Inventory of U.S. Greenhouse Gas 

Emissions and Sinks: 1990–2006
Inventory of U.S. Greenhouse Gas

Emissions and Sinks: 

1990–2006

April 15, 2008

U.S. Environmental Protection Agency

1200 Pennsylvania Avenue, N.W.

Washington, DC 20460

U.S.A.

i

Acknowledgments 

T

he Environmental Protection Agency would like to acknowledge the many individual and organizational 

contributors to this document, without whose efforts this report would not be complete. Although the complete 

list of researchers, government employees, and consultants who have provided technical and editorial support 

is too long to list here, EPA’s Office of Atmospheric Programs would like to thank some key contributors and reviewers 

whose work has significantly improved this year’s report.

Work on fuel combustion and industrial process emissions was led by Leif Hockstad and Mausami Desai. Work on 

methane emissions from the energy sector was directed by Lisa Hanle. Calculations for the waste sector were led by Melissa 

Weitz. Tom Wirth directed work on the Agriculture chapter, and Kimberly Klunich directed work on the Land Use, LandUse Change, and Forestry chapter. Work on emissions of HFCs, PFCs, and SF6 was directed by Deborah Ottinger and Dave 

Godwin. John Davies directed the work on mobile combustion and transportation.

Within the EPA, other Offices also contributed data, analysis, and technical review for this report. The Office of 

Transportation and Air Quality and the Office of Air Quality Planning and Standards provided analysis and review for several 

of the source categories addressed in this report. The Office of Solid Waste and the Office of Research and Development 

also contributed analysis and research.

The Energy Information Administration and the Department of Energy contributed invaluable data and analysis on 

numerous energy-related topics. The U.S. Forest Service prepared the forest carbon inventory, and the Department of 

Agriculture’s Agricultural Research Service and the Natural Resource Ecology Laboratory at Colorado State University 

contributed leading research on nitrous oxide and carbon fluxes from soils. 

Other government agencies have contributed data as well, including the U.S. Geological Survey, the Federal Highway 

Administration, the Department of Transportation, the Bureau of Transportation Statistics, the Department of Commerce, 

the National Agricultural Statistics Service, the Federal Aviation Administration, and the Department of Defense.

We would also like to thank Marian Martin Van Pelt, Randy Freed, and their staff at ICF International’s Energy and 

Resources Practice, including Don Robinson, Diana Pape, Susan Asam, Michael Grant, Ravi Kantamaneni, Robert Lanza, 

Chris Steuer, Lauren Pederson, Kamala Jayaraman, Jeremy Scharfenberg, Mollie Averyt, Sarah Shapiro, Nina Kshetry, 

Pankaj Kumar, Stacy Hetzel, Brian Gillis, Zachary Schaffer, Vineet Aggarwal, Colin McGroarty, Hemant Mallya, Victoria 

Thompson, Jean Kim, Tristan Kessler, Sarah Menassian, Katrin Moffroid, Veronica Kennedy, Joseph Aamidor, Aaron 

Beaudette, Dylan Harrison-Atlas, Nikhil Nadkarni, Joseph Herr, and Toby Krasney for synthesizing this report and preparing 

many of the individual analyses. Eastern Research Group, RTI International, Raven Ridge Resources, and Arcadis also 

provided significant analytical support.

iii

Preface

T

he United States Environmental Protection Agency (EPA) prepares the official U.S. Inventory of Greenhouse Gas 

Emissions and Sinks to comply with existing commitments under the United Nations Framework Convention 

on Climate Change (UNFCCC).1 Under decision 3/CP.5 of the UNFCCC Conference of the Parties, national 

inventories for UNFCCC Annex I parties should be provided to the UNFCCC Secretariat each year by April 15.

In an effort to engage the public and researchers across the country, the EPA has instituted an annual public review 

and comment process for this document. The availability of the draft document is announced via Federal Register Notice 

and is posted on the EPA web site.2 Copies are also mailed upon request. The public comment period is generally limited 

to 30 days; however, comments received after the closure of the public comment period are accepted and considered for 

the next edition of this annual report. 

1

 See Article 4(1)(a) of the United Nations Framework Convention on Climate Change <http://www.unfccc.int>.

2

 See <http://www.epa.gov/globalwarming/publications/emissions>.

v

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.1. Background Information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-2

ES.2. Recent Trends in U.S. Greenhouse Gas Emissions and Sinks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-3

ES.3. Overview of Sector Emissions and Trends. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-12

ES.4. Other Information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-15

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1.1. Background Information. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-2

1.2. Institutional Arrangements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-7

1.3. Inventory Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-7

1.4. Methodology and Data Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-10

1.5. Key Categories. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-11

1.6. Quality Assurance and Quality Control (QA/QC). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-11

1.7. Uncertainty Analysis of Emission Estimates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-13

1.8. Completeness. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-15

1.9. Organization of Report. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-15

2. Trends in Greenhouse Gas Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2.1. Recent Trends in U.S. Greenhouse Gas Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2.2. Emissions by Economic Sector. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-17

2.3. Indirect Greenhouse Gas Emissions (CO, NOx, NMVOCs, and SO2). . . . . . . . . . . . . . . . . . . . . . . . . . . 2-28

3. Energy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1

3.1. Carbon Dioxide Emissions from Fossil Fuel Combustion (IPCC Source Category 1A). . . . . . . . . . . . . 3-3

3.2. Carbon Emitted from Non-Energy Use of Fossil Fuels (IPCC Source Category 1A). . . . . . . . . . . . . . . 3-19

3.3. Stationary Combustion (excluding CO2) (IPCC Source Category 1A). . . . . . . . . . . . . . . . . . . . . . . . . . . 3-24

3.4. Mobile Combustion (excluding CO2) (IPCC Source Category 1A). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-29

3.5. Coal Mining (IPCC Source Category 1B1a). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-36

3.6. Abandoned Underground Coal Mines (IPCC Source Category 1B1a). . . . . . . . . . . . . . . . . . . . . . . . . . . 3-39

3.7. Natural Gas Systems (IPCC Source Category 1B2b). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-42

3.8. Petroleum Systems (IPCC Source Category 1B2a). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-46
vi

3.9. Municipal Solid Waste Combustion (IPCC Source Category 1A5). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-50

3.10. Energy Sources of Indirect Greenhouse Gas Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-54

3.11. International Bunker Fuels (IPCC Source Category 1: Memo Items). . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-55

3.12. Wood Biomass and Ethanol Consumption (IPCC Source Category 1A). . . . . . . . . . . . . . . . . . . . . . . . . 3-60

4. Industrial Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.1. Cement Production (IPCC Source Category 2A1). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4

4.2. Lime Production (IPCC Source Category 2A2). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6

4.3. Limestone and Dolomite Use (IPCC Source Category 2A3). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-9

4.4. Soda Ash Production and Consumption (IPCC Source Category 2A4). . . . . . . . . . . . . . . . . . . . . . . . . . 4-12

4.5. Ammonia Production (IPCC Source Category 2B1) and Urea Consumption. . . . . . . . . . . . . . . . . . . . . . 4-14

4.6. Nitric Acid Production (IPCC Source Category 2B2). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-18

4.7. Adipic Acid Production (IPCC Source Category 2B3). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-19

4.8. Silicon Carbide Production (IPCC Source Category 2B4) and Consumption. . . . . . . . . . . . . . . . . . . . . 4-22

4.9. Petrochemical Production (IPCC Source Category 2B5). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-23

4.10. Titanium Dioxide Production (IPCC Source Category 2B5). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-26

4.11. Carbon Dioxide Consumption (IPCC Source Category 2B5). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-28

4.12. Phosphoric Acid Production (IPCC Source Category 2B5). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-30

4.13. Iron and Steel Production (IPCC Source Category 2C1). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-33

4.14. Ferroalloy Production (IPCC Source Category 2C2). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-37

4.15. Aluminum Production (IPCC Source Category 2C3). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-39

4.16. Magnesium Production and Processing (IPCC Source Category 2C4). . . . . . . . . . . . . . . . . . . . . . . . . . . 4-43

4.17. Zinc Production (IPCC Source Category 2C5). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-46

4.18. Lead Production (IPCC Source Category 2C5). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-49

4.19. HCFC-22 Production (IPCC Source Category 2E1). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-50

4.20. Substitution of Ozone Depleting Substances (IPCC Source Category 2F). . . . . . . . . . . . . . . . . . . . . . . . 4-52

4.21. Semiconductor Manufacture (IPCC Source Category 2F6). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-56

4.22. Electrical Transmission and Distribution (IPCC Source Category 2F7). . . . . . . . . . . . . . . . . . . . . . . . . . 4-61

4.23. Industrial Sources of Indirect Greenhouse Gases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-66

5. Solvent and Other Product Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1. Nitrous Oxide from Product Uses (IPCC Source Category 3D). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.2. Indirect Greenhouse Gas Emissions from Solvent Use. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

6. Agriculture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1

6.1. Enteric Fermentation (IPCC Source Category 4A). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2

6.2. Manure Management (IPCC Source Category 4B). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-7

6.3. Rice Cultivation (IPCC Source Category 4C). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-12

6.4. Agricultural Soil Management (IPCC Source Category 4D). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-17

6.5. Field Burning of Agricultural Residues (IPCC Source Category 4F). . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-31
vii

7. Land Use, Land-Use Change, and Forestry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-1

7.1. Representation of the U.S. Land Base . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3

7.2. Forest Land Remaining Forest Land. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-11

7.3. Land Converted to Forest Land (IPCC Source Category 5A2). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-24

7.4. Cropland Remaining Cropland (IPCC Source Category 5B1). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-24

7.5. Land Converted to Cropland (IPCC Source Category 5B2). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-37

7.6. Grassland Remaining Grassland (IPCC Source Category 5C1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-41

7.7. Land Converted to Grassland (IPCC Source Category 5C2). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-46

7.8. Settlements Remaining Settlements. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-50

7.9. Land Converted to Settlements (Source Category 5E2). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-55

7.10. Other (IPCC Source Category 5G). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-56

8. Waste . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1

8.1. Landfills (IPCC Source Category 6A1). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-2

8.2. Wastewater Treatment (IPCC Source Category 6B). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-6

8.3. Composting (IPCC Source Category 6D). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-17

8.4. Waste Sources of Indirect Greenhouse Gases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-19

9. Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-1

10. Recalculations and Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-1

11. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11-1

List of Annexes (Annexes available on CD version only)

ANNEX 1. Key Category Analysis

ANNEX 2. Methodology and Data for Estimating CO2 Emissions from Fossil Fuel Combustion

2.1. Methodology for Estimating Emissions of CO2 from Fossil Fuel Combustion

2.2. Methodology for Estimating the Carbon Content of Fossil Fuels

2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil Fuels

ANNEX 3. Methodological Descriptions for Additional Source or Sink Categories

3.1. Methodology for Estimating Emissions of CH4, N2O, and Indirect Greenhouse Gases from 

Stationary Combustion

3.2. Methodology for Estimating Emissions of CH4, N2O, and Indirect Greenhouse Gases from Mobile Combustion

and Methodology for and Supplemental Information on Transportation-Related GHG Emissions

3.3. Methodology for Estimating CH4 Emissions from Coal Mining

3.4. Methodology for Estimating CH4 and CO2 Emissions from Natural Gas Systems

3.5. Methodology for Estimating CH4 and CO2 Emissions from Petroleum Systems

3.6. Methodology for Estimating CO2 and N2O Emissions from Municipal Solid Waste Combustion

3.7. Methodology for Estimating Emissions from International Bunker Fuels used by the U.S. Military

3.8. Methodology for Estimating HFC and PFC Emissions from Substitution of Ozone Depleting Substances

3.9. Methodology for Estimating CH4 Emissions from Enteric Fermentation
viii

3.10. Methodology for Estimating CH4 and N2O Emissions from Manure Management

3.11. Methodology for Estimating N2O Emissions from Agricultural Soil Management

3.12. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands

3.13. Methodology for Estimating Net Changes in Carbon Stocks in Mineral and Organic Soils on 

Cropland and Grassland

3.14. Methodology for Estimating CH4 Emissions from Landfills

ANNEX 4. IPCC Reference Approach for Estimating CO2 Emissions from Fossil Fuel Combustion

ANNEX 5. Assessment of the Sources and Sinks of Greenhouse Gas Emissions Excluded

ANNEX 6. Additional Information

6.1. Global Warming Potential Values

6.2. Ozone Depleting Substance Emissions

6.3. Sulfur Dioxide Emissions

6.4. Complete List of Source Categories

6.5. Constants, Units, and Conversions

6.6. Abbreviations

6.7. Chemical Formulas

ANNEX 7 Uncertainty

7.1. Overview

7.2. Methodology and Results

7.3. Planned Improvements

7.4. Additional Information on Uncertainty Analyses by Source 

List of Tables, Figures, and Boxes

Tables

Table ES-1: Global Warming Potentials (100-Year Time Horizon) Used in This Report. . . . . . . . . . . . . . . . . ES-3

Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.). . . . . . . . . . . . . . . . . ES-5

Table ES-3: CO2 Emissions from Fossil Fuel Combustion by 

 Fuel Consuming End-Use Sector (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-9

Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by 

 Chapter/IPCC Sector (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-13

Table ES-5: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.). . . . . . . . . . . . . . . ES-15

Table ES-6: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . ES-15

Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq.). . . . . . . . . . . . . . ES-16

Table ES-8: U.S. Greenhouse Gas Emissions by Economic Sector with 

Electricity-Related Emissions Distributed (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-17

Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-18

Table ES-10: Emissions of NOx, CO, NMVOCs, and SO2 (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-19

Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and 

 Atmospheric Lifetime (years) of Selected Greenhouse Gases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-3

Table 1-2: Global Warming Potentials and Atmospheric Lifetimes (Years) Used in this Report. . . . . . . . . . . . 1-7

Table 1-3: Comparison of 100-Year GWPs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-8
ix

Table 1-4: Key Categories for the United States (1990–2006) Based on Tier 1 Approach. . . . . . . . . . . . . . . . 1-12

Table 1-5. Estimated Overall Inventory Uncertainty (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . 1-14

Table 1-6: IPCC Sector Descriptions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-15

Table 1-7: List of Annexes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-16

Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . 2-4

Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg). . . . . . . . . . . . . . . . . . . . . . . . . 2-6

Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by 

 Chapter/IPCC Sector (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-8

Table 2-4: Emissions from Energy (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-10

Table 2-5: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.). . . . . . . . . . . . . . . 2-11

Table 2-6: Emissions from Industrial Processes (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-13

Table 2-7: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . 2-13

Table 2-8: Emissions from Agriculture (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-14

Table 2-9: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.). . . . . . . . . . . . . . . . 2-15

Table 2-10: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . 2-16

Table 2-11: Emissions from Waste (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-17

Table 2-12: U.S. Greenhouse Gas Emissions Allocated to 

 Economic Sectors (Tg CO2 Eq. and Percent of Total in 2006). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-18

Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . 2-20

Table 2-14: U.S. Greenhouse Gas Emissions by Economic Sector and Gas with 

Electricity-Related Emissions Distributed (Tg CO2 Eq.) and Percent of Total in 2006. . . . . . . . . . . . . . 2-21

Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . 2-24

Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-27

Table 2-17: Emissions of NOx, CO, NMVOCs, and SO2 (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-28

Table 3-1: CO2, CH4, and N2O Emissions from Energy (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

Table 3-2: CO2, CH4, and N2O Emissions from Energy (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3

Table 3-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq.). . . . . . . . . . 3-4

Table 3-4: Annual Change in CO2 Emissions from Fossil Fuel Combustion for 

 Selected Fuels and Sectors (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5

Table 3-5: CO2 Emissions from International Bunker Fuels (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-7

Table 3-6: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.). . . . . . . . . . . . . . . 3-8

Table 3-7: CO2 Emissions from Fossil Fuel Combustion in 

 Transportation End-Use Sector (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-9

Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO2 Eq./QBtu). . . . . . . . . . . 3-15

Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg CO2 Eq./QBtu). . . . . . . . . . . . . . . . 3-16

Table 3-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

Energy-Related Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq. and Percent). . . . . . . . . 3-18

Table 3-11: CO2 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO2 Eq.). . . . . . . . . . . . . . . 3-20

Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Use (TBtu). . . . . . . . . . . . . . . . . . . . . . . 3-21

Table 3-13: 2006 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions. . . . . . . . . . . 3-22
x

Table 3-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

Non-Energy Uses of Fossil Fuels (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-23

Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of 

Non-Energy Uses of Fossil Fuels (Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-23

Table 3-16: CH4 Emissions from Stationary Combustion (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-25

Table 3-17: N2O Emissions from Stationary Combustion (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-26

Table 3-18: CH4 Emissions from Stationary Combustion (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-27

Table 3-19: N2O Emissions from Stationary Combustion (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-28

Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from 

Energy-Related Stationary Combustion, Including Biomass (Tg CO2 Eq. and Percent). . . . . . . . . . . . . 3-28

Table 3-21: CH4 Emissions from Mobile Combustion (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-30

Table 3-22: N2O Emissions from Mobile Combustion (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-30

Table 3-23: CH4 Emissions from Mobile Combustion (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-31

Table 3-24: N2O Emissions from Mobile Combustion (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-31

Table 3-25: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from 

 Mobile Sources (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-33

Table 3-26: CH4 Emissions from Coal Mining (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-36

Table 3-27: CH4 Emissions from Coal Mining (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-36

Table 3-28: Coal Production (Thousand Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-37

Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining 

 (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-38

Table 3-30: CH4 Emissions from Abandoned Coal Mines (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-39

Table 3-31: CH4 Emissions from Abandoned Coal Mines (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-39

Table 3-32: Number of Gassy Abandoned Mines Occurring in U.S. Basins Grouped by 

 Class According to Post-abandonment State. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-41

Table 3-33: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from 

 Abandoned Underground Coal Mines (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-42

Table 3-34: CH4 Emissions from Natural Gas Systems (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-43

Table 3-35: CH4 Emissions from Natural Gas Systems (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-43

Table 3-36: Non-combustion CO2 Emissions from Natural Gas Systems (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . 3-43

Table 3-37: Non-combustion CO2 Emissions from Natural Gas Systems (Gg). . . . . . . . . . . . . . . . . . . . . . . . . 3-43

Table 3-38: Tier 2 Quantitative Uncertainty Estimates for CH4 and 

Non-Combustion CO2 Emissions from Natural Gas Systems (Tg CO2 Eq. and Percent). . . . . . . . . . . . . 3-45

Table 3-39: CH4 Emissions from Petroleum Systems (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-47

Table 3-40: CH4 Emissions from Petroleum Systems (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-47

Table 3-41: CO2 Emissions from Petroleum Systems (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-47

Table 3-42: CO2 Emissions from Petroleum Systems (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-47

Table 3-43: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems 

 (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-49

Table 3-44: Potential Emissions from CO2 Capture and Transport (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . 3-51

Table 3-45: Potential Emissions from CO2 Capture and Transport (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-51
xi

Table 3-46: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Tg CO2 Eq.). . . . . . . . . . . . . 3-52

Table 3-47: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Gg). . . . . . . . . . . . . . . . . . . 3-52

Table 3-48: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted. . . . . . . . . . . . . . . . . . 3-53

Table 3-49: Tier 2 Quantitative Uncertainty Estimates for CO2 and 

 N2O from Municipal Solid Waste Combustion (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . 3-54

Table 3-50: NOx, CO, and NMVOC Emissions from Energy-Related Activities (Gg). . . . . . . . . . . . . . . . . . . 3-55

Table 3-51: CO2, CH4, and N2O Emissions from International Bunker Fuels (Tg CO2 Eq.). . . . . . . . . . . . . . . 3-57

Table 3-52: CO2, CH4 and N2O Emissions from International Bunker Fuels (Gg). . . . . . . . . . . . . . . . . . . . . . 3-57

Table 3-53: Aviation Jet Fuel Consumption for International Transport (Million Gallons). . . . . . . . . . . . . . . . 3-58

Table 3-54: Marine Fuel Consumption for International Transport (Million Gallons). . . . . . . . . . . . . . . . . . . 3-58

Table 3-55: CO2 Emissions from Wood Consumption by End-Use Sector (Tg CO2 Eq.). . . . . . . . . . . . . . . . . 3-60

Table 3-56: CO2 Emissions from Wood Consumption by End-Use Sector (Gg). . . . . . . . . . . . . . . . . . . . . . . . 3-60

Table 3-57: CO2 Emissions from Ethanol Consumption (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-61

Table 3-58: CO2 Emissions from Ethanol Consumption (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-61

Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-61

Table 4-1: Emissions from Industrial Processes (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3

Table 4-2: Emissions from Industrial Processes (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4

Table 4-3: CO2 Emissions from Cement Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5

Table 4-4: Clinker Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6

Table 4-5: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

 Cement Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6

Table 4-6: CO2 Emissions from Lime Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-7

Table 4-7: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and 

 Dead-Burned-Dolomite Lime Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-7

Table 4-8: Adjusted Lime Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-8

Table 4-9: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lime Production 

 (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-9

Table 4-10: CO2 Emissions from Limestone & Dolomite Use (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . 4-9

Table 4-11: CO2 Emissions from Limestone & Dolomite Use (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-10

Table 4-12: Limestone and Dolomite Consumption (Thousand Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . 4-11

Table 4-13: Dolomitic Magnesium Metal Production Capacity (Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . 4-11

Table 4-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

 Limestone and Dolomite Use (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-12

Table 4-15: CO2 Emissions from Soda Ash Production and Consumption (Tg CO2 Eq.). . . . . . . . . . . . . . . . . 4-12

Table 4-16: CO2 Emissions from Soda Ash Production and Consumption (Gg). . . . . . . . . . . . . . . . . . . . . . . . 4-13

Table 4-17: Soda Ash Production and Consumption (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-13

Table 4-18: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

 Soda Ash Production and Consumption (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-14

Table 4-19: CO2 Emissions from Ammonia Production and Urea Consumption (Tg CO2 Eq.). . . . . . . . . . . . 4-15

Table 4-20: CO2 Emissions from Ammonia Production and Urea Consumption (Gg). . . . . . . . . . . . . . . . . . . 4-15

Table 4-21: Ammonia Production, Urea Production, Urea Net Imports, and Urea Exports (Gg). . . . . . . . . . . 4-16
xii

Table 4-22: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

 Ammonia Production and Urea Consumption (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . 4-17

Table 4-23: N2O Emissions from Nitric Acid Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . . 4-18

Table 4-24: Nitric Acid Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-18

Table 4-25: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions 

From Nitric Acid Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-19

Table 4-26: N2O Emissions from Adipic Acid Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . 4-20

Table 4-27: Adipic Acid Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-21

Table 4-28: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from 

 Adipic Acid Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-21

Table 4-29: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg CO2 Eq.). . . . . 4-22

Table 4-30: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg). . . . . . . . . . . . 4-22

Table 4-31: Production and Consumption of Silicon Carbide (Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . 4-23

Table 4-32: Tier 2 Quantitative Uncertainty Estimates for CH4 and CO2 Emissions from 

 Silicon Carbide Production and Consumption (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . 4-23

Table 4-33: CO2 and CH4 Emissions from Petrochemical Production (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . 4-24

Table 4-34: CO2 and CH4 Emissions from Petrochemical Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . 4-24

Table 4-35: Production of Selected Petrochemicals (Thousand Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . 4-25

Table 4-36: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)

 Consumption (Thousand Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-25

Table 4-37: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical Production and 

 CO2 Emissions from Carbon Black Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . 4-26

Table 4-38: CO2 Emissions from Titanium Dioxide Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . 4-27

Table 4-39: Titanium Dioxide Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-27

Table 4-41: CO2 Emissions from CO2 Consumption (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . 4-29

Table 4-42: CO2 Production (Gg CO2) and the Percent Used for Non-EOR Applications for 

 Jackson Dome and Bravo Dome. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-29

Table 4-43: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from CO2 Consumption 

 (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-30

Table 4-44: CO2 Emissions from Phosphoric Acid Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . 4-31

Table 4-45: Phosphate Rock Domestic Production, Exports, and Imports (Gg). . . . . . . . . . . . . . . . . . . . . . . . 4-31

Table 4-46: Chemical Composition of Phosphate Rock (percent by weight). . . . . . . . . . . . . . . . . . . . . . . . . . . 4-32

Table 4-47: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

 Phosphoric Acid Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-33

Table 4-48: CO2 and CH4 Emissions from Iron and Steel Production (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . 4-34

Table 4-49: CO2 and CH4 Emissions from Iron and Steel Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-34

Table 4-50: CH4 Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg). . . . . . . . . . . . . . . . 4-35

Table 4-51: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions from 

 Iron and Steel Production (Thousand Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-36
xiii

Table 4-52: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from 

 Iron and Steel Production (Tg. CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-37

Table 4-53: CO2 and CH4 Emissions from Ferroalloy Production (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . 4-37

Table 4-54: CO2 and CH4 Emissions from Ferroalloy Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-38

Table 4-55: Production of Ferroalloys (Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-38

Table 4-56: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

 Ferroalloy Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-39

Table 4-57: CO2 Emissions from Aluminum Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . . 4-40

Table 4-58: PFC Emissions from Aluminum Production (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-40

Table 4-59: PFC Emissions from Aluminum Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-40

Table 4-60: Production of Primary Aluminum (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-42

Table 4-61: Tier 2 Quantitative Uncertainty Estimates for CO2 and PFC Emissions from 

 Aluminum Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-43

Table 4-62: SF6 Emissions from Magnesium Production and Processing (Tg CO2 Eq. and Gg). . . . . . . . . . . 4-43

Table 4-63: SF6 Emission Factors (kg SF6 per metric ton of Magnesium). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-44

Table 4-64: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from 

 Magnesium Production and Processing (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-45

Table 4-65: CO2 Emissions from Zinc Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-46

Table 4-66: Zinc Production (Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-48

Table 4-67: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

 Zinc Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-48

Table 4-68: CO2 Emissions from Lead Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-49

Table 4-69: Lead Production (Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-49

Table 4-70: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from 

 Lead Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-50

Table 4-71: HFC-23 Emissions from HCFC-22 Production (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . 4-51

Table 4-72: HCFC-22 Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-51

Table 4-73: Quantitative Uncertainty Estimates for HFC-23 Emissions from 

 HCFC-22 Production (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-52

Table 4-74: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . 4-53

Table 4-75: Emissions of HFCs and PFCs from ODS Substitutes (Mg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-53

Table 4-76: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) by Sector. . . . . . . . . . . . . . . . 4-53

Table 4-77: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from 

 ODS Substitutes (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-56

Table 4-78: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg CO2 Eq.). . . . . . . . . . . . . 4-57

Table 4-80: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from 

 Semiconductor Manufacture (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-60

Table 4-81: SF6 Emissions from Electric Power Systems and 

 Electrical Equipment Manufacturers (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-61

Table 4-82: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Gg). . . . 4-61
xiv

Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from 

 Electrical Transmission and Distribution (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-64

Table 4-84: 2006 Potential and Actual Emissions of HFCs, PFCs, and SF6 from 

 Selected Sources (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-65

Table 4-85: NOx, CO, and NMVOC Emissions from Industrial Processes (Gg). . . . . . . . . . . . . . . . . . . . . . . . 4-66

Table 5-1: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . 5-1

Table 5-2: N2O Emissions from N2O Product Uses (Tg CO2 Eq. and Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-2

Table 5-3: N2O Production (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-2

Table 5-4: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from 

 N2O Product Uses (Tg CO2 Eq. and Percent) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-3

Table 5-5: Emissions of NOx, CO, and NMVOC from Solvent Use (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

Table 6-1: Emissions from Agriculture (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1

Table 6-2: Emissions from Agriculture (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2

Table 6-3: CH4 Emissions from Enteric Fermentation (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3

Table 6-4: CH4 Emissions from Enteric Fermentation (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3

Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from 

 Enteric Fermentation (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-5

Table 6-6: CH4 and N2O Emissions from Manure Management (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . 6-8

Table 6-7: CH4 and N2O Emissions from Manure Management (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-9

Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O

 (Direct and Indirect) Emissions from Manure Management (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . 6-11

Table 6-9: CH4 Emissions from Rice Cultivation (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-14

Table 6-10: CH4 Emissions from Rice Cultivation (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-14

Table 6-11: Rice Areas Harvested (Hectares). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-15

Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from 

Rice Cultivation (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-17

Table 6-13: N2O Emissions from Agricultural Soils (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-19

Table 6-14: N2O Emissions from Agricultural Soils (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-19

Table 6-15: Direct N2O Emissions from Agricultural Soils by Land Use and N Input (Tg CO2 Eq.). . . . . . . . 6-19

Table 6-16: Indirect N2O Emissions from all Land-Use Types (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . 6-20

Table 6-17: Quantitative Uncertainty Estimates of N2O Emissions from 

 Agricultural Soil Management in 2006 (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-29

Table 6-18: CH4 and N2O Emissions from Field Burning of Agricultural Residues (Tg CO2 Eq.). . . . . . . . . . 6-31

Table 6-19: CH4, N2O, CO, and NOx Emissions from Field Burning of Agricultural Residues (Gg). . . . . . . . 6-32

Table 6-20: Agricultural Crop Production (Gg of Product). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-34

Table 6-21: Percent of Rice Area Burned by State. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-34

Table 6-22: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues. . . . . . 6-34

Table 6-23: Greenhouse Gas Emission Ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-35

Table 6-24: Tier 2 Uncertainty Estimates for CH4 and N2O Emissions from 

Field Burning of Agricultural Residues (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-35
xv

Table 7-1: Net CO2 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and 

 Forestry (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2

Table 7-2: Net CO2 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and 

 Forestry (Tg C). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2

Table 7-3: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . 7-3

Table 7-4: Non-CO2 Emissions from Land Use, Land-Use Change, and Forestry (Gg). . . . . . . . . . . . . . . . . . 7-3

Table 7-5: Land Use Areas During the Inventory Reporting Period (Millions of Hectares). . . . . . . . . . . . . . . 7-4

Table 7-6: Net Annual Changes in C Stocks (Tg CO2/yr) in Forest and Harvested Wood Pools. . . . . . . . . . . . 7-14

Table 7-7: Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools. . . . . . . . . . . . . . 7-14

Table 7-8: Forest Area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools. . . . . . . . . . . . . . 7-15

Table 7-9: Estimates of CO2 (Tg/yr) emissions for the lower 48 states and Alaska. . . . . . . . . . . . . . . . . . . . . . 7-16

Table 7-10: Tier 2 Quantitative Uncertainty Estimates for Net CO2 Flux from 

Forest Land Remaining Forest Land: Changes in Forest C Stocks (Tg CO2 Eq. and Percent). . . . . . . . 7-19

Table 7-11: Estimated Non-CO2 Emissions from Forest Fires (Tg CO2 Eq.) for U.S. Forests. . . . . . . . . . . . . 7-21

Table 7-12: Estimated Non-CO2 Emissions from Forest Fires (Gg Gas) for U.S. Forests. . . . . . . . . . . . . . . . . 7-21

Table 7-13: Estimated Carbon Released from Forest Fires for U.S. Forests. . . . . . . . . . . . . . . . . . . . . . . . . . . 7-22

Table 7-14: Tier 2 Quantitative Uncertainty Estimates of Non-CO2 Emissions from 

Forest Fires in Forest Land Remaining Forest Land (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . 7-22

Table 7-15: N2O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO2 Eq. and Gg). . . . . . . . . 7-23

Table 7-16: Quantitative Uncertainty Estimates of N2O Fluxes from Soils in 

Forest Land Remaining Forest Land (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-24

Table 7-17: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg CO2 Eq.). . . . . 7-26

Table 7-18: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg C). . . . . . . . . . 7-26

Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within 

 Cropland Remaining Cropland (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-31

Table 7-20: Emissions from Liming of Agricultural Soils (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-33

Table 7-21: Emissions from Liming of Agricultural Soils (Tg C). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-33

Table 7-22: Applied Minerals (Million Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-34

Table 7-23: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Liming of 

 Agricultural Soils (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-35

Table 7-24: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg CO2 Eq.). . . . . . . 7-35

Table 7-25: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C). . . . . . . . . . . . 7-36

Table 7-26: Applied Urea (Million Metric Tons). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-36

Table 7-27: Quantitative Uncertainty Estimates for CO2 Emissions from Urea Fertilization 

 (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-36

Table 7-28: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg CO2 Eq.). . . . . . . 7-37

Table 7-29: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C). . . . . . . . . . . . 7-37

Table 7-30: Quantitative Uncertainty Estimates for C Stock Changes occurring within 

 Land Converted to Cropland (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-40

Table 7-31: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg CO2 Eq.). . . . 7-42
xvi

Table 7-32: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C). . . . . . . . . 7-42

Table 7-33: Quantitative Uncertainty Estimates for C Stock Changes occurring within 

Grassland Remaining Grassland (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-45

Table 7-34: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg CO2 Eq.). . . . . 7-47

Table 7-35: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C). . . . . . . . . . . 7-47

Table 7-36: Quantitative Uncertainty Estimates for C Stock Changes occurring within 

 Land Converted to Grassland (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-50

Table 7-37: Net C Flux from Urban Trees (Tg CO2 Eq. and Tg C). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-50

Table 7-38: C Stocks (Metric Tons C), Annual C Sequestration (Metric Tons C/yr), Tree Cover (Percent), 

 and Annual C Sequestration per Area of Tree Cover (kg C/m2 cover-yr) for 15 U.S. Cities. . . . . . . . . . 7-52

Table 7-39: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in 

 Urban Trees (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-53

Table 7-40: N2O Fluxes from Soils in Settlements Remaining Settlements (Tg CO2 Eq. and Gg). . . . . . . . . . 7-54

Table 7-41: Quantitative Uncertainty Estimates of N2O Emissions from Soils in 

 Settlements Remaining Settlements (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-56

Table 7-42: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO2 Eq.). . . . . . . . . . . . 7-57

Table 7-43: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C). . . . . . . . . . . . . . . . . 7-57

Table 7-44: Moisture Content (%), C Storage Factor, Proportion of Initial C Sequestered (%), 

Initial C Content (%), and Half-Life (years) for Landfilled Yard Trimmings and 

Food Scraps in Landfills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-58

Table 7-45: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C). . . . . . . . . . . . . . . . . . . . . . . . . 7-59

Table 7-46: Tier 2 Quantitative Uncertainty Estimates for CO2 Flux from Yard Trimmings and 

Food Scraps in Landfills (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-60

Table 8-1: Emissions from Waste (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1

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 CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-5

Table 8-6: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Tg CO2 Eq.). . . . 8-7

Table 8-7: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Gg). . . . . . . . . . . 8-8

Table 8-8: U.S. Population (Millions) and Domestic Wastewater BOD5 Produced (Gg). . . . . . . . . . . . . . . . . 8-10

Table 8-9: U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg). . . . . . 8-10

Table 8-10: Wastewater Flow (m3/ton) and BOD Production (g/L) for 

 U.S. Vegetables, Fruits and Juices Production. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-12

Table 8-11: U.S. Population (Millions) and Average Protein Intake [kg/(person-year)]. . . . . . . . . . . . . . . . . . 8-14

Table 8-12: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from 

 Wastewater Treatment (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-15

Table 8-13: CH4 and N2O Emissions from Composting (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-17

Table 8-14: CH4 and N2O Emissions from Composting (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-17

Table 8-15: U.S. Waste Composted (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-18
xvii

Table 8-16: Tier 1 Quantitative Uncertainty Estimates for Emissions from 

 Composting (Tg CO2 Eq. and Percent). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-18

Table 8-17: Emissions of NOx, CO, and NMVOC from Waste (Gg). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-19

Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-3

Table 10-2: Revisions to Net Flux of CO2 to the Atmosphere from Land Use, Land-Use Change, and 

 Forestry (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-5

Figures

Figure ES-1: U.S. Greenhouse Gas Emissions by Gas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-4

Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-4

Figure ES-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990. . . . . . . . . . . . . . . . . ES-4

Figure ES-4: 2006 Greenhouse Gas Emissions by Gas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-4

Figure ES-5: 2006 Sources of CO2 Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-7

Figure ES-6: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type. . . . . . . . . . . . . . . ES-8

Figure ES-7: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion. . . . . . . . . . . . . . . . . . . . ES-8

Figure ES-8: 2006 Sources of CH4 Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-10

Figure ES-9: 2006 Sources of N2O Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-11

Figure ES-10: 2006 Sources of HFCs, PFCs, and SF6 Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-12

Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector. . . . . . . . . . . . . . . . . . . . ES-12

Figure ES-12: 2006 U.S. Energy Consumption by Energy Source. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-13

Figure ES-13: Emissions Allocated to Economic Sectors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-16

Figure ES-14: Emissions with Electricity Distributed to Economic Sectors. . . . . . . . . . . . . . . . . . . . . . . . . . . ES-17

Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product. . . . . ES-18

Figure ES-16: 2006 Key Categories-Tier 1 Level Assessment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-20

Figure 2-1: U.S. Greenhouse Gas Emissions by Gas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2

Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990. . . . . . . . . . . . . . . . . . . 2-2

Figure 2-4: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector. . . . . . . . . . . . . . . . . . . . . . . 2-8

Figure 2-5: 2006 Energy Chapter Greenhouse Gas Emission Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-8

Figure 2-6: 2006 U.S. Fossil Carbon Flows (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-9

Figure 2-7: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type. . . . . . . . . . . . . . . . 2-11

Figure 2-8: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion. . . . . . . . . . . . . . . . . . . . . 2-11

Figure 2-9: 2006 Industrial Processes Chapter Greenhouse Gas Emission Sources. . . . . . . . . . . . . . . . . . . . . 2-12

Figure 2-10: 2006 Agriculture Chapter Greenhouse Gas Emission Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . 2-14

Figure 2-11: 2006 Waste Chapter Greenhouse Gas Emission Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-16

Figure 2-12: Emissions Allocated to Economic Sectors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-20

Figure 2-13: Emissions with Electricity Distributed to Economic Sectors. . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-22

Figure 2-14: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product. . . . . . . 2-27

Figure 3-1: 2006 Energy Chapter Greenhouse Gas Emission Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1

Figure 3-2: 2006 U.S. Fossil Carbon Flows (Tg CO2 Eq.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

Figure 3-3: 2006 U.S. Energy Consumption by Energy Source. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5
xviii

Figure 3-4: U.S. Energy Consumption (Quadrillion Btu). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5

Figure 3-5: 2006 CO2 Emissions from Fossil Fuel Combustion by Sector and Fuel Type. . . . . . . . . . . . . . . . 3-5

Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950–2006). . . . . 3-6

Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950–2006). . . . . 3-6

Figure 3-8: Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the 

United States (1974–2006). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-7

Figure 3-9: 2006 End-Use Sector Emissions of CO2 from Fossil Fuel Combustion. . . . . . . . . . . . . . . . . . . . . 3-8

Figure 3-10: Sales-Weighted Fuel Economy of New Automobiles and Light-Duty Trucks, 1990–2006. . . . . 3-10

Figure 3-11: Sales of New Automobiles and Light-Duty Trucks, 1990–2006. . . . . . . . . . . . . . . . . . . . . . . . . . 3-10

Figure 3-12: Industrial Production Indices (Index 2002=100). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-11

Figure 3-13: Electricity Generation Retail Sales by End-Use Sector. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-12

Figure 3-14: U.S. Energy Consumption and Energy-Related CO2 Emissions Per Capita and Per Dollar GDP 3-16

Figure 3-15: Mobile Source CH4 and N2O Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-29

Figure 4-1: 2006 Industrial Processes Chapter Greenhouse Gas Emission Sources. . . . . . . . . . . . . . . . . . . . . 4-1

Figure 6-1: 2006 Agriculture Chapter Greenhouse Gas Emission Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1

Figure 6-2: Agricultural Sources and Pathways of N that Result in N2O Emissions. . . . . . . . . . . . . . . . . . . . . 6-18

Figure 6-3: Major Crops, Average Annual Direct N2O Emissions Estimated Using the 

DAYCENT Model, 1990–2006 (Tg CO2 Eq./state/year). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-21

Figure 6-4: Grasslands, Average Annual Direct N2O Emissions Estimated Using the 

DAYCENT Model, 1990–2006 (Tg CO2 Eq./state/year). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-21

Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect N2O Emissions Using the 

DAYCENT Model, 1990–2006 (Gg N/state/year). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-22

Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect N2O Emissions Using the 

DAYCENT Model, 1990–2006 (Gg N/state/year). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-22

Figure 6-7: Comparison of Measured Emissions at Field Sites with Modeled Emissions Using the 

DAYCENT Simulation Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-29

Figure 7-1: Percent of Total Land Area in Each Land-Use Category by State. . . . . . . . . . . . . . . . . . . . . . . . . . 7-5

Figure 7-2: Forest Sector Carbon Pools and Flows. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-12

Figure 7-3: Estimates of Net Annual Changes in Carbon Stocks for Major Carbon Pools. . . . . . . . . . . . . . . . 7-15

Figure 7-4: Average C Density in the Forest Tree Pool in the Conterminous United States, 2007. . . . . . . . . . 7-16

Figure 7-5: Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States, 

1993–2006 Cropland Remaining Cropland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-27

Figure 7-6: Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States, 

1993–2006 Cropland Remaining Cropland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-27

Figure 7-7: Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States, 

1993–2006 Land Converted to Cropland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-39

Figure 7-8: Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States, 

1993–2006 Land Converted to Cropland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-39
xix

Figure 7-9: Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States, 

1993–2006 Grassland Remaining Grassland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-42

Figure 7-10: Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States, 

1993–2006 Grassland Remaining Grassland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-43

Figure 7-11: Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States, 

1993–2006 Land Converted to Grassland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-47

Figure 7-12: Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States, 

1993–2006 Land Converted to Grassland. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-48

Figure 8-1: 2006 Waste Chapter Greenhouse Gas Emission Sources. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1

Boxes

Box ES-1: Recalculations of Inventory Estimates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-2

Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data. . . . . . . . . . . . . . . . . . . . ES-18

Box 1-1: The IPCC Fourth Assessment Report and Global Warming Potentials. . . . . . . . . . . . . . . . . . . . . . . . 1-8

Box 1-2: IPCC Reference Approach. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-10

Box 2-1: Methodology for Aggregating Emissions by Economic Sector. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-23

Box 2-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data. . . . . . . . . . . . . . . . . . . . . 2-27

Box 2-3: Sources and Effects of Sulfur Dioxide. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-29

Box 3-1: Weather and Non-Fossil Energy Effects on CO2 from Fossil Fuel Combustion Trends. . . . . . . . . . . 3-6

Box 3-2: Carbon Intensity of U.S. Energy Consumption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-15

Box 3-3: Carbon Dioxide Transport, Injection, and Geological Storage. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-51

Box 4-1: Potential Emission Estimates of HFCs, PFCs, and SF6. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-65

Box 6-1: Tier 1 vs. Tier 3 Approach for Estimating N2O Emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-24

Box 6-2: Comparison of Tier 2 U.S. Inventory Approach and IPCC (2006) Default Approach. . . . . . . . . . . . 6-33

Box 7-1: CO2 Emissions from Forest Fires. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-16

Box 7-2: Tier 3 Inventory for Soil C Stocks Compared to Tier 1 or 2 Approaches. . . . . . . . . . . . . . . . . . . . . . 7-29

Box 8-1: Biogenic Emissions and Sinks of Carbon. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-6
Executive Summary ES-1

Executive Summary

An emissions inventory that identifies and quantifies a country’s primary anthropogenic1

 sources and sinks of

greenhouse gases is essential for addressing climate change. This Inventory adheres to both (1) a comprehensive 

and detailed set of methodologies for estimating sources and sinks of anthropogenic greenhouse gases, and (2) 

a common and consistent mechanism that enables Parties to the United Nations Framework Convention on Climate Change 

(UNFCCC) to compare the relative contribution of different emission sources and greenhouse gases to climate change. 

In 1992, the United States signed and ratified the UNFCCC. As stated in Article 2 of the UNFCCC, “The ultimate 

objective of this Convention and any related legal instruments that the Conference of the Parties may adopt is to achieve, in 

accordance with the relevant provisions of the Convention, stabilization of greenhouse gas concentrations in the atmosphere 

at a level that would prevent dangerous anthropogenic interference with the climate system. Such a level should be achieved 

within a time-frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is 

not threatened and to enable economic development to proceed in a sustainable manner.”2

Parties to the Convention, by ratifying, “shall develop, periodically update, publish and make available...national 

inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by the 

Montreal Protocol, using comparable methodologies...”3 The United States views this report as an opportunity to fulfill 

these commitments.

This chapter summarizes the latest information on U.S. anthropogenic greenhouse gas emission trends from 1990 

through 2006. To ensure that the U.S. emissions Inventory is comparable to those of other UNFCCC Parties, the estimates 

presented here were calculated using methodologies consistent with those recommended in the Revised 1996 IPCC 

Guidelines for National Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997), the IPCC Good Practice Guidance 

and Uncertainty Management in National Greenhouse Gas Inventories (IPCC 2000), and the IPCC Good Practice Guidance 

for Land Use, Land-Use Change, and Forestry (IPCC 2003). Additionally, the U.S. emission Inventory has begun to 

incorporate new methodologies and data from the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 

1The 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 <http://unfccc.int>.

3Article 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 <http://unfccc.int>.
ES-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

2006). The structure of this report is consistent with the 

UNFCCC guidelines for inventory reporting.4 For most 

source categories, the Intergovernmental Panel on Climate 

Change (IPCC) methodologies were expanded, resulting in 

a more comprehensive and detailed estimate of emissions.

ES.1. Background Information

Naturally occurring greenhouse gases include water 

vapor, carbon dioxide (CO2), methane (CH4), nitrous oxide 

(N2O), and ozone (O3). Several classes of halogenated 

substances that contain fluorine, chlorine, or bromine are also 

greenhouse gases, but they are, for the most part, solely a 

product of industrial activities. Chlorofluorocarbons (CFCs) 

and hydrochlorofluorocarbons (HCFCs) are halocarbons that 

contain chlorine, while halocarbons that contain bromine 

are referred to as bromofluorocarbons (i.e., halons). As 

stratospheric ozone depleting substances, CFCs, HCFCs, 

and halons are covered under the Montreal Protocol on 

Substances that Deplete the Ozone Layer. The UNFCCC 

defers to this earlier international treaty. Consequently, 

Parties to the UNFCCC are not required to include these 

gases in their national greenhouse gas emission inventories.5

Some other fluorine-containing halogenated substances—

hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and 

4 See <http://unfccc.int/resource/docs/cop8/08.pdf>.

5 Emission estimates of CFCs, HCFCs, halons and other ozone depleting 

substances are included in the annexes of this report for informational 

purposes.

sulfur hexafluoride (SF6)—do not deplete stratospheric ozone 

but are potent greenhouse gases. These latter substances are 

addressed by the UNFCCC and accounted for in national 

greenhouse gas emission inventories.

There are also several gases that do not have a direct 

global warming effect but indirectly affect terrestrial and/or 

solar radiation absorption by influencing the formation or 

destruction of greenhouse gases, including tropospheric and 

stratospheric ozone. These gases include carbon monoxide 

(CO), oxides of nitrogen (NOx), and non-CH4 volatile organic 

compounds (NMVOCs). Aerosols, which are extremely 

small particles or liquid droplets, such as those produced by 

sulfur dioxide (SO2) or elemental carbon emissions, can also 

affect the absorptive characteristics of the atmosphere.

Although the direct greenhouse gases CO2, CH4, and 

N2O occur naturally in the atmosphere, human activities 

have changed their atmospheric concentrations. From the preindustrial era (i.e., ending about 1750) to 2005, concentrations 

of these greenhouse gases have increased globally by 36, 148, 

and 18 percent, respectively (IPCC 2007). 

Beginning in the 1950s, the use of CFCs and other 

stratospheric ozone depleting substances (ODS) increased 

by nearly 10 percent per year until the mid-1980s, when 

international concern about ozone depletion led to the 

entry into force of the Montreal Protocol. Since then, the 

production of ODS is being phased out. In recent years, use 

of ODS substitutes such as HFCs and PFCs has grown as 

they begin to be phased in as replacements for CFCs and 

Box ES-1: Recalculations of Inventory Estimates

Each year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S. Greenhouse Gas Emissions and 

Sinks, as attempts are made to improve both the analyses themselves, through the use of better methods or data, and the overall usefulness 

of the report. In this effort, the United States follows the IPCC Good Practice Guidance (IPCC 2000), which states, regarding recalculations 

of the time series, “It is good practice to recalculate historic emissions when methods are changed or refined, when new source categories 

are included in the national inventory, or when errors in the estimates are identified and corrected.” In general, recalculations are made to the 

U.S. greenhouse gas emission estimates either to incorporate new methodologies or, most commonly, to update recent historical data.

In each Inventory report, the results of all methodology changes and historical data updates are presented in the “Recalculations 

and Improvements” chapter; detailed descriptions of each recalculation are contained within each source’s description contained in the 

report, if applicable. In general, when methodological changes have been implemented, the entire time series (in the case of the most 

recent Inventory report, 1990 through 2005) has been recalculated to reflect the change, per IPCC Good Practice Guidance. Changes 

in historical data are generally the result of changes in statistical data supplied by other agencies. References for the data are provided 

for additional information.
Executive Summary ES-3

HCFCs. Accordingly, atmospheric concentrations of these 

substitutes have been growing (IPCC 2007).

Global Warming Potentials

Gases in the atmosphere can contribute to the greenhouse 

effect both directly and indirectly. Direct effects occur when 

the gas itself absorbs radiation. Indirect radiative forcing 

occurs when chemical transformations of the substance 

produce other greenhouse gases, when a gas influences 

the atmospheric lifetimes of other gases, and/or when a 

gas affects atmospheric processes that alter the radiative 

balance of the earth (e.g., affect cloud formation or albedo).6

The IPCC developed the Global Warming Potential (GWP) 

concept to compare the ability of each greenhouse gas to trap 

heat in the atmosphere relative to another gas.

The GWP of a greenhouse gas is defined as the ratio of 

the time-integrated radiative forcing from the instantaneous 

release of 1 kilogram (kg) of a trace substance relative to 

that of 1 kg of a reference gas (IPCC 2001). Direct radiative 

effects occur when the gas itself is a greenhouse gas. The 

reference gas used is CO2, and therefore GWP-weighted 

emissions are measured in teragrams of CO2 equivalents 

(Tg CO2 Eq.).7,8 All gases in this Executive Summary are 

presented in units of Tg CO2 Eq. 

The UNFCCC reporting guidelines for national 

inventories were updated in 2002,9 but continue to require 

the use of GWPs from the IPCC Second Assessment Report 

(SAR) (IPCC 1996). This requirement ensures that current 

estimates of aggregate greenhouse gas emissions for 1990 

to 2006 are consistent with estimates developed prior to the 

publication of the IPCC Third Assessment Report (TAR) 

and the IPCC Fourth Assessment Report (AR4). Therefore, 

to comply with international reporting standards under the 

UNFCCC, official emission estimates are reported by the 

United States using SAR GWP values. All estimates are 

provided throughout the report in both CO2 equivalents and 

unweighted units. A comparison of emission values using the 

SAR GWPs versus the TAR and AR4 GWPs can be found in 

6Albedo 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.

7Carbon comprises 12/44ths of carbon dioxide by weight.

8 One teragram is equal to 1012 grams or one million metric tons.

9 See <http://unfccc.int/resource/docs/cop8/08.pdf>.

Chapter 1 and, in more detail, in Annex 6.1 of this report. The 

GWP values used in this report are listed in Table ES-1.

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 

In 2006, total U.S. greenhouse gas emissions were 

7,054.2 Tg CO2 Eq. Overall, total U.S. emissions have 

risen by 14.7 percent from 1990 to 2006, while the U.S. 

gross domestic product has increased by 59 percent over 

the same period (BEA 2007). Emissions fell from 2005 to 

2006, decreasing by 1.1 percent (75.7 Tg CO2 Eq.). The 

following factors were primary contributors to this decrease: 

(1) compared to 2005, 2006 had warmer winter conditions, 

which decreased consumption of heating fuels, as well 

as cooler summer conditions, which reduced demand for 

Table ES-1: Global Warming Potentials 

(100-Year Time Horizon) Used in This Report

Gas GWP

CO2 1

CH4* 21

N2O 310

HFC-23 11,700

HFC-32 650

HFC-125 2,800

HFC-134a 1,300

HFC-143a 3,800

HFC-152a 140

HFC-227ea 2,900

HFC-236fa 6,300

HFC-4310mee 1,300

CF4 6,500

C2F6 9,200

C4F10 7,000

C6F14 7,400

SF6 23,900

Source: IPCC (1996)

* The CH4 GWP includes the direct effects and those indirect effects due 

to the production of tropospheric ozone and stratospheric water vapor. 

The indirect effect due to the production of CO2 is not included.
ES-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

electricity, (2) restraint on fuel consumption caused by rising 

fuel prices, primarily in the transportation sector and (3) 

increased use of natural gas and renewables in the electric 

power sector.

Figure ES-1 through Figure ES-3 illustrate the overall 

trends in total U.S. emissions by gas, annual changes, and 

absolute change since 1990. Table ES-2 provides a detailed 

summary of U.S. greenhouse gas emissions and sinks for 

1990 through 2006.

Figure ES-4 illustrates the relative contribution of the 

direct greenhouse gases to total U.S. emissions in 2006. 

The primary greenhouse gas emitted by human activities 

in the United States was CO2, representing approximately 

84.8 percent of total greenhouse gas emissions. The largest 

source of CO2, and of overall greenhouse gas emissions, 

was fossil fuel combustion. CH4 emissions, which have 

declined from 1990 levels, resulted primarily from 

enteric fermentation associated with domestic livestock, 

decomposition of wastes in landfills, and natural gas 

systems. Agricultural soil management and mobile source 

fossil fuel combustion were the major sources of N2O 

emissions. The emissions of substitutes for ozone depleting 

substances and emissions of HFC-23 during the production 

of HCFC-22 were the primary contributors to aggregate 

HFC emissions. Electrical transmission and distribution 

systems accounted for most SF6 emissions, while PFC 

emissions resulted from semiconductor manufacturing and 

as a byproduct of primary aluminum production.

Figure ES-1

U.S. Greenhouse Gas Emissions by Gas

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

Tg CO2 Eq.

6,148 1990

6,106 1991

6,192 1992

6,343 1993

6,435 1994

6,494 1995

6,731 1996

6,760 1997

6,801 1998

6,839 1999

7,033 2000

6,921 2001

6,981 2002

6,998 2003

7,078 2004

7,130 2005

7,054 2006

HFCs, PFCs, & SF6

Nitrous Oxide

Methane

Carbon Dioxide

Figure ES-2

Annual Percent Change in U.S. Greenhouse Gas Emissions

-2%

-1%

0%

1%

2%

3%

4%

-0.7%1991 1.4%1992 2.4%1993 1.5%1994 0.9%1995 3.6%1996 0.4%1997 0.6%1998 0.6%1999 2.8%2000 -1.6%2001 0.9%2002 0.2%2003 1.1%2004 0.7%2005 -1.1%2006

Figure ES-3

Cumulative Change in U.S. Greenhouse Gas 

Emissions Relative to 1990

-100

0

100

200

300

400

500

600

700

800

900

1,000

Tg CO2 Eq.

-421991 441992

1951993

2871994

3461995

5831996

6121997

6521998

6911999

8842000

7732001

8332002

8502003

9302004

9062006

9822005

Figure ES-4

2006 Greenhouse Gas Emissions by Gas 

HFCs, PFCs, & SF6

N2O

CH4

CO2 84.8%

7.9%

5.2%

2.1%
Executive Summary ES-5

Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 5,068.5 5,394.2 5,939.7 5,846.2 5,908.6 5,952.7 6,038.2 6,074.3 5,983.1 

Fossil Fuel Combustion 4,724.1 5,032.4 5,577.1 5,507.4 5,564.8 5,617.0 5,681.4 5,731.0 5,637.9 

Electricity Generation 1,809.6 1,939.3 2,282.3 2,244.3 2,253.7 2,283.1 2,314.9 2,380.2 2,328.2 

Transportation 1,485.1 1,599.4 1,798.2 1,775.6 1,828.9 1,807.6 1,856.4 1,869.8 1,856.0 

Industrial 844.9 876.5 860.3 852.5 854.8 856.0 857.7 847.3 862.2 

Residential 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5 

Commercial 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1 

U.S. Territories 28.3 35.0 36.2 49.0 44.0 51.0 53.5 53.2 54.9 

Non-Energy Use of Fuels 117.2 133.2 141.4 131.9 135.9 131.8 148.9 139.1 138.0 

Iron and Steel Production 86.2 74.7 66.6 59.2 55.9 54.7 52.8 46.6 49.1 

Cement Production 33.3 36.8 41.2 41.4 42.9 43.1 45.6 45.9 45.7 

Natural Gas Systems 33.7 33.8 29.4 28.8 29.6 28.4 28.1 29.5 28.5 

Municipal Solid Waste Combustion 10.9 15.7 17.5 18.0 18.5 19.1 20.1 20.7 20.9 

Lime Production 12.0 14.0 14.9 14.3 13.7 14.5 15.2 15.1 15.8 

Ammonia Production and

Urea Consumption 16.9 17.8 16.4 13.3 14.2 12.5 13.2 12.8 12.4 

Limestone and Dolomite Use 5.5 7.4 6.0 5.7 5.9 4.8 6.7 7.4 8.6 

Cropland Remaining Cropland 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0 

Soda Ash Production 

and Consumption 4.1 4.3 4.2 4.1 4.1 4.1 4.2 4.2 4.2 

Aluminum Production 6.8 5.7 6.1 4.4 4.5 4.5 4.2 4.2 3.9 

Petrochemical Production 2.2 2.8 3.0 2.8 2.9 2.8 2.9 2.8 2.6 

Titanium Dioxide Production 1.2 1.5 1.8 1.7 1.8 1.8 2.1 1.8 1.9 

Carbon Dioxide Consumption 1.4 1.4 1.4 0.8 1.0 1.3 1.2 1.3 1.6 

Ferroalloy Production 2.2 2.0 1.9 1.5 1.3 1.3 1.4 1.4 1.5 

Phosphoric Acid Production 1.5 1.5 1.4 1.3 1.3 1.4 1.4 1.4 1.2 

Zinc Production 0.9 1.0 1.1 1.0 0.9 0.5 0.5 0.5 0.5 

Petroleum Systems 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Lead Production 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Silicon Carbide Production 

and Consumption 0.4 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 

Land Use, Land-Use Change, 

and Forestry (Sink)a (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Biomass—Wood b 215.2 229.1 218.1 193.5 192.8 193.8 205.1 204.8 204.4

International Bunker Fuelsb 113.7 100.6 101.1 97.6 89.1 103.6 119.0 122.6 127.1 

Biomass—Ethanol b 4.2 7.7 9.2 9.7 11.5 15.7 19.7 22.6 30.3

CH4 606.1 598.9 574.3 558.8 563.5 559.4 545.6 539.7 555.3 

Enteric Fermentation 126.9 132.3 124.6 123.6 123.8 124.6 122.4 124.5 126.2 

Landfills 149.6 144.0 120.8 117.6 120.1 125.6 122.6 123.7 125.7 

Natural Gas Systems 124.7 128.1 126.5 125.3 124.9 123.3 114.0 102.5 102.4 

Coal Mining 84.1 67.1 60.4 60.3 56.8 56.9 59.8 57.1 58.5 

Manure Management 31.0 35.2 38.8 40.2 41.3 40.7 40.1 41.8 41.4 

Petroleum Systems 33.9 32.0 30.3 30.2 29.9 29.2 28.7 28.3 28.4 

Forest Land Remaining Forest Land 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 

Wastewater Treatment 23.0 24.3 24.6 24.2 24.1 23.9 24.0 23.8 23.9 

Stationary Combustion 7.4 7.2 6.6 6.2 6.2 6.4 6.5 6.5 6.2 

Rice Cultivation 7.1 7.6 7.5 7.6 6.8 6.9 7.6 6.8 5.9 

Abandoned Underground Coal Mines 6.0 8.2 7.4 6.7 6.2 6.0 5.8 5.6 5.4 

Mobile Combustion 4.7 4.3 3.4 3.3 3.0 2.7 2.6 2.5 2.4 
ES-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Overall, from 1990 to 2006, total emissions of CO2

increased by 914.6 Tg CO2 Eq. (18.0 percent), while CH4

and N2O emissions decreased by 50.8 Tg CO2 Eq. (8.4 

percent) and 15.5 Tg CO2 Eq. (4.0 percent), respectively. 

During the same period, aggregate weighted emissions 

of HFCs, PFCs, and SF6 rose by 57.6 Tg CO2 Eq. (63.7 

percent). From 1990 to 2006, HFCs increased by 87.6 Tg 

CO2 Eq. (237.3 percent), PFCs decreased by 14.7 Tg CO2

Eq. (70.9 percent), and SF6 decreased by 15.3 Tg CO2 Eq. 

(47.0 percent). Despite being emitted in smaller quantities 

Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO (continued) 2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Composting 0.3 0.7 1.3 1.3 1.3 1.5 1.6 1.6 1.6 

Petrochemical Production 0.9 1.1 1.2 1.1 1.1 1.1 1.2 1.1 1.0 

Iron and Steel Production 1.3 1.3 1.2 1.1 1.0 1.0 1.0 1.0 0.9 

Field Burning of Agricultural Residues 0.7 0.7 0.8 0.8 0.7 0.8 0.9 0.9 0.8 

Ferroalloy Production + + + + + + + + + 

Silicon Carbide Production 

and Consumption + + + + + + + + + 

International Bunker Fuelsb 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 

N2O 383.4 395.6 385.9 392.9 376.1 356.6 353.5 370.1 367.9 

Agricultural Soil Management 269.4 264.8 262.1 277.0 262.0 247.3 246.9 265.2 265.0 

Mobile Combustion 43.5 53.4 52.5 49.9 45.9 42.3 39.7 36.3 33.1 

Nitric Acid Production 17.0 18.9 18.6 15.1 16.4 15.4 15.2 15.8 15.6 

Stationary Combustion 12.8 13.4 14.6 14.1 14.0 14.3 14.6 14.8 14.5 

Manure Management 12.1 12.8 13.7 14.0 14.0 13.6 13.8 13.9 14.3 

Wastewater Treatment 6.3 6.9 7.6 7.8 7.6 7.7 7.8 8.0 8.1 

Adipic Acid Production 15.3 17.3 6.2 5.1 6.1 6.3 5.9 5.9 5.9 

N2O from Product Uses 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4 

Forest Land Remaining Forest Land 0.5 0.6 2.2 1.3 2.0 1.2 1.1 1.6 2.8 

Composting 0.4 0.8 1.4 1.4 1.4 1.6 1.7 1.7 1.8 

Settlements Remaining Settlements 1.0 1.2 1.2 1.4 1.5 1.5 1.6 1.5 1.5 

Field Burning of Agricultural Residues 0.4 0.4 0.5 0.5 0.4 0.4 0.5 0.5 0.5 

Municipal Solid Waste Combustion 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 

International Bunker Fuelsb 1.0 0.9 0.9 0.9 0.8 0.9 1.1 1.1 1.1 

HFCs 36.9 61.8 100.1 97.9 106.3 104.5 116.6 121.4 124.5 

Substitution of 

Ozone Depleting Substancesc 0.3 28.5 71.2 78.0 85.0 92.0 99.1 105.4 110.4 

HCFC-22 Production 36.4 33.0 28.6 19.7 21.1 12.3 17.2 15.8 13.8 

Semiconductor Manufacture 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.3 

PFCs 20.8 15.6 13.5 7.0 8.7 7.1 6.1 6.2 6.0 

Semiconductor Manufacture 2.2 3.8 4.9 3.5 3.5 3.3 3.3 3.2 3.6 

Aluminum Production 18.5 11.8 8.6 3.5 5.2 3.8 2.8 3.0 2.5 

SF6 32.7 28.0 19.1 18.7 18.0 18.1 18.0 18.2 17.3 

Electrical Transmission and Distribution 26.7 231.5 15.1 15.0 14.4 13.8 13.9 14.0 13.2 

Magnesium Production and Processing 5.4 5.6 3.0 2.9 2.9 3.4 3.2 3.3 3.2 

Semiconductor Manufacture 0.5 0.9 1.1 0.7 0.7 0.8 0.8 1.0 1.0 

Total 6,148.3 6,494.0 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2 

Net Emissions (Sources and Sinks) 5,410.6 5,718.7 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5 

+ Does not exceed 0.05 Tg CO2 Eq. a Parentheses indicate negative values or sequestration. The net CO2 flux total includes both emissions and sequestration, and constitutes a sink in the 

United States. Sinks are only included in net emissions total.

b Emissions from International Bunker Fuels and Biomass Combustion are not included in totals.

c Small amounts of PFC emissions also result from this source.

Note: Totals may not sum due to independent rounding. 

Note: One teragram (Tg) equals one million metric tons.
Executive Summary ES-7

relative to the other principal greenhouse gases, emissions 

of HFCs, PFCs, and SF6 are significant because many of 

them have extremely high global warming potentials and, 

in the cases of PFCs and SF6, long atmospheric lifetimes. 

Conversely, U.S. greenhouse gas emissions were partly 

offset by carbon sequestration in forests, trees in urban 

areas, agricultural soils, and landfilled yard trimmings and 

food scraps, which, in aggregate, offset 12.5 percent of total 

emissions in 2006. The following sections describe each 

gas’ contribution to total U.S. greenhouse gas emissions in 

more detail. 

Carbon Dioxide Emissions

The global carbon cycle is made up of large carbon flows 

and reservoirs. Billions of tons of carbon in the form of CO2

are absorbed by oceans and living biomass (i.e., sinks) and are 

emitted to the atmosphere annually through natural processes 

(i.e., sources). When in equilibrium, carbon fluxes among 

these various reservoirs are roughly balanced. Since the 

Industrial Revolution (i.e., about 1750), global atmospheric 

concentrations of CO2 have risen about 36 percent (IPCC 

2007), principally due to the combustion of fossil fuels. 

Within the United States, fuel combustion accounted for 94.2 

percent of CO2 emissions in 2006. Globally, approximately 

28,193 Tg of CO2 were added to the atmosphere through the 

combustion of fossil fuels in 2005, of which the United States 

accounted for about 20 percent.10 Changes in land use and 

forestry practices can also emit CO2 (e.g., through conversion 

of forest land to agricultural or urban use) or can act as a sink 

for CO2 (e.g., through net additions to forest biomass).

U.S. anthropogenic sources of CO2 are shown in 

Figure ES-5. As the largest source of U.S. greenhouse gas 

emissions, CO2 from fossil fuel combustion has accounted 

for approximately 79 percent of GWP-weighted emissions 

since 1990, growing slowly from 77 percent of total 

GWP-weighted emissions in 1990 to 80 percent in 2006. 

Emissions of CO2 from fossil fuel combustion increased at 

an average annual rate of 1.1 percent from 1990 to 2006. 

The fundamental factors influencing this trend include 

(1) a generally growing domestic economy over the last 16 

years, and (2) significant overall growth in emissions from 

electricity generation and transportation activities. Between 

10 Global CO2 emissions from fossil fuel combustion were taken from 

Energy Information Administration International Energy Annual 2005

(EIA 2007).

1990 and 2006, CO2 emissions from fossil fuel combustion 

increased from 4,724.1 Tg CO2 Eq. to 5,637.9 Tg CO2 Eq.—a 

19.3 percent total increase over the sixteen-year period. From 

2005 to 2006, these emissions decreased by 93.1 Tg CO2

Eq. (1.6 percent). 

Historically, changes in emissions from fossil fuel 

combustion have been the dominant factor affecting U.S. 

emission trends. Changes in CO2 emissions from fossil fuel 

combustion are influenced by many long-term and short-term 

factors, including population and economic growth, energy 

price fluctuations, technological changes, and seasonal 

temperatures. On an annual basis, the overall consumption 

of fossil fuels in the United States generally fluctuates in 

response to changes in general economic conditions, energy 

prices, weather, and the availability of non-fossil alternatives. 

For example, in a year with increased consumption of 

goods and services, low fuel prices, severe summer and 

winter weather conditions, nuclear plant closures, and lower 

precipitation feeding hydroelectric dams, there would likely 

be proportionally greater fossil fuel consumption than a 

year with poor economic performance, high fuel prices, 

mild temperatures, and increased output from nuclear and 

hydroelectric plants.

The four major fuel consuming end-use sectors 

contributing to CO2 emissions from fossil fuel combustion 

are industrial, transportation, residential, and commercial. 

Electricity generation also emits CO2, although these 

Figure ES-5

2006 Sources of CO2 Emissions

0 25 50 75 100 125 150 175

Tg CO2 Eq.

Zinc Production

Petroleum Systems <0.5

Lead Production <0.5

Silicon Carbide Production and Consumption <0.5

Phosphoric Acid Production

Ferroalloy Production

Carbon Dioxide Consumption

Titanium Dioxide Production

Petrochemical Production

Aluminum Production

Soda Ash Production and Consumption

Cropland Remaining Cropland

Limestone and Dolomite Use

Ammonia Production and Urea Consumption

Lime Production

Municipal Solid Waste Combustion

Natural Gas Systems

Cement Production

Iron and Steel Production

Non-Energy Use of Fuels

Fossil Fuel Combustion

5,637.9

C02 as a Portion

of all Emissions

84.8%
ES-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

emissions are produced as they consume fossil fuel to 

provide electricity to one of the four end-use sectors. For 

the discussion below, electricity generation emissions have 

been distributed to each end-use sector on the basis of each 

sector’s share of aggregate electricity consumption. This 

method of distributing emissions assumes that each end-use 

sector consumes electricity that is generated from the national 

average mix of fuels according to their carbon intensity. 

Emissions from electricity generation are also addressed 

separately after the end-use sectors have been discussed. 

Note that emissions from U.S. territories are calculated 

separately due to a lack of specific consumption data for the 

individual end-use sectors. 

Figure ES-6, Figure ES-7, and Table ES-3 summarize CO2

emissions from fossil fuel combustion by end-use sector.

Transportation End-Use Sector. Transportation activities 

(excluding international bunker fuels) accounted for 33 

percent of CO2 emissions from fossil fuel combustion in 

2006.11 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 2006. Just over half of these emissions 

resulted from direct fossil fuel combustion to produce steam 

and/or heat for industrial processes. The remaining emissions 

resulted from consuming electricity for motors, electric 

furnaces, ovens, lighting, and other applications.

Residential and Commercial End-Use Sectors. The 

residential and commercial end-use sectors accounted for 

20 and 18 percent, respectively, of CO2 emissions from 

fossil fuel combustion in 2006. Both sectors relied heavily 

on electricity for meeting energy demands, with 72 and 

79 percent, respectively, of their emissions attributable to 

electricity consumption for lighting, heating, cooling, and 

operating appliances. The remaining emissions were due to 

the consumption of natural gas and petroleum for heating 

and cooking.

Electricity Generation. The United States relies on 

electricity to meet a significant portion of its energy demands, 

especially for lighting, electric motors, heating, and air 

conditioning. Electricity generators consumed 36 percent of 

U.S. energy from fossil fuels and emitted 41 percent of the 

CO2 from fossil fuel combustion in 2006. The type of fuel 

combusted by electricity generators has a significant effect 

on their emissions. For example, some electricity is generated 

11 If emissions from international bunker fuels are included, the transportation 

end-use sector accounted for 35 percent of U.S. emissions from fossil fuel 

combustion in 2006.

Figure ES-6

2006 CO2 Emissions from Fossil Fuel 

Combustion by Sector and Fuel Type

Note: Electricity generation also includes emissions of less than 0.5 Tg CO2 Eq. from geothermal-based 

electricity generation.

Natural Gas

Petroleum

Coal

0

500

1,000

1,500

2,000

2,500

Relative Contribution

by Fuel Type

Tg CO2 Eq.

U.S. 

Territories

Commercial Residential Industrial Transportation Electricity

Generation

Figure ES-7

2006 End-Use Sector Emissions of CO2 from 

Fossil Fuel Combustion

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

U.S. Transportation

Territories

Commercial Residential Industrial

From Electricity

Consumption

From Direct Fossil

Fuel Combustion

Tg CO2 Eq.
Executive Summary ES-9

with low CO2 emitting energy technologies, particularly nonfossil options such as nuclear, hydroelectric, or geothermal 

energy. However, electricity generators rely on coal for over 

half of their total energy requirements and accounted for 94 

percent of all coal consumed for energy in the United States 

in 2006. Consequently, changes in electricity demand have 

a significant impact on coal consumption and associated 

CO2 emissions.

Other significant CO2 trends included the following: 

•	 CO2 emissions from non-energy use of fossil fuels have 

increased 20.8 Tg CO2 Eq. (18 percent) from 1990 

through 2006. Emissions from non-energy uses of fossil 

fuels were 138.0 Tg CO2 Eq. in 2006, which constituted 

2.4 percent of overall fossil fuel CO2 emissions and 2.3 

percent of total national CO2 emissions, approximately 

the same proportion as in 1990. 

•	 CO2 emissions from iron and steel production increased 

by 5.3 percent to 49.1 Tg CO2 Eq. in 2006, but have 

declined overall by 37.1 Tg CO2 Eq. (43 percent) 

from 1990 through 2006, due to restructuring of the 

industry, technological improvements, and increased 

scrap utilization. 

•	 In 2006, CO2 emissions from cement production 

decreased slightly by 0.2 Tg CO2 Eq. (0.4 percent) from 

2005 to 2006. This decrease occurs despite the overall 

increase over the time series. After falling in 1991 by two 

percent from 1990 levels, cement production emissions 

grew every year through 2005. Overall, from 1990 to 

2006, emissions from cement production increased by 

37 percent, an increase of 12.5 Tg CO2 Eq.

•	 CO2 emissions from municipal solid waste combustion 

(20.9 Tg CO2 Eq. in 2006) increased by 10.0 Tg CO2

Eq. (91 percent) from 1990 through 2006, as the volume 

of plastics and other fossil carbon-containing materials 

in municipal solid waste grew.

•	 CO2 emissions from ammonia production and urea 

consumption (12.4 Tg CO2 Eq. in 2006) have decreased 

by 4.5 Tg CO2 Eq. (27 percent) since 1990. The decrease 

in emissions from ammonia production and urea 

consumption is associated with an overall decrease in 

domestic ammonia production, and is due to several 

factors including market fluctuations and high natural 

gas prices.

•	 Net CO2 sequestration from Land Use, Land-Use 

Change, and Forestry increased by 146.0 Tg CO2 Eq. 

(20 percent) from 1990 through 2006. This increase was 

primarily due to an increase in the rate of net carbon 

accumulation in forest carbon stocks, particularly in 

aboveground and belowground tree biomass. Annual 

carbon accumulation in landfilled yard trimmings and 

food scraps slowed over this period, while the rate of 

carbon accumulation in urban trees increased.

Table ES-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Consuming End-Use Sector (Tg CO2 Eq.)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Transportation 1,488.1 1,602.5 1,801.6 1,779.2 1,832.3 1,811.8 1,860.9 1,874.5 1,861.0

Combustion 1,485.1 1,599.4 1,798.2 1,775.6 1,828.9 1,807.6 1,856.4 1,869.8 1,856.0

Electricity 3.0 3.0 3.4 3.6 3.4 4.2 4.5 4.7 4.9

Industrial 1,527.5 1,589.5 1,645.1 1,583.9 1,572.5 1,592.1 1,596.8 1,579.6 1,567.1

Combustion 844.9 876.5 860.3 852.5 854.8 856.0 857.7 847.3 862.2

Electricity 682.5 713.1 784.7 731.4 717.7 736.1 739.0 732.3 704.9

Residential 929.5 995.5 1,129.7 1,121.8 1,145.6 1,178.3 1,173.1 1,206.4 1,151.9

Combustion 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5

Electricity 589.4 639.0 757.6 758.1 785.1 795.4 804.9 847.9 825.4

Commercial 750.8 810.0 964.6 973.5 970.3 983.8 997.1 1,017.3 1,003.0

Combustion 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1

Electricity 534.7 584.2 736.6 751.1 747.5 747.3 766.5 795.4 792.9

U.S. Territories 28.3 35.0 36.2 49.0 44.0 51.0 53.5 53.2 54.9

Total 4,724.1 5,032.4 5,577.1 5,507.4 5,564.8 5,617.0 5,681.4 5,731.0 5,637.9

Electricity Generation 1,809.6 1,939.3 2,282.3 2,244.3 2,253.7 2,283.1 2,314.9 2,380.2 2,328.2

Note: Totals may not sum due to independent rounding. Combustion-related emissions from electricity generation are allocated based on aggregate 

national electricity consumption by each end-use sector.
ES-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Methane Emissions

According to the IPCC, CH4 is more than 20 times as 

effective as CO2 at trapping heat in the atmosphere. Over the 

last two hundred and fifty years, the concentration of CH4

in the atmosphere increased by 148 percent (IPCC 2007). 

Anthropogenic sources of CH4 include landfills, natural gas 

and petroleum systems, agricultural activities, coal mining, 

wastewater treatment, stationary and mobile combustion, and 

certain industrial processes (see Figure ES-8).

Some significant trends in U.S. emissions of CH4 include 

the following: 

•	 Enteric fermentation is the largest anthropogenic source 

of CH4 emissions in the United States. In 2006, enteric 

fermentation CH4 emissions were 126.2 Tg CO2 Eq. 

(approximately 22.7 percent of total CH4 emissions), 

which represents a decline of 0.7 Tg CO2 Eq., or 0.6 

percent, since 1990. Despite this overall decline in 

emissions, the last two years have shown a slight 

increase in emissions.

•	 Landfills are the second largest anthropogenic source 

of CH4 emissions in the United States, accounting for 

approximately 22.6 percent of total CH4 emissions 

(125.7 Tg CO2 Eq.) in 2006. From 1990 to 2006, net 

CH4 emissions from landfills decreased by 23.9 Tg 

CO2 Eq. (16 percent), with small increases occurring 

in some interim years, including 2006. This downward 

trend in overall emissions is the result of increases in 

the amount of landfill gas collected and combusted,12

which has more than offset the additional CH4

emissions resulting from an increase in the amount of 

municipal solid waste landfilled. 

•	 CH4 emissions from natural gas systems were 102.4 

Tg CO2 Eq. in 2006; emissions have declined by 22.3 

Tg CO2 Eq. (18 percent) since 1990. This decline 

has been due to improvements in technology and 

management practices, as well as some replacement of 

old equipment.

•	 In 2006, CH4 emissions from coal mining were 58.5 Tg 

CO2 Eq., a 1.4 Tg CO2 Eq. (2.5 percent) increase over 

2005 emission levels. The overall decline of 25.6 Tg CO2

Eq. (30 percent) from 1990 results from the mining of less 

gassy coal from underground mines and the increased use 

of CH4 collected from degasification systems.

•	 CH4 emissions from manure management increased by 

34 percent for CH4, from 31.0 Tg CO2 Eq. in 1990 to 

41.4 Tg CO2 Eq. in 2006. The majority of this increase 

was from swine and dairy cow manure, since the general 

trend in manure management is one of increasing use 

of liquid systems, which tends to produce greater CH4

emissions. The increase in liquid systems is the combined 

result of a shift to larger facilities, and to facilities in 

the West and Southwest, all of which tend to use liquid 

systems. Also, new regulations limiting the application 

of manure nutrients have shifted manure management 

practices at smaller dairies from daily spread to manure 

managed and stored on site. 

Nitrous Oxide Emissions

N2O is produced by biological processes that occur in 

soil and water and by a variety of anthropogenic activities 

in the agricultural, energy-related, industrial, and waste 

management fields. While total N2O emissions are much 

lower than CO2 emissions, N2O is approximately 300 times 

more powerful than CO2 at trapping heat in the atmosphere. 

Since 1750, the global atmospheric concentration of N2O 

has risen by approximately 18 percent (IPCC 2007). The 

main anthropogenic activities producing N2O in the United 

States are agricultural soil management, fuel combustion 

12The CO2 produced from combusted landfill CH4 at landfills is not counted 

in national inventories as it is considered part of the natural C cycle of 

decomposition.

Figure ES-8

2006 Sources of CH4 Emissions

CH4 as a Portion

of all Emissions

0 20 40 60 80 100 120 140

Tg CO2

 Eq.

7.9%

Silicon Carbide Production and Consumption <0.05

Ferroalloy Production <0.05

Field Burning of Agricultural Residues

Iron and Steel Production

Petrochemical Production

Composting

Mobile Combustion

Abandoned Coal Mines

Rice Cultivation

Stationary Combustion

Wastewater Treatment

Forest Land Remaining Forest Land

Petroleum Systems

Manure Management

Coal Mining

Natural Gas Systems

Landfills

Enteric Fermentation
Executive Summary ES-11

in motor vehicles, nitric acid production, stationary fuel 

combustion, manure management, and wastewater treatment 

(see Figure ES-9).

Some significant trends in U.S. emissions of N2O include 

the following:

•	 Agricultural soils produced approximately 72 percent of 

N2O emissions in the United States in 2006. Estimated 

emissions from this source in 2006 were 265.0 Tg 

CO2 Eq. Annual N2O emissions from agricultural soils 

fluctuated between 1990 and 2006, although overall 

emissions were 1.6 percent lower in 2006 than in 1990. 

N2O emissions from this source have not shown any 

significant long-term trend, as they are highly sensitive 

to the amount of N applied to soils, which has not 

changed significantly over the time-period, and to 

weather patterns and crop type.

•	 In 2006, N2O emissions from mobile combustion were 

33.1 Tg CO2 Eq. (approximately 9 percent of U.S. N2O 

emissions). From 1990 to 2006, N2O emissions from 

mobile combustion decreased by 24 percent. However, 

from 1990 to 1998 emissions increased by 26 percent, 

due to control technologies that reduced NOx emissions 

while increasing N2O emissions. Since 1998, newer 

control technologies have led to a steady decline in N2O 

from this source.

•	 N2O emissions from adipic acid production were 5.9 

Tg CO2 Eq. in 2006, and have decreased significantly 

in recent years from the widespread installation of 

pollution control measures. Emissions from adipic acid 

production have decreased 61 percent since 1990, and 

emissions from adipic acid production have fluctuated 

by less than 1 Tg CO2 Eq. annually since 1998.

HFC, PFC, and SF6 Emissions

HFCs and PFCs are families of synthetic chemicals 

that are used as alternatives to the ODSs, which are being 

phased out under the Montreal Protocol and Clean Air 

Act Amendments of 1990. HFCs and PFCs do not deplete 

the stratospheric ozone layer, and are therefore acceptable 

alternatives under the Montreal Protocol.

These compounds, however, along with SF6, are 

potent greenhouse gases. In addition to having high 

global warming potentials, SF6 and PFCs have extremely 

long atmospheric lifetimes, resulting in their essentially 

irreversible accumulation in the atmosphere once emitted. 

Sulfur hexafluoride is the most potent greenhouse gas the 

IPCC has evaluated.

Other emissive sources of these gases include HCFC-22 

production, electrical transmission and distribution systems, 

semiconductor manufacturing, aluminum production, and 

magnesium production and processing (see Figure ES-10).

Some significant trends in U.S. HFC, PFC, and SF6

emissions include the following:

•	 Emissions resulting from the substitution of ozone 

depleting substances (e.g., CFCs) have been increasing 

from small amounts in 1990 to 110.4 Tg CO2 Eq. in 

2006. Emissions from substitutes for ozone depleting 

substances are both the largest and the fastest 

growing source of HFC, PFC, and SF6 emissions. 

These emissions have been increasing as phase-outs 

required under the Montreal Protocol come into effect, 

especially after 1994 when full market penetration 

was made for the first generation of new technologies 

featuring ODS substitutes.

•	 HFC emissions from the production of HCFC-22 

decreased by 62 percent (22.6 Tg CO2 Eq.) from 

1990 through 2006, due to a steady decline in the 

emission rate of HFC-23 (i.e., the amount of HFC-23 

0 10 20 30 40 50

N20 as a Portion

of all Emissions

5.2%

265.0

Tg CO2 Eq.

Municipal Solid Waste Combustion

Field Burning of Agricultural Residues

Settlements Remaining Settlements

Composting

Forest Land Remaining Forest Land

N2O from Product Uses

Adipic Acid Production

Wastewater Treatment

Manure Management

Stationary Combustion

Nitric Acid Production

Mobile Combustion

Agricultural Soil Management

<0.5

Figure ES-9

2006 Sources of N2O Emissions
ES-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

emitted per kilogram of HCFC-22 produced) and the 

use of thermal oxidation at some plants to reduce 

HFC-23 emissions. 

•	 SF6 emissions from electric power transmission and 

distribution systems decreased by 51 percent (13.5 

Tg CO2 Eq.) from 1990 to 2006, primarily because of 

higher purchase prices for SF6 and efforts by industry 

to reduce emissions.

•	 PFC emissions from aluminum production decreased by 

87 percent (16.1 Tg CO2 Eq.) from 1990 to 2006, due 

to both industry emission reduction efforts and lower 

domestic aluminum production. 

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. 

Emissions of all gases can be summed from each source 

category from IPCC guidance. Over the sixteen-year period 

of 1990 to 2006, total emissions in the Energy, Industrial 

Processes, and Agriculture sectors climbed by 873.0 Tg 

CO2 Eq. (17 percent), 21.0 Tg CO2 Eq. (7 percent), and 6.6 

Tg CO2 Eq. (1 percent), respectively. Emissions decreased 

in the Waste and Solvent and Other Product Use sectors by 

18.6 Tg CO2 Eq. (10 percent) and less than 0.1 Tg CO2 Eq. 

(less than 1 percent), respectively. Over the same period, 

estimates of net C sequestration in the Land Use, Land-Use 

Change, and Forestry sector increased by 122.2 Tg CO2 Eq. 

(17 percent).

Energy 

The Energy chapter contains emissions of all greenhouse 

gases resulting from stationary and mobile energy activities 

including fuel combustion and fugitive fuel emissions. 

Energy-related activities, primarily fossil fuel combustion, 

accounted for the vast majority of U.S. CO2 emissions for 

the period of 1990 through 2006. In 2006, approximately 

83 percent of the energy consumed in the United States (on 

a Btu basis) was produced through the combustion of fossil 

fuels. The remaining 17 percent came from other energy 

sources such as hydropower, biomass, nuclear, wind, and 

solar energy (see Figure ES-12). Energy-related activities are 

also responsible for CH4 and N2O emissions (37 percent and 

13 percent of total U.S. emissions of each gas, respectively). 

Overall, emission sources in the Energy chapter account 

for a combined 86.1 percent of total U.S. greenhouse gas 

emissions in 2006.

Tg CO2 Eq.

HFCs, PFCs, and

SF6 as a Portion of

all Emissions

0 25 50 75 100 125

2.1%

Aluminum Production

Magnesium Production

and Processing

Semiconductor

Manufacture

Electrical Transmission

and Distribution

HCFC-22 Production

Substitution of Ozone

Depleting Substances

Figure ES-10

2006 Sources of HFCs, PFCs, and SF6 Emissions

Figure ES-11

U.S. Greenhouse Gas Emissions and Sinks 

by Chapter/IPCC Sector

Tg CO2 Eq.

19901991199219931994199519961997199819992000200120022003200420052006

Agriculture

Energy

(1,000)

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Land Use, Land-Use Change and Forestry (sinks)

Waste

Industrial Processes LULUCF (sources)

Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and 

Other Product Use sector.
Executive Summary ES-13

Industrial Processes

The Industrial Processes chapter contains byproduct 

or fugitive emissions of greenhouse gases from industrial 

processes not directly related to energy activities such as 

fossil fuel combustion. For example, industrial processes 

can chemically transform raw materials, which often 

release waste gases such as CO2, CH4, and N2O. These 

processes include iron and steel production, cement 

production, ammonia production and urea consumption, 

lime production, limestone and dolomite use (e.g., flux 

stone, flue gas desulfurization, and glass manufacturing), 

soda ash production and use, titanium dioxide production, 

phosphoric acid production, ferroalloy production, CO2

consumption, silicon carbide production and consumption, 

aluminum production, petrochemical production, nitric acid 

production, adipic acid production, lead production, and zinc 

production. Additionally, emissions from industrial processes 

release HFCs, PFCs, and SF6. Overall, emission sources in 

the Industrial Processes chapter account for 4.5 percent of 

U.S. greenhouse gas emissions in 2006.

Solvent and Other Product Use

The Solvent and Other Product Use chapter contains 

greenhouse gas emissions that are produced as a byproduct of 

various solvent and other product uses. In the United States, 

emissions from N2O from Product Uses, the only source of 

greenhouse gas emissions from this sector, accounted for less 

than 0.1 percent of total U.S. anthropogenic greenhouse gas 

emissions on a carbon equivalent basis in 2006. 

Agriculture

The Agriculture chapter contains anthropogenic 

emissions from agricultural activities (except fuel combustion, 

which is addressed in the Energy chapter, and agricultural 

CO2 fluxes, which are addressed in the Land Use, LandUse Change, and Forestry Chapter). Agricultural activities 

contribute directly to emissions of greenhouse gases through 

a variety of processes, including the following source 

categories: enteric fermentation in domestic livestock, 

livestock manure management, rice cultivation, agricultural 

Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg CO2 Eq.)

Chapter/IPCC Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Energy 5,203.9 5,529.6 6,067.8 5,982.8 6,036.3 6,078.3 6,150.9 6,174.4 6,076.9 

Industrial Processes 299.9 315.7 326.5 297.9 308.6 301.2 315.9 315.5 320.9 

Solvent and Other Product Use 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4 

Agriculture 447.5 453.8 447.9 463.7 449.0 434.3 432.1 453.6 454.1 

Land Use, Land-Use Change, and 

Forestry (Emissions) 13.1 13.6 30.0 20.0 28.4 19.7 17.1 23.2 36.9 

Waste 179.6 176.8 155.6 152.1 154.5 160.3 157.7 158.7 161.0 

Total Emissions 6,148.3 6,494.0 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2 

Net CO2 Flux from Land Use, Land-Use 

Change, and Forestry (Sinks)* (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Net Emissions (Sources and Sinks) 5,410.6 5,718.7 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5 

* The net CO2 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions total.

Note: Totals may not sum due to independent rounding. Parentheses indicate negative values or sequestration.

Figure ES-12

2006 U.S. Energy Consumption by Energy Source

Petroleum 39%

Coal 22%

Natural Gas 22%

Renewable 9%

Nuclear 8%
ES-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

soil management, and field burning of agricultural residues. 

CH4 and N2O were the primary greenhouse gases emitted 

by agricultural activities. CH4 emissions from enteric 

fermentation and manure management represented about 

23 percent and 7 percent of total CH4 emissions from 

anthropogenic activities, respectively, in 2006. Agricultural 

soil management activities such as fertilizer application 

and other cropping practices were the largest source of U.S. 

N2O emissions in 2006, accounting for 72 percent. In 2006, 

emission sources accounted for in the Agricultural chapters 

were responsible for 6.4 percent of total U.S. greenhouse 

gas emissions.

Land Use, Land-Use Change, and Forestry 

The Land Use, Land-Use Change, and Forestry chapter 

contains emissions of CH4 and N2O, and emissions and 

removals of CO2 from forest management, other land-use 

activities, and land-use change. Forest management practices, 

tree planting in urban areas, the management of agricultural 

soils, and the landfilling of yard trimmings and food scraps 

have resulted in a net uptake (sequestration) of C in the 

United States. Forests (including vegetation, soils, and 

harvested wood) accounted for approximately 84 percent of 

total 2006 net CO2 flux, urban trees accounted for 11 percent, 

mineral and organic soil carbon stock changes accounted 

for 5 percent, and landfilled yard trimmings and food scraps 

accounted for 1 percent of the total net flux in 2006. The 

net forest sequestration is a result of net forest growth and 

increasing forest area, as well as a net accumulation of carbon 

stocks in harvested wood pools. The net sequestration in 

urban forests is a result of net tree growth in these areas. 

In agricultural soils, mineral and organic soils sequester 

approximately 70 percent more C than is emitted through 

these soils, liming, and urea fertilization, combined. The 

mineral soil C sequestration is largely due to the conversion 

of cropland to permanent pastures and hay production, a 

reduction in summer fallow areas in semi-arid areas, an 

increase in the adoption of conservation tillage practices, 

and an increase in the amounts of organic fertilizers (i.e., 

manure and sewage sludge) applied to agriculture lands. The 

landfilled yard trimmings and food scraps net sequestration is 

due to the long-term accumulation of yard trimming carbon 

and food scraps in landfills. Land use, land-use change, and 

forestry activities in 2006 resulted in a net C sequestration 

of 883.7 Tg CO2 Eq. (Table ES-5). This represents an offset 

of approximately 14.8 percent of total U.S. CO2 emissions, 

or 12.5 percent of total greenhouse gas emissions in 2006. 

Between 1990 and 2006, total land use, land-use change, and 

forestry net C flux resulted in a 20 percent increase in CO2

sequestration, primarily due to an increase in the rate of net C 

accumulation in forest C stocks, particularly in aboveground 

and belowground tree biomass. Annual C accumulation in 

landfilled yard trimmings and food scraps slowed over this 

period, while the rate of annual C accumulation increased 

in urban trees. 

Emissions from Land Use, Land-Use Change, and 

Forestry are shown in Table ES-6. The application of crushed 

limestone and dolomite to managed land (i.e., soil liming) and 

urea fertilization resulted in CO2 emissions of 8.0 Tg CO2

Eq. in 2006, an increase of 13 percent relative to 1990. The 

application of synthetic fertilizers to forest and settlement 

soils in 2006 resulted in direct N2O emissions of 1.8 Tg 

CO2 Eq. Direct N2O emissions from fertilizer application 

increased by approximately 74 percent between 1990 and 

2006. Non-CO2 emissions from forest fires in 2006 resulted 

in CH4 emissions of 24.6 Tg CO2 Eq., and in N2O emissions 

of 2.5 Tg CO2 Eq.
Executive Summary ES-15

Waste

The Waste chapter contains emissions from waste 

management activities (except waste incineration, which is 

addressed in the Energy chapter). Landfills were the largest 

source of anthropogenic CH4 emissions in the Waste chapter, 

accounting for 23 percent of total U.S. CH4 emissions.13

Additionally, wastewater treatment accounts for 4 percent 

of U.S. CH4 emissions. N2O emissions from the discharge 

of wastewater treatment effluents into aquatic environments 

were estimated, as were N2O emissions from the treatment 

process itself. Emissions of CH4 and N2O from composting 

13 Landfills also store carbon, due to incomplete degradation of organic 

materials such as wood products and yard trimmings, as described in the 

Land-Use, Land-Use Change, and Forestry chapter.

grew from 1990 to 2006, and resulted in emissions of 1.6 Tg 

CO2 Eq. and 1.8 Tg CO2 Eq., respectively. Overall, in 2006, 

emission sources accounted for in the Waste chapter generated 

2.3 percent of total U.S. greenhouse gas emissions.

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 

Table ES-5: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)

Sink Category 1990 1995 2000 2001 2002 2003 2004 2005 2006

Forest Land Remaining Forest Land (621.7) (659.9) (550.7) (623.4) (697.3) (730.9) (741.4) (743.6) (745.1)

Cropland Remaining Cropland (30.1) (39.4) (38.4) (40.0) (40.3) (40.5) (40.9) (41.0) (41.8)

Land Converted to Cropland 14.7 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 

Grassland Remaining Grassland (1.9) 16.6 16.4 16.4 16.4 16.4 16.3 16.3 16.2 

Land Converted to Grassland (14.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3)

Settlements Remaining Settlements (60.6) (71.5) (82.4) (84.6) (86.8) (88.9) (91.1) (93.3) (95.5)

Other (Landfilled Yard 

Trimmings and Food Scraps) (23.9) (14.1) (11.5) (11.6) (11.8) (10.0) (9.6) (10.0) (10.5)

Total (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration. 

Table ES-6: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)

Source Category 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0 

Cropland Remaining Cropland: Liming 

of Agricultural Soils & Urea Fertilization 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0 

CH4 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 

Forest Land Remaining Forest Land: 

Forest Fires 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 

N2O 1.5 1.8 3.5 2.7 3.5 2.7 2.6 3.1 4.3 

Forest Land Remaining Forest Land: 

Forest Fires 0.5 0.5 1.9 1.0 1.7 0.9 0.7 1.2 2.5 

Forest Land Remaining Forest Land: 

Forest Soils 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Settlements Remaining Settlements:

Settlement Soils 1.0 1.2 1.2 1.4 1.5 1.5 1.6 1.5 1.5 

Total 13.1 13.6 30.0 20.0 28.4 19.7 17.1 23.2 36.9 

Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration. 
ES-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

emissions into more commonly used sectoral categories. 

This section reports emissions by the following economic 

sectors: Residential, Commercial, Industry, Transportation, 

Electricity Generation, Agriculture, and U.S. Territories. 

Table ES-7 summarizes emissions from each of these 

sectors, and Figure ES-13 shows the trend in emissions by 

sector from 1990 to 2006.

Using this categorization, emissions from electricity 

generation accounted for the largest portion (34 percent) 

of U.S. greenhouse gas emissions in 2006. Transportation 

activities, in aggregate, accounted for the second largest 

portion (28 percent). Emissions from industry accounted 

for 19 percent of U.S. greenhouse gas emissions in 2006. 

In contrast to electricity generation and transportation, 

emissions from industry have in general declined over the 

past decade. The long-term decline in these emissions has 

been due to structural changes in the U.S. economy (i.e., shifts 

from a manufacturing-based to a service-based economy), 

fuel switching, and energy efficiency improvements. The 

remaining 19 percent of U.S. greenhouse gas emissions were 

contributed by the residential, agriculture, and commercial 

sectors, plus emissions from U.S. territories. The residential 

sector accounted for about 5 percent, and primarily consisted 

of CO2 emissions from fossil fuel combustion. Activities 

related to agriculture accounted for roughly 8 percent of 

U.S. emissions; unlike other economic sectors, agricultural 

sector emissions were dominated by N2O emissions from 

agricultural soil management and CH4 emissions from enteric 

fermentation, rather than CO2 from fossil fuel combustion. 

The commercial sector accounted for about 6 percent of 

emissions, while U.S. territories accounted for 1 percent.

CO2 was also emitted and sequestered by a variety 

of activities related to forest management practices, tree 

planting in urban areas, the management of agricultural soils, 

and landfilling of yard trimmings. 

Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO2 Eq.)

Implied Sectors 1990 1995 2000 2001 2002 2003 2004 2005 2006

Electric Power Industry 1,859.1 1,989.7 2,328.9 2,290.9 2,300.4 2,329.4 2,363.4 2,430.0 2,377.8

Transportation 1,544.1 1,685.8 1,917.5 1,895.8 1,948.5 1,925.9 1,975.4 1,987.2 1,969.5

Industry 1,460.3 1,478.0 1,432.9 1,384.3 1,384.9 1,375.5 1,388.9 1,354.3 1,371.5

Agriculture 506.8 524.1 528.0 533.4 529.3 498.0 499.2 521.3 533.6

Commercial 396.9 404.5 390.3 383.0 388.1 410.2 404.6 400.4 394.6

Residential 346.9 370.9 387.7 379.3 376.6 399.6 385.5 376.0 344.8

U.S. Territories 34.1 41.1 47.3 54.5 53.3 59.7 61.0 60.5 62.4

Total Emissions 6,148.3 6,494.0 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2

Land Use, Land-Use Change, and 

Forestry (Sinks) (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Net 5,410.6 5,718.7 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5

Note: Totals may not sum due to independent rounding. Emissions include CO2, CH4, N2O, HFCs, PFCs, and SF6. See Table 2-12 for more detailed data.

Figure ES-13

Emissions Allocated to Economic Sectors

0

500

1,000

1,500

2,000

2,500

19901991199219931994199519961997199819992000200120022003200420052006

Residential

Agriculture

Electricity Generation

Tg CO2 Eq.

Industry

Transportation

Commercial

Note: Does not include U.S. territories.
Executive Summary ES-17

Electricity is ultimately consumed in the economic 

sectors described above. Table ES-8 presents greenhouse 

gas emissions from economic sectors with emissions related 

to electricity generation distributed into end-use categories 

(i.e., emissions from electricity generation are allocated to 

the economic sectors in which the electricity is consumed). 

To distribute electricity emissions among end-use sectors, 

emissions from the source categories assigned to electricity 

generation were allocated to the residential, commercial, 

industry, transportation, and agriculture economic sectors 

according to retail sales of electricity.14 These source 

categories include CO2 from fossil fuel combustion and the 

use of limestone and dolomite for flue gas desulfurization, 

CO2 and N2O from waste combustion, CH4 and N2O from 

stationary sources, and SF6 from electrical transmission and 

distribution systems.

When emissions from electricity are distributed among 

these sectors, industry accounts for the largest share of U.S. 

greenhouse gas emissions (29 percent) in 2006. Emissions 

from the residential and commercial sectors also increase 

substantially when emissions from electricity are included, 

due to their relatively large share of electricity consumption 

(e.g., lighting, appliances, etc.). Transportation activities 

remain the second largest contributor to total U.S. emissions 

(28 percent). In all sectors except agriculture, CO2 accounts 

for more than 80 percent of greenhouse gas emissions, 

primarily from the combustion of fossil fuels. Figure ES14 shows the trend in these emissions by sector from 1990 

to 2006.

14Emissions were not distributed to U.S. territories, since the electricity 

generation sector only includes emissions related to the generation of 

electricity in the 50 states and the District of Columbia.

Figure ES-14

Emissions with Electricity Distributed 

to Economic Sectors

Note: Does not include U.S. territories.

0

500

1,000

1,500

2,000

2,500

Agriculture

Residential

Commercial

Transportation

Industrial

19901991199219931994199519961997199819992000200120022003200420052006

Tg CO2 Eq.

Table ES-8: U.S. Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions 

Distributed (Tg CO2 Eq.)

Implied Sectors 1990 1995 2000 2001 2002 2003 2004 2005 2006

Industry 2,100.4 2,141.1 2,174.3 2,061.1 2,051.6 2,064.0 2,075.4 2,038.3 2,029.2

Transportation 1,547.2 1,688.9 1,921.0 1,899.4 1,952.0 1,930.2 1,980.0 1,992.0 1,974.5

Commercial 946.3 1,003.8 1,141.9 1,149.8 1,151.1 1,172.7 1,187.2 1,212.5 1,204.4

Residential 952.4 1,026.5 1,160.7 1,153.2 1,178.0 1,211.2 1,207.2 1,241.7 1,187.8

Agriculture 567.9 592.5 587.4 603.2 595.1 560.5 567.2 584.9 595.8

U.S. Territories 34.1 41.1 47.3 54.5 53.3 59.7 61.0 60.5 62.4

Total Emissions 6,148.3 6,494.0 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2

Land Use, Land-Use Change, 

and Forestry (Sinks) (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Net Emissions (Sources and Sinks) 5,410.6 5,718.7 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5

See Table 2-14 of this report for more detailed data.
ES-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Total emissions can be compared to other economic and social indices to highlight changes over time. These comparisons include: (1) 

emissions per unit of aggregate energy consumption, because energy-related activities are the largest sources of emissions, (2) emissions 

per unit of fossil fuel consumption, because almost all energy-related emissions involve the combustion of fossil fuels, (3) emissions per 

unit of electricity consumption, because the electric power industry—utilities and nonutilities combined—was the largest source of U.S. 

greenhouse gas emissions in 2006, (4) emissions per unit of total gross domestic product as a measure of national economic activity, or 

(5) emissions per capita. 

Table ES-9 provides data on various statistics related to U.S. greenhouse gas emissions normalized to 1990 as a baseline year. Greenhouse 

gas emissions in the United States have grown at an average annual rate of 0.9 percent since 1990. This rate is slightly slower than that for 

total energy or fossil fuel consumption and much slower than that for either electricity consumption or overall gross domestic product. Total 

U.S. greenhouse gas emissions have also grown slightly slower than national population since 1990 (see Figure ES-15). 

Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data

U.S. Greenhouse Gas Emissions Per Capita and 

Per Dollar of Gross Domestic Product

Figure ES-15

Emissions 

per $GDP 

Emissions 

per capita 

Population

Real GDP

70

80

90

100

150

160

140

130

120

110

Index (1990 = 100)

19901991199219931994199519961997199819992000200120022003200420052006

Source: BEA (2007), U.S. Census Bureau (2007), and emission estimates in this report.

Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100)

Variable 1990 1995 2000 2001 2002 2003 2004 2005 2006 Growth 

Ratea

GDPb 100 113 138 139 141 145 150 155 159 3.0%

Electricity Consumptionc 100 112 127 125 128 129 131 134 135 1.9%

Fossil Fuel Consumptionc 100 107 117 115 116 116 119 119 117 1.0%

Energy Consumptionc 100 108 116 112 115 115 118 118 117 1.0%

Populationd 100 107 113 114 115 116 117 118 119 1.1%

Greenhouse Gas Emissionse 100 106 114 113 114 114 115 116 115 0.9%

a

 Average annual growth rate

b

 Gross Domestic Product in chained 2000 dollars (BEA 2007)

c

 Energy content-weighted values (EIA 2007)

d

 U.S. Census Bureau (2007)

e

 GWP-weighted values
Executive Summary ES-19

Indirect Greenhouse Gases (CO, NOx, 

NMVOCs, and SO2)

The reporting requirements of the UNFCCC15 request 

that information be provided on indirect greenhouse gases, 

which include CO, NOx, NMVOCs, and SO2. These gases do 

15 See <http://unfccc.int/resource/docs/cop8/08.pdf>.

not have a direct global warming effect, but indirectly affect 

terrestrial radiation absorption by influencing the formation 

and destruction of tropospheric and stratospheric ozone, or, 

in the case of SO2, by affecting the absorptive characteristics 

of the atmosphere. Additionally, some of these gases may 

Table ES-10: Emissions of NOx, CO, NMVOCs, and SO2 (Gg)

Gas/Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

NOx 21,645 21,272 19,203 18,410 17,938 17,043 16,177 15,569 14,869

Mobile Fossil Fuel Combustion 10,920 10,622 10,310 9,819 10,154 9,642 9,191 8,739 8,287

Stationary Fossil Fuel Combustion 9,883 9,821 8,002 7,667 6,791 6,419 6,004 5,853 5,610

Industrial Processes 591 607 626 656 534 528 524 519 515

Oil and Gas Activities 139 100 111 113 321 316 316 316 315

Municipal Solid Waste Combustion 82 88 114 114 98 97 97 97 97

Agricultural Burning 28 29 35 35 33 34 39 39 38

Solvent Use 1 3 3 3 5 5 5 5 5

Waste 0 1 2 2 2 2 2 2 2

CO 130,461 109,032 92,777 89,212 84,609 80,221 76,342 72,365 68,372

Mobile Fossil Fuel Combustion 119,360 97,630 83,559 79,851 75,421 71,038 67,096 63,154 59,213

Stationary Fossil Fuel Combustion 5,000 5,383 4,340 4,377 4,965 4,893 4,876 4,860 4,844

Industrial Processes 4,125 3,959 2,217 2,339 1,744 1,724 1,724 1,724 1,724

Municipal Solid Waste Combustion 978 1,073 1,670 1,672 1,439 1,437 1,437 1,437 1,437

Agricultural Burning 691 663 792 774 709 800 879 860 825

Oil and Gas Activities 302 316 146 147 323 321 321 321 322

Waste 1 2 8 8 7 7 7 7 7

Solvent Use 5 5 46 45 1 1 1 1 1

NMVOCs 20,930 19,520 15,228 15,048 15,640 15,170 14,807 14,444 14,082

Mobile Fossil Fuel Combustion 10,932 8,745 7,230 6,872 7,235 6,885 6,587 6,289 5,991

Solvent Use 5,216 5,609 4,384 4,547 3,881 3,862 3,854 3,846 3,839

Industrial Processes 2,422 2,642 1,773 1,769 2,036 1,972 1,931 1,890 1,849

Stationary Fossil Fuel Combustion 912 973 1,077 1,080 1,585 1,560 1,553 1,545 1,538

Oil and Gas Activities 554 582 389 400 545 538 533 528 523

Municipal Solid Waste Combustion 222 237 257 258 243 239 237 235 232

Waste 673 731 119 122 115 114 112 111 110

Agricultural Burning NA NA NA NA NA NA NA NA NA

SO2 20,935 16,891 14,829 14,452 13,403 13,631 13,232 13,114 12,258

Stationary Fossil Fuel Combustion 18,407 14,724 12,848 12,461 11,613 11,956 11,625 11,573 10,784

Industrial Processes 1,307 1,117 1,031 1,047 850 804 800 797 793

Mobile Fossil Fuel Combustion 793 672 632 624 683 621 564 508 451

Oil and Gas Activities 390 335 286 289 233 226 220 213 207

Municipal Solid Waste Combustion 38 42 29 30 23 22 22 22 22

Waste 0 1 1 1 1 1 1 1 1

Solvent Use 0 1 1 1 0 0 0 0 0

Agricultural Burning NA NA NA NA NA NA NA NA NA

Source: (EPA 2008, disaggregated based on EPA 2003) except for estimates from field burning of agricultural residues.

NA (Not Available)

Note: Totals may not sum due to independent rounding.
ES-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

react with other chemical compounds in the atmosphere to 

form compounds that are greenhouse gases.

Since 1970, the United States has published estimates 

of annual emissions of CO, NOx, NMVOCs, and SO2 (EPA 

2008),16 which are regulated under the Clean Air Act. Table 

ES-10 shows that fuel combustion accounts for the majority 

of emissions of these indirect greenhouse gases. Industrial 

processes—such as the manufacture of chemical and allied 

products, metals processing, and industrial uses of solvents—

are also significant sources of CO, NOx, and NMVOCs.

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 

16NOx and CO emission estimates from field burning of agricultural residues 

were estimated separately, and therefore not taken from EPA (2008).

level of emissions, the trend in emissions, or both.”17 By 

definition, key categories are sources or sinks that have the 

greatest contribution to the absolute overall level of national 

emissions in any of the years covered by the time series. In 

addition, when an entire time series of emission estimates 

is prepared, a thorough investigation of key categories 

must also account for the influence of trends of individual 

source and sink categories. Finally, a qualitative evaluation 

of key categories should be performed, in order to capture 

any key categories that were not identified in either of the 

quantitative analyses.

Figure ES-16 presents 2006 emission estimates for 

the key categories as defined by a level analysis (i.e., the 

contribution of each source or sink category to the total 

inventory level). The UNFCCC reporting guidelines 

request that key category analyses be reported at an 

appropriate level of disaggregation, which may lead 

17See Chapter 7 “Methodological Choice and Recalculation” in IPCC (2000). 

<http://www.ipcc-nggip.iges.or.jp/public/gp/gpgaum.htm>

Figure ES-16

2006 Key Categories-Tier 1 Level Assessment

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 2,200

Tg CO2 Eq.

CH4 Emissions from Manure Management

CO2 Emissions from Mobile Combustion: Marine

CO2 Emissions from Cement Production

CO2 Emissions from Iron and Steel Production

Indirect N2O Emissions from Applied Nitrogen

Fugitive CH4 Emissions from Coal Mining

Fugitive CH4 Emissions from Natural Gas Systems

Emissions from Substitutes for Ozone Depleting Substances

CH4 Emissions from Landfills

CH4 Emissions from Enteric Fermentation

CO2 Emissions from Non-Energy Use of Fuels

CO2 Emissions from Mobile Combustion: Aviation

Direct N2O Emissions from Agricultural Soil Management

CO2 Emissions from Stationary Combustion – Oil

CO2 Emissions from Stationary Combustion – Gas

CO2 Emissions from Mobile Combustion: Road & Other

CO2 Emissions from Stationary Combustion – Coal

Note: For a complete discussion of the key source analysis see Annex 1.
Executive Summary ES-21

to source and sink category names which differ from 

those used elsewhere in this report. For more information 

regarding key categories, see Section 1.5 and Annex 1 of 

this report.

Quality Assurance and Quality Control 

(QA/QC)

The United States seeks to continually improve the 

quality, transparency, and credibility of the Inventory of 

U.S. Greenhouse Gas Emissions and Sinks. To assist in these 

efforts, the United States implemented a systematic approach 

to QA/QC. While QA/QC has always been an integral part 

of the U.S. national system for inventory development, the 

procedures followed for the current Inventory have been 

formalized in accordance with the QA/QC plan and the 

UNFCCC reporting guidelines.

Uncertainty Analysis of Emission 

Estimates 

While the current U.S. emissions inventory provides a 

solid foundation for the development of a more detailed and 

comprehensive national inventory, there are uncertainties 

associated with the emission estimates. Some of the current 

estimates, such as those for CO2 emissions from energy-related 

activities and cement processing, are considered to have low 

uncertainties. For some other categories of emissions, however, 

a lack of data or an incomplete understanding of how emissions 

are generated increases the uncertainty associated with the 

estimates presented. Acquiring a better understanding of the 

uncertainty associated with inventory estimates is an important 

step in helping to prioritize future work and improve the overall 

quality of the Inventory. Recognizing the benefit of conducting 

an uncertainty analysis, the UNFCCC reporting guidelines 

follow the recommendations of the IPCC Good Practice 

Guidance (IPCC 2000) and require that countries provide single 

estimates of uncertainty for source and sink categories.

Currently, a qualitative discussion of uncertainty is 

presented for all source and sink categories. Within the 

discussion of each emission source, specific factors affecting 

the uncertainty surrounding the estimates are discussed. Most 

sources also contain a quantitative uncertainty assessment, 

in accordance with UNFCCC reporting guidelines.
Introduction 1-1

1. Introduction

T

his report presents estimates by the United States government of U.S. anthropogenic greenhouse gas emissions 

and sinks for the years 1990 through 2006. A summary of these estimates is provided in Table 2-1 and Table 2-2 

by gas and source category in the Trends in Greenhouse Gas Emissions chapter. The emission estimates in these 

tables are presented on both a full molecular mass basis and on a Global Warming Potential (GWP) weighted basis in order 

to show the relative contribution of each gas to global average radiative forcing.1 This report also discusses the methods 

and data used to calculate these emission estimates.

In 1992, the United States signed and ratified the United Nations Framework Convention on Climate Change (UNFCCC). 

As stated in Article 2 of the UNFCCC, “The ultimate objective of this Convention and any related legal instruments that 

the Conference of the Parties may adopt is to achieve, in accordance with the relevant provisions of the Convention, 

stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic 

interference with the climate system. Such a level should be achieved within a time-frame sufficient to allow ecosystems 

to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development 

to proceed in a sustainable manner.”2, 3

Parties to the Convention, by ratifying, “shall develop, periodically update, publish and make available...national 

inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by the 

Montreal Protocol, using comparable methodologies....”4 The United States views this report as an opportunity to fulfill 

these commitments under the UNFCCC.

In 1988, preceding the creation of the UNFCCC, the World Meteorological Organization (WMO) and the United 

Nations Environment Programme (UNEP) jointly established the Intergovernmental Panel on Climate Change (IPCC). The 

role of the IPCC is to assess on a comprehensive, objective, open and transparent basis the scientific, technical and socioeconomic 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 

1 See the section below entitled Global Warming Potentials for an explanation of GWP values.

2The 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).

3Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate Change. See <http://unfccc.

int>. (UNEP/WMO 2000)

4Article 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 <http://unfccc.int>.
1-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

guidelines. In addition, this Inventory is in accordance 

with the IPCC Good Practice Guidance and Uncertainty 

Management in National Greenhouse Gas Inventories

and the Good Practice Guidance for Land Use, Land-Use 

Change, and Forestry, which further expanded upon the 

methodologies in the Revised 1996 IPCC Guidelines. The 

IPCC has also accepted the 2006 Guidelines for National 

Greenhouse Gas Inventories (IPCC 2006) at its Twenty-Fifth 

Session (Mauritius, April 2006). The 2006 IPCC Guidelines 

build on the previous bodies of work and include new sources 

and gases “...as well as updates to the previously published 

methods whenever scientific and technical knowledge have 

improved since the previous guidelines were issued.” Many 

of the methodological improvements presented in the 2006 

Guidelines have been adopted in this Inventory.

Overall, this Inventory of anthropogenic greenhouse gas 

emissions provides a common and consistent mechanism 

through which Parties to the UNFCCC can estimate emissions 

and compare the relative contribution of individual sources, 

gases, and nations to climate change. The structure of this 

report is consistent with the current UNFCCC Guidelines on 

Annual Inventories (UNFCCC 2006).

1.1. Background Information

Greenhouse Gases

Although the earth’s atmosphere consists mainly of 

oxygen and nitrogen, neither plays a significant role in 

enhancing the greenhouse effect because both are essentially 

transparent to terrestrial radiation. The greenhouse effect 

is primarily a function of the concentration of water 

vapor, carbon dioxide (CO2), and other trace gases in the 

atmosphere that absorb the terrestrial radiation leaving the 

surface of the earth (IPCC 2001). Changes in the atmospheric 

concentrations of these greenhouse gases can alter the balance 

of energy transfers between the atmosphere, space, land, and 

the oceans.5 A gauge of these changes is called radiative 

forcing, which is a measure of the influence a factor has in 

altering the balance of incoming and outgoing energy in the 

earth-atmosphere system (IPCC 2001). Holding everything 

else constant, increases in greenhouse gas concentrations in 

the atmosphere will produce positive radiative forcing (i.e., 

a net increase in the absorption of energy by the earth).

5 For more on the science of climate change, see NRC (2001).

Climate change can be driven by changes in 

the atmospheric concentrations of a number of 

radiatively active gases and aerosols. We have 

clear evidence that human activities have affected 

concentrations, distributions and life cycles of these 

gases (IPCC 1996).

Naturally occurring greenhouse gases include water 

vapor, CO2, methane (CH4), nitrous oxide (N2O), and 

ozone (O3). Several classes of halogenated substances that 

contain fluorine, chlorine, or bromine are also greenhouse 

gases, but they are, for the most part, solely a product 

of industrial activities. Chlorofluorocarbons (CFCs) and 

hydrochlorofluorocarbons (HCFCs) are halocarbons that 

contain chlorine, while halocarbons that contain bromine 

are referred to as bromofluorocarbons (i.e., halons). As 

stratospheric ozone depleting substances, CFCs, HCFCs, and 

halons are covered under the Montreal Protocol on Substances 

that Deplete the Ozone Layer. The UNFCCC defers to this 

earlier international treaty. Consequently, Parties to the 

UNFCCC are not required to include these gases in national 

greenhouse gas inventories.6 Some other fluorine-containing 

halogenated substances—hydrofluorocarbons (HFCs), 

perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)—do 

not deplete stratospheric ozone but are potent greenhouse 

gases. These latter substances are addressed by the UNFCCC 

and accounted for in national greenhouse gas inventories. 

There are also several gases that, although they do 

not have a commonly agreed upon direct radiative forcing 

effect, do influence the global radiation budget. These 

tropospheric gases include carbon monoxide (CO), nitrogen 

dioxide (NO2), sulfur dioxide (SO2), and tropospheric 

(ground level) O3. Tropospheric ozone is formed by two 

precursor pollutants, volatile organic compounds (VOCs) 

and nitrogen oxides (NOx) in the presence of ultraviolet 

light (sunlight). Aerosols are extremely small particles or 

liquid droplets that are often composed of sulfur compounds, 

carbonaceous combustion products, crustal materials 

and other human induced pollutants. They can affect the 

absorptive characteristics of the atmosphere. Comparatively, 

however, the level of scientific understanding of aerosols is 

still very low (IPCC 2001). 

6Emission estimates of CFCs, HCFCs, halons and other ozone-depleting 

substances are included in this document for informational purposes.
Introduction 1-3

Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and Atmospheric Lifetime (years) 

of Selected Greenhouse Gases 

Atmospheric Variable CO2 CH4 N2O SF6 CF4

Pre-industrial atmospheric concentration 278 ppm 0.715 ppm 0.270 ppm 0 ppt 40 ppt

Atmospheric concentrationa 379 ppm 1.774 ppm 0.319 ppm 5.6 ppt 74 ppt

Rate of concentration change 1.4 ppm/yr 0.005 ppm/yra 0.26% yr Linearb Linearb

Atmospheric lifetimec 50–200d 12e 114e 3,200 >50,000

Source: Pre-industrial atmospheric concentrations, current atmospheric concentrations, and rate of concentration changes for all gases are from IPCC (2007).

a The growth rate for atmospheric CH4 has been decreasing from 1.4 ppb/yr in 1984 to less than 0 ppb/yr in 2001, 2004, and 2005. b IPCC (2007) identifies the rate of concentration change for SF6 and CF4 as linear. c Source: IPCC (1996). 

d No single lifetime can be defined for CO2 because of the different rates of uptake by different removal processes. e This lifetime has been defined as an “adjustment time” that takes into account the indirect effect of the gas on its own residence time. 

CO2, CH4, and N2O are continuously emitted to 

and removed from the atmosphere by natural processes 

on Earth. Anthropogenic activities, however, can cause 

additional quantities of these and other greenhouse gases 

to be emitted or sequestered, thereby changing their global 

average atmospheric concentrations. Natural activities such 

as respiration by plants or animals and seasonal cycles of 

plant growth and decay are examples of processes that only 

cycle carbon or nitrogen between the atmosphere and organic 

biomass. Such processes, except when directly or indirectly 

perturbed out of equilibrium by anthropogenic activities, 

generally do not alter average atmospheric greenhouse gas 

concentrations over decadal timeframes. Climatic changes 

resulting from anthropogenic activities, however, could 

have positive or negative feedback effects on these natural 

systems. Atmospheric concentrations of these gases, along 

with their rates of growth and atmospheric lifetimes, are 

presented in Table 1-1.

A brief description of each greenhouse gas, its sources, 

and its role in the atmosphere is given below. The following 

section then explains the concept of GWPs, which are 

assigned to individual gases as a measure of their relative 

average global radiative forcing effect.

Water Vapor (H2O). Overall, the most abundant and 

dominant greenhouse gas in the atmosphere is water vapor. 

Water vapor is neither long-lived nor well mixed in the 

atmosphere, varying spatially from 0 to 2 percent (IPCC 

1996). In addition, atmospheric water can exist in several 

physical states including gaseous, liquid, and solid. Human 

activities are not believed to affect directly the average 

global concentration of water vapor, but the radiative 

forcing produced by the increased concentrations of other 

greenhouse gases may indirectly affect the hydrologic cycle. 

While a warmer atmosphere has an increased water holding 

capacity, increased concentrations of water vapor affects the 

formation of clouds, which can both absorb and reflect solar 

and terrestrial radiation. Aircraft contrails, which consist of 

water vapor and other aircraft emittants, are similar to clouds 

in their radiative forcing effects (IPCC 1999). 

Carbon Dioxide. In nature, carbon is cycled between 

various atmospheric, oceanic, land biotic, marine biotic, 

and mineral reservoirs. The largest fluxes occur between the 

atmosphere and terrestrial biota, and between the atmosphere 

and surface water of the oceans. In the atmosphere, 

carbon predominantly exists in its oxidized form as CO2. 

Atmospheric CO2 is part of this global carbon cycle, and 

therefore its fate is a complex function of geochemical and 

biological processes. CO2 concentrations in the atmosphere 

increased from approximately 280 parts per million by 

volume (ppmv) in pre-industrial times to 379 ppmv in 2005, 

a 35 percent increase (IPCC 2007 and Hofmann 2004).7,8

The IPCC definitively states that “the present atmospheric 

CO2 increase is caused by anthropogenic emissions of CO2” 

(IPCC 2001). The predominant source of anthropogenic CO2

emissions is the combustion of fossil fuels. Forest clearing, 

other biomass burning, and some non-energy production 

7The pre-industrial period is considered as the time preceding the year 

1750 (IPCC 2001).

8Carbon dioxide concentrations during the last 1,000 years of the preindustrial period (i.e., 750–1750), a time of relative climate stability, 

fluctuated by about ±10 ppmv around 280 ppmv (IPCC 2001).
1-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

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 

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 byproduct of coal mining and incomplete 

fossil fuel combustion. Atmospheric concentrations of CH4

have increased by about 143 percent since 1750, from a 

pre-industrial value of about 722 ppb to 1,774 ppb in 2005, 

although the rate of increase has been declining. The IPCC 

has estimated that slightly more than half of the current 

CH4 flux to the atmosphere is anthropogenic, from human 

activities such as agriculture, fossil fuel use, and waste 

disposal (IPCC 2007).

CH4 is removed from the atmosphere through a reaction 

with the hydroxyl radical (OH) and is ultimately converted 

to CO2. Minor removal processes also include reaction 

with chlorine in the marine boundary layer, a soil sink, and 

stratospheric reactions. Increasing emissions of CH4 reduce 

the concentration of OH, a feedback that may increase the 

atmospheric lifetime of CH4 (IPCC 2001).

Nitrous Oxide. Anthropogenic sources of N2O emissions 

include agricultural soils, especially production of nitrogenfixing crops and forages, the use of synthetic and manure 

fertilizers, and manure deposition by livestock; fossil fuel 

combustion, especially from mobile combustion; adipic 

(nylon) and nitric acid production; wastewater treatment and 

waste combustion; and biomass burning. The atmospheric 

concentration of N2O has increased by 18 percent since 

1750, from a pre-industrial value of about 270 ppb to 319 

ppb in 2005, a concentration that has not been exceeded 

during the last thousand years. N2O is primarily removed 

from the atmosphere by the photolytic action of sunlight in 

the stratosphere (IPCC 2007).

Ozone. Ozone is present in both the upper stratosphere,9

where it shields the Earth from harmful levels of ultraviolet 

radiation, and at lower concentrations in the troposphere,10

where it is the main component of anthropogenic 

photochemical “smog.” During the last two decades, 

emissions of anthropogenic chlorine and bromine-containing 

halocarbons, such as CFCs, have depleted stratospheric 

ozone concentrations. This loss of ozone in the stratosphere 

has resulted in negative radiative forcing, representing 

an indirect effect of anthropogenic emissions of chlorine 

and bromine compounds (IPCC 1996). The depletion of 

stratospheric ozone and its radiative forcing was expected to 

reach a maximum in about 2000 before starting to recover, 

with detection of such recovery not expected to occur much 

before 2010 (IPCC 2001).

The past increase in tropospheric ozone, which is also 

a greenhouse gas, is estimated to provide the third largest 

increase in direct radiative forcing since the pre-industrial 

era, behind CO2 and CH4. Tropospheric ozone is produced 

from complex chemical reactions of volatile organic 

compounds mixing with NOx in the presence of sunlight. 

The tropospheric concentrations of ozone and these other 

pollutants are short-lived and, therefore, spatially variable 

(IPCC 2001).

Halocarbons, Perfluorocarbons, and Sulfur Hexafluoride. 

Halocarbons are, for the most part, man-made chemicals 

that have both direct and indirect radiative forcing effects. 

Halocarbons that contain chlorine (CFCs, HCFCs, methyl 

chloroform, and carbon tetrachloride) and bromine (halons, 

methyl bromide, and hydrobromofluorocarbons [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 

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.

10The troposphere is the layer from the ground up to 11 kilometers near 

the poles and up to 16 kilometers in equatorial regions (i.e., the lowest 

layer of the atmosphere where people live). It contains roughly 80 percent 

of the mass of all gases in the atmosphere and is the site for most weather 

processes, including most of the water vapor and clouds.
Introduction 1-5

important greenhouse gas in addition to shielding the 

earth from harmful levels of ultraviolet radiation. Under 

the Montreal Protocol, the United States phased out the 

production and importation of halons by 1994 and of CFCs by 

1996. Under the Copenhagen Amendments to the Protocol, a 

cap was placed on the production and importation of HCFCs 

by non-Article 511 countries beginning in 1996, and then 

followed by a complete phase-out by the year 2030. While 

ozone depleting gases covered under the Montreal Protocol

and its Amendments are not covered by the UNFCCC; they 

are reported in this Inventory under Annex 6.2 of this report 

for informational purposes.

HFCs, PFCs, and SF6 are not ozone depleting substances, 

and therefore are not covered under the Montreal Protocol. 

They are, however, powerful greenhouse gases. HFCs 

are primarily used as replacements for ozone depleting 

substances but also emitted as a byproduct of the HCFC22 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.

11Article 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.

Nitrogen Oxides. The primary climate change effects of 

nitrogen oxides (i.e., NO and NO2) are indirect and result 

from their role in promoting the formation of ozone in the 

troposphere and, to a lesser degree, lower stratosphere, 

where it has positive radiative forcing effects.12 Additionally, 

NOx emissions from aircraft are likely to decrease CH4

concentrations, thus having a negative radiative forcing 

effect (IPCC 1999). Nitrogen oxides are created from 

lightning, soil microbial activity, biomass burning (both 

natural and anthropogenic fires), fuel combustion, and, 

in the stratosphere, from the photo-degradation of N2O. 

Concentrations of NOx are both relatively short-lived in 

the atmosphere and spatially variable.

Nonmethane Volatile Organic Compounds (NMVOCs). 

Non-CH4 volatile organic compounds include substances such 

as propane, butane, and ethane. These compounds participate, 

along with NOx, in the formation of tropospheric ozone 

and other photochemical oxidants. NMVOCs are emitted 

primarily from transportation and industrial processes, as 

well as biomass burning and non-industrial consumption of 

organic solvents. Concentrations of NMVOCs tend to be both 

short-lived in the atmosphere and spatially variable.

Aerosols. Aerosols are extremely small particles or liquid 

droplets found in the atmosphere. They can be produced by 

natural events such as dust storms and volcanic activity, or by 

anthropogenic processes such as fuel combustion and biomass 

burning. Aerosols affect radiative forcing differently than 

greenhouse gases, and their radiative effects occur through 

direct and indirect mechanisms: directly by scattering and 

absorbing solar radiation; and indirectly by increasing droplet 

counts that modify the formation, precipitation efficiency, and 

radiative properties of clouds. Aerosols are removed from 

the atmosphere relatively rapidly by precipitation. Because 

aerosols generally have short atmospheric lifetimes, and 

have concentrations and compositions that vary regionally, 

spatially, and temporally, their contributions to radiative 

forcing are difficult to quantify (IPCC 2001).

The indirect radiative forcing from aerosols is typically 

divided into two effects. The first effect involves decreased 

droplet size and increased droplet concentration resulting 

from an increase in airborne aerosols. The second effect 

12 NOx emissions injected higher in the stratosphere, primarily from fuel 

combustion emissions from high altitude supersonic aircraft, can lead to 

stratospheric ozone depletion.
1-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

involves an increase in the water content and lifetime 

of clouds due to the effect of reduced droplet size on 

precipitation efficiency (IPCC 2001). Recent research has 

placed a greater focus on the second indirect radiative forcing 

effect of aerosols. 

Various categories of aerosols exist, including 

naturally produced aerosols such as soil dust, sea salt, 

biogenic aerosols, sulfates, and volcanic aerosols, and 

anthropogenically manufactured aerosols such as industrial 

dust and carbonaceous aerosols13 (e.g., black carbon, organic 

carbon) from transportation, coal combustion, cement 

production, waste incineration, and biomass burning. 

The net effect of aerosols on radiative forcing is believed 

to be negative (i.e., net cooling effect on the climate), 

although because they remain in the atmosphere for only days 

to weeks, their concentrations respond rapidly to changes in 

emissions.14 Locally, the negative radiative forcing effects 

of aerosols can offset the positive forcing of greenhouse 

gases (IPCC 1996). “However, the aerosol effects do not 

cancel the global-scale effects of the much longer-lived 

greenhouse gases, and significant climate changes can still 

result” (IPCC 1996). 

The IPCC’s Third Assessment Report notes that “the 

indirect radiative effect of aerosols is now understood to also 

encompass effects on ice and mixed-phase clouds, but the 

magnitude of any such indirect effect is not known, although 

it is likely to be positive” (IPCC 2001). Additionally, current 

research suggests that another constituent of aerosols, black 

carbon, may have a positive radiative forcing (Jacobson 

2001). The primary anthropogenic emission sources of black 

carbon include diesel exhaust and open biomass burning. 

Global Warming Potentials

A global warming potential is a quantified measure of 

the globally averaged relative radiative forcing impacts of 

a particular greenhouse gas (see Table 1-2). It is defined 

as the ratio of the time-integrated radiative forcing from 

the instantaneous release of 1 kilogram (kg) of a trace 

substance relative to that of 1 kg of a reference gas (IPCC 

2001). Direct radiative effects occur when the gas itself 

13Carbonaceous aerosols are aerosols that are comprised mainly of organic 

substances and forms of black carbon (or soot) (IPCC 2001).

14Volcanic 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).

absorbs radiation. Indirect radiative forcing occurs when 

chemical transformations involving the original gas produce 

a gas or gases that are greenhouse gases, or when a gas 

influences other radiatively important processes such as 

the atmospheric lifetimes of other gases. The reference gas 

used is CO2, and therefore GWP weighted emissions are 

measured in teragrams of CO2 equivalents (Tg CO2 Eq.)15

The relationship between gigagrams (Gg) of a gas and Tg 

CO2 Eq. can be expressed as follows: 

 

 

GWP values allow for a comparison of the impacts of 

emissions and reductions of different gases. According to the 

IPCC, GWPs typically have an uncertainty of ±35 percent. 

The parties to the UNFCCC have also agreed to use GWPs 

based upon a 100-year time horizon although other time 

horizon values are available.

Greenhouse gas emissions and removals should 

be presented on a gas-by-gas basis in units of 

mass... In addition, consistent with decision 2/

CP.3, Parties should report aggregate emissions 

and removals of greenhouse gases, expressed in 

CO2 equivalent terms at summary inventory level, 

using GWP values provided by the IPCC in its 

Second Assessment Report... based on the effects of 

greenhouse gases over a 100-year time horizon.16

Greenhouse gases with relatively long atmospheric 

lifetimes (e.g., CO2, CH4, N2O, HFCs, PFCs, and SF6) 

tend to be evenly distributed throughout the atmosphere, 

and consequently global average concentrations can be 

15Carbon comprises 12/44ths of carbon dioxide by weight.

16 Framework Convention on Climate Change; <http://unfccc.int/resource/

docs/cop8/08.pdf>; 1 November 2002; Report of the Conference of the 

Parties at its eighth session; held at New Delhi from 23 October to 1 

November 2002; Addendum; Part One: Action taken by the Conference 

of the Parties at its eighth session; Decision -/CP.8; Communications 

from Parties included in Annex I to the Convention: Guidelines for the 

Preparation of National Communications by Parties Included in Annex I to 

the Convention, Part 1: UNFCCC reporting guidelines on annual inventories; 

p. 7. (UNFCCC 2003).

where,

Tg CO2 Eq. = Teragrams of CO2 Equivalents

Gg = Gigagrams (equivalent to a 

thousand metric tons)

GWP = Global Warming Potential

Tg = Teragrams

Tg CO2 Eq. = (Gg of gas) × (GWP) × (

 Tg ) 1,000 Gg
Introduction 1-7

Table 1-2: Global Warming Potentials and Atmospheric 

Lifetimes (Years) Used in this Report

Gas

Atmospheric 

Lifetime GWPa

CO2 50–200 1

CH4

b 12±3 21

N2O 120 310

HFC-23 264 11,700

HFC-32 5.6 650

HFC-125 32.6 2,800

HFC-134a 14.6 1,300

HFC-143a 48.3 3,800

HFC-152a 1.5 140

HFC-227ea 36.5 2,900

HFC-236fa 209 6,300

HFC-4310mee 17.1 1,300

CF4 50,000 6,500

C2F6 10,000 9,200

C4F10 2,600 7,000

C6F14 3,200 7,400

SF6 3,200 23,900

Source: (IPCC 1996)

a 100-year time horizon

b The GWP of CH4 includes the direct effects and those indirect effects 

due to the production of tropospheric ozone and stratospheric water 

vapor. The indirect effect due to the production of CO2 is not included.

determined. The short-lived gases such as water vapor, 

carbon monoxide, tropospheric ozone, ozone precursors 

(e.g., NOx and NMVOCs), and tropospheric aerosols 

(e.g., SO2 products and carbonaceous particles), however, 

vary regionally, and consequently it is difficult to quantify 

their global radiative forcing impacts. No GWP values are 

attributed to these gases that are short-lived and spatially 

inhomogeneous in the atmosphere. 

1.2. Institutional Arrangements

The U.S. Environmental Protection Agency (EPA), in 

cooperation with other U.S. government agencies, prepares 

the Inventory of U.S. Greenhouse Gas Emissions and Sinks. 

A wide range of agencies and individuals are involved in 

supplying data to, reviewing, or preparing portions of the 

U.S. Inventory—including federal and state government 

authorities, research and academic institutions, industry 

associations, and private consultants.

Within EPA, the Office of Atmospheric Programs (OAP) 

is the lead office responsible for the emission calculations 

provided in the Inventory, as well as the completion of the 

National Inventory Report and the Common Reporting 

Format tables. The Office of Transportation and Air Quality 

(OTAQ) is also involved in calculating emissions for the 

Inventory. While the U.S. Department of State officially 

submits the annual Inventory to the UNFCCC, EPA’s 

OAP serves as the focal point for technical questions and 

comments on the U.S. Inventory. The staff of OAP and 

OTAQ coordinates the annual methodological choice, 

activity data collection, and emission calculations at the 

individual source category level. Within OAP, an Inventory 

Coordinator compiles the entire Inventory into the proper 

reporting format for submission to the UNFCCC, and is 

responsible for the collection and consistency of crosscutting issues in the Inventory.

Several other government agencies contribute to the 

collection and analysis of the underlying activity data 

used in the Inventory calculations. Formal relationships 

exist between EPA and other U.S. agencies that provide 

official data for use in the Inventory. The U.S. Department 

of Energy’s Energy Information Administration provides 

national fuel consumption data and the U.S. Department of 

Defense provides military fuel consumption and bunker fuels. 

Informal relationships also exist with other U.S. agencies to 

provide activity data for use in EPA’s emission calculations. 

These include: the U.S. Department of Agriculture, the U.S. 

Geological Survey, the Federal Highway Administration, the 

Department of Transportation, the Bureau of Transportation 

Statistics, the Department of Commerce, the National 

Agricultural Statistics Service, and the Federal Aviation 

Administration. Academic and research centers also provide 

activity data and calculations to EPA, as well as individual 

companies participating in voluntary outreach efforts with 

EPA. Finally, the U.S. Department of State officially submits 

the Inventory to the UNFCCC each April.

1.3. Inventory Process 

EPA has a decentralized approach to preparing the 

annual U.S. Inventory, which consists of a National Inventory 

Report (NIR) and Common Reporting Format (CRF) 

tables. The Inventory Coordinator at EPA is responsible for 

compiling all emission estimates, and ensuring consistency 

and quality and contractors familiar with the sources. A 

multi-stage process for collecting information from the 
1-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Box 1-1: The IPCC Fourth Assessment Report and Global Warming Potentials

In 2007, the IPCC published its Fourth Assessment Report (AR4), which provided an updated and more comprehensive scientific 

assessment of climate change. Within this report, the GWPs of several gases were revised relative to the SAR and the IPCC’s Third Assessment 

Report (TAR) (IPCC 2001). Thus the GWPs used in this report have been updated twice by the IPCC; although the SAR GWPs are used 

throughout this report, it is useful to review the changes to the GWPs and the impact such improved understanding has on the total GWPweighted emissions of the United States. Since the SAR and TAR, the IPCC has applied an improved calculation of CO2 radiative forcing and 

an improved CO2 response function. The GWPs are drawn from IPCC/TEAP (2005) and the TAR, with updates for those cases where new 

laboratory or radiative transfer results have been published. Additionally, the atmospheric lifetimes of some gases have been recalculated. In 

addition, the values for radiative forcing and lifetimes have been recalculated for a variety of halocarbons, which were not presented in the 

SAR. Table 1-3 presents the new GWPs, relative to those presented in the SAR.

Table 1-3: Comparison of 100-Year GWPs

Gas SAR TAR AR4 Change from SAR

TAR AR4

CO2 1 1 1 NC 0

CH4* 21 23 25 2 4

N2O 310 296 298 (14) (12)

HFC-23 11,700 12,000 14,800 300 3,100

HFC-32 650 550 675 (100) 25

HFC-125 2,800 3,400 3,500 600 700

HFC-134a 1,300 1,300 1,430 NC 130

HFC-143a 3,800 4,300 4,470 500 670

HFC-152a 140 120 124 (20) (16)

HFC-227ea 2,900 3,500 3,220 600 320

HFC-236fa 6,300 9,400 9,810 3,100 3,510

HFC-4310mee 1,300 1,500 1,640 200 340

CF4 6,500 5,700 7,390 (800) 890

C2F6 9,200 11,900 12,200 2,700 3,000

C4F10 7,000 8,600 8,860 1,600 1,860

C6F14 7,400 9,000 9,300 1,600 1,900

SF6 23,900 22,200 22,800 (1,700) (1,100)

Source: (IPCC 2007, IPCC 2001)

NC (No Change)

Note: Parentheses indicate negative values.

* The GWP of CH4 includes the direct effects and those indirect effects due to the production of tropospheric 

ozone and stratospheric water vapor. The indirect effect due to the production of CO2 is not included.

To comply with international reporting standards under the UNFCCC, official emission estimates are reported by the United States using 

SAR GWP values. The UNFCCC reporting guidelines for national inventories17 were updated in 2002 but continue to require the use of GWPs 

from the SAR so that current estimates of aggregate greenhouse gas emissions for 1990 through 2006 are consistent and comparable with 

estimates developed prior to the publication of the TAR and AR4. For informational purposes, emission estimates that use the updated GWPs 

are presented in detail in Annex 6.1 of this report. All estimates provided throughout this report are also presented in unweighted units.

17 See <http://unfccc.int/resource/docs/cop8/08.pdf>.

throughout the NIR and CRF tables. Emission calculations 

for individual sources are the responsibility of individual 

source leads, who are most familiar with each source category 

and the unique characteristics of its emissions profile. The 

individual source leads determine the most appropriate 

methodology and collect the best activity data to use in 

the emission calculations, based upon their expertise in the 

source category, as well as coordinating with researchers 
Introduction 1-9

individual source leads and producing the Inventory is 

undertaken annually to compile all information and data.

Methodology Development, Data 

Collection, and Emissions and Sink 

Estimation

Source leads at EPA collect input data and, as necessary, 

evaluate or develop the estimation methodology for the 

individual source categories. For most source categories, 

the methodology for the previous year is applied to the 

new “current” year of the Inventory, and inventory analysts 

collect any new data or update data that have changed from 

the previous year. If estimates for a new source category are 

being developed for the first time, or if the methodology is 

changing for an existing source category (e.g., the United 

States is implementing a higher Tiered approach for that 

source category), then the source category lead will develop 

a new methodology, gather the most appropriate activity 

data and emission factors (or in some cases direct emission 

measurements) for the entire time series, and conduct a 

special source-specific peer review process involving relevant 

experts from industry, government, and universities.

Once the methodology is in place and the data are 

collected, the individual source leads calculate emissions and 

sink estimates. The source leads then update or create the 

relevant text and accompanying annexes for the Inventory. 

Source leads are also responsible for completing the relevant 

sectoral background tables of the Common Reporting 

Format, conducting quality assurance and quality control 

(QA/QC) checks, and uncertainty analyses.

Summary Spreadsheet Compilation and 

Data Storage

The Inventory Coordinator at EPA collects the source 

categories’ descriptive text and Annexes, and also aggregates 

the emission estimates into a summary spreadsheet that 

links the individual source category spreadsheets together. 

This summary sheet contains all of the essential data in 

one central location, in formats commonly used in the 

Inventory document. In addition to the data from each source 

category, national trend and related data are also gathered 

in the summary sheet for use in the Executive Summary, 

Introduction, and Recent Trends sections of the Inventory 

report. Electronic copies of each year’s summary spreadsheet, 

which contains all the emission and sink estimates for the 

United States, are kept on a central server at EPA under the 

jurisdiction of the Inventory Coordinator.

National Inventory Report Preparation

The NIR is compiled from the sections developed 

by each individual source lead. In addition, the Inventory 

Coordinator prepares a brief overview of each chapter that 

summarizes the emissions from all sources discussed in the 

chapters. The Inventory Coordinator then carries out a key 

category analysis for the Inventory, consistent with the IPCC 

Good Practice Guidance, IPCC Good Practice Guidance for 

Land Use, Land Use Change and Forestry, and in accordance 

with the reporting requirements of the UNFCCC. Also at 

this time, the Introduction, Executive Summary, and Recent 

Trends sections are drafted, to reflect the trends for the most 

recent year of the current Inventory. The analysis of trends 

necessitates gathering supplemental data, including weather 

and temperature conditions, economic activity and gross 

domestic product, population, atmospheric conditions, and 

the annual consumption of electricity, energy, and fossil 

fuels. Changes in these data are used to explain the trends 

observed in greenhouse gas emissions in the United States. 

Furthermore, specific factors that affect individual sectors 

are researched and discussed. Many of the factors that affect 

emissions are included in the Inventory document as separate 

analyses or side discussions in boxes within the text. Text 

boxes are also created to examine the data aggregated in 

different ways than in the remainder of the document, such 

as a focus on transportation activities or emissions from 

electricity generation. The document is prepared to match 

the specification of the UNFCCC reporting guidelines for 

National Inventory Reports.

