1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
EPA xxx-x-xx-xxx
Inventory of U.S. Greenhouse Gas Emissions and Sinks:
1990-2005
DRAFT for Public Review
February 20,2007
U.S. Environmental Protection Agency
1200 Pennsylvania Ave., N.W.
Washington, DC 20460
U.S.A.
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Public Review Draft
[Inside Front Cover]
HOW TO OBTAIN COPIES
Yi»ii iiineiil:il Publications (\S( l !lJi ;ii (Sinn 4,Jii-,;|,js. or\ isii ihe web sue ;ibo\e ;ind
eliek dm 'order online" alter selcclnm ;m edition
\ll d;il;i tables dI"lliis document arc ;i\ ;iil;ihle for llie lull lime series I'wo throudi 2<»>4. melusi\ e. ;il llie internet
sile mentioned abo\ e.
FOR FURTHER INFORMATION
Contact Mr. Leif Hockstad, Environmental Protection Agency, (202) 343-9432, hockstad.leif@epa.gov.
Or Ms. Lisa Hanle, Environmental Protection Agency, (202) 343-9434, hanle.lisa@epa.gov.
For more information regarding climate change and greenhouse gas emissions, see the EPA web site at
.
Released for printing: xxxx
[INSERT DISCUSSION OF COVER DESIGN]
ii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
Acknowledgments
The l\u\ iroiinieul;il Rrolecliou \ueuc\ would like Id iickuow ledize the ni;ni\ indi\ idn;il ;uid oru;uii/;iliou;il
coiiiribulors U) iliis document. w ilhoiil w hose efforts llns report would ik>I he complete. Mlhoimh llie complete IN
dI" researchers. uo\ criinicul employees. ;ind consultants w |r< Ii;i\ e pro\ ided lcchuic;il ;md edilori;il support is loo
louu Id list here. I\IJ Vs ()l'l'iee of \iniospheric lJrour;inis would like to Ili;ink siime ke\ contributors ;md re\ icwers
whose work h;is smiiil'ic;iuil\ impro\ed llns \e;ir's repori
Work on fuel eombiisiioii ;md iiidiisiruil proeess emissions w;is led h\ l.eif I loeks|;id ;md Joii;iiIi;iii I.uhelskv Work
on melhiiiie emissions from I he enerus seelor w;is direeled In l.isn I hinle C;iIciiI;iiioiis lor I he w;isie seelor were
led In Meliss;i Weil/ Work on imriculiure seelor emissions w;is direeled In l oin Wirili ;iud k;ilhr\ u liiekel l oin
W i rili led I he prep;ir;iiioii ol' llie ehnpier on I .;iud I se. I .;iud-l se ( h;iime. ;md forest r\. Work on emissions ol'
lll-'('s. IJI'( s. ;md SI' w;is directed In Debonih ()iiiimer ;md l);i\ e (iodw in John l);i\ ies direeled I he work on
mobile combustion.
Wilhin ihe IP \. other ()ITices ;ilso contributed d;il;i. ;m;il> sis ;md lechiiicnl re\ lew lor lhis repori I lie ()ITice ol'
Tmuspori;iiioii ;uid \ir Oii;ilil\ ;uid the ()Hice ol' Air Ou;ihi\ lJl;iuuiim ;iud St;iud;irds pro\ ided ;m;il\ sis ;uid re\ iew
lor se\ er;il ol' the source cnleuories addressed in this repori. The ()Hice ol' Solid W;iste ;iud the ()Hice ol' Research
;uid I)e\ elopnieui ;ilso coiiiribuied ;m;il\sis ;uid research.
The I jierus lufornuiliou \dmiuisir;ilioii ;iud llie l)ep;irimeul ol' I jierus coiiiribuied iiin ;ilu;ible d;il;i ;iud ;m;il\ sis oil
numerous eiieruv-rekiled topics The I S forest Ser\ ice prepared llie loresi c;irbon iii\cuior\. ;uid the l)ep;irimeiit
ol' \uriculliire s \uricullur;il Research Ser\ ice ;uid the \;ilur;il Resource l\colou\ l.;ibor;ilor\ ;il Colorado St;iie
I iii\ersit\ coiiiribuied le;idmu research on miroiis o\ide ;md c;irbon l'lu\es from soils
()lher uo\ eriinieui ;meucies h;i\ e coiiiribuied d;il;i ;is well, including llie I S (icolouicnl Sur\ e\. llie l'eder;il
II iuIiw ;i\ '\diuimsir;iiioii. llie l)ep;irimeui ol Tr;iiisporl;itiou. I he I >u re;iu ol Tr;iiispori;itioii Si;iiisiics. llie Depmimeui
of Commerce. llie N;ilion;il \uriculiur;il Suiiisiics Ser\ ice. llie l'eder;il A\ union \dniuiisir;iiioii. mid llie l)ep;irimeui
ol' Defense
We would ;ilso like lo lliiink \l;iri;ui \1;irlin Y;ui Pel I. R;uid;ill freed. ;uid lhcirsi;il'f ;ii I (' I ¦" Cousulliim's fucrus
lJolic> ;md lJrour;inis Puclice. iiicludiim John Veue/i;i. Dun Robinson. Di;iu;i lJ;ipe. Sus;ui \s;im. Mich;iel (n';iiil.
R;i\ i K;iiil;i11i;iilei11. Roberi l.;in/;i. Chris Sieuer. L;iureu fliuu. k;ini;il;i l;i\;ii';ini;in. I);in I.ieberni;iu. Jerems
Sch;irfcubcru. I);miel K;irue>. /.eph\ r T;i\ lor. I'.elli Moore. Mollie \\er\l. S;ir;ih Sluipiro. C;irol Wiuufield. I>ii;iii
(nllis. /.;ich;ir> Schjifl'er. \ meet \uu;irw;il. Colin \1c(iro;iri\. I leni;iui \l;ill\:i. Liureu IVderson. frm l'r;iser. Joseph
11 eir. \'iclori;i Thompson. ;iud lobs \ l;i uclel lor s\ iilhesi/.iuu I his repori ;md prep;irum ni;ni\ ol' llie iudi\ idu;il
;ui;il\ses I !;isiern Research (iroup. RTI lulerii;ilioii;il. R;i\eu Ridue Resources. ;md \rc;idis ;ilso pro\ ided
si'_iiiilic;iiil ;iu;il\ iic;il suppori
-------
Public Review Draft
1 Preface
2 The United States Environmental Protection Agency (EPA) prepares the official U.S. Inventory of Greenhouse Gas
3 Emissions and Sinks to comply with existing commitments under the United Nations Framework Convention on
4 Climate Change (UNFCCC).1 Under decision 3/CP.5 of the UNFCCC Conference of the Parties, national
5 inventories for UNFCCC Annex I parties should be provided to the UNFCCC Secretariat each year by April 15.
6 In an effort to engage the public and researchers across the country, the EPA has instituted an annual public review
7 and comment process for this document. The availability of the draft document is announced via Federal Register
8 Notice and is posted on the EPA web site.2 Copies are also mailed upon request. The public comment period is
9 generally limited to 30 days; however, comments received after the closure of the public comment period are
10 accepted and considered for the next edition of this annual report.
1 See Article 4(1 )(a) of the United Nations Framework Convention on Climate Change .
2 See .
ii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
Public Review Draft
Table of Contents
ACKNOWLEDGMENTS I
TABLE OF CONTENTS III
LIST OF TABLES, FIGURES, AND BOXES VI
Tables vi
Figures xiv
Boxes xvi
EXECUTIVE SUMMARY ES-1
Background Information ES-2
Recent Trends in U.S. Greenhouse Gas Emissions and Sinks ES-4
Overview of Sector Emissions and Trends ES-11
Other Information ES-14
1. INTRODUCTION 1-1
1.1. Background Information 1 -2
1.2. Institutional Arrangements 1-9
1.3. Inventory Process 1-9
1.4. Methodology and Data Sources 1-11
1.5. Key Categories 1-12
1.6. Quality Assurance and Quality Control (QA/QC) 1-14
1.7. Uncertainty Analysis of Emission Estimates 1-15
1.8. Completeness 1-16
1.9. Organization of Report 1-16
2. TRENDS IN GREENHOUSE GAS EMISSIONS 2-1
2.1. Recent Trends in U.S. Greenhouse Gas Emissions 2-1
2.2. Emissions by Economic Sector 2-23
2.3. Indirect Greenhouse Gas Emissions (CO, NOx, NMVOCs, and S02) 2-31
3. ENERGY 3-1
3.1. Carbon Dioxide Emissions from Fossil Fuel Combustion (IPCC Source Category 1A) 3-3
3.2. Carbon Emitted from Non-Energy Uses of Fossil Fuels (IPCC Source Category 1A) 3-19
3.3. Stationary Combustion (excluding C02) (IPCC Source Category 1A) 3-24
3.4. Mobile Combustion (excluding C02) (IPCC Source Category 1A) 3-29
3.5. Coal Mining (IPCC Source Category lBla) 3-36
3.6. Abandoned Underground Coal Mines (IPCC Source Category lBla) 3-39
3.7. Petroleum Systems (IPCC Source Category lB2a) 3-42
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
3.8. Natural Gas Systems (IPCC Source Category lB2b) 3-45
3.9. Municipal Solid Waste Combustion (IPCC Source Category 1A5) 3-50
3.10. Energy Sources of Indirect Greenhouse Gas Emissions 3-53
3.11. International Bunker Fuels (IPCC Source Category 1: Memo Items) 3-54
3.12. Wood Biomass and Ethanol Consumption (IPCC Source Category 1A) 3-58
4. INDUSTRIAL PROCESSES 4-1
4.1. Cement Manufacture (IPCC Source Category 2A1) 4-4
4.2. Iron and Steel Production (IPCC Source Category 2C1) 4-6
4.3. Ammonia Manufacture and Urea Application (IPCC Source Category 2B1) 4-10
4.4. Lime Manufacture (IPCC Source Category 2A2) 4-13
4.5. Limestone and Dolomite Use (IPCC Source Category 2A3) 4-17
4.6. Soda Ash Manufacture and Consumption (IPCC Source Category 2A4) 4-20
4.7. Titanium Dioxide Production (IPCC Source Category 2B5) 4-23
4.8. Ferroalloy Production (IPCC Source Category 2C2) 4-25
4.9. Phosphoric Acid Production (IPCC Source Category 2B5) 4-27
4.10. Carbon Dioxide Consumption (IPCC Source Category 2B5) 4-31
4.11. Zinc Production (IPCC Source Category 2C5) 4-33
4.12. Lead Production (IPCC Source Category 2C5) 4-36
4.13. Petrochemical Production (IPCC Source Category 2B5) 4-38
4.14. Silicon Carbide Production (IPCC Source Category 2B4) and Consumption 4-41
4.15. Nitric Acid Production (IPCC Source Category 2B2) 4-43
4.16. Adipic Acid Production (IPCC Source Category 2B3) 4-44
4.17. Substitution of Ozone Depleting Substances (IPCC Source Category 2F) 4-47
4.18. HCFC-22 Production (IPCC Source Category 2E1) 4-50
4.19. Electrical Transmission and Distribution (IPCC Source Category 2F7) 4-51
4.20. Semiconductor Manufacture (IPCC Source Category 2F6) 4-55
4.21. Aluminum Production (IPCC Source Category 2C3) 4-59
4.22. Magnesium Production and Processing (IPCC Source Category 2C4) 4-64
4.23. Industrial Sources of Indirect Greenhouse Gases 4-66
5. SOLVENT AND OTHER PRODUCT USE 5-1
5.1. Nitrous Oxide Product Usage (IPCC Source Category 3D) 5-1
5.2. Indirect Greenhouse Gas Emissions from Solvent Use 5-4
6. AGRICULTURE 6-1
6.1. Enteric Fermentation (IPCC Source Category 4A) 6-2
6.2. Manure Management (IPCC Source Category 4B) 6-6
6.3. Rice Cultivation (IPCC Source Category 4C) 6-12
iv Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Public Review Draft
6.4.
Agricultural Soil Management (IPCC Source Category 4D)
6-16
6.5.
Field Burning of Agricultural Residues (IPCC Source Category 4F)
6-29
7.
LAND USE, LAND-USE CHANGE, AND FORESTRY
7-1
7.1.
Forest Land Remaining Forest Land
7-3
7.2.
Land Converted to Forest Land (IPCC Source Category 5A2)
7-17
7.3.
Cropland Remaining Cropland (IPCC Source Category 5B1)
7-17
7.4.
Land Converted to Cropland (IPCC Source Category 5B2)
7-26
7.5.
Grassland Remaining Grassland (IPCC Source Category 5C1)
7-29
7.6.
Land Converted to Grassland (IPCC Source Category 5C2)
7-34
7.7.
Settlements Remaining Settlements
7-37
7.8.
Land Converted to Settlements (Source Category 5E2)
7-42
7.9.
Other (IPCC Source Category 5G)
7-42
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.
Waste Sources of Indirect Greenhouse Gases
8-15
9.
OTHER
9-1
10.
RECALCULATIONS AND IMPROVEMENTS
10-1
11.
REFERENCES
11-1
v
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
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 C02 Eq.) ES-4
Table ES-3: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.) ES-7
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)ES-
11
Table ES-5: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) ES-13
Table ES-6: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) ES-13
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq.) ES-14
Table ES-8: U.S Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions Distributed
(Tg C02 Eq.) ES-15
Table ES-9: Recent Trends in Various U.S. Data (Index 1990 = 100) and Global Atmospheric C02 Concentration
ES-16
Table ES-10: Emissions of NOx, CO, NMVOCs, and S02 (Gg) ES-17
Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and Atmospheric Lifetime (years) of
Selected Greenhouse Gases 1-3
Table 1-2: Global Warming Potentials and Atmospheric Lifetimes (Years) Used in this Report 1-7
Table 1-3: Comparison of 100-Year GWPs 1-8
Table 1-4: Key Categories for the United States (1990-2005) Based on Tier 1 Approach 1-12
Table 1-5. Estimated Overall Inventory Quantitative Uncertainty (Tg C02 Eq. and Percent) 1-15
Table 1-6: IPCC Sector Descriptions 1-16
Table 1-7: List of Annexes 1-17
Table 2-1: Annual Change in C02 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg C02
Eq. and Percent) 2-2
Table 2-2: Recent Trends in Various U.S. Data (Index 1990 = 100) and Global Atmospheric C02 Concentration2-4
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.) 2-4
Table 2-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg) 2-6
Table 2-5: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.) 2-8
Table 2-6: Emissions from Energy (Tg C02 Eq.) 2-8
Table 2-7: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.) 2-10
Table 2-8: Emissions from Industrial Processes (Tg C02 Eq.) 2-14
Table 2-9: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq.) 2-18
Table 2-10: Emissions from Agriculture (Tg C02 Eq.) 2-19
Table 2-11: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) 2-21
Table 2-12: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) 2-21
vi Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
Table 2-13: Emissions from Waste (Tg C02 Eq.) 2-22
Table 2-14: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq. and Percent of Total in
2005) 2-24
Table 2-15: Electricity Generation-Related Greenhouse Gas Emissions (Tg C02 Eq.) 2-26
Table 2-16: U.S Greenhouse Gas Emissions by "Economic Sector" and Gas with Electricity-Related Emissions
Distributed (Tg C02 Eq.) and Percent of Total in 2005 2-27
Table 2-17: Transportation-Related Greenhouse Gas Emissions (Tg C02 Eq.) 2-29
Table 2-18: Emissions of NOx, CO, NMVOCs, and S02 (Gg) 2-31
Table 3-1: C02, CH4, and N20 Emissions from Energy (Tg C02 Eq.) 3-1
Table 3-2: C02, CH4, and N20 Emissions from Energy (Gg) 3-2
Table 3-3: C02 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg C02 Eq.) 3-3
Table 3-4: Annual Change in C02 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg C02
Eq. and Percent) 3-4
Table 3-5: C02 Emissions from International Bunker Fuels (Tg C02 Eq.)* 3-6
Table 3-6: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.) 3-6
Table 3-7: C02 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg C02 Eq.)a 3-8
Table 3-8: Carbon Intensity from Direct Fossil Fuel Combustion by Sector (Tg C02 Eq./QBtu) 3-12
Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg C02 Eq./QBtu) 3-13
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Energy-related Fossil Fuel
Combustion by Fuel Type and Sector (Tg C02 Eq. and Percent) 3-18
Table 3-11: C02 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg C02 Eq.) 3-19
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu) 3-20
Table 3-13: 2005 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions 3-21
Table 3-14: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Non-Energy Uses of Fossil Fuels
(Tg C02 Eq. and Percent) 3-22
Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels
(Percent) 3-23
Table 3-16: CH4 Emissions from Stationary Combustion (Tg C02 Eq.) 3-25
Table 3-17: N20 Emissions from Stationary Combustion (Tg C02 Eq.) 3-25
Table 3-18: CH4 Emissions from Stationary Combustion (Gg) 3-26
Table 3-19: N20 Emissions from Stationary Combustion (Gg) 3-26
Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Energy-Related Stationary
Combustion, Including Biomass (Tg C02 Eq. and Percent) 3-28
Table 3-21: CH4 Emissions from Mobile Combustion (Tg C02 Eq.) 3-30
Table 3-22: N20 Emissions from Mobile Combustion (Tg C02 Eq.) 3-30
Table 3-23: CH4 Emissions from Mobile Combustion (Gg) 3-31
Table 3-24: N20 Emissions from Mobile Combustion (Gg) 3-31
Table 3-25: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Mobile Sources (Tg C02
Eq. and Percent) 3-34
VII
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
Table 3-26: CH4 Emissions from Coal Mining (Tg C02 Eq.) 3-36
Table 3-27: CH4 Emissions from Coal Mining (Gg) 3-37
Table 3-28: Coal Production (Thousand Metric Tons) 3-38
Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg C02 Eq. and
Percent) 3-38
Table 3-30: CH4 Emissions from Abandoned Coal Mines (Tg C02 Eq.) 3-40
Table 3-31: CH4 Emissions from Abandoned Coal Mines (Gg) 3-40
Table 3-32: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal
Mines (Tg C02 Eq. and Percent) 3-42
Table 3-33: CH4 Emissions from Petroleum Systems (Tg C02 Eq.) 3-43
Table 3-34: CH4 Emissions from Petroleum Systems (Gg) 3-43
Table 3-35: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems (Tg C02 Eq. and
Percent) 3-45
Table 3-36. CH4 Emissions from Natural Gas Systems (Tg C02 Eq.)* 3-46
Table 3-37. CH4 Emissions from Natural Gas Systems (Gg)* 3-46
Table 3-38. Non-energy C02 Emissions from Natural Gas Systems (Tg C02 Eq.) 3-47
Table 3-39. Non-energy C02 Emissions from Natural Gas Systems (Gg) 3-47
Table 3-40: Tier 2 Quantitative Uncertainty Estimates for CH4 and Non-energy C02 Emissions from Natural Gas
Systems (Tg C02 Eq. and Percent) 3-48
Table 3-41: Emissions of C02 from EOR Operations and Pipelines (Tg C02 Eq.) 3-50
Table 3-42: Emissions of C02 from EOR Operations and Pipelines (Gg) 3-50
Table 3-43: C02 and N20 Emissions from Municipal Solid Waste Combustion (Tg C02 Eq.) 3-51
Table 3-44: C02 and N20 Emissions from Municipal Solid Waste Combustion (Gg) 3-51
Table 3-45: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted 3-52
Table 3-46: Tier 2 Quantitative Uncertainty Estimates for C02 and N20 from Municipal Solid Waste Combustion
(Tg C02 Eq. and Percent) 3-53
Table 3-47: NOx, CO, and NMVOC Emissions from Energy-Related Activities (Gg) 3-53
Table 3-48: C02, CH4, and N20 Emissions from International Bunker Fuels (Tg C02 Eq.) 3-55
Table 3-49: C02, CH4 and N20 Emissions from International Bunker Fuels (Gg) 3-55
Table 3-50: Aviation Jet Fuel Consumption for International Transport (Million Gallons) 3-56
Table 3-51: Marine Fuel Consumption for International Transport (Million Gallons) 3-57
Table 3-52: C02 Emissions from Wood Consumption by End-Use Sector (Tg C02 Eq.) 3-59
Table 3-53: C02 Emissions from Wood Consumption by End-Use Sector (Gg) 3-59
Table 3-54: C02 Emissions from Ethanol Consumption (Tg C02 Eq. and Gg) 3-59
Table 3-55: Woody Biomass Consumption by Sector (Trillion Btu) 3-60
Table 3-56: Ethanol Consumption (Trillion Btu) 3-60
Table 3-57: CH4 Emissions from Non-Combustion Fossil Sources (Gg) 3-61
Table 3-58: Formation of C02 through Atmospheric CH4 Oxidation (Tg C02 Eq.) 3-62
viii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
Table 4-1: Emissions from Industrial Processes (Tg C02 Eq.) 4-1
Table 4-2: Emissions from Industrial Processes (Gg) 4-2
Table 4-3: C02 Emissions from Cement Production (Tg C02 Eq. and Gg)* 4-4
Table 4-4: Cement Production (Gg) 4-5
Table 4-5: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Cement Manufacture (Tg C02 Eq.
and Percent) 4-6
Table 4-6: C02 and CH4 Emissions from Iron and Steel Production (Tg C02 Eq.) 4-7
Table 4-7: C02 and CH4 Emissions from Iron and Steel Production (Gg) 4-7
Table 4-8: CH4 Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg) 4-8
Table 4-9: Production and Consumption Data for the Calculation of C02 and CH4 Emissions from Iron and Steel
Production (Thousand Metric Tons) 4-9
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Iron and Steel Production
(Tg. C02 Eq. and Percent) 4-10
Table 4-11: C02Emissions from Ammonia Manufacture and Urea Application (Tg C02 Eq.) 4-11
Table 4-12: C02Emissions from Ammonia Manufacture and Urea Application (Gg) 4-11
Table 4-13: Ammonia Production, Urea Production, and Urea Net Imports (Gg) 4-12
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Ammonia Manufacture and Urea
Application (Tg C02 Eq. and Percent) 4-13
Table 4-15: Net C02 Emissions from Lime Manufacture (Tg C02 Eq.) 4-13
Table 4-16: C02 Emissions from Lime Manufacture (Gg) 4-14
Table 4-17: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and Dead-Burned-
Dolomite Lime Production (Gg) 4-15
Table 4-18: Adjusted Lime Production and Lime Use for Sugar Refining and PCC (Gg) 4-15
Table 4-19: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lime Manufacture (Tg C02 Eq. and
Percent) 4-16
Table 4-20: C02 Emissions from Limestone & Dolomite Use (Tg C02 Eq.) 4-17
Table 4-21: C02 Emissions from Limestone & Dolomite Use (Gg) 4-17
Table 4-22: Limestone and Dolomite Consumption (Thousand Metric Tons) 4-19
Table 4-23: Dolomitic Magnesium Metal Production Capacity (Metric Tons) 4-19
Table 4-24: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Limestone and Dolomite Use (Tg
C02 Eq. and Percent) 4-20
Table 4-25: C02 Emissions from Soda Ash Manufacture and Consumption (Tg C02 Eq.) 4-21
Table 4-26: C02 Emissions from Soda Ash Manufacture and Consumption (Gg) 4-21
Table 4-27: Soda Ash Manufacture and Consumption (Gg) 4-22
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Soda Ash Manufacture and
Consumption (Tg C02 Eq. and Percent) 4-22
Table 4-29: C02 Emissions from Titanium Dioxide (Tg C02 Eq. and Gg) 4-23
Table 4-30: Titanium Dioxide Production (Gg) 4-24
Table 4-31: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Titanium Dioxide Production (Tg
C02 Eq. and Percent) 4-24
ix
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
Table 4-32: C02 and CH4 Emissions from Ferroalloy Production (Tg C02 Eq.) 4-25
Table 4-33: C02 and CH4 Emissions from Ferroalloy Production (Gg) 4-25
Table 4-34: Production of Ferroalloys (Metric Tons) 4-26
Table 4-35: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Ferroalloy Production (Tg C02 Eq.
and Percent) 4-27
Table 4-36: C02 Emissions from Phosphoric Acid Production (Tg C02 Eq. and Gg) 4-28
Table 4-37: Phosphate Rock Domestic Production, Exports, and Imports (Gg) 4-29
Table 4-38: Chemical Composition of Phosphate Rock (percent by weight) 4-29
Table 4-39: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Phosphoric Acid Production (Tg
C02 Eq. and Percent) 4-30
Table 4-40: C02 Emissions from C02 Consumption (Tg C02 Eq. and Gg) 4-31
Table 4-41: C02 Production (Gg C02) and the Percent Used for Non-EOR Applications for Jackson Dome and
Bravo Dome 4-32
Table 4-42: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from C02 Consumption (Tg C02 Eq. and
Percent) 4-32
Table 4-43: C02 Emissions from Zinc Production (Tg C02 Eq. and Gg) 4-33
Table 4-44: Zinc Production (Metric Tons) 4-35
Table 4-45: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Zinc Production (Tg C02 Eq. and
Percent) 4-36
Table 4-46: C02 Emissions from Lead Production (Tg C02 Eq. and Gg) 4-36
Table 4-47: Lead Production (Metric Tons) 4-37
Table 4-48: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lead Production (Tg C02 Eq. and
Percent) 4-37
Table 4-49: C02 and CH4 Emissions from Petrochemical Production (Tg C02 Eq.) 4-38
Table 4-50: C02 and CH4 Emissions from Petrochemical Production (Gg) 4-38
Table 4-51: Production of Selected Petrochemicals (Thousand Metric Tons) 4-39
Table 4-52: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)
Consumption (Thousand Metric Tons) 4-39
Table 4-53: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical Production and C02
Emissions from Carbon Black Production (Tg C02 Eq. and Percent) 4-40
Table 4-54: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg C02 Eq.) 4-41
Table 4-55: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg) 4-41
Table 4-56: Production and Consumption of Silicon Carbide (Metric Tons) 4-42
Table 4-57: Tier 2 Quantitative Uncertainty Estimates for CH4 and C02 Emissions from Silicon Carbide Production
and Consumption (Tg C02 Eq. and Percent) 4-42
Table 4-58: N20 Emissions from Nitric Acid Production (Tg C02 Eq. and Gg), 4-43
Table 4-59: Nitric Acid Production (Gg) 4-44
Table 4-60: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From Nitric Acid Production (Tg C02
Eq. and Percent) 4-44
Table 4-61: N20 Emissions from Adipic Acid Production (Tg C02 Eq. and Gg) 4-45
x Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
Table 4-62: Adipic Acid Production (Gg) 4-46
Table 4-63: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Adipic Acid Production (Tg C02
Eq. and Percent) 4-47
Table 4-64: Emissions of HFCs and PFCs from ODS Substitutes (Tg C02 Eq.) 4-47
Table 4-65: Emissions of HFCs and PFCs from ODS Substitution (Mg) 4-48
Table 4-66: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes (Tg C02
Eq. and Percent) 4-49
Table 4-67: HFC-23 Emissions from HCFC-22 Production (Tg C02 Eq. and Gg) 4-50
Table 4-68: HCFC-22 Production (Gg) 4-51
Table 4-69: Tier 1 Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production (Tg C02
Eq. and Percent) 4-51
Table 4-70: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufactures (Tg C02 Eq.) 4-52
Table 4-71: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufactures (Gg) 4-52
Table 4-72: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg C02 Eq. and Percent) 4-55
Table 4-73: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg C02 Eq.) 4-56
Table 4-74: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg) 4-56
Table 4-75: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor
Manufacture (Tg C02 Eq. and Percent) 4-59
Table 4-76: C02 Emissions from Aluminum Production (Tg C02 Eq. and Gg) 4-60
Table 4-77: PFC Emissions from Aluminum Production (TgC02Eq.) 4-60
Table 4-78: PFC Emissions from Aluminum Production (Gg) 4-60
Table 4-79: Production of Primary Aluminum (Gg) 4-62
Table 4-80: Tier 2 Quantitative Uncertainty Estimates for C02 and PFC Emissions from Aluminum Production (Tg
C02 Eq. and Percent) 4-63
Table 4-81: SF6 Emissions from Magnesium Production and Processing (Tg C02 Eq. and Gg) 4-64
Table 4-82: SF6 Emission Factors (kg SF6 per metric ton of magnesium) 4-65
Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and
Processing (Tg C02 Eq. and Percent) 4-66
Table 4-84: NOx, CO, and NMVOC Emissions from Industrial Processes (Gg) 4-67
Table 5-1: N20 Emissions from Solvent and Other Product Use (Tg C02 Eq. and Gg) 5-1
Table 5-2: Indirect Greenhouse Gas Emissions from Solvent and Other Product Use (Gg) 5-1
Table 5-3: N20 Emissions from N20 Product Usage (Tg C02 Eq. and Gg) 5-1
Table 5-4: N20 Production (Gg) 5-3
Table 5-5: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From N20 Product Usage (Tg C02 Eq. and
Percent) 5-3
Table 5-6: Emissions of NOx, CO, and NMVOC from Solvent Use (Gg) 5-4
Table 6-1: Emissions from Agriculture (Tg C02 Eq.) 6-1
Table 6-2: Emissions from Agriculture (Gg) 6-1
XI
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg C02 Eq.) 6-3
Table 6-4: CH4 Emissions from Enteric Fermentation (Gg) 6-3
Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation (Tg C02 Eq. and
Percent) 6-5
Table 6-6: CH4 and N20 Emissions from Manure Management (Tg C02 Eq.) 6-7
Table 1-6-7: CH4 and N20 Emissions from Manure Management (Gg) 6-8
Table 1-6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Manure Management (Tg
C02 Eq. and Percent) 6-10
Table 6-9: CH4 Emissions from Rice Cultivation (Tg C02 Eq.) 6-13
Table 6-10: CH4 Emissions from Rice Cultivation (Gg) 6-13
Table 6-11: Rice Areas Harvested (Hectares) 6-14
Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation (Tg C02 Eq. and
Percent) 6-16
Table 6-13: N20 Emissions from Agricultural Soils (Tg C02 Eq.) 6-17
Table 6-14: N20 Emissions from Agricultural Soils (Gg N20) 6-17
Table 6-15: Direct N20 Emissions from Agricultural Soils by Land-Use and N Input (Tg C02 Eq.) 6-18
Table 6-16: Indirect N20 Emissions from all Land Use Types and Managed Manure Systems (Tg C02 Eq.) 6-18
Table 6-17: Quantitative Uncertainty Estimates of N20 Emissions from Agricultural Soil Management in 2005 (Tg
C02 Eq. and Percent) 6-27
Table 6-18: CH4 and N20 Emissions from Field Burning of Agricultural Residues (Tg C02 Eq.) 6-30
Table 6-19: CH4, N20, CO, and NOx Emissions from Field Burning of Agricultural Residues (Gg) 6-30
Table 6-20: Agricultural Crop Production (Gg of Product) 6-32
Table 6-21: Percent of Rice Area Burned by State 6-32
Table 6-22: Percent of Rice Area Burned in California, 1990-1998 6-33
Table 6-23: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues 6-33
Table 6-24: Greenhouse Gas Emission Ratios 6-33
Table 6-25: Tier 2 Uncertainty Estimates for CH4 and N20 Emissions from Field Burning of Agricultural Residues
(Tg C02 Eq. and Percent) 6-34
Table 7-1: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) 7-1
Table 7-2: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C) 7-2
Table 7-3: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.) 7-3
Table 7-4: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Gg) 7-3
Table 7-5. Net Annual Changes in C Stocks (Tg C02/yr) in Forest and Harvested Wood Pools 7-6
Table 7-6. Net Annual Changes in C Stocks (Tg C/yr) in Forest and Harvested Wood Pools 7-6
Table 7-7. Forest area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools 7-6
Table 7-8: Estimates of C02 (Tg/yr) emissions for the lower 48 states and Alaska1 7-7
Table 7-9: Tier 2 Quantitative Uncertainty Estimates for Net C02 Flux from Forest Land Remaining Forest Land:
Changes in Forest C Stocks (Tg C02 Eq. and Percent) 7-11
xii Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Public Review Draft
Table 7-10: Estimated Non-C02 Emissions from Forest Fires (Tg C02 Eq.) for U.S. forests1 7-14
Table 7-11: Estimated Non-C02 Emissions from Forest Fires (Gg Gas) for U.S. forests1 7-14
Table 7-12: Estimated Carbon Released from Forest Fires for U.S. Forests 7-14
Table 7-13: Tier 2 Quantitative Uncertainty Estimates of Non-C02 Emissions from Forest Fires in Forest Land
Remaining Forest Land (Tg C02 Eq. and Percent) 7-15
Table 7-14. N20 Fluxes from Soils in Forest Land Remaining Forest Land (Tg C02 Eq. and Gg) 7-15
Table 7-15: Tier 2 Quantitative Uncertainty Estimates of N20 Fluxes from Soils in Forest Land Remaining Forest
Land (Tg C02 Eq. and Percent) 7-16
Table 7-16: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland (Tg C02 Eq.) 7-18
Table 7-17: Net Soil C Stock Changes and Liming Emissions in Cropland Remaining Cropland (Tg C) 7-18
Table 7-18: Applied Minerals (Million Metric Tons) 7-23
Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within Cropland Remaining
Cropland (Tg C02 Eq. and Percent) 7-24
Table 7-20: Net Soil C Stock Changes in Land Converted to Cropland (Tg C02 Eq.) 7-26
Table 7-21: Net Soil C Stock Changes in Land Converted to Cropland (Tg C) 7-26
Table 7-22: Quantitative Uncertainty Estimates for C Stock Changes occurring w ithin Land Converted to Cropland
(Tg C02 Eq. and Percent) 7-28
Table 7-23: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C02 Eq.) 7-30
Table 7-24: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C) 7-30
Table 7-25: Quantitative Uncertainty Estimates for C Stock Changes occurring within Grassland Remaining
Grassland (Tg C02 Eq. and Percent) 7-32
Table 7-26: Net Soil C Stock Changes for Land Converted to Grassland (Tg C02 Eq.) 7-34
Table 7-27: Net Soil C Stock Changes for Land Converted to Grassland (Tg C) 7-34
Table 7-28: Quantitative Uncertainty Estimates for C Stock Changes occurring w ithin Land Converted to
Grassland (Tg C02 Eq. and Percent) 7-36
Table 7-29: Net C Flux from Urban Trees (Tg C02 Eq. and Tg C) 7-37
Table 7-30: Carbon Stocks (Metric Tons C), Annual Carbon Sequestration (Metric Tons C/yr), Tree Cover
(Percent), and Annual Carbon Sequestration per Area of Tree Cover (kg C/m2 cover-yr) for Ten U.S. Cities 7-
39
Table 7-31: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees (Tg
C02 Eq. and Percent) 7-40
Table 7-32: N20 Fluxes from Soils in Settlements Remaining Settlements (Tg C02 Eq. and Gg) 7-41
Table 7-33: Tier 2 Quantitative Uncertainty Estimates of N20 Emissions from Soils in Settlements Remaining
Settlements (Tg C02 Eq. and Percent) 7-42
Table 7-34: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C02 Eq.) 7-43
Table 7-35: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C) 7-43
Table 7-36: 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 7-46
Table 7-37: Carbon Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C) 7-46
Table 7-38: Tier 2 Quantitative Uncertainty Estimates for C02 Flux from Yard Trimmings and Food Scraps in
Landfills (Tg C02 Eq. and Percent) 7-46
xiii
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
Table 8-1: Emissions from Waste (Tg C02 Eq.) 8-1
Table 8-2: Emissions from Waste (Gg) 8-1
Table 8-3. CH4 Emissions from Landfills (Tg C02 Eq.) 8-2
Table 8-4. CH4 Emissions from Landfills (Gg) 8-3
Table 8-5. Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg C02 Eq. and Percent) 8-
5
Table 8-6. CH4 and N20 Emissions from Domestic and Industrial Wastewater Treatment (Tg C02 Eq.) 8-7
Table 8-7. CH4 and N20 Emissions from Domestic and Industrial Wastewater Treatment (Gg) 8-7
Table 8-8. U.S. Population (Millions) and Domestic Wastewater BOD5 Produced (Gg) 8-9
Table 8-9. U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg) 8-9
Table 8-10. Wastewater Flow (m3/ton) and BOD Production (g/L) for U.S. Vegetables, Fruits and Juices
Production 8-11
Table 8-11. U.S. Population (Millions) and Average Protein Intake [kg/(person-year)] 8-12
Table 8-12. Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Wastewater Treatment (Tg C02 Eq.
and Percent) 8-13
Table 8-13: Emissions of NOx, CO, and NMVOC from Waste (Gg) 8-15
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg C02 Eq.) 10-3
Table 10-2: Revisions to Net Flux of C02 to the Atmosphere from Land Use, Land-Use Change, and Forestry (Tg
C02 Eq.) 10-4
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: 2005 Greenhouse Gas Emissions by Gas (percents based on Tg C02 Eq.) ES-6
Figure ES-5: 2005 Sources of C02 ES-7
Figure ES-6: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type ES-7
Figure ES-7: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion ES-7
Figure ES-8: 2005 Sources of CH4 ES-9
Figure ES-9: 2005 Sources of N20 ES-10
Figure ES-10: 2005 Sources of HFCs, PFCs, and SF6 ES-10
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector ES-11
Figure ES-12: 2005 U.S. Energy Consumption by Energy Source ES-12
Figure ES-13: Emissions Allocated to Economic Sectors ES-14
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors ES-15
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product ES-16
Figure ES-16: 2005 Key Categories—Tier 1 Level Assessment ES-18
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas 2-1
xiv Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions 2-1
Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990 2-1
Figure 2-4: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product 2-4
Figure 2-5: U.S. Greenhouse Gas Emissions by Chapter/IPCC Sector 2-8
Figure 2-6: 2005 Energy Chapter Greenhouse Gas Sources 2-8
Figure 2-7: 2005 U.S. Fossil C Flows (Tg C02 Eq.) 2-8
Figure 2-8: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 2-10
Figure 2-9: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion 2-10
Figure 2-10: 2005 Industrial Processes Chapter Greenhouse Gas Sources 2-14
Figure 2-11: 2005 Agriculture Chapter Greenhouse Gas Sources 2-19
Figure 2-12: 2005 Waste Chapter Greenhouse Gas Sources 2-22
Figure 2-13: Emissions Allocated to Economic Sectors 2-24
Figure 2-14: Emissions with Electricity Distributed to Economic Sectors 2-27
Figure 3-1: 2005 Energy Chapter Greenhouse Gas Sources 3-1
Figure 3-2: 2005 U.S. Fossil Carbon Flows (Tg C02 Eq.) 3-1
Figure 3-3: 2005 U.S. Energy Consumption by Energy Source 3-4
Figure 3-4: U.S. Energy Consumption (QuadrillionBtu) 3-4
Figure 3-5: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type 3-5
Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950-2005) 3-5
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2005) 3-5
Figure 3-8: Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the United States (1974-2005) 3-
6
Figure 3-9: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion 3-7
Figure 3-10. Sales of New Automobiles and Light-Duty Trucks, 1990-2005 3-7
Figure 3-11. Sales-Weighted Fuel Economy of New Automobiles and Light-Duty Trucks, 1990-2005 3-7
Figure 3-12: Industrial Production Indices (Index 1997=100) 3-10
Figure 3-13: Heating Degree Days 3-10
Figure 3-14: Cooling Degree Days 3-10
Figure 3-15: Electricity Generation Retail Sales by End-Use Sector 3-11
Figure 3-16: U.S. Energy Consumption and Energy-Related C02 Emissions Per Capita and Per Dollar GDP 3-13
Figure 3-17: Mobile Source CH4 and N20 Emissions 3-30
Figure 4-1: 2005 Industrial Processes Chapter Greenhouse Gas Sources 4-1
Figure 6-1: 2005 Agriculture Chapter Greenhouse Gas Emission Sources 6-1
Figure 6-2: Agricultural Sources and Pathways of N that Result in N20 Emissions 6-17
Figure 6-3: Major Crops, Average Annual Direct N20 Emissions, 1990-2005 (Tg C02 Eq./county/year) 6-19
Figure 6-4: Grasslands, Average Annual Direct N20 Emissions, 1990-2005 (Tg C02 Eq./county/year) 6-19
Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect N20 Emissions, 1990-2005 (Tg C02
xv
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
Eq./county/year) 6-19
Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect N20 Emissions, 1990-2005 (Tg C02
Eq./county/year) 6-19
Figure 7-1: Forest Sector Carbon Pools and Flows 7-4
Figure 7-2: Estimates of Net Annual Changes in C Stocks for Major C Pools 7-7
Figure 7-3: Average C Density in the Forest Tree Pool in the Conterminous United States During 2005 7-7
Figure 7-4: Net C Stock Change for Mineral Soils in Cropland Remaining Cropland, 2005 7-19
Figure 7-5: Net C Stock Change for Organic Soils in Cropland Remaining Cropland, 2005 7-19
Figure 7-6: Net C Stock Change for Mineral Soils in Land Converted to Cropland, 2005 7-27
Figure 7-7: Net C Stock Change for Organic Soils in Land Converted to Cropland, 2005 7-27
Figure 7-8: Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 2005 7-30
Figure 7-9: Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 2005 7-30
Figure 7-10: Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 2005 7-35
Figure 7-11: Net Soil C Stock Change for Organic Soils in Land Converted to Grassland, 2005 7-35
Figure 8-1: 2005 Waste Chapter Greenhouse Gas Sources 8-1
Boxes
BoxES-1: Recalculations of Inventory Estimates ES-1
Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data ES-16
Box 1-1: The IPCC Third Assessment Report and Global Warming Potentials 1-8
Box 1-2: IPCC Reference Approach 1-11
Box 2-1: Recent Trends in Various U.S. Greenhouse-Gas-Emissions-Related Data 2-3
Box 2-2: Methodology for Aggregating Emissions by Economic Sector 2-30
Box 2-3: Sources and Effects of Sulfur Dioxide 2-32
Box 3-1: Weather and Non-Fossil Energy Effects on C02 from Fossil Fuel Combustion Trends 3-5
Box 3-2: Carbon Intensity of U.S. Energy Consumption 3-11
Box 3-3. Carbon Dioxide Transport, Injection, and Geological Storage 3-49
Box 3-4: Formation of C02 through Atmospheric CH4 Oxidation 3-61
Box 6-1. Tier 1 vs. Tier 3 Approach for Estimating N20 Emissions 6-20
Box 7-1: C02 Emissions from Forest Fires 7-7
Box 7-2: Tier 3 Inventory for Soil C Stocks compared to Tier 1 or 2 Approaches 7-20
Box 8-1: Biogenic Emissions and Sinks of Carbon 8-5
xvi Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Executive Summary
2 An emissions inventory that identifies and quantifies a country's primary anthropogenic1 sources and sinks of
3 greenhouse gases is essential for addressing climate change. This inventory adheres to both 1) a comprehensive and
4 detailed set of methodologies for estimating sources and sinks of anthropogenic greenhouse gases, and 2) a common
5 and consistent mechanism that enables Parties to the United Nations Framework Convention on Climate Change
6 (UNFCCC) to compare the relative contribution of different emission sources and greenhouse gases to climate
7 change.
8 In 1992, the United States signed and ratified the UNFCCC. As stated in Article 2 of the UNFCCC, "The ultimate
9 objective of this Convention and any related legal instruments that the Conference of the Parties may adopt is to
10 achieve, in accordance with the relevant provisions of the Convention, stabilization of greenhouse gas
11 concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the
12 climate system. Such a level should be achieved within a time-frame sufficient to allow ecosystems to adapt
13 naturally to climate change, to ensure that food production is not threatened and to enable economic development to
14 proceed in a sustainable manner."2
15 Parties to the Convention, by ratifying, "shall develop, periodically update, publish and make available.. .national
16 inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by
17 the Montreal Protocol, using comparable methodologies... "3 The United States views this report as an opportunity
18 to fulfill these commitments.
19 This chapter summarizes the latest information on U.S. anthropogenic greenhouse gas emission trends from 1990
20 through 2005. To ensure that the U.S. emissions inventory is comparable to those of other UNFCCC Parties, the
21 estimates presented here were calculated using methodologies consistent with those recommended in the Revised
22 1996IPCC Guidelines for National Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997), the IPCC Good
23 Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (IPCC 2000), and the
24 IPCC Good Practice Guidance for Land Use, Land-Use Change, and Forestry (IPCC 2003). Additionally, the U.S.
25 emission inventory has begun to incorporate new methodologies and data from the 2006 IPCC Guidelines for
26 National Greenhouse Gas Inventories (IPCC 2006). The structure of this report is consistent with the UNFCCC
27 guidelines for inventory reporting.4 For most source categories, the Intergovernmental Panel on Climate Change
28 (IPCC) methodologies were expanded, resulting in a more comprehensive and detailed estimate of emissions.
29 [BEGIN BOX]
30 BoxES-1: Recalculations of Inventory Estimates
31
32 Each year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S.
33 Greenhouse Gas Emissions and Sinks, as attempts are made to improve both the analyses themselves, through the
34 use of better methods or data, and the overall usefulness of the report. In this effort, the United States follows the
1 The term "anthropogenic", in this context, refers to greenhouse gas emissions and removals that are a direct result of human
activities or are the result of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).
2 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate
Change. See .
3 Article 4(1 )(a) of the United Nations Framework Convention on Climate Change (also identified in Article 12). Subsequent
decisions by the Conference of the Parties elaborated the role of Annex I Parties in preparing national inventories. See
.
4 See .
Executive Summary ES-1
-------
Public Review Draft
1 IPCC Good Practice Guidance (IPCC 2000), which states, regarding recalculations of the time series, "It is good
2 practice to recalculate historic emissions when methods are changed or refined, when new source categories are
3 included in the national inventory, or when errors in the estimates are identified and corrected." In general,
4 recalculations are made to the U.S. greenhouse gas emission estimates either to incorporate new methodologies or,
5 most commonly, to update recent historical data.
6 In each Inventory report, the results of all methodology changes and historical data updates are presented in the
7 "Recalculations and Improvements" chapter; detailed descriptions of each recalculation are contained within each
8 source's description contained in the report, if applicable. In general, when methodological changes have been
9 implemented, the entire time series (in the case of the most recent Inventory report, 1990 through 2004) has been
10 recalculated to reflect the change, per IPCC Good Practice Guidance. Changes in historical data are generally the
11 result of changes in statistical data supplied by other agencies. References for the data are provided for additional
12 information.
13 [END BOX]
14
15 Background Information
16 Naturally occurring greenhouse gases include water vapor, carbon dioxide (C02), methane (CH4), nitrous oxide
17 (N20), and ozone (03). Several classes of halogenated substances that contain fluorine, chlorine, or bromine are
18 also greenhouse gases, but they are, for the most part, solely a product of industrial activities. Chlorofluorocarbons
19 (CFCs) and hydrochlorofluorocarbons (HCFCs) are halocarbons that contain chlorine, while halocarbons that
20 contain bromine are referred to as bromofluorocarbons (i.e., halons). As stratospheric ozone depleting substances,
21 CFCs, HCFCs, and halons are covered under the Montreal Protocol on Substances that Deplete the Ozone Layer.
22 The UNFCCC defers to this earlier international treaty. Consequently, Parties to the UNFCCC are not required to
23 include these gases in their national greenhouse gas emission inventories.5 Some other fluorine-containing
24 halogenated substances—hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)—do
25 not deplete stratospheric ozone but are potent greenhouse gases. These latter substances are addressed by the
26 UNFCCC and accounted for in national greenhouse gas emission inventories.
27 There are also several gases that do not have a direct global warming effect but indirectly affect terrestrial and/or
28 solar radiation absorption by influencing the formation or destruction of greenhouse gases, including tropospheric
29 and stratospheric ozone. These gases include carbon monoxide (CO), oxides of nitrogen (NOx), and non-CH4
30 volatile organic compounds (NMVOCs). Aerosols, which are extremely small particles or liquid droplets, such as
31 those produced by sulfur dioxide (S02) or elemental carbon emissions, can also affect the absorptive characteristics
32 of the atmosphere.
33 Although the direct greenhouse gases C02, CH4, and N20 occur naturally in the atmosphere, human activities have
34 changed their atmospheric concentrations. From the pre-industrial era (i.e., ending about 1750) to 2004,
35 concentrations of these greenhouse gases have increased globally by 35, 143, and 18 percent, respectively (IPCC
36 2001, Hofmann 2004).
37 Beginning in the 1950s, the use of CFCs and other stratospheric ozone depleting substances (ODS) increased by
38 nearly 10 percent per year until the mid-1980s, when international concern about ozone depletion led to the entry
39 into force of the Montreal Protocol. Since then, the production of ODS is being phased out. In recent years, use of
40 ODS substitutes such as HFCs and PFCs has grown as they begin to be phased in as replacements for CFCs and
41 HCFCs. Accordingly, atmospheric concentrations of these substitutes have been growing (IPCC 2001).
5 Emissions estimates of CFCs, HCFCs, halons and other ozone-depleting substances are included in the annexes of the
Inventory report for informational purposes.
2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Public Review Draft
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 C02, and therefore GWP-
weighted emissions are measured in teragrams of C02 equivalent (Tg C02Eq.).7 All gases in this Executive
Summary are presented in units of Tg C02 Eq.
The UNFCCC reporting guidelines for national inventories were updated in 2002,8 but continue to require the use
of GWPs from the IPCC Second Assessment Report (SAR) (IPCC 1996). This requirement ensures that current
estimates of aggregate greenhouse gas emissions for 1990 to 2005 are consistent with estimates developed prior to
the publication of the IPCC Third Assessment Report (TAR). Therefore, to comply with international reporting
standards under the UNFCCC, official emission estimates are reported by the United States using SAR GWP
values. All estimates are provided throughout the report in both C02 equivalents and unweighted units. A
comparison of emission values using the SAR GWPs versus the TAR GWPs can be found in Chapter 1 and, in more
detail, in Annex 6.1 of this report. The GWP values used in this report are listed below in Table ES-1.
Table ES-1: Global Warming Potentials (100-Year Time Horizon) Used in this Report
Gas
GWP
C02
1
ch4*
21
n2o
310
HFC-23
11,700
HFC-32
650
HFC-125
2,800
HFC-134a
1,300
HFC-143a
3,800
HFC-152a
140
HFC-227ea
2,900
HFC-236fa
6,300
HFC-4310mee
1,300
cf4
6,500
c2f6
9,200
C4F10
7,000
CsFm
7,400
sf6
23,900
Source: IPCC (1996)
* The CH4 GWP includes the direct effects and those indirect effects due to the production of tropospheric ozone and
stratospheric water vapor. The indirect effect due to the production of C02 is not included.
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 12/44ths of carbon dioxide by weight.
8 See .
Executive Summary ES-3
-------
Public Review Draft
1 Global warming potentials are not provided for CO, NOx, NMVOCs, S02, and aerosols because there is no agreed-
2 upon method to estimate the contribution of gases that are short-lived in the atmosphere, spatially variable, or have
3 only indirect effects on radiative forcing (IPCC 1996).
4 Recent Trends in U.S. Greenhouse Gas Emissions and Sinks
5 In 2005, total U.S. greenhouse gas emissions were 7,262.3 Tg C02 Eq. Overall, total U.S. emissions have risen by
6 16.3 percent from 1990 to 2005, while the U.S. gross domestic product has increased by 55 percent over the same
7 period (BEA 2006). Emissions rose from 2004 to 2005, increasing by 0.8 percent (58.4 Tg C02 Eq.). The
8 following factors were primary contributors to this increase: (1) strong economic growth in 2005, leading to
9 increased demand for electricity and (2) an increase in the demand for electricity due to warmer summer conditions.
10 These factors were moderated by decreasing demand for fuels due to warmer winter conditions and higher fuel
11 prices.
12 Figure ES-1 through Figure ES-3 illustrate the overall trends in total U.S. emissions by gas, annual changes, and
13 absolute change since 1990. Table ES-2 provides a detailed summary of U.S. greenhouse gas emissions and sinks
14 for 1990 through 2005.
15
16 Figure ES-1: U.S. Greenhouse Gas Emissions by Gas
17
18 Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
19
20 Figure ES-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990
21
Table ES-2: Recent Trends in U.
S. Greenhouse Gas Emissions and Sinks (Tg
CO? Eq.)
Gas/Source
1990
1995
2000
2001
2002
2003
2004
2005
co2
5,061.7
5,384.6
I 5'940 1
5,843.1
5,892.8
5,952.6
6,064.5
6,091.2
Fossil Fuel Combustion
4,724.1
5,030.0 1
5,584.9
5,511.7
5,557.2
5,624.5
5,713.0
5,752.8
Non-Energy Use of Fuels
117.2
133.1
141.0
131.3
135.3
131.3
150.2
142.3
Cement Manufacture
33.3
36.8
41.2
41.4
42.9
43.1
45.6
45.9
Iron and Steel Production
85.0
73.5
65.3
58.0
54.7
53.5
51.5
45.4
Natural Gas Systems
33.7
33.8
29.4
28.8
29.6
28.4
28.2
28.2
Waste Combustion
10.9
15.7
17.9
18.3
18.5
19.5
20.1
20.9
Ammonia Production and Urea
Application
19.3
20.5
19.6
16.7
17.8
16.2
16.9
16.3
Lime Manufacture
11.3
12.8
13.3
12.9
12.3
13.0
13.7
13.7
Limestone and Dolomite Use
5.5
7.4
6.0
5.7
5.9
4.7
6.7
7.4
Soda Ash Manufacture and
Consumption
4.1
4.3
4.2
4.1
4.1
4.1
4.2
4.2
Aluminum Production
6.8
5.7
6.1
4.4
4.5
4.5
4.2
4.2
Petrochemical Production
2.2
2.8
3.0
2.8
2.9
2.8
2.9
2.9
Titanium Dioxide Production
1.3
1.7
1.9
1.9
2.0
2.0
2.3
1.9
Ferroalloy Production
2.2
2.0
1.9
1.5
1.3
1.3
1.4
1.4
Phosphoric Acid Production
1.5
1.5
1.4
1.3
1.3
1.4
1.4
1.4
Carbon Dioxide Consumption
1.4
1.4
1.4
0.8
1.0
1.3
1.2
1.3
Zinc Production
0.9
1.0
1.1
1.0
0.9
0.5
0.5
0.5
Lead Production
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
4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Land-Use Change and Forestry
(Sink)" (712.9) (828.5) |
International Bunker Fuelsb 113. 100.(
Wood Biomass and Ethanol 219.3 236.8i
Consumptionh
CII4 609.1 598.71
Landfills 161.0 157.11
Enteric Fermentation 115.7 120.61
Natural Gas Systems 124.5 128.11
Coal Mining 81.9 66.51
Manure Management 30.9 35.11
Petroleum Systems 34.4 31.11
Wastewater Treatment 24.1- 25.11
Forest Land Remaining Forest
(754.7) (765.5)
101.1 97.6
228.3 203.2
563.7
131.9
113.5
126.6
55.9
38.7
27.8
26.4
547.7
127.6
112.5
125.4
55.5
40.1
27.4
25.9
(809.9)
89.1
204.4
549.7
130.4
112.6
125.0
52.0
41.1
26.8
25.8
(811.6)
83.7
209.6
549.2
134.9
113.0
123.7
52.1
40.5
25.8
25.6
(824.9) (828.4)
97.2 95.6
224.8 206.5
540.3
132.1
110.5
119.0
54.5
39.7
25.4
25.7
Field Burning of Agricultural
Residues 0.7
Ferroalloy Production
Silicon Carbide Production and
Consumption
International Bunker Fuelsb 0.2
N20 482.0
Agricultural Soil Management 366.')
Mobile Sources 43.7
Nitric Acid Production 17.:-
Stationary Sources 12.3
Manure Management 8.<>
Wastewater Treatment 6.4
Adipic Acid Production 15.2
Settlements Remaining
Settlements 5.11
N20 Product U sage 4.31
Forest Land Remaining Forest
Land 0>
Waste Combustion 0.51
Field Burning of Agricultural
Residues 0.4
International Bunker Fuelsb 1a
HFCs, PFCs, and SF6 89.3
Substitution of Ozone
Depleting Substances 0.
HCFC-22 Production 35.0
Electrical Transmission and
Distribution 27.11
Semiconductor Manufacture 2.K>
Aluminum Production 18. *
Magnesium Production and
Processing 5.4|
0.7
+
+1
0.
484,21
353.4
53.7
19.9
12.81
9.0
6.91
17.2
5o
4 *
0,(.
0.51
0.4
0.9
103.5
32.21
27.0
21.8
5.0
11.8
5.6
0.S
+
0.1
499.8
376.8
53.2
19.6
14.0
9.6
7.6
6.0
5.6
4.8
1.7
0.4
0.5
0.9
143.8
80.9
29.8
15.2
6.3
8.6
3.0
0.S
+
0.1
502.5
389.0
49.7
15.9
13.5
9.8
7.6
4.9
5.5
4.8
1.0
0.5
0.5
0.9
133.8
88.6
19.8
15.1
4.5
3.5
2.4
0.7
+
+
0.1
479.3
366.1
47.1
17.2
13.4
9.7
7.7
5.9
5.6
4.3
1.4
0.5
0.4
0.8
143.0
96.9
19.8
14.3
4.4
5.2
2.4
Oi
+
0.1
459.9
350.2
43.8
16.7
13.7
9.3
7.8
6.2
5.8
4.3
1.2
0.5
0.4
0.8
142.7
105.5
12.3
13.8
4.3
3.8
2.9
0.9
+
+
0.1
445.3
338.8
41.2
16.0
13.9
9.4
7.9
5.7
6.0
4.3
1.1
0.5
0.5
0.9
153.9
13.6
4.7
2.8
2.6
539.3
132.0
112.1
111.1
52.4
41.3
28.5
25.4
Land
7.1
4.0
14.0
6.0
10.4
8.1
6.9
11.6
Stationary Sources
8.0
7.:-
7.4
6.8
6.8
7.0
7.1
6.9
Rice Cultivation
7.1
7.<>
7.5
7.6
6.8
6.9
7.6
6.9
Abandoned Coal Mines
6.0
8.2
7.3
6.7
6.1
5.9
5.8
5.5
Mobile Sources
4.7
4.3
3.5
3.2
3.1
2.9
2.8
2.6
Petrochemical Production
0.9
1.1
1.2
1.1
1.1
1.1
1.2
1.1
Iron and Steel Production
1.3
1.3
1.2
1.1
1.0
1.0
1.0
1.0
0.9
+
+
0.1
468.7
365.1
38.0
15.7
13.8
9.5
8.0
6.0
5.8
4.3
1.5
0.5
0.5
0.9
163.0
114.5 123.3
15.6 16.5
13.2
4.3
3.0
2.7
Total
6,242.1 6,571.0 7,147.3 7,027.1 7,064.8 7,104.4 7,203.9 7,262.3
Executive Summary ES-5
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
Net Emissions (Sources and
Sinks) 5,529.1 5,742.5 6,392.6 6,261.6 6,254.8 6,292.8 6,379.0 6,433.9
+ Does not exceed 0.05 Tg C02 Eq.
a Parentheses indicate negative values or sequestration. The net C02 flux total includes both emissions and sequestration, and
constitutes a sink in the United States. Sinks are only included in net emissions total.
b Emissions from International Bunker Fuels and Biomass Combustion are not included in totals.
Note: Totals may not sum due to independent rounding.
Figure ES-4 illustrates the relative contribution of the direct greenhouse gases to total U.S. emissions in 2005. The
primary greenhouse gas emitted by human activities in the United States was C02, representing approximately 83.9
percent of total greenhouse gas emissions. The largest source of C02, and of overall greenhouse gas emissions, was
fossil fuel combustion. CH4 emissions, which have steadily declined since 1990, resulted primarily from
decomposition of wastes in landfills, natural gas systems, and enteric fermentation associated with domestic
livestock. Agricultural soil management and mobile source fossil fuel combustion were the major sources of N20
emissions. The emissions of substitutes for ozone depleting substances and emissions of HFC-23 during the
production of HCFC-22 were the primary contributors to aggregate HFC emissions. Electrical transmission and
distribution systems accounted for most SF6 emissions, while PFC emissions resulted from semiconductor
manufacturing and as a by-product of primary aluminum production.
Figure ES-4: 2005 Greenhouse Gas Emissions by Gas (percents based on Tg C02 Eq.)
Overall, from 1990 to 2005, total emissions of C02 increased by 1,029.6 Tg C02 Eq. (20.3 percent), while CH4 and
N20 emissions decreased by 69.8 Tg C02 Eq. (11.5 percent) and 13.3 Tg C02 Eq. (2.8 percent), respectively.
During the same period, aggregate weighted emissions of HFCs, PFCs, and SF6 rose by 73.7 Tg C02 Eq. (82.5
percent). Despite being emitted in smaller quantities relative to the other principal greenhouse gases, emissions of
HFCs, PFCs, and SF6 are significant because many of them have extremely high global warming potentials and, in
the cases of PFCs and SF6, long atmospheric lifetimes. Conversely, U.S. greenhouse gas emissions were partly
offset by carbon sequestration in forests, trees in urban areas, agricultural soils, and landfilled yard trimmings and
food scraps, which, in aggregate, offset 11 percent of total emissions in 2005. 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
C02 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 C02 have risen
about 35 percent (IPCC 2001, Hofmann 2004), principally due to the combustion of fossil fuels. Within the United
States, fuel combustion accounted for 94 percent of C02 emissions in 2005. Globally, approximately 27,044 Tg of
C02 were added to the atmosphere through the combustion of fossil fuels in 2004, of which the United States
accounted for about 22 percent.9 Changes in land use and forestry practices can also emit C02 (e.g., through
conversion of forest land to agricultural or urban use) or can act as a sink for C02 (e.g., through net additions to
forest biomass).
9 Global C02 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy
Annual 2004 (EIA 2006a).
6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
Figure ES-5: 2005 Sources of C02
As the largest source of U.S. greenhouse gas emissions, C02 from fossil fuel combustion has accounted for
approximately 77 percent of GWP weighted emissions since 1990, growing slowly from 76 percent of total GWP-
weighted emissions in 1990 to 79 percent in 2005. Emissions of C02 from fossil fuel combustion increased at an
average annual rate of 1.3 percent from 1990 to 2005. The fundamental factors influencing this trend include (1) a
generally growing domestic economy over the last 15 years, and (2) significant overall growth in emissions from
electricity generation and transportation activities. Between 1990 and 2005, C02 emissions from fossil fuel
combustion increased from 4,724.1 Tg C02 Eq. to 5,752.8 Tg C02 Eq.—a 21.8 percent total increase over the
fifteen-year period. From 2004 to 2005, these emissions increased by 39.8 Tg C02 Eq. (0.7 percent).
Historically, changes in emissions from fossil fuel combustion have been the dominant factor affecting U.S.
emission trends. Changes in C02 emissions from fossil fuel combustion are influenced by many long-term and
short-term factors, including population and economic growth, energy price fluctuations, technological changes, and
seasonal temperatures. On an annual basis, the overall consumption of fossil fuels in the United States generally
fluctuates in 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.
Figure ES-6: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Figure ES-7: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion
The four major end-use sectors contributing to C02 emissions from fossil fuel combustion are industrial,
transportation, residential, and commercial. Electricity generation also emits C02, although these emissions are
produced as they consume fossil fuel to provide electricity to one of the four end-use sectors. For the discussion
below, electricity generation emissions have been distributed to each end-use sector on the basis of each sector's
share of aggregate electricity consumption. This method of distributing emissions assumes that each end-use sector
consumes electricity that is generated from the national average mix of fuels according to their carbon intensity.
Emissions from electricity generation are also addressed separately after the end-use sectors have been discussed.
Note that emissions from U.S. territories are calculated separately due to a lack of specific consumption data for the
individual end-use sectors.
Figure ES-6, Figure ES-7, and Table ES-3 summarize C02 emissions from fossil fuel combustion by end-use sector.
Table ES-3: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)
End-Use Sector
19901
Transportation
1,467.0
Combustion
1,464.0
Electricity
3.0
Industrial
1,539.8
Combustion
857.1
Electricity
682.7
Residential
929.9
Combustion
340.3
1,593.3
1,590.2
3.0
1,595.8
882.7
713.1
995.4
356.41
2000
2001
2002
2003
2004
2005
1,787.8
1,761.5
1,815.7
1,814.8
1,868.9
1,899.5
1,784.4
1,758.2
1,812.3
1,810.5
1,864.5
1,894.4
3.4
3.3
3.4
4.3
4.4
5.2
1,660.1
1,596.6
1,575.5
1,595.1
1,615.2
1,575.2
875.0
869.9
857.7
858.3
875.6
840.1
785.1
726.7
717.8
736.8
739.6
735.1
1,131.5
1,124.8
1,147.9
1,179.1
1,175.9
1,208.7
373.5
363.9
362.4
383.8
369.9
358.7
Executive Summary ES-7
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
Electricity
589.6
639.0
! 758.0
760.9
785.5
795.3
806.0
849.9
Commercial
759.2
810.6
! 969.3
979.7
973.8
984.2
999.1
1,016.8
Combustion
224.3
j 226.4
j 232.3
225.1
225.7
236.6
233.3
225.8
Electricity
534.9
j 584.2
i 736.9
754.6
748.0
747.6
765.8
791.0
U.S. Territories
28.3
i 35.0
| 36.2
49.0
44.3
51.3
54.0
52.5
Total
4,724.11
5,030.01
5,584.9 5,511.7 5,557.2 5,624.5 5,713.0 5,752.8
Electricity Generation 1,810.2 1.939.3— 2.283.5 2,245.5 2,254.7 2,284.0 2,315.8 2,381.2
Note: Totals may not sum due to independent rounding. Combustion-related emissions from electricity generation are allocated
based on aggregate national electricity consumption by each end-use sector.
Transportation End-Use Sector. Transportation activities (excluding international bunker fuels) accounted for 33
percent of C02 emissions from fossil fuel combustion in 2005.10 Virtually all of the energy consumed in this end-
use sector came from petroleum products. Over 60 percent of the emissions resulted from gasoline consumption for
personal vehicle use. The remaining emissions came from other transportation activities, including the combustion
of diesel fuel in heavy-duty vehicles and jet fuel in aircraft.
Industrial End-Use Sector. Industrial C02 emissions, resulting both directly from the combustion of fossil fuels and
indirectly from the generation of electricity that is consumed by industry, accounted for 27 percent of C02 from
fossil fuel combustion in 2005. About half of these emissions resulted from direct fossil fuel combustion to produce
steam and/or heat for industrial processes. The other half of the emissions resulted from consuming electricity for
motors, electric furnaces, ovens, lighting, and other applications.
Residential and Commercial End-Use Sectors. The residential and commercial end-use sectors accounted for 21
and 18 percent, respectively, of C02 emissions from fossil fuel combustion in 2005. Both sectors relied heavily on
electricity for meeting energy demands, with 70 and 78 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 C02 from fossil fuel combustion in 2005. The type of
fuel combusted by electricity generators has a significant effect on their emissions. For example, some electricity is
generated with low C02 emitting energy technologies, particularly non-fossil 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 93 percent of all coal consumed for energy in the United States in 2005. Consequently, changes
in electricity demand have a significant impact on coal consumption and associated C02 emissions.
Other significant C02 trends included the following:
• C02 emissions from non-energy use of fossil fuels has increased 25.1 Tg C02 Eq. (21 percent) from 1990
through 2005. Emissions from non-energy uses of fossil fuels were 142.3 Tg C02 Eq. in 2005, which
constituted 2.5 percent of overall fossil fuel C02 emissions and 2.3 percent of total national C02 emissions,
approximately the same proportion as in 1990.
• C02 emissions from cement production increased to 45.9 Tg C02 Eq. in 2005, a 38 percent increase in
emissions since 1990. Emissions mirror growth in the construction industry. In contrast to many other
manufacturing sectors, demand for domestic cement remains strong because it is not cost-effective to transport
cement far from its point of manufacture.
10 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 2005.
8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
• C02 emissions from iron and steel production decreased to 45.4 Tg C02 Eq. in 2005, and have declined by 39.6
Tg C02 Eq. (47 percent) from 1990 through 2005, due to reduced domestic production of pig iron, sinter, and
metallurgical coke.
• C02 emissions from waste combustion (20.9 Tg C02 Eq. in 2005) increased by 10.0 Tg C02 Eq. (91 percent)
from 1990 through 2005, as the volume of plastics and other fossil carbon-containing materials in municipal
solid waste grew.
• Net C02 sequestration from Land Use, Land-Use Change, and Forestry increased by 115.5 Tg C02 Eq. (16
percent) from 1990 through 2005. This increase was primarily due to an increase in the rate of net carbon
accumulation in forest carbon stocks, particularly in aboveground and belowground tree biomass. Annual
carbon accumulation in landfilled yard trimmings and food scraps slowed over this period, while the rate of
carbon accumulation in urban trees increased.
Methane Emissions
According to the IPCC, CH4 is more than 20 times as effective as C02 at trapping heat in the atmosphere. Over the
last two hundred and fifty years, the concentration of CH4 in the atmosphere increased by 143 percent (IPCC 2001,
Hofmann 2004). Anthropogenic sources of CH4 include landfills, natural gas and petroleum systems, agricultural
activities, coal mining, wastewater treatment, stationary and mobile combustion, and certain industrial processes
(see Figure ES-8).
Figure ES-8: 2005 Sources of CH4
Some significant trends in U.S. emissions of CH4 include the following:
• Landfills are the largest anthropogenic source of CH4 emissions in the United States. In 2005, landfill CH4
emissions were 132.0 Tg C02 Eq. (approximately 24 percent of total CH4 emissions), which represents a
decline of 29.0 Tg C02 Eq., or 18 percent, since 1990. Although the amount of solid waste landfilled each year
continues to grow, the amount of CH4 captured and burned at landfills has increased dramatically, countering
this trend.11
• In 2005, CH4 emissions from coal mining were 52.4 Tg C02 Eq. This decline of 29.5 Tg C02 Eq. (36 percent)
from 1990 results from the mining of less gassy coal from underground mines and the increased use of CH4
collected from degasification systems.
• CH4 emissions from natural gas systems were 111.1 Tg C02 Eq. in 2005; emissions have declined by 13.3 Tg
C02 Eq. (11 percent) since 1990. This decline has been due to improvements in technology and management
practices, as well as some replacement of old equipment.
• CH4 emissions from manure management were 41.3 Tg C02 Eq. in 2005. From 1990 to 2005, emissions from
this source increased by 10.4 Tg C02 Eq. (34 percent). The bulk of this increase was from swine and dairy cow
manure, and is attributed to the shift in the composition of the swine and dairy industries toward larger
facilities. Larger swine and dairy farms tend to use liquid management systems, where the decomposition of
materials in the manure tends to produce CH4.
11 The C02 produced from combusted landfill CH4 is not counted in national inventories as it is considered part of the natural C
cycle of decomposition.
Executive Summary ES-9
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
Nitrous Oxide Emissions
N20 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 N20 emissions are much
lower than C02 emissions, N20 is approximately 300 times more powerful than C02 at trapping heat in the
atmosphere. Since 1750, the global atmospheric concentration of N20 has risen by approximately 18 percent (IPCC
2001, Hofmann 2004). The main anthropogenic activities producing N20 in the United States are agricultural soil
management, fuel combustion in motor vehicles, manure management, nitric acid production, wastewater treatment,
and stationary fuel combustion (see Figure ES-9).
Figure ES-9: 2005 Sources of N20
Some significant trends in U.S. emissions of N20 include the following:
• Agricultural soil management activities such as fertilizer application and other cropping practices were the
largest source of U.S. N20 emissions, accounting for 78 percent (365.1 Tg C02 Eq.) of 2005 emissions. N20
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.
• In 2005, N20 emissions from mobile combustion were 38.0 Tg C02 Eq. (approximately 8 percent of U.S. N20
emissions). From 1990 to 2005, N20 emissions from mobile combustion decreased by 13 percent. However,
from 1990 to 1998 emissions increased by 10 percent, due to control technologies that reduced NOx emissions
while increasing N20 emissions. Since 1998, newer control technologies have led to a steady decline in N20
from this source.
HFC, PFC, and SF6 Emissions
HFCs and PFCs are families of synthetic chemicals that are used as alternatives to the ODSs, which are being
phased out under the Montreal Protocol and Clean Air Act Amendments of 1990. HFCs and PFCs do not deplete
the stratospheric ozone layer, and are therefore acceptable alternatives under the Montreal Protocol.
These compounds, however, along with SF6, are potent greenhouse gases. In addition to having high global
warming potentials, SF6 and PFCs have extremely long atmospheric lifetimes, resulting in their essentially
irreversible accumulation in the atmosphere once emitted. Sulfur hexafluoride is the most potent greenhouse gas
the IPCC has evaluated.
Other emissive sources of these gases include HCFC-22 production, electrical transmission and distribution
systems, semiconductor manufacturing, aluminum production, and magnesium production and processing (see
Figure ES-10).
Figure ES-10: 2005 Sources of HFCs, PFCs, and SF6
Some significant trends in U.S. HFC, PFC, and SF6 emissions include the following:
• Emissions resulting from the substitution of ozone depleting substances (e.g., CFCs) have been increasing from
small amounts in 1990 to 123.3 Tg C02 Eq. in 2005. Emissions from substitutes for ozone depleting
substances are both the largest and the fastest growing source of HFC, PFC and SF6 emissions. These emissions
have been increasing as phase-outs required under the Montreal Protocol come into effect, especially after 1994
10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
when full market penetration was made for the first generation of new technologies featuring ODS substitutes.
• The increase in ODS substitute emissions is offset substantially by decreases in emission of HFCs, PFCs, and
SF6 from other sources. Emissions from aluminum production decreased by 84 percent (15.6 Tg C02 Eq.) from
1990 to 2005, due to both industry emission reduction efforts and lower domestic aluminum production.
• Emissions from the production of HCFC-22 decreased by 53 percent (18.4 Tg C02 Eq.) from 1990 through
2005, due to a steady decline in the emission rate of HFC-23 (i.e., the amount of HFC-23 emitted per kilogram
of HCFC-22 manufactured) and the use of thermal oxidation at some plants to reduce HFC-23 emissions.
• Emissions from electric power transmission and distribution systems decreased by 51 percent (13.9 Tg C02
Eq.) from 1990 to 2005, primarily because of higher purchase prices for SF6 and efforts by industry to reduce
emissions.
Overview of Sector Emissions and Trends
In accordance with the Revised 1996IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997), and the 2003 UNFCCC Guidelines on Reporting and Review (UNFCCC 2003),
the Inventory of U.S. Greenhouse Gas Emissions and Sinks report is segregated into six sector-specific chapters.
Figure ES-11 and Table ES-4 aggregate emissions and sinks by these chapters.
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector
Table ES-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)
Chapter/IPCC Sector
1990
1995
i 2000
2001
2002
2003
2004
2005
Energy
5,202.1
5,525.7
1 6,069.2
5,978.9
5,021.5
5,079.2
5,181.8
6,203.6
Industrial Processes
300.2
314.9
338.8
309.7
320.3
316.6
330.8
333.8
Solvent and Other Product Use
4.3
4.5
4.8
4.8
4.3
4.3
4.3
4.3
Agriculture
530.3
526.8
547.4
560.3
537.4
521.1
507.4
536.3
Land Use, Land-Use Change, and Forestry
(Non-C02 Emissions)
13.0
10.1
21.3
12.4
17.4
15.0
13.9
18.9
Waste
192.2
189.1
165.9
161.1
163.9
168.4
165.7
165.4
Total
6,242.1
16,571.0
7,147.3
7,027.1 7,064.8
7,104.4 7,203.9
7,262.3
Net C02 Flux from Land Use, Land-Use
Change, and Forestry*
(712.9)
1 (828.5)
(754.7)
[165.5)
1809.9)
1811.6)
^824.9)
(828.4)
Net Emissions (Sources and Sinks)
5,529.1
5,742.5
1 6,392.6
5,261.6
5,254.8
5,292.8
5,379.0
6,433.9
* The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only
included in net emissions total.
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values or sequestration.
Energy
The Energy chapter contains emissions of all greenhouse gases resulting from stationary and mobile energy
activities including fuel combustion and fugitive fuel emissions. Energy-related activities, primarily fossil fuel
combustion, accounted for the vast majority of U.S. C02 emissions for the period of 1990 through 2005. In 2005,
approximately 86 percent of the energy consumed in the United States (on a Btu basis) was produced through the
combustion of fossil fuels. The remaining 14 percent came from other energy sources such as hydropower,
biomass, nuclear, wind, and solar energy (see Figure ES-12). Energy related activities are also responsible for CH4
and N20 emissions (38 percent and 11 percent of total U.S. emissions of each gas, respectively). Overall, emission
sources in the Energy chapter account for a combined 85 percent of total U.S. greenhouse gas emissions in 2005.
Executive Summary ES-11
-------
Public Review Draft
1
2 Figure ES-12: 2005 U.S. Energy Consumption by Energy Source
3
4 Industrial Processes
5 The Industrial Processes chapter contains by-product or fugitive emissions of greenhouse gases from industrial
6 processes not directly related to energy activities such as fossil fuel combustion. For example, industrial processes
7 can chemically transform raw materials, which often release waste gases such as C02, CH4 and N20. The processes
8 include iron and steel production, lead and zinc production, cement manufacture, ammonia manufacture and urea
9 application, lime manufacture, limestone and dolomite use (e.g., flux stone, flue gas desulfurization, and glass
10 manufacturing), soda ash manufacture and use, titanium dioxide production, phosphoric acid production, ferroalloy
11 production, C02 consumption, aluminum production, petrochemical production, silicon carbide production, nitric
12 acid production, and adipic acid production. Additionally, emissions from industrial processes release HFCs, PFCs
13 and SF6. Overall, emission sources in the Industrial Process chapter account for 4.6 percent of U.S. greenhouse gas
14 emissions in 2005.
15 Solvent and Other Product Use
16 The Solvent and Other Product Use chapter contains greenhouse gas emissions that are produced as a by-product of
17 various solvent and other product uses. In the United States, emissions from N20 Product Usage, the only source of
18 greenhouse gas emissions from this sector, accounted for less than 0.1 percent of total U.S. anthropogenic
19 greenhouse gas emissions on a carbon equivalent basis in 2005.
20 Agriculture
21 The Agricultural chapter contains anthropogenic emissions from agricultural activities (except fuel combustion,
22 which is addressed in the Energy chapter, and agricultural C02 fluxes, which are addressed in the Land Use, Land-
23 Use Change, and Forestry Chapter). Agricultural activities contribute directly to emissions of greenhouse gases
24 through a variety of processes, including the following source categories: enteric fermentation in domestic livestock,
25 livestock manure management, rice cultivation, agricultural soil management, and field burning of agricultural
26 residues. CH4 and N20 were the primary greenhouse gases emitted by agricultural activities. CH4 emissions from
27 enteric fermentation and manure management represented about 21 percent and 8 percent of total CH4 emissions
28 from anthropogenic activities, respectively, in 2005. Agricultural soil management activities such as fertilizer
29 application and other cropping practices were the largest source of U.S. N20 emissions in 2005, accounting for 78
30 percent. In 2005, emission sources accounted for in the Agricultural chapters were responsible for 7.4 percent of
31 total U.S. greenhouse gas emissions.
32 Land Use, Land-Use Change, and Forestry
33 The Land Use, Land-Use Change, and Forestry chapter contains emissions of CH4 and N20, and emissions and
34 removals of C02 from forest management, other land-use activities, and land-use change. Forest management
35 practices, tree planting in urban areas, the management of agricultural soils, and the landfilling of yard trimmings
36 and food scraps have resulted in a net uptake (sequestration) of C in the United States. Forests (including
37 vegetation, soils, and harvested wood) accounted for approximately 84 percent of total 2005 sequestration, urban
38 trees accounted for 11 percent, agricultural soils (including mineral and organic soils and the application of lime)
39 accounted for 2 percent, and landfilled yard trimmings and food scraps accounted for 1 percent of the total
40 sequestration in 2005. The net forest sequestration is a result of net forest growth and increasing forest area, as well
41 as a net accumulation of carbon stocks in harvested wood pools. The net sequestration in urban forests is a result of
42 net tree growth in these areas. In agricultural soils, mineral soils account for a net C sink that is almost two times
43 larger than the sum of emissions from organic soils and liming. The mineral soil C sequestration is largely due to
44 the conversion of cropland to permanent pastures and hay production, a reduction in summer fallow areas in semi-
45 arid areas, an increase in the adoption of conservation tillage practices, and an increase in the amounts of organic
12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Public Review Draft
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 2005 resulted in a net C sequestration of 828.4 Tg C02 Eq.
(Table ES-5). This represents an offset of approximately 13.6 percent of total U.S. C02 emissions, or 11.4 percent
of total greenhouse gas emissions in 2005. Total land use, land-use change, and forestry net C sequestration
increased by approximately 16 percent between 1990 and 2005, 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. Net U.S. emissions (all sources and sinks) increased by 16.4 percent from
1990 to 2005.
Non-C02 emissions from Land Use, Land-Use Change, and Forestry are shown in Table ES-6. The application of
synthetic fertilizers to forest and settlement soils in 2005 resulted in direct N20 emissions of 6.2 Tg C02 Eq. Direct
N20 emissions from fertilizer application increased by approximately 19 percent between 1990 and 2005. Non-C02
emissions from forest fires in 2005 resulted in CH4 emissions of 11.6 Tg C02 Eq., and in N20 emissions of 1.2 Tg
C02 Eq.
Table ES-5: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
1990
1995
2000
2001
2002
2003
2004
2005
Forest Land Remaining Forest Land
(598.5)
1 (717.5)
(638.7)
(645.7)
(688.1)
(687.0)
(697.3)
(698.7)
Changes in Forest Carbon Stocks
(598.5)
(717.5) ''i
(638.7)
(645.7)
(688.1)
(687.0)
(697.3)
(698.7)
Cropland Remaining Cropland
(28.1)
(37.4)
(36.5)
(38.0)
(37.8)
(38.3)
(39.4)
(39.4)
Changes in Agricultural Soil Carbon
Stocks and Liming Emissions
(28.1)
(37.4)
(36.5)
(38.0)
(37.8)
(38.3)
(39.4)
(39.4)
Land Converted to Cropland
8.7 1
7.2 ¦
7.2
7.2
7.2
7.2
7.2
7.2
Changes in Agricultural Soil Carbon
Stocks
8.7
7.2
7.2
7.2
7.2
7.2
7.2
7.2
Grassland Remaining Grassland
0.1
16.-1
16.3
16.2
16.2
16.2
16.1
16.1
Changes in Agricultural Soil Carbon
Stocks
0.1
16.4
16.3
16.2
16.2
16.2
16.1
16.1
Land Converted to Grassland
(14.6)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
Changes in Agricultural Soil Carbon
Stocks
(14.6) '
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
Settlements Remaining Settlements
(57.5)
(67.8),
(78.2)
(80.2)
(82.3)
(84.4)
(86.4)
(88.5)
Urban Trees
(57.5) 1
1 (67'8)' ''
(78.2)
(80.2)
(82.3)
(84.4)
(86.4)
(88.5)
Other
(23.0)"
(13.0)
(8.5)
(8.6)
(8.9)
(9.0)
(8.9)
(8.8)
Landfilled Yard Trimmings and Food
Scraps
(23.0)
(13.0).
(8.5)
(8.6)
(8.9)
(9.0)
(8.9)
(8.8)
Total
(712.9)
1 (828.5);
(754.7)
(765.5)
(809.9)
(811.6)
(824.9)
(828.4)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
Table ES-6: Non-C02 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
1990
1995
2000
2001
2002
2003
2004
2005
Forest Land Remaining Forest Land
7.N
4.5
15.7
6.9
11.8
9.2
8.0
13.1
CH4 Emissions from Forest Fires
7 1
4.(
14.0
6.0
10.4
8.1
6.9
11.6
N20 Emissions from Forest Fires
0."
0.4
1.4
0.6
1.1
0.8
0.7
1.2
N20 Emissions from Soils
0.1
o.:
0.3
0.3
0.3
0.3
0.3
0.3
Settlements Remaining Settlements
5.1
5.5
5.6
5.5
5.6
5.8
6.0
5.8
N20 Emissions from Soils
5 1
5.5
5.6
5.5
5.6
5.8
6.0
5.8
Total
13.0
10.1
21.3
12.4
17.4
15.0
13.9
18.9
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
Executive Summary ES-13
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Public Review Draft
Waste
The Waste chapter contains emissions from waste management activities (except waste incineration, which is
addressed in the Energy chapter). Landfills were the largest source of anthropogenic CH4 emissions, accounting for
24 percent of total U.S. CH4 emissions.12 Additionally, wastewater treatment accounts for just under 5 percent of
U.S. CH4 emissions. Nitrous oxide (N20) emissions from the discharge of wastewater treatment effluents into
aquatic environments were estimated, as were N20 emissions from the treatment process itself. Overall, in 2005,
emission sources accounted for in the Waste chapter generated 2.3 percent of total U.S. greenhouse gas emissions.
Other Information
Emissions by Economic Sector
Throughout the Inventory of U.S. Greenhouse Gas Emissions and Sinks report, emission estimates are grouped into
six sectors (i.e., chapters) defined by the IPCC: Energy, Industrial Processes, Solvent Use, Agriculture, Land Use,
Land-Use Change, and Forestry, and Waste. While it is important to use this characterization for consistency with
UNFCCC reporting guidelines, it is also useful to allocate emissions into more commonly used sectoral categories.
This section reports emissions by the following economic sectors: Residential, Commercial, Industry,
Transportation, Electricity Generation, and 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 2005.
Figure ES-13: Emissions Allocated to Economic Sectors
Table ES-7: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq.)
Implied Sectors
1990
1995
2000
2001
2002
2003
2004
2005
Electric Power Industry
1,859.7
1,989.5
2,329.9
2,292.0
2,300.9
2,330.3
2,363.5
2,429.9
Transportation
1,523.0
1,677.2
1,903.2
1,876.4
1,931.2
1,928.2
1,982.6
2,010.5
Industry
1,470.9
1,478.4
1,443.5
1,395.5
1,380.0
1,372.2
1,403.8
1,347.6
Agriculture
585.3
589.2
614.3
618.4
602.6
575.5
566.7
600.7
Commercial
417.8
420.5
415.5
406.6
413.7
433.5
432.6
431.4
Residential
351.3
375.1
393.6
383.6
382.7
404.8
391.6
380.7
U.S. Territories
34.1
41.1
47.3
54.5
53.6
60.0
63.2
61.5
Total Emissions
6,242.1
6,571.0
7,147.3
7,027.1
7,064.8
7,104.4
7,203.9
7,262.3
Land Use, Land-Use Change, and
Forestry (Sinks)
(712.9)
(828.5)
(754.7)
(765.5)
(809.9)
(811.6)
(824.9)
(828.4)
Net Emissions (Sources and Sinks)
5,529.1
5 742 5
9 *
6,392.6
6,261.6
6,254.8
6,292.8
6,379.0
6,433.9
Note: Totals may not sum due to independent rounding. Emissions include C02, CH4, N20, HFCs, PFCs, and SF6.
See Table 2-14 for more detailed data.
Using this categorization, emissions from electricity generation accounted for the largest portion (33 percent) of
U.S. greenhouse gas emissions in 2005. 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 2005.
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
12 Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as
described in the Land-Use, Land-Use Change, and Forestry chapter of the Inventory report.
14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
improvements. The remaining 20 percent of U.S. greenhouse gas emissions were contributed by the residential,
agriculture, and commercial sectors, plus emissions from U.S. territories. The residential sector accounted for about
5 percent, and primarily consisted of C02 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 N20 emissions from agricultural soil management and CH4 emissions from enteric fermentation,
rather than C02 from fossil fuel combustion. The commercial sector accounted for about 6 percent of emissions,
while U.S. territories accounted for 1 percent.
C02 was also emitted and sequestered by a variety of activities related to forest management practices, tree planting
in urban areas, the management of agricultural soils, and landfilling of yard trimmings.
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.13 These source categories include C02 from
fossil fuel combustion and the use of limestone and dolomite for flue gas desulfurization, C02 and N20 from waste
combustion, CH4 and N20 from stationary sources, and SF6 from electrical transmission and distribution systems.
When emissions from electricity are distributed among these sectors, industry accounts for the largest share of U.S.
greenhouse gas emissions (28 percent) in 2005. 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, C02 accounts for more than 80 percent of greenhouse
gas emissions, primarily from the combustion of fossil fuels. Figure ES-14 shows the trend in these emissions by
sector from 1990 to 2005.
Table ES-8: U.S Greenhouse Gas Emissions by Economic Sector with Electricity-Related Emissions Distributed
(Tg CO? Eq.)
Implied Sectors
1990
1995
2000
2001
2002
2003
2004
2005
Industry
2,111.1
2,141.5
2,185.2
2,067.2
2,046.7
2,061.8
2,090.5
2,029.6
Transportation
1,526.1
1,680.3
1,906.7
1,879.8
1,934.7
1,932.5
1,987.1
2,015.8
Commercial
967.2
1,019.1-
1,167.4
1,176.9
1,177.1
1,196.2
1,214.1
1,238.5
Residential
956V
1,030,(.
1,167.0
1,160.3
1,184.3
1,216.3
1,214.2
1,248.0
Agriculture
646.5
657.(>
673.7
688.5
668.4
637.6
634.8
668.9
U.S. Territories
34 1
41 1
47.3
54.5
53.6
60.0
63.2
61.5
Total Emissions
6,242.1
6,5'1.n
7,147.3
7,027.1
7,064.8
7,104.4
7,203.9
7,262.3
Land Use, Land-Use Change, and
Forestry (Sinks)
(712 '))
(82S ^ i
(754.7)
(765.5)
(809.9)
(811.6)
(824.9)
(828.4)
Net Emissions (Sources and Sinks)
5,529.1
5,742.5
6,392.6
6,261.6
6,254.8
6,292.8
6,379.0
6,433.9
See Table 2-16 for more detailed data.
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors
13 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.
Executive Summary ES-15
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
[BEGIN BOX]
Box ES-2: Recent Trends in Various U.S. Greenhouse Gas Emissions-Related Data
Total emissions can be compared to other economic and social indices to highlight changes over time. These
comparisons include: 1) emissions per unit of aggregate energy consumption, because energy-related activities are
the largest sources of emissions; 2) emissions per unit of fossil fuel consumption, because almost all energy-related
emissions involve the combustion of fossil fuels; 3) emissions per unit of electricity consumption, because the
electric power industry—utilities and nonutilities combined—was the largest source of U.S. greenhouse gas
emissions in 2005; 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 1.0 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). Overall, global atmospheric
C02 concentrations—a function of many complex anthropogenic and natural processes worldwide—arc increasing
at 0.4 percent per year.
Table ES-9: Recent Trends in Various U.S. Data (Index 1990
= 100) and Global Atmospheric C02 Concentration
1
Growth
Variable
1990
I 1995
2000
2001
2002
2003
2004
2005
Ratef
Greenhouse Gas Emissions3
100
10<
115
113
113
114
115
116
1.0%
Energy Consumption13
100
108
117
114
116
117
119
118
1.1%
Fossil Fuel Consumption13
100
107
117
115
116
118
119
119
1.2%
Electricity Consumption13
100
112
127
125
128
129
131
134
2.0%
GDP°
100
113
138
139
141
145
150
155
3.0%
Population11
100
107
113
114
115
116
117
118
1.1%
Atmospheric C02 Concentration6
100
I 102
104
105
105
106
106
106
0.4%
a GWP weighted values
b Energy content weighted values (EIA 2006b)
c Gross Domestic Product in chained 2000 dollars (BEA 2006)
d U.S. Census Bureau (2006)
e Hofmann (2004)
f Average annual growth rate
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product
Source: BEA (2006), U.S. Census Bureau (2006), and emission estimates in this report.
[END BOX]
Indirect Greenhouse Gases (CO, NOx, NMVOCs, and S02)
The reporting requirements of the UNFCCC'' request that information be provided on indirect greenhouse gases,
which include CO, NOx, NMVOCs, and S02. These gases do not have a direct global warming effect, but indirectly
affect terrestrial radiation absorption by influencing the formation and destruction of tropospheric and stratospheric
14 See .
16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
ozone, or, in the case of S02, by affecting the absorptive characteristics of the atmosphere. Additionally, some of
these gases may react with other chemical compounds in the atmosphere to form compounds that are greenhouse
gases.
Since 1970, the United States has published estimates of annual emissions of CO, NOx, NMVOCs, and S02 (EPA
2006),15 which are regulated under the Clean Air Act. Table ES-10 shows that fuel combustion accounts for the
majority of emissions of these indirect greenhouse gases. Industrial processes—such as the manufacture of
chemical and allied products, metals processing, and industrial uses of solvents—are also significant sources of CO,
NOx, and NMVOCs.
Table ES-10: Emissions of NOx, CO, NMVOCs, and S02 (Gg)
Gas/Activity
1990
1995
2000
2001
2002
2003
2004
2005
NOx
21,645
21,272
19,203
18,410
18,141
17,327
16,466
15,965
Mobile Fossil Fuel Combustion
10,920
10,622
10,310
9,819
10,319
9,911
9,520
9,145
Stationary Fossil Fuel Combustion
9,883
9,821
8,002
7,667
6,837
6,428
5,952
5,824
Industrial Processes
591
607
626
656
532
533
534
535
Oil and Gas Activities
139
100
111
113
316
317
317
318
Waste Combustion
82
88
114
114
97
98
98
98
Agricultural Burning
28
29
35
35
33
34
39
39
Solvent Use
1
3
3
3
5
5
5
5
Waste
0
1
2
2
2
2
2
2
CO
130,581
109,157
92,897
89,333
86,796
84,370
82,073
79,811
Mobile Fossil Fuel Combustion
119,480
97,755
83,680
79,972
77,382
74,756
72,269
69,915
Stationary Fossil Fuel Combustion
5,000
5,383
4,340
4,377
5,224
5,292
5,361
5,431
Waste Combustion
978
1,073
1,670
1,672
1,440
1,457
1,475
1,493
Industrial Processes
4,125
3,959
2,217
2,339
1,710
1,730
1,751
1,772
Agricultural Burning
691
663
792
774
709
800
879
858
Oil and Gas Activities
302
316
146
147
323
327
331
335
Waste
1
2
8
8
7
7
7
7
Solvent Use
5
5
46
45
1
1
1
1
NMVOCs
20,930
19,520
15,228
15,048
14,968
14,672
14,391
14,123
Mobile Fossil Fuel Combustion
10,932
8,745
7,230
6,872
6,608
6,302
6,011
5,734
Solvent Use
5,216
5,609
4,384
4,547
3,911
3,916
3,921
3,926
Industrial Processes
2,422
2,642
1,773
1,769
1,811
1,813
1,815
1,818
Stationary Fossil Fuel Combustion
912
973
1,077
1,080
1,733
1,734
1,735
1,736
Oil and Gas Activities
554
582
389
400
546
547
547
548
Waste Combustion
222
237
257
258
244
244
244
245
Waste
673
731
119
122
116
116
116
116
Agricultural Burning
NA
NA
NA
NA
NA
NA
NA
NA
so2
20,935
16,891
14,829
14,452
13,541
13,648
13,328
13,271
Stationary Fossil Fuel Combustion
18,407
14,724
12,848
12,461
11,852
12,002
11,721
11,698
Industrial Processes
1,307
1,117
1,031
1,047
752
759
766
774
Mobile Fossil Fuel Combustion
793
672
632
624
681
628
579
535
Oil and Gas Activities
390
335 '
286
289
233
235
238
240
Waste Combustion
38
42
29
30
23
23
23
23
Waste
0
1
1
1
1
1
1
1
Solvent Use
0
1
1
1
0
0
0
0
Agricultural Burning
NA
NA
NA
NA
NA
NA
NA
NA
Source: (EPA 2006, disaggregated based on EPA 2003) except for estimates from field burning of agricultural residues.
15 NOx and CO emission estimates from field burning of agricultural residues were estimated separately, and therefore not taken
from EPA (2006).
Executive Summary ES-17
-------
Public Review Draft
1 NA (Not Available)
2 Note: Totals may not sum due to independent rounding.
3
4 Key Categories
5 The IPCC's Good Practice Guidance (IPCC 2000) defines a key category as a "[source or sink category] that is
6 prioritized within the national inventory system because its estimate has a significant influence on a country's total
7 inventory of direct greenhouse gases in terms of the absolute level of emissions, the trend in emissions, or both."16
8 By definition, key categories are sources or sinks that have the greatest contribution to the absolute overall level of
9 national emissions in any of the years covered by the time series. In addition, when an entire time series of emission
10 estimates is prepared, a thorough investigation of key categories must also account for the influence of trends of
11 individual source and sink categories. Finally, a qualitative evaluation of key categories should be performed, in
12 order to capture any key categories that were not identified in either of the quantitative analyses.
13 Figure ES-16 presents 2005 emission estimates for the key categories as defined by a level analysis (i.e., the
14 contribution of each source or sink category to the total inventory level). The UNFCCC reporting guidelines
15 request that key category analyses be reported at an appropriate level of disaggregation, which may lead to source
16 and sink category names which differ from those used elsewhere in the Inventory report. For more information
17 regarding key categories, see section 1.5 and Annex 1 of the Inventory report.
18
19 Figure ES-16: 2005 Key Categories—Tier 1 Level Assessment
20
21 Quality Assurance and Quality Control (QA/QC)
22 The United States seeks to continually improve the quality, transparency and credibility of the Inventory of U.S.
23 Greenhouse Gas Emissions and Sinks. To assist in these efforts, the United States implemented a systematic
24 approach to QA/QC. While QA/QC has always been an integral part of the U.S. national system for inventory
25 development, the procedures followed for the current inventory have been formalized in accordance with the
26 QA/QC plan and the UNFCCC reporting guidelines.
27 Uncertainty Analysis of Emission Estimates
28 While the current U.S. emissions inventory provides a solid foundation for the development of a more detailed and
29 comprehensive national inventory, there are uncertainties associated with the emission estimates. Some of the
30 current estimates, such as those for C02 emissions from energy-related activities and cement processing, are
31 considered to have low uncertainties. For some other categories of emissions, however, a lack of data or an
32 incomplete understanding of how emissions are generated increases the uncertainty associated with the estimates
33 presented. Acquiring a better understanding of the uncertainty associated with inventory estimates is an important
34 step in helping to prioritize future work and improve the overall quality of the inventory. Recognizing the benefit of
35 conducting an uncertainty analysis, the UNFCCC reporting guidelines follow the recommendations of the IPCC
36 Good Practice Guidance (IPCC 2000) and require that countries provide single estimates of uncertainty for source
37 and sink categories.
38 Currently, a qualitative discussion of uncertainty is presented for all source and sink categories. Within the
39 discussion of each emission source, specific factors affecting the uncertainty surrounding the estimates are
16 See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 discussed. Most sources also contain a quantitative uncertainty assessment, in accordance with UNFCCC reporting
2 guidelines.
Executive Summary ES-19
-------
-------
¦ HFCs, PFCs, & SF
Nitrous Oxide
_ Methane
¦ Carbon Dioxide
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Figure ES-1: U.S. GHG Emissions by Gas
3.1%
-0.9%
-1.7%
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Figure ES-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Figure ES-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990
-------
HFCs,
N20
ch4
PFCs & SF6
2.2%
6.5%
7.4%
CO,
83.9%
Figure ES-4: 2005 Greenhouse Gas Emissions by Gas
Fossil Combustion 5,752.8
Non-Energy Use Fuels
Cement Manufacture
Iron and Steel Production
Natural Gas Systems
Waste Combustion
Ammonia Production and Urea Application
Lime Manufacture C02 as a Portion
Limestone and Dolomite Use | a" Emissions
Soda Ash Manufacture and Consumption |
Aluminum Production |
Petrochemical Production |
Titanium Dioxide Production |
Ferroalloy Production |
Phosphoric Acid Production |
Carbon Dioxide Consumption |
Zinc Production <0.5
Lead Production <0-5
Silicon Carbide Production and Consumption
<0.5
25 50 75 100 125 150 175
Tg C02 Eq
Figure ES-5: 2005 Sources of C02
-------
2,000
s i'500 -
O
u 1,000
P
500
0 J
Relative Contribution
by Fuel Type
>
Natural Gas
Petroleum
I Coal
jfc o . t
* J p
Figure ES-6: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Note: Electricity generation also includes emissions of less than 1 Tg CO 2 Eq. from geothermal-based electricity
generation.
I-
Figure ES-7: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion
-------
Landfills
Enteric Fermentation
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land I
Stationary Sources |
Rice Cultivation |
Abandoned Coal Mines |
Mobile Sources |
Petrochemical Production |
Iron and Steel Production |
Field Burning of Agricultural Residues |
Silicon Carbide Production and Consumption
Ferroalloy Production
<0.05
<0.05
20
40
CH4 as a Portion
of all Emissions
7.4%
0
60 80
Tg C02 Eq
100
120
140
Figure ES-8: 2005 Sources of CH4
Agricultural Soil Management
Mobile Sources
Nitric Acid
Stationary Sources
Manure Management |
Wastewater Treatment |
Adipic Acid |
Settlements Remaining Settlements |
N20 Product Usage |
Forest Land Remaining Forest Land |
Waste Combustion |
Field Burning of Agricultural Residues |
365.1
10
20
30
N20 as a Portion
of all Emissions
6.5%
0
40
50
Tg C02 Eq
Figure ES-9: 2005 Sources of N20
-------
Substitution of Ozone
Depleting Substances
HCFC-22 Production
Electrical Transmission
and Distribution
Semiconductor
Manufacture
Aluminum Production
Magnesium Production
and Processing
HFCs, PFCs, and SF6 as a Portion
of all Emissions
2.2%
©
25
50 75
Tg C02 Eq
100
125
Figure ES-10: 2005 Sources of HFCs, PFCs, and SF6
Industrial Processes
Waste
LULUCF (non-C02)
7,000 -
6,000
Agriculture
Land Use, Land-Use Change and Forestry (net C02 flux)
(2,000) J
T—I T—I f\l
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and Other
Product Use sector
Figure ES-11: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector
-------
6% Renewable
8% Nuclear
23%
Natural Gas
23% Coal
40%
Petroleum
Figure ES-12: 2005 U.S. Energy Consumption by Energy Source
Year
Figure ES-13: Emissions Allocated to Economic Sectors
Note: Does not include U.S. territories.
-------
2,500
Industrial
Transportation
Residential (gray)
Commercial (black)
Agriculture
Figure ES-14: Emissions with Electricity Distributed to Economic Sectors
Note: Does not include U.S. territories.
Figure ES-15: U.S. Greenhouse Gas Emissions Per Capita
and Per Dollar of Gross Domestic Product
-------
C02 Emissions from Stationary Combustion - Coal
Mobile Combustion: Road & Other
C02 Emissions from Stationary Combustion - Gas
C02 Emissions from Stationary Combustion - Oil
Direct N20 Emissions from Agricultural Soil Management
Mobile Combustion: Aviation ¦
C02 Emissions from Non-Energy Use of Fuels |
CH4 Emissions from Landfills |
Emissions from Substitutes for Ozone Depleting Substances |
CH4 Emissions from Enteric Fermentation |
Fugitive Emissions from Natural Gas Systems |
Mobile Combustion: Marine |
Indirect N20 Emissions from Applied Nitrogen |
Fugitive Emissions from Coal Mining |
C02 Emissions from Cement Manufacture |
C02 Emissions from Iron and Steel Production |
0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 2,200
Tg C02 Eq
Figure ES-16: 2005 Key Categories - Tier 1 Level Assessment
Note: For a complete discussion of the key source analysis see Annex 1
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
1. Introduction
This report presents estimates by the United States government of U.S. anthropogenic greenhouse gas emissions and
sinks for the years 1990 through 2005. A summary of these estimates is provided in Table 2-3 and Table 2-4 by gas
and source category in the Trends in Greenhouse Gas Emissions chapter. The emission estimates in these tables are
presented on both a full molecular mass basis and on a Global Warming Potential (GWP) weighted basis in order to
show the relative contribution of each gas to global average radiative forcing.1 This report also discusses the
methods and data used to calculate these emission estimates.
In 1992, the United States signed and ratified the United Nations Framework Convention on Climate Change
(UNFCCC). As stated in Article 2 of the UNFCCC, "The ultimate objective of this Convention and any related
legal instruments that the Conference of the Parties may adopt is to achieve, in accordance with the relevant
provisions of the Convention, stabilization of greenhouse gas concentrations in the atmosphere at a level that would
prevent dangerous anthropogenic interference with the climate system. Such a level should be achieved within a
time-frame sufficient to allow ecosystems to adapt naturally to climate change, to ensure that food production is not
threatened and to enable economic development to proceed in a sustainable manner."2'3
Parties to the Convention, by ratifying, "shall develop, periodically update, publish and make available.. .national
inventories of anthropogenic emissions by sources and removals by sinks of all greenhouse gases not controlled by
the Montreal Protocol, using comparable methodologies.. ."4 The United States views this report as an opportunity
to fulfill these commitments under the UNFCCC.
In 1988, preceding the creation of the UNFCCC, the World Meteorological Organization (WMO) and the United
Nations Environment Programme (UNEP) jointly established the Intergovernmental Panel on Climate Change
(IPCC). The role of the IPCC is to assess on a comprehensive, objective, open and transparent basis the scientific,
technical and socio-economic information relevant to understanding the scientific basis of risk of human-induced
climate change, its potential impacts and options for adaptation and mitigation (IPCC 2003). Under Working Group
1 of the IPCC, nearly 140 scientists and national experts from more than thirty countries collaborated in the creation
of the Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997) to
ensure that the emission inventories submitted to the UNFCCC are consistent and comparable between nations. The
IPCC accepted the Revised 1996IPCC Guidelines at its Twelfth Session (Mexico City, September 11-13, 1996).
This report presents information in accordance with these guidelines. In addition, this inventory is in accordance
with the IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories and
the Good Practice Guidance for Land Use, Land-Use Change, and Forestry, which further expanded upon the
methodologies in the Revised 1996 IPCC Guidelines. The IPCC has also accepted the 2006 Guidelines for National
Greenhouse Gas Inventories (IPCC 2006) at its Twenty-Fifth Session (Mauritius, April 2006). The 2006 IPCC
Guidelines build on the previous bodies of work and includes new sources and gases "... as well as updates to the
previously published methods whenever scientific and technical knowledge have improved since the previous
guidelines were issued." Many of the methodological improvements presented in the 2006 Guidelines have been
adopted in this inventory.
Overall, this inventory of anthropogenic greenhouse gas emissions provides a common and consistent mechanism
through which Parties to the UNFCCC can estimate emissions and compare the relative contribution of individual
1 See the section below entitled Global Warming Potentials for an explanation of GWP values.
2 The term "anthropogenic", in this context, refers to greenhouse gas emissions and removals that are a direct result of human
activities or are the result of natural processes that have been affected by human activities (IPCC/UNEP/OECD/IEA 1997).
3 Article 2 of the Framework Convention on Climate Change published by the UNEP/WMO Information Unit on Climate
Change. See . (UNEP/WMO 2000)
4 Article 4(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
.
Trends in Greenhouse Gas Emissions 1-1
-------
Public Review Draft
1 sources, gases, and nations to climate change. The structure of this report is consistent with the current UNFCCC
2 Guidelines on Annual Inventories (UNFCCC 2006).
3 1.1. Background Information
4 Greenhouse Gases
5 Although the Earth's atmosphere consists mainly of oxygen and nitrogen, neither plays a significant role in
6 enhancing the greenhouse effect because both are essentially transparent to terrestrial radiation. The greenhouse
7 effect is primarily a function of the concentration of water vapor, carbon dioxide (C02), and other trace gases in the
8 atmosphere that absorb the terrestrial radiation leaving the surface of the Earth (IPCC 2001). Changes in the
9 atmospheric concentrations of these greenhouse gases can alter the balance of energy transfers between the
10 atmosphere, space, land, and the oceans.5 A gauge of these changes is called radiative forcing, which is a measure
11 of the influence a factor has in altering the balance of incoming and outgoing energy in the Earth-atmosphere
12 system (IPCC 2001). Holding everything else constant, increases in greenhouse gas concentrations in the
13 atmosphere will produce positive radiative forcing (i.e., a net increase in the absorption of energy by the Earth).
14 Climate change can be driven by changes in the atmospheric concentrations of a number of radiatively
15 active gases and aerosols. We have clear evidence that human activities have affected concentrations,
16 distributions and life cycles of these gases (IPCC 1996).
17 Naturally occurring greenhouse gases include water vapor, C02, methane (CH4), nitrous oxide (N20), and ozone
18 (03). Several classes of halogenated substances that contain fluorine, chlorine, or bromine are also greenhouse
19 gases, but they are, for the most part, solely a product of industrial activities. Chlorofluorocarbons (CFCs) and
20 hydrochlorofluorocarbons (HCFCs) are halocarbons that contain chlorine, while halocarbons that contain bromine
21 are referred to as bromofluorocarbons (i.e., halons). As stratospheric ozone depleting substances, CFCs, HCFCs,
22 and halons are covered under the Montreal Protocol on Substances that Deplete the Ozone Layer. The UNFCCC
23 defers to this earlier international treaty. Consequently, Parties to the UNFCCC are not required to include these
24 gases in national greenhouse gas inventories.6 Some other fluorine-containing halogenated substances—
25 hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)—do not deplete stratospheric
26 ozone but are potent greenhouse gases. These latter substances are addressed by the UNFCCC and accounted for in
27 national greenhouse gas inventories.
28 There are also several gases that, although they do not have a commonly agreed upon direct radiative forcing effect,
29 do influence the global radiation budget. These tropospheric gases include carbon monoxide (CO), nitrogen dioxide
30 (N02), sulfur dioxide (S02), and tropospheric (ground level) 03. Tropospheric ozone is formed by two precursor
31 pollutants, volatile organic compounds (VOCs) and nitrogen oxides (NOx) in the presence of ultraviolet light
32 (sunlight). Aerosols are extremely small particles or liquid droplets that are often composed of sulfur compounds,
33 carbonaceous combustion products, crustal materials and other human induced pollutants. They can affect the
34 absorptive characteristics of the atmosphere. Comparatively, however, the level of scientific understanding of
35 aerosols is still very low (IPCC 2001).
36 C02, CH4, and N20 are continuously emitted to and removed from the atmosphere by natural processes on Earth.
37 Anthropogenic activities, however, can cause additional quantities of these and other greenhouse gases to be emitted
38 or sequestered, thereby changing their global average atmospheric concentrations. Natural activities such as
39 respiration by plants or animals and seasonal cycles of plant growth and decay are examples of processes that only
40 cycle carbon or nitrogen between the atmosphere and organic biomass. Such processes, except when directly or
5 For more on the science of climate change, see NRC (2001).
6 Emissions estimates of CFCs, HCFCs, halons and other ozone-depleting substances are included in this document for
informational purposes.
1-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
indirectly perturbed out of equilibrium by anthropogenic activities, generally do not alter average atmospheric
greenhouse gas concentrations over decadal timeframes. Climatic changes resulting from anthropogenic activities,
however, could have positive or negative feedback effects on these natural systems. Atmospheric concentrations of
these gases, along with their rates of growth and atmospheric lifetimes, are presented in Table 1-1.
Table 1-1: Global Atmospheric Concentration, Rate of Concentration Change, and Atmospheric Lifetime (years) of
Selected Greenhouse Gases
Atmospheric Variable CP2 CH4 N2Q SF^ CF4
Pre-industrial atmospheric
concentration 280 ppm 0.722 ppm 0.270 ppm 0 ppt 40 ppt
Atmospheric concentration3 376.7 ppm 1.756 ppm 0.319 ppm 5.4 ppt 80 ppt
Rate of concentration changeb 1,610 ppm/yr 0.005 ppm/yr 0.0007 ppm/yr 0.23 ppt/yr l.Oppt/yr
Atmospheric lifetime 50-200° Yf 3,200 >50,000
Source: Current atmospheric concentrations and rate of concentration changes for all gases but CF4 are from Hofmann (2004),
data for CF4 are from IPCC (2001). Pre-industrial atmospheric concentration and atmospheric lifetime taken from IPCC (2001).
a Concentration for CF4 was measured in 2000. Concentrations for all other gases were measured in 2004.
b Rate is calculated over the period 1990 to 2004 for C02, CH4, and N20; 1996 to 2004 for SF6; and 1990 to 1999 for CF4.
: No single lifetime can be defined for C02 because of the different rates of uptake by different removal processes.
1 This
time.
d This lifetime has been defined as an "adjustment time" that takes into account the indirect effect of the gas on its own residence
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 (H20). 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
C02. Atmospheric C02 is part of this global carbon cycle, and therefore its fate is a complex function of
geochemical and biological processes. C02 concentrations in the atmosphere increased from approximately 280
parts per million by volume (ppmv) in pre-industrial times to 376.7 ppmv in 2004, a 35 percent increase (IPCC
2001 and Hofmann 2004).7'8 The IPCC definitively states that "the present atmospheric C02 increase is caused by
anthropogenic emissions of C02" (IPCC 2001). The predominant source of anthropogenic C02 emissions is the
combustion of fossil fuels. Forest clearing, other biomass burning, and some non-energy production processes (e.g.,
cement production) also emit notable quantities of C02.
In its second assessment, the IPCC also stated that "[t]he increased amount of C02 [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
7 The pre-industrial period is considered as the time preceding the year 1750 (IPCC 2001).
8 Carbon dioxide concentrations during the last 1,000 years of the pre-industrial period (i.e., 750-1750), a time of relative climate
stability, fluctuated by about +10 ppmv around 280 ppmv (IPCC 2001).
Trends in Greenhouse Gas Emissions 1-3
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
greenhouse effect—although the magnitude and significance of the effects are not fully resolved" (IPCC 1996).
Methane. CH4 is primarily produced through anaerobic decomposition of organic matter in biological systems.
Agricultural processes such as wetland rice cultivation, enteric fermentation in animals, and the decomposition of
animal wastes emit CH4, as does the decomposition of municipal solid wastes. CH4 is also emitted during the
production and distribution of natural gas and petroleum, and is released as a by-product of coal mining and
incomplete fossil fuel combustion. Atmospheric concentrations of CH4 have increased by about 143 percent since
1750, from a pre-industrial value of about 722 ppb to 1,756 ppb in 2004, although the rate of increase has been
declining. The IPCC has estimated that slightly more than half of the current CH4 flux to the atmosphere is
anthropogenic, from human activities such as agriculture, fossil fuel use, and waste disposal (IPCC 2001).
