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

– 2006

# I nventory of 

# U.S. G reenho us e 

# G a s 

# E m issi on s and 

# S i nk s 

# : 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 MelissaWeitz. 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 SF 6 

### 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-1 2
ES .4. Other Information

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 5


## 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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1 0
1.5. Key Categories

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

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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1 3
1.8. Completeness

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1 5
1.9. Organization of Report

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1 5


## 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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1 7
2.3. Indirect Greenhouse Gas Emissions (CO, NO x 

### , NMVOCs, and SO 2 

### )

. . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2 8


## 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)

. . . . . . . . . . . . . . . 3-1 9
3.3. Stationary Combustion (excluding CO 2 

### ) (IPCC Source Category 1A)

. . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 4
3.4. Mobile Combustion (excluding CO 2 

### ) (IPCC Source Category 1A)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 9
3.5. Coal Mining (IPCC Source Category 1B1a)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 6
3.6. Abandoned Underground Coal Mines (IPCC Source Category 1B1a)

. . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 9
3.7. Natural Gas Systems (IPCC Source Category 1B2b)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 2
3.8. Petroleum Systems (IPCC Source Category 1B2a)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 6

### vi 3.9. Municipal Solid Waste Combustion (IPCC Source Category 1A5)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5 0
3.10. Energy Sources of Indirect Greenhouse Gas Emissions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5 4
3.11. International Bunker Fuels (IPCC Source Category 1: Memo Items)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5 5
3.12. Wood Biomass and Ethanol Consumption (IPCC Source Category 1A)

. . . . . . . . . . . . . . . . . . . . . . . . . 3-6 0



## 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)

. . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 2
4. 5. Ammonia Production (IPCC Source Category 2B1) and Urea Consumption

. . . . . . . . . . . . . . . . . . . . . . 4-1 4
4. 6. Nitric Acid Production (IPCC Source Category 2B2)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 8
4. 7. Adipic Acid Production (IPCC Source Category 2B3)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 9
4. 8. Silicon Carbide Production (IPCC Source Category 2B4) and Consumption

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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 3
4. 10. Titanium Dioxide Production (IPCC Source Category 2B5)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 6
4. 11. Carbon Dioxide Consumption (IPCC Source Category 2B5)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 8
4. 12. Phosphoric Acid Production (IPCC Source Category 2B5)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 0
4. 13. Iron and Steel Production (IPCC Source Category 2C1)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 3
4. 14. Ferroalloy Production (IPCC Source Category 2C2)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 7
4. 15. Aluminum Production (IPCC Source Category 2C3)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 9
4. 16. Magnesium Production and Processing (IPCC Source Category 2C4)

. . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 3
4. 17. Zinc Production (IPCC Source Category 2C5)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 6
4. 18. Lead Production (IPCC Source Category 2C5)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 9
4. 19. HCFC-22 Production (IPCC Source Category 2E1)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5 0
4. 20. Substitution of Ozone Depleting Substances (IPCC Source Category 2F)

. . . . . . . . . . . . . . . . . . . . . . . . 4-5 2
4. 21. Semiconductor Manufacture (IPCC Source Category 2F6)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5 6
4. 22. Electrical Transmission and Distribution (IPCC Source Category 2F7)

. . . . . . . . . . . . . . . . . . . . . . . . . . 4-6 1
4. 23. Industrial Sources of Indirect Greenhouse Gases

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6 6



## 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)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1 2
6.4. Agricultural Soil Management (IPCC Source Category 4D)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1 7
6.5. Field Burning of Agricultural Residues (IPCC Source Category 4F)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3 1

### 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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-1 1
7.3. Land Converted to Forest Land (IPCC Source Category 5A2)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2 4
7.4. Cropland Remaining Cropland (IPCC Source Category 5B1)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2 4
7.5. Land Converted to Cropland (IPCC Source Category 5B2)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 7
7.6. Grassland Remaining Grassland (IPCC Source Category 5C1)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4 1
7.7. Land Converted to Grassland (IPCC Source Category 5C2)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4 6
7.8. Settlements Remaining Settlements

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-5 0
7.9. Land Converted to Settlements (Source Category 5E2)

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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-5 6


## 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)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1 7
8.4. Waste Sources of Indirect Greenhouse Gases

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1 9


## 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 CO 2 

### Emissions from Fossil Fuel Combustion 2.1. Methodology for Estimating Emissions of CO 2 

### 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 CH 4 

### , N 2 

### O, and Indirect Greenhouse Gases from Stationary Combustion 3.2. Methodology for Estimating Emissions of CH 4 

### , N 2 

### O, and Indirect Greenhouse Gases from Mobile Combustion and Methodology for and Supplemental Information on Transportation-Related GHG Emissions 3.3. Methodology for Estimating CH 4 

### Emissions from Coal Mining 3.4. Methodology for Estimating CH 4 

### and CO 2 

### Emissions from Natural Gas Systems 3.5. Methodology for Estimating CH 4 

### and CO 2 

### Emissions from Petroleum Systems 3.6. Methodology for Estimating CO 2 

### and N 2 

### O 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 CH 4 

### Emissions from Enteric Fermentation

### viii 3.10. Methodology for Estimating CH 4 

### and N 2 

### O Emissions from Manure Management 3.11. Methodology for Estimating N 2 

### O 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 CH 4 

### Emissions from Landfills
ANNEX 4

. IPCC Reference Approach for Estimating CO 2 

### 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 CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . ES- 5
Table ES-3: CO 2 

### Emissions from Fossil Fuel Combustion by Fuel Consuming End-Use Sector (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES- 9
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 3
Table ES-5: Net CO 2 

### Flux from Land Use, Land-Use Change, and Forestry (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . ES-1 5
Table ES-6: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . ES-1 5
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . ES-1 6
Table ES-8: U.S. Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions Distributed (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 7
Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 8
Table ES-10: Emissions of NO x 

### , CO, NMVOCs, and SO 2 

### (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 9
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

. . . . . . . . . . . . . . . . 1-1 2
Table 1-5. Estimated Overall Inventory Uncertainty (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . 1-1 4
Table 1-6: IPCC Sector Descriptions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1 5
Table 1-7: List of Annexes

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1 6
Table 2-1: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO 2 

### 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 CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2- 8
Table 2-4: Emissions from Energy (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1 0
Table 2-5: CO 2 

### Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . 2-1 1
Table 2-6: Emissions from Industrial Processes (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1 3
Table 2-7: N 2 

### O Emissions from Solvent and Other Product Use (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . 2-1 3
Table 2-8: Emissions from Agriculture (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1 4
Table 2-9: Net CO 2 

### Flux from Land Use, Land-Use Change, and Forestry (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . 2-1 5
Table 2-10: Emissions from Land Use, Land-Use Change, and Forestry (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . 2-1 6
Table 2-11: Emissions from Waste (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1 7
Table 2-12: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg CO 2 

### Eq. and Percent of Total in 2006)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1 8
Table 2-13: Electricity Generation-Related Greenhouse Gas Emissions (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . 2-2 0
Table 2-14: U.S. Greenhouse Gas Emissions by Economic Sector and Gas with Electricity-Related Emissions Distributed (Tg CO 2 

### Eq.) and Percent of Total in 2006

. . . . . . . . . . . . . . 2-2 1
Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . 2-2 4
Table 2-16: Recent Trends in Various U.S. Data (Index 1990 = 100)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2 7
Table 2-17: Emissions of NO x 

### , CO, NMVOCs, and SO 2 

### (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2 8
Table 3-1: CO 2 

### , CH 4 

### , and N 2 

### O Emissions from Energy (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3- 2
Table 3-2: CO 2 

### , CH 4 

### , and N 2 

### O Emissions from Energy (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3- 3
Table 3-3: CO 2 

### Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO 2 

### Eq.)

. . . . . . . . . . 3- 4
Table 3-4: Annual Change in CO 2 

### Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3- 5
Table 3-5: CO 2 

### Emissions from International Bunker Fuels (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 3- 7
Table 3-6: CO 2 

### Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . 3- 8
Table 3-7: CO 2 

### Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3- 9
Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg CO 2 

### Eq./QBtu)

. . . . . . . . . . . 3-1 5
Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg CO 2 

### Eq./QBtu)

. . . . . . . . . . . . . . . . 3-1 6
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Energy-Related Fossil Fuel Combustion by Fuel Type and Sector (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . 3-1 8
Table 3-11: CO 2 

### Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . 3-2 0
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Use (TBtu)

. . . . . . . . . . . . . . . . . . . . . . . 3-2 1
Table 3-13: 2006 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions

. . . . . . . . . . . 3-2 2

### x Table 3-14: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Non-Energy Uses of Fossil Fuels (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 3
Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels (Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 3
Table 3-16: CH 4 

### Emissions from Stationary Combustion (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 5
Table 3-17: N 2 

### O Emissions from Stationary Combustion (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 6
Table 3-18: CH 4 

### Emissions from Stationary Combustion (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 7
Table 3-19: N 2 

### O Emissions from Stationary Combustion (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 8
Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### and N 2 

### O Emissions from Energy-Related Stationary Combustion, Including Biomass (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . 3-2 8
Table 3-21: CH 4 

### Emissions from Mobile Combustion (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 0
Table 3-22: N 2 

### O Emissions from Mobile Combustion (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 0
Table 3-23: CH 4 

### Emissions from Mobile Combustion (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 1
Table 3-24: N 2 

### O Emissions from Mobile Combustion (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 1
Table 3-25: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### and N 2 

### O Emissions from Mobile Sources (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 3
Table 3-26: CH 4 

### Emissions from Coal Mining (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 6
Table 3-27: CH 4 

### Emissions from Coal Mining (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 6
Table 3-28: Coal Production (Thousand Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 7
Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Coal Mining (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 8
Table 3-30: CH 4 

### Emissions from Abandoned Coal Mines (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 9
Table 3-31: CH 4 

### Emissions from Abandoned Coal Mines (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3 9
Table 3-32: Number of Gassy Abandoned Mines Occurring in U.S. Basins Grouped by Class According to Post-abandonment State

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 1
Table 3-33: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Abandoned Underground Coal Mines (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 2
Table 3-34: CH 4 

### Emissions from Natural Gas Systems (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 3
Table 3-35: CH 4 

### Emissions from Natural Gas Systems (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 3
Table 3-36: Non-combustion CO 2 

### Emissions from Natural Gas Systems (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . 3-4 3
Table 3-37: Non-combustion CO 2 

### Emissions from Natural Gas Systems (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . 3-4 3
Table 3-38: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### and
Non-Combustion CO 2 

### Emissions from Natural Gas Systems (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . 3-4 5
Table 3-39: CH 4 

### Emissions from Petroleum Systems (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 7
Table 3-40: CH 4 

### Emissions from Petroleum Systems (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 7
Table 3-41: CO 2 

### Emissions from Petroleum Systems (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 7
Table 3-42: CO 2 

### Emissions from Petroleum Systems (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 7
Table 3-43: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Petroleum Systems (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-4 9
Table 3-44: Potential Emissions from CO 2 

### Capture and Transport (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . 3-5 1
Table 3-45: Potential Emissions from CO 2 

### Capture and Transport (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5 1

### xi Table 3-46: CO 2 

### and N 2 

### O Emissions from Municipal Solid Waste Combustion (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . 3-5 2
Table 3-47: CO 2 

### and N 2 

### O Emissions from Municipal Solid Waste Combustion (Gg)

. . . . . . . . . . . . . . . . . . . 3-5 2
Table 3-48: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted

. . . . . . . . . . . . . . . . . . 3-5 3
Table 3-49: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### and
N 2 

### O from Municipal Solid Waste Combustion (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . 3-5 4
Table 3-50: NO x 

### , CO, and NMVOC Emissions from Energy-Related Activities (Gg)

. . . . . . . . . . . . . . . . . . . 3-5 5
Table 3-51: CO 2 

### , CH 4 

### , and N 2 

### O Emissions from International Bunker Fuels (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . 3-5 7
Table 3-52: CO 2 

### , CH 4 

### and N 2 

### O Emissions from International Bunker Fuels (Gg)

. . . . . . . . . . . . . . . . . . . . . . 3-5 7
Table 3-53: Aviation Jet Fuel Consumption for International Transport (Million Gallons)

. . . . . . . . . . . . . . . . 3-5 8
Table 3-54: Marine Fuel Consumption for International Transport (Million Gallons)

. . . . . . . . . . . . . . . . . . . 3-5 8
Table 3-55: CO 2 

### Emissions from Wood Consumption by End-Use Sector (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . 3-6 0
Table 3-56: CO 2 

### Emissions from Wood Consumption by End-Use Sector (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . 3-6 0
Table 3-57: CO 2 

### Emissions from Ethanol Consumption (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6 1
Table 3-58: CO 2 

### Emissions from Ethanol Consumption (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6 1
Table 3-59: Woody Biomass Consumption by Sector (Trillion Btu)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-6 1
Table 4-1: Emissions from Industrial Processes (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4- 3
Table 4-2: Emissions from Industrial Processes (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4- 4
Table 4-3: CO 2 

### Emissions from Cement Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 4- 5
Table 4-4: Clinker Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4- 6
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Cement Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4- 6
Table 4-6: CO 2 

### Emissions from Lime Production (Tg CO 2 

### 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 CO 2 

### Emissions from Lime Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4- 9
Table 4-10: CO 2 

### Emissions from Limestone & Dolomite Use (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . 4- 9
Table 4-11: CO 2 

### Emissions from Limestone & Dolomite Use (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 0
Table 4-12: Limestone and Dolomite Consumption (Thousand Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 1
Table 4-13: Dolomitic Magnesium Metal Production Capacity (Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . 4-1 1
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Limestone and Dolomite Use (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 2
Table 4-15: CO 2 

### Emissions from Soda Ash Production and Consumption (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . 4-1 2
Table 4-16: CO 2 

### Emissions from Soda Ash Production and Consumption (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . 4-1 3
Table 4-17: Soda Ash Production and Consumption (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 3
Table 4-18: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Soda Ash Production and Consumption (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 4
Table 4-19: CO 2 

### Emissions from Ammonia Production and Urea Consumption (Tg CO 2 

### Eq.)

. . . . . . . . . . . . 4-1 5
Table 4-20: CO 2 

### Emissions from Ammonia Production and Urea Consumption (Gg)

. . . . . . . . . . . . . . . . . . . 4-1 5
Table 4-21: Ammonia Production, Urea Production, Urea Net Imports, and Urea Exports (Gg)

. . . . . . . . . . . 4-1 6

### xii Table 4-22: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Ammonia Production and Urea Consumption (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . 4-1 7
Table 4-23: N 2 

### O Emissions from Nitric Acid Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . . . 4-1 8
Table 4-24: Nitric Acid Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 8
Table 4-25: Tier 2 Quantitative Uncertainty Estimates for N 2 

### O Emissions From Nitric Acid Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1 9
Table 4-26: N 2 

### O Emissions from Adipic Acid Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . . 4-2 0
Table 4-27: Adipic Acid Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 1
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for N 2 

### O Emissions from Adipic Acid Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 1
Table 4-29: CO 2 

### and CH 4 

### Emissions from Silicon Carbide Production and Consumption (Tg CO 2 

### Eq.)

. . . . . 4-2 2
Table 4-30: CO 2 

### and CH 4 

### Emissions from Silicon Carbide Production and Consumption (Gg)

. . . . . . . . . . . . 4-2 2
Table 4-31: Production and Consumption of Silicon Carbide (Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 3
Table 4-32: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### and CO 2 

### Emissions from Silicon Carbide Production and Consumption (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . 4-2 3
Table 4-33: CO 2 

### and CH 4 

### Emissions from Petrochemical Production (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . 4-2 4
Table 4-34: CO 2 

### and CH 4 

### Emissions from Petrochemical Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 4
Table 4-35: Production of Selected Petrochemicals (Thousand Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 5
Table 4-36: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock) Consumption (Thousand Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 5
Table 4-37: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Petrochemical Production and
CO 2 

### Emissions from Carbon Black Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . 4-2 6
Table 4-38: CO 2 

### Emissions from Titanium Dioxide Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . 4-2 7
Table 4-39: Titanium Dioxide Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 7
Table 4-41: CO 2 

### Emissions from CO 2 

### Consumption (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 9
Table 4-42: CO 2 

### Production (Gg CO 2 

### ) and the Percent Used for Non-EOR Applications for
Jackson Dome and Bravo Dome

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2 9
Table 4-43: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from CO 2 

### Consumption (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 0
Table 4-44: CO 2 

### Emissions from Phosphoric Acid Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . 4-3 1
Table 4-45: Phosphate Rock Domestic Production, Exports, and Imports (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . 4-3 1
Table 4-46: Chemical Composition of Phosphate Rock (percent by weight)

. . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 2
Table 4-47: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Phosphoric Acid Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 3
Table 4-48: CO 2 

### and CH 4 

### Emissions from Iron and Steel Production (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . 4-3 4
Table 4-49: CO 2 

### and CH 4 

### Emissions from Iron and Steel Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 4
Table 4-50: CH 4 

### Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg)

. . . . . . . . . . . . . . . . 4-3 5
Table 4-51: Production and Consumption Data for the Calculation of CO 2 

### and CH 4 

### Emissions from Iron and Steel Production (Thousand Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 6

### xiii Table 4-52: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### and CH 4 

### Emissions from Iron and Steel Production (Tg. CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 7
Table 4-53: CO 2 

### and CH 4 

### Emissions from Ferroalloy Production (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . 4-3 7
Table 4-54: CO 2 

### and CH 4 

### Emissions from Ferroalloy Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 8
Table 4-55: Production of Ferroalloys (Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 8
Table 4-56: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Ferroalloy Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3 9
Table 4-57: CO 2 

### Emissions from Aluminum Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . . . 4-4 0
Table 4-58: PFC Emissions from Aluminum Production (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 0
Table 4-59: PFC Emissions from Aluminum Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 0
Table 4-60: Production of Primary Aluminum (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 2
Table 4-61: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### and PFC Emissions from Aluminum Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 3
Table 4-62: SF 6 

### Emissions from Magnesium Production and Processing (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . 4-4 3
Table 4-63: SF 6 

### Emission Factors (kg SF 6 

### per metric ton of Magnesium)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 4
Table 4-64: Tier 2 Quantitative Uncertainty Estimates for SF 6 

### Emissions from Magnesium Production and Processing (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 5
Table 4-65: CO 2 

### Emissions from Zinc Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 6
Table 4-66: Zinc Production (Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 8
Table 4-67: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Zinc Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 8
Table 4-68: CO 2 

### Emissions from Lead Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 9
Table 4-69: Lead Production (Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4 9
Table 4-70: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Lead Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5 0
Table 4-71: HFC-23 Emissions from HCFC-22 Production (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . 4-5 1
Table 4-72: HCFC-22 Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5 1
Table 4-73: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5 2
Table 4-74: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . 4-5 3
Table 4-75: Emissions of HFCs and PFCs from ODS Substitutes (Mg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5 3
Table 4-76: Emissions of HFCs and PFCs from ODS Substitutes (Tg CO 2 

### Eq.) by Sector

. . . . . . . . . . . . . . . . 4-5 3
Table 4-77: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5 6
Table 4-78: PFC, HFC, and SF 6 

### Emissions from Semiconductor Manufacture (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . 4-5 7
Table 4-80: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF 6 

### Emissions from Semiconductor Manufacture (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6 0
Table 4-81: SF 6 

### Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6 1
Table 4-82: SF 6 

### Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Gg)

. . . . 4-6 1

### xiv Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF 6 

### Emissions from Electrical Transmission and Distribution (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6 4
Table 4-84: 2006 Potential and Actual Emissions of HFCs, PFCs, and SF 6 

### from Selected Sources (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6 5
Table 4-85: NO x 

### , CO, and NMVOC Emissions from Industrial Processes (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . 4-6 6
Table 5-1: N 2 

### O Emissions from Solvent and Other Product Use (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . 5- 1
Table 5-2: N 2 

### O Emissions from N 2 

### O Product Uses (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . 5- 2
Table 5-3: N 2 

### O Production (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5- 2 Table 5-4: Tier 2 Quantitative Uncertainty Estimates for N 2 

### O Emissions from
N 2 

### O Product Uses (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5- 3
Table 5-5: Emissions of NO x 

### , CO, and NMVOC from Solvent Use (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5- 4 Table 6-1: Emissions from Agriculture (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6- 1
Table 6-2: Emissions from Agriculture (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6- 2
Table 6-3: CH 4 

### Emissions from Enteric Fermentation (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6- 3
Table 6-4: CH 4 

### Emissions from Enteric Fermentation (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6- 3
Table 6-5: Quantitative Uncertainty Estimates for CH 4 

### Emissions from Enteric Fermentation (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6- 5
Table 6-6: CH 4 

### and N 2 

### O Emissions from Manure Management (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . 6- 8
Table 6-7: CH 4 

### and N 2 

### O Emissions from Manure Management (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6- 9
Table 6-8: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### and N 2 

### O (Direct and Indirect) Emissions from Manure Management (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . 6-1 1
Table 6-9: CH 4 

### Emissions from Rice Cultivation (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1 4
Table 6-10: CH 4 

### Emissions from Rice Cultivation (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1 4
Table 6-11: Rice Areas Harvested (Hectares)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1 5
Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Rice Cultivation (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1 7
Table 6-13: N 2 

### O Emissions from Agricultural Soils (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1 9
Table 6-14: N 2 

### O Emissions from Agricultural Soils (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1 9
Table 6-15: Direct N 2 

### O Emissions from Agricultural Soils by Land Use and N Input (Tg CO 2 

### Eq.)

. . . . . . . . 6-1 9
Table 6-16: Indirect N 2 

### O Emissions from all Land-Use Types (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . 6-2 0
Table 6-17: Quantitative Uncertainty Estimates of N 2 

### O Emissions from Agricultural Soil Management in 2006 (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2 9
Table 6-18: CH 4 

### and N 2 

### O Emissions from Field Burning of Agricultural Residues (Tg CO 2 

### Eq.)

. . . . . . . . . . 6-3 1
Table 6-19: CH 4 

### , N 2 

### O , CO, and NO x 

### Emissions from Field Burning of Agricultural Residues (Gg)

. . . . . . . . 6-3 2
Table 6-20: Agricultural Crop Production (Gg of Product)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3 4
Table 6-21: Percent of Rice Area Burned by State

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3 4
Table 6-22: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues

. . . . . . 6-3 4
Table 6-23: Greenhouse Gas Emission Ratios

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3 5
Table 6-24: Tier 2 Uncertainty Estimates for CH 4 

### and N 2 

### O Emissions from Field Burning of Agricultural Residues (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3 5

### xv Table 7-1: Net CO 2 

### Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7- 2
Table 7-2: Net CO 2 

### 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 CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . 7- 3
Table 7-4: Non- CO 2 

### 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 CO 2 

### /yr) in Forest and Harvested Wood Pools

. . . . . . . . . . . . 7-1 4
Table 7-7: Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools

. . . . . . . . . . . . . . 7-1 4
Table 7-8: Forest Area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools

. . . . . . . . . . . . . . 7-1 5
Table 7-9: Estimates of CO 2 

### (Tg/yr) emissions for the lower 48 states and Alaska

. . . . . . . . . . . . . . . . . . . . . . 7-1 6
Table 7-10: Tier 2 Quantitative Uncertainty Estimates for Net CO 2 

### Flux from Forest Land Remaining Forest Land: Changes in Forest C Stocks (Tg CO 2 

### Eq. and Percent)

. . . . . . . . 7-1 9
Table 7-11: Estimated Non- CO 2 

### Emissions from Forest Fires (Tg CO 2 

### Eq.) for U.S. Forests

. . . . . . . . . . . . . 7-2 1
Table 7-12: Estimated Non- CO 2 

### Emissions from Forest Fires (Gg Gas) for U.S. Forests

. . . . . . . . . . . . . . . . . 7-2 1
Table 7-13: Estimated Carbon Released from Forest Fires for U.S. Forests

. . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2 2
Table 7-14: Tier 2 Quantitative Uncertainty Estimates of Non- CO 2 

### Emissions from Forest Fires in Forest Land Remaining Forest Land (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . 7-2 2
Table 7-15: N 2 

### O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . 7-2 3
Table 7-16: Quantitative Uncertainty Estimates of N 2 

### O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2 4
Table 7-17: Net CO 2 

### Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg CO 2 

### Eq.)

. . . . . 7-2 6
Table 7-18: Net CO 2 

### Flux from Soil C Stock Changes in Cropland Remaining Cropland(Tg C)

. . . . . . . . . . 7-2 6
Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within Cropland Remaining Cropland(Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 1
Table 7-20: Emissions from Liming of Agricultural Soils (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 3
Table 7-21: Emissions from Liming of Agricultural Soils (Tg C)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 3
Table 7-22: Applied Minerals (Million Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 4
Table 7-23: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Liming of Agricultural Soils (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 5
Table 7-24: CO 2 

### Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg CO 2 

### Eq.)

. . . . . . . 7-3 5
Table 7-25: CO 2 

### Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C)

. . . . . . . . . . . . 7-3 6
Table 7-26: Applied Urea (Million Metric Tons)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 6
Table 7-27: Quantitative Uncertainty Estimates for CO 2 

### Emissions from Urea Fertilization (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 6
Table 7-28: Net CO 2 

### Flux from Soil C Stock Changes in Land Converted to Cropland (Tg CO 2 

### Eq.)

. . . . . . . 7-3 7
Table 7-29: Net CO 2 

### Flux from Soil C Stock Changes in Land Converted to Cropland (Tg C)

. . . . . . . . . . . . 7-3 7
Table 7-30: Quantitative Uncertainty Estimates for C Stock Changes occurring within Land Converted to Cropland (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4 0
Table 7-31: Net CO 2 

### Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg CO 2 

### Eq.)

. . . . 7-4 2

### xvi Table 7-32: Net CO 2 

### Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg C)

. . . . . . . . . 7-4 2
Table 7-33: Quantitative Uncertainty Estimates for C Stock Changes occurring within Grassland Remaining Grassland (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4 5
Table 7-34: Net CO 2 

### Flux from Soil C Stock Changes for Land Converted to Grassland (Tg CO 2 

### Eq.)

. . . . . 7-4 7
Table 7-35: Net CO 2 

### Flux from Soil C Stock Changes for Land Converted to Grassland (Tg C)

. . . . . . . . . . . 7-4 7
Table 7-36: Quantitative Uncertainty Estimates for C Stock Changes occurring within Land Converted to Grassland (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-5 0
Table 7-37: Net C Flux from Urban Trees (Tg CO 2 

### Eq. and Tg C)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-5 0
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

. . . . . . . . . . 7-5 2
Table 7-39: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-5 3
Table 7-40: N 2 

### O Fluxes from Soils in Settlements Remaining Settlements (Tg CO 2 

### Eq. and Gg)

. . . . . . . . . . 7-5 4
Table 7-41: Quantitative Uncertainty Estimates of N 2 

### O Emissions from Soils in Settlements Remaining Settlements (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-5 6
Table 7-42: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg CO 2 

### Eq.)

. . . . . . . . . . . . 7-5 7
Table 7-43: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C)

. . . . . . . . . . . . . . . . . 7-5 7
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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-5 8
Table 7-45: C Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C)

. . . . . . . . . . . . . . . . . . . . . . . . . 7-5 9
Table 7-46: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Flux from Yard Trimmings and Food Scraps in Landfills (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-6 0
Table 8-1: Emissions from Waste (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8- 1
Table 8-2: Emissions from Waste (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8- 2
Table 8-3: CH 4 

### Emissions from Landfills (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8- 3
Table 8-4: CH 4 

### Emissions from Landfills (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8- 3
Table 8-5: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Landfills (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8- 5
Table 8-6: CH 4 

### and N 2 

### O Emissions from Domestic and Industrial Wastewater Treatment (Tg CO 2 

### Eq.)

. . . . 8- 7
Table 8-7: CH 4 

### and N 2 

### O Emissions from Domestic and Industrial Wastewater Treatment (Gg)

. . . . . . . . . . . 8- 8
Table 8-8: U.S. Population (Millions) and Domestic Wastewater BOD 5 

### Produced (Gg)

. . . . . . . . . . . . . . . . . 8-1 0
Table 8-9: U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg)

. . . . . . 8-1 0
Table 8-10: Wastewater Flow (m 3 

### /ton) and BOD Production (g/L) for U.S. Vegetables, Fruits and Juices Production

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1 2
Table 8-11: U.S. Population (Millions) and Average Protein Intake [kg/(person-year)]

. . . . . . . . . . . . . . . . . . 8-1 4
Table 8-12: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### and N 2 

### O Emissions from
Wastewater Treatment (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1 5
Table 8-13: CH 4 

### and N 2 

### O Emissions from Composting (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1 7
Table 8-14: CH 4 

### and N 2 

### O Emissions from Composting (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1 7
Table 8-15: U.S. Waste Composted (Gg)

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

### xvii Table 8-16: Tier 1 Quantitative Uncertainty Estimates for Emissions from Composting (Tg CO 2 

### Eq. and Percent)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1 8
Table 8-17: Emissions of NO x 

### , CO, and NMVOC from Waste (Gg)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1 9 Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10- 3
Table 10-2: Revisions to Net Flux of CO 2 

### to the Atmosphere from Land Use, Land-Use Change, and Forestry (Tg CO 2 

### 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 CO 2 

### Emissions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES- 7 Figure ES- 6 : 2006 CO 2 

### Emissions from Fossil Fuel Combustion by Sector and Fuel Type

. . . . . . . . . . . . . . . ES- 8 Figure ES- 7 : 2006 End-Use Sector Emissions of CO 2 

### from Fossil Fuel Combustion

. . . . . . . . . . . . . . . . . . . . ES- 8 Figure ES- 8 : 2006 Sources of CH 4 

### Emissions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 0 Figure ES- 9 : 2006 Sources of N 2 

### O Emissions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 1 Figure ES-1 0 : 2006 Sources of HFCs, PFCs, and SF 6 

### Emissions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 2 Figure ES-1 1 : U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector

. . . . . . . . . . . . . . . . . . . . ES-1 2 Figure ES-1 2 : 2006 U.S. Energy Consumption by Energy Source

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 3 Figure ES-1 3 : Emissions Allocated to Economic Sectors

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 6 Figure ES-14: Emissions with Electricity Distributed to Economic Sectors

. . . . . . . . . . . . . . . . . . . . . . . . . . . ES-1 7 Figure ES-1 5 : U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product

. . . . . ES-1 8 Figure ES-1 6 : 2006 Key Categories-Tier 1 Level Assessment

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ES-2 0 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 CO 2 

### Eq.)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2- 9 Figure 2- 7 : 2006 CO 2 

### Emissions from Fossil Fuel Combustion by Sector and Fuel Type

. . . . . . . . . . . . . . . . 2-1 1 Figure 2- 8 : 2006 End-Use Sector Emissions of CO 2 

### from Fossil Fuel Combustion

. . . . . . . . . . . . . . . . . . . . . 2-1 1 Figure 2- 9 : 2006 Industrial Processes Chapter Greenhouse Gas Emission Sources

. . . . . . . . . . . . . . . . . . . . . 2-1 2 Figure 2-1 0 : 2006 Agriculture Chapter Greenhouse Gas Emission Sources

. . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1 4 Figure 2-1 1 : 2006 Waste Chapter Greenhouse Gas Emission Sources

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1 6 Figure 2-1 2 : Emissions Allocated to Economic Sectors

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2 0 Figure 2-1 3 : Emissions with Electricity Distributed to Economic Sectors

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

. . . . . . . 2-2 7 Figure 3- 1 

## : 2006 Energy Chapter Greenhouse Gas Emission Sources

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3- 1 Figure 3- 2 

## : 2006 U.S. Fossil Carbon Flows (Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### from Fossil Fuel Combustion

. . . . . . . . . . . . . . . . . . . . . 3- 8 Figure 3-1 0 

## : Sales-Weighted Fuel Economy of New Automobiles and Light-Duty Trucks, 1990–2006

. . . . . 3-1 0 Figure 3-1 1 

## : Sales of New Automobiles and Light-Duty Trucks, 1990–2006

. . . . . . . . . . . . . . . . . . . . . . . . . . 3-1 0 Figure 3-1 2 

## : Industrial Production Indices (Index 2002=100)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1 1 Figure 3-1 3 

## : Electricity Generation Retail Sales by End-Use Sector

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1 2 Figure 3-1 4 : U.S. Energy Consumption and Energy-Related CO 2 

### Emissions Per Capita and Per Dollar GDP 3-1 6 Figure 3-1 5 : Mobile Source CH 4 

### and N 2 

### O Emissions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2 9 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 N 2 

### O Emissions

. . . . . . . . . . . . . . . . . . . . . 6-1 8 Figure 6- 3 : Major Crops, Average Annual Direct N 2 

### O Emissions Estimated Using the DAYCENT Model, 1990–2006 (Tg CO 2 

### Eq./state/year)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2 1 Figure 6- 4 : Grasslands, Average Annual Direct N 2 

### O Emissions Estimated Using the DAYCENT Model, 1990–2006 (Tg CO 2 

### Eq./state/year)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2 1 Figure 6- 5 : Major Crops, Average Annual N Losses Leading to Indirect N 2 

### O Emissions Using the DAYCENT Model, 1990–2006 (Gg N/state/year)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2 2 Figure 6- 6 : Grasslands, Average Annual N Losses Leading to Indirect N 2 

### O Emissions Using the DAYCENT Model, 1990–2006 (Gg N/state/year)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2 2 Figure 6- 7 : Comparison of Measured Emissions at Field Sites with Modeled Emissions Using the
DAYCENT Simulation Model

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2 9 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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-1 2 Figure 7- 3 : Estimates of Net Annual Changes in Carbon Stocks for Major Carbon Pools

. . . . . . . . . . . . . . . . 7-1 5 Figure 7- 4 : Average C Density in the Forest Tree Pool in the Conterminous United States, 2007

. . . . . . . . . . 7-1 6 Figure 7- 5 : Total Net Annual CO 2 

### Flux For Mineral Soils Under Agricultural Management within States, 1993–2006 Cropland Remaining Cropland

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2 7 Figure 7- 6 : Total Net Annual CO 2 

### Flux For Organic Soils Under Agricultural Management within States, 1993–2006 Cropland Remaining Cropland

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2 7 Figure 7- 7 : Total Net Annual CO 2 

### Flux For Mineral Soils Under Agricultural Management within States, 1993–2006 Land Converted to Cropland

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 9 Figure 7- 8 : Total Net Annual CO 2 

### Flux For Organic Soils Under Agricultural Management within States, 1993–2006 Land Converted to Cropland

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-3 9

### xix Figure 7- 9 : Total Net Annual CO 2 

### Flux For Mineral Soils Under Agricultural Management within States, 1993–2006 Grassland Remaining Grassland

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4 2 Figure 7-1 0 : Total Net Annual CO 2 

### Flux For Organic Soils Under Agricultural Management within States, 1993–2006 Grassland Remaining Grassland

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4 3 Figure 7-1 1 : Total Net Annual CO 2 

### Flux For Mineral Soils Under Agricultural Management within States,
1993–2006 Land Converted to Grassland

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4 7 Figure 7-1 2 : Total Net Annual CO 2 

### Flux For Organic Soils Under Agricultural Management within States,
1993–2006 Land Converted to Grassland

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-4 8 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-1 8 Box 1-1: The IPCC Fourth Assessment Report and Global Warming Potentials

. . . . . . . . . . . . . . . . . . . . . . . . 1- 8 Box 1-2: IPCC Reference Approach

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1 0 Box 2-1: Methodology for Aggregating Emissions by Economic Sector

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2 3
Box 2-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data

. . . . . . . . . . . . . . . . . . . . . 2-2 7
Box 2-3: Sources and Effects of Sulfur Dioxide

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-2 9 Box 3-1: Weather and Non-Fossil Energy Effects on CO 2 

### from Fossil Fuel Combustion Trends

. . . . . . . . . . . 3- 6 Box 3-2: Carbon Intensity of U.S. Energy Consumption

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1 5 Box 3-3: Carbon Dioxide Transport, Injection, and Geological Storage

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-5 1
Box 4-1: Potential Emission Estimates of HFCs, PFCs, and SF 6 

### . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6 5 Box 6-1: Tier 1 vs. Tier 3 Approach for Estimating N 2 

### O Emissions

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-2 4 Box 6-2: Comparison of Tier 2 U.S. Inventory Approach and IPCC (2006) Default Approach

. . . . . . . . . . . . 6-3 3
Box 7-1: CO 2 

### Emissions from Forest Fires

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-1 6 Box 7-2: Tier 3 Inventory for Soil C Stocks Compared to Tier 1 or 2 Approaches

. . . . . . . . . . . . . . . . . . . . . . 7-2 9 Box 8-1: Biogenic Emissions and Sinks of Carbon

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8- 6

### Executive Summary ES-1 

# Executive Summary 

# A n emissions inventory that identifies and quantifies a country’s primary anthropogenic 1 

### 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

1 The term “anthropogenic,” in this context, refers to greenhouse gas emissions and removals that are a direct result of human activities or are the result of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).

2 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate Change. See <http://unfccc.int>.

3 Article 4(1)(a) of the United Nations Framework Convention on Climate Change (also identified in Article 12). Subsequent decisions by the Conference of the Parties elaborated the role of Annex I Parties in preparing national inventories. See <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 (CO 2 

### ), methane (CH 4 

### ), nitrous oxide (N 2 

### O), and ozone (O 3 

### ). 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 (SF 6 

### )—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 (NO x 

### ), and non-CH 4

### volatile organic compounds (NMVOCs). Aerosols, which are extremely small particles or liquid droplets, such as those produced by sulfur dioxide (SO 2 

### ) or elemental carbon emissions, can also affect the absorptive characteristics of the atmosphere. Although the direct greenhouse gases CO 2 

### , CH 4 

### , and
N 2 

### O occur naturally in the atmosphere, human activitieshave 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 CO 2 

### , and therefore GWP-weighted emissions are measured in teragrams of CO 2 

### equivalents (Tg CO 2 

### Eq.). 7,8 

### All gases in this Executive Summary are presented in units of Tg CO 2 

### 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 CO 2 

### equivalents and unweighted units. A comparison of emission values using the SAR GWPs versus the TAR and AR4 GWPs can be found in

6 Albedo is a measure of the Earth’s reflectivity, and is defined as the fraction of the total solar radiation incident on a body that is reflected by it.

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

8 One teragram is equal to 10 12 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, NO x 

### , NMVOCs, SO 2 

### , 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 CO 2 

### 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 CO 2 

### 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 CO 2 1 CH 4 * 21 N 2 O 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 CF 4 6,500 C 2 F 6 9,200 C 4 F 10 7,000 C 6 F 14 7,400 SF 6 23,900 Source: IPCC (1996) * The CH 4 GWP includes the direct effects and those indirect effects due

to the production of tropospheric ozone and stratospheric water vapor. The indirect effect due to the production of CO 2 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 CO 2 

### , representing approximately 84.8 percent of total greenhouse gas emissions. The largest source of CO 2 

### , and of overall greenhouse gas emissions, was fossil fuel combustion. CH 4 

### 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 N 2 

### O 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 SF 6 

### 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 8,000Tg CO2Eq.6,14819906,10619916,19219926,34319936,43519946,49419956,73119966,76019976,80119986,83919997,03320006,92120016,98120026,99820037,07820047,13020057,0542006 HFCs, PFCs, & SF 6 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 1,000Tg CO2Eq.

-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, & S F 6 N 2 O CH 4

CO 2 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 CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 Fuels b 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 CH 4 606.1 598.9 574.3 558.8 563.5 559.4 545.6 539.7 555.3

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 CO 2 

### increased by 914.6 Tg CO 2 

### Eq. (18.0 percent), while CH 4 

### and N 2 

### O emissions decreased by 50.8 Tg CO 2 

### Eq. (8.4 percent) and 15.5 Tg CO 2 

### Eq. (4.0 percent), respectively. During the same period, aggregate weighted emissions of HFCs, PFCs, and SF 6 

### rose by 57.6 Tg CO 2 

### Eq. (63.7 percent). From 1990 to 2006, HFCs increased by 87.6 Tg CO 2 

### Eq. (237.3 percent), PFCs decreased by 14.7 Tg CO 2 

### Eq. (70.9 percent), and SF 6 

### decreased by 15.3 Tg CO 2 

### Eq. (47.0 percent). Despite being emitted in smaller quantities (continued) 

### Table ES-2: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg CO 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 Fuels b 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 N 2 O 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 N 2 O 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 Fuels b 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 Substances c 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 SF 6 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 CO 2 Eq.

a Parentheses indicate negative values or sequestration. The net CO 2 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 SF 6 

### are significant because many of them have extremely high global warming potentials and, in the cases of PFCs and SF 6 

### , 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### emissions in 2006. Globally, approximately 28,193 Tg of CO 2 

### 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 CO 2

### (e.g., through conversion of forest land to agricultural or urban use) or can act as a sink for CO 2 

### (e.g., through net additions to forest biomass). U.S. anthropogenic sources of CO 2 

### are shown in Figure ES-5. As the largest source of U.S. greenhouse gas emissions, CO 2 

### 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 CO 2 

### 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 CO 2 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy Annual 2005 (EIA 2007). 

### 1990 and 2006, CO 2 

### emissions from fossil fuel combustion increased from 4,724.1 Tg CO 2

### Eq. to 5,637.9 Tg CO 2

### Eq.—a 19.3 percent total increase over the sixteen-year period. From 2005 to 2006, these emissions decreased by 93.1 Tg CO 2 

### Eq. (1.6 percent). Historically, changes in emissions from fossil fuel combustion have been the dominant factor affecting U.S. emission trends. Changes in CO 2 

### 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 CO 2 

### emissions from fossil fuel combustion are industrial, transportation, residential, and commercial. Electricity generation also emits CO 2 

### , although these Figure ES-5
2006 Sources of CO 2 

### Emissions

0 25 50 75 100 125 150 175 Tg CO 2 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

C0 2 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 CO 2 

### emissions from fossil fuel combustion by end-use sector. Transportation End-Use Sector. Transportation activities (excluding international bunker fuels) accounted for 33 percent of CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### Emissions from Fossil Fuel Combustion by Sector and Fuel Type

Note: Electricity generation also includes emissions of less than 0.5 Tg CO 2 Eq. from geothermal-based electricity generation. Natural Gas Petroleum Coal

0 500 1,000 1,500 2,000 2,500

Relative Contribution by Fuel TypeTg CO2Eq.

U.S. Territories Residential Commercial Industrial Transportation Electricity Generation



### Figure ES-7
2006 End-Use Sector Emissions of CO 2 

### from Fossil Fuel Combustion

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000

Transportation U.S. Territories Residential Commercial Industrial From Electricity Consumption From Direct Fossil Fuel CombustionTg CO2Eq.

### Executive Summary ES-9 with low CO 2

### 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 CO 2 

### emissions. Other significant CO 2 

### trends included the following:

• CO 2 

### emissions from non-energy use of fossil fuels have increased 20.8 Tg CO 2 

### Eq. (18 percent) from 1990 through 2006. Emissions from non-energy uses of fossil fuels were 138.0 Tg CO 2 

### Eq. in 2006, which constituted 2.4 percent of overall fossil fuel CO 2 

### emissions and 2.3 percent of total national CO 2 

### emissions, approximately the same proportion as in 1990.

• CO 2 

### emissions from iron and steel production increased by 5.3 percent to 49.1 Tg CO 2 

### Eq. in 2006, but have declined overall by 37.1 Tg CO 2 

### Eq. (43 percent) from 1990 through 2006, due to restructuring of the industry, technological improvements, and increased scrap utilization.

• In 2006, CO 2 

### emissions from cement production decreased slightly by 0.2 Tg CO 2 

### 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 CO 2 

### Eq.

• CO 2 

### emissions from municipal solid waste combustion (20.9 Tg CO 2 

### Eq. in 2006) increased by 10.0 Tg CO 2 

### Eq. (91 percent) from 1990 through 2006, as the volume of plastics and other fossil carbon-containing materials in municipal solid waste grew.

• CO 2 

### emissions from ammonia production and urea consumption (12.4 Tg CO 2 

### Eq. in 2006) have decreased by 4.5 Tg CO 2

### 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 CO 2 

### sequestration from Land Use, Land-Use Change, and Forestry increased by 146.0 Tg CO 2 

### 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: CO 2 

### Emissions from Fossil Fuel Combustion by Fuel Consuming End-Use Sector (Tg CO 2 

### 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, CH 4 

### is more than 20 times as effective as CO 2 

### at trapping heat in the atmosphere. Over the last two hundred and fifty years, the concentration of CH 4 

### in the atmosphere increased by 148 percent (IPCC 2007). Anthropogenic sources of CH 4 

### 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 CH 4

### include the following:

• Enteric fermentation is the largest anthropogenic source of CH 4 

### emissions in the United States. In 2006, enteric fermentation CH 4 

### emissions were 126.2 Tg CO 2 

### Eq. (approximately 22.7 percent of total CH 4 

### emissions), which represents a decline of 0.7 Tg CO 2 

### 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 CH 4 

### emissions in the United States, accounting for approximately 22.6 percent of total CH 4 

### emissions (125.7 Tg CO 2 

### Eq.) in 2006. From 1990 to 2006, net CH 4 

### emissions from landfills decreased by 23.9 Tg CO 2 

### 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 CH 4 

### emissions resulting from an increase in the amount of municipal solid waste landfilled.

• CH 4 

### emissions from natural gas systems were 102.4 Tg CO 2 

### Eq. in 2006; emissions have declined by 22.3 Tg CO 2 

### 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, CH 4

### emissions from coal mining were 58.5 Tg CO 2

### Eq., a 1.4 Tg CO 2

### Eq. (2.5 percent) increase over 2005 emission levels. The overall decline of 25.6 Tg CO 2 

### Eq. (30 percent) from 1990 results from the mining of less gassy coal from underground mines and the increased use of CH 4

### collected from degasification systems.

• CH 4 

### emissions from manure management increased by 34 percent for CH 4 

### , from 31.0 Tg CO 2 

### Eq. in 1990 to 41.4 Tg CO 2 

### 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 CH 4 

### 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

N 2 

### O 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 N 2 

### O emissions are much lower than CO 2 

### emissions, N 2 

### O is approximately 300 times more powerful than CO 2 

### at trapping heat in the atmosphere. Since 1750, the global atmospheric concentration of N 2 

### O has risen by approximately 18 percent (IPCC 2007). The main anthropogenic activities producing N 2 

### O in the United States are agricultural soil management, fuel combustion

12 The CO 2 produced from combusted landfill CH 4 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 CH 4 

### Emissions

CH 4 as a Portion of all Emissions

0 20 40 60 80 100 120 140 Tg CO 2 Eq. 7.9%

<0.05 Silicon Carbide Production and Consumption <0.05 Ferroalloy Production 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 N 2 

### O include the following:

• Agricultural soils produced approximately 72 percent of
N 2 

### O emissions in the United States in 2006. Estimated emissions from this source in 2006 were 265.0 Tg CO 2 

### Eq. Annual N 2 

### O emissions from agricultural soils fluctuated between 1990 and 2006, although overall emissions were 1.6 percent lower in 2006 than in 1990.
N 2 

### O 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, N 2 

### O emissions from mobile combustion were 33.1 Tg CO 2 

### Eq. (approximately 9 percent of U.S. N 2 

### O emissions). From 1990 to 2006, N 2 

### O emissions from mobile combustion decreased by 24 percent. However, from 1990 to 1998 emissions increased by 26 percent, due to control technologies that reduced NO x 

### emissions while increasing N 2 

### O emissions. Since 1998, newer control technologies have led to a steady decline in N 2 

### O from this source. • N 2 

### O emissions from adipic acid production were 5.9 Tg CO 2 

### 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 CO 2 

### Eq. annually since 1998. 

# HFC, PFC, and SF 6 

# 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 SF 6 

### , are potent greenhouse gases. In addition to having high global warming potentials, SF 6 

### 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 SF 6 

### 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 CO 2 

### Eq. in 2006. Emissions from substitutes for ozone depleting substances are both the largest and the fastest growing source of HFC, PFC, and SF 6 

### emissions. These emissions have been increasing as phase-outs required under the Montreal Protocolcome 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 CO 2 

### 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 N 2 0 as a Portion of all Emissions

5.2% 265.0

Tg CO 2 Eq. Municipal Solid Waste Combustion Field Burning of Agricultural Residues

Settlements Remaining Settlements Composting Forest Land Remaining Forest Land N 2 O 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 N 2 

### O 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.

• SF 6 

### emissions from electric power transmission and distribution systems decreased by 51 percent (13.5 Tg CO 2 

### Eq.) from 1990 to 2006, primarily because of higher purchase prices for SF 6 

### and efforts by industry to reduce emissions.

• PFC emissions from aluminum production decreased by 87 percent (16.1 Tg CO 2 

### 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 CO 2 

### Eq. (17 percent), 21.0 Tg CO 2 

### Eq. (7 percent), and 6.6 Tg CO 2 

### Eq. (1 percent), respectively. Emissions decreased in the Waste and Solvent and Other Product Use sectors by 18.6 Tg CO 2 

### Eq. (10 percent) and less than 0.1 Tg CO 2 

### 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 CO 2 

### 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. CO 2 

### 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 CH 4 

### and N 2 

### O 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 CO 2 Eq. HFCs, PFCs, and SF 6 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 SF 6 

### Emissions Figure ES-11
U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC SectorTg CO2Eq.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 CO 2 

### , CH 4 

### , and N 2 

### O. 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, CO 2 

### 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 SF 6 

### . 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 N 2 

### O 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 CO 2 

### 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 CO 2 

### 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 CO 2 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 CO 2 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in n et 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. CH 4 

### and N 2 

### O were the primary greenhouse gases emitted by agricultural activities. CH 4 

### emissions from enteric fermentation and manure management represented about 23 percent and 7 percent of total CH 4 

### 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.
N 2 

### O 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 CH 4 

### and N 2 

### O, and emissions and removals of CO 2 

### 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 CO 2

### 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 CO 2 

### Eq. (Table ES-5). This represents an offset of approximately 14.8 percent of total U.S. CO 2 

### 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 CO 2 

### 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 CO 2 

### emissions of 8.0 Tg CO 2 

### 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 N 2 

### O emissions of 1.8 Tg CO 2 

### Eq. Direct N 2 

### O emissions from fertilizer application increased by approximately 74 percent between 1990 and 2006. Non-CO 2 

### emissions from forest fires in 2006 resulted in CH 4 

### emissions of 24.6 Tg CO 2 

### Eq., and in N 2 

### O emissions of 2.5 Tg CO 2 

### 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 CH 4 

### emissions in the Waste chapter, accounting for 23 percent of total U.S. CH 4 

### emissions. 13 

### Additionally, wastewater treatment accounts for 4 percent of U.S. CH 4 

### emissions. N 2 

### O emissions from the discharge of wastewater treatment effluents into aquatic environments were estimated, as were N 2 

### O emissions from the treatment process itself. Emissions of CH 4 

### and N 2 

### O 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 CO 2 

### Eq. and 1.8 Tg CO 2 

### 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 CO 2 

### Flux from Land Use, Land-Use Change, and Forestry (Tg CO 2 

### 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 CO 2 

### Eq.)

Source Category 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 CH 4 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 N 2 O 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 CO 2 

### 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 N 2 

### O emissions from agricultural soil management and CH 4

### emissions from enteric fermentation, rather than CO 2 

### from fossil fuel combustion. The commercial sector accounted for about 6 percent of emissions, while U.S. territories accounted for 1 percent.

CO 2 

### 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 CO 2 

### 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 CO 2 , CH 4 , N 2 O, HFCs, PFCs, and SF 6 . See Table 2-12 for more detailed data.



### Figure ES-13
Emissions Allocated to Economic Sectors

0 500 1,000 1,500 2,000 2,50019901991199219931994199519961997199819992000200120022003200420052006 Residential Agriculture Electricity GenerationTg CO2Eq. 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 CO 2 

### from fossil fuel combustion and the use of limestone and dolomite for flue gas desulfurization, CO 2 

### and N 2 

### O from waste combustion, CH 4 

### and N 2 

### O from stationary sources, and SF 6 

### 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, CO 2 

### 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.

14 Emissions were not distributed to U.S. territories, since the electricity generation sector only includes emissions related to the generation of electricity in the 50 states and the District of Columbia. 

### 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 Industrial19901991199219931994199519961997199819992000200120022003200420052006Tg CO2Eq. 

### Table ES-8: U.S. Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions Distributed (Tg CO 2 

### 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 110Index (1990 = 100)19901991199219931994199519961997199819992000200120022003200420062005

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 Rate a GDP b 100 113 138 139 141 145 150 155 159 3.0% Electricity Consumption c 100 112 127 125 128 129 131 134 135 1.9% Fossil Fuel Consumption c 100 107 117 115 116 116 119 119 117 1.0% Energy Consumption c 100 108 116 112 115 115 118 118 117 1.0% Population d 100 107 113 114 115 116 117 118 119 1.1% Greenhouse Gas Emissions e 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, NO x 

# , NMVOCs, and SO 2 

# ) The reporting requirements of the UNFCCC 15 

### request that information be provided on indirect greenhouse gases, which include CO, NO x 

### , NMVOCs, and SO 2 

### . 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 SO 2 

### , by affecting the absorptive characteristics of the atmosphere. Additionally, some of these gases may

Table ES-10: Emissions of NO x 

### , CO, NMVOCs, and SO 2 

### (Gg)

Gas/Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006 NO x 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 SO 2 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, NO x 

### , NMVOCs, and SO 2

### (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, NO x 

### , 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

16 NO xand 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

17 See 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 CO 2 Eq. CH 4 Emissions from Manure Management CO 2 Emissions from Mobile Combustion: Marine CO 2 Emissions from Cement Production CO 2 Emissions from Iron and Steel Production Indirect N 2 O Emissions from Applied Nitrogen Fugitive CH 4 Emissions from Coal Mining Fugitive CH 4 Emissions from Natural Gas Systems Emissions from Substitutes for Ozone Depleting Substances CH 4 Emissions from Landfills CH 4 Emissions from Enteric Fermentation CO 2 Emissions from Non-Energy Use of Fuels CO 2 Emissions from Mobile Combustion: Aviation Direct N 2 O Emissions from Agricultural Soil Management CO 2 Emissions from Stationary Combustion – Oil CO 2 Emissions from Stationary Combustion – Gas CO 2 Emissions from Mobile Combustion: Road & Other CO 2 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 CO 2

### 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). Therole 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.