Common Reporting Format Table 

Compilation

The CRF tables are compiled from individual tables 

completed by each individual source lead, which contain 

source emissions and activity data. The Inventory Coordinator 

integrates the source data into the UNFCCC’s “CRF Reporter” 

for the United States, assuring consistency across all sectoral 

tables. The summary reports for emissions, methods, and 

emission factors used, the overview tables for completeness 
1-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

and quality of estimates, the recalculation tables, the notation 

key completion tables, and the emission trends tables are then 

completed by the Inventory Coordinator. Internal automated 

quality checks on the CRF Reporter, as well as reviews by 

the source leads, are completed for the entire time series of 

CRF tables before submission.

QA/QC and Uncertainty

QA/QC and uncertainty analyses are supervised by the 

QA/QC and Uncertainty coordinators, who have general 

oversight over the implementation of the QA/QC plan and 

the overall uncertainty analysis for the Inventory (see sections 

on QA/QC and Uncertainty, below). These coordinators work 

closely with the source leads to ensure that a consistent QA/

QC plan and uncertainty analysis is implemented across all 

inventory sources. The inventory QA/QC plan, detailed in 

a following section, is consistent with the quality assurance 

procedures outlined by EPA and IPCC.

Expert and Public Review Periods

During the Expert Review period, a first draft of the 

document is sent to a select list of technical experts outside 

of EPA. The purpose of the Expert Review is to encourage 

feedback on the methodological and data sources used in 

the current Inventory, especially for sources which have 

experienced any changes since the previous Inventory.

Once comments are received and addressed, a second 

draft of the document is released for public review by 

publishing a notice in the U.S. Federal Register and posting 

the document on the EPA Web site. The Public Review 

period allows for a 30 day comment period and is open to 

the entire U.S. public. 

Final Submittal to UNFCCC and Document 

Printing

After the final revisions to incorporate any comments 

from the Expert Review and Public Review periods, 

EPA prepares the final National Inventory Report and 

the accompanying Common Reporting Format Reporter 

database. The U.S. Department of State sends the official 

submission of the U.S. Inventory to the UNFCCC. The 

document is then formatted for printing, posted online, 

printed by the U.S. Government Printing Office, and made 

available for the public. 

1.4. Methodology and Data Sources

Emissions of greenhouse gases from various source and 

sink categories have been estimated using methodologies 

that are consistent with the Revised 1996 IPCC Guidelines 

for National Greenhouse Gas Inventories (IPCC/UNEP/

OECD/IEA 1997). In addition, the United States references 

the additional guidance provided in the IPCC Good Practice 

Guidance and Uncertainty Management in National 

Greenhouse Gas Inventories (IPCC 2000), the IPCC Good 

Practice Guidance for Land Use, Land-Use Change, and 

Forestry (IPCC 2003), and the 2006 IPCC Guidelines for 

National Greenhouse Gas Inventories (IPCC 2006). To the 

extent possible, the present report relies on published activity 

and emission factor data. Depending on the emission source 

category, activity data can include fuel consumption or 

deliveries, vehicle-miles traveled, raw material processed, 

etc. Emission factors are factors that relate quantities of 

emissions to an activity.

The IPCC methodologies provided in the Revised 

1996 IPCC Guidelines represent baseline methodologies 

for a variety of source categories, and many of these 

methodologies continue to be improved and refined as new 

research and data become available. This report uses the 

IPCC methodologies when applicable, and supplements them 

with other available methodologies and data where possible. 

Choices made regarding the methodologies and data sources 

used are provided in conjunction with the discussion of each 

Box 1-2: IPCC Reference Approach

The UNFCCC reporting guidelines require countries to 

complete a “top-down” reference approach for estimating CO2

emissions from fossil fuel combustion in addition to their “bottomup” 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 carbonbased 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. 
Introduction 1-11

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.

A Tier 1 approach, as defined in the IPCC’s Good 

Practice Guidance (IPCC 2000), was implemented to 

identify the key categories for the United States. This analysis 

was performed twice; one analysis included sources and 

sinks from the Land Use, Land-Use Change, and Forestry 

(LULUCF) sector, the other analysis did not include the 

LULUCF categories.

In addition to conducting Tier 1 level and trend 

assessments, a qualitative assessment of the source categories, 

as described in the IPCC’s Good Practice Guidance (IPCC 

2000), was conducted to capture any key categories that were 

not identified by either quantitative method. One additional 

key category, international bunker fuels, was identified 

using this qualitative assessment. International bunker fuels 

are fuels consumed for aviation or marine international 

transport activities, and emissions from these fuels are 

reported separately from totals in accordance with IPCC 

guidelines. If these emissions were included in the totals, 

bunker fuels would qualify as a key category according to the 

Tier 1 approach. The amount of uncertainty associated with 

18 See Chapter 7 “Methodological Choice and Recalculation” in IPCC 

(2000). <http://www.ipcc-nggip.iges.or.jp/public/gp/gpgaum.htm>

estimation of emissions from international bunker fuels also 

supports the qualification of this source category as key.

Table 1-4 presents the key categories for the United 

States based on the Tier 1 approach (including and excluding 

LULUCF categories) using emissions data in this report, 

and ranked according to their sector and GWP-weighted 

emissions in 2006. The table also indicates the criteria 

used in identifying these categories (i.e., level, trend, and/

or qualitative assessments). Annex 1 of this report provides 

additional information regarding the key categories in the 

United States and the methodologies used to identify them.

1.6. Quality Assurance and Quality 

Control (QA/QC)

As part of efforts to achieve its stated goals for inventory 

quality, transparency, and credibility, the United States has 

developed a quality assurance and quality control plan 

designed to check, document and improve the quality of 

its inventory over time. QA/QC activities on the Inventory 

are undertaken within the framework of the U.S. QA/QC 

plan, Quality Assurance/Quality Control and Uncertainty 

Management Plan for the U.S. Greenhouse Gas Inventory: 

Procedures Manual for QA/QC and Uncertainty Analysis.

In particular, key attributes of the QA/QC plan 

include:

•	 specific detailed procedures and forms that serve to 

standardize the process of documenting and archiving 

information, as well as to guide the implementation 

of QA/QC and the analysis of the uncertainty of the 

inventory estimates;

•	 expert review as well as QC—for both the inventory 

estimates and the Inventory (which is the primary 

vehicle for disseminating the results of the inventory 

development process). In addition, the plan provides 

for public review of the Inventory;

•	 both Tier 1 (general) and Tier 2 (source-specific) quality 

controls and checks, as recommended by IPCC Good 

Practice Guidance;
1-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 1-4: Key Categories for the United States (1990–2006) Based on Tier 1 Approach

IPCC Source Categories Gas

Level 

Without 

LULUCF

Trend 

Without 

LULUCF

Level 

With 

LULUCF

Trend 

With 

LULUCF Quala

2006

Emissions

(Tg CO2 Eq.)

Energy

CO2 Emissions from Stationary Combustion-Coal CO2 ✓ ✓ ✓ ✓ 2,065.3 

CO2 Emissions from Mobile Combustion: Road & Other CO2 ✓ ✓ ✓ ✓ 1,643.0 

CO2 Emissions from Stationary Combustion-Gas CO2 ✓ ✓ ✓ 1,121.9 

CO2 Emissions from Stationary Combustion-Oil CO2 ✓ ✓ ✓ ✓ 594.3 

CO2 Emissions from Mobile Combustion: Aviation CO2 ✓ ✓ ✓ ✓ 170.6 

CO2 Emissions from Non-Energy Use of Fuels CO2 ✓ ✓ 138.0 

CO2 Emissions from Mobile Combustion: Marine CO2 ✓ ✓ ✓ ✓ 42.4 

CO2 Emissions from Natural Gas Systems CO2 ✓ ✓ ✓ ✓ 28.5 

CO2 Emissions from Municipal Solid Waste Combustion CO2 ✓ ✓ 20.9 

Fugitive CH4 Emissions from Natural Gas Systems CH4 ✓ ✓ ✓ ✓ 102.4 

Fugitive CH4 Emissions from Coal Mining CH4 ✓ ✓ ✓ ✓ 58.5 

Fugitive CH4 Emissions from Petroleum Systems CH4 ✓ ✓ ✓ ✓ 28.4 

N2O Emissions from Mobile Combustion: Road & Other N2O ✓ ✓ ✓ ✓ 31.1 

International Bunker Fuelsb Several ✓ 128.4 

Industrial Processes

CO2 Emissions from Iron and Steel Production CO2 ✓ ✓ ✓ ✓ 49.1 

CO2 Emissions from Cement Production CO2 ✓ ✓ ✓ ✓ 45.7 

CO2 Emissions from Ammonia Production and Urea Application CO2 ✓ ✓ 12.4 

N2O Emissions from Adipic Acid Production N2O ✓ ✓ 5.9 

Emissions from Substitutes for Ozone Depleting Substances Several ✓ ✓ ✓ ✓ 110.4 

HFC-23 Emissions from HCFC-22 Production HFCs ✓ ✓ ✓ ✓ 13.8 

SF6 Emissions from Electrical Transmission and Distribution SF6 ✓ ✓ 13.2 

PFC Emissions from Aluminum Production PFCs ✓ ✓ 2.5 

Agriculture

CH4 Emissions from Enteric Fermentation CH4 ✓ ✓ ✓ ✓ 126.2 

CH4 Emissions from Manure Management CH4 ✓ ✓ ✓ 41.4 

Direct N2O Emissions from Agricultural Soil Management N2O ✓ ✓ ✓ ✓ 214.7 

Indirect N2O Emissions from Applied Nitrogen N2O ✓ ✓ ✓ ✓ 50.3 

Waste

CH4 Emissions from Landfills CH4 ✓ ✓ ✓ ✓ 125.7 

Land Use, Land Use Change, and Forestry

CO2 Emissions from Forest Land Remaining Forest Land CO2 ✓ ✓ (745.1)

CO2 Emissions from Settlements Remaining Settlements CO2 ✓ ✓ (95.5)

CO2 Emissions from Cropland Remaining Cropland CO2 ✓ ✓ (33.8)

CO2 Emissions from Grassland Remaining Grassland CO2 ✓ 16.2 

CO2 Emissions from Landfilled Yard Trimmings and Food Scraps CO2 ✓ (10.5)

CO2 Emissions from Land Converted to Cropland CO2 ✓ 9.4 

CH4 Emissions from Forest Land Remaining Forest Land CH4 ✓ 24.6 

Subtotal Without LULUCF 6,807.6 

Total Emissions Without LULUCF 7,017.3 

Percent of Total Without LULUCF 97.0%

Subtotal With LULUCF 5,972.8 

Total Emissions With LULUCF 6,170.5 

Percent of Total With LULUCF 96.8%

a Qualitative criteria.

b Emissions from this source not included in totals.

Note: The Tier 1 approach for identifying key source categories does not directly include assessment of uncertainty in emissions estimates.

Note: Parentheses indicate negative values or sequestration. The net CO2 flux total includes both emissions and sequestration, and constitutes a sink in 

the United States.
Introduction 1-13

•	 consideration of secondary data quality and sourcespecific quality checks (Tier 2 QC) in parallel and 

coordination with the uncertainty assessment; the 

development of protocols and templates provides for 

more structured communication and integration with 

the suppliers of secondary information;

•	 record-keeping provisions to track which procedures 

have been followed, and the results of the QA/QC 

and uncertainty analysis, and contains feedback 

mechanisms for corrective action based on the results 

of the investigations, thereby providing for continual 

data quality improvement and guided research efforts;

•	 implementation of QA/QC procedures throughout the 

whole inventory development process—from initial 

data collection, through preparation of the emission 

estimates, to publication of the Inventory;

•	 a schedule for multi-year implementation; and

•	 promotion of coordination and interaction within the 

EPA, across Federal agencies and departments, state 

government programs, and research institutions and 

consulting firms involved in supplying data or preparing 

estimates for the Inventory. The QA/QC plan itself is 

intended to be revised and reflect new information that 

becomes available as the program develops, methods 

are improved, or additional supporting documents 

become necessary. 

In addition, based on the national QA/QC plan for 

the Inventory, source-specific QA/QC plans have been 

developed for a number of sources. These plans follow the 

procedures outlined in the national QA/QC plan, tailoring 

the procedures to the specific text and spreadsheets of the 

individual sources. For each greenhouse gas emissions source 

or sink included in this Inventory, a minimum of a Tier 1 QA/

QC analysis has been undertaken. Where QA/QC activities 

for a particular source go beyond the minimum Tier 1 level, 

further explanation is provided within the respective source 

category text.

The quality control activities described in the U.S. QA/

QC plan occur throughout the inventory process; QA/QC 

is not separate from, but is an integral part of, preparing 

the Inventory. Quality control—in the form of both good 

practices (such as documentation procedures) and checks on 

whether good practices and procedures are being followed—

is applied at every stage of inventory development and 

document preparation. In addition, quality assurance occurs 

at two stages—an expert review and a public review. While 

both phases can significantly contribute to inventory quality, 

the public review phase is also essential for promoting the 

openness of the inventory development process and the 

transparency of the inventory data and methods.

The QA/QC plan guides the process of ensuring 

inventory quality by describing data and methodology 

checks, developing processes governing peer review and 

public comments, and developing guidance on conducting 

an analysis of the uncertainty surrounding the emission 

estimates. The QA/QC procedures also include feedback 

loops and provide for corrective actions that are designed 

to improve the inventory estimates over time.

1.7. 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.
1-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Additional research in the following areas could help 

reduce uncertainty in the U.S. Inventory:

•	 Incorporating excluded emission sources. Quantitative 

estimates for some of the sources and sinks of greenhouse 

gas emissions are not available at this time. In particular, 

emissions from some land-use activities and industrial 

processes are not included in the Inventory either 

because data are incomplete or because methodologies 

do not exist for estimating emissions from these source 

categories. See Annex 5 of this report for a discussion 

of the sources of greenhouse gas emissions and sinks 

excluded from this report.

•	 Improving the accuracy of emission factors. Further 

research is needed in some cases to improve the accuracy 

of emission factors used to calculate emissions from a 

variety of sources. For example, the accuracy of current 

emission factors applied to CH4 and N2O emissions from 

stationary and mobile combustion is highly uncertain.

•	 Collecting detailed activity data. Although methodologies 

exist for estimating emissions for some sources, 

problems arise in obtaining activity data at a level 

of detail in which aggregate emission factors can be 

applied. For example, the ability to estimate emissions 

of SF6 from electrical transmission and distribution is 

limited due to a lack of activity data regarding national 

SF6 consumption or average equipment leak rates.

The overall uncertainty estimate for the U.S. Greenhouse 

Gas Emissions Inventory was developed using the IPCC Tier 2 

uncertainty estimation methodology. An estimate of the overall 

quantitative uncertainty is shown below, in Table 1-5.

The IPCC provides good practice guidance on two 

approaches—Tier 1 and Tier 2—to estimating uncertainty 

for individual source categories. Tier 2 uncertainty analysis, 

employing the Monte Carlo Stochastic Simulation technique, 

was applied wherever data and resources permitted; further 

explanation is provided within the respective source category 

text. Consistent with the IPCC Good Practice Guidance, 

over a multi-year timeframe, the United States expects to 

continue to improve the uncertainty estimates presented in 

this report.

Emissions calculated for the U.S. Inventory reflect 

current best estimates; in some cases, however, estimates 

are based on approximate methodologies, assumptions, and 

incomplete data. As new information becomes available 

in the future, the United States will continue to improve 

and revise its emission estimates. See Annex 7 of this 

report for further details on the U.S. process for estimating 

uncertainties associated with emission estimates and for a 

more detailed discussion of the limitations of the current 

analysis and plans for improvement. Annex 7 also includes 

details on the uncertainty analysis performed for selected 

source categories.

Table 1-5. Estimated Overall Inventory Uncertainty (Tg CO2 Eq. and Percent)

2006 Emission 

Estimate Uncertainty Range Relative to Emission Estimatea Meanb

Standard 

Deviation

Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%) (Tg CO2 Eq.)

Lower Boundc Upper Boundc Lower Boundc Upper Boundc

CO2 5,983.1 5,884.9 6,288.6 -2% 5% 6,082.2 105.5

CH4 555.3 508.4 658.2 -8% 19% 576.6 38.9

N2O 367.9 352.2 449.3 -4% 22% 398.4 25.0

PFC, HFC & SF6

d 147.9 145.7 166.3 -1% 12% 156.1 5.2

Total 7,054.2 6,999.6 7,439.0 -1% 5% 7,213.3 115.2

Net Emissions

(Sources and Sinks) 6,170.5 6,059.0 6,615.0 -2% 7% 6,332.3 143.3

a Range of emission estimates for a 95 percent confidence interval.

b Mean value indicates the arithmetic average of the simulated emission estimates; standard deviation indicates the extent of deviation of the simulated 

values from the mean.

c The low and high estimates for total emissions were calculated separately through simulations and, hence, the low and high emission estimates for the 

sub-source categories do not sum to total emissions.

d The overall uncertainty estimate did not take into account the uncertainty in the GWP values for CH4, N2O and high-GWP gases used in the inventory 

emission calculations for 2006.
Introduction 1-15

1.8. Completeness

This report, along with its accompanying CRF reporter, 

serves as a thorough assessment of the anthropogenic sources 

and sinks of greenhouse gas emissions for the United States 

for the time series 1990 through 2006. Although this report 

is intended to be comprehensive, certain sources have been 

identified yet excluded from the estimates presented for 

various reasons. Generally speaking, sources not accounted 

for in this Inventory are excluded due to data limitations or 

a lack of thorough understanding of the emission process. 

The United States is continually working to improve upon 

the understanding of such sources and seeking to find the data 

required to estimate related emissions. As such improvements 

are made, new emission sources are quantified and included 

in the Inventory. For a complete list of sources excluded, see 

Annex 5 of this report.

1.9. Organization of Report

In accordance with the Revised 1996 IPCC Guidelines 

for National Greenhouse Gas Inventories (IPCC/UNEP/

OECD/IEA 1997), and the 2003 UNFCCC Guidelines on 

Reporting and Review (UNFCCC 2003), this Inventory of 

U.S. Greenhouse Gas Emissions and Sinks is segregated 

into six sector-specific chapters, listed below in Table 1-6. In 

addition, chapters on Trends in Greenhouse Gas Emissions 

and Other information to be considered as part of the U.S. 

Inventory submission are included.

Within each chapter, emissions are identified by the 

anthropogenic activity that is the source or sink of the 

greenhouse gas emissions being estimated (e.g., coal mining). 

Overall, the following organizational structure is consistently 

applied throughout this report:

Chapter/IPCC Sector: Overview of emission trends for each 

IPCC defined sector

Source category: Description of source pathway and 

emission trends.

Methodology: Description of analytical methods 

employed to produce emission estimates and 

identification of data references, primarily for 

activity data and emission factors.

Uncertainty: A discussion and quantification of the 

uncertainty in emission estimates and a discussion 

of time-series consistency.

QA/QC and Verification: A discussion on steps taken 

to QA/QC and verify the emission estimates, where 

beyond the overall U.S. QA/QC plan, and any key 

findings.

Recalculations: A discussion of any data or 

methodological changes that 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 sourcespecific planned improvements, if applicable.

Special attention is given to CO2 from fossil fuel 

combustion relative to other sources because of its share of 

emissions and its dominant influence on emission trends. 

Table 1-6: IPCC Sector Descriptions

Chapter/IPCC Sector Activities Included

Energy Emissions of all greenhouse gases resulting from stationary and mobile energy activities 

including fuel combustion and fugitive fuel emissions.

Industrial Processes Byproduct or fugitive emissions of greenhouse gases from industrial processes not 

directly related to energy activities such as fossil fuel combustion.

Solvent and Other Product Use Emissions, primarily of NMVOCs, resulting from the use of solvents and N2O from 

product uses.

Agriculture Anthropogenic emissions from agricultural activities except fuel combustion, which is 

addressed under Energy.

Land Use, Land-Use Change, and Forestry Emissions and removals of CO2, CH4, and N2O from forest management, other land-use 

activities, and land-use change.

Waste Emissions from waste management activities.

Source: (IPCC/UNEP/OECD/IEA 1997)
1-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

For example, each energy consuming end-use sector (i.e., 

residential, commercial, industrial, and transportation), 

as well as the electricity generation sector, is described 

individually. Additional information for certain source 

categories and other topics is also provided in several 

Annexes listed in Table 1-7.

Table 1-7: List of Annexes

ANNEX 1 Key Category Analysis

ANNEX 2 Methodology and Data for Estimating CO2 Emissions from Fossil Fuel Combustion

2.1. Methodology for Estimating Emissions of CO2 from Fossil Fuel Combustion

2.2. Methodology for Estimating the Carbon Content of Fossil Fuels

2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil Fuels

ANNEX 3 Methodological Descriptions for Additional Source or Sink Categories

3.1. Methodology for Estimating Emissions of CH4, N2O, and Indirect Greenhouse Gases from Stationary Combustion

3.2. Methodology for Estimating Emissions of CH4, N2O, and Indirect Greenhouse Gases from Mobile Combustion and 

Methodology for and Supplemental Information on Transportation-Related Greenhouse Gas Emissions

3.3. Methodology for Estimating CH4 Emissions from Coal Mining

3.4. Methodology for Estimating CH4 Emissions from Natural Gas Systems

3.5. Methodology for Estimating CH4 and CO2 Emissions from Petroleum Systems

3.6. Methodology for Estimating CO2 and N2O Emissions from Municipal Solid Waste Combustion

3.7. Methodology for Estimating Emissions from International Bunker Fuels used by the U.S. Military

3.8. Methodology for Estimating HFC and PFC Emissions from Substitution of Ozone Depleting Substances

3.9. Methodology for Estimating CH4 Emissions from Enteric Fermentation

3.10. Methodology for Estimating CH4 and N2O Emissions from Manure Management

3.11. Methodology for Estimating N2O Emissions from Agricultural Soil Management

3.12. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands

3.13. Methodology for Estimating Net Changes in Carbon Stocks in Mineral and Organic Soils on Croplands and Grasslands

3.14. Methodology for Estimating CH4 Emissions from Landfills

ANNEX 4 IPCC Reference Approach for Estimating CO2 Emissions from Fossil Fuel Combustion

ANNEX 5 Assessment of the Sources and Sinks of Greenhouse Gas Emissions Excluded

ANNEX 6 Additional Information

6.1. Global Warming Potential Values

6.2. Ozone Depleting Substance Emissions

6.3. Sulfur Dioxide Emissions

6.4. Complete List of Source Categories

6.5. Constants, Units, and Conversions

6.6. Abbreviations

6.7. Chemical Formulas

ANNEX 7 Uncertainty

7.1. Overview

7.2. Methodology and Results

7.3. Planned Improvements

7.4. Additional Information on Uncertainty Analyses by Source
Trends in Greenhouse Gas Emissions 2-1

2. Trends in Greenhouse Gas 

Emissions

2.1. Recent Trends in U.S. Greenhouse Gas Emissions

I

n 2006, total U.S. greenhouse gas emissions were 7,054.2 teragrams of carbon dioxide equivalents (Tg CO2 Eq.).1

Overall, total U.S. emissions have risen by 14.7 percent from 1990 to 2006, while the U.S. gross domestic product 

has increased by 59 percent over the same period (BEA 2007). Emissions decreased from 2005 to 2006 by 1.1 

percent (75.7 Tg CO2 Eq.). The following factors were primary contributors to this decrease: (1) compared to 2005, 2006 

had warmer winter conditions, which decreased consumption of heating fuels, as well as cooler summer conditions, which 

reduced demand for electricity, (2) restraint on fuel consumption caused by rising fuel prices, primarily in the transportation 

sector and (3) increased use of natural gas and renewables in the electric power sector. Figure 2-1 through Figure 2-3 illustrate 

the overall trends in total U.S. emissions by gas,2 annual changes, and absolute changes since 1990.

As the largest source of U.S. greenhouse gas emissions, carbon dioxide (CO2) from fossil fuel combustion has accounted 

for approximately 79 percent of global warming potential (GWP) weighted emissions since 1990, growing slowly from 

77 percent of total GWP-weighted emissions in 1990 to 80 

percent in 2006. Emissions from this source category grew by 

19.3 percent (913.8 Tg CO2 Eq.) from 1990 to 2006 and were 

responsible for most of the increase in national emissions 

during this period. From 2005 to 2006, these emissions 

decreased by 1.6 percent (93.1 Tg CO2 Eq.). Historically, 

changes in emissions from fossil fuel combustion have been 

the dominant factor affecting U.S. emission trends.

Changes in CO2 emissions from fossil fuel combustion 

are influenced by many long-term and short-term factors, 

including population and economic growth, energy 

price fluctuations, technological changes, and seasonal 

temperatures. On an annual basis, the overall consumption 

of fossil fuels in the United States generally fluctuates in 

response to changes in general economic conditions, energy 

prices, weather, and the availability of non-fossil alternatives. 

1Estimates are presented in units of teragrams of carbon dioxide equivalents (Tg CO2 Eq.), which weight each gas by its global warming potential, or 

GWP, value. (See section on global warming potentials, Executive Summary.)

2 See the following section for an analysis of emission trends by general U.S. economic sector.

Figure 2-1

U.S. Greenhouse Gas Emissions by Gas

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

Tg CO2 Eq.

6,148 1990

6,106 1991

6,192 1992

6,343 1993

6,435 1994

6,494 1995

6,731 1996

6,760 1997

6,801 1998

6,839 1999

7,033 2000

6,921 2001

6,981 2002

6,998 2003

7,078 2004

7,130 2005

7,054 2006

HFCs, PFCs, & SF6

Nitrous Oxide

Methane

Carbon Dioxide
2-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

For example, in a year with increased consumption of 

goods and services, low fuel prices, severe summer and 

winter weather conditions, nuclear plant closures, and lower 

precipitation feeding hydroelectric dams, there would likely 

be proportionally greater fossil fuel consumption than in 

a year with poor economic performance, high fuel prices, 

mild temperatures, and increased output from nuclear and 

hydroelectric plants.

In the longer-term, energy consumption patterns 

respond to changes that affect the scale of consumption (e.g., 

population, number of cars, and size of houses), the efficiency 

with which energy is used in equipment (e.g., cars, power 

plants, steel mills, and light bulbs) and consumer behavior 

(e.g., walking, bicycling, or telecommuting to work instead 

of driving).

Energy-related CO2 emissions also depend on the type 

of fuel or energy consumed and its carbon (C) intensity. 

Producing a unit of heat or electricity using natural gas 

instead of coal, for example, can reduce the CO2 emissions 

because of the lower C content of natural gas.

After emissions significantly decreased in 2001 due to 

the economic slowdown, emissions from fuel combustion 

resumed modest growth in 2002, slightly less than the average 

annual growth rate since 1990. There were a number of 

reasons behind this increase. The U.S. economy experienced 

moderate growth, recovering from weak economic conditions 

in 2001. Prices for fuels remained at or below 2001 levels; the 

cost of natural gas, motor gasoline, and electricity were all 

lower—triggering an increase in demand for fuel. In addition, 

the United States experienced one of the hottest summers on 

record, causing a significant increase in electricity use in the 

residential sector as the use of air-conditioners increased. 

Partially offsetting this increased consumption of fossil fuels, 

however, were increases in the use of nuclear and renewable 

fuels. Nuclear facilities operated at the highest capacity 

on record in 2002. Furthermore, there was a considerable 

increase in the use of hydroelectric power in 2002 after a 

very low output the previous year.

Emissions from fuel combustion continued growing in 

2003, at about the average annual growth rate since 1990. A 

number of factors played a major role in the magnitude of this 

increase. The U.S. economy experienced moderate growth 

from 2002, causing an increase in the demand for fuels. The 

price of natural gas escalated dramatically, causing some 

electric power producers to switch to coal, which remained 

at relatively stable prices. Colder winter conditions brought 

on more demand for heating fuels, primarily in the residential 

sector. Though a cooler summer partially offset demand for 

electricity as the use of air-conditioners decreased, electricity 

consumption continued to increase in 2003. The primary 

drivers behind this trend were the growing economy and the 

increase in U.S. housing stock. Nuclear capacity decreased 

slightly, for the first time since 1997. Use of renewable fuels 

rose slightly due to increases in the use of hydroelectric 

power and biofuels.

From 2003 to 2004, these emissions increased at a rate 

slightly higher than the average growth rate since 1990. A 

number of factors played a major role in the magnitude of this 

increase. A primary reason behind this trend was strong growth 

in the U.S. economy and industrial production, particularly 

Figure 2-2

Annual Percent Change in U.S. Greenhouse Gas Emissions

-2%

-1%

0%

1%

2%

3%

4%

-0.7%1991 1.4%1992 2.4%1993 1.5%1994 0.9%1995 3.6%1996 0.4%1997 0.6%1998 0.6%1999 2.8%2000 -1.6%2001 0.9%2002 0.2%2003 1.1%2004 0.7%2005 -1.1%2006

Figure 2-3

Cumulative Change in U.S. Greenhouse Gas 

Emissions Relative to 1990

-100

0

100

200

300

400

500

600

700

800

900

1,000

Tg CO2 Eq.

-421991 441992

1951993

2871994

3461995

5831996

6121997

6521998

6911999

8842000

7732001

8332002

8502003

9302004

9062006

9822005
Trends in Greenhouse Gas Emissions 2-3

in energy-intensive industries, causing an increase in the 

demand for electricity and fossil fuels. Demand for travel was 

also higher, causing an increase in petroleum consumed for 

transportation. In contrast, the warmer winter conditions led 

to decreases in demand for heating fuels, principally natural 

gas, in both the residential and commercial sectors. Moreover, 

much of the increased electricity demanded was generated by 

natural gas combustion and nuclear power, which moderated 

the increase in CO2 emissions from electricity generation. 

Use of renewable fuels rose very slightly due to increases 

in the use biofuels.

Emissions from fuel combustion increased from 2004 to 

2005 at a rate slightly lower than the average annual growth 

rate since 1990. A number of factors played a role in this 

slight increase. This small increase is primarily a result of the 

restraint on fuel consumption, primarily in the transportation 

sector, caused by rising fuel prices. Although electricity 

prices increased slightly, there was a significant increase in 

electricity consumption in the residential and commercial 

sectors due to warmer summer weather conditions. This led 

to an increase in emissions in these sectors with the increased 

use of air-conditioners. As electricity emissions increased 

among all end-use sectors, the fuels used to generate 

electricity increased as well. Despite a slight decrease in 

industrial energy-related emissions, industrial production 

and manufacturing output actually increased. The price of 

natural gas escalated dramatically, causing a decrease in 

consumption of natural gas in the industrial sector. Use of 

renewable fuels decreased slightly due to decreased use of 

biofuels and decreased electricity output by hydroelectric 

power plants.

From 2005 to 2006, emissions from fuel combustion 

decreased for the first time since 2000 to 2001. This 

decrease occurred primarily in the electricity generation, 

transportation, residential, and commercial sectors due to a 

number of factors. The decrease in emissions from electricity 

generation is a result of a smaller share of electricity by 

coal and a greater share generated by natural gas. Coal and 

natural gas consumption for electricity generation decreased 

by 1.3 percent and increased by 6.4 percent, respectively, 

in 2006, and nuclear power increased by less than 1 

percent. The transportation decrease is primarily a result 

of the restraint on fuel consumption caused by rising fuel 

prices, which directly resulted in a decrease of petroleum 

consumption within this sector of less than one percent in 

2006. The decrease in emissions from the residential sector 

is primarily a result of decreased electricity consumption 

due to increases in the price of electricity, and warmer 

winter weather conditions. The increase in emissions in 

the industrial sector is a result of increased emissions from 

fossil fuel combustion for this sector. A moderate increase 

in the industrial sector is a result of growth in industrial 

output and growth in the U.S. economy. Renewable fuels 

used to generate electricity increased in 2006, with the 

greatest growth occurring in wind.

Overall, from 1990 to 2006, total emissions of CO2

increased by 914.6 Tg CO2 Eq. (18 percent), while CH4 and 

N2O emissions decreased by 50.8 Tg CO2 Eq. (8 percent) 

and 15.5 Tg CO2 Eq. (4 percent) respectively. During the 

same period, aggregate weighted emissions of HFCs, PFCs, 

and SF6 rose by 57.6 Tg CO2 Eq. (64 percent). Despite being 

emitted in smaller quantities relative to the other principal 

greenhouse gases, emissions of HFCs, PFCs, and SF6 are 

significant because many of them have extremely high GWPs 

and, in the cases of PFCs and SF6, long atmospheric lifetimes. 

Conversely, U.S. greenhouse gas emissions were partly offset 

by C sequestration in managed forests, trees in urban areas, 

agricultural soils, and landfilled yard trimmings, which was 

estimated to be 12 percent of total emissions in 2006.

Table 2-1 summarizes emissions and sinks from all U.S. 

anthropogenic sources in weighted units of Tg CO2 Eq., while 

unweighted gas emissions and sinks in gigagrams (Gg) are 

provided in Table 2-2.

Emissions of all gases can be summed from each 

source category from Intergovernmental Panel on Climate 

Change (IPCC) guidance. Over the sixteen-year period 

of 1990 to 2006, total emissions in the Energy, Industrial 

Processes, and Agriculture sectors grew by 873.0 Tg CO2

Eq. (17 percent), 21.0 Tg CO2 Eq. (7 percent), and 6.6 Tg 

CO2 Eq. (1 percent), respectively. Emissions decreased 

in the Waste and Solvent and Other Product Use sectors 

by 18.6 Tg CO2 Eq. (10 percent) and less than 0.02 Tg 

CO2 Eq. (less than 1 percent), respectively. Over the same 

period, estimates of net C sequestration in the Land Use, 

Land-Use Change, and Forestry sector increased by 122.2 

Tg CO2 Eq. (17 percent).
2-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 5,068.5 5,394.2 5,939.7 5,846.2 5,908.6 5,952.7 6,038.2 6,074.3 5,983.1 

Fossil Fuel Combustion 4,724.1 5,032.4 5,577.1 5,507.4 5,564.8 5,617.0 5,681.4 5,731.0 5,637.9 

Electricity Generation 1,809.6 1,939.3 2,282.3 2,244.3 2,253.7 2,283.1 2,314.9 2,380.2 2,328.2 

Transportation 1,485.1 1,599.4 1,798.2 1,775.6 1,828.9 1,807.6 1,856.4 1,869.8 1,856.0 

Industrial 844.9 876.5 860.3 852.5 854.8 856.0 857.7 847.3 862.2 

Residential 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5 

Commercial 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1 

U.S. Territories 28.3 35.0 36.2 49.0 44.0 51.0 53.5 53.2 54.9 

Non-Energy Use of Fuels 117.2 133.2 141.4 131.9 135.9 131.8 148.9 139.1 138.0 

Iron and Steel Production 86.2 74.7 66.6 59.2 55.9 54.7 52.8 46.6 49.1 

Cement Production 33.3 36.8 41.2 41.4 42.9 43.1 45.6 45.9 45.7 

Natural Gas Systems 33.7 33.8 29.4 28.8 29.6 28.4 28.1 29.5 28.5 

Municipal Solid Waste Combustion 10.9 15.7 17.5 18.0 18.5 19.1 20.1 20.7 20.9 

Lime Production 12.0 14.0 14.9 14.3 13.7 14.5 15.2 15.1 15.8 

Ammonia Production 

and Urea Consumption 16.9 17.8 16.4 13.3 14.2 12.5 13.2 12.8 12.4 

Limestone and Dolomite Use 5.5 7.4 6.0 5.7 5.9 4.8 6.7 7.4 8.6 

Cropland Remaining Cropland 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0 

Soda Ash Production and Consumption 4.1 4.3 4.2 4.1 4.1 4.1 4.2 4.2 4.2 

Aluminum Production 6.8 5.7 6.1 4.4 4.5 4.5 4.2 4.2 3.9 

Petrochemical Production 2.2 2.8 3.0 2.8 2.9 2.8 2.9 2.8 2.6 

Titanium Dioxide Production 1.2 1.5 1.8 1.7 1.8 1.8 2.1 1.8 1.9 

Carbon Dioxide Consumption 1.4 1.4 1.4 0.8 1.0 1.3 1.2 1.3 1.6 

Ferroalloy Production 2.2 2.0 1.9 1.5 1.3 1.3 1.4 1.4 1.5 

Phosphoric Acid Production 1.5 1.5 1.4 1.3 1.3 1.4 1.4 1.4 1.2 

Zinc Production 0.9 1.0 1.1 1.0 0.9 0.5 0.5 0.5 0.5 

Petroleum Systems 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Lead Production 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Silicon Carbide Production 

and Consumption 0.4 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 

Land Use, Land-Use Change, 

and Forestry (Sink)a (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Wood Biomass and Ethanol Consumptionb 219.3 236.8 227.3 203.2 204.4 209.5 224.8 227.4 234.7 

International Bunker Fuelsb 113.7 100.6 101.1 97.6 89.1 103.6 119.0 122.6 127.1 

CH4 606.1 598.9 574.3 558.8 563.5 559.4 545.6 539.7 555.3 

Enteric Fermentation 126.9 132.3 124.6 123.6 123.8 124.6 122.4 124.5 126.2 

Landfills 149.6 144.0 120.8 117.6 120.1 125.6 122.6 123.7 125.7 

Natural Gas Systems 124.7 128.1 126.5 125.3 124.9 123.3 114.0 102.5 102.4 

Coal Mining 84.1 67.1 60.4 60.3 56.8 56.9 59.8 57.1 58.5 

Manure Management 31.0 35.2 38.8 40.2 41.3 40.7 40.1 41.8 41.4 

Petroleum Systems 33.9 32.0 30.3 30.2 29.9 29.2 28.7 28.3 28.4 

Forest Land Remaining Forest Land 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 

Wastewater Treatment 23.0 24.3 24.6 24.2 24.1 23.9 24.0 23.8 23.9 

Stationary Combustion 7.4 7.2 6.6 6.2 6.2 6.4 6.5 6.5 6.2 

Rice Cultivation 7.1 7.6 7.5 7.6 6.8 6.9 7.6 6.8 5.9 
Trends in Greenhouse Gas Emissions 2-5

Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Abandoned Underground Coal Mines 6.0 8.2 7.4 6.7 6.2 6.0 5.8 5.6 5.4 

Mobile Combustion 4.7 4.3 3.4 3.3 3.0 2.7 2.6 2.5 2.4 

Composting 0.3 0.7 1.3 1.3 1.3 1.5 1.6 1.6 1.6 

Petrochemical Production 0.9 1.1 1.2 1.1 1.1 1.1 1.2 1.1 1.0 

Iron and Steel Production 1.3 1.3 1.2 1.1 1.0 1.0 1.0 1.0 0.9 

Field Burning of Agricultural Residues 0.7 0.7 0.8 0.8 0.7 0.8 0.9 0.9 0.8 

Ferroalloy Production + + + + + + + + + 

Silicon Carbide Production 

and Consumption + + + + + + + + + 

International Bunker Fuelsb 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 

N2O 383.4 395.6 385.9 392.9 376.1 356.6 353.5 370.1 367.9 

Agricultural Soil Management 269.4 264.8 262.1 277.0 262.0 247.3 246.9 265.2 265.0 

Mobile Combustion 43.5 53.4 52.5 49.9 45.9 42.3 39.7 36.3 33.1 

Nitric Acid Production 17.0 18.9 18.6 15.1 16.4 15.4 15.2 15.8 15.6 

Stationary Combustion 12.8 13.4 14.6 14.1 14.0 14.3 14.6 14.8 14.5 

Manure Management 12.1 12.8 13.7 14.0 14.0 13.6 13.8 13.9 14.3 

Wastewater Treatment 6.3 6.9 7.6 7.8 7.6 7.7 7.8 8.0 8.1 

Adipic Acid Production 15.3 17.3 6.2 5.1 6.1 6.3 5.9 5.9 5.9 

N2O from Product Uses 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4 

Forest Land Remaining Forest Land 0.5 0.6 2.2 1.3 2.0 1.2 1.1 1.6 2.8 

Composting 0.4 0.8 1.4 1.4 1.4 1.6 1.7 1.7 1.8 

Settlements Remaining Settlements 1.0 1.2 1.2 1.4 1.5 1.5 1.6 1.5 1.5 

Field Burning of Agricultural Residues 0.4 0.4 0.5 0.5 0.4 0.4 0.5 0.5 0.5 

Municipal Solid Waste Combustion 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 

International Bunker Fuelsb 1.0 0.9 0.9 0.9 0.8 0.9 1.1 1.1 1.1 

HFCs 36.9 61.8 100.1 97.9 106.3 104.5 116.6 121.4 124.5 

Substitution of Ozone Depleting 

Substancesc 0.3 28.5 71.2 78.0 85.0 92.0 99.1 105.4 110.4 

HCFC-22 Production 36.4 33.0 28.6 19.7 21.1 12.3 17.2 15.8 13.8 

Semiconductor Manufacture 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.3 

PFCs 20.8 15.6 13.5 7.0 8.7 7.1 6.1 6.2 6.0 

Semiconductor Manufacture 2.2 3.8 4.9 3.5 3.5 3.3 3.3 3.2 3.6 

Aluminum Production 18.5 11.8 8.6 3.5 5.2 3.8 2.8 3.0 2.5 

SF6 32.7 28.0 19.1 18.7 18.0 18.1 18.0 18.2 17.3 

Electrical Transmission and Distribution 26.7 21.5 15.1 15.0 14.4 13.8 13.9 14.0 13.2 

Magnesium Production and Processing 5.4 5.6 3.0 2.9 2.9 3.4 3.2 3.3 3.2 

Semiconductor Manufacture 0.5 0.9 1.1 0.7 0.7 0.8 0.8 1.0 1.0 

Total 6,148.3 6,494.0 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2 

Net Emissions (Sources and Sinks) 5,410.6 5,718.7 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5 

+ Does not exceed 0.05 Tg CO2 Eq. a The net CO2 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions 

total. Parentheses indicate negative values or sequestration.

b Emissions from International Bunker Fuels and Wood Biomass and Ethanol Consumption are not included in totals.

c Small amounts of PFC emissions also result from this source.

Note: Totals may not sum due to independent rounding.

(continued)
2-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg)

Gas/Source 1990 2000 2001 2002 2003 2004 2005 2006

CO2 5,068,472 5,939,726 5,846,151 5,908,568 5,952,650 6,038,211 6,074,306 5,983,108 

Fossil Fuel Combustion 4,724,146 5,577,072 5,507,406 5,564,795 5,617,047 5,681,363 5,731,045 5,637,931 

Electricity Generation 1,809,614 2,282,278 2,244,279 2,253,729 2,283,069 2,314,907 2,380,222 2,328,153 

Transportation 1,485,057 1,798,164 1,775,636 1,828,910 1,807,591 1,856,373 1,869,848 1,856,047 

Industrial 844,937 860,325 852,494 854,822 856,042 857,722 847,328 862,187 

Residential 340,109 372,083 363,629 360,492 382,864 368,258 358,515 326,522 

Commercial 216,144 228,027 222,341 222,828 236,452 230,617 221,921 210,140 

U.S. Territories 28,285 36,195 49,027 44,014 51,030 53,486 53,213 54,882 

Non-Energy Use of Fuels 117,170 141,427 131,887 135,857 131,772 148,931 139,057 137,980 

Iron and Steel Production 86,220 66,609 59,249 55,938 54,744 52,771 46,627 49,119 

Cement Production 33,278 41,190 41,357 42,898 43,082 45,603 45,910 45,739 

Natural Gas Systems 33,729 29,390 28,793 29,629 28,445 28,122 29,462 28,504 

Municipal Solid Waste Combustion 10,950 17,518 17,971 18,458 19,058 20,097 20,673 20,922 

Lime Production 12,004 14,872 14,261 13,652 14,458 15,154 15,131 15,825 

Ammonia Production and 

Urea Consumption 16,889 16,402 13,305 14,194 12,488 13,241 12,817 12,376 

Limestone and Dolomite Use 5,533 5,960 5,733 5,885 4,753 6,702 7,397 8,615 

Cropland Remaining Cropland 7,084 7,541 7,825 8,549 8,260 7,555 7,854 8,012 

Soda Ash Production 

and Consumption 4,141 4,181 4,147 4,139 4,111 4,205 4,228 4,162 

Aluminum Production 6,831 6,086 4,381 4,490 4,503 4,231 4,207 3,923 

Petrochemical Production 2,221 3,004 2,787 2,857 2,777 2,895 2,804 2,573 

Titanium Dioxide Production 1,195 1,752 1,697 1,824 1,839 2,064 1,755 1,876 

Carbon Dioxide Consumption 1,416 1,421 829 989 1,311 1,198 1,321 1,579 

Ferroalloy Production 2,152 1,893 1,459 1,349 1,305 1,419 1,392 1,505 

Phosphoric Acid Production 1,529 1,382 1,264 1,338 1,382 1,395 1,386 1,167 

Zinc Production 949 1,140 986 937 507 477 465 529 

Petroleum Systems 376 325 325 320 316 302 287 293 

Lead Production 285 311 291 286 289 263 266 270 

Silicon Carbide Production 

and Consumption 375 248 199 183 202 224 219 207 

Land Use, Land-Use Change, 

and Forestry (Sink)a (737,677) (673,608) (750,191) (826,758) (860,912) (873,660) (878,605) (883,665)

Wood Biomass and 

Ethanol Consumptionb 219,341 227,276 203,163 204,351 209,537 224,825 227,366 234,726 

International Bunker Fuelsb 113,683 101,125 97,563 89,101 103,583 118,975 122,580 127,097 

CH4 28,861 27,346 26,608 26,832 26,637 25,979 25,698 26,442 

Enteric Fermentation 6,044 5,933 5,886 5,896 5,931 5,828 5,928 6,010 

Landfills 7,124 5,751 5,598 5,720 5,981 5,838 5,890 5,985 

Natural Gas Systems 5,937 6,024 5,968 5,946 5,874 5,426 4,880 4,877 

Coal Mining 4,003 2,874 2,874 2,707 2,709 2,846 2,717 2,784 

Manure Management 1,474 1,847 1,915 1,964 1,938 1,908 1,988 1,972 

Petroleum Systems 1,612 1,442 1,436 1,422 1,390 1,368 1,346 1,354 

Forest Land Remaining Forest Land 213 904 448 780 416 330 586 1,169 

Wastewater Treatment 1,096 1,173 1,150 1,148 1,140 1,141 1,131 1,136 

Stationary Combustion 353 316 295 295 306 311 308 296 

Rice Cultivation 339 357 364 325 328 360 326 282 

Abandoned Underground 

Coal Mines 288 350 319 293 284 276 265 257 
Trends in Greenhouse Gas Emissions 2-7

Table 2-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg)

Gas/Source 1990 2000 2001 2002 2003 2004 2005 2006

Mobile Combustion 224 162 157 141 131 126 119 112 

Composting 15 60 60 61 69 74 75 75 

Petrochemical Production 41 58 51 52 51 55 51 48 

Iron and Steel Production 63 58 51 48 49 50 45 45 

Field Burning of Agricultural 

Residues 33 38 37 34 38 42 41 39 

Ferroalloy Production 1 1 + + + + + + 

Silicon Carbide Production

 and Consumption 1 1 + + + + + + 

International Bunker Fuelsb 8 6 5 4 6 7 7 7 

N2O 1,237 1,245 1,267 1,213 1,150 1,140 1,194 1,187 

Agricultural Soil Management 869 845 894 845 798 796 855 855 

Mobile Combustion 140 169 161 148 137 128 117 107 

Nitric Acid Production 55 60 49 53 50 49 51 50 

Stationary Combustion 41 47 46 45 46 47 48 47 

Manure Management 39 44 45 45 44 44 45 46 

Wastewater Treatment 20 24 25 25 25 25 26 26 

Adipic Acid Production 49 20 16 20 20 19 19 19 

N2O from Product Uses 14 16 16 14 14 14 14 14 

Forest Land Remaining Forest Land 2 7 4 6 4 3 5 9 

Composting 1 4 5 5 5 6 6 6 

Settlements Remaining Settlements 3 4 5 5 5 5 5 5 

Field Burning of Agricultural 

Residues 1 1 1 1 1 2 2 2 

Municipal Solid Waste Combustion 2 1 1 1 1 1 1 1 

International Bunker Fuelsb 3 3 3 3 3 3 4 4 

HFCs M M M M M M M M

Substitution of Ozone Depleting 

Substancesc M M M M M M M M

HCFC-22 Production 3 2 2 2 1 1 1 1 

Semiconductor Manufacture + + + + + + + + 

PFCs M M M M M M M M

Semiconductor Manufacture M M M M M M M M

Aluminum Production M M M M M M M M

SF6 1 1 1 1 1 1 1 1 

Electrical Transmission 

and Distribution 1 1 1 1 1 1 1 1 

Magnesium Production 

and Processing + + + + + + + + 

Semiconductor Manufacture + + + + + + + + 

+ Does not exceed 0.5 Gg.

M Mixture of multiple gases.

a The net CO2 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions 

total. Parentheses indicate negative values or sequestration.

b Emissions from International Bunker Fuels and Wood Biomass and Ethanol Consumption are not included in totals.

c Small amounts of PFC emissions also result from this source.

Note: Totals may not sum due to independent rounding.

(continued)
2-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Energy

Energy-related activities, primarily fossil fuel 

combustion, accounted for the vast majority of U.S. CO2

emissions for the period of 1990 through 2006. In 2006, 

approximately 83 percent of the energy consumed in the 

United States (on a Btu basis) was produced through the 

combustion of fossil fuels. The remaining 17 percent came 

from other energy sources such as hydropower, biomass, 

nuclear, wind, and solar energy (see Figure 2-5 and Figure 

2-6). A discussion of specific trends related to CO2 as well as 

other greenhouse gas emissions from energy consumption is 

presented in the Energy chapter. Energy-related activities are 

also responsible for CH4 and N2O emissions (37 percent and 

13 percent of total U.S. emissions of each gas, respectively). 

Table 2-4 presents greenhouse gas emissions from the Energy 

chapter, by source and gas.

CO2 emissions from fossil fuel combustion are presented 

in Table 2-5 based on the underlying U.S. energy consumer 

data collected by EIA. Estimates of CO2 emissions from 

fossil fuel combustion are calculated from these EIA “enduse sectors” based on total consumption and appropriate 

fuel properties (any additional analysis and refinement of 

the EIA data is further explained in the Energy chapter of 

this report). EIA’s fuel consumption data for the electricity 

Figure 2-4

U.S. Greenhouse Gas Emissions and Sinks 

by Chapter/IPCC Sector

Tg CO2 Eq.

19901991199219931994199519961997199819992000200120022003200420052006

Agriculture

Energy

(1,000)

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Land Use, Land-Use Change and Forestry (sinks)

Waste

Industrial Processes LULUCF (sources)

Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and 

Other Product Use sector.

Figure 2-5

2006 Energy Chapter Greenhouse Gas Emission Sources

0 25 50 75 100 125 150

Tg CO2 Eq.

5,637.9

Energy as a Portion

of all Emissions

86.1%

Abandoned Underground

Coal Mines

Stationary Combustion

Municipal Solid Waste

Combustion

Petroleum Systems

Mobile Combustion

Coal Mining

Natural Gas Systems

Non-Energy Use of Fuels

Fossil Fuel Combustion

Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg CO2 Eq.)

Chapter/IPCC Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Energy 5,203.9 5,529.6 6,067.8 5,982.8 6,036.3 6,078.3 6,150.9 6,174.4 6,076.9 

Industrial Processes 299.9 315.7 326.5 297.9 308.6 301.2 315.9 315.5 320.9 

Solvent and Other Product Use 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4 

Agriculture 447.5 453.8 447.9 463.7 449.0 434.3 432.1 453.6 454.1 

Land Use, Land-Use Change, and 

Forestry (Emissions) 13.1 13.6 30.0 20.0 28.4 19.7 17.1 23.2 36.9 

Waste 179.6 176.8 155.6 152.1 154.5 160.3 157.7 158.7 161.0 

Total Emissions 6,148.3 6,494.0 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2 

Net CO2 Flux from Land Use, Land-Use 

Change, and Forestry (Sinks)* (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Net Emissions (Sources and Sinks) 5,410.6 5,718.7 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5 

* The net CO2 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in net emissions total.

Note: Totals may not sum due to independent rounding. Parentheses indicate negative values or sequestration.
Trends in Greenhouse Gas Emissions 2-9

generation sector consists of privately and publicly owned 

establishments that generate, transmit, distribute, or sell 

electricity primarily for use by the public and that meet 

EIA’s definition of an electric utility (EIA does not include 

non-utility power producers in this sector). EIA statistics 

for the industrial sector include fossil fuel consumption 

that occurs in the fields of manufacturing, agriculture, 

mining, and construction. EIA’s fuel consumption data 

for the transportation sector consists of all vehicles whose 

primary purpose is transporting people and/or goods from 

one physical location to another. EIA’s fuel consumption 

data for the industrial sector consists of all facilities and 

equipment used for producing, processing, or assembling 

goods (EIA includes generators that produce electricity 

and/or useful thermal output primarily to support on-site 

industrial activities in this sector). EIA’s fuel consumption 

data for the residential sector consists of living quarters for 

private households. EIA’s fuel consumption data for the 

commercial sector consists of service-providing facilities 

and equipment from private and public organizations and 

businesses (EIA includes generators that produce electricity 

and/or useful thermal output primarily to support the 

activities at commercial establishments in this sector). Table 

2-5, Figure 2-7, and Figure 2-8 summarize CO2 emissions 

from fossil fuel combustion by end-use sector.

The main driver of emissions in the energy sector is 

CO2 from fossil fuel combustion. The transportation enduse sector accounted for 1,861.0 Tg CO2 Eq. in 2006, or 

approximately 33 percent of total CO2 emissions from fossil 

fuel combustion, the largest share of any end-use economic 

sector.3 The industrial end-use sector accounted for 28 percent 

of CO2 emissions from fossil fuel combustion. The residential 

and commercial end-use sectors accounted for an average 20 

and 18 percent, respectively, of CO2 emissions from fossil 

fuel combustion. Both end-use sectors were heavily reliant 

on electricity for meeting energy needs, with electricity 

consumption for lighting, heating, air conditioning, and 

operating appliances contributing to about 72 and 79 percent 

of emissions from the residential and commercial end-use 

sectors, respectively. Significant trends in emissions from 

energy source categories over the sixteen-year period from 

1990 through 2006 included the following:

3Note that electricity generation is the largest emitter of CO2 when electricity 

is not distributed among end-use sectors.

Figure 2-6

2006 U.S. Fossil Carbon Flows (Tg CO2 Eq.)

Apparent

Consumption

6,266

Atmospheric

Emissions

5,997

Coal

2,219

Petroleum

840

Petroleum

1,858

NG 225

Coal 96

Other 255

Natural Gas Liquids,

Liquefied Refinery Gas,

& Other Liquids

147

Natural Gas

1,032

Combustion

Emissions

2,065

International

Bunkers

129

Non-Energy

Use Exports

98 Stock

Changes

111

Balancing

Item

29

Fossil Fuel

Energy Exports

329

Industrial

Processes

93

NEU Emissions 

9

Non-Energy Use 

Carbon Sequestered

240

Fossil Fuel

Combustion Residual

(Not Oxidized Fraction)

53

Coal Emissions

2,074

Domestic

Fossil Fuel

Production

4,238

Fossil Fuel

Energy

Imports

2,435

Non-Energy

Use Imports

67

Fossil Fuel

Consumption

U.S.

Territories

55

Non-Energy

Use U.S.

Territories

8

NEU Emissions 8

NEU Emissions 121

Combustion

Emissions

2,417

Petroleum 

Emissions

2,538

Natural Gas 

Emissions

1,163

Combustion

Emissions 1,155

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
2-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

•	 Total CO2 emissions from fossil fuel combustion 

increased from 4,724.1 Tg CO2 Eq. to 5,637.9 Tg CO2

Eq.—a 19.3 percent total increase over the sixteen-year 

period. From 2005 to 2006, these emissions decreased 

by 93.1 Tg CO2 Eq. (1.6 percent).

•	 CO2 emissions from non-energy use of fossil fuels have 

increased 20.8 Tg CO2 Eq. (18 percent) from 1990 

through 2006. Emissions from non-energy uses of fossil 

fuels were 138.0 Tg CO2 Eq. in 2006, which constituted 

2.4 percent of overall fossil fuel CO2 emissions and 2.3 

percent of total national CO2 emissions, approximately 

the same proportion as in 1990.

•	 CH4 emissions from natural gas systems were 102.4 Tg 

CO2 Eq. in 2006; emissions have declined by 22.3 Tg CO2

Eq. (18 percent) since 1990. This decline has been due to 

improvements in technology and management practices, 

as well as some replacement of old equipment.

•	 CH4 emissions from coal mining were 58.5 Tg CO2

Eq. This decline of 25.6 Tg CO2 Eq. (30 percent) 

from 1990 results from the mining of less gassy coal 

from underground mines and the increased use of CH4

collected from degasification systems.

•	 In 2006, N2O emissions from mobile combustion were 

33.1 Tg CO2 Eq. (approximately 9 percent of U.S. N2O 

emissions). From 1990 to 2006, N2O emissions from 

mobile combustion decreased by 24 percent. However, 

from 1990 to 1998 emissions increased by 26 percent, 

due to control technologies that reduced NOx emissions 

Table 2-4: Emissions from Energy (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 4,886.4 5,215.5 5,765.7 5,686.4 5,749.1 5,796.6 5,878.8 5,920.5 5,825.6

Fossil Fuel Combustion 4,724.1 5,032.4 5,577.1 5,507.4 5,564.8 5,617.0 5,681.4 5,731.0 5,637.9

Electricity Generation 1,809.6 1,939.3 2,283.1 2,314.9 2,380.2 2,328.2 2,283.1 2,314.9 2,380.2 

Transportation 1,473.5 1,590.2 1,801.5 1,849.3 1,862.6 1,848.7 1,801.5 1,849.3 1,862.6 

Industrial 849.9 880.6 858.8 861.0 850.9 866.1 858.8 861.0 850.9 

Residential 344.4 359.9 385.0 370.8 360.9 328.7 385.0 370.8 360.9 

Commercial 218.5 227.5 237.6 231.9 223.2 211.4 237.6 231.9 223.2 

U.S. Territories 28.3 35.0 51.0 53.5 53.2 54.9 51.0 53.5 53.2 

Non-Energy Use of Fuels 117.2 133.2 141.4 131.9 135.9 131.8 148.9 139.1 138.0

Natural Gas Systems 33.7 33.8 29.4 28.8 29.6 28.4 28.1 29.5 28.5

Municipal Solid Waste Combustion 10.9 15.7 17.5 18.0 18.5 19.1 20.1 20.7 20.9

Petroleum Systems 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3

Biomass—Wood* 215.2 229.1 218.1 193.5 192.8 193.8 205.1 204.8 204.4

International Bunker Fuels* 113.7 100.6 101.1 97.6 89.1 103.6 119.0 122.6 127.1

Biomass—Ethanol* 4.2 7.7 9.2 9.7 11.5 15.7 19.7 22.6 30.3

CH4 260.7 246.8 234.5 232.0 226.9 224.6 217.4 202.3 203.3

Natural Gas Systems 124.7 128.1 126.5 125.3 124.9 123.3 114.0 102.5 102.4

Coal Mining 84.1 67.1 60.4 60.3 56.8 56.9 59.8 57.1 58.5

Petroleum Systems 33.9 32.0 30.3 30.2 29.9 29.2 28.7 28.3 28.4

Stationary Combustion 7.4 7.2 6.6 6.2 6.2 6.4 6.5 6.5 6.2

Abandoned Underground Coal Mines 6.0 8.2 7.4 6.7 6.2 6.0 5.8 5.6 5.4

Mobile Combustion 4.7 4.3 3.4 3.3 3.0 2.7 2.6 2.5 2.4

International Bunker Fuels* 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2

N2O 56.8 67.3 67.5 64.4 60.4 57.1 54.7 51.5 48.0

Mobile Combustion 43.5 53.4 52.5 49.9 45.9 42.3 39.7 36.3 33.1

Stationary Combustion 12.8 13.4 14.6 14.1 14.0 14.3 14.6 14.8 14.5

Municipal Solid Waste Combustion 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4

International Bunker Fuels* 1.0 0.9 0.9 0.9 0.8 0.9 1.1 1.1 1.1

Total 5,203.9 5,529.6 6,067.8 5,982.8 6,036.3 6,078.3 6,150.9 6,174.4 6,076.9

* These values are presented for informational purposes only and are not included in totals or are already accounted for in other source categories.

Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-11

while increasing N2O emissions. Since 1998, newer 

control technologies have led to a steady decline in N2O 

from this source.

•	 CO2 emissions from municipal solid waste combustion 

(20.9 Tg CO2 Eq. in 2006) increased by 10.0 Tg CO2

Eq. (91 percent) from 1990 through 2006, as the volume 

of plastics and other fossil carbon-containing materials 

in municipal solid waste grew.

Industrial Processes

Emissions are produced as a byproduct of many nonenergy-related industrial process activities. For example, 

industrial processes can chemically transform raw materials, 

which often release waste gases such as CO2, CH4, and N2O. 

These processes include iron and steel production, cement 

production, ammonia production and urea consumption, 

lime production, limestone and dolomite use (e.g., flux 

stone, flue gas desulfurization, and glass manufacturing), 

soda ash production and use, titanium dioxide production,

Figure 2-7

2006 CO2 Emissions from Fossil Fuel 

Combustion by Sector and Fuel Type

Note: Electricity generation also includes emissions of less than 0.5 Tg CO2 Eq. from geothermal-based 

electricity generation.

Natural Gas

Petroleum

Coal

0

500

1,000

1,500

2,000

2,500

Relative Contribution

by Fuel Type

Tg CO2 Eq.

U.S. 

Territories

Commercial Residential Industrial Transportation Electricity

Generation

Figure 2-8

2006 End-Use Sector Emissions of CO2 from 

Fossil Fuel Combustion

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

U.S. Transportation

Territories

Commercial Residential Industrial

From Electricity

Consumption

From Direct Fossil

Fuel Combustion

Tg CO2 Eq.

Table 2-5: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Transportation 1,488.1 1,602.5 1,801.6 1,779.2 1,832.3 1,811.8 1,860.9 1,874.5 1,861.0

Combustion 1,485.1 1,599.4 1,798.2 1,775.6 1,828.9 1,807.6 1,856.4 1,869.8 1,856.0

Electricity 3.0 3.0 3.4 3.6 3.4 4.2 4.5 4.7 4.9

Industrial 1,527.5 1,589.5 1,645.1 1,583.9 1,572.5 1,592.1 1,596.8 1,579.6 1,567.1

Combustion 844.9 876.5 860.3 852.5 854.8 856.0 857.7 847.3 862.2

Electricity 682.5 713.1 784.7 731.4 717.7 736.1 739.0 732.3 704.9

Residential 929.5 995.5 1,129.7 1,121.8 1,145.6 1,178.3 1,173.1 1,206.4 1,151.9

Combustion 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5

Electricity 589.4 639.0 757.6 758.1 785.1 795.4 804.9 847.9 825.4

Commercial 750.8 810.0 964.6 973.5 970.3 983.8 997.1 1,017.3 1,003.0

Combustion 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1

Electricity 534.7 584.2 736.6 751.1 747.5 747.3 766.5 795.4 792.9

U.S. Territories 28.3 35.0 36.2 49.0 44.0 51.0 53.5 53.2 54.9

Total 4,724.1 5,032.4 5,577.1 5,507.4 5,564.8 5,617.0 5,681.4 5,731.0 5,637.9

Electricity Generation 1,809.6 1,939.3 2,282.3 2,244.3 2,253.7 2,283.1 2,314.9 2,380.2 2,328.2

Note: Totals may not sum due to independent rounding. Combustion-related emissions from electricity generation are allocated based on aggregate 

national electricity consumption by each end-use sector.
2-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

phosphoric acid production, ferroalloy production, CO2

consumption, silicon carbide production and consumption, 

aluminum production, petrochemical production, nitric acid 

production, adipic acid production, lead production, and zinc 

production (see Figure 2-9). Additionally, emissions from 

industrial processes release HFCs, PFCs and SF6. Table 2-6 

presents greenhouse gas emissions from industrial processes 

by source category.

Overall, emissions from industrial processes increased 

by 7.0 percent from 1990 to 2006 despite decreases in 

emissions from several industrial processes, such as iron 

and steel, aluminum production, HCFC-22 production, 

and electrical transmission and distribution. The increase 

in overall emissions was driven by a rise in the emissions 

originating from cement production and, primarily, the 

emissions from the use of substitutes for ozone depleting 

substances. Significant trends in emissions from industrial 

processes source categories over the sixteen-year period from 

1990 through 2006 included the following:

•	 HFC emissions from ODS substitutes have been 

increasing from small amounts in 1990 to 110.4 Tg CO2

Eq. in 2006. This increase results from efforts to phase 

out CFCs and other ODSs in the United States. In the 

short term, this trend is expected to continue, and will 

likely accelerate over the next decade as HCFCs—which 

are interim substitutes in many applications—are 

phased out under the provisions of the Copenhagen 

Amendments to the Montreal Protocol.

•	 CO2 and CH4 emissions from iron and steel production 

increased by 5.2 percent to 50.1 Tg CO2 Eq. in 2006, but 

have declined overall by 37.5 Tg CO2 Eq. (42.8 percent) 

from 1990 through 2006, due to restructuring of the 

industry, technological improvements, and increased 

scrap utilization.

•	 PFC emissions from aluminum production decreased by 

87 percent (16.1 Tg CO2 Eq.) from 1990 to 2006, due 

to both industry emission reduction efforts and lower 

domestic aluminum production.

•	 N2O emissions from adipic acid production were 5.9 

Tg CO2 Eq. in 2006, and have decreased significantly 

in recent years from the widespread installation of 

pollution control measures. Emissions from adipic acid 

production have decreased 61 percent since 1990, and 

emissions from adipic acid production have fluctuated 

by less than 1 Tg CO2 Eq. annually since 1998.

•	 CO2 emissions from ammonia production and urea 

consumption (12.4 Tg CO2 Eq. in 2006) have decreased 

by 4.5 Tg CO2 Eq. (27 percent) since 1990, due to a 

decrease in domestic ammonia production. This decrease 

in ammonia production can be attributed to market 

fluctuations and high natural gas prices.

Solvent and Other Product Use

Greenhouse gas emissions are produced as a byproduct 

of various solvent and other product uses. In the United 

States, N2O Emissions from Product Uses, the only source of 

greenhouse gas emissions from this sector, accounted for 4.4 

Tg CO2 Eq., or less than 0.1 percent of total U.S. emissions 

in 2006 (see Table 2-7).

•	 In 2006, N2O emissions from product uses constituted 

1 percent of U.S. N2O emissions. From 1990 to 2006, 

emissions from this source category decreased by less 

than 1 percent, though slight increases occurred in 

intermediate years.

0 25 50 75 100 125

Industrial Processes

as a Portion of

all Emissions

4.5%

Tg CO2 Eq.

Silicon Carbide Production and Consumption <0.5

Lead Production <0.5

Zinc Production

Phosphoric Acid Production

Ferroalloy Production

Carbon Dioxide Consumption

Titanium Dioxide Production

Magnesium Production and Processing

Petrochemical Production

Soda Ash Production and Consumption

Semiconductor Manufacture

Adipic Acid Production

Aluminum Production

Limestone and Dolomite Use

Ammonia Production and Urea Consumption

Electrical Transmission and Distribution

HCFC-22 Production

Nitric Acid Production

Lime Production

Cement Production

Iron and Steel Production

Substitution of Ozone Depleting Substances

2006 Industrial Processes Chapter 

Greenhouse Gas Emission Sources

Figure 2-9
Trends in Greenhouse Gas Emissions 2-13

Table 2-6: Emissions from Industrial Processes (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 175.0 171.6 166.5 151.9 151.0 147.8 151.8 145.9 149.5

Iron and Steel Production 86.2 74.7 66.6 59.2 55.9 54.7 52.8 46.6 49.1

Cement Production 33.3 36.8 41.2 41.4 42.9 43.1 45.6 45.9 45.7

Lime Production 12.0 14.0 14.9 14.3 13.7 14.5 15.2 15.1 15.8

Ammonia Production & Urea Consumption 16.9 17.8 16.4 13.3 14.2 12.5 13.2 12.8 12.4

Limestone and Dolomite Use 5.5 7.4 6.0 5.7 5.9 4.8 6.7 7.4 8.6

Soda Ash Production and Consumption 4.1 4.3 4.2 4.1 4.1 4.1 4.2 4.2 4.2

Aluminum Production 6.8 5.7 6.1 4.4 4.5 4.5 4.2 4.2 3.9

Petrochemical Production 2.2 2.8 3.0 2.8 2.9 2.8 2.9 2.8 2.6

Titanium Dioxide Production 1.2 1.5 1.8 1.7 1.8 1.8 2.1 1.8 1.9

Carbon Dioxide Consumption 1.4 1.4 1.4 0.8 1.0 1.3 1.2 1.3 1.6

Ferroalloy Production 2.2 2.0 1.9 1.5 1.3 1.3 1.4 1.4 1.5

Phosphoric Acid Production 1.5 1.5 1.4 1.3 1.3 1.4 1.4 1.4 1.2

Zinc Production 0.9 1.0 1.1 1.0 0.9 0.5 0.5 0.5 0.5

Lead Production 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3

Silicon Carbide Production and Consumption 0.4 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2

 CH4 2.2 2.4 2.5 2.2 2.1 2.1 2.2 2.0 2.0

Petrochemical Production 0.9 1.1 1.2 1.1 1.1 1.1 1.2 1.1 1.0

Iron and Steel Production 1.3 1.3 1.2 1.1 1.0 1.0 1.0 1.0 0.9

Ferroalloy Production + + + + + + + + + 

Silicon Carbide Production and Consumption + + + + + + + + + 

N2O 32.3 36.2 24.8 20.2 22.4 21.7 21.2 21.7 21.6

Nitric Acid Production 17.0 18.9 18.6 15.1 16.4 15.4 15.2 15.8 15.6

Adipic Acid Production 15.3 17.3 6.2 5.1 6.1 6.3 5.9 5.9 5.9

HFCs 36.9 61.8 100.1 97.9 106.3 104.5 116.6 121.4 124.5 

Substitution of Ozone Depleting Substancesa 0.3 28.5 71.2 78.0 85.0 92.0 99.1 105.4 110.4 

HCFC-22 Production 36.4 33.0 28.6 19.7 21.1 12.3 17.2 15.8 13.8 

Semiconductor Manufacture 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.3 

PFCs 20.8 15.6 13.5 7.0 8.7 7.1 6.1 6.2 6.0 

Semiconductor Manufacture 2.2 3.8 4.9 3.5 3.5 3.3 3.3 3.2 3.6 

Aluminum Production 18.5 11.8 8.6 3.5 5.2 3.8 2.8 3.0 2.5 

SF6 32.7 28.0 19.1 18.7 18.0 18.1 18.0 18.2 17.3 

Electrical Transmission and Distribution 26.7 21.5 15.1 15.0 14.4 13.8 13.9 14.0 13.2 

Magnesium Production and Processing 5.4 5.6 3.0 2.9 2.9 3.4 3.2 3.3 3.2 

Semiconductor Manufacture 0.5 0.9 1.1 0.7 0.7 0.8 0.8 1.0 1.0 

Total 299.9 315.7 326.5 297.9 308.6 301.2 315.9 315.5 320.9 

+ Does not exceed 0.05 Tg CO2 Eq. a Small amounts of PFC emissions also result from this source.

Note: Totals may not sum due to independent rounding.

Table 2-7: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

N2O 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4

N2O from Product Uses 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4

Total 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4
2-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Agriculture

Agricultural activities contribute directly to emissions of 

greenhouse gases through a variety of processes, including 

the following source categories: enteric fermentation in 

domestic livestock, livestock manure management, rice 

cultivation, agricultural soil management, and field burning 

of agricultural residues (see Figure 2-10).

In 2006, agricultural activities were responsible for 

emissions of 454.1 Tg CO2 Eq., or 6.4 percent of total U.S. 

greenhouse gas emissions (see Table 2-8). CH4 and N2O 

were the primary greenhouse gases emitted by agricultural 

activities. CH4 emissions from enteric fermentation and 

manure management represented about 23 percent and 7 

percent of total CH4 emissions from anthropogenic activities, 

respectively, in 2006. Agricultural soil management activities, 

such as fertilizer application and other cropping practices, 

were the largest source of U.S. N2O emissions in 2006, 

accounting for 72 percent.

Some significant trends in U.S. emissions from 

Agriculture include the following:

•	 Agricultural soils produced approximately 72 percent of 

N2O emissions in the United States in 2006. Estimated 

emissions from this source in 2006 were 265.0 Tg CO2 Eq. 

Annual N2O emissions from agricultural soils fluctuated 

between 1990 and 2006, although overall emissions were 

1.6 percent lower in 2006 than in 1990.

•	 Enteric fermentation was the largest source of CH4

emissions in 2006, at 126.2 Tg CO2 Eq. Although 

emissions from enteric fermentation have decreased by 

less than 1 percent between 1990 and 2006, emissions 

increased about 2 percent between 1990 and 1994 

and decreased 8 percent 1995 to 2004, mainly due to 

decreasing populations of both beef and dairy cattle 

and improved feed quality for feedlot cattle. The last 

two years have shown an increase in emissions. During 

this timeframe, populations of sheep have decreased 

45 percent since 1990 while horse populations have 

increased over 80 percent, mostly over the last 5 years. 

Goat and swine populations have increased 1 percent 

and 14 percent, respectively, during this timeframe.

•	 Overall, emissions from manure management increased 

29 percent between 1990 and 2006. This encompassed 

an increase of 34 percent for CH4, from 31.0 Tg 

CO2 Eq. in 1990 to 41.4 Tg CO2 Eq. in 2006; and an 

increase of 18 percent for N2O, from 12.1 Tg CO2 Eq. 

in 1990 to 14.3 Tg CO2 Eq. in 2006. The majority of 

this increase was from swine and dairy cow manure, 

Figure 2-10

2006 Agriculture Chapter Greenhouse Gas 

Emission Sources

0 50 200

Rice Cultivation

Manure Management

Field Burning of

Agricultural Residues

Enteric Fermentation

Agricultural Soil Management

Tg CO2 Eq.

Agriculture

as a Portion of

all Emissions

100 150

265.0

6.4%

Table 2-8: Emissions from Agriculture (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 165.7 175.8 171.7 172.2 172.6 173.0 170.9 174.0 174.4 

Enteric Fermentation 126.9 132.3 124.6 123.6 123.8 124.6 122.4 124.5 126.2 

Manure Management 31.0 35.2 38.8 40.2 41.3 40.7 40.1 41.8 41.4 

Rice Cultivation 7.1 7.6 7.5 7.6 6.8 6.9 7.6 6.8 5.9 

Field Burning of Agricultural Residues 0.7 0.7 0.8 0.8 0.7 0.8 0.9 0.9 0.8 

N2O 281.8 278.0 276.3 291.5 276.4 261.3 261.2 279.6 279.8 

Agricultural Soil Management 269.4 264.8 262.1 277.0 262.0 247.3 246.9 265.2 265.0 

Manure Management 12.1 12.8 13.7 14.0 14.0 13.6 13.8 13.9 14.3 

Field Burning of Agricultural Residues 0.4 0.4 0.5 0.5 0.4 0.4 0.5 0.5 0.5 

Total 447.5 453.8 447.9 463.7 449.0 434.3 432.1 453.6 454.1 

Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-15

since the general trend in manure management is one 

of increasing use of liquid systems, which tends to 

produce greater CH4 emissions.

Land Use, Land-Use Change, and Forestry

When humans alter the terrestrial biosphere through land 

use, changes in land use, and land management practices, they 

also alter the background carbon fluxes between biomass, soils, 

and the atmosphere. Forest management practices, tree planting 

in urban areas, the management of agricultural soils, and the 

landfilling of yard trimmings and food scraps have resulted in 

an uptake (sequestration) of carbon in the United States, which 

offset about 13 percent of total U.S. greenhouse gas emissions 

in 2006. Forests (including vegetation, soils, and harvested 

wood) accounted for approximately 84 percent of total 2006 

net CO2 flux, urban trees accounted for 11 percent, mineral 

and organic soil carbon stock changes accounted for 5 percent, 

and landfilled yard trimmings and food scraps accounted for 1 

percent of the total net flux in 2006. The net forest sequestration 

is a result of net forest growth, increasing forest area, and a 

net accumulation of carbon stocks in harvested wood pools. 

The net sequestration in urban forests is a result of net tree 

growth and increased urban forest size. In agricultural soils, 

mineral and organic soils sequester approximately 70 percent 

more C than is emitted through these soils, liming, and urea 

fertilization, combined. The mineral soil C sequestration is 

largely due to the conversion of cropland to hay production 

fields, the limited use of bare-summer fallow areas in semi-arid 

areas, and an increase in the adoption of conservation tillage 

practices. The landfilled yard trimmings and food scraps net 

sequestration is due to the long-term accumulation of yard 

trimming carbon and food scraps in landfills.

Land use, land-use change, and forestry activities in 

2006 resulted in a net C flux of -883.7 Tg CO2 Eq. (Table 

2-9). This represents an offset of approximately 14.8 

percent of total U.S. CO2 emissions, or 12.5 percent of 

total greenhouse gas emissions in 2006. Between 1990 and 

2006, total land use, land-use change, and forestry net C flux 

resulted in a 20 percent increase in CO2 sequestration.

Land use, land-use change, and forestry source categories 

also resulted in emissions of CO2, CH4, and N2O that are not 

included in the net CO2 flux estimates presented in Table 

2-9. The application of crushed limestone and dolomite to 

managed land (i.e., soil liming) and urea fertilization resulted 

in CO2 emissions of 8.0 Tg CO2 Eq. in 2006, and increase 

of 13 percent relative to 1990. The application of synthetic 

fertilizers to forest and settlement soils in 2006 resulted in 

direct N2O emissions of 1.8 Tg CO2 Eq. Direct N2O emissions 

from fertilizer application increased by approximately 74 

percent between 1990 and 2006. Emissions of CH4 and 

N2O from forest fires fluctuate widely from year to year, but 

overall increased by 449 percent between 1990 and 2006 

(Table 2-10).

Other significant trends from 1990 to 2006 in land use, 

land-use change, and forestry emissions include:

•	 Net C sequestration by forest land has increased 20 

percent. This is primarily due to increased forest 

management and the effects of previous reforestation. 

The increase in intensive forest management resulted in 

higher growth rates and higher biomass density. The tree 

planting and conservation efforts of the 1970s and 1980s 

continue to have a significant impact on sequestration 

rates. Finally, the forested area in the United States 

Table 2-9: Net CO2 Flux from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)

Sink Category 1990 1995 2000 2001 2002 2003 2004 2005 2006

Forest Land Remaining Forest Land (621.7) (659.9) (550.7) (623.4) (697.3) (730.9) (741.4) (743.6) (745.1)

Cropland Remaining Cropland (30.1) (39.4) (38.4) (40.0) (40.3) (40.5) (40.9) (41.0) (41.8)

Land Converted to Cropland 14.7 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 

Grassland Remaining Grassland (1.9) 16.6 16.4 16.4 16.4 16.4 16.3 16.3 16.2 

Land Converted to Grassland (14.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3)

Settlements Remaining Settlements (60.6) (71.5) (82.4) (84.6) (86.8) (88.9) (91.1) (93.3) (95.5)

Other (Landfilled Yard Trimmings and 

Food Scraps) (23.9) (14.1) (11.5) (11.6) (11.8) (10.0) (9.6) (10.0) (10.5)

Total (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
2-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

increased over the past 16 years, although only at an 

average rate of 0.1 percent per year.

•	 Net sequestration of C by urban trees has increased 

by 57 percent over this sixteen-year period. This is 

primarily due to an increase in urbanized land area in 

the United States.

•	 Annual C sequestration in landfilled yard trimmings and 

food scraps has decreased by 56 percent. This is due in 

part to a decrease in the amount of yard trimmings and 

food scraps generated. In addition, the proportion of 

yard trimmings and food scraps landfilled has decreased, 

as there has been a significant rise in the number of 

municipal composting facilities in the United States.

Waste

Waste management and treatment activities are sources 

of greenhouse gas emissions (see Figure 2-11). In 2006, 

landfills were the second largest source of anthropogenic 

CH4 emissions, accounting for 23 percent of total U.S. CH4

emissions.4 Additionally, wastewater treatment accounts 

for 4 percent of U.S. CH4 emissions, and 2 percent of N2O 

emissions. Emissions of CH4 and N2O from composting grew 

from 1990 to 2006, and resulted in emissions of 3.3 Tg CO2

Eq. A summary of greenhouse gas emissions from the Waste 

chapter is presented in Table 2-11.

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.

Overall, in 2006, waste activities generated emissions 

of 161.0 Tg CO2 Eq., or 2.3 percent of total U.S. greenhouse 

gas emissions.

Some significant trends in U.S. emissions from Waste 

include the following:

•	 From 1990 to 2006, net CH4 emissions from landfills 

decreased by 23.9 Tg CO2 Eq. (16 percent), with small 

increases occurring in interim years. This downward 

trend in overall emissions is the result of increases in 

the amount of landfill gas collected and combusted,5

which has more than offset the additional CH4 emissions 

5The CO2 produced from combusted landfill CH4 at landfills is not counted 

in national inventories as it is considered part of the natural C cycle of 

decomposition.

Figure 2-11

2006 Waste Chapter Greenhouse Gas Emission Sources

Tg CO2 Eq.

0 50 100 150

Waste as a Portion

of all Emissions 

2.3% Composting

Landfills

Wastewater

Treatment

Table 2-10: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)

Source Category 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0 

Cropland Remaining Cropland: Liming of 

Agricultural Soils & Urea Fertilization 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0 

CH4 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 

Forest Land Remaining Forest Land: 

Forest Fires 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 

N2O 1.5 1.8 3.5 2.7 3.5 2.7 2.6 3.1 4.3 

Forest Land Remaining Forest Land:

Forest Fires 0.5 0.5 1.9 1.0 1.7 0.9 0.7 1.2 2.5 

Forest Land Remaining Forest Land: 

Forest Soils 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Settlements Remaining Settlements:

Settlement Soils 1.0 1.2 1.2 1.4 1.5 1.5 1.6 1.5 1.5 

Total 13.1 13.6 30.0 20.0 28.4 19.7 17.1 23.2 36.9 

Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-17

resulting from an increase in the amount of municipal 

solid waste landfilled.

•	 From 1990 to 2006, CH4 and N2O emissions from 

wastewater treatment increased by 0.8 Tg CO2 Eq. (4 

percent) and 1.8 Tg CO2 Eq. (29 percent), respectively.

•	 CH4 and N2O emissions from composting each 

increased by less than 0.1 Tg CO2 Eq. (1 percent) from 

2005 to 2006. Emissions from composting have been 

continually increasing since 1990, from 0.7 Tg CO2

Eq. to 3.3 Tg CO2 Eq. in 2006, a four-fold increase 

over the time series.

2.2. Emissions by Economic Sector

Throughout this report, emission estimates are grouped 

into six sectors (i.e., chapters) defined by the IPCC and 

detailed above: Energy; Industrial Processes; Solvent and 

Other Product Use; Agriculture; Land Use, Land-Use 

Change, and Forestry; and Waste. While it is important to 

use this characterization for consistency with UNFCCC 

reporting guidelines, it is also useful to allocate emissions 

into more commonly used sectoral categories. This section 

reports emissions by the following U.S. economic sectors: 

residential, commercial, industry, transportation, electricity 

generation, and agriculture, as well as U.S. territories.

Using this categorization, emissions from electricity 

generation accounted for the largest portion (34 percent) 

of U.S. greenhouse gas emissions in 2006. Transportation 

activities, in aggregate, accounted for the second largest 

portion (28 percent). Emissions from industry accounted for 

about 19 percent of U.S. greenhouse gas emissions in 2006. 

In contrast to electricity generation and transportation, 

emissions from industry have in general declined over 

the past decade. The long-term decline in these emissions 

has been due to structural changes in the U.S. economy 

(i.e., shifts from a manufacturing-based to a service-based 

economy), fuel switching, and efficiency improvements. 

The remaining 19 percent of U.S. greenhouse gas emissions 

were contributed by the residential, agriculture, and 

commercial sectors, plus emissions from U.S. territories. 

The residential sector accounted for 5 percent, and primarily 

consisted of CO2 emissions from fossil fuel combustion. 

Activities related to agriculture accounted for roughly 8 

percent of U.S. emissions; unlike other economic sectors, 

agricultural sector emissions were dominated by N2O 

emissions from agricultural soil management and CH4

emissions from enteric fermentation, rather than CO2 from 

fossil fuel combustion. The commercial sector accounted 

for roughly 6 percent of emissions, while U.S. territories 

accounted for about 1 percent.

CO2 was also emitted and sequestered by a variety 

of activities related to forest management practices, tree 

planting in urban areas, the management of agricultural soils, 

and landfilling of yard trimmings.

Table 2-12 presents a detailed breakdown of emissions 

from each of these economic sectors by source category, as 

they are defined in this report. Figure 2-12 shows the trend 

in emissions by sector from 1990 to 2006.

Table 2-11: Emissions from Waste (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 172.9 169.1 146.7 143.0 145.5 151.0 148.1 149.0 151.1

Landfills 149.6 144.0 120.8 117.6 120.1 125.6 122.6 123.7 125.7

Wastewater Treatment 23.0 24.3 24.6 24.2 24.1 23.9 24.0 23.8 23.9

Composting 0.3 0.7 1.3 1.3 1.3 1.5 1.6 1.6 1.6

N2O 6.6 7.7 8.9 9.2 9.0 9.3 9.6 9.7 9.9

Wastewater Treatment 6.3 6.9 7.6 7.8 7.6 7.7 7.8 8.0 8.1

Composting 0.4 0.8 1.4 1.4 1.4 1.6 1.7 1.7 1.8

Total 179.6 176.8 155.6 152.1 154.5 160.3 157.7 158.7 161.0

Note: Totals may not sum due to independent rounding.
2-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors 

(Tg CO2 Eq. and Percent of Total in 2006)

Sector/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 Percenta

Electricity Generation 1,859.1 1,989.7 2,328.9 2,290.9 2,300.4 2,329.4 2,363.4 2,430.0 2,377.8 33.7%

CO2 from Fossil Fuel Combustion 1,809.6 1,939.3 2,282.3 2,244.3 2,253.7 2,283.1 2,314.9 2,380.2 2,328.2 33.0%

Municipal Solid Waste Combustion 11.4 16.2 17.9 18.4 18.9 19.5 20.5 21.1 21.3 0.3%

Electrical Transmission 

and Distribution 26.7 21.5 15.1 15.0 14.4 13.8 13.9 14.0 13.2 0.2%

Stationary Combustion 8.6 9.1 10.6 10.4 10.4 10.7 10.8 11.0 10.8 0.2%

Limestone and Dolomite Use 2.8 3.7 3.0 2.9 2.9 2.4 3.4 3.7 4.3 0.1%

Transportation 1,544.1 1,685.8 1,917.5 1,895.8 1,948.5 1,925.9 1,975.4 1,987.2 1,969.5 27.9%

CO2 from Fossil Fuel Combustion 1,485.1 1,599.4 1,798.2 1,775.6 1,828.9 1,807.6 1,856.4 1,869.8 1,856.0 26.3%

Substitution of Ozone Depleting 

Substances + 18.6 52.6 57.2 61.1 64.4 67.8 69.7 69.5 1.0%

Mobile Combustion 47.2 56.5 54.7 51.9 47.5 43.8 40.9 37.5 34.1 0.5%

Non-Energy Use of Fuels 11.9 11.3 12.1 11.1 10.9 10.1 10.2 10.2 9.9 0.1%

Industry 1,460.3 1,478.0 1,432.9 1,384.3 1,384.9 1,375.5 1,388.9 1,354.3 1,371.5 19.4%

CO2 from Fossil Fuel Combustion 798.2 819.1 809.4 801.8 801.9 811.0 806.6 801.8 818.6 11.6%

Natural Gas Systems 158.4 161.9 155.9 154.1 154.5 151.8 142.1 132.0 130.9 1.9%

Non-Energy Use of Fuels 99.6 115.9 118.4 115.5 115.8 113.2 131.4 121.8 120.8 1.7%

Coal Mining 84.1 67.1 60.4 60.3 56.8 56.9 59.8 57.1 58.5 0.8%

Iron and Steel Production 87.5 76.0 67.8 60.3 57.0 55.8 53.8 47.6 50.1 0.7%

Cement Production 33.3 36.8 41.2 41.4 42.9 43.1 45.6 45.9 45.7 0.6%

Petroleum Systems 34.2 32.3 30.6 30.5 30.2 29.5 29.0 28.6 28.7 0.4%

Lime Production 12.0 14.0 14.9 14.3 13.7 14.5 15.2 15.1 15.8 0.2%

Nitric Acid Production 17.0 18.9 18.6 15.1 16.4 15.4 15.2 15.8 15.6 0.2%

HCFC-22 Production 36.4 33.0 28.6 19.7 21.1 12.3 17.2 15.8 13.8 0.2%

Ammonia Production and 

Urea Consumption 16.9 17.8 16.4 13.3 14.2 12.5 13.2 12.8 12.4 0.2%

Aluminum Production 25.4 17.5 14.7 7.8 9.7 8.3 7.1 7.2 6.4 0.1%

Adipic Acid Production 15.3 17.3 6.2 5.1 6.1 6.3 5.9 5.9 5.9 0.1%

Substitution of Ozone 

Depleting Substances + 1.2 3.1 3.1 3.7 4.4 4.8 5.2 5.7 0.1%

Abandoned Underground Coal Mines 6.0 8.2 7.4 6.7 6.2 6.0 5.8 5.6 5.4 0.1%

Semiconductor Manufacture 2.9 5.0 6.3 4.5 4.3 4.3 4.3 4.4 4.8 0.1%

Stationary Combustion 4.7 5.0 4.9 4.6 4.4 4.3 4.6 4.5 4.6 0.1%

N2O Product Uses 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4 0.1%

Limestone and Dolomite Use 2.8 3.7 3.0 2.9 2.9 2.4 3.4 3.7 4.3 0.1%

Soda Ash Production 

and Consumption 4.1 4.3 4.2 4.1 4.1 4.1 4.2 4.2 4.2 0.1%

Petrochemical Production 3.1 3.8 4.2 3.9 4.0 3.9 4.1 3.9 3.6 0.1%

Magnesium Production 

and Processing 5.4 5.6 3.0 2.9 2.9 3.4 3.2 3.3 3.2 0.0%

Titanium Dioxide Production 1.2 1.5 1.8 1.7 1.8 1.8 2.1 1.8 1.9 0.0%

Carbon Dioxide Consumption 1.4 1.4 1.4 0.8 1.0 1.3 1.2 1.3 1.6 0.0%

Ferroalloy Production 2.2 2.0 1.9 1.5 1.4 1.3 1.4 1.4 1.5 0.0%

Phosphoric Acid Production 1.5 1.5 1.4 1.3 1.3 1.4 1.4 1.4 1.2 0.0%

Mobile Combustion 0.6 0.7 0.8 0.9 0.9 0.9 1.0 1.0 1.0 0.0%

Zinc Production 0.9 1.0 1.1 1.0 0.9 0.5 0.5 0.5 0.5 0.0%

Lead Production 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.0%

Silicon Carbide Production 

and Consumption 0.4 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.0%
Trends in Greenhouse Gas Emissions 2-19

(continued)

Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors 

(Tg CO2 Eq. and Percent of Total in 2006)

Sector/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 Percenta

Agriculture 506.8 524.1 528.0 533.4 529.3 498.0 499.2 521.3 533.6 7.6%

N2O from Agricultural Soil 

Management 269.4 264.8 262.1 277.0 262.0 247.3 246.9 265.2 265.0 3.8%

Enteric Fermentation 126.9 132.3 124.6 123.6 123.8 124.6 122.4 124.5 126.2 1.8%

Manure Management 43.0 48.0 52.5 54.2 55.2 54.3 53.9 55.7 55.7 0.8%

CO2 from Fossil Fuel Combustion 46.8 57.3 50.9 50.7 52.9 45.0 51.1 45.5 43.6 0.6%

CH4 and N2O from Forest Fires 4.9 5.2 20.9 10.4 18.0 9.6 7.6 13.6 27.0 0.4%

Rice Cultivation 7.1 7.6 7.5 7.6 6.8 6.9 7.6 6.8 5.9 0.1%

Liming of Agricultural Soils 4.7 4.4 4.3 4.4 5.0 4.6 3.9 4.3 4.4 0.1%

Urea Fertilization 2.4 2.7 3.2 3.4 3.6 3.7 3.7 3.5 3.6 0.1%

Field Burning of Agricultural 

Residues 1.1 1.0 1.3 1.2 1.1 1.2 1.4 1.4 1.3 0.0%

Mobile Combustion 0.4 0.5 0.4 0.4 0.5 0.4 0.4 0.4 0.4 0.0%

N2O from Forest Soils 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.0%

Stationary Combustion + + + + + + + + + 0.0%

Commercial 396.9 404.5 390.3 383.0 388.1 410.2 404.6 400.4 394.6 5.6%

CO2 from Fossil Fuel Combustion 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1 3.0%

Landfills 149.6 144.0 120.8 117.6 120.1 125.6 122.6 123.7 125.7 1.8%

Wastewater Treatment 23.0 24.3 24.6 24.2 24.1 23.9 24.0 23.8 23.9 0.3%

Substitution of Ozone Depleting

Substances + 0.7 5.5 7.4 9.6 12.1 15.0 18.5 22.4 0.3%

Human Sewage 6.3 6.9 7.6 7.8 7.6 7.7 7.8 8.0 8.1 0.1%

Composting 0.7 1.5 2.6 2.7 2.7 3.1 3.3 3.3 3.3 0.0%

Stationary Combustion 1.2 1.3 1.2 1.2 1.2 1.3 1.3 1.2 1.2 0.0%

Residential 346.9 370.9 387.7 379.3 376.6 399.6 385.5 376.0 344.8 4.9%

CO2 from Fossil Fuel Combustion 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5 4.6%

Substitution of Ozone Depleting

Substances 0.3 8.1 10.1 10.3 10.7 11.0 11.4 11.9 12.9 0.2%

Stationary Combustion 5.5 5.0 4.3 3.9 4.0 4.2 4.3 4.2 3.9 0.1%

Settlement Soil Fertilization 1.0 1.2 1.2 1.4 1.5 1.5 1.6 1.5 1.5 0.0%

U.S. Territories 34.1 41.1 47.3 54.5 53.3 59.7 61.0 60.5 62.4 0.9%

CO2 from Fossil Fuel Combustion 34.1 41.1 47.3 54.5 53.3 59.7 61.0 60.5 62.4 0.9%

Total Emissions 6,148.3 6,494.0 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2 100.0%

Sinks (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7) (12.5%)

CO2 Flux from Forests (621.7) (659.9) (550.7) (623.4) (697.3) (730.9) (741.4) (743.6) (745.1) (10.6%)

Urban Trees (60.6) (71.5) (82.4) (84.6) (86.8) (88.9) (91.1) (93.3) (95.5) (1.4%)

CO2 Flux from Agricultural Soil 

Carbon Stocks (31.5) (29.7) (29.0) (30.6) (30.9) (31.1) (31.5) (31.7) (32.6) (0.5%)

Landfilled Yard Trimmings 

and Food Scraps (23.9) (14.1) (11.5) (11.6) (11.8) (10.0) (9.6) (10.0) (10.5) (0.1%)

Net Emissions (Sources and Sinks) 5,410.6 5,718.7 6,359.0 6,171.1 6,154.4 6,137.3 6,204.3 6,251.3 6,170.5 87.5%

Note: Includes all emissions of CO2, CH4, N2O, HFCs, 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 CO2 Eq. or 0.05%. a Percent of total emissions for year 2006.
2-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Emissions with Electricity Distributed to 

Economic Sectors

It can also be useful to view greenhouse gas emissions 

from economic sectors with emissions related to electricity 

generation distributed into end-use categories (i.e., emissions 

from electricity generation are allocated to the economic 

sectors in which the electricity is consumed). The generation, 

transmission, and distribution of electricity, which is the 

largest economic sector in the United States, accounted for 

34 percent of total U.S. greenhouse gas emissions in 2006. 

Emissions increased by 28 percent since 1990, as electricity 

demand grew and fossil fuels remained the dominant 

energy source for generation. Electricity generation-related 

emissions decreased from 2005 to 2006 by 2 percent, 

primarily due to reduced CO2 emissions from fossil fuel 

combustion. The electricity generation sector in the United 

States is composed of traditional electric utilities as well as 

other entities, such as power marketers and non-utility power 

producers. The majority of electricity generated by these 

entities was through the combustion of coal in boilers to 

produce high-pressure steam that is passed through a turbine. 

Table 2-13 provides a detailed summary of emissions from 

electricity generation-related activities.

To distribute electricity emissions among economic 

end-use sectors, emissions from the source categories 

assigned to the electricity generation sector were allocated 

to the residential, commercial, industry, transportation, 

and agriculture economic sectors according to retail sales 

of electricity (EIA 2006c and Duffield 2006). These three 

source categories include CO2 from Fossil Fuel Combustion, 

CH4 and N2O from Stationary Combustion, and SF6 from 

Electrical Transmission and Distribution Systems.6

6 Emissions were not distributed to U.S. territories, since the electricity 

generation sector only includes emissions related to the generation of 

electricity in the 50 states and the District of Columbia.

Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (Tg CO2 Eq.)

Gas/Fuel Type or Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 1,823.3 1,958.6 2,302.8 2,265.1 2,275.1 2,304.5 2,338.4 2,404.6 2,353.4 

CO2 from Fossil Fuel Combustion 1,809.6 1,939.3 2,282.3 2,244.3 2,253.7 2,283.1 2,314.9 2,380.2 2,328.2 

Coal 1,531.3 1,648.7 1,909.6 1,852.3 1,868.3 1,906.2 1,917.6 1,958.4 1,932.4 

Natural Gas 176.2 229.5 280.9 289.6 306.0 278.3 296.8 319.1 339.6 

Petroleum 101.8 60.7 91.5 102.0 79.1 98.1 100.1 102.3 55.7 

Geothermal 0.4 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 

Municipal Solid Waste Combustion 10.9 15.7 17.5 18.0 18.5 19.1 20.1 20.7 20.9 

Limestone and Dolomite Use 2.8 3.7 3.0 2.9 2.9 2.4 3.4 3.7 4.3 

CH4 0.6 0.6 0.7 0.7 0.7 0.7 0.7 0.7 0.7 

Stationary Combustion* 0.6 0.6 0.7 0.7 0.7 0.7 0.7 0.7 0.7 

N2O 8.5 9.0 10.4 10.1 10.1 10.4 10.5 10.7 10.5 

Stationary Combustion* 8.1 8.6 10.0 9.7 9.7 10.0 10.0 10.3 10.1 

Municipal Solid Waste Combustion 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 

SF6 26.7 21.5 15.1 15.0 14.4 13.8 13.9 14.0 13.2 

Electrical Transmission and Distribution 26.7 21.5 15.1 15.0 14.4 13.8 13.9 14.0 13.2 

Total 1,859.1 1,989.7 2,328.9 2,290.9 2,300.4 2,329.4 2,363.4 2,430.0 2,377.8 

Note: Totals may not sum due to independent rounding.

* Includes only stationary combustion emissions related to the generation of electricity.

0

500

1,000

1,500

2,000

2,500

19901991199219931994199519961997199819992000200120022003200420052006

Residential

Agriculture

Electricity Generation

Tg CO2 Eq.

Industry

Transportation

Commercial

Figure 2-12

Emissions Allocated to Economic Sectors
Trends in Greenhouse Gas Emissions 2-21

Table 2-14: U.S. Greenhouse Gas Emissions by Economic Sector and Gas with Electricity-Related 

Emissions Distributed (Tg CO2 Eq.) and Percent of Total in 2006

Sector/Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006 Percenta

Industry 2,100.4 2,141.1 2,174.3 2,061.1 2,051.6 2,064.0 2,075.4 2,038.3 2,029.2 28.5%

Direct Emissions 1,460.3 1,478.0 1,432.9 1,384.3 1,384.9 1,375.5 1,388.9 1,354.3 1,371.5 19.2%

CO2 1,070.1 1,103.0 1,091.3 1,066.4 1,065.7 1,069.6 1,086.5 1,065.8 1,084.6 15.2%

CH4 286.5 273.6 258.3 255.4 251.3 247.8 240.5 226.7 227.1 3.2%

N2O 40.4 44.8 33.7 28.9 30.6 29.8 29.5 30.0 29.9 0.4%

HFCs, PFCs, and SF6 63.3 56.6 49.6 33.6 37.3 28.2 32.4 31.7 30.0 0.4%

Electricity-Related 640.1 663.1 741.4 676.8 666.7 688.5 686.5 683.9 657.7 9.2%

CO2 627.7 652.8 733.1 669.2 659.4 681.1 679.2 676.8 650.9 9.1%

CH4 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 +

N2O 2.9 3.0 3.3 3.0 2.9 3.1 3.0 3.0 2.9 +

SF6 9.2 7.2 4.8 4.4 4.2 4.1 4.0 3.9 3.6 0.1%

Transportation 1,547.2 1,688.9 1,921.0 1,899.4 1,952.0 1,930.2 1,980.0 1,992.0 1,974.5 27.7%

Direct Emissions 1,544.1 1,685.8 1,917.5 1,895.8 1,948.5 1,925.9 1,975.4 1,987.2 1,969.5 27.6%

CO2 1,496.9 1,610.7 1,810.2 1,786.7 1,839.8 1,817.7 1,866.6 1,880.0 1,865.9 26.2%

CH4 4.5 4.1 3.2 3.1 2.7 2.5 2.4 2.3 2.1 +

N2O 42.67 52.46 51.53 48.80 44.82 41.26 38.51 35.20 31.96 0.4%

HFCsb + 18.6 52.57 57.20 61.13 64.41 67.84 69.74 69.46 1.0%

Electricity-Related 3.1 3.1 3.49 3.69 3.49 4.33 4.59 4.78 5.03 0.1%

CO2 3.1 3.1 3.4 3.6 3.5 4.3 4.5 4.7 5.0 0.1%

CH4 + + + + + + + + + +

N2O + + + + + + + + + +

SF6 + + + + + + + + + +

Commercial 946.3 1,003.8 1,141.9 1,149.8 1,151.1 1,172.7 1,187.2 1,212.5 1,204.4 16.9%

Direct Emissions 396.9 404.5 390.3 383.0 388.1 410.2 404.6 400.4 394.6 5.5%

CO2 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1 2.9%

CH4 173.8 170.0 147.6 143.8 146.4 151.9 149.0 149.9 152.0 2.1%

N2O 7.0 8.0 9.3 9.5 9.4 9.7 9.9 10.1 10.2 0.1%

HFCs + 0.7 5.5 7.4 9.6 12.1 15.0 18.5 22.4 0.3%

Electricity-Related 549.3 599.4 751.6 766.7 763.0 762.5 782.6 812.0 809.8 11.4%

CO2 538.7 590.0 743.2 758.1 754.6 754.4 774.3 803.5 801.5 11.2%

CH4 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 +

N2O 2.5 2.7 3.3 3.4 3.4 3.4 3.5 3.6 3.6 0.1%

SF6 7.9 6.5 4.9 5.0 4.8 4.5 4.6 4.7 4.5 0.1%

When emissions from electricity are distributed among 

these sectors, industry accounts for the largest share of U.S. 

greenhouse gas emissions (29 percent), followed closely by 

emissions from transportation activities, which account for 

28 percent of total emissions. Emissions from the residential 

and commercial sectors also increase substantially when 

emissions from electricity are included, due to their relatively 

large share of electricity consumption. In all sectors except 

agriculture, CO2 accounts for more than 80 percent of 

greenhouse gas emissions, primarily from the combustion 

of fossil fuels.

Table 2-14 presents a detailed breakdown of emissions 

from each of these economic sectors, with emissions from 

electricity generation distributed to them. Figure 2-13 shows 

the trend in these emissions by sector from 1990 to 2006.
2-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Industry

The industrial end-use sector includes CO2 emissions 

from fossil fuel combustion from all manufacturing 

facilities, in aggregate. This sector also includes emissions 

that are produced as a byproduct of the non-energy-related 

industrial process activities. The variety of activities 

producing these non-energy-related emissions, to name 

a few includes fugitive CH4 emissions from coal mining, 

byproduct CO2 emissions from cement production, 

and HFC, PFC, and SF6 byproduct emissions from 

semiconductor manufacture. Overall, direct industry sector 

emissions have declined since 1990, while electricityrelated emissions have risen. In theory, emissions from 

the industrial end-use sector should be highly correlated 

with economic growth and industrial output, but heating of 

Table 2-14: U.S. Greenhouse Gas Emissions by Economic Sector and Gas with Electricity-Related 

Emissions Distributed (Tg CO2 Eq.) and Percent of Total in 2006

Sector/Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006 Percenta

Residential 952.4 1,026.5 1,160.7 1,153.2 1,178.0 1,211.2 1,207.2 1,241.7 1,187.8 16.7%

Direct Emissions 346.9 370.9 387.7 379.3 376.6 399.6 385.5 376.0 344.8 4.8%

CO2 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5 4.6%

CH4 4.4 4.0 3.4 3.1 3.1 3.3 3.3 3.3 3.1 +

N2O 2.1 2.2 2.1 2.3 2.3 2.4 2.5 2.4 2.3 +

HFCs 0.3 8.1 10.1 10.3 10.7 11.0 11.4 11.9 12.9 0.2%

Electricity-Related 605.5 655.6 773.0 773.9 801.4 811.6 821.7 865.6 843.0 11.8%

CO2 593.8 645.4 764.4 765.2 792.6 802.9 813.0 856.6 834.4 11.7%

CH4 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 +

N2O 2.8 3.0 3.4 3.4 3.5 3.6 3.6 3.8 3.7 0.1%

SF6 8.7 7.1 5.0 5.1 5.0 4.8 4.8 5.0 4.7 0.1%

Agriculture 567.9 592.5 587.4 603.2 595.1 560.5 567.2 584.9 595.8 8.4%

Direct Emissions 506.8 524.1 528.0 533.4 529.3 498.0 499.2 521.3 533.6 7.5%

CO2 53.8 64.4 58.4 58.5 61.4 53.3 58.7 53.4 51.6 0.7%

CH4 170.3 180.7 190.8 181.8 189.1 181.8 178.0 186.4 199.1 2.8%

N2O 282.6 279.0 278.8 293.1 278.8 262.9 262.6 281.5 282.9 4.0%

Electricity-Related 61.2 68.5 59.4 69.8 65.8 62.5 68.1 63.6 62.3 0.9%

CO2 60.0 67.4 58.7 69.0 65.1 61.9 67.3 63.0 61.6 0.9%

CH4 + + + + + + + + + +

N2O 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 +

SF6 0.9 0.7 0.4 0.5 0.4 0.4 0.4 0.4 0.3 +

U.S. Territories 34.1 41.1 47.3 54.5 53.3 59.7 61.0 60.5 62.4 0.9%

Total 6,148.3 6,494.0 7,032.6 6,921.3 6,981.2 6,998.2 7,078.0 7,129.9 7,054.2 100.0%

Note: Emissions from electricity generation are allocated based on aggregate electricity consumption in each end-use sector.

Totals may not sum due to independent rounding.

+ Does not exceed 0.05 Tg CO2 Eq. or 0.05 percent. a Percent of total emissions for year 2006.

b Includes primarily HFC-134a.

0

500

1,000

1,500

2,000

2,500

Agriculture

Residential

Commercial

Transportation

Industrial

19901991199219931994199519961997199819992000200120022003200420052006

Tg CO2 Eq.

Figure 2-13

Emissions with Electricity Distributed to Economic Sectors

(continued)
Trends in Greenhouse Gas Emissions 2-23

In presenting the Economic Sectors in the annual Inventory of U.S. Greenhouse Gas Emissions and Sinks, EPA expands upon the 

standard IPCC sectors common for UNFCCC reporting. EPA believes that discussing greenhouse gas emissions relevant to U.S.-specific 

sectors improves communication of the report’s findings.

•	 In the Electricity Generation economic sector, CO2 emissions from the combustion of fossil fuels included in the EIA electric utility 

fuel consuming sector are apportioned to this economic sector. Stationary combustion emissions of CH4 and N2O are also based 

on the EIA electric utility sector. Additional sources include CO2 and N2O from Municipal Solid Waste Combustion, as the majority 

of municipal solid waste is combusted in “trash-to-steam” electricity generation plants. The Electricity Generation economic sector 

also includes SF6 from Electrical Transmission and Distribution, and a portion of CO2 from Limestone and Dolomite Use (from 

pollution control equipment installed in electricity generation plants).

•	 In the Transportation economic sector, the CO2 emissions from the combustion of fossil fuels included in the EIA transportation fuel 

consuming sector are apportioned to this economic sector (additional analyses and refinement of the EIA data is further explained 

in the Energy chapter of this report). Additional emissions are apportioned from the CH4 and N2O from Mobile Combustion, based 

on the EIA transportation sector. Substitutes of Ozone Depleting Substitutes are apportioned based on their specific end-uses 

within the source category, with emissions from transportation refrigeration/air-conditioning systems to this economic sector. 

Finally, CO2 emissions from Non-Energy Uses of Fossil Fuels identified as lubricants for transportation vehicles are included in the 

Transportation economic sector.

•	 For the Industry economic sector, the CO2 emissions from the combustion of fossil fuels included in the EIA industrial fuel 

consuming sector, minus the agricultural use of fuel explained below, are apportioned to this economic sector. Stationary and mobile 

combustion emissions of CH4 and N2O are also based on the EIA industrial sector, minus emissions apportioned to the Agriculture 

economic sector described below. Substitutes of Ozone Depleting Substitutes are apportioned based on their specific end-uses 

within the source category, with most emissions falling within the Industry economic sector (minus emissions from the other 

economic sectors). Additionally, all process-related emissions from sources with methods considered within the IPCC Industrial 

Process guidance have been apportioned to this economic sector. This includes the process-related emissions (i.e., emissions 

from the actual process to make the material, not from fuels to power the plant) from such activities as cement production, iron 

and steel production, and ammonia production. Additionally, fugitive emissions from energy production sources, such as Natural 

Gas Systems, Coal Mining, and Petroleum Systems are included in the Industry economic sector. A portion of CO2 from Limestone 

and Dolomite Use (from pollution control equipment installed in large industrial facilities) are also included in the Industry economic 

sector. Finally, all remaining CO2 emissions from Non-Energy Uses of Fossil Fuels are assumed to be industrial in nature (besides 

the lubricants for transportation vehicles specified above), and are attributed to the Industry economic sector.

•	 As agriculture equipment is included in EIA’s industrial fuel consuming sector surveys, additional data is used to extract the fuel

used by agricultural equipment, to allow for accurate reporting in the Agriculture economic sector from all sources of emissions, 

such as motorized farming equipment. Energy consumption estimates are obtained from Department of Agriculture survey data, 

in combination with separate EIA fuel sales reports. This supplementary data is used to apportion CO2 emissions from fossil fuel 

combustion, and CH4 and N2O emissions from stationary and mobile combustion (all data is removed from the Industrial economic 

sector, to avoid double-counting). The other emission sources included in this economic sector are intuitive for the agriculture 

sectors, such as N2O emissions from Agricultural Soils, CH4 from Enteric Fermentation (i.e., exhalation from the digestive tracts 

of domesticated animals), CH4 and N2O from Manure Management, CH4 from Rice Cultivation, CO2 emissions from liming of 

agricultural soils and urea application, and CH4 and N2O from Forest Fires. N2O emissions from the application of fertilizers to tree 

plantations (termed “forest land” by the IPCC) are also included in the Agriculture economic sector.

•	 The Residential economic sector includes the CO2 emissions from the combustion of fossil fuels reported for the EIA residential 

sector. Stationary combustion emissions of CH4 and N2O are also based on the EIA residential fuel consuming sector. Substitutes 

of Ozone Depleting Substitutes are apportioned based on their specific end-uses within the source category, with emissions from 

residential air-conditioning systems to this economic sector. N2O emissions from the application of fertilizers to developed land 

(termed “settlements” by the IPCC) are also included in the Residential economic sector.

•	 The Commercial economic sector includes the CO2 emissions from the combustion of fossil fuels reported in the EIA commercial 

fuel consuming sector data. Stationary combustion emissions of CH4 and N2O are also based on the EIA commercial sector. 

Substitutes of Ozone Depleting Substances are apportioned based on their specific end-uses within the source category, with 

emissions from commercial refrigeration/air-conditioning systems to this economic sector. Public works sources including direct 

CH4 from Landfills and CH4 and N2O from Wastewater Treatment and Composting are included in this economic sector.

Box 2-1: Methodology for Aggregating Emissions by Economic Sector
2-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

industrial buildings and agricultural energy consumption 

are also affected by weather conditions. In addition, 

structural changes within the U.S. economy that lead to 

shifts in industrial output away from energy intensive 

manufacturing products to less energy intensive products 

(e.g., from steel to computer equipment) also have a 

significant effect on industrial emissions.

Transportation

When electricity-related emissions are distributed to 

economic end-use sectors, transportation activities accounted 

for 28 percent of U.S. greenhouse gas emissions in 2006. The 

largest sources of transportation GHGs in 2006 were passenger 

cars (34 percent), light duty trucks, which include sport utility 

vehicles, pickup trucks, and minivans (28 percent), freight 

trucks (20 percent) and commercial aircraft (7 percent). These 

figures include direct emissions from fossil fuel combustion, 

as well as HFC emissions from mobile air conditioners and 

refrigerated transport allocated to these vehicle types. Table 

2-15 provides a detailed summary of greenhouse gas emissions 

from transportation-related activities with electricity-related 

emissions included in the totals.

From 1990 to 2006, transportation emissions rose by 28 

percent due, in large part, to increased demand for travel and 

the stagnation of fuel efficiency across the U.S. vehicle fleet. 

The number of vehicle miles traveled by light-duty motor 

vehicles (passenger cars and light-duty trucks) increased 

39 percent from 1990 to 2006, as a result of a confluence 

of factors including population growth, economic growth, 

urban sprawl, and low fuel prices over much of this period. 

A similar set of social and economic trends has led to a 

significant increase in air travel and freight transportation 

by both air and road modes during the time series.

Although average fuel economy over this period 

increased slightly due primarily to the retirement of older 

vehicles, average fuel economy among new vehicles sold 

annually gradually declined from 1990 to 2004. The decline 

in new vehicle fuel economy reflects an increasing market 

share of light duty trucks, which have grown from about 

one-fifth of new vehicle sales in the 1970s to slightly over 

Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.)

Gas/Vehicle Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Passenger Cars 656.9 644.1 694.6 699.1 713.7 692.4 689.5 705.8 678.4 

CO2 628.8 604.9 643.5 647.9 662.6 642.1 640.0 658.4 634.5 

CH4 2.6 2.1 1.6 1.5 1.4 1.3 1.2 1.1 1.0 

N2O 25.4 26.9 25.2 23.8 22.5 21.0 19.5 17.8 15.6 

HFCs + 10.1 24.3 25.9 27.2 28.0 28.8 28.5 27.2 

Light-Duty Trucks 336.2 434.7 508.1 513.3 525.1 560.4 583.0 544.0 556.6 

CO2 320.7 405.0 466.0 470.3 483.2 518.8 540.8 501.9 514.9 

CH4 1.4 1.4 1.1 1.1 0.9 0.8 0.7 0.7 0.7 

N2O 14.1 22.1 22.4 21.3 18.5 16.6 15.3 13.7 12.7 

HFCs + 6.1 18.6 20.6 22.5 24.2 26.1 27.7 28.3 

Medium- and Heavy-Duty Trucks 228.6 272.5 344.3 343.6 357.9 354.4 367.4 395.2 404.6 

CO2 227.8 271.2 341.5 340.6 354.8 351.2 364.1 391.9 401.3 

CH4 + + + + + + + + + 

N2O 0.8 1.0 1.2 1.2 1.2 1.3 1.2 1.2 1.1 

HFCs + 0.3 1.6 1.7 1.8 1.9 2.1 2.1 2.2 

Buses 8.5 9.3 11.2 10.3 10.0 10.8 15.1 12.1 12.5 

CO2 8.3 9.0 10.9 10.0 9.6 10.5 14.7 11.8 12.1 

CH4 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

N2O + + + + + + + + + 

HFCs + + 0.1 0.2 0.2 0.2 0.2 0.2 0.3 

Motorcycles 1.8 1.8 1.9 1.7 1.7 1.7 1.8 1.6 1.9 

CO2 1.7 1.8 1.8 1.7 1.7 1.6 1.7 1.6 1.9 

CH4 + + + + + + + + + 

N2O + + + + + + + + + 
Trends in Greenhouse Gas Emissions 2-25

Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO2 Eq.)

Gas/Vehicle Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Commercial Aircraft—Domestica 138.1 144.6 165.9 154.4 147.6 145.4 144.4 152.0 143.6 

CO2 136.7 143.1 164.2 152.9 146.1 143.9 142.9 150.4 142.1 

CH4 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

N2O 1.3 1.4 1.6 1.5 1.4 1.4 1.4 1.5 1.4 

Other Aircraft—Domesticb 43.8 31.9 32.6 34.1 32.2 31.1 34.5 31.1 28.8 

CO2 43.3 31.5 32.2 33.7 31.9 30.8 34.1 30.8 28.5 

CH4 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

N2O 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Ships and Boats—Domesticc 47.0 56.6 65.1 47.4 65.4 38.3 47.1 50.8 47.7 

CO2 46.5 55.5 61.0 43.2 60.8 33.6 42.1 45.6 42.4 

CH4 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

N2O 0.4 0.4 0.5 0.3 0.5 0.3 0.4 0.4 0.4 

HFCs + 0.6 3.4 3.7 4.0 4.3 4.6 4.7 4.9 

Rail 38.5 44.0 50.1 50.8 50.7 52.8 55.8 56.6 57.9 

CO2 38.1 42.2 45.1 45.4 44.9 46.6 49.2 49.8 51.0 

CH4 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

N2O 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 

HFCs + 1.4 4.6 5.0 5.4 5.8 6.1 6.4 6.5 

Pipelinesd 36.1 38.2 35.2 33.6 36.6 32.7 31.2 32.3 32.4 

CO2 36.1 38.2 35.2 33.6 36.6 32.7 31.2 32.3 32.4 

Lubricants 11.9 11.3 12.1 11.1 10.9 10.1 10.2 10.2 9.9 

CO2 11.9 11.3 12.1 11.1 10.9 10.1 10.2 10.2 9.9 

Other Transportation 

(Unspecified)e + + + + + 0.1 0.1 0.2 0.2

Total Transportation 1,547.2 1,688.9 1,921.0 1,899.4 1,952.0 1,930.2 1,980.0 1,992.0 1,974.5 

International Bunker Fuelsf 114.8 101.6 102.2 98.6 90.0 104.6 120.2 123.8 128.4 

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding. Emissions estimates for passenger cars, light-duty trucks and heavy-duty trucks are calculated 

using fuel consumption data from FHWA’s Highway Statistics, which used an updated methodology to develop the 2006 estimates. In the most recent 

Highway Statistics, FHWA also updated 2005 fuel consumption estimates, but did not revise other prior years. This causes some discontinuity in the 

emissions estimates between 2004 and 2005.

Passenger cars and light-duty trucks include vehicles typically used for personal travel and less than 8,500 lbs; medium- and heavy-duty trucks include 

vehicles 8,501 lbs and above.

HFC emissions primarily reflect HFC-134a.

a Consists of emissions from jet fuel consumed by domestic operations of commercial aircraft (no bunkers).

b Consists of emissions from jet fuel and aviation gasoline consumption by general aviation and military aircraft.

c Fluctuations in emission estimates are associated with fluctuations in reported fuel consumption, and may reflect data collection problems.

d CO2 estimates reflect natural gas used to power pipelines, but not electricity. While the operation of pipelines produces CH4 and N2O, these emissions 

are not directly attributed to pipelines in the U.S. Inventory.

e Combination of gases; balancing item for transportation emissions not specifically identified in table but which are included in transportation economic 

sector emissions identified in Table 2-14.

f Emissions from International Bunker Fuels include emissions from both civilian and military activities; these emissions are not included in the 

transportation totals.

(continued)
2-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

half of the market by 2004. Increasing fuel prices have since 

decreased the momentum of light duty truck sales, and 

average new vehicle fuel economy improved in 2005 and 

2006 as the market share of passenger cars increased. VMT 

growth among all passenger vehicles has also been impacted, 

growing an average annual rate of 0.8 percent from 2004 to 

2006, compared to an annual rate of 2.7 percent over the 

period 1990 to 2004.

Almost all of the energy consumed for transportation 

was supplied by petroleum-based products, with more than 

half being related to gasoline consumption in automobiles 

and other highway vehicles. Other fuel uses, especially diesel 

fuel for freight trucks and jet fuel for aircraft, accounted for 

the remainder. The primary driver of transportation-related 

emissions was CO2 from fossil fuel combustion, which 

increased by 25 percent from 1990 to 2006. This rise in 

CO2 emissions, combined with an increase in HFCs from 

virtually no emissions in 1990 to 69.5 Tg CO2 Eq. in 2006, 

led to an increase in overall emissions from transportation 

activities of 28 percent.

Commercial

The commercial sector is heavily reliant on electricity 

for meeting energy needs, with electricity consumption for 

lighting, heating, air conditioning, and operating appliances. 

The remaining emissions were largely due to the direct 

consumption of natural gas and petroleum products, primarily 

for heating and cooking needs. Energy-related emissions from 

the residential and commercial sectors have generally been 

increasing since 1990, and are often correlated with shortterm fluctuations in energy consumption caused by weather 

conditions, rather than prevailing economic conditions. 

Landfills and wastewater treatment are included in this 

sector, with landfill emissions decreasing since 1990, while 

wastewater treatment emissions have increased slightly.

Residential

The residential sector is heavily reliant on electricity 

for meeting energy needs, with electricity consumption for 

lighting, heating, air conditioning, and operating appliances. 

The remaining emissions were largely due to the direct 

consumption of natural gas and petroleum products, primarily 

for heating and cooking needs. Emissions from the residential 

sectors have generally been increasing since 1990, and 

are often correlated with short-term fluctuations in energy 

consumption caused by weather conditions, rather than 

prevailing economic conditions. In the long-term, this sector 

is also affected by population growth, regional migration 

trends, and changes in housing and building attributes (e.g., 

size and insulation).

Agriculture

The agricultural sector includes a variety of processes, 

including enteric fermentation in domestic livestock, 

livestock manure management, and agricultural soil 

management. In 2006, enteric fermentation was the largest 

source of CH4 emissions in the United States, and agricultural 

soil management was the largest source of N2O emissions 

in the U.S. This sector also includes small amounts of CO2

emissions from fossil fuel combustion by motorized farm 

equipment like tractors.

Electricity Generation

The process of generating electricity, for consumption in 

the above sectors, is the single largest source of greenhouse 

gas emissions in the United States, representing 33 percent 

of total U.S. emissions. Electricity generation also accounted 

for the largest share of CO2 emissions from fossil fuel 

combustion, approximately 41 percent in 2006. Electricity 

was consumed primarily in the residential, commercial, 

and industrial end-use sectors for lighting, heating, electric 

motors, appliances, electronics, and air conditioning.
Trends in Greenhouse Gas Emissions 2-27

Total emissions can be compared to other economic and social indices to highlight changes over time. These comparisons include: (1) 

emissions per unit of aggregate energy consumption, because energy-related activities are the largest sources of emissions, (2) emissions 

per unit of fossil fuel consumption, because almost all energy-related emissions involve the combustion of fossil fuels, (3) emissions per 

unit of electricity consumption, because the electric power industry—utilities and non-utilities combined—was the largest source of U.S. 

greenhouse gas emissions in 2006, (4) emissions per unit of total gross domestic product as a measure of national economic activity, or 

(5) emissions per capita.

Table 2-16 provides data on various statistics related to U.S. greenhouse gas emissions normalized to 1990 as a baseline year. Greenhouse 

gas emissions in the United States have grown at an average annual rate of 0.9 percent since 1990. This rate is slightly slower than that for 

total energy or fossil fuel consumption and much slower than that for either electricity consumption or overall gross domestic product. Total 

U.S. greenhouse gas emissions have also grown slightly slower than national population since 1990 (see Figure 2-14).

Box 2-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data

Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100)

Variable 1990 1995 2000 2001 2002 2003 2004 2005 2006

Growth 

Ratea

GDPb 100 113 138 139 141 145 150 155 159 3.0%

Electricity Consumptionc 100 112 127 125 128 129 131 134 135 1.9%

Fossil Fuel Consumptionc 100 107 117 115 116 116 119 119 117 1.0%

Energy Consumptionc 100 108 116 112 115 115 118 118 117 1.0%

Populationd 100 107 113 114 115 116 117 118 119 1.1%

Greenhouse Gas Emissionse 100 106 114 113 114 114 115 116 115 0.9%

a Average annual growth rate

b Gross Domestic Product in chained 2000 dollars (BEA 2007)

c Energy-content-weighted values (EIA 2007b)

d U.S. Census Bureau (2007)

e GWP-weighted values

Figure 2-14

Emissions 

per $GDP 

Emissions 

per capita 

Population

Real GDP

70

80

90

100

150

160

140

130

120

110

Index (1990 = 100)

19901991199219931994199519961997199819992000200120022003200420052006

U.S. Greenhouse Gas Emissions Per Capita and 

Per Dollar of Gross Domestic Product

Source: BEA (2007), U.S. Census Bureau (2007), and emission estimates in the this report.
2-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

2.3. Indirect Greenhouse Gas 

Emissions (CO, NOx, NMVOCs, 

and SO2)

The reporting requirements of the UNFCCC7 request 

that information be provided on indirect greenhouse gases, 

7 See <http://unfccc.int/resource/docs/cop8/08.pdf>.

which include CO, NOx, NMVOCs, and SO2. These gases 

do not have a direct global warming effect, but indirectly 

affect terrestrial radiation absorption by influencing the 

formation and destruction of tropospheric and stratospheric 

ozone, or, in the case of SO2, by affecting the absorptive 

characteristics of the atmosphere. Additionally, some of 

Table 2-17: Emissions of NOx, CO, NMVOCs, and SO2 (Gg)

Gas/Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

NOx 21,645 21,272 19,203 18,410 17,938 17,043 16,177 15,569 14,869

Mobile Fossil Fuel Combustion 10,920 10,622 10,310 9,819 10,154 9,642 9,191 8,739 8,287

Stationary Fossil Fuel Combustion 9,883 9,821 8,002 7,667 6,791 6,419 6,004 5,853 5,610

Industrial Processes 591 607 626 656 534 528 524 519 515

Oil and Gas Activities 139 100 111 113 321 316 316 316 315

Municipal Solid Waste Combustion 82 88 114 114 98 97 97 97 97

Agricultural Burning 28 29 35 35 33 34 39 39 38

Solvent Use 1 3 3 3 5 5 5 5 5

Waste 0 1 2 2 2 2 2 2 2

CO 130,461 109,032 92,777 89,212 84,609 80,221 76,342 72,365 68,372

Mobile Fossil Fuel Combustion 119,360 97,630 83,559 79,851 75,421 71,038 67,096 63,154 59,213

Stationary Fossil Fuel Combustion 5,000 5,383 4,340 4,377 4,965 4,893 4,876 4,860 4,844

Industrial Processes 4,125 3,959 2,217 2,339 1,744 1,724 1,724 1,724 1,724

Municipal Solid Waste Combustion 978 1,073 1,670 1,672 1,439 1,437 1,437 1,437 1,437

Agricultural Burning 691 663 792 774 709 800 879 860 825

Oil and Gas Activities 302 316 146 147 323 321 321 321 322

Waste 1 2 8 8 7 7 7 7 7

Solvent Use 5 5 46 45 1 1 1 1 1

NMVOCs 20,930 19,520 15,228 15,048 15,640 15,170 14,807 14,444 14,082

Mobile Fossil Fuel Combustion 10,932 8,745 7,230 6,872 7,235 6,885 6,587 6,289 5,991

Solvent Use 5,216 5,609 4,384 4,547 3,881 3,862 3,854 3,846 3,839

Industrial Processes 2,422 2,642 1,773 1,769 2,036 1,972 1,931 1,890 1,849

Stationary Fossil Fuel Combustion 912 973 1,077 1,080 1,585 1,560 1,553 1,545 1,538

Oil and Gas Activities 554 582 389 400 545 538 533 528 523

Municipal Solid Waste Combustion 222 237 257 258 243 239 237 235 232

Waste 673 731 119 122 115 114 112 111 110

Agricultural Burning NA NA NA NA NA NA NA NA NA

SO2 20,935 16,891 14,829 14,452 13,403 13,631 13,232 13,114 12,258

Stationary Fossil Fuel Combustion 18,407 14,724 12,848 12,461 11,613 11,956 11,625 11,573 10,784

Industrial Processes 1,307 1,117 1,031 1,047 850 804 800 797 793

Mobile Fossil Fuel Combustion 793 672 632 624 683 621 564 508 451

Oil and Gas Activities 390 335 286 289 233 226 220 213 207

Municipal Solid Waste Combustion 38 42 29 30 23 22 22 22 22

Waste 0 1 1 1 1 1 1 1 1

Solvent Use 0 1 1 1 0 0 0 0 0

Agricultural Burning NA NA NA NA NA NA NA NA NA

These emission estimates were obtained from preliminary data (EPA 2008) and disaggregated based on EPA (2003), except for estimates from field 

burning of agricultural residues.

NA (Not Available)

Note: Totals may not sum due to independent rounding.
Trends in Greenhouse Gas Emissions 2-29

these gases may react with other chemical compounds in the 

atmosphere to form compounds that are greenhouse gases. 

Carbon monoxide is produced when carbon-containing 

fuels are combusted incompletely. Nitrogen oxides (i.e., 

NO and NO2) are created by lightning, fires, fossil fuel 

combustion, and in the stratosphere from N2O. Non-CH4

volatile organic compounds—which include hundreds 

of organic compounds that participate in atmospheric 

chemical reactions (i.e., propane, butane, xylene, toluene, 

ethane, and many others)—are emitted primarily from 

transportation, industrial processes, and non-industrial 

consumption of organic solvents. In the United States, 

SO2 is primarily emitted from coal combustion for electric 

power generation and the metals industry. Sulfur-containing 

compounds emitted into the atmosphere tend to exert a 

negative radiative forcing (i.e., cooling) and therefore are 

discussed separately.

One important indirect climate change effect of 

NMVOCs and NOx is their role as precursors for 

tropospheric ozone formation. They can also alter the 

atmospheric lifetimes of other greenhouse gases. Another 

example of indirect greenhouse gas formation into 

greenhouse gases is CO’s interaction with the hydroxyl 

radical—the major atmospheric sink for CH4 emissions—to 

form CO2. Therefore, increased atmospheric concentrations 

of CO limit the number of hydroxyl molecules (OH) 

available to destroy CH4.

Since 1970, the United States has published estimates 

of annual emissions of CO, NOx, NMVOCs, and SO2 (EPA 

2005),8 which are regulated under the Clean Air Act. Table 

2-17 shows that fuel combustion accounts for the majority 

of emissions of these indirect greenhouse gases. Industrial 

processes—such as the production of chemical and allied 

products, metals processing, and industrial uses of solvents—

are also significant sources of CO, NOx, and NMVOCs.

8 Estimates from preliminary data (EPA 2008) and disaggregated based 

on EPA (2003). NOx and CO emission estimates from field burning of 

agricultural residues were estimated separately, and therefore not taken 

from EPA (2008).

Sulfur dioxide (SO2) emitted into the atmosphere through natural and anthropogenic processes affects the earth’s radiative budget 

through its photochemical transformation into sulfate aerosols that can (1) scatter radiation from the sun back to space, thereby reducing 

the radiation reaching the earth’s surface, (2) affect cloud formation, and (3) affect atmospheric chemical composition (e.g., by providing 

surfaces for heterogeneous chemical reactions). The indirect effect of sulfur-derived aerosols on radiative forcing can be considered in 

two parts. The first indirect effect is the aerosols’ tendency to decrease water droplet size and increase water droplet concentration in the 

atmosphere. The second indirect effect is the tendency of the reduction in cloud droplet size to affect precipitation by increasing cloud lifetime 

and thickness. Although still highly uncertain, the radiative forcing estimates from both the first and the second indirect effect are believed 

to be negative, as is the combined radiative forcing of the two (IPCC 2001). However, because SO2 is short-lived and unevenly distributed 

in the atmosphere, its radiative forcing impacts are highly uncertain.

Sulfur dioxide is also a major contributor to the formation of regional haze, which can cause significant increases in acute and chronic 

respiratory diseases. Once SO2 is emitted, it is chemically transformed in the atmosphere and returns to the earth as the primary source of 

acid rain. Because of these harmful effects, the United States has regulated SO2 emissions in the Clean Air Act.

Electricity generation is the largest anthropogenic source of SO2 emissions in the United States, accounting for 71 percent in 

2006. Coal combustion contributes nearly all of those emissions (approximately 92 percent). Sulfur dioxide emissions have decreased 

in recent years, primarily as a result of electric power generators switching from high-sulfur to low-sulfur coal and installing flue gas 

desulfurization equipment.

Box 2-3: Sources and Effects of Sulfur Dioxide
Energy 3-1

3. Energy

E

nergy-related activities were the primary sources of U.S. anthropogenic greenhouse gas emissions, accounting 

for 86 percent of total emissions on a carbon dioxide (CO2) equivalent basis in 2006. This included 97, 37, 

and 13 percent of the nation’s CO2, methane (CH4), and nitrous oxide (N2O) emissions, respectively. Energyrelated CO2 emissions alone constituted 83 percent of national emissions from all sources on a CO2 equivalent basis, 

while the non-CO2 emissions from energy-related activities represented a much smaller portion of total national emissions 

(4 percent collectively).

Emissions from fossil fuel combustion comprise the vast majority of energy-related emissions, with CO2 being the 

primary gas emitted (see Figure 3-1). Globally, approximately 28,193 Tg of CO2 were added to the atmosphere through 

the combustion of fossil fuels in 2005, of which the United States accounted for about 20 percent.1; Due to the relative 

importance of fossil fuel combustion-related CO2 emissions, they are considered separately, and in more detail than other 

energy-related emissions (see Figure 3-2). Fossil fuel combustion also emits CH4 and N2O, as well as indirect greenhouse 

gases such as nitrogen oxides (NOx), carbon monoxide (CO), and non-CH4 volatile organic compounds (NMVOCs). Mobile 

fossil fuel combustion was the second largest source of N2O emissions in the United States, and overall energy-related 

activities were collectively the largest source of these indirect greenhouse gas emissions.

Energy-related activities other than fuel combustion, 

such as the production, transmission, storage, and distribution 

of fossil fuels, also emit greenhouse gases. These emissions 

consist primarily of fugitive CH4 from natural gas systems, 

petroleum systems, and coal mining. Smaller quantities of 

CO2, CO, NMVOCs, and NOx are also emitted. 

The combustion of biomass and biomass-based fuels also 

emits greenhouse gases. CO2 emissions from these activities, 

however, are not included in national emissions totals because 

biomass fuels are of biogenic origin. It is assumed that the 

C released during the consumption of biomass is recycled 

as U.S. forests and crops regenerate, causing no net addition 

of CO2 to the atmosphere. The net impacts of land-use and 

forestry activities on the C cycle are accounted for separately 

within the Land Use, Land-Use Change, and Forestry chapter. 

Emissions of other greenhouse gases from the combustion 

1 Global CO2 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy Annual 2005

<http://www.eia.doe.gov/emeu/iea/carbon.html> EIA (2007).

Figure 3-1

2006 Energy Chapter Greenhouse Gas Emission Sources

0 25 50 75 100 125 150

Tg CO2 Eq.

5,637.9

Energy as a Portion

of all Emissions

86.1%

Abandoned Underground

Coal Mines

Stationary Combustion

Municipal Solid Waste

Combustion

Petroleum Systems

Mobile Combustion

Coal Mining

Natural Gas Systems

Non-Energy Use of Fuels

Fossil Fuel Combustion
3-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Figure 3-2

2006 U.S. Fossil Carbon Flows (Tg CO2 Eq.)

Apparent

Consumption

6,266

Atmospheric

Emissions

5,997

Coal

2,219

Petroleum

840

Petroleum

1,858

NG 225

Coal 96

Other 255

Natural Gas Liquids,

Liquefied Refinery Gas,

& Other Liquids

147

Natural Gas

1,032

Combustion

Emissions

2,065

International

Bunkers

129

Non-Energy

Use Exports

98 Stock

Changes

111

Balancing

Item

29

Fossil Fuel

Energy Exports

329

Industrial

Processes

93

NEU Emissions 

9

Non-Energy Use 

Carbon Sequestered

240

Fossil Fuel

Combustion Residual

(Not Oxidized Fraction)

53

Coal Emissions

2,074

Domestic

Fossil Fuel

Production

4,238

Fossil Fuel

Energy

Imports

2,435

Non-Energy

Use Imports

67

Fossil Fuel

Consumption

U.S.

Territories

55

Non-Energy

Use U.S.

Territories

8

NEU Emissions 8

NEU Emissions 121

Combustion

Emissions

2,417

Petroleum 

Emissions

2,538

Natural Gas 

Emissions

1,163

Combustion

Emissions 1,155

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 3-1: CO2, CH4, and N2O Emissions from Energy (Tg CO2 Eq.)

Gas/Source 1990 1995 2000

CO2 4,886.4 5,215.5 5,765.7

2001

5,686.4

2002

5,749.1

2003

5,796.6

2004

5,878.8

2005

5,920.5

2006

5,825.6

Fossil Fuel Combustion 4,724.1 5,032.4 5,577.1 5,507.4 5,564.8 5,617.0 5,681.4 5,731.0 5,637.9

Electricity Generation 1,809.6 1,939.3 2,282.3 2,244.3 2,253.7 2,283.1 2,314.9 2,380.2 2,328.2 

Transportation 1,485.1 1,599.4 1,798.2 1,775.6 1,828.9 1,807.6 1,856.4 1,869.8 1,856.0 

Industrial 844.9 876.5 860.3 852.5 854.8 856.0 857.7 847.3 862.2 

Residential 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5 

Commercial 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1 

U.S. Territories 28.3 35.0 36.2 49.0 44.0 51.0 53.5 53.2 54.9 

Non-Energy Use of Fuels 117.2 133.2 141.4 131.9 135.9 131.8 148.9 139.1 138.0

Natural Gas Systems 33.7 33.8 29.4 28.8 29.6 28.4 28.1 29.5 28.5

Municipal Solid Waste Combustion 10.9 15.7 17.5 18.0 18.5 19.1 20.1 20.7 20.9

Petroleum Systems 0.4 0.3 0.3

Wood Biomass and Ethanol 

0.3 0.3 0.3 0.3 0.3 0.3

Consumptiona 219.3 236.8 227.3 203.2 204.4 209.5 224.8 227.4 234.7

International Bunker Fuels a 113.7 100.6 101.1 97.6 89.1 103.6 119.0 122.6 127.1

CH4 260.8 246.8 234.5 232.0 226.9 224.6 217.4 202.4 203.3

Natural Gas Systems 124.7 128.1 126.5 125.3 124.9 123.3 114.0 102.5 102.4

Coal Mining 84.1 67.1 60.4 60.3 56.8 56.9 59.8 57.1 58.5

Petroleum Systems 33.9 32.0 30.3 30.2 29.9 29.2 28.7 28.3 28.4

Stationary Combustion 7.4 7.2 6.7 6.2 6.2 6.4 6.6 6.5 6.2

Abandoned Underground Coal Mines 6.0 8.2 7.4 6.7 6.2 6.0 5.8 5.6 5.4

Mobile Combustion 4.7 4.3 3.4 3.3 3.0 2.7 2.6 2.5 2.4

International Bunker Fuels a 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2
Energy 3-3

Table 3-1: CO2, CH4, and N2O Emissions from Energy (Tg CO2 Eq.)

Gas/Source 1990 1995 2000

N2O 56.8 67.3 67.5

(continued)

2001

64.4

2002

60.4

2003

57.1

2004

54.7

2005

51.5

2006

48.0

Mobile Combustion 43.5 53.4 52.5 49.9 45.9 42.3 39.7 36.3 33.1

Stationary Combustion 12.8 13.4 14.6 14.1 14.0 14.4 14.6 14.8 14.5

Municipal Solid Waste Combustion 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4

International Bunker Fuels a 1.0 0.9 0.9

Total 5,203.9 5,529.6 6,067.8

a

 These values are presented for informational purposes only and are not included or a

0.9

5,982.8

re already a

0.8

6,036.3

ccounted for

0.9

6,078.3

 in totals.

1.1

6,150.9

1.1

6,174.4

1.1

6,076.9

Note: Totals may not sum due to independent rounding.

Table 3-2: CO2, CH4, and N2O Emissions from Energy (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 4,886,370 5,215,509 5,765,732 5,686,382 5,749,059 5,796,639 5,878,815 5,920,526 5,825,631

Fossil Fuel Combustion 4,724,146 5,032,416 5,577,072 5,507,406 5,564,795 5,617,047 5,681,363 5,731,045 5,637,931

Non-Energy Use of Fuels 117,170 133,234 141,427 131,887 135,857 131,772 148,931 139,057 137,980

Natural Gas Systems 33,729 33,806 29,390 28,793 29,629 28,445 28,122 29,462 28,504

Municipal Solid Waste 

Combustion 10,950 15,712 17,518 17,971 18,458 19,058 20,097 20,673 20,922

Petroleum Systems 376 341 325 325 320 316 302 287 293

Wood Biomass and Ethanol 

Consumptiona 219,341 236,775 227,276 203,163 204,351 209,537 224,825 227,366 234,726

International Bunker Fuels a 113,683 100,627 101,125 97,563 89,101 103,583 118,975 122,580 127,097

CH4 12,417 11,754 11,168 11,048 10,804 10,693 10,353 9,636 9,679

Natural Gas Systems 5,937 6,098 6,024 5,968 5,946 5,874 5,426 4,880 4,877

Coal Mining 4,003 3,193 2,874 2,874 2,707 2,709 2,846 2,717 2,784

Petroleum Systems 1,612 1,524 1,442 1,436 1,422 1,390 1,368 1,346 1,354

Stationary Combustion 353 341 316 295 295 306 311 308 296

Abandoned Underground 

Coal Mines 288 392 350 319 293 284 276 265 257

Mobile Combustion 224 205 162 157 141 131 126 119 112

International Bunker Fuels a 8 6 6 5 4 6 7 7 7

N2O 183 217 218 208 195 184 176 166 155

Mobile Combustion 140 172 169 161 148 137 128 117 107

Stationary Combustion 41 43 47 46 45 46 47 48 47

Municipal Solid Waste 

Combustion 2 1 1 1 1 1 1 1 1

International Bunker Fuels a 3 3 3 3 3 3 3 4 4

a

 These values are presented for informational purposes only and are not included or are already accounted for in totals.

Note: Totals may not sum due to independent rounding.

of biomass and biomass-based fuels are included in national 

totals under stationary and mobile combustion.

Table 3-1 summarizes emissions from the Energy sector 

in units of teragrams of CO2 equivalents (Tg CO2 Eq.), while 

unweighted gas emissions in gigagrams (Gg) are provided in 

Table 3-2. Overall, emissions due to energy-related activities 

were 6,076.9 Tg CO2 Eq. in 2006, an increase of 17 percent 

since 1990.

3.1. Carbon Dioxide Emissions from 

Fossil Fuel Combustion (IPCC Source 

Category 1A)

CO2 emissions from fossil fuel combustion in 2006 

decreased by 1.6 percent from the previous year. This decrease 

is primarily a result of the restraint on fuel consumption caused 
3-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

by rising fuel prices, primarily in the transportation sector, an 

increase in the cost of electricity, and decreases in the cost 

of natural gas. Additionally, warmer winter conditions in 

2006 decreased the demand for heating fuels. In 2006, CO2

emissions from fossil fuel combustion were 5,637.9 Tg CO2

Eq., or 19 percent above emissions in 1990 (see Table 3-3).2

Trends in CO2 emissions from fossil fuel combustion 

are influenced by many long-term and short-term factors. On 

a year-to-year basis, the overall demand for fossil fuels in 

the United States and other countries generally fluctuates in 

response to changes in general economic conditions, energy 

prices, weather, and the availability of non-fossil alternatives. 

For example, in a year with increased consumption of 

goods and services, low fuel prices, severe summer and 

winter weather conditions, nuclear plant closures, and lower 

precipitation feeding hydroelectric dams, there would likely 

be proportionally greater fossil fuel consumption than a 

year with poor economic performance, high fuel prices, 

mild temperatures, and increased output from nuclear and 

hydroelectric plants.