CH4 is removed from the atmosphere through a reaction with the hydroxyl radical (OH) and is ultimately converted
to C02. Minor removal processes also include reaction with chlorine in the marine boundary layer, a soil sink, and
stratospheric reactions. Increasing emissions of CH4 reduce the concentration of OH, a feedback that may increase
the atmospheric lifetime of CH4 (IPCC 2001).
Nitrous Oxide. Anthropogenic sources of N20 emissions include agricultural soils, especially production of
nitrogen-fixing crops and forages, the use of synthetic and manure fertilizers, and manure deposition by livestock;
fossil fuel combustion, especially from mobile combustion; adipic (nylon) and nitric acid production; wastewater
treatment and waste combustion; and biomass burning. The atmospheric concentration of N20 has increased by 18
percent since 1750, from a pre-industrial value of about 270 ppb to 319 ppb in 2004, a concentration that has not
been exceeded during the last thousand years. N20 is primarily removed from the atmosphere by the photolytic
action of sunlight in the stratosphere (IPCC 2001).
Ozone. Ozone is present in both the upper stratosphere,9 where it shields the Earth from harmful levels of
ultraviolet radiation, and at lower concentrations in the troposphere,10 where it is the main component of
anthropogenic photochemical "smog." During the last two decades, emissions of anthropogenic chlorine and
bromine-containing halocarbons, such as CFCs, have depleted stratospheric ozone concentrations. This loss of
ozone in the stratosphere has resulted in negative radiative forcing, representing an indirect effect of anthropogenic
emissions of chlorine and bromine compounds (IPCC 1996). The depletion of stratospheric ozone and its radiative
forcing was expected to reach a maximum in about 2000 before starting to recover, with detection of such recovery
not expected to occur much before 2010 (IPCC 2001).
The past increase in tropospheric ozone, which is also a greenhouse gas, is estimated to provide the third largest
increase in direct radiative forcing since the pre-industrial era, behind C02 and CH4. Tropospheric ozone is
produced from complex chemical reactions of volatile organic compounds mixing with NOx in the presence of
sunlight. The tropospheric concentrations of ozone and these other pollutants are short-lived and, therefore,
spatially variable. (IPCC 2001)
Halocarbons, Perfluorocarbons, and Sulfur Hexafluoride. Halocarbons are, for the most part, man-made chemicals
that have both direct and indirect radiative forcing effects. Halocarbons that contain chlorine (CFCs, HCFCs,
methyl chloroform, and carbon tetrachloride) and bromine (halons, methyl bromide, and hydrobromofluorocarbons
[HBFCs]) result in stratospheric ozone depletion and are therefore controlled under the Montreal Protocol on
Substances that Deplete the Ozone Layer. Although CFCs and HCFCs include potent global warming gases, their
9 The stratosphere is the layer from the troposphere up to roughly 50 kilometers. In the lower regions the temperature is nearly
constant but in the upper layer the temperature increases rapidly because of sunlight absorption by the ozone layer. The ozone-
layer is the part of the stratosphere from 19 kilometers up to 48 kilometers where the concentration of ozone reaches up to 10
parts per million.
10 The troposphere is the layer from the ground up to 11 kilometers near the poles and up to 16 kilometers in equatorial regions
(i.e., the lowest layer of the atmosphere where people live). It contains roughly 80 percent of the mass of all gases in the
atmosphere and is the site for most weather processes, including most of the water vapor and clouds.
1-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
net radiative forcing effect on the atmosphere is reduced because they cause stratospheric ozone depletion, which
itself is an important greenhouse gas in addition to shielding the Earth from harmful levels of ultraviolet radiation.
Under the Montreal Protocol, the United States phased out the production and importation of halons by 1994 and of
CFCs by 1996. Under the Copenhagen Amendments to the Protocol, a cap was placed on the production and
importation of HCFCs by non-Article 511 countries beginning in 1996, and then followed by a complete phase-out
by the year 2030. While ozone depleting gases covered under the Montreal Protocol and its Amendments are not
covered by the UNFCCC; they are reported in this inventory under Annex 6.2 of this report for informational
purposes.
HFCs, PFCs, and SF6 are not ozone depleting substances, and therefore are not covered under the Montreal
Protocol. They are, however, powerful greenhouse gases. HFCs are primarily used as replacements for ozone
depleting substances but also emitted as a by-product of the HCFC-22 manufacturing process. Currently, they have
a small aggregate radiative forcing impact, but it is anticipated that their contribution to overall radiative forcing
will increase (IPCC 2001). PFCs and SF6 are predominantly emitted from various industrial processes including
aluminum smelting, semiconductor manufacturing, electric power transmission and distribution, and magnesium
casting. Currently, the radiative forcing impact of PFCs and SF6 is also small, but they have a significant growth
rate, extremely long atmospheric lifetimes, and are strong absorbers of infrared radiation, and therefore have the
potential to influence climate far into the future (IPCC 2001).
Carbon Monoxide. Carbon monoxide has an indirect radiative forcing effect by elevating concentrations of CH4
and tropospheric ozone through chemical reactions with other atmospheric constituents (e.g., the hydroxyl radical,
OH) that would otherwise assist in destroying CH4 and tropospheric ozone. Carbon monoxide is created when
carbon-containing fuels are burned incompletely. Through natural processes in the atmosphere, it is eventually
oxidized to C02. Carbon monoxide concentrations are both short-lived in the atmosphere and spatially variable.
Nitrogen Oxides. The primary climate change effects of nitrogen oxides (i.e., NO and N02) are indirect and result
from their role in promoting the formation of ozone in the troposphere and, to a lesser degree, lower stratosphere,
where it has positive radiative forcing effects.12 Additionally, NOx emissions from aircraft are also likely to
decrease CH4 concentrations, thus having a negative radiative forcing effect (IPCC 1999). Nitrogen oxides are
created from lightning, soil microbial activity, biomass burning (both natural and anthropogenic fires) fuel
combustion, and, in the stratosphere, from the photo-degradation of N20. Concentrations of NOx are both relatively
short-lived in the atmosphere and spatially variable.
Nonmethane Volatile Organic Compounds (NMVOCs). Non-CH4 volatile organic compounds include substances
such as propane, butane, and ethane. These compounds participate, along with NOx, in the formation of
tropospheric ozone and other photochemical oxidants. NMVOCs are emitted primarily from transportation and
industrial processes, as well as biomass burning and non-industrial consumption of organic solvents.
Concentrations of NMVOCs tend to be both short-lived in the atmosphere and spatially variable.
Aerosols. Aerosols are extremely small particles or liquid droplets found in the atmosphere. They can be produced
by natural events such as dust storms and volcanic activity, or by anthropogenic processes such as fuel combustion
and biomass burning. Aerosols affect radiative forcing differently than greenhouse gases, and their radiative effects
occur through direct and indirect mechanisms: directly by scattering and absorbing solar radiation; and indirectly by
increasing droplet counts that modify the formation, precipitation efficiency, and radiative properties of clouds.
Aerosols are removed from the atmosphere relatively rapidly by precipitation. Because aerosols generally have
11 Article 5 of the Montreal Protocol covers several groups of countries, especially developing countries, with low consumption
rates of ozone depleting substances. Developing countries with per capita consumption of less than 0.3 kg of certain ozone
depleting substances (weighted by their ozone depleting potential) receive financial assistance and a grace period of ten
additional years in the phase-out of ozone depleting substances.
12 NOx emissions injected higher in the stratosphere, primarily from fuel combustion emissions from high altitude supersonic
aircraft, can lead to stratospheric ozone depletion.
Trends in Greenhouse Gas Emissions 1-5
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
short atmospheric lifetimes, and have concentrations and compositions that vary regionally, spatially, and
temporally, their contributions to radiative forcing are difficult to quantify (IPCC 2001).
The indirect radiative forcing from aerosols is typically divided into two effects. The first effect involves decreased
droplet size and increased droplet concentration resulting from an increase in airborne aerosols. The second effect
involves an increase in the water content and lifetime of clouds due to the effect of reduced droplet size on
precipitation efficiency (IPCC 2001). Recent research has placed a greater focus on the second indirect radiative
forcing effect of aerosols.
Various categories of aerosols exist, including naturally produced aerosols such as soil dust, sea salt, biogenic
aerosols, sulfates, and volcanic aerosols, and anthropogenically manufactured aerosols such as industrial dust and
carbonaceous13 aerosols (e.g., black carbon, organic carbon) from transportation, coal combustion, cement
manufacturing, waste incineration, and biomass burning.
The net effect of aerosols on radiative forcing is believed to be negative (i.e., net cooling effect on the climate),
although because they remain in the atmosphere for only days to weeks, their concentrations respond rapidly to
changes in emissions.14 Locally, the negative radiative forcing effects of aerosols can offset the positive forcing of
greenhouse gases (IPCC 1996). "However, the aerosol effects do not cancel the global-scale effects of the much
longer-lived greenhouse gases, and significant climate changes can still result" (IPCC 1996).
The IPCC's Third Assessment Report notes that "the indirect radiative effect of aerosols is now understood to also
encompass effects on ice and mixed-phase clouds, but the magnitude of any such indirect effect is not known,
although it is likely to be positive" (IPCC 2001). Additionally, current research suggests that another constituent of
aerosols, black carbon, may have a positive radiative forcing (Jacobson 2001). The primary anthropogenic emission
sources of black carbon include diesel exhaust and open biomass burning.
Global Warming Potentials
A global warming potential is a quantified measure of the globally averaged relative radiative forcing impacts of a
particular greenhouse gas (see Table 1-2). It is defined as the ratio of the time-integrated radiative forcing from the
instantaneous release of 1 kilogram (kg) of a trace substance relative to that of 1 kg of a reference gas (IPCC 2001).
Direct radiative effects occur when the gas itself absorbs radiation. Indirect radiative forcing occurs when chemical
transformations involving the original gas produces a gas or gases that are greenhouse gases, or when a gas
influences other radiatively important processes such as the atmospheric lifetimes of other gases. The reference gas
used is C02, and therefore GWP weighted emissions are measured interagrams of C02 equivalent (Tg C02Eq.)15
The relationship between gigagrams (Gg) of a gas and Tg C02Eq. can be expressed as follows:
f Te ^
Tg CO 2 Eq = (Gg of gas) x (GWP) x
I 1,000 Gg J
where,
Tg C02Eq. = Teragrams of C02 Equivalents
Gg = Gigagrams (equivalent to a thousand metric tons)
GWP = Global Warming Potential
13 Carbonaceous aerosols are aerosols that are comprised mainly of organic substances and forms of black carbon (or soot)
(IPCC 2001).
14 Volcanic activity can inject significant quantities of aerosol producing sulfur dioxide and other sulfur compounds into the
stratosphere, which can result in a longer negative forcing effect (i.e., a few years) (IPCC 1996).
15 Carbon comprises 12/44ths of carbon dioxide by weight.
1-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Public Review Draft
Tg = Teragrams
GWP values allow for a comparison of the impacts of emissions and reductions of different gases. According to the
IPCC, GWPs typically have an uncertainty of +35 percent. The parties to the UNFCCC have also agreed to use
GWPs based upon a 100-year time horizon although other time horizon values are available.
Greenhouse gas emissions and removals should be presented on a gas-by-gas basis in units of mass... In
addition, consistent with decision 2/CP.3, Parties should report aggregate emissions and removals of
greenhouse gases, expressed in C02 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., C02, CH4, N20, HFCs, PFCs, and SF6) tend to be
evenly distributed throughout the atmosphere, and consequently global average concentrations can be determined.
The short-lived gases such as water vapor, carbon monoxide, tropospheric ozone, ozone precursors (e.g., NOx, and
NMVOCs), and tropospheric aerosols (e.g., S02 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.
Gas
Atmospheric Lifetime
GWPa
C02
50-200
1
CH4b
12+3
21
n2o
120
310
HFC-23
264
11,700
HFC-32
5.6
650
HFC-125
32.6
2,800
HFC-134a
14.6
1,300
HFC-143a
48.3
3,800
HFC-152a
1.5
140
HFC-227ea
36.5
2,900
HFC-236fa
209
6,300
HFC-4310mee
17.1
1,300
cf4
50,000
6,500
c2f6
10,000
9,200
c4f10
2,600
7,000
c6f14
3,200
7,400
sf6
3,200
23,900
Source: (IPCC 1996)
a 100-year time horizon
b The GWP of CH4 includes the direct effects and those indirect effects due to the production of tropospheric ozone and
stratospheric water vapor. The indirect effect due to the production of C02 is not included.
[Begin Box]
16 Framework Convention on Climate Change; ; 1 November 2002; Report of the
Conference of the Parties at its eighth session; held at New Delhi from 23 October to 1 November 2002; Addendum; Part One:
Action taken by the Conference of the Parties at its eighth session; Decision -/CP. 8; Communications from Parties included in
Annex I to the Convention: Guidelines for the Preparation of National Communications by Parties Included in Annex I to the
Convention, Part 1: UNFCCC reporting guidelines on annual inventories; p. 7. (UNFCCC 2003)
Trends in Greenhouse Gas Emissions 1-7
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Public Review Draft
Box 1-1: The IPCC Third Assessment Report and Global Warming Potentials
In 2001, the IPCC published its Third Assessment Report (TAR), which provided an updated and more
comprehensive scientific assessment of climate change. Within this report, the GWPs of several gases were revised
relative to the IPCC's Second Assessment Report (SAR), and new GWPs have been calculated for an expanded set
of gases. Since the SAR, the IPCC has applied an improved calculation of C02 radiative forcing and an improved
C02 response function (presented in WMO 1999). The GWPs are drawn from WMO (1999) and the SAR, with
updates for those cases where significantly different new laboratory or radiative transfer results have been
published. Additionally, the atmospheric lifetimes of some gases have been recalculated. Because the revised
radiative forcing of C02 is about 12 percent lower than that in the SAR, the GWPs of the other gases relative to C02
tend to be larger, taking into account revisions in lifetimes. In addition, the values for radiative forcing and
lifetimes have been calculated for a variety of halocarbons, which were not presented in the SAR. Table 1-3
presents the new GWPs, relative to those presented in the SAR.
Table 1-3: Comparison of 100-Year GWPs
Gas
SAR
TAR
Change
C02
1
1
NC
NC
ch4*
21
23
2
10%
n2o
310
296
(14)
(5%)
HFC-23
11,700
12,000
300
3%
HFC-32
650
550
(100)
(15%)
HFC-125
2,800
3,400
600
21%
HFC-134a
1,300
1,300
NC
NC
HFC-143a
3,800
4,300
500
13%
HFC-152a
140
120
(20)
(14%)
HFC-227ea
2,900
3,500
600
21%
HFC-236fa
6,300
9,400
3,100
49%
HFC-4310mee
1,300
1,500
200
15%
cf4
6,500
5,700
(800)
(12%)
c2f6
9,200
11,900
2,700
29%
C4F10
7,000
8,600
1,600
23%
CsFm
7,400
9,000
1,600
22%
sf6
23,900
22,200
(1,700)
(7%)
Source: (IPCC 2001)
NC (No Change)
Note: Parentheses indicate negative values.
The GWP of CH4 includes the direct effects and those indirect effects due to the production of tropospheric ozone and
stratospheric water vapor. The indirect effect due to the production of C02 is not included.
To comply with international reporting standards under the UNFCCC, official emission estimates are reported by
the United States using SAR GWP values. The UNFCCC reporting guidelines for national inventories17 were
updated in 2002 but continue to require the use of GWPs from the SAR so that current estimates of aggregate
greenhouse gas emissions for 1990 through 2005 are consistent and comparable with estimates developed prior to
the publication of the TAR. For informational purposes, emission estimates that use the updated GWPs are
presented below and in even more detail in Annex 6.1 of this report. All estimates provided throughout this report
are also presented in unweighted units.
[END BOX]
17 See .
1-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Public Review Draft
1.2. Institutional Arrangements
The U.S. Environmental Protection Agency (EPA), in cooperation with other U.S. government agencies, prepares
the Inventory of U.S. Greenhouse Gas Emissions and Sinks. A wide range of agencies and individuals are involved
in supplying data to, reviewing, or preparing portions of the U.S. Inventory—including federal and state
government authorities, research and academic institutions, industry associations, and private consultants.
Within EPA, the Office of Atmospheric Programs (OAP) is the lead office responsible for the emission calculations
provided in the Inventory, as well as the completion of the National Inventory Report and the Common Reporting
Format tables. The Office of Transportation and Air Quality (OTAQ) is also involved in calculating emissions for
the Inventory. While the U.S. Department of State officially submits the annual Inventory to the UNFCCC, EPA's
OAP serves as the focal point for technical questions and comments on the U.S. Inventory. The staff of OAP and
OTAQ coordinates the annual methodological choice, activity data collection, and emission calculations at the
individual source category level. Within OAP, an inventory coordinator compiles the entire Inventory into the
proper reporting format for submission to the UNFCCC, and is responsible for the collection and consistency of
cross-cutting issues in the Inventory.
Several other government agencies contribute to the collection and analysis of the underlying activity data used in
the Inventory calculations. Formal relationships exist between EPA and other U.S. agencies that provide official
data for use in the Inventory. The U.S. Department of Energy's Energy Information Administration provides
national fuel consumption data and the U.S. Department of Defense provides military fuel consumption and bunker
fuels. Informal relationships also exist with other U.S. agencies to provide activity data for use in EPA's emission
calculations. These include: the U.S. Department of Agriculture, the U.S. Geological Survey, the Federal Highway
Administration, the Department of Transportation, the Bureau of Transportation Statistics, the Department of
Commerce, the National Agricultural Statistics Service, and the Federal Aviation Administration. Academic and
research centers also provide activity data and calculations to EPA, as well as individual companies participating in
voluntary outreach efforts with EPA. Finally, the U.S. Department of State officially submits the Inventory to the
UNFCCC each April.
1.3. Inventory Process
EPA has a decentralized approach to preparing the annual U.S. Inventory, which consists of a National Inventory
Report (NIR) and Common Reporting Format (CRF) tables. The Inventory coordinator at EPA is responsible for
compiling all emission estimates, and ensuring consistency and quality throughout the NIR and CRF tables.
Emission calculations for individual sources are the responsibility of individual source leads, who are most familiar
with each source category and the unique characteristics of its emissions profile. The individual source leads
determine the most appropriate methodology and collect the best activity data to use in the emission calculations,
based upon their expertise in the source category, as well as coordinating with researchers and contractors familiar
with the sources. A multi-stage process for collecting information from the individual source leads and producing
the Inventory is undertaken annually to compile all information and data.
Methodology Development, Data Collection, and Emissions and Sink Estimation
Source leads at EPA collect input data and, as necessary, evaluate or develop the estimation methodology for the
individual source categories. For most source categories, the methodology for the previous year is applied to the
new "current" year of the Inventory, and inventory analysts collect any new data or update data that have changed
from the previous year. If estimates for a new source category are being developed for the first time, or if the
methodology is changing for an existing source category (e.g., the United States is implementing a higher Tiered
approach for that source category), then the source category lead will develop a new methodology, gather the most
appropriate activity data and emission factors (or in some cases direct emission measurements) for the entire time
series, and conduct a special source-specific peer review process involving relevant experts from industry,
government, and universities.
Once the methodology is in place and the data are collected, the individual source leads calculate emissions and sink
Trends in Greenhouse Gas Emissions 1-9
-------
Public Review Draft
1 estimates. The source leads then update or create the relevant text and accompanying annexes for the Inventory.
2 Source leads are also responsible for completing the relevant sectoral background tables of the Common Reporting
3 Format, conducting quality assurance and quality control (QA/QC) checks, and uncertainty analyses.
4 Summary Spreadsheet Compilation and Data Storage
5 The inventory coordinator at EPA collects the source categories' descriptive text and Annexes, and also aggregates
6 the emission estimates into a summary spreadsheet that links the individual source category spreadsheets together.
7 This summary sheet contains all of the essential data in one central location, in formats commonly used in the
8 Inventory document. In addition to the data from each source category, national trend and related data are also
9 gathered in the summary sheet for use in the Executive Summary, Introduction, and Recent Trends sections of the
10 Inventory report. Electronic copies of each year's summary spreadsheet, which contains all the emission and sink
11 estimates for the United States, are kept on a central server at EPA under the jurisdiction of the Inventory
12 coordinator.
13 National Inventory Report Preparation
14 The NIR is compiled from the sections developed by each individual source lead. In addition, the inventory
15 coordinator prepares a brief overview of each chapter that summarizes the emissions from all sources discussed in
16 the chapters. The inventory coordinator then carries out a key category analysis for the Inventory, consistent with
17 the IPCC Good Practice Guidance, IPCC Good Practice Guidance for Land Use, Land Use Change and Forestry,
18 and in accordance with the reporting requirements of the UNFCCC. Also at this time, the Introduction, Executive
19 Summary, and Recent Trends sections are drafted, to reflect the trends for the most recent year of the current
20 Inventory. The analysis of trends necessitates gathering supplemental data, including weather and temperature
21 conditions, economic activity and gross domestic product, population, atmospheric conditions, and the annual
22 consumption of electricity, energy, and fossil fuels. Changes in these data are used to explain the trends observed in
23 greenhouse gas emissions in the United States. Furthermore, specific factors that affect individual sectors are
24 researched and discussed. Many of the factors that affect emissions are included in the Inventory document as
25 separate analyses or side discussions in boxes within the text. Text boxes are also created to examine the data
26 aggregated in different ways than in the remainder of the document, such as a focus on transportation activities or
27 emissions from electricity generation. The document is prepared to match the specification of the UNFCCC
28 reporting guidelines for National Inventory Reports.
29 Common Reporting Format Table Compilation
30 The CRF tables are compiled from individual tables completed by each individual source lead, which contain source
31 emissions and activity data. The inventory coordinator integrates the source data into the UNFCCC's "CRF
32 Reporter" for the United States, assuring consistency across all sectoral tables. The summary reports for emissions,
33 methods, and emission factors used, the overview tables for completeness and quality of estimates, the recalculation
34 tables, the notation key completion tables, and the emission trends tables are then completed by the inventory
35 coordinator. Internal automated quality checks on the CRF Reporter, as well as reviews by the source leads, are
36 completed for the entire time series of CRF tables before submission.
37 QA/QC and Uncertainty
38 QA/QC and uncertainty analyses are supervised by the QA/QC coordinator, who has general oversight over the
39 implementation of the QA/QC plan and the overall uncertainty analysis for the Inventory (see sections on QA/QC
40 and Uncertainty, below). The QA/QC coordinator works closely with the source leads to ensure a consistent
41 QA/QC plan and uncertainty analysis is implemented across all inventory sources. The inventory QA/QC plan,
42 detailed in a following section, is consistent with the quality assurance procedures outlined by EPA.
43 Expert and Public Review Periods
44 During the Expert Review period, a first draft of the document is sent to a select list of technical experts outside of
45 EPA. The purpose of the Expert Review is to encourage feedback on the methodological and data sources used in
1-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 the current Inventory, especially for sources which have experienced any changes since the previous Inventory.
2 Once comments are received and addressed, a second draft of the document is released for public review by
3 publishing a notice in the U.S. Federal Register and posting the document on the EPA Web site. The Public Review
4 period allows for a 30 day comment period and is open to the entire U.S. public.
5 Final Submittal to UNFCCC and Document Printing
6 After the final revisions to incorporate any comments from the Expert Review and Public Review periods, EPA
7 prepares the final National Inventory Report and the accompanying Common Reporting Format Reporter database.
8 The U.S. Department of State sends the official submission of the U.S. Inventory to the UNFCCC. The document is
9 then formatted for printing, posted online, printed by the U.S. Government Printing Office, and made available for
10 the public.
11 1.4. Methodology and Data Sources
12 Emissions of greenhouse gases from various source and sink categories have been estimated using methodologies
13 that are consistent with the Revised 1996IPCC Guidelines for National Greenhouse Gas Inventories
14 (IPCC/UNEP/OECD/IEA 1997). In addition, the United States references the additional guidance provided in the
15 IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (IPCC
16 2000), the IPCC Good Practice Guidance for Land Use, Land-Use Change, and Forestry (IPCC 2003), and the
17 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). To the extent possible, the present
18 report relies on published activity and emission factor data. Depending on the emission source category, activity
19 data can include fuel consumption or deliveries, vehicle-miles traveled, raw material processed, etc. Emission
20 factors are factors that relate quantities of emissions to an activity.
21 The IPCC methodologies provided in the Revised 1996 IPCC Guidelines represent baseline methodologies for a
22 variety of source categories, and many of these methodologies continue to be improved and refined as new research
23 and data become available. This report uses the IPCC methodologies when applicable, and supplements them with
24 other available methodologies and data where possible. Choices made regarding the methodologies and data
25 sources used are provided in conjunction with the discussion of each source category in the main body of the report.
26 Complete documentation is provided in the annexes on the detailed methodologies and data sources utilized in the
27 calculation of each source category.
28
29 [BEGIN BOX]
30 Box 1-2: IPCC Reference Approach
31 The UNFCCC reporting guidelines require countries to complete a "top-down" reference approach for estimating
32 C02 emissions from fossil fuel combustion in addition to their "bottom-up" sectoral methodology. This estimation
33 method uses alternative methodologies and different data sources than those contained in that section of the Energy
34 chapter. The reference approach estimates fossil fuel consumption by adjusting national aggregate fuel production
35 data for imports, exports, and stock changes rather than relying on end-user consumption surveys (see Annex 4 of
36 this report). The reference approach assumes that once carbon-based fuels are brought into a national economy,
37 they are either saved in some way (e.g., stored in products, kept in fuel stocks, or left unoxidized in ash) or
38 combusted, and therefore the carbon in them is oxidized and released into the atmosphere. Accounting for actual
39 consumption of fuels at the sectoral or sub-national level is not required.
40 [END BOX]
Trends in Greenhouse Gas Emissions 1-11
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Public Review Draft
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 estimation of emissions from
international bunker fuels also supports the qualification of this source category as key.
Table 1-4 presents the key categories for the United States based on the Tier 1 approach (including and excluding
LULUCF categories) using emissions data in this report, and ranked according to their sector and global warming
potential-weighted emissions in 2005. The table also indicates the criteria used in identifying these categories (i.e.,
level, trend, and/or qualitative assessments). Annex 1 of this report provides additional information regarding the
key categories in the United States and the methodologies used to identify them.
Table 1-4: Key Categories for the United States (1990-2005) Based on Tier 1 Approach
2005
Level Trend Level Trend Emissions
Without Without With With (Tg CO2
IPCC Source Categories Gas LULUCF LULUCF LULUCF LULUCF Qual" Eq.)
Energy
C02 Emissions from Stationary Combustion -
Coal
Mobile Combustion: Road & Other
C02 Emissions from Stationary Combustion -
Gas
C02 Emissions from Stationary Combustion - Oil
Mobile Combustion: Aviation
C02 Emissions from Non-Energy Use of Fuels
co2
2,093.6
co2
•/
•/
•/
•/
1,642.9
co2
•/
•/
1,138.2
co2
•/
•/
•/
•/
626.3
co2
•/
•/
•/
•/
187.3
co2
•/
•/
•/
142.3
18 See Chapter 7 "Methodological Choice and Recalculation" in IPCC (2000).
1-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Fugitive Emissions from Natural Gas Systems
ch4
111.1
International Bunker Fuelsb
Several
96.6
Mobile Combustion: Marine
C02
•/
•/
•/
•/
64.2
Fugitive Emissions from Coal Mining
ch4
•/
•/
•/
•/
52.4
Fugitive Emissions from Petroleum Systems
ch4
•/
•/
•/
•/
28.5
C02 Emissions from Natural Gas Systems
co2
•/
•/
•/
•/
28.2
C02 Emissions from Waste Incineration
co2
•/
•/
20.9
Mobile Combustion: Road and Other
n2o
•/
•/
•/
•/
13.8
Industrial Processes
Emissions from Substitutes for Ozone Depleting
Several
•/
•/
•/
•/
123.3
Substances
C02 Emissions from Cement Manufacture
co2
•/
•/
•/
•/
45.9
C02 Emissions from Iron and Steel Production
co2
•/
•/
•/
y
45.4
HFC-23 Emissions from HCFC-22 Manufacture
HFCs
•/
•/
•/
y
16.5
C02 Emissions from Ammonia Production and
Urea Application
C02
•/
•/
16.3
SF6 Emissions from Electrical Transmission and
Distribution
sf6
•/
y
13.2
N20 Emissions from Adipic Acid Production
n2o
•/
y
as a*
© ©
PFC Emissions from Aluminum Production
PFCs
•/
y
3.0
Agriculture
Direct N20 Emissions from Agricultural Soils
N20
•/
•/
•/
y
310.5
CH4 Emissions from Enteric Fermentation in
Domestic Livestock
ch4
•/
•/
•/
•/
112.1
Indirect N20 Emissions from Nitrogen Used in
n2o
•/
•/
•/
y
54.6
Agriculture
CH4 Emissions from Manure Management
ch4
•/
9.5
Waste
CH4 Emissions from Landfills
ch4
•/
•/
•/
y
132.0
Land Use, Land-Use Change, and Forestry
C02 Emissions from Forest Land Remaining
Forest Land
co2
•/
(698.7)
C02 Emissions from Settlements Remaining
Settlements
co2
•/
y
(88.5)
C02 Emissions from Cropland Remaining
Cropland
co2
•/
y
(39.4)
C02 Emissions from Grassland Remaining
Grassland
co2
•/
16.1
C02 Emissions from Lanfilled Yard Trimmings
co2
and Food Scraps
o.o
Subtotal Without LULUCF
7,038.1
Total Emissions Without LULUCF
7,243.4
Percent of Total Without LULUCF
97.2%
Subtotal With LULUCF
6,218.8
Total Emissions With LULUCF
6,433.9
Percent of Total With LULUCF
96.7%
Trends in Greenhouse Gas Emissions 1-13
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Public Review Draft
Qualitative criteria.
bEmissions 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.
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 (or protocols) and templates (or forms) that serve to standardize the process of
documenting and archiving information, as well as to guide the implementation of QA/QC and the analysis of
the uncertainty of the inventory estimates;
• expert review as well as QC—for both the inventory estimates and the Inventory (which is the primary vehicle
for disseminating the results of the inventory development process). In addition, the plan provides for public
review of the Inventory;
• both Tier 1 (general) and Tier 2 (source-specific) quality controls and checks, as recommended by IPCC Good
Practice Guidance;
• consideration of secondary data quality and source-specific quality checks (Tier 2 QC) in parallel and
coordination with the uncertainty assessment; the development of protocols and templates provides for more
structured communication and integration with the suppliers of secondary information;
• record-keeping provisions to track which procedures have been followed, and the results of the QA/QC and
uncertainty analysis, and contains feedback mechanisms for corrective action based on the results of the
investigations, thereby providing for continual data quality improvement and guided research efforts;
• implementation of QA/QC procedures throughout the whole inventory development process—from initial data
collection, through preparation of the emission estimates, to publication of the Inventory;
• a schedule for multi-year implementation; and
• promotion of coordination and interaction within the EPA, across Federal agencies and departments, state
government programs, and research institutions and consulting firms involved in supplying data or preparing
estimates for the inventory. The QA/QC plan itself is intended to be revised and reflect new information that
becomes available as the program develops, methods are improved, or additional supporting documents become
necessary.
In addition, based on the national QA/QC plan for the Inventory, source-specific QA/QC plans have been developed
for a number of sources. These plans follow the procedures outlined in the national QA/QC plan, tailoring the
procedures to the specific text and spreadsheets of the individual sources. For the current Inventory, source-specific
plans have been developed and implemented for the majority of sources within the Energy and Industrial Process
sectors. Throughout this inventory, a minimum of a Tier 1 QA/QC analysis has been undertaken. Where QA/QC
activities for a particular source go beyond the minimum Tier 1 level, further explanation is provided within the
respective source category text.
The quality checking and control activities described in the U.S. QA/QC plan occur throughout the inventory
process; QA/QC is not separate from, but is an integral part of, preparing the inventory. Quality control—in the
form of both good practices (such as documentation procedures) and checks on whether good practices and
procedures are being followed—is applied at every stage of inventory development and document preparation. In
addition, quality assurance occurs at two stages—an expert review and a public review. While both phases can
significantly contribute to inventory quality, the public review phase is also essential for promoting the openness of
1-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
the inventory development process and the transparency of the inventory data and methods.
QA/QC procedures guide the process of ensuring inventory quality by describing data and methodology checks,
developing processes governing peer review and public comments, and developing guidance on conducting an
analysis of the uncertainty surrounding the emission estimates. The QA/QC procedures also include feedback loops
and provide for corrective actions that are designed to improve the inventory estimates over time.
1.7. Uncertainty Analysis of Emission Estimates
Uncertainty estimates are an essential element of a complete and transparent emissions inventory. Uncertainty
information is not intended to dispute the validity of the inventory estimates, but to help prioritize efforts to improve
the accuracy of future inventories and guide future decisions on methodological choice. While the U.S. Inventory
calculates its emission estimates with the highest possible accuracy, uncertainties are associated to a varying degree
with the development of emission estimates for any inventory. Some of the current estimates, such as those for C02
emissions from energy-related activities and cement processing, are considered to have minimal uncertainty
associated with them. For some other categories of emissions, however, a lack of data or an incomplete
understanding of how emissions are generated increases the uncertainty surrounding the estimates presented.
Despite these uncertainties, the UNFCCC reporting guidelines follow the recommendation in the 1996IPCC
Guidelines (IPCC/UNEP/OECD/IEA 1997) and require that countries provide single point estimates of uncertainty
for each gas and emission or removal source category. Within the discussion of each emission source, specific
factors affecting the uncertainty associated with the estimates are discussed.
Additional research in the following areas could help reduce uncertainty in the U.S. Inventory:
• Incorporating excluded emission sources. Quantitative estimates for some of the sources and sinks of
greenhouse gas emissions are not available at this time. In particular, emissions from some land-use activities
and industrial processes are not included in the inventory either because data are incomplete or because
methodologies do not exist for estimating emissions from these source categories. See Annex 5 of this report
for a discussion of the sources of greenhouse gas emissions and sinks excluded from this report.
• Improving the accuracy of emission factors. Further research is needed in some cases to improve the accuracy
of emission factors used to calculate emissions from a variety of sources. For example, the accuracy of current
emission factors applied to CH4 and N20 emissions from stationary and mobile combustion is highly uncertain.
• Collecting detailed activity data. Although methodologies exist for estimating emissions for some sources,
problems arise in obtaining activity data at a level of detail in which aggregate emission factors can be applied.
For example, the ability to estimate emissions of SF6 from electrical transmission and distribution is limited due
to a lack of activity data regarding national SF6 consumption or average equipment leak rates.
The overall uncertainty estimate for the U.S. greenhouse gas emissions inventory was developed using the IPCC
Tier 2 uncertainty estimation methodology. A preliminary estimate of the overall quantitative uncertainty is shown
below, in Table 1-5.
The IPCC provides good practice guidance on two approaches—Tier 1 and Tier 2—to estimating uncertainty for
individual source categories. Tier 2 uncertainty analysis, employing the Monte Carlo Stochastic Simulation
technique, was applied wherever data and resources permitted; further explanation is provided within the respective
source category text. Consistent with the IPCC Good Practice Guidance, over a multi-year timeframe, the United
States expects to continue to improve the uncertainty estimates presented in this report.
Table 1-5. Estimated Overall Inventory Quantitative Uncertainty (Tg C02 Eq. and Percent)
2005 Emission
Uncertainty Range Relative to Emission
Standard
Estimate
Estimate"
Meanb Deviation
Gas
(Tg C02 Eq.)
(Tg C02 Eq.) (%)
(Tg C02 Eq.)
Lower Upper Lower Upper
Bound0 Bound0 Bound0 Bound0
Trends in Greenhouse Gas Emissions 1-15
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
co2
6,091.2
5,989.4
6,400.5
-1.7%
5.1%
6,191.5
107.2
ch4
539.3
488.0
623.8
-9.5%
15.7%
554.0
34.3
n2o
468.7
392.0
579.4
-16.4%
23.6%
485.2
47.6
PFC, HFC & SF6d
163.0
153.2
188.5
-6.0%
15.6%
170.1
9.2
Total
7,262.3
7,169.2
7,638.9
-1.3%
5.2%
7,400.8
122.6
Notes:
a Range of emission estimates for a 95 percent confidence interval.
b Mean value indicates the arithmetic average of the simulated emission estimates; Standard deviation indicates the extent of
deviation of the simulated values from the mean.
c The low and high estimates for total emissions were separately calculated through simulations and, hence, the low and high
emission estimates for the sub-source categories do not add up to total emissions.
d The overall uncertainty estimate did not take into account the uncertainty in the GWP values for CH4, N20 and high GWP
gases used in the inventory emission calculations for 2005.
Emissions calculated for the U.S. Inventory reflect current best estimates; in some cases, however, estimates are
based on approximate methodologies, assumptions, and incomplete data. As new information becomes available in
the future, the United States will continue to improve and revise its emission estimates. See Annex 7 of this report
for further details on the U.S. process for estimating uncertainties associated with emission estimates and for a more
detailed discussion of the limitations of the current analysis and plans for improvement.
1.8. Completeness
This report, along with its accompanying 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 2005.
Although this report is intended to be comprehensive, certain sources have been identified yet excluded from the
estimates presented for various reasons. Generally speaking, sources not accounted for in this inventory are
excluded due to data limitations or a lack of thorough understanding of the emission process. The United States is
continually working to improve upon the understanding of such sources and seeking to find the data required to
estimate related emissions. As such improvements are made, new emission sources are quantified and included in
the Inventory. For a complete list of sources excluded, see Annex 5 of this report.
1.9. Organization of Report
In accordance with the Revised 1996IPCC Guidelines for National Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997), and the 2003 UNFCCC Guidelines on Reporting and Review (UNFCCC 2003),
this Inventory of U.S. Greenhouse Gas Emissions and Sinks is segregated into six sector-specific chapters, listed
below in Table 1-6. In addition, chapters on Trends in Greenhouse Gas Emissions and Other information to be
considered as part of the U.S. Inventory submission are included.
Table 1-6: IPCC Sector Descriptions
Chapter/IPCC Sector
Activities Included
Energy
Emissions of all greenhouse gases resulting from stationary and mobile
energy activities including fuel combustion and fugitive fuel emissions.
Industrial Processes
By-product or fugitive emissions of greenhouse gases from industrial
processes not directly related to energy activities such as fossil fuel
combustion.
Solvent and Other Product
Emissions, of primarily NMVOCs, resulting from the use of solvents
Use
and N20 from product usage.
Agriculture
Anthropogenic emissions from agricultural activities except fuel
combustion, which is addressed under Energy.
Land Use, Land-Use Change,
Emissions and removals of C02, CH4, and N20 from forest
and Forestry
management, other land-use activities, and land-use change.
Waste
Emissions from waste management activities.
Source: (IPCC/UNEP/OECD/IEA 1997)
1-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Within each chapter, emissions are identified by the anthropogenic activity that is the source or sink of the
2 greenhouse gas emissions being estimated (e.g., coal mining). Overall, the following organizational structure is
3 consistently applied throughout this report:
4 Chapter/IPCC Sector: Overview of emission trends for each IPCC defined sector
5 Source category: Description of source pathway and emission trends.
6 Methodology: Description of analytical methods employed to produce emission estimates and identification of
7 data references, primarily for activity data and emission factors.
8 Uncertainty: A discussion and quantification of the uncertainty in emission estimates and a discussion of time-
9 series consistency.
10 QA/QC and Verification: A discussion on steps taken to QA/QC and verify the emission estimates, where beyond
11 the overall U.S. QA/QC plan, and any key findings.
12 Recalculations: A discussion of any data or methodological changes that necessitate a recalculation of previous
13 years' emission estimates, and the impact of the recalculation on the emission estimates, if applicable.
14 Planned Improvements: A discussion on any source-specific planned improvements, if applicable.
15 Special attention is given to C02 from fossil fuel combustion relative to other sources because of its share of
16 emissions and its dominant influence on emission trends. For example, each energy consuming end-use sector (i.e.,
17 residential, commercial, industrial, and transportation), as well as the electricity generation sector, is described
18 individually. Additional information for certain source categories and other topics is also provided in several
19 Annexes listed in Table 1-7.
20 Table 1-7: List of Annexes
ANNEX 1 Key Category Analysis
ANNEX 2 Methodology and Data for Estimating C02 Emissions from Fossil Fuel Combustion
2.1. Methodology for Estimating Emissions of C02 from Fossil Fuel Combustion
2.2. Methodology for Estimating the Carbon Content of Fossil Fuels
2.3. Methodology for Estimating Carbon Emitted from Non-Energy Uses of Fossil Fuels
ANNEX 3 Methodological Descriptions for Additional Source or Sink Categories
3.1. Methodology for Estimating Emissions of CH4, N20, and Indirect Greenhouse Gases from Stationary
Combustion
3.2. Methodology for Estimating Emissions of CH4, N20, and Indirect Greenhouse Gases from Mobile
Combustion and Methodology for and Supplemental Information on Transportation-Related Greenhouse
Gas Emissions
3.3. Methodology for Estimating CH4 Emissions from Coal Mining
3.4. Methodology for Estimating CH4 Emissions from Natural Gas Systems
3.5. Methodology for Estimating CH4 Emissions from Petroleum Systems
3.6. Methodology for Estimating C02 and N20 Emissions from Municipal Solid Waste Combustion
3.7. Methodology for Estimating Emissions from International Bunker Fuels used by the U. S. Military
3.8. Methodology for Estimating HFC and PFC Emissions from Substitution of Ozone Depleting Substances
3.9. Methodology for Estimating CH4 Emissions from Enteric Fermentation
3.10. Methodology for Estimating CH4 and N20 Emissions from Manure Management
3.11. Methodology for Estimating N20 Emissions from Agricultural Soil Management
3.12. Methodology for Estimating Net Carbon Stock Changes in Forest Lands Remaining Forest Lands
3.13. Methodology for Estimating Net Changes in Carbon Stocks in Mineral and Organic Soils on Croplands and
Grasslands
3.14. Methodology for Estimating CH4 Emissions from Landfills
ANNEX 4 IPCC Reference Approach for Estimating C02 Emissions from Fossil Fuel Combustion
ANNEX 5 Assessment of the Sources and Sinks of Greenhouse Gas Emissions Excluded
ANNEX 6 Additional Information
6.1. Global Warming Potential Values
6.2 . Ozone Depleting Substance Emissions
Trends in Greenhouse Gas Emissions 1-17
-------
Public Review Draft
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
1-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 2. Trends in Greenhouse Gas Emissions
2 2.1. Recent Trends in U.S. Greenhouse Gas Emissions
3 In 2005, total U.S. greenhouse gas emissions were 7,262.3 teragrams of carbon dioxide equivalents (Tg C02 Eq.).1
4 Overall, total U.S. emissions have risen by 16.3 percent from 1990 to 2005, while the U.S. gross domestic product
5 has increased by 55 percent over the same period (BEA 2006). Emissions rose from 2004 to 2005, increasing by
6 0.8 percent (58.4 Tg C02 Eq.). The following factors were primary contributors to this increase: (1) strong
7 economic growth in 2005, leading to increased demand for electricity and (2) an increase in the demand for
8 electricity due to warmer summer conditions. These factors were moderated by decreasing demand for fuels due to
9 warmer winter conditions and higher fuel prices. Figure 2-1 through Figure 2-3 illustrate the overall trends in total
10 U.S. emissions by gas,2 annual changes, and absolute changes since 1990.
11
12 Figure 2-1: U.S. Greenhouse Gas Emissions by Gas
13
14 Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
15
16 Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990
17
18 As the largest source of U.S. greenhouse gas emissions, carbon dioxide (C02) from fossil fuel combustion has
19 accounted for approximately 77 percent of global warming potential (GWP) weighted emissions since 1990,
20 growing slowly from 76 percent of total GWP-weighted emissions in 1990 to 79 percent in 2005. Emissions from
21 this source category grew by 21.8 percent (1,028.6 Tg C02Eq.) from 1990 to 2005 and were responsible for most of
22 the increase in national emissions during this period. From 2004 to 2005, these emissions increased by 0.7 percent
23 (39.8 Tg C02 Eq.), slightly less than the source's average annual growth rate of 1.3 percent from 1990 through
24 2005. Historically, changes in emissions from fossil fuel combustion have been the dominant factor affecting U.S.
25 emission trends.
26 Changes in C02 emissions from fossil fuel combustion are influenced by many long-term and short-term factors.,
27 including population and economic growth, energy price fluctuations, technological changes, and seasonal
28 temperatures. On an annual basis, the overall consumption of fossil fuels in the United States generally fluctuates in
29 response to changes in general economic conditions, energy prices, weather, and the availability of non-fossil
30 alternatives. For example, in a year with increased consumption of goods and services, low fuel prices, severe
31 summer and winter weather conditions, nuclear plant closures, and lower precipitation feeding hydroelectric dams,
32 there would likely be proportionally greater fossil fuel consumption than in a year with poor economic performance,
33 high fuel prices, mild temperatures, and increased output from nuclear and hydroelectric plants.
34 In the longer-term, energy consumption patterns respond to changes that affect the scale of consumption (e.g.,
35 population, number of cars, and size of houses), the efficiency with which energy is used in equipment (e.g., cars,
36 power plants, steel mills, and light bulbs) and consumer behavior (e.g., walking, bicycling, or telecommuting to
37 work instead of driving).
1 Estimates are presented in units of teragrams of carbon dioxide equivalent (Tg C02 Eq.), which weight each gas by its global
warming potential, or GWP, value. (See section on global warming potentials, Chapter 1.)
2 See the following section for an analysis of emission trends by general economic sector.
Trends in Greenhouse Gas Emissions 2-1
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
Energy-related C02 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 C02 emissions
because of the lower C content of natural gas. Table 2-1 shows annual changes in emissions during the last five
years for coal, petroleum, and natural gas in selected sectors.
Table 2-1: Annual Change in C02 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg C02
Eq. and Percent)
Sector
Fuel Type
2001 to 2002
2002 to 2003
2003 to 2004
2004 to 2005
Electricity Generation
Coal
16.0
0.9%
38.0
2.0%
11.4
0.6%
40.8
2.1%
Electricity Generation
Natural Gas
16.1
5.5%
-27.7
-9.0%
18.4
6.6%
22.4
7.5%
Electricity Generation
Petroleum
-22.9
-22.5%
19.0
24.0%
2.0
2.0%
2.2
2.2%
Transportation3
Petroleum
51.8
3.0%
2.0
0.1%
55.1
3.1%
30.4
1.7%
Residential
Natural Gas
6.4
2.5%
11.5
4.3%
-12.2
-4.4%
-3.4
-1.3%
Commercial
Natural Gas
6.6
4.0%
2.6
1.5%
-3.1
-1.8%
-4.2
-2.5%
Industrial
Coal
-10.1
-7.6%
0.6
0.5%
2.3
1.8%
-4.0
-3.2%
Industrial
Natural Gas
9.4
2.2%
-14.5
-3.3%
0.6
0.1%
-34.8
-8.2%
All Sectorsb
All Fuelsb
45.5
0.8%
67.3
1.2%
88.5
1.6%
39.8
0.7%
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table (see Table 3-3 for complete list of fuels by sector).
After emissions significantly decreased in 2001 due to the economic slowdown, emissions from fuel combustion
resumed modest growth in 2002, slightly less than the average annual growth rate since 1990. There were a number
of reasons behind this increase. The U.S. economy experienced moderate growth, recovering from weak economic
conditions in 2001. Prices for fuels remained at or below 2001 levels; the cost of natural gas, motor gasoline, and
electricity were all lower—triggering an increase in demand for fuel. In addition, the United States experienced one
of the hottest summers on record, causing a significant increase in electricity use in the residential sector as the use
of air-conditioners increased. Partially offsetting this increased consumption of fossil fuels, however, were
increases in the use of nuclear and renewable fuels. Nuclear facilities operated at the highest capacity on record in
2002. Furthermore, there was a considerable increase in the use of hydroelectric power in 2002 after a very low
output the previous year.
Emissions from fuel combustion continued growing in 2003, at about the average annual growth rate since 1990. A
number of factors played a major role in the magnitude of this increase. The U.S. economy experienced moderate
growth from 2002, causing an increase in the demand for fuels. The price of natural gas escalated dramatically,
causing some electric power producers to switch to coal, which remained at relatively stable prices. Colder winter
conditions brought on more demand for heating fuels, primarily in the residential sector. Though a cooler summer
partially offset demand for electricity as the use of air-conditioners decreased, electricity consumption continued to
increase in 2003. The primary drivers behind this trend were the growing economy and the increase in U.S. housing
stock. Nuclear capacity decreased slightly, for the first time since 1997. Use of renewable fuels rose slightly due to
increases in the use of hydroelectric power and biofuels.
From 2003 to 2004, these emissions increased at a rate slightly higher than the average growth rate since 1990. A
number of factors played a major role in the magnitude of this increase. A primary reason behind this trend was
strong growth in the U.S. economy and industrial production, particularly in energy-intensive industries, causing an
increase in the demand for electricity and fossil fuels. Demand for travel was also higher, causing an increase in
petroleum consumed for transportation. In contrast, the warmer winter conditions led to decreases in demand for
heating fuels, principally natural gas, in both the residential and commercial sectors. Moreover, much of the
increased electricity demanded was generated by natural gas combustion and nuclear power, which moderated the
increase in C02 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
2-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Public Review Draft
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.
Other significant trends in emissions from additional source categories over the fifteen-year period from 1990
through 2005 included the following:
• C02 emissions from waste combustion increased by 10.0 Tg C02 Eq. (91percent), as the volume of plastics and
other fossil carbon-containing materials in municipal solid waste grew.
• Net C02 sequestration from Land Use, Land-Use Change, and Forestry increased by 115.5 Tg C02 Eq. (16
percent) from 1990 through 2005. This increase was 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 C
accumulation in urban trees increased.
• Methane (CH4) emissions from coal mining declined by 29.5 Tg C02 Eq. (36 percent) from 1990 to 2005, as a
result of the mining of less gassy coal from underground mines and the increased combustion of CH4 collected
from degasification systems.
• From 1990 to 2005, nitrous oxide (N20) emissions from mobile combustion decreased by 13.1 percent.
However, from 1990 to 1998 emissions increased by 26 percent, due to control technologies that reduced CH4
emissions while increasing N20 emissions. Since 1998, new control technologies have led to a steady decline
in N20 from this source.
• Emissions resulting from the substitution of ozone depleting substances (ODS, e.g., chlorofluorocarbons
[CFCs]) have increased dramatically, from small amounts in 1990 to 123.3 Tg C02 Eq. in 2005. These
emissions have been increasing as phase-outs of ODS required under the Montreal Protocol come into effect.
• The increase in ODS substitutes emissions is offset substantially by decreases in emission of
hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6) from other sources.
Emissions from aluminum production decreased by 84 percent (15.6 Tg C02 Eq.) from 1990 to 2005, due to
both industry emission reduction efforts and lower domestic aluminum production. Emissions from the
production of HCFC-22 decreased by 53 percent (18.4 Tg C02 Eq.) from 1990 to 2005, due to a steady decline
in the emission rate ofHFC-23 (i.e., the amount of HFC-23 emitted per kilogram of HCFC-22 manufactured)
and the use of thermal oxidation at some plants to reduce HFC-23 emissions. Emissions from electric power
transmission and distribution systems decreased by 51 percent (13.9 Tg C02 Eq.) from 1990 to 2005, primarily
because of higher purchase prices for SF6 and efforts by industry to reduce emissions.
Overall, from 1990 to 2005, total emissions of C02 increased by 1,029.6 Tg C02 Eq. (20 percent), while CH4 and
N20 emissions decreased by 69.8 Tg C02 Eq. (11 percent) and 13.3 Tg C02 Eq. (2.8 percent) respectively. During
the same period, aggregate weighted emissions of HFCs, PFCs, and SF6 rose by 73.7 Tg C02 Eq. (82.5 percent).
Despite being emitted in smaller quantities relative to the other principal greenhouse gases, emissions of HFCs,
PFCs, and SF6 are significant because many of them have extremely high GWPs and, in the cases of PFCs and SF6,
long atmospheric lifetimes. Conversely, U.S. greenhouse gas emissions were partly offset by C sequestration in
managed forests, trees in urban areas, agricultural soils, and landfilled yard trimmings, which was estimated to be 11
percent of total emissions in 2005.
[BEGIN BOX]
Box 2-1: Recent Trends in Various U.S. Greenhouse-Gas-Emissions-Related Data
Trends in Greenhouse Gas Emissions 2-3
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Public Review Draft
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 2005; (4) emissions per unit of total gross domestic product as a measure of national economic activity;
or (5) emissions per capita.
Table 2-2 provides data on various statistics related to U.S. greenhouse gas emissions normalized to 1990 as a
baseline year. Greenhouse gas emissions in the United States have grown at an average annual rate of 1.1 percent
since 1990. This rate is 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 2-4). Overall, global atmospheric C02
concentrations—a function of many complex anthropogenic and natural processes—arc increasing at 0.4 percent
per year.
Table 2-2: Recent Trends in Various U.S. Data (Index 1990 = 100) and Global Atmospheric C02 Concentration
Variable
1990
1 1995
I 2000
2001
2002
2003
2004
2005
Growth
Ratef
Greenhouse Gas Emissions3
100
115
115
113
113
114
115
116
1.0%
Energy Consumption13
100
117
117
114
116
117
119
118
1.1%
Fossil Fuel Consumption13
100
117
117
115
116
118
119
119
1.2%
Electricity Consumption13
100
127
127
125
128
129
131
134
2.0%
GDP°
100
138
138
139
141
145
150
155
3.0%
Population11
100
113
113
114
115
116
117
118
1.1%
Atmospheric C02 Concentration6
100
I 104
1 104
105
105
106
106
106
0.4%
a GWP-weighted values
b Energy content weighted values (EIA 2006a)
c Gross Domestic Product in chained 2000 dollars (BEA 2006)
d (U.S. Census Bureau 2006)
e Hofmann (2004)
f Average annual growth rate
Figure 2-4: U.S. Greenhouse Gas Emissions Per Capita and Per Dollar of Gross Domestic Product
Source: BEA (2006), U.S. Census Bureau (2006), and emission estimates in this report.
[END BOX]
Table 2-3 summarizes emissions and sinks from all U.S. anthropogenic sources in weighted units of Tg C02Eq.,
while unweighted gas emissions and sinks in gigagrams (Gg) are provided in Table 2-4.
Table 2-3: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2001
2002
2003
2004
2005
co2
5,061.7
5,384.6
I 5'940 1
5,843.1
5,892.8
5,952.6
6,064.5
6,091.2
Fossil Fuel Combustion
4,724.1
5,030.0 ;
5,584.9
5,511.7
5,557.2
5,624.5
5,713.0
5,752.8
Non-Energy Use of Fuels
117.2
133.1
141.0
131.3
135.3
131.3
150.2
142.3
Cement Manufacture
33.3
36.8
41.2
41.4
42.9
43.1
45.6
45.9
Iron and Steel Production
85.0
73.5
65.3
58.0
54.7
53.5
51.5
45.4
Natural Gas Systems
33.7
33.8
29.4
28.8
29.6
28.4
28.2
28.2
Municipal Solid Waste Combustion
10.9
15.7
17.9
18.3
18.5
19.5
20.1
20.9
Ammonia Manufacture and Urea
Application
19.3
20.5
19.6
16.7
17.8
16.2
16.9
16.3
2-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and
Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Production and
Consumption
Net C02 Flux from Land Use, Land-
Use Change, and Forestry"
Lnternational Bunker Fuelsb
Wood Biomass and Ethanol
Consumptionh
CH4
Landfills
Enteric Fermentation
Natural Gas Systems
Coal Mining
Manure Management
Petroleum Systems
Wastewater Treatment
Forest Land Remaining Forest Land
Stationary Combustion
Rice Cultivation
Abandoned Underground Coal
Mines
Mobile Combustion
Petrochemical Production
Iron and Steel Production
Field Burning of Agricultural
Residues
Ferroalloy Production
Silicon Carbide Production and
Consumption
Lnternational Bunker Fuelsb
n2o
Agricultural Soil Management
Mobile Combustion
Nitric Acid Production
Stationary Combustion
Manure Management
Wastewater Treatment
Settlements Remaining Settlements
Adipic Acid Production
N20 Product Usage
Forest Land Remaining Forest Land
Municipal Solid Waste Combustion
Field Burning of Agricultural
Residues
Public Review Draft
11.3
5.51
4 11
6.S
2.21
L3i
2 21
1 51
L4i
°-9I
°-3I
°-4l
(712-9) I
113.71
219.31
609,11
16L0i
115.71
124-51
8L9i
30-9I
3441
24-.8|
7.11
8-°l
7. II
6-°l
4 71
0.9
L3I
0.71
+1
+1
0.21
482-°l
366-9I
43-7l
17.8|
12.3[
8-6l
6-4l
5 1
15.21
4 3|
0.S
0.51
0.41
12.81
7 4
4 3[
* "
2-8l
I "
2.01
1 51
I.4!
l.ol
°-3I
0.5
(828.5)\
lOO.t
236-8l
598-7(
157.11
120.6
128-11
66.51
35.lj
.31.11
25 lj
4.01
7.S
7.61
8-2l
4 3|
l.ll
13
0.71
+1
+1
ail
484-2i
3 53.41
53.7l
19-9I
12-81
9-°I
6.91
5.51
17:
4 51
0.6
0.51
0.41
13.3
12.9
12.3
13.0
13.7
13.7
6.0
5.7
5.9
4.7
6.7
7.4
4.2
4.1
4.1
4.1
4.2
4.2
6.1
4.4
4.5
4.5
4.2
4.2
3.0
2.8
2.9
2.8
2.9
2.9
1.9
1.9
2.0
2.0
2.3
1.9
1.9
1.5
1.3
1.3
1.4
1.4
1.4
1.3
1.3
1.4
1.4
1.4
1.4
0.8
1.0
1.3
1.2
1.3
1.1
1.0
0.9
0.5
0.5
0.5
0.3
0.3
0.3
0.3
0.3
0.3
0.2
0.2
0.2
0.2
0.2
0.2
(754.7)
(765.5)
(809.9)
(811.6)
(824.9)
(828.4)
101.1
97.6
89.1
83.7
97.2
95.6
228.3
203.2
204.4
209.6
224.8
206.5
563.7
547.7
549.7
549.2
540.3
539.3
131.9
127.6
130.4
134.9
132.1
132.0
113.5
112.5
112.6
113.0
110.5
112.1
126.6
125.4
125.0
123.7
119.0
111.1
55.9
55.5
52.0
52.1
54.5
52.4
38.7
40.1
41.1
40.5
39.7
41.3
27.8
27.4
26.8
25.8
25.4
28.5
26.4
25.9
25.8
25.6
25.7
25.4
14.0
6.0
10.4
8.1
6.9
11.6
7.4
6.8
6.8
7.0
7.1
6.9
7.5
7.6
6.8
6.9
7.6
6.9
7.3
6.7
6.1
5.9
5.8
5.5
3.5
3.2
3.1
2.9
2.8
2.6
1.2
1.1
1.1
1.1
1.2
1.1
1.2
1.1
1.0
1.0
1.0
1.0
0.8
0.8
0.7
0.8
0.9
0.9
+
+
+
+
+
+
+
+
+
+
+
+
0.1
0.1
0.1
0.1
0.1
0.1
499.8
502.5
479.3
459.9
445.3
468.7
376.8
389.0
366.1
350.2
338.8
365.1
53.2
49.7
47.1
43.8
41.2
38.0
19.6
15.9
17.2
16.7
16.0
15.7
14.0
13.5
13.4
13.7
13.9
13.8
9.6
9.8
9.7
9.3
9.4
9.5
7.6
7.6
7.7
7.8
7.9
8.0
5.6
5.5
5.6
5.8
6.0
5.8
6.0
4.9
5.9
6.2
5.7
6.0
4.8
4.8
4.3
4.3
4.3
4.3
1.7
1.0
1.4
1.2
1.1
1.5
0.4
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.4
0.4
0.5
0.5
Trends in Greenhouse Gas Emissions 2-5
-------
Public Review Draft
International Bunker Fuels
HFCs, PFCs, and SF6
Substitution of Ozone Depleting
Substances
HCFC-22 Production
Electrical Transmission and
Distribution
Semiconductor Manufacture
Aluminum Production
Magnesium Production and
Processing
1.0
0.9
I 0.9
0.9
0.8
0.8
0.9
0.9
89.3
1 103.5
1 143.8
133.8
143.0
142.7
153.9
163.0
0.3
1 32.2
! 809
88.6
96.9
105.5
114.5
123.3
35.0
! 27.0
29.8
19.8
19.8
12.3
15.6
16.5
27 I
2.9
18.5
5.4
21.8
5.0
11.8
5.6
15.2
6.3
8.6
3.0
15.1
4.5
3.5
2.4
14.3
4.4
5.2
2.4
13.8
4.3
3.8
2.9
13.6
4.7
2.8
2.6
13.2
4.3
3.0
2.7
7,147.3
6,392.6
7,027.1
6,261.6
7,064.8
6,254.8
7,104.4
6,292.8
7,203.9
6,379.0
Total 6,242.1 6,571.01
Net Emissions (Sources and Sinks) 5,529.1 5,742.5|
+ Does not exceed 0.05 Tg C02 Eq.
a The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only
included in net emissions total. Parentheses indicate negative values or sequestration.
b Emissions from International Bunker Fuels and Wood Biomass and Ethanol Consumption are not included in totals.
Note: Totals may not sum due to independent rounding.
Table 2-4: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks (Gg)
Gas/Source
7,262.3
6,433.9
19901
19951
2000
2001
2002
2003
2004
2005
co2
Fossil Fuel Combustion
Non-Energy Use of Fuels
Cement Manufacture
Iron and Steel Production
Natural Gas Systems
Municipal Solid Waste
Combustion
Ammonia Manufacture and
Urea Application
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and
Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Production
and Consumption
Net C02 Flux from Land Use,
Land-Use Change, and
Forestry"
International Bunker Fuelsb
Wood Biomass and Ethanol
Consumptionh
CH4
Landfills
Enteric Fermentation
Natural Gas Systems
5,061,674
4,724,149
117,2251
33,2781
85'034i
33,7291
10'950i
19.3061
11,2 731
5.5331
4 141
6.X 11
2 ::i
1,3°8|
2,1521
1,529
141^
93 91
2851
3751
(712,946)1
113,683t
219,
29'003i
7,668|
5,510
5,9271
J 5,384,6321
i 5,030,0361
13 5.13 41
36,847
73,454
33,807
15,712
20,45.31
12,844
7'3591
4,304 J
5,6591
2,75°I
1'6701
2,036|
l.^n
1'4231
1'0031
2981
| 5,940,066
5,584,880
140,970
41,190
65,259
29,390
5,843,101
5,511,719
131,342
41,357
58,047
28,793
17,889 18,344
3291
(828,477)1
100,627
236,
28,5091
7'4791
5,744
6,1011
19,616
13,344
5,960
4,181
6,086
3,004
1,918
1,893
1,382
1,416
1,129
311
248
16,719
12,861
5,733
4,147
4,381
2,787
1,857
1,459
1,264
825
976
293
199
(754,675) (765,460)
101,125 97,563
228,308
26,842
6,280
5,404
6,027
203,163
26,080
6,078
5,356
5,971
5,892,809
5,557,242
135,294
42,898
54,702
29,630
18,513
17,766
12,330
5,885
4,139
4,490
2,857
1,997
1,349
1,338
978
927
290
183
(809,916)
89,101
204,351
26,176
6,210
5,361
5,951
5,952,642
5,624,500
131,303
43,082
53,511
28,445
6,064,474
5,713,018
150,175
45,603
51,492
28,190
19,490 20,115
16,173
13,022
4,720
4,111
4,503
2,777
2,013
1,305
1,382
1,310
502
289
202
16,894
13,728
6,702
4,205
4,231
2,895
2,259
1,419
1,395
1,199
472
259
224
6,091,244
5,752,787
142,335
45,910
45,440
28,185
20,912
16,321
13,660
7,397
4,228
4,208
2,897
1,921
1,392
1,383
1,324
460
265
219
(811,596) (824,925) (828,398)
83,690 97,177 95,605
209,603 224,825 206,475
26,154 25,727 25,681
6,425 6,292 6,286
5,379 5,262 5,340
5,891 5,669 5,292
2-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Coal Mining ^,8991
Manure Management 1,4711
Petroleum Systems 1 ,< 4t >
Wastewater Treatment 1,1X01
Forest Land Remaining Forest
Land 3
Stationary Combustion 3821
Rice Cultivation 3^>
Abandoned Underground
Coal Mines 286|
Mobile Combustion 2261
Petrochemical Production 411
Iron and Steel Production 631
Field Burning of Agricultural
Residues 331
Ferroalloy Production l|
Silicon Carbide Production
and Consumption l|
International Bunker Fuelsb
N20 1,5551
Agricultural Soil Management 1,184
Mobile Combustion 1411
Nitric Acid Production 581
Stationary Combustion 4()
Manure Management 281
Wastewater Treatment 211
Settlements Remaining
Settlements 17
Adipic Acid Production 4')
N20 Product U sage 14
Forest Land Remaining Forest
Land 2
Waste Combustion 2
Field Burning of Agricultural
Residues 1|
International Bunker Fuelsb
III C S PFCs, and SF6 M|
Substitution of Ozone
Depleting Substances Mi
HCFC-22 Production0 31
Electrical Transmission and
Distribution11 l|
Semiconductor Manufacture Mi
Aluminum Production Ml
Magnesium Production and
Processing*1
3,165
1,673
1,482|
1,195
1891
3 73 [
3631
391
20"
521
621
321
I
II
1
1,562t
1,14°|
173 [
(4
411
29i
221
IS
5(>
14
2
I
1
31
M1
Ml
2
1
Ml
Ml
2,662
2,644
2,476
2,480
2,597
2,494
1,844
1,911
1,959
1,928
1,892
1,966
1,325
1,303
1,275
1,229
1,209
1,357
1,257
1,232
1,229
1,220
1,222
1,210
667
285
494
384
330
551
351
324
324
334
340
330
357
364
325
328
360
328
349
318
292
282
275
263
165
154
146
136
131
125
58
51
52
51
55
51
57
51
48
49
50
45
38
37
34
38
42
41
1
+
+
+
+
+
1
+
+
+
+
+
6
5
4
4
5
5
1,612
1,621
1,546
1,484
1,437
1,512
1,215
1,255
1,181
1,130
1,093
1,178
172
160
152
141
133
123
63
51
56
54
52
51
45
44
43
44
45
45
31
32
31
30
30
31
24
25
25
25
26
26
18
18
18
19
19
19
19
16
19
20
19
19
15
15
14
14
14
14
6
3
5
4
3
5
1
1
2
2
2
2
1
1
1
1
2
2
3
3
3
2
3
3
M
M
M
M
M
M
M
M
M
M
M
M
3
2
2
1
1
1
1
1
1
1
1
1
M
M
M
M
M
M
M
M
M
M
M
M
1 + Does not exceed 0.5 Gg.
2 M Mixture of multiple gases
3 a The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the
4 included in net emissions total. Parentheses indicate negative values or sequestration.
5 b Emissions from International Bunker Fuels and Wood Biomass and Ethanol Consumption are
6 c HFC-23 emitted.
7 d SF6 emitted.
8 Note: Totals may not sum due to independent rounding.
United States. Sinks are
not included in totals.
only
Trends in Greenhouse Gas Emissions 2-7
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
Emissions of all gases can be totaled for each source category from Intergovernmental Panel on Climate Change
(IPCC) guidance. Over the fifteen-year period of 1990 to 2005, total emissions in the Energy, Industrial Processes,
and Agriculture chapters climbed by 1,001.5 Tg C02 Eq. (19 percent), 33.6 Tg C02Eq. (11 percent), and 6.0 Tg
C02Eq. (1.1 percent), respectively. Emissions decreased from the Solvent and Other Product Use and Waste
chapters by 0.02 Tg C02 Eq. (less than 1 percent) and 26.7 Tg C02Eq. (14 percent), respectively. Over the same
period, estimates of net C sequestration in the Land Use, Land-Use Change, and Forestry chapter increased by 109.5
Tg C02Eq. (16 percent).
Figure 2-5: U.S. Greenhouse Gas Emissions by Chapter/IPCC Sector
Table 2-5: Recent Trends in U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector (Tg C02 Eq.)
Chapter/IPCC Sector
1990
1995
2000
2001
2002
2003
2004
2005
Energy
5,202.1
, 5,525.7
6,069.2 ^
5,978.9 (
5,021.5 (
5,079.2 (
5,181.8
6,203.6
Industrial Processes
300.2
! 14.9
338.8
309.7
320.3
316.6
330.8
333.8
Solvent and Other Product Use
4.3
4.5
4.8
4.8
4.3
4.3
4.3
4.3
Agriculture
530.3
526.8
547.4
560.3
537.4
521.1
507.4
536.3
Land Use, Land-Use Change, and Forestry
(Non-C02 Emissions)
13.0
10.1
21.3
12.4
17.4
15.0
13.9
18.9
Waste
192.2
IS9.1
165.9
161.1
163.9
168.4
165.7
165.4
Total
6,242.1
6,571.0
7,147.3 7,027.1 '
7,064.8 7,104.4 7,203.9
7,262.3
Net C02 Flux from Land Use, Land-Use
Change, and Forestry*
(712.9)
(828.5)
(754.7) I
1765.5) I
1809.9) I
1811.6) I
^824.9)
(828.4)
Net Emissions (Sources and Sinks)
5,529.1
: 5,742.5 !
6,392.6 (
5,261.6 (
5,254.8 (
5,292.8 (
5,379.0
6,433.9
* The net C02 flux total includes both emissions and sequestration, and constitutes a sink in the United States. Sinks are only
included in net emissions total.
Note: Totals may not sum due to independent rounding.
Note: Parentheses indicate negative values or sequestration.
Energy
Energy-related activities, primarily fossil fuel combustion, accounted for the vast majority of U.S. C02 emissions
for the period of 1990 through 2005. In 2005, approximately 86 percent of the energy consumed in the United
States (on a Btu basis) was produced through the combustion of fossil fuels. The remaining 14 percent came from
other energy sources such as hydropower, biomass, nuclear, wind, and solar energy (see Figure 2-6 and Figure 2-7).
A discussion of specific trends related to C02 as well as other greenhouse gas emissions from energy consumption
is presented below. Energy-related activities are also responsible for CH4 and N20 emissions (38 percent and 11
percent of total U.S. emissions of each gas, respectively). Table 2-6 presents greenhouse gas emissions from the
Energy chapter, by source and gas.
Figure 2-6: 2005 Energy Chapter Greenhouse Gas Sources
Figure 2-7: 2005 U.S. Fossil C Flows (Tg C02 Eq.)
Table 2-6: Emissions from Energy (Tg C02 Eq )
Gas/Source
1990
1995
2000 2001 2002 2003 2004 2005
co2
4,886.1
5,212.7
5,773.1 5,690.2 5,740.7 5,803.7 5,911.5 5,944.2
2-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Public Review Draft
Fossil Fuel Combustion 4,724.1 5,030.0 5,584.9 5,511.7 5,557.2 5,624.5 5,713.0 5,752.8
Non-Energy Use of Fuels 117.2 133.1 141.0 131.3 135.3 131.3 150.2 142.3
Natural Gas Systems 33.7 33.8 29.4 28.8 29.6 28.4 28.2 28.2
Municipal Solid Waste Combustion 10.9 15.7 17.9 18.3 18.5 19.5 20.1 20.9
Biomass-Wood* 215.2 229.1 219.1 193.5 192.8 193.8 205.1 184.1
International Bunker Fuels* 113. ~ 100.0 101.1 97.6 89.1 83.7 97.2 95.6
Biomass-Ethanol Consumption* 4.. 9.2 9.7 11.5 15.8 19.7 22.4
CH4 259.6 246.1 228.5 225.0 219.7 217.4 214.6 207.1
Natural Gas Systems 124.5 128.1 126.6 125.4 125.0 123.7 119.0 111.1
Coal Mining 81.9 66.5 55.9 55.5 52.0 52.1 54.5 52.4
Petroleum Systems 34.4 311 27.8 27.4 26.8 25.8 25.4 28.5
Stationary Combustion 8.0 7.8 7.4 6.8 6.8 7.0 7.1 6.9
Abandoned Underground Coal 6.0 8.2 7.3 6.7 6.1 5.9 5.8 5.5
Mines
Mobile Combustion
4.7
4.3
3.5
3.2
3.1
2.9
2.8
2.6
International Bunker Fuels*
0.2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
n2o
56.5
66.9
67.6
63.7
61.1
58.0
55.7
52.3
Mobile Combustion
43.7
53.7
53.2
49.7
47.1
43.8
41.2
38.0
Stationary Combustion
12.3
12.8
14.0
13.5
13.4
13.7
13.9
13.8
Municipal Solid Waste Combustion
0.5 .
0.5
0.4
0.5
0.5
0.5
0.5
0.5
International Bunker Fuels*
1.0
0.9
0.9
0.9
0.8
0.8
0.9
0.9
Total
5,202.1 5,525.7 6,069.2 5,978.9 6,021.5 6,079.2 6,181.8 6,203.6
* 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.
Fossil Fuel Combustion (5,752.8 Tg C02 Eq.)
As fossil fuels are combusted, the C stored in them is emitted almost entirely as C02. The amount of C in fuels per
unit of energy content varies significantly by fuel type. For example, coal contains the highest amount of C per unit
of energy, while petroleum and natural gas have about 25 percent and 45 percent less C than coal, respectively.
From 1990 through 2005, petroleum supplied the largest share of U.S. energy demands, accounting for an average
of 44 percent of total energy consumption with natural gas and coal each accounting for 28 percent of total energy
consumption. Petroleum was consumed primarily in the transportation end-use sector, the vast majority of coal was
used by electric power generators, and natural gas was consumed largely in the industrial and residential end-use
sectors.
Emissions of C02 from fossil fuel combustion increased at an average annual rate of 1.3 percent from 1990 to 2005.
The fundamental factors influencing this trend include (1) a generally growing domestic economy over the last 15
years, and (2) significant growth in emissions from electricity generation and transportation activities. Between
1990 and 2005, C02 emissions from fossil fuel combustion increased from 4,724.1 Tg C02 Eq. to 5,752.8 Tg C02
Eq.—a 21.8 percent total increase over the fifteen-year period.
The four major end-use sectors contributing to C02 emissions from fossil fuel combustion are industrial,
transportation, residential, and commercial. Electricity generation also emits C02, although these emissions are
produced as they consume fossil fuel to provide electricity to one of the four end-use sectors. For the discussion
below, electricity generation emissions have been distributed to each end-use sector on the basis of each sector's
share of aggregate electricity consumption. This method of distributing emissions assumes that each end-use sector
consumes electricity that is generated from the national average mix of fuels according to their C intensity.
Emissions from electricity generation are also addressed separately after the end-use sectors have been discussed.
Note that emissions from U.S. territories are calculated separately due to a lack of specific consumption data for the
individual end-use sectors.
Table 2-7, Figure 2-8, and Figure 2-9 summarize C02 emissions from fossil fuel combustion by end-use sector.
Trends in Greenhouse Gas Emissions 2-9
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Public Review Draft
Table 2-7: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eg.)
End-Use Sector
1990
1995
2000
2001
2002
2003
2004
2005
Transportation
1,467.0
1,593.3
1,787.8
1,761.5
1,815.7
1,814.8
1,868.9
1,899.5
Combustion
1,464.0
1,590.2
1,784.4
1,758.2
1,812.3
1,810.5
1,864.5
1,894.4
Electricity
3.0
3.0
3.4
3.3
3.4
4.3
4.4
5.2
Industrial
1,539.8
1,595.8
1,660.1
1,596.6
1,575.5
1,595.1
1,615.2
1,575.2
Combustion
857.1
882.7
875.0
869.9
857.7
858.3
875.6
840.1
Electricity
682.7
713.1
785.1
726.7
717.8
736.8
739.6
735.1
Residential
929.9
995.4
1,131.5
1,124.8
1,147.9
1,179.1
1,175.9
1,208.7
Combustion
340.3
356.4
373.5
363.9
362.4
383.8
369.9
358.7
Electricity
589.6
639.0 ;/,!
758.0
760.9
785.5
795.3
806.0
849.9
Commercial
759.2
810.6
969.3
979.7
973.8
984.2
999.1
1,016.8
Combustion
224.3
226.4
232.3
225.1
225.7
236.6
233.3
225.8
Electricity
534.9
584.2
736.9
754.6
748.0
747.6
765.8
791.0
U.S. Territories
28.3
35.0
36.2
49.0
44.3
51.3
54.0
52.5
Total
4,724.1
5,030.0
5,584.9
5,511.7
5,557.2
5,624.5
5,713.0
5,752.8
Electricity Generation
1,810.2
1,939.3
I 2,283.5
2,245.5
2,254.7
2,284.0
2,315.8
2,381.2
Note: Totals may not sum due to independent rounding. Combustion-related emissions from electricity generation are allocated
based on aggregate national electricity consumption by each end-use sector.
Figure 2-8: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Figure 2-9: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion
Transportation End-Use Sector. Transportation activities (excluding international bunker fuels) accounted for 33
percent of C02 emissions from fossil fuel combustion in 2005.3 Virtually all of the energy consumed in this end-
use sector came from petroleum products. Over 60 percent of the emissions resulted from gasoline consumption for
personal vehicle use. The remaining emissions came from other transportation activities, including the combustion
of diesel fuel in heavy-duty vehicles and jet fuel in aircraft.
Industrial End-Use Sector. Industrial C02 emissions, resulting both directly from the combustion of fossil fuels and
indirectly from the generation of electricity that is consumed by industry, accounted for 27 percent of C02
emissions from fossil fuel combustion in 2005. About half of these emissions resulted from direct fossil fuel
combustion to produce steam and/or heat for industrial processes. The other half of the emissions resulted from
consuming electricity for motors, electric furnaces, ovens, lighting, and other applications.
Residential and Commercial End-Use Sectors. The residential and commercial end-use sectors accounted for 21
and 18 percent, respectively, of C02 emissions from fossil fuel combustion in 2005. Both sectors relied heavily on
electricity for meeting energy demands, with 70 and 78 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
3 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 2005.
2-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 U.S. energy from fossil fuels and emitted 41 percent of the C02 from fossil fuel combustion in 2005. The type of
2 fuel combusted by electricity generators has a significant effect on their emissions. For example, some electricity is
3 generated with low-C02-emitting energy technologies, particularly non-fossil options such as nuclear, hydroelectric,
4 or geothermal energy. However, electricity generators rely on coal for over half of their total energy requirements
5 and accounted for 93 percent of all coal consumed for energy in the United States in 2005. Consequently, changes
6 in electricity demand have a significant impact on coal consumption and associated C02 emissions.
7 Non-Energy Use of Fossil Fuels (142.3 Tg C02 Eq.)
8 In addition to being combusted for energy, fossil fuels are also consumed for non-energy uses (NEUs). Fuels are
9 used in the industrial and transportation end-use sectors for a variety of NEUs, including application as solvents,
10 lubricants, and waxes, or as raw materials in the manufacture of plastics, rubber, and synthetic fibers. C02
11 emissions arise from non-energy uses via several pathways. Emissions may occur during the manufacture of a
12 product, as is the case in producing plastics or rubber from fuel-derived feedstocks. Additionally, emissions may
13 occur during the product's lifetime, such as during solvent use. Where appropriate data and methodologies are
14 available, NEUs of fossil fuels used for industrial processes are reported in the Industrial Processes chapter.
15 Emissions in 2005 for non-energy uses of fossil fuels were 142.3 Tg C02 Eq., which constituted 3 percent of overall
16 fossil fuel C02 emissions and 2 percent of total national C02 emissions, approximately the same proportion as in
17 1990. C02 emissions from non-energy use of fossil fuels increased by 25.1 Tg C02 Eq. (21 percent) from 1990
18 through 2005.
19 Natural Gas Systems (139.3 Tg C02 Eq.)
20 CH4 and non-energy C02 emissions from natural gas systems are generally process-related, with normal operations,
21 routine maintenance, and system upsets being the primary contributors. Emissions from normal operations include:
22 natural gas engines and turbine uncombusted exhaust, bleed and discharge emissions from pneumatic devices, and
23 fugitive emissions from system components. Routine maintenance emissions originate from pipelines, equipment,
24 and wells during repair and maintenance activities. Pressure surge relief systems and accidents can lead to system
25 upset emissions. In 2005, CH4 emissions from U.S. natural gas systems accounted for approximately 21 percent of
26 U.S. CH4 emissions. Also in 2005, natural gas systems accounted for approximately 0.5 percent of U.S. C02
27 emissions (28.2 Tg C02 Eq.). From 1990 through 2005, CH4 and C02 emissions from natural gas systems
28 decreased by 13.3 Tg C02 Eq. (11 percent), and 5.5 Tg C02 Eq. (16 percent) respectively.
29 International Bunker Fuels (96.6 Tg C02 Eq.)
30 Greenhouse gases emitted from the combustion of fuels used for international transport activities, termed
31 international bunker fuels under the UNFCCC, include C02, CH4, and N20. Emissions from these activities are
32 currently not included in national emission totals, but are reported separately based upon location of fuel sales. The
33 decision to report emissions from international bunker fuels separately, instead of allocating them to a particular
34 country, was made by the Intergovernmental Negotiating Committee in establishing the Framework Convention on
35 Climate Change. These decisions are reflected in the Revised 1996IPCC Guidelines, in which countries are
36 requested to report emissions from ships or aircraft that depart from their ports with fuel purchased within national
37 boundaries and are engaged in international transport separately from national totals (IPCC/UNEP/OECD/IEA
38 1997).
39 Two transport modes are addressed under the IPCC definition of international bunker fuels: aviation and marine.
40 Emissions from ground transport activities—by road vehicles and trains, even when crossing international
41 borders—are allocated to the country where the fuel was loaded into the vehicle and, therefore, are not counted as
42 bunker fuel emissions. Emissions of C02, CH4, and N20 from international bunker fuel combustion were 95.6, 0.1,
43 and 0.9 Tg C02 Eq. in 2005, respectively. From 1990 through 2005, C02, CH4, and N20 emissions from
44 international bunker fuels decreased by 18.1 Tg C02 Eq. (16 percent), 0.1 Tg C02 Eq. (36 percent), and 0.1 Tg C02
45 Eq. (10 percent), respectively.
46 Coal Mining (52.4 Tg C02 Eq.)
47 Produced millions of years ago during the formation of coal, CH4 trapped within coal seams and surrounding rock
Trends in Greenhouse Gas Emissions 2-11
-------
Public Review Draft
1 strata is released when the coal is mined. The quantity of CH4 released to the atmosphere during coal mining
2 operations depends primarily upon the type of coal and the method and rate of mining.
3 CH4 from surface mines is emitted directly to the atmosphere as the rock strata overlying the coal seam are
4 removed. Because CH4 in underground mines is explosive at concentrations of 5 to 15 percent in air, most active
5 underground mines are required to vent this CH4, typically to the atmosphere. At some mines, CH4-recovery
6 systems may supplement these ventilation systems. During 2005, coal mining activities emitted 10 percent of U.S.
7 CH4 emissions. From 1990 to 2005, emissions from this source decreased by 29.5 Tg C02 Eq. (36 percent) due to
8 increased use of the CH4 collected by mine degasification systems and a general shift toward surface mining.
9 Mobile Combustion (40.6 Tg C02 Eq.)
10 In addition to C02, mobile combustion results in N20 and CH4 emissions. N20 is a product of the reaction that
11 occurs between nitrogen and oxygen during fuel combustion. The quantity emitted varies according to the type of
12 fuel, technology, and pollution control device used, as well as maintenance and operating practices. For example,
13 some types of catalytic converters installed to reduce motor vehicle pollution can promote the formation of N20. In
14 2005, N20 emissions from mobile combustion were 38.0 Tg C02 Eq. (8 percent of U.S. N20 emissions). From
15 1990 to 2005, N20 emissions from mobile combustion decreased by 5.7 Tg C02 Eq. (13 percent). In 2005, CH4
16 emissions were estimated to be 2.6 Tg C02 Eq. The combustion of gasoline in highway vehicles was responsible
17 for the majority of the CH4 emitted from mobile combustion. From 1990 to 2005, CH4 emissions from mobile
18 combustion decreased by 2.1 Tg C02 Eq. (45 percent).
19 Petroleum Systems (28.5 Tg C02 Eq.)
20 Petroleum is often found in the same geological structures as natural gas, and the two are often retrieved together.
21 Crude oil is saturated with many lighter hydrocarbons, including CH4. When the oil is brought to the surface and
22 processed, many of the dissolved lighter hydrocarbons (as well as water) are removed through a series of high-
23 pressure and low-pressure separators. The remaining hydrocarbons in the oil are emitted at various points along the
24 system. CH4 emissions from the components of petroleum systems generally occur as a result of system leaks,
25 disruptions, and routine maintenance. In 2005, emissions from petroleum systems were about 5 percent of U. S. CH4
26 emissions. From 1990 to 2005, CH4 emissions from petroleum systems decreased by 6 Tg C02 Eq. (17 percent).
27 Municipal Solid Waste Combustion (21.4 Tg C02 Eq.)
28 Combustion is used to manage about 14 percent of the municipal solid waste generated in the United States. The
29 burning of garbage and non-hazardous solids, referred to as municipal solid waste, as well as the burning of
30 hazardous waste, is usually performed to recover energy from the waste materials. C02 and N20 emissions arise
31 from the organic materials found in these wastes. The C02 emissions from municipal solid waste containing C of
32 biogenic origin (e.g., paper, yard trimmings) are not accounted for in this Inventory, since they are presumed to be
33 offset by regrowth of the original living source, and are ultimately accounted for in the Land Use, Land-Use
34 Change, and Forestry chapter. Several components of municipal solid waste, such as plastics, synthetic rubber,
35 synthetic fibers, and carbon black, are of fossil-fuel origin, and are included as sources of C02 and N20 emissions.
36 In 2005, C02 emissions from waste combustion amounted to 20.9 Tg C02 Eq., while N20 emissions amounted to
37 0.5 Tg C02 Eq. From 1990 through 2005, C02 and N20 emissions from waste combustion increased by 10 Tg C02
38 Eq. (91 percent) and O.lTg C02 Eq. (12 percent), respectively,
39 Stationary Combustion (20.7 Tg C02 Eq.)
40 In addition to C02, stationary combustion results in N20 and CH4 emissions. In 2005, N20 emissions from
41 stationary combustion accounted for 13.8 Tg C02 Eq. (3 percent of U.S. N20 emissions). From 1990 to 2005, N20
42 emissions from stationary combustion increased by 1.5 Tg C02 Eq. (12 percent), due to increased fuel consumption.
43 In 2005, CH4 emissions were 6.9 Tg C02 Eq. (1 percent of U.S. CH4 emissions). From 1990 to 2005, CH4
44 emissions from stationary combustion decreased by 1.1 Tg C02 Eq. (13.5 percent). The majority of CH4 emissions
45 from stationary combustion resulted from the burning of wood in the residential end-use sector.
2-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Abandoned Underground Coal Mines (5.5 Tg C02 Eq.)
2 Coal mining activities result in the emission of CH4 into the atmosphere. However, the closure of a coal mine does
3 not correspond with an immediate cessation in the release of emissions. Following an initial decline, abandoned
4 mines can liberate CH4 at a near-steady rate over an extended period of time, or, if flooded, produce gas for only a
5 few years. In 2005, the emissions from abandoned underground coal mines constituted 1 percent of U.S. CH4
6 emissions. Between 1990 and 2005, emissions from this source decreased by 0.5 Tg C02 Eq. (8 percent).
7 Wood Biomass and Ethanol Consumption (206.5 Tg C02 Eq.)
8 Biomass refers to organically-based C fuels (as opposed to fossil-based). Biomass in the form of fuel wood and
9 wood waste was used primarily in the industrial sector, while the transportation sector was the predominant user of
10 biomass-based fuels, such as ethanol from corn and woody crops.
11 Although these fuels do emit C02, in the long run the C02 emitted from biomass consumption does not increase
12 atmospheric C02 concentrations if the biogenic C emitted is offset by the growth of new biomass. For example,
13 fuel wood burned one year but re-grown the next only recycles C, rather than creating a net increase in total
14 atmospheric C. Net C fluxes from changes in biogenic C reservoirs in forest lands or croplands are accounted for in
15 the estimates for the Land Use, Land-Use Change, and Forestry sector. As a result, C02 emissions from biomass
16 combustion have been estimated separately from fossil-fuel-based emissions and are not included in the U.S. totals.
17 CH4 emissions from biomass combustion are included in the Stationary Combustion source described below.
18 The consumption of wood biomass in the industrial, residential, electric power, and commercial end-use sectors
19 accounted for 56, 21, 8, and 4 percent of gross C02 emissions from wood biomass and ethanol consumption,
20 respectively. Ethanol consumption in the transportation end-use sector accounted for the remaining 11 percent.
21 C02 emissions from wood biomass and ethanol consumption decreased by 12.9 Tg C02 Eq. (approximately 6
22 percent) from 1990 through 2005.
23 International Bunker Fuels (96.6 Tg C02 Eq.)
24 Greenhouse gases emitted from the combustion of fuels used for international transport activities, termed
25 international bunker fuels under the UNFCCC, include C02, CH4, and N20. Emissions from these activities are
26 currently not included in national emission totals, but are reported separately based upon location of fuel sales. The
27 decision to report emissions from international bunker fuels separately, instead of allocating them to a particular
28 country, was made by the Intergovernmental Negotiating Committee in establishing the Framework Convention on
29 Climate Change. These decisions are reflected in the Revised 1996IPCC Guidelines, in which countries are
30 requested to report emissions from ships or aircraft that depart from their ports with fuel purchased within national
31 boundaries and are engaged in international transport separately from national totals (IPCC/UNEP/OECD/IEA
32 1997).
33 Two transport modes are addressed under the IPCC definition of international bunker fuels: aviation and marine.
34 Emissions from ground transport activities—by road vehicles and trains, even when crossing international
35 borders—are allocated to the country where the fuel was loaded into the vehicle and, therefore, are not counted as
36 bunker fuel emissions. Emissions of C02, CH4, and N20 from international bunker fuel combustion were 95.6, 0.1,
37 and 0.9 Tg C02 Eq. in 2005, respectively. From 1990 through 2005, C02, CH4, and N20 emissions from
38 international bunker fuels decreased by 18.1 Tg C02 Eq. (16 percent), 0.1 Tg C02 Eq. (36 percent), and 0.1 Tg C02
39 Eq. (10 percent), respectively.
40 Industrial Processes
41 Emissions are produced as a by-product of many non-energy-related industrial process activities. For example,
42 industrial processes can chemically transform raw materials, which often release waste gases such as C02, CH4, and
43 N20. These processes include iron and steel production, cement manufacture, ammonia manufacture and urea
44 application, lime manufacture, limestone and dolomite use (e.g., flux stone, flue gas desulfurization, and glass
Trends in Greenhouse Gas Emissions 2-13
-------
1
2
3
4
5
6
7
8
9
10
11
Public Review Draft
manufacturing), soda ash manufacture and use, titanium dioxide production, phosphoric acid production, ferroalloy
production, C02 consumption, silicon carbide production and consumption, aluminum production, petrochemical
production, nitric acid production, adipic acid production, lead production, and zinc production (see Figure 2-10).
Additionally, emissions from industrial processes release HFCs, PFCs and SF6. Table 2-8 presents greenhouse gas
emissions from industrial processes by source category.
Figure 2-10: 2005 Industrial Processes Chapter Greenhouse Gas Sources
Table 2-8: Emissions from Industrial Processes (Tg C02 Eq.)
Gas/Source 19901
1995
co2
175.6|
Cement Manufacture
33.3
Iron and Steel Production
85.0
Ammonia Manufacture &
Urea Application
19.3
Lime Manufacture
11.2
Limestone and Dolomite Use
5.5
Aluminum Production
6.8
Soda Ash Manufacture and
Consumption
4.1
Petrochemical Production
2.2
Titanium Dioxide Production
1.3
Phosphoric Acid Production
1.5
Ferroalloy Production
2.2
C02 Consumption
1.4
Zinc Production
0.9
Lead Production
0.3
Silicon Carbide Consumption
and Consumption
0.4
ch4
2.2
Petrochemical Production
0.9
Iron and Steel Production
1.3
Ferroalloy Production
+
Silicon Carbide Production
and Consummption
+
n2o
33.0
Nitric Acid Production
17'8
Adipic Acid Production
15.2
HFCs, PFCs, and SF6
89.3
Substitution of Ozone
Depleting Substances
0.3
HCFC-22 Production
35.0
Electrical Transmission and
Distribution
27.1
Semiconductor Manufacture
2.9
Aluminum Production
18.5
Magnesium Production and
Processing
5.41
171.9
36.:-
73 *
20.5
12.8
74
5.7
4 3
2.81
1.7
1.51
2.0|
1.4
1.01
0.3
0.3
2.4
I I
1.3
+1
+|
37.1
19.9
17.21
103-51
32.21
27.0
21.81
5.0
11.81
5.(>
Total
300.21
314.9
2000
2001
2002
2003
2004
2005
166.9
152.9
152.1
148.8
152.9
147.0
41.2
41.4
42.9
43.1
45.6
45.9
j 65.3
58.0
54.7
53.5
51.5
45.4
19.6
16.7
17.8
16.2
16.9
16.3
| 13.3
12.8
12.3
13.0
13.7
13.7
i 6.0
5.7
5.9
4.7
6.7
7.4
6.1
4.4
4.5
4.5
4.2
4.2
4.2
4.1
4.1
4.1
4.2
4.2
3.0
2.8
2.9
2.8
2.9
2.9
! 19
1.9
2.0
2.0
2.3
1.9
1.4
1.3
1.3
1.4
1.4
1.4
1.9
1.5
1.3
1.3
1.4
1.4
1.4
0.8
1.0
1.3
1.2
1.3
1.1
1.0
0.9
0.5
0.5
0.5
0.3
0.3
0.3
0.3
0.3
0.3
0.2
0.2
0.2
0.2
0.2
0.2
2.5
2.2
2.1
2.1
2.2
2.0
1.2
1.1
1.1
1.1
1.2
1.1
1.2
1.1
1.0
1.0
1.0
1.0
+
+
+
+
+
+
+
+
+
+
+
+
! 25.6
20.8
23.1
22.9
21.8
21.7
19.6
15.9
17.2
16.7
16.0
15.7
i 6.0
4.9
5.9
6.2
5.7
6.0
143.8
133.8
143.0
142.7
153.9
163.0
80.9
88.6
96.9
105.5
114.5
123.3
29.8
19.8
19.8
12.3
15.6
16.5
15.2
15.1
14.3
13.8
13.6
13.2
6.3
4.5
4.4
4.3
4.7
4.3
8.6
3.5
5.2
3.8
2.8
3.0
3.0
2.4
2.4
2.9
2.6
2.7
338.8
309.6
320.3
316.5
330.8
333.8
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
2-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1
2 Substitution of Ozone Depleting Substances (123.3 Tg C02 Eq.)
3 The use and subsequent emissions of HFCs and PFCs as substitutes for ODSs have increased from small amounts in
4 1990 to 123 Tg C02 Eq. in 2005, accounting for 76 percent of aggregate HFC, PFC, and SF6 emissions, an increase
5 of 36,899 percent over this time period. This increase was in large part the result of efforts to phase-out CFCs and
6 other ODSs in the United States, especially the introduction of HFC-134a as a CFC substitute in refrigeration and
7 air-conditioning applications. In the short term, this trend is expected to continue, and will likely accelerate over the
8 coming decade as HCFCs, which are interim substitutes in many applications, are themselves phased-out under the
9 provisions of the Copenhagen Amendments to the Montreal Protocol. Improvements in the technologies associated
10 with the use of these gases and the introduction of alternative gases and technologies, however, may help to offset
11 this anticipated increase in emissions.
12 Iron and Steel Production (46.4 Tg C02 Eq.)
13 Pig iron is the product of combining iron oxide (i.e., iron ore) and sinter with metallurgical coke in a blast furnace.
14 The pig iron production process, as well as the thermal processes used to create sinter and metallurgical coke,
15 results in emissions of C02 and CH4. In 2005, iron and steel production resulted in 1.0 Tg C02 Eq. of CH4
16 emissions, with the majority of the emissions coming from the pig iron production process. The majority of C02
17 emissions from iron and steel processes come from the production of coke for use in pig iron creation, with smaller
18 amounts evolving from the removal of carbon from pig iron used to produce steel. C02 emissions from iron and
19 steel amounted to 45.4 Tg C02 Eq. in 2005. From 1990 to 2005, C02 and CH4 emissions from this source
20 decreased by 39.6 Tg C02 Eq. (46 percent), and 0.4 Tg C02 Eq. (28 percent) respectively.
21 Cement Manufacture (45.9 Tg C02 Eq.)
22 Clinker is an intermediate product in the formation of finished Portland and masonry cement. Heating calcium
23 carbonate (CaC03) in a cement kiln forms lime and C02. The lime combines with other materials to produce
24 clinker, and the C02 is released into the atmosphere. From 1990 to 2005, emissions from this source increased by
25 12.6 Tg C02 Eq. (38 percent).
26 HCFC-22 Production (16.5 Tg C02 Eq.)
27 HFC-23 is a by-product of the production of HCFC-22. Emissions from this source have decreased by 18.4 Tg C02
28 Eq. (53 percent) since 1990. The HFC-23 emission rate (i.e., the amount of HFC-23 emitted per kilogram of
29 HCFC-22 manufactured) has declined significantly since 1990, although production has been increasing.
30 Ammonia Manufacture and Urea Application (16.3 Tg C02 Eq.)
31 In the United States, roughly 98 percent of synthetic ammonia is produced by catalytic steam reforming of natural
32 gas, and the remainder is produced using naphtha (i.e., a petroleum fraction) or the electrolysis of brine at chlorine
33 plants (EPA 1997). The two fossil fuel-based reactions produce carbon monoxide and hydrogen gas. This carbon
34 monoxide is transformed into C02 in the presence of a catalyst. The C02 is generally released into the atmosphere,
35 but some of the C02, together with ammonia, is used as a raw material in the production of urea [CO(NH2)2], which
36 is a type of nitrogenous fertilizer. The carbon in the urea that is produced and assumed to be subsequently applied
37 to agricultural land as a nitrogenous fertilizer is ultimately released into the environment as C02. Since 1990, C02
38 emissions from ammonia manufacture and urea application have decreased by 3.0 Tg C02 Eq. (15.5 percent).
39 Nitric Acid Production (15.7 Tg C02 Eq.)
40 Nitric acid production is an industrial source of N20 emissions. Used primarily to make synthetic commercial
41 fertilizer, this raw material is also a major component in the production of adipic acid and explosives. Virtually all
42 of the nitric acid manufactured in the United States is produced by the oxidation of ammonia, during which N20 is
43 formed and emitted to the atmosphere. In 2005, N20 emissions from nitric acid production accounted for 3 percent
44 of U.S. N20 emissions. From 1990 to 2005, emissions from this source category decreased by 2.2 Tg C02 Eq. (12
45 percent) with the trend in the time series closely tracking the changes in production.
Trends in Greenhouse Gas Emissions 2-15
-------
Public Review Draft
1 Lime Manufacture (13.7 Tg C02 Eq.)
2 Lime is used in steel making, construction, flue gas desulfurization, and water and sewage treatment. It is
3 manufactured by heating limestone (mostly CaC03) in a kiln, creating quicklime (calcium oxide, CaO) and C02,
4 which is normally emitted to the atmosphere. From 1990 to 2005, C02 emissions from lime manufacture increased
5 by 2.4 Tg C02 Eq. (21 percent).
6 Electrical Transmission and Distribution Systems (13.2 Tg C02 Eq.)
7 The primary use of SF6 is as a dielectric in electrical transmission and distribution systems. Fugitive emissions of
8 SF6 occur from leaks in and servicing of substations and circuit breakers, especially from older equipment. The gas
9 can also be released during equipment manufacturing, installation, servicing, and disposal. Estimated emissions
10 from this source decreased by 13.9 Tg C02 Eq. (51 percent) since 1990, primarily due to higher SF6 prices and
11 industrial efforts to reduce emissions.
12 Limestone and Dolomite Use (7.4 Tg C02 Eq.)
13 Limestone (CaC03) and dolomite (CaMg(C03)2) are basic raw materials used in a wide variety of industries,
14 including construction, agriculture, chemical, and metallurgy. For example, limestone can be used as a purifier in
15 refining metals. In the case of iron ore, limestone heated in a blast furnace reacts with impurities in the iron ore and
16 fuels, generating C02 as a by-product. Limestone is also used in flue gas desulfurization systems to remove sulfur
17 dioxide from the exhaust gases. From 1990 to 2005, emissions from this source increased by 1.9 Tg C02 Eq. (34
18 percent).
19 Aluminum Production (7.2 Tg C02 Eq.)
20 Aluminum production results in emissions of C02, CF4 and C2F6. C02 is emitted when alumina (aluminum oxide,
21 A1203) is reduced to aluminum. The reduction of the alumina occurs through electrolysis in a molten bath of natural
22 or synthetic cryolite. The reduction cells contain a carbon lining that serves as the cathode. Carbon is also
23 contained in the anode, which can be a carbon mass of paste, coke briquettes, or prebaked carbon blocks from
24 petroleum coke. During reduction, some of this carbon is oxidized and released to the atmosphere as C02. In 2005,
25 C02 emissions from aluminum production amounted to 4.2 Tg C02 Eq. Since 1990, C02 emissions from this
26 source have decreased by 2.6 Tg C02 Eq. (38 percent).
27 During the production of primary aluminum, CF4 and C2F6 are emitted as intermittent by-products of the smelting
28 process. These PFCs are formed when fluorine from the cryolite bath combines with carbon from the electrolyte
29 anode. PFC emissions from aluminum production have decreased by 15.6 Tg C02 Eq. (84 percent) between 1990
30 and 2005 due to emission reduction efforts by the industry and falling domestic aluminum production, although
31 there was a slight increase in emissions between 2004 and 2005, due to slightly higher production. In 2005, CF4
32 and C2F6 emissions from aluminum production amounted to 3.0 Tg C02 Eq.
33 Adipic Acid Production (6.0 Tg C02 Eq.)
34 Most adipic acid produced in the United States is used to manufacture nylon 6,6. Adipic acid is also used to
35 produce some low-temperature lubricants and to add a "tangy" flavor to foods. N20 is emitted as a by-product of
36 the chemical synthesis of adipic acid. In 2005, U.S. adipic acid plants emitted 1.3 percent of U.S. N20 emissions.
37 Even though adipic acid production has increased in recent years, by 1998 all three major adipic acid plants in the
38 United States had voluntarily implemented N20 abatement technology. As a result, emissions have decreased by
39 9.2 Tg C02 Eq. (61 percent) between 1990 and 2005.
40 Semiconductor Manufacture (4.3 Tg C02 Eq.)
41 The semiconductor industry uses combinations of HFCs, PFCs, SF6, and other gases for plasma etching and to clean
42 chemical vapor deposition tools. Emissions from this source category have increased 1.4 Tg C02 Eq. (48 percent)
43 since 1990 with the growth in the semiconductor industry and the rising intricacy of chip designs. However, the
44 growth rate in emissions has slowed since 1997, and emissions actually declined between 1999 and 2005. This later
2-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 reduction is due to the implementation of PFC emission reduction methods, such as process optimization.
2 Soda Ash Manufacture and Consumption (4.2 Tg C02 Eq.)
3 Commercial soda ash (sodium carbonate, Na2C03) is used in many consumer products, such as glass, soap and
4 detergents, paper, textiles, and food. During the manufacturing of soda ash, some natural sources of sodium
5 carbonate are heated and transformed into a crude soda ash, in which C02 is generated as a by-product. In addition,
6 C02 is often released when the soda ash is consumed. From 1990 to 2005, emissions from this source increased by
7 0.1 Tg C02 Eq. (2 percent).
8 Petrochemical Production (4.0 Tg C02 Eq.)
9 The production process for carbon black results in the release C02 emissions to the atmosphere. Carbon black is a
10 black powder generated by the incomplete combustion of an aromatic petroleum or coal-based feedstock
11 production. The majority of carbon black produced in the United States is consumed by the tire industry, which
12 adds it to rubber to increase strength and abrasion resistance. Small amounts of CH4 are also released during the
13 production of five petrochemicals: carbon black, ethylene, ethylene dichloride, styrene, and methanol. These
14 production processes resulted in emissions of 2.9 Tg C02 Eq. of C02 and 1.1 Tg C02 Eq. of CH4 in 2005.
15 Emissions from this source increased by 0.9 Tg C02 Eq. (29 percent) between 1990 and 2005.
16 Magnesium Production (2.7 Tg C02 Eq.)
17 Sulfur hexafluoride is also used as a protective cover gas for the casting of molten magnesium. Emissions from
18 primary magnesium production and magnesium casting have decreased by 2.8 Tg C02 Eq. (51 percent) since 1990.
19 This decrease has primarily taken place since 1999, due to a decline in the quantity of magnesium die cast and the
20 closure of a U.S. primary magnesium production facility.
21 Titanium Dioxide Production (1.9 Tg C02 Eq.)
22 Titanium dioxide (Ti02) is a metal oxide manufactured from titanium ore, and is principally used as a pigment. It is
23 used in white paint and as a pigment in the manufacture of white paper, foods, and other products. Two processes,
24 the chloride process and the sulfate process, are used for making Ti02. C02 is emitted from the chloride process,
25 which uses petroleum coke and chlorine as raw materials. Since 1990, emissions from this source increased by 0.6
26 Tg C02 Eq. (47 percent).
27 Phosphoric Acid Production (1.4 Tg C02 Eq.)
28 Phosphoric acid is a basic raw material in the production of phosphate-based fertilizers. The phosphate rock
29 consumed in the United States originates from both domestic mines, located primarily in Florida, North Carolina,
30 Idaho, and Utah, and foreign mining operations in Morocco. The primary use of this material is as a basic
31 component of a series of chemical reactions that lead to the production of phosphoric acid, as well as the by-
32 products C02 and phosphogypsum. From 1990 to 2005, C02 emissions from phosphoric acid production decreased
33 by 0.1 Tg C02 Eq. (9.5 percent).
34 Ferroalloy Production (1.4 Tg C02 Eq.)
35 C02 is emitted from the production of several ferroalloys. Ferroalloys are composites of iron and other elements
36 such as silicon, manganese, and chromium. When incorporated in alloy steels, ferroalloys are used to alter the
37 material properties of the steel. From 1990 to 2005, emissions from this source decreased by 0.8 Tg C02 Eq. (35
38 percent).
39 Carbon Dioxide Consumption (1.3 Tg C02 Eq.)
40 Many segments of the economy consume C02, including food processing, beverage manufacturing, chemical
41 processing, and a host of industrial and other miscellaneous applications. C02 may be produced as a by-product
42 from the production of certain chemicals (e.g., ammonia), from select natural gas wells, or by separating it from
Trends in Greenhouse Gas Emissions 2-17
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
crude oil and natural gas. The majority of the C02 used in these applications is eventually released to the
atmosphere. Since 1990, emissions from carbon dioxide consumption have decreased by 0.1 Tg C02 Eq. (6.5
percent).
Zinc Production (0.5 Tg C02 Eq.)
C02 emissions from the production of zinc in the United States occur through the primary production of zinc in the
electro-thermic production process, or through the secondary production of zinc using a Waelz Kiln furnace or the
electro-thermic production process. Both the electro-thermic and Waelz Kiln processes are emissive due to the use
of a carbon-based material (often metallurgical coke); however, zinc is also produced in the United States using
non-emissive processes. Due to the closure of an electro-thermic plant in 2003, the only emissive zinc production
process remaining occurs through the recycling of electric-arc-furnace (EAF) dust in a Waelz Kiln furnace
(secondary production) at a plant in Palmerton, Pennsylvania. From 1990 to 2005, C02 emissions from zinc
production decreased by 0.5 Tg C02 Eq. (51 percent).
Lead Production (0.3 Tg C02 Eq.)
Primary and secondary production of lead in the United States results in C02 emissions when carbon-based
materials (often metallurgical coke) are used as a reducing agent. Primary production involves the direct smelting
of lead concentrates while secondary production largely occurs through the recycling of lead-acid batteries. In
2005, emissions from primary lead production decreased by 40 percent due to the closure of one of two primary
lead production plants located in Missouri. Secondary lead production accounted for 86 percent of total lead
production emissions in 2005. Since 1990, emissions from this source have decreased by 7.2 percent.
Silicon Carbide Production and Consumption (0.2 Tg C02 Eq.)
Small amounts of CH4 are released during the production of silicon carbide (SiC), a material used as an industrial
abrasive. Additionally, small amounts of C02 are released when SiC is consumed for metallurgical and other non-
abrasive purposes (e.g., iron and steel production). Silicon carbide is made through a reaction of quartz (Si02) and
carbon (in the form of petroleum coke). CH4 is produced during this reaction from volatile compounds in the
petroleum coke. CH4 emissions from silicon carbide production have declined significantly due to a 67 percent
decrease in silicon carbide production since 1990. C02 emissions from SiC consumption have fluctuated
significantly between years dependent on consumption, but overall have decreased by 42 percent since 1990.
Solvent and Other Product Use
Greenhouse gas emissions are produced as a by-product of various solvent and other product uses. In the United
States, emissions from N20 Product Usage, the only source of greenhouse gas emissions from this chapter,
accounted for 4.3 Tg C02 Eq. of N20, or less than 0.1 percent of total U.S. emissions in 2005 (see Table 2-9).
Table 2-9: N2Q Emissions from Solvent and Other Product Use (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2001
2002
2003
2004
2005
n2o
4-3
4.5
4.8
4.8
4.3
4.3
4.3
4.3
N20 Product Usage
4.
4.5
4.8
4.8
4.3
4.3
4.3
4.3
Total
4.3
4.5
4.8
4.8
4.3
4.3
4.3
4.3
N20 Product Usage (4.3 Tg C02 Eq.)
N20 is used in carrier gases with oxygen to administer more potent inhalation anesthetics for general anesthesia and
as an anesthetic in various dental and veterinary applications. As such, it is used to treat short-term pain, for
sedation in minor elective surgeries and as an induction anesthetic. The second main use of N20 is as a propellant
in pressure and aerosol products, the largest application being pressure-packaged whipped cream. In 2005, N20
emissions from product usage constituted approximately 1 percent of U.S. N20 emissions. From 1990 to 2005,
emissions from this source category decreased by less than 1 percent.
2-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
Agriculture
Agricultural activities contribute directly to emissions of greenhouse gases through a variety of processes, including
the following source categories: enteric fermentation in domestic livestock, livestock manure management, rice
cultivation, agricultural soil management, and field burning of agricultural residues.
In 2005, agricultural activities were responsible for emissions of 536.3 Tg C02 Eq., or 7.4 percent of total U.S.
greenhouse gas emissions. CH4 and N20 were the primary greenhouse gases emitted by agricultural activities. CH4
emissions from enteric fermentation and manure management represented about 21 percent and 8 percent of total
CH4 emissions from anthropogenic activities, respectively, in 2005. Agricultural soil management activities, such
as fertilizer application and other cropping practices, were the largest source of U.S. N20 emissions in 2005,
accounting for 78 percent. Table 2-10 and Figure 2-11 present emission estimates for the Agriculture chapter.
Figure 2-11: 2005 Agriculture Chapter Greenhouse Gas Sources
Table 2-10: Emissions from Agriculture (Tg C02 Eq.)
Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005
164.0 160.5 161.0 161.2 161.1 158.7 161.2
120.(> 113.5 112.5 112.6 113.0 110.5 112.1
35.1 38.7 40.1 41.1 40.5 39.7 41.3
7.<> 7.5 7.6 6.8 6.9 7.6 6.9
0.7 0.8 0.8 0.7 0.8 0.9 0.9
362.7 386.9 399.2 376.3 359.9 348.7 375.1
353.4 376.8 389.0 366.1 350.2 338.8 365.1
9.0 9.6 9.8 9.7 9.3 9.4 9.5
0.4 0.5 0.5 0.4 0.4 0.5 0.5
ch4
154*4I
Enteric Fermentation
115.7
Manure Management
30.9
Rice Cultivation
7.1
Field Burning of Agricultural
Residues
0.7
n2o
375.9
Agricultural Soil
Management
366.9
Manure Management
8.6
Field Burning of Agricultural
Residues
0.41
Total 530.3 526.8 547.4 560.3 537.4 521.1 507.4 536.3
Note: Totals may not sum due to independent rounding.
Agricultural Soil Management (365.1 Tg C02 Eq.)
N20 is produced naturally in soils through microbial nitrification and denitrification processes. A number of
anthropogenic activities add to the amount of nitrogen available to be emitted as N20 by microbial processes. These
activities may add nitrogen to soils either directly or indirectly. Direct additions occur through the application of
synthetic and organic fertilizers; production of nitrogen-fixing crops and forages; the application of livestock
manure, crop residues, and sewage sludge; cultivation of high-organic-content soils; and direct excretion by animals
onto soil. Indirect additions result from volatilization and subsequent atmospheric deposition, and from leaching
and surface run-off of some of the nitrogen applied to or deposited on soils as fertilizer, livestock manure, and
sewage sludge. In 2005, agricultural soil management accounted for 78 percent of U.S. N20 emissions. From 1990
to 2005, emissions from this source decreased by 1.8 Tg C02 Eq. (0.5 percent); year-to-year fluctuations are largely
a reflection of annual variations in weather, synthetic fertilizer consumption, and crop production.
Enteric Fermentation (112.1 Tg C02 Eq.)
During animal digestion, CH4 is produced through the process of enteric fermentation, in which microbes residing
in animal digestive systems break down food. Ruminants, which include cattle, buffalo, sheep, and goats, have the
highest CH4 emissions among all animal types because they have a rumen, or large fore-stomach, in which CH4-
producing fermentation occurs. Non-ruminant domestic animals, such as pigs and horses, have much lower CH4
emissions. In 2005, enteric fermentation was the source of about 21 percent of U.S. CH4 emissions, and about 70
Trends in Greenhouse Gas Emissions 2-19
-------
Public Review Draft
1 percent of the CH4 emissions from agriculture. From 1990 to 2005, emissions from this source decreased by 3.6 Tg
2 C02 Eq. (3 percent). Generally, emissions have been decreasing since 1995, mainly due to decreasing populations
3 of both beef and dairy cattle and improved feed quality for feedlot cattle.