2 The term “anthropogenic”, in this context, refers to greenhouse gas emissions and removals that are a direct result of human activities or are the result of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).

3 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate Change. See <http://unfccc. int>. (UNEP/WMO 2000)

4 Article 4(1)(a) of the United Nations Framework Convention on Climate Change (also identified in Article 12). Subsequent decisions by the Conference of the Parties elaborated the role of Annex I Parties in preparing national inventories. See <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
oxy gen 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 (CO 2 

### ), 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, CO 2 

### , methane (CH 4 

### ), nitrous oxide (N 2 

### O), and ozone (O 3 

### ). 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 (SF 6 

### )—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 (NO 2 

### ), sulfur dioxide (SO 2 

### ), and tropospheric (ground level) O 3 

### . Tropospheric ozone is formed by two precursor pollutants, volatile organic compounds (VOCs) and nitrogen oxides (NO x 

### ) 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).

6 Emission 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 CO 2 CH 4 N 2 O SF 6 CF 4 Pre-industrial atmospheric concentration 278 ppm 0.715 ppm 0.270 ppm 0 ppt 40 ppt Atmospheric concentration a 379 ppm 1.774 ppm 0.319 ppm 5.6 ppt 74 ppt Rate of concentration change 1.4 ppm/yr 0.005 ppm/yr a 0.26% yr Linear b Linear b Atmospheric lifetime c 50–200 d 12 e 114 e 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 CH 4 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 SF 6 and CF 4 as linear.

c Source: IPCC (1996). d No single lifetime can be defined for CO 2 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.



### CO 2 

### , CH 4 

### , and N 2 

### O 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 (H 2 

### O). 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 CO 2 

### . Atmospheric CO 2 

### is part of this global carbon cycle, and therefore its fate is a complex function of geochemical and biological processes. CO 2 

### 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 CO 2 

### increase is caused by anthropogenic emissions of CO 2 

### ” (IPCC 2001). The predominant source of anthropogenic CO 2 

### emissions is the combustion of fossil fuels. Forest clearing, other biomass burning, and some non-energy production

7 The pre-industrial period is considered as the time preceding the year 1750 (IPCC 2001).

8 Carbon dioxide concentrations during the last 1,000 years of the 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 CO 2 

### . In its second assessment, the IPCC also stated that “[t]he increased amount of CO 2 

### [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. CH 4 

### 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 CH 4 

### , as does the decomposition of municipal solid wastes. CH 4 

### 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 CH 4 

### have increased by about 143 percent since 1750, from a pre-industrial value of about 722 ppb to 1,774 ppb in 2005, although the rate of increase has been declining. The IPCC has estimated that slightly more than half of the current CH 4 

### flux to the atmosphere is anthropogenic, from human activities such as agriculture, fossil fuel use, and waste disposal (IPCC 2007).

CH 4 

### is removed from the atmosphere through a reaction with the hydroxyl radical (OH) and is ultimately converted to CO 2 

### . Minor removal processes also include reaction with chlorine in the marine boundary layer, a soil sink, and stratospheric reactions. Increasing emissions of CH 4 

### reduce the concentration of OH, a feedback that may increase the atmospheric lifetime of CH 4 

### (IPCC 2001).

Nitrous Oxide. Anthropogenic sources of N 2 

### O emissionsinclude 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 N 2 

### O 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. N 2 

### O 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 CO 2 

### and CH 4 

### . Tropospheric ozone is produced from complex chemical reactions of volatile organic compounds mixing with NO x 

### 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.

10 The troposphere is the layer from the ground up to 11 kilometers near the poles and up to 16 kilometers in equatorial regions (i.e., the lowest layer of the atmosphere where people live). It contains roughly 80 percent of the mass of all gases in the atmosphere and is the site for most weather processes, including most of the water vapor and clouds.

### 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 5 11 

### 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 SF 6

### 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 depletingsubstances 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 SF 6 

### 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 SF 6 

### 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 CH 4 

### and tropospheric ozone through chemical reactions with other atmospheric constituents (e.g., the hydroxyl radical, OH) that would otherwise assist in destroying CH 4 

### 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 CO 2 

### . Carbon monoxide concentrations are both short-lived in the atmosphere and spatially variable.

11 Article 5 of the Montreal Protocol covers several groups of countries, especially developing countries, with low consumption rates of ozone depleting substances. Developing countries with per capita consumption of less than 0.3 kg of certain ozone depleting substances (weighted by their ozone depleting potential) receive financial assistance and a grace period of ten additional years in the phase-out of ozone depleting substances. 

### Nitrogen Oxides. The primary climate change effects of nitrogen oxides (i.e., NO and NO 2 

### ) 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, NO x 

### emissions from aircraft are likely to decrease CH 4 

### 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 N 2 

### O. Concentrations of NO x 

### are both relatively short-lived in the atmosphere and spatially variable. Nonmethane Volatile Organic Compounds (NMVOCs). Non-CH 4

### volatile organic compounds include substances such as propane, butane, and ethane. These compounds participate, along with NO x 

### , 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 NO x 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 aerosols 13 

### (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

13 Carbonaceous aerosols are aerosols that are comprised mainly of organic substances and forms of black carbon (or soot) (IPCC 2001).

14 Volcanic activity can inject significant quantities of aerosol producing sulfur dioxide and other sulfur compounds into the stratosphere, which can result in a longer negative forcing effect (i.e., a few years) (IPCC 1996). 

### 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 CO 2 

### , and therefore GWP weighted emissions are measured in teragrams of CO 2 

### equivalents (Tg CO 2 

### Eq.) 15 

### The relationship between gigagrams (Gg) of a gas and Tg CO 2 

### 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 CO 2 

### 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., CO 2 

### , CH 4 

### , N 2 

### O, HFCs, PFCs, and SF 6 

### ) tend to be evenly distributed throughout the atmosphere, and consequently global average concentrations can be

15 Carbon comprises 12/44 ths 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 CO 2 

### Eq. = Teragrams of CO 2 

### Equivalents Gg = Gigagrams (equivalent to a thousand metric tons) GWP = Global Warming Potential Tg = Teragrams Tg CO 2 

### 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 GWP a CO 2 50–200 1 CH 4 b 12 ± 3 21 N 2 O 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 CF 4 50,000 6,500 C 2 F 6 10,000 9,200 C 4 F 10 2,600 7,000 C 6 F 1 4 3,200 7,400 SF 6 3,200 23,900 Source: (IPCC 1996)

a 100-year time horizon b The GWP of CH 4 includes the direct effects and those indirect effects due to the production of tropospheric ozone and stratospheric water vapor. The indirect effect due to the production of CO 2 is not included.



### determined. The short-lived gases such as water vapor, carbon monoxide, tropospheric ozone, ozone precursors (e.g., NO x 

### and NMVOCs), and tropospheric aerosols (e.g., SO 2 

### 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 isresponsible 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 usedthroughout 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 CO 2 radiative forcing and an improved CO 2 response function. The GWPs are drawn from IPCC/TEAP (2005) and the TAR, with updates for those cases where new laboratory or radiative transfer results have been published. Additionally, the atmospheric lifetimes of some gases have been recalculated. In addition, the values for radiative forcing and lifetimes have been recalculated for a variety of halocarbons, which were not presented in the SAR. Table 1-3 presents the new GWPs, relative to those presented in the SAR.



### Table 1-3: Comparison of 100-Year GWPs

Gas SAR TAR AR4 Change from SAR TAR AR4 CO 2 1 1 1 NC 0 CH 4 * 21 23 25 2 4 N 2 O 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 CF 4 6,500 5,700 7,390 (800) 890 C 2 F 6 9,200 11,900 12,200 2,700 3,000 C 4 F 10 7,000 8,600 8,860 1,600 1,860 C 6 F 1 4 7,400 9,000 9,300 1,600 1,900 SF 6 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 CH 4 includes the direct effects and those indirect effects due to the production of tropospheric ozone and stratospheric water vapor. The indirect effect due to the production of CO 2 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 inventories 17 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 CO 2emissions 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 ofthis 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 Qual a 2006 Emissions (Tg CO 2 Eq.) Energy

CO 2 Emissions from Stationary Combustion-Coal CO 2 ✓ ✓ ✓ ✓ 2,065.3 CO 2 Emissions from Mobile Combustion: Road & Other CO 2 ✓ ✓ ✓ ✓ 1,643.0 CO 2 Emissions from Stationary Combustion-Gas CO 2 ✓ ✓ ✓ 1,121.9 CO 2 Emissions from Stationary Combustion-Oil CO 2 ✓ ✓ ✓ ✓ 594.3 CO 2 Emissions from Mobile Combustion: Aviation CO 2 ✓ ✓ ✓ ✓ 170.6 CO 2 Emissions from Non-Energy Use of Fuels CO 2 ✓ ✓ 138.0 CO 2 Emissions from Mobile Combustion: Marine CO 2 ✓ ✓ ✓ ✓ 42.4 CO 2 Emissions from Natural Gas Systems CO 2 ✓ ✓ ✓ ✓ 28.5 CO 2 Emissions from Municipal Solid Waste Combustion CO 2 ✓ ✓ 20.9 Fugitive CH 4 Emissions from Natural Gas Systems CH 4 ✓ ✓ ✓ ✓ 102.4 Fugitive CH 4 Emissions from Coal Mining CH 4 ✓ ✓ ✓ ✓ 58.5 Fugitive CH 4 Emissions from Petroleum Systems CH 4 ✓ ✓ ✓ ✓ 28.4 N 2 O Emissions from Mobile Combustion: Road & Other N 2 O ✓ ✓ ✓ ✓ 31.1 International Bunker Fuels b Several ✓ 128.4 Industrial Processes

CO 2 Emissions from Iron and Steel Production CO 2 ✓ ✓ ✓ ✓ 49.1 CO 2 Emissions from Cement Production CO 2 ✓ ✓ ✓ ✓ 45.7 CO 2 Emissions from Ammonia Production and Urea Application CO 2 ✓ ✓ 12.4 N 2 O Emissions from Adipic Acid Production N 2 O ✓ ✓ 5.9 Emissions from Substitutes for Ozone Depleting Substances Several ✓ ✓ ✓ ✓ 110.4 HFC-23 Emissions from HCFC-22 Production HFCs ✓ ✓ ✓ ✓ 13.8 SF 6 Emissions from Electrical Transmission and Distribution SF 6 ✓ ✓ 13.2 PFC Emissions from Aluminum Production PFCs ✓ ✓ 2.5 Agriculture

CH 4 Emissions from Enteric Fermentation CH 4 ✓ ✓ ✓ ✓ 126.2 CH 4 Emissions from Manure Management CH 4 ✓ ✓ ✓ 41.4 Direct N 2 O Emissions from Agricultural Soil Management N 2 O ✓ ✓ ✓ ✓ 214.7 Indirect N 2 O Emissions from Applied Nitrogen N 2 O ✓ ✓ ✓ ✓ 50.3 Waste

CH 4 Emissions from Landfills CH 4 ✓ ✓ ✓ ✓ 125.7 Land Use, Land Use Change, and Forestry CO 2 Emissions from Forest Land Remaining Forest Land CO 2 ✓ ✓ (745.1) CO 2 Emissions from Settlements Remaining Settlements CO 2 ✓ ✓ (95.5) CO 2 Emissions from Cropland Remaining Cropland CO 2 ✓ ✓ (33.8) CO 2 Emissions from Grassland Remaining Grassland CO 2 ✓ 16.2 CO 2 Emissions from Landfilled Yard Trimmings and Food Scraps CO 2 ✓ (10.5) CO 2 Emissions from Land Converted to Cropland CO 2 ✓ 9.4 CH 4 Emissions from Forest Land Remaining Forest Land CH 4 ✓ 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 CO 2 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 CO 2 

### 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 CH 4

### and N 2 

### O 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 SF 6 

### from electrical transmission and distribution is limited due to a lack of activity data regarding national SF 6 

### 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 CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Mean b Standard Deviation Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) (Tg CO 2 Eq.) Lower Bound c Upper Bound c Lower Bound c Upper Bound c CO 2 5,983.1 5,884.9 6,288.6 -2% 5% 6,082.2 105.5 CH 4 555.3 508.4 658.2 -8% 19% 576.6 38.9 N 2 O 367.9 352.2 449.3 -4% 22% 398.4 25.0 PFC, HFC & SF 6 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 CH 4 , N 2 O 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: Descr iption 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 di scussion on any sourcespecific planned improvements, if applicable. Special attention is given to CO 2 

### 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 N 2 O 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 CO 2 , CH 4 , and N 2 O 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 CO 2 Emissions from Fossil Fuel Combustion 2.1. Methodology for Estimating Emissions of CO 2 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 CH 4 , N 2 O, and Indirect Greenhouse Gases from Stationary Combustion 3.2. Methodology for Estimating Emissions of CH 4 , N 2 O, and Indirect Greenhouse Gases from Mobile Combustion and Methodology for and Supplemental Information on Transportation-Related Greenhouse Gas Emissions 3.3. Methodology for Estimating CH 4 Emissions from Coal Mining 3.4. Methodology for Estimating CH 4 Emissions from Natural Gas Systems 3.5. Methodology for Estimating CH 4 and CO 2 Emissions from Petroleum Systems 3.6. Methodology for Estimating CO 2 and N 2 O 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 CH 4 Emissions from Enteric Fermentation 3.10. Methodology for Estimating CH 4 and N 2 O Emissions from Manure Management 3.11. Methodology for Estimating N 2 O 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 CH 4 Emissions from Landfills ANNEX 4 IPCC Reference Approach for Estimating CO 2 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 CO 2 

### 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 CO 2 

### 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 (CO 2 

### ) 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 CO 2

### 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 CO 2 

### Eq.). Historically, changes in emissions from fossil fuel combustion have been the dominant factor affecting U.S. emission trends. Changes in CO 2 

### 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.

1 Estimates are presented in units of teragrams of carbon dioxide equivalents (Tg CO 2 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 8,000Tg CO2Eq.6,14819906,10619916,19219926,34319936,43519946,49419956,73119966,76019976,80119986,83919997,03320006,92120016,98120026,99820037,07820047,13020057,0542006 HFCs, PFCs, & SF 6 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 CO 2 

### 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 CO 2 

### 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 1,000Tg CO2Eq.

-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 CO 2 

### 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 CO 2 

### increased by 914.6 Tg CO 2 

### Eq. (18 percent), while CH 4 

### and
N 2 

### O emissions decreased by 50.8 Tg CO 2 

### Eq. (8 percent) and 15.5 Tg CO 2 

### Eq. (4 percent) respectively. During the same period, aggregate weighted emissions of HFCs, PFCs, and SF 6 

### rose by 57.6 Tg CO 2 

### Eq. (64 percent). Despite being emitted in smaller quantities relative to the other principal greenhouse gases, emissions of HFCs, PFCs, and SF 6 

### are significant because many of them have extremely high GWPs and, in the cases of PFCs and SF 6 

### , 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 CO 2

### 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 CO 2 

### Eq. (17 percent), 21.0 Tg CO 2 

### Eq. (7 percent), and 6.6 Tg CO 2 

### Eq. (1 percent), respectively. Emissions decreased in the Waste and Solvent and Other Product Use sectors by 18.6 Tg CO 2 

### Eq. (10 percent) and less than 0.02 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 Consumption b 219.3 236.8 227.3 203.2 204.4 209.5 224.8 227.4 234.7 International Bunker Fuels b 113.7 100.6 101.1 97.6 89.1 103.6 119.0 122.6 127.1 CH 4 606.1 598.9 574.3 558.8 563.5 559.4 545.6 539.7 555.3

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 CO 2 

### 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 Fuels b 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 N 2 O 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 N 2 O 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 Fuels b 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

Substances c 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 SF 6 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 CO 2 Eq.

a The net CO 2 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 CO 2 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 Consumption b 219,341 227,276 203,163 204,351 209,537 224,825 227,366 234,726 International Bunker Fuels b 113,683 101,125 97,563 89,101 103,583 118,975 122,580 127,097 CH 4 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 Fuels b 8 6 5 4 6 7 7 7 N 2 O 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 N 2 O 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 Fuels b 3 3 3 3 3 3 4 4 HFCs M M M M M M M M

Substitution of Ozone Depleting

Substances c 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 SF 6 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 CO 2 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. CO 2 

### 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 CO 2 

### as well as other greenhouse gas emissions from energy consumption is presented in the Energy chapter. Energy-related activities are also responsible for CH 4 

### and N 2 

### O 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.

CO 2

### 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 CO 2 

### emissions fromfossil 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 SectorTg CO2Eq.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 CO 2 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 CO 2 

### 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 CO 2 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 CO 2 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only included in n et 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 CO 2 

### emissions from fossil fuel combustion by end-use sector. The main driver of emissions in the energy sector is CO 2 

### from fossil fuel combustion. The transportation enduse sector accounted for 1,861.0 Tg CO 2 

### Eq. in 2006, or approximately 33 percent of total CO 2 

### 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 CO 2

### emissions from fossil fuel combustion. The residential and commercial end-use sectors accounted for an average 20 and 18 percent, respectively, of CO 2 

### 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:

3 Note that electricity generation is the largest emitter of CO 2when electricity is not distributed among end-use sectors. 

### Figure 2-6 2006 U.S. Fossil Carbon Flows (Tg CO 2 

### 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 CO 2 

### emissions from fossil fuel combustion increased from 4,724.1 Tg CO 2 

### Eq. to 5,637.9 Tg CO 2 

### Eq.—a 19.3 percent total increase over the sixteen-year period. From 2005 to 2006, these emissions decreased by 93.1 Tg CO 2 

### Eq. (1.6 percent).

• CO 2 

### emissions from non-energy use of fossil fuels have increased 20.8 Tg CO 2 

### Eq. (18 percent) from 1990 through 2006. Emissions from non-energy uses of fossil fuels were 138.0 Tg CO 2 

### Eq. in 2006, which constituted 2.4 percent of overall fossil fuel CO 2 

### emissions and 2.3 percent of total national CO 2 

### emissions, approximately the same proportion as in 1990.

• CH 4

### emissions from natural gas systems were 102.4 Tg CO 2

### Eq. in 2006; emissions have declined by 22.3 Tg CO 2 

### 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.

• CH 4 

### emissions from coal mining were 58.5 Tg CO 2 

### Eq. This decline of 25.6 Tg CO 2 

### Eq. (30 percent) from 1990 results from the mining of less gassy coal from underground mines and the increased use of CH 4 

### collected from degasification systems.

• In 2006, N 2 

### O emissions from mobile combustion were 33.1 Tg CO 2 

### Eq. (approximately 9 percent of U.S. N 2 

### O emissions). From 1990 to 2006, N 2 

### O emissions from mobile combustion decreased by 24 percent. However, from 1990 to 1998 emissions increased by 26 percent, due to control technologies that reduced NO x 

### emissions Table 2-4: Emissions from Energy (Tg CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 CH 4 260.7 246.8 234.5 232.0 226.9 224.6 217.4 202.3 203.3

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 N 2 O 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 N 2 

### O emissions. Since 1998, newer control technologies have led to a steady decline in N 2 

### O from this source.

• CO 2 

### emissions from municipal solid waste combustion (20.9 Tg CO 2 

### Eq. in 2006) increased by 10.0 Tg CO 2 

### Eq. (91 percent) from 1990 through 2006, as the volume of plastics and other fossil carbon-containing materials in municipal solid waste grew. 

# Industrial ProcessesEmissions 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 CO 2 

### , CH 4 

### , and N 2 

### O. 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 CO 2 

### Emissions from Fossil Fuel Combustion by Sector and Fuel Type

Note: Electricity generation also includes emissions of less than 0.5 Tg CO 2 Eq. from geothermal-based electricity generation. Natural Gas Petroleum Coal

0 500 1,000 1,500 2,000 2,500

Relative Contribution by Fuel TypeTg CO2Eq.

U.S. Territories Residential Commercial Industrial Transportation Electricity Generation 

### Figure 2-8 2006 End-Use Sector Emissions of CO 2 

### from Fossil Fuel Combustion

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000

Transportation U.S. Territories Residential Commercial Industrial From Electricity Consumption From Direct Fossil Fuel CombustionTg CO2Eq. 

### Table 2-5: CO 2 

### Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO 2 

### 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, CO 2 

### 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 SF 6 

### . 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 CO 2 

### 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

.

• CO 2 

### and CH 4 

### emissions from iron and steel production increased by 5.2 percent to 50.1 Tg CO 2 

### Eq. in 2006, but have declined overall by 37.5 Tg CO 2 

### 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 CO 2 

### Eq.) from 1990 to 2006, due to both industry emission reduction efforts and lower domestic aluminum production.

• N 2 

### O emissions from adipic acid production were 5.9 Tg CO 2 

### 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 CO 2 

### Eq. annually since 1998.

• CO 2 

### emissions from ammonia production and urea consumption (12.4 Tg CO 2 

### Eq. in 2006) have decreased by 4.5 Tg CO 2 

### 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, N 2 

### O Emissions from Product Uses, the only source of greenhouse gas emissions from this sector, accounted for 4.4 Tg CO 2 

### Eq., or less than 0.1 percent of total U.S. emissions in 2006 (see Table 2-7).

• In 2006, N 2 

### O emissions from product uses constituted 1 percent of U.S. N 2 

### O 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 CO 2 Eq. <0.5 Silicon Carbide Production and Consumption <0.5 Lead Production 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 CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 175.0 171.6 166.5 151.9 151.0 147.8 151.8 145.9 149.5

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 CH 4 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 + + + + + + + + + N 2 O 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 Substances a 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 SF 6 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 CO 2 Eq.

a Small amounts of PFC emissions also result from this source. Note: Totals may not sum due to independent rounding.



### Table 2-7: N 2 

### O Emissions from Solvent and Other Product Use (Tg CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 N 2 O 4.4 4.6 4.9 4.9 4.4 4.4 4.4 4.4 4.4

N 2 O 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 CO 2 

### Eq., or 6.4 percent of total U.S. greenhouse gas emissions (see Table 2-8). CH 4 

### and N 2 

### O were the primary greenhouse gases emitted by agricultural activities. CH 4 

### emissions from enteric fermentation and manure management represented about 23 percent and 7 percent of total CH 4 

### 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. N 2 

### O 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
N 2 

### O emissions in the United States in 2006. Estimated emissions from this source in 2006 were 265.0 Tg CO 2

### Eq. Annual N 2 

### O 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 CH 4 

### emissions in 2006, at 126.2 Tg CO 2 

### 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 CH 4 

### , from 31.0 Tg CO 2 

### Eq. in 1990 to 41.4 Tg CO 2 

### Eq. in 2006; and an increase of 18 percent for N 2 

### O, from 12.1 Tg CO 2 

### Eq. in 1990 to 14.3 Tg CO 2 

### 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 CO 2 Eq. Agriculture as a Portion of all Emissions

100 150 265.0

6.4%



### Table 2-8: Emissions from Agriculture (Tg CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 165.7 175.8 171.7 172.2 172.6 173.0 170.9 174.0 174.4

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 N 2 O 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 CH 4 

### 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 CO 2

### 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 CO 2 

### Eq. (Table 2-9). This represents an offset of approximately 14.8 percent of total U.S. CO 2 

### 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 CO 2 

### sequestration. Land use, land-use change, and forestry source categories also resulted in emissions of CO 2 

### , CH 4 

### , and N 2 

### O that are not included in the net CO 2 

### 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 CO 2 

### emissions of 8.0 Tg CO 2 

### 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 N 2 

### O emissions of 1.8 Tg CO 2

### Eq. Direct N 2 

### O emissions from fertilizer application increased by approximately 74 percent between 1990 and 2006. Emissions of CH 4 

### and
N 2 

### O 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 CO 2 

### Flux from Land Use, Land-Use Change, and Forestry (Tg CO 2 

### 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 CH 4 

### emissions, accounting for 23 percent of total U.S. CH 4 

### emissions. 4 

### Additionally, wastewater treatment accounts for 4 percent of U.S. CH 4 

### emissions, and 2 percent of N 2 

### O emissions. Emissions of CH 4

### and N 2 

### O from composting grew from 1990 to 2006, and resulted in emissions of 3.3 Tg CO 2 

### 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 CO 2 

### 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 CH 4 

### emissions from landfills decreased by 23.9 Tg CO 2 

### 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 CH 4 

### emissions

5 The CO 2 produced from combusted landfill CH 4 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 CO 2 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 CO 2 

### Eq.)

Source Category 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 CH 4 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 N 2 O 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, CH 4 

### and N 2 

### O emissions from wastewater treatment increased by 0.8 Tg CO 2

### Eq. (4 percent) and 1.8 Tg CO 2

### Eq. (29 percent), respectively.

• CH 4 

### and N 2 

### O emissions from composting each increased by less than 0.1 Tg CO 2 

### Eq. (1 percent) from 2005 to 2006. Emissions from composting have been continually increasing since 1990, from 0.7 Tg CO 2 

### Eq. to 3.3 Tg CO 2 

### 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 CO 2 

### 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 N 2 

### O emissions from agricultural soil management and CH 4 

### emissions from enteric fermentation, rather than CO 2 

### from fossil fuel combustion. The commercial sector accounted for roughly 6 percent of emissions, while U.S. territories accounted for about 1 percent.

CO 2 

### 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 CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 172.9 169.1 146.7 143.0 145.5 151.0 148.1 149.0 151.1

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 N 2 O 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 CO 2 

### Eq. and Percent of Total in 2006)

Sector/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 Percent a 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%

CO 2 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%

CO 2 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%

CO 2 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% N 2 O 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 CO 2 

### Eq. and Percent of Total in 2006)

Sector/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 Percent a Agriculture 506.8 524.1 528.0 533.4 529.3 498.0 499.2 521.3 533.6 7.6%

N 2 O 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% CO 2 from Fossil Fuel Combustion 46.8 57.3 50.9 50.7 52.9 45.0 51.1 45.5 43.6 0.6% CH 4 and N 2 O 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% N 2 O 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%

CO 2 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%

CO 2 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%

CO 2 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%)

CO 2 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%) CO 2 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 CO 2 , CH 4 , N 2 O, HFCs, PFCs, and SF 6 . Parentheses indicate negative values or sequestration. Totals may not sum due to independent rounding. ODS (Ozone Depleting Substances)

+ Does not exceed 0.05 Tg CO 2 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 CO 2 

### 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 CO 2 

### from Fossil Fuel Combustion, CH 4 

### and N 2 

### O from Stationary Combustion, and SF 6 

### 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 CO 2 

### Eq.)

Gas/Fuel Type or Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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

CO 2 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 CH 4 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 N 2 O 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 SF 6 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 2,50019901991199219931994199519961997199819992000200120022003200420052006 Residential Agriculture Electricity GenerationTg CO2Eq. 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 CO 2 

### Eq.) and Percent of Total in 2006

Sector/Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006 Percent a 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%

CO 2 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% CH 4 286.5 273.6 258.3 255.4 251.3 247.8 240.5 226.7 227.1 3.2% N 2 O 40.4 44.8 33.7 28.9 30.6 29.8 29.5 30.0 29.9 0.4% HFCs, PFCs, and SF 6 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%

CO 2 627.7 652.8 733.1 669.2 659.4 681.1 679.2 676.8 650.9 9.1% CH 4 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 + N 2 O 2.9 3.0 3.3 3.0 2.9 3.1 3.0 3.0 2.9 + SF 6 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%

CO 2 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% CH 4 4.5 4.1 3.2 3.1 2.7 2.5 2.4 2.3 2.1 + N 2 O 42.67 52.46 51.53 48.80 44.82 41.26 38.51 35.20 31.96 0.4% HFCs b + 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%

CO 2 3.1 3.1 3.4 3.6 3.5 4.3 4.5 4.7 5.0 0.1% CH 4 + + + + + + + + + + N 2 O + + + + + + + + + + SF 6 + + + + + + + + + + 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%

CO 2 216.1 225.8 228.0 222.3 222.8 236.5 230.6 221.9 210.1 2.9% CH 4 173.8 170.0 147.6 143.8 146.4 151.9 149.0 149.9 152.0 2.1% N 2 O 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%

CO 2 538.7 590.0 743.2 758.1 754.6 754.4 774.3 803.5 801.5 11.2% CH 4 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 + N 2 O 2.5 2.7 3.3 3.4 3.4 3.4 3.5 3.6 3.6 0.1% SF 6 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, CO 2 

### 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 CO 2 

### 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 CH 4 

### emissions from coal mining, byproduct CO 2 

### emissions from cement production, and HFC, PFC, and SF 6 

### byproduct emissions from semiconductor manufacture. Overall, direct industry sectoremissions 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 CO 2 

### Eq.) and Percent of Total in 2006

Sector/Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006 Percent a 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%

CO 2 340.1 356.5 372.1 363.6 360.5 382.9 368.3 358.5 326.5 4.6% CH 4 4.4 4.0 3.4 3.1 3.1 3.3 3.3 3.3 3.1 + N 2 O 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%

CO 2 593.8 645.4 764.4 765.2 792.6 802.9 813.0 856.6 834.4 11.7% CH 4 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 + N 2 O 2.8 3.0 3.4 3.4 3.5 3.6 3.6 3.8 3.7 0.1% SF 6 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%

CO 2 53.8 64.4 58.4 58.5 61.4 53.3 58.7 53.4 51.6 0.7% CH 4 170.3 180.7 190.8 181.8 189.1 181.8 178.0 186.4 199.1 2.8% N 2 O 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%

CO 2 60.0 67.4 58.7 69.0 65.1 61.9 67.3 63.0 61.6 0.9% CH 4 + + + + + + + + + + N 2 O 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 + SF 6 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 CO 2 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 Industrial19901991199219931994199519961997199819992000200120022003200420052006Tg CO2Eq. 

### 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, CO 2 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 CH 4 and N 2 O are also based on the EIA electric utility sector. Additional sources include CO 2 and N 2 O 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 SF 6 from Electrical Transmission and Distribution, and a portion of CO 2 from Limestone and Dolomite Use (from pollution control equipment installed in electricity generation plants).

• In the Transportation economic sector, the CO 2 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 CH 4 and N 2 O 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, CO 2 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 CO 2 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 CH 4 and N 2 O 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 CO 2 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 CO 2 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 CO 2 emissions from fossil fuel combustion, and CH 4 and N 2 O 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 N 2 O emissions from Agricultural Soils, CH 4 from Enteric Fermentation (i.e., exhalation from the digestive tracts of domesticated animals), CH 4 and N 2 O from Manure Management, CH 4 from Rice Cultivation, CO 2 emissions from liming of agricultural soils and urea application, and CH 4 and N 2 O from Forest Fires. N 2 O 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 CO 2 emissions from the combustion of fossil fuels reported for the EIA residential sector. Stationary combustion emissions of CH 4 and N 2 O 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. N 2 O 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 CO 2 emissions from the combustion of fossil fuels reported in the EIA commercial fuel consuming sector data. Stationary combustion emissions of CH 4 and N 2 O 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 CH 4 from Landfills and CH 4 and N 2 O 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 CO 2 

### 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

CO 2 628.8 604.9 643.5 647.9 662.6 642.1 640.0 658.4 634.5 CH 4 2.6 2.1 1.6 1.5 1.4 1.3 1.2 1.1 1.0 N 2 O 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

CO 2 320.7 405.0 466.0 470.3 483.2 518.8 540.8 501.9 514.9 CH 4 1.4 1.4 1.1 1.1 0.9 0.8 0.7 0.7 0.7 N 2 O 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

CO 2 227.8 271.2 341.5 340.6 354.8 351.2 364.1 391.9 401.3 CH 4 + + + + + + + + + N 2 O 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

CO 2 8.3 9.0 10.9 10.0 9.6 10.5 14.7 11.8 12.1 CH 4 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 N 2 O + + + + + + + + + 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

CO 2 1.7 1.8 1.8 1.7 1.7 1.6 1.7 1.6 1.9 CH 4 + + + + + + + + + N 2 O + + + + + + + + +

### Trends in Greenhouse Gas Emissions 2-25 Table 2-15: Transportation-Related Greenhouse Gas Emissions (Tg CO 2 

### Eq.)

Gas/Vehicle Type 1990 1995 2000 2001 2002 2003 2004 2005 2006 Commercial Aircraft—Domestic a 138.1 144.6 165.9 154.4 147.6 145.4 144.4 152.0 143.6

CO 2 136.7 143.1 164.2 152.9 146.1 143.9 142.9 150.4 142.1 CH 4 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 N 2 O 1.3 1.4 1.6 1.5 1.4 1.4 1.4 1.5 1.4 Other Aircraft—Domestic b 43.8 31.9 32.6 34.1 32.2 31.1 34.5 31.1 28.8

CO 2 43.3 31.5 32.2 33.7 31.9 30.8 34.1 30.8 28.5 CH 4 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 N 2 O 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Ships and Boats—Domestic c 47.0 56.6 65.1 47.4 65.4 38.3 47.1 50.8 47.7

CO 2 46.5 55.5 61.0 43.2 60.8 33.6 42.1 45.6 42.4 CH 4 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 N 2 O 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

CO 2 38.1 42.2 45.1 45.4 44.9 46.6 49.2 49.8 51.0 CH 4 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 N 2 O 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 Pipelines d 36.1 38.2 35.2 33.6 36.6 32.7 31.2 32.3 32.4

CO 2 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

CO 2 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 Fuels f 114.8 101.6 102.2 98.6 90.0 104.6 120.2 123.8 128.4 + Does not exceed 0.05 Tg CO 2 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 CO 2 estimates reflect natural gas used to power pipelines, but not electricity. While the operation of pipelines produces CH 4 and N 2 O, 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 CO 2 

### from fossil fuel combustion, which increased by 25 percent from 1990 to 2006. This rise in CO 2 

### emissions, combined with an increase in HFCs from virtually no emissions in 1990 to 69.5 Tg CO 2 

### 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 beenincreasing 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 CH 4

### emissions in the United States, and agricultural soil management was the largest source of N 2 

### O emissions in the U.S. This sector also includes small amounts of CO 2 

### 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 CO 2 

### 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 Rate a GDP b 100 113 138 139 141 145 150 155 159 3.0% Electricity Consumption c 100 112 127 125 128 129 131 134 135 1.9% Fossil Fuel Consumption c 100 107 117 115 116 116 119 119 117 1.0% Energy Consumption c 100 108 116 112 115 115 118 118 117 1.0% Population d 100 107 113 114 115 116 117 118 119 1.1% Greenhouse Gas Emissions e 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 110Index (1990 = 100)19901991199219931994199519961997199819992000200120022003200420062005 

### 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, NO x 

# , NMVOCs, and SO 2 

# )

The reporting requirements of the UNFCCC 7 

### request that information be provided on indirect greenhouse gases,

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

### which include CO, NO x 

### , NMVOCs, and SO 2 

### . 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 SO 2 

### , by affecting the absorptive characteristics of the atmosphere. Additionally, some of

Table 2-17: Emissions of NO x 

### , CO, NMVOCs, and SO 2 

### (Gg)

Gas/Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006 NO x 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 SO 2 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 NO 2 

### ) are created by lightning, fires, fossil fuel combustion, and in the stratosphere from N 2 

### O. Non-CH 4 

### 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, SO 2 

### 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 NO x 

### is their role as precursors for tropospheric ozone formation. They can also alter the atmospheric lifetimes of other greenhouse gases. Another example of indirect greenhouse gas formation into greenhouse gases is CO’s interaction with the hydroxyl radical—the major atmospheric sink for CH 4 

### emissions—to form CO 2 

### . Therefore, increased atmospheric concentrations of CO limit the number of hydroxyl molecules (OH) available to destroy CH 4 

### . Since 1970, the United States has published estimates of annual emissions of CO, NO x 

### , NMVOCs, and SO 2 

### (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, NO x 

### , and NMVOCs.

8 Estimates from preliminary data (EPA 2008) and disaggregated based on EPA (2003). NO x and CO emission estimates from field burning of agricultural residues were estimated separately, and therefore not taken from EPA (2008). Sulfur dioxide (SO 2 ) 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 SO 2 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 SO 2 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 SO 2 emissions in the Clean Air Act. Electricity generation is the largest anthropogenic source of SO 2 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 (CO 2 

### ) equivalent basis in 2006. This included 97, 37, and 13 percent of the nation’s CO 2 

### , methane (CH 4 

### ), and nitrous oxide (N 2 

### O) emissions, respectively. Energyrelated CO 2 

### emissions alone constituted 83 percent of national emissions from all sources on a CO 2 

### equivalent basis, while the non-CO 2 

### 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 CO 2 

### being the primary gas emitted (see Figure 3-1). Globally, approximately 28,193 Tg of CO 2 

### 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 CO 2 

### emissions, they are considered separately, and in more detail than other energy-related emissions (see Figure 3-2). Fossil fuel combustion also emits CH 4 

### and N 2 

### O, as well as indirect greenhouse gases such as nitrogen oxides (NO x 

### ), carbon monoxide (CO), and non-CH 4 

### volatile organic compounds (NMVOCs). Mobile fossil fuel combustion was the second largest source of N 2 

### O 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 CH 4 

### from natural gas systems, petroleum systems, and coal mining. Smaller quantities of CO 2 

### , CO, NMVOCs, and NO x 

### are also emitted.

The combustion of biomass and biomass-based fuels also emits greenhouse gases. CO 2

### 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 CO 2 

### 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 CO 2 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 CO 2 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 CO 2 

### 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: CO 2 

### , CH 4 

### , and N 2 

### O Emissions from Energy (Tg CO 2 

### Eq.)

Gas/Source 1990 1995 2000 CO 2 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

Consumption a 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 CH 4 260.8 246.8 234.5 232.0 226.9 224.6 217.4 202.4 203.3

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: CO 2 

### , CH 4 

### , and N 2 

### O Emissions from Energy (Tg CO 2 

### Eq.)

Gas/Source 1990 1995 2000 N 2 O 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: CO 2 

### , CH 4 

### , and N 2 

### O Emissions from Energy (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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

Consumption a 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 CH 4 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 N 2 O 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 CO 2 

### equivalents (Tg CO 2 

### 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 CO 2 

### Eq. in 2006, an increase of 17 percent since 1990. 

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

CO 2 

### 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, CO 2 

### emissions from fossil fuel combustion were 5,637.9 Tg CO 2 

### Eq., or 19 percent above emissions in 1990 (see Table 3-3). 2



### Trends in CO 2 

### 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).

CO 2 

### 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: CO 2 

### Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg CO 2 

### 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 Geothermal a 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 CO 2 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

2 An 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 CO 2 

### Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg CO 2 

### 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% Transportation a 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 Sectors b All Fuels b 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)19901991199219931994199519961997199819992000200120022003200420052006 0 20 40 60 80 100 120

Fossil Fuels Total Energy

Renewable & NuclearEnergy 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 CO 2 

### 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 TypeTg CO2Eq.

U.S. Territories Residential Commercial Industrial Transportation Electricity Generation Note: Electricity generation also includes emissions of less than 0.5 Tg CO 2 Eq. from geothermal-based electricity generation.



### heat or electricity using natural gas instead of coal can reduce the CO 2 

### 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 CO 2 

### 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 20Index Normal = 100(Deviation from Normal)

Normal (1,242 Cooling Degree Days) 99% Confidence19501952195419561958196019621964196619681970197219741976197819801982198419861988199019921994199619982000200220042006

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 1219501952195419561958196019621964196619681970197219741976197819801982198419861988199019921994199619982000200220042006Index 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 inter val).



### 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 CO 2 

### and smaller amounts of other gases, including CH 4 

### , CO, and NMVOCs. 5 

### These other C containing non-CO 2 

### gases are emitted as a byproduct of incomplete fuel combustion, but are, for the most part, eventually oxidized to CO 2 

### in the atmosphere. Therefore, it is assumed that all the C in fossil fuels used to produce energy is eventually converted to atmospheric CO 2 

### .

5 See the sections entitled Stationary Combustion and Mobile Combustion in this chapter for information on non-CO 2 gas emissions from fossil fuel combustion. 1 2

1

2

### Energy 3-7 Box 3-1: Weather and Non-Fossil Energy Effects on CO 2 

### from Fossil Fuel Combustion Trends

Although no new U.S. nuclear power plants have been constructed in recent years, the utilization (i.e., capacity factors 6 ) 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) 1 2

1

2



### Figure 3-8 Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the United States (1974–2006)20042002200620001998199619941992199019881986198419821980197819761974 0 10 20 30 40 50 60 70 80Capacity 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, CO 2 

### 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 CO 2 

### 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: CO 2 

### Emissions from International Bunker Fuels (Tg CO 2 

### 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: CO 2 

### Emissions from Fossil Fuel Combustion by End-Use Sector (Tg CO 2 

### 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 CO 2 

### from Fossil Fuel Combustion

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000

Transportation U.S. Territories Residential Commercial Industrial From Electricity Consumption From Direct Fossil Fuel CombustionTg CO2Eq.



### Figure 3-9 summarize CO 2 

### 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 CO 2 

### in 2006, representing 33 percent of total CO 2 

### 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 CO 2 

### 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 CO 2

### 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 CO 2 

### emissions by mode and fuel type.) Domestic transportation CO 2 

### 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 CO 2 

### 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 CH 4 

### and N 2 

### O; 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 CO 2 

### , N 2 

### O, CH 4 

### , and HFCs. Carbon dioxide emissions from passenger cars and light-duty trucks totaled 1,151.3 Tg in 2006, an increase of

7 Note that electricity generation is the largest emitter of CO 2when electricity is not distributed among end-use sectors.

### Energy 3-9 Table 3-7: CO 2 

### Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg CO 2 

### 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 Trucks b 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 Trucks b 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 Boats c 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 Trucks b 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 CO 2 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 CO 2 

### 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 2519901991199219931994199519961997199819992000200120022003200420052006Miles 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 TrucksModel Sales (’000)19901992199119931994199519961997199819992000200120022003200420052006 

### Medium- and heavy-duty truck 8 

### CO 2 

### 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. CO 2 

### 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 aviation 9 

### , CO 2 

### emissions decreased by approximately 5.2 percent (9.4 Tg CO 2 

### ) 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 CO 2 

### 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, CO 2 

### 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, CO 2 

### emissions from fossil fuel combustion and electricity use within the industrial end-use sectors were 1,571.0 Tg CO 2 

### 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 CO 2 

### 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, CO 2 

### emissions from fossil fuel combustion and electricity use within the residential and commercial end-use sectors were 1,151.9 Tg CO 2 

### Eq. and 1,003.0 Tg CO 2 

### 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 thanprevailing 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 12019901991199219931994199519961997199819992000200120022003200420052006 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 CO 2 

### emissions in the United States, representing 39 percent of total CO 2 

### emissions from all CO 2 

### emissions sources across the United States. Electricity generation also accounted for the largest share of CO 2 

### 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, CO 2 

### 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 CO 2 

### emissions from fossil fuel combustion is conceptually similar to the approach recommended by theIPCC 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 isestimated 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 Sector19741976197819801982198419861988199019921994199619982000200220042006 400 600 800 1,000 1,200 1,400 1,600

Residential

Commercial IndustrialBillion 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 CO 2 Eq. in 2006.

13 See IPCC Reference Approach for estimating CO 2 emissions from fossilfuel combustion in Annex 4 for a comparison of U.S. estimates using topdown and bottom-up approaches.

14 A crude convention to convert between gross and net calorific values is to multiply the heat content of solid and liquid fossil fuels by 0.95 and gaseous fuels by 0.9 to account for the water content of the fuels. Biomass-based fuels in U.S. energy statistics, however, are generally presented using net calorific values. 

### 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 CO 2 

### . 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 CO 2 

### . Fuels with biogenic origins are assumed to result in no net CO 2 

### 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 CO 2 

### to Canada by pipeline. Since this CO 2 

### is not emitted to the atmosphere in the United States, energy used to produce this CO 2 

### 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 CO 2 

### 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.

16 These 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 CO 2 

### . 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 CO 2 

### Emissions. Total CO 2 

### 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 CO 2 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 CO 2 in the energy conversion process, such as renewable (i.e., hydropower, biofuels, geothermal, solar, and wind) and nuclear sources. 18 Energy-related CO 2 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 CO 2 Eq./QBtu for natural gas to upwards of 95 Tg CO 2 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 CO 2 Eq./Btu). Energy generated from nuclear and many renewable sources do not result in direct emissions of CO 2 . Biofuels such as wood and ethanol are also considered to be C neutral; although these fuels do emit CO 2 , in the long run the CO 2 emitted from biomass consumption does not increase atmospheric CO 2 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 CO 2 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 CO 2 

### Eq./QBtu)

Sector 1990 1995 2000 2001 2002 2003 2004 2005 2006 Residential a 57.3 56.6 56.7 56.9 56.6 56.8 56.9 56.6 56.7 Commercial a 59.2 57.8 57.1 57.4 57.0 57.3 57.6 57.6 57.5 Industrial a 63.7 62.7 62.6 63.5 62.8 63.2 63.6 64.0 64.2 Transportation a 71.0 71.0 71.0 71.0 71.0 71.0 71.0 71.1 71.1 Electricity Generation b 86.7 86.0 85.6 85.2 85.0 85.7 85.4 85.0 84.6 U.S. Territories c 74.1 74.1 73.2 73.6 73.7 74.0 74.6 74.6 74.6 All Sectors c 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 CO 2 , 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 10 18 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 CO 2 . (continued)



### Table 3-9: Carbon Intensity from all Energy Consumption by Se

Sector 1990 1995 2000 Transportation a 70.8 70.6 70.6 

### ctor (Tg

2001 70.5 

### CO 2 

### Eq./QBtu)

2002 70.5 2003 70.3 2004 70.2 2005 70.1 2006 70.0 Other End-Use Sectors a, b 57.5 56.4 57.7 58.4 57.6 58.0 58.0 58.2 57.5 Electricity Generation c 59.0 57.9 59.9 All Sectors d 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 resultedin 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 CO 2 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 CO 2 

### Emissions Per Capita and Per Dollar GDP

75 80 85 90 95 100 105 110

CO 2 /Energy Consumption CO 2 /Capita

CO 2 /$GDP Energy Consumption/ CapitaIndex (1990 = 100)

7019901991199219931994199519961997199819992000200120022003200420052006 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, CO 2 

### 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 aircraftperformance, 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 CO 2 ) and International Bunker Fuels sections of the Energy chapter, Annex 3.2, and Annex 3.7.

### Energy 3-17 

# Uncertainty

For estimates of CO 2 

### from fossil fuel combustion, the amount of CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### emissions in 2006 were estimated to be between 5,542.9 and 5,944.7 Tg CO 2 

### Eq. at a 95 percent confidence level. This

Table 3-10: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Energy-Related Fossil Fuel Combustion by Fuel Type and Sector (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Fuel/Sector (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Coal b 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 Gas b 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% Petroleum b 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 CO 2 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. 26 Although, in general, random uncertainties are the main focus of statistical uncertainty analysis, when the uncertainty estimates are elicited from experts, their estimates include both random and systematic uncertainties. Hence, both these types of uncertainties are represented in this uncertainty analysis.

### Energy 3-19 indicates a range of 2 percent below to 5 percent above the 2006 emission estimate of 5,637.9 Tg CO 2 

### Eq.


# QA/QC and Verification A source-specific QA/QC plan for CO 2 

### 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 CO 2 

### 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 CO 2 

### Eq. (less than 0.1 percent) in CO 2 

### emissions from fossil fuel combustion for the period 1990 through 2005. 

# Planned Improvements To reduce uncertainty of CO 2

### 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 CO 2 

### 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).

CO 2 

### 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 CO 2

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### Eq.) in these fuels was stored, while the remaining 37.6 Tg C (138.0 Tg CO 2 

### Eq.) was emitted. The proportion of C emitted as CO 2 

### 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: CO 2 

### Emissions from Non-Energy Use Fossil Fuel Consumption (Tg CO 2 

### 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 Use a Coefficient Carbon Storage Stored Sector/Fuel Type (TBtu) (Tg C/QBtu) (Tg C) Factor (Tg C) Carbon Emissions (Tg C) Carbon Emissions (Tg CO 2 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 CO 2 

### 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 CO 2 

### 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 productionstatistics 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 CO 2 

### Emissions from Non-Energy Uses of Fossil Fuels (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Feedstocks CO 2 83.0 66.4 99.5 -20% +20% Asphalt CO 2 0.0 0.1 0.7 NA NA Lubricants CO 2 19.1 15.7 22.1 -17% +16% Waxes CO 2 0.8 0.6 1.2 -23% +59% Other CO 2 35.2 16.5 38.3 -53% +9% Total CO 2 138.0 110.2 150.3 -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 Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Feedstocks CO 2 62% 59% 64% -4% +3% Asphalt CO 2 100% 99% 100% -1% +0% Lubricants CO 2 9% 4% 18% -58% +89% Waxes CO 2 58% 44% 69% -24% +19% Other CO 2 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 CO 2 

# ) (IPCC Source Category 1A)

Stationary combustion encompasses all fuel combustion activities from fixed sources (versus mobile combustion). Other than CO 2 

### , which was addressed in the previous section, gases from stationary combustion include the greenhouse gases CH 4 

### and N 2 

### O and the indirect greenhouse gases NO x 

### , 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.

N 2 

### O 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. CH 4 

### emissions from stationary combustion are primarily a function of the CH 4 

### content of the fuel and combustion efficiency.

Emissions of CH 4 

### decreased 16 percent overall since 1990 to 6.2 Tg CO 2 

### Eq. (296 Gg) in 2006. This decrease in CH 4

### emissions was primarily due to lower wood consumption in the residential sector. Conversely, N 2 

### O emissions rose 13 percent since 1990 to 14.5 Tg CO 2 

### Eq. (47 Gg) in 2006. The largest source of N 2 

### O emissions was coal combustion by electricity generators, which alone accounted for 66 percent

28 Sulfur dioxide (SO 2 ) emissions from stationary combustion are addressed in Annex 6.3. 

### of total N 2 

### O emissions from stationary combustion in 2006. Overall, however, stationary combustion is a small source of CH 4 

### and N 2 

### O in the United States. Table 3-16 and Table 3-17 provide CH 4 

### and N 2 

### O emission estimates in Tg CO 2 

### Eq.; Table 3-18 and Table 3-19 present these estimates in Gg of each gas. 

# Methodology

CH 4 

### and N 2 

### O 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 CH 4 

### and N 2 

### O 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, CH 4 and N 2 O emissions from combustion by U.S. territories are only included in the stationary combustion totals.

30 Though emissions from construction and farm use occur due to both stationary and mobile sources, detailed data 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: CH 4 

### Emissions from Stationary Combustion (Tg CO 2 

### 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 CO 2 Eq. Note: Totals may not sum due to independent rounding. + 6.2 + 6.2 + 6.4 + 6.5 + 6.5 + 6.2



# Uncertainty

CH 4 

### 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 CH 4 

### and N 2 

### O 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 CH 4 

### and N 2 

### O stationary source inventory estimation models with the model for CO 2 

### 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 CO 2 

### 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 N 2 

### O 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

31 SAIC/EIA (2001) characterizes the underlying probability density function for the input variables as a combination of uniform and normal distributions (the former distribution to represent the bias component and the latter to represent the random component). However, for purposes of the current uncertainty analysis, it was determined that uniform distribution was more appropriate to characterize the probability density function underlying each of these variables.

### 3-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 Table 3-17: N 2 

### O Emissions from Stationary Combustion (Tg CO 2 

### 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 CO 2 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 CH 4 

### 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 CH 4 

### emissions in 2006 ( including biomass) were estimated to be between 4.3 and 13.4 Tg CO 2 

### 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 CO 2

### Eq. 33 

### Stationary combustion N 2 

### O emissions in 2006 ( including biomass) were estimated to be between 11.0 and 42.2 Tg CO 2 

### 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 CO 2 

### Eq.

The uncertainties associated with the emission estimates of CH 4 

### and N 2 

### O are greater than those associated with estimates of CO 2 

### from fossil fuel combustion, which mainly rely on the carbon content of the fuel combusted. Uncertainties in both CH 4 

### and N 2 

### O estimates are due to the fact that emissions are estimated based on emission factors representing only a limited subset of combustion conditions.

33 The low emission estimates reported in this section have been rounded down to the nearest integer values and the high emission estimates have been rounded up to the nearest integer values.

### Energy 3-27 Table 3-18: CH 4 

### 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 CH 4 

### , N 2 

### O, 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 CH 4 

### and N 2 

### O emissions from stationary sources (excluding CO 2 

### ) 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, N 2 

### O emission factors for coal consumption in all sectors, and CH 4 

### 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 CO 2 

### 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 CO 2 

### Eq. (8.3 percent) in

### 3-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 Table 3-19: N 2 

### O 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 CH 4 

### and N 2 

### O Emissions from Energy-Related Stationary Combustion, Including Biomass (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Stationary Combustion CH 4 6.2 4.3 13.4 -31% +116% Stationary Combustion N 2 O 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.