Longer-term changes in energy consumption patterns, 

however, tend to be more a function of aggregate societal 

trends that affect the scale of consumption (e.g., population, 

number of cars, and size of houses), the efficiency with 

which energy is used in equipment (e.g., cars, power 

plants, steel mills, and light bulbs), and social planning 

and consumer behavior (e.g., walking, bicycling, or 

telecommuting to work instead of driving).

CO2 emissions also depend on the source of energy 

and its carbon (C) intensity. The amount of C in fuels varies 

significantly by fuel type. For example, coal contains the 

highest amount of C per unit of useful energy. Petroleum has 

roughly 75 percent of the C per unit of energy as coal, and 

natural gas has only about 55 percent.3 Producing a unit of 

Table 3-3: CO2 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO2 Eq.)

Fuel/Sector 1990 1995 2000 2001 2002 2003 2004

Coal 1,698.9 1,805.4 2,053.2 1,996.3 2,002.8 2,043.1 2,058.4 

Residential 2.9 1.7 1.0 1.0 1.1 1.2 1.2 

Commercial 11.8 11.1 8.2 8.4 8.4 7.9 9.7 

Industrial 152.3 143.0 133.5 133.5 123.4 124.0 126.2 

Transportation NE NE NE NE NE NE NE

Electricity Generation 1,531.3 1,648.7 1,909.6 1,852.3 1,868.3 1,906.2 1,917.6 

U.S. Territories 0.6 0.9 0.9 1.0 1.7 3.8 3.6 

Natural Gas 1,011.5 1,172.0 1,220.5 1,175.3 1,227.6 1,200.3 1,180.1 

Residential 239.8 264.4 270.6 260.3 265.0 277.5 264.5 

Commercial 143.1 165.4 172.7 165.1 171.0 176.7 170.0 

Industrial 416.3 474.4 460.0 425.0 447.2 433.0 415.5 

Transportation 36.1 38.4 35.7 34.1 37.2 33.4 32.0 

Electricity Generation 176.2 229.5 280.9 289.6 306.0 278.3 296.8 

U.S. Territories NO NO 0.7 1.2 1.2 1.4 1.3 

Petroleum 2,013.3 2,054.7 2,303.0 2,335.5 2,334.0 2,373.3 2,442.5 

Residential 97.4 90.5 100.5 102.2 94.4 104.2 102.5 

Commercial 61.2 49.3 47.2 48.8 43.4 51.8 50.9 

Industrial 276.3 259.0 266.8 294.0 284.3 299.1 316.0 

Transportation 1,449.0 1,561.0 1,762.5 1,741.6 1,791.7 1,774.2 1,824.4 

Electricity Generation 101.8 60.7 91.5 102.0 79.1 98.1 100.1 

U.S. Territories 27.6 34.0 34.6 46.8 41.1 45.8 48.6 

Geothermala 0.40 0.34 0.36 0.35 0.37 0.37 0.38 

Total 4,724.1 5,032.4 5,577.1 5,507.4 5,564.8 5,617.0 5,681.4 

NE (Not estimated)

NO (Not occurring)

a

 Although not technically a fossil fuel, geothermal energy-related CO2 emissions are included for reporting purposes.

Note: Totals may not sum due to independent rounding.

2005

2,094.1 

0.9 

9.2 

122.0 

NE

1,958.4 

3.7 

1,173.9 

262.7 

163.2 

394.5 

33.2 

319.1 

1.3 

2,462.7 

95.0 

49.6 

330.9 

1,836.7 

102.3 

48.2 

 0.38 

5,731.0 

2006

2,065.3 

0.6 

6.2 

122.0 

NE

1,932.4 

4.1 

1,155.1 

237.5 

154.1 

389.3 

33.2 

339.6 

1.4 

2,417.1 

88.5 

49.8 

350.9 

1,822.8 

55.7 

49.4 

 0.38 

5,637.9 

2An additional discussion of fossil fuel emission trends is presented in the 

Trends in U.S. Greenhouse Gas Emissions Chapter.

3 Based on national aggregate C content of all coal, natural gas, and 

petroleum fuels combusted in the United States.
Energy 3-5

Table 3-4: Annual Change in CO2 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors 

(Tg CO2 Eq. and Percent)

Sector Fuel Type 2002 to 2003 2003 to 2004 2004 to 2005 2005 to 2006

Electricity Generation Coal 38.0 2.0% 11.4 0.6% 40.8 2.1% -26.0 -1.3%

Electricity Generation Natural Gas -27.6 -9.0% 18.5 6.6% 22.3 7.5% 20.5 6.4%

Electricity Generation Petroleum 19.0 24.0% 2.0 2.0% 2.2 2.2% -46.6 -45.5%

Transportationa Petroleum -17.5 -1.0% 50.2 2.8% 12.3 0.7% -13.9 -0.8%

Residential Natural Gas 12.5 4.7% -12.9 -4.7% -1.9 -0.7% -25.2 -9.6%

Commercial Natural Gas 5.7 3.3% -6.7 -3.8% -6.8 -4.0% -9.1 -5.6%

Industrial Coal 0.6 0.5% 2.3 1.8% -4.3 -3.4% 0.1 0.1%

Industrial Natural Gas -14.2 -3.2% -17.5 -4.0% -21.0 -5.1% -5.2 -1.3%

All Sectorsb All Fuelsb 52.3 0.9% 64.3 1.1% 49.7 0.9% -93.1 -1.6%

a

 Excludes emissions from International Bunker Fuels.

b

 Includes fuels and sectors not shown in table.

Figure 3-4

U.S. Energy Consumption (Quadrillion Btu) 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

0

20

40

60

80

100

120

Fossil Fuels

Total Energy

Renewable & Nuclear

Energy Consumption (QBtu)

Note: Expressed as gross calorific values.

Figure 3-3

2006 U.S. Energy Consumption by Energy Source

Petroleum 39%

Coal 22%

Natural Gas 22%

Renewable 9%

Nuclear 8%

Figure 3-5

2006 CO2 Emissions from Fossil Fuel 

Combustion by Sector and Fuel Type

Natural Gas

Petroleum

Coal

0

500

1,000

1,500

2,000

2,500

Relative Contribution

by Fuel Type

Tg CO2 Eq.

U.S. 

Territories

Commercial Residential Industrial Transportation Electricity

Generation

Note: Electricity generation also includes emissions of less than 0.5 Tg CO2 Eq. from geothermal-based 

electricity generation.

heat or electricity using natural gas instead of coal can reduce 

the CO2 emissions associated with energy consumption, and 

using nuclear or renewable energy sources (e.g., wind) can 

essentially eliminate emissions (see Box 3-2). Table 3-4 

shows annual changes in emissions during the last five years 

for coal, petroleum, and natural gas in selected sectors.

In the United States, 82 percent of the energy consumed 

in 2006 was produced through the combustion of fossil fuels 

such as coal, natural gas, and petroleum (see Figure 3-3 and 

Figure 3-4). The remaining portion was supplied by nuclear 

electric power (8 percent) and by a variety of renewable 

energy sources (9 percent), primarily hydroelectric power 

and biofuels (EIA 2007a). Specifically, petroleum supplied 

the largest share of domestic energy demands, accounting 
3-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Box 3-1: Weather and Non-Fossil Energy Effects on CO2 from Fossil Fuel Combustion Trends

In 2006, weather conditions became warmer in the winter and slightly cooler in the summer, compared to 2005. The winter was 

significantly warmer than usual, with heating degree days in the United States 12 percent below normal (see Figure 3-6). Warmer winter 

conditions led to a decrease in demand for heating fuels. Summer temperatures were substantially warmer than usual, with cooling degree 

days 10 percent above normal (see Figure 3-7) (EIA 2007f),4

 however the demand for electricity only increased slightly due to the cooler 

summer conditions compared to 2005. 

Figure 3-7

Annual Deviations from Normal Cooling Degree Days for the United States (1950–2006)

-20

-15

-10

-5

0

5

10

15

20

Index Normal = 100

(Deviation from Normal)

Normal (1,242 Cooling Degree Days)

99% Confidence

1950195219541956

1958

196019621964196619681970197219741976197819801982198419861988199019921994199619982000200220042006

Note: Climatological normal data are highlighted. Statistical confidence interval for “normal” climatology period of 1971 through 2000.

Figure 3-6

Annual Deviations from Normal Heating Degree Days for the United States (1950–2006)

-15

-12

-9

-6

-3

0

3

6

9

12

19501952195419561958196019621964196619681970197219741976197819801982198419861988199019921994199619982000200220042006

Index Normal = 100

(Deviation from Normal)

Normal (4,524 Heating Degree Days)

99% Confidence

Note: Climatological normal data are highlighted. Statistical confidence interval for “normal” climatology period of 1971 through 2000.

4 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).

for an average of 43 percent of total fossil fuel based energy 

consumption in 2006. Coal and natural gas followed in 

order of importance, each accounting for 28 percent of total 

consumption. Petroleum was consumed primarily in the 

transportation end-use sector, the vast majority of coal was 

used in electricity generation, and natural gas was broadly 

consumed in all end-use sectors except transportation (see 

Figure 3-5) (EIA 2007a).

Fossil fuels are generally combusted for the purpose of 

producing energy for useful heat and work. During the 

combustion process, the C stored in the fuels is oxidized 

and emitted as CO2 and smaller amounts of other gases, 

including CH4, CO, and NMVOCs.5 These other C containing 

non-CO2 gases are emitted as a byproduct of incomplete fuel 

combustion, but are, for the most part, eventually oxidized 

to CO2 in the atmosphere. Therefore, it is assumed that all 

the C in fossil fuels used to produce energy is eventually 

converted to atmospheric CO2.

5 See the sections entitled Stationary Combustion and Mobile Combustion 

in this chapter for information on non-CO2 gas emissions from fossil fuel 

combustion.
Energy 3-7

Box 3-1: Weather and Non-Fossil Energy Effects on CO2 from Fossil Fuel Combustion Trends

Although no new U.S. nuclear power plants have been 

constructed in recent years, the utilization (i.e., capacity factors6) 

of existing plants in 2006 remained high at just under 90 percent. 

Electricity output by hydroelectric power plants increased in 2006 by 

approximately 7 percent. Electricity generated by nuclear plants in 

2006 provided almost three times as much of the energy consumed 

in the United States as hydroelectric plants (EIA 2007a). Aggregate 

nuclear and hydroelectric power plant capacity factors since 1973 

are shown in Figure 3-8.

(continued)

Figure 3-8

Aggregate Nuclear and Hydroelectric Power Plant 

Capacity Factors in the United States (1974–2006) 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

0

10

20

30

40

50

60

70

80

Capacity Factor

Nuclear

Hydro

6 The capacity factor is defined as the ratio of the electrical energy produced by a generating unit for a given period of time to the electrical energy that could 

have been produced at continuous full-power operation during the same period (EIA 2007a).

For the purpose of international reporting, the 

Intergovernmental Panel on Climate Change (IPCC) 

(IPCC/UNEP/OECD/IEA 1997) recommends that particular 

adjustments be made to national fuel consumption statistics. 

Certain fossil fuels can be manufactured into plastics, asphalt, 

lubricants, or other products. A portion of the C consumed for 

these non-energy products can be stored (i.e., sequestered) 

indefinitely. To account for the fact that the C in these fuels 

ends up in products instead of being combusted (i.e., oxidized 

and released into the atmosphere), consumption of fuels for 

non-energy purposes is estimated and subtracted from total 

fuel consumption estimates. Emissions from non-energy use 

of fuels are estimated in the Carbon Emitted and Stored in 

Products from Non-Energy Use of Fossil Fuels section in 

this chapter.

According to the UNFCCC reporting guidelines, CO2

emissions from the consumption of fossil fuels for aviation 

and marine international transport activities (i.e., international 

bunker fuels) should be reported separately, and not included 

in national emission totals. Estimates of international bunker 

fuel emissions for the United States are provided in Table 

3-5, and explained in detail later in the chapter.

End-Use Sector Consumption

An alternative method of presenting CO2 emissions is 

to allocate emissions associated with electricity generation 

to the sectors in which it is used. Four end-use sectors 

were defined: industrial, transportation, residential, and 

commercial. For the discussion below, electricity generation 

emissions have been distributed to each end-use sector based 

upon the sector’s share of national electricity consumption. 

This method of distributing emissions assumes that each 

sector consumes electricity generated from an equally 

carbon-intensive mix of fuels and other energy sources. 

After the end-use sectors are discussed, emissions from 

electricity generation are addressed separately. Emissions 

from U.S. territories are also calculated separately due to 

a lack of end-use-specific consumption data. Table 3-6 and

Table 3-5: CO2 Emissions from International Bunker Fuels (Tg CO2 Eq.)a

Vehicle Mode 1990 1995 2000 2001 2002 2003 2004 2005 2006

Aviation 45.7 50.2 59.9 58.7 61.1 58.8 64.9 67.5 71.1 

Marine 68.0 50.4 41.3 38.9 28.0 44.8 54.1 55.1 56.0 

Total 113.7 100.6 101.1 97.6 89.1 103.6 119.0 122.6 127.1 

a

 See International Bunker Fuels section for additional detail.

Note: Totals may not sum due to independent rounding.
3-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 3-6: CO2 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO2 Eq.)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Transportation 1,488.1 1,602.5 1,801.6 1,779.2 1,832.3 1,811.8 1,860.9 1,874.5 1,861.0

Combustion 1,485.1 1,599.4 1,798.2 1,775.6 1,828.9 1,807.6 1,856.4 1,869.8 1,856.0

Electricity 3.0 3.0 3.4 3.6 3.4 4.2 4.5 4.7 4.9

Industrial 1,527.5 1,589.5 1,645.1 1,583.9 1,572.5 1,592.1 1,596.8 1,579.6 1,567.1

Combustion 844.9 876.5 860.3 852.5 854.8 856.0 857.7 847.3 862.2

Electricity 682.5 713.1 784.7 731.4 717.7 736.1 739.0 732.3 704.9

Residential 929.5 995.5 1,129.7 1,121.8 1,145.6 1,178.3 1,173.1 1,206.4 1,151.9

Combustion 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5

Electricity 589.4 639.0 757.6 758.1 785.1 795.4 804.9 847.9 825.4

Commercial 750.8 810.0 964.6 973.5 970.3 983.8 997.1 1,017.3 1,003.0

Combustion 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1

Electricity 534.7 584.2 736.6 751.1 747.5 747.3 766.5 795.4 792.9

U.S. Territories 28.3 35.0 36.2 49.0 44.0 51.0 53.5 53.2 54.9

Total 4,724.1 5,032.4 5,577.1 5,507.4 5,564.8 5,617.0 5,681.4 5,731.0 5,637.9

Electricity Generation 1,809.6 1,939.3 2,282.3 2,244.3 2,253.7 2,283.1 2,314.9 2,380.2 2,328.2

Note: Totals may not sum due to independent rounding. Emissions from fossil fuel combustion by electricity generation are allocated based on 

aggregate national electricity consumption by each end-use sector.

Figure 3-9

2006 End-Use Sector Emissions of CO2 from 

Fossil Fuel Combustion

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

U.S. Transportation

Territories

Commercial Residential Industrial

From Electricity

Consumption

From Direct Fossil

Fuel Combustion

Tg CO2 Eq.

Figure 3-9 summarize CO2 emissions from direct fossil fuel 

combustion and pro-rated electricity generation emissions 

from electricity consumption by end-use sector.

Transportation End-Use Sector

The transportation end-use sector accounted for 1,861.0 

Tg CO2 in 2006, representing 33 percent of total CO2

emissions from fossil fuel combustion; the largest share of 

any end-use economic sector.7

 Fuel purchased in the United 

States for international aircraft and marine travel accounted 

for an additional 127.1 Tg CO2 in 2006; these emissions 

are recorded as international bunkers, and are not included 

in U.S. totals according to UNFCCC reporting protocols. 

Among domestic transportation sources, light duty vehicles 

(including passenger cars and light-duty trucks) represented 

62 percent of CO2 emissions, medium- and heavy-duty trucks 

22 percent, domestic commercial aircraft 7.6 percent, and 

other sources just over 8 percent. (See Table 3-7 for a detailed 

breakdown of CO2 emissions by mode and fuel type.)

Domestic transportation CO2 emissions increased by 

almost 25 percent (372.9 Tg) between 1990 and 2006, an 

annualized increase of 1.5 percent. From 2005 to 2006 

transportation CO2 emissions decreased by 0.7 percent. 

Almost all of the energy consumed by the transportation 

sector is petroleum-based, including motor gasoline, diesel 

fuel, jet fuel, and residual oil. Transportation sources 

also produce CH4 and N2O; these emissions are included 

beginning in Table 3-21 the “Mobile Combustion” section. 

Annex 3.2 presents total emissions from all transportation 

and mobile sources, including CO2, N2O, CH4, and HFCs. 

Carbon dioxide emissions from passenger cars and 

light-duty trucks totaled 1,151.3 Tg in 2006, an increase of 

7Note that electricity generation is the largest emitter of CO2 when electricity 

is not distributed among end-use sectors.
Energy 3-9

Table 3-7: CO2 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg CO2 Eq.)a

Fuel/Vehicle Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Gasoline 982.8 1,038.9 1,135.7 1,145.4 1,172.3 1,176.5 1,194.8 1,181.2 1,170.0

Passenger Cars 621.0 597.0 639.9 644.2 658.9 638.0 635.8 654.2 630.4

Light-Duty Trucks 308.9 389.9 446.0 449.4 461.3 491.5 511.6 476.0 488.0

Medium- and Heavy-Duty Trucksb 38.7 35.8 36.0 35.0 35.5 30.6 30.9 34.7 35.2

Buses 0.3 0.4 0.4 0.4 0.3 0.3 0.4 0.4 0.4

Motorcycles 1.7 1.8 1.8 1.7 1.7 1.6 1.7 1.6 1.9

Recreational Boats 12.1 14.1 11.6 14.6 14.6 14.5 14.4 14.3 14.1

Distillate Fuel Oil (Diesel) 272.7 325.1 401.0 401.6 415.1 421.8 447.2 462.2 472.1 

Passenger Cars 7.8 7.7 3.6 3.6 3.7 4.2 4.3 4.2 4.1 

Light-Duty Trucks 11.3 14.7 19.8 20.6 21.6 26.9 28.8 25.5 26.4 

Medium- and Heavy-Duty Trucksb 188.3 234.9 305.1 305.1 318.8 320.0 332.5 356.5 365.4 

Buses 7.9 8.6 10.1 9.2 8.7 9.4 13.4 10.6 10.9 

Rail 35.1 39.2 41.7 41.8 41.5 42.4 44.7 45.1 46.0 

Recreational Boats 1.9 2.3 2.7 2.8 2.9 3.0 3.0 3.1 3.205 

Ships and Other Boats 8.8 8.6 11.7 13.2 12.8 8.3 10.0 7.9 7.4 

Ships (Bunkers) 11.6 9.2 6.3 5.3 5.1 7.6 10.5 9.3 8.7

Jet Fuel 222.6 222.1 253.8 242.8 236.8 231.5 239.8 246.3 239.5

Commercial Aircraft–Domestic 136.7 143.1 164.2 152.9 146.1 143.9 142.9 150.4 142.1

Military Aircraft 33.9 23.5 20.5 22.5 20.4 19.9 20.4 16.9 14.8

General Aviation Aircraft 6.3 5.3 9.2 8.8 9.1 8.8 11.5 11.4 11.4

Aircraft (Bunkers) 45.7 50.2 59.9 58.7 61.1 58.8 64.9 67.5 71.1

Aviation Gasoline 3.1 2.7 2.5 2.4 2.3 2.1 2.2 2.4 2.3

General Aviation Aircraft 3.1 2.7 2.5 2.4 2.3 2.1 2.2 2.4 2.3

Residual Fuel Oil 80.1 71.7 69.9 46.1 53.3 45.0 58.3 66.0 64.9

Ships and Other Boatsc 23.7 30.5 34.9 12.6 30.5 7.8 14.7 20.2 17.7

Ships (Bunkers)c 56.4 41.2 35.0 33.6 22.8 37.2 43.6 45.8 47.2

Natural Gas 36.1 38.4 35.7 34.1 37.2 33.4 32.0 33.2 33.2

Passenger Cars + 0.1 + + + + + + +

Light-Duty Trucks + + + + + + + + +

Buses + 0.1 0.4 0.5 0.6 0.7 0.8 0.8 0.8

Pipeline 36.1 38.2 35.2 33.6 36.6 32.7 31.2 32.3 32.4

LPG 1.4 1.1 0.7 0.8 0.8 1.0 1.1 1.1 1.1

Light-Duty Trucks 0.5 0.5 0.3 0.3 0.3 0.4 0.4 0.4 0.4

Medium- and Heavy-Duty Trucksb 0.8 0.5 0.4 0.5 0.5 0.6 0.7 0.6 0.6

Buses + + + + + + + + +

Electricity 3.0 3.0 3.4 3.6 3.4 4.2 4.5 4.7 4.9

Rail 3.0 3.0 3.4 3.6 3.4 4.2 4.5 4.7 4.9

Total (Including Bunkers)d 1,601.8 1,703.1 1,902.7 1,876.8 1,921.4 1,915.4 1,979.8 1,997.1 1,988.1 

Total (Excluding Bunkers)d 1,488.1 1,602.5 1,801.6 1,779.2 1,832.3 1,811.8 1,860.9 1,874.5 1,861.0 

Note: Totals may not sum due to independent rounding. Emissions estimates for passenger cars, light-duty trucks, and heavy-duty trucks are calculated 

using fuel consumption data from FHWA’s Highway Statistics, which used an updated methodology to develop the 2005 and 2006 estimates This causes 

some discontinuity in the emissions estimates for gasoline and diesel on-road vehicles between 2004 and 2005.

a This table does not include emissions from non-transportation mobile sources, such as agricultural equipment and construction/mining equipment; it also 

does not include emissions associated with electricity consumption by pipelines or lubricants used in transportation. 

b Includes medium- and heavy-duty trucks over 8,500 lbs.

c Fluctuations in emission estimates from the combustion of residual fuel oil are associated with fluctuations in reported fuel consumption and may reflect 

data collection problems.

d Official estimates exclude emissions from the combustion of both aviation and marine international bunker fuels; however, estimates including 

international bunker fuel-related emissions are presented for informational purposes.

+ Less than 0.05 Tg CO2 Eq.
3-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

21 percent (200.1 Tg) from 1990. The increase in light-duty 

CO2 emissions is due primarily to the growth in vehicle 

travel, which substantially outweighed improvements in 

vehicle fuel economy. Light-duty vehicle miles traveled 

(VMT) increased 39 percent from 1990 to 2006; average 

vehicle fuel economy increased from 18.9 miles per gallon 

(mpg) in 1990 to 20.4 mpg in 2006, primarily reflecting 

the retirement of older vehicles. Among new vehicles sold 

annually, average fuel economy gradually declined from 

1990 to 2006 (Figure 3-10), reflecting substantial growth in 

sales of light-duty trucks relative to passenger cars (Figure 

3-11). Average new vehicle fuel economy improved in 2005 

and 2006 as the market share of passenger cars increased in 

response to rising fuel prices. 

Figure 3-10

Sales-Weighted Fuel Economy of New Automobiles 

and Light-Duty Trucks, 1990–2006

15

16

17

18

19

20

21

22

23

24

25

19901991199219931994199519961997199819992000200120022003200420052006

Miles per Gallon

Figure 3-11

Sales of New Automobiles and Light-Duty Trucks, 

1990–2006

2,000

4,000

6,000

8,000

10,000 Passenger Cars

Light Duty Trucks

Model Sales (’000)

19901991199219931994199519961997199819992000200120022003200420052006

Medium- and heavy-duty truck8 CO2 emissions 

increased by 76 percent (173.4 Tg) from 1990 to 2006, 

representing the largest percentage increase of any major 

transportation mode. Fuel economy for the medium- and 

heavy-duty truck fleet did not significantly improve over this 

period, and most likely declined from levels recorded in the 

late 1990s. Meanwhile, medium- and heavy-duty truck VMT 

increased by 52 percent. CO2 from the domestic operation 

of commercial aircraft increased by 4 percent (5.4 Tg) 

from 1990 to 2006, well below the growth in travel activity 

(passenger miles traveled grew by 69 percent from 1990 to 

2005, the most recent year of available data). The operational 

efficiency of commercial aircraft improved substantially 

because of a growing percentage of seats occupied per flight, 

improvements in the fuel efficiency of new aircraft, and the 

accelerated retirement of older, less fuel efficient aircraft. 

Across all categories of aviation9, CO2 emissions decreased 

by approximately 5.2 percent (9.4 Tg CO2) between 1990 and 

2006. This decline reflects a 56 percent decrease in emissions 

from domestic military operations, which more than offset a 

small increase in domestic commercial and general aviation 

emissions. For further information on all greenhouse gas 

emissions from transportation sources, please refer to Table 

A-108 in Annex 3.2.

Industrial End-Use Sector

The industrial end-use sector accounted for 28 percent 

of CO2 emissions from fossil fuel combustion. On average, 

55 percent of these emissions resulted from the direct 

consumption of fossil fuels for steam and process heat 

production. The remaining 45 percent was associated with 

their consumption of electricity for uses such as motors, 

electric furnaces, ovens, and lighting. 

The industrial end-use sector, per the underlying energy 

consumption data from EIA, includes activities such as 

manufacturing, construction, mining, and agriculture. The 

largest of these activities in terms of energy consumption 

is manufacturing, of which six industries—petroleum 

8 Includes “medium- and heavy-duty trucks” fueled by gasoline, diesel 

and LPG.

9 Includes consumption of jet fuel and aviation gasoline. Does not include 

aircraft bunkers, which are not accounted for in national emission totals.
Energy 3-11

refineries, chemicals, primary metals, paper, food, and 

nonmetallic mineral products—represent the vast majority 

of the energy use (EIA 2007a and EIA 2005). 

In theory, emissions from the industrial end-use sector 

should be highly correlated with economic growth and 

industrial output, but heating of industrial buildings and 

agricultural energy consumption are also affected by weather 

conditions.10 In addition, structural changes within the U.S. 

economy that lead to shifts in industrial output away from 

energy intensive manufacturing products to less energy 

intensive products (e.g., from steel to computer equipment) 

also have a significant affect on industrial emissions.

From 2005 to 2006, total industrial production and 

manufacturing output increased by 3.9 and 4.9 percent, 

respectively (FRB 2006). Over this period, output increased 

for petroleum refineries, chemicals, primary metals, food, 

and nonmetallic mineral products, but decreased slightly for 

paper (see Figure 3-12). 

Despite the growth in industrial output (62 percent) and 

the overall U.S. economy (59 percent) from 1990 to 2006, 

CO2 emissions from the industrial end-use sector increased 

by only 3.0 percent over that time. A number of factors are 

believed to have caused this disparity between rapid growth 

in industrial output and decrease in industrial emissions, 

including: (1) more rapid growth in output from less energyintensive industries relative to traditional manufacturing 

industries and (2) improvements in energy efficiency. In 

2006, CO2 emissions from fossil fuel combustion and 

electricity use within the industrial end-use sectors were 

1,571.0 Tg CO2 Eq., or 0.8 percent below 2005 emissions. 

Residential and Commercial End-Use Sectors

The residential and commercial end-use sectors 

accounted for an average 20 and 18 percent, respectively, of 

CO2 emissions from fossil fuel combustion. Both end-use 

sectors were heavily reliant on electricity for meeting energy 

needs, with electricity consumption for lighting, heating, 

air conditioning, and operating appliances contributing to 

about 72 and 79 percent of emissions from the residential 

and commercial end-use sectors, respectively. The remaining 

emissions were largely due to the direct consumption of 

natural gas and petroleum products, primarily for heating and 

cooking needs. Coal consumption was a minor component 

of energy use in both of these end-use sectors. In 2006, CO2

emissions from fossil fuel combustion and electricity use 

within the residential and commercial end-use sectors were 

1,151.9 Tg CO2 Eq. and 1,003.0 Tg CO2 Eq., respectively.

Emissions from the residential and commercial 

sectors have generally been increasing since 1990, and 

are often correlated with short-term fluctuations in energy 

consumption caused by weather conditions, rather than 

prevailing economic conditions (see Table 3-6). In the longterm, both end-use sectors are also affected by population 

growth, regional migration trends, and changes in housing 

and building attributes (e.g., size and insulation).

Emissions from natural gas consumption represent over 

72 and 73 percent of the direct (not including electricity) 

fossil fuel emissions from the residential and commercial 

sectors, respectively. In 2006, natural gas emissions 

decreased by 10 percent and 6 percent, respectively, in each 

of these sectors. The decrease in emissions in both sectors is 

a result of warmer conditions in the United States. 

Figure 3-12

Industrial Production Indices (Index 2002=100)

80

90

100

110

120

80

90

100

110

60

70

80

90

100

110

120

70

80

90

100

110

120

1990

1991

199219931994199519961997199819992000

2001

20022003200420052006

Paper

Foods

Total excluding Computers, 

Communications Equipment, 

and Semiconductors 

Total

Industrial

Index

Stone, Clay & Glass Products 

Chemicals

Petroleum Refineries

Primary Metals

10 Some commercial customers are large enough to obtain an industrial price 

for natural gas and/or electricity and are consequently grouped with the 

industrial end-use sector in U.S. energy statistics. These misclassifications 

of large commercial customers likely cause the industrial end-use sector to 

appear to be more sensitive to weather conditions.
3-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Electricity sales to the residential and commercial 

end-use sectors in 2006 decreased less than 1 percent in 

the residential sector and increased by 2 percent in the 

commercial sector. The trend in the commercial sector can 

largely be attributed to the growing economy (2.9 percent), 

which led to increased demand for electricity. Increased 

consumption due to the growing economy was somewhat 

offset by decreased air conditioning-related electricity 

consumption in the residential sector with the cooler summer 

compared to 2005, and increases in electricity prices. 

Electricity-related emissions in both the residential and 

commercial sectors decreased due to decreased consumption; 

total emissions from the residential sector decreased by 8.9 

percent in 2006, with emissions from the commercial sector 

5.3 percent lower than in 2005.

Electricity Generation

The process of generating electricity is the single largest 

source of CO2 emissions in the United States, representing 

39 percent of total CO2 emissions from all CO2 emissions 

sources across the United States. Electricity generation 

also accounted for the largest share of CO2 emissions from 

fossil fuel combustion, approximately 41 percent in 2006. 

Electricity was consumed primarily in the residential, 

commercial, and industrial end-use sectors for lighting, 

heating, electric motors, appliances, electronics, and air 

conditioning (see Figure 3-13).

The electric power industry includes all power producers, 

consisting of both regulated utilities and nonutilities (e.g. 

independent power producers, qualifying cogenerators, 

and other small power producers). For the underlying 

energy data used in this chapter, the Energy Information 

Administration (EIA) categorizes electric power generation 

into three functional categories: the electric power sector, 

the commercial sector, and the industrial sector. The electric 

power sector consists of electric utilities and independent 

power producers whose primary business is the production 

of electricity,11 while the other sectors consist of those 

producers that indicate their primary business is other than 

the production of electricity.

In 2006, the amount of electricity generated (in kWh) 

increased by 0.1 percent. This growth is due to the growing 

economy, expanding industrial production, and warmer 

summer conditions. However, CO2 emissions decreased by 

2.2 percent, as a smaller share of electricity was generated by 

coal and a greater share generated by natural gas. Coal and 

natural gas consumption for electricity generation decreased 

by 1.3 percent and increased by 6.4 percent, respectively, in 

2006, and nuclear power increased by less than 1 percent. 

As a result of the decrease in coal consumption, C intensity 

from direct fossil fuel combustion decreased slightly overall 

in 2006 (see Table 3-8). Coal is consumed primarily by the 

electric power sector in the United States, which accounted 

for 94 percent of total coal consumption for energy purposes 

in 2006. The amount of electricity generated from renewables 

increased by 8.1 percent in 2006.

Methodology

The methodology used by the United States for 

estimating CO2 emissions from fossil fuel combustion is 

conceptually similar to the approach recommended by the 

IPCC for countries that intend to develop detailed, sectoralbased emission estimates (IPCC 2006). A detailed description 

of the U.S. methodology is presented in Annex 2.1, and is 

characterized by the following steps:

1. Determine total fuel consumption by fuel type and 

sector. Total fossil fuel consumption for each year is 

estimated by aggregating consumption data by enduse 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 

Figure 3-13

Electricity Generation Retail Sales by End-Use Sector 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

400

600

800

1,000

1,200

1,400

1,600

Residential

Commercial

Industrial

Billion kWh

Note: The transportation end-use sector consumes minor quanties of electricity.

11 Utilities primarily generate power for the U.S. electric grid for sale to 

retail customers. Nonutilities produce electricity for their own use, to sell 

to large consumers, or to sell on the wholesale electricity market (e.g., to 

utilities for distribution and resale to customers).
Energy 3-13

obtained directly from the EIA of the U.S. Department 

of Energy (DOE), primarily from the Monthly Energy 

Review and published supplemental tables on petroleum 

product detail (EIA 2007b). The United States does 

not include territories in its national energy statistics, 

so fuel consumption data for territories were collected 

separately from Grillot (2007).12

For consistency of reporting, the IPCC has recommended 

that countries report energy data using the International 

Energy Agency (IEA) reporting convention and/or 

IEA data. Data in the IEA format are presented “top 

down”—that is, energy consumption for fuel types 

and categories are estimated from energy production 

data (accounting for imports, exports, stock changes, 

and losses). The resulting quantities are referred to 

as “apparent consumption.” The data collected in the 

United States by EIA, and used in this Inventory, are, 

instead, “bottom up” in nature. In other words, they are 

collected through surveys at the point of delivery or use 

and aggregated to determine national totals.13

It is also important to note that U.S. fossil fuel energy 

statistics are generally presented using gross calorific 

values (GCV) (i.e., higher heating values). Fuel 

consumption activity data presented here have not been 

adjusted to correspond to international standard, which 

are to report energy statistics in terms of net calorific 

values (NCV) (i.e., lower heating values).14

2. Subtract uses accounted for in the Industrial Processes 

chapter. Portions of the fuel consumption data for six 

fuel categories—coking coal, industrial other coal, 

petroleum coke, natural gas, residual fuel oil, and 

other oil—were reallocated to the industrial processes 

chapter, as they were consumed during non-energy 

related industrial activity. To make these adjustments, 

additional data were collected from AISI (1995 through 

2007), Gambogi (2007), Coffeyville Resources Nitrogen 

12 Fuel consumption by U.S. territories (i.e., American Samoa, Guam, 

Puerto Rico, U.S. Virgin Islands, Wake Island, and other U.S. Pacific 

Islands) is included in this report and contributed emissions of 55 Tg CO2

Eq. in 2006.

13 See IPCC Reference Approach for estimating CO2 emissions from fossil 

fuel combustion in Annex 4 for a comparison of U.S. estimates using topdown and bottom-up approaches.

14A 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.

Fertilizers, LLC (2007), Corathers (2007), U.S. Census 

Bureau (2007), EIA (2007h), EIA (2001), Smith, G. 

(2007), USGS (1998 through 2002), USGS (1995), 

USGS (1991a through 2006a), USGS (1991b through 

2006b), USGS (1991 through 2005), and USGS (1995 

through 2006).15

3. Adjust for biofuels, conversion of fossil fuels, and exports 

of CO2. Fossil fuel consumption estimates are adjusted 

downward to exclude (1) fuels with biogenic origins, 

(2) fuels created from other fossil fuels, and (3) exports 

of CO2. Fuels with biogenic origins are assumed to 

result in no net CO2 emissions, and must be subtracted 

from fuel consumption estimates. These fuels include 

ethanol added to motor gasoline and biomass gas used 

as natural gas. Synthetic natural gas is created from 

industrial coal, and is currently included in EIA statistics 

for both coal and natural gas. Therefore, synthetic natural 

gas is subtracted from energy consumption statistics.16

Since October 2000, the Dakota Gasification Plant has 

been exporting CO2 to Canada by pipeline. Since this 

CO2 is not emitted to the atmosphere in the United 

States, energy used to produce this CO2 is subtracted 

from energy consumption statistics. To make these 

adjustments, additional data for ethanol and biogas were 

collected from EIA (2007b) and data for synthetic natural 

gas were collected from EIA (2007e), and data for CO2

exports were collected from the Dakota Gasification 

Company (2006), Fitzpatrick (2002), Erickson (2003), 

EIA (2006), and EIA (2007e).

4. Adjust Sectoral Allocation of Distillate Fuel Oil 

and Motor Gasoline. EPA had conducted a separate 

bottom-up analysis of transportation fuel consumption 

based on FHWA Vehicle Miles Traveled (VMT) that 

indicated that the amount of distillate and motor gasoline 

consumption allocated to the transportation sector in the 

EIA statistics should be adjusted. Therefore, for these 

estimates, the transportation sector’s distillate fuel and 

motor gasoline consumption was adjusted higher to 

match the value obtained from the bottom-up analysis 

based on VMT. As the total distillate consumption 

15 See sections on Iron and Steel Production, Ammonia Production, 

Petrochemical Production, Titanium Dioxide Production, Ferroalloy 

Production, Aluminum Production, and Silicon Carbide Production in the 

Industrial Processes chapter.

16These adjustments are explained in greater detail in Annex 2.1.
3-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

estimate from EIA is considered to be accurate at the 

national level, the distillate consumption totals for the 

residential, commercial, and industrial sectors were 

adjusted downward proportionately. Similarly, as the 

total motor gasoline consumption estimate is considered 

to be accurate at the national level, the motor gasoline 

consumption totals for commercial and industrial sectors 

were adjusted downward proportionately. The data 

sources used in the bottom-up analysis of transportation 

fuel consumption include AAR (2007), Benson (2002 

through 2004), DOE (1993 through 2005), EIA (2007a), 

EIA (1991 through 2005), EPA (2004), and FHWA (1996 

through 2006).

5. Adjust for fuels consumed for non-energy use. U.S. 

aggregate energy statistics include consumption of 

fossil fuels for non-energy purposes. Depending on the 

end-use, this can result in storage of some or all of the C 

contained in the fuel for a period of time. As the emission 

pathways of C used for non-energy purposes are vastly 

different than fuel combustion, these emissions are 

estimated separately in the Carbon Emitted and Stored 

in Products from Non-Energy Use of Fossil Fuels 

section in this chapter. Therefore, the amount of fuels 

used for non-energy purposes was subtracted from total 

fuel consumption. Data on non-fuel consumption was 

provided by EIA (2007b).

6. Subtract consumption of international bunker fuels.

According to the UNFCCC reporting guidelines 

emissions from international transport activities, 

or bunker fuels, should not be included in national 

totals. U.S. energy consumption statistics include 

these bunker fuels (e.g., distillate fuel oil, residual 

fuel oil, and jet fuel) as part of consumption by the 

transportation end-use sector, however, so emissions 

from international transport activities were calculated 

separately following the same procedures used for 

emissions from consumption of all fossil fuels (i.e., 

estimation of consumption, and determination of C 

content).17 The Office of the Under Secretary of Defense 

(Installations and Environment) and the Defense Energy 

Support Center (Defense Logistics Agency) of the U.S. 

Department of Defense (DoD) (DESC 2007) supplied 

data on military jet fuel and marine fuel use. Commercial 

17 See International Bunker Fuels section in this chapter for a more detailed 

discussion.

jet fuel use was obtained from BEA (1991 through 2007) 

and DOT (1991 through 2007); residual and distillate 

fuel use for civilian marine bunkers was obtained from 

DOC (1991 through 2007) for 1990 through 2002, 

and DHS (2008) for 2003 through 2008. Consumption 

of these fuels was subtracted from the corresponding 

fuels in the transportation end-use sector. Estimates of 

international bunker fuel emissions are discussed further 

in the section entitled International Bunker Fuels. 

7. Determine the total C content of fuels consumed. Total 

C was estimated by multiplying the amount of fuel 

consumed by the amount of C in each fuel. This total C 

estimate defines the maximum amount of C that could 

potentially be released to the atmosphere if all of the 

C in each fuel was converted to CO2. The C content 

coefficients used by the United States were obtained 

from EIA’s Emissions of Greenhouse Gases in the United 

States 2006 (EIA 2007c) and EIA’s Monthly Energy 

Review and published supplemental tables on petroleum 

product detail EIA (EIA 2007b). They are presented in 

Annexes 2.1 and 2.2.

8. Estimate CO2 Emissions. Total CO2 emissions are the 

product of the adjusted energy consumption (from the 

previous methodology steps 1 through 6), the C content 

of the fuels consumed, and the fraction of C that is 

oxidized. The fraction oxidized was assumed to be 100 

percent for petroleum, coal, and natural gas based on 

guidance in IPCC (2006) (see Annex 2.1).

9. Allocate transportation emissions by vehicle type.

This report provides a more detailed accounting of 

emissions from transportation because it is such a 

large consumer of fossil fuels in the United States. 

For fuel types other than jet fuel, fuel consumption 

data by vehicle type and transportation mode were 

used to allocate emissions by fuel type calculated for 

the transportation end-use sector. 

•	 For on-road vehicles, annual estimates of combined 

motor gasoline and diesel fuel consumption by vehicle 

category were obtained from FHWA (1996 through 

2006); for each vehicle category, the percent gasoline, 

diesel, and other (e.g., CNG, LPG) fuel consumption are 

estimated using data from DOE (1993 through 2005). 
Energy 3-15

Box 3-2: Carbon Intensity of U.S. Energy Consumption

Fossil fuels are the dominant source of energy in the United States, and CO2 is emitted as a product from their combustion. Useful 

energy, however, is generated in the United States from many other sources that do not emit CO2 in the energy conversion process, such as 

renewable (i.e., hydropower, biofuels, geothermal, solar, and wind) and nuclear sources.18

Energy-related CO2 emissions can be reduced by not only lowering total energy consumption (e.g., through conservation measures) 

but also by lowering the C intensity of the energy sources employed (e.g., fuel switching from coal to natural gas). The amount of C emitted 

from the combustion of fossil fuels is dependent upon the C content of the fuel and the fraction of that C that is oxidized. Fossil fuels vary in 

their average C content, ranging from about 53 Tg CO2 Eq./QBtu for natural gas to upwards of 95 Tg CO2 Eq./QBtu for coal and petroleum 

coke.19 In general, the C content per unit of energy of fossil fuels is the highest for coal products, followed by petroleum, and then natural gas. 

Other sources of energy, however, may be directly or indirectly C neutral (i.e., 0 Tg CO2 Eq./Btu). Energy generated from nuclear and many 

renewable sources do not result in direct emissions of CO2. Biofuels such as wood and ethanol are also considered to be C neutral; although 

these fuels do emit CO2, in the long run the CO2 emitted from biomass consumption does not increase atmospheric CO2 concentrations if 

the biogenic C emitted is offset by the growth of new biomass.20 The overall C intensity of the U.S. economy is thus dependent upon the 

quantity and combination of fuels and other energy sources employed to meet demand.

Table 3-8 provides a time series of the C intensity for each sector of the U.S. economy. The time series incorporates only the energy 

consumed from the direct combustion of fossil fuels in each sector. For example, the C intensity for the residential sector does not include 

the energy from or emissions related to the consumption of electricity for lighting or wood for heat. Looking only at this direct consumption 

of fossil fuels, the residential sector exhibited the lowest C intensity, which is related to the large percentage of its energy derived from natural 

gas for heating. The C intensity of the commercial sector has predominantly declined since 1990 as commercial businesses shift away 

from petroleum to natural gas. The industrial sector was more dependent on petroleum and coal than either the residential or commercial 

sectors, and thus had higher C intensities over this period. The C intensity of the transportation sector was closely related to the C content 

of petroleum products (e.g., motor gasoline and jet fuel, both around 70 Tg CO2 Eq./EJ), which were the primary sources of energy. Lastly, 

the electricity generation sector had the highest C intensity due to its heavy reliance on coal for generating electricity. 

Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO2 Eq./QBtu)

Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Residentiala 57.3 56.6 56.7 56.9 56.6 56.8 56.9 56.6 56.7 

Commerciala 59.2 57.8 57.1 57.4 57.0 57.3 57.6 57.6 57.5 

Industriala 63.7 62.7 62.6 63.5 62.8 63.2 63.6 64.0 64.2 

Transportationa 71.0 71.0 71.0 71.0 71.0 71.0 71.0 71.1 71.1 

Electricity Generationb 86.7 86.0 85.6 85.2 85.0 85.7 85.4 85.0 84.6 

U.S. Territoriesc 74.1 74.1 73.2 73.6 73.7 74.0 74.6 74.6 74.6 

All Sectorsc 72.7 72.2 72.7 72.7 72.5 72.7 72.9 73.1 73.0 

a Does not include electricity or renewable energy consumption.

b Does not include electricity produced using nuclear or renewable energy.

c Does not include nuclear or renewable energy consumption.

Note: Excludes non-energy fuel use emissions and consumption. 

In contrast to Table 3-8, Table 3-9 presents C intensity values that incorporate energy consumed from all sources (i.e., fossil fuels, 

renewables, and nuclear). In addition, the emissions related to the generation of electricity have been attributed to both electricity generation 

and the end-use sectors in which that electricity was eventually consumed.21 This table, therefore, provides a more complete picture of the 

actual C intensity of each end-use sector per unit of energy consumed. The transportation end-use sector in Table 3-9 emerges as the most 

C intensive when all sources of energy are included, due to its almost complete reliance on petroleum products and relatively minor amount 

of biomass-based fuels used, such as ethanol. The “other end-use sectors” (i.e., residential, commercial, and industrial) use significant

18 Small quantities of CO2, however, are released from some geologic formations tapped for geothermal energy. These emissions are included with fossil 

fuel combustion emissions from 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.

19 One exajoule (EJ) is equal to 1018 joules or 0.9478 QBtu.

20 Net C fluxes from changes in biogenic C reservoirs in wooded or croplands are accounted for in the estimates for Land Use, Land-Use Change, 

and Forestry.

21 In other words, the emissions from the generation of electricity are intentionally double counted by attributing them both to electricity generation and the 

end-use sector in which electricity consumption occurred.
3-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Box 3-2: Carbon Intensity of U.S. Energy Consumption

quantities of biofuels such as wood, thereby lowering the overall C intensity. The C intensity of the electricity generation sector differs greatly 

from the scenario in Table 3-8, where only the energy consumed from the direct combustion of fossil fuels was included. This difference is 

due almost entirely to the inclusion of electricity generation from nuclear and hydropower sources, which do not emit CO2.

(continued)

Table 3-9: Carbon Intensity from all Energy Consumption by Se

Sector 1990 1995 2000

Transportationa 70.8 70.6 70.6 

ctor (Tg 

2001

70.5 

CO2 Eq./QBtu)

2002

70.5 

2003

70.3 

2004

70.2 

2005

70.1 

2006

70.0 

Other End-Use Sectorsa, b 57.5 56.4 57.7 58.4 57.6 58.0 58.0 58.2 57.5 

Electricity Generationc 59.0 57.9 59.9 

All Sectorsd 61.1 60.3 61.4 

a

 Includes electricity (from fossil fuel, nuclear, and renewable sources) and direct renew

60.2 

61.8 

able energy

59.2 

61.3 

 consumption.

59.8 

61.5 

59.6 

61.5 

59.9 

61.6 

58.8 

61.1 

b

 Other End-Use Sectors includes the residential, commercial, and industrial sectors. 

c

 Includes electricity generation from nuclear and renewable sources.

d

 Includes nuclear and renewable energy consumption. 

Note: Excludes non-energy fuel use emissions and consumption.

By comparing the values in Table 3-8 and Table 3-9, a few observations 

can be made. The use of renewable and nuclear energy sources has resulted 

in a significantly lower C intensity of the U.S. economy. Over the sixteenyear period of 1990 through 2006, however, the C intensity of U.S. energy 

consumption has been fairly constant, as the proportion of renewable and 

nuclear energy technologies have not changed significantly. Per capita energy 

consumption has fluctuated, but is now roughly equivalent to levels in 1990 

(see Figure 3-14). Due to a general shift from a manufacturing-based economy 

to a service-based economy, as well as overall increases in efficiency, energy 

consumption and energy-related CO2 emissions per dollar of gross domestic 

product (GDP) have both declined since 1990 (BEA 2007).

C intensity estimates were developed using nuclear and renewable 

energy data from EIA (2007a) and fossil fuel consumption data as discussed 

above and presented in Annex 2.1.

Figure 3-14

U.S. Energy Consumption and Energy-Related CO2

Emissions Per Capita and Per Dollar GDP

75

80

85

90

95

100

105

110

CO2 /Energy Consumption

CO2 /Capita

CO2 /$GDP

Energy

Consumption/

Capita 

Index (1990 = 100)

70

19901991199219931994199519961997199819992000200120022003200420052006

Energy Consumption/$GDP

•	 For non-road vehicles, activity data were obtained 

from AAR (2007), APTA (2007 and 2006), BEA (1991 

through 2007), Benson (2002 through 2004), DOE 

(1993 through 2005), DESC (2007), DOC (1991 through 

2007), DOT (1991 through 2007), EIA (2007a), EIA 

(2007d), EIA (2007g), EIA (2002), EIA (1991 through 

2005), EPA (2004), FAA (2005), and Gaffney (2007). 

•	 For jet fuel used by aircraft, CO2 emissions were 

calculated directly based on reported consumption of 

fuel as reported by EIA, and allocated to commercial 

aircraft using flight-specific fuel consumption data from 

the Federal Aviation Administration’s (FAA) System for 

assessing Aviation’s Global Emission (SAGE) model.22

Allocation to domestic general aviation was made 

using FAA Aerospace Forecast data, and allocation to 

domestic military uses was made using DoD data (see 

Annex 3.7).

Heat contents and densities were obtained from EIA 

(2007a) and USAF (1998).23

22 FAA’s System for assessing Aviation’s Global Emissions (SAGE) 

model develops aircraft fuel burn and emissions for all commercial flights 

globally in a given year. The SAGE model dynamically models aircraft 

performance, fuel burn, and emissions, and is based on actual flight-byflight aircraft movements. See <http://www.faa.gov/about/office_org/

headquarters_offices/aep/models/sage/>.

23 For a more detailed description of the data sources used for the analysis 

of the transportation end use sector see the Mobile Combustion (excluding 

CO2) and International Bunker Fuels sections of the Energy chapter, Annex 

3.2, and Annex 3.7.
Energy 3-17

Uncertainty

For estimates of CO2 from fossil fuel combustion, the 

amount of CO2 emitted is directly related to the amount of 

fuel consumed, the fraction of the fuel that is oxidized, and 

the carbon content of the fuel. Therefore, a careful accounting 

of fossil fuel consumption by fuel type, average carbon 

contents of fossil fuels consumed, and production of fossil 

fuel-based products with long-term carbon storage should 

yield an accurate estimate of CO2 emissions.

Nevertheless, there are uncertainties in the consumption 

data, carbon content of fuels and products, and carbon 

oxidation efficiencies. For example, given the same primary 

fuel type (e.g., coal, petroleum, or natural gas), the amount 

of carbon contained in the fuel per unit of useful energy 

can vary. For the United States, however, the impact of 

these uncertainties on overall CO2 emission estimates is 

believed to be relatively small. See, for example, Marland 

and Pippin (1990).

Although statistics of total fossil fuel and other energy 

consumption are relatively accurate, the allocation of this 

consumption to individual end-use sectors (i.e., residential, 

commercial, industrial, and transportation) is less certain. For 

example, for some fuels the sectoral allocations are based on 

price rates (i.e., tariffs), but a commercial establishment may 

be able to negotiate an industrial rate or a small industrial 

establishment may end up paying an industrial rate, leading 

to a misallocation of emissions. Also, the deregulation of 

the natural gas industry and the more recent deregulation of 

the electric power industry have likely led to some minor 

problems in collecting accurate energy statistics as firms in 

these industries have undergone significant restructuring.

To calculate the total CO2 emission estimate from 

energy-related fossil fuel combustion, the amount of 

fuel used in these non-energy production processes were 

subtracted from the total fossil fuel consumption for 2006. 

The amount of CO2 emissions resulting from non-energy 

related fossil fuel use has been calculated separately and 

reported in the Carbon Emitted from Non-Energy Use 

of Fossil Fuels section of this report. These factors all 

contribute to the uncertainty in the CO2 estimates. Detailed 

discussions on the uncertainties associated with C emitted 

from Non-Energy Use of Fossil Fuels can be found within 

that section of this chapter.

Various sources of uncertainty surround the estimation 

of emissions from international bunker fuels, which are 

subtracted from the U.S. totals (see the detailed discussions 

on these uncertainties provided in the International Bunker 

Fuels section of this chapter). Another source of uncertainty 

is fuel consumption by U.S. territories. The United States 

does not collect energy statistics for its territories at the 

same level of detail as for the fifty states and the District of 

Columbia. Therefore, estimating both emissions and bunker 

fuel consumption by these territories is difficult. 

Uncertainties in the emission estimates presented above 

also result from the data used to allocate CO2 emissions from 

the transportation end-use sector to individual vehicle types 

and transport modes. In many cases, bottom-up estimates of 

fuel consumption by vehicle type do not match aggregate 

fuel-type estimates from EIA. Further research is planned to 

improve the allocation into detailed transportation end-use 

sector emissions. In particular, residual fuel consumption 

data for marine vessels are highly uncertain, as shown by the 

large fluctuations in emissions that do not mimic changes in 

other variables such as shipping ton miles.

The uncertainty analysis was performed by primary fuel 

type for each end-use sector, using the IPCC-recommended 

Tier 2 uncertainty estimation methodology, Monte Carlo 

Simulation technique, with @RISK software. For this 

uncertainty estimation, the inventory estimation model for 

CO2 from fossil fuel combustion was integrated with the 

relevant inventory variables from the inventory estimation 

model for International Bunker Fuels, to realistically 

characterize the interaction (or endogenous correlation) 

between the variables of these two models. About 150 input 

variables were modeled for CO2 from energy-related Fossil 

Fuel Combustion (including about 10 for non-energy fuel 

consumption and about 20 for International Bunker Fuels). 

In developing the uncertainty estimation model, uniform 

distributions were assumed for all activity-related input 

variables and emission factors, based on the SAIC/EIA 

(2001) report.24 Triangular distributions were assigned for 

the oxidization factors (or combustion efficiencies). The 

24 SAIC/EIA (2001) characterizes the underlying probability density 

function for the input variables as a combination of uniform and normal 

distributions (the former to represent the bias component and the latter to 

represent the random component). However, for purposes of the current 

uncertainty analysis, it was determined that uniform distribution was more 

appropriate to characterize the probability density function underlying each 

of these variables.
3-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

uncertainty ranges were assigned to the input variables 

based on the data reported in SAIC/EIA (2001) and on 

conversations with various agency personnel.25

The uncertainty ranges for the activity-related input 

variables were typically asymmetric around their inventory 

estimates; the uncertainty ranges for the emissions factors 

were symmetric. Bias (or systematic uncertainties) associated 

with these variables accounted for much of the uncertainty 

associated with these variables (SAIC/EIA 2001).26 For 

purposes of this uncertainty analysis, each input variable was 

simulated 10,000 times through Monte Carlo Sampling. 

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 3-10. Fossil fuel combustion CO2

emissions in 2006 were estimated to be between 5,542.9 and 

5,944.7 Tg CO2 Eq. at a 95 percent confidence level. This 

Table 3-10: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Energy-Related Fossil Fuel 

Combustion by Fuel Type and Sector (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Fuel/Sector (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Coalb 2,065.3 1,996.8 2,262.1 -3% +10%

Residential 0.6 0.5 0.7 -6% +15%

Commercial 6.2 5.9 7.1 -5% +15%

Industrial 122.0 117.3 142.4 -4% +17%

Transportation NE NE NE NA NA

Electricity Generation 1,932.4 1,856.4 2,119.9 -4% +10%

U.S. Territories 4.1 3.6 4.9 -12% +19%

Natural Gasb 1,155.1 1,164.8 1,231.2 +1% +7%

Residential 237.5 230.8 254.2 -3% +7%

Commercial 154.1 149.7 164.9 -3% +7%

Industrial 389.3 399.5 440.0 +3% +13%

Transportation 33.2 32.3 35.5 -3% +7%

Electricity Generation 339.6 329.6 356.9 -3% +5%

U.S. Territories 1.4 1.2 1.6 -12% +17%

Petroleumb 2,417.1 2,282.9 2,554.7 -6% +6%

Residential 88.5 83.8 92.8 -5% +5%

Commercial 49.8 47.5 51.8 -5% +4%

Industrial 350.9 305.2 407.1 -13% +16%

Transportation 1,822.8 1,700.5 1,940.0 -7% +6%

Electricity Generation 55.7 53.3 59.7 -4% +7%

U.S. Territories 49.4 45.6 54.9 -8% +11%

Total (excluding Geothermal)b 5,637.6 5,542.5 5,944.3 -2% +5%

Geothermal 0.4 NE NE NE NE

Total (including Geothermal)b,c 5,637.9 5,542.9 5,944.7 -2% +5%

NA (Not Applicable)

NE (Not Estimated)

a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

b The low and high estimates for total emissions were calculated separately through simulations and, hence, the low and high emission estimates for the 

sub-source categories do not sum to total emissions.

c Geothermal emissions added for reporting purposes, but an uncertainty analysis was not performed for CO2 emissions from geothermal production.

Note: Totals may not sum due to independent rounding.

25 In the SAIC/EIA (2001) report, the quantitative uncertainty estimates 

were developed for each of the three major fossil fuels used within each 

end-use sector; the variations within the sub-fuel types within each end-use 

sector were not modeled. However, for purposes of assigning uncertainty 

estimates to the sub-fuel type categories within each end-use sector in 

the current uncertainty analysis, SAIC/EIA (2001)-reported uncertainty 

estimates were extrapolated. 

26Although, 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

indicates a range of 2 percent below to 5 percent above the 

2006 emission estimate of 5,637.9 Tg CO2 Eq. 

QA/QC and Verification

A source-specific QA/QC plan for CO2 from fossil fuel 

combustion was developed and implemented. This effort 

included a Tier 1 analysis, as well as portions of a Tier 2 

analysis. The Tier 2 procedures that were implemented 

involved checks specifically focusing on the activity data and 

methodology used for estimating CO2 emissions from fossil 

fuel combustion in the United States. Emission totals for the 

different sectors and fuels were compared and trends were 

investigated to determine whether any corrective actions 

were needed. Minor corrective actions were taken.

Recalculations Discussion 

The Energy Information Administration (EIA 2007b) 

updated energy consumption data for all years. These 

revisions primarily impacted the emission estimates for 

2005. Overall, these changes resulted in an average annual 

increase of 0.8 Tg CO2 Eq. (less than 0.1 percent) in CO2

emissions from fossil fuel combustion for the period 1990 

through 2005.

Planned Improvements

To reduce uncertainty of CO2 from fossil fuel combustion 

estimates, efforts will be taken to work with EIA and other 

agencies to improve the quality of the U.S. territories data. 

This improvement is not all-inclusive, and is part of an 

ongoing analysis and efforts to continually improve the CO2

from fossil fuel combustion estimates. In addition, further 

expert elicitation may be conducted to better quantify the total 

uncertainty associated with emissions from this source.

3.2. Carbon Emitted from NonEnergy Use of Fossil Fuels (IPCC 

Source Category 1A) 

In addition to being combusted for energy, fossil 

fuels are also consumed for non-energy use (NEU) in 

the United States. The fuels used for these purposes are 

diverse, including natural gas, liquefied petroleum gases 

(LPG), asphalt (a viscous liquid mixture of heavy crude 

oil distillates), petroleum coke (manufactured from heavy 

oil), and coal coke (manufactured from coking coal). 

The non-energy applications are equally diverse, and 

include feedstocks for the manufacture of plastics, rubber, 

synthetic fibers and other materials; reducing agents for 

the production of various metals and inorganic products; 

and non-energy products such as lubricants, waxes, and 

asphalt (IPCC 2006). 

CO2 emissions arise from non-energy use 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 C consumed for non-energy purposes 

was stored in products, and not released to the atmosphere; 

the remaining 38 percent was emitted. 

There are several areas in which non-energy use of fossil 

fuels are closely related to other parts of the Inventory. For 

example, some of the NEU products release CO2 at the end of 

their commercial life when they are combusted after disposal; 

these emissions are reported separately within the Energy 

chapter in the Municipal Solid Waste Combustion source 

category. In addition, there is some overlap between fossil 

fuels consumed for non-energy use and the fossil-derived 

CO2 emissions accounted for in the Industrial Processes 

chapter, especially for fuels used as reducing agents. To avoid 

double-counting, the “raw” non-energy fuel consumption 

data reported by EIA are modified to account for these 

overlaps. There are also net exports of petrochemicals that 

are not completely accounted for in the EIA data, and these 

affect the mass of C in non-energy applications.

As shown in Table 3-11, fossil fuel emissions in 2006 

from the non-energy use of fossil fuels were 138.0 Tg CO2

Eq., which constituted approximately 2 percent of overall 

fossil fuel emissions, approximately the same proportion as 

in 1990. In 2006, the consumption of fuels for non-energy 

use (after the adjustments described above) was 5,417.8 

TBtu, an increase of 21 percent since 1990 (see Table 3-12). 

About 65.4 Tg of the C (239.6 Tg CO2 Eq.) in these fuels 

was stored, while the remaining 37.6 Tg C (138.0 Tg CO2

Eq.) was emitted. The proportion of C emitted as CO2 has 

remained about constant since 1990, at about 36 to 40 percent 

of total non-energy consumption (see Table 3-11).
3-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 3-11: CO2 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO2 Eq.)

Emissions/Storage 1990 1995 2000

Potential Emissions 312.6 346.8 385.5 

2001

364.8 

2002

368.4 

2003

356.3 

2004

394.9 

2005

382.2 

2006

377.6 

C Stored 195.5 213.5 244.1 232.9 232.6 224.5 246.0 243.1 239.6 

Emissions as a % of Potential 37% 38% 37%

Emissions 117.2 133.2 141.4

Note: Totals may not sum due to independent rounding.

36%

131.9

37%

135.9

37%

131.8

38%

148.9

36%

139.1

37%

138.0

Methodology

The first step in estimating C stored in products was to 

determine the aggregate quantity of fossil fuels consumed 

for non-energy use. The C content of these feedstock fuels 

is equivalent to potential emissions, or the product of 

consumption and the fuel-specific C content values. Both 

the non-energy fuel consumption and C content data were 

supplied by the EIA (2007) (see Annex 2.1). Consumption 

of natural gas, LPG, pentanes plus, naphthas, other oils, and 

special naphtha were adjusted to account for net exports of 

these products that are not reflected in the raw data from EIA. 

Consumption values for industrial coking coal, petroleum 

coke, other oils, and natural gas in Table 3-12 and Table 

3-13 have been adjusted to subtract non-energy uses that are 

included in the source categories of the Industrial Processes 

chapter.27 Consumption values were also adjusted to subtract 

exports of intermediary chemicals.

For the remaining non-energy uses, the quantity of C 

stored was estimated by multiplying the potential emissions 

by a storage factor. For several fuel types—petrochemical 

feedstocks (including natural gas for non-fertilizer uses, LPG, 

pentanes plus, naphthas, other oils, still gas, special naphtha, 

and industrial other coal), asphalt and road oil, lubricants, 

and waxes—U.S. data on C stocks and flows were used to 

develop C storage factors, calculated as the ratio of (a) the 

C stored by the fuel’s non-energy products to (b) the total 

C content of the fuel consumed. A lifecycle approach was 

used in the development of these factors in order to account 

for losses in the production process and during use. Because 

losses associated with municipal solid waste management are 

handled separately in this sector under the Municipal Solid 

Waste Combustion source category, the storage factors do not 

account for losses at the disposal end of the life cycle. For 

industrial coking coal and distillate fuel oil, storage factors 

were taken from IPCC/UNEP/OECD/IEA (1997), which in 

turn draws from Marland and Rotty (1984). For the remaining 

fuel types (petroleum coke, miscellaneous products, and 

other petroleum), IPCC does not provide guidance on storage 

factors, and assumptions were made based on the potential 

fate of C in the respective NEU products.

Lastly, emissions were estimated by subtracting the C 

stored from the potential emissions (see Table 3-11). More 

detail on the methodology for calculating storage and emissions 

from each of these sources is provided in Annex 2.3.

Where storage factors were calculated specifically for 

the United States, data were obtained on (1) products such as 

asphalt, plastics, synthetic rubber, synthetic fibers, cleansers 

(soaps and detergents), pesticides, food additives, antifreeze 

and deicers (glycols), and silicones and (2) industrial 

releases including volatile organic compound, solvent, and 

non-combustion CO emissions, Toxics Release Inventory 

(TRI) releases, hazardous waste incineration, and energy 

recovery. Data were taken from a variety of industry sources, 

government reports, and expert communications. Sources 

include EPA reports and databases such as compilations of 

air emission factors (EPA 1995, 2001), National Air Quality 

and Emissions Trends Report (EPA 2006a), Toxics Release 

Inventory, 1998 (2000a), Biennial Reporting System (EPA 

2004a, 2006b, 2007), and pesticide sales and use estimates 

(EPA 1998, 1999, 2002, 2004b); the EIA Manufacturer’s 

Energy Consumption Survey (MECS) (EIA 1994, 1997, 

2001, 2005); the National Petrochemical & Refiners 

Association (NPRA 2001); the National Asphalt Pavement 

Association (Connolly 2000); the Emissions Inventory 

Improvement Program (EIIP 1998, 1999); the U.S. Census 

Bureau (1999, 2003, 2004); the American Plastics Council 

(APC 2000, 2001, 2003, 2005, 2006; Eldredge-Roebuck 

2000); the Society of the Plastics Industry (SPI 2000); 

Bank of Canada (2006); Financial Planning Association 

27 These source categories include Iron and Steel Production, Lead 

Production, Zinc Production, Ammonia Production, Carbon Black 

Production (included in Petrochemical Production), Titanium Dioxide 

Production, Ferroalloy Production, Silicon Carbide Production, and 

Aluminum Production. 
Energy 3-21

Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Use (TBtu)

Sector/Fuel Type 1990 1995 2000

Industry 4,221.2 4,771.8 5,261.1

2001

5,044.4

2002

5,032.4

2003

4,865.3

2004

5,308.4

2005

5,210.0

2006

5,160.5

Industrial Coking Coal 0.0 43.9 62.8 25.6 46.5 72.1 214.7 109.7 85.9

Industrial Other Coal 8.2 11.3 12.4

Natural Gas to Chemical Plants, 

11.3 12.0 11.9 11.9 11.9 12.4

Other Uses 276.0 330.4 421.1 407.8 364.6 352.0 360.2 390.3 403.2

Asphalt & Road Oil 1,170.2 1,178.2 1,275.7 1,256.9 1,239.9 1,219.5 1,303.8 1,323.2 1,225.6

LPG 1,119.0 1,484.7 1,604.6 1,539.0 1,565.4 1,437.8 1,436.7 1,442.0 1,491.8

Lubricants 186.3 177.8 189.9 174.0 171.9 159.0 161.0 160.2 130.6

Pentanes Plus 77.3 285.3 228.7 199.8 166.1 158.3 156.5 146.0 105.1

Naphtha (<401° F) 325.7 350.6 592.8 489.4 564.2 573.4 687.9 678.6 592.9

Other Oil (>401° F) 677.2 612.7 554.3 525.9 456.2 501.0 547.8 518.7 573.4

Still Gas 21.3 40.1 12.6 35.8 57.8 59.0 63.5 67.7 122.3

Petroleum Coke 81.0 44.1 47.8 128.1 110.2 76.9 161.3 145.0 178.7

Special Naphtha 100.9 66.9 94.4 77.9 99.5 75.7 47.2 60.9 68.7

Distillate Fuel Oil 7.0 8.0 11.7 11.7 11.7 11.7 11.7 11.7 11.7

Waxes 33.3 40.6 33.1 36.3 32.2 31.0 30.8 31.4 25.2

Miscellaneous Products 137.8 97.1 119.2 124.9 134.2 126.0 113.4 112.8 133.2

Transportation 176.0 167.9 179.4 164.3 162.4 150.1 152.1 151.3 147.0

Lubricants 176.0 167.9 179.4 164.3 162.4 150.1 152.1 151.3 147.0

U.S. Territories 86.7 90.8 165.5 80.3 138.6 127.9 110.8 107.6 110.3

Lubricants 0.7 2.0 16.4 + 1.5 9.3 5.1 5.2 5.4

Other Petroleum (Misc. Prod.) 86.0 88.8 149.1 80.3 137.2 118.6 105.7 102.4 104.9

Total 4,483.9 5,030.6 5,605.9 5,289.0 5,333.4 5,143.4 5,571.3 5,468.9 5,417.8

+ Does not exceed 0.05 TBtu

Note: To avoid double-counting, coal coke, petroleum coke, natural gas consumption, and other oils are adjusted for industrial process consumption 

reported in the Industrial Processes sector. Natural gas, LPG, Pentanes Plus, Naphthas, Special Naphtha, and Other Oils are adjusted to account for exports 

of chemical intermediates derived from these fuels. For residual oil (not shown in the table), all non-energy use is assumed to be consumed in C black 

production, which is also reported in the Industrial Processes chapter. 

Note: Totals may not sum due to independent rounding.

(2006); INEGI (2006); Statistics Canada (2006); the United 

States International Trade Commission (2006, 2007); the 

Pesticide Action Network (PAN 2002); Gosselin, Smith, 

and Hodge (1984); the Rubber Manufacturers’ Association 

(RMA 2002, 2006; STMC 2003); the International Institute 

of Synthetic Rubber Products (IISRP 2000, 2003); the Fiber 

Economics Bureau (FEB 2001, 2003, 2005 through 2007); 

the Material Safety Data Sheets (Miller 1999); the Chemical 

Manufacturer’s Association (CMA 1999); and the American 

Chemistry Council (ACC 2005 through 2007) Specific data 

sources are listed in full detail in Annex 2.3.

Uncertainty 

An uncertainty analysis was conducted to quantify the 

uncertainty surrounding the estimates of emissions and storage 

factors from non-energy uses. This analysis, performed 

using @RISK software and the IPCC-recommended Tier 2 

methodology (Monte Carlo Simulation technique), provides 

for the specification of probability density functions for key 

variables within a computational structure that mirrors the 

calculation of the inventory estimate. The results presented 

below provide the 95 percent confidence interval, the range 

of values within which emissions are likely to fall, for this 

source category. 

As noted above, the non-energy use analysis is based 

on U.S.-specific storage factors for (1) feedstock materials 

(natural gas, LPG, pentanes plus, naphthas, other oils, still 

gas, special naphthas, and other industrial coal), (2) 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 
3-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 3-13: 2006 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions 

Adjusted Carbon 

Non-Energy Content Potential Carbon

Usea Coefficient Carbon Storage Stored

Sector/Fuel Type (TBtu) (Tg C/QBtu) (Tg C) Factor (Tg C)

Carbon

Emissions

(Tg C)

Carbon

Emissions

(Tg CO2 Eq.)

Industry 5,160.5 - 97.8 - 64.9 32.9 120.8

Industrial Coking Coal 85.9 31.00 2.7 0.10 0.3 2.4 8.8 

Industrial Other Coal 12.4 25.63 0.3 0.62 0.2 0.1 0.4 

Natural Gas to Chemical Plants 403.2 14.47 5.8 0.62 3.6 2.2 8.2 

Asphalt & Road Oil 1,225.6 20.62 25.3 1.00 25.3 0.0 0.0 

LPG 1,491.8 16.78 25.0 0.62 15.4 9.6 35.3 

Lubricants 130.6 20.24 2.6 0.09 0.2 2.4 8.8 

Pentanes Plus 105.1 18.24 1.9 0.62 1.2 0.7 2.7 

Naphtha (<401° F) 592.9 18.14 10.8 0.62 6.6 4.1 15.2 

Other Oil (>401° F) 573.4 19.95 11.4 0.62 7.0 4.4 16.1 

Still Gas 122.3 17.51 2.1 0.62 1.3 0.8 3.0 

Petroleum Coke 178.7 27.85 5.0 0.50 2.5 2.5 9.1 

Special Naphtha 68.7 19.86 1.4 0.62 0.8 0.5 1.9 

Distillate Fuel Oil 11.7 19.95 0.2 0.50 0.1 0.1 0.4 

Waxes 25.2 19.81 0.5 0.58 0.3 0.2 0.8 

Miscellaneous Products 133.2 20.33 2.7 0.00 0.0 2.7 9.9 

Transportation 147.0 - 3.0 - 0.3 2.7 9.9 

Lubricants 147.0 20.24 3.0 0.09 0.3 2.7 9.9 

U.S. Territories 110.3 - 2.2 - 0.2 2.0 7.3 

Lubricants 5.4 20.24 0.1 0.09 + 0.1 0.4 

Other Petroleum (Misc. Prod.) 104.9 20.00 2.1 0.10 0.2 1.89 6.9 

Total 5,417.8 103.0 65.4 37.6 138.0 

+ Does not exceed 0.05 TBtu

- Not applicable.

a To avoid double counting, exports have been deducted.

Note: Totals may not sum due to independent rounding.

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 use of 

fossil fuels in 2006 was estimated to be between 110.2 and 

150.3 Tg CO2 Eq. at a 95 percent confidence level. This 

indicates a range of 20 percent below to 9 percent above the 

2006 emission estimate of 138.0 Tg CO2 Eq. The uncertainty 

in the emission estimates is a function of uncertainty in both 

the quantity of fuel used for non-energy purposes and the 

storage factor. 

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 wellcharacterized, 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 
Energy 3-23

Table 3-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Non-Energy Uses of Fossil Fuels 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Feedstocks CO2 83.0 66.4 99.5 -20% +20%

Asphalt CO2 0.0 0.1 0.7 NA NA

Lubricants CO2 19.1 15.7 22.1 -17% +16%

Waxes CO2 0.8 0.6 1.2 -23% +59%

Other CO2 35.2 16.5 38.3 -53% +9%

Total CO2 138.0 110.2 150.3 -20% +9%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

NA (Not Applicable)

Note: Totals may not sum due to independent rounding.

Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels 

(Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Feedstocks CO2 62% 59% 64% -4% +3%

Asphalt CO2 100% 99% 100% -1% +0%

Lubricants CO2 9% 4% 18% -58% +89%

Waxes CO2 58% 44% 69% -24% +19%

Other CO2 24% 20% 64% -17% +162%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval, as a percentage of the inventory value 

(also expressed in percent terms).

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 use of 

fossil fuels was developed and implemented. This effort 

included a Tier 1 analysis, as well as portions of a Tier 

2 analysis for non-energy uses involving petrochemical 

feedstocks and for imports and exports. The Tier 2 procedures 

that were implemented involved checks specifically focusing 

on the activity data and methodology for estimating the fate 

of C (in terms of storage and emissions) across the various 

end-uses of fossil C. Emission and storage totals for the 

different subcategories were compared, and trends across 

the time series were analyzed to determine whether any 

corrective actions were needed. Corrective actions were taken 

to rectify minor errors and to improve the transparency of 

the calculations, facilitating future QA/QC.

For petrochemical import and export data, special 

attention was paid to NAICS numbers and titles to verify 

that none had changed or been removed. Import and export 

totals were compared for 2006 as well as their trends across 

the time series.

Planned Improvements

There are several improvements planned for the 

future:

•	 Future updates in line with the 2006 IPCC Guidelines. 

These changes could affect both the non-energy use and 

industrial processes sections.

•	 Improving the uncertainty analysis. Most of the input 

parameter distributions are based on professional 

judgment rather than rigorous statistical characterizations 

of uncertainty. 

•	 Better characterizing flows of fossil C. Additional “fates” 

may be researched, including the fossil C load in organic 

chemical wastewaters, plasticizers, adhesives, films, 
3-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

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 nonenergy fuel types (industrial coking coal and distillate oil), 

and broad assumptions are being used for the remaining 

fuels (petroleum coke, miscellaneous products, and other 

petroleum). Over the long term, there are plans to improve 

these storage factors by conducting analyses of C fate similar 

to those described in Annex 2.3.

3.3. Stationary Combustion 

(excluding CO2) (IPCC Source 

Category 1A)

Stationary combustion encompasses all fuel combustion 

activities from fixed sources (versus mobile combustion). 

Other than CO2, which was addressed in the previous section, 

gases from stationary combustion include the greenhouse 

gases CH4 and N2O and the indirect greenhouse gases NOx, 

CO, and NMVOCs.28 Emissions of these gases from stationary 

combustion sources depend upon fuel characteristics, size 

and vintage, along with combustion technology, pollution 

control equipment, and ambient environmental conditions. 

Emissions also vary with operation and maintenance 

practices.

N2O emissions from stationary combustion are closely 

related to air-fuel mixes and combustion temperatures, as 

well as the characteristics of any pollution control equipment 

that is employed. CH4 emissions from stationary combustion 

are primarily a function of the CH4 content of the fuel and 

combustion efficiency.

Emissions of CH4 decreased 16 percent overall since 

1990 to 6.2 Tg CO2 Eq. (296 Gg) in 2006. This decrease in 

CH4 emissions was primarily due to lower wood consumption 

in the residential sector. Conversely, N2O emissions rose 13 

percent since 1990 to 14.5 Tg CO2 Eq. (47 Gg) in 2006. The 

largest source of N2O emissions was coal combustion by 

electricity generators, which alone accounted for 66 percent 

28 Sulfur dioxide (SO2) emissions from stationary combustion are addressed 

in Annex 6.3.

of total N2O emissions from stationary combustion in 2006. 

Overall, however, stationary combustion is a small source 

of CH4 and N2O in the United States.

Table 3-16 and Table 3-17 provide CH4 and N2O 

emission estimates in Tg CO2 Eq.; Table 3-18 and Table 3-19 

present these estimates in Gg of each gas.

Methodology

CH4 and N2O emissions were estimated by multiplying 

fossil fuel and wood consumption data by emission factors 

(by sector and fuel type). National coal, natural gas, fuel 

oil, and wood consumption data were grouped by sector: 

industrial, commercial, residential, electricity generation, 

and U.S. territories. For the CH4 and N2O estimates, fuel 

consumption data for coal, natural gas, fuel oil for the United 

States were obtained from EIA’s Monthly Energy Review 

and unpublished supplemental tables on petroleum product 

detail (EIA 2007a). Wood consumption data for the United 

States was obtained from EIA’s Annual Energy Review (EIA 

2007b). Because the United States does not include territories 

in its national energy statistics, fuel consumption data for 

territories were provided separately by Grillot (2007).29 Fuel 

consumption for the industrial sector was adjusted to subtract 

out construction and agricultural use, which is reported 

under mobile sources.30 Construction and agricultural fuel 

use was obtained from EPA (2004). Estimates for wood 

biomass consumption for fuel combustion do not include 

wood wastes, liquors, municipal solid waste, tires, etc. that 

are reported as biomass by EIA. 

Emission factors for the four end-use sectors were provided 

by the 2006 IPCC Guidelines for National Greenhouse Gas 

Inventories (IPCC 2006). U.S. territories’ emission factors 

were estimated using the U.S. emission factors for the primary 

sector in which each fuel was combusted. 

More detailed information on the methodology for 

calculating emissions from stationary combustion, including 

emission factors and activity data, is provided in Annex 3.1.

29 U.S. territories data also include combustion from mobile activities 

because data to allocate territories’ energy use were unavailable. For this 

reason, CH4 and N2O emissions from combustion by U.S. territories are 

only included in the stationary combustion totals.

30Though emissions from construction and farm use occur due to both 

stationary and mobile sources, detailed data were not available to determine 

the magnitude from each. Currently, these emissions are assumed to be 

predominantly from mobile sources.
Energy 3-25

Table 3-16: CH4 Emissions from Stationary Combustion (Tg CO2 Eq.)

Sector/Fuel Type 1990 1995 2000

Electric Power 0.6 0.6 0.7 

2001

0.7 

2002

0.7 

2003

0.7 

2004

0.7 

2005

0.7 

2006

0.7 

Coal 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 

Fuel Oil 0.1 + 0.1 0.1 0.1 0.1 0.1 0.1 + 

Natural gas 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Wood 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Industrial 1.5 1.6 1.6 1.5 1.4 1.4 1.5 1.5 1.5 

Coal 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Fuel Oil 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 

Natural gas 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.1 

Wood 0.9 1.0 1.0 0.9 0.8 0.8 0.9 0.9 0.9 

Commercial/Institutional 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.8 

Coal + + + + + + + + + 

Fuel Oil 0.2 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1 

Natural gas 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Wood 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 

Residential 4.4 4.0 3.4 3.1 3.1 3.3 3.3 3.3 3.1 

Coal 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 + 

Fuel Oil 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Natural Gas 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.4 

Wood 3.5 3.1 2.5 2.2 2.3 2.4 2.5 2.5 2.3 

U.S. Territories + + 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Coal + + + + + + + + + 

Fuel Oil + + + 0.1 0.1 0.1 0.1 0.1 0.1 

Natural Gas + + + + + + + + + 

Wood + + + 

Total 7.4 7.2 6.6 

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.

+ 

 6.2 

+ 

 6.2 

+ 

 6.4 

+ 

 6.5 

+ 

 6.5 

+ 

 6.2 

Uncertainty 

CH4 emission estimates from stationary sources exhibit 

high uncertainty, primarily due to difficulties in calculating 

emissions from wood combustion (i.e., fireplaces and wood 

stoves). The estimates of CH4 and N2O emissions presented 

are based on broad indicators of emissions (i.e., fuel use 

multiplied by an aggregate emission factor for different 

sectors), rather than specific emission processes (i.e., by 

combustion technology and type of emission control). 

An uncertainty analysis was performed by primary fuel 

type for each end-use sector, using the IPCC-recommended 

Tier 2 uncertainty estimation methodology, Monte Carlo 

Simulation technique, with @RISK software.

The uncertainty estimation model for this source 

category was developed by integrating the CH4 and N2O 

stationary source inventory estimation models with the 

model for CO2 from fossil fuel combustion to realistically 

characterize the interaction (or endogenous correlation) 

between the variables of these three models. A total of 115 

input variables were simulated for the uncertainty analysis of 

this source category (85 from the CO2 emissions from fossil 

fuel combustion inventory estimation model and 30 from the 

stationary source inventory models). 

In developing the uncertainty estimation model, uniform 

distribution was assumed for all activity-related input 

variables and N2O emission factors, based on the SAIC/

EIA (2001) report.31 For these variables, the uncertainty 

ranges were assigned to the input variables based on the 

31SAIC/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.
3-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 3-17: N2O Emissions from Stationary Combustion (Tg CO2 Eq.)

Sector/Fuel Type 1990 1995 2000

Electric Power 8.1 8.6 10.0 

2001

9.7 

2002

9.7 

2003

10.0 

2004

10.0 

2005

10.3 

2006

10.1 

Coal 7.6 8.1 9.4 9.1 9.2 9.4 9.5 9.7 9.5 

Fuel Oil 0.2 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.1 

Natural Gas 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 

Wood 0.2 0.1 0.2 0.1 0.2 0.2 0.2 0.2 0.2 

Industrial 3.2 3.4 3.3 3.1 3.0 3.0 3.1 3.1 3.2 

Coal 0.8 0.7 0.7 0.7 0.6 0.6 0.6 0.6 0.6 

Fuel Oil 0.5 0.4 0.5 0.5 0.5 0.5 0.5 0.6 0.6 

Natural Gas 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 

Wood 1.7 1.9 1.9 1.7 1.6 1.6 1.7 1.7 1.7 

Commercial/Institutional 0.4 0.4 0.3 0.3 0.3 0.4 0.4 0.3 0.3 

Coal 0.1 0.1 + + + + + + + 

Fuel Oil 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Natural Gas 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Wood 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Residential 1.1 1.0 0.9 0.9 0.9 0.9 0.9 0.9 0.8 

Coal + + + + + + + + + 

Fuel Oil 0.3 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.2 

Natural Gas 0.1 0.1 0.2 0.1 0.1 0.2 0.1 0.1 0.1 

Wood 0.7 0.6 0.5 0.4 0.4 0.5 0.5 0.5 0.5 

U.S. Territories 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Coal + + + + + + + + + 

Fuel Oil 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Natural Gas + + + + + + + + + 

Wood + + + + 

Total 12.8 13.4 14.6 14.1 

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.

+ 

14.0 

+ 

14.3 

+ 

14.6 

+ 

14.8 

+ 

14.5 

data reported in SAIC/EIA (2001).32 However, the CH4

emission factors differ from those used by EIA. Since these 

factors were obtained from IPCC/UNEP/OECD/IEA (1997), 

uncertainty ranges were assigned based on IPCC default 

uncertainty estimates (IPCC 2000). 

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 3-20. Stationary combustion CH4

emissions in 2006 (including biomass) were estimated to be 

between 4.3 and 13.4 Tg CO2 Eq. at a 95 percent confidence 

level. This indicates a range of 31 percent below to 116 

32 In the SAIC/EIA (2001) report, the quantitative uncertainty estimates 

were developed for each of the three major fossil fuels used within each 

end-use sector; the variations within the sub-fuel types within each end-use 

sector were not modeled. However, for purposes of assigning uncertainty 

estimates to the sub-fuel type categories within each end-use sector in 

the current uncertainty analysis, SAIC/EIA (2001)-reported uncertainty 

estimates were extrapolated. 

percent above the 2006 emission estimate of 6.2 Tg CO2 Eq.33

Stationary combustion N2O emissions in 2006 (including

biomass) were estimated to be between 11.0 and 42.2 Tg 

CO2 Eq. at a 95 percent confidence level. This indicates a 

range of 24 percent below to 190 percent above the 2006 

emissions estimate of 14.5 Tg CO2 Eq. 

The uncertainties associated with the emission 

estimates of CH4 and N2O are greater than those associated 

with estimates of CO2 from fossil fuel combustion, which 

mainly rely on the carbon content of the fuel combusted. 

Uncertainties in both CH4 and N2O estimates are due to the 

fact that emissions are estimated based on emission factors 

representing only a limited subset of combustion conditions. 

33The low emission estimates reported in this section have been rounded 

down to the nearest integer values and the high emission estimates have 

been rounded up to the nearest integer values.
Energy 3-27

Table 3-18: CH4 Emissions from Stationary Combustion (Gg)

Sector/Fuel Type 1990 1995 2000

Electric Power 27 27 33 

2001

32 

2002

32 

2003

34 

2004

34 

2005

35 

2006

34 

Coal 16 18 20 20 20 20 20 21 21 

Fuel Oil 4 2 3 4 3 4 4 4 2 

Natural Gas 3 4 5 5 5 5 5 6 6 

Wood 4 4 4 4 4 5 5 5 5 

Industrial 73 78 76 71 69 68 71 71 72 

Coal 16 15 14 14 13 13 13 13 13 

Fuel Oil 9 7 7 8 8 8 9 9 10 

Natural Gas 7 8 8 8 8 8 7 7 7 

Wood 41 47 47 41 40 39 42 41 42 

Commercial/Institutional 41 43 43 41 42 44 43 42 40 

Coal 1 1 1 1 1 1 1 1 1 

Fuel Oil 8 7 7 7 6 7 7 7 7 

Natural Gas 13 15 15 15 15 16 15 15 14 

Wood 19 21 20 19 20 20 20 20 18 

Residential 210 190 162 147 149 158 159 157 147 

Coal 9 5 3 3 4 4 4 3 2 

Fuel Oil 14 13 15 15 14 15 15 14 13 

Natural Gas 21 24 24 23 24 25 24 24 21 

Wood 165 148 120 105 108 114 117 117 111 

U.S. Territories 2 2 2 3 3 3 3 3 3 

Coal + + + + + + + + + 

Fuel Oil 2 2 2 3 3 3 3 3 3 

Natural Gas + + + + + + + + + 

Wood + + + 

Total 353 341 316 

+ Does not exceed 0.5 Gg

Note: Totals may not sum due to independent rounding.

+ 

295 

+ 

295 

+ 

306 

+ 

311 

+ 

308 

+ 

296 

For the indirect greenhouse gases, uncertainties are partly 

due to assumptions concerning combustion technology 

types, age of equipment, emission factors used, and activity 

data projections.

QA/QC and Verification

A source-specific QA/QC plan for stationary combustion 

was developed and implemented. This effort included a 

Tier 1 analysis, as well as portions of a Tier 2 analysis. The 

Tier 2 procedures that were implemented involved checks 

specifically focusing on the activity data and emission factor 

sources and methodology used for estimating CH4, N2O, and 

the indirect greenhouse gases from stationary combustion in 

the United States. Emission totals for the different sectors and 

fuels were compared and trends were investigated. 

Recalculations Discussion 

Historical CH4 and N2O emissions from stationary 

sources (excluding CO2) were revised due to several changes. 

One of the most significant changes was implementing 

stationary combustion emission factors updated in 

IPCC (2006). As a result, N2O emission factors for coal 

consumption in all sectors, and CH4 emission factors for 

industrial petroleum and natural gas were revised. Slight 

changes to emission estimates for sectors are also due to 

revised data from EIA (2007a). This revision is explained in 

greater detail in the section on CO2 Emissions from Fossil 

Fuel Combustion within this sector. Wood consumption 

data from EIA (2007b) were revised for the residential, 

industrial, and electric power sectors. The combination of 

the methodological and historical data changes resulted in an 

average annual decrease of 0.6 Tg CO2 Eq. (8.3 percent) in 
3-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 3-19: N2O Emissions from Stationary Combustion (Gg)

Sector/Fuel Type 1990 1995 2000

Electric Power 26 28 32 

2001

31 

2002

31 

2003

32 

2004

32 

2005

33 

2006

32 

Coal 24 26 30 29 30 30 31 31 31 

Fuel Oil 1 + 1 1 1 1 1 1 + 

Natural Gas + + 1 1 1 + 1 1 1 

Wood + + 1 + 1 1 1 1 1 

Industrial 10 11 11 10 10 10 10 10 10 

Coal 2 2 2 2 2 2 2 2 2 

Fuel Oil 2 1 1 2 2 2 2 2 2 

Natural Gas 1 1 1 1 1 1 1 1 1 

Wood 5 6 6 5 5 5 6 6 6 

Commercial/Institutional 1 1 1 1 1 1 1 1 1 

Coal + + + + + + + + + 

Fuel Oil + + + + + + + + + 

Natural Gas + + + + + + + + + 

Wood + + + + + + + + + 

Residential 4 3 3 3 3 3 3 3 3 

Coal + + + + + + + + + 

Fuel Oil 1 1 1 1 1 1 1 1 1 

Natural Gas + + + + + + + + + 

Wood 2 2 2 1 1 2 2 2 1 

U.S. Territories + + + + + + + + + 

Coal + + + + + + + + + 

Fuel Oil + + + + + + + + + 

Natural Gas + + + + + + + + + 

Wood + + + 

Total 41 43 47 

+ Does not exceed 0.5 Gg

Note: Totals may not sum due to independent rounding.

+ 

46 

+ 

45 

+ 

46 

+ 

47 

+ 

48 

+ 

47 

Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Energy-Related Stationary 

Combustion, Including Biomass (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Stationary Combustion CH4 6.2 4.3 13.4 -31% +116%

Stationary Combustion N2O 14.5 11.0 42.2 -24% +190%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

CH4 emissions from stationary combustion and an average 

annual increase of 0.6 Tg CO2 Eq. (4.9 percent) in N2O 

emissions from stationary combustion for the period 1990 

through 2005.

Planned Improvements

Several items are being evaluated to improve the CH4

and N2O emission estimates from stationary combustion 

and to reduce uncertainty. Efforts will be taken to work with 

EIA and other agencies to improve the quality of the U.S. 
Energy 3-29

territories data. Because these data are not broken out by 

stationary and mobile uses, further research will be aimed at 

trying to allocate consumption appropriately. In addition, the 

uncertainty of biomass emissions will be further investigated 

since it was expected that the exclusion of biomass from the 

uncertainty estimates would reduce the uncertainty; and in 

actuality the exclusion of biomass increases the uncertainty. 

These improvements are not all-inclusive, but are part of an 

ongoing analysis and efforts to continually improve these 

stationary estimates.

3.4. Mobile Combustion (excluding 

CO2) (IPCC Source Category 1A)

Mobile combustion produces greenhouse gases other 

than CO2, including CH4, N2O, and indirect greenhouse 

gases including NOx, CO, and NMVOCs. Mobile combustion 

includes all transportation sources identified in the U.S. 

Inventory with the exception of pipelines, which are 

stationary; mobile sources also include non-transportation 

sources such as construction/mining equipment, agricultural 

equipment, vehicles used off-road, and other sources that 

have utility associated with their movement but do not have 

a primary purpose of transporting people or goods (e.g., 

snowmobiles, riding lawnmowers, etc.). Annex 3.2 includes 

a summary of all emissions from both transportation and 

mobile sources.

As with stationary combustion, N2O and NOx emissions 

are closely related to fuel characteristics, air-fuel mixes, 

combustion temperatures, and the use of pollution control 

equipment. N2O, in particular, can be formed by the catalytic 

processes used to control NOx, CO, and hydrocarbon 

emissions. Carbon monoxide emissions from mobile 

combustion are significantly affected by combustion 

efficiency and the presence of post-combustion emission 

controls. CO emissions are highest when air-fuel mixtures 

have less oxygen than required for complete combustion. 

These emissions occur especially in idle, low speed, and cold 

start conditions. CH4 and NMVOC emissions from motor 

vehicles are a function of the CH4 content of the motor fuel, 

the amount of hydrocarbons passing uncombusted through 

the engine, and any post-combustion control of hydrocarbon 

emissions (such as catalytic converters).

Table 3-21 and Table 3-22 provide CH4 and N2O 

emission estimates in Tg CO2 Eq.; Table 3-23 and Table 3-24 

present these estimates in Gg of each gas.34

Mobile combustion was responsible for a small portion 

of national CH4 emissions (0.4 percent) but was the second 

largest source of U.S. N2O emissions (9 percent). From 

1990 to 2006, mobile source CH4 emissions declined by 50 

percent, to 2.4 Tg CO2 Eq. (112 Gg), due largely to control 

technologies employed in on-road vehicles since the mid1990s to reduce CO, NOx, NMVOC, and CH4 emissions. 

Mobile source emissions of N2O decreased by 24 percent, 

to 33.1 Tg CO2 Eq (107 Gg). Earlier generation control 

technologies initially resulted in higher N2O emissions, 

causing a 26 percent increase in N2O emissions from mobile 

sources between 1990 and 1998. Improvements in latergeneration emission control technologies have reduced N2O 

output, resulting in a 40 percent decrease in mobile source 

N2O emissions from 1998 to 2006 (see Figure 3-15). Overall, 

CH4 and N2O emissions were predominantly from gasolinefueled passenger cars and light-duty trucks. 

Figure 3-15

Mobile Source CH4 and N2O Emissions

0

10

20

30

40

50

60 N2O 1990 1991 1992 1993 1994 1995 1996 1997 1998

19992000200120022003200420052006

Tg CO2 Eq.

CH4 

34 See Annex 3.2 for a complete time series of emission estimates for 1990 

through 2006.
3-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 3-21: CH4 Emissions from Mobile Combustion (Tg CO2 Eq.)

Fuel Type/Vehicle Typea 1990 1995 2000

Gasoline On-Road 4.2 3.8 2.8 

2001

2.7 

2002

2.4 

2003

2.2 

2004

2.0 

2005

1.9 

2006

1.7 

Passenger Cars 2.6 2.1 1.6 1.5 1.4 1.3 1.2 1.1 1.0 

Light-Duty Trucks 1.4 1.4 1.1 1.1 0.9 0.8 0.7 0.7 0.7 

Medium- and Heavy-Duty Trucks and Buses 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Motorcycles + + + + + + + + + 

Diesel On-Road + + + + + + + + + 

Passenger Cars + + + + + + + + + 

Light-Duty Trucks + + + + + + + + + 

Medium- and Heavy-Duty Trucks and Buses + + + + + + + + + 

Alternative Fuel On-Road + + + + + + 0.1 0.1 0.1 

Non-Road 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.6 0.6 

Ships and Boats–Domestic 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Rail 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Agricultural Equipment 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Construction/Mining Equipment + 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Aircraft–Domestic 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 

Otherb + + + + 0.1 0.1 0.1 0.1 0.1 

Total 4.7 4.3 3.4 3.3 3.0 2.7 2.6 2.5 2.4 

+ Less than 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.

a See Annex 3.2 for definitions of on-road vehicle types. 

b “Other” includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport equipment, 

commercial equipment, and industrial equipment.

Table 3-22: N2O Emissions from Mobile Combustion (Tg CO2 Eq.)

Fuel Type/Vehicle Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Gasoline On-Road 40.1 49.8 48.4 45.9 41.8 38.4 35.6 32.1 29.0 

Passenger Cars 25.4 26.9 25.2 23.8 22.5 21.0 19.5 17.7 15.6 

Light-Duty Trucks 14.1 22.1 22.4 21.2 18.5 16.5 15.3 13.6 12.6 

Medium- and Heavy-Duty Trucks and Buses 0.6 0.7 0.9 0.9 0.9 0.9 0.8 0.8 0.7 

Motorcycles + + + + + + + + + 

Diesel On-Road 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Passenger Cars + + + + + + + + + 

Light-Duty Trucks + + + + + + + + + 

Medium- and Heavy-Duty Trucks and Buses 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Alternative Fuel On-Road 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 

Non-Road 3.2 3.3 3.7 3.6 3.6 3.4 3.6 3.7 3.6 

Ships and Boats–Domestic 0.4 0.4 0.5 0.3 0.5 0.3 0.4 0.4 0.4 

Rail 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.4 

Agricultural Equipment 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4

Construction/Mining Equipment 0.3 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.5

Aircraft–Domestic 1.7 1.7 1.9 1.8 1.7 1.7 1.7 1.7 1.6

Other a 0.2 0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 

Total 43.5 53.4 52.5 49.9 45.9 42.3 39.7 36.3 33.1 

+ Less than 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.

a “Other” 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 3-23: CH4 Emissions from Mobile Combustion (Gg)

Fuel Type/Vehicle Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Gasoline On-Road 201 180 134 129 112 103 96 88 82 

Passenger Cars 125 101 77 72 66 61 56 52 47 

Light-Duty Trucks 65 69 50 52 41 38 35 32 31 

Medium- and Heavy-Duty Trucks and Buses 10 9 5 5 4 4 4 3 3 

Motorcycles 1 1 1 1 1 1 1 1 1 

Diesel On-Road 1 1 1 1 1 1 1 1 1 

Passenger Cars + + + + + + + + + 

Light-Duty Trucks + + + + + + + + + 

Medium- and Heavy-Duty Trucks and Buses 1 1 1 1 1 1 1 1 1 

Alternative Fuel On-Road + + 1 2 2 2 3 3 3 

Non-Road 22 24 26 25 26 24 26 27 27 

Ships and Boats–Domestic 3 4 5 3 4 3 3 4 3 

Rail 3 3 3 3 3 3 4 4 4 

Agricultural Equipment 4 5 5 6 6 6 6 7 7 

Construction/Mining Equipment 2 3 3 3 3 3 3 4 4

Aircraft–Domestic 7 7 7 7 7 6 7 7 7

Other a 2 2 2 2 2 3 3 3 3 

Total 224 205 162 157 141 131 126 119 112 

+ Less than 0.5 Gg

Note: Totals may not sum due to independent rounding.

a “Other” includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad equipment, airport equipment, 

commercial equipment, and industrial equipment.

Table 3-24: N2O Emissions from Mobile Combustion (Gg)

Fuel Type/Vehicle Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Gasoline On-Road 129 161 156 148 135 124 115 104 93

Passenger Cars 82 87 81 77 72 68 63 57 50

Light-Duty Trucks 45 71 72 69 60 53 49 44 41

Medium- and Heavy-Duty Trucks and Buses 2 2 3 3 3 3 3 2 2

Motorcycles + + + + + + + + + 

Diesel On-Road 1 1 1 1 1 1 1 1 1

Passenger Cars + + + + + + + + + 

Light-Duty Trucks + + + + + + + + + 

Medium- and Heavy-Duty Trucks and Buses 1 1 1 1 1 1 1 1 1

Alternative Fuel On-Road + + + + + 1 1 1 1 

Non-Road 10 11 12 11 12 11 12 12 12

Ships and Boats–Domestic 1 1 2 1 2 1 1 1 1

Rail 1 1 1 1 1 1 1 1 1

Agricultural Equipment 1 1 1 1 1 1 1 1 1

Construction/Mining Equipment 1 1 1 1 1 2 2 2 2

Aircraft–Domestic 6 5 6 6 6 5 6 6 5

Other a 1 1 1 1 1 1 1 1 1

Total 140 172 169 161 148 137 128 117 107 

+ Less than 0.5 Gg

Note: Totals may not sum due to independent rounding.

a “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: 1990–2006

Methodology

Estimates of CH4 and N2O emissions from mobile 

combustion were calculated by multiplying emission factors 

by measures of activity for each fuel and vehicle type 

(e.g., light-duty gasoline trucks). Activity data included 

vehicle miles traveled (VMT) for on-road vehicles and fuel 

consumption for non-road mobile sources. The activity data 

and emission factors used are described in the subsections 

that follow. A complete discussion of the methodology used 

to estimate CH4 and N2O emissions from mobile combustion 

and the emission factors used in the calculations is provided 

in Annex 3.2. 

EPA (2008, 2005, 2003) provides emission estimates 

of NOx, CO, and NMVOCs for eight categories of onroad vehicles,35 aircraft, and seven categories of non-road 

vehicles.36 These emission estimates primarily reflect EPA 

data, which, in final iteration, will be published on the 

National Emission Inventory (NEI) Air Pollutant Emission 

Trends web site. The methodology used to develop these 

estimates can be found on EPA’s Air Pollutant Emission 

Trends website, at <http://www.epa.gov/ttn/chief/trends/

index.html>.

On-Road Vehicles 

Estimates of CH4 and N2O emissions from gasoline 

and diesel on-road vehicles are based on VMT and emission 

factors by vehicle type, fuel type, model year, and emission 

control technology. Emission estimates for alternative fuel 

vehicles (AFVs)37 are based on VMT and emission factors 

by vehicle and fuel type. 

Emission factors for gasoline and diesel on-road 

vehicles utilizing Tier 2 and Low Emission Vehicle (LEV) 

technologies were developed by ICF (2006b); all other 

gasoline and diesel on-road vehicle emissions factors were 

developed by ICF (2004). These factors were derived 

35Categories include: gasoline passenger cars, diesel passenger cars, lightduty gasoline trucks less than 6,000 pounds in weight, light-duty gasoline 

trucks between 6,000 and 8,500 pounds in weight, light-duty diesel trucks, 

heavy-duty gasoline trucks and buses, heavy-duty diesel trucks and buses, 

and motorcycles.

36 Categories include: locomotives, marine vessels, farm equipment, 

construction equipment, other non-road liquid fuel (e.g. recreational vehicles 

and lawn and garden equipment), and other non-road gaseous fuel (e.g., 

other non-road equipment running on compressed natural gas). 

37Alternative fuel and advanced technology vehicles are those that can 

operate using a motor fuel other than gasoline or diesel. This includes 

electric or other bifuel or dual fuel vehicles that may be partially powered 

by gasoline or diesel. 

from EPA, California Air Resources Board (CARB), and 

Environment Canada laboratory test results of different 

vehicle and control technology types. The EPA, CARB and 

Environment Canada tests were designed following the 

Federal Test Procedure (FTP), which covers three separate 

driving segments, since vehicles emit varying amounts of 

GHGs depending on the driving segment. These driving 

segments are: (1) a transient driving cycle that includes 

cold start and running emissions, (2) a cycle that represents 

running emissions only, and (3) a transient driving cycle that 

includes hot start and running emissions. For each test run, a 

bag was affixed to the tailpipe of the vehicle and the exhaust 

was collected; the content of this bag was then analyzed 

to determine quantities of gases present. The emissions 

characteristics of segment 2 were used to define running 

emissions, and subtracted from the total FTP emissions to 

determine start emissions. These were then recombined based 

upon the ratio of start to running emissions for each vehicle 

class from MOBILE6.2, an EPA emission factor model that 

predicts gram per mile emissions of CO2, CO, HC, NOx, and 

PM from vehicles under various conditions, to approximate 

average driving characteristics.38

Emission factors for AFVs were developed by ICF 

(2006a) after examining Argonne National Laboratory’s 

GREET 1.7-Transportation Fuel Cycle Model (ANL 2006) 

and Lipman and Delucchi (2002). These sources describe 

AFV emission factors in terms of ratios to conventional 

vehicle emission factors. Ratios of AFV to conventional 

vehicle emissions factors were then applied to estimated 

Tier 1 emissions factors from light-duty gasoline vehicles 

to estimate light-duty AFVs. Emissions factors for heavyduty AFVs were developed in relation to gasoline heavyduty vehicles. A complete discussion of the data source and 

methodology used to determine emission factors from AFVs 

is provided in Annex 3.2. 

Annual VMT data for 1990 through 2006 were obtained 

from the Federal Highway Administration’s (FHWA) 

Highway Performance Monitoring System database as 

reported in Highway Statistics (FHWA 1996 through 2007). 

VMT estimates were then allocated from FHWA’s vehicle 

categories to fuel-specific vehicle categories using the 

calculated shares of vehicle fuel use for each vehicle category 

38Additional information regarding the model can be found online at <http://

www.epa.gov/OMS/m6.htm>.
Energy 3-33

by fuel type reported in DOE (1993 through 2007) and 

information on total motor vehicle fuel consumption by fuel 

type from FHWA (1996 through 2007). VMT for AFVs were 

taken from Browning (2003). The age distributions of the 

U.S. vehicle fleet were obtained from EPA (2007c, 2000), and 

the average annual age-specific vehicle mileage accumulation 

of U.S. vehicles were obtained from EPA (2000). 

Control technology and standards data for on-road 

vehicles were obtained from EPA’s Office of Transportation 

and Air Quality (EPA 2007a, 2007b, 2000, 1998, and 1997) and 

Browning (2005). These technologies and standards are defined 

in Annex 3.2, and were compiled from EPA (1993, 1994a, 

1994b, 1998, 1999a) and IPCC/UNEP/OECD/IEA (1997).

These emission estimates were obtained from preliminary 

data (EPA 2008), and disaggregated based on EPA (2003), 

which, in its final iteration, will be published on the National 

Emission Inventory (NEI) Air Pollutant Emission Trends 

web site.

Non-Road Vehicles

To estimate emissions from non-road vehicles, fuel 

consumption data were employed as a measure of activity, 

and multiplied by fuel-specific emission factors (in grams 

of N2O and CH4 per kilogram of fuel consumed).39 Activity 

data were obtained from AAR (2007), APTA (2007 and 

2006), BEA (1991 through 2005), Benson (2002 through 

2004), DHS (2008), DOC (1991 through 2007), DOE (1993 

through 2007), DESC (2007), DOT (1991 through 2007), EIA 

(2007a, 2007b, 2007d, 2002), EIA (1991 through 2007), EPA 

(2006b), Esser (2003 through 2004), FAA (2007 and 2006), 

Gaffney (2007), Lou (2008), and Whorton (2006 through 

2007). Emission factors for non-road modes were taken from 

IPCC/UNEP/OECD/IEA (1997).

Uncertainty

A quantitative uncertainty analysis was conducted 

for the on-road portion of the mobile source sector using 

the IPCC-recommended Tier 2 uncertainty estimation 

methodology, Monte Carlo simulation technique, using @

RISK software. The uncertainty analysis was performed on 

2006 estimates of CH4 and N2O emissions, incorporating 

probability distribution functions associated with the 

major input variables. For the purposes of this analysis, the 

uncertainty was modeled for the following two major sets 

of input variables: (1) vehicle miles traveled (VMT) data, 

by vehicle and fuel type and (2) emission factor data, by 

vehicle, fuel, and control technology type.

Uncertainty analyses were not conducted for NOx, CO, 

or NMVOC emissions. Emission factors for these gases have 

been extensively researched since emissions of these gases 

from motor vehicles are regulated in the United States, and 

the uncertainty in these emission estimates is believed to be 

relatively low. However, a much higher level of uncertainty 

is associated with CH4 and N2O emission factors, because 

emissions of these gases are not regulated in the United States 

(and, therefore, there are not adequate emission test data), 

and because, unlike CO2 emissions, the emission pathways 

of CH4 and N2O are highly complex.

The results of the Tier 2 quantitative uncertainty analysis 

for the mobile source CH4 and N2O emissions from on-road 

vehicles are summarized in Table 3-25. As noted above, an 

Table 3-25: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Mobile Sources 

(Tg CO2 Eq. and Percent)

2006 Emission Estimatea Uncertainty Range Relative to Emission Estimatea,b

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

On-Road Sources CH4 1.8 1.7 1.9 -6% +6%

On-Road Sources N2O 29.5 23.8 35.2 -19% +19%

a

 The 2006 emission estimates and the uncertainty range presented in this table correspond to on-road vehicles, comprising conventional and alternative 

fuel vehicles. Because the uncertainty associated with the emissions from non-road vehicles were not estimated, they were excluded from the estimates 

reported in this table.

b

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

39The consumption of international bunker fuels is not included in these 

activity data, but is estimated separately under the International Bunker 

Fuels source category.
3-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

uncertainty analysis was not performed for CH4 and N2O 

emissions from non-road vehicles. Mobile combustion CH4

emissions (from on-road vehicles) in 2006 were estimated to 

be between 1.7 and 1.9 Tg CO2 Eq. at a 95 percent confidence 

level. This indicates a range of 6 percent below to 6 percent 

above the corresponding 2006 emission estimate of 1.8 

Tg CO2 Eq. Also at a 95 percent confidence level, mobile 

combustion N2O emissions from on-road vehicles in 2006 

were estimated to be between 23.8 and 35.2 Tg CO2 Eq., 

indicating a range of 19 percent below to 19 percent above the 

corresponding 2006 emission estimate of 29.5 Tg CO2 Eq. 

This uncertainty analysis is a continuation of a multiyear process for developing quantitative uncertainty estimates 

for this source category using the IPCC Tier 2 approach to 

uncertainty analysis. As a result, as new information becomes 

available, uncertainty characterization of input variables 

may be improved and revised. For additional information 

regarding uncertainty in emission estimates for CH4 and N2O 

please refer to the Uncertainty Annex.

QA/QC and Verification

A source-specific QA/QC plan for mobile combustion 

was developed and implemented. This plan is based on the 

IPCC-recommended QA-QC Plan. The specific plan used 

for mobile combustion was updated prior to collection and 

analysis of this current year of data. This effort included 

a Tier 1 analysis, as well as portions of a Tier 2 analysis. 

The Tier 2 procedures focused on the emission factor and 

activity data sources, as well as the methodology used for 

estimating emissions. These procedures included a qualitative 

assessment of the emissions estimates to determine whether 

they appear consistent with the most recent activity data 

and emission factors available. A comparison of historical 

emissions between the current Inventory and the previous 

Inventory was also conducted to ensure that the changes in 

estimates were consistent with the changes in activity data 

and emission factors.

Recalculations Discussion 

In order to ensure that these estimates are continuously 

improved, the calculation methodology is revised annually 

based on comments from internal and external reviewers. A 

number of adjustments were made to the methodologies used 

in calculating emissions in the current Inventory. 

Carbon dioxide emissions from gasoline-powered onroad sources are now calculated directly using “bottom-up” 

fuel sales data; this methodology is similar to the bottomup calculation of CO2 from transportation diesel sources 

implemented beginning with the 1990–2004 Inventory 

report. On-road gasoline fuel sales estimates come from 

FHWA’s Highway Statistics (FHWA 1996 through 2007). 

The ethanol component of these fuel sales is subtracted to 

yield a fossil-only estimate, which is used to calculate CO2 for 

gasoline-powered passenger cars, light-duty trucks, mediumand heavy-duty trucks, and buses. To preserve EIA’s estimate 

of total gasoline consumption across all sectors, adjustments 

were made to estimated gasoline consumption by recreational 

boats, the commercial sector and the industrial sector. EIA 

estimates of transportation sector fuel consumption continue 

to serve as the foundation of inventory estimates for other fuel 

types (jet fuel, aviation gasoline, residual fuel, natural gas, 

LPG and natural gas). CO2 from these fuels continues to be 

apportioned to individual modes using bottom-up data from 

BTS, FAA, and DOE’s Transportation Energy Data Book. 

Vehicle age distributions for 1999 to the present were 

revised based on new data obtained from EPA’s MOVES 

model (EPA 2007c). Diesel fractions for light trucks and 

medium- and heavy-duty trucks and buses were updated 

based on data obtained from the Transportation Energy 

Data Book (DOE 1993 through 2007) for 1998 through 

2003, which increased emissions from diesel vehicles 

and reduced emissions from gasoline vehicles. Updates 

were made to alternative fuel vehicle (AFV) vehicle miles 

traveled (VMT) numbers based on new activity data (ICF 

2006a) and biodiesel was also added as a vehicle category 

under alternative fuel vehicles. VMT and fuel consumption 

estimates for on-road vehicles were also revised for 2005 

based on updated data from FHWA’s Highway Statistics 

(FHWA 1996 through 2007). 

Several changes were also made in the calculation of 

emissions from non-road vehicles. Similar to the previous 

Inventory, commercial aircraft energy consumption 

estimates for 2000–2005 come from the Federal Aviation 

Administration’s (FAA) System for Assessing Aviation’s 

Global Emissions (SAGE) database (FAA 2006). Aviation 

estimates were developed without the availability of 2006 

data from the Federal Aviation Administration’s (FAA) 

System for Assessing Aviation’s Global Emissions (SAGE) 
Energy 3-35

database. Estimates for 1990–1999 were calculated using fuel 

consumption estimates from the Bureau of Transportation 

Statistics (DOT 1991 through 2007) adjusted based on 

the 2000–2005 data. For 2006, an estimate—similar to 

the method used for 1990–1999—was derived using a 

combination of data from BTS and SAGE data. Class II and 

III railroad diesel use estimates are now obtained from the 

American Short Line and Regional Railroad Association, 

with new data for 2002, 2004, and 2006 (Whorton 2006 

through 2007).

As a result of these changes, average estimates of CH4

and N2O emissions from mobile combustion were slightly 

lower relative to the previous Inventory—showing a decrease 

of no more than 0.7 Tg CO2 Eq. (2.0 percent) each year—for 

the period 1990 through 2000. Larger decreases in estimates 

occurred for years 2002 to 2005 when comparing the current 

inventory estimates with the previous Inventory’s estimates. 

The greatest decrease, 1.5 Tg CO2 Eq. (4 percent), occurs 

with the 2005 N2O estimate. Estimates for the year 2001 are 

the exception, as these estimates increased from the previous 

Inventory’s estimates by 0.07 Tg CO2 Eq. for CH4 and 0.15 

Tg CO2 Eq. for N2O.

Planned Improvements

While the data used for this report represent the most 

accurate information available, six areas have been identified 

that could potentially be improved in the short-term given 

available resources. 

1. Develop new emission factors for non-road sources. 

The current inventory estimates for non-CO2 emissions 

from non-road sources are based on emission factors 

from IPCC guidelines published in 1996. Recent data 

on non-road sources from Environment Canada and the 

California Air Resources Board will be investigated in 

order to assess the feasibility of developing new N2O 

and CH4 emissions factors for non-road equipment. 

2. Examine the feasibility of estimating aircraft N2O 

and CH4 emissions by the number of takeoffs and 

landings, instead of total fuel consumption. Various 

studies have indicated that aircraft N2O and CH4

emissions are more dependent on aircraft takeoffs 

and landings than on total aircraft fuel consumption; 

however, aircraft emissions are currently estimated 

from fuel consumption data. FAA’s SAGE database 

contains detailed data on takeoffs and landings for each 

calendar year starting in 1999, and could potentially be 

used to conduct a Tier II analysis of aircraft emissions. 

This methodology will require a detailed analysis of 

the number of takeoffs and landings by aircraft type 

on domestic trips and development of procedures to 

develop comparable estimates for years prior to 1999. 

The feasibility of this approach will be explored. 

3. Develop improved estimates of domestic waterborne fuel 

consumption. The inventory estimates for residual fuel 

used by ships and boats is based in part on data on bunker 

fuel use from the U.S. Department of Commerce. The 

Department of Homeland Security (DHS) maintains an 

electronic reporting system that automatically registers 

monthly sales of bunker fuel at ports, which should 

provide a more accurate and comprehensive estimate 

of residual bunker fuel use by reducing the amount of 

non-reporting. This system has been used to collect data 

since 2002, and these data could be incorporated into 

the development of inventory figures. The DHS figures 

will need to be reconciled with figures from the current 

sources of data and a methodology will need to be 

developed to produce updated estimates for prior years. 

4. Develop improved estimates of domestic aviation fuel 

consumption. The inventory calculation of domestic 

jet fuel consumption is derived by first estimating 

international aviation bunker fuel consumption and 

subtracting this value from EIA’s estimate of total jet fuel 

consumption. Aviation bunker fuel estimates involve a 

number of uncertainties, including the lack of specific 

data on the amount of total jet fuel consumption to 

allocate to international bunkers. As mentioned above, 

FAA’s SAGE database contains detailed data of domestic 

operations of aircraft and associated fuel consumption, 

and could potentially be used for a direct calculation of 

commercial aviation fuel consumption similar to the 

bottom-up approaches currently used for transportation 

diesel sources and on-road gasoline. 

5. Improve the process of apportioning VMT by vehicle 

type to each fuel type. The current inventory process for 

estimating VMT by vehicle/fuel type category involves 

apportioning VMT on the basis of fuel consumption. 

While this is a reasonable simplification, this approach 

implicitly assumes the same average fuel economy 

for gasoline and diesel vehicles. A more accurate 

apportionment of VMT by fuel type for light-duty trucks 
3-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

and medium/heavy-duty trucks could potentially be 

developed using data on vehicle travel from the Vehicle 

Inventory and Use Survey (U.S. Census Bureau 2000) 

and other publications, or using VMT breakdowns by 

vehicle/fuel type combinations from the MOBILE6 or 

MOVES models. 

6. Continue to examine the use of EPA’s MOVES model 

in the development of the inventory estimates, including 

use for uncertainty analysis. Although the Inventory 

uses some of the underlying data from MOVES, such as 

vehicle age distributions by model year, MOVES is not 

used directly in calculating mobile source emissions. As 

MOVES goes through additional testing and refinement, 

the use of MOVES will be further explored.

3.5. Coal Mining (IPCC Source 

Category 1B1a)

Three types of coal mining related activities release 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 120 

gassy underground coal mines in the United States employ 

ventilation systems to ensure that CH4 levels remain within 

safe concentrations. These systems can exhaust significant 

amounts of CH4 to the atmosphere in low concentrations. 

Additionally, 20 U.S. coal mines supplement ventilation 

systems with degasification systems. Degasification systems 

are wells drilled from the surface or boreholes drilled inside 

the mine that remove large volumes of CH4 before, during, 

or after mining. In 2006, 13 coal mines collected 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 2006 were estimated to be 

58.5 Tg CO2 Eq. (2,784 Gg), a decline of 30 percent since 

1990 (see Table 3-26 and Table 3-27). Of this amount, 

underground mines accounted for 61 percent, surface 

Table 3-26: CH4 Emissions from Coal Mining (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Underground Mining 62.3 46.7 39.4 38.2 35.5 36.0 38.1 35.2 35.9

Liberated 67.9 59.1 55.0 55.5 54.7 53.0 53.2 52.3 54.6

Recovered & Used (5.6) (12.4) (15.6) (17.2) (19.2) (17.0) (15.1) (17.1) (18.7)

Surface Mining 12.0 11.5 12.3 13.2 12.8 12.4 12.9 13.3 14.0 

Post-Mining (Underground) 7.7 6.9 6.7 6.8 6.4 6.4 6.6 6.4 6.3

Post-Mining (Surface) 2.0 1.9 2.0 2.1 2.1 2.0 2.1 2.2 2.3 

Total 84.1 67.1 60.4 60.3 56.8 56.9 59.8 57.1 58.5 

Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.

Table 3-27: CH4 Emissions from Coal Mining (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Underground Mining 2,968 2,226 1,875 1,820 1,692 1,715 1,813 1,675 1,709 

Liberated 3,234 2,816 2,619 2,641 2,605 2,522 2,534 2,491 2,599 

Recovered & Used (266) (591) (744) (821) (913) (807) (721) (815) (891)

Surface Mining 574 548 586 627 610 592 616 633 668

Post-Mining (Underground) 368 330 318 325 305 306 317 306 298 

Post-Mining (Surface) 93 89 95 102 99 96 100 103 109 

Total 4,003 3,193 2,874 2,874 2,707 2,709 2,846 2,717 2,784 

Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Energy 3-37

mines accounted for 24 percent, and post-mining emissions 

accounted for 15 percent. The decline in CH4 emissions 

from underground mines from 1996 to 2002 was the result 

of the reduction of overall coal production, the mining 

of less gassy coal, and an increase in CH4 recovered and 

used. Since that time, underground coal production and the 

associated methane emissions have remained fairly level, 

while surface coal production and its associated emissions 

have steadily increased.

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-bymine basis and then summed to determine total emissions. 

The second step involves estimating emissions from surface 

mines and post-mining activities by multiplying basinspecific coal production by basin-specific emission factors.

Underground mines. Total CH4 emitted from underground 

mines was estimated as the sum of CH4 liberated from 

ventilation systems and CH4 liberated by means of 

degasification systems, minus CH4 recovered and used. The 

Mine Safety and Heath Administration (MSHA) samples 

CH4 emissions from ventilation systems for all mines with 

detectable40 CH4 concentrations. These mine-by-mine 

measurements are used to estimate CH4 emissions from 

ventilation systems. 

Some of the higher-emitting underground mines also 

use degasification systems (e.g., wells or boreholes) that 

remove CH4 before, during, or after mining. This CH4 can 

then be collected for use or vented to the atmosphere. Various 

approaches were employed to estimate the quantity of CH4

collected by each of the twenty mines using these systems, 

depending on available data. For example, some mines report 

to EPA the amount of CH4 liberated from their degasification 

systems. For mines that sell recovered CH4 to a pipeline, 

pipeline sales data published by state petroleum and natural 

gas agencies were used to estimate degasification emissions. 

For those mines for which no other data are available, default 

recovery efficiency values were developed, depending on 

the type of degasification system employed.

Finally, the amount of CH4 recovered by degasification 

systems and then used (i.e., not vented) was estimated. In 

2006, thirteen active coal mines sold recovered CH4 into 

the local gas pipeline networks, while one coal mine used 

recovered CH4 on site. Emissions avoided for these projects 

were estimated using gas sales data reported by various 

state agencies. For most mines with recovery systems, 

companies and state agencies provided individual well 

production information, which was used to assign gas sales 

to a particular year. For the few remaining mines, coal mine 

operators supplied information regarding the number of years 

in advance of mining that gas recovery occurs. In the case 

of Jim Walter Resources (JWR), the emissions avoided data 

was taken from the 1605b reports that the mining company 

has been filing with the Department of Energy (DOE) since 

1991 as part of their Voluntary Reporting Program.

Surface Mines and Post-Mining Emissions. Surface 

mining and post-mining CH4 emissions were estimated by 

multiplying basin-specific coal production, obtained from the 

Energy Information Administration’s Annual Coal Report 

(see Table 3-28) (EIA 2006), by basin-specific emission 

factors. Surface mining emission factors were developed by 

assuming that surface mines emit two times as much CH4

as the average in situ CH4 content of the coal. Revised data 

on in situ CH4 content and emissions factors are taken from 

EPA (2005), EPA (1996), and AAPG (1984). This calculation 

accounts for CH4 released from the strata surrounding the 

coal seam. For post-mining emissions, the emission factor 

was assumed to be 32.5 percent of the average in situ CH4

content of coals mined in the basin. 

Table 3-28: Coal Production (Thousand Metric Tons)

Year Underground Surface Total

1990 384,250 546,818 931,068

1995 359,477 577,638 937,115

2000 338,173 635,592 973,765

2001 345,305 676,142 1,021,446

2002 324,219 667,619 991,838

2003 320,047 651,251 971,297

2004 333,449 674,551 1,008,000

2005 334,404 691,460 1,025,864

2006 325,703 728,459 1,054,162

40 MSHA records coal mine CH4 readings with concentrations of greater 

than 50 ppm (parts per million) CH4. Readings below this threshold are 

considered non-detectable.
3-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Uncertainty

A quantitative uncertainty analysis was conducted for the 

coal mining source category using the IPCC-recommended 

Tier 2 uncertainty estimation methodology. Because emission 

estimates from underground ventilation systems were 

based on actual measurement data, uncertainty is relatively 

low. A degree of imprecision was introduced because the 

measurements used were not continuous but rather an 

average of quarterly instantaneous readings. Additionally, 

the measurement equipment used can be expected to have 

resulted in an average of 10 percent overestimation of annual 

CH4 emissions (Mutmansky and Wang 2000). Estimates of 

CH4 recovered by degasification systems are relatively certain 

because many coal mine operators provided information on 

individual well gas sales and mined through dates. Many of 

the recovery estimates use data on wells within 100 feet of 

a mined area. Uncertainty also exists concerning the radius 

of influence of each well. The number of wells counted, and 

thus the avoided emissions, may vary if the drainage area is 

found to be larger or smaller than currently estimated. 

Compared to underground mines, there is considerably 

more uncertainty associated with surface mining and postmining emissions because of the difficulty in developing 

accurate emission factors from field measurements. However, 

since underground emissions comprise the majority of total 

coal mining emissions, the uncertainty associated with 

underground emissions is the primary factor that determines 

overall uncertainty. The results of the Tier 2 quantitative 

uncertainty analysis are summarized in Table 3-29. Coal 

mining CH4 emissions in 2006 were estimated to be between 

53.3 and 76.3 Tg CO2 Eq. at a 95 percent confidence level. 

This indicates a range of 9 percent below to 30 percent above 

the 2006 emission estimate of 58.5 Tg CO2 Eq. 

Recalculations Discussion 

In 2006, recalculations of emissions avoided at three JWR 

coal mines in Alabama were performed as the mining company 

provided copies of their 1605b reports that they had been 

filing with DOE. These reports cover the years 1991 through 

2005. The 2006 report has not yet been filed, however JWR 

provided the 2006 data. In previous inventories, emissions 

avoided calculations for any pre-drainage wells at JWR coal 

mines were based on publicly-available data records from the 

Alabama State Oil & Gas Board. Emission reductions were 

calculated for pre-drainage wells located inside the mine plan 

boundaries and were declared “shut-in” by the O&G Board. 

The total production for a well was claimed in the year that 

the well was shut-in and mined through. 

Secondly, the gas content values assigned to each 

coal basin in the surface mine emissions component of the 

Inventory were changed to reflect recent work carried out 

by U.S. EPA (EPA 2005). This change impacted the reported 

emissions attributed to surface mining operations (active and 

post mining) for the full time-series, resulting in increased 

emission estimates for surface and post-surface mining 

operations for all reported years. 

Finally, the conversion factor used previously to convert 

from mmcf of CH4 to Gg of CH4 was 52,150. The conversion 

factor used in the natural gas emission estimates is 51,921. 

In order to ensure consistency of emission estimates across 

the Inventory, the conversion factor for the active mines 

emissions was changed to 51,921. This change impacted all 

estimates for the values previously calculated and reported 

for Gg of CH4 emitted, and for Tg of CO2 Eq. emitted. The 

difference between these factors is 0.44 percent.

Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Coal Mining CH4 58.5 53.3 76.3 -9% +30%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Energy 3-39

3.6. Abandoned Underground Coal 

Mines (IPCC Source Category 1B1a)

Underground coal mines contribute the largest share of 

CH4 emissions, with active underground mines the leading 

source of underground emissions. However, mines also 

continue to release CH4 after closure. As mines mature 

and coal seams are mined through, mines are closed and 

abandoned. Many are sealed and some flood through intrusion 

of groundwater or surface water into the void. Shafts or 

portals are generally filled with gravel and capped with a 

concrete seal, while vent pipes and boreholes are plugged 

in a manner similar to oil and gas wells. Some abandoned 

mines are vented to the atmosphere to prevent the buildup 

of CH4 that may find its way to surface structures through 

overburden fractures. As work stops within the mines, the 

CH4 liberation decreases but it does not stop completely. 

Following an initial decline, abandoned mines can liberate 

CH4 at a near-steady rate over an extended period of time, 

or, if flooded, produce gas for only a few years. The gas 

can migrate to the surface through the conduits described 

above, particularly if they have not been sealed adequately. In 

addition, diffuse emissions can occur when CH4 migrates to 

the surface through cracks and fissures in the strata overlying 

the coal mine. The following factors influence abandoned 

mine emissions:

•	 Time since abandonment;

•	 Gas content and adsorption characteristics of coal;

•	 CH4 flow capacity of the mine;

•	 Mine flooding;

•	 Presence of vent holes; and

•	 Mine seals.

Gross abandoned mine CH4 emissions ranged from 

6.0 to 9.1 Tg CO2 Eq. from 1990 through 2006, varying, in 

general, by less than 1 to approximately 19 percent from year 

to year. Fluctuations were due mainly to the number of mines 

closed during a given year as well as the magnitude of the 

emissions from those mines when active. Gross abandoned 

mine emissions peaked in 1996 (9.1 Tg CO2 Eq.) due to the 

large number of mine closures from 1994 to 1996 (70 gassy 

mines closed during the three-year period). In spite of this 

rapid rise, abandoned mine emissions have been generally 

on the decline since 1996. There were fewer than fifteen 

gassy mine closures during each of the years from 1998 

through 2006, with only one closure in 2006. By 2006, gross 

abandoned mine emissions declined to 6.8 Tg CO2 Eq. (see 

Table 3-30 and Table 3-31). Gross emissions are reduced 

by methane recovered and used at 20 mines, resulting in net 

emissions in 2006 of 5.4 Tg CO2Eq.

Methodology

Estimating CH4 emissions from an abandoned coal mine 

requires predicting the emissions of a mine from the time of 

abandonment through the inventory year of interest. The flow 

of CH4 from the coal to the mine void is primarily dependent 

on the mine’s emissions when active and the extent to which 

the mine is flooded or sealed. The CH4 emission rate before 

abandonment reflects the gas content of the coal, rate of coal 

mining, and the flow capacity of the mine in much the same 

Table 3-30: CH4 Emissions from Abandoned Coal Mines (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Abandoned Underground Mines 6.0 8.9 8.9 8.2 7.7 7.5 7.3 7.0 6.8

Recovered & Used 0.0 0.7 1.5 1.5 1.6 1.5 1.5 1.4 1.4

Total 6.0 8.2 7.4 6.7 6.2 6.0 5.8 5.6 5.4

Note: Totals may not sum due to independent rounding.

Table 3-31: CH4 Emissions from Abandoned Coal Mines (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Abandoned Underground Mines 288 424 422 389 368 356 347 333 322

Recovered & Used 0 32 72 70 75 72 71 68 65

Total 288 392 350 319 293 284 276 265 257

Note: Totals may not sum due to independent rounding.
3-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

way as the initial rate of a water-free conventional gas well 

reflects the gas content of the producing formation and the 

flow capacity of the well. A well or a mine which produces 

gas from a coal seam and the surrounding strata will produce 

less gas through time as the reservoir of gas is depleted. 

Depletion of a reservoir will follow a predictable pattern 

depending on the interplay of a variety of natural physical 

conditions imposed on the reservoir. The depletion of a 

reservoir is commonly modeled by mathematical equations 

and mapped as a type curve. Type curves which are referred 

to as decline curves have been developed for abandoned 

coal mines. Existing data on abandoned mine emissions 

through time, although sparse, appear to fit the hyperbolic 

type of decline curve used in forecasting production from 

natural gas wells. 

In order to estimate CH4 emissions over time for a given 

mine, it is necessary to apply a decline function, initiated 

upon abandonment, to that mine. In the analysis, mines 

were grouped by coal basin with the assumption that they 

will generally have the same initial pressures, permeability 

and isotherm. As CH4 leaves the system, the reservoir 

pressure, Pr, declines as described by the isotherm. The 

emission rate declines because the mine pressure (Pw) is 

essentially constant at atmospheric pressure, for a vented 

mine, and the PI term is essentially constant at the pressures 

of interest (atmospheric to 30 psia). A rate-time equation can 

be generated that can be used to predict future emissions. 

This decline through time is hyperbolic in nature and can 

be empirically expressed as:

Gas rate at time elapsed from time zero in million cubic feet per day equals Initial gas rate at 

time zero in million cubic feet per day multiplied by open parenthesis one plus the Hyperbolic 

exponent, dimensionless, multiplied by Initial decline rate, one per year, multiplied by elapsed 

time from time zero closed parenthesis raised to the open parenthesis negative one divided by the 

Hyperbolic exponent, dimensionless, closed parenthesis power

This equation is applied to mines of various initial 

emission rates that have similar initial pressures, permeability 

and adsorption isotherms (EPA 2003).

The decline curves created to model the gas emission 

rate of coal mines must account for factors that decrease 

the rate of emission after mining activities cease, such as 

sealing and flooding. Based on field measurement data, it 

was assumed that most U.S. mines prone to flooding will 

become completely flooded within eight years and therefore 

no longer have any measurable CH4 emissions. Based on this 

assumption, an average decline rate for flooding mines was 

established by fitting a decline curve to emissions from field 

measurements. An exponential equation was developed from 

emissions data measured at eight abandoned mines known to 

be filling with water located in two of the five basins. Using 

a least squares, curve-fitting algorithm, emissions data were 

matched to the exponential equation shown below. There 

was not enough data to establish basin-specific equations as 

was done with the vented, non-flooding mines (EPA 2003).

Gas flow rate at time elapsed from time zero in million cubic feet per day equals Initial gas flow rate 

at time zero in million cubic feet per day multiplied by base of natural log raised to the open parenthesis 

Negative decline rate, one per year, multiplied by Elapsed time from time zero closed parenthesis power

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 × (1 - (initial emissions from sealed mine/

emission rate at abandonment prior to sealing)). Significant 

differences are seen between 50 percent, 80 percent and 95 

percent closure. These decline curves were therefore used as 

the high, middle, and low values for emissions from sealed 

mines (EPA 2003).

For active coal mines, those mines producing over 100 

mcfd account for 98 percent of all CH4 emissions. This 

same relationship is assumed for abandoned mines. It was 

determined that 441 abandoned mines closing after 1972 

produced emissions greater than 100 mcfd when active. 

Further, the status of 264 of the 441 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 

q = qi (1+bDit)(-1/b) 

where,

q = Gas rate at time t in mmcf/d

qi = Initial gas rate at time zero (to) in million cubic 

feet per day mmcfd

b = The hyperbolic exponent, dimensionless

Di = Initial decline rate, 1/yr

t = Elapsed time from to (years)

q = qie(-Dt)

where,

q = Gas flow rate at time t in mcf/d

qi = Initial gas flow rate at time zero (to) in mcfd

D = Decline rate, 1/yr

t = Elapsed time from to (years)
Energy 3-41

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 

by state and county are helpful, but do not provide enough 

data to directly employ the methodology used to calculate 

emissions from mines abandoned after 1971. It is assumed 

that pre-1972 mines are governed by the same physical, 

geologic, and hydrologic constraints that apply to post-1972 

mines; thus, their emissions may be characterized by the 

same decline curves. 

During the 1970s, 78 percent of CH4 emissions from 

coal mining came from seventeen counties in seven states. 

In addition, mine closure dates were obtained for two states, 

Colorado and Illinois, for the hundred year period extending 

from 1900 through 1999. The data were used to establish 

a frequency of mine closure histogram (by decade) and 

applied to the other five states with gassy mine closures. As 

a result, basin-specific decline curve equations were applied 

to 145 gassy coal mines estimated to have closed between 

1920 and 1971 in the United States, representing 78 percent 

of the emissions. State-specific, initial emission rates were 

used based on average coal mine CH4 emission rates during 

the 1970s (EPA 2003). 

Abandoned mines emission estimates are based on all 

closed mines known to have active mine CH4 ventilation 

emission rates greater than 100 mcfd at the time of 

abandonment; a list by region is shown in Table 3-32. 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 pre1990 closures. CH4 degasification amounts were added to the 

quantity of CH4 ventilated for the total CH4 liberation rate for 

fifteen mines that closed between 1992 and 2006. Since the 

sample of gassy mines (with active mine emissions greater 

than 100 mcfd) is assumed to account for 78 percent of the 

pre-1971 and 98 percent of the post-1971 abandoned mine 

emissions, the modeled results were multiplied by 1.22 and 

1.02 to account for all U.S. abandoned mine emissions. 

From 1993 through 2006, emission totals were 

downwardly adjusted to reflect abandoned mine CH4

emissions avoided from those mines. The emission estimates 

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 

Table 3-32: Number of Gassy Abandoned Mines Occurring in U.S. Basins Grouped by Class According to 

Post-abandonment State

Basin Sealed Vented Flooded Total Known Unknown Total Mines

Central Appl. 23 25 48 96 111 207

Illinois 28 3 14 45 25 70

Northern Appl. 41 22 16 79 32 111

Warrior Basin 0 0 14 14 0 14

Western Basins 25 3 2 30 9 39

Total 117 53 94 264 177 441
3-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

each mine, the methodology for estimating emissions was 

used that generates a probability distribution of potential 

outcomes based on the most likely value and the probable 

range of values for each parameter. The range of values is 

not meant to capture the extreme values, but values that 

represent the highest and lowest quartile of the cumulative 

probability density function of each parameter. Once the 

low, mid, and high values are selected, they are applied to a 

probability density function. 

The results of the Tier 2 quantitative uncertainty 

analysis are summarized in Table 3-33. Abandoned coal 

mines CH4 emissions in 2006 were estimated to be between 

4.5 and 6.4 Tg CO2 Eq. at a 95 percent confidence level. 

This indicates a range of 17 percent below to 19 percent 

above the 2006 emission estimate of 5.4 Tg CO2 Eq. One 

of the reasons for the relatively narrow range is that minespecific data is used in the methodology. The largest degree 

of uncertainty is associated with the unknown status mines 

(which account for 40 percent of the mines), with a ±50 

percent uncertainty. 

3.7. Natural Gas Systems 

(IPCC Source Category 1B2b)

The U.S. natural gas system encompasses hundreds 

of thousands of wells, hundreds of processing facilities, 

and over a million miles of transmission and distribution 

pipelines. Overall, natural gas systems emitted 102.4 Tg CO2

Eq. (4,877 Gg) of CH4 in 2006, an 18 percent decrease over 

1990 emissions (see Table 3-34 and Table 3-35), and 28.5 

Tg CO2 Eq. (28,504 Gg) of non-combustion CO2 in 2006, 

a 15 percent decrease over 1990 emissions (see Table 3-36 

and Table 3-37). Improvements in management practices and 

technology, along with the replacement of older equipment, 

have helped to stabilize emissions. 

CH4 and non-combustion CO2 emissions from natural 

gas systems are generally process related, with normal 

operations, routine maintenance, and system upsets being 

the primary contributors. Emissions from normal operations 

include: natural gas engines and turbine uncombusted 

exhaust, bleed and discharge emissions from pneumatic 

devices, and fugitive emissions from system components. 

Routine maintenance emissions originate from pipelines, 

equipment, and wells during repair and maintenance 

activities. Pressure surge relief systems and accidents can 

lead to system upset emissions. Below is a characterization 

of the four major stages of the natural gas system. Each of 

the stages is described and the different factors affecting CH4

and non-combustion CO2 emissions are discussed. 

Field Production. In this initial stage, wells are used to 

withdraw raw gas from underground formations. Emissions 

arise from the wells themselves, gathering pipelines, and 

well-site gas treatment facilities such as dehydrators and 

separators. Fugitive emissions and emissions from pneumatic 

devices account for the majority of CH4 emissions. Flaring 

emissions account for the majority of the non-combustion 

CO2 emissions. Emissions from field production accounted 

for approximately 27 percent of CH4 emissions and about 

25 percent of non-combustion CO2 emissions from natural 

gas systems in 2006. 

Table 3-33: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal Mines 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Abandoned Underground 

Coal Mines CH4 5.4 4.5 6.4 -17% +19%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Energy 3-43

Processing. In this stage, natural gas liquids and various 

other constituents from the raw gas are removed, resulting in 

“pipeline quality” gas, which is injected into the transmission 

system. Fugitive CH4 emissions from compressors, including 

compressor seals, are the primary emission source from this 

stage. The majority of non-combustion CO2 emissions come 

from acid gas removal units, which are designed to remove 

CO2 from natural gas. Processing plants account for about 12 

percent of CH4 emissions and approximately 74 percent of 

non-combustion CO2 emissions from natural gas systems. 

Transmission and Storage. Natural gas transmission 

involves high pressure, large diameter pipelines that transport 

gas long distances from field production and processing areas 

to distribution systems or large volume customers such as 

Table 3-35: CH4 Emissions from Natural Gas Systems (Gg)a

Stage 1990 1995 2000 2001 2002 2003 2004 2005 2006

Field Production 1,555 1,774 1,849 1,976 2,024 1,909 1,566 1,190 1,317

Processing 707 711 693 699 675 646 639 560 568

Transmission and Storage 2,206 2,181 2,087 1,936 2,019 2,039 1,947 1,834 1,817

Distribution 1,468 1,432 1,395 1,356 1,228 1,279 1,275 1,296 1,176

Total 5,937 6,098 6,024 5,968 5,946 5,874 5,426 4,880 4,877 

a

 Including CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.

Note: Totals may not sum due to independent rounding.

Table 3-34: CH4 Emissions from Natural Gas Systems (Tg CO2 Eq.)a

Stage 1990 1995 2000 2001 2002 2003 2004 2005 2006

Field Production 32.7 37.2 38.8 41.5 42.5 40.1 32.9 25.0 27.6

Processing 14.9 14.9 14.6 14.7 14.2 13.6 13.4 11.8 11.9

Transmission and Storage 46.3 45.8 43.8 40.7 42.4 42.8 40.9 38.5 38.2

Distribution 30.8 30.1 29.3 28.5 25.8 26.9 26.8 27.2 24.7

Total 124.7 128.1 126.5 125.3 124.9 123.3 114.0 102.5 102.4

a

 Including CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.

Note: Totals may not sum due to independent rounding.

Table 3-37: Non-combustion CO2 Emissions from Natural Gas Systems (Gg)

Stage 1990 1995 2000 2001 2002 2003 2004 2005 2006

Field Production 5,876 9,083 5,956 6,307 6,463 6,342 6,242 7,627 7,203

Processing 27,752 24,621 23,333 22,387 23,066 22,002 21,780 21,736 21,204

Transmission and Storage 58 60 60 59 61 61 61 60 59

Distribution 42 42 41 40 40 40 40 39 37

Total 33,729 33,806 29,390 28,793 29,629 28,445 28,122 29,462 28,504

Note: Totals may not sum due to independent rounding.

Table 3-36: Non-combustion CO2 Emissions from Natural Gas Systems (Tg CO2 Eq.)

Stage 1990 1995 2000 2001 2002 2003 2004 2005 2006

Field Production 5.9 9.1 6.0 6.3 6.5 6.3 6.2 7.6 7.2 

Processing 27.8 24.6 23.3 22.4 23.1 22.0 21.8 21.7 21.2 

Transmission and Storage 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Distribution + + + + + + + + + 

Total 33.7 33.8 29.4 28.8 29.6 28.4 28.1 29.5 28.5 

Note: Totals may not sum due to independent rounding.
3-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

power plants or chemical plants. Compressor station facilities, 

which contain large reciprocating and turbine compressors, are 

used to move the gas throughout the United States transmission 

system. Fugitive CH4 emissions from these compressor 

stations and from metering and regulating stations account 

for the majority of the emissions from this stage. Pneumatic 

devices and engine uncombusted exhaust are also sources of 

CH4 emissions from transmission facilities. 

Natural gas is also injected and stored in underground 

formations, or liquefied and stored in above ground tanks, 

during periods of low demand (e.g., summer), and withdrawn, 

processed, and distributed during periods of high demand 

(e.g., winter). Compressors and dehydrators are the primary 

contributors to emissions from these storage facilities. CH4

emissions from the transmission and storage sector account 

for approximately 37 percent of emissions from natural gas 

systems, while CO2 emissions from transmission and storage 

account for less than 1 percent of the non-combustion CO2

emissions from natural gas systems. 

Distribution. Distribution pipelines take the highpressure gas from the transmission system at “city gate” 

stations, reduce the pressure and distribute the gas through 

primarily underground mains and service lines to individual 

end users. There were over 1,250,000 miles of distribution 

mains in 2006, an increase from just over 947,000 miles in 

1990 (OPS 2007b). Distribution system emissions, which 

account for approximately 24 percent of CH4 emissions 

from natural gas systems and less than 1 percent of noncombustion CO2 emissions, result mainly from fugitive 

emissions from gate stations and pipelines.41 An increased 

use of plastic piping, which has lower emissions than other 

pipe materials, has reduced emissions from this stage. 