4 Manure Management (50.8 Tg C02 Eq.)
5 Both CH4 and N20 result from manure management. The decomposition of organic animal waste in an anaerobic
6 environment produces CH4. The most important factor affecting the amount of CH4 produced is how the manure is
7 managed, because certain types of storage and treatment systems promote an oxygen-free environment. In
8 particular, liquid systems tend to encourage anaerobic conditions and produce significant quantities of CH4, whereas
9 solid waste management approaches produce little or no CH4. Higher temperatures and moist climatic conditions
10 also promote CH4 production.
11 CH4 emissions from manure management were 41.3 Tg C02 Eq., or about 8 percent of U.S. CH4 emissions in 2005
12 and 26 percent of the CH4 emissions from agriculture. From 1990 to 2005, emissions from this source increased by
13 10.4 Tg C02 Eq. (34 percent). The bulk of this increase was from swine and dairy cow manure, and is attributed to
14 the shift of the swine and dairy industries towards larger facilities. Larger swine and dairy farms tend to use liquid
15 management systems.
16 N20 is also produced as part of microbial nitrification and denitrification processes in managed and unmanaged
17 manure. Emissions from unmanaged manure are accounted for within the agricultural soil management source
18 category. Total N20 emissions from managed manure systems in 2005 accounted for 9.5 Tg C02 Eq., or 2 percent
19 of U.S. N20 emissions. From 1990 to 2005, emissions from this source category increased by 0.9 Tg C02 Eq. (10
20 percent), primarily due to increases in swine and poultry populations over the same period.
21 Rice Cultivation (6.9 Tg C02 Eq.)
22 Most of the world's rice, and all of the rice in the United States, is grown on flooded fields. When fields are
23 flooded, anaerobic conditions develop and the organic matter in the soil decomposes, releasing CH4 to the
24 atmosphere, primarily through the rice plants. In 2005, rice cultivation was the source of 1 percent of U.S. CH4
25 emissions, and about 4 percent of U.S. CH4 emissions from agriculture. Emission estimates from this source have
26 decreased about 3 percent since 1990.
27 Field Burning of Agricultural Residues (1.4 Tg C02 Eq.)
28 Burning crop residues releases N20 and CH4. Because field burning is not a common debris clearing method in the
29 United States, it was responsible for only 0.2 percent of U.S. CH4 (0.9 Tg C02 Eq.) and 0.1 percent of U.S. N20
30 (0.5 Tg C02 Eq.) emissions in 2005. Since 1990, emissions from this source have increased by approximately 28
31 percent.
32 Land Use, Land-Use Change, and Forestry
33 When humans alter the terrestrial biosphere through land use, changes in land use, and land management practices,
34 they also alter the background carbon fluxes between biomass, soils, and the atmosphere. Forest management
35 practices, tree planting in urban areas, the management of agricultural soils, and the landfilling of yard trimmings
36 and food scraps have resulted in a net uptake (sequestration) of carbon in the United States, which offset about 11
37 percent of total U.S. greenhouse gas emissions in 2005. Forests (including vegetation, soils, and harvested wood)
38 accounted for approximately 85 percent of total 2005 sequestration, urban trees accounted for 11 percent,
39 agricultural soils (including mineral and organic soils and the application of lime) accounted for 3 percent, and
40 landfilled yard trimmings and food scraps accounted for 1 percent of the total sequestration in 2005. The net forest
41 sequestration is a result of net forest growth and increasing forest area, as well as a net accumulation of carbon
42 stocks in harvested wood pools. The net sequestration in urban forests is a result of net tree growth in these areas.
43 In agricultural soils, mineral soils account for a net carbon sink that is almost two times larger than the sum of
44 emissions from organic soils and liming. The mineral soil C sequestration is largely due to the conversion of
45 cropland to permanent pastures and hay production, a reduction in summer fallow areas in semi-arid areas, an
46 increase in the adoption of conservation tillage practices, and an increase in the amounts of organic fertilizers (i.e.,
2-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Public Review Draft
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 2005 resulted in a net C sequestration of 828.4 Tg C02 Eq.
(Table 2-11). This represents an offset of approximately 13.6 percent of total U.S. C02 emissions, or 11.4 percent
of total greenhouse gas emissions in 2005. Total land use, land-use change, and forestry net C sequestration
increased by approximately 16 percent between 1990 and 2005, 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. Net U.S. emissions (all sources and sinks) increased by 16.4 percent from
1990 to 2005.
Table 2-11: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Sink Category
1990
1995
2000
2001
2002
2003
2004
2005
Forest Land Remaining Forest
Land
(598.5)
(717.5) ''
1 (638-7)
(645.7)
(688.1)
(687.0)
(697.3)
(698.7)
Changes in Forest Carbon Stocks
(598.5)
(717.5) 'i
(638.7)
(645.7)
(688.1)
(687.0)
(697.3)
(698.7)
Cropland Remaining Cropland
(28.1)
(37.4)
(36.5)
(38.0)
(37.8)
(38.3)
(39.4)
(39.4)
Changes in Agricultural Soil Carbon
Stocks and Liming Emissions
(28.1)
(37.4)
(36.5)
(38.0)
(37.8)
(38.3)
(39.4)
(39.4)
Land Converted to Cropland
8.7
7.2
7.2
7.2
7.2
7.2
7.2
7.2
Changes in Agricultural Soil Carbon
Stocks
8.7
7.2
7.2
7.2
7.2
7.2
7.2
7.2
Grassland Remaining Grassland
0.1
16.4
1 16,3
16.2
16.2
16.2
16.1
16.1
Changes in Agricultural Soil Carbon
Stocks
0.1
16.4
16.3
16.2
16.2
16.2
16.1
16.1
Land Converted to Grassland
(14.6)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
Changes in Agricultural Soil Carbon
Stocks
(14.6)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
Settlements Remaining Settlements
(57.5)
(67.8)
(78.2)
(80.2)
(82.3)
(84.4)
(86.4)
(88.5)
Urban Trees
(57.5)
(67.8)
(78.2)
(80.2)
(82.3)
(84.4)
(86.4)
(88.5)
Other
(23.0)
(13.0)
(8.5)
(8.6)
(8.9)
(9.0)
(8.9)
(8.8)
Landfilled Yard Trimmings and
Food Scraps
(23.0)
(13.0)
(8.5)
(8.6)
(8.9)
(9.0)
(8.9)
(8.8)
Total
(712.9)
I (828.5)
1 (754.7)
(765.5)
(809.9)
(811.6)
(824.9)
(828.4)
Note: Totals may not sum due to independent rounding. Parentheses indicate net sequestration.
Land use, land-use change, and forestry activities in 2005 also resulted in emissions of N20 (7.3 Tg C02 Eq.) from
application of fertilizers to forests and settlements and from forest fires, and of CH4 (11.6 Tg C02 Eq.) from forest
fires, as shown in Table 2-12. Total N20 emissions from the application of fertilizers to forests and settlements
increased by approximately 19 percent between 1990 and 2005. Emissions of CH4 and N20 from forest fires
fluctuate widely from year to year, but overall increased by 64 percent between 1990 and 2005.
Table 2-12: Non-CQ2 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Land-Use Category
1990
Forest Land Remaining Forest
Land
7.8
CH4 Emissions from Forest Fires
7.1
N20 Emissions from Forest Fires
0.7
N20 Emissions from Soils1
0.1
Settlements Remaining
Settlements6
5.1
N20 Emissions from Soils2
5.1
Total
13.0
2000 2001 2002 2003 2004 2005
15.7
14.0
1.4
0.3
5.6
5.6
6.9
6.0
0.6
0.3
5.5
5.5
11.8
10.4
1.1
0.3
5.6
5.6
9.2
8.1
0.8
0.3
5.8
5.8
8.0
6.9
0.7
0.3
6.0
6.0
13.1
11.6
1.2
0.3
5.8
5.8
21.3
12.4
17.4
15.0 13.9
18.9
Trends in Greenhouse Gas Emissions 2-21
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
Note: Totals may not sum due to independent rounding.
Forest Land Remaining Forest Land (13.1 Tg C02 Eq.)
As with other agricultural applications, forests may be fertilized to stimulate growth rates. The relative magnitude
of the impact of this practice is limited, however, because forests are generally only fertilized twice during their life
cycles, and applications account for no more than one percent of total U.S. fertilizer applications annually. In terms
of trends, however, N20 emissions from forest soils for 2005 were more than 5 times higher than in 1990, primarily
the result of an increase in the fertilized area of pine plantations in the southeastern U.S. This source accounts for
approximately 0.1 percent of total U.S. N20 emissions. Non-C02 emissions from forest fires are directly related to
the area of forest burned, which varies greatly from year to year. CH4 from this source (11.6 Tg C02 Eq.) accounts
for approximately 2 percent of total U.S. CH4 emissions, while N20 from forest fires (1.2 Tg C02 Eq.) accounts for
about 0.3 percent of U.S. N20 emissions. From 1990 to 2005, CH4 and N20 emissions from Forest Land
Remaining Forest Land increased by 4.5 Tg C02 Eq. (64 percent) and 0.8 Tg C02 Eq. (98 percent), respectively.
Settlements Remaining Settlements (5.8 Tg C02 Eq.)
Of the fertilizers applied to soils in the United States, approximately 10 percent are applied to lawns, golf courses,
and other landscaping within settled areas. In 2005, N20 emissions from settlement soils constituted approximately
1 percent of total U.S. N20 emissions. There has been an overall increase in emissions of 13 percent since 1990, a
result of a general increase in the applications of synthetic fertilizers.
Waste
Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 2-12). Landfills
were the largest source of anthropogenic CH4 emissions, accounting for 24 percent of total U.S. CH4 emissions.4
Additionally, wastewater treatment accounts for 5 percent of U.S. CH4 emissions, and 2 percent of N20 emissions.
Nitrogen oxides (NOx), carbon monoxide (CO), and non-CH4 volatile organic compounds (NMVOCs) are also
emitted by waste activities. A summary of greenhouse gas emissions from the Waste chapter is presented in Table
2-13.
Figure 2-12: 2005 Waste Chapter Greenhouse Gas Sources
Overall, in 2005, waste activities generated emissions of 165.4 Tg C02 Eq., or 2.3 percent of total U.S. greenhouse
gas emissions.
Table 2-13: Emissions from Waste (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2001
2002
2003
2004
2005
ch4
185.8
182.2
158.3
153.5
156.2
160.5
157.8
157.4
Landfills
161.0
157.1
131.9
127.6
130.4
134.9
132.1
132.0
Wastewater Treatment
24.8
25.1
26.4
25.9
25.8
25.6
25.7
25.4
n2o
6.4
6.9
7.6
7.6
7.7
7.8
7.9
8.0
Wastewater Treatment
6.4
6.9 ¦;
7.6
7.6
7.7
7.8
7.9
8.0
Total
192.2
189.1
165.9
161.1
163.9
168.4
165.7
165.4
Note: Totals may not sum due to independent rounding.
4 Landfills also store carbon, due to incomplete degradation of organic materials such as wood products and yard trimmings, as
described in the Land-Use, Land-Use Change, and Forestry chapter.
2-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Public Review Draft
Landfills (132.0 Tg C02 Eq.)
Landfills are the largest anthropogenic source of CH4 emissions in the United States, accounting for approximately
24 percent of total CH4 emissions in 2005. In an environment where the oxygen content is low or zero, anaerobic
bacteria decompose organic materials, such as yard waste, household waste, food waste, and paper, resulting in the
generation of CH4 and biogenic C02. Factors such as waste composition and moisture influence the level of CH4
generation. From 1990 to 2005, net CH4 emissions from landfills decreased by 29 Tg C02 Eq. (18 percent), with
small increases occurring in some interim years. This downward trend in overall emissions is the result of increases
in the amount of landfill gas collected and combusted,5 which has more than offset the additional CH4 emissions
resulting from an increase in the amount of municipal solid waste landfilled.
Wastewater Treatment (33.4 Tg C02 Eq.)
Wastewater from domestic sources (i.e., municipal sewage) and industrial sources is treated to remove soluble
organic matter, suspended solids, pathogenic organisms and chemical contaminants. Soluble organic matter is
generally removed using biological processes in which microorganisms consume the organic matter for maintenance
and growth. Microorganisms can biodegrade soluble organic material in wastewater under aerobic or anaerobic
conditions, with the latter condition producing CH4. During collection and treatment, wastewater may be
accidentally or deliberately managed under anaerobic conditions. In addition, the sludge may be further
biodegraded under aerobic or anaerobic conditions. Untreated wastewater may also produce CH4 if contained under
anaerobic conditions. N20 may be generated during both nitrification and denitrification of the nitrogen present,
usually in the form of urea, ammonia, and proteins. In 2005, wastewater treatment was the source of approximately
5 percent of U.S. CH4 emissions, and 2 percent of N20 emissions. From 1990 to 2005, CH4 and N20 emissions
from wastewater treatment increased by 0.6 Tg C02 Eq. (2.5 percent) and 1.6 Tg C02 Eq. (26 percent), respectively.
2.2. Emissions by Economic Sector
Throughout this report, emission estimates are grouped into six sectors (i.e., chapters) defined by the IPCC:
Energy; Industrial Processes; Solvent 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 "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 2005. 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 2005.
In contrast to electricity generation and transportation, emissions from industry have in general declined over the
past decade. The long-term decline in these emissions has been due to structural changes in the U.S. economy (i.e.,
shifts from a manufacturing-based to a service-based economy), fuel switching, and efficiency improvements. The
remaining 20 percent of U.S. greenhouse gas emissions were contributed by the residential, agriculture, and
commercial sectors, plus emissions from U.S. territories. The residential sector accounted for about 5 percent, and
primarily consisted of C02 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 N20 emissions from agricultural soil management and CH4 emissions from enteric fermentation, rather than C02
from fossil fuel combustion. The commercial sector accounted for about 6 percent of emissions, while U.S.
territories accounted for 1 percent.
5 The C02 produced from combusted landfill CH4 at landfills is not counted in national inventories as it is considered part of the
natural C cycle of decomposition.
Trends in Greenhouse Gas Emissions 2-23
-------
Public Review Draft
1 C02 was also emitted and sequestered by a variety of activities related to forest management practices, tree planting
2 in urban areas, the management of agricultural soils, and landfilling of yard trimmings.
3 Table 2-14 presents a detailed breakdown of emissions from each of these economic sectors by source category, as
4 they are defined in this report. Figure 2-13 shows the trend in emissions by sector from 1990 to 2005.
5
6 Figure 2-13: Emissions Allocated to Economic Sectors
7
8 Table 2-14: U.S. Greenhouse Gas Emissions Allocated to Economic Sectors (Tg C02 Eq. and Percent of Total in
9 2005)
Sector/Source
1990
1995
2000
2001
2002
2003
2004
2005
Percent3
Electricity Generation
1,859.7
1,989.5
2,329.9
2,292.0
2,300.9
2,330.3
2,363.5
2,429.9
33.5%
C02 from Fossil Fuel
Combustion
1,810.2
1 i'939-3
2,283.5
2,245.5
2,254.7
2,284.0
2,315.8
2,381.2
32.8%
Municipal Solid Waste
Combustion
11.4
16.2
18.3
18.8
19.0
20.0
20.6
21.4
0.3%
Electrical Transmission and
Distribution
27.1
21.8
15.2
15.1
14.3
13.8
13.6
13.2
0.2%
Stationary Combustion
8.1
8.6
10.0
9.8
9.8
10.1
10.1
10.4
0.1%
Limestone and Dolomite
Use
2.8
3.7
3.0
2.9
2.9
2.4
3.4
3.7
0.1%
Transportation
1,523.0
1,677.2
1,903.2
1,876.4
1,931.2
1,928.2
1,982.6
2,010.5
27.7%
C02 from Fossil Fuel
Combustion
1,464.0
1 1,590.2
1,784.4
1,758.2
1,812.3
1,810.5
1,864.5
1,894.4
26.1%
Substitution of Ozone
Depleting Substances
+
19.2
51.6
55.8
59.4
62.5
65.6
67.1
0.9%
Mobile Combustion
47.2
56.5
55.2
51.3
48.5
45.0
42.2
38.9
0.5%
Non-Energy Use of Fuels
11.9
11.3
12.1
11.1
10.9
10.1
10.2
10.2
0.1%
Industry
1,470.9
1,478.4
1,443.5
1,395.5
1,380.0
1,372.2
1,403.8
1,347.6
18.6%
C02 from Fossil Fuel
Combustion
810.3
825.4
824.2
819.3
804.8
813.5
824.7
789.2
10.9%
Natural Gas Systems
158.2
161.9
156.0
154.2
154.6
152.1
147.2
139.3
1.9%
Non-Energy Use of Fuels
99.6
115.8
117.9
115.0
115.2
112.7
130.9
123.4
1.7%
Coal Mining
81.9
66.5
55.9
55.5
52.0
52.1
54.5
52.4
0.7%
Iron and Steel Production
86.4
74.8
66.5
59.1
55.7
54.5
52.5
46.4
0.6%
Cement Manufacture
33.3
36.8
41.2
41.4
42.9
43.1
45.6
45.9
0.6%
Petroleum Systems
34.4
31.1
27.8
27.4
26.8
25.8
25.4
28.5
0.4%
HCFC-22 Production
35.0
27.0
29.8
19.8
19.8
12.3
15.6
16.5
0.2%
Ammonia Production and
Urea Application
19.3
20.5
19.6
16.7
17.8
16.2
16.9
16.3
0.2%
Nitric Acid Production
17.8
19.9
19.6
15.9
17.2
16.7
16.0
15.7
0.2%
Lime Manufacture
11.3
12.8
13.3
12.9
12.3
13.0
13.7
13.7
0.2%
Aluminum Production
25.4
17.5
14.7
7.8
9.7
8.3
7.1
7.2
0.1%
Adipic Acid Production
15.2
1 112
6.0
4.9
5.9
6.2
5.7
6.0
0.1%
Substitution of Ozone
Depleting Substances
+
1.2
3.3
3.2
3.9
4.6
5.1
5.5
0.1%
Abandoned Underground
Coal Mines
6.0
8.2
7.3
6.7
6.1
5.9
5.8
5.5
0.1%
Stationary Combustion
5.3
5.6
5.5
5.1
5.0
4.9
5.2
4.6
0.1%
N20 Product Usage
4.3
4.5
4.8
4.8
4.3
4.3
4.3
4.3
0.1%
Semiconductor Manufacture
2.9
5.0
6.3
4.5
4.4
4.3
4.7
4.3
0.1%
2-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Soda Ash Manufacture and
Consumption
4.1
4.3
4.2
4.1
4.1
4.1
4.2
4.2
0.1%
Petrochemical Production
3.1
3.8
4.2
3.9
4.0
3.9
4.1
4.0
0.1%
Limestone and Dolomite
Use
2.8
3.7
3.0
2.9
2.9
2.4
3.4
3.7
0.1%
Magnesium Production and
Processing
5.4
5.6
3.0
2.4
2.4
2.9
2.6
2.7
0.0%
Titanium Dioxide
Production
1.3
1.7
1.9
1.9
2.0
2.0
2.3
1.9
0.0%
Phosphoric Acid Production
1.5
1.5
1.4
1.3
1.3
1.4
1.4
1.4
0.0%
Ferroalloy Production
2.2
2.0
1.9
1.5
1.4
1.3
1.4
1.4
0.0%
Carbon Dioxide
Consumption
1.4
1.4
1.4
0.8
1.0
1.3
1.2
1.3
0.0%
Mobile Combustion
0.9
1.0
1.1
1.2
1.2
1.3
1.3
1.3
0.0%
Zinc Production
0.9
1.0
1.1
1.0
0.9
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
0.0%
Silicon Carbide Production
and Consumption
0.4
0.3
0.3
0.2
0.2
0.2
0.2
0.2
0.0%
Agriculture
585.3
589.2
614.3
618.4
602.6
575.5
566.7
600.7
8.3%
Agricultural Soil
Management
366.9
353.4
376.8
389.0
366.1
350.2
338.8
365.1
5.0%
Enteric Fermentation
115.7
120.6
113.5
112.5
112.6
113.0
110.5
112.1
1.5%
C02 from Fossil Fuel
Combustion
46.8
57.3
50.8
50.7
52.9
44.8
50.9
50.9
0.7%
Manure Management
39.5
44.1
48.3
50.0
50.8
49.8
49.2
50.8
0.7%
Forest Land Remaining
Forest Land
7.85
4.5
15.7
6.9
11.8
9.2
8.0
13.1
0.2%
Rice Cultivation
7.1
7.6
7.5
7.6
6.8
6.9
7.6
6.9
0.1%
Field Burning of
Agricultural Residues
1.1
1.0
1.3
1.2
1.1
1.2
1.4
1.4
0.0%
Mobile Combustion
0.4
0.5
0.4
0.4
0.5
0.4
0.4
0.4
0.0%
Stationary Combustion
+
1 +1I
+
+
+
+
+
+
0.0%
Commercial
417.8
420.5
415.5
406.6
413.7
433.5
432.6
431.4
6%
C02 from Fossil Fuel
Combustion
224.3
226.4
232.3
225.1
225.7
236.6
233.3
225.8
3.1%
Landfills
161.0
157.1
131.9
127.6
130.4
134.9
132.1
132.0
1.8%
Substitution of Ozone
Depleting Substances
+
3.8
16.0
19.1
22.9
27.3
32.3
38.9
0.5%
Wastewater Treatment CH4
24.8
25.1
26.4
25.9
25.8
25.6
25.7
25.4
0.3%
Wastewater Treatment N20
6.4
6.9
7.6
7.6
7.7
7.8
7.9
8.0
0.1%
Stationary Combustion
1.3
1.3
1.3
1.2
1.2
1.3
1.3
1.2
0.0%
Residential
351.3
375.1
393.6
383.6
382.7
404.8
391.6
380.7
5%
C02 from Fossil Fuel
Combustion
340.3
356.4
373.5
363.9
362.4
383.8
369.9
358.7
4.9%
Substitution of Ozone
Depleting Substances
0.3
8.1
10.1
10.4
10.7
11.0
11.5
11.9
0.2%
Settlement Soil Fertilization
5.1
5.5
5.6
5.5
5.6
5.8
6.0
5.8
0.1%
Stationary Combustion
5.5
5.0
4.4
3.9
4.0
4.2
4.3
4.3
0.1%
U.S. Territories
34.1
41.1
47.3
54.5
53.6
60.0
63.2
61.5
0.8%
C02 from Fossil Fuel
Combustion
34.1
41.1
47.3
54.5
53.6
60.0
63.2
61.5
0.8%
Total Emissions
6,242.1
I 6,571.0
7,147.3
7,027.1
7,064.8
7,104.4
7,203.9
7,262.3
100.0%
Sinks
(712.9)
1 (828.5)
(754.7)
(765.5)
(809.9)
(811.6)
(824.9)
(828.4)
-11.4%
Forests
(598.5)
(717.5)
(638.7)
(645.7)
(688.1)
(687.0)
(697.3)
(698.7)
-9.6%
Urban Trees
(57.5)
(67.8)
(78.2)
(80.2)
(82.3)
(84.4)
(86.4)
(88.5)
-1.2%
Trends in Greenhouse Gas Emissions 2-25
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Public Review Draft
C02 Flux from Agricultural
Soils
Landfilled Yard Trimmings
and Food Scraps
(33.9) (30.1)
(23.0) ' (13.0)j
(29.4) (30.9) (30.7) (31.2) (32.4) (32.4)
(8.5) (8.6) (8.9) (9.0) (8.9) (8.8)
5,742.5 6,392.6 6,261.6 6,254.8 6,292.8 6,379.0 6,433.9
-0.4%
-0.1%
88.6%
Net Emissions (Sources and
Sinks) 5,529.11
Note: Includes all emissions of C02, CH4, N20, HFCs, PFCs, and SF6. Parentheses indicate negative values or sequestration.
Totals may not sum due to independent rounding.
ODS (Ozone Depleting Substances)
+ Does not exceed 0.05 Tg C02 Eq. or 0.05%.
a Percent of total emissions for year 2005.
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 2005. Emissions increased by 31 percent since 1990, as electricity demand grew and fossil fuels
remained the dominant energy source for generation. The electricity generation sector in the United States is
composed of traditional electric utilities as well as other entities, such as power marketers and nonutility power
producers. The majority of electricity generated by these entities was through the combustion of coal in boilers to
produce high-pressure steam that is passed through a turbine. Table 2-15 provides a detailed summary of emissions
from electricity generation-related activities.
Table 2-15: Electricity Generation-Related Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Fuel Type or Source
1990
1995
2000
2001
2002
2003
2004
2005
co2
1,823.9
1,958.7
2,304.3 2,266.7 2,
276.2 2,305.8 2,339.2
2,405.8
C02 from Fossil Fuel Combustion
1,810.2
1,939.3
2,283.5 2,245.5 2,
254.7 2,284.0 2,315.8
2,381.2
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
Natural Gas
176.8
229.5
282.0
290.8
307.0
279.3
297.7
320.2
Petroleum
101.8
60.7
91.5
102.0
79.1
98.1
100.1
102.3
Geothermal
0.4
0.3
0.4
0.4
0.4
0.4
0.4
0.4
Municipal Solid Waste Combustion
10.9
15.7
17.9
18.3
18.5
19.5
20.1
20.9
Limestone and Dolomite Use
2.8
3.7
3.0
2.9
2.9
2.4
3.4
3.7
ch4
0.6
0.6
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
n2o
8.0
8.5
9.7
9.5
9.7
9.9
9.9
10.2
Stationary Combustion*
7.6
8.0
9.3
9.1
9.1
9.4
9.4
9.6
Waste Combustion
0.5
0.5
0.4
0.5
0.5
0.5
0.5
0.5
SF6
27.1
21.8
15.2
15.1
14.3
13.8
13.6
13.2
Electrical Transmission and
Distribution
27.1
21.8
15.2
15.1
14.3
13.8
13.6
13.2
Total
1,859.7
1,989.5
2,329.9 2,292.0 2,300.9 2,330.3 2,363.5 2,429.9
Note: Totals may not sum due to independent rounding.
* Includes only stationary combustion emissions related to the generation of electricity.
To distribute electricity emissions among economic end-use sectors, emissions from the source categories assigned
to the electricity generation sector were allocated to the residential, commercial, industry, transportation, and
agriculture economic sectors according to retail sales of electricity (EIA 2006c and Duffield 2006). These three
2-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 source categories include C02 from Fossil Fuel Combustion, CH4 and N20 from Stationary Combustion, and SF6
2 from Electrical Transmission and Distribution Systems.6
3 When emissions from electricity are distributed among these sectors, industry accounts for the largest share of U.S.
4 greenhouse gas emissions (28 percent), followed closely by emissions from transportation activities, which also
5 account for 28 percent of total emissions. Emissions from the residential and commercial sectors also increase
6 substantially when emissions from electricity are included, due to their relatively large share of electricity
7 consumption. In all sectors except agriculture, C02 accounts for more than 80 percent of greenhouse gas emissions,
8 primarily from the combustion of fossil fuels.
9 Table 2-16 presents a detailed breakdown of emissions from each of these economic sectors, with emissions from
10 electricity generation distributed to them. Figure 2-14 shows the trend in these emissions by sector from 1990 to
11 2005.
12
13 Figure 2-14: Emissions with Electricity Distributed to Economic Sectors
14
15 Table 2-16: U.S Greenhouse Gas Emissions by "Economic Sector" and Gas with Electricity-Related Emissions
16 Distributed (Tg C02 Eq.) and Percent of Total in 2005
Sector/Gas
1990
1995
2000
2001
2002
2003
2004
2005
Percent"
Industry
2,111.1
2,141.5
1 2'185-2
2,067.2
2,046.7
2,061.8
2,090.5
2,029.6
27.9%
Direct Emissions
1,470.9
1,478.4
1,443.5
1,395.5
1,380.0
1,372.2
1,403.8
1,347.6
18.6%
C02
1,082.8
1.109.5
1,106.1
1,084.3
1,069.2
1,072.8
1,105.3
1,056.0
14.5%
ch4
284.9
272.5 ,
251.8
248.1
243.8
240.2
237.4
229.8
3.2%
n2o
41.3
45.8
34.6
29.7
31.4
31.2
30.3
29.9
0.4%
HFCs, PFCs, and SF6
61.9
50.6
50.9
33.4
35.6
27.9
30.8
32.0
0.4%
Electricity-Related
640.2 ;
663.1 '
741.7
671.7
666.7
689.6
686.8
682.0
9.4%
C02
627.9
652.8
733.6
664.2
659.5
682.4
679.7
675.2
9.3%
ch4
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.0%
n2o
2.8
2.8
3.1
2.8
2.8
2.9
2.9
2.9
0.0%
sf6
9.3
7.3
4.8
4.4
4.2
4.1
4.0
3.7
0.1%
Transportation
1,526.1
1,680.3
1,906.7
1,879.8
1,934.7
1,932.5
1,987.1
2,015.8
27.8%
Direct Emissions
1,523.0
1,677.2
1,903.2
1,876.4
1,931.2
1,928.2
1,982.6
2,010.5
27.7%
C02
1,475.8
1,601.5
1,796.5
1,769.3
1,823.3
1,820.6
1,874.7
1,904.6
26.2%
ch4
4.5
4.1
3.2
2.9
2.8
2.6
2.5
2.3
0.0%
n2o
42.66
52.45
51.97
48.39
45.75
42.43
39.76
36.56
0.5%
HFCsb
+
19.2
51.59
55.81
59.41
62.54
65.65
67.05
0.9%
Electricity-Related
3.1
3.1
149
3.38
3.46
4.34
4.49
5.26
0.1%
C02
3.1
3.1
3.5
3.3
3.4
4.3
4.4
5.2
0.1%
ch4
+
I +1I
+
+
+
+
+
+
0.0%
n2o
+
I +I1
+
+
+
+
+
+
0.0%
sf6
+
1 +11
+
+
+
+
+
+
0.0%
Commercial
967.2
1,019.8
1,167.4
1,176.9
1,177.1
1,196.2
1,214.1
1,238.5
17.1%
Direct Emissions
417.8
420.5
415.5
406.6
413.7
433.5
432.6
431.4
5.9%
C02
224.3
226.4
232.3
225.1
225.7
236.6
233.3
225.8
3.1%
ch4
186.7
183.1
159.2
154.4
157.1
161.5
158.7
158.3
2.2%
6 Emissions were not distributed to U.S. territories, since the electricity generation sector only includes emissions related to the
generation of electricity in the 50 states and the District of Columbia.
Trends in Greenhouse Gas Emissions 2-27
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Public Review Draft
n2o
6.8
7.2
7.9
7.9
8.0
8.2
8.3
8.4
0.1%
HFCs
3.8
16.0
19.1
22.9
27.3
32.3
38.9
0.5%
Electricity-Related
549.5
599.3
751.9
770.2
763.4
762.8
781.6
807.2
11.1%
C02
538.9
590.0
743.7
761.7
755.2
754.8
773.5
799.2
11.0%
ch4
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.0%
n2o
2.4
2.6
3.1
3.2
3.2
3.2
3.3
3.4
0.0%
sf6
8.0
6.6
4.9
5.1
4.8
4.5
4.5
4.4
0.1%
Residential
956.9
1,030.6
1,167.0
1,160.3
1,184.3
1,216.3
1,214.2
1,248.0
17.2%
Direct Emissions
351.3
375.1
393.6
383.6
382.7
404.8
391.6
380.7
5.2%
C02
340.3
356.4
373.5
363.9
362.4
383.8
369.9
358.7
4.9%
ch4
4.4
4.0
3.5
3.1
3.1
3.3
3.3
3.4
0.0%
n2o
6.2
6.5
6.5
6.3
6.5
6.7
6.9
6.7
0.1%
HFCs
0.3
8.1
10.1
10.4
10.7
11.0
11.5
11.9
0.2%
Electricity-Related
605.7
655.5
773.4
776.7
801.6
811.4
822.6
867.3
11.9%
C02
594.0
645.4
764.9
768.1
793.0
802.9
814.2
858.7
11.8%
ch4
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.3
0.0%
n2o
2.6
2.8
3.2
3.2
3.4
3.4
3.5
3.6
0.0%
sf6
8.8
7.2
5.0
5.1
5.0
4.8
4.7
4.7
0.1%
Agriculture
646.5
657.6
673.7
688.5
668.4
637.6
634.8
668.9
9.2%
Direct Emissions
585.3 ''
589.2
614.3
618.4
602.6
575.5
566.7
600.7
8.3%
C02
46.8
57.3
50.8
50.7
52.9
44.8
50.9
50.9
0.7%
ch4
161.6
168.2
174.6
167.2
171.8
169.3
165.8
172.9
2.4%
n2o
377.0
364.0
388.9
400.5
377.9
361.4
350.1
377.0
5.2%
Electricity-Related
61.2
68.5
59.4
70.1
65.8
62.1
68.0
68.2
0.9%
C02
60.0
67.4
58.8
69.3
65.1
61.5
67.4
67.5
0.9%
ch4
1 +11
+
+
+
+
+
+
0.0%
n2o
0.3
0.3
0.2
0.3
0.3
0.3
0.3
0.3
0.0%
sf6
0.9
0.8
0.4
0.5
0.4
0.4
0.4
0.4
0.0%
U.S. Territories
34.1
41.1
47.3
54.5
53.6
60.0
63.2
61.5
0.8%
Total
6,242.1
6,571.0
7,147.3
7,027.1
7,064.8
7,104.4
7,203.9
7,262.3
100.0%
Note: Emissions from electricity generation are allocated based on aggregate electricity consumption in each end-use sector.
Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg C02 Eq. or 0.05%.
a Percent of total emissions for year 2005.
b Includes primarily HFC-134a.
Transportation
Transportation activities accounted for 28 percent of U.S. greenhouse gas emissions in 2005. Table 2-17 provides a
detailed summary of greenhouse gas emissions from transportation-related activities. Total emissions in Table 2-17
differ slightly from those shown in Table 2-16 primarily because the table below excludes a few minor non-
transportation mobile sources, such as construction and industrial equipment.
From 1990 to 2005, transportation emissions rose by 32 percent due, in part, to increased demand for travel and the
stagnation of fuel efficiency across the U.S. vehicle fleet. Since the 1970s, the number of highway vehicles
registered in the United States has increased faster than the overall population, according to the Federal Highway
Administration (FHWA). Likewise, the number of miles driven (up 21 percent from 1990 to 2005) and the gallons
of gasoline consumed each year in the United States have increased steadily since the 1980s, according to the
FHWA and Energy Information Administration, respectively. These increases in motor vehicle usage are the result
of a confluence of factors including population growth, economic growth, urban sprawl, low fuel prices, and
increasing popularity of sport utility vehicles and other light-duty trucks that tend to have lower fuel efficiency. A
similar set of social and economic trends has led to a significant increase in air travel and freight transportation by
both air and road modes during the time series.
Almost all of the energy consumed for transportation was supplied by petroleum-based products, with nearly two-
2-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 thirds being related to gasoline consumption in automobiles and other highway vehicles. Other fuel uses, especially
2 diesel fuel for freight trucks and jet fuel for aircraft, accounted for the remainder. The primary driver of
3 transportation-related emissions was C02 from fossil fuel combustion, which increased by 29 percent from 1990 to
4 2005. This rise in C02 emissions, combined with an increase of 67.1 Tg C02 Eq. in HFC emissions over the same
5 period, led to an increase in overall emissions from transportation activities of 32 percent.
6 Table 2-17: Transportation-Related Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Vchicic Type
1990
1995
2000
2001
2002
2003
2004
2005
co2
1,478.8
1,604.(.
1,799.9
1,772.6
1,826.7
1,824.9
1,879.1
1,909.7
Passenger Cars
615.1
599.(>
632.0
634.7
649.6
629.1
628.7
614.9
Light-Duty Trucks
314.0
401.6
459.2
462.7
476.6
510.7
533.6
550.3
Other Trucks
227.0
270.9
343.2
343.3
358.1
355.4
368.5
384.6
Buses
8.3
9.0
11.0
10.1
9.7
10.6
14.9
15.1
Aircraft3
180.0
174.6
196.4
186.6
178.0
174.7
179.7
187.3
Ships and Boats
46.8
55.4
63.8
43.0
60.6
53.3
61.1
64.2
Locomotives
38.1
42.2
45.1
45.1
44.9
46.6
49.2
50.3
Otherb
49.6
51.3
49.1
47.2
49.2
44.4
43.5
43.1
International Bunker
Fuelsc
113.7
100.6
101.1
97.6
89.1
83.7
97.2
95.6
ch4
4.5
4.1
3.2
2.9
2.8
2.6
2.5
2.3
Passenger Cars
2.6
2.1
1.6
1.5
1.4
1.3
1.2
1.1
Light-Duty Trucks
1.4
1.4
1.1
1.0
1.0
0.9
0.8
0.8
Other Trucks and Buses
0.2
0.2
0.1
0.1
0.1
0.1
0.1
0.1
Aircraft
0.2
0.1
0.2
0.1
0.1
0.1
0.1
0.1
Ships and Boats
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
Locomotives
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
Motorcycles
+
+
+
+
+
+
+
+
International Bunker
Fuelsc
0.2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
n2o
42.7
52.5
52.0
48.4
45.8
42.4
39.7
36.5
Passenger Cars
25.4
26.9
24.7
23.2
21.9
20.3
18.8
17.0
Light-Duty Trucks
14.1
22.1
23.3
21.4
20.1
18.3
17.0
15.6
Other Trucks and Buses
0.8
1.0
1.2
1.3
1.3
1.3
1.3
1.2
Aircraft
1.7
1.7
1.9
1.8
1.7
1.7
1.7
1.8
Ships and Boats
0.4
0.4
0.5
0.3
0.5
0.4
0.5
0.5
Locomotives
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.4
Motorcycles
+
+
+
+
+
+
+
+
International Bunker
Fuelsc
1.0
0.9
0.9
0.9
0.8
0.8
0.9
0.9
HFCs
+
19.2
51.6
55.8
59.4
62.5
65.6
67.1
Mobile Air Conditioners'1
+
16.8
41.6
44.9
47.7
50.0
52.2
53.1
Comfort Cooling in Buses
and Trains
+
+
0.2
0.2
0.2
0.2
0.3
0.3
Refrigerated Transport
+
2.3
9.8
10.8
11.5
12.3
13.1
13.6
Total
1,526.1
1,680.4
1,906.7
1,879.7
1,934.6
1,932.4
1,986.9
2,015.6
7 + Does not exceed 0.05 Tg C02 Eq.
8 Note: Totals may not sum due to independent rounding.
9 a Aircraft emissions consist of emissions from all jet fuel (less bunker fuels) and aviation gas consumption.
10 b "Other" C02 emissions include motorcycles, pipelines, and lubricants.
11 c Emissions from International Bunker Fuels include emissions from both civilian and military activities, but are not included in
12 totals.
13 d Includes primarily HFC-134a.
14
15 [BEGIN BOX]
Trends in Greenhouse Gas Emissions 2-29
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
Box 2-2: Methodology for Aggregating Emissions by Economic Sector
In order to aggregate emissions by economic sector, source category emission estimates were generated according
to the methodologies outlined in the appropriate sections of this report. Those emissions were then simply
reallocated into economic sectors. In most cases, the IPCC subcategories distinctly fit into an apparent economic
sector category. Several exceptions exist, and the methodologies used to disaggregate these subcategories are
described below:
• Agricultural C02 Emissions from Fossil Fuel Combustion, and Non-CO 2 Emissions from Stationary and
Mobile Combustion. Emissions from on-farm energy use were accounted for in the Energy chapter as part of
the industrial and transportation end-use sectors. To calculate agricultural emissions related to fossil fuel
combustion, energy consumption estimates were obtained from economic survey data from the U.S.
Department of Agriculture (Duffield 2006) and fuel sales data (EIA 1991 through 2005). To avoid double-
counting, emission estimates of C02 from fossil fuel combustion and non-C02 from stationary and mobile
combustion were subtracted from the industrial economic sector, although some of these fuels may have been
originally accounted for under the transportation end-use sector.
• Landfills and Wastewater Treatment. CH4 emissions from landfills and CH4 and N20 emissions from
wastewater treatment were allocated to the commercial sector.
• Waste Combustion. C02 and N20 emissions from waste combustion were allocated completely to the
electricity generation sector since nearly all waste combustion occurs in waste-to-energy facilities.
• Limestone and Dolomite Use. C02 emissions from limestone and dolomite use are allocated to the electricity
generation (50 percent) and industrial (50 percent) sectors, because 50 percent of the total emissions for this
source are due to flue gas desulfurization.
• Substitution of Ozone Depleting Substances. All greenhouse gas emissions resulting from the substitution of
ozone depleting substances were placed in the industrial economic sector, with the exception of emissions from
domestic, commercial, and mobile and transport refrigeration/air-conditioning systems, which were placed in
the residential, commercial, and transportation sectors, respectively. Emissions from non-MDI aerosols were
attributed to the residential economic sector.
• Settlement Soil Fertilization, Forest Soil Fertilization. Emissions from settlement soil fertilization were
allocated to the residential economic sector; forest soil fertilization was allocated to the agriculture economic
sector.
• Forest Fires. N20 and CH4 emissions from forest fires were allocated to the agriculture economic sector.
[END BOX]
2-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Public Review Draft
2.3. Indirect Greenhouse Gas Emissions (CO, NOx, NMVOCs, and SO2)
The reporting requirements of the UNFCCC7 request that information be provided on indirect greenhouse gases,
which include CO, NOx, NMVOCs, and S02. These gases do not have a direct global warming effect, but indirectly
affect terrestrial radiation absorption by influencing the formation and destruction of tropospheric and stratospheric
ozone, or, in the case of S02, by affecting the absorptive characteristics of the atmosphere. Additionally, some of
these gases may react with other chemical compounds in the 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 N02) are created by lightning, fires, fossil fuel combustion, and in the stratosphere from nitrous oxide
(N20). Non-CH4 volatile organic compounds—w hich include hundreds of organic compounds that participate in
atmospheric chemical reactions (i.e., propane, butane, xylene, toluene, ethane, and many others)—arc emitted
primarily from transportation, industrial processes, and non-industrial consumption of organic solvents. In the
United States, S02 is primarily emitted from coal combustion for electric power generation and the metals industry.
Sulfur-containing compounds emitted into the atmosphere tend to exert a negative radiative forcing (i.e., cooling)
and therefore are discussed separately.
One important indirect climate change effect of NMVOCs and NOx is their role as precursors for tropospheric
ozone formation. They can also alter the atmospheric lifetimes of other greenhouse gases. Another example of
indirect greenhouse gas formation into greenhouse gases is CO's interaction with the hydroxyl radical—the major
atmospheric sink for CH4 emissions—to form C02. Therefore, increased atmospheric concentrations of CO limit
the number of hydroxyl molecules (OH) available to destroy CH4.
Since 1970, the United States has published estimates of annual emissions of CO, NOx, NMVOCs, and S02 (EPA
2005),8 which are regulated under the Clean Air Act. Table 2-18 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—arc also significant sources of CO,
NOx> and NMVOCs.
Table 2-18: Emissions of NOx, CO, NMVOCs, and S02 (Gg)
Gas/Activity
19901
19951
NOx 21'6451
Mobile Fossil Fuel Combustion 10,9201
Stationary Fossil Fuel Combustion 9,8831
Industrial Processes 5911
Oil and Gas Activities 1391
Waste Combustion 82|
Agricultural Burning 281
Solvent Use I
Waste u
CO 130'581[
Mobile Fossil Fuel Combustion 119,480J
Stationary Fossil Fuel Combustion 5,000|
Industrial Processes 4,1251
Waste Combustion 9781
Agricultural Burning 6911
Oil and Gas Activities 302|
Waste I
21,272
io,6::
9,821
607
100
88
2*¦>
31
1
109,157
97,755
5,3831
3,95^
1'073I
663|
31<>
:
2000
2001
2002
2003
2004
2005
19,203
18,410
18,141
17,327
16,466
15,965
10,310
9,819
10,319
9,911
9,520
9,145
8,002
7,667
6,837
6,428
5,952
5,824
626
656
532
533
534
535
111
113
316
317
317
318
114
114
97
98
98
98
35
35
33
34
39
39
3
3
5
5
5
5
2
2
2
2
2
2
92,897
89,333
86,796
84,370
82,073
79,811
83,680
79,972
77,382
74,756
72,269
69,915
4,340
4,377
5,224
5,292
5,361
5,431
2,217
2,339
1,710
1,730
1,751
1,772
1,670
1,672
1,440
1,457
1,475
1,493
792
774
709
800
879
858
146
147
323
327
331
335
8
8
7
7
7
7
7 See .
8 NOx and CO emission estimates from field burning of agricultural residues were estimated separately, and therefore not taken
from EPA (2005).
Trends in Greenhouse Gas Emissions 2-31
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Public Review Draft
Solvent Use * 51
NMVOCs 20,930 19>5201
Mobile Fossil Fuel Combustion 10,932 8,7451
Solvent Use 5.21 (» 5,6091
Industrial Processes 2,422 2,6421
Stationary Fossil Fuel Combustion 912 9731
Oil and Gas Activities 554 5821
Waste Combustion 222 2371
Waste 67 7311
Agricultural Burning N NAl
S02 20,935 16'8911
Stationary Fossil Fuel Combustion 18,407 14,7241
Industrial Processes 1,307 1,1171
Mobile Fossil Fuel Combustion 79 672|
Oil and Gas Activities 390 3351
Waste Combustion 31- 421
Solvent Use n 11
Agricultural Burning NA NA|
Source: (EPA 2005) except for estimates from field burning of agricultural residues.
NA (Not Available)
Note: Totals may not sum due to independent rounding.
46
15,228
7,230
4,384
1,773
1,077
389
257
119
NA
14,829
12,848
1,031
632
286
29
1
1
NA
45
15,048
6,872
4,547
1,769
1,080
400
258
122
NA
14,452
12,461
1,047
624
289
30
1
1
NA
1
14,968
6,608
3,911
1,811
1,733
546
244
116
NA
13,541
11,852
752
681
233
23
1
0
NA
1
14,672
6,302
3,916
1,813
1,734
547
244
116
NA
13,648
12,002
759
628
235
23
1
0
NA
1
14,391
6,011
3,921
1,815
1,735
547
244
116
NA
13,328
11,721
766
579
238
23
1
0
NA
1
14,123
5,734
3,926
1,818
1,736
548
245
116
NA
13,271
11,698
774
535
240
23
1
0
NA
[BEGIN BOX]
Box 2-3: Sources and Effects of Sulfur Dioxide
Sulfur dioxide (S02) emitted into the atmosphere through natural and anthropogenic processes affects the earth's
radiative budget through its photochemical transformation into sulfate aerosols that can (1) scatter radiation from
the sun back to space, thereby reducing the radiation reaching the earth's surface; (2) affect cloud formation; and (3)
affect atmospheric chemical composition (e.g., by providing surfaces for heterogeneous chemical reactions). The
indirect effect of sulfur-derived aerosols on radiative forcing can be considered in two parts. The first indirect
effect is the aerosols' tendency to decrease water droplet size and increase water droplet concentration in the
atmosphere. The second indirect effect is the tendency of the reduction in cloud droplet size to affect precipitation
by increasing cloud lifetime and thickness. Although still highly uncertain, the radiative forcing estimates from
both the first and the second indirect effect are believed to be negative, as is the combined radiative forcing of the
two (IPCC 2001). However, because S02 is short-lived and unevenly distributed in the atmosphere, its radiative
forcing impacts are highly uncertain.
Sulfur dioxide is also a major contributor to the formation of regional haze, which can cause significant increases in
acute and chronic respiratory diseases. Once S02 is emitted, it is chemically transformed in the atmosphere and returns
to the earth as the primary source of acid rain. Because of these harmful effects, the United States has regulated S02
emissions in the Clean Air Act.
Electricity generation is the largest anthropogenic source of S02 emissions in the United States, accounting for 88
percent in 2005. Coal combustion contributes nearly all of those emissions (approximately 92 percent). Sulfur
dioxide emissions have decreased in recent years, primarily as a result of electric power generators switching from
high-sulfur to low-sulfur coal and installing flue gas desulfurization equipment.
[END BOX]
2-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
8,000 -I
7,000 -
6,000
o- 5,000
LU
O 4,000
P 3,000
2,000 -
1,000 -
0 -
I HFCs, PFCs, & SF6
Nitrous Oxide
i Methane
I Carbon Dioxide
6.242 6.186 6.286
6444 6.519 6.571
6.831 6,856 6,920 6,931 7<147 7,027 7'065 7,104
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Figure 2-1: U.S. Greenhouse Gas Emissions by Gas
4.0%
3.1%
-0.9%
-1.7%
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Figure 2-2: Annual Percent Change in U.S. Greenhouse Gas Emissions
1,020
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Figure 2-3: Cumulative Change in U.S. Greenhouse Gas Emissions Relative to 1990
-------
1,000 -
Industrial Processes
Waste
LULUCF (non-C02)
Land Use, Land-Use Change and Forestry (net C02 flux)
(2,000) J
Note: Relatively smaller amounts of GWP-weighted emissions are also emitted from the Solvent and Other
Product Use sector
Figure 2-5: U.S. Greenhouse Gas Emissions and Sinks by Chapter/IPCC Sector
-------
Petroleum
841
Fossil Fuel
Energv Exports
281
Stock
Changes
<1
Non-Energy
Use Exports
91
Coal
2,168
Natural Gas
1,007
t
Domestic
Fossil Fuel
Production
4,161
Apparent
Consumption
6,345
-Natural Gas Liquids,
Liquefied Refinery Gas,
& Other Liquids
145 _
Petroleum
1,904 „
NG 233 -
Coal 81 *
Fossil Fuel
Energy
Imports
2,430
7
Non-Energy Consumption
Use Imports U.S.
03 Territories
53
Fossil Fuel Non-Energy
Use U.S.
Territories
10
Balancing
item
International
Bunkers
98
industrial
Processes
NEU Emissions
. 14
Coal Emissions
2,108
Combustion
Emissions
2,094
Natural Gas Emissions
r 1,178
Atmospheric
Emissions
6,082
Combustion
Emissions 1,170-
Combustion
Emissions
2,489
NEU Emissions 121
Petroleum
• Emissions
2,610
Non-Energy Use
Carbon Sequestered
243
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
-------
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Sources
Petroleum Systems
Stationary Sources ¦
Waste Combustion I
Abandoned Coal Mines |
15,752.8
25
Energy as a Portion
of all Emissions
50 75 100
Tg C02 Eq.
125 150
Figure 2-6: 2005 Energy Sector Greenhouse Gas Sources
2,000
S i'500
o
u 1,000
F
500
0
Relative Contribution
by Fuel Type
>
Natural Gas
Petroleum
¦ Coal
o .u
£ ra ui 5
Figure 2-8: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Note: Electricity generation also includes emissions of less than 1 Tg C02 Eq. from geothermal-based electricity generatic
-------
2,000
1,800 -
1,600
o- 1,400
"i i/200 -
8 1,000
cn 800 -
H 600
400
200 -
0
From Electricity
i/i £
=> F
Figure 2-9: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion
Substitution of Ozone Depleting Substances
Iron and Steel Production
Cement Manufacture
HCFC-22 Production
Ammonia Production and Urea Application
Nitric Acid
Lime Manufacture
Electrical Transmission and Distribution
Limestone and Dolomite Use ^
Aluminum Production |
Adipic Acid |
Semiconductor Manufacture |
Soda Ash Manufacture and Consumption |
Petrochemical Production |
Magnesium Production and Processing |
Titanium Dioxide Production |
Ferroalloy Production |
Phosphoric Acid Production |
Carbon Dioxide Consumption |
Zinc Production <0.5
Lead Production <0.5
Silicon Carbide Production and Consumption <0-5
Industrial Processes
as a Portion of all Emissions
4.6%
25
50 75
Tg C02 Eq.
100
125
Figure 2-10: 2005 Industrial Processes Chapter
Greenhouse Gas Sources
-------
Agricultural Soil
Management
Enteric Fermentation
Manure Management
Rice Cultivation
Field Burning of
Agricultural Residues
50
100
Agriculture as a Portion of all
Emissions
7.4%
©
150 200
Tg C02 Eq
250
300
Figure 2-11: 2005 Agriculture Chapter GHG Sources
Figure 2-12: 2005 Waste Chapter Greenhouse Gas Sources
-------
3,000
2,500
"J 2,000
hi
0 1,500
O)
t 1,000
500
Electricity Generation
Transportation
Industry
Agriculture
Commercial
Residential
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Year
Figure 2-13: Emissions Allocated to Economic Sectors
2,500 -I
2,000 -
iff 1,500 -
o
o
o> 1,000
500
Industrial
Transportation
Residential
Commercial
Agriculture
Figure 2-14: Emissions with Electricity Distributed to Economic Sectors
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
3. Energy
Energy-related activities were the primary sources of U.S. anthropogenic greenhouse gas emissions, accounting for
85 percent of total emissions on a carbon (C) equivalent basis in 2005. This included 98, 38, and 11 percent of the
nation's carbon dioxide (C02), methane (CH4), and nitrous oxide (N20) emissions, respectively. Energy-related
C02 emissions alone constituted 82 percent of national emissions from all sources on a C equivalent basis, while the
non-C02 emissions from energy-related activities represented a much smaller portion of total national emissions (4
percent collectively).
Emissions from fossil fuel combustion comprise the vast majority of energy-related emissions, with C02 being the
primary gas emitted (see Figure 3-1). Globally, approximately 27,044 Tg of C02 were added to the atmosphere
through the combustion of fossil fuels in 2004, of which the United States accounted for about 22 percent.1 Due to
the relative importance of fossil fuel combustion-related C02 emissions, they are considered separately, and in more
detail than other energy-related emissions (see Figure 3-2). Fossil fuel combustion also emits CH4 and N20, as well
as indirect greenhouse gases such as nitrogen oxides (NOx), carbon monoxide (CO), and non-CH4 volatile organic
compounds (NMVOCs). Mobile fossil fuel combustion was the second largest source of N20 emissions in the
United States, and overall energy-related activities were collectively the largest source of these indirect greenhouse
gas emissions.
Figure 3-1: 2005 Energy Chapter Greenhouse Gas Sources
Figure 3-2: 2005 U.S. Fossil Carbon Flows (Tg C02 Eq.)
Energy-related activities other than fuel combustion, such as the production, transmission, storage, and distribution
of fossil fuels, also emit greenhouse gases. These emissions consist primarily of fugitive CH4 from natural gas
systems, petroleum systems, and coal mining. Smaller quantities of C02, CO, NMVOCs, and NOx are also emitted.
The combustion of biomass and biomass-based fuels also emits greenhouse gases. C02 emissions from these
activities, however, are not included in national emissions totals because biomass fuels are of biogenic origin. It is
assumed that the C released during the consumption of biomass is recycled as U.S. forests and crops regenerate,
causing no net addition of C02 to the atmosphere. The net impacts of land-use and forestry activities on the C cycle
are accounted for within the Land Use, Land-Use Change, and Forestry chapter. Emissions of other greenhouse
gases from the combustion of biomass and biomass-based fuels are included in national totals under stationary and
mobile combustion.
Table 3-1 summarizes emissions from the Energy sector in units of teragrams of C02 equivalents (Tg C02 Eq.),
while unweighted gas emissions in gigagrams (Gg) are provided in Table 3-2. Overall, emissions due to energy-
related activities were 6,203.6 Tg C02 Eq. in 2005, an increase of 19 percent since 1990.
Table 3-1: C02, CH4, and N2Q Emissions from Energy (Tg C02 Eq.)
Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005
C02 4,886.1 5,212.7 5,773.1 5,690.2 5,740.7 5,803.7 5,911.5 5,944.2
Fossil Fuel Combustion 4,724.1 5,030.0 5,584.9 5,511.7 5,557.2 5,624.5 5,713.0 5,752.8
Non-Energy Use of Fuels 117.2 133.1 141.0 131.3 135.3 131.3 150.2 142.3
1 Global C02 emissions from fossil fuel combustion were taken from Energy Information Administration International Energy
Annual 2004 EIA (2006).
Energy 3-1
-------
Public Review Draft
Natural Gas Systems
Municipal Solid Waste 10.91
Combustion
International Bunker Fuels* 113.7
Wood Biomass and Ethanol 219.31
Consumption *
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Source Combustion
Abandoned Underground Coal
Mines
Mobile Source Combustion
International Bunker Fuels*
n2o
Mobile Source Combustion
Stationary Source Combustion
Municipal Solid Waste
Combustion
International Bunker Fuels* 1.0 .
33.£
15.71
100.6
236. J
29.4
17.9
101.1
228.3
28.8
18.3
97.6
203.2
29.6
18.5
89.1
204.4
28.4
19.5
83.7
209.6
28.2
20.1
97.2
224.8
28.2
20.9
95.6
206.5
259.6
246.1
228.5
225.0
219.7
217.4
214.6
207.1
124.5
128.1
126.6
125.4
125.0
123.7
119.0
111.1
81.9
66.5
55.9
55.5
52.0
52.1
54.5
52.4
34.4
3L1
27.8
27.4
26.8
25.8
25.4
28.5
8.0
7.8
7.4
6.8
6.8
7.0
7.1
6.9
6.0
8.2
7.3
6.7
6.1
5.9
5.8
5.5
4.7
4.3||
3.5
3.2
3.1
2.9
2.8
2.6
0..
OA 111
0.1
0.1
0.1
0.1
0.1
0.1
56.5
66'91II1
67.6
63.7
61.1
58.0
55.7
52.3
43.7
53.7||
53.2
49.7
47.1
43.8
41.2
38.0
12.3
12-81I1
14.0
13.5
13.4
13.7
13.9
13.8
0.5
O.5IIII
0.4
0.5
0.5
0.5
0.5
0.5
0.91
0.9
0.9
0.8
0.8
0.9
0.9
Total
5,202.1 5,525.7|
* These values are presented for informational purposes only and
Note: Totals may not sum due to independent rounding.
6,069.2 5,978.9 6,021.5 6,079.2 6,181.8 6,203.6
are not included or are already accounted for in totals.
Table 3-2: C02, CH4, and N2Q Emissions from Energy (Gg)
Gas/Source
19901
1995
co2
Fossil Fuel Combustion
Non-Energy Use of
Fuels
Natural Gas Systems
Municipal Solid Waste
Combustion
International Bunker
Fuels*
Wood Biomass and
Ethanol Consumption *
CH4
Natural Gas Systems
Coal Mining
Petroleum Systems
Stationary Combustion
Abandoned
Underground Coal
4,886,053111 5,212,689
4,724,149® 5,030,036
117,2:^
33,729
10,950
113,683
219,3-
12,360
5,927
3,899
1,640
382
133,134
33,807
15,712
100,627
236,775
11,718
6,101
3,165
1,482
373
Municipal Solid Waste
Combustion
2000
2001
2002
2003
2004
2005
5,773,129 5,690,198 5,740,679 5,803,739 5,911,497 5,944,218
5,584,880 5,511,719 5,557,242 5,624,500 5,713,018 5,752,787
140,970
29,390
17,889
101,125
228,308
10,879
6,027
2,662
1,325
351
131,342
28,793
18,344
97,563
203,163
10,714
5,971
2,644
1,303
324
135,294
29,630
18,513
89,101
204,351
10,463
5,951
2,476
1,275
324
131,303
28,445
19,490
83,690
209,603
10,352
5,891
2,480
1,229
334
150,175 142,335
28,190 28,185
20,115
97,177
224,825
10,221
5,669
2,597
1,209
340
20,912
95,605
206,475
9,862
5,292
2,494
1,357
330
Mines
286
391
349
318
292
282
275
263
Mobile Combustion
226
207
165
154
146
136
131
125
International Bunker
Fuels*
S11
6
6
5
4
4
5
5
n2o
182
216
218
205
197
187
180
169
Mobile Combustion
141
173
172
160
152
141
133
123
Stationary Combustion
40
41
45
44
43
44
45
45
3-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Public Review Draft
International Bunker
Fuels* 3 3 3 2
* These values are presented for informational purposes only and are not included or are already accounted for in totals.
Note: Totals may not sum due to independent rounding.
3.1. Carbon Dioxide Emissions from Fossil Fuel Combustion (IPCC Source
Category 1A)
C02 emissions from fossil fuel combustion in 2005 increased by 0.7 percent from the previous year. This small
increase is primarily a result of the restraint on fuel consumption caused by rising fuel prices, primarily in the
transportation sector. Additionally, warmer winter conditions in 2005 decreased the demand for heating fuels. In
contrast, warmer summer conditions in 2005 increased the demand for electricity. In 2005, C02 emissions from
fossil fuel combustion were 5,752.8 Tg C02 Eq., or 22 percent above emissions in 1990 (see Table 3-3).2
Table 3-3: C02 Emissions from Fossil Fuel Combustion by Fuel Type and Sector (Tg C02 Eq.)
Fuel/Sector
1990
I 1995
2000
2001
2002
2003
2004
2005
Coal
1,699.0
1,805.5
1 2'053-9
1,997.2
2,003.3
2,043.3
2,058.6
2,093.6
Residential
3.0
1.7
1.1
1.1
1.2
1.2
1.3
1.0
Commercial
11.8
n.i
00
00
9.2
8.6
7.8
9.6
8.0
Industrial
152.3
I 143.0
133.5
133.5
123.4
124.0
126.2
122.2
Transportation
NE
NE
NE
NE
NE
NE
NE
NE
Electricity Generation
1,531.3
1 1,648.7
1,909.6
1,852.3
1,868.3
1,906.2
1,917.6
1,958.4
U.S. Territories
0.6
I 0.9
0.9
1.0
1.9
4.1
3.9
4.0
Natural Gas
1,011.4
I 1,169.6
1,227.6
1,178.7
1,219.6
1,187.9
1,190.4
1,170.0
Residential
240.0
| 264.3
272.0
260.5
266.9
278.4
266.2
262.8
Commercial
143.3
| 165.2
173.2
165.0
171.7
174.3
171.2
167.0
Industrial
415.3
I 472.2
464.0
426.2
435.6
421.2
421.8
387.0
Transportation
36.1
1 38.4
35.7
34.9
37.2
33.4
32.3
31.8
Electricity Generation
176.8
j 229.5
282.0
290.8
307.0
279.3
297.7
320.1
U.S. Territories
NO
1 NO
0.7
1.2
1.2
1.4
1.3
1.3
Petroleum
2,013.3
| 2,054.6
1 2'303-0
2,335.5
2,333.9
2,392.9
2,463.6
2,488.8
Residential
97.4
1 90.5
100.5
102.2
94.4
104.2
102.5
95.0
Commercial
69.2
1 50.1
50.3
50.9
45.5
54.5
52.5
50.9
Industrial
289.5
| 267.5
277.4
310.2
298.7
313.2
327.6
330.9
Transportation
1,427.9
| 1,551.8
1,748.7
1,723.3
1,775.1
1,777.1
1,832.2
1,862.5
Electricity Generation
101.8
60.7
91.5
102.0
79.1
98.1
100.1
102.3
U.S. Territories
27.6
34.0
34.6
46.8
41.1
45.8
48.7
47.2
Geothermal*
0.40
1 0.34
0.36
0.35
0.37
0.37
0.37
0.37
Total
4,724.1
| 5,030.0
5,584.9
5,511.7
5,557.2
5,624.5
5,713.0
5,752.8
NE (Not estimated)
NO (Not occurring)
* Although not technically a fossil fuel, geothermal energy-related C02 emissions are included for reporting purposes.
Note: Totals may not sum due to independent rounding.
Trends in C02 emissions from fossil fuel combustion are influenced by many long-term and short-term factors. On
a year-to-year basis, the overall demand for fossil fuels in the United States and other countries generally fluctuates
in response to changes in general economic conditions, energy prices, weather, and the availability of non-fossil
alternatives. For example, in a year with increased consumption of goods and services, low fuel prices, severe
2 An additional discussion of fossil fuel emission trends is presented in the Trends in U.S. Greenhouse Gas Emissions Chapter.
Energy 3-3
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
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).
C02 emissions also depend on the source of energy and its C intensity. The amount of C in fuels varies
significantly by fuel type. For example, coal contains the highest amount of C per unit of useful energy. Petroleum
has roughly 75 percent of the C per unit of energy as coal, and natural gas has only about 55 percent.3 Producing a
unit of heat or electricity using natural gas instead of coal can reduce the C02 emissions associated with energy
consumption, and using nuclear or renewable energy sources (e.g., wind) can essentially eliminate emissions (see
Box 3-2). Table 3-4 shows annual changes in emissions during the last five years for coal, petroleum, and natural
gas in selected sectors.
Table 3-4: Annual Change in C02 Emissions from Fossil Fuel Combustion for Selected Fuels and Sectors (Tg C02
Eq. and Percent)
Sector
Fuel Type
2001 to 2002
2002 to 2003
2003 to 2004
2004 to 2005
Electricity Generation
Coal
16.0
1%
38.0
2%
11.4
1%
40.8
2%
Electricity Generation
Natural Gas
16.1
6%
-27.7
-9%
18.4
7%
22.4
8%
Electricity Generation
Petroleum
-22.9
-22%
19.0
24%
2.0
2%
2.2
2%
Transportation3
Petroleum
51.8
3%
2.0
0%
55.1
3%
30.4
2%
Residential
Natural Gas
6.4
2%
11.5
4%
-12.2
-4%
-3.4
-1%
Commercial
Natural Gas
6.6
4%
2.6
2%
-3.1
-2%
-4.2
-2%
Industrial
Coal
-10.1
-8%
0.6
0%
2.3
2%
-4.0
-3%
Industrial
Natural Gas
9.4
2%
-14.5
-3%
0.6
0%
-34.8
-8%
All Sectorsb
All Fuelsb
45.5
1%
67.3
1%
88.5
2%
39.8
1%
a Excludes emissions from International Bunker Fuels.
b Includes fuels and sectors not shown in table.
In the United States, 86 percent of the energy consumed in 2005 was produced through the combustion of fossil
fuels such as coal, natural gas, and petroleum (see Figure 3-3 and Figure 3-4). The remaining portion was supplied
by nuclear electric power (8 percent) and by a variety of renewable energy sources (6 percent), primarily
hydroelectric power and biofuels (EIA 2006a). Specifically, petroleum supplied the largest share of domestic
energy demands, accounting for an average of 44 percent of total fossil fuel based energy consumption in 2005.
Natural gas and coal 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 2006a).
Figure 3-3: 2005 U.S. Energy Consumption by Energy Source
Figure 3-4: U.S. Energy Consumption (QuadrillionBtu)
3 Based on national aggregate carbon content of all coal, natural gas, and petroleum fuels combusted in the United States.
3-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1
2 Figure 3-5: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
3
4 Fossil fuels are generally combusted for the purpose of producing energy for useful heat and work. During the
5 combustion process, the C stored in the fuels is oxidized and emitted as C02 and smaller amounts of other gases,
6 including CH4, CO, and NMVOCs.4 These other C containing non-C02 gases are emitted as a by-product of
7 incomplete fuel combustion, but are, for the most part, eventually oxidized to C02 in the atmosphere. Therefore, it
8 is assumed that all the C in fossil fuels used to produce energy is eventually converted to atmospheric C02.
9
10 [BEGIN BOX]
11 Box 3-1: Weather and Non-Fossil Energy Effects on C02 from Fossil Fuel Combustion Trends
12
13 In 2005, weather conditions became warmer in both the winter and summer. The winter was slightly milder than
14 usual, with heating degree days in the United States 5 percent below normal (see Figure 3-6). Warmer winter
15 conditions led to a decrease in demand for heating fuels. Summer temperatures were substantially warmer than
16 usual, with cooling degree days 15 percent above normal (see Figure 3-7) (EIA 2006f),5 thereby increasing the
17 demand for electricity.
18
19 Figure 3-6: Annual Deviations from Normal Heating Degree Days for the United States (1950-2005)
20
21 Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2005)
22
23 Although no new U.S. nuclear power plants have been constructed in recent years, the utilization (i.e., capacity
24 factors6) of existing plants in 2005 remained high at slightly over 89 percent. Electricity output by hydroelectric
25 power plants decreased in 2005 by approximately 1 percent. Electricity generated by nuclear plants in 2005
26 provided almost 3 times as much of the energy consumed in the United States as hydroelectric plants (EIA 2006a).
27 Aggregate nuclear and hydroelectric power plant capacity factors since 1973 are shown in Figure 3-8.
28
4 See the sections entitled Stationary Combustion and Mobile Combustion in this chapter for information on non-C02 gas
emissions from fossil fuel combustion.
5 Degree days are relative measurements of outdoor air temperature. Heating degree days are deviations of the mean daily
temperature below 65° F, while cooling degree days are deviations of the mean daily temperature above 65° F. Heating degree
days have a considerably greater affect on energy demand and related emissions than do cooling degree days. Excludes Alaska
and Hawaii. Normals are based on data from 1971 through 2000. The variation in these normals during this time period was
+10 percent and +14 percent for heating and cooling degree days, respectively (99 percent confidence interval).
6 The capacity factor is defined as the ratio of the electrical energy produced by a generating unit for a given period of time to
the electrical energy that could have been produced at continuous full-power operation during the same period (EIA 2006a).
Energy 3-5
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
Figure 3-8: Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the United States (1974-2005)
[END BOX]
For the purpose of international reporting, the Intergovernmental Panel on Climate Change (IPCC)
(IPCC/UNEP/OECD/IEA 1997) recommends that particular adjustments be made to national fuel consumption
statistics. Certain fossil fuels can be manufactured into plastics, asphalt, lubricants, or other products. A portion of
the C consumed for these non-energy products can be stored (i.e., sequestered) indefinitely. To account for the fact
that the C in these fuels ends up in products instead of being combusted (i.e., oxidized and released into the
atmosphere), consumption of fuels for non-energy purposes is estimated and subtracted from total fuel consumption
estimates. Emissions from non-energy uses of fuels are estimated in the Carbon Emitted and Stored in Products
from Non-Energy Uses of Fossil Fuels section in this chapter.
According to the UNFCCC reporting guidelines, C02 emissions from the consumption of fossil fuels for aviation
and marine international transport activities (i.e., international bunker fuels) should be reported separately, and not
included in national emission totals. Estimates of international bunker fuel emissions for the United States are
provided in Table 3-5.
Table 3-5: C02 Emissions from International Bunker Fuels (Tg C02 Eq.)*
Vehicle Mode
1990
1995
2000
2001
2002
2003
2004
2005
Aviation
45.7
50.2
59.9
58.7
61.1
58.8
62.2
61.5
Marine
68.0
50.4
41.3
38.9
28.0
24.9
34.9
34.2
Total
113.7
100.6
101.1
97.6
89.1
83.7
97.2
95.6
* See International Bunker Fuels section for additional detail.
Note: Totals may not sum due to independent rounding.
End-Use Sector Consumption
An alternative method of presenting C02 emissions is to allocate emissions associated with electricity generation to
the sectors in which it is used. Four end-use sectors were defined: industrial, transportation, residential, and
commercial. For the discussion below, electricity generation emissions have been distributed to each end-use sector
based upon the sector's share of national electricity consumption. This method of distributing emissions assumes
that each sector consumes electricity generated from an equally carbon-intensive mix of fuels and other energy
sources. After the end-use sectors are discussed, emissions from electricity generation are addressed separately.
Emissions from U.S. territories are also calculated separately due to a lack of end-use-specific consumption data.
Table 3-6 and Figure 3-9 summarize C02 emissions from direct fossil fuel combustion and pro-rated electricity
generation emissions from electricity consumption by end-use sector.
Table 3-6: C02 Emissions from Fossil Fuel Combustion by End-Use Sector (Tg C02 Eq.)
End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005
Transportation 1,467.0 1,593.3 1,787.8 1,761.5 1,815.7 1,814.8 1,868.9 1,899.5
Combustion 1,464.0 1,590.2 1,784.4 1,758.2 1,812.3 1,810.5 1,864.5 1,894.4
Electricity 3.0 3.0 3.4 3.3 3.4 4.3 4.4 5.2
Industrial 1,539.8 1,595.8 1,660.1 1,596.6 1,575.5 1,595.1 1,615.2 1,575.2
Combustion 857.1 882.7 875.0 869.9 857.7 858.3 875.6 840.1
Electricity 682.7 713.1 785.1 726.7 717.8 736.8 739.6 735.1
Residential 929.9 995.4 1,131.5 1,124.8 1,147.9 1,179.1 1,175.9 1,208.7
Combustion 340 ^ 356.4 373.5 363.9 362.4 383.8 369.9 358.7
Electricity 589,(. 639.0 758.0 760.9 785.5 795.3 806.0 849.9
Commercial 759.2 810.6 969.3 979.7 973.8 984.2 999.1 1,016.8
Combustion 224 ^ 226.4 232.3 225.1 225.7 236.6 233.3 225.8
Electricity 534.'> 584.2 736.9 754.6 748.0 747.6 765.8 791.0
U.S. Territories 28.3 35.0 36.2 49.0 44.3 51.3 54.0 52.5
3-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Total 4,724.1 5,030.0 5,584.9 5,511.7 5,557.2 5,624.5 5,713.0 5,752.8
Electricity Generation 1,810.2 I.'>39.3 2,283.5 2,245.5 2,254.7 2,284.0 2,315.8 2,381.2
1 Note: Totals may not sum due to independent rounding. Emissions from fossil fuel combustion by electricity generation are
2 allocated based on aggregate national electricity consumption by each end-use sector.
3
4 Figure 3-9: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion
5
6 Transportation End-Use Sector
7 Using this allocation method, the transportation end-use sector accounted for 1,899.5 Tg C02 in 2005, or
8 approximately 33 percent of total C02 emissions from fossil fuel combustion, the largest share of any end-use
9 economic sector.7 Between 1990 and 2005, transportation C02 emissions increased by 432.5 Tg C02, representing
10 approximately 41 percent of the growth in energy-related C02 emissions from all sectors. Almost all of the energy
11 consumed in the transportation sector was petroleum-based, including motor gasoline, diesel fuel, jet fuel, and
12 residual oil.
13 Table 3-7 provides a detailed breakdown of C02 emissions by fuel category and vehicle type for the transportation
14 end-use sector. As detailed in the table, overall transportation C02 emissions increased by 29 percent from 1990 to
15 2005, representing an average annual increase of 1.8 percent. Between 2004 and 2005 transportation C02
16 emissions increased by 1.6 percent.
17 Transportation fuel consumption is broadly affected by travel activity and the amount of energy vehicles use to
18 move people and goods by various travel modes. In the short-term, changes in transportation energy consumption
19 and C02 emissions primarily reflect variation in travel activity that accompanies year-to-year economic fluctuations.
20 Long-term factors, especially the cost of fuel, can impact travel patterns and vehicle energy efficiency. Since 1990,
21 there has been a significant increase in vehicle miles traveled (VMT) by light-duty trucks, freight trucks and
22 aircraft. At the same time, the fuel economy of light-duty trucks and freight trucks has remained roughly constant.
23 By contrast, commercial aircraft have become noticeably more fuel efficient.
24 As shown in Table 3-7, automobiles and light-duty trucks (consuming both gasoline and diesel) accounted for
25 approximately 61 percent of transportation C02 emissions in 2005. From 1990 to 2005, C02 emissions from
26 automobiles and light-duty trucks increased roughly 25 percent (236.2 Tg C02). Over this period, VMT by
27 automobile and light-duty trucks increased by 39 percent, outweighing a small increase in overall fleet fuel
28 economy. Much of the small increase in overall fleet fuel economy resulted from the retirement of older, less fuel
29 efficient vehicles. Figure 3-10 presents a comparison of the sales of automobiles and light-duty trucks from 1990
30 through 2005; Figure 3-11 then presents the overall sales-weighted fuel economy of new vehicles sold in the United
31 States over the time period.
32
33 Figure 3-10. Sales of New Automobiles and Light-Duty Trucks, 1990-2005
34
35 Figure 3-11. Sales-Weighted Fuel Economy of New Automobiles and Light-Duty Trucks, 1990-2005
36
7 Note that electricity generation is actually the largest emitter of C02 when electricity is not distributed among end-use sectors.
Energy 3-7
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Public Review Draft
Carbon dioxide emissions from freight trucks8 increased by 69 percent (157.7 Tg) from 1990 to 2005, representing
the largest emissions rate increase of any major transportation mode. Fuel economy for the freight truck fleet was
relatively constant over this period, while truck VMT increased by 51 percent. Aircraft9 C02 emissions increased
by approximately four percent (7.3 Tg C02) between 1990 and 2005, reflecting both an increase in emissions from
commercial aircraft emissions and a decrease in domestic military aircraft emissions. While C02 emissions from
commercial aircraft grew by approximately 16 percent (21.8 Tg C02) from 1990 to 2005, passenger miles traveled
increased by 69 percent over the same period, reflecting improvements in the fuel efficiency of planes and an
increasing percentage of occupied seats per plane. For further information on all greenhouse gas emissions from
transportation sources, please refer to Table A-108 in Annex 3.2.
Table 3-7 provides a detailed breakdown of C02 emissions by fuel category and vehicle type for the transportation
end-use sector. Fifty-seven percent of the emissions from this end-use sector in 2005 were the result of the
combustion of motor gasoline in passenger cars and light-duty trucks. Trucks and jet aircraft were also significant
contributors, respectively accounting for 20 and 12 percent of C02 emissions from the transportation end-use
sector.10 For information on C02 emissions from off-road equipment and vehicles, please refer to Table A-107 in
Annex 3.2.
Table 3-7: C02 Emissions from Fossil Fuel Combustion in Transportation End-Use Sector (Tg C02 Eq.)a
Fuel/Vehicle Type 1990 1995 2000 2001 2002 2003 2004
Gasoline 961.7 1,029.7
Automobiles 607.3 591.7
Light-Duty Trucks 302.1 386.4
Other Trucks 37.'J 35.51
Buses 0.3 0.4
Motorcycles 1.7 1.71
Boats (Recreational) 12.4 14.01
Distillate Fuel Oil (Diesel) 272.7 325.11
Automobiles 7.1- 7.7J
Light-Duty Trucks 11.3 14.71
Other Trucks 188.3 234.91
Buses 1 8.61
Locomotives 35.1 39.21
Ships & Boats 10.7 10.91
Ships (Bunkers) 11.(> 9.21
Jet Fuelb 222.
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
Light Trucks
+
Buses
+
Pipeline
36.1
LPG
1.4
Light Trucks
0.5
Other Trucks
0.8
Buses
+
Electricity
3.0
Rail
3.0
+1
0.1
38:
I.I
0 *
0.5
+1
3.0
3 u
+
+
+
+
+
+
0.4
0.5
0.6
0.7
0.7
0.7
35.2
34.4
36.6
32.7
31.5
31.1
0,7
0.8
0.8
1.0
1.1
1.1
0.3
0.3
0.3
0.4
0.4
0.4
0.4
0.5
0.5
0.6
0.7
0.7
+
+
+
+
+
+
3.4
3.3
3.4
4.3
4.4
5.2
3.4
3.3
3.4
4.3
4.4
5.2
1,888.9
1,859.1
1,904.8
1,898.5
1,966.0
1,995.1
1,787.8
1,761.5
1,815.7
1,814.8
1,868.9
1,899.5
Total (Including Bunkers)d 1,580." 1,693.9|
Total (Excluding 1,467.0
Bunkers)*1 1,593.3|
Note: Totals may not sum due to independent rounding.
a This table does not include emissions from non-transportation mobile sources, such as agricultural equipment and construction
equipment; it also does not include emissions associated with electricity consumption by pipelines or lubricants used in
transportation.
b Due to a change in methodology for estimating jet fuel consumption by aircraft type, the amount of jet fuel assigned to
commercial aircraft is higher than in previous inventories; the "other aircraft" category has also been eliminated as a result of
this change in methodology.
c Fluctuations in emission estimates from the combustion of residual fuel oil are currently unexplained, but may be related to 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 C02 Eq.
Industrial End-Use Sector
The industrial end-use sector accounted for 27 percent of C02 emissions from fossil fuel combustion. On average,
53 percent of these emissions resulted from the direct consumption of fossil fuels for steam and process heat
production. The remaining 47 percent was associated with their consumption of electricity for uses such as motors,
electric furnaces, ovens, and lighting.
The industrial end-use sector includes activities such as manufacturing, construction, mining, and agriculture. The
largest of these activities in terms of energy consumption is manufacturing, of which six industries—Petroleum
Refineries, Chemicals, Primary Metals, Paper, Food, and Nonmetallic Mineral Products—represent the vast
majority of the energy use (EIA 2006a and 2005b).
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 is also affected by weather
conditions.11 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 2004 to 2005, total industrial production and manufacturing output increased by 3.3 and 4.0 percent,
respectively (FRB 2006). Over this period, output increased for Paper, Food, and Nonmetallic Mineral Products,
but declined for Petroleum Refineries, Chemicals, and Primary Metals (see Figure 3-12).
11 Some commercial customers are large enough to obtain an industrial price for natural gas and/or electricity and are
consequently grouped with the industrial end-use sector in U.S. energy statistics. These misclassifications of large commercial
customers likely cause the industrial end-use sector to appear to be more sensitive to weather conditions.
Energy 3-9
-------
Public Review Draft
1 Figure 3-12: Industrial Production Indices (Index 1997=100)
2
3 Despite the growth in industrial output (56 percent) and the overall U.S. economy (55 percent) from 1990 to 2005,
4 C02 emissions from the industrial end-use sector increased by only 2.3 percent. A number of factors are believed to
5 have caused this disparity between rapid growth in industrial output and decrease in industrial emissions, including:
6 (1) more rapid growth in output from less energy-intensive industries relative to traditional manufacturing
7 industries, and (2) improvements in energy efficiency. In 2005, C02 emissions from fossil fuel combustion and
8 electricity use within the industrial end-use sectors were 1,575.2 Tg C02 Eq., or 2.5 percent below 2004 emissions.
9 Residential and Commercial End-Use Sectors
10 The residential and commercial end-use sectors accounted for an average 21 and 18 percent, respectively, of C02
11 emissions from fossil fuel combustion. Both end-use sectors were heavily reliant on electricity for meeting energy
12 needs, with electricity consumption for lighting, heating, air conditioning, and operating appliances contributing to
13 about 70 and 78 percent of emissions from the residential and commercial end-use sectors, respectively. The
14 remaining emissions were largely due to the direct consumption of natural gas and petroleum products, primarily for
15 heating and cooking needs. Coal consumption was a minor component of energy use in both of these end-use
16 sectors. In 2005, C02 emissions from fossil fuel combustion and electricity use within the residential and
17 commercial end-use sectors were 1,208.7 Tg C02 Eq. and 1,016.8 Tg C02 Eq., respectively.
18 Emissions from the residential and commercial sectors have generally been increasing since 1990, and are often
19 correlated with short-term fluctuations in energy consumption caused by weather conditions, rather than prevailing
20 economic conditions (see Table 3-6). In the long-term, both end-use sectors are also affected by population growth,
21 regional migration trends, and changes in housing and building attributes (e.g., size and insulation).
22 Emissions from natural gas consumption represent over 73 percent of the direct (not including electricity) fossil fuel
23 emissions from the residential and commercial sectors. In 2005, natural gas emissions decreased by 1 and 2 percent,
24 respectively, in each of these sectors, due to warmer conditions in the United States (see Figure 3-13).
25
26 Figure 3-13: Heating Degree Days12
27
28 Electricity sales to the residential and commercial end-use sectors in 2005 increased by 5 and 3 percent,
29 respectively, from 2004. This trend can largely be attributed to the growing economy (3.2 percent), which led to
30 increased demand for electricity. Increased air conditioning-related electricity consumption in these sectors was
31 also attributable to the warmer summer (see Figure 3-14). Electricity-related emissions in both the residential and
32 commercial sectors rose due to increased consumption; total emissions from the residential sector increased by 2.8
33 percent in 2005, with emissions from the commercial sector 1.8 percent higher than in 2004.
34
35 Figure 3-14: Cooling Degree Days13
12 Degree days are relative measurements of outdoor air temperature. Heating degree days are deviations of the mean daily
temperature below 65° F. Excludes Alaska and Hawaii. Normals are based on data from 1971 through 2000.
13 Degree days are relative measurements of outdoor air temperature. Cooling degree days are deviations of the mean daily
temperature above 65° F. Excludes Alaska and Hawaii. Normals are based on data from 1971 through 2000.
3-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1
2 Electricity Generation
3 The process of generating electricity is the single largest source of C02 emissions in the United States, representing
4 39 percent of total C02 emissions from all C02 emissions sources across the United States. Electricity generation
5 also accounted for the largest share of C02 emissions from fossil fuel combustion, approximately 41 percent in
6 2005. Electricity was consumed primarily in the residential, commercial, and industrial end-use sectors for lighting,
7 heating, electric motors, appliances, electronics, and air conditioning (see Figure 3-15).
8
9 Figure 3-15: Electricity Generation Retail Sales by End-Use Sector
10
11 The electric power industry includes all power producers, consisting of both regulated utilities and nonutilities (e.g.
12 independent power producers, qualifying cogenerators, and other small power producers). For the underlying
13 energy data used in this chapter, the Energy Information Administration (EIA) categorizes electric power generation
14 into three functional categories: the electric power sector, the commercial sector, and the industrial sector. The
15 electric power sector consists of electric utilities and independent power producers whose primary business is the
16 production of electricity,14 while the other sectors consist of those producers that indicate their primary business is
17 other than the production of electricity.
18 In 2005, the amount of electricity generated (in kWh) increased by 2.4 percent, largely due to the growing economy,
19 expanding industrial production, and warmer summer conditions. However, C02 emissions increased by 2.8
20 percent, as a larger share of electricity was generated by coal. Coal and natural gas consumption for electricity
21 generation increased by 2.1 percent and 7.5 percent, respectively, in 2005, and nuclear power decreased by 1.1
22 percent. As a result of the increase in coal consumption, C intensity from direct fossil fuel combustion increased
23 slightly overall in 2005 (see Table 3-9). Coal is consumed primarily by the electric power sector in the United
24 States, which accounted for 94 percent of total coal consumption for energy purposes in 2005. The amount of
25 electricity generated from renewables decreased by 1.7 percent in 2005.
26
27 [BEGIN BOX]
28 Box 3-2: Carbon Intensity of U.S. Energy Consumption
29
30 Fossil fuels are the dominant source of energy in the United States, and C02 is emitted as a product from their
31 combustion. Useful energy, however, is generated in the United States from many other sources that do not emit
32 C02 in the energy conversion process, such as renewable (i.e., hydropower, biofuels, geothermal, solar, and wind)
33 and nuclear sources.15
14 Utilities primarily generate power for the U.S. electric grid for sale to retail customers. Nonutilities produce electricity for
their own use, to sell to large consumers, or to sell on the wholesale electricity market (e.g., to utilities for distribution and resale
to customers).
15 Small quantities of C02, however, are released from some geologic formations tapped for geothermal energy. These
emissions are included with fossil fuel combustion emissions from the electricity generation. Carbon dioxide emissions may also
be generated from upstream activities (e.g., manufacture of the equipment) associated with fossil fuel and renewable energy
Energy 3-11
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
Public Review Draft
Energy-related C02 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 C02 Eq./QBtu for natural gas to upwards of 95 Tg C02 Eq./QBtu for coal and petroleum coke.16
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 C02
Eq./Btu). Energy generated from nuclear and many renewable sources do not result in direct emissions of C02.
Biofuels such as wood and ethanol are also considered to be C neutral; although these fuels do emit C02, in the long
run the C02 emitted from biomass consumption does not increase atmospheric C02 concentrations if the biogenic C
emitted is offset by the growth of new biomass.17 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 C02 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 C02 Eq./QBtu)
Sector
1990
1 1995
1 2000
2001
2002
2003
2004
2005
Residential3
57.3
56.6
56.7
56.9
56.6
56.8
56.9
56.7
Commercial3
59.6
57.8
57.3
57.6
57.1
57.4
57.6
57.5
Industrial3
63.8
62.7
62.6
63.5
63.0
63.4
63.5
64.0
Transportation3
71.0
7L0
7L0
71.0
71.0
71.0
71.1
71.1
Electricity Generation13
86.7
86.0
85.6
85.1
85.0
85.7
85.4
85.0
U.S. Territories0
74.1
1 74.1
I 73.2
73.6
73.7
74.1
74.0
74.1
All Sectors0
72.7
I 72.2
| 72.6
72.7
72.5
72.8
72.9
73.1
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.18 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
activities, but are not accounted for here.
16 One exajoule (EJ) is equal to 1018 joules or 0.9478 QBtu.
17 Net carbon fluxes from changes in biogenic carbon reservoirs in wooded or croplands are accounted for in the estimates for
Land Use, Land-Use Change, and Forestry.
18 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.
3-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
all sources of energy are included, due to its almost complete reliance on petroleum products and relatively minor
amount of biomass-based fuels used, such as ethanol. The "other end-use sectors" (i.e., residential, commercial, and
industrial) use significant quantities of biofuels such as wood, thereby lowering the overall C intensity. The C
intensity of the electricity generation sector differs greatly from the scenario in Table 3-8, where only the energy
consumed from the direct combustion of fossil fuels was included. This difference is due almost entirely to the
inclusion of electricity generation from nuclear and hydropower sources, which do not emit C02.
Table 3-9: Carbon Intensity from all Energy Consumption by Sector (Tg C02 Eq./QBtu)
Sector
1990
1995
1 2000
2001
2002
2003
2004
2005
Transportation3
70.8
70.6
70.6
70.5
70.5
70.4
70.3
70.2
Other End-Use Sectorsa b
57.6
56.5
57.9
58.4
57.6
58.1
58.0
58.5
Electricity Generation0
59.0
57.9
59.9
60.0
58.9
59.6
59.4
59.8
All Sectors'1
61.1
j 60.3
61.4
61.8
61.3
61.6
61.5
61.9
a Includes electricity (from fossil fuel, nuclear, and renewable sources) and direct renewable energy consumption.
b Other End-Use Sectors includes the residential, commercial, and industrial sectors.
c Includes electricity generation from nuclear and renewable sources.
d Includes nuclear and renewable energy consumption.
Note: Excludes non-energy fuel use emissions and consumption.
By comparing the values in Table 3-8 and Table 3-9, a few observations can be made. The use of renewable and
nuclear energy sources has resulted in a significantly lower C intensity of the U.S. economy. Over the fifteen-year
period of 1990 through 2005, 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 3-16). Due to a general
shift from a manufacturing-based economy to a service-based economy, as well as overall increases in efficiency,
energy consumption and energy-related C02 emissions per dollar of gross domestic product (GDP) have both
declined since 1990 (BEA 2006).
Figure 3-16: U.S. Energy Consumption and Energy-Related C02 Emissions Per Capita and Per Dollar GDP
C intensity estimates were developed using nuclear and renewable energy data from EIA (2006a) and fossil fuel
consumption data as discussed above and presented in Annex 2.1.
[END BOX]
Methodology
The methodology used by the United States for estimating C02 emissions from fossil fuel combustion is
conceptually similar to the approach recommended by the IPCC for countries that intend to develop detailed,
sectoral-based emission estimates (IPCC 2006). A detailed description of the U.S. methodology is presented in
Annex 2.1, and is characterized by the following steps:
1. Determine total fuel consumption by fuel type and sector. Total fossil fuel consumption for each year is
estimated by aggregating consumption data by end-use sector (e.g., commercial, industrial, etc.), primary fuel
type (e.g., coal, petroleum, gas), and secondary fuel category (e.g., motor gasoline, distillate fuel oil, etc.). Fuel
consumption data for the United States were obtained directly from the Energy Information Administration
(EIA) of the U.S. Department of Energy (DOE), primarily from the Monthly Energy Review and unpublished
supplemental tables on petroleum product detail (EIA 2006b). The United States does not include territories in
Energy 3-13
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
its national energy statistics, so fuel consumption data for territories were collected separately from Grillot
(2006).19
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.20
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).21
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 Gambogi (2006), EFMA
(1995), U.S. Census Bureau (1991 through 1994), U.S. Census Bureau (2006a), USITC (2006), U.S. Census
Bureau (2005), EIA (2005a), EIA (2001b), USAA (2006), USGS (1998 through 2002), USGS (1995),
Corathers (2006), USGS (1991 through 2005), USGS (1991 through 2005), U.S. International Trade
Commission (2006), U.S. International Trade Commission (2004), Onder and Bagdoyan (1993), and Johnson
(2006).22
3. Adjust for biofuels, conversion offossil fuels, and exports of C02. Fossil fuel consumption estimates are
adjusted downward to exclude (1) fuels with biogenic origins, (2) fuels created from other fossil fuels, and (3)
exports of C02. Fuels with biogenic origins are assumed to result in no net C02 emissions, and must be
subtracted from fuel consumption estimates. These fuels include ethanol added to motor gasoline and biomass
gas used as natural gas. Synthetic natural gas is created from industrial coal, and is currently included in EIA
statistics for both coal and natural gas. Therefore, synthetic natural gas is subtracted from energy consumption
statistics.23 Since October 2000, the Dakota Gasification Plant has been exporting C02 to Canada by pipeline.
Since this C02 is not emitted to the atmosphere in the United States, energy used to produce this C02 is
subtracted from energy consumption statistics. To make these adjustments, additional data for ethanol and
biogas were collected from EIA (2006b) and data for synthetic natural gas were collected from EIA (2006e),
and data for C02 exports were collected from the Dakota Gasification Company (2006), Fitzpatrick (2002),
Erickson (2003), EIA (2001a), EIA (2004), EIA (2006e), and Kass (2005).
4. Adjust Sectoral Allocation of Distillate Fuel Oil. EPA had conducted a separate bottom-up analysis of
19 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 53 Tg C02 Eq. in 2005.
20 See IPCC Reference Approach for estimating C02 emissions from fossil fuel combustion in Annex 4 for a comparison of U.S.
estimates using top-down and bottom-up approaches.
21 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.
22 See sections on Iron and Steel Production, Ammonia Manufacture, Petrochemical Production, Titanium Dioxide Production,
Ferroalloy Production, Aluminum Production, and Silicon Carbide Production in the Industrial Processes chapter.
23 These adjustments are explained in greater detail in Annex 2.1.
3-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Public Review Draft
transportation fuel consumption based on FHWA Vehicle Miles Traveled (VMT) that indicated that the amount
of distillate consumption allocated to the transportation sector in the EIA statistics should be adjusted.
Therefore, for these estimates, the transportation sector's distillate fuel consumption was adjusted higher to
match the value obtained from the bottom-up analysis based on VMT. As the total distillate consumption
estimate from EIA is considered to be accurate at the national level, the distillate consumption totals for the
residential, commercial, and industrial sectors were adjusted downward proportionately. The data sources used
in the bottom-up analysis of transportation fuel consumption include AAR (2005), Benson (2002 through
2004), DOE (1993 through 2004), EIA (2006a), EIA (1991 through 2005), EPA (2004), and FHWA (1996
through 2006).
5. Adjust for fuels consumed for non-energy uses. U.S. aggregate energy statistics include consumption of fossil
fuels for non-energy purposes. Depending on the end-use, this can result in storage of some or all of the C
contained in the fuel for a period of time. As the emission pathways of C used for non-energy purposes are
vastly different than fuel combustion, these emissions are estimated separately in the Carbon Emitted and
Stored in Products from Non-Energy Uses of Fossil Fuels section in this chapter. Therefore, the amount of
fuels used for non-energy purposes was subtracted from total fuel consumption. Data on non-fuel consumption
was provided by EIA (2006b).
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).24 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 2006) supplied data on military jet fuel use. Commercial jet
fuel use was obtained from BEA (1991 through 2006) and DOT (1991 through 2006); residual and distillate
fuel use for civilian marine bunkers was obtained from DOC (1991 through 2006). 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 C02. The C content
coefficients used by the United States were obtained from EIA's Emissions of Greenhouse Gases in the United
States 2005 (EIA 2006c) and EIA's Monthly Energy Review and unpublished supplemental tables on petroleum
product detail EIA (EIA 2006b). They are presented in Annexes 2.1 and 2.2.
8. Estimate C02 Emissions. Total C02 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 highway vehicles, annual estimates of combined motor gasoline and diesel fuel consumption by vehicle
24 See International Bunker Fuels section in this chapter for a more detailed discussion.
Energy 3-15
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
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
2004).
• For non-highway vehicles, activity data were obtained from AAR (2005), BEA (1991 through 2006), Benson
(2002 through 2004), DOE (1993 through 2004), DESC (2006), DOC (1991 through 2006), DOT (1991
through 2006), EIA (2002a), EIA (2006a), EIA (2006d), EIA (2006g), EIA (1991 through 2005), EPA
(2004), and FAA (2005).
• For jet fuel used by aircraft, C02 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.25 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 (2006a) and USAF (1998).26
Uncertainty
For estimates of C02 from fossil fuel combustion, the amount of C02 emitted is directly related to the amount of
fuel consumed, the fraction of the fuel that is oxidized, and the carbon content of the fuel. Therefore, a careful
accounting of fossil fuel consumption by fuel type, average carbon contents of fossil fuels consumed, and
production of fossil fuel-based products with long-term carbon storage should yield an accurate estimate of C02
emissions.
Nevertheless, there are uncertainties in the consumption data, carbon content of fuels and products, and carbon
oxidation efficiencies. For example, given the same primary fuel type (e.g., coal, petroleum, or natural gas), the
amount of carbon contained in the fuel per unit of useful energy can vary. For the United States, however, the
impact of these uncertainties on overall C02 emission estimates is believed to be relatively small. See, for example,
Marland and Pippin (1990).
Although statistics of total fossil fuel and other energy consumption are relatively accurate, the allocation of this
consumption to individual end-use sectors (i.e., residential, commercial, industrial, and transportation) is less
certain. For example, for some fuels the sectoral allocations are based on price rates (i.e., tariffs), but a commercial
establishment may be able to negotiate an industrial rate or a small industrial establishment may end up paying an
industrial rate, leading to a misallocation of emissions. Also, the deregulation of the natural gas industry and the
more recent deregulation of the electric power industry have likely led to some minor problems in collecting
accurate energy statistics as firms in these industries have undergone significant restructuring.
To calculate the total C02 emission estimate from energy-related fossil fuel combustion, the amount of fuel used in
these non-energy production processes were subtracted from the total fossil fuel consumption for 2005. The amount
of C02 emissions resulting from non-energy related fossil fuel use has been calculated separately and reported in the
Carbon Emitted from Non-Energy Uses of Fossil Fuels section of this report. These factors all contribute to the
uncertainty in the C02 estimates. Detailed discussions on the uncertainties associated with C emitted from Non-
25 FAA's System for assessing Aviation's Global Emissions (SAGE) model develops aircraft fuel burn and emissions for all
commercial flights globally in a given year. The SAGE model dynamically models aircraft performance, fuel burn, and
emissions, and is based on actual flight-by-flight aircraft movements. See
.
26 For a more detailed description of the data sources used for the analysis of the transportation end use sector see the Mobile
Combustion (excluding C02) and International Bunker Fuels sections of the Energy chapter, Annex 3.2, and Annex 3.7.
3-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
Energy Uses of Fossil Fuels can be found within that section of this chapter.
Various sources of uncertainty surround the estimation of emissions from international bunker fuels, which are
subtracted from the U.S. totals (see the detailed discussions on these uncertainties provided in the International
Bunker Fuels section of this chapter). Another source of uncertainty is fuel consumption by U.S. territories. The
United States does not collect energy statistics for its territories at the same level of detail as for the fifty states and
the District of Columbia. Therefore, estimating both emissions and bunker fuel consumption by these territories is
difficult.
Uncertainties in the emission estimates presented above also result from the data used to allocate C02 emissions
from the transportation end-use sector to individual vehicle types and transport modes. In many cases, bottom-up
estimates of fuel consumption by vehicle type do not match aggregate fuel-type estimates from EIA. Further
research is planned to improve the allocation into detailed transportation end-use sector emissions. In particular,
residual fuel consumption data for marine vessels are highly uncertain, as shown by the large fluctuations in
emissions that do not mimic changes in other variables such as shipping ton miles.
The uncertainty analysis was performed by primary fuel type for each end-use sector, using the IPCC-recommended
Tier 2 uncertainty estimation methodology, Monte Carlo Simulation technique, with @RISK software. For this
uncertainty estimation, the inventory estimation model for C02 from fossil fuel combustion was integrated with the
relevant inventory variables from the inventory estimation model for International Bunker Fuels, to realistically
characterize the interaction (or endogenous correlation) between the variables of these two models. About 150
input variables were modeled for C02 from energy-related Fossil Fuel Combustion (including about 10 for non-
energy fuel consumption and about 20 for International Bunker Fuels).
In developing the uncertainty estimation model, uniform distributions were assumed for all activity-related input
variables and emission factors, based on the SAIC/EIA (2001) report.27 Triangular distributions were assigned for
the oxidization factors (or combustion efficiencies). The uncertainty ranges were assigned to the input variables
based on the data reported in SAIC/EIA (2001) and on conversations with various agency-personnel.28
The uncertainty ranges for the activity-related input variables were typically asymmetric around their inventory
estimates; the uncertainty ranges for the emissions factors were symmetric. Bias (or systematic uncertainties)
associated with these variables accounted for much of the uncertainties associated with these variables (SAIC/EIA
2001).29 For purposes of this uncertainty analysis, each input variable was simulated 10,000 times through Monte
Carlo Sampling.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-10. Fossil fuel combustion
C02 emissions in 2005 were estimated to be between 5,658.2 and 6,062.1 Tg C02 Eq. at a 95 percent confidence
level. This indicates a range of 2 percent below to 5 percent above the 2005 emission estimate of 5,752.8 Tg C02
Eq.
27 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.
28 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.
29 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 3-17
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Public Review Draft
Table 3-10: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Energy-related Fossil Fuel
Combustion by Fuel Type and Sector (Tg C02 Eq. and Percent)
2005 Emission
Estimate
Fuel/Sector (Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Bound
Upper Bound
Lower Bound Upper
Bound
Coal"
2,093.6
2,024.6
2,290.6
-3%
+9%
Residential
1.0
0.9
1.1
-5%
+15%
Commercial
8.0
7.6
9.2
-5%
+15%
Industrial
122.2
117.5
142.3
-4%
+16%
Transportation
NE
NE
NE
NA
NA
Electricity Generation
1,958.4
1,882.7
2,146.7
-4%
+10%
U.S. Territories
4.0
3.5
4.7
-12%
+19%
Natural Gasb
1,170.0
1,179.5
1,245.4
1%
+6%
Residential
262.8
255.4
281.2
-3%
+7%
Commercial
167.0
162.3
178.6
-3%
+7%
Industrial
387.0
395.9
435.7
2%
+13%
Transportation
31.8
30.9
34.1
-3%
+7%
Electricity Generation
320.1
311.0
336.5
-3%
+5%
U.S. Territories
1.3
1.1
1.5
-12%
+17%
Petroleumb
2,488.8
2,356.9
2,629.8
-5%
+6%
Residential
95.0
90.1
99.5
-5%
+5%
Commercial
50.9
48.6
52.9
-5%
+4%
Industrial
330.9
283.9
387.0
-14%
+17%
Transportation
1,862.5
1,740.7
1,980.8
-7%
+6%
Electric Utilities
102.3
98.6
108.1
-4%
+6%
U.S. Territories
47.2
43.7
52.3
-7%
+11%
Total (excluding
Geothermal)b
5,752.4
5,657.8
6,061.8
-2%
+5%
Geothermal
0.4
NE
NE
NE
NE
Total (including
Geothermal)b'c
5,752.8
5,658.2
6,062.1
-2%
+5%
NA (Not Applicable)
NE (Not Estimated)
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
b The low and high estimates for total emissions were calculated separately through simulations and, hence, the low and high
emission estimates for the sub-source categories do not sum to total emissions.
c Geothermal emissions added for reporting purposes, but an uncertainty analysis was not performed for C02 emissions from
geothermal production.
QA/QC and Verification
A source-specific QA/QC plan for C02 from fossil fuel combustion was developed and implemented. This effort
included a Tier 1 analysis, as well as portions of a Tier 2 analysis. The Tier 2 procedures that were implemented
involved checks specifically focusing on the activity data and methodology used for estimating C02 emissions from
fossil fuel combustion in the United States. Emission totals for the different sectors and fuels were compared and
trends were investigated to determine whether any corrective actions were needed. Minor corrective actions were
taken.
Recalculations Discussion
The most significant change impacting fuel combustion estimates in the current inventory was updating the C
oxidation factor for all fuel types to 100 percent. This change was made according to IPCC (2006) and impacted
emission estimates for all fuel types for all years.
3-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 An additional adjustment for silicon carbide used for petroleum coke manufacturing was added to the current
2 Inventory as a source that is accounted for in the Industrial Processes chapter. This was reallocated to the industrial
3 processes chapter, as the silicon carbide was consumed during non-energy related industrial activity.
4 The Energy Information Administration (EIA 2006b) updated energy consumption data for all years. These
5 revisions primarily impacted the emission estimates for 2004. EIA (2006b) no longer reports a small amount of
6 consumption of other liquids in the electricity generation sector, which represented a change from the previous
7 inventory.
8 Overall, changes resulted in an average annual increase of 36.9 Tg C02 Eq. (0.7 percent) in C02 emissions from
9 fossil fuel combustion for the period 1990 through 2004.
10 Planned Improvements
11 To reduce uncertainty of C02 from fossil fuel combustion estimates, efforts will be taken to work with EIA and
12 other agencies to improve the quality of the U.S. territories data. This improvement is not all-inclusive, and is part
13 of an ongoing analysis and efforts to continually improve the C02 from fossil fuel combustion estimates.
14 3.2. Carbon Emitted from Non-Energy Uses of Fossil Fuels (IPCC Source
15 Category 1A)
16 In addition to being combusted for energy, fossil fuels are also consumed for non-energy uses (NEU) in the United
17 States. The fuels used for these purposes are diverse, including natural gas, liquified petroleum gases (LPG),
18 asphalt (a viscous liquid mixture of heavy crude oil distillates), petroleum coke (manufactured from heavy oil), and
19 coal coke (manufactured from coking coal). The non-energy applications are equally diverse, and include
20 feedstocks for the manufacture of plastics, rubber, synthetic fibers and other materials; reducing agents for the
21 production of various metals and inorganic products; and non-energy products such as lubricants, waxes, and
22 asphalt (IPCC 2006).
23 C02 emissions arise from non-energy uses via several pathways. Emissions may occur during the manufacture of a
24 product, as is the case in producing plastics or rubber from fuel-derived feedstocks. Additionally, emissions may
25 occur during the product's lifetime, such as during solvent use. Overall, throughout the time series and across all
26 uses, about 61 percent of the total C consumed for non-energy purposes was stored in products, and not released to
27 the atmosphere; the remaining 39 percent was emitted.
28 There are several areas in which non-energy uses of fossil fuels are closely related to other parts of the inventory.
29 For example, some of the NEU products release C02 at the end of their commercial life when they are combusted
30 after disposal; these emissions are reported separately within the Energy chapter in the Municipal Solid Waste
31 Combustion source category. In addition, there is some overlap between fossil fuels consumed for non-energy uses
32 and the fossil-derived C02 emissions accounted for in the Industrial Processes chapter, especially for fuels used as
33 reducing agents. To avoid double-counting, the "raw" non-energy fuel consumption data reported by EIA are
34 modified to account for these overlaps. There are also net exports of petrochemicals that are not completely
35 accounted for in the EIA data, and these affect the mass of C in non-energy applications.
36 As shown in Table 3-11, fossil fuel emissions in 2005 from the non-energy uses of fossil fuels were 142.3 Tg C02
37 Eq., which constituted approximately 3 percent of overall fossil fuel emissions, approximately the same proportion
38 as in 1990. In 2005, the consumption of fuels for non-energy uses (after the adjustments described above) was
39 5,492 TBtu, an increase of 22 percent since 1990 (see Table 3-12). About 66.3 Tg of the C (243.1 Tg C02 Eq.) in
40 these fuels was stored, while the remaining 38.8 Tg C (142.4 Tg C02 Eq.) was emitted. The proportion of C
41 emitted as C02 has remained about constant since 1990, at about 36 to 40 percent of total non-energy consumption
42 (see Table 3-11).
43 Table 3-11: C02 Emissions from Non-Energy Use Fossil Fuel Consumption (Tg C02 Eq.)
Energy 3-19
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Public Review Draft
Year
1990 1<
)95 2000
2001
2002
2003
2004
2005
Potential Emissions
312S 34
6." 85.5
364.9
368.4
356.4
396.6
385.5
C Stored
195,(. 21
3.<> 244.5
233.5
233.1
225.1
246.4
243.1
Emissions as a % of Potential
37"., 3
8°/., 37%
36%
37%
37%
38%
37%
Emissions
117.2 13
3.1 141.0
131.3
135.3
131.3
150.2
142.3
Methodology
The first step in estimating C stored in products was to determine the aggregate quantity of fossil fuels consumed
for non-energy uses. The C content of these feedstock fuels is equivalent to potential emissions, or the product of
consumption and the fuel-specific C content values. Both the non-energy fuel consumption and C content data were
supplied by the EI A (2006) (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.30 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.
Table 3-12: Adjusted Consumption of Fossil Fuels for Non-Energy Uses (TBtu)
Year
19901
19951
2000 2001 2002 2003 2004 2005
Industry 4,223.7
Industrial Coking Coal 0.0
Industrial Other Coal 8.2
Natural Gas to Chemical 278.4
Plants, Other Uses
Asphalt & Road Oil 1,170.2
LPG 1,119.1
Lubricants 186.
Pentanes Plus 77.
Naphtha (<401 °F) 325.7
Other Oil (>401 °F) 677.2
Still Gas 21
Petroleum Coke 81.0
4,771.7
43.*
11
330.3
1,178.2
1,484.7
177.£
285.31
350,(.
612.7
40.1
44.1
5,261.2
62.8
12.4
421.3
1,275.7
1,604.6
189.9
228.7
592.8
554.3
12.6
47.8
5,045.2
25.5
11.3
408.6
1,256.9
1,539.0
174.0
199.8
489.4
525.9
35.8
128.1
5.032.3
46.4
12.0
364.6
1,240.0
1.565.4
171.9
166.1
564.2
456.2
57.8
110.2
4,864.3
72.0
11.9
348.8
1,219.5
1,437.7
159.0
158.3
573.4
501.0
59.0
79.3
5,295.4
214.7
11.9
340.2
1,303.9
1,435.9
161.0
156.4
687.5
547.5
63.5
169.8
5,208.2
136.6
11.9
365.8
1,323.2
1,441.6
160.2
146.0
678.5
515.1
67.7
145.0
30 These source categories include Iron and Steel Production, Lead Production, Zinc Production, Ammonia Manufacture, Carbon
Black Manufacture (included in Petrochemical Production), Titanium Dioxide Production, Ferroalloy Production, Silicon
Carbide Production, and Aluminum Production.
3-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Public Review Draft
Special Naphtha 100.9
Distillate Fuel Oil 7.0
Waxes 33.
Miscellaneous Products 13 7. £
Transportation 176.0
Lubricants 176.0
U.S. Territories 86.7
Lubricants 0.7
Other Petroleum (Misc. Prod.) 86.0
Total
4,486.4
66.9
94.4
77.9
99.5
75.7
47.2
60.9
| 8.0
11.7
11.7
11.7
11.7
11.7
11.7
40.6
33.1
36.3
32.2
31.0
30.8
31.4
911
119.2
124.9
134.2
126.0
113.4
112.8
167.9
179.4
164.3
162.4
150.1
152.1
151.3
167.9
179.4
164.3
162.4
150.1
152.1
151.3
90.8
165.5
80.3
138.6
127.9
136.6
132.2
2.0
16.4
0.0
1.5
9.3
10.0
9.6
1 88.8
I 149.1
80.3
137.2
118.6
126.6
122.6
i 5,030.5
1 5,606.1
5,289.8
5,333.3
5,142.4
5,584.1
5,491.7
+ Does not exceed 0.05 TBtu
Note: To avoid double-counting, coal coke, petroleum coke, natural gas consumption, and other oils are adjusted for industrial
process consumption reported in the Industrial Processes sector. Natural gas, LPG, Pentanes Plus, Naphthas, Special Naphtha,
and Other Oils are adjusted to account for exports of chemical intermediates derived from these fuels. For residual oil (not
shown in the table), all non-energy use is assumed to be consumed in C black production, which is also reported in the Industrial
Processes chapter.
Note: Totals may not sum due to independent rounding.
Table 3-13: 2005 Adjusted Non-Energy Use Fossil Fuel Consumption, Storage, and Emissions
Adjusted
Non-Energy
Carbon
Carbon
Carbon
Carbon
Use3
Content
Storage
Stored
Emissions
Emissions
Sector/Fuel Type
(TBtu)
(TgC)
Factor
(TgC)
(TgC)
(Tg C02 Eq.)
Industry
5,208.2
99.4
_
65.8
33.7
123.4
Industrial Coking Coal
136.6
4.2
0.10
0.4
3.8
14.0
Industrial Other Coal
11.9
0.3
0.61
0.2
0.1
0.4
Natural Gas to Chemical Plants
365.8
5.3
0.61
3.2
2.0
7.5
Asphalt & Road Oil
1,323.2
27.3
1.00
27.3
0.0
0.0
LPG
1,441.6
24.2
0.61
14.9
9.4
34.3
Lubricants
160.2
3.2
0.09
0.3
2.9
10.8
Pentanes Plus
146.0
2.7
0.61
1.6
1.0
3.8
Naphtha (<401° F)
678.5
12.3
0.61
7.6
4.8
17.4
Other Oil (>401° F)
515.1
10.3
0.61
6.3
4.0
14.6
Still Gas
67.7
1.2
0.61
0.7
0.5
1.7
Petroleum Coke
145.0
4.0
0.50
2.0
2.0
7.4
Special Naphtha
60.9
1.2
0.61
0.7
0.5
1.7
Distillate Fuel Oil
11.7
0.2
0.50
0.1
0.1
0.4
Waxes
31.4
0.6
0.58
0.4
0.3
1.0
Miscellaneous Products
112.8
2.3
0.00
0.0
2.3
8.4
Transportation
151.3
3.1
-
0.3
2.8
10.2
Lubricants
151.3
3.1
0.09
0.3
2.8
10.2
U.S. Territories
132.2
2.6
-
0.3
2.4
8.7
Lubricants
9.6
0.2
0.09
0.0
0.2
0.6
Other Petroleum (Misc. Prod.)
122.6
2.5
0.10
0.2
2.21
8.1
Total
5,491.7
105.1
66.3
38.8
142.3
+ Does not exceed 0.05 TBtu
- Not applicable.
aTo avoid double counting, exports have been deducted.
