon stock changes is
provided in the Cropland Remaining Cropland (Section
1.3.1) and will only be summarized here. 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 Revised 1996 IPCC Guidelines
for National Greenhouse Gas Inventories (IPCC/UNEP/
OECD/IEA 1997) and the IPCC Good Practice Guidance
for Land Use, Land-Use Change, andForestry (IPCC 2003)
recommend reporting changes in soil organic C stocks due
to: (1) agricultural land-use and management activities on
mineral soils; (2) agricultural land-use and management
activities on organic soils, and (3) C02 emissions that result
from liming of soils with dolomite and limestone. Mineral
soil C stock changes are reported here for Land Converted to
Cropland, but stock changes associated with management of
Land Use, Land-Use Change, and Forestry 7-27
-------
organic soils and liming are reported in Cropland Remaining
Cropland because it was not possible to subdivide those
estimates by land use and land-use change categories (see
Methodology section below for additional discussion).
Land-use and management of mineral soils in Land
Converted to Cropland led to small losses of soil C during
the early 1990s but this trend was reversed over the decade,
so that these soils were gaining small amounts of C through
the latter part of the time series (Table 7-19 and Table 7-20).
The rate of change in soil C stocks was 2.8 Tg CO2 Eq. (0.8
Tg C) in 2004.
The spatial variability in annual CO2 flux associated
with C stock changes in mineral soils for Land Converted
to Cropland is displayed in Figure 7-8 and Figure 7-9. While
a large portion of the United States had net losses in soil C
for Land Converted to Cropland, there were some notable
areas with sequestration in the intermountain west and
Central United States. These areas were gaining C following
conversion because the cropland were irrigated or receiving
higher fertilizer inputs relative to the previous land use.
The estimates presented here are restricted to C stock
changes associated with land use and management of
agricultural soils. Agricultural soils are also important
sources of other greenhouse gases, particularly N20 from
application of fertilizers, manure, and crop residues and
from cultivation of legumes, as well as methane (CH4) from
flooded rice cultivation. These emissions are accounted for
under the Agriculture sector, along with non-CO2 greenhouse
gas emissions from field burning of crop residues and CH4
and N2O emissions from livestock digestion and manure
management.
Methodology
The following section includes a description of the
methodology used to estimate changes in soil carbon stocks
due to agricultural land-use and management activities on
mineral soils for Land Converted to Cropland.
Mineral and Organic Soil Carbon Stock Changes
Soil C stock changes were estimated for Land Converted
to Cropland according to land-use histories recorded in the
USDA National Resources Inventory (NRI) survey (USDA-
NRCS 2000)." Land use and some management information
(e.g., crop type, soil attributes, and irrigation) were collected
for each NRI point on a 5-year cycle beginning in 1982. NRI
points were classified as Land Converted to Cropland if the
land use was currently cropland but had been converted from
Table 7-19: Net Soil C Stock Changes in Land Converted to Cropland (Tg C02 Eq.)
Soil Type
Mineral Soils
Organic Soils3
Liming of Soils3
Total Net Flux
1990
1.5
1.5
1998
(2.8)
(2.8)
1999
(2.8)
(2.8)
2000
(2.8)
(2.8)
2001
(2.8)
(2.8)
2002
(2.8)
(2.8)
2003
(2.8)
(2.8)
2004
(2.8)
(2.8)
a Emissions from liming and organic soils from Land Converted to Cropland are reported in Cropland Remaining Cropland
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values
are based on historical data only.
Table 7-20: Net Soil C Stock Changes in Land Converted to Cropland (Tg C)
Soil Type
1990
1998
1999
2000
2001
2002
2003
2004
Mineral Soils
Organic Soils3
Liming of Soils3
0.4
(0.8)
(0.8)
(0.8)
(0.8)
(0.8)
(0.8)
(0.8)
Total Net Flux
0.4
(0.8) (0.8) (0.8) (0.8)
(0.8) (0.8)
(0.8)
a Emissions from liming and organic soils from Land Converted to Cropland are reported in Cropland Remaining Cropland
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values
are based on historical data only.
11 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
7-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 7-8
Net C Stock Change for Mineral Soils in Land Converted to Cropland, 1990-1992
Tg C02 Eq/yr
n Oto2
n-0.1 toO
n-0.5 to-0.1
• -Ko-0.5
• -1.1(0-1
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes
associated with the Tier 3 inventory computations. See Methodology for additional details.
This map shows the spatial variability in net carbon stock change for mineral soils for the years 1990 through 1992. The color assigned to each polygon
represents the total annual flux for the area of managed mineral soils in that polygon.
Figure 7-9
Net C Stock Change for Mineral Soils in Land Converted to Cropland, 1993-2004
Tg C02 Eq/yr
n 0 to 0.5
D-0.1 toO
n-0.5 to-0.1
• -0.8(0-0.5
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes
associated with the Tier 3 inventory computations. See Methodology for additional details.
This map shows the spatial variability in net carbon stock change for mineral soils for the years 1993 through 2004. The color assigned to each polygon
represents the total annual flux for the area of managed mineral soils in that polygon.
Land Use, Land-Use Change, and Forestry 7-29
-------
another use since 1982. Cropland includes all land used to
produce food or fiber, as well as forage that is harvested and
used as feed (e.g., hay and silage).
A new Tier 3 model-based approach was developed
to estimate C stock changes for soils on Land Converted
to Cropland used to produce a majority of annual crops in
the United States (i.e., all crops except vegetables, tobacco,
perennial/horticultural crops, and rice), in addition to C stock
changes for grassland soils. An IPCC Tier 2 method was used
to estimate C stock changes on the remaining land base for
Land Converted to Cropland on mineral soils that were not
addressed with the Tier 3 method, in addition to emission
estimates for organic soils (Ogle et al. 2003). Tier 1 methods
were used to estimate additional changes in mineral soil C
stocks due to manure amendments that were not included in
the Tier 2 and 3 analyses.
Further elaboration on the methodologies and data used
to estimate stock changes for mineral and organic soils are
provided in the Cropland Remaining Cropland section and
Annex 3.13.
Mineral Soils
Tier 3 Approach
Mineral SOC stocks and stock changes were estimated
using the Century biogeochemical model for grassland
converted to cropland, with the exception of vegetable crops,
tobacco, perennial/horticultural crops, and rice. National
estimates were obtained by using the model to simulate
historical land-use change patterns as recorded in the USDA
National Resources Inventory.
Tier 2 Approach
Mineral SOC stock changes were estimated using a Tier
2 Approach for land converted from forest or federal land
to cropland, in addition to grassland converted to perennial,
horticultural, tobacco and rice cropland. These cropland
areas have not been subdivided into land use/land-use change
categories, which is a planned improvement for the soil C
inventory. Consequently the stock changes are reported in
Cropland Remaining Cropland.
Additional Mineral C Stock Change Calculations
Annual C stock changes for Land Converted to Cropland
on mineral soils between 1990 and 2004 were adjusted to
account for additional C stock changes associated with
variation in manure N production (see Annex 3.13, Table A-
195) and thus areas amended with manure relative to 1997.
Additional changes are reported in the Cropland Remaining
Cropland section because it is not possible to subdivide
these changes into the individual land use/land-use change
categories.
Organic Soils
Annual C emission estimates from drained organic
soils in Land Converted to Cropland were estimated using
the Tier 2 Approach, and reported in Cropland Remaining
Cropland because organic soil areas have not subdivided into
land use/land-use change categories. Differentiating organic
soils between Land Converted to Cropland and Cropland
Remaining Cropland is a planned future improvement for
the soil C inventory.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone
and dolomite applied to Land Converted to Cropland are
reported in the Cropland Remaining Cropland, because it
was not possible to disaggregate liming application among
land use and land-use change categories.
Uncertainty
Uncertainty associated with the Land Converted to
Cropland category includes the uncertainty associated with
changes in mineral soil carbon stocks.
Mineral and Organic Soil Carbon Stock Changes
Uncertainties in Mineral Soil C Stock Changes
Tier 3 Approach
The uncertainty analysis for Land Converted to
Cropland using the Tier 3 approach was based on the same
method described for Cropland Remaining Cropland, except
that the uncertainty inherent in the structure of the Century
model was not addressed. The empirically-based uncertainty
estimator described in the Cropland Remaining Cropland
section has not been developed to estimate uncertainties in
Century model results for Land Converted to Cropland but
this is a planned improvement for the inventory. See the
Tier 3 approach for mineral soils under Cropland Remaining
Cropland for additional discussion. The inventory estimate
for 2004 and associated 95 percent confidence interval are
provided in Table 7-21. The uncertainty in the inventory
7-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 7-21: Quantitative Uncertainty Estimates for C stock changes in mineral soils occurring within Land Converted to
Cropland, which were estimated using the Tier 3 Approach (Tg C02 Eq. and Percent)
Change Estimate Uncertainty Range Relative to Stock Change Estimate
Source (Tg C02 Eg.) (Tg C02 Eg.) (%)
Lower Bound
Upper Bound
Lower Bound Upper Bound
Mineral Soil C Stocks: Land
Converted to Cropland
(2.8)
(2.2)
(3.3)
-22%
+ 17%
estimate of 2.8 Tg CO2 Eq. was 22 percent below the mean
and 17 percent above the mean.
Uncertainties in Organic Soil C Stock Changes
Annual C emission estimates from drained organic
soils in Land Converted to Cropland were estimated
using the Tier 2 Approach, and reported in the Cropland
Remaining Cropland Section because organic soil areas have
not subdivided into land use/land-use change categories.
Differentiating organic soils between Land Converted to
Cropland and Cropland Remaining Cropland is a planned
future improvement for the soil C inventory. See Cropland
Remaining Cropland for discussion on the uncertainty
estimation for drained organic soils in grasslands.
Additional Uncertainties in Mineral and Organic Soil
C Stock Changes
Additional uncertainties are discussed in Cropland
Remaining Cropland.
QA/QC and Verification
See Cropland Remaining Cropland.
Recalculations Discussion
See Cropland Remaining Cropland.
Planned Improvements
See Cropland Remaining Cropland.
7.5. Grassland Remaining
Grassland (IPCC Source Category
5C1)
Background on agricultural carbon stock changes is
provided in the Cropland Remaining Cropland section and
will only be summarized here. 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 Revised 1996 IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA1997)
and IPCC Good Practice Guidance for Land Use, Land-Use
Change, and Forestry (IPCC 2003) recommend reporting
changes in soil organic C stocks due to: (1) agricultural
land-use and management activities on mineral soils; (2)
agricultural land-use and management activities on organic
soils, and (3) C02 emissions that result from liming of soils
with dolomite and limestone. Mineral and organic soil C
stock changes are reported here for Grassland Remaining
Grassland, but stock changes associated with liming are
reported in Cropland Remaining Cropland because it was
not possible to subdivide those estimates by land use/land-
use change categories (see Methodology section below for
additional discussion).
Land-use and management of mineral soils in Grassland
Remaining Grassland increased soil C during the early 1990s,
but this trend was reversed over the decade, with small losses
of C prevailing during the latter part of the time series (see
Table 7-22 and Table 7-23). Organic soils lost about the
same amount of C in each year of the inventory. The overall
trend shifted from small increases in soil C during 1990 to
decreases during the latter years, estimated at 7.3 Tg CO2
Eq. (2.0 Tg C) in 2004.
The spatial variability in annual CO2 flux associated with
C stock changes in mineral and organic soils is displayed
in Figure 7-10 through Figure 7-13. The highest rates of
sequestration occurred in Major Land Resource Areas found
in the southern portion of the United States, although these
rates declined over the 1990s. Sequestration was driven
by irrigation and seeding legumes. Similar to Cropland
Remaining Cropland, emission rates from drained organic
Land Use, Land-Use Change, and Forestry 7-31
-------
Table 7-22: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C02 Eq.)
Soil Type
Mineral Soils
Organic Soils3
Liming of Soils"
Total Net Flux
1990
(8.8)
4.3
(4.5)
1998
2.9
4.6
7.5
1999
2.9
4.6
7.5
2000
2.9
4.6
7.4
2001
2.8
4.6
7.4
2002
2.8
4.6
7.4
2003
2.7
4.6
7.3
2004
2.7
4.6
7.3
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values
are based on historical data only.
a Also includes emissions due to drainage of organic soils in Land Converted to Grassland.
b Emissions from liming in Grassland Remaining Grassland are reported in Cropland Remaining Cropland.
Table 7-23: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C)
Soil Type
1990
1998
1999
2000
2001
2002
2003
2004
Mineral Soils
Organic Soils3
Liming of Soils"
(2.4)
1.2
0.8
1.3
0.8
1.3
0.8
1.3
0.8
1.3
0.8
1.3
0.7
1.3
0.7
1.3
Total Net Flux
(1.2)
2.1
2.0
2.0
2.0
2.0
2.0
2.0
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values
are based on historical data only.
a Also includes emissions due to drainage of organic soils in Land Converted to Grassland.
b Emissions from liming in Grassland Remaining Grassland are reported in Cropland Remaining Cropland.
Figure 7-10
Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 1990-1992
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes
associated with the Tier 3 inventory computations, but not the Tier 1 estimates for sewage sludge additions. See Methodology
for additional details.
Tg C02 Eq/yr
n Oto4
n-0.1 toO
n-0.5 to-0.1
n-1to-0.5
• -2to-1
• -6 to-2
This map shows the spatial variability in net carbon stock change for mineral soils for the years 1990 through 1992. The color assigned to each polygon
represents the total annual flux for the area of managed mineral soils in that polygon.
7-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 7-11
Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 1993-2004
Tg C02 Eq/yr
n Oto8
•-0.1 toO
n-0.5 to-0.1
n-1to-0.5
• -2to-1
n-3to-2
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes
associated with the Tier 3 inventory computations, but not the Tier 1 estimates for sewage sludge additions. See Methodology
for additional details.
This map shows the spatial variability in net carbon stock change for mineral soils for the years 1993 through 2004. The color assigned to each polygon
represents the total annual flux for the area of managed mineral soils in that polygon.
Figure 7-12
Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 1990-1992
Note: Values greater than zero represent emissions.
Tg C02 Eq/yr
• 0.5 to 1
n 0.1 to 0.5
DO to 0.1
Q| No organic soils
This map shows the spatial variability in net carbon stock change for organic soils for the years 1990 through 1992. The color assigned to each polygon
represents the total annual flux for the area of managed organic soils in that polygon.
Land Use, Land-Use Change, and Forestry 7-33
-------
Figure 7-13
Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 1993-2004
Tg C02 Eq/yr
lto2
0.5 to 1
n 0.1 to 0.5
DO to 0.1
Q No organic soils
Note: Values greater than zero represent emissions.
This map shows the spatial variability in net carbon stock change for organic soils for the years 1993 through 2004. The color assigned to each polygon
represents the total annual flux for the area of managed organic soils in that polygon.
soils were highest along the southeastern coastal region, in
the northeast central United States surrounding the Great
Lakes, and along the central and northern portions of the
west coast.
The estimates presented here are restricted to C stock
changes associated with land use and management of
agricultural soils. Agricultural soils are also important
sources of other greenhouse gases, particularly N20 from
application of fertilizers, manure, and crop residues and
from cultivation of legumes, as well as methane (CH4) from
flooded rice cultivation. These emissions are accounted for
under the Agriculture sector, along withnon-CO2 greenhouse
gas emissions from field burning of crop residues and CH4
and N2O emissions from livestock digestion and manure
management.
Methodology
The following section includes a description of the
methodology used to estimate changes in soil carbon stocks
due to agricultural land-use and management activities
on mineral and organic soils for Grassland Remaining
Grassland.
Mineral and Organic Soil Carbon Stock Changes
Soil C stock changes were estimated for Grassland
Remaining Grassland according to land-use histories
recorded in the USDA National Resources Inventory
(NRI) survey (USDA-NRCS 2000).12 Land use and some
management information (e.g., irrigation, legume pastures)
were collected for each NRI point on a 5-year cycle
beginning in 1982. NRI points were classified as Grassland
Remaining Grassland if the land use was grassland since
1982. Grassland includes pasture and rangeland used for
grass forage production, where the primary use is livestock
grazing. Rangeland are typically extensive areas of native
grassland that are not intensively managed, while pastures
are often seeded grassland, possibly following tree removal,
that may or may not be improved with practices such as
irrigation and interseeding legumes.
A new Tier 3 model-based approach was developed
to estimate C stock changes for mineral soils in Grassland
'• NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
7-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Remaining Grassland. An IPCC Tier 2 method was used to
estimate emissions from organic soils (Ogle et al. 2003).
Tier 1 methods were used to estimate additional changes in
C stocks in mineral soils due to manure amendments and
sewage sludge additions to soils. Further elaboration on
the methodologies and data used to estimate stock changes
from mineral and organic soils are provided in the Cropland
Remaining Cropland section and Annex 3.13.
Mineral Soils
Tier 3 Approach
Mineral SOC stocks and stock changes for Grassland
Remaining Grassland were estimated using the Century
biogeochemical model, as described in Cropland Remaining
Cropland. Historical land-use and management patterns
were used in the Century simulations as recorded in the
USDA National Resources Inventory (NRI) survey, with
supplemental information on fertilizer use and rates for
grassland in different regions of the United States from
the USDA Economic Research Service Cropping Practices
Survey (ERS 1997) and National Agricultural Statistics
Service (NASS 1992, 1999, 2004). Manure application
frequency to grassland and rates were estimated from data
compiled by the USDA Natural Resources Conservation
Service for 1997 (Edmonds et al. 2003). Pasture/Range/
Paddock (PRP) manure N additions were estimated internally
in the Century model, as part of the grassland system
simulations (i.e., PRP manure production was not an external
input into the model). See the Cropland Remaining Cropland
section for additional discussion on the Tier 3 methodology
for mineral soils.
Tier 2 Approach
No Tier 2 method was used to estimate mineral soil C
stock changes for Grassland Remaining Grassland because
the Tier 3 Century-based method was used to estimate stock
changes for the entire land base classified in this land use
category.
Additional Mineral C Stock Change Calculations
Annual C flux estimates for mineral soils between 1990
and 2004 were adjusted to account for additional C stock
changes associated with sewage sludge amendments.
Estimates of the amounts of sewage sludge N applied to
agricultural land were derived from national data on sewage
sludge generation, disposition, and nitrogen content. Total
sewage sludge generation data for 1988,1996, and 1998, and
a projection for 2000, in dry mass units, were obtained from
EPA reports (EPA 1993, 1999), and linearly interpolated to
estimate values for the intervening years. N application rates
from Kellogg et al. (2000) were used to determine the amount
of area receiving sludge amendments. Although sewage sludge
can be added to land managed for other land uses, it was
assumed that agricultural amendments occur in grassland.
Cropland is assumed to be rarely if ever amended with sewage
sludge due to the high metal content and other pollutants
in human waste. The soil C storage rate was estimated at
0.33 metric tons C per hectare per year for sewage sludge
amendments to grassland. The stock change rate is based on
country-specific factors using the IPCC method (see Annex
3.13 for further discussion).
The influence of variation in application of manure to
grassland soils may also affect C stock changes in Grassland
Remaining Grassland. However, the net impact is reported in
Cropland Remaining Cropland because it was not possible to
differentiate between manure amendments on cropland and
grassland in reporting years other than 1997 but the manure
is differentiated in the Agricultural Soil Management section
(i.e., Edmonds et al. 2003 only provides information on
amendments for the 1997 reporting year). Note that variation
in manure deposited directly onto PRP was assumed to
not increase soil C stocks. Much of the carbon in biomass
is returned to soils in grassland systems, either through
grazers as manure or directly in litter fall, and variation in
the manure production is assumed to have a minimal impact
on soil C stocks.
Organic Soils
Annual C emissions from grassland (Grassland
Remaining Grassland and Land Converted to Grassland)
on drained organic soils were estimated using methods
provided in the Revised 1996 IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA1997)
and IPCC Good Practice Guidance for Land Use, Land-Use
Change, and Forestry (IPCC 2003), except that U.S.-specific
C loss rates were used in the calculations rather than default
IPCC rates (Ogle et al. 2003). See the Cropland Remaining
Cropland section for additional discussion on the estimation
of C emissions from drained organic soils.
Land Use, Land-Use Change, and Forestry 7-35
-------
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone
and dolomite applied to Grassland Remaining Grassland are
reported in the Cropland Remaining Cropland, because it
was not possible to disaggregate liming application among
land use/land-use change categories.
Uncertainty
Uncertainty associated with the Grassland Remaining
Grassland category includes the uncertainty associated with
changes in mineral and organic soil carbon stocks.
Mineral and Organic Carbon Stock Changes
Uncertainties in Mineral Soil C Stock Changes
Tier 3 Approach
The uncertainty analysis for Grassland Remaining
Grassland using the Tier 3 approach was based on the same
method described for Cropland Remaining Cropland, except
that the uncertainty inherent in the structure of the Century
model was not addressed. The empirically-based uncertainty
estimator described in the Cropland Remaining Cropland
section has not been developed to estimate uncertainties in
Century model results for Grassland Remaining Grassland,
but this is a planned improvement for the inventory. See
the Tier 3 approach for mineral soils under the Cropland
Remaining Cropland section for additional discussion.
The inventory estimate for 2004 and associated 95 percent
confidence interval are provided in Table 7-24. The
uncertainty in the inventory estimate of 3.96 Tg C02 Eq.
was -44 percent and +39 percent.
Additional Mineral C Stock Change Calculations
A +50 percent uncertainty was assumed for additional
adjustments to the soil C stocks between 1990 and 2004
to account for additional C stock changes associated with
amending grassland soils with sewage sludge. The estimated
adjustment for 2004 and associated 95 percent confidence
interval are provided in Table 7-25.
Uncertainties in Organic Soil C Stock Changes
Uncertainty in carbon emissions from organic soils were
estimated using country specific factors and a Monte Carlo
Analysis. PDFs for emission factors were derived from a
synthesis of 10 studies, and combined with uncertainties
in the NRI land use and management data for organic
soils in the Monte Carlo Analysis. See the Tier 2 section
under minerals soils of Cropland Remaining Cropland for
additional discussion. Organic soils in Grassland Remaining
Grassland were estimated to emit between 2.2 and 7.7 Tg
C02 Eq. at a 95 percent confidence level (Table 7-26). This
indicates a range of 52 percent below to 68 percent above
the 2004 flux estimate of 4.58 Tg CO2 Eq.
Table 7-24: Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within Grassland
Remaining Grassland, which were Estimated Using the Tier 3 Approach (Tg C02 Eq. and Percent)
Source
Mineral Soil C Stocks: Grassland
Remaining Grassland
Chan °e Estimate Uncertainty Range Relative to Stock Change Estimate
(Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound
4.0 2.2
Upper Bound
5.5
Lower Bound
-44%
Upper Bound
+39%
Table 7-25: Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within Grassland Remaining
Grassland, which were Estimated Using the Tier 2 Approach (Tg C02 Eq. and Percent).
Source
2004 Stock
Change Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Stock Change Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Mineral Soil C Stocks: Grassland
Remaining Grassland (Change in Soil C
due to Sewage Sludge Amendments)
(1.3)
(1.9)
(0.6)
-50%
+50%
7-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 7-26: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Organic Soils Occurring within
Grassland Remaining Grassland (Tg C02 Eq. and Percent)
Change Estimate Uncertainty Range Relative to Stock Change Estimate"
Source (TgC02Eg.) (Tg C02 Eg.) (%)
Lower Bound
Upper Bound
Lower Bound Upper Bound
Organic Soil C Stocks: Grassland
Remaining Grassland"
4.6
2.2
7.7
-52%
+68%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
b Grassland Remaining Grassland and Land Converted to Grassland are both reported in this section because grassland on organic soils has not been
subdivided into land use/land-use change categories.
Additional Uncertainties in Mineral and Organic Soil
C Stock Changes
Minimal data exist on where and how much sewage
sludge has been applied to U.S. agricultural land and
the accounting of this activity appears to be much more
difficult than the related-activity of using manure to amend
agricultural soils. Consequently, there is considerable
uncertainty in the application of sewage sludge, which is
assumed to be applied to Grassland Remaining Grassland.
However, some sludge may be applied to other agricultural
land, but there is not sufficient information to further
subdivide application among the agricultural land use/
land-use change categories. See section on "Additional
Uncertainties in Soil C Stock Changes" in Cropland
Remaining Cropland (Section 1.3.1) for discussion of other
uncertainties.
QA/QC and Verification
See Cropland Remaining Cropland.
Recalculations Discussion
See Cropland Remaining Cropland.
Planned Improvements
See Cropland Remaining Cropland.
7.6. Land Converted to Grassland
(IPCC Source Category 5C2)
Background on agricultural carbon stock changes is
provided in the Cropland Remaining Cropland and will
only be summarized here. 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 Revised 1996 IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA
1997) recommend reporting changes in soil organic C
stocks due to: (1) agricultural land-use and management
activities on mineral soils; (2) agricultural land-use and
management activities on organic soils, and (3) C02
emissions that result from liming of soils with dolomite
and limestone. Mineral soil C stock changes are reported
here for Land Converted to Grassland, but stock changes
associated with management of organic soils and liming
are reported in Cropland Remaining Cropland because it
was not possible to subdivide those estimates by land use
and land-use change categories (see Methodology section
below for additional discussion).
Land-use and management of mineral soils in Land
Converted to Grassland led to an increase in soil C stocks
over the entire time series, which was largely caused by
annual cropland converted into pasture (see Table 7-26 and
Table 7-28). Stock change rates varied from 17.6 to 21.1 Tg
C02 Eq. (4.8 to 5.8 Tg C)
The spatial variability in annual CO2 flux associated with
C stock changes in mineral soils is displayed in Figure 7-14
and Figure 7-15. Soil C stock increased in most MLRAs for
Land Converted to Grassland. The largest gains were in the
southeast and northwest, and the amount of sequestration
increased through the 1990s. The patterns were driven by
conversion of annual cropland into continuous pasture.
The estimates presented here are restricted to C
stock changes associated with the use and management
of agricultural soils. Agricultural soils are also important
sources of other greenhouse gases, particularly N20 from
application of fertilizers, manure, and crop residues and
from cultivation of legumes, as well as methane (CH4) from
Land Use, Land-Use Change, and Forestry 7-37
-------
Table 7-27: Net Soil C Stock Changes for Land Converted to Grassland (Tg C02 Eq.)
Soil Type
1990
1998
1999
2000
2001
2002
2003
2004
Mineral Soils
Organic Soils3
Liming of Soils"
(17.6)
(21.1) (21.1) (21.1) (21.1) (21.1) (21.1) (21.1)
Total Net Flux
(17.6)
(21.1) (21.1) (21.1) (21.1) (21.1) (21.1) (21.1)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values
are based on historical data only.
a Emissions from organic soils in Land Converted to Grassland are reported in Grassland Remaining Grassland.
b Emissions from liming in Land Converted to Grassland are reported in Cropland Remaining Cropland.
Table 7-28: Net Soil C Stock Changes for Land Converted to Grassland (Tg C)
Soil Type
1990
1998
1999
2000
2001
2002
2003
2004
Mineral Soils
Organic Soils3
Liming of Soils"
(4.8)
(5.8)
(5.8
(5.8)
(5.8)
(5.8)
(5.8)
(5.8)
Total Net Flux
(4.8)
(5.8) (5.8) (5.8) (5.8)
(5.8) (5.8)
(5.8)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values
are based on historical data only.
a Emissions from organic soils in Land Converted to Grassland are reported in Grassland Remaining Grassland.
b Emissions from liming in Land Converted to Grassland are reported in Cropland Remaining Cropland.
Figure 7-14
Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 1990-1992
i i ~-» ^
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.
This map shows the spatial variability in net carbon stock change for mineral soils for the years 1990 through 1992. The color;
Tg C02 Eq/yr
~-0.1 toO
-0.5to-0.1
-1 to -0.5
-2 to -1
-2.4to-2
Note: Values greater than zero represent emissions, and values less than zero represent sequesi
associated with the Tier 2 and 3 inventory computations. See Methodology for additional details
This map shows the spatial variability in net carbon stock change for mineral soils for the years
represents the total annual flux for the area of managed mineral soils in that polygon.
».
1990 through 1992. The color assigned to each polygon
7-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure 7-15
Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 1993-2004
Tg C02 Eq/yr
G 0 to 0.003
H-0.1 toO
G-0.5 to-0.1
H-1to-0.5
G-2to-1
G -3 to -2
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes
associated with the Tier 2 and 3 inventory computations. See Methodology for additional details.
This map shows the spatial variability in net carbon stock change for mineral soils for the years 1993 through 2004. The color assigned to each polygon
represents the total annual flux for the area of managed mineral soils in that polygon.
flooded rice cultivation. These emissions are accounted for
under the Agriculture sector, along withnon-CO2 greenhouse
gas emissions from field burning of crop residues and CH4
and N2O emissions from livestock digestion and manure
management.
Methodology
The following section includes a description of the
methodology used to estimate changes in soil carbon stocks
due to agricultural land-use and management activities on
mineral soils for Land Converted to Grassland.
Mineral and Organic Soil Carbon Stock Changes
Soil C stock changes were estimated for Land Converted
to Grassland, according to land-use histories recorded in
the USDA National Resources Inventory (NRI) survey
(USDA-NRCS 2000).13 Land use and some management
information (e.g., legume pastures, crop type, soil attributes,
and irrigation) were collected for each NRI point on a 5-
year cycle beginning in 1982. NRI points were classified as
Land Converted to Grassland if the land use was currently
grassland but had been converted from another use since
1982. Grassland includes pasture and rangeland used for
grass forage production, where the primary use is livestock
grazing. Rangeland are typically extensive areas of native
grassland that are not intensively managed, while pastures
are often seeded grassland, possibly following tree removal,
that may or may not be improved with practices such as
irrigation and interseeding legumes.
A new Tier 3 model-based approach was developed to
estimate C stock changes for Land Converted to Grassland
on mineral soils. An IPCC Tier 2 method was used to
estimate C stock changes for portions of the land base
for Land Converted to Grassland on mineral soils that
were not addressed with the Tier 3 method, in addition to
emission estimates for organic soils (Ogle et al. 2003). An
IPCC Tier 2 method was used to estimate emissions from
organic soils (Ogle et al. 2003). Tier 1 methods were used
to estimate additional changes in mineral soil C stocks due
to manure amendments that were not included in the Tier
13 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
Land Use, Land-Use Change, and Forestry 7-39
-------
2 and 3 analyses, and also for sewage sludge amendments.
Further elaboration on the methodologies and data used to
estimate stock changes from mineral and organic soils are
provided in the Cropland Remaining Cropland section and
Annex 3.13.
Mineral Soils
Tier 3 Approach
Mineral SOC stocks and stock changes were estimated
using the Century biogeochemical model for cropland
converted into grassland, with the exception of prior cropland
used to produce vegetables, tobacco, perennial/horticultural
crops, and rice. Similar to Grassland Remaining Grassland,
historical land-use and management patterns were used in
the Century simulations as recorded in the NRI survey, with
supplemental information on fertilizer use and rates from
USDA Economic Research Service Cropping Practices
Survey (ERS 1997) and National Agricultural Statistics
Service (NASS 1992, 1999, 2004). Manure application
frequency and rates were simulated based on data compiled
by the USDA Natural Resources Conservation Service for
1997 (Edmonds et al. 2003). PRP manure N additions were
estimated internally in the Century model, as part of the
grassland system simulations (i.e., PRP manure was not an
input into the model). See Cropland Remaining Cropland
for additional discussion on the Tier 3 methodology for
mineral soils.
Tier 2 Approach
Mineral SOC stock changes were estimated using a Tier
2 Approach for land converted to grassland from perennial,
horticultural, tobacco and rice cropland. See Cropland
Remaining Cropland for additional discussion on the Tier 2
methodology for mineral soils.
Additional Mineral C Stock Change Calculations
Annual C stock changes for Land Converted to
Grassland on mineral soils between 1990 and 2004 were
adjusted to account for additional C stock changes associated
with sewage sludge amendments to soils, variation in
manure N production (see Annex 3.13, Table A-204) and
thus areas amended with manure relative to 1997. Additional
changes due to sewage sludge amendments are reported in
Grassland Remaining Grassland because it is not possible
to subdivide these changes into the individual land use/land-
use change categories. Similarly, additional changes due to
manure amendments were reported in Cropland Remaining
Cropland. See Grassland Remaining Grassland and Cropland
Remaining Cropland for further elaboration on the methods
used to estimate these additional changes in mineral soil C
stocks.
Organic Soils
Annual C emission estimates from drained organic soils
in Land Converted to Grassland were estimated using the
Tier 2 Approach, and reported in the Grassland Remaining
Grassland section because organic soil areas have not
been subdivided into land use/land-use change categories.
Differentiating organic soils between Land Converted to
Grassland and Grassland Remaining Grassland is a planned
future improvement for the soil C inventory. See Grassland
Remaining Grassland for discussion on the estimation of C
emissions from drained organic soils.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone
and dolomite applied to Land Converted to Grassland are
reported in the Cropland Remaining Cropland, because it
was not possible to disaggregate liming application among
land use and land-use change categories.
Uncertainty
Uncertainty associated with the Land Converted to
Grassland category includes the uncertainty associated with
changes in mineral soil carbon stocks.
Mineral and Organic Soil Carbon Stock Changes
Uncertainties in Mineral Soil C Stock Changes
Tier 3 Approach
The uncertainty analysis for Land Converted to
Grassland using the Tier 3 approach was based on the same
method described Cropland Remaining Cropland, except
that the uncertainty inherent in the structure of the Century
model was not addressed. The empirically-based uncertainty
estimator described in the Cropland Remaining Cropland
section has not been developed to estimate uncertainties in
Century model results for Land Converted to Grassland,
but this is a planned improvement for the inventory. See the
Tier 3 approach for mineral soils under Cropland Remaining
Cropland for additional discussion. The inventory estimate
for 2004 and associated 95 percent confidence interval are
7-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 7-29: Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within Land
Converted to Grassland, which were Estimated Using the Tier 3 Approach (Tg C02 Eq. and Percent)
Source
2004 Stock
Change Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Stock Change Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Mineral Soil C Stocks: Land
Converted to Grassland
(16.0)
(15.8)
(16.1)
-1%
+1%
provided in Table 7-29. The uncertainty in the inventory
estimate of-16.0 Tg C02 Eq. was +1 percent.
Tier 2 Approach
The uncertainty analysis for Land Converted to
Grassland using the Tier 2 approach was based on the same
method described for Cropland Remaining Cropland. See the
Tier 2 section under minerals soils in Cropland Remaining
Cropland section for additional discussion. Mineral soils on
Land Converted to Grassland, which were estimated using
the Tier 2 approach, had a carbon stock change between
-2.9 and -7.3 Tg CO2 Eq. at a 95 percent confidence level
(Table 7-30). This indicates a range of 43 percent below to
43 percent above the 2004 stock change estimate of -5.1
TgC02Eq.
Uncertainties in Organic Soil C Stock Changes
Annual C emission estimates from drained organic
soils in Land Converted to Grassland were estimated
using the Tier 2 Approach, and reported in the Grassland
Remaining Grassland Section because organic soil areas
have not subdivided into land use/land-use change categories.
Differentiating organic soils between Land Converted to
Grassland and Grassland Remaining Grassland is a planned
future improvement for the soil C inventory. See Grassland
Remaining Grassland for discussion on the uncertainty
estimation for drained organic soils in grassland.
Additional Uncertainties in Mineral and Organic Soil
C Stock Changes
Additional uncertainties are discussed in Cropland
Remaining Cropland.
QA/QC and Verification
See Cropland Remaining Cropland.
Recalculations Discussion
See Cropland Remaining Cropland.
Planned Improvements
See Cropland Remaining Cropland.
7.7. Settlements Remaining
Settlements
Changes in Yard Trimming and Food
Scrap Carbon Stocks in Landfills
(IPCC Source Category 5E1)
As is the case with carbon in landfilled forest products,
carbon contained in landfilled yard trimmings and food
scraps can be stored for very long periods. In the United
States, yard trimmings (i.e., grass clippings, leaves, and
Table 7-30: Tier 2 Quantitative Uncertainty Estimates for C Stock Changes in Mineral Soils Occurring within Land
Converted to Grassland that were Estimated Using the Tier 2 Approach (Tg C02 Eq. and Percent)
Chanqe Estimate Uncertainty Range Relative to Stock Change Estimate"
Source (Tg C02 Eq.) (Tg C02 Eq.) (%)
Lower Bound
Upper Bound
Lower Bound Upper Bound
Mineral Soil C Stocks: Land
Converted to Grassland
(5.1)
(7.3)
(2.9)
-43%
+43%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Land Use, Land-Use Change, and Forestry 7-41
-------
branches) and food scraps comprise a significant portion
of the municipal waste stream, and a large fraction of the
collected yard trimmings and food scraps are discarded
in landfills. However, both the amount of yard trimmings
and food scraps collected annually and the fraction that is
landfilled have declined over the last decade. In 1990, nearly
51 million metric tons (wet weight) of yard trimmings and
food scraps were generated (i.e., put at the curb for collection
or taken to disposal or composting facilities) (EPA 2005).
Since then, programs banning or discouraging disposal have
led to an increase in backyard composting and the use of
mulching mowers, and a consequent 18 percent decrease in
the amount of yard trimmings collected. At the same time,
a dramatic increase in the number of municipal composting
facilities has reduced the proportion of collected yard
trimmings that are discarded in landfills—from 72 percent
in 1990 to 35 percent in 2003 (the most recent year for
which data are available; 2004 values are assumed equal to
2003). There is considerably less centralized composting
of food scraps; generation has grown by 32 percent since
1990, though the proportion of food scraps discarded in
landfills has decreased slightly from 81 percent in 1990 to
78 percent in 2003. Overall, there has been a decrease in the
yard trimmings and food scrap landfill disposal rate, which
has resulted in a decrease in the rate of landfill carbon storage
to 9.3 Tg C02 Eq. in 2004 from 24.5 Tg CO2 Eq. in 1990
(Table 7-31 and Table 7-32).
Methodology
Estimates of net carbon flux resulting from landfilled
yard trimmings and food scraps were developed by
estimating the change in landfilled carbon stocks between
inventory years. Carbon stock estimates were calculated by
determining the mass of landfilled carbon resulting from yard
trimmings or food scraps discarded in a given year; adding
the accumulated landfilled carbon from previous years; and
subtracting the portion of carbon landfilled in previous years
that decomposed.
To determine the total landfilled carbon 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
carbon storage factor of the landfilled yard trimmings and
food scraps adjusted by mass balance; and (4) the rate of
decomposition of the degradable carbon. 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 carbon storage factor and rate
Table 7-31: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C02 Eq.)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Net Flux
1990
(21.7)
(2.4)
(9.8)
(9.6)
(2.8)
(24.5)
1997
(8.7)
(0.8)
(3.9)
(4.0)
(2.6)
(11.3)
1998
(8.0)
(0.8)
(3.6)
(3.7)
(2.9)
(10.9)
1999
(6.9)
(0.6)
(3.0)
(3.2)
(2.9)
(9.8)
2000
(5.6)
(0.5)
(2.5)
(2.7)
(3.2)
(8.9)
2001
(5.8)
(0.6)
(2.5)
(2.7)
(3.2)
(9.0)
2002
(6.1)
(0.6)
(2.6)
(2.8)
(3.2)
(9.3)
2003
(6.3)
(0.7)
(2.7)
(2.9)
(3.1)
(9.4)
2004
(6.4)
(0.7)
(2.8)
(2.9)
(2.9)
(9.3)
Note: Totals may not sum due to independent rounding.
Table 7-32: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Net Flux
Note: Totals may not sum
1990
(5.9)
(0.6)
(2.7)
(2.6)
(0.8)
(6.7)
due to independent rounding.
1997
(2.4)
(0.2)
(1.1)
(1.1)
(0.7)
(3.1)
1998
(2.2)
(0.2)
(1.0)
(1.0)
(0.8)
(3.0)
1999
(1.9)
(0.2)
(0.8)
(0.9)
(0.8)
(2.7)
2000
(1.5)
(0.1)
(0.7)
(0.7)
(0.9)
(2.4)
2001
(1.6)
(0.2)
(0.7)
(0.7)
(0.9)
(2.5)
2002
(1.7)
(0.2)
(0.7)
(0.8)
(0.9)
(2.5)
2003
(1.7)
(0.2)
(0.7)
(0.8)
(0.8)
(2.6)
2004
(1.7)
(0.2)
(0.8)
(0.8)
(0.8)
(2.5)
7-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
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: 2003 Facts and Figures (EPA 2005).
That report provides data for 1960,1970,1980,1990,1995,
and 2000 through 2003. To provide data for some of the
missing years in the 1990 through 1999 period, two earlier
reports were used (Characterization of Municipal Solid
Waste in the United States: 1998 Update (EPA 1999), and
Municipal Solid Waste in the United States: 2001 Facts
and Figures (EPA 2003)). Remaining years in the time
series for which data were not provided were estimated
using linear interpolation. Values for 2004 are assumed to
be equal to values for 2003. The reports do not subdivide
discards of individual materials into volumes landfilled
and combusted, although they provide an estimate of the
proportion of overall wastestream discards managed in
landfills and combustors (i.e., ranging from 81 percent
and 19 percent respectively in 1990, to 80 percent and 20
percent in 2000).
The amount of carbon 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) carbon 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 carbon contents
were determined by Barlaz (1998; 2005) (Table 7-33).
The amount of carbon remaining in the landfill for
each subsequent year was tracked based on a simple model
of carbon fate. As demonstrated by Barlaz (1998; 2005),
a portion of the initial carbon resists decomposition and
is essentially persistent in the landfill environment; the
modeling approach applied here builds on his findings.
Barlaz (1998; 2005) conducted a series of experiments
designed to measure biodegradation of yard trimmings,
food scraps, and other materials, in conditions designed to
promote decomposition (i.e., by providing ample moisture
and nutrients). After measuring the initial carbon content,
the materials were placed in sealed containers along with a
"seed" containing methanogenic microbes from a landfill.
Once decomposition was complete, the yard trimmings
and food scraps were re-analyzed for carbon content; the
carbon remaining in the solid sample can be expressed as
a proportion of initial carbon (shown in the row labeled
"CS" in Table 7-33).
For purposes of simulating U.S. landfill carbon flows,
the proportion of carbon stored is assumed to persist in
landfills; the remaining portion is assumed to degrade (and
results in emissions of CH4 and C02; the methane emissions
resulting from decomposition of yard trimmings and food
scraps are counted in the Waste chapter). The degradable
portion of the carbon is assumed to decay according to first
order kinetics. Grass and food scraps are assumed to have
a half -life of 5 years; leaves and branches are assumed to
have a half-life of 20 years.
For each of the four materials (grass, leaves, branches,
food scraps), the stock of carbon in landfills for any
given year is calculated according to the following
formula:
LFC j t = 2 Wj n x (1 -
{[CSixICCJ
x ICQ x
\\ -kx(t-n) 1
))xe
where,
= the year for which carbon stocks are being
estimated,
Table 7-33: Moisture Content (%), Carbon Storage Factor, Initial Carbon Content (%), Proportion of Initial Carbon
Sequestered (%), and Half-Life (years) for Landfilled Yard Trimmings and Food Scraps in Landfills
Variable
Moisture Content (% H20)
CS, proportion of initial carbon C stored
Initial Carbon Content (%)
Half-life (years)
Grass
70
68%
45
5
Yard Trimmings
Leaves
30
72%
42
20
Branches
10
77%
49
20
Food Scraps
70
16%
51
5
Land Use, Land-Use Change, and Forestry 7-43
-------
W(
MQ
LFC j t = the stock of carbon in landfills in year t,
for waste i (grass, leaves, branches, food
scraps)
= the mass of waste i disposed in landfills in
year n, in units of wet weight
= the year in which the waste was disposed,
where 1960 < n < t
= moisture content of waste i,
= the proportion of initial carbon that is stored
for waste i,
= the initial carbon content of waste i,
e = the natural logarithm, and
k = the first order rate constant for waste i, and
is equal to 0.693 divided by the half -life for
decomposition.
For a given year t, the total stock of carbon in landfills
(TLFCt) is the sum of stocks across all four materials. The
annual flux of carbon in landfills (Fj for year t is calculated
as the change in stock compared to the preceding year:
Ft = TLFCt-TLFCt_i
Thus, the carbon placed in a landfill in year n is tracked
for each year t through the end of the inventory period (2004).
For example, disposal of food scraps in 1960 resulted in
depositing about 1,140,000 metric tons of carbon. Of this
amount, 16 percent (180,000 metric tons) is persistent; the
remaining 84 percent (960,000 metric tons) is degradable.
By 1965, half of the degradable portion (480,000 metric
tons) decomposes, leaving a total of 660,000 metric tons (the
persistent portion, plus the remaining half of the degradable
portion) .
Continuing the example, by 2004, the total food scraps
carbon originally disposed in 1960 had declined to 181,000
metric tons (i.e., virtually all of the degradable carbon
had decomposed). By summing the carbon remaining
from 1960 with the carbon remaining from food scraps
disposed in subsequent years (1961 through 2004), the
total landfill carbon from food scraps in 2004 was 30.5
million metric tons. This value is then added to the carbon
stock from grass, leaves, and branches to calculate the total
landfill carbon stock in 2004, yielding a value of 232.6
million metric tons (as shown in Table 7-34). In exactly
the same way total net flux is calculated for forest carbon
and harvested wood products, the total net flux of landfill
carbon for yard trimmings and food scraps for a given year
(Table 7-32) is the difference in the landfill carbon stock
for a given year and the stock in the preceding year. For
example, the net change in 2004 shown in Table 7-32 (2.5
Tg C) is equal to the stock in 2004 (232.6 Tg C) minus the
stock in 2003 (230.0 Tg C).
When applying the carbon storage data reported by
Barlaz (1998), an adjustment was made to the reported
values so that a perfect mass balance on total carbon could
be attained for each of the materials. There are four principal
elements in the mass balance:
• Initial carbon content (ICC, measured),
• Carbon output as methane (CH4-C, measured),
• Carbon output as carbon dioxide (CO2-C, not measured),
and
• Residual stored carbon (CS, measured).
In a simple system where the only carbon fates are CH4,
C02, and carbon storage, the following equation is used to
attain a mass balance:
CH4-C + COrC + CS = ICC
The experiments by Barlaz and his colleagues (Barlaz
1998, Eleazer et al. 1997) did not measure CO2 outputs
in experiments. However, if the only decomposition is
Table 7-34: Carbon Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C)
Carbon Pool
Yard Trimmings
Grass
Leaves
Branches
Food Scraps
Total Carbon Stocks
1990
161.3
18.2
72.8
70.3
20.3
181.6
1997
189.7
21.1
85.5
83.0
24.7
214.4
1998
191.9
21.4
86.5
84.0
25.5
217.4
1999
193.7
21.5
87.3
84.9
26.3
220.1
2000
195.3
21.7
88.0
85.6
27.2
222.5
2001
196.9
21.8
88.7
86.4
28.1
224.9
2002
198.5
22.0
89.4
87.1
28.9
227.5
2003
200.3
22.2
90.2
87.9
29.8
230.0
2004
202.0
22.4
90.9
88.7
30.5
232.6
Note: Totals may not sum due to independent rounding.
7-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
anaerobic, then CH4-C = C02-C.14 Thus, the system should
be defined by:
2 x CH4-C + CS = ICC
The carbon outputs (=2 x CH4-C + CS ) were less than
100 percent of the initial carbon mass for food scraps, leaves,
and branches (75,86, and 90 percent, respectively). For these
materials, it was assumed that the unaccounted for carbon had
exited the experiment as CH4 and C02, and no adjustment
was made to the measured value of CS.
In the case of grass, the outputs were slightly more
(103 percent) than initial carbon mass. To resolve the mass
balance discrepancy, it was assumed that the measurements
of initial carbon content and methane mass were accurate.
Thus, the value of CS was calculated as the residual of ICC
(initial carbon content) minus (2 x CH4-C). This adjustment,
reduced the carbon storage value from the 71 percent reported
by Barlaz (1998) to 68 percent (as shown in Table 7-33).
Uncertainty
The estimation of carbon storage in landfills is directly
related to the following yard trimming and food scrap data
and factors: disposal in landfills per year (tons of carbon),
initial carbon content, moisture content, decomposition
rate (half-life), and proportion of carbon stored. The
carbon storage landfill estimates are also a function of the
composition of the yard trimmings (i.e., the proportions of
grass, leaves and branches in the yard trimmings mixture).
There are uncertainties associated with each of these
factors.
The uncertainty ranges were assigned based on expert
judgment and are assumed to be uniformly distributed around
the inventory estimate (e.g., +10 percent), except for the
values for decomposition rate, proportion of carbon stored,
and moisture content for branches.
The uncertainty ranges associated with the input
variables for the proportion of grass and leaves in yard
trimmings, as well as the initial carbon content and moisture
content for grass, leaves, and food scraps (all expressed as
percentages in the calculations for the inventory) were plus
or minus 10 percent. For the moisture content of branches
(where the inventory estimate is 10 percent), the uncertainty
range was assumed to be 5 to 30 percent.
The uncertainty ranges associated with the disposal of
grass, leaves, branches, and food scraps were bound at 50
percent to 150 percent times the inventory estimates. The
half-life of grass and food scraps were assumed to range from
1 to 20 years, and the half-lives of leaves and branches were
assumed to range from 5 to 30 years. Finally, the proportion
of carbon stored in grass, leaves, branches, and food scraps
was assumed to vary plus or minus 20 percent from the best
estimate, with an upper bound of 100 percent and a lower
bound of 0 percent.
A Monte Carlo (Tier 2) uncertainty analysis was then
applied to estimate the overall uncertainty of the sequestration
estimate. The results of the Tier 2 quantitative uncertainty
analysis are summarized in Table 7-35. Total yard trimmings
and food scraps C02 flux in 2004 was estimated to be
between-16.3 and-5.7TgCO2Eq. at a 95 percent confidence
level (or 19 of 20 Monte Carlo Stochastic Simulations). This
indicates a range of 75 percent below to 39 percent above
the 2004 flux estimate of -9.3 Tg CO2 Eq.
The uncertainty of the landfilled carbon storage estimate
arises from the disposal data and the factors applied to the
following data.
Table 7-35: Tier 2 Quantitative Uncertainty Estimates for C02 Flux from Yard Trimmings and Food Scraps in Landfills
(Tg C02 Eq. and Percent)
Source
^Estimate'"" Uncertainty Range Relative to Emission Estimate"
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Yard Trimmings and
Food Scraps
C02 (9.3) (16.3) (5.7) -75% +39%
aRange of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Note: Parentheses indicate negative values or net carbon sequestration.
14 The molar ratio of CH4 to C02 is 1:1 for carbohydrates (e.g., cellulose, hemicellulose). For proteins as C3 2H5ON0 86, the molar ratio is 1.65 CH4 per
1.55 C02 (Barlaz et al. 1989). Given the predominance of carbohydrates, for all practical purposes, the overall ratio is 1:1.
Land Use, Land-Use Change, and Forestry 7-45
-------
Disposal per Year (tons of carbon)
A source of uncertainty affecting CO2 sequestration
is the estimate of the tonnage of yard trimmings and food
scraps which are disposed of in landfills each year. Of all
the individual inputs tested for sensitivity in the uncertainty
analysis, net carbon storage in landfills is most sensitive to
the estimate of the food scrap disposal rate. The estimates
for yard trimming and food scrap disposal in landfills are
determined using data from EPA (1999,2002,2003) estimates
of materials generated, discarded, and combusted, which carry
considerable uncertainty associated with the wastestream
sampling methodology used to generate them.
Moisture Content and Initial Carbon Content
Moisture content, and to a lesser extent carbon content,
vary widely. Moisture content for a given sample of waste
can be affected by the precipitation conditions when the
waste is placed at the curb for collection, as well as the status
and condition of the landfill cover. Carbon content (on a dry
weight basis) is a function of the specific waste constituents
(e.g., oak leaves versus pine needles or banana peels versus
bacon grease), which in turn vary temporally, geographically,
and demographically (i.e., characteristics of households in
the wasteshed).
Decomposition Rate
Although several investigators have made estimates
of the decomposition rate of mixed solid waste in a landfill
environment, there are no known studies of decomposition
rates for individual materials in actual landfills, and thus
the inventory estimate is based on assumed values. The
uncertainty analysis indicates that the results are sensitive
to decomposition rates, especially the food scraps half-life,
and thus the decomposition rates introduce considerable
uncertainty into the analysis.
Proportion of Carbon Stored
The estimate of the proportion of carbon stored is based
on a set of experiments measuring the amount of carbon
persisting in conditions promoting decomposition. Because
these experiments have only used conditions conducive to
decomposition, they are more likely to underestimate than
to overestimate carbon storage. Nonetheless, measurement
error may be the dominant source of uncertainty, and so the
uncertainty analysis used symmetrical values (plus or minus
20 percent) as inputs.
Recalculations Discussion
The principal change this year is the addition of newly
generated experimental results for leaves, provide by Barlaz
(2005). This has the effect of reducing the overall estimate of
landfill carbon storage, as the new results for leaves indicate
more decomposition than the earlier values.
This year's inventory also reflects changes in the
estimate for carbon storage from grass, reflecting the mass
balance constraint described above in the methodology
section. This mass balance constraint had not been applied
in previous years.
Overall, the recalculations have the effect of reducing
carbon stocks by about 4 percent in this year's inventory
compared to those reported last year.
Planned Improvements
Future work may evaluate the potential contribution
of inorganic carbon to landfill sequestration and to assure
consistency between the estimates of carbon storage
described in this chapter and the estimates of landfill CH4
emissions described in the Waste chapter.
Changes in Carbon Stocks in Urban
Trees (IPCC Source Category 5E1)
Urban forests constitute a significant portion of the total
U.S. tree canopy cover (Dwyer et al. 2000). Urban areas
(cities, towns, and villages) are estimated to cover over 4.4
percent of the United States (Nowak et al. (in review)). With
an average tree canopy cover of 27.1 percent, urban areas
account for approximately 3 percent of total tree cover in the
Table 7-36: Net C Flux from Urban Trees (Tg C02 Eq. and
TgC)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
(58.7)
(73.3)
(77.0)
(77.0)
(80.7)
(80.7)
(84.3)
(88.0)
TgC
(16.0)
(20.0)
(21.0)
(21.0)
(22.0)
(22.0)
(23.0)
(24.0)
Note: Parentheses indicate net sequestration.
7-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
continental United States (Nowak et al. 2001). Trees in urban
areas of the United States were estimated to account for an
average annual net sequestration of 72.1 Tg CO2 Eq. (19.7
Tg C) over the period from 1990-2004. Total sequestration
increased by 50 percent between 1990 and 2004 due to
increases in urban land area. Data on carbon storage and
urban tree coverage were collected throughout the 1990s,
and have been applied to the entire time series in this report.
Annual estimates of CO2 flux were developed based on
periodic U.S. Census data on urban area (Table 7-36).
Net carbon flux from urban trees is proportionately
greater on an area basis than that of forests. This trend is
primarily the result of different net growth rates in urban
areas versus forests —urban trees often grow faster than forest
trees because of the relatively open structure of the urban
forest (Nowak and Crane 2002). Also, areas in each case are
accounted for differently. Because urban areas contain less
tree coverage than forest areas, the carbon storage per hectare
of land is in fact smaller for urban areas. However, urban tree
reporting occurs on a per unit tree cover basis (tree canopy
area), rather than total land area. Urban trees, therefore,
appear to have a greater carbon density than forested areas
(Nowak and Crane 2002).
Methodology
The methodology used by Nowak and Crane (2002) is
based on average annual estimates of urban tree growth and
decomposition, which were derived from field measurements
and data from the scientific literature, urban area estimates
from U.S. Census data, and urban tree cover estimates from
remote sensing data. This approach is consistent with the
default IPCC methodology in the IPCC Good Practice
Guidance for Land Use, Land-Use Change and Forestry
(IPCC 2003), although sufficient data are not yet available
to determine interannual changes in carbon stocks in the
living biomass of urban trees. Annual changes in net C flux
from urban trees are based solely on changes in total urban
area in the United States.
Nowak and Crane (2002) developed estimates of
annual gross carbon sequestration from tree growth and
annual gross carbon emissions from decomposition for
ten U.S. cities: Atlanta, GA; Baltimore, MD; Boston, MA;
Chicago, IL; Jersey City, NJ; New York, NY; Oakland, CA;
Philadelphia, PA; Sacramento, CA; and Syracuse, NY. The
gross carbon sequestration estimates were derived from field
data that were collected in these ten cities during the period
from 1989 through 1999, including tree measurements of
stem diameter, tree height, crown height, and crown width,
and information on location, species, and canopy condition.
The field data were converted to annual gross carbon
sequestration rates for each species (or genus), diameter
class, and land-use condition (forested, park-like, and open
growth) by applying allometric equations, a root-to-shoot
ratio, moisture contents, a carbon content of 50 percent (dry
weight basis), an adjustment factor to account for smaller
aboveground biomass volumes (given a particular diameter)
in urban conditions compared to forests, an adjustment
factor to account for tree condition (fair to excellent, poor,
critical, dying, or dead), and annual diameter and height
growth rates. The annual gross carbon sequestration rates
for each species (or genus), diameter class, and land-use
condition were then scaled up to city estimates using tree
population information. The field data from the 10 cities,
some of which are unpublished, are described in Nowak and
Crane (2002) and references cited therein. The allometric
equations were taken from the scientific literature (see
Nowak 1994, Nowak et al. 2002), and the adjustments to
account for smaller volumes in urban conditions were based
on information in Nowak (1994). A root-to-shoot ratio of
0.26 was taken from Cairns et al. (1997), and species- or
genus-specific moisture contents were taken from various
literature sources (see Nowak 1994). Adjustment factors
to account for tree condition were based on percent crown
dieback (Nowak and Crane 2002). Tree growth rates were
also taken from existing literature. Average diameter growth
was based on the following sources: estimates for trees in
forest stands came from Smith and Shifley (1984); estimates
for trees on land uses with a park-like structure came from
deVries (1987); and estimates for more open-grown trees
came from Nowak (1994). Formulas from Fleming (1988)
formed the basis for average height growth calculations.
Annual gross carbon emission estimates were derived
by applying estimates of annual mortality and condition, and
assumptions about whether dead trees were removed from
the site, to carbon stock estimates. These values were derived
as intermediate steps in the sequestration calculations, and
different decomposition rates were applied to dead trees
left standing compared with those removed from the site.
The annual gross carbon emission rates for each species
(or genus), diameter class, and condition class were then
Land Use, Land-Use Change, and Forestry 7-47
-------
scaled up to city estimates using tree population information.
Estimates of annual mortality rates by diameter class and
condition class were derived from a study of street-tree
mortality (Nowak 1986). Assumptions about whether dead
trees would be removed from the site were based on expert
judgment of the authors. Decomposition rates were based on
literature estimates (Nowak and Crane 2002).
National annual net carbon sequestration by urban trees
was estimated from estimates of gross and net sequestration
from seven of the ten cities, and urban area and urban tree cover
data for the United States. Annual net carbon sequestration
estimates were derived for seven cities by subtracting the
annual gross emission estimates from the annual gross
sequestration estimates.15 The urban areas are based on 1990
and 2000 U.S. Census data. The 1990 U.S. Census defined
urban land as "urbanized areas," which included land with a
population density greater than 1,000 people per square mile,
and adjacent "urban places," which had predefined political
boundaries and a population total greater than 2,500. In 2000,
the U.S. Census replaced the "urban places" category with a
new category of urban land called an "urban cluster," which
included areas with more than 500 people per square mile.
Urban land area has increased by approximately 36 percent
from 1990 to 2000; Nowak et al. (in review) estimate that
the changes in the definition of urban land have resulted in
approximately 20 percent of the total reported increase in
urban land area from 1990 to 2000. Under both 1990 and 2000
definitions, urban encompasses most cities, towns, and villages
(i.e., it includes both urban and suburban areas). National urban
tree cover area was estimated by Nowak et al. (2002) to be
27.1 percent of urban areas.
The gross and net carbon sequestration values for
each city were divided by each city's area of tree cover
to determine the average annual sequestration rates per
unit of tree area for each city. The median value for gross
sequestration (0.30 kg C/m -year) was then multiplied by
the estimate of national urban tree cover area to estimate
national annual gross sequestration. To estimate national
annual net sequestration, the estimate of national annual
gross sequestration was multiplied by the average of
the ratios of net to gross sequestration for those cities
that had both estimates (0.70). The urban tree cover area
estimates for each of the 10 cities and the United States
were obtained from Dwyer et al. (2000) and Nowak et al.
(in review).
Uncertainty
The only quantifiable uncertainty associated with
changes in C stocks in urban trees was sampling, as reported
by Nowak and Crane (2002). The average standard deviation
for urban tree carbon storage was 27 percent of the mean
carbon storage on an area basis. Additionally, a 5 percent
uncertainty was associated with national urban tree covered
area. These estimates are based on field data collected in
ten U.S. cities, and uncertainty in these estimates increases
as they are scaled up to the national level.
Table 7-37: Carbon Stocks (Metric Tons C), Annual Carbon Sequestration (Metric Tons C/yr), Tree Cover (Percent),
and Annual Carbon Sequestration per Area of Tree Cover (kg C/m2 cover-yr) for Ten U.S. Cities
City
New York, NY
Atlanta, GA
Sacramento, CA
Chicago, IL
Baltimore, MD
Philadelphia, PA
Boston, MA
Syracuse, NY
Oakland, CA
Jersey City, NJ
Carbon Stocks
1,225,200
1,220,200
1,107,300
854,800
528,700
481,000
289,800
148,300
145,800
19,300
Gross Annual
Sequestration
38,400
42,100
20,200
40,100
14,800
14,600
9,500
4,700
NA
800
Net Annual
Sequestration
20,800
32,200
NA
NA
10,800
10,700
6,900
3,500
NA
600
Tree Cover
20.9
36.7
13.0
11.0
25.2
15.7
22.3
24.4
21.0
11.5
Gross Annual
Sequestration per
Area of Tree Cover
0.23
0.34
0.66
0.61
0.28
0.27
0.30
0.30
NA
0.18
Net Annual
Sequestration per
Area of Tree Cover
0.12
0.26
NA
NA
0.20
0.20
0.22
0.22
NA
0.13
NA = not analyzed
15 Three cities did not have net estimates.
7-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 7-38: Tier 1 Quantitative Uncertainty Estimates for Net C Flux from Changes in Carbon Stocks in Urban Trees
(Tg C02 Eq. and Percent)
Source
Ft t Uncertainty Range Relative to Emission Estimate
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Changes in C Stocks in
Urban Trees
C02 (88.0) (120.5) (55.5) -37% +37%
Note: Parentheses indicate negative values or net sequestration.
There is additional uncertainty associated with the
biomass equations, conversion factors, and decomposition
assumptions used to calculate carbon sequestration and
emission estimates (Nowak et al. 2002). These results also
exclude changes in soil carbon stocks, and there may be
some overlap between the urban tree carbon estimates and
the forest tree carbon estimates. However, both the omission
of urban soil carbon flux and the potential overlap with forest
carbon are believed to be relatively minor (Nowak 2002).
Because these are inestimable, they are not quantified as
part of this analysis.
The results of the Tier 1 quantitative uncertainty analysis
are summarized in Table 7-38. Net C flux from changes in
C stocks in urban trees was estimated to be between -120.5
and -55.5 Tg C02 Eq. at a 95 percent confidence level. This
indicates a range of 37 percent above and below the 2004
flux estimate of -88.0 Tg CO2 Eq.
QA/QC and Verification
The net carbon flux resulting from urban trees
was calculated using estimates of gross and net carbon
sequestration estimates for urban trees and urban tree
coverage area found in literature. The validity of these data
for their use in this section of the Inventory was evaluated
through correspondence established with an author of the
papers. Through the correspondence, the methods used
to collect the urban tree sequestration and area data were
further clarified and the use of these data in the Inventory
was reviewed and validated (Nowak 2002).
Recalculations Discussion
New estimates of urban area available in the 2000 U.S.
Census have made it possible to develop estimates of net
C flux in urban trees over the time series 1990 to 2004.
Previous Inventory estimates relied solely on 1990 U.S.
Census data, which were applied over the entire time series
from 1990 to 2004. The new 2000 estimates were applied to
the calculation of net C flux in that year. Additionally, 1990
and 2000 estimates were used as the basis for interpolating
and extrapolating, respectively, estimates of urban area in
the intervening years (1991 through 1999) and subsequent
years (2001 through 2004). New 1990 estimates for urban
area were also used in the current Inventory. Estimates used
in previous Inventories did not include Alaska and Hawaii.
Nowak et al. (in review) provide new 1990 estimates that
include Alaska and Hawaii. Net C flux for the entire time
series 1990 through 2004 was calculated based on these new
estimates of urban area. These changes resulted in a change
in emissions estimates for every year except 1990 and 1991.
Estimates of net C flux from urban trees changed an average
of 21 percent over the period from 1990 to 2003 relative to
the previous report.
N20 Fluxes from Soils (IPCC Source Category 5E1)
Of the fertilizers applied to soils in the United States,
approximately 10 percent are applied to lawns, golf courses,
and other landscaping occurring within settled areas.
Application rates are less than those occurring on cropped
soils, and, therefore, account for a smaller proportion of
Table 7-39: N20 Fluxes from Soils in Settlements Remaining Settlements (Tg C02 Eq. and Gg)
Settlements Remaining Settlements:
N20 Fluxes from Soils
Tg C02 Eq.
eg
1990
5.6
18
1998
6.2
20
1999
6.2
20
2000
6.0
19
2001
5.8
19
2002
6.0
19
2003
6.2
20
2004
6.4
21
Land Use, Land-Use Change, and Forestry 7-49
-------
total U.S. soil N2O emissions per unit area. In 2004, N20
emissions from this source were 6.4 Tg CO2 Eq. (20.8 Gg).
There was an overall increase of 15 percent over the period
from 1990 through 2004 due to a general increase in the
application of synthetic fertilizers. 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
7-39.
Methodology
For soils within Settlements Remaining Settlements, the
IPCC Tier 1 approach was used to estimate soil N20 emissions
from synthetic N fertilizer and sewage sludge additions.