Distribution system CH4 emissions in 2006 were 20 percent 

lower than 1990 levels.

Methodology

The primary basis for estimates of CH4 and noncombustion-related CO2 emissions from the U.S. natural gas 

industry is a detailed study by the Gas Research Institute 

and EPA (EPA/GRI 1996). The EPA/GRI study developed 

over 80 CH4 emission and activity factors to characterize 

emissions from the various components within the operating 

stages of the U.S. natural gas system. The same activity 

41The percentages of total emissions from each stage may not sum to 100 

percent due to independent rounding.

factors were used to estimate both CH4 and non-combustion 

CO2 emissions. However, the CH4 emission factors were 

adjusted for CO2 content when estimating fugitive and 

vented non-combustion CO2 emissions. The EPA/GRI 

study was based on a combination of process engineering 

studies and measurements at representative gas facilities. 

From this analysis, a 1992 emission estimate was developed 

using the emission and activity factors. For other years, 

a set of industry activity factor drivers was developed 

that can be used to update activity factors. These drivers 

include statistics on gas production, number of wells, 

system throughput, miles of various kinds of pipe, and other 

statistics that characterize the changes in the U.S. natural 

gas system infrastructure and operations. 

See Annex 3.4 for more detailed information on the 

methodology and data used to calculate CH4 and noncombustion CO2 emissions from natural gas systems.

Activity factor data were taken from the following 

sources: American Gas Association (AGA 1991 through 

1998); Minerals and Management Service (MMS 2007a-e); 

Monthly Energy Review (EIA 2007f); Natural Gas Liquids 

Reserves Report (EIA 2005); Natural Gas Monthly (EIA 

2007b,c,e); the Natural Gas STAR Program annual emissions 

savings (EPA 2007); Oil and Gas Journal (OGJ 1997 through 

2007); Office of Pipeline Safety (OPS 2007a-b) and other 

Energy Information Administration publications (EIA 2001, 

2004, 2007a,d); World Oil Magazine (2007a-b). Data for 

estimating emissions from hydrocarbon production tanks is 

incorporated (EPA 1999). Coalbed CH4 well activity factors 

were taken from the Wyoming Oil and Gas Conservation 

Commission (Wyoming 2007) and the Alabama State Oil 

and Gas Board (Alabama 2007). Other state well data was 

taken from: American Association of Petroleum Geologists 

(AAPG 2004); Brookhaven College (Brookhaven 2004); 

Kansas Geological Survey (Kansas 2007); Montana Board 

of Oil and Gas Conservation (Montana 2007); Oklahoma 

Geological Survey (Oklahoma 2007); Morgan Stanley 

(Morgan Stanley 2005); Rocky Mountain Production Report 

(Lippman (2003); New Mexico Oil Conservation Division 

(New Mexico 2007a,b); Texas Railroad Commission (Texas 

2007a-d); Utah Division of Oil, Gas and Mining (Utah 2007). 

Emission factors were taken from EPA/GRI (1996). GTI’s 

Unconventional Natural Gas and Gas Composition Databases 

(GTI 2001) were used to adapt the CH4 emission factors into 

non-combustion related CO2 emission factors. Additional 
Energy 3-45

information about CO2 content in transmission quality 

natural gas was obtained via the internet from numerous 

U.S. transmission companies to help further develop the 

non-combustion CO2 emission factors.

Uncertainty

A quantitative uncertainty analysis was conducted to 

determine the level of uncertainty surrounding estimates of 

emissions from natural gas systems. Performed using @RISK 

software and the IPCC-recommended Tier 2 methodology 

(Monte Carlo Simulation technique), this analysis provides 

for the specification of probability density functions for key 

variables within a computational structure that mirrors the 

calculation of the inventory estimate. The results presented 

below provide with 95 percent certainty the range within 

which emissions from this source category are likely to fall. 

The heterogeneous nature of the natural gas industry 

makes it difficult to sample facilities that are completely 

representative of the entire industry. Because of this, scaling 

up from model facilities introduces a degree of uncertainty. 

Additionally, highly variable emission rates were measured 

among many system components, making the calculated 

average emission rates uncertain. The results of the Tier 2 

quantitative uncertainty analysis is summarized in Table 3-38. 

Natural gas systems CH4 emissions in 2006 were estimated 

to be between 79.1 and 148.4 Tg CO2 Eq. at a 95 percent 

confidence level. Natural gas systems non-combustion CO2

emissions in 2006 were estimated to be between 22.0 and 

41.3 Tg CO2 Eq. at 95 percent confidence level. 

Recalculations Discussion 

Offshore oil and gas platform counts are driven by the 

percentage of total platforms that are located on oil and gas 

fields, respectively, as identified by MMS. This percentage 

can be calculated from MMS (2007a,b,e) for years 2003 

onward. For year 1992, the estimate was provided by MMS 

by direct communication. The oil platform count for years 

1990, 1991, and 1993 through 2002 are driven by a linear 

projection based on known platform counts in 1992 and 

2003. A miscalculation in year 2003 for oil platform count 

was re-estimated, which caused the entire time series prior 

to year 2003 (except 1992) to change. This change resulted 

in a reallocation of platform counts to the natural gas and 

petroleum models. The total number of offshore platforms, 

both oil and gas, used as drivers remained the same. The 

effects of this recalculation are most significant in 1990, 

with an absolute difference of 31 Gg; less significant changes 

occurred in all subsequent years. 

The second recalculation is a result of changing several 

base year (1992) activity factor and emissions factor data 

to the exact values from the EPA/GRI 1996 report. These 

changes were small and the effects were an increase of less 

than 1 percent in 1992 CH4 emissions. 

A third recalculation is the result of updating previous 

years’ activity and Natural Gas STAR reduction values 

with revised data. This is especially evident in 2005, where 

the revised reductions data reports an additional 443 Gg of 

reductions totaled from all four sectors; decreasing total 2005 

emission estimates by nearly 9.5 percent. 

QA/QC and Verification Discussion 

A Tier 2 QA/QC analysis was undertaken to examine why 

emissions from small reciprocating compressors are lower 

in the production sector than in other sectors of the natural 

gas industry. The emission factor for these compressors is 

based on EPA/GRI 1996. Background information from 

EPA/GRI 1996, along with information from the Natural Gas 

STAR program was analyzed and it was determined that the 

Table 3-38: Tier 2 Quantitative Uncertainty Estimates for CH4 and Non-Combustion CO2 Emissions from Natural Gas 

Systems (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Natural Gas Systems CH4 102.4 79.1 148.4 -23% +45%

Natural Gas Systemsb CO2 28.5 22.0 41.3 -23% +45%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

b

 An uncertainty analysis for the non-combustion CO2 emissions was not performed. The relative uncertainty estimated (expressed as a percent) from the 

CH4 uncertainty analysis was applied to the point estimate of non-combustion CO2 emissions.
3-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

emission factor for small compressors in the eastern United 

States (U.S. East) was significantly lower than the emission 

factor developed for the western area of the country (U.S. 

West). Details of the emission factor development revealed 

that the U.S. East emission factor in EPA/GRI 1996 does not 

include fugitives from compressor seals and pressure relief 

valves. Experience from the Natural Gas STAR Program 

demonstrates that seal leakage from rod packing is the largest 

source of fugitive emissions from reciprocating compressors. 

To account for compressor seal leakage, the U.S. West 

emission factor was used for the entire United States for 1990 

through 2006. These updated emission factors are an interim 

improvement and further research is underway to compare 

these updated emissions factors with recent vendor data. 

Planned Improvements

Currently, activity factors for most sources in the natural 

gas inventory are dependent on EPA/GRI 1996 estimates of 

activity data in base year 1992. The activity factors for all 

years other than the base year are estimated from the base 

year activity data and are driven by an appropriate activity 

driver. However, in some instances activity data are directly 

available from published sources and there is no need to 

derive the current year activity data through the use of drivers. 

Research is underway to determine the feasibility of using 

published activity data, where available, and whether this 

would impact any of the emission factors currently used. 

Separately, work has been initiated to update select 

emission factors from the earlier study. Where relevant, these 

emission factors will be incorporated into the Inventory when 

they become available. 

As noted above, additional research will be undertaken 

to evaluate, and as necessary refine, the emission factor for 

small reciprocating compressors in the U.S. West region. 

3.8. Petroleum Systems (IPCC 

Source Category 1B2a)

CH4 emissions from petroleum systems are primarily 

associated with crude oil production, transportation, 

and refining operations. During each of these activities, 

CH4 emissions are released to the atmosphere as fugitive 

emissions, vented emissions, emissions from operational 

upsets, and emissions from fuel combustion. Fugitive and 

vented CO2 emissions from petroleum systems are primarily 

associated with crude oil production and are negligible in 

the transportation and refining operations. Combusted CO2

emissions are already accounted for in the Fossil Fuels 

Combustion calculations previously discussed, and hence 

have not been taken into account in this Inventory. Total CH4

and CO2 emissions from petroleum systems in 2006 were 

28.4 Tg CO2 Eq. (1,354 Gg CH4) and 0.3 Tg CO2 (293 Gg) 

respectively. Since 1990, CH4 emissions have declined by 

16 percent, due to industry efforts to reduce emissions and 

a decline in domestic oil production (see Table 3-39, Table 

3-40, Table 3-41, and Table 3-42). CO2 emissions have also 

declined by 22 percent since 1990 due to similar reasons. 

Production Field Operations. Production field operations 

account for over 97 percent of total CH4 emissions from 

petroleum systems. Vented CH4 from field operations account 

for over 91 percent of the emissions from the production 

sector, unburned CH4 combustion emissions account for 5.2 

percent, fugitive emissions are 3.4 percent, and process upset 

emissions, slightly over one-tenth of a percent. The most 

dominant sources of emissions, in the order of magnitude, 

are shallow water offshore oil platforms, natural-gas-powered 

pneumatic devices (low bleed and high bleed), field storage 

tanks, gas engines, chemical injection pumps and deep water 

offshore platforms. These seven sources alone emit over 95 

percent of the production field operations emissions. Offshore 

platform emissions are a combination of fugitive, vented, 

and unburned fuel combustion emissions from all equipment 

housed on oil platforms producing oil and associated gas. 

Emissions from high and low-bleed pneumatics occur when 

pressurized gas that is used for control devices is bled to the 

atmosphere as they cycle open and closed to modulate the 

system. Emissions from storage tanks occur when the CH4

entrained in crude oil under pressure volatilizes once the 

crude oil is put into storage tanks at atmospheric pressure. 

Emissions from gas engines are due to unburned CH4 that 

vents with the exhaust. Emissions from chemical injection 

pumps are due to the 25 percent that use associated gas to 

drive pneumatic pumps. The remaining five percent of the 

emissions are distributed among 26 additional activities 

within the four categories: vented, fugitive, combustion and 

process upset emissions. For more detailed, source-level, 

data on methane emissions in production field operations 

refer to Annex 3.5.
Energy 3-47

Table 3-39: CH4 Emissions from Petroleum Systems (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Production Field Operations 33.2 31.3 29.6 29.5 29.2 28.5 28.0 27.6 27.7 

Pneumatic device venting 10.3 9.7 9.0 8.9 8.9 8.7 8.6 8.3 8.4 

Tank venting 3.8 3.4 3.2 3.2 3.2 3.1 3.0 2.8 2.9 

Combustion & process upsets 1.9 1.7 1.6 1.6 1.6 1.5 1.5 1.5 1.5 

Misc. venting & fugitives 16.8 16.0 15.3 15.3 15.1 14.7 14.5 14.5 14.5 

Wellhead fugitives 0.5 0.5 0.5 0.5 0.5 0.5 0.4 0.4 0.4 

Crude Oil Transportation 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Refining 0.5 0.5 0.6 0.6 0.6 0.6 0.6 0.6 0.6 

Total 33.9 32.0 30.3 30.2 29.9 29.2 28.7 28.3 28.4 

Note: Totals may not sum due to independent rounding.

Table 3-40: CH4 Emissions from Petroleum Systems (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Production Field Operations 1,581 1,493 1,409 1,404 1,390 1,357 1,335 1,314 1,321 

Pneumatic device venting 489 463 428 425 424 412 408 397 399 

Tank venting 179 161 154 154 151 150 142 135 138 

Combustion & process upsets 88 82 76 75 75 73 72 71 72 

Misc. venting & fugitives 799 762 728 727 717 701 692 691 693 

Wellhead fugitives 26 25 22 22 23 22 21 20 20 

Crude Oil Transportation 7 6 5 5 5 5 5 5 5 

Refining 25 25 28 27 27 27 28 28 28 

Total 1,612 1,524 1,442 1,436 1,422 1,390 1,368 1,346 1,354 

Note: Totals may not sum due to independent rounding.

Table 3-41: CO2 Emissions from Petroleum Systems (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Production Field Operations 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Pneumatic device venting + + + + + + + + +

Tank venting 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.3 

Misc. venting & fugitives + + + + + + + + +

Wellhead fugitives + + + + + + + + +

Total 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

+ Does not exceed 0.05 Tg CO2 Eq. 

Table 3-42: CO2 Emissions from Petroleum Systems (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Production Field Operations 376 341 325 325 320 316 302 287 293

Pneumatic device venting 27 26 24 24 24 23 23 22 22 

Tank venting 328 296 283 283 278 276 262 248 253 

Misc. venting & fugitives 18 18 17 17 16 16 16 16 16 

Wellhead fugitives 1 1 1 1 1 1 1 1 1 

Total 376 341 325 325 320 316 302 287 293 

Note: Totals may not sum due to independent rounding.
3-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Vented CO2 associated with natural gas emissions 

from field operations account for 99 percent of the total 

CO2 emissions, while fugitive and process upsets together 

account for 1 percent of the emissions. The most dominant 

sources of vented emissions are field storage tanks, 

pneumatic devices (high bleed and low bleed), shallow 

water offshore oil platforms, and chemical injection pumps. 

These five sources together account for 98.5 percent of the 

non-combustion CO2 emissions while the remaining 1.5 

percent of the emissions is distributed among 24 additional 

activities within the three categories: vented, fugitive and 

process upsets. 

Crude Oil Transportation. Crude oil transportation 

activities account for less than one half of one percent of 

total CH4 emissions from the oil industry. Venting from tanks 

and marine vessel loading operations accounts for 64 percent 

of CH4 emissions from crude oil transportation. Fugitive 

emissions, almost entirely from floating roof tanks, account 

for 19 percent. The remaining 17 percent is distributed among 

six additional sources within these two categories. Emissions 

from pump engine drivers and heaters were not estimated 

due to lack of data. 

Crude Oil Refining. Crude oil refining processes and 

systems account for slightly over two percent of total CH4

emissions from the oil industry because most of the CH4

in crude oil is removed or escapes before the crude oil is 

delivered to the refineries. There is an insignificant amount 

of CH4 in all refined products. Within refineries, vented 

emissions account for about 87 percent of the emissions, 

while fugitive and combustion emissions account for 

approximately six and seven percent, respectively. Refinery 

system blowdowns for maintenance and the process of asphalt 

blowing—with air, to harden the asphalt—are the primary 

venting contributors. Most of the fugitive CH4 emissions 

from refineries are from leaks in the fuel gas system. Refinery 

combustion emissions include small amounts of unburned 

CH4 in process heater stack emissions and unburned CH4 in 

engine exhausts and flares. 

Methodology

The methodology for estimating CH4 emissions 

from petroleum systems is a bottom-up approach, based 

on comprehensive studies of CH4 emissions from U.S. 

petroleum systems (EPA 1996, EPA 1999). These studies 

combined emission estimates from 64 activities occurring 

in petroleum systems from the oil wellhead through crude 

oil refining, including 33 activities for crude oil production 

field operations, 11 for crude oil transportation activities, 

and 20 for refining operations. Annex 3.5 provides greater 

detail on the emission estimates for these 64 activities. The 

estimates of CH4 emissions from petroleum systems do 

not include emissions downstream of oil refineries because 

these emissions are very small compared to CH4 emissions 

upstream of oil refineries.

The methodology for estimating CH4 emissions from the 

64 oil industry activities employs emission factors initially 

developed by EPA (1999) and activity factors that are based 

on two EPA studies (1996, 1999) and EPA (2005). Emissions 

are estimated for each activity by multiplying emission factors 

(e.g., emission rate per equipment item or per activity) by 

their corresponding activity factor (e.g., equipment count or 

frequency of activity). The report provides emission factors 

and activity factors for all activities except those related to 

offshore oil production and field storage tanks. For offshore 

oil production, two emission factors were calculated using 

data collected over a one-year period for all federal offshore 

platforms (EPA 2005, MMS 2004). One emission factor is 

for oil platforms in shallow water, and one emission factor 

is for oil platforms in deep water. Emission factors are held 

constant for the period 1990 through 2006. The number of 

platforms in shallow water and the number of platforms in 

deep water are used as activity factors and are taken from 

Minerals Management Service statistics (MMS 2007a-c). 

For oil storage tanks, the emission factor was calculated 

from API TankCalc data as the total emissions per barrel of 

crude charge (EPA 1999).

The methodology for estimating CO2 emissions from 

petroleum systems combines vented, fugitive and process 

upset emissions sources from 29 activities for crude oil 

production field operations. Emissions are estimated for 

each activity by multiplying emission factors by their 

corresponding activity factors. The emission factors for 

CO2 are estimated by multiplying the CH4 emission factors 

by a conversion factor, which is the ratio of CO2 content 

and methane content in produced associated gas. The only 

exceptions to this methodology are the emission factors 

for crude oil storage tanks which are obtained from API 

TankCalc simulation runs.
Energy 3-49

Activity factors for years 1990 through 2006 were 

collected from a wide variety of statistical resources. For 

some years, complete activity factor data were not available. 

In such cases, one of three approaches was employed. Where 

appropriate, the activity factor was calculated from related 

statistics using ratios developed for EPA (1996). For example, 

EPA (1996) found that the number of heater treaters (a source 

of CH4 emissions) is related to both number of producing 

wells and annual production. To estimate the activity factor 

for heater treaters, reported statistics for wells and production 

were used, along with the ratios developed for EPA (1996). 

In other cases, the activity factor was held constant from 

1990 through 2006 based on EPA (1999). Lastly, the previous 

year’s data were used when data for the current year were 

unavailable. The CH4 and CO2 sources in the production 

sector share common activity factors. See Annex 3.5 for 

additional detail. 

Nearly all emission factors were taken from EPA (1995, 

1996, 1999). The remaining emission factors were taken 

from EPA default values in (EPA 2005) and the consensus 

of industry peer review panels. 

Among the more important references used to obtain 

activity factors are the Energy Information Administration 

annual and monthly reports (EIA 1990 through 2006, 1990 

through 2007, 1995 through 2007a-b), Methane Emissions 

from the Natural Gas Industry by the Gas Research Institute 

and EPA (EPA/GRI 1996a-d), Estimates of Methane 

Emissions from the U.S. Oil Industry (EPA 1999), consensus 

of industry peer review panels, MMS reports (MMS 2001, 

2007a-c), analysis of MMS data (EPA 2005, MMS 2004), 

the Oil & Gas Journal (OGJ 2007a,b), the Interstate Oil and 

Gas Compact Commission (IOGCC 2007), and the United 

States Army Corps of Engineers (1995–2005). 

Uncertainty 

This section describes the analysis conducted to quantify 

uncertainty associated with the estimates of emissions from 

petroleum systems. Performed using @RISK software and 

the IPCC-recommended Tier 2 methodology (Monte Carlo 

Simulation technique), the method employed provides for 

the specification of probability density functions for key 

variables within a computational structure that mirrors the 

calculation of the inventory estimate. The results provide 

the range within which, with 95 percent certainty, emissions 

from this source category are likely to fall. 

The detailed, bottom-up inventory analysis used to 

evaluate U.S. petroleum systems reduces the uncertainty 

related to the CH4 emission estimates in comparison with 

a top-down approach. However, some uncertainty still 

remains. Emission factors and activity factors are based on 

a combination of measurements, equipment design data, 

engineering calculations and studies, surveys of selected 

facilities and statistical reporting. Statistical uncertainties 

arise from natural variation in measurements, equipment 

types, operational variability and survey and statistical 

methodologies. Published activity factors are not available 

every year for all 64 activities analyzed for petroleum systems; 

therefore, some are estimated. Because of the dominance of 

the seven major sources, which account for 93.0 percent of 

the total emissions, the uncertainty surrounding these seven 

sources has been estimated most rigorously, and serves as the 

basis for determining the overall uncertainty of petroleum 

systems emission estimates. 

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 3-43. Petroleum systems CH4

emissions in 2006 were estimated to be between 20.5 and 

69.3 Tg CO2 Eq., while CO2 emissions were estimated to be 

Table 3-43: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Petroleum Systems CH4 28.4 20.5 69.3 -28% +144%

Petroleum Systems CO2 0.3 0.2 0.7 -28% +144%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
3-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

between 0.2 and 0.7 Tg CO2 Eq. at a 95 percent confidence 

level. This indicates a range of 28 percent below to 144 

percent above the 2006 emission estimates of 28.4 and 0.3 

Tg CO2 Eq. for CH4 and CO2, respectively. 

Recalculations Discussion 

Estimates of vented, fugitive, and process upset CO2

emissions from the production sector were incorporated into 

the petroleum systems emission estimates for 1990 through 

2006. CO2 emissions were estimated using the methane 

emission sources’ activity factors and drivers for the 

corresponding CO2 emission sources. The emission factors 

for CO2 were estimated by multiplying the methane emission 

factors by a conversion factor, which is the ratio of CO2

content divided by CH4 content in produced associated gas. 

The only exceptions to this methodology are the emission 

factors for crude oil storage tanks, which were estimated 

from API TankCalc simulation runs. CO2 emissions from 

the production sector account for 293 Gg of CO2 in the year 

2006. CO2 emissions from the transportation and refining 

sectors are assumed to be negligible. Combustion emissions 

are already accounted for in the Fossils Fuels Combustion 

section of this chapter.

In addition, two types of activity factor and seven types of 

activity driver revisions were made for the current Inventory. 

All revisions but one were due to updating previous years’ data 

with revised data from existing data sources. The one exception 

to the general revisions was the recalculation of an activity 

driver for oil platforms. Offshore oil and gas platform counts 

are driven by the percentage of total platforms that are located 

on oil and gas fields, respectively, as identified by MMS. This 

percentage can be calculated from MMS (2007a-c) for years 

2003 onward. For year 1992, the estimate was provided by 

MMS by direct communication. The oil platform counts for 

years 1990, 1991, and 1993 through 2002 are driven by a linear 

projection based on known platform counts in 1992 and 2003. 

A miscalculation in year 2003 was re-estimated, causing the 

entire time series prior to year 2003 (except 1992) to change. 

This change resulted in a reallocation of platform counts to 

the natural gas and petroleum models. The total number of 

offshore platforms, both oil and gas, used as drivers remained 

the same.

Overall changes resulted in a decrease in total emissions 

of approximately 0.22 Tg CO2 Eq. (0.8 percent) for year 

2005. For 1990 and 1991, total emissions decreased by 

2 percent or less; while between 1993 and 2004 the total 

emission estimates increased by up to 13 percent from the 

previous inventory’s estimates. This increase is largely due 

to the recalculation of the oil platform activity driver.

Planned Improvements

As noted above, nearly all emission factors used in the 

development of the petroleum systems estimates were taken 

from EPA (1995, 1996, 1999), with the remaining emission 

factors taken from EPA default values in (EPA 2005) and a 

consensus of industry peer review panels. These emission 

factors will be reviewed as part of future inventory work. 

Results of this review and analysis will be incorporated into 

future Inventories, as appropriate. 

3.9. Municipal Solid Waste 

Combustion (IPCC Source Category 

1A5)

Combustion is used to manage about 7 to 17 percent 

of the municipal solid wastes (MSW) generated in the 

United States, depending on the source of the estimate and 

the scope of materials included in the definition of solid 

waste (EPA 2000b, Goldstein and Matdes 2001, Kaufman 

et al. 2004a, Simmons et al. 2006). Almost all combustion 

of municipal solid wastes in the United States occurs at 

waste-to-energy facilities where useful energy is recovered, 

and thus emissions from waste combustion are accounted 

for in the Energy chapter. Combustion of municipal solid 

wastes results in conversion of the organic inputs to CO2. 

According to IPCC guidelines, when the CO2 emitted is of 

fossil origin, it is counted as a net anthropogenic emission 

of CO2 to the atmosphere. Thus, the emissions from waste 

combustion are calculated by estimating the quantity of waste 

combusted and the fraction of the waste that is C derived 

from fossil sources.

Most of the organic materials in municipal solid wastes 

are of biogenic origin (e.g., paper, yard trimmings), and have 

their net C flows accounted for under the Land Use, Land-Use 

Change, and Forestry chapter. However, some components—

plastics, synthetic rubber, synthetic fibers, and carbon 

black—are of fossil origin. Plastics in the U.S. waste stream 

are primarily in the form of containers, packaging, and durable 

goods. Rubber is found in durable goods, such as carpets, and 

in non-durable goods, such as clothing and footwear. Fibers in 
Energy 3-51

Box 3-3: Carbon Dioxide Transport, Injection, and Geological Storage

Carbon dioxide is produced, captured, transported, and used for Enhanced Oil Recovery (EOR) as well as commercial and non-EOR industrial 

applications. This CO2 is produced from both naturally-occurring CO2 reservoirs and from industrial sources such as natural gas processing 

plants and ammonia plants. In the current Inventory, emissions from naturally-produced CO2 are estimated based on the application.

In the current Inventory report, the CO2 that is used in non-EOR industrial and commercial applications (e.g., food processing, chemical 

production) is assumed to be emitted to the atmosphere during its industrial use. These emissions are discussed in the Carbon Dioxide 

Consumption section. The naturally-occurring CO2 used in EOR operations is assumed to be fully sequestered. Additionally, all anthropogenic 

CO2 emitted from natural gas processing and ammonia plants is assumed to be emitted to the atmosphere, regardless of whether the CO2 is 

captured or not. These emissions are currently included in the Natural Gas Systems and the Ammonia Production sections of the Inventory 

report, respectively.

IPCC (2006) includes, for the first time, methodological guidance to estimate emissions from the capture, transport, injection, and 

geological storage of CO2. The methodology is based on the principle that the carbon capture and storage system should be handled in a 

complete and consistent manner across the entire Energy sector. The approach accounts for CO2 captured at natural and industrial sites as 

well as emissions from capture, transport, and use. For storage specifically, a Tier 3 methodology is outlined for estimating and reporting 

emissions based on site-specific evaluations. However, IPCC (2006) notes that if a national regulatory process exists, emissions information 

available through that process may support development of CO2 emissions estimates for geologic storage.

In October 2007, the U.S. EPA announced plans to develop regulations for geologic sequestration of CO2 under the EPA Underground 

Injection Control Program. Given that the regulatory process is in its early phases, and site-specific emissions estimates are not yet available, 

emissions estimates from CO2 capture, transport, injection and geologic storage are not yet included in national totals. Preliminary estimates 

indicate that the amount of CO2 captured from industrial and natural sites, as well as fugitive emissions from pipelines is 39.0 Tg CO2 (39,041 

Gg CO2) (see Table 3-44). Site-specific monitoring and reporting data for CO2 injection sites (i.e., EOR operations) were not readily available, 

therefore, these estimates assume all CO2 is emitted. 

Table 3-45: Potential Emissions from CO2 Capture and Transport (Gg)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Acid Gas Removal Plants 4,832 3,672 2,264 2,894 2,943 2,993 3,719 5,992 6,997

Naturally Occurring CO2 15,129 22,547 23,149 23,442 22,967 24,395 27,002 28,192 31,359

Ammonia Production Plants 0 676 676 676 676 676 676 676 676

Pipelines Transporting CO2 8 8 8 8 8 8 7 7 8

Total 19,969 26,904 26,098 27,020 26,595 28,073 31,405 34,868 39,041

Table 3-44: Potential Emissions from CO2 Capture and Transport (Tg CO2 Eq.)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Acid Gas Removal Plants 4.8 3.7 2.3 2.9 2.9 3.0 3.7 6.0 7.0

Naturally Occurring CO2 15.1 22.7 23.1 23.4 23.0 24.4 27.0 28.2 31.4

Ammonia Production Plants 0.0 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7

Pipelines Transporting CO2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Total 20.0 26.9 26.1 27.0 26.6 28.1 31.4 34.9 39.0
3-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

municipal solid wastes are predominantly from clothing and 

home furnishings. Tires (which contain rubber and carbon 

black) are also considered a “non-hazardous” waste and are 

included in the municipal solid waste combustion estimate, 

though waste disposal practices for tires differ from the rest of 

municipal solid waste (viz., most combustion occurs outside 

of MSW combustion facilities).

Over 31 million metric tons of municipal solid wastes 

were combusted in the United States in 2006 (EPA 2007). 

CO2 emissions from combustion of municipal solid wastes 

rose 91 percent since 1990, to an estimated 20.9 Tg CO2

Eq. (20,922 Gg) in 2006, as the volume of synthetic fibers 

and other fossil C-containing materials in MSW increased 

(see Table 3-46 and Table 3-47). Waste combustion is also 

a source of N2O emissions (De Soete 1993). N2O emissions 

from municipal solid waste combustion were estimated to be 

0.4 Tg CO2 Eq. (1 Gg N2O) in 2006, and have not changed 

significantly since 1990.

Methodology

Emissions of CO2 from MSW combustion include 

CO2 generated by the combustion of plastics, synthetic 

fibers, and synthetic rubber, as well as the combustion of 

synthetic rubber and carbon black in tires. These emissions 

were estimated by multiplying the amount of each material 

combusted by the C content of the material and the fraction 

oxidized (98 percent). Plastics combusted in municipal solid 

wastes were categorized into seven plastic resin types, each 

material having a discrete C content. Similarly, synthetic 

rubber is categorized into three product types, and synthetic 

fibers were categorized into four product types, each having 

a discrete C content. Scrap tires contain several types of 

synthetic rubber, as well as carbon black. Each type of 

synthetic rubber has a discrete C content, and carbon black 

is 100 percent C. Emissions of CO2 were calculated based 

on the number of scrap tires used for fuel and the synthetic 

rubber and carbon black content of the tires. 

More detail on the methodology for calculating 

emissions from each of these waste combustion sources is 

provided in Annex 3.6. 

For each of the methods used to calculate CO2 emissions 

from municipal solid waste combustion, data on the quantity 

of product combusted and the C content of the product are 

needed. For plastics, synthetic rubber, and synthetic fibers, 

the amount of material in municipal solid wastes and its 

Table 3-46: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Tg CO2 Eq.)

Gas/Waste Product 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 10.9 15.7 17.5 18.0 18.5 19.1 20.1 20.7 20.9 

Plastics 8.0 10.3 11.8 12.1 12.3 12.7 13.4 13.7 13.7 

Synthetic Rubber in Tires 0.2 0.8 0.9 0.9 1.0 1.0 1.1 1.2 1.2 

Carbon Black in Tires 0.2 1.1 1.2 1.2 1.2 1.3 1.4 1.6 1.6 

Synthetic Rubber in MSW 1.3 1.6 1.6 1.7 1.8 1.8 1.9 1.9 1.9 

Synthetic Fibers 1.2 1.8 2.0 2.1 2.2 2.3 2.3 2.4 2.5 

N2O 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.4 0.4 

Total 11.4 16.2 17.9 18.4 18.9 19.5 20.5 21.1 21.3 

Note: Totals may not sum due to independent rounding.

Table 3-47: CO2 and N2O Emissions from Municipal Solid Waste Combustion (Gg)

Gas/Waste Product 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 10,950 15,712 17,518 17,971 18,458 19,058 20,097 20,673 20,922

Plastics 7,976 10,347 11,791 12,094 12,316 12,657 13,356 13,662 13,746

Synthetic Rubber in Tires 191 841 893 895 952 1,010 1,108 1,207 1,207

Carbon Black in Tires 249 1,099 1,167 1,170 1,245 1,320 1,449 1,579 1,579

Synthetic Rubber in MSW 1,334 1,596 1,640 1,721 1,760 1,815 1,871 1,873 1,902

Synthetic Fibers 1,200 1,830 2,027 2,090 2,185 2,257 2,312 2,352 2,489

N2O 2 1 1 1 1 1 1 1 1

Note: Totals may not sum due to independent rounding.
Energy 3-53

portion combusted were taken from the Characterization 

of Municipal Solid Waste in the United States (EPA 2000b, 

2002, 2003, 2005a, 2006b, 2007) and detailed unpublished 

backup data for some years not shown in the reports 

(Schneider 2007). For synthetic rubber and carbon black in 

scrap tires, information was obtained from U.S. Scrap Tire 

Markets in the United States 2005 Edition (RMA 2006) and 

Scrap Tires, Facts and Figures (STMC 2000 through 2003, 

2006). For 2006, synthetic rubber data is set equal to 2005 

due to a lack of more recently available data.

Average C contents for the “Other” plastics category, 

synthetic rubber in municipal solid wastes, and synthetic fibers 

were calculated from 1998 production statistics, which divide 

their respective markets by chemical compound. Information 

about scrap tire composition was taken from the Scrap Tire 

Management Council’s internet site (STMC 2006).

The assumption that 98 percent of organic C is oxidized 

(which applies to all municipal solid waste combustion 

categories for CO2 emissions) was reported in EPA’s life 

cycle analysis of greenhouse gas emissions and sinks from 

management of solid waste (EPA 2006a).

Combustion of municipal solid waste also results in 

emissions of N2O. These emissions were calculated as a 

function of the total estimated mass of municipal solid waste 

combusted and an emission factor. The N2O emission estimates 

are based on different data sources than the CO2 emission 

estimates. As noted above, N2O emissions are a function of 

total waste combusted in each year; for 1990 through 2004, 

these data were derived from the information published 

in BioCycle (Simmons et al. 2006). Data on total waste 

combusted was not available for 2005 and 2006, so the values 

for 2005 and 2006 were assumed to equal the most recent value 

available (2004). Table 3-48 provides data on municipal solid 

waste generation and percentage combustion for the total waste 

stream. The emission factor of N2O emissions per quantity of 

municipal solid waste combusted is an average of values from 

IPCC’s Good Practice Guidance (2000).

Uncertainty 

A Tier 2 Monte Carlo analysis was performed to determine 

the level of uncertainty surrounding the estimates of CO2

emissions and N2O emissions from municipal solid waste 

combustion. IPCC Tier 2 analysis allows the specification 

of probability density functions for key variables within a 

computational structure that mirrors the calculation of the 

inventory estimate. Uncertainty estimates and distributions 

for waste generation variables (i.e., plastics, synthetic rubber, 

and textiles generation) were obtained through a conversation 

with one of the authors of the Municipal Solid Waste in the 

United States reports. Statistical analyses or expert judgments 

of uncertainty were not available directly from the information 

sources for the other variables; thus, uncertainty estimates 

for these variables were determined using assumptions based 

on source category knowledge and the known uncertainty 

estimates for the waste generation variables.

The uncertainties in the waste combustion emission 

estimates arise from both the assumptions applied to 

the data and from the quality of the data. Key factors 

include MSW combustion rate; fraction oxidized; missing 

data on MSW composition; average C content of MSW 

components; assumptions on the synthetic/biogenic C ratio; 

and combustion conditions affecting N2O emissions. The 

highest levels of uncertainty surround the variables that 

are based on assumptions (e.g., percent of clothing and 

footwear composed of synthetic rubber); the lowest levels 

of uncertainty surround variables that were determined by 

quantitative measurements (e.g., combustion efficiency, C 

content of C black).

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 3-49. Municipal solid waste 

combustion CO2 emissions in 2006 were estimated to be 

between 16.8 and 23.7 Tg CO2 Eq. at a 95 percent confidence 

level. This indicates a range of 20 percent below to 13 

percent above the 2006 emission estimate of 20.9 Tg CO2

Table 3-48: Municipal Solid Waste Generation (Metric 

Tons) and Percent Combusted

Year Waste Generation Combusted (%)

1990 266,365,714 11.5

1995 296,390,405 10.0

2000 371,071,109 7.0

2001 353,086,962a 7.4a

2002 335,102,816 7.7

2003 343,482,645b 7.6b

2004 351,862,474 7.4

2005 351,862,474c 7.4c

2006 351,86,2474c 7.4c

a Interpolated between 2000 and 2002 values.

b Interpolated between 2002 and 2004 values.

c Assumed equal to 2004 value.
3-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Eq. Also at a 95 percent confidence level, municipal solid 

waste combustion N2O emissions in 2006 were estimated to 

be between 0.1 and 1.1 Tg CO2 Eq. This indicates a range 

of 66 percent below to 184 percent above the 2006 emission 

estimate of 0.4 Tg CO2 Eq. 

QA/QC and Verification

A source-specific QA/QC plan was implemented for 

MSW Combustion. This effort included a Tier 1 analysis, as 

well as portions of a Tier 2 analysis. The Tier 2 procedures 

that were implemented involved checks specifically focusing 

on the activity data and specifically focused on the emission 

factor and activity data sources and methodology used for 

estimating emissions from MSW combustion. Trends across 

the time series were analyzed to determine whether any 

corrective actions were needed. 

Planned Improvements

Additional data sources for calculating an N2O emission 

factor for U.S. MSW combustion will be investigated for 

future drafts. In addition, the use of new techniques using 

radiocarbon dating to directly measure biogenic C content 

of MSW combustion flue gas will also be investigated. 

Additional data sources for calculating an N2O emission 

factor for U.S. MSW combustion will be investigated for 

future drafts. In addition, the use of new techniques using 

radiocarbon dating to directly measure biogenic C content 

of MSW combustion flue gas will also be investigated. 

Furthermore, efforts have been initiated to reconcile 

differences in the separate data sources used for the CO2 and 

N2O emission calculations

3.10. Energy Sources of Indirect 

Greenhouse Gas Emissions

In addition to the main greenhouse gases addressed 

above, many energy-related activities generate emissions of 

indirect greenhouse gases. Total emissions of nitrogen oxides 

(NOx), carbon monoxide (CO), and non-CH4 volatile organic 

compounds (NMVOCs) from energy-related activities from 

1990 to 2006 are reported in Table 3-50. 

Methodology

These emission estimates were obtained from 

preliminary data (EPA 2008), and disaggregated based on 

EPA (2003), which, in its final iteration, will be published 

on the National Emission Inventory (NEI) Air Pollutant 

Emission Trends web site. Emissions were calculated either 

for individual categories or for many categories combined, 

using basic activity data (e.g., the amount of raw material 

processed) as an indicator of emissions. National activity 

data were collected for individual categories from various 

agencies. Depending on the category, these basic activity 

data may include data on production, fuel deliveries, raw 

material processed, etc.

Activity data were used in conjunction with emission 

factors, which together relate the quantity of emissions to the 

activity. Emission factors are generally available from the 

EPA’s Compilation of Air Pollutant Emission Factors, AP-42 

(EPA 1997). The EPA currently derives the overall emission 

control efficiency of a source category from a variety of 

information sources, including published reports, the 1985 

Table 3-49: Tier 2 Quantitative Uncertainty Estimates for CO2 and N2O from Municipal Solid Waste Combustion 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Municipal Solid Waste Combustion CO2 20.9 16.8 23.7 -20% +13%

Municipal Solid Waste Combustion N2O 0.4 0.1 1.1 -66% +184%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Energy 3-55

National Acid Precipitation and Assessment Program 

emissions inventory, and other EPA databases.

Uncertainty

Uncertainties in these estimates are partly due to the 

accuracy of the emission factors used and accurate estimates 

of activity data. A quantitative uncertainty analysis was 

not performed.

3.11. International Bunker Fuels 

(IPCC Source Category 1: Memo 

Items)

Emissions resulting from the combustion of fuels used 

for international transport activities, termed international 

bunker fuels under the UNFCCC, are currently not included 

in national emission totals, but are reported separately 

based upon location of fuel sales. The decision to report 

emissions from international bunker fuels separately, instead 

of allocating them to a particular country, was made by the 

Intergovernmental Negotiating Committee in establishing the 

Framework Convention on Climate Change.42 These decisions 

are reflected in the Revised 1996 IPCC Guidelines, as well 

as the 2006 IPCC GLs, in which countries are requested to 

report emissions from ships or aircraft that depart from their 

ports with fuel purchased within national boundaries and are 

engaged in international transport separately from national 

totals (IPCC/UNEP/OECD/IEA 1997).43

Greenhouse gases emitted from the combustion of 

international bunker fuels, like other fossil fuels, include CO2, 

CH4 and N2O. Two transport modes are addressed under the 

IPCC definition of international bunker fuels: aviation and 

marine.44 Emissions from ground transport activities—by 

road vehicles and trains—even when crossing international 

borders are allocated to the country where the fuel was loaded 

into the vehicle and, therefore, are not counted as bunker 

fuel emissions.

42 See report of the Intergovernmental Negotiating Committee for a 

Framework Convention on Climate Change on the work of its ninth 

session, held at Geneva from 7 to 18 February 1994 (A/AC.237/55, annex 

I, para. 1c).

43Note that the definition of international bunker fuels used by the UNFCCC 

differs from that used by the International Civil Aviation Organization.

44 Most emission related international aviation and marine regulations are 

under the rubric of the International Civil Aviation Organization (ICAO) or 

the International Maritime Organization (IMO), which develop international 

codes, recommendations, and conventions, such as the International 

Convention of the Prevention of Pollution from Ships (MARPOL).

Table 3-50: NOx, CO, and NMVOC Emissions from Energy-Related Activities (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

NOx 21,024 20,631 18,537 17,714 17,364 16,474 15,607 15,005 14,309

Mobile Combustion 10,920 10,622 10,310 9,819 10,154 9,642 9,191 8,739 8,287

Stationary Combustion 9,883 9,821 8,002 7,667 6,791 6,419 6,004 5,853 5,610

Oil and Gas Activities 139 100 111 113 321 316 316 316 315

Municipal Solid Waste Combustion 82 88 114 114 98 97 97 97 97

International Bunker Fuels a 1,985 1,540 1,334 1,266 988 900 1,190 1,190 1,731

CO 125,640 104,402 89,715 86,046 82,148 77,689 73,731 69,773 65,815

Mobile Combustion 119,360 97,630 83,559 79,851 75,421 71,038 67,096 63,154 59,213

Stationary Combustion 5,000 5,383 4,340 4,377 4,965 4,893 4,876 4,860 4,844

Municipal Solid Waste Combustion 302 316 146 147 323 321 321 321 322

Oil and Gas Activities 978 1,073 1,670 1,672 1,439 1,437 1,437 1,437 1,437

International Bunker Fuels a 115 113 124 120 118 112 128 133 150

NMVOCs 12,620 10,538 8,953 8,610 9,608 9,223 8,910 8,597 8,284

Mobile Combustion 10,932 8,745 7,230 6,872 7,235 6,885 6,587 6,289 5,991

Stationary Combustion 912 973 1,077 1,080 1,585 1,560 1,553 1,545 1,538

Oil and Gas Activities 554 582 389 400 545 538 533 528 523

Municipal Solid Waste Combustion 222 237 257 258 243 239 237 235 232

International Bunker Fuels a 59 48 44 42 35 32 41 41 56

a

 These values are presented for informational purposes only and are not included in totals.

Note: Totals may not sum due to independent rounding.
3-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

The IPCC Guidelines distinguish between different 

modes of air traffic. Civil aviation comprises aircraft used for 

the commercial transport of passengers and freight, military 

aviation comprises aircraft under the control of national 

armed forces, and general aviation applies to recreational and 

small corporate aircraft. The IPCC Guidelines further define 

international bunker fuel use from civil aviation as the fuel 

combusted for civil (e.g., commercial) aviation purposes by 

aircraft arriving or departing on international flight segments. 

However, as mentioned above, and in keeping with the IPCC 

Guidelines, only the fuel purchased in the United States and 

used by aircraft taking-off (i.e., departing) from the United 

States are reported here. The standard fuel used for civil 

aviation is kerosene-type jet fuel, while the typical fuel used 

for general aviation is aviation gasoline.45

Emissions of CO2 from aircraft are essentially a function 

of fuel use. CH4 and N2O emissions also depend upon engine 

characteristics, flight conditions, and flight phase (i.e., takeoff, climb, cruise, decent, and landing). CH4 is the product 

of incomplete combustion and occur mainly during the 

landing and take-off phases. In jet engines, N2O is primarily 

produced by the oxidation of atmospheric nitrogen, and 

the majority of emissions occur during the cruise phase. 

International marine bunkers comprise emissions from fuels 

burned by ocean-going ships of all flags that are engaged 

in international transport. Ocean-going ships are generally 

classified as cargo and passenger carrying, military (i.e., 

Navy), fishing, and miscellaneous support ships (e.g., 

tugboats). For the purpose of estimating greenhouse gas 

emissions, international bunker fuels are solely related to 

cargo and passenger carrying vessels, which is the largest of 

the four categories, and military vessels. Two main types of 

fuels are used on sea-going vessels: distillate diesel fuel and 

residual fuel oil. CO2 is the primary greenhouse gas emitted 

from marine shipping. 

Overall, aggregate greenhouse gas emissions in 2006 

from the combustion of international bunker fuels from 

both aviation and marine activities were 128.4 Tg CO2 Eq., 

or 12 percent above emissions in 1990 (see Table 3-51 and 

Table 3-52). Although emissions from international flights 

departing from the United States have increased significantly 

(56 percent), emissions from international shipping voyages 

45 Naphtha-type jet fuel was used in the past by the military in turbojet and 

turboprop aircraft engines.

departing the United States have decreased by 18 percent 

since 1990. The majority of these emissions were in the 

form of CO2; however, small amounts of CH4 and N2O were 

also emitted. 

Methodology

Emissions of CO2 were estimated by applying C content 

and fraction oxidized factors to fuel consumption activity 

data. This approach is analogous to that described under 

CO2 from Fossil Fuel Combustion. C content and fraction 

oxidized factors for jet fuel, distillate fuel oil, and residual 

fuel oil were taken directly from EIA and are presented in 

Annex 2.1, Annex 2.2, and Annex 3.7 of this Inventory. 

Density conversions were taken from Chevron (2000), ASTM 

(1989), and USAF (1998). Heat content for distillate fuel 

oil and residual fuel oil were taken from EIA (2007) and 

USAF (1998), and heat content for jet fuel was taken from 

EIA (2007). A complete description of the methodology 

and a listing of the various factors employed can be found 

in Annex 2.1. See Annex 3.7 for a specific discussion 

on the methodology used for estimating emissions from 

international bunker fuel use by the U.S. military.

Emission estimates for CH4 and N2O were calculated 

by multiplying emission factors by measures of fuel 

consumption by fuel type and mode. Emission factors used 

in the calculations of CH4 and N2O emissions were obtained 

from the Revised 1996 IPCC Guidelines (IPCC/UNEP/

OECD/IEA 1997). For aircraft emissions, the following 

values, in units of grams of pollutant per kilogram of fuel 

consumed (g/kg), were employed: 0.09 for CH4 and 0.1 

for N2O For marine vessels consuming either distillate 

diesel or residual fuel oil the following values (g/MJ), were 

employed: 0.32 for CH4 and 0.08 for N2O. Activity data 

for aviation included solely jet fuel consumption statistics, 

while the marine mode included both distillate diesel and 

residual fuel oil.

Activity data on aircraft fuel consumption were collected 

from three government agencies. Jet fuel consumed by U.S. 

flag air carriers for international flight segments was supplied 

by the Bureau of Transportation Statistics (DOT 1991 through 

2006). It was assumed that 50 percent of the fuel used by U.S. 

flagged carriers for international flights—both departing and 

arriving in the United States—was purchased domestically 

for flights departing from the United States. In other words, 
Energy 3-57

only one-half of the total annual fuel consumption estimate 

was used in the calculations. Data on jet fuel expenditures 

by foreign flagged carriers departing U.S. airports was taken 

from unpublished data collected by the Bureau of Economic 

Analysis (BEA) under the U.S. Department of Commerce 

(BEA 1991 through 2006). Approximate average fuel prices 

paid by air carriers for aircraft on international flights was 

taken from DOT (1991 through 2006) and used to convert 

the BEA expenditure data to gallons of fuel consumed. Data 

on U.S. Department of Defense (DoD) aviation bunker fuels 

and total jet fuel consumed by the U.S. military was supplied 

by the Office of the Under Secretary of Defense (Installations 

and Environment), DoD. Estimates of the percentage of each 

Service’s total operations that were international operations 

were developed by DoD. Military aviation bunkers included 

international operations, operations conducted from 

naval vessels at sea, and operations conducted from U.S. 

installations principally over international water in direct 

support of military operations at sea. Military aviation 

bunker fuel emissions were estimated using military fuel 

and operations data synthesized from unpublished data by 

the Defense Energy Support Center, under DoD’s Defense 

Logistics Agency (DESC 2007). Together, the data allow the 

quantity of fuel used in military international operations to 

be estimated. Densities for each jet fuel type were obtained 

from a report from the U.S. Air Force (USAF 1998). Final jet 

fuel consumption estimates are presented in Table 3-53. See 

Annex 3.7 for additional discussion of military data.

Activity data on distillate diesel and residual fuel oil 

consumption by cargo or passenger carrying marine vessels 

departing from U.S. ports were taken from unpublished 

data collected by the Foreign Trade Division of the U.S. 

Department of Commerce’s Bureau of the Census (DOC 1991 

through 2007) for 1990 through 2002, and the Department of 

Homeland Security’s Bunker Report for 2003 through 2006 

(DHS 2008). Activity data on distillate diesel consumption 

Table 3-52: CO2, CH4 and N2O Emissions from International Bunker Fuels (Gg)

Gas/Mode 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 113,683 100,627 101,125 97,563 89,101 103,583 118,975 122,580 127,097

Aviation 45,731 50,202 59,853 58,696 61,120 58,806 64,891 67,517 71,141

Marine 67,952 50,425 41,272 38,866 27,981 44,777 54,084 55,063 55,956

CH4 8 6 6 5 4 6 7 7 7

Aviation 1 1 2 2 2 2 2 2 2

Marine 7 5 4 4 3 4 5 5 5

N2O 3 3 3 3 3 3 3 4 4

Aviation 1 2 2 2 2 2 2 2 2

Marine 2 1 1 1 1 1 1 1 1

Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.

Table 3-51: CO2, CH4, and N2O Emissions from International Bunker Fuels (Tg CO2 Eq.)

Gas/Mode 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 113.7 100.6 101.1 97.6 89.1 103.6 119.0 122.6 127.1 

Aviation 45.7 50.2 59.9 58.7 61.1 58.8 64.9 67.5 71.1 

Marine 68.0 50.4 41.3 38.9 28.0 44.8 54.1 55.1 56.0 

CH4 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 

Aviation + + + + + + + + + 

Marine 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

N2O 1.0 0.9 0.9 0.9 0.8 0.8 1.1 1.1 1.1 

Aviation 0.5 0.5 0.6 0.6 0.6 0.6 0.6 0.7 0.7 

Marine 0.5 0.4 0.3 0.3 0.2 0.3 0.4 0.4 0.4 

Total 114.8 101.6 102.2 98.6 90.0 104.6 120.2 123.8 128.4 

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
3-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

by military vessels departing from U.S. ports were provided 

by DESC (2007). The total amount of fuel provided to 

naval vessels was reduced by 13 percent to account for fuel 

used while the vessels were not underway (i.e., in port). 

Data on the percentage of steaming hours underway versus 

not-underway were provided by the U.S. Navy. These fuel 

consumption estimates are presented in Table 3-54.

Uncertainty

Emission estimates related to the consumption 

of international bunker fuels are subject to the same 

uncertainties as those from domestic aviation and marine 

mobile combustion emissions; however, additional 

uncertainties result from the difficulty in collecting accurate 

fuel consumption activity data for international transport 

activities separate from domestic transport activities.46

For example, smaller aircraft on shorter routes often carry 

sufficient fuel to complete several flight segments without 

refueling in order to minimize time spent at the airport gate or 

take advantage of lower fuel prices at particular airports. This 

practice, called tankering, when done on international flights, 

complicates the use of fuel sales data for estimating bunker 

fuel emissions. Tankering is less common with the type of 

large, long-range aircraft that make many international flights 

from the United States, however. Similar practices occur in 

the marine shipping industry where fuel costs represent a 

46 See uncertainty discussions under Carbon Dioxide Emissions from Fossil 

Fuel Combustion.

significant portion of overall operating costs and fuel prices 

vary from port to port, leading to some tankering from ports 

with low fuel costs.

Particularly for aviation, the DOT (1991 through 

2007) international flight segment fuel data used for U.S. 

flagged carriers does not include smaller air carriers and 

unfortunately defines flights departing to Canada and some 

flights to Mexico as domestic instead of international. As 

for the BEA (1991 through 2007) data on foreign flagged 

carriers, there is some uncertainty as to the average fuel price, 

and to the completeness of the data. It was also not possible 

to determine what portion of fuel purchased by foreign 

carriers at U.S. airports was actually used on domestic flight 

segments; this error, however, is believed to be small.47

Uncertainties exist with regard to the total fuel used by 

military aircraft and ships, and in the activity data on military 

operations and training that were used to estimate percentages 

of total fuel use reported as bunker fuel emissions. Total 

aircraft and ship fuel use estimates were developed from 

DoD records, which document fuel sold to the Navy and 

Air Force from the Defense Logistics Agency. These data 

may slightly over or under estimate actual total fuel use in 

aircraft and ships because each Service may have procured 

47Although 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.

Table 3-53: Aviation Jet Fuel Consumption for International Transport (Million Gallons)

Nationality 1990 1995 2000 2001 2002 2003 2004 2005 2006

U.S. Carriers 1,954 2,221 2,737 2,619 2,495 2,418 2,466 2,760 2,914

Foreign Carriers 2,051 2,544 3,162 3,113 3,537 3,377 3,953 3,975 4,272

U.S. Military 862 581 480 524 482 473 498 462 400

Total 4,867 5,347 6,380 6,255 6,515 6,268 6,917 7,198 7,586

Note: Totals may not sum due to independent rounding.

Table 3-54: Marine Fuel Consumption for International Transport (Million Gallons)

Fuel Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Residual Fuel Oil 4,781 3,495 2,967 2,846 1,937 3,152 3,695 3,881 4,004

Distillate Diesel Fuel & 

Other 617 573 290 204 158 290 505 444 446

U.S. Military Naval Fuels 522 334 329 318 348 459 530 471 414

Total 5,920 4,402 3,586 3,368 2,443 3,901 4,730 4,796 4,864

Note: Totals may not sum due to independent rounding.
Energy 3-59

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 fueltype, emissions factors, fuel densities, diesel fuel sulfur 

content, aircraft and vessel engine characteristics and fuel 

efficiencies, and the methodology used to back-calculate 

the data set to 1990 using the original set from 1995. The 

data were adjusted for trends in fuel use based on a closely 

correlating, but not matching, data set. All assumptions used 

to develop the estimate were based on process knowledge, 

Department and military Service data, and expert judgments. 

The magnitude of the potential errors related to the various 

uncertainties has not been calculated, but is believed to be 

small. The uncertainties associated with future military 

bunker fuel emission estimates could be reduced through 

additional data collection.

Although aggregate fuel consumption data have been 

used to estimate emissions from aviation, the recommended 

method for estimating emissions of gases other than CO2 in 

the Revised 1996 IPCC Guidelines is to use data by specific 

aircraft type (IPCC/UNEP/OECD/IEA 1997). The IPCC 

also recommends that cruise altitude emissions be estimated 

separately using fuel consumption data, while landing and 

take-off (LTO) cycle data be used to estimate near-ground 

level emissions of gases other than CO2.

48

There is also concern as to the reliability of the existing 

DOC (1991 through 2007) data on marine vessel fuel 

consumption reported at U.S. customs stations due to the 

significant degree of inter-annual variation.

QA/QC and Verification

A source-specific QA/QC plan for international bunker 

fuels was developed and implemented. This effort included 

a Tier 1 analysis, as well as portions of a Tier 2 analysis. The 

Tier 2 procedures that were implemented involved checks 

specifically focusing on the activity data and emission 

factor sources and methodology used for estimating CO2, 

CH4, and N2O from international bunker fuels in the United 

States. Emission totals for the different sectors and fuels 

were compared and trends were investigated. No corrective 

actions were necessary.

Recalculations Discussion 

Historical activity data for aviation was revised for both 

U.S. and foreign carriers. In addition, distillate and residual 

fuel oil consumption by cargo or passenger carrying marine 

vessels from 2003 through 2006 was revised using DHS 

(2008). These historical data changes resulted in changes 

to the emission estimates for 1990 through 2005, which 

averaged to an annual decrease in emissions relative to the 

previous Inventory from international bunker fuels of 4.3 Tg 

CO2 Eq. (4.7 percent) in CO2 emissions, an annual decrease 

of less than 0.1 Tg CO2 Eq. (8 percent) in CH4 emissions, 

and annual decrease of less than 0.1 Tg CO2 Eq. (4 percent) 

in N2O emissions.

48U.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.
3-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

3.12. Wood Biomass and Ethanol 

Consumption (IPCC Source Category 

1A)

The combustion of biomass fuels—such as wood, 

charcoal, and wood waste—and biomass-based fuels—

such as ethanol from corn and woody crops—generates 

CO2. However, in the long run the CO2 emitted from 

biomass consumption does not increase atmospheric CO2

concentrations, assuming that the biogenic C emitted is 

offset by the uptake of CO2 that results from the growth 

of new biomass. As a result, CO2 emissions from biomass 

combustion have been estimated separately from fossil fuelbased emissions and are not included in the U.S. totals. Net 

C fluxes from changes in biogenic C reservoirs in wooded 

or crop lands are accounted for in the Land Use, Land-Use 

Change, and Forestry chapter.

In 2006, total CO2 emissions from the burning of 

woody biomass in the industrial, residential, commercial, 

and electricity generation sectors were approximately 

204.4 Tg CO2 Eq. (204,435 Gg) (see Table 3-55 and 

Table 3-56). As the largest consumer of woody biomass, 

the industrial sector was responsible for 67 percent of the 

CO2 emissions from this source. The residential sector 

was the second largest emitter, constituting 20 percent of 

the total, while the commercial and electricity generation 

sectors accounted for the remainder.

Biomass-derived fuel consumption in the United States 

consisted primarily of ethanol use in the transportation 

sector. Ethanol is primarily produced from corn grown 

in the Midwest, and was used mostly in the Midwest and 

South. Pure ethanol can be combusted, or it can be mixed 

with gasoline as a supplement or octane-enhancing agent. 

The most common mixture is a 90 percent gasoline, 10 

percent ethanol blend known as gasohol. Ethanol and ethanol 

blends are often used to fuel public transport vehicles such 

as buses, or centrally fueled fleet vehicles. These fuels burn 

cleaner than gasoline (i.e., lower in NOx and hydrocarbon 

emissions), and have been employed in urban areas with poor 

air quality. However, because ethanol is a hydrocarbon fuel, 

its combustion emits CO2.

In 2006, the United States consumed an estimated 

459 trillion Btu of ethanol, and as a result, produced 

approximately 30.3 Tg CO2 Eq. (30,291 Gg) (see Table 3-57 

and Table 3-58) of CO2 emissions. Ethanol production and 

consumption has grown steadily every year since 1990, with 

the exception of 1996 due to short corn supplies and high 

prices in that year. 

Table 3-55: CO2 Emissions from Wood Consumption by End-Use Sector (Tg CO2 Eq.)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Industrial 135.3 155.1 153.6 135.4 131.1 128.0 138.5 136.3 137.9

Residential 59.8 53.6 43.3 38.2 39.2 41.2 42.3 42.3 40.2

Commercial 6.8 7.5 7.4 6.9 7.1 7.4 7.3 7.2 6.7

Electricity Generation 13.3 12.9 13.9 13.0 15.5 17.3 17.0 19.1 19.6

Total 215.2 229.1 218.1 193.5 192.8 193.8 205.1 204.8 204.4

Note: Totals may not sum due to independent rounding.

Table 3-56: CO2 Emissions from Wood Consumption by End-Use Sector (Gg)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Industrial 135,348 155,075 153,559 135,415 131,079 127,970 138,522 136,269 137,929

Residential 59,808 53,621 43,309 38,153 39,184 41,247 42,278 42,278 40,215

Commercial 6,779 7,463 7,370 6,887 7,080 7,366 7,252 7,191 6,685

Electricity Generation 13,252 12,932 13,851 13,034 15,487 17,250 17,034 19,704 19,606

Total 215,186 229,091 218,088 193,489 192,830 193,833 205,086 204,812 204,435

Note: Totals may not sum due to independent rounding.
Energy 3-61

Methodology

Woody biomass emissions were estimated by applying 

two EIA gross heat contents (Lindstrom 2006) to U.S. 

consumption data (EIA 2007) (see Table 3-59), provided in 

energy units for the industrial, residential, commercial, and 

electric generation sectors. One heat content (16.953114 

MMBtu/MT wood and wood waste) was applied to the 

industrial sector’s consumption, while the other heat content 

(15.432359 MMBtu/MT wood and wood waste) was applied 

to the consumption data for the other sectors. An EIA 

emission factor of 0.434 MT C/MT wood (Lindstrom 2006) 

was then applied to the resulting quantities of woody biomass 

to obtain CO2 emission estimates. It was assumed that the 

woody biomass contains black liquor and other wood wastes, 

has a moisture content of 12 percent, and is converted into 

CO2 with 100 percent efficiency. The emissions from ethanol 

consumption were calculated by applying an EIA emission 

factor of 17.99 Tg C/QBtu (Lindstrom 2006) to U.S. ethanol 

consumption estimates that were provided in energy units 

(EIA 2007) (see Table 3-60).

Uncertainty

It is assumed that the combustion efficiency for 

woody biomass is 100 percent, which is believed to be an 

Table 3-57: CO2 Emissions from Ethanol Consumption (Tg CO2 Eq.)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Transportation 4.1 7.6 9.1 9.5 11.3 15.4 19.3 22.0 29.6

Industrial 0.1 0.1 0.1 0.2 0.2 0.3 0.4 0.5 0.6

Commercial + + + + + 0.1 0.1 0.1 0.1

Total 4.2 7.7 9.2 9.7 11.5 15.7 19.7 22.6 30.3

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding. 

Table 3-58: CO2 Emissions from Ethanol Consumption (Gg)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Transportation 4,066 7,570 9,078 9,479 11,280 15,353 19,267 22,014 29,566

Industrial 55 104 85 172 209 296 418 478 641

Commercial 33 9 25 22 31 55 55 62 84

Total 4,155 7,683 9,188 9,673 11,520 15,704 19,740 22,554 30,291

Note: Totals may not sum due to independent rounding.

Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Industrial 1,442 1,652 1,636 1,443 1,396 1,363 1,476 1,452 1,469

Residential 580 520 420 370 380 400 410 410 390

Commercial 66 72 71 67 69 71 70 70 65

Electricity Generation 129 125 134 126 150 167 165 185 190

Total 2,216 2,370 2,262 2,006 1,995 2,002 2,121 2,116 2,114

Table 3-60: Ethanol Consumption (Trillion Btu)

End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006

Transportation 61.7 114.8 137.7 143.7 171.0 232.8 292.1 333.8 448.3

Industrial 0.8 1.6 1.3 2.6 3.2 4.5 6.3 7.2 9.7

Commercial 0.5 0.1 0.4 0.3 0.5 0.8 0.8 0.9 1.3

Total 63.0 116.5 139.3 146.7 174.7 238.1 299.3 342.0 459.3
3-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

overestimate of the efficiency of wood combustion processes 

in the United States. Decreasing the combustion efficiency 

would increase emission estimates. Additionally, the heat 

content applied to the consumption of woody biomass in 

the residential, commercial, and electric power sectors is 

unlikely to be a completely accurate representation of the 

heat content for all the different types of woody biomass 

consumed within these sectors. Emission estimates from 

ethanol production are more certain than estimates from 

woody biomass consumption due to better activity data 

collection methods and uniform combustion techniques.

Recalculations Discussion 

Residential wood consumption values were revised in 

1997, 1999, and 2000 based on updated information from 

EIA’s Annual Energy Review (EIA 2007). EIA (2007) also 

reported minor changes in wood consumption for all sectors 

in 2005. This adjustment of historical data for wood biomass 

consumption resulted in an average annual increase in 

emissions from wood biomass consumption of 1.1 Tg CO2

Eq. (0.6 percent) from 1990 through 2005. Industrial and 

commercial sector ethanol consumption is now estimated in 

EIA (2007), which slightly decreased estimates for ethanol 

consumed in the transportation sector in all years. As a result 

of these adjustments, average annual emissions from ethanol 

consumption in the transportation sector decreased by 0.2 

Tg CO2 Eq. (1.8 percent).
Industrial Processes 4-1

4. Industrial Processes

G

reenhouse gas emissions are produced as the byproducts of various non-energy-related industrial activities. 

That is, these emissions are produced from an industrial process itself and are not directly a result of energy 

consumed during the process. For example, raw materials can be chemically transformed from one state to 

another. This transformation can result in the release of greenhouse gases such as carbon dioxide (CO2), methane (CH4), 

or nitrous oxide (N2O). The processes addressed in this chapter include iron and steel production, cement production, lime 

production, ammonia production and urea consumption, limestone and dolomite use (e.g., flux stone, flue gas desulfurization, 

and glass manufacturing), soda ash production and consumption, aluminum production, titanium dioxide production, CO2

consumption, ferroalloy production, phosphoric acid production, zinc production, lead production, petrochemical production, 

silicon carbide production and consumption, nitric acid production, and adipic acid production (see Figure 4-1).

In addition to the three greenhouse gases listed above, there are also industrial sources of man-made fluorinated compounds 

called hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), 

and sulfur hexafluoride (SF6). The present contribution of 

these gases to the radiative forcing effect of all anthropogenic 

greenhouse gases is small; however, because of their 

extremely long lifetimes, many of them will continue 

to accumulate in the atmosphere as long as emissions 

continue. In addition, many of these gases have high global 

warming potentials; SF6 is the most potent greenhouse gas 

the Intergovernmental Panel on Climate Change (IPCC) 

has evaluated. Usage of HFCs for the substitution of ozone 

depleting substances is growing rapidly, as they are the 

primary substitutes for ozone depleting substances (ODSs), 

which are being phased-out under the Montreal Protocol 

on Substances that Deplete the Ozone Layer. In addition 

to their use as ODS substitutes, HFCs, PFCs, SF6, and 

other fluorinated compounds are employed and emitted by 

a number of other industrial sources in the United States. 

These industries include aluminum production, HCFC-22 

production, semiconductor manufacture, electric power 

transmission and distribution, and magnesium metal 

production and processing.

In 2006, industrial processes generated emissions 

of 320.9 teragrams of CO2 equivalents (Tg CO2 Eq.), or 

5 percent of total U.S. greenhouse gas emissions. CO2

0 25 50 75 100 125

Industrial Processes

as a Portion of

all Emissions

4.5%

Tg CO2 Eq.

Silicon Carbide Production and Consumption <0.5

Lead Production <0.5

Zinc Production

Phosphoric Acid Production

Ferroalloy Production

Carbon Dioxide Consumption

Titanium Dioxide Production

Magnesium Production and Processing

Petrochemical Production

Soda Ash Production and Consumption

Semiconductor Manufacture

Adipic Acid Production

Aluminum Production

Limestone and Dolomite Use

Ammonia Production and Urea Consumption

Electrical Transmission and Distribution

HCFC-22 Production

Nitric Acid Production

Lime Production

Cement Production

Iron and Steel Production

Substitution of Ozone Depleting Substances

2006 Industrial Processes Chapter 

Greenhouse Gas Emission Sources

Figure 4-1
4-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

emissions from all industrial processes were 149.5 Tg CO2

Eq. (149,465 Gg) in 2006, or 2 percent of total U.S. CO2

emissions. CH4 emissions from industrial processes resulted 

in emissions of approximately 2.0 Tg CO2 Eq. (94 Gg) in 

2006, which was less than 1 percent of U.S. CH4 emissions. 

N2O emissions from adipic acid and nitric acid production 

were 21.6 Tg CO2 Eq. (70 Gg) in 2006, or 4 percent of total 

U.S. N2O emissions. In 2006, combined emissions of HFCs, 

PFCs and SF6 totaled 147.9 Tg CO2 Eq. Overall, emissions 

from industrial processes increased by 7.0 percent from 1990 

to 2006 despite decreases in emissions from several industrial 

processes, such as iron and steel, aluminum production, 

HCFC-22 production, and electrical transmission and 

distribution. The increase in overall emissions was driven by 

a rise in the emissions originating from cement production 

and, primarily, the emissions from the use of substitutes for 

ozone depleting substances.

Table 4-1 summarizes emissions for the Industrial 

Processes chapter in units of Tg CO2 Eq., while unweighted 

native gas emissions in Gg are provided in Table 4-2. The 

source descriptions that follow in the chapter are presented 

in the order as reported to the UNFCCC in the common 

reporting format tables, corresponding generally to: mineral 

products, chemical production, metal production, and 

emissions from the uses of HFCs, PFCs, and SF6.

Tier 1 quality assurance and quality control procedures 

have been performed for all industrial process sources. For 

industrial process sources of CO2 and CH4 emissions, a 

detailed plan was developed and implemented. This plan 

was based on U.S. strategy, but was tailored to include 

specific procedures recommended for these sources. Two 

types of checks were performed using this plan (1) general, 

or Tier 1, procedures that focus on annual procedures and 

checks to be used when gathering, maintaining, handling, 

documenting, checking and archiving the data, supporting 

documents, and files and (2) source-category specific, or Tier 

2, procedures that focus on procedures and checks of the 

emission factors, activity data, and methodologies used for 

estimating emissions from the relevant Industrial Processes 

sources. Examples of these procedures include, among 

others, checks to ensure that activity data and emission 

estimates are consistent with historical trends; that, where 

possible, consistent and reputable data sources are used 

across sources; that interpolation or extrapolation techniques 

are consistent across sources; and that common datasets and 

factors are used where applicable.

The general method employed to estimate emissions 

for industrial processes, as recommended by the IPCC, 

involves multiplying production data (or activity data) for 

each process by an emission factor per unit of production. 

The uncertainty in the emission estimates is therefore 

generally a function of a combination of the uncertainties 

surrounding the production and emission factor variables. 

Uncertainty of activity data and the associated probability 

density functions for industrial processes CO2 sources were 

estimated based on expert assessment of available qualitative 

and quantitative information. Uncertainty estimates and 

probability density functions for the emission factors used 

to calculate emissions from this source were devised based 

on IPCC recommendations.

Activity data is obtained through a survey of manufacturers 

conducted by various organizations (specified within each 

source); the uncertainty of the activity data is a function of the 

reliability of plant-level production data and is influenced by 

the completeness of the survey response. The emission factors 

used were either derived using calculations that assume precise 

and efficient chemical reactions, or were based upon empirical 

data in published references. As a result, uncertainties in 

the emission coefficients can be attributed to, among other 

things, inefficiencies in the chemical reactions associated 

with each production process or to the use of empiricallyderived emission factors that are biased; therefore, they may 

not represent U.S. national averages. Additional assumptions 

are described within each source.

The uncertainty analysis performed to quantify 

uncertainties associated with the 2006 inventory estimates 

from industrial processes continues a multi-year process 

for developing credible quantitative uncertainty estimates 

for these source categories using the IPCC Tier 2 approach. 

As the process continues, the type and the characteristics 

of the actual probability density functions underlying 

the input variables are identified and better characterized 

(resulting in development of more reliable inputs for the 

model, including accurate characterization of correlation 

between variables), based primarily on expert judgment. 
Industrial Processes 4-3

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.

Table 4-1: Emissions from Industrial Processes (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 175.0 171.6 166.5 151.9 151.0 147.8 151.8 145.9 149.5

Iron and Steel Production 86.2 74.7 66.6 59.2 55.9 54.7 52.8 46.6 49.1

Cement Production 33.3 36.8 41.2 41.4 42.9 43.1 45.6 45.9 45.7

Lime Production 12.0 14.0 14.9 14.3 13.7 14.5 15.2 15.1 15.8

Ammonia Production & Urea Consumption 16.9 17.8 16.4 13.3 14.2 12.5 13.2 12.8 12.4

Limestone and Dolomite Use 5.5 7.4 6.0 5.7 5.9 4.8 6.7 7.4 8.6

Soda Ash Production and Consumption 4.1 4.3 4.2 4.1 4.1 4.1 4.2 4.2 4.2

Aluminum Production 6.8 5.7 6.1 4.4 4.5 4.5 4.2 4.2 3.9

Petrochemical Production 2.2 2.8 3.0 2.8 2.9 2.8 2.9 2.8 2.6

Titanium Dioxide Production 1.2 1.5 1.8 1.7 1.8 1.8 2.1 1.8 1.9

Carbon Dioxide Consumption 1.4 1.4 1.4 0.8 1.0 1.3 1.2 1.3 1.6

Ferroalloy Production 2.2 2.0 1.9 1.5 1.3 1.3 1.4 1.4 1.5

Phosphoric Acid Production 1.5 1.5 1.4 1.3 1.3 1.4 1.4 1.4 1.2

Zinc Production 0.9 1.0 1.1 1.0 0.9 0.5 0.5 0.5 0.5

Lead Production 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3

Silicon Carbide Production and Consumption 0.4 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2

CH4 2.2 2.4 2.5 2.2 2.1 2.1 2.2 2.0 2.0

Petrochemical Production 0.9 1.1 1.2 1.1 1.1 1.1 1.2 1.1 1.0

Iron and Steel Production 1.3 1.3 1.2 1.1 1.0 1.0 1.0 1.0 0.9

Ferroalloy Production + + + + + + + + + 

Silicon Carbide Production and Consumption + + + + + + + + + 

N2O 32.3 36.2 24.8 20.2 22.4 21.7 21.2 21.7 21.6

Nitric Acid Production 17.0 18.9 18.6 15.1 16.4 15.4 15.2 15.8 15.6

Adipic Acid Production 15.3 17.3 6.2 5.1 6.1 6.3 5.9 5.9 5.9

HFCs 36.9 61.8 100.1 97.9 106.3 104.4 116.6 121.4 124.5

Substitution of Ozone Depleting Substancesa 0.3 28.5 71.2 78.0 85.0 92.0 99.1 105.4 110.4

HCFC-22 Production 36.4 33.0 28.6 19.7 21.1 12.3 17.2 15.8 13.8

Semiconductor Manufacture 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.3

PFCs 20.8 15.6 13.5 7.0 8.7 7.1 6.1 6.2 6.1

Semiconductor Manufacture 2.2 3.8 4.9 3.5 3.5 3.3 3.3 3.2 3.6

Aluminum Production 18.5 11.8 8.6 3.5 5.2 3.8 2.8 3.0 2.5

SF6 32.7 28.0 19.1 18.7 18.0 18.1 18.0 18.2 17.3

Electrical Transmission and Distribution 26.7 21.5 15.1 15.0 14.4 13.8 13.9 14.0 13.2

Magnesium Production and Processing 5.4 5.6 3.0 2.9 2.9 3.4 3.2 3.3 3.2

Semiconductor Manufacture 0.5 0.9 1.1 0.7 0.7 0.8 0.8 1.0 1.0

Total 299.9 315.7 326.5 297.9 308.6 301.2 315.9 315.5 320.9

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.

a

 Small amounts of PFC emissions also result from this source.
4-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

4.1. Cement Production 

(IPCC Source Category 2A1)

Cement production is an energy- and raw-materialintensive process that results in the generation of CO2 from 

both the energy consumed in making the cement and the 

chemical process itself.1 Cement is produced in 37 states 

and Puerto Rico. CO2 emitted from the chemical process of 

cement production is the second largest source of industrial 

CO2 emissions in the United States.

1 The CO2 emissions related to the consumption of energy for cement 

production are accounted for under CO2 from Fossil Fuel Combustion in 

the Energy chapter.

Table 4-2: Emissions from Industrial Processes (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 175,018 171,600 166,452 151,944 150,960 147,752 151,841 145,926 149,465

Iron and Steel Production 86,220 74,729 66,609 59,249 55,938 54,744 52,771 46,627 49,119

Cement Production 33,278 36,847 41,190 41,357 42,898 43,082 45,603 45,910 45,739

Lime Production 12,004 14,019 14,872 14,261 13,652 14,458 15,154 15,131 15,825

Ammonia Production & Urea Consumption 16,889 17,796 16,402 13,305 14,194 12,488 13,241 12,817 12,376

Limestone and Dolomite Use 5,533 7,359 5,960 5,733 5,885 4,753 6,702 7,397 8,615

Soda Ash Production and Consumption 4,141 4,304 4,181 4,147 4,139 4,111 4,205 4,228 4,162

Aluminum Production 6,831 5,659 6,086 4,381 4,490 4,503 4,231 4,207 3,923

Petrochemical Production 2,221 2,750 3,004 2,787 2,857 2,777 2,895 2,804 2,573

Titanium Dioxide Production 1,195 1,526 1,752 1,697 1,824 1,839 2,064 1,755 1,876

Carbon Dioxide Consumption 1,416 1,422 1,421 829 989 1,311 1,198 1,321 1,579

Ferroalloy Production 2,152 2,036 1,893 1,459 1,349 1,305 1,419 1,392 1,505

Phosphoric Acid Production 1,529 1,513 1,382 1,264 1,338 1,382 1,395 1,386 1,167

Zinc Production 949 1,013 1,140 986 937 507 477 465 529

Lead Production 285 298 311 291 286 289 263 266 270

Silicon Carbide Production and Consumption 375 329 248 199 183 202 224 219 207

CH4 106 116 117 103 101 101 106 97 94

Petrochemical Production 41 52 58 51 52 51 55 51 48

Iron and Steel Production 63 62 58 51 48 49 50 45 45

Ferroalloy Production 1 1 1 + + + + + + 

Silicon Carbide Production and Consumption 1 1 1 + + + + + + 

N2O 104 117 80 65 72 70 68 70 70

Nitric Acid Production 55 61 60 49 53 50 49 51 50

Adipic Acid Production 49 56 20 16 20 20 19 19 19

HFCs M M M M M M M M M

Substitution of Ozone Depleting Substancesa M M M M M M M M M

HCFC-22 Production 3 3 2 2 2 1 1 1 1

Semiconductor Manufacture + + + + + + + + + 

PFCs M M M M M M M M M

Semiconductor Manufacture M M M M M M M M M

Aluminum Production M M M M M M M M M

SF6 1 1 1 1 1 1 1 1 1

Electrical Transmission and Distribution 1 1 1 1 1 1 1 1 1

Magnesium Production and Processing + + + + + + + + + 

Semiconductor Manufacture + + + + + + + + + 

+ Does not exceed 0.5 Gg

M (Mixture of gases)

Note: Totals may not sum due to independent rounding.

a

 Small amounts of PFC emissions also result from this source.
Industrial Processes 4-5

During the cement production process, calcium carbonate 

(CaCO3) is heated in a cement kiln at a temperature of about 

1,450°C (2,400°F) to form lime (i.e., calcium oxide or CaO) 

and CO2 in a process known as calcination or calcining. A 

very small amount of carbonates other than CaCO3 and noncarbonates are also present in the raw material; however, for 

calculation purposes all of the raw material is assumed to be 

CaCO3. Next, the lime is combined with silica-containing 

materials to produce clinker (an intermediate product), with 

the earlier byproduct CO2 being released to the atmosphere. 

The clinker is then allowed to cool, mixed with a small 

amount of gypsum, and potentially other materials (e.g., 

slag) and used to make portland cement.2

In 2006, U.S. clinker production—including Puerto 

Rico—totaled 88,453 thousand metric tons (van Oss 

2007). The resulting emissions of CO2 from 2006 cement 

production were estimated to be 45.7 Tg CO2 Eq. (45,739 

Gg) (see Table 4-3).

After falling in 1991 by two percent from 1990 levels, 

cement production emissions grew every year through 2005, 

and then decreased slightly from 2005 to 2006. Overall, from 

1990 to 2006, emissions increased by 37 percent. Cement 

continues to be a critical component of the construction 

industry; therefore, the availability of public construction 

funding, as well as overall economic growth, have had 

considerable influence on cement production.

2Approximately six percent of total clinker production is used to produce 

masonry cement, which is produced using plasticizers (e.g., ground 

limestone, lime) and portland cement. CO2 emissions that result from the 

production of lime used to create masonry cement are included in the Lime 

Production source category (van Oss 2008).

Methodology

CO2 emissions from cement production are created by 

the chemical reaction of carbon-containing minerals (i.e., 

calcining limestone) in the cement kiln. While in the kiln, 

limestone is broken down into CO2 and lime with the CO2

released to the atmosphere. The quantity of CO2 emitted 

during cement production is directly proportional to the 

lime content of the clinker. During calcination, each mole 

of CaCO3 (i.e., limestone) heated in the clinker kiln forms 

one mole of lime (CaO) and one mole of CO2:

Limestone plus heat forms one mole of lime and one mole of carbon dioxide.

CO2 emissions were estimated by applying an emission 

factor, in tons of CO2 released per ton of clinker produced, 

to the total amount of clinker produced. The emission factor 

used in this analysis is the product of the average lime fraction 

for clinker of 65 percent (van Oss 2008) and a constant 

reflecting the mass of CO2 released per unit of lime. This 

calculation yields an emission factor of 0.51 tons of CO2 per 

ton of clinker produced, which was determined as follows:

The emission factor for a clinker equals 0.65 mole of lime multiplied by begin parentheses 44.01 grams per mole of carbon dioxide divided by 56.08 

grams per mole of lime end parentheses equals 0.51 tons carbon dioxide per ton clinker.

During clinker production, some of the clinker precursor 

materials remain in the kiln as non-calcinated, partially 

calcinated, or fully calcinated cement kiln dust (CKD). The 

emissions attributable to the calcinated portion of the CKD 

are not accounted for by the clinker emission factor. The IPCC 

recommends that these additional CKD CO2 emissions should 

be estimated as two percent of the CO2 emissions calculated 

from clinker production. Total cement production emissions 

were calculated by adding the emissions from clinker 

production to the emissions assigned to CKD (IPCC 2006).3

The 1990 through 2006 activity data for clinker 

production (see Table 4-4) were obtained through a personal 

communication with Hendrik van Oss (van Oss 2007) of the 

USGS and through the USGS Mineral Yearbook: Cement

(USGS 1993 through 2006). The data were compiled by 

3The 2 percent CO2 addition associated with CKD is included in the emission 

estimate for completeness. The cement emission estimate also includes an 

assumption that all raw material is limestone (CaCO3) when in fact a small 

percentage is likely composed of non-carbonate materials. Together these 

assumptions may result in a small emission overestimate (van Oss 2008).

CaCO3 + heat → CaO + CO2

Table 4-3: CO2 Emissions from Cement Production 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 33.3 33,278

1995 36.8 36,847

2000 41.2 41,190

2001 41.4 41,357

2002 42.9 42,898

2003 43.1 43,082

2004 45.6 45,603

2005 45.9 45,910

2006 45.7 45,739

EFClinker = 0.65 CaO × [ 44.01 g/mole CO2 ] 

= 0.51 tons CO2/ton clinker

56.08 g/mole CaO
4-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

USGS through questionnaires sent to domestic clinker and 

cement production 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 cement 

kiln. Uncertainty is also associated with the assumption 

that all calcium-containing raw material is CaCO3 when a 

small percentage likely consists of other carbonate and noncarbonate raw materials. The lime content of clinker varies 

from 60 to 67 percent (van Oss 2008). CKD loss can range 

from 1.5 to 8 percent depending upon plant specifications. 

Additionally, some amount of CO2 is reabsorbed when the 

cement is used for construction. As cement reacts with water, 

alkaline substances such as calcium hydroxide are formed. 

During this curing process, these compounds may react with 

CO2 in the atmosphere to create calcium carbonate. This 

reaction only occurs in roughly the outer 0.2 inches of surface 

area. Because the amount of CO2 reabsorbed is thought to 

be minimal, it was not estimated.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-5. Cement production CO2

emissions were estimated to be between 39.8 and 52.0 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates 

a range of approximately 13 percent below and 14 percent 

above the emission estimate of 45.7 Tg CO2 Eq.

4.2. Lime Production 

(IPCC Source Category 2A2)

Lime is an important manufactured product with many 

industrial, chemical, and environmental applications. Its 

major uses are in steel making, flue gas desulfurization (FGD) 

systems at coal-fired electric power plants, construction, 

and water purification. For U.S. operations, the term 

“lime” actually refers to a variety of chemical compounds. 

These include calcium oxide (CaO), or high-calcium 

quicklime; calcium hydroxide (Ca(OH)2), or hydrated lime; 

dolomitic quicklime ([CaO•MgO]); and dolomitic hydrate 

([Ca(OH)2•MgO] or [Ca(OH)2•Mg(OH)2]).

Lime production involves three main processes: stone 

preparation, calcination, and hydration. CO2 is generated 

during the calcination stage, when limestone—mostly 

calcium carbonate (CaCO3)—is roasted at high temperatures 

in a kiln to produce CaO and CO2. The CO2 is given off as 

a gas and is normally emitted to the atmosphere. In certain 

applications, lime reabsorbs CO2 during use.

Lime production in the United States—including Puerto 

Rico—was reported to be 20,929 thousand metric tons in 

2006 (USGS 2007). This resulted in estimated CO2 emissions 

of 15.8 Tg CO2 Eq. (or 15,825 Gg) (see Table 4-6).

The contemporary lime market is distributed across five 

end-use categories as follows: metallurgical uses, 36 percent; 

environmental uses, 29 percent; chemical and industrial uses, 

21 percent; construction uses, 13 percent; and refractory 

dolomite, 1 percent. In the construction sector, lime is used 

to improve durability in plaster, stucco, and mortars, as well 

as to stabilize soils. In 2006, the amount of lime used for 

Table 4-4: Clinker Production (Gg)

Year Clinker

1990 64,355

1995 71,257

2000 79,656

2001 79,979

2002 82,959

2003 83,315

2004 88,190

2005 88,783

2006 88,453

Table 4-5: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Cement Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Cement Production CO2 45.7 39.8 52.0 -13% +14%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-7

construction decreased slightly from 2005 levels, most likely 

as a result of increased prices for lime and the downturn in 

new home construction (USGS 2007).

Lime production in 2006 slightly increased over 2005, 

the fourth annual increase in production after four years of 

decline. Overall, from 1990 to 2006, lime production has 

increased by 32 percent. Annual consumption for industrial 

and chemical, and environmental lime consumption increased 

by 8 percent and 7 percent, respectively (USGS 2007). The 

increase in environmental production for environmental 

uses is attributed in part to growth in demand for flue gas 

desulfurization technologies, particularly at incineration 

plants, and wastewater treatment (USGS 2007).

Methodology

During the calcination stage of lime production, CO2

is given off as a gas and normally exits the system with 

the stack gas. To calculate emissions, the amounts of highcalcium and dolomitic lime produced were multiplied by 

their respective emission factors. The emission factor is the 

product of a constant reflecting the mass of CO2 released per 

unit of lime and the average calcium plus magnesium oxide 

(CaO + MgO) content for lime (95 percent for both types 

of lime) (IPCC 2006). The emission factors were calculated 

as follows:

For high-calcium lime: 

Begin parentheses 44.01 grams per mole carbon dioxide divided by 56.08 grams per mole of calcium 

oxide end parentheses multiplied by 0.95 mole of calcium oxide per mole of lime equals 0.75 grams 

carbon dioxide per gram of lime.

For dolomitic lime:

Begin parentheses 88.02 grams per mole carbon dioxide divided by 96.39 grams per mole calcium 

oxide end parentheses multiplied by 0.95 mole of calcium oxide per mole of lime equals 0.87 grams 

carbon dioxide per gram lime.

Production was adjusted to remove the mass of 

chemically combined water found in hydrated lime, 

determined according to the molecular weight ratios of H2O 

to (Ca(OH)2 and [Ca(OH)2•Mg(OH)2]) (IPCC 2000). These 

factors set the chemically combined water content to 24.3 

percent for high-calcium hydrated lime, and 27.3 percent for 

dolomitic hydrated lime.

Lime emission estimates were multiplied by a factor of 

1.02 to account for lime kiln dust (LKD), which is produced 

as a byproduct during the production of lime (IPCC 2006).

Lime production data (high-calcium- and dolomiticquicklime, high-calcium- and dolomitic-hydrated, and deadburned dolomite) for 1990 through 2006 (see Table 4-7) were 

obtained from USGS (1992 through 2007). Natural hydraulic 

lime, which is produced from CaO and hydraulic calcium 

silicates, is not produced in the United States (USGS 2006). 

[(44.01 g/mole CO2) ÷ (56.08 g/mole CaO)] ×

(0.95 CaO/lime) = 0.75 g CO2/g lime

[(88.02 g/mole CO2) ÷ (96.39 g/mole CaO)] ×

(0.95 CaO/lime) = 0.87 g CO2/g lime

Table 4-6: CO2 Emissions from Lime Production 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 12.0 12,004

1995 14.0 14,019

2000 14.9 14,872

2001 14.3 14,261

2002 13.7 13,652

2003 14.5 14,458

2004 15.2 15,154

2005 15.1 15,131

2006 15.8 15,825

Table 4-7: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, 

and Dead-Burned-Dolomite Lime Production (Gg)

Year

High-Calcium 

Quicklime

Dolomitic 

Quicklime

High-Calcium 

Hydrated

Dolomitic 

Hydrated

Dead-Burned 

Dolomite

1990 11,166 2,234 1,781 319 342

1995 13,165 2,635 2,027 363 308

2000 14,300 3,000 1,550 421 200

2001 13,600 2,580 2,030 447 200

2002 13,400 2,420 1,500 431 200

2003 13,900 2,460 2,140 464 200

2004 14,200 3,020 2,140 421 200

2005 14,100 2,990 2,220 474 200

2006 15,000 2,950 2,370 409 200
4-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Total lime production was adjusted to account for the water 

content of hydrated lime by converting hydrate to oxide 

equivalent, based on recommendations from the IPCC Good 

Practice Guidance and is presented in Table 4-8 (USGS 1992 

through 2007, IPCC 2000). The CaO and CaO•MgO contents 

of lime were obtained from the IPCC (IPCC 2006). Since data 

for the individual lime types (high calcium and dolomitic) 

was not provided prior to 1997, total lime production for 

1990 through 1996 was calculated according to the three 

year distribution from 1997 to 1999.

Uncertainty

The uncertainties contained in these estimates can be 

attributed to slight differences in the chemical composition 

of these products. Although the methodology accounts for 

various formulations of lime, it does not account for the 

trace impurities found in lime, such as iron oxide, alumina, 

and silica. Due to differences in the limestone used as a raw 

material, a rigid specification of lime material is impossible. 

As a result, few plants manufacture lime with exactly the 

same properties.

In addition, a portion of the CO2 emitted during lime 

production will actually be reabsorbed when the lime is 

consumed. As noted above, lime has many different chemical, 

industrial, environmental, and construction applications. In 

many processes, CO2 reacts with the lime to create calcium 

carbonate (e.g., water softening). CO2 reabsorption rates 

vary, however, depending on the application. For example, 

100 percent of the lime used to produce precipitated calcium 

carbonate reacts with CO2; whereas most of the lime used 

in steel making reacts with impurities such as silica, sulfur, 

and aluminum compounds. A detailed accounting of lime use 

in the United States and further research into the associated 

processes are required to quantify the amount of CO2 that 

is reabsorbed.4

In some cases, lime is generated from calcium carbonate 

byproducts at pulp mills and water treatment plants.5 The 

lime generated by these processes is not included in the 

USGS data for commercial lime consumption. In the pulping 

industry, mostly using the Kraft (sulfate) pulping process, 

lime is consumed in order to causticize a process liquor 

(green liquor) composed of sodium carbonate and sodium 

sulfide. The green liquor results from the dilution of the smelt 

created by combustion of the black liquor where biogenic 

C is present from the wood. Kraft mills recover the calcium 

carbonate “mud” after the causticizing operation and calcine 

it back into lime—thereby generating CO2—for reuse in the 

pulping process. Although this re-generation of lime could 

be considered a lime production process, the CO2 emitted 

during this process is mostly biogenic in origin, and therefore 

is not included in inventory totals.6

In the case of water treatment plants, lime is used in the 

softening process. Some large water treatment plants may 

recover their waste calcium carbonate and calcine it into 

quicklime for reuse in the softening process. Further research 

is necessary to determine the degree to which lime recycling 

is practiced by water treatment plants in the United States.

The results of the Tier 2 quantitative uncertainty 

analysis are summarized in Table 4-9. Lime CO2 emissions 

were estimated to be between 14.6 and 17.1 Tg CO2 Eq. 

at the 95 percent confidence level. This indicates a range 

of approximately 8 percent below and 8 percent above the 

emission estimate of 15.8 Tg CO2 Eq.

4 Representatives of the National Lime Association estimate that CO2

reabsorption that occurs from the use of lime may offset as much as a quarter 

of the CO2 emissions from calcination (Males 2003).

5 Some carbide producers may also regenerate lime from their calcium 

hydroxide byproducts, which does not result in emissions of CO2. In 

making calcium carbide, quicklime is mixed with coke and heated in electric 

furnaces. The regeneration of lime in this process is done using a waste 

calcium hydroxide (hydrated lime) [CaC2 + 2H2O → C2H2 + Ca(OH)2], 

not calcium carbonate [CaCO3]. Thus, the calcium hydroxide is heated in 

the kiln to simply expel the water [Ca(OH)2 + heat ( CaO + H2O] and no 

CO2 is released.

6 Based on comments submitted by and personal communication with 

Dr. Sergio F. Galeano, Georgia-Pacific Corporation.

Table 4-8: Adjusted Lime Productiona (Gg)

Year High-Calcium Dolomitic

1990 12,514 2,809

1995 14,700 3,207

2000 15,473 3,506

2001 15,137 3,105

2002 14,536 2,934

2003 15,520 2,998

2004 15,820 3,526

2005 15,781 3,535

2006 16,794 3,448

a

 Minus water content of hydrated lime
Industrial Processes 4-9

Recalculations Discussion

Estimates of CO2 emissions from lime production were 

revised for all years in the time series to remove estimates 

of CO2 recovery associated with lime use during sugar 

refining and precipitate calcium carbonate (PCC) production. 

Currently, research does not indicate that CO2 used in these 

processes stems from CO2 captured during lime production. 

Additional research is needed to determine if lime production 

plants in the US capture CO2 as well as to determine the fates 

of precipitates formed during the sugar refining process. This 

change resulted in an average annual emission increase of 

9.5 percent.

4.3. Limestone and Dolomite Use 

(IPCC Source Category 2A3)

Limestone (CaCO3) and dolomite (CaCO3MgCO3)

7

are basic raw materials used by a wide variety of industries, 

including construction, agriculture, chemical, metallurgy, 

glass production, and environmental pollution control. 

7Limestone and dolomite are collectively referred to as limestone by the 

industry, and intermediate varieties are seldom distinguished.

Limestone is widely distributed throughout the world 

in deposits of varying sizes and degrees of purity. Large 

deposits of limestone occur in nearly every state in the United 

States, and significant quantities are extracted for industrial 

applications. For some of these applications, limestone is 

sufficiently heated during the process and generates CO2 as a 

byproduct. Examples of such applications include limestone 

used as a flux or purifier in metallurgical furnaces, as a 

sorbent in flue gas desulfurization systems for utility and 

industrial plants, or as a raw material in glass manufacturing 

and magnesium production.

In 2006, approximately 13,192 thousand metric tons of 

limestone and 5,886 thousand metric tons of dolomite were 

consumed during production for these applications. Overall, 

usage of limestone and dolomite resulted in aggregate CO2

emissions of 8.6 Tg CO2 Eq. (8,615 Gg) (see Table 4-10 and 

Table 4-11). Emissions in 2006 increased 17 percent from 

the previous year and have increased 56 percent overall from 

1990 through 2006.

Table 4-9: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lime Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Lime Production CO2 15.8 14.6 17.1 -8% +8%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

Table 4-10: CO2 Emissions from Limestone & Dolomite Use (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Flux Stone 3.0 4.0 2.8 2.5 2.4 2.1 4.1 3.3 5.1

Glass Making 0.2 0.5 0.4 0.1 0.1 0.3 0.4 0.4 0.7

FGD 1.4 1.7 1.8 2.6 2.8 1.9 1.9 3.0 2.1

Magnesium Production 0.1 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0

Other Miscellaneous Uses 0.8 1.1 0.9 0.5 0.7 0.4 0.4 0.7 0.7

Total 5.5 7.4 6.0 5.7 5.9 4.8 6.7 7.4 8.6

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.
4-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Methodology

CO2 emissions were calculated by multiplying the 

quantity of limestone or dolomite consumed by the average 

C content, approximately 12.0 percent for limestone and 

13.2 percent for dolomite (based on stoichiometry), and 

converting this value to CO2. This methodology was used 

for flux stone, glass manufacturing, flue gas desulfurization 

systems, chemical stone, mine dusting or acid water 

treatment, acid neutralization, and sugar refining and then 

converting to CO2 using a molecular weight ratio.

Traditionally, the production of magnesium metal was 

the only other significant use of limestone and dolomite that 

produced CO2 emissions. At the start of 2001, there were 

two magnesium production plants operating in the United 

States and they used different production methods. One plant 

produced magnesium metal using a dolomitic process that 

resulted in the release of CO2 emissions, while the other 

plant produced magnesium from magnesium chloride using 

a CO2-emissions-free process called electrolytic reduction. 

However, the plant utilizing the dolomitic process ceased 

its operations prior to the end of 2001, so beginning in 2002 

there were no emissions from this particular sub-use.

Consumption data for 1990 through 2006 of limestone 

and dolomite used for flux stone, glass manufacturing, flue 

gas desulfurization systems, chemical stone, mine dusting or 

acid water treatment, acid neutralization, and sugar refining 

(see Table 4-12) were obtained from the USGS Minerals 

Yearbook: Crushed Stone Annual Report (USGS 1993, 

1995a, 1996a through 2007a). The production capacity 

data for 1990 through 2006 of dolomitic magnesium metal 

(see Table 4-13) also came from the USGS (1995b, 1996b 

through 2007b). The last plant in the United States that 

used the dolomitic production process for magnesium metal 

closed in 2001. The USGS does not mention this process 

in the 2006 Minerals Yearbook: Magnesium; therefore, it 

is assumed that this process continues to be non-existent in 

the United States (USGS 2007b). During 1990 and 1992, the 

USGS did not conduct a detailed survey of limestone and 

dolomite consumption by end-use. Consumption for 1990 

was estimated by applying the 1991 percentages of total 

limestone and dolomite use constituted by the individual 

limestone and dolomite uses to 1990 total use. Similarly, the 

1992 consumption figures were approximated by applying an 

average of the 1991 and 1993 percentages of total limestone 

and dolomite use constituted by the individual limestone and 

dolomite uses to the 1992 total.

Additionally, each year the USGS withholds data 

on certain limestone and dolomite end-uses due to 

confidentiality agreements regarding company proprietary 

data. For the purposes of this analysis, emissive end-uses 

that contained withheld data were estimated using one of 

the following techniques: (1) the value for all the withheld 

data points for limestone or dolomite use was distributed 

evenly to all withheld end-uses, (2) the average percent of 

total limestone or dolomite for the withheld end-use in the 

preceding and succeeding years, or (3) the average fraction 

of total limestone or dolomite for the end-use over the entire 

time period.

Finally, there is a large quantity of crushed stone 

reported to the USGS under the category “unspecified uses.” 

Table 4-11: CO2 Emissions from Limestone & Dolomite Use (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Flux Stone 2,999 4,004 2,830 2,514 2,405 2,081 4,112 3,265 5,072

Limestone 2,554 3,077 1,810 1,640 1,330 913 2,023 1,398 2,291

Dolomite 446 927 1,020 874 1,075 1,168 2,088 1,867 2,781

Glass Making 217 533 368 113 61 339 350 427 747

Limestone 189 410 368 113 61 339 350 406 717

Dolomite 28 122 0 0 0 0 0 21 31

FGD 1,433 1,663 1,774 2,551 2,766 1,950 1,871 2,985 2,061

Magnesium Production 64 41 73 53 0 0 0 0 0

Other Miscellaneous Uses 819 1,119 916 501 652 383 369 721 735

Total 5,533 7,359 5,960 5,733 5,885 4,753 6,702 7,397 8,615

Notes: Totals may not sum due to independent rounding. Other miscellaneous uses include chemical stone, mine dusting or acid water treatment, acid 

neutralization, and sugar refining.
Industrial Processes 4-11

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, 

among other minerals. The exact specifications for limestone 

8This approach was recommended by USGS.

or dolomite used as flux stone vary with the pyrometallurgical 

process and the kind of ore processed. Similarly, the quality 

of the limestone used for glass manufacturing will depend 

on the type of glass being manufactured.

The estimates below also account for uncertainty 

associated with activity data. Large fluctuations in reported 

consumption exist, reflecting year-to-year changes in the 

number of survey responders. The uncertainty resulting from 

a shifting survey population is exacerbated by the gaps in 

the time series of reports. The accuracy of distribution by 

end use is also uncertain because this value is reported by 

the manufacturer and not the end user. Additionally, there is 

significant inherent uncertainty associated with estimating 

withheld data points for specific end uses of limestone and 

dolomite. The uncertainty of the estimates for limestone 

used in glass making is especially high; however, since 

glass making accounts for a small percent of consumption, 

its contribution to the overall emissions estimate is low. 

Lastly, much of the limestone consumed in the United 

States is reported as “other unspecified uses;” therefore, it 

is difficult to accurately allocate this unspecified quantity to 

the correct end-uses.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-14. Limestone and Dolomite Use 

CO2 emissions were estimated to be between 8.0 and 9.2 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates a 

range of approximately 7 percent below and 7 percent above 

the emission estimate of 8.6 Tg CO2 Eq.

Table 4-12: Limestone and Dolomite Consumption (Thousand Metric Tons)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Flux Stone 6,738 8,935 6,249 5,558 5,275 4,521 8,971 7,086 11,030

Limestone 5,804 6,995 4,114 3,727 3,023 2,075 4,599 3,176 5,208

Dolomite 933 1,941 2,135 1,831 2,252 2,446 4,373 3,910 5,822

Glass Making 489 1,189 836 258 139 771 796 966 1,693

Limestone 430 933 836 258 139 771 796 923 1,629

Dolomite 59 256 0 0 0 0 0 43 64

FGD 3,258 3,779 4,031 5,798 6,286 4,432 4,253 6,785 4,683

Other Miscellaneous Uses 1,835 2,543 2,081 1,138 1,483 870 840 1,638 1,671

Total 12,319 16,445 13,197 12,751 13,183 10,594 14,859 16,475 19,078

Notes: “Other miscellaneous uses” includes chemical stone, mine dusting or acid water treatment, acid neutralization, and sugar refining. Zero values for 

limestone and dolomite consumption for glass making result during years when the USGS reports that no limestone or dolomite are consumed for this use.

Table 4-13: Dolomitic Magnesium Metal Production 

Capacity (Metric Tons)

Year Production Capacity

1990 35,000

1995 22,222

2000 40,000

2001 29,167

2002 0

2003 0

2004 0

2005 0

2006 0

Note: Production capacity for 2002, 2003, 2004, 2005, and 2006 

amounts to zero because the last U.S. production plant employing the 

dolomitic process shut down mid-2001 (USGS 2002b through 2007b).
4-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Recalculations Discussion

Emission estimates for 2003 were revised to reflect 

updated limestone production data. This change resulted in 

a less than one percent increase in 2003 emissions.

Planned Improvements

Future improvements to the limestone and dolomite 

source category involve research into the availability of 

limestone and dolomite end-use data. If sufficient data are 

available, limestone and dolomite used as process materials 

in source categories to be included in future inventories (e.g., 

glass production, other process use of carbonates) may be 

removed and the emission estimates included there.

4.4. Soda Ash Production and 

Consumption (IPCC Source 

Category 2A4)

Soda ash (sodium carbonate, Na2CO3) is a white 

crystalline solid that is readily soluble in water and strongly 

alkaline. Commercial soda ash is used as a raw material in a 

variety of industrial processes and in many familiar consumer 

products such as glass, soap and detergents, paper, textiles, 

and food. It is used primarily as an alkali, either in glass 

manufacturing or simply as a material that reacts with and 

neutralizes acids or acidic substances. Internationally, two 

types of soda ash are produced—natural and synthetic. The 

United States produces only natural soda ash and is second 

only to China in total soda ash-production. Trona is the 

principal ore from which natural soda ash is made.

Only two states produce natural soda ash: Wyoming and 

California. Of these two states, only net emissions of CO2

from Wyoming were calculated due to specifics regarding 

the production processes employed in the state.9 During the 

production process used in Wyoming, trona ore is treated 

to produce soda ash. CO2 is generated as a byproduct of 

this reaction, and is eventually emitted into the atmosphere. 

In addition, CO2 may also be released when soda ash is 

consumed.

In 2006, CO2 emissions from the production of soda ash 

from trona were approximately 1.6 Tg CO2 Eq. (1,626 Gg). 

Soda ash consumption in the United States generated 2.5 

Tg CO2 Eq. (2,536 Gg) in 2006. Total emissions from soda 

9 In California, soda ash is produced using sodium carbonate-bearing brines 

instead of trona ore. To extract the sodium carbonate, the complex brines are 

first treated with CO2 in carbonation towers to convert the sodium carbonate 

into sodium bicarbonate, which then precipitates from the brine solution. 

The precipitated sodium bicarbonate is then calcined back into sodium 

carbonate. Although CO2 is generated as a byproduct, the CO2 is recovered 

and recycled for use in the carbonation stage and is not emitted.

A third state, Colorado, produced soda ash until the plant was idled in 2004. 

The lone producer of sodium bicarbonate no longer mines trona in the 

state. For a brief time, NaHCO3 was produced using soda ash feedstocks 

mined in Wyoming and shipped to Colorado. Because the trona is mined 

in Wyoming, the production numbers given by the USGS included the 

feedstocks mined in Wyoming and shipped to Colorado. In this way, the 

sodium bicarbonate production that took place in Colorado was accounted 

for in the Wyoming numbers.

Table 4-14: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Limestone and Dolomite Use 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Limestone and 

Dolomite Use CO2 8.6 8.0 9.2 -7% +7%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

Table 4-15: CO2 Emissions from Soda Ash Production 

and Consumption (Tg CO2 Eq.)

Year Production Consumption Total

1990 1.4 2.7 4.1

1995 1.6 2.7 4.3

2000 1.5 2.7 4.2

2001 1.5 2.6 4.1

2002 1.5 2.7 4.1

2003 1.5 2.6 4.1

2004 1.6 2.6 4.2

2005 1.7 2.6 4.2

2006 1.6 2.5 4.2

Note: Totals may not sum due to independent rounding.
Industrial Processes 4-13

ash production and consumption in 2006 were 4.2 Tg CO2

Eq. (4,162 Gg) (see Table 4-15 and Table 4-16). Emissions 

have fluctuated since 1990. These fluctuations were strongly 

related to the behavior of the export market and the U.S. 

economy. Emissions in 2006 decreased by approximately 1.6 

percent from the previous year, and have increased overall 

by approximately 0.5 percent since 1990.

The United States represents about one-fourth of total 

world soda ash output. The approximate distribution of 

soda ash by end-use in 2006 was glass making, 50 percent; 

chemical production, 29 percent; soap and detergent 

manufacturing, 9 percent; distributors, 4 percent; flue gas 

desulfurization, 2 percent; water treatment, 2 percent; pulp 

and paper production, 1 percent; and miscellaneous, 3 percent 

(USGS 2007).

Although the United States continues to be a major 

supplier of world soda ash, China, which surpassed the 

United States in soda ash production in 2003, is the world’s 

leading producer. While Chinese soda ash production 

appears to be stabilizing, U.S. competition in Asian markets 

is expected to continue. Despite this competition, U.S. soda 

ash production is expected to increase by about 0.5 percent 

annually over the next five years (USGS 2006).

Methodology

During the production process, trona ore is calcined in a 

rotary kiln and chemically transformed into a crude soda ash 

that requires further processing. CO2 and water are generated 

as byproducts of the calcination process. CO2 emissions 

from the calcination of trona can be estimated based on the 

following chemical reaction:

Two moles of trona are converted to three moles of soda ash plus five moles of water plus one 

mole of carbon dioxide.

Based on this formula, approximately 10.27 metric tons 

of trona are required to generate one metric ton of CO2, or 

an emission factor of 0.097 metric tons CO2 per metric ton 

trona (IPCC 2006). Thus, the 16.7 million metric tons of 

trona mined in 2006 for soda ash production (USGS 2007) 

resulted in CO2 emissions of approximately 1.6 Tg CO2 Eq. 

(1,626 Gg).

Once manufactured, most soda ash is consumed in 

glass and chemical production, with minor amounts in soap 

and detergents, pulp and paper, flue gas desulfurization and 

water treatment. As soda ash is consumed for these purposes, 

additional CO2 is usually emitted. In these applications, it 

is assumed that one mole of C is released for every mole of 

soda ash used. Thus, approximately 0.113 metric tons of C 

(or 0.415 metric tons of CO2) are released for every metric 

ton of soda ash consumed.

The activity data for trona production and soda ash 

consumption (see Table 4-17) were taken from USGS (1994 

through 2007). Soda ash production and consumption data 

were collected by the USGS from voluntary surveys of the 

U.S. soda ash industry.

Uncertainty

Emission estimates from soda ash production have 

relatively low associated uncertainty levels in that 

reliable and accurate data sources are available for the 

Table 4-16: CO2 Emissions from Soda Ash Production 

and Consumption (Gg)

Year Production Consumption Total

1990 1,431 2,710 4,141

1995 1,607 2,698 4,304

2000 1,529 2,652 4,181

2001 1,500 2,648 4,147

2002 1,470 2,668 4,139

2003 1,509 2,602 4,111

2004 1,607 2,598 4,205

2005 1,655 2,573 4,228

2006 1,626 2,536 4,162

Note: Totals may not sum due to independent rounding.

Table 4-17: Soda Ash Production and 

Consumption (Gg)

Year Production* Consumption

1990 14,700 6,530

1995 16,500 6,500

2000 15,700 6,390

2001 15,400 6,380

2002 15,100 6,430

2003 15,500 6,270

2004 16,500 6,260

2005 17,000 6,200

2006 16,700 6,110

* Soda ash produced from trona ore only.

2(Na3(CO3)(HCO3)•2H2O) → 3Na2CO3 + 5H2O + CO2

[trona] [soda ash]
4-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

emission factor and activity data. The primary source of 

uncertainty, however, results from the fact that emissions 

from soda ash consumption are dependent upon the type of 

processing employed by each end-use. Specific information 

characterizing the emissions from each end-use is limited. 

Therefore, there is uncertainty surrounding the emission 

factors from the consumption of soda ash.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-18. Soda Ash Production and 

Consumption CO2 emissions were estimated to be between 

3.9 and 4.5 Tg CO2 Eq. at the 95 percent confidence level. 

This indicates a range of approximately 7 percent below and 

7 percent above the emission estimate of 4.2 Tg CO2 Eq.

Planned Improvements

Future Inventories may include estimates of emissions 

from glass production and other use of carbonates. These 

Inventories will extract soda ash consumed for glass 

production and other use of carbonates from the current 

soda ash consumption emission estimates and include them 

under those sources.

4.5. Ammonia Production (IPCC 

Source Category 2B1) and Urea 

Consumption

Emissions of CO2 occur during the production of 

synthetic ammonia, primarily through the use of natural gas 

as a feedstock. The natural-gas-based, naphtha-based, and 

petroleum-coke-based processes produce CO2 and hydrogen 

(H2), the latter of which is used in the production of ammonia. 

One nitrogen production plant located in Kansas is producing 

ammonia from petroleum coke feedstock. In some plants the 

CO2 produced is captured and used to produce urea. The 

brine electrolysis process for production of ammonia does 

not lead to process-based CO2 emissions.

There are five principal process steps in synthetic 

ammonia production from natural gas feedstock. The primary 

reforming step converts CH4 to CO2, carbon monoxide (CO), 

and H2 in the presence of a catalyst. Only 30 to 40 percent 

of the CH4 feedstock to the primary reformer is converted 

to CO and CO2. The secondary reforming step converts the 

remaining CH4 feedstock to CO and CO2. The CO in the 

process gas from the secondary reforming step (representing 

approximately 15 percent of the process gas) is converted to 

CO2 in the presence of a catalyst, water, and air in the shift 

conversion step. CO2 is removed from the process gas by the 

shift conversion process, and the hydrogen gas is combined 

with the nitrogen (N2) gas in the process gas during the 

ammonia synthesis step to produce ammonia. The CO2 is 

included in a waste gas stream with other process impurities 

and is absorbed by a scrubber solution. In regenerating the 

scrubber solution, CO2 is released.

The conversion process for conventional steam reforming 

of CH4, including primary and secondary reforming and the 

shift conversion processes, is approximately as follows:

0.88 mole of methane plus 1.26 mole air plus 1.24 mole water are converted with a catalyst to 0.88 mole of carbon 

dioxide plus one mole of nitrogen plus three moles of hydrogen. 

One mole of nitrogen plus three moles of hydrogen are converted to two moles of ammonia.

To produce synthetic ammonia from petroleum coke, 

the petroleum coke is gasified and converted to CO2 and H2. 

These gases are separated, and the H2 is used as a feedstock 

to the ammonia production process, where it is reacted with 

N2 to form ammonia.

Not all of the CO2 produced in the production of 

ammonia is emitted directly to the atmosphere. Both 

ammonia and CO2 are used as raw materials in the production 

of urea [CO(NH2)2], which is another type of nitrogenous 

(catalyst)

0.88 CH4 + 1.26 Air + 1.24H2O → 0.88 CO2 + N2 + 3H2

N2 + 3H2 → 2 NH3

Table 4-18: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Soda Ash Production and 

Consumption (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Soda Ash Production 

and Consumption CO2 4.2 3.9 4.5 -7% +7%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-15

fertilizer that contains C as well as N. The chemical reaction 

that produces urea is:

Two moles of ammonia plus one mole of carbon dioxide are converted to one mole of ammonium carbonate which converts to one mole of urea plus one mole of water.

Urea is consumed in a variety of uses, including as a 

nitrogenous fertilizer, in urea-formaldehyde resins, and as 

a deicing agent (TIG 2002). The C in the consumed urea is 

assumed to be released into the environment as CO2 during 

use. Therefore, the CO2 produced by ammonia production 

that is subsequently used in the production of urea is still 

emitted during urea consumption. The majority of CO2

emissions associated with urea consumption are those 

that result from its use as a fertilizer. These emissions are 

accounted for in the Cropland Remaining Cropland section 

of the Land Use, Land-Use Change, and Forestry chapter. 

CO2 emissions associated with other uses of urea are 

accounted for in this chapter. Net emissions of CO2 from 

ammonia production in 2006 were 11.8 Tg CO2 Eq. (11,832 

Gg), and are summarized in Table 4-19 and Table 4-20. 

Emissions of CO2 from urea consumed for non-fertilizer 

purposes in 2006 totaled 0.5 Tg CO2 Eq. (543 Gg), and are 

summarized in Table 4-19 and Table 4-20. The decrease 

in ammonia production in recent years is due to several 

factors, including market fluctuations and high natural gas 

prices. Ammonia production relies on natural gas as both 

a feedstock and a fuel, and as such, domestic producers 

are competing with imports from countries with lower gas 

prices. If natural gas prices remain high, it is likely that 

domestically produced ammonia will continue to decrease 

with increasing ammonia imports (EEA 2004).

Methodology

The calculation methodology for non-combustion 

CO2 emissions from production of nitrogenous fertilizers 

from natural gas feedstock is based on a CO2 emission 

factor published by the European Fertilizer Manufacturers 

Association (EFMA). The selected EFMA factor is based on 

ammonia production technologies that are similar to those 

employed in the United States. The CO2 emission factor (1.2 

metric tons CO2/metric ton NH3) is applied to the percent 

of total annual domestic ammonia production from natural 

gas feedstock. Emissions from fuels consumed for energy 

purposes during the production of ammonia are accounted 

for in the Energy chapter. Emissions of CO2 from ammonia 

production are then adjusted to account for the use of some of 

the CO2 produced from ammonia production as a raw material 

in the production of urea. For each ton of urea produced, 8.8 

of every 12 tons of CO2 are consumed and 6.8 of every 12 

tons of ammonia are consumed. The CO2 emissions reported 

for ammonia production are therefore reduced by a factor 

of 0.73 multiplied by total annual domestic urea production. 

Total CO2 emissions resulting from nitrogenous fertilizer 

production do not change as a result of this calculation, 

but some of the CO2 emissions are attributed to ammonia 

production and some of the CO2 emissions are attributed to 

urea consumption. Those CO2 emissions that result from the 

use of urea as a fertilizer are accounted for in the Land Use, 

Land-Use Change, and Forestry chapter.

Approximately 87 percent (TIG 2002) of urea consumed 

in the United States is consumed as a nitrogenous fertilizer 

2 NH3 + CO2 → NH2COONH4 → CO(NH2)2 + H2O

Table 4-19: CO2 Emissions from Ammonia Production and Urea Consumption (Tg CO2 Eq.)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Ammonia Production 16.5 17.4 15.9 12.8 13.7 11.9 12.7 12.3 11.8

Urea Consumptiona 0.4 0.4 0.5 0.5 0.5 0.6 0.5 0.5 0.5

Total 16.9 17.8 16.4 13.3 14.2 12.5 13.2 12.8 12.4

Note: Totals may not sum due to independent rounding.

a

 Urea Consumption is for non-fertilizer purposes only. Urea consumed as a fertilizer is accounted for in the Land Use, Land-Use Change, and Forestry chapter.

Table 4-20: CO2 Emissions from Ammonia Production and Urea Consumption (Gg)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Ammonia Production 16,528 17,399 15,922 12,795 13,660 11,937 12,695 12,293 11,832

Urea Consumptiona 361 397 480 510 534 551 546 524 543

Total 16,889 17,796 16,402 13,305 14,194 12,488 13,241 12,817 12,376

Note: Totals may not sum due to independent rounding.

a

 Urea Consumption is for non-fertilizer purposes only. Urea consumed as a fertilizer is accounted for in the Land Use, Land-Use Change, and Forestry chapter.
4-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

on agricultural lands. The total amount of urea consumed 

is estimated based on this percent and the quantity of urea 

fertilizer applied to agricultural lands, which is obtained 

directly from the Land Use, Land-Use Change, and Forestry 

Chapter, and is reported in Table 4-21. CO2 emissions 

associated with the remaining urea are estimated using a 

factor of 0.73 tons of CO2 per ton of urea consumed. Total 

urea production is estimated based on the amount of urea 

applied plus the sum of net urea imports and exports.

All ammonia production and subsequent urea production 

are assumed to be from the same process—conventional 

catalytic reforming of natural gas feedstock, with the exception 

of ammonia production from petroleum coke feedstock at 

one plant located in Kansas. The CO2 emission factor for 

production of ammonia from petroleum coke is based on plantspecific data, wherein all C contained in the petroleum coke 

feedstock that is not used for urea production is assumed to be 

emitted to the atmosphere as CO2 (Bark 2004). Ammonia and 

urea are assumed to be produced in the same manufacturing 

complex, as both the raw materials needed for urea production 

are produced by the ammonia production process. The CO2

emission factor (3.57 metric tons CO2/metric ton NH3) is 

applied to the percent of total annual domestic ammonia 

production from petroleum coke feedstock.

The emission factor of 1.2 metric ton CO2/metric ton 

NH3 for production of ammonia from natural gas feedstock 

was taken from the EFMA Best Available Techniques 

publication, Production of Ammonia (EFMA 1995). The 

EFMA reported an emission factor range of 1.15 to 1.30 

metric ton CO2/metric ton NH3, with 1.2 metric ton CO2/

metric ton NH3 as a typical value. Technologies (e.g., catalytic 

reforming process) associated with this factor are found to 

closely resemble those employed in the United States for 

use of natural gas as a feedstock. The EFMA reference also 

indicates that more than 99 percent of the CH4 feedstock 

to the catalytic reforming process is ultimately converted 

to CO2. The emission factor of 3.57 metric ton CO2/metric 

ton NH3 for production of ammonia from petroleum coke 

feedstock was developed from plant-specific ammonia 

production data and petroleum coke feedstock utilization 

data for the ammonia plant located in Kansas (Bark 2004). 

As noted earlier, emissions from fuels consumed for energy 

purposes during the production of ammonia are accounted for 

in the Energy chapter. Ammonia production data (see Table 

4-21) was obtained from Coffeyville Resources (Coffeyville 

2005, 2006, 2007) and the Census Bureau of the U.S. 

Department of Commerce (U.S. Census Bureau 1991 through 

1994, 1998 through 2007) as reported in Current Industrial 

Reports Fertilizer Materials and Related Products annual 

and quarterly reports. Urea-ammonia nitrate production 

was obtained from Coffeyville Resources (Coffeyville 2005 

through 2007). With the exception of 2006 urea export data, 

import and export data for urea were obtained from the 

U.S. Census Bureau Current Industrial Reports Fertilizer 

Materials and Related Products annual and quarterly reports 

for 1997 through 2006 (U.S. Census Bureau 1998 through 

2007), The Fertilizer Institute (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 4-21). Because the U.S. Census 

Bureau did not report urea export data for 2006, 2005 data 

were proxied.

Table 4-21: Ammonia Production, Urea Production, Urea Net Imports, and Urea Exports (Gg)

Year Ammonia Production Urea Applied as Fertilizer Urea Imports Urea Exports

1990 15,425 3,296 1,860 774

1995 15,788 3,623 2,936 881

2000 14,342 4,382 3,904 663

2001 11,092 4,655 4,800 792

2002 12,577 4,871 3,840 970

2003 10,279 5,025 4,973 723

2004 10,939 4,982 4,935 704

2005 10,143 4,779 5,026 579

2006 9,962 4,958 5,029 579
Industrial Processes 4-17

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, and the assumption that 87 percent of urea 

consumed is as fertilizer. Uncertainties are also associated 

with natural gas feedstock consumption data for the U.S. 

ammonia industry as a whole, the assumption that all 

ammonia production and subsequent urea production was 

from the same process—conventional catalytic reforming 

of natural gas feedstock, with the exception of one ammonia 

production plant located in Kansas that is manufacturing 

ammonia from petroleum coke feedstock. It is also assumed 

that ammonia and urea are produced at collocated plants from 

the same natural gas raw material.

Such recovery may or may not affect the overall estimate 

of CO2 emissions depending upon the end use to which the 

recovered CO2 is applied. Further research is required to 

determine whether byproduct CO2 is being recovered from 

other ammonia production plants for application to end uses 

that are not accounted for elsewhere.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-22. Ammonia Production and 

Urea Consumption CO2 emissions were estimated to 

be between 11.1 and 13.8 Tg CO2 Eq. at the 95 percent 

confidence level. This indicates a range of approximately 10 

percent below and 12 percent above the emission estimate 

of 12.4 Tg CO2 Eq.

Recalculations Discussion

Estimates of CO2 emissions from ammonia production 

and urea consumption were revised for all years to allocate 

CO2 emissions associated with urea applied as fertilizer 

to the Land Use, Land-Use Change, and Forestry chapter. 

Revised estimates reflect a new methodology that estimates 

urea production and consumption based on urea consumed as 

fertilizer. Previous estimates of urea production are believed 

to have overestimated actual urea production. On average, 

this change resulted in a 19 percent decrease in emissions 

for each year in the time series 1990 through 2005; however, 

because CO2 captured during ammonia production to produce 

urea is estimated based on the amount of urea produced, 

emissions from ammonia production have increased.

Planned Improvements

Plans for improvements to the ammonia production and 

urea consumption source category include updating emission 

factors to include both fuel and feedstock CO2 emissions and 

incorporating CO2 capture and storage. Methodologies will 

also be updated if additional ammonia-production plants are 

found to hydrocarbons other than natural gas for ammonia 

production.

Table 4-22: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ammonia Production and Urea 

Consumption (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Ammonia Production 

and Urea Consumption CO2 12.4 11.1 13.8 -10% +12%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

4.6. Nitric Acid Production (IPCC 

Source Category 2B2)

Nitric acid (HNO3) is an inorganic compound used 

primarily to make synthetic commercial fertilizers. It is 

also a major component in the production of adipic acid—a 

feedstock for nylon—and explosives. Virtually all of the 

nitric acid produced in the United States is produced by the 

catalytic oxidation of ammonia (EPA 1997). During this 

reaction, N2O is formed as a byproduct and is released from 

reactor vents into the atmosphere.

Currently, the nitric acid industry controls for emissions 

of NO and NO2 (i.e., NOx). As such, the industry uses a 

combination of non-selective catalytic reduction (NSCR) 

and selective catalytic reduction (SCR) technologies. In the 

process of destroying NOx, NSCR systems are also very 

effective at destroying N2O. However, NSCR units are 

generally not preferred in modern plants because of high 

energy costs and associated high gas temperatures. NSCRs 

were widely installed in nitric plants built between 1971 

and 1977. Approximately 20 percent of nitric acid plants 

use NSCR (Choe et al. 1993). The remaining 80 percent use 

SCR or extended absorption, neither of which is known to 

reduce N2O emissions.

N2O emissions from this source were estimated to be 

15.6 Tg CO2 Eq. (50 Gg) in 2006 (see Table 4-23). Emissions 

from nitric acid production have decreased by 7.8 percent 

since 1990, with the trend in the time series closely tracking 

the changes in production.

Methodology

N2O emissions were calculated by multiplying nitric 

acid production by the amount of N2O emitted per unit of 

nitric acid produced. The emission factor was determined as 

a weighted average of 2 kg N2O/metric ton HNO3 for plants 

using non-selective catalytic reduction (NSCR) systems 

and 9 kg N2O/metric ton HNO3 for plants not equipped 

with NSCR (IPCC 2006). In the process of destroying NOx, 

NSCR systems destroy 80 to 90 percent of the N2O, which 

is accounted for in the emission factor of 2 kg N2O/metric 

ton HNO3. An estimated 20 percent of HNO3 plants in the 

United States are equipped with NSCR (Choe et al. 1993). 

Hence, the emission factor is equal to (9 × 0.80) + (2 × 0.20) 

= 7.6 kg N2O per metric ton HNO3.

Nitric acid production data for 1990 through 2004 was 

obtained from the U.S. Census Bureau, Current Industrial 

Reports (2006) and for 2005 through 2006, from the U.S. 

Census Bureau, Current Industrial Reports (2007) (see 

Table 4-24).

Uncertainty

The overall uncertainty associated with the 2006 

N2O emissions estimate from nitric acid production 

was calculated using the IPCC Guidelines for National 

Greenhouse Gas Inventories (2006) Tier 2 methodology. 

Uncertainty associated with the parameters used to estimate 

N2O emissions included that of production data, the share 

of U.S. nitric acid production attributable to each emission 

abatement technology, and the emission factors applied to 

each abatement technology type.

Table 4-23: N2O Emissions from Nitric Acid Production 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 17.0 55

1995 18.9 61

2000 18.6 60

2001 15.1 49

2002 16.4 53

2003 15.4 50

2004 15.2 49

2005 15.8 51

2006 15.6 50

Table 4-24: Nitric Acid Production (Gg)

Year Gg

1990 7,195

1995 8,019

2000 7,900

2001 6,417

2002 6,941

2003 6,522

2004 6,467

2005 6,711

2006 6,637
Industrial Processes 4-19

The results of this Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-25. N2O emissions from nitric acid 

production were estimated to be between 9.4 and 22.1 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates a 

range of approximately 40 percent below to 41 percent above 

the 2006 emissions estimate of 15.6 Tg CO2 Eq.

Recalculations Discussion

The nitric acid production values for 2003 and 2005 

have been updated relative to the previous Inventory based 

on revised production data published by the U.S. Census 

Bureau (2006, 2007). The updated production data for 2003 

resulted in a decrease of 0.6 Tg CO2 Eq. (3.3 percent) in N2O 

emissions relative to the previous Inventory. The updated 

production data for 2005 resulted in an increase of 1.0 Tg CO2

Eq. (6.1 percent) in N2O emissions relative to the previous 

Inventory. Minor changes in production data due to directly 

citing U.S. Census Bureau reports in this Inventory resulted in 

negligible changes in N2O emissions relative to the previous 

Inventory (less than one-tenth of one percent) for all other 

years in the time series, respectively. Additionally, the N2O 

emission factor for plants not equipped with NSCR systems 

has been updated based on IPCC Guidelines (2006), which 

resulted in a slight decrease in emissions in each year of 

the time series relative to the previous Inventory. Overall, 

these changes resulted in an average annual decrease in N2O 

emissions of 0.9 Tg CO2 Eq. (4.8 percent) for the period 1990 

through 2005 relative to the previous Inventory.

Planned Improvements

Planned improvements are focused on assessing 

the plant-by-plant implementation of NOx abatement 

technologies to more accurately match plant production 

capacities to appropriate emission factors, instead of using 

a national profiling of abatement implementation.

4.7. Adipic Acid Production (IPCC 

Source Category 2B3)

Adipic acid production is an anthropogenic source of 

N2O emissions. Worldwide, few adipic acid plants exist. 

The United States and Europe are the major producers. 

The United States has three companies in four locations 

accounting for 34 percent of world production, and eight 

European producers account for a combined 38 percent 

of world production (CW 2007). Adipic acid is a white 

crystalline solid used in the manufacture of synthetic fibers, 

plastics, coatings, urethane foams, elastomers, and synthetic 

lubricants. Commercially, it is the most important of the 

aliphatic dicarboxylic acids, which are used to manufacture 

polyesters. Eighty-four percent of all adipic acid produced 

in the United States is used in the production of nylon 6,6, 

9 percent is used in the production of polyester polyols, 4 

percent is used in the production of plasticizers, and the 

remaining 4 percent is accounted for by other uses, including 

unsaturated polyester resins and food applications (ICIS 

2007). Food-grade adipic acid is used to provide some foods 

with a “tangy” flavor (Thiemens and Trogler 1991).

Adipic acid is produced through a two-stage process 

during which N2O is generated in the second stage. The 

first stage of production usually involves the oxidation of 

cyclohexane to form a cyclohexanone/cyclohexanol mixture. 

The second stage involves oxidizing this mixture with nitric 

acid to produce adipic acid. N2O is generated as a byproduct 

of the nitric acid oxidation stage and is emitted in the waste 

gas stream (Thiemens and Trogler 1991). Process emissions 

from the production of adipic acid vary with the types of 

technologies and level of emission controls employed by a 

facility. In 1990, two of the three major adipic acid-producing 

plants had N2O abatement technologies in place and, as of 

1998, the three major adipic acid production facilities had 

Table 4-25: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions From Nitric Acid Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Nitric Acid Production N2O 15.6 9.4 22.1 -40% +41%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

control systems in place.10 Only one small plant, representing 

approximately two percent of production, does not control 

for N2O (Reimer 1999).

N2O emissions from adipic acid production were 

estimated to be 5.9 Tg CO2 Eq. (19 Gg) in 2006 (see Table 

4-26). National adipic acid production has increased by 

approximately 36 percent over the period of 1990 through 

2006, to approximately one million metric tons. At the same 

time, emissions have been reduced by 61 percent due to the 

widespread installation of pollution control measures in the 

late 1990s.

Methodology

For two production plants, 1990 to 2002 emission 

estimates were obtained directly from the plant engineer 

and account for reductions due to control systems in place at 

these plants during the time series (Childs 2002, 2003). These 

estimates were based on continuous emissions monitoring 

equipment installed at the two facilities. Reported emission 

estimates for 2003 to 2006 were unavailable and, thus, 

were calculated by applying 4.4, 4.2, 0.0, and 0.0 percent 

national production growth rates, respectively. 2003 national 

production was calculated through linear interpolation 

between 2002 and 2004 reported national production data. 

2005 national production was calculated through linear 

interpolation between 2004 and 2006 reported national 

production. Subsequently, the growth rates for 2004, 2005, 

and 2006 were based on the change between the estimated 

10 During 1997, the N2O emission controls installed by the third plant 

operated for approximately a quarter of the year.

2003 production data and the reported 2004 production data, 

the change between 2004 reported production data and the 

estimated 2005 production data, and between the estimated 

2005 production data and the reported 2006 production 

data, respectively (see discussion below on sources of 

production data). For the other two plants, N2O emissions 

were calculated by multiplying adipic acid production by 

an emission factor (i.e., N2O emitted per unit of adipic acid 

produced) and adjusting for the percentage of N2O released 

as a result of plant-specific emission controls. On the basis 

of experiments, the overall reaction stoichiometry for N2O 

production in the preparation of adipic acid was estimated 

at approximately 0.3 metric tons of N2O per metric ton of 

product (IPCC 2006). Emissions are estimated using the 

following equation:

Nitrous Oxide emissions equal production of adipic acid begin bracket metric tons of adipic acid 

end bracket, multiplied by begin parenthesis 0.3 metric tons of nitrous oxide divided by metric tons 

of adipic adic end parenthesis multiplied by begin parenthesis 1 minus open bracket nitrous oxide 

destruction factor multiplied by abatement system utility factor close bracket end parenthesis.

The “N2O destruction factor” represents the percentage 

of N2O emissions that are destroyed by the installed abatement 

technology. The “abatement system utility factor” represents 

the percentage of time that the abatement equipment operates 

during the annual production period. Overall, in the United 

States, two of the plants employ catalytic destruction, one 

plant employs thermal destruction, and the smallest plant 

uses no N2O abatement equipment. For the one plant that 

uses thermal destruction and for which no reported plantspecific emissions are available, the N2O abatement system 

destruction factor is assumed to be 98.5 percent, and the 

abatement system utility factor is assumed to be 97 percent 

(IPCC 2006).

For 1990 to 2003, plant-specific production data was 

estimated where direct emission measurements were not 

available. In order to calculate plant-specific production 

for the two plants, national adipic acid production was 

allocated to the plant level using the ratio of their known plant 

capacities to total national capacity for all U.S. plants. The 

estimated plant production for the two plants was then used 

for calculating emissions as described above. For 2004 and 

2006, actual plant production data were obtained for these 

two plants and used for emission calculations. For 2005, 

interpolated national production was used for calculating 

emissions as described above.

N2O emissions = production of adipic acid (MT) ×

(0.3 MT N2O/MT adipic acid) ×

(1-[N2O destruction factor × abatement system utility factor])

Table 4-26: N2O Emissions from Adipic Acid Production 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 15.3 49

1995 17.3 56

2000 6.2 20

2001 5.1 16

2002 6.1 20

2003 6.3 20

2004 5.9 19

2005 5.9 19

2006 5.9 19
Industrial Processes 4-21

National adipic acid production data (see Table 4-27) 

for 1990 through 2002 were obtained from the American 

Chemistry Council (ACC 2003). Production for 2003 was 

estimated based on linear interpolation of 2002 and 2004 

reported production. Production for 2004 and 2006 were 

obtained from Chemical Week, Product Focus: Adipic Acid 

(CW 2005, 2007). Plant capacities for 1990 through 1994 

were obtained from Chemical and Engineering News, “Facts 

and Figures” and “Production of Top 50 Chemicals” (C&EN 

1992 through 1995). Plant capacities for 1995 and 1996 were 

kept the same as 1994 data. The 1997 plant capacities were 

taken from Chemical Market Reporter “Chemical Profile: 

Adipic Acid” (CMR 1998). The 1998 plant capacities for all 

four plants and 1999 plant capacities for three of the plants 

were obtained from Chemical Week, Product Focus: Adipic 

Acid/Adiponitrile (CW 1999). Plant capacities for 2000 for 

three of the plants were updated using Chemical Market 

Reporter, “Chemical Profile: Adipic Acid” (CMR 2001). For 

2001 through 2005, the plant capacities for these three plants 

were kept the same as the year 2000 capacities. Plant capacity 

for 1999 to 2005 for the one remaining plant was kept the 

same as 1998. For 2004 to 2006, although plant capacity data 

are available (CW 1999, CMR 2001, ICIS 2007), they are 

not used to calculate plant-specific production for these years 

because plant-specific production data for 2004 and 2006 are 

also available and are used in our calculations instead (CW 

2005, CW 2007).

Uncertainty

The overall uncertainty associated with the 2006 N2O 

emission estimate from adipic acid production was calculated 

using the IPCC Guidelines for National Greenhouse 

Gas Inventories (2006) Tier 2 methodology. Uncertainty 

associated with the parameters used to estimate N2O 

emissions included that of company specific production data, 

industry wide estimated production growth rates, emission 

factors for abated and unabated emissions, and company 

specific historical emissions estimates.

The results of this Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-28. N2O emissions from adipic 

acid production were estimated to be between 5.0 and 6.9 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates a 

range of approximately 15 percent below to 16 percent above 

the 2006 emission estimate of 5.9 Tg CO2 Eq.

Recalculations Discussion

The adipic acid production value for 2005 was 

recalculated. In the 1990–2005 Inventory, 2005 production 

was calculated by applying the annual production growth rate 

from 2003 to 2004 of 4 percent to 2004 production. In this 

Inventory, 2005 production was recalculated because 2006 

production data is now available (CW 2007). 2005 production 

was estimated through linear interpolation between 2004 

and 2006 reported production data. The updated production 

value for 2005 resulted in a decrease of 0.3 Tg CO2 Eq. (4.1 

percent) in N2O emissions relative to the previous inventory. 

Additionally, changes based on IPCC Guidelines (2006) to 

the N2O destruction factor and abatement system utilization 

factor for one plant resulted in an increase of between 0.1 

and 0.2 Tg CO2 Eq. (0.8 to 3.2 percent) in N2O emissions in 

each year of the historical time series, respectively.

Table 4-27: Adipic Acid Production (Gg)

Year Gg

1990 735

1995 830

2000 925

2001 835

2002 921

2003 961

2004 1,002

2005 1,002

2006 1,002

Table 4-28: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions from Adipic Acid Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Adipic Acid Production N2O 5.9 5.0 6.9 -15% +16%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Planned Improvements

Improvement efforts will be focused on obtaining direct 

measurement data from facilities. If they become available, 

cross verification with top-down approaches will provide a 

useful Tier 2 level QC check. Also, additional information 

on the actual performance of the latest catalytic and thermal 

abatement equipment at plants with continuous emission 

monitoring may support the re-evaluation of current default 

abatement values.

4.8. Silicon Carbide Production 

(IPCC Source Category 2B4) and 

Consumption

CO2 and CH4 are emitted from the production of silicon 

carbide (SiC), a material used as an industrial abrasive. 

To make SiC, quartz (SiO2) is reacted with C in the form 

of petroleum coke. A portion (about 35 percent) of the C 

contained in the petroleum coke is retained in the SiC. The 

remaining C is emitted as CO2, CH4, or CO.

CO2 is also emitted from the consumption of SiC for 

metallurgical and other non-abrasive applications. The USGS 

reports that a portion (approximately 50 percent) of SiC is 

used in metallurgical and other non-abrasive applications, 

primarily in iron and steel production (USGS 2005a).

CO2 from SiC production and consumption in 2006 

were 0.2 Tg CO2 Eq. (207 Gg). Approximately 44 percent 

of these emissions resulted from SiC production while the 

remainder result from SiC consumption. CH4 emissions from 

SiC production in 2006 were 0.01 Tg CO2 Eq. CH4 (0.4 Gg) 

(see Table 4-29 and Table 4-30).

Methodology

Emissions of CO2 and CH4 from the production of SiC 

were calculated by multiplying annual SiC production by 

the emission factors (2.62 metric tons CO2/metric ton SiC 

for CO2 and 11.6 kg CH4/metric ton SiC for CH4) provided 

by the 2006 IPCC Guidelines for National Greenhouse Gas 

Inventories (IPCC 2006).

Emissions of CO2 from silicon carbide consumption 

were calculated by multiplying the annual SiC consumption 

(production plus net imports) by the percent used in 

metallurgical and other non-abrasive uses (50 percent) 

(USGS 2005a). The total SiC consumed in metallurgical and 

other non-abrasive uses was multiplied by the C content of 

SiC (31.5 percent), which was determined according to the 

molecular weight ratio of SiC.

Production data for 1990 through 2005 were obtained 

from the Minerals Yearbook: Manufactured Abrasives 

(USGS 1991a through 2005a, 2006). Production data for 

2006 were obtained from a personal communication with 

the USGS Minerals Commodity Specialist (Corathers 2007). 

Silicon carbide consumption by major end use was obtained 

from the Minerals Yearbook: Silicon (USGS 1991b through 

2005b) (see Table 4-31) for years 1990 through 2004 and 

from the USGS Minerals Commodity Specialist for 2005 

and 2006 (Corathers 2006, 2007). Net imports for the entire 

time series were obtained from the U.S. Census Bureau 

(2005 through 2007).

Table 4-29: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg CO2 Eq.)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 0.4 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2

CH4 + + + + + + + + +

Total 0.4 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.

Table 4-30: CO2 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 375 329 248 199 183 202 224 219 207

CH4 1 1 1 + + + + + +

+ Does not exceed 0.5 Gg.
Industrial Processes 4-23

Uncertainty

There is uncertainty associated with the emission factors 

used because they are based on stoichiometry as opposed to 

monitoring of actual SiC production plants. An alternative 

would be to calculate emissions based on the quantity 

of petroleum coke used during the production process 

rather than on the amount of silicon carbide produced. 

However, these data were not available. For CH4, there is 

also uncertainty associated with the hydrogen-containing 

volatile compounds in the petroleum coke (IPCC 2006). 

There is also some uncertainty associated with production, 

net imports, and consumption data as well as the percent of 

total consumption that is attributed to metallurgical and other 

non-abrasive uses.

The results of the Tier 2 quantitative uncertainty 

analysis are summarized in Table 4-32. Silicon carbide 

production and consumption CO2 emissions were estimated 

to be between 10 percent below and 10 percent above the 

emission estimate of 0.2 Tg CO2 Eq. at the 95 percent 

confidence level. Silicon carbide production CH4 emissions 

were estimated to be between 9 percent below and 10 

percent above the emission estimate of 0.01 Tg CO2 Eq. at 

the 95 percent confidence level.

Planned Improvements

Future improvements to the carbide production source 

category include continued research to determine if calcium 

carbide production and consumption data are available for 

the United States. If these data are available, calcium carbide 

emission estimates will be included in this source category.

4.9. Petrochemical Production 

(IPCC Source Category 2B5)

The production of some petrochemicals results in 

the release of small amounts of CH4 and CO2 emissions. 

Petrochemicals are chemicals isolated or derived from 

petroleum or natural gas. CH4 emissions are presented 

here from the production of C black, ethylene, ethylene 

dichloride, and methanol, while CO2 emissions are presented 

here for only C black production. The CO2 emissions from 

petrochemical processes other than C black are currently 

included in the Carbon Stored in Products from Non-Energy 

Uses of Fossil Fuels section of the Energy chapter. The CO2

from C black production is included here to allow for the 

direct reporting of CO2 emissions from the process and direct 

accounting of the feedstocks used in the process.

C black is an intensely black powder generated by 

the incomplete combustion of an aromatic petroleum or 

coal-based feedstock. Most C black produced in the United 

States is added to rubber to impart strength and abrasion 

resistance, and the tire industry is by far the largest consumer. 

Ethylene is consumed in the production processes of the 

plastics industry including polymers such as high, low, and 

Table 4-31: Production and Consumption of Silicon 

Carbide (Metric Tons)

Year Production Consumption

1990 105,000 172,464

1995 75,400 227,397

2000 45,000 225,280

2001 40,000 162,142

2002 30,000 180,956

2003 35,000 191,289

2004 35,000 229,692

2005 35,000 220,150

2006 35,000 199,938

Table 4-32: Tier 2 Quantitative Uncertainty Estimates for CH4 and CO2 Emissions from Silicon Carbide Production 

and Consumption (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Silicon Carbide Production 

and Consumption CO2 0.2 0.2 0.2 -10% +10%

Silicon Carbide Production 

and Consumption CH4 + + + -9% +10%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

+ Does not exceed 0.05 Tg CO2 Eq. or 0.5 Gg.
4-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

linear low density polyethylene (HDPE, LDPE, LLDPE), 

polyvinyl chloride (PVC), ethylene dichloride, ethylene 

oxide, and ethylbenzene. Ethylene dichloride is one of the 

first manufactured chlorinated hydrocarbons with reported 

production as early as 1795. In addition to being an important 

intermediate in the synthesis of chlorinated hydrocarbons, 

ethylene dichloride is used as an industrial solvent and as a 

fuel additive. Methanol is an alternative transportation fuel 

as well as a principle ingredient in windshield wiper fluid, 

paints, solvents, refrigerants, and disinfectants. In addition, 

methanol-based acetic acid is used in making PET plastics 

and polyester fibers.