Note: Totals may not sum due to independent rounding.
Lastly, emissions were estimated by subtracting the C stored from the potential emissions (see Table 3-11). More
detail on the methodology for calculating storage and emissions from each of these sources is provided in Annex
2.3.
Energy 3-21
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
Public Review Draft
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), and pesticide sales and use estimates (EPA 1998, 1999,
2002, 2004b); the EIA Manufacturer's Energy Consumption Survey (MECS) (EIA 1994, 1997, 2001a, 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. Bureau of the Census
(1999, 2003, 2004); the American Plastics Council (APC 2000, 2001, 2003, 2005, 2006; Eldredge-Roebuck 2000);
the Society of the Plastics Industry (SPI2000); Bank of Canada (2006); Financial Planning Association (2006);
INEGI (2006); Statistics Canada (2006); the United States International Trade Commission (2006); 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, 2006); the Material Safety Data Sheets (Miller 1999); the Chemical
Manufacturer's Association (CMA 1999); and the American Chemistry Council (ACC 2005, 2006.) 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, fortius source category.
As noted above, the non-energy use analysis is based on U.S.-specific storage factors for (1) feedstock materials
(natural gas, LPG, pentanes plus, naphthas, other oils, still gas, special naphthas, and other industrial coal), (2)
asphalt, (3) lubricants, and (4) waxes. For the remaining fuel types (the "other" category), the storage factors were
taken directly from the IPCC Guidelines for National Greenhouse Gas Inventories, where available, and otherwise
assumptions were made based on the potential fate of carbon in the respective NEU products. To characterize
uncertainty, five separate analyses were conducted, corresponding to each of the five categories. In all cases,
statistical analyses or expert judgments of uncertainty were not available directly from the information sources for
all the activity variables; thus, uncertainty estimates were determined using assumptions based on source category
knowledge.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-14 (emissions) and Table 3-15
(storage factors). Carbon emitted from non-energy uses of fossil fuels in 2005 was estimated to be between 113.3
and 153.7 Tg C02 Eq. at a 95 percent confidence level. This indicates a range of 20 percent below to 8 percent
above the 2005 emission estimate of 142.4 Tg C02 Eq. The uncertainty in the emission estimates is a function of
uncertainty in both the quantity of fuel used for non-energy purposes and the storage factor.
Table 3-14: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Non-Energy Uses of Fossil Fuels
(Tg C02 Eq. and Percent)
2005
Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Feedstocks
C02
81.1
65.1 97.9 -20% +21%
Asphalt
co2
0.0
0.2 0.8 NA NA
Lubricants
co2
21.6
18.0 25.1 -17% +16%
3-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Waxes C02 1.0 0.7 1.5 -24% +55%
Other C02 38J \T6 402 -56% +4%
Total CP2 142.3 113.3 153.7 -20% +8%
1 a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
2 NA (Not Applicable)
3
4 Table 3-15: Tier 2 Quantitative Uncertainty Estimates for Storage Factors of Non-Energy Uses of Fossil Fuels
5 (Percent)
2005 Storage
Source Gas Factor Uncertainty Range Relative to Inventory Factor"
(%) (%) (%, Relative)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Feedstocks
C02
61%
59%
63%
-4%
+3%
Asphalt
C02
100%
99%
100%
-1%
+0%
Lubricants
C02
9%
4%
17%
-57%
+88%
Waxes
C02
58%
44%
69%
-24%
+20%
Other
C02
22%
20%
63%
-10%
+187%
6 a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval, as a percentage of the
7 inventory value (also expressed in percent terms).
8
9 In Table 3-15, feedstocks and asphalt contribute least to overall storage factor uncertainty on a percentage basis.
10 Although the feedstocks category—the largest use category in terms of total carbon flows—appears to have tight
11 confidence limits, this is to some extent an artifact of the way the uncertainty analysis was structured. As discussed
12 in Annex 2.3, the storage factor for feedstocks is based on an analysis of six fates that result in long-term storage
13 (e.g., plastics production), and eleven that result in emissions (e.g., volatile organic compound emissions). Rather
14 than modeling the total uncertainty around all of these fate processes, the current analysis addresses only the storage
15 fates, and assumes that all C that is not stored is emitted. As the production statistics that drive the storage values
16 are relatively well-characterized, this approach yields a result that is probably biased toward understating
17 uncertainty.
18 As is the case with the other uncertainty analyses discussed throughout this document, the uncertainty results above
19 address only those factors that can be readily quantified. More details on the uncertainty analysis are provided in
20 Annex 2.3.
21 QA/QC and Verification
22 A source-specific QA/QC plan for non-energy uses of fossil fuels was developed and implemented. This effort
23 included a Tier 1 analysis, as well as portions of a Tier 2 analysis for non-energy uses involving petrochemical
24 feedstocks. The Tier 2 procedures that were implemented involved checks specifically focusing on the activity data
25 and methodology for estimating the fate of C (in terms of storage and emissions) across the various end-uses of
26 fossil C. Emission and storage totals for the different subcategories were compared, and trends across the time
27 series were analyzed to determine whether any corrective actions were needed. Corrective actions were taken to
28 rectify minor errors and to improve the transparency of the calculations, facilitating future QA/QC.
29 Recalculations Discussion
30 The methodology of the current Inventory reflects two corrections and minor change. Plastics data from the
31 American Plastics Council includes some Mexican and Canadian production in addition to U.S. production. In the
32 previous inventory, the plastics geography correction was not correctly accounting for Mexican and Canadian
33 production from 2002 through 2004. This correction caused an increase in the quantity of C emitted by 0.64 Tg C,
34 0.98 Tg C, and 1.02 Tg C compared to the previously reported estimates for 2002 though 2004.
35 As noted earlier, there is some overlap between fossil fuels consumed for non-energy uses and the fossil-derived
Energy 3-23
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
C02 emissions accounted for in the Industrial Processes chapter. For the current inventory, for the first time, silicon
carbide production is reported as a specific industrial process. To avoid double-counting of C emissions in the NEU
section and the Industrial Processes chapter, the quantity of petroleum coke used as an input to silicon carbide was
deducted from the potential emissions covered in this chapter.
In addition, in the previous inventory, the cleanser consumption data was not properly accounting for data over the
whole time series. The update in the current Inventory resulted in an increase in exports throughout the time series
and decreased C emissions across the time series.
Planned Improvements
There are several improvements planned for the future:
• Updating the analysis to comply with IPCC (2006). These changes will effect both the non-energy use and
industrial processes sections.
• Improving the uncertainty analysis. Most of the input parameter distributions are based on professional
judgment rather than rigorous statistical characterizations of uncertainty.
• Better characterizing flows of fossil C. Additional "fates" may be researched, including the fossil C load in
organic chemical wastewaters, plasticizers, adhesives, films, paints, and coatings. There is also a need to
further clarify the treatment of fuel additives and backflows (especially methyl tert-butyl ether, MTBE).
Finally, although U.S.-specific storage factors have been developed for feedstocks, asphalt, lubricants, and waxes,
default values from IPCC are still used for two of the non-energy fuel types (industrial coking coal and distillate
oil), and broad assumptions are being used for the remaining fuels (petroleum coke, miscellaneous products, and
other petroleum). Over the long term, there are plans to improve these storage factors by conducting analyses of C
fate similar to those described in Annex 2.3.
3.3. Stationary Combustion (excluding CO2) (IPCC Source Category 1A)
Stationary combustion encompasses all fuel combustion activities from fixed sources (versus mobile combustion).
Other than C02, which was addressed in the previous section, gases from stationary combustion include the
greenhouse gases CH4 and N20 and the indirect greenhouse gases NOx, CO, and NMVOCs.31 Emissions of these
gases from stationary combustion sources depend upon fuel characteristics, size and vintage, along with combustion
technology, pollution control equipment, and ambient environmental conditions. Emissions also vary with
operation and maintenance practices.
N20 and NOx emissions from stationary combustion are closely related to air-fuel mixes and combustion
temperatures, as well as the characteristics of any pollution control equipment that is employed. Carbon monoxide
emissions from stationary combustion are generally a function of the efficiency of combustion; they are highest
when less oxygen is present in the air-fuel mixture than is necessary for complete combustion. These conditions are
most likely to occur during start-up, shutdown and during fuel switching (e.g., the switching of coal grades at a
coal-burning electric utility plant). CH4 and NMVOC emissions from stationary combustion are primarily a
function of the CH4 and NMVOC content of the fuel and combustion efficiency.
Emissions of CH4 decreased 13 percent overall since 1990 to 6.9 Tg C02 Eq. (330 Gg) in 2005. This decrease in
CH4 emissions was primarily due to lower wood consumption in the residential sector. Conversely, N20 emissions
rose 12 percent since 1990 to 13.8 Tg C02 Eq. (45 Gg) in 2005. The largest source of N20 emissions was coal
combustion by electricity generators, which alone accounted for 65 percent of total N20 emissions from stationary
31 Sulfur dioxide (S02) emissions from stationary combustion are addressed in Annex 6.3.
3-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 combustion in 2005. Overall, however, stationary combustion is a small source of CH4 and N20 in the United
2 States.
Table 3-16: CH4 Emissions from Stationary Combustion (Tg C02 Eg.)
Sector/Fuel Type
1990
Electric Power
Coal
Fuel Oil
Natural gas
Wood
Industrial
Coal
Fuel Oil
Natural gas
Wood
Commercial
Coal
Fuel Oil
Natural gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
I 2000
2001
2002
2003
2004
2005
1 0,7
0.7
0.7
0.7
0.7
0.7
0.4
0.4
0.4
0.4
0.4
0.4
0.1
0.1
0.1
0.1
0.1
0.1
OA
0.1
0.1
0.1
0.1
0.1
OA
0.1
0.1
0.1
0.1
0.1
2.3
2.1
2.0
2.0
2.1
1.9
0.3
0.3
0.3
0.3
0.3
0.3
O.i
0.1
0.1
0.1
0.1
0.1
09
0.8
0.8
0.8
0.8
0.7
1.0
0.9
0.8
0.8
0.9
0.7
0.9
0.9
0.9
0.9
0.9
0.9
+
+
+
+
+
+
O.i
0.1
0.1
0.2
0.2
0.1
0.3
0.3
0.3
0.3
0.3
0.3
OA
0.4
0.4
0.4
0.4
0.4
3.5
3.1
3.1
3.3
3.4
3.4
0.1
0.1
0.1
0.1
0.1
0.1
0.3
0.3
0.3
0.3
0.3
0.3
1 05
0.5
0.5
0.5
0.5
0.5
2.6
2.2
2.3
2.4
2.5
2.5
O.i
0.1
0.1
0.1
0.1
0.1
+
+
+
+
+
+
+
0.1
0.1
0.1
0.1
0.1
+
+
+
+
+
+
1 +
+
+
+
+
+
I 7.4
6.8
6.8
7.0
7.1
6.9
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 3-17: N2Q Emissions from Stationary Combustion (Tg C02 Eq.)
Sector/Fuel Type
1990
Electric Power
Coal
Fuel Oil
Natural Gas
Wood
Industrial
Coal
Fuel Oil
Natural Gas
Wood
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
2000
2001
2002
2003
2004
2005
9.3
9.1
9.1
9.4
9.4
9.6
8.8
8.5
8.6
8.8
8.8
9.0
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.2
0.1
0.2
0.2
0.2
0.2
3.3
3.1
3.0
2.9
3.1
2.8
0.6
0.6
0.6
0.6
0.6
0.6
0.5
0.5
0.5
0.5
0.6
0.6
0.3
0.2
0.2
0.2
0.2
0.2
1.9
1.7
1.6
1.6
1.7
1.5
0.4
0.3
0.3
0.4
0.4
0.3
+
+
+
+
+
+
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.9
0.9
0.9
0.9
0.9
0.9
+
+
+
+
+
+
0.3
0.3
0.3
0.3
0.3
0.3
Energy 3-25
-------
Public Review Draft
Natural Gas
0.1
0.1
0.2
0.1
0.1
0.2
0.1
0.1
Wood
0.7
0.6
0.5
0.4
0.4
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
Coal
+11111
+11111
+
+
+
+
+
+
Fuel Oil
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
Natural Gas
+11111
+11111
+
+
+
+
+
+
Wood
+
+ 1 ;
+
+
+
+
+
+
Total
12.3
12.8
14.0
13.5
13.4
13.7
13.9
13.8
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 3-18: CH4 Emissions from Stationary Combustion (Gg)
Sector/Fuel Type
1990
I 1995
I 2000
2001
2002
2003
2004
2005
Electric Power
27
27
33
32
32
34
34
35
Coal
16
18
20
20
20
20
20
21
Fuel Oil
4II111
2
3
4
3
4
4
4
Natural Gas
311I11
4
5
5
5
5
5
6
Wood
41III111
4
4
4
4
5
5
5
Industrial
101
110
108
99
97
96
99
89
Coal
16
15
14
14
13
13
14
13
Fuel Oil
611111
5
5
6
5
6
6
6
Natural Gas
37
42
42
38
39
38
38
35
Wood
41
47
47
41
40
39
42
35
Commercial
42
43
44
42
42
44
44
43
Coal
111I1I
1 1
1
1
1
1
1
1
Fuel Oil
91I111
1 7
7
7
6
7
8
7
Natural Gas
13
15
16
15
15
16
15
15
Wood
19
21
20
19
20
20
20
20
Residential
210
1 190
165
147
150
158
160
160
Coal
91I11
1 5
3
4
4
4
4
3
Fuel Oil
14
13
15
15
14
15
15
14
Natural Gas
21
24
24
23
24
25
24
24
Wood
165 |
1 148
1 122
105
108
114
117
120
U.S. Territories
2111
I 2
2
3
3
3
3
3
Coal
+lllllll
+
+
+
+
+
+
+
Fuel Oil
21I1I
1 2
2
3
3
3
3
3
Natural Gas
+111II1
+
+
+
+
+
+
+
Wood
+
I +
1 +
+
+
+
+
+
Total
382
1 373
I 351
324
324
334
340
330
+ Does not exceed 0.5 Gg
Note: Totals may not sum due to independent rounding.
Table 3-19: N2Q Emissions from Stationary Combustion (Gg)
Sector/Fuel Type
1990
I 1995
I 2000
2001
2002
2003
2004
2005
Electricity Generation
24
26
30
29
29
30
30
31
Coal
23
25
28
28
28
28
28
29
Fuel Oil
1I111
+
1
1
1
1
1
1
Natural Gas
+1I1I1II
+
1
1
1
+
1
1
Wood
+1II1
+
1
+
1
1
1
1
Industrial
10
11
11
10
10
9
10
9
Coal
21111I
2
2
2
2
2
2
2
Fuel Oil
211111
1
2
2
2
2
2
2
Natural Gas
1Ili
1
1
1
1
1
1
1
Wood
5
6
6
5
5
5
6
5
3-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Public Review Draft
Commercial
Coal
Fuel Oil
Natural Gas
Wood
Residential
Coal
Fuel Oil
Natural Gas
Wood
U.S. Territories
Coal
Fuel Oil
Natural Gas
Wood
Total
llllllB
1
+1111111
+
11111111
+
+111
+
+llllli
+
4WM
3
+111111
+
ill
1
+1111111
+
2IIIIII
2
+HH
+
+111111
+
+1111
+
+11111
+
+
+|
40
41
+ Does not exceed 0.5 Gg
Note: Totals may not sum due to independent rounding.
1
1
1
1
1
1
I +
+
+
+
+
+
| +
+
+
+
+
+
I +
+
+
+
+
+
+
+
+
+
+
+
3
3
3
3
3
3
1 +
+
+
+
+
+
1
1
1
1
1
1
+
+
+
+
+
+
2
1
1
2
2
2
I +
+
+
+
+
+
I +
+
+
+
+
+
| +
+
+
+
+
+
I +
+
+
+
+
+
+
+
+
+
+
+
1 45
44
43
44
45
45
Methodology
CH4 and N20 emissions were estimated by multiplying fossil fuel and wood consumption data by emission factors
(by sector and fuel type). National coal, natural gas, fuel oil, and wood consumption data were grouped by sector:
industrial, commercial, residential, electric power, and U.S. territories. For the CH4 and N20 estimates, fuel
consumption data for 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 2006a). Wood consumption data for
the United States was obtained from EIA's Annual Energy Review (EIA 2006b). Because the United States does
not include territories in its national energy statistics, fuel consumption data for territories were provided separately
by Grillot (2006).32 Fuel consumption for the industrial sector was adjusted to subtract out construction and
agricultural use, which is reported under mobile sources.33 Construction and agricultural fuel use was obtained
from EPA (2004). Estimates for wood biomass consumption for fuel combustion do not include wood wastes,
liquors, municipal solid waste, tires, etc. that are reported as biomass by EIA.
Emission factors for the four end-use sectors were provided by the Revised 1996IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC/UNEP/OECD/IEA 1997). U.S. territories' emission factors were estimated
using the U.S. emission factors for the primary sector in which each fuel was combusted.
More detailed information on the methodology for calculating emissions from stationary combustion, including
emission factors and activity data, is provided in Annex 3.1.
Uncertainty
CH4 emission estimates from stationary sources exhibit high uncertainty, primarily due to difficulties in calculating
emissions from wood combustion (i.e., fireplaces and wood stoves). The estimates of CH4 and N20 emissions
32 U.S. territories data also include combustion from mobile activities because data to allocate territories' energy use were
unavailable. For this reason, CH4 and N20 emissions from combustion by U.S. territories are only included in the stationary
combustion totals.
33 Though emissions from construction and farm use occur due to both stationary and mobile sources, detailed data was not
available to determine the magnitude from each. Currently, these emissions are assumed to be predominantly from mobile
sources.
Energy 3-27
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Public Review Draft
presented are based on broad indicators of emissions (i.e., fuel use multiplied by an aggregate emission factor for
different sectors), rather than specific emission processes (i.e., by combustion technology and type of emission
control).
An uncertainty analysis was performed by primary fuel type for each end-use sector, using the IPCC-recommended
Tier 2 uncertainty estimation methodology, Monte Carlo Simulation technique, with @RISK software.
The uncertainty estimation model for this source category was developed by integrating the CH4 and N20 stationary
source inventory estimation models with the model for C02 from fossil fuel combustion to realistically characterize
the interaction (or endogenous correlation) between the variables of these three models. A total of 115 input
variables were simulated for the uncertainty analysis of this source category (85 from the C02 emissions from fossil
fuel combustion inventory estimation model and 30 from the stationary source inventory models).
In developing the uncertainty estimation model, uniform distribution was assumed for all activity-related input
variables and N20 emission factors, based on the SAIC/EIA (2001) report.34 For these variables, the uncertainty
ranges were assigned to the input variables based on the data reported in SAIC/EIA (2001).35 However, the CH4
emission factors differ from those used by EIA. Since these factors were obtained from IPCC/UNEP/OECD/IEA
(1997), uncertainty ranges were assigned based on IPCC default uncertainty estimates (IPCC Good Practice
Guidance, 2000).
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-20. Stationary combustion
CH4 emissions in 2005 (including biomass) were estimated to be between 4.8 and 14.7 Tg C02 Eq. at a 95 percent
confidence level. This indicates a range of 30 percent below to 112 percent above the 2005 emission estimate of 6.9
Tg C02 Eq.36 Stationary combustion N20 emissions in 2005 (including biomass) were estimated to be between
10.8 and 39.9 Tg C02 Eq. at a 95 percent confidence level. This indicates a range of 22 percent below to 189
percent above the 2005 emissions estimate of 13.8 Tg C02 Eq.
Table 3-20: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Energy-Related Stationary
Combustion, Including Biomass (Tg C02 Eq. and Percent)
2005 Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower
Bound
Upper
Bound
Stationary Combustion
CH4
6.9
4.8 14.7
-30%
+112%
Stationary Combustion
n2o
13.8
10.8 39.9
-22%
+189%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
The uncertainties associated with the emission estimates of CH4 and N20 are greater than those associated with
estimates of C02 from fossil fuel combustion, which mainly rely on the carbon content of the fuel combusted.
34 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.
35 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.
36 The low emission estimates reported in this section have been rounded down to the nearest integer values and the high
emission estimates have been rounded up to the nearest integer values.
3-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Uncertainties in both CH4 and N20 estimates are due to the fact that emissions are estimated based on emission
2 factors representing only a limited subset of combustion conditions. For the indirect greenhouse gases, uncertainties
3 are partly due to assumptions concerning combustion technology types, age of equipment, emission factors used,
4 and activity data projections.
5 QA/QC and Verification
6 A source-specific QA/QC plan for stationary combustion was developed and implemented. This effort included a
7 Tier 1 analysis, as well as portions of a Tier 2 analysis. The Tier 2 procedures that were implemented involved
8 checks specifically focusing on the activity data and emission factor sources and methodology used for estimating
9 CH4, N20, and the indirect greenhouse gases from stationary combustion in the United States. Emission totals for
10 the different sectors and fuels were compared and trends were investigated.
11 Recalculations Discussion
12 Historical CH4 and N20 emissions from stationary sources (excluding C02) were revised due to several changes.
13 Slight changes to emission estimates for sectors are due to revised data from EIA (2006a). This revision is
14 explained in greater detail in the section on C02 Emissions from Fossil Fuel Combustion within this sector. Wood
15 consumption data from EIA (2006b) were revised for the commercial/institutional and residential sectors. The
16 combination of the methodological and historical data changes resulted in an average annual increase of 0.2 Tg C02
17 Eq. (2.0 percent) in CH4 emissions from stationary combustion and an average annual increase of 0.1 Tg C02 Eq.
18 (0.2 percent) in N20 emissions from stationary combustion for the period 1990 through 2004.
19 Planned Improvements
20 Several items are being evaluated to improve the CH4 and N20 emission estimates from stationary source
21 combustion and to reduce uncertainty. Efforts will be taken to work with EIA and other agencies to improve the
22 quality of the U.S. territories data. Because these data are not broken out by stationary and mobile uses, further
23 research will be aimed at trying to allocate consumption appropriately. In addition, the uncertainty of biomass
24 emissions will be further investigated since it was expected that the exclusion of biomass from the uncertainty
25 estimates would reduce the uncertainty; and in actuality the exclusion of biomass increases the uncertainty. These
26 improvements are not all-inclusive, but are part of an ongoing analysis and efforts to continually improve these
27 stationary estimates.
28 3.4. Mobile Combustion (excluding CO2) (IPCC Source Category 1A)
29 Mobile combustion produces greenhouse gases other than C02, including CH4, N20, as well as indirect greenhouse
30 gases including NOx, CO, and NMVOCs. As with stationary combustion, N20 and NOx emissions are closely
31 related to fuel characteristics, air-fuel mixes, combustion temperatures, and the use of pollution control equipment.
32 N20, in particular, can be formed by the catalytic processes used to control NOx, CO, and hydrocarbon emissions.
33 Carbon monoxide emissions from mobile combustion are significantly affected by combustion efficiency and the
34 presence of post-combustion emission controls. Carbon monoxide emissions are highest when air-fuel mixtures
35 have less oxygen than required for complete combustion. These emissions occur especially in idle, low speed, and
36 cold start conditions. CH4 and NMVOC emissions from motor vehicles are a function of the CH4 content of the
37 motor fuel, the amount of hydrocarbons passing uncombusted through the engine, and any post-combustion control
38 of hydrocarbon emissions (such as catalytic converters).
39 Emissions from mobile combustion were estimated by transport mode (e.g., highway, air, rail), fuel type (e.g. motor
40 gasoline, diesel fuel, jet fuel), and vehicle type (e.g. passenger cars, light-duty trucks). Road transport accounted for
41 the majority of mobile source fuel consumption, and hence, the majority of mobile combustion emissions. Table
Energy 3-29
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Public Review Draft
3-21 and Table 3-22 provide CH4 and N20 emission estimates- in Tg C02Eq.; Table 3-23 and Table 3-24 present
these estimates in Gg of each gas.37
Mobile combustion was responsible for a small portion of national CH4 emissions (0.5 percent) but was the second
largest source of U.S. N20 emissions (8 percent). From 1990 to 2005, mobile source CH4 emissions declined by 45
percent, to 2.6 Tg C02 Eq. (125 Gg), due largely to control technologies employed on highway vehicles since the
mid-1990s to reduce CO, NOx, NMVOC, and CH4 emissions. Mobile source emissions of N20 decreased by 13
percent, to 38.0 Tg C02 Eq. Earlier generation control technologies initially resulted in higher N20 emissions,
causing a 26 percent increase in N20 emissions from mobile sources between 1990 and 1998. Improvements in
later-generation emission control technologies have reduced N20 output, resulting in a 31 percent decrease in
mobile source N20 emissions from 1998 to 2005. As a result, N20 emissions in 2005 were 13 percent lower than in
1990, at 38.0 Tg C02 Eq. (123 Gg) (see Figure 3-17). Overall, CH4 and N20 emissions were predominantly from
gasoline-fueled passenger cars and light-duty trucks.
Figure 3-17: Mobile Source CH4 and N20 Emissions
Table 3-21: CH4 Emissions fromMobile Combustion (Tg C02 Eq.)
Fuel Type/Vehicle Type"
1990
I 19951
Gasoline Highway
4.2
3,8
Passenger Cars
2.6
2.1
Light-Duty Trucks
1.4
1.4
Heavy-Duty Vehicles
0.2 " '
0.2
Motorcycles
+1111
I +
Diesel Highway
+111
I +
Passenger Cars
+111
I +
Light-Duty Trucks
+I11I11
I +
Heavy-Duty Vehicles
+1III11
1 +
Alternative Fuel Highway
+1I1111
I +
Non-Highway
0.5
0.5
Ships and Boats
0.1
0.1
Locomotives
0.1
0.1
Farm Equipment
0.2 ' ' "
O.i
Construction Equipment
0.1
O.i
Aircraft
+II11II1
O.i
Otherb
0.1
i 0.11
Total
4.7 , ;
1 4.31
1 2000
2001
2002
2003
2004
2005
2.8
2.6
2.4
2.2
2.1
1.9
1.6
1.5
1.4
1.2
1.2
1.1
1.1
1.0
1.0
0.9
0.8
0.8
O.i
0.1
0.1
0.1
0.1
0.1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
0.6
0.6
0.6
0.6
0.6
0.6
O.i
0.1
0.1
0.1
0.1
0.1
O.i
0.1
0.1
0.1
0.1
0.1
0.2
0.1
0.1
0.1
0.1
0.1
O.i
0.1
0.1
0.1
0.1
0.1
O.i
0.1
0.1
0.1
0.1
0.1
! o.i
0.1
0.1
0.1
0.1
0.1
I 3.5
3.2
3.1
2.9
2.8
2.6
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
a See Annex 3.2 for definitions of highway vehicle types.
b "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
equipment, airport equipment, commercial equipment, and industrial equipment.
Table 3-22: N20 Emissions from Mobile Combustion (T^
; C02 Eq.)
Fuel Type/Vehicle Type
1990
i 1995
j 2000
2001
2002
2003
2004
2005
Gasoline Highway
40.1
49.8
| 48.8
45.5
42.8
39.5
36.7
33.4
Passenger Cars
25.4
26.9
24.7
23.2
21.9
20.3
18.8
17.0
Light-Duty Trucks
14.1
22.1
23.3
21.4
20.0
18.2
17.0
15.6
Heavy-Duty Vehicles
0.6
! 0.7
0.9
0.9
0.9
0.9
0.9
0.8
Motorcycles
+1111111
1 +1IIIB
J +
+
+
+
+
+
37 See Annex 3.2 for a complete time series of emission estimates for 1990 through 2005.
3-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
Public Review Draft
Diesel Highway
0.2
0.3
Passenger Cars
+llllil
+
Light-Duty Trucks
+lllll
+
Heavy-Duty Vehicles
0.2
0.2
Alternative Fuel Highway
0.1
0.1
Non-Highway
3.4
3.6
Ships and Boats
0.4
0.4
Locomotives
0.3
0.3
Farm Equipment
L71I1
1.7
Construction Equipment
0.2
0.3
Aircraft
0.3
0.4
Other*
0.4
0.5
Total
43.7
53.7
0.3
0.3
0.3
0.3
0.3
0.3
+
+
+
+
+
+
+
+
+
+
+
+
0.3
0.3
0.3
0.3
0.3
0.3
0.1
0.1
0.1
0.1
0.1
0.1
4.0
3.8
3.9
3.9
4.0
4.2
0.5
0.3
0.5
0.4
0.5
0.5
0.3
0.3
0.3
0.3
0.3
0.4
1.9
1.8
1.7
1.7
1.7
1.8
0.3
0.3
0.3
0.3
0.4
0.4
0.4
0.5
0.5
0.5
0.5
0.5
0.5
0.6
0.6
0.6
0.6
0.6
53.2
49.7
47.1
43.8
41.2
38.0
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
*"Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
equipment, airport equipment, commercial equipment, and industrial equipment.
Table 3-23: CH4 Emissions from Mobile Combustion (Gg)
Fuel Type/Vehicle Type
1990
1995)
Gasoline Highway
201
180
Passenger Cars
125
101
Light-Duty Trucks
65
69
Heavy-Duty Vehicles
10
9
Motorcycles
11I111
1
Diesel Highway
iH|
1
Passenger Cars
+11II11
+
Light-Duty Trucks
+11I1
+
Heavy-Duty Vehicles
iH|
1
Alternative Fuel Highway
+liil
+
Non-Highway
24
26
Ships and Boats
3I111
4
Locomotives
31111
3
Farm Equipment
71II11
7
Construction Equipment
41I1
5
Aircraft
21111
3
Other*
3
31
Total
226
1 207!
2000
2001
2002
2003
2004
2005
135
124
115
106
99
92
76
70
65
59
56
51
53
49
45
42
39
37
5
5
4
4
4
3
1
1
1
1
1
1
1
1
1
1
1
1
+
+
+
+
+
+
+
+
+
+
+
+
1
1
1
1
1
1
1
1
2
2
2
2
28
27
28
28
29
30
5
3
4
4
4
4
3
3
3
3
4
4
7
7
7
6
7
7
5
6
6
6
6
7
3
3
3
4
4
4
4
4
4
4
4
4
165
154
146
136
131
125
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
* "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
equipment, airport equipment, commercial equipment, and industrial equipment.
Table 3-24: N2Q Emissions from Mobile Combustion (Gg)
Fuel Type/Vehicle Type
1990
1995
2000
2001
2002
2003
2004
2005
Gasoline Highway
129
161
158
147
138
127
118
108
Passenger Cars
82
87 <
80
75
71
66
61
55
Light-Duty Trucks
45
1 7l^B
75
69
65
59
55
50
Heavy-Duty Vehicles
21111I
1 211I1I
3
3
3
3
3
3
Motorcycles
+JII
+
+
+
+
+
+
+
Diesel Highway
iH|
1
1
1
1
1
1
1
Passenger Cars
+11II11
1
+
+
+
+
+
+
Light-Duty Trucks
+11I1
1 +lllilll
+
+
+
+
+
+
Heavy-Duty Vehicles
illllill
1 1
1
1
1
1
1
1
Energy 3-31
-------
Public Review Draft
Alternative Fuel Highway
+¦¦¦¦
+¦¦¦¦
i +
+
+
+
+
+
Non-Highway
11
12
13
12
13
12
13
13
Ships and Boats
1llll
iH|
2
1
2
1
1
2
Locomotives
iH|
a
1
1
1
1
1
1
Farm Equipment
5^H
6
6
6
5
6
6
Construction Equipment
1111I
iH|[
1
1
1
1
1
1
Aircraft
1llllll
iH|
1
1
2
2
2
2
Other*
i
2
i 2
2
2
2
2
2
Total
141
173
1 172
160
152
141
133
123
1 + Less than 0.5 Gg
2 Note: Totals may not sum due to independent rounding.
3 * "Other" includes snowmobiles and other recreational equipment, logging equipment, lawn and garden equipment, railroad
4 equipment, airport equipment, commercial equipment, and industrial equipment.
5
6 Methodology
7 Estimates of CH4 and N20 emissions from mobile combustion were calculated by multiplying emission factors by
8 measures of activity for each fuel and vehicle type (e.g., light-duty gasoline trucks). Activity data included vehicle
9 miles traveled (VMT) for highway (on-road) vehicles and fuel consumption for non-road mobile sources. The
10 activity data and emission factors used are described in the subsections that follow. A complete discussion of the
11 methodology used to estimate emissions from mobile combustion and the emission factors used in the calculations
12 is provided in Annex 3.2.
13 EPA (2006c), EPA (2005) and EPA (2003) provide emission estimates of NOx, CO, and NMVOCs for eight
14 categories of highway vehicles,38 aircraft, and seven categories of non-highway vehicles.39 These emission
15 estimates primarily reflect EPA data, which, in final iteration, will be published on the National Emission Inventory
16 (NEI) Air Pollutant Emission Trends web site. The methodology used to develop these estimates can be found on
17 EPA's Air Pollutant Emission Trends website, at .
18 Highway Vehicles
19 Estimates of CH4 and N20 emissions from gasoline and diesel highway vehicles are based on VMT and emission
20 factors by vehicle type, fuel type, model year, and control technology. Emission estimates from alternative fuel
21 vehicles (AFVs)40 are based on VMT and emission factors by vehicle and fuel type.
22 Emission factors for gasoline and diesel highway vehicles utilizing Tier 2 and Low Emission Vehicle (LEV)
23 technologies were developed by ICF (2006b); all other gasoline and diesel highway vehicle emissions factors were
24 developed by ICF (2004). These factors were derived from EPA, California Air Resources Board (CARB) and
25 Environment Canada laboratory test results of different vehicle and control technology types. The EPA, CARB and
26 Environment Canada tests were designed following the Federal Test Procedure (FTP), which covers three separate
27 driving segments, since vehicles emit varying amounts of GHGs depending on the driving segment. These driving
28 segments are: (1) a transient driving cycle that includes cold start and running emissions, (2) a cycle that represents
29 running emissions only, and (3) a transient driving cycle that includes hot start and running emissions. For each test
38 These categories included: gasoline passenger cars, diesel passenger cars, light-duty gasoline trucks less than 6,000 pounds in
weight, light-duty gasoline trucks between 6,000 and 8,500 pounds in weight, light-duty diesel trucks, heavy-duty gasoline
trucks and buses, heavy-duty diesel trucks and buses, and motorcycles.
39 These categories included: locomotives, marine vessels, farm equipment, construction equipment, other off-highway liquid
fuel (e.g. recreational vehicles and lawn and garden equipment), and other off-highway gaseous fuel (e.g., other off-highway
equipment running on compressed natural gas).
40 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.
3-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 ran, a bag was affixed to the tailpipe of the vehicle and the exhaust was collected; the content of this bag was then
2 analyzed to determine quantities of gases present. The emissions characteristics of segment 2 were used to define
3 running emissions, and subtracted from the total FTP emissions to determine start emissions. These were then
4 recombined based upon the ratio of start to running emissions for each vehicle class from MOBILE6.2 to
5 approximate average driving characteristics.
6 Emission factors for AFVs were developed by ICF (2006a) after examining Argonne National Laboratory's GREET
7 1.7-Transportation Fuel Cycle Model (ANL 2006) and Lipman and Delucchi (2002). These sources describe AFV
8 emission factors in terms of ratios to conventional vehicle emission factors. Ratios of AFV to conventional vehicle
9 emissions factors were then applied to estimated Tier 1 emissions factors from light-duty gasoline vehicles to
10 estimate light-duty AFVs. Emissions factors for heavy-duty AFVs were developed in relation to gasoline heavy-
11 duty vehicles. A complete discussion of the data source and methodology used to determine emission factors from
12 AFVs is provided in Annex 3.2.
13 Annual VMT data for 1990 through 2005 were obtained from the Federal Highway Administration's (FHWA)
14 Highway Performance Monitoring System database as reported in Highway Statistics (FHWA 1996 through 2006).
15 VMT was then allocated from FHWA's vehicle categories to fuel-specific vehicle categories using the calculated
16 shares of vehicle fuel use for each vehicle category by fuel type reported in DOE (1993 through 2006) and
17 information on total motor vehicle fuel consumption by fuel type from FHWA (1996 through 2006). VMT for
18 AFVs were taken from Browning (2003). The age distributions of the U.S. vehicle fleet were obtained from EPA
19 (2006e) and EPA (2000), and the average annual age-specific vehicle mileage accumulation of U.S. vehicles were
20 obtained from EPA (2000).
21 Control technology and standards data for highway vehicles were obtained from EPA's Office of Transportation
22 and Air Quality (EPA 2006a, 2006b, 2000, 1998, and 1997) and Browning (2005). These technologies and
23 standards are defined in Annex 3.2, and were compiled from EPA (1993), EPA (1994a), EPA (1994b), EPA (1998),
24 EPA (1999a), and IPCC/UNEP/OECD/IEA (1997).
25 These emission estimates were obtained from preliminary data (EPA 2006c), and disaggregated based on EPA
26 (2003), which, in its final iteration, will be published on the National Emission Inventory (NEI) Air Pollutant
27 Emission Trends web site.
28 Non-Highway Vehicles
29 To estimate emissions from non-highway vehicles, fuel consumption data were employed as a measure of activity,
30 and multiplied by fuel-specific emission factors (in grams of N20 and CH4 per kilogram of fuel consumed).41
31 Activity data were obtained from AAR (2006), APTA (2006), BEA (1991 through 2005), Benson (2002 through
32 2004), DOE (1993 through 2006), DESC (2006), DOC (1991 through 2006), DOT (1991 through 2006), EIA
33 (2002a), EIA (2002b), EIA (2006a), EIA (2006b), EIA (2004), EIA (2003 through 2004), EIA (1991 through
34 2006), EPA (2006e), FAA (2006a and 2006b), and Whorton (2006). Emission factors for non-highway modes were
3 5 taken from IPCC/UNEP/OECD/IEA (1997).
36 Uncertainty
37 This section discusses the uncertainty of the emission estimates for CH4 and N20. Uncertainty was analyzed
38 separately for highway vehicles and non-highway vehicles due to differences in their characteristics and their
39 contributions to total mobile source emissions.
40 A quantitative uncertainty analysis was conducted for the highway portion of the mobile source sector using the
41 The consumption of international bunker fuels is not included in these activity data, but is estimated separately under the
International Bunker Fuels source category.
Energy 3-33
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
IPCC-recommended Tier 2 uncertainty estimation methodology, Monte Carlo Simulation technique, using @RISK
software. The uncertainty analysis was performed on 2005 estimates of CH4and N20 emissions, incorporating
probability distribution functions associated with the major input variables. For the purposes of this analysis, the
uncertainty was modeled for the following two major sets of input variables: (1) vehicle miles traveled (VMT) data,
by vehicle and fuel type and (2) emission factor data, by vehicle, fuel, and control technology type.
The emission factors for highway vehicles used in the Inventory were obtained from ICF (2006b) and ICF (2004).
These factors were based on laboratory testing of vehicles. While the controlled testing environment simulates real
driving conditions, emission results from such testing can only approximate real world conditions and emissions.
For some vehicle and control technology types, the testing did not yield statistically significant results within the 95
percent confidence interval, requiring expert judgment to be used in developing the emission factors. In those
cases, the emission factors were developed based on comparisons of fuel consumption between similar vehicle and
control technology categories.
The estimates of VMT for highway vehicles by vehicle type in the United States were provided by FHWA (1996
through 2006), and were generated through the cooperation of FHWA and state and local governments. While the
uncertainty associated with total U.S. VMT is believed to be low, the uncertainty within individual source
categories was assumed to be higher given uncertainties associated with apportioning total VMT into individual
vehicle categories, by fuel type, by technology type, and equipment age.
A significant amount of uncertainty is associated with the emission estimates for non-road sources. A primary
cause is a large degree of uncertainty regarding emission factors. The IPCC Good Practice Guidance reports that
CH4 emissions from aviation and marine sources may be uncertain by a factor of two, while N20 emissions may be
uncertain by an order of magnitude for marine sources and several orders of magnitude for aviation. No
information is provided on the uncertainty of emission factors for other non-highway sources.
Fuel consumption data have a lower uncertainty than emission factors, though large uncertainties do exist for
individual sources.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-25. Mobile combustion CH4
emissions in 2005 were estimated to be between 2.5 and 2.8 Tg C02 Eq. at a 95 percent confidence level (or in 19
out of 20 Monte Carlo Simulations). This indicates a range of 6 percent below to 6 percent above the 2005
emission estimate of 2.6 Tg C02 Eq. Also at a 95 percent confidence level, mobile combustion N20 emissions in
2005 were estimated to be between 31.0 and 45.0 Tg C02 Eq., indicating a range of 18 percent below to 19 percent
above the 2005 emission estimate of 38.0 Tg C02 Eq.
Table 3-25: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Mobile Sources (Tg C02
Eq. and Percent)
2005 Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Mobile Sources
ch4
2.6
2.5 2.8 -6% +6%
Mobile Sources
n2o
38.0
31.0 45.0 -18% +19%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
This uncertainty analysis is a continuation of a multi-year process for developing quantitative uncertainty estimates
for this source category using the IPCC Tier 2 approach to uncertainty analysis. As a result, as new information
becomes available, uncertainty characterization of input variables may be improved and revised.
QA/QC and Verification
A source-specific QA/QC plan for mobile combustion was developed and implemented. This effort included a Tier
1 analysis, as well as portions of a Tier 2 analysis. The Tier 2 procedures focused on the emission factor and
3-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Public Review Draft
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 historical data
used in calculating emissions in the current Inventory.
For highway sources, vehicle age distributions for 1999 to the present were revised based on new data obtained
from EPA's MOVES model (EPA 2006e). Diesel fractions for light trucks and medium-heavy trucks for 1998
through 2003 were updated based on data obtained from the Transportation Energy Data Book (DOE 2006). The
highway vehicle emissions estimation procedures now include a new gasoline vehicle emission control technology,
Tier 2, and updated emissions factors for LEVs (ICF 2006b). These changes resulted in a reduction in gasoline
highway vehicle emissions from 1996 onward, and most notably since 2002. In addition, revisions were made to
both the light-duty and heavy-duty alternative fuel vehicle (AFV) emissions factors (ICF 2006a), which resulted in
an increase in N20 emissions and a decrease in CH4 from AFVs. Lastly, VMT and fuel consumption estimates for
non-highway vehicles were revised for 2004 based on updated data from FHWA's Highway Statistics (FHWA 1996
through 2006).
Several improvements and updates were also made in the calculation of emissions from non-road vehicles.
Commercial aircraft energy consumption estimates now come from the Federal Aviation Administration's (FAA)
System for Assessing Aviation's Global Emissions (SAGE) database (FAA 2006b), rather than from the Bureau of
Transportation Statistics. This change increased estimates of fuel consumption and emissions attributed to
commercial aircraft, but does not affect the total aircraft emissions figures, since the "Other Aviation" category was
eliminated. Class II and III railroad diesel use estimates for 2002 and 2004 were obtained from the American Short
Line and Regional Railroad Association (Whorton 2006), instead of the Upper Great Plains Institute. EPA's
updated NONROAD model was used to recalculate fuel consumption for non-highway mobile sources.
As a result of these changes, average estimates of CH4 and N20 emissions from mobile combustion were slightly
higher—showing an increase of no more than 0.32 Tg C02 Eq. (less than 0.6 percent) each year—for the period
1990 through 2000. In contrast, emissions estimates were lower in every year between 2001 and 2004, compared to
last year's inventory. Specifically, estimates decreased 1.16 Tg C02 Eq. (2.4 percent) in 2003 and 1.83 Tg C02 Eq.
(4 percent) in 2004.
Planned Improvements
While the data used for this report represent the most accurate information available, four areas have been identified
that could potentially be improved in the short-term given available resources:
1) Improve estimation of VMT and fuel consumption by vehicle type (e.g., passenger car, light-duty truck, heavy-
duty truck, bus): Potential improvements in the breakdown of VMT and fuel consumption by vehicle type could be
developed based on further investigation of the methodologies and data sources used. Estimates of motor vehicle
travel and fuel consumption by vehicle type are taken from FHWA's Highway Statistics (FHWA 1996 to 2006),
which in turn are based on data from the Highway Performance Monitoring System, fuel tax receipts, Vehicle
Inventory and Use Survey (VIUS), and other sources. FHWA annually updates only the most recent year of
historical VMT and fuel consumption estimates (for instance, only the 2004 estimates in 2005 Highway Statistics
are recalculated, while 1990-2003 remain constant). Additional data might help to develop improved estimates of
historical VMT and fuel consumption by vehicle type going back through 1990. Moreover, the shares of VMT
associated with each vehicle type reported by FHWA are quite different from estimates used in EPA's MOBILE
model, and these differences should be investigated.
Energy 3-35
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
Public Review Draft
2) 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 by vehicle type to each fuel type on the
basis of fuel consumption. While this is a reasonable simplification, this approach implicitly assumes the same
average fuel economy for gasoline and diesel vehicles. A more accurate apportionment of VMT by fuel type for
light-duty trucks and medium/heavy-duty trucks could potentially be developed using data on vehicle travel from
the Vehicle Inventory and Use Survey (Census 2000) and other publications, or using VMT breakdowns by
vehicle/fuel type combinations from the MOBILE6 or MOVES models.
3) Continue the Reconciliation of Fuel Consumption Estimates used for Calculating N20/CH4 and C02: Estimates
of transportation fuel consumption by fuel type from EIA are used as the basis for estimating C02 emissions from
the transportation sector. These estimates are then apportioned to mode and vehicle category based on "bottom up"
estimates of fuel consumption from sources such as FHWA's Highway Statistics (FHWA 1996 through 2006) and
DOE's Transportation Energy Data Book (DOE 1993 through 2006). These sources are also used to develop N20
and CH4 estimates. The EPA fuel consumption estimates, however, differ from the estimates derived using "bottom
up" sources. For this Inventory, estimates of distillate fuel consumption have been reconciled. Potential
improvements include reconciling additional fuel consumption estimates from EIA and other data sources, and
revising the current process of allocating C02 emissions to particular vehicle types.
4) Continue to examine ways to utilize 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. The
use of MOVES should be further explored.
3.5. Coal Mining (IPCC Source Category 1B1a)
Three types of coal mining related activities release CH4 to the atmosphere: underground mining, surface mining,
and post-mining (i.e., coal-handling) activities. Underground coal mines contribute the largest share of CH4
emissions. All 115 gassy underground coal mines in the United States employ ventilation systems to ensure that
CH4 levels remain within safe concentrations. These systems can exhaust significant amounts of CH4 to the
atmosphere in low concentrations. Additionally, 24 U.S. coal mines supplement ventilation systems with
degasification systems. Degasification systems are wells drilled from the surface or boreholes drilled inside the
mine that remove large volumes of CH4 before, during, or after mining. In 2005, 13 coal mines collected CH4 from
degasification systems and sold this gas to a pipeline, thus reducing emissions to the atmosphere. In addition, one
coal mine used CH4 from its degasification system to heat mine ventilation air on site. Two of the coal mines that
sold gas to pipelines also used CH4 to generate electricity or fuel a thermal coal dryer. Surface coal mines also
release CH4 as the overburden is removed and the coal is exposed, but the level of emissions is much lower than
from underground mines. Finally, some of the CH4 retained in the coal after mining is released during processing,
storage, and transport of the coal.
Total CH4 emissions in 2005 were estimated to be 52.4 Tg C02 Eq. (2,494 Gg), a decline of 36 percent since 1990
(see Table 3-26 and Table 3-27). Of this amount, underground mines accounted for 68 percent, surface mines
accounted for 17 percent, and post-mining emissions accounted for 15 percent. The decline in CH4 emissions from
underground mines from 1996 to 2002 was the result of the reduction of overall coal production, the mining of less
gassy coal, and an increase in CH4 recovered and used. CH4 emissions increased slightly in 2003 due to additional
gas drainage being vented to the atmosphere and a reduction in CH4 recovery. Although overall emissions declined,
recovery decreased again in 2005 with reduced production from pre-drainage wells, increased use of horizontal gob
wells that are vented to the atmosphere, and temporary closure of a major project due to a mine fire. Surface mine
emissions and post-mining emissions remained relatively constant from 1990 to 2005.
Table 3-26: CH4 Emissions from Coal Mining (Tg C02 Eq.)
Activity
1990
1995
2000
2001
2002
2003
2004
2005
Underground Mining
62.1
49.2
39.1
38.1
35.4
35.8
37.9
35.6
Liberated
67.6
61.0
53.9
54.5
52.7
51.3
53.9
50.6
Recovered & Used
(5.6)
(12.4; (14.8)
(16.5)
(17.4)
(15.5)
(16.0)
(15.0)
3-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
Surface Mining
10.4 8
00
00
as
9.2
8.8
8.4
8.6
8.9
Post-Mining (Underground)
7.7 6
.9 6.7
6.8
6.4
6.4
6.6
6.4
Post-Mining (Surface)
1 " 1
4 1.4
1.5
1.4
1.4
1.4
1.4
Total
81.9 (.6
.5 55.9
55.5
52.0
52.1
54.5
52.4
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Table 3-27: CH4 Emissions from Coal Mining (Gg)
Activity
1990
I 1995
| 2000
2001
2002
2003
2004
2005
Underground Mining
2,955
2,343
1,860
1,812
1,684
1,707
1,803
1,696
Liberated
3,220
2,935
2,565
2,596
2,511
2,443
2,565
2,408
Recovered & Used
(265)
(592)
(704)
(784)
(827)
(736)
(762)
(712)
Surface Mining
497
425 , ,
417
438
420
402
411
425
Post-Mining (Underground)
367
| 328
317
323
304
305
315
305
Post-Mining (Surface)
81
1 69
| 68
71
68
65
67
69
Total
3,899
1 3,165
I 2,662
2,644
2,476
2,480
2,597
2,494
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
Methodology
The methodology for estimating CH4 emissions from coal mining consists of two parts. The first part involves
estimating CH4 emissions from underground mines. Because of the availability of ventilation system
measurements, underground mine emissions can be estimated on a mine-by-mine basis and then summed to
determine total emissions. The second step involves estimating emissions from surface mines and post-mining
activities by multiplying basin-specific coal production by basin-specific emission factors.
Underground mines. Total CH4 emitted from underground mines was estimated as the sum of CH4 liberated from
ventilation systems and CH4 liberated by means of degasification systems, minus CH4 recovered and used. The
Mine Safety and Heath Administration (MSHA) samples CH4 emissions from ventilation systems for all mines with
detectable42 CH4 concentrations. These mine-by-mine measurements are used to estimate CH4 emissions from
ventilation systems.
Some of the higher-emitting underground mines also use degasification systems (e.g., wells or boreholes) that
remove CH4 before, during, or after mining. This CH4 can then be collected for use or vented to the atmosphere.
Various approaches were employed to estimate the quantity of CH4 collected by each of the twenty-four mines
using these systems, depending on available data. For example, some mines report to EPA the amount of CH4
liberated from their degasification systems. For mines that sell recovered CH4 to a pipeline, pipeline sales data
published by state petroleum and natural gas agencies were used to estimate degasification emissions. For those
mines for which no other data are available, default recovery efficiency values were developed, depending on the
type of degasification system employed.
Finally, the amount of CH4 recovered by degasification systems and then used (i.e., not vented) was estimated. In
2005, thirteen active coal mines sold recovered CH4 into the local gas pipeline networks, while one coal mine used
recovered CH4 on site. Emissions avoided for these projects were estimated using gas sales data reported by various
state agencies. For most mines with recovery systems, companies and state agencies provided individual well
production information, which was used to assign gas sales to a particular year. For the few remaining mines, coal
mine operators supplied information regarding the number of years in advance of mining that gas recovery occurs.
Surface Mines and Post-Mining Emissions. Surface mining and post-mining CH4 emissions were estimated by
42 MSHA records coal mine methane readings with concentrations of greater than 50 ppm (parts per million) methane. Readings
below this threshold are considered non-detectable.
Energy 3-37
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
multiplying basin-specific coal production, obtained from the Energy Information Administration's Annual Coal
Report (see Table 3-28) (EIA 2006), by basin-specific emission factors. Surface mining emission factors were
developed by assuming that surface mines emit two times as much CH4 as the average in situ CH4 content of the
coal. Revised data on in situ CH4 content and emissions factors are taken from EPA (1996) and AAPG (1984).
This calculation accounts for CH4 released from the strata surrounding the coal seam. For post-mining emissions,
the emission factor was assumed to be 32.5 percent of the average in situ CH4 content of coals mined in the basin.
Table 3-28: Coal Production (Thousand Metric Tons)
Year Underground Surface Total
1990
2000
2001
2002
2003
2004
2005
384,250
338,173
345,305
324,219
320,047
333,449
334,404
546,818
635,592
676,142
667,619
651,251
674,551
691,460
931,068
973,765
1,021,446
991,838
971,297
1,008,000
1,025,864
Uncertainty
A quantitative uncertainty analysis was conducted for the coal mining source category using the IPCC-
recommended Tier 2 uncertainty estimation methodology. Because emission estimates from underground
ventilation systems were based on actual measurement data, uncertainty is relatively low. A degree of imprecision
was introduced because the measurements used were not continuous but rather an average of quarterly
instantaneous readings. Additionally, the measurement equipment used can be expected to have resulted in an
average of 10 percent overestimation of annual CH4 emissions (Mutmansky and Wang 2000). Estimates of CH4
liberated and recovered by degasification systems are relatively certain because many coal mine operators provided
information on individual well gas sales and mined through dates. Many of the recovery estimates use data on wells
within 100 feet of a mined area. Uncertainty also exists concerning the radius of influence of each well. The
number of wells counted, and thus the avoided emissions, may increase if the drainage area is found to be larger
than currently estimated.
Compared to underground mines, there is considerably more uncertainty associated with surface mining and post-
mining emissions because of the difficulty in developing accurate emission factors from field measurements.
However, since underground emissions comprise the majority of total coal mining emissions, the uncertainty
associated with underground emissions is the primary factor that determines overall uncertainty. The results of the
Tier 2 quantitative uncertainty analysis are summarized in Table 3-29. Coal mining CH4 emissions in 2005 were
estimated to be between 49.8 and 58.7 Tg C02 Eq. at a 95 percent confidence level. This indicates a range of 5
percent below to 12 percent above the 2005 emission estimate of 52.4 Tg C02 Eq.
Table 3-29: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Coal Mining (Tg C02 Eq. and
Percent)
2005 Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Lower Upper
Bound Bound
Bound Bound
Coal Mining
ch4
52.4
49.8 58.7
-5% +12%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
3-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Public Review Draft
Recalculations Discussion
In 2005, recalculations of emissions avoided at three Jim Walter Resources (JWR) coal mines in Alabama were
performed because the mining company provided mine maps describing mined-out areas for each month from 2000
through 2005. 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. Also in previous
inventories, emission reductions were calculated for pre-drainage wells that were located inside the mine plan
boundaries and were declared "shut-in" by the O&G Board. In recent years, JWR had mined-through numerous
pre-drainage wells that were subsequently converted to gob wells for further coal mine degasification. Because they
were never shut in, emissions avoided were not calculated.
The mine maps provided by JWR allowed for a more accurate accounting as to when and which pre-drainage wells
should be included in the emissions avoided calculations. As a result, recalculations were performed on years 2000
through 2004. The most pronounced changes to the inventory were made in the years 2003 through 2004, where
corrections led to an overall reduction of emissions in 2003 and 2004 by 2.7 and 1.8 Tg C02 Eq., respectively.
Minor changes were made to JWR emissions avoided for 1995 through 1996 as well.
For the current inventory, recalculations were performed on all years with negligible changes in 1994, 1996, and
1998 through 2002, as QA/QC of databases uncovered that emissions avoided had been miscalculated. Some
recalculations were done in 2003 on Alabama mines but were not linked retroactively. These recalculations either
led to no change in net emissions, or a change of 0.1 Tg C02 Eq. Emissions avoided for 2003 were adjusted
downward as a major operator reported in 2004 that double-counting of some pre-drainage wells had previously
occurred. Correction of this error led to a reduction in emissions avoided of 1.0 Tg C02 Eq., which contributed to
the reduction in emissions in 2003 from 54.8 to 52.1 Tg C02 Eq.
3.6. Abandoned Underground Coal Mines (IPCC Source Category 1B1a)
All underground and surface coal mining liberates CH4 as part of the normal mining operations. The amount of
CH4 liberated depends on the amount that resides in the coal ("in situ") and surrounding strata when mining occurs.
The in-situ CH4 content depends upon the amount of CH4 created during the coal formation (i.e., coalification)
process, and the geologic characteristics of the coal seams. During coalification, more deeply buried deposits tend
to generate more CH4 and retain more of the gas after uplift to minable depths. Deep underground coal seams
generally have higher CH4 contents than shallow coal seams or surface deposits.
Underground coal mines contribute the largest share of CH4 emissions, with active underground mines the leading
source of underground emissions. However, mines also continue to release CH4 after closure. As mines mature and
coal seams are mined through, mines are closed and abandoned. Many are sealed and some flood through intrusion
of groundwater or surface water into the void. Shafts or portals are generally filled with gravel and capped with a
concrete seal, while vent pipes and boreholes are plugged in a manner similar to oil and gas wells. Some abandoned
mines are vented to the atmosphere to prevent the buildup of CH4 that may find its way to surface structures through
overburden fractures. As work stops within the mines, the CH4 liberation decreases but it does not stop completely.
Following an initial decline, abandoned mines can liberate CH4 at a near-steady rate over an extended period of
time, or, if flooded, produce gas for only a few years. The gas can migrate to the surface through the conduits
described above, particularly if they have not been sealed adequately. In addition, diffuse emissions can occur
when CH4 migrates to the surface through cracks and fissures in the strata overlying the coal mine. The following
factors influence abandoned mine emissions:
• Time since abandonment;
• Gas content and adsorption characteristics of coal;
• CH4 flow capacity of the mine;
• Mine flooding;
• Presence of vent holes; and
• Mine seals.
Gross abandoned mine CH4 emissions ranged from 6.0 to 9.1 Tg C02Eq. from 1990 through 2005, varying, in
Energy 3-39
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
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.
Abandoned mine emissions peaked in 1996 (9.1 Tg C02Eq.) 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 2005, with only two closures in 2005. By 2005, abandoned mine emissions declined to
5.5 Tg C02Eq. (see Table 3-30 and Table 3-31).
Table 3-30: CH4 Emissions from Abandoned Coal Mines (Tg C02 Eq.)
Activity 1990
Abandoned Underground
Mines
Recovered & Used
I 1995
2000
2001
2002
2003
2004
2005
8.9
OO
00
8.1
7.7
7.5
7.3
7.0
! 0.7
1.5
1.5
1.6
1.5
1.5
1.4
Total 6.0 8.2 7.3 6.7 6.1 5.9 5.8 5.5
Note: Totals may not sum due to independent rounding.
Table 3-31: CH4 Emissions from Abandoned Coal Mines (Gg)
Activity
1990
I 1995
2000
2001
2002
2003
2004
2005
Abandoned Underground
287
421
387
367
354
345
331
Mines
422
Recovered & Used
0
1
72
70
75
72
70
68
Total
286
1 391
349
318
292
282
275
263
Note: Totals may not sum due to independent rounding.
Methodology
Estimating CH4 emissions from an abandoned coal mine requires predicting the emissions of a mine from the time
of abandonment through the inventory year of interest. The flow of CH4 from the coal to the mine void is primarily
dependent on the mine's emissions when active and the extent to which the mine is flooded or sealed. The CH4
emission rate before abandonment reflects the gas content of the coal, rate of coal mining, and the flow capacity of
the mine in much the same way as the initial rate of a water-free conventional gas well reflects the gas content of the
producing formation and the flow capacity of the well. Existing data on abandoned mine emissions through time,
although sparse, appear to fit the hyperbolic type of decline curve used in forecasting production from natural gas
wells.
In order to estimate CH4 emissions over time for a given mine, it is necessary to apply a decline function, initiated
upon abandonment, to that mine. In the analysis, mines were grouped by coal basin with the assumption that they
will generally have the same initial pressures, permeability and isotherm. As CH4 leaves the system, the reservoir
pressure, Pr, declines as described by the isotherm. The emission rate declines because the mine pressure (Pw) is
essentially constant at atmospheric pressure, for a vented mine, and the PI term is essentially constant at the
pressures of interest (atmospheric to 30 psia). A rate-time equation can be generated that can be used to predict
future emissions. This decline through time is hyperbolic in nature and can be empirically expressed as:
q = qi(l+bDit)("1/b)
where,
q = Gas rate at time t in mcf/d
q = Initial gas rate at time zero (to) in million cubic feet per day (mcfd)
b = The hyperbolic exponent, dimensionless
D = Initial decline rate, 1/yr
t = Elapsed time from tQ (years)
This equation is applied to mines of various initial emission rates that have similar initial pressures, permeability
and adsorption isotherms (EPA 2003).
3-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Public Review Draft
The decline curves are also affected by both sealing and flooding. Based on field measurement data, it was assumed
that most U.S. mines prone to flooding will become completely flooded within eight years and therefore no longer
have any measurable CH4 emissions. Based on this assumption, an average decline rate for flooding mines was
established by fitting a decline curve to emissions from field measurements. An exponential equation was
developed from emissions data measured at eight abandoned mines known to be filling with water located in two of
the five basins. Using a least squares, curve-fitting algorithm, emissions data were matched to the exponential
equation shown below. There was not enough data to establish basin-specific equations as was done with the
vented, non-flooding mines (EPA 2003).
where,
q = Gas flow rate at time t in mcf/d
q = Initial gas flow rate at time zero (to) in mcfd
D = Decline rate, 1/yr
t = Elapsed time from tQ (years)
Seals have an inhibiting effect on the rate of flow of CH4 into the atmosphere compared to the rate that would be
emitted if the mine had an open vent. The total volume emitted will be the same, but will occur over a longer
period. The methodology, therefore, treats the emissions prediction from a sealed mine similar to emissions from a
vented mine, but uses a lower initial rate depending on the degree of sealing. The computational fluid dynamics
simulator was again used with the conceptual abandoned mine model to predict the decline curve for inhibited flow.
The percent sealed is defined as 100 x (l - initial emissions from sealed mine / emission rate at abandonment prior
to sealing). Significant differences are seen between 50 percent, 80 percent and 95 percent closure. These decline
curves were therefore used as the high, middle, and low values for emissions from sealed mines (EPA 2003).
For active coal mines, those mines producing over 100 mcfd account for 98 percent of all CH4 emissions. This
same relationship is assumed for abandoned mines. It was determined that 440 abandoned mines closing after 1972
produced emissions greater than 100 mcfd when active. Further, the status of 264 of the 440 mines (or 60 percent)
is known to be either 1) vented to the atmosphere, 2) sealed to some degree (either earthen or concrete seals), or 3)
flooded (enough to inhibit CH4 flow to the atmosphere). The remaining 40 percent of the mines were placed in one
of the three categories by applying a probability distribution analysis based on the known status of other mines
located in the same coal basin (EPA 2003).
Inputs to the decline equation require the average emission rate and the date of abandonment. Generally this data is
available for mines abandoned after 1972; however, such data are largely unknown for mines closed before 1972.
Information that is readily available such as coal production by state and county are helpful, but do not provide
enough data to directly employ the methodology used to calculate emissions from mines abandoned after 1971. It is
assumed that pre-1972 mines are governed by the same physical, geologic, and hydrologic constraints that apply to
post-1972 mines; thus, their emissions may be characterized by the same decline curves.
During the 1970s, 78 percent of CH4 emissions from coal mining came from seventeen counties in seven states. In
addition, mine closure dates were obtained for two states, Colorado and Illinois, throughout the 20th century. The
data were used to establish a frequency of mine closure histogram (by decade) and applied to the other five states
with gassy mine closures. As a result, basin-specific decline curve equations were applied to 145 gassy coal mines
estimated to have closed between 1920 and 1971 in the United States, representing 78 percent of the emissions.
State-specific, initial emission rates were used based on average coal mine CH4 emissions rates during the 1970s
(EPA 2003).
Abandoned mines emission estimates are based on all closed mines known to have active mine CH4 ventilation
emission rates greater than 100 mcfd at the time of abandonment. For example, for 1990 the analysis included 145
mines closed before 1972 and 258 mines closed between 1972 and 1990. Initial emission rates based on MSHA
reports, time of abandonment, and basin-specific decline curves influenced by a number of factors were used to
calculate annual emissions for each mine in the database. Coal mine degasification data are not available for years
prior to 1990, thus the initial emission rates used reflect ventilation emissions only for pre-1990 closures. CH4
Energy 3-41
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
degasification amounts were added to ventilation data for the total CH4 liberation rate for fourteen mines that closed
between 1992 and 2005. 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 2005, emission totals were downwardly adjusted to reflect abandoned mine CH4 emissions avoided from
those mines. The inventory totals were not adjusted for abandoned mine reductions in 1990 through 1992, because
no data was reported for abandoned coal mining CH4 recovery projects during that time.
Uncertainty
A quantitative uncertainty analysis was conducted to estimate the uncertainty surrounding the estimates of
emissions from abandoned underground coal mines. The uncertainty analysis described below provides for the
specification of probability density functions for key variables within a computational structure that mirrors the
calculation of the inventory estimate. The results provide the range within which, with 95 percent certainty,
emissions from this source category are likely to fall.
As discussed above, the parameters for which values must be estimated for each mine in order to predict its decline
curve are: 1) the coal's adsorption isotherm; 2) CH4 flow capacity as expressed by permeability; and 3) pressure at
abandonment. Because these parameters are not available for each mine, a methodological approach to estimating
emissions was used that generates a probability distribution of potential outcomes based on the most likely value
and the probable range of values for each parameter. The range of values is not meant to capture the extreme
values, but values that represent the highest and lowest quartile of the cumulative probability density function of
each parameter. Once the low, mid, and high values are selected, they are applied to a probability density function.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-32. Abandoned coal mines
CH4 emissions in 2005 were estimated to be between 4.6 and 6.5 Tg C02 Eq. at a 95 percent confidence level. This
indicates a range of 16 percent below to 18 percent above the 2005 emission estimate of 5.5 Tg C02 Eq. One of the
reasons for the relatively narrow range is that mine-specific data is used in the methodology. The largest degree of
uncertainty is associated with the unknown status mines (which account for 40 percent of the mines), with a ±50
percent uncertainty.
Table 3-32: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Abandoned Underground Coal
Mines (Tg C02 Eq. and Percent)
2005 Emission
Uncertainty Range Relative to
Estimate
Emission Estimate"
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Abandoned Underground Coal Mines
ch4
5.5
4.6 6.5
-16% +18%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
Recalculations Discussion
Quality assurance/quality control of the calculation spreadsheets for the 1990 through 2004 inventory years revealed
an equation link that contained a minor error. The error was tracked back to the 1998 calculation worksheet and
carried through 2004. The equation was corrected and the emissions recalculated for 1998 through 2004. In
addition, a few other minor data corrections were completed during the recalculation process.
3.7. Petroleum Systems (IPCC Source Category 1B2a)
CH4 emissions from petroleum systems are primarily associated with crude oil production, transportation, and
refining operations. During each of these activities, CH4 is released to the atmosphere as fugitive emissions, vented
emissions, emissions from operational upsets, and emissions from fuel combustion. Total CH4 emissions from
petroleum systems in 2005 were 28.5 Tg C02 Eq. (1,357 Gg). Since 1990, emissions have declined by 17 percent,
due to a decline in domestic oil production and industry efforts to reduce emissions (see Table 3-33 and Table
3-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
3-34). The emission increase exhibited between 2004 and 2005 resulted from an increase in the number of offshore
platforms (primarily shallow water, but also deep water). The various sources of emissions are detailed below.
Production Field Operations. Production field operations account for over 97 percent of total CH4 emissions from
petroleum systems. Vented CH4 from field operations account for approximately 91 percent of the emissions from
the production sector, fugitive emissions account for 3.5 percent, combustion emissions 5.3 percent, and process
upset emissions, slightly over one-tenth of a percent. The most dominant sources of vented emissions are offshore
oil platforms (shallow and deep water platforms), field storage tanks and natural-gas-powered pneumatic devices
(low bleed and high bleed). These five sources alone emit over 86 percent of the production field operations
emissions. Offshore platform emissions are a combination of fugitive, vented, and combustion emissions from all
equipment housed on the platform for both oil and associated gas on those labeled as oil platforms. Emissions from
storage tanks occur when the CH4 entrained in crude oil under pressure volatilizes once the crude oil is put into
storage tanks at atmospheric pressure. Emissions from high and low-bleed pneumatics occur when pressurized gas
that is used for control devices is bled to the atmosphere as they cycle open and closed to modulate the system.
Two additional large sources, chemical injection pumps and gas engines, together account for nine percent of
emissions from the production sector. The remaining five percent of the emissions are distributed among 26
additional activities within the four categories: vented, fugitive, combustion and process upset emissions.
Crude Oil Transportation. Crude oil transportation activities account for less than one percent of total CH4
emissions from the oil industry. Venting from tanks and marine vessel loading operations accounts for 65 percent
of CH4 emissions from crude oil transportation. Fugitive emissions, almost entirely from floating roof tanks,
account for 18 percent. The remaining 17 percent is distributed among seven additional sources within these two
categories. Emissions from pump engine drivers and heaters were not estimated due to lack of data.
Crude Oil Refining. Crude oil refining processes and systems account for slightly over two percent of total CH4
emissions from the oil industry because most of the CH4 in crude oil is removed or escapes before the crude oil is
delivered to the refineries. There is an insignificant amount of CH4 in all refined products. Within refineries,
vented emissions account for about 87 percent of the emissions, while fugitive and combustion emissions account
for approximately six and seven percent respectively. Refinery system blowdowns for maintenance and the process
of asphalt blowing—with air, to harden the asphalt—arc the primary venting contributors. Most of the fugitive
methane emissions from refineries are from leaks in the fuel gas system. Refinery combustion emissions include
small amounts of unburned CH4 in process heater stack emissions and unburned CH4 in engine exhausts and flares.
Table 3-33: CH4 Emissions from Petroleum Systems (Tg C02 Eq.)
Activity
1990
I 1995
2000
2001
2002
2003
2004
2005
Production Field Operations
33.8
30.5
27.1
26.7
26.1
25.1
24.7
27.8
Pneumatic device venting
10.3
9.7
9.0
8.9
8.9
8.7
8.6
8.5
Tank Venting
3.8
3.4
3.2
3.2
3.2
3.2
3.0
2.8
Combustion & process upsets
1.9
1.7ll»
1.6
1.6
1.6
1.5
1.5
1.5
Misc. venting & fugitives
17.4
15.1
12.8
12.5
12.0
11.3
11.2
14.5
Wellhead fugitives
0.5 1
0.5
0.5
0.5
0.5
0.5
0.4
0.4
Crude Oil Transportation
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
Total
34.4
1 31.1
27.8
27.4
26.8
25.8
25.4
28.5
Note: Totals may not sum due to independent rounding.
Table 3-34: CH4 Emissions from Petroleum Systems (Gg)
Activity
1990
1 1995
2000
2001
2002
2003
2004
2005
Production Field Operations
1,609
1,450
1,292
1,271
1,242
1,196
1,176
1,324
Pneumatic device venting
489
463
428
425
424
412
408
406
Tank Venting
179
161
154
154
151
150
142
133
Combustion & process upsets
88
82
76
75
75
73
72
72
Misc. venting & fugitives
827 1
719
612
594
570
540
533
692
Wellhead fugitives
26
25
22
22
23
22
21
21
Energy 3-43
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Public Review Draft
Crude Oil Transportation 7 (> 555555
Refining 25 25 28 27 27 27 28 28
Total 1,640 1,482 1,325 1,303 1,275 1,229 1,209 1,357
Note: Totals may not sum due to independent rounding.
Methodology
The methodology for estimating CH4 emissions from petroleum systems is a bottom-up approach, based on
comprehensive studies of CH4 emissions from U.S. petroleum systems (EPA 1999, EPA 1996). These studies
combined emission estimates from 64 activities occurring in petroleum systems from the oil wellhead through crude
oil refining, including 33 activities for crude oil production field operations, 11 for crude oil transportation
activities, and 20 for refining operations. Annex 3.5 provides greater detail on the emission estimates for these 64
activities. The estimates of CH4 emissions from petroleum systems do not include emissions downstream of oil
refineries because these emissions are very small compared to CH4 emissions upstream of oil refineries.
The methodology for estimating CH4 emissions from the 64 oil industry activities employs emission factors initially
developed by EPA (1999) and activity factors that are based on two EPA studies (1996, 1999). Emissions are
estimated for each activity by multiplying emission factors (e.g., emission rate per equipment item or per activity)
by their corresponding activity factor (e.g., equipment count or frequency of activity). The report provides emission
factors and activity factors for all activities except those related to offshore oil production. For offshore oil
production, two emission factors were calculated using data collected over a one-year period for all federal offshore
platforms (EPA 2005, MMS 2005c). One emission factor is for oil platforms in shallow water, and one emission
factor is for oil platforms in deep water. Emission factors are held constant for the period 1990 through 2005. The
number of platforms in shallow water and the number of platforms in deep water are used as activity factors and are
taken from Minerals Management Service statistics (MMS 2005a,b,d).
Activity factors for years 1990 through 2005 were collected from a wide variety of statistical resources. For some
years, complete activity factor data were not available. In such cases, one of three approaches was employed.
Where appropriate, the activity factor was calculated from related statistics using ratios developed for EPA (1996).
For example, EPA (1996) found that the number of heater treaters (a source of CH4 emissions) is related to both
number of producing wells and annual production. To estimate the activity factor for heater treaters, reported
statistics for wells and production were used, along with the ratios developed for EPA (1996). In other cases, the
activity factor was held constant from 1990 through 2005 based on EPA (1999). Lastly, the previous year's data
were used when data for the current year were unavailable. See Annex 3.5 for additional detail.
Nearly all emission factors were taken from 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 1990-2005,1990-2006, 1995-2005, 1995-2006), 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, 2005a,b,d), ICF analysis of MMS (EPA 2005, MMS 2005c), the Oil & Gas Journal (OGJ 2005-2006) and the
United States Army Corps of Engineers (1995-2004).
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.
3-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 The detailed, bottom-up inventory analysis used to evaluate U.S. petroleum systems reduces the uncertainty related
2 to the CH4 emission estimates in comparison with a top-down approach. However, some uncertainty still remains.
3 Emission factors and activity factors are based on a combination of measurements, equipment design data,
4 engineering calculations and studies, surveys of selected facilities and statistical reporting. Statistical uncertainties
5 arise from natural variation in measurements, equipment types, operational variability and survey and statistical
6 methodologies. Published activity factors are not available every year for all 64 activities analyzed for petroleum
7 systems; therefore, some are estimated. Because of the dominance of five major sources, which account for 86
8 percent of the total emissions, the uncertainty surrounding these five sources has been estimated most rigorously,
9 and serves as the basis for determining the overall uncertainty of petroleum systems emission estimates.
10 The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 3-35. Petroleum systems CH4
11 emissions in 2005 were estimated to be between 21.7 and 70.7 Tg C02 Eq. at a 95 percent confidence level. This
12 indicates a range of 24 percent below to 148 percent above the 2005 emission estimate of 28.5 Tg C02 Eq.
13 Table 3-35: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petroleum Systems (Tg C02 Eq. and
14 Percent)
2005 Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
Source Gas
(Ts C02 Eq.)
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Petroleum Systems CH4
28.5
21.7 70.7 -24% +148%
15 a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
16
17 Recalculations Discussion
18 Two types of activity factor and activity driver revisions were made in the 2005 Petroleum Systems emissions
19 inventory. Some revisions were due to a change in data sources referenced, while some revisions were due to
20 updating previous years' data with revised data from existing data sources. Overall changes resulted in an annual
21 decrease of approximately 0.14 Tg C02 Eq. (0.6 percent) for 2003 and 0.26 Tg C02 Eq. (1 percent) for 2004,
22 relative to the previous inventory. For other years in the time series, the emission estimates increased by less than
23 0.1 percent.
24 Planned Improvements
25 A key improvement being contemplated is to include fugitive, vented, and combustion C02 emissions sources in the
26 Petroleum Systems inventory.
27 3.8. Natural Gas Systems (IPCC Source Category 1B2b)
28 The U.S. natural gas system encompasses hundreds of thousands of wells, hundreds of processing facilities, and
29 over a million miles of transmission and distribution pipelines. Overall, natural gas systems emitted 111.1 Tg C02
30 Eq. (5,292 Gg) of CH4 in 2005, an 11 percent decrease over 1990 emissions (see Table 3-36 and Table 3-37), and
31 28.2 Tg C02 Eq. (28,185Gg) of non-energy C02 in 2005, a 16 percent decrease over 1990 emissions (see Table
32 3-38). Improvements in management practices and technology, along with the replacement of older equipment,
33 have helped to stabilize emissions.
34 CH4 and non-energy C02 emissions from natural gas systems are generally process related, with normal operations,
35 routine maintenance, and system upsets being the primary contributors. Emissions from normal operations include:
36 natural gas engines and turbine uncombusted exhaust, bleed and discharge emissions from pneumatic devices, and
37 fugitive emissions from system components. Routine maintenance emissions originate from pipelines, equipment,
38 and wells during repair and maintenance activities. Pressure surge relief systems and accidents can lead to system
39 upset emissions. Below is a characterization of the four major stages of the natural gas system. Each of the stages
40 is described and the different factors affecting CH4 and non-energy C02 emissions are discussed.
Energy 3-45
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
Field Production. In this initial stage, wells are used to withdraw raw gas from underground formations. Emissions
arise from the wells themselves, gathering pipelines, and well-site gas treatment facilities such as dehydrators and
separators. Fugitive emissions and emissions from pneumatic devices account for the majority of CH4 emissions.
Flaring emissions account for the majority of the non-energy C02 emissions. Emissions from field production
accounted for approximately 32 percent of CH4 emissions and about 23 percent of non-energy C02 emissions from
natural gas systems in 2005.
Processing. In this stage, natural gas liquids and various other constituents from the raw gas are removed, resulting
in "pipeline quality" gas, which is injected into the transmission system. Fugitive CH4 emissions from compressors,
including compressor seals, are the primary emission source from this stage. The majority of non-energy C02
emissions come from acid gas removal units, which are designed to remove C02 from natural gas. Processing
plants account for about 11 percent of CH4 emissions and approximately 77 percent of non-energy C02 emissions
from natural gas systems.
Transmission and Storage. Natural gas transmission involves high pressure, large diameter pipelines that transport
gas long distances from field production and processing areas to distribution systems or large volume customers
such as power plants or chemical plants. Compressor station facilities, which contain large reciprocating and
turbine compressors, are used to move the gas throughout the United States transmission system. Fugitive CH4
emissions from these compressor stations and from metering and regulating stations account for the majority of the
emissions from this stage. Pneumatic devices and engine uncombusted exhaust are also sources of CH4 emissions
from transmission facilities.
Natural gas is also injected and stored in underground formations, or liquefied and stored in above ground tanks,
during periods of low demand (e.g., summer), and withdrawn, processed, and distributed during periods of high
demand (e.g., winter). Compressors and dehydrators are the primary contributors to emissions from these storage
facilities. CH4 emissions from the transmission and storage sector account for approximately 34 percent of
emissions from natural gas systems, while C02 emissions from transmission and storage account for less than 1
percent of the non-energy C02 emissions from natural gas systems.
Distribution. Distribution pipelines take the high-pressure gas from the transmission system at "city gate" stations,
reduce the pressure and distribute the gas through primarily underground mains and service lines to individual end
users. There were over 1,034,000 miles of distribution mains in 2005, an increase from just over 888,000 miles in
1990 (OPS 2006b). Distribution system emissions, which account for approximately 25 percent of CH4 emissions
from natural gas systems and less than 1 percent of non-energy C02 emissions, result mainly from fugitive
emissions from gate stations and non-plastic piping (cast iron, steel).43 An increased use of plastic piping, which has
lower emissions than other pipe materials, has reduced emissions from this stage. Distribution system CH4
emissions in 2005 were 12 percent lower than 1990 levels.
Table 3-36. CH4 Emissions from Natural Gas Systems (Tg C02 Eq.)*
Stage
1990
1995
2000
2001
2002
2003
2004
2005
Field Production
31.8
36/.
38.5
41.2
42.4
40.9
38.0
35.2
Processing
14.8
14.<>
14.5
14.7
14.1
13.5
13.5
11.9
Transmission and Storage
46.8
46.
44.1
41.0
42.5
42.3
40.6
36.8
Distribution
31.0
30.:
29.4
28.6
25.9
27.0
26.9
27.4
Total
124.5
1 128.1
126.6
125.4
125.0
123.7
119.0
111.1
*Inchiding CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.
Note: Totals may not sum due to independent rounding.
Table 3-37. CH4 Emissions from Natural Gas Systems (Gg)*
43 The percentages of total emissions from each stage may not sum to 100 percent due to independent rounding.
3-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
Stage
1990
1995
2000
2001
2002
2003
2004
2005
Field Production
1,514
1 1;745
1,832
1,963
2,021
1,949
1,811
1,675
Processing
706
70<>
692
698
673
645
643
564
Transmission and Storage
2,230
2,205
2,102
1,950
2,025
2,013
1,934
1,751
Distribution
1,477
1,442
1,401
1,360
1,231
1,284
1,281
1,303
Total 5,927 6,101 6,027 5,971 5,951 5,891 5,669 5,292
*Inchiding CH4 emission reductions achieved by the Natural Gas STAR program and NESHAP regulations.
Note: Totals may not sum due to independent rounding.
Table 3-38. Non-energy C02 Emissions from Natural Gas Systems (Tg C02 Eq.)
Stage
1990
1995
2000
2001
2002
2003
2004
2005
Field Production
5.9
9.1
6.0
6.3
6.5
6.3
6.3
6.4
Processing
27.8
24.(>
23.3
22.4
23.1
22.0
21.8
21.7
Transmission and Storage
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
28.2
28.2
Note: Totals may not sum due to independent rounding.
Table 3-39. Non-energy C02 Emissions from Natural Gas Systems (Gg)
Stage
1990
1995
2000
2001
2002
2003
2004
2005
Field Production
5,876
9,083
5,955
6,307
6,462
6,341
6,309
6,350
Processing
27,752
24,621
23,333
22,387
23,066
22,002
21,780
21,736
Transmission and Storage
58
1 60M
61
59
62
61
62
60
Distribution
43
42
41
40
40
40
40
39
Total
33,729
33,807
29,390
28,793
29,630
28,445
28,190
28,185
Note: Totals may not sum due to independent rounding.
Methodology
The primary basis for estimates of CH4 and non-energy related C02 emissions from the U.S. natural gas industry is
a detailed study by the Gas Research Institute and EPA (EPA/GRI 1996). The EPA/GRI study developed over 80
CH4 emission and activity factors to characterize emissions from the various components within the operating stages
of the U.S. natural gas system. The same activity factors were used to estimate both CH4 and non-energy C02
emissions. However, the CH4 emission factors were adjusted for C02 content when estimating fugitive and vented
non-energy C02 emissions. The EPA/GRI study was based on a combination of process engineering studies and
measurements at representative gas facilities. From this analysis, a 1992 emission estimate was developed using the
emission and activity factors. For other years, a set of industry activity factor drivers was developed that can be
used to update activity factors. These drivers include statistics on gas production, number of wells, system
throughput, miles of various kinds of pipe, and other statistics that characterize the changes in the U.S. natural gas
system infrastructure and operations.
See Annex 3.4 for more detailed information on the methodology and data used to calculate CH4 and non-energy
C02 emissions from natural gas systems.
Activity factor data were taken from the following sources: American Gas Association (AGA 1991-1998);
American Petroleum Institute (API 2005); Minerals and Management Service (MMS 2006a-e); Monthly Energy
Review (EIA 2006e); Natural Gas Liquids Reserves Report (EIA 2005); Natural Gas Monthly (EIA 2006c,d,f); the
Natural Gas STAR Program annual emissions savings (EPA 2006); Oil and Gas Journal (OGJ 1997-2006); Office
of Pipeline Safety (OPS 2006a-b) and other Energy Information Administration publications (EIA 2004, 2006a,b,g);
World Oil Magazine (2006a-b). Data for estimating emissions from hydrocarbon production tanks is incorporated
(EPA 1999). Coalbed CH4 well activity factors were taken from the Wyoming Oil and Gas Conservation
Commission (Wyoming 2006) and the Alabama State Oil and Gas Board (Alabama 2006). Other state well data
was taken from: American Association of Petroleum Geologists (AAPG 2004); Brookhaven College (Brookhaven
2004); Kansas Geological Survey (Kansas 2006); Montana Board of Oil and Gas Conservation (Montana 2006);
Energy 3-47
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
Oklahoma Geological Survey (Oklahoma 2006); Morgan Stanley (Morgan Stanley 2005); Rocky Mountain
Production Report (Lippman (2003); New Mexico Oil Conservation Division (New Mexico 2006a,b); Texas
Railroad Commission (Texas 2006a-d); Utah Division of Oil, Gas and Mining (Utah 2006). Emission factors were
taken from EPA/GRI (1996). GRI's Unconventional Natural Gas and Gas Composition Databases (GRI2001) were
used to adapt the CH4 emission factors into non-energy related C02 emission factors. Additional information about
C02 content in transmission quality natural gas was obtained via the internet from numerous U.S. transmission
companies to help further develop the non-energy C02 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 are
summarized in Table 3-40. Natural gas systems CH4 emissions in 2005 were estimated to be between 82.2 and
144.4 Tg C02 Eq. at a 95 percent confidence level. Natural gas systems non-energy C02 emissions in 2005 were
estimated to be between 20.8 and 36.5 Tg C02 Eq. at 95 percent confidence level.
Table 3-40: Tier 2 Quantitative Uncertainty Estimates for CH4 and Non-energy C02 Emissions from Natural Gas
2005
Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
Source
Gas
(T2 C02 Eq.)
(T2 C02 Eq.)
(%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Natural Gas Systems
ch4
111.1
82.2
144.4
-26%
+30%
Natural Gas Systems'3
C02
28.2
20.8
36.5
-26%
+30%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
b An uncertainty analysis for the non-energy C02 emissions was not performed. The relative uncertainty estimated (expressed as
a percent) from the CH4 uncertainty analysis was applied to the point estimate of non-energy C02 emissions.
Recalculations Discussion
Significant changes were made to the emission calculations in the Production sector. The first change implemented
was to incorporate a variable CH4 content of the natural gas produced in the United States to the emission factors of
the production sector. In the past, CH4 content for the emission factors was kept constant for each year and
different National Energy Modeling System (NEMS) regions. For the revised method, the CH4 content is first
estimated in two base years, 1990 and 1995, using GRI and GTI data source estimates, respectively. Then the CH4
content for other years in the time series 1990 through 2005 are driven by the natural gas production for each state
and year. Each NEMS region's CH4 content is calculated separately to reflect the differences in the reservoir basins
around the country. The net effect of this restructuring on the historical emission estimates is an average 3 percent
increase in emissions. The varying CH4 content in each region added another source of uncertainty to the
uncertainty analysis.
The second change to the production sector of the inventory was replacement of activity factors for five sources:
separators, heaters, pneumatic devices, chemical injection pumps and compressors. The new activity factors were
developed by re-organizing the original GRI activity factor data into the new NEMS production regions. The net
3-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 effect of this change is a 2 percent decrease in 2004 emission estimates.
2 Another change in the estimates for the current Inventory is the accounting of CH4 emission reductions from U.S.
3 EPA National Emissions Standards for Hazardous Air Pollutants (NESHAP) regulations, which is the civil
4 enforcement of the Maximum Achievable Control Technology or MACT standard. These federal regulations were
5 enacted in 1999 and require a 95 percent reduction of emissions from dehydrator vents and condensate tanks with
6 throughputs above the threshold levels set by the regulation. The inventory methodology now incorporates these
7 emission reductions when describing the total emissions from natural gas systems. Overall, the net effect on the
8 historical CH4 emission estimates from this change is less than an average 1 percent decrease in emissions since
9 1999.
10 Finally, the inventory now contains estimates for non-energy related (vented, fugitive, flared) C02 emissions from
11 the natural gas industry. The estimation uses the same activity and emission factors as the CH4 emission estimates
12 but adjusts the emission factors using the ratio of C02/CH4 content of the natural gas. Efforts were made to ensure
13 that there was no double-accounting of C02 emissions from other systems reported elsewhere in the U.S. inventory.
14 The combination of these methodological and historical data changes resulted in an average annual decrease of 0.3
15 Tg C02 Eq. (0.3 percent) in CH4 emissions from natural gas systems for the period 1990 through 2004.
16 Planned Improvements
17 One improvement being contemplated involves a trend analysis for the time series. As discussed above, the natural
18 gas systems inventory now reflects changing emissions factors based on changing methane content in natural gas in
19 different NEMS regions. The uncertainty analysis, for the sake of simplicity, currently assumes a constant
20 uncertainty across all years in the emissions time series. A trend analysis reflecting changing uncertainty in the time
21 series will be conducted to more closely follow the IPCC Guidelines. Additional improvements include developing
22 region specific emission and activity factors and incorporating any new data that becomes available from new
23 studies in the future into the emissions estimates model.
24
25 [BEGIN BOX]
26 Box 3-3. Carbon Dioxide Transport, Injection, and Geological Storage
27 Carbon dioxide is produced, captured, transported, and used for Enhanced Oil Recovery (EOR) as well as
28 commercial and non-EOR industrial applications. This C02 is produced from both naturally-occurring C02
29 reservoirs and from industrial sources such as natural gas processing plants and ammonia plants. In the current
30 Inventory, emissions from naturally-produced C02 are estimated based on the application.
31 In the current Inventory report, the C02 that is used in non-EOR industrial and commercial applications (e.g., food
32 processing, chemical production) is assumed to be emitted to the atmosphere during its industrial use. These
33 emissions are discussed in the Carbon Dioxide Consumption section. The naturally-occurring C02 used in EOR
34 operations is assumed to be fully sequestered. Additionally, all anthropogenic C02 emitted from gas processing and
35 ammonia plants is assumed to be emitted to the atmosphere, regardless of whether the C02 is captured or not. These
36 emissions are currently included in the Natural Gas Systems and the Ammonia Manufacture and Urea Application
37 sections of the Inventory report, respectively.
38 IPCC (2006) includes, for the first time, methodological guidance to estimate emissions from the capture, transport,
39 injection, and geological storage of C02. The methodology is based on the principle that the carbon capture and
40 storage system should be handled in a complete and consistent manner across the entire Energy sector. The
41 approach accounts for C02 captured at natural and industrial sites as well as emissions from capture, transport, and
42 use. For storage specifically, a Tier 3 methodology is outlined for estimating and reporting emissions based on site-
43 specific evaluations. If site-specific monitoring and reporting data are not available, and the carbon capture and
44 storage system cannot, therefore, be considered in a complete and consistent manner, the assumptions that the
Energy 3-49
-------
Public Review Draft
1 captured C02 is emitted. The assumption that, in the absence of site specific data, all C02 injected in storage sites is
2 emitted is opposite from the current methodology implemented by the United States. The new methodology will not
3 affect emission estimates for C02 consumption for non-EOR applications.
4 The United States initiated data collection efforts to incorporate this new methodology for the current Inventory
5 report. However, time was not sufficient to fully implement this guidance and the estimates are not yet included in
6 national totals. Preliminary estimates indicate that the amount of C02 emitted from EOR operations and pipelines is
7 35.2 Tg C02 (35,156 Gg C02) (see Table 3-41). Site-specific monitoring and reporting data for C02 injection sites
8 (i.e., EOR operations) were not readily available. Therefore, these estimates assume all C02 is emitted. The United
9 States is initiating a process to collect the necessary data to fully implement the 2006 IPCC Guidelines methodology
10 for this source category in subsequent inventory reports.
11 Table 3-41: Emissions of C02 from EOR Operations and Pipelines (Tg C02 Eq.)
Year
1990
1995
2000
2001
2002
2003
2004
2005
Acid Gas Removal Plants
4 S
3.7
2.3
2.9
2.9
3.0
3.7
6.0
Naturally Occurring C02
20.:-
22.7
22.7
23.0
21.9
24.3
27.1
28.5
Ammonia Production Plants
0.0
0.7
0.7
0.7
0.7
0.7
0.7
0.7
Pipelines Transporting C02
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Total
25.6
27.0
25.6
26.6
25.5
28.0
31.5
35.2
12
Table 3-42: Emissions of C02 from EOR Operations and Pipelines (Gg)
Year
1990
I 1995
2000
2001
2002
2003
2004
2005
Acid Gas Removal Plants
4,832
3,672
2,264
2,894
2,943
2,993
3,719
5,992
Naturally Occurring C02
20,752
22,687
22,649
23,015
21,854
24,273
27,085
28,481
Ammonia Production Plants
0
676
676
676
676
676
676
676
Pipelines Transporting C02
8
8
8
8
8
8
7
7
Total
25,592
1 27,044
25,598
26,593
25,482
27,951
31,489
35,156
14 [END BOX]
15 3.9. Municipal Solid Waste Combustion (IPCC Source Category 1A5)
16 Combustion is used to manage about 7 to 17 percent of the municipal solid wastes (MSW) generated in the United
17 States, depending on the source of the estimate and the scope of materials included in the definition of solid waste
18 (EPA 2000b, Goldstein and Matdes 2001, Kaufman et al. 2004a, Simmons et al. 2006). Almost all combustion of
19 MSW in the United States occurs at waste-to-energy facilities where useful energy is recovered, and thus emissions
20 from waste combustion are accounted for in the Energy chapter. Combustion of municipal solid wastes results in
21 conversion of the organic inputs to C02. According to IPCC guidelines, when the C02 emitted is of fossil origin, it
22 is counted as a net anthropogenic emission of C02 to the atmosphere. Thus, the emissions from waste combustion
23 are calculated by estimating the quantity of waste combusted and the fraction of the waste that is C derived from
24 fossil sources.
25 Most of the organic materials in municipal solid wastes are of biogenic origin (e.g., paper, yard trimmings), and
26 have their net C flows accounted for under the Land Use, Land-Use Change, and Forestry chapter. However, some
27 components—plastics, synthetic rubber, synthetic fibers, and carbon black—are of fossil origin. Plastics in the U.S.
28 waste stream are primarily in the form of containers, packaging, and durable goods. Rubber is found in durable
29 goods, such as carpets, and in non-durable goods, such as clothing and footwear. Fibers in municipal solid wastes
30 are predominantly from clothing and home furnishings. Tires (which contain rubber and carbon black) are also
31 considered a "non-hazardous" waste and are included in the municipal solid waste combustion estimate, though
32 waste disposal practices for tires differ from the rest of municipal solid waste.
33 Approximately 34 million metric tons of municipal solid wastes were combusted in the United States in 2005
34 (Simmons et al. 2006). C02 emissions from combustion of municipal solid wastes rose 91 percent since 1990, to an
35 estimated 20.9 Tg C02 Eq. (20,912 Gg) in 2005, as the volume of plastics and other fossil C-containing materials in
3-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
MSW increased (see Table 3-43 and Table 3-44). Waste combustion is also a source of N20 emissions (De Soete
1993). N20 emissions from municipal solid waste combustion were estimated to be 0.5 Tg C02 Eq. (2 Gg N20) in
2005, and have not changed significantly since 1990.
Table 3-43: C02 and N2Q Emissions from Municipal Solid Waste Combustion (Tg C02 Eq.)
Gas/Waste Product
1990
i 1995
2000
2001
2002
2003
2004
2005
co2
10.9
15,7
17.9
18.3
18.5
19.5
20.1
20.9
Plastics
8.0
10.3
12.1
12.4
12.4
13.0
13.4
13.9
Synthetic Rubber in Tires
0.2
0.8
0.9
0.9
1.0
1.0
1.1
1.2
Carbon Black in Tires
0.2
1.1
1.2
1.2
1.2
1.3
1.4
1.6
Synthetic Rubber in MSW
1.3
1.6
1.7
1.8
1.8
1.9
1.9
1.9
Synthetic Fibers
1.2
1.8
2.1
2.1
2.2
2.3
2.3
2.4
n2o
0.5
1 0.5
0.4
0.5
0.5
0.5
0.5
0.5
Total
11.4
1 16.2
i 18.3
18.8
19.0
20.0
20.6
21.4
Table 3-44: C02 and N2Q Emissions from Municipal Solid Waste Combustion (Gg)
Gas/Waste Product
1990
1995
2000
2001
2002
2003
2004
2005
co2
10,950
15,712
17,889
18,344
18,513
19,490
20,115
20,912
Plastics
7,976
10,347
12,068
12,378
12,365
12,984
13,381
13,852
Synthetic Rubber in Tires
191
841
893
895
952
1,010
1,108
1,207
Carbon Black in Tires
249
1,099
1,167
1,170
1,245
1,320
1,449
1,579
Synthetic Rubber in MSW
1,334
1,596
1,678
1,762
1,767
1,862
1,875
1,899
Synthetic Fibers
1,200
1,830
2,083
2,139
2,184
2,315
2,302
2,375
n2o
2
1
1
1
2
2
2
2
Methodology
Emissions of C02 from MSW combustion include C02 generated by the combustion of plastics, synthetic fibers,
and synthetic rubber, as well as the combustion of synthetic rubber and carbon black in tires. These emissions were
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 C02 were calculated based on the number of scrap tires used for
fuel and the synthetic rubber and carbon black content of the tires.
More detail on the methodology for calculating emissions from each of these waste combustion sources is provided
in Annex 3.6.
For each of the methods used to calculate C02 emissions from municipal solid waste combustion, data on the
quantity of product combusted and the C content of the product are needed. For plastics, synthetic rubber, and
synthetic fibers, the amount of material in municipal solid wastes and its portion combusted were taken from the
Characterization of Municipal Solid Waste in the United States (EPA 2000b, 2002, 2003, 2005a, 2006b) 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, 2001, 2002, 2003, 2006).
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).
Energy 3-51
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
The assumption that 98 percent of organic C is oxidized (which applies to all municipal solid waste combustion
categories for C02 emissions) was reported in the EPA's life cycle analysis of greenhouse gas emissions and sinks
from management of solid waste (EPA 2006a).
Combustion of municipal solid waste also results in emissions of N20. These emissions were calculated as a
function of the total estimated mass of municipal solid waste combusted and an emission factor. The N20 emission
estimates are based on different data sources. As noted above, N20 emissions are a function of total waste
combusted in each year; for 1990 through 2005, these data were derived from the information published in BioCycle
(Simmons et al. 2006). Data on total waste combusted was not available for 2005, so the value for 2005 was
assumed to equal the most recent value available (2004). Table 3-45 provides data on municipal solid waste
generation and percentage combustion for the total waste stream. The emission factor of N20 emissions per
quantity of municipal solid waste combusted is an average of values from IPCC's Good Practice Guidance (2000).
Table 3-45: Municipal Solid Waste Generation (Metric Tons) and Percent Combusted
Year Waste Generation Combusted (%)
1990 266,365,714 11.5
2000 371,071,109 7.0
2001 404,520,472a 7.4a
2002 437,969,836 7.7
2003 449,937,860b 7.6b
2004 461,905,884 7.4
200 5 461,905,884° 7.4C
a Interpolated between 2000 and 2002 values.
b Interpolated between 2002 and 2004 values.
c Assumed equal to 2004 value.
Uncertainty
A Tier 2 Monte Carlo analysis was performed to determine the level of uncertainty surrounding the estimates of
C02 emissions and N20 emissions from municipal solid waste combustion. IPCC Tier 2 analysis allows the
specification of probability density functions for key variables within a computational structure that mirrors the
calculation of the inventory estimate. Uncertainty estimates and distributions for waste generation variables (i.e.,
plastics, synthetic rubber, and textiles generation) were obtained through a conversation with one of the authors of
the Municipal Solid Waste in the United States reports. Statistical analyses or expert judgments of uncertainty were
not available directly from the information sources for the other variables; thus, 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 N20 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 3-46. Municipal solid waste
combustion C02 emissions in 2005 were estimated to be between 15.5 and 25.0 Tg C02 Eq. at a 95 percent
confidence level. This indicates a range of 26 percent below to 19 percent above the 2005 emission estimate of 20.9
Tg C02 Eq. Also at a 95 percent confidence level, municipal solid waste combustion N20 emissions in 2005 were
estimated to be between 0.14 and 1.34TgC02Eq. This indicates a range of 74 percent below to 153 percent above
the 2005 emission estimate of 0.53 Tg C02 Eq.
3-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Public Review Draft
Table 3-46: Tier 2 Quantitative Uncertainty Estimates for C02 and N20 from Municipal Solid Waste Combustion
(Tg C02 Eg. and Percent)
2005
Emission
Uncertainty Range Relative to Emission
Estimate
Estimate"
Source
Gas
(Ts C02 Eq.)
(Ts C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Municipal Solid Waste Combustion
C02
20.9
15.5 25.0 -26% +19%
Municipal Solid Waste Combustion
n2o
0.5
0.1 1.3 -74% +153%
a Range of emission estimates predicted by Monte Carlo Simulation for a 95 percent confidence interval.
QA/QC and Verification
A source-specific QA/QC plan for 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. Corrective actions were taken to rectify minor errors and to
improve the transparency of the calculations, facilitating future QA/QC.
3.10. Energy Sources of Indirect Greenhouse Gas Emissions
In addition to the main greenhouse gases addressed above, many energy-related activities generate emissions of
indirect greenhouse gases. Total emissions of nitrogen oxides (NOx), carbon monoxide (CO), and non-CH4 volatile
organic compounds (NMVOCs) from energy-related activities from 1990 to 2005 are reported in Table 3-47.
Table 3-47: NOx, CO, and NMVOC Emissions from Energy-Related Activities (Gg)
Gas/Source
1990
1995
2000
2001
2002
2003
2004
2005
NOx
21,024
20,631
18,537
17,714
17,569
16,753
15,886
15,385
Mobile Combustion
10,920
10,622
10,310
9,819
10,319
9,911
9,520
9,145
Stationary Combustion
9,883
9,821
8,002
7,667
6,837
6,428
5,952
5,824
Oil and Gas Activities
139
100
111
113
316
317
317
318
Waste Combustion
82
88
114
114
97
98
98
98
International Bunker Fuels*
1,985
1,540
1,334
1,266
988
900
1,179
1,155
CO
125,759
1104,527
89,835
86,167
84,369
81,832
79,435
77,173
Mobile Combustion
119,480
97,755
83,680
79,972
77,382
74,756
72,269
69,915
Stationary Combustion
5,000
5,383
4,340
4,377
5,224
5,292
5,361
5,431
Waste Combustion
978
1 073
1,670
1,672
1,440
1,457
1,475
1,493
Oil and Gas Activities
302
316
146
147
323
327
331
335
International Bunker Fuels*
115
113
124
120
118
112
124
122
NMVOCs
12,620
10,538
8,953
8,610
9,131
8,827
8,538
8,263
Mobile Combustion
10,932
8,745
7,230
6,872
6,608
6,302
6,011
5,734
Stationary Combustion
912
973
1,077
1,080
1,733
1,734
1,735
1,736
Oil and Gas Activities
554
582
389
400
546
547
547
548
Waste Combustion
222
237
257
258
244
244
244
245
International Bunker Fuels*
59
48
44
42
35
32
40
40
* These values are presented for informational purposes only and are not included in totals.
Note: Totals may not sum due to independent rounding.
Methodology
These emission estimates were obtained from preliminary data (EPA 2006), and disaggregated based on EPA
Energy 3-53
-------
Public Review Draft
1 (2003), which, in its final iteration, will be published on the National Emission Inventory (NEI) Air Pollutant
2 Emission Trends web site. Emissions were calculated either for individual categories or for many categories
3 combined, using basic activity data (e.g., the amount of raw material processed) as an indicator of emissions.
4 National activity data were collected for individual categories from various agencies. Depending on the category,
5 these basic activity data may include data on production, fuel deliveries, raw material processed, etc.
6 Activity data were used in conjunction with emission factors, which together relate the quantity of emissions to the
7 activity. Emission factors are generally available from the EPA's Compilation of Air Pollutant Emission Factors,
8 AP-42 (EPA 1997). The EPA currently derives the overall emission control efficiency of a source category from a
9 variety of information sources, including published reports, the 1985 National Acid Precipitation and Assessment
10 Program emissions inventory, and other EPA databases.
11 Uncertainty
12 Uncertainties in these estimates are partly due to the accuracy of the emission factors used and accurate estimates of
13 activity data. A quantitative uncertainty analysis was not performed.
14 3.11. International Bunker Fuels (IPCC Source Category 1: Memo Items)
15 Emissions resulting from the combustion of fuels used for international transport activities, termed international
16 bunker fuels under the UNFCCC, are currently not included in national emission totals, but are reported separately
17 based upon location of fuel sales. The decision to report emissions from international bunker fuels separately,
18 instead of allocating them to a particular country, was made by the Intergovernmental Negotiating Committee in
19 establishing the Framework Convention on Climate Change.44 These decisions are reflected in the Revised 1996
20 IPCC Guidelines, as well as the 2006 IPCC GLs, in which countries are requested to report emissions from ships or
21 aircraft that depart from their ports with fuel purchased within national boundaries and are engaged in international
22 transport separately from national totals (IPCC/UNEP/OECD/IEA 1997) 45
23 Greenhouse gases emitted from the combustion of international bunker fuels, like other fossil fuels, include C02,
24 CH4 and N20. Two transport modes are addressed under the IPCC definition of international bunker fuels: aviation
25 and marine.46 Emissions from ground transport activities—by road vehicles and trains—even when crossing
26 international borders are allocated to the country where the fuel was loaded into the vehicle and, therefore, are not
27 counted as bunker fuel emissions.
28 The IPCC Guidelines distinguish between different modes of air traffic. Civil aviation comprises aircraft used for
29 the commercial transport of passengers and freight, military aviation comprises aircraft under the control of national
30 armed forces, and general aviation applies to recreational and small corporate aircraft. The IPCC Guidelines further
31 define international bunker fuel use from civil aviation as the fuel combusted for civil (e.g., commercial) aviation
32 purposes by aircraft arriving or departing on international flight segments. However, as mentioned above, and in
33 keeping with the IPCC Guidelines, only the fuel purchased in the United States and used by aircraft taking-off (i.e.,
34 departing) from the United States are reported here. The standard fuel used for civil aviation is kerosene-type jet
44 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. lc).
45 Note that the definition of international bunker fuels used by the UNFCCC differs from that used by the International Civil
Aviation Organization.
46 Most emission related international aviation and marine regulations are under the rubric of the International Civil Aviation
Organization (ICAO) or the International Maritime Organization (IMO), which develop international codes, recommendations,
and conventions, such as the International Convention of the Prevention of Pollution from Ships (MARPOL).
3-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Public Review Draft
fuel, while the typical fuel used for general aviation is aviation gasoline.47
Emissions of C02 from aircraft are essentially a function of fuel use. CH4 and N20 emissions also depend upon
engine characteristics, flight conditions, and flight phase (i.e., take-off, climb, cruise, decent, and landing). CH4 is
the product of incomplete combustion and occur mainly during the landing and take-off phases. In jet engines, N20
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. C02 is the primary greenhouse gas emitted from marine
shipping.
Overall, aggregate greenhouse gas emissions in 2005 from the combustion of international bunker fuels from both
aviation and marine activities were 96.6 Tg C02 Eq., or 16 percent below emissions in 1990 (see Table 3-48).
Although emissions from international flights departing from the United States have increased significantly (34
percent), emissions from international shipping voyages departing the United States have decreased by 50 percent
since 1990. The majority of these emissions were in the form of C02; however, small amounts of CH4 and N20
were also emitted.
Table 3-48: C02, CH4, and N20 Emissions from International Bunker Fuels (Tg C02 Eq.)
Gas/Mode
1990
1995
2000
2001
2002
2003
2004
2005
co2
113.7
100.(i
101.1
97.6
89.1
83.7
97.2
95.6
Aviation
45.7
50.:
59.9
58.7
61.1
58.8
62.2
61.5
Marine
68.0
50.4
41.3
38.9
28.0
24.9
34.9
34.2
ch4
0.2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
Aviation
+1111111
+II11IB
+
+
+
+
+
+
Marine
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
n2o
1.0
0.'>
0.9
0.9
0.8
0.8
0.9
0.9
Aviation
0.5
0.5
0.6
0.6
0.6
0.6
0.6
0.6
Marine
0.5
0.4
0.3
0.3
0.2
0.2
0.3
0.3
Total
114.8
101.6
102.2
98.6
90.0
84.5
98.2
96.6
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
Table 3-49: C02, CH4 and N20 Emissions from International Bunker Fuels (Gg)
Gas/Mode
1990
1995
2000
2001
2002
2003
2004
2005
co2
113,683
100,627
101,125
97,563
89,101
83,690
97,177
95,605
Aviation
45,73 1
50,202
59,853
58,696
61,120
58,806
62,241
61,452
Marine
67,952
50,425
41,272
38,866
27,981
24,884
34,937
34,153
ch4
8
6
6
5
4
4
5
5
Aviation
ill
1 llllll
2
2
2
2
2
2
Marine
7III
I 5II
4
4
3
2
3
3
n2o
311111B
3
3
3
3
2
3
3
Aviation
ill
2 1
2
2
2
2
2
2
Marine
2 \j
1 1
1
1
1
1
1
1
Note: Totals may not sum due to independent rounding. Includes aircraft cruise altitude emissions.
47 Naphtha-type jet fuel was used in the past by the military in turbojet and turboprop aircraft engines.
Energy 3-55
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Public Review Draft
Methodology
Emissions of C02 were estimated by applying of C content and fraction oxidized factors to fuel consumption
activity data. This approach is analogous to that described under C02 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 (2006) and USAF (1998), and heat content for jet fuel was taken from EIA (2006). A complete
description of the methodology and a listing of the various factors employed can be found in Annex 2.1. See Annex
3.7 for a specific discussion on the methodology used for estimating emissions from international bunker fuel use by
the U.S. military.
Emission estimates for CH4 and N20 were calculated by multiplying emission factors by measures of fuel
consumption by fuel type and mode. Emission factors used in the calculations of CH4 and N20 emissions were
obtained from the Revised 1996IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997). For aircraft emissions, the
following values, in units of grams of pollutant per kilogram of fuel consumed (g/kg), were employed: 0.09 for CH4
and 0.1 for N20 For marine vessels consuming either distillate diesel or residual fuel oil the following values
(g/MJ), were employed: 0.32 for CH4 and 0.08 for N20. 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—w as purchased domestically for flights departing from
the United States. In other words, only one-half of the total annual fuel consumption estimate was used in the
calculations. Data on jet fuel expenditures by foreign flagged carriers departing U.S. airports was taken from
unpublished data collected by the Bureau of Economic Analysis (BEA) under the U. S. Department of Commerce
(BEA 1991 through 2006). Approximate average fuel prices paid by air carriers for aircraft on international flights
was taken from DOT (1991 through 2006) and used to convert the BEA expenditure data to gallons of fuel
consumed. Data on U.S. Department of Defense (DoD) aviation bunker fuels and total jet fuel consumed by the
U.S. military was supplied by the Office of the Under Secretary of Defense (Installations and Environment), DoD.
Estimates of the percentage of each Service's total operations that were international operations were developed by
DoD. Military aviation bunkers included international operations, operations conducted from naval vessels at sea,
and operations conducted from U.S. installations principally over international water in direct support of military
operations at sea. Military aviation bunker fuel emissions were estimated using military fuel and operations data
synthesized from unpublished data by the Defense Energy Support Center, under DoD's Defense Logistics Agency
(DESC 2006). 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 3-50. 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 2006). Activity data on distillate diesel
consumption by military vessels departing from U.S. ports were provided by DESC (2006). 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 3-51.
Table 3-50: Aviation Jet Fuel Consumption for International Transport (Million Gallons)
Nationality
1990
1 1995
2000
2001
2002
2003
2004
2005
U.S. Carriers
1,954
2,22i
2,737
2,619
2,495
2,418
2,465
2,760
Foreign Carriers
2,051
2,544
3,162
3,113
3,537
3,377
3,671
3,450
U.S. Military
862
1 581
480
524
482
473
498
343
Total
4,867
5,347
6,380
6,255
6,515
6,268
6,634
6,553
Note: Totals may not sum due to independent rounding.
3-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
Table 3-51: Marine Fuel Consumption for International Transport (Million Gallons)
Fuel Type
1990
1995
2000
2001
2002
2003
2004
2005
Residual Fuel Oil
4,781
3,495
2,967
2,846
1,937
1,597
2,363
2,320
Distillate Diesel Fuel & Other
617 ,
573
290
204
158
137
167
241
U.S. Military Naval Fuels
522
1 334
329
318
348
459
530
427
Total
5,920
4,402
3,586
3,368
2,443
2,193
3,059
2,989
Note: Totals may not sum due to independent rounding.
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.48 For example, smaller aircraft on shorter routes often carry sufficient fuel to
complete several flight segments without refueling in order to minimize time spent at the airport gate or take
advantage of lower fuel prices at particular airports. This practice, called tankering, when done on international
flights, complicates the use of fuel sales data for estimating bunker fuel emissions. Tankering is less common with
the type of large, long-range aircraft that make many international flights from the United States, however. Similar
practices occur in the marine shipping industry where fuel costs represent a significant portion of overall operating
costs and fuel prices vary from port to port, leading to some tankering from ports with low fuel costs.
Particularly for aviation, the DOT (1991 through 2006) 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 2006) 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.49
Uncertainties exist with regard to the total fuel used by military aircraft and ships, and in the activity data on
military operations and training that were used to estimate percentages of total fuel use reported as bunker fuel
emissions. Total aircraft and ship fuel use estimates were developed from DoD records, which document fuel sold
to the Navy and Air Force from the Defense Logistics Agency. These data may slightly over or under estimate
actual total fuel use in aircraft and ships because each Service may have procured fuel from, and/or may have sold
to, traded with, and/or given fuel to other ships, aircraft, governments, or other entities. There are uncertainties in
aircraft operations and training activity data. Estimates for the quantity of fuel actually used in Navy and Air Force
flying activities reported as bunker fuel emissions had to be estimated based on a combination of available data and
expert judgment. Estimates of marine bunker fuel emissions were based on Navy vessel steaming hour data, which
reports fuel used while underway and fuel used while not underway. This approach does not capture some voyages
that would be classified as domestic for a commercial vessel. Conversely, emissions from fuel used while not
underway preceding an international voyage are reported as domestic rather than international as would be done for
a commercial vessel. There is uncertainty associated with ground fuel estimates for 1997 through 2001. Small fuel
quantities may have been used in vehicles or equipment other than that which was assumed for each fuel type.