Estimates of direct N20 emissions from soils in settlements
were based on the amount of N applied to turf grass annually
through the application of synthetic commercial fertilizers
and the amount of N in sewage sludge applied to non-
agricultural land and in surface disposal of sewage sludge.
Nitrogen applications to turf grass are assumed to be 10
percent of the total synthetic fertilizer used in the United
States (Qian 2004). Total synthetic fertilizer applications
were derived from fertilizer statistics (TVA 1991, 1992,
1993,1994;AAPFCO 1995,1996,1997,1998,1999,2000b,
2002, 2003, 2004, 2005) and a recent AAPFCO database
(AAPFCO 2000a). Sewage sludge applications were derived
from national data on sewage sludge generation, disposition,
and nitrogen content (see Annex 3.11 for further detail). The
IPCC default volatilization factor for synthetic fertilizer
N applied (10 percent) was used to calculate the amount
of unvolatilized N applied to turf grass through synthetic
fertilizers (IPCC/UNEP/OECD/IEA1997). The IPCC default
volatilization factor for N excreted by livestock (20 percent)
was used to calculate the amount of unvolatilized N applied
to non-agricultural land through sewage sludge applications
and resulting from surface disposal of sewage sludge (IPCC/
UNEP/OECD/IEA1997).16 The total amount of unvolatilized
N resulting from these sources was multiplied by the IPCC
default emission factor (1.25 percent) to estimate direct N20
emissions. The volatilized and leached/runoff proportion,
calculated with the IPCC default volatilization factors (10 or
20 percent, respectively, for synthetic or organic fertilizers)
and leaching/runoff factor (30 percent), was included with
the total N contributions to indirect emissions, as reported
in the N2O Emissions from Agricultural Soil Management
source category of the Agriculture sector.
Uncertainty
The amount of N20 emitted from settlements depends
not only on N inputs, but also on a large number of variables,
including organic carbon availability, O2 partial pressure, soil
moisture content, pH, temperature, and irrigation/watering
practices. The effect of the combined interaction of these
variables on N2O flux is complex and highly uncertain. The
IPCC default methodology used here does not incorporate
any of these variables and only accounts for variations in
national fertilizer application rates. All settlement soils are
treated equivalently under this methodology. Uncertainties
exist in both the fertilizer application rates and the emission
factors used to derive emission estimates.
The 95 percent confidence interval for the IPCC's
default emission factor for synthetic fertilizer applied to
soil ranges from 0.25 to 6 percent, according to Chapter 4
of IPCC (2000). While a Tier 1 analysis should be generated
from a symmetrical distribution of uncertainty around the
emission factor, an asymmetrical distribution was imposed
here to account for the fact that the emission factor used
Table 7-40: Tier 1 Quantitative Uncertainty Estimates of N20 Emissions from Soils in Settlements Remaining
Settlements (Tg C02 Eq. and Percent)
2004 Flux
Estimate
Source Gas (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Settlements Remaining Settlements:
N20 Fluxes from Soils N20 6.5
0.4 37.6 -94% +483%
16 Although the IPCC default factor of 20 percent is for the application of livestock manure, it is assumed to be a more accurate representation of volatilization
for organic N additions when compared to the volatilization factor for synthetic N additions.
7-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
was not the mean of the range given by IPCC. Therefore, an
upper bound of 480 percent and a lower bound of 80 percent
were assigned to the emission factor. The uncertainty in
the amount of synthetic fertilizer N applied to settlement
soils was conservatively estimated to be 50 percent (Qian
2004). The results of the Tier 1 quantitative uncertainty
analysis are summarized in Table 7-40. N20 emissions
from soils in Settlements Remaining Settlements in 2004
were estimated to be between 0.4 and 37.6 Tg CO2 Eq. at
a 95 percent confidence level. This indicates a range of
94 percent below to 483 percent above the 2004 emission
estimate of 6.5 Tg C02Eq.
Recalculations Discussion
The 2003 data were updated from the AAPFCO
Commercial Fertilizers 2004 report (2005). This change
resulted in a one percent decrease in the emissions estimates
for that year. The inclusion of N in sewage sludge applied to
non-agricultural land and surface disposal of sewage sludge
is new to the current Inventory. These changes resulted in
an average change of about 1 percent over the period from
1990 to 2003.
Planned Improvements
The indirect N2O emissions from fertilization of
settlements, which are currently reported in the Agriculture
chapter, will be reported here. In addition, the process-based
model DAYCENT, which was used to estimate N20 emissions
from cropped soils this year, could also be used to simulate
direct emissions as well as volatilization and leaching/runoff
from settlements. DAYCENT has been parameterized
to simulate turf grass. State-level settlement area data is
available from the National Resource Inventory.
7.8. Land Converted to Settlements
(Source Category 5E2)
Land-use change is constantly occurring, and land under
a number of uses undergoes urbanization in the United States
each year. However, data on the amount of land converted
to settlements is currently lacking. Given the lack of
available information relevant to this particular IPCC source
category, it is not possible to separate CO2 or N2O fluxes on
Land Converted to Settlements from fluxes on Settlements
Remaining Settlements at this time.
Land Use, Land-Use Change, and Forestry 7-51
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8. Waste
Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 8-1). Landfills
were the largest source of anthropogenic methane (CH4) emissions in 2004, accounting for 25 percent of total
U.S. CH4 emissions.1 Additionally, wastewater treatment accounts for 7 percent of U.S. CH4 emissions. Nitrous
oxide (N2O) emissions from the discharge of wastewater treatment effluents into aquatic environments were estimated, as were
N2O emissions from the treatment process itself, using a simplified methodology. Nitrogen oxide (NOj, 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 and indirect greenhouse gas emissions from the Waste chapter is presented
in Table 8-1 and Table 8-2.
Overall, in 2004, waste activities generated emissions of 193.8 Tg CO2 Eq., or 3 percent of total U.S. greenhouse
gas emissions.
8.1. Landfills (IPCC Source Category 6A1)
2004 Waste Chapter Greenhouse Gas Sources
Landfills are the largest anthropogenic source of CH4 emissions in the United States. In 2004, landfill CH4 emissions were
approximately 140.9 Tg CO2 Eq. (6,709 Gg). Emissions from municipal solid waste (MSW) landfills, which received about
61 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 1,800 operational landfills exist in the United States,
with the largest landfills receiving most of the waste and generating the majority of the CH4 (BioCycle 2004).
After being placed in a landfill, waste (such as paper, food FJQlire 8-1
scraps, and yard trimmings) is initially decomposed by aerobic
bacteria. After the oxygen has been depleted, the remaining
waste is available for consumption by anaerobic bacteria,
which break down organic matter into substances such as
cellulose, amino acids, and sugars. These substances are further
broken down through fermentation into gases and short-chain
organic compounds that form the substrates for the growth
of methanogenic bacteria. These CH4-producing anaerobic
bacteria convert the fermentation products into stabilized
organic materials and biogas consisting of approximately 50 Tg CO, Eq.
percent carbon dioxide (CO2) and 50 percent CH4, by volume.2
Landfills
Human Sewage
30
60
120
150
1 Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as described in the Land
Use, Land-Use Change, and Forestry chapter.
2 The percentage of CO2 in biogas released from a landfill may be smaller because some CO2 dissolves in landfill water (Bingemer and Crutzen 1987).
Additionally, less than 1 percent of landfill gas is typically composed of non-methane volatile organic compounds (NMVOCs).
Waste 8-1
-------
Table 8-1: Emissions from Waste (Tg C02 Eq.)
Gas/Source
CH4
Landfills
Wastewater Treatment
N20
Human Sewage
Total
Note: Totals may not sum due to
Table 8-2: Emissions from
Gas/Source
CH4
Landfills
Wastewater Treatment
N20
Human Sewage
NMVOCs
CO
NO,
1990
197.1
172.3
24.8
12.9
12.9
210.0
independent rounding.
Waste (Gg)
1990
9,385
8,206
1,180
42
42
673
1
+
1998
176.9
144.4
32.6
14.9
14.9
191.8
1998
8,425
6,874
1,550
48
48
161
5
3
1999
175.3
141.6
33.6
15.4
15.4
190.7
1999
8,346
6,743
1,602
50
50
140
13
3
2000
173.3
139.0
34.3
15.5
15.5
188.8
2000
8,254
6,619
1,635
50
50
119
8
2
2001
170.8
136.2
34.7
15.6
15.6
186.4
2001
8,135
6,484
1,651
50
50
122
8
2
2002
175.6
139.8
35.8
15.6
15.6
191.3
2002
8,364
6,659
1,705
50
50
133
8
2
2003
179.0
142.4
36.6
15.8
15.8
194.8
2003
8,524
6,782
1,742
51
51
134
8
2
2004
177.8
140.9
36.9
16.0
16.0
193.8
2004
8,467
6,709
1,758
52
52
134
8
2
Note: Totals may not sum due to independent rounding.
Significant CH4 production typically begins one or two
years after waste disposal in a landfill and continues for
10 to 60 years.
From 1990 to 2004, net CH4 emissions from landfills
decreased by approximately 18 percent (see Table 8-3 and
Table 8-4), with small increases occurring in some interim
years. This downward trend in overall emissions is the result
of increases in the amount of landfill gas collected and
combusted by landfill operators, which has more than offset
the additional CH4 emissions resulting from an increase in
the amount of municipal solid waste landfilled.
CH4 emissions from landfills are a function of several
factors, including: (1) the total amount of municipal solid
waste in landfills, which is related to total municipal solid
waste landfilled annually; (2) the characteristics of landfills
receiving waste (i.e., composition of waste-in-place, size,
climate); (3) the amount of CH4 that is recovered and either
flared or used for energy purposes; and (4) the amount of
CH4 oxidized in landfills instead of being released into the
atmosphere. The estimated annual quantity of waste placed
in landfills increased from about 209 Tg in 1990 to 279 Tg
in 2004, an increase of 33 percent (see Annex 3.14). During
this period, the estimated CH4 recovered and combusted
from landfills increased as well. In 1990, for example,
approximately 930 Gg of CH4 were recovered and combusted
(i.e., used for energy or flared) from landfills. In 2004,
the estimated quantity of CH4 recovered and combusted
increased to 5,343 Gg.
Over the next several years, the total amount of
municipal solid waste generated is expected to increase as
the U.S. population continues to grow. The percentage of
waste landfilled, however, may decline due to increased
recycling and composting practices. In addition, the quantity
of CH4 that is recovered and either flared or used for energy
purposes is expected to increase primarily as a result of 1996
federal regulations that require large municipal solid waste
landfills to collect and combust landfill gas (see 40 CFR Part
60, Subpart Cc 2005 and 40 CFR Part 60, Subpart WWW
2005), and the Landfill Methane Outreach Program (LMOP),
an EPA program that encourages voluntary CH4 recovery and
use at landfills not affected by the regulation.
Methodology
CH4 emissions from landfills were estimated to equal the
CH4 produced from municipal solid waste landfills, minus
the CH4 recovered and combusted, plus the CH4 produced
8-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 8-3: CH4 Emissions from Landfills (Tg C02 Eq.)
Activity
1990
1998
1999
2000
2001
2002
2003
2004
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
197.2
13.8
(14.0)
(5.5)
(19.1)
219.1
15.3
(41.6)
(32.4)
(16.0)
222.3
15.6
(47.0)
(33.5)
(15.7)
226.5
15.9
(50.8)
(37.1)
(15.4)
231.9
16.2
(56.2)
(40.7)
(15.1)
238.6
16.7
(56.3)
(43.7)
(15.5)
245.0
17.2
(57.8)
(46.2)
(15.8)
251.2
17.6
(59.7)
(52.5)
(15.7)
Total
172.3
144.4
141.6
139.0
136.2
139.8
142.4
140.9
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
aIncludes oxidation at both municipal and industrial landfills.
Table 8-4: CH4 Emissions from Landfills (Gg)
Activity
1990
1998
1999
2000
2001
2002
2003
2004
MSW Landfills
Industrial Landfills
Recovered
Gas-to-Energy
Flared
Oxidized3
9,391
657
(667)
(263)
(912)
10,435
730
(1,982)
(1,545)
(764)
10,588
741
(2,239)
(1,597)
(749)
10,785
755
(2,419)
(1,767)
(735)
11,045
773
(2,676)
(1,938)
(720)
11,364
795
(2,679)
(2,082)
(740)
11,669
817
(2,751)
(2,199)
(754)
11,960
837
(2,841)
(2,502)
(745)
Total
8,206
6,874 6,743 6,619 6,484 6,659 6,782
6,709
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
aIncludes oxidation at municipal and industrial landfills.
by industrial landfills, minus the CH4 oxidized before being
released into the atmosphere:
CH4 Solid Waste = [(CH^MSW - R) + CH4 lnd] - Ox
where,
Solid Waste
= CH4 emissions from solid waste
CH4 MSw = CH4 generation from municipal solid
waste landfills,
R = CH4 recovered and combusted,
CH4 lnd = CH4 generation from industrial
landfills, and
Ox = CH4 oxidized from MSW and
industrial landfills before release to
the atmosphere.
The methodology for estimating CH4 emissions from
municipal solid waste landfills is based on the first order
decay model described in the Intergovernmental Panel on
Climate Change (IPCC) Good Practice Guidance (IPCC
2000) and in a background paper prepared by Jensen and
Pipatti (2002). Values for the CH4 generation potential (L0)
and rate constant (k) were obtained from an analysis of
CH4 recovery rates for a database of 52 landfills and from
published studies of other landfills (RTI 2004; EPA 1998;
SWANA 1998; Peer, Thorneloe, and Epperson 1993). The
rate constant was found to increase with average annual
rainfall; consequently, values of k were developed for 3
ranges of rainfall. The annual quantity of waste placed in
landfills was apportioned to the 3 ranges of rainfall based on
the percent of the U.S. population in each of the 3 ranges,
and historical census data were used to account for the
shift in population to more arid areas over time. For further
information, see Annex 3.14.
National landfill waste generation and disposal data for
1989 through 2004 were obtained from BioCycle (2004).
Because BioCycle does not account for waste generated
in U.S. territories, waste generation for the territories was
estimated using population data obtained from the U.S.
Census Bureau (2005) and national per capita solid waste
generation from BioCycle (2004). Estimates of the annual
quantity of waste landfilled for 1960 through 1988 were
obtained from EPA s Anthropogenic Methane Emissions in
the United States, Estimates for 1990: Report to Congress
(EPA 1993) and an extensive landfill survey by the EPAs
Waste 8-3
-------
Office of Solid Waste in 1986 (EPA 1988). Although waste
placed in landfills in the 1940s and 1950s contributes very
little to current CH4 generation, estimates for those years
were included in the first order decay model for completeness
in accounting for CH4 generation rates and are based on the
population in those years and the per capita rate for land
disposal for the 1960s.
The estimated landfill gas recovered per year was
based on updated data collected from vendors of flaring
equipment, a database of landfill gas-to-energy (LFGTE)
projects compiled by EPA's Landfill Methane Outreach
Program (LMOP) (EPA 2005a), and a database maintained
by the Energy Information Administration (EIA) for the
voluntary reporting of greenhouse gases (EIA 2005). The
three databases were carefully compared to identify landfills
that were in two or all three of the databases to avoid double-
counting reductions. Based on the information provided
by the EIA and flare vendor databases, the CH4 combusted
by flares in operation from 1990 to 2004 was estimated.
This quantity likely underestimates flaring because these
databases do not have information on all flares in operation.
Additionally, the EIA and LMOP databases provided data
on landfill gas flow and energy generation for 359 landfills
with LFGTE projects. If a landfill in the EIA database was
also in the LMOP and/or the flare vendor database, the
emissions avoided were based on the EIA data because
landfill owners or operators reported the amount recovered
based on measurements of gas flow and concentration, and
the reporting accounted for changes over time. If both flare
data and LMOP recovery data were available for any of the
remaining landfills (i.e., not in the EIA database), then the
emissions recovery was based on the LMOP data, which
provides reported landfill-specific data on gas flow for
direct use projects and project capacity (i.e., megawatts)
for electricity projects. The flare data, on the other hand,
only provided a range of landfill gas flow for a given flare
size. Given that each LFGTE project is likely to also have
a flare, double counting reductions from flares and LFGTE
projects in the LMOP database was avoided by subtracting
emissions reductions associated with LFGTE projects for
which a flare had not been identified from the emissions
reductions associated with flares.
Emissions from industrial landfills were assumed to
be equal to seven percent of the total CH4 emissions from
municipal landfills (EPA 1993). The amount of CH4 oxidized
by the landfill cover at both municipal and industrial landfills
was assumed to be ten percent of the CH4 generated that is
not recovered (Mancinelli and McKay 1985; Czepiel et al.
1996). To calculate net CH4 emissions, both CH4 recovered
and CH4 oxidized were subtracted from CH4 generated at
municipal and industrial landfills.
Uncertainty
Several types of uncertainty are associated with the
estimates of CH4 emissions from landfills. The primary
uncertainty concerns the characterization of landfills.
Information is not available on two fundamental factors
affecting CH4 production: the amount and composition of
waste placed in every landfill for each year of its operation. The
approach used here assumes that the CH4 generation potential
and the rate of decay that produces CH4 as determined from
several studies of CH4 recovery at landfills are representative
of U.S. landfills. Also, the approach used to estimate the
contribution of industrial non-hazardous wastes to total CH4
generation introduces uncertainty. Aside from uncertainty in
estimating CH4 generation potential, uncertainty exists in the
estimates of oxidation by cover soils.
The N2O emissions from the application of sewage
sludge on landfills are not explicitly modeled as part of
greenhouse gas emissions from landfills. N20 emissions
from sewage sludge applied to landfills would be relatively
small because the microbial environment in landfills is
not very conducive to the nitrification and denitrification
processes that result in N2O emissions. The total nitrogen
(N) in sewage sludge increased from 189 to 261 Gg total N
between 1990 and 2004, however; the quantity of sewage
sludge applied to landfills decreased from 28 to 10 percent
from 1990 to 2004.3
The results of the Tier 2 quantitative uncertainty analysis
are summarized in Table 8-5. Landfill CH4 emissions in 2004
were estimated to be between 90.2 and 163.4 Tg CO2 Eq.
at a 95 percent confidence level (or in 19 out of 20 Monte
Carlo Stochastic Simulations). This indicates a range of 36
3 The methodology for estimating the quantity of N in sewage sludge disposed via incineration, land application, surface disposal, landfill, ocean dumping,
and other is described in Annex 3.11 Methodology for Estimating N2O Emissions From Agricultural Soil Management.
8-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg C02 Eq. and Percent)
Source
2004 Emission
Estimate Uncertainty Range Relative to Emission Estimate3
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Landfills
CH4 140.9 90.2 163.4 -36% +16%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
percent below to 16 percent above the 2004 emission estimate
of 140.9 Tg CO2 Eq.
Recalculations Discussion
The primary recalculation was that associated with
updating the EIA, LMOP, and flare vendor databases. The
estimates of gas recovery at LFGTE projects decreased by 6.6
percent for the 2003 estimate, and most of this change is due
to updating the EIA database. The EIA database for 2003 did
not become available until late in 2004; consequently, the gas
recovery rate for 2003 was estimated from the 2002 data. The
2004 update showed that LFGTE projects in the EIA 2002
database reported less gas recovery in 2003 than 2002, which
decreased the estimate of CH4 recovery. Another change
affecting estimates of CH4 recovery was due to additional
projects reported in the EIA update that were previously
included in the LMOP database. The recovery rates for these
projects were changed to reflect the EIA estimate rather than
the estimate of the LMOP database. A preference is given
to the EIA database because those estimates are based on
measured gas recovery rates, and they reflect changes in the
recovery rate over time. Other changes affecting (decreasing)
recovery rates over the time series resulted from identifying
a few landfill projects that were inadvertently included in
more than one of the three databases used to estimate gas
recovery. There were also changes due to correcting and
updating the LMOP database with changes in operational
status and project start date. Overall, these changes resulted
in an average annual decrease of 2.8 percent over the time
series in CH4 recovered by gas-to-energy projects.
Similar updates were made to the flare database and
flares in the EIA database. The flare changes resulted in an
average annual decrease of 8.4 percent in reductions due
to flaring over the 1990 to 2003 time series. The primary
factor causing this decrease was an adjustment made to
the estimates for flaring when the flare vendor supplied
information on the flare's maximum capacity. An analysis
of flare capacity versus measured CH4 flow rates from the
EIA database showed that the flares operated at 51 percent of
capacity when averaged over the time series and at 72 percent
of capacity for the highest flow rate for a given year. For those
cases when the flare vendor supplied maximum capacity, the
analysis was revised to estimate actual flow as 50 percent
of capacity. Other factors contributing to the decrease were
the update of the recovery by flares in the EIA database and
removing flares inadvertently included in the flare database
because they were reported in the EIA database. Average
annual CH4 emissions over the time series increased by 4
percent because of the decrease in estimates of CH4 recovered
for gas-to-energy projects and flaring.
The recovery of CH4 for flaring increased by 14 percent
from 2003 to 2004 (from 2,199 Gg to 2,502 Gg). This
increase was due to 41 additional flares identified by flare
vendors as becoming operational in 2004 and an additional 9
landfills with flares added to the EIA database. CH4 recovery
by LFGTE proj ects increased by 3 percent from 2003 to 2004
(from 2,751 Gg to 2,841 Gg). This increase was due to 22 new
projects in the LMOP database becoming operational in 2004
and the addition of 4 new projects to the EIA database.
Planned Improvements
For future inventories, emerging guidance will be
incorporated to help provide more accurate estimates of
CH4 generation by using the first order decay model and
incorporating a delay time for CH4 generation. The equation
presented by Jensen and Pipatti (2002) and the 1996 IPCC
guidance approximates the CH4 generation rate using an
estimate of the instantaneous rate at a point in time. This
approximation simplifies estimating CH4 generation using
nationwide totals for waste disposal for each year. The
revised guidance will improve the CH4 generation estimate
and incorporate a time lag to reflect the delay in CH4
Waste 8-5
-------
Box 8-1: Biogenic Emissions and Sinks of Carbon
C02 emissions from the combustion or decomposition of biogenic materials (e.g., paper, wood products, and yard trimmings) grown
on a sustainable basis are considered to mimic the closed loop of the natural carbon cycle—that is, they return to the atmosphere C02 that
was originally removed by photosynthesis. However, CH4 emissions from landfilled waste occur due to the man-made anaerobic conditions
conducive to CH4 formation that exist in landfills, and are consequently included in this inventory.
The removal of carbon from the natural cycling of carbon between the atmosphere and biogenic materials—which occurs when wastes of
biogenic origin are deposited in landfills—sequesters carbon. When wastes of sustainable, biogenic origin are landfilled, and do not completely
decompose, the carbon that remains is effectively removed from the global carbon cycle. Landfilling of forest products, yard trimmings,
and food scraps resulted in net long-term storage of 9.3 Tg C02 Eq. in 2004, as described in the Land Use, Land-Use Change, and Forestry
chapter, based on methods presented in the IPCC Good Practice Guidance for Land Use, Land-Use Change and Forestry (IPCC 2003).
generation from the time the waste is disposed. The new
guidance will result in a decrease of about 2 percent in the
CH4 generation rates presented here.
Additional efforts will be made to improve the estimates
of CH4 generation at industrial landfills and estimates of
oxidation, especially for landfills with gas recovery systems.
Improvements to the flare database will be investigated, and
an effort will be made to identify additional landfills that have
flares. The parameters for the first order decay model will be
re-evaluated as more data become available.
8.2. Wastewater Treatment (IPCC
Source Category 6B)
Wastewater from domestic (municipal sewage) and
industrial sources is treated to remove soluble organic matter,
suspended solids, pathogenic organisms, and chemical
contaminants. Treatment may either occur off-site or on-
site. For example, in the United States, approximately 25
percent of domestic wastewater is treated in septic systems
or other on-site systems (EPA 1996). 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 organic content, expressed in terms of either
biochemical oxygen demand (BOD) or chemical oxygen
demand (COD), governs the CH4 producing potential of
wastewater. BOD represents the amount of oxygen that
would be required to completely consume the organic matter
contained in the wastewater through aerobic decomposition
processes. COD refers to the amount of oxygen consumed
under specified conditions in the oxidation of the organic
and oxidizable inorganic matter and is a parameter typically
used to characterize industrial wastewater.
In 2004, CH4 emissions from domestic wastewater
treatment were estimated to be 20.0 Tg CO2 Eq. (953
Gg). Emissions have increased since 1990 in response
to the increase in the U.S. human population. Also, the
per capita organic wastewater loading has increased. In
2004, CH4 emissions from industrial wastewater treatment
were estimated to be 16.9 Tg CO2Eq. (805 Gg). Industrial
emission sources include wastewater from the pulp and
paper, meat and poultry, and the vegetables, fruits and juices
processing industries.4 Table 8-6 and Table 8-7 provide
emission estimates from domestic and industrial wastewater
treatment.
Methodology
Domestic wastewater CH4 emissions were estimated
using the default IPCC methodology:
CH
4 (domestic wastewat
ter) = UoP
X 365 X
16.25 % x EF
4 Emissions associated with refinery wastewater are estimated in Annex 2.3 Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil
Fuels. Other industrial sectors include organic chemicals, starch production, alcohol refining, creameries, and textiles, however emissions from these
sectors are considered to be insignificant.
8-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 8-6: CH4 Emissions from Domestic and Industrial Wastewater Treatment (Tg C02 Eq.)
Activity
1990
1998
1999
2000
2001
2002
2003
2004
Domestic
Industrial*
11.4
13.4
16.4
16.1
17.1
16.5
17.8
16.5
18.5
16.2
19.1
16.7
19.8
16.7
20.0
16.9
Total
24.8
32.6
33.6
34.3
34.7
35.8
* Industrial activity includes the pulp and paper, meat and poultry, and the vegetables, fruits and juices processing industries.
Note: Totals may not sum due to independent rounding.
36.6
36.9
* Industrial activity includes the pulp and paper, meat and poultry, and the vegetables, fruits and juices processing industries.
Note: Totals may not sum due to independent rounding.
Table 8-7: CH4 Emissions from Domestic and Industrial Wastewater Treatment (Gg)
Activity
Domestic
Industrial*
Total
1990
543
637
1,180
1998
783
767
1,550
1999
815
787
1,602
2000
848
788
1,635
2001
880
771
1,651
2002
912
794
1,705
2003
944
797
1,742
2004
953
805
1,758
where,
CH4 = Total CH4 emissions from
domestic wastewater
(kg/year)
USpop = U.S. population
BOD5 = organic loading in wastewater
(kg BOD5/person.day)5
365 = days per year
16.25% = Percent of wastewater BOD5
that is anaerobically digested
EF = Emission factor (0.6 kg CH4/
kgBOD5)
National population data for 1990 to 2004, used in
the domestic wastewater emissions estimates, were based
on data from the U.S. Census Bureau (2005). For BOD5
for domestic wastewater, two data points were available,
for 1991 and 2003 (Metcalf & Eddy 1990; Metcalf &
Eddy 2003). The BOD loadings for intervening years
were obtained by linear interpolation. Table 8-8 presents
population and domestic wastewater BOD5 produced. The
emission factor (0.6 kg CH4/kg BOD5) was taken from
IPCC Good Practice Guidance (IPCC 2000). The percent
of wastewater BOD5 that was anaerobically digested was
assumed to be 16.25 percent (ARCADIS 2001). This
value also accounts for U.S. septic systems and is based
on expert judgment and on septic system usage data from
EPA (1996).
CH4 emissions estimates from industrial wastewater
were developed according to the methodology described in
IPCC (2000). Industry categories that are likely to produce
significant CH4 emissions from wastewater treatment
were identified. High volumes of wastewater generated
and a high organic wastewater load were the main criteria.
The top three industries that meet these criteria are pulp
and paper manufacturing; meat and poultry packing; and
vegetables, fruits, and juices processing. Table 8-9 presents
the U.S. production of pulp and paper; meat and poultry; and
vegetables, fruits, and juices.
Table 8-8: U.S. Population (Millions) and Domestic
Wastewater BOD5 Produced (Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Population
254
280
283
286
289
292
295
297
BOD6
5,566
8,032
8,363
8,695
9,021
9,351
9,685
9,774
Source: U.S. Census Bureau (2005); Metcalf & Eddy 1990; Metcalf &
Eddy 2003.
5 BOD5 is the 5-day biochemical oxygen demand measurement (Metcalf and Eddy 2003).
Waste 8-7
-------
CH4 emissions from these categories were estimated
by multiplying the annual product output by the average
outflow, the organics loading (in COD or BOD) in the
outflow, the percentage of organic loading assumed to
degrade anaerobically, and the emission factor. For pulp
and paper as well as meat and poultry wastewater, BOD was
used. In developing estimates for the vegetables, fruits, and
juices category, COD was used instead of BOD, because
no accurate BOD numbers were available. The emission
factor used for pulp and paper as well as meat and poultry
wastewater is 0.6 kg CH4/kg BOD5, whereas the emission
factor for vegetables, fruits and juices category is 0.25 kg
CH4/kg COD (IPCC 2000). The methodological equation
is:
CH4 (mdusteal wastewater) = P x W x (COD or BOD) x
MCF x EF
where,
CH4 (mdustnai wastewater) = Total CH4 emissions from
industrial wastewater (kg/year)
P = Industry output (metric tons/
year)
W = Wastewater generated (m3/
metric ton of product)
COD or BOD = Organics loading in
wastewater (kg /m3)
MCF = CH4 correction factor,
indicating the extent to which
the organic COD or BOD
degrades anaerobically
EF = Emission factor (0.6 kg CH4/
kg BOD5 for meat and poultry
and pulp and paper; 0.25 kg
CH4/kg COD for vegetables,
fruits and juices)
Wastewater treatment for the pulp and paper industry
typically includes neutralization, screening, sedimentation,
and flotation/hydrocycloning to remove solids (World
Bank 1999, Nemerow and Dasgupta 1991). Secondary
treatment (storage, settling, and biological treatment)
mainly consists of lagooning. In determining the percent
that degrades anaerobically, both primary and secondary
treatment were considered. Primary treatment lagoons are
aerated to reduce anaerobic activity. However, the lagoons
are large and zones of anaerobic activity may occur and,
consequently, the primary lagoons are assumed to be 1.4
percent anaerobic (expert judgment). Approximately 42
percent of the BOD passes on to secondary treatment, which
is less likely to be aerated (EPA 1993). Twenty-five percent
of the BOD in secondary treatment lagoons was assumed to
degrade anaerobically, while 10 percent passes through to
be discharged with the effluent (EPA 1997a). Consequently,
the overall percentage of wastewater organics that degrade
anaerobically was determined to be 10.3 percent (i.e., 58% x
1.4% + 42% x 90% x 25%). A time series of CH4 emissions
for post-1990 years was developed based on production
figures reported in the Lockwood-Post Directory (Lockwood-
Post 2002). The overall wastewater outflow was estimated to
be 85 m3/metric ton, and the average BOD loading entering
the secondary treatment lagoons was estimated to be 0.4 gram
BOD/liter (EPA 1997b, EPA 1993, World Bank 1999).
Table 8-9: U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg)
Year
1990
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Pulp and Paper
128.9
140.9
140.3
145.6
144.0
145.1
142.8
134.3
137.5
140.0
140.0
Meat
(carcass weight)
17.6
19.8
19.8
19.7
20.5
21.0
21.0
20.8
21.5
21.2
21.5
Poultry
(carcass weight)
10.6
13.8
14.5
15.0
15.1
16.0
16.4
16.8
17.3
17.5
17.7
Vegetables,
Fruits and Juices
29.8
36.8
36.4
37.7
36.5
37.4
38.9
35.0
36.5
34.1
36.6
8-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 8-10: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Wastewater Treatment (Tg C02 Eq.
and Percent)
Source
Gas
2004 Emission Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate3
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Wastewater Treatment
CH4
36.9
24.9
51.2
-33%
+39%
! Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
The meat and poultry processing industry makes
extensive use of anaerobic lagoons in sequence with
screening, fat traps and dissolved air flotation. Production
data, in carcass weight for the meat and poultry industry,
were obtained from the U.S. Census (2004). EPA (2002)
provided estimates for wastewater flows into anaerobic
lagoons: 7.9 and 16.6 m3/metric ton for meat and poultry
production, respectively. The loadings are 2.8 and 1.5 g
BOD/liter for meat and poultry, respectively. Ninety percent
of organic BOD is believed to degrade anaerobically in the
lagoon (EPA 1997V).
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 andDasgupta 1991). Consequently, 5
percent of these wastewater organics are assumed to degrade
anaerobically. The USDA National Agricultural Statistics
Service (USDA 2004) provided production data for the fruits,
vegetables, and juices processing sector. Outflow data for
various subsectors (canned fruit, canned vegetables, frozen
vegetables, fruit juices, jams, baby food) were obtained from
World Bank (1999) and an average wastewater outflow of
5.6 m3/metric ton was used. For the organics loading, a COD
value of 5 g/liter was used (EPA 1997V).
Uncertainty
The overall uncertainty associated with the 2004 CH4
emissions estimate from wastewater treatment was calculated
using the IPCC Good Practice GuidanceTier 2 methodology.
Uncertainty associated with the parameters used to estimate
CH4 emissions included that of numerous input variables
used to model emissions from domestic wastewater, and
wastewater from the pulp and paper industry, meat and
poultry processing, as well as from fruits, vegetables and
juices processing.
The results of this Tier 2 quantitative uncertainty
analysis are summarized in Table 8-10. CH4 emissions from
wastewater treatment were estimated to be between 24.9 and
51.2 Tg CO 2 Eq. at the 95 percent confidence level (or in 19
out of 20 Monte Carlo Stochastic Simulations). This indicates
a range of approximately 33 percent below to 39 percent
above the 2004 emissions estimate of 36.9 Tg CO2 Eq.
Recalculations Discussion
The 2004 estimates did not include any methodological
changes or refinements. However, the time series for
domestic wastewater changed because population estimates
for the United States and U.S. territories changed slightly.
This change resulted in a less than one percent decrease in
emission estimates over the time series.
Planned Improvements Discussion
The methodology to estimate emissions from domestic
wastewater uses a factor of 16.25 percent for the overall
quantity of organics (BOD) in wastewater that is anaerobically
digested. This factor is based on the percentage of the
population that uses septic systems and on the amount of
BOD that degrades anaerobically in septic systems and in
centralized treatment plants. Information may be available
that will allow for refinement of this factor. Another area for
improvement is characterization of pulp and paper wastewater
treatment (organics loading, wastewater generation and
anaerobic degradation percentage).
Waste 8-9
-------
8.3. Human Sewage (Domestic
Wastewater) (IPCC Source Category
6B)
Domestic human sewage is usually mixed with other
household wastewater, which includes effluent from
shower drains, sink drains, washing machines, etc., and is
either discharged directly, or transported to an on-site or
decentralized wastewater treatment system, or to a centralized
wastewater treatment system. Decentralized wastewater
treatment systems are septic systems and package plants.
Centralized wastewater treatment systems may include a
variety of processes, ranging from lagooning to advanced
tertiary treatment technology for removing nutrients. Often,
centralized wastewater treatment systems also treat certain
flows of industrial, commercial, and institutional wastewater.
After processing, treated effluent is discharged to a receiving
water environment (e.g., river, lake, estuary, etc.), or applied
to soils, or disposed of below the surface.
N2O may be generated during both nitrification and
denitrification of the nitrogen present, usually in the form
of urea, ammonia, and proteins. These compounds are
converted to nitrate (N03) 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). N20 can be an intermediate
product of both processes, but is more often associated with
denitrification.
The United States identifies two distinct sources for
N2O emissions from domestic wastewater: emissions
from centralized wastewater treatment processes; and
emissions from effluent that has been discharged into aquatic
environments. The 2004 emissions of N20 from wastewater
treatment processes and from effluent were estimated to
be 0.3 Tg CO2 Eq. (1 Gg) and 15.8 Tg CO2 Eq. (51 Gg),
respectively. Total N20 emissions from domestic wastewater
were estimated to be 16.0 Tg CO2 Eq. (52 Gg) (see Table
8-11). Emissions from wastewater treatment processes have
Table 8-11: N20 Emissions from Human Sewage (Tg C02
Eq. and Gg)
Year
1990
1998
1999
2000
2001
2002
2003
2004
Tg C02 Eq.
12.9
14.9
15.4
15.5
15.6
15.6
15.8
16.0
Gg
42
48
50
50
50
50
51
52
gradually increased as a result of increasing U.S. population
and protein consumption.
Methodology
The IPCC default methodology (IPCC/UNEP/OECD/
IEA 1997) assumes that nitrogen disposal, and thus N20
emissions associated with land disposal, subsurface disposal,
and domestic wastewater treatment are negligible and all
nitrogenis discharged directly into aquatic environments. For
the United States, N20 emissions from domestic wastewater
(human sewage) were estimated using the IPCC methodology
with three modifications:
• In the United States, a certain amount of nitrogen is
removed with sewage sludge, which is applied to land,
incinerated or landfilled (Nsludge). The nitrogen disposal
into aquatic environments is reduced to account for the
sewage sludge application.6
• The IPCC methodology uses annual, per capita protein
consumption (kg protein/(person-year)). This number
is likely to underestimate the amount of protein
entering the sewer or septic system. Food (waste)
that is not consumed is often washed down the drain,
as a result of the use of garbage disposals. Also, bath
and laundry water can be expected to contribute to
nitrogen loadings. A factor of 1.4 is introduced to
account for non-consumption nitrogen.7 Furthermore, a
6 The methodology for estimating the quantity of sewage sludge N not entering aquatic environments is described in Annex 3.11 Methodology for Estimating
N2O Emissions From Agricultural Soil Management.
7 Metcalf & Eddy (1991) provides an indication of the nitrogen concentration of 40 mg Total Kjeldahl Nitrogen (TKN)/liter for average wastewater from
residences, which includes bathwater, laundry, and the use of garbage disposals. According to the Needs Survey (1996), the total volume of wastewater
generated in the United States in 1996 was 32,175 million gallons per day (MGD), serving 189,710,899 people (72 percent of population, not including
the septic system users). In 1996, the per capita TKN loading was: 40 [mg/1] x 32,175 x 106 [gal/day] x 3.8 [I/gal] x 365 days/yr x 1/(189.7 x 106) x 10 «
= 9.4 [kg TKN/yr.person]. Average protein intake in 1996 was 41 kg protein /(person-year) (6.6 kg N/(person-year)), leading to a factor of 1.4 (9.4/6.6).
8-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
significant quantity of industrial wastewater (nitrogen)
is co-discharged with domestic wastewater. To account
for this, a factor of 1.25 is introduced. In summary,
a factor of 1.75 (1.4 x 1.25) is used to account for
the extra nitrogen discharge from kitchen, bath, and
laundry wastes, as well as industrial wastewater that is
co-discharged into sewers, based on Metcalf & Eddy
(1991) and expert judgment.
• Process emissions from wastewater treatment plants are
not accounted for in the current IPCC methodology. To
estimate N20 emissions from U.S. wastewater treatment
plants, an overall emission factor (4 g N2O/(person-
year)) was introduced. This emission factor is based
on a factor of 3.2 g N2O/(person-year) (Czepiel et al.
1995) multiplied by the 1.25 factor mentioned above,
which adjusts for co-discharged industrial nitrogen
and is based on expert judgment. The nitrogen quantity
associated with these emissions (NWWT) is calculated
by multiplying the N2O emitted by (2 x 14)144 and is
subtracted from the total quantity of nitrogen that is
ultimately disposed into the aquatic environment.
With the modifications described above, N20 emissions
from domestic wastewater were estimated using the IPCC
default methodology (IPCC/UNEP/OECD/IEA 1997). This
methodology is illustrated below:
N20(s) = (USpop x 0.75 x EFj x 1O3) +
{[(Protein x 1.75 x FracNPR x USPOP) - NWWT - Nsludge] x
NPR
EF2 x
where,
N20(s) = N20 emissions from domestic wastewater
("human sewage") [kg/year]
USpop = U.S. population
0.75 = Fraction of population using centralized
wastewater treatment plants (as opposed to
septic systems)
EFj = Emission factor (4 g N2O/person-year)
expressing emissions from the centralized
wastewater treatment plants
Protein = Annual per capita protein consumption
[kg N/(person-year)]
1.75 = Fraction of non-consumption protein in
domestic wastewater
FracNP = Fraction of nitrogen in protein
(i.e., 0.16 kg N/kg protein)
NWWT = Quantity of wastewater nitrogen removed
by wastewater treatment processes
[(USp0p x 0.75 x EFjX 10-3) x 28/44]
([kg N/year)
N,
sludge
= Quantity of sewage sludge N not
entering aquatic environments (kg N/year)
EF2 = Emission factor (kg N2O-N/kg sewage-
N produced)
(44/28) = Molecular weight ratio of N20 to N2.
U.S. population data were taken from the U.S. Census
Bureau International Database (2005) and include the
populations of the United States, American Samoa, Guam,
Northern Mariana Islands, Puerto Puco, and the Virgin
Islands. The fraction of the U.S. population using wastewater
treatment plants is from the Needs Survey (EPA 1996). The
emission factor (EFj) to estimate emissions from wastewater
treatment is based on Czepiel, et al. (1995). Data on annual
per capita protein intake were provided by the United Nations
Food and Agriculture Organization for the 1990 to 2002
time frame (FAO, 2002). Because data on protein intake
were unavailable for 2003 and 2004, the value of per capita
protein consumption was extrapolated from previous years.
Table 8-12: U.S. Population (Millions) and Average
Protein Intake [kg/(person-year)]
Year
1990
1998
1999
2000
2001
2002
2003
2004
Population
254
280
283
286
289
292
295
297
Protein
39.2
41.2
42.0
41.9
41.8
41.6
41.8
42.0
Source: U.S. Census Bureau 2005, FAO 2002, and extrapolation from
FAO 2002.
8 The type, composition, and quantity of this co-discharged wastewater vary greatly between municipalities. Metcalf & Eddy (1991) provide an indicative
nitrogen loading of 20 to 85 mg TKN/liter (average 55) for combined residential and industrial wastewater, while residential wastewater loading was
roughly estimated at 40 mg TKN/liter (see previous footnote). Until better data become available, the amount of N in wastewater is increased by 10 mg/1
to account for industrial co-discharge (factor of 1.25).
Waste 8-11
-------
Table 8-12 presents the data for U.S. population and average
protein intake. An emission factor to estimate emissions
from effluent (EF2) has not been specifically estimated for
the United States, thus the default IPCC value (0.01 kg
N2O-N/kg sewage-N produced) was applied. The fraction of
nitrogen in protein (0.16 kg N/kg protein) was also obtained
from IPCC/UNEP/OECD/IEA (1997).
Uncertainty
The overall uncertainty associated with the 2004 N20
emissions estimate from human sewage was calculated using
the IPCC Good Practice Guidance Tier 2 methodology.
Uncertainty associated with the parameters used to estimate
N2O emissions included that of sewage sludge disposal,
total U.S. population, average protein consumed per person,
fraction of nitrogen in protein, non-consumption nitrogen
factor, emission factors for individuals and per mass of
wastewater, and for the percentage of total population using
centralized wastewater treatment plants. The activity data
inputs and their associated uncertainties and distributions
are summarized in Table 8-13.
The results of this Tier 2 quantitative uncertainty
analysis are summarized in Table 8-14. N20 emissions from
human sewage were estimated to be between 4.1 and 30.3
Tg CO2 Eq. at the 95 percent confidence level (or in 19 out
of 20 Monte Carlo Stochastic Simulations). This indicates a
range of approximately 75 percent below to 89 percent above
the 2004 emissions estimate of 16.0 Tg CO2 Eq.
Planned Improvements
The default emission factor for N20 from wastewater
effluent has a high uncertainty. Future research may
identify new studies that include updated data. The factor
that accounts for non-sewage nitrogen in wastewater (bath,
laundry, kitchen, industrial components) also has a high
uncertainty. Several parameters constituting this factor
are based on references that have since been updated,
including the Needs Survey (1996) and Metcalf & Eddy
(1991). The uncertainty associated with this factor can
likely be reduced by incorporating more recent data.
Also, the fraction of the U.S. population using centralized
wastewater treatment plants is currently set at 0.75. This
fraction can likely be refined with recent data from the
2004 Needs Survey. The U.S. Environmental Protection
Agency intends to conduct research to update the protein
consumption data.
Table 8-13: Sources of Uncertainty in N20 Emissions from Human Sewage
Variable
Sewage Sludge Disposal (106 metric tons total N)
U.S. and Territories Total Population (million persons)
Protein (kg/(person-yr))
Fraction of Nitrogen in Protein (kg N/kg protein)
Fraction of Non-Consumption Protein in Domestic WW
EF2 (kg N20-N/kg sewage-N produced)
Population Using Centralized Wastewater Treatment
Plants (%)
EFi (g N20/(person-year))
Value
0.26
297
42
0.16
1.75
0.01
75%
4.0
Distribution
Type
Triangular
Normal
Normal
Normal
Normal
Normal
Normal
Normal
Uncertainty Range3
Lower Bound
-39%
-5%
-5%
-2%
-25%
-80%
-25%
-50%
Upper Bound
+39%
+5%
+5%
+2%
+25%
+80%
+25%
+50%
Reference
Expert Judgment
Expert Judgment
Expert Judgment
Expert Judgment
Expert Judgment
IPCC Guidelines
Expert Judgment
Expert Judgment
a Parameters presented represent upper and lower bounds as a percentage of the mean, based on a 95 percent confidence interval.
Table 8-14: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Human Sewage (Tg C02 Eq. and
Percent)
Source
20°E4s«matei0n Uncertainty Range Relative to Emission Estimate"
Gas (TgC02Eq.) (Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Human Sewage
N20 16.0 4.1 30.3 -75% +89%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
8-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Recalculations Discussion
The 2004 estimates did not include any methodological
changes or refinements. However, the time series for
domestic wastewater changed because the amount of
nitrogen that is removed with the sewage sludge (i.e., Nsludge)
was adjusted to include N from surface disposal, ocean
dumping, and other disposals of N, in addition to sewage
sludge that is incinerated, applied to land, or landfilled.
This change resulted in less than a one percent decrease
in emission estimates over the time series relative to the
previous report.
8.4. Waste Sources of Indirect
Greenhouse Gases
In addition to the main greenhouse gases addressed
above, waste generating and handling processes are also
sources of indirect greenhouse gas emissions. Total emissions
of NOX, CO, and NMVOCs from waste sources for the years
1990 through 2004 are provided in Table 8-15.
Methodology and Data Sources
These emission estimates were obtained from preliminary
data (EPA 2005), and disaggregated based on EPA (2003),
which, in its final iteration, will be published on the National
Emission Inventory (NEI) Air Pollutant Emission Trends
web site. Emission estimates of these gases were provided by
sector, using a "top down" estimating procedure—emissions
were calculated either for individual sources or for many
sources combined, using basic activity data (e.g., the amount
of raw material processed) as an indicator of emissions.
National activity data were collected for individual source
categories from various agencies. Depending on the source
category, these basic activity data may include data on
production, fuel deliveries, raw material processed, etc.
Activity data were used in conjunction with emission
factors, which relate the quantity of emissions to the activity.
Emission factors are generally available from the EPA's
Compilation of Air Pollutant Emission Factors, AP-42(EPA
1997). The EPA currently derives the overall emission control
efficiency of a source category from a variety of information
sources, including published reports, the 1985 National Acid
Precipitation and Assessment Program emissions inventory,
and other EPA databases.
Uncertainty
No quantitative estimates of uncertainty were calculated
for this source category. Uncertainties in these estimates,
however, are primarily due to the accuracy of the emission
factors used and accurate estimates of activity data.
Table 8-15: Emissions of NOX, CO, and NMVOC from Waste (Gg)
Gas/Source
NO,
Landfills
Wastewater Treatment
Miscellaneous3
CO
Landfills
Wastewater Treatment
Miscellaneous3
NMVOCs
Landfills
Wastewater Treatment
Miscellaneous3
1990
+
+
+
+
1
1
+
+
673
58
57
558
1998
3
2
+
1
5
5
+
+
161
33
63
65
1999
3
3
+
+
13
12
1
+
140
27
59
54
2000
2
2
+
+
8
7
1
+
119
23
51
46
2001
2
2
+
+
8
7
1
+
122
23
53
46
2002
2
2
+
+
8
7
1
+
133
25
58
51
2003
2
2
+
+
8
7
1
+
134
25
58
51
2004
2
2
+
+
8
7
1
+
134
25
58
51
a Miscellaneous includes TSDFs (Treatment, Storage, and Disposal Facilities under the Resource Conservation and Recovery Act [42 U.S.C. § 6924,
SWDA § 3004]) and other waste categories.
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.5 Gg.
Waste 8-13
-------
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-------
9. Other
The United States does not report any greenhouse gas emissions under the "other" Intergovernmental Panel on Climate
Change (IPCC) sector.
Other 9-1
-------
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-------
1O. Recalculations and
Improvements
Each year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S. Greenhouse
Gas Emissions and Sinks, as attempts are made to improve both the analyses themselves, through the use of
better methods or data, and the overall usefulness of the report. In this effort, the United States follows the
Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance (IPCC 2000), which states, "It is good
practice to recalculate historic emissions when methods are changed or refined, when new source categories are included
in the national inventory, or when errors in the estimates are identified and corrected."
The results of all methodology changes and historical data updates are presented in this section; detailed descriptions of
each recalculation are contained within each source's description contained in this report, if applicable. Table 10-1 summarizes
the quantitative effect of these changes on U.S. greenhouse gas emissions and Table 10-2 summarizes the quantitative effect
on U.S. sinks, both relative to the previously published U.S. Inventory (i.e., the 1990 through 2003 report). These tables
present the magnitude of these changes in units of teragrams of carbon dioxide (CO^ equivalent (Tg C02 Eq). In addition
to the changes summarized by the tables below, three new sources—silicon carbide consumption, lead production, and zinc
production—have been added to the current Inventory.
The Recalculations Discussion section of each source presents the details of each recalculation. In general, when
methodological changes have been implemented, the entire time series (i.e., 1990 through 2003) has been recalculated to
reflect the change, per IPCC Good Practice Guidance. Changes in historical data are generally the result of changes in
statistical data supplied by other agencies. References for the data are provided for additional information.
The following emission sources, which are listed in descending order of absolute average annual change in emissions
from 1990 through 2003, underwent some of the most important methodological and historical data changes. A brief
summary of the recalculation and/or improvement undertaken is provided for each emission source.
• Land Use, Land- Use Change, and Forestry. The most influential of the changes in the Land Use, Land-Use Change, and
Forestry sector occurred in calculations for forest carbon stocks. These changes included the use of survey data, utilizing
all available state surveys in the FIADB with RPA data used as necessary. There were also changes in calculations for
agricultural soil carbon stocks, the most significant being the implementation of the Tier 3 model-based approach for
mineral soils. In addition, these recalculations reflect the inclusion of new categories to the LULUCF chapter (e.g.,
Grassland Remaining Grassland). Overall, these changes, in combination with adjustments in the other sources/sinks,
resulted in an average annual increase in net flux of CO2 to the atmosphere from the Land Use, Land-Use Change, and
Forestry sector of 155.0 Tg C02 Eq. (17 percent) for the period 1990 through 2003.
• Agricultural Soil Management. Changes occurred as a result of minor adjustments in activity data and the use of an
updated version of the DAYCENT model. The DAYCENT model was revised to more realistically represent the grain
filling period and life span of crops. Additionally, this year a different soils database was used for model simulations.
Recalculations and Improvements 10-1
-------
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Flaring
Cement Manufacture
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and Consumption
C02 Consumption
Municipal Solid Waste Combustion
Titanium Dioxide Production
Aluminum Production
Iron and Steel Production
Ferroalloy Production
Ammonia Manufacture & Urea Application
Petrochemical Production
Phosphoric Acid Production
Silicon Carbide Consumption3
Lead Production3
Zinc Production3
Net CO 2 Flux From Land Use, Land-Use Change, and Forestry
International Bunker Fuels
Wood Biomass and Ethanol Consumption
CH4
Stationary Combustion
Mobile Combustion
Coal Mining
Abandoned Underground Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production
Iron and Steel Production
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of Agricultural Residues
Landfills
Wastewater Treatment
International Bunker Fuels
N20
Stationary Combustion
Mobile Combustion
Adipic Acid Production
Nitric Acid Production
Manure Management
Agricultural Soil Management
Field Burning of Agricultural Residues
Human Sewage
N20 Product Usage
Municipal Solid Waste Combustion
Settlements Remaining Settlements
Forest Land Remaining Forest Land
International Bunker Fuels
MFCs, PFCs, and SF6
Substitution of Ozone Depleting Substances
Aluminum Production
HCFC-22 Production
Semiconductor Manufacture
Electrical Transmission and Distribution
Magnesium Production and Processing
Net Change in Total Emissions"
Percent Change
1990
(4.3)
(15.2)
9.2
NC
NC
+
NC
NC
+
NC
NC
0.7
(0.4)
NC
NC
NC
NC
0.1
0.3
0.9
131.7
NC
+
12.7
+
(0.1)
NC
+
(1.6)
14.5
NC
NC
NC
NC
+
NC
+
0.1
(0.1)
NC
12.9
+
(0.3)
NC
NC
+
13.1
+
(0.1)
NC
0.1
0.1
NC
NC
(0.5)
NC
0.1
NC
NC
(0.6)
+
20.9
0.3%
1998
13.0
(6.9)
17.4
NC
NC
+
NC
NC
+
NC
NC
0.6
0.3
NC
NC
NC
NC
0.2
0.3
1.1
137.0
NC
NC
10.4
(0.1)
(0.1)
+
(0.3)
(6.4)
11.2
NC
NC
NC
+
+
NC
+
5.9
+
NC
32.9
+
(0.5)
NC
NC
+
33.4
+
(0.1)
NC
+
+
NC
NC
(2.3)
(2.1)
+
NC
NC
(0.3)
+
53.9
0.8%
1999
17.1
(3.5)
19.0
NC
NC
+
NC
NC
+
NC
NC
0.6
(0.6)
NC
NC
NC
NC
0.1
0.3
1.1
60.4
(0.1)
NC
11.7
(0.1)
+
0.1
(0.4)
(5.7)
10.7
NC
NC
NC
+
(0.6)
NC
+
7.6
+
+
37.2
+
(0.6)
NC
NC
+
37.8
+
(0.1)
NC
+
+
NC
+
(3.3)
(3.0)
+
NC
NC
(0.3)
+
62.7
0.9%
2000
6.3
(11.4)
16.0
NC
NC
+
+
NC
+
(0.1)
NC
0.5
(0.4)
NC
+
NC
NC
0.1
0.3
1.1
62.9
+
NC
12.8
(0.1)
0.1
+
(0.5)
(5.4)
10.3
NC
NC
NC
+
+
+
+
8.3
+
+
14.3
(0.1)
+
NC
NC
+
14.3
+
+
NC
+
+
NC
+
(4.2)
(3.8)
+
NC
NC
(0.4)
+
29.1
0.4%
2001
50.4
38.9
10.9
NC
NC
+
NC
NC
+
(0.1)
NC
0.4
(1.1)
NC
+
NC
NC
0.1
0.3
1.0
58.9
(0.1)
NC
13.4
+
0.2
(0.1)
(0.4)
(6.2)
9.9
NC
NC
NC
0.1
(0.1)
NC
+
10.0
+
+
27.0
+
1.0
NC
NC
+
25.8
+
+
NC
0.1
+
NC
+
(4.6)
(4.6)
NC
NC
NC
(0.1)
+
86.2
1.3%
2002
19.1
0.3
17.6
+
NC
+
NC
NC
+
0.1
NC
0.4
(0.5)
NC
(0.1)
NC
NC
0.1
0.3
0.9
57. 8
NC
(12.9)
17.3
(0.2)
0.3
0.1
(0.3)
(5.3)
9.7
NC
NC
NC
0.1
+
NC
+
13.0
+
NC
26.9
(0.3)
1.9
NC
NC
+
25.2
+
(0.1)
NC
0.1
+
NC
NC
(5.6)
(5.3)
+
NC
NC
(0.2)
(0.1)
57.7
0.8%
2003
36.2
19.5
15.5
0.1
0.1
+
NC
+
+
0.6
+
0.4
(0.4)
(0.2)
(0.3)
NC
NC
0.1
0.3
0.5
53.2
(0.1)
(14.7)
19.4
(0.2)
0.3
1.0
(0.6)
(1.2)
8.8
NC
NC
NC
0.1
+
NC
+
11.3
(0.2)
+
9.3
(0.3)
2.7
0.2
0.9
+
5.7
+
(0.1)
NC
0.1
0.2
NC
+
(6.0)
(6.0)
+
NC
NC
(0.1)
+
58.9
0.9%
+ Absolute value does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
NC (No Change)
a New source category relative to previous inventory.
b Excludes net C02 flux from Land Use, Land-Use Change, and Forestry, and emissions from International Bunker Fuels and Wood Biomass and Ethanol
consumption.
Note: Totals may not sum due to independent rounding.
10-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table 10-2: Revisions to Net Flux of C02 to the Atmosphere from Land Use, Land-Use Change, and Forestry
(Tg C02 Eq.)
Component
Forest Land Remaining Forest Land
Cropland Remaining Cropland
Land Converted to Cropland3
Grassland Remaining Grassland3
Land Converted to Grassland3
Settlements Remaining Settlements
Net Change in Total Flux
Percent Change
1990
175.9
(25.0)
1.5
(4.5)
(17.6)
1.5
131.7
12.6%
1998
186.7
(20.3)
(2.8)
7.5
(21.1)
(13.0)
137.0
15.5%
1999
113.9
(20.3)
(2.8)
7.5
(21.1)
(16.7)
60.4
7.3%
2000
116.9
(20.5)
(2.8)
7.4
(21.1)
(17.0)
62.9
7.6%
2001
116.9
(20.7)
(2.8)
7.4
(21.1)
(20.8)
58.9
7.1%
2002
116.9
(21.3)
(2.8)
7.4
(21.1)
(21.1)
57.8
7.0%
2003
116.9
(22.0)
(2.8)
7.3
(21.1)
(25.0)
53.2
6.4%
+ Absolute value does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
NC (No Change)
a Estimates for this category was reported in Cropland Remaining Cropland in the previous inventory.
Note: Numbers in parentheses indicate a decrease in estimated net flux of C02 to the atmosphere, or an increase in net sequestration.
Note: Totals may not sum due to independent rounding.
Overall, changes resulted in an average annual increase
in nitrous oxide (N20) emissions from agricultural soil
management of 30.6 Tg C02 Eq. (12 percent) for the period
1990 through 2003.
Non-Energy Use of Fuels. There were several refinements
to the methodology for calculating emissions and storage
for petrochemical feedstocks. There was a thorough
review of system boundaries on the mass balance, which
involved reconciling disparities in data for production
and consumption, and making corresponding revisions
to the import/export calculations. Three additional NEU
fates were incorporated into the calculations—antifreeze
and deicers, food additives, and silicone rubber—and
refinery wastewaters was removed from the mass
balance. There were also revisions to the data used to
calculate storage factors. Overall, changes resulted in
an average annual increase in C02 emissions from non-
energy use of fuels of 15.2 Tg C02 Eq. (13 percent) for
the period 1990 through 2003.
Petroleum Systems. There was one major change
to this source with respect to previous inventories.
Previously, offshore petroleum production emissions
were calculated as eight separate sources. New analysis
of the 2000 GOADS report (MMS 2005c) yields
comprehensive shallow and deep water sources and
related emissions factors, which account for all offshore
emissions. The sources from the GOADS analysis have
replaced the eight sources from previous inventories.
Overall, changes resulted in an average annual increase
in methane (CH4) emissions from petroleum systems
of 11.8 Tg C02 Eq. (63 percent) for the period 1990
through 2003.
CO2 from Fossil Fuel Combustion. The most important
change affecting historical estimates for fossil fuel
combustion was the correction of overestimated
emissions from the industrial sector. Previously, a
portion of industrial sector fuels that are exported as
petrochemical feedstocks or used in industrial processes
were not subtracted from fuels consumed for energy
purposes. Overall, this change, along with several other
alterations, resulted in an average annual decrease of 5.6
Tg C02 Eq. (0.1 percent) in C02 emissions from fossil
fuel combustion for the period 1990 through 2003.
Landfills. Changes to historical data were a result of updating
the EIA, LMOP, and flare vendor databases. Average
annual emissions increased over the time series because of
a decrease in estimates of CH4 recovered for gas-to-energy
projects and flaring. Overall, changes resulted in an average
annual increase in CH4 emissions from landfills of 4.7 Tg
C02 Eq. (4 percent) for the period 1990 through 2003.
Natural Gas Systems. The most significant changes to
this source resulted from methodological revisions in
calculating offshore natural gas production emissions.
Previously, these emissions were calculated as five
separate sources. New analysis of the 2000 GOADS
report (MMS 2005c) yields comprehensive shallow
and deep water sources and related emissions factors,
which account for all offshore emissions. The sources
from the GOADS report have replaced the five sources
from previous inventories. Overall, changes resulted
Recalculations and Improvements 10-3
-------
in an average annual decrease in CH4 emissions from
natural gas systems of 4.5 Tg C02 Eq. (3 percent) for
the period 1990 through 2003.
WoodBiomass andEthanol Consumption. The historical
data for wood biomass consumption was adjusted, which
resulted in an average annual decrease in emissions from
wood biomass and ethanol consumption of 2.0 Tg C02
Eq. (0.9 percent) from 1990 through 2003.
Substitution of Ozone Depleting Substances. Assumptions
to the Vintaging Model were updated based on changes
in chemical substitution trends, market sizes, growth
rates, and charge sizes. Overall, changes resulted in
an average annual decrease in hydrofluorocarbon
(HFC) and perfluorocarbon (PFC) emissions from the
substitution of ozone depleting substances of 2.0 Tg
C02 Eq. (3 percent) for the period 1990 through 2003.
10-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
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-------
Mobile Combustion: Estimating CH4 and N20 emissions from highway vehicles depends upon a number of
engine factors, including fuel characteristics, air-fuel mixes, combustion temperatures, as well as usage of
pollution control equipment. The methodology used for the U.S. Inventory applies emission factors per mile
that are based on laboratory testing of vehicles by size, fuel type, and control technology. These factors are
then applied to estimates of annual vehicle miles traveled (VMT) for these vehicle categories, developed
using a combination of data on control technology distribution by model year, vehicle age distributions, and
average mileage accumulation.
Semiconductors: PEVM: Estimates of emissions of PFCs from semiconductor manufacturing rely on a
combination of industry emission reporting and EPA's PEC Emissions Vintage Model (PEVM). PEVM uses an
emission factor based on the historical emissions reported by EPA's semiconductor industry Partners to estimate
emissions from the U.S. semiconductor manufacturers who do not report to EPA. PEVM incorporates detailed
information on the factors that affect the number of layers, tracking U.S. silicon consumption by linewidth
technology and product type. For each linewidth technology and device type, PEVM calculations utilize the
number of layers, the silicon consumption and the specific emission factor to obtain emissions.
Landfills: The United States estimates landfill CH4 emissions using a first order decay model based on the
IPCC, applied to three ranges of precipitation in the United States. The data used to estimate national landfill
waste generation and disposal data come from published reports and from extensive surveys of historic annual
quantities of waste landfilled. Additionally, landfill gas recovered annually is based on data compiled from
industry data reports.
Agricultural Soil Management: DAYCENT: N20 emissions from agricultural soil management are complex and
depend on many factors, including weather, soil type, crop type, fertilizer use, and grazing animals. The United
States applies the DAYCENT model to estimate direct N20 emissions from major crops on mineral soils, as
well as most of the direct N20 emissions from grasslands. The DAYCENT model uses national, regional, and
county-level data inputs to simulate emissions—a finer-grained and more sensitive analysis than the use of
broad emission factors would yield.
-------
xvEPA
United States
Enviromental Protection
Agency
EPA 430-R-06-002 April 2006
Office of Atmospheric Programs (6207J)
Washington, DC 20460
Official Business
Penalty for Private Use
$300
-------
ANNEX 1 Key Category Analysis
The United States has identified national key categories based on the estimates presented in this report. The
IPCC's Good Practice Guidance (JPCC 2000) describes a key category as a "[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."1 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 determination of key categories must also account for the influence of the trends of individual categories.
Therefore, a trend assessment is conducted to identify source and sink categories for which significant uncertainty in
the estimate would have considerable effects on overall emission trends. 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, but can be considered key because of the unique country-specific estimation methods.
The methodology for conducting a key category, analysis, as defined by IPCC's Good Practice Guidance
(IPCC 2000) and IPCC's Good Practice Guidance for Land Use, Land-Use Change and Forestry (IPCC 2003),
includes:
• Tier 1 approach (including both level and trend assessments);
• Tier 2 approach (including both level and trend assessments, and incorporating uncertainty analysis); arid
• Qualitative approach.
This Annex presents an analysis of key categories, both for sources only and also for sources and sinks
(i.e., including LULUCF); discusses Tier I, Tier 2, and qualitative approaches to identifying, key categories;
provides level and trend assessment equations; and provides a brief statistical evaluation of IPCC's quantitative
, methodologies for defining key categories.
Table A- 1 presents the key categories for the United States based on the Tier 1 approach (including and
not including LULUCF categories) using emissions data in this report, and ranked according to their sector and
global warming potential-weighted emissions in 2004. The table also indicates the criteria used in identifying these
source and sink categories (i.e., level, trend, and/or qualitative assessments).
T8U0A-1: KeySoureeCaieoorte8lorOieUDliedSiates[1990-2004]B8$6donTlermiiDToacti
Level Trend Level Trend
Without Without • With With 2004 Emissions
IPCC Source Categories
Energy
COj Emissions from Stationary Combustion— Coal
Mobile Combustion: Road & Other
CO: Emissions from Stationary Combustion— Gas
COz Emissions from Stationary Combustion— Oil
Mobile Combustion: Aviation
Fugitive Emissions from Natural Gas Operations
COj Emissions from Non-Energy Use of Fuels
International Bunker Fuelsb •
Fugitive Emissions from Coal Mining and Handling '
Mobile Combustion: Marine
Mobile Combustion: Road & Cither
Fugitive Emissions from Oil Operations
Industrial Processes
Gas
COi
COz
COz
C02
COi
CH4
CO*
Several
CH4
C02
NaO.