### CH 4 

### emissions from stationary combustion and an average annual increase of 0.6 Tg CO 2 

### Eq. (4.9 percent) in N 2 

### O emissions from stationary combustion for the period 1990 through 2005. 

# Planned Improvements Several items are being evaluated to improve the CH 4 

### and N 2 

### O 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 CO 2 

# ) (IPCC Source Category 1A)

Mobile combustion produces greenhouse gases other than CO 2 

### , including CH 4 

### , N 2 

### O, and indirect greenhouse gases including NO x 

### , 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, N 2 

### O and NO x

### emissions are closely related to fuel characteristics, air-fuel mixes, combustion temperatures, and the use of pollution control equipment. N 2 

### O, in particular, can be formed by the catalytic processes used to control NO x 

### , 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. CH 4 

### and NMVOC emissions from motor vehicles are a function of the CH 4 

### 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 CH 4 

### and N 2 

### O emission estimates in Tg CO 2 

### 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 CH 4 

### emissions (0.4 percent) but was the second largest source of U.S. N 2 

### O emissions (9 percent). From 1990 to 2006, mobile source CH 4 

### emissions declined by 50 percent, to 2.4 Tg CO 2 

### Eq. (112 Gg), due largely to controltechnologies employed in on-road vehicles since the mid1990s to reduce CO, NO x 

### , NMVOC, and CH 4 

### emissions. Mobile source emissions of N 2 

### O decreased by 24 percent, to 33.1 Tg CO 2 

### Eq (107 Gg). Earlier generation control technologies initially resulted in higher N 2 

### O emissions, causing a 26 percent increase in N 2 

### O emissions from mobilesources between 1990 and 1998. Improvements in latergeneration emission control technologies have reduced N 2 

### O output, resulting in a 40 percent decrease in mobile source
N 2 

### O emissions from 1998 to 2006 (see Figure 3-15). Overall, CH 4 

### and N 2 

### O emissions were predominantly from gasolinefueled passenger cars and light-duty trucks.

Figure 3-15
Mobile Source CH 4 

### and N 2 

### O Emissions

0 10 20 30 40 50 60 N 2 O19901991199219931994199519961997199819992000200120022003200420052006Tg CO2Eq.

CH 4

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: CH 4 

### Emissions from Mobile Combustion (Tg CO 2 

### Eq.)

Fuel Type/Vehicle Type a 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 Other b + + + + 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 CO 2 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: N 2 

### O Emissions from Mobile Combustion (Tg CO 2 

### 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 CO 2 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: CH 4 

### 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: N 2 

### O 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 CH 4 

### and N 2 

### O 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 CH 4 

### and N 2 

### O 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 NO x 

### , 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 CH 4 

### and N 2 

### O 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

35 Categories 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).

37 Alternative fuel and advanced technology vehicles are those that can operate using a motor fuel other than gasoline or diesel. This includes electric or other bifuel or dual fuel vehicles that may be partially powered by gasoline or diesel. 

### 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 CO 2 

### , CO, HC, NO x 

### , 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 vehiclesto 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

38 Additional 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 N 2 

### O and CH 4 

### 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 CH 4 

### and N 2 

### O 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 NO x 

### , 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 CH 4 

### and N 2 

### O 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 CO 2 

### emissions, the emission pathways of CH 4 

### and N 2 

### O are highly complex. The results of the Tier 2 quantitative uncertainty analysis for the mobile source CH 4 

### and N 2 

### O emissions from on-road vehicles are summarized in Table 3-25. As noted above, an

Table 3-25: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### and N 2 

### O Emissions from Mobile Sources (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate a Uncertainty Range Relative to Emission Estimate a,b

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound On-Road Sources CH 4 1.8 1.7 1.9 -6% +6% On-Road Sources N 2 O 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.

39 The consumption of international bunker fuels is not included in these activity data, but is estimated separately under the International Bunker Fuels source category.

### 3-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 uncertainty analysis was not performed for CH 4 

### and N 2 

### O emissions from non-road vehicles. Mobile combustion CH 4 

### emissions (from on-road vehicles) in 2006 were estimated to be between 1.7 and 1.9 Tg CO 2

### 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 CO 2 

### Eq. Also at a 95 percent confidence level, mobile combustion N 2 

### O emissions from on-road vehicles in 2006 were estimated to be between 23.8 and 35.2 Tg CO 2 

### Eq., indicating a range of 19 percent below to 19 percent above the corresponding 2006 emission estimate of 29.5 Tg CO 2 

### 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 CH 4 

### and N 2 

### O 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 CO 2 

### 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 CO 2

### forgasoline-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). CO 2 

### 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 CH 4 

### and N 2 

### O emissions from mobile combustion were slightly lower relative to the previous Inventory—showing a decrease of no more than 0.7 Tg CO 2 

### 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 CO 2 

### Eq. (4 percent), occurs with the 2005 N 2 

### O estimate. Estimates for the year 2001 are the exception, as these estimates increased from the previous Inventory’s estimates by 0.07 Tg CO 2 

### Eq. for CH 4 

### and 0.15 Tg CO 2 

### Eq. for N 2 

### O. 

# 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-CO 2 

### 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 N 2 

### O and CH 4 

### emissions factors for non-road equipment.

2. Examine the feasibility of estimating aircraft N 2 

### O and CH 4 

### emissions by the number of takeoffs and landings, instead of total fuel consumption. Various studies have indicated that aircraft N 2 

### O and CH 4 

### 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 CH 4 

### to the atmosphere: underground mining, surface mining, and post-mining (i.e., coal-handling) activities. Underground coal mines contribute the largest share of CH 4 

### emissions. All 120 gassy underground coal mines in the United States employ ventilation systems to ensure that CH 4 

### levels remain within safe concentrations. These systems can exhaust significant amounts of CH 4 

### 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 CH 4 

### before, during, or after mining. In 2006, 13 coal mines collected CH 4 

### from degasification systems and sold this gas to a pipeline, thus reducing emissions to the atmosphere. In addition, one coal mine used CH 4 

### from its degasification system to heat mine ventilation air on site. Two of the coal mines that sold gas to pipelines also used CH 4 

### to generate electricity or fuel a thermal coal dryer. Surface coal mines also release CH 4 

### 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 CH 4 

### retained in the coal after mining is released during processing, storage, and transport of the coal.

Total CH 4 

### emissions in 2006 were estimated to be 58.5 Tg CO 2 

### 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: CH 4 

### Emissions from Coal Mining (Tg CO 2 

### 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: CH 4 

### 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 CH 4 

### emissions from underground mines from 1996 to 2002 was the result of the reduction of overall coal production, the mining of less gassy coal, and an increase in CH 4 

### 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 CH 4 

### emissions from coal mining consists of two parts. The first part involves estimating CH 4 

### 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 surfacemines and post-mining activities by multiplying basinspecific coal production by basin-specific emission factors. Underground mines . Total CH 4

### emitted from underground mines was estimated as the sum of CH 4 

### liberated from ventilation systems and CH 4 

### liberated by means of degasification systems, minus CH 4 

### recovered and used. The Mine Safety and Heath Administration (MSHA) samples CH 4 

### emissions from ventilation systems for all mines with detectable 40 

### CH 4 

### concentrations. These mine-by-mine measurements are used to estimate CH 4 

### emissions from ventilation systems. Some of the higher-emitting underground mines also use degasification systems (e.g., wells or boreholes) that remove CH 4 

### before, during, or after mining. This CH 4 

### can then be collected for use or vented to the atmosphere. Various approaches were employed to estimate the quantity of CH 4 

### collected by each of the twenty mines using these systems, depending on available data. For example, some mines report to EPA the amount of CH 4 

### liberated from their degasification systems. For mines that sell recovered CH 4 

### 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 CH 4 

### recovered by degasification systems and then used (i.e., not vented) was estimated. In 2006, thirteen active coal mines sold recovered CH 4 

### into the local gas pipeline networks, while one coal mine used recovered CH 4 

### 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 CH 4 

### 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 CH 4 

### as the average in situ CH 4 

### content of the coal. Revised data

on in situ CH 4 

### content and emissions factors are taken from EPA (2005), EPA (1996), and AAPG (1984). This calculation accounts for CH 4 

### 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 CH 4 

### 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 CH 4 readings with concentrations of greater than 50 ppm (parts per million) CH 4 . 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 CH 4 

### emissions (Mutmansky and Wang 2000). Estimates of CH 4

### 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 considerablymore 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 CH 4 

### emissions in 2006 were estimated to be between 53.3 and 76.3 Tg CO 2 

### 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 CO 2 

### 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 CH 4 

### to Gg of CH 4 

### 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 CH 4 

### emitted, and for Tg of CO 2 

### Eq. emitted. The difference between these factors is 0.44 percent.

Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Coal Mining (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Coal Mining CH 4 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 CH 4 

### emissions, with active underground mines the leading source of underground emissions. However, mines also continue to release CH 4 

### 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 CH 4 

### that may find its way to surface structures through overburden fractures. As work stops within the mines, the CH 4 

### liberation decreases but it does not stop completely. Following an initial decline, abandoned mines can liberate CH 4 

### 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 CH 4 

### 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;

• CH 4 

### flow capacity of the mine; • Mine flooding;

• Presence of vent holes; and

• Mine seals.

Gross abandoned mine CH 4 

### emissions ranged from 6.0 to 9.1 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### Eq. 

# Methodology Estimating CH 4

### 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 CH 4 

### 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 CH 4 

### 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: CH 4 

### Emissions from Abandoned Coal Mines (Tg CO 2 

### 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: CH 4 

### 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 CH 4 

### 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 CH 4 

### 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 CH 4 

### 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 CH 4 

### 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 CH 4 

### 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 CH 4 

### flow to the atmosphere). The remaining 40 percent of the mines were placed in one q = q i

### (1 + bD i 

### t) (-1/b)


### where,

q = Gas rate at time t in mmcf/d

q i 

### = Initial gas rate at time zero (t o 

### ) in million cubic feet per day mmcfd b = The hyperbolic exponent, dimensionless
D i 

### = Initial decline rate, 1/yr

t = Elapsed time from t o 

### (years) q = q i 

### e (-Dt)


### where,

q = Gas flow rate at time t in mcf/d

q i 

### = Initial gas flow rate at time zero (t o 

### ) in mcfd
D = Decline rate, 1/yr

t = Elapsed time from t o 

### (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 CH 4 

### 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 CH 4 

### emission rates during the 1970s (EPA 2003).

Abandoned mines emission estimates are based on all closed mines known to have active mine CH 4 

### 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 initialemission rates used reflect ventilation emissions only for pre1990 closures. CH 4 

### degasification amounts were added to the quantity of CH 4 

### ventilated for the total CH 4 

### 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 CH 4 

### 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 CH 4 

### 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) CH 4 

### 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 CH 4 

### emissions in 2006 were estimated to be between 4.5 and 6.4 Tg CO 2 

### 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 CO 2 

### Eq. Oneof 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 CO 2 

### Eq. (4,877 Gg) of CH 4 

### in 2006, an 18 percent decrease over 1990 emissions (see Table 3-34 and Table 3-35), and 28.5 Tg CO 2 

### Eq. (28,504 Gg) of non-combustion CO 2 

### 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.

CH 4 

### and non-combustion CO 2 

### 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 CH 4 

### and non-combustion CO 2 

### 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 CH 4 

### emissions. Flaring emissions account for the majority of the non-combustion CO 2 

### emissions. Emissions from field production accounted for approximately 27 percent of CH 4 

### emissions and about 25 percent of non-combustion CO 2 

### emissions from natural gas systems in 2006. Table 3-33: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Abandoned Underground Coal Mines (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Abandoned Underground

Coal Mines CH 4 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 CH 4

### emissions from compressors, including compressor seals, are the primary emission source from this stage. The majority of non-combustion CO 2 

### emissions come from acid gas removal units, which are designed to remove CO 2

### from natural gas. Processing plants account for about 12 percent of CH 4 

### emissions and approximately 74 percent of non-combustion CO 2 

### 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: CH 4 

### 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 CH 4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations. Note: Totals may not sum due to independent rounding. 

### Table 3-34: CH 4 

### Emissions from Natural Gas Systems (Tg CO 2 

### 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 CH 4 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 CO 2 

### 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 CO 2 

### Emissions from Natural Gas Systems (Tg CO 2 

### 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 CH 4 

### 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 CH 4

### 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. CH 4 

### emissions from the transmission and storage sector account for approximately 37 percent of emissions from natural gas systems, while CO 2

### emissions from transmission and storage account for less than 1 percent of the non-combustion CO 2 

### 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 CH 4 

### emissionsfrom natural gas systems and less than 1 percent of noncombustion CO 2 

### 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 CH 4 

### emissions in 2006 were 20 percent lower than 1990 levels. 

# Methodology The primary basis for estimates of CH 4 

### and noncombustion-related CO 2 

### 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 CH 4 

### 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

41 The percentages of total emissions from each stage may not sum to 100 percent due to independent rounding. 

### factors were used to estimate both CH 4 

### and non-combustion CO 2 

### emissions. However, the CH 4 

### emission factors were adjusted for CO 2 

### content when estimating fugitive and vented non-combustion CO 2 

### 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 CH 4 

### and noncombustion CO 2 

### 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 CH 4 

### 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 CH 4 

### emission factors into non-combustion related CO 2 

### emission factors. Additional

### Energy 3-45 information about CO 2 

### content in transmission quality natural gas was obtained via the internet from numerous U.S. transmission companies to help further develop the non-combustion CO 2 

### 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 CH 4 

### emissions in 2006 were estimated to be between 79.1 and 148.4 Tg CO 2 

### Eq. at a 95 percent confidence level. Natural gas systems non-combustion CO 2 

### emissions in 2006 were estimated to be between 22.0 and 41.3 Tg CO 2 

### 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 CH 4 

### 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 CH 4 

### and Non-Combustion CO 2 

### Emissions from Natural Gas Systems (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Natural Gas Systems CH 4 102.4 79.1 148.4 -23% +45% Natural Gas Systems b CO 2 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 CO 2 emissions was not performed. The relative uncertainty estimated (expressed as a percent) from the CH 4 uncertainty analysis was applied to the point estimate of non-combustion CO 2 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)

CH 4 

### emissions from petroleum systems are primarily associated with crude oil production, transportation, and refining operations. During each of these activities, CH 4 

### emissions are released to the atmosphere as fugitive emissions, vented emissions, emissions from operational upsets, and emissions from fuel combustion. Fugitive and vented CO 2 

### emissions from petroleum systems are primarily associated with crude oil production and are negligible in the transportation and refining operations. Combusted CO 2 

### 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 CH 4 

### and CO 2 

### emissions from petroleum systems in 2006 were 28.4 Tg CO 2 

### Eq. (1,354 Gg CH 4 

### ) and 0.3 Tg CO 2 

### (293 Gg) respectively. Since 1990, CH 4 

### 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). CO 2 

### 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 CH 4 

### emissions from petroleum systems. Vented CH 4

### from field operations account for over 91 percent of the emissions from the production sector, unburned CH 4 

### 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 CH 4 

### 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 CH 4 

### 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: CH 4 

### Emissions from Petroleum Systems (Tg CO 2 

### 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: CH 4 

### 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: CO 2 

### Emissions from Petroleum Systems (Tg CO 2 

### 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 CO 2 Eq.



### Table 3-42: CO 2 

### 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 CO 2 

### associated with natural gas emissions from field operations account for 99 percent of the total CO 2 

### 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 CO 2 

### 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 CH 4 

### emissions from the oil industry. Venting from tanks and marine vessel loading operations accounts for 64 percent of CH 4 

### 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 CH 4 

### emissions from the oil industry because most of the CH 4 

### in crude oil is removed or escapes before the crude oil is delivered to the refineries. There is an insignificant amount of CH 4 

### 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 CH 4 

### emissions from refineries are from leaks in the fuel gas system. Refinery combustion emissions include small amounts of unburned CH 4 

### in process heater stack emissions and unburned CH 4 

### in engine exhausts and flares. 

# Methodology The methodology for estimating CH 4 

### emissions from petroleum systems is a bottom-up approach, based on comprehensive studies of CH 4 

### 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 CH 4 

### emissions from petroleum systems do not include emissions downstream of oil refineries because these emissions are very small compared to CH 4 

### emissions upstream of oil refineries. The methodology for estimating CH 4

### 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 CO 2 

### 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 CO 2 

### are estimated by multiplying the CH 4 

### emission factors by a conversion factor, which is the ratio of CO 2 

### 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 CH 4 

### 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 CH 4 

### and CO 2 

### 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 CH 4 

### 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 CH 4 

### emissions in 2006 were estimated to be between 20.5 and 69.3 Tg CO 2 

### Eq., while CO 2 

### emissions were estimated to be

Table 3-43: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Petroleum Systems (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Petroleum Systems CH 4 28.4 20.5 69.3 -28% +144% Petroleum Systems CO 2 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 CO 2 

### 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 CO 2 

### Eq. for CH 4 

### and CO 2 

### , respectively.



# Recalculations Discussion Estimates of vented, fugitive, and process upset CO 2 

### emissions from the production sector were incorporated into the petroleum systems emission estimates for 1990 through 2006. CO 2 

### emissions were estimated using the methane emission sources’ activity factors and drivers for the corresponding CO 2 

### emission sources. The emission factors for CO 2 

### were estimated by multiplying the methane emission factors by a conversion factor, which is the ratio of CO 2 

### content divided by CH 4 

### 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. CO 2 

### emissions from the production sector account for 293 Gg of CO 2 

### in the year 2006. CO 2 

### 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 CO 2 

### 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 CO 2 

### . According to IPCC guidelines, when the CO 2 

### emitted is of fossil origin, it is counted as a net anthropogenic emission of CO 2 

### 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 CO 2 is produced from both naturally-occurring CO 2 reservoirs and from industrial sources such as natural gas processing plants and ammonia plants. In the current Inventory, emissions from naturally-produced CO 2 are estimated based on the application. In the current Inventory report, the CO 2 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 CO 2 used in EOR operations is assumed to be fully sequestered. Additionally, all anthropogenic CO 2 emitted from natural gas processing and ammonia plants is assumed to be emitted to the atmosphere, regardless of whether the CO 2 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 CO 2 . 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 CO 2 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 CO 2 emissions estimates for geologic storage. In October 2007, the U.S. EPA announced plans to develop regulations for geologic sequestration of CO 2 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 CO 2 capture, transport, injection and geologic storage are not yet included in national totals. Preliminary estimates indicate that the amount of CO 2 captured from industrial and natural sites, as well as fugitive emissions from pipelines is 39.0 Tg CO 2 (39,041 Gg CO 2 ) (see Table 3-44). Site-specific monitoring and reporting data for CO 2 injection sites (i.e., EOR operations) were not readily available, therefore, these estimates assume all CO 2 is emitted.



### Table 3-45: Potential Emissions from CO 2 

### 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 CO 2 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 CO 2 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 CO 2 

### Capture and Transport (Tg CO 2 

### 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 CO 2 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 CO 2 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). CO 2 

### emissions from combustion of municipal solid wastes rose 91 percent since 1990, to an estimated 20.9 Tg CO 2 

### 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 N 2 

### O emissions (De Soete 1993). N 2 

### O emissions from municipal solid waste combustion were estimated to be 0.4 Tg CO 2 

### Eq. (1 Gg N 2 

### O) in 2006, and have not changed significantly since 1990. 

# Methodology

Emissions of CO 2 

### from MSW combustion include CO 2 

### 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 CO 2 

### 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 CO 2

### 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: CO 2 

### and N 2 

### O Emissions from Municipal Solid Waste Combustion (Tg CO 2 

### Eq.)

Gas/Waste Product 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 N 2 O 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: CO 2 

### and N 2 

### O Emissions from Municipal Solid Waste Combustion (Gg)

Gas/Waste Product 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 N 2 O 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 CO 2 

### 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 N 2 

### O. These emissions were calculated as a function of the total estimated mass of municipal solid waste combusted and an emission factor. The N 2 

### O emission estimates are based on different data sources than the CO 2

### emission estimates. As noted above, N 2 

### O 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 N 2 

### O 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 CO 2 

### emissions and N 2 

### O 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 N 2 

### O 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 CO 2 

### emissions in 2006 were estimated to be between 16.8 and 23.7 Tg CO 2

### 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 CO 2 

### 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 353,086,962 a 7.4 a 2002 335,102,816 7.7 2003 343,482,645 b 7.6 b 2004 351,862,474 7.4 2005 351,862,474 c 7.4 c 2006 351,86,2474 c 7.4 c

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 N 2 

### O emissions in 2006 were estimated to be between 0.1 and 1.1 Tg CO 2 

### Eq. This indicates a range of 66 percent below to 184 percent above the 2006 emission estimate of 0.4 Tg CO 2 

### 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 N 2 

### O 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 N 2 

### O 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 CO 2 

### and
N 2 

### O 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 (NO x 

### ), carbon monoxide (CO), and non-CH 4 

### 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 CO 2 

### and N 2 

### O from Municipal Solid Waste Combustion (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Municipal Solid Waste Combustion CO 2 20.9 16.8 23.7 -20% +13% Municipal Solid Waste Combustion N 2 O 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 CO 2 

### , CH 4 

### and N 2 

### O. 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).

43 Note that the definition of international bunker fuels used by the UNFCCC differs from that used by the International Civil Aviation Organization.

44 Most emission related international aviation and marine regulations are under the rubric of the International Civil Aviation Organization (ICAO) or the International Maritime Organization (IMO), which develop international codes, recommendations, and conventions, such as the International Convention of the Prevention of Pollution from Ships (MARPOL). 

### Table 3-50: NO x 

### , CO, and NMVOC Emissions from Energy-Related Activities (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 NO x 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 CO 2

### from aircraft are essentially a function of fuel use. CH 4 

### and N 2 

### O emissions also depend upon enginecharacteristics, flight conditions, and flight phase (i.e., takeoff, climb, cruise, decent, and landing). CH 4 

### is the product of incomplete combustion and occur mainly during the landing and take-off phases. In jet engines, N 2 

### O 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. CO 2 

### 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 CO 2 

### 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 CO 2 

### ; however, small amounts of CH 4 

### and N 2 

### O were also emitted. 

# Methodology

Emissions of CO 2 

### were estimated by applying C content and fraction oxidized factors to fuel consumption activity data. This approach is analogous to that described under CO 2 

### 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 CH 4 

### and N 2 

### O were calculated by multiplying emission factors by measures of fuel consumption by fuel type and mode. Emission factors used in the calculations of CH 4 

### and N 2 

### O 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 CH 4 

### and 0.1 for N 2 

### O For marine vessels consuming either distillate diesel or residual fuel oil the following values (g/MJ), were employed: 0.32 for CH 4 

### and 0.08 for N 2 

### O. 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: CO 2 

### , CH 4 

### and N 2 

### O Emissions from International Bunker Fuels (Gg)

Gas/Mode 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 113,683 100,627 101,125 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 CH 4 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 N 2 O 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: CO 2 

### , CH 4 

### , and N 2 

### O Emissions from International Bunker Fuels (Tg CO 2 

### Eq.)

Gas/Mode 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 113.7 100.6 101.1 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 CH 4 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 N 2 O 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 CO 2 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

47 Although foreign flagged air carriers are prevented from providing domestic flight services in the United States, passengers may be collected from multiple airports before an aircraft actually departs on its international flight segment. Emissions from these earlier domestic flight segments should be classified as domestic, not international, according to the IPCC. 

### 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 CO 2 

### in the Revised 1996 IPCC Guidelines is to use data by specific aircraft type (IPCC/UNEP/OECD/IEA 1997). The IPCC also recommends that cruise altitude emissions be estimated separately using fuel consumption data, while landing and take-off (LTO) cycle data be used to estimate near-ground level emissions of gases other than CO 2 

### . 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 CO 2 

### , CH 4 

### , and N 2 

### O 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 CO 2 

### Eq. (4.7 percent) in CO 2 

### emissions, an annual decrease of less than 0.1 Tg CO 2 

### Eq. (8 percent) in CH 4 

### emissions, and annual decrease of less than 0.1 Tg CO 2 

### Eq. (4 percent) in N 2 

### O emissions.

48 U.S. aviation emission estimates for CO, NO x , 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, NO x , 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 CO 2 

### . However, in the long run the CO 2 

### emitted from biomass consumption does not increase atmospheric CO 2 

### concentrations, assuming that the biogenic C emitted is offset by the uptake of CO 2 

### that results from the growth of new biomass. As a result, CO 2 

### emissions from biomasscombustion 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 CO 2 

### emissions from the burning of woody biomass in the industrial, residential, commercial, and electricity generation sectors were approximately 204.4 Tg CO 2 

### 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 CO 2 

### 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 NO x 

### and hydrocarbon emissions), and have been employed in urban areas with poor air quality. However, because ethanol is a hydrocarbon fuel, its combustion emits CO 2 

### . In 2006, the United States consumed an estimated 459 trillion Btu of ethanol, and as a result, produced approximately 30.3 Tg CO 2 

### Eq. (30,291 Gg) (see Table 3-57 and Table 3-58) of CO 2 

### 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: CO 2 

### Emissions from Wood Consumption by End-Use Sector (Tg CO 2 

### 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: CO 2 

### 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 CO 2 

### 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 CO 2

### 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: CO 2 

### Emissions from Ethanol Consumption (Tg CO 2 

### 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 CO 2 Eq. Note: Totals may not sum due to independent rounding.



### Table 3-58: CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 (CO 2 

### ), methane (CH 4 

### ), or nitrous oxide (N 2 

### O). 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, CO 2 

### 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 (SF 6 

### ). 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; SF 6 

### 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, SF 6 

### , 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 CO 2 

### equivalents (Tg CO 2 

### Eq.), or 5 percent of total U.S. greenhouse gas emissions. CO 2 0 25 50 75 100 125 Industrial Processes

as a Portion of all Emissions

4.5%

Tg CO 2 Eq. <0.5 Silicon Carbide Production and Consumption <0.5 Lead Production 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 CO 2 

### Eq. (149,465 Gg) in 2006, or 2 percent of total U.S. CO 2 

### emissions. CH 4 

### emissions from industrial processes resulted in emissions of approximately 2.0 Tg CO 2 

### Eq. (94 Gg) in 2006, which was less than 1 percent of U.S. CH 4 

### emissions.
N 2 

### O emissions from adipic acid and nitric acid production were 21.6 Tg CO 2 

### Eq. (70 Gg) in 2006, or 4 percent of total U.S. N 2 

### O emissions. In 2006, combined emissions of HFCs, PFCs and SF 6 

### totaled 147.9 Tg CO 2 

### 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 CO 2 

### 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 SF 6 

### . Tier 1 quality assurance and quality control procedures have been performed for all industrial process sources. For industrial process sources of CO 2 

### and CH 4 

### 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 CO 2 

### 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 associatedwith 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 CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 175.0 171.6 166.5 151.9 151.0 147.8 151.8 145.9 149.5

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 CH 4 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 + + + + + + + + + N 2 O 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 Substances a 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 SF 6 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 CO 2 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 CO 2 

### from both the energy consumed in making the cement and the chemical process itself. 1 

### Cement is produced in 37 states and Puerto Rico. CO 2 

### emitted from the chemical process of cement production is the second largest source of industrial CO 2 

### emissions in the United States.

1 The CO 2 emissions related to the consumption of energy for cement production are accounted for under CO 2 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 CO 2 175,018 171,600 166,452 151,944 150,960 147,752 151,841 145,926 149,465

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 CH 4 106 116 117 103 101 101 106 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 + + + + + + N 2 O 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 Substances a 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 SF 6 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 (CaCO 3 

### ) 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 CO 2 

### in a process known as calcination or calcining. A very small amount of carbonates other than CaCO 3 

### and noncarbonates are also present in the raw material; however, for calculation purposes all of the raw material is assumed to be CaCO 3 

### . Next, the lime is combined with silica-containing materials to produce clinker (an intermediate product), with the earlier byproduct CO 2 

### 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 CO 2 

### from 2006 cement production were estimated to be 45.7 Tg CO 2 

### 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.

2 Approximately six percent of total clinker production is used to produce masonry cement, which is produced using plasticizers (e.g., ground limestone, lime) and portland cement. CO 2 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

CO 2 

### 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 CO 2 

### and lime with the CO 2 

### released to the atmosphere. The quantity of CO 2 

### emitted during cement production is directly proportional to the lime content of the clinker. During calcination, each mole of CaCO 3 

### (i.e., limestone) heated in the clinker kiln forms one mole of lime (CaO) and one mole of CO 2 

### :

Limestone plus heat forms one mole of lime and one mole of carbon dioxide.


### CO 2 

### emissions were estimated by applying an emission factor, in tons of CO 2 

### 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 CO 2 

### released per unit of lime. This calculation yields an emission factor of 0.51 tons of CO 2 

### 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 CO 2

### emissions should be estimated as two percent of the CO 2

### 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

3 The 2 percent CO 2addition 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 (CaCO 3 ) 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). 

### CaCO 3 

### +heat → CaO +CO 2



### Table 4-3: CO 2 

### Emissions from Cement Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 

### EF Clinker 

### = 0.65 CaO × 

# [ 44.01 g/mole CO 2 

# ]

= 0.51 tons CO 2 

### /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 CaCO 3 

### when asmall 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### emissions were estimated to be between 39.8 and 52.0 Tg CO 2 

### 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 CO 2 

### 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. CO 2 

### is generated during the calcination stage, when limestone—mostly calcium carbonate (CaCO 3 

### )—is roasted at high temperatures in a kiln to produce CaO and CO 2 

### . The CO 2 

### is given off as a gas and is normally emitted to the atmosphere. In certain applications, lime reabsorbs CO 2 

### 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 CO 2

### emissions of 15.8 Tg CO 2 

### 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 CO 2 

### Emissions from Cement Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Cement Production CO 2 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, CO 2 

### 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 CO 2 

### 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 H 2 

### O 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 CO 2 

### ) ÷(56.08 g/mole CaO)] × (0.95 CaO/lime) = 0.75 g CO 2 

### /g lime

[(88.02 g/mole CO 2 

### ) ÷(96.39 g/mole CaO)] × (0.95 CaO/lime) = 0.87 g CO 2 

### /g lime Table 4-6: CO 2 

### Emissions from Lime Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 CO 2 

### emitted during lime production will actually be reabsorbed when the lime is consumed. As noted above, lime has many different chemical, industrial, environmental, and construction applications. In many processes, CO 2 

### reacts with the lime to create calcium carbonate (e.g., water softening). CO 2 

### reabsorption rates vary, however, depending on the application. For example, 100 percent of the lime used to produce precipitated calcium carbonate reacts with CO 2 

### ; 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 CO 2 

### 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 CO 2 

### —for reuse in the pulping process. Although this re-generation of lime could be considered a lime production process, the CO 2 

### 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 CO 2 

### emissions were estimated to be between 14.6 and 17.1 Tg CO 2 

### 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 CO 2 

### Eq.

4 Representatives of the National Lime Association estimate that CO 2 reabsorption that occurs from the use of lime may offset as much as a quarter of the CO 2 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 CO 2 . 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) [CaC 2 +2H 2 O → C 2 H 2 +Ca(OH) 2 ], not calcium carbonate [CaCO 3 ]. Thus, the calcium hydroxide is heated in the kiln to simply expel the water [Ca(OH) 2 +heat ( CaO +H 2 O] and no CO 2 is released.

6 Based on comments submitted by and personal communication with Dr. Sergio F. Galeano, Georgia-Pacific Corporation. 

### Table 4-8: Adjusted Lime Production a 

### (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 CO 2 

### emissions from lime production were revised for all years in the time series to remove estimates of CO 2 

### recovery associated with lime use during sugar refining and precipitate calcium carbonate (PCC) production. Currently, research does not indicate that CO 2 

### used in these processes stems from CO 2 

### captured during lime production. Additional research is needed to determine if lime production plants in the US capture CO 2 

### 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 (CaCO 3 

### ) and dolomite (CaCO 3 

### MgCO 3 

### ) 7 

### are basic raw materials used by a wide variety of industries, including construction, agriculture, chemical, metallurgy, glass production, and environmental pollution control.

7 Limestone 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 CO 2 

### 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 CO 2 

### emissions of 8.6 Tg CO 2 

### 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 CO 2 

### Emissions from Lime Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Lime Production CO 2 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: CO 2 

### Emissions from Limestone & Dolomite Use (Tg CO 2 

### 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

CO 2 

### 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 CO 2 

### . 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 CO 2 

### using a molecular weight ratio. Traditionally, the production of magnesium metal was the only other significant use of limestone and dolomite that produced CO 2 

### 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 CO 2 

### emissions, while the other plant produced magnesium from magnesium chloride using a CO 2 

### -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 u nder the category “unspecified uses.” Table 4-11: CO 2 

### 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 uncerta inty 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

8 This 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 CO 2 

### emissions were estimated to be between 8.0 and 9.2 Tg CO 2 

### 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 CO 2 

### 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, Na 2 

### CO 3 

### ) 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 CO 2 

### 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. CO 2 

### is generated as a byproduct of this reaction, and is eventually emitted into the atmosphere. In addition, CO 2 

### may also be released when soda ash is consumed.
In 2006, CO 2 

### emissions from the production of soda ash from trona were approximately 1.6 Tg CO 2 

### Eq. (1,626 Gg). Soda ash consumption in the United States generated 2.5 Tg CO 2 

### 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 CO 2 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 CO 2 is generated as a byproduct, the CO 2 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, NaHCO 3 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 CO 2 

### Emissions from Limestone and Dolomite Use (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Limestone and

Dolomite Use CO 2 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: CO 2 

### Emissions from Soda Ash Production and Consumption (Tg CO 2 

### 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 CO 2 

### 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. CO 2

### and water are generated as byproducts of the calcination process. CO 2 

### 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 CO 2 

### , or an emission factor of 0.097 metric tons CO 2 

### 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 CO 2 

### emissions of approximately 1.6 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### ) 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: CO 2 

### 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(Na 3 

### (CO 3 

### )(HCO 3 

### )•2H 2 

### O) → 3Na 2 

### CO 3 

### + 5H 2 

### O +CO 2 [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 CO 2 

### emissions were estimated to be between 3.9 and 4.5 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### and hydrogen (H 2 

### ), 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 CO 2 

### produced is captured and used to produce urea. The brine electrolysis process for production of ammonia does not lead to process-based CO 2 

### emissions. There are five principal process steps in synthetic ammonia production from natural gas feedstock. The primary reforming step converts CH 4 

### to CO 2 

### , carbon monoxide (CO), and H 2 

### in the presence of a catalyst. Only 30 to 40 percent of the CH 4 

### feedstock to the primary reformer is converted to CO and CO 2 

### . The secondary reforming step converts the remaining CH 4 

### feedstock to CO and CO 2 

### . The CO in the process gas from the secondary reforming step (representing approximately 15 percent of the process gas) is converted to CO 2 

### in the presence of a catalyst, water, and air in the shift conversion step. CO 2 

### is removed from the process gas by the shift conversion process, and the hydrogen gas is combined with the nitrogen (N 2 

### ) gas in the process gas during the ammonia synthesis step to produce ammonia. The CO 2 

### is included in a waste gas stream with other process impurities and is absorbed by a scrubber solution. In regenerating the scrubber solution, CO 2 

### is released. The conversion process for conventional steam reforming of CH 4 

### , 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 CO 2 

### and H 2 

### . These gases are separated, and the H 2 

### is used as a feedstock to the ammonia production process, where it is reacted with
N 2 

### to form ammonia.

Not all of the CO 2 

### produced in the production of ammonia is emitted directly to the atmosphere. Both ammonia and CO 2

### are used as raw materials in the production of urea [CO(NH 2 

### ) 2 

### ], which is another type of nitrogenous (catalyst) 

### 0.88 CH 4 

### +1.26 Air +1.24 H 2 

### O → 0.88 CO 2 

### +N 2 

### +3 H 2 

### N 2 

### +3 H 2 

### → 2 NH 3 

### Table 4-18: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Soda Ash Production and Consumption (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Soda Ash Production

and Consumption CO 2 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 CO 2 

### during use. Therefore, the CO 2 

### produced by ammonia production that is subsequently used in the production of urea is still emitted during urea consumption. The majority of CO 2 

### 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. CO 2 

### emissions associated with other uses of urea are accounted for in this chapter. Net emissions of CO 2 

### from ammonia production in 2006 were 11.8 Tg CO 2 

### Eq. (11,832 Gg), and are summarized in Table 4-19 and Table 4-20. Emissions of CO 2 

### from urea consumed for non-fertilizer purposes in 2006 totaled 0.5 Tg CO 2 

### 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 CO 2 

### emissions from production of nitrogenous fertilizers from natural gas feedstock is based on a CO 2 

### 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 CO 2 

### emission factor (1.2 metric tons CO 2 

### /metric ton NH 3 

### ) 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 CO 2 

### from ammonia production are then adjusted to account for the use of some of the CO 2

### 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 CO 2 

### are consumed and 6.8 of every 12 tons of ammonia are consumed. The CO 2 

### emissions reported for ammonia production are therefore reduced by a factor of 0.73 multiplied by total annual domestic urea production. Total CO 2 

### emissions resulting from nitrogenous fertilizer production do not change as a result of this calculation, but some of the CO 2 

### emissions are attributed to ammonia production and some of the CO 2 

### emissions are attributed to urea consumption. Those CO 2 

### 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 NH 3 

### +CO 2 

### → NH 2 

### COONH 4 

### → CO(NH 2 

### ) 2 

### +H 2 

### O

Table 4-19: CO 2 

### Emissions from Ammonia Production and Urea Consumption (Tg CO 2 

### 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 Consumption a 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.

aUrea Consumption is for non-fertilizer purposes only. Urea consumed as a fertilizer is accounted for in the Land Use, Land-Use Change, and Forestry chapter.



### Table 4-20: CO 2 

### 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 Consumption a 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.

aUrea Consumption is for non-fertilizer purposes only. Urea consumed as a fertilizer is accounted for in the Land Use, Land-Use Change, and Forestry chapter.

### 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. CO 2 

### emissions associated with the remaining urea are estimated using a factor of 0.73 tons of CO 2 

### 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 CO 2

### emission factor forproduction 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 CO 2

### (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 CO 2 

### emission factor (3.57 metric tons CO 2 

### /metric ton NH 3 

### ) is applied to the percent of total annual domestic ammonia production from petroleum coke feedstock.

The emission factor of 1.2 metric ton CO 2 

### /metric ton
NH 3 

### 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 CO 2 

### /metric ton NH 3 

### , with 1.2 metric ton CO 2 

### / metric ton NH 3 

### 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 CH 4 

### feedstock to the catalytic reforming process is ultimately converted to CO 2 

### . The emission factor of 3.57 metric ton CO 2 

### /metric
ton NH 3 

### 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 CO 2 

### emissions depending upon the end use to which the recovered CO 2 

### is applied. Further research is required to determine whether byproduct CO 2 

### 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 CO 2 

### emissions were estimated to be between 11.1 and 13.8 Tg CO 2 

### 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 CO 2 

### Eq.



# Recalculations Discussion

Estimates of CO 2 

### emissions from ammonia production and urea consumption were revised for all years to allocate CO 2 

### 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 CO 2

### 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 CO 2 

### emissions and incorporating CO 2 

### 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 CO 2 

### Emissions from Ammonia Production and Urea Consumption (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Ammonia Production

and Urea Consumption CO 2 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 (HNO 3 

### ) 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, N 2 

### O 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 NO 2 

### (i.e., NO x 

### ). As such, the industry uses a combination of non-selective catalytic reduction (NSCR) and selective catalytic reduction (SCR) technologies. In the process of destroying NO x 

### , NSCR systems are also very effective at destroying N 2 

### O. 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 N 2 

### O emissions.

N 2 

### O emissions from this source were estimated to be 15.6 Tg CO 2

### 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

N 2 

### O emissions were calculated by multiplying nitric acid production by the amount of N 2 

### O emitted per unit of nitric acid produced. The emission factor was determined as a weighted average of 2 kg N 2 

### O/metric ton HNO 3 

### for plants using non-selective catalytic reduction (NSCR) systems and 9 kg N 2 

### O/metric ton HNO 3 

### for plants not equipped with NSCR (IPCC 2006). In the process of destroying NO x 

### , NSCR systems destroy 80 to 90 percent of the N 2 

### O, which is accounted for in the emission factor of 2 kg N 2 

### O/metric ton HNO 3 

### . An estimated 20 percent of HNO 3 

### 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 N 2 

### O per metric ton HNO 3 

### . 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
N 2 

### O 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
N 2 

### O 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: N 2 

### O Emissions from Nitric Acid Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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. N 2 

### O emissions from nitric acid production were estimated to be between 9.4 and 22.1 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### Eq. (3.3 percent) in N 2 

### O emissions relative to the previous Inventory. The updated production data for 2005 resulted in an increase of 1.0 Tg CO 2 

### Eq. (6.1 percent) in N 2 

### O 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 N 2 

### O emissions relative to the previous Inventory (less than one-tenth of one percent) for all other years in the time series, respectively. Additionally, the N 2 

### O 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 N 2 

### O emissions of 0.9 Tg CO 2

### 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 NO x 

### 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
N 2 

### O 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 N 2 

### O 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. N 2 

### O 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 N 2 

### O 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 N 2 

### O Emissions From Nitric Acid Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Nitric Acid Production N 2 O 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 N 2 

### O (Reimer 1999).

N 2 

### O emissions from adipic acid production were estimated to be 5.9 Tg CO 2 

### 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 N 2 O 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, N 2 

### O emissions were calculated by multiplying adipic acid production by an emission factor (i.e., N 2 

### O emitted per unit of adipic acid produced) and adjusting for the percentage of N 2 

### O released as a result of plant-specific emission controls. On the basis of experiments, the overall reaction stoichiometry for N 2 

### O production in the preparation of adipic acid was estimated at approximately 0.3 metric tons of N 2 

### O 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 “N 2 

### O destruction factor” represents the percentage of N 2 

### O 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 N 2 

### O abatement equipment. For the one plant thatuses thermal destruction and for which no reported plantspecific emissions are available, the N 2 

### O 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. N 2 

### O emissions = production of adipic acid (MT) × (0.3 MT N 2 

### O/MT adipic acid) × (1-[N 2 

### O destruction factor × abatement system utility factor]) Table 4-26: N 2 

### O Emissions from Adipic Acid Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 N 2 

### O 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 N 2 

### O 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. N 2 

### O emissions from adipic acid production were estimated to be between 5.0 and 6.9 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### Eq. (4.1 percent) in N 2 

### O emissions relative to the previous inventory. Additionally, changes based on IPCC Guidelines (2006) to the N 2 

### O destruction factor and abatement system utilization factor for one plant resulted in an increase of between 0.1 and 0.2 Tg CO 2 

### Eq. (0.8 to 3.2 percent) in N 2 

### O 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 N 2 

### O Emissions from Adipic Acid Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Adipic Acid Production N 2 O 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

CO 2 

### and CH 4 

### are emitted from the production of silicon carbide (SiC), a material used as an industrial abrasive. To make SiC, quartz (SiO 2 

### ) 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 CO 2 

### , CH 4 

### , or CO.

CO 2 

### 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).

CO 2 

### from SiC production and consumption in 2006 were 0.2 Tg CO 2 

### Eq. (207 Gg). Approximately 44 percent of these emissions resulted from SiC production while the remainder result from SiC consumption. CH 4

### emissions from SiC production in 2006 were 0.01 Tg CO 2 

### Eq. CH 4 

### (0.4 Gg) (see Table 4-29 and Table 4-30). 

# Methodology

Emissions of CO 2 

### and CH 4 

### from the production of SiC were calculated by multiplying annual SiC production by the emission factors (2.62 metric tons CO 2 

### /metric ton SiC for CO 2 

### and 11.6 kg CH 4 

### /metric ton SiC for CH 4 

### ) provided by the 2006 IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006).

Emissions of CO 2 

### 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: CO 2 

### and CH 4 

### Emissions from Silicon Carbide Production and Consumption (Tg CO 2 

### Eq.)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 0.4 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 CH 4 + + + + + + + + + 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 CO 2 Eq. Note: Totals may not sum due to independent rounding.



### Table 4-30: CO 2 

### and CH 4 

### Emissions from Silicon Carbide Production and Consumption (Gg)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 375 329 248 199 183 202 224 219 207 CH 4 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 CH 4 

### , 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 CO 2 

### emissions were estimated to be between 10 percent below and 10 percent above the emission estimate of 0.2 Tg CO 2 

### Eq. at the 95 percent confidence level. Silicon carbide production CH 4 

### emissions were estimated to be between 9 percent below and 10 percent above the emission estimate of 0.01 Tg CO 2 

### 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 CH 4 

### and CO 2 

### emissions. Petrochemicals are chemicals isolated or derived from petroleum or natural gas. CH 4 

### emissions are presented here from the production of C black, ethylene, ethylene dichloride, and methanol, while CO 2

### emissions are presented here for only C black production. The CO 2 

### 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 CO 2 

### from C black production is included here to allow for the direct reporting of CO 2

### 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 CH 4 

### and CO 2 

### Emissions from Silicon Carbide Production and Consumption (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Silicon Carbide Production

and Consumption CO 2 0.2 0.2 0.2 -10% +10% Silicon Carbide Production

and Consumption CH 4 + + + -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 CO 2 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 CO 2 

### and CH 4 

### from petrochemical production in 2006 were 2.6 Tg CO 2 

### Eq. (2,573 Gg) and 1.0 Tg CO 2 

### Eq. (48 Gg), respectively (see Table 4-33 and Table 4-34), totaling 3.6 Tg CO 2 

### Eq. Emissions of CO 2 

### from C black production decreased from 2.8 Tg CO 2 

### Eq. (2,805 Gg) in 2005 to 2.6 Tg CO 2

### Eq. (2,573 Gg) in 2006 . There has been an overall increase in CO 2

### emissions from C black production of 16 percent since 1990. CH 4 

### emissions from petrochemical production decreased by less than 1 percent from the previous year and increased 16 percent since 1990. 

# Methodology

Emissions of CH 4 

### were calculated by multiplying annual estimates of chemical production by the appropriate emission factor, as follows: 11 kg CH 4 

### /metric ton C black, 1 kg CH 4 

### /metric ton ethylene, 0.4 kg CH 4 

### /metric ton ethylene dichloride, 11 

### and 2 kg CH 4 

### /metric ton methanol. Although the production of other chemicals may also result in CH 4

11 The emission factor obtained from IPCC/UNEP/OECD/IEA (1997), page 2.23 is assumed to have a misprint; the chemical identified should be ethylene dichloride (C 2 H 4 Cl 2 ) rather than dichloroethylene (C 2 H 2 Cl 2 ). 

### 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 producedin 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: CO 2 

### and CH 4 

### Emissions from Petrochemical Production (Tg CO 2 

### Eq.)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 2.2 2.8 3.0 2.8 2.9 2.8 2.9 2.8 2.6 CH 4 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: CO 2 

### and CH 4 

### Emissions from Petrochemical Production (Gg)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 2,221 2,750 3,004 2,787 2,857 2,777 2,895 2,804 2,573 CH 4 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 CO 2 

### , carbon monoxide, sulfur compounds, CH 4 

### , and non-CH 4 

### 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 CO 2 

### 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 CH 4 

### or CO 2 

### . The C content of the CH 4 

### emissions, estimated as described above, is subtracted from the total C lost in the process to calculate the amount of C emitted as CO 2 

### . 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 dataare 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 CH 4 

### 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 CH 4 

### arising from petrochemical production activities that have not been included in these estimates. The results of the quantitative uncertainty analysis for the CO 2 

### 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 CO 2 

### 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 CO 2 

### emissions were estimated to be between 1.7 and 3.6 Tg CO 2 

### 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 CO 2

### Eq. Petrochemical production CH 4 

### emissions were estimated to be between 0.9 and 1.1 Tg CO 2 

### 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 CO 2 

### Eq.



# Recalculations Discussion

Estimates of CO 2 

### 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 CH 4 

### and CO 2 

### 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 (TiO 2 

### ) 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 TiO 2 

### : the chloride process and the sulfate process. The chloride process uses petroleum coke and chlorine as raw materials and emits process-related CO 2 

### . The sulfate process does not use petroleum coke or other forms of C as a raw material and does not emit CO 2 

### . 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 FeTiO 3 

### (the Ti-containing ore) to form CO 2 

### . The majority of U.S. TiO 2 

### 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 CO 2 

### in 2006 were 1.9 Tg CO 2 

### 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 FeTiO 3 

### +7 Cl 2 

### +3 C → 2 TiCl 4 

### +2 FeCl 3 

### +3 CO 2 

### 2 TiCl 4 

### +2 O 2 

### → 2 TiO 2 

### +4 Cl 2 

### Table 4-37: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Petrochemical Production and CO 2 

### Emissions from Carbon Black Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Petrochemical Production CO 2 2.6 1.7 3.6 -35% +39% Petrochemical Production CH 4 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 CO 2

### from TiO 2

### production were calculated by multiplying annual TiO 2 

### production by chloride-processspecific emission factors.

Data were obtained for the total amount of TiO 2 

### produced each year. For years previous to 2004, it was assumed that TiO 2 

### 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 TiO 2 

### production results from the chloride process (USGS 2005). An emission factor of 0.4 metric tons C/metric ton TiO 2 

### was applied to the estimated chloride-process production. It was assumed that all TiO 2 

### produced using the chloride process was produced using petroleum coke, although some TiO 2 

### may have been produced with graphite or other C inputs. The amount of petroleum coke consumed annually in TiO 2 

### 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 TiO 2 

### 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 TiO 2 

### 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 Yearbookwere 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 TiO 2 

### 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 CO 2 

### per unit of TiO 2 

### 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 TiO 2 

### produced, sufficient data were not available to do so.
Also, annual TiO 2 

### 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 TiO 2 

### production capacity that was attributed to the chloride process was multiplied by total TiO 2 

### production to estimate the amount of TiO 2 

### 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: CO 2 

### Emissions from Titanium Dioxide Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 accountfor differences in production efficiency among chlorideprocess plants. In calculating the amount of petroleum coke consumed in chloride-process TiO 2 

### production, literature data were used for petroleum coke composition. Certain grades of petroleum coke are manufactured specifically for use in the TiO 2 

### 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 CO 2 

### emissions were estimated to be between 1.7 and 2.1 Tg CO 2 

### 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 CO 2 

### Eq.



# Recalculations Discussion

Estimates of CO 2 

### 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 TiO 2 

### 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)

CO 2 

### 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). CO 2 

### 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, CO 2

### used in non-EOR applications will eventually be released to the atmosphere, and for the purposes of this analysis CO 2 

### used in commercial applications other than EOR is assumed to be emitted to the atmosphere. CO 2 

### 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.

CO 2 

### is produced from naturally occurring CO 2 

### 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 CO 2 

### as a component. Only CO 2 

### produced from naturally occurring CO 2 

### reservoirs and used in industrial applications other than EOR is included in this analysis. Neither byproduct CO 2 

### generated from energy nor industrial production processes nor CO 2 

### separated from crude oil and natural gas are included in this analysis for a number of reasons. CO 2 

### captured from biogenic sources (e.g., ethanol production plants) is not included in the inventory. CO 2 

### captured from crude oil and gas production is used in EOR applications and is therefore reported in the Energy Chapter. Any CO 2 

### captured from industrial or energy production processes (e.g., ammonia plants, fossil fuel combustion) and used in non-EOR applications is assumed to be emitted to the atmosphere. The CO 2 

### emissions from such capture and use are therefore accounted for under Ammonia Production, Fossil Fuel Combustion, or other appropriate source category.