There are also uncertainties in fuel end-uses by fuel-type, emissions factors, fuel densities, diesel fuel sulfur content,
aircraft and vessel engine characteristics and fuel efficiencies, and the methodology used to back-calculate the data
48 See uncertainty discussions under Carbon Dioxide Emissions from Fossil Fuel Combustion.
49 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.
Energy 3-57
-------
Public Review Draft
1 set to 1990 using the original set from 1995. The data were adjusted for trends in fuel use based on a closely
2 correlating, but not matching, data set. All assumptions used to develop the estimate were based on process
3 knowledge, Department and military Service data, and expert judgments. The magnitude of the potential errors
4 related to the various uncertainties has not been calculated, but is believed to be small. The uncertainties associated
5 with future military bunker fuel emission estimates could be reduced through additional data collection.
6 Although aggregate fuel consumption data have been used to estimate emissions from aviation, the recommended
7 method for estimating emissions of gases other than C02 in the Revised 1996IPCC Guidelines is to use data by
8 specific aircraft type (IPCC/UNEP/OECD/IEA 1997). The IPCC also recommends that cruise altitude emissions be
9 estimated separately using fuel consumption data, while landing and take-off (LTO) cycle data be used to estimate
10 near-ground level emissions of gases other than C02.50
11 There is also concern as to the reliability of the existing DOC (1991 through 2006) data on marine vessel fuel
12 consumption reported at U.S. customs stations due to the significant degree of inter-annual variation.
13 QA/QC and Verification
14 A source-specific QA/QC plan for international bunker fuels was developed and implemented. This effort included
15 a Tier 1 analysis, as well as portions of a Tier 2 analysis. The Tier 2 procedures that were implemented involved
16 checks specifically focusing on the activity data and emission factor sources and methodology used for estimating
17 C02, CH4, and N20 from international bunker fuels in the United States. Emission totals for the different sectors
18 and fuels were compared and trends were investigated. No corrective actions were necessary.
19 Recalculations Discussion
20 Historical activity data for aviation was slightly revised for both U.S. and foreign carriers. These changes were due
21 to revisions to international fuel cost for foreign carriers and international jet fuel consumption for U.S. carriers,
22 provided by DOT (1991 through 2006). The density for jet fuel was also revised to reflect data obtained from
23 Chevron (2000) and ASTM (1989). This revision increased the heat content for aviation jet fuel by 2 percent for all
24 years. The C content coefficient was also revised from 0.99 to 1 for all fuel types based on guidance in IPCC
25 (2006). These historical data changes resulted in changes to the emission estimates for 1990 through 2004, which
26 averaged to an annual increase in emissions from international bunker fuels of 0.1 Tg C02 Eq. (0.1 percent) in C02
27 emissions, annual increase of less than 0.1 Tg C02 Eq. (less than 0.2 percent) in CH4 emissions, and annual increase
28 of less than 0.1 Tg C02 Eq. (0.2 percent) in N20 emissions.
29 3.12. Wood Biomass and Ethanol Consumption (IPCC Source Category 1A)
30 The combustion of biomass fuels—such as wood, charcoal, and wood waste—and biomass-based fuels—such as
31 ethanol from corn and woody crops—generates C02. However, in the long run the C02 emitted from biomass
32 consumption does not increase atmospheric C02 concentrations, assuming that the biogenic C emitted is offset by
33 the uptake of C02 that results from the growth of new biomass. As a result, C02 emissions from biomass
34 combustion have been estimated separately from fossil fuel-based emissions and are not included in the U.S. totals.
35 Net C fluxes from changes in biogenic C reservoirs in wooded or crop lands are accounted for in the Land Use,
50 U.S. aviation emission estimates for CO, NOx, and NMVOCs are reported by EPA's National Emission Inventory (NEI) Air
Pollutant Emission Trends web site, and reported under the Mobile Combustion section. It should be noted that these estimates
are based solely upon LTO cycles and consequently only capture near ground-level emissions, which are more relevant for air
quality evaluations. These estimates also include both domestic and international flights. Therefore, estimates reported under
the Mobile Combustion section overestimate IPCC-defined domestic CO, NOx, and NMVOC emissions by including landing and
take-off (LTO) cycles by aircraft on international flights, but underestimate because they do not include emissions from aircraft
on domestic flight segments at cruising altitudes. The estimates in Mobile Combustion are also likely to include emissions from
ocean-going vessels departing from U.S. ports on international voyages.
3-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Public Review Draft
Land-Use Change, and Forestry chapter.
In 2005, total C02 emissions from the burning of woody biomass in the industrial, residential, commercial, and
electricity generation sectors were approximately 184.1 Tg C02 Eq. (184,067 Gg) (see Table 3-52 and Table 3-53).
As the largest consumer of woody biomass, the industrial sector was responsible for 63 percent of the C02
emissions from this source. The residential sector was the second largest emitter, constituting 24 percent of the
total, while the commercial and electricity generation sectors accounted for the remainder.
Table 3-52: C02 Emissions from Wood Consumption by End-Use Sector (Tg C02 Eq.)
End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005
Industrial 135.3 155.1 153.6 135.4 131.1 128.0 138.5 116.2
Residential 59.S 53(. 44.3 38.2 39.2 41.2 42.3 43.3
Commercial 6.U 7o 7.4 6.9 7.1 7.4 7.3 7.2
Electricity Generation m 123 13.9 13.0 15.5 17.3 17.0 17.3
Total 215.2 229.1 219.1 193.5 192.8 193.8 205.1 184.1
Note: Totals may not sum due to independent rounding.
Table 3-53: C02 Emissions from Wood Consumption by End-Use Sector (Gg)
End-Use Sector 1990 1995 2000 2001 2002 2003 2004 2005
Industrial 135,348 155,075 153,559 135,415 131,079 127,970 138,522 116,238
Residential 59,808 53,621 44,340 38,153 39,184 41,247 42,278 43,309
Commercial 6,IT) 7,463 7,370 6,887 7,080 7,366 7,252 7,236
Electricity Generation 13,252 12,932 13,851 13,034 15,487 17,250 17,034 17,284
Total 215,186 229,091 219,119 193,489 192,830 193,833 205,086 184,067
Note: Totals may not sum due to independent rounding.
Biomass-derived fuel consumption in the United States consisted primarily of ethanol use in the transportation
sector. Ethanol is primarily produced from corn grown in the Midwest, and was used mostly in the Midwest and
South. Pure ethanol can be combusted, or it can be mixed with gasoline as a supplement or octane-enhancing agent.
The most common mixture is a 90 percent gasoline, 10 percent ethanol blend known as gasohol. Ethanol and
ethanol blends are often used to fuel public transport vehicles such as buses, or centrally fueled fleet vehicles.
These fuels burn cleaner than gasoline (i.e., lower in NOx and hydrocarbon emissions), and have been employed in
urban areas with poor air quality. However, because ethanol is a hydrocarbon fuel, its combustion emits C02.
In 2005, the United States consumed an estimated 3.4 trillion Btu of ethanol, and as a result, produced
approximately 22.4 Tg C02 Eq. (22,408 Gg) (see Table 3-54) of C02 emissions. Ethanol production and
consumption has grown steadily every year since 1990, with the exception of 1996 due to short corn supplies and
high prices in that year.
Table 3-54: C02 Emissions from Ethanol Consumption (Tg C02 Eq. and Gg)
Year
Tg C02 Eq.
Gg
1990
4.2
4.155
19'^
7 7
7,683
2000
9.2
9,188
2001
9.7
9,673
2002
11.5
11,520
2003
15.8
15,770
2004
19.7
19,740
2005
22.4
22,408
Energy 3-59
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Public Review Draft
Methodology
Woody biomass emissions were estimated by applying two EIA gross heat contents (Lindstrom 2006) to U.S.
consumption data (EIA 2006) (see Table 3-55), 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 C02 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 C02 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 2006) (see Table 3-56).
Table 3-55: Woody Biomass Consumption by Sector (Trillion Btu)
Year
Industrial
Residential Commercial Electricity Generation
1990
1,442
580
66
129
1995
2000
2001
2002
2003
2004
2005
1,652
1,636
1,443
1,396
1,363
1,476
1,238
520
430
370
380
400
410
420
72
125
71
67
69
71
70
70
134
126
150
167
165
168
Table 3-56: Ethanol Consumption (Trillion Btu)
Year Trillion Btu
1990 63
2000 139
2001 147
2002 175
2003 239
2004 299
2005 340
Uncertainty
It is assumed that the combustion efficiency for woody biomass is 100 percent, which is believed to be an
overestimate of the efficiency of wood combustion processes in the United States. Decreasing the combustion
efficiency would increase emission estimates. Additionally, the heat content applied to the consumption of woody
biomass in the residential, commercial, and electric power sectors is unlikely to be a completely accurate
representation of the heat content for all the different types of woody biomass consumed within these sectors.
Emission estimates from ethanol production are more certain than estimates from woody biomass consumption due
to better activity data collection methods and uniform combustion techniques.
Recalculations Discussion
Commercial wood consumption values were revised for the full time series, based on updated information from
EIA's Commercial Building Energy Consumption Survey (EIA 2006). EIA (2006) also reported minor changes in
wood consumption by the residential and industrial sectors for the full time series, and in ethanol consumption for
3-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
2001 through 2004.
[BEGIN BOX]
Box 3-4: Formation of C02 through Atmospheric CH4 Oxidation
CH4 emitted to the atmosphere will eventually oxidize into C02, which remains in the atmosphere for up to 200
years. The global warming potential (GWP) of CH4, however, does not account for the radiative forcing effects of
the C02 formation that results from this CH4 oxidation. The IPCC Guidelines for Greenhouse Gas Inventories
(IPCC/UNEP/OECD/IEA 1997) do not explicitly recommend a procedure for accounting for oxidized CH4, but
some of the resulting C02 is, in practice, included in the inventory estimates because of the intentional "double-
counting" structure for estimating C02 emissions from the combustion of fossil fuels. According to the IPCC
Guidelines, countries should estimate emissions of CH4, CO, and NMVOCs from fossil fuel combustion, but also
assume that these compounds eventually oxidize to C02 in the atmosphere. This is accomplished by using C02
emission factors that do not factor out carbon in the fuel that is released as in the form of CH4, CO, and NMVOC
molecules. Therefore, the carbon in fossil fuel is intentionally double counted, as an atom in a CH4 molecule and as
an atom in a C02 molecule.51 While this approach does account for the full radiative forcing effect of fossil fuel-
related greenhouse gas emissions, the timing is not accurate because it may take up to 12 years for the CH4 to
oxidize and form C02.
There is no similar IPCC approach to account for the oxidation of CH4 emitted from sources other than fossil fuel
combustion (e.g., landfills, livestock, and coal mining). CH4 from biological systems contains carbon that is part of
a rapidly cycling biological system, and therefore any C created from oxidized CH4 from these sources is matched
with carbon removed from the atmosphere by biological systems—likely during the same or subsequent year. Thus,
there are no additional radiative forcing effects from the oxidation of CH4 from biological systems. For example,
the C content of CH4 from enteric fermentation is derived from plant matter, which itself was created through the
conversion of atmospheric C02 to organic compounds.
The remaining anthropogenic sources of CH4 (e.g., fugitive emissions from coal mining and natural gas systems,
industrial process emissions) do increase the long-term C02 burden in the atmosphere, and this effect is not captured
in the inventory. The following tables provide estimates of the equivalent C02 production that results from the
atmospheric oxidation of CH4 from these remaining sources. The estimates for CH4 emissions are gathered from the
respective sections of this report, and are presented in Table 3-57. The C02 estimates are summarized in Table
3-58.
Table 3-57: CH4 Emissions from Non-Combustion Fossil Sources (Gg)
Source
1990
I 1995
2000
2001
2002
2003
2004
2005
Coal Mining
3,899
3.1(0
2,662
2,644
2,476
2,480
2,597
2,494
Abandoned Coal Mines
286
| 391
349
318
292
282
275
263
Natural Gas Systems
5,927
6,101
6,027
5,971
5,951
5,891
5,669
5,292
Petroleum Systems
1,640
1,482
1,325
1,303
1,275
1,229
1,209
1,357
Petrochemical Production
41
52
58
51
52
51
55
52
Silicon Carbide
1
Production
1
1 1
1
+
+
+
+
+
51 It is assumed that 100 percent of the CH4 emissions from combustion sources are accounted for in the overall carbon
emissions calculated as C02 for sources using emission factors and carbon mass balances. However, it may be the case for some
types of combustion sources that the oxidation factors used for calculating C02 emissions do not accurately account for the full
mass of carbon emitted in gaseous form (i.e., partially oxidized or still in hydrocarbon form).
Energy 3-61
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Public Review Draft
Iron and Steel Production 63 62 57 51 48 49 50 45
Total 11,85S 11,254 10,479 10,339 10,094 9,982 9,855 9,504
Note: These emissions are accounted for under their respective source categories. Totals may not sum due to independent
rounding.
Table 3-58: Formation of C02 through Atmospheric CH4 Oxidation (Tg C02 Eq.)
Source
1990
1995
2000
2001
2002
2003
2004
2005
Coal Mining
|u "
8.7
7.3
7.3
6.8
6.8
7.1
6.9
Abandoned Coal Mines
o.:<
1.1
1.0
0.9
0.8
0.8
0.8
0.7
Natural Gas Systems
ii> '
16.8
16.6
16.4
16.4
16.2
15.6
14.6
Petroleum Systems
4 *
4.1
3.6
3.6
3.5
3.4
3.3
3.7
Petrochemical Production
0 1
0.1
0.2
0.1
0.1
0.1
0.2
0.1
Silicon Carbide Production
+1111
+1111
+
+
+
+
+
+
Iron and Steel Production
ii:
o.:
0.2
0.1
0.1
0.1
0.1
0.1
Total 32* 30/) 28.8 28.4 27.8 27.4 27.1 26.1
Note: Totals may not sum due to independent rounding.
+ Does not exceed 0.05 Tg C02 Eq.
The estimates of C02 formation are calculated by applying a factor of 44/16, which is the ratio of molecular weight
of C02 to the molecular weight of CH4. For the purposes of the calculation, it is assumed that CH4 is oxidized to
C02 in the same year that it is emitted. As discussed above, this is a simplification, because the average
atmospheric lifetime of CH4 is approximately 12 years.
C02 formation can also result from the oxidation of CO and NMVOCs. However, the resulting increase of C02 in
the atmosphere is explicitly included in the mass balance used in calculating the storage and emissions from non-
energy uses of fossil fuels, with the carbon components of CO and NMVOC counted as C02 emissions in the mass
balance.52
[END BOX]
52 See Annex 2.3 for a more detailed discussion on accounting for indirect emissions from CO and NMVOCs.
3-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Petroleum
841
Fossil Fuel
Energv Exports
281
Stock
Changes
<1
Non-Energy
Use Exports
91
Coal
2,168
Natural Gas
1,007
t
Domestic
Fossil Fuel
Production
4,161
Apparent
Consumption
6,345
-Natural Gas Liquids,
Liquefied Refinery Gas,
& Other Liquids
145 _
Petroleum
1,904 „
NG 233 -
Coal 81 *
Fossil Fuel
Energy
Imports
2,430
7
Non-Energy Consumption
Use Imports U.S.
03 Territories
53
Fossil Fuel Non-Energy
Use U.S.
Territories
10
Balancing
item
International
Bunkers
98
industrial
Processes
NEU Emissions
. 14
Coal Emissions
2,108
Combustion
Emissions
2,094
Natural Gas Emissions
r 1,178
Atmospheric
Emissions
6,082
Combustion
Emissions 1,170-
Combustion
Emissions
2,489
NEU Emissions 121
Petroleum
• Emissions
2,610
Non-Energy Use
Carbon Sequestered
243
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
-------
Fossil Fuel Combustion
Non-Energy Use of Fuels
Natural Gas Systems
Coal Mining
Mobile Sources
Petroleum Systems
Stationary Sources |
Waste Combustion |
Abandoned Coal Mines |
0
25
| 5,752.8
Energy as a Portion
of all Emissions
50
75 100
Tg C02 Eq
125
150
Figure 3-1: 2005 Energy Sector Greenhouse Gas Sources
6% Renewable
8% Nuclear
23%
Natural Gas
23% Coal
40%
Petroleum
Figure 3-3: 2005 U.S. Energy Consumption by Energy Source
-------
Figure 3-4: U.S. Energy Consumption (Quadrillion Btu)
Note: Expressed as gross calorific values
2,000 -
S i'500
o
u 1,000 -
F
500 -
0
Relative Contribution
by Fuel Type
>
Natural Gas
Petroleum
I Coal
.£¦ o
0) c
id a
O
Z> P
Figure 3-5: 2005 C02 Emissions from Fossil Fuel Combustion by Sector and Fuel Type
Note: The electricity generation sector also includes emissions of less than 0.01 Tg CO 2 Eq.
from geothermal-based electricity generation
-------
Normal
(4,576 Heating Degree Days)
orM^-iocoorM^-iocoorM^-iocoorM^-iocoorM^-ioco
LnLDLnLnLniX)iX)iX)iX)^[\i\i\i\i\cocococococncncncncn
(N (N N
Figure 3-6. Annual Deviations from Normal Heating Degree Days for the United States (1950-2005)
Note: Climatological normal data are highlighted.
Statistical confidence interval for "normal" climatology period of 1961 through 1990.
rM^-*ocoorM^-*ocoorM^-*ocoorM^-*ocoof\i^-*oco
UlinuiinifliDiDiDiDNNNNNKlCOcacOW^OiW^Oi
OiOiOiffiOiOiOiOiOiOiOiOiOiOiffiOiffiOiOlOlOlOlOl®
(M N N
Figure 3-7: Annual Deviations from Normal Cooling Degree Days for the United States (1950-2005)
Note: Climatological normal data are highlighted.
Statistical confidence interval for "normal" climatology period of 1961 through 1990.
100
80
60
40
20
^ Hydro
Nuclear
^¦^DCOO(N^-U)COO(N^-^DCO
r*>r*>r*>cococococoo\o\o\o\o\
CiCiO^O^O^O^O^O^O^O^O^O^O^
f\l M f\l
Figure 3-8: Aggregate Nuclear and Hydroelectric Power Plant Capacity Factors in the United States (1974-2005)
-------
Figure 3-9: 2005 End-Use Sector Emissions of C02 from Fossil Fuel Combustion
Figure 3-10: Sales of New Automobiles and Light-Duty Trucks, 1990-2005
25 1
24 -
23 -
16 -
15 J , , 1 1 , 1 1 , , 1 , , 1 1 ,
o^cNjco^-LOcor^coaio^cNjcoxrio
0)0)0)0)0)0)0)0)0)0)000000
0)0)0)0)0)0)0)0)0)0)000000
T-T-T-T-T-T-T-T-T-T-CNCMCMCMCNJCNJ
Model Year
Figure 3-11: Sales-Weighted Fuel Economy of New Automobiles and Light-Duty Trucks, 1990-2005
-------
110 1
100 - ¦
90 -
80
70
60
Total
Industrial
Index
Total excluding Computers,
Communications Equip., and
Semiconductors
110
Paper
100
90 -
Foods
80 J
110
100 --
90 -
80
70 J
120
110
100
90
80 J
o
CTl
CT1
.Sione^ Clay.&_Glass_.
Products
Chemicals
Primary
.Metals
i-HfNjro^fLD^rvcoo^
010101010101010101
010101010101010101
(N (N fM (N (N
re 3-12: Industrial Production Indexes (Index 2002=100)
-------
120
S HO 1
II
: ioo
90
80
Normal
(4,524 Heatinq Deqree Days)
• •
• •
Figure 3-13: Heating Degree Days
Note: Excludes Alaska and Hawaii
120
S110 H
II
E100
aj 90 -
80
Normal
(1,215 Cooling Degree Days)
• -«
• •
ft.
CTi (Ti (Ti (Ti (Ti 0~i 0*i 0~i
o~i cr> cr> o"< cx>
(N fN (N (N
Figure 3-14: Cooling Degree Days
Note: Excludes Alaska and Hawaii
Figure 3-15: Electric Generation Retail Sales by End-Use Sector
Note: The transportation end-use sector consumes minor quanties of electricity.
-------
Figure 3-16: U.S. Energy Consumption and Energy-Related C02 Emissions
Per Capita and Per Dollar GDP
Figure 3-17: Mobile Source CH4 and N20 Emissions
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
4. Industrial Processes
Greenhouse gas emissions are produced as a by-product of various non-energy-related industrial activities. That is,
these emissions are produced from an industrial process itself and are not directly a result of energy consumed
during the process. For example, raw materials can be chemically transformed from one state to another. This
transformation can result in the release of greenhouse gases such as carbon dioxide (C02), methane (CH4), or
nitrous oxide (N20). The processes addressed in this chapter include iron and steel production, cement
manufacture, ammonia manufacture and urea application, lime manufacture, limestone and dolomite use (e.g., flux
stone, flue gas desulfurization, and glass manufacturing), soda ash manufacture and use, titanium dioxide
production, phosphoric acid production, ferroalloy production, C02 consumption, aluminum production,
petrochemical production, silicon carbide production and consumption, lead production, zinc production, nitric acid
production, and adipic acid production (see Figure 4-1).
Figure 4-1: 2005 Industrial Processes Chapter Greenhouse Gas Sources
In addition to the three greenhouse gases listed above, there are also industrial sources of man-made fluorinated
compounds called hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6). The
present contribution of these gases to the radiative forcing effect of all anthropogenic greenhouse gases is small;
however, because of their extremely long lifetimes, many of them will continue to accumulate in the atmosphere as
long as emissions continue. In addition, many of these gases have high global warming potentials; SF6 is the most
potent greenhouse gas the Intergovernmental Panel on Climate Change (IPCC) has evaluated. Usage of HFCs for
the substitution of ozone depleting substances is growing rapidly, as they are the primary substitutes for ozone
depleting substances (ODSs), which are being phased-out under the Montreal Protocol on Substances that Deplete
the Ozone Layer. In addition to their use as ODS substitutes, HFCs, PFCs, SF6, and other fluorinated compounds
are employed and emitted by a number of other industrial sources in the United States. These industries include
aluminum production, HCFC-22 production, semiconductor manufacture, electric power transmission and
distribution, and magnesium metal production and processing.
In 2005, industrial processes generated emissions of 333.8 teragrams of C02 equivalent (Tg C02 Eq.), or 5 percent
of total U.S. greenhouse gas emissions. C02 emissions from all industrial processes were 147.0 Tg C02 Eq.
(147,026 Gg) in 2005, or 2 percent of total U.S. C02 emissions. CH4 emissions from industrial processes resulted
in emissions of approximately 2.0 Tg C02 Eq. (97 Gg) in 2005, which was less than 1 percent of U.S. CH4
emissions. N20 emissions from adipic acid and nitric acid production were 21.7 Tg C02 Eq. (70 Gg) in 2005, or 5
percent of total U.S. N20 emissions. In 2005, combined emissions of HFCs, PFCs and SF6 totaled 163.0 Tg C02
Eq. Overall, emissions from industrial processes increased by 11.2 percent from 1990 to 2005 despite decreases in
emissions from several industrial processes, such as iron and steel, aluminum production, ammonia manufacture and
urea application, HCFC-22 production, and electrical transmission and distribution. The increase in overall
emissions was driven by a rise in the emissions originating from cement manufacture and, primarily, the emissions
from the use of substitutes for ozone depleting substances.
Table 4-1 summarizes emissions for the Industrial Processes chapter in units of Tg C02 Eq., while unweighted
native gas emissions in gigagrams (Gg) are provided in Table 4-2.
Table 4-1: Emissions from Industrial Processes (Tg C02 Eq.)
Gas/Source
199H
1995
2000
2001
2002
2003
2004
2005
co2
175.(i
171.9
166.9
152.9
152.1
148.9
153.0
147.0
Cement Manufacture
33.3
36.8
41.2
41.4
42.9
43.1
45.6
45.9
Iron and Steel Production
85.li
73.5
65.3
58.0
54.7
53.5
51.5
45.4
Ammonia Manufacture & Urea Application
19.3
20.5
19.6
16.7
17.8
16.2
16.9
16.3
Lime Manufacture
11.3
12.8
13.3
12.9
12.3
13.0
13.7
13.7
Industrial Processes 4-1
-------
Public Review Draft
Limestone and Dolomite Use 5.51
Soda Ash Manufacture and Consumption 4. l|
Aluminum Production 6. £
Petrochemical Production 2.21
Titanium Dioxide Production 1.31
Ferroalloy Production 2.21
Phosphoric Acid Production 1.51
C02 Consumption 1.41
Zinc Production 0.91
Lead Production 0.31
Silicon Carbide Production and Consumption 0.41
CH4 2.1
Petrochemical Production 0.91
Iron and Steel Production 1.31
Ferroalloy Production +1
Silicon Carbide Production and Consumption +1
NjO 33.01
Nitric Acid Production 17.XI
Adipic Acid Production 15.21
HFCs, PFCs, and SF„ 89.31
Substitution of Ozone Depleting Substances 0.31
HCFC-22 Production3 35.01
Electrical Transmission and Distribution13 27. II
Semiconductor Manufacture 2.91
Aluminum Production IX.51
Magnesium Production and Processing13 5.4j
Total
300.21
+ Does not exceed 0.05 Tg C02 Eq.
aHFC-23 emitted
b SF6 emitted
Note: Totals may not sum due to independent rounding.
Table 4-2: Emissions from Industrial Processes (Gg)
Gas/Source
19901
19951
co2
Cement Manufacture
Iron and Steel Production
Ammonia Manufacture & Urea
Application
Lime Manufacture
Limestone and Dolomite Use
Soda Ash Manufacture and
Consumption
Aluminum Production
Petrochemical Production
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
C02 Consumption
Zinc Production
Lead Production
Silicon Carbide Production and
Consumption
CH4
Petrochemical Production
175,621
33,278
85,034
19,306
11,273
5,53
4,141
6,831
2,221
1,308
2,152
1,529
1,41 *
93^
2S^
) 171,943
36,847
73,454
20,45
12,844
7,359
4,304
5,659
2,750
1,670
2,036
1,5 I ^
1,4: ^
1,00
298
7 4
4.31
5 "
2.XI
1.7
2.01
1.51
I 4
l.oj
°-3l
0.31
2.4
1.11
1 31
+1
+1
37.1
19 ')
17 2
103.5
32.21
27U
2L81
5.0
11.XI
5,i.
6.0
5.7
5.9
4.7
6.7
4.2
4.1
4.1
4.1
4.2
6.1
4.4
4.5
4.5
4.2
3.0
2.8
2.9
2.8
2.9
1.9
1.9
2.0
2.0
2.3
1.9
1.5
1.3
1.3
1.4
1.4
1.3
1.3
1.4
1.4
1.4
0.8
1.0
1.3
1.2
1.1
1.0
0.9
0.5
0.5
0.3
0.3
0.3
0.3
0.3
0.2
0.2
0.2
0.2
0.2
2.5
2.2
2.1
2.1
2.2
1.2
1.1
1.1
1.1
1.2
1.2
1.1
1.0
1.0
1.0
+
+
+
+
+
+
+
+
+
+
25.6
20.8
23.1
22.9
21.8
19.6
15.9
17.2
16.7
16.0
6.0
4.9
5.9
6.2
5.7
143.8
133.8
143.0
142.7
153.9
80.9
88.6
96.9
105.5
114.5
29.8
19.8
19.8
12.3
15.6
15.2
15.1
14.3
13.8
13.6
6.3
4.5
4.4
4.3
4.7
8.6
3.5
5.2
3.8
2.8
3.0
2.4
2.4
2.9
2.6
7.4
4.2
4.2
2.9
1.9
1.4
1.4
1.3
0.5
0.3
0.2
2.0
1.1
1.0
+
+
21.7
15.7
6.0
163.0
123.3
16.5
13.2
4.3
3.0
2.7
314.91
338.8 309.7 320.3 316.6 330.8 333.8
2000
2001
2002
2003
2004
2005
166,937
152,904
152,130
148,903
152,977
147,026
41,190
41,357
42,898
43,082
45,603
45,910
65,259
58,047
54,702
53,511
51,492
45,440
19,616
16,719
17,766
16,173
16,894
16,321
13,344
12,861
12,330
13,022
13,728
13,660
5,960
5,733
5,885
4,720
6,702
7,397
4,181
4,147
4,139
4,111
4,205
4,228
6,086
4,381
4,490
4,503
4,231
4,208
3,004
2,787
2,857
2,777
2,895
2,897
1,918
1,857
1,997
2,013
2,259
1,921
1,893
1,459
1,349
1,305
1,419
1,392
1,382
1,264
1,338
1,382
1,395
1,383
1,416
825
978
1,310
1,199
1,324
1,129
976
927
502
472
460
311
293
290
289
259
265
375
329
248
199
183
202
224
219
106
116
117
103
101
101
106
97
41
52
58
51
52
51
55
51
4-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
Iron and Steel Production 63 62
Ferroalloy Production 1 11
Silicon Carbide Production and
Consumption 1 ll
N20 107 120
Nitric Acid Production 58 64
Adipic Acid Production 49 5< >
HFCs, PFCs, and SF6 M M
Substitution of Ozone
Depleting Substances M M
HCFC-22 Production3 3 2
Electrical Transmission and
Distribution13 1 1
Semiconductor Manufacture M M
Aluminum Production M M
Magnesium Production and
Processing13
NOx 591 607
CO 4,125 3,959
NMVOCs 2,422 2,642
+ Does not exceed 0.5 Gg
M (Mixture of gases)
aHFC-23 emitted
b SF6 emitted
Note: Totals may not sum due to independent rounding.
57
51
48
49
50
45
1
+
+
+
+
+
1
+
+
+
+
+
83
67
75
74
70
70
63
51
56
54
52
51
19
16
19
20
19
19
M
M
M
M
M
M
M
M
M
M
M
M
3
2
2
1
1
1
1
1
1
1
1
1
M
M
M
M
M
M
M
M
M
M
M
M
+
626
2,217
1,773
+
656
2,339
1,769
+
532
1,710
1,811
+
533
1,730
1,813
+
534
1,751
1,815
+
535
1,772
1,818
In order to ensure the quality of the emission estimates from industrial processes, Tier 1 quality assurance and
quality control (QA/QC) procedures and checks have been performed on all industrial process sources. Where
performed, Tier 2 procedures focused on the emission factor and activity data sources and methodology used for
estimating emissions, and will be described within the QA/QC and Verification Discussion of that source
description. In addition to the national QA/QC plan, a more detailed plan was developed specifically for the C02
and CH4 industrial processes sources. This plan was based on the U.S. strategy, but was tailored to include specific
procedures recommended for these sources.
The general method employed to estimate emissions for industrial processes, as recommended by the IPCC,
involves multiplying production data (or activity data) for each process by an emission factor per unit of production.
The uncertainty 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 C02 sources were estimated based on expert assessment of available
qualitative and quantitative information. Uncertainty estimates and probability density functions for the emission
factors used to calculate emissions from this source were devised based on IPCC recommendations.
Activity data is obtained through a survey of manufacturers conducted by various organizations (specified within
each source); the uncertainty of the activity data is a function of the reliability of plant-level production data and is
influenced by the completeness of the survey response. The emission factors used were either derived using
calculations that assume precise and efficient chemical reactions, or were based upon empirical data in published
references. As a result, uncertainties in the emission coefficients can be attributed to, among other things,
inefficiencies in the chemical reactions associated with each production process or to the use of empirically-derived
emission factors that are biased; therefore, they may not represent U.S. national averages. Additional assumptions
are described within each source.
The uncertainty analysis performed to quantify uncertainties associated with the 2005 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
Industrial Processes 4-3
-------
Public Review Draft
1 (resulting in development of more reliable inputs for the model, including accurate characterization of correlation
2 between variables), based primarily on expert judgment. Accordingly, the quantitative uncertainty estimates
3 reported in this section should be considered illustrative and as iterations of ongoing efforts to produce accurate
4 uncertainty estimates. The correlation among data used for estimating emissions for different sources can influence
5 the uncertainty analysis of each individual source. While the uncertainty analysis recognizes very significant
6 connections among sources, a more comprehensive approach that accounts for all linkages will be identified as the
7 uncertainty analysis moves forward.
8 4.1. Cement Manufacture (IPCC Source Category 2A1)
9 Cement manufacture is an energy- and raw-material-intensive process that results in the generation of C02 from
10 both the energy consumed in making the cement and the chemical process itself.1 Cement production, at the most
11 recent estimation, accounted for about 2.4 percent of total global industrial and energy-related C02 emissions (IPCC
12 1996, USGS 2003). Cement is manufactured in 37 states and Puerto Rico. C02 emitted from the chemical process
13 of cement production is the largest source of industrial C02 emissions in the United States.
14 During the cement production process, calcium carbonate (CaC03) is heated in a cement kiln at a temperature of
15 about 1,300°C (2,400°F) to form lime (i.e., calcium oxide or CaO) and C02 in a process known as calcination or
16 calcining. A very small amount of carbonates other than CaC03 is also present in the raw material; however, for
17 calculation purposes all of the raw material is assumed to be CaC03. Next, the lime is combined with silica-
18 containing materials to produce clinker (an intermediate product), with the earlier by-product C02 being released to
19 the atmosphere. The clinker is then allowed to cool, mixed with a small amount of gypsum, and used to make
20 Portland cement. Additional C02 emissions result from the production of masonry cement, which accounts for
21 approximately 6 percent of total clinker production, and is produced using lime and Portland cement. However, this
22 additional lime is already accounted for in the Lime Manufacture source category in this chapter; therefore, the
23 additional emissions from making masonry cement from clinker are not counted in this source category's total.
24 They are presented here for informational purposes only.
25 In 2005, U.S. clinker production—including Puerto Rico—totaled 88,783 thousand metric tons (Van Oss 2006).
26 The resulting emissions of C02 from 2005 cement production were estimated to be 45.9 Tg C02 Eq. (45,910 Gg)
27 (see Table 4-3). Emissions from masonry production from clinker raw material are accounted for under Lime
28 Manufacture.
29 Table 4-3: C02 Emissions from Cement Production (Tg C02 Eq. and Gg)*
Year Tg CP2 Eq. Gg
1990 33.3 33,278
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
30 * Totals exclude C02 emissions from making masonry cement from clinker, which are accounted for under Lime Manufacture.
31
32 After falling in 1991 by two percent from 1990 levels, cement production emissions have grown every year since.
1 The C02 emissions related to the consumption of energy for cement manufacture are accounted for under C02 from Fossil Fuel
Combustion in the Energy chapter.
4-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
Overall, from 1990 to 2005, emissions increased by 38 percent. Cement continues to be a critical component of the
construction industry; therefore, the availability of public construction funding, as well as overall economic growth,
have had considerable influence on cement production.
Methodology
C02 emissions from cement manufacture are created by the chemical reaction of carbon-containing minerals (i.e.,
calcining limestone). While in the kiln, limestone is broken down into C02 and lime with the C02 released to the
atmosphere. The quantity of C02 emitted during cement production is directly proportional to the lime content of
the clinker. During calcination, each mole of CaC03 (i.e., limestone) heated in the clinker kiln forms one mole of
lime (CaO) and one mole of C02:
CaC03 + heat CaO + C02
C02 emissions were estimated by applying an emission factor, in tons of C02 released per ton of clinker produced,
to the total amount of clinker produced. The emission factor used in this analysis is the product of the average lime
fraction for clinker of 64.6 percent (IPCC 2000) and a constant reflecting the mass of C02 released per unit of lime.
This calculation yields an emission factor of 0.507 tons of C02 per ton of clinker produced, which was determined
as follows:
EF =0.646 CaO)
Clinker
44.01 g/moleCO^
56.08 g/moleCaO
= 0.507 tons CO /ton clinker
2
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 C02
emissions should be estimated as two percent of the C02 emissions calculated from clinker production. Total
cement production emissions were calculated by adding the emissions from clinker production to the emissions
assigned to CKD (IPCC 2000).
Masonry cement requires additional lime over and above the lime used in clinker production. In particular, non-
plasticizer additives such as lime, slag, and shale are added to the cement, increasing its weight by approximately
five percent. Lime accounts for approximately 60 percent of this added weight. Thus, the additional lime is
equivalent to roughly 2.86 percent of the starting amount of the product, since:
0.6 x 0.05/(1 + 0.05) = 2.86%
An emission factor for this added lime can then be calculated by multiplying this 2.86 percent by the molecular
weight ratio of C02 to CaO (0.785) to yield 0.0224 metric tons of additional C02 emitted for every metric ton of
masonry cement produced.
As previously mentioned, the C02 emissions from the additional lime added during masonry cement production are
accounted for in the section on C02 emissions from Lime Manufacture. Thus, the activity data for masonry cement
production are shown in this chapter for informational purposes only, and are not included in the cement emission
totals.
The 1990 through 2005 activity data for clinker and masonry cement production (see Table 4-4) were obtained
through a personal communication with Hendrick Van Oss (Van Oss 2006) of the USGS and through the USGS
Mineral Yearbook: Cement (USGS 1993 through 2005). The data were compiled by USGS through questionnaires
sent to domestic clinker and cement manufacturing plants.
Table 4-4: Cement Production (Gg)
Year Clinker Masonry
Industrial Processes 4-5
-------
Public Review Draft
1990 64,355 3,209
2000 79,656 4,332
2001 79,979 4,450
2002 82,959 4,449
2003 83,315 4,737
2004 88,190 5,000
2005 88,783 5,514
1
2 Uncertainty
3 The uncertainties contained in these estimates are primarily due to uncertainties in the lime content of clinker and in
4 the percentage of CKD recycled inside the clinker kiln. Uncertainty is also associated with the amount of lime
5 added to masonry cement, but it is accounted for under the Lime Manufacture source category. The lime content of
6 clinker varies from 64 to 66 percent. CKD loss can range from 1.5 to 8 percent depending upon plant
7 specifications. Additionally, some amount of C02 is reabsorbed when the cement is used for construction. As
8 cement reacts with water, alkaline substances such as calcium hydroxide are formed. During this curing process,
9 these compounds may react with C02 in the atmosphere to create calcium carbonate. This reaction only occurs in
10 roughly the outer 0.2 inches of surface area. Because the amount of C02 reabsorbed is thought to be minimal, it
11 was not estimated.
12 The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-5. Cement Manufacture C02
13 emissions were estimated to be between 40.0 and 52.0 Tg C02 Eq. at the 95 percent confidence level. This
14 indicates a range of approximately 13 percent below and 13 percent above the emission estimate of 45.9 Tg C02 Eq.
15 Table 4-5: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Cement Manufacture (Tg C02 Eq.
16 and Percent)
2005 Emission
Source
Gas
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Cement Manufacture
C02
45.9
40.0 52.0
-13% +13%
17 a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
18
19 Recalculations Discussion
20 The historical activity data used to calculate the emissions from cement production were updated for the year 2004.
21 The change resulted in a decrease of 0.04 Tg C02 Eq. (less than one percent) in C02 emissions from cement
22 production for that year.
23 4.2. Iron and Steel Production (IPCC Source Category 2C1)
24 In addition to being an energy intensive process, the production of iron and steel also generates process-related
25 emissions of C02 and CH4. Iron is produced by first reducing iron oxide (iron ore) with metallurgical coke in a
26 blast furnace to produce pig iron (impure iron containing about 3 to 5 percent C by weight). Metallurgical coke is
27 manufactured using coking coal as a raw material. Iron may be introduced into the blast furnace in the form of raw
28 iron ore, pellets, briquettes, or sinter. Pig iron is used as a raw material in the production of steel, which contains
29 about 0.4 percent C by weight. Pig iron is also used as a raw material in the production of iron products in
30 foundries. The pig iron production process produces C02 emissions and fugitive CH4 emissions.
4-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Public Review Draft
The production of metallurgical coke from coking coal and the consumption of the metallurgical coke used as a
reducing agent in the blast furnace are considered in the inventory to be non-energy (industrial) processes, not
energy (combustion) processes. Metallurgical coke is produced by heating coking coal in a coke oven in a low-
oxygen environment. The process drives off the volatile components of the coking coal and produces coal
(metallurgical) coke. Coke oven gas and coal tar are C containing by-products of the coke manufacturing process.
Coke oven gas is generally burned as a fuel within the steel mill. Coal tar is used as a raw material to produce
anodes used for primary aluminum production and other electrolytic processes, and also used in the production of
other coal tar products. The coke production process produces C02 emissions and fugitive CH4 emissions.
Sintering is a thermal process by which fine iron-bearing particles, such as air emission control system dust, are
baked, which causes the material to agglomerate into roughly one-inch pellets that are then recharged into the blast
furnace for pig iron production. Iron ore particles may also be formed into larger pellets or briquettes by
mechanical means, and then agglomerated by heating prior to being charged into the blast furnace. The sintering
process produces C02 emissions and fugitive CH4 emissions.
The metallurgical coke is a reducing agent in the blast furnace. C02 is produced as the metallurgical coke used in
the blast furnace process is oxidized and the iron is reduced. Steel is produced from pig iron in a variety of
specialized steel-making furnaces. The majority of C02 emissions from the iron and steel process come from the
use of coke in the production of pig iron, with smaller amounts evolving from the removal of C from pig iron used
to produce steel. Some C is also stored in the finished iron and steel products.
Emissions of C02 and CH4 from iron and steel production in 2005 were 45.4 Tg C02 Eq. (45,440 Gg) and 1.0 Tg
C02 Eq. (45 Gg), respectively (see Table 4-6 and Table 4-7), totaling 46.4 Tg C02 Eq. Emissions have fluctuated
significantly from 1990 to 2005 due to changes in domestic economic conditions and changes in product imports
and exports. In 2005, domestic production of pig iron decreased by 12.0 percent and coal coke production
decreased by 1.1 percent. Overall, domestic pig iron and coke production have declined since the 1990s. Pig iron
production in 2005 was 21 percent lower than in 2000 and 24 percent below 1990 levels. Coke production in 2005
was 20 percent lower than in 2000 and 39 percent below 1990 levels. Overall, emissions from iron and steel
productions have declined by 47% (40.0 Tg C02 Eq.) from 1990 to 2005.
Table 4-6: C02 and CH4 Emissions from Iron and Steel Production (Tg C02 Eq.)
Year
1990
1995
2000
2001
2002
2003
2004
2005
C02
85.0
73.5
65.3
58.0
54.7
53.5
51.5
45.4
ch4
1.3
1.3
1.2
1.1
1.0
1.0
1.0
1.0
Total
86.4
74.8
66.5
59.1
55.7
54.5
52.5
46.4
Table 4-7:
C02 and CH4 Emissions from Iron and Steel Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
C02
85,034
73,454
65,259
58,047
54,702
53,511
51,492
45,440
ch4
63
62
57
51
48
49
50
45
Methodology
Coking coal is used to manufacture metallurgical (coal) coke that is used primarily as a reducing agent in the
production of iron and steel, but is also used in the production of other metals including lead and zinc (see Lead
Production and Zinc Production in this chapter). The total coking coal consumed at coke plants and the total
amount of coking coal produced were identified. These data were used to estimate the emissions associated with
producing coke from coking coal and attributed to the production of iron and steel. Additionally, the amount of
coke consumed to produce pig iron and the emissions associated with this production were estimated. The C
content of the coking coal and coke consumed in these processes were estimated by multiplying the energy
consumption by material specific C-content coefficients. The C content coefficients used are presented in Annex
2.1.
Emissions from the re-use of scrap steel were also estimated by assuming that all the associated C content of the
Industrial Processes 4-7
-------
Public Review Draft
1 scrap steel, which has an associated C content of approximately 0.4 percent, are released during the scrap re-use
2 process.
3 Lastly, emissions from C anodes, used during the production of steel in electric arc furnaces (EAFs), were also
4 estimated. Emissions of C02 were calculated by multiplying the annual production of steel in EAFs by an emission
5 factor (4.4 kg C02/ton steelEAF)- It was assumed that the C anodes used in the production of steel in EAFs are
6 composed of 80 percent petroleum coke and 20 percent coal tar pitch (DOE 1997). Since coal tar pitch is a by-
7 product of the coke production process and its C-related emissions have already been accounted for earlier in the
8 iron and steel emissions calculation as part of the process, the emissions were reduced by the amount of C in the
9 coal tar pitch used in the anodes to avoid double counting.
10 Emissions associated with the production of coke from coking coal, pig iron production, the re-use of scrap steel,
11 and the consumption of C anodes during the production of steel were summed.
12 Additionally, the coal tar pitch component of C anodes consumed during the production of aluminum are accounted
13 for in the aluminum production section of this chapter. The emissions were reduced by the amount of coal tar pitch
14 used in aluminum production to avoid double counting. The amount of coal tar pitch consumed for processes other
15 than the aluminum production and as EAF anodes and net imports of coal tar were also estimated. A storage factor
16 was applied to estimate emissions associated with other coal tar pitch consumption and net imports.
17 C storage was accounted for by assuming that all domestically manufactured steel had a C content of 0.4 percent.
18 Furthermore, any pig iron that was not consumed during steel production, but fabricated into finished iron products,
19 was assumed to have a C content of 4 percent.
20 The potential C02 emissions associated with C contained in pig iron used for purposes other than iron and steel
21 production, stored in the steel product, stored as coal tar, and attributed to C anode consumption during aluminum
22 production were summed and subtracted from the total emissions estimated above.
23 The production processes for coal coke, sinter, and pig iron result in fugitive emissions of CH4, which are emitted
24 via leaks in the production equipment rather than through the emission stacks or vents of the production plants. The
25 fugitive emissions were calculated by applying emission factors taken from the 1995 IPCC Guidelines
26 (IPCC/UNEP/OECD/IEA 1995) (see Table 4-8) to annual domestic production data for coal coke, sinter, and pig
27 iron.
28 Table 4-8: CH4 Emission Factors for Coal Coke, Sinter, and Pig Iron Production (g/kg)
Material Produced
g CH^kg produced
Coal Coke
0.5
Pig Iron
0.9
Sinter
0.5
29 Source: IPCC/UNEP/OECD/IEA 1997.
30
31 Data relating to the amount of coal consumed at coke plants, and for the production of coke for domestic
32 consumption in blast furnaces, were taken from the Energy Information Administration (EIA), Quarterly Coal
33 Report October through December (EIA 1998, 1999, 2000, 2001, 2002, 2003, 2004a) and January through March
34 (EIA 2006c). Data on total coke consumed for pig iron production were taken from the American Iron and Steel
35 Institute {MSI), Annual Statistical Report (AISI 2001, 2002, 2003, 2004, 2005, 2006). Scrap steel consumption
36 data for 1990 through 2005 were obtained from Annual Statistical Report (AISI 1995, 2001, 2002, 2003, 2004,
37 2005, 2006) (see Table 4-9). Crude steel production, as well as pig iron use for purposes other than steel
38 production, was also obtained from Annual Statistical Report (AISI 1996, 2001, 2002, 2004, 2005, 2006). C
39 content percentages for pig iron and crude steel and the C02 emission factor for C anode emissions from steel
40 production were obtained from IPCC Good Practice Guidance (IPCC 2000). Data on the non-energy use of coking
41 coal were obtained from EIA's Emissions of U.S. Greenhouse Gases in the United States (EIA 2004b, 2006b).
42 Information on coal tar net imports was determined using data from the U.S. Bureau of the Census's U.S.
43 International Trade Commission's Trade Dataweb (U.S. Bureau of the Census 2006). Coal tar consumption for
4-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 aluminum production data was estimated based on information gathered by EPA's Voluntary Aluminum Industrial
2 Partnership (VAIP) program and data from USAA Primary Aluminum Statistics (USAA 2005, 2005, 2006) (see
3 Aluminum Production in this chapter). Annual consumption of iron ore used in sinter production for 1990 through
4 2004 was obtained from the USGS Iron Ore Yearbook (USGS 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001,
5 2002, 2003, 2004) and for 2005 from the USGS Commodity Specialist (Jorgenson 2006). The C02 emission factor
6 for C anode emissions from aluminum production was taken from the Revised 1996IPCC Guidelines
1 (IPCC/UNEP/OECD/IEA 1997). Estimates for the composition of C anodes used during EAF steel and aluminum
8 production were obtained from Energy and Environmental Profile of the U.S. Aluminum Industry (DOE 1997).
9 Table 4-9: Production and Consumption Data for the Calculation of C02 and CH4 Emissions from Iron and Steel
10 Production (Thousand Metric Tons)
Gas/Activity Data
1990
1995
2000
2001
2002
2003
2004
2005
co2
Coal Consumption at Coke Plants
35,269
I 29'948
26,254
23,655
21,461
21,998
21,473
21,259
Coke Consumption for Pig Iron
25,043
1 22'288
19,307
17,236
15,959
15,482
15,068
13,848
Basic Oxygen Furnace Steel Production
56,216
56,721
53,965
47,359
45,463
45,874
47,714
42,705
Electric Arc Furnace Steel Production
ch4
Coke Production
33,510
I 38'472
47,860
42,774
46,125
47,804
51,969
52,194
25,054
21,545
18,877
17,191
15,221
15,579
15,340
15,167
Iron Ore Consumption for Sinter
12,239
12,575
10,784
9,234
9,018
8,984
8,047
8,313
Domestic Pig Iron Production for Steel
49,062
' 50,233
47,400
41,741
39,601
40,487
42,292
37,222
11
12 Uncertainty
13 The time series data sources for production of coal coke, sinter, pig iron, steel, and aluminum upon which the
14 calculations are based are assumed to be consistent for the entire time series. The estimates of C02 emissions from
15 the production and utilization of coke are based on consumption data, average C contents, and the fraction of C
16 oxidized. Uncertainty is associated with the total U.S. coke consumption and coke consumed for pig iron
17 production. These data are provided by different data sources (EIA and AISI) and comparisons between the two
18 datasets for net imports, production, and consumption identified discrepancies; however, the data chosen are
19 considered the best available. These data and factors produce a relatively accurate estimate of C02 emissions.
20 However, there are uncertainties associated with each of these factors. For example, C oxidation factors may vary
21 depending on inefficiencies in the combustion process, where varying degrees of ash or soot can remain unoxidized.
22 Simplifying assumptions were made concerning the composition of C anodes and the C contents of all pig iron and
23 crude steel. It was also assumed that all coal tar used during anode production originates as a by-product of the
24 domestic coking process. There is also uncertainty associated with the total amount of coal tar products produced
25 and with the storage factor for coal tar. Uncertainty surrounding the C02 emission factor for C anode consumption
26 in aluminum production was also estimated.
27 For the purposes of the CH4 calculation it is assumed that none of the CH4 is captured in stacks or vents and that all
28 of the CH4 escapes as fugitive emissions. Additionally, the C02 emissions calculation is not corrected by
29 subtracting the C content of the CH4, which means there may be a slight double counting of C as both C02 and CH4.
30 The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-10. Iron and Steel C02
31 emissions were estimated to be between 40.8 and 57.4 Tg C02 Eq. at the 95 percent confidence level. This
32 indicates a range of approximately 10 percent below and 26 percent above the emission estimate of 45.4 Tg C02 Eq.
33 Iron and Steel CH4 emissions were estimated to be between 0.9 Tg C02 Eq. and 1.0 Tg C02 Eq. at the 95 percent
34 confidence level. This indicates a range of approximately 8 percent below and 8 percent above the emission
35 estimate of 1.0 Tg C02 Eq.
36
37
Industrial Processes 4-9
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
Table 4-10: Tier 2 Quantitative Uncertainty Estimates for C02 and CH4 Emissions from Iron and Steel Production
(Tg. C02 Eg. and Percent)
2005
Emission
Source
Gas
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Upper
Lower
Upper
Bound
Bound
Bound
Bound
Iron and Steel Production
C02
45.4
40.8
57.4
-10%
+26%
Iron and Steel Production
ch4
1.0
0.9
1.0
-8%
+8%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
C02 emission estimates for the iron and steel source category were updated for the entire time series to reflect
revisions to the coal tar import/export data. These revisions resulted in a change in emissions of less than one
percent throughout the time series.
Planned Improvements
The methodology to estimate emissions from the Iron and Steel source category will be updated in future
inventories to include methodologies outlined in the 2006IPCC Guidelines for National Greenhouse Gas
Inventories (IPCC 2006). These methodologies involve the inclusion of energy-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 production in addition to iron and steel production.
4.3. Ammonia Manufacture and Urea Application (IPCC Source Category 2B1)
Emissions of C02 occur during the production of synthetic ammonia, primarily through the use of natural gas as a
feedstock. The natural gas-based, naphtha-based, and petroleum coke-based processes produce C02 and hydrogen
(H2), the latter of which is used in the production of ammonia. One nitrogen production plant located in Kansas is
producing ammonia from petroleum coke feedstock. In some plants the C02 produced is captured and used to
produce urea. The brine electrolysis process for production of ammonia does not lead to process-based C02
emissions.
There are five principal process steps in synthetic ammonia production from natural gas feedstock. The primary
reforming step converts CH4 to C02, carbon monoxide (CO), and H2 in the presence of a catalyst. Only 30 to 40
percent of the CH4 feedstock to the primary reformer is converted to CO and C02. The secondary reforming step
converts the remaining CH4 feedstock to CO and C02. The CO in the process gas from the secondary reforming
step (representing approximately 15 percent of the process gas) is converted to C02 in the presence of a catalyst,
water, and air in the shift conversion step. C02 is removed from the process gas by the shift conversion process,
and the hydrogen gas is combined with the nitrogen (N2) gas in the process gas during the ammonia synthesis step
to produce ammonia. The C02 is included in a waste gas stream with other process impurities and is absorbed by a
scrubber solution. In regenerating the scrubber solution, C02 is released.
The conversion process for conventional steam reforming of CH4, including primary and secondary reforming and
the shift conversion processes, is approximately as follows:
(catalyst)
0.88 CH4 + 1.26 Air + 1.24 H20 > 0.88 C02 + N2 + 3 H2
N2 + 3 H2 —> 2 NH3
To produce synthetic ammonia from petroleum coke, the petroleum coke is gasified and converted to C02 and H2.
These gases are separated, and the H2 is used as a feedstock to the ammonia production process, where it is reacted
4-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
with N2 to form ammonia.
Not all of the C02 produced in the production of ammonia is emitted directly to the atmosphere. Both ammonia and
C02 are used as raw materials in the production of urea [CO(NH2)2], which is another type of nitrogenous fertilizer
that contains C as well as N. The chemical reaction that produces urea is:
2 NH3 + C02 NH2COONH4 CO(NH2)2 + H20
The C in the urea that is produced and assumed to be subsequently applied to agricultural land as a nitrogenous
fertilizer is ultimately released into the environment as C02; therefore, the C02 produced by ammonia production
and subsequently used in the production of urea does not change overall C02 emissions. However, the C02
emissions are allocated to the ammonia and urea production processes in accordance to the amount of ammonia and
urea produced.
Net emissions of C02 from ammonia manufacture in 2005 were 9.2 Tg C02 Eq. (9,197 Gg), and are summarized in
Table 4-11 and Table 4-12. Emissions of C02 from urea application in 2005 totaled 7.1 Tg C02 Eq. (7,124 Gg),
and are summarized in Table 4-11 and Table 4-12.
Table 4-11: C02Emissions from Ammonia Manufacture and Urea Application (Tg C02 Eq.)
Source
1990
1 1995
2000
2001
2002
2003
2004
2005
Ammonia Manufacture
12.6
13.5
12.1
9.3
10.5
00
00
9.6
9.2
Urea Application
6.8
1 6.9
7.5
7.4
7.3
7.4
7.3
7.1
Total
19.3
20.5
19.6
16.7
17.8
16.2
16.9
16.3
Note: Totals may not sum due to independent rounding.
Table 4-12: C02Emissions from Ammonia Manufacture and Urea Application (Gg)
Source 1990 1995 2000 2001 2002 2003 2004 2005
Ammonia Manufacture 12,553 13,54(. 12,128 9,321 10,501 8,815 9,571 9,197
Urea Application 6,753 6,907 7,488 7,398 7,266 7,358 7,323 7,124
Total 19,30(i 20,453 19,616 16,719 17,766 16,173 16,894 16,321
Note: Totals may not sum due to independent rounding.
Methodology
The calculation methodology for non-combustion C02 emissions from production of nitrogenous fertilizers from
natural gas feedstock is based on a C02 emission factor published by the European Fertilizer Manufacturers
Association (EFMA). The C02 emission factor (1.2 metric tons C02/metric ton NH3) is applied to the percent of
total annual domestic ammonia production from natural gas feedstock. Emissions of C02 from ammonia production
are then adjusted to account for the use of some of the C02 produced from ammonia production as a raw material in
the production of urea. For each ton of urea produced, 8.8 of every 12 tons of C02 are consumed and 6.8 of every
12 tons of ammonia are consumed. The C02 emissions reported for ammonia production are therefore reduced by a
factor of 0.73 multiplied by total annual domestic urea production, and that amount of C02 emissions is allocated to
urea fertilizer application. Total C02 emissions resulting from nitrogenous fertilizer production do not change as a
result of this calculation, but some of the C02 emissions are attributed to ammonia production and some of the C02
emissions are attributed to urea application.
The calculation of the total non-combustion C02 emissions from nitrogenous fertilizers accounts for C02 emissions
from the application of imported and domestically produced urea. For each ton of imported urea applied, 0.73 tons
of C02 are emitted to the atmosphere. The amount of imported urea applied is calculated based on the net of urea
imports and exports.
All ammonia production and subsequent urea production are assumed to be from the same process—conventional
catalytic reforming of natural gas feedstock, with the exception of ammonia production from petroleum coke
feedstock at one plant located in Kansas. The C02 emission factor for production of ammonia from petroleum coke
is based on plant specific data, wherein all C contained in the petroleum coke feedstock that is not used for urea
Industrial Processes 4-11
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
production is assumed to be emitted to the atmosphere as C02 (Bark 2004). Ammonia and urea are assumed to be
manufactured in the same manufacturing complex, as both the raw materials needed for urea production are
produced by the ammonia production process. The C02 emission factor (3.57 metric tons C02/metric ton NH3) is
applied to the percent of total annual domestic ammonia production from petroleum coke feedstock.
The emission factor of 1.2 metric ton C02/metric ton NH3 for production of ammonia from natural gas feedstock
was taken from the EFMA Best Available Techniques publication, Production of Ammonia (EFMA 1995). The
EFMA reported an emission factor range of 1.15 to 1.30 metric ton C02/metric ton NH3, with 1.2 metric ton
C02/metric ton NH3 as a typical value. The EFMA reference also indicates that more than 99 percent of the CH4
feedstock to the catalytic reforming process is ultimately converted to C02. The emission factor of 3.57 metric ton
C02/metric ton NH3 for production of ammonia from petroleum coke feedstock was developed from plant-specific
ammonia production data and petroleum coke feedstock utilization data for the ammonia plant located in Kansas
(Bark 2004). Ammonia and urea production data (see Table 4-13) were obtained from Coffeyville Resources
(Coffeyville 2005, 2006) and the Census Bureau of the U.S. Department of Commerce (U.S. Census Bureau 1991,
1992, 1993, 1994, 1998, 1999, 2000, 2001a, 2001b, 2002a, 2002b, 2002c, 2003, 2004, 2005, 2006) as reported in
Current Industrial Reports Fertilizer Materials and Related Products annual and quarterly reports. Import and
export data for urea were obtained from the U. S. Census Bureau Current Industrial Reports Fertilizer Materials and
Related Products annual and quarterly reports for 1997 through 2005 (U.S. Census Bureau 1998, 1999, 2000,
2001a, 2001b, 2002a, 2002b, 2002c, 2003, 2004, 2005, 2006), The Fertilizer Institute (TFI2002) for 1993 through
1996, and the United States International Trade Commission Interactive Tariff and Trade DataWeb (U.S. ITC 2002)
for 1990 through 1992 (see Table 4-13).
Table 4-13: Ammonia Production, Urea Production, and Urea Net Imports (Gg)
Year Ammonia Production Urea Production Urea Net Imports
1990
2000
2001
2002
2003
2004
2005
15,425
14,342
11,092
12,577
10,279
10,939
10,143
8,124
6,969
6,080
7,038
5,783
5,755
5,268
1,086
3,241
4,008
2,870
4,250
4,230
4,447
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. 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, and the assumption that 100 percent of the urea production and net imports are used
as fertilizer or in otherwise emissive uses. It is also assumed that ammonia and urea are produced at collocated
plants from the same natural gas raw material.
Such recovery may or may not affect the overall estimate of C02 emissions depending upon the end use to which
the recovered C02 is applied. Further research is required to determine whether byproduct C02 is being recovered
from other ammonia production plants for application to end uses that are not accounted for elsewhere.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-14. Ammonia Manufacture
and Urea Application C02 emissions were estimated to be between 15.0 and 17.6 Tg C02 Eq. at the 95 percent
confidence level. This indicates a range of approximately 8 percent below and 8 percent above the emission
estimate of 16.3 Tg C02 Eq.
4-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
Table 4-14: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Ammonia Manufacture and Urea
Application (Tg C02 Eg. and Percent)
2005 Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Bound
Upper
Bound
Lower Upper
Bound Bound
Ammonia Manufacture
and Urea Application
C02
16.3
15.0
17.6
-8% +8%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of C02 emissions from ammonia manufacture and urea application for the years 2002 and 2003 were
revised to reflect updated data from the U.S. Census Bureau Current Industrial Report. These changes resulted in a
decrease in C02 emissions from urea manufacture of 0.7 Tg C02 Eq. (10 percent) for 2002 and an increase of 0.9
Tg C02 Eq. (13 percent) for 2003.
Planned Improvements
Future improvements to the ammonia-manufacture and urea-application source category include updating emission
factors to include both fuel and feedstock C02 emissions and incorporating C02 capture and storage if U.S. plants
are found to use C02 capture technology. Methodologies will also be updated if additional ammonia-production
plants are found to use hydrocarbons other than natural gas for ammonia production.
4.4. Lime Manufacture (IPCC Source Category 2A2)
Lime is an important manufactured product with many industrial, chemical, and environmental applications. Its
major uses are in steel making, flue gas desulfurization (FGD) systems at coal-fired electric power plants,
construction, and water purification. Lime has historically ranked fifth in total production of all chemicals in the
United States. For U.S. operations, the term "lime" actually refers to a variety of chemical compounds. These
include calcium oxide (CaO), or high-calcium quicklime; calcium hydroxide (Ca(OH)2), or hydrated lime; dolomitic
quicklime ([CaOMgO]); and dolomitic hydrate ([Ca(OH)2»MgO] or [Ca(OH)2»Mg(OH)2]).
Lime production involves three main processes: stone preparation, calcination, and hydration. C02 is generated
during the calcination stage, when limestone—mostly calcium carbonate (CaC03)—is roasted at high temperatures
in a kiln to produce CaO and C02. The C02 is given off as a gas and is normally emitted to the atmosphere. Some
of the C02 generated during the production process, however, is recovered at some facilities for use in sugar
refining and precipitated calcium carbonate (PCC)2 production. It is also important to note that, for certain
applications, lime reabsorbs C02 during use (see Uncertainty, below).
Lime production in the United States—including Puerto Rico—w as reported to be 19,984 thousand metric tons in
2005 (USGS 2006). This resulted in estimated C02 emissions of 13.7 Tg C02 Eq. (or 13,660 Gg) (see Table 4-15
and Table 4-16).
Table 4-15: Net C02 Emissions from Lime Manufacture (Tg C02 Eq.)
Year Tg CP2 Eq.
1990 11.3
2 Precipitated calcium carbonate is a specialty filler used in premium-quality coated and uncoated papers.
Industrial Processes 4-13
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Public Review Draft
Table 4-16: C02 Emissions from Lime Manufacture (Gg)
Year Potential Recovered* Net Emissions
2000
2001
2002
2003
2004
2005
11,766
14,577
13,978
13,381
14,171
14,853
14,831
(1,233)
(1,118)
(1,051)
(1,149)
(1,125)
(1,171)
11,273
13,344
12,861
12,330
13,022
13,728
13,660
* For sugar refining and precipitated calcium carbonate production.
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
The contemporary lime market is distributed across five end-use categories as follows: metallurgical uses, 36
percent; environmental uses, 28 percent; chemical and industrial uses, 21 percent; construction uses, 14 percent; and
refractory dolomite, 1 percent. In the construction sector, hydrated lime is still used to improve durability in plaster,
stucco, and mortars. In 2005, the amount of hydrated lime used for traditional building increased slightly from 2004
levels to 493 metric tons (USGS 2006).
Lime production in 2005 slightly increased over 2004, the third annual increase in production after four years of
decline. Overall, from 1990 to 2005, lime production has increased by 26 percent. The increase in production is
attributed in part to growth in demand for environmental applications, especially flue gas desulfurization
technologies. In 1993, EPA completed regulations under the Clean Air Act capping sulfur dioxide (S02) emissions
from electric utilities. Lime scrubbers' high efficiencies and increasing affordability have allowed the flue gas
desulfurization end-use to expand significantly over the years. Phase II of the Clean Air Act Amendments, which
went into effect on January 1, 2000, remains the driving force behind the growth in the flue gas desulfurization
market (USGS 2003).
Methodology
During the calcination stage of lime manufacture, C02 is given off as a gas and normally exits the system with the
stack gas. To calculate emissions, the amounts of high-calcium and dolomitic lime produced were multiplied by
their respective emission factors. The emission factor is the product of a constant reflecting the mass of C02
released per unit of lime and the average calcium plus magnesium oxide (CaO + MgO) content for lime (95 percent
for both types of lime). The emission factors were calculated as follows:
For high-calcium lime:
[(44.01 g/mole C02) ^ (56.08 g/mole CaO)] x (0.95 CaO/lime) = 0.75 g C02/g lime
For dolomitic lime:
4-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Public Review Draft
[(88.02 g/mole C02) ^ (96.39 g/mole CaO)] x (0.95 CaO/lime) = 0.87 g C02/g lime
Production was adjusted to remove the mass of chemically combined water found in hydrated lime, using the
midpoint of default ranges provided by the IPCC Good Practice Guidance (IPCC 2000). These factors set the
chemically combined water content to 24.3 percent for high-calcium hydrated lime, and 27.3 percent for dolomitic
hydrated lime.
Lime production in the United States was 19,984 thousand metric tons in 2005 (USGS 2006), resulting in potential
C02 emissions of 14.8 Tg C02 Eq. Some of the C02 generated during the production process, however, was
recovered for use in sugar refining and PCC production. Combined lime manufacture by these producers was 1,964
thousand metric tons in 2005. It was assumed that approximately 80 percent of the C02 involved in sugar refining
and PCC was recovered, resulting in actual C02 emissions of 13.7 Tg C02 Eq.
Lime production data (high-calcium- and dolomitic-quicklime, high-calcium- and dolomitic-hydrated, and dead-
burned dolomite) for 1990 through 2005 (see Table 4-17) were obtained from USGS (1992 through 2005). Natural
hydraulic lime, which is produced from CaO and hydraulic calcium silicates, is not produced in the United States
(USGS 2005). Total lime production was adjusted to account for the water content of hydrated lime and is
presented with lime consumption by sugar refining and PCC production in Table 4-18 (USGS 1992 through 2005).
The CaO and CaO'MgO contents of lime were obtained from the IPCC Good Practice Guidance (IPCC 2000).
Since data for the individual lime types (high calcium and dolomitic) was not provided prior to 1997, total lime
production for 1990 through 1996 was calculated according to the three year distribution from 1997 to 1999. For
sugar refining and PCC, it was assumed that 100 percent of lime manufacture and consumption was high-calcium,
based on communication with the National Lime Association (Males 2003).
Table 4-17: High-Calcium- and Dolomitic-Quicklime, High-Calcium- and Dolomitic-Hydrated, and Dead-Burned-
Dolomite Lime Production (Gg)
Year
1990
1995
2000
2001
2002
2003
2004
2005
High-Calcium
Quicklime
11,166
14,300
13,600
13,400
13,900
14,200
14,100
Dolomitic
Quicklime
High-Calcium
Hydrated
Dolomitic
Hydrated
2,234
3,000
2,580
2,420
2,460
3,020
2,990
1,781
1,550
2,030
1,500
2,140
2,140
2,220
319
421
447
431
464
421
474
Dead-Burned
Dolomite
342
¦
¦
200
200
200
200
200
200
Table 4-18: Adjusted Lime Production and Lime Use for Sugar Refining and PCC (Gg)
Year High-Calcium Dolomitic Use for Sugar
Refining and PCC
1990
2000
2001
2002
2003
2004
2005
12,514
15,473
15,137
14,536
15,520
15,820
15,781
2,809
3,506
3,105
2,934
2,998
3,526
3,535
826
2,067
1,874
1,762
1,926
1,887
1,964
Industrial Processes 4-15
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
Uncertainty
The uncertainties contained in these estimates can be attributed to slight differences in the chemical composition of
these products. Although the methodology accounts for various formulations of lime, it does not account for the
trace impurities found in lime, such as iron oxide, alumina, and silica. Due to differences in the limestone used as a
raw material, a rigid specification of lime material is impossible. As a result, few plants manufacture lime with
exactly the same properties.
In addition, a portion of the C02 emitted during lime manufacture will actually be reabsorbed when the lime is
consumed. As noted above, lime has many different chemical, industrial, environmental, and construction
applications. In many processes, C02 reacts with the lime to create calcium carbonate (e.g., water softening). C02
reabsorption rates vary, however, depending on the application. For example, 100 percent of the lime used to
produce precipitated calcium carbonate reacts with C02; whereas most of the lime used in steel making reacts with
impurities such as silica, sulfur, and aluminum compounds. A detailed accounting of lime use in the United States
and further research into the associated processes are required to quantify the amount of C02 that is reabsorbed.3
In some cases, lime is generated from calcium carbonate by-products at pulp mills and water treatment plants.4 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 C02—for reuse in the pulping process. Although this re-generation of lime could be considered a lime
manufacturing process, the C02 emitted during this process is mostly biogenic in origin, and therefore is not
included in Inventory totals.5
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 4-19. Lime C02 emissions were
estimated to be between 12.6 and 14.8 Tg C02 Eq. at the 95 percent confidence level. This indicates a range of
approximately 8 percent below and 8 percent above the emission estimate of 13.7 Tg C02 Eq.
Table 4-19: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lime Manufacture (Tg C02 Eq. and
Percent)
2005
Emission
Source
Gas Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
3 Representatives of the National Lime Association estimate that C02 reabsorption that occurs from the use of lime may offset as
much as a quarter of the C02 emissions from calcination (Males 2003).
4 Some carbide producers may also regenerate lime from their calcium hydroxide by-products, which does not result in
emissions of C02. In making calcium carbide, quicklime is mixed with coke and heated in electric furnaces. The regeneration of
lime in this process is done using a waste calcium hydroxide (hydrated lime) [CaC2 + 2H20 —» C2H2 + Ca(OH)2], not calcium
carbonate [CaC03]. Thus, the calcium hydroxide is heated in the kiln to simply expel the water [Ca(OH)2 + heat —» CaO + H20]
and no C02 is released.
5 Based on comments submitted by and personal communication with Dr. Sergio F. Galeano, Geortia-Pacific Corporation.
4-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
Lime Manufacture C02 117 I2J> 1A8 -8% +8%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Corrections were made to the chemically combined water content percentages of high-calcium hydrated lime and
dolomitic hydrated lime. This change resulted in a 0.2 percent increase in emissions on average throughout the time
series. Estimates of C02 from lime manufacture for the year 2004 were revised to reflect updated data from the
USGS. These changes resulted in a decrease in C02 emissions from lime manufacture of less than one percent for
2004.
Planned Improvements
Future inventories are anticipated to include emissions associated with lime kiln dust (LKD) in the lime emission
estimates. Research will be conducted to determine the availability of LKD data in the United States for inclusion
in the emission estimates.
4.5. Limestone and Dolomite Use (IPCC Source Category 2A3)
Limestone (CaC03) and dolomite (CaC03MgC03)6 are basic raw materials used by a wide variety of industries,
including construction, agriculture, chemical, metallurgy, glass manufacture, and environmental pollution control.
Limestone is widely distributed throughout the world in deposits of varying sizes and degrees of purity. Large
deposits of limestone occur in nearly every state in the United States, and significant quantities are extracted for
industrial applications. For some of these applications, limestone is sufficiently heated during the process and
generates C02 as a by-product. Examples of such applications include limestone used as a flux or purifier in
metallurgical furnaces, as a sorbent in flue gas desulfurization systems for utility and industrial plants, or as a raw
material in glass manufacturing and magnesium production.
In 2005, approximately 12,522 thousand metric tons of limestone and 3,953 thousand metric tons of dolomite were
consumed during production for these applications. Overall, usage of limestone and dolomite resulted in aggregate
C02 emissions of 7.4 Tg C02 Eq. (7,397 Gg) (see Table 4-20 and Table 4-21). Emissions in 2005 increased 10
percent from the previous year and have increased 34 percent overall from 1990 through 2005.
Table 4-20: C02 Emissions from Limestone & Dolomite Use (Tg C02 Eq.)
Activity
1990
1995
2000
2001
2002
2003
2004
2005
Flux Stone
3.0
4.0
2.8
2.5
2.4
2.1
4.1
3.3
Glass Making
0.2 ,
0.5
0.4
0.1
0.1
0.3
0.4
0.4
FGD
1.4
1.7
1.8
2.6
2.8
1.9
1.9
3.0
Magnesium Production
0.1
0.0
0.1
0.1
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
Total
5.5
7.4
6.0
5.7
5.9
4.7
6.7
7.4
Notes: Totals may not sum due to independent rounding. "Other miscellaneous uses" include chemical stone, mine dusting or
acid water treatment, acid neutralization, and sugar refining.
Table 4-21: C02 Emissions from Limestone & Dolomite Use (Gg)
Activity 1990 1995 2000 2001 2002 2003 2004 2005
Flux Stone 2,999 4,004 2,830 2,514 2,405 2,072 4,112 3,265
6 Limestone and dolomite are collectively referred to as limestone by the industry, and intermediate varieties are seldom
distinguished.
Industrial Processes 4-17
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
Limestone 2,5541
Dolomite 446
Glass Making 217
Limestone 1891
Dolomite 281
FGD 1,43 31
Magnesium Production i >4
Other Miscellaneous Uses 819
Total
3,077
927
53
410
122
1,6<>'
41
1,119
5,533 7,359
1,810
1,640
1,330
904
2,023
1,398
1,020
874
1,075
1,168
2,088
1,867
368
113
61
337
350
427
368
113
61
337
350
406
0
0
0
0
0
21
1.774
2,551
2,766
1,932
1,871
2,985
73
53
0
0
0
0
I 916
501
652
380
369
721
j 5,960
5,733
5,885
4,720
6,702
7,397
Notes: Totals may not sum due to independent rounding,
water treatment, acid neutralization, and sugar refining.
Other miscellaneous uses include chemical stone, mine dusting or acid
Methodology
C02 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). This
assumes that all C is oxidized and released. This methodology was used for flux stone, glass manufacturing, flue
gas desulfurization systems, chemical stone, mine dusting or acid water treatment, acid neutralization, and sugar
refining and then converting to C02 using a molecular weight ratio.
Traditionally, the production of magnesium metal was the only other use of limestone and dolomite that produced
C02 emissions. At the start of 2001, there were two magnesium production plants operating in the United States
and they used different production methods. One plant produced magnesium metal using a dolomitic process that
resulted in the release of C02 emissions, while the other plant produced magnesium from magnesium chloride using
a C02-emissions-free process called electrolytic reduction. However, the plant utilizing the dolomitic process
ceased its operations prior to the end of 2001, so beginning in 2002 there were no emissions from this particular
sub-use.
Consumption data for 1990 through 2005 of limestone and dolomite used for flux stone, glass manufacturing, flue
gas desulfurization systems, chemical stone, mine dusting or acid water treatment, acid neutralization, and sugar
refining (see Table 4-22) were obtained from personal communication with Deborah Weaver of the USGS (Weaver
2006) and in the USGS Minerals Yearbook: Crushed Stone Annual Report (USGS 1993, 1995a, 1995b, 1996a,
1997a, 1998a, 1999a, 2000a, 2001a, 2002a, 2003a, 2004a, 2005a). The production capacity data for 1990 through
2005 of dolomitic magnesium metal (see Table 4-23) also came from the USGS (1995c, 1996b, 1997b, 1998b,
1999b, 2000b, 2001b, 2002b, 2003b, 2004b, 2005b, 2006). 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
2005 Minerals Yearbook: Magnesium; therefore, it is assumed that this process continues to be non-existent in the
United States (USGS 2006). 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.
4-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
Public Review Draft
Finally, there is a large quantity of crushed stone reported to the USGS under the category "unspecified uses." A
portion of this consumption is believed to be limestone or dolomite used for emissive end uses. The quantity listed
for "unspecified uses" was, therefore, allocated to each reported end-use according to each end uses fraction of total
consumption in that year.7
Table 4-22: Limestone and Dolomite Consumption (Thousand Metric Tons)
Activity
1990
1995
2000
2001
2002
2003
2004
2005
Flux Stone
6,738
8,935
6,249
5,558
5,275
4,501
8,971
7,086
Limestone
5,804
6,995
4,114
3,727
3,023
2,055
4,599
3,176
Dolomite
933
1,941
2,135
1,831
2,252
2,466
4,373
3,910
Glass Making
489
1,189
836
258
139
765
796
966
Limestone
430
933
836
258
139
765
796
923
Dolomite
59
256
0
0
0
0
0
43
FGD
3,258
3,779 1 ,
4,031
5,798
6,286
4,390
4,253
6,785
Other Miscellaneous Uses
1,835
2,543
2,081
1,138
1,483
863
840
1,638
Total
12,319
16,445
13,197
12,751
13,183
10,520
14,859
16,475
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 4-23: Dolomitic Magnesium Metal Production Capacity (Metric Tons)
Year Production Capacity
1990 35,000
2000 40,000
2001 29,167
2002 0
2003 0
2004 0
200 5 0
Note: Production capacity for 2002, 2003, 2004, and 2005 amounts to zero because the last U.S. production plant employing the
dolomitic process shut down mid-2001 (USGS 2002b, 2003b, 2004b, 2005b, 2006).
Uncertainty
The uncertainty levels presented in this section arise in part due to variations in the chemical composition of
limestone. In addition to calcium carbonate, limestone may contain smaller amounts of magnesia, silica, and sulfur.
The exact specifications for limestone or dolomite used as flux stone vary with the pyrometallurgical process, the
kind of ore processed, and the final use of the slag. Similarly, the quality of the limestone used for glass
manufacturing will depend on the type of glass being manufactured.
The estimates below also account for uncertainty associated with activity data. Much of the limestone consumed in
the United States is reported as "other unspecified uses;" therefore, it is difficult to accurately allocate this
unspecified quantity to the correct end-uses. Also, some of the limestone reported as "limestone" is believed to
actually be dolomite, which has a higher C content. Additionally, there is significant inherent uncertainty associated
with estimating withheld data points for specific end uses of limestone and dolomite. Lastly, the uncertainty of the
estimates for limestone used in glass making is especially high. Large fluctuations in reported consumption exist,
7 This approach was recommended by USGS.
Industrial Processes 4-19
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Public Review Draft
reflecting year-to-year changes in the number of survey responders. The uncertainty resulting from a shifting
survey population is exacerbated by the gaps in the time series of reports. However, since glass making accounts
for a small percent of consumption, its contribution to the overall emissions estimate is low.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-24. Limestone and Dolomite
Use C02 emissions were estimated to be between 6.9 and 7.9 Tg C02 Eq. at the 95 percent confidence level. This
indicates a range of approximately 6 percent below and 6 percent above the emission estimate of 7.4 Tg C02 Eq.
Table 4-24: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Limestone and Dolomite Use (Tg
C02 Eq. and Percent)
2005 Emission
Source
Gas
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Limestone and Dolomite Use
C02
7.4
6.9 7.9
-6% +6%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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.
4.6. Soda Ash Manufacture and Consumption (IPCC Source Category 2A4)
Soda ash (sodium carbonate, Na2C03) is a white crystalline solid that is readily soluble in water and strongly
alkaline. Commercial soda ash is used as a raw material in a variety of industrial processes and in many familiar
consumer products such as glass, soap and detergents, paper, textiles, and food. It is used primarily as an alkali,
either in glass manufacturing or simply as a material that reacts with and neutralizes acids or acidic substances.
Internationally, two types of soda ash are produced—natural and synthetic. The United States produces only natural
soda ash and is second only to China in total soda ash-production. Trona is the principal ore from which natural
soda ash is made.
Only three states produce natural soda ash: Wyoming, California, and Colorado. Of these three states, only net
emissions of C02 from Wyoming were calculated due to specifics regarding the production processes employed in
each state.8 During the production process used in Wyoming, trona ore is treated to produce soda ash. C02 is
generated as a by-product of this reaction, and is eventually emitted into the atmosphere. In addition, C02 may also
be released when soda ash is consumed.
8 In California, soda ash is manufactured using sodium carbonate-bearing brines instead of trona ore. To extract the sodium
carbonate, the complex brines are first treated with C02 in carbonation towers to convert the sodium carbonate into sodium
bicarbonate, which then precipitates from the brine solution. The precipitated sodium bicarbonate is then calcined back into
sodium carbonate. Although C02 is generated as a by-product, the C02 is recovered and recycled for use in the carbonation
stage and is not emitted.
In Colorado, the lone producer of sodium bicarbonate no longer mines trona in the state. Instead, NaHC03 is 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 include the feedstocks mined in Wyoming and shipped to Colorado. In this way, the sodium
bicarbonate production that takes place in Colorado is accounted for in the Wyoming numbers.
4-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Public Review Draft
In 2005, C02 emissions from the manufacture of soda ash from trona were approximately 1.7 Tg C02 Eq. (1,655
Gg). Soda ash consumption in the United States generated 2.6 Tg C02 Eq. (2,573 Gg) in 2005. Total emissions
from soda ash manufacture and consumption in 2005 were 4.2 Tg C02 Eq. (4,228 Gg) (see Table 4-25 and Table
4-26). Emissions have fluctuated since 1990. These fluctuations were strongly related to the behavior of the export
market and the U.S. economy. Emissions in 2005 increased by approximately 0.5 percent from the previous year,
and have increased overall by approximately 2 percent since 1990.
Table 4-25: C02 Emissions from Soda Ash Manufacture and Consumption (Tg C02Eq.)
Year Manufacture Consumption Total
1990
1.4
2.7
4.1
1995
1.6
2.7
2000
2001
2002
2003
2004
2005
1.5
1.5
1.5
1.5
1.6
1.7
2.7
2.6
2.7
2.6
2.6
2.6
4.3
lllllfllfll
4.2
4.1
4.1
4.1
4.2
4.2
Note: Totals may not sum due to independent rounding.
Table 4-26: C02 Emissions from Soda Ash Manufacture and Consumption (Gg)
Year Manufacture Consumption Total
1990
2000
2001
2002
2003
2004
2005
1,431
1,529
1,500
1,470
1,509
1,607
1,655
2,710
2,652
2,648
2,668
2,602
2,598
2,573
4,141
4,181
4,147
4,139
4,111
4,205
4,228
Note: Totals may not sum due to independent rounding.
The United States represents about one-fourth of total world soda ash output. The approximate distribution of soda
ash by end-use in 2005 was glass making, 49 percent; chemical production, 27 percent; soap and detergent
manufacturing, 10 percent; distributors, 5 percent; flue gas desulfurization, 2 percent; water treatment, 1 percent;
pulp and paper production, 1 percent; and miscellaneous, 4 percent (USGS 2006).
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. C02 and water are generated as by-products of the calcination process. C02
emissions from the calcination of trona can be estimated based on the following chemical reaction:
2(Na H(CO ) -2H O) 3Na CO + 5H O + CO
3 3 2 2 23 2 2
[trona] [soda ash]
Industrial Processes 4-21
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Public Review Draft
Based on this formula, approximately 10.27 metric tons of trona are required to generate one metric ton of C02.
Thus, the 17 million metric tons of trona mined in 2005 for soda ash production (USGS 2006) resulted in C02
emissions of approximately 1.7 Tg C02 Eq. (1,655 Gg).
Once manufactured, most soda ash is consumed in glass and chemical production, with minor amounts in soap and
detergents, pulp and paper, flue gas desulfurization and water treatment. As soda ash is consumed for these
purposes, additional C02 is usually emitted. In these applications, it is assumed that one mole of C is released for
every mole of soda ash used. Thus, approximately 0.113 metric tons of C (or 0.415 metric tons of C02) are released
for every metric ton of soda ash consumed.
The activity data for trona production and soda ash consumption (see Table 4-27) were taken from USGS (1994
through 2006). Soda ash manufacture and consumption data were collected by the USGS from voluntary surveys of
the U.S. soda ash industry.
Table 4-27: Soda Ash Manufacture and Consumption (Gg)
Year Manufacture* Consumption
1990
14,700
6 530
2000
2001
2002
2003
2004
2005
15,700
15,400
15,100
15,500
16,500
17,000
6,390
6,380
6,430
6,270
6,260
6,200
: Soda ash manufactured from trona ore only.
Uncertainty
Emission estimates from soda ash manufacture have relatively low associated uncertainty levels in that reliable and
accurate data sources are available for the emission factor and activity data. The primary source of uncertainty,
however, results from the fact that emissions from soda ash consumption are dependent upon the type of processing
employed by each end-use. Specific information characterizing the emissions from each end-use is limited.
Therefore, there is uncertainty surrounding the emission factors from the consumption of soda ash.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-28. Soda Ash Manufacture
and Consumption C02 emissions were estimated to be between 3.9 and 4.5 Tg C02 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
C02 Eq.
Table 4-28: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Soda Ash Manufacture and
Consumption (Tg C02 Eq. and Percent)
2005
Emission
Source
Gas
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Lower Upper
Bound Bound
Bound Bound
Soda Ash Manufacture and
Consumption
C02
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.
4-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Planned Improvements
2 Future inventories are anticipated to estimate emissions from glass production and other use of carbonates. These
3 inventories will extract soda ash consumed for glass production and other use of carbonates from the current soda
4 ash consumption emission estimates and include them under those sources.
5 4.7. Titanium Dioxide Production (IPCC Source Category 2B5)
6 Titanium dioxide (Ti02) is a metal oxide manufactured from titanium ore, and is principally used as a pigment.
7 Titanium dioxide is a principal ingredient in white paint, and is also used as a pigment in the manufacture of white
8 paper, foods, and other products. There are two processes for making Ti02: the chloride process and the sulfate
9 process. The chloride process uses petroleum coke and chlorine as raw materials and emits process-related C02.
10 The sulfate process does not use petroleum coke or other forms of C as a raw material and does not emit C02.
11 The chloride process is based on the following chemical reactions:
12 2 FeTi03 + 7 Cl2 + 3 C -> 2 TiCl4 + 2 FeCl3 + 3 C02
13 2 TiCl4 + 2 02 -> 2 Ti02 + 4 Cl2
14 The C in the first chemical reaction is provided by petroleum coke, which is oxidized in the presence of the chlorine
15 and FeTi03 (the Ti-containing ore) to form C02. The majority of U.S. Ti02 was produced in the United States
16 through the chloride process, and a special grade of petroleum coke is manufactured specifically for this purpose
17 Emissions of C02 in 2005 were 1.9 Tg C02 Eq. (1,921 Gg), a decrease of 18 percent from the previous year and an
18 increase of 47 percent since 1990. The trend upward, due to increasing production within the industry, was
19 disrupted in 2005 as a result of Hurricane Katrina (see Table 4-29), which disrupted production of titanium dioxide
20 pigment in Mississippi (USGS 2006).
21 Table 4-29: C02 Emissions from Titanium Dioxide (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
1990 1.3 1,308
2000 1.9 1,918
2001 1.9 1,857
2002 2.0 1,997
2003 2.0 2,013
2004 2.3 2,259
2005 1.9 1,921
22
23 Methodology
24 Emissions of C02 from Ti02 production were calculated by multiplying annual Ti02 production by chloride-
25 process-specific emission factors.
26 Data were obtained for the total amount of Ti02 produced each year. For years previous to 2004, it was assumed
27 that Ti02 was produced using the chloride process and the sulfate process in the same ratio as the ratio of the total
28 U.S. production capacity for each process. As of 2004, the last remaining sulfate-process plant in the United States
29 closed. As a result, all U.S. current Ti02 production results from the chloride process (USGS 2005). An emission
30 factor of 0.4 metric tons C/metric ton Ti02 was applied to the estimated chloride-process production. It was
31 assumed that all Ti02 produced using the chloride process was produced using petroleum coke, although some Ti02
32 may have been produced with graphite or other C inputs. The amount of petroleum coke consumed annually in
Industrial Processes 4-23
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
Ti02 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 Ti02 chloride process was taken from the report, Everything You've Always Wanted to
Know about Petroleum Coke (Onder and Bagdoyan 1993). Titanium dioxide production data and the percentage of
total Ti02 production capacity that is chloride process for 1990 through 2005 (see Table 4-30) were obtained from a
personal communication with Deborah Kramer, USGS Commodity Specialist, of the USGS (Kramer 2006) and
through the Minerals Yearbook: Titanium Annual Report (USGS 1991 through 2005). Percentage chloride-process
data were not available for 1990 through 1993, and data from the 1994 USGS Minerals Yearbook were used for
these years. Because a sulfate-process plant closed in September 2001, the chloride-process percentage for 2001
was estimated based on a discussion with Joseph Gambogi (2002). By 2002, only one sulfate plant remained online
in the United States and this plant closed in 2004 (USGS 2005). The composition data for petroleum coke were
obtained from Onder and Bagdoyan (1993).
Table 4-30: Titanium Dioxide Production (Gg)
Year Gg
1990
2000
2001
2002
2003
2004
2005
979
1,400
1,330
1,410
1,420
1,540
1,310
Uncertainty
Although some Ti02 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 C02 per unit of Ti02 produced as compared to that generated through the use of petroleum coke in
production. While the most accurate method to estimate emissions would be to base calculations on the amount of
reducing agent used in each process rather than on the amount of Ti02 produced, sufficient data were not available
to do so.
Also, annual Ti02 is not reported by USGS by the type of production process used (chloride or sulfate). Only the
percentage of total production capacity by process is reported. The percent of total Ti02 production capacity that
was attributed to the chloride process was multiplied by total Ti02 production to estimate the amount of Ti02
produced using the chloride process (since, as of 2004, the last remaining sulfate-process plant in the United States
closed). This assumes that the chloride-process plants and sulfate-process plants operate at the same level of
utilization. Finally, the emission factor was applied uniformly to all chloride-process production, and no data were
available to account for differences in production efficiency among chloride-process plants. In calculating the
amount of petroleum coke consumed in chloride-process Ti02 production, literature data were used for petroleum
coke composition. Certain grades of petroleum coke are manufactured specifically for use in the Ti02 chloride
process; however, this composition information was not available.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-31. Titanium dioxide
consumption C02 emissions were estimated to be between 1.6 and 2.2 Tg C02 Eq. at the 95 percent confidence
level. This indicates a range of approximately 16 percent below and 16 percent above the emission estimate of 1.9
Tg C02 Eq.
Table 4-31: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Titanium Dioxide Production (Tg
C02 Eq. and Percent)
4-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
2005
Emission
Source
Gas
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Titanium Dioxide Production
C02
1.9
1.6 2.2
-16% +16%
1 a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
2
3 Planned Improvements
4 Future improvements to Ti02 production methodology include researching the significance of titanium-slag
5 production in electric furnaces and synthetic-rutile production using the Becher process in the United States.
6 Significant use of these production processes will be included in future estimates.
7 4.8. Ferroalloy Production (IPCC Source Category 2C2)
8 C02 and CH4 are emitted from the production of several ferroalloys. Ferroalloys are composites of iron and other
9 elements such as silicon, manganese, and chromium. When incorporated in alloy steels, ferroalloys are used to alter
10 the material properties of the steel. Estimates from two types of ferrosilicon (25 to 55 percent and 56 to 95 percent
11 silicon), silicon metal (about 98 percent silicon), and miscellaneous alloys (36 to 65 percent silicon) have been
12 calculated. Emissions from the production of ferrochromium and ferromanganese are not included here because of
13 the small number of manufacturers of these materials in the United States. Subsequently, government information
14 disclosure rules prevent the publication of production data for these production facilities.
15 Similar to emissions from the production of iron and steel, C02 is emitted when metallurgical coke is oxidized
16 during a high-temperature reaction with iron and the selected alloying element. Due to the strong reducing
17 environment, CO is initially produced, and eventually oxidized to C02. A representative reaction equation for the
18 production of 50 percent ferrosilicon is given below:
19 Fe203 +2Si02 +7C2FeSi + 7CO
20 While most of the C contained in the process materials is released to the atmosphere as C02, a percentage is also
21 released as CH4 and other volatiles. The amount of CH4 that is released is dependent on furnace efficiency,
22 operation technique, and control technology.
23 Emissions of C02 from ferroalloy production in 2005 were 1.4 Tg C02 Eq. (1,392 Gg) (see Table 4-32 and Table
24 4-33), which is a 2 percent decrease from the previous year and a 35 percent reduction since 1990. Emissions of
25 CH4 from ferroalloy production in 2005 were 0.01 Tg C02 Eq. (0.4 Gg), which is a 1 percent decrease from the
26 previous year and a 43 percent decrease since 1990.
27 Table 4-32: C02 and CH4 Emissions from Ferroalloy Production (Tg C02 Eq.)
Year
1990
I 1995
2000
2001
2002
2003
2004
2005
C02
2.2
2.0
1.9
1.5
1.3
1.3
1.4
1.4
ch4
+
1 +
+
+
+
+
+
+
Total
2.2
j 2.0
1.9
1.5
1.4
1.3
1.4
1.4
28 + Does not exceed 0.05 Tg C02 Eq.
29 Note: Totals may not sum due to independent rounding.
30
31 Table 4-33: C02 and CH4 Emissions from Ferroalloy Production (Gg)
Year 1990 1995 2000 2001 2002 2003 2004 2005
C02 2,152 2,03<> 1,893 1,459 1,349 1,305 1,419 1,392
CH4 0/7 (U- 0.5 0.4 0.4 0.4 0.4 0.4
Industrial Processes 4-25
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
Methodology
Emissions of C02 and CH4 from ferroalloy production were calculated by multiplying annual ferroalloy production
by material-specific emission factors. Emission factors taken from the 2006IPCC Guidelines for National
Greenhouse Gas Inventories (IPCC 2006) were applied to ferroalloy production. For ferrosilicon alloys containing
25 to 55 percent silicon and miscellaneous alloys (including primarily magnesium-ferrosilicon, but also including
other silicon alloys) containing 32 to 65 percent silicon, an emission factor for 45 percent silicon was applied for
C02 (2.5 metric tons C02/metric ton of alloy produced) and an emission factor for 65 percent silicon was applied
for CH4 (1 kg C02/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 C02 and CH4 (4 metric tons
C02/metric ton alloy produced and 1 kg CH4/metric ton of alloy produced, respectively). The emission factors for
silicon metal equaled 5 tons C02/metric ton metal produced and 1.2 kg CH |/mctric 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 2005 (see Table 4-34) were obtained from the USGS through personal
communications with the USGS Silicon Commodity Specialist (Corathers 2006) and through the Minerals
Yearbook: Silicon Annual Report (USGS 1991 through 2005). 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 4-34). The
composition data for petroleum coke was obtained from Onder and Bagdoyan (1993).
Table 4-34: Production of Ferroalloys (Metric Tons)
Year
Ferrosilicon
25%-55%
Ferrosilicon
56%-95%
Silicon Metal
Misc. Alloys
32-65%
1990
2000
2001
2002
2003
2004
2005
321,385
229,000
167,000
156,000
115,000
120,000
123,000
109,566
100,000
89,000
98,600
80,500
92,300
86,100
145,744
184,000
137,000
113,000
139,000
150,000
148,000
72,442
NA
NA
NA
NA
NA
NA
NA (Not Available)
Uncertainty
Although some ferroalloys may be produced using wood or other biomass as a C source, information and data
regarding these practices were not available. Emissions from ferroalloys produced with wood or other biomass
would not be counted under this source because wood-based C is of biogenic origin.9 Even though emissions from
ferroalloys produced with coking coal or graphite inputs would be counted in national trends, they may be generated
with varying amounts of C02 per unit of ferroalloy produced. The most accurate method for these estimates would
be to base calculations on the amount of reducing agent used in the process, rather than the amount of ferroalloys
produced. These data, however, were not available.
9 Emissions and sinks of biogenic carbon are accounted for in the Land-Use Change, and Forestry chapter.
4-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Emissions of CH4 from ferroalloy production will vary depending on furnace specifics, such as type, operation
2 technique, and control technology. Higher heating temperatures and techniques such as sprinkle charging will
3 reduce CH4 emissions; however, specific furnace information was not available or included in the CH4 emission
4 estimates.
5 Also, annual ferroalloy production is now reported by the USGS in three broad categories: ferroalloys containing 25
6 to 55 percent silicon (including miscellaneous alloys), ferroalloys containing 56 to 95 percent silicon, and silicon
7 metal. It was assumed that the IPCC emission factors apply to all of the ferroalloy production processes, including
8 miscellaneous alloys. Finally, production data for silvery pig iron (alloys containing less than 25 percent silicon)
9 are not reported by the USGS to avoid disclosing company proprietary data. Emissions from this production
10 category, therefore, were not estimated.
11 The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-35. Ferroalloy production C02
12 emissions were estimated to be between 1.2 and 1.6 Tg C02 Eq. at the 95 percent confidence level. This indicates a
13 range of approximately 13 percent below and 13 percent above the emission estimate of 1.4 Tg C02 Eq. Ferroalloy
14 production CH4 emissions were estimated to be between a range of approximately 12 percent below and 12 percent
15 above the emission estimate of 0.01 Tg C02 Eq. .
16 Table 4-35: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Ferroalloy Production (Tg C02 Eq.
17 and Percent)
Source
Gas
2005 Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Lower
Upper
Bound Bound
Bound
Bound
Ferroalloy Production
C02
1.4
1.2 1.6
-13%
+13%
Ferroalloy Production
ch4
+
+ +
-12%
+12%
18 a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
19 + Does not exceed 0.05 Tg C02 Eq.
20
21 Recalculations Discussion
22 Estimates of C02 emissions from ferroalloy production were revised for the entire time series to reflect updated
23 emission factors based on the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006). This
24 change resulted in a 9.5 percent (0.2 Tg C02 Eq.) increase in emissions on average throughout the timeseries.
25 Estimates of CH4 emissions are included for the first time during the current inventory year.
26 Planned Improvements
27 Future improvements to the ferroalloy production source category include research into the data availability for
28 ferroalloys other than ferrosilicon and silicon metal. If data are available, emissions will be estimated for those
29 ferroalloys. Additionally, research will be conducted to determine whether data are available concerning raw
30 material consumption (e.g., coal coke, limestone and dolomite flux, etc.) for inclusion in ferroalloy production
31 emission estimates.
32 4.9. Phosphoric Acid Production (IPCC Source Category 2B5)
33 Phosphoric acid (H3P04) is a basic raw material in the production of phosphate-based fertilizers. Phosphate rock is
34 mined in Florida, North Carolina, Idaho, Utah, and other areas of the United States and is used primarily as a raw
35 material for phosphoric acid production. The production of phosphoric acid from phosphate rock produces
36 byproduct gypsum (CaS04-2H20), referred to as phosphogypsum.
37 The composition of natural phosphate rock varies depending upon the location where it is mined. Natural
38 phosphate rock mined in the United States generally contains inorganic C in the form of calcium carbonate
Industrial Processes 4-27
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
(limestone) and also may contain organic C. The chemical composition of phosphate rock (francolite) mined in
Florida is:
Caio-x-y Nax Mgy (PO4)6-x(CO3)xF2+0.4x
The calcium carbonate component of the phosphate rock is integral to the phosphate rock chemistry. Phosphate
rock can also contain organic C that is physically incorporated into the mined rock but is not an integral component
of the phosphate rock chemistry. Phosphoric acid production from natural phosphate rock is a source of C02
emissions, due to the chemical reaction of the inorganic C (calcium carbonate) component of the phosphate rock.
The phosphoric acid production process involves chemical reaction of the calcium phosphate (Ca3(P04)2)
component of the phosphate rock with sulfuric acid (H2S04) and recirculated phosphoric acid (H3P04) (EFMA
1997). The primary chemical reactions for the production of phosphoric acid from phosphate rock are:
Ca3(P04)2 + 4H3P04 3Ca(H2P04)2
3Ca(H2P04)2 + 3H2S04 + 6H20 -> 3CaS04 6H20 + 6H3P04
The limestone (CaC03) component of the phosphate rock reacts with the sulfuric acid in the phosphoric acid
production process to produce calcium sulfate (phosphogypsum) and C02. The chemical reaction for the
limestone-sulfuric acid reaction is:
CaC03 + H2S04 + H20 CaS04 2H20 + C02
Total marketable phosphate rock production in 2005 was 36.0 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, 2.6 million metric tons of crude phosphate rock was imported
for consumption in 2005. Marketable phosphate rock production, including domestic production and imports for
consumption, decreased by approximately 1.0 percent between 2004 and 2005. However, over the 1990 to 2005
period, production decreased by 12 percent. The 35.3 million metric tons produced in 2001 was the lowest
production level recorded since 1965 and was driven by a worldwide decrease in demand for phosphate fertilizers.
Total C02 emissions from phosphoric acid production were 1.4 Tg C02 Eq. (1,383 Gg) in 2005 (see Table 4-36).
Table 4-36: C02 Emissions from Phosphoric Acid Production (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
1990 1.5 1,529
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
Methodology
C02 emissions from production of phosphoric acid from phosphate rock is calculated by multiplying the average
amount of calcium carbonate contained in the natural phosphate rock by the amount of phosphate rock that is used
annually to produce phosphoric acid, accounting for domestic production and net imports for consumption.
From 1993 to 2004, the USGS Mineral Yearbook: Phosphate Rock disaggregated phosphate rock mined annually in
Florida and North Carolina phosphate rock mined annually in Idaho and Utah, and reported the annual amounts of
4-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
phosphate rock exported and imported for consumption (see Table 4-37). For the years 1990, 1991, 1992, and
2005, 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 2005 were obtained from USGS Minerals Yearbook: Phosphate Rock
(USGS 1994 through 2006). In 2004 and 2005, the USGS reported no exports of phosphate rock from U.S.
producers (USGS 2005, 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
4-38).
Carbonate content data for phosphate rock mined in Florida are used to calculate the C02 emissions from
consumption of phosphate rock mined in Florida and North Carolina (87 percent of domestic production) and
carbonate content data for phosphate rock mined in Morocco are used to calculate C02 emissions from consumption
of imported phosphate rock. The C02 emissions calculation is based on the assumption that all of the domestic
production of phosphate rock is used in uncalcined form. 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 2005). Carbonate content data for uncalcined phosphate rock mined in Idaho and Utah (13
percent of domestic production) were not available, and carbonate content was therefore estimated from the
carbonate content data for calcined phosphate rock mined in Idaho.
The C02 emissions calculation methodology is based on the assumption that all of the inorganic C (calcium
carbonate) content of the phosphate rock reacts to C02 in the phosphoric acid production process and is emitted
with the stack gas. The methodology also assumes that none of the organic C content of the phosphate rock is
converted to C02 and that all of the organic C content remains in the phosphoric acid product.
Table 4-37: Phosphate Rock Domestic Production, Exports, and Imports (Gg)
Location/Year 1990 1995 2000 2001 2002 2003 2004 2005
U.S. Production3
49,800
! 43,720
37,370
32,830
34,720
36,410
36,530
36,000
FL & NC
42,494
! 38,100
31,900
28,100
29,800
31,300
31,600
31,140
ID & UT
7,306
1 5,620
5,470
4,730
4,920
5,110
4,930
4,860
Exports—FL & NC
6,240
2,760
1 299
9
62
64
-
-
Imports—Morocco
451
I 1,800
1 1,930
2,500
2,700
2,400
2,500
2,630
Total U.S. Consumption
44,011
| 42,760
I 39,001
35,321
37,358
38,746
39,030
38,630
a USGS does not disaggregate production data regionally (FL & NC and ID & UT) for 1990 and 2005. Data for those years are
estimated based on the remaining time series distribution.
- Assumed equal to zero.
Table 4-38: Chemical Composition of Phosphate Rock (percent by weight)
Central
North Carolina
Idaho
Composition
Florida
North Florida
(calcined)
(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 C02)
3.67
3.43
1.50
1.00
5.00
Source: FIPR 2003
- Assumed equal to zero.
Industrial Processes 4-29
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Public Review Draft
Uncertainty
Phosphate rock production data used in the emission calculations are developed by the USGS through monthly and
semiannual voluntary surveys of the active phosphate rock mines during 2005. For previous years in the timeseries,
USGS provided the data disaggregated regionally; however, for 2005 only total U.S. phosphate rock production
were reported. Regional production for 2005 was estimated based on regional-production data from previous the
year and multiplied by regionally-specific emission factors. There is uncertainty associated with the degree to
which the estimated 2005 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 C02 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 C02 emissions from phosphoric acid production.
A third source of uncertainty is the assumption that all domestically-produced phosphate rock is used in phosphoric
acid production and used without first being calcined. Calcination of the phosphate rock would result in conversion
of some of the organic C in the phosphate rock into C02. However, according to the USGS, only one producer in
Idaho is currently calcining phosphate rock, and no data were available concerning the annual production of this
single producer (USGS 2005). 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 10 percent of domestically-produced phosphate rock is used to manufacture elemental
phosphorus and other phosphorus-based chemicals, rather than phosphoric acid (USGS 2006). According to USGS,
there is only one domestic producer of elemental phosphorus, in Idaho, and no data were available concerning the
annual production of this single producer. Elemental phosphorus is produced by reducing phosphate rock with coal
coke, and it is therefore assumed that 100 percent of the carbonate content of the phosphate rock will be converted
to C02 in the elemental phosphorus production process. The calculation for C02 emissions is based on the
assumption that phosphate rock consumption, for purposes other than phosphoric acid production, results in C02
emissions from 100 percent of the inorganic C content in phosphate rock, but none from the organic C content.
This phosphate rock, consumed for other purposes, constitutes approximately 10 percent of total phosphate rock
consumption.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-39. Phosphoric acid
production C02 emissions were estimated to be between 1.1 and 1.6 Tg C02 Eq. at the 95 percent confidence level.
This indicates a range of approximately 18 percent below and 19 percent above the emission estimate of 1.4 Tg C02
Eq.
Table 4-39: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Phosphoric Acid Production (Tg
C02 Eq. and Percent)
2005 Emission
Uncertainty Range Relative to Emission Estimate"
Source
Gas
Estimate
(T2 C02 Eq.)
(T2 C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower
Bound
Upper
Bound
Phosphoric Acid Production
C02
1.4
1.1 1.6
-18%
+19%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
4-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
4.10. Carbon Dioxide Consumption (IPCC Source Category 2B5)
C02 is used for a variety of commercial applications, including food processing, chemical production, carbonated
beverage production, and refrigeration, and is also used in petroleum production for enhanced oil recovery (EOR).
C02 used for EOR is injected into the underground reservoirs to increase the reservoir pressure to enable additional
petroleum to be produced.
For the most part, C02 used in non-EOR applications will eventually be released to the atmosphere, and for the
purposes of this analysis C02 used in commercial applications other than EOR is assumed to be emitted to the
atmosphere. C02 used in EOR applications is discussed in the Energy Chapter under "Carbon Capture and Storage,
including Enhanced Oil Recovery" and is not discussed in this section.
C02 is produced from naturally occurring C02 reservoirs, as a by-product from the energy and industrial production
processes (e.g., ammonia production, fossil fuel combustion, ethanol production), and as a by-product from the
production of crude oil and natural gas, which contain naturally occurring C02 as a component. Only C02
produced from naturally occurring C02 reservoirs and used in industrial applications other than EOR is included in
this analysis. Neither by-product C02 generated from energy or industrial production processes nor C02 separated
from crude oil and natural gas are included in this analysis for a number of reasons. C02 captured from biogenic
sources (e.g., ethanol production plants) is not included in the inventory. C02 captured from crude oil and gas
production is used in EOR applications and is therefore reported in the Energy Chapter. Any C02 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 C02 emissions from such capture and use are
therefore accounted for under Ammonia Production, Fossil Fuel Combustion, or other appropriate source category.
C02 is produced as a by-product of crude oil and natural gas production. This C02 is separated from the crude oil
and natural gas using gas processing equipment, and may be emitted directly to the atmosphere, or captured and
reinjected into underground formations, used for EOR, or sold for other commercial uses. A further discussion of
C02 used in EOR is described in the Energy Chapter under "Box 3-3 Carbon Dioxide Transport, Injection, and
Geological Storage." The only C02 consumption that is accounted for in this analysis is C02 produced from
naturally-occurring C02 reserviors that is used in commercial applications other than EOR.
There are currently two facilities, one in Mississippi and one in New Mexico, producing C02 from naturally
occurring C02 reservoirs for use in both EOR and in other commercial applications (e.g., chemical manufacturing,
food production). There are other naturally occurring C02 reservoirs, mostly located in the western U.S. Facilities
are producing C02 from these natural reservoirs, but they are only producing C02 for EOR applications, not for
other commercial applications (Allis et al. 2000). C02 production from these facilities is discussed in the Energy
Chapter.
In 2005, the amount of C02 produced by the Mississippi and New Mexico facilities for commercial applications and
subsequently emitted to the atmosphere were 1.3 Tg C02Eq. (1,324 Gg) (see Table 4-40). This amount represents a
increase of 10 percent from the previous year and a decrease of 6 percent from emissions in 1990. This decrease
was due to a decrease in the percent of the Mississippi facility's total reported production that was used for
commercial applications. During this period the Mississippi facility dedicated more of its total production to EOR.
Table 4-40: C02 Emissions from C02 Consumption (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
1990 1.4 1,415
1995
1.4
1,423
2000
2001
2002
2003
2004
0.8
1.4
1.0
1.3
1.2
1,416
825
978
1,310
1,199
Industrial Processes 4-31
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
2005
1.3
1,324
Methodology
C02 emission estimates for 1990 through 2005 were based on production data for the two facilities currently
producing C02 from naturally-occurring C02 reservoirs for use in non-EOR applications. Some of the C02
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 C02 production used in commercial
applications other than EOR is eventually released into the atmosphere.
C02 production data for the Jackson Dome, Mississippi facility and the percentage of total production that was used
for EOR and in non-EOR applications were obtained from the Advanced Resources Institute (ARI2006) for 1990
to 2000 and from the Annual Reports for Denbury Resources (Denbury Resources 2002, 2003, 2004, 2005, 2006)
for 2001 to 2005. Denbury Resources reported the average C02 production in units of MMCF C02 per day for
2001 through 2005 and reported the percentage of the total average annual production that was used for EOR. C02
production data for the Bravo Dome, New Mexico facility were obtained from the New Mexico Bureau of Geology
and Mineral Resources for the years 1990 through 2003 (Broadhead 2006). The New Mexico Bureau of Geology
reported production in billion cubic feet per year. According to the New Mexico Bureau, the amount of C02
produced from Bravo Dome for use in non-EOR applications is less than one percent of total production
(Broadhead 2003a). Production data for 2004 and 2005 were not available for Bravo Dome, so it is assumed that
the production values for those years are equal to the 2003 value.
Table 4-41: C02 Production (Gg C02) and the Percent Used for Non-EOR Applications for Jackson Dome and
Bravo Dome
Year Jackson Dome C02
Production (Gg)
Jackson Dome % Used
for Non-EOR
Bravo Dome C02
Production (Gg)
Bravo Dome % Used
for Non-EOR
2000
2001
2002
2003
2004
2005
1,353
1,624
2,010
3,286
4,214
4,678
100%
47%
46%
38%
27%
27%
6,328
6,196
5,295
6,090
6,090
6,090
1%
1%
1%
1%
1%
1%
Uncertainty
Uncertainty is associated with the number of facilities that are currently producing C02from naturally occurring
C02 reservoirs for commercial uses other than EOR, and for which the C02 emissions are not accounted for
elsewhere. Research indicates that there are only two such facilities, which are in New Mexico and Mississippi;
however, additional facilities may exist that have not been identified. In addition, it is possible that C02 recovery
exists in particular production and end-use sectors that are not accounted for elsewhere. Such recovery may or may
not affect the overall estimate of C02 emissions from that sector depending upon the end use to which the recovered
C02 is applied. Further research is required to determine whether C02 is being recovered from other facilities for
application to end uses that are not accounted for elsewhere.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-42. C02 consumption C02
emissions were estimated to be between 1.1 and 1.6 Tg C02 Eq. at the 95 percent confidence level. This indicates a
range of approximately 16 percent below to 21 percent above the emission estimate of 1.3 Tg C02 Eq.
Table 4-42: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from C02 Consumption (Tg C02 Eq. and
Percent)
4-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Source
2005 Emission
Gas Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
C02 Consumption
C02 1.3
1.1 1.6
-16% +21%
1 a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
2
3 Recalculations Discussion
4 Data for total Bravo Dome C02 production were updated for the entire time series based on new production data
5 from the facility. Data for C02 production from Jackson Dome were provided for years 1990 through 2000 for the
6 first time during the current inventory year. These changes resulted in an average emission increase of 70 percent
7 for years 1990 through 2000 and an average emission increase of less than one percent for years 2001 to 2005.
8 4.11. Zinc Production (IPCC Source Category 2C5)
9 Zinc production in the United States consists of both primary and secondary processes. Primary production
10 techniques used in the United States are the electro-thermic and electrolytic process while secondary techniques
11 used in the United States include a range of metallurgical, hydrometallurgical, and pyrometallurgical processes.
12 Worldwide primary zinc production also employs a pyrometallurgical process using the Imperial Smelting Furnace
13 process; however, this process is not used in the United States (Sjardin 2003). Of the primary and secondary
14 processes used in the United States, the electro-thermic process results in non-energy C02 emissions, as does the
15 Waelz Kiln process—a technique used to produce secondary zinc from electric-arc furnace (EAF) dust (Viklund-
16 White 2000).
17 During the electro-thermic zinc production process, roasted zinc concentrate and, when available, secondary zinc
18 products enter a sinter feed where they are burned to remove impurities before entering an electric retort furnace.
19 Metallurgical coke added to the electric retort furnace reduces the zinc oxides and produces vaporized zinc, which is
20 then captured in a vacuum condenser. This reduction process produces non-energy C02 emissions (Sjardin 2003).