CH4
LULUCF LULUCF LULUCF
,
y
y
y
y
. y
y
y
>
y •
y
y
y
y
y
y
y
y
y
y
y
•
y
y
y
y
y
y
y
y
y
y
y
y
y
LULUCF dual- (TgCO^Eq.)
y
y
y
y
y
y
y
y
y
y
-
2,027.0
1,621.5
1,153,8
619.9
179.6
-153.4
- 118.8
; 95.5
56.3
544
40.6
25.7
A-3
-------
Emissions from Substitutes for Ozone Depleting Substances
COz Emissions from Iron and Steel Production
COz Emissions from Cement Production
COi Emissions from Ammonia Production and Urea Application
SF« Emissions from Electrical Equipment
HFC-23 Emissions from HCFC-22 Manufacture
NzO Emissions from Adipic Acid Production
PFC Emissions from Aluminum Production
Agriculture
Direct NzO Emissions from Agricultural Soils
CH4 Emissions from Enteric Fermentation in Domestic Livestock
Indirect NzO Emissions from Nitrogen Used in Agriculture
CH< Emissions from Manure Management
Waste
Cm Emissions from Solid Waste Disposal Sites
ChU Emissions from Wastewater Handling
COz Emissions from Waste Incineration
Land Use, Land-Use Change, and Forestry
COz Emissions from Forest Land Remaining Forest Land
COz Emissions from Settlements Remaining Settlements
COz Emissions from Cropland Remaining Cropland
Subtotal Without LULUCF
Total Emissions Without LULUCF
Percent of Total Without LULUCF
Subtotal With LULUCF
Total Emissions With LULUCF
Percent of Total With LULUCF
•Qualitative criteria
'Emissions from this source not included in totals.
Several ^
COz -f
COz •/
COz
SF«
MFCs '
NzO
PFCs
NzO J
CH4 ^
NzO S
CH4
CH4 '
CH4
COz
COz
COz
COz
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
103.3
51.3
45.6
16.9
15.6
13.8
5.7
. 2.8
170.9
112.6
. . 90.6
39.4
140.9
' 36.9
19.4
(637.2)
(97.3)
(28.9)
6,918.2
7,067.6
97.9%
6,154.8
6,294.3
97 ,8%
Note: The Tier 1 approach for identifying key source categones does not directly include assessment of uncertainty in emissions estimates.
Table A- 2 provides a complete listing of source categories by IPCC sector, along with comments on the
criteria used in identifying key categories, without LULUCF sources and sinks. Similarly, Table A- 3 provides a
complete listing of source and sink categories by IPCC sector, along with comments on the criteria used in
identifying key categories, including LULUCF sources and sinks. The comments refer specifically to the year(s)
over the course of the entire inventory time series (i.e., 1990 to 2004) in which each source category reached the
threshold for being a key source based on a Tier 1 level assessment.
In addition to conducting Tier 1 level and trend assessments, a qualitative assessment of the source and sink
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.
Following the text of this Annex, Table A- 3 through Table A- 7 contain the 1990 and 2004 level
assessments for both with and withouth LULCF sources and sinks, and contain further detail on where each source
falls within the analysis. Table A- 8 and Table A- 9 detail the "with LULUCF" and "without LULUCF" trend
assessments for 1990 through 2004.
A-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table A- 2: U.S Greenhouse Gas inventory Source Categories wlttrom LULDCF
IPCC Source Categories
Energy
COz Emissions from Stationary Combustion— Coal
Mobile Combustion: Road & Other
COz Emissions from Stationary Combustion— Gas
COz Emissions from Stationary Combustion— Oil
Mobile Combustion: Aviation
COz Emissions from Non-Energy Use of Fuels
Mobile Combustion: Marine
COz Emissions from Natural Gas Flaring
COz Emissions from Stationary Combustion— Geothermal
Energy
Fugitive Emissions from Natural Gas Operations
Fugitive Emissions from Coal Mining and Handling
Fugitive Emissions from Oil Operations
Non-COz Emissions from Stationary Combustion
Fugitive Emissions from Abandoned Coal Mines
Mobile Combustion: Road & Other
Mobile Combustion: Aviation
Mobile Combustion: Marine
Mobile Combustion: Road & Other
Non-COz Emissions from Stationary Combustion
Mobile Combustion: Aviation
Mobile Combustion: Marine
International Bunker Fuels*
Industrial Processes
COz Emissions from Iron and Steel Production
COz Emissions from Cement Production
COz Emissions from Ammonia Production and Urea Application
CO: Emissions from Lime Production
COz Emissions from Limestone and Dolomite Use
COz Emissions from Aluminum Production
COz Emissions from Soda Ash Manufacture and Consumption
COz Emissions from Petrochemical Production
COz Emissions tram Titanium Dioxide Production
COz Emissions from Phosphoric Acid Production
COz Emissions from Ferroalloys
COz Emissions from COz Consumption
COz Emissions from Zinc Production
COz Emissions from Lead Production
COz Emissions from Silicon Carbide Consumption '
ChU Emissions from Petrochemical Production
CI-U Emissions from Iron and Steel Production
CH4 Emissions from Silicon Carbide Production
NzO Emissions from Nitric Add Production
NzO Emissions from Adipic Acid Production
NzO Emissions from NzO Product Usage
Emissions from Substitutes for Ozone Depleting Substances
HFC-23 Emissions from HCFC-22 Manufacture
SFe Emissions from Electrical Equipment
PFC, HFC, and SF« Emissions from Semiconductor
Manufacture
Direct 20M Key
GjTT Emissions Category ID
(Tg COz Eq.) Flag? Criteria
COz
COz
COz
COz
COz
COz
COz
COz
CO
• 2
ChU
CH4
CH«
ChU
ChU
ChU
'ChU
CH4
NiO
•NzO
NzO
NzO
Several
COz
COz
COz
COz
COz
COz
COz
COz
COz
COz
COz
COz
•COz
COj
COz
CH4
ChU
CH4 .
NzO
N20
NzO
HiGWP
HiGWP
HiGWP
LJiPlA/D
niuWr
2,027.0
1,621.5
1,153.8
619.9
179.6
153.4
54,4
6.0
0.4
118.8
56.3
25.7
6.4
5.6
2.7
0.1
0.1
40.6
13.7
1.8
0.4
95.5
51.3
45.6 '
16,9
13.7
6.7
4.3
4.2
2.9
2.3
1.4
1.3
1.2
0.5
0.3
0.1
1.6
1.0
-»-
16.6 .
5,7
4.8
103.3
15.6
13.8
'4.7
' LJ
•f LJ
•* L,T
•f LJ
/ • • L,T
' Lj'
/ L
' LJ
' LJ
•f UT
* LJ
/ Q
J LJ
' LJ
•/ T
'J T
-f LJ
' LJ
/ T
Comments
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 2004
Level in 1990
A-5
-------
PFC Emissions from Aluminum Production
SFo Emissions from Magnesium Production
Agriculture
CH< Emissions from Enteric Fermentation in Domestic Livestock
Cm Emissions from Manure Management
CH4 Emissions from Rice Production
CH« Emissions from Agricultural Residue Burning
Direct NzO Emissions from Agricultural Soils
Indirect NzO Emissions from Nitrogen Used in Agriculture
NzO Emissions from Manure Management
NzO Emissions from Agricultural Residue Burning
Waste
CO? Emissions from Waste Incineration
Cm Emissions from Solid Waste Disposal Sites
Cm Emissions from Wastewater Handling
toO Emissions from Wastewater Handling
NzO Emissions from Waste Incineration
1 Emissions from these sources not included in totals.
+ Does not exceed 0 05 Tg COz Eq.
Note- LULUCF sourcesand sinks are not included in this analysts.
HiGWP
HiGWP
CH4
CH4
CH4
CH4
NzO
NzO
toO
NzO
CO!
CH4
CH4
NzO
too
2.8 /
2.7
112.6 S
39.4
7.6
0.9
170.9, /
90.6 J
17.7
0.5
19.4 • •/
140.9 S
36.9 ^
16.0
0.5"
"
T
L,T
L
L,T
T
L,T
T
1
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Level in 1990 and 2004
Note: The Tier 1 approach for identifying key categories does not directly include assessment of uncertainty in emission estimates.
Table A- 3: 0.S Greenhouse Gas Inventoiy Source Categories with tOlOCF
C
IPCC Source Categories
Energy
COz Emissions from Stationary Combustion— Coal
Mobile Combustion: Road & Other
COz Emissions from Stationary Combustion— Gas
COz Emissions from Stationary Combustion— Oil
Mobile Combustion: Aviation
COz Emissions from Non-Energy Use of Fuels
Mobile Combustion: Marine
COz Emissions from Natural Gas Flaring
COz Emissions from Stationary Combustion— Geothermai
Energy
Fugitive Emissions from Natural Gas Operations
Fugitive Emissions from Coal Mining and Handling
Fugitive Emissions from Oil Operations
Non-COz Emissions from Stationary Combustion
Fugitive Emissions from Abandoned Coal Mines
Mobile Combustion: Road & Other
Mobile Combustion: Aviation
Mobile Combustion: Marine
Mobile Combustion: Road & Others
Non-COz Emissions from Stationary Combustion
Mobile Combustion: Aviation
Mobile Combustion: Marine
International Bunker Fuels*
Industrial Processes
COz Emissions from Iron and Steel Production
COz Emissions from Cement Production
Direct
GHG
COz
COz
COz
COz
COz
COz
COz
COz
CO?
owz
CH4
CH4
CH4
CH4
CH4
CH4
CH4
CH4
NzO
NzO
NzO
NzO
Several
C02
C02
2004 Key Source
Emissions Category
(Tg CO: Eq.) Flag?
2,027.0 /
1,621.5 /
1,153.8 , /
619.9
-------
COz Emissions from Ammonia Production and Urea Application
COz Emissions from Lime Production
COz Emissions from Limestone and Dolomite Use
COz Emissions from Aluminum Production
COz Emissions from Soda Ash Manufacture and Consumption
COz Emissions from Petrochemical Production .
COz Emissions from Titanium Dioxide Production
COz Emissions from Phosphoric Acid Product on
COz Emissions from Ferroalloys
COz Emissions from COz Consumption
COz Emissions from Zinc Production
COz Emissions from Lead Production
COz Emissions from Silicon Carbide Consumption
CH4 Emissions from Petrochemical Production
CH4 Emissions from Iron and Steel Production
CHU Emissions from Silicon Carbide Production
NzO Emissions from Nitric Add Production
NzO Emissions from Adipic Acid Production
N20 Emissions from NzO Product Usage
• Emissions from Substitutes for Ozone Depleting Substances
HFC-23 Emissions from HCFC-22 Manufacture
SFe Emissions from Electrical Equipment
PFC, HFC, and SF« Emissions from Semiconductor
Manufacture
PFC Emissions from Aluminum Production
SFe Emissions from Magnesium Production
Agriculture
CH4 Emissions from Enteric Fermentation in Domestic Livestock
Cm Emissions from Manure Management
CH< Emissions from Rice Production
CH4 Emissions from Agricultural Residue Burning
Direct NzO Emissions from Agricultural Soils ' '.
Indirect NzO Emissions from Nitrogen Used in Agriculture
NzO Emissions from Manure Management
NzO Emissions from Agricultural Residue Burning •
Waste
COz Emissions from Waste Incineration
ChU Emissions from Solid Waste Disposal Sites
CH» Emissions from Wastewater Handling
NzO Emissions from Wastewater Handling
NzO Emissions from Waste Incineration
Land Use, Land-Use Change, and Forestry
COz Emissions from Forest Land Remaining Forest Land
COz Emissions from Settlements Remaining Settlements
COz Emissions from Cropland Remaining Cropland
COz Emissions from Land Converted to Grassland
COz Emissions from Grassland Remaining Grassland
COz Emissions from Land Converted to Cropland
NzO Emissions from Settlements Remaining Settlements
NjO Emissions from Forest Land Remaining Forest Land
COz
COz
COz
COz
COz
COz
COz
COz
COz
COz
COz
COz
COz
CH4 '
CH4' •
CH4
NzO
• NzO
NzO
HiGWP
HiGWP
HiGWP
HiGWP
niv3¥f r
HiGWP
HiGWP
CH4
CH4
CH4
CH4
NsO
NzO
NzO
NzO
COz
CH4 "
CH4.
NzO
NzO
COz
COz
COz
COz '
COz
COz
NzO
NzO
15.9
13.7
6.7
4.3
4.2
2.9
2.3
1.4
1.3.
1.2
0.5
0.3
0.1
1.6
1.0
+
16.6 .
5.7
4.8
103.3
15.6
13.8
4.7
2.8
2.7
112.6
39.4
7.6
0.9
170.9
90.6
17.7
0.5
19.4
140.9
36.9
16.0
0.5
(637.2)
(97.3)
(28.9)
(21.1)
7.3
(2.8)
6.4
0.4
-
'
.
•f T
•
•f L,T Level in 2004
-------
Evaluation of Tier 1 Key Categories
Level Assessment
When using a Tier 1 approach for the level assessment, a predetermined cumulative emissions threshold is
used to identify key categories. When source and sink categories are sorted in order of decreasing absolute
emissions, those that fall at the top of the list and cumulatively account for 95 percent of emissions are considered
key categories. The 95 percent threshold in the IPCC Good Practice Guidance (IPCC 2000) was designed to
establish a general level where the key category analysis covers approximately 75 to 92 percent of inventory
uncertainty.
It is important to note that a key category analysis can be sensitive to the definitions of the source and sink
categories. If a large source category is split into many subcategories, then the subcategories may have
contributions to the total inventory that are too small for those source categories to be considered key. Similarly, a
collection of small, non-key source categories adding up to less than 5 percent of total emissions could become key
source categories if those source categories were aggregated into a single source category. The United States has
attempted to define source and sink categories by the conventions which would allow comparison with other
international key categories, while still maintaining the category definitions that constitute how the emissions
estimates were calculated for this report. As such, some of the category names used in the key category analysis
may differ from the names used in the main body of the report. Additionally, the United States accounts for some
source categories, including fossil fuel feedstocks, international bunkers, and emissions from U.S. territories, that
are derived from unique data sources using country-specific methodologies.
Trend Assessment
The United States is currently taking a Tier 1 approach to identify trend assessment key categories until a
full and consistent inventory-wide uncertainty analysis is completed. The Tier 1 approach for trend assessment is
defined as the product of the source or sink category level assessment and the absolute difference between the
source or sink category trend and the total trend. In turn, the source or sink category trend is defined as the change
in emissions from the base year to the current year, as a percentage of current year emissions from that source or
sink category. The total trend is the percentage change in total inventory emissions from the base year to the current
year.
Thus, the source or sink category trend assessment will be large if the source or sink category represents a
large percentage of emissions and/or has a trend that is quite different from the overall inventory trend. To
determine key categories, the trend assessments are sorted in decreasing order, so that the source or sink categories
with the highest trend assessments appear first. The trend assessments are summed until the threshold of 95 percent
is reached; all categories that fall within that cumulative 95 percent are considered key categories.
Tier 2 Key Category Assessment
IPCC Good Practice Outdance (IPCC 2000) recommends using a Tier 2 method for identifying key source
categories if nationally derived source-level uncertainties are measured. The Tier 2 approach is a more detailed
analysis that builds on the Tier 1 approach by multiplying the results of the Tier 1 analysis by the relative
uncertainty of each source category. This method is likely to reducevthe number of key source categories under
consideration. As part of its multi-year uncertainty assessment effort, the United States has already developed
quantitative uncertainty estimates for most source and sink categories. When quantitative estimates of uncertainty
become available for all source categories, future inventories can incorporate this Tier 2 approach.
Table ft- 4:1990 Key source Category Her 1 Analysis—Uwel Assessment, wlthoinLOLOCF
Cumulative
1990 Estimate 1990 Estimate Level Total of Level
A-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
CM* Cmsttvn tarn, UBUB M
SFu Emissions from Electrical Equipment SFa
CH4 Emissions from Wastewater Handling CH4
COz Emissions from Ammonia Production and Urea Application COz
RFC Emissions from Aluminum Production PFCs
NzO Emissions from Nitric Acid Production NzO
NzO Emissions from Manure Management NzO
NzO Emissions from Adipic Acid Production NzO
NzO Emissions from Wastewater Handling NzO
Non-COz Emissions from Stationary Combustion NzO
CO; Emissions from Lime Production C02
COz Emissions from Waste Incineration C02
Non-COz Emissions from Stationary Combustion OU
CH« Emissions from Rice Production CH4
COz Emissions from Aluminum Production COz
Fugitive Emissions from Abandoned Coal Mines Chk
COj Emissions from Natural Gas Flaring COz
COz Emissions from Limestone and Dolomite Use C02
SF« Emissions from Magnesium Production SFe
Mobile Combustion: Road & Other CH4
NzO Emissions from NzO Product Usage NzO
COz Emissions from Soda Ash Manufacture and Consumption CO?
PFC, HFC, and SFa Emissions from Semiconductor Manufacture SFa
COz Emissions from Petrochemical Production CO:
COz Emissions from Ferroalloys CO?
Mobile Combustion: Aviation NzO
COz Emissions from Phosphoric Acid Production COz
ChU Emissions from Iron and Steel Production CH»
C02 Emissions from Titanium Dioxide Production COz
Cm Emissions from Petrochemical Production Cm
CO: Emissions from Zinc Production COz
COz Emissions from CO: Consumption COz
Cm Emissions from Ag ricultural Residue Burning CH4
NjO Emissions from Waste Incineration NzO
Emissions from Substitutes for Ozone Depleting Substances Several -
CO: Emissions from Stationary Combustion—Geothermal Energy COz
NzO Emissions from Agricultural Residue Burning NzO
Mobile Combustion. Marine NzO
COj Emissions from Lead Production COz
Mobile Combustion: Aviation Cm
COz Emissions from Silicon Carbide Consumption COz
Mobile Combustion: Marine Cm
Cm Emissions from Silicon Carbide Production CH4
28.6
24.8
19.3
18.4
17.8
16.3
15.2
12.9
12.3
11.2
10.9
7.9
7.1'
7.0
6.0
5.8
5.5
5.4
4.5
4.3
4,1
2.9
2.2
2.0'
1.7
1.5
1.3
1.3
1.2
0.9
0.9
0.7
0.5
0.4
0.4
0.4
0.4
0.3
0.2
0.1
0.1
• 0.0
312
28.6
24.8
19.3
18.4
17.8
16.3
15.2
12.9
12.3
11.2
10.9
7.9
7.1-
7.0
6.0
5.8
• 5.5
5.4
4.5
4.3
4.1
2.9
2.2
2.0
1.7
1.5
1.3
1.3
1.2
0.9
0.9
0.7
0.5
0.4
0.4.
0.4
0.4
0.3
0.2
0.1
0.1
0.0
Ct:
<0.01
<0.01
O.01 '
O.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0,01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01 .
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
335
0.96
097
0.97
0.97
0.97
0.98
0.98
0.98
0.98
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1,00
1.00
1.00
TOTAL
6,103.3
6,103.3
1.00
Note' LULUCF sources and sinks are not included in this analysis.
Table A- S: 1990 Key Source Category Her 1 Analysis—level Assessment with IOIUCF
_ _ _ . . _ Cumulative
1990 Estimate 1990 Estimate Level Total of Level
IPCC Source Categories Direct GHG (TgCOzEq.) (TgCOiEq.) Assessment Assessment
A-9
-------
J=U oMsifcru IKH Ihnagetfer11
SF« Emissions from Electrical Equipment SF«
CH< Emissions from Wastewater Handling CH<
C02 Emissions from Ammonia Production and Urea Application COj
PFC Emissions from Aluminum Production PFCs
N20 Emissions from Nitric Acid Production toO
C02 Emissions from Land Converted to Grassland CO?
toO Emissions from Manure Management toO
NzO Emissions from Adipic Add Production toO
N20 Emissions from Wastewater Handling N20
Non- C02 Emissions from Stationary Combustion NzO
C02 Emissions from Lime Production C02
C02 Emissions from Waste Incineration COj
Non- C02 Emissions from Stationary Combustion , CH<
CH* Emissions from Rice Production CH<
C02 Emissions from Aluminum Production COj
Fugitive Emissions from Abandoned Coat Mines - CH<
COj Emissions from Natural Gas Flaring CO?
toO Emissions from Settlements Remaining Settlements . toO
C02 Emissions from Limestone and Dolomite Use C02
SFo Emissions from Magnesium Production SF«
CQj Emissions from Grassland Remaining Grassland COj
Mobile Combustion: Road & Other CH<
N20 Emissions from N2O Product Usage toO
C02 Emissions from Soda Ash Manufacture and Consumption C02
PFC, HFC, and SFe Emissions from Semiconductor Manufacture SFe
C02 Emissions from Petrochemical Production CO}
COi Emissions from Ferroalloys CO:
Mobile Combustion: Aviation N20
CQj Emissions from Phosphoric Acid Production COi
CO} Emissions from Land Converted to Cropland CCk
CH4 Emissions from Iron and Steel Production ChU
C02 Emissions from Titanium Dioxide Production C02
CH4 Emissions from Petrochemical Production ChU
C02 Emisstons from Zinc Production C02
COj Emissions from CCh Consumption C02
CM4 Emissions from Agricultural Residue Burning CH4
N20 Emissions from Waste Incineration • NjO
Emissions from Substitutes for Ozone Depleting Substances Several
C02 Emissions from Stationary Combustion—Geothermal Energy C02
N20 Emissions from Agricultural Residue Burning N20
Mobile Combustion: Marine - toO
r
28.6
24.8
19.3
18.4
17.8
17.6
16.3
15.2
12.9
12.3
11.2
10.9
7.9
7.1
7.0
6.0
5.8
5.6
5.5
5.4
4.5
4.5
4.3
4.1
2.9
2.2
2.0
1.7
1.5
1.5
1.3
1.3
1.2
0.9
0.9
0.7
0.5
0.4
0.4
0.4
0.4
28.6
24.8
19.3
18.4
17.8
17.6
16.3
15.2
12.9
12.3
11.2
10.9
7.9
7.1
7.0
6.0
5.8
5.6
5.5
5.4
4.5
4.5
4.3
4.1
2.9
2.2
2.0
1.7
1.5
1.5
1.3
1.3
1.2
0.9
0.9
0.7
0.5
0.4
0.4
0.4
0.4
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<001
0.96
0.97
0.97
0.97
0.97
0.98
0.98
0.98
0.98
0.98
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00'
1.00
1.00
1.00
1.00
1.00
100
1.00
1.00
A-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
COz Emissions from Lead Production
Mobile Combustion: Aviation
C02 Emissions from Silicon Carbide Consumption
Mobile Combustion: Marine
NzO Emissions from Forest Land Remaining Forest Land
ChU Emissions from Silicon Carbide Production
TOTAL
COz
CH<
C02
ChU
N20
CH4
.0.3
0.2
0.1
0.1
0,1
0.0
7,022.3
0.3 •
0.2
0.1
' 0.1
0.1
0.0
7,022.3
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
1.00
1.00
t.oo
1.00
1.00
1.00
1.00
Table A- 6:2004 Key Seine Category Her 1 Analysis-level Assessment wlthont UIDCF
. Cumulative
1990 Estimate 2004 Estimate Level Total of Level
£4* t^ESMwis, ram tartA
ChU Emissions from Wastewater Handling CH4
Fugitive Emissions from Oil Operations CH*
COz Emissions from Waste Incineration COz
NzO Emissions from Manure Management NzO
COz Emissions from Ammonia Production and U rea Application COz
NzO Emissions from Nitric Acid Production NzO
NzO Emissions from Wastewater Handling NzO
HFC-23 Emissions from HCFC-22 Manufacture MFCs
SF« Emissions from Electrical Equipment SFe
COi Emissions from Lime Production " COz
Non-CO: Emissions from Stationary Combustion NzO
ChU Emissions from Rice Production ChU
COz Emissions from Limestone and Dolomite Use ' COz
Non-COz Emissions from Stationary Combustion CH4
COz Emissions from Natural Gas Flaring COz
NzO Emissions from Adipic Add Production NzO
Fugitive Emissions from Abandoned Coal Mines ChU
NzO Emissions from NzO Product Usage NzO
PFC, HFC, and SF« Emissions from Semiconductor Manufacture SF«
COz Emissions from Aluminum Production COz
COz Emissions from Soda Ash Manufacture and Consumption COz
COz Emissions from Petrochemical Production COa
PFC Emissions from Aluminum Production PFCs
Mobile Combustion: Road & Other CH4
SFe Emissions from Magnesium Production SFe
COz Emissions from Titanium Dioxide Production . COz
Mobile Combustion: Aviation NzO
CH4 Emissions from Petrochemical Production - ChU
COz Emissions from Phosphoric Acid Production COz
COz Emissions from Ferroalloys COi
COz Emissions from CO; Consumption CO?
24.8
34.4
10.9
16.3
19.3
17.8
12.9
35.0
28.6
11.2
12.3
7.1
5.5
7,9
5.8
15.2
6.0
4.3
2.9
7.0
4.1
•2.2
18.4
4.5
5.4
1.3
1.7
1.2
1.5
2.0
0.9
#1
36.9
25,7-
19.4
17.7
16.9
16.6
16.0
15.6
13.8
13.7
13.7
7,6
6.7
6.4
6.0
5.7
5.6
4.8
4.7
4.3
4.2
2.9
2.8
2.7
2.7
2.3
1.8'
1.6
1.4
1.3
1.2
Ct'
0.01
<0.01
<0.01
<0.01
<0.01
<0.01
0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0,01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
O.01
<0.01
<0.01
<0.01
<0.01
;»
0.96'
0.97
0.97
0.97
0.98
0.98
0.98
0.99
0.99
0-99
0.99
0.99
0.99
0.99
0.99
0.99
1.00
1,00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
A-11
-------
CH« Emissions from Iron and Steel Production
CHU Emissions from Agricultural Residue Burning
NjO Emissions from Waste Incineration
N20 Emissions from Agricultural Residue Burning
COz Emissions from 3nc Production
Mobile Combustion: Marine
COz Emissions from Stationary Combustion— Geothennal Energy
COz Emissions from Lead Production
Mobile Combustion: Aviation
COj Emissions from Silicon Carbide Consumption
Mobile Combustion: Marine
CH4 Emissions from Silicon Carbide Production
TOTAL
CH4
CH4
N20
N20
C02
N20
C02
COj
CH4
COj
CH4
CH4
1.3
0.7
. 0.5
0.4
0.9
0.4
0.4
0.3
0.2
0.1
0.1
0.0
6,103.3
1.0
0.9
0.5
0.5
0.5
0.4
0.4
0.3
0.1
0.1
0.1
0.0
7,067.6
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Note: LULUCF sources and sinks are not included in this analysis.
TBDle ft-7:2004 Key Source Category Tier 1 Anatals-lBvel ftssessmemwltti IUIDCF
Cumulative
Level Total of Level
1990 Estimate
Di-Ki a-C (TaCChEqj
2004 Estimate
=s=!S™!-ft«-?e5c-'g-= mv_jr., -| ----iiHi, £,~r"EJSEa~ ~
- and n-
CO; Emissions from Cropland Remaining Cropland COz
Fugitive Emissions from Oil Operations CH4
COz Emissions from Land Converted to Grassland C02
CO? Emissions from Waste Incineration C02
NjO Emissions from Manure Management NzO
COj Emissions from Ammonia Production and Urea Application CO:
NzO Emissions from Nitric Acid Production N?0
NzO Emissions from Wastewater Handling NjO
HFC-23 Emissions from HCFC-22 Manufacture MFCs
SFt Emissions from Electrical Equipment SFg
CO: Emissions from Lime Production CO:
Non-CO: Emissions from Stationary Combustion N20
CM4 Emissions from Rice Production CH«
C02 Emissions from Grassland Remaining Grassland CO?
C02 Emissions from Limestone and Dolomite Use COj
N20 Emissions from Settlements Remaining Settlements NzO
Non-COz Emissions from Stationary Combustion CH4
CChr Emissions from Natural Gas Flaring CO:
N20 Emissions from Adipic Ackf Production NzO
Fugitive Emissions from Abandoned Coal Mines ChU
N20 Emissions from N20 Product Usage NaO
33.1
344
17.6
10.9
16.3
19.3
17.8
12.9
35.0
28.6
11.2
123
7.1
4.5
5.5
5.6
7.9
5.8
15.2
6.0
4.3
36 £
28.9
25.7
21.1
19.4
17,7
16.9
16.6
16.0
15.6
13.8
13.7
13.7
7.6
7.3
6.7
6.4
6.4
6.0
5.7
5.6
4.8
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<001
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
59S
0.96
0.97
0.97
0,97
0.97
0.98
0.98
0.98
0.98
0.98
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
A-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
PFC, HFC, and SF» Emissions from Semiconductor Manufacture
C02 Emissions from Aluminum Production
C02 Emissions from Soda Ash Manufacture and Consumption
C02 Emissions from Petrochemical Production
PFC Emissions from Aluminum Production
COi Emissions from Land Converted to Cropland
Mobile Combustion: Road & Other
SF» Emissions from Magnesium Production
COz Emissions from Titanium Dioxide Production
Mobile Combustion: Aviation
CH* Emissions from Petrochemical Production
C02 Emissions from Phosphoric Acid Production
COz Emissions from Ferroalloys
COz Emissions from C02 Consumption
CH* Emissions from Iron and Steel Production
CH* Emissions from Agricultural Residue Burning
NjO Emissions from Waste incineration
NjO Emissions from Agricultural Residue Burning
CO: Emissions from Zinc Production
Mobile Combustion: Marine
NzO Emissions from Forest Land Remaining Forest Land
CO? Emissions from Stationary Combustion— Geothermal Energy
COz Emissions from Lead Production
Mobile Combustion: Aviation
CO? Emissions from Silicon Carbide Consumption
Mobile Combustion: Marine
CH* Emissions from Silicon Carbide Production
TOTAL
SFe
C02
C02
COz
PFCs
C02
CH*
SFe
C02
NzO
CH*
C02
C02
C02
CH4
CH*
N20
NzO
C02
NzO
N20
C02
COz
CH*
COz
CH*
CH*
2.9
7.0
4,1
2.2
18.4
1.5
4.5
5.4
1.3
1.7
1.2
1.5
2.0
0.9
1.3
0,7
0,5
0,4
0.9'
0.4
0.1
0.4
0,3
0,2
0.1
0.1 •
0.0
7,022.3
4.7
' 4.3
4.2
2.9
2.8
2.8
2.7
2.7
2.3
1.8
1.6
1.4
1.3
1.2
1.0
• 0.9"
0.5
0.5
0.5
0.4
0.4
. 0.4
0.3
0.1
0.1
0.1
0.0
7,869.0
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0,01 '
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01 '
<0.01
<0.01
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
. 1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
Table ft- 8:1990-2004 Key Source Cute gory Tie M Analysis-Trend
ml without LOLDGF
Direct 1990 Estimate 2004 Estimate
Percent Cumulative
Trend Contribution to Contribution
lpTiMta>]
A-13
-------
Mobile Combustion: Marine.
COz Emissions from Aluminum Production
SF» Emissions from Magnesium Production
CH4 Emissions from Manure Management
. Direct NzO Emissions from Agricultural Soils
Non-COz Emissions from Stationary Combustion
Mobile Combustion: Road & Other
RFC, HFC, and SF» Emissions from Semiconductor
Manufacture
Fugitive Emissions from Abandoned Coal Mines
NzO Emissions from Manure Management
NzO Emissions from Wastewater Handling
COz Emissions from Ferroalloys
COz Emissions from Titanium Dioxide Production
COz Emissions from Natural Gas Flaring
CH4 Emissions from Rice Production
COz Emissions from Lime Production
COz Emissions from Soda Ash Manufacture and
Consumption
C02 Emissions from Zinc Production
Non-COz Emissions from Stationary Combustion
CH4 Emissions from Iron and Steel Production
CCb Emissions from Phosphoric Acid Production
CCb Emissions from Petrochemical Production
COz Emissions from Limestone and Dolomite Use
CH4 Emissions from Petrochemical Production
Mobile Combustion: Aviation
NzO Emissions from NzO Product Usage
COz Emissions from COz Consumption
COz Emissions from Stationary Combustion—
Geothermal Energy
NzO Emissions from Agricultural Residue Burning
CH4 Emissions from Agricultural Residue Burning
CO? Emissions from Lead Production
Mobile Combustion: Aviation
Mobile Combustion: Marine
NzO Emissions from Waste Incineration
CH4 Emissions from Silicon Carbide Production
COz Emissions from Silicon Carbide Consumption
Mobile Combustion: Marine
COz
C02
SF«
CH4
N20
CH4
CH4
SF9
CH4
NzO
NzO
COz
COz
COz
CH4
COz
COj
COz
NzO
CH4
COz
COi
COz
CH4
NzO
NzO
COz
COz
NzO
CH4
COz
CH4
NzO
NzO
CH4
COz
CH4
43.6
7.0
5.4
31.2
150.4
7.9
4.5
2.9
6.0
16.3
12.9
2.0
1.3
5.8
7.1
11.2
4.1
0.9
12.3
1.3
1.5
2.2
5.5
1.2
1.7
4.3
0.9
0.4
0.4
0.7
0.3
0.2
0.4
0.5
0.0
0,1
0.1
6,103.3
54.4
4.3
2.7
39.4
170.9
6.4
2.7
4.7
5.6
17.7
16.0
1.3
2.3
60
7.6
13.7
4.2
0.5
13.7
1.0
1.4
2.9
6.7
1.6
1.8
4.8
1.2
0.4
0.5
0.9
0.3-
0.1
0.4
0.5
0.0 '
0.1
0.1
7.067.6
O.01
<0.01
<0.01
<0.01
<0.01
O.01
O.01
<0.01
<0.01
<0.01
<0.01
O.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<001
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
• <0.01
-20^
0.4
0.4
0.4
0.4
0.4
0.3
0.3
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
•=0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
96.4
96.8
97.2
97.6
97.9
98.2
98.5
98.7
99.1
99.2
99.3
99.3
99.4
99.5
99.6
99.6
99.7
99.7
99.8
99.8
99.8
99.9
99.9
99.9
99.9
100.0
100.0
100.0
100.0
100.0
1000
100.0
100.0
100.0
100.0
A-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
-Sft'TSuiSar-: i.
Mobile Combustion: Marine
COz Emissions from Ammonia Production and Urea
Application
OU Emissions from Manure Management
COz Emissions from Settlements Remaining
Settlements
CO? Emissions from Aluminum Production •
N20 Emissions from Nitric Acid Production
SF« Emissions from Magnesium Production
Direct NiO Emissions from Agricultural Soils
Non-era Emissions from Stationary Combustion
Mobile Combustion: Road & Other
C02 Emissions from Grassland Remaining
Grassland
NzO Emissions from Wastewater Handling
PFC, HFC, and SFe Emissions from Semiconductor
Manufacture
COz Emissions from Land Converted to Grassland
COz Emissions from Land Converted to Cropland
COz Emissions from Lime Production
Fugitive Emissions from Abandoned Coal Mines
COz Emissions from Ferroalloys
COz Emissions from Titanium Dioxide Production
COz Emissions from Zinc Production
NzO Emissions from Manure Management
COz Emissions from Limestone and Dolomite Use
COz Emissions from Natural Gas Flaring
COz Emissions from Soda Ash Manufacture and
Consumption
CH4 Emissions from Iron and Steel Production
CH« Emissions from Rice Production .
COz Emissions from Petrochemical Production
NzO Emissions from Forest Land Remaining Forest
Land
COz Emissions from Phosphoric Acid Production
CH« Emissions from Petrochemical Production
COz Emissions from COz Consumption
Mobile Combustion: Aviation
NzO Emissions from Settlements Remaining
Settlements
CH< Emissions from Agricultural Residue Burning
NzO Emissions from Agricultural Residue Burning
COz Emissions from Stationary Combustion—
Geothermal Energy
Non-COz Emissions from Stationary Combustion
COz Emissions from Lead Production
NzO Emissions from NzO Product Usage
Mobile Combustion: Marine '
Mobile Combustion: Aviation '
NtC
COz
COz
CH4
COz
COz
NzO
SFe
NzO
CH*
CH*
COz
NzO
SFe
COz
CO*
COz
CH*
COz
COz
COz
NzO
COz
COz
COz
CH*
CH*
COz
NzO
COz
CH*
COz
NzO
NzO
CH*
NzO
COz
NzO
COz
NzO
NzO
CH*
f..4
43.6
19.3
31.2
83.2
7,0
17,8
5.4
150.4
7.9
4.5
4.5
12.9
2.9
17.6
1.5
11.2
6.0
2.0
1.3
0.9
16.3
5.5
5.8
4.1
1.3
7.1
2,2
0.1
1.5
1.2
0.9
1.7
5.6
0.7
0.4
0.4
12.3
0.3
4.3
0.4
0.2
40i
54.4
16.9
39.4
97.3
4.3
16.6
2.7
170.9
6.4
2.7
7.3
16.0
4.7
21.1
2.8
13.7
5.6
1,3
2,3
0,5
17.7
6.7
6.0
4.2
1.0
7.6
2.9
0.4
1.4
1,6
1,2
1,8
6.4
0.9
0.5'
0,4
13.7
0.3
4.8
0.4
0.1
cfcfcr
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
es
0.5
0.4
0.4
0.3
0.3
0.3
0.3
0.2
02
0.2
0.2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
96.1
96.5
96.8
97.2
97.5
97.7
98.0
98.2
98.4
98.6
98.8
99.0
99.1
99.2
99.3
99.4
99.5
99.5
99.6
99.6
99.7
99.7
99.7
99.8
99.8
99.8
99.9
99.9
99.9
99.9
99.9
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
A-15
-------
CO: Emissions from Silicon Carbide Consumption
CH4 Emissions from Silicon Carbide Production
NzO Emissions from Waste Incineration
Mobile Combustion: Marine
Total
C02
CH4
N20
CH4
0.1
0.0
0.5
0.1
7,022.3
0.1
0.0
0.5
0.1
7,869.0
<0.01
<0,01
<0.01
<0.01
0.14
<0.01
<0.01
<0.01
<0.01
100.0
100.0
100.0
100.0
References
Flugsrud, K., W. Irving, and K. Rypdal (1999) Methodological Choice in Inventory Preparation.
Suggestions for Good Practice Guidance. Statistics Norway Department of Economic Statistics. 1999/19.
IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas
Inventories, Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme.
A-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
ANNEX 2 Methodology and Dat for
Estimating CO2 Emissions from Fo il
Fuel Combustion
2.1. Methodology for Estimating Emissions of C02 from Fossil Fuel Combustion
Carbon dioxide (CO2) emissions from fossil fuel combustion were estimated using a "bottom-up"
methodology characterized by nine steps. These steps are described below.
Stepl: Determine Total Fuel Consumption by Fuel Type and Sector
i • r ,
The bottom-up methodology used by the United States for estimating CO2 emissions from fossil fuel
combustion is conceptually similar to the approach recommended by the Intergovernmental Panel on Climate
Change (1PCC) for countries that intend to develop detailed, sectoral-based emission estimates
(IPCC/UNEP/OECD/IEA 1997). Adjusted consumption data are presented in Columns 2 through 8 of Table A-10
through Table A-24, with totals by fuel type in Column 8 and totals by end-use sector in the last rows. Fuel'
consumption data for the bottom-up approach were obtained directly from the Energy Information Administration
(EIA) of the U.S. Department of Energy. These data were first gathered in physical units, and then converted to
their energy equivalents (see "Energy Conversions" in Annex 6.5). The EIA data were collected through a variety
of consumption surveys at the point of delivery or use and qualified with survey data on fuel production, imports,
exports, and stock changes. Individual data elements were supplied by a variety of sources within EIA. Most
information was taken from published reports, although some data were drawn from unpublished energy studies and
databases maintained by EIA.
Energy consumption data were aggregated by sector (i.e.; residential, commercial, industrial,
transportation, electricity generation, and U.S. territories), primary fuel type (e.g., coal, natural gas, and petroleum),
and secondary fuel type (e.g., motor gasoline, distillate fuel, etc.). • The 2004 total adjusted energy consumption
across all sectors, including territories, and energy types was 77,845.5 trillion British thermal units (TBtu), as
indicated in the last entry of Column 8 in Table A-10. This total excludes fuel used for non-energy purposes and
fuel consumed as international bunkers, both of which were deducted in earlier steps.
Electricity consumption information was allocated to each sector based on El A's distribution of electricity
retail sales to ultimate customers (i.e., residential, commercial, industrial, and other). Because the "other" fuel use
includes sales to both the commercial and transportation sectors, EIA's limited transportation electricity use data
were subtracted from "other" electricity use and also reported separately. This total was consequently combined
with the commercial electricity data. Further information on these electricity end uses is described in EIA's Annual
Energy Review (2005a).
There are also three basic differences between the consumption data presented in Table A-10 through Table
A-24 and those recommended in the IPCC emission inventory methodology.
First, consumption data in the U.S. inventory are presented using higher heating values (HHV)1 rather than
the lower heating values (LHV)2 reflected in the IPCC emission inventory methodology. This convention is
followed because data obtained from EIA are based on HHV. Of note, however, is that EIA renewable energy
statistics are often published using LHV. The difference between the two conventions relates to the treatment of the
heat energy that is consumed in the process of evaporating the water contained in the fuel. The simplified
convention used by the International Energy Agency for converting from HHV to LHV is to multiply the energy
content by 0.95 for petroleum and coal and by 0.9 for natural gas.
1 Also referred to as Gross Calorific Values (GCV).
2 Also referred to as Net Calorific Values (NCV). ,
A-17
-------
Second, while EIA's energy use data for the United States includes only the 50 U.S. states and the District
of Columbia, the data reported to the Framework Convention on Climate Change are to include energy consumption
within territories. Therefore, consumption estimates for U.S. territories were added to domestic consumption of
fossil fuels. Energy consumption data from U.S. territories are presented in Column 7 of Table A-10 through Table
A-24. It is reported separately from domestic sectoral consumption, because it is collected separately by EIA with
no sectoral disaggregation.
Third, there were a number of modifications made in this report that may cause consumption information
herein to differ from figures given in the cited literature. These are 1) the reallocation of select amounts of coking
coal, petroleum coke, natural gas, residual fuel oil, and other oil (>401 F) for processes accounted for in the
Industrial Processes chapter, 2) corrections for synthetic natural gas production, 3) corrections for ethanol added to
motor gasoline, and 4) corrections for faiogas in natural gas, 5) subtraction of other fuels used for non-energy
purposes, and 6) subtraction of international bunker fuels. These adjustments are described in the following steps.
Step 2: Subtract uses accounted for in the Industrial Processes chapter.
Portions of the fuel consumption data for six fuel categories—coking coal, industrial other coal, petroleum
coke, natural gas, residual fuel oil, and other oil (>401 F)—were reallocated to the Industrial Processes chapter, as
these portions were consumed as raw materials during non-energy related industrial processes. Emissions from
these fuels used as raw materials are presented in the Industrial Processes chapter, and is removed from the energy
and non-energy consumption estimates within the Energy chapter.
• Coking coal, also called "coal coke," is used as a raw material (specifically as a reducing agent) in the
blast furnace process to produce iron and steel, lead, and zinc and therefore is not used as a fuel for this
process.
• Similarly, petroleum coke is used in multiple processes as a raw material, and is thus not used as a fuel
in those applications. The processes in which petroleum coke is used include 1) ferroalloy production,
2) aluminum production (for the production of carbon anodes and cathodes), 3) titanium dioxide
production (in the chloride process), and 4) ammonia production. <
• Natural gas consumption is used for the production of ammonia, and blast furnace and coke oven gas
used in iron and steel production.
• Residual fuel oil and other oil (>401 F) are both used in the production of carbon black.
Step 3: Adjust for Biofuels and Conversion of Fossil Fuels
First, a portion of industrial "other" coal that is accounted for in EIA coal combustion statistics is actually
used to make "synthetic natural gas" via coal gasification at the Dakota Gasification Plant, a synthetic natural gas '
plant. The plant produces synthetic natural gas and byproduct carbon dioxide. The synthetic natural gas enters the
natural gas distribution system. Since October 2000 a portion of the carbon dioxide produced by the coal
gasification plant has been exported to Canada by pipeline. The remainder of the carbon dioxide byproduct from the
plant is released to the atmosphere. The energy in this synthetic natural gas enters the natural gas distribution
stream, and is accounted for in EIA natural gas combustion statistics. Because this energy of the synthetic natural
gas is already, accounted for as natural gas combustion, this amount of energy is deducted from the industrial coal
consumption statistics to avoid double counting. The exported CO2 is not emitted to the atmosphere in the United
States, and therefore the energy used to produce this amount of CO2 is subtracted from industrial other coal.
Second, ethanol has been added to the motor gasoline stream for several years, .but prior to 1993 this
addition was not captured in EIA motor gasoline statistics. Starting in 1993, ethanol was included in gasoline
statistics. However, because ethanol is a biofuel, which is assumed to result in no net CO2 emissions, the amount of
ethanol added is subtracted from total gasoline consumption. Thus, motor gasoline consumption statistics given in
this report may be slightly lower than in EIA sources.
Third, EIA natural gas consumption statistics include "biomass gas," which is upgraded landfill methane
that is sold to pipelines. However, because this gas is biogenic, the biomass gas total is deducted from natural gas
consumption. The subtraction is done only from natural gas in the industrial sector, as opposed to all end-sectors,
A-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
because the biogas amount is small. Due to this adjustment-and the ammonia adjustment mentioned previously-
industrial natural gas consumption in this report is slightly lower than in El A sources.
Step 4: Subtract Consumption for Non-Energy Use
U.S. aggregate energy statistics include consumption of fossil fuels for non-energy purposes. Depending on
the end-use, non-energy uses of fossil fuels can result in long term storage of some or all of the carbon contained in
the fuel. For example, asphalt made from petroleum can sequester up to 100 percent of the carbon contained in the
petroleum feedstock for extended periods of time. Other non-energy fossil fuel products, such as lubricants or
plastics also store carbon, but can lose or emit some of this carbon when they are used and/or burned as waste.3 As
the emission pathways of carbon used for non-energy purposes are vastly different than fuel combustion, these
emissions are estimated separately in the Carbon Emitted in Products from Non-Energy Uses of Fossil Fuels section
in this chapter. Therefore, the amount of fuels used for non-energy purposes, shown in Table A-25, was subtracted
from total fuel consumption.
Step 5: Subtract Consumption of International Bunker Fuels
Emissions from international transport activities, or international bunker fuel consumption, are not included
in national totals, as required by the IPCC (IPCC/UNEP/OECD/IEA 1997). There is currently disagreement
internationally as to how these emissions should be allocated, and until this issue is resolved, countries are asked to
report them separately. EIA energy statistics, however, include these bunker fuels—jet fuel for aircraft, and
distillate fuel oil and residual fuel oil for marine shipping—as part of fuel consumption by the transportation end-use
sector. Therefore, the amount of consumption for international bunker fuels was estimated and subtracted from total
fuel consumption (see Table A-26). Emissions from international bunker fuels have been estimated separately and
not included in national totals.4
Step 6: Determine the Carbon Content of All Fuels
The carbon content of combusted fossil fuels was estimated by multiplying adjusted energy consumption
(Columns 2 through 8 of Table A-10 through Table A-24) by fuel-specific carbon content coefficients (see Table A-
27 and Table A-28) that reflect the amount of carbon per unit of energy in each fuel. The resulting carbon contents
are sometimes referred to as potential emissions, or the maximum amount of carbon that could potentially be
released to the atmosphere if all carbon in the fuels were oxidized. The carbon content coefficients used in the U.S.
inventory were derived by EIA from detailed fuel information and are similar to the carbon content coefficients
contained in the IPCC's default methodology (IPCC/UNEP/OECD/IEA 1997), with modifications reflecting fuel
qualities specific to the United States.
Step 7: Account for Carbon that Does Not Oxidize During Combustion
Because combustion processes are not 100 percent efficient, some of the carbon contained in fuels is not
emitted in a gaseous form to the atmosphere. Rather, it remains behind as soot, particulate matter and ash. The
estimated fraction of carbon not oxidized in U.S. energy conversion processes due to inefficiencies during
combustion ranges from 0.5 percent for natural gas to 1 percent for petroleum and coal. Except for coal these
assumptions are consistent with the default values recommended by the IPCC (IPCC/UNEP/OECD/IEA 1997). In
the United States, unoxidized carbon from coal combustion was estimated to be no more than one percent (Bechtel
1993). Table A-27 presents fractions oxidized by fuel type, which are multiplied by the net carbon content of the
combusted energy to give final emissions estimates.
Of the fraction of carbon that is oxidized (e.g., 99 to 99.5 percent), the vast majority is emitted in its fully
oxidized form as carbon dioxide (COi). A much smaller portion of this "oxidized" carbon is also emitted as carbon
^ See Waste Combustion section of the Energy chapter and Annex 3.6 for a discussion of emissions from the
combustion of plastics in the municipal solid waste stream.
4 Refer to the International Bunker Fuels section of the Energy chapter for a description of the methodology for
distinguishing between bunker and non-bunker fuel consumption.
...:__
-------
monoxide (CO), methane (CH4), and non-methane volatile organic compounds (NMVOCs). When in the
atmosphere, though, these partially oxidized or unoxidized carbon compounds are generally oxidized to CO2
through atmospheric processes (e.g., reaction with hydroxyl (OH)).5
Step 8: Summarize Emission Estimates
Actual CO2 emissions in the United States were summarized by major fuel (i.e., coal, petroleum, natural
gas, geothermal) and consuming sector (i.e., residential, commercial, industrial, transportation, electricity
generation, and U.S. territories). Emission estimates are expressed in teragrams of carbon dioxide equivalents (Tg
C02Eq.).
To determine total emissions by final end-use sector, emissions from electricity generation were distributed
to each end-use sector according to its share of aggregate electricity consumption (see Table A-29). This pro-rated
approach to allocating emissions from electricity generation may overestimate or underestimate emissions for
particular sectors due to differences in the average carbon content of fuel mixes burned to generate electricity.
5 See the Indirect CO: fr°m CHj Oxidation box in the Energy chapter for a discussion of accounting of carbon from
hydrocarbon and CO emissions.
A-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table A-1D: 2004 Energy consaropdoD Data and CO. Emissions tram Fossil Fuel Corafiosdon by Fuel Typa
6
8
9
10
11
12
13
14
15
Fuel Type •'
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg,F)
Pentanes Plus
•Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
11.0 - ' 87.0
11.0
87.0
,
'
5,030.0 3,082.0
1,570.6 803.9
944.0 502.4
89.2 23.7
• 537.4 94.8
46.6
136.1
,
0.3
6,611.6 3,972.9
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,258.3 NE .
1,258.3
NE
.
8,114.8 708.0
4,239.3 25,304.5
31.2
1,174.0 5,816.6'
2,528.7
20.6
601.8 13.3
319.3 16,568.7
213.5 345.8
10.6
(155.5)
52.1
595.9
1,482.6
(75.6)
13,612.4 26,012.5
20,081.9
20,081.9
5,604.1
1,200.9
111.1
12.7
*
885.5
191.6
-
49.0
26,935.9
Terr.
39.8
39.8
24.73
635.7
106.5
71.9
9.7
13.4
215.0
219.2
700.2
Total
21,478.0
11.0
- 87.0
1,258.3
20,081.9
39.8
22,563.7
33,754.9
31.2
8,654.6
2,613.3
143.2
1,260.7
17,149.6
.1,800.2
10.6
(155.5)
52.1
787.8
1,482.6
(75.6)
49.0
77,845.5
Emissions'1 (Tg COj Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
1.0 8.2
1.0
8.2
265.5 162.7
108.5 57.9
68.4 36.4
6.4 1.7
33.7 5.9
3.3
10.6
"fl.O
375.0 228.9
117.1
117.1
428.4
305.1
85.0
1.5
37.8
22.4
16.7
0.7
(11.3)
3.4
60.2
94.2
(5.6)
850.6
NE
yiA
1,791.2
2.1
421.2
177.4
0.8
1,162.6
27.0
-
1,828.6
1,877.6
1,877.6
295.9
97.4
-
8.0
0.9
69.1
*
19.4
0.4
2,271.2
3.6
3.6
1.3
46.5
7.7
5.0
0.7
0.8
15,1
17.1
51.4
Total
2,007.5
1.0
8.2
117.1
NE
1,877.6
3.6
1,191.2
2,406.6
• 2.1
626.7
183.4
10.3
79.1
•
1,203.4
140.4
0.7
(11.3)
3.4
• 79.6
94.2
(5.6)
0.4
5.605.7
•Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
* Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-21
-------
Table ft-Tl: 2003 Energy Consumption Data and COi Emissions from Fossa Fuel Combustion by Fuel Type
1 23456789
10
12
13
14
15
Fuel Type
Total Coal
. Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
10.0 84.0
10.0
84.0
5,246.0 3,323.0
1,502.9 750.7
904.6 481.4
75.5 20.1
522.9 92.3
45.5
111.1
j.
0.3
,
6,758.9 4,157.7
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,265.4
1,265.4
7,882,3
4,112.5
1,124.5
17.4
574.2
312.0
163.9
7.5
(143.8)
51.7
578.3
1,477,3
(50.4)
13,260.2
NE 20,066.1
NE
20,066.1
706.0 5,259.2
24,643.4 1,208.9
30.2
5,583.6 160.3
2,418.3 11.2
13.0
16,266.4
331.9 875.4
*
162.1
49.2
25,349.4 26,583.4
Terr.
39.6
39.6
26.94
597.1
100.3
68.5
9.1
12.5
201.2
205.4
*
663.6
Total
21,465.1
10.0
84.0
1,265.4
20,066.1
39.6
22,443.5
32,815.6
30.2
8,354.7
2,498.0
122.2
1,214.8
16,825.1
1,687.6
7.5
(143.8)
51.7
740.7
1,477.3
(50.4)
49.2
76,773.4
Emissions" (Tg CO: Eq.) from Energy Use
Res. Comm. Ind. Trans. .Elec. Terr.
0.9 7.9
0.9
7,9
276.9 175.4
103.7 54.0
65.5 34.9
5.4 1.4
32.8 5.8
3.2
8.7
0.0
381.6 237.3
117.7
117.7
416.1
295.6
81.4
1.2
36.0
21.9
12.8
0.5
(10.4)
3.4
58.5
93.9
(3.7)
829.4
NE
37.3
1,744.2
2,1
404.4
169.7
0.8
1.141.4
25.9
1,781.5
1,876.1
1,876.1
277.6
97.1
11.6
0.8
68.3
16.4
0.4
2,251.2
3.6
3.6
U
43.7
7.3
4.8
0.7
0.8
14.1
16.0
'
48.7
Total
2,006.3
0.9
7.9
117.7
NE
1,876.1
3.6
1,184.8
2,338.2
2.1
605.0
175.3
8.7
76,3
1,180.6
131.6
0.5
(10.4)
3.4
74.9
93.9
(3.7)
0.4
5,529.7
• Expressed as gross calonfic values (he., higher heating values). Adjustments indude biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption {see Table A-26).
"»Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
Table ft-12:2002 Energy Consumption Data and CO, I missions from Fossil Fnel Combustion by Fuel fyro
A-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
10
12
13
14
15
Fuel Type .
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bl)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
' AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oi(>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Cotnm.
11.0 91.0
11.0
91.0
5,031.0 3,235.0
1,462.5 680.9
859.8 444.1
59.9 16.0
542.7 95.8
45.1
79.8
0.2
6,504.5 4,006.9
Adjusted Consumption (TBtu|*
Ind. • Trans. Elec.
1,250.9 NE
,.'
1,250.9 '
NE
8,167.4 70ZO
3,980.9 24.41Z4
33.7
1,192.7 5,322.2
2,459.8
13.8
579.6 13.5
309.0 16,196.3
133.5 386.9
7.5
(144.2)
52.4
569.0
1,403.3
(135.7)
13,399.2 25,114.4
19,659.7
,
19,659.7
5,789.4
960.1
126.8
7.2
663.4
, -162.7
49.4
26,458.6
Tern
12.6
12.6
22.85
556.8
92.8
61.8
8.2
11.2
189.4
193.6
-
592.3
Total
21,025.2
11.0
91.0
1,250.9
19,659.7
12.6
22,947.6
32,053.7
33.7
8,038.3
2,528.8
97.9
1,242.7
16,739.8
1,457.2
7.5
(144.2)
52.4
732.0
1,403.3
(135.7)
49.4
76,075.9
Emissions'9 {Tg CO] Eq.) from Energy Use
Res. • Comm. Ind. Trans. Elec. Terr.
1.0 8.6
1.0
8.6
265.6 170.8
100.6 48.7
62.3 32.2
4.3 1.1
34.1 6.0
3.2
6.2
0.0
367.3 228.1
116.4
116.4
431.1
286.1
86.4
1.0
36.4
21.7
10.4
0.5
(10.4)
3.5
57.5
89.2
(10.0)
833.7
NE
37.1
1,729.0
2.3
385.4
172.6
0.8
1.137.6
30.2
1,766.1
1,838.1
1,838.1
305.6
77.9
9.2
0.5
f
51.7
16.4
0.4
2,222.0
1.2
1.2
1.2
40.7
6.7
4.3
0.6
0.7
13.3
15.1
43.1
Total
1,965.3
1.0
8.6
116.4
NE
1,838.1
1.2
1,211.4
2,283.1
2.3
582.1
177.5
7.0
78.0
1,175.8
113,7
0.5
(10.4)
3.5
74.0
89.2
(10.0)
0.4
5,460.2
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include btofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fiiel consumption (see Table A-26).
' Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated) . ' • • .
A-23
-------
Table M3:2001 Energy Consumption Data and CO, Emissions from Fossil Fuel condmsdon by Fuel Type
6
8
10
11
12
13
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalts. Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
' Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg. F)
Other Oil (>401 deg. F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All FuelsL
Res. Comm.
11.2 91.0
11.2
91.0
4,906.5 3,123.7
1,538.6 754.8
908.3 508.4
95.1 31.4
535.2 94.5
37.4
82.9
0.2
6,456.4 3,969.4
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,355.2 NE
1,355.2
NE
8,047.6 642.0
4,155.3 23,940.0
34.9
1,288.2 5,219.3
2,580.4
23.2
500.6 12.9
295.0 15.823.4
184.7 269.0
6.1
(131.3)
61.6
571.8
1,430.7
(75.4)
13,558.0 24,582.0
19,574.4
19,574.4
5,484.3
1,284.1
170.5
1,016.0
97.6
46.9
26,389.6
Terr.
10.2
10.2
22.92
632.2
109.4
98.9
0.9
7.0
187.6
228.4
665.3
Total
21,042.0
11.2
91.0
1,355,2
19,574.4
10.2
22,227.0
32,304.9
34.9
8,204.1
2,679.2
150.6
1,150.2
16,343.5
1,781.1
6.1
(131.3)
61.6
669.6
1.430.7
(75.4)
46.9
75,620.8
Emissions1* (Tg COj Eq.) from Energy Use
Res. Comm. Ind. Trans, Elec. Terr.
1.1 8.6
1.1
8.6
259.0 164.9
106.2 54.1
65.8 36.8
6.8 2.2
33.6 5.9
2.6
6.5
0.0
366.3 227.6
126.1
126.1
424.9
299.7
93.3
1,7
31.4
20.7
14.4
0.4
(9.5)
4.1
57.8
90.9
(5.6)
850.6
NE
,
33.9
1,694.1
2.4
378.0
181.1
0.8
1,110.9
21.0
1,728.0
1,830.1
1,830.1
289.5
101.5
12.3
79.3
9.9
0.4
2,221.5
0.9
0.9
U
46.4
7.9
6.9
0.1
0.4
13.2
17.8
48.5
Total
1,966.8
1.1
8.6
126.1
NE
1,830.1
0.9
1,173.4
2,301.9
2.4
594.1
188.0
10.8
72.2
1,147.4
138.9
0.4
(9.5)
4.1
67.7
90.9
(5.6)
0.4
5,442.4
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
* Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Tttle 0-14: 2000 Eoenw CO
vtion Data and CO, Emissions mm Fossa Wei Gomhmdon to fnel Time
i
6
8
10
12
13
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal •
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt& Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401 deg, F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes'
Geothermal
TOTAL (All Fuels)
Res. Comm.
10.6 85.8
10.6
85.6
i
5,099.8 3,254.4
1,563.1 749.7
904.8 491.0
94.6 29.7
563.7 99.5
44.5
84.9
-
0.2
i
6,673.5 4,089.9
Adjusted Consumption (TBtu)* '
Ind. Trans. Elec.
1,366.8 NE
1,366.8
NE
8,745.5 672.0
3,692.7 23,976.8
36,3
1,188.7 5.078.7
2.718.1
15.6
605.3 11.2
150.2 15,753,5
169.6 379.1
3,8
(145.6)
106.5
564.0
1,435.6
(401.2)
13,805.0 24,648.8
20,110.4
20,110.4
5,114.7
1,150.3
174.5
-
882.2
93.6
48.1
26,423.5
Terr.
10.2
10.2
12.67
471.7
71.3
74.1
2.4
8.0
185,1
130.9
494.6
Total
21,583.8
10.6
85.8
1,366.8
20,110.4
10.2
22,889.1
31,604.3
36.3
7,908.9
2,792.1
142.2
1,287.7
16,133.3
1,646.8
3.8
(145.6)
106.5
657.8
1,435.6
(401.2)
48.1
76,135.3
Emissions6 (Tg CCh Eq.) from Energy Use •
Res. Comm. Ind. Trans. Elec. Terr.
1.0 8.1
1.0
8.1
269.2 171.8
107.7 53.7
65.5 35.6
6.8 2.1
35.4 6.2
3.1
-~6.6
0.0
377.9 233.6
127.2
127.2
461.7
264.5
86.1
1.1
38.0
10.5
13.2
0.3
(10.5)
7.0
57.0
91.2
(29.5)
853.4
NE
35.5
1,697.2
2.5
367.8
190.7
0.7
1.106.0
29.6
1,732.7
1,880.2
1,880.2
270.0
90.9
12.6
68.8
9.5
0.4
2,241.5
05
0.9
0.7
34.2
5.2
5.2
0.2
0.5
13.0
10.2
35.8
Total
2,017.4
1.0
8.1
. 127.2
NE
1,880,2
0.9
1,208.9
2,248.3
2.5
572,7
195.9
10,2
80,8
1,132.6
128.5
• 0,3
(10.5)
7.0
66.5
91.2
(29.5)
0.4
5,475.0
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
11 Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-25
-------
Table R-15:1999 Eaeim Consninmlon Data and C0> Emissions mm Fossil Fuel Combustion by Fuel Tina
6
8
9
W
11
12
13
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Othef Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401 deg. F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Corom,
13.9 101.6
13.9
101.6
4,856.9 3,132.0
1,472.7 661.4
827.8 438.4
111.2 26.9
533.7 94.2
28.4
73.3
0.1
6,343.4 3,895.1
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,362.2 NE
1,362.2
NE
8,598.1 674.0
3,598.1 23,415.5
39.2
1,175.5 4.887.4
2,623.8
12.8
435.0 13.5
151.7 15,675.9
150.9 175.7
6.4
(127.8)
103.5
556.9
1,421.1
(287,9)
13,558.4 24,089.5
19,333.6
19,333.6
4,736.3
1,215.8
139.5
970.4
• 106.0
50.6
25,336.3
Terr.
10.2
10.2
.
461.0
79.4
59.5
3.7
8.3-
164.0
146.0
471.2
Total
20,821.5
13.9
101.6
1,362.2
19,333.6
10.2
21,997.3
30,824.5
39.2
7,548.0
2,683.4
154.7
1,084.7
16,020,0
1,516.3
6.4
' (127.8)
103.5
663.0
1,421.1
(287.9)
50.6
73,693.8
Emissions11 (Tg CO: Eq.) from Energy Use
Res. Comm. Ind. Trans. Elee. Terr.
1.3 9.6
1.3
9.6
256.4 165.3
101.5 47.3
59.9 318
8.0 1.9
33.6 5.9
2.0
5.7
0.0
^
359.2 222.3
126.7
126.7
453.9
259.4
85.1
0.9
27.4
10.6
11.8
0.4
(9.3)
6.9
56.3
90.3
(21.1)
840.0
NE
35.6
1,655.2
2.7
353.9
184.1
0.8
1,099.9
13.7
1,690.8
1,807.6
1,807.6
250.0
96.5
10.1
75.7
10.7
0.4
2,154.5
0.9
0.9
33.6
5.8
4,2
0.3
0.5
11.5
11.4
34.5
Total
1,946.2
1.3
9.6
126.7
NE
1,807.6
0.9
1,161.3
2,193.6
2.7
546.6
188.3
11.1
68.3
1,124.1
118.3
*
• 0.4
(9.3)
6,9
67.0
90.3
(21.1)
0.4
5,301.4
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
b Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table ft-16:1998 Energy ConsamjrrJonData and CO. Eral»lons from fostil Fuel ComliDsdonDyFnel Type
10
12
13
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel • :
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
• Res. Comm.
12.4 100.6
'12.4
100.6
4,671.1 3,098.2
1,313.8 660.8
771.9 428.8
108.3 31.2
433.6 76.5
39.0
85.2
•
0.1
5,997.4 3,859.6
Adjusted Consumption (TBtu)«
Ind. Trans. • Elec.
1,409.4
1,409.4
8,980.5
3,511.2
1,199.8
22.1
303.9
*
199.4
173.3
4.0
(154.9)
89.7
550.6
1,437.3
(313.9)
13,901.0
NE
NE
665.0
22,623.1
35.5
4,652.7
2,549.4
16.6
15,289.9
78.9
23,288.1
19,264.2
19,264.2
4,507.1
1,3104
• 135.5
1.059.5
115,3
50.4
25,132.1
Terr. Total
10.5 20,797.1
12.4
100.6
1,409.4
19,264.2
10.5 10.5
• 21,921.9
445.4 29,864.7
35,5
71.9 7,260.6
59.9 2,609.2
6.3 167.8
5.9 836.5
160.3 15,688.7
141.1 1,538.1
4.0
(154.9)
89.7
666.1
1,437.3
(313.9)
50.4
456.0 72,634.2
. Emissions11 (Tg CO: Eq.) from Energy Use
Res. Comm. . Ind. Trans. Elec. Terr.