CO 2 

### is produced as a byproduct of crude oil and natural gas production. This CO 2 

### is separated from the crude oil and Table 4-40: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Titanium Dioxide Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Titanium Dioxide

Production CO 2 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 CO 2 

### used in EOR is described in the Energy Chapter under “Box 3-3 Carbon Dioxide Transport, Injection, and Geological Storage.” The only CO 2 

### consumption that is accounted for in this analysis is CO 2

### produced from naturally-occurring CO 2

### reservoirs that is used in commercial applications other than EOR. There are currently two facilities, one in Mississippi and one in New Mexico, producing CO 2

### from naturally occurring CO 2 

### reservoirs for use in both EOR and in other commercial applications (e.g., chemical manufacturing, food production). There are other naturally occurring CO 2 

### reservoirs, mostly located in the western U.S. facilities are producing CO 2 

### from these natural reservoirs, but they are only producing CO 2 

### for EOR applications, not for other commercial applications (Allis et al. 2000). CO 2 

### production from these facilities is discussed in the Energy Chapter.
In 2006, the amount of CO 2 

### produced by the Mississippi and New Mexico facilities for commercial applications and subsequently emitted to the atmosphere were 1.6 Tg CO 2 

### 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

CO 2 

### emission estimates for 1990 through 2006 were based on production data for the two facilities currently producing CO 2 

### from naturally-occurring CO 2 

### reservoirs for use in non-EOR applications. Some of the CO 2 

### 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 CO 2 

### production used in commercial applications other than EOR is eventually released into the atmosphere.

CO 2 

### 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 CO 2 

### production in units of MMCF CO 2 

### per day

Table 4-42: CO 2 

### Production (Gg CO 2 

### ) and the Percent Used for Non-EOR Applications for Jackson Dome and Bravo Dome

Year Jackson Dome CO 2 Production (Gg) Jackson Dome % Used for Non-EOR Bravo Dome CO 2 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: CO 2 

### Emissions from CO 2 

### Consumption (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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. CO 2 

### 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 CO 2 

### from naturally occurring CO 2 

### reservoirs for commercial uses other than EOR, and for which the CO 2 

### 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 CO 2 

### 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 CO 2 

### emissions from that sector depending upon the end use to which the recovered CO 2 

### is applied. Further research is required to determine whether CO 2 

### 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. CO 2 

### consumption CO 2 

### emissions were estimated to be between 1.3 and 2.0 Tg CO 2 

### 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 CO 2 

### Eq.



# Recalculations Discussion

Data for total Bravo Dome CO 2 

### 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 (H 3 

### PO 4 

### ) 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 (CaSO 4- 

### 2H 2 

### O), 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 CO 2 

### 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 (Ca 3 

### (PO 4 

### ) 2 

### ) component of the phosphate rock with sulfuric acid (H 2 

### SO 4 

### ) and recirculated phosphoric acid (H 3 

### PO 4 

### ) (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. 

### Ca 10-x-y 

### Na x 

### Mg y 

### (PO 4 

### ) 6-x 

### (CO 3 

### ) x 

### F 2 + 0.4x



### Ca 3 

### (PO 4 

### ) 2 

### +4H 3 

### PO 4 

### → 3Ca(H 2 

### PO 4 

### ) 2



### 3Ca(H 2 

### PO 4 

### ) 2 

### +3H 2 

### SO 4 

### +6H 2 

### O → 3CaSO 4 

### • 6H 2 

### O +6H 3 

### PO 4 

### Table 4-43: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from CO 2 

### Consumption (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound CO 2 Consumption CO 2 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 (CaCO 3 

### ) component of the phosphate rock reacts with the sulfuric acid in the phosphoric acid production process to produce calcium sulfate (phosphogypsum) and CO 2 

### . 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 CO 2 

### emissions from phosphoric acid production were 1.2 Tg CO 2 

### Eq. (1,167 Gg) in 2006 (see Table 4-44). 

# Methodology

CO 2

### 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 CO 2 

### emissions calculation methodology is based on the assumption that all of the inorganic C (calcium carbonate) content of the phosphate rock reacts to CO 2 

### 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 CO 2 

### 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). CaCO 3 

### +H 2 

### SO 4 

### +H 2 

### O → CaSO 4 

### • 2H 2 

### O +CO 2



### Table 4-44: CO 2 

### Emissions from Phosphoric Acid Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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. Production a 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 CO 2 

### 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 CO 2 

### emissions from consumption of imported phosphate rock. The CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 ) 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 CO 2 

### . 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 CO 2 

### in the elemental phosphorus production process. The calculation for CO 2 

### emissions is based on the assumption that phosphate rock consumption, for purposes other than phosphoric acid production, results in CO 2 

### 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 CO 2 

### emissions were estimated to be between 1.0 and 1.4 Tg CO 2 

### 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 CO 2 

### 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 CO 2

### and CH 4 

### . 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 CO 2 

### emissions and fugitive CH 4 

### 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 CO 2 

### Emissions from Phosphoric Acid Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Phosphoric Acid Production CO 2 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 CO 2 

### emissions and fugitive CH 4

### 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 CO 2 

### emissions and fugitive CH 4 

### emissions. The metallurgical coke is a reducing agent in the blast furnace. CO 2

### 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 CO 2 

### 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 CO 2 

### and CH 4 

### from iron and steel production in 2006 were 49.1 Tg CO 2 

### Eq. (49,119 Gg) and 0.9 Tg CO 2 

### Eq. (45 Gg), respectively (see Table 4-48 and Table 4-49), totaling 50.1 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### 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: CO 2 

### and CH 4 

### Emissions from Iron and Steel Production (Tg CO 2 

### Eq.)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 86.2 74.7 66.6 59.2 55.9 54.7 52.8 46.6 49.1 CH 4 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: CO 2 

### and CH 4 

### Emissions from Iron and Steel Production (Gg)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 86,220 74,729 66,609 59,249 55,938 54,744 52,771 46,627 49,119 CH 4 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 CO 2 

### were calculated by multiplying the annual production of steel in EAFs by an emission factor (4.4 kg CO 2 

### /ton steel EAF 

### ). It was assumed that the C anodes used in the production of steel in EAFs are composed of 80 percent petroleum coke and 20 percent coal tar pitch (DOE 1997). Since coal tar pitch is a 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 CO 2

### 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 CH 4 

### , 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 CO 2 

### 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: CH 4 

### Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg)

Material Produced g CH 4 /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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### emission factor for C anode consumption in aluminum production was also estimated. For the purposes of the CH 4 

### calculation it is assumed that none of the CH 4 

### is captured in stacks or vents and that all of the CH 4 

### escapes as fugitive emissions. Additionally, the CO 2 

### emissions calculation is not corrected by subtracting the C content of the CH 4 

### , which means there may be a slight double counting of C as both CO 2 

### and CH 4 

### . The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-52. Iron and Steel CO 2 

### emissions were estimated to be between 40.3 and 56.5 Tg CO 2 

### 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 CO 2 

### Eq. Iron and Steel CH 4 

### emissions were estimated to be between 0.9 Tg CO 2 

### Eq. and 1.0 Tg CO 2 

### 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 CO 2 

### Eq. Table 4-51: Production and Consumption Data for the Calculation of CO 2 

### and CH 4 

### Emissions from Iron and Steel Production (Thousand Metric Tons)

Gas/Activity Data 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2

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 CH 4

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 CO 2 

### 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)

CO 2 

### and CH 4 

### 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, CO 2 

### 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 CO 2 

### . 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 CO 2 

### , a percentage is also released as CH 4 

### and other volatiles. The amount of CH 4 

### that is released is dependent on furnace efficiency, operation technique, and control technology.

Emissions of CO 2 

### from ferroalloy production in 2006 were 1.5 Tg CO 2 

### 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 CH 4 

### from ferroalloy production in 2006 were 0.01 Tg CO 2 

### Eq. (0.4 Gg), which is an 11 percent increase from the previous year and a 37 percent decrease since 1990. Fe 2 

### O 3 

### +2 SiO 2 

### +7C → 2FeSi +7CO Table 4-52: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### and CH 4 

### Emissions from Iron and Steel Production (Tg. CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Iron and Steel Production CO 2 49.1 40.3 56.5 -18% +15% Iron and Steel Production CH 4 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: CO 2 

### and CH 4 

### Emissions from Ferroalloy Production (Tg CO 2 

### Eq.)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 2.2 2.0 1.9 1.5 1.3 1.3 1.4 1.4 1.5 CH 4 + + + + + + + + + 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 CO 2 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 CO 2

### and CH 4

### 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 siliconand 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 CO 2

### (2.5 metric tons CO 2

### /metric ton of alloy produced) and an emission factor for 65 percent silicon was applied for CH 4

### (1 kg CH 4 

### /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 CO 2

### and CH 4

### (4 metric tons CO 2

### /metric ton alloy produced and 1 kg CH 4

### /metric ton of alloy produced, respectively). The emission factors for silicon metal equaled 5 metric tons CO 2

### /metric ton metal produced and 1.2 kg CH 4 

### / 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: CO 2 

### and CH 4 

### Emissions from Ferroalloy Production (Gg)

Year 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 2,152 2,036 1,893 1,459 1,349 1,305 1,419 1,392 1,505 CH 4 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 CO 2 

### 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 CH 4 

### 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 CH 4 

### emissions; however, specific furnace information was not available or included in the CH 4 

### 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 CO 2 

### emissions were estimated to be between 1.3 and 1.7 Tg CO 2 

### 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 CO 2 

### Eq. Ferroalloy production

12 Emissions and sinks of biogenic carbon are accounted for in the Land Use, Land-Use Change, and Forestry chapter. 

### CH 4 

### emissions were estimated to be between a range of approximately 12 percent below and 12 percent above the emission estimate of 0.01 Tg CO 2 

### 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 CO 2 

### and two perfluorocarbons (PFCs): perfluoromethane (CF 4 

### ) and perfluoroethane (C 2 

### F 6 

### ).

CO 2 

### is emitted during the aluminum smelting process when alumina (aluminum oxide, Al 2 

### O 3 

### ) 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 CO 2 

### Emissions from Ferroalloy Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Ferroalloy Production CO 2 1.5 1.3 1.7 -12% +12% Ferroalloy Production CH 4 + + + -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 CO 2 Eq.

### 4-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 molten bath of natural or synthetic cryolite (Na 3 

### AlF 6 

### ). 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 CO 2 

### . Process emissions of CO 2 

### from aluminum production were estimated to be 3.9 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### from Fossil Fuel Combustion source category of the Energy sector. Similarly, the coal tar pitch portion of these CO 2 

### process emissions is accounted for here rather than in the Iron and Steel source category of the Industrial Processes sector.

In addition to CO 2 

### 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 CF 4 

### and C 2 

### F 6 

### . 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 CF 4 

### and C 2 

### F 6 

### have both declined by 87 percent to 2.1 Tg CO 2

### Eq. of CF 4 

### (0.4 Gg) and 0.4 Tg CO 2 

### Eq. of C 2 

### F 6 

### (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 CF 4 

### and C 2 

### F 6 

### 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 CF 4 C 2 F 6 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: CO 2 

### Emissions from Aluminum Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 CO 2 

### Eq.)

Year CF 4 C 2 F 6 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

CO 2 

### emissions released during aluminum productionwere 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 CO 2 

### 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, CO 2 

### is also emitted during the anode baking process. These emissions can account for approximately 10 percent of total process CO 2 

### emissions from prebake smelters. The CO 2 

### 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). CO 2 

### 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 CO 2

### 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 CO 2 

### 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), CO 2 

### emission estimates were estimated using Tier 1 Søderberg and/or Prebake emission factors (metric ton of CO 2 

### 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) ortechnology-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 2Al 2 

### O 3 

### +3C → 4Al +3CO 2



### PFC (CF 4 

### or C 2 

### F 6 

### ) 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 CO 2 

### , CF 4 

### , and C 2 

### F 6 

### emission estimates were calculated using a Tier 2 approach, as defined by IPCC (2006). For CO 2 

### , uncertainty was assigned to each of the parameters used to estimate CO 2 

### 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 CO 2 

### 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 CF 4 

### and C 2 

### F 6 

### , 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 CO 2 

### emissions were estimated to be between 3.7 and 4.1 Tg CO 2 

### 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 CO 2 

### Eq. Also, productionrelated CF 4 

### emissions were estimated to be between 1.9 and 2.3 Tg CO 2 

### 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 CO 2 

### Eq. Finally, aluminum production-related C 2 

### F 6 

### emissions were estimated to be between 0.3 and 0.4 Tg CO 2 

### 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 CO 2 

### 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 ownedby 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 CF 4 

### and C 2 

### F 6 

### 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 SF 6 

### 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, SF 6 

### emissions from aluminum activities have been omitted from estimates of global SF 6 

### emissions, with the explanation that any emissions would be insignificant (Ko et al. 1993, Victor and MacDonald 1998). The concentration of SF 6 

### in the mixtures is small and a portion of the SF 6 

### 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 CO 2 

### emissions for 2005. 

# 4.16. Magnesium Production and Processing (IPCC Source Category 2C4)

The magnesium metal production and casting industry uses sulfur hexafluoride (SF 6 

### ) as a cover gas to prevent the rapid oxidation of molten magnesium in the presence of air. A dilute gaseous mixture of SF 6 

### with dry air and/or CO 2 

### is blown over molten magnesium metal to induce and stabilize the formation of a protective crust. A small portion of the SF 6 

### reacts with the magnesium to form a thin molecular film of mostly magnesium oxide and magnesium fluoride. The amount of SF 6 

### reacting in magnesium production and processing is assumed to be negligible and thus all SF 6 

### 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 CO 2 

### Eq. (0.1 Gg) of SF 6 

### 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 CO 2 

### and PFC Emissions from Aluminum Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Aluminum Production CO 2 3.9 3.7 4.1 -5% +5% Aluminum Production CF 4 2.1 1.9 2.3 -9% +9% Aluminum Production C 2 F 6 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: SF 6 

### Emissions from Magnesium Production and Processing (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 SF 6 

### 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 SF 6 

### 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, secondaryproduction 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 SF 6 

### per metric ton. Die casting emissions for 1999 through 2006, which accounted for 25 to 52 percent of all SF 6 

### 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 SF 6 

### 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 SF 6 

### 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 SF 6 

### 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: SF 6 

### Emission Factors (kg SF 6 

### per metric ton of Magnesium)

Year Die Casting Permanent Mold Wrought Anodes 1999 2.14 a 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

SF 6 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 SF 6 

### sales to the magnesium sector that is reported in the RAND survey of major SF 6 

### 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 SF 6 

### 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 SF 6

### 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 SF 6 

### 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 SF 6 

### 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 SF 6 

### emissions, total SF 6 

### 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. SF 6 

### emissions associated with magnesium production and processing were estimated to be between 2.7 and 3.6 Tg CO 2 

### Eq. at the 95 percent confidence level (or in 19 out of 20 Monte Carlo Stochastic Simulations). This indicates a range of approximately 14 percent below to 14 percent above the 2006 emissions estimate of 3.2 Tg CO 2 

### 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 SF 6 

### emissions of 0.03 Tg CO 2 

### Eq. (approximately 0.5 percent) for 1990 to 1998 and 0.6 Tg CO 2

### Eq. (approximately 22 percent) for 2001 to 2005 relative to the previous report.

Table 4-64: Tier 2 Quantitative Uncertainty Estimates for SF 6 

### Emissions from Magnesium Production and Processing (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Magnesium Production SF 6 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 SF 6 

### utilized is emitted to the atmosphere. EPA-funded measurements of SF 6 

### in die casting applications have indicated that the latter assumption may be incorrect, with observed SF 6 

### 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 SF 6 

### , 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 CO 2

### 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 CO 2 

### emissions (Sjardin 2003). Theelectrolytic zinc production process does not produce nonenergy CO 2 

### 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 CO 2

### from zinc production in 2006 were estimated to be 0.5 Tg CO 2

### Eq. (529 Gg) (see Table 4-65). All 2006 CO 2 

### 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: CO 2 

### Emissions from Zinc Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 CO 2

### 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 CO 2

### /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 zincproduction 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 CO 2 

### 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, CO 2

### 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 thetotal amount of secondary zinc produced using the electrothermic process. This value is then multiplied by the Waelz Kiln process emission factor to obtain total CO 2

### 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 CO 2 

### 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 CO 2 

### metric tons C
3.66 metric tons CO 2 

### metric tons zinc EF Waelz Kiln 

### =

0.4 metric tons coke metric tons EAF dust

0.84 metric tons C metric tons coke
3.67 metric tons CO 2 

### metric tons C
1.23 metric tons CO 2 

### metric tons EAF dust ×

×

= EF EAF 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### emissions were estimated to be between 0.4 and 0.7 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### Emissions from Zinc Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Zinc Production CO 2 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 CO 2 

### (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 CO 2 

### 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, CO 2 

### 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 CO 2

### from 2006 production were estimated to be 0.3 Tg CO 2

### 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 CO 2

### 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 CO 2 

### 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 CO 2

### /ton lead. For secondary lead production, Sjardin (2003) and IPCC (2006) provide an emission factor of 0.2 metric tons CO 2 

### /ton lead produced. Both factors are multiplied by total U.S. primary and secondary lead production, respectively, to estimate CO 2 

### emissions. The 1990 through 2006 activity data for primary and secondary lead production (see Table 4-69) were obtained Table 4-68: CO 2 

### Emissions from Lead Production (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 CO 2 

### 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 CO 2 

### emissions were estimated to be between 0.2 and 0.3 Tg CO 2 

### 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 CO 2 

### Eq.



# Recalculations Discussion

Estimates of CO 2 

### 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 CHF 3 

### ) 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 (CHCl 3 

### ) and hydrogen fluoride (HF) in the presence of a catalyst, SbCl 5 

### . The reaction of the catalyst and HF produces SbCl x 

### F y 

### , (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 (CHCl 2 

### F), HCFC-22 (CHClF 2 

### ), HFC-23 (CHF 3 

### ), 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

13 As construed, interpreted, and applied in the terms and conditions of the Montreal Protocol on Substances that Deplete the Ozone Layer [42 U.S.C. §7671m(b), CAA §614]. 

### Table 4-70: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Lead Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Lead Production CO 2 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 CO 2 

### 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 CO 2 

### Eq. and Gg)

Year Tg CO 2 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 CO 2 

### 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 CO 2 

### 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 emissionsfor three plants that operated in the early 1990s were recalculated to conform with the 2006 IPCC Guidelines usingthe 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-500used 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]

15 R-404A contains HFC-125, HFC-143a, and HFC-134a. 

### Table 4-73: Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 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 CO 2 

### 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 CO 2 

### 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 CF 4 + + + + + + + + + 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 CO 2 Eq. * Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee, C 4 F 10 , 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 C 6 F 14 . 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 CF 4 + + 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, C 4 F 10 , 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 CO 2 

### 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 –2006as ODS substitutes in 2006 include refrigeration and airconditioning (94.6 Tg CO 2

### Eq., or approximately 86 percent), aerosols (11.6 Tg CO 2

### Eq., or approximately 10 percent), and foams (2.4 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### , methylene chloride, and hydrocarbons. The majority of rigid PU foamshave 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 (CCl 4 

### ) 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 selectivesolvency. 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 aneffort 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 CO 2 

### Eq. at the 95 percent confidence level (or in 19 out of 20 Monte Carlo Stochastic Simulations). This indicates a range of approximately 0.3 percent below to 17 percent above the emission estimate of 110.4 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CHF 3 

### ), perfluoromethane (CF 4 

### ), perfluoroethane (C 2 

### F 6 

### ), nitrogen trifluoride (NF 3 

### ), and sulfur hexafluoride (SF 6 

### ), although other compounds such as perfluoropropane (C 3 

### F 8 

### ) and perfluorocyclobutane (c-C 4 

### F 8 

### ) 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 CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 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 C 2 

### F 6 

### is used in cleaning or etching, CF 4 

### 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 CO 2 

### 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 CO 2 

### 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.

16 A Partner refers to a participant of the U.S. EPA PFC Reduction/Climate Partnership for the Semiconductor Industry. Through a Memorandum of Understanding (MoU) with the EPA, Partners voluntarily report their PFC emissions to the EPA by way of a third party. 

### Table 4-78: PFC, HFC, and SF 6 

### Emissions from Semiconductor Manufacture (Tg CO 2 

### Eq.)

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006 CF 4 0.7 1.3 1.8 1.3 1.1 1.0 1.1 1.1 1.2 C 2 F 6 1.5 2.5 3.0 2.1 2.2 2.1 2.1 2.0 2.2 C 3 F 8 0.0 0.0 0.1 0.1 0.1 0.1 0.0 0.0 0.0 C 4 F 8 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 SF 6 0.5 0.9 1.1 0.7 0.7 0.8 0.8 1.0 1.0 NF 3 * 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. * NF 3 emissions are presented for informational purposes, using a GWP of 8,000, and are not included in totals.



### Table 4-79: PFC, HFC, and SF 6 

### Emissions from Semiconductor Manufacture (Mg)

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006 CF 4 115 193 281 202 174 161 172 169 183 C 2 F 6 160 272 322 230 241 227 225 217 242 C 3 F 8 0 0 18 14 10 14 6 5 5 C 4 F 8 0 0 0 0 6 9 9 13 13 HFC-23 15 25 23 15 15 16 17 18 22 SF 6 22 38 45 31 28 35 35 41 40 NF 3 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.

23 Two 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 emissionsreported 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 operatingplant 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.

25 Currently, 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 analysis 26 

### 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 fromdiscussions 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 Watchdatabase. 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 CO 2 

### 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 CO 2 

### 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.

27 Error propagation resulted in Partnership gas-specific uncertainties ranging from 17 to 33 percent.

28 The average of 1996 to 1999 emission factor is used to derive the PEVM emission factor. 

### 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 SF 6 

### Emissions from Semiconductor Manufacture (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate a Uncertainty Range Relative to Emission Estimate b Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound c Upper Bound c Lower Bound Upper Bound Semiconductor

Manufacture HFC, PFC, and SF 6 5.1 4.8 5.5 -10% +8%

a Because the uncertainty analysis covered all emissions (including NF 3 ), 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 emissionreduction 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 SF 6 

### , 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 SF 6 

### 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 SF 6 

### from equipment manufacturing and from electrical transmission and distribution systems were estimated to be 13.2 Tg CO 2 

### 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 SF 6 

### during the 1990s and to a growing awareness of the environmental impact of SF 6 

### emissions, through programs such as the EPA’s SF 6 

### 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 SF 6 

### 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: SF 6 

### 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: SF 6 

### Emissions from Electric Power Systems and Electrical Equipment Manufacturers (Tg CO 2 

### 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, SF 6 

### is contained primarily in transmission equipment rated at or above 34.5 kV. The equations were developed based on the 1999 SF 6 

### 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 SF 6 

### 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 SF 6 

### 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 SF 6 

### 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 depletingsubstances, 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 SF 6 

### 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 SF 6 

### 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 SF 6 

### 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 SF 6 

### 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 SF 6 

### 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 SF 6 

### from electric power systems in 1999 (estimated to be 15.0 Tg CO 2 

### Eq.). Two factors may affect the relationship between the RAND sales trends and actual global emission trends. One is utilities’ inventories of SF 6 

### in storage containers. When SF 6 

### prices rise, utilities are likely to deplete internal inventories before purchasing new SF 6 

### at the higher price, in which case SF 6 

### sales will fall more quickly than emissions. On the other hand, when SF 6 

### prices fall, utilities are likely to purchase more SF 6 

### 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 SF 6 

### 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. SF 6 

### 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 SF 6 

### charged into new equipment. The quantity of SF 6 

### 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 SF 6 

### charged into new equipment for 2001 to 2006 were estimated using partner reported data and the total industry SF 6 

### nameplate capacity estimate (128.4 Tg CO 2 

### 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 SF 6 

### 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 SF 6 

### ) = SF 6 

### purchased to refill existing equipment (kilograms) + nameplate capacity 29 

### of retiring equipment (kilograms)

29 Nameplate capacity is defined as the amount of SF 6 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 SF 6 

### 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 SF 6 

### Emission ReductionPartnership include emissions from both reporting and nonreporting Partners. For reporting partners, individual partnerreported SF 6 

### 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 SF 6 

### charged into equipment by equipment manufacturers, which is projected from Partner provided nameplate capacity data and industry SF 6 

### nameplate capacity estimates, and the manufacturers’ SF 6 

### emissions rate. The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-83. Electrical Transmission and Distribution SF 6 

### emissions were estimated to be between 11.1 and 15.4 Tg CO 2 

### 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 CO 2 

### Eq. In addition to the uncertainty quantified above, there is uncertainty associated with using global SF 6 

### sales data to estimate U.S. emission trends from 1990 through 1999. However, the trend in global emissions implied by sales of SF 6 

### appears to reflect the trend in global emissions implied by changing SF 6 

### 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, SF 6 

### emission estimates for the period 1990 through 2006 were updated based on (1) new data from EPA’s SF 6 

### 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 SF 6 

### 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, SF 6 

### emissions from electric transmission and distribution decreased from 1990 to 2000 and in 2003 and

Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF 6 

### Emissions from Electrical Transmission and Distribution (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Electrical Transmission

and Distribution SF 6 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 SF 6 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 CF 4 and C 2 F 6 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 SF 6 from semiconductor manufacture, and SF 6 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 SF 6 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 CF 4 consumption were adjusted to account for the conversion of other chemicals into CF 4 during the semiconductor manufacturing process, again using the default factors from the IPCC Good Practice Guidance . Potential SF 6 emission estimates for electrical transmission and distribution were developed using U.S. utility purchases of SF 6 for electrical equipment. From 1999 through 2006, estimates were obtained from reports submitted by participants in EPA’s SF 6 Emission Reduction Program for Electric Power Systems. U.S. utility purchases of SF 6 for electrical equipment from 1990 through 1998 were backcasted based on world sales of SF 6 to utilities. Purchases of SF 6 by utilities were added to SF 6 purchases by electrical equipment manufacturers to obtain total SF 6 purchases by the electrical equipment sector.

30 See Annex 5 for a discussion of sources of SF 6 emissions excluded from the actual emissions estimates in this report. 

### Table 4-84: 2006 Potential and Actual Emissions of HFCs, PFCs, and SF 6 

### from Selected Sources (Tg CO 2 

### 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 SF 6

### 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 (NO x 

### ), carbon monoxide (CO), and non-CH 4 

### 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: NO x 

### , CO, and NMVOC Emissions from Industrial Processes (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 NO x 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 (N 2 

### O) 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)

N 2 

### O is a clear, colorless, oxidizing liquefied gas, with a slightly sweet odor. Two companies operate a total of five N 2 

### O production facilities in the United States (CGA 2003). N 2 

### O 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 N 2 

### O is as a propellant in pressure and aerosol products, the largest application being pressure-packaged whipped cream. Small quantities of N 2 

### O 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 N 2 

### O in 2006 was approximately 15 Gg. N 2 

### O emissions were 4.4 Tg CO 2 

### Eq. (14 Gg) in 2006 (see Table 5-3). Production of N 2 

### O 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 N 2 

### O. The use of N 2 

### O 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: N 2 

### O Emissions from Solvent and Other Product Use (Tg CO 2 

### Eq. and Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 N 2 O from Product Uses

Tg CO 2 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: N 2 

### O 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: N 2 

### O Emissions from N 2 

### O Product Uses (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 N 2 

### O product uses were calculated by first multiplying the total amount of N 2 

### O produced in the United States by the share of the total quantity of N 2 

### O 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 N 2 

### O product usage emissions. Emissions were determined using the following equation:

The share of total quantity of N 2 

### O usage by end use represents the share of national N 2 

### O 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 N 2 

### O produced, followed by food processing propellants at 6.5 percent. All other categories combined used the remainder of the
N 2 

### O produced. This subcategory breakdown has changed only slightly over the past decade. For instance, the small share of N 2 

### O 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 N 2 

### O 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 N 2 

### O was allocated across the following categories: medical applications, foodprocessing propellant, and sodium azide production (pre1996). A usage emissions rate was then applied for each sector to estimate the amount of N 2 

### O 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 N 2 

### O in blood and other tissues, none of the N 2 

### O 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 N 2 

### O used as a propellant in pressurized and aerosol food products, none of the N 2 

### O is reacted during the process and all of the N 2 

### O 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 N 2 

### O is consumed/reacted during the process, and therefore the emissions rate was considered to be zero percent (Tupman 2002). The 1990 through 1992 N 2 

### O production data were obtained from SRI Consulting’s Nitrous Oxide, North
America report (Heydorn 1997). N 2 

### O 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 N 2 

### O 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 N 2 

### O Product Uses Emissions = ∑ i

### [Total U.S. Production of N 2 

### O] × [Share of Total Quantity of N 2 

### O 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 N 2 

### O emissions for years 1993 through 2001 (Tupman 2003). The 2002 and 2003 N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O usage by sector was obtained from communication with a N 2 

### O industry expert (Tupman 2002). The 2002 and 2003 share of total quantity of N 2 

### O usage by sector was obtained from CGA (2002, 2003). Due to unavailable data, the share of total quantity of N 2 

### O 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
N 2 

### O industry expert (Tupman 2002). The emissions rate for all other subcategories was obtained from communication with a N 2 

### O 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 N 2 

### O emission estimate from N 2 

### O 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 N 2 

### O 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. N 2 

### O emissions from
N 2 

### O product uses were estimated to be between 4.3 and 4.5 Tg CO 2 

### Eq. at the 95 percent confidence level (or in 19 out of 20 Monte Carlo Stochastic Simulations). This indicates a range of approximately 2 percent below to 2 percent above the 2006 emissions estimate of 4.4 Tg CO 2 

### Eq.



# Recalculations Discussion

The N 2 

### O 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 N 2 

### O emissions from N 2 

### O product uses relative to the previous Inventory for each year in the 1990 through 2005 time series of 0.1 Tg CO 2

### 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 N 2 

### O Emissions From N 2 

### O Product Uses (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound N 2 O Product Usage N 2 O 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 N 2 

### O.


# 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-CH 4 

### 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 (NO x 

### ), 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 NO x 

### , NMVOCs, and CO from 1990 to 2006 are reported in Table 5-5.

Table 5-5: Emissions of NO x 

### , CO, and NMVOC from Solvent Use (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006 NO x 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 Processes a + + + + + + + + + Non-Industrial Processes b + + + + + + + + + Other NA + + + + + + + + CO 5 5 46 45 1 1 1 1 1

Surface Coating + 1 46 45 1 1 1 1 1 Other Industrial Processes a 4 3 + + + + + + + Dry Cleaning + 1 + + + + + + + Degreasing + + + + + + + + + Graphic Arts + + + + + + + + + Non-Industrial Processes b + + + + + + + + + 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 Processes b 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 Processes a 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 NO x

### 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 (CO 2 

### ) 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. CO 2 

### 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 CO 2 

### equivalents (Tg CO 2 

### Eq.), or 6 percent of total U.S. greenhouse gas emissions. Methane (CH 4 

### ) and nitrous oxide (N 2 

### O) were the primary greenhouse gases emitted by agricultural activities. CH 4 

### emissions from enteric fermentation and manure management represent about 23 percent and 7 percent of total CH 4 

### emissions from anthropogenic activities, respectively. Of all domestic animal types, beef and dairy cattle were by far the largest emitters of CH 4 

### . Rice cultivation and field burning of agricultural residues were minor sources of CH 4 

### . Agricultural soil management activities such as fertilizer application and

Table 6-1: Emissions from Agriculture (Tg CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 165.7 175.8 171.7 172.2 172.6 173.0 170.9 174.0 174.4

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 N 2 O 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 CO 2 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. N 2 

### O emissions, accounting for 72 percent. Manure management and field burning of agricultural residues were also small sources of N 2 

### O emissions. Table 6-1 and Table 6-2 present emission estimates for the Agriculture sector. Between 1990 and 2006, CH 4 

### emissions from agricultural activities increased by 5 percent, while N 2 

### O emissions fluctuated from year to year, but overall decreased by less than 1 percent.


# 6.1. Enteric Fermentation (IPCC Source Category 4A)

CH 4 

### 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 CH 4 

### as a byproduct, which can be exhaled or eructated by the animal. The amount of CH 4 

### 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 CH 4

### because of their uniquedigestive 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 therumen enables them to digest coarse plant material that nonruminant animals cannot. Ruminant animals, consequently, have the highest CH 4 

### emissions among all animal types. Non-ruminant animals (e.g., swine, horses, and mules) also produce CH 4 

### emissions through enteric fermentation, although this microbial fermentation occurs in the large intestine. These non-ruminants emit significantly less CH 4 

### on a per-animal basis than ruminants because the capacity of the large intestine to produce CH 4 

### is lower. In addition to the type of digestive system, an animal’s feed quality and feed intake also affects CH 4 

### emissions. In general, lower feed quality and/or higher feed intake lead to higher CH 4 

### 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).

CH 4 

### emission estimates from enteric fermentation are provided in Table 6-3 and Table 6-4. Total livestock CH 4 

### emissions in 2006 were 126.2 Tg CO 2 

### Eq. (6,010 Gg). Beef cattle remain the largest contributor of CH 4 

### 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 CH 4 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 N 2 O 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 CH 4 

### 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 CH 4 

### produced by individual ruminant animals, particularly cattle. The Cattle Enteric Fermentation Model (CEFM), developed by EPA to estimate cattle enteric CH 4

### 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: CH 4 

### Emissions from Enteric Fermentation (Tg CO 2 

### 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: CH 4 

### 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 CH 4

### conversion rates (Y m 

### ) (expressed as the fraction of gross energy converted to CH 4 

### ) for each population category. The IPCC recommends Y m

### 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 Y m 

### values unique to the United States were developed, rather than using the recommended IPCC values. The diet characterizations and estimation of DE and Y m 

### 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 Y m 

### 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 Y m 

### 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 Y m 

### 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 CH 4 

### 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

1 Emissions from bulls are estimated using a Tier 1 approach because it is assumed there is minimal variation in population and diets; calves younger than 7 months are assumed to emit little or no CH 4 . 

### production (e.g., pregnant, lactating) groupings to more fully capture differences in CH 4 

### 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 CH 4 

### 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. CH 4 

### emissions from these animals accounted for a minor portion of total CH 4 

### 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. CH 4 

### 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 CH 4 

### 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 CO 2 

### Eq., calculated as 11 percent below and 18 percent above the actual 2006 emission estimate of 126.2 Tg CO 2 

### Eq. Among the individual cattle sub-source categories, beef cattle account for the largest amount of CH 4 

### 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 Cf i

### (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 CH 4 

### Emissions from Enteric Fermentation (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a, b Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Enteric Fermentation CH 4 126.2 112.3 148.9 -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 (NE g 

### ), 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 Y m

### 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 Y m

### 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,

NE g 

### = 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 ani

mals in the population, kg/day NE g 

### = 22.02 × 

# ( Weight 

# ) 0.75 

### × WG 1.097 

### C × MW

NE g 

### = 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 CH 4

### and N 2 

### O emissions. Methane is produced by the anaerobic decomposition of manure. Direct N 2 

### O 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 N 2 

### O emissions are produced as result of the volatilization of nitrogen as ammonia (NH 3 

### ) and nitrogen oxides (NO x 

### ) 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 CH 4 

### . 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 N 2 O 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 CH 4 

### . Ambient temperature, moisture, and manure storage or residency time affect the amount of CH 4

### produced because they influence the growth of the bacteria responsible for CH 4

### formation. For non-liquidbased manure systems, moist conditions (which are a function of rainfall and humidity) can promote CH 4

### production. Manure composition, which varies by animal diet, growth rate, and type, including the animal’s digestive system, also affects the amount of CH 4

### produced. In general, the greater the energy content of the feed, the greater the potential for CH 4

### 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 N 2 

### O 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 N 2 

### O emissions to occur, the manure must first be handled aerobically where NH 3 

### or organic nitrogen is converted to nitrates and nitrites (nitrification), and then handled anaerobically where the nitrates and nitrites are reduced to nitrogen gas (N 2 

### ), with intermediate production of N 2 

### O 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 N 2 

### O in the waste management system (WMS). Indirect N 2 

### O emissions are produced when nitrogen is lost from the system through volatilization (as
NH 3 

### or NO x 

### ) or through runoff and leaching. The vast majority of volatilization losses from these operations are
NH 3 

### . Although there are also some small losses of NO x 

### , there are no quantified estimates available for use, so losses due to volatilization are only based on NH 3 

### 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 CH 4 

### emissions in 2006 were 41.4 Tg CO 2 

### Eq. (1,972 Gg), 34 percent higher than in 1990. Emissions increased on average by 0.6 Tg CO 2 

### 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 CH 4 

### , 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 CH 4 

### emissions than dry systems. This shift was accounted for by incorporating state and WMS-specific CH 4 

### 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 CH 4 

### emissions from animal manure management. From 2005 to 2006, there was a 1 percent decrease in total CH 4 

### 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 N 2 

### O emissions were estimated to be 14.3 Tg CO 2 

### Eq. (46 Gg); in 1990, emissions were 12.1 Tg CO 2 

### Eq. (39 Gg). These values include both direct and indirect
N 2 

### O emissions from manure management. N 2 

### O emissions have remained fairly steady since 1990. Small changes in N 2 

### O emissions from individual animal groups exhibit the same trends as the animal group populations, with the overall net effect that N 2 

### O 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 CH 4

### and N 2 

### O emissions from manure management by animal category.

Table 6-6: CH 4 

### and N 2 

### O Emissions from Manure Management (Tg CO 2 

### Eq.)

Gas/Animal Type 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 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 N 2 O b 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 CO 2 Eq. Note: Totals may not sum due to independent rounding.

aIncludes CH 4 emission reductions due to anaerobic digestion. b Includes both direct and indirect N 2 O emissions.

### Agriculture 6-9 

# Methodology The methodologies presented in IPCC (2006) form the basis of the CH 4 

### and N 2 

### O 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);

• CH 4

### producing potential of the volatile solids (by animal type);

• Extent to which the CH 4 

### 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 CH 4

### and N 2 

### O emissions from manure management for this Inventory. See Annex 3.10 for more detailed information on the methodology and data used to calculate CH 4

### and N 2 

### O emissions from manure management.

Both CH 4 

### and N 2 

### O 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 N 2 

### O 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: CH 4 

### and N 2 

### O Emissions from Manure Management (Gg)

Gas/Animal Type 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 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 N 2 O b 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 CH 4 emission reductions due to anaerobic digestion. b Includes both direct and indirect N 2 O 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 N 2 

### O emission factors for all systems were set equal to default IPCC factors (IPCC 2006). For indirect
N 2 

### O, the default indirect N 2 

### O emission factors suggested by IPCC were used: 0.010 kg N 2 

### O-N/kg N for volatilization and 0.0075 kg N 2 

### O-N/kg N for runoff/leaching. The amount of nitrogen that is lost due to volatilization of NH 3 

### and NO x 

### (Frac Gas 

### ) 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 (Frac Runoff/Leaching 

### ) is based on regional cattle runoff data from EPA’s Office of Water (EPA 2002b).

CH 4

### 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 CH 4

### producing capacity of the waste (B o 

### ) and the state- and WMS-specific MCFs.

The maximum CH 4 

### producing capacity of the VS, or B o 

### , was determined based on data collected in a literature review (ERG 2000b). B o

### 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 N 2 

### O 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 thenmultiplied by the average weight of the animal and the statespecific animal population. State- and WMS-specific direct
N 2 

### O emission factors were then applied to total nitrogen production to estimate direct N 2 

### O emissions.

Indirect N 2 

### O emissions were calculated by first estimating the amount of nitrogen loss from volatilization and runoff/leaching by multiplying the N excreted by
Frac Gas 

### and Frac Runoff/Leaching 

### . The N losses were then multiplied by the indirect N 2 

### O emission factors to estimate indirect N 2 

### O 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 N 2 

### O emissions from livestock manure management. The quantitative uncertainty analysis for thissource 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 CH 4

### and N 2 

### O 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 CH 4 

### emissions in 2006 were estimated to be between 34.0 and 49.7 Tg CO 2 

### 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 CO 2 

### Eq. At the 95 percent confidence level, N 2 

### O emissions were estimated to be between 12.0 and 17.7 Tg CO 2 

### Eq. (or approximately 16 percent below and 24 percent above the actual 2006 emission estimate of 14.3 Tg CO 2 

### Eq.).

3 Total 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 N 2 

### O emissions 4 

### from managed systems and CH 4 

### 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 N 2 

### O and CH 4

### emissions calculations for the current Inventory. These emissions are now calculated from the “bottom up” such that CH 4 

### and N 2 

### O 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 N 2 

### O 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 N 2 O emissions in the previous Inventory reflect only direct emissions whereas the current N 2 O 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 N 2 

### O emissions in the manure management sector associated with N losses from volatilization of N as ammonia (NH 3 

### ), nitrogen oxides (NO x 

### ), and leaching and runoff, as recommended by IPCC (2006). These indirect N 2 

### O emissions are added to the direct
N 2 

### O emissions to present a more complete picture of N 2 

### O emissions from manure management. The days per year used in N 2 

### O calculations was changed from 365 to 365.25 to include leap years and to be consistent with the CH 4 

### 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 N 2 

### O 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 CH 4 

### and N 2 

### O (Direct and Indirect) Emissions from Manure Management (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Manure Management CH 4 41.4 34.0 49.7 -18% +20% Manure Management N 2 O 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, CH 4 

### 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 CH 4 

### emission estimates are more than those of the previous Inventory by about one percent.

N 2 

### O 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 N 2 

### O emissions. The most significant changes in N 2 

### O 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 N 2 

### O 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 CH 4 

### emission reductions will be investigated. This method would include separating systems with anaerobic digesters from the total animal population before estimating CH 4 

### emissions, and then estimating emissions from the digesters using the amount of biogas/CH 4 

### 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 N 2 

### O emissions. The current methodology for calculating runoff for indirect N 2 

### O 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 CH 4 

### emission estimates by linking directly to the database that calculates CH 4 

### 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, CH 4 

### is produced through anaerobic decomposition of soil organic matter by methanogenic bacteria. As much as 60 to 90 percent of the CH 4 

### 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 CH 4 

### is also leached away as dissolved CH 4 

### in floodwater that percolates from the field. The remaining un-oxidized CH 4 

### is transported from the submerged soil to the atmosphere primarily by diffusive transport through the rice plants. Minor amounts of CH 4 

### 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 CH 4 

### emissions. Upland rice fields are not flooded, and therefore are not believed to produce CH 4 

### . In deepwater rice fields (i.e., fields with flooding depths greater than one meter), the lower stems and roots of the rice plants are dead, so the primary CH 4 

### transport pathway to the atmosphere is blocked. The quantities of CH 4 

### 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, CH 4 

### emissions decrease or stop entirely. This is due to soil aeration, which not only causes existing soil CH 4 

### to oxidize but also inhibits further CH 4 

### production in soils. All rice in the United States is grown under continuously floodedconditions; none is grown under deepwater conditions. Midseason drainage does not occur except by accident (e.g., due to levee breach).

Other factors that influence CH 4 

### 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 CH 4 

### emitted over the growing season; the total amount of CH 4 

### released depends primarily on the amount of organic substrate available. Soil temperature is known to be an important factor regulating the activity of methanogenic bacteria, and therefore the rate of CH 4 

### production. However, although temperature controls the amount of time it takes to convert a given amount of organic material to CH 4 

### , that time is short relative to a growing season, so the dependence of total emissions over an entire growing season on soil temperature

5 The roots of rice plants shed organic material, which is referred to as “root exudate.” The amount of root exudate produced by a rice plant over a growing season varies among rice varieties. 

### is weak. The application of synthetic fertilizers has also been found to influence CH 4 

### emissions; in particular, both nitrate and sulfate fertilizers (e.g., ammonium nitrate and ammonium sulfate) appear to inhibit CH 4 

### 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. CH 4

### 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 CH 4 

### in the United States (Table 6-9 and Table 6-10). In 2006, CH 4 

### emissions from rice cultivation were 5.9 Tg CO 2

### 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.

6 A very small amount of rice is grown on about 20 acres in South Carolina; however, this amount was determined to be too insignificant to warrant inclusion in national emissions estimates.

7 The 14 percent decrease occurred between 2005 and 2006; the 17 percent increase happened between 1993 and 1994.

### 6-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 

# Methodology IPCC (2006) recommends using harvested rice areas, area-based daily emission factors (i.e., amount of CH 4

### emitted per day per unit harvested area), and length of growing season to estimate annual CH 4 

### 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: CH 4 

### 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: CH 4 

### Emissions from Rice Cultivation (Tg CO 2 

### 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 CO 2 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 CH 4 

### emission factors should be used for the primary and ratoon crops, CH 4 

### 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 CH 4 

### 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 results 8 

### 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 CH 4 

### /hectareseason, and the resultant emission factor for the ratoon crop is 780 kg CH 4 

### /hectare-season. 

# Uncertainty The largest uncertainty in the calculation of CH 4 

### 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/m 2 /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 CH 4 

### /hectare-season and ratoon emissions ranged from 481 to 1,490 kg CH 4 

### /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 CH 4 

### 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 CH 4 

### emissions in 2006 were estimated to be between 2.1 and 12.8 Tg CO 2 

### 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 CO 2 

### 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 N 2 

### O 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;

9 Nitrification and denitrification are driven by the activity of microorganisms in soils. Nitrification is the aerobic microbial oxidation of ammonium (NH 4 ) to nitrate (NO 3 ), and denitrification is the anaerobic microbial reduction of nitrate to N 2 . 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 N 2 

### O 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 N 2 

### O emissions from all sources (cropland, grassland, forest lands, settlements, and managed manure) are reported in this chapter. Agricultural soils produce the majority of N 2 

### O emissions in the United States. Estimated emissions from this source in 2006 were 265.0 Tg CO 2 

### Eq. (855 Gg N 2 

### O) (see Table 6-13 and Table 6-14). Annual N 2 

### O 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 N 2 O emissions from these soils.

11 Asymbiotic N fixation is the fixation of atmospheric N 2 by bacteria living in soils that do not have a direct relationship with plants.

12 These processes entail volatilization of applied N as NH 3 and NO x , transformation of these gases within the atmosphere (or upon deposition), and deposition of the N primarily in the form of particulate ammonium (NH 4 ), nitric acid (HNO 3 ), and NO x . 

### Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### Emissions from Rice Cultivation (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Rice Cultivation CH 4 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 N 2 

### O 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 N 2 

### O Emissions

### Agriculture 6-19 Table 6-13: N 2 

### O Emissions from Agricultural Soils (Tg CO 2 

### 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 CO 2 Eq.



### Table 6-14: N 2 

### O 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 N 2 

### O Emissions from Agricultural Soils by Land Use and N Input (Tg CO 2 

### 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 Amendments a 9.4 10.1 10.2 11.1 10.7 10.0 10.7 10.4 10.7 Residue N b 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 Manure d 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 N b 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 N 2 

### O emissions for direct sources and regional patterns of N losses leading to indirect N 2 

### O emissions, respectively, for major crops and grasslands across the United States. Direct
N 2 

### O 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 CO 2

### 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 (NO 3 

### 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 NO 3 

### leaching in coarse-textured soils. Table 6-16: Indirect N 2 

### O Emissions from all Land-Use Types (Tg CO 2 

### 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 CO 2 Eq.

### Agriculture 6-21 Grasslands, Average Annual Direct N 2 

### O Emissions Estimated Using the DAYCENT Model, 1990–2006 (Tg CO 2 

### Eq./state/year) Figure 6-4

Tg CO 2 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 N 2 

### O Emissions Estimated Using the DAYCENT Model, 1990–2006 (Tg CO 2 

### Eq./state/year) Figure 6-3

Tg CO 2 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O. 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 atmosphere 13 

### 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 estimatedirect 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
N 2 

### O emissions in the United States, accounting for more of the environmental and management influences on soil N 2 

### O 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 N 2 

### O emissions, (2) adopting a revised emission factor for direct N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O emissions from each component.

### 6-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 Direct N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O emissions by anthropogenic activity directly from model outputs (e.g., N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 O 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 N 2 O emissions only during that year and cannot be stored in soils and contribute to N 2 O emissions in subsequent years. This is a simplifying assumption that is likely to create bias in estimated N 2 O 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 N 2 O during subsequent years. 

### Box 6-1: Tier 1 vs. Tier 3 Approach for Estimating N 2 

### O 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 N 2 

### O, 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 N 2 

### O emissions does not vary by source).

DAYCENT was used to estimate direct N 2 

### O 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 N 14 

### 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 NO x 

### , and runoff and leaching; more information on these losses is available in Annex 3.10, Manure Management. Animal-specific bedding factors

14 Total 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 N 2 

### O 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 N 2 

### O emissions (g N 2 

### O-N m -2 

### ) for major crops, whichwere 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O 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.

15 Other commercial organic fertilizers include manure applied to non-major crops, dried blood, dried manure, tankage, compost, other, but excludes sewage sludge that is used as commercial fertilizer.

### 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
N 2 

### O emissions from non-major crop types.

Drainage and Cultivation of Organic Cropland Soils
Tier 1 methods were used to estimate direct N 2 

### O 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 N 2 

### O Emissions from Grassland Soils
As with N 2 

### O 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 N 2 

### O 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
N 2 

### O emissions (g N 2 

### O-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 N 2 

### O 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 N 2 

### O 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 N 2 

### O emissions from agricultural soil management (see Table 6-13 and Table 6-14). Indirect N 2 

### O Emissions from Managed Soils of all Land-Use Types This section describes the methods used for estimating indirect soil N 2 

### O emissions from all land-use types (i.e., croplands, grasslands, forest lands, and settlements). Indirect
N 2 

### O 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 N 2 

### O. There are two pathways leading to indirect emissions. The first pathway results from volatilization of N as NO x 

### and NH 3 

### 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 N 2 

### O. The second pathway occurs via leaching and runoff of soil N (primarily in the form of nitrate [NO 3 - 

### ]) 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 N 2 

### O emissions. Regardless of the eventual location of the indirect N 2 

### O 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 N 2 

### O 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 N 2 

### O emissions associated with the amount of volatilized N (Table 6-16).

### Agriculture 6-29 Indirect N 2 

### O 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 N 2 

### O 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 N 2 

### O 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
N 2 

### O emissions in 2006 were estimated to be between 191.7 and 238.9 Tg CO 2

### 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 CO 2

### Eq. The indirect soil N 2 

### O emissions in 2006 were estimated to range from 28.0 to 113.2 Tg CO 2

### 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 CO 2

### Eq.


# QA/QC and Verification For quality control, DAYCENT results for N 2 

### O emissions and NO 3 

### leaching were compared with field data representing various cropped/grazed systems, soils types, and climate patterns (Del Grosso et al. 2005). N 2 

### O 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 N 2 

### O 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 N 2 

### O emissions. NO 3 

### leaching data were available for three sites

Table 6-17: Quantitative Uncertainty Estimates of N 2 

### O Emissions from Agricultural Soil Management in 2006 (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Direct Soil N 2 O Emissions N 2 O 214.7 191.7 238.9 -11% +11% Indirect Soil N 2 O Emissions N 2 O 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
corng 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 N 2 

### O emissions and NO 3 

### leaching, respectively. This comparison demonstrates that DAYCENT provides relatively high predictive capability for N 2 

### O emissions and NO 3 

### 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 N 2 

### O 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 N 2 

### O 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
N 2 

### O 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 N 2 

### O emissions from non-major crops are approximately 83 percent higher, on average, compared to the previous Inventory. However, direct soil N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 CO 2 

### , because the carbon released to the atmosphere as

Table 6-18: CH 4 

### and N 2 

### O Emissions from Field Burning of Agricultural Residues (Tg CO 2 

### Eq.)

Gas/Crop Type 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 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 + + + + + + + + + N 2 O 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 CO 2 Eq. Note: Totals may not sum due to independent rounding.

### 6-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 CO 2 

### during burning is assumed to be reabsorbed during the next growing season. Crop residue burning is, however, a net source of CH 4 

### , N 2 

### O, CO, and NO x 

### , 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 CO 2 

### Eq. (36 Gg) of CH 4 

### and 0.4 Tg CO 2 

### Eq. (1 Gg) of N 2 

### O (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

16 The 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

17 As is explained later in this section, the fraction of rice residues burned varies among states, so these equations were applied at the state level for rice. These equations were applied at the national level for all other crop types. 

### CH 4 

### and N 2 

### O 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: CH 4 

### , N 2 

### O, CO, and NO x

### Emissions from Field Burning of Agricultural Residues (Gg)

Gas/Crop Type 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 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 + + + + + + + + + N 2 O 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 NO x 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 acreages 18 

### (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

18 Rice production yield data are not available for Oklahoma, so the Arkansas values are used as a proxy. 

### where, Combustion = The proportion of CH 4 

### or Efficiency N 2 

### O released with respect to the total amount of C or N available in the burned material, respectively Emissions Ratio = g CH 4 

### -C/g C released or g N 2 

### O-N/g N released Conversion Factor = Molecular weight ratio of CH 4 

### :C or N 2 

### O:N

This Inventory calculates emissions from Burning of Agricultural Residues using a Tier 2 methodology that is based onIPCC/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 CH 4 and 36 percent higher emissions of N 2 O 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-CO 2 

### 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. CH 4 

### emissions from field burning of agricultural residues in 2006 were estimated to be between 0.3 and 1.5 Tg CO 2 

### 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 CO 2 

### Eq. Also at the 95 percent confidence level, N 2 

### O emissions were estimated to be between 0.2 and 0.9 Tg CO 2 

### Eq. (or approximately 64 percent below and 73 percent above the 2006 emission estimate of 0.5 Tg CO 2 

### 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 CH 4 

### emission estimate for 2005 of 0.2 percent, and a decrease in the N 2 

### O 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 CH 4 a 0.005 CO a 0.060 N 2 O b 0.007 NO x 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 CH 4 

### and N 2 

### O Emissions from Field Burning of Agricultural Residues (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Field Burning of Agricultural Residues CH 4 0.8 0.3 1.5 -65% +79% Field Burning of Agricultural Residues N 2 O 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 flux 1 

### 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 (CO 2 

### ) 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 CO 2 

### 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 CO 2 

### fluxes from wood products and urban trees, and CO 2 

### 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. CO 2 

### 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-CO 2 

### emissions from forest fires are based on forest CO 2 

### 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 CO 2 

### flux from forests, agricultural soils, and landfilled yard trimmings and food scraps are based in part on extrapolation. CO 2 

### 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 CO 2 

### flux. Land use, land-use change, and forestry activities in 2006 resulted in a net C sequestration of 883.7 Tg CO 2 

### 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. CO 2 

### emissions. Total

1 The term “flux” is used here to encompass both emissions of greenhouse gases to the atmosphere, and removal of C from the atmosphere. Removal of C from the atmosphere is also referred to as “carbon sequestration.”

### 7-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 land use, land-use change, and forestry net C sequestration 2 

### 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.

2 Carbon sequestration estimates are net figures. The C stock in a given pool fluctuates due to both gains and losses. When losses exceed gains, the C stock decreases, and the pool acts as a source. When gains exceed losses, the C stock increases, and the pool act as a sink. This is also referred to as net C sequestration. 