21 The electrolytic zinc production process does not produce non-energy C02 emissions.
22 In the Waelz Kiln process, EAF dust, which is captured during the recycling of galvanized steel, enters a kiln along
23 with a reducing agent—often metallurgical coke. When kiln temperatures reach approximately 1100-1200°C, zinc
24 fumes are produced, which are combusted with air entering the kiln. This combustion forms zinc oxide, which is
25 collected in a baghouse or electrostatic precipitator, and is then leached to remove chloride and fluoride. Through
26 this process, approximately 0.33 tons of zinc are produced for every ton of EAF dust treated (Viklund-White 2000).
27 In 2005, U.S. primary and secondary zinc production totaled 540,200 metric tons (Gabby 2006). The resulting
28 emissions of C02 from zinc production in 2005 were estimated to be 0.5 Tg C02 Eq. (460 Gg) (see Table 4-43). All
29 2005 C02 emissions result from secondary zinc production.
30 Table 4-43: C02 Emissions from Zinc Production (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
1990 0.9 939
2000 1.1 1,129
2001 1.0 976
2002 0.9 927
2003 0.5 502
2004 0.5 472
2005 0.5 460
Industrial Processes 4-33
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Public Review Draft
After a gradual increase in total emissions from 1990 to 2000, largely due to an increase in secondary zinc
production, 2005 emissions have decreased by nearly half that of 1990 (49 percent) due to the closing of an electro-
thermic-process zinc plant inMonaca, PA (USGS 2004).
Methodology
Non-energy C02 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 C02/ton zinc
produced for emissive zinc production processes; however, this emission factor is based on the Imperial Smelting
Furnace production process. Because the Imperial Smelting Furnace production process is not used in the United
States, emission factors specific to those emissive zinc production processes used in the United States, which consist
of the electro-thermic and Waelz Kiln processes, were needed. Due to the limited amount of information available
for these electro-thermic processes, only Waelz Kiln process-specific emission factors were developed. These
emission factors were applied to both the Waelz Kiln process and the electro-thermic zinc production processes. A
Waelz Kiln emission factor based on the amount of zinc produced was developed based on the amount of
metallurgical coke consumed for non-energy purposes per ton of zinc produced, 1.19 metric tons coke/metric ton
zinc produced (Viklund-White 2000), and the following equation:
1.19 metric tons coke 0.84 metric tons C 3.67 metric tons C02 3.66 metric tons C02
EF = x x =
Waelz Kiln metric tons zinc metric ton coke metric ton C metric ton zinc
The USGS disaggregates total U.S. primary zinc production capacity into zinc produced using the electro-thermic
process and zinc produced using the electrolytic process; however, the USGS does not report the amount of zinc
produced using each process, only the total zinc production capacity of the zinc plants using each process. The total
electro-thermic zinc production capacity is divided by total primary zinc production capacity to estimate the percent
of primary zinc produced using the electro-thermic process. This percent is then multiplied by total primary zinc
production to estimate the amount of zinc produced using the electro-thermic process, and the resulting value is
multiplied by the Waelz Kiln process emission factor to obtain total C02 emissions for primary zinc production.
According to the USGS, the only remaining plant producing primary zinc using the electro-thermic process closed
in 2003 (USGS 2004). Therefore, C02 emissions for primary zinc production are reported only for years 1990
through 2002.
In the United States, secondary zinc is produced through either the electro-thermic or Waelz Kiln process. In 1997,
the Horsehead Corporation plant, located in Monaca, PA, produced 47,174 metric tons of secondary zinc using the
electro-thermic process (Queneau et al. 1998). This is the only plant in the United States that uses the electro-
thermic process to produce secondary zinc, which, in 1997, accounted for 13 percent of total secondary zinc
production. This percentage was applied to all years within the time series up until the Monaca plant's closure in
2003 (USGS 2004) to estimate the total amount of secondary zinc produced using the electro-thermic process. This
value is then multiplied by the Waelz Kiln process emission factor to obtain total C02 emissions for secondary zinc
produced using the electro-thermic process.
U.S. secondary zinc is also produced by processing recycled EAF dust in a Waelz Kiln furnace. Due to the
complexities of recovering zinc from recycled EAF dust, an emission factor based on the amount of EAF dust
consumed rather than the amount of secondary zinc produced is believed to represent actual C02 emissions from the
process more accurately (Stuart 2005). An emission factor based on the amount of EAF dust consumed was
developed based on the amount of metallurgical coke consumed per ton of EAF dust consumed, 0.4 metric tons
coke/metric ton EAF dust consumed (Viklund-White 2000), and the following equation:
0.4 metric tons coke 0.84 metric tons C 3.67 metric tons C02 1.23 metric tons C02
EF = x x =
EAF Dust metric tons EAF dust metric ton coke metric ton C metric ton EAF Dust
The Horsehead Corporation plant, located in Palmerton, PA, is the only large plant in the United States that
produces secondary zinc by recycling EAF dust (Stuart 2005). In 2003, this plant consumed 408,240 metric tons of
4-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
EAF dust, producing 137,169 metric tons of secondary zinc (Recycling Today 2005). This zinc production
accounted for 36 percent of total secondary zinc produced in 2003. This percentage was applied to the USGS data
for total secondary zinc production for all years within the time series to estimate the total amount of secondary zinc
produced by consuming recycled EAF dust in a Waelz Kiln furnace. This value is multiplied by the Waelz Kiln
process emission factor for EAF dust to obtain total C02 emissions.
The 1990 through 2004 activity data for primary and secondary zinc production (seeTable 4-44) were obtained
through the USGS Mineral Yearbook: Zinc (USGS 1994 through 2005). Activity data for 2005 were obtained from
the USGS Commodity Specialist (Gabby 2006).
Table 4-44: Zinc Production (Metric Tons)
Year Primary Secondary
1990 262,704 341,400
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 191,200 349,000
Uncertainty
The uncertainties contained in these estimates are two-fold, relating to activity data and emission factors used.
First, there are uncertainties associated with the percent of total zinc production, both primary and secondary, that is
attributed to the electro-thermic and Waelz Kiln emissive zinc production processes. For primary zinc production,
the amount of zinc produced annually using the electro-thermic process is estimated from the percent of primary-
zinc production capacity that electro-thermic production capacity constitutes for each year of the time series. This
assumes that each zinc plant is operating at the same percentage of total production capacity, which may not be the
case and this calculation could either overestimate or underestimate the percentage of the total primary zinc
production that is produced using the electro-thermic process. The amount of secondary zinc produced using the
electro-thermic process is estimated from the percent of total secondary zinc production that this process accounted
for during a single year, 2003. The amount of secondary zinc produced using the Waelz Kiln process is estimated
from the percent of total secondary zinc production this process accounted for during a single year, 1997. This
calculation could either overestimate or underestimate the percentage of the total secondary zinc production that is
produced using the electro-thermic or Waelz Kiln processes. Therefore, there is uncertainty associated with the fact
that percents of total production data estimated from production capacity, rather than actual production data, are
used for emission estimates.
Second, there are uncertainties associated with the emission factors used to estimate C02 emissions from the
primary and secondary production processes. Because the only published emission factors are based on the
Imperial Smelting Furnace, which is not used in the United States, country-specific emission factors were developed
for the Waelz Kiln zinc production process. Data limitations prevented the development of emission factors for the
electro-thermic process. Therefore, emission factors for the Waelz Kiln process were applied to both electro-
thermic and Waelz Kiln production processes. Furthermore, the Waelz Kiln emission factors are based on materials
balances for metallurgical coke and EAF dust consumed during zinc production provided by Viklund-White (2000).
Therefore, the accuracy of these emission factors depend upon the accuracy of these materials balances.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-45. Zinc production C02
emissions were estimated to be between 0.4 and 0.6 Tg C02 Eq. at the 95 percent confidence level. This indicates a
range of approximately 22 percent below and 25 percent above the emission estimate of 0.5 Tg C02 Eq.
Industrial Processes 4-35
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
Table 4-45: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Zinc Production (Tg C02 Eq. and
Percent)
Source
Gas
2005 Emission
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Zinc Production
C02
0.5
©
-1"
©
-22% +25%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
The historical activity data used to calculate the emissions from zinc production were updated for the year 2004.
The change resulted in a decrease of 0.03 Tg C02 Eq. (6 percent) in C02 emissions from zinc production for that
year.
4.12. Lead Production (IPCC Source Category 2C5)
Lead production in the United States consists of both primary and secondary processes. In the United States,
primary lead production, in the form of direct smelting, mostly occurs at a plants located in Alaska and Missouri,
while secondary production largely involves the recycling of lead acid batteries at 14 separate smelters located in 11
states throughout the United States (USGS 2005). Secondary lead production has increased in the United States
over the past decade while primary lead production has decreased. In 2005, secondary lead production accounted
for approximately 89 percent of total lead production (Gabby 2006, USGS 1995). Both the primary lead and
secondary lead production processes used in the United States emit C02 (Sjardin 2003).
Primary production of lead through the direct smelting of lead concentrate produces C02 emissions as the lead
concentrates are reduced in a furnace using metallurgical coke (Sjardin 2003). U.S. primary lead production
decreased by 3 percent from 2004 to 2005 and has decreased by 63 percent since 1990 (Gabby 2006, USGS 1995)
In the United States, approximately 82 percent of secondary lead is produced by recycling lead acid batteries in
either blast furnaces or reverberatory furnaces. The remaining 18 percent of secondary lead is produced from lead
scrap. Similar to primary lead production, C02 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
3 percent from 2004 to 2005, and has increased by 24 percent since 1990.
The United States is the third largest mine producer of lead in the world, behind China and Australia, accounting for
14 percent of world production in 2005 (USGS 2005). In 2005, U.S. primary and secondary lead production totaled
1,288,000 metric tons (Gabby 2006). The resulting emissions of C02 from 2005 production were estimated to be
0.3 Tg C02 Eq. (265 Gg) (see Table 4-46). The majority of 2005 lead production is from secondary processes,
which account for 86 percent of total 2005 C02 emissions.
Table 4-46: C02 Emissions from Lead Production (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
1990 0.3 285
iws o; :«w
2000 0.3 311
2001 0.3 293
4-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Public Review Draft
2002 0.3 290
2003 0.3 289
2004 0.3 259
200 5 03 265
After a gradual increase in total emissions from 1990 to 2000, total emissions have decreased by seven percent since
1990, largely due a decrease in primary production and a transition within the United States from primary lead
production to secondary lead production, which is less emissive than primary production (USGS 2005).
Methodology
Non-energy C02 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) provides an emission factor of 0.25 metric tons C02/ton lead. For secondary lead production,
Sjardin (2003) provides an emission factor of 0.2 metric tons C02/ton lead produced. Both factors are multiplied by
total U.S. primary and secondary lead production, respectively, to estimate C02 emissions.
The 1990 through 2004 activity data for primary and secondary lead production (see Table 4-47) were obtained
through the USGS Mineral Yearbook: Lead (USGS 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003,
2004, 2005). Primary and secondary lead production data for 2005 were obtained from the USGS Lead Minerals
Commodity Specialist (Gabby 2006).
Table 4-47: Lead Production (Metric Tons)
Year Primary Secondary
1990 404,000 922,000
2000 341,000 1,130,000
2001 290,000 1,100,000
2002 262,000 1,120,000
2003 245,000 1,140,000
2004 148,000 1,110,000
2005 143,000 1,145,000
Uncertainty
Uncertainty associated with lead production relates to the emission factors and activity data used. The direct
smelting emission factor used in primary production is taken from Sjardin (2003) who averages the values provided
by three other studies (Dutrizac et al. 2000, Morris et al. 1983, Ullman 1997). For secondary production, Sjardin
(2003) reduces this factor by 50 percent and adds a C02 emissions factor associated with battery treatment. The
applicability of these emission factors to plants in the United States is uncertain. There is also a smaller level of
uncertainty associated with the accuracy of primary and secondary production data provided by the USGS.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-48. Lead production C02
emissions were estimated to be between 0.2 and 0.3 Tg C02 Eq. at the 95 percent confidence level. This indicates a
range of approximately 16 percent below and 17 percent above the emission estimate of 0.3 Tg C02 Eq.
Table 4-48: Tier 2 Quantitative Uncertainty Estimates for C02 Emissions from Lead Production (Tg C02 Eq. and
Percent)
2005 Emission TT . . . „ n ^ ^ ± *
„ „ . Uncertainty Range Relative to Emission Estimate
Source Gas Estimate
(Tg CP2 Eq.) (Tg CP2 Eq.) (%)
Lower Upper Lower Upper
Industrial Processes 4-37
-------
Public Review Draft
Bound
Bound
Bound
Bound
Lead Production
C02
0.3
0.2
0.3
-16%
+17%
1 a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
2
3 4.13. Petrochemical Production (IPCC Source Category 2B5)
4 The production of some petrochemicals results in the release of small amounts of CH4 and C02 emissions.
5 Petrochemicals are chemicals isolated or derived from petroleum or natural gas. CH4 emissions are presented here
6 from the production of C black, ethylene, ethylene dichloride, and methanol, while C02 emissions are presented
7 here for only C black production. The C02 emissions from petrochemical processes other than C black are
8 currently included in the Carbon Stored in Products from Non-Energy Uses of Fossil Fuels Section of the Energy
9 chapter. The C02 from C black production is included here to allow for the direct reporting of C02 emissions from
10 the process and direct accounting of the feedstocks used in the process.
11 C black is an intensely black powder generated by the incomplete combustion of an aromatic petroleum or coal-
12 based feedstock. Most C black produced in the United States is added to rubber to impart strength and abrasion
13 resistance, and the tire industry is by far the largest consumer. Ethylene is consumed in the production processes of
14 the plastics industry including polymers such as high, low, and linear low density polyethylene (HDPE, LDPE,
15 LLDPE), polyvinyl chloride (PVC), ethylene dichloride, ethylene oxide, and ethylbenzene. Ethylene dichloride is
16 one of the first manufactured chlorinated hydrocarbons with reported production as early as 1795. In addition to
17 being an important intermediate in the synthesis of chlorinated hydrocarbons, ethylene dichloride is used as an
18 industrial solvent and as a fuel additive. Methanol is an alternative transportation fuel as well as a principle
19 ingredient in windshield wiper fluid, paints, solvents, refrigerants, and disinfectants. In addition, methanol-based
20 acetic acid is used in making PET plastics and polyester fibers.
21 Emissions of C02 and CH4 from petrochemical production in 2005 were 2.9 Tg C02 Eq. (2,895 Gg) and 1.1 Tg C02
22 Eq. (52 Gg), respectively (see Table 4-49 and Table 4-50), totaling 4.0 Tg C02 Eq. Emissions of C02 from C black
23 production in 2005 essentially equaled those from the previous year. There has been an overall increase in C02
24 emissions from C black production of 30 percent since 1990. CH4 emissions from petrochemical production
25 increased by six percent from the previous year and increased 26 percent since 1990.
26 Table 4-49: C02 and CH4 Emissions from Petrochemical Production (Tg C02 Eq.)
Year
1990
1995
2000
2001
2002
2003
2004
2005
C02
2.2
2.:<
3.0
2.8
2.9
2.8
2.9
2.9
ch4
o
I i
1.2
1.1
1.1
1.1
1.2
1.1
Total
3.1
3.8
4.2
3.9
4.0
3.9
4.1
4.0
27
28 Table 4-50: C02 and CI I: Emissions from Petrochemical Production (Gg)
Year 1990 1995 2000 2001 2002 2003 2004 2005
C02 2,221 2,750 3,004 2,787 2,857 2,777 2,895 2,897
CH4 41 58 51 52 51 55 51
29
30 Methodology
31 Emissions of CH4 were calculated by multiplying annual estimates of chemical production by the appropriate
32 emission factor, as follows: 11 kg CH /metric ton C black, 1 kg CH4/metric ton ethylene, 0.4 kg CH4/metric ton
33 ethylene dichloride,10 and 2 kg CH 4/mctric ton methanol. Although the production of other chemicals may also
10 The emission factor obtained from IPCC/UNEP/OECD/IEA (1997), page 2.23 is assumed to have a misprint; the chemical
4-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
result in CH4 emissions, there were not sufficient data available to estimate their emissions.
Emission factors were taken from the Revised 1996IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997). Annual
production data for 1990 (see Table 4-51) were obtained from the Chemical Manufacturer's Association Statistical
Handbook (CMA 1999). Production data for 1991 through 2005 were obtained from the American Chemistry
Council's Guide to the Business of Chemistry (ACC 2002, 2003, 2005, 2006) and the International Carbon Black
Association (Johnson 2003, 2005, 2006).
Table 4-51: Production of Selected Petrochemicals (Thousand Metric Tons)
Chemical
1990
199S
2000
2001
2002
2003
2004
2005
Carbon Black
1,307
1,619
1,769
1,641
1,682
1,635
1,705
1,651
Ethylene
16,542
21,215
24,971
22,521
23,623
22,957
25,660
23,955
Ethylene Dichloride
6,282
7,829
9,866
9,294
9,288
9,952
12,111
11,261
Methanol
3,785
4,992
4,876
3,402
3,289
3,166
2,937
2,336
Almost all C black in the United States is produced from petroleum-based or coal-based feedstocks using the
"furnace black" process (European IPPC Bureau 2004). The furnace black process is a partial combustion process
in which a portion of the C black feedstock is combusted to provide energy to the process. C black is also produced
in the United States by the thermal cracking of acetylene-containing feedstocks ("acetylene black process") and by
the thermal cracking of other hydrocarbons ("thermal black process"). One U.S. C black plant produces C black
using the thermal black process, and one U.S. C black plant produces C black using the acetylene black process
(The Innovation Group 2004).
The furnace black process produces C black from "C black feedstock" (also referred to as "C black oil"), which is a
heavy aromatic oil that may be derived as a byproduct of either the petroleum refining process or the metallurgical
(coal) coke production process. For the production of both petroleum-derived and coal-derived C black, the
"primary feedstock" (i.e., C black feedstock) is injected into a furnace that is heated by a "secondary feedstock"
(generally natural gas). Both the natural gas secondary feedstock and a portion of the C black feedstock are
oxidized to provide heat to the production process and pyrolyze the remaining C black feedstock to C black. The
"tail gas" from the furnace black process contains C02, carbon monoxide, sulfur compounds, CH4, and non-CH4
volatile organic compounds. A portion of the tail gas is generally burned for energy recovery to heat the
downstream 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 C02 released
during the process. The C content of national C black production is subtracted from the total amount of C contained
in primary and secondary C black feedstock to find the amount of C lost during the production process. It is
assumed that the C lost in this process is emitted to the atmosphere as either CH4 or C02. The C content of the CH4
emissions, estimated as described above, is subtracted from the total C lost in the process to calculate the amount of
C emitted as C02. The total amount of primary and secondary C black feedstock consumed in the process (see
Table 4-52) is estimated using a primary feedstock consumption factor and a secondary feedstock consumption
factor estimated from U.S. Census Bureau (1999 and 2004) data. The average C black feedstock consumption
factor for U.S. C black production is 1.43 metric tons of C black feedstock consumed per metric ton of C black
produced. The average natural gas consumption factor for U.S. C black production is 341 normal cubic meters of
natural gas consumed per metric ton of C black produced. The amount of C contained in the primary and secondary
feedstocks is calculated by applying the respective C contents of the feedstocks to the respective levels of feedstock
consumption (EIA 2003, 2004).
Table 4-52: Carbon Black Feedstock (Primary Feedstock) and Natural Gas Feedstock (Secondary Feedstock)
Consumption (Thousand Metric Tons)
identified should be ethylene dichloride (C2H4C12) rather than dichloroethylene (C2H2CI2).
Industrial Processes 4-39
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
Activity
1990
1995
2000
2001
2002
2003
2004
2005
Primary Feedstock
1,864
2,308
2,521
2,339
2,398
2,331
2,430
2,430
Secondary Feedstock
302
374
408
379
388
377
393
393
For the purposes of emissions estimation, 100 percent of the primary C black feedstock is assumed to be derived
from petroleum refining byproducts. C black feedstock derived from metallurgical (coal) coke production (e.g.,
creosote oil) is also used for C black production; however, no data are available concerning the annual consumption
of coal-derived C black feedstock. C black feedstock derived from petroleum refining byproducts is assumed to be
89 percent elemental C (Srivastava et al. 1999). It is assumed that 100 percent of the tail gas produced from the C
black production process is combusted and that none of the tail gas is vented to the atmosphere uncontrolled. The
furnace black process is assumed to be the only process used for the production of C black because of the lack of
data concerning the relatively small amount of C black produced using the acetylene black and thermal black
processes. The C black produced from the furnace black process is assumed to be 97 percent elemental C (Othmer
et al. 1992).
Uncertainty
The CH4 emission factors used for petrochemical production are based on a limited number of studies. Using plant-
specific factors instead of average factors could increase the accuracy of the emission estimates; however, such data
were not available. There may also be other significant sources of CH4 arising from petrochemical production
activities that have not been included in these estimates.
The results of the quantitative uncertainty analysis for the C02 emissions from 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 C02 emissions from the utilization of coal-based feedstock are not included in the
emission estimate. In addition, other data sources indicate that the amount of petroleum-based feedstock used in 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 4-53. Petrochemical production
CH4 emissions were estimated to be between 1.0 and 1.2 Tg C02 Eq. at the 95 percent confidence level. This
indicates a range of approximately 8 percent below to 9 percent above the emission estimate of 1.1 Tg C02 Eq.
Petrochemical production C02 emissions were estimated to be between 1.9 and 4.1 Tg C02 Eq. at the 95 percent
confidence level. This indicates a range of approximately 34 percent below to 41 percent above the emission
estimate of 2.9 Tg C02 Eq.
Table 4-53: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Petrochemical Production and C02
Emissions from Carbon Black Production (Tg C02 Eq. and Percent)
2005 Emission
Source
Gas
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Upper
Lower
Upper
Bound
Bound
Bound
Bound
Petrochemical Production
C02
2.9
1.9
4.1
-34%
+41%
Petrochemical Production
ch4
1.1
1.0
1.2
-8%
+9%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Estimates of CH4 emissions from petrochemical production have been revised for the entire time series to include
the removal of styrene, which has been removed due to inconsistent information regarding its emissive use in the
4-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
United States. On average, the removal of styrene resulted in a decrease of 0.4 Tg C02 Eq. (27 percent) from the
previous estimate.
Planned Improvements
Future improvements to the petrochemicals source category include research into the use of acrylonitrile in the
United States, revisions to the C black CH4 and C02 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.
4.14. Silicon Carbide Production (iPCC Source Category 2B4) and Consumption
C02 and CH4 are emitted from the production of silicon carbide (SiC), a material used as an industrial abrasive. To
make SiC, quartz (Si02) 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 C02, CH4, or CO.
C02 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).
C02 from SiC production and consumption in 2005 were 219 Gg (0.2 Tg C02 Eq.). Approximately 42 percent of
these emissions resulted from SiC production while the remainder result from SiC consumption. CH4 emissions
from SiC production in 2005 were 0.4 Gg CH4 (0.01 Tg C02 Eq.) (see Table 4-54 and Table 4-55).
Table 4-54: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Tg C02 Eq.)
Year
1990
1 1995
2000
2001
2002
2003
2004
2005
C02
0.4
1 0.3
0.2
0.2
0.2
0.2
0.2
0.2
ch4
+
1 + :,"i
+
+
+
+
+
+
Total
0.4
i 0.3
0.3
0.2
0.2
0.2
0.2
0.2
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 4-55: C02 and CH4 Emissions from Silicon Carbide Production and Consumption (Gg)
Year
1990 1995 2000 2001 2002 2003
2004
2005
C02
375 329 248 199 183 202
224
219
ch4
+
+
+
+
+
+ Does not exceed 0.5 Gg.
Methodology
Emissions of C02 and CH4 from the production of SiC were calculated by multiplying annual SiC production by the
emission factors (2.62 metric tons C02/metric ton SiC for C02 and 11.6 kg CH4/metric ton SiC for CH4) provided
by the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC 2006).
Emissions of C02 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, 1992a, 1993a, 1994a, 1995a, 1996a, 1997a, 1998a, 1999a, 2000a, 2001a, 2002a, 2003a, 2004a,
2005a, 2006). Silicon carbide consumption by major end use was obtained from the Minerals Yearbook: Silicon
(USGS 1991b,1992b,1993b,1994b,1995b,1996b,1997b,1998b,1999b,2000b,2001b,2002b,2003b,2004b,
Industrial Processes 4-41
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Public Review Draft
2005b) (see Table 4-56) for years 1990 through 2004 and from the USGS Minerals Commodity Specialist for 2005
(Corathers 2006). Net imports were obtained from the U.S. Census Bureau (2005, 2006).
Table 4-56: Production and Consumption of Silicon Carbide (Metric Tons)
Year Production Consumption
1990 105,000 172,464
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
Uncertainty
There is uncertainty associated with the emission factors used because they are based on stoichiometry as opposed
to monitoring of actual SiC production plants. An alternative would be to calculate emissions based on the quantity
of petroleum coke used during the production process rather than on the amount of silicon carbide produced.
However, these data were not available. For CH4, there is also uncertainty associated with the hydrogen-containing
volatile compounds in the petroleum coke (IPCC 2006). There is also some uncertainty associated with production,
net imports, and consumption data as well as the percent of total consumption that is attributed to metallurgical and
other non-abrasive uses.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-57. Silicon carbide production
CH4 emissions were estimated to be between 9 percent below and 9 percent above the emission estimate of 0.01 Tg
C02 Eq. at the 95 percent confidence level. Silicon carbide production and consumption C02 emissions were
estimated to be between 10 percent below and 10 percent above the emission estimate of 0.2 Tg C02 Eq. at the 95
percent confidence level.
Table 4-57: Tier 2 Quantitative Uncertainty Estimates for CH4 and C02 Emissions from Silicon Carbide Production
and Consumption (Tg C02 Eq. and Percent)
2005 Emission
Source
Gas
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Silicon Carbide Production
and Consumption
C02
0.2
0.2
0.2
-10%
+10%
Silicon Carbide Production
and Consumption
ch4
+
+
+
-9%
+9%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
+ Does not exceed 0.05 Tg C02 Eq. or 0.5 Gg.
Recalculations Discussion
Emissions of C02 from SiC production were included for the first time during this inventory year. Overall
emissions from C02 production and consumption increased throughout the time series by an average of 56 percent
as a result of this change.
4-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
Planned Improvements
Future improvements to the carbide production source category include performing 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.
4.15. Nitric Acid Production (IPCC Source Category 2B2)
Nitric acid (HN03) is an inorganic compound used primarily to make synthetic commercial fertilizers. It is also a
major component in the production of adipic acid—a feedstock for nylon—and explosives. Virtually all of the
nitric acid produced in the United States is manufactured by the catalytic oxidation of ammonia (EPA 1997).
During this reaction, N20 is formed as a by-product and is released from reactor vents into the atmosphere.
Currently, the nitric acid industry controls for emissions of NO and N02 (i.e., NOx). As such, the industry uses a
combination of non-selective catalytic reduction (NSCR) and selective catalytic reduction (SCR) technologies. In
the process of destroying NOx, NSCR systems are also very effective at destroying N20. However, NSCR units are
generally not preferred in modern plants because of high energy costs and associated high gas temperatures.
NSCRs were widely installed in nitric plants built between 1971 and 1977. Approximately 20 percent of nitric acid
plants use NSCR (Choe et al. 1993). The remaining 80 percent use SCR or extended absorption, neither of which is
known to reduce N20 emissions.
N20 emissions from this source were estimated to be 15.7 Tg C02 Eq. (51 Gg) in 2005 (see Table 4-58). Emissions
from nitric acid production have decreased by 12.1 percent since 1990, with the trend in the time series closely
tracking the changes in production.
Table 4-58: N20 Emissions from Nitric Acid Production (Tg C02 Eq. and Gg),
Year Tg CP2 Eq. Gg
1990
17.8
58
1995
19.9
2000
2001
2002
2003
2004
2005
19.6
15.9
17.2
16.7
16.0
15.7
63
51
56
54
52
51
Methodology
N20 emissions were calculated by multiplying nitric acid production by the amount of N20 emitted per unit of nitric
acid produced. The emission factor was determined as a weighted average of 2 kg N20 / metric ton HN03 for plants
using non-selective catalytic reduction (NSCR) systems and 9.5 kg N20/metric ton HN03for plants not equipped
with NSCR (Choe et al. 1993). In the process of destroying NOx, NSCR systems destroy 80 to 90 percent of the
N20, which is accounted for in the emission factor of 2 kg N20/metric ton HN03. An estimated 20 percent of
HN03 plants in the United States are equipped with NSCR (Choe et al. 1993). Hence, the emission factor is equal
to (9.5 x 0.80) + (2 x 0.20) = 8 kg N20 per metric ton HN03.
Nitric acid production data for 1990 (see Table 4-59) was obtained from Chemical and Engineering News, "Facts
and Figures" (C&EN 2001). Nitric acid production data for 1991 through 1992 (see Table 4-59) were obtained
from Chemical and Engineering News, "Facts and Figures" (C&EN 2002). Nitric acid production data for 1993
was obtained from Chemical and Engineering News, "Facts and Figures" (C&EN 2004). Nitric acid production
data for 1994 was obtained from Chemical and Engineering News, "Facts and Figures" (C&EN 2005). Nitric acid
production data for 1995 through 2005 were obtained from Chemical and Engineering News, "Facts and Figures"
Industrial Processes 4-43
-------
Public Review Draft
9
10
11
12
13
14
15
16
17
18
19
20
21
(C&EN 2006). The emission factor range was taken from Choe et al. (1993).
Table 4-59: Nitric Acid Production (Gg)
Year Gg
1990
1995
2000
2001
2002
2003
2004
2005
7,196
8,018
Uncertainty
The overall uncertainty associated with the 2005 N20 emissions estimate from nitric acid production was calculated
using the IPCC Good Practice Guidance Tier 2 methodology. Uncertainty associated with the parameters used to
estimate N20 emissions included that of production data, the share of U.S. nitric acid production attributable to each
emission abatement technology, and the emission factors applied to each abatement technology type.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-60. N20 emissions from nitric
acid production were estimated to be between 13.2 and 18.5 Tg C02 Eq. at the 95 percent confidence level. This
indicates a range of approximately 16 percent below to 18 percent above the 2005 emissions estimate of 15.7 Tg
C02 Eq.
Table 4-60: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From Nitric Acid Production (Tg C02
2005 Emission
Uncertainty Range Relative to Emission
Source
Gas
Estimate
Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Nitric Acid Production
N20
15.7
13.2 18.5
-16% +18%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
The nitric acid production values for 1998, 2002, and 2004 have been updated relative to the previous Inventory
based on revised production data presented in C&EN (2006). The updated production data for 1998 and 2002
resulted in an increases of less than O.OlTg C02 Eq. (0.01 percent), respectively, in N20 emissions from nitric acid
production for these years relative to the previous Inventory. The updated production data for 2004 resulted in a
decrease of 0.6 Tg C02 Eq. (3.5 percent) in N20 emissions relative to the previous Inventory.
22 Planned Improvements
23 Planned improvements are focused on assessing the plant-by-plant implementation of NOx abatement technologies
24 to more accurately match plant production capacities to appropriate emission factors, instead of using a national
25 profiling of abatement implementation.
26 4.16. Adipic Acid Production (IPCC Source Category 2B3)
27 Adipic acid production is an anthropogenic source of N20 emissions. Worldwide, few adipic acid plants exist. The
4-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
Public Review Draft
United States is the major producer, with three companies in four locations accounting for approximately one-third
of world production (CW 2005). Adipic acid is a white crystalline solid used in the manufacture of synthetic fibers,
coatings, plastics, urethane foams, elastomers, and synthetic lubricants. Commercially, it is the most important of
the aliphatic dicarboxylic acids, which are used to manufacture polyesters. Approximately 90 percent of all adipic
acid produced in the United States is used in the production of nylon 6,6 (CMR 2001). Food grade adipic acid is
also used to provide some foods with a "tangy" flavor (Thiemens and Trogler 1991).
Adipic acid is produced through a two-stage process during which N20 is generated in the second stage. The first
stage of manufacturing usually involves the oxidation of cyclohexane to form a cyclohexanone/cyclohexanol
mixture. The second stage involves oxidizing this mixture with nitric acid to produce adipic acid. N20 is generated
as a by-product of the nitric acid oxidation stage and is emitted in the waste gas stream (Thiemens and Trogler
1991). Process emissions from the production of adipic acid vary with the types of technologies and level of
emission controls employed by a facility. In 1990, two of the three major adipic acid-producing plants had N20
abatement technologies in place and, as of 1998, the three major adipic acid production facilities had control
systems in place.11 Only one small plant, representing approximately two percent of production, does not control
for N20 (Reimer 1999).
N20 emissions from adipic acid production were estimated to be 6.0 Tg C02 Eq. (19 Gg) in 2005 (see Table 4-61).
National adipic acid production has increased by approximately 42 percent over the period of 1990 through 2005, 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.
Table 4-61: N2Q Emissions from Adipic Acid Production (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
2000
2001
2002
2003
2004
2005
6.0
4.9
5.9
6.2
5.7
6.0
19
16
19
20
19
19
Methodology
For two production plants, 1990 to 2002 emission estimates were obtained directly from the plant engineer and
account for reductions due to control systems in place at these plants during the time series (Childs 2002, 2003).
These estimates were based on continuous emissions monitoring equipment installed at the two facilities. Reported
estimates for 2003, 2004, and 2005 were unavailable and, thus, were calculated by applying a 4.4, 4.2 and 4.2
percent production growth rates, respectively. The production for 2003 was obtained through linear interpolation
between 2002 and 2004 reported national production data. Subsequently, the growth rate for 2004 and 2005 was
based on the change between the estimated 2003 production data and the reported 2004 production data (see
discussion below on sources of production data). For the other two plants, N20 emissions were calculated by
multiplying adipic acid production by an emission factor (i.e., N20 emitted per unit of adipic acid produced) and
adjusting for the percentage of N20 released as a result of plant-specific emission controls. On the basis of
experiments, the overall reaction stoichiometry for N20 production in the preparation of adipic acid was estimated
at approximately 0.3 metric tons of N20 per metric ton of product (Thiemens and Trogler 1991). Emissions are
1 during 1997, the N20 emission controls installed by the third plant operated for approximately a quarter of the year.
Industrial Processes 4-45
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
estimated using the following equation:
N20 emissions = (production of adipic acid [metric tons {MT} of adipic acid]) x (0.3 MT N20 / MT adipic acid) x
(1 - [N20 destruction factor x abatement system utility factor])
The "N20 destruction factor" represents the percentage of N20 emissions that are destroyed by the installed
abatement technology. The "abatement system utility factor" represents the percentage of time that the abatement
equipment operates during the annual production period. Overall, in the United States, two of the plants employ
catalytic destruction, one plant employs thermal destruction, and the smallest plant uses no N20 abatement
equipment. The N20 abatement system destruction factor is assumed to be 95 percent for catalytic abatement and
98 percent for thermal abatement (Reimer et al. 1999, Reimer 1999). For the one plant that uses thermal
destruction and for which no reported plant-specific emissions are available, the abatement system utility factor is
assumed to be 98 percent.
For 1990 to 2003 and 2005, 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, actual plant production data were obtained for these two plants and used for emission
calculations.
National adipic acid production data (see Table 4-62) 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 was obtained from Chemical Week, Product Focus: Adipic Acid (CW
2005). Production for 2005 was calculated by applying a 4.2 percent production growth rate to reported 2004
production. This growth rate was based on the change between the estimated 2003 production and the reported
2004 production. The 4.2 percent production growth rate applied in this case is in line with the expected growth in
global adipic acid demand of 3.2 percent per year from 2005 to 2010 (CW 2005). Plant capacities for 1990 through
1994 were obtained from Chemical and Engineering News, "Facts and Figures" and "Production of Top 50
Chemicals" (C&EN 1992, 1993, 1994, 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.
Table 4-62: Adipic Acid Production (Gg)
Year Gg
1990 735
2000 925
2001 835
2002 921
2003 961
2004 1,002
200 5 1,044
Uncertainty
The overall uncertainty associated with the 2005 N20 emission estimate from adipic acid production was calculated using the
IPCC Good Practice Guidance Tier 2 methodology. Uncertainty associated with the parameters used to estimate N20 emissions
included that of company specific production data, industry wide estimated production growth rates, emission factors for abated
4-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Public Review Draft
and unabated emissions, and company specific historical emissions estimates.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-63. N20 emissions from
adipic acid production were estimated to be between 3.2 and 8.8 Tg C02 Eq. at the 95 percent confidence level.
This indicates a range of approximately 46 percent below to 47 percent above the 2005 emission estimate of 6.0 Tg
C02 Eq.
Table 4-63: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions from Adipic Acid Production (Tg C02
Eq. and Percent)
2005 Emission
Source
Gas
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Adipic Acid Production
N20
6.0
3.2 8.8 -46% +47%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
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.
4.17. 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 1990.12 Ozone depleting substances—chlorofluorocarbons (CFCs), halons, carbon
tetrachloride, methyl chloroform, and hydrochlorofluorocarbons (HCFCs)—arc 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 4-64 and Table 4-65.
Table 4-64: Emissions of HFCs and PFCs from OPS Substitutes (Tg C02 Eq.)
Gas
Total
1990
HFC-23
+
HFC-32
+1
HFC-125
+|
HFC-134a
+1
HFC-143a
+1
HFC-236fa
+1
cf4
+1
Others*
0.3
2000
2001
2002
2003
2004
2005
+
+
+
+
+
+
0.3
0.3
0.4
0.4
0.5
0.6
11.2
12.4
13.7
15.4
17.3
19.8
56.3
60.7
64.7
68.3
71.8
74.0
8.3
10.3
12.7
15.4
18.4
22.1
0.7
0.8
0.8
0.9
1.0
1.0
+
+
+
+
+
+
4.2
4.0
4.5
5.1
5.4
5.7
80.9
88.6
96.9
105.5
114.5
123.3
+ Does not exceed 0.05 Tg C02 Eq.
* Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee, and PFC/PFPEs, the latter being a proxy for a diverse
12 [42 U.S.C § 7671, CAA § 601]
Industrial Processes 4-47
-------
Public Review Draft
1 collection of PFCs and perfluoropolyethers (PFPEs) employed for solvent applications. For estimating purposes, the GWP value
2 used for PFC/PFPEs was based upon C6Fi 4.
3 Note: Totals may not sum due to independent rounding.
4
5 Table 4-65: Emissions of HFCs and PFCs from OPS Substitution (Mg)
Gas
1990
1995
2000
2001
2002
2003
2004
2005
HFC-23
+
+
1
2
2
2
3
3
HFC-32
+111111
+
465
498
558
645
762
963
HFC-125
+1111
1,267
3,983
4,423
4,901
5,484
6,177
7,065
HFC-134a
+11111
19,999
43,274
46,677
49,774
52,521
55,265
56,943
HFC-143a
+1111111
228
2,193
2,723
3,338
4,045
4,847
5,822
HFC-236fa
+1IIIIB
36
110
123
135
145
155
163
cf4
+11111
+
1
1
1
1
1
2
Others*
M
M
M
M
M
M
M
M
6 M (Mixture of Gases)
7 + Does not exceed 0.5 Mg
8 * Others include HFC-152a, HFC-227ea, HFC-245fa, HFC-4310mee, C4F10, and PFC/PFPEs, the latter being a proxy for a
9 diverse collection of PFCs and perfluoropolyethers (PFPEs) employed for solvent applications.
10
11 In 1990 and 1991, the only significant emissions of HFCs and PFCs as substitutes to ODSs were relatively small
12 amounts of HFC-152a—a component of the refrigerant blend R-500 used in chillers—and HFC-134a in
13 refrigeration end-uses. Beginning in 1992, HFC-134a was used in growing amounts as a refrigerant in motor
14 vehicle air-conditioners and in refrigerant blends such as R-404A.13 In 1993, the use of HFCs in foam production
15 and as an aerosol propellant began, and in 1994 these compounds also found applications as solvents and sterilants.
16 In 1995, ODS substitutes for halons entered widespread use in the United States as halon production was phased-
17 out.
18 The use and subsequent emissions of HFCs and PFCs as ODS substitutes has been increasing from small amounts in
19 1990 to 123.3 Tg C02 Eq. in 2005. This increase was in large part the result of efforts to phase out CFCs and other
20 ODSs in the United States. In the short term, this trend is expected to continue, and will likely accelerate over the
21 next decade as HCFCs, which are interim substitutes in many applications, are themselves phased-out under the
22 provisions of the Copenhagen Amendments to the Montreal Protocol. Improvements in the technologies associated
23 with the use of these gases and the introduction of alternative gases and technologies, however, may help to offset
24 this anticipated increase in emissions.
25 The end-use sectors that contribute the most toward emissions of HFCs and PFCs as ODS substitutes include
26 refrigeration and air-conditioning (107.8 Tg C02Eq., or approximately 87 percent), aerosols (11.3 Tg C02Eq., or
27 approximately 9 percent), and solvents (1.6 Tg C02Eq., or approximately 1 percent). Within the refrigeration and
28 air-conditioning end-use sector, motor vehicle air-conditioning was the highest emitting end-use (53.1 Tg C02 Eq.),
29 followed by retail food and refrigerated transport. In the aerosols end-use sector, non-metered-dose inhaler (MDI)
30 emissions make up a majority of the end-use sector emissions.
31 Methodology
32 A detailed Vintaging Model of ODS-containing equipment and products was used to estimate the actual—versus
33 potential—emissions of various ODS substitutes, including HFCs and PFCs. The name of the model refers to the
34 fact that the model tracks the use and emissions of various compounds for the annual "vintages" of new equipment
35 that enter service in each end-use. This Vintaging Model predicts ODS and ODS substitute use in the United States
36 based on modeled estimates of the quantity of equipment or products sold each year containing these chemicals and
37 the amount of the chemical required to manufacture and/or maintain equipment and products over time. Emissions
13 R-404A contains HFC-125, HFC-143a, and HFC-134a.
4-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
for each end-use were estimated by applying annual leak rates and release profiles, which account for the lag in
emissions from equipment as they leak over time. By aggregating the data for more than 50 different end-uses, the
model produces estimates of annual use and emissions of each compound. Further information on the Vintaging
Model is contained in Annex 3.8.
Uncertainty
Given that emissions of ODS substitutes occur from thousands of different kinds of equipment and from millions of
point and mobile sources throughout the United States, emission estimates must be made using analytical tools such
as the Vintaging Model or the methods outlined in IPCC/UNEP/OECD/IEA (1997). Though the model is more
comprehensive than the IPCC default methodology, significant uncertainties still exist with regard to the levels of
equipment sales, equipment characteristics, and end-use emissions profiles that were used to estimate annual
emissions for the various compounds.
The Vintaging Model estimates emissions from over 50 end-uses. The uncertainty analysis, however, quantifies the
level of uncertainty associated with the aggregate emissions resulting from the top 16 end-uses and 5 others. In an
effort to improve the uncertainty analysis, additional end-uses are added annually, with the intention that over time
uncertainty for all emissions from the Vintaging Model will be fully characterized. This year, one new end-use was
included in the uncertainty estimate- fire extinguishing streaming agents. Any end-uses included in previous years'
uncertainty analysis were included in the current uncertainty analysis, whether or not those end-uses were included
in the top 95 percent of emissions from ODS Substitutes.
In order to calculate uncertainty, functional forms were developed to simplify some of the complex "vintaging"
aspects of some end-use sectors, especially with respect to refrigeration and air-conditioning, and to a lesser degree,
fire extinguishing. These sectors calculate emissions based on the entire lifetime of equipment, not just equipment
put into commission in the current year, thereby necessitating simplifying equations. The functional forms used
variables that included growth rates, emission factors, transition from ODSs, change in charge size as a result of the
transition, disposal quantities, disposal emission rates, and either stock for the current year or original ODS
consumption. Uncertainty was estimated around each variable within the functional forms based on expert
judgment, and a Monte Carlo analysis was performed. The most significant sources of uncertainty for this source
category include the emission factors for mobile air-conditioning and retail food refrigeration, as well as the stock
(MT) of retail food refrigerant.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-66. Substitution of ozone
depleting substances HFC and PFC emissions were estimated to be between 95.0 and 158.9 Tg C02 Eq. at the 95
percent confidence level (or in 19 out of 20 Monte Carlo Stochastic Simulations). This indicates a range of
approximately 9 percent below to 13 percent above the emission estimate of 123.3 Tg C02 Eq.
Table 4-66: Tier 2 Quantitative Uncertainty Estimates for HFC and PFC Emissions from ODS Substitutes (Tg C02
Eq. and Percent)
2005 Emission
Source
Gases
Estimate
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower
Bound
Upper
Bound
Substitution of Ozone
HFCs and
Depleting Substances
PFCs
123.3
112.7 148.6
-9%
+20%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
An extensive review of the chemical substitution trends, market sizes, growth rates, and charge sizes, together with
input from industry representatives, resulted in updated assumptions for the Vintaging Model. These changes
resulted in an average annual net increase of 7.6 Tg C02 Eq. (21 percent) in HFC and PFC emissions from the
substitution of ozone depleting substances for the period 1990 through 2004.
Industrial Processes 4-49
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
4.18. HCFC-22 Production (IPCC Source Category 2E1)
Trifluoromethane (HFC-23 or CHF3) is generated as a by-product during the manufacture of chlorodifluoromethane
(HCFC-22), which is primarily employed in refrigeration and air conditioning systems and as a chemical feedstock
for manufacturing synthetic polymers. Between 1990 and 2000, U.S. production of HCFC-22 increased
significantly as HCFC-22 replaced chlorofluorocarbons (CFCs) in many applications. Since 2000, U.S. production
has fluctuated. 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.14 Feedstock production, however, is permitted to continue
indefinitely.
HCFC-22 is produced by the reaction of chloroform (CHC13) and hydrogen fluoride (HF) in the presence of a
catalyst, SbCl5. The reaction of the catalyst and HF produces SbClxFy, (where x + y = 5), which reacts with
chlorinated hydrocarbons to replace chlorine atoms with fluorine. The HF and chloroform are introduced by
submerged piping into a continuous-flow reactor that contains the catalyst in a hydrocarbon mixture of chloroform
and partially fluorinated intermediates. The vapors leaving the reactor contain HCFC-21 (CHC12F), HCFC-22
(CHC1F2), HFC-23 (CHF3), HC1, chloroform, and HF. The under-fluorinated intermediates (HCFC-21) and
chloroform are then condensed and returned to the reactor, along with residual catalyst, to undergo further
fluorination. The final vapors leaving the condenser are primarily HCFC-22, HFC-23, HC1 and residual HF. The
HC1 is recovered as a useful byproduct, and the HF is removed. Once separated from HCFC-22, the HFC-23 is
generally vented to the atmosphere as an unwanted by-product, but it is sometimes captured for use in a limited
number of applications.
Emissions of HFC-23 in 2005 were estimated to be 16.5 Tg C02 Eq. (1.3 Gg) (Table 4-67). This quantity
represents a 6 percent increase from 2004 emissions and a 53 percent decline from 1990 emissions. The increase in
2005 emissions is due primarily to a slight increases in the HFC-23 emission rate (i.e., the amount of HFC-23
emitted per kilogram of HCFC-22 manufactured), while the decline from 1990 emissions is primarily due to the
large decline in the HFC-23 emission rate between 1990 and 2005. Three HCFC-22 production plants operated in
the United States in 2005, two of which used thermal oxidation to significantly lower their HFC-23 emissions.
Year
Tg C02 Eq.
Gg
1990
35.0
3
—
¦—
199^
27U
2
——
2000
29.8
3
2001
19.8
2
2002
19.8
2
2003
12.3
1
2004
15.6
1
2005
16.5
1
Methodology
The methodology employed for estimating emissions is based upon measurements at individual HCFC-22
production plants. Plants using thermal oxidation to abate their HFC-23 emissions monitor the performance of their
oxidizers to verily that the HFC-23 is almost completely destroyed. The other plants periodically measure HFC-23
concentrations in the output stream using gas chromatography. This information is combined with information on
14 As construed, interpreted, and applied in the terms and conditions of Hie Montreal Protocol on Substances that Deplete the
Ozone Layer. [42 U.S.C. §7671m(b), CAA §614]
4-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Public Review Draft
quantities of critical feed components (e.g., HF) and/or products (HCFC-22) to estimate HFC-23 emissions using a
material balance approach. HFC-23 concentrations are determined at the point the gas leaves the chemical reactor;
therefore, estimates also include fugitive emissions.
Production data and emission estimates were prepared in cooperation with the U.S. manufacturers of HCFC-22
(ARAP 1997, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006; RTI 1997). Annual estimates of U.S. HCFC-22
production are presented in Table 4-68.
Table 4-68: HCFC-22 Production (Gg)
Year Gg
1990 139
2000 187
2001 152
2002 144
2003 138
2004 155
2005 156
Uncertainty
A high level of confidence has been attributed to the HFC-23 concentration data employed because measurements
were conducted frequently and accounted for day-to-day and process variability. The results of the Tier 1
quantitative uncertainly analysis are summarized in Table 4-69. HFC-23 emissions from HCFC-22 production were
estimated to be between 14.9 and 18.2 Tg C02 Eq. at the 95 percent confidence level. This indicates a range of 10
percent above and 10 percent below the 2005 emission estimate of 16.5 Tg C02 Eq.
Table 4-69: Tier 1 Quantitative Uncertainty Estimates for HFC-23 Emissions from HCFC-22 Production (Tg C02
Eq. and Percent)
2005 Emission
Source
Gas
Estimate
(Tg C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
HCFC-22 Production
HFC-23
16.5
14.9 18.2 -10% +10%
a Range of emission reflect a 95 percent confidence interval.
4.19. Electrical Transmission and Distribution (IPCC Source Category 2F7)
The largest use of SF6, both in the United States and internationally, is as an electrical insulator and interrupter in
equipment that transmits and distributes electricity (RAND 2004). The gas has been employed by the electric
power industry in the United States since the 1950s because of its dielectric strength and arc-quenching
characteristics. It is used in gas-insulated substations, circuit breakers, and other switchgear. Sulfur hexafluoride
has replaced flammable insulating oils in many applications and allows for more compact substations in dense urban
areas.
Fugitive emissions of SF6 can escape from gas-insulated substations and switch gear through seals, especially from
older equipment. The gas can also be released during equipment manufacturing, installation, servicing, and
disposal. Emissions of SF6 from equipment manufacturing and from electrical transmission and distribution
systems were estimated to be 13.2 Tg C02 Eq. (0.6 Gg) in 2005. This quantity represents a 51 percent decrease
from the estimate for 1990 (see Table 4-70 and Table 4-71). This decrease is believed to be a response to increases
Industrial Processes 4-51
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Public Review Draft
in the price of SF6 during the 1990s and to growing awareness of the environmental impact of SF6 emissions,
through programs such as the EPA's SF6 Emission Reduction Partnership for Electric Power Systems.
Table 4-70: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufactures (Tg C02 Eq.)
Electric Power Electrical Equipment
Year Systems Manufacturers Total
1990 26.8 0.3 27.1
¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦¦
199^ 21.3 0 * 21.8
2000 14.5 0.7 15.2
2001 14.4 0.7 15.1
2002 13.7 0.7 14.3
2003 13.2 0.7 13.8
2004 12.9 0.7 13.6
2005 12.5 0.7 13.2
Table 4-71: SF6 Emissions from Electric Power Systems and Electrical Equipment Manufactures (Gg)
Year Emissions
1990 1.1
2000 0.6
2001 0.6
2002 0.6
2003 0.6
2004 0.6
2005 0.6
Methodology
The estimates of emissions from electric transmission and distribution are comprised of emissions from electric
power systems and emissions from the manufacture of electrical equipment. The methodologies for estimating both
sets of emissions are described below.
1999 to 2005 Emissions from Electric Power Systems
Emissions from electric power systems from 1999 to 2005 were estimated based on: (1) reporting from utilities
participating in EPA's SF6 Emission Reduction Partnership for Electric Power Systems (partners), which began in
1999; and, (2) utilities' transmission miles as reported in the 2001 and 2004 Utility Data Institute (UDI) Directories
of Electric Power Producers and Distributors (UDI 2001, 2004). (Transmission miles are defined as the miles of
lines carrying voltages above 34.5 kV.) Over the period from 1999 to 2005, participating utilities represented
between 31 percent and 39 percent of total U.S. transmission miles. For each year, the emissions reported by
participating utilities were added to the emissions estimated for utilities that do not participate in the 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. For 2005, if no data was provided,
estimates were calculated based on historical trends or partner-specific emission reduction targets (i.e., emissions
were assumed to decline linearly toward a partners' future stated goal). In 2005, non-reporting partners account for
approximately 2 percent of the total emissions attributable to utilities involved in the SF6 Emission Reduction
Partnership.
4-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Public Review Draft
Emissions from non-partners in every year since 1999 were estimated using the results of a regression analysis that
showed that the emissions of reporting utilities were most strongly correlated with their transmission miles. The
results of this analysis are not surprising given that, in the United States, SF6 is contained primarily in transmission
equipment rated at or above 34.5 kV. The equations were developed based on the 1999 SF6 emissions reported by
49 partner utilities (representing approximately 31 percent of U.S. transmission miles), and 2000 transmission
mileage data obtained from the 2001 UDI Directory of Electric Power Producers and Distributors (UDI 2001). Two
equations were developed, one for small and one for large utilities (i.e., with less or more than 10,000 transmission
miles, respectively). The distinction between utility sizes was made because the regression analysis showed that the
relationship between emissions and transmission miles differed for small and large transmission networks. The
same equations were used to estimate non-partner emissions in 1999 and every year thereafter because non-partners
were assumed not to have implemented any changes that would have resulted in reduced emissions since 1999.
The regression equations are:
Non-partner small utilities (less than 10,000 transmission miles, in kilograms):
Emissions (kg) = 0.874 x Transmission Miles
Non-partner large utilities (more than 10,000 transmission miles, in kilograms):
Emissions (kg) = 0.558 x Transmission Miles
Data on transmission miles for each non-partner utility for the years 2000 and 2003 were obtained from the 2001
and 2004 UDI Directories of Electric Power Producers and Distributors, respectively (UDI 2001, 2004). Given that
the U.S. transmission system grew by over 14,000 miles between 2000 and 2003, and that this increase probably
occurred gradually, transmission mileage was assumed to increase exponentially at an annual rate of 0.7 percent
between 2000 and 2003. This growth rate is assumed to have continued through 2005.
As a final step, total emissions were determined for each year by summing the partner emissions (reported to the
EPA's SF6 Emission Reduction Partnership for Electric Power Systems), and the non-partner emissions (determined
using the 1999 regression equation).
1990 to 1998 Emissions from Electric Power Systems
Because most participating utilities reported emissions only for 1999 through 2005, it was necessary to model SF6
emissions from electric power systems for the years 1990 through 1998. To do so, it was assumed that U.S.
emissions followed the same trajectory as global emissions from this source during the 1990 to 1998 period. To
estimate global emissions, the RAND survey of global SF6 sales were used, together with the following equation,
which is derived from the mass-balance equation for chemical emissions (Volume 3, Equation 7.3) in the IPCC
Guidelines for National Greenhouse Gas Inventories (IPCC 2006). (Although equation 7.3 of the IPCC Guidelines
appears in the discussion of substitutes for ozone-depleting substances, it is applicable to emissions from any long-
lived pressurized equipment that is periodically serviced during its lifetime.)
Emissions (kilograms) = SF6 purchased to refill existing equipment (kilograms) + nameplate capacity of retiring
equipment (kilograms)
Note that the above equation holds whether the gas from retiring equipment is released or recaptured; if the gas is
recaptured, it is used to refill existing equipment, thereby lowering the amount of SF6 purchased by utilities for this
purpose.
Sulfur hexafluoride purchased to refill existing equipment in a given year was assumed to be approximately equal to
the SF6 purchased by utilities in that year. Gas purchases by utilities and equipment manufacturers from 1961
through 2003 are available from the RAND (2004) survey. To estimate the quantity of SF6 released or recovered
from retiring equipment, the nameplate capacity of retiring equipment in a given year was assumed to equal 81.2
percent of the amount of gas purchased by electrical equipment manufacturers 40 years previous (e.g., in 2000, the
Industrial Processes 4-53
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Public Review Draft
nameplate capacity of retiring equipment was assumed to equal 81.2 percent of the gas purchased in 1960). The
remaining 18.8 percent was assumed to have been emitted at the time of manufacture. The 18.8 percent emission
factor is an average of IPCC default SF6 emission rates for Europe and Japan for 1995 (IPCC 2006). The 40-year
lifetime for electrical equipment is also based on IPCC (2006). The results of the two components of the above
equation were then summed to yield estimates of global SF6 emissions from 1990 through 1998.
U.S. emissions between 1990 and 1998 are assumed to follow the same trajectory as global emissions during this
period. To estimate U.S. emissions, global emissions for each year from 1990 through 1998 were divided by the
estimated global emissions from 1999. The result was a time series of factors that express each year's global
emissions as a multiple of 1999 global emissions. Historical U.S. emissions were estimated by multiplying the
factor for each respective year by the estimated U.S. emissions of SF6 from electric power systems in 1999
(estimated to be 15.3 Tg C02 Eq.).
Two factors may affect the relationship between the RAND sales trends and actual global emission trends. One is
utilities' inventories of SF6 in storage containers. When SF6 prices rise, utilities are likely to deplete internal
inventories before purchasing new SF6 at the higher price, in which case SF6 sales will fall more quickly than
emissions. On the other hand, when SF6 prices fall, utilities are likely to purchase more SF6 to rebuild inventories,
in which case sales will rise more quickly than emissions. This effect was accounted for by applying 3-year
smoothing to utility SF6 sales data. The other factor that may affect the relationship between the RAND sales
trends and actual global emissions is the level of imports from and exports to Russia and China. SF6 production in
these countries is not included in the RAND survey, but may have been significant during the 1990 through 1999
period. This factor was not accounted for; however, atmospheric studies confirmed that the downward trend in the
estimated global emissions between 1995 and 1998 was real (see the Uncertainty discussion below).
1990 to 2005 Emissions from Manufacture of Electrical Equipment
The 1990 to 2005 emissions estimates for original equipment manufacturers (OEMs) were derived by assuming that
manufacturing emissions equal 10 percent of the quantity of SF6 charged into new equipment. The quantity of SF6
charged into new equipment was estimated based on statistics compiled by the National Electrical Manufacturers
Association (NEMA). These statistics were provided for 1990 to 2000; the quantities of SF6 charged into new
equipment for 2001 to 2005 were assumed to equal that charged into equipment in 2000. The 10 percent emission
rate is the average of the "ideal" and "realistic" manufacturing emission rates (4 percent and 17 percent,
respectively) identified in a paper prepared under the auspices of the International Council on Large Electric
Systems (CIGRE) in February 2002 (O'Connell et al. 2002).
Uncertainty
To estimate the uncertainty associated with emissions of SF6 from electric transmission and distribution,
uncertainties associated with three variables were estimated: (1) emissions from partners, (2) emissions from non-
partners, and (3) emissions from manufacturers of electrical equipment. A Monte Carlo analysis was then applied to
estimate the overall uncertainty of the emissions estimate.
Total emissions from the SF6 Emission Reduction Partnership include emissions from both reporting and non-
reporting partners. For reporting partners, individual partner-reported SF6 data was assumed to have an uncertainty
of 10 percent. Based on a Monte Carlo analysis, the cumulative uncertainty of all partner reported data was
estimated to be 4.9 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 2005
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 61 percent of
U.S. transmission miles) will remain at levels defined by partners who reported in 1999. However, the last source
of uncertainty was not modeled.
4-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
Uncertainties were also estimated regarding the quantity of SF6 charged into equipment by equipment
manufacturers, which is projected from 2000 data from NEMA,and the manufacturers' SF6 emissions rate
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-72. Electrical Transmission
and Distribution SF6 emissions were estimated to be between 12.4 and 14.1 Tg C02 Eq. at the 95 percent confidence
level. This indicates a range of approximately 6 percent below and 7 percent above the emission estimate of 13.2
Tg C02 Eq.
Table 4-72: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Electrical Transmission and
Distribution (Tg C02 Eq. and Percent)
2005
Emission
Estimate
Uncertainty Range Relative to 2005 Emission Estimate3
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Electrical Transmission
and Distribution
sf6
13.2
12.4 14.1
-6% +7%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
In addition to the uncertainty quantified above, there is uncertainty associated with using global SF6 sales data to
estimate U.S. emission trends from 1990 through 1999. However, the trend in global emissions implied by sales of
SF6 appears to reflect the trend in global emissions implied by changing SF6 concentrations in the atmosphere. That
is, emissions based on global sales declined by 29 percent between 1995 and 1998, and emissions based on
atmospheric measurements declined by 27 percent over the same period. However, U.S. emission patterns may
differ from global emission patterns.
Recalculations Discussion
Relative to the previous Inventory report, SF6 emission estimates for the period 1990 through 2004 were updated
based on 1) new data from EPA's SF6 Emission Reduction Partnership, and 2) revisions to the assumptions used in
estimating global emissions between 1990 and 1999. For the period 1999 through 2004, estimates have been
revised to incorporate additional data from new partners. For the period 1990 through 1998, estimates have been
revised by updating the estimated lifetime of electrical equipment and the estimated historical emission rate during
equipment manufacturing. Previously, it was assumed that the equipment lifetime was 30 years, and that during
manufacture 22.5 percent of the SF6 purchased by equipment manufacturers was emitted. These variables have
been revised to 40 years and 18.8 percent, respectively, to reflect new data presented in IPCC Guidelines for
National Greenhouse Gas Inventories (IPCC 2006). Based on these revisions, SF6 emissions from electric
transmission and distribution have decreased by approximately 1 percent for each year during the 1999 to 2004
period. Between 1990 and 1998, estimates have changed between -16 percent (decrease) to +5 percent (increase)
depending on the specific year, relative to the previous report.
4.20. Semiconductor Manufacture (IPCC Source Category 2F6)
The semiconductor industry uses multiple long-lived fluorinated gases in plasma etching and plasma enhanced
chemical vapor deposition (PECVD) processes to produce semiconductor products. The gases most commonly
employed are trifluoromethane (HFC-23 or CHF3), perfluoromethane (CF4), perfluoroethane (C2F6), nitrogen
trifluoride (NF3), and sulfur hexafluoride (SF6), although other compounds such as perfluoropropane (C3F8) and
perfluorocyclobutane (c-C4F8) are also used. The exact combination of compounds is specific to the process
employed.
A single 300 mm silicon wafer that yields between 400 to 500 semiconductor products (devices or chips) may
require as many as 100 distinct fluorinated-gas-using process steps, principally to deposit and pattern dielectric
films. Plasma etching (or patterning) of dielectric films, such as silicon dioxide and silicon nitride, is performed to
Industrial Processes 4-55
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
provide pathways for conducting material to connect individual circuit components in each device. The patterning
process uses plasma-generated fluorine atoms, which chemically react with exposed dielectric film, to selectively
remove the desired portions of the film. The material removed as well as undissociated fluorinated gases flow into
waste streams and, unless emission abatement systems are employed, into the atmosphere. PECVD chambers, used
for depositing dielectric films, are cleaned periodically using fluorinated and other gases. During the cleaning cycle
the gas is converted to fluorine atoms in plasma, which etches away residual material from chamber walls,
electrodes, and chamber hardware. Undissociated fluorinated gases and other products pass from the chamber to
waste streams and, unless abatement systems are employed, into the atmosphere. In addition to emissions of
unreacted gases, some fluorinated compounds can also be transformed in the plasma processes into different
fluorinated compounds which are then exhausted, unless abated, into the atmosphere. For example, when C2F6 is
used in cleaning or etching, CF4 is generated and emitted as a process by-product. Besides dielectric film etching
and PECVD chamber cleaning, much smaller quantities of fluorinated gases are used to etch polysilicon films and
refractory metal films like tungsten.
For 2005, total weighted emissions of all fluorinated greenhouse gases by the U.S. semiconductor industry were
estimated to be 4.3 Tg C02 Eq. Combined emissions of all fluorinated greenhouse gases are presented in Table
4-73 and Table 4-74, below. The rapid growth of this industry and the increasing complexity (growing number of
layers) of semiconductor products led to an increase in emissions of 147 percent between 1990 and 1999. The
emissions growth rate began to slow after 1997, and emissions declined by 41 percent between 1999 and 2005. The
initial implementation of PFC emission reduction methods such as process optimization and abatement technologies
is responsible for this decline. Together, these two trends resulted in a net increase in emissions of 47 percent
between 1990 and 2005.
Table 4-73: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Tg C02 Eq.)
Year
1990
1995
2000
2001
2002
2003
2004
2005
cf4
0.7
1.3
| 1.8
1.3
1.1
1.0
1.2
1.1
c2f6
1.5
2.5 mm
3.0
2.1
2.2
2.1
2.2
1.9
c3f8
0.0
+ mm
O.i
0.1
0.1
0.1
0.0
0.0
c4f8
0.0
+ II1IB
0.0
0.0
0.0
0.1
0.1
0.1
HFC-23
0.2
0.3
0.3
0.2
0.2
0.2
0.2
0.2
sf6
0.5
0.9
1.1
0.8
0.7
0.8
0.9
1.0
nf3*
0.0
0.1
I 0.1
0.1
0.3
0.2
0.3
0.2
Total
2.9
5.0
6.3
4.5
4.4
4.3
4.7
4.3
Note: Totals may not sum due to independent rounding.
* NF3 emissions are presented for informational purposes, using a GWP of 8,000, and are not included in totals.
Table 4-74: PFC, HFC, and SF6 Emissions from Semiconductor Manufacture (Mg)
Year
1990
1995
cf4
115
192
c2f6
160
272
c3f8
o Hi
o
CA
o Hi
o
HFC-23
15
26
sf6
22
38
nf3
3
6
| 2000
2001
2002
2003
2004
2005
281
202
175
161
185
163
324
231
244
228
245
211
17
14
9
13
6
4
°
0
5
8
9
13
23
16
15
17
20
18
46
31
28
35
38
40
i 11
12
32
30
31
27
Methodology
Emissions from semiconductor manufacturing were estimated using three distinct methods, one each for the periods
1990 through 1994, 1995 through 1999, and 2000 and beyond. For 1990 through 1994, emissions were estimated
4-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
using the most recent version of EPA's PFC Emissions Vintage Model (PEVM) (Burton and Beizaie 2001).15 PFC
emissions per square centimeter of silicon increase as the number of layers in semiconductor devices increases.
Thus, PEVM incorporates information on the two attributes of semiconductor devices that affect the number of
layers: (1) linewidth technology (the smallest feature size, which leads to an increasing number of layers),16 and (2)
product type (memory vs. logic).17 PEVM derives historical consumption of silicon (i.e., square centimeters) by
linewidth technology from published data on annual wafer starts and average wafer size (Burton and Beizaie 2001).
For each linewidth technology, a weighted average number of layers is estimated using VLSI product-specific
worldwide silicon demand data in conjunction with complexity factors (i.e., the number of layers per IC) specific to
product type (Burton and Beizaie 2001, ITRS 2005). The distribution of memory/logic devices ranges over the
period covered from 52 percent logic devices in 1995 to 59 percent logic devices in 2000. These figures were used
to determine emission factors that express emissions per average layer per unit of area of silicon consumed during
product manufacture. The per-layer emission factor was based on the total annual emissions reported by
participants in EPA's PFC Reduction/Climate Partnership for the Semiconductor Industry in 1995 and later years.
For 1995 through 1999, total U.S. emissions were extrapolated from the total annual emissions reported by the
Partnership participants (2005 Aggregate PFC Emissions provided to EPA by Latham & Watkins). The emissions
reported by the participants were divided by the ratio of the total layer-weighted capacity of the plants operated by
the participants and the total layer-weighted capacity of all of the semiconductor plants in the United States; this
ratio represents the share of layer-weighted capacity attributable to partnership participants. The layer-weighted
capacity of a plant (or group of plants) consists of the silicon capacity of that plant multiplied by the estimated
number of layers used to fabricate products at that plant. This method assumes that participants and non-
participants have similar capacity utilizations and per-layer emission factors. Plant capacity, linewidth technology,
products manufactured information is contained in the World Fab Watch (WFW) database, which is updated
quarterly (see for example, Semiconductor Equipment and Materials Industry 2006).
The U.S. estimate for the years 2000 through 2005—the period during which partners began the consequential
application of PFC-reduction measures—was based on a different estimation method. The emissions reported by
Partnership participants for each year were accepted as the quantity emitted from the share of the industry
represented by those Partners. Remaining emissions (those from non-partners), however, were estimated using
PEVM and the method described above. (Non-partners are assumed not to have implemented any PFC-reduction
measures, and PEVM models emissions without such measures.) The portion of the U.S. total attributed to non-
Partners is obtained by multiplying PEVM's total U.S. figure by the non-partner share of total layer-weighted
silicon capacity for each year (as described above). Annual updates to PEVM reflect published figures for actual
silicon consumption from VLSI Research, Inc. as well as revisions and additions to the world population of
semiconductor manufacturing plants (see Semiconductor Equipment and Materials Industry 2006).1819
15 The most recent version of this model is v.3.2.0506.0507, completed in September 2005.
16 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 requires as many as 11 layers of component interconnects to achieve functionality while a device
manufactured with 130 nm feature size might contain a few hundred million transistors and require 8 layers of component
interconnects (ITRS, 2005).
17 Memory devices manufactured with the same feature sizes as microprocessors (a logic device) require approximately one-half
the number of interconnect layers (ITRS, 2005).
18 Special attention was given to the manufacturing capacity of plants that use wafers with 300 mm diameters because the actual
capacity of these plants in 2004 is below design capacity, the figure provided in WFW. To prevent overstating estimates of
partner-capacity shares from plants using 300 mm wafers, design capacities contained in WFW were replaced with estimates of
actual installed capacities for 2004 published by Citigroup Smith Barney (2005). Without this correction, the partner share of
capacity would be overstated, by approximately 5 percentage points. For perspective, approximately 95 percent of all new
capacity additions in 2004 used 300 mm wafers and by year-end those plants, on average, could operate at but approximately 70
percent of the design capacity. For 2005, actual installed capacities was estimated using an entry in the World Fab Watch
Industrial Processes 4-57
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
Two different approaches were also used to estimate the distribution of emissions of specific PFCs. Before 1999,
when there was no consequential adoption of PFC-reducing measures, a fixed distribution was assumed to apply to
the entire U.S. industry. This distribution was based upon the average PFC purchases by semiconductor
manufacturers during this period and the application of IPCC default emission factors for each gas (Burton and
Beizaie 2001). For the 2000 through 2005 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 2005 were estimated by adding the emissions reported by the Partners to those
estimated for the non-Partners.20
Partners estimate their emissions using a range of methods. For 2005, 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. However, this is expected to change with publication of the updated IPCC
(2006). The partners with relatively high emissions typically use the more accurate IPCC 2b or 2a methods,
multiplying estimates of their PFC consumption by process-specific emission factors that they have either measured
or obtained from tool suppliers.
Data used to develop emission estimates were prepared in cooperation with the Partnership. Estimates of operating
plant capacities and characteristics for participants and non-participants were derived from the Semiconductor
Equipment and Materials Industry (SEMI) World Fab Watch (formerly International Fabs on Disk) database (1996
to 2006). Estimates of silicon consumed by line-width from 1990 through 2005 were derived from information
from VLSI Research (2005), and the number of layers per line-width was obtained from International Technology
Roadmap for Semiconductors: 1998-2004 (Burton and Beizaie 2001, ITRS 2005).
Uncertainty
A quantitative uncertainty analysis of this source category was performed using the IPCC-recommended Tier 2
uncertainty estimation methodology, the Monte Carlo Stochastic Simulation technique. The equation used to
estimate uncertainty is:
U.S. emissions = PEVM estimate - (Partnership share * PEVM estimate) + Partnership submittal
The Monte Carlo analysis results presented below relied on estimates of uncertainty attributed to the three variables
on the right side of the equation. Estimates of uncertainty for the three variables were in turn developed using the
estimated uncertainties associated with the individual inputs to each variable, error propagation analysis, and expert
judgment. For the relative uncertainty associated with the PEVM estimate in 2005, an uncertainty of ±20 percent
was estimated, using the calculus of error propagation and considering the aggregate average emission factor, world
silicon consumption, and the U.S. share of layer-weighted silicon capacity. For the share of U.S. layer-weighted
silicon capacity accounted for by Partners, a relative uncertainty of ±10 percent was estimated based on information
from the firm that compiled the World Fab Watch database (SMA 2003). For the aggregate PFC emissions data
supplied to the partnership, a relative uncertainty of approximately ±10 percent was estimated (representing a 95
percent confidence interval).
database (April 2006 Edition) called "wafers/month, 8-inch equivalent, which denotes the actual installed capacity instead of the
fully-ramped capacity.
19 In 2005, the trend in co-owernship of manufacturing facilities in the industry 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 US layer-weighted manufacturing
capacity.
20 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.
4-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
Consideration was also given to the nature and magnitude of the potential bias that PEVM might have in its
estimates of the number of layers associated with devices manufactured at each technology node. The result of a
brief analysis indicated that PEVM overstates the average number of layers across all product categories and all
manufacturing technologies for 2004 by 0.12 layers or 2.9 percent. This bias is represented in the uncertainty
analysis by deducting the absolute bias value from the PEVM emission estimate when it is incorporated into the
Monte Carlo analysis.
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 4-75. The emissions estimate for
total U.S. PFC emissions from semiconductor manufacturing were estimated to be between 3.6 and 5.4 Tg C02 Eq.
at a 95 percent confidence level. This range represents 21 percent below to 20 percent above the 2005 emission
estimate of 4.5 Tg C02 Eq. This range and the associated percentages apply to the estimate of total emissions rather
than those of individual gases. Uncertainties associated with individual gases will be somewhat higher than the
aggregate, but were not explicitly modeled.
Table 4-75: Tier 2 Quantitative Uncertainty Estimates for HFC, PFC, and SF6 Emissions from Semiconductor
Manufacture (Tg C02 Eq. and Percent)
2005
Emission
Uncertainty Range
Source
Estimate"
Relative to Emission Estimateb
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Upper
Lower
Upper
Bound
Bound
Bound
Bound
Semiconductor
HFC, PFC,
Manufacture
and SF6
4.3
3.6
5.4
-21%
+20%
a Because the uncertainty analysis covered all emissions (including NF3), the emission estimate presented here does not match
that shown in Table 4-73.
b Range of emissions estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Planned Improvements
The method to estimate non-partner related emissions (i.e., PEVM) is not expected to change (with the exception of
possible future updates to emission factors and added technology nodes). Future improvements to the national
emission estimates will primarily be associated with determining the portion of national emissions to attribute to
partner report totals (about 80 percent in recent years). As the nature of the partner reports change through time and
industry-wide reduction efforts increase, consideration will be given to what emission reduction efforts—if any—
are likely to be occurring at non-partner facilities. (Currently none are assumed to occur.)
4.21. Aluminum Production (IPCC Source Category 2C3)
Aluminum is a light-weight, malleable, and corrosion-resistant metal that is used in many manufactured products,
including aircraft, automobiles, bicycles, and kitchen utensils. In 2005, 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 C02 and two perfluorocarbons
(PFCs): perfluoromethane (CF4) and perfluoroethane (C2F6).
C02 is emitted during the aluminum smelting process when alumina (aluminum oxide, A1203) is reduced to
aluminum using the Hall-Heroult reduction process. The reduction of the alumina occurs through electrolysis in a
molten bath of natural or synthetic cryolite (Na3AlF6). The reduction cells contain a 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 C02.
Process emissions of C02 from aluminum production were estimated to be 4.2 Tg C02 Eq. (4,208 Gg) in 2005 (see
Table 4-76). The C anodes consumed during aluminum production consist of petroleum coke and, to a minor
Industrial Processes 4-59
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Public Review Draft
extent, coal tar pitch. The petroleum coke portion of the total C02 process emissions from aluminum production is
considered to be a non-energy use of petroleum coke, and is accounted for here and not under the C02 from Fossil
Fuel Combustion source category of the Energy sector. Similarly, the coal tar pitch portion of these C02 process
emissions is accounted for here rather than in the Iron and Steel source category of the Industrial Processes sector.
Table 4-76: C02 Emissions from Aluminum Production (Tg C02 Eq. and Gg)
Year TgCQ2Eq. Gg
6,831
2000
2001
2002
2003
2004
2005
6.1
4.4
4.5
4.5
4.2
4.2
6,086
4,381
4,490
4,503
4,231
4,208
In addition to C02 emissions, the aluminum production industry is also a source of PFC emissions. During the
smelting process, when the alumina ore content of the electrolytic bath falls below critical levels required for
electrolysis, rapid voltage increases occur, which are termed "anode effects." These anode effects cause C from the
anode and fluorine from the dissociated molten cryolite bath to combine, thereby producing fugitive emissions of
CF4 and C2F6. In general, the magnitude of emissions for a given level of production depends on the frequency and
duration of these anode effects. As the frequency and duration of the anode effects increase, emissions increase.
Since 1990, emissions of CF4 and C2F6 have both declined by 84 percent to 2.5 Tg C02 Eq. of CF4 (0.4 Gg) and 0.4
Tg C02 Eq. of C2F6 (0.05 Gg) in 2005, as shown in Table 4-77 and Table 4-78. This decline is due both to
reductions in domestic aluminum production and to actions taken by aluminum smelting companies to reduce the
frequency and duration of anode effects. Since 1990, aluminum production has declined by 39 percent, while the
average CF4 and C2F6 emission rates (per metric ton of aluminum produced) have each been reduced by 74 percent.
Table 4-77: PFC Emissions from Aluminum Production (Tg C02 Eq.)
Year CF4 C2F6 Total
2000
2001
2002
2003
2004
2005
7.
3.0
4.6
3.3
2.4
2.5
Oi
0.4
0.7
0.5
0.4
0.4
S.6
3.5
5.2
3.8
2.8
3.0
Note: Totals may not sum due to independent rounding.
Table 4-78: PFC Emissions from Aluminum Production (Gg)
Year
cf4
c2f6
1990
2.4
0.3
¦ill
lilllil
¦¦¦
19'^
1.6
o:
—
2000
1.2
0.1
2001
0.5
+
2002
0.7
0.1
4-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
2003
2004
2005
0.5
0.4
0.4
0.1
+
+
1 + Does not exceed 0.05 Gg
2 In 2005, U.S. primary aluminum production totaled approximately 2.5 million metric tons, similar to 2004
3 production levels. Due to high electric power costs in various regions of the country, aluminum production has
4 been curtailed at several U.S. smelters, which resulted in 2005 production levels that were approximately 34 percent
5 lower than the levels in 1999, the year with the highest production over the prior decade, 1995 through 2005. The
6 transportation industry remained the largest domestic consumer of primary aluminum, accounting for about 39
7 percent of U.S. consumption (USGS 2006).
8 Methodology
9 C02 emissions released during aluminum production were estimated using the combined application of process-
10 specific emissions estimates modeling with individual partner reported data. These estimates are achieved through
11 information gathered by EPA's Voluntary Aluminum Industrial Partnership (VAIP) program.
12 Most of the C02 emissions released during aluminum production occur during the electrolysis reaction of the C
13 anode, as described by the following reaction.
14 2A1203 + 3C -> 4A1 + 3C02
15 For prebake smelter technologies, C02 is also emitted during the anode baking process. These emissions can
16 account for approximately 10 percent of total process C02 emissions from prebake smelters. The C02 emission
17 factor employed was estimated from the production of primary aluminum metal and the C consumed by the process.
18 Emissions vary depending on the specific technology used by each plant (e.g., prebake or Soderberg). C02 process
19 emissions were estimated using the methodology recommended by IPCC (2006).
20 The prebake process specific formula recommended by IPCC (2006) accounts for various parameters, including net
21 C consumption, and the sulfur, ash, and impurity content of the baked anode. For anode baking emissions, process
22 formulas account for packing coke consumption, the sulfur and ash content of the packing coke, as well as the pitch
23 content and weight of baked anodes produced. The Soderberg process formula accounts for the weight of paste
24 consumed per metric ton of aluminum produced, and pitch properties, including sulfur, hydrogen, and ash content.
25 Through the VAIP, process data have been reported for 1990, 2000, 2003, 2004, and 2005. Where available,
26 smelter-specific process data reported under the VAIP were used; however, if the data were incomplete or
27 unavailable, information was supplemented using industry average values recommended by IPCC (2006). Smelter-
28 specific C02 process data were provided by 18 of the 23 operating smelters in 1990 and 2000, by 14 out of 16
29 operating smelters in 2003 and 2004, and by 14 out of 15 operating smelters in 2005. For years where C02 process
30 data were not reported by these companies, estimates were developed through linear interpolation, and/or assuming
31 industry default values.
32 In the absence of any smelter specific process data (i.e., 1 out of 15 smelters in 2005, and 5 out of 23 between 1990
33 and 2003), C02 emission estimates were estimated using Tier 1 Soderberg and/or Prebake emission factors (metric
34 ton of C02 per metric ton of aluminum produced) from IPCC(2006)
35 Aluminum production data for all operating smelters were reported under the VAIP in 2005. Between 1990 and
36 2004, production data were provided by 21 of the 23 U.S. smelters that operated during at least part of that period.
37 For the non-reporting smelters, production was estimated based on the difference between reporting smelters and
38 national aluminum production levels (USAA 2006), with allocation to specific smelters based on reported
39 production capacities (USGS 2002).
40 PFC emissions from aluminum production were estimated using a per-unit production emission factor that is
41 expressed as a function of operating parameters (anode effect frequency and duration), as follows:
Industrial Processes 4-61
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
PFC (CF4 or C2F6) kg/metric ton A1 = S x Anode Effect Minutes/Cell-Day
where,
S = Slope coefficient (kg PFC/metric ton Al/(Anode Effect minutes/cell day))
Anode Effect Minutes/Cell-Day = Anode Effect Frequency/Cell-Day x Anode Effect Duration (minutes)
Smelter-specific slope coefficients that are based on field measurements yield the most accurate results. To estimate
emissions between 1990 and 2004, smelter-specific coefficients were available and were used for 12 out of the 23
U.S. smelters that operated during at least part of that period. To estimate 2005 emissions, smelter-specific
coefficients were available and were used for 5 out of the 15 operating U.S. smelters, representing approximately 33
percent of operating 2005 U.S. production capacity. For the remaining 10 operating smelters, technology-specific
slope coefficients from IPCC (2001) were applied. The slope coefficients were combined with smelter-specific
anode effect data collected by aluminum companies and reported under the VAIP, to estimate emission factors over
time. In 2005, smelter-specific anode effect data were available for all operating smelters. Where smelter-specific
anode effect data were not available (i.e., 2 out of 23 smelters between 1990 and 2004), industry averages were
used. For all smelters, emission factors were multiplied by annual production to estimate annual emissions at the
smelter level. In 2005, smelter-specific production data were available for all operating smelters. Between 1990
and 2004, production data has been provided by 21 of the 23 U.S. smelters. Emissions were then aggregated across
smelters to estimate national emissions. The methodology used to estimate emissions is consistent with the
methodologies recommended by IPCC (2006).
National primary aluminum production data for 1990 through 2001 (see Table 4-79) were obtained from USGS,
Mineral Industry Surveys: Aluminum Annual Report (USGS 1995, 1998, 2000, 2001, 2002). For 2002 through
2005, national aluminum production data were obtained from the United States Aluminum Association's Primary
Aluminum Statistics (USAA 2004, 2005, 2006).
Table 4-79: Production of Primary Aluminum (Gg)
Year Gg
1990
4,048
1995
3,375
2000
2001
2002
2003
2004
2005
3,668
2,637
2,705
2,705
2,517
2,478
Uncertainty
The overall uncertainties associated with the 2005 C02, CF4, and C2F6 emission estimates were calculated using
Approach 2, as defined by IPCC (2006). For C02, uncertainty was assigned to each of the parameters used to
estimate C02 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 C02 emission estimate for the U.S. aluminum industry
as a whole, and the results are provided below.
To estimate the uncertainty associated with emissions of CF4 and C2F6, the uncertainties associated with three
variables were estimated for each smelter: (1) the quantity of aluminum produced, (2) the anode effect minutes per
cell day (which may be reported directly or calculated as the product of anode effect frequency and anode effect
duration), and (3) the smelter- or technology-specific slope coefficient. A Monte Carlo analysis was then applied
to estimate the overall uncertainty of the emission estimate for each smelter or company and for the U.S. aluminum
4-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
industry as a whole.
The results of this quantitative uncertainty analysis are summarized in Table 4-80. Aluminum production-related
C02 emissions were estimated to be between 4.0 and 4.4 Tg C02 Eq. at the 95 percent confidence level. This
indicates a range of approximately 5 percent below to 5 percent above the emission estimate of 4.2 Tg C02 Eq.
Also, production-related CF4 emissions were estimated to be between 2.3 and 2.7 Tg C02 Eq. at the 95 percent
confidence level. This indicates a range of approximately 8 percent below to 8 percent above the emission estimate
of 2.5 Tg C02 Eq. Finally, aluminum production-related C2F6 emissions were estimated to be between 0.4 and 0.5
Tg C02 Eq. at the 95 percent confidence level. This indicates a range of approximately 15 percent below to 16
percent above the emission estimate of 0.4 Tg C02 Eq.
Table 4-80: Tier 2 Quantitative Uncertainty Estimates for C02 and PFC Emissions from Aluminum Production (Tg
C02 Eq. and Percent)
2005
Uncertainty Range Relative to 2005 Emission Estimate3
Emission
Source
Gas
Estimate
(Tg C02 Eq.)
(%)
Lower
Upper
Lower
Upper
(Tg C02 Eq.)
Bound
Bound
Bound
Bound
Aluminum Production
C02
4.2
4.0
4.4
-5%
+5%
Aluminum Production
cf4
2.5
2.3
2.7
-8%
+8%
Aluminum Production
c2f6
0.4
0.4
0.5
-15%
+16%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Note that the 2005 emission estimate was developed using IPCC (2001) slope coefficients for the 10 operating
smelters without site-specific PFC measurements. If these slope coefficients were revised to incorporate recent
IPCC (2006) slope data, overall PFC emission estimates for 2005 would be on the order of 10 percent lower than
current estimates. Additionally, since these smelters are owned by one company, data have been reported on a
company-wide basis as totals or weighted averages. Consequently, uncertainties in anode effect minutes per cell
day, slope coefficients, and aluminum production have been applied to the company as a whole, and not on a
smelter-specific basis. This probably overestimates the uncertainty associated with the cumulative emissions from
these smelters, because errors that were in fact independent were treated as if they were correlated. It is therefore
likely that uncertainties calculated above for the total U.S. 2005 emission estimates for CF4 and C2F6 are also high.
This inventory may slightly underestimate greenhouse gas emissions from aluminum production and casting
because it does not account for the possible use of SF6 as a cover gas or a fluxing and degassing agent in
experimental and specialized casting operations. The extent of such use in the U.S. is not known. Historically, SF6
emissions from aluminum activities have been omitted from estimates of global SF6 emissions, with the explanation
that any emissions would be insignificant (Ko et al. 1993, Victor and MacDonald 1998). The concentration of SF6
in the mixtures is small and a portion of the SF6 is decomposed in the process (MacNeal et al. 1990, Gariepy and
Dube 1992, Ko et al. 1993, Ten Eyck and Lukens 1996, Zurecki 1996).
Recalculations Discussion
Relative to the previous Inventory report, C02 emission estimates for the period 1990 through 2004 were updated
based on revisions to default parameters used in the estimation methodology. Previous C02 emission estimates
were based on default emission factors defined by IPCC/UNEP/OED/IEA (1997) and Aluminum Sector Greenhouse
Gas Protocol (IAI2003). Current estimates utilize default parameters defined in IPCC (2006). Based on this
revision, C02 emissions from aluminum production have decreased by approximately 3 percent for each year during
the 1990 to 2004 period relative to the previous report.
The default slope coefficients used to estimate PFC emissions from two smelters that have not developed Tier 3b
site-specific estimates were revised to reflect data presented in IPCC (2006). This change has resulted in an
increase in PFC emissions of approximately 1 percent in 1990, an average decrease of 0.1 percent between 1991
and 1996 and 2002 through 2004, and an average decrease of 6 percent from 1997 through 2001, relative to the
estimates developed for the 1990 to 2004 inventory.
Industrial Processes 4-63
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
4.22. Magnesium Production and Processing (IPCC Source Category 2C4)
The magnesium metal production and casting industry uses sulfur hexafluoride (SF6) as a cover gas to prevent the
rapid oxidation of molten magnesium in the presence of air. A dilute gaseous mixture of SF6 with dry air and/or
C02 is blown over molten magnesium metal to induce and stabilize the formation of a protective crust. A small
portion of the SF6 reacts with the magnesium to form a thin molecular film of mostly magnesium oxide and
magnesium fluoride. The amount of SF6 reacting in magnesium production and processing is assumed to be
negligible and thus all SF6 used is assumed to be emitted into the atmosphere. Sulfur hexafluoride has been used in
this application around the world for the last twenty years.
The magnesium industry emitted 2.7 Tg C02 Eq. (0.1 Gg) of SF6 in 2005, representing an increase of approximately
2 percent from 2004 emissions (see Table 4-81). A planned expansion of primary magnesium production in the
United States has been delayed due to unfavorable market conditions. Antidumping duties imposed on Chinese
imports by the U.S. International Trade Commission have shifted the majority of U.S. demand for primary
magnesium to imports from Canada, Israel, and Russia (USGS 2006). Die casting operations in the United States
have remained stable and are expected to increase as demand for die cast parts for the automotive sector increases
due to fuel efficiency design objectives.
Table 4-81: SF6 Emissions from Magnesium Production and Processing (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
1990
5.4
0.2
1995
5.6
0.2
mmm
2000
3.0
0.1
2001
2.4
0.1
2002
2.4
0.1
2003
2.9
0.1
2004
2.6
0.1
2005
2.7
0.1
Methodology
1999 to 2005 Emissions
Emission estimates for the magnesium industry from 1999 through 2005 incorporate information provided by
industry participants in EPA's SF6 Emission Reduction Partnership for the Magnesium Industry. The Partnership
started in 1999 and currently, participating companies represent 100 percent of U.S. primary and secondary
production and 90 percent of the casting sector (i.e., die, sand, permanent mold, wrought, and anode casting).
Absolute emissions for 1999 through 2005 from primary production, secondary production (i.e., recycling), and die
casting were reported by Partnership participants. Emission factors for 2002 to 2005 for sand casting activities were
also acquired through the Partnership. The 1999 through 2005 emissions from casting operations (other than die)
were estimated by multiplying emission factors (kg SF6 per metric ton of Mg produced or processed) by the amount
of metal produced or consumed. U.S. magnesium metal production (primary and secondary) and consumption
(casting) data from 1990 through 2005 were available from the USGS (USGS 2002, 2003, 2005a, 2005b, 2006).
The emission factors for casting activities are provided below in Table 4-82. The emission factors for primary
production, secondary production, and sand casting are withheld to protect company-specific production
information. However, the emission factor for primary production has not risen above the 1995 value of 1.1 kg SF6
per metric ton, and the emission factor for secondary production is slightly lower than the industry-reported historic
value of 1 kg SF6 per metric ton.
Die casting emissions for 1999 through 2005, which accounted for 33 to 52 percent of all SF6 emissions from the
U.S. magnesium industry during this period, were estimated based on information supplied by industry Partners.
From 2000 to 2005, Partners accounted for all U.S. die casting that was tracked by USGS. If Partners did not report
4-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
emissions data for a certain year, SF6 emissions data were estimated using available information on emission factors
and production reported in prior years. Each non-reporting Partner's production was assumed to have remained
constant since the last report, while each non-reporting Partner's emission factor was assumed to have followed the
same trend as the emission factors for reporting die casting partners. Emissions from non-reporting Partners are
estimated to have accounted for less than 15 percent of die-casting emissions in all years since 1999.
In 1999, Partners did not account for all die casting tracked by USGS, and, therefore, it was necessary to estimate
the emissions of die casters who were not Partners. Die casters who were not Partners were assumed to be similar
to Partners who cast small parts. Due to process requirements, these casters consume larger quantities of SF6 per
metric ton of processed magnesium than casters that process large parts. Consequently, emission estimates from
this group of die casters were developed using an average emission factor of 5.2 kg SF6 per metric ton of
magnesium. The emission factors for the other industry sectors (i.e., permanent mold, wrought, and anode casting)
were based on discussions with industry representatives.
Permanent
Year
Die Casting
Mold
Wrought Anodes
1999
2.14a
2
1 1
2000
0.73
2
1 1
2001
0.77
2
1 1
2002
0.70
2
1 1
2003
0.84
2
1 1
2004
0.78
2
1 1
2005
0.75
2
1 1
a Weighted average that includes an estimated emission factor of 5.2 kg SF6 per metric ton of magnesium for die casters that do
not participate in the Partnership.
1990 to 1998 Emissions
To estimate emissions for 1990 through 1998, industry emission factors were multiplied by the corresponding metal
production and consumption (casting) statistics from USGS. The primary production emission factors were 1.2 kg
per metric ton for 1990 through 1993, and 1.1 kg per metric ton for 1994 through 1996. These factors were based
on information reported by U.S. primary producers. For die casting, an emission factor of 4.1 kg per metric ton was
used for the period 1990 through 1996, based on an international survey (Gjestland & Magers 1996). For 1996
through 1998, the emission factors for primary production and die casting were assumed to decline linearly to the
level estimated based on Partner reports in 1999. This assumption is consistent with the trend in SF6 sales to the
magnesium sector that is reported in the RAND survey of major SF6 manufacturers, which shows a decline of 70
percent from 1996 to 1999 (RAND 2002). The emission factor for sand casting between 1990 and 2001 was
assumed to have been the same as the 2002 emission factor provided by Partners for this process. The emission
factor for secondary production from 1990 through 1998 was similarly assumed to be constant at 1 kg per metric
ton. 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 4-82.
Uncertainty
To estimate the uncertainty of the estimated 2005 SF6 emissions from magnesium production and processing, the
uncertainties associated with three variables were estimated: (1) emissions reported by magnesium producers and
processors that participate in the 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. In general, where precise quantitative information was not
available on the uncertainty of a parameter, an upper-bound value was used.
Additional uncertainties exist in these estimates, such as the basic assumption that SF6 neither reacts nor
decomposes during use. The melt surface reactions and high temperatures associated with molten magnesium could
potentially cause some gas degradation. Recent measurement studies have identified SF6 cover gas degradation at
hot-chambered die casting machines on the order of 10 percent (Bartos et al. 2003). As is the case for other sources
Industrial Processes 4-65
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
of SF6 emissions, total SF6 consumption data for magnesium production and processing in the United States were
not available. Sulfur hexafluoride may also be used as a cover gas for the casting of molten aluminum with high
magnesium content; however, to what extent this technique is used in the United States is unknown.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 4-83. SF6 emissions associated
with magnesium production and processing were estimated to be between 2.6 and 2.8 Tg C02 Eq. at the 95 percent
confidence level. This indicates a range of approximately 4 percent below to 4 percent above the 2005 emissions
estimate of 2.7 Tg C02 Eq.
Table 4-83: Tier 2 Quantitative Uncertainty Estimates for SF6 Emissions from Magnesium Production and
2005 Emission
Uncertainty Range Relative to Emission
Source
Gas
Estimate
Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Bound
Upper
Bound
Lower Upper
Bound Bound
Magnesium
Production
sf6
2.7
2.6
2.8
-4% +4%
1 Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
The methodology for estimating secondary magnesium production (recycling) emissions from 1999 to 2005 was
adjusted to rely solely on Partner-reported information, because this was believed to yield a more accurate estimate
than adding Partner-reported emissions to the product of USGS secondary magnesium production and a default
industry SF6 emission factor. In previous years, the "remelt" activity reported by Partners was small compared to
the secondary production reported by USGS, and it was uncertain whether this remelt activity was included in
USGS totals. Thus, emissions were estimated both for Partner-reported remelt and for USGS-reported secondary
production. With the addition of new Partners, however, it appears that Partner-reported remelt is actually a more
complete estimate of U.S. secondary production than the USGS value. Thus, to avoid double-counting, only the
emissions reported by the Partners are included in the totals for the time series. The change resulted in a decrease of
0.2 Tg C02 Eq. (approximately 7 percent) in SF6 emissions from magnesium production and processing for 1999 to
2002, and a decrease in SF6 emissions of 0.1 Tg C02 Eq. (approximately 4 percent) for 2003 to 2004 relative to the
previous report.
Planned Improvements
As more work assessing the degree of cover gas degradation and associated byproducts is undertaken and
published, results could potentially be used to refine the emission estimates, which currently assume (per IPCC
Good Practice Guidance, IPCC 2000) that all SF6 utilized is emitted to the atmosphere. EPA-funded measurements
of SF6 in hot chamber die casting have indicated that the latter assumption may be incorrect, with observed SF6
degradation on the order of 10 percent (Bartos et al. 2003). More recent EPA-funded measurement studies have
confirmed this observation for cold chamber die casting (EPA 2004). Another issue that will be addressed in future
inventories is the likely adoption of alternate cover gases by U.S. magnesium producers and processors. These
cover gases, which include AM-Cover™ (containing HFC-134a) and Novec™ 612, have lower GWPs than SF6,
and tend to quickly decompose during their exposure to the molten metal. Additionally, as more companies join the
Partnership, in particular those from sectors not currently represented such as permanent mold and anode casting,
emission factors will be refined to incorporate these additional data.
4.23. Industrial Sources of Indirect Greenhouse Gases
In addition to the main greenhouse gases addressed above, many industrial processes generate emissions of indirect
greenhouse gases. Total emissions of nitrogen oxides (NOx), carbon monoxide (CO), and non-CH4 volatile organic
compounds (NMVOCs) from non-energy industrial processes from 1990 to 2005 are reported in Table 4-84.
4-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Public Review Draft
Table 4-84: NOx, CO, and NMVOC Emissions from Industrial Processes (Gg)
Gas/Source
1990
19951
NOx
591
607
Other Industrial Processes
343
362
Chemical & Allied Product Manufacturing
152
143
Metals Processing
88
89
Storage and Transport
311
5
Miscellaneous*
511
8
CO
4,125
3,959
Metals Processing
2,395
2,159
Other Industrial Processes
487
566
Chemical & Allied Product Manufacturing
1,073
1.110
Storage and Transport
69
23
Miscellaneous*
101
102
NMVOCs
2,422
2,642
Storage and Transport
1,352
1,499
Other Industrial Processes
364
408
Chemical & Allied Product Manufacturing
575
5"
Metals Processing
111
113
Miscellaneous*
20
231
| 2000
2001
2002
2003
2004
2005
! 626
656
532
533
534
535
434
457
389
390
390
391
I 95
97
63
63
63
63
1 81
86
63
63
63
63
14
15
17
17
17
17
1 2
1
1
1
1
1
1 2,217
2,339
1,710
1,730
1,751
1,772
I 1,175
1,252
895
906
917
928
1 538
558
445
450
456
461
1 327
338
258
261
264
267
| 154
162
107
108
109
111
| 23
30
5
5
5
4
I 1,773
1,769
1,811
1,813
1,815
1,818
| 1,067
1,082
1,140
1,142
1,143
1,144
! 412
381
400
401
401
402
I 230
238
227
227
227
227
61
65
42
42
42
42
I 3
4
2
2
2
2
* Miscellaneous includes the following categories: catastrophic/accidental release, other combustion, health services, cooling
towers, and fugitive dust. It does not include agricultural fires or slash/prescribed burning, which are accounted for under the
Field Burning of Agricultural Residues source.
Note: Totals may not sum due to independent rounding.
Methodology
These emission estimates were obtained from preliminary data (EPA 2006), 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.
Industrial Processes 4-67
-------
-------
Substitution of Ozone Depleting Substances
Iron and Steel Production
Cement Manufacture
HCFC-22 Production
Ammonia Production and Urea Application
Nitric Acid
Lime Manufacture
Electrical Transmission and Distribution
Limestone and Dolomite Use
Aluminum Production
Adipic Acid
Semiconductor Manufacture
Soda Ash Manufacture and Consumption
Petrochemical Production
Magnesium Production and Processing
Titanium Dioxide Production
Ferroalloy Production
Phosphoric Acid Production
Carbon Dioxide Consumption
Zinc Production
Lead Production
Silicon Carbide Production and Consumption
I
I
I
I
I
I
ko.5
<0.5
<0.5
Industrial Processes
as a Portion of all
Emissions
4.6%
25
50 75
Tg C02 Eq
100
125
Figure 4-1: 2005 Industrial Processes Chapter Greenhouse Gas Sources
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
5. Solvent and Other Product Use
Greenhouse gas emissions are produced as a by-product of various solvent and other product uses. In the United
States, emissions from Nitrous Oxide (N20) Product Usage, the only source of greenhouse gas emissions from this
sector, accounted for less than 0.1 percent of total U.S. anthropogenic greenhouse gas emissions on a carbon
equivalent basis in 2005 (see Table 5-1). Indirect greenhouse gas emissions also result from solvent and other
product use, and are presented in Table 5-2 in teragrams of C02 equivalent (Tg C02 Eq.) and gigagrams (Gg).
Table 5-1: N2Q Emissions from Solvent and Other Product Use (Tg C02 Eq. and Gg)
Gas/Source
1990
I 1995
2000
2001
2002
2003
2004
2005
N20 Product Usage
Tg C02 Eq.
4.3
4.5
4.8
4.8
4.3
4.3
4.3
4.3
Gg
14
I 14
15
15
14
14
14
14
Table 5-2: Indirect Greenhouse Gas Emissions from Solvent and Other Product Use (Gg)
Gas/Source
1990
1 1995
2000
2001
2002
2003
2004
2005
NMVOCs
5,216
5,60'J
4,384
4,547
3,911
3,916
3,921
3,926
CO
5 ¦
5
46
45
1
1
1
1
NOx
'
1 3
3
3
5
5
5
5
5.1. Nitrous Oxide Product Usage (IPCC Source Category 3D)
N20 is a clear, colorless, oxidizing liquefied gas, with a slightly sweet odor. N20 is produced by thermally
decomposing ammonium nitrate (NH4N03), a chemical commonly used in fertilizers and explosives. The
decomposition creates steam (H20) and N20 through a low-pressure, low-temperature (500°F) reaction. Once the
steam is removed through condensation, the remaining N20 is purified, compressed, dried, and liquefied for storage
and distribution. Two companies operate a total of five N20 production facilities in the United States (CGA 2003).
N20 is primarily used in carrier gases with oxygen to administer more potent inhalation anesthetics for general
anesthesia and as an anesthetic in various dental and veterinary applications. As such, it is used to treat short-term
pain, for sedation in minor elective surgeries and as an induction anesthetic. The second main use of N20 is as a
propellant in pressure and aerosol products, the largest application being pressure-packaged whipped cream. Small
quantities of N20 also are used in the following applications:
• 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 N20 in 2005 was approximately 15 Gg. N20 emissions were 4.3 Tg C02 Eq. (14 Gg) in 2005 (see
Table 5-3). Production of N20 stabilized during the 1990s because medical markets had found other substitutes for
anesthetics, and more medical procedures were being performed on an outpatient basis using local anesthetics that
do not require N20. The use of N20 as a propellant for whipped cream has also stabilized due to the increased
popularity of cream products packaged in reusable plastic tubs (Heydorn 1997).
Table 5-3: N2Q Emissions from N2Q Product Usage (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
1990 4.3 14
1995 4.5 14
Solvent and Other Product Use 5-1
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
2000 4.8 15
2000
2001
2002
2003
2004
2005
15
15
14
14
14
14
4.8
4.3
4.3
4.3
4.3
Methodology
Emissions from N20 product usage were calculated by first multiplying the total amount of N20 produced in the
United States by the share of the total quantity of N20 attributed to each end use. This value was then multiplied by
the associated emissions rate for each end use. After the emissions were calculated for each end use, they were
added together to obtain a total estimate of N20 product usage emissions. Emissions were determined using the
following equation:
The share of total quantity of N20 usage by end use represents the share of national N20 produced that is used by
the specific subcategory (i.e., anesthesia, food processing, etc.). In 2005, the medical/dental industry used an
estimated 89.5 percent of total N20 produced, followed by food processing propellants at 6.5 percent. All other
categories combined used the remainder of the N20 produced. This subcategory breakdown has changed only
slightly over the past decade. For instance, the small share of N20 usage in the production of sodium azide has
declined significantly during the decade of the 1990s. Due to the lack of information on the specific time period of
the phase-out in this market subcategory, most of the N20 usage for sodium azide production is assumed to have
ceased after 1996, with the majority of its small share of the market assigned to the larger medical/dental
consumption subcategory. The N20 was allocated across these subcategories, a usage emissions rate was then
applied for each sector to estimate the amount of N20 emitted.
Only the medical/dental and food propellant subcategories were estimated to release emissions into the atmosphere,
and therefore these subcategories were the only usage subcategories with emission rates. For the medical/dental
subcategory, due to the poor solubility of N20 in blood and other tissues, approximately 97.5 percent of the N20 is
not metabolized during anesthesia and quickly leaves the body in exhaled breath. Therefore, an emission factor of
97.5 percent was used for this subcategory (Tupman 2002). For N20 used as a propellant in pressurized and aerosol
food products, none of the N20 is reacted during the process and all of the N20 is emitted to the atmosphere,
resulting in an emissions factor of 100 percent for this subcategory (Heydorn 1997). For the remaining
subcategories, all of the N20 is consumed/reacted during the process, and therefore the emissions rate was
considered to be zero percent (Tupman 2002).
The 1990 through 1992 and 1996 N20 production data were obtained from SRI Consulting's Nitrous Oxide, North
America report (Heydorn 1997). These data were provided as a range. For example, in 1996, Heydorn (1997)
estimates N20 production to range between 13.6 and 18.1 thousand metric tons. Tupman (2003) provided a
narrower range for 1996 that falls within the production bounds described by Heydorn (1997). These data are
considered more industry specific and current. The midpoint of the narrower production range (15.9 to 18.1
thousand metric tons) was used to estimate N20 emissions for years 1993 through 2001 (Tupman 2003). The 2002
and 2003 N20 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 N20 production to range between 13.6 and 15.9 thousand metric tons. Due to unavailable
data, production for 2004 and 2005 were held at the value provided for 2003.
The 1996 share of the total quantity of N20 used by each subcategory was obtained from SRI Consulting's Nitrous
N20 Product Usage Emissions = X, [Total U.S. Production of N20] x [Share of Total Quantity of N20
Usage by Sector i] x [Emissions Rate for Sector i]
where,
i = sector.
5-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Oxide, North America report (Heydorn 1997). The 1990 through 1995 share of total quantity of N20 used by each
2 subcategory was kept the same as the 1996 number provided by SRI Consulting. The 1997 through 2001 share of
3 total quantity of N20 usage by sector was obtained from communication with a N20 industry expert (Tupman
4 2002). The 2002 and 2003 share of total quantity of N20 usage by sector was obtained from CGA (2002, 2003).
5 Due to unavailable data, the share of total quantity of N20 usage data for 2004 and 2005 was assumed to equal that
6 of 2003. The emissions rate for the food processing propellant industry was obtained from SRI Consulting's
7 Nitrous Oxide, North America report (Heydorn 1997), and confirmed by a N20 industry expert (Tupman 2002).
8 The emissions rate for all other subcategories was obtained from communication with a N20 industry expert
9 (Tupman 2002). The emissions rate for the medical/dental subcategory was substantiated by the Encyclopedia of
10 Chemical Technology (Othmer 1990).
11 Table 5-4: N2Q Production (Gg)
Year Gg
1990 16
2000 17
2001 17
2002 15
2003 15
2004 15
2005 15
12
13 Uncertainty
14 The overall uncertainty associated with the 2005 N20 emission estimate from N20 product usage was calculated
15 using the Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance Tier 2 methodology.
16 Uncertainty associated with the parameters used to estimate N20 emissions included that of production data, total
17 market share of each end use, and the emission factors applied to each end use, respectively.
18 The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 5-5. N20 emissions from N20
19 product usage were estimated to be between 4.1 and 4.5 Tg C02 Eq. at the 95 percent confidence level (or in 19 out
20 of 20 Monte Carlo Stochastic Simulations). This indicates a range of approximately 4 percent below to 4 percent
21 above the 2005 emissions estimate of 4.3 Tg C02 Eq.
22 Table 5-5: Tier 2 Quantitative Uncertainty Estimates for N20 Emissions From N20 Product Usage (Tg C02 Eq. and
23 Percent)
2005 Emission
Uncertainty Range Relative to Emission
Source
Gas
Estimate
Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
N20 Product Usage
N20
4.3
4.1 4.5
-4% +4%
24 a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
25 Recalculations Discussion
26 The N20 production values for 2002, 2003, and 2004 have been updated relative to the previous Inventory based on
27 revised production data presented in CGA (2003). The updated production data resulted in a decrease of 0.5 Tg
28 C02 Eq. (10 percent), respectively, in N20 emissions from nitrous oxide product usage for these years relative to the
29 previous Inventory.
Solvent and Other Product Use 5-3
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Public Review Draft
Planned Improvements
Planned improvements include a continued evaluation of alternative production statistics for cross verification and a
reassessment of subcategory usage to accurately represent the latest trends in the product usage.
5.2. Indirect Greenhouse Gas Emissions from Solvent Use
The use of solvents and other chemical products can result in emissions of various ozone precursors (i.e., indirect
greenhouse gases).1 Non-CH4 volatile organic compounds (NMVOCs), commonly referred to as "hydrocarbons,"
are the primary gases emitted from most processes employing organic or petroleum based solvents. As some of
industrial applications also employ thermal incineration as a control technology, combustion by-products, such as
carbon monoxide (CO) and nitrogen oxides (NOx), are also reported with this source category. In the United States,
emissions from solvents are primarily the result of solvent evaporation, whereby the lighter hydrocarbon molecules
in the solvents escape into the atmosphere. The evaporation process varies depending on different solvent uses and
solvent types. The major categories of solvent uses include: degreasing, graphic arts, surface coating, other
industrial uses of solvents (i.e., electronics, etc.), dry cleaning, and non-industrial uses (i.e., uses of paint thinner,
etc.).
Total emissions of NOx, NMVOCs, and CO from 1990 to 2005 are reported in Table 5-6.
Table 5-6: Emissions of NOx, CO, and NMVOC from Solvent Use (Gg)
Activity
1990
1995
2000
2001
2002
2003
2004
2005
NOx
1
3
3
3
5
5
5
5
Surface Coating
1 I
11 2 111
3
3
5
5
5
5
Degreasing
+ 111
11 + 111
+
+
+
+
+
+
Graphic Arts
+ JIJJ
11 1 1
+
+
+
+
+
+
Dry Cleaning
+ JjJI
11 + 1
+
+
+
+
+
+
Other Industrial Processes3
+ jj|Jj
11 + 1
+
+
+
+
+
+
Non-Industrial Processes'3
+ Jjl
11 + 1
+
+
+
+
+
+
Other
NA
11 + 1
+
+
+
+
+
+
CO
5
11 5 111
46
45
1
1
1
1
Surface Coating
+ Jill
11 1 ill
I :
46
45
1
1
1
1
Degreasing
+ 111
¦ + 11
+
+
+
+
+
+
Graphic Arts
+ jjjj
|| + 111
+
+
+
+
+
+
Dry Cleaning
+ Jll
¦I 1 ill
+
+
+
+
+
+
Other Industrial Processes3
4 1
¦I 3 111
+
+
+
+
+
+
Non-Industrial Processes'3
+ 111
111 + 111
+
+
+
+
+
+
Other
NA
NA
+
+
+
+
+
+
NMVOCs
5,216
5,609
4,384
4,547
3,911
3,916
3,921
3,926
Surface Coating
2,289
2,432
1,767
1,863
1,602
1,604
1,606
1,608
Non-Industrial Processes'3
1,724
1,858
1,676
1,707
1,468
1,470
1,472
1,474
Degreasing
675
716
316
331
285
285
286
286
Dry Cleaning
195
209
265
272
234
234
234
235
Graphic Arts
249
307
222
229
197
197
197
197
Other Industrial Processes3
85
87
98
103
89
89
89
89
Other
+ 111
111 + 1111
40
42
36
36
36
37
1 Includes rubber and plastics manufacturing, and other miscellaneous applications.
1 Solvent usage in the United States also results in the emission of small amounts of hydrofluorocarbons (HFCs) and
hydrofluoroethers (HFEs), which are included under Substitution of Ozone Depleting Substances in the Industrial Processes
chapter.
5-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 b Includes cutback asphalt, pesticide application adhesives, consumer solvents, and other miscellaneous applications.
2 Note: Totals may not sum due to independent rounding.
3 + Does not exceed 0.5 Gg.
4
5 Methodology
6 Emissions were calculated by aggregating solvent use data based on information relating to solvent uses from
7 different applications such as degreasing, graphic arts, etc. Emission factors for each consumption category were
8 then applied to the data to estimate emissions. For example, emissions from surface coatings were mostly due to
9 solvent evaporation as the coatings solidify. By applying the appropriate solvent-specific emission factors to the
10 amount of solvents used for surface coatings, an estimate of emissions was obtained. Emissions of CO and NOx
11 result primarily from thermal and catalytic incineration of solvent-laden gas streams from painting booths, printing
12 operations, and oven exhaust.
13 These emission estimates were obtained from preliminary data (EPA 2006), and disaggregated based on EPA
14 (2003), which, in its final iteration, will be published on the National Emission Inventory (NEI) Air Pollutant
15 Emission Trends web site. Emissions were calculated either for individual categories or for many categories
16 combined, using basic activity data (e.g., the amount of solvent purchased) as an indicator of emissions. National
17 activity data were collected for individual applications from various agencies.
18 Activity data were used in conjunction with emission factors, which together relate the quantity of emissions to the
19 activity. Emission factors are generally available from the EPA's Compilation of Air Pollutant Emission Factors,
20 AP-42 (EPA 1997). The EPA currently derives the overall emission control efficiency of a source category from a
21 variety of information sources, including published reports, the 1985 National Acid Precipitation and Assessment
22 Program emissions inventory, and other EPA data bases.
23 Uncertainty
24 Uncertainties in these estimates are partly due to the accuracy of the emission factors used and the reliability of
25 correlations between activity data and actual emissions.