1.2 9.5
1.2
9.5
246.6 163.6
90.9 47.5
55.9 31.1
7.8 2.2
27.3 4.8
2.7
6.6
•
0.0
338.7 220.5
131.1
,
131.1
474.1
254,0
86,9
1.6
19.1
14.0
13.5'
0.3
(11-2)
5,9
55,7
91.4
(23.1)
859.3
NE
35.1
1,598.3
2.4
336.9
178.9
1.0
1,072.9
6.2
1,633.4
1,801.1
1,801.1
""
237.9
104.1
9.8
82.7
11.7
0.4 -
2,143.5
1.0
1.0
32.5
5.2
4,2
0.4
0.4
_
11.3
11.0
33.5
Total
1,943.9
1.2
9.5
131.1
NE
1,801.1
1.0
1,157.3
2,127.4
2.4
525.8
183,1
12.0
52.6
1,100.8
120.0
0.3
1
(11.2)
5.9
67.3
91.4
(23.1)
04
5,228.9
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels. conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
k Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-27
-------
Table MI: 1991 Enem Consumption Daia and CO, missions from Fossil Fuel ComttusdoDbv FOB) TVDO
6
8
9
W
12
13
15
Fuel Type
Total Coal
Residential Coal
Commercial Coat
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha '
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
15.9 128.7
15.9
128.7
5,125.0 3.306.4
1,428.1 703.9
874.4 443.8
92.9 24.6
460.7 81.3
42.7
111.2
0.1
6,569.0 4,139.0
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,462.7 NE
1,462.7
NE
9,203.5 779.0
3,873.0 22,089.5
39.7
1,192.6 4.546.8
2,511.6
18.8
463.7 13.4
211.8 14,841.6
235.6 136.5
9.1
4.6
(152.4)
30.0
516.9
1,445.1
(102.9)
14,539.2 22,868.5
18,945.2
18,945.2
3,987.6
929.9
110.5
723.1
-96.4
' 502
23,913.0
Terr.
10.4
10.4
•
445.3
81.6
62.1
4.0
6.5
160.0
131.1
455.7
Total
20,563.0
15.9
128.7
1,462.7
18,945,2
10.4
22,401.4
29,469.7
39.7
7,249.7
2,573.7
140.3
1,025.7
15,256.2
1,337.5
9.1
4.6
(152.4)
30.0
613.4
1,445.1
(102.9)
50.2
72,484.4
Emissions" (Tg COz Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
1.5 122
1.5
12.2
270.6 174.5
98.9 50.7
63.3 32.1
6.6 1.8
28.9 5.1
3.0
8.7
0.0
370.9 237.4
136.1
136.1
485.9
278.5
86.4
1.3
29,1
14.9
18.4
0.6
0.3
(11.0)
2.0
52.3
91,8
<7.6)
900.5
NE
41.1
1,5622
2.7
329.3
176.2
0.8
1,042.5
10.6
1,603.3
1,771.3
1,771.3
210.5
74.2
8.0
56.4
9.7
0.4
2,056.3
1.0
1.0
32.4
5.9
4.4
0.3
0.4
11.2
10.2
33.4
Total
1,922.0
1.5
12.2
136.1
NE
1,771.3
1.0
1.182.6
2,096.8
2.7
525.0
180.6
10.0
64.3
1,071.6
104.3
0.6
0.3
(11.0)
2.0
62.0
91.8
(7.6)
0.4
5,201.8
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
* Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table JM8:1996 Energy ConsummiOD Data and CO, Emotion* from Fossil Fool Comliusflon by Fuel Type
9
10
13
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil.
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
16.4 120.1
16.4
120.1
5,390.6 3,251.0
1,488.0 751.3
_
926.0 482.9
88.8 21.0
473.2 83.5
• 26.5
137.2
^
0.1
f
6,895.0 4,122.3
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,498.9
•
1.498.9
9,198.1.
3,865.3
1,177.6
18.3
436.9
199,9
' 281.7
7.0
13.7
(151.4)
38.5
518.8
1,437.1
(112.8)
14,5613
NE
NE
736.0
21,966.1
37.4
4,355.2
2.530.6
14.7
14,713.3
314.9
22,702.1
18,467.6
18,467.6
3,729.0
819.5
109.3
635.0
-
. 75.2
48.9
23,065.0
Terr. Total
10.3 20,113.3
16.4
--120.1
1.498.9
18,467.6
10.3 10.3
• 22,304.6
434.3 29,324.6
37.4
76.5 7,127.5
78.5 2.609.0
3.0 131,1
7.3 1,015.7
151.1 15,090.8
118.0 1.486.7
.
7.0
13.7
(151.4)
38.5
594.2
1,437.1
(112.8)
48.9
444.7 71,791.3
Emissions'" (Tg CO: Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
1.5 11.3
1.5
11.3
284.6 171.6
103.1 54.3
67.1 35.0
6.4 1.5
29.7 5.2
1.9
10.7
0.0
389.2 237.2
139.3
139.3
485.6
278.6
85.3
1.3
27.4
14.0
22.0
0.5
1.0
(11.0)
2.6
52.4
91.3
(8.3)
903.5
NE
38.9
1,555.0
2.6
315.4
177.6
0.9
1,034.0
24.6
^
1,593.9
1,725.8
1,725.8
196.9
65.1
7.9
49.5
7.6
0.4
1,988.1
0.9
0.9
31.5
5.5
5.5
0.2
0.5
10.6
9.2
"
32.5
Total
1,878.9
1.5
11.3
139.3
NE
1,725.8
0.9
1,177.5
2,087.6
2.6
516,2
183.1
9.4
63.7
1,060.5
116.0
0.5
1.0
(11.0)
2.6
60.1
91.3
(8.3)
0.4
5,144.4
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
b Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
U.S EPA Headquarters Library
, Mail code 34Q4T
1200 Pennsylvania Avenue NW
Washinaton. DC 20460
A-29
-------
•-.-y • ' ,J ••'»{ .;'.•: \ '- • '" /'
; ; ^,^\'v-:-""J.''^^ " ' ^
Table ft-19:1995 Energy Consumption Data and COi Emissions Mm Fossil fuel Combnstion by Fuel Type
7 •
8
S
10
13
14
15
Fuel Type ^
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Penlanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Contm.
17.4 116.3
17.4
116.3
4,983.6 3,116.6
1,383.3 732.0
904.8 478.9
74.3 22.1
404.2 71.3
18.1
141.5
0.1
6,384.3 3,964.9
Adjusted Consumption jTBtu)*
' Ind. 'Trans. Elec.
1,521.7 NE
1
1,521.7
NE
8,900.4 723.0
3,524.4 21,357.1
39.6
1,123.0 4,069.2
2,409.2
15.4
432,5 16.7
200.1 14,435.1
284.7 387.3
5.3
14.5
(144.7)
34.5
502.5
1,377.3
(320.9)
13,946.4 22,080.1
17,466.3
17,466.3
4,325.5
757.4
108.1
2.8
566.0
80.5
45.6
22,594.8
Terr.
10.2
10.2
•
461.8
89.5
75.7
3.6
5.6
146.7
140.7
472.0
Total
19,131.9
17.4
'116.3
1,521.7
17,466.3
10.2
22,049.0
28,216.0
39.6
6,773.4
2,487.8
115.4
930.5
14,800.0
1,520.1
5.3
14.5
(144.7)
34.5
583.2
1.377.3
(320.9)
45.6
69,442.6
Emissions" (Tg COi Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
1.6 11.0
1.6
11.0
263.1 164.5
96.2 53.1
65.5 34.7
5.3 1.6
25.4 ' 4.5
1.3
11.0
0.0
360.9 228.6
141.6
141.6
469.9
253.9
81.3
1.1
27.1
14.1
22.2
0.4
1.1
(10.5)
2.3
50.8
87.5
(23.6)
i
865.3
NE
38.2
1,513.3
2.7
294.7
169.1
1.1
1,015.5
30.2
1,551.4
1,632.2
1,632.2
228.3
60.3
7.8
0.2
44.2
8.1
0.3
1,921.2
0.9
0.9
33.7
6.5
5.3
0.3
0.4
10.3
11.0
34.6
Total
1,787.4
1.6
11.0
141.6
NE
1,632.2
0.9
1,164.0
2,010.4
2.7
490.5
174.6
8.3
58,4
1,041.2
118.6
0.4
1.1
(10.5)
2.3
59.0
87.5
(23.6)
0.3
4,962.2
• Expressed as gross calorific values (i.e., higher heating values). Adjustments indude biofuds, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
b Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table ft-20:1994 Energy Consompdon Data and CO, Emissions from Fossfl Fuel Cotnlrasdon by Fael Typo
6
8
10
11
12
13
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel-
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke ,
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
20.7 117.1
20.7
117.1
4,980.9 2,978.1
1,420.2 787.5
959.8 500.9
64.9 19.5
395.4 69.8
25.2
171.9
0.1
6,421.8 3,882.7
Adjusted Consumption (TBtu)*
Ind. Trans. Bee.
1,575.0
1,575.0
i
8,424.0
3,742.0
1,103.7
16.9
450.8
.
192.4
368.4
6.1
18.7
(135,8)
80.8
501.8
1,417.5
(279.2)
13,741.0
NE 17,260.9
NE
17,260.9
708.0 4,000.1
20,941.9 . 1,063.2
38.1
3,910.8 120.1
2,470.6 . 4.4
32.2
-
14,132.1
358.1 869.0
1
69.7
53.0
21,650.0 22,377.2
Terr.
10.0
'10.0
•
506.3
118.8
65.8
3.0
7.3
*
H7.4
164.1
516.3
Total
18,983.7
20.7
117.1
1,575.0
17,260.9
10.0
21,091.2
28,461.0
38.1
6,714.1
2,540.7
104.3
955.5
14,497.1
1,931.5
6.1
•18.7
(135.8)
. 80.8
571.7
1,417.5
(279.2)
53.0
68,588.9
Emissions11 (Tg CO: Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
1.9 11.0
1.9
11.0
263.0 157.2
99.0 57.3
J
69.5 36.3
4.6 1.4
24.8 4.4
1.8
13.4
0.0
363.9 225.5
146.6
146.6
-
444.7
269.4
79.9
1.2
28.3
13.6
28.7
0.4
1.4
(9.8)
5.4
50.7
90.1
"
(20.5)
860.7
NE
37.4
1,487.1
2.6
283.2
173.5
2.0
997.8
27.9
1,524.5
1,611.5
1,611.5
211.2
83.8
8.7
0.3
67.8
7.0
• 0.4
1,906.9
0.9
0.9
37.1
8.6
4.6
0.2
0.5
•
10.4
12.8
38.0
Total
1,771.9
1.9
11.0
146.6
NE
1,611.5
0.9
1,113.4
2,033.7
2.6
486.2
178.4
7.5
• 60.0
f
1,023.5
150.7
0.4
1.4
(9-8)
5.4
57.8
90.1
(20.5)
0.4
4,919.4
'Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26)
b Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-31
-------
Tabln A-21:1993 Enemy GonsnmiiOon Data and COt iralssionsfrora Fossil Rial eombDSttoa by Fuel Time
10
11
13
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coa!
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
'Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
25.6 116.5
25.6
116.5
5,098.0 2,944.4
1,448.0 779.9
973.8 493.0
75.6 14.0
398.6 70.3
29.6
172.7
0,2
6,571.5 3,840.8
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,573.9 NE
1,573.9
NE
8,445.6 644.0
3,619.5 20,535.0
38.4
1.109.9 3,649.2
2,352.9
13.1
443.3 19.0
179.5 14,108.0
391.5 367.5
0.1
21.2
(114.3)
56.4
513.1
1,401.8
(396.0)
13,639.1 21,179.0
17,187.6
17,187.6
3,559.8
1,125.1
86.5
1.4
958.6
78.6
57.3
21,929.8
Terr.
9.6
9.6
-
459.9
104.9
62.1
3.8
4.9
128.3
155.9
469.5
Total
18,913.2
25.6
116.5
1,573.9
17,187.6
9.6
20,691.8
27,967.4
38.4
6,417.3
2,416.3
106.5
936.2
14.445,3
2,046.3
0.1
21.2
(114.3)
56.4
591.9
1,401.8
(396.0)
57.3
67,629.7
Emissions'1 (Tg C02 Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
2.4 11.0
2.4
11.0
269.1 155.4
101.0 56.7
70.5 35.7
5.4 1.0
25.0 4.4
2.1
13.5
0.0
372.5 223.1
146.3
146.3
445.9
261.3
80.4
0.9
27.8
12.7
30.5
0.0
1.6
(8.3)
3.7
51.9
89.1
(29.1)
853.4
NE
34.0
1,457.3
2.6
264.3
165.5
1.2
995.0
28.7
1,491.3
1,603.9
1,603.9
187.9
89.1
6.3
0.1
74.8
8.0
0.4
1,881.3
0.9
0.9
33.8
7.6
4.4
0.3
0.3
9.0
12.2
34.6
Total
1,764.4
2.4
11.0
146.3
NE
1,603.9
0.9
1,092.3
1,999.1
2.6
464.7
169.9
7.6
58.8
1,018.8
159.6
0.0
1.6
(8.3)
3.7
59.8
89.1
(29.1)
0.4
4,856.3
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion gf fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
b Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table A-22:1992 Energy ConsumpUoD Data and Cl> Emissions from Fossil Fuel Combustion by fuel Type
1
6
a
10
.11
12
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke '
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
25.6 118.8
. 25.6
116.8
4,819.7 2,882.8
1,427.2 854.0
979.7 506.7
65.0 11.1
382.5 67.5
79.6
189.1
0.1
^
6,272.4 3,853.6
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,536.4 NE
1,536.4
NE
8,319.8 608.0
3,933.2 20,013.9
41.1
1,100.1 3,538.0
2.334.9
9.8
469.1 18.3
194.2 13.681.4
328.4 400.1
0.2
27.4
75.7
'
(85.8)
261.0
472.3
1,435.7
(354.8)
13,789.4 20,621.9
16,465.6
16,465.6
3,534.1
991.4
73.5
0.7
872.2
—
45.0
55.1
21,046.2
Terr.
8.8
8.8
•
444.9
91.8
61.3
3.3
11.9
•
122.1
154.6
453.7
Total
18,153.2
25.6
116.8
1.536.4
16,465.6
8.8
20,164.3
27,664.6
41.1
6,289.7
2,396.9
89.2
949.3
14,077.4
1,944.3
0.2
27.4
75.7
(85.8)
261.0
517.4
1,435.7
(354.8)
55.1
66,037.1
Emissions" (Tg CO] Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
2.4 11.1
2.4
11.1
254.4 1512
99.6 62.1
70.9 36.7
4.7 0.8
24.0 4.2
5.6
14.8
*
•,
0.0
•
356.5 225.4
142,9
'
142.9
439.2
280.5
79.7
0.7
29.5
13.7
25.6
0.0
2.0
5.3
(6.2)
17.3
47.8
91.3
(26.0)
862.6
NE
32.1"
1,420.2
2.8
256.2
164.3
1.2
964.5
31.2
1,452.3
1,535.8
1,535.8
186.6
78.0
5.3
0.1
68.0
4.5
0.4
1,800.7
0.8
0.8
32.6
6.6
4.3
0.2
0.7
8.6
12.1
'
33.4
Total
1,692.9
2.4
•11.1
142.9
• NE
1,535.8
0.8
1,064.5
1,973.0
2.8
455.5
168.7
6.4
59.6
992.4
151.7
0.0
2.0
5.3
(6.2)
17.3
52.3
91.3
(26.0)
0.4
4,730.9
1 Expressed as gross calorific values (i.e., hig to heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
" Consumption and/or emissions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-33
-------
Table A-2& 1991 Energy ConsompdoD Data and CO, Emissions from Fossil Fuel Combustion by Fuel Two
1
6
11
12
13
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Totfll Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401 deg. F)
Other Oil (>401 deg. F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
2S.3 115.4
25.3
115.4
4,683.7 2,806.6
1,392.2 905.2
930.4 517.4
72.3 12.1
389.5 68.7
85.1
221.9
6,101.2 3,827.2
Adjusted Consumption (TBtu)"
Ind. Trans. Elec.
1,577.2 NE
1,577.2
NE
.
7,942.3 620.0
3,562.1 19,589.9
41.7
1,070.8 3,451.3
2,364.4
11.4
371.4 19.9
193.3 13,488.2
270.9 224.4
(0.1)
38.9
(25,9)
(18.4)
249.2
446.2
1,404.5
(450.2)
13,081.6 20,209.9
16,249.7
16,249.7
3,398.8
1,198.6
83.6
0.3
1,085.3
29.3
54.5
20,901.6
Terr.
7.7
7.7
-
425.4
71.4
78.2
2.8
13.8
124.7
134.6
433.2
Total
17,975.4
25.3
115.4
1,577.2
16,249.7
7.7
19,451.4
27,073.5
41.7
6,124.9
2,443.0
98.6
863.3
13,891.2
1,937.1
(0.1)
38.9
(25.9)
(18.4)
249.2
475.5
1,404.5
(450.2)
54.5
64,554.7
Emissions'1 (Tg COi Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
2.4 10.9
2.4
10.9
247.3 148.2
97.0 66.0
67.4 37.5
5.2 0.9
24.5 4.3
6.0
17.3
346.7 225.0
146.5
- 146.5
419.3
254.0
77.5
0.8
23.3
13.6
21.1
(0.0)
.2.9
(1.8)
(1.3)
16.5
45.1
89.3
(33.0)
819.8
NE
32.7
1,388.4
2.9
249.9
166.5
1.3
,
950.4
17.5
1,421.t
1,515.6
v 1,515.6
179.4
93.7
6.1
0.0
84.7
3.0
. 0.4
1,789.2
0.7
0,7
31.0
'5.2
5.5
0.2
0.9
8.8
10.5
31.7
Total
1,676.2
2.4
10.9
146.5
NE
1,515.6
0.7
1,026.5
1,930.1
2.9
443.6
172.0
7.1
54.2
978.8
151.1
(0.0)
2.9
(1.8)
(1.3)
16.5
48.1
89.3
(33.0)
0.4
4,633.6
* Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuets, conversion of fossil fuels, non-energy use (see Table A-25), and international bunker fuel consumption (see Table A-26).
»Consumption and/or emissions of select fuels are shewn as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table Jfr-241990 Energy Conjummion Data and CO. Emissions from f ossO Fuel Combustion by Fuel Type
6
10
11
12
13
14
15
Fuel Type
Total Coal
Residential Coal
Commercial Coal
Industrial Other Coal
Transportation Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Total Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG
Lubricants
Motor Gasoline
Residual Fuel
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Pentanes Plus
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
TOTAL (All Fuels)
Res. Comm.
31.0 123.8
31.0
123.8
4,519.1 2,697.8
1,407.0 953.1
978.1 535.8
63.9 11.8
365.0 64.4
111.2
229.8
5,957.0 3,774.8
Adjusted Consumption (TBtu)*
Ind. Trans. Elec.
1,628.1
1,628.1
7,826.4
3,875.7
1,143.4
12.3
406.4
185.2
364.1
0.2
50.9
53.7
(33.1)
167.8
441.8
1,451.9
(369.0)
13,330.2
NE
NE
680.0
19,900.3
45.0
3,503.1
2,473.0
21.6
13,557.2
300.3
20,580.3
16,294.6
16,294.6
3,335.0
1,2912
96.5
1,167.0
28.7
52.7
20,974.6
Terr. Total
7.0 18,084.5
31.0
123.8
1,628.1
16,294.6
7.0 7.0
• 19,058.3
374.8 27,803.3
45.0
74.0 6,331.1
61,0 2,534.0
2.6 90.6
14.4 ' 871.9
101.0 13,954.6
121.8 2,183.2
0.2
50.9
53.7
'
(33.1)
167.8
470.6
1,451.9
(369.0)
52.7
381.9 64,998.8
Emissions6 (Tg CO? Eq.) from Energy Use
Res. Comm. Ind. Trans. Elec. Terr.
2.9 11.6
2.9
11.6
238.6 142.4
98.3 69.5
70.8 38.8
4.6 0.8
22.9 4.0
7,8
17.9
339.8 223.5
151.2
151.2
4132
276.9
82.8
0.9
25.5
13.0
28.4
0.0
3.7
3.8
(2-4)
11.1
44.7
92.3
(27.0)
841.3
NE
35.9
1,410.9
3.1
253.7
174.2
1.4
955.2
23.4
1,446.8
1,519.1
1,519.1
176.1
100.9
7.0
91.0
2.9
0.4
1,796.5
0.6
0.6
27.4
5.4
4.3
0.2
0.9
7.1
9.5
28.0
Total
1,685.5
2.9
11.6
151.2
NE
1,519.1
0.6
1,006.1
1,9835
3.1
458.5
178.5
6.5
54.8
983.2
170.3
0.0
3.7
3.8
(2.4)
11.1
47.6
92.3
(27.0)
0.4
4,675.9
• Expressed as gross calorific values (i.e., higher heating values). Adjustments include biofuels, conversion of fossil fuels, non-energy use (see Table A-2S), and international bunker fuel consumption (see Table A-26).
b Consumption and/or missions of select fuels are shown as negative due to differences in EIA energy balancing accounting. These are designated with parentheses.
NE (Not Estimated)
A-35
-------
iWHBOrza: unaaiusuuiu
Sector/Fuel Type
Industry
Industrial Coking Coal
Industrial Other Coal
Natural Gas to Chemical
Plants, Other Uses
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Naphtha (<401deg.F)
Other Oil (>401deg.F)
Still Gas
Petroleum Coke
Special Naphtha
Other (Wax/Misc.)
Distillate Fuel Oil
Waxes
Miscellaneous Products
Transportation
Lubricants
U.S. Territories
Lubricants
Other Petroleum (Misc. Prod.)
Total
iD-town row coanunguon UHUII
1990 1991
4,537.5 4,559.5
0.0 0.0
8.2 8.5
302.5 301.1
1,170.2 1,076.5
1,201.4 1,377.9
186.3 166.7
82.6 44.8
347.8 "298.9
753.9 827.3
21.3 22.0
178.0 153.0
107.1 88.0
7.0 7.1
33.3 35.1
137.8 152.6
176.0 157,5
176.0 157.5
86.7 114.4
0.7 0.6
86.0 113.8
4,800.2 4,831.4
1992 1993
4,676.3 4,843.9
0.0 0.0
9.5 10.0
259.4 292.0
1,102.2 1,149.0
1,390.7 1,351.0
170.0 173.1
61.5 275.9
377.1 350.6
814.5 844.1
11.3 28.4
231.1 123.5
104.6 104.6
7.0 6.9
37.3 40.0
100.1 94.7
160.5 163.5
160.5 163.5
62.6 74.3
1.5 3.3
61.2 71.0
4,899.4 5,081.6
1994 1995
5,161.3 5,221.7
9.3 43.8
10.9 11.3
354.0 357.2
1,172.9 1,178.2
1,545.7 1,586.9
180.9 177.8
257.9 303.4
398.3 373.0
838.6 801.0
21.9 40.1
136.4 132.6
81.1 70.8
6.8 8.0
40.6 40.6
105.9 97.1
170.8 167.9
170.8 167.9
54.9 92.8
1.9 2.0
53.0 90.8
5,387.0 5,482.4
1996
5,292.9
26.0
11.4
359.9
1,175.9
1,652.0
172.5
316.5
479.3
729.6
0.0
148.2
74.5
9.2
48.7
89.0
163.0
163.0
121.0
0.8
120.2
5,576.9
1997 1998
5,513.5 .5,744.4
0.0 8.4
11.2 10.4
385.5 426.6
1,223.6 1,262.6
1,670.4 1,744.4
182.3 190.8
298.9 204.3
.536.4 584.0
861.3 818.7
2.1 0.0
117.7 213.8
72.3 107.3
10.4 11.7
43.7 42.4
97.8 119.0
172.1 180.2
172.1 180.2
133.5 137.9
2.5 1.3
131.0 136.7
5,819.1 6,062.5
1999
6,013.4
45.7
11.1
437.7
1,324.4
1,820.7
192.8
261.4
502.1
811.1
16.1
283.9
145.4
11.7
37.4
111.9
182.1
182.1
143.8
1.4
142.4
6,339.2
2000
5,633.6
62.7
12.4
440.6
1,275.7
1,665,4
189.9
236.7
613.5
722.2
12.6
140.7
97.4
11.7
33.1
119.2
179.4
179.4
165.5
16.4
149.1
5,978.4
2001
5,289.1
25.5
11.3
415.7
1.256.9
1.553.4
174.0
201,6
493.7
662.4
35.8
207.6
78.5
11.7
36.3
124.9
164.3
164.3
80.3
0.0
80.3
5,533.8
2002
5,429.8
46.4
12.0
422.8
1,240.0
1,620.3
171.9
171,4
582.6
632.1
57.8
192.1
102.4
11.7
32.2
134.2
162.4
162.4
138.7
1.5
137.2
5,730.9
2003
5,384.0
72.0
11.9
423.4
1,219.5
1,545.1
159.0
169.1
613.0
699.4
59.0
163.5
80.5
11.7
31.0
126.0
150.1
150.1
146.6
1.6
145.0
5,680.8
2004
5,933.3
214.3
11.9
423.4
1,303.9
1,576.4
161.0
170.4
749.4
779.5
63.5
272.7
51.0
11.7
30.8
113.4
152.1
152.1
156.3
1.7
154.6
6,241.8
Note, These values are unadjusted non-energy fuel use provided by E1A. They have not yet been adjusted to remove petroleum feedstock exports and processes accounted for in the Industrial Processes Chapter.
Table fl-26: intaraaUoDal Bunker Fad Consumption (nan
Fuel Type
Marine Residual Fuel Oil
1990 1991
715.7 801.5
Marine Distillate Fuel Oil & Other 1 58.0 1 49.3
Aviation Jet Fuel
Total
656.5 660.6
1,530.2 1,611.4
1992 1993
669,8 533.9
145.9 146,6
666.4 675.1
1,482.2 1.355.7
1994 1995
524.5 523.2
121.2 125.7
683.9 723.0
1,329.6 1,372.0
1996
536,4
114.1
743.7
1,3942
1997 1998
575.2 594.8
125.5 158.8
796.6 807.4
1,497.3 1,561.0
1999
489.7
113.6
837.9
1,441.2
2000
444.1
85.9
862.3
1,392.2
2001
426.0
72.4
845.6
1,344.0
2002
289.9
70.2
880.5
1,240.7
2003
239.0
82.7
847.2
1,168.9
2004
353.7
96.6
853.8
1,304.1
A-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table A-27: Key Awumpdonslor Estimating Carton Dioxide Emissions
Carbon Content Coefficient
Fuel Type (Tg Carfaon/QBtu) Fraction Oxidized
Coal
Residential Coal
Commercial Coal
Industrial Coking Coal
Industrial Other Coal
Electric Power Coal
U.S. Territory Coal (bit)
Natural Gas
Petroleum
Asphalt & Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel
Kerosene
LPG (energy use)
LPG (non-energy use)
Lubricants
Motor Gasoline
Residual Fuel Oil
Other Petroleum
AvGas Blend Components
Crude Oil
MoGas Blend Components
Misc. Products
Misc. Products (Territories)
Naphtha (<401 deg. F)
Other Oil (>401deg.F)
Pentanes Plus
Petrochemical Feedstocks
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils
Waxes
Geothermal
[a]
[a]
31.00
[a]
[a]
25.14
14.47
20.62
18.87
19.95
(a)
19.72 .
[a]
[a]
20.24
[a] .
21.49
18.87
N
[aj
la]
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
[a]
19.81
2.05
0.99
0.99
0.99
0.99
0.99
-0.99
0.995
0.99
0.99
0.99
0.99
0.99
0.995
.
0.99
0.99
0.99.
0.99
0.99
0.99
0.99
0.99
•0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
0.99
1.00
Sources: Carbon coefficients from EIA (2004b) Combustion efficiency for coal from Bechtel (1993) and for petroleum and natural gas from IPCC
(IPCC/UNEPWECD/IEA1997)
|a| These coefficients vary annually due to fluctuations in fuel quality (see Table A-28).
A-37
-------
IibleJUfcAmunDy Variable Carton Content Coefflclenu by Year (TgCarbon/QBtm
Fuel Type
Residential Coal
Commercial Coal
Industrial Other Coal
Electric Power Coal
LPG (energy use)
LPG (non-energy use)
Motor Gasoline
Jet Fuel
MoGas Blend Components
Misc. Products
Unfinished Oils
Crude Oil
1990
25.92
25.92
25.58
25.68
17.21
16.83
19.41
19.40
19.41
20.16
20.16
20.16
1991
26.00
26.00
25.60
25.69
17.21
16.84
19.41
19.40
19.41
20.18
20.18
20.18
1992
26.13
26.13
25,62
25.69
17.21
16.84
19.42
19.39
19.42
20.22
20.22
20.22
1993
25.97
25.97
25.61
25.71
17,22
16,80
19.43
19.37
19.43
20.22
20.22
20.22
1994
25.95
25.95
25.63
25.72
17.22
16.88
19.45
19.35
19.45
20.21
20.21
20.21
1995
26.00
26.00
25.63
25.74
17.20
16.87
19.38
19.34
19.38
20.23
20.23
20.23
1996
25.92
25.92
25.61
25.74
17.20
16.86
19.36
19.33
19.36
20.25
20.25
20.25
1997
26,00
26.00
25.63
25.76
17.18
16.88
19.35
19.33
19.35
20.24
20.24
20.24
1998
26.00
26.00
25.63
25.76
17.23
16.88
19.33
19.33
19.33
20,24
20,24
20,24
1999
26.00
26.00 '
25.63
25.76
17.25
16.84
19.33
19.33
19.33
20.19
20.19
20.19
2000
26.00
26.00
25.63
25.76
17.20
16.81
19.34
19.33
19.34
20.23
20.23
20.23
2001
26.00
26.00
25,63
25.76
17.21
16.83
19.34
19.33
19.34
20.29
20,29
20.29
2002
26.00
26.00
25.63
25.76
17.20
16.82
19,35
19.33
19.35
20.30 '
20.30
20.30
2003
26.00
26.00
25.63
25.76
17.21
16.84
19,33
19.33
19.33
20.28
20.28
20.28
2004
26.00
26.00
25.63
25.76
17.20
16.81
19.33
19.33
19.33
20.33
20.33
20,33
Source: ElA(2004b)
Tablo ft-29: Electrtcitv Consumption by EniHJse Sector (BilDon Kilowatt-Hours]
End-Use Sector
Residential
Commercial
Industrial
Transportation
Total
1990
924
838
1,070
5
2,837
1991
955
855
1,071
5
2,886
1992
936
850
1,107
5
2,897
1993
995
885
1,116
5
3,001
1994
1,008
913
1,154
5
3,081
1995
1,043
953
1,163
5
3,164
1996
1,083
980
1,186
5
3,254
1997
1,076
1,027
1,194
5
3,302
1998
1,130
1,078
1,212
5
3,425
1999
1,145
1,104
1,230
5
3,484
2000
1,192
1,159
1,235
5
3,592
2001
1,203
1,197
1,127
5
3,532
2002
1,267
1,218
1,138
6
3,629
2003
1,273
1,200
1,176
7
3,656
2004
1,293
1,229
1,187
8
3,717
Note. Does not mdude the U.S. territories.
Source EIA(2004a)
A-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
2.2. Methodology for Estimating the Carbon Content of Fossil Fuels
This subannex presents the background and methodology for estimating the carbon content of fossil fuels
combusted in the United States. The carbon content of a particular'fossil fuel represents the maximum potential
emissions to the atmosphere if all carbon in the fuel is oxidized during combustion. The carbon content coefficients
used in this report were developed using methods first'outlined in EIA's Emissions of Greenhouse Gases in the
United States: 1987-1992 (1994) and were developed primarily by EIAl This annex describes an updated
methodology for estimating the carbon content of coal, and presents a time-series analysis of changes in U.S. carbon
content coefficients. A summary of carbon content coefficients used in this report appears in Table A-30.
Though the methods for estimating carbon contents for coal, natural gas, and petroleum products differ in
their details, they each follow the same basic approach. First, because carbon coefficients are presented in terms of
mass per unit energy (i.e., teragrams carbon per quadrillion Btu or Tg/QBtu), those fuels that are typically described
in volumetric units (petroleum products and natural gas) are converted to units of mass using an estimated density.
Second, carbon contents are derived from fuel sample data, using descriptive statistics to estimate the carbon share
of the fuel by weight. The heat content of the fuel is then estimated based on the sample data, or where sample data
are unavailable or unrepresentative, by default values that reflect the characteristics of the fuel as defined by market
requirements. A discussion of each fuel appears below.
The carbon content of coal is described first because approximately one-third of all U.S. carbon emissions
from fossil fuel combustion are associated with coal consumption. The methods and sources for estimating the
carbon content of natural gas are provided next. Approximately one-fifth of U.S. greenhouse gas emissions from
fossil fuel combustion are attributable to natural gas consumption. Finally, this subannex examines carbon contents
of petroleum products. U.S. energy consumption statistics account for more than 20 different petroleum products.
A-39
-------
Table ft-30: Carton Content Coefficients Died In this Report fTg Cartion/QBtul
Fuel Type
Coal
Residential Coal9
Commercial Coal"
Industrial Coking Coal'
Industrial Other Coal3
Utility Coal*
Natural Gas •
Petroleum
Asphalt and Road Oil
Aviation Gasoline
Distillate Fuel Oil
Jet Fuel'
Kerosene
LPG (energy use)'
LPG (non-energy use)"
Lubricants
Motor Gasoline-
Residual Fuel
Other Petroleum
Av Gas Blend Comp.
Mo Gas Blend Comp"
Crude Oil"
Misc. Products9
Misc. Products (Terr.)
Naphtha (<401 deg. F)
Other oil (>401deg.F)
Pentanes Plus
Petrochemical Feed.
Petroleum Coke
Still Gas
Special Naphtha
Unfinished Oils'
Waxes
Other Wax and Misc.
Geothermal
1990
25.92
25.92
25.51
25.58
25.68
14.47
20.62
18.87
19.95
19.40
19.72
17.21
16.83
20.24
19.41
21.49
18.87
19.41
20.16
20.16
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.16
19.81
19.81
2.05
1991
26.00
26.00
25,51
25.60
25.69
14.47
20.62
18.87
19.95
19.40
19.72
17.21
16.84
20.24
19.41
21.49
18.87
19.41
20.18
20.18
20.00
18.14
19.95
18.24
19.37
27.85
17.51.
19.86
20.18
19.81
19.81
2.05
1992
26.13
26.13
25.51
25.62
25,69
14.47
20.62
18.87
19.95
19.39
19.72
17.21
16.84
20.24
19.42
21.49
18.87
19.42
20.22
20.22
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.22
19.81
19.81
2.05
1993
25.97
25.97
25.51
25.61
25.71
14.47
20.62
18.87
19.95
19.37
19.72
17.22
16.80
20.24
19.43
21.49
18.87
19.43
20.22
20.22
20.00
18.14
19.95
18,24
19.37
27.85
17.51
19.86
20.22
19.81
19.81
2.05
1994
25.95
25.95
25.52
25.63
25.72
14.47
20,62
18,87
19.95
19.35
19.72
17.22
16.88
20.24
19.45
21.49
18.87
19.45
20.21
20.21
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.21
19.81
19.81
2.05
1995
26.00
26.00
25.53
25.63
25.74
14.47
20.62
18.87
19.95
19.34
19.72
17,20
16,87
20.24
19.38
21.49
18.87
19.38
20.23
20.23
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.23
19.81
19.81
2.05
1996
25.92
25.92
25.55
25.61
25.74
14.47
20.62
18.87
19.95
19.33
19.72
17.20
16.86
20.24
19,36
21.49
- 18.87
19.36
20,25
20.25
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.25
19.81
19.81
2.05
1997
26.00
26.00
25.56
25,63
25.76
14.47
20.62
18.87
19.95
19.33
19.72
17.18
16.88
20.24
19.35
21.49
18.87 '
19.35
20,24
20.24
20.00
18.14
19.95
18.24
19.37
27.85
17.51 -
19.86
20.24
19.81
19.81
2.05
1998
26.00
26.00
25.56
25.63
25.76
14.47
20.62
18.87
19.95
19.33
19.72
17.23
16.88
20.24
19.33
21.49
18.87
19.33
20.24
20.24
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.24
19.81
19,81
2.05
1999
26.00
26.00
25.56
25.63
25.76
14.47
20.62
18.87
19.95
19.33
19.72
17.25
16.84
20.24
19.33
21.49
18.87
19.33
20.19
20.19 '
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20,19
19.81
19.81
2.05
2000
26.00
26.00
25.56
25.63'
25.76
14.47-
20.62
18.87
19.95
19.33
19.72
17.20
16.81
20.24
19.34
21.49
18.87
19.34
20.23
20.23
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.23
19.81
19.81
2.05
2001
26.00
26.00
25.56
25.63
25.76
14.47
20.62
18.87
19.95
19.33
19.72
17.21
16.83
20.24
19.34
21.49
18.87
19.34
20.29
20.29
20.00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.29
19.81
19.81
2.05
2002
.
26.00
26.00
25.56
25.63
25.76
14.47
20.62
18.87
19.95
19.33
19.72
17.20
16,82
20.24-
19.35
21.49
18.87
19.35
20.30
20.30
20.00
18.14
19.95
18.24
19.37
.27.85
17.51
19.86
20.30
19.81
19.81
2.05
2003
26.00
26.00
25.56
25.63
25.76
14.47
20.62
18.87
19,95
19.33
19.72
17,21
16.84
20.24
19.33
21.49
18.87
19.33
20.28
20.28
20,00
18.14
19.95
18.24
19.37
27.85
17.51
19.86
20.28
19.81
19.81
2.05
2004
26.00
26,00
25.56
25.63
25.76
14.47
20,62
18.87
19.95
19.33
19.72
17.20
16.81
20.24
19.33
•21.49
18.87
19.33
20.33
20.33
20.00
• 18.14
19,95
18.24
19,37
27.85
17,51
19.86
20.33
19,81
19.81
2.05
•Carbon contents vary annually based on changes in fuel composition.
"•Carbon content for utility coat used in the electric power calculations. Ail coefficients based on higher heating value. Higher heating value (gross heating value) is the total amount of heat released when a fuel is burned.
Coal, crude oil, and natural gas all include chemical compounds of carbon and hydrogen. When those fuels are burned, the carbon and hydrogen combine with oxygen in the air lo produce carbon dioxide and water. Some of
heating value), in contrast,' does not include the heat spent in transforming the water into steam. Using a simplified methodology based on International Energy Agency defaults, higher heating value can be converted to .
lower heating value for coal and petroteum products by multiplying by 0.95 and for natural gas by multiplying by 0.90. Carbon content coefficients are presented in higher heating value because U.S. energy statistics are
reported by higher heating value.
A-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Coal
Approximately one-third of all U.S. carbon dioxide emissions from fossil fiiel combustion are associated
with coal consumption. Although the IPCC guidelines provide carbon contents for coal according to rank, it was
necessary to deveJop carbon content coefficients by consuming sector to match the format in which coal
consumption is reported by EIA. Because the carbon content of coal varies by the state in which it was mined and
by coal rank, and because the sources of coal for each consuming sector vary by year, the weighted average carbon
content for coal combusted in each consuming sector also varies over time. A time series of carbon contents by coal
rank and consuming sector appears in Table A-31.'
Methodology
The methodology for developing carbon contents for coal by consuming sector consists of four steps.
Step 1. Determine carton contents by rank and by state of origin ',
Carbon contents by rank are estimated on the basis of 6,588 coal samples collected by the U.S. Geological '
Survey between 1973 and 1989. These coal samples are classified according to rank and state of origin. For each
rank in each state, the average heat content and carbon content of the coal samples are calculated. Dividing the
carbon content (reported impounds carbon dioxide) by the heat content (reported in million Btu or MMBtu) yields
an average carbon content coefficient. This coefficient is then converted into units of Tg/QBtu.
Step 2. Allocate sectoral consumption by rank and state of origin
U.S. energy statistics provide data on the origin of coal used in four areas: 1) the electric power industry, 2)
industrial coking, 3) all other industrial uses, and 4) the residential and commercial end-use sectors. Because U.S.
energy statistics do not provide the distribution of coal rank consumed by each consuming sector, it is assumed that
each sector consumes a representative mixture of coal ranks from a particular state that matches the mixture of all
coal produced in that state during the year.
Step 3. Weight sectoral carbon contents to reflect the rank and state of origin of coal consumed
Sectoral carbon contents are calculated by multiplying the share of coal purchased from each state by rank
by the carbon content estimated in Step 1. The resulting partial carbon contents are then totaled across all states and
ranks to generate a national sectoral carbon content.
Where,
= The carbon content by consuming sector;
= The portion of consuming sector coal consumption attributed to a given rank in each state;
= The estimated carbon content of a given rank in each state.
1 For a comparison to earlier estimated carbon contents please see Chronology and Explanation of Changes in
Individual Carbon Content Coefficients of Fossil Fuels near the «nd of this annex.
\
A-41
-------
Table ft-31: Carbon Content Coefficients for Coal by Consuming Sector and Coal Rank tTg/QBtn) (1990-2004)
Consuming Sector
Electric Power
Industrial Coking
Other Industrial
Residential/ Commercial
Coal Rank
Anthracite
Bituminous
Sub-bituminous
Lignite
1990
25.68
25.51
25.58
25.92
28.26
25.43
26.50
26.19
1991
25.69
25.51
25.60
26.00
28.26
25.45
26.49
26.21
1992
25.69
25.51
25.62
26.13
28.26
25.44
26.49
26.22
1993
25.71
25.51
25.61
25.97
28.26
25.45
26.48
26.21
1994
25.72
25.52
25.63
25.95
28.26
25.46
26.49
26.24
1995
25.74
25.53
25.63
26.00
28.26
25.47
26.49
26.22
1996
25.74
25.55
25.61
25.92
28.26
25.47
26.49
26.17
1997
25.76
25.56
25.63
26.00
28.26
25.48
26.49
26.20
1998
25.76
25.56
25.63
26.00
28.26
25.47
26.49
26.23
1999
25.76
25.56
25.63
26.00
28.26
25.48
26.49
26.26
2000
25.76
25.56
25.63
26.00
28.26
25.49
26.48
26.30
2001
25.76
25.56
25.63
26.00
28.26
25.49
26.48
26.30
2002
25.76
25.56
25.63
26.00
28.26
25.49
26.48
26.30
2003
25.76
25.56
25.63
26.00
28.26
25.49
' 26.48
26.30
2004
25.76
25.56
25.63
26.00
28.26 »
25.49 P
26.48 P
26.30 P
' Preliminary
Sources: Carbon content coefficients by consuming sector from EIA (2005a). Carbon content coefficients by coal rank from USGS (1998) and SAIC (2005).
A-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Step 4. Develop national-level carbon contents by rank for comparison to IPCC defaults
Although not used to calculate emissions, national-level carbon contents by rank are more easily compared
to carbon contents of other countries than are sectoral carbon contents. This step requires weighting the state-level
carbon contents by rank developed under Step 1 by overall coal production by state and rank (consumption by rank
is unavailable in U.S. energy statistics). Each state-level carbon content by rank is multiplied by the share of
national production of that rank that each state represents. The resulting partial carbon contents are then summed
across all states to generate an overall carbon content for each rank.
Jvwik "rankl ^-rankl "rank2 ^-rtnk2 "i"*..""" "rinkn *-rankn
Where,
Nnmk = The national carbon content by rank;
Prank = The portion of U.S. coal production attributed to a given rank in each state; and
Cnnk = The estimated carbon content of a given rank in each state.
Data Sources
The ultimate analysis of coal samples was based on the 6,588 coal samples from USGS (1998). Data
contained in the CoalQual Database are derived primarily from samples taken between 1973 and 1989, and were
largely reported in State Geological Surveys.
Data on coal distribution by state and consumption by sector, as well as coal production by state and rank,
was obtained from EIA (2002).
Uncertainty
Carbon contents vary considerably by state. Bituminous coal production and sub-bituminous coal
production represented 53.4 percent and 38.1 percent of total U.S. supply in 2000,'respectively. Carbon content
coefficients for bituminous coal vary from a low of 200.5 pounds carbon dioxide per MMBtu in Kansas to a high of
232.0 pounds carbon dioxide per MMBtu in Montana. In 2000, however, just 200 tons of bituminous coal was
produced in Kansas, and none was produced in Montana. In 2000, more than 60 percent of bituminous coal was
produced in three states: West Virginia, Kentucky, and Pennsylvania, and this share has remained fairly constant
since 1990. These three states show a variation in carbon content for bituminous coals of ±0.7 percent, based on
more than 2,000 samples (see Table A-32).
Similarly, the carbon content coefficients for sub-bituminous coal range from 201.3 pounds carbon dioxide
per MMBtu in Utah to 217.5 pounds carbon dioxide per MMBtu in Washington. Utah showed no sub-bituminous
coal production in 2000, and Washington produced just 4,000 tons. Wyoming, however, has represented between 75
percent and 82 percent of total .sub-bituminous coal production in the United States since 1990. Thus, the carbon
content coefficient for Wyoming, based on 435 samples, dominates.
The interquartile range of carbon content coefficients among samples of sub-bituminous coal in Wyoming
was ±1.5 percent from the mean. Similarly, this range among samples of bituminous coal from West Virginia,
Kentucky, and Pennsylvania was ±1.0 percent or less for each state. The large number of samples and the low
variability within the sample set of the states that represent the predominant source of supply for U.S. coal suggest
that the uncertainty in this factor is very low, on the order of+1.0 percent.
Table ft-32: Variability in Carbon content Coefficients by Rank Across States [Kilograms Carbon Dioxide Per
MMBtnl
State
Alabama
Alaska
Arizona
Arkansas
Colorado
Georgia
Number of
Samples
946
90
11
70
292
35
Bituminous
92.85
98.34
9652
94.39
95.03
Sub-
bituminous
98.11
97.52
•96.48
Anthracite
-
Lignite
99.11
98.66
94.98
96.48
A-43
-------
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maryland
Massachusetts
Michigan
Mississippi
Missouri
Montana
Nevada '
New Mexico
North Dakota
Ohio
Oklahoma
Pennsylvania
Tennessee
Texas
Utah
Virginia
Washington
West Virginia
Wyoming
1
16
125
89
28 •
870
1
46
3
3
8
91
301
2
167
186
646
46
739
58
48
152
456
14
566
476
.
93.35
92.67
91.94
90.94
92.58
.
94.35
-
92.85
-
91.85
105.23
94.39
95.25
.
91.85
92.67
93.39
92.80
-
96.07
93.53
95.39
93.89
94.66
94.89
.
.
.
-
.
-
-
.
-
-
-
9775
.
94.89
• -
.
.
-
-
-
91.31
-
98.66
- -
97.20
-
.
-•
-
.
-
.
'.
114.82
-
-
.
103.60
.
103.92
.
.
'
103.65
-
-
.
98.52
102.51
-
-
.
.
.
..
.
.
96.03
.
.
-
98.20
'
99.36
99.84
.
99.56
.
.
-
.
94.76
-
-
106.55
'
-
-No Sample Data Available
Sources: USGS (1998) and SAIC (2005)
Natural Gas
Natural gas is predominantly composed of methane, which is 75 percent carbon by weight and contains
14.2 Tg C/QBtu (Higher Heating Value), but it may also contain many other compounds that can lower or raise its
overall carbon content. These other compounds may be divided into two classes: 1} natural gas liquids (NGLs), and
2) non-hydrocarbon gases. The most common NGLs are ethane (QHe), propane (C3Hg), butane (C4HIO), and, to a
lesser extent, pentane (C5H,2) and hexane (QsH,,,). Because the NGLs have more carbon atoms than methane
(which has only one), their presence increases the overall carbon content of natural gas. NGLs have a commercial
value greater than that of methane, and therefore are usually separated from raw natural gas at gas processing plants
and sold as separate products. Ethane is typically used as a petrochemical feedstock, propane and butane have
diverse uses, and natural gasoline1 contributes to the gasoline/naphtha "octane pool," used primarily to make motor
gasoline.. '•
Raw natural gas can also contain varying amounts of non-hydrocarbon gases, such as carbon dioxide,
nitrogen, helium and other noble gases, and hydrogen sulfide. The share of non-hydrocarbon gases is usually less
than 5 percent of the total, but there are individual natural gas reservoirs where the share can be much larger. The
treatment of non-hydrocarbon gases in raw gas varies. Hydrogen sulfide is always removed. Inert gases are
removed if their presence is substantial enough to reduce the energy content of the gas below pipeline specifications.
Otherwise, inert gases will usually be left in the natural gas. Because the raw gas that is usually flared contains
NGLs and carbon dioxide, it will typically have a higher overall carbon content than gas that has been processed and
moved to end-use customers via transmission and distribution pipelines.
Methodology
The methodology for estimating the carbon contents of natural gas can be described in five steps.
1 A term used in the gas processing industry to refer to a mixture of liquid hydrocarbons (mostly pentanes and heavier
hydrocarbons) extracted from natural gas.
A-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Stepf. Define pipeline-quality natural gas
In the United States, pipeline-quality natural gas is expected to have an energy content greater than 970 Btu
per cubic foot, but less than 1,100 Btu per. cubic foot. Hydrogen sulfide content must be negligible. Typical
pipeline-quality natural gas is about 95 percent methane, 3 percent NGLs, and 2 percent non-hydrocarbon gases, of
which approximately 1 percent is carbon dioxide.
However, there is a range of gas compositions that are consistent with pipeline specifications. The
minimum carbon content coefficient for natural gas would match that for pure methane, which equates to an energy
content of 1,005 Btu per standard cubic foot. Gas compositions with higher or lower Btu content tend to have
higher carbon emissions factors, because the "low" Btu gas has a higher content of inert gases (including carbon
dioxide offset with more NGLs), while "high" Btu gas tends to have more NGLs.
is flared:
Step 2. Define flared gas
Every year, a certain amount of natural gas is flared in the United States. There are several reasons that gas
• There may be no market for some batches of natural gas, the amount may be too small or too variable, or
the quality might be too poor to justify treating the gas and transporting it to market (such is the case when
gas contains large shares of carbon dioxide). All natural gas flared for these reasons is probably "rich"
. associated gas, with relatively high energy content, high NGL content, and a high carbon content ,
f , • • ' •
» Gas treatment plants may flare substantial volumes of natural gas because of "process upsets," because the
gas is "off spec," or possibly as part of an emissions controJ system. Gas flared at processing plants may be
of variable quality.
Data on the energy content of flare gas, as reported by states to El A, indicate an energy content of 1,130
Btu per standard cubic foot. Flare gas may have an even higher energy content than reported by, EIA since rich
associated gas can have energy contents as high as 1,300 to 1,400 Btu per cubic foot. ''
Sfep3. Determine a relationship between carbon content and heat content
A relationship between carbon content and.heat content may be used to develop a carbon content
coefficient for natural gas consumed in the United States. In 1994, EIA examined the composition (and therefore
carbon contents) of 6,743 samples of pipeline-quality natural gas from utilities and/or pipeline companies in 26
cities located in 19 states. To demonstrate that these samples were representative of actual natural gas "as
consumed" in the United States, their heat content was compared to that of the national average. For the most recent
year, the average heat content of natural gas consumed in the United States was 1,025 Btu per cubic foot, varying by
less than 1 percent (1,025 to 1,031 Btu per cubic foot) over the past 5 years. Meanwhile, the average heat content
of the 6,743 samples was 1,027 Btu per cubic foot, and the median heat content was 1,031 Btu per cubic foot. Thus,
the average heat content of the sample set falls well within the typical range of natural gas consumed in the United
States, suggesting that these samples continue to be representative of natural gas "as consumed" in the United States.
The average and median composition of these samples appears in Table A-33.
Table A-33: Composldon of Natural BBS (Percent]
Compound
Methane
Ethane
Propane
Higher Hydrocarbons
Non-hydrocarbons
Higher Heating Value (Btu per cubic foot)
Average
93.07
3.21
0.59
0.32
2.81
1,027
Median
95.00
2.79
1 0.48
0.30
1.43
1,032
Source. Gas Technology Institute (1992)
Carbon contents were then calculated for a series of sub samples stratified by heat content. Carbon
contents were developed for eight separate sub-samples based on heat content and are shown in Table A-34.
A-45
-------
Table A-34: Carbon Content of Pipeline-Quality Natural Gas m Energy Content ITB/QBtn)
Sample . Average Carbon Content
GRI Full Sample 14.51
Greater than 1,000 Btu " . 14.47
1,025 to 1,035 Btu ' 14.45
975 to 1,000 Btu 14.73
1,000 (01,025 Btu - 14.43
1,025 to 1,050 Btu - 14.47
1,050 to 1,075 Btu ' 14,58
1,075 to 1,100 Btu ' ' 14.65 '
Greater than 1,100 Btu ' 14,92
Weighted National Average 14.47
Source- EIA(1994).
Step 4. Apply carbon content coefficients developed in Step 3 to pipeline natural gas
Because there is some regional variation in the energy content of natural gas consumed, a weighted national
average carbon content was calculated using the average carbon contents for each sub-sample of gas that conformed
with an individual state's typical cubic foot of natural gas. The result was a weighted national average of 14,47
Tg/QBtu. This was identical to the average carbon content ofall samples with more than 1,000 Btu per cubic foot
and the average carbon content for all samples with a heat content between 1,025 and 1,050 Btu per cubic foot.
Because those samples with a heat content below 1,000 Btu had an unusually high carbon content coefficient
attributable to large portions of carbon dioxide (not seen in the median sample), they were excluded so as not to bias
the carbon content coefficient upwards by including them in the final sample used to select a carbon content.
Step 5. Apply carbon content coefficients developed in Step 3 to flare gas
Selecting a carbon content coefficient for flare gas was much more difficult than for pipeline natural gas
because of the uncertainty of its composition and uncertainty of the combustion efficiency of the flare. Because El A
estimates the heat content of flare gas at 1,130 Btu per cubic foot, the average carbon content for samples with more
than 1,100 Btu per cubic foot, 14.92 Tg/QBtu, was adopted as the coefficient for flare gas. It should be noted that
the sample data set did not include any samples with more than 1,130 Btu per cubic foot.
Data Sources
Natural gas samples were obtained from the Gas Technology Institute (1992). Average heat content data
for natural gas consumed in the United States and on a state-by-state basis were taken from E1A (2005a) and El A
(2003), respectively.
Uncertainty
• The assignment of carbon content coefficients for natural gas, and particularly for flare gas, requires more
subjective judgment than the methodology used for coal. This subjective judgment may introduce additional
uncertainty.
Figure A-l shows the relationship between the calculated carbon contents for each natural gas sample and
its energy content. This figure illustrates the relatively restricted range of variation in both the energy content
(which varies by about 6 percent from average) and the carbon emission coefficient of natural gas (which varies by
about 5 percent). Thus, the knowledge that gas has been sold via pipeline to an end-use consumer allows its carbon
emission coefficient to be predicted with an accuracy of ±5.0 percent.
Figaro fl-1: Carbon Content for Samples el Plpellne-Qaalliv Natural Gas included in the Gas Technology Institute
Database
Source: EIA(1994).
A-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Natural gas suppliers may achieve the same energy contents with a wide variety of methane, higher
hydrocarbon, and non-hydrocarbon gas combinations. Thus, the plot reveals large variations in carbon content for a
single Btu value. In fact, the variation in carbon content for a single Btu value may be nearly as great as the
variation for the whole sample. As a result, while energy content has some predictive vaiue, the specific energy
content does not substantially improve the accuracy of an estimated carbon content coefficient beyond the ±5.0
percent offered with the knowledge that it is of pipeline-quality.
The plot of carbon content also reveals other interesting anomalies. Samples with the lowest emissions
coefficients tend to have energy contents of about 1,000 Btu per cubic foot. They are composed of almost pure
methane. Samples with a greater proportion of NGLs (e.g., ethane, propane, and butane) tend to have energy
contents greater than 1,000 Btu per cubic foot, along with higher emissions coefficients. Samples with a greater
proportion of inert gases tend to have lower energy content, but they usually contain carbon dioxide as one of the
inert gases and, consequently, also tend to have higher emission coefficients (see left side of Figure A-l).
For the full sample (N=6,743), the average carbon content of a cubic foot of gas was 14.51 Tg/QBtu (see
Table A-34). However, this average was raised by both the samples with less than 1,000 Btu per cubic foot that
contain large amounts of inert carbon dioxide and those samples with more than 1,050 Btu per cubic foot that
contain an unusually large amount of NGLs. Because typical gas consumed in the United States does not contain
such a large amount of carbon dioxide or natural gas liquids, a weighted national average of 14.47 Tg/QBtu that
represents fuels more typically consumed is used.2
Petroleum
There are four critical determinants of the carbon content coefficient for a petroleum-based fuel:
. • The density of the fuel (e.g., the weight in kilograms of one barrel of fuel);
• The fraction by mass of the product that consists of hydrocarbons, and the fraction of non-hydrocarbon
impurities;
• The specific types of 'families' of hydrocarbons that make up the hydrocarbon portion of the fuel; and
• The heat content of the fuel.
Cfud= (PiwxSfaO/EM
Where,
Cfuei = The carbon content coefficient of the fuel;
Dfuei = The density of the fuel;
Sfuei = The share of the fuel that is carbon; and
Efue, * = The heat content of the fuel.
Petroleum products vary between 5.6 degrees API gravity (dense products such as asphalt and road oil) and
247 degrees (ethane).3 This is a range in density of 60 to 150 kilograms per barrel, or ±50 percent. The variation in
carbon content, however, is much smaller (±5 to 7 percent): ethane is 80 percent carbon by weight, while petroleum
coke is 90 to 92 percent carbon. The tightly bound range of carbon contents can be explained by basic petroleum
chemistry.
2 The national average was weighted by applying the carbon content associated with the average heat content of natural
gas consumed in each state by the portion of national natural gas consumption represented by that state.
3 API gravity is an arbitrary scale expressing the gravity or density of liquid petroleum products, as established by the
American Petroleum Institute (API). The measuring scale is calibrated in terms of degrees API. The higher the API gravity, the
lighter the compound. Light crude oils generally exceed 38 degrees API and heavy crude oils are all crude oils with an API
gravity of 22 degrees or below. Intermediate crude oils fall in the range of 22 degrees to 38 degrees API gravity. API gravity
can be calculated.with the following formula: API Gravity = (141.5/Specific Gravity)- 131.5. Specific gravity is the density of a
material relative to that of water. At standard temperature and pressure, there are 62.36 pounds of water per cubic foot, or 8.337
pounds water per gallon.
A-47
-------
Petroleum Chemistry
Crude oil and petroleum products are typically mixtures of several hundred distinct compounds,
predominantly hydrocarbons. All hydrocarbons contain hydrogen and carbon in various proportions. When crude
oil is distilled into petroleum products, it is sorted into fractions by the boiling temperature of these hundreds of
organic compounds. Boiling temperature is strongly correlated with the number of carbon atoms in each molecule.
Petroleum products consisting of relatively simple molecules and few carbon atoms have low boiling temperatures,
while larger molecules with more carbon atoms have higher boiling temperatures.
Products that boil off at higher temperatures are usually more dense, which implies greater carbon content
as well. Petroleum products with higher carbon contents, in general, have lower energy content per unit mass and
higher energy content per unit volume than products with lower carbon contents. Empirical research led to the
establishment of a set of quantitative relationships between density, energy content per unit weight and volume, and
carbon and hydrogen content Figure A-2 compares carbon content coefficients calculated on the basis of the
derived formula with actual carbon content coefficients for a range of crude oils, fuel oils, petroleum products, and
pure hydrocarbons. The actual fuel samples were drawn from the sources described below in the discussions of
individual petroleum products.
„ )
Figure fl-2: Estimated and Actual Relationships Between Petroleum Carbon Content Coefficients and Hydrocarbon
Source: Carbon content factors for paraffins are calculated based on the properties of hydrocarbons in Guthrie (1960). Carbon content factors from other
petroleum products are drawn from sources described below. Relationship between density and emission factors based on the relationship between density and
energy content in DOC (1929), and relationship between energy content and fuel composition in Ringen et al. (1979).
The derived empirical relationship between carbon content per unit heat and density is based on the types
of hydrocarbons most frequently encountered. Actual petroleum fuels can vary from this relationship due to non-
hydrocarbon impurities and variations in molecular structure among classes of hydrocarbons. In the absence of
more exact information, this empirical relationship offers a good indication of carbon content.
Non-hydrocarbon Impurities
Most fuels contain a certain share of non-hydrocarbon material. This is also primarily true of crude oils
and fuel oils. The most common impurity is sulfur, which typically accounts for between 0.5 and 4 percent of the
mass of most crude oils, and can form an even higher percentage of heavy fuel oils. Some crude oils and fuel oils
also contain appreciable quantities of oxygen and nitrogen, typically in the form of asphaltenes or various acids.
The nitrogen and oxygen content of crude oils can range from near zero to a few percent by weight. Lighter
petroleum products have much lower levels of impurities, because the refining process tends to concentrate all of the
non-hydrocarbons in the residual oil fraction. Light products usually contain less than 0.5 percent non-hydrocarbons
by mass. Thus, the carbon content of heavy fuel oils can often be several percent lower than that of lighter fuels,
due entirely to the presence of non-hydrocarbons.
Variations in Hydrocarbon Classes
Hydrocarbons can be divided into five general categories, each with a distinctive relationship between
density and carbon content and physical properties. Refiners tend to control the mix of hydrocarbon types in
particular products in order to give petroleum products distinct properties. The main classes of hydrocarbons are
described below.
Paraffins. Paraffins are the most common constituent of crude oil, usually comprising 60 percent by mass.
Paraffins are straight-chain hydrocarbons with the general formula C^n^- Paraffins include ethane (C2H6),
propane (C3HB), butane (C4H]o), and octane (CjH)8). As the chemical formula suggests, the carbon content of the
paraffins increases with their carbon number: ethane is 80 percent carbon by weight, octane-84 percent. As the size
of paraffin molecules increases, the carbon content approaches the limiting value of 85.7 percent asymptotically (see
Figure A- 3).
A-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Cycloparaffins. Cycloparaffins are similar to paraffins, except that the carbon molecules form ring
structures rather than straight chains, and consequently require two fewer hydrogen molecules than paraffins.
CycJoparaffins always have the general formula CnH2n and are 85.7 percent carbon by mass, regardless of molecular
size.
Olefins. Olefms are a reactive and unstable form of paraffin: a straight chain with the two hydrogen atoms
at each end of the chain missing. They are never found in crude oil but are created in moderate quantities by the
refining process. Thus, gasoline, for example, may contain 2 percent olefins. They also have the general formula
CnH2i» and hence are also always 85.7 percent carbon by weight. Propylene (C3HS), a common intermediate
petrochemical product, is an oJefm.
Aromatics. Aromatics are very reactive hydrocarbons that are relatively uncommon in crude oil (10
percent or less). Light aromatics increase the octane level in gasoline, and consequently are deliberately created by
steam reforming of naphtha. Aromatics also take the form of ring structures with some double bonds between
carbon atoms. The most common aromatics are benzene (QH^), toluene (C?H8), and xylene (C8H|0). The general
formula for aromatics is CnH2n-6- Benzene is 92 percent carbon by mass, while xylene is 90.6 percent carbon by
mass. Unlike the other hydrocarbon families, the carbon content of aromatics declines asymptotically toward 85.7
percent with increasing carbon number and density. (See Figure A- 3)
Pofynuclear Aromatics. Polynuclear aromatics are large molecules with a multiple ring structure and few
hydrogen atoms, such-as naphthalene (C|0H2 and 94.4 percent carbon by mass) and anthracene (C|4H4 and 97.7
percent carbon). They are relatively rare but do appear in heavier petroleum products.
Figure A- 3 illustrates the share of carbon by weight for each class of hydrocarbon! Hydrocarbon molecules
containing 2 to 4 carbon atoms are all natural gas liquids; hydrocarbons with 5 to 10 carbon atoms are
predominantly found in naphtha and gasoline; and hydrocarbon compounds with 12 to 20 carbons comprise "middle
distillates," which are used to make diesel fuel, kerosene and jet fuel. Larger molecules are generally used as
lubricants, waxes, and residual ruel oil.
i
Figure A- 3: Carbon Content of Pore Hydrocarbons as a Function of carton Number
Source: Hunt (1979) . . ' '
If one knows nothing about the composition of a particular petroleum product, assuming that it is 85.7
percent carbon by mass is not an unreasonable first approximation. Since denser products have higher carbon
numbers, this guess would be most likely to be correct for crude oils and fuel oils. The carbon content of lighter
products is more affected by the shares of paraffins and aromatics in the blend.
Energy Content of Petroleum Products
The exact energy content (gross heat of combustion) of petroleum products is not generally known. EIA
estimates energy consumption in Btu on the basis of a set of industry-standard conversion factors. These conversion
factors are generally accurate to within 3 to 5 percent.
Individual Petroleum Products
The United States maintains data on the consumption of more than'20 separate petroleum products and
product categories. The carbon contents, heat contents, and density for each product are provided below in Table A-
35. A description of the methods and data sources for estimating the key parameters for each individual petroleum
product appears below.
Table ft-35: CartOD Content Coefficients and Underlying Data for Petroleum Products
Fuel 2004 Carbon Content Gross Heat of Combustion Density Percent
(TgJQBtu) (MMBtu/Barrel) (API Gravity) Carbon
A-49
-------
Motor Gasoline
LPG(total)
LPG (energy use)
LPG (non-energy use)
Jet Fuel
Distillate Fuel
Residual Fuel
Asphalt and Road Oil
Lubricants
Petrochemical Feedstocks
Aviation Gas
Kerosene
Petroleum Coke
Special Naphtha
Petroleum Waxes
Still Gas
Crude Oil
Unfinished Oils
Miscellaneous Products
Pentanes Plus
Natural Gasoline
19.33
16.99
17.20
16.81
19.33
19.95
21.49
' 20.62
20.24
19.37
18.87
19.72
27.85
19.86
19.81
17.51
20.33
20.33
20.33
18.24
18.24
5.253
a
a
a
5.670
5.825
6.287
6.636
6.065
5.248"
5.048
5.670
6.024
5.248
5.537
6.000
5.800
5.825
5.796
4.620
4.620
. 59.6
a
a
a
42.0
35.5
11.0
5.6
25.6
67.1"
69.0
41.4
.