### 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 CO 2

### emissions of 8.0 Tg CO 2

### Eq. (8,012 Gg). The application of synthetic fertilizers to forest and settlement soils in 2006 resulted in direct N 2 

### O emissions of 1.8 Tg CO 2 

### Eq. (6 Gg). Direct N 2 

### O emissions from fertilizer application increased by approximately 174 percent between 1990 and 2006. Forest fires in 2006 resulted in methane (CH 4 

### ) emissions of 24.6 Tg CO 2 

### Eq. (1,169 Gg), and in N 2 

### O emissions of 2.5 Tg CO 2 

### Eq. (8 Gg). Table 7-1: Net CO 2 

### Flux from Carbon Stock Changes in Land Use, Land-Use Change, and Forestry (Tg CO 2 

### Eq.)

Sink Category 1990 1995 2000 2001 2002 2003 2004 2005 2006 Forest Land Remaining Forest Land a (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 b (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 CO 2 

### 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 Land a (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 Settlements b (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 CO 2 

### Eq.)

Source Category 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 CH 4 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 N 2 O 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 a 0.1 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Settlements Remaining Settlements:

Settlement Soils b 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 N 2 O 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-CO 2 

### Emissions from Land Use, Land-Use Change, and Forestry (Gg)

Source Category 1990 1995 2000 2001 2002 2003 2004 2005 2006 CO 2 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 CH 4 213 224 904 448 780 416 330 586 1,169

Forest Land Remaining Forest Land:

Forest Fires 213 224 904 448 780 416 330 586 1,169 N 2 O 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 Soils a 0 1 1 1 1 1 1 1 1 Settlements Remaining Settlements:

Settlement Soils b 3 4 4 5 5 5 5 5 5 Note: These estimates include direct emissions only. Indirect N 2 O 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 Land 7 

### 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

11%

– 30% > 50% 31%

– 50% < 10%

### 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

8 A new NLCD product is being developed that will meet the standards of Approach 3 data, with explicit information on land cover change, opposed to information based solely on land cover for individual years.

9 Wetlands are an exception to this general definition, because these lands, as specified by IPCC (2006), are only considered managed if they are created through human activity, such as dam construction, or the water level is artificially altered by human activity. Distinguishing between managed and unmanaged wetlands is difficult, however, due to limited data availability. Wetlands are not characterized by use within the NRI. Therefore, unless wetlands are managed for cropland or grassland, it is not possible to know if they are artificially created or if the water table is managed based on the use of NRI data. 

### • 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 stocked 13 

### 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>.

13 The percentage stocked refers to the degree of occupancy of land by trees, measured either by basal area or number of trees by size and spacing or both, compared to a stocking standard.

### 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-cultivatedlands. 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-asides 16 

### ). 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,

14 These subcategory definitions are fully described in the Forest Land Remaining Forest Land section.

15 Currently, there is no data source to account for biomass C stock change associated with woody plant growth and losses in alley cropping systems and windbreaks in cropping systems, although these areas are included in the cropland land base.

16 A set-aside is cropland that has been taken out of active cropping and converted to some type of vegetative cover, including, for example, native grasses or trees. 

### in addition to tundra are considered Grassland. 17 

### Woody plant communities of low forbs and shrubs, such asmesquite, 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.

19 The survey programs also do not include U.S. Territories with the exception of non-federal lands in Puerto Rico, which are included in the NRI survey. Furthermore, NLCD does not include coverage for U.S. Territories.

### 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 Survey 20 

### 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 definitions 21 

### 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.

22 With 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

23 With 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 theytend 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 recommendedin 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 CO 2 

### 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 17 th 

### century following European settlement had slowed by the late 19 th 

### century. Through the later part of the 20 th 

### 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

24 The term “biomass density” refers to the mass of live vegetation per unit area. It is usually measured on a dry-weight basis. Dry biomass is 50 percent C by weight.

### 7-14 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 CO 2 

### 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 CO 2 

### /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 50Forest Sector Net Carbon Flux (Tg/yr) Soil

Total Net Change

Forest, Nonsoil Harvested Wood19901991199219931994199519961997199819992000200120022003200420052006 

### 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 CO 2 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 CO 2 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 CO 2 emissions from fire disturbance, these estimates are being highlighted here, using the full extent of available data. Non-CO 2 greenhouse gas emissions from forest fires are also quantified in a separate section below. The IPCC (2003) methodology was employed to estimate CO 2 emissions from forest fires. CO 2 emissions for the lower 48 states and Alaska in 2006 were estimated to be 267.9 Tg CO 2 /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: CO 2 

### Emissions from Forest Fires

Table 7-9: Estimates of CO 2 

### (Tg/yr) emissions for the lower 48 states and Alaska a

Year CO 2 Emitted in the Lower 48 States (Tg/yr) CO 2 Emitted in Alaska

(Tg/yr) Total CO 2 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 lands 25 

### 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 accuraterepresentation 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 PlanningAct 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 CO 2 

### Eq. at a 95 percent confidence level. This includes a range of -471.2 to -802.2 Tg CO 2 

### Eq. in forest ecosystems and -85.5 to -136.8 Tg CO 2 

### 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 CO 2 

### 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 conductedconsistent 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 CO 2 

### Flux from Forest Land Remaining Forest Land : Changes in Forest C Stocks (Tg CO 2 

### Eq. and Percent)

2006 Flux Estimate Uncertainty Range Relative to Flux Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Forest Ecosystem CO 2 (635.1) (802.2) (471.2) -26% +26% Harvested Wood Products CO 2 (110.0) (136.8) (85.5) -24% +22% Total Forest CO 2 (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 broadforest 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-CO 2

# Emissions From Forest Fires

Emissions of non-CO 2 

### 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 CO 2 

### Eq. of CH 4 

### and 2.5 Tg CO 2 

### Eq. of N 2 

### O, asshown in Table 7-11 and Table 7-12. The estimates of nonCO 2 

### 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-CO 2 

### emissions from forest fires. Estimates for CH 4 

### 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. N 2 

### O 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 CO 2 

### emissions from forest fires, presented

CH 4 

### Emissions = (C released) × (emission ratio) × 16/12

N 2 

### O Emissions = (C released) × (N/C ratio) × (emission ratio) × 44/28

Table 7-11: Estimated Non-CO 2 

### Emissions from Forest Fires (Tg CO 2 

### Eq.) for U.S. Forests a

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 4.5 4.7 19.0 9.4 16.4 8.7 6.9 12.3 24.6 N 2 O 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-CO 2 

### Emissions from Forest Fires (Gg Gas) for U.S. Forests a

Gas 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 213 224 904 448 780 416 330 586 1,169 N 2 O 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-CO 2 

### 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 N 2 

# O 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-CO 2 

### Emissions from Forest Fires in Forest Land Remaining Forest Land (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Non-CO 2 Emissions from Forest Fires CH 4 24.6 7.7 42.1 -69% +71% Non-CO 2 Emissions from Forest Fires N 2 O 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. N 2 

### O emissions from forest soils are estimated to have increased by a multiple of 5.5 from 1990 to 2006. The trend toward increasing N 2 

### O emissions is a result of an increase in the area of N fertilized pine plantations in the southeastern United States. Total forest soil N 2 

### O emissions are summarized in Table 7-15. 

# Methodology The IPCC Tier 1 approach was used to estimate N 2 

### O 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O emitted from forests depends not only on N inputs, but also on a large number of variables, including organic C availability, O 2 

### partial pressure, soil moisture content, pH, temperature, and tree planting/harvesting cycles. The effect of the combined interaction of these variables
on N 2 

### O 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: N 2 

### O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 N 2 O emissions from N fertilizer additions only. Indirect N 2 O 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 level 26 

### 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 N 2 

### O 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. N 2 

### O fluxes from soils were estimated to be between 0.1 and 1.1 Tg CO 2 

### 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 CO 2 

### 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 N 2 

### O 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 CO 2 

### or N 2 

### O 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 CO 2

### 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 N 2 

### O Fluxes from Soils in Forest Land Remaining Forest Land (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Forest Land Remaining Forest Land:

N 2 O Fluxes from Soils N 2 O 0.3 0.1 1.1 -59% +211%
Note: This estimate includes direct N 2 O 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 CO 2 

### emissions. Because of the depth and richness of the organic layers, C loss from drained organic soils can continue over long periods of

27 CO 2 emissions associated with liming are also estimated but included in a separate section of the report. 

### time. The rate of CO 2 

### 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 years 28 

### 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, CO 2 

### emissions and removals 29 

### 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 CO 2 

### 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 CO 2 

### Eq. (7.5 Tg C) in 2006. In total, U.S. agricultural soils in Cropland Remaining Cropland removed approximately 41.8 Tg CO 2 

### 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 CO 2 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 CO 2

### 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 N 2 

### O from application of fertilizers, manure, and crop residues and from cultivation of legumes, as well as CH 4 

### from flooded rice cultivation. These emissions are accounted for in the Agriculture chapter, along with non-CO 2 

### greenhouse gas emissions from field burning of crop residues and CH 4 

### and N 2 

### O emissions from livestock digestion and manure management. Table 7-17: Net CO 2 

### Flux from Soil C Stock Changes in Cropland Remaining Cropland (Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### Flux For Mineral Soils Under Agricultural Management within States, 1993–2006 Cropland Remaining Cropland

Tg CO 2 Eq./year

< -2 -2 to -1 -1 to -0.5 -0.5 to -0.1 -0.1 to 0 > 0



### Total Net Annual CO 2 

### 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 CO 2 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-NRCS2000). 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 levelsince 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 obtainedfor 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 CO 2 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 NO x 

### , 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 simulationpurposes. 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 CO 2 

### Eq. and Percent)

2006 Flux Estimate a Uncertainty Range Relative to Flux Estimate a

Source (Tg CO 2 Eq.) (Tg CO 2 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 CO 2 

### 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 CO 2 

### 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.


# CO 2

# Emissions from Agricultural Liming

IPCC (2006) recommends reporting CO 2

### emissions from lime additions (in the form of crushed limestone (CaCO 3 

### ) and dolomite (CaMg(CO 3 

### ) 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 CO 2 

### . 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 CO 2 

### Eq. to 5.0 Tg CO 2 

### Eq. In 2006, liming of agricultural soils in the United States resulted in emissions of 4.4 Tg CO 2 

### 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 CO 2 

### Eq.)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 Liming of Soils a 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 Soils a 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

CO 2 

### 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 CO 2 

### emission factors from West and McBride (2005). These emission factors (0.059 metric ton C/metric ton limestone, 0.064 metric ton C/metric ton dolomite) are lower than the IPCC default emission factors, because they account for the portion of agricultural lime that may leach through the soil and travel by rivers to the ocean (West and McBride 2005). The annual application rates of limestone and dolomite were derived from estimates and industry statistics provided in the Minerals Yearbook and Mineral Industry Surveys (Tepordei 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006; Willett 2007; USGS 2007). To develop these data, the U.S. Geological Survey (USGS; U.S. Bureau of Mines prior to 1997) obtained production and use information by surveying crushed stone manufacturers. Because some manufacturers were reluctant to provide information, the estimates of total crushed limestone and dolomite production and use were divided into three components: (1) production by end-use, as reported by manufacturers (i.e., “specified” production), (2) production reported by manufacturers without end-uses specified (i.e., “unspecified” production), and (3) estimated additional production by manufacturers who did not respond to the survey (i.e., “estimated” production). The “unspecified” and “estimated” amounts of crushed limestone and dolomite applied to agricultural soils were calculated by multiplying the percentage of total “specified” limestone and dolomite production applied to agricultural soils by the total amounts of “unspecified” and “estimated” limestone and dolomite production. In other words, the proportion of total “unspecified” and “estimated” crushed limestone and dolomite that was applied to agricultural soils (as opposed to other uses of the stone) was assumed to be proportionate to the amount of “specified” crushed limestone and dolomite that was applied to agricultural soils. In addition, data were not available for 1990, 1992, and 2006 on the fractions of total crushed stone production that were limestone and dolomite, and on the fractions of limestone and dolomite production that were applied to soils. To estimate the 1990 and 1992 data, a set of average fractions were calculated using the 1991 and 1993 data. These average fractions were applied to the quantity of “total crushed stone produced or used” reported for 1990 and 1992 in the 1994 Minerals Yearbook (Tepordei 1996). To estimate 2006 data, the previous year’s fractions were applied to a 2006 estimate of total crushed stone presented in the USGS Mineral Industry Surveys: Crushed Stone and Sand and Gravel in the First Quarter of 2007 (USGS 2007). The primary source for limestone and dolomite activity data is the Minerals Yearbook , published by the Bureau of Mines through 1994 and by the USGS from 1995 to the present. In 1994, the “Crushed Stone” chapter in the Minerals Yearbook began rounding (to the nearest thousand) quantities for total crushed stone produced or used. It then reported revised (rounded) quantities for each of the years from 1990 to 1993. In order to minimize the inconsistencies in the activity data, these revised production numbers have been used in all of the subsequent calculations. Since limestone and dolomite activity data are also available at the state level, the national-level estimates reported here were broken out by state for the first time this year, but are not reported here. 

# 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 CO 2 

### 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 CO 2 

### emissions from liming. The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 7-23. CO 2 

### emissions from Liming of Agricultural Soils in 2006 were estimated to be between 0.2 and 8.5 Tg CO 2 

### 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 CO 2 

### 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.


# CO 2

# Emissions from Urea Fertilization

The use of urea (CO(NH 2 

### ) 2 

### ) as fertilizer leads to emissions of CO 2 

### that was fixed during the industrial production process. Urea in the presence of water and urease enzymes is converted into ammonium (NH 4 + 

### ), hydroxyl ion (OH

- 

### ), and bicarbonate (HCO 3 - 

### ). The bicarbonate then Table 7-23: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Emissions from Liming of Agricultural Soils (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Liming of Agricultural Soils b CO 2 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: CO 2 

### Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg CO 2 

### Eq.)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 Urea Fertilization a 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 CO 2

### and water. Emissions from urea fertilization in the United States totaled 3.6 Tg CO 2 

### 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 CO 2 

### Eq. to 3.7 Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### . 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: CO 2 

### Emissions from Urea Fertilization in Cropland Remaining Cropland (Tg C)

Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 Urea Fertilization a 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 CO 2 

### Emissions from Urea Fertilization (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Urea Fertilization CO 2 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 Fertilization a 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. CO 2 

### emissions from Urea Fertilization of Agricultural Soils in 2006 were estimated to be between 2.1 and 3.8 Tg CO 2 

### 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 CO 2 

### 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 currentlyincluded 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 years 34 

### 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 CO 2 

### Flux from Soil C Stock Changes in Land Converted to Cropland (Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### Eq. (2.6 Tg C) in 2006. Emissions from mineral soils were estimated at 6.7 Tg CO 2 

### Eq. (1.8 Tg C) in 2006, while drainage and cultivation of organic soils led to annual losses of 2.6 Tg CO 2 

### Eq. (0.7 Tg C) in 2006. The spatial variability in annual CO 2 

### 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

35 CO 2 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 asrecorded 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 CO 2 

### 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 CO 2 Eq./year

-0.5 to -0.1 -0.1 to 0 > 0



### Total Net Annual CO 2 

### 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 CO 2 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 CO 2 

### 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 Estimates a 

### for C Stock Changes occurring within Land Converted to Cropland (Tg CO 2 

### Eq. and Percent)

2006 Flux Estimate a Uncertainty Range Relative to Flux Estimate a

Source (Tg CO 2 Eq.) (Tg CO 2 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 CO 2 

### 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 Croplandsection 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 Croplandfor 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 years 38 

### 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 CO 2 

### Eq. (4.4 Tg C) in 2006 (Table 7-31 and Table 7-32). Overall, flux rates changed by 18.1 Tg CO 2 

### Eq. (4.9 Tg C) from 1990 to 2006. The spatial variability in annual CO 2

### 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.

39 CO 2 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 CO 2 

### Flux from Soil C Stock Changes in Grassland Remaining Grassland (Tg CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 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 CO 2 

### 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 CO 2 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 obtainedfor 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 NO x 

### , 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 CO 2 

### 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 Estimates a 

### for C Stock Changes occurring within Grassland Remaining Grassland (Tg CO 2 

### Eq. and Percent)

2006 Flux Estimate a Uncertainty Range Relative to Flux Estimate a Source (Tg CO 2 Eq.) (Tg CO 2 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%

aFlux 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 CO 2 

### 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 Croplandfor 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 years 41 

### 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 CO 2 

### 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 CO 2 

### Eq./yr (0.1 to 0.2 Tg C). The spatial variability in annual CO 2

### 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

42 CO 2 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 CO 2 

### Flux from Soil C Stock Changes for Land Converted to Grassland (Tg CO 2 

### Eq.)

Soil Type 1990 1995 2000 2001 2002 2003 2004 2005 2006 Mineral Soils a (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 CO 2 

### 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 Soils a (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 CO 2 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 CO 2 

### 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 CO 2 

### Flux For Organic Soils Under Agricultural Management within States, 1993–2006 Land Converted to Grassland Figure 7-12

Tg CO 2 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 CO 2 

### 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 CO 2 

### 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 Croplandfor 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### 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 CO 2 

### Eq. and Tg C)

Year Tg CO 2 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 Estimates a 

### for C Stock Changes occurring within Land Converted to Grassland (Tg CO 2 

### Eq. and Percent)

2006 Flux Estimate a Uncertainty Range Relative to Flux Estimate a

Source (Tg CO 2 Eq.) (Tg CO 2 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

46 Two 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/m 2 

### 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 CO 2

### 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 CO 2

### 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 CO 2 

### Eq. and Percent)

2006 Flux Estimate Uncertainty Range Relative to Flux Estimate

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Changes in C Stocks in Urban Trees CO 2 (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 N 2 

# O 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 N 2 

### O emissions per unit area. In addition to synthetic N fertilizers, a portion of surface applied sewage sludge is applied to settlement areas. In 2006, N 2 

### O emissions from this source were 1.5 Tg CO 2 

### 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 N 2 

### O emissions from synthetic N fertilizer and sewage sludge additions. Estimates of direct N 2 

### O 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 wascalculated 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 N 2 

### O 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: N 2 

### O Fluxes from Soils in Settlements Remaining Settlements (Tg CO 2 

### Eq. and Gg)

Year Tg CO 2 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 N 2 O emissions from N fertilizer additions only. Indirect N 2 O 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 N 2 

### O Emissions from Agricultural Soil Management source category of the Agriculture chapter. 

# Uncertainty

The amount of N 2 

### O emitted from settlements depends not only on N inputs, but also on a large number of variables, including organic C availability, O 2 

### partial pressure, soil moisture content, pH, temperature, and irrigation/watering practices. The effect of the combined interaction of these variables on N 2 

### O 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 level 47 

### 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. N 2 

### O emissions from soils in Settlements Remaining Settlements in 2006 were estimated to be between 0.8 and 3.9 Tg CO 2 

### 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 CO 2 

### 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 N 2 

### O 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 CO 2 

### or N 2 

### O 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 CO 2 

### Eq. in 1990 to 10.5 Tg CO 2 

### 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 N 2 

### O Emissions from Soils in Settlements Remaining Settlements (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Settlements Remaining Settlements:

N 2 O Fluxes from Soils N 2 O 1.5 0.8 3.9 -49% +163%
Note: This estimate includes direct N 2 O 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 CO 2 

### 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 decompositionwas 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 CH 4 

### and CO 2 

### (the CH 4 

### 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 CH 4 

### 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 (TLFC t 

### ) is the sum of stocks across all four materials. The annual flux of C in landfills (F t 

### ) 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 W i,n 

### × (1 - MC i 

### ) × ICC i 

### ×

n 

### {[CS i 

### × ICC i 

### ] +[(1 - (CS i 

### × ICC i 

### )) × 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), LFC i,t 

### = Stock of C in landfills in year t , for waste i (metric tons), W

i,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), MC i 

### = Moisture content of waste i (percent of water), CS i 

### = Proportion of initial C that is stored for

waste i (percent), ICC i 

### = 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 (% H 2 O) 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



### F t



### = TLFC t 

### - TLFC t - 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 CH 4 

### (CH 4 

### -C, measured),

• C output as CO 2 

### (CO 2 

### -C, not measured), and

• Residual stored C (CS, measured). In a simple system where the only C fates are CH 4 

### , CO 2 

### , 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 CO 2

### outputs in experiments. However, if the only decomposition is anaerobic, then CH 4 

### -C = CO 2 

### -C. 48 

### Thus, the system should be defined by:

48 The molar ratio of CH 4 to CO 2 is 1:1 for carbohydrates (e.g., cellulose, hemicellulose). For proteins as C 3.2 H 5 ON 0.86 , the molar ratio is 1.65 CH 4 per 1.55 CO 2 (Barlaz et al. 1989). Given the predominance of carbohydrates, for all practical purposes, the overall ratio is 1:1. 

### The C outputs (= 2 × CH 4 

### -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 CH 4

### and CO 2 

### , 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 CO 2

### flux in 2006 was estimated to be between -19.1 and -6.0 Tg CO 2

### 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 CO 2 

### Eq. More information on the uncertainty estimates for Yard Trimmings and Food Scraps in Landfills is contained within the Uncertainty Annex. CH 4 

### -C +CO 2 

### -C +CS = ICC

2 × CH 4 

### -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 CH 4 

### . 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 CH 4 

### , 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 CH 4 

### emissions described in the Waste chapter. Table 7-46: Tier 2 Quantitative Uncertainty Estimates for CO 2 

### Flux from Yard Trimmings and Food Scraps in Landfills (Tg CO 2 

### Eq. and Percent)

2006 Flux Estimate Uncertainty Range Relative to Flux Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Yard Trimmings and Food Scraps CO 2 (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 

# W aste 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 (CH 4 

### ) emissions in 2006, 1 

### the second largest contribution of any CH 4 

### 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. CH 4 

### emissions, respectively. Nitrous oxide (N 2 

### O) emissions from the discharge of wastewater treatment effluents into aquatic environments were estimated, as were N 2 

### O emissions from the treatment process itself. N 2 

### O emissions from composting were also estimated. Together, these waste activities account for less than 3 percent of total U.S. N 2 

### O emissions. Nitrogen oxide (NO x 

### ), carbon monoxide (CO), and non-CH 4 

### 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 CO 2 

### Eq., or just over 2 percent of total U.S. greenhouse gas emissions.

1 Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as described in the Land Use, Land-Use Change, and Forestry chapter. 

### Table 8-1: Emissions from Waste (Tg CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 172.9 169.1 146.7 143.0 145.5 151.0 148.1 149.0 151.1

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 N 2 O 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 CO 2 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 CH 4 

### emissions were approximately 125.7 Tg CO 2

### Eq. (5,985 Gg of CH 4 

### ), representing the second largest source of CH 4 

### 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 CH 4 

### (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 CH 4 

### -producing anaerobic bacteria convert the fermentation products into stabilized organic materials and biogas consisting of approximately 50 percent carbon dioxide (CO 2 

### ) and 50 percent CH 4 

### , by volume. 2 

### Significant CH 4 

### production typically begins one or two years after waste disposal in a landfill and continues for 10 to 60 years or longer.

2 The percentage of CO 2 in biogas released from a landfill may be smaller because some CO 2 dissolves in landfill water (Bingemer and Crutzen 1987). Additionally, less than 1 percent of landfill gas is typically composed of non-CH 4 volatile organic compounds (NMVOCs). 

### From 1990 to 2006, net CH 4 

### 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 CH 4 

### 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 CH 4

### that is recovered and either flared or used for energy purposes; and (4) the amount of CH 4

### 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 CH 4

### recovered and combusted from MSW landfills increased as well. In 1990, for example, approximately 888 Gg of CH 4 

### were recovered and combusted (i.e., used for energy or flared) from landfills, while in 2006, 5,958 Gg CH 4

### 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 CH 4

### 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

3 The CO 2 produced from combusted landfill CH 4 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 CH 4 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 N 2 O 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 CH 4

### that is recovered and either flared or used for energy purposes is expected to continue to increase as a result of 1996 federal regulations that require large municipal solid waste landfills to collect and combust landfill gas (see 40 CFR Part 60, Subpart Cc 2005 and 40 CFR Part 60, Subpart WWW 2005), voluntary programs encouraging CH 4

### 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 CH 4 

### emissions from landfills can be found in Annex 3.14.

CH 4 

### emissions from landfills were estimated to equal the CH 4 

### produced from municipal solid waste landfills, plus the CH 4 

### produced by industrial landfills, minus the CH 4 

### recovered and combusted, minus the CH 4 

### oxidized before being released into the atmosphere:

The methodology for estimating CH 4 

### 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 CH 4 

### generation potential (L 0 

### ) and rate constant (k) were obtained from an analysis of CH 4 

### recovery rates for a database of 52 landfills and from published studies of other landfills (RTI 2004; Table 8-3: CH 4 

### Emissions from Landfills (Tg CO 2 

### 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) Oxidized a (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: CH 4 

### 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) Oxidized a (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.



### CH 4,Solid Waste 

### = [CH 4,MSW 

### + CH 4,ind

### – R] – Ox where,

CH 4,Solid Waste 

### = CH 4 

### emissions from solid waste CH 4,MSW 

### = CH 4 

### generation from municipal solid waste landfills, CH 4,ind 

### = CH 4 

### generation from industrial landfills,
R = CH 4 

### recovered and combusted, and Ox = CH 4 

### 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 CH 4 

### generation, estimates for those years were included in the first order decay model for completeness in accounting for CH 4 

### 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 landfillsthat 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 CH 4 

### 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 CH 4 

### recovered to estimate CH 4 

### 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 CH 4 

### oxidized by the landfill cover at both municipal and industrial landfills was assumed to be ten percent of the CH 4 

### generated that is not recovered (IPCC 2006, Mancinelli and McKay 1985, Czepiel et al. 1996). To calculate net CH 4 

### emissions, both CH 4 

### recovered and CH 4 

### oxidized were subtracted from CH 4 

### generated at municipal and industrial landfills.

### Waste 8-5 

# Uncertainty Several types of uncertainty are associated with the estimates of CH 4 

### emissions from landfills. The primary uncertainty concerns the characterization of landfills. Information is not available on two fundamental factors affecting CH 4 

### production: the amount and composition of waste placed in every landfill for each year of its operation. The approach used here assumes that the CH 4 

### generation potential and the rate of decay that produces CH 4 

### , as determined from several studies of CH 4 

### recovery at landfills, are representative of U.S. landfills. Additionally, the approach used to estimate the contribution of industrial wastes to total CH 4 

### generation introduces uncertainty. Aside from uncertainty in estimating CH 4 

### 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).

N 2 

### O emissions from the application of sewage sludge on landfills are not explicitly modeled as part of greenhouse gas emissions from landfills. N 2 

### O 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 N 2 

### O emissions. Furthermore, the 2006 IPCC Guidelines (IPCC 2006) did not include a methodology for estimating
N 2 

### O emissions from solid waste disposal sites “because they are not significant.” Therefore, any uncertainty or bias caused by not including N 2 

### O emissions from landfills is expected to be minimal. The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 8-5. Landfill CH 4 

### emissions in 2006 were estimated to be between 74.7 and 168.5 Tg CO 2 

### Eq., which indicates a range of 41 percent below to 34 percent above the 2006 emission estimate of 125.7 Tg CO 2 

### 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 CH 4 

### Emissions from Landfills (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Landfills CH 4 125.7 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 CH 4

### generation rate for the 1990 to 2005 time series by 5.6 percent, and it reduced the industrial landfill CH 4 

### generation rate for the 1990 to 2005 time series by 1.8 percent. Another significant recalculation, which affected estimates of CH 4 

### 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 CH 4 

### recovered and destroyed by gas-to-energy projects and a net decrease of 0.5 percent in the estimated CH 4 

### 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 CH 4 

### and N 2 

### O 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 ofdomestic 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. CO 2 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 CO 2 that was originally removed by photosynthesis. In contrast, CH 4 emissions from landfilled waste occur due to the man-made anaerobic conditions conducive to CH 4 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 CH 4 

### . 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 N 2 

### O 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 (NO 3 

### ) through the aerobic process of nitrification. Denitrification occurs under anoxic conditions (without free oxygen), and involves the biological conversion of nitrate into dinitrogen gas (N 2 

### ). N 2 

### O can be an intermediate product of both processes, but is more often associated with denitrification. The principal factor in determining the CH 4 

### 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 CH 4 

### 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 availablefor chemical oxidation (both biodegradable and nonbiodegradable). Because BOD is an aerobic parameter, it is preferable to use COD to estimate CH 4 

### production. The principal factor in determining the N 2 

### O generation potential of wastewater is the amount of N in the wastewater. In 2006, CH 4 

### emissions from domestic wastewater treatment were 16.0 Tg CO 2 

### 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, CH 4 

### emissions from industrial wastewater treatment were estimated to be 7.9 Tg CO 2 

### 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 CH 4 

### and N 2 

### O emission estimates from domestic and industrial wastewater treatment. With respect to N 2 

### O, the United States identifies two distinct sources for N 2 

### O 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 N 2 

### O from centralized wastewater treatment processes and from effluent were estimated to be 0.3 Tg CO 2 

### Eq. (1 Gg) and 7.8 Tg CO 2 

### Eq. (25 Gg), respectively. Total N 2 

### O emissions from domestic wastewater were estimated to be 8.1 Tg CO 2 

### Eq. (26 Gg).
N 2 

### O 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: CH 4 

### and N 2 

### O Emissions from Domestic and Industrial Wastewater Treatment (Tg CO 2 

### Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 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 N 2 O 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 CH 4 

### Emission Estimates Domestic wastewater CH 4 

### emissions originate from both septic systems and from centralized treatment systems, such as publicly owned treatment works (POTWs). Within these centralized systems, CH 4 

### 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. CH 4 

### emissions from septic systems were estimated by multiplying the total BOD 5 

### produced in the United States by the percent of wastewater treated in septic systems (21 percent), the maximum CH 4 

### producing capacity for domestic wastewater (0.60 kg CH 4 

### /kg BOD), and the CH 4 

### correction factor (MCF) for septic systems (0.5). CH 4 

### emissions from POTWs were estimated by multiplying the total BOD 5 

### 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 BOD 5 

### treated after primary treatment (67.5 percent), the maximum CH 4 

### -producing capacity of domestic wastewater (0.6), and the relative MCFs for aerobic (zero or 0.3) and anaerobic (0.8) systems. CH 4 

### emissions from anaerobic digesters were estimated by multiplying the amount of biogas generated by wastewater sludge treated in anaerobic digesters by the proportion of CH 4 

### in digester biogas (0.65), the density of CH 4 

### (662 g CH 4 

### /m 3 

### CH 4 

### ), and the destruction efficiency associated with burning the biogas in an energy/thermal device (0.99). 6 

### The methodological equations are:

6 Anaerobic digesters at wastewater treatment plants generated 798 Gg CH 4 in 2006, 790 Gg of which was combusted in flares or energy devices (assuming a 99% destruction efficiency). 

### Table 8-7: CH 4 

### and N 2 

### O Emissions from Domestic and Industrial Wastewater Treatment (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 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 N 2 O 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 BOD 5 

### produced) × (B o 

### ) × (MCF-septic) × 1/10^6 Emissions from Centrally Treated Aerobic Systems = B = [(% collected) × (total BOD 5 

### produced) × (% aerobic) × (% aerobic w/out primary) + (% collected) × (total BOD 5 

### produced) × (% aerobic) × (% aerobic w/primary) × (1-% BOD removed in prim. treat.)] × (% operations not well managed) × (B o 

### ) × (MCF-aerobic_not_well_man.) × 1/10^6 Emissions from Centrally Treated Anaerobic Systems = C = [(% collected) × (total BOD 5 

### produced) × (% anaerobic) × (% anaerobic w/out primary) + (% collected) ×(total BOD 5 

### produced) × (% anaerobic) ×(% anaerobic w/primary) × (1-%BOD removed in prim. treat.)] × (B o 

### ) × (MCF-anaerobic) × 1/10^6 Emissions from Anaerobic Digesters = D = [(POTW_flow_AD) × (digester gas)/(per capita flow)] × conversion to m 3 

### × (FRAC_CH 4 

### ) _ (365.25) × (density of CH 4 

### ) × (1-DE) × 1/10^9

Total CH 4 

### Emissions (Gg) = A + B + C + D
where,

% o nsite = 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 BOD 5 

### 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 BOD 5 

### production rate (0.09 kg/capita/day) for domestic wastewater was obtained from Metcalf and Eddy (1991 and 2003). The CH 4 

### emission factor (0.6 kg CH 4 

### /kg BOD 5 

### ) and the MCFs were taken from IPCC (2006). The CH 4 

### 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

7 Aerobic and anaerobic treatment were determined based on unit processes in use at the facilities. Because the list of unit processes became more extensive in the 2000 and 2004 surveys, the criteria used to identify aerobic and anaerobic treatment differ slightly across the time series. Once facilities were identified as aerobic or anaerobic, they were separated by whether or not they had anaerobic digestion in place. Once these classifications were determined, the flows associated with facilities in each category were summed. 

### % 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 BOD 5 

### produced = kg BOD/capita/day × U.S. population × 365.25 days/yr

B o 

### = Maximum CH 4 

### -producing capacity for domestic wastewater (0.60 kg CH 4 

### /kg BOD) MCF-septic = CH 4 

### correction factor for septic systems (0.5)

1/10^6 = Conversion factor, kg to Gg MCF-aerobic_ not_ well_man. = CH 4 

### correction factor for aerobic systems that are not well managed (0.3)

MCFanaerobic = CH 4 

### correction factor for anaerobic systems (0.8)

DE = CH 4 

### 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 ft 3 

### /person/ day) (Metcalf and Eddy 1991) per capita flow = Wastewater flow to POTW per person per day (100 gal/person/day)

conversion to m 3 

### = Conversion factor, ft 3 

### to m 3 

### (0.0283)
FRAC_CH 4 

### = Proportion CH 4 

### in biogas (0.65) density of CH 4 

### = 662 (g CH 4 

### /m 3 

### CH 4 

### )
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 ft 3 

### /person/day) and the proportion of CH 4 

### 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 CH 4 

### Emission Estimates
CH 4 

### emissions estimates from industrial wastewater were developed according to the methodology described in IPCC (2006). Industry categories that are likely to produce significant CH 4 

### 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.

CH 4 

### 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 B o 

### value used for all industries is the IPCC default value of 0.25 kg CH 4 

### /kg COD (IPCC 2006). The methodological equation is: Table 8-8: U.S. Population (Millions) and Domestic Wastewater BOD 5 

### Produced (Gg)

Year Population BOD 5 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 

### CH 4 

### (industrial wastewater) =
P × W × COD × TA × B o 

### × MCF where,

CH 4 

### (industrial wastewater) = Total CH 4 

### emissions from industrial wastewater (kg/year)

P = Industry output (metric tons/year)

W = Wastewater generated (m 3 

### /metric ton of product)

COD = Organics loading in wastewater (kg /m 3 

### )

TA = Percent of wastewater treated anaerobically on site

B o 

### = Maximum CH 4 

### producing potential of industrial wastewater (default value of 0.25 kg CH 4 

### /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 CH 4 

### 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 CH 4 

### emission calculation is: A time series of CH 4

### 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 m 3 

### /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 B o 

### of 0.25 kg CH 4 

### / kg COD and default MCF of 0.8 for anaerobic lagoons were used to estimate the CH 4 

### 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

m 3 

### /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 × B o 

### × MCF where,

Production = metric tons of pulp, paper, and paperboard production
Flow = cubic meters of wastewater gener

ated 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%)

B o 

### = maximum methane producing capacity (0.25 mg CH 4 

### /mg COD)

MCF = methane conversion factor for anaerobic deep lagoons (0.80) MCF = CH 4

### correction factor, indicating the extent to which the organic content (mea

sured 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 B o 

### of 0.25 kg CH 4 

### /kg COD and default MCF of 0.8 for anaerobic treatment were used to estimate the CH 4 

### 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. CH 4 

### 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). CH 4 

### emissions were then estimated as follows: Table 8-10: Wastewater Flow (m 3 

### /ton) and BOD Production (g/L) for U.S. Vegetables, Fruits and Juices Production

Commodity Wastewater Outflow (m 3 /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 × B o 

### × MCF × % Not Recovered] + [Production × Flow × 3.785 × COD × %TA × B o 

### × MCF × (% Recovered) × (1-DE)] × 1/10^9

### Waste 8-13 A time series of CH 4 

### emissions for 1990 through 2006 was developed based on production data from the Renewable Fuels Association (RFA 2006).

Domestic Wastewater N 2 

### O Emission Estimates
N 2 

### O 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 (N SLUDGE 

### ). 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 N 2 

### O 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 N 2 

### O 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 N 2 

### O per capita per year.

8 The methodology for estimating the quantity of sewage sludge N not entering aquatic environments is described in Annex 3.11.

9 Metcalf & Eddy (1991) provide a typical influent nitrogen concentration of 40 mg/L Total Kjeldahl Nitrogen (TKN) for average wastewater from residences, which includes bathwater, laundry, and the use of garbage disposals. The factor for non-consumptive protein was estimated based on wastewater treated in 1990, the percent of population serviced by centralized treatment systems, and the per capita TKN loading, resulting in a factor of 1.4.

10 The type, composition, and quantity of this co-discharged wastewater vary greatly between municipalities. Metcalf & Eddy (1991) provide a range of influent nitrogen concentrations of 20 to 85 mg/L TKN (average 55) for combined residential and industrial wastewater, while residential wastewater loading was roughly estimated at 40 mg TKN/L (see previous footnote). Until better data become available, the amountof 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)

B o 

### = maximum methane producing capacity (0.25 g CH 4 

### /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, N 2 

### O 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 (EF 1 

### ) 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 (EF 3 

### ) has not been specifically estimated for the United States, thus the default IPCC value (0.005 kg
N 2 

### O-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. 

### N 2 

### O TOTAL 

### = N 2 

### O PLANT

### + N 2 

### O EFFLUENT 

### N 2 

### O PLANT

### = N 2 

### O NIT/DENIT

### + N 2 

### O WOUT NIT/DENIT 

### N 2 

### O NIT/DENIT

### = [(US POPND 

### ) × EF 2 

### × F IND-COM 

### ] × 1/10^9

N 2 

### O WOUT NIT/DENIT 

### = {[(US POP 

### × WWTP) - US POPND 

### × F IND-COM 

### ] × EF 1 

### } × 1/10^9

N 2 

### O EFFLUENT

### = {[(US POP 

### × Protein × F NPR 

### × F NON-CON 

### × F IND-COM 

### ) - N SLUDGE 

### ] × EF 3 

### × 44/28} × 1/10^6
where,

N 2 

### O TOTAL 

### = Annual emissions of N 2 

### O (kg)

N 2 

### O PLANT 

### = N 2 

### O emissions from centralized wastewater treatment plants (kg)

N 2 

### O NIT/DENIT 

### = N 2 

### O emissions from centralized wastewater treatment plants with nitrification/denitrification (kg)

N 2 

### O WOUT NIT/DENIT 

### = N 2 

### O emissions from centralized wastewater treatment plants without nitrification/denitrifica

tion (kg)

N 2 

### O EFFLUENT 

### = N 2 

### O emissions from wastewater effluent discharged to aquatic environments (kg)

US POP 

### = U.S. population

US POPND 

### = U.S. population that is served by biological denitrification (from CWNS)

WWTP = Fraction of population using WWTP (as opposed to septic systems)

EF 1 

### = Emission factor (3.2 g N 2 

### O/ person-year)

EF 2 

### = Emission factor (7 g N 2 

### O/ person-year)

Protein = Annual per capita protein con

sumption (kg/person/year)

F NPR 

### = Fraction of N in protein, default = 0.16 (kg N/kg protein)

F NON-CON 

### = Factor for non-consumed protein added to wastewater (1.4) F IND-COM 

### = Factor for industrial and commer

cial co-discharged protein into the sewer system (1.25)

N SLUDGE 

### = N removed with sludge, kg N/yr

EF 3 

### = Emission factor (0.005 kg N 2 

### O -N/kg sewage-N produced)

44/28 = Molecular weight ratio of N 2 

### O to N 2

### 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 (N SLUDGE 

### ) 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 CH 4 

### and N 2 

### O 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 CH 4 

### 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 N 2 

### O 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. CH 4 

### emissions from wastewater treatment were estimated to be between 15.0 and 35.2 Tg CO 2 

### Eq. at the 95 percent confidence level (or in 19 out of 20 Monte Carlo Stochastic Simulations). This indicates a range of approximately 37 percent below to 48 percent above the 2006 emissions estimate of 23.9 Tg CO 2 

### Eq. N 2 

### O emissions from wastewater treatment were estimated to be between 1.8 and 16.2 Tg CO 2 

### Eq., which indicates a range of approximately 78 percent below to 100 percent above the actual 2006 emissions estimate of 8.1 Tg CO 2 

### 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 CH 4 

### emissions from domestic wastewater include one major methodological refinement

Table 8-12: Tier 2 Quantitative Uncertainty Estimates for CH 4 

### and N 2 

### O Emissions from Wastewater Treatment (Tg CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate a

Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Wastewater Treatment CH 4 23.9 15.0 35.2 -37% +48%

Domestic CH 4 16.0 7.9 26.6 -51% +66% Industrial CH 4 7.9 4.5 12.8 -43% +62% Domestic Wastewater

Treatment N 2 O 8.1 1.8 16.2 -78% +100%

a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.

### 8-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 and one major data change. First, for centralized wastewater treatment systems, CH 4 

### emissions were estimated based on the total BOD 5 

### available for biological treatment rather than the total BOD 5 

### entering wastewater treatment plants. Metcalf and Eddy (1991) estimate that 25

– 40 percent of BOD 5 

### at aerobic and anaerobic plants is removed through primary sedimentation, meaning that not all of the BOD 5 

### 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 CH 4 

### occur during primary treatment. The estimate of BOD treated anaerobically during secondary treatment was also updatedbased on the number of operations expected to have nonaerated stabilization basins. These systems were reclassified as anaerobic deep lagoons, and CH 4 

### 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 CH 4 

### emission estimates for wastewater treatment are on average 6 percent lower than the previous Inventory. For N 2 

### O 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 N 2 

### O emissions from centralized wastewater treatment plants. This resulted in a N 2 

### O emission factor from centralized treatment plants that have intentional nitrification/ denitrification unit operations of 8.75 g N 2 

### O/person-year (7 g N 2 

### O/person-year × 1.25) and a N 2 

### O emission factor from centralized wastewater treatment plants that do not have intentional nitrification/denitrification unit operations of 4 g N 2 

### O/person-year (3.2 g N 2 

### O/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 (CH 4 

### and N 2 

### O) decreased by an average of approximately 5 percent from the previous Inventory. 

# Planned Improvements Discussion The methodology to estimate CH 4 

### 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 CH 4 

### (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 CH 4 

### , 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 N 2 

### O emissions, the default emission factor for N 2 

### O 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 N 2 

### O 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 (CO 2 

### ). Methane (CH 4 

### ) 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 CH 4 

### 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 (N 2 

### O). 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 CH 4 

### and N 2 

### O from composting have increased by the same percentage (see Table 8-13 and Table 8-14). In 2006, CH 4 

### emissions from composting were 1.6 Tg CO 2 

### Eq. (75 Gg), and N 2 

### O emissions from composting were 1.8 Tg CO 2 

### 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: CH 4 

### and N 2 

### O Emissions from Composting (Tg CO 2 

### Eq.)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 0.3 0.7 1.3 1.3 1.3 1.5 1.6 1.6 1.6 N 2 O 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: CH 4 

### and N 2 

### O Emissions from Composting (Gg)

Activity 1990 1995 2000 2001 2002 2003 2004 2005 2006 CH 4 15 35 60 60 61 69 74 75 75 N 2 O 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 CO 2 

### Eq. and Percent)

2006 Emission Estimate Uncertainty Range Relative to Emission Estimate Source Gas (Tg CO 2 Eq.) (Tg CO 2 Eq.) (%) Lower Bound Upper Bound Lower Bound Upper Bound Composting CH 4 , N 2 O 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

CH 4 

### and N 2 

### O 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 CH 4 

### 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 CO 2 

### Eq., which indicates a range of 50 percent below to 50 percent above the actual 2006 emission estimate of 3.3 Tg CO 2 

### 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 CH 4 

### and N 2 

### O 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,

E i 

### = CH 4 

### or N 2 

### O emissions from composting, Gg CH 4 

### or N 2 

### O,

M = mass of organic waste composted in Gg,

EF i 

### = emission factor for composting, 4 g CH 4 

### / kg of waste treated (wet basis) and 0.3 g N 2 

### O/kg of waste treated (wet basis), and

i = designates either CH 4 

### or N 2 

### O.

### 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 NO x 

### , 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 NO x 

### , CO, and NMVOC from Waste (Gg)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 2006 NO x + 1 2 2 2 2 2 2 2

Landfills + 1 2 2 2 2 2 2 2 Wastewater Treatment + + + + + + + + + Miscellaneous a + 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 + + + + + Miscellaneous a + 1 + + + + + + + NMVOCs 673 731 119 122 115 114 112 111 110

Wastewater Treatment 57 61 23 23 22 22 21 21 21 Miscellaneous a 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 CO 2 

### Eq). In addition to the changes summarized by the tables below, the following sources and gases were added to the current Inventory:

• Carbon dioxide ( CO 2 

### ) emissions from Cropland Remaining Cropland, which include CO 2 

### emissions from Agricultural Liming and Urea Fertilization;

• CO 2 

### 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 (CH 4 

### ) and nitrous oxide (N 2 

### O) 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 N 2 

### O emissions from Agricultural Soil Management of 102.1 Tg CO 2 

### Eq. (27.5 percent) for the period 1990 through 2005.

### 10-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 • Net CO 2 

### Flux from Land Use, Land-Use Change, and Forestry. Forest Land Remaining Forest Land is the principal section contributing to the change in net CO 2 

### 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 CO 2 

### to the atmosphere from the Land Use, Land-Use Change, and Forestry sector of 20.1 Tg CO 2 

### 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 CH 4 

### recovery. Overall, changes resulted in an average annual decrease in CH 4 

### emissions from landfills of 11.4 Tg CO 2 

### Eq. (7.8 percent) for the period 1990 through 2005.

• Enteric Fermentation. Changes in the estimates of CH 4 

### 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 CH 4 

### emissions from Enteric Fermentation of 11.4 Tg CO 2 

### 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 CO 2

### Eq. (14.1 percent) for the period 1990 through 2005.

• Settlements Remaining Settlements. The data source used for N fertilization was updated for N 2 

### O 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 N 2 

### O emissions from Settlements Remaining Settlements of 4.4 Tg CO 2

### 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 CO 2 

### emissions from International Bunker Fuels of 4.2 Tg CO 2 

### 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 N 2 

### O 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 N 2 

### O emissions in the Manure Management Sector associated with N losses from volatilization of nitrogen as ammonia (NH 3 

### ), nitrogen oxides (NO x 

### ), and leaching and runoff. Fourth, the days

### Recalculations and Improvements 10-3 per year used in N 2 

### O calculations was changed from 365 to 365.25 to include leap years and to be consistent with the CH 4 

### 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 N 2 

### O emissions from Manure Management of 4.0 Tg CO 2 

### 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 CH 4 

### emissions from Coal Mining of 3.7 Tg CO 2 

### Eq. (6.2 percent) for the period 1990 through 2005.

• Ammonia Manufacture and Urea Consumption. CO 2 

### 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 CO 2 

### 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 CO 2 

### emissions from Ammonia Manufacture and Urea Consumption of 3.0 Tg CO 2 

### Eq. (15.8 percent) for the period 1990 through 2005.

Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 CO 2 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 Cropland a 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 CO 2 

### Eq.)

Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005 CH 4 (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) Composting a 0.3 0.7 1.3 1.3 1.3 1.5 1.6 1.6 International Bunker Fuels NC NC NC NC NC + + + N 2 O (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) + N 2 O 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 Composting a 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 SF 6 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 Emissions b (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 CO 2 Eq. or 0.05 percent. NC (No Change)

a New source category relative to previous inventory. b Excludes net CO 2 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 CO 2 

### to the Atmosphere from Land Use, Land-Use Change, and Forestry (Tg CO 2 

### Eq.)

Component: Net CO 2 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 CO 2 to the atmosphere, or an increase in net sequestration. Note: Totals may not sum due to independent rounding.

### References 11-1 

# 11. References

Executive Summary

BEA (2007) 2006 Comprehensive Revision of the National Income and Product Accounts: Current-dollar and “real” GDP, 1929–2006 . Bureau of Economic Analysis (BEA), U.S. Department of Commerce, Washington, DC. July 29, 2007. Available online at <http://www.bea.doc.gov/bea/ dn1.htm>. EIA (2007a) “Supplemental Tables on Petroleum Product detail.” Monthly Energy Review, September 2007

. Unpublished. Energy Information Administration (EIA),U.S. Department of Energy. Washington, DC, DOE/EIA0035(2007/09). EIA (2007b) International Energy Annual 2005 . Energy Information Administration (EIA), U.S. Department of Energy. Washington, DC. Updated June–October 2007. Available online at <http://www.eia.doe.gov/emeu/iea/ carbon.html>. EPA (2008) Air Emissions Trends—Continued Progress Through 2006 . U.S. Environmental Protection Agency (EPA), Washington, DC. Available online at <http://www. epa.gov/air/airtrends/index.html>. December 19, 2006. EPA (2003) E-mail correspondence. Air pollutant data. Office of Air Pollution to the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency (EPA). December 22, 2003. IPCC (2007) Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change . S. Solomon , D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.). Cambridge University Press. Cambridge, United Kingdom, 996. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry . National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, J. Penman, et al. (eds.). Available online at <http://www.ipcc-nggip.iges.or.jp/public/gpglulucf/ gpglulucf.htm>. August 13, 2004. IPCC (2001) Climate Change 2001: The Scientific Basis

. Intergovernmental Panel on Climate Change, J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell (eds.). Cambridge University Press. Cambridge, United Kingdom. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
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### 11-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 

# Introduction

Blasing and Jones (2004) “Current Greenhouse Gas Concentrations.” In Trends: A Compendium of Data on Global Change . Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory. Oak Ridge, TN. EPA (2008) Air Emissions Trends—Continued Progress Through 2006 . U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www.epa.gov/ airtrends/econ-emissions.html>. EPA (2003) E-mail correspondence. Air pollutant data. Office of Air Pollution to the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency (EPA). December 22, 2003. IPCC (2001) Climate Change 2001: The Scientific Basis

. Intergovernmental Panel on Climate Change, J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell (eds.). Cambridge University Press. Cambridge, United Kingdom. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
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. Intergovernmental Panel on Climate Change, , J.E. Penner, et al. (eds.). Cambridge University Press. Cambridge, United Kingdom. IPCC (1996) Climate Change 1995: The Science of Climate Change . Intergovernmental Panel on Climate Change, J.T. Houghton, L.G. Meira Filho, B.A. Callander, N. Harris, A. Kattenberg, and K. Maskell. (eds.). Cambridge University Press. Cambridge, United Kingdom. IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. Jacobson, M.Z. (2001) “Strong Radiative Heating Due to the Mixing State of Black Carbon in Atmospheric Aerosols.” Nature , 409:695–697. NRC (2001) Climate Change Science: An Analysis of Some Key Questions . Committee of the Science of Climate Change, National Research Council (NRC). Available online at <http://books.nap.edu/html/climatechange>. UNEP/WMO (1999) Information Unit on Climate Change

. Framework Convention on Climate Change. Available online at <http://unfccc.int>. UNFCCC (2006) Updated UNFCCC reporting guidelines on annual inventories following incorporation of the provisions of decision 14/CP.11 . Note by the secretariat. (FCCC/SBSTA/2006/9). United Nations Office at Geneva, Geneva. UNFCCC (2003) National Communications: Greenhouse Gas Inventories from Parties included in Annex I to the Convention , UNFCCC Guidelines on Reporting and Review. Conference of the Parties, Eighth Session, New Delhi. (FCCC/CP/2002/8). March 28, 2003. WMO (1999) Scientific Assessment of Ozone Depletion, Global Ozone Research and Monitoring Project-Report No. 44 , World Meteorological Organization, Geneva, Switzerland.


# Trends in Greenhouse Gas Emissions

BEA (2007) 2006 Comprehensive Revision of the National Income and Product Accounts: Current-dollar and “real” GDP, 1929–2006 . Bureau of Economic Analysis (BEA), U.S. Department of Commerce, Washington, DC. July 29, 2007. Available online at <http://www.bea.doc.gov/bea/ dn1.htm>. Duffield, J. (2006) Personal communication. Jim Duffield, Office of Energy Policy and New Uses, USDA and Lauren Flinn, ICF International. April and December. EIA (2007b) Short-Term Energy Outlook . Energy Information Administration, U.S. Department of Energy, Washington, DC. EIA. (2007c) “Appendix A. Table A3: Approximate Heat Content of Petroleum Consumption.” Annual Energy Review

. Energy Information Administration, U.S. Department of Energy. Washington, D.C. Available online at <http://tonto. eia.doe.gov/bookshelf/SearchResults.asp?title=Annual+ Energy+Review>. EIA (1991 through 2006) “Table 22: Adjusted Sales for Farm Use: Distillate Fuel Oil and Kerosene; Sales for Electric Power and Oil Company Uses: Distillate Fuel Oil and Residual Fuel Oil, 2005.” Fuel Oil and Kerosene Sales

. Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www. eia.doe.gov/pub/oil_gas/petroleum/data_publications/fuel_ oil_and_kerosene_sales/historical/2005/foks_2005.html> EPA (2008) Air Emissions Trends—Continued Progress Through 2006 . U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www.epa.gov/ airtrends/econ-emissions.html>. Heydorn, B. (1997) “Nitrous Oxide—North America.” Chemical Economics Handbook, SRI Consulting . May 1997.

### References 11-3 IPCC (2001) Climate Change 2001: The Scientific Basis

. Intergovernmental Panel on Climate Change, J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell (eds.). Cambridge University Press. Cambridge, United Kingdom. U.S. Census Bureau (2007) U.S. Census Bureau International Database (IDB) . Available online at <http://www.census. gov/ipc/www/idbnew.html>. August 15, 2007. 

# Energy

EIA (2007) International Energy Annual 2007 . Energy Information Administration, U.S. Department of Energy. Washington, DC. Updated June-October 2007. Available online at <http://www.eia.doe.gov/emeu/iea/carbon.html>.