Emissions of CO2 and CH4 from petrochemical 

production in 2006 were 2.6 Tg CO2 Eq. (2,573 Gg) and 1.0 

Tg CO2 Eq. (48 Gg), respectively (see Table 4-33 and Table 

4-34), totaling 3.6 Tg CO2 Eq. Emissions of CO2 from C 

black production decreased from 2.8 Tg CO2 Eq. (2,805 Gg) 

in 2005 to 2.6 Tg CO2 Eq. (2,573 Gg) in 2006 . There has been 

an overall increase in CO2 emissions from C black production 

of 16 percent since 1990. CH4 emissions from petrochemical 

production decreased by less than 1 percent from the previous 

year and increased 16 percent since 1990.

Methodology

Emissions of CH4 were calculated by multiplying 

annual estimates of chemical production by the appropriate 

emission factor, as follows: 11 kg CH4/metric ton C black, 1 

kg CH4/metric ton ethylene, 0.4 kg CH4/metric ton ethylene 

dichloride,11 and 2 kg CH4/metric ton methanol. Although 

the production of other chemicals may also result in CH4

11The 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).

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 4-35) were obtained 

from the Chemical Manufacturer’s Association Statistical 

Handbook (CMA 1999). Production data for 1991 through 

2006 were obtained from the American Chemistry Council’s 

Guide to the Business of Chemistry (ACC 2002, 2003, 

2005 through 2007) and the International Carbon Black 

Association (Johnson 2003, 2005 through 2007).

Almost all C black in the United States is produced 

from petroleum-based or coal-based feedstocks using the 

“furnace black” process (European IPPC Bureau 2004). 

The furnace black process is a partial combustion process 

in which a portion of the C black feedstock is combusted 

to provide energy to the process. C black is also produced 

in the United States by the thermal cracking of acetylenecontaining feedstocks (“acetylene black process”) and by 

the thermal cracking of other hydrocarbons (“thermal black 

process”). One U.S. C black plant produces C black using the 

thermal black process, and one U.S. C black plant produces 

C black using the acetylene black process (The Innovation 

Group 2004).

The furnace black process produces C black from “C 

black feedstock” (also referred to as “C black oil”), which 

is a heavy aromatic oil that may be derived as a byproduct 

of either the petroleum refining process or the metallurgical 

(coal) coke production process. For the production of both 

Table 4-33: CO2 and CH4 Emissions from Petrochemical Production (Tg CO2 Eq.)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 2.2 2.8 3.0 2.8 2.9 2.8 2.9 2.8 2.6

CH4 0.9 1.1 1.2 1.1 1.1 1.1 1.2 1.1 1.0

Total 3.1 3.8 4.2 3.9 4.0 3.9 4.1 4.0 3.6

Table 4-34: CO2 and CH4 Emissions from Petrochemical Production (Gg)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 2,221 2,750 3,004 2,787 2,857 2,777 2,895 2,804 2,573

CH4 41 52 58 51 52 51 55 51 48
Industrial Processes 4-25

petroleum-derived and coal-derived C black, the “primary 

feedstock” (i.e., C black feedstock) is injected into a furnace 

that is heated by a “secondary feedstock” (generally natural 

gas). Both the natural gas secondary feedstock and a portion 

of the C black feedstock are oxidized to provide heat to the 

production process and pyrolyze the remaining C black 

feedstock to C black. The “tail gas” from the furnace black 

process contains CO2, carbon monoxide, sulfur compounds, 

CH4, and non-CH4 volatile organic compounds. A portion of 

the tail gas is generally burned for energy recovery to heat 

the downstream C black product dryers. The remaining tail 

gas may also be burned for energy recovery, flared, or vented 

uncontrolled to the atmosphere.

The calculation of the C lost during the production 

process is the basis for determining the amount of CO2

released during the process. The C content of national C 

black production is subtracted from the total amount of C 

contained in primary and secondary C black feedstock to 

find the amount of C lost during the production process. It 

is assumed that the C lost in this process is emitted to the 

atmosphere as either CH4 or CO2. The C content of the CH4

emissions, estimated as described above, is subtracted from 

the total C lost in the process to calculate the amount of C 

emitted as CO2. The total amount of primary and secondary 

C black feedstock consumed in the process (see Table 4-36) 

is estimated using a primary feedstock consumption factor 

and a secondary feedstock consumption factor estimated 

from U.S. Census Bureau (1999 and 2004) data. The 

average C black feedstock consumption factor for U.S. C 

black production is 1.43 metric tons of C black feedstock 

consumed per metric ton of C black produced. The average 

natural gas consumption factor for U.S. C black production is 

341 normal cubic meters of natural gas consumed per metric 

ton of C black produced. The amount of C contained in the 

primary and secondary feedstocks is calculated by applying 

the respective C contents of the feedstocks to the respective 

levels of feedstock consumption (EIA 2003, 2004).

For the purposes of emissions estimation, 100 percent of 

the primary C black feedstock is assumed to be derived from 

petroleum refining byproducts. C black feedstock derived 

from metallurgical (coal) coke production (e.g., creosote 

oil) is also used for C black production; however, no data 

are available concerning the annual consumption of coalderived C black feedstock. C black feedstock derived from 

petroleum refining byproducts is assumed to be 89 percent 

elemental C (Srivastava et al. 1999). It is assumed that 100 

percent of the tail gas produced from the C black production 

process is combusted and that none of the tail gas is vented 

to the atmosphere uncontrolled. The furnace black process 

is assumed to be the only process used for the production of 

C black because of the lack of data concerning the relatively 

small amount of C black produced using the acetylene black 

and thermal black processes. The C black produced from the 

furnace black process is assumed to be 97 percent elemental 

C (Othmer et al. 1992).

Uncertainty

The CH4 emission factors used for petrochemical 

production are based on a limited number of studies. Using 

plant-specific factors instead of average factors could increase 

the accuracy of the emission estimates; however, such data 

were not available. There may also be other significant 

Table 4-35: Production of Selected Petrochemicals (Thousand Metric Tons)

Chemical 1990 1995 2000 2001 2002 2003 2004 2005 2006

Carbon Black 1,307 1,619 1,769 1,641 1,682 1,635 1,705 1,651 1,515

Ethylene 16,542 21,215 24,971 22,521 23,623 22,957 25,660 23,954 25,000

Ethylene Dichloride 6,282 7,829 9,866 9,294 9,288 9,952 12,111 11,261 9,737

Methanol 3,785 4,992 4,876 3,402 3,289 3,166 2,937 2,336 1,123

Table 4-36: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock) 

Consumption (Thousand Metric Tons)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Primary Feedstock 1,864 2,308 2,521 2,339 2,398 2,331 2,430 2,353 2,159

Secondary Feedstock 302 374 408 379 388 377 393 381 350
4-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

sources of CH4 arising from petrochemical production 

activities that have not been included in these estimates.

The results of the quantitative uncertainty analysis for 

the CO2 emissions from C black production calculation 

are based on feedstock consumption, import and export 

data, and C black production data. The composition of C 

black feedstock varies depending upon the specific refinery 

production process, and therefore the assumption that C 

black feedstock is 89 percent C gives rise to uncertainty. 

Also, no data are available concerning the consumption of 

coal-derived C black feedstock, so CO2 emissions from the 

utilization of coal-based feedstock are not included in the 

emission estimate. In addition, other data sources indicate 

that the amount of petroleum-based feedstock used in C 

black production may be underreported by the U.S. Census 

Bureau. Finally, the amount of C black produced from the 

thermal black process and acetylene black process, although 

estimated to be a small percentage of the total production, is 

not known. Therefore, there is some uncertainty associated 

with the assumption that all of the C black is produced using 

the furnace black process.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-37. Petrochemical production 

CO2 emissions were estimated to be between 1.7 and 3.6 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates 

a range of approximately 35 percent below to 39 percent 

above the emission estimate of 2.6 Tg CO2 Eq. Petrochemical 

production CH4 emissions were estimated to be between 0.9 

and 1.1 Tg CO2 Eq. at the 95 percent confidence level. This 

indicates a range of approximately 9 percent below to 9 

percent above the emission estimate of 1.0 Tg CO2 Eq.

Recalculations Discussion

Estimates of CO2 from carbon black have been revised 

for 2005 to reflect new production data. The revision resulted 

in a decrease in emissions of less than one percent.

Planned Improvements

Future improvements to the petrochemicals source 

category include research into the use of acrylonitrile in 

the United States, revisions to the C black CH4 and CO2

emission factors, and research into process and feedstock 

data to obtain Tier 2 emission estimates from the production 

of methanol, ethylene, propylene, ethylene dichloride, and 

ethylene oxide.

4.10. Titanium Dioxide Production 

(IPCC Source Category 2B5)

Titanium dioxide (TiO2) is a metal oxide produced from 

titanium ore, and is principally used as a pigment. Titanium 

dioxide is a principal ingredient in white paint, and is also 

used as a pigment in the manufacture of white paper, foods, 

and other products. There are two processes for making TiO2: 

the chloride process and the sulfate process. The chloride 

process uses petroleum coke and chlorine as raw materials 

and emits process-related CO2. The sulfate process does not 

use petroleum coke or other forms of C as a raw material 

and does not emit CO2.

The chloride process is based on the following chemical 

reactions:

Two moles of titanium tetrachloride plus two moles of oxygen 

are converted to two moles of titanium dioxide plus four moles 

of chlorine.

The C in the first chemical reaction is provided by 

petroleum coke, which is oxidized in the presence of the 

chlorine and FeTiO3 (the Ti-containing ore) to form CO2. 

The majority of U.S. TiO2 was produced in the United States 

through the chloride process, and a special grade of petroleum 

coke is manufactured specifically for this purpose.

Emissions of CO2 in 2006 were 1.9 Tg CO2 Eq. (1,876 

Gg), an increase of 7 percent from the previous year and an 

increase of 57 percent since 1990 (Table 4-38).

2 FeTiO3 + 7 Cl2 + 3 C → 2 TiCl4 + 2 FeCl3 + 3 CO2

2 TiCl4 + 2 O2 → 2 TiO2 + 4 Cl2

Table 4-37: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical Production and 

CO2 Emissions from Carbon Black Production (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Petrochemical Production CO2 2.6 1.7 3.6 -35% +39%

Petrochemical Production CH4 1.0 0.9 1.1 -9% +9%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-27

Methodology

Emissions of CO2 from TiO2 production were calculated 

by multiplying annual TiO2 production by chloride-processspecific emission factors.

Data were obtained for the total amount of TiO2

produced each year. For years previous to 2004, it was 

assumed that TiO2 was produced using the chloride process 

and the sulfate process in the same ratio as the ratio of 

the total U.S. production capacity for each process. As 

of 2004, the last remaining sulfate-process plant in the 

United States had closed. As a result, all U.S. current TiO2

production results from the chloride process (USGS 2005). 

An emission factor of 0.4 metric tons C/metric ton TiO2 was 

applied to the estimated chloride-process production. It was 

assumed that all TiO2 produced using the chloride process 

was produced using petroleum coke, although some TiO2

may have been produced with graphite or other C inputs. 

The amount of petroleum coke consumed annually in TiO2

production was calculated based on the assumption that 

petroleum coke used in the process is 90 percent C and 10 

percent inert materials.

The emission factor for the TiO2 chloride process 

was taken from the 2006 IPCC Guidelines for National 

Greenhouse Gas Inventories (IPCC 2006). Titanium dioxide 

production data and the percentage of total TiO2 production 

capacity that is chloride process for 1990 through 2006 (see 

Table 4-39) were obtained from a personal communication 

with Joe Gambogi, USGS Commodity Specialist, of the 

USGS (Gambogi 2007) and through the Minerals Yearbook: 

Titanium Annual Report (USGS 1991 through 2005). 

Percentage chloride-process data were not available for 

1990 through 1993, and data from the 1994 USGS Minerals 

Yearbook were used for these years. Because a sulfateprocess plant closed in September 2001, the chloride-process 

percentage for 2001 was estimated based on a discussion with 

Joseph Gambogi (2002). By 2002, only one sulfate plant 

remained online in the United States and this plant closed 

in 2004 (USGS 2005). The composition data for petroleum 

coke were obtained from Onder and Bagdoyan (1993).

Uncertainty

Although some TiO2 may be produced using graphite or 

other C inputs, information and data regarding these practices 

were not available. Titanium dioxide produced using graphite 

inputs, for example, may generate differing amounts of CO2

per unit of TiO2 produced as compared to that generated 

through the use of petroleum coke in production. While the 

most accurate method to estimate emissions would be to 

base calculations on the amount of reducing agent used in 

each process rather than on the amount of TiO2 produced, 

sufficient data were not available to do so.

Also, annual TiO2 is not reported by USGS by the 

type of production process used (chloride or sulfate). Only 

the percentage of total production capacity by process is 

reported. The percent of total TiO2 production capacity that 

was attributed to the chloride process was multiplied by total 

TiO2 production to estimate the amount of TiO2 produced 

using the chloride process (since, as of 2004, the last 

remaining sulfate-process plant in the United States closed). 

This assumes that the chloride-process plants and sulfateprocess plants operate at the same level of utilization. Finally, 

the emission factor was applied uniformly to all chlorideTable 4-38: CO2 Emissions from Titanium Dioxide 

Production (Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 1.2 1,195

1995 1.5 1,526

2000 1.8 1,752

2001 1.7 1,697

2002 1.8 1,824

2003 1.8 1,839

2004 2.1 2,064

2005 1.8 1,755

2006 1.9 1,876

Table 4-39: Titanium Dioxide Production 

(Gg)

Year Gg

1990 979

1995 1,250

2000 1,400

2001 1,330

2002 1,410

2003 1,420

2004 1,540

2005 1,310

2006 1,400
4-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

process production, and no data were available to account 

for differences in production efficiency among chlorideprocess plants. In calculating the amount of petroleum coke 

consumed in chloride-process TiO2 production, literature 

data were used for petroleum coke composition. Certain 

grades of petroleum coke are manufactured specifically for 

use in the TiO2 chloride process; however, this composition 

information was not available.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-40. Titanium dioxide consumption 

CO2 emissions were estimated to be between 1.7 and 2.1 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates 

a range of approximately 12 percent below and 13 percent 

above the emission estimate of 1.9 Tg CO2 Eq.

Recalculations Discussion

Estimates of CO2 emissions from titanium dioxide 

production were updated to reflect a revised chloride-process 

emission factor provided by the 2006 IPCC Guidelines for 

National Greenhouse Gas Inventories (IPCC 2006). The 

change in emission factor resulted in a decrease in emissions 

of 8.6 percent for each year in the time series.

Planned Improvements

Future improvements to TiO2 production methodology 

include researching the significance of titanium-slag 

production in electric furnaces and synthetic-rutile 

production using the Becher process in the United States. 

Significant use of these production processes will be included 

in future estimates.

4.11. Carbon Dioxide Consumption 

(IPCC Source Category 2B5)

CO2 is used for a variety of commercial applications, 

including food processing, chemical production, carbonated 

beverage production, and refrigeration, and is also used in 

petroleum production for enhanced oil recovery (EOR). CO2

used for EOR is injected into the underground reservoirs to 

increase the reservoir pressure to enable additional petroleum 

to be produced.

For the most part, CO2 used in non-EOR applications will 

eventually be released to the atmosphere, and for the purposes 

of this analysis CO2 used in commercial applications other 

than EOR is assumed to be emitted to the atmosphere. CO2

used in EOR applications is discussed in the Energy Chapter 

under “Carbon Capture and Storage, including Enhanced Oil 

Recovery” and is not discussed in this section.

CO2 is produced from naturally occurring CO2

reservoirs, as a byproduct from the energy and industrial 

production processes (e.g., ammonia production, fossil 

fuel combustion, ethanol production), and as a byproduct 

from the production of crude oil and natural gas, which 

contain naturally occurring CO2 as a component. Only CO2

produced from naturally occurring CO2 reservoirs and used 

in industrial applications other than EOR is included in this 

analysis. Neither byproduct CO2 generated from energy 

nor industrial production processes nor CO2 separated from 

crude oil and natural gas are included in this analysis for 

a number of reasons. CO2 captured from biogenic sources 

(e.g., ethanol production plants) is not included in the 

inventory. CO2 captured from crude oil and gas production 

is used in EOR applications and is therefore reported in 

the Energy Chapter. Any CO2 captured from industrial or 

energy production processes (e.g., ammonia plants, fossil fuel 

combustion) and used in non-EOR applications is assumed to 

be emitted to the atmosphere. The CO2 emissions from such 

capture and use are therefore accounted for under Ammonia 

Production, Fossil Fuel Combustion, or other appropriate 

source category.

CO2 is produced as a byproduct of crude oil and natural 

gas production. This CO2 is separated from the crude oil and 

Table 4-40: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Titanium Dioxide Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Titanium Dioxide 

Production CO2 1.9 1.7 2.1 -12% +13%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-29

natural gas using gas processing equipment, and may be 

emitted directly to the atmosphere, or captured and reinjected 

into underground formations, used for EOR, or sold for other 

commercial uses. A further discussion of CO2 used in EOR 

is described in the Energy Chapter under “Box 3-3 Carbon 

Dioxide Transport, Injection, and Geological Storage.” The 

only CO2 consumption that is accounted for in this analysis 

is CO2 produced from naturally-occurring CO2 reservoirs that 

is used in commercial applications other than EOR.

There are currently two facilities, one in Mississippi and 

one in New Mexico, producing CO2 from naturally occurring 

CO2 reservoirs for use in both EOR and in other commercial 

applications (e.g., chemical manufacturing, food production). 

There are other naturally occurring CO2 reservoirs, mostly 

located in the western U.S. facilities are producing CO2 from 

these natural reservoirs, but they are only producing CO2 for 

EOR applications, not for other commercial applications 

(Allis et al. 2000). CO2 production from these facilities is 

discussed in the Energy Chapter.

In 2006, the amount of CO2 produced by the Mississippi 

and New Mexico facilities for commercial applications and 

subsequently emitted to the atmosphere were 1.6 Tg CO2

Eq. (1,579 Gg) (see Table 4-41). This amount represents 

an increase of 17.9 percent from the previous year and 

an increase of 9.9 percent from emissions in 1990. This 

increase was due to an in increase in production at the 

Mississippi facility, despite the decrease in the percent of 

the facility’s total reported production that was used for 

commercial applications.

Methodology

CO2 emission estimates for 1990 through 2006 were 

based on production data for the two facilities currently 

producing CO2 from naturally-occurring CO2 reservoirs for 

use in non-EOR applications. Some of the CO2 produced 

by these facilities is used for EOR and some is used in other 

commercial applications (e.g., chemical manufacturing, 

food production). It is assumed that 100 percent of the CO2

production used in commercial applications other than EOR 

is eventually released into the atmosphere.

CO2 production data for the Jackson Dome, Mississippi 

facility and the percentage of total production that was used 

for EOR and in non-EOR applications were obtained from 

the Advanced Resources Institute (ARI 2006, 2007) for 

1990 to 2000 and from the Annual Reports for Denbury 

Resources (Denbury Resources 2002 through 2007) for 

2001 to 2006 (see Table 4-42). Denbury Resources reported 

the average CO2 production in units of MMCF CO2 per day 

Table 4-42: CO2 Production (Gg CO2) and the Percent Used for Non-EOR Applications for Jackson Dome and 

Bravo Dome

Year

Jackson Dome CO2

Production (Gg)

Jackson Dome % Used 

for Non-EOR

Bravo Dome CO2

Production (Gg)

Bravo Dome % Used 

for Non-EOR

1990 1,353 100% 6,301 1%

1995 1,353 100% 6,862 1%

2000 1,353 100% 6,834 1%

2001 1,624 47% 6,627 1%

2002 2,010 46% 6,420 1%

2003 3,286 38% 6,213 1%

2004 4,214 27% 6,006 1%

2005 4,678 27% 5,799 1%

2006 7,615 20% 5,613 1%

Table 4-41: CO2 Emissions from CO2 Consumption 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 1.4 1,416

1995 1.4 1,422

2000 1.4 1,421

2001 0.8 829

2002 1.0 989

2003 1.3 1,311

2004 1.2 1,198

2005 1.3 1,321

2006 1.6 1,579
4-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

for 2001 through 2006 and reported the percentage of the 

total average annual production that was used for EOR. CO2

production data for the Bravo Dome, New Mexico facility 

were obtained from the Advanced Resources International, 

Inc. (ARI 2006, 2007).

Uncertainty

Uncertainty is associated with the number of facilities 

that are currently producing CO2 from naturally occurring 

CO2 reservoirs for commercial uses other than EOR, and for 

which the CO2 emissions are not accounted for elsewhere. 

Research indicates that there are only two such facilities, 

which are in New Mexico and Mississippi; however, 

additional facilities may exist that have not been identified. In 

addition, it is possible that CO2 recovery exists in particular 

production and end-use sectors that are not accounted for 

elsewhere. Such recovery may or may not affect the overall 

estimate of CO2 emissions from that sector depending upon 

the end use to which the recovered CO2 is applied. Further 

research is required to determine whether CO2 is being 

recovered from other facilities for application to end uses 

that are not accounted for elsewhere.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-43. CO2 consumption CO2

emissions were estimated to be between 1.3 and 2.0 Tg CO2

Eq. at the 95 percent confidence level. This indicates a range 

of approximately 21 percent below to 26 percent above the 

emission estimate of 1.6 Tg CO2 Eq.

Recalculations Discussion

Data for total Bravo Dome CO2 production were 

updated for the entire time series based on new production 

data from the facility. These changes resulted in an average 

annual emission increase of less than one percent for 1990 

through 2005.

4.12. Phosphoric Acid Production 

(IPCC Source Category 2B5)

Phosphoric acid (H3PO4) is a basic raw material in the 

production of phosphate-based fertilizers. Phosphate rock 

is mined in Florida, North Carolina, Idaho, Utah, and other 

areas of the United States and is used primarily as a raw 

material for phosphoric acid production. The production of 

phosphoric acid from phosphate rock produces byproduct 

gypsum (CaSO4-2H2O), referred to as phosphogypsum.

The composition of natural phosphate rock varies 

depending upon the location where it is mined. Natural 

phosphate rock mined in the United States generally contains 

inorganic C in the form of calcium carbonate (limestone) and 

also may contain organic C. The chemical composition of 

phosphate rock (francolite) mined in Florida is:

Calcium subscript 10 subtract x subtract y Sodium subscript x Magnesium subscript y begin 

parentheses phosphate end parentheses subscript six minus x begin parentheses carbonate end 

parentheses subscript x fluorine subscript 2 plus 0.4 x.

The calcium carbonate component of the phosphate rock 

is integral to the phosphate rock chemistry. Phosphate rock 

can also contain organic C that is physically incorporated 

into the mined rock but is not an integral component of the 

phosphate rock chemistry. Phosphoric acid production from 

natural phosphate rock is a source of CO2 emissions, due to 

the chemical reaction of the inorganic C (calcium carbonate) 

component of the phosphate rock.

The phosphoric acid production process involves 

chemical reaction of the calcium phosphate (Ca3(PO4)2) 

component of the phosphate rock with sulfuric acid (H2SO4) 

and recirculated phosphoric acid (H3PO4) (EFMA 2000). The 

primary chemical reactions for the production of phosphoric 

acid from phosphate rock are:

One mole of calcium phosphate plus four moles of phosphoric acid are 

converted to three moles of monocalcium phosphate.

Three moles of monocalcium phosphate plus three moles of sulfuric acid 

plus six moles of water are converted to three moles of hydrated calcium 

sulfate plus six moles of phosphoric acid.

Ca10-x-y Nax Mgy (PO4)6-x(CO3)xF2+0.4x

Ca3(PO4)2 + 4H3PO4 → 3Ca(H2PO4)2

3Ca(H2PO4)2 + 3H2SO4 + 6H2O →

3CaSO4 • 6H2O + 6H3PO4

Table 4-43: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from CO2 Consumption 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

CO2 Consumption CO2 1.6 1.3 2.0 -21% +26%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-31

The limestone (CaCO3) component of the phosphate rock 

reacts with the sulfuric acid in the phosphoric acid production 

process to produce calcium sulfate (phosphogypsum) and 

CO2. The chemical reaction for the limestone-sulfuric acid 

reaction is:

One mole of limestone plus one mole of sulfuric acid plus one mole of water are converted to one 

mole of hydrated calcium sulfate plus one mole of carbon dioxide.

Total marketable phosphate rock production in 2006 

was 30.1 million metric tons. Approximately 87 percent of 

domestic phosphate rock production was mined in Florida 

and North Carolina, while approximately 13 percent of 

production was mined in Idaho and Utah. In addition, 2.4 

million metric tons of crude phosphate rock was imported for 

consumption in 2006. Marketable phosphate rock production, 

including domestic production and imports for consumption, 

decreased by approximately 16 percent between 2005 and 

2006. However, over the 1990 to 2006 period, production 

has decreased by 26 percent. Total CO2 emissions from 

phosphoric acid production were 1.2 Tg CO2 Eq. (1,167 Gg) 

in 2006 (see Table 4-44).

Methodology

CO2 emissions from production of phosphoric acid from 

phosphate rock are calculated by multiplying the average 

amount of calcium carbonate contained in the natural 

phosphate rock by the amount of phosphate rock that is used 

annually to produce phosphoric acid, accounting for domestic 

production and net imports for consumption.

The CO2 emissions calculation methodology is based 

on the assumption that all of the inorganic C (calcium 

carbonate) content of the phosphate rock reacts to CO2 in 

the phosphoric acid production process and is emitted with 

the stack gas. The methodology also assumes that none of 

the organic C content of the phosphate rock is converted 

to CO2 and that all of the organic C content remains in the 

phosphoric acid product.

From 1993 to 2004, the USGS Mineral Yearbook: 

Phosphate Rock disaggregated phosphate rock mined 

annually in Florida and North Carolina from phosphate 

rock mined annually in Idaho and Utah, and reported the 

annual amounts of phosphate rock exported and imported 

for consumption (see Table 4-45). For the years 1990, 1991, 

1992, 2005, and 2006 only nationally aggregated mining data 

was reported by USGS. For these years, the breakdown of 

phosphate rock mined in Florida and North Carolina, and the 

amount mined in Idaho and Utah, are approximated using 

1993 to 2004 data. Data for domestic production of phosphate 

rock, exports of phosphate rock, and imports of phosphate 

rock for consumption for 1990 through 2006 were obtained 

from USGS Mineral Yearbook: Phosphate Rock (USGS 

1994 through 2007. From 2004–2006, the USGS reported 

no exports of phosphate rock from U.S. producers (USGS 

2005 through 2007).

CaCO3 + H2SO4 + H2O → CaSO4 • 2H2O + CO2

Table 4-44: CO2 Emissions from Phosphoric Acid 

Production (Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 1.5 1,529

1995 1.5 1,513

2000 1.4 1,382

2001 1.3 1,264

2002 1.3 1,338

2003 1.4 1,382

2004 1.4 1,395

2005 1.4 1,383

2006 1.2 1,167

Table 4-45: Phosphate Rock Domestic Production, Exports, and Imports (Gg)

Location/Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

U.S. Productiona 49,800 43,720 37,370 32,830 34,720 36,410 36,530 36,000 30,100

FL & NC 42,494 38,100 31,900 28,100 29,800 31,300 31,600 31,140 26,037

ID & UT 7,306 5,620 5,470 4,730 4,920 5,110 4,930 4,860 4,064

Exports—FL & NC 6,240 2,760 299 9 62 64 - - -

Imports—Morocco 451 1,800 1,930 2,500 2,700 2,400 2,500 2,630 2,420

Total U.S. Consumption 44,011 42,760 39,001 35,321 37,358 38,746 39,030 38,630 32,520

a

 USGS does not disaggregate production data regionally (FL & NC and ID & UT) for 1990 and 2006. Data for those years are estimated based on the 

remaining time series distribution.

- Assumed equal to zero.
4-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

The carbonate content of phosphate rock varies 

depending upon where the material is mined. Composition 

data for domestically mined and imported phosphate rock 

were provided by the Florida Institute of Phosphate Research 

(FIPR 2003). Phosphate rock mined in Florida contains 

approximately 1 percent inorganic C, and phosphate rock 

imported from Morocco contains approximately 1.46 percent 

inorganic C. Calcined phosphate rock mined in North 

Carolina and Idaho contains approximately 0.41 percent and 

0.27 percent inorganic C, respectively (see Table 4-46).

Carbonate content data for phosphate rock mined 

in Florida are used to calculate the CO2 emissions from 

consumption of phosphate rock mined in Florida and North 

Carolina (87 percent of domestic production) and carbonate 

content data for phosphate rock mined in Morocco are used 

to calculate CO2 emissions from consumption of imported 

phosphate rock. The CO2 emissions calculation is based 

on the assumption that all of the domestic production of 

phosphate rock is used in uncalcined form. At last reporting, 

the USGS noted that one phosphate rock producer in Idaho 

produces calcined phosphate rock; however, no production 

data were available for this single producer (USGS 2006). 

Carbonate content data for uncalcined phosphate rock mined 

in Idaho and Utah (13 percent of domestic production) were 

not available, and carbonate content was therefore estimated 

from the carbonate content data for calcined phosphate rock 

mined in Idaho.

Uncertainty

Phosphate rock production data used in the emission 

calculations were developed by the USGS through monthly 

and semiannual voluntary surveys of the active phosphate 

rock mines during 2006. For previous years in the time 

series, USGS provided the data disaggregated regionally; 

however, for 2006 only total U.S. phosphate rock production 

were reported. Regional production for 2006 was estimated 

based on regional production data from previous years and 

multiplied by regionally-specific emission factors. There is 

uncertainty associated with the degree to which the estimated 

2006 regional production data represents actual production 

in those regions. Total U.S. phosphate rock production data 

are not considered to be a significant source of uncertainty 

because all the domestic phosphate rock producers report 

their annual production to the USGS. Data for imports for 

consumption and exports of phosphate rock used in the 

emission calculation are based on international trade data 

collected by the U.S. Census Bureau. These U.S. government 

economic data are not considered to be a significant source 

of uncertainty.

An additional source of uncertainty in the calculation 

of CO2 emissions from phosphoric acid production is the 

carbonate composition of phosphate rock; the composition 

of phosphate rock varies depending upon where the material 

is mined, and may also vary over time. Another source of 

uncertainty is the disposition of the organic C content of the 

phosphate rock. A representative of the FIPR indicated that 

in the phosphoric acid production process, the organic C 

content of the mined phosphate rock generally remains in the 

phosphoric acid product, which is what produces the color 

of the phosphoric acid product (FIPR 2003a). Organic C is 

therefore not included in the calculation of CO2 emissions 

from phosphoric acid production.

Table 4-46: Chemical Composition of Phosphate Rock (percent by weight)

Composition Central Florida North Florida

North Carolina 

(calcined)

Idaho 

(calcined) Morocco

Total Carbon (as C) 1.60 1.76 0.76 0.60 1.56

Inorganic Carbon (as C) 1.00 0.93 0.41 0.27 1.46

Organic Carbon (as C) 0.60 0.83 0.35 - 0.10

Inorganic Carbon (as CO2) 3.67 3.43 1.50 1.00 5.00

Source: FIPR 2003

- Assumed equal to zero. 
Industrial Processes 4-33

A third source of uncertainty is the assumption that all 

domestically-produced phosphate rock is used in phosphoric 

acid production and used without first being calcined. 

Calcination of the phosphate rock would result in conversion 

of some of the organic C in the phosphate rock into CO2. 

However, according to the USGS, only one producer in 

Idaho is currently calcining phosphate rock, and no data were 

available concerning the annual production of this single 

producer (USGS 2005). For available years, total production 

of phosphate rock in Utah and Idaho combined amounts to 

approximately 13 percent of total domestic production on 

average (USGS 1994 through 2005).

Finally, USGS indicated that approximately 7 percent 

of domestically-produced phosphate rock is used to produce 

elemental phosphorus and other phosphorus-based chemicals, 

rather than phosphoric acid (USGS 2006). According to 

USGS, there is only one domestic producer of elemental 

phosphorus, in Idaho, and no data were available concerning 

the annual production of this single producer. Elemental 

phosphorus is produced by reducing phosphate rock with 

coal coke, and it is therefore assumed that 100 percent of the 

carbonate content of the phosphate rock will be converted to 

CO2 in the elemental phosphorus production process. The 

calculation for CO2 emissions is based on the assumption 

that phosphate rock consumption, for purposes other than 

phosphoric acid production, results in CO2 emissions from 

100 percent of the inorganic C content in phosphate rock, 

but none from the organic C content.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-47. Phosphoric acid production 

CO2 emissions were estimated to be between 1.0 and 1.4 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates 

a range of approximately 18 percent below and 19 percent 

above the emission estimate of 1.2 Tg CO2 Eq.

Planned Improvements

Currently, data sources for the carbonate content of the 

phosphate rock are limited. If additional data sources are found, 

this information will be incorporated into future estimates.

4.13. Iron and Steel Production 

(IPCC Source Category 2C1)

In addition to being an energy intensive process, the 

production of iron and steel also generates process-related 

emissions of CO2 and CH4. Iron is produced by first reducing 

iron oxide (iron ore) with metallurgical coke in a blast 

furnace to produce pig iron (impure or crude iron containing 

about 3 to 5 percent C by weight). Metallurgical coke is 

manufactured using coking coal as a raw material. Iron may 

be introduced into the blast furnace in the form of raw iron 

ore, pellets, briquettes, or sinter. Pig iron is used as a raw 

material in the production of steel, which contains about 4 

percent C by weight. Pig iron is also used as a raw material 

in the production of iron products in foundries. The pig iron 

production process produces CO2 emissions and fugitive 

CH4 emissions.

The production of metallurgical coke from coking coal and 

the consumption of the metallurgical coke used as a reducing 

agent in the blast furnace are considered in the inventory to 

be non-energy (industrial) processes, not energy (combustion) 

processes. Metallurgical coke is produced by heating coking 

coal in a coke oven in a low-oxygen environment. The process 

drives off the volatile components of the coking coal and 

produces coal (metallurgical) coke. Coke oven gas and coal 

tar are C containing byproducts 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 

Table 4-47: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Phosphoric Acid Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Phosphoric Acid Production CO2 1.2 1.0 1.4 -18% +19%

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: 1990–2006

anodes used for primary aluminum production and other 

electrolytic processes, and also used in the production of other 

coal tar products. The coke production process produces CO2

emissions and fugitive CH4 emissions.

Sintering is a thermal process by which fine iron-bearing 

particles, such as air emission control system dust, are baked, 

which causes the material to agglomerate into roughly oneinch pellets that are then recharged into the blast furnace for 

pig iron production. Iron ore particles may also be formed 

into larger pellets or briquettes by mechanical means, and 

then agglomerated by heating prior to being charged into the 

blast furnace. The sintering process produces CO2 emissions 

and fugitive CH4 emissions.

The metallurgical coke is a reducing agent in the blast 

furnace. CO2 is produced as the metallurgical coke used in the 

blast furnace process is oxidized and the iron ore is reduced. 

Steel is produced from pig iron in a variety of specialized 

steel-making furnaces. The majority of CO2 emissions from 

the iron and steel process come from the use of coke in the 

production of pig iron, with smaller amounts evolving from 

the removal of C from pig iron used to produce steel. Some 

C is also stored in the finished iron and steel products.

Emissions of CO2 and CH4 from iron and steel 

production in 2006 were 49.1 Tg CO2 Eq. (49,119 Gg) and 

0.9 Tg CO2 Eq. (45 Gg), respectively (see Table 4-48 and 

Table 4-49), totaling 50.1 Tg CO2 Eq. Emissions increased 

in 2006 after declining steadily from 1990 to 2005 due to 

restructuring of the industry, technological improvements, 

and increased scrap utilization. Interannual fluctuations in 

CO2 emissions per unit of steel produced result, in part, 

because iron and steel emission estimates include emissions 

associated with producing metallurgical coke. Metallurgical 

coke emissions are included here because metallurgical coke 

is primarily used to produce iron and steel; however, some 

amounts are also used to produce other metals (e.g., lead, 

zinc). In 2006, domestic production of pig iron increased 

by 1.8 percent and coal coke production decreased by 1.9 

percent. Overall, domestic pig iron and coke production have 

declined since the 1990s. Pig iron production in 2006 was 

21 percent lower than in 2000 and 23 percent below 1990 

levels. Coke production in 2006 was 21 percent lower than 

in 2000 and 41 percent below 1990 levels. Overall, emissions 

from iron and steel productions have declined by 43 percent 

(37.4 Tg CO2 Eq.) from 1990 to 2006.

Methodology

Coking coal is used to manufacture metallurgical 

(coal) coke that is used primarily as a reducing agent in the 

production of iron and steel, but is also used in the production 

of other metals including lead and zinc (see Lead Production 

and Zinc Production in this chapter). Emissions associated 

with producing metallurgical coke from coking coal are 

estimated, and then attributed to the iron and steel sector. To 

estimate emission from coke produced from coking coal the 

amount of C contained in coke (calculated by multiplying 

the amount of C contained in coke by the amount of coke 

produced) is deducted from the amount of C contained in 

the coking coal (calculated by multiplying the C content 

of coking coal by the amount of coking coal consumed). 

The amount of coking coal needed for these production 

processes is deducted from coking coal amounts provided 

in the Energy chapter to avoid double counting. Emissions 

associated with the consumption of coke to produce pig 

iron are also estimated. The C content of the coking coal 

and coke consumed in these processes were estimated by 

Table 4-48: CO2 and CH4 Emissions from Iron and Steel Production (Tg CO2 Eq.)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 86.2 74.7 66.6 59.2 55.9 54.7 52.8 46.6 49.1

CH4 1.3 1.3 1.2 1.1 1.0 1.0 1.0 1.0 0.9

Total 87.5 76.0 67.8 60.3 57.0 55.8 53.8 47.6 50.1

Table 4-49: CO2 and CH4 Emissions from Iron and Steel Production (Gg)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 86,220 74,729 66,609 59,249 55,938 54,744 52,771 46,627 49,119

CH4 63 62 58 51 48 49 50 45 45
Industrial Processes 4-35

multiplying the energy consumption by material specific 

C-content coefficients. The C content coefficients used are 

presented in Annex 2.1.

Emissions from the reuse of scrap steel were also 

estimated by assuming that all the associated C content 

of the scrap steel, which has an associated C content of 

approximately 0.5 percent, are released during the scrap 

re-use process.

Lastly, emissions from C anodes, used during the 

production of steel in electric arc furnaces (EAFs), were also 

estimated. Emissions of CO2 were calculated by multiplying 

the annual production of steel in EAFs by an emission factor 

(4.4 kg CO2/ton steelEAF). It was assumed that the C anodes 

used in the production of steel in EAFs are composed of 

80 percent petroleum coke and 20 percent coal tar pitch 

(DOE 1997). Since coal tar pitch is a byproduct of the coke 

production process and its C-related emissions have already 

been accounted for earlier in the iron and steel emissions 

calculation as part of the process, the emissions were reduced 

by the amount of C in the coal tar pitch used in the anodes 

to avoid double counting.

Emissions associated with the production of coke from 

coking coal, pig iron production, the re-use of scrap steel, 

and the consumption of C anodes during the production of 

steel were summed.

Additionally, the coal tar pitch component of C anodes 

consumed during the production of aluminum is accounted 

for in the aluminum production section of this chapter. The 

emissions were reduced by the amount of coal tar pitch 

used in aluminum production to avoid double counting. 

The amount of coal tar pitch consumed for processes other 

than the aluminum production and as EAF anodes and net 

imports of coal tar were also estimated. A storage factor was 

applied to estimate emissions associated with other coal tar 

pitch consumption and net imports.

C storage was accounted for by assuming that all 

domestically produced steel had a C content of 0.1 percent. 

Furthermore, any pig iron that was not consumed during 

steel production, but fabricated into finished iron products, 

was assumed to have a C content of 4 percent.

The potential CO2 emissions associated with C contained 

in pig iron used for purposes other than iron and steel 

production, stored in the steel product, stored as coal tar, 

and attributed to C anode consumption during aluminum 

production were summed and subtracted from the total 

emissions estimated above.

The production processes for coal coke, sinter, and pig 

iron result in fugitive emissions of CH4, which are emitted 

via leaks in the production equipment rather than through the 

emission stacks or vents of the production plants. The fugitive 

emissions were calculated by applying emission factors taken 

from the 1995 IPCC Guidelines (IPCC/UNEP/OECD/IEA 

1995) (see Table 4-50) to annual domestic production data 

for coal coke, sinter, and pig iron.

Data relating to the amount of coal consumed at 

coke plants, and for the production of coke for domestic 

consumption in blast furnaces, were taken from the Energy 

Information Administration (EIA), Quarterly Coal Report 

October through December (EIA 1998 through 2004a) 

and January through March (EIA 2006a, 2007). Data on 

total coke consumed for pig iron production were taken 

from the American Iron and Steel Institute (AISI), Annual 

Statistical Report (AISI 2001 through 2007). Scrap steel 

consumption data for 1990 through 2005 were obtained 

from Annual Statistical Report (AISI 1995, 2001 through 

2006) (see Table 4-51). Because scrap steel consumption 

data were unavailable for 2006, 2005 data were used. 

Crude steel production, as well as pig iron use for purposes 

other than steel production, was also obtained from Annual 

Statistical Report (AISI 1996, 2001 through 2007). C content 

percentages for pig iron and the CO2 emission factor for C 

anode emissions from steel production were obtained from 

IPCC Good Practice Guidance (IPCC 2000). C content 

percentages for crude steel were taken from USGS (2005a). 

Data on the non-energy use of coking coal were obtained 

from EIA’s Emissions of Greenhouse Gases in the United 

States (EIA 2004b, 2006b). Information on coal tar net 

imports was determined using data from the U.S. Bureau 

of the Census’s U.S. International Trade Commission’s 

Trade Dataweb (U.S. Bureau of the Census 2007). Coal tar 

Table 4-50: CH4 Emission Factors for Coal Coke, 

Sinter, and Pig Iron Production (g/kg)

Material Produced g CH4/kg produced

Coal Coke 0.5

Pig Iron 0.9

Sinter 0.5

Source: IPCC/UNEP/OECD/IEA 1997.
4-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

consumption for aluminum production data was estimated 

based on information gathered by EPA’s Voluntary Aluminum 

Industrial Partnership (VAIP) program and data from USAA 

Primary Aluminum Statistics (USAA 2004, 2005, 2006) (see 

Aluminum Production in this chapter). Annual consumption 

of iron ore used in sinter production for 1990 through 2005 

was obtained from the USGS Iron Ore Yearbook (USGS 

1994 through 2005b). Iron ore consumption for 2006 was 

obtained from the USGS Minerals Commodity Specialist 

(Jorgenson 2007). The CO2 emission factor for C anode 

emissions from aluminum production was taken from the 

Revised 1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA 

1997). Estimates for the composition of C anodes used 

during EAF steel and aluminum production were obtained 

from Energy and Environmental Profile of the U.S. Aluminum 

Industry (DOE 1997).

Uncertainty

The time series data sources for production of coal 

coke, sinter, pig iron, steel, and aluminum upon which 

the calculations are based are assumed to be consistent 

for the entire time series. The estimates of CO2 emissions 

from the production and utilization of coke are based on 

consumption data, average C contents, and the fraction of C 

oxidized. Uncertainty is associated with the total U.S. coke 

consumption and coke consumed for pig iron production. 

These data are provided by different data sources (EIA 

and AISI) and comparisons between the two datasets 

for net imports, production, and consumption identified 

discrepancies; however, the data chosen are considered the 

best available. These data and factors produce a relatively 

accurate estimate of CO2 emissions. However, there are 

uncertainties associated with each of these factors. For 

example, C oxidation factors may vary depending on 

inefficiencies in the combustion process, where varying 

degrees of ash or soot can remain unoxidized.

Simplifying assumptions were made concerning the 

composition of C anodes and the C contents of all pig iron 

and crude steel. It was also assumed that all coal tar used 

during anode production originates as a byproduct of the 

domestic coking process. There is also uncertainty associated 

with the total amount of coal tar products produced and with 

the storage factor for coal tar. Uncertainty surrounding the 

CO2 emission factor for C anode consumption in aluminum 

production was also estimated.

For the purposes of the CH4 calculation it is assumed 

that none of the CH4 is captured in stacks or vents and that 

all of the CH4 escapes as fugitive emissions. Additionally, 

the CO2 emissions calculation is not corrected by subtracting 

the C content of the CH4, which means there may be a slight 

double counting of C as both CO2 and CH4.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-52. Iron and Steel CO2 emissions 

were estimated to be between 40.3 and 56.5 Tg CO2 Eq. at 

the 95 percent confidence level. This indicates a range of 

approximately 18 percent below and 15 percent above the 

emission estimate of 49.1 Tg CO2 Eq. Iron and Steel CH4

emissions were estimated to be between 0.9 Tg CO2 Eq. 

and 1.0 Tg CO2 Eq. at the 95 percent confidence level. This 

indicates a range of approximately 8 percent below and 9 

percent above the emission estimate of 0.9 Tg CO2 Eq.

Table 4-51: Production and Consumption Data for the Calculation of CO2 and CH4 Emissions from Iron and 

Steel Production (Thousand Metric Tons)

Gas/Activity Data 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2

Coal Consumption at Coke Plants 35,269 29,948 26,254 23,655 21,461 21,998 21,473 21,259 20,827

Coke Consumption for Pig Iron 25,043 22,288 19,307 17,236 15,959 15,482 15,068 13,848 14,729

Basic Oxygen Furnace Steel Production 56,216 56,721 53,965 47,359 45,463 45,874 47,714 42,705 42,119

Electric Arc Furnace Steel Production 33,510 38,472 47,860 42,774 46,125 47,804 51,969 52,194 56,071

CH4

Coke Production 25,054 21,545 18,877 17,191 15,221 15,579 15,340 15,167 14,882

Iron Ore Consumption for Sinter 12,239 12,575 10,784 9,234 9,018 8,984 8,047 8,313 7,085

Domestic Pig Iron Production for Steel 49,062 50,233 47,888 42,134 40,226 40,644 42,292 37,222 37,903
Industrial Processes 4-37

Recalculations Discussion

Estimates of CO2 from iron and steel production have 

been revised for the entire time series to reflect a revised 

carbon content for crude steel. This revision resulted in an 

average annual increase in emissions of 2 percent throughout 

the time series.

Planned Improvements

Plans for improvements to the Iron and Steel source 

category are to include methodologies outlined in the 2006 

IPCC Guidelines for National Greenhouse Gas Inventories 

(IPCC 2006). These methodologies involve the inclusion 

of energy- and flux-related emissions in the iron and steel 

emission estimates as well as emissions associated with 

metallurgical coke production, sinter production, pellet 

production, and direct reduced iron ore production in addition 

to iron and steel production.

4.14. Ferroalloy Production (IPCC 

Source Category 2C2)

CO2 and CH4 are emitted from the production of several 

ferroalloys. Ferroalloys are composites of iron and other 

elements such as silicon, manganese, and chromium. When 

incorporated in alloy steels, ferroalloys are used to alter the 

material properties of the steel. Estimates from two types of 

ferrosilicon (25 to 55 percent and 56 to 95 percent silicon), 

silicon metal (about 98 percent silicon), and miscellaneous 

alloys (36 to 65 percent silicon) have been calculated. 

Emissions from the production of ferrochromium and 

ferromanganese are not included here because of the small 

number of manufacturers of these materials in the United 

States. Subsequently, government information disclosure 

rules prevent the publication of production data for these 

production facilities.

Similar to emissions from the production of iron and 

steel, CO2 is emitted when metallurgical coke is oxidized 

during a high-temperature reaction with iron and the selected 

alloying element. Due to the strong reducing environment, 

CO is initially produced, and eventually oxidized to CO2. 

A representative reaction equation for the production of 50 

percent ferrosilicon is given below:

One mole of iron oxide plus two moles of silicon dioxide plus seven moles of carbon are 

converted to two moles of ferrosilicon plus seven moles of carbon monoxide.

While most of the C contained in the process materials 

is released to the atmosphere as CO2, a percentage is also 

released as CH4 and other volatiles. The amount of CH4 that 

is released is dependent on furnace efficiency, operation 

technique, and control technology.

Emissions of CO2 from ferroalloy production in 2006 

were 1.5 Tg CO2 Eq. (1,505 Gg) (see Table 4-53 and Table 

4-54), which is an eight percent increase from the previous 

year and a 30 percent reduction since 1990. Emissions of CH4

from ferroalloy production in 2006 were 0.01 Tg CO2 Eq. 

(0.4 Gg), which is an 11 percent increase from the previous 

year and a 37 percent decrease since 1990.

Fe2O3 + 2 SiO2 + 7C → 2FeSi + 7CO

Table 4-52: Tier 2 Quantitative Uncertainty Estimates for CO2 and CH4 Emissions from Iron and Steel Production 

(Tg. CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Iron and Steel Production CO2 49.1 40.3 56.5 -18% +15%

Iron and Steel Production CH4 0.9 0.9 1.0 -8% +9%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

Table 4-53: CO2 and CH4 Emissions from Ferroalloy Production (Tg CO2 Eq.)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 2.2 2.0 1.9 1.5 1.3 1.3 1.4 1.4 1.5

CH4 + + + + + + + + +

Total 2.2 2.0 1.9 1.5 1.4 1.3 1.4 1.4 1.5

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.
4-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Methodology

Emissions of CO2 and CH4 from ferroalloy production 

were calculated by multiplying annual ferroalloy production 

by material-specific emission factors. Emission factors taken 

from the 2006 IPCC Guidelines for National Greenhouse Gas 

Inventories (IPCC 2006) were applied to ferroalloy production. 

For ferrosilicon alloys containing 25 to 55 percent silicon 

and miscellaneous alloys (including primarily magnesiumferrosilicon, but also including other silicon alloys) containing 

32 to 65 percent silicon, an emission factor for 45 percent 

silicon was applied for CO2 (2.5 metric tons CO2/metric ton of 

alloy produced) and an emission factor for 65 percent silicon 

was applied for CH4 (1 kg CH4/metric ton of alloy produced). 

Additionally, for ferrosilicon alloys containing 56 to 95 percent 

silicon, an emission factor for 75 percent silicon ferrosilicon 

was applied for both CO2 and CH4 (4 metric tons CO2/metric 

ton alloy produced and 1 kg CH4/metric ton of alloy produced, 

respectively). The emission factors for silicon metal equaled 

5 metric tons CO2/metric ton metal produced and 1.2 kg CH4/

metric ton metal produced. It was assumed that 100 percent 

of the ferroalloy production was produced using petroleum 

coke using an electric arc furnace process (IPCC 2006), 

although some ferroalloys may have been produced with 

coking coal, wood, other biomass, or graphite C inputs. The 

amount of petroleum coke consumed in ferroalloy production 

was calculated assuming that the petroleum coke used is 90 

percent C and 10 percent inert material.

Ferroalloy production data for 1990 through 2006 (see 

Table 4-55) were obtained from the USGS through personal 

communications with the USGS Silicon Commodity Specialist 

(Corathers 2007) and through the Minerals Yearbook: Silicon 

Annual Report (USGS 1991 through 2006). Because USGS 

does not provide estimates of silicon metal production for 

2006, 2005 production data are used. Until 1999, the USGS 

reported production of ferrosilicon containing 25 to 55 

percent silicon separately from production of miscellaneous 

alloys containing 32 to 65 percent silicon; beginning in 1999, 

the USGS reported these as a single category (see Table 

4-55). The composition data for petroleum coke was obtained 

from Onder and Bagdoyan (1993).

Uncertainty

Although some ferroalloys may be produced using 

wood or other biomass as a C source, information and data 

regarding these practices were not available. Emissions from 

ferroalloys produced with wood or other biomass would not 

Table 4-55: Production of Ferroalloys (Metric Tons)

Year

Ferrosilicon

25%–55%

Ferrosilicon

56%–95% Silicon Metal

Misc. Alloys

32%–65%

1990 321,385 109,566 145,744 72,442

1995 184,000 128,000 163,000 99,500

2000 229,000 100,000 184,000 NA

2001 167,000 89,000 137,000 NA

2002 156,000 98,600 113,000 NA

2003 115,000 80,500 139,000 NA

2004 120,000 92,300 150,000 NA

2005 123,000 86,100 148,000 NA

2006 164,000 88,700 148,000 NA

NA (Not Available)

Table 4-54: CO2 and CH4 Emissions from Ferroalloy Production (Gg)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 2,152 2,036 1,893 1,459 1,349 1,305 1,419 1,392 1,505

CH4 0.7 0.6 0.5 0.4 0.4 0.4 0.4 0.4 0.4
Industrial Processes 4-39

be counted under this source because wood-based C is of 

biogenic origin.12 Even though emissions from ferroalloys 

produced with coking coal or graphite inputs would be 

counted in national trends, they may be generated with 

varying amounts of CO2 per unit of ferroalloy produced. 

The most accurate method for these estimates would be to 

base calculations on the amount of reducing agent used in 

the process, rather than the amount of ferroalloys produced. 

These data, however, were not available.

Emissions of CH4 from ferroalloy production will 

vary depending on furnace specifics, such as type, 

operation technique, and control technology. Higher heating 

temperatures and techniques such as sprinkle charging 

will reduce CH4 emissions; however, specific furnace 

information was not available or included in the CH4

emission estimates.

Also, annual ferroalloy production is now reported by 

the USGS in three broad categories: ferroalloys containing 

25 to 55 percent silicon (including miscellaneous alloys), 

ferroalloys containing 56 to 95 percent silicon, and silicon 

metal. It was assumed that the IPCC emission factors apply 

to all of the ferroalloy production processes, including 

miscellaneous alloys. Finally, production data for silvery 

pig iron (alloys containing less than 25 percent silicon) are 

not reported by the USGS to avoid disclosing company 

proprietary data. Emissions from this production category, 

therefore, were not estimated.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-56. Ferroalloy production CO2

emissions were estimated to be between 1.3 and 1.7 Tg CO2

Eq. at the 95 percent confidence level. This indicates a range 

of approximately 12 percent below and 12 percent above the 

emission estimate of 1.5 Tg CO2 Eq. Ferroalloy production 

12Emissions and sinks of biogenic carbon are accounted for in the Land 

Use, Land-Use Change, and Forestry chapter.

CH4 emissions were estimated to be between a range of 

approximately 12 percent below and 12 percent above the 

emission estimate of 0.01 Tg CO2 Eq.

Planned Improvements

Future improvements to the ferroalloy production 

source category include research into the data availability 

for ferroalloys other than ferrosilicon and silicon metal. If 

data are available, emissions will be estimated for those 

ferroalloys. Additionally, research will be conducted to 

determine whether data are available concerning raw 

material consumption (e.g., coal coke, limestone and 

dolomite flux, etc.) for inclusion in ferroalloy production 

emission estimates.

4.15. Aluminum Production (IPCC 

Source Category 2C3)

Aluminum is a light-weight, malleable, and corrosionresistant metal that is used in many manufactured products, 

including aircraft, automobiles, bicycles, and kitchen 

utensils. As of last reporting, the United States was the fourth 

largest producer of primary aluminum, with approximately 

eight percent of the world total (USGS 2006). The United 

States was also a major importer of primary aluminum. The 

production of primary aluminum—in addition to consuming 

large quantities of electricity—results in process-related 

emissions of CO2 and two perfluorocarbons (PFCs): 

perfluoromethane (CF4) and perfluoroethane (C2F6).

CO2 is emitted during the aluminum smelting process 

when alumina (aluminum oxide, Al2O3) is reduced to 

aluminum using the Hall-Heroult reduction process. The 

reduction of the alumina occurs through electrolysis in a 

Table 4-56: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Ferroalloy Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Ferroalloy Production CO2 1.5 1.3 1.7 -12% +12%

Ferroalloy Production CH4 + + + -12% +12%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

+ Does not exceed 0.05 Tg CO2 Eq.
4-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

molten bath of natural or synthetic cryolite (Na3AlF6). The 

reduction cells contain a C lining that serves as the cathode. C 

is also contained in the anode, which can be a C mass of paste, 

coke briquettes, or prebaked C blocks from petroleum coke. 

During reduction, most of this C is oxidized and released to 

the atmosphere as CO2.

Process emissions of CO2 from aluminum production 

were estimated to be 3.9 Tg CO2 Eq. (3,923 Gg) in 2006 

(see Table 4-57). The C anodes consumed during aluminum 

production consist of petroleum coke and, to a minor extent, 

coal tar pitch. The petroleum coke portion of the total CO2

process emissions from aluminum production is considered 

to be a non-energy use of petroleum coke, and is accounted 

for here and not under the CO2 from Fossil Fuel Combustion 

source category of the Energy sector. Similarly, the coal tar 

pitch portion of these CO2 process emissions is accounted 

for here rather than in the Iron and Steel source category of 

the Industrial Processes sector.

In addition to CO2 emissions, the aluminum production 

industry is also a source of PFC emissions. During the 

smelting process, when the alumina ore content of the 

electrolytic bath falls below critical levels required for 

electrolysis, rapid voltage increases occur, which are termed 

“anode effects.” These anode effects cause carbon from the 

anode and fluorine from the dissociated molten cryolite bath 

to combine, thereby producing fugitive emissions of CF4

and C2F6. In general, the magnitude of emissions for a given 

level of production depends on the frequency and duration 

of these anode effects. As the frequency and duration of the 

anode effects increase, emissions increase.

Since 1990, emissions of CF4 and C2F6 have both 

declined by 87 percent to 2.1 Tg CO2 Eq. of CF4 (0.4 Gg) and 

0.4 Tg CO2 Eq. of C2F6 (0.04 Gg) in 2006, as shown in Table 

4-58 and Table 4-59. This decline is due both to reductions 

in domestic aluminum production and to actions taken by 

aluminum smelting companies to reduce the frequency and 

duration of anode effects. Since 1990, aluminum production 

has declined by 44 percent, while the average CF4 and C2F6

emission rates (per metric ton of aluminum produced) have 

each been reduced by 76 percent.

In 2006, U.S. primary aluminum production totaled 

approximately 2.3 million metric tons, a slight decrease from 

2005 production levels. Due to high electric power costs in 

various regions of the country, aluminum production has been 

curtailed at several U.S. smelters, which resulted in 2006 

production levels that were approximately 40 percent lower 

Table 4-59: PFC Emissions from Aluminum Production (Gg)

Year CF4 C2F6

1990 2.4 0.3

1995 1.6 0.2

2000 1.2 0.1

2001 0.5 +

2002 0.7 0.1

2003 0.5 0.1

2004 0.4 +

2005 0.4 +

2006 0.3 +

+ Does not exceed 0.05 Gg

Table 4-57: CO2 Emissions from Aluminum Production 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 6.8 6,831

1995 5.7 5,659

2000 6.1 6,086

2001 4.4 4,381

2002 4.5 4,490

2003 4.5 4,503

2004 4.2 4,231

2005 4.2 4,207

2006 3.9 3,923

Table 4-58: PFC Emissions from Aluminum Production 

(Tg CO2 Eq.)

Year CF4 C2F6 Total

1990 15.9 2.7 18.5

1995 10.2 1.7 11.8

2000 7.8 0.8 8.6

2001 3.0 0.4 3.5

2002 4.6 0.7 5.2

2003 3.3 0.5 3.8

2004 2.4 0.4 2.8

2005 2.5 0.4 3.0

2006 2.1 0.4 2.5

Note: Totals may not sum due to independent rounding.
Industrial Processes 4-41

than the levels in 1999, the year with the highest production 

since 1995.

Methodology

CO2 emissions released during aluminum production 

were estimated using the combined application of processspecific emissions estimates modeling with individual 

partner reported data. These estimates are achieved through 

information gathered by EPA’s Voluntary Aluminum 

Industrial Partnership (VAIP) program.

Most of the CO2 emissions released during aluminum 

production occur during the electrolysis reaction of the C 

anode, as described by the following reaction.

Two moles of aluminum oxide plus three moles of Carbon are converted to four moles of aluminum 

and three moles of carbon dioxide.

For prebake smelter technologies, CO2 is also emitted 

during the anode baking process. These emissions can 

account for approximately 10 percent of total process CO2

emissions from prebake smelters. The CO2 emission factor 

employed was estimated from the production of primary 

aluminum metal and the C consumed by the process. 

Emissions vary depending on the specific technology 

used by each plant (e.g., prebake or Søderberg). CO2

process emissions were estimated using the methodology 

recommended by IPCC (2006).

The prebake process specific formula recommended by 

IPCC (2006) accounts for various parameters, including net C 

consumption, and the sulfur, ash, and impurity content of the 

baked anode. For anode baking emissions, process formulas 

account for packing coke consumption, the sulfur and ash 

content of the packing coke, as well as the pitch content and 

weight of baked anodes produced. The Søderberg process 

formula accounts for the weight of paste consumed per metric 

ton of aluminum produced, and pitch properties, including 

sulfur, hydrogen, and ash content.

Through the VAIP, process data have been reported for 

1990, 2000, 2003, 2004, 2005, and 2006. Where available, 

smelter-specific process data reported under the VAIP were 

used; however, if the data were incomplete or unavailable, 

information was supplemented using industry average values 

recommended by IPCC (2006). Smelter-specific CO2 process 

data were provided by 18 of the 23 operating smelters in 

1990 and 2000, by 14 out of 16 operating smelters in 2003 

and 2004, 14 out of 15 operating smelters in 2005, and 12 

out of 13 operating smelters in 2006. For years where CO2

process data were not reported by these companies, estimates 

were developed through linear interpolation, and/or assuming 

industry default values.

In the absence of any smelter specific process data (i.e., 

1 out of 13 in 2006, 1 out of 15 smelters in 2005, and 5 out 

of 23 between 1990 and 2003), CO2 emission estimates were 

estimated using Tier 1 Søderberg and/or Prebake emission 

factors (metric ton of CO2 per metric ton of aluminum 

produced) from IPCC (2006).

Aluminum production data for 12 out of 13 operating 

smelters were reported under the VAIP in 2006. Between 

1990 and 2005, production data were provided by 21 of 

the 23 U.S. smelters that operated during at least part of 

that period. For the non-reporting smelters, production was 

estimated based on the difference between reporting smelters 

and national aluminum production levels (USAA 2006), with 

allocation to specific smelters based on reported production 

capacities (USGS 2002).

PFC emissions from aluminum production were 

estimated using a per-unit production emission factor that 

is expressed as a function of operating parameters (anode 

effect frequency and duration), as follows:

Kilograms of Tetrafluoromethane or Hexafluoroethane divided by one metric ton aluminum are equal 

to the slope coefficient multiplied by anode effect minutes per cell day.

This approach corresponds to either the Tier 3 or the Tier 

2 approach in the 2006 IPCC Guidelines, depending upon 

whether the slope-coefficient is smelter-specific (Tier 3) or 

technology-specific (Tier 2). For 1990 through 2006, smelterspecific slope coefficients were available and were used for 

smelters representing between 30 and 55 percent of U.S. 

primary aluminum production. The percentage changed from 

year to year as some smelters closed or changed hands and as 

the production at remaining smelters fluctuated. For smelters 

that did not report smelter-specific slope coefficients, IPCC 

2Al2O3 + 3C → 4Al + 3CO2

PFC (CF4 or C2F6) kg/metric ton Al = 

S × Anode Effect Minutes/Cell-Day

where,

S = Slope coefficient (kg PFC/metric ton 

Al)/(Anode Effect Minute/Cell-Day)

Anode Effect 

Minutes/

Cell-Day = Anode Effect Frequency/Cell-Day × 

Anode Effect Duration (Minutes)
4-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

technology-specific slope coefficients were applied (IPCC 

2001, 2006). The slope coefficients were combined with 

smelter-specific anode effect data collected by aluminum 

companies and reported under the VAIP, to estimate emission 

factors over time. For 1990 through 2006, smelter-specific 

anode effect data were available for smelters representing 

between 80 and 100 percent of U.S. primary aluminum 

production. Where smelter-specific anode effect data were 

not available, industry averages were used.

For all smelters, emission factors were multiplied by 

annual production to estimate annual emissions at the smelter 

level. For 1990 through 2006, smelter-specific production 

data were available for smelters representing between 30 

and 100 percent of U.S. primary aluminum production. 

(For the years after 2000, this percentage was near the high 

end of the range.) Production at non-reporting smelters 

was estimated by calculating the difference between the 

production reported under VAIP and the total U.S. production 

supplied by USGS and then by allocating this difference 

to non-reporting smelters in proportion to their production 

capacity. Emissions were then aggregated across smelters to 

estimate national emissions.

National primary aluminum production data for 2006 

were obtained via communication with USGS (USGS, 

2007). For 1990 through 2001 (see Table 4-60) data were 

obtained from USGS, Mineral Industry Surveys: Aluminum 

Annual Report (USGS 1995, 1998, 2000, 2001, 2002). For 

2002 through 2005, national aluminum production data were 

obtained from the United States Aluminum Association’s 

Primary Aluminum Statistics (USAA 2004, 2005, 2006).

Uncertainty

The overall uncertainties associated with the 2006 

CO2, CF4, and C2F6 emission estimates were calculated 

using a Tier 2 approach, as defined by IPCC (2006). For 

CO2, uncertainty was assigned to each of the parameters 

used to estimate CO2 emissions. Uncertainty surrounding 

reported production data was assumed to be 2 percent (IPCC 

2006). For additional variables, such as net C consumption, 

and sulfur and ash content in baked anodes, estimates for 

uncertainties associated with reported and default data 

were obtained from IPCC (2006). A Monte Carlo analysis 

was applied to estimate the overall uncertainty of the CO2

emission estimate for the U.S. aluminum industry as a whole, 

and the results are provided below.

To estimate the uncertainty associated with emissions 

of CF4 and C2F6, the uncertainties associated with three 

variables were estimated for each smelter: (1) the quantity of 

aluminum produced, (2) the anode effect minutes per cell day 

(which may be reported directly or calculated as the product 

of anode effect frequency and anode effect duration), and 

(3) the smelter- or technology-specific slope coefficient. A 

Monte Carlo analysis was then applied to estimate the overall 

uncertainty of the emission estimate for each smelter or 

company and for the U.S. aluminum industry as a whole.

The results of this quantitative uncertainty analysis are 

summarized in Table 4-61. Aluminum production-related 

CO2 emissions were estimated to be between 3.7 and 4.1 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates a 

range of approximately 5 percent below to 5 percent above 

the emission estimate of 3.9 Tg CO2 Eq. Also, productionrelated CF4 emissions were estimated to be between 1.9 

and 2.3 Tg CO2 Eq. at the 95 percent confidence level. 

This indicates a range of approximately 9 percent below 

to 9 percent above the emission estimate of 2.1 Tg CO2

Eq. Finally, aluminum production-related C2F6 emissions 

were estimated to be between 0.3 and 0.4 Tg CO2 Eq. at 

the 95 percent confidence level. This indicates a range of 

approximately 17 percent below to 17 percent above the 

emission estimate of 0.4 Tg CO2 Eq.

The 2006 emission estimate was developed using IPCC 

(2001) slope coefficients for 7 of the 8 operating smelters 

without site-specific PFC measurements. If these slope 

coefficients were revised to incorporate recent IPCC (2006) 

Table 4-60: Production of Primary Aluminum (Gg)

Year Gg

1990 4,048

1995 3,375

2000 3,668

2001 2,637

2002 2,705

2003 2,704

2004 2,517

2005 2,478

2006 2,284
Industrial Processes 4-43

slope data, overall PFC emission estimates for 2006 would 

probably be on the order of 10 percent lower than current 

estimates. Additionally, since these smelters are owned 

by one company, data have been reported on a companywide basis as totals or weighted averages. Consequently, 

uncertainties in anode effect minutes per cell day, slope 

coefficients, and aluminum production have been applied to 

the company as a whole, and not on a smelter-specific basis. 

This probably overestimates the uncertainty associated with 

the cumulative emissions from these smelters, because errors 

that were in fact independent were treated as if they were 

correlated. It is therefore likely that uncertainties calculated 

above for the total U.S. 2006 emission estimates for CF4 and 

C2F6 are also overestimated.

This Inventory may slightly underestimate greenhouse 

gas emissions from aluminum production and casting 

because it does not account for the possible use of SF6 as a 

cover gas or a fluxing and degassing agent in experimental 

and specialized casting operations. The extent of such use in 

the United States is not known. Historically, SF6 emissions 

from aluminum activities have been omitted from estimates 

of global SF6 emissions, with the explanation that any 

emissions would be insignificant (Ko et al. 1993, Victor and 

MacDonald 1998). The concentration of SF6 in the mixtures 

is small and a portion of the SF6 is decomposed in the process 

(MacNeal et al. 1990, Gariepy and Dube 1992, Ko et al. 1993, 

Ten Eyck and Lukens 1996, Zurecki 1996).

Recalculations Discussion

The 2005 emission estimates were updated to reflect 

revised prebake smelter production data. This change has 

resulted in a less than one percent increase in PFC and CO2

emissions for 2005.

4.16. Magnesium Production 

and Processing (IPCC Source 

Category 2C4)

The magnesium metal production and casting industry 

uses sulfur hexafluoride (SF6) as a cover gas to prevent the 

rapid oxidation of molten magnesium in the presence of air. 

A dilute gaseous mixture of SF6 with dry air and/or CO2 is 

blown over molten magnesium metal to induce and stabilize 

the formation of a protective crust. A small portion of the 

SF6 reacts with the magnesium to form a thin molecular 

film of mostly magnesium oxide and magnesium fluoride. 

The amount of SF6 reacting in magnesium production and 

processing is assumed to be negligible and thus all SF6

used is assumed to be emitted into the atmosphere. Sulfur 

hexafluoride has been used in this application around the 

world for the last twenty years.

The magnesium industry emitted 3.2 Tg CO2 Eq. (0.1 

Gg) of SF6 in 2006, representing a decrease of approximately 

3 percent from 2005 emissions (see Table 4-62). The recent 

closure of a production facility in Canada has resulted in 

Table 4-61: Tier 2 Quantitative Uncertainty Estimates for CO2 and PFC Emissions from Aluminum Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Aluminum Production CO2 3.9 3.7 4.1 -5% +5%

Aluminum Production CF4 2.1 1.9 2.3 -9% +9%

Aluminum Production C2F6 0.4 0.3 0.4 -17% +17%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

Table 4-62: SF6 Emissions from Magnesium Production 

and Processing (Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 5.4 0.2

1995 5.6 0.2

2000 3.0 0.1

2001 2.9 0.1

2002 2.9 0.1

2003 3.4 0.1

2004 3.2 0.1

2005 3.3 0.1

2006 3.2 0.1
4-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

supply pressures in North America for magnesium ingot 

that may encourage the expansion of primary magnesium 

production in the United States (USGS 2007a). The 

automotive industry is continuing to work towards converting 

components to magnesium for fuel efficiency gains. As a 

result of this shift, magnesium die casting processing is 

forecasted to grow by 3 percent for 2007 with another 4 

percent gain in 2008 (NADCA 2007).

Methodology

Emission estimates for the magnesium industry 

incorporate information provided by industry participants 

in EPA’s SF6 Emission Reduction Partnership for the 

Magnesium Industry. The Partnership started in 1999 and, 

currently, participating companies represent 100 percent of 

U.S. primary and secondary production and 90 percent of the 

casting sector production (i.e., die, sand, permanent mold, 

wrought, and anode casting). Absolute emissions for 1999 

through 2006 from primary production, secondary production 

(i.e., recycling), and die casting were generally reported 

by Partnership participants. When a Partner did not report 

emissions, they were estimated based on the metal processed 

and emission rate reported by that Partner in previous years. 

( The extrapolation was based on the trend shown by Partners 

reporting in the current and previous years.) Emissions for 

one Partner that is a secondary producer were estimated 

based on the average emission factor for other Partners that 

are secondary producers.

Emission factors for 2002 to 2006 for sand casting 

activities were also acquired through the Partnership. The 

1999 through 2006 emissions from casting operations (other 

than die) were estimated by multiplying emission factors 

(kg SF6 per metric ton of Mg produced or processed) by 

the amount of metal produced or consumed. The emission 

factors for casting activities are provided below in Table 

4-63. The emission factors for primary production, secondary 

production and sand casting are withheld to protect companyspecific production information. However, the emission 

factor for primary production has not risen above the average 

1995 Partner value of 1.1 kg SF6 per metric ton.

Die casting emissions for 1999 through 2006, which 

accounted for 25 to 52 percent of all SF6 emissions from the 

U.S. magnesium industry during this period, were estimated 

based on information supplied by industry Partners. From 

2000 to 2006, Partners accounted for all U.S. die casting 

that was tracked by USGS. In 1999, Partners did not account 

for all die casting tracked by USGS, and, therefore, it was 

necessary to estimate the emissions of die casters who were 

not Partners. Die casters who were not Partners were assumed 

to be similar to Partners who cast small parts. Due to process 

requirements, these casters consume larger quantities of SF6

per metric ton of processed magnesium than casters that 

process large parts. Consequently, emissions estimates from 

this group of die casters were developed using an average 

emission factor of 5.2 kg SF6 per metric ton of magnesium. 

The emission factors for the other industry sectors (i.e., 

permanent mold, wrought, and anode casting) were based 

on discussions with industry representatives.

Data used to develop SF6 emission estimates were 

provided by the Magnesium Partnership participants and 

the USGS. U.S. magnesium metal production (primary 

and secondary) and consumption (casting) data from 1990 

through 2006 were available from the USGS (USGS 2002, 

2003, 2005, 2006, 2007b). Emission factors from 1990 

through 1998 were based on a number of sources. Emission 

factors for primary production were available from U.S. 

primary producers for 1994 and 1995, and an emission 

factor for die casting of 4.1 kg per metric ton was available 

for the mid-1990s from an international survey (Gjestland 

& Magers 1996).

To estimate emissions for 1990 through 1998, industry 

emission factors were multiplied by the corresponding metal 

production and consumption (casting) statistics from USGS. 

The primary production emission factors were 1.2 kg per 

Table 4-63: SF6 Emission Factors (kg SF6 per metric ton 

of Magnesium)

Year

Die

Casting

Permanent 

Mold Wrought Anodes

1999 2.14a 2 1 1

2000 0.72 2 1 1

2001 0.72 2 1 1

2002 0.71 2 1 1

2003 0.81 2 1 1

2004 0.81 2 1 1

2005 0.76 2 1 1

2006 0.86 2 1 1

a Weighted average that includes an estimated emission factor of 5.2 kg 

SF6 per metric ton of magnesium for die casters that do not participate 

in the Partnership.
Industrial Processes 4-45

metric ton for 1990 through 1993, and 1.1 kg per metric 

ton for 1994 through 1997. For die casting, an emission 

factor of 4.1 kg per metric ton was used for the period 1990 

through 1996. For 1996 through 1998, the emission factors 

for primary production and die casting were assumed to 

decline linearly to the level estimated based on Partner 

reports in 1999. This assumption is consistent with the trend 

in SF6 sales to the magnesium sector that is reported in the 

RAND survey of major SF6 manufacturers, which shows 

a decline of 70 percent from 1996 to 1999 (RAND 2002). 

Sand casting emission factors for 2002 through 2006 were 

provided by the Magnesium Partnership participants and 

1990 through 2001 emission factors for this process were 

assumed to have been the same as the 2002 emission factor. 

The emission factor for secondary production from 1990 

through 1998 was assumed to be constant at the 1999 average 

partner value. The emission factors for the other processes 

(i.e., permanent mold, wrought, and anode casting), about 

which less is known, were assumed to remain constant at 

levels defined in Table 4-63.

Uncertainty

To estimate the uncertainty of the estimated 2006 SF6

emissions from magnesium production and processing, EPA 

estimated the uncertainties associated with three variables (1) 

emissions reported by magnesium producers and processors 

that participate in the SF6 Emission Reduction Partnership, (2) 

emissions estimated for magnesium producers and processors 

that participate in the Partnership but did not report this year, 

and (3) emissions estimated for magnesium producers and 

processors that do not participate in the Partnership.

Additional uncertainties exist in these estimates, 

such as the basic assumption that SF6 neither reacts nor 

decomposes during use. The melt surface reactions and 

high temperatures associated with molten magnesium 

could potentially cause some gas degradation. Recent 

measurement studies have identified SF6 cover gas 

degradation in die casting applications on the order of 

20 percent (Bartos et al. 2007). As is the case for other 

sources of SF6 emissions, total SF6 consumption data for 

magnesium production and processing in the United States 

were not available. Sulfur hexafluoride may also be used as 

a cover gas for the casting of molten aluminum with high 

magnesium content; however, to what extent this technique 

is used in the United States is unknown.

The results of this Tier 2 quantitative uncertainty 

analysis are summarized in Table 4-64. SF6 emissions 

associated with magnesium production and processing 

were estimated to be between 2.7 and 3.6 Tg CO2 Eq. at 

the 95 percent confidence level (or in 19 out of 20 Monte 

Carlo Stochastic Simulations). This indicates a range of 

approximately 14 percent below to 14 percent above the 

2006 emissions estimate of 3.2 Tg CO2 Eq.

Recalculations Discussion

Data from the USGS (USGS 2007b) slightly revised the 

amount of magnesium processed in 2005 for the wrought, 

sand and permanent mold casting sectors. In addition, 

wrought production numbers for 1990 and 1992 were 

revised to match historical USGS publications based on 

a data review. Revisions were also made to the approach 

for extrapolating and interpolating data for non-reporting 

Partners in order to improve accuracy. Emission estimates 

for secondary production activities by a non-reporting 

Partner were added for the years 2001 through 2006. The 

default historical emission factor for secondary production 

from 1990 to 1998 was also revised to be held constant at 

the 1999 Partner reported value. These changes resulted in 

an average annual increase in SF6 emissions of 0.03 Tg CO2

Eq. (approximately 0.5 percent) for 1990 to 1998 and 0.6 Tg 

CO2 Eq. (approximately 22 percent) for 2001 to 2005 relative 

to the previous report.

Table 4-64: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and Processing 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Magnesium Production SF6 3.2 2.7 3.6 -14% +14%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Planned Improvements

As more work assessing the degree of cover gas 

degradation and associated byproducts is undertaken and 

published, results could potentially be used to refine the 

emission estimates, which currently assume (per IPCC 

Good Practice Guidance, IPCC 2006) that all SF6 utilized 

is emitted to the atmosphere. EPA-funded measurements of 

SF6 in die casting applications have indicated that the latter 

assumption may be incorrect, with observed SF6 degradation 

on the order of 20 percent (Bartos et al. 2007). Another 

issue that will be addressed in future Inventories is the 

likely adoption of alternate cover gases by U.S. magnesium 

producers and processors. These cover gases, which include 

AM-coverTM (containing HFC-134a) and NovecTM 612, 

have lower GWPs than SF6, and tend to quickly decompose 

during their exposure to the molten metal. Magnesium 

producers and processors have already begun using these 

cover gases during this inventory year in a limited fashion; 

because the amounts are negligible these emissions are only 

being monitored and recorded at this time. Additionally, as 

more companies join the Partnership, in particular those 

from sectors not currently represented, such as permanent 

mold and anode casting, emission factors will be refined to 

incorporate these additional data.

4.17. Zinc Production (IPCC Source 

Category 2C5)

Zinc production in the United States consists of both 

primary and secondary processes. Primary production 

techniques used in the United States are the electro-thermic 

and electrolytic process while secondary techniques used 

in the United States include a range of metallurgical, 

hydrometallurgical, and pyrometallurgical processes. 

Worldwide primary zinc production also employs a 

pyrometallurgical process using the Imperial Smelting Furnace 

process; however, this process is not used in the United States 

(Sjardin 2003). Of the primary and secondary processes used 

in the United States, the electro-thermic process results in 

non-energy CO2 emissions, as does the Waelz Kiln process—a 

technique used to produce secondary zinc from electric-arc 

furnace (EAF) dust (Viklund-White 2000).

During the electro-thermic zinc production process, 

roasted zinc concentrate and, when available, secondary 

zinc products enter a sinter feed where they are burned to 

remove impurities before entering an electric retort furnace. 

Metallurgical coke added to the electric retort furnace reduces 

the zinc oxides and produces vaporized zinc, which is then 

captured in a vacuum condenser. This reduction process 

produces non-energy CO2 emissions (Sjardin 2003). The 

electrolytic zinc production process does not produce nonenergy CO2 emissions.

In the Waelz Kiln process, EAF dust, which is captured 

during the recycling of galvanized steel, enters a kiln along 

with a reducing agent—often metallurgical coke. When kiln 

temperatures reach approximately 1100–1200°C, zinc fumes 

are produced, which are combusted with air entering the kiln. 

This combustion forms zinc oxide, which is collected in a 

baghouse or electrostatic precipitator, and is then leached 

to remove chloride and fluoride. Through this process, 

approximately 0.33 ton of zinc is produced for every ton of 

EAF dust treated (Viklund-White 2000).

In 2006, U.S. primary and secondary zinc production 

totaled 510,000 metric tons (USGS 2008 ). The resulting 

emissions of CO2 from zinc production in 2006 were estimated 

to be 0.5 Tg CO2 Eq. (529 Gg) (see Table 4-65). All 2006 CO2

emissions result from secondary zinc production.

After a gradual increase in total emissions from 1990 to 

2000, largely due to an increase in secondary zinc production, 

emissions have decreased in recent years due to the closing 

of an electro-thermic-process zinc plant in Monaca, PA 

(USGS 2004). In 2006, emissions, which are nearly half 

those of 1990 (44 percent), increased by 14 percent over 

2005 levels despite decreases in overall production due to 

an increase in production from emissive secondary zinc 

production processes.

Table 4-65: CO2 Emissions from Zinc Production 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 0.9 949

1995 1.0 1,013

2000 1.1 1,140

2001 1.0 986

2002 0.9 937

2003 0.5 507

2004 0.5 477

2005 0.5 465

2006 0.5 529
Industrial Processes 4-47

Methodology

Non-energy CO2 emissions from zinc production result 

from those processes that use metallurgical coke or other 

C-based materials as reductants. Sjardin (2003) provides an 

emission factor of 0.43 metric tons CO2/ton zinc produced for 

emissive zinc production processes; however, this emission 

factor is based on the Imperial Smelting Furnace production 

process. Because the Imperial Smelting Furnace production 

process is not used in the United States, emission factors 

specific to those emissive zinc production processes used in the 

United States, which consist of the electro-thermic and Waelz 

Kiln processes, were needed. Due to the limited amount of 

information available for these electro-thermic processes, only 

Waelz Kiln process-specific emission factors were developed. 

These emission factors were applied to both the Waelz Kiln 

process and the electro-thermic zinc production processes. 

A Waelz Kiln emission factor based on the amount of zinc 

produced was developed based on the amount of metallurgical 

coke consumed for non-energy purposes per ton of zinc 

produced, 1.19 metric tons coke/metric ton zinc produced 

(Viklund-White 2000), and the following equation: The Waelz Kiln emission factor equals 1.19 metric tons coke per metric tons zinc multiplied by 0.84 metric tons carbon per metric ton coke multiplied by 3.67 metric tons carbon dioxide per metric ton carbon equals 3.66 metric tons carbon dioxide per metric ton zinc.

The USGS disaggregates total U.S. primary zinc 

production capacity into zinc produced using the electrothermic process and zinc produced using the electrolytic 

process; however, the USGS does not report the amount 

of zinc produced using each process, only the total zinc 

production capacity of the zinc plants using each process. 

The total electro-thermic zinc production capacity is divided 

by total primary zinc production capacity to estimate the 

percent of primary zinc produced using the electro-thermic 

process. This percent is then multiplied by total primary zinc 

production to estimate the amount of zinc produced using the 

electro-thermic process, and the resulting value is multiplied 

by the Waelz Kiln process emission factor to obtain total 

CO2 emissions for primary zinc production. According to 

the USGS, the only remaining plant producing primary zinc 

using the electro-thermic process closed in 2003 (USGS 

2004). Therefore, CO2 emissions for primary zinc production 

are reported only for years 1990 through 2002.

In the United States, secondary zinc is produced through 

either the electro-thermic or Waelz Kiln process. In 1997, 

the Horsehead Corporation plant, located in Monaca, PA, 

produced 47,174 metric tons of secondary zinc using the 

electro-thermic process (Queneau et al. 1998). This is the only 

plant in the United States that uses the electro-thermic process 

to produce secondary zinc, which, in 1997, accounted for 13 

percent of total secondary zinc production. This percentage 

was applied to all years within the time series up until the 

Monaca plant’s closure in 2003 (USGS 2004) to estimate the 

total amount of secondary zinc produced using the electrothermic process. This value is then multiplied by the Waelz 

Kiln process emission factor to obtain total CO2 emissions for 

secondary zinc produced using the electro-thermic process.

U.S. secondary zinc is also produced by processing 

recycled EAF dust in a Waelz Kiln furnace. Due to the 

complexities of recovering zinc from recycled EAF dust, an 

emission factor based on the amount of EAF dust consumed 

rather than the amount of secondary zinc produced is believed 

to represent actual CO2 emissions from the process more 

accurately (Stuart 2005). An emission factor based on the 

amount of EAF dust consumed was developed based on the 

amount of metallurgical coke consumed per ton of EAF dust 

consumed, 0.4 metric tons coke/metric ton EAF dust consumed 

(Viklund-White 2000), and the following equation:

The electric arc furnace dust emission factor equals 0.4 metric tons coke per metric ton electric arc furnace dust multiplied by 0.84 metric tons carbon per metric ton coke multiplied by 3.67 metric tons carbon dioxide per metric ton carbon equals 1.23 metric tons carbon dioxide per metric ton electric arc furnace 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 

 ×

 × 

 =

 

 1.19 metric tons coke

metric tons zinc

0.84 metric tons C

metric tons coke

3.67 metric tons CO2

metric tons C

3.66 metric tons CO2

metric tons zinc

EFWaelz Kiln = 

0.4 metric tons coke

metric tons EAF dust

0.84 metric tons C

metric tons coke

3.67 metric tons CO2

metric tons C

1.23 metric tons CO2

metric tons EAF dust

 ×

 ×

 =

 

EFEAF Dust = 
4-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

recycled EAF dust in a Waelz Kiln furnace. This value is 

multiplied by the Waelz Kiln process emission factor for 

EAF dust to obtain total CO2 emissions.

The 1990 through 2006 activity data for primary and 

secondary zinc production (see Table 4-66) were obtained 

through the USGS Mineral Yearbook: Zinc (USGS 1994 

through 2008).

Uncertainty

The uncertainties contained in these estimates are twofold, relating to activity data and emission factors used.

First, there are uncertainties associated with the percent 

of total zinc production, both primary and secondary, that 

is attributed to the electro-thermic and Waelz Kiln emissive 

zinc production processes. For primary zinc production, the 

amount of zinc produced annually using the electro-thermic 

process is estimated from the percent of primary-zinc 

production capacity that electro-thermic production capacity 

constitutes for each year of the time series. This assumes 

that each zinc plant is operating at the same percentage of 

total production capacity, which may not be the case and 

this calculation could either overestimate or underestimate 

the percentage of the total primary zinc production that is 

produced using the electro-thermic process. The amount of 

secondary zinc produced using the electro-thermic process is 

estimated from the percent of total secondary zinc production 

that this process accounted for during a single year, 2003. 

The amount of secondary zinc produced using the Waelz 

Kiln process is estimated from the percent of total secondary 

zinc production this process accounted for during a single 

year, 1997. This calculation could either overestimate or 

underestimate the percentage of the total secondary zinc 

production that is produced using the electro-thermic 

or Waelz Kiln processes. Therefore, there is uncertainty 

associated with the fact that percents of total production 

data estimated from production capacity, rather than actual 

production data, are used for emission estimates.

Second, there are uncertainties associated with the 

emission factors used to estimate CO2 emissions from the 

primary and secondary production processes. Because the 

only published emission factors are based on the Imperial 

Smelting Furnace, which is not used in the United States, 

country-specific emission factors were developed for 

the Waelz Kiln zinc production process. Data limitations 

prevented the development of emission factors for the 

electro-thermic process. Therefore, emission factors for the 

Waelz Kiln process were applied to both electro-thermic and 

Waelz Kiln production processes. Furthermore, the Waelz 

Kiln emission factors are based on materials balances for 

metallurgical coke and EAF dust consumed during zinc 

production provided by Viklund-White (2000). Therefore, the 

accuracy of these emission factors depend upon the accuracy 

of these materials balances.

The results of the Tier 2 quantitative uncertainty 

analysis are summarized in Table 4-67. Zinc production CO2

emissions were estimated to be between 0.4 and 0.7 Tg CO2

Eq. at the 95 percent confidence level. This indicates a range 

of approximately 21 percent below and 25 percent above the 

emission estimate of 0.5 Tg CO2 Eq.

Table 4-66: Zinc Production (Metric Tons)

Year Primary Secondary

1990 262,704 341,400

1995 231,840 353,000

2000 227,800 440,000

2001 203,000 375,000

2002 181,800 366,000

2003 186,900 381,000

2004 188,200 358,000

2005 191,120 349,000

2006 113,000 397,000

Table 4-67: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Zinc Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Zinc Production CO2 0.5 0.4 0.7 -21% +25%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-49

4.18. Lead Production (IPCC Source 

Category 2C5)

Lead production in the United States consists of both 

primary and secondary processes—both of which emit CO2

(Sjardin 2003). Primary lead production, in the form of 

direct smelting, mostly occurs at plants located in Alaska 

and Missouri, though to a lesser extent in Idaho, Montana, 

and Washington. Secondary production largely involves the 

recycling of lead acid batteries at 18 separate smelters located 

in 11 states (USGS 2006). Secondary lead production has 

increased in the United States over the past decade while 

primary lead production has decreased. In 2006, secondary 

lead production accounted for approximately 88 percent of 

total lead production (Smith 2007, USGS 1995).

Primary production of lead through the direct smelting 

of lead concentrate produces CO2 emissions as the lead 

concentrates are reduced in a furnace using metallurgical 

coke (Sjardin 2003). U.S. primary lead production increased 

by 7 percent from 2005 to 2006 and has decreased by 62 

percent since 1990 (Smith 2007, USGS 1995).

Approximately 92 percent of U.S. secondary lead is 

produced by recycling lead acid batteries in either blast 

furnaces or reverberatory furnaces (USGS 2006). The 

remaining 8 percent of secondary lead is produced from lead 

scrap. Similar to primary lead production, CO2 emissions 

result when a reducing agent, usually metallurgical coke, is 

added to the smelter to aid in the reduction process (Sjardin 

2003). U.S. secondary lead production increased by half a 

percent from 2005 to 2006, and has increased by 25 percent 

since 1990.

At last reporting, the United States was the third largest 

mine producer of lead in the world, behind China and Australia, 

accounting for 13 percent of world production in 2005 (USGS 

2006). In 2006, U.S. primary and secondary lead production 

totaled 1,313,000 metric tons (Smith 2007). The resulting 

emissions of CO2 from 2006 production were estimated to 

be 0.3 Tg CO2 Eq. (270 Gg) (see Table 4-68). The majority 

of 2006 lead production is from secondary processes, which 

account for 86 percent of total 2006 CO2 emissions.

After a gradual increase in total emissions from 1990 to 

2000, total emissions have decreased by five percent since 

1990, largely due to a decrease in primary production (62 

percent since 1990) and a transition within the United States 

from primary lead production to secondary lead production, 

which is less emissive than primary production, although 

the sharp decrease leveled off in 2005 and even increased 

slightly in 2006 (USGS 2006, Smith 2007).

Methodology

Non-energy CO2 emissions from lead production result 

from primary and secondary production processes that use 

metallurgical coke or other C-based materials as reductants. 

For primary lead production using direct smelting, Sjardin 

(2003) and the IPCC (2006) provide an emission factor of 

0.25 metric tons CO2/ton lead. For secondary lead production, 

Sjardin (2003) and IPCC (2006) provide an emission factor 

of 0.2 metric tons CO2/ton lead produced. Both factors 

are multiplied by total U.S. primary and secondary lead 

production, respectively, to estimate CO2 emissions.

The 1990 through 2006 activity data for primary and 

secondary lead production (see Table 4-69) were obtained 

Table 4-68: CO2 Emissions from Lead Production 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 0.3 285

1995 0.3 298

2000 0.3 311

2001 0.3 291

2002 0.3 286

2003 0.3 289

2004 0.3 263

2005 0.3 266

2006 0.3 270

Table 4-69: Lead Production (Metric Tons)

Year Primary Secondary

1990 404,000 922,000

1995 374,000 1,020,000

2000 341,000 1,130,000

2001 290,000 1,090,000

2002 262,000 1,100,000

2003 245,000 1,140,000

2004 148,000 1,127,000

2005 143,000 1,154,000

2006 153,000 1,160,000
4-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

through the USGS Mineral Yearbook: Lead (USGS 1994 

through 2008).

Uncertainty

Uncertainty associated with lead production relates 

to the emission factors and activity data used. The direct 

smelting emission factor used in primary production is taken 

from Sjardin (2003) who averages the values provided by 

three other studies (Dutrizac et al. 2000, Morris et al. 1983, 

Ullman 1997). For secondary production, Sjardin (2003) 

reduces this factor by 50 percent and adds a CO2 emission 

factor associated with battery treatment. The applicability 

of these emission factors to plants in the United States 

is uncertain. There is also a smaller level of uncertainty 

associated with the accuracy of primary and secondary 

production data provided by the USGS.

The results of the Tier 2 quantitative uncertainty 

analysis are summarized in Table 4-70. Lead production CO2

emissions were estimated to be between 0.2 and 0.3 Tg CO2

Eq. at the 95 percent confidence level. This indicates a range 

of approximately 16 percent below and 16 percent above the 

emission estimate of 0.3 Tg CO2 Eq.

Recalculations Discussion

Estimates of CO2 emissions from lead production were 

revised for the 2001, 2002, 2004, 2005, and 2006 to reflect 

updated secondary production activity (USGS 2008). This 

change resulted in a less than 2 percent decrease in emissions 

for 2001 and 2002, and a less than 2 percent increase in 

emissions for 2004 and 2005.

4.19. HCFC-22 Production (IPCC 

Source Category 2E1)

Trifluoromethane (HFC-23 or CHF3) is generated as a 

byproduct during the production of chlorodifluoromethane 

(HCFC-22), which is primarily employed in refrigeration 

and air conditioning systems and as a chemical feedstock 

for manufacturing synthetic polymers. Between 1990 and 

2000, U.S. production of HCFC-22 increased significantly 

as HCFC-22 replaced chlorofluorocarbons (CFCs) in many 

applications. Since 2000, U.S. production has fluctuated but 

has generally remained above 1990 levels. Because HCFC-22 

depletes stratospheric ozone, its production for non-feedstock 

uses is scheduled to be phased out by 2020 under the U.S. 

Clean Air Act.13 Feedstock production, however, is permitted 

to continue indefinitely.

HCFC-22 is produced by the reaction of chloroform 

(CHCl3) and hydrogen fluoride (HF) in the presence of a 

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 (CHCl2F), HCFC-22 (CHClF2), 

HFC-23 (CHF3), HCl, chloroform, and HF. The underfluorinated 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, HCl and residual HF. The HCl is recovered as a 

useful byproduct, and the HF is removed. Once separated 

13As 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].

Table 4-70: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Lead Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Lead Production CO2 0.3 0.2 0.3 -16% +16%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-51

from HCFC-22, the HFC-23 is generally vented to the 

atmosphere as an unwanted byproduct, but it is sometimes 

captured for use in a limited number of applications.

Emissions of HFC-23 in 2006 were estimated to be 

13.8 Tg CO2 Eq. (1.2 Gg) (Table 4-71). This quantity 

represents a 13 percent decline from 2005 emissions and a 

62 percent decline from 1990 emissions. Both declines are 

primarily due to decreases in the HFC-23 emission rate. 

These decreases are primarily attributable to four factors: 

(a) five plants that did not capture and destroy the HFC-23 

generated have ceased production of HCFC-22 since 1990, 

(b) one plant that captures and destroys the HFC-23 generated 

began to produce HCFC-22, (c) one plant implemented and 

documented a process change that reduced the amount of 

HFC-23 generated, and (d) the same plant began recovering 

HFC-23, primarily for destruction and secondarily for sale. 

Three HCFC-22 production plants operated in the United 

States in 2006, two of which used thermal oxidation to 

significantly lower their HFC-23 emissions.

Methodology

To estimate their emissions of HFC-23, five of the eight 

HCFC-22 plants that have operated in the United States 

since 1990 use (or, for those plants that have closed, used) 

methods comparable to the Tier 3 methods in the 2006 IPCC 

Guidelines. The other three plants, the last of which closed 

in 1993, used methods comparable to the Tier 1 method in 

the 2006 IPCC Guidelines. Emissions from these three plants 

have been recalculated using the recommended emission 

factor for unoptimized plants operating before 1995 (0.04 

kg HCFC-23/kg HCFC-22 produced).

The five plants that have operated since 1994 measure(d) 

concentrations of HFC-23 to estimate their emissions of HFC23. Plants using thermal oxidation to abate their HFC-23 

emissions monitor the performance of their oxidizers to verify 

that the HFC-23 is almost completely destroyed. Plants that 

release (or historically have released) some of their byproduct 

HFC-23 periodically measure HFC-23 concentrations in the 

output stream using gas chromatography. This information is 

combined with information on quantities of products (e.g., 

HCFC-22) to estimate HFC-23 emissions.

Production data and emission estimates were prepared 

in cooperation with the U.S. producers of HCFC-22 (ARAP 

1997, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007; 

RTI 1997; RTI 2008). Annual estimates of U.S. HCFC-22 

production are presented in Table 4-72.

Uncertainty

The uncertainty analysis presented in this section was 

based on a Monte Carlo simulation as described in the 2006 

IPCC Guidelines for each plant for 2006. The Monte Carlo 

analysis used estimates of the uncertainties in the individual 

variables in each plant’s estimating procedure. This analysis 

was based on the generation of 10,000 random samples of 

model inputs from the probability density functions for each 

input. A normal probability density function was assumed 

for all measurements and biases except the equipment leak 

estimates for one plant; a log-normal probability density 

function was used for this plant’s equipment leak estimates.

Table 4-71: HFC-23 Emissions from HCFC-22 

Production (Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 36.4 3

1995 33.0 3

2000 28.6 2

2001 19.7 2

2002 21.1 2

2003 12.3 1

2004 17.2 1

2005 15.8 1

2006 13.8 1

Table 4-72: HCFC-22 Production (Gg)

Year Gg

1990 139

1995 155

2000 186

2001 152

2002 149

2003 138

2004 155

2005 156

2006 154
4-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-73. HCFC-22 production HFC 

emissions were estimated to be between 12.9 and 15.2 Tg 

CO2 Eq. at the 95 percent confidence level. This indicates 

a range of approximately 7 percent below and 10 percent 

above the emission estimate of 13.8 Tg CO2 Eq.

Recalculations

EPA recently completed a comprehensive review of 

plant-level estimates of HFC-23 emissions and HCFC-22 

production (RTI, 2008). This review resulted in generally 

small adjustments to estimates of HCFC-22 production and 

HFC-23 emissions. As noted above, the HFC-23 emissions 

for three plants that operated in the early 1990s were recalculated to conform with the 2006 IPCC Guidelines using 

the Tier 1 emission factor of 0.04 kg HFC-23/kg HCFC22. This revision increased the estimated U.S. emissions 

by 4 to 6 percent for 1990 to 1993. The largest adjustment 

was for the year 1995, for which the HFC-23 emissions 

estimate increased by 22 percent. This increase reflected 

a correction made by one plant to its emissions estimate. 

This calculation was documented in the plant’s files and 

made the plant’s 1995 emission rate more consistent with 

its emission rates for previous and following years. There 

were also minor revisions (ranging from -4 percent to 

+10 percent) to the emissions estimated for 2000, 2002, 

2004 and 2005. These changes reflected revisions that 

plants made to their estimates after they were submitted 

to the Alliance for Responsible Atmospheric Policy, which 

aggregates the emissions of the plants and sends the total 

to EPA. Again, the revised estimates were documented in 

the plants’ files.

4.20. Substitution of Ozone 

Depleting Substances (IPCC Source 

Category 2F)

Hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs) 

are used as alternatives to several classes of ozone depleting 

substances (ODSs) that are being phased out under the terms 

of the Montreal Protocol and the Clean Air Act Amendments 

of 1990.14 Ozone depleting substances—chlorofluorocarbons 

(CFCs), halons, carbon tetrachloride, methyl chloroform, and 

hydrochlorofluorocarbons (HCFCs)—are used in a variety 

of industrial applications including refrigeration and air 

conditioning equipment, solvent cleaning, foam production, 

sterilization, fire extinguishing, and aerosols. Although HFCs 

and PFCs are not harmful to the stratospheric ozone layer, 

they are potent greenhouse gases. Emission estimates for 

HFCs and PFCs used as substitutes for ODSs are provided 

in Table 4-74 and Table 4-75.

In 1990 and 1991, the only significant emissions of 

HFCs and PFCs as substitutes to ODSs were relatively 

small amounts of HFC-152a—used as an aerosol propellant 

and also a component of the refrigerant blend R-500 

used in chillers—and HFC-134a in refrigeration enduses. Beginning in 1992, HFC-134a was used in growing 

amounts as a refrigerant in motor vehicle air-conditioners 

and in refrigerant blends such as R-404A.15 In 1993, 

the use of HFCs in foam production began, and in 1994 

these compounds also found applications as solvents and 

sterilants. In 1995, ODS substitutes for halons entered 

widespread use in the United States as halon production 

was phased-out.

14 [42 U.S.C § 7671, CAA § 601]

15R-404A contains HFC-125, HFC-143a, and HFC-134a.

Table 4-73: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

HCFC-22 Production HFC-23 13.8 12.9 15.2 -7% +10%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-53

The use and subsequent emissions of HFCs and PFCs 

as ODS substitutes has been increasing from small amounts 

in 1990 to 110.4 Tg CO2 Eq. in 2006. This increase was in 

large part the result of efforts to phase out CFCs and other 

ODSs in the United States. In the short term, this trend is 

expected to continue, and will likely accelerate over the next 

decade as HCFCs, which are interim substitutes in many 

applications, are themselves phased-out under the provisions 

of the Copenhagen Amendments to the Montreal Protocol. 

Improvements in the technologies associated with the use 

of these gases and the introduction of alternative gases and 

technologies, however, may help to offset this anticipated 

increase in emissions.

Table 4-76 presents HFCs and PFCs emissions by enduse sector for 1990 through 2006. The end-use sectors that 

contributed the most toward emissions of HFCs and PFCs 

Table 4-74: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.)

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006

HFC-23 + + + + + + + + + 

HFC-32 + + + 0.1 0.1 0.2 0.3 0.4 0.6 

HFC-125 + 0.8 5.2 6.0 6.8 7.8 9.0 10.3 12.3 

HFC-134a + 25.4 57.2 62.0 66.3 70.0 73.8 76.3 76.6 

HFC-143a + 0.5 4.1 5.4 6.8 8.3 10.1 12.2 14.4 

HFC-236fa + 0.2 0.5 0.6 0.6 0.7 0.7 0.8 0.8 

CF4 + + + + + + + + + 

Others* 0.3 1.6 4.0 3.9 4.3 4.9 5.2 5.4 5.7 

Total 0.3 28.5 71.2 78.0 85.0 92.0 99.1 105.4 110.4 

+ Does not exceed 0.05 Tg CO2 Eq.

* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee, C4F10, and PFC/PFPEs, the latter being a proxy for a diverse collection of PFCs and 

perfluoropolyethers (PFPEs) employed for solvent applications. For estimating purposes, the GWP value used for PFC/PFPEs was based upon C6F14.

Note: Totals may not sum due to independent rounding.

Table 4-75: Emissions of HFCs and PFCs from ODS Substitutes (Mg)

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006

HFC-23 + + 1 1 1 1 1 1 1 

HFC-32 + + 44 92 166 268 400 562 913 

HFC-125 + 291 1,873 2,150 2,442 2,798 3,220 3,675 4,395 

HFC-134a + 19,536 44,001 47,712 51,016 53,843 56,787 58,700 58,923 

HFC-143a + 132 1,089 1,415 1,781 2,194 2,654 3,200 3,782 

HFC-236fa + 36 85 94 103 111 118 125 131 

CF4 + + 1 1 1 2 2 2 2 

Others* M M M M M M M M M

M (Mixture of Gases)

+ Does not exceed 0.5 Mg

* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee, C4F10, and PFC/PFPEs, the latter being a proxy for a diverse collection of PFCs and 

perfluoropolyethers (PFPEs) employed for solvent applications.

Table 4-76: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO2 Eq.) by Sector

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006

Refrigeration/Air Conditioning + 19.3 58.6 65.3 71.6 77.7 84.4 90.1 94.6 

Aerosols + 8.1 10.1 10.3 10.6 10.8 11.1 11.3 11.6

Foams + + + + 1.0 1.8 2.0 2.2 2.4

Solvents + 0.9 2.1 1.8 1.6 1.3 1.3 1.3 1.3

Fire Protection + + + + + + + 0.5 0.6

Total + 28.5 71.2 78.0 85.0 92.0 99.1 105.4 110.4 
4-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

as ODS substitutes in 2006 include refrigeration and airconditioning (94.6 Tg CO2 Eq., or approximately 86 percent), 

aerosols (11.6 Tg CO2 Eq., or approximately 10 percent), and 

foams (2.4 Tg CO2 Eq., or approximately 2 percent). Within 

the refrigeration and air-conditioning end-use sector, motor 

vehicle air-conditioning was the highest emitting end-use 

(55.8 Tg CO2 Eq.), followed by retail food and refrigerated 

transport. Each of the end-use sectors is described in more 

detail below.

Refrigeration/Air Conditioning

The refrigeration and air-conditioning sector includes a 

wide variety of equipment types that have historically used 

CFCs or HCFCs. End uses within this sector include motor 

vehicle air-conditioning, retail food refrigeration, refrigerated 

transport (e.g., ship holds, truck trailers, railway freight cars), 

household refrigeration, residential and small commercial 

air-conditioning/heat pumps, chillers (large comfort 

cooling), cold storage facilities, and industrial process 

refrigeration (e.g., systems used in food processing, chemical, 

petrochemical, pharmaceutical, oil and gas, and metallurgical 

industries). As the ODS phaseout is taking effect, most 

equipment is being or will eventually be retrofitted or 

replaced to use HFC-based substitutes. Common HFCs in 

use today in refrigeration/air-conditioning equipment are 

HFC-134a, R-410A, R-404A, and R-507A. These HFCs are 

emitted to the atmosphere during equipment manufacture 

and operation (as a result of component failure, leaks, and 

purges), as well as at servicing and disposal events.

Aerosols

Aerosol propellants are used in metered dose inhalers 

(MDIs) and a variety of personal care products and technical/

specialty products (e.g., duster sprays and safety horns). 

Many pharmaceutical companies that produce MDIs—a 

type of inhaled therapy used to treat asthma and chronic 

obstructive pulmonary disease—have committed to replace 

the use of CFCs with HFC-propellant alternatives. The 

earliest ozone-friendly MDIs were produced with HFC-134a, 

but eventually, the industry expects to use HFC-227ea as well. 

Conversely, since the use of CFC propellants was banned in 

1978, most consumer aerosol products have not transitioned 

to HFCs, but to “not-in-kind” technologies, such as solid 

roll-on deodorants and finger-pump sprays. The transition 

away from ODS in specialty aerosol products has also led 

to the introduction of non-fluorocarbon alternatives (e.g., 

hydrocarbon propellants) in certain applications, in addition 

to HFC-134a or HFC-152a. These propellants are released 

into the atmosphere as the aerosol products are used.

Foams

CFCs and HCFCs have traditionally been used as foam 

blowing agents to produce polyurethane (PU), polystyrene, 

polyolefin, and phenolic foams, which are used in a wide 

variety of products and applications. Since the Montreal 

Protocol, flexible PU foams as well as other types of 

foam, such as polystyrene sheet, polyolefin, and phenolic 

foam, have transitioned almost completely away from 

fluorocompounds, into alternatives such as CO2, methylene 

chloride, and hydrocarbons. The majority of rigid PU foams 

have transitioned to HFCs—primarily HFC-134a and HFC245fa. Today, these HFCs are used to produce polyurethane 

appliance foam, PU commercial refrigeration, PU spray, and 

PU panel foams—used in refrigerators, vending machines, 

roofing, wall insulation, garage doors, and cold storage 

applications. In addition, HFC-152a is used to produce 

polystyrene sheet/board foam, which is used in food 

packaging and building insulation. Emissions of blowing 

agents occur when the foam is manufactured as well as 

during the foam lifetime and at foam disposal, depending on 

the particular foam type.

Solvents

CFCs, methyl chloroform (1,1,1-trichloroethane or 

TCA), and to a lesser extent carbon tetrachloride (CCl4) 

were historically used as solvents in a wide range of cleaning 

applications, including precision, electronics, and metal 

cleaning. Since their phaseout, metal cleaning end-use 

applications have primarily transitioned to non-fluorocarbon 

solvents and not-in-kind processes. The precision and 

electronics cleaning end-uses have transitioned in part to 

high-GWP gases, due to their high reliability, excellent 

compatibility, good stability, low toxicity, and selective 

solvency. These applications rely on HFC-4310mee, HFC365mfc, HFC-245fa, and to a lesser extent, PFCs. Electronics 

cleaning involves removing flux residue that remains after 
Industrial Processes 4-55

a soldering operation for printed circuit boards and other 

contamination-sensitive electronics applications. Precision 

cleaning may apply to either electronic components or to 

metal surfaces, and is characterized byproducts, such as disk 

drives, gyroscopes, and optical components, that require a high 

level of cleanliness and generally have complex shapes, small 

clearances, and other cleaning challenges. The use of solvents 

yields fugitive emissions of these HFCs and PFCs.

Fire Protection

Fire protection applications include portable fire 

extinguishers (“streaming” applications) that originally used 

halon 1211, and total flooding applications that originally 

used halon 1301, as well as some halon 2402. Since the 

production and sale of halons were banned in the United 

States in 1994, the halon replacement agent of choice in the 

streaming sector has been dry chemical, although HFC-236ea 

is also used to a limited extent. In the total flooding sector, 

HFC-227ea has emerged as the primary replacement for 

halon 1301 in applications that require clean agents. Other 

HFCs, such as HFC-23, HFC-236fa, and HFC-125, are used 

in smaller amounts. The majority of HFC-227ea in total 

flooding systems is used to protect essential electronics, as 

well as in civil aviation, military mobile weapons systems, 

oil/gas/other process industries, and merchant shipping. As 

fire protection equipment is tested or deployed, emissions of 

these HFCs are released.

Methodology

A detailed Vintaging Model of ODS-containing 

equipment and products was used to estimate the actual—

versus potential—emissions of various ODS substitutes, 

including HFCs and PFCs. The name of the model refers to 

the fact that the model tracks the use and emissions of various 

compounds for the annual “vintages” of new equipment 

that enter service in each end-use. This Vintaging Model 

predicts ODS and ODS substitute use in the United States 

based on modeled estimates of the quantity of equipment 

or products sold each year containing these chemicals and 

the amount of the chemical required to manufacture and/or 

maintain equipment and products over time. Emissions for 

each end-use were estimated by applying annual leak rates 

and release profiles, which account for the lag in emissions 

from equipment as they leak over time. By aggregating the 

data for more than 50 different end-uses, the model produces 

estimates of annual use and emissions of each compound. 

Further information on the Vintaging Model is contained in 

Annex 3.8.

Uncertainty

Given that emissions of ODS substitutes occur from 

thousands of different kinds of equipment and from millions 

of point and mobile sources throughout the United States, 

emission estimates must be made using analytical tools such 

as the Vintaging Model or the methods outlined in IPCC 

(2006). Though the model is more comprehensive than the 

IPCC default methodology, significant uncertainties still 

exist with regard to the levels of equipment sales, equipment 

characteristics, and end-use emissions profiles that were used 

to estimate annual emissions for the various compounds.

The Vintaging Model estimates emissions from over 50 

end-uses. The uncertainty analysis, however, quantifies the 

level of uncertainty associated with the aggregate emissions 

resulting from the top 16 end-uses, comprising over 95 

percent of the total emissions, and 5 other end-uses. In an 

effort to improve the uncertainty analysis, additional enduses are added annually, with the intention that over time 

uncertainty for all emissions from the Vintaging Model 

will be fully characterized. This year, one new end-use was 

included in the uncertainty estimate—fire extinguishing 

streaming agents. Any end-uses included in previous years’ 

uncertainty analysis were included in the current uncertainty 

analysis, whether or not those end-uses were included in the 

top 95 percent of emissions from ODS Substitutes.

 In order to calculate uncertainty, functional forms were 

developed to simplify some of the complex “vintaging” 

aspects of some end-use sectors, especially with respect to 

refrigeration and air-conditioning, and to a lesser degree, 

fire extinguishing. These sectors calculate emissions based 

on the entire lifetime of equipment, not just equipment put 

into commission in the current year, thereby necessitating 

simplifying equations. The functional forms used variables 

that included growth rates, emission factors, transition from 

ODSs, change in charge size as a result of the transition, 

disposal quantities, disposal emission rates, and either stock 

for the current year or original ODS consumption. Uncertainty 
4-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

was estimated around each variable within the functional 

forms based on expert judgment, and a Monte Carlo analysis 

was performed. The most significant sources of uncertainty 

for this source category include the emission factors for 

mobile air-conditioning and retail food refrigeration, as well 

as the stock (MT) of retail food refrigerant.

The results of the Tier 2 quantitative uncertainty 

analysis are summarized in Table 4-77. Substitution of ozone 

depleting substances HFC and PFC emissions were estimated 

to be between 110.1 and 129.6 Tg CO2 Eq. at the 95 percent 

confidence level (or in 19 out of 20 Monte Carlo Stochastic 

Simulations). This indicates a range of approximately 0.3 

percent below to 17 percent above the emission estimate of 

110.4 Tg CO2 Eq.

Recalculations Discussion

An extensive review of the chemical substitution trends, 

market sizes, growth rates, and charge sizes, together with 

input from industry representatives, resulted in updated 

assumptions for the Vintaging Model. These changes resulted 

in an average annual net decrease of 8.5 Tg CO2 Eq. (14 

percent) in HFC and PFC emissions from the substitution of 

ozone depleting substances for the period 1990 through 2005. 

The refrigeration and air conditioning sector was the source 

of the greatest change, with an average annual net decrease 

of 10.2 Tg CO2 Eq. (15 percent) in emissions. This decrease 

can be attributed to changes in the assumptions regarding the 

quantity of emissions at end of life (disposal) across the entire 

sector, based on revised assumptions considering input from 

industry representatives, as well significant modification to 

assumptions for chiller end uses, based on industry input.

4.21. Semiconductor Manufacture 

(IPCC Source Category 2F6)

The semiconductor industry uses multiple long-lived 

fluorinated gases in plasma etching and plasma enhanced 

chemical vapor deposition (PECVD) processes to produce 

semiconductor products. The gases most commonly employed 

are trifluoromethane (HFC-23 or CHF3), perfluoromethane 

(CF4), perfluoroethane (C2F6), nitrogen trifluoride (NF3), 

and sulfur hexafluoride (SF6), although other compounds 

such as perfluoropropane (C3F8) and perfluorocyclobutane 

(c-C4F8) are also used. The exact combination of compounds 

is specific to the process employed.

A single 300 mm silicon wafer that yields between 

400 to 500 semiconductor products (devices or chips) may 

require as many as 100 distinct fluorinated-gas-using process 

steps, principally to deposit and pattern dielectric films. 

Plasma etching (or patterning) of dielectric films, such as 

silicon dioxide and silicon nitride, is performed to provide 

pathways for conducting material to connect individual 

circuit components in each device. The patterning process 

uses plasma-generated fluorine atoms, which chemically 

react with exposed dielectric film, to selectively remove the 

desired portions of the film. The material removed as well as 

undissociated fluorinated gases flow into waste streams and, 

unless emission abatement systems are employed, into the 

atmosphere. PECVD chambers, used for depositing dielectric 

films, are cleaned periodically using fluorinated and other 

gases. During the cleaning cycle the gas is converted to 

fluorine atoms in plasma, which etches away residual material 

from chamber walls, electrodes, and chamber hardware. 

Undissociated fluorinated gases and other products pass 

Table 4-77: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Substitution of Ozone 

Depleting Substances

HFCs and 

PFCs 110.4 110.1 129.6 -0.3% +17%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-57

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 byproduct. 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 2006, total weighted emissions of all fluorinated 

greenhouse gases by the U.S. semiconductor industry were 

estimated to be 4.8 Tg CO2 Eq. Combined emissions of all 

fluorinated greenhouse gases are presented in Table 4-78 

and Table 4-79 for years 1990, 1995 and the period 2000 to 

2006. The rapid growth of this industry and the increasing 

complexity (growing number of layers) of semiconductor 

products led to an increase in emissions of 149 percent 

between 1990 and 1999, when emissions peaked at 7.2 

Tg CO2 eq. The emissions growth rate began to slow after 

1998, and emissions declined by 34 percent between 1999 

and 2006. Together, industrial growth and use of abatement 

technologies resulted in a net increase in emissions of 64 

percent between 1990 and 2006.

Methodology

Emissions are based on Partner reported emissions 

data received through the EPA’s PFC Reduction/Climate 

Partnership and the EPA’s PFC Emissions Vintage Model 

(PEVM), a model which estimates industry emissions in 

the absence of emission control strategies (Burton and 

Beizaie 2001).16 The availability and applicability of Partner 

data differs across the 1990 through 2006 time series. 

Consequently, emissions from semiconductor manufacturing 

were estimated using three distinct methods, one each for the 

periods 1990 through 1994, 1995 through 1999, and 2000 

and beyond.

16A Partner refers to a participant of the U.S. EPA PFC Reduction/Climate 

Partnership for the Semiconductor Industry. Through a Memorandum of 

Understanding (MoU) with the EPA, Partners voluntarily report their PFC 

emissions to the EPA by way of a third party.

Table 4-78: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg CO2 Eq.)

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006

CF4 0.7 1.3 1.8 1.3 1.1 1.0 1.1 1.1 1.2

C2F6 1.5 2.5 3.0 2.1 2.2 2.1 2.1 2.0 2.2

C3F8 0.0 0.0 0.1 0.1 0.1 0.1 0.0 0.0 0.0

C4F8 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1

HFC-23 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.3

SF6 0.5 0.9 1.1 0.7 0.7 0.8 0.8 1.0 1.0

NF3* 0.0 0.0 0.1 0.1 0.3 0.2 0.2 0.2 0.3

Total 2.9 5.0 6.3 4.5 4.3 4.3 4.3 4.4 4.8

Note: Totals may not sum due to independent rounding.

* NF3 emissions are presented for informational purposes, using a GWP of 8,000, and are not included in totals.

Table 4-79: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg)

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006

CF4 115 193 281 202 174 161 172 169 183

C2F6 160 272 322 230 241 227 225 217 242

C3F8 0 0 18 14 10 14 6 5 5

C4F8 0 0 0 0 6 9 9 13 13

HFC-23 15 25 23 15 15 16 17 18 22

SF6 22 38 45 31 28 35 35 41 40

NF3 3 6 11 12 32 30 30 26 40
4-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

1990 through 1994

For 1990 through 1994, Partnership data was unavailable 

and emissions were modeled using the PEVM (Burton and 

Beizaie 2001).17 1990 to 1994 emissions are assumed to be 

primarily uncontrolled, since reduction strategies such as 

chemical substitution and abatement were not widespread 

during this period.

PEVM is based on the assumption that PFC emissions 

from semiconductor manufacturing vary with (1) the number 

of layers on different kinds of semiconductor devices 

(including both silicon wafer and metal interconnect layers), 

and (2) silicon consumption (i.e., the area of semiconductors 

produced) for each kind of device. The product of these 

two quantities, Total Manufactured Layer Area (TMLA), 

constitutes the activity data for semiconductor manufacturing. 

PEVM also incorporates an emission factor that expresses 

emissions per unit of layer area. Emissions are estimated by 

multiplying TMLA by this emission factor.

PEVM incorporates information on the two attributes 

of semiconductor devices that affect the number of layers: 

(1) linewidth technology (the smallest feature size),18 and 

(2) product type (discrete, memory or logic).19 For each 

linewidth technology, a weighted average number of layers 

is estimated using VLSI product-specific worldwide silicon 

demand data in conjunction with complexity factors (i.e., 

the number of layers per IC) specific to product type (Burton 

and Beizaie 2001, ITRS 2007). PEVM derives historical 

consumption of silicon (i.e., square inches) by linewidth 

17 Various versions of the PEVM exist, to reflect changing industrial 

practices. From 1990 to 1994 emissions estimates are from PEVM v1.0, 

completed in September 1998. The emission factor used to estimate 1990 to 

1994 emissions is an average of the 1995 and 1996 emission factors, which 

were derived from Partner reported data for those years.

18 By decreasing features of IC components, more components can be 

manufactured per device, which increases its functionality. However, as those 

individual components shrink it requires more layers to interconnect them 

to achieve the functionality. For example, a microprocessor manufactured 

with the smallest feature sizes (65 nm) might contain as many as 1 billion 

transistors and require as many as 11 layers of component interconnects 

to achieve functionality while a device manufactured with 130 nm feature 

size might contain a few hundred million transistors and require 8 layers 

of component interconnects (ITRS, 2007).

19 Memory devices manufactured with the same feature sizes as 

microprocessors (a logic device) require approximately one-half the number 

of interconnect layers, whereas discrete devices require only a silicon base 

layer and no interconnect layers (ITRS, 2007). Since discrete devices did 

not start using PFCs appreciably until 2004, they are only accounted for in 

the PEVM emissions estimates from 2004 onwards.

technology from published data on annual wafer starts and 

average wafer size (VLSI Research, 2007).

The emission factor in PEVM is the average of the 

four historical emission factors derived by dividing the 

total annual emissions reported by the Partners for each 

year between 1996 and 1999 by the total TMLA estimated 

for the Partners in each of those years. Since Partners are 

not believed to have applied significant emission reduction 

measures before 2000, the resulting average emission factor 

does not reflect such measures.

1995 through 1999

For 1995 through 1999, total U.S. emissions were 

extrapolated from the total annual emissions reported by the 

Partners (1995 through 1999). Partner-reported emissions are 

considered more accurate than PEVM estimated emissions, 

and are used to generate total U.S. emissions when applicable. 

The emissions reported by the Partners were divided by the 

ratio of the total layer-weighted capacity of the plants operated 

by the Partners and the total layer-weighted capacity of all 

of the semiconductor plants in the United States; this ratio 

represents the share of layer-weighted capacity attributable 

to the Partnership. The layer-weighted capacity of a plant (or 

group of plants) consists of the silicon capacity of that plant 

multiplied by the estimated number of layers used to fabricate 

products at that plant. This method assumes that Partners and 

non-Partners have similar capacity utilizations and per-layer 

emission factors. Plant capacity, linewidth technology, and 

products manufactured information is contained in the World 

Fab Watch (WFW) database, which is updated quarterly 

(see for example, Semiconductor Equipment and Materials 

Industry 2007).

2000 through 2006

The U.S. estimate for the years 2000 through 2006—the 

period during which Partners began the consequential 

application of PFC-reduction measures—was estimated 

using a combination of Partner reported emissions and 

PEVM modeled emissions. The emissions reported by 

Partners for each year were accepted as the quantity emitted 

from the share of the industry represented by those Partners. 

Remaining emissions (those from non-Partners), however, 

were estimated using PEVM and the method described 

above. This is because non-Partners are assumed not to 

have implemented any PFC-reduction measures, and PEVM 
Industrial Processes 4-59

models emissions without such measures. The portion 

of the U.S. total attributed to non-Partners is obtained by 

multiplying PEVM’s total world emissions figure by the 

non-Partner share of total layer-weighted silicon capacity for 

each year (as described above).20 Annual updates to PEVM 

reflect published figures for actual silicon consumption from 

VLSI Research, Inc., revisions and additions to the world 

population of semiconductor manufacturing plants, and 

changes in IC fabrication practices within the semiconductor 

industry (see Semiconductor Equipment and Materials 

Industry 2007).21, 22, 23

Gas-Specific Emissions

Two different approaches were also used to estimate 

the distribution of emissions of specific PFCs. Before 1999, 

when there was no consequential adoption of PFC-reducing 

measures, a fixed distribution was assumed to apply to the 

20 Generally 5 percent or less of the fields needed to estimate TMLA shares 

are missing values in the World Fab Watch databases. In the 2007 World 

Fab Watch database, used to generate the 2006 non-Partner TMLA capacity 

share, these missing values were replaced with the corresponding mean 

TMLA across fabs manufacturing similar classes of products. However, 

the impact of replacing missing values on the non-Partner TMLA capacity 

share was inconsequential.

21 Special attention was given to the manufacturing capacity of plants that 

use wafers with 300 mm diameters because the actual capacity of these 

plants is ramped up to design capacity, typically over a 2–3 year period. To 

prevent overstating estimates of partner-capacity shares from plants using 

300 mm wafers, design capacities contained in WFW were replaced with 

estimates of actual installed capacities for 2004 published by Citigroup 

Smith Barney (2005). Without this correction, the partner share of capacity 

would be overstated, by approximately 5 percentage points. For perspective, 

approximately 95 percent of all new capacity additions in 2004 used 300 

mm wafers and by year-end those plants, on average, could operate at 

approximately 70 percent of the design capacity. For 2005, actual installed 

capacities was estimated using an entry in the World Fab Watch database 

(April 2006 Edition) called “wafers/month, 8-inch equivalent,” which 

denoted the actual installed capacity instead of the fully-ramped capacity. 

For 2006, actual installed capacities of new fabs were estimated using an 

average monthly ramp rate of 1100 wafer starts per month (wspm) derived 

from various sources such as semiconductor fabtech, industry analysts, 

and articles in the trade press. The monthly ramp rate was applied from the 

first-quarter of silicon volume (FQSV), to determine the average design 

capacity over the 2006 period.

22 In 2006, the industry trend in co-owernship of manufacturing facilities 

continued. Several manufacturers, who are Partners, now operate fabs 

with other manufacturers, who in some cases are also Partners and in 

other cases not Partners. Special attention was given to this occurrence 

when estimating the Partner and non-Partner shares of U.S. layer-weighted 

manufacturing capacity.

23Two versions of PEVM are used to model non-Partner emissions during 

this period. For the years 2000 to 2003 PEVM v3.2.0506.0507 was used to 

estimate non-Partner emissions. During this time discrete devices did not use 

PFCs during manufacturing and, therefore, only memory and logic devices 

were modeled in the PEVM v3.2.0506.0507. From 2004 onwards discrete 

device fabrication started to use PFCs, hence PEVM v4.0.0701.0701, the 

first version of PEVM to account for PFC emissions from discrete devices, 

was used to estimate non-Partner emissions for this time period.

entire U.S. industry. This distribution was based upon the 

average PFC purchases by semiconductor manufacturers 

during this period and the application of IPCC default 

emission factors for each gas (Burton and Beizaie 2001). 

For the 2000 through 2006 period, the 1990 through 1999 

distribution was assumed to apply to the non-Partners. 

Partners, however, began to report gas-specific emissions 

during this period. Thus, gas specific emissions for 2000 

through 2006 were estimated by adding the emissions 

reported by the Partners to those estimated for the nonPartners.24

Data Sources

Partners estimate their emissions using a range of 

methods. For 2006, we assume that most Partners used 

a method as least as accurate as the IPCC’s Tier 2c 

Methodology, recommended in the IPCC (2000), since that 

has been their approach for the past several years. Although 

some of the default emission factors have been updated in 

the IPCC (2006) guidelines, as of the 2006 reporting year 

Partners continue to use the IPCC (2000) default emission 

factors.25 The Partners with relatively high emissions use 

leading-edge manufacturing technology, the newest process 

equipment. When purchased, this equipment is supplied with 

PFC emission factors, measured using industry standard 

guidelines (International Sematech, 2006). The larger 

emitting Partners likely use these process-specific emission 

factors instead of the less accurate default emission factors 

provided in IPCC guidelines; however, the documentation 

regarding Partner emissions is incomplete (Burton and 

Kshetry, 2007).

Data used to develop emission estimates were prepared 

in cooperation with the Partnership. Estimates of operating 

plant capacities and characteristics for Partners and nonPartners were derived from the Semiconductor Equipment 

and Materials Industry (SEMI) World Fab Watch (formerly 

International Fabs on Disk) database (1996 through 2007). 

Estimates of silicon consumed by linewidth from 1990 through 

2006 were derived from information from VLSI Research 

24 In recent years, the Partnership started reporting gas-specific emissions using 

GWP values from the Third Assessment Report (TAR), while in previous 

years the values were taken from the Second Assessment Report (SAR). The 

emissions reported here are restated using GWPs from the SAR.

25Currently, the majority of Partners use the IPCC (2000) Tier 2c guidelines, 

which most closely resemble the IPCC (2006) Tier 2a guidelines.
4-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

(2007), and the number of layers per linewidth was obtained 

from International Technology Roadmap for Semiconductors: 

2006 Update (Burton and Beizaie 2001, ITRS 2007).

Uncertainty

A quantitative uncertainty analysis26 of this source 

category was performed using the IPCC-recommended Tier 

2 uncertainty estimation methodology, the Monte Carlo 

Stochastic Simulation technique. The equation used to 

estimate uncertainty is:

United States emissions are equal to the summation of partnership gas-specific submittals plus open parenthesis non-Partner share of world total 

manufactured layer area close parenthesis multiplied by open parenthesis PFC emissions vintage model emission factor multiplied by world total 

manufactured layer area close parenthesis.

The Monte Carlo analysis results presented below relied 

on estimates of uncertainty attributed to the four quantities 

on the right side of the equation. Estimates of uncertainty for 

the four quantities were in turn developed using the estimated 

uncertainties associated with the individual inputs to each 

quantity, error propagation analysis, Monte Carlo simulation 

and expert judgment. The relative uncertainty associated 

with the world TMLA estimate in 2006 is approximately 

±10 percent, based on the uncertainty estimate obtained from 

discussions with VLSI, Inc. For the share of world layerweighted silicon capacity accounted for by non-Partners, a 

relative uncertainty of ±8 percent was estimated based on a 

separate Monte Carlo simulation to account for the random 

occurrence of missing data in the World Fab Watch database. 

For the aggregate PFC emissions data supplied to the 

partnership, a relative uncertainty of ±50 percent was estimated 

26 All uncertainties listed in this section are 95 percent confidence 

intervals.

for each gas-specific PFC emissions value reported by an 

individual Partner, and error propagation techniques were 

used to estimate uncertainty for total Partnership gas-specific 

submittals.27 A relative error of approximately 11 percent was 

estimated for the PEVM emission factor, based on the standard 

deviation of the 1996 to 1999 emission factors.28

Consideration was also given to the nature and 

magnitude of the potential bias that World activity data (i.e., 

world TMLA) might have in its estimates of the number 

of layers associated with devices manufactured at each 

technology node. The result of a brief analysis indicated that 

U.S. TMLA overstates the average number of layers across 

all product categories and all manufacturing technologies 

for 2004 by 0.12 layers or 2.9 percent. The same upward 

bias is assumed for world TMLA, and is represented in the 

uncertainty analysis by deducting the absolute bias value 

from the world activity estimate when it is incorporated into 

the Monte Carlo analysis.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-80. The emissions estimate for 

total U.S. PFC emissions from semiconductor manufacturing 

were estimated to be between 4.8 and 5.5 Tg CO2 Eq. at a 95 

percent confidence level. This range represents 10 percent 

below to 8 percent above the 2006 emission estimate of 

5.1 Tg CO2 Eq. This range and the associated percentages 

apply to the estimate of total emissions rather than those of 

individual gases. Uncertainties associated with individual 

gases will be somewhat higher than the aggregate, but were 

not explicitly modeled.

27Error propagation resulted in Partnership gas-specific uncertainties ranging 

from 17 to 33 percent.

28The average of 1996 to 1999 emission factor is used to derive the PEVM 

emission factor.

U.S. emissions = ∑Partnership gas-specific submittals +

(non-Partner share of world TMLA) ×

(PEVM emission factor × world TMLA)

Table 4-80: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor 

Manufacture (Tg CO2 Eq. and Percent)

2006 Emission Estimatea Uncertainty Range Relative to Emission Estimateb

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Boundc Upper Boundc Lower Bound Upper Bound

Semiconductor 

Manufacture

HFC, PFC, 

and SF6 5.1 4.8 5.5 -10% +8%

a Because the uncertainty analysis covered all emissions (including NF3), the emission estimate presented here does not match that shown in Table 4-78. b

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

c

 Absolute lower and upper bounds were calculated using the corresponding lower and upper bounds in percentages.
Industrial Processes 4-61

Planned Improvements

The method to estimate non-Partner related emissions 

(i.e., PEVM) is not expected to change (with the exception 

of possible future updates to emission factors and added 

technology nodes). Future improvements to the national 

emission estimates will primarily be associated with 

determining the portion of national emissions to attribute to 

Partner report totals (about 80 percent in recent years) and 

improvements in Partner emission reporting (e.g., adoption 

of the IPCC (2006) guidelines). As the nature of the Partner 

reports change through time and industry-wide reduction 

efforts increase, consideration will be given to what emission 

reduction efforts—if any—are likely to be occurring at nonPartner facilities. (Currently none are assumed to occur.)

4.22. Electrical Transmission 

and Distribution (IPCC Source 

Category 2F7)

The largest use of SF6, both in the United States and 

internationally, is as an electrical insulator and interrupter in 

equipment that transmits and distributes electricity (RAND 

2004). The gas has been employed by the electric power 

industry in the United States since the 1950s because of its 

dielectric strength and arc-quenching characteristics. It is 

used in gas-insulated substations, circuit breakers, and other 

switchgear. Sulfur hexafluoride has replaced flammable 

insulating oils in many applications and allows for more 

compact substations in dense urban areas.

Fugitive emissions of SF6 can escape from gas-insulated 

substations and switch gear through seals, especially from 

older equipment. The gas can also be released during 

equipment manufacturing, installation, servicing, and 

disposal. Emissions of SF6 from equipment manufacturing 

and from electrical transmission and distribution systems 

were estimated to be 13.2 Tg CO2 Eq. (0.6 Gg) in 2006. 

This quantity represents a 51 percent decrease from the 

estimate for 1990 (see Table 4-81 and Table 4-82). This 

decrease is believed to be a response to increases in the price 

of SF6 during the 1990s and to a growing awareness of the 

environmental impact of SF6 emissions, through programs 

such as the EPA’s SF6 Emission Reduction Partnership for 

Electric Power Systems.

Methodology

The estimates of emissions from electric transmission 

and distribution are comprised of emissions from electric 

power systems and emissions from the manufacture of 

electrical equipment. The methodologies for estimating both 

sets of emissions are described below.

1999 through 2006 Emissions from Electric Power Systems

Emissions from electric power systems from 1999 to 

2006 were estimated based on: (1) reporting from utilities 

participating in EPA’s SF6 Emission Reduction Partnership 

for Electric Power Systems (Partners), which began in 

1999; and, (2) the relationship between emissions and 

utilities’ transmission miles as reported in the 2001, 2004 

and 2007 Utility Data Institute (UDI) Directories of Electric 

Table 4-82: SF6 Emissions from Electric Power Systems 

and Electrical Equipment Manufacturers (Gg)

Year Emissions

1990 1.1

1995 0.9

2000 0.6

2001 0.6

2002 0.6

2003 0.6

2004 0.6

2005 0.6

2006 0.6

Table 4-81: SF6 Emissions from Electric Power Systems 

and Electrical Equipment Manufacturers (Tg CO2 Eq.)

Year

Electric 

Power 

Systems

Electrical 

Equipment 

Manufacturers

Total

1990 26.4 0.3 26.7

1995 20.9 0.5 21.5

2000 14.4 0.7 15.1

2001 14.5 0.6 15.0

2002 13.6 0.8 14.4

2003 13.2 0.7 13.8

2004 13.3 0.7 13.9

2005 13.2 0.8 14.0

2006 12.4 0.8 13.2
4-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Power Producers and Distributors (UDI 2001, 2004, 2007). 

(Transmission miles are defined as the miles of lines carrying 

voltages above 34.5 kV.) Over the period from 1999 to 2006, 

Partner utilities, which for inventory purposes are defined 

as utilities that either currently are or previously have been 

part of the Partnership, represented between 42 percent and 

46 percent of total U.S. transmission miles. For each year, 

the emissions reported by Partner utilities were added to the 

emissions estimated for utilities that have never participated 

in the Partnership (i.e., non-Partners).

Emissions from Partner utilities were estimated using a 

combination of reported data and, where reported data were 

unavailable, interpolated or extrapolated data. If a Partner 

utility did not provide data for a historical year, emissions 

were interpolated between years for which data were available 

or extrapolated based on Partner-specific transmission mile 

growth rates. In 2006, non-reporting Partners account for 

approximately 6 percent of the total emissions attributable 

to Partner utilities.

Emissions from non-Partners in every year since 1999 

were estimated using the results of a regression analysis 

that showed that the emissions from reporting utilities were 

most strongly correlated with their transmission miles. The 

results of this analysis are not surprising given that, in the 

United States, SF6 is contained primarily in transmission 

equipment rated at or above 34.5 kV. The equations were 

developed based on the 1999 SF6 emissions reported by 43 

Partner utilities (representing approximately 24 percent of 

U.S. transmission miles), and 2000 transmission mileage 

data obtained from the 2001 UDI Directory of Electric Power 

Producers and Distributors (UDI 2001). Two equations were 

developed, one for small and one for large utilities (i.e., with 

less or more than 10,000 transmission miles, respectively). 

The distinction between utility sizes was made because the 

regression analysis showed that the relationship between 

emissions and transmission miles differed for small and 

large transmission networks. The same equations were 

used to estimate non-Partner emissions in 1999 and every 

year thereafter because non-Partners were assumed not to 

have implemented any changes that would have resulted in 

reduced emissions since 1999.

The regression equations are:

Emissions in kilograms are equal to 0.88 multiplied by transmission miles.

Emissions in kilograms are equal to 0.58 multiplied by transmission miles.

Data on transmission miles for each non-Partner utility 

for the years 2000, 2003 and 2006 were obtained from the 

2001, 2004 and 2007 UDI Directories of Electric Power 

Producers and Distributors, respectively (UDI 2001, 2004, 

2007). The U.S. transmission system grew by over 22,000 

miles between 2000 and 2003 and by over 55,000 miles 

between 2003 and 2006. These periodic increases are 

assumed to have occurred gradually, therefore transmission 

mileage were assumed to increase at an annual rate of 1.2 

percent between 2000 and 2003 and 2.8 percent between 

2003 and 2006.

As a final step, total emissions were determined for 

each year by summing the Partner reported and estimated 

emissions (reported data was available through the EPA’s SF6

Emission Reduction Partnership for Electric Power Systems), 

and the non-Partner emissions (determined using the 1999 

regression equations).

1990 through 1998 Emissions from Electric Power Systems

Because most participating utilities reported emissions 

only for 1999 through 2006, modeling was used to estimate 

SF6 emissions from electric power systems for the years 

1990 through 1998. To perform this modeling, U.S. 

emissions were assumed to follow the same trajectory 

as global emissions from this source during the 1990 to 

1998 period. To estimate global emissions, the RAND 

survey of global SF6 sales were used, together with the 

following equation for estimating emissions, which is 

derived from the mass-balance equation for chemical 

emissions (Volume 3, Equation 7.3) in the IPCC Guidelines 

for National Greenhouse Gas Inventories (IPCC 2006). 

(Although equation 7.3 of the IPCC Guidelines appears 

in the discussion of substitutes for ozone depleting 

substances, it is applicable to emissions from any longNon-Partner small utilities (less than 10,000 transmission 

miles, in kilograms):

Emissions (kg) = 0.88 × Transmission Miles

Non-Partner large utilities (more than 10,000 transmission 

miles, in kilograms):

Emissions (kg) = 0.58 × Transmission Miles
Industrial Processes 4-63

lived pressurized equipment that is periodically serviced 

during its lifetime.)

Emissions in kilograms of sulfur hexafluoride are equal to the sum of sulfur hexafluoride purchased to 

the kilograms used to refill existing equipment and the nameplate capacity of retiring equipment.

Note that the above equation holds whether the gas 

from retiring equipment is released or recaptured; if the 

gas is recaptured, it is used to refill existing equipment, 

thereby lowering the amount of SF6 purchased by utilities 

for this purpose.

Sulfur hexafluoride purchased to refill existing 

equipment in a given year was assumed to be approximately 

equal to the SF6 purchased by utilities in that year. Gas 

purchases by utilities and equipment manufacturers 

from 1961 through 2003 are available from the RAND 

(2004) survey. To estimate the quantity of SF6 released or 

recovered from retiring equipment, the nameplate capacity 

of retiring equipment in a given year was assumed to equal 

81.2 percent of the amount of gas purchased by electrical 

equipment manufacturers 40 years previous (e.g., in 2000, 

the nameplate capacity of retiring equipment was assumed 

to equal 81.2 percent of the gas purchased in 1960). The 

remaining 18.8 percent was assumed to have been emitted 

at the time of manufacture. The 18.8 percent emission factor 

is an average of IPCC default SF6 emission rates for Europe 

and Japan for 1995 (IPCC 2006). The 40-year lifetime for 

electrical equipment is also based on IPCC (2006). The 

results of the two components of the above equation were 

then summed to yield estimates of global SF6 emissions 

from 1990 through 1998.

U.S. emissions between 1990 and 1998 are assumed to 

follow the same trajectory as global emissions during this 

period. To estimate U.S. emissions, global emissions for each 

year from 1990 through 1998 were divided by the estimated 

global emissions from 1999. The result was a time series of 

factors that express each year’s global emissions as a multiple 

of 1999 global emissions. Historical U.S. emissions were 

estimated by multiplying the factor for each respective year 

by the estimated U.S. emissions of SF6 from electric power 

systems in 1999 (estimated to be 15.0 Tg CO2 Eq.).

Two factors may affect the relationship between the 

RAND sales trends and actual global emission trends. One is 

utilities’ inventories of SF6 in storage containers. When SF6

prices rise, utilities are likely to deplete internal inventories 

before purchasing new SF6 at the higher price, in which case 

SF6 sales will fall more quickly than emissions. On the other 

hand, when SF6 prices fall, utilities are likely to purchase 

more SF6 to rebuild inventories, in which case sales will 

rise more quickly than emissions. This effect was accounted 

for by applying 3-year smoothing to utility SF6 sales data. 

The other factor that may affect the relationship between 

the RAND sales trends and actual global emissions is the 

level of imports from and exports to Russia and China. SF6

production in these countries is not included in the RAND 

survey, but may have been significant during the 1990 

through 1999 period. This factor was not accounted for; 

however, atmospheric studies confirmed that the downward 

trend in the estimated global emissions between 1995 and 

1998 was real (see the Uncertainty discussion below).

1990 through 2006 Emissions from Manufacture of 

Electrical Equipment

The 1990 to 2006 emissions estimates for original 

equipment manufacturers (OEMs) were derived by assuming 

that manufacturing emissions equal 10 percent of the 

quantity of SF6 charged into new equipment. The quantity 

of SF6 charged into new equipment was estimated based on 

statistics compiled by the National Electrical Manufacturers 

Association (NEMA). These statistics were provided for 1990 

to 2000; the quantities of SF6 charged into new equipment for 

2001 to 2006 were estimated using partner reported data and 

the total industry SF6 nameplate capacity estimate (128.4 Tg 

CO2 Eq. in 2006). Specifically, the ratio of new nameplate 

capacity to total nameplate capacity of a subset of Partners 

for which new nameplate capacity data was available from 

1999 to 2006 was calculated. This ratio was then multiplied 

by the total industry nameplate capacity estimate to derive 

the amount of SF6 charged into new equipment for the entire 

industry. The 10 percent emission rate is the average of 

the “ideal” and “realistic” manufacturing emission rates (4 

percent and 17 percent, respectively) identified in a paper 

prepared under the auspices of the International Council 

on Large Electric Systems (CIGRE) in February 2002 

(O’Connell et al. 2002).

Emissions (kilograms SF6) = SF6 purchased to refill 

existing equipment (kilograms) + nameplate capacity29

of retiring equipment (kilograms)

29 Nameplate capacity is defined as the amount of SF6 within fully charged 

electrical equipment.
4-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Uncertainty

To estimate the uncertainty associated with emissions of 

SF6 from electric transmission and distribution, uncertainties 

associated with three quantities were estimated: (1) emissions 

from Partners, (2) emissions from non-Partners, and (3) 

emissions from manufacturers of electrical equipment. A 

Monte Carlo analysis was then applied to estimate the overall 

uncertainty of the emissions estimate.

Total emissions from the SF6 Emission Reduction 

Partnership include emissions from both reporting and nonreporting Partners. For reporting partners, individual partnerreported SF6 data was assumed to have an uncertainty of 10 

percent. Based on a Monte Carlo analysis, the cumulative 

uncertainty of all partner reported data was estimated to be 

4.1 percent. The uncertainty associated with extrapolated 

or interpolated emissions from non-reporting Partners was 

assumed to be 20 percent.