51.2
43.3
.
30.5
30.5
30.5
81.7
81.7
86.60
a
a
a
8630
86.34
85.68
' 83.47
85.80
84.1 1»
85.00
86.01
92.28
84.76
85.29
.
85.49
85.49
85.49
83.70
83.70
• LPG is a blend of multiple parafftnic hydrocarbons: ethane, propane, isobutane, and normal butane, each with their own heat content, density and carbon
content, see Table A-38
b Parameters presented are for naphthas with a boiling temperature less than 400 degrees Fahrenheit Petrochemical feedstocks with higher boiling points are
assumed to have the same characteristics as distillate fuel.
- No sample data available
Sources: EIA (1994), EIA (2005a), and SAIC (2005).
Motor Gasoline and Motor Gasoline Blending Components
Motor gasoline is a complex mixture of relatively volatile hydrocarbons with or without small quantities of
additives, blended to form a fuel suitable for use in spark-ignition engines.4 "Motor Gasoline" includes
conventional gasoline; all types of oxygenated gasoline, including gasohol; and reformulated gasoline; but excludes
aviation gasoline.
Gasoline is the most widely used petroleum product in the United States, and its combustion accounts for
nearly 20 percent of all U.S. carbon dioxide emissions. EIA collects consumption data (i.e., "petroleum products
supplied" by wholesalers) for several types of gasoline: leaded regular, unleaded regular, and unleaded high octane.
The American Society for Testing and Materials (ASTM) standards permit a broad range of densities for gasoline,
ranging from 50 to 70 degrees API gravity, or 111.52 to 112.65 kilograms per barrel, which implies a range of
possible carbon and energy contents per barrel. Table A-36 reflects changes in the density of gasoline over time and
across grades of gasoline through 2004.
Table A-36: Motor Basollne Density, 1900 - 2004 (Degrees API)
Fuel Grade
Winter Grade
Low Octane
Mid Octane
High Octane
Summer Grade
Low Octane
Mid Octane
High Octane
1990
62.0
60.8
59.0
58.2
57.4
55.5
1991
61.8
60.4
59.3
58.0
57.1
55.7
1992
61.4
60.2
59.0
57.4
56.4
55.6
1993
61.0
59.9
58.7
56.1
55.5
54.4
1994
60.1
59.4
58.5
55.7
54.8
53.8
1995
59.8
59.1
58.0
56.1
55.6
55.1
1996
60.6
59.9
58.5
56.9
56.2
55.3
1997
61.5
60.7
59.3
57.1
56.6
56.4
1998
61.8
61.2
60.0
57.6
56.7
55.7
1999
61.6
61.3
60.3
57.7
57.4
57.4
2000
61.6
61.2
59.7
56.8
58.0
55.8
2001
61.7
61.2
59.1
57.2
58.0
55.5
2002
61.6
61.2
59.0
56.5
58.0
55.7
2003
61,8
61,2
59.9
56.8
58.0
56.0
2004
62.4
61.2
60.7
57.4
58.0
57.0
Source: National Institute of Petroleum and Energy Research (1990 through 2005).
The density of motor gasoline increased across all grades through 1994, partly as a result of the leaded
gasoline phase-out. In order to maintain the "anti-knock" quality and octane ratings of gasoline in the absence of
4 Motor gasoline, as defined in ASTM Specification D 4814 or Federal Specification VV-G-1690C, is characterized as
having a boiling range of 122 degrees to 158 degrees Fahrenheit at the 10-percent recovery point to 365 degrees to 374 degrees
Fahrenheit at the 90-percent recovery point.
A-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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lead, the portion of aromatic hydrocarbons used in gasoline increased. As discussed above, aromatic hydrocarbons
have a lower ratio of hydrogen to carbon than other hydrocarbons typically found in gasoline, and therefore increase
fuel density.
The trend in gasoline density was reversed beginning in'1996 with the development of fuel additives that
raised oxygen content. In 1995, a requirement for reformulated gasoline in non-attainment areas implemented under
the Clean Air Act Amendments further changed the composition of gasoline consumed in the United States. In
reformulated gasoline, methyl tertiary butyl ether (MTBE) and tertiary amyl methyl ether (TAME) are often added
to standard gasoline to boost its oxygen content. The increased oxygen reduces the emissions of carbon monoxide
and unbumed hydrocarbons. These oxygen-rich blending components are also much lower in carbon than standard
gasoline. The average gallon of reformulated gasoline consumed in 2001 contained 8 percent MTBE and 0.5
percent TAME. The characteristics of reformulated fuel additives appear in Table A-37.
Table fl-87: Cfiaracierteflcs of Major Reformulated Fuel flmntfm
Additive Density (Degrees API) Carbon Share (Percent) • Carbon Content (Tg/QBtu)
MTBE
ETBE
TAME
59.1
• 59.1
52.8 >
68.2
70.5
70.5
16.92
17.07
' • 17.00
Source: API (1988).
i
Methodology
Step 1. Disaggregate U.S. gasoline consumption by grade and type
U.S. gasoline consumption was divided by product grade and season for both standard gasoline and
reformulated gasoline. . • .' »
. * <
Step 2. Develop carbon content coefficients for each grade and type '
Carbon content coefficients for each grade and type are derived from three parameters: gasoline density,
share of the gasoline mixture that is carbon; and the energy content of a gallon of gasoline. Carbon content
coefficients for reformulated fuels were calculated by applying the carbon content coefficient for the fuel additives
listed in Table A-37 to the increased share of reformulated gasoline represented by these additives (standard
gasoline contains small amounts of MTBE and TAME) and weighting the gasoline carbon content accordingly.
Step 3. Weight overall gasoline carbon content coefficient for consumption of each grade and type
The carbon content for each grade and type of fuel is multiplied by the share of overall consumption
represented by the grade and fuel type. Individual coefficients are then summed and totaled to yield an overall
carbon content coefficient.
Data Sources
Data for the density of motor gasoline were obtained from the National Institute for Petroleum and Energy
Research (1990 through 2005). Data on the characteristics of reformulated gasoline were taken from API (1988).
Carbon contents of motor gasoline were obtained from the following: DeLuchi (1993), Applied Systems
Corporation (1979), Ward, C.C. (1978), and Rose and Cooper (1977).
Standard heat contents for motor gasoline of 5.253 MMBtu per barrel conventional gasoline and 5.150
MMBtu per barret reformulated gasoline were adopted from EIA (2005a).
Uncertainty
There are two primary contributors to the uncertainty of carbon content coefficients for motor gasoline.
The first is the small number of motor gasoline samples and ultimate analyses from Deluchi et al. However, as
demonstrated above in Figure A- 3, the amount of variation in carbon content of gasoline is restricted by the
compounds in the fuel to ±4 percent.
The second primary contributor to uncertainty is the assumed heat content. The heat contents are industry
standards established many years ago. The heat contents are standard conversion factors used by EIA to convert
volumetric energy data to energy units. Because the heat contents of fuels change over time, without necessarily
and directly altering their volume, the conversion of known volumetric data to energy units may introduce bias.
A-51
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Thus, a more precise approach to estimating emissions factors would be to calculate carbon content per unit of
volume, rather than per unit of energy. Adopting this approach, however, makes it difficult to compare U.S. carbon
content coefficients with those of other nations.
The changes in density of motor gasoline over the last decade suggest that the heat content of the fuels is
also changing. However, that change within any season grade has been less than 1 percent over the decade. Of
greater concern is the use of a standardized heat content across grades, which show a variation in density of ±1.5
percent.
Jet Fuel
Jet fuel is a refined petroleum product used in jet aircraft engines. There are two classes of jet fuel used in
the United States: "naphtha-based" jet fuels and "kerosene-based" jet fuels. In 1989, 13 percent^ of U.S.
consumption was naphtha-based fuel, with the remainder kerosene-based jet fuel. In 1993, the U.S. Department of
Defense began a conversion from naphtha-based JP-4 jet fuel to kerosene-based jet fuel, because of the possibility of
increased demand for reformulated motor gasoline limiting refinery production of naphtha-based jet fuel. By 1996,
naphtha-based jet fuel represented less than one-half of one percent of all jet fuel consumption. The carbon content
coefficient for jet fuel used in this report represents a consumption-weighted combination of the naphtha-based and
kerosene-based coefficients.
*
Methodology
Step I. Estimate the carbon content far naphtha-based jet fuels
Because naphtha-based jet fuels are used on a limited basis in the United States, sample data on its
characteristics are limited. The density of naphtha-based jet fuel (49 degrees) was estimated as the central point of
the acceptable API gravity range published by ASTM. The heat content of the fuel was assumed to be 5.355
MMBtu per barrel based on EIA industry standards. The carbon fraction was derived from an estimated hydrogen
content of 14.1 percent (Mattel and Angello 1977), and an estimated content of sulfur and other non-hydrocarbons
of 0.1 percent.1
Step 2. Estimate the carbon content for kerosene-based jet fuels
The density and carbon share of kerosene-based jet fuels was based on the average composition of 39 fuel
samples taken by Boeing Corporation (the leading U.S. commercial airline manufacturer) in 1989. The EIA's
standard heat content of 5.670 MMBtu per barrel was adopted for kerosene-based jet fuel.
Step 3, Weight the overall jet fuel carbon content coefficient for consumption of each type of fuel
The carbon content for each jet fuel type is multiplied by the share of overall consumption of that fuel type.
Individual coefficients are then summed and totaled to yield an overall carbon content coefficient
Data on the carbon content of naphtha-based jet fuel was taken from C.R. Mattel and L.C. Angello (1977).
Data on the density of naphtha-based jet fuel was taken from ASTM (1985). Standard heat contents for kerosene
and naphtha-based jet fuels were adopted from EIA (2005a). Data on the carbon content and density of kerosene-
based jet fuel was taken from Hadallar and Momenthy (1990).
Uncertainty
Variability in jet fuel is relatively small with the average carbon share of kerosene-based jet fuel varying by
less than ±1 percent and the density varying by ±1 percent. This is because the ratio of fuel mass to useful energy
must be tightly bounded to maximize safety and range. There is more uncertainty associated with the density and
carbon share of naphtha-based jet fuel because sample data were unavailable and default values were used. This
uncertainty has only a small impact on the overall uncertainty of the carbon content coefficient for jet fuels,
however, because naphtha-based jet fuel represents a small and declining share of total jet fuel consumption in the
United States.
A-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Distillate Fuel
Distillate fuel is a general classification for diesel fuels and fuel oils. Products known as No. 1, No. 2, and
No. 4 diesel fuel are used in on-highway diesel engines., such as those in trucks and automobiles, as well as off-
highway engines, such as those in railroad locomotives and agricultural machinery. No. 1, No. 2, and No. 4 fuel oils
are also used for space heating and electric power generation.
Methodology
For the purposes of this report, the carbon content of No. 2 fuel oil is assumed to typify the carbon content
of distillate fuel generally. The carbon share in No. 2 fuel oil was estimated based on the average of 11 ultimate
analyses. This carbon share was combined with ElA's standard heat content of S.82S MMBtu per barrel and the
density of distillate assumed to be 35.5 degrees API, in accord with its heat content.
Data Sources
Data on carbon contents and density were derived from four samples from C. T. Hare and R.L. Bradow
(1979). Samples were taken from the following sources: Funkenbush, et al. (1979), Mason (1981), and Black and
High (1979). . . .
A standard heat content was adopted from EIA (2005a).
Uncertainty
The primary source of uncertainty for the estimated carbon content of distillate fuel is the selection of No.2
fuel oil as the typical distillate fuel. No.2 fuel oil is generally consumed for home heating. No.l fuel oil is generally
less dense and if it is consumed in large, portions for mobile sources, the carbon content estimated for this report is
likely to be too high. The five No.l fuel oil samples obtained by EIA contained an average of 86.01 percent carbon
compared to the 86.34 percent contained, in samples of No.2 fuel oil. A carbon content coefficient based on No.l
fuel oil would equal 19.72 Tg/QBtu rather than the 19.95 Tg/QBtu for No. 2 fuel oil. There is also small uncertainty
in the share of carbon based on the limited sample size of ±1 percent.
Residual Fuel /
Residual fuel is a general classification for the heavier oils, known as No. 5 and No. 6 fuel oils, that remain
after the distillate fuel oils and lighter hydrocarbons are distilled away in refinery operations. Residual fuel
conforms to ASTM Specifications D 396 and D 975 and Federal Specification VV-F-8I5C. No. 5, a residual fuel
oil of medium viscosity, is also known as Navy Special and is defined in Military Specification MIL-F-859E,
including Amendment 2 (NATO Symbol F-770). It is used in steam-powered vessels in government service and
inshore power plants. No. 6 fuel oil includes Bunker C fuel oil and is used for the production of electric power,
space heating, vessel bunkering, and various industrial purposes.
In the United States, electric utilities purchase about a third of the residual oil consumed. A somewhat
larger share is used for vessel bunkering, and the balance is used in the commercial and industrial sectors. The
residual oil (defined as No.6 fuel oil) consumed by electric utilities has an energy content of 6.287 MMBtu per
barrel and an average sulfur content of I percent (EIA 2001). This implies a density of about 17 degrees API.
Methodology
For this report, residual fuel was defined as No.6 fuel oil. The National Institute of Petroleum and Energy
Research, Fuel Oil Survey shows an average density for fuel oil of 11.3 API gravity and anecdotal evidence suggests
that marine residual fuel is also very dense, with typical gravity of 10.5 to 11.5 degrees API (EIA 1993). Because
the largest share of fuel oil consumption is for marine vessels, a density of 11 degrees API was adopted when
developing the carbon content coefficient for this report.- An average share of carbon in residual fuel of 85.67
percent by mass was used based on ultimate analyses of a dozen samples.
Data Sources
Data on carbon content were derived from three samples of residual fuel from the Middle East and one
sample from Texas. These data were found in Mosby, et al. (1976). Three samples of heavy fuel oils were taken
from Longwell (1991); three samples from Ward (1978); two samples from Vorum (1974); and one sample from
Rose and Cooper (1977). Density of residual fuel consumed for electric power generation was obtained from EIA
A-53
-------
(2001). Density of residual fuel consumed in marine vessels was obtained from EIA (1992,1993). A standard heat
content was adopted from EIA (2005a).
Uncertainty
The largest source of uncertainty for estimating the carbon content of residual fuel centers on the estimates
of density, which differ from power generation to marine vessel fuels. The difference between the density implied
by the energy content of utility fuels and the density observed in the NIPER surveys is probably due tp nonsulfur
impurities, which reduce the energy content without greatly affecting the density of the product. Impurities of
several percent are commonly observed in residual oil. The presence of these impurities also affects the share of the
fuel that is carbon. Overall, the uncertainty associated with the carbon content of residual fuel is probably ±1
percent.
Liquefied Petroleum Gases (LPG)
EIA identifies four categories of paraffmic hydrocarbons as LPG: ethane, propane, isobutane, and n-butane.
Because each of these compounds is a pure paraffmic hydrocarbon, their carbon snares are easily derived by taking
into account the atomic weight of carbon (12) and the atomic weight of hydrogen (1). Thus, for example, the carbon
share of propane, C3H8, is 81.8 percent. The densities and heat content of the compounds are also well known
allowing carbon content coefficients to be calculated directly. Table A-38 summarizes the physical characteristic of
LPG.
Table A-3B: Physical Characteristics of Liquefied Petnieam Gases
Compound
Ethane
Propane
Isobutane
n-butane
Chemical Density (Barrels Carbon Content Energy Content Carbon Content
Formula Per Metric Ton) (Percent) (MMBtu/Barrel) Coefficient (Tg/QBtu)
CzHe
CaHs
C*HTO
C4Hio
16.88
12.44
11.20
10,79
80.0
81.8
82.8
82.8
2.916
3.824
4.162
4.328
1625
17.20
17.75
17.72
Source: Guttirie (1960).
Methodology
Step 1. Assign carbon content coefficients to each pure paraffmic compound
Based on their known physical characteristics, a carbon content coefficient is assigned to each compound
contained in the U.S. energy statistics category, Liquefied Petroleum Gases.
Step 2. Weight.individual LPG coefficients for share of fuel use consumption
A, carbon content coefficient for LPG used as fuel is developed based on the consumption mix of the
individual compound reported in U.S. energy statistics.
Step 3. Weight individual LPG coefficients for share of non-fuel use consumption
• The mix of LPG consumed for non-fuel use differs significantly from the mix of LPG that is combusted.
While the majority of LPG consumed for fuel use is propane, ethane is the largest component of LPG used for non-
fuel applications. A carbon content coefficient for LPG used for non-fuel applications is developed based on the
consumption mix of the individual compound reported in U.S. energy statistics.
Step 4. Weight the carbon content coefficients for fuel use and non-fuel use by their respective shares of
consumption
The changing shares of LPG fuel use and non-fuel use consumption appear below in Table A-39.
Data Sources
s
Data on carbon share, density, and heat content of LPG was obtained from Guthrie (1960). LPG
consumption was based on data obtained from API (1990-2005) and EIA (2005b). Non-fuel use of LPG was
obtained from API (1990 through 2005).
Uncertainty
A-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Because LPG consists of pure paraffinic compounds whose density, heat content and carbon share are
physical constants, there is limited uncertainty associated with the carbon content coefficient for this petroleum
product Any uncertainty is associated with the collection of consumption data and non-fuel data in U.S. energy
statistics. This uncertainty is probably less than ±3 percent.
A-55
-------
Table ft-39: Consumption and Carton Content Coefficients of Unaefled Petroleum Gases; 1990-2004
1990
Energy Consumption (QBtu)
Fuel Use 0.90
Ethane 0.03
Propane 0.79
Butane 0.08
Non-Fuel Use 1.20
Ethane 0.55
Propane 0.53
Butane 0.13
Carbon Content (Tg C/QBtu)
Fuel Use 17.21
Non-Fuel Use 16.83
1991
0.85
0.02
0.79
0.05
1.38
0.62
0.59
0.17
17.21
16.84
1992 .
0.94
0.03
0.84
0.07
1.39
0.62
0.61
0.16
17.21
16.84
1993
0.94
0.02
0.86
0.06
1.35
0.65
0.55
0.15
17.22
16.80
1994
0.96
0.02
0.86
0.07
1.55
0.65
0.65
0.25
17.22
16.88
1995
0.93
0.02
0.86
0.05
1,59
0.68
0.67
0.24
17.20
16.87
1996
1.02
0.03
0.95
0.04
1.65
0.74
0.65
0.26
17.20
16.86
1997
1.03
0.05
0.92
0.05
1.67
0,71
0,71
0.25
17.18
16.88
1998
0.84
0.00
0.80
0.04
1.74
0.73
0.77
0.24
17.23
16.88
1999
1.09
0.00
0.97
0.11
1.82
0.82
0.77
0.22
17.25
16.84
2000
1.29
0.08
1.08
0.14
1.67
0.80
0.66
0.21
17.20
16.81
2001
1.15
0.05
1.01
0.10
1.55
0.73
0.59
0.23
17.21
16.83
2002
1.24
0.05
1.10
0.09
1.62
0.77
0.65
0.21
17.20
16.82
2003
1.21
0.05
1.07
0.09
1.55
0.70
0.63
0.22
17.21
16.84
2004
1.25
0.05
1.13
0.07
1.58
0.74
0.66
0.17
17.20
16.81
Sources- Fuel use of LPG based on data from ElA (2005b) and API (1990 through 2005). Non-fuel use of LPG from API (1990 through 2005). Carbon contents from EIA (2005a).
A-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Aviation Gasoline ' ' ' '
Aviation gasoline is used in piston-powered airplane engines. It is a complex mixture of relatively volatile
hydrocarbons with or without small quantities of additives, blended to form a fuel suitable for use in aviation
reciprocating engines. Fuel specifications are provided in ASTM Specification D910 and Military Specification
MIL-G-5572. Aviation gas is a relatively minor contributor to greenhouse gas emissions compared to other
petroleum products, representing approximately 0.1 percent of all consumption.
The ASTM standards for boiling and freezing points in aviation gasoline effectively limit the aromatics
content to a maximum of 25 percent (ASTM D910). Because weight is critical in the operation of an airplane,
aviation gas must have as many Btu per pound (implying a lower density) as possible, given other requirements of
piston engines such as high anti-knock quality.
Methodology
A carbon content coefficient for aviation gasoline was calculated on the basis of the EIA standard heat
content of 5.048 MMBtu per barrel. This implies a density of approximately 69 degrees API gravity or 5.884
pounds per gallon. To estimate the share of carbon in the fuel, it was assumed that aviation gasoline is 87.5 percent
iso-octane, 9.0 percent toluene, and 3.5 percent xylene. The maximum allowable sulfur content in aviation gasoline
is 0.05 percent, and the maximum allowable lead content is 0.1 percent. These amounts were judged negligible and
excluded for the purposes of this analysis. This yielded a carbon share of 85 percent and a carbon content
coefficient of 18.87 Tg/QBtu.
Data sources include ASTM (1985). A standard heat content for aviation gas was adopted from EIA
(2005a).
Uncertainty
The uncertainty associated with the carbon content coefficient for aviation gasoline is larger than that for
other liquid petroleum products examined because no ultimate analyses of samples are available. Given the
requirements for safe operation of piston-powered aircraft the composition of aviation gas is well bounded and the
uncertainty of the carbon content coefficient is likely to be ±5 percent.
StillGas '
Still gas, or refinery gas is composed of light hydrocarbon gases that are released as petroleum is processed
in a refinery. The composition of still gas is highly variable, depending primarily on the nature of the refining
process and secondarily on the composition of the product being processed. Petroleum refineries produce still gas
from many different processes. Still gas can be used as a fuel or feedstock within the refinery, sold as a
petrochemical feedstock, or purified and sold as pipeline-quality natural gas. In general, still gas tends to include
large amounts of free hydrogen and methane, as well as smaller amounts of heavier hydrocarbons. Because
different refinery operations result in different gaseous byproducts, it is difficult to determine what represents typical
still gas.
Methodology
The EIA obtained data on four samples of still gas. Table A-40 below shows the composition of those
samples.
Tame A-40: Composition, Energy Content and Carton content Coofflclent lor Four Samples of Sdll Gas
Sample
One
Two
Three
Four
Hydrogen
12.7
." 34.7
72.0
17.0
Methane
(*)
28.1
20.5
12.8
31.0
Ethane
17.1
20.5
10.3
16.2
Propane Btu Per Cubic Carbon Content
<%) Foot (Tfl/QBtu)
11.9
6.7
3.8
2.4
1.388
1.143
• 672
1.100
17.51
14.33
10.23
15.99
A-57
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Because gas streams with a large free hydrogen content are likely to be used as refinery or chemical
feedstocks, EIA selected the carbon content coefficient from the sample with the lowest hydrogen content as the
representative value for still gas.
Data Sources
Data sources include one still gas sample from American Gas Association (1974) and three still gas
samples from Guerra, et al. (1979).
Uncertainty
Because the composition of still gas is highly heterogeneous, the carbon content coefficient for this product
is highly uncertain, with an accuracy of ±33 percent. The carbon content coefficient used for this report is probably
at the high end of the plausible range.
Asphalt
Asphalt is used to pave roads. Because most of its carbon is retained in those roads, it is a small source of
emissions. It is derived from a class of hydrocarbons called "asphaltenes," abundant in some crude oils but not in
others. Asphaltenes have oxygen and nitrogen atoms bound into their molecular structure, so that they tend to have
lower carbon contents than other hydrocarbons.
Methodology
Ultimate analyses of twelve samples of asphalts showed an average carbon content of 83.5 percent. The
EIA standard Btu content for asphalt of 6.636 MMBtu per barrel was assumed. The ASTM petroleum measurement
tables show a density of 5.6 degrees API or 8.605 pounds per gallon for asphalt. Together, these variables generate
carbon content coefficient of 20.62 Tg/QBtu.
Data Sources
A standard heat content.for asphalt was adopted from EIA (2005a). The density of asphalt was determined
by the ASTM (1985). v
Uncertainty
The share of carbon in asphalt ranges from 79 to 88 percent by weight. Also present in the mixture are
hydrogen and sulfur, with shares by weight ranging from seven to 13 percent for hydrogen, and from trace levels to
eight percent for sulfur. Because carbon share and total heat content in asphalts do vary systematically, the overall
carbon content coefficient is likely to be accurate to ±5 percent.
Lubricants
Lubricants are substances used to reduce friction between bearing surfaces, or incorporated into processing
materials used in the manufacture of other products, or used as carriers of other materials. Petroleum lubricants may
be produced either from distillates or residues. Lubricants include all grades of lubricating oils, from spindle oil to
cylinder oil to those used in greases. Lubricant consumption is dominated by motor oil for automobiles, but there is
a large range of product compositions and end uses within this category.
Methodology
The ASTM Petroleum Measurement tables give the density of lubricants at 25.6 degrees API. Ultimate
analysis of a single sample of motor oil yielded a carbon content of 85.8 percent. A standard heat content of 6.065
MMBtu per barrel was adopted from EIA. These factors produce a carbon content coefficient of 20.24 Tg/QBtu.
Data Sources
A standard heat content was adopted from the EIA (2005a). The density of asphalt was determined by
ASTM (1985).
Uncertainty
A-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Uncertainty in the estimated carbon content coefficient for lubricants is driven by the large range of product
compositions and end uses in this category combined with an inability to establish the shares of the various products
captured under this category in U.S. energy statistics. Because lubricants may be produced from either the distillate
or residual tractions during refineries, the possible carbon content coefficients range from just under 20.0 Tg/QBtu
to about 21.5 Tg/QBtu or an uncertainty band from -1 percent to + 6 percent of the estimated value.
Petrochemical Feedstocks
U.S. energy statistics distinguish between two different kinds of petrochemical feedstocks: those with a
boiling temperature below 400 degrees Fahrenheit, generally called "naphtha," and those with a boiling temperature
400 degrees Fahrenheit and above.
Methodology
The method for estimating the carbon content of petrochemical feedstocks includes three steps.
Step 1. Estimate the carbon content coefficient for naphtha
Because reformed naphtha is used to make motor gasoline (hydrogen is released to raise aromatics content
and octane rating), "straight-run" naphtha is assumed to be used as a petrochemical feedstock. Ultimate analyses of
five samples of naphtha were examined and showed an average carbon share of 84.11 percent and an average
density of 67.1 degrees API gravity. The standard EIA heat content of 5.248 MMBtu per barrel is used to estimate a
carbon content coefficient of 18.14 Tg/QBtu.
Step 2. Estimate the carbon content coefficient for petrochemical feedstocks with a boiling temperature 400
degrees Fahrenheit and above
The boiling temperature of this product places it into the "middle distillate" fraction in the refining process,
and EIA estimates that these petrochemical feedstocks have the same heat content as distillate fuel. Thus, the
carbon content coefficient of 19.95 Tg/Btu used for distillate fuel is also adopted for this portion of petrochemical
feedstocks.
Step 3. Weight the carbon content coefficients for the two classes of petrochemical feedstock by
consumption
The weighted average of the two carbon content coefficients for petroleum feedstocks equals 19.37 Tg/Btu.
Data Sources
Data on the carbon content and density of naphtha was taken from Unzelman (1992). A standard heat
content for petrochemical feedstock was adopted from EIA (2005a).
Uncertainty
Petrochemical feedstocks are not so much distinguished on the basis of chemical composition as on the
identity of the purchaser, who may be presumed to be a chemical company or a petrochemical unit co-located on the
refinery grounds. This produces a considerable degree of uncertainty about the exact composition of petrochemical
feedstocks. .Since the carbon content coefficient for petrochemical feedstocks is a weighted average of the
coefficients for naphtha and some class of middle distillates, the accurate coefficient is likely bounded by the two
individual coefficients, suggesting an uncertainty of ±6 percent.
Kerosene
A light petroleum distillate that is used in space heaters, cook stoves, and water heaters and is suitable for
use as a light source when burned in wick-fed lamps, kerosene is drawn from the same petroleum fraction as jet fuel.
Kerosene is generally comparable to No. 1 fuel oil. , . ,
Methodology
The average density of 41.4 degrees API and average carbon share of 86.01 percent found in five ultimate
analyses of No. 1 fuel oil samples were applied to a standard heat content of 5.670 MMBtu per barrel to yield a
carbon content coefficient of 19.72 Tg/Btu.
A-59
-------
Data Sources
A standard heat content was adopted from EIA (2005a).
Uncertainty
Uncertainty in the estimated carbon content for kerosene is driven by the selection of No. 1 fuel oil as a
proxy for kerosene. If kerosene is more like kerosene-based jet fuel, the true carbon content coefficient is likely to
be some 2 percent lower. If kerosene is more aptly compared to No. 2 fuel oil, then the true carbon content
coefficient is likely to be about 1 percent higher.
Pefroteum Cote
Petroleum coke is the solid residue by-product of the extensive processing of crude oil. It is a coal-like
solid, usually with a carbon content greater than 90 percent, that is used as a boiler fuel and industrial raw material.
Methodology
Ultimate analyses of two samples of petroleum coke showed an average carbon share of 92.3 percent. The
ASTM standard density of 9.S43 pounds per gallon was adopted and the EIA standard energy content of 6.024
MMBtu per barrel assumed. Together, these factors produced an estimated carbon content coefficient of 27.85
Tg/QBtu.
Data Sources
Carbon content was derived from two samples from Martin, S.W. (1960). The density of petroleum coke
was taken from the ASTM (1985). A standard heat content for petroleum coke was adopted from filA (2005a).
Uncertainty
The uncertainty associated with the estimated carbon content coefficient of petroleum coke can be traced to
two factors: the use of only two samples to establish carbon contents and a standard heat content which may be too
low. Together, these uncertainties are likely to bias the carbon content coefficient upwards by as much as 6 percent.
Special Naphtha
Special naphtha is defined as a light petroleum product to be used for solvent applications, including
commercial hexane and four classes of solvent: stoddard solvent, used in dry cleaning; high flash point solvent, used
as an industrial paint because of its slow evaporative characteristics; odorless solvent, most often used for residential
paints; and high solvency mineral spirits, used for architectural finishes. These products differ in both density and
carbon percentage, requiring the development of multiple coefficients.
Methodology
The method for estimating the carbon content coefficient of special naphtha includes three steps.
Step 1. Estimate the carbon content coefficient for hexane
Hexane is a pure paraffin containing 6 carbon atoms and 14 hydrogen atoms. Thus, it is 83.7 percent
carbon. Its density is 76.6 degrees API or 5.649 pounds per gallon and its derived carbon content coefficient is
17.17 Tg/QBtu.
Step 2 Estimate the carbon contents ofnon-hexane special naphthas
The hydrocarbon compounds in special naphthas are assumed to be either paraffmic or aromatic (see
discussion above). The portion of aromatics in odorless solvents is estimated at less than 1 percent, Stoddard and
high flash point solvents contain 15 percent aromatics and high solvency mineral spirits contain 30 percent
aromatics (Boldt and Hall 1977). These assumptions, when combined with the relevant densities, yield the carbon
content factors contained in Table A-41, below.
Table A-41: CharactertsrJes of Non-n exane Special Napnthas
~ Aromatic Content Density Carbon Content Carbon Content
Special Naphtha (Percent) (Degrees API) (Percent) (Tg«tu)
A-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Odorless Solvent
Stoddard Solvent
High Flash Point
Mineral Spirits
1
15
15
30
55,0
47.9
47.6
43,6
84.51
84.44
84,70
85.83
19.41
20.11
20.17
20.99
Step 3. Develop weighted carbon content coefficient based on consumption of each special naphtha
EIA reports only a single consumption figure for special naphtha. The carbon contents of the five special
naphthas are weighted according to the following formula: approximately 10 percent of all special naphtha
consumed is hexane; the remaining 90 percent is assumed to be distributed evenly among the four other solvents.
The resulting emissions coefficient for special naphthas is 19.86 Tg/QBtu.
Data Sources
A standard heat content for special naphtha was adopted from EIA (2005a). Density and aromatic contents
were adopted from Boldt and Hall (1977).
Uncertainty • •
The principal uncertainty associated with the estimated carbon content coefficient for special naphtha is the
allocation of overall consumption across individual solvents. The overall uncertainty is bounded on the low end by
the carbon content of hexane and on the upper end by the carbon content of high solvency mineral spirits. This
implies an uncertainty band of—15 percent to+6 percent.
Petroleum Waxes
The ASTM standards define petroleum wax as a product separated from petroleum that is solid or semi-
solid at 77 degrees Fahrenheit (25 degrees Celsius). The two classes of petroleum wax are paraffin waxes and
microcrystalline waxes. They differ in the number of carbon atoms and the type of hydrocarbon compounds.
Microcrystalline waxes have longer carbon chains and more variation in their chemical bonds than paraffin waxes..
Methodology
The method for estimating the carbon content coefficient for petroleum waxes includes three steps.
Step I. Estimate the carbon content of paraffin waxes
For the purposes of this analysis, paraffin waxes are assumed to be composed of 100 percent paraffinic
compounds with a chain of 25 carbon atoms. The resulting carbon share for paraffinic wax is 85.23 percent and the
density is estimated at 45 degrees AP! or 6.684 pounds per gallon.
Step 2. Estimate the carbon content of microcrystalline waxes
Microcrystalline waxes are assumed to consist of 50 percent paraffinic and 50 percent cycloparaffinic
compounds with, a chain of 40 carbon atoms, yielding a carbon share of 85.56 percent. The density of
microcrystalline waxes is estimated at 36.7 degrees API, based on a sample of 10 microcrystalline waxes found in
the Petroleum Products Handbook.
Step 3. Develop a carbon content coefficient for petroleum waxes by weighting the density and carbon
content of paraffinic and microcrystalline waxes ' . . .'•
A weighted average density and carbon content was calculated for petroleum waxes, assuming that wax
consumption is 80 percent paraffin wax and 20 percent microcrystalline wax. The weighted average carbon content
is 85.29 percent, and the weighted average density is 6.75 pounds per gallon. EIA's standard heat content for waxes
is 5.537 MMBtu per barrel. These inputs.yield a carbon content coefficient for petroleum waxes of 19.81 Tg/QBtu.
Data Sources • • •
Density of paraffin wax was taken from ASTM (1985). Density of microcrystalline waxes was derived
from 10 samples found in Guthrie (1960). A standard heat content for petroleum waxes was adopted from EIA
(2005a).
Uncertainty
A-61
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Although there is considerable qualitative uncertainty associated with the allocation of petroleum waxes
and microcrystalline waxes, the quantitative variation in the carbon contents for all waxes is limited to ± 1 percent
because of the nearly uniform relationship between carbon and other elements in petroleum waxes broadly defined.
Crude Oil, Unfinished Oils, and Miscellaneous
U.S. energy statistics include several categories of petroleum products designed to ensure that reported
refinery accounts "balance" and cover any "loopholes" in the taxonomy of petroleum products. These categories
include crude oil, unfinished oils, and miscellaneous products. Crude oil is rarely consumed directly, miscellaneous
products account for less than one percent of oil consumption and unfinished oils are a balancing item that may
show negative consumption. For carbon accounting purposes, it was assumed that all these products have the same
carbon content as crude oil.
Methodology
E1A reports on the average density and sulfur content of U.S. crude oil purchased by refineries. To develop
a method of estimating carbon content based on this information, ultimate analyses of 182 crude oil samples were
collected. Within the sample set, carbon content ranged from 82 to 88 percent carbon, but almost all samples fell
between 84 percent and 86 percent carbon. The density and sulfur content of the crude oil data were regressed on
the carbon content, producing the following equation:
Percent Carbon = 76.99 + (10.19 x Specific Gravity) + (-0.76 x Sulfur Content)
Absent the term representing sulfur content, the equation had an R-squared of only 0.35.' When carbon
content was adjusted to exclude sulfur, the R-squared value rose to 0.65. While sulfur is the most important
nonhydrocarbon impurity, nitrogen and oxygen can also be significant, but they do not seem to be correlated with
either density or sulfur content. Restating these results, density accounts for about 35 percent of the variation in
carbon content, impurities account for about 30 percent of the variation, and the remaining 35 percent is accounted
for by other factors, including (presumably) the degree to which aromatics and polynuclear aromatics are present in
the crude oil. Applying this equation to the 2001- crude oil quality data (30.49 degrees API and 1.42 percent sulfur)
produces an estimated-carbon content of 85.81 percent. Applying the density and carbon content to the EIA
standard energy content for crude oil of 5.800 MMBtu per barrel produced an emissions coefficient of 20.23
Tg/QBtu.
Data Sources
Carbon content was derived from 150 crude oil samples from U.S. National Research Council (1927). A
standard heat content for crude oil was adopted from EIA (2005a).
Uncertainty
The uncertainty of the estimated carbon content for crude oil centers on the 35 percent of variation that
cannot be explained by density and sulfur content. This variation is likely to alter the carbon content coefficient by
±3 percent. Since unfinished oils and miscellaneous products are impossible to define, the uncertainty of applying a
crude oil carbon content is likery to be bounded by the range of petroleum products described in this chapter at ±10
percent.
Chronology and Explanation of Changes in Individual Carbon Content Coefficients of Fossil Fuels
Coal
The estimates of carbon content coefficients for coal were updated and revised in 2005. The methodology
employed for these estimates was unchanged from previous years; however, the underlying coal data sample set was
updated. Previously -a set of 5,426 coal samples from the EIA Coal Analysis File was used to develop carbon
content estimates. The results from that sample set appear below in Table A-42. The EIA Coal Analysis File was
originally developed by the U.S. Bureau of Mines and contained over 60,000 coal samples obtained through
1 R-squared represents the percentage of variation in the dependent variable (in this case carbon content) explained by
variation in the independent variables.
A-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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numerous coal seams throughout the United States. Many of the samples were collected starting in the 1940s and
1950s through the 1980s and analyzed in U.S. government laboratories. The updated sample set included 6,588 coal
samples collected by the U.S. Geological Survey between 1973 and 1 989.
Petroleum Products
Between 1994 and 1995, the carbon content coefficient for kerosene-based jet fuel was revised downward
from 19.71 Tg/QBtu to 19.33 Tg/QBtu. This downward revision was the result of a shift in the sample set used
from one collected between 1959 and 1972 and reported on by Martel and Angello in 1977 to one collected by
Boeing in 1989 and published by Hadaller and Momenthy in 1990. The downward revision was a result of a
decrease in density, as well as slightly lower carbon shares than in the earlier samples. However, the assumed heat
content is unchanged because it is based on an EIA standard and probably yields a downward bias in the revised
carbon content coefficient.
Liquefied Petroleum Gases (LPG)
The carbon content coefficient of LPG is updated annually to reflect changes in the consumption mix of the
underlying compounds: ethane; propane; isobutane; and normal butane. In 1994, EIA included pentanes plus —
assumed to have the characteristics of hexane — in the mix of compounds broadly described as LPG. In 1995, EIA
removed pentanes plus from this fuel category. Because pentanes plus is relatively rich in carbon per unit of
energy, its removal from the consumption mix lowered the carbon content coefficient for LPG from 17.26 Tg/QBtu
to 17.02 Tg/QBtu. In 1998, EIA began separating LPG consumption into two categories: energy use and non-fuel
use and providing individual coefficients for each. Because LPG for fuel use typically contains higher proportions
of propane than LPG for non-fuel use, the carbon content coefficient for fuel use is about 2 percent higher than the
coefficient for non-fuel use.
Motor Gasoline
The carbon content coefficient for motor gasoline varies annually based on the density of and proportion of
additives in a representative sample of motor gasoline examined each year. However, in 1997 EIA began
incorporating the effects of the introduction of reformulated gasoline into its estimate of carbon content coefficients
for motor gasoline, This change resulted in a downward step function in carbon content coefficients for gasoline of
approximately 0.3 percent beginning in 1995.
A-63
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Tame flr4Z: Carton content Coefficients lor Coal tt Consuming Sector and Coal Rank, 1990-2004 irg/QBtn)
Consuming Sector
Electric Power
Industrial Coking
Other Industrial
Residential/Commercial
Coal Rank
Anthracite
Bituminous
Sub-bituminous
Lignite
1990
25.68
25.51
25.58
25.92
28.26
25.43
26.50
26.19
1991
25.69
25.51
25.60
26.00
28.26
25.45
26.49
26.21
1992
25.69
25.51
25.62
26.13
28.26
25.44
26.49
26.22
1993
25,71
25,51
25.61
25.97
28.26
25.45
26.48
26.21
1994
25.72
25.52
25.63
25.95
28.26
25.46
26.49
26.24
1995
25.74
25.53
25.63
26.00
28.26
25.47
26.49
26.22
1996
25.74
25.55
25.61
25.92
28.26
25.47
26.49
26.17
1997
25,76
25.56
25.63
26.00
28.26
25,48
26.49
26.20
1998
25.76
25.56
25.63
26.00
28.26
25.47
26.49
26.23
1999
25.76
25,56
25.63
26,00
28,26
25.48
26.49
26.26
2000
25.76
25.56
25.63
26.00
28.26
25.49
26.48
26.30
. 2001
25.76
25.56
25.63
26.00
28.26
25.49
26.48
26.30
2002
25.76
25.56
25.63
26.00
28.26
25,49
26.48
26.30
2003
25.76
25.56
25.63
26.00
28.26
25.49
26.48
26.30
2004
25.76
25.56
25.63
26.00
28.26 P
25.49 "
26.48 P
26.30"
o (Preliminary)
Sources: Carton content coefficients by consuming sector from EIA (2005a). Carbon content coefficients by coal rank from USGS (1998) and SAIC (2005).
A-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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References
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^ ASTM (1985) ASTMand Other Specifications for Petroleum Products and Lubricants, American Society
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Black, F, and L. High (1979) "Methodology for Determining Paniculate and Gaseous Diesel Emissions,"
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EIA (1993) Btu Tax on Finished Petroleum Products, Energy Information Administration, Petroleum
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EIA (1994) Emissions of Greenhouse Gases in the United States 1987-1992, Energy Information
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EIA (2001) Cost and Quality of Fuels for Electric Utility Plants 2000, Energy Information Administration.
• Washington, DC, August 2001. Available online at .
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Washington, DC.
EIA (2003) State Energy Data 2000: Consumption, Energy Information Administration, U.S. Department
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EIA (2005a) Monthly Energy Review, September 2005 and Unpublished Supplemental Tables on
Petroleum Product detaii.Table A4. Energy Information Administration, U.S. Department of Energy, Washington,
DC, DOE/EIA-0035(2005/09). s
EIA (2005b) Petroleum Supply Annual, Energy Information Administration, U.S. Department of Energy,
Washington, DC. Available online at •
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Funkenbush, E.F., D.G. Leddy, and J.H. Johnson (1979) "The Organization of the Soluble Organic Fraction
of Diesel Paniculate Matter," in Society of Automotive Engineers, The Measurement and Control of Diesel
Particulate Emissions, p. 128.
Gas Technology Institute (1992) Database as documented in W.E. Liss, W.H. Thrasher, G.F. Steinmetz, P.
Chowdiah, and A. Atari, Variability of Natural Gas Composition in Select Major Metropolitan Areas of the United
States. GR1-92/0123. March 1992. •
A-65
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Guerra, C.R., K. Kelton, and D.C. Nielsen (1979) "Natural Gas Supplementation with Refinery Gases and
Hydrogen," in Institute of Gas Technology, New Fuels and Advances in Combustion Technologies. Chicago, IL,
June 1979.
Guthrie, V.B. (ed.) (1960) Characteristics of Compounds, Petroleum Products Handbook, p.3-3. New
York, NY, McGraw-Hill.
Hadaller, O.J. and A.M. Momenthy (1990) The Characteristics of Future Fuels, Part 1, "Conventional Heat
Fuels". Seattle,.WA, Boeing Corp. September 1990. pp. 46-50.
Hare, C.T. and R.L. Bradow (1979) "Characterization of Heavy-Duty Diesel Gaseous and Paniculate
Emissions, and the Effects of Fuel Composition," in Society of Automotive Engineers, The Measurement and
Control of Diesel,? articulate Emissions, p. 128.
Hare, C.T., K.J. Springer, and R.L. Bradow (1979) "Fuel and Additive Effects on-Diesel Particulate-
Development and Demonstration of Methodology," in Society of Automotive Engineers, The Measurement and
Control of Diesel Paniculate Emissions, p. 179.
Hong, B.D. and E.R. Slatnick (1994) "Carbon Dioxide Emission Factors for Coal, "U.S. Energy
Information Administration, Quarterly Coal Report, January-March 1994. Washington, DC.
Hunt, J.M. (1979) Petroleum Geochemistry and Geology. San Francisco, CA. W.H. Freeman and
Company, pp. 31-37.
Longwell, J.P. (1991) "Interface Between Fuels and Combustion," in Fossil Fuel Combustion: A
Sourcebook, New York, NY, John Wiley & Sons.
Martel, C.R., and L.C. Angello (1977) "Hydrogen Content as a Measure of the Combustion Performance of
Hydrocarbon Fuels," in Current Research in Petroleum Fuels, Volume I. New York, NY, MSS Information
Company, p. 116.
Martin, S.W. (1960) "Petroleum Coke," in Virgil Guthrie (ed.), Petroleum Processing Handbook, New
York, NY, McGraw-Hill, pp. 14-15.
Mason, R.L. (1981) "Developing Prediction Equations for Fuels and Lubricants," SAE Paper 811218, p.34.
October 1981.
Mosby, F., G.B. Hoekstra, T.A. Kleinhenz, and J.M. Sokra (1976) "Pilot Plant Proves Resid Process," in
Chemistry of Petroleum Processing and Extraction, MSS Information Corporation, p.227.
National Institute for Petroleum and Energy Research (1990 through 2005) Motor Gasolines, Summer and
Motor Gasolines, Winter.
National Institute for Petroleum and Energy Research (1992) Fuel Oil Surveys, Bartlesville, OK.
Ringen, S., J. Lanum, and F.P. Miknis (1979) "Calculating Heating Values from the Elemental
Composition of Fossil Fuels," Fuel, Vol. 58, January 1979, p.69.
Rose, J.W. and J.R. Cooper (1977) Technical Data on Fuel, The British National Committee, World
Energy Conference, London, England.
SAIC (1992) "Analysis of the Relationship Between Heat and Carbon Content of U.S. Fuels: Final Task
Report," Science Applications International Corporation, prepared for the U.S. Energy Information Administration,
Office of Coal, Nuclear, Electric and Alternative Fuels. Washington, DC.
SAIC (2005) Analysis prepared by Science Applications International Corporation for EPA, Office of Air
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**-
U.S. National Research Council (1927) International Critical Tables of Numerical Data, Physics,
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Unzelman, G.H. (1992) "A Sticky Point for Refiners: FCC Gasoline and the Complex Model," Fuel
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USGS (1998) CoalQual Database Version 2 0, U.S. Geological Survey.
A-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Vorum, D.A. (1974) "Fuel and Synthesis Gases from Gaseous and Liquid Hydrocarbons," in American Gas
Association, Gas Engineer's Handbook, New York, NY, Industrial Press, p. 3/71.
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2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil
Fuels
Carbon storage associated with the non-energy use of fossil fuels was calculated by multiplying each fuel's
potential emissions (i.e., each fuel's total carbon content) by a fuel-specific storage factor, as listed in Table A-43.
This subannex explains the methods and data sources employed in developing the storage factors for petrochemical
feedstocks (industrial other coal, natural gas for non-fertilizer uses, LPG, pentanes plus, naphthas, other oils, still
gas, special naphtha), asphalt and road oil, lubricants, waxes, and miscellaneous products. The storage factors for
the remaining non-energy fuel uses are either based on values recommended for use by IPCC (1997), or when these
were not available, assumptions based on the potential fate of carbon in the respective NEU products. .
Table A-43: Fool Types end Percent of Carbon Stored lor N on-Enemy Uses
Sector/Fuel Type Storage Factor (%)
Industry - • "\
Industrial Coking Coal* 0.75
Industrial Other Coal" 0.62
Natural Gas to Chemical Plants11 0.62
Asphalt & Road Oil 1.00 ' • ' •
LPGb 0.62
Lubricants . , 0.09
Pentanes Plus" 0.62
Naphtha (<401deg.F)b ' 0.62 ,
Other Oil (>401deg.F)>- 0.62
Still Gasb 0.62
Petroleum Coke" 0.50
Special Naphtha11 . . 0.62
Distillate Fuel Oil , 0.50
-Waxes 0.58
Miscellaneous Products , 0.00
Transportation
Lubricants " 0.09
U.S. Territories
Lubricants ' ' 0.09
Other Petroleum (Misc. Prod.) m 0.10
-Not applicable
»Includes processes for which specific coking coal consumption and emission factor data are not available. Consumption of coking coal for production of iron
and steel is covered in the Industrial Processes chapter.
b The storage factor listed is the value for 2004. As described in this annex, the factor vanes over time.
* Includes processes for which specific petroleum cote consumption and emission factor data are not available (e.g., carbon fibers and textiles, refractory,
electric motor parts, brake parts, batteries). Consumption of petroleum coke for production of primary alummurn anodes, electric arc furnace anodes, titanium
dioxide, ammonia, urea, and ferroalloys is covered in the industrial Processes chapter.
The following sections describe the non-energy uses in greater detail, outlining the methods employed and
data used in estimating each storage factor. Several of the fuel types tracked by El A are used in organic chemical
synthesis and in other manufacturing processes, and are referred to collectively as "petrochemical feedstocks."
Because the methods and data used to analyze them overlap, they are handled as a group and are discussed first.
Discussions of the storage factors for asphalt and road oil, lubricants, waxes, and miscellaneous products follow.
A-69
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Petrochemical Feedstocks
Petrochemical feedstocks—industrial other coal, natural gas for non-fertilizer uses, LPG, pentanes plus,
naphthas, other oils, still gas, special naphtha—are used in the manufacture of a wide variety of man-made
chemicals and products. Plastics, rubber, synthetic fibers, solvents, paints, fertilizers, Pharmaceuticals, and food
additives are just a few of the derivatives of these fuel types. Chemically speaking, these fuels are diverse, ranging
from simple natural gas (i.e., predominantly CH4) to heavier, more complex naphthas and other oils.12
After adjustments for (1) use in industrial processes and (2) net exports, these eight fuel categories
constituted approximately 215.1 Tg CO2 Eq., or 53 percent, of the 403.6 Tg CO2 Eq. of non-energy fuel
consumption in 2004. For 2004 the storage factor for the eight fuel categories was 62 percent. In other words, of
the net consumption, 62 percent was destined for long-term storage in products—including products subsequently
combusted for waste disposal—while the remaining 38 percent was emitted to the atmosphere directly as CO2 (e.g.,
through combustion of industrial byproducts) or indirectly as CO2 precursors (e.g., through evaporative product
use). The indirect emissions include a variety of organic gases such as volatile organic compounds (VOCs) and
carbon monoxide (CO), which eventually oxidize into CO2 in the atmosphere. The derivation of the storage factor is
described in the following sections.
Methodology and Data Sources
The petrochemical feedstocks storage factor is equal to the ratio of carbon stored in the final products to
total carbon content for the non-energy fossil fuel feedstocks used in industrial processes, after adjusting for net
exports of feedstocks. One aggregate storage factor was calculated to represent all eight fuel feedstock types. The
feedstocks were grouped because of the overlap of their derivative products. Due to the many reaction pathways
involved in producing petrochemical products (or wastes), it becomes extraordinarily complex to link individual
products (or wastes) to their parent fuel feedstocks.
Import and export data for feedstocks were obtained from the Energy Information Administration (EIA) for
the major categories of petrochemical feedstocks. EIA's Petroleum Supply Annual (EIA, 2005) publication tracks
imports and exports of petrochemical feedstocks, including butanes, butylenes, ethane, ethylene, propane, propylene,
LPG, and naphthas (i.e., most of the large volume primary chemicals produced by petroleum refineries). These
imports and exports are already factored into the U.S. fuel consumption statistics. However, EIA does not track
imports and exports of chemical intermediates and products produced by the chemical industry (e.g., xylenes, vinyl
chloride), which are derived from the primary chemicals produced by the refineries. These products represent very
large flows of carbon derived from fossil fuels (i.e., fossil carbon), so estimates of net flows not already considered
in EIA's dataset were developed for the entire time series from 1990 to 2004.
The approach to estimate imports and exports involves three steps:
Step 1. Identify commodities derived from petrochemical feedstocks, and calculate net import/export for
each.
Step 2. Estimate the carbon content for each commodity.
Step 3. Sum the net carbon imports/exports across all commodities.
Step 1 relies heavily on information provided by the National Petrochemical and Refiners Association
(NPRA) and U.S. Bureau of the Census (BoC) trade statistics published by the U.S. International Trade Commission
(USITC). NPRA provided a spreadsheet of the ten-digit BoC Harmonized Tariff Schedule (HTS) Commodity
Codes used to compile import-export data for periodic reports issued to NPRA's membership on trade issues.
Additional feedstock commodities were identified by HTS code in the BoC data system and included in the net
import/export analysis.
One of the difficulties in analyzing trade data is that a large portion of the outputs from the refining
industry are fuels and fuel components, and it was difficult to segregate these from the outputs used for non-energy
uses. The NPRA-supplied codes identify fuels and fuel components, thus providing a sound basis for isolating net
12 Naphthas are compounds distilled from petroleum containing 4 to 12 carbon atoms per molecule and having a
boiling point less than 401° F. Other oils are distillates containing 12 to 25 carbon atoms per molecule and having a boiling point
greater than 401° F.
A-70 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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imports/exports of petrochemical feedstocks. Although MTBE and related ether imports are included in the
published NPRA data, these commodities are not included in the total net imports/exports calculated here, because it
is assumed that they are fuel additives and do not contribute to domestic petrochemical feedstocks. Net exports of
MTBE and related ethers are also not included in the totals, as these commodities are considered to be refinery
products that are already accounted for in the El A data. Imports and exports of commodities for which production
and consumption data are provided by EIA (e.g., butane, ethylene, and liquefied petroleum gases) are also not
included in the totals, to avoid double counting.
Another difficulty is that one must be careful to assure that there is not double-counting of imports and
exports in the data set. Other parts of the mass balance (described later) provide information on carbon flows, in
some cases based on production data and in other cases based on consumption data. Production data relates only to
production within the country; consumption data incorporates information on imports and exports as well as
production. Because many commodities are emissive in their use, but not necessarily their production, consumption
data is appropriately used in calculations for emissive fates. For purposes of developing an overall mass balance on
U.S. non-energy uses of carbon, for those materials that are non-emissive (e.g., plastics), production data is most
applicable. And for purposes of adjusting the mass balance to incorporate carbon flows associated with imports and
exports, it was necessary to carefully review whether the mass balance already incorporated cross-boundary flows
(through the use of consumption data) or not, and to adjust the import/export balance accordingly.
The BoC trade statistics are publicly available13 and cover a complete time series from 1990 to 2004. These
statistics include information on imports and exports of thousands of commodities. After collecting information on
annual flows of the more than 100 commodities identified by NPRA, Step 2 involves calculating the carbon content
for each commodity from its chemical formula. In cases where the imports and exports were expressed in units of
volume, rather than mass, they were converted to mass based on the commodities' densities.
Step 3 involves summing the net carbon imports/exports across all commodities. The results of this step
are shown in Table A-44. As shown in the table, the United States has been a net exporter of chemical intermediates
and products throughout the 1990 to 2004 period.
Table M4: Net Exports of Petrochemical Feedstocks, 1990 - 2004 ITB CO, EH)
1990 1991 1992 1993 1994 1995 1998 1997 1998 1999 2000 2001 2002 2003 2004
NetExports -12.0 -13.6 -12.9 -15.3 -12.9 -14.2 -11.7 -13.8 -9.0 -8.9 -8.7 -2.2 -7.5 -15.0 -20.4
After adjusting for imports and exports, the carbon budget is adjusted for the quantity of carbon that is used
in the industrial processes sector of the GHG inventory." Fossil fuels used for non-energy purposes in industrial
processes—and for which carbon emissions and storage have been characterized through mass balance calculations
and/or emission factors that directly link the non-energy use fossil fuel raw material and the industrial process
product—are not included in the non-energy use sector. These industrial processes (and their non-energy use fossil
fuel raw materials) include iron and steel (coal coke), primary aluminum (petroleum coke), titanium oxide
(petroleum coke), ferroalloys (petroleum coke), and ammonia and urea (petroleum coke and natural gas).
For each year in the Inventory, the total carbon content of non-energy uses was calculated by starting with
the EIA estimate of non-energy use, and reducing it by the adjustment factor for net exports (see Table A-44) to
yield net domestic fuel consumption for non-energy. The balance was apportioned to either stored carbon or
emissive carbon, based on a storage factor.
The overall storage factor for the feedstocks was determined by developing a mass balance on the carbon in
feedstocks, and characterizing products, uses, and environmental releases as resulting in either storage or emissions.
The total carbon in the system was estimated by multiplying net domestic consumption for non-energy by the carbon
content of each of the feedstocks (i.e., industrial other coal, natural gas for non-fertilizer uses, LPG, pentanes plus,
naphthas, other oils, still gas, special naphtha). Carbon content values for the fuel feedstocks are discussed in
Annexes 2.1 and 2.2.
Next, carbon pools and releases in a variety of industrial releases, energy recovery processes, and products
were characterized. The carbon fate categories are plastics, energy recovery, synthetic rubber, synthetic fibers,
organic solvents, carbon black, detergents and personal cleansers, industrial non-methane volatile organic compound
13 See the U.S International Trade Commission (USITC) Trade Dataweb at .
A-71
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(NMVOC) emissions, hazardous waste incineration, industrial toxic chemical (i.e., TRJ) releases, pesticides, food
additives, antifreeze and deicers (glycols), and silicones.14
The carbon in each product or waste produced was categorized as either stored or emitted. The aggregate
storage factor is the carbon-weighted average of storage across fuel types. As discussed later in the section on
uncertainty, the sum of stored carbon and emitted carbon (i.e., the outputs of the system) exceeded total carbon
consumption (the inputs to the system) for some years in the time series.15 To address this mass imbalance, the
storage factor was calculated as carbon storage divided by total carbon outputs (rather than carbon storage divided
by carbon inputs).
Note that the system boundaries for the storage factor do not encompass the entire life-cycle of fossil-based
carbon consumed in the United States insofar as emissions of CO? from waste combustion are accounted for
separately in the Inventory and are discussed in the Waste Combustion section of the Energy chapter.
The following sections provide details on the calculation steps, assumptions, and data sources employed in
estimating and classifying the carbon in each product and waste shown in Table A-45. Summing the carbon stored
and dividing it by total carbon outputs yields the overall storage factor, as shown in the following equation for 2004:
Overall Storage Factor = Carbon Stored / (Carbon Stored + Carbon Emitted) =
156.5 Tg CO2 Eq. / (156.5 + 94.0) Tg CO2 Eq. = 62 %
Tame MS: Carton stored and Emitted in Products mm feedstocks ID 2004 tfgCOiEiU
Product/Waste Type
Industrial Releases
TRI Releases
Industrial VOCs •
Non-combustion CO
Hazardous Waste Intin.
Energy Recovery
Products
Plastics
Synthetic Rubber
Abraded tire rubber
Synthetic Fiber
Pesticides
Soaps, shampoos, detergents
Food additives
Antifreeze and deicers
Silicones
Solvent VOCs -
Total
Carbon Stored Carbon Emitted
{Tg CO] Eq.) (Tg CO) Eq.)
0.4
0.4
-
-
-
'
156.0
133.2
11.5
.
10.6 '
0.3
1
-
-
0.5
-
156.S
5.2
1.0
2.0
0.9
1.4
71.2
17.6
.
-
0.7
-
0.2
5.6
0.9
1.3
-
8.8
94.0
-Not applicable
Note: Totals may not sum due to independent rounding.
The three categories of carbon accounted for in the table are industrial releases, energy recovery, and
products. Each is discussed below.
14 For the most part, the releases covered by the U.S. Toxic Release Inventory (TR1) represent air emissions or water
discharges associated with production facilities. Similarly, VOC emissions are generally associated with production facilities.
These emissions could have been accounted for as part of the Waste chapter, but because they are not necessarily associated with
waste management, they were included here. Toxic releases are not a "product" category, but they are referred to as such for ease
of discussion.
15 Overall, there was fairly close agreement between inputs and outputs; for the entire 1990 through 2004 time series,
outputs exceeded inputs by 0.2 percent. During the period 1990 through 1999, carbon inputs exceeded carbon outputs (i.e., the
sum of carbon stored and carbon emitted), and for those years, the assumption was made that the "missing" carbon was lost
through fates leading to emissions.
A-72 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Industrial Releases
Industrial releases include toxic chemicals reported through the Toxics Release Inventory, industrial
emissions of volatile organic compounds (VOCs), carbon monoxide emissions (other than those related to fuel
combustion), and emissions from hazardous waste incineration.
TRI Releases
' Fossil-derived carbon is found in many toxic substances released by industrial facilities. • The Toxics
Release Inventory (TRI), maintained by EPA, tracks these releases by chemical and environmental release medium
(i.e., land, air, or water) on a biennial basis (EPA 2000b). By examining the carbon contents and receiving media
for the top 35 toxic chemicals released, which account for 90 percent of the total mass of chemicals, the quantity of
carbon stored and emitted in the form of toxic releases can be estimated.
The TRI specifies releases by chemical, so carbon contents were assigned to each chemical based on
molecular formula. The TRI also classifies releases by disposal location as either off-site or on-site. The on-site
releases are further subdivided into air emissions, surface water discharges, underground injection, and releases to
land; the latter is further broken down to disposal in a RCRA Subtitle C (i.e., hazardous waste) landfill or to "Other
On-Site Land Disposal."16 The carbon released in each disposal location is provided in Table A-46,
Each on-site classification was assigned a storage factor. A one hundred percent storage factor was applied
to disposition of carbon to underground injection and to disposal to RCRA-permitted landfills, while the other
disposition categories were assumed to result in an ultimate fate of emission as C02 (i.e., a storage factor of zero
was applied to these categories.) The release allocation is not reported for off-site releases; therefore, the approach
was to develop a carbon-weighted average storage factor for the on-site carbon and apply it to the off-site releases.
For the remaining 10 percent of the TRI releases, the weights of all chemicals were added and an average
carbon content value, based upon the top 35 chemicals' carbon contents, was applied. The storage and emission
allocation for the remaining 10 percent of the TRI releases was carried out in the same fashion as for the 35 major
chemicals.
Data on TRI releases for the full 1990 through 2004 time series were not readily available. Since this
category is small (less than 1 MMTC emitted and stored), the 1998 value was applied for the entire time series.
Table W6:1998 TRI Releases by Disposal location (Go C0> EoJ
Disposal Location
Air Emissions
Surface Water Discharges
Underground Injection
RCRA Subtitle C Landfill Disposal
Other On-Site Land Releases
Off-site Releases
Total
Carbon Stored Carbon Emitted
(Gg CO: Eq.) {Gg COi Eq.)
89,4
1.4
6.4'
97.2
924.0
6.7
15.9
36.0
982.6
-Not applicable
Note: Totals may not sum due to independent rounding.
Volatile Organic Compound Emissions from Industrial Processes and Solvent Evaporation Emissions .
Data on annual non-methane volatile organic compound (NMVOC) emissions were obtained from National
Air Quality and Emissions Trends Report data (EPA 2005). The 1990-2004 Trends Report data include information
on NMVOC emissions by end-use category; some of these fall into the heading of''industrial releases" in Table A-
45 above, and others are related to "product use"; for ease of discussion, both are covered here. The end-use
categories that represent "Industrial NMVOC Emissions" include chemical and allied products, metals processing,
16 Only the top 9 chemicals had their land releases separated into RCRA Landfills and Other Land Disposal. For the
remaining chemicals, it was assumed that the ratio of disposal in these two categories was equal to the carbon-weighted average
of the land disposal fate of the top 9 chemicals (i.e., 8 percent attributed to RCRA Landfills and 92 percent in the "Other"
category).
A-73
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and other industrial processes. NMVOC emissions from solvent utilization (product use) were considered to be a
result of non-energy use of petrochemical feedstocks. These categories were used to distinguish non-energy uses
from energy uses; other categories where VOCs could be emitted due to combustion of fossil fuels were excluded to
avoid double counting.
Because solvent evaporation and industrial NMVOC emission data are provided in tons of total NMVOCs,
assumptions were made concerning the average carbon content of the NMVOCs for each category of emissions.
The assumptions for calculating the carbon fraction of industrial and solvent utilization emissions were made
separately and differ significantly. For industrial NMVOC emissions, a carbon content of 85 percent was assumed.
This value was chosen to reflect the carbon content of an average volatile organic compound based on the list of the
most abundant NMVOCs provided in the Trends Report The list contains only pure hydrocarbons, including
saturated alkanes (carbon contents ranging from 80 to 85 percent based upon carbon number), alkenes (carbon
contents approximately 85.7 percent), and some aromatics (carbon contents approximately 90 percent, depending
upon substitution).
t
An EPA solvent evaporation emissions dataset (Tooly 2001) was used to estimate the carbon content of
solvent emissions. The dataset identifies solvent emissions by compound or compound category for six different
solvent end-use categories: degreasing, graphic arts, dry cleaning, surface coating, other industrial processes, and
non-industrial processes. The percent carbon of each compound identified in the dataset was calculated based on the
molecular formula of the individual compound (e.g., the carbon content of methylene chloride is 14 percent; the
carbon content of toluene is 91 percent). For solvent emissions that are identified in the EPA dataset only by
chemical category (e.g., butanediol derivatives) a single individual compound was selected to represent each
category, and the carbon content of the category was estimated based on the carbon content of the representative
compound.1 The overall carbon content of the solvent evaporation emissions for 1998, estimated to-be 56 percent, is
assumed to be constant across the entire time series.
The results of the industrial and solvent NMVOC emissions analysis are provided in Table A-47 for 1990
through 2004. Solvent evaporation emissions in 2004 were 8.8 Tg CO2 Eq., and industrial NMVOC emissions in
2004 were 2.0 Tg COj Eq. In 2004, NMVOC and solvent activity data were revised across the entire time series to
reflect updated information from the 2004 National Air Quality and Emissions Trends Report.