# Carbon Dioxide Emissions from Fossil Fuel Combustion AAR (2007) Personal Communication. Clyde Crimmel, Association of American Railroads. Diesel Fuel Consumption for Class I Railroads and Aaron Beaudette, ICF International. October 9, 2007. AISI (1995 through 2007) Annual Statistical Report

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### Pipeline Route and Designation Information . Bismarck, ND. Available online at <http://www.dakotagas.com/SafetyHealth/ Pipeline_Information.html>. DHS (2008). Email communication. Elissa Kay, Department of Homeland Security, and Joe Aamidor, ICF International. January 11, 2008. DESC (2007) Unpublished data from the Defense Fuels Automated Management System (DFAMS). Defense Energy Support Center, Defense Logistics Agency, U.S. Department of Defense. Washington, DC. DOC (1991 through 2007) Unpublished Report of Bunker Fuel Oil Laden on Vessels Cleared for Foreign Countries. Form-563. Foreign Trade Division, Bureau of the Census, U.S. Department of Commerce. Washington, DC. DOE (1993 through 2005) Transportation Energy Data Book . Office of Transportation Technologies, Center for Transportation Analysis, Energy Division, Oak Ridge National Laboratory. Oak Ridge, TN. ORNL-6959. DOT (1991 through 2007) Fuel Cost and Consumption

. Federal Aviation Administration, Bureau of Transportation Statistics, U.S. Department of Transportation . Washington, DC. DAI-10. EIA (2007a) Annual Energy Review 2006 . Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0384(2006). June 2007. EIA (2007b) Supplemental Tables on Petroleum Product detail. Monthly Energy Review , December 2007, Energy Information Administration, U.S. Department of Energy, Washington, DC. DOE/EIA-0035(2007/12). EIA (2007c) Emissions of Greenhouse Gases in the United States 2006 , Draft Report. Office of Integrated Analysis and Forecasting, Energy Information Administration,U.S. Department of Energy. Washington, DC. DOE-EIA0573(2006). EIA (2007d) “Table 3.1: World Petroleum Supply and Disposition.” International Energy Annual . Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe. gov/iea/pet.html>. EIA (2007e) Natural Gas Annual 2006 . Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0131(06). November 2007. EIA (2007f) Short-Term Energy Outlook . Energy Information Administration, U.S. Department of Energy. Washington, DC. December 2006. EIA (2007g) Personal Communication. Joel Lou, Energy Information Administration and Aaron Beaudette, ICF International. Residual and Distillate Fuel Oil Consumption for Vessel Bunkering (Both International and Domestic) for American Samoa, U.S. Pacific Islands, and Wake Island

. October 24, 2007.

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### Reduction (PCOR) Partnership

. Presented at the Regional Carbon Sequestration Partnership Meeting Pittsburgh, Pennsylvania, Energy and Environmental Research Center, University of North Dakota. November 3, 2003. Available online at <http://www.netl.doe.gov/ publications/proceedings/03/carbon-seq/Erickson.pdf>. FAA (2005) “Table 32: General Aviation Aircraft Fuel Consumption,” FAA Aerospace Forecasts Fiscal Years 2005–2016 . Federal Aviation Administration. Available online at <http://www.faa.gov/data_statistics/aviation/ aerospace_forecasts/2005-2016/>. Fitzpatrick, E. (2002) The Weyburn Project: A Model for International Collaboration . Available online at <http://www. netl.doe.gov/coalpower/sequestration/pubs/mediarelease/ mr-101102.pdf>. FHWA (1996 through 2006) Highway Statistics . Federal Highway Administration, U.S. Department of Transportation. Washington, DC. Report FHWA-PL-96-023-annual. FRB (2006) Industrial Production and Capacity Utilization

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, 79(26). June 25, 2001. Available online at <http://pbus.acs. org/cen>. APC (2000) as reported in “Facts & Figures for the Chemical Industry.” Chemical & Engineering News , 78(26). June 26, 2000. American Plastics Council, Arlington, VA. Available online at <http://www.plasticsindustry.org/industry/stat3. htm>. Bank of Canada (2006) Financial Markets Department Year Average of Exchange Rates . Available online at <http://www. bankofcanada.ca/en/rates/exchange_avg_pdf.html>. CMA (1999) U.S. Chemical Industry Statistical Handbook

. Chemical Manufacturer’s Association, Washington, DC. Connolly, U. (2000) Personal communication. Una Connelly, National Asphalt Pavement Association and Suzanne Bratis, ICF International. August 2000. EIA (2007) “Supplemental Tables on Petroleum Product detail.” Monthly Energy Review , December 2007. Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0035(2007/12). EIA (2005) EIA Manufacturing Consumption of Energy (MECS) 2002. Energy Information Administration, U.S. Department of Energy. Washington, DC. EIA (2001) Manufacturing Energy Consumption Survey (MECS) 1998. Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe.gov/emeu/mecs/mecs98/datatables/ contents.html>. EIA (1997) Manufacturing Energy Consumption Survey (MECS) 1994. Energy Information Administration, U.S. Department of Energy. Washington, DC. December 1997. DOE/EIA-0512(94). EIA (1994) Manufacturing Energy Consumption Survey (MECS) 1991. Energy Information Administration, U.S. Department of Energy. Washington, DC. December 1994. DOE/EIA-0512(91). EIIP (1999) Methods for Estimating Greenhouse Gas Emissions from Combustion of Fossil Fuels . Emissions Inventory Improvement Program: State and Territorial Air Pollution Program Administrators/Association of Local Air Pollution Control Officials and U.S. Environmental Protection Agency, EIIP Document Series Volume VIII, Chapter 1, STAPPA/ALAPCO/EPA, Washington, DC. August 2000. Available online at <http://www.epa.gov/ttn/ chief/eiip/viii01.pdf>. August 28, 2000. EIIP (1998) “Area Sources.” In Asphalt Paving . Emissions Inventory Improvement Program: State and Territorial Air Pollution Program Administrators/Association of Local Air Pollution Control Officials and U.S. Environmental Protection Agency, EIIP Document Series Volume III, Chapter 17, STAPPA/ALAPCO/EPA, Washington, DC. August 2000. Available online at <http://www.epa.gov/ttn/ chief/eiip/iii17.pdf>. July 27, 2000. Eldredge-Roebuck, B. (2000) Personal communication Brandt Eldredge-Roebuck, American Plastics Council and Joe Casola, ICF International. July 11, 2000. EPA (2007) Biennial Reporting System (BRS) Database

. Envirofacts Warehouse, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www. epa.gov/enviro/html/brs/>. EPA (2006a) Air Emissions Trends—Continued Progress Through 2005 . U.S. Environmental Protection Agency, Washington, DC. December 19, 2006.Available online at <http://www.epa.gov/air/airtrends/index.html>. EPA (2006b) Biennial Reporting System (BRS) Database

. Envirofacts Warehouse, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www. epa.gov/enviro/html/brs/>. EPA (2004a) Biennial Reporting System (BRS) Database

. Envirofacts Warehouse, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www. epa.gov/enviro/html/brs/>. EPA (2004b) Pesticides Industry Sales and Usage: 2000 and 2001 Market Estimates . Office of Prevention, Pesticides and Toxic Substances, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www.epa.gov/ oppbead1/pestsales/>. EPA (2004c) “Ch. 11: Mineral Products Industry, Hot Mix Asphalt Plants.” AP 42, Fifth Edition Compilation of Air Pollutant Emission Factors, Volume 1: Stationary Point and Area Sources . Available online at <http://www.epa.gov/ttn/ chief/ap42/>. February 25, 2008. EPA (2002) Pesticides Industry Sales and Usage, 1998 and 1999 Market Estimates . Office of Prevention, Pesticides and Toxic Substances, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www.epa.gov/ oppbead1/pestsales/99pestsales/market_estimates1999.pdf>. July 2003.

### 11-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 EPA (2001) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–1999 . Office of Atmospheric Programs, U.S. Environmental Protection Agency. Washington, DC. EPA 236-R-01-001. EPA (2000a) Toxics Release Inventory, 1998 . Office of Information Analysis and Access, Office of Environmental Information, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www.epa.gov/ triexplorer/chemical.htm>. EPA (2000b) Hot Mix Asphalt Plants Emission Assessment Report (Draft Report), AP-42 . Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. June 2000. Available online at <http://www.epa.gov/ttn/emc/asphalt/ea-report.pdf>. July 25, 2000. EPA (1999) Pesticides Industry Sales and Usage: 1996 and 1997 Market Estimates . Office of Prevention, Pesticides and Toxic Substances, U.S. Environmental Protection Agency, Washington, DC. Available online at <http://www.epa.gov/ oppbead1/pestsales/97pestsales/market_estimates1997. pdf>. EPA (1998) Pesticides Industry Sales and Usage, 1994 and 1995 Market Estimates . Office of Prevention, Pesticides and Toxic Substances, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www.epa.gov/ oppbead1/pestsales/95pestsales/market_estimates1995.pdf>. July 2003. EPA (1995) Asphalt Paving Operations, AP-42 . Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. FEB (2007) Fiber Economics Bureau, as cited in C&EN (2007) “Gains in Chemical Output Continue.” Chemical & Engineering News . American Chemical Society. Available online at <http://www.cen-online.org>. July 2, 2007. FEB (2003, 2005, 2006) Fiber Economics Bureau, as cited in C&EN (2006) “Production: Growth in the Norm.” Chemical & Engineering News . American Chemical Society. Available online at <http://www.cen-online.org>. FEB (2001) as reported in “Production: slow gains in output of chemicals and products lagged behind U.S. economy as a whole.” Chemical & Engineering News . Vol. 79(26). Fiber Economics Bureau, Washington, DC. June 25, 2001. Available online at <http://pubs.acs.org/cen/coverstory/792 6/7926facts&figures.html>. The Financial Planning Association (2006) Canada/ US Cross-Border Tools: US/Canada Exchange Rates

. Available online at <http://www.fpanet.org/global/planners/ US_Canada_ex_rates.cfm>. August 16, 2006. Gosselin, Smith, and Hodge (1984) Clinical Toxicology of Commercial Products . Fifth Edition, Williams & Wilkins, Baltimore, MD. IISRP (2003) IISRP Forecasts Moderate Growth in North America to 2007 . International Institute of Synthetic Rubber Producers, Inc. Available online at <http://www.iisrp.com/press-releases/2003-Press-Releases/IISRP-NA-Forecast03-07.html>. IISRP (2000) as reported in ACS (2001) “Facts & Figures for the Chemical Industry.” Chemical & Engineering News . Vol. 78(26). June 26, 2000. International Institute of Synthetic Rubber Producers, Houston, Texas. Available online at <http://www.iisrp.com/Press%20Releases/2000%20 Press%20Releases/ASPR2000-2004.PDF>. February 18, 2000. INEGI (2006) Producción bruta total de las unidades económicas manufactureras por Subsector, Rama, Subrama y Clase de actividad . Available online at <http://www.inegi. gob.mx/est/contenidos/espanol/proyectos/censos/ce2004/ tb_manufacturas.asp>. August 15, 2006. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme. The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. Marland, G. and R. M. Rotty (1984) “Carbon dioxide emissions from fossil fuels: a procedure for estimation and results for 1950–1982.” Tellus , 36B(4), 232–261. Miller, T. (1999) Material Safety Data Sheet, Carbon Black

. Continental Carbon Company. September 1, 1999. Available online at <http://www.continentalcarbon.com/downloads/ MSDS.pdf>. October 10, 2003. NPRA (2001) Selected Petrochemical Statistics—U.S. Trade, Production and Consumption . National Petrochemical & Refiners Association. Washington, DC. PAN (2002) Pesticides Database . Pesticide Action Network North America. Available online at <http://www. pesticideinfo.org>. 2003. RMA (2006) Scrap Tire Markets in the United States 2005 Edition . Rubber Manufacturers Association. Washington, DC. November 2006. RMA (2002) U.S. Scrap Tire Markets 2001 . Rubber Manufacturers Association. Washington, DC. December 2002. Schneider, S. (2007) E-mail communication. Shelly Schneider, Franklin Associates and Sarah Shapiro, ICF International. January 10, 2007. SPI (2000) “The Society of the Plastics Industry.” Available online at <http://www.plasticsindustry.org/industry/stat3. htm>. June 28, 2000.

### References 11-7 Statistics Canada (2006) “Canadian Trade by Industry - NAICS Codes: NAICS 3252 - Resin, Synthetic Rubber, and Artificial and Synthetic Fibres and Filaments Manufacturing (NAICS 3252).” Available online at <http://strategis.ic.gc. ca/sc_mrkti/tdst/tdo/tdo.php?headFootDir=%2Fsc_mrkti%2 Ftdst%2Fheadfoot&naArea=&lang=30&searchType=CS&t oFromCountry=CDN¤cy=US&hSelectedCodes=%7 C3252&period=&timePeriod=%7CCustom+Years&periodS tring=1990%7C1991%7C1992%7C1993%7C1994%7C19 95%7C1996%7C1997%7C1998%7C1999%7C2000%7C2 001%7C2002%7C2003&productBreakDown=Custom+Ye ars&reportType=DS&productType=NAICS&areaCodeStr g=%7CAll&runReport_x=32&javaChart_x=&runGraph_x =&outputType=RPT&chartType=columnApp&grouped= GROUPED#tag>. STMC (2003) Scrap Tire Facts and Figures . Scrap Tire Management Council of the Rubber Manufacturers Association. Washington, DC. Available online at <http:// www.rma.org/scrap_tires/scrap_tire_markets/facts_and_ figures/> and <http://www.rma.org/scrap_tires/scrap_tire_ markets/scrap_tire_characteristics/>. July 7, 2003. Tooly, L. (2001) E-mail communication. Lee Tooly, EPA Office of Air Quality Planning and Standards and Robert Lanza, ICF International. August 20, 2001. U.S. Census Bureau (2004) Soap and Other Detergent Manufacturing: 2002 . December 2004, EC02-31I-325611 (RV). Available online at <http://www.census.gov/prod/ec02/ ec0231i325611.pdf>. U.S. Census Bureau (2003) U.S International Trade Commission (USITC) Trade Dataweb . Available online at <http://dataweb.usitc.gov/>. U.S. Census Bureau (1999) 1997 Economic Census, Manufacturing—Industry Series, Petroleum Lubricating Oil and Grease Manufacturing and Petroleum Refining

. EC97M-3241D and EC97M-3241A (2 reports). U.S. International Trade Commission (2007) Available online at <http://dataweb.usitc.gov/>. November 7, 2007. U.S. International Trade Commission (2006) Available online at <http://dataweb.usitc.gov/>. September 27, 2006. Wood, A. (2003) “Compendium of Pesticide Common Names.” Available online at <http://www.alanwood.net/ pesticides/index.html>. 

# Stationary Combustion (excluding CO 2 

# ) EIA (2007a) “Supplemental Tables on Petroleum Product detail.” Monthly Energy Review , December 2007, Energy Information Administration, U.S. Department of Energy, Washington, DC. DOE/EIA-0035(2007/12). EIA (2007b) Annual Energy Review 2006 . Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0384(2006). June 2007. EPA (2004) NONROAD Model . Office of Transportation and Air Quality, U.S. Environmental Protection Agency. Available online at <http://www.epa.gov/otaq/ngm.htm>. EPA (2003) E-mail correspondence. Air pollutant data

. Office of Air Pollution to the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency (EPA). December 22, 2003. Grillot, M. (2007) Personal communication. U.S. Territories Fossil Fuel Consumption, 1990–2006 . Unpublished . U.S. Energy Information Administration. Washington, DC. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme. The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

. National Greenhouse Gas Inventories Programme, Intergovernmental Panel on Climate Change. Montreal. May 2000. IPCC-XVI/Doc. 10 (1.IV.2000). IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. SAIC/EIA (2001) Monte Carlo Simulations of Uncertainty in U.S. Greenhouse Gas Emission Estimates. Final Report

. Prepared by Science Applications International Corporation (SAIC) for Office of Integrated Analysis and Forecasting, Energy Information Administration , U.S. Department of Energy. Washington, DC. June 22, 2001. 

# Mobile Combustion (excluding CO 2 

# ) AAR (2007) Railroad Facts, 2007 Ed. Policy and Economics Department, Association of American Railroads, Washington, DC. ANL (2006) Argonne National Laboratory (2006) GREET Model Version 1.7. June 2006. APTA (2007) Public Transportation Fact Book . American Public Transportation Association, Washington, DC. Available online at <http://www.apta.com/research/stats/ factbook/index.cfm>. APTA (2006) Commuter Rail National Totals . American Public Transportation Association, Washington, DC. Available online at <http://www.apta.com/research/stats/ rail/crsum.cfm>. Benson, D. (2002 through 2004) Personal communication. Unpublished data developed by the Upper Great Plains Transportation Institute, North Dakota State University and American Short Line & Regional Railroad Association.

### 11-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 BEA (1991 through 2005) Unpublished BE-36 Survey Data. Bureau of Economic Analysis (BEA), U.S. Department of Commerce. Browning, L. (2005) ICF International internal analysis by Lou Browning, Emission control technologies for diesel highway vehicles specialist. Browning, L. (2003) “VMT Projections for Alternative Fueled and Advanced Technology Vehicles through 2025.” 13 th 

### CRC On-Road Vehicle Emissions Workshop. April 2003. DHS (2008). Personal communication. Elissa Kay, Residual and Distillate Fuel Oil Consumption (International Bunker Fuels). Department of Homeland Security, Bunker Report. January 11, 2008. DESC (2007) Unpublished data from the Defense Fuels Automated Management System (DFAMS). Defense Energy Support Center, Defense Logistics Agency, U.S. Department of Defense. DOC (1991 through 2007) Unpublished Report of Bunker Fuel Oil Laden on Vessels Cleared for Foreign Countries

. Form-563, Foreign Trade Division, Bureau of the Census, U.S. Department of Commerce. DOE (1993 through 2007) Transportation Energy Data Book . Office of Transportation Technologies, Center for Transportation Analysis, Energy Division, Oak Ridge National Laboratory. ORNL-5198. DOT (1991 through 2007) Fuel Cost and Consumption

. Federal Aviation Administration, U.S. Department of Transportation, Bureau of Transportation Statistics, Washington, DC. DAI-10. EIA (2007a) “Supplemental Tables on Petroleum Product detail.” Monthly Energy Review, December 2007 , Energy Information Administration, U.S. Department of Energy, Washington, DC. DOE/EIA-0035(2007/12). EIA (2007b) International Energy Annual . World Petroleum Supply and Disposition, Table 3.1. Available online at <http:// www.eia.doe.gov/iea/pet.html>. EIA (2007c) Annual Energy Review 2006 . Energy Information Administration, U.S. Department of Energy, Washington, DC. July 2006. DOE/EIA-0384(2005). EIA (2007d) Natural Gas Annual 2006 . Energy Information Administration, U.S. Department of Energy, Washington, DC. DOE/EIA-0131(06). EIA (2002) Alternative Fuels Data Tables . Energy Information Administration, U.S. Department of Energy, Washington, DC. Available online at <http://www.eia.doe. gov/fuelrenewable.html>. EIA (1991 through 2007) Fuel Oil and Kerosene Sales

. Energy Information Administration, U.S. Department of Energy, Washington, DC. DOE/EIA-0535-annual. EPA (2008) Air Emissions Trends—Continued Progress Through 2006 . U.S. Environmental Protection Agency, Washington, DC. December 19, 2006. Available online at <http://www.epa.gov/air/airtrends/index.html>. EPA (2007a) Annual Certification Test Results Report. Office of Transportation and Air Quality, U.S. Environmental Protection Agency. Available online at <http://www.epa. gov/otaq/crttst.htm>. EPA (2007b) Confidential engine family sales data submitted to EPA by manufacturers. Office of Transportation and Air Quality, U.S. Environmental Protection Agency. EPA (2007c) Motor Vehicle Emission Simulator (MOVES). Office of Transportation and Air Quality, U.S. Environmental Protection Agency. Available online at <http://www.epa.gov/ otaq/ngm.htm>. EPA (2006a) NONROAD Model . Office of Transportation and Air Quality, U.S. Environmental Protection Agency. Available online at <http://www.epa.gov/otaq/nonrdmdl. htm>. EPA (2005) National Emissions Inventory Air Pollutant Emissions Trends Data. Available online at <http://www. epa.gov/ttn/chief/trends/index.html#tables>. EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between the Office of Air Pollution and the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency (EPA). December 22, 2003. EPA (2000) Mobile6 Vehicle Emission Modeling Software

. Office of Mobile Sources, U.S. Environmental Protection Agency, Ann Arbor, Michigan. EPA (1999a) Emission Facts: The History of Reducing Tailpipe Emissions . Office of Mobile Sources. May 1999. EPA 420-F-99-017. Available online at <http://www.epa. gov/oms/consumer/f99017.pdf>. EPA (1999b) Regulatory Announcement: EPA’s Program for Cleaner Vehicles and Cleaner Gasoline. Office of Mobile Sources. December 1999. EPA420-F-99-051. Available online at <http://www.epa.gov/otaq/regs/ld-hwy/tier-2/frm/ f99051.pdf>. EPA (1998) Emissions of Nitrous Oxide from Highway Mobile Sources: Comments on the Draft Inventory of U.S. Greenhouse Gas Emissions and Sinks, 1990–1996 . Office of Mobile Sources, Assessment and Modeling Division, U.S. Environmental Protection Agency. August 1998. EPA420- R-98-009. EPA (1997) Mobile Source Emission Factor Model (MOBILE5a) . Office of Mobile Sources, U.S. Environmental Protection Agency, Ann Arbor, Michigan. EPA (1994a) Automobile Emissions: An Overview

.Office of Mobile Sources. August 1994. EPA 400-F92-007. Available online at <http://www.epa.gov/otaq/ consumer/05-autos.pdf>.

### References 11-9 EPA (1994b) Milestones in Auto Emissions Control . Office of Mobile Sources. August 1994. EPA 400-F-92-014. Available online at <http://www.epa.gov/otaq/consumer/12-miles. pdf>. EPA (1993) Automobiles and Carbon Monoxide . Office of Mobile Sources. January 1993. EPA 400-F-92-005. Available online at <http://www.epa.gov/otaq/consumer/03-co.pdf>. Esser, C. (2003 through 2004) Personal Communication with Charles Esser, Residual and Distillate Fuel Oil Consumption for Vessel Bunkering (Both International and Domestic) for American Samoa, U.S. Pacific Islands, and Wake Island. FAA (2007). Table 30 “General Aviation Aircraft Fuel Consumption,” FAA Aerospace Forecasts Fiscal Years 2007–2020 . Federal Aviation Administration. Available online at <http://www.faa.gov/data_statistics/aviation/ aerospace_forecasts/2007-2020/media/FORECAST%20 BOOK%20SM.pdf/>. FAA (2006) Email correspondence containing aviation emissions estimates from the System for Assessing Aviation’s Global Emissions (SAGE). August 2006. FHWA (1996 through 2007) Highway Statistics . Federal Highway Administration, U.S. Department of Transportation, Washington, DC. Report FHWA-PL-96-023-annual. Available online at <http://www.fhwa.dot.gov/policy/ohpi/ hss/hsspubs.htm>. Gaffney, J. (2007) Email communication. John Gaffney, American Public Transportation Association and Joe Aamidor, ICF International. December 17, 2007. ICF (2006a) Revisions to Alternative Fuel Vehicle (AFV) Emission Factors for the U.S. Greenhouse Gas Inventory

. Memorandum from ICF International to John Davies, Office of Transportation and Air Quality, U.S. Environmental Protection Agency. November 2006. ICF (2006b) Revised Gasoline Vehicle EFs for LEV and Tier 2 Emission Levels . Memorandum from ICF International to John Davies, Office of Transportation and Air Quality, U.S. Environmental Protection Agency. November 2006. ICF (2004) Update of Methane and Nitrous Oxide Emission Factors for On-Highway Vehicles . Final Report to U.S. Environmental Protection Agency. February 2004. IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency, Paris, France. Lipman, T. and M. Delucchi (2002) “Emissions of Nitrous Oxide and Methane from Conventional and Alternative Fuel Motor Vehicles.” Climate Change , 53:477–516. Lou, J. (2008) Email Communication. Joel Lou, Energy Information Administration, U.S. Department of Energy and Aaron Beaudette, ICF International. January 3, 2008. Unnasch, S., L. Browning, and E. Kassoy (2001) Refinement of Selected Fuel-Cycle Emissions Analyses. Final Report to ARB. U.S. Census Bureau (2000) V ehicle Inventory and Use Survey . U.S. Census Bureau, Washington, DC. Database CD-EC97-VIUS. Whorton, D. (2006 through 2007) Email communication. David Whorton, American Short Line and Regional Railroad Association Aaron Beaudette, ICF International. December 11, 2007. 

# Coal Mining AAPG (1984) Coalbed Methane Resources of the United States . AAPG Studies in Geology Series #17. DOE (1983) Methane Recovery from Coalbeds: A Potential Energy Source . U.S. Department of Energy. DOE/METC/ 83-76. EIA (2006) Annual Coal Report 1991–2005 (Formerly called Coal Industry Annual ). Table 3. Energy Information Administration, U.S. Department of Energy, Washington, DC. EPA (1996) Evaluation and Analysis of Gas Content and Coal Properties of Major Coal Bearing Regions of the United States . U.S. Environmental Protection Agency. EPA/600/R96-065. GRI (1988) A Geologic Assessment of Natural Gas from Coal Seams . Topical Reports, Gas Research Institute 1986–88. Mutmansky, Jan M. and Yanebi Wang (2000) “Analysis of Potential Errors in Determination of Coal Mine Annual Methane Emissions.” Mineral Resources Engineering , 9(4). December 2000. USBM (1986) Results of the Direct Method Determination of the Gas Contents of U.S. Coal Basins . Circular 9067, U.S. Bureau of Mines. 

# Abandoned Underground Coal Mines EPA (2003) Methane Emissions Estimates & Methodology for Abandoned Coal Mines in the U.S. U.S. Environmental Protection Agency. Draft Final Report. Washington, DC. June 2003. Mutmansky, Jan M., and Yanbei Wang (2000) Analysis of Potential Errors in Determination of Coal Mine Annual Methane Emissions . Department of Energy and GeoEnvironmental Engineering, Pennsylvania State University. University Park, PA. U.S. Department of Labor, Mine Health & Safety Administration (2007) Data Retrieval System . Available online at <http://www.msha.gov/drs/drshome.htm>.

### 11-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 

# Natural Gas Systems AAPG (2004) Shale Gas Exciting Again. American Association of Petroleum Geologists. Available online at <http://www.aapg.org/explorer/2001/03mar/gas_shales. html>. AGA (1991 through 1998) Gas Facts . American Gas Association. Washington, DC. API (2005) “Table 12—Section III—Producing Oil Wells in the United States by State.” In Basic Petroleum Data Book

. American Petroleum Institute, Volume XXV, Number 1. February 2005. Alabama (2007) “Alabama State Oil and Gas Board.” Available online at <http://www.ogb.state.al.us>. Brookhaven (2004) Natural Gas Field Subject of Interest at Brookhaven College . Brookhaven College. Available online at <http://www.brookhavencollege.edu/news/2004/ news1752.html>. EIA (2007a) Number of Producing Gas and Gas Condensate Wells , 1989–2005, Natural Gas Navigator. Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://tonto.eia.doe.gov/dnav/ng/ ng_prod_wells_s1_a.htm>. EIA (2007b) “Table 1—Supply and Disposition of Dry Natural Gas in the United States 1999–2006.” Natural Gas Monthly , Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe.gov>. EIA (2007c) “Table 2—Natural Gas Consumption in the United States.” Natural Gas Monthly , Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe.gov>. EIA (2007d) “Table 5.2.” Monthly Energy Review . Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe. gov/emeu/mer/resource.html>. EIA (2007e) “Table 6—Marketed Production of Natural Gas by State.” Natural Gas Monthly , Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe.gov>. EIA (2007f) U.S. Imports by Country . Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://tonto.eia.doe.gov/dnav/ng/ ng_move_top.asp>. EIA (2005) “Table 5—U.S. Crude Oil, Natural Gas, and Natural Gas Liquids Reserves, 1977–2003.” Energy Information Administration, Department of Energy. Washington, DC. EIA (2004) US LNG Markets and Uses . Energy Information Administration, U.S. Department of Energy. Washington, DC. June 2004. Available online at <http://www.eia.doe. gov/pub/oil_gas/natural_gas/ feature_articles/2004/lng/ lng2004.pdf>. EIA (2001) “Documentation of the Oil and Gas Supply Module (OGSM).” Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://tonto.eia.doe.gov/FTPROOT/modeldoc/ m063(2001).pdf>. EIA (1996) “Emissions of Greenhouse Gases in the United States” Carbon Dioxide Emissions . Energy Information Administration, U.S. Department of Energy, Washington, DC. EPA (2007) Natural Gas STAR Reductions 1990–2006

. Natural Gas STAR Program. EPA (1999) Estimates of Methane Emissions from the U.S. Oil Industry (Draft Report) . Prepared by ICF-Kaiser, Office of Air and Radiation, U.S. Environmental Protection Agency. October 1999. EPA/GRI (1996) Methane Emissions from the Natural Gas Industry . Harrison, M., T. Shires, J. Wessels, and R. Cowgill, (eds.). Radian International LLC for National Risk Management Research Laboratory, Air Pollution Preventionand Control Division, Research Triangle Park, NC. EPA600/R-96-080a. GTI (2001) Gas Resource Database: Unconventional Natural Gas and Gas Composition Databases . Second Edition. GRI-01/0136. IPCC (2007) 2007 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, Intergovernmental Panel on Climate Change. H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe, (eds.). Hayama, Kanagawa, Japan. Kansas (2007) “Oil and Gas Production Data, All Wells.” Kansas Geological Survey . University of Kansas. Available online at <http://www.kgs.ku.edu/PRS/petroDB.html>. Lippman (2003) Rocky Mountain Region Second Quarter 2003 Production Report . Lippman Consulting, Inc. MMS (2007a) Gulf of Mexico Region Offshore Information

. Minerals Management Service, U.S. Department of the Interior. Available online at <http://www.gomr.mms.gov/ homepg/offshore/fldresv/resvmenu.html>. MMS (2007b) Gulf of Mexico Region Products/Free Data

. Minerals Management Service, U.S. Department of the Interior. Available online at <http://www.gomr.mms.gov/ homepg/pubinfo/freeasci/platform/freeplat.html>. MMS (2007c) Gulfwide Emission Inventory Study for the Regional Haze and Ozone Modeling Effort . OCS Study MMS 2004-072. MMS (2007d) OCS Platform Activity . Minerals Management Service, U.S. Department of the Interior. Available online at <http://www.mms.gov/stats>. MMS (2007e) Pacific OCS Region . Minerals Management Service, U.S. Department of the Interior. Available online at <http://www.gomr.mms.gov/homepg/pubinfo/ pacificfreeasci/platform/pacificfreeplat.html>.

### References 11-11 Montana (2007) Montana Online Oil and Gas Information System . Montana Board of Oil and Gas Conservation, Billing Office. Available online at <http://bogc.dnrc.state.mt.us/ jdpIntro.htm>.Morgan Stanley (2005) “Barnett Shale Update: NoneCore Confidence Rises.” Available online at <http:// www.endevcoinc.com/technical%20papers/Morgan%20 Stanley%20Outlook%20on%20Barnett%20 Shale.pdf>. New Mexico (2007a) “Annual Gas Well Counts by State District.” Available online at <http://www.emnrd.state. nm.us/emnrd/ocd/>. New Mexico (2007b) “Districts.” Available online at <http:// www.emnrd.state.nm.us/ocd/districts.htm>. OGJ (1997–2007) “Worldwide Gas Processing.” Oil & Gas Journal , PennWell Corporation, Tulsa, OK. Oklahoma (2007) Oklahoma Petroleum Information Center—Coalbed-Methane Completions database . Oklahoma Geological Survey. Available online at <http://www.ogs. ou.edu/OPIC/>. OPS (2007a) Natural Gas Transmission Pipeline Annual Mileage . Office of Pipeline Safety, U.S. Department of Transportation. Washington, DC. Available online at <http:// ops.dot.gov/stats/stats.htm>. OPS (2007b) Distribution Annuals Data . Office of Pipeline Safety, U.S. Department of Transportation. Washington, DC. Available online at <http://ops.dot.gov/stats/DT98.htm>. Texas (2007a) Gas Well Counts by County . Texas Railroad Commission. Available online at <http://www.rrc.state.tx.us/ divisions/og/statistics/wells/oggwlct.pdf>. Texas (2007b) Oil Well Counts by County . Texas Railroad Commission. Available online at <http://www.rrc.state.tx.us/ divisions/og/statistics/wells/ogowlct.pdf>. Texas (2007c) The Barnett Shale Regional Report . Brad Foster, Devon Energy, Texas Railroad Commission. Available online at <http://www.findarticles.com/p/articles/ mi_qn4182/is_20050620/ai_n14675582>. Texas (2007d) Oil and Gas District Boundaries . Texas Railroad Commission. Available online at <http://www.rrc. state.tx.us/divisions/og/ogmap.html>. Utah (2007) Oil and Gas Data Download . Utah Division of Oil, Gas and Mining, Department of Natural Resources. Available online at <http://ogm.utah.gov/oilgas/DOWNLOAD/ downpage.htm>. World Oil Magazine (2007a) “Outlook 2007: Producing Gas Wells.” 228(2). February 2007. Available online at <http:// www.worldoil.com/magazine/MAGAZINE_DETAIL. asp?ART_ID=3115&MONTH_YEAR=Feb-2007>. World Oil Magazine (2007b) “Outlook 2007: Producing Oil Wells.” 228(2). February 2007. Available online at <http:// www.worldoil.com/magazine/MAGAZINE_DETAIL. asp?ART_ID=3114&MONTH_YEAR=Feb-2007>. Wyoming (2007) “Wyoming Oil and Gas Conservation Commission.” Available online at <http://wogcc.state.wy.us/ coalbedchart.cfm>. 

# Petroleum Systems EIA (1990 through 2006) Petroleum Supply Annual 1990– 2005 Volume 1 . Energy Information Administration, U.S. Department of Energy. Washington, DC. EIA (1990 through 2007) Refinery Capacity Report . Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe. gov/oil_gas/petroleum/data_publications/refinery_capacity_ data/refcapacity.html>. EIA (1995 through 2007a) Annual Energy Review . Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe. gov/emeu/aer/contents.html>. EIA (1995 through 2007b) Monthly Energy Review . Energy Information Administration, U.S. Department of Energy. Washington, DC. Available online at <http://www.eia.doe. gov/emeu/mer>. EPA (2005) Incorporating the Mineral Management Service Gulfwide Offshore Activities Data System (GOADS) 2000 data into the methane emissions inventories . Prepared by ICF International. U.S. Environmental Protection Agency. 2005. EPA (1999) Estimates of Methane Emissions from the U.S. Oil Industry (Draft Report) . Prepared by ICF International. Office of Air and Radiation, U.S. Environmental Protection Agency. October 1999. EPA (1996) Methane Emissions from the U.S. Petroleum Industry (Draft) . Prepared by Radian. U.S. Environmental Protection Agency. June 1996. EPA (1995) Compilation of Air Pollutant Emission Factors AP-42, Fifth Edition, Volume I: Stationary Point and Area Sources . U.S. Environmental Protection Agency. Available online at <http://www.epa.gov/ttn/chief/ap42/index.html>. EPA/GRI (1996a) Methane Emissions from the Natural Gas Industry, V7: Blow and Purge Activities . Prepared by Radian. U.S. Environmental Protection Agency. April 1996. EPA/GRI (1996b) Methane Emissions from the Natural Gas Industry, V11: Compressor Driver Exhaust . Prepared by Radian. U.S. Environmental Protection Agency. April 1996. EPA/GRI (1996c) Methane Emissions from the Natural Gas Industry, V12: Pneumatic Devices . Prepared by Radian. U.S. Environmental Protection Agency. April 1996. EPA/GRI (1996d) Methane Emissions from the Natural Gas Industry, V13: Chemical Injection Pumps . Prepared by Radian. U.S. Environmental Protection Agency. April 1996.

### 11-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 IOGCC (2007) Marginal Wells: Fuel for Economic Growth 2006 Report . Interstate Oil & Gas Compact Commission. Available online at <http://www.iogcc.state.ok.us/news_ pubs.aspx>. MMS (2001) Field and Reserve Information . Minerals Management Service, U.S. Department of the Interior. Available online at <http://www.gomr.mms.gov/homepg/ offshore/fldresv/resvmenu.html>. MMS (2004). Gulfwide Emission Inventory Study for the Regional Haze and Ozone Modeling Effort . OCS Study MMS 2004-072. MMS (2007a) OCS Platform Activity . Minerals Management Service, U.S. Department of the Interior. Available online at <http://www.mms.gov/stats>. MMS (2007b) Platform Information and Data . Minerals Management Service, U.S. Department of the Interior. Available online at <http://www.gomr.mms.gov/homepg/ pubinfo/freeasci/platform/freeplat.html>. MMS (2007c) Pacific OCS Region . Minerals Management Service, U.S. Department of the Interior. Available online at <http://www.gomr.mms.gov/homepg/pubinfo/ pacificfreeasci/platform/pacificfreeplat.html>. OGJ (2007a) Oil & Gas Journal 1990–2007. Pipeline Economics Issue. September 2007. OGJ (2007b) Oil & Gas Journal1990–2007. Worldwide Refining Issue. January 1, 2007. United States Army Corps of Engineers (1995–2005) Waterborne Commerce of the United States, Part 5: National Summaries . U.S. Army Corps of Engineers. Washington, DC. 

# Municipal Solid Waste Combustion De Soete, G.G. (1993) “Nitrous Oxide from Combustion and Industry: Chemistry, Emissions and Control.” In A. R. Van Amstel, (ed) Proc. of the International Workshop Methane and Nitrous Oxide: Methods in National Emission Inventories and Options for Control , Amersfoort, NL. February 3–5, 1993. DeZan, D. (2000) Personal communication. Diane DeZan, Fiber Economics Bureau and Joe Casola, ICF International. August 4, 2000. EPA (2007) Municipal Solid Waste in the United States: Facts and Figures for 2006 . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www. epa.gov/epaoswer/non-hw/muncpl/msw99.htm>. EPA (2006a) Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions and Sinks

. Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. EPA (2006b) Municipal Solid Waste in the United States: Facts and Figures for 2005 . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www. epa.gov/epaoswer/non-hw/muncpl/msw99.htm>. EPA (2005a) Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and Figures for 2003 . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency, Washington. DC. Available online at <http://www.epa.gov/epaoswer/non-hw/ muncpl/pubs/msw05rpt.pdf>. EPA (2003) Characterization of Municipal Solid Waste in the United States: 2001 Update (Draft) . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. EPA (2002) Characterization of Municipal Solid Waste in the United States: 2000 Update . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. EPA530-R-02-001. EPA (2000a) Characterization of Municipal Solid Waste in the United States: 1999 Update Fact Sheet (and Data Tables)

. Office of Solid Waste, U.S. Environmental Protection Agency. Washington, DC. EPA530-F-00-024. EPA (2000b) Characterization of Municipal Solid Waste in the United States: Source Data on the 1999 Update . Office of Solid Waste, U.S. Environmental Protection Agency. Washington, DC. EPA530-F-00-024. EPA (1996 through 1999) Characterization of Municipal Solid Waste in the United States . Office of Solid Waste, U.S. Environmental Protection Agency. Washington, DC. EPA (1995) Compilation of Air Pollutant Emission Factors, AP-42 . Fifth Edition, “Volume I: Stationary Point and Area Sources: Introduction.” Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. October 1995. FEB (2006) Fiber Economics Bureau, as cited in C&EN (2006) “Production: Growth in Most Regions,” Chemical & Engineering News , American Chemical Society. July 11, 2006. Available online at <http://www.cen-online.org>. Glenn, Jim (1999) “11 th 

### Annual BioCycle Nationwide Survey: The State of Garbage in America.” BioCycle . JG Press, Emmaus, PA. April 1999. Goldstein, N. and C. Madtes (2001) “13 th

### Annual BioCycle Nationwide Survey: The State of Garbage in America.” BioCycle . JG Press, Emmaus, PA. December 2001. Goldstein, N. and C. Madtes (2000) “12 th

### Annual BioCycle Nationwide Survey: The State of Garbage in America, Part I.” BioCycle , JG Press, Emmaus, PA. November 2000. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
., National Greenhouse Gas Inventories Programme, Intergovernmental Panel on Climate Change. Montreal. May 2000. IPCC-XVI/Doc. 10 (1.IV.2000).

### References 11-13 Kaufman, et al. (2004a) “14 th

### Annual BioCycle Nationwide Survey: The State of Garbage in America 2004” BioCycle

. JG Press, Emmaus, PA. January, 2004. Kaufman, et al. (2004b) “Corrections to State of Garbage 2004” BioCycle . JG Press, Emmaus, PA. April, 2004. Miller, T. (1999) Material Safety Data Sheet, Carbon Black

. Continental Carbon Company. September 1, 1999. Available online at <http://www.continentalcarbon.com/downloads/ MSDS.pdf>. October 10, 2003. RMA (2006) U.S. Scrap Tire Markets in the United States 2005 Edition . Rubber Manufacturers Association. Washington, DC. November 2006. Schneider, S. (2007) E-mail communication. Shelly Schneider, Franklin Associates, and Sarah Shapiro, ICF International. January 10, 2007. Simmons, et al. (2006) “15 th

### Nationwide Survey of Municipal Solid Waste Management in the United States: The State of Garbage in America” BioCycle . JG Press, Emmaus, PA. April 2006. STMC (2003, 2006) Scrap Tire Facts and Figures . Scrap Tire Management Council of the Rubber Manufacturers Association. Washington, DC. Available online at <http:// www.rma.org/scrap_tires/scrap_tire_markets/facts_and_ figures/> and <http://www.rma.org/scrap_tires/scrap_tire_ markets/scrap_tire_characteristics/>. STMC (2001, 2002) Scrap Tire Facts and Figures . Scrap Tire Management Council of the Rubber Manufacturers Association. Washington, DC. Available online at <http:// www.rma.org/scraptires/facts_figures.html>. STMC (2000) Scrap Tire Facts and Figures . Scrap Tire Management Council of the Rubber Manufacturers Association. Washington, DC. Available online at <http:// www.rma.org/scrapfctn.html>. July 26, 2000. 

# Energy Sources of Indirect Greenhouse Gas Emissions EPA (2008) Air Emissions Trends—Continued Progress Through 2006 . U.S. Environmental Protection Agency, Washington, DC. December 19, 2006.Available online at <http://www.epa.gov/air/airtrends/index.html>. EPA (2003) E-mail correspondence. Air pollutant data. Office of Air Pollution to the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency (EPA). December 22, 2003. EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42 . Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. October 1997. 

# International Bunker Fuels ASTM (1989) Military Specification for Turbine Fuels, Aviation, Kerosene Types . NATO F-34 (JP-8) and NATO F-35. February 10, 1989. Available online at <http://test. wbdg.org/ccb/FEDMIL/t_83133d.pdf>. BEA (1991 through 2007) Unpublished BE-36 survey data. Bureau of Economic Analysis (BEA), U.S. Department of Commerce. Washington, DC. Chevron (2000) Aviation Fuels Technical Review (FTR-3)

. Chevron Products Company, Chapter 2. Available online at <http://www.chevron.com/products/prodserv/fuels/bulletin/ aviationfuel/2_at_fuel_perf.shtm>. DESC (2007) Unpublished data from the Defense Fuels Automated Management System (DFAMS). Defense Energy Support Center, Defense Logistics Agency, U.S. Department of Defense. Washington, DC. DOC (1991 through 2007) Unpublished Report of Bunker Fuel Oil Laden on Vessels Cleared for Foreign Countries. Form-563. Foreign Trade Division, Bureau of the Census, U.S. Department of Commerce. Washington, DC. DOT (1991 through 2007) Fuel Cost and Consumption

. Airline Information, Bureau of Transportation Statistics, U.S. Department of Transportation. Washington, DC. EIA (2007) “Supplemental Tables on Petroleum Product detail.” Monthly Energy Review, December 2007 , Energy Information Administration, U.S. Department of Energy, Washington, DC. DOE/EIA-0035(2007/12). IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. USAF (1998) Fuel Logistics Planning . U.S. Air Force pamphlet AFPAM23-221, May 1,1998. 

# Wood Biomass and Ethanol Consumption EIA (2007) Annual Energy Review 2006 . Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0384(2006). June 2007. IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France.

### 11-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 Lindstrom, P. (2006) Personal communication. Perry Lindstrom, Energy Information Administration and Jean Kim, ICF International.


# Industrial Processes

Cement Production IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. USGS (1999 through 2006) Minerals Yearbook: Cement Annual Report . U.S. Geological Survey, Reston, VA. USGS (1998) Mineral Industrial Survey: Cement 1997 . U.S. Geological Survey, Reston, VA. USGS (1997) Mineral Industrial Survey: Cement 1996 . U.S. Geological Survey, Reston, VA. USGS (1993 through 1996) Minerals Yearbook: Cement Annual Report . U.S. Geological Survey, Reston, VA. van Oss (2007) Personal communication. Hendrik van Oss, Commodity Specialist of the U.S. Geological Survey and Tristan Kessler, ICF International. October 2, 2007. van Oss (2008) Personal communication. Hendrik van Oss, Commodity Specialist of the U.S. Geological Survey and Chris Steuer, ICF International. February 7, 2008.



# Lime Production IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

. National Greenhouse Gas Inventories Programme, Intergovernmental Panel on Climate Change. Montreal. May 2000. IPCC-XVI/Doc. 10 (1.IV.2000). Males, E. (2003) Memorandum from Eric Males, National Lime Association to Mr. William N. Irving & Mr. Leif Hockstad, Environmental Protection Agency. March 6, 2003. USGS (1992 through 2007) Minerals Yearbook: Lime Annual Report . U.S. Geological Survey, Reston, VA. 

# Limestone and Dolomite Use USGS (1995 through 2007a) Minerals Yearbook: Crushed Stone Annual Report . U.S. Geological Survey, Reston, VA. USGS (1995 through 2007b) Minerals Yearbook: Magnesium Annual Report . U.S. Geological Survey, Reston, VA. USGS (1993) Minerals Yearbook: Crushed Stone Annual Report 1991 . U.S. Geological Survey, Reston, VA.


# Soda Ash Production and Consumption

IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. USGS (1994 through 2007) Minerals Yearbook: Soda Ash Annual Report . U.S. Geological Survey, Reston, VA.



# Ammonia Production and Urea Consumption Bark (2004) Coffeyville Nitrogen Plant. Available online at <http://www.gasification.org/Docs/2003_Papers/07BARK. pdf>. December 15, 2004. Coffeyville Resources Nitrogen Fertilizers, LLC (2005 through 2007) Business Data . Available online at <http:// www.coffeyvillegroup.com/businessSnapshot.asp>. EEA (2004) Natural Gas Issues for the U.S. Industrial and Power Generation Sectors . Submitted to National Commission on Energy Policy. EFMA (1995) Production of Ammonia . European Fertilizer Manufacturers Association. March 1, 1995. EIA (2001) Manufacturing Energy Consumption Survey (MECS) 1998 . U.S. Department of Energy, Energy Information Administration. Washington, DC. Available online at <http://www.eia.doe.gov/emeu/mecs/mecs98/ datatables/contents.html>. EIA (1994) Manufacturing Energy Consumption Survey (MECS) 1991 . U.S. Department of Energy, Energy Information Administration. Washington, DC. December 1994. DOE/EIA-0512(91). IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. TFI (2002) U.S. Nitrogen Imports/Exports Table . The Fertilizer Institute. Available online at <http://www.tfi.org/ statistics/usnexim.asp>. August 2002.

### References 11-15 TIG (2002) Chemical Profiles—Urea . The Innovation Group. Available online at <http://www.the-innovation-group.com/ ChemProfiles/Urea.htm>. September 2007. U.S. Census Bureau (2007) Current Industrial Reports Fertilizer Materials and Related Products: 2006 Summary

. Available online at <http://www.census.gov/industry/1/ mq325b065.pdf>. U.S. Census Bureau (2006) Current Industrial Reports Fertilizer Materials and Related Products: 2005 Summary

. Available online at <http://www.census.gov/cir/www/325/ mq325b.html>. U.S. Census Bureau (2002, 2004, 2005) Current Industrial Reports Fertilizer Materials and Related Products: Fourth Quarter Report Summary . Available online at <http://www. census.gov/cir/www/325/mq325b.html>. U.S. Census Bureau (1998 through 2002b, 2003) Current Industrial Reports Fertilizer Materials and Related Products: Annual Reports Summary . Available online at <http://www. census.gov/cir/www/325/mq325b.html>. U.S. Census Bureau (2002a) Current Industrial Reports Fertilizer Materials and Related Products: First Quarter 2002 . Available online at <http://www.census.gov/cir/ www/325/mq325b.html>. June 2002. U.S. Census Bureau (2002c) Current Industrial Reports Fertilizer Materials and Related Products: Third Quarter 2001 . Available online at <http://www.census.gov/cir/ www/325/mq325b.html>. January 2002. U.S. Census Bureau (2001a) Current Industrial Reports Fertilizer Materials and Related Products: Second Quarter 2001 . Available online at <http://www.census.gov/cir/ www/325/mq325b.html>. September 2001. U.S. Census Bureau (1991 through 1994) Current Industrial Reports Fertilizer Materials Annual Report . Report No. MQ28B. U.S. Census Bureau, Washington, DC. U.S. ITC (2002) United States International Trade Commission Interactive Tariff and Trade DataWeb , Version 2.5.0. Available online at <http://dataweb.usitc.gov/scripts/ user_set.aspH>. August 2002.



# Nitric Acid Production EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42 . Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. October 1997. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. U.S. Census Bureau (2007) “Table 1: Summary of Production of Principal Fertilizers and Related Chemicals.” Current Industrial Reports. Fertilizers and Related Chemicals: First Quarter 2007 . MQ325B(07)-1. Available online at <http:// www.census.gov/industry/1/mq325b071.pdf>. June, 2007. U.S. Census Bureau (2006) “Table 995: Inorganic Chemicals and Fertilizers.” Current Industrial Reports ., August, 2006. Series MAQ325A Available online at <http://www.census. gov/compendia/statab/tables/07s0995.xls>. Choe, J.S., P.J. Cook, and F.P. Petrocelli (1993) “Developing N 2 

### O Abatement Technology for the Nitric Acid Industry.” Prepared for presentation at the 1993 ANPSG Conference. Air Products and Chemicals, Inc., Allentown, PA. 

# Adipic Acid Production ACC (2003) “Adipic Acid Production.” Table 3.12— Production of the Top 100 Chemicals. American Chemistry Council Guide to the Business of Chemistry . August 2003. C&EN (1995) “Production of Top 50 Chemicals Increased Substantially in 1994.” Chemical & Engineering News
, 73(15):17. April 10, 1995. C&EN (1994) “Top 50 Chemicals Production Rose Modestly Last Year.” Chemical & Engineering News , 72(15):13. April 11, 1994. C&EN (1993) “Top 50 Chemicals Production Recovered Last Year.” Chemical & Engineering News , 71(15):11. April 12, 1993. C&EN (1992) “Production of Top 50 Chemicals Stagnates in 1991.” Chemical & Engineering News , 70(15): 17. April 13, 1992. Childs, D. (2003) Personal communication. Dave Childs, DuPont, USA and Duncan Rotherham, ICF International. August 7, 2003. Childs, D. (2002) Personal communication. Dave Childs, DuPont, USA and Laxmi Palreddy, ICF, Consulting. August 8, 2002. CMR (2001) “Chemical Profile: Adipic Acid.” Chemical Market Reporter . July 16, 2001. CMR (1998) “Chemical Profile: Adipic Acid.” Chemical Market Reporter . June 15, 1998. CW (2007) “Product Focus: Adipic Acid.” Chemical Week

. August 1–8, 2007. CW (2005) “Product Focus: Adipic Acid.” Chemical Week

. May 4, 2005. CW (1999) “Product Focus: Adipic Acid/Adiponitrile.” Chemical Week , p. 31. March 10, 1999. ICIS (2007) “Adipic Acid.” ICIS Chemical Business Americas . July 9, 2007. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan.

### 11-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 Reimer, R. (1999) Personal communication. Ron Reimer, DuPont, USA and Heike Mainhardt, ICF International. May 19, 1999. Thiemens, M.H., and W.C. Trogler (1991) “Nylon production; an unknown source of atmospheric nitrous oxide.” Science, 251:932–934.



# Silicon Carbide Production Corathers, L. (2007) Personal communication. Lisa Corathers, Commodity Specialist, U.S. Geological Survey and Michael Obeiter, ICF International. September 2007. Corathers, L. (2006) Personal communication. Lisa Corathers, Commodity Specialist, U.S. Geological Survey and Erin Fraser, ICF International. October 2006. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe, eds.; Institute for Global Environmental Strategies (IGES). Hayama, Kanagawa, Japan. U.S. Census Bureau (2005 through 2007) U.S International Trade Commission (USITC) Trade DataWeb . Available online at <http://dataweb.usitc.gov/>. USGS (2006) Minerals Yearbook: Manufactured Abrasives Annual Report 2005 . U.S. Geological Survey, Reston, VA. USGS (1991a through 2005a) Minerals Yearbook: Manufactured Abrasives Annual Report 2004 . U.S. Geological Survey, Reston, VA. USGS (1991b through 2005b) Minerals Yearbook: Silicon Annual Report 2004 . U.S. Geological Survey, Reston, VA.