There are two sources of uncertainty associated with 

the regression equations used to estimate emissions in 2006 

from non-partners: (1) uncertainty in the coefficients (as 

defined by the regression standard error estimate), and (2) the 

uncertainty in total transmission miles for non-Partners. In 

addition, there is uncertainty associated with the assumption 

that the emission factor used for non-Partner utilities (which 

accounted for approximately 58 percent of U.S. transmission 

miles in 2006) will remain at levels defined by Partners who 

reported in 1999. However, the last source of uncertainty 

was not modeled.

Uncertainties were also estimated regarding the quantity 

of SF6 charged into equipment by equipment manufacturers, 

which is projected from Partner provided nameplate capacity 

data and industry SF6 nameplate capacity estimates, and the 

manufacturers’ SF6 emissions rate.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 4-83. Electrical Transmission and 

Distribution SF6 emissions were estimated to be between 11.1 

and 15.4 Tg CO2 Eq. at the 95 percent confidence level. This 

indicates a range of approximately 16 percent below and 17 

percent above the emission estimate of 13.2 Tg CO2 Eq.

In addition to the uncertainty quantified above, there 

is uncertainty associated with using global SF6 sales data 

to estimate U.S. emission trends from 1990 through 1999. 

However, the trend in global emissions implied by sales of 

SF6 appears to reflect the trend in global emissions implied 

by changing SF6 concentrations in the atmosphere. That 

is, emissions based on global sales declined by 29 percent 

between 1995 and 1998, and emissions based on atmospheric 

measurements declined by 27 percent over the same period. 

However, U.S. emission patterns may differ from global 

emission patterns.

Recalculations Discussion

Relative to the previous Inventory report, SF6 emission 

estimates for the period 1990 through 2006 were updated 

based on (1) new data from EPA’s SF6 Emission Reduction 

Partnership, (2) revisions to the assumptions used in 

interpolating and extrapolating non-reported Partner data, (3) 

new information on transmission mile growth available in the 

UDI 2007 database, (4) removal of double counting between 

parent companies and their subsidiaries in UDI databases, and 

(5) revision in the methodology for estimating 2001 to 2006 

OEM emissions. For the period 1999 through 2006, estimates 

have been revised to incorporate additional data from new 

Partners. Additionally, Partner estimates are now based on 

Partner-specific transmission mile growth rates, obtained via 

the UDI 2001, 2004, and 2007 databases. Partner data and the 

industry SF6 nameplate capacity estimates are now used to 

estimate OEM emissions from 2001 onwards, since NEMA 

data for these years does not exist. Based on the revisions 

listed above, SF6 emissions from electric transmission and 

distribution decreased from 1990 to 2000 and in 2003 and 

Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and 

Distribution (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Electrical Transmission 

and Distribution SF6 13.2 11.1 15.4 -16% +17%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Industrial Processes 4-65

increased in 2002, 2004 and 2005, compared to the 1990 to 

2005 Inventory. The magnitude of the differences between 

the 1990 to 2005 inventory estimates and this year’s estimates 

varied by year and ranged from 0 to 6 percent.

Emissions of HFCs, PFCs and SF6 from industrial processes can be estimated in two ways, either as potential emissions or as actual 

emissions. Emission estimates in this chapter are “actual emissions,” which are defined by the Revised 1996 IPCC Guidelines for National 

Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) as estimates that take into account the time lag between consumption and 

emissions. In contrast, “potential emissions” are defined to be equal to the amount of a chemical consumed in a country, minus the amount 

of a chemical recovered for destruction or export in the year of consideration. Potential emissions will generally be greater for a given year 

than actual emissions, since some amount of chemical consumed will be stored in products or equipment and will not be emitted to the 

atmosphere until a later date, if ever. Although actual emissions are considered to be the more accurate estimation approach for a single 

year, estimates of potential emissions are provided for informational purposes.

Separate estimates of potential emissions were not made for industrial processes that fall into the following categories:

• Byproduct emissions. Some emissions do not result from the consumption or use of a chemical, but are the unintended byproducts 

of another process. For such emissions, which include emissions of CF4 and C2F6 from aluminum production and of HFC-23 from 

HCFC-22 production, the distinction between potential and actual emissions is not relevant.

• Potential emissions that equal actual emissions. For some sources, such as magnesium production and processing, no delay 

between consumption and emission is assumed and, consequently, no destruction of the chemical takes place. In this case, actual 

emissions equal potential emissions.

Table 4-84 presents potential emission estimates for HFCs and PFCs from the substitution of ozone depleting substances, HFCs, PFCs, 

and SF6 from semiconductor manufacture, and SF6 from magnesium production and processing and electrical transmission and distribution.30

Potential emissions associated with the substitution for ozone depleting substances were calculated using the EPA’s Vintaging Model. 

Estimates of HFCs, PFCs, and SF6 consumed by semiconductor manufacture were developed by dividing chemical-by-chemical emissions 

by the appropriate chemical-specific emission factors from the IPCC Good Practice Guidance (Tier 2c). Estimates of CF4 consumption were 

adjusted to account for the conversion of other chemicals into CF4 during the semiconductor manufacturing process, again using the default 

factors from the IPCC Good Practice Guidance. Potential SF6 emission estimates for electrical transmission and distribution were developed 

using U.S. utility purchases of SF6 for electrical equipment. From 1999 through 2006, estimates were obtained from reports submitted by 

participants in EPA’s SF6 Emission Reduction Program for Electric Power Systems. U.S. utility purchases of SF6 for electrical equipment from 

1990 through 1998 were backcasted based on world sales of SF6 to utilities. Purchases of SF6 by utilities were added to SF6 purchases by 

electrical equipment manufacturers to obtain total SF6 purchases by the electrical equipment sector.

30 See Annex 5 for a discussion of sources of SF6 emissions excluded from the actual emissions estimates in this report.

Table 4-84: 2006 Potential and Actual Emissions of HFCs, PFCs, and SF6

from Selected Sources (Tg CO2 Eq.)

Source Potential Actual

Substitution of Ozone Depleting Substances 182.1 110.4

Aluminum Production - 2.5

HCFC-22 Production - 13.8

Semiconductor Manufacture 7.6 4.8

Magnesium Production and Processing 3.2 3.2

Electrical Transmission and Distribution 22.6 13.2

- Not applicable.

Box 4-1: Potential Emission Estimates of HFCs, PFCs, and SF6
4-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

4.23. Industrial Sources of Indirect 

Greenhouse Gases

In addition to the main greenhouse gases addressed 

above, many industrial processes generate emissions of 

indirect greenhouse gases. Total emissions of nitrogen 

oxides (NOx), carbon monoxide (CO), and non-CH4 volatile 

organic compounds (NMVOCs) from non-energy industrial 

processes from 1990 to 2006 are reported in Table 4-85.

Methodology

These emission estimates were obtained from preliminary 

data (EPA 2008), and disaggregated based on EPA (2003), 

which, in its final iteration, will be published on the National 

Emission Inventory (NEI) Air Pollutant Emission Trends 

web site. Emissions were calculated either for individual 

categories or for many categories combined, using basic 

activity data (e.g., the amount of raw material processed) 

as an indicator of emissions. National activity data were 

collected for individual categories from various agencies. 

Depending on the category, these basic activity data may 

include data on production, fuel deliveries, raw material 

processed, etc.

Activity data were used in conjunction with emission 

factors, which together relate the quantity of emissions to the 

activity. Emission factors are generally available from the 

EPA’s Compilation of Air Pollutant Emission Factors, AP-42 

(EPA 1997). The EPA currently derives the overall emission 

control efficiency of a source category from a variety of 

information sources, including published reports, the 1985 

National Acid Precipitation and Assessment Program 

emissions inventory, and other EPA databases.

Uncertainty

Uncertainties in these estimates are partly due to the 

accuracy of the emission factors used and accurate estimates 

of activity data. A quantitative uncertainty analysis was 

not performed.

Table 4-85: NOx, CO, and NMVOC Emissions from Industrial Processes (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

NOx 591 607 626 656 534 528 524 519 515

Other Industrial Processes 343 362 434 457 390 385 381 377 373

Chemical & Allied Product Manufacturing 152 143 95 97 63 61 61 61 61

Metals Processing 88 89 81 86 63 63 63 63 62

Storage and Transport 3 5 14 15 17 17 17 17 17

Miscellaneous* 5 8 2 1 2 1 1 1 1

CO 4,125 3,959 2,217 2,339 1,744 1,724 1,724 1,724 1,724

Metals Processing 2,395 2,159 1,175 1,252 895 895 895 895 895

Other Industrial Processes 487 566 538 558 444 444 444 443 443

Chemical & Allied Product Manufacturing 1,073 1,110 327 338 258 257 257 257 257

Storage and Transport 69 23 154 162 107 107 107 107 107

Miscellaneous* 101 102 23 30 39 22 22 22 22

NMVOCs 2,422 2,642 1,773 1,769 2,036 1,972 1,931 1,890 1,849

Storage and Transport 1,352 1,499 1,067 1,082 1,346 1,304 1,274 1,245 1,215

Other Industrial Processes 364 408 412 381 401 394 386 379 372

Chemical & Allied Product Manufacturing 575 599 230 238 226 223 220 217 214

Metals Processing 111 113 61 65 42 42 42 42 41

Miscellaneous* 20 23 3 4 20 10 9 8 7

* Miscellaneous includes the following categories: catastrophic/accidental release, other combustion, health services, cooling towers, and fugitive dust. 

It does not include agricultural fires or slash/prescribed burning, which are accounted for under the Field Burning of Agricultural Residues source.

Note: Totals may not sum due to independent rounding.
Solvent and Other Product Use 5-1

5. Solvent and Other Product Use

G

reenhouse gas emissions are produced as a byproduct of various solvent and other product uses. In the United 

States, emissions from Nitrous Oxide (N2O) Product Usage, the only source of greenhouse gas emissions from 

this sector, accounted for less than 0.1 percent of total U.S. anthropogenic greenhouse gas emissions on a carbon 

equivalent basis in 2006 (see Table 5-1). Indirect greenhouse gas emissions also result from solvent and other product use, 

and are presented in Table 5-5 in gigagrams (Gg). 

5.1. Nitrous Oxide from Product Uses (IPCC Source Category 3D)

N2O is a clear, colorless, oxidizing liquefied gas, with a slightly sweet odor. Two companies operate a total of five N2O 

production facilities in the United States (CGA 2003). N2O is primarily used in carrier gases with oxygen to administer 

more potent inhalation anesthetics for general anesthesia and as an anesthetic in various dental and veterinary applications. 

As such, it is used to treat short-term pain, for sedation in minor elective surgeries, and as an induction anesthetic. The 

second main use of N2O is as a propellant in pressure and aerosol products, the largest application being pressure-packaged 

whipped cream. Small quantities of N2O also are used in the following applications:

•	 Oxidizing agent and etchant used in semiconductor manufacturing;

•	 Oxidizing agent used, with acetylene, in atomic absorption spectrometry;

•	 Production of sodium azide, which is used to inflate airbags;

•	 Fuel oxidant in auto racing; and

•	 Oxidizing agent in blowtorches used by jewelers and others (Heydorn 1997). 

Production of N2O in 2006 was approximately 15 Gg. N2O emissions were 4.4 Tg CO2 Eq. (14 Gg) in 2006 (see Table 

5-3). Production of N2O stabilized during the 1990s because medical markets had found other substitutes for anesthetics, 

and more medical procedures were being performed on an outpatient basis using local anesthetics that do not require N2O. 

The use of N2O as a propellant for whipped cream has also stabilized due to the increased popularity of cream products 

packaged in reusable plastic tubs (Heydorn 1997). 

Table 5-1: N2O Emissions from Solvent and Other Product Use (Tg CO2 Eq. and Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

N2O from Product Uses

Tg CO2 Eq. 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4 

Gg 14 15 16 16 14 14 14 14 14
5-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 5-3: N2O Production (Gg)

Year Gg

1990 16

1995 17

2000 17

2001 17

2002 15

2003 15

2004 15

2005 15

2006 15

Table 5-2: N2O Emissions from N2O Product Uses 

(Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 4.4 14

1995 4.6 15

2000 4.9 16

2001 4.9 16

2002 4.4 14

2003 4.4 14

2004 4.4 14

2005 4.4 14

2006 4.4 14

Methodology

Emissions from N2O product uses were calculated by first 

multiplying the total amount of N2O produced in the United 

States by the share of the total quantity of N2O attributed to 

each end use. This value was then multiplied by the associated 

emission rate for each end use. After the emissions were 

calculated for each end use, they were added together to obtain 

a total estimate of N2O product usage emissions. Emissions 

were determined using the following equation:

 

 

 

 

The share of total quantity of N2O usage by end use 

represents the share of national N2O produced that is 

used by the specific subcategory (i.e., anesthesia, food 

processing, etc.). In 2006, the medical/dental industry 

used an estimated 89.5 percent of total N2O produced, 

followed by food processing propellants at 6.5 percent. 

All other categories combined used the remainder of the 

N2O produced. This subcategory breakdown has changed 

only slightly over the past decade. For instance, the small 

share of N2O usage in the production of sodium azide has 

declined significantly during the decade of the 1990s. Due 

to the lack of information on the specific time period of 

the phase-out in this market subcategory, most of the N2O 

usage for sodium azide production is assumed to have 

ceased after 1996, with the majority of its small share of the 

market assigned to the larger medical/dental consumption 

subcategory (Heydorn 1997). The N2O was allocated 

across the following categories: medical applications, food 

processing propellant, and sodium azide production (pre1996). A usage emissions rate was then applied for each 

sector to estimate the amount of N2O emitted.

Only the medical/dental and food propellant subcategories 

were estimated to release emissions into the atmosphere, 

and therefore these subcategories were the only usage 

subcategories with emission rates. For the medical/dental 

subcategory, due to the poor solubility of N2O in blood and 

other tissues, none of the N2O is assumed to be metabolized 

during anesthesia and quickly leaves the body in exhaled 

breath. Therefore, an emission factor of 100 percent was 

used for this subcategory (IPCC 2006). For N2O used as a 

propellant in pressurized and aerosol food products, none of 

the N2O is reacted during the process and all of the N2O is 

emitted to the atmosphere, resulting in an emissions factor 

of 100 percent for this subcategory (IPCC 2006). For the 

remaining subcategories, all of the N2O is consumed/reacted 

during the process, and therefore the emissions rate was 

considered to be zero percent (Tupman 2002). 

The 1990 through 1992 N2O production data were 

obtained from SRI Consulting’s Nitrous Oxide, North 

America report (Heydorn 1997). N2O production data for 

1993 through 1995 were not available. Production data for 

1996 was specified as a range in two data sources (Heydorn 

1997, Tupman 2002). In particular, for 1996, Heydorn 

(1997) estimates N2O production to range between 13.6 

and 18.1 thousand metric tons. Tupman (2003) provided a 

narrower range (i.e., 15.9 to 18.1 thousand metric tons) for 

N2O Product Uses Emissions =

∑i [Total U.S. Production of N2O] ×

[Share of Total Quantity of N2O Usage by Sector i] ×

[Emissions Rate for Sector i],

where,

i = sector.
Solvent and Other Product Use 5-3

1996 that falls within the production bounds described by 

Heydorn (1997). Tupman (2003) data are considered more 

industry specific and current. Therefore, the midpoint of 

the narrower production range was used to estimate N2O 

emissions for years 1993 through 2001 (Tupman 2003). The 

2002 and 2003 N2O production data were obtained from 

the Compressed Gas Association Nitrous Oxide Fact Sheet 

and Nitrous Oxide Abuse Hotline (CGA 2002, 2003). These 

data were also provided as a range. For example, in 2003, 

CGA (2003) estimates N2O production to range between 

13.6 and 15.9 thousand metric tons. Due to unavailable 

data, production for 2004, 2005, and 2006 were held at 

the 2003 value.

The 1996 share of the total quantity of N2O used by 

each subcategory was obtained from SRI Consulting’s 

Nitrous Oxide, North America report (Heydorn 1997). The 

1990 through 1995 share of total quantity of N2O used by 

each subcategory was kept the same as the 1996 number 

provided by SRI Consulting. The 1997 through 2001 share 

of total quantity of N2O usage by sector was obtained from 

communication with a N2O industry expert (Tupman 2002). 

The 2002 and 2003 share of total quantity of N2O usage 

by sector was obtained from CGA (2002, 2003). Due to 

unavailable data, the share of total quantity of N2O usage 

data for 2004, 2005, and 2006 was assumed to equal the 2003 

value. The emissions rate for the food processing propellant 

industry was obtained from SRI Consulting’s Nitrous Oxide, 

North America report (Heydorn 1997), and confirmed by a 

N2O industry expert (Tupman 2002). The emissions rate for 

all other subcategories was obtained from communication 

with a N2O industry expert (Tupman 2002). The emissions 

rate for the medical/dental subcategory was obtained from 

the 2006 IPCC Guidelines.

Uncertainty

The overall uncertainty associated with the 2006 N2O 

emission estimate from N2O product uses was calculated 

using the IPCC Guidelines for National Greenhouse 

Gas Inventories (2006) Tier 2 methodology. Uncertainty 

associated with the parameters used to estimate N2O 

emissions included that of production data, total market 

share of each end use, and the emission factors applied to 

each end use, respectively. 

The results of this Tier 2 quantitative uncertainty 

analysis are summarized in Table 5-4. N2O emissions from 

N2O product uses were estimated to be between 4.3 and 4.5 

Tg CO2 Eq. at the 95 percent confidence level (or in 19 out 

of 20 Monte Carlo Stochastic Simulations). This indicates a 

range of approximately 2 percent below to 2 percent above 

the 2006 emissions estimate of 4.4 Tg CO2 Eq. 

Recalculations Discussion

The N2O emission factor for medical applications has been 

updated relative to the previous Inventory based on the revised 

IPCC Guidelines for National Greenhouse Gas Inventories 

(2006). The updated emission factor resulted in an average 

increase in N2O emissions from N2O product uses relative to 

the previous Inventory for each year in the 1990 through 2005 

time series of 0.1 Tg CO2 Eq. (2 percent), respectively.

Planned Improvements

Planned improvements include a continued evaluation 

of alternative production statistics for cross verification and 

a reassessment of subcategory usage to accurately represent 

the latest trends in the product usage, and investigation 

of production and use cycles and the potential need to 

Table 5-4: Tier 2 Quantitative Uncertainty Estimates for N2O Emissions From N2O Product Uses 

(Tg CO2 Eq. and Percent) 

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

N2O Product Usage N2O 4.4 4.3 4.5 -2% +2%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
5-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

incorporate a time lag between production and ultimate 

product use and resulting release of N2O.

5.2. Indirect Greenhouse Gas 

Emissions from Solvent Use

The use of solvents and other chemical products can 

result in emissions of various ozone precursors (i.e., indirect 

greenhouse gases).1 Non-CH4 volatile organic compounds 

(NMVOCs), commonly referred to as "hydrocarbons," are 

the primary gases emitted from most processes employing 

organic or petroleum based solvents. As some of industrial 

applications also employ thermal incineration as a control 

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.

technology, combustion byproducts, such as carbon 

monoxide (CO) and nitrogen oxides (NOx), are also reported 

with this source category. In the United States, emissions 

from solvents are primarily the result of solvent evaporation, 

whereby the lighter hydrocarbon molecules in the solvents 

escape into the atmosphere. The evaporation process varies 

depending on different solvent uses and solvent types. The 

major categories of solvent uses include: degreasing, graphic 

arts, surface coating, other industrial uses of solvents (i.e., 

electronics, etc.), dry cleaning, and non-industrial uses (i.e., 

uses of paint thinner, etc.). 

Total emissions of NOx, NMVOCs, and CO from 1990 

to 2006 are reported in Table 5-5.

Table 5-5: Emissions of NOx, CO, and NMVOC from Solvent Use (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

NOx 1 3 3 3 5 5 5 5 5 

Surface Coating 1 2 3 3 5 5 5 5 5 

Graphic Arts + 1 + + + + + + + 

Degreasing + + + + + + + + + 

Dry Cleaning + + + + + + + + + 

Other Industrial Processesa + + + + + + + + + 

Non-Industrial Processesb + + + + + + + + + 

Other NA + + + + + + + + 

CO 5 5 46 45 1 1 1 1 1 

Surface Coating + 1 46 45 1 1 1 1 1 

Other Industrial Processesa 4 3 + + + + + + + 

Dry Cleaning + 1 + + + + + + + 

Degreasing + + + + + + + + + 

Graphic Arts + + + + + + + + + 

Non-Industrial Processesb + + + + + + + + + 

Other NA NA + + + + + + + 

NMVOCs 5,216 5,609 4,384 4,547 3,881 3,862 3,854 3,846 3,839 

Surface Coating 2,289 2,432 1,767 1,863 1,590 1,582 1,579 1,576 1,573 

Non-Industrial Processesb 1,724 1,858 1,676 1,707 1,457 1,450 1,447 1,444 1,441 

Degreasing 675 716 316 331 283 281 281 280 280 

Dry Cleaning 195 209 265 272 232 231 230 230 229 

Graphic Arts 249 307 222 229 195 194 194 193 193 

Other Industrial Processesa 85 87 98 103 88 88 88 88 87 

Other + + 40 42 36 36 36 36 36 

a

 Includes rubber and plastics manufacturing, and other miscellaneous applications.

b

 Includes cutback asphalt, pesticide application adhesives, consumer solvents, and other miscellaneous applications.

Note: Totals may not sum due to independent rounding.

+ Does not exceed 0.5 Gg.
Solvent and Other Product Use 5-5

Methodology

Emissions were calculated by aggregating solvent use data 

based on information relating to solvent uses from different 

applications such as degreasing, graphic arts, etc. Emission 

factors for each consumption category were then applied to 

the data to estimate emissions. For example, emissions from 

surface coatings were mostly due to solvent evaporation as the 

coatings solidify. By applying the appropriate solvent-specific 

emission factors to the amount of solvents used for surface 

coatings, an estimate of emissions was obtained. Emissions 

of CO and NOx result primarily from thermal and catalytic 

incineration of solvent-laden gas streams from painting booths, 

printing operations, and oven exhaust.

These emission estimates were obtained from preliminary 

data (EPA 2008), and disaggregated based on EPA (2003), 

which, in its final iteration, will be published on the National 

Emission Inventory (NEI) Air Pollutant Emission Trends 

web site. Emissions were calculated either for individual 

categories or for many categories combined, using basic 

activity data (e.g., the amount of solvent purchased) as an 

indicator of emissions. National activity data were collected 

for individual applications from various agencies.

Activity data were used in conjunction with emission 

factors, which together relate the quantity of emissions to the 

activity. Emission factors are generally available from the 

EPA’s Compilation of Air Pollutant Emission Factors, AP-42 

(EPA 1997). The EPA currently derives the overall emission 

control efficiency of a source category from a variety of 

information sources, including published reports, the 1985 

National Acid Precipitation and Assessment Program 

emissions inventory, and other EPA databases.

Uncertainty

Uncertainties in these estimates are partly due to the 

accuracy of the emission factors used and the reliability of 

correlations between activity data and actual emissions.
Agriculture 6-1

6. Agriculture

A

gricultural 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 agriculturerelated land-use activities, such as conversion of grassland 

to cultivated land, are presented in the Land Use, Land-Use 

Change, and Forestry chapter. CO2 emissions from on-farm 

energy use are accounted for in the Energy chapter.

In 2006, the Agricultural sector was responsible for 

emissions of 454.1 teragrams of CO2 equivalents (Tg CO2

Eq.), or 6 percent of total U.S. greenhouse gas emissions. 

Methane (CH4) and nitrous oxide (N2O) were the primary 

greenhouse gases emitted by agricultural activities. CH4

emissions from enteric fermentation and manure management 

represent about 23 percent and 7 percent of total CH4

emissions from anthropogenic activities, respectively. Of all 

domestic animal types, beef and dairy cattle were by far the 

largest emitters of CH4. Rice cultivation and field burning of 

agricultural residues were minor sources of CH4. Agricultural 

soil management activities such as fertilizer application and 

Table 6-1: Emissions from Agriculture (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 165.7 175.8 171.7 172.2 172.6 173.0 170.9 174.0 174.4 

Enteric Fermentation 126.9 132.3 124.6 123.6 123.8 124.6 122.4 124.5 126.2 

Manure Management 31.0 35.2 38.8 40.2 41.3 40.7 40.1 41.8 41.4 

Rice Cultivation 7.1 7.6 7.5 7.6 6.8 6.9 7.6 6.8 5.9 

Field Burning of Agricultural Residues 0.7 0.7 0.8 0.8 0.7 0.8 0.9 0.9 0.8 

N2O 281.8 278.0 276.3 291.5 276.4 261.3 261.2 279.6 279.8 

Agricultural Soil Management 269.4 264.8 262.1 277.0 262.0 247.3 246.9 265.2 265.0 

Manure Management 12.1 12.8 13.7 14.0 14.0 13.6 13.8 13.9 14.3 

Field Burning of Agricultural Residues 0.4 0.4 0.5 0.5 0.4 0.4 0.5 0.5 0.5 

Total 447.5 453.8 447.9 463.7 449.0 434.3 432.1 453.6 454.1 

Note: Totals may not sum due to independent rounding.

Figure 6-1

2006 Agriculture Chapter Greenhouse Gas 

Emission Sources

0 50 200

Rice Cultivation

Manure Management

Field Burning of

Agricultural Residues

Enteric Fermentation

Agricultural Soil Management

Tg CO2 Eq.

Agriculture

as a Portion of

all Emissions

100 150

265.0

6.4%
6-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

other cropping practices were the largest source of U.S. N2O 

emissions, accounting for 72 percent. Manure management 

and field burning of agricultural residues were also small 

sources of N2O emissions.

Table 6-1 and Table 6-2 present emission estimates 

for the Agriculture sector. Between 1990 and 2006, CH4

emissions from agricultural activities increased by 5 percent, 

while N2O emissions fluctuated from year to year, but overall 

decreased by less than 1 percent. 

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 byproduct, which 

can be exhaled or eructated by the animal. The amount of 

CH4 produced and emitted by an individual animal depends 

primarily upon the animal’s digestive system, and the amount 

and type of feed it consumes. 

Ruminant animals (e.g., cattle, buffalo, sheep, goats, and 

camels) are the major emitters of CH4 because of their unique 

digestive system. Ruminants possess a rumen, or large “forestomach,” 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 nonruminant animals cannot. Ruminant animals, consequently, 

have the highest CH4 emissions among all animal types.

Non-ruminant animals (e.g., swine, horses, and mules) 

also produce CH4 emissions through enteric fermentation, 

although this microbial fermentation occurs in the large 

intestine. These non-ruminants emit significantly less CH4

on a per-animal basis than ruminants because the capacity 

of the large intestine to produce CH4 is lower.

In addition to the type of digestive system, an animal’s 

feed quality and feed intake also affects CH4 emissions. In 

general, lower feed quality and/or higher feed intake lead to 

higher CH4 emissions. Feed intake is positively correlated 

to animal size, growth rate, and production (e.g., milk 

production, wool growth, pregnancy, or work). Therefore, 

feed intake varies among animal types as well as among 

different management practices for individual animal types 

(e.g., animals in feedlots or grazing on pasture).

CH4 emission estimates from enteric fermentation are 

provided in Table 6-3 and Table 6-4. Total livestock CH4

emissions in 2006 were 126.2 Tg CO2 Eq. (6,010 Gg). Beef 

cattle remain the largest contributor of CH4 emissions from 

enteric fermentation, accounting for 71 percent in 2006. 

Emissions from dairy cattle in 2006 accounted for 24 percent, 

and the remaining emissions were from horses, sheep, swine, 

and goats.

From 1990 to 2006, emissions from enteric fermentation 

have decreased by less than 1 percent. Generally, emissions 

have been decreasing since 1995 to 2004, mainly due to 

decreasing populations of both beef and dairy cattle and 

improved feed quality for feedlot cattle. The last two years 

have shown an increase in emissions. During this timeframe, 

populations of sheep have decreased 45 percent since 1990 

while horse populations have increased over 80 percent, 

Table 6-2: Emissions from Agriculture (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 7,890 8,373 8,174 8,201 8,219 8,236 8,138 8,284 8,304 

Enteric Fermentation 6,044 6,302 5,933 5,886 5,896 5,931 5,828 5,928 6,010 

Manure Management 1,474 1,676 1,847 1,915 1,964 1,938 1,908 1,988 1,972 

Rice Cultivation 339 363 357 364 325 328 360 326 282 

Field Burning of Agricultural Residues 33 32 38 37 34 38 42 41 39 

N2O 909 897 891 940 892 843 842 902 902 

Agricultural Soil Management 869 854 845 894 845 798 796 855 855 

Manure Management 39 41 44 45 45 44 44 45 46 

Field Burning of Agricultural Residues 1 1 1 1 1 1 2 2 2 

Note: Totals may not sum due to independent rounding.
Agriculture 6-3

mostly over the last 5 years. Goat and swine populations 

have increased 1 percent and 14 percent, respectively, during 

this timeframe. 

Methodology

Livestock emission estimates fall into two categories: 

cattle and other domesticated animals. Cattle, due to 

their large population, large size, and particular digestive 

characteristics, account for the majority of CH4 emissions 

from livestock in the United States. A more detailed 

methodology (i.e., IPCC Tier 2) was therefore applied to 

estimate emissions for all cattle except for bulls. Emission 

estimates for other domesticated animals (horses, sheep, 

swine, goats, and bulls) were handled using a less detailed 

approach (i.e., IPCC Tier 1). 

While the large diversity of animal management practices 

cannot be precisely characterized and evaluated, significant 

scientific literature exists that describes the quantity of CH4

produced by individual ruminant animals, particularly cattle. 

The Cattle Enteric Fermentation Model (CEFM), developed 

by EPA to estimate cattle enteric CH4 emissions, incorporates 

this information and other analyses of livestock population, 

feeding practices and production characteristics were used 

to estimate emissions from cattle populations. 

National cattle population statistics were disaggregated 

into the following cattle sub-populations: 

• Dairy Cattle

• Calves

• Heifer Replacements 

• Cows

• Beef Cattle

• Calves

• Heifer Replacements

• Heifer and Steer Stockers

• Animals in Feedlots (Heifers and Steers)

• Cows

• Bulls

Calf birth rates, end of year population statistics, detailed 

feedlot placement information, and slaughter weight data 

were used to create a transition matrix that models cohorts of 

individual animal types and their specific emission profiles. 

The key variables tracked for each of the cattle population 

Table 6-3: CH4 Emissions from Enteric Fermentation (Tg CO2 Eq.)

Livestock Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Beef Cattle 89.9 96.9 90.4 89.4 89.3 89.5 87.2 88.2 89.2

Dairy Cattle 31.2 29.9 28.9 28.8 29.0 29.2 28.9 29.6 30.3

Horses 1.9 1.9 2.0 2.1 2.3 2.6 3.0 3.5 3.5

Sheep 1.9 1.5 1.2 1.2 1.1 1.1 1.0 1.0 1.0

Swine 1.7 1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9

Goats 0.3 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3

Total 126.9 132.3 124.6 123.6 123.8 124.6 122.4 124.5 126.2

Note: Totals may not sum due to independent rounding.

Table 6-4: CH4 Emissions from Enteric Fermentation (Gg)

Livestock Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Beef Cattle 4,281 4,616 4,304 4,257 4,251 4,260 4,155 4,198 4,249

Dairy Cattle 1,488 1,422 1,377 1,374 1,381 1,393 1,377 1,411 1,441

Horses 91 92 94 99 108 126 144 166 166

Sheep 91 72 56 55 53 51 49 49 50

Swine 81 88 88 88 90 90 91 92 93

Goats 13 12 12 12 13 13 13 13 13

Total 6,044 6,302 5,933 5,886 5,896 5,931 5,828 5,928 6,010

Note: Totals may not sum due to independent rounding.
6-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

categories are described in Annex 3.9. These variables 

include performance factors such as pregnancy and lactation 

as well as average weights and weight gain. Annual cattle 

population data were obtained from the U.S. Department 

of Agriculture’s (USDA) National Agricultural Statistics 

Service Quick Stats database (USDA 2007). 

Diet characteristics were estimated by region for U.S. 

dairy, beef, and feedlot cattle. These estimates were used 

to calculate Digestible Energy (DE) values (expressed as 

the percent of gross energy intake digested by the animal) 

and CH4 conversion rates (Ym) (expressed as the fraction of 

gross energy converted to CH4) for each population category. 

The IPCC recommends Ym values of 3.0±1.0 percent for 

feedlot cattle and 6.5±1.0 percent for other well-fed cattle 

consuming temperate-climate feed types (IPCC 2006). Given 

the availability of detailed diet information for different regions 

and animal types in the United States, DE and Ym values 

unique to the United States were developed, rather than using 

the recommended IPCC values. The diet characterizations and 

estimation of DE and Ym values were based on information 

from state agricultural extension specialists, a review of 

published forage quality studies, expert opinion, and modeling 

of animal physiology. The diet characteristics for dairy cattle 

were from Donovan (1999), while those for beef cattle were 

derived from NRC (2000). DE and Ym for dairy cows were 

calculated from diet characteristics using a model simulating 

ruminant digestion in growing and/or lactating cattle (Donovan 

and Baldwin 1999). For feedlot animals, DE and Ym values 

recommended by Johnson (1999) were used. Values from EPA 

(1993) were used for dairy replacement heifers. For grazing 

beef cattle, DE values were based on diet information in 

NRC (2000) and Ym values were based on Johnson (2002). 

Weight data were estimated from Feedstuffs (1998), Western 

Dairyman (1998), and expert opinion. See Annex 3.9 for more 

details on the method used to characterize cattle diets in the 

United States.

To estimate CH4 emissions from all cattle types except 

bulls and calves younger than 7 months,1 the population 

was divided into state, age, sub-type (e.g., dairy cows 

and replacements, beef cows and replacements, heifer 

and steer stockers, and heifer and steer in feedlots), and 

1Emissions from bulls are estimated using a Tier 1 approach because it is 

assumed there is minimal variation in population and diets; calves younger 

than 7 months are assumed to emit little or no CH4.

production (e.g., pregnant, lactating) groupings to more 

fully capture differences in CH4 emissions from these 

animal types. The transition matrix was used to simulate 

the age and weight structure of each sub-type on a monthly 

basis, to more accurately reflect the fluctuations that occur 

throughout the year. Cattle diet characteristics were then 

used in conjunction with Tier 2 equations from IPCC 

(2006) to produce CH4 emission factors for the following 

cattle types: dairy cows, beef cows, dairy replacements, 

beef replacements, steer stockers, heifer stockers, steer 

feedlot animals, and heifer feedlot animals. To estimate 

emissions from cattle, population data were multiplied by 

the emission factor for each cattle type. More details are 

provided in Annex 3.9.

Emission estimates for other animal types were based on 

average emission factors representative of entire populations 

of each animal type. CH4 emissions from these animals 

accounted for a minor portion of total CH4 emissions from 

livestock in the United States from 1990 through 2006. Also, 

the variability in emission factors for each of these other 

animal types (e.g., variability by age, production system, and 

feeding practice within each animal type) is less than that 

for cattle. Annual livestock population data for these other 

livestock types, except horses and goats, as well as feedlot 

placement information were obtained for all years from 

the U.S. Department of Agriculture’s National Agricultural 

Statistics Service (USDA 2007). Horse population data were 

obtained from the FAOSTAT database (FAO 2007), because 

USDA does not estimate U.S. horse populations annually. 

Goat population data were obtained for 1992, 1997, and 2002 

(USDA 2007); these data were interpolated and extrapolated 

to derive estimates for the other years. CH4 emissions from 

sheep, goats, swine, and horses were estimated by using 

emission factors utilized in Crutzen et al. (1986, cited in 

IPCC 2006). These emission factors are representative of 

typical animal sizes, feed intakes, and feed characteristics 

in developed countries. The methodology is the same as that 

recommended by IPCC (2006).

See Annex 3.9 for more detailed information on the 

methodology and data used to calculate CH4 emissions from 

enteric fermentation.
Agriculture 6-5

Uncertainty

Quantitative uncertainty of this source category was 

performed through the IPCC-recommended Tier 2 uncertainty 

estimation methodology, Monte Carlo Stochastic Simulation 

technique as described in ICF (2003). These uncertainty 

estimates were developed for the 1990 through 2001 Inventory 

report. No significant changes occurred in the method of data 

collection, data estimation methodology, or other factors that 

influence the uncertainty ranges around the 2006 activity 

data and emission factor input variables used in the current 

submission. Consequently, these uncertainty estimates were 

directly applied to the 2006 emission estimates.

A total of 185 primary input variables (177 for cattle 

and 8 for non-cattle) were identified as key input variables 

for the uncertainty analysis. A normal distribution was 

assumed for almost all activity- and emission factor-related 

input variables. Triangular distributions were assigned to 

three input variables (specifically, cow-birth ratios for the 

three most recent years included in the 2001 model run) 

to capture the fact that these variables can not be negative. 

For some key input variables, the uncertainty ranges around 

their estimates (used for inventory estimation) were collected 

from published documents and other public sources; others 

were based on expert opinion and our best estimates. In 

addition, both endogenous and exogenous correlations 

between selected primary input variables were modeled. The 

exogenous correlation coefficients between the probability 

distributions of selected activity-related variables were 

developed through expert judgment.

The uncertainty ranges associated with the activity 

data-related input variables were plus or minus 10 percent 

or lower. However, for many emission factor-related input 

variables, the lower- and/or the upper-bound uncertainty 

estimates were over 20 percent. The results of the quantitative 

uncertainty analysis (Table 6-5) indicate that, on average, the 

emission estimate range of this source is approximately 112.3 

to 148.9 Tg CO2 Eq., calculated as 11 percent below and 18 

percent above the actual 2006 emission estimate of 126.2 Tg 

CO2 Eq. Among the individual cattle sub-source categories, 

beef cattle account for the largest amount of CH4 emissions 

as well as the largest degree of uncertainty in the inventory 

emission estimates. Among non-cattle, horses account for 

the largest degree of uncertainty in the inventory emission 

estimates because there is a higher degree of uncertainty 

among the FAO population estimates used for horses than 

for the USDA population estimates used for swine, goats, 

and sheep. 

QA/QC and Verification 

In order to ensure the quality of the emission estimates 

from enteric fermentation, the IPCC Tier 1 and Tier 2 

Quality Assurance/Quality Control (QA/QC) procedures 

were implemented consistent with the U.S. QA/QC plan. 

Tier 2 QA procedures included independent peer review of 

emission estimates. Particular emphasis was placed this year 

on reviewing and implementing the revised IPCC Guidelines 

(IPCC 2006). Additionally, as described below, this year the 

CEFM was modified to allow generation of the estimates by 

state, which required further QA/QC to ensure consistency 

of estimates generated by the updated model.

Recalculations Discussion 

There were several modifications that had an effect on 

emission estimates, including: 

•	 The Cfi (a coefficient used for calculating the net energy 

required for maintenance) used for lactating cattle was 

adjusted from 0.322 (previously used for all cattle) to 

0.386, based on the revised IPCC equations (IPCC 2006). 

This change had the effect of increasing the energy 

requirement for maintenance of lactating cows and thus 

increasing emissions for dairy cows by approximately 

7 percent and beef cows by approximately 16 percent.

Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea, b

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Enteric Fermentation CH4 126.2 112.3 148.9 -11% +18%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

b

 Note that the relative uncertainty range was estimated with respect to the 2001 emission estimates submitted in 2003 and applied to 2006 estimates.
6-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

•	 During the QA/QC process it was noted that the C 

factor (a coefficient used in calculating the net energy 

required for growth) of 0.8 was only being used for some 

feedlot heifers, and all other cows and heifers were being 

calculated using a C factor of 1.0. This has been updated 

so that all cows and heifers use a C factor of 0.8 and all 

steer use a C factor of 1.0, as stated in the revised IPCC 

Guidelines (IPCC 2006). This change resulted in an 

increase in emissions of between three and ten percent in 

animal subcategories that experience weight gain (e.g., 

feedlot, replacement, and stocker animals), depending 

on the subcategory. 

•	 The equation used to calculate the net energy of growth 

(NEg), which is part of the gross energy equation, was 

also updated to match the simplified equation provided in 

the revised IPCC Guidelines (IPCC 2006). The equation 

now reads: 

 

 

 

Previously the equation used was: 

 

 

 

 

This change resulted in a decrease of less than one 

half of one percent in animal subcategories that experience 

growth (i.e., weight gain, including, feedlot, replacement, 

and stocker animals).

•	 In the current Inventory, the CEFM, which was used 

to calculate emissions from cattle enteric fermentation, 

was updated to output results by individual state rather 

than by regional groupings, during this process two 

changes occurred. First, the averaging approach used 

to calculate the step-up DE and Ym for feedlot animals 

is based on an average of the feedlot and stocker diet 

characteristics. Given that we changed the model to run 

50 states rather than 7 regions, the final values for the 

step-up diet characteristics changed slightly. Second, 

the milk production numbers are now input at the state, 

rather than regional level, which allows for data input at 

a more detailed level. Both of these changes had a very 

small effect on emissions compared to the additional 

modifications, discussed above.

•	 Population estimates were revised by FAO for 2001 

through 2005 for horses. 

•	 The USDA published revised population estimates that 

affected historical emissions estimated for swine in 

2005. In addition, some historical population estimates 

for certain beef and dairy populations were also updated 

as a result of changes in USDA inputs.

As a result of these changes, dairy cattle emissions 

increased an average of 99 Gg (7.6 percent) per year and beef 

cattle increased an average of 435 Gg (11.1 percent) per year 

over the entire time series. Historical emission estimates for 

swine in 2005 increased by less than one half of one percent 

as a result of the USDA revisions described above. Historical 

emission estimates for horses increased by an average of 35 

percent from 2001 through 2005.

Planned Improvements

Continued research and regular updates are necessary 

to maintain a current model of cattle diet characterization, 

feedlot placement data, rates of weight gain and calving, 

among other data inputs. Research is currently underway to 

update the diet assumptions. There are a variety of models 

available to predict methane production from cattle. Four 

of these models (two mechanistic, and two empirical) are 

being evaluated to determine appropriate Ym and DE values 

for each cattle type and state. In addition to the model 

evaluation, separate research is being conducted to update 

the assumptions used for cattle diet components for each 

animal type. At the conclusion of both of these updates, it 

is anticipated that a peer-reviewed article will be published 

and will serve as the basis for future emission estimates for 

enteric fermentation. 

where,

NEg = The net energy required for 

growth, MJ/day

Weight = Average live body weight of the 

animals in the population, kg

C = A coefficient that is 0.8 for females, 

1.0 for steer, and 1.2 for bulls

MW = The mature weight of an adult 

female in moderate condition, kg

WG = The average weight gain for animals in the population, kg/day

NEg = 22.02 × ( Weight )0.75 × WG1.097

 C × MW

NEg = 4.18 × 0.0635 ×

[ 0.891 × (Weight × 0.96) × ( 478 )]0.75 

×

C × MW

(WG × 0.92)1.097
Agriculture 6-7

In addition to the diet characteristics discussed above 

several revisions will be investigated, including: 

•	 The possible inclusion of bulls into the CEFM at a Tier 

1 or 2 level;

•	 Updating input variables that are from older data sources, 

such as beef births by month and beef cow lactation 

rates; 

•	 The possible breakout of other animal types from 

national estimates to state-level estimates; and

•	 Including bison in the estimates for other domesticated 

animals.

It is anticipated that these updates may result in 

significant changes to some of the activity data used in 

generating emissions. Additionally, since these revised inputs 

will be state-specific and peer-reviewed, uncertainty ranges 

around these variables will likely decrease. As a consequence, 

the current uncertainty analysis will become outdated, and a 

revision of the quantitative uncertainty surrounding emission 

estimates from this source category will be initiated.

6.2. Manure Management (IPCC 

Source Category 4B)

The management of livestock manure can produce 

anthropogenic CH4 and N2O emissions. Methane is produced 

by the anaerobic decomposition of manure. Direct N2O 

emissions are produced as part of the nitrogen cycle through 

the nitrification and denitrification of the organic nitrogen 

in livestock manure and urine.2 Indirect N2O emissions are 

produced as result of the volatilization of nitrogen as ammonia 

(NH3) and nitrogen oxides (NOx) and runoff and leaching of 

nitrogen during treatment, storage and transportation.

When livestock or poultry manure are stored or treated in 

systems that promote anaerobic conditions (e.g., as a 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 

2 Direct and indirect N2O emissions from manure and urine spread onto 

fields either directly as daily spread or after it is removed from manure 

management systems (e.g., lagoon, pit, etc.) and from livestock manure 

and urine deposited on pasture, range, or paddock lands are accounted for 

and discussed in the Agricultural Soil Management source category within 

the Agriculture sector.

aerobically and produce little or no CH4. Ambient temperature, 

moisture, and manure storage or residency time affect the 

amount of CH4 produced because they influence the growth 

of the bacteria responsible for CH4 formation. For non-liquidbased manure systems, moist conditions (which are a function 

of rainfall and humidity) can promote CH4 production. Manure 

composition, which varies by animal diet, growth rate, and 

type, including the animal’s digestive system, also affects the 

amount of CH4 produced. In general, the greater the energy 

content of the feed, the greater the potential for CH4 emissions. 

However, some higher energy feeds also are more digestible 

than lower quality forages, which can result in less overall 

waste excreted from the animal. 

The production of direct N2O emissions from livestock 

manure depends on the composition of the manure and 

urine, the type of bacteria involved in the process, and 

the amount of oxygen and liquid in the manure system. 

For direct N2O emissions to occur, the manure must first 

be handled aerobically where NH3 or organic nitrogen is 

converted to nitrates and nitrites (nitrification), and then 

handled anaerobically where the nitrates and nitrites are 

reduced to nitrogen gas (N2), with intermediate production 

of N2O and nitric oxide (NO) (denitrification) (Groffman et 

al. 2000). These emissions are most likely to occur in dry 

manure handling systems that have aerobic conditions, but 

that also contain pockets of anaerobic conditions due to 

saturation. A very small portion of the total nitrogen excreted 

is expected to convert to N2O in the waste management 

system (WMS). Indirect N2O emissions are produced when 

nitrogen is lost from the system through volatilization (as 

NH3 or NOx) or through runoff and leaching. The vast 

majority of volatilization losses from these operations are 

NH3. Although there are also some small losses of NOx, there 

are no quantified estimates available for use, so losses due 

to volatilization are only based on NH3 loss factors. Runoff 

losses would be expected from operations that house animals 

or store manure in a manner that is exposed to weather. 

Runoff losses are also specific to the type of animal housed 

on the operation. Little information is known about leaching 

from manure management systems as most research focuses 

on leaching from land application systems. Since leaching 

losses are expected to be minimal, leaching losses are coupled 

with runoff losses and the runoff/leaching estimate does not 

include any leaching losses.
6-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Estimates of CH4 emissions in 2006 were 41.4 Tg CO2

Eq. (1,972 Gg), 34 percent higher than in 1990. Emissions 

increased on average by 0.6 Tg CO2 Eq. (2.0 percent) 

annually over this period. The majority of this increase was 

from swine and dairy cow manure, where emissions increased 

34 and 49 percent, respectively. Although the majority of 

manure in the United States is handled as a solid, producing 

little CH4, the general trend in manure management, 

particularly for dairy and swine (which are both shifting 

towards larger facilities), is one of increasing use of liquid 

systems. Also, new regulations limiting the application of 

manure nutrients have shifted manure management practices 

at smaller dairies from daily spread to manure managed and 

stored on site. Although national dairy animal populations 

have been generally decreasing, some states have seen 

increases in their dairy populations as the industry becomes 

more concentrated in certain areas of the country. These 

areas of concentration, such as California, New Mexico, and 

Idaho, tend to utilize more liquid-based systems to manage 

(flush or scrape) and store manure. Thus the shift toward 

larger facilities is translated into an increasing use of liquid 

manure management systems, which have higher potential 

CH4 emissions than dry systems. This shift was accounted 

for by incorporating state and WMS-specific CH4 conversion 

factor (MCF) values in combination with the 1992, 1997, and 

2002 farm-size distribution data reported in the Census of 

Agriculture (USDA 2005). Methane emissions from horses 

have nearly doubled since 1990 (an 82 percent increase from 

1990 to 2006); however, this is due to population increases 

rather than changes in manure management practices. 

Overall, horses contribute only 2 percent of CH4 emissions 

from animal manure management. From 2005 to 2006, there 

was a 1 percent decrease in total CH4 emissions, due to minor 

shifts in the animal populations and the resultant effects on 

manure management system allocations and increased use 

of anaerobic digesters. 

In 2006, total N2O emissions were estimated to be 14.3 

Tg CO2 Eq. (46 Gg); in 1990, emissions were 12.1 Tg CO2

Eq. (39 Gg). These values include both direct and indirect 

N2O emissions from manure management. N2O emissions 

have remained fairly steady since 1990. Small changes 

in N2O emissions from individual animal groups exhibit 

the same trends as the animal group populations, with the 

overall net effect that N2O emissions showed an 18 percent 

increase from 1990 to 2006 and a 2.5 percent increase from 

2005 through 2006. 

Table 6-6 and Table 6-7 provide estimates of CH4 and N2O 

emissions from manure management by animal category. 

Table 6-6: CH4 and N2O Emissions from Manure Management (Tg CO2 Eq.)

Gas/Animal Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4

a 31.0 35.2 38.8 40.2 41.3 40.7 40.1 41.8 41.4

Dairy Cattle 12.0 13.4 15.8 16.6 17.3 17.7 17.2 17.9 17.9

Beef Cattle 2.5 2.6 2.4 2.4 2.4 2.3 2.3 2.3 2.5

Swine 13.1 16.0 17.4 17.8 18.3 17.2 17.1 17.9 17.5

Sheep 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Goats + + + 0.0 + + + + +

Poultry 2.8 2.7 2.6 2.7 2.7 2.7 2.6 2.6 2.7

Horses 0.5 0.4 0.5 0.5 0.5 0.6 0.7 0.8 0.8

N2Ob 12.1 12.8 13.7 14.0 14.0 13.6 13.8 13.9 14.3

Dairy Cattle 3.5 3.5 3.6 3.6 3.7 3.7 3.7 3.7 3.8

Beef Cattle 5.5 5.9 6.7 6.9 6.7 6.3 6.5 6.5 6.7

Swine 1.2 1.4 1.4 1.4 1.5 1.5 1.5 1.5 1.5

Sheep 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

Goats + + + 0.0 + + + + +

Poultry 1.5 1.6 1.7 1.7 1.7 1.7 1.7 1.7 1.8

Horses 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.4 0.4

Total 43.0 48.0 52.5 54.2 55.2 54.3 53.9 55.7 55.7

+ Does not exceed 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.

a

 Includes CH4 emission reductions due to anaerobic digestion. b

 Includes both direct and indirect N2O emissions.
Agriculture 6-9

Methodology

The methodologies presented in IPCC (2006) form the 

basis of the CH4 and N2O emission estimates for each animal 

type. The calculation of emissions requires the following 

information:

•	 Animal population data (by animal type and state);

•	 Amount of N produced (excretion rate by animal type 

times animal population);

•	 Amount of volatile solids produced (excretion rate by 

animal type times animal population);

•	 CH4 producing potential of the volatile solids (by animal 

type);

•	 Extent to which the CH4 producing potential is realized 

for each type of manure management system (by state 

and manure management system, including the impacts 

of any biogas collection efforts);

•	 Portion of manure managed in each manure management 

system (by state and animal type); and

•	 Portion of manure deposited on pasture, range, or 

paddock or used in daily spread systems.

This section presents a summary of the methodologies used 

to estimate CH4 and N2O emissions from manure management 

for this Inventory. See Annex 3.10 for more detailed 

information on the methodology and data used to calculate 

CH4 and N2O emissions from manure management. 

Both CH4 and N2O emissions were estimated by first 

determining activity data, including animal population, waste 

characteristics, and manure management system usage. For 

swine and dairy cattle, manure management system usage 

was determined for different farm size categories using data 

from USDA (USDA 1996b, 1998b, 2000b) and EPA (ERG 

2000a, EPA 2002a, 2002b). For beef cattle and poultry, 

manure management system usage data were not tied to 

farm size but were based on other data sources (ERG 2000a, 

USDA 2000c, UEP 1999). For other animal types, manure 

management system usage was based on previous estimates 

(EPA 1992).

MCFs and N2O emission factors were determined for 

all manure management systems. MCFs for dry systems 

were set equal to default IPCC factors based on each state’s 

climate for each year (IPCC 2006). MCFs for liquid/slurry, 

anaerobic lagoon, and deep pit systems were calculated based 

on the forecast performance of biological systems relative to 

temperature changes as predicted in the van’t Hoff-Arrhenius 

equation. The MCF calculations model the average monthly 

ambient temperature, a minimum system temperature, the 

carryover of volatile solids (VS) in the system from month 

Table 6-7: CH4 and N2O Emissions from Manure Management (Gg)

Gas/Animal Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4

a 1,474 1,676 1,847 1,915 1,964 1,938 1,908 1,988 1,972

Dairy Cattle 572 638 751 792 822 844 818 854 852

Beef Cattle 120 121 114 117 113 112 111 112 117

Swine 623 762 830 849 873 821 815 853 832

Sheep 7 5 4 4 4 4 4 4 4

Goats 1 1 1 1 1 1 1 1 1

Poultry 131 128 125 129 127 127 126 126 126

Horses 22 21 22 23 25 29 34 39 39

N2Ob 39 41 44 45 45 44 44 45 46

Dairy Cattle 11 11 12 12 12 12 12 12 12

Beef Cattle 18 19 22 22 22 20 21 21 22

Swine 4 5 5 5 5 5 5 5 5

Sheep + + + + + + + + +

Goats + + + + + + + + +

Poultry 5 5 5 5 6 6 6 6 6

Horses 1 1 1 1 1 1 1 1 1

Note: Totals may not sum due to independent rounding.

a

 Includes CH4 emission reductions due to anaerobic digestion. b

 Includes both direct and indirect N2O emissions.

+ Less than 0.5 Gg.
6-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

to month due to long storage times exhibited by anaerobic 

lagoon systems, and a factor to account for management and 

design practices that result in the loss of VS from lagoon 

systems. Direct N2O emission factors for all systems were 

set equal to default IPCC factors (IPCC 2006). For indirect 

N2O, the default indirect N2O emission factors suggested 

by IPCC were used: 0.010 kg N2O-N/kg N for volatilization 

and 0.0075 kg N2O-N/kg N for runoff/leaching. The amount 

of nitrogen that is lost due to volatilization of NH3 and NOx

(FracGas) is based on WMS-specific volatilization values as 

estimated from U.S. EPA’s National Emission Inventory—

Ammonia Emissions from Animal Agriculture Operations

(EPA 2005). The amount of nitrogen that is lost due to runoff 

and leaching (FracRunoff/Leaching) is based on regional cattle 

runoff data from EPA’s Office of Water (EPA 2002b). 

CH4 emissions were estimated using the VS production 

for livestock. For all cattle groups except bulls and calves, 

regional animal-specific VS production rates that are related to 

the diet of the animal for each year of the Inventory were used 

(Pederson et al., 2007). For other animal groups, VS production 

was calculated using a national average VS production rate 

from the Agricultural Waste Management Field Handbook

(USDA 1996a), which was then multiplied by the average 

weight of the animal and the state-specific animal population. 

The resulting VS for each animal group were then multiplied 

by the maximum CH4 producing capacity of the waste (Bo) 

and the state- and WMS-specific MCFs.

The maximum CH4 producing capacity of the VS, or Bo, 

was determined based on data collected in a literature review 

(ERG 2000b). Bo data were collected for each animal type 

for which emissions were estimated. 

Anaerobic digester reductions for 1990-2005 were 

estimated based on data from the EPA AgSTAR program, 

including information presented in the AgSTAR Digest (EPA 

2000, 2003b, 2006). Anaerobic digestion reductions for 2006 

were calculated based on data from an AgSTAR digester 

inventory (ERG 2008). 

Nitrogen excretion rates from the USDA Agricultural 

Waste Management Field Handbook (USDA 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. 

Direct N2O emissions were estimated by determining 

total Kjeldahl nitrogen (TKN)3 production for all livestock 

wastes using a national average N excretion rate for 

each animal group from USDA (1996a), which was then 

multiplied by the average weight of the animal and the statespecific animal population. State- and WMS-specific direct 

N2O emission factors were then applied to total nitrogen 

production to estimate direct N2O emissions.

Indirect N2O emissions were calculated by first 

estimating the amount of nitrogen loss from volatilization 

and runoff/leaching by multiplying the N excreted by 

FracGas and FracRunoff/Leaching. The N losses were then 

multiplied by the indirect N2O emission factors to estimate 

indirect N2O emissions.

Uncertainty

An analysis was conducted for the manure management 

emission estimates presented in EPA’s Inventory of U.S. 

Greenhouse Gas Emissions and Sinks: 1990–2001 (EPA 

2003a, ERG 2003) to determine the uncertainty associated 

with estimating CH4 and N2O emissions from livestock manure 

management. The quantitative uncertainty analysis for this 

source category was performed in 2002 through the IPCCrecommended Tier 2 uncertainty estimation methodology, 

the Monte Carlo Stochastic Simulation technique. The 

uncertainty analysis was developed based on the methods used 

to estimate CH4 and N2O emissions from manure management 

systems. A normal probability distribution was assumed for 

each source data category. The series of equations used were 

condensed into a single equation for each animal type and 

state. The equations for each animal group contained four 

to five variables around which the uncertainty analysis was 

performed for each state. 

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 6-8. Manure management CH4

emissions in 2006 were estimated to be between 34.0 and 

49.7 Tg CO2 Eq. at a 95 percent confidence level, which 

indicates a range of 18 percent below to 20 percent above the 

actual 2006 emission estimate of 41.4 Tg CO2 Eq. At the 95 

percent confidence level, N2O emissions were estimated to 

be between 12.0 and 17.7 Tg CO2 Eq. (or approximately 16 

percent below and 24 percent above the actual 2006 emission 

estimate of 14.3 Tg CO2 Eq.). 

3Total Kjeldahl nitrogen is a measure of organically bound nitrogen and 

ammonia nitrogen.
Agriculture 6-11

QA/QC and Verification 

Tier 1 and Tier 2 QA/QC activities were conducted 

consistent with the U.S. QA/QC plan. Tier 2 activities 

focused on comparing estimates for the previous and current 

inventories for N2O emissions4 from managed systems and 

CH4 emissions from livestock manure. All errors identified 

were corrected. Order of magnitude checks were also 

conducted, and corrections made where needed. Manure N 

data were checked by comparing state-level data with bottom 

up estimates derived at the county level and summed to the 

state level. Similarly, a comparison was made by animal 

and WMS type for the full time series, between national 

level estimates for nitrogen excreted and the sum of county 

estimates for the full time series.

Recalculations Discussion

There was a major change in the N2O and CH4 emissions 

calculations for the current Inventory. These emissions are 

now calculated from the “bottom up” such that CH4 and N2O 

are calculated for each animal group, manure management 

system, and state. These values are then summed to calculate 

the total greenhouse gas emissions from manure management 

in the United States. This methodology differs from previous 

Inventories which calculated state weighted average N2O 

emission factors and methane conversion factors (MCFs). 

Although this new methodology does not alter the overall 

estimates of greenhouse gases associated with this section, 

it now allows emissions to be viewed by animal type and 

manure management system at the state and national level. 

In the previous Inventory, dairy heifers and beef on feed 

each had a separate WMS distribution for managed systems 

and unmanaged systems. The managed WMS distribution was 

4 N2O emissions in the previous Inventory reflect only direct emissions 

whereas the current N2O emissions include both direct and indirect emissions 

from livestock manure management.

used to calculate a state average EF for managed systems. In 

the current inventory methodology, dairy heifers and beef on 

feed have one WMS distribution that represents managed and 

unmanaged systems. For all animals, emissions are calculated 

for each WMS using the EF for that system, and not using 

a state average EF. This change in calculation methodology 

results in a slightly different (less than one percent change) 

emission estimate for these animal groups.

The Inventory now includes indirect N2O emissions 

in the manure management sector associated with N losses 

from volatilization of N as ammonia (NH3), nitrogen oxides 

(NOx), and leaching and runoff, as recommended by IPCC 

(2006). These indirect N2O emissions are added to the direct 

N2O emissions to present a more complete picture of N2O 

emissions from manure management. 

The days per year used in N2O calculations was changed 

from 365 to 365.25 to include leap years and to be consistent 

with the CH4 inventory calculations. 

Methane emission reductions from anaerobic digestion 

for 2006 were calculated from an AgSTAR digester inventory 

by summing the estimated emission reductions by animal 

type (ERG 2008). Anaerobic digestion reductions in previous 

years were based on data obtained from AgSTAR Digests 

(EPA 2000, 2003b, 2006). 

Errors were identified in the calculation of the sheep 

WMS distribution; population values for other states were 

incorrectly distributed in the calculations. Correcting this 

error resulted in very small changes in N2O emissions 

estimates from sheep.

Changes were made to the current calculations involving 

animal population data. Animal population data were 

updated to reflect the final estimates reports from USDA 

NASS (USDA 1994a-b, 1995a-b, 1998a-b, 1999a-c, 2000a, 

2004a-e, 2006a-c, 2007a-d). The population data may differ 

from previous Inventories because some values changed due 

Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O (Direct and Indirect) Emissions from 

Manure Management (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Manure Management CH4 41.4 34.0 49.7 -18% +20%

Manure Management N2O 14.3 12.0 17.7 -16% +24%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
6-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

to USDA NASS review. For horses, state-level populations 

were estimated using the national FAO population data (FAO 

2007) and the state distributions from the 1992, 1997, and 

2002 Census of Agriculture (USDA 2005). The FAO horse 

population estimates for recent years increased dramatically 

between the current and previous Inventories, resulting in a 

much larger estimated horse population, and therefore greater 

greenhouse gas emissions from this source category.

With these recalculations, CH4 emission estimates 

from manure management systems are slightly higher than 

reported in the previous Inventory for dairy cattle and swine, 

as well as horses for years 2001 through 2005. On average, 

annual CH4 emission estimates are more than those of the 

previous Inventory by about one percent. 

N2O emission estimates from manure management 

systems have increased by approximately 30 percent for 

all years of the current Inventory compared to the previous 

Inventory due to the change in calculation methodology, 

which incorporates direct and indirect N2O emissions. The 

most significant changes in N2O emissions compared to the 

previous Inventory occurred in the poultry and swine sectors, 

whose emissions were approximately 70 percent higher due 

to the inclusion of indirect N2O emissions.

Changes were made to the Cattle Enteric Fermentation 

Model that produces the VS estimates for all cattle groups 

except bulls and calves. Refer to the Recalculations section 

in Enteric Fermentation to see specific changes made to 

the model. 

Planned Improvements

The Manure Management emission estimates will be 

updated to reflect changes in the Cattle Enteric Fermentation 

Model (CEFM). In addition, efforts will be made to ensure 

that the manure management estimates and CEFM are using 

the same data sources and variables where appropriate.

The American Society of Agricultural Engineers proposed 

new standards for manure production characteristics in 2004 

and finalized them in 2005. These data were investigated and 

evaluated for incorporation into future estimates. 

A method to better estimate anaerobic digester CH4

emission reductions will be investigated. This method would 

include separating systems with anaerobic digesters from the 

total animal population before estimating CH4 emissions, 

and then estimating emissions from the digesters using the 

amount of biogas/CH4 collected and a 99 percent destruction 

efficiency. 

The uncertainty analysis will be updated in the future to 

more accurately assess uncertainty of emission calculations. 

This update is necessary due to the extensive changes in 

emission calculation methodology in the current Inventory, 

including estimation of emissions at the WMS level and 

the use of new calculations and variables for indirect N2O 

emissions. 

The current methodology for calculating runoff for 

indirect N2O emissions will be reevaluated. Currently, 

runoff is estimated at all manure management systems based 

on outdoor cattle operations. A new methodology may be 

incorporated which takes into account more recent model 

runs from EPA’s Office of Water.

In order to improve the efficiency of MCF calculations, 

MCFs will be calculated in a database instead of spreadsheets 

in the next inventory. Calculating MCFs in a database 

will also increase the overall efficiency of CH4 emission 

estimates by linking directly to the database that calculates 

CH4 estimates.

6.3. Rice Cultivation (IPCC Source 

Category 4C)

Most of the world’s rice, and all rice in the United States, 

is grown on flooded fields. When fields are flooded, aerobic 

decomposition of organic material gradually depletes most 

of the oxygen present in the soil, causing anaerobic soil 

conditions. Once the environment becomes anaerobic, CH4

is produced through anaerobic decomposition of soil organic 

matter by methanogenic bacteria. As much as 60 to 90 percent 

of the CH4 produced is oxidized by aerobic methanotrophic 

bacteria in the soil (some oxygen remains at the interfaces of 

soil and water, and soil and root system) (Holzapfel-Pschorn 

et al. 1985, Sass et al. 1990). Some of the 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.
Agriculture 6-13

The water management system under which rice is 

grown is one of the most important factors affecting CH4

emissions. Upland rice fields are not flooded, and therefore 

are not believed to produce CH4. In deepwater rice fields 

(i.e., fields with flooding depths greater than one meter), 

the lower stems and roots of the rice plants are dead, so 

the primary CH4 transport pathway to the atmosphere is 

blocked. The quantities of CH4 released from deepwater 

fields, therefore, are believed to be significantly less than 

the quantities released from areas with shallower flooding 

depths. Some flooded fields are drained periodically during 

the growing season, either intentionally or accidentally. If 

water is drained and soils are allowed to dry sufficiently, 

CH4 emissions decrease or stop entirely. This is due to soil 

aeration, which not only causes existing soil 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. Midseason drainage does not occur except by accident (e.g., due 

to levee breach).

Other factors that influence CH4 emissions from flooded 

rice fields include fertilization practices (especially the use of 

organic fertilizers), soil temperature, soil type, rice variety, 

and cultivation practices (e.g., tillage, seeding, and weeding 

practices). The factors that determine the amount of organic 

material available to decompose (i.e., organic fertilizer use, 

soil type, rice variety,5 and cultivation practices) are the most 

important variables influencing the amount of CH4 emitted 

over the growing season; the total amount of CH4 released 

depends primarily on the amount of organic substrate 

available. Soil temperature is known to be an important 

factor regulating the activity of methanogenic bacteria, and 

therefore the rate of CH4 production. However, although 

temperature controls the amount of time it takes to convert 

a given amount of organic material to CH4, that time is short 

relative to a growing season, so the dependence of total 

emissions over an entire growing season on soil temperature 

5The 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.

is weak. The application of synthetic fertilizers has also 

been found to influence CH4 emissions; in particular, both 

nitrate and sulfate fertilizers (e.g., ammonium nitrate and 

ammonium sulfate) appear to inhibit CH4 formation. 

Rice is cultivated in eight states: Arkansas, California, 

Florida, Louisiana, Mississippi, Missouri, Oklahoma, and 

Texas.6 Soil types, rice varieties, and cultivation practices 

for rice vary from state to state, and even from farm to 

farm. However, most rice farmers apply organic fertilizers 

in the form of residue from the previous rice crop, which is 

left standing, disked, or rolled into the fields. Most farmers 

also apply synthetic fertilizer to their fields, usually urea. 

Nitrate and sulfate fertilizers are not commonly used in rice 

cultivation in the United States. In addition, the climatic 

conditions of Arkansas, southwest Louisiana, Texas, and 

Florida allow for a second, or ratoon, rice crop. CH4 emissions 

from ratoon crops have been found to be considerably higher 

than those from the primary crop. This second rice crop is 

produced from regrowth of the stubble after the first crop 

has been harvested. Because the first crop’s stubble is left 

behind in ratooned fields, and there is no time delay between 

cropping seasons (which would allow the stubble to decay 

aerobically), the amount of organic material that is available 

for anaerobic decomposition is considerably higher than with 

the first (i.e., primary) crop. 

Rice cultivation is a small source of CH4 in the United 

States (Table 6-9 and Table 6-10). In 2006, CH4 emissions 

from rice cultivation were 5.9 Tg CO2 Eq. (282 Gg). Although 

annual emissions fluctuated unevenly between the years 1990 

and 2006, ranging from an annual decrease of 14 percent 

to an annual increase of 17 percent, there was an overall 

decrease of 17 percent over the sixteen-year period, due to 

an overall decrease in primary crop area.7 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.

6A very small amount of rice is grown on about 20 acres in South Carolina; 

however, this amount was determined to be too insignificant to warrant 

inclusion in national emissions estimates.

7The 14 percent decrease occurred between 2005 and 2006; the 17 percent 

increase happened between 1993 and 1994.
6-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Methodology

IPCC (2006) recommends using harvested rice areas, 

area-based daily emission factors (i.e., amount of CH4 emitted 

per day per unit harvested area), and length of growing season 

to estimate annual CH4 emissions from rice cultivation. This 

inventory uses the recommended methodology and employs 

Tier 2 U.S.-specific emission factors derived from rice field 

measurements. State-specific and daily emission factors were 

not available, however, so average U.S. seasonal emission 

factors were used. Seasonal emissions have been found to 

be much higher for ratooned crops than for primary crops, 

so emissions from ratooned and primary areas are estimated 

separately using emission factors that are representative of 

the particular growing season. This approach is consistent 

with IPCC (2006).

Table 6-10: CH4 Emissions from Rice Cultivation (Gg)

State 1990 1995 2000 2001 2002 2003 2004 2005 2006

Primary 241 265 260 283 274 255 283 287 241 

Arkansas 102 114 120 138 128 124 132 139 119 

California 34 40 47 40 45 43 50 45 44 

Florida 1 2 2 1 1 + 1 1 1 

Louisiana 46 48 41 46 45 38 45 45 29 

Mississippi 21 24 19 22 22 20 20 22 16 

Missouri 7 10 14 18 15 15 17 18 18 

Oklahoma + + + + + + + + + 

Texas 30 27 18 18 18 15 19 17 13 

Ratoon 98 98 97 81 52 73 77 39 41 

Arkansas + + + + + + + 1 + 

Florida 2 4 2 2 2 2 2 + 1 

Louisiana 52 54 61 52 25 50 50 22 22 

Texas 45 40 34 27 24 22 24 17 18 

Total 339 363 357 364 325 328 360 326 282 

+ Less than 0.5 Gg

Note: Totals may not sum due to independent rounding.

Table 6-9: CH4 Emissions from Rice Cultivation (Tg CO2 Eq.)

State 1990 1995 2000 2001 2002 2003 2004 2005 2006

Primary 5.1 5.6 5.5 5.9 5.7 5.4 6.0 6.0 5.1 

Arkansas 2.1 2.4 2.5 2.9 2.7 2.6 2.8 2.9 2.5 

California 0.7 0.8 1.0 0.8 0.9 0.9 1.1 0.9 0.9 

Florida + + + + + + + + + 

Louisiana 1.0 1.0 0.9 1.0 1.0 0.8 1.0 0.9 0.6 

Mississippi 0.4 0.5 0.4 0.5 0.5 0.4 0.4 0.5 0.3 

Missouri 0.1 0.2 0.3 0.4 0.3 0.3 0.3 0.4 0.4 

Oklahoma + + + + + + + + + 

Texas 0.6 0.6 0.4 0.4 0.4 0.3 0.4 0.4 0.3 

Ratoon 2.1 2.1 2.0 1.7 1.1 1.5 1.6 0.8 0.9 

Arkansas + + + + + + + + + 

Florida + 0.1 0.1 + + + + + + 

Louisiana 1.1 1.1 1.3 1.1 0.5 1.0 1.1 0.5 0.5 

Texas 0.9 0.8 0.7 0.6 0.5 0.5 0.5 0.4 0.4 

Total 7.1 7.6 7.5 7.6 6.8 6.9 7.6 6.8 5.9 

+ Less than 0.05 Tg CO2 Eq.

Note: Totals may not sum due to independent rounding.
Agriculture 6-15

The harvested rice areas for the primary and ratoon 

crops in each state are presented in Table 6-11. Primary 

crop areas for 1990 through 2006 for all states except 

Florida and Oklahoma were taken from U.S. Department 

of Agriculture’s Field Crops Final Estimates 1987–1992

(USDA 1994), Field Crops Final Estimates 1992–1997

(USDA 1998), Field Crops Final Estimates 1997–2002

(USDA 2003), and Crop Production Summary (USDA 2005 

through 2007). Harvested rice areas in Florida, which are not 

reported by USDA, were obtained from: Tom Schueneman 

(1999b, 1999c, 2000, 2001a) and Arthur Kirstein (2003, 

2006), Florida agricultural extension agents; Dr. Chris Deren 

(2002) of the Everglades Research and Education Centre 

at the University of Florida; Gaston Cantens (2004, 2005), 

Vice President of Corporate Relations of the Florida Crystals 

Company; and Rene Gonzalez (2007a), Plant Manager of 

Sem-Chi Rice Company. Harvested rice areas for Oklahoma, 

which also are not reported by USDA, were obtained from 

Danny Lee of the Oklahoma Farm Services Agency (2003 

through 2007). Acreages for the ratoon crops were derived 

from conversations with the agricultural extension agents 

in each state. In Arkansas, ratooning occurred only in 1998, 

1999, 2005, and 2006, when the ratooned area was less 

than 1 percent of the primary area (Slaton 1999 through 

2001a; Wilson 2002 through 2007). In Florida, the ratooned 

area was 50 percent of the primary area from 1990 to 1998 

(Schueneman 1999a), about 65 percent of the primary area in 

1999 (Schueneman 2000), around 41 percent of the primary 

area in 2000 (Schueneman 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), about 77 percent 

of the primary area in 2004 (Cantens 2005), 0 percent of the 

primary area in 2005 (there was no ratooning this year due to 

Hurricane Wilma), and about 28 percent of the primary area 

in 2006 (Gonzalez 2007a). In Louisiana, the percentage of 

the primary area that was ratooned was constant at 30 percent 

over the 1990 to 1999 period, increased to approximately 40 

percent in 2000, returned to 30 percent in 2001, dropped to 

15 percent in 2002, rose to 35 percent in 2003, returned to 30 

percent in 2004, dropped to 13 percent in 2005 and increased 

to 20 percent in 2006 (Linscombe 1999, 2001a, 2002 through 

2007; Bollich 2000). In Texas, the percentage of the primary 

area that was ratooned was constant at 40 percent over the 

1990 to 1999 period, increased to 50 percent in 2000 due to 

an early primary crop, and then decreased to 40 percent in 

2001, 37 percent in 2002, 38 percent in 2003, 35 percent in 

2004, 27 percent in 2005 and increased to 39 percent in 2006 

Table 6-11: Rice Areas Harvested (Hectares)

State/Crop 1990 1995 2000 2001 2002 2003 2004 2005 2006

Arkansas

Primary 485,633 542,291 570,619 656,010 608,256 588,830 629,300 661,675 566,572

Ratoon* 0 0 0 0 0 0 0 662 6

California 159,854 188,183 221,773 190,611 213,679 205,180 238,770 212,869 211,655

Florida

Primary 4,978 9,713 7,801 4,562 5,077 2,369 3,755 4,565 4,575

Ratoon 2,489 4,856 3,193 2,752 2,734 2,369 2,899 0 1,295

Louisiana

Primary 220,558 230,676 194,253 220,963 216,512 182,113 215,702 212,465 139,620

Ratoon 66,168 69,203 77,701 66,289 32,477 63,739 64,711 27,620 27,924

Mississippi 101,174 116,552 88,223 102,388 102,388 94,699 94,699 106,435 76,487

Missouri 32,376 45,326 68,393 83,772 73,654 69,203 78,915 86,605 86,605

Oklahoma 617 364 283 265 274 53 158 271 17

Texas

Primary 142,857 128,693 86,605 87,414 83,367 72,845 88,223 81,344 60,704

Ratoon 57,143 51,477 43,302 34,966 30,846 27,681 30,878 21,963 23,675

Total Primary 1,148,047 1,261,796 1,237,951 1,345,984 1,303,206 1,215,291 1,349,523 1,366,228 1,146,235

Total Ratoon 125,799 125,536 124,197 104,006 66,056 93,790 98,488 50,245 52,899

Total 1,273,847 1,387,333 1,362,148 1,449,991 1,369,262 1,309,081 1,448,011 1,416,473 1,199,135

*Arkansas ratooning occurred only in 1998, 1999, 2005, and 2006.

Note: Totals may not sum due to independent rounding.
6-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

(Klosterboer 1999, 2000, 2001a, 2002, 2003; Stansel 2004, 

2005; Texas Agricultural Experiment Station 2006, 2007). 

California, Mississippi, Missouri, and Oklahoma have not 

ratooned rice over the period 1990 through 2006 (Guethle 

1999, 2000, 2001a, 2002 through 2007; Lee 2003 through 

2007; Mutters 2002 through 2005; Street 1999 through 2003; 

Walker 2005, 2007). 

To determine what CH4 emission factors should be used 

for the primary and ratoon crops, CH4 flux information from 

rice field measurements in the United States was collected. 

Experiments which involved atypical or nonrepresentative 

management practices (e.g., the application of nitrate 

or sulfate fertilizers, or other substances believed to 

suppress CH4 formation), as well as experiments in which 

measurements were not made over an entire flooding season 

or floodwaters were drained mid-season, were excluded 

from the analysis. The remaining experimental results8 were 

then sorted by season (i.e., primary and ratoon) and type 

of fertilizer amendment (i.e., no fertilizer added, organic 

fertilizer added, and synthetic and organic fertilizer added). 

The experimental results from primary crops with added 

synthetic and organic fertilizer (Bossio et al. 1999; Cicerone 

et al. 1992; Sass et al. 1991a, 1991b) were averaged to derive 

an emission factor for the primary crop, and the experimental 

results from ratoon crops with added synthetic fertilizer 

(Lindau and Bollich 1993, Lindau et al. 1995) were averaged 

to derive an emission factor for the ratoon crop. The resultant 

emission factor for the primary crop is 210 kg CH4/hectareseason, 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 

8 In some of these remaining experiments, measurements from individual 

plots were excluded from the analysis because of the aforementioned 

reasons. In addition, one measurement from the ratooned fields (i.e., the flux 

of 2.041 g/m2/day in Lindau and Bollich 1993) was excluded, because this 

emission rate is unusually high compared to other flux measurements in the 

United States, as well as IPCC (2006) default emission factors.

differences in cultivation practices, in particular, fertilizer 

type, amount, and mode of application; differences in cultivar 

type; and differences in soil and climatic conditions. A portion 

of this variability is accounted for by separating primary from 

ratooned areas. However, even within a cropping season or 

a given management regime, measured emissions may vary 

significantly. Of the experiments used to derive the emission 

factors applied here, primary emissions ranged from 22 to 

479 kg CH4/hectare-season and ratoon emissions ranged 

from 481 to 1,490 kg CH4/hectare-season. The uncertainty 

distributions around the primary and ratoon emission factors 

were derived using the distributions of the relevant primary 

or ratoon emission factors available in the literature and 

described above. Variability about the rice emission factor 

means was not normally distributed for either primary or 

ratooned crops, but rather skewed, with a tail trailing to the 

right of the mean. A lognormal statistical distribution was, 

therefore, applied in the Tier 2 Monte Carlo analysis. 

Other sources of uncertainty include the primary ricecropped area for each state, percent of rice-cropped area 

that is ratooned, and the extent to which flooding outside of 

the normal rice season is practiced. Expert judgment was 

used to estimate the uncertainty associated with primary 

rice-cropped area for each state at 1 to 5 percent, and a 

normal distribution was assumed. Uncertainties were applied 

to ratooned area by state, based on the level of reporting 

performed by the state. No uncertainties were calculated for 

the practice of flooding outside of the normal rice season 

because CH4 flux measurements have not been undertaken 

over a sufficient geographic range or under a broad enough 

range of representative conditions to account for this source 

in the emission estimates or its associated uncertainty.

To quantify the uncertainties for emissions from rice 

cultivation, a Monte Carlo (Tier 2) uncertainty analysis 

was performed using the information provided above. The 

results of the Tier 2 quantitative uncertainty analysis are 

summarized in Table 6-12. Rice cultivation CH4 emissions 

in 2006 were estimated to be between 2.1 and 12.8 Tg CO2

Eq. at a 95 percent confidence level, which indicates a range 

of 65 percent below to 117 percent above the actual 2006 

emission estimate of 5.9 Tg CO2 Eq. 
Agriculture 6-17

QA/QC and Verification

A source-specific QA/QC plan for rice cultivation was 

developed and implemented. This effort included a Tier 1 

analysis, as well as portions of a Tier 2 analysis. The Tier 2 

procedures focused on comparing trends across years, states, 

and cropping seasons to attempt to identify any outliers or 

inconsistencies. No problems were found. 

Recalculations Discussion

When compiling the previous Inventory, no data on 

area harvested and percent of area ratooned in Florida were 

available for 2005, and consequently 2004 data was held 

constant. For the current Inventory, Gonzalez (2007a) was 

able to provide data for 2005 as well as 2006, resulting in an 

decrease of about 0.6 percent in the estimate for 2005.

6.4. Agricultural Soil Management 

(IPCC Source Category 4D)

Nitrous oxide is produced naturally in soils through the 

microbial processes of nitrification and denitrification.9 A 

number of agricultural activities increase mineral nitrogen 

(N) availability in soils, thereby increasing the amount 

available for nitrification and denitrification, and ultimately 

the amount of N2O emitted. These activities increase soil 

mineral N either directly or indirectly (see Figure 6-2). Direct 

increases occur through a variety of management practices 

that add, or lead to greater release of, mineral N to the soil, 

including: fertilization; application of managed livestock 

manure and other organic materials such as sewage sludge; 

9Nitrification and denitrification are driven by the activity of microorganisms 

in soils. Nitrification is the aerobic microbial oxidation of ammonium (NH4) 

to nitrate (NO3), and denitrification is the anaerobic microbial reduction of 

nitrate to N2. Nitrous oxide is a gaseous intermediate product in the reaction 

sequence of denitrification, which leaks from microbial cells into the soil and 

then into the atmosphere. Nitrous oxide is also produced during nitrification, 

although by a less well-understood mechanism (Nevison 2000).

deposition of manure on soils by domesticated animals in 

pastures, rangelands, and paddocks (PRP) (i.e., by grazing 

animals and other animals whose manure is not managed); 

production of N-fixing crops and forages; retention of crop 

residues; and drainage and cultivation of organic cropland 

soils (i.e., soils with a high organic matter content, otherwise 

known as histosols).10 Other agricultural soil management 

activities, including irrigation, drainage, tillage practices, 

and fallowing of land, can influence N mineralization in 

soils and thereby affect direct emissions. Mineral N is 

also made available in soils through decomposition of 

soil organic matter and plant litter, as well as asymbiotic 

fixation of N from the atmosphere.11 Indirect emissions of 

N2O occur through two pathways: (1) volatilization and 

subsequent atmospheric deposition of applied N,12 and (2) 

surface runoff and leaching of applied N into groundwater 

and surface water. Direct emissions from agricultural lands 

(i.e., croplands and grasslands) are included in this section, 

while direct emissions from forest lands and settlements are 

presented in the Land Use, Land-Use Change, and Forestry 

chapter. However, indirect N2O emissions from all sources 

(cropland, grassland, forest lands, settlements, and managed 

manure) are reported in this chapter.

Agricultural soils produce the majority of N2O 

emissions in the United States. Estimated emissions from 

this source in 2006 were 265.0 Tg CO2 Eq. (855 Gg N2O) 

(see Table 6-13 and Table 6-14). Annual N2O emissions 

from agricultural soils fluctuated between 1990 and 2006, 

although overall emissions were 1.6 percent lower in 

10 Drainage and cultivation of organic soils in former wetlands enhances 

mineralization of N-rich organic matter, thereby enhancing N2O emissions 

from these soils.

11Asymbiotic N fixation is the fixation of atmospheric N2 by bacteria living 

in soils that do not have a direct relationship with plants.

12 These processes entail volatilization of applied N as NH3 and 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.

Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Rice Cultivation CH4 5.9 2.1 12.8 -65% +117%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
6-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

2006 than in 1990. Year-to-year fluctuations are largely a 

reflection of annual variation in weather patterns, synthetic 

fertilizer use, and crop production. On average, cropland 

accounted for approximately 64 percent of total direct 

emissions, while grassland accounted for approximately 

36 percent. Estimated direct and indirect N2O emissions 

by sub-source category are provided in Table 6-15 and 

Table 6-16.

Figure 6-2

Agricultural Sources and Pathways of N that Result in N2O Emissions
Agriculture 6-19

Table 6-13: N2O Emissions from Agricultural Soils (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Direct 218.3 210.3 216.0 222.3 217.7 202.2 208.6 217.9 214.7 

Cropland 130.9 133.1 142.0 147.6 137.1 130.2 136.1 140.0 138.9 

Grassland 87.4 77.2 74.0 74.8 80.6 72.0 72.5 77.9 75.8 

Indirect (All Land-Use Types) 51.1 54.5 46.0 54.7 44.3 45.0 38.3 47.3 50.3 

Cropland 30.1 30.5 28.4 28.9 24.8 27.8 21.6 28.4 30.2 

Grassland 20.6 23.6 17.1 25.2 18.9 16.7 16.1 18.3 19.5 

Forest Land + 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Settlements 0.3 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.5 

Total 269.4 264.8 262.1 277.0 262.0 247.3 246.9 265.2 265.0 

+ Less than 0.05 Tg CO2 Eq.

Table 6-14: N2O Emissions from Agricultural Soils (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Direct 704 678 697 717 702 652 673 703 693 

Cropland 422 429 458 476 442 420 439 452 448 

Grassland 282 249 239 241 260 232 234 251 244 

Indirect (All Land-Use Types) 165 176 149 176 143 145 124 153 162 

Cropland 97 98 92 93 80 90 70 92 97 

Grassland 67 76 55 81 61 54 52 59 63 

Forest Land + + + + + + + + + 

Settlements 1 1 1 2 2 2 2 2 2 

Total 869 854 845 894 845 798 796 855 855 

+ Less than 0.5 Gg

Table 6-15: Direct N2O Emissions from Agricultural Soils by Land Use and N Input (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Cropland 130.9 133.1 142.0 147.6 137.1 130.2 136.1 140.0 138.9 

Mineral Soils 128.1 130.3 139.1 144.7 134.3 127.4 133.2 137.1 136.1 

Synthetic Fertilizer 51.3 55.3 55.8 57.2 54.2 50.4 55.3 53.6 53.6 

Organic Amendmentsa 9.4 10.1 10.2 11.1 10.7 10.0 10.7 10.4 10.7 

Residue Nb 9.0 9.6 10.2 9.7 8.9 10.4 9.2 9.6 10.1 

Other c 58.4 55.2 62.8 66.8 60.4 56.5 58.1 63.6 61.7 

Organic Soils 2.8 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 

Grassland 87.4 77.2 74.0 74.8 80.6 72.0 72.5 77.9 75.8 

Synthetic Fertilizer 3.0 2.6 2.5 2.6 2.7 2.5 2.5 2.5 2.6 

PRP Manure 19.8 18.4 19.6 18.5 23.3 19.2 20.9 18.9 19.6 

Managed Manured 0.6 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 

Sewage Sludge 0.3 0.3 0.4 0.4 0.4 0.4 0.5 0.5 0.5 

Residue Nb 12.5 11.4 10.4 10.9 10.8 10.3 10.5 11.2 10.4 

Other c 51.3 44.0 40.7 41.8 42.8 39.2 37.6 44.2 42.2 

Total 218.3 210.3 216.0 222.3 217.7 202.2 208.6 217.9 214.7 

a Organic amendment inputs include managed manure amendments and other commercial organic fertilizer (i.e., dried blood, dried manure, tankage, 

compost, and other).

b

 Residue N inputs include unharvested fixed N from legumes as well as crop residue N.

c

 Other N inputs include mineralization from decomposition of soil organic matter as well as asymbiotic fixation of N from the atmosphere.

d

 Accounts for managed manure that is applied to grassland soils.
6-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Figure 6-3 through Figure 6-6 show regional patterns 

in N2O emissions for direct sources and regional patterns of 

N losses leading to indirect N2O emissions, respectively, for 

major crops and grasslands across the United States. Direct 

N2O emissions tend to be high in the Corn Belt (Illinois, 

Iowa, Indiana, Ohio, southern Minnesota, and eastern 

Nebraska). A large portion of the land in many of these states 

is covered with highly fertilized corn and with N-fixing 

soybean cropping. Emissions are also high in North Dakota, 

Kansas, and Texas, primarily from irrigated cropping and 

dryland wheat cropping. Emissions are low in many parts of 

the eastern United States because a small portion of land is 

cultivated, and also low in many western states where rainfall 

and access to irrigation water are limited.

Direct emissions (Tg CO2 Eq./state/year) from grasslands 

are highest in the central and western United States (Figure 

6-4) where a high proportion of the land in many states is 

used for cattle grazing. Some areas in the Great Lake states, 

the Northeast, and Southeast have moderate emissions even 

though emissions from these areas tend to be high on a per 

unit area basis, because the total amount of grazed land is 

much lower than states in the central and western United 

States. 

Indirect emissions for croplands and grasslands (Figure 

6-5 and Figure 6-6) show patterns similar to direct emissions, 

because the factors that control direct emissions (N inputs, 

weather, soil type) also influence indirect emissions. 

However, there are some exceptions, because the processes 

that contribute to indirect emissions (NO3 leaching, N 

volatilization) do not respond in exactly the same manner as 

the processes that control direct emissions (nitrification and 

denitrification). For example, coarse-textured soils facilitate 

nitrification and moderate direct emissions in grasslands in 

some southeastern states, but indirect emissions are relatively 

high in Florida and Georgia grasslands due to high rates of N 

volatilization and NO3 leaching in coarse-textured soils. 

Table 6-16: Indirect N2O Emissions from all Land-Use Types (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Cropland 30.1 30.5 28.4 28.9 24.8 27.8 21.6 28.4 30.2 

Volatilization and Atm. Deposition 5.8 6.1 6.7 6.1 6.0 6.4 6.1 6.6 6.5 

Surface Leaching & Run-Off 24.3 24.4 21.7 22.8 18.8 21.4 15.5 21.8 23.7 

Grassland 20.6 23.6 17.1 25.2 18.9 16.7 16.1 18.3 19.5 

Volatilization and Atm. Deposition 10.7 10.2 9.3 9.4 9.3 9.4 9.2 10.1 9.4 

Surface Leaching & Run-Off 9.9 13.4 7.8 15.8 9.6 7.2 6.9 8.2 10.1 

Forest Land + 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Volatilization and Atm. Deposition + + + + + + + + + 

Surface Leaching & Run-Off + + 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Settlements 0.3 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.5 

Volatilization and Atm. Deposition 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 

Surface Leaching & Run-Off 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Total 51.1 54.5 46.0 54.7 44.3 45.0 38.3 47.3 50.3 

+ Less than 0.05 Tg CO2 Eq.
Agriculture 6-21

Grasslands, Average Annual Direct N2O Emissions Estimated Using the DAYCENT Model, 

1990–2006 (Tg CO2 Eq./state/year)

Figure 6-4

Tg CO2 Eq./state/year

< 0.25

0.25–0.5

0.5 –1

10–11.9

5–10

2 –5

1–2

Major Crops, Average Annual Direct N2O Emissions Estimated Using the DAYCENT Model, 

1990–2006 (Tg CO2 Eq./state/year)

Figure 6-3

Tg CO2 Eq./state/year

< 0.25

0.25–0.5

0.5 –1

10–13.8

5–10

2 –5

1–2
6-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Major Crops, Average Annual N Losses Leading to Indirect N2O Emissions Using the DAYCENT Model, 

1990–2006 (Gg N/state/year)

Figure 6-5

Gg N/state/year

< 10

10–20

20–50

400–692.9

200–400

100–200

50–100

Grasslands, Average Annual N Losses Leading to Indirect N2O Emissions Using the DAYCENT Model, 

1990–2006 (Gg N/state/year)

Figure 6-6

Gg N/state/year

< 10

10–20

20–50

400–872.3

200–400

100–200

50–100
Agriculture 6-23

Methodology

The Revised 1996 IPCC Guidelines (IPCC/UNEP/

OECD/IEA 1997) divide the Agricultural Soil Management 

source category into three components: (1) direct emissions 

from agricultural soils due to N additions to cropland and 

grassland mineral soils, planting of legumes on cropland 

and grassland soils, and drainage and cultivation of organic 

cropland soils, (2) direct emissions from soils due to the 

deposition of manure by livestock on PRP grasslands, 

and (3) indirect emissions from soils and water due to 

N additions and manure deposition to soils that leads to 

volatilization, leaching, or runoff of N and subsequent 

conversion to N2O. Moreover, the 2006 IPCC Guidelines

(IPCC 2006) recommend reporting total emissions from 

managed lands, and, therefore, this chapter includes 

estimates for direct emissions due to asymbiotic fixation of 

N from the atmosphere13 and decomposition of soil organic 

matter and litter.

The methodology used to estimate emissions from 

agricultural soil management in the United States is based 

on a combination of IPCC Tier 1 and 3 approaches. A Tier 

3, process-based model (DAYCENT) was used to estimate 

direct emissions from major crops on mineral (i.e., nonorganic) soils; as well as most of the direct emissions from 

grasslands. The Tier 3 approach is more refined for estimating 

N2O emissions in the United States, accounting for more of 

the environmental and management influences on soil N2O 

emissions than the IPCC Tier 1 method (see Box 6-1 for 

further elaboration). The Tier 1 IPCC methodology was used 

to estimate (1) direct emissions from non-major crops on 

mineral soils, (2) the portion of the grassland direct emissions 

that were not estimated with the Tier 3 DAYCENT model, 

and (3) direct emissions from drainage and cultivation of 

13 N inputs from asymbiotic N fixation are not directly addressed in 

2006 IPCC Guidelines, but are a component of the total emissions from 

managed lands and are included in the Tier 3 approach developed for this 

Inventory.

organic cropland soils. The Tier 1 approach was based on 

the 2006 IPCC Guidelines (IPCC 2006). Indirect emissions 

were also estimated with a combination of DAYCENT and 

the IPCC Tier 1 method.

Several recommendations from IPCC (2006) have been 

adopted that are considered improvements over previous 

IPCC methods, including: (1) estimating the contribution 

of N from crop residues to indirect soil N2O emissions, (2) 

adopting a revised emission factor for direct N2O emissions, 

(3) removing double counting of emissions from N-fixing 

crops associated with the symbiotic and crop residue N 

input categories, (4) using revised crop residue statistics 

to compute N inputs to soils based on harvest yield data, 

and (5) accounting for indirect as well as direct emissions 

from N made available via mineralization of soil organic 

matter and litter, in addition to asymbiotic fixation (i.e., 

computing total emissions from managed land). IPCC (2006) 

recommends reporting all emissions from managed lands, 

largely because management affects all processes leading 

to soil N2O emissions. Agronomic practices, particularly 

tillage, have a pervasive impact on soil processes. In 

past Inventory reports, attempts were made to subtract 

“background” emissions that would presumably occur if 

the lands were not managed. However, this approach is 

likely to be inaccurate for estimating the anthropogenic 

influence on soil N2O emissions. Moreover, if background 

emissions could be measured or modeled based on processes 

unaffected by anthropogenic activity, they would be a 

very small portion of the total emissions due to the high 

inputs of N to agricultural soils from fertilization. Given 

the recommendation from IPCC (2006) and the influence 

of management on all processes leading to N2O emissions 

from soils in agricultural systems, the decision was made to 

report total emissions from managed lands for this source 

category. Annex 3.11 provides more detailed information on 

the methodologies and data used to calculate N2O emissions 

from each component.
6-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Direct N2O Emissions from Cropland Soils

Major Crop Types on Mineral Cropland Soils

The DAYCENT ecosystem model (Del Grosso et al. 

2001, Parton et al. 1998) was used to estimate direct N2O 

emissions from mineral cropland soils that are managed for 

production of major crops—specifically corn, soybeans, 

wheat, alfalfa hay, other hay, sorghum, and cotton—

representing approximately 90 percent of total croplands in 

the United States. DAYCENT simulated crop growth, soil 

organic matter decomposition, greenhouse gas fluxes, and 

key biogeochemical processes affecting N2O emissions, and 

the simulations were driven by model input data generated 

from daily weather records (Thornton et al. 1997, 2000; 

Thornton and Running 1999), land management surveys 

(see citations below), and soil physical properties determined 

from national soil surveys (Soil Survey Staff 2005). 

DAYCENT simulations were conducted for each 

major crop at the county scale in the United States. 

Simulating N2O emissions at the county scale was 

facilitated by soil and weather data that were available 

for every county with more than 100 acres of agricultural 

land. However, land management data (e.g., timing of 

planting, harvesting, intensity of cultivation) were only 

available at the agricultural region level as defined by the 

Agricultural Sector Model (McCarl et al. 1993). There are 

63 agricultural regions in the contiguous United States, 

and most states correspond to one region, except for those 

states with greater heterogeneity in agricultural practices, 

where there are further subdivisions. While several cropping 

systems were simulated for each county in an agricultural 

region with county-level weather and soils data, the model 

parameters that determined the influence of management 

activities on soil N2O emissions (e.g., when crops were 

planted/harvested) did not differ among the counties in 

an agricultural region. Consequently, the results will best 

represent emissions at the regional (i.e., state) and national 

levels due to the scale of management data.

Nitrous oxide emission estimates from DAYCENT are 

influenced by N additions, crop type, irrigation, and other 

factors in aggregate, and, therefore, it is not possible to 

partition N2O emissions by anthropogenic activity directly 

from model outputs (e.g., N2O emissions from synthetic 

fertilizer applications cannot be distinguished from those 

resulting from manure applications). Nitrous oxide emissions 

from managed agricultural lands are the result of interactions 

among anthropogenic activities (e.g., N fertilization, manure 

application, tillage) and other driving variables, such as 

weather and soil characteristics. These factors influence key 

processes associated with N dynamics in the soil profile, 

including immobilization of N by soil microbial organisms, 

decomposition of organic matter, plant uptake, leaching, 

runoff, and volatilization, as well as the processes leading 

to N2O production (nitrification and denitrification). To 

approximate emissions by activity, the amount of mineral N 

added to the soil for each of these sources was determined and 

then divided by the total amount of mineral N that was made 

available in the soil according to the DAYCENT model. The 

percentages were then multiplied by the total N2O emissions 

The Tier 1 approach (IPCC 2006) is based on multiplying activity data on different N sources (e.g., synthetic fertilizer, manure, N fixation, 

etc.) by the appropriate default IPCC emission factors to estimate N2O emissions on a source-by-source basis. The Tier 3 approach developed 

for this Inventory employs a process-based model (i.e., DAYCENT) that represents the interaction of N inputs and the environmental conditions 

at specific locations. Consequently, it is necessary to know the amount of N inputs and also the conditions under which the anthropogenic 

activity is increasing mineral N in a soil profile. The Tier 1 approach requires a minimal amount of activity data, readily available in most 

countries (e.g., total N applied to crops); calculations are simple; and the methodology is highly transparent. The Tier 3 approach is thought 

to produce more accurate estimates; it accounts for land-use and management impacts and their interaction with environmental factors (i.e., 

weather patterns and soil characteristics), which may enhance or dampen anthropogenic influences. However, the Tier 3 approach requires 

more refined activity data (e.g., crop-specific N amendment rates, daily weather, soil types, etc.) and considerable computational resources 

and programming expertise. The Tier 3 methodology is less transparent, and thus it is critical to evaluate the output of Tier 3 methods with 

measured data in order to demonstrate the adequacy of the method for estimating emissions (IPCC 2006). Another important difference 

between the Tier 1 and Tier 3 approaches relates to assumptions regarding N cycling. Tier 1 assumes that N added to a system is subject to 

N2O emissions only during that year and cannot be stored in soils and contribute to N2O emissions in subsequent years. This is a simplifying 

assumption that is likely to create bias in estimated N2O emissions for a specific year. In contrast, the process-based model used in the Tier 

3 approach includes such legacy effects when N is mineralized from soil organic matter and emitted as N2O during subsequent years.

Box 6-1: Tier 1 vs. Tier 3 Approach for Estimating N2O Emissions
Agriculture 6-25

in order to approximate the portion attributed to key practices. 

This approach is only an approximation because it assumes 

that all N made available in soil has an equal probability 

of being released as N2O, regardless of its source, which is 

unlikely to be the case. However, this approach allows for 

further disaggregation by source of N, which is valuable for 

reporting purposes and is similar to the IPCC (2006) Tier 

1 method (which assumes the rate of direct N2O emissions 

does not vary by source). 

DAYCENT was used to estimate direct N2O emissions 

due to mineral N available from: (1) the application of 

synthetic fertilizers, (2) the application of livestock manure, 

(3) the retention of crop residues (i.e., leaving residues 

in the field after harvest instead of burning or collecting 

residues), and (4) mineralization of soil organic matter and 

litter, in addition to asymbiotic fixation. This last source is 

generated internally by the DAYCENT model. For the first 

three practices, annual increases in soil mineral N due to 

anthropogenic activity were obtained or derived from the 

following sources:

•	 Crop-specific N-fertilization rates: Data sources for 

fertilization rates include Alexander and Smith (1990), 

Anonymous (1924), Battaglin and Goolsby (1994), 

Engle and Makela (1947), ERS (1994, 2003), Fraps and 

Asbury (1931), Ibach and Adams (1967), Ibach et al. 

(1964), NFA (1946), NRIAI (2003), Ross and Mehring 

(1938), Skinner (1931), Smalley et al. (1939), Taylor 

(1994), USDA (1966, 1957, 1954, 1946). Information on 

fertilizer use and rates by crop type for different regions 

of the United States were obtained primarily from the 

USDA Economic Research Service Cropping Practices 

Survey (ERS 1997) with additional data from other 

sources, including the National Agricultural Statistics 

Service (NASS 1992, 1999, 2004). 

•	 Managed manure production and application to 

croplands and grasslands: Manure N amendments 

applied to croplands and grasslands (not including 

PRP manure) were determined using USDA Manure N 

Management Databases for 1997 (Kellogg et al. 2000; 

Edmonds et al. 2003). Amendment data for 1997 were 

scaled to estimate values for other years based on the 

availability of managed manure N for application to soils 

in 1997 relative to other years. The amount of available 

nitrogen from managed manure for each livestock type 

was calculated by first determining the population of 

animals that were on feedlots or otherwise housed 

in order to collect and manage the manure. Annual 

animal population data for all livestock types, except 

horses and goats, were obtained for all years from the 

U.S. Department of Agriculture-National Agricultural 

Statistics Service. Population data used for cattle, swine, 

and sheep were downloaded from the USDA NASS 

Population Estimates Database (USDA 2007a). Poultry 

population data were obtained from USDA NASS 

reports (USDA 1995a, 1995b, 1998a, 1999, 2004a, 

2004b, 2006a, 2006b, 2007b, 2007c). Horse population 

data were obtained from the FAOSTAT database (FAO 

2007). Goat population data for 1992, 1997, and 2002 

were obtained from the Census of Agriculture (USDA 

2005); these data were interpolated and extrapolated 

to derive estimates for the other years. Information 

regarding the poultry turnover (i.e., slaughter) rate was 

obtained from state Natural Resource Conservation 

Service personnel (Lange 2000). Additional population 

data for different farm size categories for dairy and swine 

were obtained from the 1992, 1997, and 2002 Census of 

Agriculture (USDA 2005). Once the animal populations 

for each livestock type and management system were 

estimated, these populations were multiplied by a 

typical animal mass constant (USDA 1996, ASAE 

1999; NRC 2000, ERG 2003, EPA 1992, Safley 2000) 

to derive total animal mass for each animal type in each 

management system. Total Kjeldahl N14 excreted per 

year for each livestock type and management system 

was then calculated using daily rates of N excretion per 

unit of animal mass (USDA 1996, ASAE 1999). The 

annual amounts of Kjeldahl N were then summed over 

all livestock types and management systems to derive 

estimates of the annual managed manure N produced. 

Nitrogen available for application was estimated for 

managed systems based on the total amount of N 

produced in manure minus N losses and including the 

addition of N from bedding materials. Nitrogen losses 

include direct nitrous oxide emissions, volatilization 

of ammonia and NOx, and runoff and leaching; more 

information on these losses is available in Annex 3.10, 

Manure Management. Animal-specific bedding factors 

14Total Kjeldahl N is a measure of organically bound N and ammonia N in 

both solid and liquid wastes.
6-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

were set equal to IPCC default factors (IPCC 2006). The 

estimated amount of manure available for application 

was adjusted for the small percent of poultry manure 

used for cattle feed between 1990 and 2002 (Carpenter 

1992, Carpenter and Starkey 2007). The remaining 

manure N that was not applied to major crops and 

grassland was assumed to be applied to non-major 

crop types. Frequency and rates of manure application 

to cropland during the inventory period were estimated 

from data compiled by the USDA Natural Resources 

Conservation Service for 1997 (Edmonds et al. 2003), 

with adjustments based on managed manure N excretion 

in other years of the Inventory. 

•	 Retention of crop residue, N mineralization from 

soil organic matter, and asymbiotic N fixation from 

the atmosphere: The IPCC approach considers this 

information as separate activity data. However, they 

are not treated as separate activity data in DAYCENT 

simulations because residue production, N fixation, 

mineralization of N from soil organic matter, and 

asymbiotic fixation are internally generated by the 

model. In other words, DAYCENT accounts for the 

influence of N fixation, mineralization of N from soil 

organic matter, and retention of crop residue on N2O 

emissions, but these are not model inputs. The total 

input of N from these sources is determined during the 

model simulations.

•	 Historical and modern crop rotation and management 

information (e.g., timing and type of cultivation, 

timing of planting/harvest, etc.): These activity data 

were derived from Hurd (1930, 1929), Latta (1938), 

Iowa State College Staff Members (1946), Bogue 

(1963), Hurt (1994), USDA (2004f), USDA (2000b) as 

extracted by Eve (2001) and revised by Ogle (2002), 

CTIC (1998), Piper et al. (1924), Hardies and Hume 

(1927), Holmes (1902, 1929), Spillman (1902, 1905, 

1907, 1908), Chilcott (1910), Smith (1911), Kezer (ca. 

1917), Hargreaves (1993), ERS (2002), Warren (1911), 

Langston et al. (1922), Russell et al. (1922), Elliott and 

Tapp (1928), Elliott (1933), Ellsworth (1929), Garey 

(1929), Hodges et al. (1930), Bonnen and Elliott (1931), 

Brenner et al. (2002, 2001), and Smith et al. (2002).

DAYCENT simulations produced per-area estimates 

of N2O emissions (g N2O-N m-2) for major crops, which 

were multiplied by the cropland area data to obtain countyscale emission estimates. Cropland area data were from 

NASS (USDA 2006g). The emission estimates by reported 

crop areas in the county were scaled to the regions, and the 

national estimate was calculated by summing results across 

all regions. DAYCENT is sensitive to actual interannual 

variability in weather patterns and other controlling variables, 

so emissions associated with individual activities vary 

through time even if the management practices remain the 

same (e.g., if N fertilization remains the same for two years). 

In contrast, Tier 1 methods do not capture this variability and 

rather have a linear, monotonic response that depends solely 

on management practices. DAYCENT’s ability to capture 

these interactions between management and environmental 

conditions produces more accurate estimates of N2O 

emissions than the Tier 1 method. 

Non-Major Crop Types on Mineral Cropland Soils

The Tier 1 methodology (IPCC 2006) was used to 

estimate direct N2O emissions for mineral cropland soils 

that are managed for production of non-major crop types, 

including barley, oats, tobacco, sugarcane, sugar beets, 

sunflowers, millet, rice, peanuts, and other crops which 

were not included in the DAYCENT simulations. Estimates 

of direct N2O emissions from N applications to non-major 

crop types were based on mineral soil N that was made 

available from the following practices: (1) the application 

of synthetic commercial fertilizers, (2) application of other 

commercial organic fertilizers,15 and (3) the retention 

of above- and below-ground crop residues. Non-manure 

organic amendments were not included in the DAYCENT 

simulations because county-level data were not available 

and this source of fertilizer is a very small portion of total 

organic amendments. Consequently, non-manure organic 

amendments, as well as manure amendments not included 

in the DAYCENT simulations, were included in the Tier 

1 analysis. The following sources were used to derive 

activity data.

15Other commercial organic fertilizers include manure applied to non-major 

crops, dried blood, dried manure, tankage, compost, other, but excludes 

sewage sludge that is used as commercial fertilizer.
Agriculture 6-27

•	 A process-of-elimination approach was used to estimate 

N fertilizer additions for non-major crops, because little 

information exists on their fertilizer application rates. 

The total amount of fertilizer used on farms has been 

estimated by the USGS from sales records (Ruddy et 

al. 2006), and these data were aggregated to obtain 

state-level N additions to farms. After subtracting 

the portion of fertilizer applied to major crops and 

grasslands (see sections on Major Crops and Grasslands 

for information on data sources), the remainder of the 

total fertilizer used on farms was assumed to be applied 

on non-major crops.

•	 A process-of-elimination approach was used to estimate 

manure N additions for non-major crops, because 

little information exists on application rates for these 

crops. The amount of manure N applied to major crops 

and grasslands was subtracted from total manure N 

available for land application (see sections on Major 

Crops and Grasslands for information on data sources), 

and this difference was assumed to be applied to nonmajor crops.

•	 Non-manure organic fertilizer additions were based on 

organic fertilizer consumption statistics, which were 

converted to units of N using average organic fertilizer 

N content (TVA 1991, 1992a, 1993, 1994; AAPFCO 

1995 through 2000a, 2000b, 2002 through 2007).

•	 Crop residue N was derived by combining amounts 

of above- and below-ground biomass, which were 

determined based on crop production yield statistics 

(USDA 1994a, 1998b, 2003, 2005i, 2006b, 2007), 

dry matter fractions (IPCC 2006), linear equations to 

estimate above-ground biomass given dry matter crop 

yields (IPCC 2006), ratios of below-to-above-ground 

biomass (IPCC 2006), and N contents of the residues 

(IPCC 2006).

The total increase in soil mineral N from applied fertilizers 

and crop residues was multiplied by the IPCC (2006) default 

emission factor (IPCC 2006) to derive an estimate of direct 

N2O emissions from non-major crop types.

Drainage and Cultivation of Organic Cropland Soils

Tier 1 methods were used to estimate direct N2O 

emissions due to drainage and cultivation of organic soils 

at a state scale. State-scale estimates of the total area of 

drained and cultivated organic soils were obtained from 

the Natural Resources Inventory (NRI) (USDA 2000b, as 

extracted by Eve 2001 and amended by Ogle 2002), using 

temperature and precipitation data from Daly et al. (1994, 

1998) to subdivide areas into temperate and tropical climates. 

Data were available for 1982, 1992 and 1997, which were 

linearly interpolated and extrapolated to estimate areas for 

the other years in the inventory time series. To estimate 

annual emissions, the total temperate area was multiplied by 

the IPCC default emission factor for temperate regions, and 

the total sub-tropical area was multiplied by the average of 

the IPCC default emission factors for temperate and tropical 

regions (IPCC 2006).

Direct N2O Emissions from Grassland Soils 

As with N2O from croplands, the Tier 3 process-based 

DAYCENT model and Tier 1 method described in the IPCC 

(2006) guidelines were combined to estimate emissions 

from grasslands. Grasslands include pastures and rangelands 

used for grass forage production, where the primary use is 

livestock grazing. Rangelands are typically extensive areas 

of native grasslands that are not intensively managed, while 

pastures are often seeded grasslands, possibly following tree 

removal, which may or may not be improved with practices 

such as irrigation and interseeding legumes.

DAYCENT was used to simulate county-scale N2O 

emissions from grasslands resulting from manure deposited 

by livestock directly onto the pasture (i.e., PRP manure, 

which is simulated internally within the model), N fixation 

from legume seeding, managed manure amendments (i.e., 

manure other than PRP manure), and synthetic fertilizer 

application. The simulations used the same weather, soil, 

and synthetic N fertilizer data as discussed under the section 

for Major Crop Types on Mineral Cropland Soils. Managed 

manure N amendments to grasslands were estimated from 

Edmonds et al. (2003) and adjusted for annual variation 

using data on the availability of managed manure N for 

application to soils, according to methods described in Annex 

3.11. Other N inputs were simulated within the DAYCENT 

framework, including N input from mineralization due to 

decomposition of soil organic matter and plant litter, as 

well as asymbiotic fixation of N from the atmosphere and 

atmospheric N deposition.

DAYCENT simulations produced per-area estimates of 

N2O emissions (g N2O-N m-2) for pasture and rangelands, 

which were multiplied by the reported pasture and rangeland 
6-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

areas in the county. Grassland area data were obtained 

from the NRI (USDA 2000b). The 1997 NRI area data for 

pastures and rangeland were aggregated to the county level 

to estimate the grassland areas for 1995 to 2006, and the 

1992 NRI pasture and rangeland data were aggregated to 

the county level to estimate areas from 1990 to 1994. The 

county estimates were scaled to the 63 agricultural regions, 

and the national estimate was calculated by summing results 

across all regions.

Manure N deposition from grazing animals is modeled 

internally within DAYCENT. Comparisons with estimates of 

total manure deposited on PRP (see Annex 3.11) showed that 

DAYCENT accounted for approximately 73 percent of total 

PRP manure. The remainder of the PRP manure N excretions 

were assumed to be excreted on federal grasslands (i.e., 

DAYCENT simulations were only conducted for privatelyowned grasslands), and the N2O emissions were estimated 

using the Tier 1 method with IPCC default emission factors 

(IPCC 2006).

Sewage sludge was assumed to be applied on 

grasslands because of the heavy metal content and other 

pollutants in human waste that limit its use as an amendment 

to croplands. Sewage sludge application was estimated 

from data compiled by EPA (1993, 1999, 2003), McFarland 

(2001), and NEBRA (2007). Sewage sludge data on soil 

amendments in agricultural lands were only available at 

the national scale, and it was not possible to associate 

application with specific soil conditions and weather at the 

county scale. Consequently, emissions from sewage sludge 

were also estimated using the Tier 1 method with IPCC 

default emission factors (IPCC 2006).

Total Direct N2O Emissions from Cropland and 

Grassland Soils

Emission estimates from DAYCENT and the IPCC 

method were summed to provide total national emissions 

for grasslands in the United States. Annual direct emissions 

from major and non-major crops on mineral cropland soils, 

from drainage and cultivation of organic cropland soils, and 

from grassland soils were summed to obtain total direct N2O 

emissions from agricultural soil management (see Table 6-13 

and Table 6-14).

Indirect N2O Emissions from Managed Soils of all 

Land-Use Types 

This section describes the methods used for estimating 

indirect soil N2O emissions from all land-use types (i.e., 

croplands, grasslands, forest lands, and settlements). Indirect 

N2O emissions occur when mineral N made available through 

anthropogenic activity is transported from the soil either in 

gaseous or aqueous forms and later converted into N2O. 

There are two pathways leading to indirect emissions. The 

first pathway results from volatilization of N as NOx and 

NH3 following application of synthetic fertilizer or organic 

amendments (e.g., manure, sewage sludge) and deposition 

of PRP manure N made available from mineralization of 

soil organic matter and asymbiotic fixation also contributes 

to volatilized N emissions. Through atmospheric deposition, 

volatilized N can be returned to soils, and a portion is emitted 

to the atmosphere as N2O. The second pathway occurs via 

leaching and runoff of soil N (primarily in the form of nitrate 

[NO3

-

]) that was made available through anthropogenic 

activity on managed lands, mineralization of soil organic 

matter, asymbiotic fixation, and atmospheric deposition. 

The nitrate is subject to denitrification in water bodies, 

which leads to additional N2O emissions. Regardless of the 

eventual location of the indirect N2O emissions, the emissions 

are assigned to the original source of the N for reporting 

purposes, which here includes croplands, grasslands, forest 

lands, and settlements.

Indirect N2O Emissions from Atmospheric Deposition 

of Volatilized N from Managed Soils

Similarly to the direct emissions calculation, several 

approaches were combined to estimate the amount of applied 

N that was transported from croplands, grasslands, forest 

lands, and settlements, through volatilization. DAYCENT was 

used to simulate the amount of N transported from land areas 

whose direct emissions were simulated with DAYCENT (i.e., 

major croplands and most grasslands), while the Tier 1 method 

was used for areas that were not simulated with DAYCENT 

(i.e., non-major croplands, sewage sludge application on 

grasslands, PRP manure N excretion on federal grasslands) 

(IPCC 2006). The IPCC (2006) default emission factor was 

used to estimate indirect N2O emissions associated with the 

amount of volatilized N (Table 6-16).
Agriculture 6-29

Indirect N2O from Leaching/Runoff

As in the calculations of indirect emissions from 

volatilized N, several approaches were combined to estimate 

the amount of applied N that was transported from croplands, 

grasslands, forest lands, and settlements through leaching 

and surface runoff into water bodies. DAYCENT was used 

to simulate the amount of N transported from major cropland 

types and most grasslands. N transport from all other areas 

(i.e., non-major croplands, sewage sludge amendments on 

grasslands, PRP manure N excreted on federal grasslands, 

in addition to N inputs on settlements and forest lands) was 

estimated using the IPCC (2006) default factors for the 

amount of N subject to leaching and runoff from mineral 

fertilizer, manure, above- and below-ground crop residues, 

soil organic matter decomposition and asymbiotic fixation. 

The IPCC (2006) default emission factor was used to estimate 

indirect N2O emissions associated with N losses through 

leaching and runoff (Table 6-16).

Uncertainty

Uncertainty was estimated differently for each of 

the following four components of N2O emissions from 

agricultural soil management: (1) direct emissions calculated 

by DAYCENT, (2) the components of indirect emissions (N 

volatilized and leached or runoff) calculated by DAYCENT 

(3) direct emissions not calculated by DAYCENT, and (4) 

indirect emissions not calculated by DAYCENT.

Uncertainties from the Tier 1 and Tier 3 estimates were 

combined using simple error propagation (IPCC 2006), and the 

results are summarized in Table 6-17. Agricultural direct soil 

N2O emissions in 2006 were estimated to be between 191.7 

and 238.9 Tg CO2 Eq. at a 95 percent confidence level. This 

indicates a range of 11 percent below and 11 percent above the 

2006 emission estimate of 214.7 Tg CO2 Eq. The indirect soil 

N2O emissions in 2006 were estimated to range from 28.0 to 

113.2 Tg CO2 Eq. at a 95 percent confidence level, indicating 

an uncertainty of 44 percent below and 125 percent above the 

2006 emission estimate of 50.3 Tg CO2 Eq.

QA/QC and Verification

For quality control, DAYCENT results for N2O 

emissions and NO3 leaching were compared with field data 

representing various cropped/grazed systems, soils types, and 

climate patterns (Del Grosso et al. 2005). N2O measurement 

data were available for seven sites in the United States and 

one in Canada, representing 25 different combinations of 

fertilizer treatments and cultivation practices. DAYCENT 

estimates of N2O emissions were closer to measured values 

at all sites except for Colorado irrigated corn (Figure 6-7). 

In general, IPCC Tier 1 methodology tends to over-estimate 

when observed values are low and under-estimate when 

observed values are high, while DAYCENT estimates are less 

biased. This is not surprising because DAYCENT accounts 

for site-level factors (weather, soil type) that influence N2O 

emissions. NO3 leaching data were available for three sites 

Table 6-17: Quantitative Uncertainty Estimates of N2O Emissions from Agricultural Soil Management in 2006 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Direct Soil N2O Emissions N2O 214.7 191.7 238.9 -11% +11%

Indirect Soil N2O Emissions N2O 50.3 28.0 113.2 -44% +125%

Note: Due to lack of data, uncertainties in areas for major crops, managed manure N production and PRP manure N production are currently treated as certain.

Measured

DAYCENT

IPCC

CO

dryland

wheat

NE

dryland

wheat

MI corn/

soy/

alfalfa

TN corn CO

irrigated

corn

CO

irrigated

corn/

barley

Ontario

corn

g N/ha/day

0

10

20

30

40

50

60

Comparison of Measured Emissions at Field Sites with 

Modeled Emissions Using the DAYCENT Simulation Model

Figure 6-7
6-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

in the United States representing nine different combinations 

of fertilizer amendments. Linear regressions of simulated 

vs. observed emission and leaching data yielded correlation 

coefficients of 0.73 and 0.96 for annual N2O emissions and 

NO3 leaching, respectively. This comparison demonstrates 

that DAYCENT provides relatively high predictive capability 

for N2O emissions and NO3 leaching, and is also an 

improvement over the IPCC Tier 1 method (see additional 

information in Annex 3.11). 

Spreadsheets containing input data and PDFs required 

for DAYCENT simulations of major croplands and 

grasslands and unit conversion factors were checked, as well 

as the program scripts that were used to run the Monte Carlo 

uncertainty analysis. An error was identified in direct N2O 

estimates from major crops. The units were not converted 

correctly with the transfer of data between the DAYCENT 

model and the structural uncertainty estimator, leading to an 

over-estimation of direct N2O emissions from major crops. 

The error has been resolved and corrected. Spreadsheets 

containing input data and emission factors required for the 

Tier 1 approach used for non-major crops and grasslands 

not simulated by DAYCENT were checked and no errors 

were found. 

Recalculations Discussion

Revisions in the calculations for the Agricultural Soil 

N2O emission estimates included (1) using state-level N data 

for on-farm use to estimate synthetic N fertilizer application 

on non-major crops, (2) including uncertainty in DAYCENT 

outputs of N volatilization and N leaching/runoff in the 

calculation of uncertainty for indirect emissions, (3) using a 

default uncertainty of ±50 percent for Tier 1 uncertainties that 

were addressed in previous inventory, including crop yields 

and organic fertilizers, (4) assuming that manure N available 

for land application not accounted for by the DAYCENT 

simulations was applied to non-major crop types, (5) revising 

DAYCENT parameterization for sorghum, and (6) correcting 

an error in the empirically-based uncertainty estimator. 

In the previous Inventory, N fertilizer application to minor 

crops was based on total N available for application after 

subtracting the amount applied to major crops, settlements, 

and forest lands. In the current Inventory, a USGS study 

(Ruddy et al. 2006) provides data from sales records about 

the on-farm use of fertilizers, which were used to estimate 

the amount of N applied to non-major crops after subtracting 

the amount estimated for major crops from the DAYCENT 

simulations. Previously, it was assumed that 90 percent 

of the synthetic N fertilizer used in the United States was 

applied to agricultural soils whereas the on-farm-use data 

raise the amount to 97 percent. In addition, after accounting 

for the amount applied to major crops and grasslands in the 

DAYCENT simulations, the current Inventory assumes that 

all manure N available for agricultural land application is 

applied to non-major crops. Due to these changes, direct N2O 

emissions from non-major crops are approximately 83 percent 

higher, on average, compared to the previous Inventory. 

However, direct soil N2O emissions from major crops 

reported in the 1990-2005 Inventory were over-estimated by 

approximately a factor of 2 as a result of a unit conversion error 

in the empirically-based uncertainty estimator. Because major 

crops are the greatest source, total emission estimates are 

approximately 27.5 percent lower, on average, than reported 

in the 1990-2005 Inventory. The revised parameterization for 

sorghum had a minor influence on the emission estimates.

Planned Improvements

Three major improvements are planned for the 

Agricultural Soil Management sector. The first improvement 

is to incorporate more land-use survey data from the NRI 

(USDA 2000b) into the DAYCENT simulation analysis, 

beyond the area estimates for rangeland and pasture that 

are currently used to estimate emissions from grasslands. 

NRI has a record of land-use activities since 1982 for all 

U.S. agricultural land, which is estimated at about 386 

Mha. NASS is used as the basis for land-use records in the 

current Inventory, and there are three major disadvantages 

to this cropping survey. First, most crops are grown in 

rotation with other crops (e.g., corn-soybean), but NASS 

data provide no information regarding rotation histories. In 

contrast, NRI is designed to track rotation histories, which 

is important because emissions from any particular year 

can be influenced by the crop that was grown the previous 

year. Second, NASS does not conduct a complete survey of 

cropland area each year, leading to gaps in the land base. 

NRI does provide a complete history of cropland areas for 

four out of every five years from 1979 to 1997, and then 

every year after 1998. Third, the current Inventory based on 

NASS does not quantify the influence of land-use change 

on emissions, which can be addressed using the NRI survey 

records. NRI also provides additional information on pasture 

land management that can be incorporated into the analysis 
Agriculture 6-31

(particularly the use of irrigation). Using NRI data will also 

make the Agricultural Soil N2O methods more consistent with 

the methods used to estimate C stock changes for agricultural 

soils. However, the structure of model input files that contain 

land management data will need to be extensively revised to 

facilitate use of NRI data.

The second planned improvement is to further refine the 

uncertainty analysis. New studies are being completed and 

published evaluating agricultural management impacts on 

soil N2O emissions, and these studies can be incorporated into 

the empirical analysis, leading to a more robust assessment 

of structural uncertainty in DAYCENT. Moreover, structural 

uncertainty is currently only evaluated for emission estimates 

in croplands, but structural uncertainty is likely to be 

significant for grasslands as well, and it is anticipated that 

the analysis of structural uncertainty could be expanded in 

the near future to include grasslands. In addition, the Monte 

Carlo analysis will be expanded to address uncertainties in 

activity data related to crop- and grassland areas, as well 

as irrigation and tillage histories. Currently, the land-area 

statistics are treated as certain because the NASS data do 

not include a measure of uncertainty. Incorporating land-use 

survey data from the NRI will facilitate the assessment of 

uncertainties in agricultural activity data.

The third planned improvement is to further evaluate 

the application of manure to major and minor crops, as well 

as N recovery and losses from manure management systems 

and field application. Manure amendments are a key source 

of N leading to N2O emissions so any further improvements 

in this estimation will reduce uncertainties in the emission 

estimates. We will also evaluate potential for change in 

application rates over time due to regulation of confined 

animal feeding operations; this will improve the emission 

estimates and reduce uncertainty. Additional improvements 

are minor but will lead to more accurate estimates, including 

updating DAYMET weather for more recent years.

6.5. Field Burning of Agricultural 

Residues (IPCC Source Category 4F)

Farming activities produce large quantities of agricultural 

crop residues, and farmers use or dispose of these residues in 

a variety of ways. For example, agricultural residues can be 

left on or plowed into the field; composted and then applied 

to soils; landfilled; or burned in the field. Alternatively, they 

can be collected and used as fuel, animal bedding material, 

supplemental animal feed, or construction material. Field 

burning of crop residues is not considered a net source 

of CO2, because the carbon released to the atmosphere as 

Table 6-18: CH4 and N2O Emissions from Field Burning of Agricultural Residues (Tg CO2 Eq.)

Gas/Crop Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 0.7 0.7 0.8 0.8 0.7 0.8 0.9 0.9 0.8 

Wheat 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Rice 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Sugarcane + + + + + + + + + 

Corn 0.3 0.3 0.4 0.3 0.3 0.4 0.4 0.4 0.4 

Barley + + + + + + + + + 

Soybeans 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 

Peanuts + + + + + + + + + 

N2O 0.4 0.4 0.5 0.5 0.4 0.4 0.5 0.5 0.5 

Wheat + + + + + + + + + 

Rice + + + + + + + + + 

Sugarcane + + + + + + + + + 

Corn 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Barley + + + + + + + + + 

Soybeans 0.2 0.2 0.3 0.3 0.3 0.2 0.3 0.3 0.3 

Peanuts + + + + + + + + + 

Total 1.1 1.0 1.3 1.2 1.1 1.2 1.4 1.4 1.3 

+ Less than 0.05 Tg CO2 Eq. 

Note: Totals may not sum due to independent rounding.
6-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

CO2 during burning is assumed to be reabsorbed during the 

next growing season. Crop residue burning is, however, a 

net source of CH4, N2O, CO, and NOx, which are released 

during combustion. 

Field burning is not a common method of agricultural 

residue disposal in the United States. The primary crop types 

whose residues are typically burned in the United States are 

wheat, rice, sugarcane, corn, barley, soybeans, and peanuts. 

Less than 5 percent of the residue for each of these crops is 

burned each year, except for rice.16 Annual emissions from 

this source over the period 1990 to 2006 have remained 

relatively constant, averaging approximately 0.8 Tg CO2

Eq. (36 Gg) of CH4 and 0.4 Tg CO2 Eq. (1 Gg) of N2O (see 

Table 6-18 and Table 6-19).

Methodology

The Tier 2 methodology used for estimating greenhouse 

gas emissions from field burning of agricultural residues in 

the United States is consistent with IPCC (2006) (for more 

details, see Box 6-2). In order to estimate the amounts of 

16The fraction of rice straw burned each year is significantly higher than 

that for other crops (see “Methodology” discussion below).

carbon (C) and nitrogen (N) released during burning, the 

following equation was used:17

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

17As 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.

CH4 and N2O Emissions from Field Burning of 

Agricultural Residues = (Fraction of Residues Burned 

In Situ) × (Mass of Fuel Available for Combustion) ×

(Burning Efficiency) × (Emission Factor) × 10-3

where,

Burning Efficiency = The proportion of prefire 

fuel biomass consumed

To calculate the mass of fuel available for combustion, the 

following equation was used:

Mass of Fuel Available for Combustion = 

(Annual Crop Production) × (Residue/Crop Product Ratio) 

× (Dry Matter Content of the Residue) 

To calculate the emission factor, the following equation 

was used:

Emission Factor = (Combustion Efficiency) 

× (C or N Content of the Residue) × (Emissions Ratio) 

× (Conversion Factor) × 1,000

Table 6-19: CH4, N2O, CO, and NOx Emissions from Field Burning of Agricultural Residues (Gg)

Gas/Crop Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 33 32 38 37 34 38 42 41 39 

Wheat 7 5 5 5 4 6 5 5 4 

Rice 4 4 4 4 3 5 4 5 4 

Sugarcane 1 1 1 1 1 1 1 1 1 

Corn 13 13 17 16 15 17 20 19 18 

Barley 1 1 1 + + + + + + 

Soybeans 7 8 10 11 10 9 11 11 12 

Peanuts + + + + + + + + + 

N2O 1 1 1 1 1 1 2 2 2 

Wheat + + + + + + + + + 

Rice + + + + + + + + + 

Sugarcane + + + + + + + + + 

Corn + + + + + + + + + 

Barley + + + + + + + + + 

Soybeans 1 1 1 1 1 1 1 1 1 

Peanuts + + + + + + + + + 

CO 691 663 792 774 709 800 879 860 825 

NOx 28 29 35 35 33 34 39 39 38 

+ Less than 0.5 Gg

Note: Totals may not sum due to independent rounding.
Agriculture 6-33

The types of crop residues burned in the United States 

were determined from various state-level greenhouse gas 

emission inventories (ILENR 1993, Oregon Department of 

Energy 1995, Wisconsin Department of Natural Resources 

1993) and publications on agricultural burning in the United 

States (Jenkins et al. 1992, Turn et al. 1997, EPA 1992). 

Crop production data for all crops except rice in 

Florida and Oklahoma were taken from the USDA’s Field 

Crops, Final Estimates 1987–1992, 1992–1997, 1997–2002

(USDA 1994, 1998, 2003), and Crop Production Summary 

(USDA 2005, 2006, 2007). Rice production data for Florida 

and Oklahoma, which are not collected by USDA, were 

estimated separately. Average primary and ratoon crop yields 

for Florida (Schueneman and Deren 2002) were applied to 

Florida acreages (Schueneman 1999b, 2001; Deren 2002; 

Kirstein 2003, 2004; Cantens 2004, 2005; Gonzalez 2007a), 

and crop yields for Arkansas (USDA 1994, 1998, 2003, 

2005, 2006) were applied to Oklahoma acreages18 (Lee 2003 

through 2006). The production data for the crop types whose 

residues are burned are presented in Table 6-20. 

The percentage of crop residue burned was assumed 

to be 3 percent for all crops in all years, except rice, based 

on state inventory data (ILENR 1993, Oregon Department 

of Energy 1995, Noller 1996, Wisconsin Department of 

Natural Resources 1993, and Cibrowski 1996). Estimates 

of the percentage of rice residue burned were derived from 

state-level estimates of the percentage of rice area burned 

each year, which were multiplied by state-level annual 

rice production statistics. The annual percentages of rice 

area burned in each state were obtained from agricultural 

extension agents in each state and reports of the California 

Air Resources Board (Anonymous 2006; Bollich 2000; 

California Air Resources Board 1999, 2001; Cantens 2005; 

Deren 2002; Fife 1999; Guethle 2007; Klosterboer 1999a, 

1999b, 2000 through 2003; Lancero 2006, 2007; Lee 2005 

through 2007; Lindberg 2002 through 2005; Linscombe 

1999a, 1999b, 2001 through 2007; Najita 2000, 2001; 

Sacramento Valley Basinwide Air Pollution Control Council 

2005, 2007; Schueneman 1999a, 1999b, 2001; Stansel 

2004, 2005; Street 2001 through 2003; Texas Agricultural 

Experiment Station 2006, 2007; Walker 2004 through 2007; 

Wilson 2003 through 2007) (see Table 6-21). The estimates 

provided for Florida remained constant over the entire 1990 

through 2006 period, while the estimates for all other states 

varied over the time series, except for Missouri, which 

remained constant through 2005 and dropped in 2006. For 

California, the annual percentages of rice area burned in 

the Sacramento Valley are assumed to be representative of 

burning in the entire state, because the Sacramento Valley 

accounts for over 95 percent of the rice acreage in California 

(Fife 1999). These values generally declined between 1990 

and 2006 because of a legislated reduction in rice straw 

18Rice production yield data are not available for Oklahoma, so the Arkansas 

values are used as a proxy.

where,

Combustion = The proportion of CH4 or 

Efficiency N2O released with respect 

to the total amount of C or 

N available in the burned 

material, respectively

Emissions Ratio = g CH4-C/g C released or g 

N2O-N/g N released

Conversion Factor = Molecular weight ratio of 

CH4:C or N2O:N

This Inventory calculates emissions from Burning of 

Agricultural Residues using a Tier 2 methodology that is based on 

IPCC/UNEP/OECD/IEA (1997) and incorporates crop- and countryspecific emission factors and variables. The equation used in this 

Inventory varies slightly in form from the one presented in the IPCC 

(2006) guidelines, but both equations rely on the same underlying 

variables. The IPCC (2006) equation was developed to be broadly 

applicable to all types of biomass burning, and, thus, is not specific 

to agricultural residues. IPCC (2006) default factors are provided 

only for four crops (wheat, corn, rice, and sugarcane), while this 

Inventory analyzes emissions from seven crops. A comparison of 

the methods and factors used in (1) the current Inventory and (2) 

the default IPCC (2006) approach was undertaken to determine 

the magnitude of the difference in overall estimates resulting from 

the two approaches. Since the default IPCC (2006) approach calls 

for area burned data that are currently unavailable for the United 

States, estimates of area burned were developed using USDA data 

on area harvested for each crop multiplied by the estimated fraction 

of residue burned for that crop (see Table 6-22). 

The IPCC (2006) default run resulted in 20 percent higher 

emissions of CH4 and 36 percent higher emissions of N2O than 

the current estimates in this Inventory. It was determined that it is 

reasonable to maintain the current methodology, since the IPCC 

(2006) defaults are only available for four crops and are worldwide 

average estimates, while current Inventory estimates are based on 

U.S.-specific, crop-specific, published data.

Box 6-2: Comparison of Tier 2 U.S. Inventory Approach 

and IPCC (2006) Default Approach
6-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

burning (Lindberg 2002), although there was a slight increase 

from 2004 to 2005 (see Table 6-21). 

All residue/crop product mass ratios except sugarcane 

were obtained from Strehler and Stützle (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 Stützle 

(1987). Peanut dry matter content was obtained through 

personal communications with Jen Ketzis (1999), who 

accessed Cornell University’s Department of Animal 

Science’s computer model, Cornell Net Carbohydrate and 

Protein System. The residue carbon contents and nitrogen 

contents for all crops except soybeans and peanuts are 

from Turn et al. (1997). The residue C content for soybeans 

and peanuts is the IPCC default (IPCC/UNEP/OECD/IEA 

1997). The N content of soybeans is from Barnard and 

Kristoferson (1985). The N content of peanuts is from 

Ketzis (1999). These data are listed in Table 6-22. The 

burning efficiency was assumed to be 93 percent, and the 

combustion efficiency was assumed to be 88 percent, for 

all crop types (EPA 1994). Emission ratios for all gases 

(see Table 6-23) were taken from the Revised 1996 IPCC 

Guidelines (IPCC/UNEP/OECD/IEA 1997).

Table 6-21: Percent of Rice Area Burned by State

State 1990 1995 2000 2001 2002 2003 2004 2005 2006

Arkansas 13% 13% 13% 13% 16% 22% 17% 22% 27%

California 75% 59% 27% 23% 13% 14% 11% 16% 10%

Florida* 0% 0% 0% 0% 0% 0% 0% 0% 0%

Louisiana 6% 6% 5% 4% 3% 3% 3% 3% 5%

Mississippi 10% 10% 40% 40% 8% 65% 23% 23% 25%

Missouri 18% 18% 18% 18% 18% 18% 18% 18% 3%

Oklahoma 90% 90% 90% 90% 90% 100% 88% 94% 0%

Texas 1% 1% 0% 0% 0% 0% 0% 0% 0%

*Although rice is cultivated in Florida, crop residue burning is illegal.

Table 6-20: Agricultural Crop Production (Gg of Product)

Crop 1990 1995 2000 2001 2002 2003 2004 2005 2006

Wheat 74,292 59,404 60,641 53,001 43,705 63,814 58,738 57,280 49,316 

Rice 7,114 7,947 8,705 9,794 9,601 9,084 10,565 10,150 8,813 

Sugarcane 25,525 27,922 32,762 31,377 32,253 30,715 26,320 24,137 26,752 

Corn* 201,534 187,970 251,854 241,377 227,767 256,278 299,914 282,311 267,598 

Barley 9,192 7,824 6,919 5,407 4,940 6,059 6,091 4,613 3,920 

Soybeans 52,416 59,174 75,055 78,671 75,010 66,778 85,013 83,368 86,770 

Peanuts 1,635 1,570 1,481 1,940 1,506 1,880 1,945 2,209 1,576 

*Corn for grain (i.e., excludes corn for silage).

Table 6-22: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues

Crop Residue/

Crop Ratio

Fraction of 

Residue Burned

Dry Matter 

Fraction

C 

Fraction

N

Fraction

Burning 

Efficiency

Combustion 

Efficiency

Wheat 1.3 0.03 0.93 0.4428 0.0062 0.93 0.88

Rice 1.4 Variable 0.91 0.3806 0.0072 0.93 0.88

Sugarcane 0.8 0.03 0.62 0.4235 0.0040 0.93 0.88

Corn 1.0 0.03 0.91 0.4478 0.0058 0.93 0.88

Barley 1.2 0.03 0.93 0.4485 0.0077 0.93 0.88

Soybeans 2.1 0.03 0.87 0.4500 0.0230 0.93 0.88

Peanuts 1.0 0.03 0.86 0.4500 0.0106 0.93 0.88
Agriculture 6-35

Uncertainty

A significant source of uncertainty in the calculation 

of non-CO2 emissions from field burning of agricultural 

residues is in the estimates of the fraction of residue of each 

crop type burned each year. Data on the fraction burned, 

as well as the gross amount of residue burned each year, 

are not collected at either the national or state level. In 

addition, burning practices are highly variable among crops 

and among states. The fractions of residue burned used in 

these calculations were based upon information collected 

by state agencies and in published literature. Based on 

expert judgment, uncertainty in the fraction of crop residue 

burned ranged from zero to 100 percent, depending on the 

state and crop type.

The results of the Tier 2 Monte Carlo uncertainty 

analysis are summarized in Table 6-24. CH4 emissions from 

field burning of agricultural residues in 2006 were estimated 

to be between 0.3 and 1.5 Tg CO2 Eq. at a 95 percent 

confidence level. This indicates a range of 65 percent below 

and 79 percent above the 2006 emission estimate of 0.8 

Tg CO2 Eq. Also at the 95 percent confidence level, N2O 

emissions were estimated to be between 0.2 and 0.9 Tg CO2

Eq. (or approximately 64 percent below and 73 percent 

above the 2006 emission estimate of 0.5 Tg CO2 Eq.). 

QA/QC and Verification

A source-specific QA/QC plan for field burning of 

agricultural residues was implemented. This effort included 

a Tier 1 analysis, as well as portions of a Tier 2 analysis. 

The Tier 2 procedures focused on comparing trends across 

years, states, and crops to attempt to identify any outliers or 

inconsistencies. No problems were found. 

Recalculations Discussion

The crop production data for 2005 and 2006 were 

updated using data from USDA (2007). This change resulted 

in an increase in the CH4 emission estimate for 2005 of 0.2 

percent, and a decrease in the N2O emission estimate for 

2005 of 0.1 percent relative to the previous Inventory. In 

addition, a more robust uncertainty analysis was run for 

the current Inventory, taking into account shared variables 

between the Field Burning of Agricultural Residues and 

Rice Cultivation sources and correcting errors that were 

identified in the uncertainty analysis undertaken for the 

previous Inventory. These changes resulted in a greater 

uncertainty range surrounding the 2006 estimates than 

those presented in the previous Inventory for the 2005 

emission estimates.

Table 6-23: Greenhouse Gas Emission Ratios 

Gas Emission Ratio

CH4

a 0.005

COa 0.060

N2Ob 0.007

NOx

b 0.121

a Mass of C compound released (units of C) relative to mass of total 

C released from burning (units of C).

b Mass of N compound released (units of N) relative to mass of total 

N released from burning (units of N).

Table 6-24: Tier 2 Uncertainty Estimates for CH4 and N2O Emissions from Field Burning of Agricultural Residues 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Field Burning of Agricultural Residues CH4 0.8 0.3 1.5 -65% +79%

Field Burning of Agricultural Residues N2O 0.5 0.2 0.9 -64% +73%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
6-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Planned Improvements

The estimated 3 percent of crop residue burned for all 

crops, except rice, is based on data gathered from several 

state greenhouse gas inventories. This fraction is the most 

statistically significant input to the emissions equation, and 

an important area for future improvement. More crop- and 

state-specific information on the fraction burned will be 

investigated by literature review and/or by contacting state 

departments of agriculture. 

Preliminary research on agricultural burning in the 

United States indicates that residues from several additional 

crop types (e.g., grass for seed, blueberries, and fruit and 

nut trees) are burned. Whether sufficient information 

exists for inclusion of these additional crop types in future 

inventories is being investigated. The extent of recent state 

crop-burning regulations is also being investigated.
Land Use, Land-Use Change, and Forestry 7-1

7. Land Use, Land-Use Change, 

and Forestry

T

his chapter provides an assessment of the net greenhouse gas flux1 resulting from the uses and changes in land 

types and forests in the United States. The Intergovernmental Panel on Climate Change (IPCC) Good Practice 

Guidance for Land Use, Land-Use Change, and Forestry (IPCC 2003) recommends reporting fluxes according 

to changes within and conversions between certain land-use types, termed forest land, cropland, grassland, and settlements 

(as well as wetlands). The greenhouse gas flux from Forest Land Remaining Forest Land is reported using estimates of 

changes in forest carbon (C) stocks, non-carbon dioxide (CO2) emissions from forest fires, and the application of synthetic 

fertilizers to forest soils. The greenhouse gas flux reported in this chapter from agricultural lands (i.e., cropland and grassland) 

includes changes in organic C stocks in mineral and organic soils due to land use and management, and emissions of CO2

due to the application of crushed limestone and dolomite to managed land (i.e., soil liming) and urea fertilization. Fluxes 

are reported for four agricultural land use/land-use change categories: Cropland Remaining Cropland, Land Converted to 

Cropland, Grassland Remaining Grassland, and Land Converted to Grassland. Fluxes resulting from Settlements Remaining 

Settlements include those from urban trees and soil fertilization. Landfilled yard trimmings and food scraps are accounted 

for separately under Other.

The estimates in this chapter, with the exception of CO2 fluxes from wood products and urban trees, and CO2 emissions 

from liming and urea fertilization, are based on activity data collected at multiple-year intervals, which are in the form of 

forest, land-use, and municipal solid waste surveys. CO2 fluxes from forest C stocks (except the wood product components) 

and from agricultural soils (except the liming component) are calculated on an average annual basis from data collected 

in intervals ranging from 1 to 10 years. The resulting annual averages are applied to years between surveys. Calculations 

of non-CO2 emissions from forest fires are based on forest CO2 flux data. Agricultural mineral and organic soil C flux 

calculations are based primarily on national surveys, so these results are largely constant over multi-year intervals, with 

large discontinuities between intervals. For the landfilled yard trimmings and food scraps source, periodic solid waste survey 

data were interpolated so that annual storage estimates could be derived. In addition, because the most recent national 

forest, and land-use surveys were completed prior to 2005, the estimates of CO2 flux from forests, agricultural soils, and 

landfilled yard trimmings and food scraps are based in part on extrapolation. CO2 flux from urban trees is based on neither 

annual data nor periodic survey data, but instead on data collected over the period 1990 through 1999. This flux has been 

applied to the entire time series, and periodic U.S. census data on changes in urban area have been used to develop annual 

estimates of CO2 flux.