A-74 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Table Ml: Indnnrtal and Sohrent NMVOC Emissions
1990 1991 199T 1993 1994~ 1995 1996 ^1997 1998 1999^ 2000 2001 2002 2003 2004
Industrial NMVOCs-
NMVOCs ('000 Short Tons)
Carbon Content (%)
Carbon Emitted fTgCOzEq.)
1,157
85%
3.3
1,224
85%
3.5
1,254
85%
3.5
1.267
85%
3.6
1,254
85%
3.5
1,235
85%
3.5
896
85%
2.5
904
85%
2.6
915
85%
2.6
755
85%
2.1
775
85%
2.2
753
85%
2.1
689
85%
1.9
690
85%
2.0
691
85%
2.0
Solvent Evaporation11 .
Solvents ('000 Short Tons) 5,750 5,782 5,901 6,016 6,162 6,183 5,477 5,622 5,149 5,037 4,832 5,012 4,692 4,698 4,704
Carbon Content (%) 56% -56% 56% 56% 56% 56% 56% 56% 56% 56% 56% 56% 56% "56% 56%
Carton Emitted (To. CO* Eg.) 10.8 10.B 11.0 11.3 11.5 11.6 10.3 105 9.6 9.4 9.0 9.4 8.8 8.8 8.8
* Includes emissions from chemical and allied products, petroleum and related industries, and other industrial processes categories.
11 Includes solvent usage and solvent evaporation emissions from decreasing, graphic arts, dry cleaning, surface coating, other industrial processes, and non-industrial processes.
A-75
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Non-Combustion Carbon Monoxide Emissions
Carbon monoxide (CO) emissions data were also obtained from the 2004 National Air Quality and
Emissions Trends Report (EPA 2005). There are three categories of CO emissions in the report that are classified as
process-related emissions not related to fuel combustion. These include chemical and allied products
manufacturing, metals processing, and other industrial processes. Some of these CO emissions are accounted for in
the Industrial Processes section of this report, and are therefore not accounted for in this section. These include total
carbon emissions from the primary aluminum, titanium dioxide, iron and steel, and ferroalloys production processes.
The total carbon (CO and CO2) emissions from oil and gas production, petroleum refining, and asphalt
manufacturing are also accounted for elsewhere in this Inventory. Sustainably harvested biogenic emissions (e.g.,
pulp and paper process emissions) are also excluded from calculation of CO emissions in this section. Those CO
emissions that are not accounted for elsewhere are considered to be byproducts of non-fuel use of feedstocks and are
included in the calculation of the petrochemical feedstocks storage factor. Table A-48 lists the CO emissions that
remain after taking into account the exclusions listed above. \
Table *48: Non-Combustion Carton Monoxide Emissions'
Year
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
CO Emitted
(Thousand Short Tons)
489
441
454
486
481
481
552
570
567
605
623
650
633
633
633
Carbon Emitted
(TgCOzEq.)
0.7
0.6
0.6
0.7
0.7
0.7
0.8
0.8
0.8
0.9
0.9
0.9
0.9
0.9
0.9
1 Includes emissions from chemical and allied products, petroleum and related industries, metals processing, and ottier industrial processes categories.
Hazardous Waste incineration
Hazardous wastes are defined by the EPA under the Resource Conservation and Recovery Act (RCRA).17
Industrial wastes, such as rejected products, spent reagents, reaction by-products, and sludges from wastewater or air
pollution control, are federally regulated as hazardous wastes if they are found to be ignitable, corrosive, reactive, or
toxic according to standardized tests or studies conducted by the EPA.
Hazardous wastes must be treated prior to disposal according to the federal regulations established under
the authority of RCRA. Combustion is one of the most common techniques for hazardous waste treatment,
particularly for those wastes that are primarily organic in composition or contain primarily organic contaminants.
Generally speaking, combustion devices fall into two categories: incinerators that burn waste solely for the purpose
of waste management, and boilers and industrial furnaces (BIFs) that bum waste in part to recover energy from the
waste. More than half of the hazardous waste combusted in the U.S. is burned in BIFs; these processes are included
in the energy recovery calculations described below.
EPA's Office of Solid Waste requires biennial reporting of hazardous waste management activities, and
these reports provide estimates of the amount of hazardous waste burned for incineration or energy recovery. EPA
stores this information in its Biennial Reporting System (BRS) database (EPA 2000a, 2004). Combusted hazardous
wastes are identified based on EPA-defmed management system types M041 through M049 (incineration).
Combusted quantities are grouped into four representative waste form categories based on the form codes reported
in the BRS: aqueous liquids, organic liquids and sludges, organic solids, and inorganic solids. To relate hazardous
17 [42 U.S.C. §6924, SDWA §3004]
A-76 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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waste quantities to carbon emissions, "fuel equivalent" factors were derived for hazardous waste by assuming that
the hazardous wastes are simple mixtures of a common fuel, water, and noncombustible ash. For liquids and
sludges, crude oil is used as the fuel equivalent and coal is used to represent solids.
Fuel equivalent factors were multiplied by the tons of waste incinerated to obtain the tons of fuel
equivalent. Multiplying the tons of fuel equivalent by the carbon content factors (discussed in Annex 2.2} yields
tons of carbon emitted. Implied carbon content is calculated by dividing the tons of carbon emitted by the
associated tons of waste incinerated.
Waste quantity data for hazardous wastes were obtained from EPA's BRS database for reporting years
1989,1991, 1993, 1995, 1997, 1999, and 2001 (EPA 2000a, 2004). Values for years after 2001 were held constant
at the 2001 level. Combusted waste quantities were obtained from Form CM (Generation and Management) for
wastes bumed on site and Form WR (Wastes Received) for waste received from off-site for combustion. For each
of the waste types, assumptions were developed on average waste composition (see Table A-49). Regulations
require incinerators to achieve at least 99.99 percent destruction of organics; this formed the basis for assuming the
fraction of carbon oxidized. Emissions from hazardous waste incineration in 2001 were 1.4 Tg CO2Eq. Table A-50
lists the CO2 emissions from hazardous waste incineration.
Table M9: Assumed Composition ol Combusted Hazardous waste by Walnut Percent)
Waste Type Water Noncombustibles Fuel Equivalent (%)
(%) [%}
Aqueous Waste 90 5 5
Otganic Liquids and Sludges ,40 20 40 ' '
Oiganic Solids 20 40 40 .
Inorganic Solids 20 . 70 10 .
Table 0-50: C0> Emitted from Hazardous Waste incineration erg CO, EqJ
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004'
CCkEmissions 1.1 1.1 1,1 1.2 1.5 1.7 1.7 1.8 1.6 ,1.4 1.4 1.4 1.4 1.4 1.4
Energy Recovery
The amount of feedstocks combusted for energy recovery was estimated from data included in EIA's
Manufacturers Energy Consumption Survey (MECS) for 1991, 1994, 1998, and 2002 (ElA 1994, 1997, 200 Ib,
2004). Some fraction of the fossil carbon exiting refineries and designated for use for feedstock purposes actually
ends up being combusted for energy recovery (despite the designation of feedstocks as a "non-energy" use) because
the chemical reactions in which fuel feedstocks are used are not 100 percent efficient These chemical reactions
may generate unreacted raw material feedstocks or generate byproducts that have a high energy content. The
chemical industry and many downstream industries are energy-intensive and often have boilers or other energy
recovery units on-site, and thus these unreacted feedstocks or byproducts are often combusted for energy recovery.
Also, as noted above in the section on hazardous waste incineration, regulations provide a strong incentive—and in
some cases require—burning of organic wastes generated from chemical production processes.
Information available from the MECS include data on the consumption for energy recovery of "other" fuels
in the petroleum and coal products, chemicals, primary metals, nonmetallic minerals, and other manufacturing
sectors. These "other" fuels include refinery still gas; waste gas; waste oils, tars, and related materials; petroleum
coke, coke oven and blast furnace gases; and other uncharacterized fuels. Fuel use of petroleum coke is included
separately in the fuel use data provided annually by EIA, and energy recovery of coke oven gas and blast furnace
gas (i.e., byproducts of the iron and steel production process) is addressed in the Iron and Steel production section in
the Industrial Processes chapter. Consumption of refinery still gas in the refinery sector is also included separately
in the fuel use data from EIA. Consumption of net steam, assumed to be generated from fossil fuel combustion, is
also included separately in the fuel use data from EIA. Therefore these categories of "other" fuels are addressed
elsewhere in the Inventory and not considered as part of the petrochemical feedstocks energy recovery analysis. The
remaining categories of fuels, including waste gas; waste oils, tars, and related materials; and other uncharacterized
fuels are assumed to be petrochemical feedstocks burned for energy recovery (see Table A-51). The conversion
factors listed in Annex 2.1 were used to convert the Btu values for each fuel feedstock to Tg CO2. Petrochemical
feedstocks combusted for energy recovery corresponded to 42.2 Tg COj Eq. in 1991, 35.4 Tg CO2 Eq. in 1994, 58.1
Tg CO2 Eq. in 1998, and 71.2 Tg CO2 in 2002. Values for petrochemical feedstocks burned for energy recovery for
A-77
-------
years between 1991 and 1994, between 1994 and 1998, and between 1998 and 2002 have been estimated by
interpolation. The value for 1990 is assumed to be the same as the value for 1991, and values for years subsequent
to 2002 are assumed to be the same as the value for 2002 (Table A-52).
Table 0-51: Summary of 2002 MEGS Data far Otter Fuels Used In Mamnacturlno/Ehennr Recovery (Trillion Btul
Subsector and Industry
NAICS CODE
Waste Gas*
Waste Refinery Still
Other
Oils/Tars"
Gasc Net Steam" Fuels*
Printing and Related Support
Petroleum and Coal Products
Chemicals
Plastics and Rubber Products
Nonmetallic Mineral Products
Primary Metals
Fabricated Metal Products
Machinery ,
Computer and Electronic Products
Electrical Equip., Appliances, Components
Transportation Equipment
Furniture and Related Products
Miscellaneous
Total (Trillion Btu)
Average Carbon Content (Tg/QBtu)
Fraction Oxidized
Total Carbon (Tg) ,
Total Carbon (Tg) (ex. still gas from refining)
323
324
325
326
327
331
332
333
334
335
336
337
339
0
0
483
0
0
1
0
o .
0
0
1
0
, 0
485
18.14
099
8.71
8.71
0
2
10
0
0
1
0
0
, .0
0
0
8
0
21
20.62
0.99
0.43
0.43
0
1396
0
0
0
0
0
0
0
0
0
0
0
1396
17.51
0.99
24.20
0.00
0
89
261
4
0 '
• 31-
0
2
1
1
7
1
1
397
0
0
1
67
394
1
43
•4
2
2
1
0
18
2
1
536
19.37
0.99
10.27
10.27
• Carbon content: Waste Gas is assumed to be same as naphtha <4Q1 cleg. F
b Carbon content: Waste Oils/Tare is assumed to be same as asphaitfroad oil
c Refinery 'still gas* fuel consumption is reported elsewhere in the Inventory and is excluded from the total carbon content estimate
" Net steam fuel consumption ts reported elsewhere in the Inventory and is excluded from the total carbon content estimate
• Carbon content: 'Other* is assumed to be the same as petrochemical feedstocks
Tahlo A-Sfe Carbon Emitted tram Fuels Darned for Energy Recovery (To CO? la J
1990 1991 1992 1993 1994 1995 1996 1997 1998 J999 2000 2001 2002 2003 2004~
Cimissions 42,2 42.2 40.0 37.7 35.4 41.1 46,8 52.4 58.1 61.4 64.6 67.9 71,2 71.2 71.2
Products
More carbon is found in products than in industrial releases or energy recovery. The principal types of
products are plastics; synthetic rubber; synthetic fiber; carbon black; pesticides; soaps, detergents, and cleansers;
food additives; antifreeze and deicers (glycols); silicones; and solvents. Solvent evaporation was discussed
previously along with industrial releases of NMVOCs; the other product types are discussed below.
P/asffcs
Data on.annual production of plastics were taken from the American Plastics Council (AFC), as published
in Chemical & Engineering News and on the APC and Society of Plastics Industry (SP1) websites, and through
direct communication with the APC (APC 2000, 2001, 2003, 2004, 2005; SPI 2000; Eldredge-Roebuck 2000).
These data were organized by resin type (see Table A-S3) and by year. Several of the resin categories included
production from Canada and/or Mexico, in addition to the U.S. values for part of the time series. The data for the
affected resins and years were corrected using an economic adjustment factor, based on the percent of North
American production value in this industry sector accounted for by the United States. A carbon content was then
assigned for each resin. These contents were based on molecular formulas and are listed in Table A-54 and Table
A-55. In cases where the resin type is generic, referring to a group of chemicals and not a single polymer (e.g.,
phenolic resins, other styrenic resins), a representative compound was.chosen. For engineering resins and other
resins, a weighted carbon content of 68 percent was assumed (i.e., it was assumed that these resins had the same
content as those for which a representative compound could be assigned).
A-78 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990*2004
-------
There were no emissive uses of plastics identified, so 100 percent of the carbon was considered stored in.
products. However, an estimate of emissions related to the combustion of these plastics in the municipal solid waste
stream can be found in the Waste Combustion section of the Energy chapter.
Table A-53:2004 Plasdc Resta Production (Tg dry wolgfttl and Carton Stored (To eo> Eoj
2004 Production1 Carbon Stored
Resin Type {Tg dry weight) (Tg COz Eq.)
Epoxy
Urea
Melamine
Phenolic
Low-Density Polyethylene (LDPE)
Linear Low-Density Polyethylene (LLDPE)
High Density Polyethylene (HOPE) ,.
Polypropylene (PP)
Acrylonitrile-butadiene-styrene (ABS)
Styrene-acrylonitrile(SAN)'
Other Styrenics
Polystyrene (PS)
Nyton
Poryvinyl chloride (PVC)* '
Thermoplastic Polyester
Engineering Resins
All Other (including Polyester (unsaturated))
Total
0.29
0.71
0.71
1.98
. 3.54 .
5.31
7.50 '
7.93 ,
0.56
0.06
0.72
2.88
0.55
6.83
3.41
1.16
5.22
49.35
0.8
0.9
0.8
5.6
• 11.1
16.7
?3.6
24.9
1.8
0.2
2.4
9.8
1.3
9.6
7.8
2.9
13.1
133.2
> Originally included production from Canada for Urea, Melamine, LDPE, LLDPE, HDPE, PP, ABS, SAN, Phenolic, Other Styrenics, PS, Nylon, PVC,
Thermoplastic Polyester, and Engineering Resins, and' production from Mexico for ABS, SAN, Other Styrenics, Nyton, and Thermoplastic Polyester. Values have
been adjusted to account just for U.S. production.
i Includes copolymers
Note: Totals may not sum due to independent rounding.
Table n-54: Assigned Carbon contents of Ha
r% by weight)
Resin Type
Carbon •
Content Source of Carbon Content Assumption
Epoxy
Polyester (Unsaturated)
Urea
Melamine
Phenolic
Low-Density Polyethylene (LDPE)
Linear Low-Density Polyethylene (LLDPE)
High Density Polyethylene (HDPE)
Polypropylene (PP)
Acryionitrile-Butadiene-Styrene (ABS)
Styrene-Acrylonitrile (SAN)
Other Styrenics
Polystyrene (PS)
Nylon
PolyvinylChtoride(PVC)
Thermoplastic Polyester
Engineering Resins
All Other
76% Typical epoxy resin made from epichlorhydrin and bisphenol A
63% Poly (elhylene terephthalate) (PET)
34% 50%carbamal,50%N-(hydroxymetrryl)urea*
29% Trimethylol melamine *
77% Phenol
86% Polyethylene
86% Polyethylene
86% Polyethylene
86% Polypropylene
85% 50% styrene, 25% acrylonitrile, 25% butadiene
80% 50% styrene, 50% acrylonitrile
92% Polystyrene
92% Polystyrene
65% Average of nylon resins (see Table A-55)
38% Polyvinyl chloride
63% Polyethylene terephthalate
68% Weighted average of other resin production
68% Weighted average of other resin production
•Does not include alcoholic hydrogens.
Table A-55: Major Nylon Resins and their Carbon Contents t%ttv weight)
A-79
-------
Resin Carbon Content
Nylon 6 64%
Nylon 6,6 64%
Nylon 4 52%
Nylon 6,10 . 68%
Nylon 6,11 69%
Nylon 6,12 t 70%
Nylon 11 72%
Synthetic Rubber
Data on synthetic rubber in tires were derived from data on the scrap tire market and the composition of
scrap tires from the Rubber Manufacturers' Association's (RMA) Scrap Tire Management Council (STMC). The
market information is presented in the report U.S. Scrap Tire Markets 2003 (RMA 2004), while the tire composition
information is from the "Scrap Tires, Facts and Figures" section of the organization's website (STMC 2003). No
data were available for 2004, so tire consumption for 2004 was assumed to equal 2003 consumption. Data on
synthetic rubber in other products (durable goods, nondurable goods, and containers and packaging) were obtained
from EPA's Municipal Solid Waste in the United States reports (1996, 1997, 1998, 1999, 2000, 2001, 2002,2003,
and 2005). The abraded rubber from scrap passenger tires was assumed to be 5 Ibs per scrap tire while the abraded
rubber from scrap truck tires was assumed to be 20 Ibs per scrap tire. Data on abraded rubber weight were obtained
by calculating the average weight difference between new and scrap tires (STMC 2003).
A carbon content for synthetic rubber (90 percent for tire synthetic rubber and 85 percent for non-tire
synthetic rubber) was assigned based on the weighted average of carbon contents (based on molecular formula) by
elastomer type consumed in 1998, 2000, and 2001 (see Table A-56). The 1998 consumption data were obtained
from the International Institute of Synthetic Rubber Producers (1ISRP) press release "Synthetic Rubber Use Growth
to Continue Through 2004, Says I1SRP and RMA" {I1SRP 2000). The 2001 and 2002 consumption data were
obtained from the IISRP press release ""IISRP Forecasts Moderate Growth in North America to 2007" (IISRP
2003).
The rubber in tires that is abraded during use (the difference between new tire and scrap tire rubber weight)
was considered to be 100 percent emitted. Other than abraded rubber, there were no emissive uses of scrap tire and
non-tire rubber identified, so 100 percent of the non-abraded amount was assumed stored. Emissions related to the
combustion of rubber in scrap tires and consumer goods can be found in the Waste Combustion section of the
Energy chapter,
Table A-56:2002 Rubber Consumption (fig) and Carbon Content (%]
Elastomer Type
SBR Solid
Polybutadiene
Ethylene Propylene
Polychloroprene
NBR Solid
Polyisoprene
Others
Weighted Average
Total
2002 Consumption
(Gg)*
768
583
301
•54
84
58
367
.
2,215
Carbon
Content
91%
89%
86%
59%
77%
88%
88%
90%
-
'Includesconsumption in Canada.
-Not applicable
Note: Totals may not sum due to independent rounding.
Synthetic Fibers
Annual synthetic fiber production data were obtained from the Fiber Economics Bureau, as published in
Chemical & Engineering News (2001, 2003, and 2005). These data are organized by year and fiber type. For each
fiber, a carbon content was assigned based on molecular formula (see Table A-57). For polyester, the carbon
content for polyethylene terephthalate) (PET) was used as a representative compound. For nylon, the average
carbon content of nylon 6 and nylon 6,6 was used, since these are the most widely produced nylon fibers. Cellulosic
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fibers, such as acetate and rayon, have been omitted from the synthetic fibers' carbon accounting because much of
their carbon is of biogenic origin. These fibers account for only 4 percent of overall fiber production by weight.
There were no emissive uses of fibers identified, so 100 percent of the carbon was considered stored. Note
that emissions related to the combustion of textiles in municipal solid waste are accounted for under the Waste
Combustion section of the Energy chapter.
Table ft-57: 2004* Fiber production erg), Carton content (%), and Carton stored tig co> Eqj
~ Fiber Type
Polyester
Nylon
Olefin
Acrylic
Total
Production (Tg)
1.5
1.1
1.4
0.1
4.1
Carbon Content
63%
64%
86%
68%
'-
Carbon Stored •
(TgCOjEq.)
3.33
2.67.
4.31
0.27
10.59
Note: Totals may not sum due to independent rounding
Pesfic/'ctes /•
Pesticide consumption data were obtained from the 1994/1995, 1996/1997. and 1998/1999 Pesticides
Industry Sales and Usage Market Estimates (EPA 1998b, 1999b, 2002c) reports. The most recent data available
were for 1999, so it was assumed that the 2000 through 2003 consumption was equal to that of 1999. Active
ingredient compound names and consumption weights were available for the top 25 agriculturally-used pesticides
and top 10 pesticides used in the home and garden and the industry/commercial/govemment categories. The report
provides a range of consumption for each active ingredient; the midpoint was used to represent actual consumption.
Each of these compounds was assigned a carbon content value based on molecular formula. If the compound
contained aromatic rings substituted with chlorine or other halogens, then the compound was considered persistent
and the carbon in the compound was assumed to be stored. All other pesticides were assumed to release their carbon
to the atmosphere. Over one-third of 1999 total pesticide active ingredient consumption was not specified by
chemical type in the Sales and Usage report (EPA 2002c). This unspecified portion of the active 'ingredient
consumption was treated as a single chemical and assigned a carbon content and a storage factor based on the
weighted average of the known chemicals' values.
Table n-58: Acdra ingredient Consumption In Pesticides [Million insJ and Carbon Emitted end Stored (Tg C0> Enj
Pesticide Use*
Agricultural Uses •
Non-Agricultural Uses"
Home & Garden
Industry/GcH/t/Commercial
Other
Total
. Active Ingredient
(Million Ibs.)
475.0
80.5
33.5
47.0
356.5
912.0
Carbon Emitted (Tg
COjEq.)
0.1
0.1
0.2
Carbon Stored
(TgCOzEq.)
0.2
0.1
0.3
+ Less than 0.05 Tg COi Eq.
'1999 estimates (EPA 2CC2c).
Note-Totals may not sum due to independent rounding.
Soaps, Shampoos, and Detergents
Cleansers—soaps, shampoos, and detergents—are among the major consumer products that may contain
fossil carbon. All of the carbon in cleansers was assumed to be fossil-derived, and, as cleansers eventually
biodegrade, all of the carbon was assumed to be emitted. The first step in estimating carbon flows was to
characterize the "ingredients" in a sample of cleansers. For this analysis, cleansers were limited to the following
personal household cleaning products: bar soap, shampoo, laundry detergent (liquid and granular), dishwasher
detergent, and dishwashing liquid. Data on the annual consumption of household personal cleansers were obtained
from the U.S. Census Bureau 1992,1997 and 2002 Economic Census. Consumption values for 1990 and 1991 were
assumed to be the same as the 1992 value; consumption was interpolated between 1992 and 1997 and between 1997
and 2002; consumption for 2003 and 2004 was assumed to equal the 2002 value.
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Chemical formulae were used to determine carbon contents (as percentages) of the ingredients in the
cleansers. Each product's overall carbon content was then derived from the composition and contents of its
ingredients. From these values the mean carbon content for cleansers was calculated to be 21.9 percent.
The Census Bureau presents consumption data in terms of quantity (in units of million gallons or million
pounds) and/or terms of value (thousands of dollars) for eight specific categories, such as "household liquid laundry
detergents, heavy duty" and "household dry alkaline automatic dishwashing detergents." Additionally, the report
provides dollar values for the total consumption of "soaps, detergents, etc.—dry" and "soaps, detergents, etc.—
liquid." The categories for which both quantity and value data are available is a subset of total production. Those
categories that presented both quantity and value data were used to derive pounds per dollar and gallons per dollar
conversion rates, and they were extrapolated (based on the Census Bureau estimate of total value) to estimate the
total quantity of dry and liquid18 cleanser categories, respectively.
Next, the total tonnage of cleansers was calculated (wet and dry combined). Multiplying the mean carbon
content (21.9 percent) by this value yielded an estimate of 4.9 Tg CO2 Eq. in cleansers for 1997. For 1992 and 2002
the estimates are 3.9 Tg CO2 Eq. and 5.6 Tg CO2 Eq. Estimates for other years are based on these values as
described above, and are shown in Table A-59.
Table A-59: Carton Emitted from UrJitzaflon of soaps. Shampoos, and Detergents (To CO, EoJ
.1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
C Emissions 3.9 3.9 3.9 4.1 4.3 4.5 4.7 4.9 4.9 4.7 4.8 5.2 5.6 5.6 5.6
Antifreeze and Deicers
Glyc'ol compounds, including ethylene glycol, propylene glycol, diethylene glycol, and triethylene glycol,
are used as antifreeze in motor vehicles, deicing fluids for commercial aircraft, and other similar uses. These glycol
compounds are assumed to ultimately enter wastewater treatment plants where they are degraded by the wastewater
treatment process to CO2 or to otherwise biodegrade to COZ. Glycols are water soluble and degrade rapidly in the
environment (Howard 1993). \
Annual production data for each glycol compound used as antifreeze and deicers were obtained from the
Guide to the Business of Chemistry, 2003 (American Chemistry Council 2004). Import and export data were used
to adjust annual production data to annual consumption data. The percentage of the annual consumption of each
glycol compound used for antifreeze and deicing applications was estimated from Chemical Profiles data published
on The Innovation Group website and from similar data published in the Chemical Market Reporter.
The consumption of glycol compounds in antifreeze and deicing applications is assumed to be 100 percent
emitted as C02. Emissions of COZ from utilization of antifreeze and deicers are summarized in Table A-60.
Table A-60: Carton Emitted from DUIIzadon of flmtfreeze and Deicers (Tg CO, EuJ
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
CEmisslons 1.1 1.1 1.1 1.2 1.2 1.2 1.3 1.3 1.3 1.3 1.3 1.1 1.2 1.2 1.3
Food Additives
Petrochemical feedstocks are used to manufacture synthetic food additives, including preservatives,
flavoring agents, and processing agents. These compounds include glycerin, propylene glycol, benzole acid, and
other compounds. These compounds are incorporated into food products, and are assumed to ultimately enter
wastewater treatment plants where they are degraded by the wastewater treatment processes to CO2 or to otherwise
biodegrade to CO2. Certain food additives, e.g., glycerin, are manufactured both from petrochemical feedstocks and
from •biogenic feedstocks. Food additives that are derived from biogenic feedstocks are not considered in this
analysis.
Annual production data for food additive compounds were obtained from the Guide to the Business of
Chemistry, 2003 (American Chemistry Council 2004). Import and export data 'were used to adjust annual
production data to annual consumption data. The percentage of the annual consumption of food additive compounds
18 A density of 1.05 g/mL—slightly denser than water—was assumed for liquid cleansers.
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was estimated from Chemical Profiles data published on The Innovation Group website . The consumption of synthetic food additives is assumed to be 100 percent
emitted as CO2. Emissions of CO2 from utilization of synthetic food additives are summarized in Table A-62.
Table A-61: Carton Emitted from ouiizauon of Food Additives (To CO, EoJ
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
Emissions 0.6 0.6 0.6 0,7 0.7 0.7 0.7 0.7 0.7 0.8 0.9 0.8 0.9 0.9 0.9
Silicones
Silicone compounds (e.g., polymethyl siloxane) are used as sealants and in manufactured products.
Silicone compounds are manufactured from petrochemical feedstocks including methyl chloride. It is assumed that
petrochemical feedstocks used to manufacture silicones are incorporated into the silicone products and not emitted
as CO2 in the manufacturing process. It is also assumed that the carbon contained in the silicone products is stored,
and not emitted as CO2.
Annual production data for each silicone manufacturing compound were obtained from the Guide to the
Business of Chemistry, 2003 (American Chemistry Council, 2004). Import and export data were used to adjust
annual production data to annual consumption data. The percentage of the annual consumption of each silicone
manufacturing compound was estimated from Chemical Profiles data published on The Innovation Group website
. The consumption of silicone manufacturing compounds is
assumed to be 100 percent stored, and not emitted as CO2. Storage of silicone manufacturing compounds is
summarized in Table A-62.
Tattle A-62: Carton stored hi Silicone Products (Tg CO, EoJ
1990 1991 1992 1993 1994 "1995. 1996 1997 1998 19$9~2000 2001 2002 2003 2004
C Storage 0.3 0.3 0.3 JK 0.4 0.4 0.4 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.5
Uncertainty
A Tier 2 Monte Carlo analysis was performed using @R]SK software to determine the level of uncertainty
surrounding the estimates of the feedstocks carbon storage factor and the quantity of carbon emitted from feedstocks
in 2004. The Tier 2 analysis was performed to allow the specification of probability density functions for key
variables, within a computational structure that mirrors the calculation of the Inventory estimate. Statistical analyses
or expert judgments of uncertainty were not available directly from the information sources for the activity
variables; thus, uncertainty estimates were determined using assumptions based on source category knowledge.
Uncertainty estimates, for production data (the majority of the variables) were assumed to exhibit a normal
distribution with a relative error of ±20 percent in the underlying El A estimates, plus an additional ±15 percent to
account for uncertainty in the assignment of imports and exports. An additional 10 percent (for a total of ±45
percent) was appliedjo the production of other oils (>401 deg. F) to reflect the additional uncertainty in the
assignment of part of the production quantity to industrial processes. A relatively narrow uniform distribution ±1
percent to ±10 percent, depending on the fuel type) was applied to each carbon coefficient
The Monte Carlo analysis produced a storage factor distribution that approximates a normal curve around a
mean of 62.2 percent, with a standard deviation of 1 percent and 95 percent confidence limits of 60 percent and 64
percent. This compares to the calculated estimate, used in the Inventory, of 65 percent. The analysis produced a
carbon emission distribution approximating a normal curve with a mean of SO.O Tg CO2 Eq., standard deviation of
2.2 Tg CO2 Eq., and 95 percent confidence limits of 64.8 and 95.9 Tg CC^ Eq. This compares with a calculated
estimate of 80.5 Tg CO2 Eq. The uncertainty emission distribution does not currently capture additional emissions
from industrial other coal, which constitutes less than 0.5 Tg CO2 to the overall estimate of feedstocks emissions;
improvements to include other industrial coal in the uncertainty analysis will be made in future Inventories.
The apparently tight confidence limits for the storage factor and. carbon storage probably understate
uncertainty, as a result of the way this initial analysis was structured. As discussed above, 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
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around all 17 of these fate processes, the current analysis addresses only the storage fates, and assumes that all
carbon that is not stored is emitted. As the production statistics that drive the storage factors are relatively well-
characterized, this approach yields a result that is probably biased toward understating uncertainty.
As far as specific sources of uncertainty, there are several cross-cutting factors that pervade the
characterization of carbon flows for feedstocks. The aggregate storage factor for petrochemical feedstocks
(industrial other coal, natural gas for non-fertilizer uses, LPG, pentanes plus, naphthas, other oils, still gas, special
naphtha) is based on assuming that the ultimate fates of all of these fuel types —in terms of storage and emissions—
are similar. In addition, there are uncertainties associated with the simplifying assumptions made for each end use
category carbon estimate! Generally, the estimate for a product is subject to one or both of the following
uncertainties:
• The value used for estimating the carbon content has been assumed or assigned based upon a representative.
compound.
• The split between carbon storage and emission has been assumed based on an examination of the
environmental fate of the products in each end use category.
• Environmental fates leading to emissions are assumed to operate rapidly, i.e., emissions are assumed to
1 occur within one year of when the fossil carbon enters the non-energy mass balance. Some of the pathways
that lead to emissions as CO2 may take actually place on a time-scale of several years or decades. By
attributing the emissions to the year in which the carbon enters the mass balance (i.e., the year in which it
leaves refineries as a non-energy fuel use and thus starts being tracked by EIA), this approach has the effect
of "front-end loading" the emission profile.
Another cross-cutting source of uncertainty is that for several sources the amount of carbon stored or
emitted was calculated based on data for only a single year. This specific year may not be representative of storage
for the entire Inventory period. Sources of uncertainty associated with specific elements of the analysis are
discussed below.
Import and export data for petrochemical feedstocks were obtained from EIA, the National Petroleum
Refiners Association, and the U.S. BoC for the major categories of petrochemical feedstocks (EIA 2001a, NPRA
2001, and U.S. BoC 2005). The complexity of the organic chemical industry, with multiple feedstocks,
intermediates, and subtle differences in nomenclature, makes it difficult to ensure that the adjustments to the EIA
data for imports and exports is accurate and the approach used here may underestimate or overestimate net exports
of carbon.
Oxidation factors have been applied to non-energy uses of petrochemical feedstocks in the same manner as
for energy uses. However, this "oxidation factor" may be inherent in the storage factor applied when calculating
emissions from non-energy consumption, which would result in a double-counting of the unoxidized carbon.
Oxidation factors are small corrections, on the order of 1 percent, and therefore application of oxidation factors to
non-energy uses may result in a slight underestimation of carbon emissions from non-energy uses.
The major uncertainty in using the TRI data are the possibility of double counting of emissions that are
already accounted for in the NMVOC data (see above) and in the storage and emission assumptions used. The -
approach for predicting environmental fate simplifies some complex processes, and the balance between storage and -\
emissions is very sensitive to the assumptions on fate. Extrapolating from known to unknown characteristics also
introduces uncertainty. The two extrapolations with the greatest uncertainty are: 1) that the release media and fate of
the off-site releases were assumed to be the same as for on-site releases, and 2) that the carbon content of the least
frequent 10 percent of TRI releases was assumed to be the same as for the chemicals comprising 90 percent of the
releases. However, the contribution of these chemicals to the overall estimate is small. The off-site releases only
account for 3 percent of the total releases, by weight, and, by definition, the less frequent compounds only account
for 10 percent of the total releases.
The principal sources of uncertainty in estimating CO2 emissions from solvent evaporation and industry are
in the estimates of total NMVOC emissions and in the application of factors for the carbon content of these
emissions.- Solvent evaporation and industrial NMVOC emissions reported by EPA are based on a number of data
sources and emission factors, and may underestimate or overestimate emissions. The carbon content for solvent
evaporation emissions is calculated directly from the specific solvent compounds identified by EPA as being
emitted, and is thought to have relatively low uncertainty. The carbon content for industrial emissions has more
A-84 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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uncertainty, however, as it is calculated from the average carbon content of an average volatile organic compound
based'on the list of the most abundant measured NMVOCs provided in EPA (2002a).
Uncertainty in the hazardous waste combustion analysis is introduced by the assumptions t about the
composition of combusted hazardous wastes, including the characterization that hazardous wastes are similar to
mixtures of water, noncombustibles, and fuel equivalent materials. Another limitation is the assumption that all of
the carbon that enters hazardous waste combustion is emitted—some small fraction is likely to be sequestered in
combustion ash—but given that the destruction and removal efficiency for hazardous organics is required to meet or
exceed 99.99 percent, this is. a very minor source of uncertainty. Carbon emission estimates from hazardous waste
should be considered central value estimates that are likely to.be accurate to within ±50 percent.
•The amount of feedstocks combusted for energy recovery was estimated from data included in the
Manufacturers Energy Consumption Surveys (MECS) for 1991, 1994, 1998, and 2002 (EIA 1994, 1997, 2001b,
2004). MECS is a comprehensive survey that is conducted every four years and intended to represent U.S. industry
as a whole, but because EIA does not receive data from all manufacturers (i.e., it is a sample rather than a census),
EIA must extrapolate from the sample. Also, the "other" fuels are identified in the MECS data in broad categories,
including refinery still gas; waste gas; waste oils, tars, and related materials; petroleum coke,'coke oven and blast
furnace gases; and other uncharacterized fuels. Moreover, the industries using these "other" fuels are also identified
only in broad categories, including the petroleum and coal products, chemicals, primary metals, nonmetallic
minerals, and other manufacturing sectors. The "other" fuel consumption data are reported in BTUs (energy units)
and there is uncertainty concerning the selection of a specific conversion factor for each broad "other" fuel category
to convert energy units to mass units. Taken as a whole, the estimate of energy recovery emissions'probably
introduces more uncertainty than any other element of the non-energy analysis.
Uncertainty in the carbon storage estimate for plastics arises primarily from three factors. First, the raw
data on production for several resins include Canadian and/or Mexican production and may overestimate the amount
of plastic produced from U.S. fuel feedstocks; this analysis includes adjustments to "back out" the Canadian and
Mexican values, but these adjustments are approximate. Second, the assumed carbon content values are estimates
for representative compounds, and thus do not account for the many formulations of resins available. This
uncertainty is greater for resin categories that are generic (e.g., phenolics, other styrenics, nylon) than for resins with
more specific formulations (e.g., polypropylene, polyethylene). Lastly, the assumption that all of the carbon
contained in plastics is stored ignores certain end uses (e.g., adhesives and coatings) where the resin may be released
to the atmosphere; however, these end uses are likely to be small relative to use in plastics.
The quantity of carbon stored in synthetic rubber only accounts for the carbon stored in scrap tire synthetic
rubber. The value does not take into account the rubber stored in other durable goods, clothing, footwear, and other
non-durable goods, or containers and packaging. -This adds uncertainty to the total mass balance of carbon stored.
There are also uncertainties as to the assignment of carbon content values; however, they are much smaller than in
the case of plastics. There are probably fewer variations in rubber formulations than in plastics, and the range of
potential carbon content values is much narrower. Lastly, assuming that all of the carbon contained in rubber is
stored ignores the possibility of volatilization or degradation during product lifetimes. However, the proportion of
the total carbon that is released to the atmosphere during use is probably negligible.
•A small degree of uncertainty arises from the assignment of carbon content values; however, the magnitude
of this uncertainty is less than that for plastics or rubber. Although there is considerable variation in final textile
products, the stock fiber formulations are standardized and proscribed explicitly by the Federal Trade Commission.
For pesticides, the largest source of uncertainty involves the assumption that an active ingredient's carbon
is either 0 percent stored or 100 percent stored. This split is a generalization of chemical behavior, based upon
active-ingredient molecular structure, and not on compound-specific environmental data. The mechanism by which
a compound is bound or released from soils is very complicated and can be affected by many variables, including
the type of crop, temperature, application method, and harvesting practice. Another smaller source of uncertainty
arises from the carbon content values applied to the unaccounted for portion of active ingredient, Carbon contents
vary widely among pesticides, from 7 to 72 percent, and the remaining pesticides may have a chemical make-up that
is very different from the 32 pesticides that have been examined. Additionally, pesticide consumption data were
only available for 1987, 1993,1995, 1997, and 1999; the majority of the time series data were interpolated or held
constant at the latest (1999) value. Another source of uncertainty is that only the "active" ingredients of pesticides
are considered in the calculations; the "inactive" ingredients may also be derived from petrochemical feedstocks.
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It is important to note that development of this uncertainty analysis is a multi-year process. The current
feedstocks analysis examines NEU fuels that end in storage fates .Thus only carbon stored in pesticides,- plastics,
synthetic fibers, synthetic rubbers, silicones, and TRI releases to underground injection and Subtitle C landfills is
accounted for in the uncertainty estimate above. In the future this analysis will be expanded to include the
uncertainty surrounding emitted fates in addition to the storage fates. Estimates of variable uncertainty will also be
refined where possible to include fewer assumptions. With these"-major changes in future Inventories, the
uncertainty estimate is expected to change, and likely increase. An increase in the uncertainty estimate in the
coming years will not indicate that the Inventory calculations have become less certain, but rather that the methods
for estimating uncertainty have become more comprehensive; thus, potential future changes in the results of this
analysis will reflect a change in the uncertainty analysis, not a change in the Inventory quality.
Asphalt and Road Oil
Asphalt is one of the principal non-energy uses of fossil fuels. The term "asphalt" generally refers to a
mixture of asphalt cement and a rock material aggregate, a volatile petroleum distillate, or water. For the purposes
of this analysis, "asphalt" is used interchangeably with asphalt cement, a residue of crude oil. According to EPA
(2000e), approximately 100 Tg CO2 Eq. has been used in the production of asphalt cement annually. Though minor
amounts of carbon are emitted during production, asphalt has an overall carbon storage factor of almost 100 percent,
as discussed below.
Paving is the primary application of asphalt cement, comprising 86 percent of production. The three types
of asphalt paving produced in the United States are hot mix asphalt (HMA), cut-backs, and emulsified asphalt.
HMA, which makes up 90 percent of total asphalt paving (EPA 2000c), contains asphalt cement mixed with an
aggregate of rock materials. Cut-back asphalt is composed of asphalt cement thinned with a volatile petroleum
distillate (e.g., naphtha). Emulsified asphalt contains only asphalt cement and water. Roofing products are the other
significant end use of asphalt cement, accounting for approximately 14 percent of U.S. production (Kelly 2000). No
data were available on the fate of carbon in asphalt roofing; it was assumed that it has the same fate as carbon in
asphalt paving applications.
Methodology and Data Sources
A carbon storage factor was calculated for each type of asphalt paving. The fraction of carbon emitted by
each asphalt type was multiplied by consumption data for asphalt paving (EPA 2000c, EIIP 1998) to come up with a
weighted average carbon storage factor for asphalt as a whole.
The fraction of carbon emitted by HMA was determined by first calculating the organic emissions (volatile
organic compounds [VOCs], carbon monoxide, polycyclic aromatic hydrocarbons [PAHs], hazardous air pollutants
[HAPs], and phenol) from HMA paving, using emission factors reported in EPA (2000e) and total HMA
production.19 The next step was to estimate the carbon content of the organic emissions. This calculation was
based on the carbon content of carbon monoxide (CO) and phenol, and an assumption of 85 percent carbon content
for PAHs and HAPs. The carbon content of asphalt paving is a function of (1) the proportion of asphalt cement in
asphalt paving, assumed to be 5 percent asphalt cement content based on personal communication with an expert
from the National Asphalt Paving Association (Connolly 2000), and (2) the proportion of carbon in asphalt cement.
For the latter factor, all paving types were characterized as having a mass fraction of 85 percent carbon in asphalt
cement, based on the assumption that asphalt is primarily composed of saturated paraffin ic hydrocarbons. By
combining these estimates, the result is that over 99.99 percent of the carbon in asphalt cement was retained (i.e.,
stored), and less than 0.01 percent was emitted.
Cut-back asphalt is produced in three forms (i.e., rapid, medium and slow cure). All three forms emit
carbon only from the volatile petroleum distillate used to thin the asphalt cement (EPA 1995). Because the
petroleum distillates are not included in the EIA fuel use statistics for asphalt, the storage factor for cut-back is
assumed to be 100 percent.
It was also assumed that there was no loss of carbon from emulsified asphalt (i.e., the storage factor is 100
percent) based on personal communication with an expert from Akzo Nobel Coatings, Inc. (James 2000).
'^ The emission factors are expressed as a function of asphalt paving tonnage (i.e., including the rock aggregate as well
as the asphalt cement).
A-86 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Data on asphalt and road oil consumption and carbon content factors were supplied by EIA. Hot mix
asphalt production and emissions factors were obtained from "Hot Mix Asphalt Plants Emissions Assessment
Report" from EPA's AP-42 (EPA 2000e) publication. The asphalt cement content, of HMA was provided by Una •
Connolly of National Asphalt Paving Association (Connolly 2000). The .consumption data for cut-back and
emulsified asphalts were taken from a Moulthrop, et al. study used as guidance for estimating air pollutant emissions
from paving processes (E1IP 1998). "Asphalt Paving Operation" AP-42 (EPA 1995) provided the emissions source
information used in the calculation of the carbon storage factor for cut-back asphalt. The storage factor for
emulsified asphalt was provided by Alan James of Akzo Nobel Coatings, Inc. (James 2000).
Uncertainty
A Tier 2 Monte Carlo analysis was performed using @RISK. software to determine the level of uncertainty
surrounding the estimates of the asphalt carbon'storage factor and the quantity of carbon stored in asphalt in 2004.
The Tier 2 analysis was performed to allow the specification of probability density functions for key variables,
within a computational structure that mirrors the calculation of the Inventory estimate. Statistical analyses or expert
judgments of uncertainty were not available directly from the information sources for the activity variables; thus,
uncertainty estimates were determined using assumptions based on source category knowledge. Uncertainty
estimates for asphalt production were assumed to be ±20 percent, while the asphalt property variables were assumed
to have narrower distributions. A narrow uniform distribution, with maximum 5 percent uncertainty around the
mean, was applied to the carbon content coefficient.
The Monte Carlo analysis, given a 95 percent confidence interval, produced a storage factor distribution
that approximates a normal curve skewed to the right, around a mean of 99.4 percent, with a standard deviation of
0.2 percent and boundaries between 99.0 and 99.7 percent. This compares to the storage factor value used in the
Inventory of 100 percent. The analysis produced an emission distribution, skewed to the left, with an uncertainty
range slightly below 100 percent. The emission uncertainty range is not applicable since the Inventory calculation
estimates that zero carbon is emitted from asphalts and road oil.
' i
The principal source of uncertainty is that the available data are from short-term studies of emissions
associated with the production and application of asphalt. As a practical matter, the cement in asphalt deteriorates
over time, contributing to the need for periodic re-paving. Whether this deterioration is due to physical erosion of
the cement and continued storage of carbon in a refractory form or physicochemtcal degradation and eventual
release of CO2 is uncertain. Long-term studies may reveal higher lifetime emissions rates associated with
degradation.
Many of the values used in the analysis are also uncertain and are based on estimates and professional
judgment. For example, the asphalt cement input for hot mix asphalt was based on expert advice indicating that the
range is variable—from about 3 to 5 percent—with actual content based on climate and geographical factors
(Connolly 2000). Over this range, the effect on the calculated carbon storage factor is minimal (on the order of 0.1
percent). Similarly, changes in the assumed carbon content of asphalt cement would have only a minor effect.
The consumption figures for cut-back and emulsified asphalts are based on information reported'for 1994.
More recent trends indicate a, decrease in cut-back use due to high VOC emission levels and a related increase in
emulsified asphalt use as a substitute. However, because the carbon storage factor of each is 100 percent, use of
more recent data would not affect the overall result.
Future improvements to this uncertainty analysis, and to the overall estimation of a storage factor for
asphalt, include characterizing the long-term fate of asphalt.
Lubricants
' Lubricants are used in industrial and transportation applications. They can be subdivided into oils and
greases, which differ in terms of physical characteristics (e.g., viscosity), commercial applications, and
environmental fate. According to EIA (2005), the carbon content from U.S. production of lubricants in 2004 was
approximately 6.4 Tg C. Based on apportioning oils and greases to various environmental fates, and characterizing
those fates as resulting in either long-term storage or emissions, the overall carbon storage factor was estimated to be
9 percent; thus, emissions in 2004 were about 5.7 Tg C, or 20.9 Tg CO2 Eq.
•A-87
-------
Methodology and Data Sources
For each lubricant category, a storage factor was derived by identifying disposal fates and applying
assumptions as to the disposition of the carbon for each practice. An overall lubricant carbon storage factor was
calculated by taking a production-weighted average of the oil and grease storage factors.
0//s
Regulation of used oil in the United States has changed dramatically over the past 20 years.20 The effect
of these regulations and policies has been to restrict landfilling and dumping, and to encourage collection of used
oil. Given the relatively inexpensive price of crude oil, the economics have not favored re-refining—instead, most
of the used oil that has been collected has been combusted.
Table A-63 provides an estimated allocation of the fates of lubricant oils (Rinehart 2000), along with an
estimate of the proportion of carbon stored in each fate. The ultimate fate of the majority of oils (about 84 percent)
is combustion, either during initial use or after collection as used oil. Combustion results in 99 percent oxidation to
CO2 (EHP 1999), with correspondingly little long-term storage of carbon in the form of ash. Dumping onto the
ground or into storm sewers, primarily by "do-it-yourselfers" who change their own oil, is another fate that results in
conversion to CO2 given that the releases are generally small and most of the oil is biodegraded (based on the
observation that land farming—application to soil—is one of the most frequently used methods for degrading
refinery wastes). In the landfill environment, which tends to be anaerobic within municipal landfills, it is assumed
that 90 percent of the oil persists in an underrated form, based on analogy with the persistence of petroleum in native
petroleum-bearing strata, which are both anaerobic. Re-refining adds a recycling loop to the fate of oil. Re-refined
oil was assumed to have a storage factor equal to the weighted average for the other fates (i.e., after re-refining, the
oil would have the same probability of combustion, landfilling, or dumping as virgin oil), i.e., it was assumed that
'about 97 percent of the carbon in re-refined oil is ultimately oxidized. Because of the dominance of fates that result
in eventual release as CO2, only about 3 percent of the carbon in oil lubricants goes into long-term storage.
Table A-63: Commercial and Environmental Fata of Oil Lubricant! [Percent]
Fate of Oil
Portion of Total Oil
Carbon Stored
Combusted During Use
.NotCombusted During Use
Combusted as Used Oil*
Dumped on the ground or in storm sewers
Landfilled
Re-refined into lube oil base stock and other products
20
80
64
6
2
1
1
0
90
3
Weighted Average
2.9
*(e.g., in boilers or space heaters)
-Not applicable
Greases
Table A-64 provides analogous estimates for lubricant greases. Unlike oils, grease is generally not
combusted during use, and combustion for energy recovery and re-refining is thought to be negligible. Although
little is known about the fate of waste grease, it was assumed that 90' percent of the non-combusted portion is
landfilled, and the remainder is dumped onto the ground or storm sewers. Because much of the waste grease will be
in containers that render it relatively inaccessible to biodegradation, and because greases contain longer chain
paraffins, which are more persistent than oils, it was assumed that 90 percent and SO percent of the carbon in
landfilled and dumped grease, respectively, would be stored. The overall storage factor is 82 percent for grease.
Tablo A-64: Commercial and Environmental Fate af Greasa Lubricants (Percent]
20 For example, the U.S. EPA "RCRA (Resource Conservation and Recovery Act) On-line" web site
() has over 50 entries on used oil regulation and policy for 1994 through 2000.
A-88 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Fate of Grease
Combusted During Use
Not Combusted During Use
Landfilled
Dumped on Hie ground or in storm sewers
Weighted Average
• Total Grease
5
95
85.5
'9.5
-
Carbon Stored
1
90
• 50
81.8
-Not applicable
Having derived separate storage factors for oil and grease, the last step was to estimate the weighted
average for lubricants as a whole. No data were found apportioning the mass of lubricants into these two categories,
but the U.S. Census Bureau (1999) does maintain records of the value of production of'lubricating oils and
lubricating greases. Assuming that the mass of lubricants can be allocated according to the proportion of value of
production (92 percent oil, 8 percent grease), applying these weights to the storage factors for oils and greases (3
percent and 82 percent) yields an overall storage factor of 9 percent.
Uncertainty
A Tier 2 Monte Carlo analysis was performed using @RISK software to determine the level of uncertainty
surrounding the estimates of the lubricants weighted average carbon storage factor and the quantity of carbon
emitted from lubricants in 2004. The Tier 2 analysis was performed to allow die specification of probability density
functions for key variables, within a computational structure that mirrors the calculation of the Inventory estimate.
Statistical analyses or expert judgments of uncertainty were not available directly from the information sources for
the activity variables; thus, uncertainty estimates were determined using assumptions based on source category
knowledge. Uncertainty estimates for oil and grease variables were assumed to have a moderate variance, in
triangular or uniform distribution. Uncertainty estimates for lubricants production were assumed to be rather high
(±20 percent). A narrow uniform distribution, with maximum 6% uncertainty around the mean, was applied to the
lubricant carbon content coefficient.
The Monte Carlo analysis, given a 95 percent confidence interval, produced a storage factor distribution
that approximates a normal curve, around a mean of 10.2 percent, with a standard deviation of 3.7 percent and 95
percent confidence limits of 4.5 and 16.5 percent. This compares to the calculated estimate, used in the Inventory,
of 9.2 percent. The analysis produced an emission distribution approximating a normal curve with a mean of 20.8
Tg COi, standard deviation of 0.5, and 95 percent confidence limits of 18.0 and 23.8 Tg CO2. This compares with a
calculated estimate of 21.1 Tg CO2
The principal sources of uncertainty for the disposition of lubricants are the estimates of the commercial
use, post-use, and environmental fate of lubricants, which, as noted above, are largely based on assumptions and
judgment. There is no comprehensive system to track used oil and greases, which makes it difficult to develop a
verifiable estimate of the commercial fates of oil and grease. The environmental fate estimates for percent of carbon
stored are less uncertain, but also introduce uncertainty in the estimate.
The assumption that the mass of oil and grease can be divided according, to their value also introduces
uncertainty. Given the large difference between the storage factors for oil and grease, changes in their share of total
lubricant production have a large effect on the weighted storage factor.
Future improvements to the analysis of uncertainty surrounding the'lubricants carbon storage factor and
carbon stored include further refinement of the uncertainty estimates for the individual activity variables.
Waxes
Waxes are organic substances that are solid at ambient temperature, but whose viscosity decreases as
temperature increases. Most commercial waxes are produced from petroleum refining, though "mineral" waxes
derived from animals, plants, and lignite [coal] are also used. Previous Inventories have assumed that all carbon
contained in this source is stored (i.e., an assumed storage factor of 100 percent). An analysis of wax end uses in the
US, and the fate of carbon in these uses, suggests that about 42 percent of carbon in waxes is emitted, and 58 percent
is stored.
A-89
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Methodology and Data Sources
At present, the National Petroleum Refiners Association (NPRA) considers the exact amount' of wax
consumed each year by end use to be proprietary (Maguire 2004). In general, about thirty percent of the wax
consumed each year is used in packaging materials, though this percentage has declined in recent years. The next
highest wax end use, and fastest growing end use, is candles, followed by construction materials and firelogs. There
are many other wax end uses, which the NPRA generally classifies into cosmetics, plastics, tires and rubber, hot
melt (adhesives), chemically modified wax substances, and other miscellaneous wax uses. {NPRA 2002)
A carbon storage factor for each wax end use was estimated and then summed across all end uses to
provide an overall carbon storage factor for wax. Because no specific data on carbon contents of wax used in each
end use were available, all wax products are assumed to have the same carbon content. Table A-65 categorizes wax
end uses identified by the NPRA, and lists each end use's estimated carbon storage factor.
Table ft-65: Wm End-Dies by Fate, Percent ol Total Man; Percept stored, and Percent of Total Mass Stored
Percent of Total Percent Stored Percent of Total
Use Mass Mass Stored
Candles
Firelogs
Hotmelts
Packaging
Construction Materials
Cosmetics
Plastics
Tires/Rubber
Chemically Modified
Other
Total
20%
7%
3%
30% '
18%
3%
3%
3%
1%
12%
100%
10%
" 1%.
50%
79%
79%
79%
79%
47%
79%
79%
NA
2%
+
2%
24%
14%
• 2%
2%
1%
1%
10%
58%
i- Does not exceed 0.5 percent
Source, mass percentages: NPRA 2002. Estimates of percent stored are based on professional judgment, ICF Consulting.
Emissive wax end uses include candles, firelogs (synthetic fireplace logs), hotmelts (adhesives), matches,
and explosives. At about 20 percent, candles consume the greatest portion of wax among emissive end uses. As
candles combust during use, they release emissions to the atmosphere. For the purposes of the Inventory, it is
assumed that 90 percent of carbon contained in candles is emitted as CO2. In firelogs, petroleum wax is used as a
binder and as a fuel, and is combusted during product use, likely resulting in the emission of nearly all carbon
contained in product. Similarly, carbon contained in hotmelts is assumed to be emitted as CO2 as heat is applied to
these products during use. It is estimated that SO percent of the carbon contained in hot melts is stored. Together,
candles, firelogs, and hotmelts constitute approximately 30 percent of annual wax production (NPRA 2002).
All of the wax utilized in the production of packaging, cosmetics, plastics, tires and rubber, and other
products is assumed to remain in the product (i.e., it is assumed that there are no emissions of CO2 from wax during
the production of the product.) Wax is used in many different packaging materials including: wrappers, cartons,
papers, paperboard, and corrugated products (NPRA 2002). Davie (1993) and Davie et al. (1995) suggest that wax
coatings in packaging products degrade rapidly in an aerobic environment, producing CO2; however, because
packaging products ultimately enter landfills typically having an anaerobic environment, most of the carbon from
this end use is assumed to be stored in the landfill.
in construction materials, petroleum wax is used as a water repellent on wood-based composite boards,
such as particle board (1GI 2002). Wax used for this end-use should follow the life-cycle of the harvested wood
used in product, which is classified into one of 21 categories, evaluated by life-cycle, and ultimately assumed to
either be disposed of in landfills or be combusted (EPA 2003).
The fate of wax used for packaging, in construction materials, and most remaining end uses is ultimately to
enter the municipal solid waste '(MSW) stream, where they are either combusted or sent to landfill for disposal.
Most of the carbon contained in these wax products will be stored. It is assumed that approximately 21 percent of
the carbon contained in these products will be emitted through combustion or at landfill. With the exception of tires
and rubber, these end uses are assigned a carbon storage factor of 79 percent.
Waxes used in tires and rubber follow the life cycle of the tire and rubber products. Used tires are
ultimately recycled, landfilled, or combusted. The life-cycle of tires is addressed elsewhere in this annex as part of
A-90 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
the discussion of rubber products derived from petrochemical feedstocks. For the purposes of the estimation of the
carbon storage factor for waxes,* wax contained in tires and rubber products is assigned a carbon storage factor of 47
percent-
Uncertainty
A Tier 2 Monte Carlo analysis was performed using @RISK software to determine the level of uncertainty
surrounding the estimates of the wax carbon storage factor and the quantity of carbon emitted from wax in 2004.
Tier 2 analysis was performed to allow the specification of probability density functions for key variables, within a
computational structure that mirrors the calculation of the Inventory estimate. Statistical analyses or expert
judgments of uncertainty were not available directly from the information sources for the activity variables; thus,
uncertainty estimates were determined using assumptions based on source category knowledge. ' Uncertainty
estimates for wax variables were assumed to have'a moderate variance, in normal, uniform, or triangular
distribution; uniform distributions were applied to total consumption of waxes and the carbon content coefficients.
The Monte Carlo analysis produced a storage factor distribution that approximates a normal curve around a
mean of 57.8 percent, with a standard deviation of 6.6 percent and 95 percent confidence limits of 46 percent and 68
percent. This compares to the calculated estimate, used in the Inventory, of 58 percent. The analysis produced an
emission distribution approximating a normal curve with a mean of 1.0 Tg CO2, standard deviation of 0,19 Tg CO2,
and 95 percent confidence limits of 0.76 and 1,39 Tg CO2. This compares with a calculated estimate of 0.95 Tg
COZ. This value is within the range of 95 percent confidence limits established by this quantitative uncertainty
analysis. Uncertainty associated with the wax storage factor is considerable due to several assumptions pertaining to
wax imports/exports, consumption, and fates.
Miscellaneous Products
Miscellaneous products are defined by the U.S. Energy Information Administration as: "all finished
[petroleum] products not classified elsewhere, e.g. petrolatum; lube refining byproducts (e.g., aromatic extracts and
tars); absorption oils; ram-jet fuel; petroleum rocket fuel; synthetic natural gas feedstocks; and specialty oils."
Methodology and Data Sources
Data are not available concerning the distribution of each of the above-listed subcategories within the
"miscellaneous products" category. However, based on the anticipated disposition of the products in each
subcategory, it is assumed that all of the carbon content of miscellaneous products is emitted rather than stored.
Petrolatum and specialty oils (which include greases) are likely to end up in solid waste or wastewater streams rather
than in durable products, and would be emitted through waste treatment. Absorption oil is used in natural gas
processing and is not a feedstock for manufacture of durable products Jet fuel and rocket fuel are assumed to be
combusted in use, and synthetic natural gas feedstocks are assumed to be converted to synthetic natural gas that is
also combusted in use. Lube refining byproducts could potentially be used as feedstocks for manufacture of durable
goods, but such byproducts are more likely to be used in emissive uses. Lube refining byproducts and absorption
oils are liquids and are would be precluded from disposal in landfills. Because no sequestering end uses of any of
the miscellaneous products subcategories have been identified, a zero percent storage factor is assigned to
miscellaneous products. According to EIA (2004) U.S. production of miscellaneous petroleum products in 2004
was 154.6 TBtu. One hundred percent of the carbon content is assumed to be emitted to the atmosphere, where it is
oxidized to CO2. • !
Uncertainty
A separate uncertainty analysis was not conducted for miscellaneous products, though this category was
included in the uncertainty analysis of other non-energy uses discussed in the following section.
Other Non-Energy Uses
The remaining fuel types use storage factors that are not based on U.S.-specific analysis. For industrial
coking coal and distillate fuel oil, storage factors were taken from the IPCC Guidelines for National Greenhouse
Gas Inventories, which in turn draws from Marland and Rotty (1984). For the remaining fuel types (petroleum
A-91
-------
coke, miscellaneous products, and other petroleum), IPCC does not provide guidance on storage factors, and
assumptions were made based on the potential fate of carbon in the respective NEUs. For all these fuel types, the
overall methodology simply involves multiplying carbon content by a storage factor, yielding an estimate of the
mass of carbon stored. To provide a complete analysis of uncertainty for the entire NEU subcategory, the
uncertainty around the estimate of "other" NEUs was characterized, as discussed below.
Uncertainty
A Tier 2 Monte Carlo analysis was performed using @RISK software to determine the level of uncertainly
surrounding the weighted average of the remaining fuels' carbon storage factors and the total quantity of carbon
emitted from these other fuels in 2004. A Tier 2 analysis was performed to allow the specification of probability
density functions for key variables, within a computational structure that mirrors the calculation of the Inventory
estimate. Statistical analyses or expert judgments of uncertainty were not available directly from the information
sources for some of the activity variables; thus, uncertainty estimates were determined using assumptions based on
source category knowledge. A uniform distribution was applied to coking coal consumption, while the remaining
consumption inputs were assumed to be normally distributed. The carbon content coefficients were assumed to have
a uniform distribution; the greatest uncertainty range, 10 percent, was applied to coking coal and miscellaneous
products. Carbon coefficients for distillate fuel oil ranged from 19.52 to 20.15 Tg C/QBtu. The fuel-specific
storage factors were assigned wide triangular distributions indicating greater uncertainty.
,_ The Monte Carlo analysis produced a storage factor distribution that approximates a normal curve around a
mean of 42.0 percent, with a standard deviation of 12.2 percent and 95 percent confidence limits of 24 percent and
64 percent This compares to the calculated, weighted average (across the various fuels) storage factor of 28
percent. The analysis produced an emission distribution approximating a normal curve with a mean of 31.0 Tg CO2
and a standard deviation of 6.9 Tg CO2, and 95 percent confidence limits of 19.2 Tg CO2 and 42.1 Tg CO2. This
compares with the Inventory estimate of 39.3 Tg CO2, which falls closer to the upper boundary of the confidence
limit. The uncertainty analysis results are driven primarily by the very broad uncertainty inputs for the storage
factors.
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A-92 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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A-94 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Figure fl-1: Carton Content for Samples of Pipeline-Quality Natural Gas Included In the Gas Technology Institute
-H.O
•*^970:
, f• « i* i» I*- k •• fc * *• » t -t ' i r r >> >* 1 '"*( V^" » *" "* "51 " * >• ' '-tV,? "'•>•,' i j «„»»" ,•« **• ' '-V' *i< K > >"i<>"''
.it," *-•"•> -1 '"/ -- V. ki > '.'" * , *Vi --,-.-. x^- '•.h-,'!.-- . s'.V11 "' •" : •,«• "i"n' '"• ' .•"V'', < V*'"*
„-, --^ -. v , ^ ' , W>^/ - > i ^ ,-vy »r - ' ]' " ,%,* .,,,*, N ,v » " i", „* „ '-.!"" -j'j'x- <*/•.•<>•'"<;•" „',•>. >*>• •*•„*
/I vtggo\7''Uf.i ^ojb j ;''-^)\W6;j^-^050
5. *- f -,'y i' x Ty>N 1 -
* v » , , '^ ' * - -'tty x - .
Source: EIA (1994) Energy Information Administration, Emissions of Greenhouse Gases in the United States 1987-1992, U.S. Department of
Energy, Washington, DC, November, 1994, DOE/EiA 0573, Appendix A.
-------
figure A-2: Estimated and Actual Belattonshlps Between Petroleum Carton Content coefficients and Hydrocarbon
Density
24,-i
22-
20 -
18 -
16
•-•Refer mate
< -Light Reformat
Heavy Reformats
- i-hexane
" •,, i-pentane i ...
n-bute.ne j. butane
•Propylene
-f-'Pro pane
•'''•-, ..''"' '-'",,
"T7 = Paraffin Hydrocarbons
VO 15 30 45 60 - 75 ,90 105
- - ' ' Hydrocarbon Density (API Gravity)
120 135
150
Source: Carbon content factors for paraffins are calculated based on the properties of hydrocarbons in V. Guthrie (ed.), Petroleum Products
Handbook (New York: McGraw Kill, 1960} p. 33. Carbon content factors from other petroleum products are drawn from sources described
below. Relationship between density and emission factors based on the relationship between density and energy content in U.S. Department of
Commerce, National Bureau of Standards, Thermal Properties of Petroleum Products, Miscellaneous Publication, No. 97 (Washington, D.C.,
1929), pp.16-21, and relationship between energy content and fuel composition in S. Ringen, J. Lanum, and F.P. Miknis, "Calculating Heating
Values from the Elemental Composition of Fossil Fuels,' Fuel, Vol. 58 (January 1979), p.69.
-------
Figure A-3: Carton Content of Pure Hydrocarbons as a hincdon of Canon Number
100 -i
95 -
190 J
>. ••
85 H
•j.H
75 -
70
• Paraffins _. , ' -
,rt Cyclo panaffint
-TAro matics
ttttttttttttttttt
n-pentaiie • •
"Butane
/ , 'Propane ,
'- "Ethane
• Methane' , '*'•','
' Gasoline Jet Fuel • • "'-
. LPG . Naphtha Kerosene Dieiel
-LibeOil Fuel Oil
10 15 ' - 20 -- 25
Number of Carbo n Atoms in Molecule *
30 , , '. 35
Source: J.M. Hunt, Petoleum Geochemistry and Geology (San Francisco, CA, W.H. Freeman and Company, 1979), pp. 31-37.