# Petrochemical Production ACC (2002, 2003, 2005 through 2007) Guide to the Business of Chemistry . American Chemistry Council. Arlington, VA. CMA (1999) U.S. Chemical Industry Statistical Handbook

. Chemical Manufacturer’s Association. Washington, DC. EIA (2004) Annual Energy Review 2003 . Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0384(2003). September 2004. EIA (2003) Emissions of Greenhouse Gases in the United States 2002 . Office of Integrated Analysis and Forecasting, Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE-EIA-0573(2002). February 2003. European IPPC Bureau (2004) Draft Reference Document on Best Available Techniques in the Large Volumen Inorganic Chemicals—Solid and Others Industry , Table 4.21. European Commission, 224. August 2004. IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. Johnson, G. L. (2007) Personal communication. Greg Johnson of Liskow & Lewis, on behalf of the International Carbon Black Association (ICBA) and Tristan Kessler, ICF International. November 2007. Johnson, G. L. (2006) Personal communication. Greg Johnson of Liskow & Lewis, on behalf of the International Carbon Black Association (ICBA) and Erin Fraser, ICF International. October 2006. Johnson, G. L. (2005) Personal communication. Greg Johnson of Liskow & Lewis, on behalf of the International Carbon Black Association (ICBA) and Erin Fraser, ICF International. October 2005. Johnson, G. L. (2003) Personal communication. Greg Johnson of Liskow & Lewis, on behalf of the International Carbon Black Association (ICBA) and Caren Mintz, ICF International November 2003. Othmer, K. (1992) Carbon ( Carbon Black), Vol. 4, 1045. Srivastava, Manoj, I.D. Singh, and Himmat Singh (1999) “Structural Characterization of Petroleum Based Feedstocks for Carbon Black Production,” Table-1. Petroleum Science and Technology, 17(1&2):67–80. The Innovation Group (2004) Carbon Black Plant Capacity

. Available online at <http://www.the-innovation-group.com/ ChemProfiles/Carbon%20Black.htm>. U.S. Census Bureau (2008) U.S International Trade Commission (USITC) Trade DataWeb . Available online at <http://dataweb.usitc.gov/>. January 2008. U.S. Census Bureau (2006) U.S International Trade Commission (USITC) Trade DataWeb . Available online at <http://dataweb.usitc.gov/>. Fall 2006. U.S. Census Bureau (2004) 2002 Economic Census: Manufacturing—Industry Series: Carbon Black Manufacturing . Department of Commerce. Washington, DC. EC02-311-325182. September 2004. U.S. Census Bureau (1999) 1997 Economic Census: Manufacturing—Industry Series: Carbon Black Manufacturing . Department of Commerce. Washington, DC. EC97M-3251F. August 1999.



# Titanium Dioxide Production Gambogi, J. (2002) Telephone communication. Joseph Gambogi, Commodity Specialist, U.S. Geological Survey and Philip Groth, ICF International. November 2002. Gambogi, J. (2007) Personal communication. Joseph Gambogi, Commodity Specialist, U.S. Geological Survey and Michael Obeiter, ICF International. October 2007.

### References 11-17 IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. Onder, H, and E.A. Bagdoyan (1993) Everything You’ve Always Wanted to Know about Petroleum Coke . Allis Mineral Systems. USGS (1991 through 2005) Mineral Yearbook: Titanium Annual Report . U.S. Geological Survey, Reston, VA. 

# Carbon Dioxide Consumption Allis, R. et al. (2000) Natural CO 2 

### Reservoirs on the Colorado Plateau and Southern Rocky Mountains: Candidates for CO 2 

### Sequestration . Utah Geological Survey and Utah Energy and Geoscience Institute. Salt Lake City, Utah. ARI (2007). Presented at “Modeling the Oil Transition-a DOE/EPA Workshop on the Economic and Environmental Implications of Global Energy Transitions.” CO 2 

### -EOR: An Enabling Bridge for the Oil Transition . Washington, DC. April 20–21, 2007. ARI (2006) Presented at “Modeling the Oil Transition-a DOE/EPA Workshop on the Economic and Environmental Implications of Global Energy Transitions.” CO 2 

### -EOR: An Enabling Bridge for the Oil Transition . Washington, DC. April 20–21, 2006. Denbury Resources Inc. (2002 through 2007) Annual Report, 2004, 6. 

# Phosphoric Acid Production EFMA (2000) “Production of Phosphoric Acid.” Best Available Techniques for Pollution Prevention and Control in the European Fertilizer Industry . Booklet 4 of 8. European Fertilizer Manufacturers Association. Available online at <http://www.efma.org/Publications/BAT%202000/Bat04/ section04.asp>. FIPR (2003) “Analyses of Some Phosphate Rocks.” Facsimile Gary Albarelli, the Florida Institute of Phosphate Research, Bartow, Florida, and Robert Lanza, ICF International. July 29, 2003. FIPR (2003a) Florida Institute of Phosphate Research. Personal communication. Mr. Michael Lloyd, Laboratory Manager, FIPR, Bartow, Florida, and Mr. Robert Lanza, ICF International. August 2003. USGS (1994 through 2002, 2004 through 2006) Minerals Yearbook. Phosphate Rock Annual Report . U.S. Geological Survey, Reston, VA. 

# Iron and Steel Production AISI (1995 through 2007) Annual Statistical Report
, American Iron and Steel Institute, Washington, DC. DOE (1997) Energy and Environmental Profile of the U.S. Aluminum Industry . Office of Industrial Technologies, U.S. Department of Energy. July 1997. EIA (2007) Quarterly Coal Report : January–March 2007
, Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0121. EIA (2006a) Quarterly Coal Report : January–March 2006
, Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0121. EIA (2006b) Emissions of Greenhouse Gases in the United States 2005 . Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0573 (2005). EIA (1998 through 2004a) Quarterly Coal Report : October– December , Energy Information Administration, U.S. Department of Energy. Washington, DC. DOE/EIA-0121. EIA (2004b) Emissions of Greenhouse Gases in the United States 2003 . Energy Information Administration, U.S. Department of Energy, Washington, DC. DOE/EIA-0573. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
., National Greenhouse Gas Inventories Programme, Intergovernmental Panel on Climate Change. Montreal. May 2000. IPCC-XVI/Doc. 10 (1.IV.2000). IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. IPCC/UNEP/OECD/IEA (1995) “Volume 3: Greenhouse Gas Inventory Reference Manual. Table 2-2.” IPCC Guidelines for National Greenhouse Gas Inventories . Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic Co-Operation and Development, International Energy Agency. IPCC WG1 Technical Support Unit, United Kingdom. Jorgenson J. (2007) Personal communication. John Jorgenson, Commodity Specialist, U.S. Geological Survey and Tristan Kessler, ICF International. October 2007. USAA (2004 through 2006) Primary Aluminum Statistics

. U.S. Aluminum Association, Washington, DC. January 2006.

### 11-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 U.S. Census Bureau (2007) U.S International Trade Commission (USITC) Trade Dataweb . Available online at <http://dataweb.usitc.gov/>. Accessed Fall 2007. USGS (2005a) Mineral Commodity Profiles—Iron and Steel. Open-File Report 2005-1254. U.S. Geological Survey, Reston, VA. USGS (1994 through 2004, 2005b) Minerals Yearbook: Iron Ore Report . U.S. Geological Survey, Reston, VA. 

# Ferroalloy Production Corathers, L. (2007) Personal communication. Lisa Corathers, Commodity Specialist, U.S. Geological Survey and Tristan Kessler, ICF International. November 6, 2007. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. Onder, H., and E.A. Bagdoyan (1993) Everything You’ve Always Wanted to Know about Petroleum Coke . Allis Mineral Systems. USGS (1991 through 2006) Minerals Yearbook: Silicon Annual Report . U.S. Geological Survey, Reston, VA.



# Aluminum Production Gariepy, B. and G. Dube (1992) “Treating Aluminum with Chlorine.” U.S. Patent 5,145,514. Issued September 8, 1992. IAI (2003) Aluminum Sector Greenhouse Gas Protocol: Greenhouse Gas Emissions Monitoring and Reporting by the Aluminum Industry , International Aluminum Institute, May 2003. Available at <http://www.world-aluminium.org/ environment/climate/ghg_protocol.pdf>. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
., National Greenhouse Gas Inventories Programme, Intergovernmental Panel on Climate Change. Montreal. May 2000. IPCC-XVI/Doc. 10 (1.IV.2000). Kantamaneni R. and D. Pape (2001) “2000 Aluminum Inventory—Uncertainty Analysis,” EPA Contract No. 68- W6-0029, Task Order 408. Memorandum to EPA from ICF International. October, 18, 2001. Ko, M.K.W., N.D. Sze, W.-C. Wang, G. Shia, A. Goldman, F.J. Murcray, D.G. Murcray, and C.P. Rinsland (1993) “Atmospheric Sulfur Hexafluoride: Sources, Sinks, and Greenhouse Warming.” Journal of Geophysical Research
, 98:10499–10507. MacNeal, J., T. Rack, and R. Corns (1990) “Process for Degassing Aluminum Melts with Sulfur Hexafluoride.” U.S. Patent 4,959,101. Issued September 25, 1990. Ten Eyck, N. and M. Lukens (1996) “Process for Treating Molten Aluminum with Chlorine Gas and Sulfur Hexafluoride to Remove Impurities.” U.S. Patent 5,536,296. Issued July 16, 1996. USAA (2004 through 2006) Primary Aluminum Statistics

. U.S. Aluminum Association, Washington, DC. USGS (2007) Email Communication Lee Bray, U.S. Geological Survey, Reston, VA. September 19, 2007. USGS (2006) Mineral Commodity Summaries . U.S. Geological Survey, Reston, VA. USGS (1995, 1998, 2000 through 2002) Minerals Yearbook: Aluminum Annual Report . U.S. Geological Survey, Reston, VA. Victor, D.G. and G.J. MacDonald (1998) “A Model for Estimating Future Emissions of Sulfur Hexafluoride and Perfluorcarbons.” Interim Report for the International Institute for Applied Systems Analysis (IIASA). July, 1998. Available online at <http://www.iiasa.ac.at/>. May 23, 2000. Zurecki, Z. (1996) “Effect of Atmosphere Composition on Homogenizing Al-Mg and Al-Li Alloys.” Gas Interactions in Nonferrous Metals Processing—Proceedings of the 1996 125 th 

### The Minerals, Metals & Materials Society (TMS) Annual Meeting , Anaheim, CA, 77–93. 

# Magnesium Production and Processing Bartos S., C. Laush, J. Scharfenberg, and R. Kantamaneni (2007) “Reducing greenhouse gas emissions from magnesium die casting,” Journal of Cleaner Production , 15: 979–987, March. Gjestland, H. and D. Magers (1996) “Practical Usage of Sulphur [Sulfur] Hexafluoride for Melt Protection in the Magnesium Die Casting Industry,” #13, 1996 Annual Conference Proceedings , International Magnesium Association. Ube City, Japan. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. NADCA (2007) Twarog, Daniel L. State of the Industry Report . Die Casting Industry Links, North American Die Casting Association, February. RAND (2002) RAND Environmental Science and Policy Center, “Production and Distribution of SF 6 

### by End-Use Applications” Katie D. Smythe. International Conference on SF 6 

### and the Environment: Emission Reduction Strategies

. San Diego, CA. November 21–22, 2002.

### References 11-19 USGS (2007a) Mineral Industry Surveys: Magnesium in the Second Quarter. U.S. Geological Survey, Reston, VA. Available online at <http://minerals.usgs.gov/minerals/pubs/ commodity/magnesium/ mis-2007q2-mgmet.pdf>. USGS (2002, 2003, 2005 through 2007b) Minerals Yearbook: Magnesium Annual Report . U.S. Geological Survey, Reston, VA. Available online at <http://minerals.usgs.gov/minerals/ pubs/commodity/magnesium/index.html#mis>.



# Zinc Production Queneau P.B., S.E. James, J.P. Downey, and G.M. Livelli (1998) Recycling Lead and Zinc in the United States . Zinc and Lead Processing. The Metallurgical Society of CIM. Recycling Today (2005) Horsehead Sales Complete

. Available at <http://www.recyclingtoday.com/news/news.as p?ID=5137&SubCatID=74&CatID=23>. January 5, 2005. Sjardin (2003) CO 2 

### Emission Factors for Non-Energy Use in the Non-Ferrous Metal, Ferroalloys and Inorganics Industry

. Copernicus Institute. Utrecht, The Netherlands. Stuart (2005) Personal communication. Eric Stuart, Steel Manufacturers Association and Christopher Steuer, ICF International. October 31, 2005. USGS (1994 through 2008) Minerals Yearbook: Zinc Annual Report . U.S. Geological Survey, Reston, VA. Viklund-White C. (2000) “The Use of LCA for the Environmental Evaluation of the Recycling of Galvanized Steel.” ISIJ International. Volume 40 No. 3: 292–299.



# Lead Production Dutrizac, J.E., V. Ramachandran, and J.A. Gonzalez (2000) Lead-Zinc 2000 . The Minerals, Metals, and Materials Society. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. Morris, D., F.R. Steward, and P. Evans (1983) Energy Efficiency of a Lead Smelter . Energy 8(5):337–349. Sjardin, M. (2003) CO 2 

### Emission Factors for Non-Energy Use in the Non-Ferrous Metal, Ferroalloys and Inorganics Industry . Copernicus Institute. Utrecht, The Netherlands. Smith, G. (2007) Personal communication. Gerald Smith, Commodity Specialist, USGS and Toby Krasney, ICF International. October 7, 2007. Ullman’s Encyclopedia of Industrial Chemistry: Fifth Edition (1997) Volume A5. John Wiley and Sons. USGS (1994 through 2006) Minerals Yearbook: Lead Annual Report . U.S. Geological Survey, Reston, VA. 

# HCFC-22 Production ARAP (2007) Electronic mail communication. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Deborah Ottinger, U.S. Environmental Protection Agency. October 2, 2007. ARAP (2006) Electronic mail communication. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Sally Rand, U.S. Environmental Protection Agency. July 11, 2006. ARAP (2005) Electronic mail communication. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Deborah Ottinger, U.S. Environmental Protection Agency. August 9, 2005. ARAP (2004) Electronic mail communication. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Deborah Ottinger, U.S. Environmental Protection Agency. June 3, 2004. ARAP (2003) Electronic mail communication. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Sally Rand, U.S. Environmental Protection Agency. August 18, 2003. ARAP (2002) Electronic mail communication. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Deborah Ottinger, U.S. Environmental Protection Agency. August 7, 2002. ARAP (2001) Electronic mail communication. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Deborah Ottinger, U.S. Environmental Protection Agency. August 6, 2001. ARAP (2000) Electronic mail communication. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Sally Rand, U.S. Environmental Protection Agency. August 13, 2000. ARAP (1999) Facsimile. Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy and Deborah Ottinger Schaefer, U.S. Environmental Protection Agency. September 23, 1999. ARAP (1997) Letter. Dave Stirpe, Director, Alliance for Responsible Atmospheric Policy and Elizabeth Dutrow, U.S. Environmental Protection Agency. December 23, 1997. Rand, S., M. Branscome, and D. Ottinger (1999) “Opportunities for the Reduction of HFC-23 Emissions from the Production of HCFC-22.” In: Proceedings from the Joint IPCC/TEAP Expert Meeting On Options for the Limitation of Emissions of HFCs and PFCs . Petten, The Netherlands, 26–28 May 1999. RTI (2008) “Verification of Emission Estimates of HFC-23 from the Production of HCFC-22: Emissions from 1990 through 2006.” Report prepared by RTI International for the Climate Change Division. March, 2008.

### 11-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 RTI (1997) “Verification of Emission Estimates of HFC-23 from the Production of HCFC-22: Emissions from 1990 through 1996.” Report prepared by Research Triangle Institute for the Cadmus Group. November 25, 1997; revised February 16, 1998. 

# Subsitution of Ozone Depleting Substances IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France.



# Semiconductor Manufacture Burton, C.S., and R, Beizaie (2001) “EPA’s PFC Emissions Model (PEVM) v. 2.14: Description and Documentation” prepared for Office of Global Programs, U. S. Environmental Protection Agency, Washington, DC. November 2001. Burton, C.S., and N. Kshetry (2007) “PFC Reduction/ Climate Partnership for the Semiconductor Industry: Trends in Emissions and Documentation,” Draft Report, prepared for Office of Atmospheric Programs, U. S. Environmental Protection Agency, Washington, DC. July 2007. Citigroup Smith Barney (2005) Global Supply/Demand Model for Semiconductors . March 2005. International Sematech (2006) “Guideline for Characterization of Semiconductor Process Equipment,” International Sematech, Technology Transfer # 06124825A-ENG, December 22, 2006. Note that this is an update to previousguideline, TT from International Sematech # 01104197AXFR, December 2001. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe, eds.; Institute for Global Environmental Strategies (IGES). Hayama, Kanagawa, Japan. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, NationalGreenhouse Gas Inventories Programme, Montreal, IPCCXVI/Doc. 10 (1.IV.2000). May 2000. ITRS (2007) International Technology Roadmap for Semiconductors: 2006 Update . January 2007. This and earlier editions and updates are available at <http://public. itrs.net.> Information about the number of interconnect layers for years 1990 - 2010 is contained in Burton and Beizaie, 2001. PEVM is updated using new editions and updates of the ITRS, which are published annually. Semiconductor Equipment and Materials Industry (2007) World Fab Watch, January 2006 Edition

. VLSI Research, Inc. (2007) Document 327028, V6.12.1- Worldwide Silicon Demand by Wafer Size, by Linewidth and by Device Type. January 2007. Available online at <http:// www.vlsiresearch.com>.



# Electrical Transmission and Distribution IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. O’Connell, P., F. Heil, J. Henriot, G. Mauthe, H. Morrison, L. Neimeyer, M. Pittroff, R. Probst, J.P. Tailebois (2002) SF 6 

### in the Electric Industry . Status 2000, Cigre. February 2002. RAND (2004) RAND Environmental Science and Policy Center. “Trends in SF6 Sales and End-Use Applications: 1961–2003.” Katie D. Smythe. International Conference on SF 6 

### and the Environment: Emission Reduction Strategies

. Scottsdale, AZ. December 1–3, 2004. UDI (2007) 2007 UDI Directory of Electric Power Producers and Distributors, 115 th 

### Edition , Platts. UDI (2004) 2004 UDI Directory of Electric Power Producers and Distributors, 112 th 

### Edition , Platts. UDI (2001) 2001 UDI Directory of Electric Power Producers and Distributors, 109 th 

### Edition , Platts.



# Industrial Sources of Indirect Greenhouse Gases EPA (2008) Air Emissions Trends—Continued Progress Through 2006 . U.S. Environmental Protection Agency, Washington, DC. December 19, 2006. Available online at <http://www.epa.gov/air/airtrends/index.html>. EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data. Office of Air Pollution and the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. December 22, 2003. EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42 . Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. October 1997.


# Solvent and Other Product Use

Nitrous Oxide from Product Uses CGA (2003) “CGA Nitrous Oxide Abuse Hotline: CGA/ NWSA Nitrous Oxide Fact Sheet.” Compressed Gas Association. November 3, 2003. CGA (2002) “CGA/NWSA Nitrous Oxide Fact Sheet.” Compressed Gas Association. March 25, 2002.

### References 11-21 Heydorn, B. (1997) “Nitrous Oxide—North America.” Chemical Economics Handbook . SRI Consulting. May 1997. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. Tupman, M. (2003) Personal communication. Martin Tupman, Airgas Nitrous Oxide and Daniel Lieberman, ICF International. August 8, 2003. Tupman, M. (2002) Personal communication. Martin Tupman of Airgas Nitrous Oxide and Laxmi Palreddy, ICF International. July 3, 2002.



# Solvent Use EPA (2008) Air Emissions Trends—Continued Progress Through 2006 . U.S. Environmental Protection Agency, Washington, DC. December 19, 2006. Available online at <http://www.epa.gov/air/airtrends/index.html>. EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data. Office of Air Pollution and the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. December 22, 2003. EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42 . Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. October 1997. 

# Agriculture

Enteric Fermentation Baldwin R.L. (1995) Modeling Ruminant Digestion and Metabolism . Chapman & Hall, London, UK. Crutzen, P.J., I. Aselmann, and W. Seiler (1986) “Methane Production by Domestic Animals, Wild Ruminants, Other Herbivores, Fauna, and Humans.” Tellus , 38B:271–284. Donovan, K. (1999) Personal Communication. Kacey Donovan, University of California at Davis and staff at ICF International. Donovan, K. and L. Baldwin (1999) “Results of the AAMOLLY model runs for the Enteric Fermentation Model.” University of California, Davis. Ellis J.L., Kebreab E., Odongo N.E., McBride B.W., Okine E.K. and France J. 2007. “Prediction of methane production from dairy and beef cattle.” J. Dairy Sci . 90:3456–3467. EPA (2000) Draft Enteric Fermentation Model Documentation

. Office of Air and Radiation, U.S. Environmental Protection Agency. Washington, DC. June 13, 2000. EPA (1993) Anthropogenic Methane Emissions in the United States: Estimates for 1990 . Report to Congress, Office of Air and Radiation, U.S. Environmental Protection Agency. Washington, DC. FAO (2007) FAOSTAT Statistical Database . Food and Agriculture Organization of the United Nations. Available online at <http://apps.fao.org>. Feedstuffs (1998) “Nutrient requirements for pregnant replacement heifers.” Feedstuffs , Reference Issue, p. 50. ICF (2006) Cattle Enteric Fermentation Model: Model Documentation . Prepared by ICF International for the Environmental Protection Agency. June 2006. ICF (2003) Uncertainty Analysis of 2001 Inventory Estimates of Methane Emissions from Livestock Enteric Fermentation in the U.S . Memorandum from ICF International to the Environmental Protection Agency. May 2003. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
., National Greenhouse Gas Inventories Programme, Intergovernmental Panel on Climate Change. Montreal. May 2000. IPCC-XVI/Doc. 10 (1.IV.2000). IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. Johnson, D. (2002) Personal Communication. Don Johnson, Colorado State University, Fort Collins, and ICF International. Johnson, D. (2000) Enteric Fermentation Model Progress and Changes . Comments prepared by Don Johnson of Colorado State University, Fort Collins, for ICF International. Johnson, D. (1999) Personal Communication. Don Johnson, Colorado State University, Fort Collins, and David Conneely, ICF International. Kebreab E., Mills J.A.N., Crompton L.A., Bannink A., Dijkstra J., Gerrits W.J.J. and France J. 2004. “An integrated mathematical model to evaluate nutrient partition in dairy cattle between animal and environment.” Anim. Feed Sci. Technol . 112:131–154. Lange, J. (2000) Personal Communication. Lee-Ann Tracy, ERG and John Lange, Agricultural Statistician, U.S. Department of Agriculture, National Agriculture Statistics Service. Washington, DC. May 8, 2000.

### 11-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 Mills J.A.N., Dijkstra J., Bannink A., Cammell S.B., Kebreab E. and France J. (2001) “A mechanistic model of whole-tract digestion and methanogenesis in the lactating dairy cow: model development, evaluation, and application.” J. Anim. Sci . 79: 1584–1597. Molly (2007) Version 3.0 available from <http:// animalscience.ucdavis.edu/research/molly/>. NRC (2000) Nutrient Requirements of Beef Cattle: Seventh Revised Edition: Update 2000 . Table 11-1, Appendix Table 1. National Research Council. NRC (1999) 1996 Beef NRC : Appendix Table 22. National Research Council. USDA (2007) Quick Stats: Agricultural Statistics Database

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http:// www.nass.usda.gov/QuickStats/>. July 20, 2007. USDA (1996) Beef Cow/Calf Health and Productivity Audit (CHAPA): Forage Analyses from Cow/Calf Herds in 18 States . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. March 1996. Available online at <http://www.aphis.usda.gov/vs/ceah/ cahm>. USDA:APHIS:VS (2002) Reference of 2002 Dairy Management Practices . National Animal Health Monitoring System. Fort Collins, CO. Available online at <http://www. aphis.usda.gov/vs/ceah/cahm>. USDA:APHIS:VS (1998) Beef ‘97 . National Animal Health Monitoring System. Fort Collins, CO. Available online at <http://www.aphis.usda.gov/vs/ceah/cahm>. USDA:APHIS:VS (1996) Reference of 1996 Dairy Management Practices . National Animal Health Monitoring System. Fort Collins, CO. Available online at <http://www. aphis.usda.gov/vs/ceah/cahm>. USDA:APHIS:VS (1994) Beef Cow/Calf Health and Productivity Audit . National Animal Health Monitoring System. Fort Collins, CO. Available online at <http://www. aphis.usda.gov/vs/ceah/cahm>. USDA:APHIS:VS (1993) Beef Cow/Calf Health and Productivity Audit . National Animal Health Monitoring System. Fort Collins, CO. August 1993. Available online at <http://www.aphis.usda.gov/vs/ceah/cahm>. Western Dairyman (1998) “How Big Should Heifers Be at Calving?” The Western Dairyman , p. 12. September 1998. 

# Manure Management Anderson, S. (2000) Personal Communication. Lee-Ann Tracy, ERG and Steve Anderson, Agricultural Statistician, National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. May 31, 2000. ASAE (1999) ASAE Standards 1999, 46th

### Edition . American Society of Agricultural Engineers. St. Joseph, MI. Bryant, M.P., V.H. Varel, R.A. Frobish, and H.R. Isaacson (1976) In H.G. Schlegel (ed.); Seminar on Microbial Energy Conversion . E. Goltz KG. Göttingen, Germany. Deal, P. (2000) Personal Communication. Lee-Ann Tracy, ERG and Peter B. Deal, Rangeland Management Specialist, Florida Natural Resource Conservation Service. June 21, 2000. EPA (2006) AgSTAR Digest . Office of Air and Radiation, U.S. Environmental Protection Agency. Washington, DC. Winter 2006. Available online at <http://www.epa.gov/ agstar/pdf/2005digest.pdf>. July 2006. EPA (2005) National Emission Inventory—Ammonia Emissions from Animal Agricultural Operations, Revised Draft Report . U.S. Environmental Protection Agency. Washington, DC. April 22, 2005. Available online at ftp:// ftp.epa.gov/EmisInventory/2002finalnei/documentation/ nonpoint/nh3inventory_draft_042205.pdf>. August 2007. EPA (2003a) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2001 . EPA 430-R-03-004. U.S. Environmental Protection Agency. Washington, DC. April 15, 2003. EPA (2003b) AgSTAR Digest . Office of Air and Radiation, U.S. Environmental Protection Agency. Washington, DC. Winter 2003. <http://www.epa.gov/agstar/pdf/2002digest. pdf>. July 2006. EPA (2002a) Development Document for the Final Revisions to the National Pollutant Discharge Elimination System (NPDES) Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations (CAFOS) . U.S. Environmental Protection Agency. EPA-821-R-03-001. December 2002. EPA (2002b) C ost Methodology for the Final Revisions to the National Pollutant Discharge Elimination System Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations . U.S. Environmental Protection Agency. EPA821-R-03-004. December 2002. EPA (2000) AgSTAR Digest . Office of Air and Radiation, U.S. Environmental Protection Agency. Washington, DC. EPA (1992) Global Methane Emissions from Livestock and Poultry Manure . Office of Air and Radiation, U.S. Environmental Protection Agency. February 1992. ERG (2003) “Methodology for Estimating Uncertainty for Manure Management Greenhouse Gas Inventory.” Contract No. GS-10F-0036, Task Order 005. Memorandum to EPA from ERG, Lexington, MA. September 26, 2003. ERG (2001) Summary of development of MDP Factor for methane conversion factor calculations . ERG, Lexington, MA. September 2001.

### References 11-23 ERG (2000a) Calculations: Percent Distribution of Manure for Waste Management Systems . ERG, Lexington, MA. August 2000. ERG (2000b) Discussion of Methodology for Estimating Animal Waste Characteristics (Summary of Bo Literature Review). ERG, Lexington, MA. June 2000. FAO (2007) Yearly U.S. total horse population data from the Food and Agriculture Organization of the United Nations database . Available online at <http://faostat.fao.org>. June 2007. Garrett, W.N. and D.E. Johnson (1983) “Nutritional energetics of ruminants.” Journal of Animal Science
, 57(suppl.2):478–497. Groffman, P.M., R. Brumme, K. Butterbach-Bahl, K.E. Dobbie, A.R. Mosier, D. Ojima, H. Papen, W.J. Parton, K.A. Smith, and C. Wagner-Riddle (2000) “Evaluating annual nitrous oxide fluxes at the ecosystem scale.” Global Biogeochemcial Cycles , 14(4):1061–1070. Hashimoto, A.G. (1984) “Methane from Swine Manure: Effect of Temperature and Influent Substrate Composition on Kinetic Parameter (k).” Agricultural Wastes , 9:299–308. Hashimoto, A.G., V.H. Varel, and Y.R. Chen (1981) “Ultimate Methane Yield from Beef Cattle Manure; Effect of Temperature, Ration Constituents, Antibiotics and Manure Age.” Agricultural Wastes , 3:241–256. Hill, D.T. (1984) “Methane Productivity of the Major Animal Types.” Transactions of the ASAE , 27(2):530–540. Hill, D.T. (1982) “Design of Digestion Systems for Maximum Methane Production.” Transactions of the ASAE
, 25(1):226–230. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. Johnson, D. (2000) Personal Communication. Lee-Ann Tracy, ERG and Dan Johnson, State Water Management Engineer, California Natural Resource Conservation Service. June 23, 2000. Lange, J. (2000) Personal Communication. Lee-Ann Tracy, ERG and John Lange, Agricultural Statistician, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC. May 8, 2000. Miller, P. (2000) Personal Communication. Lee-Ann Tracy, ERG and Paul Miller, Iowa Natural Resource Conservation Service. June 12, 2000. Milton, B. (2000) Personal Communication. Lee-Ann Tracy, ERG and Bob Milton, Chief of Livestock Branch, U.S. Department of Agriculture, National Agriculture Statistics Service. May 1, 2000. Morris, G.R. (1976) Anaerobic Fermentation of Animal Wastes: A Kinetic and Empirical Design Fermentation . M.S. Thesis. Cornell University. NOAA (2007) National Climate Data Center (NCDC)

. Available online at <ftp://ftp.ncdc.noaa.gov/pub/data/cirs/> (for all states except Alaska and Hawaii) and <ftp://ftp.ncdc. noaa.gov/pub/data/gsod/2006/> (for Alaska and Hawaii). June 2007. Pederson, L., D. Pape and K. Moffroid (2007) 1990–2006 Volatile Solids and Nitrogen Excretion Rates . EPA Contract GS-10F-0124J, Task Order 056-01. Memorandum to EPA from ICF International. August 2007. Poe, G., N. Bills, B. Bellows, P. Crosscombe, R. Koelsch, M. Kreher, and P. Wright (1999) Staff Paper Documenting the Status of Dairy Manure Management in New York: Current Practices and Willingness to Participate in Voluntary Programs . Department of Agricultural, Resource, and Managerial Economics; Cornell University. Ithaca, New York. September. Safley, L.M., Jr. and P.W. Westerman (1990) “Psychrophilic anaerobic digestion of animal manure: proposed design methodology.” Biological Wastes , 34:133–148. Safley, L.M., Jr. (2000) Personal Communication. Deb Bartram, ERG and L.M. Safley, President, Agri-Waste Technology. June and October 2000. Stettler, D. (2000) Personal Communication. Lee-Ann Tracy, ERG and Don Stettler, Environmental Engineer, National Climate Center, Oregon Natural Resource Conservation Service. June 27, 2000. Sweeten, J. (2000) Personal Communication. Indra Mitra, ERG and John Sweeten, Texas A&M University. June 2000. UEP (1999) Voluntary Survey Results—Estimated Percentage Participation/Activity . Caged Layer Environmental Management Practices, Industry data submissions for EPA profile development, United Egg Producers and National Chicken Council. Received from John Thorne, Capitolink. June 2000. USDA (2007a) Published Estimates Database . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http:// www.nass.usda.gov/Publications/index.asp>. May 2006. USDA (2007b) Chicken and Eggs 2006 Summary

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. February 2007. Available online at <http://www.nass.usda.gov/Publications/index. asp>. USDA (2007c) Poultry - Production and Value 2006 Summary . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2007. Available online at <http://www.nass.usda.gov/Publications/ index.asp>.

### 11-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 USDA (2006a) Chicken and Eggs 2005 Summary

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. February 2006. Available online at <http://www.nass.usda.gov/Publications/index. asp>. USDA (2006b) Poultry - Production and Value 2005 Summary . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2006. Available online at <http://www.nass.usda.gov/Publications/ index.asp>. USDA (2005) 1992, 1997, and 2002 Census of Agriculture

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http:// www.nass.usda.gov/census/>. March 2006. USDA (2004a) Chicken and Eggs—Final Estimates 1998–2003 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2004. Available online at <http://usda.mannlib.cornell.edu/reports/ general/sb/>. USDA (2004b) Poultry Production and Value—Final Estimates 1998–2002 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2004. Available online at <http://usda.mannlib.cornell. edu/reports/general/sb/>. USDA (2000a) National Animal Health Monitoring System’s (NAHMS) Dairy ‘96 Study . Stephen L. Ott, Animal and Plant Health Inspection Service, U.S. Department of Agriculture. June 19, 2000. USDA (2000b) Layers ‘99—Part II: References of 1999 Table Egg Layer Managementin the U.S. Animal and Plant Health Inspection Service (APHIS), National Animal Health Monitoring System (NAHMS), U.S. Department of Agriculture. January 2000. USDA (1999) Poultry Production and Value—Final Estimates 1994–97 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. March 1999. Available online at <http://usda.mannlib.cornell.edu/ reports/general/sb/>. USDA (1998a) Chicken and Eggs—Final Estimates 1994– 97 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. December 1998. Available online at <http://usda.mannlib.cornell.edu/reports/general/ sb/>. USDA (1998b) National Animal Health Monitoring System’s (NAHMS) Swine ‘95 Study . Eric Bush, Centers for Epidemiology and Animal Health , U.S. Department of Agriculture. USDA (1996a) Agricultural Waste Management Field Handbook, National Engineering Handbook (NEH)
, Part 651. Natural Resources Conservation Service, U.S. Department of Agriculture. July 1996. USDA (1996b) Swine ‘95: Grower/Finisher Part II: Reference of 1995 U.S. Grower/Finisher Health & Management Practices . Animal Plant Health and Inspection Service, U.S. Department of Agriculture. Washington, DC. June 1996. USDA (1995a) Chicken and Eggs—Final Estimates 1988–1993 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http://usda.mannlib.cornell.edu/data-sets/ livestock/95908/sb908.txt>. January 1995. USDA (1995b) Poultry Production and Value—Final Estimates 1988–1993 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 1995. Available online at <http://usda.mannlib. cornell.edu/reports/general/sb/>. USDA (1994) Sheep and Goats—Final Estimates 1989–1993 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 31, 1994. Available online at <http://usda.mannlib.cornell.edu/ reports/general/sb/>. Wright, P. (2000) Personal Communication. Lee-Ann Tracy, ERG and Peter Wright, Cornell University, College of Agriculture and Life Sciences. June 23, 2000.



# Rice Cultivation Bollich, P. (2000) Personal Communication. Pat Bollich, Professor with Louisiana State University Agriculture Center and Payton Deeks, ICF International. May 17, 2000. Bossio, D.A., W. Horwath, R.G. Mutters, and C. van Kessel (1999) “Methane pool and flux dynamics in a rice field following straw incorporation.” Soil Biology and Biochemistry , 31:1313–1322. Cantens, G. (2005) Personal Communication. Janet Lewis, Assistant to Gaston Cantens, Vice President, Corporate Relations, Florida Crystals Company and Lauren Flinn, ICF International. August 4, 2005. Cantens, G. (2004) Personal Communication. Janet Lewis, Assistant to Gaston Cantens, Vice President, Corporate Relations, Florida Crystals Company and Lauren Flinn, ICF International. July 30, 2004. Cicerone R.J., C.C. Delwiche, S.C. Tyler, and P.R. Zimmerman (1992) “Methane Emissions from California Rice Paddies with Varied Treatments.” Global Biogeochemical Cycles
, 6:233–248. Deren, C. (2002) Personal Communication. Dr. Chris Deren, Everglades Research and Education Centre at the University of Florida and Caren Mintz, ICF International. August 15, 2002. Gonzalez, R. (2007a) Email correspondence. Rene Gonzalez, Plant Manager, Sem-Chi Rice Company and Sarah Menassian, ICF International. August 29, 2007.

### References 11-25 Gonzalez, R. (2007b) Email correspondence. Rene Gonzalez, Plant Manager, Sem-Chi Rice Company and Victoria Thompson, ICF International. August 2007. Guethle, D. (2007) Email correspondence. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Victoria Thompson, ICF International. July 30, 2007. Guethle, D. (2006) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Lauren Flinn, ICF International. July 2006. Guethle, D. (2005) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Lauren Flinn, ICF International. July 2005. Guethle, D. (2004) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Lauren Flinn, ICF International. June 23, 2004. Guethle, D. (2003) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Caren Mintz, ICF International. June 19, 2003. Guethle, D. (2002) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Caren Mintz, ICF International. August 19, 2002. Guethle, D. (2001a) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Caren Mintz, ICF International. July 31, 2001. Guethle, D. (2001b) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Caren Mintz, ICF International. September 4, 2001. Guethle, D. (2000) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Payton Deeks, ICF International. May 17, 2000. Guethle, D. (1999) Personal Communication. David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Payton Deeks, ICF International. August 6, 1999. Holzapfel-Pschorn, A., R. Conrad, and W. Seiler (1985) “Production, Oxidation, and Emissions of Methane in Rice Paddies.” FEMS Microbiology Ecology, 31:343–351. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories
., National Greenhouse Gas Inventories Programme, Intergovernmental Panel on Climate Change. Montreal. May 2000. IPCC-XVI/Doc. 10 (1.IV.2000). IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. Kirstein, A. (2006) Personal Communication. Arthur Kirstein, Coordinator, Agricultural Economic Development Program, Palm Beach County Cooperative Extension Service, FL and Lauren Flinn, ICF International. August 17, 2006. Kirstein, A. (2004) Personal Communication. Arthur Kirstein, Coordinator, Agricultural Economic Development Program, Palm Beach County Cooperative Extension Service, FL and Lauren Flinn, ICF International. June 30, 2004. Kirstein, A. (2003) Personal Communication. Arthur Kirstein, Coordinator, Agricultural Economic Development Program, Palm Beach County Cooperative Extension Service, FL and Caren Mintz, ICF International. August 13, 2003. Klosterboer, A. (2003) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M University and Caren Mintz, ICF International. July 7, 2003. Klosterboer, A. (2002) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M University and Caren Mintz, ICF International. August 19, 2002. Klosterboer, A. (2001a) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M University and Caren Mintz, ICF International. August 6, 2001. Klosterboer, A. (2001b) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M University and Caren Mintz, ICF International. October 8, 2001. Klosterboer, A. (2000) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M University and Payton Deeks, ICF International. May 18, 2000. Klosterboer, A. (1999) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M University and Catherine Leining, ICF International. June 10, 1999. Klosterboer, A. (1997) Personal Communication. Arlen Klosterboer, retired Extension Agronomist, Texas A&M University and Holly Simpkins, ICF Incorporated. December 1, 1997. Lancero, J. (2007) Email correspondence. Jeff Lancero, California Air Resources Board and Victoria Thompson, ICF International. July 24, 2007.

### 11-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 Lancero, J. (2006) Email correspondence. Jeff Lancero, California Air Resources Board and Lauren Flinn, ICF International. August 11, 2006. Lee, D. (2007) Email correspondence. Danny Lee, OK Farm Service Agency and Victoria Thompson, ICF International. July 30, 2007. Lee, D. (2006) Email correspondence. Danny Lee, OK Farm Service Agency and Lauren Flinn, ICF International. July 13, 2006. Lee, D. (2005) Email correspondence. Danny Lee, OK Farm Service Agency and Lauren Flinn, ICF International. July and September 2005. Lee, D. (2004) Personal Communication. Danny Lee, OK Farm Service Agency and Lauren Flinn, ICF International July 23, 2004. Lee, D. (2003) Personal Communication. Danny Lee, OK Farm Service Agency and Caren Mintz, ICF International. July 2, 2003. Lindau, C.W. and P.K. Bollich (1993) “Methane Emissions from Louisiana First and Ratoon Crop Rice.” Soil Science
, 156:42–48. Lindau, C.W., P.K Bollich, and R.D. DeLaune (1995) “Effect of Rice Variety on Methane Emission from Louisiana Rice.” Agriculture, Ecosystems and Environment , 54:109–114. Linscombe, S. (2007) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Victoria Thompson, ICF International. July 24, 2007. Linscombe, S. (2006) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Lauren Flinn, ICF International. August 15, 2006. Linscombe, S. (2005) Email correspondence. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Lauren Flinn, ICF International. July 2005. Linscombe, S. (2004) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Lauren Flinn, ICF International. June 23, 2004. Linscombe, S. (2003) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Caren Mintz, ICF International. June 10, 2003. Linscombe, S. (2002) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Caren Mintz, ICF International. August 21, 2002. Linscombe, S. (2001a) Personal Communication. Steve Linscombe, Research Agronomist, Rice Research Station in Crowley, LA and Caren Mintz, ICF International. July 30–August 1, 2001. Linscombe, S. (2001b) Email correspondence. Steve Linscombe, Research Agronomist, Rice Research Station in Crowley, LA and Caren Mintz, ICF International. October 4, 2001. Linscombe, S. (1999) Personal Communication. Steve Linscombe, Research Agronomist, Rice Research Station in Crowley, LA and Catherine Leining, ICF International June 3, 1999. Mayhew, W. (1997) Personal Communication. Walter Mayhew, University of Arkansas, Little Rock and Holly Simpkins, ICF Incorporated. November 24, 1997. Mutters, C. (2005) Email correspondence. Cass Mutters, Rice Farm Advisor for Butte, Glen, and Tehama Counties University of California, Cooperative Extension Service and Lauren Flinn, ICF International. July 2004. Mutters, C. (2004) Personal Communication. Cass Mutters, Rice Farm Advisor for Butte, Glen, and Tehama Counties University of California, Cooperative Extension Service and Lauren Flinn, ICF International. June 25, 2004. Mutters, C. (2003) Personal Communication. Cass Mutters, Rice Farm Advisor for Butte, Glen, and Tehama Counties University of California, Cooperative Extension Service and Caren Mintz, ICF International. June 23, 2003. Mutters, C. (2002) Personal Communication. Cass Mutters, Rice Farm Advisor for Butte, Glen, and Tehama Counties University of California, Cooperative Extension Service and Caren Mintz, ICF International. August 27, 2002. Mutters, C. (2001) Personal Communication. Cass Mutters, Rice Farm Advisor for Butte, Glen, and Tehama Counties University of California, Cooperative Extension Service and Caren Mintz, ICF International. September 5, 2001. Sacramento Valley Basinwide Air Pollution Control Council (2007) Report on the Conditional Rice Straw Burning Permit Program . June 1, 2007. Available online at <http://www. bcaqmd.org/default.asp?docpage=html/bcc.htm>. Sacramento Valley Basinwide Air Pollution Control Council (2005) Report on the Conditional Rice Straw Burning Permit Program . May 25, 2005. Available online at <http://www. bcaqmd.org/default.asp?docpage=html/bcc.htm>. Saichuk, J. (1997) Personal Communication. John Saichuk, Louisiana State University and Holly Simpkins, ICF Incorporated. November 24, 1997. Sass, R.L., F.M Fisher, P.A. Harcombe, and F.T. Turner (1991a) “Mitigation of Methane Emissions from Rice Fields: Possible Adverse Effects of Incorporated Rice Straw.” Global Biogeochemical Cycles , 5:275–287. Sass, R.L., F.M. Fisher, F.T. Turner, and M.F. Jund (1991b) “Methane Emissions from Rice Fields as Influenced by Solar Radiation, Temperature, and Straw Incorporation.” Global Biogeochemical Cycles , 5:335–350.

### References 11-27 Sass, R.L., F.M. Fisher, P.A. Harcombe, and F.T. Turner (1990) “Methane Production and Emissions in a Texas Rice Field.” Global Biogeochemical Cycles , 4:47–68. Schueneman, T. (2001a) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Caren Mintz, ICF International. July 30, 2001. Schueneman, T. (2001b) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Caren Mintz, ICF International. October 9, 2001. Schueneman, T. (2000) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Payton Deeks, ICF International. May 16, 2000. Schueneman, T. (1999a) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Catherine Leining, ICF International. June 7, 1999. Schueneman, T. (1999b) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Payton Deeks, ICF International. August 10, 1999. Schueneman, T. (1999c) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and John Venezia, ICF International. August 7, 1999. Schueneman, T. (1997) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Barbara Braatz, ICF Incorporated. November 7, 1997. Slaton, N. (2001a) Personal Communication. Nathan Slaton, Extension Agronomist—Rice, University of Arkansas Division of Agriculture Cooperative Extension Service and Caren Mintz, ICF International. August 23, 2001. Slaton, N. (2001b) Personal Communication. Nathan Slaton, Extension Agronomist—Rice, University of Arkansas Division of Agriculture Cooperative Extension Service and Caren Mintz, ICF International. October 3, 2001. Slaton, N. (2000) Personal Communication. Nathan Slaton, Extension Agronomist—Rice, University of Arkansas Division of Agriculture Cooperative Extension Service and Payton Deeks, ICF International. May 20, 2000. Slaton, N. (1999) Personal Communication. Nathan Slaton, Extension Agronomist—Rice, University of Arkansas Division of Agriculture Cooperative Extension Service and Catherine Leining, ICF International. June 3, 1999. Stansel, J. (2005) Email correspondence. Dr. Jim Stansel, Resident Director and Professor Emeritus, Texas A&M University Agricultural Research and Extension Center and Lauren Flinn, ICF International. July 2005. Stansel, J. (2004) Personal Communication. Dr. Jim Stansel, Resident Director and Professor Emeritus, Texas A&M University Agricultural Research and Extension Center and Lauren Flinn, ICF International. July 12, 2004. Stevens, G. (1997) Personal Communication. Gene Stevens, Extension Specialist, Missouri Commercial Agriculture Program, Delta Research Center and Holly Simpkins, ICF Incorporated. December 17, 1997. Street, J. (2003) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Caren Mintz, ICF International. June 19, 2003. Street, J. (2002) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Caren Mintz, ICF International. August 19, 2002. Street, J. (2001a) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Caren Mintz, ICF International. August 1, 2001. Street, J. (2001b) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Caren Mintz, ICF International. October 3, 2001. Street, J. (2000) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Payton Deeks, ICF International. May 17, 2000. Street, J. (1999) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Catherine Leining, ICF International June 8, 1999. Street, J. (1997) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Holly Simpkins, ICF Incorporated. December 1, 1997. Texas Agricultural Experiment Station (2007) 2006 - Texas Rice Acreage by Variety . Agricultural Research and Extension Center, Texas Agricultural Experiment Station, Texas A&M University System. Available online at <http://beaumont. tamu.edu/CropSurvey/CropSurveyReport.aspx>. Texas Agricultural Experiment Station (2006) 2005 - Texas Rice Crop Statistics Report . Agricultural Research and Extension Center, Texas Agricultural Experiment Station, Texas A&M University System, p. 8. Available online at <http://beaumont.tamu.edu/eLibrary/TRRFReport_default. htm>. USDA (2007) Crop Production 2006 Summary , National Agricultural Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture. Washington, DC. Available online at <http://usda.mannlib.cornell.edu>.

### 11-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 USDA (2005 through 2006) Crop Production Summary
, National Agricultural Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture. Washington, DC. Available online at <http://usda.mannlib.cornell.edu>. USDA (2003) Field Crops, Final Estimates 1997–2002

. Statistical Bulletin No. 982. National Agricultural Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture, Washington, DC. Available online at <http:// usda.mannlib.cornell.edu/usda/reports/general/sb/>. September 2005. USDA (1998) Field Crops Final Estimates 1992–97

. Statistical Bulletin Number 947 a. National Agricultural Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture, Washington, DC. Available online at <http://usda.mannlib.cornell.edu/>. July 2001. USDA (1994) Field Crops Final Estimates 1987–1992

. Statistical Bulletin Number 896. National Agricultural Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture, Washington, DC. Available online at <http://usda.mannlib.cornell.edu/>. July 2001. Walker, T. (2007) Personal Communication. Tim Walker, Assistant Research Professor, Mississippi State University Delta Branch Exp. Station and Victoria Thompson, ICF International. August 15, 2007. Walker, T. (2005) Email correspondence. Tim Walker, Assistant Research Professor, Mississippi State University Delta Branch Exp. Station and Lauren Flinn, ICF International.. July 2005. Wilson, C. (2007) Personal Communication. Dr. Chuck Wilson, Rice Specialist at the University of Arkansas Cooperative Extension Service and Victoria Thompson, ICF International. August 22, 2007. Wilson, C. (2006) Email correspondence. Dr. Chuck Wilson, Rice Specialist at the University of Arkansas Cooperative Extension Service and Lauren Flinn, ICF International. August 8, 2006. Wilson, C. (2005) Email correspondence. Dr. Chuck Wilson, Rice Specialist at the University of Arkansas Cooperative Extension Service and Lauren Flinn, ICF International. August 2005. Wilson, C. (2004) Personal Communication. Dr. Chuck Wilson, Rice Specialist at the University of Arkansas Cooperative Extension Service and Lauren Flinn, ICF International. June 23, 2004. Wilson, C. (2003) Personal Communication. Dr. Chuck Wilson, Rice Specialist at the University of Arkansas Cooperative Extension Service and Caren Mintz, ICF International. June 11, 2003. Wilson, C. (2002) Personal Communication. Dr. Chuck Wilson, Rice Specialist at the University of Arkansas Cooperative Extension Service and Caren Mintz, ICF International. August 23, 2002. 

# Agricultural Soil Management AAPFCO (1995 through 2000b, 2002 through 2007) Commercial Fertilizers . Association of American Plant Food Control Officials. University of Kentucky, Lexington, KY. AAPFCO (2000a) 1999–2000 Commercial Fertilizers Data, ASCII files. Available from David Terry, Secretary, Association of American Plant Food Control Officials. Alexander, R.B. and R.A. Smith (1990) County-Level Estimates of Nitrogen and Phosphorous Fertilizer Use in the United States, 1945–1985 . U.S. Geological Survey Open File Report 90–130. Anderson, S. (2000) Personal Communication. Lee-Ann Tracy, ERG and Steve Anderson, Agricultural Statistician, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC. May 31, 2000. Anonymous (1924) Fertilizer Used on Cotton, 1923–1924. “Miscellaneous Agricultural Statistics,” Table 753. 1924 Yearbook of the Department of Agriculture , 1171. ASAE (1999) ASAE Standards 1999, 46th

### Edition . American Society of Agricultural Engineers. St. Joseph, MI. Bastian, R. (2007) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection Agency, Washington, DC and Victoria Thompson, ICF International. July 20, 2007. Bastian, R. (2006) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection Agency, Washington, DC and Lauren Flinn, ICF International. July 17, 2006. Bastian, R. (2005) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection Agency, Washington, DC and Lauren Flinn, ICF International. September 2005. Bastian, R. (2003) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection Agency, Washington, DC and Caren Mintz, ICF International. August 13, 2003. Bastian, R. (2002) Personal Communication. Robert Bastian, Office of Water, U.S. Environmental Protection Agency, Washington, DC and Caren Mintz, ICF International. August 23, 2002. Battaglin, W.A., and D.A. Goolsby (1994) Spatial Data in Geographic Information System Format on Agricultural Chemical Use, Land Use, and Cropping Practices in the United States . U.S. Geological Survey Water-Resources Investigations Report 94

– 4176. Bogue A.G. (1963) From Prairie to Corn Belt: Farming on the Illinois and Iowa prairies in the Nineteenth Century . The University of Chicago Press. Chicago, IL. Bonnen C.A., and F.F. Elliott (1931) Type of Farming Areas in Texas . Bulletin Number 427, Texas Agricultural Experiment Station, Agricultural and Mechanical College of Texas.