Land use, land-use change, and forestry activities in 2006 resulted in a net C sequestration of 883.7 Tg CO2 Eq. (241.0 

Tg C) (Table 7-1 and Table 7-2). This represents an offset of approximately 14.8 percent of total U.S. CO2 emissions. Total 

1The term “flux” is used here to encompass both emissions of greenhouse gases to the atmosphere, and removal of C from the atmosphere. Removal of 

C from the atmosphere is also referred to as “carbon sequestration.”
7-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

land use, land-use change, and forestry net C sequestration2

increased by approximately 20 percent between 1990 and 

2006. This increase was primarily due to an increase in 

the rate of net C accumulation in forest C stocks. Net C 

accumulation in Settlements Remaining Settlements, Land 

Converted to Grassland, and Cropland Remaining Cropland

increased, while net C accumulation in landfilled yard 

trimmings and food scraps slowed over this period. The 

Grassland Remaining Grassland land-use category resulted 

in a net C sink from 1990 through 1994 and then remained 

a fairly constant emission source. Emissions from Land 

Converted to Cropland declined between 1990 and 2006.

2Carbon sequestration estimates are net figures. The C stock in a given pool 

fluctuates due to both gains and losses. When losses exceed gains, the C 

stock decreases, and the pool acts as a source. When gains exceed losses, 

the C stock increases, and the pool act as a sink. This is also referred to as 

net C sequestration.

Emissions from Land Use, Land-Use Change, and 

Forestry are shown in Table 7-3 and Table 7-4. Liming of 

agricultural soils and urea fertilization in 2006 resulted in 

CO2 emissions of 8.0 Tg CO2 Eq. (8,012 Gg). The application 

of synthetic fertilizers to forest and settlement soils in 2006 

resulted in direct N2O emissions of 1.8 Tg CO2 Eq. (6 Gg). 

Direct N2O emissions from fertilizer application increased 

by approximately 174 percent between 1990 and 2006. 

Forest fires in 2006 resulted in methane (CH4) emissions of 

24.6 Tg CO2 Eq. (1,169 Gg), and in N2O emissions of 2.5 

Tg CO2 Eq. (8 Gg).

Table 7-1: Net CO2 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)

Sink Category 1990 1995 2000 2001 2002 2003 2004 2005 2006

Forest Land Remaining Forest Landa (621.7) (659.9) (550.7) (623.4) (697.3) (730.9) (741.4) (743.6) (745.1)

Cropland Remaining Cropland (30.1) (39.4) (38.4) (40.0) (40.3) (40.5) (40.9) (41.0) (41.8)

Land Converted to Cropland 14.7 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4 

Grassland Remaining Grassland (1.9) 16.6 16.4 16.4 16.4 16.4 16.3 16.3 16.2 

Land Converted to Grassland (14.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3)

Settlements Remaining Settlementsb (60.6) (71.5) (82.4) (84.6) (86.8) (88.9) (91.1) (93.3) (95.5)

Other (Landfilled Yard Trimmings 

and Food Scraps) (23.9) (14.1) (11.5) (11.6) (11.8) (10.0) (9.6) (10.0) (10.5)

Total (737.7) (775.3) (673.6) (750.2) (826.8) (860.9) (873.7) (878.6) (883.7)

Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.

a

 Estimates include C stock changes on both Forest Land Remaining Forest Land and Land Converted to Forest Land. b

 Estimates include C stock changes on both Settlements Remaining Settlements and Land Converted to Settlements. 

Table 7-2: Net CO2 Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg C)

Sink Category 1990 1995 2000 2001 2002 2003 2004 2005 2006

Forest Land Remaining Forest Landa (169.6) (180.0) (150.2) (170.0) (190.2) (199.3) (202.2) (202.8) (203.2)

Cropland Remaining Cropland (8.2) (10.7) (10.5) (10.9) (11.0) (11.0) (11.1) (11.2) (11.4)

Land Converted to Cropland 4.0 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2.6 

Grassland Remaining Grassland (0.5) 4.5 4.5 4.5 4.5 4.5 4.5 4.4 4.4 

Land Converted to Grassland (3.9) (4.5) (4.5) (4.5) (4.5) (4.5) (4.5) (4.5) (4.5)

Settlements Remaining Settlementsb (16.5) (19.5) (22.5) (23.1) (23.7) (24.3) (24.9) (25.4) (26.0)

Other (Landfilled Yard Trimmings 

and Food Scraps) (6.5) (3.9) (3.1) (3.2) (3.2) (2.7) (2.6) (2.7) (2.9)

Total (201.2) (211.4) (183.7) (204.6) (225.5) (234.8) (238.3) (239.6) (241.0)

Note: 1 Tg C = 1 teragram C = 1 million metric tons C. Parentheses indicate net sequestration. Totals may not sum due to independent rounding. 

a

 Estimates include C stock changes on both Forest Land Remaining Forest Land and Land Converted to Forest Land. b

 Estimates include C stock changes on both Settlements Remaining Settlements and Land Converted to Settlements. 
Land Use, Land-Use Change, and Forestry 7-3

7.1. Representation of the 

U.S. Land Base 

A national land-use categorization system that is 

consistent and complete both temporally and spatially is 

needed in order to assess land use and land-use change 

status and the associated greenhouse gas fluxes over the 

Inventory time series. This system should be consistent with 

IPCC (2006), such that all countries reporting on national 

greenhouse gas fluxes to the UNFCCC should (1) describe the 

methods and definitions used to determine areas of managed 

and unmanaged lands in the country, (2) describe and apply 

a consistent set of definitions for land-use categories over 

the entire national land base and time series associated with 

the greenhouse gas inventory, such that increases in the 

land areas within particular land use categories are balanced

Table 7-3: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO2 Eq.)

Source Category 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0 

Cropland Remaining Cropland: Liming 

of Agricultural Soils & Urea Fertilization 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 8.0 

CH4 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 

Forest Land Remaining Forest Land: 

Forest Fires 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 

N2O 1.5 1.8 3.5 2.7 3.5 2.7 2.6 3.1 4.3 

Forest Land Remaining Forest Land: 

Forest Fires 0.5 0.5 1.9 1.0 1.7 0.9 0.7 1.2 2.5 

Forest Land Remaining Forest Land:

Forest Soilsa 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Settlements Remaining Settlements: 

Settlement Soilsb 1.0 1.2 1.2 1.4 1.5 1.5 1.6 1.5 1.5 

Total 13.1 13.6 30.0 20.0 28.4 19.7 17.1 23.2 36.9 

Note: These estimates include direct emissions only. Indirect N2O emissions are reported in the Agriculture chapter. Totals may not sum due to independent 

rounding.

a

 Estimates include emissions from N fertilizer additions on both Forest Land Remaining Forest Land, and Land Converted to Forest Land, but not from 

land-use conversion.

b

 Estimates include emissions from N fertilizer additions on both Settlements Remaining Settlements, and Land Converted to Settlements, but not from 

land-use conversion.

Table 7-4: Non-CO2 Emissions from Land Use, Land-Use Change, and Forestry (Gg)

Source Category 1990 1995 2000 2001 2002 2003 2004 2005 2006

CO2 7,084 7,049 7,541 7,825 8,549 8,260 7,555 7,854 8,012 

Cropland Remaining Cropland: Liming 

of Agricultural Soils & Urea Fertilization 7,084 7,049 7,541 7,825 8,549 8,260 7,555 7,854 8,012 

CH4 213 224 904 448 780 416 330 586 1,169

Forest Land Remaining Forest Land: 

Forest Fires 213 224 904 448 780 416 330 586 1,169

N2O 5 6 11 9 11 9 8 10 14

Forest Land Remaining Forest Land: 

Forest Fires 1 2 6 3 5 3 2 4 8

Forest Land Remaining Forest Land:

Forest Soilsa 0 1 1 1 1 1 1 1 1

Settlements Remaining Settlements: 

Settlement Soilsb 3 4 4 5 5 5 5 5 5

Note: These estimates include direct emissions only. Indirect N2O emissions are reported in the Agriculture chapter. Totals may not sum due to independent 

rounding.

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.
7-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

by decreases in the land areas of other categories, and (3) 

account for greenhouse gas fluxes on all managed lands. 

The implementation of such a system helps to ensure that 

estimates of greenhouse gas fluxes are as accurate as possible. 

This section of the national greenhouse gas Inventory has 

been developed in order to comply with this guidance.

Multiple databases are utilized to track land management 

in the United States, which are also used as the basis to 

categorize the land area into the following six IPCC land-use 

categories:3 Forest Land, Cropland, Grassland, Wetlands, 

Settlements and Other Land (IPCC 2006). The primary 

databases are the U.S. Department of Agriculture (USDA) 

National Resources Inventory (NRI)4 and the USDA Forest 

Service (USFS) Forest Inventory and Analysis (FIA) 

Database.5 The U.S. Geological Survey (USGS) National 

Land Cover Dataset (NLCD)6 is also used to identify land 

uses in regions that were not included in the NRI or FIA. In 

1990, the United States had a total of 243 million hectares of 

Forest Land, 169 million hectares of Cropland, 301 million 

hectares of Grassland, 32 million hectares of Wetlands, 32 

million hectares of Settlements, and 28 million hectares in 

the Other Land7 category (Table 7-5). By 2006, the total area 

in Forest Land had increased by 3.9 percent to 252 million 

hectares, Cropland had declined by 4.0 percent to 162 million 

hectares, Grassland declined by 2.8 percent to 293 million 

hectares, Wetlands decreased by 4.8 percent to 31 million 

hectares, Settlements increased by 32.2 percent to 42 million 

3 Land-use category definitions are provided in the Methodology section.

4 NRI data are available at <http://www.ncgc.nrcs.usda.gov/ products/nri/

index.html>.

5 FIA data are available at <http://fia.fs.fed .us/tools-data/data/>.

6 NLCD data are available at <http://www.mrlc.gov/>.

7 Other Land is a miscellaneous category that includes lands that are not 

classified into the other five land-use categories. It also allows the total of 

identified land areas to match the national area.

hectares, and Other Land decreased by 11.1 percent to 25 

million hectares. 

Dominant land uses vary by region, largely due to 

climate patterns, soil types, geology, proximity to coastal 

regions, and historical settlement patterns, although all 

land-uses occur within each of the fifty states (Figure 

7-1). Forest Land tends to be more common in the eastern 

states, mountainous regions of the western United States, 

and Alaska. Cropland is concentrated in the mid-continent 

region of the United States, and Grassland is more common 

in the western United States. Wetlands are fairly ubiquitous 

throughout the United States, though they are more common 

in the upper Midwest and eastern portions of the country. 

Settlements are more concentrated along the coastal margins 

and in the eastern states. 

Methodology

IPCC Approaches for Representing Land Areas

IPCC (2006) describes three approaches for representing 

land areas. Approach 1 provides data on the total area for 

each individual land-use category, but does not provide 

detailed information on changes of area between categories 

and is not spatially explicit other than at the national or 

regional level. With Approach 1, total net conversions 

between categories can be detected, but not the individual 

changes between the land-use categories that led to those 

net changes. Approach 2 introduces tracking of individual 

land-use changes between the categories (e.g. forest land 

to cropland, cropland to forest land, grassland to cropland, 

etc.). Approach 3 extends Approach 2 by allowing each 

land-use conversion to be tracked on a spatially explicit 

basis. The three approaches are not presented as hierarchical 

tiers and are not mutually exclusive. 

Table 7-5: Land Use Areas During the Inventory Reporting Period (Millions of Hectares)

Land Use 1990 1995 2000 2001 2002 2003 2004 2005 2006

Forest Land 243 246 249 250 250 251 251 252 252

Cropland 169 166 163 163 162 162 162 162 162

Grassland 301 296 296 295 295 294 294 293 293

Wetlands 32 32 31 31 31 31 31 31 31

Settlements 32 36 40 41 41 42 42 42 42

Other Land 28 28 25 25 25 25 25 25 25

Note: Unmanaged land is not currently estimated because the only land designated as unmanaged occurs in Alaska, which has not been included in the 

current U.S. land representation assessment. See Planned Improvements for discussion on plans to include Alaska in future Inventory reports.
Land Use, Land-Use Change, and Forestry 7-5

Other Lands

Settlements

Percent of Total Land Area in Each Land-Use Category by State

Figure 7-1

Croplands Forest Lands

Wetlands

Grasslands

< 10% 11%–30% 31%–50% > 50% 
7-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

According to IPCC (2003), the approach or mix of 

approaches selected by an inventory agency should reflect 

the calculation needs and national circumstances. For this 

analysis, the NRI, FIA, and the NLCD have been combined 

to provide a complete representation of land use for managed 

lands. These data sources are described in more detail later 

in this section. The NRI and the FIA data surveys meet the 

standards for Approach 3, but the data from NLCD that are 

currently utilized only meet the standards for Approach 1.8

Consequently, Approach 1 is being used to provide a full 

representation of land use in the current Inventory. The United 

States is pursuing an effort to analyze available data with the 

intent of moving beyond Approach 1 in future Inventories.

Definitions of Land Use in the United States

Managed and Unmanaged Land 

The U.S. definitions of managed and unmanaged lands 

are similar to the basic IPCC (2006) definition of managed 

land, but with some additional elaboration to reflect national 

circumstances. Based on the following definitions, most lands 

in the United States are classified as managed: 

•	 Managed Land: Land is considered managed if direct 

human intervention has influenced its condition. 

Direct intervention includes altering or maintaining 

the condition of the land to produce commercial or 

non-commercial products or services; to serve as 

transportation corridors or locations for buildings, 

landfills, or other developed areas for commercial 

or non-commercial purposes; to extract resources or 

facilitate acquisition of resources; or to provide social 

functions for personal, community or societal objectives. 

Managed land also includes legal protection of lands 

(e.g., wilderness, preserves, parks, etc.) for conservation 

purposes (i.e., meets societal objectives).9

8A new NLCD product is being developed that will meet the standards of 

Approach 3 data, with explicit information on land cover change, opposed 

to information based solely on land cover for individual years.

9Wetlands are an exception to this general definition, because these lands, as 

specified by IPCC (2006), are only considered managed if they are created 

through human activity, such as dam construction, or the water level is 

artificially altered by human activity. Distinguishing between managed and 

unmanaged wetlands is difficult, however, due to limited data availability. 

Wetlands are not characterized by use within the NRI. Therefore, unless 

wetlands are managed for cropland or grassland, it is not possible to know 

if they are artificially created or if the water table is managed based on the 

use of NRI data.

•	 Unmanaged Land: All other land is considered 

unmanaged. Unmanaged land largely comprises 

areas inaccessible to human intervention due to the 

remoteness of the locations, or lands with essentially 

no development interest or protection due to limited 

personal, commercial or social value. Though these 

lands may be influenced indirectly by human actions 

such as atmospheric deposition of chemical species 

produced in industry, they are not influenced by a direct 

human intervention.10

Land-Use Categories

As with the definition of managed lands, IPCC (2003, 

2006) provide general non-prescriptive definitions for 

the six main land-use categories: Forest Land, Cropland, 

Grassland, Wetlands, Settlements, and Other Land. In order 

to reflect U.S. circumstances, country-specific definitions 

have been developed, based predominantly on criteria used 

in the land-use surveys for the United States. Specifically, 

the definition of Forest Land is based on the FIA definition 

of forest,11 while definitions of Cropland, Grassland, and 

Settlements are based on the NRI.12 The definitions for 

Other Land and Wetlands are based on the IPCC (2006) 

definitions for these categories.

•	 Forest Land: A land-use category that includes land 

that is at least 10 percent stocked13 by forest trees 

of any size, or land formerly having such tree cover, 

and not currently developed for a non-forest use. The 

minimum area for classification as Forest Land is one 

acre (0.40 ha). Roadside, stream-side, and shelterbelt 

strips of timber must be at least 120 feet (36.58 m) wide 

to qualify as Forest Land. Unimproved roads and trails, 

streams and other bodies of water, or natural clearings 

in forested areas are classified as Forest Land, if less 

than 120 feet (36.58 m) in width or one acre (0.40 ha) 

in size. Improved roads within Forest Land, however, 

are extracted from forest area estimates and included 

10 There will be some areas that qualify as Forest Land or Grassland 

according to the land use criteria, but are classified as unmanaged land due 

to the remoteness of their location.

11 See <http://socrates.lv-hrc.nevada.edu/fia/ab/issues/pending/glossary/

Glossary_5_30_06.pdf>.

12 See <http://www.nrcs.usda.gov/technical/land/nri01/glossary.html>.

13The percentage stocked refers to the degree of occupancy of land by trees, 

measured either by basal area or number of trees by size and spacing or 

both, compared to a stocking standard.
Land Use, Land-Use Change, and Forestry 7-7

in Other Land. Grazed woodlands, fields reverting to 

forest, and pastures that are not actively maintained are 

included if the above qualifications are satisfied. Forest 

Land consists of three main subcategories: timberland, 

reserved forest land, and other forest land.14 Forest Land 

also includes woodlands, which describes forest types 

consisting primarily of species that have their diameter 

measured at root collar, and for which there are no 

site index equations, nor stocking guides. These may 

include areas with degrees of stocking between 5 and 

9.9 percent. The FIA regions with woodland areas are, 

however, considering new definitions that should result 

in all Forest Land meeting the minimum 10 percent 

stocking threshold.

•	 Cropland: A land-use category that includes areas used 

for the production of adapted crops for harvest, this 

category includes both cultivated and non-cultivated 

lands. Cultivated crops include row crops or closegrown crops and also hay or pasture in rotation with 

cultivated crops. Non-cultivated cropland includes 

continuous hay, perennial crops (e.g., orchards) and 

horticultural cropland. Cropland also includes land 

with alley cropping and windbreaks,15 as well as lands 

in temporary fallow or enrolled in conservation reserve 

programs (i.e., set-asides16). Roads through Cropland, 

including interstate highways, state highways, other 

paved roads, gravel roads, dirt roads, and railroads are 

excluded from Cropland area estimates and are, instead, 

classified as Other Land.

•	 Grassland: A land-use category on which the plant cover 

is composed principally of grasses, grass-like plants, 

forbs, or shrubs suitable for grazing and browsing, 

and includes both pastures and native rangelands. This 

includes areas where practices such as clearing, burning, 

chaining, and/or chemicals are applied to maintain the 

grass vegetation. Savannas, some wetlands and deserts, 

14These subcategory definitions are fully described in the Forest Land 

Remaining Forest Land section.

15Currently, there is no data source to account for biomass C stock change 

associated with woody plant growth and losses in alley cropping systems 

and windbreaks in cropping systems, although these areas are included in 

the cropland land base.

16A set-aside is cropland that has been taken out of active cropping and 

converted to some type of vegetative cover, including, for example, native 

grasses or trees.

in addition to tundra are considered Grassland.17 Woody 

plant communities of low forbs and shrubs, such as 

mesquite, chaparral, mountain shrub, and pinyonjuniper, are also classified as Grassland if they do not 

meet the criteria for Forest Land. Grassland includes 

land managed with agroforestry practices such as 

silvipasture and windbreaks, assuming the stand or 

woodlot does not meet the criteria for Forest Land. 

Roads through Grassland, including interstate highways, 

state highways, other paved roads, gravel roads, dirt 

roads, and railroads are excluded from Grassland area 

estimates and are, instead, classified as Other Land.

•	 Wetlands: A land-use category that includes land 

covered or saturated by water for all or part of the year. 

Managed Wetlands are those where the water level is 

artificially changed, or were created by human activity. 

IPCC (2006) provides guidance under “Wetlands” 

for managed peatlands and flooded lands, such as 

reservoirs developed for hydroelectricity, irrigation, and 

navigation. Certain areas that fall under the managed 

Wetlands definition are covered in other areas of the 

IPCC guidance and/or the Inventory, including Cropland 

(e.g., rice cultivation), Grassland, and Forest Land 

(including drained or undrained forested wetlands).

•	 Settlements: A land-use category consisting of 

units of 0.25 acres (0.1 ha) or more that includes 

residential, industrial, commercial, and institutional 

land; construction sites; public administrative sites; 

railroad yards; cemeteries; airports; golf courses; 

sanitary landfills; sewage treatment plants; water control 

structures and spillways; parks within urban and built-up 

areas; and highways, railroads, and other transportation 

facilities if they are surrounded by urban or built-up 

areas. Also included are tracts of less than 10 acres 

(4.05 ha) that may meet the definitions for Forest Land, 

Cropland, Grassland, or Other Land but are completely 

surrounded by urban or built-up land, and so are included 

in the settlement category.

•	 Other Land: A land-use category that includes bare 

soil, rock, ice, non-settlement transportation corridors, 

and all land areas that do not fall into any of the other 

five land-use categories. It allows the total of identified 

17 IPCC guidelines (2006) do not include provisions to separate desert and 

tundra as land categories.
7-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

land areas to match the managed national area. It also 

specifically includes roads through forests (excluding 

unimproved roads/trails) and all types of roads through 

Grassland and Cropland areas that are discernible using 

aerial photography or remote sensing imagery (i.e., 

interstate highways, state highways, other paved roads, 

gravel roads, dirt roads, and railroads).

Land Use Data Sources: Description 

and Application to U.S. Land Area 

Classification

U.S. Land Use Data Sources

The three main data sources for land area and use data in 

the United States are the NRI, FIA, and the NLCD. The NRI 

is conducted by the USDA Natural Resources Conservation 

Service and is designed to assess soil, water, and related 

environmental resources on nonfederal lands. The NRI has 

a stratified multi-stage sampling design, where primary 

sample units are stratified on the basis of county and township 

boundaries defined by the U.S. Public Land Survey (Nusser 

and Goebel 1997). Within a primary sample unit (typically 

a 160-acre (64.75 ha) square quarter-section), three sample 

points are selected according to a restricted randomization 

procedure. Each point in the survey is assigned an area weight 

(expansion factor) based on other known areas and land-use 

information (Nusser and Goebel 1997). The NRI survey 

utilizes data derived from remote sensing imagery and site 

visits in order to provide detailed information on land use and 

management, particularly for croplands, and is used as the 

basis to account for C stock changes in agricultural lands. The 

NRI survey was conducted every 5 years between 1982 and 

1997, but shifted to annualized data collection in 1998.

The FIA program, conducted by the USFS, is used to 

obtain forest area and management data FIA engages in a 

hierarchical system of sampling, with sampling categorized 

as Phases 1 through 3, in which sample points for phases are 

subsets of the previous phase. Phase 1 refers to collection of 

remotely-sensed data (either aerial photographs or satellite 

imagery) primarily to classify land into forest or non-forest 

and to identify landscape patterns like fragmentation and 

urbanization. Phase 2 is the collection of field data on 

a network of ground plots that enable classification and 

summarization of area, tree, and other attributes associated 

with forest land uses. Phase 3 plots are a subset of Phase 2 

plots where data on indicators of forest health are measured. 

Data from all three phases are also used to estimate C stock 

changes for forest land. Historically, FIA inventory surveys 

had been conducted periodically, with all plots in a state 

being measured at a frequency of every 5 to 14 years. A 

new national plot design and annual sampling design was 

introduced by FIA about ten years ago. Most states, though, 

have only recently been brought into this system. Annualized 

sampling means that a portion of plots throughout each state 

is sampled each year, with the goal of measuring all plots 

once every 5 years. See Annex 3.12 to see the specific survey 

data available by state.

Because NRI only includes land use information 

for non-federal land, and the FIA only records for forest 

land,18 major gaps exist when the datasets are combined, 

such as federal grassland operated by the Bureau of Land 

Management (BLM), USDA, and National Park Service, as 

well as most of Alaska.19 Consequently, the NLCD is used 

as a supplementary database to account for federal land areas 

that are not included in the NRI and FIA databases. The 

NLCD is a land cover classification scheme, available for 

1992 and 2001, that has been applied over the conterminous 

United States. It is based primarily on Landsat Thematic 

Mapper imagery. The NLCD contains 21 categories of land 

cover information, which have been aggregated into the six 

IPCC land-use categories, and the data are available at a 

spatial resolution of 30 meters. The NLCD is strictly a source 

of land cover information, however, and does not provide 

the necessary site conditions, crop types and management 

information from which to estimate C stock changes on 

those lands. 

Along with the incorporation of NLCD data, another 

major step has been taken to address gaps, as well as overlaps 

in the representation of the U.S. land base between the 

Agricultural Carbon Stock Inventory (Cropland Remaining 

Cropland, Land Converted to Cropland, Grassland 

Remaining Grassland, Land Converted to Grassland) and 

18 FIA does collect some data on nonforest land use, but these are held in 

regional databases versus the national database. The status of these data is 

being investigated.

19The survey programs also do not include U.S. Territories with the exception 

of non-federal lands in Puerto Rico, which are included in the NRI survey. 

Furthermore, NLCD does not include coverage for U.S. Territories.
Land Use, Land-Use Change, and Forestry 7-9

Forest Land Carbon Stock Inventory (Forest Land Remaining 

Forest Land and Land Converted to Forest Land), which 

are based on the NRI and FIA databases, respectively. NRI, 

which covers only non-federal land, and FIA have different 

criteria for classifying forest land, leading to discrepancies 

in the resulting estimates of forest land area on non-federal 

land. Similarly, there are discrepancies between the NLCD 

and FIA data for forest land on federal lands. Moreover, 

dependence exists between the Forest Land area and the 

amount of land designated as other land uses in the NRI 

and NLCD, such as grassland, cropland and wetland, and 

thus there are inconsistencies in the Forest Land definitions 

among the three databases. FIA is the main database for 

forest statistics, and consequently, the NRI and NLCD were 

adjusted to achieve consistency with FIA estimates of Forest 

Land. The adjustments were made at a state-scale, and it was 

assumed that the majority of the discrepancy in forest area 

was associated with an under- or over-prediction of grassland 

and wetland area in the NRI and NLCD due to differences in 

Forest Land definitions. Specifically, the Forest Land area for 

a given state according to the NRI and NLCD was adjusted 

to match the FIA estimates for non-federal and federal land, 

respectively. Adjustments were allotted to grassland and 

wetlands, based on the proportion of land within each of these 

land-use categories at the state-level. A higher proportion of 

grassland led to a larger adjustment in grassland area and vice 

versa. In a second step, corresponding increases or decreases 

were made in the area estimates of grassland and wetland 

from the NRI and NLCD, in order to balance the change in 

forest area, and therefore not change the overall amount of 

managed land within an individual state. 

There are minor differences between the U.S. Census 

Survey20 land area estimates and the land use surveys derived 

for the Inventory because of discrepancies in the reporting 

approach for the census and the methods used in the NRI, FIA 

and NLCD. The area estimates of land-use categories, based 

on NRI, FIA and NLCD, are derived from remote sensing 

data instead of the land survey approach used by the U.S. 

Census Survey. More importantly, the U.S. Census Survey 

does not provide a time series of land-use change data or land 

management information, which is critical for conducting 

emission inventories and is provided from the NRI and FIA 

surveys. Regardless, the total difference between the U.S. 

20 See <http://www.census.gov/geo/www/tiger>.

Census Survey and the data sources used in the Inventory is 

relatively minor, estimated at about 6 million hectares for the 

total land base of over 800 million hectares currently included 

in the Inventory, or a 0.7 percent difference. 

Approach for Combining Data Sources

The managed land base in the United States has been 

classified into the six IPCC land-use categories using 

definitions21 developed to meet national circumstances, while 

adhering to IPCC (2006). In practice, the land was initially 

classified into a variety of land-use categories using the NRI, 

FIA and NLCD, and then aggregated into the six broad land 

uses identified in IPCC (2006). Details on the approach used 

to combine data sources for each land use are described below 

along with gaps that will be reconciled as part of ongoing 

planned improvements: 

•	 Forest Land: Both non-federal and federal forest lands 

in both the continental United States and coastal Alaska 

are covered by FIA. FIA is used as the basis for both 

Forest Land area data as well as to estimate C stocks and 

fluxes on Forest Land. Interior Alaska is not currently 

surveyed by FIA and at this time the NLCD cannot be 

used to classify land use in this region. FIA surveys are 

currently being conducted on U.S. territories and will 

become available in the future. FIA data will also be 

collected in Hawaii in the future. 

•	 Cropland: Cropland is classified using the NRI, which 

covers all non-federal lands, within 49 states, including 

state and local government-owned land as well as 

tribal lands. NRI is used as the basis for both Cropland 

area data as well as to estimate C stocks and fluxes on 

Cropland. Cropland in Alaska and U.S. territories is 

excluded from both NRI data collection and the NLCD.22

Though crops are grown on some federal lands, these 

Cropland areas are considered minimal and are excluded 

from the inventory. 

•	 Grassland: Grassland on non-federal lands is classified 

using the NRI within 49 states, including state and 

local government-owned land as well as tribal lands. 

NRI is used as the basis for both Grassland area data as 

well as to estimate C stocks and fluxes on Grassland. 

21 Definitions are provided in the previous section.

22With the exception of non-federal cropland in Puerto Rico, which are 

included in the NRI survey.
7-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Alaska and U.S. territories are excluded from both NRI 

data collection and the current release of the NLCD 

product.23 Grassland on federal BLM lands, National 

Parks and within USFS lands is covered by the NLCD. 

Department of Defense grasslands are also included in 

area estimates using the NLCD.

•	 Wetlands: NRI captures wetlands on non-federal lands 

within 49 states, while federal wetlands are covered by 

the NLCD. Alaska and U.S. territories are excluded. 

This currently includes both managed and unmanaged 

wetlands as no database has yet been applied to make this 

distinction. See Planned Improvements for details.

•	 Settlements: The NRI captures non-federal settlement 

area in 49 states. If areas of Forest Land or Grassland 

under 10 acres (4.05 ha) are contained within settlements 

or urban areas, they are classified as Settlements (urban) 

in the NRI database. If these parcels exceed the 10 

acre (4.05 ha) threshold and are grassland, they will 

be classified as such by NRI. If within an urban area, a 

forested area is classified as nonforest by FIA, regardless 

of size. Settlements on federal lands are covered by 

NLCD. Settlements in Alaska and U.S. territories are 

currently excluded from NRI and NLCD.

•	 Other Land: Any land not falling into the other five land 

categories and, therefore, categorized as Other Land is 

classified using the NRI and NLCD. Other land in Alaska 

and U.S. territories are excluded from the NLCD.

Some lands can be classified into one or more categories 

due to multiple uses that meet the criteria of more than 

one definition. However, a ranking has been developed for 

assigning priority in these cases. The ranking process is 

initiated by distinguishing between managed and unmanaged 

lands. The managed lands are then assigned, from highest to 

lowest priority, in the following manner: 

 

Settlements are given the highest assignment priority 

because they are extremely heterogeneous with a mosaic 

of patches that include buildings, infrastructure and travel 

corridors, but also open grass areas, forest patches, riparian 

areas, and gardens. The latter examples could be classified as 

23With the exception of non-federal grasslands in Puerto Rico, which are 

included in the NRI survey.

Grassland, Forest Land, Wetlands, and Cropland, respectively, 

but when located in close proximity to settlement areas they 

tend to be managed in a unique manner compared to nonsettlement areas. Consequently, these areas are assigned to 

the Settlements land-use category. Cropland is given the 

second assignment priority, because cropping practices tend 

to dominate management activities on areas used to produce 

food, forage, or fiber. The consequence of this ranking is that 

crops in rotation with grass will be classified as Cropland, 

and land with woody plant cover that is used to produce 

crops (e.g., orchards) is classified as Cropland, even though 

these areas may meet the definitions of Grassland or Forest 

Land, respectively. Similarly, Wetlands that are used for rice 

production are considered Croplands. Forest Land occurs 

next in the priority assignment because traditional forestry 

practices tend to be the focus of the management activity in 

areas with woody plant cover that are not croplands (e.g., 

orchards) or settlements (e.g., housing subdivisions with 

significant tree cover). Grassland occurs next in the ranking, 

while Wetlands and Other Land complete the list.

Priority does not reflect the level of importance for 

reporting GHG emissions and removals on managed 

land, but is intended to classify all areas into a single land 

use. Currently, the IPCC does not make provisions in the 

guidelines for assigning land to multiple uses. For example, a 

Wetland is classified as Forest Land if the area has sufficient 

tree cover to meet the stocking and stand size requirements. 

Similarly, Wetlands are classified as Cropland if they are used 

to produce a crop, such as rice. In either case, emissions from 

Wetlands are included in the Inventory if human interventions 

are influencing emissions from Wetlands in accordance with 

the guidance provided in IPCC (2006).

Planned Improvements

Area data by land-use category are not estimated for 

major portions of Alaska and any of the U.S. territories. A 

key planned improvement is to incorporate land-use data 

from these areas in the national greenhouse gas emissions 

Inventory. For Alaska, a new NLCD 2001 data product 

will be used to cover those land areas presently omitted. 

Fortunately, most of the managed land in the United States 

is included in the current land use statistics, but a complete 

accounting is a key goal for the near future. Data sources will 

be evaluated for representing land use in U.S. Territories.

Settlements > Cropland > Forest Land > Grassland > 

Wetlands > Other Land
Land Use, Land-Use Change, and Forestry 7-11

Another planned improvement is to utilize Approach 

3-type area data for the U.S. land base. A new NLCD product, 

with spatially-explicit information on land-use change is 

currently being developed and will qualify as Approach 3. By 

using this new data product in combination with the existing 

NRI and FIA databases, land-use statistics will be further 

subdivided by land-use change categories as recommended 

in IPCC (2006). This will include land remaining in a landuse category and land converted to another land-use category 

(e.g., Forest Land Remaining Forest Land, Cropland 

Converted to Forest Land, Grassland Converted to Forest 

Land). The additional subdivisions will provide more explicit 

land-use change statistics than currently reported, and also 

provide better accounting of emissions and stock changes 

associated with land use activities.

Additional work will be done to reconcile differences in 

Forest Land estimates between the NRI and FIA, evaluating 

the assumption that the majority of discrepancies in Forest 

Land areas are associated with an over- or under-estimation 

of Grassland and Wetland area. In some regions of the United 

States, a discrepancy in Forest Land areas between NRI and 

FIA may be associated with an over- or under-prediction of 

other land uses. 

There are also other databases that may need to be 

reconciled with the NRI and NLCD datasets, particularly 

for Settlements and Wetlands. Urban area estimates, used 

to produce C stock and flux estimates from urban trees, are 

currently based on population data (1990 and 2000 U.S. 

Census data). Using the population statistics, “urban clusters” 

are defined as areas with more than 500 people per square 

mile. The USFS is currently moving ahead with an urban 

forest inventory program so that urban forest area estimates 

will be consistent with FIA forest area estimates outside of 

urban areas, which would be expected to reduce omissions 

and overlap of forest area estimates along urban boundary 

areas. For Wetlands, current estimates using the NRI and 

NLCD databases will be compared and reconciled to the 

extent possible with the Army Corps of Engineers National 

Inventory of Dams (ACE 2005) which provides data on the 

total surface area of reservoirs created by dams.

7.2. Forest Land Remaining 

Forest Land

Changes in Forest Carbon Stocks 

(IPCC Source Category 5A1)

For estimating C stocks or stock change (flux), C in 

forest ecosystems can be divided into the following five 

storage pools (IPCC 2003): 

•	 Aboveground biomass, which includes all living 

biomass above the soil including stem, stump, branches, 

bark, seeds, and foliage. This category includes live 

understory.

•	 Belowground biomass, which includes all living biomass 

of coarse living roots greater than 2 mm diameter.

•	 Dead wood, which includes all non-living woody 

biomass either standing, lying on the ground (but not 

including litter), or in the soil.

•	 Litter, which includes the litter, fumic, and humic layers, 

and all non-living biomass with a diameter less than 7.5 

cm at transect intersection, lying on the ground.

•	 Soil organic C (SOC), including all organic material in 

soil to a depth of 1 meter but excluding the coarse roots 

of the aboveground pools.

In addition, there are two harvested wood pools 

necessary for estimating C flux:

•	 Harvested wood products in use.

•	 Harvested wood products in solid waste disposal sites 

(SWDS).

C is continuously cycled among these storage pools and 

between forest ecosystems and the atmosphere as a result 

of biological processes in forests (e.g., photosynthesis, 

respiration, growth, mortality, decomposition, and 

disturbances such as fires or pest outbreaks) and 

anthropogenic activities (e.g., harvesting, thinning, 

clearing, and replanting). As trees photosynthesize and 

grow, C is removed from the atmosphere and stored in 
7-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

living tree biomass. As trees die and otherwise deposit 

litter and debris on the forest floor, C is released to the 

atmosphere or transferred to the soil by organisms that 

facilitate decomposition.

The net change in forest C is not equivalent to the 

net flux between forests and the atmosphere because 

timber harvests do not cause an immediate flux of C to the 

atmosphere. Instead, harvesting transfers C to a “product 

pool.” Once in a product pool, the C is emitted over time as 

CO2 when the wood product combusts or decays. The rate 

of emission varies considerably among different product 

pools. For example, if timber is harvested to produce energy, 

combustion releases C immediately. Conversely, if timber 

is harvested and used as lumber in a house, it may be 

many decades or even centuries before the lumber decays 

and C is released to the atmosphere. If wood products are 

disposed of in SWDS, the C contained in the wood may 

be released many years or decades later, or may be stored 

almost permanently in the SWDS. 

This section quantifies the net changes in C stocks in 

the five forest C pools and two harvested wood pools. The 

net change in stocks for each pool is estimated, and then the 

changes in stocks are summed over all pools to estimate total 

net flux. The focus on C implies that all C-based greenhouse 

gases are included, and the focus on stock change suggests 

that specific ecosystem fluxes do not need to be separately 

itemized in this report. Disturbances from forest fires and 

pest outbreaks are implicitly included in the net changes. 

For instance, an inventory conducted after fire counts only 

trees left. The change between inventories thus accounts for 

the C changes due to fires; however, it may not be possible 

to attribute the changes to the disturbance specifically. The 

IPCC (2003) recommends reporting C stocks according to 

several land-use types and conversions, specifically Forest 

Land Remaining Forest Land and Land Converted to Forest 

Land. Currently, consistent datasets are not available for the 

entire United States to allow results to be partitioned in this 

way. Instead, net changes in all forest-related land, including 

non-forest land converted to forest and forests converted to 

non-forest are reported here.

Forest C storage pools, and the flows between them 

via emissions, sequestration, and transfers, are shown in 

Figure 7-2. In the figure, boxes represent forest C storage 

pools and arrows represent flows between storage pools or 

between storage pools and the atmosphere. Note that the 

Combustion from 

 forest fires (carbon 

 dioxide, methane) Combustion from forest fires

(carbon dioxide, methane)

Figure 7-2

Forest Sector Carbon Pools and Flows
Land Use, Land-Use Change, and Forestry 7-13

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 (Smith et al. 2004b). The 

current forest inventory includes 249 million hectares in the 

conterminous 48 states (USDA Forest Service 2006b) that 

are considered managed and are included in this inventory. 

The additional forest lands are located in Alaska and 

Hawaii. This inventory includes approximately 3.7 million 

hectares of Alaska forest, which are in the southeast and 

south central regions of Alaska and represent the majority 

of the state’s managed forest land. Survey data are not yet 

available from Hawaii. While Hawaii and U.S. territories 

have relatively small areas of forest land and will probably 

not affect the overall C budget to a great degree, these 

areas will be included as sufficient data become available. 

Agroforestry systems are also not currently accounted for 

in the Inventory, since they are not explicitly inventoried by 

either of the two primary national natural resource inventory 

programs: the Forest Inventory and Analysis (FIA) program 

of the U.S. Department of Agriculture (USDA) Forest 

Service and the National Resources Inventory (NRI) of 

the USDA Natural Resources Conservation Service (Perry 

et al. 2005).

Sixty-seven percent of U.S. forests (204 million 

hectares) are classified as timberland, meaning they meet 

minimum levels of productivity and are available for timber 

harvest. Nine percent of Alaska forests and 79 percent of 

forests in the conterminous United States are classified as 

timberlands. Of the remaining nontimberland forests, 31 

million hectares are reserved forest lands (withdrawn by 

law from management for production of wood products) 

and 68 million hectares are lower productivity forest 

lands (Smith et al. 2004b). Historically, the timberlands in 

the conterminous 48 states have been more frequently or 

intensively surveyed than other forest lands. 

Forest land declined by approximately 10 million 

hectares over the period from the early 1960s to the late 

1980s. Since then, forest area has increased by about 7 

million hectares. Current trends in forest area represent 

average annual change of only about 0.2 percent. Given 

the low rate of change in U.S. forest land area, the major 

influences on the current net C flux from forest land are 

management activities and the ongoing impacts of previous 

land-use changes. These activities affect the net flux of C 

by altering the amount of C stored in forest ecosystems. For 

example, intensified management of forests that leads to 

an increased rate of growth increases the eventual biomass 

density of the forest, thereby increasing the uptake of C.24

Net volume of growing stock on U.S. timberlands increased 

by 36 percent from 1953 to 1997. Though harvesting forests 

removes much of the aboveground C, there is a positive 

growth to harvest ratio on U.S. timberlands (AF&PA 2001). 

The reversion of cropland to forest land increases C storage 

in biomass, forest floor, and soils. The net effects of forest 

management and the effects of land-use change involving 

forest land are captured in the estimates of C stocks and 

fluxes presented in this chapter.

In the United States, improved forest management 

practices, the regeneration of previously cleared forest 

areas, as well as timber harvesting and use have resulted in 

net uptake (i.e., net sequestration) of C each year from 1990 

through 2006. The rate of forest clearing begun in the 17th 

century following European settlement had slowed by the 

late 19th century. Through the later part of the 20th century 

many areas of previously forested land in the United States 

were allowed to revert to forests or were actively reforested. 

The impacts of these land-use changes still affect C fluxes 

from these forest lands. More recently, the 1970s and 1980s 

saw a resurgence of federally-sponsored forest management 

programs (e.g., the Forestry Incentive Program) and soil 

conservation programs (e.g., the Conservation Reserve 

Program), which have focused on tree planting, improving 

24The term “biomass density” refers to the mass of live vegetation per 

unit area. It is usually measured on a dry-weight basis. Dry biomass is 50 

percent C by weight.
7-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

timber management activities, combating soil erosion, 

and converting marginal cropland to forests. In addition 

to forest regeneration and management, forest harvests 

have also affected net C fluxes. Because most of the timber 

harvested from U.S. forests is used in wood products, and 

many discarded wood products are disposed of in SWDS 

rather than by incineration, significant quantities of C in 

harvested wood are transferred to long-term storage pools 

rather than being released rapidly to the atmosphere (Skog 

and Nicholson 1998, Skog in preparation). The size of 

these long-term C storage pools has increased during the 

last century.

Changes in C stocks in U.S. forests and harvested 

wood were estimated to account for net sequestration of 

745.1 Tg CO2 Eq. (203.2 Tg C) in 2006 (Table 7-6, Table 

7-7, and Figure 7-3). In addition to the net accumulation 

of C in harvested wood pools, sequestration is a reflection 

of net forest growth and increasing forest area over this 

period. Overall, average C in forest ecosystem biomass 

(aboveground and belowground) increased from 71 to 

75 Mg C/ha between 1990 and 2007 (see Table A-4 for 

average C densities by specific regions and forest types). 

Continuous, regular annual surveys are not available over 

the period for each state; therefore, estimates for non-survey 

years were derived by interpolation between known data 

points. Survey years vary from state to state, and national 

estimates are a composite of individual state surveys. 

Therefore, changes in sequestration over the interval 1990 

Table 7-6: Net Annual Changes in C Stocks (Tg CO2/yr) in Forest and Harvested Wood Pools

Carbon Pool 1990 1995 2000 2001 2002 2003 2004 2005 2006

Forest (489.1) (540.5) (436.8) (529.0) (598.0) (635.1) (635.1) (635.1) (635.1)

Aboveground Biomass (287.6) (318.4) (335.4) (367.7) (384.4) (406.5) (406.5) (406.5) (406.5)

Belowground Biomass (54.2) (62.4) (67.2) (73.7) (76.9) (80.9) (80.9) (80.9) (80.9)

Dead Wood (40.1) (57.5) (44.9) (50.0) (53.0) (56.9) (56.9) (56.9) (56.9)

Litter (63.3) (34.9) (17.3) (36.3) (47.7) (56.2) (56.2) (56.2) (56.2)

Soil Organic Carbon (43.9) (67.5) 28.0 (1.3) (36.0) (34.5) (34.5) (34.5) (34.5)

Harvested Wood (132.6) (119.4) (113.9) (94.5) (99.2) (95.9) (106.3) (108.5) (110.0)

Products in Use (64.8) (55.2) (47.0) (31.9) (35.1) (35.4) (45.5) (47.3) (45.3)

SWDS (67.9) (64.1) (66.9) (62.6) (64.2) (60.4) (60.8) (61.2) (64.7)

Total Net Flux (621.7) (659.9) (550.7) (623.4) (697.3) (730.9) (741.4) (743.6) (745.1)

Note: Forest C stocks do not include forest stocks in U.S. territories, Hawaii, a large portion of Alaska, or trees on non-forest land (e.g., urban trees, 

agroforestry systems). Parentheses indicate net C sequestration (i.e., a net removal of C from the atmosphere). Total net flux is an estimate of the actual 

net flux between the total forest C pool and the atmosphere. Forest area estimates are based on interpolation and extrapolation of inventory data as 

described in the text and in Annex 3.12. Harvested wood estimates are based on results from annual surveys and models. Totals may not sum due to 

independent rounding.

Table 7-7: Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools

Carbon Pool 1990 1995 2000 2001 2002 2003 2004 2005 2006

Forest (133.4) (147.4) (119.1) (144.3) (163.1) (173.2) (173.2) (173.2) (173.2)

Aboveground Biomass (78.4) (86.8) (91.5) (100.3) (104.8) (110.9) (110.9) (110.9) (110.9)

Belowground Biomass (14.8) (17.0) (18.3) (20.1) (21.0) (22.1) (22.1) (22.1) (22.1)

Dead Wood (10.9) (15.7) (12.2) (13.6) (14.5) (15.5) (15.5) (15.5) (15.5)

Litter (17.3) (9.5) (4.7) (9.9) (13.0) (15.3) (15.3) (15.3) (15.3)

Soil Organic Carbon (12.0) (18.4) 7.6 (0.4) (9.8) (9.4) (9.4) (9.4) (9.4)

Harvested Wood (36.2) (32.6) (31.1) (25.8) (27.1) (26.1) (29.0) (29.6) (30.0)

Products in Use (17.7) (15.1) (12.8) (8.7) (9.6) (9.7) (12.4) (12.9) (12.3)

SWDS (18.5) (17.5) (18.2) (17.1) (17.5) (16.5) (16.6) (16.7) (17.7)

Total Net Flux (169.6) (180.0) (150.2) (170.0) (190.2) (199.3) (202.2) (202.8) (203.2)

Note: Forest C stocks do not include forest stocks in U.S. territories, Hawaii, a large portion of Alaska, or trees on non-forest land (e.g., urban trees, 

agroforestry systems). Parentheses indicate net C sequestration (i.e., a net removal of C from the atmosphere). Total net flux is an estimate of the actual 

net flux between the total forest C pool and the atmosphere. Harvested wood estimates are based on results from annual surveys and models. Totals 

may not sum due to independent rounding.
Land Use, Land-Use Change, and Forestry 7-15

to 2006 are the result of the sequences of new inventories for 

each state. Net annual sequestration increased by 20 percent 

for 2006 relative to 1990. C in forest ecosystem biomass 

had the greatest effect on total change. As discussed above, 

this was due to increased C density and total forest land. 

Management practices that increase C stocks on forest land, 

as well as afforestation and reforestation efforts influence 

the trends of increased C densities in forests and increased 

forest land in the United States.

Stock estimates for forest and harvested wood C storage 

pools are presented in Table 7-8. Together, the aboveground 

live and forest soil pools account for a large proportion of 

total forest C stocks. C stocks in all non-soil pools increased 

over time. Therefore, C sequestration was greater than C 

emissions from forests, as discussed above. Figure 7-4 shows 

county-average C densities for live trees on forest land, 

including both above- and below-ground biomass. 

Table 7-8: Forest Area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools

1990 1995 2000 2001 2002 2003 2004 2005 2006 2007

Forest Area (1000 ha) 245,799 249,036 252,251 252,798 253,443 254,155 254,889 255,624 256,358 257,093 

Carbon Pools (Tg C)

Forest 40,106 40,810 41,535 41,654 41,798 41,962 42,135 42,308 42,481 42,654

Aboveground Biomass 14,547 14,955 15,405 15,496 15,596 15,701 15,812 15,923 16,034 16,145

Belowground Biomass 2,896 2,974 3,063 3,081 3,102 3,123 3,145 3,167 3,189 3,211

Dead Wood 2,453 2,515 2,592 2,605 2,618 2,633 2,648 2,664 2,679 2,695

Litter 4,557 4,641 4,680 4,684 4,694 4,707 4,723 4,738 4,753 4,769

Soil Organic Carbon 15,652 15,725 15,795 15,788 15,788 15,798 15,807 15,817 15,826 15,835

Harvested Wood 1,862 2,033 2,193 2,224 2,250 2,277 2,303 2,332 2,362 2,392

Products in Use 1,231 1,311 1,382 1,395 1,404 1,413 1,423 1,436 1,448 1,461

SWDS 631 722 810 829 846 863 880 896 913 931

Total Carbon Stock 41,968 42,843 43,728 43,878 44,048 44,238 44,438 44,640 44,843 43,376 

Note: Forest Area estimates include portions of Alaska, which represents an addition relative to previous versions of this table. Forest C stocks do not 

include forest stocks in U.S. territories, Hawaii, a large portion of Alaska, or trees on non-forest land (e.g., urban trees, agroforestry systems). Wood 

product stocks include exports, even if the logs are processed in other countries, and exclude imports. Forest area estimates are based on interpolation 

and extrapolation of inventory data as described in Smith et al. (2007) and in Annex 3.12. Harvested wood estimates are based on results from annual 

surveys and models. Totals may not sum due to independent rounding. Inventories are assumed to represent stocks as of January 1 of the inventory year. 

Flux is the net annual change in stock. Thus, an estimate of flux for 2006 requires estimates of C stocks for 2006 and 2007.

-250

-200

-150

-100

-50

0

50

Forest Sector Net Carbon Flux (Tg/yr)

Soil

Total Net Change

Forest, Nonsoil

Harvested Wood

19901991199219931994199519961997199819992000200120022003200420052006

Estimates of Net Annual Changes in Carbon Stocks 

for Major Carbon Pools

Figure 7-3
7-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Note: This graphic shows county-average carbon densities for live trees on forestland, including both above- and belowground biomass. These data 

are based on the most recent forest inventory survey in each state. (See Table A-3 for the most recent inventory year for each state or substate.)

Average C Density in the Forest Tree Pool in the Conterminous United States, 2007

Figure 7-4

Live Tree

Mg CO2 Eq./ha

1–200

201–400

over 400

As stated previously, the forest inventory approach implicitly 

accounts for emissions due to disturbances such as forest fires, 

because only C remaining in the forest is estimated. Net C stock 

change is estimated by subtracting consecutive C stock estimates. 

A disturbance removes C from the forest. The inventory data on 

which net C stock estimates are based already reflect this C loss. 

Therefore, estimates of net annual changes in C stocks for U.S. forest 

land already account for CO2 emissions from forest fires occurring in 

the lower 48 states as well as in the proportion of Alaska’s managed 

forest land captured in this Inventory. Because it is of interest to 

quantify the magnitude of CO2 emissions from fire disturbance, these 

estimates are being highlighted here, using the full extent of available 

data. Non-CO2 greenhouse gas emissions from forest fires are also 

quantified in a separate section below. 

The IPCC (2003) methodology was employed to estimate CO2

emissions from forest fires. CO2 emissions for the lower 48 states and 

Alaska in 2006 were estimated to be 267.9 Tg CO2/yr. This amount is 

masked in the estimate of net annual forest carbon stock change for 

2006, however, because this net estimate accounts for the amount 

sequestered minus any emissions.

Box 7-1: CO2 Emissions from Forest Fires

Table 7-9: Estimates of CO2 (Tg/yr) emissions for 

the lower 48 states and Alaskaa

Year

CO2 Emitted in 

the Lower 48 

States (Tg/yr)

CO2 Emitted 

in Alaska

(Tg/yr)

Total CO2

Emitted

(Tg/yr)

1990 36.8 12.0 48.8

1995 51.1 0.2 51.3

2000 196.9 10.3 207.2

2001 99.7 3.0 102.6

2002 149.0 29.7 178.7

2003 92.4 3.0 95.4

2004 43.4 32.1 75.5

2005 111.4 22.9 134.3

2006 266.6 1.3 267.9

a

 Note that these emissions have already been accounted for in the 

estimates of net annual changes in carbon stocks, which accounts 

for the amount sequestered minus any emissions.
Land Use, Land-Use Change, and Forestry 7-17

Methodology

The methodology described herein is consistent 

with IPCC (2003) and IPCC/UNEP/OECD/IEA (1997). 

Estimates of net annual C stock change, or flux, of forest 

ecosystems are derived from applying C estimation factors 

to forest inventory data and interpolating between successive 

inventory-based estimates of C stocks. C emissions from 

harvested wood are based on factors such as the allocation 

of wood to various primary and end-use products as well as 

half-life (the time at which half of amount placed in use will 

have been discarded from use) and expected disposition (e.g., 

product pool, SWDS, combustion). Different data sources 

are used to estimate the C stocks and stock change in forest 

ecosystems or harvested wood products. See Annex 3.12 

for details and additional information related to the methods 

described below.

Forest Carbon Stocks and Fluxes

The first step in developing forest ecosystem estimates 

is to identify useful inventory data and resolve any 

inconsistencies among datasets. Forest inventory data 

were obtained from the USDA Forest Service FIA program 

(Frayer and Furnival 1999, USDA Forest Service 2006a). 

Inventories include forest lands25 of the conterminous United 

States and are organized as a number of separate datasets, 

each representing a complete inventory, or survey, of an 

individual state at a specified time. Forest C calculations 

are organized according to these state surveys, and the 

frequency of surveys varies by state. To calculate a C stock 

change, at least two surveys are needed in each state. Thus, 

the most recent surveys for each state are used as well as 

all additional consistent inventory data back through 1990. 

Because C flux is based on change between successive C 

stocks, consistent representation of forest land in successive 

inventories is necessary. In order to achieve accurate 

representation of forests from 1990 to the present, statelevel data are sometimes subdivided or additional inventory 

sources are used to produce the consistent state or sub-state 

inventories.

The principal FIA datasets employed are freely available 

for download at USDA Forest Service (2006b) as the Forest 

25 Forest land in the United States includes land that is at least 10 percent 

stocked with trees of any size. Timberland is the most productive type of 

forest land, which is on unreserved land and is producing or capable of 

producing crops of industrial wood. 

Inventory and Analysis Database (FIADB) Version 2.1. 

These data are identified as “snapshot” files, also identified 

as FISDB 2.1, and include detailed plot information, 

including individual-tree data. However, to achieve 

consistent representation (spatial and temporal), two other 

general sources of past FIA data are included as necessary. 

First, older FIA plot- and tree-level data—not in the FIADB 

format—are used if available. Second, Resources Planning 

Act Assessment (RPA) databases, which are periodic, plotlevel only, summaries of state inventories, are used mostly 

to provide the data at or before 1990. A detailed list of the 

specific inventory data used in this Inventory is in Table 

A-188 of Annex 3.12.

Forest C stocks are estimated from inventory data by a 

collection of conversion factors and models referred to as 

FORCARB2 (Birdsey and Heath 1995, Birdsey and Heath 

2001, Heath et al. 2003, Smith et al. 2004a), which have 

been formalized in an application referred to as the Carbon 

Calculation Tool (CCT), (Smith et al. 2007). The conversion 

factors and model coefficients are usually categorized by 

region and forest type, and forest C stock estimates are 

dependent on these particular sets of factors. Factors are 

applied to the data at the scale of FIA inventory plots. The 

results are estimates of C density (Mg per hectare) for the 

various forest pools. C density for live trees, standing dead 

trees, understory vegetation, down dead wood, forest floor, 

and soil organic matter are estimated. All non-soil pools 

except forest floor can be separated into aboveground and 

belowground components. The live tree and understory C 

pools are pooled as biomass in this Inventory. Similarly, 

standing dead trees and down dead wood are pooled as dead 

wood in this Inventory. Definitions of ecosystem pools and 

the C conversion process follow, with additional information 

in Annex 3.12.

Live Biomass, Dead Wood, and Litter Carbon

Live tree C pools include aboveground and belowground 

(coarse root) biomass of live trees with diameter at diameter 

breast height (d.b.h.) of at least 2.54 cm at 1.37 m above 

the forest floor. Separate estimates are made for full-tree 

and aboveground-only biomass in order to estimate the 

belowground component. If inventory plots include data 

on individual trees, tree C is based on Jenkins et al. (2003) 

and is a function of species and diameter. Some inventory 

data do not provide measurements of individual trees; tree 
7-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

C in these plots is estimated from plot-level volume of 

merchantable wood, or growing-stock volume, of live trees, 

which is calculated from updates of Smith et al. (2003). Some 

inventory data, particularly some of the older datasets, may 

not include sufficient information to calculate tree C because 

of incomplete or missing tree or volume data; C estimates 

for these plots are based on averages from similar, but more 

complete, inventory data.

Understory vegetation is a minor component of biomass, 

which is defined as all biomass of undergrowth plants in a 

forest, including woody shrubs and trees less than 2.54 cm 

d.b.h. In this Inventory, it is assumed that 10 percent of total 

understory C mass is belowground. Estimates of C density 

are based on information in Birdsey (1996). 

The two components of dead wood—standing dead trees 

and down dead wood—are estimated separately. The standing 

dead tree C pools include aboveground and belowground 

(coarse root) mass and include trees of at least 2.54 cm d.b.h. 

Down dead wood is defined as pieces of dead wood greater 

than 7.5 cm diameter, at transect intersection, that are not 

attached to live or standing dead trees. Down dead wood 

includes stumps and roots of harvested trees. Ratios of down 

dead wood to live tree are used to estimate this quantity. 

Litter C is the pool of organic C (also known as duff, humus, 

and fine woody debris) above the mineral soil and includes 

woody fragments with diameters of up to 7.5 cm. Estimates 

are based on equations of Smith and Heath (2002). 

Forest Soil C

Soil organic C (SOC) includes all organic material in 

soil to a depth of 1 meter but excludes the coarse roots of the 

biomass or dead wood pools. Estimates of SOC are based on 

the national STATSGO spatial database (USDA 1991), and 

the general approach described by Amichev and Galbraith 

(2004). Links to FIA inventory data were developed with 

the assistance of the USDA Forest Service FIA Geospatial 

Service Center by overlaying FIA forest inventory plots on 

the soil C map. Thus, SOC is defined by region and forest 

type group.

C stocks and fluxes for Forest Land Remaining Forest 

Land are reported in pools following IPCC (2006). Total forest 

C stock and flux estimates start with the plot-level calculations 

described above. The separate C densities are summed and 

multiplied by the appropriate expansion factors to obtain 

a C stock estimate for the plot. In turn, these are summed 

to state or sub-state total C stocks. Annualized estimates 

of C stocks are based on interpolating or extrapolating as 

necessary to assign a C stock to each year. For example, the 

C stock of Alabama for 2007 is an extrapolation of the two 

most recent inventory datasets for that particular state, which 

are from 1999 and 2003. Flux, or net annual stock change, is 

simply the difference between two successive years with the 

appropriate sign convention so that net increases in ecosystem 

C are identified as negative flux. This methodological detail 

accounts for the constant estimates of flux from the second 

most recent Inventory to the present (see 2003 through 2006 

on Table 7-6 as an example). 

Harvested Wood Carbon

Estimates of the harvested wood product (HWP) 

contribution to forest C sinks and emissions (hereafter called 

“HWP Contribution”) are based on methods described in 

Skog (in preparation) using the WOODCARB II model. 

These methods are based on IPCC (2006) guidance for 

estimating HWP C. IPCC (2006) provides methods that 

allow Parties to report HWP Contribution using one of 

several different accounting approaches: production, stock 

change and atmospheric flow, as well as a default method 

that assumes there is no change in HWP C stocks (see 

Annex 3-12 for more details about each approach). The 

United States uses the production accounting approach to 

report HWP Contribution. Under the production approach, 

C in exported wood is estimated as if it remains in the 

United States, and C in imported wood is not included in 

inventory estimates. Though reported U.S. HWP estimates 

are based on the production approach, estimates resulting 

from use of the two alternative approaches, the stock change 

and atmospheric flow approaches, are also presented for 

comparison (see Annex 3.12). Annual estimates of change 

are calculated by tracking the additions to and removals from 

the pool of products held in end uses (i.e., products in use 

such as housing or publications) and the pool of products 

held in SWDS. 

Solidwood products added to pools include lumber and 

panels. End-use categories for solidwood include single and 

multifamily housing, alteration and repair of housing, and 

other end-uses. There is one product category and one end-use 

category for paper. Additions to and removals from pools are 

tracked beginning in 1900, with the exception that additions 

of softwood lumber to housing begins in 1800. Solidwood 
Land Use, Land-Use Change, and Forestry 7-19

and paper product production and trade data are from USDA 

Forest Service and other sources (Hair and Ulrich 1963; 

Hair 1958; USDC Bureau of Census; 1976; Ulrich, 1985, 

1989; Steer 1948; AF&PA 2006a 2006b; Howard 2003 & 

forthcoming). Estimates for disposal of products reflect the 

change over time in the fraction of products discarded to 

SWDS (as opposed to burning or recycling) and the fraction 

of SWDS that are in sanitary landfills versus dumps.

There are 5 annual HWP variables that are used in varying 

combinations to estimate HWP Contribution using any one of 

the three main approaches listed above. These are:

(1A) annual change of C in wood and paper products in 

use in the United States, 

(1B) annual change of C in wood and paper products in 

SWDS in the United States, 

(2A) annual change of C in wood and paper product 

in use in the United States and other countries 

where the wood came from trees harvested in the 

United States, 

(2B) annual change of C in wood and paper products 

in SWDS in the United States and other countries 

where the wood came from trees harvested in the 

United States, 

(3) C in imports of wood, pulp, and paper to the 

United States, 

(4) C in exports of wood, pulp and paper from the 

United States, and

(5) C in annual harvest of wood from forests in the 

United States.

The sum of variables 2A and 2B yields the estimate 

for HWP Contribution under the production accounting 

approach. A key assumption for estimating these variables 

is that products exported from the United States and held in 

pools in other countries have the same half lives for products 

in use, the same percentage of discarded products going to 

SWDS, and the same decay rates in SWDS as they would 

in the United States.

Uncertainty

The 2006 flux estimate for forest C stocks is estimated 

to be between -579.0 and -913.2 Tg CO2 Eq. at a 95 percent 

confidence level. This includes a range of -471.2 to -802.2 

Tg CO2 Eq. in forest ecosystems and -85.5 to -136.8 Tg CO2

Eq. for HWP. The relatively smaller range of uncertainty, 

in terms of percentage, for the total relative to the two 

separate parts is because the total is based on summing the 

two independent uncertain parts, as discussed above. More 

information on the uncertainty estimates for Net CO2 Flux 

from Forest Land Remaining Forest Land: Changes in Forest 

C Stocks is contained within the Uncertainty Annex.

QA/QC and Verification

As discussed above, the FIA program has conducted 

consistent forest surveys based on extensive statisticallybased sampling of most of the forest land in the conterminous 

United States, dating back to 1952. The main purpose of the 

FIA program has been to estimate areas, volume of growing 

stock, and timber products output and utilization factors. 

The FIA program includes numerous quality assurance and 

quality control (QA/QC) procedures, including calibration 

among field crews, duplicate surveys of some plots, and 

systematic checking of recorded data. Because of the 

statistically-based sampling, the large number of survey plots, 

and the quality of the data, the survey databases developed 

by the FIA program form a strong foundation for C stock 

estimates. Field sampling protocols, summary data, and 

detailed inventory databases are archived and are publicly 

available on the Internet (USDA Forest Service 2006b).

Table 7-10: Tier 2 Quantitative Uncertainty Estimates for Net CO2 Flux from Forest Land Remaining Forest Land: 

Changes in Forest C Stocks (Tg CO2 Eq. and Percent)

2006 Flux Estimate Uncertainty Range Relative to Flux Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Forest Ecosystem CO2 (635.1) (802.2) (471.2) -26% +26%

Harvested Wood Products CO2 (110.0) (136.8) (85.5) -24% +22%

Total Forest CO2 (745.1) (913.2) (579.0) -23% +22%

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.
7-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Many key calculations for estimating current forest C 

stocks based on FIA data are based on coefficients from 

the FORCARB2 model (see additional discussion in the 

Methodology section above and in Annex 3.12). The model 

has been used for many years to produce national assessments 

of forest C stocks and stock changes. General quality control 

procedures were used in performing calculations to estimate 

C stocks based on survey data. For example, the derived C 

datasets, which include inventory variables such as areas 

and volumes, were compared with standard inventory 

summaries such as Resources Planning Act (RPA) Forest 

Resource Tables or selected population estimates generated 

from the FIA Database (FIADB), which are available at an 

FIA Internet site (USDA Forest Service 2006b). Agreement 

between the C datasets and the original inventories is 

important to verify accuracy of the data used. Finally, C stock 

estimates were compared with previous Inventory report 

estimates to ensure that any differences could be explained 

by either new data or revised calculation methods (see the 

“Recalculations” discussion below).

Estimates of the HWP variables and the HWP 

Contribution under the production accounting approach use 

data from U.S. Census and USDA Forest Service surveys of 

production and trade. Factors to convert wood and paper from 

original units to C units are based on estimates by industry 

and Forest Service published sources. The WOODCARB II 

model uses estimation methods suggested by IPCC (2006). 

Estimates of annual C change in solidwood and paper 

products in use were verified by two independent criteria. The 

first criteria is that the WOODCARB II model estimate of C 

in houses standing in 2001 needs to match an independent 

estimate of C in housing based on U.S. Census and USDA 

Forest Service survey data. Meeting the first criteria resulted 

in an estimated half life of about 80 years for single family 

housing built in the 1920s, which is confirmed by other 

U.S. Census data on housing. The second criteria is that the 

WOODCARB II model estimate of wood and paper being 

discarded to SWDS needs to match EPA estimates of discards 

each year over the period 1990 to 2000. These criteria help 

reduce uncertainty in estimates of annual change in C in 

products in use in the United States and to a lesser degree 

reduces uncertainty in estimates of annual change in C in 

products made from wood harvested in the United States.

Recalculations Discussion

The overall process for developing annualized estimates 

of forest ecosystem C stocks based on the individual state 

surveys and the C conversion factors are identical to that 

presented in the previous Inventory (Smith et al. 2007). 

However, revised estimates of forest ecosystem C stock 

increased by 3 percent for 1990 and 2005. Similarly, estimated 

net stock change increased by 4 percent for 1990 and by 6 

percent for 2005. The addition of newly available forest 

inventory data as well as some refinements in previously 

existing data were the principal factors contributing to these 

changes. Inventory data changed for 31 of the 48 states 

included in the previous Inventory. However, not all of the 

changes are apparent in the list of inventory data used for 

C estimates (Table A-186) because some changes involved 

reclassification and recalculation of existing data. In addition, 

a portion of Alaskan forest is included in this Inventory for 

the first time. Carbon stock and change estimates for the 

early 1990s are still sensitive to updates made over the last 

year, which are primarily associated with the most recent 

data per state, because 13 of the 49 states are still entirely 

or partly based on two C stock estimates (Table A-186). 

Thus, even an update for a 2006 C stock, for example, is 

propagated throughout the interval when stock change is 

linearly interpolated between the two stocks.

The basic model and data used to estimate HWP 

contribution under the production approach are unchanged 

since the previous Inventory (Skog in preparation). However, 

minor modifications to some model coefficients resulted 

in slight increases in estimated C sequestration so that net 

annual additions to C in HWP increased by 0.5 and 5 percent 

for 1990 and 2005, respectively, with an average increase of 3 

percent across the sixteen years. Modifications to parameters 

included: (1) shorter half-life for decay in dumps and (2) 

separation of decay in dumps from decay in landfills.

Planned Improvements

The ongoing annual surveys by the FIA Program will 

improve precision of forest C estimates as new state surveys 

become available (Gillespie 1999). The annual surveys will 

eventually include all states. To date, five states are not yet 

reporting any data from the annualized sampling design of 

FIA: Hawaii, Mississippi, New Mexico, Oklahoma, and 
Land Use, Land-Use Change, and Forestry 7-21

Wyoming. Estimates for these states are currently based on 

older, periodic data. Hawaii and U.S. territories will also be 

included when appropriate forest C data are available. In 

addition, the more intensive sampling of down dead wood, 

litter, and soil organic C on some of the permanent FIA plots 

continues and will substantially improve resolution of C pools 

at the plot level for all U.S. forest land when this information 

becomes available. Improved resolution, incorporating more 

of Alaska’s forests, and using annualized sampling data as 

it becomes available for those states currently not reporting 

are planned for future reporting.

As more information becomes available about historical 

land use, the ongoing effects of changes in land use and 

forest management will be better accounted for in estimates 

of soil C (Birdsey and Lewis 2003, Woodbury et al. 2006, 

Woodbury et al. 2007). Currently, soil C estimates are based 

on the assumption that soil C density depends only on broad 

forest type group, not on land-use history. However, longterm residual effects on soil and forest floor C stocks are 

likely after land-use change. Estimates of such effects are 

being developed based on methods described by Woodbury 

et al. (2007), and preliminary results demonstrate effects 

on soil organic C and forest floor. Additional development 

is required to link model results with: (1) the C change 

methods used for this Inventory (Smith et al. 2007), and (2) 

a consistent representation of the land base and land-use 

change for the United States (See 7.1 Representation of the 

U.S. Land Base in the National Greenhouse Gas Inventory 

for more details).

Similarly, agroforestry practices, such as windbreaks 

or riparian forest buffers along waterways, are not currently 

accounted for in the Inventory. In order to properly account 

for the C stocks and fluxes associated with agroforestry, 

research will be needed that provides the basis and tools for 

including these plantings in a nation-wide Inventory, as well 

as the means for entity-level reporting.

Non-CO2 Emissions From Forest Fires

Emissions of non-CO2 gases from forest fires were 

estimated using the default IPCC (2003) methodology. 

Emissions from this source in 2006 were estimated to be 

24.6 Tg CO2 Eq. of CH4 and 2.5 Tg CO2 Eq. of N2O, as 

shown in Table 7-11 and Table 7-12. The estimates of nonCO2 emissions from forest fires account for both the lower 

48 states and Alaska.

Methodology

The IPCC (2003) Tier 2 default methodology was used 

to calculate non-CO2 emissions from forest fires. Estimates 

for CH4 emissions were calculated by multiplying the total 

estimated C emitted (see Table 7-13) from forest burned by 

gas-specific emissions ratios and conversion factors. N2O 

emissions were calculated in the same manner, but were also 

multiplied by an N-C ratio of 0.01 as recommended by IPCC 

(2003). The equations used were: 

 

 

 

Estimates for C emitted from forest fires, presented 

in Table 7-13, are the same estimates used to generate 

estimates of CO2 emissions from forest fires, presented 

CH4 Emissions = (C released) × (emission ratio) × 16/12

N2O Emissions = (C released) × (N/C ratio) ×

(emission ratio) × 44/28

Table 7-11: Estimated Non-CO2 Emissions from Forest Fires (Tg CO2 Eq.) for U.S. Forestsa

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6

N2O 0.5 0.5 1.9 1.0 1.7 0.9 0.7 1.2 2.5

Total 4.9 5.2 20.9 10.4 18.0 9.6 7.6 13.6 27.0

a

 Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003).

Table 7-12: Estimated Non-CO2 Emissions from Forest Fires (Gg Gas) for U.S. Forestsa

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 213 224 904 448 780 416 330 586 1,169

N2O 1 2 6 3 5 3 2 4 8

a

 Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003).
7-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

earlier in Box 7-1. See Table A-197 and explanation in 

Annex 3.12 for more details on the methodology used to 

estimate C emitted from forest fires.

Uncertainty

Non-CO2 gases emitted from forest fires depend on 

several variables, including forest area and average C 

density for forest land in both Alaska and the lower 48 states, 

emission ratios, and combustion factor values (proportion 

of biomass consumed by fire). To quantify the uncertainties 

for emissions from forest fires, a Monte Carlo (Tier 2) 

uncertainty analysis was performed using information about 

the uncertainty surrounding each of these variables. The 

results of the Tier 2 quantitative uncertainty analysis are 

summarized in Table 7-14. 

QA/QC and Verification

Tier 1 and Tier 2 QA/QC activities were conducted 

consistent with the U.S. QA/QC plan. The QA/QC plan 

for forest fires followed the QA/QC plan implemented 

for forest C. A source-specific QA/QC plan for forest fires 

will be developed and implemented for the next Inventory. 

Quality control measures included checking input data, 

documentation, and calculations to ensure data were properly 

handled through the Inventory process. Errors that were 

found during this process were corrected as necessary.

Recalculations Discussion

Average carbon density for Alaska was updated from 

70 Mg/ha to 331 Mg/ha based on new data from the FIA 

National Program. In addition, the static ratio used in the 

previous Inventory to estimate the proportion of forestland 

burned from data on total area burned was replaced with a 

ratio that varied across the inventory time series. See Annex 

3.12 for details and additional information related to the 

methods described.

Direct N2O Fluxes from Forest Soils 

(IPCC Source Category 5A1) 

Of the synthetic N fertilizers applied to soils in the 

United States, no more than one percent is applied to forest 

soils. Application rates are similar to those occurring on 

cropped soils, but in any given year, only a small proportion 

Table 7-13: Estimated Carbon Released from Forest 

Fires for U.S. Forests

Year C Emitted (Tg/yr)

1990 13.3

1995 14.0

2000 56.5

2001 28.0

2002 48.7

2003 26.0

2004 20.6

2005 36.6

2006 73.1

Table 7-14: Tier 2 Quantitative Uncertainty Estimates of Non-CO2 Emissions from Forest Fires in Forest Land 

Remaining Forest Land (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Non-CO2 Emissions from Forest Fires CH4 24.6 7.7 42.1 -69% +71%

Non-CO2 Emissions from Forest Fires N2O 2.5 0.8 4.4 -69% +75%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Land Use, Land-Use Change, and Forestry 7-23

of total forested land receives N fertilizer. This is because 

forests are typically fertilized only twice during their 

approximately 40-year growth cycle (once at planting and 

once approximately 20 years later). Thus, although the rate 

of N fertilizer application for the area of forests that receives 

N fertilizer in any given year is relatively high, average 

annual applications, inferred by dividing all forest land that 

may undergo N fertilization at some point during its growing 

cycle by the amount of N fertilizer added to these forests in a 

given year, is quite low. N2O emissions from forest soils are 

estimated to have increased by a multiple of 5.5 from 1990 to 

2006. The trend toward increasing N2O emissions is a result 

of an increase in the area of N fertilized pine plantations in the 

southeastern United States. Total forest soil N2O emissions 

are summarized in Table 7-15.

Methodology

The IPCC Tier 1 approach was used to estimate N2O 

from soils within Forest Land Remaining Forest Land. 

According to U.S. Forest Service statistics for 1996 (USDA 

Forest Service 2001), approximately 75 percent of trees 

planted were for timber, and about 60 percent of national 

total harvested forest area are in the southeastern United 

States. It was assumed that southeastern pine plantations 

represent the vast majority of fertilized forests in the United 

States. Therefore, estimates of direct N2O emissions from 

fertilizer applications to forests were based on the area 

of pine plantations receiving fertilizer in the southeastern 

United States and estimated application rates (North Carolina 

Sate Forest Nutrition Cooperative 2002). Not accounting 

for fertilizer applied to non-pine plantations is justified 

because fertilization is routine for pine forests but rare for 

hardwoods (Binkley et al. 1995). For each year, the area of 

pine receiving N fertilizer was multiplied by the midpoint 

of the reported range of N fertilization rates (150 lbs. N per 

acre). Data for areas of forests receiving fertilizer outside the 

southeastern United States were not available, so N additions 

to non-southeastern forests are not included here. It should 

be expected, however, that emissions from the small areas 

of fertilized forests in other regions would not be substantial 

because the majority of trees planted and harvested for timber 

are in the southeastern United States (USDA Forest Service 

2001). Area data for pine plantations receiving fertilizer in 

the Southeast were not available for 2002, 2003, 2004, 2005, 

and 2006, so data from 2001 were used for these years. The 

N applied to forests was multiplied by the IPCC (2006) 

default emission factor of 1 percent to estimate direct N2O 

emissions. The volatilization and leaching/runoff fractions, 

calculated according to the IPCC default factors of 10 percent 

and 30 percent, respectively, were included with all sources 

of indirect emissions in the Agricultural Soil Management 

source category of the Agriculture chapter. 

Uncertainty

The amount of N2O emitted from forests depends not only 

on N inputs, but also on a large number of variables, including 

organic C availability, O2 partial pressure, soil moisture 

content, pH, temperature, and tree planting/harvesting cycles. 

The effect of the combined interaction of these variables 

on N2O flux is complex and highly uncertain. IPCC (2006) 

does not incorporate any of these variables into the default 

methodology and only accounts for variations in estimated 

fertilizer application rates and estimated areas of forested land 

receiving N fertilizer. All forest soils are treated equivalently 

under this methodology. Furthermore, only synthetic N 

fertilizers are captured, so applications of organic N fertilizers 

are not estimated. However, the total quantity of organic N 

inputs to soils is included in the Agricultural Soil Management 

and Settlements Remaining Settlements sections. 

Table 7-15: N2O Fluxes from Soils in Forest Land 

Remaining Forest Land (Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 0.1 0.2

1995 0.2 0.5

2000 0.3 1.0

2001 0.3 1.1

2002 0.3 1.1

2003 0.3 1.1

2004 0.3 1.1

2005 0.3 1.1

2006 0.3 1.1

Note: These estimates include direct N2O emissions from N fertilizer 

additions only. Indirect N2O emissions from fertilizer additions are 

reported in the Agriculture chapter. These estimates include emissions 

from both Forest Land Remaining Forest Land and from Land Converted 

to Forest Land.
7-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Uncertainties exist in the fertilization rates, annual 

area of forest lands receiving fertilizer, and the emission 

factors. Fertilization rates were assigned a default level26

of uncertainty at ±50 percent, and area receiving fertilizer 

was assigned a ±20 percent according to expert knowledge 

(Binkley 2004). IPCC (2006) provided estimates for the 

uncertainty associated with direct N2O emission factor 

for synthetic N fertilizer application to soils. Quantitative 

uncertainty of this source category was estimated through 

the IPCC-recommended Tier 2 uncertainty estimation 

methodology. The uncertainty ranges around the 2005 

activity data and emission factor input variables were directly 

applied to the 2006 emissions estimates. The results of the 

quantitative uncertainty analysis are summarized in Table 

7-16. N2O fluxes from soils were estimated to be between 

0.1 and 1.1 Tg CO2 Eq. at a 95 percent confidence level. This 

indicates a range of 59 percent below and 211 percent above 

the 2006 emission estimate of 0.3 Tg CO2 Eq.

Recalculations Discussion

No recalculations were performed for the time series.

Planned Improvements

State-level area data will be acquired for southeastern 

pine plantations receiving fertilizer to estimate soil N2O 

emission by state and provide information about regional 

variation in emission patterns.

26 Uncertainty is unknown for the fertilization rates so a conservative value 

of ±50% was used in the analysis.

7.3. Land Converted to Forest Land

(IPCC Source Category 5A2)

Land-use change is constantly occurring, and areas 

under a number of differing land-use types are converted to 

forest each year, just as forest land is converted to other uses. 

However, the magnitude of these changes is not currently 

known. Given the paucity of available land-use information 

relevant to this particular IPCC source category, it is not 

possible to separate CO2 or N2O fluxes on Land Converted 

to Forest Land from fluxes on Forest Land Remaining Forest 

Land at this time.

7.4. Cropland Remaining Cropland

(IPCC Source Category 5B1)

Mineral and Organic Soil Carbon 

Stock Changes

Soils contain both organic and inorganic forms of C, but 

soil organic C (SOC) stocks are the main source or sink for 

atmospheric CO2 in most soils. Changes in inorganic C stocks 

are typically minor. Soil organic C is the dominant organic 

C pool in cropland ecosystems, because biomass and dead 

organic matter have considerably less C and those pools are 

relatively ephemeral. IPCC/UNEP/OECD/IEA (1997) and 

IPCC (2006) recommends reporting changes in soil organic C 

Table 7-16: Quantitative Uncertainty Estimates of N2O Fluxes from Soils in Forest Land Remaining Forest Land 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Forest Land Remaining Forest Land: 

N2O Fluxes from Soils N2O 0.3 0.1 1.1 -59% +211%

Note: This estimate includes direct N2O emissions from N fertilizer additions to both Forest Land Remaining Forest Land and Land Converted to Forest Land.
Land Use, Land-Use Change, and Forestry 7-25

stocks due to agricultural land-use and management activities 

on mineral soils and organic soils.27

Typical well-drained mineral soils contain from 1 to 6 

percent organic C by weight, although some mineral soils 

that are saturated with water for substantial periods during the 

year may contain significantly more C (NRCS 1999). When 

mineral soils undergo conversion from their native state to 

agricultural uses, as much as half the SOC can be lost to the 

atmosphere. The rate and ultimate magnitude of C loss will 

depend on pre-conversion conditions, conversion method and 

subsequent management practices, climate, and soil type. In 

the tropics, 40 to 60 percent of the C loss generally occurs 

within the first 10 years following conversion; C stocks 

continue to decline in subsequent decades but at a much 

slower rate. In temperate regions, C loss can continue for 

several decades, reducing stocks by 20 to 40 percent of native 

C levels. Eventually, the soil can reach a new equilibrium 

that reflects a balance between C inputs (e.g., decayed plant 

matter, roots, and organic amendments such as manure and 

crop residues) and C loss through microbial decomposition 

of organic matter. However, land use, management, and 

other conditions may change before the new equilibrium is 

reached. The quantity and quality of organic matter inputs and 

their rate of decomposition are determined by the combined 

interaction of climate, soil properties, and land use. Land-use 

and agricultural practices such as clearing, drainage, tillage, 

planting, grazing, crop residue management, fertilization, 

and flooding, can modify both organic matter inputs and 

decomposition and thereby result in a net flux of C to or 

from the pool of soil C.

Organic soils, also referred to as histosols, include all 

soils with more than 12 to 20 percent organic C by weight, 

depending on clay content (NRCS 1999, Brady and Weil 

1999). The organic layer of these soils can be very deep 

(i.e., several meters), forming under inundated conditions, 

in which minimal decomposition of plant residue occurs. 

When organic soils are prepared for crop production, they 

are drained and tilled, leading to aeration of the soil, which 

accelerates the rate of decomposition and CO2 emissions. 

Because of the depth and richness of the organic layers, C loss 

from drained organic soils can continue over long periods of 

27CO2 emissions associated with liming are also estimated but included in 

a separate section of the report.

time. The rate of CO2 emissions varies depending on climate 

and composition (i.e., decomposability) of the organic matter. 

Also, the use of organic soils for annual crop production 

leads to higher C loss rates than drainage of organic soils 

in grassland or forests, due to deeper drainage and more 

intensive management practices in cropland (Armentano and 

Verhoeven 1990, as cited in IPCC/UNEP/OECD/IEA 1997). 

C losses are estimated from drained organic soils under both 

grassland and cropland management in this Inventory.

Cropland Remaining Cropland includes all cropland 

in a year of the Inventory that had been cropland for the 

last 20 years28 according to the USDA NRI land use survey 

(USDA-NRCS 2000). Consequently, the area of Cropland 

Remaining Cropland changes through time with land-use 

change. For this area, CO2 emissions and removals29 due 

to changes in mineral soil C stocks are estimated using a 

Tier 3 approach for the majority of annual crops. A Tier 2 

IPCC method is used for the remaining crops (vegetables, 

tobacco, perennial/horticultural crops, and rice) not included 

in the Tier 3 method. In addition, a Tier 2 method is used for 

very gravelly, cobbly or shaley soils (i.e., classified as soils 

that have greater than 35 percent of soil volume comprised 

of gravel, cobbles or shale) and for additional changes in 

mineral soil C stocks that were not addressed with the Tier 

2 or 3 approaches (i.e., change in C stocks after 1997 due to 

Conservation Reserve Program enrollment). Emissions from 

organic soils are estimated using a Tier 2 IPCC method. 

Of the two sub-source categories, land-use and land 

management of mineral soils was the most important 

component of total net C stock change between 1990 and 

2006 (see Table 7-17 and Table 7-18). In 2006, mineral soils 

were estimated to remove about 69.5 Tg CO2 Eq. (19.0 Tg 

C). This rate of C storage in mineral soils represented about a 

20 percent increase in the rate since the initial reporting year 

of 1990. Emissions from organic soils were about 27.7 Tg 

CO2 Eq. (7.5 Tg C) in 2006. In total, U.S. agricultural soils 

in Cropland Remaining Cropland removed approximately 

41.8 Tg CO2 Eq. (11.4 Tg C) in 2006.

28 NRI points were classified according to land-use history records starting 

in 1982 when the NRI survey began. Therefore, the classification was based 

on less than 20 years of recorded land-use history for the time series from 

1982 to 2001.

29 Note that removals occur through crop and forage uptake of CO2 into 

biomass C that is later incorporated into soils pools.
7-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

The net increase in soil C stocks (39 percent for 2006, 

relative to 1990) was largely due to an increase in annual 

cropland enrolled in the Conservation Reserve Program, 

intensification of crop production by limiting the use of 

bare-summer fallow in semi-arid regions, increased hay 

production, and adoption of conservation tillage (i.e., 

reduced- and no-till practices). At present (2006), cropland 

enrolled in the Conservation Reserve Program accounts 

for 32 percent of the increase of C stocks for Cropland 

Remaining Cropland on mineral soils (Table 7-18).

The spatial variability in annual CO2 flux associated with 

C stock changes in mineral and organic soils is displayed in 

Figure 7-5 and Figure 7-6. The highest rates of sequestration 

in mineral soils occurred in the Midwest, where there were 

the largest amounts of cropland managed with conservation 

tillage. Rates were also high in the Great Plains due to 

enrollment in the Conservation Reserve Program. Emission 

rates from drained organic soils were highest along the 

southeastern coastal region, in the northeast central United 

States surrounding the Great Lakes, and along the central 

and northern portions of the west coast.

The estimates presented here are restricted to C 

stock changes in agricultural soils. Agricultural soils 

are also important sources of other greenhouse gases, 

particularly N2O from application of fertilizers, manure, 

and crop residues and from cultivation of legumes, as well 

as CH4 from flooded rice cultivation. These emissions 

are accounted for in the Agriculture chapter, along with 

non-CO2 greenhouse gas emissions from field burning of 

crop residues and CH4 and N2O emissions from livestock 

digestion and manure management.

Table 7-17: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg CO2 Eq.)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Mineral Soils (57.5) (67.0) (66.1) (67.7) (68.0) (68.1) (68.5) (68.7) (69.5)

Organic Soils 27.4 27.7 27.7 27.7 27.7 27.7 27.7 27.7 27.7

Total Net Flux (30.1) (39.4) (38.4) (40.0) (40.3) (40.5) (40.9) (41.0) (41.8)

Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are 

based on historical data only. Totals may not sum due to independent rounding.

Table 7-18: Net CO2 Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg C)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Mineral Soils (15.7) (18.3) (18.0) (18.5) (18.5) (18.6) (18.7) (18.7) (19.0)

Organic Soils 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5 7.5

Total Net Flux (8.2) (10.7) (10.5) (10.9) (11.0) (11.0) (11.1) (11.2) (11.4)

Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values 

are based on historical data only. Totals may not sum due to independent rounding.
Land Use, Land-Use Change, and Forestry 7-27

Figure 7-5

Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the 

Tier 2 and 3 Inventory computations. See Methodology for additional details.

Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States, 1993–2006 

Cropland Remaining Cropland

Tg CO2 Eq./year

< -2

-2 to -1

-1 to -0.5

-0.5 to -0.1

-0.1 to 0

> 0

Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States, 1993–2006 

Cropland Remaining Cropland

Figure 7-6

Note: Values greater than zero represent emissions.

Tg CO2 Eq./year

0 to 0.1

0.1 to 0.5

0.5 to 1

1 to 2

> 2

No organic soils
7-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Methodology

The following section includes a description of 

the methodology used to estimate changes in soil C 

stocks due to: (1) agricultural land-use and management 

activities on mineral soils, and (2) agricultural land-use 

and management activities on organic soils for Cropland 

Remaining Cropland.

Soil C stock changes were estimated for Cropland 

Remaining Cropland (as well as agricultural land falling into 

the IPCC categories Land Converted to Cropland, Grassland 

Remaining Grassland, and Land Converted to Grassland) 

according to land-use histories recorded in the USDA 

National Resources Inventory (NRI) survey (USDA-NRCS 

2000). The NRI is a statistically-based sample of all nonfederal land, and includes ca. 400,000 points in agricultural 

land of the conterminous United States and Hawaii.30 Each 

point is associated with an “expansion factor” that allows 

scaling of C stock changes from NRI points to the entire 

country (i.e., each expansion factor represents the amount 

of area with the same land-use/management history as the 

sample point). Land-use and some management information 

(e.g., crop type, soil attributes, and irrigation) were collected 

for each NRI point on a 5-year cycle beginning in 1982, 

and were subdivided into four inventory time periods, 1980 

through 1984, 1985 through 1989, 1990 through 1994, and 

1995 through 2000. 

NRI points were classified as Cropland Remaining 

Cropland for an inventory time period (e.g., 1990 through 

1994 and 1995 through 2000) if the land use had been 

cropland for 20 years.31 Cropland includes all land used to 

produce food or fiber, as well as forage that is harvested and 

used as feed (e.g., hay and silage). 

Mineral Soil Carbon Stock Changes

An IPCC Tier 3 model-based approach was used to 

estimate C stock changes for mineral soils used to produce a 

majority of annual crops in the United States. The remaining 

crops on mineral soils were estimated using an IPCC Tier 

2 method (Ogle et al. 2003), including vegetables, tobacco, 

30 NRI points were classified as agricultural if under grassland or cropland 

management in 1992 and/or 1997.

31 NRI points were classified according to land-use history records starting 

in 1982 when the NRI survey began. Therefore, the classification was based 

on less than 20 years of recorded land-use history for the time series from 

1982 to 2001.

perennial/horticultural crops, rice, and crops rotated with 

these crops. The Tier 2 method was also used for very 

gravelly, cobbly or shaley soils (greater than 35 percent by 

volume). Mineral SOC stocks were estimated using a Tier 

2 method for these areas, because the Century model used 

for the Tier 3 method has not been fully tested to address 

its adequacy for estimating C stock changes associated 

with certain crops and rotations, as well as cobbly, gravelly 

or shaley soils. An additional stock change calculation 

was made for mineral soils using Tier 2 emission factors, 

accounting for enrollment patterns in the Conservation 

Reserve Program after 1997, which was not addressed by 

the Tier 3 methods. 

Further elaboration on the methodology and data used 

to estimate stock changes from mineral soils are described 

below and in Annex 3.13. 

Tier 3 Approach

Mineral SOC stocks and stock changes were estimated 

using the Century biogeochemical model (Parton et al. 1987, 

1988, 1994; Metherell et al. 1993), which simulates the 

dynamics of C and other elements in cropland, grassland, 

forest, and savanna ecosystems. It uses monthly weather 

data as input, along with information about soil physical 

properties. Input data on land use and management can 

be specified at monthly resolution and include land-use 

type, crop/forage type and management activities (e.g., 

planting, harvesting, fertilization, manure amendments, 

tillage, irrigation, residue removal, grazing, and fire). The 

model computes net primary productivity and C additions 

to soil, soil temperature, and water dynamics, in addition to 

turnover, stabilization, and mineralization of soil organic 

matter C and nutrient (N, K, S) elements. This method is 

more accurate than the Tier 1 and 2 approaches provided 

by the IPCC, because the simulation model treats changes 

as continuous over time rather than the simplified discrete 

changes represented in the default method (see Box 7-2 for 

additional information). National estimates were obtained by 

simulating historical land-use and management patterns as 

recorded in the USDA National Resources Inventory (NRI) 

survey. Land-use and management activities were grouped 

into inventory time periods (i.e., time “blocks”) for 1980 

through 1984, 1985 through 1989, 1990 through 1994, and 

1995 through 2000, using NRI data from 1982, 1987, 1992, 

and 1997, respectively.
Land Use, Land-Use Change, and Forestry 7-29

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 notill agriculture (Towery 2001). Information on fertilizer use 

and rates by crop type for different regions of the United 

States were obtained primarily from the USDA Economic 

Research Service Cropping Practices Survey (ERS 1997) 

with additional data from other sources, including the 

National Agricultural Statistics Service (NASS 1992, 

1999, 2004). Frequency and rates of manure application to 

cropland during 1997 were estimated from data compiled 

by the USDA Natural Resources Conservation Service 

(Edmonds et al. 2003), and then adjusted using countylevel estimates of manure available for application in other 

years of the Inventory. Specifically, county-scale ratios of 

manure available in other years relative to 1997 were used 

to adjust the area amended with manure (see Annex 3.13 for 

further details). Greater availability of managed manure N 

relative to 1997 was, thus, assumed to increase the amount 

of area amended with manure, while reduced availability 

of manure N relative to 1997 was assumed to reduce the 

amended area. 

The amount of manure produced by each livestock 

type was calculated for managed and unmanaged waste 

management systems. Managed systems include feedlots or 

other housing (which requires manure to be collected and 

managed); unmanaged systems include daily spread, pasture, 

range, and paddock systems. Annual animal population data 

for all livestock types, except horses and goats, were obtained 

for all years from the U.S. Department of AgricultureNational Agricultural Statistics Service. Population data 

used for cattle, swine, and sheep were downloaded from the 

USDA NASS Population Estimates Database (USDA 2007a). 

Poultry population data were obtained from USDA NASS 

reports (USDA 1995a, 1995b, 1998a, 1999, 2004a, 2004b, 

2006a, 2006b, 2007b, 2007c). Horse population data were 

obtained from the FAOSTAT database (FAO 2007). Goat 

population data for 1992, 1997, and 2002 were obtained 

from the Census of Agriculture (USDA 2005); these data 

were interpolated and extrapolated to derive estimates for 

A Tier 3 model-based approach is used to inventory soil C stock changes on the majority of agricultural land with mineral soils. This 

approach entails several fundamental differences compared to the IPCC Tier 1 or 2 methods, which are based on a classification of land areas 

into a number of discrete states based on a highly aggregated classification of climate, soil, and management (i.e., only six climate regions, 

seven soil types and eleven management systems occur in U.S. agricultural land under the IPCC categorization scheme). Input variables 

to the Tier 3 model, including climate, soils, and management activities (e.g., fertilization, crop species, tillage, etc.), are represented in 

considerably more detail both temporally and spatially, and exhibit multi-dimensional interactions through the more complex model structure 

compared with the IPCC Tier 1 or 2 approach. The spatial resolution of the analysis is also finer in the Tier 3 method compared to the lower 

tier methods as implemented in the United States for previous Inventories (e.g., 3,037 counties versus 181 Major Land Resource Areas 

(MLRAs), respectively).

In the Century model, soil C dynamics (and CO2 emissions and uptake) are treated as continuous variables, which change on a monthly 

time step. C emissions and removals are an outcome of plant production and decomposition processes, which are simulated in the model 

structure. Thus, changes in soil C stocks are influenced by not only changes in land use and management but also inter-annual climate 

variability and secondary feedbacks between management activities, climate and soils as they affect primary production and decomposition. 

This latter characteristic constitutes one of the greatest differences between the methods, and forms the basis for a more complete accounting 

of soil C stock changes in the Tier 3 approach compared with Tier 2 methodology.

Because the Tier 3 model simulates a continuous time period rather than as an equilibrium step change used in the IPCC methodology 

(Tier 1 and 2), the Tier 3 model addresses the delayed response of the soil to management and land-use changes, which can occur due to 

variable weather patterns and other environmental constraints that interact with land use and management and affect the time frame over 

which stock changes occur. Moreover, the Tier 3 method also accounts for the overall effect of increasing yields and, hence, C input to soils 

that have taken place across management systems and crop types within the United States. Productivity has increased by 1 to 2 percent 

annually over the past 4 to 5 decades for most major crops in the United States (Reilly and Fuglie 1998), which is believed to have led to 

increases in cropland soil C stocks (e.g., Allmaras et al. 2000). This is a major difference from the IPCC-based Tier 1 and 2 approaches, 

in which soil C stocks change only with discrete changes in management and/or land use, rather than a longer term trend such as gradual 

increases in crop productivity. 

Box 7-2: Tier 3 Inventory for Soil C Stocks Compared to Tier 1 or 2 Approaches
7-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

the other years. Information regarding poultry turnover (i.e., 

slaughter) rate was obtained from state Natural Resource 

Conservation Service personnel (Lange 2000). Additional 

population data for different farm size categories for dairy 

and swine were obtained from the 1992, 1997, and 2002 

Census of Agriculture (USDA 2005).

Manure amendments were an input to the Century Model 

based on manure N available for application from all managed 

or unmanaged systems except Pasture/Range/Paddock.32

Data on the county-level N available for application were 

estimated for managed systems based on the total amount 

of N excreted in manure minus N losses and including the 

addition of N from bedding materials. N losses include direct 

nitrous oxide emissions, volatilization of ammonia and NOx, 

and runoff and leaching. More information on these losses 

is available in the description of the Manure Management 

source category. Animal-specific bedding factors were set 

equal to IPCC default factors (IPCC 2006). For unmanaged 

systems, it is assumed that no N losses or additions occur.

Monthly weather data, aggregated to county-scale from 

the Parameter-elevation Regressions on Independent Slopes 

Model (PRISM) database (Daly et al. 1994), were used as 

an input in the model simulations. Soil attributes, which 

were obtained from an NRI database, were assigned based 

on field visits and soil series descriptions. Where more than 

one inventory point was located in the same county (i.e., 

same weather) and had the same land-use/management 

histories and soil type, data inputs to the model were identical 

and, therefore, these points were clustered for simulation 

purposes. For the 370,738 NRI points representing nonfederal cropland and grassland, there were a total of 170,279 

clustered points that represent the unique combinations of 

climate, soils, land use, and management in the modeled 

data set. Each NRI cluster point was run 100 times as part 

of the uncertainty assessment, yielding a total of over 14 

million simulation runs for the analysis. C stock estimates 

from Century were adjusted using a structural uncertainty 

estimator accounting for uncertainty in model algorithms 

and parameter values (Ogle et al. 2007). Mean changes in C 

stocks and 95 percent confidence intervals were estimated 

32 Pasture/Range/Paddock manure additions to soils are addressed in 

the Grassland Remaining Grassland and Land Converted to Grassland

categories.

for 1990 to 1994 and 1995 to 2000 (see Uncertainty section 

for more details). C stock changes from 2001 to 2006 were 

assumed to be similar to the 1995 to 2000 block, because 

no additional activity data are currently available from the 

NRI for the later years.

Tier 2 Approach

In the IPCC Tier 2 method, data on climate, soil types, 

land-use, and land management activity were used to classify 

land area to apply appropriate stock change factors. MLRAs 

formed the base spatial unit for mapping climate regions in 

the United States; each MLRA represents a geographic unit 

with relatively similar soils, climate, water resources, and 

land uses (NRCS 1981). MLRAs were classified into climate 

regions according to the IPCC categories using the PRISM 

climate database of Daly et al. (1994). 

Reference C stocks were estimated using the National 

Soil Survey Characterization Database (NRCS 1997) with 

cultivated cropland as the reference condition, rather than 

native vegetation as used in IPCC (2003, 2006). Changing the 

reference condition was necessary because soil measurements 

under agricultural management are much more common and 

easily identified in the National Soil Survey Characterization 

Database (NRCS 1997) than those that are not considered 

cultivated cropland. 

U.S.-specific stock change factors were derived from 

published literature to determine the impact of management 

practices on SOC storage, including changes in tillage, 

cropping rotations and intensification, and land-use change 

between cultivated and uncultivated conditions (Ogle et 

al. 2003, Ogle et al. 2006).33 U.S. factors associated with 

organic matter amendments were not estimated because of 

an insufficient number of studies to analyze those impacts. 

Instead, factors from IPCC (2003) were used to estimate the 

effect of those activities. Euliss and Gleason (2002) provided 

the data for computing the change in SOC storage resulting 

from restoration of wetland enrolled in the Conservation 

Reserve Program. 

Similar to the Tier 3 Century method, activity data 

were primarily based on the historical land-use/management 

33 Stock change factors have been derived from published literature to 

reflect changes in tillage, cropping rotations and intensification, land-use 

change between cultivated and uncultivated conditions, and drainage of 

organic soils.
Land Use, Land-Use Change, and Forestry 7-31

patterns recorded in the NRI. Each NRI point was classified 

by land use, soil type, climate region (using PRISM data, 

Daly et al. 1994) and management condition. Classification 

of cropland area by tillage practice was based on data 

from the Conservation Tillage Information Center (CTIC 

1998, Towery 2001) as described above. Activity data on 

wetland restoration of Conservation Reserve Program land 

were obtained from Euliss and Gleason (2002). Manure N 

amendments over the inventory time period were based on 

application rates and areas amended with manure N from 

Edmonds et al. (2003), in addition to the managed manure 

production data discussed in the previous methodology 

subsection on the Tier 3 analysis for mineral soils.

Combining information from these data sources, SOC 

stocks for mineral soils were estimated 50,000 times for 

1982, 1992, and 1997, using a Monte Carlo simulation 

approach and the probability distribution functions for 

U.S.-specific stock change factors, reference C stocks, and 

land-use activity data (Ogle et al. 2002, Ogle et al. 2003). 

The annual C flux for 1990 through 1992 was determined 

by calculating the average annual change in stocks between 

1982 and 1992; annual C flux for 1993 through 2006 was 

determined by calculating the average annual change in 

stocks between 1992 and 1997. 

Additional Mineral C Stock Change

Annual C flux estimates for mineral soils between 1990 

and 2006 were adjusted to account for additional C stock 

changes associated with gains or losses in soil C after 1997 

due to changes in Conservation Reserve Program enrollment. 

The change in enrollment acreage relative to 1997 was based 

on data from USDA-FSA (2007) for 1998 through 2006, 

and the differences in mineral soil areas were multiplied 

by 0.5 metric tons C per hectare per year to estimate the 

net effect on soil C stocks. The stock change rate is based 

on estimations using the IPCC method (see Annex 3.13 for 

further discussion).

Organic Soil Carbon Stock Changes

Annual C emissions from drained organic soils in 

Cropland Remaining Cropland were estimated using the Tier 

2 method provided in IPCC (2003, 2006), with U.S.-specific 

C loss rates (Ogle et al. 2003) rather than default IPCC rates. 

Similar to the Tier 2 analysis for mineral soils, the final 

estimates included a measure of uncertainty as determined 

from the Monte Carlo simulation with 50,000 iterations. 

Emissions were based on the 1992 and 1997 Cropland 

Remaining Cropland areas from the 1997 National Resources 

Inventory (USDA-NRCS 2000). The annual flux estimated 

for 1992 was applied to 1990 through 1992, and the annual 

flux estimated for 1997 was applied to 1993 through 2006.

Uncertainty

Uncertainty associated with the Cropland Remaining 

Cropland land-use category was addressed for changes in 

agricultural soil C stocks (including both mineral and organic 

soils). Uncertainty estimates are presented in Table 7-19 for 

mineral soil C stocks and organic soil C stocks disaggregated 

Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within Cropland Remaining Cropland

(Tg CO2 Eq. and Percent)

2006 Flux Estimatea Uncertainty Range Relative to Flux Estimatea

Source (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower 

Bound

Upper 

Bound

Lower 

Bound

Upper 

Bound

Mineral Soil C Stocks: Cropland Remaining Cropland, 

Tier 3 Inventory Methodology (64.0) (74.1) (53.5) -16% +16%

Mineral Soil C Stocks: Cropland Remaining Cropland, 

Tier 2 Inventory Methodology (3.0) (6.9) 0.8 -127% +128%

Mineral Soil C Stocks: Cropland Remaining Cropland 

(Change in CRP enrollment relative to 1997) (2.5) (3.7) (1.2) -50% +50%

Organic Soil C Stocks: Cropland Remaining Cropland, 

Tier 2 Inventory Methodology 27.7 15.8 36.9 -43% +33%

Combined Uncertainty for Flux associated with 

Agricultural Soil Carbon Stock Change in Cropland 

Remaining Cropland (41.8) (57.9) (27.3) -38% +35%

a

 Flux estimates based on soil C stock changes.
7-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

to the level of the inventory methodology employed (i.e., Tier 

2 and Tier 3). A combined uncertainty estimate for changes in 

soil C stocks occurring within Cropland Remaining Cropland

is also included. Uncertainty estimates from each component 

were combined using the error propagation equation in 

accordance with IPCC (2006). The combined uncertainty was 

calculated by taking the square root of the sum of the squares 

of the standard deviations of the uncertain quantities. More 

details on how the individual uncertainties were developed 

appear later in this section. The combined uncertainty for soil 

C stocks in Cropland Remaining Cropland ranged from 38 

percent below and 35 percent above the 2006 stock change 

estimate of -41.8 Tg CO2 Eq.

QA/QC and Verification

Quality control measures included checking input data, 

model scripts, and results to ensure data were properly 

handled through the inventory process. The manure 

amendment records were not recorded correctly in a subset 

of the Century model output; corrective actions were 

taken to resolve this error. As discussed in the uncertainty 

sections, results were compared to field measurements, and a 

statistical relationship was developed to assess uncertainties 

in the model’s predictive capability. The comparisons 

included over 40 long-term experiments, representing 

about 800 combinations of management treatments across 

all of the sites (Ogle et al. 2007). Inventory reporting forms 

and text were reviewed and revised as needed to correct 

transcription errors.

Recalculations Discussion

Two changes were implemented in the current Inventory 

that led to a change in the time series. First, there was a 

modification in the land-use classification. The classification 

is based on the land use in a specific year of the Inventory 

and the previous 20 years. However, in the 1990 through 

2005 Inventory, each point was only classified once based 

on the entire NRI time series of the land-use history. This 

approach led to incorrect classifications for the early 1990s. 

For example, a NRI point may have been cropland in 1982, 

1987 and 1992, but converted to grassland in 1997. In the 

previous Inventory, the NRI point would be classified as Land 

Converted to Grassland for the entire inventory from 1990 

through 2005. This is incorrect for the early 1990s because 

the point was Cropland Remaining Cropland during those 

years. Second, the time series for manure N between 1990 

and 2006, which was used to adjust manure applications 

relative to 1997, was based on manure N available for 

application rather than manure N production. Overall, the 

recalculations resulted in an average annual decrease of 1.9 

Tg CO2 Eq. for the period 1990 through 2005, compared to 

the previous Inventory.

Planned Improvements 

Several improvements are planned for the agricultural 

soil C inventory. The first improvement is to incorporate 

new land-use and management activity data from the NRI. 

In the current Inventory, NRI data only provide land-use 

and management statistics through 1997, but it is anticipated 

that new statistics will be released in the coming year for 

2000 through 2003. The new data will greatly improve the 

accuracy of land-use and management influences on soil C 

in the latter part of the time series.

The second improvement is to incorporate additional 

crops into the Tier 3 approach. Currently, crops such as 

vegetables, rice, perennial and horticultural crops have not 

been fully implemented in the Century model application. 

However, efforts are currently underway to further develop 

the model application for simulating soil C dynamics in land 

managed for production of these crops. This improvement is 

expected to reduce uncertainties in the inventory results.

The third improvement is to incorporate remote sensing 

in the analysis for estimation of crop and forage production. 

Specifically, the Enhanced Vegetation Index (EVI) product 

that is derived from MODIS satellite imagery is being used 

to refine the production estimation for the Tier 3 assessment 

framework. EVI reflects changes in plant “greenness” over 

the growing season and can be used to compute production 

based on the light use efficiency of the crop or forage 

(Potter et al. 1993). In the current framework, production is 

simulated based on the weather data, soil characteristics, and 
Land Use, Land-Use Change, and Forestry 7-33

the genetic potential of the crop. While this method produces 

reasonable results, remote sensing can be used to refine the 

productivity estimates and reduce biases in crop production 

and subsequent C input to soil systems. It is anticipated 

that precision in the Tier 3 assessment framework will be 

increased by 25 percent or more with the new method.

The fourth improvement is to develop an automated 

quality control system to evaluate the results from Century 

model simulations. Currently, there are over 14 million 

simulations, and it is not possible to manually review each 

simulation. Results are aggregated and evaluated at larger 

scales such as MLRAs and States. QA/QC at these larger 

scales may not uncover errors at the scale of individual 

NRI points, which is the scale at which the Century model 

is used to simulate soil C dynamics. An automated system 

would greatly improve QA/QC, performing checks on the 

results from each simulation and identifying errors for 

further refinements.

The final improvement is to further develop the 

uncertainty analysis for the Tier 3 method by addressing the 

uncertainty inherent in the Century model results for other 

agricultural land (i.e., Grassland Remaining Grassland, Land 

Converted to Grassland, and Land Converted to Cropland). 

In addition, uncertainties need to be addressed in the 

simulation of soil C stocks for the pre-NRI time period (i.e., 

before 1979). In the current analysis, inventory development 

focused on uncertainties in the last two decades because the 

management activity during the most recent time periods 

will likely have the largest impact on current trends in soil C 

storage. However, legacy effects of past management can also 

have a significant effect on current C stock trends, as well as 

trajectories of those C stocks in the near future. Therefore, 

a planned improvement is to revise the Inventory to address 

uncertainties in management activity prior to 1979, providing 

a more rigorous accounting of uncertainties associated with 

the Tier 3 method.

CO2 Emissions from Agricultural 

Liming

IPCC (2006) recommends reporting CO2 emissions from 

lime additions (in the form of crushed limestone (CaCO3) 

and dolomite (CaMg(CO3)2) to agricultural soils. Limestone 

and dolomite are added by land managers to ameliorate 

acidification. When these compounds come in contact with 

acid soils, they degrade, thereby generating CO2. The rate 

and ultimate magnitude of degradation of applied limestone 

and dolomite depends on the soil conditions, climate regime, 

and the type of mineral applied. Emissions from liming have 

fluctuated over the past sixteen years, ranging from 3.9 Tg 

CO2 Eq. to 5.0 Tg CO2 Eq. In 2006, liming of agricultural 

soils in the United States resulted in emissions of 4.4 Tg CO2

Eq. (1.2 Tg C), representing about a 6 percent decrease in 

emissions since 1990 (see Table 7-20 and Table 7-21).

Table 7-20: Emissions from Liming of Agricultural Soils (Tg CO2 Eq.)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Liming of Soilsa 4.7 4.4 4.3 4.4 5.0 4.6 3.9 4.3 4.4

Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. a

 Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.

Table 7-21: Emissions from Liming of Agricultural Soils (Tg C)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Liming of Soilsa 1.3 1.2 1.2 1.2 1.4 1.2 1.1 1.2 1.2

Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. a

 Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.
7-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Methodology

CO2 emissions from degradation of limestone and 

dolomite applied to agricultural soils were estimated using 

a Tier 2 methodology consistent with IPCC (2006). The 

annual amounts of limestone and dolomite applied (see Table 

7-22) were multiplied by CO2 emission factors from West 

and McBride (2005). These emission factors (0.059 metric 

ton C/metric ton limestone, 0.064 metric ton C/metric ton 

dolomite) are lower than the IPCC default emission factors, 

because they account for the portion of agricultural lime that 

may leach through the soil and travel by rivers to the ocean 

(West and McBride 2005). The annual application rates of 

limestone and dolomite were derived from estimates and 

industry statistics provided in the Minerals Yearbook and 

Mineral Industry Surveys (Tepordei 1993, 1994, 1995, 1996, 

1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006; 

Willett 2007; USGS 2007). To develop these data, the U.S. 

Geological Survey (USGS; U.S. Bureau of Mines prior to 

1997) obtained production and use information by surveying 

crushed stone manufacturers. Because some manufacturers 

were reluctant to provide information, the estimates of total 

crushed limestone and dolomite production and use were 

divided into three components: (1) production by end-use, 

as reported by manufacturers (i.e., “specified” production), 

(2) production reported by manufacturers without end-uses 

specified (i.e., “unspecified” production), and (3) estimated 

additional production by manufacturers who did not respond 

to the survey (i.e., “estimated” production).

The “unspecified” and “estimated” amounts of crushed 

limestone and dolomite applied to agricultural soils were 

calculated by multiplying the percentage of total “specified” 

limestone and dolomite production applied to agricultural 

soils by the total amounts of “unspecified” and “estimated” 

limestone and dolomite production. In other words, the 

proportion of total “unspecified” and “estimated” crushed 

limestone and dolomite that was applied to agricultural 

soils (as opposed to other uses of the stone) was assumed 

to be proportionate to the amount of “specified” crushed 

limestone and dolomite that was applied to agricultural 

soils. In addition, data were not available for 1990, 1992, 

and 2006 on the fractions of total crushed stone production 

that were limestone and dolomite, and on the fractions of 

limestone and dolomite production that were applied to soils. 

To estimate the 1990 and 1992 data, a set of average fractions 

were calculated using the 1991 and 1993 data. These average 

fractions were applied to the quantity of “total crushed stone 

produced or used” reported for 1990 and 1992 in the 1994 

Minerals Yearbook (Tepordei 1996). To estimate 2006 data, 

the previous year’s fractions were applied to a 2006 estimate 

of total crushed stone presented in the USGS Mineral 

Industry Surveys: Crushed Stone and Sand and Gravel in 

the First Quarter of 2007 (USGS 2007).

The primary source for limestone and dolomite activity 

data is the Minerals Yearbook, published by the Bureau of 

Mines through 1994 and by the USGS from 1995 to the 

present. In 1994, the “Crushed Stone” chapter in the Minerals 

Yearbook began rounding (to the nearest thousand) quantities 

for total crushed stone produced or used. It then reported 

revised (rounded) quantities for each of the years from 1990 

to 1993. In order to minimize the inconsistencies in the 

activity data, these revised production numbers have been 

used in all of the subsequent calculations. Since limestone 

and dolomite activity data are also available at the state level, 

the national-level estimates reported here were broken out by 

state for the first time this year, but are not reported here. 

Uncertainty

Uncertainty regarding limestone and dolomite activity 

data inputs was estimated at ±15 percent and assumed to 

be uniformly distributed around the inventory estimate 

(Tepordei 2003b). Analysis of the uncertainty associated with 

the emission factors included the following: the fraction of 

agricultural lime dissolved by nitric acid versus the fraction 

that reacts with carbonic acid, and the portion of bicarbonate 

that leaches through the soil and is transported to the ocean. 

Uncertainty regarding the time associated with leaching and 

Table 7-22: Applied Minerals (Million Metric Tons)

Mineral 1990 1995 2000 2001 2002 2003 2004 2005 2006

Limestone 19.01 17.30 15.86 16.10 20.45 18.71 15.50 18.09 18.20

Dolomite 2.36 2.77 3.81 3.95 2.35 2.25 2.33 1.85 1.87

Note: These numbers represent amounts applied to all agricultural land, including Land Converted to Cropland, Grassland Remaining Grassland, and Land 

Converted to Grassland.
Land Use, Land-Use Change, and Forestry 7-35

transport was not accounted for, but should not change the 

uncertainty associated with CO2 emissions (West 2005). The 

uncertainty associated with the fraction of agricultural lime 

dissolved by nitric acid and the portion of bicarbonate that 

leaches through the soil were each modeled as a smoothed 

triangular distribution between ranges of 0 percent to 100 

percent. The uncertainty surrounding these two components 

largely drives the overall uncertainty estimates reported 

below. More information on the uncertainty estimates 

for Liming of Agricultural Soils is contained within the 

Uncertainty Annex.

A Monte Carlo (Tier 2) uncertainty analysis was applied 

to estimate the uncertainty of CO2 emissions from liming. 

The results of the Tier 2 quantitative uncertainty analysis are 

summarized in Table 7-23. CO2 emissions from Liming of 

Agricultural Soils in 2006 were estimated to be between 0.2 

and 8.5 Tg CO2 Eq. at the 95 percent confidence level. This 

indicates a range of 95 percent below to 95 percent above 

the 2006 emission estimate of 4.4 Tg CO2 Eq.

QA/QC and Verification

A QA/QC analysis was performed for data gathering and 

input, documentation, and calculation. The QA/QC analysis 

did not reveal any inaccuracies or incorrect input values.

Recalculations Discussion

Several adjustments were made in the current Inventory 

to improve the results. The quantity of applied minerals 

reported in the previous Inventory for 2005 has been revised. 

Consequently, the reported emissions resulting from liming 

in 2005 have also changed. In the previous Inventory, to 

estimate 2005 data, the previous year’s fractions were 

applied to a 2005 estimate of total crushed stone presented 

in the USGS Mineral Industry Surveys: Crushed Stone and 

Sand and Gravel in the First Quarter of 2006 (USGS 2006). 

Since publication of the previous Inventory, the Minerals 

Yearbook has published actual quantities of crushed stone 

sold or used by producers in the United States in 2005. These 

values have replaced those used in the previous Inventory 

to calculate the quantity of minerals applied to soil and the 

emissions from liming. 

CO2 Emissions from Urea Fertilization

The use of urea (CO(NH2)2) as fertilizer leads to 

emissions of CO2 that was fixed during the industrial 

production process. Urea in the presence of water and urease 

enzymes is converted into ammonium (NH4

+), hydroxyl 

ion (OH-), and bicarbonate (HCO3

-

). The bicarbonate then 

Table 7-23: Tier 2 Quantitative Uncertainty Estimates for CO2 Emissions from Liming of Agricultural Soils 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Liming of Agricultural Soilsb CO2 4.4 0.2 8.5 -95% +95%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

b

 Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.

Table 7-24: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg CO2 Eq.)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Urea Fertilizationa 2.4 2.7 3.2 3.4 3.6 3.7 3.7 3.5 3.6

Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. a

 Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.
7-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

evolves into CO2 and water. Emissions from urea fertilization 

in the United States totaled 3.6 Tg CO2 Eq. (1.0 Tg C) in 

2006 (Table 7-24 and Table 7-25). Emissions from urea 

fertilization have fluctuated over the past sixteen years, 

ranging from 2.3 Tg CO2 Eq. to 3.7 Tg CO2 Eq.

Methodology

Carbon dioxide emissions from the application of urea 

to agricultural soils were estimated using the IPCC (2006) 

Tier 1 methodology. The annual amounts of urea fertilizer 

applied (see Table 7-26) were derived from state-level 

fertilizer sales data provided in Commercial Fertilizers

(TVA 1991, 1992, 1993, 1994; AAPFCO 1995, 1996, 1997, 

1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006) 

and were multiplied by the default IPCC (2006) emission 

factor of 0.20, which is equal to the C content of urea on 

an atomic weight basis. Because fertilizer sales data are 

reported in fertilizer years (July through June), a calculation 

was performed to convert the data to calendar years (January 

through December). According to historic monthly fertilizer 

use data (TVA 1992b), 65 percent of total fertilizer used in 

any fertilizer year is applied between January through June 

of that calendar year, and 35 percent of total fertilizer used in 

any fertilizer year is applied between July through December 

of the previous calendar year. Fertilizer use data for the 2007 

fertilizer year were not available in time for publication, so 

July through December 2006 fertilizer use was estimated 

by calculating the percent change (increase or decrease) in 

fertilizer use from January through June 2005 to July through 

December 2005. This percent change was then multiplied by 

the January through June 2006 data to estimate July through 

December 2006 fertilizer use. State-level estimates of CO2

emissions from the application of urea to agricultural soils 

were summed to estimate total emissions for the entire 

United States.

Uncertainty

Uncertainty estimates are presented in Table 7-27 

for Urea Fertilization. A Tier 2 Monte Carlo analysis was 

completed. The largest source of uncertainty was the default 

emission factor, which assumes that 100 percent of the C 

applied to soils is ultimately emitted into the environment 

as CO2. This factor does not incorporate the possibility that 

some of the C may be retained in the soil. The emission 

estimate is, thus, likely to be high. In addition, each urea 

consumption data point has an associated uncertainty. Urea 

for non-fertilizer use may be included in consumption totals; 

it was determined through personal communication with 

Table 7-25: CO2 Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Urea Fertilizationa 0.7 0.7 0.9 0.9 1.0 1.0 1.0 1.0 1.0

Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. a

 Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.

Table 7-27: Quantitative Uncertainty Estimates for CO2 Emissions from Urea Fertilization (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Urea Fertilization CO2 3.6 2.1 3.8 -43% +3%

Note: These numbers represent amounts applied to all agricultural land, including Land Converted to Cropland, Grassland Remaining Grassland, and Land 

Converted to Grassland. a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

Table 7-26: Applied Urea (Million Metric Tons)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

Urea Fertilizationa 3.30 3.62 4.38 4.66 4.87 5.02 4.98 4.78 4.96

Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. a

 Also includes emissions from urea fertilization on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland.
Land Use, Land-Use Change, and Forestry 7-37

Fertilizer Regulatory Program Coordinator David L. Terry 

(2007), however, that amount is most likely very small. 

Lastly, there is uncertainty surrounding the assumptions 

behind the calculation that converts fertilizer years to 

calendar years. CO2 emissions from Urea Fertilization of 

Agricultural Soils in 2006 were estimated to be between 2.1 

and 3.8 Tg CO2 Eq. at the 95 percent confidence level. This 

indicates a range of 43 percent below to 3 percent above the 

2006 emission estimate of 3.6 Tg CO2 Eq.

QA/QC and Verification

A QA/QC analysis was performed for data gathering 

and input, documentation, and calculation. Minor errors 

were found in these steps and corrective actions were taken, 

including a data point that was incorrectly transcribed. 

Inventory reporting forms and text were reviewed and revised 

as needed to correct transcription errors.

Recalculations Discussion

Emissions from Urea production and application were 

previously included in the Industrial Processes chapter. That 

chapter has been modified to only include emissions from 

Urea production.

Planned Improvements 

Several improvements are planned for the urea 

fertilization inventory. The first improvement is to investigate 

using a Tier 2 or Tier 3 approach, which would utilize 

country-specific information to estimate a more precise 

emission factor. The second improvement is to investigate 

and quantify, if possible, the amount of urea that is currently 

included in urea consumption totals, but is used for nonagricultural practices such as deicing.

7.5. Land Converted to Cropland

(IPCC Source Category 5B2)

Land Converted to Cropland includes all cropland in 

an inventory year that had been another land use in the past 

20 years34 according to the USDA NRI land use survey 

(USDA-NRCS 2000). Consequently, the area considered 

in Land Converted to Cropland changes through time with 

land-use change. Lands are retained in this category for 

20 years as recommended by the IPCC guidelines (IPCC 

2006) unless there is another land-use change. Background 

on agricultural C stock changes is provided in Cropland 

Remaining Cropland and will only be summarized here for 

34 NRI points were classified according to land-use history records starting 

in 1982 when the NRI survey began. Therefore, the classification was based 

on less than 20 years of recorded land-use history for the time series from 

1982 to 2001.

Table 7-28: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg CO2 Eq.)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Mineral Soils 12.3 6.7 6.7 6.7 6.7 6.7 6.7 6.7 6.7

Organic Soils 2.4 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2.6 

Total Net Flux 14.7 9.4 9.4 9.4 9.4 9.4 9.4 9.4 9.4

Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. 

Totals may not sum due to independent rounding.

Table 7-29: Net CO2 Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Mineral Soils 3.4 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8

Organic Soils 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7

Total Net Flux 4.0 2.6 2.6 2.6 2.6 2.6 2.6 2.6 2.6

Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on historical data only. 

Totals may not sum due to independent rounding.
7-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Land Converted to Cropland. Soils are the largest pool of C 

in agricultural land, and also have the greatest potential for 

storage or release of C, because biomass and dead organic 

matter C pools are relatively small and ephemeral compared 

with soils. The IPCC/UNEP/OECD/IEA (1997) and the IPCC 

(2003, 2006) recommend reporting changes in soil organic 

C stocks due to: (1) agricultural land-use and management 

activities on mineral soils, and (2) agricultural land-use and 

management activities on organic soils.35

Land use and management of mineral soils in Land 

Converted to Cropland led to losses of soil C during the early 

1990s but losses declined slightly through the latter part of 

the time series (Table 7-28 and Table 7-29). The total rate 

of change in soil C stocks was 9.4 Tg CO2 Eq. (2.6 Tg C) in 

2006. Emissions from mineral soils were estimated at 6.7 Tg 

CO2 Eq. (1.8 Tg C) in 2006, while drainage and cultivation 

of organic soils led to annual losses of 2.6 Tg CO2 Eq. (0.7 

Tg C) in 2006.

The spatial variability in annual CO2 flux associated 

with C stock changes in mineral and organic soils for Land 

Converted to Cropland is displayed in Figure 7-7 and Figure 

7-8. While a large portion of the United States had net 

losses in soil C for Land Converted to Cropland, there were 

some notable areas with sequestration in the Intermountain 

West and central United States. These areas were gaining 

C following conversion, because croplands were irrigated 

or receiving higher fertilizer inputs relative to the previous 

land use. Emissions from organic soils were largest in 

California, Florida and the upper Midwest, which coincided 

with largest concentrations of cultivated organic soils in the 

United States.

Methodology 

The following section includes a brief description of the 

methodology used to estimate changes in soil C stocks due to 

agricultural land-use and management activities on mineral 

and organic soils for Land Converted to Cropland. 

Soil C stock changes were estimated for Land Converted 

to Cropland according to land-use histories recorded in the 

USDA NRI survey (USDA-NRCS 2000). Land use and some 

management information (e.g., crop type, soil attributes, and 

irrigation) were collected for each NRI point on a 5-year 

35CO2 emissions associated with liming are also estimated but included in 

a separate section of the report.

cycle beginning in 1982, and were subdivided into four 

inventory time periods, 1980 through 1984, 1985 through 

1989, 1990 through 1994 and 1995 through 2000. NRI 

points were classified as Land Converted to Cropland for 

an inventory time period (e.g., 1990 through 1994 and 1995 

through 2000) if the land use was cropland in the respective 

inventory time period but had been another use during the 

previous 20 years.36 Cropland includes all land used to 

produce food or fiber, as well as forage that is harvested and 

used as feed (e.g., hay and silage). Further elaboration on 

the methodologies and data used to estimate stock changes 

for mineral and organic soils are provided in the Cropland 

Remaining Cropland section and Annex 3.13.

Mineral Soil Carbon Stock Changes

A Tier 3 model-based approach was used to estimate 

C stock changes for soils on Land Converted to Cropland

used to produce a majority of all crops. Soil C stock changes 

on the remaining soils were estimated with the IPCC Tier 2 

method (Ogle et al. 2003), including land used to produce 

vegetable, tobacco, perennial/horticultural crops, and rice; 

land on very gravelly, cobbly or shaley soils (greater than 

35 percent by volume); and land converted from forest or 

federal ownership.37

Tier 3 Approach

Mineral SOC stocks and stock changes were estimated 

using the Century biogeochemical model for the Tier 3 

methods. National estimates were obtained by using the 

model to simulate historical land-use change patterns as 

recorded in the USDA National Resources Inventory (USDANRCS 2000). The methods used for Land Converted to 

Cropland are the same as those described in the Tier 3 portion 

of Cropland Remaining Cropland Section for mineral soils 

(see Cropland Remaining Cropland Tier 3 methods section 

for additional information).

Tier 2 Approach

For the mineral soils not included in the Tier 3 analysis, 

SOC stock changes were estimated using a Tier 2 Approach 

36 NRI points were classified according to land-use history records starting 

in 1982 when the NRI survey began. Therefore, the classification was based 

on less than 20 years of recorded land-use history for the time series from 

1982 to 2001.

37 Federal land is not a land use, but rather an ownership designation that 

is treated as forest or nominal grassland for purposes of these calculations. 

The specific use for federal lands is not identified in the NRI survey 

(USDA-NRCS 2000).
Land Use, Land-Use Change, and Forestry 7-39

Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States, 1993–2006 

Land Converted to Cropland

Figure 7-7

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.

Tg CO2 Eq./year

-0.5 to -0.1

-0.1 to 0

> 0

Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States, 1993–2006 

Land Converted to Cropland

Figure 7-8

Note: Values greater than zero represent emissions.

Tg CO2 Eq./year

No organic soils

0 to 0.1

0.1 to 0.5

0.5 to 1
7-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

for Land Converted to Cropland as described in the Tier 2 

portion of Cropland Remaining Cropland Section for mineral 

soils (see Cropland Remaining Cropland Tier 2 methods 

section for additional information).

Organic Soil Carbon Stock Changes

Annual C emissions from drained organic soils in Land 

Converted to Cropland were estimated using the Tier 2 

method provided in IPCC (2003, 2006), with U.S.-specific 

C loss rates (Ogle et al. 2003) rather than default IPCC rates. 

The final estimates included a measure of uncertainty as 

determined from the Monte Carlo simulation with 50,000 

iterations. Emissions were based on the 1992 and 1997 

Land Converted to Cropland areas from the 1997 National 

Resources Inventory (USDA-NRCS 2000). The annual 

flux estimated for 1992 was applied to 1990 through 1992, 

and the annual flux estimated for 1997 was applied to 1993 

through 2006.

Uncertainty

Uncertainty analysis for mineral soil C stock changes 

using the Tier 3 and Tier 2 approaches were based on the 

same method described for Cropland Remaining Cropland, 

except that the uncertainty inherent in the structure of the 

Century model was not addressed. The uncertainty for 

annual C emission estimates from drained organic soils 

in Land Converted to Cropland was estimated using the 

Tier 2 approach, as described in the Cropland Remaining 

Cropland Section.

Uncertainty estimates are presented in Table 7-30 for 

each subsource (i.e., mineral soil C stocks and organic 

soil C stocks) disaggregated to the level of the inventory 

methodology employed (i.e., Tier 2 and Tier 3). A combined 

uncertainty estimate for changes in agricultural soil C 

stocks occurring within Land Converted to Cropland is also 

included. Uncertainty estimates from each component were 

combined using the error propagation equation in accordance 

with IPCC (2006), i.e., by taking the square root of the sum 

of the squares of the standard deviations of the uncertain 

quantities. The combined uncertainty for soil C stocks in 

Land Converted to Cropland was estimated to be 25 percent 

below and 22 percent above the inventory estimate of 9.4 

Tg CO2 Eq.

QA/QC and Verification

See QA/QC and Verification Section under Cropland 

Remaining Cropland.

Recalculations Discussion

Two changes were implemented in the current 

Inventory that led to a change in the time series. First, 

there was a modification in the land-use classification. The 

classification is based on the land use in a specific year of 

the Inventory and the previous 20 years. However, in the 

Table 7-30: Quantitative Uncertainty Estimatesa for C Stock Changes occurring within Land Converted to Cropland

(Tg CO2 Eq. and Percent)

2006 Flux Estimatea Uncertainty Range Relative to Flux Estimatea

Source (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower 

Bound

Upper 

Bound

Lower 

Bound

Upper 

Bound

Mineral Soil C Stocks: Land Converted to Cropland, 

Tier 3 Inventory Methodology 2.6 2.0 3.1 -21% +21%

Mineral Soil C Stocks: Land Converted to Cropland, 

Tier 2 Inventory Methodology 4.1 2.3 5.8 -44% +41%

Organic Soil C Stocks: Land Converted to Cropland, 

Tier 2 Inventory Methodology 2.6 1.2 3.7 -53% +41%

Combined Uncertainty for Flux associated with Soil 

Carbon Stock Change in Land Converted to Cropland 9.4 7.0 11.4 -25% +22%

a

 Flux estimates based on soil C stock changes.
Land Use, Land-Use Change, and Forestry 7-41

1990 through 2005 Inventory, each point was only classified 

once based on the entire NRI time series of the land-use 

history. This approach led to incorrect classifications for 

the early 1990s. For example, a NRI point may have been 

grassland in 1982, 1987 and 1992, but converted to cropland 

in 1997. In the previous Inventory, the NRI point would 

be classified as Land Converted to Cropland for the entire 

Inventory from 1990 through 2005. This is incorrect for the 

early 1990s because the point was Grassland Remaining 

Grassland during those years. Second, the time series for 

manure N between 1990 through 2006, which was used 

to adjust manure applications relative to 1997, was based 

on manure N available for application rather than manure 

N production. Overall, these recalculations resulted in an 

average annual increase in emissions of 3.3 Tg CO2 Eq. for 

soil C stock changes in Land Converted to Cropland over 

the time series from 1990 through 2005, compared to the 

previous Inventory. 

Planned Improvements 

The empirically-based uncertainty estimator 

described in the Cropland Remaining Cropland section 

for the Tier 3 approach has not been developed to 

estimate uncertainties related to the structure of Century 

model for Land Converted to Cropland, but this is a 

planned improvement. This improvement will produce 

a more rigorous assessment of uncertainty. See Planned 

Improvements section under Cropland Remaining 

Cropland for additional planned improvements.

7.6. Grassland Remaining Grassland

(IPCC Source Category 5C1) 

Grassland Remaining Grassland includes all grassland 

in an inventory year that had been grassland for the previous 

20 years38 according to the USDA NRI land use survey 

(USDA-NRCS 2000). Consequently, the area considered 

38 NRI points were classified according to land-use history records starting 

in 1982 when the NRI survey began. Therefore, the classification was based 

on less than 20 years of recorded land-use history for the time series from 

1982 to 2001.

in Grassland Remaining Grassland changes through time 

with land-use change. Background on agricultural C stock 

changes is provided in the Cropland Remaining Cropland

section and will only be summarized here for Grassland 

Remaining Grassland. Soils are the largest pool of C in 

agricultural land, and also have the greatest potential for 

storage or release of C, because biomass and dead organic 

matter C pools are relatively small and ephemeral compared 

to soils. The IPCC/UNEP/OECD/IEA (1997) and IPCC 

(2003, 2006) recommend reporting changes in soil organic 

C stocks due to: (1) agricultural land-use and management 

activities on mineral soils, and (2) agricultural land-use and 

management activities on organic soils.39

Land use and management of mineral soils in Grassland 

Remaining Grassland increased soil C during the early 

1990s, but this trend was reversed over the decade, with small 

losses of C prevailing during the latter part of the time series. 

Organic soils lost about the same amount of C in each year of 

the Inventory. Due to the pattern for mineral soils, the overall 

trend shifted from small increases in soil C during 1990 to 

decreases in soil C during the latter years of the Inventory, 

estimated at 16.2 Tg CO2 Eq. (4.4 Tg C) in 2006 (Table 7-31 

and Table 7-32). Overall, flux rates changed by 18.1 Tg CO2

Eq. (4.9 Tg C) from 1990 to 2006. 

The spatial variability in annual CO2 flux associated with 

C stock changes in mineral and organic soils is displayed 

in Figure 7-9 and Figure 7-10. Grassland is losing soil 

organic C in the United States largely due to droughts that 

are causing small losses of C on a per hectare basis, but are 

occurring over a large land base. In areas with net gains in 

soil organic C, sequestration was driven by irrigation and 

seeding legumes. Similar to Cropland Remaining Cropland, 

emission rates from drained organic soils were highest along 

the southeastern coastal region, in the northeast central 

United States surrounding the Great Lakes, and along the 

central and northern portions of the West Coast.

39CO2 emissions associated with liming are also estimated but included in 

a separate section of the report.
7-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Methodology 

The following section includes a brief description of the 

methodology used to estimate changes in soil C stocks due to 

agricultural land-use and management activities on mineral 

and organic soils for Grassland Remaining Grassland.

Soil C stock changes were estimated for Grassland 

Remaining Grassland according to land-use histories recorded 

in the USDA NRI survey (USDA-NRCS 2000). Land-use 

and some management information (e.g., irrigation, legume 

pastures) were collected for each NRI point on a 5-year 

cycle beginning in 1982, 1980 through 1984, 1985 through 

Table 7-31: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg CO2 Eq.)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Mineral Soils (5.7) 12.9 12.8 12.7 12.7 12.7 12.6 12.6 12.5 

Organic Soils 3.9 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7

Total Net Flux (1.9) 16.6 16.4 16.4 16.4 16.4 16.3 16.3 16.2 

Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are 

based on historical data only. Totals may not sum due to independent rounding.

Table 7-32: Net CO2 Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Mineral Soils (1.6) 3.5 3.5 3.5 3.5 3.5 3.4 3.4 3.4 

Organic Soils 1.1 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0

Total Net Flux (0.5) 4.5 4.5 4.5 4.5 4.5 4.5 4.4 4.4 

Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are 

based on historical data only. Totals may not sum due to independent rounding.

Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States, 1993–2006 

Grassland Remaining Grassland

Figure 7-9

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.

Tg CO2 Eq./year

-1 to -0.5

-0.5 to -0.1

-0.1 to 0

> 0
Land Use, Land-Use Change, and Forestry 7-43

1989, 1990 through 1994 and 1995 through 2000. NRI points 

were classified as Grassland Remaining Grassland for an 

inventory time period (e.g., 1990 through 1994 and 1995 

through 2000) if the land use was grassland in the inventory 

time period and had been grassland for the previous 20 

years.40 Grassland includes pasture and rangeland used for 

grass forage production, where the primary use is livestock 

grazing. Rangelands are typically extensive areas of native 

grassland that are not intensively managed, while pastures 

are often seeded grassland, possibly following tree removal, 

that may or may not be improved with practices such as 

irrigation and interseeding legumes. Further elaboration on 

the methodologies and data used to estimate stock changes 

from mineral and organic soils are provided in the Cropland 

Remaining Cropland section and Annex 3.13.

Mineral Soil Carbon Stock Changes 

An IPCC Tier 3 model-based approach was used to 

estimate C stock changes for most mineral soils in Grassland 

40 NRI points were classified according to land-use history records starting 

in 1982 when the NRI survey began. Therefore, the classification was based 

on less than 20 years of recorded land-use history for the time series from 

1982 to 2001.

Remaining Grassland. The C stock changes for the remaining 

soils were estimated with an IPCC Tier 2 method (Ogle et 

al. 2003), including gravelly, cobbly or shaley soils (greater 

than 35 percent by volume) and additional stock changes 

associated with sewage sludge amendments. 

Tier 3 Approach

Mineral soil organic C stocks and stock changes for 

Grassland Remaining Grassland were estimated using the 

Century biogeochemical model, as described in Cropland 

Remaining Cropland. Historical land-use and management 

patterns were used in the Century simulations as recorded 

in the USDA National Resources Inventory (NRI) survey, 

with supplemental information on fertilizer use and rates 

from the USDA Economic Research Service Cropping 

Practices Survey (ERS 1997) and National Agricultural 

Statistics Service (NASS 1992, 1999, 2004). Frequency 

and rates of manure application to grassland during 1997 

were estimated from data compiled by the USDA Natural 

Resources Conservation Service (Edmonds, et al. 2003), 

and then adjusted using county-level estimates of manure 

available for application in other years of the Inventory. 

Specifically, county-scale ratios of manure available in other 

Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States, 1993–2006 

Grassland Remaining Grassland

Figure 7-10

Note: Values greater than zero represent emissions.

Tg CO2 Eq./year

No organic soils

0 to 0.1

0.1 to 0.5

0.5 to 1

1 to 2
7-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

years relative to 1997 were used to adjust the area amended 

with manure (see Annex 3.13 for further details). Greater 

availability of managed manure N relative to 1997 was, 

thus, assumed to increase the area amended with manure, 

while reduced availability of manure N relative to 1997 was 

assumed to reduce the amended area. 

The amount of manure produced by each livestock 

type was calculated for managed and unmanaged waste 

management systems. Managed systems include feedlots or 

other housing (which requires manure to be collected and 

managed); unmanaged systems include daily spread, pasture, 

range, and paddock systems. Annual animal population data 

for all livestock types, except horses and goats, were obtained 

for all years from the U.S. Department of AgricultureNational Agricultural Statistics Service. Population data 

used for cattle, swine, and sheep were downloaded from the 

USDA NASS Population Estimates Database (USDA 2007a). 

Poultry population data were obtained from USDA NASS 

reports (USDA 1995a, 1995b, 1998a, 1999, 2004a, 2004b, 

2006a, 2006b, 2007b, 2007c). Horse population data were 

obtained from the FAOSTAT database (FAO 2007). Goat 

population data for 1992, 1997, and 2002 were obtained 

from the Census of Agriculture (USDA 2005); these data 

were interpolated and extrapolated to derive estimates for 

the other years. Information regarding poultry turnover (i.e., 

slaughter) rate was obtained from state Natural Resource 

Conservation Service personnel (Lange 2000). Additional 

population data for different farm size categories for dairy 

and swine were obtained from the 1992, 1997, and 2002 

Census of Agriculture (USDA 2005).

Pasture/Range/Paddock (PRP) manure N deposition 

was estimated internally in the Century model, as part 

of the grassland system simulations (i.e., PRP manure 

deposition was not an external input into the model). Manure 

amendments were an input to the Century Model based on 

manure N available for application from all other managed 

or unmanaged systems. Data on the county-level N available 

for application were estimated for managed systems based on 

the total amount of N excreted in manure minus N losses and 

including the addition of N from bedding materials. Nitrogen 

losses include direct nitrous oxide emissions, volatilization 

of ammonia and NOx, and runoff and leaching. More 

information on these losses is available in the description of 

the Manure Management source category. Animal-specific 

bedding factors were set equal to IPCC default factors (IPCC 

2006). For unmanaged systems, it is assumed that no N 

losses or additions occur. See the Tier 3 methods in Cropland 

Remaining Cropland section for additional discussion on the 

Tier 3 methodology for mineral soils.

Tier 2 Approach

The Tier 2 approach is based on the same methods 

described in the Tier 2 portion of Cropland Remaining 

Cropland Section for mineral soils (see Cropland 

Remaining Cropland Tier 2 methods section for additional 

information).

Additional Mineral C Stock Change Calculations

Annual C flux estimates for mineral soils between 1990 

and 2006 were adjusted to account for additional C stock 

changes associated with sewage sludge amendments using 

a Tier 2 method. Estimates of the amounts of sewage sludge 

N applied to agricultural land were derived from national 

data on sewage sludge generation, disposition, and nitrogen 

content. Total sewage sludge generation data for 1988, 1996, 

and 1998, in dry mass units, were obtained from an EPA 

report (EPA 1999) and estimates for 2004 were obtained 

from an independent national biosolids survey (NEBRA 

2007). These values were linearly interpolated to estimate 

values for the intervening years. N application rates from 

Kellogg et al. (2000) were used to determine the amount of 

area receiving sludge amendments. Although sewage sludge 

can be added to land managed for other land uses, it was 

assumed that agricultural amendments occur in grassland. 

Cropland is assumed to rarely be amended with sewage 

sludge due to the high metal content and other pollutants 

in human waste. The soil C storage rate was estimated at 

0.38 metric tons C per hectare per year for sewage sludge 

amendments to grassland. The stock change rate is based on 

country-specific factors and the IPCC default method (see 

Annex 3.13 for further discussion).

Organic Soil Carbon Stock Changes

Annual C emissions from drained organic soils in 

Grassland Remaining Grassland were estimated using the 

Tier 2 method provided in IPCC (2003, 2006), which utilizes 

U.S.-specific C loss rates (Ogle et al. 2003) rather than 

default IPCC rates. Emissions were based on the 1992 and 

1997 Grassland Remaining Grassland areas from the 1997 
Land Use, Land-Use Change, and Forestry 7-45

National Resources Inventory (USDA-NRCS 2000). The 

annual flux estimated for 1992 was applied to 1990 through 

1992, and the annual flux estimated for 1997 was applied to 

1993 through 2006.

Uncertainty

Uncertainty estimates are presented in Table 7-33 for 

each subsource (i.e., mineral soil C stocks and organic 

soil C stocks) disaggregated to the level of the inventory 

methodology employed (i.e., Tier 2 and Tier 3). A combined 

uncertainty estimate for changes in agricultural soil C stocks 

occurring within Grassland Remaining Grassland is also 

included. Uncertainty estimates from each component were 

combined using the error propagation equation in accordance 

with IPCC Guidelines (2006), i.e., by taking the square root 

of the sum of the squares of the standard deviations of the 

uncertain quantities. The combined uncertainty for soil C 

stocks in Grassland Remaining Grassland was estimated 

to be 18 percent below and 15 percent above the inventory 

estimate of 16.2 Tg CO2 Eq.