-------
Descriptions of Figures: Annex 2
Figure A-l shows the relationship between the calculated carbon contents for each natural gas sample and
its energy content. This figure illustrates the relatively restricted range of variation in both the energy
content (which varies by about 6 percent from average) and the carbon emission coefficient of natural gas
(which varies by about 5 percent). Thus, the knowledge that gas has been sold via pipeline to an end-use
consumer allows its carbon emission coefficient to be predicted with an accuracy of ±5.0 percent.
Figure A-2 compares carbon content coefficients calculated on the basis of the derived formula with actual
carbon content coefficients for a range of crude oils, fuel oils, petroleum products, and pure hydrocarbons.
The estimated relationship is shown as a line depicting decreasing carbon content with increasing
hydrocarbon density. The actual relationship is appears as dozens of points scattered along this line.
Figure A-3 illustrates the share of carbon by weight for each class of hydrocarbon. Hydrocarbon molecules
containing 2 to 4 carbon atoms are all natural gas liquids; hydrocarbons with 5 to 10 carbon atoms are
predominantly found in naphtha and gasoline; and hydrocarbon compounds with 12 to 20 carbons comprise
"middle distillates," which are used to make diesel fuel, kerosene and jet fuel. Larger molecules are
generally used as lubricants, waxes, and residual fuel oil.
-------
ANNEX 4 IPCC Reference Approach for
Estimating CO2 Emissions from Fossil
Fuel Combustion
It is possible to estimate carbon dioxide (CO2) emissions from fossil fuel consumption using alternative
methodologies and different data sources than those described in Annex 2.1. For example, the UNFCCC reporting
guidelines request that countries, in addition to their "bottom-up" sectoral methodology, complete a "top-down"
Reference Approach for estimating C02 emissions from fossil fuel combustion. Section 1.3 of the Revised 1996
IPCC Guidelines for National Greenhouse Gas Inventories: Reporting Instructions states, "If a detailed, Sectoral
Approach for energy has been used for the estimation of CO2 from fuel combustion you are still asked to
complete...the Reference Approach...for verification purposes" (IPCC/UNEP/OECD/IEA 1997). This reference
method 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. The basic principle is 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 following discussion provides the detailed calculations for estimating CO2 emissions from fossil fuel
combustion from the United States using the IPCC-recommended Reference Approach.
->
Step 1: Collect and Assemble Data in Proper Format
To ensure the comparability of national inventories, the IPCC has recommended that countries report
energy data using the International Energy Agency (IEA) reporting convention. National energy statistics were
collected in physical units from several EIA documents in order to obtain the necessary data on production, imports,
exports, and stock changes.
It was necessary to make-a number of modifications to these data to generate more accurate apparent
consumption estimates of these fuels. The first modification adjusts for consumption of fossil fuel feedstocks
accounted for in the Industrial Processes chapter, which include the following: unspecified coal for coal coke used in
iron and steel production; natural gas used for ammonia production; petroleum coke used in the production of
aluminum, ferroalloys, titanium dioxide, and ammonia; and other oil and residual fuel oil used in the manufacture of
carbon black. The second modification adjusts for the fact that EIA energy statistics include synthetic natural gas in
both coal and natural gas data. The third modification adjusts for the inclusion of ethanol in motor gasoline statistics.
Ethanol is a biofuel, and it is assumed that no net CO2 emissions occur due to its combustion. The fourth
modification adjusts for consumption of bunker fuels, which refer to quantities of fuels used for international
transportation estimated separately from U.S. totals. The fifth modification consists of the addition of U.S.
territories data that are typically excluded from the national aggregate energy statistics. The territories include
Puerto Rico, U.S. Virgin Islands, Guam, American Samoa, Wake Island, and U.S. Pacific Islands. These data, as
well as the production, import, export, and stock change statistics, are presented in Table A-201.
The carbon content of fuel varies with the fuel's heat content. Therefore, for an accurate estimation of CO2
emissions, fuel statistics were provided on an energy content basis (e.g., Btu or joules).. Because detailed fuel
production statistics are typically provided in physical units (as in Table A-201 for 2004), they were converted to
units of energy before COZ emissions were calculated. Fuel statistics were converted to their energy equivalents by
using conversion factors provided by EIA. These factors and their data sources are displayed in Table A-202. The
resulting fuel type-specific energy data for 2004 are provided in Table A-203.
Step 2: Estimate Apparent Fuel Consumption
The next step of the IPCC Reference Approach is to estimate "apparent consumption" of fuels within the
country. This requires a balance of primary fuels produced, plus imports, minus exports, and adjusting for stock
A-249
-------
changes. In this way, carbon enters an economy through energy production and imports (and decreases in fuel
stocks) and is transferred out of the country through exports (and increases in fuel stocks). Thus, apparent
consumption of primary fuels (including crude oil, natural gas liquids, anthracite, bituminous, subbituminous and
lignite coal, and natural gas) can be calculated as follows:
Apparent Consumption = Production + Imports - Exports - Stock Change
Flows of secondary fuels (e.g., gasoline, residual fuel, coke) should be added to primary apparent
consumption. The production of secondary fuels, however, should be ignored in the calculations of apparent
consumption since the carbon contained in these fuels is already accounted for in the supply of primary fuels from
which they were derived (e.g., the estimate for apparent consumption of crude oil already contains the carbon from
which gasoline would be refined). Flows of secondary fuels should therefore be calculated as follows:
Secondary Consumption = Imports - Exports - Stock Change
Note that this calculation can result in negative numbers for apparent consumption of secondary fuels. This
result is perfectly acceptable since it merely indicates a net export or stock increase in the country of that fuel when
domestic production is not considered.
Next, the apparent consumption and secondary consumption need to be adjusted for feedstock uses of fuels
accounted for in the Industrial Processes chapter, international bunker fuels, and U.S. territory fuel consumption.
Bunker fuels and feedstocks accounted for in the Industrial Processes chapter are subtracted from these estimates,
while fuel consumption in U.S. territories is added.
The IPCC Reference Approach calls for estimating apparent fuel consumption before converting'to a
common energy unit. However, certain primary fuels in the United States (e.g., natural gas and steam coal) have
separate conversion factors for production, imports, exports, and stock changes. In these cases, it is not appropriate
to multiply apparent consumption by a single conversion factor since each of its components have different heat
contents. Therefore, United States fuel statistics were converted to their heat equivalents before estimating apparent
consumption. Results are provided in Table A-202.
Step 3: Estimate Carbon Emissions
Once apparent consumption is estimated, the remaining calculations are similar to those for the "bottom-
up" Sectoral Approach (see Annex 2.1). Potential COj emissions were estimated using fuel-specific carbon
coefficients (see Table A-203).1 The carbon in products from non-energy uses of fossil fuels (e.g., plastics or
asphalt) was then estimated and subtracted (see Table A-20S). This step differs from the Sectoral Approach in that
emissions from both fuel combustion and non-energy uses are accounted for in this approach. Finally, to obtain
actual CO2 emissions, net emissions were adjusted for any carbon that remained unoxidized as a result of incomplete
combustion (e.g., carbon contained in ash or soot).2
Step 4: Convert to COz Emissions
. Because the IPCC reporting guidelines recommend that countries report greenhouse gas emissions on a full
molecular weight basis, the final step in estimating CO2 emissions from fossil fuel consumption was converting
from units of carbon to units of CO2. Actual carbon emissions were multiplied by the motecular-to-atomic weight
ratio of CO2 to carbon (44/12) to obtain total carbon dioxide emitted from fossil fuel combustion in teragrams (Tg).
The results are contained in Table A-204.
1 Carbon coefficients from EIA were used wherever possible. Because EIA did not provide coefficients for coal, the
IPCC-recommended emission factors were used in the top-down calculations for these fuels. See notes in Table A-204 for more
specific source information.
2 For the portion of carbon that is unoxidized during coal combustion, the IPCC suggests a global average value of 2
percent. However, because combustion technologies in the United States are more efficient, the United States inventory uses 1
percent in its calculations for petroleum and coal and 0.5 percent for natural gas.
A-250 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Comparison Between Sectoral and Reference Approaches
These two alternative approaches can both produce reliable estimates that are comparable within a few
percent. Note that the reference approach includes emissions from non-energy uses. Therefore, these totals should
be compared to the aggregation of fuel use and emission totals from Emissions of CO2 from Fossil Fuel Combustion
(Annex 2.1) and Carbon Emitted from Non-Energy Uses of Fossil Fuels (Annex 2.3). These two sections together
are henceforth referred to as the Sectoral Approach. Other-than this distinction, the major difference between
methodologies employed by each approach lies in the energy, data used to derive carbon emissions (i.e., the actual
surveyed consumption for the Sectoral Approach versus apparent consumption derived for the Reference Approach).
In theory, both approaches should yield identical results. In practice, however, slight discrepancies occur. For the
United States, these differences are discussed below.
Differences In Total Amount of Energy Consumed
Table A-207 summarizes the differences between the Reference and Sectoral approaches in estimating tota!
energy consumption in the United States. Although theoretically the two methods should arrive at the same estimate
for U.S. energy consumption, the Reference Approach provides an energy total that is 0.8 percent.lower than the
Sectoral Approach for 2004. The greatest differences lie in lower estimates for both petroleum and natural gas
consumption for the Reference Approach (1.0 percent).
There are several potential sources for the discrepancies in consumption estimates:
• Product Definitions The fuel categories in the Reference Approach are different from those used in
the Sectoral Approach, particularly for petroleum. For example, the Reference Approach estimates
. apparent consumption for crude oil. Crude oil is not typically consumed directly, but refined into other
products. As a result, the United States does not focus on estimating the energy content of the various
grades of crude oil, but rather estimating the energy content of the various products resulting from
crude oil refining. The United States does not believe that estimating apparent consumption for crude
oil, and the resulting energy content of the crude oil, is the most reliable method for the United States
to estimate its energy consumption. Other differences in product definitions include using sector-
specific coal statistics in the Sectoral Approach (i.e., residential,' commercial, industrial coking,
industrial other, and transportation coal), while the Reference Approach characterizes coal by rank (i.e.
anthracite, bituminous, etc.). Also, the liquefied petroleum gas (LPG) statistics used in the bottom-up
calculations are actually a composite category composed of natural gas liquids (NGL) and LPG.
• Heat Equivalents. It can be difficult to obtain heat equivalents for certain fuel types, particularly for
categories such as "crude oil" where the key statistics are derived from thousands of producers in the
United States and abroad.
• Possible inconsistencies in U.S. Energy Data. The United States has not focused its energy data
collection efforts on obtaining the type of aggregated information used in the Reference Approach.
Rather, the United States believes that its emphasis on collection of detailed energy consumption data
is a more accurate methodology for the United States to obtain reliable energy data. Therefore, top-
down statistics used in the Reference Approach may not be as accurately collected as bottom-up
statistics applied to the Sectoral Approach.
• Balancing Item. The Reference Approach uses apparent consumption estimates while the Sectoral
Approach uses reported consumption estimates. While these numbers should be equal, there always
seems to be a slight difference that is often accounted for in energy statistics as a "balancing item."
Differences In Estimated CO2 Emissions s
Given these differences in energy consumption data, the next step for each methodology involved
estimating emissions of CO2. Table A-208 summarizes the differences between the two methods in estimated
carbon emissions.
As mentioned above, for 2004, the Reference Approach resulted in a 0.8 percent lower estimate of energy
consumption in the United States than the Sectoral Approach. The resulting emissions estimate for the Reference
Approach was 0.6 percent higher. Estimates of coal and natural gas emissions using each approach yield very
A-251
-------
similar values (within 0.8 percent), though petroleum emission estimates from the Reference Approach are slightly
higher (1.4 percent) than the Sectoral Approach. Potential reasons for these differences may include:
• Product Definitions. Coal data is aggregated differently in each methodology, as noted above. The
format used for the Sectoral Approach likely results in more accurate estimates than in the Reference
Approach. Also, the Reference Approach relies on a "crude oil" category for determining petroleum-
related emissions. Given the many sources of crude oil in the United States, it is not an easy matter to
track potential differences in carbon content between many different sources of crude, particularly
since information on the carbon content of crude oil is not regularly collected. ('
• Carbon Coefficients. The Reference Approach relies on several default carbon coefficients by rank
provided by IPCC (IPCC/UNEP/OECD/IEA 1997), while the Sectoral Approach uses annually
updated category-specific coefficients by sector that .are likely to be more accurate. Also, as noted
above, the carbon coefficient for crude oil is more uncertain than that for specific secondary petroleum
products, given the many sources and grades of crude oil consumed in the United States.
Although the two approaches produce similar results, the United States believes that the "bottom-up"
Sectoral Approach provides a more accurate assessment of CO2 emissions at the fuel level. This improvement in
accuracy is largely a result of the data collection techniques used in the United States, where there has been more
emphasis on obtaining the detailed products-based information used in the Sectoral Approach than obtaining the
aggregated energy flow data used in the Reference Approach. The United States believes that it is valuable to
understand both methods.
References
EIA (2005a) Monthly Energy Review, September 2005 and Unpublished Supplemental Tables on Petroleum Product
detail. Energy Information Administration, U.S. Department of Energy, Washington, DC, DOE/EIA-
0035(2005/09). j '
EIA (2005b) Monthly Energy Review, Energy Information Administration, U.S. Department of Energy, Washington,
DC. November. DOE/EIA 0035(02)-monthly.
EIA (2005c) Annual Energy Review 2004. Energy Information Administration, U.S. Department of Energy,
Washington, DC, DOE/EIA-0384(2004). September.
EIA (1995-2005) Petroleum Supply Annual, Energy Information Administration, U.S. Department of Energy,
Washington, DC, Volume I. DOE/EIA-0340. .
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, Paris;
Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
Co-Operation and Development, International Energy Agency.
<
SA1C (2004) Analysis prepared by Science Applications International Corporation for EPA, Office of Air and
Radiation, Market Policies Branch.
USGS (1998) CoalQual Database Version 2.0, U.S. Geological Survey.
A-252 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Table A-201:2004 D.S. Energy Statistics (Physical Dnlts)
Stock
Fuel Category (Units)
Solid Fuels (Thousand Short Tons)
Gas Fuels (Million Cubic Feet)
Liquid Fuels (Thousand Barrels)
Fuel Type
Anthracite Coal
Bituminous Coal
Sub-bituminous Coal
Lignite
Coke
Unspecified Coal
Natural Gas
Crude Oil
Nat Gas Liquids and LRGs
Other Liquids
Motor Gasoline
Aviation Gasoline
Kerosene
Jet Fuel
Distillate Fuel
Residual Fuel
Naphtha for petrochemical feedstocks
Petroleum Coke
Other Oil for petrochemical feedstocks
Special Naphthas
Lubricants
Waxes
Asphalt/Road Oil
Still Gas
Misc. Products
U.S.
Production Imports Exports Change Adjustment Bunkers Territories
1,700
546,605
479,634
83,540
19,027,423
1,983,302
662,151
(13,459)
167,587
.
a
a
a
a
6,873
27,280
4,258,558
3,692,063
111,710
361,583
181,682
119
765
46,505
119,118
156,024
48,800
11,912
57,804
2,984
2,912
1,470
15,604
0
49
a
a
a
a
1,319
47,998
854,138
9,783
16,649
22,976
45,498
• o
1,333
14,799
40,101
74,885
0
128,034
0
9,902
14,916
1,532
2,215
0
1,012
a
a
a
a '
(28)
(18,221)
110,436
54,078
10,196
19,177
(3.680)
139
(699)
1,302
(10,270) •
4,563-
(207)
(1,939)
245
(266)
481
(87)
2,829
0
640
423
3,542
15,857
236,320
85,297
150,389
14,896
9,000 56,257
13,828
27,456
1,783
24,010
3,484
41,230
1,717
12,681
18,284
34,869
281
26,660
[a] Included in Unspecified Coal
Data Sources: Solid and Gas Fuels: EIA (2005a); Liquid Fuels: EIA (1995-2005).
253
-------
Table ft-JOfc Conversion Factors to Energy Units Heat Equivalents}
Fuel Category (Units)
Solid Fuels (Million Btu/ShortTon)
Natural Gas (BTU/Cubic Foot)
Liquid Fuels (Million Btu/Barrel)
Stock U.S.
Fuel Type ' Production Imports Exports Change Adjustment Bunkers Territories
Anthracite Coal
Bituminous Coal
Sub-bituminous Coal
Lignite
Coke .
Unspecified
Crude Oil
Nat Gas Liquids and LRGs
Other Liquids
Motor Gasoline
Aviation Gasoline
Kerosene
Jet Fuel
Distillate Fuel
Residual Oil
Naphtha for petrochemical feedstocks
Petroleum Coke
Other Oil for petrochemical feedstocks
Special Naphthas
Lubricants
Waxes
Asphalt/Road Oil
Still Gas
Misc. Products
22.57
23.89
17.14
12.87
24.80
25.00
1,030 1,023
5.80 5.98
3.72 3.72
5.83 5.83
5.22 5.22
5.05
5.67
5.67
5.83
6.29
5.25
6.02
5.83
5.25
6.07
5.54
6.64
6.00
5.80 '
24.80
25.97
1,009
5.80
3.72
5.83
5.22
5.05
5.67
5.67
5.83
6.29
5.25
6.02
5.83
5.25
6.07
5.54
• 6.84
6.00
5.80
24.80
20.86
1,030
5.80
3.72
5.83
5.22
5.05
5.67
5.67
5.83
6.29
5.25
6.02
5.83
5.25
6.07
5.54
6.64
6.00
5,80
28.16
12.87
27.43
1,025
5.80
3.72
5.83
5.22 5.22
5.05
5.67
5.67
5.83
6.29 6.29
5.25
6,02 6,02
5.83 5.83
5.25
6.07
5.54
6.64
6.00
5.80
25.14
1,030
5.80
3.72
5.83
5.22
5.05
5.67
5.67
5.83
6.29
525
6.02
5.83
5.25
6.07
5.54
6.64
6.00
5.80
Data Sources: Coal and lignite production: EIA (2005c); Unspecified Solid Fuels: EIA (2005b); Coke, Natural Gas and Petroleum Products: EIA (2D05a).
254 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003
-------
Table A-203:2004 Apparent Consumption of fossil Fuels fTBtt)
Fuel Category
Solid Fuels
Gas Fuels
Liquid Fuels
Total
Fuel Type
Anthracite Coal
Bituminous Coal
Sub-bituminous Coal
Lignite
Coke
Unspecified
Natural Gas
Crude Oil
Nat Gas Liquids and LRGs
Other Liquids
Motor Gasoline
Aviation Gasoline
Kerosene
Jet Fuel
Distillate Fuel
Residual Oil
Naphtha (or petrochemical feedstocks '
Petroleum Coke
Other Oil for petrochemical feedstocks
Special Naphthas
Lubricants
Waxes
Asphalt/Road Oil
Still Gas
Misc. Products
Production
36.4
13,058.4
8,220.9
1,074.8
• 19,598.2
11,503.2
2,465.9
(78.4)
874,0
56,755.3
Imports
170.5
682.0
4,356.5
22,078.5
416.0
2,106.2 '
947.5 .
0.6
4.3
263.7 '
693.9
980.9
256.1
71.8
336.7
- 15.7
17.7
8.1
103.5
0.0
0.3
33,510.5
Exports
32,7
1,246.6
861.8
56.7
62.0
133.8
237.3
0.0
7.6
83.9
233,6
470.8
0.0
771.3
0.0
52.0
90.5
8.5
14.7
0.0
5.9
4,369.6
Stock U.S. Apparent
Change Adjustment Bunkers Territories Consumption
(0.7)
(380.1)
113.7
313.7
38.0
111.7
(19.2)
0.7 .
(4.0)
7.4
(59.8)
28.7
(1.1)
(11.7)
1.4
(1-4)
2.9
(0.5)
18.8
0.0
3.7
162.3
11.9
45.6
434.9
242.2
444.8
852.7
86.8
56.6 353.7
83.3
159.9
t
1,479.2 1,293.2
44.8
24.7
13.0
215.0
9.7
71.9
106.5
219.2
1.7
"154.5
861.1
38,4
13,058.4
8,209.0
1,029.3
138.4
(574.6)
• 22,761.7
33,211.3
2,794.9
1,782.3
1,373.5
(0.1)
10.5
(608.4)
539.8
290.4
257.2
(771.1)
175.3
(34.9)
(74.0)
0.1
70.1
0.0
145.2
83,822.7
Note: Totals may not sum due to independent rounding.
255
-------
TaHoA-204:2004 PoieatM Carton Dloifdo [missions
Apparent Consumption (QBtu) Carbon Coefficients Potential Emissions
Fuel Category
Solid Fuels
Gas Fuels
Liquid Fuels
Total
Fuel Type
Anthracite Coal
Bituminous Coal
Sub-bituminous Coal
Lignite
Coke
Unspecified
Natural Gas
Crude Oil
Nat Gas Liquids and LRGs
Other Liquids
Motor Gasoline
Aviation Gasoline
Kerosene
Jet Fuel
Distillate Fuel
Residual Oil
Naphtha for petrochemical feedstocks
Petroleum Coke
Other Oil for petrochemical feedstocks
Special Naphthas
Lubricants
Waxes
Asphalt/Road Oil
Still Gas
Misc. Products
(Tg Carbon/QBtu) (Tg COj Eq.)
0.038
13.058
8.209
1.029
0.138
(0.620)
22.762
33.211
2.795
1.782
1.374
(0.000)
0.010
{0.608)
0.540
0.290
0.257
(0.771)
0.175
(0.035)
(0.074)
0.000
0.070
0.000
0.145
28.26
25.49
26.48
26.30
31.00
25.34
14.47
20.33
16.99
20.33
19.33
18.87
19.72
19.33
19.95
21.49
18.14
27.85
19.95
19.86
20.24
19.81
20.62
17.51
20.33
4.0
1,220.5
797.0
99.3
15.7
(53.4)
1,207.7
2,475.4
174.1
132.8
97.4
(0.0)
0.8
(43.1)
39.5
22.9
17.1
(78.7)
118
(2.5)
(5.5)
0.0
5.3
0.0
10.8
6,149.8
Data Sources: Carbon content coefficients by coal rank from USGS (1998) and SAIC (2004); Unspecified Solid Fuels, Natural Gas and Liquid Fuels: EIA (2005a).
Note: Totals may not sum due to independent rounding.
256 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2003
-------
Table A-205:2004 Don-Enemy Carton stored In Products
Consumption Carbon Carbon Fraction Carton
for Non-Energy Coefficients Content Sequestered Stored {Tg
Fuel Type UsefTBtu) (Tg Carbon/QBtu) (Tg Carbon) COiEq.)
Coal
Natural Gas
Asphalt & Road Oil
LPG
Lubricants
Pentanes Plus
Petrochemical Feedstocks
Petroleum Coke
Special Naphtha
Waxes/Misc.
Misc. U.S. Territories
Petroleum
Total
214.3
380.1 ,
1,303.9
1,437,5
314.8
156.5
a
189.4
47.2
a
a
31.00
14.47
20.62
16.81
20.24
' 18.24
a
27.85
19.86
a
a
6.6
5.5
26.9
24.2
6.4
2.9
a
5.3
0.9
a
a
0.10
0.62.
1.00
0.62
0.09
0.62
• a
0.50
0.62
a
a
2.44
12.60
98.58
55.36
2.16
6.54
57.52
9.67
2.15
1.72
1.13
249.9
[a] Values for Misc. U.S. Temtones Petroleum, Petrochemical Feedstocks and Waxes/Misc. are not shown because these categories are aggregates of
numerous smaller components.
Note: Totals may not sum due to Independent rounding.
Table A-206: 2004 Reference Approach COi Emission* from Fossil fuel Consumption tTg COt Eq. unless otnerwlse
noted]
Fuel Category
Coal
Petroleum
Natural Gas
Total
Potential Carbon
Emissions Sequestered
2,083.1
2,859.0
1,207.7
6,149.8
2.4
234.8
12.6
249.9
Net
Emissions
2,080.7
2,624.2
1,195.1
5,899.9
Fraction
Oxidized .
99.0%
99.0%
99.5%
'
Total
Emissions
2,059.9
2,597.9
1,189.1
5,846.9
Note Totals may not sum due to independent rounding.
257
-------
Table A-207: Fuel Consumption in too Dnlted States hy EsUmadng Approach mtu)
Approach
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Sectoral ' 69,870.9 69,479.5 71,110.2 72,901.2 74,196.2 75,174.5 77,735.3 78,683.5
Coal 18,074.7 17,999.9 18,191.3 18,951.9 19,046.5 19,231.5 20,151.5 20,578.5
NaturalGas 19,375.8 19,765.4 20,438.1 20,994.7 21,455.7 22,426.5 22,837.6 22,966.8
Petroleum 32,420.3 31,714.3 32,480.8 32,954.6 33.694.0 33,516.5 34,746.2 35,138.2
Reference
(Apparent) 69,125.2 68,348.8 69,894.8 71,695,3 73,205.3 74,113.3 . 76,558.8 77,991.3
Coal 17,602.8 17,400.9 17,725.1 18,260.8 18,724.4 18,610,6 19,519.0 20,160.7
Natural Gas 19,746.7 19,765.4 20,425.2 20,980.8 21,459.9 22,411,9 22,816.2 22,951.1
Petroleum 31,775.6 31,182.4 31,744.5 32,453.7 33,021.0 33,090,8 34,223.6 34.879.5
79,108.3 80,413.5 82,693.3 81,486.6 82,098.6 82,738.8 84,472.9
20,817.1 20,878.9 21,833.9 21,247.2 21,207.0 21,667.5 21,912.7
22,559.5 22,641.7 23,554.5 22,642.7 23,370.3 22.866.9 22,987.1
35,731.6 36,892.9 37,305.0 37,596.7 37.521.3 38,204.4 39,573.1
78,072.3 79,240.4 81,675.2 80,741.0 81,582.5 82,149.4 83,822.7
20,033.0 20,080.7 21,039.2 20,781.3 20,875.0 21,178.1 '21,898.9
22,531.1 22,635.1 23,598.7 22,659.2 23,360.9 22,860.2 22,761.7
35.508.3 36,524.7 37,037.3 37,300.5 37,346.6 38,111.1 39,162.1
Difference
Coal
Natural Gas
Petroleum
-1.1%
-2.6%
1.9%
-2.0%
•1.6%
-3.3%
0.0%
-1.7%
•1.7%
-2.6%
-0.1%
-2.3%
•1.7%
-3.6%
-0.1%
-1.5%
•1.3%
-1.7%
0.0%
-2.0%
•1.4%
-3,2%
-0.1%
-1.3%
•1.5%
-3.1%
-0.1%
-1.5%
•0.9%
-2.0%
-0,1%
-0.7%
•1.3%
-3.8%
-0.1%
-0.6%
•1.5%
-3.8%
0.0%
-1.0%
•1.2%
-3.6%
0.2%
-0.7%
-0.9%
-2.2%
0.1%
-0.8%
•0.6%
-1.6%
0.0%
-0.5%
•0.7% -0.8%
-2,3% -0.1%
O.'0% -1.0%
-0,2% -1.0%
* Includes U.S. territories. Does not include international bunker fuels.
+Does not exceed 0.05%.
Note: Totals may not sum due ID independent rounding.
Taua A-208: CO, Emissions mm Fossil Fuel Combustion by Estimating oppnaeli (To CO, EqJ
Approach
Sectoral
Coal
Natural Gas
Petroleum
Reference
(Apparent)
Coal
Natural Gas
Petroleum
Difference
Coal
Natural Gas
Petroleum
1990
4,813.3
1,684.1
1,013.1
2,116.1
4,771,6
1,641.6
1,034.0
2,096.0
-0.9%
-2.5%
2.1%
-0,9%
1991
4,779.5
1,678.0
1,034.0
2,067.6
4,717.7
1,625.0
1,035.3
2,057.4
•1.3%
-3.2%
0.1%
-0.5%
1992
4,876.0
1,696.0
1,070.5
2.109.5
4,819.9
1,655.1
1,070.9
2.093.9
•1.2%
-2.4%
0.0%
-0.7%
1993
5,006.0
1,767.5
1,099.0
2,139.4
4,951.9
1.708.1
1,099.6
2,144.2
•1.1%
-3.4%
0.1%
0.2%
1994
5,082.5
1,777.3
1,121.7
2,183.5
5,048.9
1,752.6
1,123.2
2,173.2
•0.7%
-1.4%
0.1%
-0.5%
1995
5,129.1
1,796.5
1,172.6
2,160.1
5,092.9
1,743.4
1.173.2
2,176.3
•0.7%
-3.0%
0.1%
0.7%
1996
5,315.8
1,882.1
1,194.0
2,239.7
5,273.5
1,827.8
1,194.0
2,251.7
-0.8%
-2.9%
0.0%
0.5%
1997
5,381.9
1,922.8
1,200.3
2,258.7
5,383.1
1,888.8
1,200.8
2,293.4
0.0%
-1.8%
0.0%
1.5%
1998
5,424.2
1,945.3
1,177.9
2,301.1
5,3924
1,880.8
1,177.3
2,334,3
•0.6%
-3.3%
0.0%
1.4%
1999
5,502.6
1,951.3
1,181.6
2,369.7
5,455.9
1,889.0
1.182.2
2,384.7
•0.8%
-3.2%
0.0%
0.6%
2000
5,674.0
2,040.6
1,228.7
2,404.7
5,642.1
1,977.1
1,232.0
2,433.0
-0.6%
-3.1%
0.3%
1.2%
2001
5,617.6
1,985.6
1,182.0
2,450.0
5,608.0
1.954.6
1,183.1
2,470.4
•0.2%
-1.6%
0.1%
0.8%
2002
5,637.8
1,982.0
1,219.8
2,436.1
5,6575
1,963.5
1,220.2
2,474.2
0.4%
-0.9%
0.0%
1.6%
2003
5,704.2
2,025.2
1,192.9'
2,486.1
5,719.3
1,990.8
1,194.3
2,534.2
0.3%
-1.7%
0.1%
1.9%
2004
5,809.6
2,049.4
1,198.7
2,561.5
5,846.9
2,059.9
1,189.1
2,597.9
0.6%
0.5%
-0.8%
1.4%
*• Does not exceed 0.05%.
Note: Totals may not sum due to independent rounding. Includes U.S. territories. Does not include emissions from international bunker fuels.
A-258 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
ANNEX 5 Assessment of the Sources
and Sinks of Greenhouse Gas
Emissions Excluded
Although this report is intended to be a comprehensive assessment of anthropogenic64 sources and sinks of
greenhouse gas emissions for the United States, certain sources have been identified yet excluded from the estimates
presented for various reasons. Before discussing these sources, however, it is important to note that processes or
activities that are not anthropogenic in origin or do not result in a net source or sink of greenhouse gas emissions are
intentionally excluded from a national inventory of anthropogenic greenhouse gas emissions. In general, processes
or activities that are not anthropogenic are considered natural (i.e., not directly influenced by human activity) in
origin and, as an example, would include the following:
• Volcanic eruptions
• Carbon dioxide (CO2) exchange (i.e., uptake or release) by oceans
• Natural forest fires65
• Methane (CH4) emissions from wetlands not affected by human induced land-use changes
*
Some processes or activities may be anthropogenic in origin but do not result in net emissions of
greenhouse gases, such as the respiration of CO2 by people or domesticated animals.66 Given a source category that
is both anthropogenic and results in net greenhouse gas emissions, reasons for excluding a source related to an
anthropogenic activity include one or more of the following:
• There is insufficient scientific understanding to develop a reliable method for estimating emissions at a
national level.
• Although an estimating method has been developed, data were not adequately available to calculate
emissions.
• Emissions were implicitly accounted for within 'another source category (e.g., CO2 from Fossil Fuel
Combustion).
It is also important to note that the United States believes the exclusion of the sources discussed below
introduces only a minor bias in its overall estimate of U.S. greenhouse gas emissions.
CQz from Burning in Coal Deposits and Waste Piles
Coal is periodically burned in deposits and waste piles. It has been estimated that the burning of coal in
deposits and-waste piles would represent less than 1.3 percent of total U.S. coal consumption, averaged over ten-
years. Because there is currently no known source of data on the quantity of coal burned in waste piles and there is
uncertainty as to the traction of coal oxidized during such burnings, these CO2 emissions are not currently estimated.
Further research would be required to develop accurate emission factors and activity data for these emissions to be
64 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/1EA
1997).
65 In some cases forest fires that are started either intentionally or unintentionally are viewed as mimicking natural
burning processes that have been suppressed by other human forest management activities. The United States does not consider
forest fires within its national boundaries to be a net source of greenhouse emissions.
66 Respiration of COj by biological organisms is simply part of the broader global carbon cycle that also includes
uptake of CO2 by photosynthetic organisms.
A-259
-------
estimated (see Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories: Reference Manual, p.
1.112-1.113).
CO: from Enhanced Oil Recovery (EOR)
Carbon dioxide is injected into underground formations to increase crude oil production, in a field
technique known as Enhanced Oil Recovery (EOR). It is thought that much of the injected CO2 may be effectively
and permanently sequestered in the underground formations, however, the fraction of the injected CO2 that is re-
released remains uncertain. The fraction re-released varies from one formation to another depending upon the field
geology and the gas capture/reinjection technology employed at the wellhead. In 2002 the amount of CO2 derived
from natural sources and natural gas processing plants and used in EOR was approximately 12 Tg CO2. Further
research into EOR is required before the resulting CO2 emissions can be adequately' quantified (see CO2
Consumption in the Industrial Processes Chapter).
COj from Natural Gas Processing
Carbon dioxide (CO2) is produced as a byproduct of natural gas production and processing. Natural gas
produced from natural gas wells (referred to as non-associated natural gas) and natural gas produced from crude oil
wells (referred to as associated-dissolved natural gas) may contain naturally occurring CO2 that must be removed
from the natural gas in order for it to meet pipeline specifications for CO2 content. A fraction of the CO2 remains in
the natural gas delivered to end-users by pipeline, and is emitted when the natural gas is combusted. However, the
majority of the CO2 is separated from natural gas at gas processing plants. CO2 removed at gas processing plants is
generally vented to the atmosphere, but several gas processing plants in Wyoming and Texas compress the CO2
separated from natural gas and transport this CO2 by pipeline for use in enhanced oil recovery. CO2 used for
enhanced oil recovery is injected into oil reservoirs to improve the recovery of oil remaining in the reservoir through
a number of processes, including reduction of crude oil viscosity and oil density, acid effects on carbonate
reservoirs, and miscible and immiscible displacement, and is assumed to remain sequestered in the underground
formations.
Data obtained from ElA's Natural Gas Annual and the Minerals Management Service's report on emissions
in the Gulf of Mexico were used to develop a preliminary estimate of emissions. In 2002, the total amount of CO2
produced from natural gas processing was 29.5 Tg CO2 Eq. (29,455 Gg). There are four gas processing plants
currently in operation—one in Wyoming and three in Texas—that produce CO2 for use in enhanced oil recovery. In
2002, the amount of CO2 produced by these facilities and used for enhanced oil recovery was 4.7 Tg CO2 Eq. (4,696
Gg). This amount is not emitted to the atmosphere and is therefore subtracted from the total amount of CO2
produced from natural gas to calculate the total amount of CO2 produced from natural gas processing that is emitted
to the atmosphere, which was 24.7 Tg CO2 Eq. (24,654 Gg) in 2002. However,,since these estimates have not been
integrated with CH, from Natural Gas Systems and CO2 from Fossil Fuel Combustion estimates to ensure that there
is no double-counting, they are not yet included in national estimates.
COifrom "Unaccounted for" Natural Gas
There is a discrepancy between the amount of natural gas sold by producers and that reported as purchased
by consumers. This discrepancy, known as "unaccounted for" or unmetered natural gas, was assumed to be the sum
of leakage, measurement errors, data collection problems, undetected non-reporting, undetected over reporting, and
undetected under reporting. Historically, the amount of gas sold by producers has always exceeded that reportedly
purchased by consumers; therefore, some portion of unaccounted for natural gas was assumed to be a source of CO2
emissions. In other words, it was assumed that consumers were underreporting their usage of natural gas. In
DOE/EIA's energy statistics for 1996, however, reported consumption of natural gas exceeded the amount sold by
producers. Therefore, the historical explanation given for this discrepancy has tost credibility and unaccounted for
natural gas is no longer used to calculate CO2 emissions.
A-260 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
COi from Shale Oil Production
Oil shale is shale saturated with kerogen.67 ft can be thought of as the geological predecessor to crude oil.
Carbon dioxide is released as a by-product of the process of producing petroleum products from shale oil. As of
now, it is not cost-effective to mine and process shale oil into usable petroleum products. The only identified large-
scale oil shale processing facility in the United States was operated by Unocal during the years 1985 to 1990. There
have been no known emissions from shale oil processing in the United States since 1990 when the Unocal facility
closed. '
CH* from the Production of Carbides other than Silicon Carbide
Methane (CH4) may be emitted from the production of carbides because the petroleum coke used in the
process contains volatile organic compounds, which form CH4 during thermal decomposition. Methane emissions
from the production of silicon carbide were estimated and accounted for, but emissions from the production of
calcium carbide and other carbides were not. Further research is needed to estimate CH4 emissions'from the
production of calcium carbide and other carbides other than silicon carbide. (See Revised 1996IPCC Guidelines for
National Greenhouse Gas Inventories: Reference Manual, pp. 2.20 - 2.21)
CO* from Calcium Carbide and Silicon Carbide Production
Carbon dioxide is formed by the oxidation of petroleum coke in the production of both calcium carbide and
silicon carbide. These CO2 emissions are implicitly accounted for in the storage factor calculation for the non-
energy use of petroleum coke in the Energy chapter. There is currently not sufficient data on coke consumption to.
estimate emissions from these sources explicitly. (See Revised 1996 IPCC Guidelines for National Greenhouse Gas
Inventories: Reference Manual, pp. 2.20 — 2.21)
COi from Graphite Consumption in Ferroalloy and Steel Production
Emissions from "graphite" "wood" or "biomass" in calculating CO2 emissions from ferroalloy production,
iron and steel production or other "Industrial Processes" included in Chapter 4 of the inventory are not explicitly
calculated. It is assumed that 100% of the carbon used in ferroalloy production is derived from petroleum coke and
that all of the carbon used in iron and steel production is derived from coal coke or petroleum coke. It is also
assumed that all of the carbon used in lead and zinc production is derived from coal coke. It is possible that some
non-coke carbon is used in the production of ferroalloys, lead, zinc, and iron and steel, but no data are available to
conduct inventory calculations for sources of carbon other than petroleum coke and coal coke used in these
processes.
. 1
Non-fuel uses 'of coal coke and petroleum coke are accounted for in the Industrial Process chapter, either
directly for iron and steel, aluminum, ferroalloy, lead, zinc, and titanium dioxide production, or indirectly by
applying a storage factor to "uncharacterized" non-fuel uses of petroleum coke and coal coke.Non-fuel uses of wood
and biomass are not accounted for in the Energy or Industrial Process chapters, as'all uses of wood and biomass are
accounted for in the Land Use and Forestry chapter. It is assumed for the purposes of the CO2 emission calculation
that no wood or other biogenic carbon is used in any of these industrial processes. Some biogenic carbon may be
used in these industrial processes but sufficient data to estimate emissions are not available.
Consumption of either natural or synthetic graphite is not explicitly accounted for in the Industrial Process
chapter. It is assumed that all of the carbon used in manufacturing carbon anodes for production of aluminum,
ferroalloys, and electric arc furnace (EAF) steel are derived directly from petroleum coke and coal tar pitch (a coal
coke byproduct), not.from natural graphite or synthetic graphite sources. Some amount of carbon used in these
industrial processes may be derived from natural or synthetic graphite sources, but sufficient data to estimate
emissions are not currently available.
67 Kerogen is fossilized insoluble organic material found in sedimentary rocks, usually shales, which can be converted
to petroleum products by distillation.
A-261
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NzO from Caprolactam Production
Caprolactam is a widely used chemical intermediate, primarily to produce nylon-6. All processes for
producing Caprolactam involve the catalytic oxidation of ammonia, with N2O being produced as a by-product.
Caprolactam production could be a significant source of N2O—it has been identified as such in the Netherlands.
More research is required to determine this source's significance because there is currently insufficient information
available on Caprolactam production to estimate emissions in the United States. (See Revised 1996IPCC Guidelines
for National Greenhouse Gas Inventories. Reference Manual, pp. 2.22 - 2.23)
^ NiO from Cracking of Certain Oil Fractions "
In order to improve the gasoline yield in crude oil refining, certain oil fractions are processed in a
catcracker. Because crude oil contains some nitrogen, N2O emissions may result from this cracking process. There
is currently insufficient data to develop a methodology for estimating these emissions. (See Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories: Reference Manual, p. 2.23)
CH4 from Petroleum Coke Production
Coke production may result in CH4 emissions. Detailed coke production statistics were not available for
the purposes of estimating CH4 emissions from this minor source. (See Petrochemical Production in the Industrial
Processes chapter and the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories: Reference
Manual, p. 2.23).,
COi from Metal Production '
Coke is used as a reducing agent in the production of some metals from their ores, including magnesium,
chromium, , nickel, silicon, and tin. Carbon dioxide may be emitted during the metal's production from the
oxidization of this coke and, in some cases, from the carbonate ores themselves (e.g., some magnesium ores contain
carbonate). The CO2 emissions from the carbonate ores are not presently accounted for, but their quantities are
thought to be minor. (See Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories: Reference
Manual, p. 2.37-2.38)
NjO from Acrylonitrile Production
Nitrous oxide may be emitted during acrylonitrile production. No methodology was available for
estimating these emissions, and therefore further research is needed if these emissions are to be included. (See
Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories: Reference Manual, p. 2.22)
SFi from Aluminum Fluxing and Degassing
- ' Occasionally, sulfur hexafluoride (SF6) is used by the aluminum industry as a fluxing and degassing agent
in experimental and specialized casting operations. In these cases it is normally mixed with argon, nitrogen, and/or
chlorine and blown through molten aluminum; however, this practice is not used by primary aluminum production
firms in the United States and is not believed to be extensively used by secondary casting firms. Where it does
occur, the concentration of SF6 in the mixture is small and a portion of the SF« is decomposed in the process (Waite
and Bernard 1990, Corns 1990). It has been estimated that 230 Mg of SF6 were used by the aluminum, industry in
the United States and Canada (Maiss and Brenninkmeijer 1998); however, this estimate is highly uncertain.
• * *
SFi from Production/Leakage/Breakage of Soundproofed Double-glazed Windows
Sulfur hexafluoride (SF6) may be emitted from the production, breakage, or leakage of soundproof double-
glazed windows. No methodology was available for estimating these emissions, and therefore further research is
needed if these emissions are to be included.
A-262 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
SFifrbm Production/Leakage/Dismantling of Radar, Tracer and Night Vision Equipment
Sulfur hexafluoride (SF6) may be emitted from the production, leakage, and dismantling of radar, tracer,
and night vision equipment. Emissions from this source are believed to be minor, and no data were available for
estimating the emissions.
SFifrom Applications in Sports Shoes, Tires, and Tennis Balls
Sulfur hexafluoride (SF6) may be emitted from application involving the production of sport shoes, tires,
and tennis balls. These emissions are believed to be minor, and no data were available for estimating emissions.
SFifrom Applications to Trace Leakage of Pressure Vessels and Used as a Tracer Gas in Open Air
' Sulfur hexafluoride (SF6) may be emitted from application involving tracer gasses to detect leakage from
pressure vessels and as a tracer gas in the open air. Although emissions from this source are believed to be minor,
emissions estimation data and methodologies were not available.
Miscellaneous SFe Uses
Sulfur hexafluoride may be used in foam insulation, for dry etching, in laser systems, for indoor air quality
testing, for laboratory hood testing, for chromatography, in tandem accelerators, in loudspeakers, in shock absorbers,
and for certain biomedical applications. Data need to be gathered and methodologies developed if these emissions
are to be estimated. A preliminary global assessment of aggregate emissions from these applications can be found in
Maiss, M. Brenninkmeijer, and C.A.M. Brenninkmeijer (1998).
NjO from Domestic House Animal Waste Deposited on Soils
A substantial amount of liquid and solid waste is produced by domestic animals that are kept as pets. A
preliminary methodology was developed to estimate nitrous oxide (N20) emissions from the deposition of domestic
house animal (i.e., dogs and cats) waste on lawns, fields and parks. Estimates calculated with this methodology
suggest that, in 1990, approximately 330 Gg of nitrogen originating as domestic house animal waste were deposited
on soils resulting in approximately 2.9 Tg CO? Eq. of N2O emissions from soils. To estimate the amount of nitrogen
deposited by domestic house animals, only those excretions that remained on (and surfaces—as opposed to wastes
that were collected by owners and are managed as municipal solid waste—were included.
Annual dog and cat population numbers were obtained from the Pet Food Institute.68 Annual nitrogen
excretion rates were estimated from protein intake. The recommended protein intake for an average size adult of
each animal type69 was multiplied by the average amount of nitrogen per unit of protein (0.16 kg N/kg protein, from
the Revised 1996IPCC Guidelines) to estimate nitrogen consumption. It was then assumed that 95 percent of this
nitrogen was excreted, either in solid or liquid form (i.e., it was assumed that 5 percent was retained for fur and milk
production). Of the total nitrogen excretion, 90 percent was assumed to occur through liquid waste, with the balance
from solid waste.70 Both cat and dog populations were divided into urban and rural fractions, using the metropolitan
and non-metropolitan human population categories, respectively, of the U.S. Census Bureau.71 Both liquid and
solid wastes from the urban cat population, and solid waste from the urban dog population were assumed to be
collected (i.e., not deposited on soils). Nitrous oxide emission estimates from domestic house animal excretion were
calculated in the same manner as performed for estimating emissions from livestock excretion. Producing these
estimates involved making a number of simplifying assumptions regarding average animal size and protein
consumption, as well as the proportions of animal populations residing in urban and rural areas and the proportions
68 Pet Food Institute (1999) Pet Incidence Trend Report. Pet Food Institute, Washington DC.
69 Bright, S. (1999) Personal communication between Marco Alcaraz of ICF Consulting and Susan Bright of the
Dupont Animal Clinic, Washington, DC, August 1999.
70 Swenson, M.J. and W.G. Reece, eds. (1993) Duke's Physiology of Domestic Animals. Cornell University Press. 11th
Edition.
71 U.S. Census Bureau (1999)
A-263
-------
of wastes that are deposited on land. Further methodological development and data collection is required in order to
reduce the uncertainty involved in the domestic house animal excretion estimates.
CO] from Non-Hazardous Industrial Waste Combustion
Waste combustion is incorporated in two sections of the energy chapter of the inventory: in the section on
CO2 emissions from waste combustion, and in the calculation of emissions and storage from non-energy uses of
fossil fuels. The former section addresses fossil-derived materials (such as plastics) that are discarded as part of the
municipal wastestream and combusted (generally for energy recovery). The latter addresses two types of
combustion: hazardous waste incineration of organic materials (assumed to be fossil-derived), in which regulated
wastes are burned without energy recovery, and burning of fossil-derived materials for energy recovery. There is
one potentially significant category of waste combustion that is not included in our calculus: industrial non-
hazardous waste, burned for disposal (rather than energy recovery). Data are not readily available for this source;
further research is needed to estimate the magnitude of CO2 emissions.
ChU from Land-Use Changes Including Wetlands Creation or Destruction
Wetlands are a known source of methane (CH4) emissions. When wetlands are destroyed, CH4 emissions
may be reduced. Conversely, when wetlands are created (e.g., during the construction of hydroelectric plants),
emissions may increase. Grasslands and forestlands may also be weak sinks for CHi due to the presence of
methanotrophic bacteria that use CH4 as an energy source (i.e., they oxidize CHi to CO2). Currently, an adequate
scientific basis for estimating these emissions and sinks does not exist, and therefore further research and
methodological development is required.
NjO from Wastewater Treatment and Biological Processes
As a result of nitrification and denitrification processes, nitrous oxide (N2O) may be produced and emitted
from large-scale composting, small scale composting (e.g. households), post-composting of anaerobic digested
wastes, and both domestic and industrial wastewater treatment plants. Nitrogen-containing compounds are found in
composted wastes and wastewater due to the presence of both human excrement and other nitrogen- containing
constituents (e.g. garbage, industrial wastes, animal carcasses, etc.) The portion of emitted N2O that originates from
human excrement is currently estimated under the Human Sewage source category- based upon average dietary
assumptions. The portion of emitted N2O that originates from other nitrogen-containing constituents is not currently
estimated. Further research and methodological development is needed if these emissions are to be accurately
estimated.
Cm from Large and Small Scale Composting
Methane (CH4) may be released through large and small scale (e.g. household) composting. Detailed
composting data is necessary in order to estimate emissions but were not available. .
ChU from Treatment of Dredging Sludge, Remediation of Groundwater, Intermediate Storage of Slaughter
Waste, Production of Process Water from Groundwater, and Post Composting of Anaerobic Digested Wastes
Methane (CH4) may be released through the treatment of dredging sludge, remediation of groundwater,
intermediate storage of slaughter waste, production of process water from groundwater, and post composting of
anaerobic digested wastes. No methodology was available for estimating these emissions, and therefore further
research is needed if these emissions are to be included.
References
Census (2002) Industrial Gases: 2001. U.S. Census Bureau, Department of Commerce, Washington, DC.
MQ325C(01)-5.
EIA (2002) Emissions of Greenhouse Gases in the United States 2001. Energy Information Administration,
Office of Integrated Analysis and Forecasting. DOE-EIA-0573(2001).
A-264 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
EPA (2000) Toxics Release Inventory, 1998. U.S. Environmental Protection Agency, Office of
Environmental Information, Office of Information Analysis and Access, Washington, DC. Available online at
.
Freedonia Group, Inc. (2000) Report 1091: Industrial Gases To 2003, Record 4, Carbon Dioxide
Shipments and Production, 1989-2009. Cleveland, OH.
A-265
-------
-------
ANNEX 6 Additional Information
6.1. Global Warming Potential Values
Global Warming Potentials (GWPs) are intended as a quantified measure of the globally averaged relative
radiative forcing impacts of a particular greenhouse gas. It is defined as the cumulative radiative forcing—both
direct and indirect effects—integrated over a period of time from the emission of a unit mass of gas relative to some
reference gas (IPCC 1996). Carbon dioxide (CO2) was chosen as this reference gas. Direct effects occur when the
gas itself is a greenhouse gas. 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 relationship between gigagrams (Gg) of a gas and
Tg CO2 Eq. can be expressed as follows:
= (Ggofgas)x(GWP)x| 1B I
Where,
Tg CO2 Eq. ' = Teragrams of Carbon Dioxide Equivalents
Gg = Gigagrams (equivalent to a thousand metric tons)
GWP = Global Warming Potential •
Tg = Teragrams
GWP values allow policy makers to compare the impacts of emissions and reductions of different gases.
According to the IPCC, GWPs typically have an uncertainty of roughly ±35 percent, though some GWPs have larger
uncertainty than others, especially those in which lifetimes have not yet been ascertained. In the following decision,
the parties to the UNFCCC have agreed to use consistent GWPs from the IPCC Second Assessment Report (SAR),
based upon a 100 year time horizon, although other time horizon values are available (see Table A-209).
In addition to communicating emissions in units of mass, Parties may choose also to use global
•warming potentials (GWPs) to reflect their inventories and projections in carbon dioxide-equivalent terms,
using information provided by the Intergovernmental Panel on Climate Change (IPCC) in its Second
Assessment Report. Any use of GWPs should be based on the effects of the greenhouse gases over a 100-
year time horizon. In addition. Parties may also use other time horizons. ^
Greenhouse gases with relatively long atmospheric lifetimes'(e.g., CO2, CH4, N2O, MFCs, PFCs, and SFS)
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, other indirect
greenhouse gases (e.g., NO,, and NMVOCs), and tropospheric aerosols (e.g., SO2 products and black carbon),
however, vary spatially, and consequently it is difficult to quantify their global radiative forcing impacts. GWP
values are generally not attributed to these gases that are short-lived and spatially inhomogeneous in the atmosphere.
Table A-209: Global Warming Potentials IGWP) and Atmospheric lifetimes (Yean) olGnesOsed la mis Ropert
Gas Atmospheric Lifetime 1 00-year GWP'
Carbon dioxide (C02)
Methane (CH4)b
Nitrous oxide (NjO)
HFC-23
50-200
12±3
120
264
1
21
310
11,700
20-yearGWP
1
56
280
' 9,100
500-year GWP
1
6.5
170
9,800
• , 72 Framework Convention on Climate Change; FCCC/CP/1996/15/Add.l; 29 October 1996; Report of the Conference
of the Parties at its second session; held at Geneva from 8 to 19 July 1996; Addendum; Part Two: Action taken by the Conference
of the Parties at its second session; Decision 9/CP.2; Communications from Parties included in Annex I to the Convention:
guidelines, schedule and process for consideration; Annex: Revised Guidelines for the Preparation of National Communications
by Parties Included in Annex I to the Convention; p. 18. FCCC (1996)
' A-267
-------
HFC-125
HFC-1343
HFC-143a
HFC-152a
HFC-227ea
HFC-236fa
HFC-4310mee
CF4
C2F«
C«Fio
CeFu
SF«
32.6
14.6
48.3
1.5
36.5
209
17.1
50,000
. 10,000
2,600
3,200
3,200
2,800
1,300
3,800 '
140
2,900
6,300
1,300
6,500
9,200
7,000
7,400
23,900
4,600
3,400
5,000
460
4,300
5,100
3,000
4,400
•6,200
4,800
5,000
16,300
920
420
1,400
42
950
4,700
' 400
10,000
14,000
10,100
10,700
34,900
Source: IPCC (1996)
• GWPs used in this report are calculated over 100 year time horizon
b The methane GWP includes the direct effects and those indirect effects due to the production of tropospheric ozone and stratospheric water vapor. The indirect
effect due to the production of CO: is not included,
Table A-210 presents direct and net {i.e., direct and indirect) GWPs for ozone-depleting substances
(ODSs). Ozone-depleting substances directly absorb infrared radiation and contribute to positive radiative forcing;
however, their effect as ozone-dcplctcrs also leads to a negative radiative forcing because ozone itself is a potent
greenhouse gas. There is considerable uncertainty regarding this indirect effect; therefore, a range of net GWPs is
provided for ozone depleting substances.
Table ft-ZlO: Net 100-year Global Wamlnii Potentials lor Select Ozone DooletlnB Substances'
Gas
CFC-11
CFC-12
CFC-113
HCFC-22
HCFC-123
HCFC-124
HCFC-141b
HCFC-142b
CHCIa
ecu
CHaBr
Halort-1211
Halon-1301
Direct
4,600
10,600
6,000
1,700
120
620
700
2,400
140
1,800
5
1,300
6,900
Netmln
' (600)
7,300
• 2,200
1,400
20
480
• (5)
1,900
(560)
(3,900)
(2,600)
(24,000)
(76,000)
NeW
3,600
9,900
5,200
1,700
100
590
570
2,300
0
660
(500)
(3,600)
(9,300)
Source- IPCC (2001)
* Because these compounds have been shown to deplete stratospheric ozone, they are typically referred to as ozone depleting substances (ODSs). However, they
are also potent greenhouse gases. Recognizing the harmful effects of these compounds on the ozone layer, in 1987 many governments signed the Montreal Protocol
on Substances that Deplete the Ozone Layer to limit the production and importation of a number of CFCs and other halogenated compounds. The United States
furthered its commitment to phase-out ODSs by signing and ratifying the Copenhagen Amendments to the Montreal Protocol in 1992. Under these amendments, the
United States committed to ending the production and importation of halons by 1994, and CFCs by 1996. The IPCC Guidelines and (he UNFCCC do not include
reporting instructions for estimating emissions of ODSs because their use is being phased-out under the Montreal Protocol. The effects of these compounds on
radiative forcing are not addressed in this report
The IPCC has published its Third Assessment Report (TAR), providing the most current and
comprehensive scientific assessment of climate change (IPCC 2001). Within this report, the GWPs of several gases
were revised relative to the IPCC's Second Assessment Report (SAR) (IPCC 1996), and new GWPs have been
calculated for an expanded set of gases. Since the SAR, the IPCC has applied an improved calculation of CO2
radiative forcing and an improved COj response function (presented in WMO 1999). The GWPs are drawn from
WMO (1999) and the SAR, 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. Because the revised
radiative forcing of CO2 is about 12 percent lower than that in the SAR, the GWPs of the other gases relative to CO2
tend to be larger, taking into account revisions in lifetimes. However, there were some instances in which other
variables, such as the radiative efficiency or the chemical lifetime, were altered that resulted in further increases or
decreases in particular GWP values. In addition, the values for radiative forcing and lifetimes have been calculated
for a variety of halocarbons, which were not presented in the SAR. The changes are described in the TAR as
follows:
A-268 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
New categories of gases include fluorinated organic molecules, many of which are ethers that are
proposed as halocarbon substitutes. Some of the GWPs have larger uncertainties than that of others,
particularly for those gases where detailed laboratory data on lifetimes are not yet available. The direct GWPs
have been calculated relative to CO2 using an improved calculation of the CO2 radiative forcing, the SAR
response Junction for a CO} pulse, and new values for the radiative ^forcing and lifetimes for a number of
halocarbons.
-v
Table A- 211 compares the lifetimes and GWPs for the SAR and TAR. As can be seen in Table A- 211,
GWPs changed anywhere from a decrease of 35 percent to an increase of 49 percent.
Table A- 211: Comparison of GWPs and lifetimes uud ID the SAR and die TAR
Gas
Carbon dioxide (COz)
Methane (CH*)"
Nitrous oxide (NzO)
Hydrofluorocarbons
HFC-23
HFC-32
HFC-41
HFC-125
HFC-134
HFC-1348
HFC-143
HFC-1433
HFC-152
HFC-152a
HFC-161
HFC-227ea
HFC-236cb
HFC-236ea
HFC-236fa
HFC-245ca
HFC-245fa
HFC-365mfc
HFC-4310mee
lodocarbons
FIC-1311
Fully Fluorinated Species
SFe
CF<
CZF»
CjFg
C«Fio
C-C4F8
CsFtt
C«F,4
Ethers and Halogenated Ethers
CHsOCHs
(CF&CFOCHs
(CFa)CH20H
CF3CF2CHZOH
(CF3)2CHOH
HFE-125 '
HFE-134
HFE-143a
HCFE-235da2
HFE-245cb2
HFE-245fa2
HFE-254cb2
HFE-347mcc3
Lifetime (years)
SAR
50-200
12±3
TAR
5-2001
8.4/12'
120 120/1 14 e
264
5.6
3.7
32.6
10.6
14.6
• 3.8
48.3
NA
1.5
NA
36.5
NA
NA
209
6.6
NA
'NA
17.1
<0.005
3,200
50,000
10,000
2,600
2,600
3,200
4,100
3,200
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
260
5.0
2,6
29
9.6
13.8
3.4
52
0.5
1.4
0.3
33.0
13.2
10
220
5.9
7.2
9.9
15
0,005
3,200
50,000
10,000
2,600
2,600
3,200
4,100
3,200
0.015
3.4
0.5
0.4
1.8
150
26.2
4.4
2.6
4.3
4.4
0.22
4.5
SAR
1
21
310
11,700
650
150
2,800
1,000
1,300
300
3,800 .
NA
140
NA
2,900
NA
NA
6,300
560
NA
NA
1,300
<1
23,900
6,500
9,200
7,000
7,000
8,700
7,500
7,400
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
GWP (100 year)
TAR
1
23
296
12,000
550
97
3,400
1,100
1,300
330
4,300
43 •
120
12
3,500
1.300
1,200
9,400
640
950
890
1,500
1
22,200
5,700
11.900 '
8,600 '
8,600
10,000
8,900
9,000
1
330
57
40
190
14,900
6.100
750
340
5SO
570
30
480
Difference
NC
2
(14)
300
(100)
(53)
600
100
NC
30
500
NA
' (20)
NA
600
NA
NA ,
3,100
80
NA
NA
200
NC
(1,900)
(800)
2,700
1,600
1,600
1,300
1,400
1,600
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NC
10%
(5%)
3%
(15%)
(35%)
21%
10%
NC
10%
13%
NA
(14%)
NA
21%
NA
NA
49%
- 14%
NA
NA
15%
NC
(7%)
(12%)
29%
23%
23%
15%
19%
22%
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
A-269
-------
HFE-356pcl3
HFE-374pcf2
HFE-7100
HFE-7200
H-Galden 1040x
HG-10
HG-01
Other^
NFj
SFsCFj
C-C3F,
HFE-227ea
HFE-236ea2
HFE-236fa
HFE-245fa1
HFE-263(b2
HFE-329mcc2
HFE-338mcf2
HFE-347-mcf2
HFE-356mec3
HFE-356pcc3
HFE-356pcf2
HFE-365mcf3
(CFj)2CHOCHFj
(GFj)2CHOCHi
-(CFz>4CH(OH)-
NA
NA
NA
NA ,
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA '
NA
NA
NA
NA
NA
NA
3.2
. 5.0
5.0
0.77
6.3
12.1
6.2
740
>1,000
>1,000
11
5.8
3.7
2.2
0.1
6.8
4.3
2.8
0.94
0.93
2.0
0.11
3.1
0.25
0.85
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
430
540
390
55
1,800
2,700
1,500
10,800
>17,500
>16,800
1,500
960
470
280
11
890
540
360
98
110
260
11
370
26
70
NA
NA
NA
NA
' NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
' NA
NA
.NA
' NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
NA
> No single lifetime can be determined for carbon dioxide. (See IPCC 2001)
b The methane GWP Includes the direct effects and those indirect effects due to the production of (ropospheric ozone and stratospheric water vapor. The Indirect
effect due to the production of CQi is not included.
e Methane and nitrous oxide have chemical feedback systems that can alter the length of the atmospheric response, in ttiese cases, global mean atmospheric
lifetime (LT) is given first, followed by perturbation time (PT).
«Gases whose lifetime has been determined only via indirect means or for whom there is uncertainty over the loss process.
Source: IPCC (2001)
NC (No Change)
NA (Not Applicable)
When the GWPs from the TAR are applied to the emission estimates presented in this report, total
emissions for the year 2004 are 7,107.9 Tg CO2 Eq., as compared to 7,074.4 Tg CO2 Eq. when the GWPs from the
SAR are used (a 0.5 percent difference). Table A-212 provides a detailed summary of U.S. greenhouse gas
emissions and sinks for 1990 through 2004, using the GWPs from the TAR. The adjusted greenhouse gas emissions
are shown for each gas in units of Tg CO2 Eq. in Table A-213. The correlating percent change in emissions of each
gas is shown in Table A-214. The percent change in emissions is equal to the percent change in the GWP, however,
in cases where multiple gases are emitted in varying amounts the percent change is variable over the years, such as
with substitutes for ozone depleting substances. Table A-215 summarizes the emissions and resulting change in
emissions using GWPs from the SAR or the TAR for 1990 and 2004.
Table A-212: Recent Trends In DA Graenhaase Gas Emissions and Sinks using tnaTM GWPs (ig CO, EoJ
Gas/Source
C02
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Flaring
Cement Manufacture
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and Consumption
Carbon Dioxide Consumption
Waste Combustion
Titanium Dioxide Production
Aluminum Production
Iron and Steel Production
Ferroalloys
1996
5,620.2
5,271.8
152.8
6.6
39.2
13.9
7.4
4.3
. 0.9
17.1
1.8
6.4
67.7
2.0
1999
5,695.0
5,342.4
160.6
6.9
40.0
13.5
8.1
4.2
0.8
17.6
1.9
6.5
63.8
2.0
2000
5,864.5
5,533.7
140.7
5.8
41.2
13.3
6.0
4.2
1.0
17.9
1.9
6.2
65.3
1.7
2001
5,795.2
5,486.9
131.0
6.1
41.4
12.8
5.7
4.1
0.8
18.6
1.9
4.5
57.8
1.3
2002
5,815.9
5,501.8
136.5
6.2
42.9
12.3
5.9
4.1
1.0
18.9
2.0
4.6
54.6
1.2
2003
5,877.7
5,571.1
133.5
6.1
43.1
13.0
4.7
4.1
1.3
19.4
2.0-
4.6
53.3
1.2
2004
5,988.0
5,656.6
153.4
6.0
45.6
13.7
6.7
4.2
1.2
19.4
23
4.3
51.3
1.3
A-270 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Ammonia Manufacture . 19.3]
Phosphoric Acid Production 1.5l
Petrochemical Production 2.2t
Silicon Carbide Consumption 0.1 [
Lead Production 0.3|
Zinc Production ' 0.9J
Land-Use Change and Forestry (Sink)> (910.4)\
International Bunker Fusts? 113,51
Biomass Combustion 216.1
CH* 676.91
Stationary Sources 8.61
Mobile Sources . 5.2|
Coal Mining - . • 89.71
Abandoned Coal Mines 6.6l
, Natural Gas Systems 138.81
Petroleum Systems 37.71
Petrochemical Production 1.3|
Silicon Carbide Produ ction
Iron and Steel Production ' 1.4|
Enteric Fermentation 129.1]
Manure Managemenl 34.11
Rice Cultivation 7.8J
Agricultural Residue Burning 0.&I
Landfills 188.71
Wastewater Treatment 27.11
International Bunker Fuels'1 0.2\
NjO , 377.01
Stationary Source * 11.71
Mobile Sources 41.51
AdipicAcid 14.51
Nitric Acid 17.0J
Manure Management 15.5J
Agricultural Soil Management ' 254.11
Agricultural Residue Burning 0.4l
Human Sewage • - ' 12.31
NjO Product Usage 4.1 [
Waste Combustion 0.51
Settlements Remaining Settlements 5.41
Forest Land Remaining Forest Land 0.1 [
International Bunker Fuels" 0.9\
MFCs, PFCs, and SFs 87.8|
Substitution of Ozone Depleting Substances
Aluminum Production 17.11
HCFC-22 Production 35.91
Semiconductor Manufacture 3.2J
Electrical Transmission and Distribution11 26.61
Magnesium Production and Processing" 5.0|
Total
6.147.11
21.9
1.6
3.0
0.2
0.3
-1.1
(744,0)
114.6
217.2
634,7
7.5
4.2
68.8
7,5
137.4
32.5
1.8
1.3
127.9
42.5
8.7
0.9
158.1
35.7
0.2
420.7
12.8
52.3
5.7
19.9
16.6
287.5
0,4
14.2
4.6
0.4
5,9
0.3
1,0
130.5
52,0
8.4
41.2
8.0
15.5
5.4
6,806.0
20.6
1.5
3.1
0.1
0.3
1.1
(765.7)
105.2
222.3
623.2
7.7
4.0
64.6
7.6
133.3
31.2
1.9
1.3
127,9
41.8'
9.1
0.8
155.1
36.9
0.1-
400.4
12.8
51.6
5.2
19.2
16.6
268.5
0.4
14.7
4.6
0.4
5.9
0.4
0.9
128.2
60.1
8.3
31.2
8.1
14.9
5.6
6,846.8
196
1.4
3.0
0.1
0.3
1.1
(759.5)
' 101.4
" 226.8
620.9
7.9
3.8
61.6
7,9
138,7
30,5
1.8
1.3
126.7
41.7
. 8.2
0.9
152.2
37.6
0.1
397.4
13.3
, - 50.7
5.8
18.7
17.0
.265,6
0.4
• ' 14.8
4.6
0.4-
5.7
- 0.3
0.9
131.6
68.6
8.2
' 30.6
7.0
14.2
3.0
7,014.4
16.7
1.3
2.8
0.1
0.3
1.0
(768.0)
97.8
200.5
613.6
7.3
3.7
60.8
7,2
137.6
30.0
1.6
1.2
125.6
42.6
•8.4
0.8
149.1
38.0
0.1
394.2
12.9
47.7
4.7
15.2
17.3
270.2
0.4
14.9
4.6
0.4
5.6
0.4
0.8
122.0
76.3
3.7
20,3
5.0
14.3
2.4
6,925.0
18.5
1.3
2.9
0,1
0.3
0.9
(768.6)
89.5
194.4
613.1
6.8
3.5
57.5
6.6
137.3
29.3
1.7
1.1
125.6
43.0
7.5 '
0.8
153.2
39.2
0.1
389.0
12.6
45.4
5.6
16.4
17.2
265.3
0.4
- 14.9
4.6
0.5
5.7
0.4
0.8
130.2 '
84.0
' 4.9
20.3
5.1
13.5
2.4
6,948.2
15.3
1.4
2.8
0.1
0.3
0.5
(774.8)
84. 1
202.1
618.1
7.2
3.3
60.1
6.4
136.6
28.4
1.7
1.1
126.1
42.9
7.6
0.9
156.0
N 40.1
0.1
368.6
12.9
42.8
5.9
16.0
16.7
247.5
0.4
15.1
4.6
0.5
5.9
0.4
0.7
128.7
91.6
3.5
- 12.7
5.1
13.0
2.8
6,993.1
16.9
1.4
2.9
0.1
0.3
0.5
(780,1)
94.5
211.2
609.8
, 7.1
3.2
61.7
6.2
130.1
28.1
1.8
1.1
123.3
43.1
8.3
1.0
154.3
40.4
0.1
369.2
13.1
40.9
5.5
15.9
16.9
249.7
0.5
15.3
4.6
0.5
6.2
0.4
0.8
140.9
101.4
2.7
16.0
5.4
12.8
2.5
7,107.9
Parentheses indicate negative values (or sequestration).