### References 11-29 Brenner, J., K. Paustian, G. Bluhm, J. Cipra, M. Easter, R. Foulk, K. Killian, R. Moore, J. Schuler, P. Smith, and S. Williams (2002) Quantifying the Change in Greenhouse Gas Emissions Due to Natural Resource Conservation Practice Application in Nebraska . Colorado State University Natural Resource Ecology Laboratory and USDA Natural Resources Conservation Service. Fort Collins, CO. Brenner, J., K. Paustian., G. Bluhm, J. Cipra, M. Easter, E.T. Elliott, T. Koutza, K. Killian, J. Schuler, S. Williams (2001) Quantifying the Change in Greenhouse Gas Emissions Due to Natural Resource Conservation Practice Application in Iowa . Final report to the Iowa Conservation Partnership. Colorado State University Natural Resource Ecology Laboratory and U.S. Department of Agriculture Natural Resources Conservation Service. Fort Collins, CO. Brumme, R., Borken, W., and Finke, S. (1999) “Hierarchical control on nitrous oxide emission in forest ecosystems.” Global Biochem. Cycles , 13:1137–1148. Butterbach-Bahl, K., R. Gasche, L. Breuer, and H. Papen. (1997) “Fluxes of NO and N 2 

### O from temperate forest soils: impact of forest type, N deposition and of liming on the NO and N 2 

### O emissions.” Nutr. Cycl. Agroecosyst ., 48:79–90. Carpenter, G.H. (1992) “Current Litter Practices and Future Needs.” In 1992 National Poultry Waste Management Symposium Proceedings . J.P. Blake, J.O. Donald, and P.H. Patterson (eds.); Auburn University Printing Service. Auburn, AL, 268–273. Carpenter, G. and J. Starkey (2007) Personal Communication. Glenn Carpenter, USDA; John Starkey, U.S. Poultry & Egg Association and Victoria Thompson, ICF International, April to June, 2007. Chilcott E.C. (1910) A Study of Cultivation Methods and Crop Rotations for the Great Plains Area . Bureau of Plant Industry Bulletin Number 187, U.S. Department of Agriculture. Government Printing Office. Washington, DC. Clough, T., J.E. Bertram, R.R. Sherlock, R.L. Leonard, andB.L. Nowicki (2006) “Comparison of measured and EF5-rderived N 2 

### O fluxes from a spring-fed river.” Glob. Change Biol ., 12:477–488. Cochran, W.G. (1977) Sampling Techniques, Third Edition

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### References 11-35 USDA. (1957) Fertilizer Used on Crops and Pastures in the United States—1954 Estimates . Statistical Bulletin Number 216, Agricultural Research Service, U.S. Department of Agriculture. USDA. (1954) Fertilizer Use and Crop Yields in the United States . Agricultural Handbook Number 68, the Fertilizer Work Group, U.S. Department of Agriculture. USDA. (1946) Fertilizers and Lime in the United States

. Miscellaneous Publication Number 586, U.S. Department of Agriculture. USDA-NASS (2007) USDA National Agricultural Statistics Service, Quick Stats for U.S. and all states county data for crops. U.S. Department of Agriculture, National Agricultural Statistics Service. Washington, D.C. Available online at <http://www.nass.usda.gov/QuickStats/ Create_County_All.jsp>. VEMAP (1995) Members (J.M. Melillo, J. Borchers, J. Chaney, H. Fisher, S. Fox, A. Haxeltine, A. Janetos, D.W. Kicklighter, T.G.F. Kittel, A.D. McGuire, R. McKeown, R. Neilson, R. Nemani, D.S. Ojima, T. Painter, Y. Pan, W.J. Parton, L. Pierce, L. Pitelka, C. Prentice, B. Rizzo, N.A. Rosenbloom, S. Running, D.S. Schimel, S. Sitch, T. Smith, I. Woodward). “Vegetation/Ecosystem Modeling and Analysis Project (VEMAP): Comparing Biogeography and Biogeochemistry Models in a Continental-Scale Study of Terrestrial Ecosystem Responses to Climate Change and CO 2 

### Doubling.” Global Biogeochemical Cycles , 9:407–437. Vogelmann, J.E., S.M. Howard, L. Yang, C. R. Larson, B. K. Wylie, and J. N. Van Driel (2001) “Completion of the 1990’s National Land Cover Data Set for the conterminous United States.” Photogrammetric Engineering and Remote Sensing , 67:650–662. Warren J.A. (1911) Agriculture in the Central Part of the Semiarid Portion of the Great Plains . Bulletin Number 215, Bureau of Plant Industry, U.S. Department of Agriculture. Williams, S.A. (2006) Data compiled for the Consortium for Agricultural Soils Mitigation of Greenhouse Gases (CASMGS) from an unpublished manuscript. Natural Resource Ecology Laboratory, Colorado State University. Williams-Jacobse, J.G.F.M. (ed.) (2002) Proceedings 3 rd 

### International Symposium Non-CO 2 

### Greenhouse Gases

. Maastricht, The Netherlands, 185–190. Wright, P. (2000) Personal Communication. Lee-Ann Tracy, ERG and Peter Wright, Cornell University, College of Agriculture and Life Sciences. June 23, 2000. 

# Field Burning of Agricultural Residues Anonymous (2006) Personal communication with Lauren Flinn, ICF International. August 11, 2006. Barnard, G., and L. Kristoferson (1985) Agricultural Residues as Fuel in the Third World . Earthscan Energy Information Programme and the Beijer Institute of the Royal Swedish Academy of Sciences. London, England. Bollich, P. (2000) Personal Communication. Pat Bollich, Professor with Louisiana State University Agriculture Center and Payton Deeks, ICF International.. May 17, 2000. California Air Resources Board (2001) Progress Report on the Phase Down and the 1998–2000 Pause in the Phase Down of Rice Straw Burning in the Sacramento Valley Air Basin
, Proposed 2001 Report to the Legislature. June 2001. California Air Resources Board (1999) Progress Report on the Phase Down of Rice Straw Burning in the Sacramento Valley Air Basin . Proposed 1999 Report to the Legislature. December 1999. Cantens, G. (2005) Personal Communication. Janet Lewis, Assistant to Gaston Cantens, Vice President of Corporate Relations, Florida Crystals Company and Lauren Flinn, ICF International. July 2005. Cantens, G. (2004) Personal Communication. Janet Lewis, Assistant to Gaston Cantens, Vice President of Corporate Relations, Florida Crystals Company and Lauren Flinn, ICF International. July 30, 2004. Cibrowski, P. (1996) Personal Communication. Peter Cibrowski, Minnesota Pollution Control Agency and Heike Mainhardt, ICF Incorporated. July 29, 1996. Deren, C. (2002) Personal communication. Dr. Chris Deren, Everglades Research and Education Centre at the University of Florida and Caren Mintz, ICF International. August 15, 2002. EPA (1994) International Anthropogenic Methane Emissions: Estimates for 1990, Report to Congress . EPA 230-R-93-010. Office of Policy Planning and Evaluation, U.S. Environmental Protection Agency. Washington, DC. EPA (1992) Prescribed Burning Background Document and Technical Information Document for Prescribed Burning Best Available Control Measures . Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. EPA-450/2-92-003. Fife, L. (1999) Personal Communication. Les Fife, President and General Manager, Fife Environmental and Catherine Leining, ICF International. June 9, 1999. Gonzalez, R. (2007a) Email correspondence. Rene Gonzalez, Plant Manager, Sem-Chi Rice Company and Sarah Menassian, ICF International. August 29, 2007. Gonzalez, R. (2007b) Email correspondence. Rene Gonzalez, Plant Manager, Sem-Chi Rice Company and Victoria Thompson, ICF International. August 2007. Guethle, D. (2007) Email correspondence David Guethle, Agronomy Specialist, Missouri Cooperative Extension Service and Victoria Thompson, ICF International. July 30, 2007. ILENR (1993) Illinois Inventory of Greenhouse Gas Emissions and Sinks: 1990 . Office of Research and Planning, Illinois Department of Energy and Natural Resources. Springfield, IL.

### 11-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories

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### References 11-37 Linscombe, S. (2004) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Lauren Flinn, ICF International. June 23, 2004. Linscombe, S. (2003) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Caren Mintz, ICF International. June 10, 2003. Linscombe, S. (2002) Email correspondence. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Caren Mintz, ICF International. August 21, 2002. Linscombe, S. (2001) Email correspondence. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Caren Mintz, ICF International. July 30–August 1, 2001. Linscombe, S. (1999a) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Catherine Leining, ICF International. June 3, 1999. Linscombe, S. (1999b) Personal Communication. Steve Linscombe, Professor with the Rice Research Station at Louisiana State University Agriculture Center and Payton Deeks, ICF International. August 9, 1999. Najita, T. (2001) Personal Communication. Theresa Najita, Air Pollution Specialist, California Air Resources Board and Caren Mintz, ICF International. July 31, 2001. Najita, T. (2000) Personal Communication. Theresa Najita, Air Pollution Specialist, California Air Resources Board and Payton Deeks, ICF International. August 17, 2000. Noller, J. (1996) Personal Communication. John Noller, Missouri Department of Natural Resources and Heike Mainhardt, ICF Incorporated. July 30, 1996. Oregon Department of Energy (1995) Report on Reducing Oregon’s Greenhouse Gas Emissions: Appendix D Inventory and Technical Discussion . Oregon Department of Energy. Salem, OR. Sacramento Valley Basinwide Air Pollution Control Council (2007) Report on the Conditional Rice Straw Burning Permit Program . June 1, 2007. Available online at: <http://www. bcaqmd.org/default.asp?docpage=html/bcc.htm>. Sacramento Valley Basinwide Air Pollution Control Council (2005) Report on the Conditional Rice Straw Burning Permit Program . May 25, 2005. Available online at <http://www. bcaqmd.org/default.asp?docpage=html/bcc.htm>. Schueneman, T. (2001) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Caren Mintz, ICF International. July 30, 2001. Schueneman, T. (1999a) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Catherine Leining, ICF International. June 7, 1999. Schueneman, T. (1999b) Personal Communication. Tom Schueneman, Agricultural Extension Agent, Palm Beach County, FL and Payton Deeks, ICF International. August 10, 1999. Schueneman, T.J. and C.W. Deren (2002) “An Overview of the Florida Rice Industry” SS-AGR-77, Agronomy Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Revised November 2002. Stansel, J. (2005) Email correspondence. Dr. Jim Stansel, Resident Director and Professor Emeritus, Texas A&M University Agricultural Research and Extension Center and Lauren Flinn, ICF International. July 2005. Stansel, J. (2004) Personal Communication. Dr. Jim Stansel, Resident Director and Professor Emeritus, Texas A&M University Agricultural Research and Extension Center and Lauren Flinn, ICF International. July 12, 2004. Street, J. (2003) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Caren Mintz, ICF International. June 19, 2003. Street, J. (2002) ) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Caren Mintz, ICF International. August 19, 2002. Street, J. (2001) ) Personal Communication. Joe Street, Rice Specialist, Mississippi State University, Delta Research Center and Caren Mintz, ICF International. August 1, 2001. Strehler, A., and W. Stützle (1987) “Biomass Residues.” In Hall, D.O. and Overend, R.P. (eds.) Biomass. John Wiley and Sons, Ltd. Chichester, UK. Texas Agricultural Experiment Station (2006) 2005 - Texas Rice Crop Statistics Report . Agricultural Research and Extension Center, Texas Agricultural Experiment Station, Texas A&M University System, p. 8. Available online at <http://beaumont.tamu.edu/eLibrary/TRRFReport_ default.htm>. Texas Agricultural Experiment Station (2007) 2006 - Texas Rice Acreage by Variety . Agricultural Research and Extension Center, Texas Agricultural Experiment Station, Texas A&M University System. 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### 11-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 University of California (1977) Emission Factors From Burning of Agricultural Waste Collected in California

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# Land Use, Land-Use Change, and Forestry

IPCC (2003) Good Practice Guidance for Land Use, LandUse Change, and Forestry . The Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, J. Penman, et al., eds. August 13, 2004. Available online at <http://www.ipcc-nggip.iges.or.jp/public/ gpglulucf/gpglulucf.htm>. 

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., Brooks, K.N. and Folliott, P.F. (eds). 12-15 June 2005, Rochester, MN [CD-ROM]. Dept. of Forest Resources, Univ. Minnesota, St. Paul, MN, 12 p. Available online at <http:// cinram.umn.edu/afta2005/> (verified 23 Sept 2006). Phillips, D.L., S.L. Brown, P.E. Schroeder, and R.A. Birdsey (2000) “Toward Error Analysis of Large-Scale Forest Carbon Budgets.” Global Ecology and Biogeography 9:305–313. Skog, K.E., and G.A. Nicholson (1998) “Carbon Cycling Through Wood Products: The Role of Wood and Paper Products in Carbon Sequestration.” Forest Products Journal 48:75–83. Skog, K.E., K. Pingoud, and J.E. Smith (2004) “A method countries can use to estimate changes in carbon stored in harvested wood products and the uncertainty of such estimates.” Environmental Management 33(Suppl. 1):S65– S73. Skog, K.E. (In preparation) “Sequestration of carbon in harvested wood products for the United States.” USDA Forest Service, Forest Products Laboratory. Draft manuscript, July 2007. Smith, J.E., and L.S. Heath (2002) “A model of forest floorcarbon mass for United States forest types.” Res. Paper NE722. USDA Forest Service, Northeastern Research Station, Newtowne Square, PA. Smith, J. E., L. S. Heath, and J. C. Jenkins (2003) Forest Volume-to-Biomass Models and Estimates of Mass for Live and Standing Dead Trees of U.S. Forests . General Technical Report NE-298, USDA Forest Service, Northeastern Research Station, Newtown Square, PA. Smith, J.E., L.S. Heath, and M.C. Nichols (2007). U.S. Forest Carbon Calculation Tool User’s Guide: Forestland Carbon Stocks and Net Annual Stock Change. General Technical Report NRS-13, U.S. Department of Agriculture Forest Service, Northern Research Station. Smith, J. E., L. S. Heath, and P. B. Woodbury (2004 a) “How to estimate forest carbon for large areas from inventory data.” Journal of Forestry 102:25–31. Smith, W. B., P. D. Miles, J. S. Vissage, and S. A. Pugh (2004b) Forest Resources of the United States, 2002 . General Technical Report NC-241, U.S. Department of Agriculture Forest Service, North Central Research Station, St. Paul, MN. Steer, Henry B. (1948) Lumber production in the United States . Misc. Pub. 669, U.S. Department of Agriculture Forest Service. Washington, DC. Ulrich, A.H. (1989) U.S. Timber Production, Trade, Consumption, and Price Statistics, 1950–1987 . USDA Miscellaneous Publication No. 1471, U.S. Department of Agriculture Forest Service. Washington, DC, 77. Ulrich, Alice (1985) U.S. Timber Production, Trade, Consumption, and Price Statistics 1950–1985 . Misc. Pub. 1453, U.S. Department of Agriculture Forest Service. Washington, DC. USDC Bureau of Census (1976) Historical Statistics of the United States, Colonial Times to 1970, Vol. 1 . Washington, DC. USDA Forest Service. (2006a) Forest Inventory and Analysis National Program, FIA library. Available online at <http:// www.fia.fs.fed.us/library/field-guides-methods-proc/>. Accessed September 20, 2006. USDA Forest Service. (2006b) Forest Inventory and Analysis Data Center. Available online at <http://ncrs2.fs.fed.us/4801/ fiadb/>. Accessed September 20, 2006. USDA Forest Service. (2006c) FIA Data Mart: Download. Available online at <http://www.ncrs2.fs.fed.us/FIADatamart/ fiadatamart.aspx>. Click on documentation link to download Users Guide to the Forest Inventory Snapshot Database Version 2.1. Accessed September 20, 2006. USDA Forest Service (1992) “1984–1990 Wildfire Statistics.” Prepared by State and Private Forestry Fire and Aviation Management Staff. Facsimile from Helene Cleveland, USDA Forest Service, to ICF International. January 30, 2008.

### References 11-41 USDA (1991) State Soil Geographic (STATSG0) Data Base Data use information . Miscellaneous Publication Number 1492, National Soil Survey Center, Natural Resources Conservation Service, U.S. Department of Agriculture, Fort Worth, TX. Woodbury, P.B., L.S. Heath, and J.E. Smith (2007) Effects of land use change on soil carbon cycling in the conterminous United States from 1900 to 2050, Global Biogeochem. Cycles, 21, GB3006, doi:10.1029/2007GB002950. Woodbury, P.B., L.S. Heath, and J.E. Smith, (2006) “Land Use Change Effects on Forest Carbon Cycling Throughout the Southern United States.” Journal of Environmental Quality , 35:1348–1363. 

# Forest Land Remaining Forest Land: N 2 

# O Fluxes from Soils Binkley, D. (2004) Email correspondence regarding the 95% CI for area estimates of southern pine plantations receiving N fertilizer (±20%) and the rate applied for areas receiving N fertilizer (100 to 200 pounds/acre). Dan Binkley, Department of Forest, Rangeland, and Watershed Stewardship, Colorado State University and Stephen Del Grosso, Natural Resource Ecology Laboratory, Colorado State University. September 19, 2004. Binkley, D., R. Carter, and H.L. Allen (1995) Nitrogen Fertilization Practices in Forestry. In: Nitrogen Fertilization in the Environment , P.E. Bacon (ed.), Marcel Decker, Inc., New York. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. North Carolina State Forest Nutrition Cooperative (2002) 31 st 

### Annual Report. Available online at <http://www.ncsu. edu/ncsfnc>. Accessed October 2004. USDA Forest Service (2001) U.S. Forest Facts and Historical Trends . FS-696. U.S. Department of Agriculture Forest Service. Washington, DC. Available online at <http:// www.fia.fs.fed.us/library/ForestFactsMetric.pdf>. 

# Cropland Remaining Cropland, Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland: Changes in Agricultural Soil Carbon Stocks Allmaras, R.R., H.H. Schomberg, C.L. Douglas, Jr., and T.H. Dao (2000) “Soil organic carbon sequestration potential of adopting conservation tillage in U.S. croplands.” J Soil Water Conserv 55:365–373. Armentano, T.V. and J.T.A. Verhoeven (1990) “Biogeochemical Cycles: Global.” In B.C. Patten, et al. (eds.); Wetlands and Shallow Continental Water Bodies

. SPB Academic Publishing. The Hague, the Netherlands, Vol. I, 281–311. Brady, N.C. and R.R. Weil (1999) The Nature and Properties of Soils . Prentice Hall. Upper Saddle River, NJ, 881. CTIC (1998) “1998 Crop Residue Management Executive Summary.” Conservation Technology Information Center. West Lafayette, IN. Daly, C., R.P. Neilson, and D.L. Phillips (1994) “A Statistical-Topographic Model for Mapping Climatological Precipitation Over Mountainous Terrain.” Journal of Applied Meteorology 33:140–158. Edmonds, L., R. L. Kellogg, B. Kintzer, L. Knight, C. Lander, J. Lemunyon, D. Meyer, D.C. Moffitt, and J. Schaefer (2003) “Costs associated with development and implementation of Comprehensive Nutrient Management Plans.” Part I—Nutrient management, land treatment, manure and wastewater handling and storage, and recordkeeping

. Natural Resources Conservation Service, U.S. Department of Agriculture. Available online at <http://www.nrcs.usda. gov/technical/land/pubs/cnmp1.html>. EPA (1999) Biosolids Generation, Use and Disposal in the United States . Office of Solid Waste, U.S. Environmental Protection Agency. Available online at <http://biosolids. policy.net/relatives/18941.PDF>. EPA (1993) Federal Register. Part II. Standards for the Use and Disposal of Sewage Sludge; Final Rules. U.S. Environmental Protection Agency, 40 CFR Parts 257, 403, and 503. ERS. (1997) Cropping Practices Survey Data—1995

. Economic Research Service, United States Department of Agriculture. Available online at <http://www.ers.usda.gov/ data/archive/93018/>. Euliss, N., and R. Gleason (2002) Personal communication regarding wetland restoration factor estimates and restoration activity data. Ned Euliss and Robert Gleason of the U.S. Geological Survey, Jamestown, ND, to Stephen Ogle of the National Resource Ecology Laboratory, Fort Collins, CO. August 2002. FAO (2006) Yearly U.S. Total Horse Population Data from the Food and Agriculture Organization of the United Nations database. Available online at <http://faostat.fao.org/>. Accessed July 2006. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan.

### 11-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 IPCC (2003) Good Practice Guidance for Land Use, LandUse Change, and Forestry . The Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, J. Penman, et al., eds. August 13, 2004. Available online at <http://www.ipcc-nggip.iges.or.jp/public/ gpglulucf/gpglulucf.htm>. IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. Kellogg, R.L., C.H. Lander, D.C. Moffitt, and N. Gollehon (2000) Manure Nutrients Relative to the Capacity of Cropland and Pastureland to Assimilate Nutrients: Spatial and Temporal Trends for the United States . U.S. Department of Agriculture. Washington, DC. Publication number nps00- 0579. Lange, J. (2000) Personal Communication Lee-Ann Tracy, ERG and John Lange, Agricultural Statistician, U.S. Department of Agriculture, National Agriculture Statistics Service. Washington, DC. May 8, 2000. Metherell, A.K., L.A. Harding, C.V. Cole, and W.J. Parton (1993) “CENTURY Soil Organic Matter Model Environment.” Agroecosystem version 4.0. Technical documentation, GPSR Tech. Report No. 4, USDA/ARS, Ft. Collins, CO. NASS (2004) Agricultural Chemical Usage: 2003 Field Crops Summary . Report AgCh1(04)a. National Agricultural Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http://usda.mannlib. cornell.edu/reports/nassr/other/pcu-bb/agcs0504.pdf>. NASS (1999) Agricultural Chemical Usage: 1998 Field Crops Summary . Report AgCH1(99). National Agricultural Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http://usda.mannlib. cornell.edu/reports/nassr/other/pcu-bb/agch0599.pdf>. NASS (1992) Agricultural Chemical Usage: 1991 Field Crops Summary . Report AgCh1(92). National Agricultural Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http://usda.mannlib. cornell.edu/reports/nassr/other/pcu-bb/agch0392.txt>. NRCS (1999) “Soil Taxonomy: A basic system of soil classification for making and interpreting soil surveys, 2nd Edition.” Agricultural Handbook Number 436 , Natural Resources Conservation Service, U.S. Department of Agriculture. Washington, DC. NRCS (1997) “National Soil Survey Laboratory Characterization Data,” Digital Data, Natural Resources Conservation Service, U.S. Department of Agriculture. Lincoln, NE. NRCS (1981) “Land Resource Regions and Major Land Resource Areas of the United States,” USDA Agriculture Handbook 296 , United States Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Cente., Lincoln, NE, pp. 156. Ogle, S.M., F.J. Breidt, M. Easter, S. Williams and K. Paustian. (2007) “Empirically-Based Uncertainty Associated with Modeling Carbon Sequestration Rates in Soils.” Ecological Modeling 205:453–463. Ogle, S.M., F.J. Breidt, and K. Paustian. (2006) “Bias and variance in model results due to spatial scaling of measurements for parameterization in regional assessments.” Global Change Biology 12:516–523. Ogle, S.M., M.D. Eve, F.J. Breidt, and K. Paustian (2003) “Uncertainty in estimating land use and management impacts on soil organic carbon storage for U.S. agroecosystems between 1982 and 1997.” Global Change Biology 9:1521– 1542. Ogle, S., M. Eve, M. Sperrow, F.J. Breidt, and K. Paustian (2002) Agricultural Soil C Emissions, 1990-2001: Documentation to Accompany EPA Inventory Tables. Natural Resources Ecology Laboratory, Fort Collins, CO. Provided in an e-mail from Stephen Ogle, NREL to Barbara Braatz, ICF International. September 23, 2002. Parton, W.J., D.S. Ojima, C.V. Cole, and D.S. Schimel (1994) “A General Model for Soil Organic Matter Dynamics: Sensitivity to litter chemistry, texture and management.” In Quantitative Modeling of Soil Forming Processes . Special Publication 39, Soil Science Society of America, Madison, WI, 147–167. Parton, W.J., D.S. Schimel, C.V. Cole, D.S. Ojima (1987) “Analysis of factors controlling soil organic matter levels in Great Plains grasslands.” Soil Science Society of America Journal 51:1173–1179. Parton, W.J., J.W.B. Stewart, C.V. Cole. (1988) “Dynamics of C, N, P, and S in grassland soils: a model.” Biogeochemistry 5:109–131. Potter, C. S., J.T. Randerson, C.B. Fields, P.A. Matson, P.M. Vitousek, H.A. Mooney, and S.A. Klooster. (1993) “Terrestrial ecosystem production: a process model based on global satellite and surface data.” Global Biogeochemical Cycles 7:811–841. Reilly, J.M. and K.O. Fuglie. (1998) “Future yield growth in field crops: What evidence exists?” Soil Till Res47:275–290. Towery, D. (2001) Personal Communication. Dan Towery regarding adjustments to the CTIC (1998) tillage data to reflect long-term trends, Conservation Technology Information Center, West Lafayette, IN, and Marlen Eve, National Resource Ecology Laboratory. Fort Collins, CO. February 2001.

### References 11-43 USDA-FSA (2007) Conservation Reserve Program Summary and Enrollment Statistics FY 2006. U.S. Department of Agriculture, Farm Service Agency. Washington, D.C., Available online at <http://www.fsa.usda.gov/Internet/ FSA_File/06rpt.pdf>. USDA (2006a) Cattle . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 2006. Available online at <http://www.nass.usda. gov>. USDA (2006b) Cattle on Feed . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2006. Available online at <http://www.usda.gov/nass/ pubs/estindx1.htm>. USDA (2006c) Chicken and Eggs 2005 Summary

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. February 2006. Available online at <http://www.nass.usda.gov>. USDA (2006d) Poultry—Production and Value 2005 Summary . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2006. Available online at <http://www.nass.usda.gov>. USDA (2006e) Published Estimates Database . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http:// www.nass.usda.gov>. Accessed May 2006. USDA (2005a) Cattle . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 28, 2005. Available online at <http://www.usda.gov/ nass/pubs/estindx1.htm>. USDA (2005b) Cattle on Feed . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 21, 2005. Available online at <http://www.usda.gov/ nass/pubs/estindx1.htm>. USDA (2005c) Hogs and Pigs . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. March 24, 2005. Available online at <http://www.usda.gov/ nass/pubs/estindx1.htm>. USDA (2005d) Chicken and Eggs Annual Summary

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. February 2005. Available online at <http://www.usda.gov/nass/pubs/estindx1.htm>. USDA (2005e) Poultry Production and Value Annual Summary . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 28, 2005. Available online at <http://www.usda.gov/nass/pubs/ estindx1.htm>. USDA (2005f) Sheep and Goats . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 28, 2005. Available online at <http://www.usda.gov/nass/pubs/reportname.htm>. USDA (2005g) Census of Agriculture . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. Data for 1992, 1997, and 2002. Available online at <http://www.nass.usda.gov/census/>. June 2005. USDA (2004a) Cattle—Final Estimates 1999–2003

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2004. Available online at <http://usda.mannlib.cornell.edu/reports/general/sb/>. USDA (2004b) Hogs and Pigs—Final Estimates 1998–2002

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. March 2004. Available online at <http://usda.mannlib.cornell.edu/reports/general/sb/>. USDA (2004c) Chicken and Eggs—Final Estimates 1998–2003 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2004. Available online at <http://usda.mannlib.cornell.edu/reports/ general/sb/>. USDA (2004d) Poultry Production and Value—Final Estimates 1998–2002 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2004. Available online at <http://usda.mannlib.cornell. edu/reports/general/sb/>. USDA (2004e) Sheep and Goats—Final Estimates 1999–2003 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. April 2004. Available online at <http://usda.mannlib.cornell.edu/reports/ general/sb/>. USDA (2000) Chicken and Eggs—Final Estimates 1988–1993 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. Available online at <http://usda.mannlib.cornell.edu/data-sets/ livestock/95908/sb908.txt>. May 3, 2000. USDA (1999a) Cattle—Final Estimates 1994–98 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 1999. Available online at <http://www.nass.usda.gov:81/ipedb/>. USDA (1999b) Poultry Production and Value—Final Estimates 1994–97 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. March 1999. USDA (1999c) Sheep and Goats—Final Estimates 1994–1998 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 1999. USDA (1998a) Chicken and Eggs—Final Estimates 1994– 97 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. December 1998. USDA (1998b) Hogs and Pigs—Final Estimates 1993–97

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. December 1998. Available online at <http://www.nass.usda.gov:81/ipedb/>.

### 11-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 USDA (1995a) Cattle—Final Estimates 1989–93 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 1995. Available online at <http://www.nass.usda.gov:81/ipedb/>. USDA (1995b) Poultry Production and Value—Final Estimates 1989–1993 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. USDA (1994a) Hogs and Pigs—Final Estimates 1988–92

. National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. December 1994. Available online at <http://www.nass.usda.gov:81/ipedb/>. USDA (1994b) Sheep and Goats—Final Estimates 1989–1993 . National Agriculture Statistics Service, U.S. Department of Agriculture. Washington, DC. January 1994. USDA-NRCS (2000) Digital Data And Summary Report: 1997 National Resources Inventory . Revised December 2000. Resources Inventory Division, Natural Resources Conservation Service, United States Department of Agriculture. Beltsville, MD. 

# Liming and Urea AAPFCO (1995 through 2000, 2002 through 2007) Commercial Fertilizers . Association of American Plant Food Control Officials. University of Kentucky. Lexington, KY. AAPFCO (2000) 1999–2000 Commercial Fertilizers Data, ASCII files . Available from David Terry, Secretary, AAPFCO. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2003) Good Practice Guidance for Land Use, LandUse Change, and Forestry . The Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, J. Penman, et al., eds. August 13, 2004. Available online at <http://www.ipcc-nggip.iges.or.jp/public/ gpglulucf/gpglulucf.htm>. IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories

. Intergovernmental Panel on Climate Change, United NationsEnvironment Programme, Organization for Economic CoOperation and Development, International Energy Agency. Paris, France. Tepordei, V.V. (1997 through 2006) “Crushed Stone,” In Minerals Yearbook . U.S. Geological Survey. Washington, DC. Available online at <http://minerals.usgs.gov/minerals/ pubs/commodity/stone_crushed/index.html#mis>. Tepordei, V.V. (1996) “Crushed Stone,” In Minerals Yearbook 1994 . Bureau of Mines, U.S. Department of the Interior, Washington, DC. Available online at <http:// minerals.usgs.gov/minerals/pubs/commodity/stone_crushed/ index.html#mis>. Accessed August 2000. Tepordei, V.V. (1995) “Crushed Stone,” In Minerals Yearbook 1993 . Bureau of Mines, U.S. Department of the Interior, Washington, DC. pp. 1107–1147. Tepordei, V. V. (1994) “Crushed Stone,” In Minerals Yearbook 1992 . Bureau of Mines, U.S. Department of the Interior, Washington, DC. pp. 1279–1303. Tepordei, V.V. (1993) “Crushed Stone,” In Minerals Yearbook 1991 . Bureau of Mines, U.S. Department of the Interior, Washington, DC. pp. 1469–1511. Terry, D. (2007) Personal communication. David Terry, Fertilizer Regulatory program, University of Kentucky and David Berv, ICF International. September 7, 2007. TVA (1991 through 1994) Commercial Fertilizers . Tennessee Valley Authority, Muscle Shoals, AL. USGS (2007) Mineral Industry Surveys: Crushed Stone and Sand and Gravel in the First Quarter of 2007 . U.S. Geological Survey, Reston, VA. Available online at <http:// minerals.usgs.gov/minerals/pubs/commodity/stone_crushed/ index.html#mis>. USGS (2006) Mineral Industry Surveys: Crushed Stone and Sand and Gravel in the First Quarter of 2006 . U.S. Geological Survey, Reston, VA. Available online at <http:// minerals.usgs.gov/minerals/pubs/commodity/stone_crushed/ index.html#mis>. West, T.O., and A.C. McBride (2005) “The contribution of agricultural lime to carbon dioxide emissions in the United States: dissolution, transport, and net emissions,” Agricultural Ecosystems & Environment 108:145–154. Willett, J.C. (2007) “Crushed Stone,” In Minerals Yearbook 2005 . U.S. Geological Survey, Washington, DC. Available online at <http://minerals.usgs.gov/minerals/pubs/ commodity/stone_crushed/index.html#mis>. Accessed August 2007. 

# Settlements Remaining Settlements: Changes in Carbon Stocks in Urban Trees Cairns, M.A., S. Brown, E.H. Helmer, and G.A. Baumgardner (1997) “Root Biomass Allocation in the World’s Upland Forests.” Oceologia 111: 1–11. deVries, R.E. (1987) A Preliminary Investigation of the Growth and Longevity of Trees in Central Park . New Brunswick, NJ: Rutgers University, M.S. thesis.

### References 11-45 Dwyer, J.F., D.J. Nowak, M.H. Noble, and S.M Sisinni (2000) Connecting People with Ecosystems in the 21 st 

### Century: An Assessment of Our Nation’s Urban Forests

. General Technical Report PNW-GTR-490, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. Portland, OR. Fleming, L.E. (1988) Growth Estimation of Street Trees in Central New Jersey . M.S. thesis, Rutgers University. New Brunswick, NJ. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. Nowak, D.J. (2007a) “New York City’s Urban Forest.” Newtown Square, PA: USDA Forest Service, Feb 2007. Nowak, D.J. (2007b) Personal Communication. David Nowak, USDA Forest Service and Susan Asam, ICF International. September 25, 2007. Nowak, D.J. (2007c) E-mail correspondence regarding revised sequestration values and standard errors for sequestration values. David Nowak, USDA Forest Service to Susan Asam, ICF International. October 31, 2007. Nowak, D.J. (2002a) E-mail correspondence containing information on possible urban tree carbon and forest carbon overlap. David Nowak, USDA Forest Service to Barbara Braatz, ICF International. January 10, 2002. Nowak, D.J. (2002b) E-mail correspondence regarding significant digits. David Nowak, USDA Forest Service to Barbara Braatz, ICF International. October 29, 2002. Nowak, D.J. (1994) “Atmospheric Carbon Dioxide Reduction by Chicago’s Urban Forest.” In: E.G. McPherson, D.J. Nowak, and R.A. Rowntree (eds.); Chicago’s Urban Forest Ecosystem: Results of the Chicago Urban Forest Climate Project . U.S. Department of Agriculture Forest Service General Technical Report NE-186. Radnor, PA, 83–94. Nowak, D.J., (1986) “Silvics of an Urban Tree Species: Norway Maple (Acer platanoides L. ).” M.S. thesis, College of Environmental Science and Forestry, State University of New York. Syracuse, NY. Nowak, D.J. and D.E. Crane (2002) “Carbon Storage and Sequestration by Urban Trees in the United States.” Environmental Pollution 116(3): 381–389. Nowak, D.J., D.E. Crane, J.C. Stevens, and M. Ibarra (2002) Brooklyn’s Urban Forest . General Technical Report NE-290, U.S. Department of Agriculture Forest Service. Newtown Square, PA. Nowak, D.J., M.H. Noble, S.M. Sisinni, and J.F. Dwyer (2001) “Assessing the U.S. Urban Forest Resource.” Journal of Forestry 99(3):37–42. Nowak, D.J., J.T. Walton, L.G. Kaya, and J.F. Dwyer (2005) “The Increasing Influence of Urban Environments on U.S. Forest Management.” Journal of Forestry

. Smith, W.B. and S.R. Shifley (1984) Diameter Growth, Survival, and Volume Estimates for Trees in Indiana and Illinois . Res. Pap. NC-257. North Central Forest Experiment Station, U.S. Department of Agriculture Forest Service. St. Paul, MN. 

# Settlements Remaining Settlements: N 2 

# O Fluxes from Soils IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. Ruddy B.C., D.L. Lorenz, and D.K. Mueller (2006) Countylevel estimates of nutrient inputs to the land surface of the conterminous United States , 1982–2001. Scientific Investigations Report 2006–5012. U.S. Department of the Interior. 

# Other: Changes in Yard Trimming and Food Scrap Carbon Stocks in Landfills Barlaz, M.A. (2008) “Re: Corrections to Previously Published Carbon Storage Factors.” Memorandum to Randall Freed, ICF International. February 28, 2008. Barlaz, M.A. (2005) “Decomposition of Leaves in Simulated Landfill.” Letter report to Randall Freed, ICF Consulting. June 29, 2005. Barlaz, M.A. (1998) “Carbon Storage during Biodegradation of Municipal Solid Waste Components in Laboratory-Scale Landfills.” Global Biogeochemical Cycles 12: 373–380. Eleazer, W.E., W.S. Odle, Y. Wang, and M. Barlaz (1997) “Biodegradability of Municipal Solid Waste Components in Laboratory-Scale Landfills” Environmental Science Technology , 31: 911–917. EPA (2006, 2007) Municipal Solid Waste in the United States: Facts and Figures . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www. epa.gov/epaoswer/non-hw/muncpl/msw99.htm>. EPA (2005) Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and Figures for 2003 Facts and Figures . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www. epa.gov/epaoswer/non-hw/muncpl/pubs/msw05rpt.pdf>.

### 11-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 EPA (2005a) Municipal Solid Waste in the United States: 2003 Data Tables . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www.epa.gov/ epaoswer/non-hw/muncpl/pubs/03data.pdf>. EPA (2003) Characterization of Municipal Solid Waste in the United States: 2001 Update . (Draft) Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. EPA. Washington, DC. EPA (1999) Characterization of Municipal Solid Waste in the United States: 1998 Update . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. IPCC (2003) Good Practice Guidance for Land Use, LandUse Change, and Forestry . The Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, J. Penman, et al., eds. August 13, 2004. Available online at <http://www.ipcc-nggip.iges.or.jp/public/ gpglulucf/gpglulucf.htm>. Oshins, C., and D. Block (2000) “Feedstock Composition at Composting Sites.” BioCycle 41(9):31-34. Schneider, S. (2007 through 2008) Email correspondence. Shelly Schneider, Franklin Associates, and Sarah Shapiro, ICF International. Tchobanoglous, G., H. Theisen, and S.A. Vigil (1993) Integrated Solid Waste Management, 1 st 

### edition . McGrawHill, NY. Cited by Barlaz (1998).


# Waste

Landfills 40 CFR Part 60, Subpart Cc (2005) Emission Guidelines and Compliance Times for Municipal Solid Waste Landfills, 60.30c--60.36c, Code of Federal Regulations, Title 40. Available online at <http://www.access.gpo.gov/nara/cfr/ waisidx_05/40cfr60_05.html>. 40 CFR Part 60, Subpart WWW (2005) Standards of Performance for Municipal Solid Waste Landfills, 60.750--60.759, Code of Federal Regulations, Title 40. Available online at <http://www.access.gpo.gov/nara/cfr/ waisidx_05/40cfr60_05.html>. Bingemer, H. and J. Crutzen (1987) “The Production of Methane from Solid Wastes,” Journal of Geophysical Research , 92:2181–2187. BioCycle (2006) “15 th

### Annual BioCycle Nationwide Survey: The State of Garbage in America” By P. Simmons, N. Goldstein, S. Kaufman, N. Goldstein, N. Themelis, and J. Thompson. BioCycle . April 2006. Czepiel, P., B. Mosher, P. Crill, and R. Harriss (1996) “Quantifying the Effect of Oxidation on Landfill Methane Emissions.” Journal of Geophysical Research
, 101(D11):16721–16730. EIA (2007) Voluntary Greenhouse Gas Reports for EIA Form 1605B (Reporting Year 2005). Available online at <ftp://ftp. eia.doe.gov/pub/oiaf/1605/cdrom/>. EPA (2007) Landfill Gas-to-Energy Project Database

. Landfill Methane and Outreach Program. July 2007. EPA (2005) Municipal Solid Waste in the United States: 2003 Facts and Figures . U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response., Washington, DC. Available online at <http://www.epa.gov/ epaoswer/non-hw/muncpl/msw99.htm>. EPA (1998) Compilation of Air Pollution Emission Factors, Publication AP-42 , Section 2.4 Municipal Solid Waste Landfills. November 1998. EPA (1993) Anthropogenic Methane Emissions in the United States, Estimates for 1990: Report to Congress
, U.S. Environmental Protection Agency, Office of Air and Radiation. Washington, DC. EPA/430-R-93-003. April 1993. EPA (1988) National Survey of Solid Waste (Municipal) Landfill Facilities , U.S. Environmental Protection Agency. Washington, DC. EPA/530-SW-88-011. September 1988. ERG (2007). Production Data Supplied by ERG for 1990– 2006 for Pulp and Paper, Fruits and Vegetables, and Meat. July 2007. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. Jensen, J.E.F., and R. Pipatti (2002) “CH 4 

### Emissions from Solid Waste Disposal.” Background paper for the Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories. Mancinelli, R. and C. McKay (1985) “Methane-Oxidizing Bacteria in Sanitary Landfills.” Proc. First Symposium on Biotechnical Advances in Processing Municipal Wastes for Fuels and Chemicals , Minneapolis, MN, 437–450. August 1985. Minz C., R. Feed, and M. Walsh (2003) “Timeline of Anaerobic Land Disposal of Solid Waste.” Memorandum to T. Wirth (EPA) and K. Skog (USDA), December 31, 2003.

### References 11-47 Peer, R., S. Thorneloe, and D. Epperson (1993) “A Comparison of Methods for Estimating Global Methane Emissions from Landfills.” Chemosphere , 26(1–4):387–400. RTI (2004) Documentation for Changes to the Methodology for the Inventory of Methane Emissions from Landfills. September 2004. Solid Waste Association of North America (SWANA) (1998) Comparison of Models for Predicting Landfill Methane Recovery . Publication No. GR-LG 0075. March 1998. U.S. Bureau of Census (2007) International Data Base. July 2007. Available online at <http://www.census.gov/ipc/ www/idb/>. U.S. Department of Agriculture (2003) U.S. Timber Production, Trade, Consumption, and Price Statistics 1965–2002 . Research Paper FPL-RP-615. Available online at <http://permanent.access.gpo.gov/lps5730/1965-2002/fplrp615.pdf#search=%22research%20paper%20fpl-rp615%22>. December 2003. Weitz, K. and M. Bahner (2006) “Methane Emissions for Industrial Landfills.” Memorandum to M. Weitz (EPA). September 5, 2006.



# Wastewater Treatment ARCADIS (2004) “Response to ERG Review and New US M&P estimates.” Memorandum from M. Doorn, ARCADIS to D. Pape, ICF International and E. Scheehle, U.S. Environmental Protection Agency. August 16, 2004. Beecher et al. (2007) “A National Biosolids Regulation, Quality, End Use & Disposal Survey, Preliminary Report.” Northeast Biosolids and Residuals Association. April 14, 2007. Donovan (1996) Siting an Ethanol Plant in the Northeast

. C.T. Donovan Associates, Inc. Report presented to Northeast Regional Biomass Program (NRBP). (April). Available online at <http://www.nrbp.org/pdfs/pub09.pdf>. Accessed October 2006. EIA (2006) U.S. Department of Energy—Energy Information Administration (EIA). Annual Energy Outlook 2006 with Projections to 2030. DOE/EIA-0383(2006). (February). Available online at <http://www.eia.doe.gov/oiaf/aeo/gas. html>. Date Accessed: October 2006. EPA (2004a) Clean Watersheds Needs Survey 2004 - Report to Congress . U.S. Environmental Protection Agency, Office of Wastewater Management. Washington, DC. EPA (2004b) Technical Development Document for the Final Effluent Limitations Guidelines and Standards for the Meat and Poultry Products Point Source Category (40 CFR 432)

. Office of Water, U.S. Environmental Protection Agency. Washington, DC, EPA-821-R-04-011. July 2004. EPA (2002) Development Document for the Proposed Effluent Limitations Guidelines and Standards for the Meat and Poultry Products Industry Point Source Category (40 CFR 432) . Office of Water, U.S. Environmental Protection Agency. Washington, DC, EPA-821-B-01-007. January 2002. EPA (2000) Clean Watersheds Needs Survey 2000 - Report to Congress . Office of Wastewater Management, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www.epa.gov/owm/mtb/ cwns/2000rtc/toc.htm>. Accessed July 2007. EPA (1999) Biosolids Generation, Use and Disposal in the United States . Office of Solid Waste and Emergency Response, U.S. Environmental Protection Agency. Washington, DC, EPA530-R-99-009. September 1999. EPA (1998) “AP-42 Compilation of Air Pollutant Emission Factors.” Chapter 2.4, Table 2.4-3, page 2.4-13. Available online at <http://www.epa.gov/ttn/chief/ap42/ch02/final/ c02s04.pdf>. EPA (1997a) Estimates of Global Greenhouse Gas Emissions from Industrial and Domestic Wastewater Treatment . Office of Policy, Planning, and Evaluation, U.S. Environmental Protection Agency. Washington, DC, EPA-600/R-97-091. September 1997. EPA (1997b) Supplemental Technical Development Document for Effluent Guidelines and Standards (Subparts B & E). EPA-821-R-97-011 . Office of Water, U.S. Environmental Protection Agency. Washington, DC. October 1997. EPA (1996) 1996 Clean Water Needs Survey Report to Congress. Assessment of Needs for Publicly Owned Wastewater Treatment Facilities, Correction of Combined Sewer Overflows, and Management of Storm Water and Nonpoint Source Pollution in the United States . Office of Wastewater Management, U.S. Environmental Protection Agency. Washington, DC. Available online at <http://www. epa.gov/owm/mtb/cwns/1996rtc/toc.htm>. Accessed July 2007. EPA (1993a) Anthropogenic Methane Emissions in the U.S.: Estimates for 1990, Report to Congress . Office of Air and Radiation, U.S. Environmental Protection Agency. Washington, DC. April 1993. EPA (1993b) Development Document for the Proposed Effluent Limitations Guidelines and Standards for the Pulp, Paper and Paperboard Point Source Category . EPA-821- R-93-019. Office of Water, U.S. Environmental Protection Agency. Washington, DC. October 1993. EPA (1992) Clean Watersheds Needs Survey 1992 - Report to Congress . Office of Wastewater Management, U.S. Environmental Protection Agency. Washington, DC.

### 11-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990 –2006 EPA (1975) Development Document for Interim Final and Proposed Effluent Limitations Guidelines and New Source Performance Standards for the Fruits, Vegetables, and Specialties Segment of the Canned and Preserved Fruits and Vegetables Point Source Category. Office of Water, United States Environmental Protection Agency. EPA-440/1-75-046. Washington, DC. October 1975. EPA (1974) Development Document for Effluent Limitations Guidelines and New Source Performance Standards for the Apple, Citrus, and Potato Processing Segment of the Canned and Preserved Fruits and Vegetables Point Source Category

. Office of Water, U.S. Environmental Protection Agency. Washington, DC, EPA-440/1-74-027-a. March 1974. ERG (2006) Memorandum: Assessment of Greenhouse Gas Emissions from Wastewater Treatment of U.S. Ethanol Production Wastewaters. Prepared for Melissa Weitz, EPA. 10 October 2006. ESE (1975) Draft Development Document for Effluent Limitations Guidelines and new Source Performance Standards for the Miscellaneous Foods and Beverages Point Source Category . Prepared by Environmental Science and Engineering, Inc. for U.S. EPA. February 1975. Great Lakes-Upper Mississippi River Board of State and Provincial Public Health and Environmental Managers. (2004) Recommended Standards for Wastewater Facilities (Ten-State Standards)

. Holman (2006a) Personal Communication. Steven Williams, Iowa Department of Natural Resources, Wastewater Division, NPDES Permits and Sarah Holman, ERG. “Ethanol Production Facilities - VeraSun Energy Corp., NPDES ID No. IA0079227.” August 31, 2006. Holman (2006b) Personal Communication. Kelly Buscher, South Dakota Department of Environment and Natural Resources, Surface Water Discharge Permits and Sarah Holman, ERG. “South Dakota Ethanol Production Facilities - Dakota Ethanol, NPDES ID No. SD0027847.” September 1, 2006. Holman (2006c) Personal Communication. Dr. Joe Ruocco, Phoenix Bio-Systems and Sarah Holman, ERG. “Bio-Methanator Units at Ethanol Production Facilities.” September 5, 2006. Holman (2006d) Personal Communication. Peggi Badten, City of Aberdeen, South Dakota and Sarah Holman, ERG. “South Dakota Ethanol Production Facilities - Heartland Grain Fuels, LP.” September 6, 2006. Holman (2006e) Personal Communication. Ron Ash, Nebraska Department of Environmental Quality, Water Division, NPDES Program and Sarah Holman, ERG. “Nebraska Ethanol Production Facilities - Chief Ethanol, NPDES ID No. NE0114243.” September 7, 2006. Holman (2006f) Personal Communication. Matt Gluckman, U.S. EPA, Region 5, WN-16J and Sarah Holman, ERG. “Region 5 Ethanol Production Facilities - New Energy Corp. and MGPI.” September 19, 2006. Holman (2006g) Personal Communication. Dr. Ann Wilkie, University of Florida, Soil and Water Science Department and Sarah Holman, ERG. “Wastewater stillage from ethanol production facilities.” September 20, 2006. Holman (2006h) Personal Communication. Mike Pring, ERG and Sarah Holman, ERG. “Emissions from ethanol production facilities.” September 7, 2006. IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T. Ngara, and K. Tanabe (eds.). Hayama, Kanagawa, Japan. LBNL (2003) Lawrence Berkeley National Laboratory (LBNL). Energy Efficiency Improvement and Cost Saving Opportunities for the Corn Wet Milling Industry: An ENERGY STAR ® 

### Guide for Energy and Plant Managers. LBNL-52307. July. Available online at <http://ies.lbl.gov/ iespubs/52307.pdf>. Accessed October 2006. Lockwood-Post (2002) Lockwood-Post’s Directory of Pulp, Paper and Allied Trades, Miller-Freeman Publications. San Francisco, CA. Merrick (1998) Wastewater Treatment Options for the Biomass-to-Ethanol Process. Report presented to National Renewable Energy Laboratory (NREL). Merrick & Company. Subcontract No. AXE-8-18020-01. October 22, 1998. Metcalf & Eddy, Inc. (2003) Wastewater Engineering: Treatment, Disposal and Reuse, 4 th 

### ed. McGraw Hill Publishing. Metcalf & Eddy, Inc. (1991) Wastewater Engineering: Treatment, Disposal and Reuse, 3 rd

### ed . McGraw Hill Publishing. Nemerow, N.L. and A. Dasgupta (1991) Industrial and Hazardous Waste Treatment. Van Nostrand Reinhold. NY. ISBN 0-442-31934-7. NRBP (2001) Northeast Regional Biomass Program. An Ethanol Production Guidebook for Northeast States

. Washington, D.C. (May 3). Available online at <http://www. nrbp.org/pdfs/pub26.pdf>. Accessed October 2006. Paper 360o (2007) “U.S. production rises slightly in December.” March 2007. Available online at <http://www. thefreelibrary.com/U.S.+production+rises+slightly+in+Dece mber.(The+Pulse)-a0161909243>. Accessed June 2007. PBS (2006) General Project Experience: Anaerobic. Phoenix Bio-Systems. Available online at <http://www.pbiosystems. com/experience.htm>. Accessed October 2006. Pulp and Paper (2006) “AF&PA projects more capacity losses this year, small gains in 2007–08.” April 2006.

### References 11-49 Pulp and Paper (2005) “U.S. paper/board production rises in 2004 to 91.47 million tons.” April 2005. Pulp and Paper (2003–2006) “Month in Statistics.” January 2003–June 2006. Rausch (2006) “The Future of Coproducts from Corn Processing.” Applied Biochemistry and Biotechnology. 128: 47-86. Available online at <http://www.ag-bioeng.uiuc.edu/ fbe/FBE%20web%20downloads/The%20future%20of%20 coproducts%20from%20corn%20processing.pdf>. Accessed October, 2006. Renewable Fuels Association (2006) Historic U.S. Fuel Ethanol Production. Available online at <http://www. ethanolrfa.org/industry/statistics/>. Accessed June 2007. Ruocco (2006a) Email correspondence. Dr. Joe Ruocco, Phoenix Bio-Systems and Sarah Holman, ERG. “Capacity of Bio-Methanators (Dry Milling).” October 6, 2006. Ruocco (2006b) Email correspondence. Dr. Joe Ruocco, Phoenix Bio-Systems and Sarah Holman ,ERG. “Capacity of Bio-Methanators (Wet Milling).” October 16, 2006. Scheehle, E.A., and Doorn, M.R. (2001) “Improvements to the U.S. Wastewater Methane and Nitrous Oxide Emissions Estimate.” July 2001. U.S. Census Bureau (2007a) International Database. Available online at <http://www.census.gov/ipc/www/ idb/> and <http://www.census.gov/ipc/www/idbprint.html>. Accessed July 2007. U.S. Census Bureau (2007b) “American Housing Survey.” Table 1A-4: Selected Equipment and Plumbing--All Housing Units. From 1989, 1991, 1993, 1995, 1997, 1999, 2001, 2003 and 2005 reports. Available online at <http://www.census. gov/hhes/www/housing/ahs/nationaldata.html>. Accessed July 2007. USDA (2007a) National Agricultural Statistics Service. Washington, DC. Available online at <http://www.nass.usda. gov/Publications/Ag_Statistics/index.asp> and <http://www. nass.usda.gov/Data_and_Statistics/Quick_Stats/>. Accessed July 2007. USDA (2007b) U.S. Food Supply: Nutrients and Other Food Components, Per Capita Per Day. Economic Research Service, U.S. Department of Agriculture. Washington DC. Available online at <http://www.ers.usda.gov/Data/ FoodConsumption/spreadsheets/nutrients07.xls#Totals!a1>. Accessed July 2007. USDA (2005) United States Department of Agriculture (USDA). Office of Energy Policy and New Uses. USDA’s 2002 Ethanol Cost-of-Production Survey. Agricultural Economic Report Number 841. July. USPoultry (2006) Email correspondence. John Starkey, USPOULTRY and D. Bartram, ERG. August 30, 2006. White and Johnson (2003) White, P.J. and Johnson, L.A. Editors. Corn: Chemistry and Technology. 2nd ed. AACC Monograph Series. American Association of Cereal Chemists. St. Paul, MN. World Bank (1999) Pollution Prevention and Abatement Handbook 1998 , Toward Cleaner Production. The International Bank for Reconstruction and Development, The World Bank, Washington, DC. ISBN 0-8213-3638-X.



# Waste Sources of Indirect Greenhouse Gas Emissions EPA (2008) Air Emissions Trends - Continued Progress Through 2006. U.S. Environmental Protection Agency. Washington, DC. December 19, 2006. Available online at <http://www.epa.gov/air/airtrends/index.html>. EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data. Office of Air Pollution and the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency (EPA). December 22, 2003. EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42 . Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Research Triangle Park, NC. October 1997.

## 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 (SF 6 ) 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 Environmental Protection Agency

EPA 430-R-08-005 April 2008 Office of Atmospheric Programs (6207J) Washington, DC 20460

Official Business Penalty for Private Use $300

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