Solvent and Other Product Use 5-5
-------
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Public Review Draft
6. Agriculture
Agricultural activities contribute directly to emissions of greenhouse gases through a variety of processes. This
chapter provides an assessment of non-carbon-dioxide emissions from the following source categories: enteric
fermentation in domestic livestock, livestock manure management, rice cultivation, agricultural soil management,
and field burning of agricultural residues (see Figure 6-1). Carbon dioxide (C02) emissions and removals from
agriculture-related land-use activities, such as conversion of grassland to cultivated land, are presented in the Land
Use, Land-Use Change, and Forestry chapter. C02 emissions from on-farm energy use are accounted for in the
Energy chapter.
Figure 6-1: 2005 Agriculture Chapter Greenhouse Gas Emission Sources
In 2005, the agricultural sector was responsible for emissions of 536.3 teragrams of C02 equivalent (Tg C02 Eq.),
or 7 percent of total U.S. greenhouse gas emissions. Methane (CH4) and nitrous oxide (N20) were the primary
greenhouse gases emitted by agricultural activities. CH4 emissions from enteric fermentation and manure
management represent about 21 percent and 8 percent of total CH4 emissions from anthropogenic activities,
respectively. Of all domestic animal types, beef and dairy cattle were by far the largest emitters of CH4. Rice
cultivation and field burning of agricultural residues were minor sources of CH4. Agricultural soil management
activities such as fertilizer application and other cropping practices were the largest source of U.S. N20 emissions,
accounting for 78 percent. Manure management and field burning of agricultural residues were also small sources
of N20 emissions.
Table 6-1 and Table 6-2 present emission estimates for the Agriculture sector. Between 1990 and 2005, CH4
emissions from agricultural activities increased by 4 percent, while N20 emissions fluctuated from year to year, but
overall decreased by less than 1 percent. In addition to CH4 and N20, field burning of agricultural residues was also
a minor source of the indirect greenhouse gases carbon monoxide (CO) and nitrogen oxides (NOx).
Table 6-1: Emissions from Agriculture (Tg C02 Eq.)
Gas/Source 1990 1995 2000 2001 2002 2003 2004 2005
164.0 160.5 161.0 161.2 161.1 158.7 161.2
120.(> 113.5 112.5 112.6 113.0 110.5 112.1
35.1 38.7 40.1 41.1 40.5 39.7 41.3
7.<> 7.5 7.6 6.8 6.9 7.6 6.9
0.7 0.8 0.8 0.7 0.8 0.9 0.9
362.7 386.9 399.2 376.2 359.9 348.7 375.1
353.4 376.8 389.0 366.1 350.2 338.8 365.1
9.0 9.6 9.8 9.7 9.3 9.4 9.5
0.4 0.5 0.5 0.4 0.4 0.5 0.5
ch4
154.4I
Enteric Fermentation
115.7
Manure Management
30.9
Rice Cultivation
7.11
Field Burning of Agricultural
0.7
Residues
I
n2o
375.9
Agricultural Soil
366.9
Management
I
Manure Management
8.6
Field Burning of Agricultural
0.4
Residues
I
Total 530.3 526.8 547.4 560.3 537.4 521.1 507.4 536.3
Note: Totals may not sum due to independent rounding.
Table 6-2: Emissions from Agriculture (Gg)
Gas/Source
1990
1995
2000
2001
2002
2003
2004
2005
ch4
7,353
7,811
7,643
7,668
7,678
7,673
7,556
7,674
Enteric Fermentation
5,510
5,744
5,404
5,356
5,361
5,379
5,262
5,340
Manure Management
1,471
1,673
1,844
1,911
1,959
1,928
1,892
1,966
Agriculture 6-1
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
Rice Cultivation 3391
Field Burning of Agricultural 331
Residues
N20 1,213 1,1701
Agricultural Soil 1,184 1,140[
Management
Manure Management 281
Field Burning of Agricultural 1 [
Residues
CO 6911
NO, 281
357
364
325
328
360
328
38
37
34
38
42
41
1,248
1,288
1,213
1,161
1,125
1,210
1,215
1,255
1,181
1,130
1,093
1,178
31
32
31
30
30
31
1
1
1
1
2
2
792
774
709
800
879
858
35
35
33
34
39
39
Note: Totals may not sum due to independent rounding.
6.1. Enteric Fermentation (IPCC Source Category 4A)
CH4 is produced as part of normal digestive processes in animals. During digestion, microbes resident in an
animal's digestive system ferment food consumed by the animal. This microbial fermentation process, referred to
as enteric fermentation, produces CH4 as a by-product, which can be exhaled or eructated by the animal. The
amount of CH4 produced and excreted by an individual animal depends primarily upon the animal's digestive
system, and the amount and type of feed it consumes.
Ruminant animals (e.g., cattle, buffalo, sheep, goats, and camels) are the major emitters of CH4 because of their
unique digestive system. Ruminants possess a rumen, or large "fore-stomach," in which microbial fermentation
breaks down the feed they consume into products that can be absorbed and metabolized. The microbial
fermentation that occurs in the rumen enables them to digest coarse plant material that non-ruminant animals
cannot. Ruminant animals, consequently, have the highest CH4 emissions among all animal types.
Non-ruminant domesticated animals (e.g., swine, horses, and mules) also produce CH4 emissions through enteric
fermentation, although this microbial fermentation occurs in the large intestine. These non-ruminants emit
significantly less CH4 on a per-animal basis than ruminants because the capacity of the large intestine to produce
CH4 is lower.
In addition to the type of digestive system, an animal's feed quality and feed intake also affects CH4 emissions. In
general, lower feed quality or higher feed intake lead to higher CH4 emissions. Feed intake is positively related to
animal size, growth rate, and production (e.g., milk production, wool growth, pregnancy, or work). Therefore, feed
intake varies among animal types as well as among different management practices for individual animal types.
CH4 emission estimates from enteric fermentation are provided in Table 6-3 and Table 6-4. Total livestock CH4
emissions in 2005 were 112.1 Tg C02 Eq. (5,340 gigagrams [Gg]), increasing slightly since 2004 due to minor
increases in most animal populations and dairy cow milk production in all regions. Beef cattle remain the largest
contributor of CH4 emissions from enteric fermentation, accounting for 71 percent in 2005. Emissions from dairy
cattle in 2005 accounted for 25 percent, and the remaining emissions were from horses, sheep, swine, and goats.
From 1990 to 2005, emissions from enteric fermentation have decreased by 3 percent. Generally, emissions have
been decreasing since 1995, mainly due to decreasing populations of both beef and dairy cattle and improved feed
quality for feedlot cattle. During this timeframe, populations of sheep have decreased by an average annual rate of
about 4 percent per year while horse, goat, and swine populations have remained relatively constant.
6-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
Table 6-3: CH4 Emissions from Enteric Fermentation (Tg C02 Eg.)
Livestock Type
1990
1995
2000
2001
2002
2003
2004
2005
Beef Cattle
81.0
87.4
81.3
80.3
80.2
80.5
78.3
79.2
Dairy Cattle
28.9
27.7
27.0
26.9
27.1
27.3
27.0
27.7
Horses
1.9
1.9
2.0
2.0
2.0
2.0
2.0
2.0
Sheep
1.9
1.5
1.2
1.2
1.1
1.1
1.0
1.0
Swine
1.7
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
Total
115.7
120.6
113.5
112.5
112.6
113.0
110.5
112.1
Note: Totals may not sum due to independent rounding.
Table 6-4: CH4 Emissions from Enteric Fermentation (Gg)
Livestock Type
1990
1995
2000
2001
2002
2003
2004
2005
Beef Cattle
3,859
4,160
3,869
3,825
3,821
3,832
3,730
3,772
Dairy Cattle
1,375
1,320
1,283
1,280
1,288
1,299
1,285
1,319
Horses
91
92
94
95
95
95
95
95
Sheep
91
72
56
55
53
51
49
49
Swine
81
88
88
88
90
90
91
91
Goats
13
12
12
12
13
13
13
13
Total
5,510
5,744
5,404
5,356
5,361
5,379
5,262
5,340
Note: Totals may not sum due to independent rounding.
Methodology
Livestock emission estimates fall into two categories: cattle and other domesticated animals. Cattle, due to their
large population, large size, and particular digestive characteristics, account for the majority of CH4 emissions from
livestock in the United States. A more detailed methodology (i.e., IPCC Tier 2) was therefore applied to estimate
emissions for all cattle except for bulls. Emission estimates for other domesticated animals (horses, sheep, swine,
goats, and bulls) were handled using a less detailed approach (i.e., IPCC Tier 1).
While the large diversity of animal management practices cannot be precisely characterized and evaluated,
significant scientific literature exists that describes the quantity of CH4 produced by individual ruminant animals,
particularly cattle. A detailed model that incorporates this information and other analyses of livestock population,
feeding practices and production characteristics was used to estimate emissions from cattle populations.
National cattle population statistics were disaggregated into the following cattle sub-populations:
• Dairy Cattle
o Calves
o Heifer Replacements
o Cows
• Beef Cattle
o Calves
o Heifer Replacements
o Heifer and Steer Stackers
o Animals in Feedlots (Heifers and Steers)
o Cows
o Bulls
Calf birth rates, end of year population statistics, detailed feedlot placement information, and slaughter weight data
were used to model cohorts of individual animal types and their specific emissions profiles. The key variables
tracked for each of the cattle population categories are described in Annex 3.9. These variables include
performance factors such as pregnancy and lactation as well as average weights and weight gain. Annual cattle
Agriculture 6-3
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Public Review Draft
population data were obtained from the U.S. Department of Agriculture's National Agricultural Statistics Service
(1995a,b; 1999a,c,d,f,g; 2000a,c,d,e; 2001a,c,d,f; 2002a,c,d,f; 2003a,c,d,f; 2004a,c,d,f, 2005a-d, 2006a-d).
Diet characteristics were estimated by region for U.S. dairy, beef, and feedlot cattle. These estimates were used to
calculate Digestible Energy (DE) values and CH4 conversion rates (Ym) for each population category. The IPCC
recommends Ym values of 3.5 to 4.5 percent for feedlot cattle and 5.5 to 6.5 percent for other well-fed cattle
consuming temperate-climate feed types. Given the availability of detailed diet information for different regions
and animal types in the United States, DE and Ym values unique to the United States were developed, rather than
using the recommended IPCC values. The diet characterizations and estimation of DE and Ym values were based on
information from state agricultural extension specialists, a review of published forage quality studies, expert
opinion, and modeling of animal physiology. The diet characteristics for dairy cattle were from Donovan (1999),
while those for beef cattle were derived from NRC (2000). DE and Ym for dairy cows were calculated from diet
characteristics using a model simulating ruminant digestion in growing and/or lactating cattle (Donovan and
Baldwin 1999). For feedlot animals, DE and Ym values recommended by Johnson (1999) were used. Values from
EPA (1993) were used for dairy replacement heifers. For grazing beef cattle, DE values were based on diet
information in NRC (2000) and Ym values were based on Johnson (2002). Weight data were estimated from
Feedstuffs (1998), Western Dairyman (1998), and expert opinion. See Annex 3.9 for more details on the method
used to characterize cattle diets in the United States.
To estimate CH4 emissions from cattle, the population was divided into region, age, sub-type (e.g., dairy cows and
replacements, beef cows and replacements, heifer and steer stackers, and heifer and steer in feedlots), and
production (e.g., pregnant, lactating) groupings to more fully capture differences in CH4 emissions from these
animal types. Cattle diet characteristics were used to develop regional emission factors for each sub-category. Tier
2 equations from IPCC (2000) were used to produce CH4 emission factors for the following cattle types: dairy cows,
beef cows, dairy replacements, beef replacements, steer stackers, heifer stackers, steer feedlot animals, and heifer
feedlot animals. To estimate emissions from cattle, population data were multiplied by the emission factor for each
cattle type. More details are provided in Annex 3.9.
Emission estimates for other animal types were based on average emission factors representative of entire
populations of each animal type. CH4 emissions from these animals accounted for a minor portion of total CH4
emissions from livestock in the United States from 1990 through 2005. Also, the variability in emission factors for
each of these other animal types (e.g., variability by age, production system, and feeding practice within each
animal type) is less than that for cattle. Annual livestock population data for these other livestock types, except
horses and goats, as well as feedlot placement information were obtained for all years from the U.S. Department of
Agriculture's National Agricultural Statistics Service (USDA 1994a-b, 1995a,c, 1998a-b, 1999a,b,e,f, 2000a,b,e,f,
2001 a,b,e,f, 2002 a,b,e,f, 2003 a,b,e,f, 2004a,b,e-h, 2005a,d-h, 2006a,d-h). Horse population data were obtained
from the FAOSTAT database (FAO 2006), because USDA does not estimate U.S. horse populations annually. Goat
population data for 1992, 1997, and 2002 were obtained from the Census of Agriculture (USDA 2005i); these data
were interpolated and extrapolated to derive estimates for the other years. Information regarding poultry turnover
(i.e., slaughter) rate was obtained from state Natural Resource Conservation Service personnel (Lange 2000).
Additional population data for different farm size categories for dairy and swine were obtained from the 1992 and
1997 Census of Agriculture (USDA 2005i). CH4 emissions from sheep, goats, swine, and horses were estimated by
using emission factors utilized in Crutzen et al. (1986, cited in IPCC/UNEP/OECD/IEA 1997). These emission
factors are representative of typical animal sizes, feed intakes, and feed characteristics in developed countries. The
methodology is the same as that recommended by IPCC (IPCC/UNEP/OECD/IEA 1997, IPCC 2000).
See Annex 3.9 for more detailed information on the methodology and data used to calculate CH4 emissions from
enteric fermentation.
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 estimates
were developed for the 2001 inventory estimates. No significant changes occurred in the method of data collection,
data estimation methodology, or other factors that influence the uncertainty ranges around the 2005 activity data and
emission factor input variables. Consequently, these uncertainty estimates were directly applied to the 2005
6-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 emission estimates.
2 A total of 185 primary input variables (177 for cattle and 8 for non-cattle) were identified as key input variables for
3 uncertainty analysis. The normal distribution was assumed for almost all activity- and emission factor-related input
4 variables. Triangular distributions were assigned to three input variables (specifically, cow-birth ratios for the three
5 most recent years included in the 2001 model run). For some key input variables, the uncertainty ranges around
6 their estimates (used for inventory estimation) were collected from published documents and other public sources.
7 In addition, both endogenous and exogenous correlations between selected primary input variables were modeled.
8 The exogenous correlation coefficients between the probability distributions of selected activity-related variables
9 were developed as educated estimates.
10 The uncertainty ranges associated with the activity-related input variables were plus or minus 10 percent or lower.
11 However, for many emission factor-related input variables, the lower- and/or the upper-bound uncertainty estimates
12 were over 20 percent. The results of the quantitative uncertainty analysis (Table 6-5) indicate that, on average, the
13 emission estimate range of this source is approximately 99.8 to 132.3 Tg C02 Eq., within the range of
14 approximately 11 percent below and 18 percent above the actual 2005 emission estimate of 112.1 Tg C02 Eq.
15 Among the individual sub-source categories, beef cattle account for the largest amount of CH4 emissions as well as
16 the largest degree of uncertainty in the inventory emission estimates. Consequently, the cattle sub-source categories
17 together contribute to the largest degree of uncertainty in the inventory estimates of CH4 emissions from livestock
18 enteric fermentation. Among non-cattle, horses account for the largest degree of uncertainty in the inventory
19 emission estimates.
20 Table 6-5: Quantitative Uncertainty Estimates for CH4 Emissions from Enteric Fermentation (Tg C02 Eq. and
21 Percent)
2005
Emission
Source
Gas
Estimate
Uncertainty Range Relative to Emission Estimate3'b
(Ts C02 Eq.)
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Enteric Fermentation
ch4
112.1
99.8 132.3 -11% +18%
22 a Range of emissions estimates predicted by Monte Carlo Stochastic Simulation for a 95% confidence interval.
23 b Note that the relative uncertainty range was estimated with respect to the 2001 emission estimates and applied to 2005
24 estimates.
25
26 QA/QC and Verification
27 In order to ensure the quality of the emission estimates from enteric fermentation, the IPCC Tier 1 and Tier 2
28 Quality Assurance/Quality Control (QA/QC) procedures were implemented consistent with the U.S. QA/QC plan.
29 Tier 2 QA procedures included independent peer review of emission estimates. Particular emphasis was placed this
30 year on cattle population and growth data, and on evaluating the effects of data updates as described in the
31 recalculations discussion below.
32 Recalculations Discussion
33 While there were no changes in the methodologies used for estimating CH4 emissions from enteric fermentation,
34 emissions were revised slightly due to changes in data. USDA published revised population estimates which
35 affected historical emissions estimated for swine, sheep, goats, and poultry. Recent historical emission estimates
36 also changed for certain beef and dairy populations as a result USDA inputs and the calving rate described below.
37 The emission factor for bulls has also changed according to IPCC (2006). Previously, the emission factor for bulls
38 was 100 kg CH/hcad/vr. which in the 2006 IPCC Guidelines was changed to 53 kg CH/hcad/vr. This change in
39 the emission factor resulted in an annual 47 percent decrease in emissions from bulls.
Agriculture 6-5
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
Several changes to previously reported emissions occurred due to revisions to population data and a change to the
emissions factor for bulls. Year 2002 total (dairy and beef) cattle CH4 emissions decreased by 2 percent. For 2004,
beef cattle CH4 emissions decreased 2.6 percent while dairy cattle emissions remained relatively constant. The
majority of the change in emissions from beef cattle is a result of the change in emission factor for bulls. The
decreased emission factor in bull emissions from 1990 through 2005 resulted in a decrease in CH4 emissions for
each of those years. In 2004, this change lowered emissions by 100 Gg (2.0 percent of total enteric fermentation
emissions from all animals). Recent historical emission estimates for swine changed (by less than one half of one
percent of respective 2004 emissions) as a result of the USD A revisions described above.
Planned Improvements
Continued research and regular updates are necessary to maintain a current model of cattle diet characterization,
feedlot placement data, rates of weight gain and calving, among other data inputs. While EPA has no plans for
methodological changes in the modeling framework, the opportunity exists to continue to refine the model's results
through identifying and improving individual data inputs. Research is currently underway to differentiate emissions
from "dry" and lactating cows within the model. This improvement to the model would improve inventory
estimates by taking into account the milk production for lactating cows. Other research is currently underway to
identify updates of this nature.
6.2. Manure Management (IPCC Source Category 4B)
The management of livestock manure can produce anthropogenic CH4 and N20 emissions. CH4 is produced by the
anaerobic decomposition of manure. N20 is produced as part of the nitrogen cycle through the nitrification and
denitrification of the organic nitrogen in livestock manure and urine.1
When livestock or poultry manure are stored or treated in systems that promote anaerobic conditions (e.g., as a
liquid/slurry in lagoons, ponds, tanks, or pits), the decomposition of materials in the manure tends to produce CH4.
When manure is handled as a solid (e.g., in stacks or drylots) or deposited on pasture, range, or paddock lands, it
tends to decompose aerobically and produce little or no CH4. Ambient temperature, moisture, and manure storage
or residency time affect the amount of CH4 produced because they influence the growth of the bacteria responsible
for CH4 formation. For non-liquid-based manure systems, moist conditions (which are a function of rainfall and
humidity) can promote CH4 production. Manure composition, which varies by animal diet, growth rate, and type,
including the animal's digestive system, also affects the amount of CH4 produced. In general, the greater the energy
content of the feed, the greater the potential for CH4 emissions. However, some higher energy feeds also are more
digestible than lower quality forages, which can result in less overall waste excreted from the animal.
The production of N20 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 N20 emissions to
occur, the manure must first be handled aerobically where ammonia or organic nitrogen is converted to nitrates and
nitrites (nitrification), and then handled anaerobically where the nitrates and nitrites are reduced to nitrogen gas
(N2), with intermediate production of N20 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 N20 in the waste management system.
1 Emissions from livestock manure and urine deposited on pasture, range, or paddock lands, indirect emissions from volatile
nitrogen losses that occur primarily in the forms of ammonia and NOx, and 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.) are accounted
and discussed in the Agricultural Soil Management source category within the Agriculture sector.
6-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
Public Review Draft
Estimates of CH4 emissions in 2005 were 41.3 Tg C02 Eq. (1,966 Gg), 34 percent higher than in 1990. Emissions
increased on average by 0.7 Tg C02 Eq. (2 percent) annually over this period. The majority of this increase was
from swine and dairy cow manure, where emissions increased 37 and 50 percent, respectively. Although the
majority of manure in the United States is handled as a solid, producing little CH4, the general trend in manure
management, particularly for dairy and swine (which are both shifting towards larger facilities), is one of increasing
use of liquid systems. Also, new regulations limiting the application of manure nutrients have shifted manure
management practices at smaller dairies from daily spread to manure managed and stored on site. Although national
dairy animal populations have been generally decreasing, some states have seen increases in their dairy populations
as the industry becomes more concentrated in certain areas of the country. These areas of concentration, such as
California, New Mexico, and Idaho, tend to utilize more liquid-based systems to manage (flush or scrape) and store
manure. Thus the shift toward larger facilities is translated into an increasing use of liquid manure management
systems, which have higher potential CH4 emissions than dry systems. This shift was accounted for by
incorporating state-specific weighted CH4 conversion factor (MCF) values in combination with the 1992, 1997, and
2002 farm-size distribution data reported in the Census of Agriculture (USDA 2005e). From 2004 to 2005, there
was a 4 percent increase in CH4 emissions, due to minor shifts in the animal populations and the resultant effects on
manure management system allocations.
In 2005, total N20 emissions were estimated to be 9.5 Tg C02 Eq. (31 Gg); in 1990, emissions were 8.6 Tg C02 Eq.
(28 Gg). Emissions increased on average by 0.06 Tg C02 Eq. (0.7 percent) annually over this period, driven by
beef cattle. The 10 percent increase in N20 emissions from 1990 to 2005 can be partially attributed to a shift in the
poultry industry away from the use of liquid manure management systems in favor of litter-based systems and high-
rise houses. In addition, there was an overall increase in the population of poultry and swine from 1990 to 2005,
although swine populations periodically declined slightly throughout the time series. N20 emissions showed a 0.9
percent increase from 2004 through 2005, due to minor shifts in animal populations.
The population of beef cattle in feedlots increased over the period of 1990 to 2005, resulting in increased N20
emissions from this sub-category of cattle. N20 emissions from dairy cattle increased slightly over the period 1990
through 2005, a net result of different emission trends for dairy cows and dairy heifers. Although dairy cow
populations decreased overall for the period 1990 through 2005, the population of dairy cows increased at dairies
that manage and store manure on-site (as opposed to using pasture, range, or paddock or daily spread systems). The
shift at dairies to more liquid manure management systems at large operations resulted in lower N20 emissions for
dairy cows. This trend differed from the increasing dairy heifer N20 emissions from dairy heifers, whose
populations were increasingly managed in drylot systems.
Table 6-6and Table 1-6-7 provide estimates of CH4 and N20 emissions from manure management by animal
category.
Table 6-6: CH4 and N2Q Emissions from Manure Management (Tg C02 Eq.)
Gas/Animal Type
1990
1995
2000
2001
2002
2003
2004
2005
ch4
30.9
35.1
38.7
40.1
41.1
40.5
39.7
41.3
Dairy Cattle
11.9
13.3
15.7
16.6
17.2
17.6
17.1
17.9
Beef Cattle
2.5
2.6
2.4
2.5
2.4
2.4
2.3
2.3
Swine
13.1
16.0
17.4
17.8
18.3
17.2
17.1
17.9
Sheep
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
Goats
+
+
+
+
+
+
+
+
Poultry
2.7
2.7
2.6
2.7
2.7
2.7
2.6
2.6
Horses
0.5
0.4
0.5
0.5
0.5
0.5
0.5
0.5
n2o
8.6
9.0
9.6
9.8
9.7
9.3
9.4
9.5
Dairy Cattle
2.4
2.4
2.5
2.5
2.5
2.5
2.5
2.5
Beef Cattle
4.9
5.3
5.9
6.1
6.0
5.6
5.7
5.8
Swine
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
Sheep
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1
Goats
+
+
+
+
+
+
+
+
Poultry
0.5
0.4
0.4
0.4
0.4
0.4
0.4
0.4
Horses
0.2
o.:
0.2
0.2
0.2
0.2
0.2
0.2
Agriculture 6-7
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
Total
39.5
44.1
48.3
50.0
50.8
49.8
49.2
50.8
+ Does not exceed 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 1-6-7: CH4 and N20 Emissions from Manure Management (Gg)
Gas/Animal Type
1990
1995
2000
2001
2002
2003
2004
2005
ch4
1,471
1,673
1,844
1,911
1,959
1,928
1,892
1,966
Dairy Cattle
568
634
748
789
818
839
814
851
Beef Cattle
120
122
114
117
114
113
110
111
Swine
623
762
830
849
873
821
815
852
Sheep
7
5
4
4
4
4
4
4
Goats
1
1
1
1
1
1
1
1
Poultry
131
128
125
129
127
127
126
125
Horses
22
21
22
22
22
22
22
22
n2o
28
29
31
32
31
30
30
31
Dairy Cattle
8
8
8
8
8
8
8
8
Beef Cattle
16
17
19
20
19
18
19
19
Swine
2
2
2
1
2
2
2
2
Sheep
0
0
0
0
0
0
0
0
Goats
0
0
0
0
0
0
0
0
Poultry
1
1
1
1
1
1
1
1
Horses
1
1
1
1
1
1
1
1
+ Does not exceed 0.5 Gg.
Note: Totals may not sum due to independent rounding.
Methodology
The methodologies presented in IPCC (2006) form the basis of the CH4 and N20 emission estimates for each animal
type. The calculation of emissions requires the following information:
• Animal population data (by animal type and state);
• Amount of nitrogen produced (excretion rate by animal type times animal population);
• Amount of volatile solids produced (excretion rate by animal type times animal population);
• CH4 producing potential of the volatile solids (by animal type);
• Extent to which the CH4 producing potential is realized for each type of manure management system (by
state and manure management system, including the impacts of any biogas collection efforts);
• Portion of manure managed in each manure management system (by state and animal type); and
• Portion of manure deposited on pasture, range, or paddock or used in daily spread systems.
This section presents a summary of the methodologies used to estimate CH4 and N20 emissions from manure
management for this inventory. See Annex 3.10 for more detailed information on the methodology and data used to
calculate CH4 and N20 emissions from manure management.
Both CH4 and N20 emissions were estimated by first determining activity data, including animal population, waste
characteristics, and manure management system usage. For swine and dairy cattle, manure management system
usage was determined for different farm size categories using data from USD A (USD A 1996b, 1998c, 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 N20 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 in the system
6-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 from month to month due to long storage times exhibited by anaerobic lagoon systems, and a factor to account for
2 management and design practices that result in the loss of volatile solids from lagoon systems. N20 emission
3 factors for all systems were set equal to default IPCC factors (IPCC 2006).
4 CH4 emissions were estimated using the volatile solids (VS) production for all livestock. For most cattle groups,
5 regional animal-specific VS production rates that are related to the diet of the animal for each year of the inventory
6 were used (Pederson and Pape 2006). For all other animal groups, VS production was calculated using a national
7 average VS production rate from the Agricultural Waste Management Field Handbook (USD A 1996a), which was
8 then multiplied by the average weight of the animal and the state-specific animal population. The resulting VS for
9 each animal group were then multiplied by the maximum CH4 producing capacity of the waste (B0) and the state-
10 specific MCFs.
11 The maximum CH4 producing capacity of the VS, or B0, was determined based on data collected in a literature
12 review (ERG 2000b). B0 data were collected for each animal type for which emissions were estimated.
13 Anaerobic digester reductions are estimated based on data from the EPA AgSTAR program, including information
14 presented in the AgSTAR Digest (EPA 2000, 2003b, 2006). A destruction efficiency of 99 percent was applied to
15 CH4 recovered to estimate CH4 emissions from digesters. The value for efficiency was selected based on the range
16 of efficiencies (98 to 100 percent) recommended for flares in EPA's "AP-42 Compilation of Air Pollutant Emission
17 Factors, Chapter 2.4," efficiencies used to establish new source performance standards (NSPS) for landfills, and in
18 recommendations for closed flares used in LMOP.
19 Nitrogen excretion rate data from the USD A Agricultural Waste Management Field Handbook (USD A 1996a) were
20 used for all livestock except sheep, goats, and horses. Data from the American Society of Agricultural Engineers
21 (ASAE 1999) were used for these animal types. VS excretion rate data from USD A (1996a) were used for swine,
22 poultry, bulls, and calves not on feed.
23 N20 emissions were estimated by determining total Kjeldahl nitrogen (TKN)^ production for all livestock wastes
24 using a national average nitrogen excretion rate for each animal group from USD A (1996a), which was then
25 multiplied by the average weight of the animal and the state-specific animal population. State-specific weighted
26 N20 emission factors specific to the type of manure management system were then applied to total nitrogen
27 production to estimate N20 emissions.
28 Uncertainty
29 An analysis was conducted for the manure management emission estimates presented in EPA's Inventory of U.S.
30 Greenhouse Gas Emissions and Sinks: 1990-2001 (EPA 2003a, ERG 2003) to determine the uncertainty associated
31 with estimating CH4 and N20 emissions from livestock manure management. Because no substantial modifications
32 were made to the inventory methodology since the development of these estimates, it is expected that this analysis is
33 applicable to the uncertainty associated with the current manure management emission estimates.
34 The quantitative uncertainty analysis for this source category was performed through the IPCC-recommended Tier 2
35 uncertainty estimation methodology, the Monte Carlo Stochastic Simulation technique. The uncertainty analysis
36 was developed based on the methods used to estimate CH4 and N20 emissions from manure management systems.
37 A normal probability distribution was assumed for each source data category. The series of equations used were
38 condensed into a single equation for each animal type and state. The equations for each animal group contained
39 four to five variables around which the uncertainty analysis was performed for each state.
40 The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 1-6-8. Manure management CH4
2 Total Kjeldahl nitrogen is a measure of organically bound nitrogen and ammonia nitrogen.
Agriculture 6-9
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Public Review Draft
emissions in 2005 were estimated to be between 33.8 and 49.5 Tg C02 Eq. at a 95 percent confidence level, which
indicates a range of 18 percent below to 20 percent above the actual 2005 emission estimate of 41.3 Tg C02 Eq. At
the 95 percent confidence level, N20 emissions were estimated to be between 8.0 and 11.8 Tg C02 Eq. (or
approximately 16 percent below and 24 percent above the actual 2005 emission estimate of 9.5 Tg C02 Eq.).
Table 1-6-8: Tier 2 Quantitative Uncertainty Estimates for CH4 and N20 Emissions from Manure Management (Tg
2005 Emission
Uncertainty Range Relative to Emission
Source
Gas
Estimate
Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower
Bound
Upper
Bound
Manure Management
ch4
41.3
33.8 49.5
-18%
+20%
Manure Management
n2o
9.5
8.0 11.8
-16%
+24%
aRange of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
QA/QC and Verification
Tier 1 and Tier 2 QA/QC activities were conducted consistent with the U.S. QA/QC plan. Tier 2 activities focused
on comparing estimates for the 2004 and 2005 Inventories for N20 emissions from managed systems and CH4
emissions from livestock manure. All errors identified were corrected. Order of magnitude checks were also
conducted, and corrections made where needed. Manure nitrogen data were 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 waste management system type for the full time series, between national level estimates for
nitrogen excreted and the sum of county estimates for the full time series.
Recalculations Discussion
A few changes have been incorporated into the overall methodology for the manure management emission
estimates. State temperatures are now calculated using data from every county in the state. The previous
methodology linked the temperature data to a list of counties/climate divisions that were determined using a weather
station list from the National Climatic Data Center (NCDC). The list of weather stations, however, did not include a
match of county to climate division for all U.S. counties. The new methodology for utilizing the temperature data
for the contiguous United States is to link the temperature data by climate division to a complete list of U.S.
counties/climate divisions (NOAA 2005). Although this change in methodology provides a more accurate
calculation of state temperatures, it has little effect on the final temperature calculations, MCFs, or emissions
estimates.
Another major change in methodology was using climate-specific MCFs for dry manure management systems. In
previous inventories, a "temperate" climate zone was assumed for all U.S. states and years of the inventory, and the
temperate MCFs for all dry manure management systems were used in methane emission calculations. A climate
classification (cool, temperate, or warm) was assigned to each state and year using the average state temperatures.
New climate-specific MCFs were incorporated into the current inventory for the following manure management
systems: pasture/range/paddock, daily spread, solid storage, dry lot, burned for fuel, cattle deep bedding (<1 month
and >1 month), composting - intensive windrow, and composting - passive windrow. The change in status for
some states from temperate to cool climates and MCFs caused the most significant changes in methane emissions
for animal groups that most rely on pasture/range/paddock waste management systems (i.e., beef cattle, sheep,
horses, and goats), which showed decreased CH4 emissions for all years in the current inventory compared to the
previous inventory.
The percentage of dairy cattle, swine, and sheep on each type of manure management system was also updated for
the 2005 inventory, based on farm size data from the 2002 USDA Census of Agriculture. Liquid-based systems are
in increasing use for swine and dairy manure, due to the increasing farm size for these animals. Sheep continue to
be managed using dry manure management systems. These manure management system updates decreased N20
6-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 estimates and increased CH4 estimates for dairy cattle and increased N20 and CH4 estimates for swine in the current
2 inventory.
3 Changes were also made to the current calculations involving animal population data. Animal population data were
4 updated to reflect the final estimates reports from USDA NASS, and 2002 USDA Census of Agriculture data
5 (USDA 1994a-b, 1995a-b, 1998a-b, 1999a-c, 2000a, 2004a-e, 2005a-d, 2006a-e). The population data in the most
6 recent final estimates reflect some adjustments due to USDA NASS review. For horses, state-level populations
7 were estimated using the national FAO population data (FAO 2006) and the state distributions from the 1992, 1997,
8 and 2002 Census of Agriculture (USDA 2005e).
9 For the current inventory, new VS production and nitrogen excretion rates were calculated for poultry hens and
10 pullets, based on 1990 to 2004 population and VS data and nitrogen excretion data. This change was incorporated
11 because USDA now reports a combined hen and pullet population, therefore weighted average rates for the
12 combined population were developed.
13 With these recalculations, CH4 emission estimates from manure management systems are slightly higher than
14 reported in the previous inventory for the years 1999 through 2004 and slightly lower for 1990 through 1998. On
15 average, annual emissions estimates are less than those of the previous inventory by less than one percent.
16 N20 emission estimates from manure management systems have decreased for all years of the current inventory
17 compared to the previous inventory, by 47 percent on average, due to the use of updated emission factors published
18 by IPCC (2006).
19 Planned Improvements
20 Although an effort was made to introduce the variability in VS production due to differences in diet for beef and
21 dairy cows, heifers, and steer, further research is needed to confirm and track diet changes over time. A
22 methodology to assess variability in swine VS production would be useful in future inventory estimates.
23 Research will be initiated into the estimation and validation of the maximum CH4-producing capacity of animal
24 manure (B0), for the purpose of obtaining more accurate data to develop emission estimates.
25 The American Society of Agricultural Engineers proposed new standards for manure production characteristics in
26 2004 and finalized them in 2005. These data will be investigated and evaluated for incorporation into future
27 estimates.
28 The methodology to calculate MCFs for liquid systems will be examined to determine how to account for a
29 maximum temperature in the liquid systems. It will also be evaluated whether the lower bound estimate of
30 temperature established for lagoons and other liquid systems should be revised for use with this methodology.
31 Additionally, available research will be investigated to develop a relationship between ambient air temperature and
32 temperature in liquid waste management systems in order to improve that relationship in the MCF methodology.
33 The development of the National Ammonia Emissions Inventory for the United States (EPA 2004) used similar data
34 sources to the current estimates of emissions from manure management, and through the course of development of
35 the ammonia inventory, updated waste management distribution data were identified. Future inventory estimates
36 will incorporate these updated data.
37 The estimation of indirect N20 emissions associated with manure management (e.g., ammonia NOx) is currently
38 included in the Agricultural Soil Management source category. Based on IPCC (2006), a methodology to estimate
39 these indirect N20 emissions separately and include them in the Manure Management source category will be
40 evaluated for future inventories.
41 The IPCC provides a suggested MCF for poultry waste management operations of 1.5 percent. Additional study is
42 needed in this area to determine if poultry high-rise houses promote sufficient aerobic conditions to warrant a lower
43 MCF.
Agriculture 6-11
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Public Review Draft
A minor error was identified in the MCF calculations, which used a value of 303.17 K instead of 303.15 K when
calculating the f factor. This error will be corrected in future inventory estimates. This error has little impact
overall on the CH4 emission estimates. The calculated MCFs are expected to increase up to 0.1 percent, and the
overall CH4 emissions are expected to increase by up to 0.05 percent.
6.3. Rice Cultivation (IPCC Source Category 4C)
Most of the world's rice, and all rice in the United States, is grown on flooded fields. When fields are flooded,
aerobic decomposition of organic material gradually depletes most of the oxygen present in the soil, causing
anaerobic soil conditions. Once the environment becomes anaerobic, CH4 is produced through anaerobic
decomposition of soil organic matter by methanogenic bacteria. As much as 60 to 90 percent of the CH4 produced
is oxidized by aerobic methanotrophic bacteria in the soil (some oxygen remains at the interfaces of soil and water,
and soil and root system) (Holzapfel-Pschorn et al. 1985, Sass et al. 1990). Some of the CH4 is also leached away
as dissolved CH4 in floodwater that percolates from the field. The remaining un-oxidized CH4 is transported from
the submerged soil to the atmosphere primarily by diffusive transport through the rice plants. Minor amounts of
CH4 also escape from the soil via diffusion and bubbling through floodwaters.
The water management system under which rice is grown is one of the most important factors affecting CH4
emissions. Upland rice fields are not flooded, and therefore are not believed to produce CH4. In deepwater rice
fields (i.e., fields with flooding depths greater than one meter), the lower stems and roots of the rice plants are dead,
so the primary CH4 transport pathway to the atmosphere is blocked. The quantities of CH4 released from deepwater
fields, therefore, are believed to be significantly less than the quantities released from areas with shallower flooding
depths. Some flooded fields are drained periodically during the growing season, either intentionally or accidentally.
If water is drained and soils are allowed to dry sufficiently, CH4 emissions decrease or stop entirely. This is due to
soil aeration, which not only causes existing soil CH4 to oxidize but also inhibits further CH4 production in soils.
All rice in the United States is grown under continuously flooded conditions; none is grown under deepwater
conditions. Mid-season drainage does not occur except by accident (e.g., due to levee breach).
Other factors that influence CH4 emissions from flooded rice fields include fertilization practices (especially the use
of organic fertilizers), soil temperature, soil type, rice variety, and cultivation practices (e.g., tillage, seeding, and
weeding practices). The factors that determine the amount of organic material available to decompose (i.e., organic
fertilizer use, soil type, rice variety,3 and cultivation practices) are the most important variables influencing the
amount of CH4 emitted over the growing season; the total amount of CH4 released depends primarily on the amount
of organic substrate available. Soil temperature is known to be an important factor regulating the activity of
methanogenic bacteria, and therefore the rate of CH4 production. However, although temperature controls the
amount of time it takes to convert a given amount of organic material to CH4, that time is short relative to a growing
season, so the dependence of total emissions over an entire growing season on soil temperature is weak. The
application of synthetic fertilizers has also been found to influence CH4 emissions; in particular, both nitrate and
sulfate fertilizers (e.g., ammonium nitrate and ammonium sulfate) appear to inhibit CH4 formation.
Rice is cultivated in eight states: Arkansas, California, Florida, Louisiana, Mississippi, Missouri, Oklahoma, and
Texas.4 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.
3 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.
4 Additionally, 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.
6-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Public Review Draft
CH4 emissions from ratoon crops have been found to be considerably higher than those from the primary crop. This
second rice crop is produced from regrowth of the stubble after the first crop has been harvested. Because the first
crop's stubble is left behind in ratooned fields, and there is no time delay between cropping seasons (which would
allow the stubble to decay aerobically), the amount of organic material that is available for anaerobic decomposition
is considerably higher than with the first (i.e., primary) crop.
Rice cultivation is a small source of CH4 in the United States (Table 6-9 and Table 6-10). In 2005, CH4 emissions
from rice cultivation were 6.9 Tg C02 Eq. (328 Gg). Although annual emissions fluctuated unevenly between the
years 1990 and 2005, ranging from an annual decrease of 11 percent to an annual increase of 17 percent, there was
an overall decrease of 3 percent over the fifteen-year period, due to an overall decrease in primary crop area.5 The
factors that affect the rice acreage in any year vary from state to state, although the price of rice relative to
competing crops is the primary controlling variable in most states.
Table 6-9: CH4 Emissions from Rice Cultivation (Tg C02 Eq.)
State
1990
1995
2000
2001
2002
2003
2004
2005
Primary
5.1
5.6
5.5
5.9
5.7
5.4
6.0
6.0
Arkansas
2.1
2.4
2.5
2.9
2.7
2.6
2.8
2.9
California
0.7
0.8
1.0
0.8
0.9
0.9
1.1
0.9
Florida
+mlm
0.0
+
+
+
+
+
+
Louisiana
1.0
1.0
0.9
1.0
1.0
0.8
1.0
0.9
Mississippi
0.4
0.5
0.4
0.5
0.5
0.4
0.4
0.5
Missouri
0.1
0.2
0.3
0.4
0.3
0.3
0.3
0.4
Oklahoma
0.0
+
+
+
+
+
+
Texas
0.6
0.6
0.4
0.4
0.4
0.3
0.4
0.4
Ratoon
2.1
2.1
2.0
1.7
1.1
1.5
1.6
0.9
Arkansas
+BB
0.0
+
+
+
+
+
+
Florida
0.1
0.1
+
+
+
+
+
Louisiana
ill
1.1
1.3
1.1
0.5
1.0
1.1
0.5
Texas
0.9
0.8
0.7
0.6
0.5
0.5
0.5
0.4
Total
7.1
7.<>
7.5
7.6
6.8
6.9
7.6
6.9
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 6-10: CH4 Emissions from Rice Cultivation (Gg)
State
1990
1995
Primary
241
265
Arkansas
102
114
California
34
40
Florida
il
2
Louisiana
46
48
Mississippi
21
24
Missouri
7l
10
Oklahoma
+
Texas
30
27
Ratoon
98
98
Arkansas
+
Florida
2I
4
Louisiana
52
54
2000
2001
2002
2003
2004
2005
260
283
274
255
283
287
120
138
128
124
132
139
47
40
45
43
50
45
2
1
1
+
1
1
41
46
45
38
45
45
19
22
22
20
20
22
14
18
15
15
17
18
+
+
+
+
+
+
18
18
18
15
19
17
97
81
52
73
77
41
+
+
+
+
+
1
2
2
2
2
2
2
61
52
25
50
50
22
5 The 11 percent decrease occurred between 1992 and 1993 and 2001 and 2002; the 17 percent increase happened between 1993
and 1994.
Agriculture 6-13
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
Texas
45
40
34
27
24
22
24
17
Total
339
363
357
364
325
328
360
328
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
Methodology
The IPCC/UNEP/OECD/IEA (1997) recommends using harvested rice areas and area-based seasonally integrated
emission factors (i.e., amount of CH4 emitted over a growing season per unit harvested area) to estimate annual CH4
emissions from rice cultivation. This Inventory uses the recommended methodology and employs U.S.-specific
emission factors derived from rice field measurements. Seasonal emissions have been found to be much higher for
ratooned crops than for primary crops, so emissions from ratooned and primary areas are estimated separately using
emission factors that are representative of the particular growing season. This approach is consistent with IPCC
Good Practice Guidance (IPCC 2000).
The harvested rice areas for the primary and ratoon crops in each state are presented in Table 6-11. Primary crop
areas for 1990 through 2005 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, 2006). 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; and Gaston
Cantens (2004, 2005), Vice President of Corporate Relations of the Florida Crystals Company. Harvested rice area
in Florida for 2005 was unavailable and set equal to the 2004 figure (Kirstein 2006, Cantens 2005). Harvested rice
areas for Oklahoma, which also are not reported by USDA, were obtained from Danny Lee of the Oklahoma Farm
Services Agency (2003, 2004, 2005, 2006). 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, and 2005, when
the ratooned area was less than 1 percent of the primary area (Slaton 1999, 2000, 2001a; Wilson 2002, 2003, 2004,
2005, 2006). In Florida, the ratooned area was 50 percent of the primary area from 1990 to 1998 (Schueneman
1999a), about 65 percent of the primary area in 1999 (Schueneman 2000), around 41 percent of the primary area in
2000 (Schueneman 2001a), about 60 percent of the primary area in 2001 (Deren 2002), about 54 percent of the
primary area in 2002 (Kirstein 2003), about 100 percent of the primary area in 2003 (Kirstein 2004), and about 77
percent of the primary area in 2004 (Cantens 2005). Ratooned area for 2005 was set equal to 2004, since no new
data were available. 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, and dropped to 13 percent
in 2005 (Linscombe 1999, 2001a, 2002, 2003, 2004, 2005, 2006; 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, and 27 percent in 2005 (Klosterboer 1999, 2000, 2001a, 2002, 2003; Stansel 2004, 2005;
Texas Agricultural Experiment Station 2006). California, Mississippi, Missouri, and Oklahoma have not ratooned
rice over the period 1990-2005 (Guethle 1999, 2000, 2001a, 2002, 2003, 2004, 2005, 2006; Lee 2003, 2004, 2005,
2006; Mutters 2002, 2003, 2004, 2005; Street 1999, 2000, 2001a, 2002, 2003; Walker 2005).
Table 6-11: Rice Areas Harvested (Hectares)
State/Crop
1990
1995
2000
2001
2002
2003
2004
2005
Arkansas
Primary
485,633
542,291
570,619
656,010
608,256
588,830
629,300
661,675
Ratoon*
oil
0
0
0
0
0
0
662
California
159,854
188,183
221,773
190,611
213,679
205,180
238,770
212,869
Florida
Primary
4,978
9,713
7,801
4,562
5,077
2,369
3,755
3,755
Ratoon
2,489
4,856
3,193
2,752
2,734
2,369
2,899
2,899
Louisiana
Primary
220,558
230,676
1 194,253
220,963
216,512
182,113
215,702
212,465
6-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
Ratoon
66,168
69,203
77,701
66,289
32,477
63,739
64,711
27,620
Mississippi
101,174
116,552
88,223
102,388
102,388
94,699
94,699
106,435
Missouri
32,376
45,326
68,393
83,772
73,654
69,203
78,915
86,605
Oklahoma
617
364
283
265
274
53
158
271
Texas
Primary
142,857
128,693
86,605
87,414
83,367
72,845
88,223
81,344
Ratoon
57,143
51,477
43,302
34,966
30,846
27,681
30,878
21,963
Total Primary
1,148,047
1,261,7961
1,237,951 1,345,984 1,303,206 1,215,291 1,349,523 1,365,418
Total Ratoon
125,799
125,5361
124,197
104,006
66,056
93,790
98,488
53,144
Total
1,273,847
1,387,3331
1,362,148 1,449,991 1,369,262 1,309,081 1,448,011 1,418,562
* Arkansas ratooning occurred only in 1998,1999, and 2005.
Note: Totals may not sum due to independent rounding.
To determine what seasonal CH4 emission factors should be used for the primary and ratoon crops, CH4 flux
information from rice field measurements in the United States was collected. Experiments which involved atypical
or nonrepresentative management practices (e.g., the application of nitrate or sulfate fertilizers, or other substances
believed to suppress CH4 formation), as well as experiments in which measurements were not made over an entire
flooding season or floodwaters were drained mid-season, were excluded from the analysis. The remaining
experimental results6 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/hcctarc-
season, and the resultant emission factor for the ratoon crop is 780 kg CH 4/hcctarc-scason.
Uncertainty
The largest uncertainty in the calculation of CH4 emissions from rice cultivation is associated with the emission
factors. Seasonal emissions, derived from field measurements in the United States, vary by more than one order of
magnitude. This inherent variability is due to differences in cultivation practices, in particular, fertilizer type,
amount, and mode of application; differences in cultivar type; and differences in soil and climatic conditions. A
portion of this variability is accounted for by separating primary from ratooned areas. However, even within a
cropping season or a given management regime, measured emissions may vary significantly. Of the experiments
used to derive the emission factors applied here, primary emissions ranged from 22 to 479 kg CH 4/hcctarc-scason
and ratoon emissions ranged from 481 to 1,490 kg CH4/hectare-season. The uncertainty distributions around the
primary and ratoon emission factors were derived using the distributions of the relevant primary or ratoon emission
factors available in the literature and described above. Variability about the rice emission factor means was not
normally distributed for either primary or ratooned crops, but rather skewed, with a tail trailing to the right of the
mean. A lognormal statistical distribution was, therefore, applied in the Tier 2 Monte Carlo analysis.
Other sources of uncertainty include the primary rice-cropped area for each state, percent of rice-cropped area that
is rationed, and the extent to which flooding outside of the normal rice season is practiced. Expert judgment was
used to estimate the uncertainty associated with primary rice-cropped area for each state at 1 to 5 percent, and a
normal distribution was assumed. Uncertainties were applied to ratooned area by state, based on the level of
reporting performed by the state. No uncertainties were calculated for the practice of flooding outside of the normal
rice season because CH4 flux measurements have not been undertaken over a sufficient geographic range or under a
6 In some of these remaining experiments, measurements from individual plots were excluded from the analysis because of the
aforementioned reasons. In addition, one measurement from the ratooned fields (i.e., the flux of 2.041 g/m2/day in Lindau and
Bollich 1993) was excluded, because this emission rate is unusually high compared to other flux measurements in the United
States, as well as in Europe and Asia (IPCC/UNEP/OECD/IEA 1997).
Agriculture 6-15
-------
Public Review Draft
1 broad enough range of representative conditions to account for this source in the emission estimates or its associated
2 uncertainty.
3 To quantify the uncertainties for emissions from rice cultivation, a Monte Carlo (Tier 2) uncertainty analysis was
4 performed using the information provided above. The results of the Tier 2 quantitative uncertainty analysis are
5 summarized in Table 6-12. Rice cultivation CH4 emissions in 2005 were estimated to be between 2.1 and 18.6 Tg
6 C02 Eq. at a 95 percent confidence level, which indicates a range of 70 percent below to 170 percent above the
7 actual 2005 emission estimate of 6.9 Tg C02 Eq.
8 Table 6-12: Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Rice Cultivation (Tg C02 Eq. and
9 Percent)
2005 Emission
Source
Gas
Estimate
(T2 C02 Eq.)
Uncertainty Range Relative to Emission Estimate"
(T2 C02 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Rice Cultivation
ch4
6.9
2.1 18.6 -70% +170%
10 aRange of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
11
12 QA/QC and Verification
13 A source-specific QA/QC plan for rice cultivation was developed and implemented. This effort included a Tier 1
14 analysis, as well as portions of a Tier 2 analysis. The Tier 2 procedures focused on comparing trends across years,
15 states, and cropping seasons to attempt to identify any outliers or inconsistencies. No problems were found.
16 Recalculations Discussion
17 An error in the spreadsheets used to calculate emissions estimates was found during the development of the current
18 inventory and corrected, resulting in a 0.06 percent decrease in the 2004 emission estimates.
19 6.4. Agricultural Soil Management (IPCC Source Category 4D)
20 Nitrous oxide is produced naturally in soils through the microbial processes of nitrification and denitrification.7 A
21 number of agricultural activities increase mineral nitrogen (N) availability in soils, thereby increasing the amount
22 available for nitrification and denitrification, and ultimately the amount of N20 emitted. These activities increase
23 soil mineral N either directly or indirectly (see Figure 6-2). Direct increases occur through a variety of management
24 practices that add or lead to greater release of mineral N in the soil, including: fertilization; application of managed
25 livestock manure and other organic materials such as sewage sludge; deposition of manure on soils by domesticated
26 animals in pastures, rangelands, and paddocks (PRP) (i.e., by grazing animals and other animals whose manure is
27 not managed); production of N-fixing crops and forages; retention of crop residues; and cultivation of organic soils
28 (i.e., soils with a high organic matter content, otherwise known as histosols).8 Other agricultural soil management
29 activities, including irrigation, drainage, tillage practices, and fallowing of land, can influence N mineralization in
30 soils and thereby affect direct emissions. Mineral N is also made available in soils through decomposition of soil
7 Nitrification and denitrification are driven by the activity of microorganisms in soils. Nitrification is the aerobic microbial
oxidation of ammonium (NH4) to nitrate (N03), and denitrification is the anaerobic microbial reduction of nitrate to nitrogen gas
(N2)- Nitrous oxide is a gaseous intermediate product in the reaction sequence of denitrification, which leaks from microbial
cells into the soil and then into the atmosphere. Nitrous oxide is also produced during nitrification, although by a less well-
understood mechanism (Nevison 2000).
8 Drainage and cultivation of organic soils in former wetlands enhances mineralization of N-rich organic matter, thereby
enhancing N20 emissions from these soils.
6-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Public Review Draft
organic matter and plant litter, as well as asymbiotic fixation of N from the atmosphere.9 Indirect emissions of N20
occur through two pathways: (1) volatilization and subsequent atmospheric deposition of applied N,10 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. In contrast, indirect N20
emissions from all sources (agriculture, forest lands, settlements, and managed manure) are reported in this chapter.
Figure 6-2: Agricultural Sources and Pathways of N that Result in N20 Emissions
Agricultural soils produce the majority of N20 emissions in the United States. Estimated emissions from this source
in 2005 were 365.1 Tg C02 Eq. (1,178 Gg N20) (see Table 6-13 and Table 6-14). Annual agricultural soil
management N20 emissions fluctuated between 1990 and 2005, although overall emissions were 0.5 percent lower
in 2005 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 75 percent of total
direct emissions, while grassland accounted for approximately 25 percent.
Table 6-13: N2Q Emissions from Agricultural Soils (Tg C02 Eq.)
Activity
Direct
Cropland
Grassland
Indirect (All Land-Use Types)
Cropland
Grassland
Managed Manure3
Forest Land
Settlements
Total
366.9
2000
2001
2002
2003
2004
2005
324.4
327.4
314.1
297.4
292.1
310.5
250.5
252.6
234.0
226.4
220.9
234.2
73.9
74.8
80.1
71.0
71.3
76.4
52.4
61.6
52.0
52.8
46.6
54.6
25.0
26.1
22.5
25.7
20.1
26.2
17.1
25.1
18.9
16.5
16.0
17.8
8.4
8.5
8.7
8.5
8.5
8.5
0.1
0.1
0.1
0.1
0.1
0.1
1.8
1.8
1.9
1.9
2.0
1.9
376.8 389.0 366.1 350.2 338.8 365.1
+ Less than 0.05 Tg C02 Eq.
a Accounts for loss of manure N prior to soil application during transport, treatment, and storage, including both volatilization
and leaching/runoff.
Table 6-14: N2Q Emissions from Agricultural Soils (Gg N2Q)
Activity W90 1995 2000 2001 2002 2003 2004 2005
Direct 1,000 942 1,046 1,056 1,013 959 942 1,002
Cropland 716 691 808 815 755 730 712 755
Grassland 284 251 238 241 259 229 230 246
Indirect (All Land-Use Types) 183 198 169 199 168 170 150 176
Cropland 88 88 81 84 72 83 65 84
Grassland 66 78 55 81 61 53 52 57
Managed Manure3 24 2<> 27 27 28 28 27 28
Forest Land + + + + + + + +
Settlements 5 <> 6 6 6 6 6 6
Total 1,184 1,140 1,215 1,255 1,181 1,130 1,093 1,178
9 Asymbiotic N fixation is the fixation of atmospheric N2 by bacteria living in soils that do not have a direct relationship with
plants.
10 These processes entail volatilization of applied N as ammonia (NH3) and oxides of N (NOx), transformation of these gases
within the atmosphere (or upon deposition), and deposition of the N primarily in the form of particulate ammonium (NH4), nitric
acid (HN03), and NOx.
Agriculture 6-17
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
Public Review Draft
+ Less than 0.5 Gg N20.
a Accounts for loss of manure N prior to soil application during transport, treatment, and storage, including both volatilization
and leaching/runoff.
Estimated direct and indirect N20 emissions by sub-source category are provided in Table 6-15 and Table 6-16.
Table 6-15: Direct N2Q Emissions from Agricultural Soils by Land-Use and N Input (Tg C02 Eq.)
Activity
1990
Cropland
222.1
Mineral Soils
219.3
Synthetic Fertilizer
83.6
Organic Amendmenta
10.3
Residue N b
15.0
Other0
110.3
Organic Soils
2.8
Grassland
88.0
Synthetic Fertilizer
2.0
PRP Manure
16.4
Managed Manured
0.4
Sewage Sludge
0.2
Residue Nb
34.4
Other0
34.5|
1995
Total
310.11
214.2
211.4
85.1
10.91
15.81
99.6
2.81
77.81
1.7
15.81
0.4
0.4
29.9
29.6
292 01
2000
2001
2002
2003
2004
2005
250.5
252.6
234.0
226.4
220.9
234.2
247.6
249.7
231.1
223.5
217.9
231.2
91.9
94.2
90.2
84.6
88.5
86.9
12.1
12.9
12.0
11.2
11.6
11.7
18.5
16.6
15.1
18.3
14.7
16.0
125.1
126.0
113.8
109.4
103.1
116.6
2.9
2.9
2.9
2.9
2.9
2.9
73.9
74.8
80.1
71.0
71.3
76.4
1.6
1.7
1.8
1.6
1.7
1.7
16.8
15.3
20.6
15.5
17.2
14.3
0.4
0.4
0.4
0.3
0.4
0.4
0.5
0.5
0.5
0.5
0.5
0.5
28.1
29.9
28.0
27.9
26.4
29.8
26.5
27.0
28.8
25.2
25.0
29.7
324.4 327.4 314.1 297.4 292.1 310.5
+ Less than 0.05 Tg C02 Eq.
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.
dAccounts for managed manure that is applied to grassland soils
Table 6-16: Indirect N2Q Emissions from all Land Use Types and Managed Manure Systems (Tg C02 Eq.)
Activity 1990 1995
Cropland 27.2 27.21
Volatilization and Atm. Deposition 4.<> 4.91
Surface Leaching & Run-Off 22.6 22.31
Grassland 20.4 24.31
Volatilization and Atm. Deposition 10.7 10.31
Surface Leaching & Run-Off 9.6 14.01
Managed manure systems 7.5 8.01
Volatilization and Atm. Deposition3 7.5 8.01
Forest Land + 0.11
Volatilization and Atm. Deposition + +
Surface Leaching & Run-Off + +
Settlements 1.7 1.8
Volatilization and Atm. Deposition 0.5 0.61
Surface Leaching & Run-Off L2 1.21
Total 56.8 61.41
| 2000
2001
2002
2003
2004
2005
25.0
26.1
22.5
25.7
20.1
26.2
5.3
4.9
5.0
5.4
5.3
5.4
1 19.7
21.2
17.5
20.3
14.8
20.7
17.1
25.1
18.9
16.5
16.0
17.8
9.3
9.4
9.3
9.4
9.1
9.9
7.8
15.7
9.5
7.1
6.9
7.9
8.4
8.5
8.7
8.5
8.5
8.5
8.4
8.5
8.7
8.5
8.5
8.5
0.1
0.1
0.1
0.1
0.1
0.1
+
+
+
+
+
+
0.1
0.1
0.1
0.1
0.1
0.1
1.8
1.8
1.9
1.9
2.0
1.9
0.6
0.6
0.6
0.6
0.6
0.6
1.3
1.2
1.3
1.3
1.3
1.3
I 52.4
61.6
52.0
52.8
46.6
54.6
+ Less than 0.05 Tg C02 Eq.
a Accounts for loss of manure N prior to soil application during transport, treatment, and storage.
Figure 6-3 through Figure 6-6 show regional patterns in N20 emissions for direct sources and regional patterns of N
losses leading to indirect N20 emissions, respectively, for major crops and grasslands across the United States.
Direct N20 emissions tend to be high in the Corn Belt (Illinois, Iowa, Southern Minnesota and Wisconsin, and
Eastern Nebraska). A large portion of the land in many of these counties is covered with high input corn and N-
6-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 fixing soybean cropping, resulting in high emissions on a per county basis. Emissions are also high in some
2 counties in the Dakotas, Kansas, Eastern Colorado, Oklahoma, and Texas. High input irrigated cropping and
3 moderate input dryland wheat cropping are major contributors to emissions in these counties. Emissions are high
4 along the lower Mississippi Valley because this area is intensively cropped and fine-textured soils along the river
5 facilitate denitrification and high N20 emissions. Emissions are also high in some counties in California where
6 intensive, irrigated cropping is a dominant land use. Emissions are low in the eastern United States because a small
7 portion of land in most of these counties is cropped, and also low in many counties in the West where rainfall and
8 access to irrigation water are limited. Counties with less than a minimum number of cropped acres were not
9 simulated by DAYCENT (white areas). Emissions from these counties were calculated at the national scale using
10 Tier 1 methodology.
11 Direct emissions (Tg C02 Eq./county/year) from grasslands are highest in the western United States (Figure 6-4)
12 where counties tend to be large and a high proportion of the land in many of these counties is used for cattle
13 grazing. Some counties in the Great Lake states, the Northeast, and Florida have moderate county level emissions
14 even though emissions from these areas tend to be high on a per unit area basis, because the total amount of grazed
15 land in these counties is much less than many counties in the West.
16 Indirect emissions for crops and grasslands (Figure 6-5 and Figure 6-6) show patterns similar to direct emissions,
17 because the factors that control direct emissions (N inputs, weather, soil type) also influence indirect emissions.
18 However, there are some exceptions, because the processes that contribute to indirect emissions (N03 leaching, N
19 volatilization) do not respond in exactly the same manner to these controls as the processes that control direct
20 emissions (nitrification and denitrification). For example, coarse-textured soils facilitate nitrification and moderate
21 direct emissions in Florida grasslands, but indirect emissions are relatively high in Florida grasslands due to high
22 rates of N volatilization and N03 leaching in coarse-textured soils. Indirect emissions from crops in some counties
23 in the Carolinas are also relatively high compared to direct emissions because these soils tend to be coarse-textured.
24
25 Figure 6-3: Major Crops, Average Annual Direct N20 Emissions, 1990-2005 (Tg C02 Eq./county/year)
26
27 Figure 6-4: Grasslands, Average Annual Direct N20 Emissions, 1990-2005 (Tg C02 Eq./county/year)
28
29 Figure 6-5: Major Crops, Average Annual N Losses Leading to Indirect N20 Emissions, 1990-2005 (Tg C02
30 Eq./county/year)
31
32 Figure 6-6: Grasslands, Average Annual N Losses Leading to Indirect N20 Emissions, 1990-2005 (Tg C02
33 Eq./county/year)
34
35 Methodology
36 The Revised 1996IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997) divide the Agricultural Soil Management
37 source category into three components: (1) direct emissions from agricultural soils due to N additions to cropland
38 and grassland mineral soils, planting of legumes on cropland and grassland soils, and drainage and cultivation of
39 organic cropland soils; (2) direct emissions from soils due to the deposition of manure by livestock on PRP
40 grasslands; and (3) indirect emissions from soils and water due to N additions and manure deposition to soils that
Agriculture 6-19
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Public Review Draft
leads to volatilization, leaching, or runoff of N and subsequent conversion to N20. Moreover, the 2006IPCC
Guidelines (IPCC 2006) recommend reporting total emissions from managed lands, and, therefore, this chapter
includes estimates for direct emissions due to decomposition of soil organic matter and litter, and asymbiotic
fixation of N from the atmosphere.11
The methodology used to estimate emissions from agricultural soil management in the United States is based on a
combination of IPCC Tier 1 and 3 approaches. A Tier 3, process-based model (DAYCENT) was used to estimate
direct emissions from major crops on mineral (i.e., non-organic) soils; as well as most of the direct emissions from
grasslands. The Tier 3 approach is more refined for estimating N20 emissions in the United States, accounting for
more of the environmental and management influences on soil N20 emissions than the IPCC Tier 1 method (see
Box 6-1 for further elaboration). The Tier 1 IPCC methodology was used to estimate direct emissions from non-
major crops on mineral soils, the portion of the grassland direct emissions that were not estimated with the Tier 3
DAYCENT model, and direct emissions from drainage and cultivation of organic cropland soils. The Tier 1
approach was based on the 2006 IPCC Guidelines (IPCC 2006), which was originally developed in the Revised
1996 IPCC Guidelines (IPCC/UNEP/OECD/IEA 1997) and IPCC Good Practice Guidance Reports (IPCC 2000,
2003). A combination of DAYCENT and the IPCC Tier 1 method was used to estimate indirect emissions from
soils.
The Agricultural Soil Management sector has adopted several recommendations from IPCC (2006) that are
considered improvements over previous IPCC methods, including: (1) estimating the contribution of N from crop
residues to indirect soil N20 emissions, (2) adopting the revised emission factor for direct N20 emissions, (3)
removing double counting of emissions due to estimating N-fixing crops in both the symbiotic and crop residue N
input categories, (4) using revised crop residue statistics to compute N inputs to soil 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). Annex
3.11 provides more detailed information on the methodologies and data used to calculate N20 emissions from each
component.
[BEGIN BOX]
Box 6-1. Tier 1 vs. Tier 3 Approach for Estimating N20 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 N20 emissions on a
source-by-source basis. The Tier 3 approach developed for this Inventory employs a process-based model (i.e.,
DAYCENT) and is based on the interaction of N inputs and the environmental conditions at a specific location.
Consequently, it is necessary not only to know the amount of N inputs but 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.
Another important difference between the Tier 1 and Tier 3 approaches relates to assumptions regarding N cycling.
Tier 1 assumes that N added to a system is subject to N20 emissions only during that year; e.g., N added as fertilizer
or through fixation contributes to N20 emission for that year, but cannot be stored in soils and contribute to N20
11 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.
6-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Public Review Draft
emission in subsequent years. In contrast, the process-based model used in the Tier 3 approach includes such
legacy effects when N is mineralized from soil organic matter and emitted as N20 during subsequent years.
[END BOX]
Direct N20 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 N20
emissions from mineral cropland soils that are managed for production of major crops, specifically corn, soybean,
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 N20 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. The county
scale was selected, because soil and weather data were available for every county with more than 100 acres of
agricultural land. However, land management data (e.g., timing of planting, harvesting, 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 N20 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 and national levels due to the scale of management data.
Nitrous oxide emission estimates from DAYCENT include the influence of N additions, crop type, irrigation, and
other factors in aggregate, and, therefore, it is not possible to partition N20 emissions by anthropogenic activity
directly from model outputs (e.g., N20 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 between the combined anthropogenic interventions that are implemented (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 N20 production (nitrification and denitrification). According to IPCC/UNEP/OECD/IEA
(1997), soil N20 inventories are expected to report emissions from mineral soils associated with mineral N
fertilization, organic amendments, crop residue N added to soils, and symbiotic N-fixation. In addition, IPCC
(2006) recommends reporting total N20 emissions from managed lands, which would also include "other N Inputs"
from mineralization due to decomposition of soil organic matter and litter, as well as asymbiotic fixation of N from
the atmosphere. To approximate emissions by activity, the amount of mineral N added to the soil for each of these
practices 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 N20 emissions in order to
approximate the portion attributed to key practices. This approach is not precise because it assumes that all N made
available in soil has an equal probability of being released as N20, regardless of its source, which is unlikely to be
the case. Since it is not possible to track N flows from different sources using the DAYCENT model, this approach
allows for further disaggregation by source of N, which is valuable for reporting purposes.
Consequently, DAYCENT was used to estimate direct N20 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), and (4) mineralization of soil organic matter and litter, in addition to
Agriculture 6-21
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Public Review Draft
asymbiotic fixation. This last source is generated internally by the DAYCENT model. For each of the first 3
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). These values were scaled to
estimate values for other years based on estimates of annual production of managed manure. The amount
of managed manure for each livestock type was calculated by 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 (USDA 1994a-b, 1995a-b, 1998a-b,
1999a-c, 2000a, 2004a-e, 2005a-d, 2006a). Horse population data were obtained from the FAOSTAT
database (FAO 2006). Goat population data for 1992, 1997, and 2002 were obtained from the Census of
Agriculture (USDA 2005g); 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 and 1997 Census of Agriculture (USDA
2005g). These values may be slightly high because about 5 percent of poultry manure is used for feed
(Carpenter 1992). However, poultry manure production is relatively small compared to other livestock
categories, particularly cattle. Only a portion of the managed manure N is applied to crop and grassland
soils according to Edmonds et al. (2003). The difference between manure N applied to soils and remaining
N in the managed manure was assumed to be lost through volatilization and leaching/runoff of N species
during treatment, storage, and transportation. Instead of assuming that 20 percent of organic N applied to
soils is volatilized and 30 percent of applied N was lost through leaching/runoff, as approximated with
IPCC (2006) methodology, volatilization and N leaching/runoff from manure that was amended to soils
was calculated by the DAYCENT process-based model. 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.
• Nitrogen-fixing crops and forages, 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 considered separate activity data for the 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 N20 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),
6-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Public Review Draft
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-generated per-area estimates of N20 emissions (g N20-N m"2) from major crops were multiplied by the
cropland area data to obtain county-scale emission estimates. Cropland area data were from NASS (USDA 2005g).
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, and 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 enables it to produce more accurate estimates of N20 emissions.
Non-Major Crop Types on Mineral Cropland Soils
The Tier 1 methodology (IPCC/UNEP/OECD/IEA 1997, IPCC 2006) was used to estimate direct N20 emissions for
mineral cropland soils that are managed for production of non-major crop types. Estimates of direct N20 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 non-manure other
commercial organic fertilizers;12 and (3) the retention of above- and below-ground crop residues. No manure
amendments were considered here because most of this material was applied to crops simulated by DAYCENT.
DAYCENT simulations included the 5 major cropping systems (corn, hay, sorghum, soybean, wheat), which are the
land management systems receiving the vast majority (approximately 95 percent) of manure applications to cropped
land in the United States (Kellogg et al. 2000, Edmonds et al. 2003). Non-manure organic amendments were not
included in the DAYCENT simulations, because county-level data for this source were not available and this source
is a very small portion of total organic amendments. Consequently, non-manure organic amendments were included
in the Tier 1 analysis.
1. A process-of-elimination approach was used to estimate N fertilizer additions for these crops, because little
information exists on fertilizer application rates for non-major crop types. N fertilizer additions to major
crops, grassland, forest land, and settlements were summed, this sum was subtracted from total annual
fertilizer sales, and the difference was assumed to be applied to non-major crop types. Non-major crop
types include: (a) fruits, nuts, and vegetables, and (b) other annual crops not simulated by DAYCENT
(barley, oats, tobacco, sugarcane, sugar beets, sunflowers, millet, peanuts, etc.).
2. Annual 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 statistics (TVA 1991, 1992a,
1993, 1994; AAPFCO 1995, 1996, 1997, 1998, 1999, 2000a, 2000b, 2002, 2003, 2004, 2005, 2006).
3. Crop residue N was derived by combining amounts of above- and below-ground biomass, which were
determined based on crop production yield statistics (1994a, 1998b, 2003, 2005i, 2006b), 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 (Bouwman et al. 2002a, 2002b, Novoa and Tejeda 2006, Stehfest and Bouwman 2006) to
derive an estimate of cropland direct N20 emissions from non-major crop types.
12 Other commercial organic fertilizers include dried blood, dried manure, tankage, compost, other, but excludes manure and
sewage sludge, which are used as commercial fertilizers.
Agriculture 6-23
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Public Review Draft
Drainage and Cultivation of Organic Cropland Soils
Tier 1 methods were used to estimate direct N20 emissions from the drainage and cultivation of organic cropland
soils. Estimates of the total U.S. acreage of drained organic soils cultivated annually for temperate and sub-tropical
climate regions were obtained for 1982, 1992, and 1997 from the Natural Resources Inventory (USD A 2000b, as
extracted by Eve 2001 and amended by Ogle 2002), using temperature and precipitation data from Daly et al. (1994,
1998). These areas were linearly interpolated and extrapolated to estimate areas for the missing years. To estimate
annual emissions, the total temperate 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 N20 Emissions from Grassland Soils
As with N20 from croplands, the Tier 3 process-based DAYCENT model and Tier 1 methods 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, that may or may not be improved with practices such as irrigation and interseeding
legumes.
DAYCENT was used to simulate N20 emissions from grasslands at the county scale 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 and soils 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 managed manure N production data according to
methods described in Annex 3.11. "other N inputs" were simulated within the DAY CENT 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-generated per-area estimates of N20 emissions (g N20-N m"2) from pasture and rangelands were
multiplied by the reported pasture and rangeland areas in the county. Grassland area data were obtained from the
National Resources Inventory (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 2005, 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 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 DAY CENT accounted for approximately 70
percent of total PRP manure. It is reasonable that DAYCENT did not account for all PRP manure, because the NRI
data do not include some grassland areas such as federal grasslands. N20 emissions from the portion of PRP
manure N not accounted for by DAYCENT were estimated using the Tier 1 method with IPCC default emission
factors (de Klein 2004, IPCC 2006). Sewage sludge was assumed to be applied on grasslands (but not included in
the DAYCENT simulations) 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,
1997, 1999, 2003), Bastian (2002, 2003, 2005), and Metcalf and Eddy (1991). 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 (Bouwman et al. 2002a,
2002b, Novoa and Tejeda 2006, Stehfest and Bouwman 2006, IPCC 2006). 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 N20 emissions from
agricultural soil management (see Table 6-13 and Table 6-14).
6-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Public Review Draft
Indirect N20 Emissions from Managed Soils of all Land-Use Types and Managed Manure Systems
This section describes methods for estimating indirect soil N20 emissions from all land-use types (i.e., cropland,
grassland, forest land, and settlements) and managed manure systems based on losses of N through volatilization,
leaching, and runoff. The sources of indirect N from volatilization, leaching, and runoff are estimated in the same
manner as direct N20 emissions from soils (i.e., using DAYCENT and the Tier 1 method as described for direct
emissions). The indirect emissions from these N sources are estimated using the Tier 1 method (IPCC 2006).
Indirect N20 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 N20. There are two pathways leading to indirect
emissions. The first pathway results from volatilization of N as NOx and NH3 following application of synthetic
fertilizer or organic amendments (e.g., manure, sewage sludge); deposition of PRP manure; or during storage,
treatment, and transport of managed 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 N20. The second pathway occurs via leaching
and runoff of soil N (primarily in the form of nitrate [N03~]) 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 N20 emissions. Regardless of the
eventual location of the indirect N20 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 N20 Emissions from Atmospheric Deposition ofN Volatilized by Managed Soils and Managed
Manure Systems
Similar to the direct emissions calculation, several approaches were combined to estimate the amount of applied N
that was exported from application sites through volatilization. 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 IPCC method was used for land areas that were not simulated with DAYCENT (i.e., non-
major croplands and a small portion of grasslands) (IPCC 2006). Manure N from managed systems assumed to be
volatilized during storage, treatment, and transport was also estimated and included as a source of N for indirect
emissions.
The N volatilized from managed agricultural, forest land, and settlement soils, in addition to volatilization during
storage, treatment, and transport of managed manure was summed to obtain total volatilization. N lost from storage,
treatment, and transport of managed manure is counted as volatilized even though some of this N is likely to be
leached/runoff This is a conservative approach because the IPCC emission factor for volatilization is slightly
higher than for leaching/runoff (IPCC 2006). The IPCC default emission factor (Brumme et al. 1999, Butterbach-
Bahl et al. 1997, Corre et al. 1999, Denier van der Gon and Bleeker 2005, IPCC/UNEP/OECD/IEA 1997, IPCC
2006) was applied to the total amount of N volatilized to estimate indirect N20 emissions from volatilization due to
the use and management of U.S. croplands, grasslands, forest lands, settlements and managed manure (Table 6-16).
Indirect N20 from Leaching/Runoff
Similar to the indirect emissions calculation from volatilized N, several approaches were combined to estimate the
amount of applied N that was transported from application sites through leaching and surface runoff into
waterbodies. DAYCENT was used to simulate the amount of N transported from major cropland types and most
grasslands, while N transport from non-major croplands and grasslands not addressed in the DAYCENT model
simulations (i.e., from land areas that were not simulated with DAYCENT), settlements, and forestland were
obtained by applying the IPCC default fractions for leaching and runoff (IPCC/UNEP/OECD/IEA 1997, IPCC
2006) to total N made available from fertilizer applied, manure applied or deposited, above- and below-ground crop
residue retention, soil organic matter decomposition, and asymbiotic fixation.
The N leached/runoff from managed soils, forests, and settlements was summed to obtain total N leaching or surface
runoff. The IPCC default emission factor was applied to the total amount of N leached/runoff to estimate total
indirect N20 emissions due to the use and management of croplands, grasslands, forest lands, and settlements (Table
Agriculture 6-25
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Public Review Draft
6-16) (IPCC 2006).
Uncertainty
Uncertainty was estimated differently for each of the following three components of N20 emissions from
agricultural soil management: (1) direct emissions calculated by DAYCENT, (2) direct emissions not calculated by
DAYCENT, and (3) indirect emissions.
For direct emissions calculated using DAYCENT, uncertainty in the results was attributed to model inputs and the
structure of the model (i.e., underlying model equations and parameterization). A Monte Carlo analysis was
implemented to address these uncertainties and propagate errors through the modeling process (Del Grosso et al., in
prep). A Monte Carlo analysis was conducted using probability distribution functions (PDFs) for weather, soil
characteristics, and N inputs to simulate direct N20 emissions for each crop- or grassland type in a county. A joint
PDF was used to address the structural uncertainty for direct N20 emissions from crops, which was derived using an
empirically-based method (Ogle et al. 2007).
County-scale PDFs for weather were based on the variation in temperature and precipitation as represented in
DAYMET weather data grid cells (lxl km) occurring in croplands and grasslands in a county. The National Land
Cover Dataset (Vogelman et al. 2001) provided the data on distribution of croplands and grasslands. Similarly,
county-scale PDFs for soil characteristics were based on STATSGO Soil Map Units (Soil Survey Staff 2005), that
occurred in croplands and grasslands. PDFs for fertilizer were derived from survey data for major U.S. crops, both
irrigated and rainfed (ERS 1997; NASS 2004, 1999, 1992; Grant and Krenz 1985). State-level PDFs were
developed for each crop if a minimum of 15 data points existed for each of the two categories (irrigated and
rainfed). Where data were insufficient at the state-level, PDFs were developed for multi-state Farm Production
Regions. Uncertainty in manure applications for specific crops was incorporated into the analysis based on total
manure available for application in each county, a weighted average application rate, and the crop-specific land area
amended with manure for 1997 (compiled from USD A data on animal numbers, manure production, storage
practices, application rates and associated land areas receiving manure amendments; see Edmonds et al. 2003).
Together with the total area for each crop within a county, the result yielded a probability that a given crop in a
specific county would either receive manure or not in the Monte Carlo analysis. A ratio of manure N production in
each year of the Inventory relative to 1997 was used to adjust the amount of area amended with manure, under the
assumption that greater or less manure N production would lead to a proportional change in amended area (see the
section on Major Crop Types on Mineral Soils for data sources on manure N production). If soils were amended
with manure, a reduction factor was applied to the N fertilization rate accounting for the interaction between
fertilization and manure N amendments (i.e., producers often reduce mineral fertilization rates if applying manure).
Reduction factors were randomly selected from probability distribution factors based on relationships between
manure N application and fertilizer rates (ERS 1997).
An empirically-based uncertainty estimator was developed using a method described by Ogle et al. (2007) to assess
uncertainty in model structure associated with the algorithms and parameterization. The estimator was based on a
linear mixed-effect modeling analysis comparing N20 emission estimates from eight agricultural experiments with
50 treatments. Although the dataset was relatively small, modeled emissions were significantly related to
measurements with a p-value of less than 0.01. Random effects were included to capture the dependence in time
series and data collected from the same experimental site, which were needed to estimate appropriate standard
deviations for parameter coefficients. The structural uncertainty estimator accounted for bias and prediction error in
the DAYCENT model results, as well as random error associated with fine-scale emission predictions in counties
over a time series from 1990 to 2005. Note that the current application only addresses structural uncertainty in
cropland estimates; further development will be needed to address these uncertainties in model estimates for
grasslands, which is a planned improvement as more soil N20 measurement data become available for grassland
sites. In general, DAYCENT tended to underestimate emissions if the rates were above 6 g N20 m"2 (Del Grosso et
al., in prep).
A simple error propagation method (IPCC 2006) was used to estimate uncertainties for direct emissions from
mineral N inputs estimated with Tier 1 methods, including management on croplands that were used to produce
minor crops and N inputs on grasslands that were not addressed in the DAYCENT simulations. Similarly, indirect
6-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Public Review Draft
emissions from agricultural soil management, which were calculated according to the IPCC methodology, were
estimated using the simple error propagation method (IPCC 2006).
Uncertainties from Tier 3 and Tier 1 approaches were combined using simple error propagation (IPCC 2006). The
results of the uncertainty analysis are summarized in Table 6-17. Agricultural direct soil N20 emissions in 2005
were estimated to be between 247.5 and 380.0 Tg C02 Eq. at a 95 percent confidence level. This indicates a range
of 20 percent below and 22 percent above the actual 2005 emission estimate of 310.5 Tg C02 Eq. The indirect soil
N20 emissions in 2005 were estimated to range from 31.9 to 128.4 Tg C02 Eq. at a 95 percent confidence level,
indicating an uncertainty of 42 percent below and 135 percent above the actual 2005 emission estimate of 54.6 Tg
C02 Eq.
Table 6-17: Quantitative Uncertainty Estimates of N20 Emissions from Agricultural Soil Management in 2005 (Tg
C02 Eq. and Percent)
2005 Emission
Uncertainty Range Relative to Emission
Source
Gas
Estimate
Estimate
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Bound
Upper
Bound
Lower Upper
Bound Bound
Direct Soil N20 Emissions
N20
310.5
247.5
380.0
-20% 22%
Indirect Soil N20 Emissions
n2o
54.6
31.9
128.4
-42% 135%
Note: Due to lack of data, uncertainties in managed manure N production, PRP manure N production, other organic fertilizer
amendments, indirect losses of N in the DAYCENT simulations, and sewage sludge amendments to soils are currently treated as
certain; every attempt will be made to include these sources of uncertainty in future Inventories.
QA/QC and Verification
For quality control, DAYCENT results for N20 emissions and N03 leaching were compared with field data
representing various cropped/grazed systems, soils types, and climate patterns (Del Grosso et al. 2005). N20
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. N03 leaching data were available for three sites in
the United States representing nine different combinations of fertilizer amendments. Linear regressions of
simulated vs. observed emission and leaching data yielded correlation coefficients of 0.74 and 0.96 for annual N20
emissions and N03 leaching, respectively.
Spreadsheets containing input data and PDFs required for DAYCENT simulations of major croplands and
grasslands and unit conversion factors were checked, as well as the program scripts that were used to run the Monte
Carlo Analysis. There is a pending problem with timing of management activities (e.g., planting dates, harvest) as
scheduled in the DAYCENT simulations for sorghum production in some counties, and this issue has been
prioritized for correction. 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.
Total emissions and emissions from the different categories were compared with inventories from previous years
and differences were reasonable given the methodological differences (see Recalculations section for further
discussion).
Recalculations Discussion
Major revisions in the Agricultural Soil Management sector this year included (1) modifying N inputs to be
consistent with the agricultural soil C sector, (2) modeling within-county variation in soil characteristics and
weather, (3) developing a Monte Carlo Analysis to address uncertainties in the DAYCENT results, (4)
implementing a separate uncertainty analysis for direct emissions calculated with the IPCC default methodology,
and (5) incorporating revised methods and emission factors from IPCC (2006).
In terms of N inputs, several changes were needed in order to achieve consistency between the agricultural soil N20
and soil C inventories. First, the method for simulating mineral N fertilization was changed, so that application
rates for major crops were assumed to be stable over the Inventory time period. Changes in the amount of fertilizer
Agriculture 6-27
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Public Review Draft
applied to soils were assumed to be a result of changing land area for application rather than the rate of application.
Second, manure amendment data were altered, so that the area of application varied from year to year based on a
county-scale ratio of manure production in an Inventory year relative to 1997. Therefore, the amount of area
amended with manure varies through time as a function of the amount of manure. Third, N20 emissions from soil
application of sewage sludge were estimated using the Tier 1 methodology (IPCC 2006) instead of the DAYCENT
model. DAYCENT simulates N20 emissions at the county scale, but sewage sludge application data were only
available at the national scale. This created a mismatch in the scale of the DAYCENT model analysis compared to
input data availability. The Tier 1 method was assumed to better represent these emissions, since it was not possible
with the current dataset to associate sewage sludge application with specific soil and weather conditions at the
county scale. Fourth, non-manure commercial organic amendments to soils were assumed to be applied on fields
used to produce minor crops, and N20 emissions were estimated with the IPCC default methodology. Commercial
organic fertilizers are more expensive than manure and mineral fertilizers, and, therefore, assumed to be used on
cash crops (e.g., vegetables). Cash crops are considered non-major crops for purposes of the Inventory calculations,
and, thus, estimated using the Tier 1 methods. Fifth, N inputs from forage legumes not accounted for by the
DAYCENT simulations are no longer included in the emissions calculations. In the previous inventory, the
difference between the total N inputs from forage legumes, estimated using an alternative approach, and the
DAYCENT estimate was included in the N20 emissions estimate. However, it was determined that DAYCENT is
likely providing a reasonable estimate of total N inputs from forage legumes so the additional production from the
alternative approach is no longer included.
In last year's Inventory, weather and soils data were based on the conditions at the centroid location of a county.
However, conditions do vary across a county, so the analysis was modified to include sub-county scale
heterogeneity in these data. The National Land Cover Dataset (Vogelman et al. 2001) was used to determine the
overlap between cropland and DAYMET weather records, which are produced on a 1 x 1 km grid, as well as the soil
map units from the STATSGO database that overlap with cropland. The same procedure was also used to
determine heterogeneity in weather and soil characteristics for grasslands. PDFs were formed for each of these data
inputs and used in a Monte Carlo uncertainty analysis.
The methods for Agricultural Soil Management have been revised in IPCC (2006), and key changes have been
incorporated into this year's Inventory. First, the default emission factor for direct soil N20 emissions was lowered
from 1.25 to 1.0 percent of N inputs. Second, previously a portion of the N inputs were removed from the
calculation of direct N20 emissions because it was assumed to be lost through volatilization before direct emissions
occurred. However, the direct emission factor was developed based on total N inputs, and therefore the new method
has been revised to estimate direct N20 emissions based on total N input. Third, unlike IPCC/UNEP/OECD/IEA
(1997) that counted N fixed by legumes and transported to aboveground biomass as N inputs, as well as N in crop
residues, the IPCC (2006) does not double-count symbiotic N fixation separately from the crop residue N inputs.
However, the new method does incorporate crop N inputs from not only the aboveground residues, as in
IPCC/UNEP/OECD/IEA (1997), but also the root N input to the soil as well. Fourth, regarding indirect emissions,
only N inputs from synthetic and organic fertilizer additions were assumed to contribute to N03 runoff and leaching
in IPCC/UNEP/OECD/IEA (1997). IPCC (2006) assumes that N from crop residues, which includes unharvested N
that was symbiotically fixed, is also available for runoff and leaching. Sixth, the amount of N leached out of the soil
profile or run off the soil surface that is assumed to be denitrified to N20 in aquatic systems was lowered from 2.5
to 0.75 percent. Lastly, IPCC (2006) recommends reporting total emissions from managed lands because of the
subjectivity with attempting to separate anthropogenic influences from "natural" emissions in a managed
environment (i.e., all processes leading to N mineralization in a managed environment and resulting emissions are
influenced by anthropogenic activity). Thus, N20 emissions were not reduced by attempting to estimate a natural
background emission based on simulating native vegetation, which had been done in the previous Inventory.
There are two main consequences of adopting new methods from IPCC (2006). First, total emissions are higher, in
large part because the non-anthropogenic portion was not subtracted from total emissions. Second, indirect
emissions are lower because the amount of nitrate N leached and runoff that is assumed to be converted to N20 in
waterways is substantially lower (0.75 versus 2.5 percent of nitrate N in IPCC/UNEP/OECD/IEA [1997]).
The total change following recalculations ranged from a 15 to 42 percent increase in emissions with an average
increase of 32.5 per cent. As noted above, one reason for the increase is that under the new methods from IPCC
6-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Public Review Draft
(2006) non-anthropogenic emissions were not subtracted from total emissions. The second main reason is that
application of the structural uncertainty estimator described above tended to increase direct N20 estimates, because
DAYCENT under-estimated emissions when the annual rate exceeded 6 g N20 m"2.
Planned Improvements
Two major improvements are planned for the Agricultural Soil Management sector. The first improvement will be
to incorporate more land survey data from the National Resources Inventory (NRI) (USD A 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 land 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, and this 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
4 out of every 5 years, and is currently moving to an annualized inventory that will include a full record for each
year. Third, the current Inventory based on NASS does not quantify the influence of land-use change on emissions,
which can be addressed using the NRI survey records. NRI also provides additional information on pasture land
management that can be incorporated into the analysis (particularly the use of irrigation). Using NRI data will also
make the Agricultural Soil Management sector 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 N20 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 only evaluated for emission estimates in croplands, but it is anticipated that the evaluation
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 survey data from the NRI will facilitate the assessment of uncertainties in
agricultural activity data. Finally, uncertainties in managed manure N production, PRP manure N production, other
organic fertilizer amendments, indirect losses of N in the DAYCENT simulations, and sewage sludge amendments
to soils are currently treated as certain. Uncertainties in these quantities will be derived and included in future
years.
Additional improvements are more minor but will lead to more accurate estimates, including updating D AYMET
weather for more recent years and revising manure N application data to not include poultry manure that is used for
cattle feed. Currently, it is estimated that approximately 5 percent of poultry manure is used for feed in the United
States and, therefore, not applied to soils. Future inventories will also create a time series of poultry manure going
to feed, since initial research indicates that the percentage may have changed over time. In addition, some
simulations for sorghum did not run to completion. Input files for counties where this occurred will be examined
and the errors corrected. Lastly, instead of assuming that a constant 10 percent of total fertilizer used annually in
the US is applied to settlements, an attempt will be made in the future to recognize that this value varies through the
time series because of increasing urbanization, particularly in metropolitan areas. This improvement will be
accomplished by exploring the possibility of developing a database that has county-level nitrogen fertilizer data
partitioned by farm and non-farm use.
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,
Agriculture 6-29
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Public Review Draft
animal bedding material, supplemental animal feed, or construction material. Field burning of crop residues is not
considered a net source of C02, because the carbon released to the atmosphere as C02 during burning is assumed to
be reabsorbed during the next growing season. Crop residue burning is, however, a net source of CH4, N20, CO,
and NOx, which are released during combustion.
Field burning is not a common method of agricultural residue disposal in the United States. The primary crop types
whose residues are typically burned in the United States are wheat, rice, sugarcane, corn, barley, soybeans, and
peanuts. Less than 5 percent of the residue for each of these crops is burned each year, except for rice.13 Annual
emissions from this source over the period 1990 to 2005 have remained relatively constant, averaging
approximately 0.9 Tg C02 Eq. (41 Gg) of CH4, 0.5 Tg C02 Eq. (2 Gg) of N20 (see Table 6-18 and Table 6-19).
Table 6-18: CH4 and N2Q Emissions from Field Burning of Agricultural Residues (Tg C02 Eq.)
Gas/Crop Type
1990
1995
2000
2001
2002
2003
2004
2005
ch4
0.7
0.7
0.8
0.8
0.7
0.8
0.9
0.9
Wheat
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
Sugarcane
+WM
+
+
+
+
+
+
Corn
0.3
0.3
0.4
0.3
0.3
0.4
0.4
0.4
Barley
+¦
+
+
+
+
+
+
Soybeans
0.1
0.2
0.2
0.2
0.2
0.2
0.2
0.2
Peanuts
+¦[
+¦1
+
+
+
+
+
+
n2o
0.4
0.4
0.5
0.5
0.4
0.4
0.5
0.5
Wheat
+¦[
+BI
+
+
+
+
+
+
Rice
+
+
+
+
+
+
Sugarcane
+
+
+
+
+
+
Corn
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
Peanuts
+
+
+
+
+
+
+
+
Total
1.1
i.oB
1.3
1.2
1.1
1.2
1.4
1.4
+ Less than 0.05 Tg C02 Eq.
Note: Totals may not sum due to independent rounding.
Table 6-19: CH4, N2Q, CO, and NOx Emissions from Field Burning of Agricultural Residues (Gg)
Gas/Crop Type
1990
1995)
ch4
33
32
Wheat
7l
5
Rice
4l
4
Sugarcane
ill
1
Corn
13Hi
13
Barley
iH
1
Soybeans
7I
8
Peanuts
0
n2o
il
1
Wheat
+¦[
+
Rice
+
Sugarcane
+
Corn
+
mm
+
2000
2001
2002
2003
2004
2005
38
37
34
38
42
41
5
5
4
6
5
5
4
4
3
5
4
4
1
1
1
1
1
1
17
16
15
17
20
19
1
+
+
+
+
+
10
11
10
9
11
11
+
+
+
+
+
+
1
1
1
1
2
2
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
13 The fraction of rice straw burned each year is significantly higher than that for other crops (see "Methodology" discussion
below).
6-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Public Review Draft
Barley
+
Soybeans
ll
1
Peanuts
+
CO
691
663
Wheat
137
109
Rice
87
88
Sugarcane
18
20
Corn
282
263
Barley
l6H
13
Soybeans
148
167
Peanuts
2H
2
NOx
28
29
Wheat
4H
3
Rice
31H
3
Sugarcane
+¦1
+
Corn
7H
6
Barley
iH
+
Soybeans
ill
16
Peanuts
+
+
+
+
+
+
+
+
1
1
1
1
1
1
+
+
+
+
+
+
792
774
709
800
879
858
112
98
80
117
108
105
78
81
64
100
78
91
24
23
23
22
19
18
353
338
319
359
420
395
12
9
8
10
10
8
212
222
212
189
240
237
2
3
2
3
3
3
35
35
33
34
39
39
3
3
2
3
3
3
3
3
2
3
3
3
+
+
+
+
+
+
8
8
8
9
10
9
+
+
+
+
+
+
20
21
20
18
23
22
+
+
+
+
+
+
+ Less than 0.5 Gg
Note: Totals may not sum due to independent rounding.
Methodology
The methodology for estimating greenhouse gas emissions from field burning of agricultural residues is consistent
with IPCC/UNEP/OECD/IEA (1997). In order to estimate the amounts of C and N released during burning, the
following equations were used:14
[C or N] Released = (Annual Crop Production) x (Residue/Crop Product Ratio) x (Fraction of Residues Burned in
situ) x (Dry Matter Content of the Residue) x (Burning Efficiency) x ([C or N] Content of the Residue) x
(Combustion Efficiency)15
Emissions were calculated by multiplying the amount of C or N released by the appropriate IPCC default emission
ratio (i.e., CH4-C/C and, N20-N/N).
The types of crop residues burned in the United States were determined from various state-level greenhouse gas
emission inventories (ILENR 1993, Oregon Department of Energy 1995, Wisconsin Department of Natural
Resources 1993) and publications on agricultural burning in the United States (Jenkins et al. 1992, Turn et al. 1997,
EPA 1992).
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). Rice production data for Florida and Oklahoma, which are not collected by USDA, were
14 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.
15 Burning Efficiency is defined as the fraction of dry biomass exposed to burning that actually burns. Combustion Efficiency is
defined as the fraction of carbon in the fire that is oxidized completely to C02. In the methodology recommended by the IPCC,
the "burning efficiency" is assumed to be contained in the "fraction of residues burned" factor. However, the number used here
to estimate the "fraction of residues burned" does not account for the fraction of exposed residue that does not burn. Therefore, a
"burning efficiency factor" was added to the calculations.
Agriculture 6-31
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
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), and
crop yields for Arkansas (USDA 1994, 1998, 2003, 2005, 2006) were applied to Oklahoma acreages16 (Lee 2003,
2004, 2005, 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 the
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; Klosterboer
1999a, 1999b, 2000, 2001, 2002, 2003; Lancero 2006; Lee 2005, 2006; Lindberg 2002, 2003, 2004, 2005;
Linscombe 1999a, 1999b, 2001, 2002, 2003, 2004, 2005, 2006; Najita 2000, 2001; Sacramento Valley Basinwide
Air Pollution Control Council 2005; Schueneman 1999a, 1999b, 2001; Stansel 2004, 2005; Street 2001, 2002,
2003; Walker 2004, 2005, 2006; Wilson 2003, 2004, 2005, 2006) (see Table 6-21 and Table 6-22). The estimates
provided for Florida and Missouri remained constant over the entire 1990 through 2005 period, while the estimates
for all other states varied over the time series. For California, the annual percentages of rice area burned in the
Sacramento Valley are assumed to be representative of burning in the entire state, because the Sacramento Valley
accounts for over 95 percent of the rice acreage in California (Fife 1999). These values generally declined between
1990 and 2005 because of a legislated reduction in rice straw burning (Lindberg 2002), although there was a slight
increase from 2004 to 2005 (see Table 6-21 and Table 6-22).
All residue/crop product mass ratios except sugarcane were obtained from Strehler and Stiitzle (1987). The datum
for sugarcane is from University of California (1977). Residue dry matter contents for all crops except soybeans
and peanuts were obtained from Turn et al. (1997). Soybean dry matter content was obtained from Strehler and
Stiitzle (1987). Peanut dry matter content was obtained through personal communications with Jen Ketzis (1999),
who accessed Cornell University's Department of Animal Science's computer model, Cornell Net Carbohydrate and
Protein System. The residue carbon contents and nitrogen contents for all crops except soybeans and peanuts 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
nitrogen content of peanuts is from Ketzis (1999). These data are listed in Table 6-23. 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 6-24) were taken from the Revised 1996 IPCC Guidelines
(IPCC/UNEP/OECD/IEA 1997).
Table 6-20: Agricultural Crop Production (Gg of Product)
Crop
1990
1995
2000
2001
2002
2003
2004
2005
Wheat
74,292
59,404
60,641
53,001
43,705
63,814
58,738
57,280
Rice
7,114
7,947
8,705
9,794
9,601
9,084
10,565
10,152
Sugarcane
25,525
27,922
32,762
31,377
32,253
30,715
26,320
25,308
Corn
201,534
187,970
251,854
241,377
227,767
256,278
299,914
282,260
Barley
9,192
7,824
6,919
5,407
4,940
6,059
6,091
4,613
Soybeans
52,416
59,174
75,055
78,671
75,010
66,778
85,013
83,999
Peanuts
1,635
1,570
1,481
1,940
1,506
1,880
1,945
2,187
*Corn for grain (i.e., excludes corn for silage).
Table 6-21: Percent of Rice Area Burned by State
State 1990-1998 1999 2000 2001 2002 2003 2004 2005
16 Rice production yield data are not available for Oklahoma, so the Arkansas values are used as a proxy.
6-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Arkansas
13%
13%
13%
13%
16%
22%
17%
22%
California
Variable3
27%
27%
23%
13%
14%
11%
12%
Florida13
0%
0%
0%
0%
0%
0%
0%
0%
Louisiana
6%
0%
5%
4%
3%
3%
3%
3%
Mississippi
10%
40%
40%
40%
8%
65%
23%
23%
Missouri
18%
18%
18%
18%
18%
18%
18%
18%
Oklahoma
90%
90%
90%
90%
90%
100%
88%
94%
Texas
1%
2%
0%
0%
0%
0%
0%
0%
1 a Values provided in Table 6-22.
2 b Although rice is cultivated in Florida, crop residue burning is illegal. Therefore, emissions remain zero throughout the time
3 series.
4
5 Table 6-22: Percent of Rice Area Burned in California, 1990-1998
Year Percentage
1990
75%
1991
75%
1992
66%
1993
60%
1994
69%
1995
59%
1996
63%
1997
34%
1998
35%
6
7 Table 6-23: Key Assumptions for Estimating Emissions from Field Burning of Agricultural Residues
Crop
Residue/Crop
Fraction of
Dry Matter
C
N
Burning
Combustion
Ratio
Residue Burned
Fraction
Fraction
Fraction
Efficiency
Efficiency
Wheat
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
8
9 Table 6-24: Greenhouse Gas Emission Ratios
Gas
Emission Ratio
CH/
0.005
coa
0.060
N2Ob
0.007
NOxb
0.121
10 a Mass of C compound released (units of C) relative to mass of total C released from burning (units of C).
11 b Mass of N compound released (units of N) relative to mass of total N released from burning (units of N).
12
13 Uncertainty
14 A significant source of uncertainty in the calculation of non-C02 emissions from field burning of agricultural
15 residues is in the estimates of the fraction of residue of each crop type burned each year. Data on the fraction
16 burned, as well as the gross amount of residue burned each year, are not collected at either the national or state
17 level. In addition, burning practices are highly variable among crops, as well as among states. The fractions of
18 residue burned used in these calculations were based upon information collected by state agencies and in published
19 literature. Based on expert judgment, uncertainty in the fraction of crop residue burned ranged from zero to 100
20 percent, depending on the state and crop type.
Agriculture 6-33
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
The results of the Tier 2 Monte Carlo uncertainty analysis are summarized in Table 6-25. CH4 emissions from field
burning of agricultural residues in 2005 were estimated to be between 0.75 and 0.97 Tg C02 Eq. at a 95 percent
confidence level. This indicates a range of 13 percent below and 13 percent above the 2005 emission estimate of
0.9 Tg C02 Eq. Also at the 95 percent confidence level, N20 emissions were estimated to be between 0.45 and 0.57
Tg C02 Eq. (or approximately 11 percent below and 12 percent above the 2005 emission estimate of 0.5 Tg C02
Eq.).
Table 6-25: Tier 2 Uncertainty Estimates for CH4 and N20 Emissions from Field Burning of Agricultural Residues
(Tg C02 Eq. and Percent)
2005 Emission
Uncertainty Range Relative to Emission
Source
Gas
Estimate
Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Field Burning of Agricultural Residues
Field Burning of Agricultural Residues
ch4
n2o
0.9
0.5
0.75 0.97
0.45 0.57
-13% 13%
-11% 12%
aRange of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
QA/QC and Verification
A source-specific QA/QC plan for 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 2004 were updated using data from USDA (2006). Data on the percentage of rice
residue burned in Missouri were revised for all years to 17.5 percent based on new information (Anonymous 2006).
Similarly, the percentage of rice residue burned in Mississippi was revised to 22.5 percent for 2004 based on new
information provided by Walker (2006). New data for acres of rice harvested in Arkansas in 2005 changed the
average rice yield for Arkansas for all years. Subsequently, this change resulted in a change in the rice production
data for Oklahoma for all years, since Arkansas data are used as a proxy to calculate rice production in Oklahoma.
These modifications resulted in a change in emissions estimates for CH4 and N20 for all years. From 1990 to 2004,
emission estimates for CH4 increased by amounts ranging between 0.18 and 0.51 percent. From 1990 to 2003, N20
emission estimates increased by amounts ranging between 0.15 and 0.39 percent. In 2004, N20 emission estimates
decreased by 0.05 percent.
Planned Improvements
Preliminary research on agricultural burning in the United States indicates that residues from several additional crop
types (e.g., grass for seed, blueberries, and fruit and nut trees) are burned. Whether sufficient information exists for
inclusion of these additional crop types in future inventories is being investigated. The extent of recent state crop-
burning regulations is also being investigated.
6-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Enteric Fermentation
Agriculture as a Portion of
Manure Management all Emissions
Rice Cultivation |
Field Burning of I
Agricultural Residues | 1.4
o
50 100 150 200 250 300
Tg C02 Eq
Figure 6-1: 2005 Agriculture Chapter GHG Sources
-------
N Volatilization
Synthetic N Fertilizers
FERTILIZER
N Flows:
N Inputs to
Managed Soils
Organic
Amendments
Direct N20
Emissions
Includes both commercial and
non-commercial fertilizers (i.e.,
animal manure, compost,
sewage sludge, tankage, etc.)
N Volatilization
and Deposition
Urine and Dung from
Grazing Animals
Indirect N20
Emissions
Crop Residues
Includes above- and belowground ^
residues for all crops (non-N and N
fixing) and from perennial forage
crops and pastures following renewal
Mineralization of
Soil Organic Matter
N Emissions
Biomass Burning
Histosol
Cultivation
Although N emissions from
biomass burning are not
currently accounted for in the
Inventory, they are a potential
source of N to soils through
volatilization and deposition.
Storage and Management
of Livestock Manure
Includes non-N20 N emissions from storage
and management of manure used as
fertilizer.
Surface
Watej/
Groundwater
This graphic illustrates the sources and pathways of nitrogen that result in direct and indirect N20 emissions from soils in the United States. Sources of nitrogen applied to, or deposited
on, soils are represented with arrows on the left-hand side of the graphic. Emission pathways are also shown with arrows. On the lower right-hand side is a cut-away view of a
representative section of a managed soil; histosol cultivation is represented here.
-------
Tg C02 Eq/County/yr
~ Not simulated
~ <0.05
~ 0.05-0.1
~ 0.1 -0.2
HO.2-0.3
¦ 0.3 -0.5
¦ >0.5
-------
Figure 6-4
Grasslands, Average Annual Direct N20 Emissions, 1990-2005 (Tg C02 Eq.)
Tg C02 Eq/County/yr
~ Not simulated
~ <0.01
~ 0.01-0.025
~ 0.025-0.05
¦ 0.05-0.1
¦ 0.1 -0.25
¦ >0.25
Agriculture 6-2
-------
Figure 6-5
Major Crops, Average Annual N Losses Leading to Indirect N20 Emissions, 1990-2005 (Tg C02 Eq.)
6-3 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Figure 6-6
Grasslands, Average Annual N Losses Leading to Indirect N20 Emissions, 1990-2005 (Tg C02 Eq.)
Tg C02 Eq/County/yr
~ Not simulated
~ <0.005
~ 0.005-0.01
~ 0.01-0.02
¦ 0.02 -0.05
¦ 0.05 -0.1
¦ >0.1
Agriculture 6-4
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
7. Land Use, Land-Use Change, and Forestry
This chapter provides an assessment of the net greenhouse gas flux1 resulting from the uses and changes in land
types and forests in the United States. IPCC Good Practice Guidance for Land Use, Land-Use Change, and
Forestry (IPCC 2003) recommends reporting fluxes according to changes within and conversions between certain
land-use types, termed forest land, cropland, grassland, and settlements (as well as wetlands). The greenhouse gas
flux from Forest Land Remaining Forest Land is reported using estimates of changes in forest carbon (C) stocks,
non-carbon dioxide (C02) 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 C02 due to the
application of crushed limestone and dolomite to managed land (i.e., soil liming). 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 flux estimates in this chapter, with the exception of C02 fluxes from wood products, urban trees, and liming,
are based on activity data collected at multiple-year intervals, which are in the form of forest, land-use, and
municipal solid waste surveys. Carbon dioxide fluxes from forest C stocks (except the wood product components)
and from agricultural soils (except the liming component) are calculated on an average annual basis from data
collected in intervals ranging from 1 to 10 years. The resulting annual averages are applied to years between
surveys. Calculations of non-C02 emissions from forest fires are based on forest C02 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, land-use, and municipal solid waste surveys were
completed prior to 2005, the estimates of C02 flux from forests, agricultural soils, and landfilled yard trimmings and
food scraps are based in part on extrapolation. Carbon dioxide flux from urban trees is based on neither annual data
nor periodic survey data, but instead on data collected over the period 1990 through 1999. This flux has been
applied to the entire time series, and periodic U.S. census data on changes in urban area have been used to develop
annual estimates of C02 flux.
Land use, land-use change, and forestry activities in 2005 resulted in a net C sequestration of 828.4 Tg C02 Eq.
(225.9 Tg C) (Table 7-1 and Table 7-2). This represents an offset of approximately 16 percent of total U.S. C02
emissions. Total land use, land-use change, and forestry net C sequestration2 increased by approximately 16
percent between 1990 and 2005. 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 net C emissions in
1990 and 1991, became a net C sink from 1992 to 1994, and then remained a fairly constant emission source.
Emissions from Land Converted to Cropland declined between 1990 and 2005.
Table 7-1: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Land-Use Category 199n 1995 2000 2001 2002 2003 2004 2005
Forest Land Remaining Forest Land (598.5) (717.5) (638.7) (645.7) (688.1) (687.0) (697.3) (698.7)
1 The term "flux" is used here to encompass both emissions of greenhouse gases to the atmosphere, and removal of C from the
atmosphere. Removal of C from the atmosphere is also referred to as "carbon sequestration."
2 Carbon sequestration estimates are net figures. The C stock in a given pool fluctuates due to both gains and losses. When
losses exceed gains, the C stock decreases, and the pool acts as a source. When gains exceed losses, the C stock increases, and
the pool act as a sink. This is also referred to as net C sequestration.
Land Use, Land-Use Change, and Forestry 7-1
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Public Review Draft
Changes in Forest C Stocks1 (598.5)1
Cropland Remaining Cropland (28.1)|
Changes in Agricultural Soil C Stocks
and Liming Emissions2 (28.1)1
Land Converted to Cropland 8.71
Changes in Agricultural Soil C Stocks3 8.7 J
Grassland Remaining Grassland O.ll
Changes in Agricultural Soil C Stocks4 O.ll
Land Converted to Grassland (14.6)1
Changes in Agricultural Soil C Stocks5 (14.6)1
Settlements Remaining Settlements6 (57.5)1
Urban Trees (57.5)1
Other (23.0)|
Landfilled Yard Trimmings and Food
Scraps (23.0)|
(717.5)1
(37.4)
(37.4)
7.2
7.2
16.4
16.4
(16.3)
(16.3)
(67.8)
(67.8)
(13.0)
(13.0)
(638.7)
(645.7)
(688.1)
(687.0)
(697.3)
(698.7)
(36.5)
(38.0)
(37.8)
(38.3)
(39.4)
(39.4)
(36.5)
(38.0)
(37.8)
(38.3)
(39.4)
(39.4)
7.2
7.2
7.2
7.2
7.2
7.2
7.2
7.2
7.2
7.2
7.2
7.2
16.3
16.2
16.2
16.2
16.1
16.1
16.3
16.2
16.2
16.2
16.1
16.1
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(16.3)
(78.2)
(80.2)
(82.3)
(84.4)
(86.4)
(88.5)
(78.2)
(80.2)
(82.3)
(84.4)
(86.4)
(88.5)
(8.5)
(8.6)
(8.9)
(9.0)
(8.9)
(8.8)
(8.5)
(8.6)
(8.9)
(9.0)
(8.9)
(8.8)
Total
(712.9) (828.5) (754.7) (765.5) (809.9) (811.6) (824.9) (828.4)
Note: Parentheses indicate net sequestration. Totals may not sum due to independent rounding.
1 Estimates include C stock changes on both Forest Land Remaining Forest Land, and Land Converted to Forest Land.
2 Estimates include C stock changes in mineral soils and organic soils on Cropland Remaining Cropland, C stock changes in
organic soils on Land Converted to Cropland, and liming emissions from all managed land.
3 Estimates includes C stock changes in mineral soils only; organic soil C stock changes and liming emissions for this land
use/land-use change category are reported under Cropland Remaining Cropland.
4 Estimates include C stock changes in mineral soils and organic soils on Grassland Remaining Grassland, and C stock changes
in organic soils on Land Converted to Grassland. Liming emissions for this land use/land-use change category are reported
under Cropland Remaining Cropland.
5 Estimates include C stock changes in mineral soils only; organic soil C stock changes and liming emissions for this land
use/land-use change category are reported under Grassland Remaining Grassland and Cropland Remaining Cropland,
respectively.
6 Estimates include C stock changes on both Settlements Remaining Settlements, and Land Converted to Settlements. Liming
emissions for this land use/land-use change category are reported under Cropland Remaining Cropland.
Table 7-2: Net C02 Flux from Land Use, Land-Use Change, and Forestry (Tg C)
Land-Use Category
1990
1995
2000
2001
2002
2003
2004
2005
Forest Land Remaining Forest Land
(163.2)
(195.7)
(174.2)
(176.1)
(187.7)
(187.4)
(190.2)
(190.6)
Changes in Forest C Stocks1
(163.2)
(195.7)
(174.2)
(176.1)
(187.7)
(187.4)
(190.2)
(190.6)
Cropland Remaining Cropland
(7.7)
(10.2)
(10.0)
(10.4)
(10.3)
(10.4)
(10.7)
(10.7)
Changes in Agricultural Soil C Stocks
and Liming Emissions2
(7.7)
(10.2)
(10.0)
(10.4)
(10.3)
(10.4)
(10.7)
(10.7)
Land Converted to Cropland
2.4
2.ojj
2.0
2.0
2.0
2.0
2.0
2.0
Changes in Agricultural Soil C Stocks3
2.4
2.0
2.0
2.0
2.0
2.0
2.0
2.0
Grassland Remaining Grassland
0.0
4.5
4.4
4.4
4.4
4.4
4.4
4.4
Changes in Agricultural Soil C Stocks4
0.0
4.5
4.4
4.4
4.4
4.4
4.4
4.4
Land Converted to Grassland
(4.0)
(4.5)
(4.5)
(4.5)
(4.5)
(4.5)
(4.5)
(4.5)
Changes in Agricultural Soil C Stocks5
(4.0)
(4-5)
(4.5)
(4.5)
(4.5)
(4.5)
(4.5)
(4.5)
Settlements Remaining Settlements6
(15.7)
(18.5)
(21.3)
(21.9)
(22.4)
(23.0)
(23.6)
(24.1)
Urban Trees
(15.7)
(18-5)
(21.3)
(21.9)
(22.4)
(23.0)
(23.6)
(24.1)
Other
(6.3)
(3.5)
(2.3)
(2.3)
(2.4)
(2.5)
(2.4)
(2.4)
Landfilled Yard Trimmings and Food
Scraps
(6.3)
(3.5)
(2.3)
(2.3)
(2.4)
(2.5)
(2.4)
(2.4)
Total
(194.4)
1 (225.9)
1 (205.8)
(208.8)
(220.9)
(221.3)
(225.0)
(225.9)
Note: 1 Tg C = 1 teragram C = 1 million metric tons C. Parentheses indicate net sequestration. Totals may not sum due to
independent rounding.
1 Estimates include C stock changes on both Forest Land Remaining Forest Land, and Land Converted to Forest Land.
2 Estimates include C stock changes in mineral soils and organic soils on Cropland Remaining Cropland, C stock changes in
organic soils on Land Converted to Cropland, and liming emissions from all managed land.
3 Estimates includes C stock changes in mineral soils only; organic soil C stock changes and liming emissions for this land
use/land-use change category are reported under Cropland Remaining Cropland.