+Does not exceed 0.05 Tg CO: Eq.
• Sinks are only included in net emissions total, and are based partially on projected activity data
b Emissions from International Bunker Fuels and Biomass Combustion are not included in totals.
"HFC-23 emitted
' Emissions from HFC-23. CF<, CzF6, CjF», SF,, and trie addition of NFj
•SF. emitted
Note: Totals may not sum due to independent rounding.
TaDIa A-213: Change In 0.1 Greenhouse Gas Emissions and Sinks Using TAB vs. SAB fiWPs (Tg CO* EoJ
Gas
COj
cm
N20
HFCs,PFCs.andSFo* .
1998
NC
55.2
(19.9)
(2-9)
1999
NC
54.2
(18.9)
(3.3)
2000
NC
54.0
(18.8)
(3-D
2001
NC
53.4
(18.6)
(2.8)
2002
NC
53.3
(18.4)
(25)
2003
NC
53.7
(17.4)
(2.3)
2004
NC
53.0
(17.5)
(2.1)
A-271
-------
Total
31.9
32.1
31.9 32.4
34.0
33.5
NC (No change)
•Includes NF3
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Table ft-ZM: Change In O.S. Greenhouse Gas Emissions Using TAR vs. SAR GWPs tPercemJ
Gas/Source
COz
CH4
N20
MFCs, PFCs, and SF8
Substitution of Ozone Depleting Substances
Aluminum Production1 ••
HCFC-22 Production"
Semiconductor Manufacture'
Electrical Transmission and Distribution'1
Magnesium Production and Processing**
Total
(3.2%)
(98.6%)
(7.2%)
2.6%
11.6%
(7.1%)
1998
NC
9.5%
(4.5%)
(2.2%)
(4.6%)
(7.9%)
2.6%
11.9%
(7.1%)
(7.1%)
0.5%
1999
NC
9.5%
(4,5%)
(2.5%)
(4.3%)
(7.9%)
2.6%
11.9%
(7.1%)
(7.1%)
0.5%
2000
NC
9.5%
(4.5%)
(2.3%)
(3.6%)
(8.1%)
2.6%
11.6%
(7.1%)
(7.1%)
0.5%
2001
NC
9.5%
(4.5%)
(2.2%)
(3.0%)
(6.8%)
2.6%
12.7%
(7.1%)
(7.1%)
0.5%
2002
NC
9.5%
(4.5%)
(1.9%)
(2.6%)
(6.8%)
2.6%
18.1%
(7.1%)
(7.1%)
0.5%
2003
NC
" 9.5%
(4.5%)
(1.8%)
(2.0%)
(6.6%)
2.6%
16.4%
(7.1%)
(7.1%)
0.5%
2004
NC
• 9.5%
(4.5%)
(1.5%)
(1.8%)
(6.0%)
2.6%
15.4%
(7.1%)
(7.1%)
0.5%
NC (No change)
1 RFC emissions from CF4 and Cft
"HFC-23 emitted
• Emissions from HFC-23, CF,, C2F«, C3F.. SF,, and the addition of NFj
"SFe emitted
Note: Excludes Sinks. Parentheses indicate negative values.
Table A-215: Effects on U.S. Greenhouse Gas Emissions using TAR vs. SM GWPS ffg CO.iq.)
Ga»
Trend from 1990 to 2004
SAR TAR
Revisions to Annual Estimates
1990 2004
C02
CH4
N20
MFCs, PFCs, and SF«*
Total
Percent Change
982.7
(61.3)
(8.2)
52.2
965.4
15.8%
982.7
(67.2)
(7-8)
53.0
960.8
15.6%
NC
58.9
(17.8)
(2.9)
38.1
0.6%
NC
53.0
(17.5)
(2.1)
33.5
05%
NC (No Change)
•Includes NF3
Note: Totals may not sum due to independent rounding. Excludes Sinks. Parentheses indicate negative values.
Overall, these revisions to GWP values do not have a significant effect on U.S. emission trends, as shown
in Table A-213 and Table A-214. Table A-216 below shows a comparison of total emissions estimates by sector
using both the IPCC SAR and TAR GWP values. For most sectors, the change in emissions was minimal. The effect
on emissions from waste was by far the greatest (8.4 percent in 2004), due the predominance of CRt emissions in
this sector. Emissions from all other sectors were comprised of mainly CO2 or a mix of gases, which moderated the
effect of the changes.
Table A-216: Comparison el Emissions by Sector using IPCC SAR and TAR GWP Values CTg CO.Erj.)
Sector
1990
Energy
SAR GWP (Used in Inventory)
TAR GWP
Difference (%)
Industrial Processes
SAR GWP (Used in Inventory)
TAR GWP
Difference (%)
Solvent and Other Product Use
SAR GWP (Used in Inventory)
TAR GWP
Difference (%)
Agriculture
SAR GWP (Used in Inventory)
5,148.3
5,170.7
0.4%!
1998
1999
2000
2001
2002
2003
2004
5,752.3
5,771.6
0.3%
5,822.3
5,840.8
0.3%
5,994.3
6,013.0
0.3%
5,931.6
5,950.1
0.3%
5,944.6
5,962.8
0.3%
6,009.8
6,028.1
0.3%
6,108.2
6,126.2
03%
439.6
335.1
331.2
(1.2%)
4.8
4.6
(4.5%)
483.2
327.5
323.3
(1.3%)
4.8
4.6
(4.5%)
463.1
329.6
325.6
(1.2%)
4.8
4.6
{4.5%}
458.4
300.7
297.2
(1.2%)
4.8
4.6
(4.5%)
463.4
310.9
307.6
d-1%)
4.8
4.6
(4.5%)
457.8
304.1
301.0
(1.0%)
4.8
4.6
(4.5%)
439.1
320.7
317.8
(0.9%)
4.8
4.6
(4.5%)
440,1
A-272 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
TARGWP
Difference (%)
Land Use, Land-Use Change, and
Forestry
SARGWP (Used in Inventory)
TARGWP,
Difference {%)
Waste
SAR GWP (Used in Inventory)
TAR GWP
Difference (%)
Net Emission* (Sources and Sinks)
SAR GWP (Used in Inventory)
TARGWP
Difference (%)
441.7IH
0.5%B
1
I
, (904J)B
(905.0)B
+l
•
2io.oH|
228 2H
' 8.7%B|
^H
5.198.6H
• • 5.236.7B
0.7%B
I 484.5
0.3%
(737.5)
(737.8)
-h
191.8
208.0
I 8.4%
i 6,029.6
i 6,062.0
i 0.5%
465,2
0.5%
(759.0)
(759.3)
•«-
190.7
206.7
8.4%
6,049.2
6,081.1
0.5%
460.5
0.4%
(753.1)
(753.4)
-h
188.8
204.7
8.4%
6,222.8
6,254.9
0.5%
465.2
0.4%
(761.8)
(762.0)
+
186.4
202.0
8.4%
6,125.1
6,157.0
0.5%
459.8
0.4%
(762.2)
(762.5)
-h
191.3
207.3
8.4%
6,147.2
6,179.5
0.5%
442.0
0.7%
(768.3)
(768.6)
•f
{
•194.8
211.2
' 8.4%
6,184.3
. 6,218.3
0.5%
442.8
0.6%
(773,3)
(773.6)
+
193.8
210.0
8.4%
6,294.3
6,327.8
0.5%
NC (No change)
+Does not exceed 0.05 7g CO: Eq.
Note: Totals nay not sum due to independent rounding. Parentheses indicate negative values.
A-273
-------
6.2. Ozone Depleting Substance Emissions
Ozone is present in both the stratosphere,73 where it shields the earth from harmful levels of ultraviolet
radiation, and at lower concentrations in the troposphere,74 where it is the main component of anthropogenic
photochemical "smog." Chlorofluorocarbons (CFCs), halons, carbon tetrachloride, methyl chloroform, and
hydrochlorofluorocarbons (HCFCs), along with certain other chlorine and bromine containing compounds, have
been found to deplete the ozone levels in the stratosphere. These compounds are commonly referred to as ozone
depleting substances (ODSs), If left unchecked, stratospheric ozone depletion could result in a dangerous increase
of ultraviolet radiation reaching the earth's surface. In 1987, nations around the world signed the Montreal Protocol
on Substances that'Deplete the Ozone Layer, This landmark agreement created an international framework for
limiting, and ultimately eliminating, the production of most ozone depleting substances. ODSs have historically
been used in a variety of industrial applications, including refrigeration and air conditioning, foam blowing, fire
extinguishing, as an aerosol propellant, sterilization, and solvent cleaning.
In the United States, the Clean Air Act Amendments of 1990 provide the legal instrument for
implementation of the Montreal Protocol controls. The Clean Air Act classifies ozone depleting substances as
either Class 1 or Class 11, depending upon the ozone depletion potential (ODP) of the compound.75 The production
of CFCs, halons, carbon tetrachloride, and methyl chloroform—all Class I substances—has already ended in the
United States. However, large amounts of these chemicals remain in existing equipment,76 and stockpiles of the
ODSs are used for maintaining the equipment. In addition, U.S. regulations require the recovery of ODSs in order
to minimize "venting" to the atmosphere. As a result, emissions of Class I compounds will continue, albeit in ever
decreasing amounts, for many more years. Class II designated substances, all of which are
hydrochlorofluorocarbons (HCFCs), are being phased out at later dates because they have lower ozone depletion
potentials. These compounds serve as interim replacements for Class I compounds in many industrial applications.
The use and emissions of HCFCs in the United States is anticipated to increase over the next several years as
equipment that use Class I substances are retired from use. Under current controls, however, the production for
domestic use of all HCFCs in the United States will end by the year 2030.
In addition to contributing to ozone depletion, CFCs, halons, carbon tetrachloride, methyl chloroform, and
HCFCs are also potent greenhouse gases. However, the depletion of the ozone layer has a cooling effect on the
climate that counteracts the direct warming from tropospheric emissions of ODSs. Stratospheric ozone influences
the earth's radiative balance by absorption and emission of longwave radiation from the troposphere as well as
absorption of shortwave radiation from the sun, overall, stratospheric ozone has a warming effect.
The IPCC has prepared both direct GWPs and net (combined direct warming and indirect cooling) GWP
ranges for some of the most common ozone depleting substances (IPCC 1996). See Annex 6,1 for a listing of the
net GWP values for ODS.
Although the IPCC emission inventory guidelines do not require the reporting of emissions of ozone
depleting substances, the United States believes that no inventory is complete without the inclusion of these
compounds. Emission estimates for several ozone depleting substances are provided in Table A- 217.
Tattle a- m-. Emissions of damn Depleting Substances (Ggl
Compound 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
73 The stratosphere is the layer from the top of the troposphere up to about 50 kilometers. Approximately 90 percent of
atmospheric ozone is within the stratosphere. The greatest concentration of ozone occurs in the middle of the stratosphere, in a
region commonly called the ozone layer.
74 The troposphere is the layer from the ground up to about 11 kilometers near the poles and 16 kilometers in
equatorial regions (i.e., the lowest layer of the atmosphere, where humans live). It contains roughly 80 percent of the mass of all
gases in the atmosphere and is the site for weather processes including most of the water vapor and clouds.
75 Substances with an ozone depletion potential of 0.2 or greater are designated as Class 1. All other substances that
may deplete stratospheric ozone but which have an ODP of less than 0.2 are Class II.
76 Older refrigeration and air-conditioning equipment, fire extinguishing systems, meter-dose inhalers, and foam
products blown with CFCs/HCFCs may still contain ODS.
(
. A-274 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Class 1
CFC-11
CFC-12
PFP.H^
CFC-114
CFC-115
Methyl Chloroform
Halon-1211
Halon-1301
Class II
HCFC-22
HCFC-123
HCFC-124
HCFC-141b
HCFC-142b
HCFC-225ca/cb
29,0
341.7
777
12.9
11.4
1 R
6.1
NA
0.9
15.2
+ /-
+
0.2
1.0
+
29.8
345.2
7Q^
9.2
11.8
4 7
6.2
NA
'0.9
16.3
- +
-1-
0.2
1.6
13.3
341.1
717
5.5
11.3
1 A
5.7
NA
0.9,
16.9
+
-*
0.2
2.2
12.4
327.2
679
1.5
10.5
1 n
5.2
NA
0.9
17.6
0.2'
0.3
2.8
11.3
267.9
AS 7
1.5
9.9
n?
4,0
NA
0.9
19.3
4-
0.3
'0.5 •
2.4
10.1
209.1
^*t 1
1.4
8.9
(\A
2.0
NA
0.9
21.0
+
0.4
0.6
1.8
8.6
182.7
1.4
7.4
0.2
NA
0.8
22.6
-t-
0.4 .
0.8
1.2
8.1
159.0
1.5
6.1
+
NA
0.8
24.1
+
0,5
0.9
1.3
7.6
131.1
1.3
4.6
+
NA
0.8
25.6
+
0.6
1.0
1.4
+
7.0
110.0
0,6
4.1
+
NA
0.8
26.9
-*-
0.6
1.1
1.4
10.5
93.1
0.5
3.8
+
NA
0.8
30.1
0.1
0.6
1.1
1.5
10.0
75.6
0.3
3.5
+
NA
0,7
31.1
0.1
0.6
1.1
1.5
9.6
-61.3
0.1
3.2
+
NA
0.7
31.8
0.1
0.5
1.0
•1.6
9.1
47.3
4-
2.9
+
NA
0.7
32.3
0.1
0.5
0.9
•1.6
8.5
33.4
+
2.7
+
NA
'0.7
.32.8
0,1
0.5
0.8
•1.7
i+
> Does not exceed 0.05 Gg
t
Methodology and Data Sources . .
Emissions of ozone depleting substances were estimated using the EPA's Vintaging Model. The model,
named for its method of tracking the emissions of annual "vintages" of new equipment that enter into service, is a
"bottom-up" model. It models the consumption of chemicals based on estimates of the quantity of equipment or
products sold, serviced, and retired each year, and the amount of the chemical required to manufacture and/or
maintain the equipment. The Vintaging model makes use of this market information to build an inventory of the in-
use stocks of the equipment in each of the end-uses. Emissions are estimated by applying annual leak rates, service
emission rates, and disposal emission rates to each population of equipment. By aggregating the emission and
consumption output from the different end-uses, the model produces estimates of total annual use and emissions of
each chemical. Please see Annex 3.8 of this Inventory for a more detailed discussion of the Vintaging Model.
Uncertainties
Uncertainties exist with regard to the levels of chemical production, equipment sales, equipment
characteristics, and end-use emissions profiles that are used by these models. Please see the ODS Substitutes section
of this report for a more detailed description of the uncertainties that exist in the Vinlaging Model.
References
EPA (2004) Air -Emissions Trends—Continued Progress Through 2003. U.S. Environmental Protection
Agency^ Washington DC. Available online at . November 27,
2004.
EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP
andEPAOAQPS. December 22,2003.
A-275
-------
6.3. Sulfur Dioxide Emissions
Sulfur dioxide (SO2), emitted into the atmosphere through natural and anthropogenic processes, affects the
Earth's radiative budget through photochemical transformation into sulfate aerosols that can (1) scatter sunlight back
to space, thereby reducing the radiation reaching the Earth's surface; (2) affect cloud formation; and (3) affect
atmospheric chemical composition (e.g., stratospheric ozone, by providing surfaces for heterogeneous chemical
reactions). The overall effect of SO2-derived aerosols on radiative forcing is believed to be negative (1PCC 1996).
However, because SO2 is short-lived and unevenly distributed through the atmosphere, its radiative forcing impacts
are highly uncertain. Sulfur dioxide emissions have been provided below in Table A-218.
The major source of SO2 emissions in the United States is the burning of sulfur containing fuels, mainly
coal. Metal smelting and other industrial processes also release significant quantities of SO2. The largest
contributor to U.S. emissions of S02 is electricity generation, accounting for 61 percent of total SO2 emissions in
2004 (see Table A-219); coal combustion accounted for approximately 92 percent of that total. The second largest
source was industrial fuel combustion, which produced 7 percent of 2004 SO2 emissions. Overall, SO2 emissions in
the United States decreased by 34 percent from 1990 to 2004. The majority of this decline came from reductions
from electricity generation, primarily due to increased consumption of low sulfur coal from surface mines in western
'states.
Sulfur dioxide is important for reasons other than its effect on radiative forcing. It is a major contributor to
the formation of urban smog and acid rain. As a contributor to urban smog, high concentrations of SO2 can cause
significant increases in acute and chronic respiratory diseases. In addition, once SO2 is emitted, it is chemically
transformed in the atmosphere and returns to earth as the primary contributor to acid deposition, or acid rain. Acid
rain has been found to accelerate the decay of building materials and paints, and to cause the acidification of lakes
and streams and damage trees. As a result of these harmful effects, the United States has regulated the emissions of
SO2 under the Clean Air Act. The EPA has also developed a strategy to control these emissions via four programs:
(1) the National Ambient Air Quality Standards program,77 (2) New Source Performance Standards,78 (3) the New
Source Review/Prevention of Significant Deterioration Program,79 and (4) the sulfur dioxide allowance program.80
References
EPA (2005) Air Emissions Trends—Continued Progress Through 2004. U.S. Environmental Protection
Agency, Washington DC. August 18, 2005.
EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP
andEPAOAQPS. December 22,2003.
Table A-21B: SO, Emissions (Ggl
Sector/Source
Energy
Stationary Combustion
Mobile Combustion
Oil and Gas Activities
Waste Combustion
Industrial Processes
Chemical Manufacturing
Metals Processing
Storage and Transport
Other Industrial Processes
77 [42 U.S.C § 7409, CAA § 109]
78[42U.S.C§7411,CAA§111]
79 [42 U.S.C § 7473, CAA § 163]
80 [42 U.S.C § 7651, CAA § 401]
A-276 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990*2004
-------
Miscellaneous'
Solvent Use
Oegreasing
Graphic Arts
Dry Cleaning
Surface Coating
Other Industrial
Non-Industrial
Agriculture
Agricultural Burning
Waste
Landfills
Wastewater Treatment
Miscellaneous Waste
Total
20.936
NA
NA
0
1
1
61
1
1
NA
NA
0
1
1
• 63
1
0
- 0
0
0
1
NA
NA
0
1
1
40
1
0
0
0
I)
1
NA
NA
NA
1
1
82
1
0
0
0
0
1
NA
NA
NA
1
1
82
1
0
0
0
0
1
NA
NA
NA
1
1
82
1
0
0
0
0
1
NA
NA
NA
1
1
17,189 15,917 14,829 14,452 13,928 14,208 13,910
Source: Data taken from EPA (2005) and disaggregated based on EPA (2003).
* Miscellaneous includes other combustion and fugitive dust categories.
+ Does not exceed 0.5 Gg
NA (Not Available)
Note: Totals may not sum due to independent rounding.
Table fl-219: SO. Emissions from DecMeltv Generation (Gg)
Fuel Type
Coal
Petroleum
Natural Gas
Misc. Internal Combustion
Other
Total
Source Data taken (ram EPA (2005) and disaggregated based on EPA (2003).
Note: Totals may not sum due to independent rounding.
1998
11,312
691
5
52
110
12,170
1999
10,639
527
151
54
45
11,416
2000
9,621
429
. 157
1 54
78
10,339
2001
9,056
478
181
55
74
9,843
2002
8,587
453
172
56
70
9,338
2003
8,839
466
177
58
72
9,612
2004
8,560
451
171
. 56
70
9,308
A-277
-------
6.4. Complete List of Source Categories
Chapter/Source
Gas(es)
Energy
Fossil Fuel Combustion
Non-Energy Use of Fossil Fuels
Stationary Combustion (excluding COz)
Mobile Combustion (excluding CCb)
Coal Mining
Abandoned Coal Mines
Natural Gas Systems
Petroleum Systems
Natural Gas Flaring
Waste Combustion
Industrial Processes
Zinc Production
Lead Production
Titanium Dioxide Production
Aluminum Production
Iron and Steel Production
Ferroalloys
Ammonia Production and Urea Application
Cement Manufacture
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and Consumption
Carbon Dioxide Consumption
Phosphoric Acid Production
Petrochemical Production
Silicon Carbide Production
Adipic Acid
Nitric Acid <
Substitution of Ozone Depleting Substances
HCFC-22 Production
Semiconductor Manufacture
Electrical Transmission and Distributing
Magnesium Production and Processing
Solvent and Other Product Use
NzO Product Usage
Agriculture
Enteric Fermentation
Manure Management
Rice Cultivation
Agricultural Residue Burning
Agricultural Soil Management
Land Use, Land-Use Change, and Forestry
COz Flux
Settlements Remaining Settlements
Forest Land Remaining Forest Land
Waste
Landfills
Wastewater Treatment
Human Sewage
C02
CO*
CH4) NjO, CO, NOx, NMVOC
Cm.NzO.CO.NOx.NMVOC
cm
cm
CH«
CH4
COz
C02.N20
COi
C02
coz •
C02. CF«, C2Fa
COz, CH4
C02 • j
COz
COz
COz
COz
COa
COz
C02
cm, cos
cm, COi
NzO
NzO
MFCs, PFCs'
HFC-23
HFCs.PFCs.SF."
SFe
SF» .
CO, N0», NMVOC
N20
CH4
CH4, NzO
CH4
CH4, NzO
NzO, CO, NO,
CO: (sink)
COz (sink), NzO
COz (sink), NzO
CHi
cm
NzO
• Includes HFC-23, HFC-32, HFO125, HFO134a, HFO143a, HFO236fa, CF4, HFO152a, HFC-227ea, HFC-245fa, HFC-4310mee, and
PFC/PFPEs.
* Included such gases as HFC-23, CF(, C2F8| SF8.
A-278 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
6.5. Constants, Units, and Conversions
Metric Prefixes
Although most activity data for the United States is gathered in customary U.S. units, these units
are converted into metric units per international reporting guidelines. Table A- 220 provides a guide for
determining the magnitude of metric units. '
Tame fl- 220: Guide to Metric Dnlt Prefixes
Prefix/Symbol
atto(a)
femto (f)
pico(p)
nano (n)
micro (p )
milli (m)
centi(c)
deci (d)
deca(da)
hecto (h)
kilo (k)
mega(M)
giga(G)
tera(T)
peta(P)
exa(E)
Factor
10-"
10-w
10"12
10*
10^
10-3
10-2
10-1
10
102
103
10"
10*
10<2
10W
10"
Unit Conversions
t
\ kilogram = 2.205 pounds
1 pound = 0.454 kilograms . .
1 short ton = 2,000 pounds = 0.9072 metric tons
1 metric ton = 1,000 kilograms = 1.1023 short tons
1 cubic meter = 35.315 cubic feet
1 cubic foot = 0.02832 cubic meters
1 U.S. gallon = 3.785412 liters
1 barrel (bbl) = 0.159 cubic meters
1 barrel (bbl) = 42 U.S. gallons
1 liter = 0.001-cubic meters
1 foot = 0.3048 meters
1 meter = 3.28 feet
Imile = 1.609 kilometers
1 kilometer = 0.622 miles
1 acre = 43,560 square feet = 0.4047 hectares = 4,047 square meters
1 square mile = 2.589988 square kilometers
To convert degrees Fahrenheit to degrees Celsius, subtract 32 and multiply by 5/9
To convert degrees Celsius to Kelvin, add 273.15 to the number of Celsius degrees
A-279
-------
Density Conversions81
Methane
Carbon dioxide
1 cubic meter
1 cubic meter
0.67606 kilograms
1.85387 kilograms
Natural gas liquids
Unfinished oils
Alcohol
Liquefied petroleum gas
Aviation gasoline
Naphtha jet fuel
Kerosene jet fuel
Motor gasoline
Kerosene
Naphtha
Distillate
Residual oil
Lubricants
Bitumen
Waxes
Petroleum coke
Petrochemical feedstocks
Special naphtha
Miscellaneous products
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
metric ton
11.6 barrels
7.46 barrels
7.94 barrels
11.6 barrels
8.9 barrels
8.27 barrels
7.93 barrels
8.53 barrels
7.73 barrels
8.22 barrels
7.46 barrels
6.66 barrels
7.06 barrels
6.06 barrels
7.87 barrels
5.51 barrels
7.46 barrels
8.53 barrels
8.00 barrels
1,844.2 liters
1,186.04 liters
1,262.36 liters
1,844.2 liters
1,415.0 liters
1,314.82 liters
1,260.72 liters
1,356.16 liters
1,228.97 liters
1,306.87 liters
1,186.04 liters
1,058.85 liters
1,122.45 liters
963.46 liters
1,251.23 liters
876.02 liters
1,186.04 liters
1,356.16 liters
1,271.90 liters
Energy Conversions
Converting Various Energy Units to Joules
The common energy unit used in international reports of greenhouse gas emissions is the joule. A
joule is the energy required to push with a force of one Newton for one meter, A terajoule (TJ) is one
trillion (1012) joules. A British thermal unit (Btu, the customary U.S. energy unit) is the quantity of heat
required to raise the temperature of one pound of water one degree Fahrenheit at or near 39.2 Fahrenheit.
2.388xlOu calories
1 T, _ 23.88 metric tons of crude oil equivalent •«
947.8 million Btus
277,800 kilowatt-hours
Converting Various Physical Units to Energy Units
Data on the production and consumption of fuels are first gathered in physical units. These units
must be converted to their energy equivalents. The conversion factors in Table A-221 can be used as
default factors, if local data are not available. See Appendix A of EIA's Annual Energy Review 1997 (EIA
1998) for more detailed information on the energy content of various fuels.
Table A-221: Conversion Factors to Energy Unite meat Equivalents)
Fuel Type (Units)
Factor
Solid Fuels (Million Btu/Short ton)
Anthracite coal 22.573
Bituminous coal 23.89
Sub-bituminous coal 17.14
Lignite 12.866
Coke 24.8
81 Reference: EIA (1998a)
A-280 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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Natural Gas (Btu/Cubic foot) 1,027
Liquid Fuels (Million Btu/Barrel)
Crude oil 5.800
Natural gas liquids and LRGs 3.777
Other liquids 5.825
Motor gasoline • 5.253
Aviation gasoline 5.048
Kerosene 5.670
Jet fuel, kerosene-type 5.670
Distillate fuel • 5.825
Residual oil 6.287
Naphtha for petrochemicals 5.248
Petroleum coke 6.024
Other oil for petrochemicals 5.825
Special naphthas 5.248
Lubricants 6.065
Waxes 5.537
Asphalt 6.636
Still gas 6.000
Misc. products 5.796
Note: For petroleum and natural gas. Annual Energy Review 1997 (EIA 1998b). For coal ranks, Slate Energy Data Report 7992 (EIA1993). All
values are given in higher heating values (gross calorific values).
References
EIA (I998a) Emissions of Greenhouse Gases in the United States, DOE/EIA-0573(97), Energy
Information Administration, U.S. Department of Energy. Washington, DC. October.
EIA (1998b) Annual Energy Review, DOE/EIA-0384(97), Energy Information Administration,
U.S. Department of Energy. Washington, DC. July.
EIA (1993) State Energy Data Report 1992, DOE/EIA-0214(93), Energy Information
Administration, U.S. Department of Energy. Washington, DC. December.
\
A-281
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6.6. Abbreviations
AAPFCO American Association of Plant Food Control Officials
ABS - Acrylonitrile Butadiene Styrene
AFEAS Alternative Fluorocarbon Environmental Acceptability Study
AFV Alternative Fuel Vehicle
AGA American Gas Association
AHEF Atmospheric and Health Effect Framework
APC American Plastics Council
API American Petroleum Institute
ASAE American Society of Agricultural Engineers
ASTM American Society for Testing and Materials
BEA Bureau of Economic Analysis, U.S. Department of Commerce
BoC Bureau of Census
BODS Biochemical oxygen demand over a 5-day period
BRS Biennial Reporting System
BTS Bureau of Transportation Statistics, U.S. Department of Transportation
Btu British thermal unit
C&EN Chemical and Engineering News
CAAA Clean Air Act Amendments of 1990
CAPP " Canadian Association of Petroleum Producers
CBI Confidential Business Information
CFC . Chlorofluorocarbon
CFR Code of Federal Regulations
CMA Chemical Manufacturer's Association
CMOP ' Coalbed Methane Outreach Program
CNG • Compressed Natural Gas
CRF Common Reporting Format
CRM Crop Residue Management
CRP Conservation Reserve Program
CTIC Conservation Technology Information Center
CVD ' Chemical vapor deposition
DE Digestible Energy
DESC Defense Energy Support Center-DoD's defense logistics agency
DFAMS Defense Fuels Automated Management System
DIC Dissolved inorganic carbon
DM Dry Matter
DOC U.S. Department of Commerce
DoD U.S. Department of Defense
DOE U.S. Department of Energy
DOI U.S. Department of the Interior
DOT U.S. Department of Transportation
EAF Electric Arc Furnace
EF Emission Factor
EGR Exhaust Gas Recirculation
EIA Energy Information Administration, U.S. Department of Energy
EIIP Emissions Inventory Improvement Program
EOR Enhanced oil recovery
EPA U.S. Environmental Protection Agency
FAA Federal Aviation Administration
FAO Food and Agricultural Organization
FCCC Framework Convention on Climate Change
FEB Fiber Economics Bureau
FHWA Federal Highway Administration
FIA Forest Inventory and Analysis
GAA Governmental Advisory Associates
GCV Gross calorific value
GDP Gross domestic product
Gg Gigagram
GHG Greenhouse gas
GRI Gas Research Institute
GSAM Gas Systems Analysis Model
A-282 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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GWP Global warming potential
HBFC Hydrobromofluorocarbon
HC Hydrocarbon •
HCFC Hydrochlorofluorocarbon
HDDV Heavy duty diesel vehicle
HDGV Heavy duty gas vehicle
HOPE High density polyethylene
HFC Hydrofluorocarbon
HFE Hydrofluoroethers
HHV Higher Heating Value
HMA Hot Mix Asphalt
HIS Harmonized Tariff Schedule
ICAO International Civil Aviation Organization
IEA International Energy Association
IFO Intermediate Fuel Oil
ItSRP International Institute of Synthetic Rubber Products
ILENR Illinois Department of Energy and Natural Resources
IMO International Maritime Organization
IPAA Independent Petroleum Association of America
IPCC Intergovernmental Panel on Climate Change
LOOT Light duty diesel truck
LDDV Light duty diesel vehicle
LDGT Light duty gas truck
LOGV Light duty gas vehicle
LDPE Low density polyethylene
LEV Low emission vehicles
LFG Landfill gas
LFGT6 Landfill gas-to-energy
LHV Lower Heating Value
LLDPE Linear low density polyethylene •
LMOP EPA's Landfill Methane Outreach Program
LNG Liquefied Natural Gas
LPG Liquefied petroleum gas(es)
LTO Landing and take-off
LULUCF Land use, land-use change, and forestry
MC Motorcycle
MCF Methane conversion factor
MGO Marine Gas Oil
MLRA Major Land Resource Area
MMCFD Million Cubic Feet Per Day
MMS Minerals Management Service
MMTCE Million metric tons carbon equivalent
MSHA Mine Safety and Health Administration
MSW Municipal solid waste
MTBE Methyl Tertiary Butyl Ether
NAHMS National Animal Health Monitoring System
NAPAP National Add Precipitation and Assessment Program
NASS USDA's National Agriculture Statistics Service
NCV Net calorific value
NEU Non-Energy Use
NEV Neighborhood Electric Vehicle
NGL Natural Gas Liquids
NIAR Norwegian Institute for Air Research
NIR National Inventory Report
NMVOC Non-methane volatile organic compound
NOx Nitrogen Oxides
NPRA National Petroleum and Refiners Association
NRC National Research Council
NRCS Natural Resources Conservation Service
NRi National Resources Inventory
NSCR Non-selective catalytic reduction
NVFEL National Vehicle Fuel Emissions Laboratory
A-283
-------
NWS National Weather Service
GAP EPA Office of Atmospheric Programs
OAQPS EPA Office of Air Quality Planning and Standards
ODP Ozone Depleting Potential
ODS Ozone depleting substances
OECD Organization of Economic Co-operation and Development
OMS EPA Office of Mobile Sources
ORNL Oak Ridge National Laboratory
OSHA Occupational Safety and Health Administration
OTA Office of Tech nology Assessment
OTAQ EPA Office of Transportation and Air-Quality
PAH Polycyclic Aromatic Hydrocarbons
PDF Probability Density Function
PET Polyethylene Terephttialate
PFC Perfluorocarbon
PFPE Perfluoropolyether
POTW Publicly Owned Treatment Works
Ppbv Parts per billion (109) by volume
PPC Precipitated calcium carbonate
Ppmv Parts per million(108) by volume
Pptv Parts per trillion (1012) by volume
PS Polystyrene
PSU Primary Sample Unit
PVC Polyvinyl chloride
QA/QC Quality Assurance and Quality Control
QBtu Quadrillion Btu
RCRA Resource Conservation and Recovery Act
SAE Society of Automotive Engineers
SAN StyreneAcrylonitrile
SAR IPCC Second Assessment Report
SBSTA Subsidiary Body for Scientific and Technical Advice
SCR Selective catalytic reduction
SNAP Significant New Alternative Policy Program
SNG Synthetic natural gas
SCO Soil Organic Carbon
STMC Scrap Tire Management Council
SULEV Super Ultra Low Emissions Vehicle
SWANA Solid Waste Association of North America
TAME Tertiary Amyl Methyl Ether
TAR IPCC Third Assessment Report
TBtu Trillion Btu
TDN Total Digestible Nutrients
Tg C02 Eq. Teragrams carbon dioxide equivalent
' TJ Terajoule
TLEV Traditional Low Emissions Vehicle
TRI Toxic Release Inventory
TSDF Hazardous waste treatment, storage, and disposal facility
TVA Tennessee Valley Authority
U.S. United States
UEP • United Egg Producers
ULEV Ultra Low Emission Vehicle
UNEP United Nations Environmental Programme
UNFCCC United Nations Framework Convention on Climate Change
USAF United States Air Force
USDA United States Department of Agriculture
USFS United States Forest Service
USGS United States Geological Survey
VAIP EPA's Voluntary Aluminum Industrial Partnership
VKT Vehicle kilometers traveled
VMT Vehicle miles traveled
VOCs Volatile Organic Compounds
VS Volatile Solids
A-284 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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WIP Waste In Place
WMO World Meteorological Organization
ZEVs Zero Emissions Vehicles
A-285
-------
6.7. Chemical Formulas
Table fl-222: Guide to Chemical foimolas
Symbol
Name
Al
AbOj
Br
C
CH4
CaH8
CjH.
CF4
C2F9
C-CsF«
C3F«
C-C4F«
CsF«
CeFi4
CF3|
CFCb
CF2Cb
CFaCI
CzFsCb
CCbCFa
CZF«CI2
CzFsCl
CHCbF
CHF2a
CzFjHCb
C2F«HCI
CaFHsCb
CFiCFzCHCb
CCIFiCFzCHCIF
ecu
CHCICCIj
CHaCt
CHsCCb
CHzCb
CHCb
CHFs
CHiFz
CH3F
CjHFs
CH2FCF3
CHiFCHzF
C2H4F2
CF3CF?CH2F
CF3CHFCHF2
CHF?CH2CF3
Aluminum
Aluminum Oxide
Bromine
Carbon
Methane
Ethane
Propane
Perfluoromethane
Perfluoroelhane, hexafluoroethane
Perfluorocycloprapane
Perfluoropropane
Perfluorocyclobutane
Perfluorobutane
Perfluoropenlane
Perfluorohexana
Trifluoroiodomethane
Trichlorofluoromethane (CFC-11)
Dichlorodifluoromethane (CFC-12)
Chlorotrifluoromethane (CFC-13)
Trichlorotrifluoroethane (CFC-113)*
CFC-113a*
Dichlorotetrafluoroethane (CFC-114}
Ctiloropentaftuoroethane (CFC-115)
HCFC-21
Chlorodifluoromethane (HCFC-22)
HCFC-123
HCFC-124
HCFC-U1b
HCFC-142b
HCFC-225oa
HCFC-225cb
Carbon telrachloride
Trichloroelhylene
Perchloroethylene, tetrachloroethene
Melhylchloride
Methylchtoroform
Methylenecfiloride
Chloroform, trichloromethane
HFC-23
HFC-32
HFC-41
HFC-125
HFC-134
HFC-134a
' HFC-143*
HFC-143a*
HFC-152*
HFC-152a*
HFC-161
HFC-227ea
HFC-236cb
HFC-236ea
HFC-236fa
HFC-245ca
HFC-245fa
HFC-365mfc
HFC-43-10mee
A-286 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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CFsOCHF2
CF2HOCF2H
CHiOCFj
CFaCHFOCFa
CF3CHCIOCHF2
CF3CHFOCHF2
CFsCHzOCFa
CFsCFiOCHj
CHF2CH2OCFs "
CFjCH20CHF2
CHF2CF2OCH3
CF3CH20CH3
CF3CF2OCF2CHF2
CF3CFzOCH2CF3
CF3CF2CFjOCH3
CF3CFzOCH2CHF2
CFaCHFCFjOCHs
CHF2CF2CF2OCH3
CHF2CF20CH2CHF2
CHF2CF2CH2OCHF2
CF3CF2CH20CH3
CHF2CF2OCH2CH3
kFsOCHs
C
-------
0, Ch atomic Oxygen, molecular Oxygen
Oa Ozone
S atomic Sulfur
HzSCU Sulfuric add
SFe Sulfur hexafluoride
SFsCFa Trifluoromethylsulphur pentafluoride
Spz Sulfur dioxide
Si Silicon
SiC Silicon carbide
SiQi Quartz
* Distinct isomers
A-288 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
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ANNEX 7 Uncertainty
The annual U.S. Inventory presents the best effort to produce estimates for greenhouse gas source and sink
categories in the United States. These estimates were generated according to the UNFCCC reporting guidelines,
following the recommendations set forth in the Revised 1996 IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC/UNEP/OECD/IEA 1997), the IPCC Good Practice Guidance (IPCC 2000), and the Good
Practice Guidance for Land Use, Land-Use Change and Forestry (IPCC 2003). This Annex provides an overview of
the uncertainty analysis conducted to support the U.S. Inventory, describes the sources of uncertainty characterized
throughout the Inventory associated with various source categories (including emissions and sinks), and describes
the methods through which uncertainty information was collected, quantified, and presented.
7.1. Overview
Some of the current inventory estimates, such as those for C02 Emissions from Fossil Fuel Combustion for
example, have a relatively low level of uncertainty associated with them. Other categories of emissions exist,
however, for which the inventory emission estimates are considered less certain. The major types of uncertainty
associated with these inventory estimates are (1) model uncertainty, which arises when the emission and/or removal
estimation models used in developing the inventory estimates do not fully and accurately characterize the respective
emission and/or removal processes (due to a lack of technical details or other resources), resulting in the use of
incorrect or incomplete estimation methodologies and (2) parameter uncertainty, which arises due to a lack of
precise input data such as emission factors and activity data.
The model uncertainty can be evaluated by comparing model results with those of other models developed
to characterize the same emission (or removal) process and through sensitivity analysis. However, it would be very
difficult—if not impossible—to quantify the model uncertainty associated with the inventory estimates (primarily
because, in most cases, only a single model has been developed to estimate emissions from any one source).
Therefore,, model uncertainty was not quantified in this report. Nonetheless, it has been discussed qualitatively,
where appropriate, along with the individual source category description and inventory estimation methodology
Parameter uncertainty is, therefore, the principal type and source of uncertainty associated with the national
inventory estimates and is the main focus of the quantitative uncertainty .analyses in this report. Parameter
uncertainty has been quantified for most of the emission sources in the U.S. Inventory.
The primary purpose of the uncertainty analysis conducted in support of the U.S. Inventory is (i) to
determine the quantitative uncertainty associated with the emission (and removal) estimates presented in the main
body of this report [based on the uncertainty associated with the input parameters used in the emission (and
removal) estimation methodologies] and (ii) to evaluate the relative importance of the input parameters in
contributing to uncertainty in the associated source category inventory estimate and in the overall inventory
estimate. Thus the U.S. Inventory uncertainty analysis provides a strong foundation for • developing future
improvements and revisions to the Inventory estimation process. For each source category, the analysis highlights
opportunities for changes to data measurement, data collection, and calculation methodologies. These are presented
in the "Planned Improvements" sections of each source category's discussion in the main body of the report.
7.2. Methodology arid Results
The United States has developed a QA/QC and uncertainty management plan in accordance with the IPCC
Good Practice Guidance. Like the quality assurance/quality control plan, the uncertainty management plan is part
of a continually evolving process. The uncertainty management plan provides for a quantitative assessment of the
inventory analysis itself, thereby contributing to continuing efforts to understand both what causes uncertainty and
how to improve inventory quality (EPA 2002). Although the plan provides both general and specific guidelines for
implementing quantitative uncertainty analysis, its components are intended to evolve over time, consistent with the
inventory estimation process. The U.S. plan includes procedures and guidelines, and forms and templates, for
developing quantitative assessments of uncertainty in the national Inventory estimates.
A-289
-------
. The IPCC Good Practice Guidance recommends two approaches—Tier 1 and Tier 2—for developing
quantitative estimates of uncertainty in the inventory estimate of individual source categories and the overall
inventory. Of these, the Tier 2 approach is both more flexible and more powerful than Tier 1; both methods are
described in the next section. The United States is currently in the process of implementing a multi-year strategy to
develop quantitative estimates of uncertainty for all source categories using the Tier 2 approach. This year, which
represents the third year of this process, a Tier 2 approach was implemented for all source categories except HCFC-
22 production and CO2 from natural gas flaring, and some Land Use, Land-Use Change and Forestry source
categories. • -
The current Inventory reflects significant improvements over the previous publication in the extent to
which the Tier 2 approach to uncertainty analysis was adopted. For the current Inventory, the Tier 1 approach was
only adopted for one source category (i.e., HCFC-22 production), as compared to 10 source categories in the
previous Inventory report. Each of the new Tier 2 analyses reflect additional detail and characterization of input
parameters using statistical data collection, expert elicitation methods and more informed judgment. Quantitative
uncertainty estimates were not calculated for CO2 from Natural Gas Flaring (IPCC Source Category 1B2), although
the emissions from this source have been included in the national Inventory estimate for 2004. Future efforts will be
made to quantify uncertainty of this source category's emissions estimates using the Tier 2 approach. Emissions and
sinks from International Bunker Fuels, Biomass Burning, and Indirect Greenhouse Gas Emissions are not included
in total emissions estimated for the U.S. Inventory; therefore, no quantitative uncertainty estimates have been
developed for these source categories.
Tier 1 and Tier 2 Approach
The Tier 1 method for estimating uncertainty is based on the error propagation equation. This equation
combines the uncertainty associated with the activity data and the uncertainty associated with the emission (or the
other) factors. The Tier 1 approach is applicable where emissions (or removals) are usually estimated as the product
of an activity value and an emission factor or as the sum of individual sub-source category values. Inherent in
employing the Tier 1 method are the assumptions that, for each source category, (i) both the activity data and the
emission factor values are approximately normally distributed, (ii) the coefficient of variation associated with each
input variable is less than 30 percent, and (iii) the input variables (i.e., values to be combined) are not correlated.
The Tier 2 method is preferred (i) if the uncertainty associated with the input variables are significantly
large, (ii) if the distributions underlying the input variables are not normal, (iii) if the estimates of uncertainty
associated with the input variables are significantly correlated, and/or (iv) if a sophisticated estimation methodology
and/or several input variables are used to characterize the emission (or removal) process correctly. In practice, the
Tier 2 is the preferred method of uncertainty analysis for all source categories where sufficient and reliable data are
available to characterize the uncertainty of the input variables.
The Tier 2 method employs the Monte Carlo Stochastic Simulation technique (also referred to as the Monte
Carlo method).' Under this method, estimates of emissions (or removals) for a particular source category are
generated many times (equal to the number of iterations specified) using an uncertainty model—which is an emission
(or removal) estimation equation that simulates or is the same as the inventory estimation model for a particular
source category. These estimates are generated using the respective, randomly-selected values for the constituent
input variables using a simulation-software such as @RISK or Crystal Ball.
Characterization of Uncertainty in Input Variables
Both Tier 1 and Tier 2 uncertainty analyses require that all the input variables are well-characterized in
terms of their distributions or PDFs. In the absence of particularly convincing data measurements, sufficient data
samples, or expert .judgments that determined otherwise, the PDFs incorporated in this year's source category
uncertainty analyses were limited to uniform, triangular, lognormal, or normal. The choice among these four PDFs
depended largely on the observed or measured data and expert judgment
• Source Category Inventory U ncertainty Estimates
Discussion surrounding the input parameters and sources of uncertainty for each source category appears in
the body of this report. Table A- 223 summarizes results based on assessments of source category-level uncertainty.
A-290 .Inventory of U.S. Greenhouse Gas Emissions and Sinks; 1990-2004
-------
The table presents base year (1990 or 1995) and current year (2004) emissions for each source category. The
combined uncertainty for each source category is expressed as a percent of the total 2004 emissions estimated for
that source category. Source category trend uncertainty is subsequently described in this Annex.
Source Category
COi
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Flaring
Cement Manufacture
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and Consumption
Carbon Dioxide Consumption
Waste Combustion
Titanium Dioxide Production
Aluminum Production
Iron and Steel Production
Ferroalloys
Ammonia Production and Urea Application
Phosphoric Acid Production
, Petrochemical Production
Silicon Carbide Consumption
Lead Production
• Zinc Production
Land-Use Change and Forestry (Sink)1
, International Bunker Fuels?
Biomass Combustion*
CH4
Stationary Sources
Mobile Sources .
Coal Mining
Abandoned Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production
Iron and Steel Production ,
Enteric Fermentation
Manure Management
Rice Cultivation
Agricultural Residue Burning
Landfills
Wastewater Treatment
International Bunker Fuefe*
NjO
Stationary Sources
Mobile Sources
AdipicAcid
Nitric Acid
Manure Management
Agricultural Soil Management
Agricultural Residue Burning
Human Sewage
NZ0 Product Usage
Waste Combustion
Settlements Remaining Settlements
Forest Land Remaining Forest Land
Base Year
Emissions*
TgCOaEq..
5,005.3
4,696.6
117.2
5.8
33.3
11.2
5.5
4.1
0.9
10.9
1,3
7.0
85.0
2.0
19.3
1.5
2.2
0.1
0.3
0.9
(910.4)
113.5
/ 216.7
618.1
7.9
4.7 •
81.9
6.0
126.7
34,4
1.2
+
1.3
117,9
31,2
7.1
0.7
172.3
24.8
0.2
394.9
12.3
43.5-
15.2
17.8
16.3
266.1
0.4
12.9
4.3
0.5
5.6
0.1
2004
Emissions
Tg CO: Eq.
5,987.96
5,656.6
153.4
6.0
45.6
13.7
6.7
4.2
1.2,
19.4
2.3
4.3
51.3
1.3
16.9
1.4
2.9
0,1
0.3
0.5
' (730.1)
94.5
211.2
556.7
6.4
2.9
56.3
5.6
118.8
25.7
1,6171
+
1.0
112.6
39.4
7.6
0.9
140.9
36.9
0.1
386.7
13.7
42.8
5.7
16.6
17.7
261.5
0.5
16.0
4.8'
0.5
6.4
0.4
2004 Uncertainty
Low
-1%
' -20%
NE
' -13%
'•«%
-7%
-7%
-14%,
-15%
-16%
' -30%
-11%
-3%
-8% . •'
-18%
-14%
-17%
-11%
-12%
-26%
-8%
-4%
-18%
-29% •
-33%
-8%
-10%
-7% .
-11%
-18%
-67%
-75%
-36%
•33%
-24%
-16%
45%
-16%
-16%
-82%
-73%
-75%
-7%
-73%
-84%
-96%
High
6%
8%
NE
14%
8%
6%
7%
14%
10%
16%
30%
45%
3%
8%
19%
5%
18%
11%
13%
94%
4%
4%
23%
31%
141%
6%
10%
9%
18%
20%
157%
96%
16%
39%
188%
29%
44%
17%
24%
82%
85%
89%
7%
157%
349%
483%
A-291
-------
International Bunker Fuels'1
MFCs, PFCs, and SF«
Substitution of Ozone Depleting Substances
Aluminum Production (CF4) '
Aluminum Production (CzF«)
HCFC-22 Production
Semiconductor Manufacture1
Electrical Transmission and Distribution
Magnesium Production and Processing
Total
Net Emission (Sources and Sinks)
1.0
114.5
24.1
16.2
2.2
35.0
2.9
28.6
5.4
6,132.7
5,222.3
0.9
143.2
103.3
2.4
0.4
15.6
5.0
13.8
2.7
7,074.7
6,294.6
-13%
-10%
-16%
-10%
-23%
-13%
-11%
20%
12%
18%
10%
23%
13%
13%
•Base Year is 1990 for all sources except Substitution of Ozone Depleting Substances, for which the United States has chosen to use 1995
+ Does not exceed 0 05 Tg CO; Eq.
• Sinks are only included in net emissions total.
>> Emissions from international Bunker Fuels and Biomass Combustion are not included in totals.
« For the purposes of this uncertainty analysis, emissions from Semiconductor Manufacture presented here differ from those reported in the national toys. This
was done to reflect that the uncertainty analysis was based on the individual gases, such as NFj, rattier than on an analysis on the total mix of gases for this
source.
Note: Totals may not sum due to independent rounding.
Overall (Aggregate) Inventory Uncertainty Estimate
The overall uncertainty estimate for the U.S. greenhouse gas emissions inventory was developed using the
IPCC Tier 2 uncertainty estimation methodology. For each source category, the Monte Carlo simulation output data,
which were generated during its quantitative uncertainty analysis, were used to fit an appropriate probability
distribution. If such detailed output data were not available for particular emissions sources, individual probability
distributions were assigned to those source category emission estimates based on the most detailed output statistics
available from the quantitative uncertainty analysis performed.
For the HCFC production source category, only Tier 1 uncertainty results were used in the overall
uncertainty analysis estimation. However, for all other emission sources (excluding international bunker fuels, CO2
from biomass combustion, land-use change and forestry source and sink categories, and natural gas flaring), Tier 2
uncertainty results were used in the overall uncertainty estimation.
The results from the overall uncertainty model indicate that the 2004 U.S. greenhouse gas emissions are
estimated to be within the range of approximately 6,967 to 7,519 Tg of COj equivalent emissions reflecting a
relative 95 percent confidence interval uncertainty range of -2 percent to 6 percent with respect to the total U.S.
greenhouse gas emissions estimate of about 7,075 Tg CO2 Eq. The uncertainty interval associated with the total CO2
emissions, which constitute about 85% of the total U.S. greenhouse gas emissions in 2004, ranges from about -1
percent to about 6 percent of the total CO2 emissions estimated. The results indicate that the uncertainty associated
with the inventory estimate of the total N2O emissions is the largest (-39 percent to 48 percent), followed by the total
inventory CH4 emissions (±11 percent) and high GWP gas emissions (-9 percent to 15 percent).
A summary of the overall quantitative uncertainty estimates are shown below, in Table A- 224.
Table a- 224. Quantitative Uncertainly Assessment of Overall National inventory [missions (Tg CO, En. and Percent]
Gas
2004 Emission
Estimate
(Tg CO: Eq.}
Uncertainty Range Relative to Emission Estimate*
(TgCOjEq.) (%)
Lower Bound0
COj
CH«
N20
PFC.HFC&SF."
Total
5,988.0
556.7
386.7
143.2
7,074.7
5,920.5
495.3
235.1
130.1
6,966.8
Upper
Bound0
6,329.8
620.2
571.5
164.8
7,518.9
Lower
Bound'
-1%
-11%
-39%
-9%
•2%
Upper
Boundc
6%
11%
48%
15%
5%
Standard
Mean* Deviation
•> (TgCOzEq.)
6,120.6
556.5
403.1
147.2
. 7,245.2
105.3
31.8
' 88.3
8.9
142.2
Notes:
• Range of emission estimates tor a 95 percent confidence interval.
b Mean value indicates the arithmetic average of the simulated emission estimates; Standard deviation indicates the extent of deviation of the simulated values
from the mean.
c The low and high estimates for total emissions were separately calculated through simulations and, hence, the low and high emission estimates for the sub-
source categories do not add up to total emissions.
. A-292 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990*2004
-------
" The overall uncertainty estimate did not take into account the uncertainty m the GWP values for CH<, NiO and high GWP gases used in the inventory emission
calculations for 2004
Trend Uncertainty
In addition to the estimates of uncertainty associated with the current year's emission estimates, this Annex
also presents estimates of trend uncertainty. The IPCC Good Practice Guidance defines trend as the difference in
emissions between the base year {i.e., 1990 or 1995) and the current year (i,e,, 2004) inventory estimates. However,
for purposes of understanding the concept of trend uncertainty, the emission trend is defined in this report as the
percentage change in the emissions (or removal) estimated for the current year, relative to the emission (or removal)
estimated for the base year, the uncertainty associated with this emission trend is referred to as trend uncertainty.
Under the Tier 1 approach, the trend uncertainty for a source category is estimated using the sensitivity of
the calculated difference between base year and 2004 emissions to an incremental (i.e., 1 percent) increase in one or
both of these values for that source category. The two sensitivities are expressed as percentages: Type A sensitivity
highlights the effect on the difference between the base and the current year emissions caused by a 1 percent change
in both, while Type B sensitivity highlights the effect caused by a change to only the current year's emissions. Both
sensitivities are simplifications introduced in order to analyze correlation between base and current year estimates.
Once calculated, the two sensitivities are combined using the error propagation equation to estimate overall trend
uncertainty.
Under the Tier 2 approach, the trend uncertainty is estimated using Monte Carlo Stochastic Simulation
technique. The trend uncertainty analysis takes into account the fact that the base and the current year estimates
often share input variables. For purposes of the current Inventory, a simple approach has been adopted, under which
the base year source category emissions (or removals) are assumed to exhibit the same uncertainty characteristics as
the current year emissions (or removals). Source category-specific PDFs for the base year estimates were developed
using the 2004 uncertainty output data. These were adjusted to account for differences in magnitude between the the
base and the current years' inventory estimates. Then, for each source category, a trend uncertainty estimate was
developed using the Monte Carlo method. The overall inventory trend uncertainty estimate was developed by
combining all source category-specific trend uncertainty estimates. These preliminary trend uncertainty estimates
present the range of tikely change from base year to 2004, and are shown in Table A- 225.
Table A- 225. Quantitative Assessment of Trend uncertainty no Cfl! En, and Percent)
Gas/Source
CO:
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Flaring
Cement Manufacture
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and Consumption
Carbon Dioxide Consumption
Waste Combustion
Titanium Dioxide Production
Aluminum Production
Iron and Steel Production. ,
Ferroalloys
Ammonia Production and Urea Application
Phosphoric Acid Production
Petrochemical Production
Silicon Carbide Consumption
Lead Production
Zinc Production
Land-Use Change and Forestry (Sink)"
International Bunker Fuels'
Base Year*
Emissions
2004 Trend
Trend Range1
(TgC02Eq.) (%) (%)
. 5,005.3
4,696.6
117.2
5.8
33.3
11.2
5.5
4.1
0.9
10.9
1.3
7.0
85.0
2.0
19.3
1.5
2.2
0.1
0.3
0.9
(910.4)
113.5
5,988.0
5,656.6
153.4
6.0
45,6
13.7
6.7
4.2
1.2
19.4
2.3
4.3
51.3
1.3
16.9'
. 1.4 '
2.9
0.1
0.3
0.5
(780. 1)
94.5
20%
20%
31%
4%
37%
22%
21%
2%
38%
77%
73%
-38%
-40%
-35%
-12%
-9%
30%
33% .
-9%
47%
0%
0%
Lower
Bound
14%
14%
5%
12% .
9%
9%
-9%
12%
48%
37%
-60%
-57%
-38%
-22%
-30%
8%
3% "
-23%
-56%
Upper
Bound
25%
26%
64%
,66%
37%
35%
13%
68%
112%
119%
-6%
-15%
-32%
-2%
18%
44%
71%
6%
-36%
A-293
-------
Biomass Combustion*
CH4
Stationary Sources
Mobile Sources
Coal Mining
Abandoned Coal Mines
Natural Gas Systems
Petroleum Systems
Petrochemical Production
Silicon Carbide Production >
Iron and Steel Production
Enteric Fermentation
Manure Management
Rice Cultivation
Agricultural Residue Burning
Landfills
Wastewater Treatment
International Bunker Fuels*
NiO
Stationary Sources
Mobile Sources
Adipic Acid
Nitric Acid V
Manure Management
Agricultural Soil Management
Agricultural Residue Burning
Human Sewage
NzO Product Usage
Waste Combustion
Settlements Remaining Settlements
Forest Land Remaining Forest Land
International Bunker Fuels?
MFCs, PFCs, and SF»
Substitution of Ozone Depleting Substances
Aluminum Production (CF«)
Aluminum Production (CjFe)
HCFC-22 Production
Semiconductor Manufacture'
Electrical Transmission and Distribution
Magnesium Production and Processing
Total
216.7
618.1
7.9
4.7
81.9
6.0
. 126.7
34.4
1.2
0.0
1.3
117.9
31.2
7.1
0.7
172.3
24.8
0.2
394.9
12.3
43.5
15.2
17.8
16.3
266.1
0.4
12.9
4.3
0.5
5.6
0.1
1.0
114.5
24.1
16.2
2.2
35.0 '
2.9
28.6
5.4
6,132.7
211.2
556.7
6.4
2.9
56.3
- 5.6
118.8
25.7
1.6
0.0
1.0
112.6
39.4
7.6 .
0.9
140,9
36.9
0,1
386.7
13 J
42.8
5.7
16.6
17.7
261.5
0.5
16.0
4.8
0.5
6.4
0.4
0.9
143.2
103,3
2,4
0,4
15.6
5.0
. 13.8
2.7
7,074,7
0%
•10%
-18%
-38%
-31%
-6%
-6%
-26%
39% .
-67%
-21%
-4%
26%
6%
27%
-18%
49%
-36%
•2%
11%
-1%
-62%
-7%
9%
-2%
39%
24%
11%
10%
15%
556%
-12%
25%
328%
-85%
-81%
-55%
69%
-52%
-50%
15%
•25%
-61%
-52%
-35%'
-30%
40%
-76%
24%
-71%
-29%
-22%
-3%
-75%
-70%
46%
-10%
-48%
-60% -
-35%
-81%
-26%
-17%
-66%
-66%
-71%.
0%
-77%
-90%
-38%
12%
241%
-87%
-85%
-61%
15%
• -60%
-58%
8%
4%
73%
43%
-27%
26%
. 46%
52%
52%
-62%
-11%
17%
67%
351%
448%
24%
150%
86%
222%
20%
-24%
18%
46% -
206%
481%
414%
24%
532%
1145%
6527%
46%
438%
-82%
-76%
49%
125%
42%
41%
21%
•Base Year is 1990 for all sources except Substitution of Ozone Depleting Substances, for which the United States has chosen to use 1995.
+Does not exceed 0.05 Tg COj Eq.
* Trend Range represents the 95% confidence interval for the change in emissions from Base Year to 2004.
»Sinks are only included in net emissions total.
c Emissions from International Bunker Fuels and Biomass Combustion are not included in totals.
' For the purposes of this uncertainty analysis, emissions from Semiconductor Manufacture presented here differ from those reported in the national totals. This
was done to reflect that the uncertainty analysis was based on the individual gases, such as NF3, rather than on an analysis on the total mix of gases for this
source.
Note: Totals may not sum due to independent rounding.
7.3. Planned Improvements
Identifying the sources of uncertainty in the emission and sink estimates of the Inventory and quantifying
the magnitude of the associated uncertainty is the crucial first step towards improving those estimates. Quantitative
assessment of the parameter uncertainty may also provide information about the relative importance of input
parameters (such as activity data and emission factors), based on their relative contribution to the uncertainty within
the source category estimates. Such information can be used to prioritize resources with a goal of reducing
uncertainty over time within or among inventory source categories and their input parameters. In the current
Inventory, potential sources of model uncertainty have been identified for some emission sources, and preliminary
uncertainty estimates based on their parameters' uncertainty have been developed for most of the emission source
categories.
A-294 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2004
-------
Specific areas that require further research include:
• Incorporating excluded emission sources. Quantitative estimates of the uncertainty associated with some
of the sources and sinks of greenhouse gas emissions are not available at this time. In the future, efforts
will focus on developing uncertainty estimates for all source categories for which emissions or removals
are estimated.
• 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 are 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.
d •*
In improving the quality of uncertainty estimates, the following areas deserve further attention:
• Refine Source Category and Overall Uncertainty Estimates. For many individual source categories, further
research is needed to more accurately characterize PDFs that surround emissions modeling input variables.
In some cases, this might involve using measured or published statistics rather than relying on expert
judgment if such data are available.
• Include GWP uncertainty in the estimation of Overall level and trend uncertainty. The current year's
Inventory, does not include the uncertainty associated with the GWP values in the estimation of the overall
uncertainty for the Inventory, Including this source would contribute to a better characterization of overall
uncertainty and help assess the level of attention that this source of uncertainty warrants in the future.
• Improve characterization of trend uncertainty associated with the base year Inventory estimates. Improve
characterization of the base year uncertainty estimates in order to improve the analysis of trend uncertainty,
to replace the simplifying assumptions described in the "Trend Uncertainty" section above.
References ?
EPA (2002) Quality Assurance/Quality Control and Uncertainty Management Plan for the U.S. Greenhouse
Gas Inventory: Background on the U.S. Greenhouse Gas Inventory Process, U.S. Environmental Protection Agency,
Office of Atmospheric Programs, Greenhouse Gas Inventory Program, Washington, DC, EPA 430-R-02-007A, June
2002.
IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories,
Paris: Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for
Economic Co-Operation and Development, International Energy Agency.
IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas
Inventories, Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme,
Montreal, IPCC-XVI/Doc. 10 (1.IV.2000), May 2000. • • ,
A-295
-------
0.45
X <= -0.96
2.5%
X <= 2.96
97.5%
Value of input variable
Figure A-11: Example of a Normal Distribution
X <= 0.29
2.5%
X<=25
97.5%
0.0
10 1.5
Value of input variable
2.0
2.5
3.0
3.5
Figure A-12: Example of a Lognormal Distribution
-------
X <= 5.34
97.5%
3 4
Value of input variable
Figure A-13: Example of a Triangular Distribution
0.50
Uniform Probability Density Function
X <= 1 3525
2.5%
1.5
2.0 2.5
Value of input variable
X <= 3.3475
97.5%
3.0
3.5
Figure A-14: Example of a Uniform Distribution
-------
Descriptions of Figures: Annex 7
Figure A-l 1 illustrates a normal distribution. For a full description of a normal distribution, refer to the
annex text.
Figure A-12 illustrates a lognormal distribution. For a full description of a lognormal distribution, refer to
the annex text.
Figure A-13 illustrates a triangular distribution. For a full description of a triangular distribution, refer to
the annex text.
Figure A-14 illustrates a uniform distribution. For a full description of a uniform distribution, refer to the
annex text.
------- |