Uncertainties in Mineral Soil Carbon Stock Changes

The uncertainty analysis for Grassland Remaining 

Grassland using the Tier 3 approach and Tier 2 approach 

were based on the same method described for Cropland 

Remaining Cropland, except that the uncertainty inherent in 

the structure of the Century model was not addressed. See 

the Tier 3 approach for mineral soils under the Cropland 

Remaining Cropland section for additional discussion.

A ±50 percent uncertainty was assumed for additional 

adjustments to the soil C stocks between 1990 and 2006 

to account for additional C stock changes associated with 

amending grassland soils with sewage sludge.

Uncertainties in Soil Carbon Stock Changes for Organic Soils

Uncertainty in C emissions from organic soils was 

estimated using country-specific factors and a Monte Carlo 

analysis. Probability distribution functions for emission 

factors were derived from a synthesis of 10 studies, and 

combined with uncertainties in the NRI land-use and 

management data for organic soils in the Monte Carlo 

analysis. See the Tier 2 section under minerals soils of 

Cropland Remaining Cropland for additional discussion.

QA/QC and Verification

Quality control measures included checking input data, 

model scripts, and results to ensure data were properly 

handled through the inventory process. The manure 

amendment records were not recorded correctly in a subset 

of the Century model output; corrective actions were taken 

to resolve this error.

Recalculations Discussion

Two changes were implemented in the current Inventory 

that led to a change in the time series. First, there was a 

modification in the land-use classification. The classification 

is based on the land use in a specific year of the Inventory and 

the previous 20 years. However, in the previous Inventory, 

Table 7-33: Quantitative Uncertainty Estimatesa for C Stock Changes occurring within Grassland Remaining 

Grassland (Tg CO2 Eq. and Percent)

2006 Flux Estimatea Uncertainty Range Relative to Flux Estimatea

Source (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower 

Bound

Upper 

Bound

Lower 

Bound

Upper 

Bound

Mineral Soil C Stocks: Grassland Remaining Grassland,

Tier 3 Inventory Methodology 13.9 12.5 15.3 -10% +10%

Mineral Soil C Stocks: Grassland Remaining Grassland,

Tier 2 Inventory Methodology (0.2) (0.3) 0.0 -89% +127%

Mineral Soil C Stocks: Grassland Remaining Grassland 

(Change in Soil C due to Sewage Sludge Amendments) (1.2) (1.7) (0.6) -50% +50%

Organic Soil C Stocks: Grassland Remaining Grassland, 

Tier 2 Inventory Methodology 3.7 1.2 5.5 -66% +49%

Combined Uncertainty for Flux Associated with 

Agricultural Soil Carbon Stock Change in Grassland 

Remaining Grassland 16.2 13.4 18.6 -18% +15%

a

 Flux estimates based on soil C stock changes.
7-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

each point was only classified once based on the entire NRI 

time series of the land-use history. This approach led to 

incorrect classifications for the early 1990s. For example, a 

NRI point may have been grassland in 1982, 1987 and 1992, 

but converted to cropland in 1997. In the previous Inventory, 

the NRI point would be classified as Land Converted to 

Cropland for the entire Inventory from 1990 through 2005. 

This is incorrect for the early 1990s because the point was 

Grassland Remaining Grassland during those years. Second, 

the time series for manure N between 1990 through 2006, 

which was used to adjust manure applications relative to 

1997, was based on manure N available for application 

rather than manure N production. Overall, the recalculations 

resulted in an average annual decrease in emissions of 0.5 

Tg CO2 Eq. for the time series over the period from 1990 

through 2005, compared to the previous Inventory. 

Planned Improvements 

The empirically-based uncertainty estimator described 

in the Cropland Remaining Cropland section for the Tier 3 

approach has not been developed to estimate uncertainties in 

Century model results for Grassland Remaining Grassland, 

but this is a planned improvement for the Inventory. This 

improvement will produce a more rigorous assessment 

of uncertainty. See Planned Improvements section under 

Cropland Remaining Cropland for additional planned 

improvements.

7.7. Land Converted to Grassland

(IPCC Source Category 5C2)

Land Converted to Grassland includes all grassland in 

an inventory year that had been in another land use during 

the previous 20 years41 according to the USDA NRI land 

use survey (USDA-NRCS 2000). Consequently, the area 

of Land Converted to Grassland changes through time 

with land-use change. Lands are retained in this category 

for 20 years as recommended by IPCC (2006) unless there 

is another land-use change. Background on agricultural C 

stock changes is provided in Cropland Remaining Cropland

and will only be summarized here for Land Converted to 

41 NRI points were classified according to land-use history records starting 

in 1982 when the NRI survey began. Therefore, the classification was based 

on less than 20 years of recorded land-use history for the time series from 

1982 to 2001.

Grassland. Soils are the largest pool of C in agricultural 

land, and also have the greatest potential for storage or 

release of C, because biomass and dead organic matter C 

pools are relatively small and ephemeral compared with 

soils. IPCC/UNEP/OECD/IEA (1997) and IPCC (2003, 

2006) recommend reporting changes in soil organic C 

stocks due to: (1) agricultural land-use and management 

activities on mineral soils, and (2) agricultural land-use 

and management activities on organic soils.42

Land use and management of mineral soils in Land 

Converted to Grassland led to an increase in soil C stocks 

from 1990 through 2006, which was largely caused by annual 

cropland converted into pasture (see Table 7-34 and Table 

7-35). Stock change rates over the time series varied from 

-14.7 to -17.2 Tg CO2 Eq./yr (4 to 5 Tg C). Drainage of 

organic soils for grazing management led to losses varying 

from 0.5 to 0.9 Tg CO2 Eq./yr (0.1 to 0.2 Tg C).

The spatial variability in annual CO2 flux associated with 

C stock changes in mineral soils is displayed in Figure 7-11 

and Figure 7-12. Soil C stock increased in most states for 

Land Converted to Grassland. The largest gains were in the 

Southeast and Northwest, and the amount of sequestration 

increased through the 1990s. The patterns were driven by 

conversion of annual cropland into continuous pasture. 

Emissions from organic soils were largest in California, 

Florida and the upper Midwest, which coincides with largest 

concentrations of organic soils in the United States that are 

used for agricultural production.

Methodology 

This section includes a brief description of the 

methodology used to estimate changes in soil C stocks due to 

agricultural land-use and management activities on mineral 

soils for Land Converted to Grassland. 

Soil C stock changes were estimated for Land Converted 

to Grassland according to land-use histories recorded in 

the USDA NRI survey (USDA-NRCS 2000). Land-use 

and some management information (e.g., legume pastures, 

crop type, soil attributes, and irrigation) was collected for 

each NRI point on a 5-year cycle beginning in 1982, and 

was subdivided into four inventory time periods, 1980 

through 1984, 1985 through 1989, 1990 through 1994 and 

42CO2 emissions associated with liming are also estimated but included in 

a separate section of the report.
Land Use, Land-Use Change, and Forestry 7-47

1995 through 2000. NRI points were classified as Land 

Converted to Grassland for an inventory time period (e.g., 

1990 through 1994 and 1995 through 2000) if the land use 

was grassland at the end of the respective inventory time 

period but had been another use in the previous 20 years.43

43 NRI points were classified according to land-use history records starting 

in 1982 when the NRI survey began. Therefore, the classification was based 

on less than 20 years of recorded land-use history for the time series from 

1982 to 2001.

Table 7-34: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg CO2 Eq.)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Mineral Soilsa (14.7) (17.2) (17.2) (17.2) (17.2) (17.2) (17.2) (17.2) (17.2)

Organic Soils 0.5 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9

Total Net Flux (14.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3) (16.3)

Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are 

based on historical data only. Totals may not sum due to independent rounding.

a Stock changes due to application of sewage sludge are reported in Grassland Remaining Grassland.

Table 7-35: Net CO2 Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006

Mineral Soilsa (4.0) (4.7) (4.7) (4.7) (4.7) (4.7) (4.7) (4.7) (4.7)

Organic Soils 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2

Total Net Flux (3.9) (4.5) (4.5) (4.5) (4.5) (4.5) (4.5) (4.5) (4.5)

Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and projections. All other values are 

based on historical data only. Totals may not sum due to independent rounding.

a Stock changes due to application of sewage sludge in Land Converted to Grassland are reported in Grassland Remaining Grassland.

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.

Tg CO2 Eq./year

< -2

-2 to -1

-1 to -0.5

-0.5 to -0.1

-0.1 to 0

Figure 7-11

Total Net Annual CO2 Flux For Mineral Soils Under Agricultural Management within States, 1993–2006 

Land Converted to Grassland
7-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Grassland includes pasture and rangeland used for grass 

forage production, where the primary use is livestock grazing. 

Rangeland typically includes extensive areas of native 

grassland that are not intensively managed, while pastures 

are often seeded grassland, possibly following tree removal, 

that may or may not be improved with practices such as 

irrigation and interseeding legumes. Further elaboration on 

the methodologies and data used to estimate stock changes 

from mineral and organic soils are provided in the Cropland 

Remaining Cropland section and Annex 3.13.

Mineral Soil Carbon Stock Changes

An IPCC Tier 3 model-based approach was used to 

estimate C stock changes for Land Converted to Grassland

on most mineral soils. C stock changes on the remaining soils 

were estimated with an IPCC Tier 2 approach (Ogle et al. 

2003), including prior cropland used to produce vegetables, 

tobacco, perennial/horticultural crops, and rice; land areas 

with very gravelly, cobbly or shaley soils (greater than 35 

percent by volume); and land converted from forest or federal 

ownership.44 A Tier 2 approach was also used to estimate 

additional changes in mineral soil C stocks due to sewage 

sludge amendments. However, stock changes associated with 

sewage sludge amendments are reported in the Grassland 

Remaining Grassland section.

Tier 3 Approach

Mineral SOC stocks and stock changes were estimated 

using the Century biogeochemical model as described for 

Grassland Remaining Grassland. Historical land-use and 

management patterns were used in the Century simulations 

as recorded in the NRI survey, with supplemental information 

on fertilizer use and rates from the USDA Economic Research 

Service Cropping Practices Survey (ERS 1997) and the 

National Agricultural Statistics Service (NASS 1992, 1999, 

2004) (see Grassland Remaining Grassland Tier 3 methods 

section for additional information).

44 Federal land is not a land use, but rather an ownership designation that 

is treated as forest or nominal grassland for purposes of these calculations. 

The specific use for federal lands is not identified in the NRI survey 

(USDA-NRCS 2000).

Note: Values greater than zero represent emissions.

Total Net Annual CO2 Flux For Organic Soils Under Agricultural Management within States, 1993–2006 

Land Converted to Grassland

Figure 7-12

Tg CO2 Eq./year

No organic soils

0 to 0.1

0.1 to 0.5

0.5 to 1
Land Use, Land-Use Change, and Forestry 7-49

Tier 2 Approach

The Tier 2 approach used for Land Converted to 

Grassland on mineral soils is the same as described for 

Cropland Remaining Cropland (See Cropland Remaining 

Cropland Tier 2 Approach for additional information). 

Organic Soil Carbon Stock Changes

Annual C emissions from drained organic soils in Land 

Converted to Grassland were estimated using the Tier 2 

method provided in IPCC (2003, 2006), which utilizes U.S.-

specific C loss rates (Ogle et al. 2003) rather than default 

IPCC rates. Emissions were based on the 1992 and 1997 

Land Converted to Grassland areas from the 1997 National 

Resources Inventory (USDA-NRCS 2000). The annual flux 

estimated for 1992 was applied to 1990 through 1992, and 

the annual flux estimated for 1997 was applied to 1993 

through 2006.

Uncertainty

Uncertainty analysis for mineral soil C stock changes 

using the Tier 3 and Tier 2 approaches were based on the 

same method described in Cropland Remaining Cropland, 

except that the uncertainty inherent in the structure of 

the Century model was not addressed. The uncertainty or 

annual C emission estimates from drained organic soils 

in Land Converted to Grassland was estimated using the 

Tier 2 approach, as described in the Cropland Remaining 

Cropland section.

Uncertainty estimates are presented in Table 7-36 for 

each subsource (i.e., mineral soil C stocks and organic 

soil C stocks), disaggregated to the level of the inventory 

methodology employed (i.e., Tier 2 and Tier 3). A combined 

uncertainty estimate for changes in agricultural soil C 

stocks occurring within Land Converted to Grassland is 

also included. Uncertainty estimates from each component 

were combined using the error propagation equation in 

accordance with IPCC (2006), (i.e., by taking the square 

root of the sum of the squares of the standard deviations of 

the uncertain quantities). The combined uncertainty for soil 

C stocks in Land Converted to Grassland ranged from 13 

percent below and 14 percent above the 2006 estimate of 

16.3 Tg CO2 Eq.

QA/QC and Verification

See the QA/QC and Verification section under Grassland 

Remaining Grassland. 

Recalculations Discussion

Two changes were implemented in the current 

Inventory that led to a change in the time series. First, 

there was a modification in the land-use classification. The 

classification is based on the land use in a specific year of 

the Inventory and the previous 20 years. However, in the 

1990 through 2005 Inventory, each point was only classified 

once based on the entire NRI time series of the land-use 

history. This approach led to incorrect classifications for 

the early 1990s. For example, a NRI point may have been 

cropland in 1982, 1987 and 1992, but converted to grassland 

in 1997. In the previous Inventory, the NRI point would 

be classified as Land Converted to Grassland for the entire 

Inventory from 1990 through 2005. This is incorrect for the 

early 1990s because the point was Cropland Remaining 

Cropland during those years. Second, the time series for 

manure N between 1990 through 2006, which was used 

to adjust manure applications relative to 1997, was based 

on manure N available for application rather than manure 

N production. Overall, the recalculations resulted in an 

average annual decrease in emissions of 0.1 Tg CO2 Eq. 

for the time series from 1990 through 2005, compared to 

the previous Inventory. 

Planned Improvements 

The empirically-based uncertainty estimator described 

in the Cropland Remaining Cropland section for the Tier 3 

approach has not been developed to estimate uncertainties 

in Century model results for Land Converted to Grassland, 

but this is a planned improvement for the Inventory. This 

improvement will produce a more rigorous assessment 

of uncertainty. See Planned Improvements section under 

Cropland Remaining Cropland for additional planned 

improvements.
7-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

7.8. Settlements Remaining 

Settlements

Changes in Carbon Stocks in Urban 

Trees (IPCC Source Category 5E1)

Urban forests constitute a significant portion of the total 

U.S. tree canopy cover (Dwyer et al. 2000). Urban areas 

(cities, towns, and villages) are estimated to cover over 

4.4 percent of the United States (Nowak et al. 2005). With 

an average tree canopy cover of 27 percent, urban areas 

account for approximately 3 percent of total tree cover in 

the continental United States (Nowak et al. 2001). Trees in 

urban areas of the United States were estimated to account 

for an average annual net sequestration of 78.1 Tg CO2 Eq. 

(21 Tg C) over the period from 1990 through 2006. Total 

sequestration increased by 57 percent between 1990 and 

2006 due to increases in urban land area. Data on C storage 

and urban tree coverage were collected since the early 1990s 

and have been applied to the entire time series in this report. 

Annual estimates of CO2 flux were developed based on 

periodic U.S. Census data on urban area (Table 7-37). Net 

C flux from urban trees in 2006 was estimated to be -95.5 

Tg CO2 Eq. (-26 Tg C).

Net C flux from urban trees is proportionately greater 

on an area basis than that of forests. This trend is primarily 

the result of different net growth rates in urban areas versus 

forests—urban trees often grow faster than forest trees 

because of the relatively open structure of the urban forest 

(Nowak and Crane 2002). Also, areas in each case are 

accounted for differently. Because urban areas contain less 

tree coverage than forest areas, the C storage per hectare of 

land is in fact smaller for urban areas. However, urban tree 

reporting occurs on a per unit tree cover basis (tree canopy 

area), rather than total land area. Urban trees, therefore, 

appear to have a greater C density than forested areas (Nowak 

and Crane 2002).

Methodology

The methodology used by Nowak and Crane (2002) is 

based on average annual estimates of urban tree growth and 

decomposition, which were derived from field measurements 

and data from the scientific literature, urban area estimates 

from U.S. Census data, and urban tree cover estimates 

from remote sensing data. This approach is consistent with 

Table 7-37: Net C Flux from Urban Trees 

(Tg CO2 Eq. and Tg C)

Year Tg CO2 Eq. Tg C

1990 (60.6) (16.5)

1995 (71.5) (19.5)

2000 (82.4) (22.5)

2001 (84.6) (23.1)

2002 (86.8) (23.7)

2003 (88.9) (24.3)

2004 (91.1) (24.9)

2005 (93.3) (25.4)

2006 (95.5) (26.0)

Note: Parentheses indicate net sequestration.

Table 7-36: Quantitative Uncertainty Estimatesa for C Stock Changes occurring within Land Converted to Grassland

(Tg CO2 Eq. and Percent)

2006 Flux Estimatea Uncertainty Range Relative to Flux Estimatea

Source (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower 

Bound

Upper 

Bound

Lower 

Bound

Upper 

Bound

Mineral Soil C Stocks: Land Converted to Grassland,

Tier 3 Inventory Methodology (12.2) (12.5) (11.9) -2% +2%

Mineral Soil C Stocks: Land Converted to Grassland, 

Tier 2 Inventory Methodology (5.0) (7.0) (2.8) -39% +43%

Organic Soil C Stocks: Land Converted to Grassland,

Tier 2 Inventory Methodology 0.9 0.2 1.8 -76% +104%

Combined Uncertainty for Flux associated with 

Agricultural Soil Carbon Stocks in Land Converted 

to Grassland (16.3) (18.4) (14.0) -13% +14%

a

 Flux estimates based on soil C stock changes.
Land Use, Land-Use Change, and Forestry 7-51

the default IPCC methodology in IPCC (2006), although 

sufficient data are not yet available to determine interannual 

gains and losses in C stocks in the living biomass of urban 

trees. Annual changes in net C flux from urban trees are based 

solely on changes in total urban area in the United States.

Most of the field data were analyzed using the U.S. 

Forest Service’s Urban Forest Effects (UFORE) model.45 The 

UFORE model is a computer model that uses standardized 

field data from random plots and local air pollution and 

meteorological data to quantify urban forest structure, values 

of the urban forest, and environmental effects, including total 

C stored and annual C sequestration (Nowak et al. 2007a).

Nowak and Crane (2002) developed estimates of annual 

gross C sequestration from tree growth and annual gross C 

emissions from decomposition for 15 U.S. cities: Atlanta, 

GA; Baltimore, MD; Boston, MA; Chicago, IL; Freehold, NJ; 

Jersey City, NJ; Minneapolis, MN; Moorestown, NJ; New 

York, NY; Oakland, CA; Philadelphia, PA; San Francisco, 

CA; Syracuse, NY; Washington, DC; and Woodbridge, NJ. 

The gross C sequestration estimates were derived from field 

data that were collected in these 15 cities during the period 

from 1989 through 2006, including tree measurements of 

stem diameter, tree height, crown height, and crown width, 

and information on location, species, and canopy condition. 

The field data were converted to annual gross C sequestration 

rates for each species (or genus), diameter class, and land-use 

condition (forested, park-like, and open growth) by applying 

allometric equations, a root-to-shoot ratio, moisture contents, 

a C content of 50 percent (dry weight basis), an adjustment 

factor to account for smaller aboveground biomass volumes 

(given a particular diameter) in urban conditions compared 

to forests, an adjustment factor to account for tree condition 

(fair to excellent, poor, critical, dying, or dead), and annual 

diameter and height growth rates. The annual gross C 

sequestration rates for each species (or genus), diameter 

class, and land-use condition were then scaled up to city 

estimates using tree population information. The field data 

from the 15 cities, some of which are unpublished (Nowak 

2007c), are described in Nowak and Crane (2002), Nowak 

et al. (2007a), and references cited therein. The allometric 

equations were taken from the scientific literature (see 

Nowak 1994, Nowak et al. 2002), and the adjustments to 

45 Oakland and Chicago estimates were based on prototypes to the UFORE 

model.

account for smaller volumes in urban conditions were based 

on information in Nowak (1994). A root-to-shoot ratio of 

0.26 was taken from Cairns et al. (1997), and species- or 

genus-specific moisture contents were taken from various 

literature sources (see Nowak 1994). Tree growth rates were 

taken from existing literature. Average diameter growth was 

based on the following sources: estimates for trees in forest 

stands came from Smith and Shifley (1984); estimates for 

trees on land uses with a park-like structure came from 

deVries (1987); and estimates for more open-grown trees 

came from Nowak (1994). Formulas from Fleming (1988) 

formed the basis for average height growth calculations. 

Growth rates were adjusted to account for tree condition. 

Growth factors for Atlanta, Boston, Chicago, Freehold, 

Jersey City, Moorestown, New York, Oakland, Philadelphia, 

and Woodbridge were adjusted based on the typical growth 

conditions of different land-use categories (e.g., forest stands, 

park-like stands). Growth factors for the more recent studies 

in Baltimore, Minneapolis, San Francisco, Syracuse, and 

Washington were adjusted using an updated methodology 

based on the condition of each individual tree, which is 

determined using tree competition factors (depending on 

whether it is open grown or suppressed) (Nowak 2007b).

Annual gross C emission estimates were derived by 

applying estimates of annual mortality and condition, and 

assumptions about whether dead trees were removed from 

the site, to C stock estimates. These values were derived 

as intermediate steps in the sequestration calculations, and 

different decomposition rates were applied to dead trees left 

standing compared with those removed from the site. The 

annual gross C emission rates for each species (or genus), 

diameter class, and condition class were then scaled up to 

city estimates using tree population information. Estimates of 

annual mortality rates by diameter class and condition class 

were derived from a study of street-tree mortality (Nowak 

1986). Assumptions about whether dead trees would be 

removed from the site were based on expert judgment of 

the authors. Decomposition rates were based on literature 

estimates (Nowak and Crane 2002).

National annual net C sequestration by urban trees was 

calculated based on estimates of gross and net sequestration 

from 13 of the 15 cities (Table 7-38), and urban area and 

urban tree cover data for the United States. Annual net 

C sequestration estimates were derived for 13 cities by 

subtracting the annual gross emission estimates from the 
7-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

annual gross sequestration estimates.46 The urban areas are 

based on 1990 and 2000 U.S. Census data. The 1990 U.S. 

Census defined urban land as “urbanized areas,” which 

included land with a population density greater than 1,000 

people per square mile, and adjacent “urban places,” which 

had predefined political boundaries and a population total 

greater than 2,500. In 2000, the U.S. Census replaced the 

“urban places” category with a new category of urban 

land called an “urban cluster,” which included areas with 

more than 500 people per square mile. Urban land area 

has increased by approximately 36 percent from 1990 to 

2000; Nowak et al. (2005) estimate that the changes in the 

definition of urban land have resulted in approximately 20 

percent of the total reported increase in urban land area 

from 1990 to 2000. Under both 1990 and 2000 definitions, 

urban encompasses most cities, towns, and villages (i.e., it 

includes both urban and suburban areas). The gross and net 

C sequestration values for each city were divided by each 

city’s area of tree cover to determine the average annual 

sequestration rates per unit of tree area for each city. The 

median value for gross sequestration (0.31 kg C/m2-year) 

was then multiplied by the estimate of national urban tree 

46Two cities did not have net estimates.

cover area to estimate national annual gross sequestration. 

To estimate national annual net sequestration, the estimate 

of national annual gross sequestration was multiplied by the 

average of the ratios of net to gross sequestration for those 

cities that had both estimates (0.72). The urban tree cover 

estimates for each of the 15 cities and the United States were 

obtained from Dwyer et al. (2000), Nowak et al. (2002), and 

Nowak (2007a). The urban area estimates were taken from 

Nowak et al. (2005). 

Uncertainty 

Uncertainty associated with changes in C stocks in 

urban trees includes the uncertainty associated with urban 

area, percent urban tree coverage, and estimates of gross 

and net C sequestration for the 15 U.S. cities. A 10 percent 

uncertainty was associated with urban area estimates while 

a 5 percent uncertainty was associated with percent urban 

tree coverage. Both of these uncertainty estimates were based 

on expert judgment. Uncertainty associated with estimates 

of gross and net C sequestration for the 15 U.S. cities was 

based on standard error estimates for each of the city-level 

sequestration estimates reported by Nowak (2007c). These 

estimates are based on field data collected in 15 U.S. cities, 

Table 7-38: C Stocks (Metric Tons C), Annual C Sequestration (Metric Tons C/yr), Tree Cover (Percent), and 

Annual C Sequestration per Area of Tree Cover (kg C/m2 cover-yr) for 15 U.S. Cities

City Carbon

Stocks

Gross Annual 

Sequestration

Net Annual 

Sequestration

Tree 

Cover

Gross Annual 

Sequestration per 

Area of Tree Cover

Net Annual 

Sequestration per 

Area of Tree Cover

Atlanta, GA 1,219,256 42,093 32,169 36.7% 0.34 0.26

Baltimore, MD 541,589 14,696 9,261 21.0% 0.35 0.22

Boston, MA 289,392 9,525 6,966 22.3% 0.30 0.22

Chicago, IL NA NA NA 11.0% 0.61 NA

Freehold, NJ 18,144 494 318 34.4% 0.28 0.18

Jersey City, NJ 19,051 807 577 11.5% 0.18 0.13

Minneapolis, MN 226,796 8,074 4,265 26.4% 0.20 0.11

Moorestown, NJ 106,141 3,411 2,577 28.0% 0.32 0.24

NewYork, NY 1,224,699 38,374 20,786 20.9% 0.23 0.12

Oakland, CA NA NA NA 21.0% NA NA

Philadelphia, PA 480,808 14,606 10,530 15.7% 0.27 0.20

San Francisco, CA 175,994 4,627 4,152 11.9% 0.33 0.29

Syracuse, NY 156,943 4,917 4,270 23.1% 0.33 0.29

Washington, DC 477,179 14,696 11,661 28.6% 0.32 0.26

Woodbridge, NJ 145,150 5,044 3,663 29.5% 0.28 0.21

NA = not analyzed.

Sources: Nowak and Crane (2002) and Nowak (2007a,c).
Land Use, Land-Use Change, and Forestry 7-53

and uncertainty in these estimates increases as they are scaled 

up to the national level. 

Additional uncertainty is associated with the biomass 

equations, conversion factors, and decomposition assumptions 

used to calculate C sequestration and emission estimates 

(Nowak et al. 2002). These results also exclude changes in 

soil C stocks, and there may be some overlap between the 

urban tree C estimates and the forest tree C estimates.Due 

to data limitations, urban soil flux is not quantified as part of 

this analysis, while reconciliation of urban tree and forest tree 

estimates will be addressed through the land representation 

effort described at the beginning of this chapter.

A Monte Carlo (Tier 2) uncertainty analysis was applied to 

estimate the overall uncertainty of the sequestration estimate. 

The results of the Tier 2 quantitative uncertainty analysis are 

summarized in Table 7-39. The net C flux from changes in 

C stocks in urban trees was estimated to be between -112.1 

and -76.5 Tg CO2 Eq. at a 95 percent confidence level. This 

indicates a range of 17 percent below and 20 percent above 

the 2006 flux estimate of -95.5 Tg CO2 Eq. 

QA/QC and Verification 

The net C flux resulting from urban trees was 

calculated using estimates of gross and net C sequestration 

estimates for urban trees and urban tree coverage area 

found in literature. The validity of these data for their use 

in this section of the Inventory was evaluated through 

correspondence established with an author of the papers. 

Through this correspondence, the methods used to collect 

the urban tree sequestration and area data were further 

clarified and the use of these data in the Inventory was 

reviewed and validated (Nowak 2002a, 2007b).

Recalculations Discussion

New data were added for six U.S. cities: Freehold, NJ; 

Minneapolis, MN; Moorestown, NJ; San Francisco, CA; 

Washington, DC; and Woodbridge, NJ. Data for Sacramento, 

CA was removed from the urban trees estimates because it 

was analyzed using a different methodology. These changes 

brought the total number of included cities to 15, providing 

a better median estimate of net and gross sequestration 

than the previous inventory estimate based on data from 

10 U.S. cities.

There was also a slight change in the methodology for 

adjusting urban tree growth rates to account for tree condition. 

Some of the older studies used average growth rates based on 

the typical growth conditions of different land-use categories. 

In contrast, some of the newer studies adjust growth factors 

based on the condition of the tree, which is determined using 

tree competition factors (depending on whether it is open 

grown or suppressed) for each individual tree. The cities that 

use each of these methodologies are identified above in the 

Methodology section. The difference that resulted from this 

change in methodological approach is very small and likely 

washes out on average (Nowak 2007b).

These changes resulted in changes in the estimates of 

net annual C sequestration by urban trees for the time period 

1990 through 2005. On average, estimates of net annual C 

sequestration by urban trees increased by 5.3 percent over the 

period from 1990 to 2005 relative to the previous report.

Planned Improvements

A consistent representation of the managed land base 

in the United States is being developed. A component 

of this effort, which is discussed at the beginning of the 

Table 7-39: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees (Tg 

CO2 Eq. and Percent)

2006 Flux Estimate Uncertainty Range Relative to Flux Estimate

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower 

Bound

Upper 

Bound

Lower 

Bound

Upper 

Bound

Changes in C Stocks in Urban Trees CO2 (95.5) (112.1) (76.5) -17% +20%

Note: Parentheses indicate negative values or net sequestration. 
7-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

LULUCF chapter, will involve reconciling the overlap 

between urban forest and non-urban forest greenhouse gas 

inventories. It is highly likely that urban forest inventories 

are including areas considered non-urban under the Forest 

Inventory and Analysis (FIA) program of the USDA Forest 

Service, resulting in “double-counting” of these land areas in 

estimates of C stocks and fluxes for the Inventory. Planned 

improvements to the FIA program include the development 

of a long-term dataset that will define urban area boundaries 

and make it possible to identify what area is forested. Once 

those data become available, they will be incorporated into 

estimates of net C flux resulting from urban trees.

Urban forest data for additional cities is expected in 

the near term, and the use of this data will further refine 

the estimated median sequestration value. It may also be 

possible to report C losses and gains separately in the future. 

It is currently not possible, since existing studies estimate 

rather than measure natality or mortality; net sequestration 

estimates are based on assumptions about whether dead trees 

are being removed, burned, or chipped. There is an effort 

underway to develop long-term data on permanent plots in 

at least two cities, which would allow for direct calculation 

of C losses and gains from observed rather than estimated 

natality and mortality of trees.

Direct N2O Fluxes from Settlement 

Soils (IPCC Source Category 5E1)

Of the synthetic N fertilizers applied to soils in the 

United States, approximately 2.5 percent are currently 

applied to lawns, golf courses, and other landscaping 

occurring within settlement areas. Application rates are less 

than those occurring on cropped soils, and, therefore, account 

for a smaller proportion of total U.S. soil N2O emissions per 

unit area. In addition to synthetic N fertilizers, a portion of 

surface applied sewage sludge is applied to settlement areas. 

In 2006, N2O emissions from this source were 1.5 Tg CO2

Eq. (4.7 Gg). There was an overall increase of 48 percent 

over the period from 1990 through 2006 due to a general 

increase in the application of synthetic N fertilizers to an 

expanding settlement area. Interannual variability in these 

emissions is directly attributable to interannual variability 

in total synthetic fertilizer consumption and sewage sludge 

applications in the United States. Emissions from this source 

are summarized in Table 7-40.

Methodology

For soils within Settlements Remaining Settlements, 

the IPCC Tier 1 approach was used to estimate soil N2O 

emissions from synthetic N fertilizer and sewage sludge 

additions. Estimates of direct N2O emissions from soils 

in settlements were based on the amount of N in synthetic 

commercial fertilizers applied to settlement soils and the 

amount of N in sewage sludge applied to non-agricultural 

land and in surface disposal of sewage sludge. 

Nitrogen applications to settlement soils are estimated 

using data compiled by the USGS (Ruddy et al. 2006). The 

USGS estimated on-farm and non-farm fertilizer use based 

on sales records at the county level from 1982 through 2001 

(Ruddy et al. 2006). Non-farm N fertilizer was assumed to 

be applied to settlements and forests and values for 2001 

were used for 2002 through 2006. Settlement application was 

calculated by subtracting forest application from total nonfarm fertilizer use. Sewage sludge applications were derived 

from national data on sewage sludge generation, disposition, 

and N content (see Annex 3.11 for further detail). The total 

amount of N resulting from these sources was multiplied by 

the IPCC default emission factor for applied N (1 percent) to 

estimate direct N2O emissions (IPCC 2006). The volatilized 

and leached/runoff proportions, calculated with the IPCC 

default volatilization factors (10 or 20 percent, respectively, 

for synthetic or organic N fertilizers) and leaching/runoff 

factor for wet areas (30 percent), were included with the 

total N contributions to indirect emissions, as reported in the 

Table 7-40: N2O Fluxes from Soils in Settlements 

Remaining Settlements (Tg CO2 Eq. and Gg)

Year Tg CO2 Eq. Gg

1990 1.0 3.2

1995 1.2 3.9

2000 1.2 4.0

2001 1.4 4.6

2002 1.5 4.7

2003 1.5 4.9

2004 1.6 5.0

2005 1.5 4.8

2006 1.5 4.7

Note: These estimates include direct N2O emissions from N fertilizer 

additions only. Indirect N2O emissions from fertilizer additions are 

reported in the Agriculture chapter. These estimates include emissions 

from both Settlements Remaining Settlements and from Land Converted 

to Settlements.
Land Use, Land-Use Change, and Forestry 7-55

N2O Emissions from Agricultural Soil Management source 

category of the Agriculture chapter. 

Uncertainty 

The amount of N2O emitted from settlements depends 

not only on N inputs, but also on a large number of variables, 

including organic C availability, O2 partial pressure, soil 

moisture content, pH, temperature, and irrigation/watering 

practices. The effect of the combined interaction of these 

variables on N2O flux is complex and highly uncertain. 

The IPCC default methodology does not incorporate any of 

these variables and only accounts for variations in fertilizer 

N and sewage sludge application rates. All settlement soils 

are treated equivalently under this methodology. 

Uncertainties exist in both the fertilizer N and sewage 

sludge application rates in addition to the emission factors. 

Uncertainty in fertilizer N application was assigned a 

default level47 of ±50 percent. Uncertainty in the amounts 

of sewage sludge applied to non-agricultural lands and used 

in surface disposal was derived from variability in several 

factors, including: (1) N content of sewage sludge, (2) total 

sludge applied in 2000, (3) wastewater existing flow in 

1996 and 2000, and (4) the sewage sludge disposal practice 

distributions to non-agricultural land application and surface 

disposal. Uncertainty in the emission factors was provided 

by the IPCC (2006).

Quantitative uncertainty of this source category was 

estimated through the IPCC-recommended Tier 2 uncertainty 

estimation methodology. The uncertainty ranges around the 

2005 activity data and emission factor input variables were 

directly applied to the 2006 emissions estimates. The results 

of the quantitative uncertainty analysis are summarized 

in Table 7-41. N2O emissions from soils in Settlements 

Remaining Settlements in 2006 were estimated to be between 

0.8 and 3.9 Tg CO2 Eq. at a 95 percent confidence level. This 

indicates a range of 49 percent below to 163 percent above 

the 2006 emission estimate of 1.5 Tg CO2 Eq. 

47 No uncertainty is provided with the USGS application data (Ruddy et al. 

2006) so a conservative ±50% was used in the analysis.

Recalculations Discussion

A new data source was used for N fertilization in the 

current inventory. Instead of assuming settlement soils 

receive 10 percent of total synthetic N fertilizer applied in the 

United States, fertilization data were based on county-scale 

non-farm application amounts from a database compiled 

by the USGS (Ruddy et al. 2006). According to the USGS 

data, approximately 1.7 percent of synthetic fertilizer N sold 

was for non-farm use in 1990 and this gradually increased 

to 3.1 percent in 2001. After subtracting forest application 

from non-farm fertilizer use, this change resulted in a 75 

percent decrease in the emission estimates for 2005 and an 

average decrease of about 78 percent over the period from 

1990 to 2005.

Planned Improvements

The key planned improvement is to estimate emissions 

using the process-based DAYCENT model instead of the 

IPCC default methodology. DAYCENT has been used to 

estimate N2O emissions from agricultural soils, reducing 

bias and improving precision in estimates for the cropland 

and grassland soils. Applying the DAYCENT model is also 

anticipated to reduce uncertainties in the estimated emissions 

from settlement soils. In addition, this planned improvement 

would incorporate state-level settlement area data from the 

National Resource Inventory. Another minor improvement is 

to update the uncertainty analysis for direct emissions from 

settlements to be consistent with the most recent activity 

data for this source.

7.9. Land Converted to Settlements 

(Source Category 5E2)

Land-use change is constantly occurring, and land under 

a number of uses undergoes urbanization in the United States 

each year. However, data on the amount of land converted 

to settlements is currently lacking. Given the lack of 

available information relevant to this particular IPCC source 

category, it is not possible to separate CO2 or N2O fluxes on 

Land Converted to Settlements from fluxes on Settlements 

Remaining Settlements at this time. 
7-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

7.10. Other 

(IPCC Source Category 5G)

Changes in Yard Trimming and Food 

Scrap Carbon Stocks in Landfills 

In the United States, a significant change in C stocks 

results from the removal of yard trimmings (i.e., grass 

clippings, leaves, and branches) and food scraps from 

settlements to be disposed in landfills. Yard trimmings and 

food scraps account for a significant portion of the municipal 

waste stream, and a large fraction of the collected yard 

trimmings and food scraps are discarded in landfills. C 

contained in landfilled yard trimmings and food scraps can 

be stored for very long periods. 

Carbon storage estimates are associated with particular 

land uses. For example, harvested wood products are 

accounted for under Forest Land Remaining Forest Land

because these wood products are a component of the forest 

ecosystem. The wood products serve as reservoirs to which 

C resulting from photosynthesis in trees is transferred, but 

the removals in this case occur in the forest. C stock changes 

in yard trimmings and food scraps are associated with 

settlements, but removals in this case do not occur within 

settlements. To address this complexity, yard trimming and 

food scrap C storage is therefore reported under the “Other” 

source category. 

Both the amount of yard trimmings and food scraps 

collected annually and the fraction that is landfilled have 

declined over the last decade. In 1990, over 51 million 

metric tons (wet weight) of yard trimmings and food 

scraps were generated (i.e., put at the curb for collection 

to be taken to disposal sites or to composting facilities) 

(EPA 2007; Schneider 2007, 2008). Since then, programs 

banning or discouraging disposal have led to an increase 

in backyard composting and the use of mulching mowers, 

and a consequent 7 percent decrease in the amount of 

yard trimmings generated (i.e., collected for composting 

or disposal). At the same time, a dramatic increase in the 

number of municipal composting facilities has reduced the 

proportion of collected yard trimmings that are discarded in 

landfills—from 72 percent in 1990 to 31 percent in 2006. The 

net effect of the reduction in generation and the increase in 

composting is a 60 percent decrease in the quantity of yard 

trimmings disposed in landfills since 1990. Food scraps 

generation has grown by 50 percent since 1990, but the 

proportion of food scraps discarded in landfills has decreased 

slightly from 81 percent in 1990 to 80 percent in 2006. 

Overall, the decrease in the yard trimmings landfill disposal 

rate has more than compensated for the increase in food scrap 

disposal in landfills, and the net result is a decrease in annual 

landfill C storage from 23.9 Tg CO2 Eq. in 1990 to 10.5 Tg 

CO2 Eq. in 2006 (Table 7-42 and Table 7-43).

Methodology

As empirical evidence shows, the removal of C from the 

natural cycling of C between the atmosphere and biogenic 

materials, which occurs when wastes of biogenic origin 

are deposited in landfills, sequesters C (Barlaz 1998, 2005, 

2008). When wastes of sustainable, biogenic origin (such 

as yard trimming and food scraps) are landfilled and do not 

completely decompose, the C that remains is effectively 

removed from the global C cycle. Estimates of net C flux 

resulting from landfilled yard trimmings and food scraps 

were developed by estimating the change in landfilled C 

stocks between inventory years, based on methodologies 

presented for the Land Use, Land-Use Change and Forestry 

sector in IPCC (2003). C stock estimates were calculated 

by determining the mass of landfilled C resulting from 

yard trimmings or food scraps discarded in a given year; 

Table 7-41: Quantitative Uncertainty Estimates of N2O Emissions from Soils in Settlements Remaining Settlements

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Settlements Remaining Settlements:

N2O Fluxes from Soils N2O 1.5 0.8 3.9 -49% +163%

Note: This estimate includes direct N2O emissions from N fertilizer additions to both Settlements Remaining Settlements and from Land Converted to 

Settlements.
Land Use, Land-Use Change, and Forestry 7-57

adding the accumulated landfilled C from previous years; 

and subtracting the portion of C landfilled in previous years 

that decomposed.

To determine the total landfilled C stocks for a given 

year, the following were estimated: (1) the composition of 

the yard trimmings, (2) the mass of yard trimmings and food 

scraps discarded in landfills, (3) the C storage factor of the 

landfilled yard trimmings and food scraps adjusted by mass 

balance, and (4) the rate of decomposition of the degradable 

C. The composition of yard trimmings was assumed to be 

30 percent grass clippings, 40 percent leaves, and 30 percent 

branches on a wet weight basis (Oshins and Block 2000). The 

yard trimmings were subdivided, because each component 

has its own unique adjusted C storage factor and rate of 

decomposition. The mass of yard trimmings and food scraps 

disposed of in landfills was estimated by multiplying the 

quantity of yard trimmings and food scraps discarded by the 

proportion of discards managed in landfills. Data on discards 

(i.e., the amount generated minus the amount diverted to 

centralized composting facilities) for both yard trimmings 

and food scraps were taken primarily from Municipal Solid 

Waste Generation, Recycling, and Disposal in the United 

States: 2006 Facts and Figures (EPA 2007), which provides 

data for 1960, 1970, 1980, 1990, 2000, 2002, and 2004 

through 2006. To provide data for some of the missing years, 

detailed backup data was obtained from Schneider (2007, 

2008). Remaining years in the time series for which data were 

not provided were estimated using linear interpolation. The 

report does not subdivide discards of individual materials into 

volumes landfilled and combusted, although it provides an 

estimate of the proportion of overall waste stream discards 

managed in landfills and combustors (i.e., ranging from 90 

percent and 10 percent respectively in 1980, to 67 percent 

and 33 percent in 1960). 

The amount of C disposed of in landfills each year, 

starting in 1960, was estimated by converting the discarded 

landfilled yard trimmings and food scraps from a wet weight 

to a dry weight basis, and then multiplying by the initial (i.e., 

pre-decomposition) C content (as a fraction of dry weight). 

The dry weight of landfilled material was calculated using dry 

weight to wet weight ratios (Tchobanoglous et al. 1993, cited 

by Barlaz 1998) and the initial C contents were determined 

by Barlaz (1998, 2005, 2008) (Table 7-44).

The amount of C remaining in the landfill for each 

subsequent year was tracked based on a simple model of 

C fate. As demonstrated by Barlaz (1998, 2005, 2008), a 

portion of the initial C resists decomposition and is essentially 

persistent in the landfill environment. Barlaz (1998, 2005, 

2008) conducted a series of experiments designed to measure 

biodegradation of yard trimmings, food scraps, and other 

Table 7-42: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO2 Eq.)

Carbon Pool 1990 1995 2000 2001 2002 2003 2004 2005 2006

Yard Trimmings (21.4) (12.6) (8.2) (8.5) (8.7) (7.1) (6.2) (6.5) (6.8)

Grass (1.9) (0.8) (0.4) (0.5) (0.6) (0.4) (0.3) (0.4) (0.5)

Leaves (9.7) (6.0) (4.0) (4.1) (4.2) (3.5) (3.1) (3.2) (3.3)

Branches (9.7) (5.8) (3.7) (3.8) (3.9) (3.2) (2.8) (2.9) (3.0)

Food Scraps (2.5) (1.6) (3.3) (3.1) (3.1) (2.9) (3.4) (3.5) (3.7)

Total Net Flux (23.9) (14.1) (11.5) (11.6) (11.8) (10.0) (9.6) (10.0) (10.5)

Note: Totals may not sum due to independent rounding.

Table 7-43: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C)

Carbon Pool 1990 1995 2000 2001 2002 2003 2004 2005 2006

Yard Trimmings (5.8) (3.4) (2.2) (2.3) (2.4) (1.9) (1.7) (1.8) (1.9)

Grass (0.5) (0.2) (0.1) (0.1) (0.2) (0.1) (0.1) (0.1) (0.1)

Leaves (2.7) (1.6) (1.1) (1.1) (1.1) (0.9) (0.8) (0.9) (0.9)

Branches (2.6) (1.6) (1.0) (1.0) (1.1) (0.9) (0.8) (0.8) (0.8)

Food Scraps (0.7) (0.4) (0.9) (0.8) (0.8) (0.8) (0.9) (0.9) (1.0)

Total Net Flux (6.5) (3.9) (3.1) (3.2) (3.2) (2.7) (2.6) (2.7) (2.9)

Note: Totals may not sum due to independent rounding.
7-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

materials, in conditions designed to promote decomposition 

(i.e., by providing ample moisture and nutrients). After 

measuring the initial C content, the materials were placed 

in sealed containers along with a “seed” containing 

methanogenic microbes from a landfill. Once decomposition 

was complete, the yard trimmings and food scraps were reanalyzed for C content; the C remaining in the solid sample 

can be expressed as a proportion of initial C (shown in the 

row labeled “CS” in Table 7-44). 

The modeling approach applied to simulate U.S. landfill 

C flows builds on the findings of Barlaz (1998, 2005, 2008). 

The proportion of C stored is assumed to persist in landfills. 

The remaining portion is assumed to degrade, resulting in 

emissions of CH4 and CO2 (the CH4 emissions resulting 

from decomposition of yard trimmings and food scraps 

are accounted for in the Waste chapter). The degradable 

portion of the C is assumed to decay according to first order 

kinetics. Food scraps are assumed to have a half-life of 3.7 

years; grass is assumed to have a half-life of 5 years; leaves 

are assumed to have a half-life of 20 years; and branches 

are assumed to have a half-life of 23.1 years. The half-life 

of food scraps is consistent with analysis for landfill CH4 in 

the Waste chapter.

For each of the four materials (grass, leaves, branches, 

food scraps), the stock of C in landfills for any given year is 

calculated according to the following formula: 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

For a given year t, the total stock of C in landfills (TLFCt

) 

is the sum of stocks across all four materials. The annual flux 

of C in landfills (Ft) for year t is calculated as the change in 

stock compared to the preceding year:

 

 

 

Thus, the C placed in a landfill in year n is tracked for 

each year t through the end of the inventory period (2006). For 

example, disposal of food scraps in 1960 resulted in depositing 

about 1,135,000 metric tons of C. Of this amount, 16 percent 

(179,000 metric tons) is persistent; the remaining 84 percent 

(956,000 metric tons) is degradable. By 1964, more than half 

of the degradable portion (500,000 metric tons) decomposes, 

leaving a total of 635,000 metric tons (the persistent portion, 

plus the remainder of the degradable portion). 

Continuing the example, by 2006, the total food scraps 

C originally disposed in 1960 had declined to 179,000 metric 

tons (i.e., virtually all of the degradable C had decomposed). 

By summing the C remaining from 1960 with the C remaining 

from food scraps disposed in subsequent years (1961 through 

2006), the total landfill C from food scraps in 2006 was 29.5 

million metric tons. This value is then added to the C stock 

LFC i,t = Σ Wi,n × (1 - MCi) × ICCi × n

{[CSi × ICCi] + [(1 - (CSi × ICCi)) × e-k (t - n) ]}

where,

t = Year for which C stocks are being estimated 

(year), 

i = Waste type for which C stocks are being 

estimated (grass, leaves, branches, food 

scraps),

LFCi,t = Stock of C in landfills in year t, for waste i

(metric tons),

Wi,n = Mass of waste i disposed in landfills in year 

n (metric tons, wet weight), 

n = Year in which the waste was disposed (year, 

where 1960 U≤U n U≤U t), 

MCi = Moisture content of waste i (percent of water),

CSi = Proportion of initial C that is stored for 

waste i (percent),

ICCi = Initial C content of waste i (percent),

e = Natural logarithm, and

k = First order rate constant for waste i, which 

is equal to 0.693 divided by the half-life for 

decomposition (year-1).

Table 7-44: Moisture Content (%), C Storage Factor, Proportion of Initial C Sequestered (%), Initial C Content (%), 

and Half-Life (years) for Landfilled Yard Trimmings and Food Scraps in Landfills 

Yard Trimmings Food Scraps

Variable Grass Leaves Branches

Moisture Content (% H2O) 70 30 10 70

CS, proportion of initial C stored (%) 53 85 77 16

Initial C Content (%) 45 46 49 51

Half-life (years) 5 20 23 4

Ft = TLFCt - TLFCt - 1
Land Use, Land-Use Change, and Forestry 7-59

from grass, leaves, and branches to calculate the total landfill 

C stock in 2006, yielding a value of 234.4 million metric tons 

(as shown in Table 7-45). In exactly the same way total net 

flux is calculated for forest C and harvested wood products, 

the total net flux of landfill C for yard trimmings and food 

scraps for a given year (Table 7-43) is the difference in the 

landfill C stock for a given year and the stock in the preceding 

year. For example, the net change in 2006 shown in Table 

7-43 (2.9 Tg C) is equal to the stock in 2006 (234.4 Tg C) 

minus the stock in 2005 (231.5 Tg C).

When applying the C storage data reported by Barlaz 

(1998, 2005, 2008), an adjustment was made to the reported 

values so that a perfect mass balance on total C could be 

attained for each of the materials. There are four principal 

elements in the mass balance:

•	 Initial C content (ICC, measured),

•	 C output as CH4 (CH4-C, measured),

•	 C output as CO2 (CO2-C, not measured), and 

•	 Residual stored C (CS, measured).

In a simple system where the only C fates are CH4, 

CO2, and C storage, the following equation is used to attain 

a mass balance: 

 

The experiments by Barlaz and his colleagues (Barlaz 

1998, 2005; Eleazer et al. 1997) did not measure CO2 outputs 

in experiments. However, if the only decomposition is 

anaerobic, then CH4-C = CO2-C.48 Thus, the system should 

be defined by:

 

 

48The molar ratio of CH4 to CO2 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 CO2 (Barlaz et al. 1989). Given the predominance of carbohydrates, 

for all practical purposes, the overall ratio is 1:1.

The C outputs (= 2 × CH4-C + CS ) were less than 100 

percent of the initial C mass for food scraps, leaves, grass, 

and branches (75, 94, 86, and 90 percent, respectively). For 

these materials, it was assumed that the unaccounted for C 

had exited the experiment as CH4 and CO2, and no adjustment 

was made to the measured value of CS. The resulting C stocks 

are shown in Table 7-45. 

Uncertainty

The uncertainty analysis for landfilled yard trimmings 

and food scraps includes an evaluation of the effects of 

uncertainty for the following data and factors: disposal in 

landfills per year (tons of C), initial C content, moisture 

content, decomposition rate (half-life), and proportion of C 

stored. The C storage landfill estimates are also a function of 

the composition of the yard trimmings (i.e., the proportions 

of grass, leaves and branches in the yard trimmings mixture). 

There are respective uncertainties associated with each of 

these factors. 

A Monte Carlo (Tier 2) uncertainty analysis was applied 

to estimate the overall uncertainty of the sequestration 

estimate. The results of the Tier 2 quantitative uncertainty 

analysis are summarized in Table 7-46. Total yard trimmings 

and food scraps CO2 flux in 2006 was estimated to be between 

-19.1 and -6.0 Tg CO2 Eq. at a 95 percent confidence level (or 

19 of 20 Monte Carlo stochastic simulations). This indicates 

a range of -82 percent below to 43 percent above the 2006 

flux estimate of -10.5 Tg CO2 Eq. More information on the 

uncertainty estimates for Yard Trimmings and Food Scraps 

in Landfills is contained within the Uncertainty Annex.

CH4-C + CO2-C + CS = ICC

2 × CH4-C + CS = ICC

Table 7-45: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C)

Carbon Pool 1990 1995 2000 2001 2002 2003 2004 2005 2006

Yard Trimmings 156.9 180.2 192.9 195.2 197.6 199.5 201.2 203.0 204.9

Grass 15.8 17.7 18.3 18.5 18.6 18.8 18.8 19.0 19.1

Leaves 70.2 81.0 87.2 88.3 89.5 90.4 91.3 92.1 93.0

Branches 70.9 81.6 87.4 88.4 89.5 90.4 91.1 91.9 92.8

Food Scraps 17.9 20.6 24.1 25.0 25.8 26.6 27.5 28.5 29.5

Total Carbon Stocks 174.8 200.8 217.1 220.2 223.4 226.2 228.8 231.5 234.4
7-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

QA/QC and Verification

A QA/QC analysis was performed for data gathering 

and input, documentation, and calculation. 

Recalculations Discussion

The half lives of branches and food scraps were updated 

to be consistent with recommended values for food scraps 

and woody materials provided in IPCC (2006) for analyzing 

landfill CH4. 

The current Inventory uses detailed unpublished backup 

data (Schneider 2007, 2008) for some years not previously 

shown in the MSW Facts and Figures reports (EPA 1999, 

2003, 2005, 2005a, 2006, 2007). These data included updated 

generation, materials recovery, composting, combustion, 

and discard data for 1960, 1970, 1980, and 1990 through 

2006. These newly available data allowed several previous 

interpolations to be replaced with the complete time series 

of data used to create the MSW Facts and Figures reports 

(EPA 1999, 2003, 2005, 2005a, 2006, 2007).

Additionally, updated experimental results from Barlaz 

(2008) were incorporated. These data changed several 

estimates for leaves: the initial C content (from 42 percent 

to 46 percent), the proportion of initial C stored (from 72 

percent to 85 percent), and the C output from CH4, used 

as a check on the mass balance, The proportion of initial 

C stored for grass also changed (from 68 percent to 53 

percent). These changes are the result of a re-interpretation 

of the experimental results, which combined a sample of the 

material being tested (e.g., leaves) with a sample of “seed” 

material—decomposed refuse—containing microorganisms 

capable of anaerobic decomposition. Because the seed 

material also contained some organic C, the mass balance had 

to be adjusted to net out the influence of the C from the seed. 

The re-interpretation of the results accounts for differences 

in the rates of decomposition of the seed along compared to 

the seed plus the material being tested.

These changes resulted in an average 7 percent increase 

in stocks across the time series and a 13 percent change in the 

stocks for 2005 compared to the previous Inventory.

Planned Improvements 

Future work may evaluate the potential contribution 

of inorganic C, primarily in the form of carbonates, to 

landfill sequestration, as well as the consistency between 

the estimates of C storage described in this chapter and 

the estimates of landfill CH4 emissions described in the 

Waste chapter.

Table 7-46: Tier 2 Quantitative Uncertainty Estimates for CO2 Flux from Yard Trimmings and Food Scraps in Landfills 

(Tg CO2 Eq. and Percent)

2006 Flux Estimate Uncertainty Range Relative to Flux Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower 

Bound

Upper 

Bound

Lower 

Bound

Upper 

Bound

Yard Trimmings and Food Scraps CO2 (10.5) (19.1) (6.0) -82% +43%

Note: Parentheses indicate negative values or net C sequestration.

a

 Range of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Waste 8-1

8. Waste 

Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 8-1). Landfills 

accounted for approximately 23 percent of total U.S. anthropogenic methane (CH4) emissions in 2006,1

the second largest contribution of any CH4 source in the United States. Additionally, wastewater treatment 

and composting of organic waste accounted for approximately 4 percent and less than 1 percent of U.S. CH4 emissions, 

respectively. Nitrous oxide (N2O) emissions from the discharge of wastewater treatment effluents into aquatic environments 

were estimated, as were N2O emissions from the treatment 

process itself. N2O emissions from composting were also 

estimated. Together, these waste activities account for less 

than 3 percent of total U.S. N2O emissions. Nitrogen oxide 

(NOx), carbon monoxide (CO), and non-CH4 volatile organic 

compounds (NMVOCs) are emitted by waste activities, and 

are addressed separately at the end of this chapter. A summary 

of greenhouse gas emissions from the Waste chapter is 

presented in Table 8-1 and Table 8-2.

Overall, in 2006, waste activities generated emissions 

of 161.0 Tg CO2 Eq., or just over 2 percent of total U.S. 

greenhouse gas emissions.

1Landfills 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.

Table 8-1: Emissions from Waste (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 172.9 169.1 146.7 143.0 145.5 151.0 148.1 149.0 151.1

Landfills 149.6 144.0 120.8 117.6 120.1 125.6 122.6 123.7 125.7

Wastewater Treatment 23.0 24.3 24.6 24.2 24.1 23.9 24.0 23.8 23.9

Composting 0.3 0.7 1.3 1.3 1.3 1.5 1.6 1.6 1.6

N2O 6.6 7.7 8.9 9.2 9.0 9.3 9.6 9.7 9.9

Domestic Wastewater Treatment 6.3 6.9 7.6 7.8 7.6 7.7 7.8 8.0 8.1

Composting 0.4 0.8 1.4 1.4 1.4 1.6 1.7 1.7 1.8

Total 179.6 176.8 155.6 152.1 154.5 160.3 157.7 158.7 161.0

Note: Totals may not sum due to independent rounding.

Figure 8-1

2006 Waste Chapter Greenhouse Gas Emission Sources

Tg CO2 Eq.

0 50 100 150

Waste as a Portion

of all Emissions 

2.3% Composting

Landfills

Wastewater

Treatment
8-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

8.1. Landfills (IPCC Source 

Category 6A1)

In 2006, landfill CH4 emissions were approximately 

125.7 Tg CO2 Eq. (5,985 Gg of CH4), representing the second 

largest source of CH4 emissions in the United States, behind 

enteric fermentation. Emissions from municipal solid waste 

(MSW) landfills, which received about 64 percent of the total 

solid waste generated in the United States, accounted for 

about 88 percent of total landfill emissions, while industrial 

landfills accounted for the remainder. Approximately 1,800 

operational landfills exist in the United States, with the 

largest landfills receiving most of the waste and generating 

the majority of the CH4 (BioCycle 2006, adjusted to include 

missing data from five states).

After being placed in a landfill, waste (such as paper, 

food scraps, and yard trimmings) is initially decomposed 

by aerobic bacteria. After the oxygen has been depleted, the 

remaining waste is available for consumption by anaerobic 

bacteria, which break down organic matter into substances 

such as cellulose, amino acids, and sugars. These substances 

are further broken down through fermentation into gases and 

short-chain organic compounds that form the substrates for 

the growth of methanogenic bacteria. These CH4-producing 

anaerobic bacteria convert the fermentation products 

into stabilized organic materials and biogas consisting 

of approximately 50 percent carbon dioxide (CO2) and 

50 percent CH4, by volume.2 Significant CH4 production 

typically begins one or two years after waste disposal in a 

landfill and continues for 10 to 60 years or longer.

2The percentage of CO2 in biogas released from a landfill may be smaller 

because some CO2 dissolves in landfill water (Bingemer and Crutzen 1987). 

Additionally, less than 1 percent of landfill gas is typically composed of 

non-CH4 volatile organic compounds (NMVOCs).

From 1990 to 2006, net CH4 emissions from landfills 

decreased by approximately 16 percent (see Table 8-3 and 

Table 8-4), with small increases occurring in some interim 

years. This downward trend in overall emissions is the 

result of increases in the amount of landfill gas collected 

and combusted,3 which has more than offset the additional 

CH4 generation resulting from an increase in the amount of 

municipal solid waste landfilled. 

Methane emissions from landfills are a function of several 

factors, including: (1) the total amount of waste in MSW 

landfills, which is related to total waste landfilled annually; 

(2) the characteristics of landfills receiving waste (i.e., 

composition of waste-in-place, size, climate); (3) the amount 

of CH4 that is recovered and either flared or used for energy 

purposes; and (4) the amount of CH4 oxidized in landfills 

instead of being released into the atmosphere. The estimated 

annual quantity of waste placed in MSW landfills increased 

from about 209 Tg in 1990 to 307 Tg in 2006, an increase of 

47 percent (see Annex 3.14). During this period, the estimated 

CH4 recovered and combusted from MSW landfills increased 

as well. In 1990, for example, approximately 888 Gg of CH4

were recovered and combusted (i.e., used for energy or flared) 

from landfills, while in 2006, 5,958 Gg CH4 was combusted. 

In 2006, an estimated 26 new landfill gas-to-energy (LFGTE) 

projects and 41 new flares began operation, resulting in a 

4.4 percent increase in the quantity of CH4 recovered and 

combusted from 2005 levels.

Over the next several years, the total amount of municipal 

solid waste generated is expected to increase as the U.S. 

population continues to grow. The percentage of waste 

3The CO2 produced from combusted landfill CH4 at landfills is not counted 

in national inventories as it is considered part of the natural C cycle of 

decomposition.

Table 8-2: Emissions from Waste (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 8,235 8,052 6,983 6,808 6,928 7,190 7,053 7,096 7,197

Landfills 7,124 6,859 5,751 5,598 5,720 5,981 5,838 5,890 5,985

Wastewater Treatment 1,096 1,158 1,173 1,150 1,148 1,140 1,141 1,131 1,136

Composting 15 35 60 60 61 69 74 75 75

N2O 21 25 29 30 29 30 31 31 32

Domestic Wastewater Treatment 20 22 24 25 25 25 25 26 26

Composting 1 3 4 5 5 5 6 6 6

Note: Totals may not sum due to independent rounding.
Waste 8-3

landfilled, however, may decline due to increased recycling 

and composting practices. In addition, the quantity of CH4 that 

is recovered and either flared or used for energy purposes is 

expected to continue to increase as a result of 1996 federal 

regulations that require large municipal solid waste landfills to 

collect and combust landfill gas (see 40 CFR Part 60, Subpart 

Cc 2005 and 40 CFR Part 60, Subpart WWW 2005), voluntary 

programs encouraging CH4 recovery and use such as EPA’s 

Landfill Methane Outreach Program (LMOP), and federal and 

state incentives that promote renewable energy (e.g. tax credits, 

low interest loans, and Renewable Portfolio Standards). 

Methodology 

A detailed description of the methodology used to 

estimate CH4 emissions from landfills can be found in 

Annex 3.14.

CH4 emissions from landfills were estimated to equal 

the CH4 produced from municipal solid waste landfills, plus 

the CH4 produced by industrial landfills, minus the CH4

recovered and combusted, minus the CH4 oxidized before 

being released into the atmosphere: 

 

 

 

The methodology for estimating CH4 emissions from 

municipal solid waste landfills is based on the first order 

decay model described by the Intergovernmental Panel on 

Climate Change (IPCC 2006). Values for the CH4 generation 

potential (L0) and rate constant (k) were obtained from an 

analysis of CH4 recovery rates for a database of 52 landfills 

and from published studies of other landfills (RTI 2004;

Table 8-3: CH4 Emissions from Landfills (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

MSW Landfills 172.6 191.8 206.9 211.4 225.8 225.8 233.7 241.2 248.6

Industrial Landfills 12.3 13.6 15.2 15.5 15.8 15.8 16.0 16.1 16.2

Recovered

Gas-to-Energy (13.6) (23.4) (51.3) (56.1) (57.2) (57.2) (60.6) (62.2) (65.3)

Flared (5.1) (22.0) (36.7) (40.3) (44.9) (44.9) (52.7) (57.7) (59.8)

Oxidizeda (16.6) (16.0) (13.4) (13.1) (14.0) (14.0) (13.6) (13.7) (14.0)

Total 149.6 144.0 120.8 117.6 120.1 125.6 122.6 123.7 125.7

Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.

a

 Includes oxidation at both municipal and industrial landfills.

Table 8-4: CH4 Emissions from Landfills (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

MSW Landfills 8,219 9,132 9,854 10,068 10,367 10,754 11,127 11,486 11,838

Industrial Landfills 585 649 725 739 746 754 760 760 770

Recovered

Gas-to-Energy (646) (1,113) (2,441) (2,670) (2,721) (2,723) (2,888) (2,961) (3,110)

Flared (242) (1,047) (1,747) (1,917) (2,037) (2,140) (2,512) (2,748) (2,848)

Oxidizeda (792) (762) (639) (622) (636) (665) (649) (654) (665)

Total 7,124 6,859 5,751 5,598 5,720 5,981 5,838 5,890 5,985

Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.

a

 Includes oxidation at both municipal and industrial landfills.

CH4,Solid Waste = [CH4,MSW + CH4,ind – R] – Ox

where,

CH4,Solid Waste = CH4 emissions from solid waste

CH4,MSW = CH4 generation from municipal solid 

waste landfills,

CH4,ind = CH4 generation from industrial landfills, 

R = CH4 recovered and combusted, and

Ox = CH4 oxidized from MSW and 

industrial landfills before release to 

the atmosphere.
8-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

EPA 1998; SWANA 1998; Peer, Thorneloe, and 

Epperson 1993). The rate constant was found to increase 

with average annual rainfall; consequently, values of k were 

developed for 3 ranges of rainfall. The annual quantity of 

waste placed in landfills was apportioned to the 3 ranges of 

rainfall based on the percent of the U.S. population in each of 

the 3 ranges, and historical census data were used to account 

for the shift in population to more arid areas over time. For 

further information, see Annex 3.14.

National landfill waste generation and disposal data for 

1989 through 2006 were obtained from BioCycle (2006). 

Because BioCycle does not account for waste generated 

in U.S. territories, waste generation for the territories was 

estimated using population data obtained from the U.S. 

Census Bureau (2007) and national per capita solid waste 

generation from BioCycle (2006). Estimates of the annual 

quantity of waste landfilled for 1960 through 1988 were 

obtained from EPA’s Anthropogenic Methane Emissions in 

the United States, Estimates for 1990: Report to Congress 

(EPA 1993) and an extensive landfill survey by the EPA’s 

Office of Solid Waste in 1986 (EPA 1988). Although waste 

placed in landfills in the 1940s and 1950s contributes very 

little to current CH4 generation, estimates for those years 

were included in the first order decay model for completeness 

in accounting for CH4 generation rates and are based on the 

population in those years and the per capita rate for land 

disposal for the 1960s. For calculations in this Inventory, 

wastes landfilled prior to 1980 were broken into two groups: 

wastes disposed in landfills (MCF of 1) and those disposed 

in dumps (MCF of 0.6). Please see the Recalculations 

Discussion section and Annex 3.14 for more details.

The estimated landfill gas recovered per year was based 

on updated data collected from vendors of flaring equipment, 

a database of landfill gas-to-energy (LFGTE) projects 

compiled by LMOP (EPA 2007), and a database maintained 

by the Energy Information Administration (EIA) for the 

voluntary reporting of greenhouse gases (EIA 2007). The 

three databases were carefully compared to identify landfills 

that were in two or all three of the databases to avoid doublecounting reductions. Based on the information provided by the 

EIA and flare vendor databases, the CH4 combusted by flares 

in operation from 1990 to 2006 was estimated. This quantity 

likely underestimates flaring because these databases do not 

have information on all flares in operation. Additionally, the 

EIA and LMOP databases provided data on landfill gas flow 

and energy generation for landfills with LFGTE projects. If 

a landfill in the EIA database was also in the LMOP and/or 

the flare vendor database, the emissions avoided were based 

on the EIA data because landfill owners or operators reported 

the amount recovered based on measurements of gas flow 

and concentration, and the reporting accounted for changes 

over time. If both flare data and LMOP recovery data were 

available for any of the remaining landfills (i.e., not in the 

EIA database), then the emissions recovery was based on 

the LMOP data, which provides reported landfill-specific 

data on gas flow for direct use projects and project capacity 

(i.e., megawatts) for electricity projects. The flare data, on 

the other hand, only provided a range of landfill gas flow for 

a given flare size. Given that each LFGTE project is likely 

to also have a flare, double counting reductions from flares 

and LFGTE projects in the LMOP database was avoided by 

subtracting emissions reductions associated with LFGTE 

projects for which a flare had not been identified from the 

emissions reductions associated with flares. 

A destruction efficiency of 99 percent was applied to 

CH4 recovered to estimate CH4 emissions avoided. The 

value for efficiency was selected based on the range of 

efficiencies (98 to 100 percent) recommended for flares in 

EPA’s AP-42 Compilation of Air Pollutant Emission Factors, 

Chapter 2.4 (EPA 1998) efficiencies used to establish new 

source performance standards (NSPS) for landfills, and in 

recommendations for closed flares used in LMOP.

Emissions from industrial landfills were estimated from 

activity data for industrial production, waste disposal factors, 

and the first order decay model. As over 99 percent of the 

organic waste placed in industrial landfills originated from 

the food processing (meat, vegetables, fruits) and pulp and 

paper industries, estimates of industrial landfill emissions 

focused on these two sectors (EPA 1993). The amount of CH4

oxidized by the landfill cover at both municipal and industrial 

landfills was assumed to be ten percent of the CH4 generated 

that is not recovered (IPCC 2006, Mancinelli and McKay 

1985, Czepiel et al. 1996). To calculate net CH4 emissions, 

both CH4 recovered and CH4 oxidized were subtracted from 

CH4 generated at municipal and industrial landfills. 
Waste 8-5

Uncertainty

Several types of uncertainty are associated with the 

estimates of CH4 emissions from landfills. The primary 

uncertainty concerns the characterization of landfills. 

Information is not available on two fundamental factors 

affecting CH4 production: the amount and composition of 

waste placed in every landfill for each year of its operation. 

The approach used here assumes that the CH4 generation 

potential and the rate of decay that produces CH4, as 

determined from several studies of CH4 recovery at landfills, 

are representative of U.S. landfills.

Additionally, the approach used to estimate the 

contribution of industrial wastes to total CH4 generation 

introduces uncertainty. Aside from uncertainty in estimating 

CH4 generation potential, uncertainty exists in the estimates 

of oxidation by cover soils. There is also uncertainty in 

the estimates of methane that is recovered by flaring and 

energy projects. The IPCC default value of 10 percent for 

uncertainty in recovery estimates was used in the uncertainty 

analysis when metering was in place (for about 64 percent 

of the methane estimated to be recovered). For flaring 

without metered recovery data (approximately 34 percent 

of the methane estimated to be recovered), a much higher 

uncertainty of approximately 50 percent was used (e.g., 

when recovery was estimated as 50 percent of the flare’s 

design capacity).

N2O emissions from the application of sewage sludge 

on landfills are not explicitly modeled as part of greenhouse 

gas emissions from landfills. N2O emissions from sewage 

sludge applied to landfills would be relatively small because 

the microbial environment in landfills is not very conducive 

to the nitrification and denitrification processes that result 

in N2O emissions. Furthermore, the 2006 IPCC Guidelines 

(IPCC 2006) did not include a methodology for estimating 

N2O emissions from solid waste disposal sites “because they 

are not significant.” Therefore, any uncertainty or bias caused 

by not including N2O emissions from landfills is expected 

to be minimal.

The results of the Tier 2 quantitative uncertainty analysis 

are summarized in Table 8-5. Landfill CH4 emissions in 2006 

were estimated to be between 74.7 and 168.5 Tg CO2 Eq., 

which indicates a range of 41 percent below to 34 percent 

above the 2006 emission estimate of 125.7 Tg CO2 Eq.

QA/QC and Verification

A QA/QC analysis was performed for data gathering 

and input, documentation, and calculation. A primary 

focus of the QA/QC checks was to ensure that methane 

recovery estimates were not double-counted. Both manual 

and electronic checks were made to ensure that emission 

avoidance from each landfill was calculated only in one of 

the three databases. The primary calculation spreadsheet is 

tailored from the IPCC waste model and has been verified 

previously using the original, peer-reviewed IPCC waste 

model. All model input values were verified by secondary 

QA/QC review.

Recalculations Discussion

In developing the 1990 to 2006 Inventory report, the 

proportion of waste disposed of in managed landfills versus 

open dumps prior to 1980 was re-evaluated. Based on the 

historical data presented by Minz et al. (2003), a timeline 

was developed for the transition from the use of open dumps 

for solid waste disposed to the use of managed landfills. 

Based on this timeline, 6 percent of the waste that was land 

disposed in 1940 was disposed of in managed landfills and 

94 percent was managed in open dumps. Between 1940 

and 1980, the fraction of waste land disposed transitioned 

towards managed landfills until 100 percent of the waste 

was disposed of in managed landfills in 1980. Although this 

timeline was based primarily on information about MSW 

disposal, a similar trend in disposal practices was expected 

Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Landfills CH4 125.7 74.7 168.5 -41% +34%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
8-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

for industrial landfills; therefore, this same time line was 

applied to the industrial landfills. For wastes disposed of 

in dumps, a methane correction factor (MCF) of 0.6 was 

used based on the recommended IPCC default value for 

uncharacterized land disposal (IPCC 2006); this MCF is 

equivalent to assuming 50 percent of the open dumps are 

deep and 50 percent are shallow. The recommended IPCC 

default value for the MCF for managed landfills of 1 was used 

for the managed landfills (IPCC 2006). This recalculation 

reduced the MSW landfill CH4 generation rate for the 1990 to 

2005 time series by 5.6 percent, and it reduced the industrial 

landfill CH4 generation rate for the 1990 to 2005 time series 

by 1.8 percent.

Another significant recalculation, which affected 

estimates of CH4 recovery, was associated with updating the 

EIA, LMOP, and flare vendor databases. The estimates of 

gas recovery by LFGTE projects for 1990 to 2005 increased 

because more landfills with operational gas recovery projects 

were identified and included in the LFGTE database. 

However, many of these LFGTE projects did not have a 

corresponding flare in the flare vendor database. The gas 

recovery and combustion estimates from the flare database 

were adjusted by deducting the recovery and combustion 

estimates associated with these LFGTE projects with 

unmatched flares from the flare combustion totals. This 

results in a decrease in the estimates for flaring. For the 1990 

to 2005 time series, the recalculation resulted in an average 

increase of 1.4 percent in the amount of CH4 recovered and 

destroyed by gas-to-energy projects and a net decrease of 

0.5 percent in the estimated CH4 emissions.

Overall, these recalculations resulted in an average 

decrease of 7.8 percent in emissions across the time series 

relative to the previous Inventory. 

Planned Improvements

For future Inventories, additional efforts will be made 

to improve the estimates of the amount of waste placed in 

MSW landfills. Improvements to the flare database will be 

investigated, and an effort will be made to identify additional 

landfills that have flares. 

8.2. Wastewater Treatment (IPCC 

Source Category 6B)

Wastewater treatment processes can produce 

anthropogenic CH4 and N2O emissions. Wastewater from 

domestic (municipal sewage) and industrial sources is 

treated to remove soluble organic matter, suspended 

solids, pathogenic organisms, and chemical contaminants. 

Treatment may either occur on site, most commonly through 

septic systems or package plants,4 or off site at centralized 

treatment systems. Centralized wastewater treatment systems 

may include a variety of processes, ranging from lagooning 

to advanced tertiary treatment technology for removing 

nutrients. In the United States, approximately 21 percent of 

domestic wastewater is treated in septic systems or other onsite systems, while the rest is collected and treated centrally 

(U.S. Census Bureau 2007b). 

Soluble organic matter is generally removed using 

biological processes in which microorganisms consume the 

organic matter for maintenance and growth. The resulting 

biomass (sludge) is removed from the effluent prior to 

discharge to the receiving stream. Microorganisms can 

4 Package plants are treatment plants assembled in a factory, skid mounted, 

and transported to the treatment site.

CO2 emissions from the combustion or decomposition of 

biogenic materials (e.g., paper, wood products, and yard trimmings) 

grown on a sustainable basis are considered to mimic the closed 

loop of the natural carbon cycle—that is, they return to the 

atmosphere CO2 that was originally removed by photosynthesis. 

In contrast, CH4 emissions from landfilled waste occur due to the 

man-made anaerobic conditions conducive to CH4 formation that 

exist in landfills, and are consequently included in this Inventory. 

Depositing wastes of biogenic origin in landfills causes the 

removal of carbon from its natural cycle between the atmosphere 

and biogenic materials. As empirical evidence shows, some of 

these wastes degrade very slowly in landfills, and the carbon they 

contain is effectively sequestered in landfills over a period of time 

(Barlaz 1998, 2005). Estimates of carbon removals from landfilling 

of forest products, yard trimmings, and food scraps are further 

described in the Land Use, Land-Use Change, and Forestry chapter, 

based on methods presented in IPCC (2003) and IPCC (2006). 

Box 8-1: Biogenic Emissions and Sinks of Carbon
Waste 8-7

biodegrade soluble organic material in wastewater under 

aerobic or anaerobic conditions, where the latter condition 

produces CH4. During collection and treatment, wastewater 

may be accidentally or deliberately managed under anaerobic 

conditions. In addition, the sludge may be further biodegraded 

under aerobic or anaerobic conditions. The generation of N2O 

may also result from the treatment of domestic wastewater 

during both nitrification and denitrification of the nitrogen 

present, usually in the form of urea, ammonia, and proteins. 

These compounds are converted to nitrate (NO3) through 

the aerobic process of nitrification. Denitrification occurs 

under anoxic conditions (without free oxygen), and involves 

the biological conversion of nitrate into dinitrogen gas (N2). 

N2O can be an intermediate product of both processes, but 

is more often associated with denitrification.

The principal factor in determining the CH4 generation 

potential of wastewater is the amount of degradable organic 

material in the wastewater. Common parameters used to 

measure the organic component of the wastewater are the 

Biochemical Oxygen Demand (BOD) and Chemical Oxygen 

Demand (COD). Under the same conditions, wastewater 

with higher COD (or BOD) concentrations will generally 

yield more CH4 than wastewater with lower COD (or BOD) 

concentrations. BOD represents the amount of oxygen that 

would be required to completely consume the organic matter 

contained in the wastewater through aerobic decomposition 

processes, while COD measures the total material available 

for chemical oxidation (both biodegradable and nonbiodegradable). Because BOD is an aerobic parameter, it 

is preferable to use COD to estimate CH4 production. The 

principal factor in determining the N2O generation potential 

of wastewater is the amount of N in the wastewater.

In 2006, CH4 emissions from domestic wastewater 

treatment were 16.0 Tg CO2 Eq. (762 Gg). Emissions 

gradually increased from 1990 through 1997, but have 

decreased since 1998 due to decreasing percentages of 

wastewater being treated in anaerobic systems, including 

reduced use of on-site septic systems and central anaerobic 

treatment systems. In 2006, CH4 emissions from industrial 

wastewater treatment were estimated to be 7.9 Tg CO2

Eq. (374 Gg). Industrial emission sources have increased 

across the time series through 1999 and then fluctuated up 

and down in keeping with production changes associated 

with the treatment of wastewater from the pulp and paper 

manufacturing, meat and poultry processing, fruit and 

vegetable processing, and starch-based ethanol production 

industries.5 Table 8-6 and Table 8-7 provide CH4 and N2O 

emission estimates from domestic and industrial wastewater 

treatment. With respect to N2O, the United States identifies 

two distinct sources for N2O emissions from domestic 

wastewater: emissions from centralized wastewater treatment 

processes, and emissions from effluent from centralized 

treatment systems that has been discharged into aquatic 

environments. The 2006 emissions of N2O from centralized 

wastewater treatment processes and from effluent were 

estimated to be 0.3 Tg CO2 Eq. (1 Gg) and 7.8 Tg CO2 Eq. 

(25 Gg), respectively. Total N2O emissions from domestic 

wastewater were estimated to be 8.1 Tg CO2 Eq. (26 Gg). 

N2O emissions from wastewater treatment processes 

gradually increased across the time series as a result of 

increasing U.S. population and protein consumption. 

5 Other industrial sectors include organic chemicals, starch production, 

alcohol refining, creameries, and textiles; however, emissions from these 

sectors are considered to be insignificant.

Table 8-6: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 23.0 24.3 24.6 24.2 24.1 23.9 24.0 23.8 23.9

Domestic 16.4 16.9 16.8 16.6 16.5 16.4 16.3 16.2 16.0

Industrial* 6.6 7.4 7.8 7.5 7.6 7.6 7.7 7.6 7.9

N2O 6.3 6.9 7.6 7.8 7.6 7.7 7.8 8.0 8.1

Domestic 6.3 6.9 7.6 7.8 7.6 7.7 7.8 8.0 8.1

Total 29.3 31.2 32.2 32.0 31.7 31.6 31.8 31.8 32.0

* Industrial activity includes the pulp and paper manufacturing, meat and poultry processing, fruit and vegetable processing, and starch-based ethanol 

production industries.

Note: Totals may not sum due to independent rounding.
8-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Methodology

Domestic Wastewater CH4 Emission Estimates

Domestic wastewater CH4 emissions originate from 

both septic systems and from centralized treatment systems, 

such as publicly owned treatment works (POTWs). Within 

these centralized systems, CH4 emissions can arise from 

aerobic systems that are not well managed, anaerobic 

systems (anaerobic lagoons and facultative lagoons), and 

from anaerobic digesters when the captured biogas is not 

completely combusted. CH4 emissions from septic systems 

were estimated by multiplying the total BOD5 produced in 

the United States by the percent of wastewater treated in 

septic systems (21 percent), the maximum CH4 producing 

capacity for domestic wastewater (0.60 kg CH4/kg BOD), 

and the CH4 correction factor (MCF) for septic systems 

(0.5). CH4 emissions from POTWs were estimated by 

multiplying the total BOD5 produced in the United States 

by the percent of wastewater treated centrally (79 percent), 

the relative percentage of wastewater treated by aerobic and 

anaerobic systems, the relative percentage of wastewater 

facilities with primary treatment, the percentage of BOD5

treated after primary treatment (67.5 percent), the maximum 

CH4-producing capacity of domestic wastewater (0.6), and 

the relative MCFs for aerobic (zero or 0.3) and anaerobic 

(0.8) systems. CH4 emissions from anaerobic digesters were 

estimated by multiplying the amount of biogas generated 

by wastewater sludge treated in anaerobic digesters by the 

proportion of CH4 in digester biogas (0.65), the density of 

CH4 (662 g CH4/m3 CH4), and the destruction efficiency 

associated with burning the biogas in an energy/thermal 

device (0.99).6

 The methodological equations are: 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

6Anaerobic digesters at wastewater treatment plants generated 798 Gg 

CH4 in 2006, 790 Gg of which was combusted in flares or energy devices 

(assuming a 99% destruction efficiency).

Table 8-7: CH4 and N2O Emissions from Domestic and Industrial Wastewater Treatment (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 1,096 1,158 1,173 1,150 1,148 1,140 1,141 1,131 1,136

Domestic 782 804 802 792 786 780 775 770 762

Industrial* 314 355 371 358 362 360 366 361 374

N2O 20 22 24 25 25 25 25 26 26

Domestic 20 22 24 25 25 25 25 26 26

* Industrial activity includes the pulp and paper manufacturing, meat and poultry processing, fruit and vegetable processing, and starch-based ethanol 

production industries.

Note: Totals may not sum due to independent rounding.

Emissions from Septic Systems = A

= (% onsite) × (total BOD5 produced) × (Bo) ×

(MCF-septic) × 1/10^6

Emissions from Centrally Treated Aerobic Systems = B

= [(% collected) × (total BOD5 produced) × (% aerobic) × 

(% aerobic w/out primary) + (% collected) ×

(total BOD5 produced) × (% aerobic) ×

(% aerobic w/primary) ×

(1-% BOD removed in prim. treat.)] ×

(% operations not well managed) × (Bo) ×

(MCF-aerobic_not_well_man.) × 1/10^6

Emissions from Centrally Treated Anaerobic Systems = C

= [(% collected) × (total BOD5 produced) ×

(% anaerobic) × (% anaerobic w/out primary) + 

(% collected) × (total BOD5 produced) ×

(% anaerobic) × (% anaerobic w/primary) ×

(1-%BOD removed in prim. treat.)] × (Bo) ×

(MCF-anaerobic) × 1/10^6

Emissions from Anaerobic Digesters = D

= [(POTW_flow_AD) × (digester gas)/(per capita flow)] ×

conversion to m3 × (FRAC_CH4) _ (365.25) ×

(density of CH4) × (1-DE) × 1/10^9

Total CH4 Emissions (Gg) = A + B + C + D

where,

% onsite = Flow to septic systems/total flow

% collected = Flow to POTWs/total flow
Waste 8-9

U.S. population data were taken from the U.S. Census 

Bureau International Database (U.S. Census 2007a) and 

include the populations of the United States, American 

Samoa, Guam, Northern Mariana Islands, Puerto Rico, and 

the Virgin Islands. Table 8-8 presents U.S. population and 

total BOD5 produced for 1990 through 2006. The proportions 

of domestic wastewater treated onsite versus at centralized 

treatment plants were based on data from the 1989, 1991, 

1993, 1995, 1997, 1999, 2001, 2003, and 2005 American 

Housing Surveys conducted by the U.S. Census Bureau (U.S. 

Census 2007b), with data for intervening years obtained by 

linear interpolation. The wastewater flow to aerobic systems 

and anaerobic systems, and the wastewater flow to POTWs 

that have anaerobic digesters were obtained from the 1992, 

1996, 2000, and 2004 Clean Watershed Needs Survey (EPA 

1992, 1996, 2000, and 2004a).7 Data for intervening years 

were obtained by linear interpolation. The BOD5 production 

rate (0.09 kg/capita/day) for domestic wastewater was 

obtained from Metcalf and Eddy (1991 and 2003). The CH4

emission factor (0.6 kg CH4/kg BOD5) and the MCFs were 

taken from IPCC (2006). The CH4 destruction efficiency, 99 

percent, was selected based on the range of efficiencies (98 to 

100 percent) recommended for flares in AP-42 Compilation 

of Air Pollutant Emission Factors, Chapter 2.4 (EPA 1998), 

efficiencies used to establish new source performance 

7Aerobic and anaerobic treatment were determined based on unit processes 

in use at the facilities. Because the list of unit processes became more 

extensive in the 2000 and 2004 surveys, the criteria used to identify 

aerobic and anaerobic treatment differ slightly across the time series. 

Once facilities were identified as aerobic or anaerobic, they were separated 

by whether or not they had anaerobic digestion in place. Once these 

classifications were determined, the flows associated with facilities in 

each category were summed. 

% aerobic = Flow to aerobic systems/total flow 

to POTWs

% anaerobic = Flow to anaerobic systems/total 

flow to POTWs

% aerobic 

w/out 

primary = Percent of aerobic systems that do 

not employ primary treatment

% aerobic 

w/primary = Percent of aerobic systems that 

employ primary treatment

% BOD 

removed in 

prim. treat. = 32.5 %

% operations 

not well 

managed = Percent of aerobic systems that are 

not well managed and in which 

Some anaerobic degradation occurs

% anaerobic 

w/out 

primary = Percent of anaerobic systems that 

do not employ primary treatment

% anaerobic 

w/primary = Percent of anaerobic systems that 

employ primary treatment

Total BOD5

produced = kg BOD/capita/day × U.S. 

population × 365.25 days/yr

Bo = Maximum CH4-producing capacity 

for domestic wastewater (0.60 kg 

CH4/kg BOD)

MCF-septic = CH4 correction factor for septic 

systems (0.5)

1/10^6 = Conversion factor, kg to Gg

MCF-aerobic_

not_

well_man. = CH4 correction factor for aerobic 

systems that are not well managed 

(0.3) 

MCFanaerobic = CH4 correction factor for anaerobic 

systems (0.8)

DE = CH4 destruction efficiency from 

flaring or burning in engine (0.99 

for enclosed flares)

POTW_

flow_AD = Wastewater influent flow to POTWs 

that have anaerobic digesters (gal)

digester gas = Cubic feet of digester gas produced 

per person per day (1.0 ft3/person/

day) (Metcalf and Eddy 1991)

per capita 

flow = Wastewater flow to POTW per 

person per day (100 gal/person/day)

conversion 

to m3 = Conversion factor, ft3 to m3

(0.0283)

FRAC_CH4 = Proportion CH4 in biogas (0.65)

density of 

CH4 = 662 (g CH4/m3 CH4)

1/10^9 = Conversion factor, g to Gg
8-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

standards (NSPS) for landfills, and in recommendations 

for closed flares used by LMOP. The cubic feet of digester 

gas produced per person per day (1.0 ft3/person/day) and 

the proportion of CH4 in biogas (0.65) come from Metcalf 

and Eddy (1991). The wastewater flow to a POTW (100 

gal/person/day) was taken from the Great Lakes-Upper 

Mississippi River Board of State and Provincial Public Health 

and Environmental Managers, “Recommended Standards for 

Wastewater Facilities (Ten-State Standards)” (2004). 

Industrial Wastewater CH4 Emission Estimates

CH4 emissions estimates from industrial wastewater 

were developed according to the methodology described in 

IPCC (2006). Industry categories that are likely to produce 

significant CH4 emissions from wastewater treatment were 

identified. High volumes of wastewater generated and a 

high organic wastewater load were the main criteria. The 

top four industries that meet these criteria are pulp and paper 

manufacturing; meat and poultry processing; vegetables, 

fruits, and juices processing; and starch-based ethanol 

production. Table 8-9 contains production data for these 

industries.

CH4 emissions from these categories were estimated by 

multiplying the annual product output by the average outflow, 

the organics loading (in COD) in the outflow, the percentage 

of organic loading assumed to degrade anaerobically, and the 

emission factor. Ratios of BOD:COD in various industrial 

wastewaters were obtained from EPA (1997a) and used to 

estimate COD loadings. The Bo value used for all industries 

is the IPCC default value of 0.25 kg CH4/kg COD (IPCC 

2006). The methodological equation is: 

 

 

 

 

 

 

 

 

 

Table 8-8: U.S. Population (Millions) and Domestic 

Wastewater BOD5 Produced (Gg)

Year Population BOD5

1990 254 8,350

1995 271 8,895

2000 287 9,419

2001 289 9,509

2002 292 9,597

2003 295 9,685

2004 297 9,774

2005 300 9,864

2006 303 9,954

Source: U.S. Census Bureau (2006a); Metcalf & Eddy 1991 and 2003.

Table 8-9: U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg)

Year Pulp and Paper

Meat 

(Live Weight Killed)

Poultry 

(Live Weight Killed)

Vegetables, 

Fruits and Juices Ethanol

1990 128.9 27.3 14.6 38.7 2.7

1995 140.9 30.8 18.9 46.9 4.2

2000 142.8 32.1 22.2 50.9 4.9

2001 134.3 31.6 22.8 45.0 5.3

2002 132.7 32.7 23.5 47.7 6.4

2003 131.9 32.3 23.7 44.8 8.4

2004 136.4 31.2 24.4 47.8 10.2

2005 131.4 31.4 25.1 43.3 11.7

2006 137.4 32.5 25.5 42.6 14.5

CH4 (industrial wastewater) = 

P × W × COD × TA × Bo × MCF

where,

CH4

(industrial 

wastewater) = Total CH4 emissions from industrial 

wastewater (kg/year)

P = Industry output (metric tons/year)

W = Wastewater generated (m3/metric 

ton of product)

COD = Organics loading in wastewater 

(kg /m3)

TA = Percent of wastewater treated 

anaerobically on site 

Bo = Maximum CH4 producing potential 

of industrial wastewater (default 

value of 0.25 kg CH4/kg COD)
Waste 8-11

Wastewater treatment for the pulp and paper industry 

typically includes neutralization, screening, sedimentation, 

and flotation/hydrocycloning to remove solids (World Bank 

1999, Nemerow and Dasgupta 1991). Secondary treatment 

(storage, settling, and biological treatment) mainly consists 

of lagooning. In determining the percent that degrades 

anaerobically, both primary and secondary treatment were 

considered. In the United States, primary treatment is focused 

on solids removal, equalization, neutralization, and color 

reduction (EPA 1993b). The vast majority of pulp and paper 

mills with on-site treatment systems use mechanical clarifiers 

to remove suspended solids from the wastewater. About 10 

percent of pulp and paper mills with treatment systems use 

settling ponds for primary treatment and these are more 

likely to be located at mills that do not perform secondary 

treatment (EPA 1993b). However, because the vast majority 

of primary treatment operations at U.S. pulp and paper mills 

use mechanical clarifiers, and less than 10 percent of pulp 

and paper wastewater is managed in primary settling ponds 

that are not expected to have anaerobic conditions, negligible 

emissions are assumed to occur during primary treatment.

Approximately 42 percent of the BOD passes on to 

secondary treatment, which consists of activated sludge, 

aerated stabilization basins, or non-aerated stabilization 

basins. No anaerobic activity is assumed to occur in 

activated sludge systems or aerated stabilization basins 

(note: although IPCC recognizes that some CH4 can be 

emitted from anaerobic pockets, they recommend an MCF 

of zero). However, about 25 percent of the wastewater 

treatment systems used in the United States are non-aerated 

stabilization basins. These basins are typically 10 to 25 feet 

deep. These systems are classified as anaerobic deep lagoons 

(MCF = 0.8). Therefore, the pulp and paper CH4 emission 

calculation is:

 

 

 

 

 

 

 

 

 

 

A time series of CH4 emissions for 1990 through 2001 

was developed based on production figures reported in the 

Lockwood-Post Directory (Lockwood-Post 2002). Published 

data from the American Forest and Paper Association, data 

published by Paper Loop, and other published statistics were 

used to estimate production for 2002 through 2006 (Pulp and 

Paper 2005, 2006 and monthly reports from 2003 through 

2006; Paper 360o 2007). The overall wastewater outflow 

was estimated to be 85 m3

/metric ton, and the average BOD 

concentrations in raw wastewater was estimated to be 0.4 g 

BOD/liter (EPA 1997b, EPA 1993b, World Bank 1999).

The meat and poultry processing industry makes 

extensive use of anaerobic lagoons in sequence with 

screening, fat traps and dissolved air flotation when treating 

wastewater on site. About 33 percent of meat processing 

operations (EPA 2002) and 25 percent of poultry processing 

operations (U.S. Poultry 2006) perform on-site treatment in 

anaerobic lagoons. The IPCC default Bo of 0.25 kg CH4/

kg COD and default MCF of 0.8 for anaerobic lagoons 

were used to estimate the CH4 produced from these on-site 

treatment systems. Production data, in carcass weight and 

live weight killed for the meat and poultry industry, were 

obtained from the USDA Agricultural Statistics Database and 

the Agricultural Statistics Annual Reports (USDA 2007a). 

Data collected by EPA’s Office of Water provided estimates 

for wastewater flows into anaerobic lagoons: 5.3 and 12.5 

m3/metric ton for meat and poultry production (live weight 

killed), respectively (EPA 2002). The loadings are 2.8 and 

1.5 g BOD/liter for meat and poultry, respectively. 

Treatment of wastewater from fruits, vegetables, and 

juices processing includes screening, coagulation/settling and 

biological treatment (lagooning). The flows are frequently 

Methane = Production × Flow × BOD × 42% ×

COD:BOD Ratio × %TA × Bo × MCF

where,

Production = metric tons of pulp, paper, and 

paperboard production

Flow = cubic meters of wastewater generated per ton production

BOD = BOD concentration in influent 

(4000 mg/L)

42% = Percent of BOD entering secondary 

treatment

COD:BOD = COD to BOD ratio (for pulp and 

paper, COD:BOD = 2)

%TA = estimated percent of wastewater 

treated anaerobically on site (25%)

Bo = maximum methane producing 

capacity (0.25 mg CH4/mg COD)

MCF = methane conversion factor for 

anaerobic deep lagoons (0.80)

MCF = CH4 correction factor, indicating the 

extent to which the organic content (measured as COD) degrades anaerobically
8-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

seasonal, and robust treatment systems are preferred for 

on-site treatment. Effluent is suitable for discharge to the 

sewer. This industry is likely to use lagoons intended for 

aerobic operation, but the large seasonal loadings may 

develop limited anaerobic zones. In addition, some anaerobic 

lagoons may also be used (Nemerow and Dasgupta 1991). 

Consequently, 5 percent of these wastewater organics are 

assumed to degrade anaerobically. The IPCC default Bo of 

0.25 kg CH4/kg COD and default MCF of 0.8 for anaerobic 

treatment were used to estimate the CH4 produced from these 

on-site treatment systems. The USDA National Agricultural 

Statistics Service (USDA 2007a) provided production data 

for potatoes, other vegetables, citrus fruit, non-citrus fruit, 

and grapes processed for wine. Outflow and BOD data, 

presented in Table 8-10, were obtained from EPA (1974) 

for potato, citrus fruit, and apple processing, and from EPA 

(1975) for all other sectors. 

Ethanol, or ethyl alcohol, is produced primarily for use 

as a fuel component, but is also used in industrial applications 

and in the manufacture of beverage alcohol. Ethanol can be 

produced from the fermentation of sugar-based feedstocks 

(e.g., molasses and beets), starch- or grain-based feedstocks 

(e.g., corn, sorghum, and beverage waste), and cellulosic 

biomass feedstocks (e.g., agricultural wastes, wood, and 

bagasse). Ethanol can also be produced synthetically from 

ethylene or hydrogen and carbon monoxide. However, 

synthetic ethanol comprises only about 2 percent of ethanol 

production, and although the Department of Energy predicts 

cellulosic ethanol to greatly increase in the coming years, 

currently it is only in an experimental stage in the United 

States. According to the Renewable Fuels Association, 82 

percent of ethanol production facilities use corn as the sole 

feedstock and 7 percent of facilities use a combination of 

corn and another starch-based feedstock. The fermentation 

of corn is the principal ethanol production process in the 

United States and is expected to increase for at least the next 

6 years, and potentially more; therefore, emissions associated 

with wastewater treatment at starch-based ethanol production 

facilities were estimated (ERG 2006).

Ethanol is produced from corn (or other starch-based 

feedstocks) primarily by two methods: wet milling and dry 

milling. Historically, the majority of ethanol was produced 

by the wet milling process, but now the majority is produced 

by the dry milling process. The wastewater generated at 

ethanol production facilities is handled in a variety of 

ways. Dry milling facilities often combine the resulting 

evaporator condensate with other process wastewaters, 

such as equipment wash water, scrubber water, and boiler 

blowdown and anaerobically treat this wastewater using 

various types of digesters. Wet milling facilities often treat 

their steepwater condensate in anaerobic systems followed by 

aerobic polishing systems. Wet milling facilities may treat the 

stillage (or processed stillage) from the ethanol fermentation/

distillation process separately or together with steepwater 

and/or wash water. CH4 generated in anaerobic digesters is 

commonly collected and either flared or used as fuel in the 

ethanol production process (ERG 2006).

Available information was compiled from the industry 

on wastewater generation rates, which ranged from 1.25 

gallon per gallon ethanol produced (for dry milling) to 

10 gallons per gallon ethanol produced (for wet milling) 

(Ruocco 2006a,b; Merrick 1998; Donovan 1996; and NRBP 

2001). COD concentrations were also found to be about 

3 g/L (Ruocco 2006a; Merrick 1998; White and Johnson 

2003). The amount of wastewater treated anaerobically 

was estimated, along with how much of the methane is 

recovered through the use of biomethanators (ERG 2006). 

CH4 emissions were then estimated as follows:

 

 

 

 

 

 

 

 

 

 

Table 8-10: Wastewater Flow (m3/ton) and BOD 

Production (g/L) for U.S. Vegetables, Fruits and Juices 

Production

Commodity Wastewater Outflow 

(m3/ton)

BOD

(g/L)

Vegetables

Potatoes 10.27 1.765

Other Vegetables 8.86 0.813

Fruit

Apples 3.66 1.371

Citrus 10.11 0.317

Non-citrus 12.42 1.204

Grapes (for wine) 2.78 1.831

Methane = [Production × Flow × COD × 3.785 ×

% TA × Bo × MCF × % Not Recovered] + 

[Production × Flow × 3.785 × COD × %TA ×

Bo × MCF × (% Recovered) × (1-DE)] × 1/10^9
Waste 8-13

A time series of CH4 emissions for 1990 through 2006 

was developed based on production data from the Renewable 

Fuels Association (RFA 2006).

Domestic Wastewater N2O Emission Estimates

N2O emissions from domestic wastewater (wastewater 

treatment) were estimated using the IPCC (2006) methodology, 

including calculations that take into account N removal with 

sewage sludge, non-consumption and industrial wastewater 

N, and emissions from advanced centralized wastewater 

treatment plants:

• In the United States, a certain amount of N is removed 

with sewage sludge, which is applied to land, incinerated 

or landfilled (NSLUDGE). The N disposal into aquatic 

environments is reduced to account for the sewage 

sludge application.8

• The IPCC methodology uses annual, per capita protein 

consumption (kg protein/[person-year]). This number is 

likely to underestimate the amount of protein entering 

the sewer or septic system. Food (waste) that is not 

consumed is often washed down the drain, as a result 

of the use of garbage disposals. Also, bath and laundry 

water can be expected to contribute to N loadings. 

As a result, a factor of 1.4 for non-consumption N is 

introduced for each year in the Inventory.9 Furthermore, 

a significant quantity of industrial wastewater (N) is 

co-discharged with domestic wastewater. To account 

for this, a factor of 1.25 is used.10

• Small amounts of gaseous nitrogen oxides are formed as 

byproducts in the conversion of nitrate to N gas in anoxic 

biological treatment systems. Approximately 7 g N2O 

is generated per capita per year if wastewater treatment 

includes intentional nitrification and denitrification 

(Scheehle and Doorn 2001) Analysis of the 2000 

CWNS shows there are 88 treatment plants in the United 

States, serving a population of 2.6 million people, with 

denitrification as one of their unit operations. Based on 

an emission factor of 7 grams/capita/year, approximately 

17.5 metric tons of additional N2O may have been 

emitted via denitrification in 2000. Similar analyses 

were completed for each year in the Inventory using data 

from CWNS on the amount of wastewater in centralized 

systems treated in denitrification units. Plants without 

intentional nitrification/denitrification are assumed to 

generate 3.2 g N2O per capita per year. 

8The methodology for estimating the quantity of sewage sludge N not 

entering aquatic environments is described in Annex 3.11.

9 Metcalf & Eddy (1991) provide a typical influent nitrogen concentration 

of 40 mg/L Total Kjeldahl Nitrogen (TKN) for average wastewater from 

residences, which includes bathwater, laundry, and the use of garbage 

disposals. The factor for non-consumptive protein was estimated based 

on wastewater treated in 1990, the percent of population serviced by 

centralized treatment systems, and the per capita TKN loading, resulting 

in a factor of 1.4.

10 The type, composition, and quantity of this co-discharged wastewater 

vary greatly between municipalities. Metcalf & Eddy (1991) provide 

a range of influent nitrogen concentrations of 20 to 85 mg/L TKN 

(average 55) for combined residential and industrial wastewater, while 

residential wastewater loading was roughly estimated at 40 mg TKN/L 

(see previous footnote). Until better data become available, the amount 

of N in wastewater is increased by 10 mg/L to account for industrial codischarge (factor of 1.25).

where,

Production = gallons ethanol produced 

(wet milling or dry milling)

Flow = gallons wastewater generated per 

gallon ethanol produced (1.25 dry 

milling, 10 wet milling)

COD = COD concentration in influent 

(3 g/l)

3.785 = conversion, gallons to liters

% TA = percent of wastewater treated 

anaerobically (for dry milling 

operations, this value is estimated 

separately for facilities using 

biomethanators with 100% recovery 

and facilities using other anaerobic 

systems)

Bo = maximum methane producing 

capacity (0.25 g CH4/g COD)

MCF = methane conversion factor (0.8 for 

anaerobic systems)

% Recovered = percent of wastewater treated in 

system with emission recovery

% Not 

Recovered = 1 - percent of wastewater treated in 

system with emission recovery

DE = destruction efficiency of recovery 

system (99%)

1/10^9 = conversion factor, g to Gg
8-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

With the modifications described above, N2O emissions 

from domestic wastewater were estimated using the 

following methodology:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

U.S. population data were taken from the U.S. Census 

Bureau International Database (U.S. Census 2007a) and 

include the populations of the United States, American 

Samoa, Guam, Northern Mariana Islands, Puerto Rico, 

and the Virgin Islands. The fraction of the U.S. population 

using wastewater treatment plants is based on data from 

the 1989, 1991, 1993, 1995, 1997, 1999, 2001, 2003, and 

2005 American Housing Survey (U.S. Census 2007b). Data 

for intervening years were obtained by linear interpolation. 

The emission factor (EF1) to estimate emissions from 

wastewater treatment was taken from IPCC (2006). Data 

on annual per capita protein intake were provided by U.S. 

Department of Agriculture Economic Research Service 

(ERS 2006b). Protein consumption data for 2005 and 2006 

were extrapolated from data for 1990 through 2004. Table 

8-11 presents the data for U.S. population and average 

protein intake. An emission factor to estimate emissions 

from effluent (EF3) has not been specifically estimated for 

the United States, thus the default IPCC value (0.005 kg 

N2O-N/kg sewage-N produced) was applied. The fraction 

of N in protein (0.16 kg N/kg protein) was also obtained 

from IPCC (2006). Sludge generation was obtained from 

Table 8-11: U.S. Population (Millions) and Average 

Protein Intake [kg/(person-year)]

Year Population Protein

1990 254 38.7

1995 271 39.8

2000 287 41.3

2001 289 42.0

2002 292 40.9

2003 295 40.9

2004 297 41.3

2005 300 41.7

2006 303 41.9

Source: U.S. Census Bureau 2006a, USDA ERS 2006b.

N2OTOTAL = N2OPLANT + N2OEFFLUENT

N2OPLANT = N2ONIT/DENIT + N2OWOUT NIT/DENIT

N2ONIT/DENIT = [(USPOPND) × EF2 × FIND-COM] × 1/10^9

N2OWOUT NIT/DENIT = {[(USPOP × WWTP) - USPOPND ×

FIND-COM] × EF1} × 1/10^9

N2OEFFLUENT = {[(USPOP × Protein × FNPR × FNON-CON ×

FIND-COM) - NSLUDGE] × EF3 × 44/28} × 1/10^6

where,

N2OTOTAL = Annual emissions of N2O (kg)

N2OPLANT = N2O emissions from centralized 

wastewater treatment plants (kg)

N2ONIT/DENIT = N2O emissions from centralized 

wastewater treatment plants with 

nitrification/denitrification (kg)

N2OWOUT NIT/DENIT= N2O emissions from centralized 

wastewater treatment plants 

without nitrification/denitrification (kg)

N2OEFFLUENT = N2O emissions from wastewater 

effluent discharged to aquatic 

environments (kg)

USPOP = U.S. population

USPOPND = U.S. population that is served by 

biological denitrification (from 

CWNS)

WWTP = Fraction of population using 

WWTP (as opposed to septic 

systems)

EF1 = Emission factor (3.2 g N2O/

person-year)

EF2 = Emission factor (7 g N2O/

person-year)

Protein = Annual per capita protein consumption (kg/person/year)

FNPR = Fraction of N in protein, default = 

0.16 (kg N/kg protein)

FNON-CON = Factor for non-consumed protein 

added to wastewater (1.4)

FIND-COM = Factor for industrial and commercial co-discharged protein into 

the sewer system (1.25)

NSLUDGE = N removed with sludge, kg N/yr

EF3 = Emission factor (0.005 kg N2O 

-N/kg sewage-N produced)

44/28 = Molecular weight ratio of N2O to 

N2
Waste 8-15

EPA (1999) for 1988, 1996, and 1998 and from Beecher et 

al. (2007) for 2004. Intervening years were interpolated, and 

estimates for 2005 and 2006 were forecasted from the rest 

of the time series. An estimate for the N removed as sludge 

(NSLUDGE) was obtained by determining the amount of sludge 

disposed by incineration, by land application (agriculture or 

other), through surface disposal, in landfills, or through ocean 

dumping. In 2006, 263 Tg N was removed with sludge.

Uncertainty

The overall uncertainty associated with both the 

2006 CH4 and N2O emission estimates from wastewater 

treatment and discharge was calculated using the IPCC 

Good Practice Guidance Tier 2 methodology (2000). 

Uncertainty associated with the parameters used to estimate 

CH4 emissions include that of numerous input variables 

used to model emissions from domestic wastewater, 

and wastewater from pulp and paper production, meat 

and poultry processing, fruits and vegetable processing, 

and ethanol production. Uncertainty associated with the 

parameters used to estimate N2O emissions include that 

of sewage sludge disposal, total U.S. population, average 

protein consumed per person, fraction of N in protein, 

non-consumption N factor, emission factors per capita 

and per mass of sewage-N, and for the percentage of total 

population using centralized wastewater treatment plants. 

The results of this Tier 2 quantitative uncertainty 

analysis are summarized in Table 8-12. CH4 emissions from 

wastewater treatment were estimated to be between 15.0 and 

35.2 Tg CO2 Eq. at the 95 percent confidence level (or in 19 

out of 20 Monte Carlo Stochastic Simulations). This indicates 

a range of approximately 37 percent below to 48 percent 

above the 2006 emissions estimate of 23.9 Tg CO2 Eq. N2O 

emissions from wastewater treatment were estimated to be 

between 1.8 and 16.2 Tg CO2 Eq., which indicates a range 

of approximately 78 percent below to 100 percent above the 

actual 2006 emissions estimate of 8.1 Tg CO2 Eq. 

QA/QC and Verification 

A QA/QC analysis was performed on activity data, 

documentation, and emission calculations. This effort 

included a Tier 1 analysis, including the following checks:

• Checked for transcription errors in data input;

• Ensured references were specified for all activity data 

used in the calculations;

• Checked a sample of each emission calculation used for 

the source category;

• Checked that parameter and emission units were 

correctly recorded and that appropriate conversion 

factors were used;

• Checked for temporal consistency in time series input 

data for each portion of the source category;

• Confirmed that estimates were calculated and reported 

for all portions of the source category and for all 

years;

• Investigated data gaps that affected emissions estimates 

trends; and

• Compared estimates to previous estimates to identify 

significant changes.

All transcription errors identified were corrected. The 

QA/QC analysis did not reveal any systemic inaccuracies or 

incorrect input values.

Recalculations Discussion

The 2006 estimates for CH4 emissions from domestic 

wastewater include one major methodological refinement 

Table 8-12: Tier 2 Quantitative Uncertainty Estimates for CH4 and N2O Emissions from Wastewater Treatment 

(Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimatea

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Wastewater Treatment CH4 23.9 15.0 35.2 -37% +48%

Domestic CH4 16.0 7.9 26.6 -51% +66%

Industrial CH4 7.9 4.5 12.8 -43% +62%

Domestic Wastewater 

Treatment N2O 8.1 1.8 16.2 -78% +100%

a

 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
8-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

and one major data change. First, for centralized wastewater 

treatment systems, CH4 emissions were estimated based on 

the total BOD5 available for biological treatment rather than 

the total BOD5 entering wastewater treatment plants. Metcalf 

and Eddy (1991) estimate that 25–40 percent of BOD5 at 

aerobic and anaerobic plants is removed through primary 

sedimentation, meaning that not all of the BOD5 entering 

treatment plants has the potential to generate methane during 

biological treatment. This change resulted in a decrease of 

methane emissions from centrally treated anaerobic systems 

of 20 percent, and an overall reduction in methane emissions 

of 4.5 to 5.5 percent. The major data adjustment for the 

current Inventory estimates involved the adjustment of the 

1995 AHS data (US Census Bureau 2007b) that indicates 

the percent of wastewater treated onsite versus the percent 

collected. The previous Inventory indicated a total percent 

of wastewater treated onsite and collected of 97.6 percent 

for 1995, while all other years had a total of approximately 

99.5 percent. Reevaluation of the 1995 AHS data resulted 

in an updated total percent of 99.5 percent.

For industrial wastewater, the 2006 estimates include a 

change in calculation methodology for pulp and paper, and 

the inclusion of wastewater emissions from U.S. starch-based 

ethanol production. First, the types of primary treatment in 

place at pulp and paper operations were evaluated and it 

was concluded that due to the majority of operations using 

mechanical clarifiers, negligible emissions of CH4 occur 

during primary treatment. The estimate of BOD treated 

anaerobically during secondary treatment was also updated 

based on the number of operations expected to have nonaerated stabilization basins. These systems were reclassified 

as anaerobic deep lagoons, and CH4 emissions were revised. 

These changes resulted in a decrease in emissions from pulp 

and paper wastewater treatment of 18.5 percent across the 

time series.

Next, emissions associated with ethanol production were 

estimated, as described earlier. The addition of this industrial 

sector increased industrial wastewater emission estimates by 

0.4 to 0.9 percent across the time series.

Flow and BOD data for fruits and vegetable processing 

wastewater were updated to reflect commodity-specific data, 

which had minimal impact on the emissions. Overall, the CH4

emission estimates for wastewater treatment are on average 

6 percent lower than the previous Inventory.

For N2O emissions from domestic wastewater, one 

major data source adjustment was made along with two 

minor changes to account for co-discharged industrial and 

commercial wastewater and to update the values used for 

the nitrogen composition of sludge. The current Inventory 

utilizes protein consumption data from the U.S. Department of 

Agriculture Economic Research Service (USDA 2006b). The 

previous Inventory report used UN FAO protein consumption 

data. The protein data changed on average approximately 

one percent for each year in the time series. The current 

Inventory estimates also apply a factor for co-discharged 

industrial and commercial wastewater to the emission 

factors for direct N2O emissions from centralized wastewater 

treatment plants. This resulted in a N2O emission factor from 

centralized treatment plants that have intentional nitrification/

denitrification unit operations of 8.75 g N2O/person-year 

(7 g N2O/person-year × 1.25) and a N2O emission factor 

from centralized wastewater treatment plants that do not 

have intentional nitrification/denitrification unit operations 

of 4 g N2O/person-year (3.2 g N2O/person-year × 1.25). In 

addition, the nitrogen composition of sludge was updated to 

3.9 percent, representing an average N composition, rather 

than the previous value of 3.3 percent which represented a 

median value. The sludge generation estimates across the 

time series changed slightly based on the inclusion of a new 

reference for sludge generation in 2004.

Overall, emissions from wastewater treatment and 

discharge (CH4 and N2O) decreased by an average of 

approximately 5 percent from the previous Inventory. 

Planned Improvements Discussion

The methodology to estimate CH4 emissions from 

domestic wastewater treatment currently utilizes estimates 

for the percentage of centrally treated wastewater that is 

treated by aerobic systems and anaerobic systems. These 

data come from the 1992, 1996, 2000, and 2004 CWNS. 

The designation of systems as aerobic or anaerobic could 

be further refined to differentiate aerobic systems with the 

potential to generate small amounts of CH4 (aerobic lagoons) 

versus other types of aerobic systems, and to differentiate 

between anaerobic systems to allow for the use of different 

MCFs for different types of anaerobic treatment systems. 

Currently it is assumed that all aerobic systems are well 

managed and produce no CH4, and that all anaerobic systems 

have an MCF of 0.8. Efforts to obtain better data reflecting 
Waste 8-17

emissions from various types of municipal treatment systems 

are currently being pursued.

Available data on wastewater treatment emissions at 

petroleum refineries will be reviewed to determine if this 

is a significant source to be included in future versions of 

the Inventory. 

With respect to estimating N2O emissions, the default 

emission factor for N2O from wastewater effluent has a high 

uncertainty. The IPCC recently updated this factor; however, 

future research may identify new studies that include updated 

data. The factor that accounts for non-sewage nitrogen in 

wastewater (bath, laundry, kitchen, industrial components) 

also has a high uncertainty. Obtaining data on the changes 

in average influent nitrogen concentrations to centralized 

treatment systems over the time series would improve the 

estimate of total N entering the system, which would reduce 

or eliminate the need for other factors for non-consumed 

protein or industrial flow. In addition there is uncertainty 

associated with the N2O emission factors for direct emissions 

from centralized wastewater treatment facilities. Efforts to 

gain greater confidence in these emission factors are currently 

being pursued.

8.3. Composting (IPCC Source 

Category 6D)

Composting of organic waste, such as food waste, garden 

(yard) and park waste and sludge, is common in the United 

States. Advantages of composting include reduced volume in 

the waste material, stabilization of the waste, and destruction 

of pathogens in the waste material. The end products of 

composting, depending on its quality, can be recycled as 

fertilizer and soil amendment, or be disposed in a landfill.

Composting is an aerobic process and a large fraction 

of the degradable organic carbon in the waste material 

is converted into carbon dioxide (CO2). Methane (CH4) 

is formed in anaerobic sections of the compost, but it is 

oxidized to a large extent in the aerobic sections of the 

compost. Anaerobic sections are created in composting piles 

when there is excessive moisture or inadequate aeration (or 

mixing) of the compost pile. The estimated CH4 released 

into the atmosphere ranges from less than 1 percent to a few 

per cent of the initial carbon content in the material (IPCC 

2006). Composting can also produce emissions of nitrous 

oxide (N2O). The range of the estimated emissions varies 

from less than 0.5 percent to 5 percent of the initial nitrogen 

content of the material (IPCC 2006).

From 1990 to 2006, the amount of material composted 

in the United States has increased from 3,810 Gg to 18,852 

Gg, an increase of almost 400 percent. Emissions of CH4

and N2O from composting have increased by the same 

percentage (see Table 8-13 and Table 8-14). In 2006, CH4

emissions from composting were 1.6 Tg CO2 Eq. (75 Gg), 

and N2O emissions from composting were 1.8 Tg CO2 Eq. (6 

Gg). The wastes that are composted include primarily yard 

trimmings (grass, leaves, and tree and brush trimmings) and 

food scraps from residences and commercial establishments 

(such as grocery stores, restaurants, and school and factory 

cafeterias). The composting waste quantities reported here do 

not include backyard composting. The growth in composting 

is attributable primarily to two factors: (1) steady growth in 

population and residential housing and (2) state and local 

governments started enacting legislation that discouraged the 

disposal of yard trimmings in landfills. In 1992, 11 states and 

the District of Columbia had legislation in effect that banned 

or discouraged disposal of yard trimmings in landfills. In 

Table 8-13: CH4 and N2O Emissions from Composting (Tg CO2 Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 0.3 0.7 1.3 1.3 1.3 1.5 1.6 1.6 1.6

N2O 0.4 0.8 1.4 1.4 1.4 1.6 1.7 1.7 1.8

Total 0.7 1.5 2.6 2.7 2.7 3.1 3.3 3.3 3.3

Table 8-14: CH4 and N2O Emissions from Composting (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

CH4 15 35 60 60 61 69 74 75 75

N2O 1 3 4 5 5 5 6 6 6
8-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 8-16: Tier 1 Quantitative Uncertainty Estimates for Emissions from Composting (Tg CO2 Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate

Source Gas (Tg CO2 Eq.) (Tg CO2 Eq.) (%)

Lower Bound Upper Bound Lower Bound Upper Bound

Composting CH4, N2O 3.3 1.7 5.0 -50% +50%

Table 8-15: U.S. Waste Composted (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006

Waste Composted 3,810 8,682 14,923 15,014 15,187 17,309 18,570 18,643 18,852

Source: EPA 2005, EPA 2006, and EPA 2007.

2005, 21 states and the District of Columbia, representing 

about 50 percent of the nation’s population, had enacted such 

legislation (EPA 2006).

Methodology 

CH4 and N2O emissions from composting depend on 

factors such as the type of waste composted, the amount and 

type of supporting material (such as wood chips and peat) 

used, temperature, moisture content and aeration during the 

process.

The emissions shown in Table 8-13 and Table 8-14 were 

estimated using the IPCC default (Tier 1) methodology (IPCC 

2006), which is the product of an emission factor and the 

mass of organic waste composted (note: no CH4 recovery is 

expected to occur at composting operations): 

 

 

 

Estimates of the quantity of waste composted (M) are 

presented in Table 8-15. Estimates of the quantity composted 

for 1990, 1995, 2001, and 2002 were taken from EPA’s 

Municipal Solid Waste Generation, Recycling, and Disposal 

in the United States: Facts and Figures for 2003 (EPA 2005); 

estimates of the quantity composted for 2003 through 2005 

were taken from EPA’s Municipal Solid Waste In The United 

States: 2005 Facts and Figures (EPA 2006). The quantity 

composted estimate for 2006 was taken from the “2006 

MSW Characterization Data Tables” associated with EPA’s 

Municipal Solid Waste In The United States: 2006 Facts and 

Figures (EPA 2007). 

Uncertainty

The estimated uncertainty from the 2006 IPCC 

Guidelines is ±50 percent for the Tier 1 methodology. 

Emissions from composting in 2006 were estimated to be 

between 1.7 and 5.0 Tg CO2 Eq., which indicates a range 

of 50 percent below to 50 percent above the actual 2006 

emission estimate of 3.3 Tg CO2 Eq. (see Table 8-16). 

Recalculations Discussion

No recalculations were performed because this is the first 

year that composting has been included in the Inventory.

Planned Improvements

For future Inventories, additional efforts will be 

made to improve the estimates of CH4 and N2O emissions 

from composting. For example, a literature search may 

be conducted to determine if emission factors specific 

to various composting systems and composted materials 

are available. 

Ei = M × EFi

where,

Ei = CH4 or N2O emissions from composting, 

Gg CH4 or N2O,

M = mass of organic waste composted in Gg,

EFi = emission factor for composting, 4 g CH4/

kg of waste treated (wet basis) and 0.3 g 

N2O/kg of waste treated (wet basis), and

i = designates either CH4 or N2O.
Waste 8-19

8.4. Waste Sources of Indirect 

Greenhouse Gases

In addition to the main greenhouse gases addressed 

above, waste generating and handling processes are also 

sources of indirect greenhouse gas emissions. Total emissions 

of NOx, CO, and NMVOCs from waste sources for the years 

1990 through 2006 are provided in Table 8-17.

Methodology 

These emission estimates were obtained from preliminary 

data (EPA 2008), and disaggregated based on EPA (2003), 

which, in its final iteration, will be published on the National 

Emission Inventory (NEI) Air Pollutant Emission Trends 

web site. Emission estimates of these gases were provided by 

sector, using a “top down” estimating procedure—emissions 

were calculated either for individual sources or for many 

sources combined, using basic activity data (e.g., the amount 

of raw material processed) as an indicator of emissions. 

National activity data were collected for individual source 

categories from various agencies. Depending on the source 

category, these basic activity data may include data on 

production, fuel deliveries, raw material processed, etc.

Activity data were used in conjunction with emission 

factors, which relate the quantity of emissions to the activity. 

Emission factors are generally available from the EPA’s 

Compilation of Air Pollutant Emission Factors, AP-42 (EPA 

1997). The EPA currently derives the overall emission control 

efficiency of a source category from a variety of information 

sources, including published reports, the 1985 National Acid 

Precipitation and Assessment Program emissions inventory, 

and other EPA databases.

Uncertainty

No quantitative estimates of uncertainty were calculated 

for this source category. Uncertainties in these estimates, 

however, are primarily due to the accuracy of the emission 

factors used and accurate estimates of activity data.

Table 8-17: Emissions of NOx, CO, and NMVOC from Waste (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006

NOx + 1 2 2 2 2 2 2 2

Landfills + 1 2 2 2 2 2 2 2

Wastewater Treatment + + + + + + + + + 

Miscellaneousa + 1 + + + + + + + 

CO 1 2 8 8 7 7 7 7 7

Landfills 1 2 7 7 6 6 6 6 6

Wastewater Treatment + + 1 1 + + + + + 

Miscellaneousa + 1 + + + + + + + 

NMVOCs 673 731 119 122 115 114 112 111 110

Wastewater Treatment 57 61 23 23 22 22 21 21 21

Miscellaneousa 557 602 51 53 50 49 48 48 47

Landfills 58 68 46 46 44 43 43 42 42

a

 Miscellaneous includes TSDFs (Treatment, Storage, and Disposal Facilities under the Resource Conservation and Recovery Act [42 U.S.C. § 6924, 

SWDA § 3004]) and other waste categories.

Note: Totals may not sum due to independent rounding.

+ Does not exceed 0.5 Gg.
Other 9-1

9. Other

T

he United States does not report any greenhouse gas emissions under the Intergovernmental Panel on Climate 

Change (IPCC) “Other” sector.
Recalculations and Improvements 10-1

10. Recalculations and 

Improvements

E

ach year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S. Greenhouse 

Gas Emissions and Sinks, as attempts are made to improve both the analyses themselves, through the use of 

better methods or data, and the overall usefulness of the report. In this effort, the United States follows the 

Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance (IPCC 2000), which states, “It is good 

practice to recalculate historic emissions when methods are changed or refined, when new source categories are included 

in the national inventory, or when errors in the estimates are identified and corrected.”

The results of all methodology changes and historical data updates are presented in this section; detailed descriptions of 

each recalculation are contained within each source’s description contained in this report, if applicable. Table 10-1 summarizes 

the quantitative effect of these changes on U.S. greenhouse gas emissions and Table 10-2 summarizes the quantitative effect 

on U.S. sinks, both relative to the previously published U.S. Inventory (i.e., the 1990 through 2005 report). These tables 

present the magnitude of these changes in units of teragrams of carbon dioxide equivalents (Tg CO2 Eq). In addition to the 

changes summarized by the tables below, the following sources and gases were added to the current Inventory: 

•	 Carbon dioxide (CO2) emissions from Cropland Remaining Cropland, which include CO2 emissions from 

Agricultural Liming and Urea Fertilization;

•	 CO2 emissions from Petroleum Systems, which account for vented, fugitive, and process upset emissions sources 

from 29 activities for crude oil production field operations; and

•	 Methane (CH4) and nitrous oxide (N2O) emissions from Composting.

The Recalculations Discussion section of each source presents the details of each recalculation. In general, when 

methodological changes have been implemented, the entire time series (i.e., 1990 through 2005) has been recalculated to 

reflect the change, per IPCC (2000). Changes in historical data are generally the result of changes in statistical data supplied 

by other agencies.

The following emission sources, which are listed in descending order of absolute average annual change in emissions 

between 1990 and 2005, underwent some of the most important methodological and historical data changes. A brief summary 

of the recalculation and/or improvement undertaken is provided for each emission source.

•	 Agricultural Soil Management. Changes occurred as a result of incorporating state-level nitrogen (N) fertilizer application 

data for on-farm use as opposed to regional data, revising assumptions of manure N availability for land application, 

and revising DAYCENT parameterization for sorghum. Overall, changes resulted in an average annual decrease in N2O 

emissions from Agricultural Soil Management of 102.1 Tg CO2 Eq. (27.5 percent) for the period 1990 through 2005.
10-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

•	 Net CO2 Flux from Land Use, Land-Use Change, and 

Forestry. Forest Land Remaining Forest Land is the 

principal section contributing to the change in net CO2

flux from Land Use, Land-Use Change, and Forestry 

sector. The addition of newly available forest inventory 

data as well as some refinements in previously existing 

data were the principal factors contributing to the 

changes. Changes for the period 1990 through 2005, 

as compared to the estimates presented in the previous 

Inventory, are based on the cumulative effects of (1) 

incorporating and updating state and sub-state inventory 

data, and (2) including a portion of Alaskan forest for 

the first time. Minor refinements to the harvested wood 

product contribution included (1) shorter half-life for 

decay in dumps and (2) separation of decay in dumps 

from decay in landfills. Overall, these changes, in 

combination with adjustments in the other sources/sinks 

within the sector, resulted in an average annual increase 

in net flux of CO2 to the atmosphere from the Land Use, 

Land-Use Change, and Forestry sector of 20.1 Tg CO2

Eq. (2.5 percent) for the period 1990 through 2005.

•	 Landfills. For municipal solid waste landfills, changes 

to historical data resulted from revising the proportion 

of waste disposed of in managed landfills versus open 

dumps prior to 1980 and from using the recommended 

IPCC (2006) default value for uncharacterized 

land disposal. Additionally, the Energy Information 

Administration, Landfill Methane Outreach Program, 

and flare vendor databases were updated, affecting 

estimates of CH4 recovery. Overall, changes resulted 

in an average annual decrease in CH4 emissions from 

landfills of 11.4 Tg CO2 Eq. (7.8 percent) for the period 

1990 through 2005.

•	 Enteric Fermentation. Changes in the estimates of CH4

emissions resulting from Enteric Fermentation occurred 

as a result of (1) modifying the Cfi coefficient based on 

the revised IPCC equations (IPCC 2006), (2) updating 

the C factor in accordance with the revised IPCC 

Guidelines (IPCC 2006), (3) revising the equation for 

net energy of growth (NEg), (4) modifying the Cattle 

Enteric Fermentation Model to output at the state level 

and include more detailed data inputs, (5) incorporating 

revised FAO horse population estimates for 2001 

through 2005, and (6) including revised USDA estimates 

of swine population for 2005. Overall, changes resulted 

in an average annual increase in CH4 emissions from 

Enteric Fermentation of 11.4 Tg CO2 Eq. (9.9 percent) 

from 1990 through 2005.

•	 Substitution of Ozone Depleting Substances. An extensive 

review of chemical substitution trends, market sizes, 

growth rates, and charge sizes, together with input from 

industry representatives, resulted in updated assumptions 

for the Vintaging Model, which is used to calculate 

emissions from this category. These changes resulted in 

an average annual decrease in hydrofluorocarbon (HFC) 

emissions from the Substitution of Ozone Depleting 

Substances of 7.4 Tg CO2 Eq. (14.1 percent) for the period 

1990 through 2005. 

•	 Settlements Remaining Settlements. The data source 

used for N fertilization was updated for N2O Emissions 

from Settlement Soils. This fertilization data is based 

on county-scale non-farm application amounts from a 

USGS database. Overall, changes resulted in an average 

annual decrease in N2O emissions from Settlements 

Remaining Settlements of 4.4 Tg CO2 Eq. (78.1 percent) 

for the period 1990 through 2005.

•	 International Bunker Fuels. Historical activity data for 

aviation was revised for both U.S. and foreign carriers. 

In addition, distillate and residual fuel oil consumption 

by cargo or passenger carrying marine vessels from 2003 

through 2006 was revised. Overall, changes resulted 

in an average annual increase in CO2 emissions from 

International Bunker Fuels of 4.2 Tg CO2 Eq. (4.5 

percent) for the period 1990 through 2005.

•	 Manure Management. Several changes were made in 

this section. First, a major change in the N2O emission 

calculations is that emissions are now calculated from 

the “bottom-up” such that emissions are calculated for 

each animal group, manure management system, and 

state. These values are then summed to calculate the total 

greenhouse gas emissions from manure management 

in the United States. Second, dairy heifers and beef on 

feed now have one WMS distribution that represents 

managed and unmanaged systems, and emissions are 

calculated for each WMS using the EF for that system, 

and not using a state average EF. Third, the Inventory 

now includes indirect N2O emissions in the Manure 

Management Sector associated with N losses from 

volatilization of nitrogen as ammonia (NH3), nitrogen 

oxides (NOx), and leaching and runoff. Fourth, the days 
Recalculations and Improvements 10-3

per year used in N2O calculations was changed from 

365 to 365.25 to include leap years and to be consistent 

with the CH4 inventory calculations. Fifth, changes 

were also made to the current calculations involving 

animal population data. Overall, the changes resulted 

in an average annual increase in N2O emissions from 

Manure Management of 4.0 Tg CO2 Eq. (43.1 percent) 

for the period 1990 through 2005.

•	 Coal Mining. Three changes were made across the Coal 

Mining sector. First, recalculations of emissions avoided 

at three JWR coal mines in Alabama were performed 

as the mining company reported and filed data for 

1991 through 2005; data was also provided for 2006. 

Secondly, the gas content values assigned to each coal 

basin in the surface mine emissions component of the 

inventory were changed to reflect recent work carried 

out by U.S. EPA. Third, the conversion factor used 

to convert from mmcf of methane was updated to be 

consistent across the Inventory. Overall, the changes 

resulted in an average annual increase in CH4 emissions 

from Coal Mining of 3.7 Tg CO2 Eq. (6.2 percent) for 

the period 1990 through 2005.

•	 Ammonia Manufacture and Urea Consumption. CO2

emissions estimates were revised for all years to 

incorporate a new methodology that estimates urea 

production and consumption based on urea consumed 

as fertilizer. The new methodology allocated CO2

emissions associated with urea applied as fertilizer to 

the Land Use, Land-Use Change, and Forestry chapter. 

Overall, the changes resulted in an average annual 

decrease in CO2 emissions from Ammonia Manufacture 

and Urea Consumption of 3.0 Tg CO2 Eq. (15.8 percent) 

for the period 1990 through 2005.

Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005

CO2 6.8 9.5 (0.2) 3.1 15.8 0.1 (26.1) (15.2)

Fossil Fuel Combustion + 2.4 (7.8) (4.3) 7.6 (7.5) (31.7) (20.2)

Non-Energy Use of Fuels (0.1) + 0.4 0.5 0.5 0.4 (1.3) (3.3)

Natural Gas Systems + + + + + + (0.1) 1.3 

Cement Manufacture NC NC NC NC NC NC NC NC

Lime Manufacture 0.7 1.2 1.5 1.4 1.3 1.4 1.4 1.5 

Limestone and Dolomite Use NC NC NC NC NC + NC NC

Soda Ash Manufacture and Consumption NC NC NC NC NC NC NC NC

Carbon Dioxide Consumption + + + + + + + +

Municipal Solid Waste Combustion NC NC (0.4) (0.4) (0.1) (0.4) + (0.2)

Titanium Dioxide Production (0.1) (0.1) (0.2) (0.2) (0.2) (0.2) (0.2) (0.2)

Aluminum Production NC NC NC NC NC NC NC +

Iron and Steel Production 1.3 1.4 1.5 1.3 1.3 1.4 1.5 1.4 

Ferroalloy Production NC NC NC NC NC NC NC NC

Ammonia Manufacture and Urea Consumption (2.4) (2.7) (3.2) (3.4) (3.6) (3.7) (3.7) (3.5)

Phosphoric Acid Production NC NC NC NC NC NC NC +

Petrochemical Production NC NC NC NC NC NC NC (0.1)

Silicon Carbide Production and Consumption NC NC NC NC NC NC NC NC

Lead Production NC NC NC + + NC + +

Zinc Production NC NC NC NC NC NC NC NC

Cropland Remaining Croplanda 7.1 7.0 7.5 7.8 8.5 8.3 7.6 7.9 

Petroleum Systems 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 

Land-Use, Land-Use Change, and 

Forestry (Sink) (24.9) 53.5 83.1 17.3 (14.9) (49.0) (48.9) (50.2)

International Bunker Fuels + + NC NC NC 19.9 21.8 25.4 

Wood Biomass and Ethanol Consumption + + (1.0) NC NC (0.1) NC 20.9 
10-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2006

Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO2 Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005

CH4 (3.0) 0.2 10.6 11.1 13.8 10.1 5.3 0.4 

Stationary Combustion (0.6) (0.7) (0.7) (0.6) (0.6) (0.6) (0.6) (0.5)

Mobile Combustion + + (0.1) 0.1 (0.1) (0.1) (0.1) (0.1)

Coal Mining 2.2 0.6 4.5 4.8 4.8 4.8 5.2 4.7 

Abandoned Underground Coal Mines + + + + + + + +

Natural Gas Systems 0.2 (0.1) (0.1) (0.1) (0.1) (0.4) (5.1) (8.7)

Petroleum Systems (0.6) 0.9 2.4 2.8 3.1 3.4 3.3 (0.2)

Petrochemical Production NC NC NC NC NC NC NC NC

Silicon Carbide Production and Consumption NC NC NC NC NC NC NC NC

Iron and Steel Production NC NC + + + + NC NC

Ferroalloy Production NC NC NC NC NC NC NC NC

Enteric Fermentation 11.2 11.7 11.1 11.1 11.2 11.6 11.9 12.4 

Manure Management 0.1 0.1 0.1 0.1 0.1 0.2 0.3 0.5 

Rice Cultivation NC NC NC NC NC NC NC +

Field Burning of Agricultural Residues + + + + + + + +

Forest Land Remaining Forest Land (2.6) 0.7 5.0 3.4 6.0 0.7 + 0.7 

Landfills (11.4) (13.0) (11.1) (10.1) (10.3) (9.3) (9.5) (8.3)

Wastewater Treatment (1.8) (0.8) (1.8) (1.7) (1.7) (1.7) (1.7) (1.6)

Compostinga 0.3 0.7 1.3 1.3 1.3 1.5 1.6 1.6 

International Bunker Fuels NC NC NC NC NC + + +

N2O (98.6) (88.6) (113.9) (109.6) (103.1) (103.2) (91.7) (98.5)

Stationary Combustion 0.5 0.6 0.6 0.6 0.6 0.6 0.6 1.0 

Mobile Combustion (0.2) (0.2) (0.7) 0.2 (1.2) (1.4) (1.5) (1.7)

Adipic Acid Production 0.1 0.1 0.2 0.2 0.2 0.2 0.2 (0.1)

Nitric Acid Production (0.9) (1.0) (1.0) (0.8) (0.9) (1.4) (0.8) 0.1 

Manure Management 3.4 3.8 4.1 4.2 4.3 4.3 4.4 4.4 

Agricultural Soil Management (97.5) (88.6) (114.7) (112.0) (104.0) (102.9) (91.9) (99.9)

Field Burning of Agricultural Residues + + + + + + + +

Wastewater Treatment (0.1) + + 0.2 + (0.1) (0.1) +

N2O from Product Uses 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 

Municipal Solid Waste Combustion NC NC NC NC NC NC NC NC

Settlements Remaining Settlements (4.1) (4.3) (4.4) (4.0) (4.1) (4.3) (4.4) (4.3)

Forest Land Remaining Forest Land (0.3) 0.1 0.5 0.3 0.6 0.1 + 0.1 

Compostinga 0.4 0.8 1.4 1.4 1.4 1.6 1.7 1.7 

International Bunker Fuels NC NC NC NC NC 0.1 0.2 0.2 

HFCs, PFCs, and SF6 1.0 1.9 (11.1) (10.2) (9.9) (13.0) (13.2) (17.2)

Substitution of Ozone Depleting Substances + (3.7) (9.7) (10.6) (11.8) (13.5) (15.3) (18.0)

Aluminum Production NC NC NC NC NC NC + NC

HCFC-22 Production 1.4 5.9 (1.2) (0.1) 1.3 + 1.6 (0.7)

Semiconductor Manufacture NC + + + + + (0.4) 0.1 

Electrical Transmission and Distribution (0.4) (0.3) (0.1) (0.1) 0.1 + 0.3 0.7 

Magnesium Production and Processing + + + 0.5 0.6 0.6 0.6 0.6 

Net Change in Total Emissionsb (93.7) (77.0) (114.6) (105.7) (83.4) (106.0) (125.7) (130.5)

Percent Change -2.1% -0.4% -0.5% -1.4% -1.6% -2.5% -2.7% -2.8%

+ Absolute value does not exceed 0.05 Tg CO2 Eq. or 0.05 percent.

NC (No Change)

a

 New source category relative to previous inventory.

b

 Excludes net CO2 flux from Land Use, Land-Use Change, and Forestry, and emissions from International Bunker Fuels and Wood Biomass and Ethanol 

Consumption.

Note: Totals may not sum due to independent rounding.

(continued)
Recalculations and Improvements 10-5

Table 10-2: Revisions to Net Flux of CO2 to the Atmosphere from Land Use, Land-Use Change, and Forestry 

(Tg CO2 Eq.)

Component: Net CO2 Flux From Land Use, 

Land-Use Change, and Forestry 1990 1995 2000 2001 2002 2003 2004 2005

Forest Land Remaining Forest Land (23.1) 57.6 87.9 22.3 (9.2) (43.9) (44.1) (44.9)

Cropland Remaining Cropland (1.9) (2.0) (1.9) (2.0) (2.6) (2.2) (1.5) (1.6)

Land Converted to Cropland 6.1 2.1 2.1 2.1 2.1 2.1 2.1 2.1 

Grassland Remaining Grassland (2.0) 0.2 0.2 0.2 0.2 0.2 0.2 0.2 

Land Converted to Grassland 0.3 NC NC NC NC NC NC NC

Settlements Remaining Settlements (3.1) (3.7) (4.3) (4.4) (4.5) (4.6) (4.7) (4.8)

Other (1.1) (0.8) (1.0) (1.0) (1.0) (0.6) (0.9) (1.2)

Net Change in Total Flux (24.9) 53.5 83.1 17.3 (14.9) (49.0) (48.9) (50.2)

Percent Change -3.5% 6.5% 11.0% 2.3% -1.8% -6.0% -5.9% -6.1%

NC (No Change)

Note: Numbers in parentheses indicate a decrease in estimated net flux of CO2 to the atmosphere, or an increase in net sequestration.

Note: Totals may not sum due to independent rounding.
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How to Obtain Copies

You can electronically download this document on the U.S. EPA’s homepage at <http://www.epa.gov/climatechange/emissions/

usinventoryreport.html>. To request free copies of this report, call the National Service Center for Environmental Publications 

(NSCEP) at (800) 490–9198, or visit the web site above and click on “order online” after selecting an edition.

All data tables of this document are available for the full time series 1990 through 2006, inclusive, at the internet site 

mentioned above.

For Further Information

Contact Mr. Leif Hockstad, Environmental Protection Agency, (202) 343–9432, hockstad.leif@epa.gov.

Or Ms. Melissa Weitz, Environmental Protection Agency, (202) 343–9897, weitz.melissa@epa.gov.

For more information regarding climate change and greenhouse gas emissions, see the EPA web site at <http://www.epa.

gov/climatechange>.

Released for printing: April 15, 2008

Greenhouse Gases

The photos on the front and back cover of this report depict the types of greenhouse gases covered in the 1990–2006 Inventory. 

This Inventory presents emissions of carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, and sulfur 

hexafluoride. Of these, carbon dioxide is emitted in the largest quantities in the United States, so three of the pictures below 

depict sources and sinks of carbon dioxide, while sources of each of the other gases are represented in one picture each. 

Carbon Dioxide: Industrial Processes

Some industrial processes emit carbon dioxide as part of the process itself rather than from energy consumption. 

The two largest industrial emitters of carbon dioxide are iron and steel production and cement production, each 

accounting for 1 percent of all carbon dioxide emissions in 2006. Industrial emissions of this process-based 

carbon dioxide have decreased 15 percent since 1990.

Nitrous Oxide 

Nitrous oxide is approximately 310 times stronger than carbon dioxide at trapping heat, and is emitted from 

a variety of sources. In the United States, the largest source of this gas is agricultural soil management, 

responsible for approximately 72 percent of nitrous oxide emissions. Other significant sources include mobile 

and stationary combustion, adipic acid production, wastewater treatment, and manure management. Emissions 

of nitrous oxide have decreased 4 percent since 1990.

Hydrofluorocarbons (HFCs)

HFCs are a class of synthetic chemicals, primarily used as alternatives to ozone depleting substances being phased 

out under the Montreal Protocol. The uses of HFCs as a substitute include refrigeration and air-conditioning, foam 

blowing, aerosols, and solvents. In addition, some is emitted during the production of another fluorochemical, 

HCFC-22, and from semiconductor manufacture. Emissions of this gas have increased 237 percent since 1990, 

mostly due to the phaseout of ozone depleting substances over that period. HFCs generally have high global warming 

potentials compared to the naturally occurring greenhouse gases (carbon dioxide, methane, and nitrous oxide).

Sulfur Hexafluoride

Sulfur hexafluoride (SF6) is an inert synthetic chemical with a long atmospheric lifetime and a very high 

global warming potential, and is the most potent greenhouse gas the IPCC has evaluated. Because of its inert 

properties, it is used in electrical transmission and distribution as an insulator and interrupter, as a cover gas 

in magnesium production and processing, and in semiconductor manufacture. Emissions have decreased 47 

percent since 1990. 
Perfluorocarbons (PFCs) 

A family of synthetic fluorinated chemicals, PFCs are used in semiconductor manufacture and also emitted 

during the electrolysis phase of aluminum production. PFCs generally have long atmospheric lifetimes as well 

as very high global warming potentials, though they are emitted in relatively small quantities. Since 1990, 

PFC emissions have decreased 71 percent. 

Carbon Dioxide: Fossil Fuel Combustion

Carbon dioxide from the combustion of fossil fuels is the largest source of carbon dioxide emissions in the 

United States, accounting for 80 percent of all emissions in 2006. In order of decreasing size, the contributors to 

these emissions were electricity generation, and the transportation, industry, and the residential and commercial 

end-use sectors. Emissions from fossil fuel combustion have increased 19 percent since 1990.

Carbon Dioxide: Land Use, Land-Use Change, and Forestry

Forests and soils in the United States are a net sink for carbon dioxide, offsetting about 15 percent of 

emissions in 2006. The sink has increased by about 20 percent since 1990. Soils can also be a source of 

carbon dioxide: liming of agricultural soils and urea application to cropland both lead to a small amount 

of carbon dioxide emissions.

Methane

Methane is a greenhouse gas that is approximately 21 times stronger than carbon dioxide and is emitted from 

numerous sources in the United States. The four largest sources of methane are enteric fermentation in domestic 

animals, landfills, natural gas systems, and coal mining. Since 1990, emissions of methane have decreased 8 

percent in the United States.
United States

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EPA 430-R-08-005 April 2008

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