7-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
4 Estimates include C stock changes in mineral soils and organic soils on Grassland Remaining Grassland, and C stock changes
in organic soils on Land Converted to Grassland. Liming emissions for this land use/land-use change category are reported
under Cropland Remaining Cropland.
5 Estimates include C stock changes in mineral soils only; organic soil C stock changes and liming emissions for this land
use/land-use change category are reported under Grassland Remaining Grassland and Cropland Remaining Cropland,
respectively.
6 Estimates include C stock changes on both Settlements Remaining Settlements, and Land Converted to Settlements. Liming
emissions for this land use/land-use change category are reported under Cropland Remaining Cropland.
Non-C02 emissions from Land Use, Land-Use Change, and Forestry are shown in Table 7-3 and Table 7-4. The
application of synthetic fertilizers to forest and settlement soils in 2005 resulted in direct N20 emissions of 6.2 Tg
C02 Eq. (20 Gg N20). Direct N20 emissions from fertilizer application increased by approximately 19 percent
between 1990 and 2005. Non-C02 emissions from forest fires in 2005 resulted in CH4 emissions of 11.6 Tg C02
Eq. (551 Gg), and inN20 emissions of 1.2 Tg C02 Eq. (4 Gg).
Table 7-3: Non-CQ2 Emissions from Land Use, Land-Use Change, and Forestry (Tg C02 Eq.)
Land-Use Category
1990
Forest Land Remaining Forest Land
CH4 Emissions from Forest Fires
N20 Emissions from Forest Fires
N20 Emissions from Soils1
Settlements Remaining Settlements
N2Q Emissions from Soils2
Total
2000 2001 2002 2003 2004 2005
15.7
14.0
1.4
0.3
5.6
5.6
6.9
6.0
0.6
0.3
5.5
5.5
11.8
10.4
1.1
0.3
5.6
5.6
9.2
8.1
0.8
0.3
5.8
5.8
8.0
6.9
0.7
0.3
6.0
6.0
13.1
11.6
1.2
0.3
5.8
5.8
13.0
21.3
12.4
17.4
15.0
13.9
18.9
Note: These estimates include direct emissions only. Indirect N20 emissions are reported in the Agriculture chapter. Totals may
not sum due to independent rounding.
1 Estimates include emissions from N fertilizer additions on both Forest Land Remaining Forest Land, and Land Converted to
Forest Land, but not from land-use conversion.
2 Estimates include emissions from N fertilizer additions on both Settlements Remaining Settlements, and Land Converted to
Settlements, but not from land-use conversion.
Table 7-4: Non-CQ2 Emissions from Land Use, Land-Use Change, and Forestry (Gg)
Land-Use Category
199H
1995
2000
2001
2002
2003
2004
2005
Forest Land Remaining Forest Land
CH4 Emissions from Forest Fires
337
189
667
285
494
384
330
551
N20 Emissions from Forest Fires
7.11111
llllll
5
2
3
3
2
4
N20 Emissions from Soils1
oil
illiB
1
1
1
1
1
1
Settlements Remaining Settlements
¦IB
N20 Emissions from Soils2
17
18
18
18
18
19
19
19
Note: These estimates include direct emissions only. Indirect N20 emissions are reported in the Agriculture chapter. Totals may
not sum due to independent rounding.
1 Estimates include emissions from N fertilizer additions on both Forest Land Remaining Forest Land, and Land Converted to
Forest Land, but not from land-use conversion.
2 Estimates include emissions from N fertilizer additions on both Settlements Remaining Settlements, and Land Converted to
Settlements, but not from land-use conversion.
7.1. 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
Land Use, Land-Use Change, and Forestry 7-3
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Public Review Draft
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 carbon (SOC), including all organic material in soil to a depth of 1 meter but excluding
the coarse roots of the aboveground pools.
In addition, there are two harvested wood pools also necessary for estimating C flux, which are:
• Harvested wood products in use.
• Harvested wood products in solid waste disposal sites (SWDS).
C is continuously cycled among these storage pools and between forest ecosystems and the atmosphere as a result of
biological processes in forests (e.g., photosynthesis, respiration, growth, mortality, decomposition, and disturbances
such as fires or pest outbreaks) and anthropogenic activities (e.g., harvesting, thinning, clearing, and replanting). As
trees photosynthesize and grow, C is removed from the atmosphere and stored in living tree biomass. As trees age,
they continue to accumulate C until they reach maturity, at which point they store a relatively constant amount of C.
As trees die and otherwise deposit litter and debris on the forest floor, C is released to the atmosphere or transferred
to the soil by organisms that facilitate decomposition.
The net change in forest C is not equivalent to the net flux between forests and the atmosphere because timber
harvests do not cause an immediate flux of C to the atmosphere. Instead, harvesting transfers C to a "product pool."
Once in a product pool, the C is emitted over time as C02 when the wood product combusts or decays. The rate of
emission varies considerably among different product pools. For example, if timber is harvested to produce energy,
combustion releases C immediately. Conversely, if timber is harvested and used as lumber in a house, it may be
many decades or even centuries before the lumber decays and C is released to the atmosphere. If wood products are
disposed of in 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. Thus, the focus on C implies that all C-based greenhouse gases are included, and the focus on stock
change suggests that specific ecosystem fluxes do not need to be separately itemized in this report. Disturbances
from forest fires and pest outbreaks are implicitly included in the net changes. For instance, an inventory conducted
after fire counts only trees left. The change between inventories thus accounts for the C changes due to fires;
however, it may not be possible to attribute the changes to the disturbance specifically. The IPCC (2003)
recommends reporting C stocks according to several land-use types and conversions, specifically Forest Land
Remaining Forest Land and Land Converted to Forest Land. Currently, consistent datasets are not available for the
entire United States to allow results to be partitioned in this way. Instead, net changes in all forest-related land,
including non-forest land converted to forest and forests converted to non-forest are reported here.
Forest C storage pools, and the flows between them via emissions, sequestration, and transfers, are shown in Figure
7-1. In the figure, boxes represent forest C storage pools and arrows represent flows between storage pools or
between storage pools and the atmosphere. Note that the boxes are not identical to the storage pools identified in
this chapter. The storage pools identified in this chapter have been altered in this graphic to better illustrate the
processes that result in transfers of C from one pool to another, and emissions to the atmosphere as well as uptake
from the atmosphere.
Figure 7-1: Forest Sector Carbon Pools and Flows
Approximately 33 percent (303 million hectares) of the U.S. land area is forested, of which approximately 250
7-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Public Review Draft
million hectares are located in the conterminous 48 states. An additional 52 million hectares are located in Alaska
and Hawaii, though this inventory does not currently account for these stocks and fluxes due to data limitations.
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. Alaska has over 50 million hectares of forest land, however, and more efforts will be
made to account for this area in the future (see Planned Improvements for more details). Agroforestry systems are
also not currently accounted for in the U.S. 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 (USD A) Forest Service and the National Resources Inventory (NRI) of the USD A
Natural Resources Conservation Service (Perry et al. 2005).
Seventy-nine percent of the 250 million hectares are classified as timberland, meaning they meet minimum levels of
productivity and are available for timber harvest. Historically, the timberlands in the conterminous 48 states have
been more frequently or intensively surveyed than other forest lands. Of the remaining 51 million hectares, 16
million hectares are reserved forest lands (withdrawn by law from management for production of wood products)
and 35 million hectares are lower productivity forest lands (Smith et al. 2004b). From the early 1970s to the early
1980s, forest land declined by approximately 2.4 million hectares. During the 1980s and 1990s, forest area
increased by about 3.7 million hectares. These net changes in forest area represent average annual fluctuations of
only about 0.1 percent. Given the low rate of change in U.S. forest land area, the major influences on the current
net C flux from forest land are management activities and the ongoing impacts of previous land-use changes. These
activities affect the net flux of C by altering the amount of C stored in forest ecosystems. For example, intensified
management of forests can increase both the rate of growth and the eventual biomass density of the forest, thereby
increasing the uptake of C.3 Harvesting forests removes much of the aboveground C, but trees can grow on this
area again and sequester C. The reversion of cropland to forest land increases C storage in biomass, forest floor,
and soils. The net effects of forest management and the effects of land-use change involving forest land are
captured in the estimates of C stocks and fluxes presented in this chapter.
In the United States, improved forest management practices, the regeneration of previously cleared forest areas, as
well as timber harvesting and use have resulted in net uptake (i.e., net sequestration) of C each year from 1990
through 2005. Due to improvements in U.S. agricultural productivity, the rate of forest clearing for crop cultivation
and pasture slowed in the late 19th century, and by 1920, this practice had all but ceased. As farming expanded in
the Midwest and West, large areas of previously cultivated land in the East were taken out of crop production,
primarily between 1920 and 1950, and were allowed to revert to forests or were actively reforested. The impacts of
these land-use changes still affect C fluxes from forests in the East. In addition, C fluxes from eastern forests have
been affected by a trend toward managed growth on private land. Collectively, these changes have nearly doubled
the biomass density in eastern forests since the early 1950s. More recently, the 1970s and 1980s saw a resurgence
of federally-sponsored forest management programs (e.g., the Forestry Incentive Program) and soil conservation
programs (e.g., the Conservation Reserve Program), which have focused on tree planting, improving timber
management activities, combating soil erosion, and converting marginal cropland to forests. In addition to forest
regeneration and management, forest harvests have also affected net C fluxes. Because most of the timber harvested
from U.S. forests is used in wood products, and many discarded wood products are disposed of in SWDS rather
than by incineration, significant quantities of C in harvested wood are transferred to long-term storage pools rather
than being released rapidly to the atmosphere (Skog and Nicholson 1998, Skog 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 698.7 Tg
C02 Eq. (190.6 Tg C) in 2005 (Table 7-5, Table 7-6, and Figure 7-2). In addition to the net accumulation of C in
harvested wood pools, sequestration is a reflection of net forest growth and increasing forest area over this period,
though the increase in forest sequestration is due more to an increasing C density per area than to the increase in
area of forest land. Forest land in the conterminous United States was approximately 246, 250, and 251 million
3 The term "biomass density" refers to the mass of vegetation per unit area. It is usually measured on a dry-weight basis. Dry
biomass is 50 percent carbon by weight.
Land Use, Land-Use Change, and Forestry 7-5
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Public Review Draft
hectares for 1987, 1997, and 2002, respectively, which amounts to only a 2 percent increase over the period (Smith
et al. 2004b). Continuous, regular annual surveys are not available over the period for each state; therefore,
estimates for non-survey years were derived by interpolation between known data points. Survey years vary from
state to state. National estimates are a composite of individual state surveys. Total sequestration increased by 17
percent between 1990 and 2005 (see Recalculations Discussion). Estimated sequestration in the aboveground
biomass C pool had the greatest effect on total change. This was primarily due to an increase in the rate of net C
accumulation as density, or the rate of change in tonnes of C per hectare per year, approximately a 21 percent
increase over the 1990 through 2005 time series. This increase is particularly evident for the aboveground and
belowground tree biomass pools, for which rate of C accumulation increased by about 37 percent.
Table 7-5. Net Annual Changes in C Stocks (Tg C02/yr) in Forest and Harvested Wood Pools
Carbon Pool
1990
Forest
(466.5)
Aboveground Biomass
(251.8)
Belowground Biomass
(63.9)
Dead Wood
(36.7)
Litter
(65.6)
Soil Organic Carbon
(48.5)
Harvested Wood
(132.0)
Products in use
(63.1)
SWDS
(68.9)
19951
Total Net Flux
(598.5),
(602.0)1
(331.0)
(69.8)
(60.9)
(49.5)
(90.8)
(115.5)
(53.5)
(62.0)
(717.5)
2000
2001
2002
2003
2004
2005
(529.4)
(555.5)
(595.3)
(595.3)
(595.3)
(595.3)
(347.1)
(360.4)
(376.4)
(376.4)
(376.4)
(376.4)
(73.9)
(76.4)
(79.5)
(79.5)
(79.5)
(79.5)
(48.2)
(50.0)
(52.4)
(52.4)
(52.4)
(52.4)
(35.8)
(47.1)
(52.2)
(52.2)
(52.2)
(52.2)
(24.5)
(21.6)
(34.8)
(34.8)
(34.8)
(34.8)
(109.3)
(90.2)
(92.8)
(91.7)
(101.9)
(103.4)
(46.2)
(31.2)
(34.1)
(33.4)
(43.3)
(44.4)
(63.1)
(59.0)
(58.7)
(58.3)
(58.7)
(59.0)
(638.7)
(645.7)
(688.1)
(687.0)
(697.3)
(698.7)
Note: Forest C stocks do not include forest stocks in Alaska, Hawaii, or U.S. territories, or trees on non-forest land (e.g., urban
trees, 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 7-6. 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
Forest
(127.2)
(164.2)
(144.4)
(151.5)
(162.4)
(162.4)
(162.4)
(162.4)
Aboveground Biomass
(68.7)
(90.3)
(94.7)
(98.3)
(102.7)
(102.7)
(102.7)
(102.7)
Belowground Biomass
(17.4)
(19.0)
(20.1)
(20.8)
(21.7)
(21.7)
(21.7)
(21.7)
Dead Wood
(10.0)
(16.6) '
(13.1)
(13.6)
(14.3)
(14.3)
(14.3)
(14.3)
Litter
(17.9)
(13.5)
(9.8)
(12.9)
(14.2)
(14.2)
(14.2)
(14.2)
Soil Organic Carbon
(13.2)
(24.8)
(6.7)
(5.9)
(9.5)
(9.5)
(9.5)
(9.5)
Harvested Wood
(36.0)
(31.5)
(29.8)
(24.6)
(25.3)
(25.0)
(27.8)
(28.2)
Products in use
(17.2)
(14.6)
(12.6)
(8.5)
(9.3)
(9.1)
(11.8)
(12.1)
SWDS
(18.8)
(16.9) '
(17.2)
(16.1)
(16.0)
(15.9)
(16.0)
(16.1)
Total Net Flux
(163.2)
I (195.7)
(174.2)
(176.1)
(187.7)
(187.4)
(190.2)
(190.6)
Note: Forest C stocks do not include forest stocks in Alaska, Hawaii, or U.S. territories, or trees on non-forest land (e.g., urban
trees, agroforestry systems). Parentheses indicate net C sequestration (i.e., a net removal of C from the atmosphere). Total net
flux is an estimate of the actual net flux between the total forest C pool and the atmosphere. Harvested wood estimates are based
on results from annual surveys and models. Totals may not sum due to independent rounding.
Stock estimates for forest and harvested wood C storage pools are presented in Table 7-7. Together, the
aboveground live and forest soil pools account for a large proportion of total forest C stocks. C stocks in all non-
soil pools increased over time. Therefore, C sequestration was greater than C emissions from forests, as discussed
above. Figure 7-3 shows county-average C densities for live trees on forest land, including both above- and
belowground biomass.
Table 7-7. Forest area (1000 ha) and C Stocks (Tg C) in Forest and Harvested Wood Pools
1990 1995j| 2000 2001 2002 2003 2004 2005 2006
Forest Area (1000 ha) 242,300^245,946 250,275 251,110 251,977 252,879 253,782 254,684 255,587
7-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
Carbon Pools (Tg C)
Forest 39,026 39,762® 40,576 40,721 40,872 41,035 41,197 41,359 41,522
Aboveground Biomass 14,164 14,565 15,031 15,125 15,224 15,326 15,429 15,532 15,634
Belowground Biomass 2,794 2,885 2,983 3,003 3,024 3,045 3,067 3,089 3,110
Dead Wood 2,354 2>418il 2A" 2>512 2>526 2>540 2>555 2>569 2>583
Litter 4,404 4,497 4,559 4,569 4,582 4,596 4,610 4,625 4,639
Soil Organic C 15,310 15>3981| 15>505 15>511 15>517 15>527 15>536 15>546 15>555
Harvested Wood 1,888 2,067 2,225 2,255 2,287 2,317 2,341 2,367 2,395
Products in use 1,184 i'268!! !>341 !>354 !>368 !>381 !>389 !>399 M11
SWDS 704 799 884 901 919 936 952 968 984
Total C Stock 40,914 41,829|1 42,801 42,976 43,159 43,352 43,538 43,726 43,917
Note: Forest area estimates are based on interpolation and extrapolation of inventory data as described in the text and in Annex
3.12. Forest C stocks do not include forest stocks in Alaska, Hawaii, or U.S. territories, or trees on non-forest land (e.g., urban
trees, 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 the text and in
Annex 3.12. Harvested wood estimates are based on results from annual surveys and models. Totals may not sum due to
independent rounding. Inventories are assumed to represent stocks as of January 1 of the inventory year. Flux is the net annual
change in stock. Thus, an estimate of flux for 2005 requires estimates of C stocks for 2005 and 2006.
Figure 7-2: Estimates of Net Annual Changes in C Stocks for Major C Pools
Figure 7-3: Average C Density in the Forest Tree Pool in the Conterminous United States During 2005
[BEGIN BOX]
Box 7-1: C02 Emissions from Forest Fires
As stated previously, the forest inventory approach implicitly accounts for emissions due to disturbances such as
forest fires, because only C remaining in the forest is estimated. Net C stock change is estimated by subtracting
consecutive C stock estimates. A disturbance removes C from the forest. The inventory data on which net C stock
estimates are based already reflect this C loss. Therefore, estimates of net annual changes in C stocks for U.S.
forestland already account for C02 emissions from forest fire, but only for the lower 48 states. As detailed
previously, Alaska is not yet included in national estimates of forest C stocks and fluxes, due to lack of forest
inventory data at this time (see Planned Improvements). Wildfire data is, however, available for Alaska, so it has
been included in these calculations. Because it is of interest to quantify the magnitude of C02 emissions from fire
disturbance, these estimates are being highlighted here, using the full extent of available data. Non-C02 greenhouse
gas emissions from forest fires are also quantified in a separate section below.
The IPCC (2003) methodology was employed to estimate C02 emissions from forest fires. C02 emissions for the
lower 48 states and Alaska in 2005 were estimated to be 126.4 Tg C02/yr. This amount is masked in the estimates
of total flux for 2005, however, by an additional 126.4 Tg C02/yr being sequestered (i.e., flux already accounts for
the amount sequestered minus any emissions).
Table 7-8: Estimates of C02 (Tg/yr) emissions for the lower 48 states and Alaska1
C02 emitted in C02 emitted in Total C02
the Lower 48 Alaska emitted
Year States (Tg/yr) (Tg/yr) (Tg/yr)
1990 42.7 34.5 77.2
1995 42.9 0.5 43.3
Land Use, Land-Use Change, and Forestry 7-7
-------
Public Review Draft
2000
144.6
8.2
152.8
2001
63.0
2.4
65.3
2002
89.7
23.6
113.3
2003
81.4
6.5
87.9
2004
5.0
70.6
75.6
2005
75.9
50.5
126.4
Note that these emissions have already been accounted for in the net C sequestration estimates (i.e., net flux already accounts
for the amount sequestered minus any emissions).
[END BOX]
7 Methodology
8 The methodology described herein is consistent with IPCC (2003) and IPCC/UNEP/OECD/IEA (1997). Estimates
9 of net annual C stock change, or flux, of forest ecosystems are derived from applying C estimation factors to forest
10 inventory data and interpolating between successive inventory-based estimates of C stocks. C emissions from
11 harvested wood are based on factors such as the allocation of wood to various primary and end-use products as well
12 as half-life (the time at which half of amount placed in use will have been discarded from use) and expected
13 disposition (e.g., product pool, SWDS, combustion). Different data sources are used to estimate the C stocks and
14 stock change in forest ecosystems or harvested wood products. See Annex 3.12 for details and additional
15 information related to the methods described below.
16 Forest Carbon Stocks and Fluxes
17 The first step in developing forest ecosystem estimates is to identify useful inventory data and resolve any
18 inconsistencies among datasets. Forest inventory data were obtained from the USD A Forest Service, Forest
19 Inventory and Analysis (FIA) program (Frayer and Furnival 1999, USDA Forest Service 2006a). Inventories
20 include forest lands4 of the conterminous United States and are organized as a number of separate datasets, each
21 representing a complete inventory, or survey, of an individual state at a specified time. Forest C calculations are
22 organized according to these state surveys, and the frequency of surveys varies by state. To calculate a C stock
23 change, at least two surveys are needed in each state. Thus, the most recent surveys for each state are used as well
24 as all additional consistent inventory data back through 1990. Because C flux is based on change between
25 successive C stocks, consistent representation of forest land in successive inventories is necessary. In order to
26 achieve accurate representation of forests from 1990 to the present, sometimes state-level data are subdivided or
27 additional inventory sources are used to produce the consistent state or sub-state inventories.
28 The principal FIA forest inventory datasets employed are freely available for download at USDA Forest Service
29 (2006b) as the Forest Inventory and Analysis Database (FIADB) Version 2.1. These data are identified as
30 "snapshot" files, also identified as FISDB 2.1, and include detailed plot information, including individual-tree data.
31 However, to achieve consistent representation (spatial and temporal), two other general sources of past FIA data are
32 included as necessary. Firstly, older FIA plot- and tree-level data—not in the FIADB format—are used if available.
33 Secondly, Resources Planning Act Assessment (RPA) databases, which are periodic, plot-level only, summaries of
34 state inventories, are used mostly to provide the data at or before 1990. A detailed list of the specific inventory data
35 used here is in Table A-188 of Annex 3.12.
4 Forest land in the United States includes land that is at least 10 percent stocked with trees of any size. Timberland is the most
productive type of forest land, which is on unreserved land and is producing or capable of producing crops of industrial wood.
7-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Public Review Draft
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 in preparation).
The conversion factors and model coefficients are usually categorized by region and forest type, and forest C stock
estimates are dependent on these particular sets of factors. Factors are applied to the data at the scale of FIA
inventory plots. The results are estimates of C density (Mg per hectare) for the various forest pools. C density for
live trees, standing dead trees, understory vegetation, down dead wood, forest floor, and soil organic matter are
estimated. All non-soil pools except forest floor can be separated into aboveground and belowground components.
The live tree and understory C pools are pooled as biomass in this inventory. Similarly, standing dead trees and
down dead wood are pooled as dead wood in this inventory. Definitions of ecosystem pools and the C conversion
process follow, with additional information in Annex 3.12.
Live Biomass, Dead Wood, and Litter Carbon
Live tree C pools include aboveground and belowground (coarse root) biomass of live trees with diameter at
diameter breast height (d.b.h.) of at least 2.54 cm at 1.37 m above the forest floor. Separate estimates are made for
full-tree and aboveground-only biomass in order to estimate the belowground component. If inventory plots include
data on individual trees, tree C is based on Jenkins et al. (2003) and is a function of species and diameter. Some
inventory data do not provide measurements of individual trees; tree C in these plots is estimated from plot-level
volume of merchantable wood, or growing-stock volume, of live trees, which is calculated from updates of Smith et
al. (2003). Some inventory data, particularly some of the older datasets, may not include sufficient information to
calculate tree C because of incomplete or missing tree or volume data; C estimates for these plots are based on
averages from similar, but more complete, inventory data.
Understory vegetation is a minor component of biomass, which is defined as all biomass of undergrowth plants in a
forest, including woody shrubs and trees less than 2.54 cm d.b.h. In this inventory, it is assumed that 10 percent of
total understory C mass is belowground. Estimates of C density are based on information in Birdsey (1996).
The two components of dead wood—standing dead trees and down dead wood—are estimated separately. The
standing dead tree C pools include aboveground and belowground (coarse root) mass and include trees of at least
2.54 cm d.b.h. Down dead wood is defined as pieces of dead wood greater than 7.5 cm diameter, at transect
intersection, that are not attached to live or standing dead trees. Down dead wood includes stumps and roots of
harvested trees. Ratios of down dead wood to live tree are used to estimate this quantity. Litter C is the pool of
organic C (also known as duff, humus, and fine woody debris) above the mineral soil and includes woody fragments
with diameters of up to 7.5 cm. Estimates are based on equations of Smith and Heath (2002).
Forest Soil C
Soil organic carbon (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 (2003). 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 2005 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 2002 through 2005 on
Table 7-5 as an example).
Land Use, Land-Use Change, and Forestry 7-9
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
Public Review Draft
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 are based on the methods suggested in IPCC (2006) for estimating HWP carbon. The United States uses the
production accounting approach to report HWP Contribution. This means that 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 the
production approach is used in this inventory, 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 in four HWP summary quantities are calculated by tracking the additions to and removals from
the pool of products held in end uses (i.e., products in use such as housing or publications, and the pool of products
held in solid waste disposal sites (SWDS)). These four categories of annual change of C in wood and paper
products are 1) all products in use in the United States; 2) all products in SWDS in the United States; 3) products in
use in the United States and other countries where the wood came from trees harvested in the United States; and 4)
products in SWDS in the United States and other countries where the wood came from trees harvested in the United
States.
Solidwood products added to pools include lumber and panels. End-use categories for solidwood include single and
multifamily housing, alteration and repair of housing, and other end-uses. There is one product category and one
end-use category for paper. Additions to and removals from pools are tracked beginning in 1900, with the
exception that additions of softwood lumber to housing begins in 1800. Solidwood and paper product production
and trade data are from USD A 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.
Summary categories 3 and 4 (above) are used to estimate 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 forest survey data that underlie the forest C estimates are based on a statistical sample designed to represent the
wide variety of growth conditions present over large territories. The USD A Forest Service inventories are designed
to be accurate within 3 percent at the 67 percent confidence level (one standard error) per 405,000 ha (1 million
acres) of timberland (USDA Forest Service 2006c). For larger areas, the uncertainty in area is concomitantly
smaller, and precision at plot levels is larger. An analysis of uncertainty in growing stock volume data for timber
producing land in the Southeast by Phillips et al. (2000) found that nearly all of the uncertainty in their analysis was
due to sampling rather than the regression equations used to estimate volume from tree height and diameter. The
quantitative uncertainty analysis summarized here (and in Table 7-9) primarily focuses on uncertainties associated
with the estimates of specific C stocks at the plot level and does not address error in tree diameters or volumes.
Estimates for stand-level C pools are derived from extrapolations of site-specific studies to all forest land, because
survey data on these pools are not generally available. Such extrapolation introduces uncertainty because available
studies may not adequately represent regional or national averages. Uncertainty may also arise due to: (1) modeling
errors (e.g., relying on coefficients or relationships that are not well known); and (2) errors in converting estimates
from one reporting unit to another (Birdsey and Heath 1995). An important source of uncertainty is that there is
little consensus from available data sets on the effect of land-use change and forest management activities (such as
harvest) on soil C stocks. For example, while Johnson and Curtis (2001) found little or no net change in soil C
following harvest, on average, across a number of studies, many of the individual studies did exhibit differences.
Heath and Smith (2000) noted that the experimental design in a number of soil studies limited their usefulness for
determining effects of harvesting on soil C. Because soil C stocks are large, estimates need to be very precise, since
even small relative changes in soil C sum to large differences when integrated over large areas. The soil C stock
and stock change estimates presented here are based on the assumption that soil C density for each broad forest type
7-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
group stays constant over time. The state of information and modeling are improving in this regard (Woodbury et
al. 2006); the effects of land use and of changes in land use and forest management will be better accounted for in
future estimates of soil C.
Uncertainty in estimates about the HWP Contribution is based on Monte Carlo simulation of the production
approach. The uncertainty analysis is based on Skog et al. (2004). However, the uncertainty analysis simulation
has been revised in conjunction with overall revisions in the HWP model (Skog in preparation). The analysis
includes an evaluation of the effect of uncertainty in 13 sources including production and trade data, factors to
convert products to quantities of C, rates at which wood and paper are discarded, and rates and limits for decay of
wood and paper in SWDS.
The 2005 flux estimate forforest C stocks is estimated to be between -513.1 and -889.5 Tg C02 Eq. at a 95 percent
confidence level. This includes a range of -410.5 to -785.2 Tg C02 Eq. in forest ecosystems and -78.9 to -130.2 Tg
C02 Eq. for HWP. The relatively smaller range of uncertainty, in terms of percentage, for the total relative to the
two separate parts in because the total is based on summing the two independent uncertain parts, as discussed
above.
Table 7-9: Tier 2 Quantitative Uncertainty Estimates for Net C02 Flux from Forest Land Remaining Forest Land:
Changes in Forest C Stocks (Tg C02 Eq. and Percent)
2005 Flux
Source
Gas
Estimate
Uncertainty Range Relative to Flux Estimate"
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Forest Ecosystem
Harvested Wood Products
C02
co2
(595.3)
(103.4)
(785.2)
(130.2)
(410.5)
(78.9)
-32%
-26%
+31%
+24%
Total Forest
co2
(698.7)
(889.5)
(513.1)
-27%
+27%
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.
QA/QC and Verification
As discussed above, the FIA program has conducted consistent forest surveys based on extensive statistically-based
sampling of most of the forest land in the conterminous United States, dating back to 1952. The main purpose of
the FIA program has been to estimate areas, volume of growing stock, and timber products output and utilization
factors. The FIA program includes numerous quality assurance and quality control (QA/QC) procedures, including
calibration among field crews, duplicate surveys of some plots, and systematic checking of recorded data. Because
of the statistically-based sampling, the large number of survey plots, and the quality of the data, the survey
databases developed by the FIA program form a strong foundation for C stock estimates. Field sampling protocols,
summary data, and detailed inventory databases are archived and are publicly available on the Internet (USDA
Forest Service 2006b).
Many key calculations for estimating current forest C stocks based on FIA data are based on coefficients from the
FORCARB2 model (see additional discussion in the Methodology section above and in Annex 3.12). The model
has been used for many years to produce national assessments of forest C stocks and stock changes. General quality
control procedures were used in performing calculations to estimate C stocks based on survey data. For example,
the derived C datasets, which include inventory variables such as areas and volumes, were compared with standard
inventory summaries such as Resources Planning Act (RPA) Forest Resource Tables or selected population
estimates generated from the FIA Database (FIADB), which are available at an FIA Internet site (USDA Forest
Service 2006b). Agreement between the C datasets and the original inventories is important to verily 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).
Land Use, Land-Use Change, and Forestry 7-11
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
Public Review Draft
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 the 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 scheme for developing annualized estimates of forest ecosystem C stocks based on the individual state
surveys and the C conversion factors used are similar to that presented in the previous inventory (EPA 2006). The
principal change from the previous year's methods involves the increased use of sub-state classification of the
survey data as indicated in Table A-188 in Annex 3.12, which details the survey data used for the current inventory.
For the current inventory, the emphasis was on improving consistency between successive surveys or portions of
surveys when sub-state portions of inventory data provided better continuity. The FIADB "snapshot" datasets were
the primary source of FIA inventory data. Secondary sources included the plot and tree data from older, pre-
FIADB, inventories and the plot-level RPA datasets. By improving the consistency of these datasets, substantial
revisions were made to previous estimates, which primarily affected early years in the calculations. The new
calculations of forest C stocks in 1990 decreased the estimate of C sequestration by 23 percent (174.9 Tg C02 Eq.),
while increasing C sequestration estimates for forest C stocks in 2004 by 9 percent (60.1 Tg C02 Eq.).
The change in stock and flux estimates for the period since 1990, as compared to the estimates presented in the
previous inventory, is based on the cumulative effects of 1) additional inventory data, and 2) how the state or sub-
state inventories are classified. State-level inventory data changed more dramatically for some particular states as
compared to others. As an example, stock and flux estimates for the state of California are based on the FIA
datasets specified in Table A-188 in Annex 3.12. In past inventories (for example, EPA 2006), chaparral
ecosystems were included in forest inventory data and, therefore, forest C stock estimates. However, much of this
ecological community type fails to meet the definition of forestland. Current FIA forest inventory data does not
include non-forest land of this ecological community. In order to maintain consistency across the time series, non-
forest chaparral estimates had to be removed from California's total stock estimates in earlier inventories. This
caused a dramatic decrease in forest C stock estimates at the early part of the time series for the state of California
compared to those California estimates used for the previous inventory submission.
The estimate of HWP contribution under the production account approach has been revised. Estimates of 5 HWP
variables have been added, which allow estimates using alternate accounting approaches. The basic method used to
estimate the HWP variables has not changed—tracking additions to and removals from pools—but more detailed
product and trade data are used and discard and decay parameters have been revised. With use of more detailed
production and trade data and modification in half lives for solidwood and paper product in use (to meet calibration
criteria), the estimates of C additions to product in use (under the production approach) varies differently from year
to year. Average annual total additions due to HWP from the period 1990 through 2004 (111 Tg C02 Eq.) is about
47 percent less than the previous estimate of 209 Tg C02 Eq. The estimate of total C in products in use in 2004 has
increased from 1344 Tg to 1389 Tg. Changes have been greater for estimates of C additions to SWDS. Estimates
of the fractions of discarded wood going to landfills and dumps were revised using data from EPA (2006 and prior
years), Melosi (1981, 2000) and other sources. Estimates of the fraction of wood and paper not subject to decay in
landfills were revised, based on Freed and Mintz (2003), using data from studies by Eleazer et al. (1997) and Barlaz
(1998). The estimated fraction of C in wood subject to decay in landfills was revised from 3 percent to 23 percent,
while the estimated fraction of C in paper subject to decay in landfills increased from 26 percent to 56 percent.
Those fractions of wood and paper not subject to decay, therefore, decreased. Previous estimates of wood and
7-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Public Review Draft
paper subject to decay in landfills had been based on Micales and Skog (1997). Estimates of the rates of decay in
landfills and dumps were also updated to 29 years and 14.5 years, respectively, using values from IPCC (2006).
These half-lives are the midpoints of the estimated ranges of decay for wood and paper in temperate regions. The
estimate of total C additions in SWDS over the period 1990 through 2004 decreased from 630 Tg to 256 Tg.
Overall, the estimate of C additions under the production accounting approach over the period 1990 to 2004 has
decreased from 857 Tg to 455 Tg, or 47 percent.
Another change in the current inventory is the inclusion of estimates of C emissions caused by fire disturbance.
Although these emissions are implicitly included in total forest C flux estimates, expert and public reviews of
previous inventories indicated an interest in the magnitude of this flux. An estimate of C emissions was, therefore,
calculated and included in Box 7-1 in the current inventory. C emissions caused by fire disturbance are still
implicitly included as part of the overall forest C flux estimate, and, thus, not treated as a separate estimate in the
current inventory.
Non-C02 emissions from forest fires is a new source included in the current inventory. CH4 and N20 emissions
resulting from forest fires were not previously calculated, but these estimates are now included in their own
subsection of Forest Land Remaining Forest Land.
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. Therefore, inventory-
based estimates of net annual flux for Alaska will become available, starting with the more productive forest in the
southeastern portion of the state. Forest inventory data is limited in Alaska and, in the past, a net C change of zero
was assumed. Alaska has over 50 million hectares of forest land, however, and could have a significant effect on
estimates of total C emissions and sinks. A review of the scientific literature indicates Alaskan forests could change
U.S. national forest C flux estimates by -5 to 10 percent (not including harvested wood). In addition, the more
intensive sampling of down dead wood, litter, and soil organic C on some of the permanent FIA plots will
substantially improve resolution of C pools at the plot level for all U.S. forest land.
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). Currently, soil C estimates are based on the assumption that soil C density depends only on broad forest type
group, not on land-use history. However, many forests in the Eastern United States are re-growing on abandoned
agricultural land. During such regrowth, soil and forest floor C stocks often increase substantially over many years
or even decades, especially on highly eroded agricultural land. In addition, with deforestation, soil C stocks often
decrease over many years. A new methodology is being developed to account for these changes in soil C over time.
This methodology includes estimates of area changes among land uses (especially forest and agriculture), estimates
of the rate of soil C stock gain with afforestation, and estimates of the rate of soil C stock loss with deforestation
over time. This topic is important because soil C stocks are large, and soil C flux estimates contribute substantially
to total forest C flux.
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 into a nation-
wide inventory, as well as the means for entity-level reporting.
An additional planned improvement is to develop a consistent representation of the U.S. managed land base.
Currently, the forest C and the agricultural soil C inventories are the two major analyses addressing land-use and
management impacts on C stocks. The forest inventory relies on the activity data from the FIA Program to estimate
anthropogenic impacts on forest land, while the agricultural soil C inventory relies on the USD A National
Resources Inventory (NRI). Recent research has revealed that the classification of forest land is not consistent
between the FIA and NRI, leading to some double-counting and gaps in the current forest C and agricultural soil C
inventories (e.g., some areas classified as forest land in the FIA are considered rangeland in the NRI).
Consequently, the land bases are in the process of being compared between the inventories to determine where
Land Use, Land-Use Change, and Forestry 7-13
-------
Public Review Draft
1 overlap or gaps occur, and then ensure that the inventories are revised to have a consistent and complete accounting
2 of land-use and management impacts across all managed land in the United States.
3 Non-C02 Emissions From Forest Fires
4 Emissions of non-C02 gases from forest fires were estimated using the default IPCC (2003) methodology.
5 Emissions from this source in 2005 were estimated to be 11.6 Tg C02 Eq.of CH4 and 1.2 Tg C02 Eq. of N20, as
6 shown in Table 7-10 and Table 7-11. The non-C02 estimates of forest fire emissions account for both the lower 48
7 states and Alaska, while the national inventory estimates of forest C stocks and fluxes currently include only the
8 conterminous states.
9 Table 7-10: Estimated Non-CQ2 Emissions from Forest Fires (Tg C02 Eq.) for U.S. forests1
Gas 1990 1995 2000 2001 2002 2003 2004 2005
CH4 7 1 4 0 14.0 6.0 10.4 8.1 6.9 11.6
N2Q 0J 04 1.4 0.6 1.1 0.8 0.7 1.2
Total 7.8 4.4 15.4 6.6 11.4 8.9 7.6 12.8
10 1 Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003).
11
12 Table 7-11: Estimated Non-CQ2 Emissions from Forest Fires (Gg Gas) for U.S. forests1
Gas 1990 1995 2000 2001 2002 2003 2004 2005
CH4 337 189 667 285 494 384 330 551
N2Q : 1 5 2 3 3 2 4
13 1 Calculated based on C emission estimates in Changes in Forest Carbon Stocks and default factors in IPCC (2003).
14
15 Methodology
16 The IPCC (2003) Tier 2 default methodology was used to calculate non-C02 emissions from forest fires. Estimates
17 for CH4 emissions were calculated by multiplying the total estimated C emitted (see Table 7-12) from forest burned
18 by gas-specific emissions ratios and conversion factors. N20 emissions were calculated in the same manner, but
19 were also multiplied by a N-C ratio of 0.01 as recommended by IPCC (2003). The equations used were:
20 CH4 Emissions = (C released) x (emission ratio) x 16/12
21 N20 Emissions = (C released) x (N/C ratio) x (emission ratio) x 44/28
22 Estimates for C emitted from forest fires, presented in Table 7-12 below, are the same estimates used to generate
23 estimates of C02 emissions from forest fires, presented earlier in Box 7-1. See Table A-197 and explanation in
24 Annex 3.12 for more details on the methodology used to estimate C emitted from forest fires.
25 Table 7-12: Estimated Carbon Released from Forest Fires for U.S. Forests
Year C Emitted (Tg/yr)
1990 21.1
1995
2000 41.7
2001 17.8
2002 30.9
2003 24.0
2004 20.6
200 5 34.5
26
27 Uncertainty
28 Non-C02 gases emitted from forest fires depend on several variables, including forest area and average C density
7-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
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 the information provided above. The results of the Tier 2 quantitative
uncertainty analysis are summarized in Table 7-14.
Table 7-13: Tier 2 Quantitative Uncertainty Estimates of Non-C02 Emissions from Forest Fires in Forest Land
Remaining Forest Land (Tg C02 Eq. and Percent)
2005 Emission
Uncertainty Range Relative to
Source
Gas
Estimate
Emission Estimate
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Upper
Lower Upper
Bound
Bound
Bound Bound
Non-C02 Emissions from Forest Fires
ch4
11.6
3.2
21.5
-71% 92%
n2o
1.2
0.3
2.2
-70% 93%
Direct N20 Fluxes from Forest Soils (IPCC Source Category 5A1)
Of the synthetic N fertilizers applied to soils in the United States, no more than one percent is applied to forest soils.
Application rates are similar to those occurring on cropped soils, but in any given year, only a small proportion of
total forested land receives N fertilizer. This is because forests are typically fertilized only twice during their
approximately 40-year growth cycle (once at planting and once approximately 20 years later). Thus, although the
rate of N fertilizer application for the area of forests that receives N fertilizer in any given year is relatively high,
average annual applications, inferred by dividing all forest land that may undergo N fertilization at some point
during its growing cycle by the amount of N fertilizer added to these forests in a given year, is quite low. Nitrous
oxide emissions from forest soils are estimated to have increased by a multiple of 5.5 from 1990 to 2005. The trend
toward increasing N20 emissions is a result of an increase in the area of N fertilized pine plantations in the
southeastern United States. Total forest soil N20 emissions are summarized in Table 7-14.
Table 7-14. N2Q Fluxes from Soils in Forest Land Remaining Forest Land (Tg C02 Eq. and Gg)
Year Tg CP2 Eq. Gg
1990
0.1
<1
199^
0.2
2000
2001
2002
2003
2004
2005
0.3
0.3
0.3
0.3
0.3
0.3
Note: These estimates include direct N20 emissions from N fertilizer additions only. Indirect N20 emissions from fertilizer
additions are reported in the Agriculture chapter. These estimates include emissions from both Forest Land Remaining Forest
Land and from Land Converted to Forest Land.
Methodology
The IPCC Tier 1 approach was used to estimate N20 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. Consequently, it was assumed that southeastern pine plantations represent the vast majority of fertilized
forests in the United States. Therefore, estimates of direct N20 emissions from fertilizer applications to forests were
based on the area of pine plantations receiving fertilizer in the 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).
Land Use, Land-Use Change, and Forestry 7-15
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
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 be insubstantial because the
majority of trees planted and harvested for timber are in the southeastern United States (USD A Forest Service
2001). Area data for pine plantations receiving fertilizer in the Southeast were not available for 2002, 2003, 2004,
and 2005, 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 N20 emissions. The volatilization and leaching/runoff
fractions, calculated according to the IPCC default factors of 10 percent and 30 percent, respectively, were included
with all sources of indirect emissions in the Agricultural Soil Management source category of the Agriculture
chapter.
Uncertainty
The amount of N20 emitted from forests depends not only on N inputs, but also on a large number of variables,
including organic C availability, 02 partial pressure, soil moisture content, pH, temperature, and tree
planting/harvesting cycles. The effect of the combined interaction of these variables on N20 flux is complex and
highly uncertain. The IPCC default methodology used here does not incorporate any of these variables and only
accounts for variations in estimated fertilizer application rates and estimated areas of forested land receiving 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 accounted for here. However, the total quantity of
organic N inputs to soils are accounted for in the Agricultural Soil Management and Settlements Remaining
Settlements sections.
Uncertainties exist in the fertilizer application rates, the area of forested land receiving fertilizer, and the emission
factors used to derive emission estimates.
To quantify the uncertainties for N20 fluxes from forest soils, 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 7-15. N20 fluxes from soils were estimated to be between 0.1 and 1.1 Tg C02 Eq. at a 95
percent confidence level. This indicates a range of 59 percent below and 211 percent above the 2005 emission
estimate of 0.3 Tg C02 Eq.
Table 7-15: Tier 2 Quantitative Uncertainty Estimates of N20 Fluxes from Soils in Forest Land Remaining Forest
Land (Tg C02 Eq. and Percent)
2005 Emission
Uncertainty Range Relative to
Estimate
Emission Estimate
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound Bound Bound Bound
Forest Land Remaining Forest Land: N20
Fluxes from Soils
N20
0.3
0.1 1.1 -59% +211%
Note: This estimate includes direct N20 emissions from N fertilizer additions to both Forest Land Remaining Forest Land and
Land Converted to Forest Land.
Recalculations Discussion
The IPCC default emission factor of 1.25 percent for direct emissions from applied N was updated to 1 percent
based on IPCC (2006). Additionally, because the direct emission factor was developed based on total N inputs, the
new method has been revised to estimate direct N20 emissions based on total N input. Previously, a portion of the
N inputs were removed from the calculation of direct N20 emissions, because it was assumed to be lost through
volatilization before direct emissions occurred.
7-16 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Public Review Draft
Planned Improvements
Area data for southeastern pine plantations receiving fertilizer will be updated with more recent datasets.
7.2. Land Converted to Forest Land (IPCC Source Category 5A2)
Land-use change is constantly occurring, and areas under a number of differing land-use types are converted to
forest each year, just as forest land is converted to other uses. However, the magnitude of these changes is not
currently known. Given the paucity of available land-use information relevant to this particular IPCC source
category, it is not possible to separate C02 or N20 fluxes on Land Converted to Forest Land from fluxes on Forest
Land Remaining Forest Land at this time.
7.3. Cropland Remaining Cropland (IPCC Source Category 5B1)
Soils contain both organic and inorganic forms of C, but soil organic carbon (SOC) stocks are the main source or
sink for atmospheric C02 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) recommends reporting changes in soil
organic C stocks due to agricultural land-use and management activities on mineral soils and organic soils. In
addition, the IPCC Guidelines recommend reporting C02 emissions that result from liming of soils with dolomite
and limestone.
Typical well-drained mineral soils contain from 1 to 6 percent organic 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 C02 emissions. Because of the depth and richness of the organic
layers, C loss from drained organic soils can continue over long periods of time. The rate of C02 emissions varies
depending on climate and composition (i.e., decomposability) of the organic matter. Also, the use of organic soils
for annual crop production leads to higher C loss rates than drainage of organic soils in grassland or forests, due to
deeper drainage and more intensive management practices in cropland (Armentano and Verhoeven 1990, as cited in
IPCC/UNEP/OECD/IEA 1997). C losses are estimated from drained organic soils under both grassland and
cropland management in this inventory.
The last category of the IPCC methodology addresses emissions from lime additions (in the form of crushed
limestone (CaC03) and dolomite (CaMg(C03)2) to agricultural soils. Lime and dolomite are added by land
managers to ameliorate acidification. When these compounds come in contact with acid soils, they degrade, thereby
generating C02. The rate and ultimate magnitude of degradation of applied limestone and dolomite depends on the
Land Use, Land-Use Change, and Forestry 7-17
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
soil conditions, climate regime, and the type of mineral applied.
Cropland Remaining Cropland includes all areas designated as cropland that had been cropland since 1982
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, C02 emissions and removals5 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. Emissions from liming are estimated using a Tier 2 IPCC method that relies on national
aggregate statistics of lime application and emissions factors developed by West and McBride (2005).
Of the three 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 2005 (see Table 7-16 and Table 7-17). In 2005, mineral
soils were estimated to remove about 71.1 Tg C02 Eq. (19.4 Tg C). This rate of C storage in mineral soils
represented about an 18 percent increase in the rate since the initial reporting year of 1990. Emissions from organic
soils had the second largest flux, emitting about 27.7 Tg C02 Eq. (7.5 Tg C) in 2005. Liming emitted another 4.0
Tg C02 Eq. (1.1 Tg C) in 2005. In total, U.S. agricultural soils in Cropland Remaining Cropland removed
approximately 39.4 Tg C02 Eq. (10.7 Tg C) in 2005.
Table 7-16: Net Soil C Stock Changes and Liming I-missions in Cropland Remaining Cropland (Tg C02 Eq.)
Soil Type
1990
1 1995
2000
2001
2002
2003
2004
2005
Mineral Soils
(60.2)
(69.5)
<<>X 5)
("n I )
("n 4)
("u 5)
("1 in
("1 1)
Organic Soils
27.4
27.7
¦> —
¦> —
_ _
_ _
Liming of Soils1
4.7
1 4.4
4 ^
44
5 u
4 (>
. I)
4.0
Total Net Flux
(28.1)
I (37.4)
(J6.5)
(3X.0)
IJ-'.S)
(3X.3)
(39.4)
(39.4)
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.
1 Also includes emissions from liming on Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to
Grassland.
Table 7-17: Net Soil C Stock Changes and Liming I-missions in Cropland Remaining Cropland (Tg C)
Soil Type
1990
1 1995
2000
2001
2002
2003
2004
2005
Mineral Soils
(16.4)
(18.9)
( 18 ")
( 1 'J 1 )
( 1 'J 2)
( I'J 2)
( I'M)
( 1 'M)
Organic Soils
7.5
7.5
7.5
7.5
~ 5
~ 5
7.5
7.5
Liming of Soils1
1.3
I 1-2
i:
i:
1 4
i:
1 1
1 1
Total Net Flux
(7.7)
(10.2)
(10.0)
(10.4)
(10.3)
(10.4)
(10. "'I
(10. "'I
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and
projections. All other values are based on historical data only. Totals may not sum due to independent rounding.
1 Also includes emissions from liming in Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to
Grassland.
The net increase in soil C stocks over the period from 1990 through 2005 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).
The spatial variability in annual C02 flux associated with C stock changes in mineral and organic soils is displayed
5 Note that removals occur through crop and forage uptake of C02 into biomass C that is later incorporated into soils pools.
7-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 in Figure 7-4 and Figure 7-5. The highest rates of sequestration in mineral soils occurred in the Midwest, where
2 there were the largest amounts of cropland managed with conservation tillage adoption. Rates were also high in the
3 Great Plains due to enrollment in the Conservation Reserve Program. Emission rates from drained organic soils
4 were highest along the southeastern coastal region, in the northeast central United States surrounding the Great
5 Lakes, and along the central and northern portions of the west coast.
6
7 Figure 7-4: Net C Stock Change for Mineral Soils in Cropland Remaining Cropland, 2005
8
9 Figure 7-5: Net C Stock Change for Organic Soils in Cropland Remaining Cropland, 2005
10
11 The estimates presented here are restricted to C stock changes in agricultural soils. Agricultural soils are also
12 important sources of other greenhouse gases, particularly N20 from application of fertilizers, manure, and crop
13 residues and from cultivation of legumes, as well as CH4 from flooded rice cultivation. These emissions are
14 accounted for in the Agriculture chapter, along with non-C02 greenhouse gas emissions from field burning of crop
15 residues and CH4 and N20 emissions from livestock digestion and manure management.
16 Methodology
17 The following section includes a description of the methodology used to estimate changes in soil C stocks due to:
18 (1) agricultural land-use and management activities on mineral soils; (2) agricultural land-use and management
19 activities on organic soils; and (3) C02 emissions that result from liming of soils with dolomite and limestone for
20 Cropland Remaining Cropland.
21 Soil C stock changes were estimated for Cropland Remaining Cropland (as well as agricultural land falling into the
22 IPCC categories Land Converted to Cropland, Grassland Remaining Grassland, and Land Converted to Grassland)
23 according to land use histories recorded in the USD A National Resources Inventory (NRI) survey (USDA-NRCS
24 2000). The NRI is a statistically-based sample of all non-federal land, and includes ca. 400,000 points in
25 agricultural land of the conterminous United States and Hawaii.6 Each point is associated with an "expansion
26 factor" that allows scaling of C stock changes from NRI points to the entire country (i.e., each expansion factor
27 represents the amount of area with the same land-use/management history as the sample point). Land-use and some
28 management information (e.g., crop type, soil attributes, and irrigation) were collected for each NRI point on a 5-
29 year cycle beginning in 1982, and were subdivided into four inventory time periods, 1980-84, 1985-1989, 1990-94
30 and 1995-2000. Currently, the NRI is being revised to collect data annually from a subset of points. However, at
31 present, no additional inventory point data are available for years after 1997.
32 NRI points were classified as Cropland Remaining Cropland for an inventory time period (e.g., 1990-1994 and
33 1995-2000) if the land use had been cropland since the first year of the NRI survey in 1982 through the end of the
34 respective time period. Cropland includes all land used to produce food or fiber, as well as forage that is harvested
35 and used as feed (e.g., hay and silage).
36 Mineral Soil Carbon Stock Changes
37 A Tier 3 model-based approach was used to estimate C stock changes for mineral soils used to produce a majority
38 of annual crops in the United States (i.e., all crops except vegetables, tobacco, perennial/horticultural crops, and rice
39 in addition to lands with very gravelly, cobbly or shaley soils (greater than 35 percent by volume)). An IPCC Tier 2
6 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
Land Use, Land-Use Change, and Forestry 7-19
-------
Public Review Draft
1 method (see Ogle et al. 2003) was used to estimate C stock changes for cropland on mineral soils that were not
2 addressed with the Tier 3 method: vegetables, tobacco, perennial/horticultural crops, rice, and crops rotated with
3 these crops. The Tier 2 method was also used for very gravelly, cobbly or shaley soils. Mineral SOC stocks were
4 estimated using a Tier 2 method for these areas, because the Century model used for the Tier 3 method has not been
5 fully tested to address its adequacy for estimating C stock changes associated with certain crops and rotations, as
6 well as cobbly, gravelly or shaley soils. An additional stock change calculation was made for mineral soils using
7 Tier 2 emission factors. These calculations accounted for enrollment patterns in the Conservation Reserve Program
8 after 1997, which was not addressed by the Tier 3 methods.
9 Further elaboration on the methodology and data used to estimate stock changes from mineral are described below
10 and in Annex 3.13.
11 Tier 3 Approach
12 Mineral SOC stocks and stock changes were estimated using the Century biogeochemical model (Parton et al. 1987,
13 1988, 1994; Metherell et al. 1993), which simulates the dynamics of C and other elements in cropland, grassland,
14 forest, and savanna ecosystems. It uses monthly weather data as input, along with information about soil physical
15 properties. Input data on land use and management can be specified at monthly resolution and include land-use
16 type, crop/forage type and management activities (e.g., planting, harvesting, fertilization, manure amendments,
17 tillage, irrigation, residue removal, grazing, and fire). The model computes net primary productivity and C
18 additions to soil, temperature, and water dynamics, in addition to turnover, stabilization, and mineralization of soil
19 organic matter C and nutrient (N, K, S) elements. This method is more accurate than the Tier 1 and 2 approaches
20 provided by the IPCC, because the simulation model treats changes as continuous over time rather than the
21 simplified discrete changes represented in the default method (see Box 7-2 for additional information). National
22 estimates were obtained by simulating historical land-use and management patterns as recorded in the USD A
23 National Resources Inventory (NRI) survey. Land-use and management activities were grouped into inventory time
24 periods (i.e., time "blocks") for 1980-84, 1985-89, 1990-94 and 1995-2000, using NRI data from 1982, 1987, 1992,
25 and 1997, respectively.
26
27 [BEGIN BOX]
28
29 Box 7-2: Tier 3 Inventory for Soil C Stocks compared to Tier 1 or 2 Approaches
30
31 A Tier 3 model-based approach is used to inventory soil C stock changes on the majority of agricultural land with
32 mineral soils. This approach entails several fundamental differences compared to the IPCC Tier 1 or 2 methods,
33 which are based on a classification of land areas into a number of discrete states based on a highly aggregated
34 classification of climate, soil, and management (i.e., only six climate regions, seven soil types and eleven
35 management systems occur in U.S. agricultural land). Input variables to the Tier 3 model, including climate, soils,
36 and management activities (e.g., fertilization, crop species, tillage, etc.), are represented in considerably more detail
37 both temporally and spatially, and exhibit multi-dimensional interactions through the more complex model structure
38 compared with the IPCC Tier 1 or 2 approach. The spatial resolution of the analysis is also finer in the Tier 3
39 method compared to the lower tier methods as implemented in the United States for previous inventories (e.g.,
40 3,037 counties versus 181 Major Land Resource Areas (MLRAs), respectively).
41 In the Century model, soil C dynamics (and C02 emissions and uptake) are treated as continuous variables, which
42 change on a monthly time step. C emissions and removals are an outcome of plant production and decomposition
43 processes, which are simulated in the model structure. Thus, changes in soil C stocks are influenced by not only
44 changes in land use and management but also inter-annual climate variability and secondary feedbacks between
45 management activities, climate and soils as they affect primary production and decomposition. This latter
7-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Public Review Draft
characteristic constitutes one of the greatest differences between the methods, and forms the basis for a more
complete accounting of soil C stock changes in the Tier 3 approach compared with Tier 2 methodology.
Because the Tier 3 model simulates a continuous time period rather than as an equilibrium step change used in the
IPCC methodology (Tier 1 and 2), the Tier 3 model addresses the delayed response of the soil to management and
land-use changes, which can occur due to variable weather patterns and other environmental constraints that interact
with land use and management and affect the time frame over which stock changes occur. Moreover, the Tier 3
method also accounts for the overall effect of increasing yields and, hence, C input to soils that have taken place
across management systems and crop types within the United States. Productivity has increased by 1 to 2 percent
annually over the past 4 to 5 decades for most major crops in the United States (Reilly and Fuglie 1998), which is
believed to have led to increases in cropland soil C stocks (e.g., Allmaras et al. 2000). This is a major difference
from the IPCC-based Tier 1 and 2 approaches, in which soil C stocks change only with discrete changes in
management and/or land use, rather than a longer term trend such as gradual increases in crop productivity.
[END BOX]
Additional sources of activity data were used to supplement the land-use information from NRI. The Conservation
Technology Information Center (CTIC 1998) provided annual data on tillage activity at the county level since 1989,
with adjustments for long-term adoption of no-till agriculture (Towery 2001). Information on fertilizer use and
rates by crop type for different regions of the United States were obtained primarily from the USD A 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 USD A Natural Resources Conservation Service
(Edmonds et al. 2003), and adjusted based on county-level manure production rates for other years in the inventory.
Specifically, county-scale ratios of manure production in other years relative to 1997 were used to estimate the area
amended in the other years, essentially scaling the amendment data compiled by USDA in 1997 across the time
series (see Annex 3.13 forfurther details). Higher managed manure N production relative to 1997 was, thus,
assumed to increase the amount of area amended with manure, while less managed manure N production relative to
1997 was assumed to reduce the amended area. The amount of managed manure produced by each livestock type
was calculated by determining the population of animals that were on feedlots or otherwise housed (requiring
manure to be collected and managed). 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
(USDA 1994a-b, 1995a-b, 1998a-b, 1999a-c, 2000, 2004a-e, 2005a-e, 2006a-e). Horse population data were
obtained from the FAOSTAT database (FAO 2006). Goat population data for 1992, 1997, and 2002 were obtained
from the Census of Agriculture (USDA 2005f); these data were interpolated and extrapolated to derive estimates for
the other years. Information regarding poultry turnover (i.e., slaughter) rate was obtained from state Natural
Resource Conservation Service personnel (Lange 2000). Additional population data for different farm size
categories for dairy and swine were obtained from the 1992 and 1997 Census of Agriculture (USDA 2005g).
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 were
obtained from an NRI database, which were assigned based on field visits and soil series descriptions. Where more
than one inventory point was located in the same county (i.e., same weather) and having the same land-
use/management histories and soil type, data inputs to the model were identical and, therefore, these points were
clustered for simulation purposes. For the 370,738 NRI points representing non-federal cropland and grassland,
there were a total of 170,279 clustered points that represent the unique combinations of climate, soils, land use, and
management in the modeled data set. Each NRI cluster point was run 100 times as part of the uncertainty
assessment, yielding a total of over 14 million simulation runs for the analysis. C stock estimates from Century
were adjusted using a structural uncertainty estimator accounting for uncertainty in model algorithms and parameter
values (Ogle et al. 2007). Mean changes in C stocks and 95 percent confidence intervals were estimated for 1990 to
1994 and 1995 to 2000 (see Uncertainty section for more details). C stock changes from 2001 to 2005 were
assumed to be similar to the 1995 to 2000 block, because no additional activity data are currently available from the
NRI for the latter years.
Land Use, Land-Use Change, and Forestry 7-21
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
Tier 2 Approach
In the 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).7 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/UNEP/OECD/IEA
(1997) and IPCC (2003). Changing the reference condition was necessary because soil measurements under
agricultural management are much more common and easily identified in the National Soil 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).8 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
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 2005 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 2005 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 FSA (2006) for 1998
through 2005, 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).
7 The polygons displayed in Figure 7-7 through Figure 7-10 are the Major Land Resource Areas.
8 Stock change factors have been derived from published literature to reflect changes in tillage, cropping rotations and
intensification, land-use change between cultivated and uncultivated conditions, and drainage of organic soils.
7-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Public Review Draft
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/UNEP/OECD/IEA (1997) and IPCC (2003), which utilizes 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 2005.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone and dolomite applied to agricultural soils were estimated
using a Tier 2 methodology. The annual amounts of limestone and dolomite applied (see Table 7-18) were
multiplied by C02 emission factors from West and McBride (2005). These emission factors (0.059 metric ton
C/metric ton limestone, 0.064 metric ton C/metric ton dolomite) are lower than the IPCC default emission factors,
because they account for the portion of agricultural lime that may leach through the soil and travel by rivers to the
ocean (West and McBride 2005). The annual application rates of limestone and dolomite were derived from
estimates and industry statistics provided in the Minerals Yearbook and Mineral Industry Surveys (Tepordei 1993,
1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006; USGS 2006). 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 2005 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 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 of2006 (USGS 2006).
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.
Table 7-18: Applied Minerals (Million Metric Tons)
Mineral
1990 1995
2000
2001
2002
2003
2004
2005
Limestone
19.01 17.30
15.86
16.10
20.45
18.71
15.50
16.10
Dolomite
2.36 2.77
3.81
3.95
2.35
2.25
2.33
2.42
Note: These numbers represent amounts applied to all agricultural land, not just Cropland Remaining Cropland.
Land Use, Land-Use Change, and Forestry 7-23
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
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) and soil liming emissions. Uncertainty
estimates are presented in Table 7-19 for each subsource (i.e., mineral soil C stocks, organic soil C stocks, soil
liming) disaggregated to the level of the inventory methodology employed (i.e., Tier 2 and Tier 3). A combined
uncertainty estimate for changes in soil C stocks occurring within Cropland Remaining Cropland is also included.
Uncertainty estimates from each component were combined using the error propagation equation in accordance with
IPCC (2006). The combined uncertainty was calculated by taking the square root of the sum of the squares of the
standard deviations of the uncertain quantities. More details on how the individual uncertainties were developed
appear later in this section. The combined uncertainty for soil C stocks in Cropland Remaining Cropland ranged
from 43 percent below and 38 percent above the 2005 stock change estimate of -39.4 Tg C02 Eq.
Table 7-19: Quantitative Uncertainty Estimates for C Stock Changes occurring within Cropland Remaining
Cropland (Tg C02 Eq. and Percent)
2005 Stock
Change
Uncertainty Range Relative to Stock
Estimate
Change Estimate
Source
(Tg C02 Eq.)
(Tg C02 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Mineral Soil C Stocks: Cropland Remaining
Cropland, Tier 3 Inventory Methodology
(66.4)
(77.0)
(55.9)
-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)
(1.6)
(2.5)
(0.8)
-50%
+50%
Organic Soil C Stocks: Cropland Remaining
Cropland, Tier 2 Inventory Methodology
27.7
15.8
36.9
-43%
+33%
C02 Emissions from Liming
4.0
0.2
8.0
-96%
98%
Combined Uncertainty for Agricultural Soil C
Stocks in Cropland Remaining Cropland
(39.4)
(56.2)
(24.3)
-43%
+38%
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. Errors were found in these steps and corrective actions were taken. One of
the errors involved a subset of the transitions from full tillage to reduced till between the late 1980s and early 1990s.
The reduced tillage transition was not occurring and the script was revised to correct the transition. The second
error involved improved estimation of root production in irrigated systems. Root production had been
parameterized based on rainfed crops, and so the parameters were adjusted to better approximate C allocation to
belowground growth in irrigated lands. In addition, QA/QC activities uncovered that the empirically-based
structural uncertainty estimator for the Century model did not address the random variation associated with
predicting soil C stock changes at the site level in the previous inventory, which is equivalent to NRI points. This
uncertainty is not insignificant, and, thus, previous uncertainty estimates were unrealistically low because the
random variation was not addressed. Adjustments were made in the current inventory, and the results better reflect
the uncertainty in the Tier 3 approach as implemented in the United States.
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.
7-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
Public Review Draft
Recalculations Discussion
Several adjustments were made in the current inventory to improve the results. First, consistency was achieved in
the N inputs data between the agricultural soil C and soil N20 source categories (see Agricultural Soil Management
section of the Agriculture chapter). Although this improvement required several changes to soil N20 inventory
methods, the only change to the soil C source was the scaling of manure amendment data in 1997 based on variation
in managed manure N production during other years of the Inventory. Second, scheduling files, (used in the model
program to determine when activities such as fertilization, tillage, planting, and harvesting occur) were adjusted in
the Tier 3 approach, so that transitions from full tillage to reduced till were properly modeled, and allocation of C to
roots was reduced for irrigated systems due to excessively high root biomass discovered through QA/QC checks.
Third, uncertainty was estimated in the current inventory for the random variation associated with Century model
estimates at the site scale. This is a significant uncertainty in the assessment framework, which was not addressed
in the previous inventory. Fourth, annual C emissions from organic cropland soils are subdivided between
Cropland Remaining Cropland and Land Converted to Cropland. In the previous inventory, all C emissions
associated with drainage of organic soils for crop production were reported in the Cropland Remaining Cropland
category.
The quantity of applied minerals reported in the previous inventory for 2004 has been revised. Consequently, the
reported emissions resulting from liming in 2004 have also changed. In the previous inventory, to estimate 2004
data, the previous year's fractions were applied to a 2004 estimate of total crushed stone presented in the USGS
Mineral Industry Surveys: Crushed Stone and Sand and Gravel in the First Quarter of2005 (USGS 2005). 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 2004. These values have replaced those used in the previous inventory
to calculate the quantity of minerals applied to soil and the emissions from liming. Additionally, a correction was
made to liming activity data from 2003 that was inaccurately transcribed from the original source.
Overall, the recalculations resulted in an average annual increase in sinks of 5.3 Tg C02 Eq. (21 percent) for soil C
stock changes in Cropland Remaining Cropland for the period 1990 through 2004.
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 develop a consistent representation of the U.S. managed land base. More details on
this planned improvement are provided in the Forest Land Remaining Forest Land section.
The third 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.
The fourth improvement is to incorporate remote sensing in the analysis for estimation of crop and forage
production. Specifically, the Enhanced Vegetation Index (EVI) product that is derived from MODIS satellite
imagery is being used to refine the production estimation for the Tier 3 assessment framework. EVI reflects
changes in plant "greenness" over the growing season and can be used to compute production based on the light use
efficiency of the crop or forage (Potter et al. 1993). In the current framework, production is simulated based on the
weather data, soil characteristics, and the genetic potential of the crop. While this method produces reasonable
results, remote sensing can be used to refine the productivity estimates and reduce biases in crop production and
subsequent C input to soil systems. It is anticipated that precision in the Tier 3 assessment framework will be
increased by 25 percent or more with the new method.
Land Use, Land-Use Change, and Forestry 7-25
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
The fifth 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 single
simulation. Results are aggregated and evaluated at larger scales such as Major Land Resource Areas 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 last 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.
7.4. Land Converted to Cropland (IPCC Source Category 5B2)
Land Converted to Cropland includes all areas designated as cropland that had been another land use in a prior time
period according to the USDA NRI land use survey (USDA-NRCS 2000). Consequently, the area considered in
Land Converted to Cropland changes through time with land-use change. Lands are retained in this category for 20
years as recommended by the IPCC guidelines (IPCC 2006) unless there is another land-use change. Background on
agricultural C stock changes is provided in Cropland Remaining Cropland and will only be summarized here for
Land Converted to Cropland. Soils are the largest pool of C in agricultural land, and also have the greatest potential
for storage or release of C, because biomass and dead organic matter C pools are relatively small and ephemeral
compared with soils. The IPCC/UNEP/OECD/IEA (1997) and the IPCC (2003) recommend reporting changes in
soil organic C stocks due to: (1) agricultural land-use and management activities on mineral soils, (2) agricultural
land-use and management activities on organic soils, and (3) C02 emissions that result from liming of soils with
dolomite and limestone. Mineral soil C stock changes and C emissions from drained and cultivated organic soils are
reported for Land Converted to Cropland. It was not possible, however, to subdivide the liming application
estimates by land use/land-use change categories (see Methodology section below for additional discussion)
Land-use and management of mineral soils in Land Converted to Cropland led to losses of soil C during the early
1990s but losses declined slightly through the latter part of the time series (Table 7-20 and Table 7-21). The rate of
change in soil C stocks was 7.2 Tg C02 Eq. (2.0 Tg C) in 2005. Emissions from mineral soils were estimated at 4.6
Tg C02 Eq. (1.2 Tg C) in 2005, while drainage and cultivation of organic soils led to annual losses of 2.6 Tg C02
Eq. (0.7 Tg C) in 2005.
Table 7-20: Net Soil C Stock Changes in Land Converted to Cropland (Tg C02 Eq.)
Soil Type
1990
1995
2000
2001
2002
2003
2004
2005
Mineral Soils
6.2
4.6
4 (>
4 (.
4 (>
4 (>
4 (>
4 (>
Organic Soils
2.4
2.6
2 (.
2 (.
2.(>
2.(>
2 (.
2 (.
Liming of Soils1
-
-
-
-
-
-
-
-
Total Net Flux
8.7
7.2
7 2
7 2
7.2
7.2
7.2
7 2
1 Emissions from liming in Land Converted to Cropland are reported in Cropland Remaining Cropland
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 7-21: Net Soil C Stock Changes in Land Converted to Cropland (Tg C)
Soil Type 1990 1995 1000 2001 2002 2003 2004 2005
Mineral Soils I " I : 12 12 12 12 12 12
Organic Soils 0.7 0.7 (> " (> " (>" (>" (> " t>.~
Liming of Soils1 - - ......
7-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Total Net Flux 14 2ji 2.0 2.0 2.0 2.0 2.0 2.0
1 1 Emissions from liming in Land Converted to Cropland are reported in Cropland Remaining Cropland
2 Note: Shaded areas indicate values based on a combination of historical data and projections. All other values are based on
3 historical data only. Totals may not sum due to independent rounding.
4
5 The spatial variability in annual C02 flux associated with C stock changes in mineral and organic soils for Land
6 Converted to Cropland is displayed in Figure 7-6 and Figure 7-7. While a large portion of the United States had net
7 losses in soil C for Land Converted to Cropland, there were some notable areas with sequestration in the
8 Intermountain West and Central United States. These areas were gaining C following conversion, because
9 croplands were irrigated or receiving higher fertilizer inputs relative to the previous land use. Emissions from
10 organic soils were largest in California, Florida and the upper Midwest, which coincided with largest concentrations
11 of cultivated organic soils in the United States.
12 Figure 7-6: Net C Stock Change for Mineral Soils in Land Converted to Cropland, 2005
13
14 Figure 7-7: Net C Stock Change for Organic Soils in Land Converted to Cropland, 2005
15
16 Methodology
17 The following section includes a brief description of the methodology used to estimate changes in soil C stocks due
18 to agricultural land-use and management activities on mineral and organic soils for Land Converted to Cropland.
19 Soil C stock changes were estimated for Land Converted to Cropland according to land-use histories recorded in the
20 USDA NRI survey (USDA-NRCS 2000).9 Land use and some management information (e.g., crop type, soil
21 attributes, and irrigation) were collected for each NRI point on a 5-year cycle beginning in 1982, and were
22 subdivided into four inventory time periods, 1980-84, 1985-1989, 1990-94 and 1995-2000. NRI points were
23 classified as Land Converted to Cropland for an inventory time period (e.g., 1990-1994 and 1995-2000) if the land
24 use was cropland at the end of the respective inventory time period but had been another use in a prior inventory
25 time period. Cropland includes all land used to produce food or fiber, as well as forage that is harvested and used as
26 feed (e.g., hay and silage). Further elaboration on the methodologies and data used to estimate stock changes for
27 mineral and organic soils are provided in the Cropland Remaining Cropland section and Annex 3.13.
28 Mineral Soil Carbon Stock Changes
29 A Tier 3 model-based approach was used to estimate C stock changes for soils on Land Converted to Cropland used
30 to produce a majority of all crops. Exceptions, which relied on an IPCC Tier 2 method to estimate C stock changes,
31 included: land used to produce vegetable, tobacco, perennial/horticultural crops, and rice; land on very gravelly,
32 cobbly or shaley soils (greater than 35 percent by volume); and land converted from forest or federal ownership.10
33 (Ogle et al. 2003)
34 Tier 3 Approach
35 Mineral SOC stocks and stock changes were estimated using the Century biogeochemical model for the Tier 3
9 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
1° 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 7-27
-------
Public Review Draft
1 methods. National estimates were obtained by using the model to simulate historical land-use change patterns as
2 recorded in the USDA National Resources Inventory (USDA-NRCS 2000). The methods used for Land Converted
3 to Cropland are the same as those described in the Tier 3 portion of Cropland Remaining Cropland Section for
4 mineral soils (see Cropland Remaining Cropland Tier 3 methods section for additional information).
5 Tier 2 Approach
6 For the mineral soils not included in the Tier 3 analysis, SOC stock changes were estimated using a Tier 2 Approach
7 for Land Converted to Cropland as described in the Tier 2 portion of Cropland Remaining Cropland Section for
8 mineral soils (see Cropland Remaining Cropland Tier 2 methods section for additional information).
9 Organic Soil Carbon Stock Changes
10 Annual C emissions from drained organic soils in Land Converted to Cropland were estimated using the Tier 2
11 method provided in IPCC/UNEP/OECD/IEA (1997) and IPCC (2003), which utilizes U.S.-specific C loss rates
12 (Ogle et al. 2003) rather than default IPCC rates. The final estimates included a measure of uncertainty as
13 determined from the Monte Carlo simulation with 50,000 iterations. Emissions were based on the 1992 and 1997
14 Land Converted to Cropland areas from the 1997 National Resources Inventory (USDA-NRCS 2000). The annual
15 flux estimated for 1992 was applied to 1990 through 1992, and the annual flux estimated for 1997 was applied to
16 1993 through 2005.
17 C02 Emissions from Agricultural Liming
18 Carbon dioxide emissions from degradation of limestone and dolomite applied to Land Converted to Cropland are
19 reported in Cropland Remaining Cropland, because it was not possible to disaggregate liming application among
20 land use and land-use change categories.
21 Uncertainty
22 Uncertainty associated with the Land Converted to Cropland land-use change category includes the uncertainty
23 associated with changes in mineral and organic soil C stocks. Uncertainty estimates are presented in Table 7-22 for
24 each subsource (i.e., mineral soil C stocks and organic soil C stocks) disaggregated to the level of the Inventory
25 methodology employed (i.e., Tier 2 and Tier 3). A combined uncertainty estimate for changes in agricultural soil C
26 stocks occurring within Land Converted to Cropland is also included. Uncertainty estimates from each component
27 were combined using the error propagation equation in accordance with IPCC (2006). The combined uncertainty
28 was calculated by taking the square root of the sum of the squares of the standard deviations of the uncertain
29 quantities. More details on how the individual uncertainties were developed appear later in this section. The
30 combined uncertainty for soil C stocks in Land Converted to Cropland was estimated to be 33 percent below and 29
31 percent above the inventory estimate of 7.2 Tg C02 Eq.
32 Table 7-22: Quantitative Uncertainty Estimates for C Stock Changes occurring w ithin Land Converted to Cropland
33 (Tg C02 Eq. and Percent)
2005 Stock Uncertainty Range Relative to Stock
Change Estimate Change Estimate
Source (Tg CP2 Eq.) (Tg CP2 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Mineral Soil C Stocks: Land Converted to
Cropland, Tier 3 Inventory Methodology
Mineral Soil C Stocks: Land Converted to
0.4
(0.1)
0.9
-124%
+124%
Cropland, Tier 2 Inventory Methodology
Organic Soil C Stocks: Land Converted to
4.1
2.3
5.8
-44%
+41%
Cropland, Tier 2 Inventory Methodology
2.6
1.2
3.7
-53%
+41%
Combined Uncertainty for Agricultural Soil
7.2
4.9
9.3
-33%
29%
7-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Carbon Stocks in Land Converted to
Cropland
1
2 Uncertainties in Mineral Soil Carbon Stock Changes
3 The uncertainty analysis for Land Converted to Cropland using the Tier 3 and 2 approaches were based on the same
4 method described for Cropland Remaining Cropland, except that the uncertainty inherent in the structure of the
5 Century model was not addressed.
6 Uncertainties in Organic Soil Carbon Stock Changes
7 Annual C emission estimates from drained organic soils in Land Converted to Cropland were estimated using the
8 Tier 2 Approach, as described in the Cropland Remaining Cropland Section.
9 QA/QC and Verification
10 See QA/QC and Verification Section under Cropland Remaining Cropland.
11 Recalculations Discussion
12 The specific changes in reporting in the current Inventory for Land Converted to Cropland are the same as those
13 described in the Cropland Remaining Cropland section, except that the uncertainty is not addressed for the random
14 variation associated with Century model estimates at the site scale. The structural uncertainty requires further
15 development before it can be used to address uncertainty inherent in the structure of the Century model for Land
16 Converted to Cropland. A further change affecting this section is that organic soil emissions for the Cropland
17 Remaining Cropland and Land Converted to Cropland sections were previously reported together in the Cropland
18 Remaining Cropland section. For the current inventory, they have been reapportioned between the land use
19 categories and, therefore, a portion of the emissions are now reported in the Land Converted to Cropland section
20 Overall, these recalculations resulted in an average annual increase in emissions of 9.1 Tg C02 Eq. (71.4 percent)
21 for soil C stock changes in Land Converted to Cropland over the time series from 1990 through 2004. The changes
22 also resulted in a shift from the previous inventory's reporting of this category as an overall sink to the current
23 reporting as an overall source.
24 Planned Improvements
25 The empirically-based uncertainty estimator described in the Cropland Remaining Cropland section for the Tier 3
26 approach has not been developed to estimate uncertainties related to the structure of Century model for Land
27 Converted to Cropland, but this is a planned improvement. See Planned Improvements section under Cropland
28 Remaining Cropland for additional planned improvements.
29 7.5. Grassland Remaining Grassland (IPCC Source Category 5C1)
30 Grassland Remaining Grassland includes all areas of grassland that had been designated as grassland since 1982
31 according to the USDA NRI land use survey (USDA-NRCS 2000). Consequently, the area considered in
32 Grassland Remaining Grassland changes through time with land-use change. Background on agricultural C stock
33 changes is provided in the Cropland Remaining Cropland section and will only be summarized here for Grassland
34 Remaining Grassland. Soils are the largest pool of C in agricultural land, and also have the greatest potential for
35 storage or release of C, because biomass and dead organic matter C pools are relatively small and ephemeral
36 compared to soils. The IPCC/UNEP/OECD/IEA (1997) and IPCC (2003) recommend reporting changes in soil
37 organic C stocks due to: (1) agricultural land-use and management activities on mineral soils, (2) agricultural land-
38 use and management activities on organic soils, and (3) C02 emissions that result from liming of soils with dolomite
39 and limestone. Mineral and organic soil C stock changes are reported here for Grassland Remaining Grassland, but
40 stock changes associated with liming are reported in Cropland Remaining Cropland, because it was not possible to
41 subdivide those estimates by land use/land-use change categories (see Methodology section below for additional
Land Use, Land-Use Change, and Forestry 7-29
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
discussion).
Land-use and management of mineral soils in Grassland Remaining Grassland increased soil C during the early
1990s, but this trend was reversed over the decade, with small losses of C prevailing during the latter part of the
time series (see Table 7-23 and Table 7-24). Organic soils lost about the same amount of C in each year of the
inventory. The overall trend shifted from small decreases in soil C during 1990 to larger decreases during the latter
years, estimated at 16.1 Tg C02 Eq. (4.4 Tg C) in 2005.
Table 7-23: Net Soil C Stock Changesin Grassland Remaining Grassland (Tg C02 Eq.)
Soil Type
1990
1995
2000
2001
2002
2003
2004
2005
Mineral Soils
(3.7)
12.7
12 (.
12 (.
12 5
i: 5
12 5
12 4
Organic Soils
3.9
3.7
) . /
•) _ /
•) _ /
^. /
) . /
Liming of Soils1
-
-
-
-
-
-
-
-
Total Net Flux
0.1
16.4
16.3
16.2
16.2
16.2
16.1
16.1
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and
projections. All other values are based on historical data only. Totals may not sum due to independent rounding.
1 Emissions from liming in Grassland Remaining Grassland are reported in Cropland Remaining Cropland.
Table 7-24: Net Soil C Stock Changes in Grassland Remaining Grassland (Tg C)
Soil Type
1990
1995
2000
2001
2002
2003
2004
2005
Mineral Soils
(1.0)
3.5
^ 4
^ 4
^ 4
\4
^ 4
^ 4
Organic Soils
1.1
1.0
l.o
l.o
1 o
1 o
l.o
l.o
Liming of Soils1
-
-
-
-
-
-
-
-
Total Net Flux
0
4.5
4.4
4.4
4.4
4.4
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.
1 Emissions from liming in Grassland Remaining Grassland are reported in Cropland Remaining Cropland.
The spatial variability in annual C02 flux associated with C stock changes in mineral and organic soils is displayed
in Figure 7-8 and Figure 7-9. Grassland is losing soil organic C in the United States largely due to droughts that are
causing small losses of C on a per hectare basis, but are occurring over a large land base. In areas with net gains in
soil organic C, sequestration was driven by irrigation and seeding legumes. Similar to Cropland Remaining
Cropland, emission rates from drained organic soils were highest along the southeastern coastal region, in the
northeast central United States surrounding the Great Lakes, and along the central and northern portions of the west
coast.
Figure 7-8: Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 2005
Figure 7-9: Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 2005
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.
7-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
Public Review Draft
Soil C stock changes were estimated for Grassland Remaining Grassland according to land-use histories recorded
in the USDA NRI survey (USDA-NRCS 2000).11 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, 1980-84, 1985-1989,
1990-94 and 1995-2000. NRI points were classified as Grassland Remaining Grassland for an inventory time
period (e.g., 1990-1994 and 1995-2000) if the land use had been grassland since the first year of the NRI survey in
1982 through the end of the respective time period. 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
A Tier 3 model-based approach was used to estimate C stock changes for mineral soils in Grassland Remaining
Grassland, except for lands with very gravelly, cobbly or shaley soils (greater than 35 percent by volume). An
IPCC Tier 2 method was used to estimate stock changes for the gravelly, cobbly or shaley soils and additional
changes in C stocks in mineral soils. A Tier 2 method was also used to estimate 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
manure production rates for other years in the inventory. Specifically, county-scale ratios of manure production in
other years relative to 1997 were used to adjust the area amended with manure for other years in the inventory (see
Annex 3.13 for further details). Higher managed manure N production relative to 1997 was, thus, assumed to
increase the amount of area amended with manure, while less managed manure N production relative to 1997 was
assumed to reduce the amended area. The amount of managed manure produced by each livestock type was
calculated by determining the population of animals that were on feedlots or otherwise housed (requiring manure to
be collected and managed). 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 (USDA
1994a-b, 1995a-b, 1998a-b, 1999a-c, 2000, 2004a-e, 2005a-d, 2006a-e). Horse population data were obtained from
the FAOSTAT database (FAO 2006). Goat population data for 1992, 1997, and 2002 were obtained from the
Census of Agriculture (USDA 2005g); these data were interpolated and extrapolated to derive estimates for the
other years. Information regarding poultry turnover (i.e., slaughter) rate was obtained from state Natural Resource
Conservation Service personnel (Lange 2000). Additional population data for different farm size categories for
dairy and swine were obtained from the 1992 and 1997 Census of Agriculture (USDA 2005g).
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). See the Tier 3
methods in Cropland Remaining Cropland section for additional discussion on the Tier 3 methodology for mineral
soils.
Tier 2 Approach
11 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
Land Use, Land-Use Change, and Forestry 7-31
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
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 2005 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, and a projection for 2000, in dry
mass units, were obtained from EPA reports (EPA 1993, 1999), and linearly interpolated to estimate values for the
intervening years. N application rates from Kellogg et al. (2000) were used to determine the amount of area
receiving sludge amendments. Although sewage sludge can be added to land managed for other land uses, it was
assumed that agricultural amendments occur in grassland. Cropland is assumed to 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/UNEP/OECD/IEA (1997) and IPCC (2003), which utilizes 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
Grassland Remaining Grassland areas from the 1997 National Resources Inventory (USDA-NRCS 2000). The
annual flux estimated for 1992 was applied to 1990 through 1992, and the annual flux estimated for 1997 was
applied to 1993 through 2005.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone and dolomite applied to Grassland Remaining Grassland
are reported in Cropland Remaining Cropland, because it was not possible to disaggregate liming application
among land use/land-use change categories.
Uncertainty
Uncertainty associated with the Grassland Remaining Grassland category includes the uncertainty associated with
changes in mineral and organic soil C stocks. Uncertainty estimates are presented in Table 7-25 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 (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 Grassland Remaining Grassland was estimated to be 18 percent below
and 15 percent above the inventory estimate of 16.1 Tg C02 Eq.
Table 7-25: Quantitative Uncertainty Estimates for C Stock Changes occurring within Grassland Remaining
Grassland (Tg C02 Eq. and Percent)
2005 Stock
Uncertainty Range Relative to Stock
Change Estimate
Change Estimate
Source
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Bound
Upper
Bound
Lower Upper
Bound Bound
Mineral Soil C Stocks Grassland Remaining
Grassland, Tier 3 Inventory Methodology
13.9
12.4
15.3
-10% +10%
7-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
Mineral Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Inventory Methodology
Mineral Soil C Stocks: Grassland Remaining
Grassland (Change in Soil C due to Sewage
Sludge Amendments)
Organic Soil C Stocks: Grassland Remaining
Grassland, Tier 2 Inventory Methodology
Combined Uncertainty for Agricultural Soil
Carbon Stocks in Grassland Remaining
Grassland 16.1 13.2 18.5 -18% +15%
1
2 Uncertainties in Mineral Soil Carbon Stock Changes
3 Tier 3 Approach
4 The uncertainty analysis for Grassland Remaining Grassland using the Tier 3 approach and Tier 2 approach were
5 based on the same method described for Cropland Remaining Cropland, except that the uncertainty inherent in the
6 structure of the Century model was not addressed. See the Tier 3 approach for mineral soils under the Cropland
7 Remaining Cropland section for additional discussion.
8 Additional Mineral Carbon Stock Change Calculations
9 A ±50 percent uncertainty was assumed for additional adjustments to the soil C stocks between 1990 and 2005 to
10 account for additional C stock changes associated with amending grassland soils with sewage sludge.
11 Uncertainties in Organic Soil Carbon Stock Changes
12 Uncertainty in C emissions from organic soils were estimated using country-specific factors and a Monte Carlo
13 analysis. PDFs for emission factors were derived from a synthesis of 10 studies, and combined with uncertainties in
14 the NRI land use and management data for organic soils in the Monte Carlo analysis. See the Tier 2 section under
15 minerals soils of Cropland Remaining Cropland for additional discussion.
16 QA/QC and Verification
17 Quality control measures included checking input data, model scripts, and results to ensure data were properly
18 handled through the inventory process. An error was found in these steps and a corrective action was taken.
19 Specifically, the error involved improved estimation of root production in irrigated systems. Root production had
20 been parameterized based on rainfed forages; the parameters were adjusted to approximate C allocation to
21 belowground growth in irrigated lands.
22 Recalculations Discussion
23 The specific changes in reporting in the current Inventory for Grassland Remaining Grassland are the same as those
24 described in the Cropland Remaining Cropland section, except that the uncertainty is not addressed in the current
25 inventory for the random variation associated with Century model estimates at the site scale. The structural
26 uncertainty requires further development before it can be used to address uncertainty inherent in the structure of the
27 Century model for Grassland Remaining Grassland. Overall, the recalculations resulted in an average annual
28 increase in emissions of 7.4 Tg C02 Eq. (46.2 percent) for soil C stock changes in Grassland Remaining Grassland
29 over the period from 1990 through 2004.
30 Planned Improvements
31 The empirically-based uncertainty estimator described in the Cropland Remaining Cropland section for the Tier 3
32 approach has not been developed to estimate uncertainties in Century model results for Grassland Remaining
(0.2) (0.3) 0.04 -89% +127%
(1.3) (1.9) (0.6) -50% +50%
3.7 1.2 5.5 -66% +49%
Land Use, Land-Use Change, and Forestry 7-33
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
Public Review Draft
Grassland, but this is a planned improvement for the inventory. See Planned Improvements section under Cropland
Remaining Cropland for additional planned improvements.
7.6. Land Converted to Grassland (IPCC Source Category 5C2)
Land Converted to Grassland includes all areas designated as grassland that had been in another land use in a prior
time period 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 the IPCC guidelines (IPCC 2006) unless there is another land use change. Background
on agricultural C stock changes is provided in Cropland Remaining Cropland and will only be summarized here for
Land Converted to 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) recommends reporting changes in soil organic C
stocks due to: (1) agricultural land-use and management activities on mineral soils, (2) agricultural land-use and
management activities on organic soils, and (3) C02 emissions that result from liming of soils with dolomite and
limestone. Mineral soil C stock changes and C emissions from organic soils are reported here for Land Converted
to Grassland, but emissions from liming are reported in Cropland Remaining Cropland, because it was not possible
to subdivide those estimates by land use and land-use change categories (see the Methodology section below for
additional discussion).
Land-use and management of mineral soils in Land Converted to Grassland led to an increase in soil C stocks over
the entire time series, which was largely caused by annual cropland converted into pasture (see Table 7-26 and
Table 7-27). Stock change rates over the time series varied from 14.6 to 16.3 Tg C02 Eq./yr (4.0 to 4.5 Tg C).
Drainage of organic soils for grazing management led to annual losses of 0.9 Tg C02 Eq. in 2005.
Table 7-26: Net Soil C Stock Changes for Land Converted to Grassland (Tg C02 Eq.)
Soil Type 199n 1995 2 2001 2002 2003 2004 2005
Mineral Soils1 (15.0) (17.2) (I ~ 21 (I ~ 21 (I ~ 2) (I ~ 2) (I ~ 2) (I ~ 2)
Organic Soils 0.5 0.1> n 'J n 'J «') «') n 'J n 'J
Liming of Soils2 - - - - - - - -
Total Net Flux (14.6) (16.3) (16.3) 116.3) 116.3) (16.3) 116.3) 116.3)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and
projections. All other values are based on historical data only. Totals may not sum due to independent rounding.
1 Stock changes due to application of sewage sludge is reported in Grassland Remaining Grassland.
2 Emissions from liming in Land Converted to Grassland are reported in Cropland Remaining Cropland.
Table 7-27: Net Soil C Stock Changes for Land Converted to Grassland (Tg C)
Soil Type
1990
1995
2000
2001
2002
2003
2004
2005
Mineral Soils1
(4.1)
(4.7)
(4 ")
(4 ")
(4 "i
(4 "i
(4 "i
(4 "i
Organic Soils
0.1
0.2
u:
ii:
u:
u:
ii :
ii :
Liming of Soils2
-
-
-
-
-
-
-
Total Net Flux
(4.0)
(4.5)
(4.5)
(4.5)
(4.5)
(4.5)
(4.5)
(4.5)
Note: Parentheses indicate net sequestration. Shaded areas indicate values based on a combination of historical data and
projections. All other values are based on historical data only. Totals may not sum due to independent rounding.
1 Stock changes due to application of sewage sludge is reported in Grassland Remaining Grassland.
2 Emissions from liming in Land Converted to Grassland are reported in Cropland Remaining Cropland.
The spatial variability in annual C02 flux associated with C stock changes in mineral soils is displayed in Figure
7-10 and Figure 7-11. Soil C stock increased in most MLRAs for Land Converted to Grassland. The largest gains
were in the southeast and northwest, and the amount of sequestration increased through the 1990s. The patterns
were driven by conversion of annual cropland into continuous pasture. 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.
7-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Figure 7-10: Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 2005
2
3 Figure 7-11: Net Soil C Stock Change for Organic Soils in Land Converted to Grassland, 2005
4
5 Methodology
6 The following section includes a brief description of the methodology used to estimate changes in soil C stocks due
7 to agricultural land-use and management activities on mineral soils for Land Converted to Grassland.
8 Soil C stock changes were estimated for Land Converted to Grassland according to land-use histories recorded in
9 the USDA NRI survey (USDA-NRCS 2000).12 Land use and some management information (e.g., legume
10 pastures, crop type, soil attributes, and irrigation) were collected for each NRI point on a 5-year cycle beginning in
11 1982, and were subdivided into four inventory time periods, 1980-84, 1985-1989, 1990-94 and 1995-2000. NRI
12 points were classified as Land Converted to Grassland for an inventory time period (e.g., 1990-1994 and 1995-
13 2000) if the land use was grassland at the end of the respective inventory time period but had been another use in a
14 prior inventory time period. Grassland includes pasture and rangeland used for grass forage production, where the
15 primary use is livestock grazing. Rangeland are typically extensive areas of native grassland that are not intensively
16 managed, while pastures are often seeded grassland, possibly following tree removal, that may or may not be
17 improved with practices such as irrigation and interseeding legumes. Further elaboration on the methodologies and
18 data used to estimate stock changes from mineral and organic soils are provided in the Cropland Remaining
19 Cropland section and Annex 3.13.
20 Mineral Soil Carbon Stock Changes
21 A Tier 3 model-based approach was used to estimate C stock changes for Land Converted to Grassland on mineral
22 soils, with the exception of prior cropland used to produce vegetables, tobacco, perennial/horticultural crops, and
23 rice, in addition to land areas with very gravelly, cobbly or shaley soils (greater than 35 by volume). An IPCC Tier
24 2 approach was used to estimate C stock changes for portions of the land base for Land Converted to Grassland that
25 were not addressed with the Tier 3 approach (Ogle et al. 2003). A Tier 2 approach was also used to estimate
26 additional changes in mineral soil C stocks due to sewage sludge amendments. However, stock changes associated
27 with sewage sludge amendments are reported in the Grassland Remaining Grassland section.
28 Tier 3 Approach
29 Mineral SOC stocks and stock changes were estimated using the Century biogeochemical model as described for
30 Grassland Remaining Grassland. Historical land-use and management patterns were used in the Century
31 simulations as recorded in the NRI survey, with supplemental information on fertilizer use and rates from USDA
32 Economic Research Service Cropping Practices Survey (ERS 1997) and National Agricultural Statistics Service
33 (NASS 1992, 1999, 2004) (see Grassland Remaining Grassland Tier 3 methods section for additional information).
34 Tier 2 Approach
35 The Tier 2 Approach used for Land Converted to Grassland on mineral soils is the same as described for Cropland
36 Remaining Cropland (See Cropland Remaining Cropland Tier 2 Approach for additional information).
12 NRI points were classified as agricultural if under grassland or cropland management in 1992 and/or 1997.
Land Use, Land-Use Change, and Forestry 7-35
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
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/UNEP/OECD/IEA (1997) and IPCC (2003), which utilizes 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 a Monte Carlo simulation with 50,000 iterations. 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 2005.
C02 Emissions from Agricultural Liming
Carbon dioxide emissions from degradation of limestone and dolomite applied to Land Converted to Grassland are
reported in Cropland Remaining Cropland, because it was not possible to disaggregate liming application among
land use and land-use change categories.
Uncertainty
Uncertainty associated with the Land Converted to Grassland category includes the uncertainty associated with
changes in mineral soil C stocks. Uncertainty estimates are presented in Table 7-28 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). 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 Land Converted to Grassland ranged from 13 percent below and 14 percent above the 2005 estimate of 16.3 Tg
C02 Eq.
Table 7-28: Quantitative Uncertainty Estimates for C Stock Changes occurring within Land Converted to
Grassland (Tg C02 Eq. and Percent)
2005 Stock
Change
Uncertainty Range Relative to Stock
Estimate
Change Estimate
Source
(Tg C02 Eq.)
(Tg C02 Eq.) (%)
Lower Upper Lower Upper
Bound
Bound
Bound
Bound
Mineral Soil C Stocks: Land Converted to
Grassland, Tier 3 Inventory Methodology
Mineral Soil C Stocks: Land Converted to
(12.2)
(12.5)
(11.9)
-2%
+2%
Grassland, Tier 2 Inventory Methodology
Organic Soil C Stocks: Land Converted to
(5.0)
(7.0)
(2.8)
-39%
+43%
Grassland, Tier 2 Inventory Methodology
0.9
0.2
1.8
-76%
+104%
Combined Uncertainty for Agricultural Soil
Carbon Stocks in Land Converted to Grassland
(16.3)
(18.4)
(14.0)
-13%
14%
Uncertainties in Mineral Soil Carbon Stock Changes
Tier 3 Approach
The uncertainty analysis for Land Converted to Grassland 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.
7-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
Uncertainties in Organic Soil Carbon Stock Changes
Annual C emission estimates from drained organic soils in Land Converted to Grassland were estimated using the
Tier 2 approach, as described in the Cropland Remaining Cropland section.
QA/QC and Verification
See the QA/QC and Verification section under Grassland Remaining Grassland.
Recalculations Discussion
The specific changes in reporting in the current Inventory for Land Converted to Grassland are the same as those
described in the Cropland Remaining Cropland section, except that the uncertainty is not addressed in the current
inventory for the random variation associated with Century model estimates at the site scale. The structural
uncertainty requires further development before it can be used to address uncertainty inherent in the structure of the
Century model for other uses besides cropland. Overall, the recalculations resulted in an average annual decrease in
sinks of 4.3 Tg C02 Eq. (21.1 percent) for soil C stock changes in Land Converted to Grassland for the time series
from 1990 through 2004.
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. See Planned Improvements section under Cropland
Remaining Cropland for additional planned improvements.
7.7. 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 27.1 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 73.0 Tg C02 Eq. (19.9 Tg C) over the period from 1990 through
2005. Total sequestration increased by 54 percent between 1990 and 2005 due to increases in urban land area. Data
on C storage and urban tree coverage were collected throughout the 1990s, and have been applied to the entire time
series in this report. Annual estimates of C02 flux were developed based on periodic U.S. Census data on urban
area (Table 7-29).
Net C flux from urban trees is proportionately greater on an area basis than that of forests. This trend is primarily
the result of different net growth rates in urban areas versus forests—urban trees often grow faster than forest trees
because of the relatively open structure of the urban forest (Nowak and Crane 2002). Also, areas in each case are
accounted for differently. Because urban areas contain less tree coverage than forest areas, the C storage per
hectare of land is in fact smaller for urban areas. However, urban tree reporting occurs on a per unit tree cover basis
(tree canopy area), rather than total land area. Urban trees, therefore, appear to have a greater C density than
forested areas (Nowak and Crane 2002).
Table 7-29: Net C Flux from Urban Trees (Tg C02 Eq. and Tg C)
Year Tg CP2 Eq. Tg C
Land Use, Land-Use Change, and Forestry 7-37
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
Public Review Draft
2001
(80.2)
(21.9)
2002
(82.3)
(22.4)
2003
(84.4)
(23.0)
2004
(86.4)
(23.6)
2005
(88.5)
(24.1)
Note: Parentheses indicate net sequestration.
Methodology
The methodology used by Nowak and Crane (2002) is based on average annual estimates of urban tree growth and
decomposition, which were derived from field measurements and data from the scientific literature, urban area
estimates from U.S. Census data, and urban tree cover estimates from remote sensing data. This approach is
consistent with the default IPCC methodology in IPCC (2003), although sufficient data are not yet available to
determine interannual changes 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.
Nowak and Crane (2002) developed estimates of annual gross C sequestration from tree growth and annual gross C
emissions from decomposition for ten U.S. cities: Atlanta, GA; Baltimore, MD; Boston, MA; Chicago, IL; Jersey
City, NJ; New York, NY; Oakland, CA; Philadelphia, PA; Sacramento, CA; and Syracuse, NY. The gross C
sequestration estimates were derived from field data that were collected in these ten cities during the period from
1989 through 1999, including tree measurements of stem diameter, tree height, crown height, and crown width, and
information on location, species, and canopy condition. The field data were converted to annual gross 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 10 cities, some of which are unpublished, are
described in Nowak and Crane (2002) and references cited therein. The allometric equations were taken from the
scientific literature (see Nowak 1994, Nowak et al. 2002), and the adjustments to account for smaller volumes in
urban conditions were based on information in Nowak (1994). A root-to-shoot ratio of 0.26 was taken from Cairns
et al. (1997), and species- or genus-specific moisture contents were taken from various literature sources (see
Nowak 1994). Adjustment factors to account for tree condition were based on percent crown dieback (Nowak and
Crane 2002). Tree growth rates were also taken from existing literature. Average diameter growth was based on
the following sources: estimates for trees in forest stands came from Smith and Shifley (1984); estimates for trees
on land uses with a park-like structure came from deVries (1987); and estimates for more open-grown trees came
from Nowak (1994). Formulas from Fleming (1988) formed the basis for average height growth calculations.
Annual gross 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 estimated from estimates of gross and net sequestration from
seven of the ten cities, and urban area and urban tree cover data for the United States. Annual net C sequestration
estimates were derived for seven cities by subtracting the annual gross emission estimates from the annual gross
7-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
sequestration estimates.13 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 (0.30 kg C/m2-year) was then multiplied by the estimate of national urban
tree cover area to estimate national annual gross sequestration. To estimate national annual net sequestration, the
estimate of national annual gross sequestration was multiplied by the average of the ratios of net to gross
sequestration for those cities that had both estimates (0.70). The urban tree cover estimates for each of the 10 cities
and the United States were obtained from Dwyer et al. (2000) and Nowak et al. (2002). The urban area estimates
were taken from Nowak et al. (2005).
Table 7-30: Carbon Stocks (Metric Tons C), Annual Carbon Sequestration (Metric Tons C/yr), Tree Cover
(Percent), and Annual Carbon Sequestration per Area of Tree Cover (kg C/m2 cover-yr) for Ten U.S. Cities
City
Carbon
Stocks
Gross Annual Net Annual
Sequestration Sequestration
Tree
Cover
Gross Annual
Sequestration per
Area of Tree Cover
Net Annual
Sequestration per
Area of Tree Cover
New York, NY
1,225,200
38,400
20,800
20.9
0.23
0.12
Atlanta, GA
1,220,200
42,100
32,200
36.7
0.34
0.26
Sacramento, CA
1,107,300
20,200
NA
13.0
0.66
NA
Chicago, IL
854,800
40,100
NA
11.0
0.61
NA
Baltimore, MD
528,700
14,800
10,800
25.2
0.28
0.20
Philadelphia, PA
481,000
14,600
10,700
15.7
0.27
0.20
Boston, MA
289,800
9,500
6,900
22.3
0.30
0.22
Syracuse, NY
148,300
4,700
3,500
24.4
0.30
0.22
Oakland, CA
145,800
NA
NA
21.0
NA
NA
Jersey City, NJ
19,300
800
600
11.5
0.18
0.13
NA = not analyzed.
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 ten U.S. cities. A 10 percent
uncertainty was associated with urban area estimates, based on expert judgment. A 5 percent uncertainty was
associated with national urban tree covered area. Uncertainty associated with estimates of gross and net C
sequestration for the ten U.S. cities was based on standard error estimates for each of the city-level sequestration
estimates as reported in Nowak et al. (2002). These estimates are based on field data collected in ten U.S. cities,
and uncertainty in these estimates increases as they are scaled up to the national level.
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.
However, both the omission of urban soil C flux and the potential overlap with forest C are believed to be relatively
minor (Nowak 2002a). Because these factors are currently inestimable due to data limitations, they are not
13 Three cities did not have net estimates.
Land Use, Land-Use Change, and Forestry 7-39
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
Public Review Draft
quantified as part of this analysis.
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 7-31. The net C flux
from changes in C stocks in urban trees was estimated to be between -108.5 and -71.3 Tg C02 Eq. at a 95 percent
confidence level. This indicates a range of 23 percent below and 19 percent above the 2005 flux estimate of -88.5
Tg C02 Eq.
Table 7-31: Tier 2 Quantitative Uncertainty Estimates for Net C Flux from Changes in C Stocks in Urban Trees (Tg
2005 Flux
Estimate
Uncertainty Range Relative to Flux Estimate
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower
Bound
Upper
Bound
Lower Upper
Bound Bound
Changes in C Stocks in
Urban Trees
C02
(88.5)
(108.5)
(71.3)
-23% +19%
Note: Parentheses indicate negative values or net sequestration.
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
the correspondence, the methods used to collect the urban tree sequestration and area data were further clarified and
the use of these data in the inventory was reviewed and validated (Nowak 2002a).
Recalculations Discussion
In previous inventories, estimates of Tg C had been rounded to 2 signficant figures based on Nowak 2002b. Since a
Tier 2 uncertainty analysis was run for this source starting from the current Inventory, this rounding step was
removed. This change resulted in a change in emission estimates for 1990 through 2004. On average, estimates of
net C flux from urban trees decreased by less than one percent over the period from 1990 to 2004 relative to the
previous report.
Planned Improvements
New estimates of C in urban trees based on new satellite and field data are being developed. Once those data
become available, they will be incorporated into estimates of net C flux resulting from urban trees.
A consistent representation of the managed land base in the United States is also being developed. A component of
this project will involve reconciling the overlap between urban forest and non-urban forest GHG 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 U.S. inventory. One goal of the plan to develop the consistent representation of the
United States land base is to eliminate this overlap.
Direct N20 Fluxes from Settlement Soils (IPCC Source Category 5E1)
Of the synthetic N fertilizers applied to soils in the United States, approximately 10 percent are 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 N20 emissions per unit
area. In addition to synthetic N fertilizers, a portion of surface applied sewage sludge is applied to settlement areas.
In 2005, N20 emissions from this source were 5.8 Tg C02 Eq. (19 Gg). There was an overall increase of 13 percent
7-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
over the period from 1990 through 2005 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 7-32.
Table 7-32: N2Q Fluxes from Soils in Settlements Remaining Settlements (Tg C02 Eq. and Gg)
Year Tg C02 Eq. G
g_
1990
5.1
17
1995
5.5
18
2000
2001
2002
2003
2004
2005
5.6
5.5
5.6
5.8
6.0
5.8
18
18
18
19
19
19
Note: These estimates include direct N20 emissions from N fertilizer additions only. Indirect N20 emissions from fertilizer
additions are reported in the Agriculture chapter. These estimates include emissions from both Settlements Remaining
Settlements and from Land Converted to Settlements.
Methodology
For soils within Settlements Remaining Settlements, the IPCC Tier 1 approach was used to estimate soil N20
emissions from synthetic N fertilizer and sewage sludge additions. Estimates of direct N20 emissions from soils in
settlements were based on the amount of N 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 assumed to be 10 percent of the total synthetic fertilizer used in the
United States (Qian 2004). Total synthetic fertilizer applications were derived from fertilizer statistics (TVA 1991,
1992, 1993, 1994; AAPFCO 1995, 1996, 1997, 1998, 1999, 2000b, 2002, 2003, 2004, 2005, 2006) and a recent
AAPFCO database (AAPFCO 2000a). Sewage sludge applications were derived from national data on sewage
sludge generation, disposition, and nitrogen content (see Annex 3.11 for further detail). The total amount of N
resulting from these sources was multiplied by the IPCC default emission factor for applied N (1 percent) to
estimate direct N20 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 N20 Emissions from Agricultural Soil Management source category of the Agriculture chapter.
Uncertainty
The amount of N20 emitted from settlements depends not only on N inputs, but also on a large number of variables,
including organic C availability, 02 partial pressure, soil moisture content, pH, temperature, and irrigation/watering
practices. The effect of the combined interaction of these variables on N20 flux is complex and highly uncertain.
The IPCC default methodology used here does not incorporate any of these variables and only accounts for
variations in national fertilizer 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 and the
emission factors used to derive emission estimates.
The uncertainty in the amounts of sewage sludge applied to non-agricultural lands and used in surface disposal was
based on the uncertainty of the following data points, which were used to determine the amounts applied in 2005:
(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.
Land Use, Land-Use Change, and Forestry 7-41
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 7-33. N20 emissions from soils
in Settlements Remaining Settlements in 2005 were estimated to be between 2.1 and 10.7 Tg C02 Eq. at a 95 percent
confidence level. This indicates a range of 49 percent below to 163 percent above the 2005 emission estimate of 5.8
Tg C02 Eq.
Table 7-33: Tier 2 Quantitative Uncertainty Estimates of N20 Emissions from Soils in Settlements Remaining
Settlements (Tg C02 Eq. and Percent)
2005
Uncertainty Range Relative to 2005 Emission
Emissions
Estimate
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower
Bound
Upper
Bound
Settlements Remaining Settlements'.
N20 Fluxes from Soils
N20
5.8
2.1 10.7
-49%
163%
Note: This estimate includes direct N20 emissions from N fertilizer additions to both Settlements Remaining Settlements and
from Land Converted to Settlements.
Recalculations Discussion
There were several recalculations for the current inventory. The 2003 and 2004 total fertilizer application data were
updated from the APPFCO Commercial Fertilizers 2003 Report (2004) and 2004 Report (2005). An error in unit
conversion used in the sewage sludge calculations was corrected. Changes were made to the data used to calculate
the amount of sewage sludge applied from 2001 to 2005, as discussed in Annex 3.11. In the previous inventory,
sewage sludge applied as commercial fertilizer was included in total synthetic fertilizer applied, as well as added to
the total synthetic fertilizer applied, effectually double counting the amounts of sewage sludge applied to
settlements. This error was corrected by not including sewage sludge in total synthetic fertilizer applied. The IPCC
default emission factor of 1.25 percent for direct emissions from applied N was updated to 1 percent based on IPCC
(2006). Additionally, because the direct emission factor was developed based on total N inputs, the new method has
been revised to estimate direct N20 emissions based on total N input. Previously, a portion of the N inputs were
removed from the calculation of direct N20 emissions, because it was assumed to be lost through volatilization
before direct emissions occurred. All of these changes resulted in a 7.6 percent decrease in the emissions estimates
for 2004 and an average decrease of about 7.5 percent over the period from 1990 to 2004.
Planned Improvements
The process-based DAYCENT model, which was used to estimate N20 emissions from cropped soils, could also be
used to simulate direct and indirect emissions from settlement soils using state-level settlement area data from the
National Resource Inventory.
7.8. Land Converted to Settlements (Source Category 5E2)
Land-use change is constantly occurring, and land under a number of uses undergoes urbanization in the United
States each year. However, data on the amount of land converted to settlements is currently lacking. Given the lack
of available information relevant to this particular IPCC source category, it is not possible to separate C02 or N20
fluxes on Land Converted to Settlements from fluxes on Settlements Remaining Settlements at this time.
7.9. 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
7-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
be stored for very long periods.
C storage is associated with particular land uses. For example, harvested wood products are accounted for under
Forest Land Remaining Forest Land because these products are a component of this ecosystem. C stock changes in
yard trimmings and food scraps are associated with settlements, but removals do not occur within settlements. Yard
trimming and food scrap C storage is therefore reported under "Other."
Both the amount of yard trimmings and food scraps collected annually and the fraction that is landfilled have
declined over the last decade. In 1990, nearly 51 million metric tons (wet weight) of yard trimmings and food
scraps were generated (i.e., put at the curb for collection or taken to disposal or composting facilities) (EPA 2005).
Since then, programs banning or discouraging disposal have led to an increase in backyard composting and the use
of mulching mowers, and a consequent 18 percent decrease in the amount of yard trimmings collected. At the same
time, a dramatic increase in the number of municipal composting facilities has reduced the proportion of collected
yard trimmings that are discarded in landfills—from 72 percent in 1990 to 35 percent in 2003 (the most recent year
for which data are available; 2004 and 2005 values are assumed to equal 2003). There is considerably less
centralized composting of food scraps; generation has grown by 32 percent since 1990, though the proportion of
food scraps discarded in landfills has decreased slightly from 81 percent in 1990 to 78 percent in 2003. Overall,
there has been a decrease in the yard trimmings and food scrap landfill disposal rate, which has resulted in a
decrease in the rate of landfill C storage to 8.8 Tg C02 Eq. in 2005 from 23.0 Tg C02 Eq. in 1990 (Table 7-34 and
Table 7-35).
Table 7-34: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C02 Eq.)
Carbon Pool
1990
1995
2000
2001
2002
2003
2004
2005
Yard Trimmings
(20.2)
(11.2)
(5.2)
(5.4)
(5.7)
(5.9)
(6.0)
(6.0)
Grass
(2.4) '
(1.2)
(0.5)
(0.6)
(0.6)
(0.7)
(0.7)
(0.8)
Leaves
(8.2) ' 1
(4.6)
(2.1)
(2.1)
(2.2)
(2.3)
(2.3)
(2.3)
Branches
(9.6) j
(5.5)
(2.7)
(2.7)
(2.8)
(2.9)
(2.9)
(2.9)
Food Scraps
(2.8)
(1.8)
(3.2)
(3.2)
(3.2)
(3.1)
(2.9)
(2.7)
Total Net Flux
(23.0)
(13.0)1111
(8.5)
(8.6)
(8.9)
(9.0)
(8.9)
(8.8)
Note: Totals may not sum due to independent rounding.
Table 7-35: Net Changes in Yard Trimming and Food Scrap Stocks in Landfills (Tg C)
Carbon Pool
1990
1995
2000
2001
2002
2003
2004
2005
Yard Trimmings
(5.5)
(3.1)
(1.4)
(1.5)
(1.6)
(1.6)
(1.6)
(1.6)
Grass
(0.6) ,
(0.3)
(0.1)
(0.2)
(0.2)
(0.2)
(0.2)
(0.2)
Leaves
(2.2)
(1.2)
(0.6)
(0.6)
(0.6)
(0.6)
(0.6)
(0.6)
Branches
(2.6) ,
(1.5)
(0.7)
(0.7)
(0.8)
(0.8)
(0.8)
(0.8)
Food Scraps
(0.8)
(0.5)
(0.9)
(0.9)
(0.9)
(0.8)
(0.8)
(0.7)
Total Net Flux
(6.3)
(3.5)
(2.3)
(2.3)
(2.4)
(2.5)
(2.4)
(2.4)
Note: Totals may not sum due to independent rounding.
Methodology
As empirical evidence shows, the removal of C from the natural cycling of C between the atmosphere and biogenic
materials, which occurs when wastes of biogenic origin are deposited in landfills, sequesters C (Barlaz 1998, 2005).
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
Forestery sector in IPCC (2003) and IPCC (2006). C stock estimates were calculated by determining the mass of
landfilled C resulting from yard trimmings or food scraps discarded in a given year; adding the accumulated
landfilled C from previous years; and subtracting the portion of C landfilled in previous years that decomposed.
To determine the total landfilled C stocks for a given year, the following were estimated: 1) the composition of the
Land Use, Land-Use Change, and Forestry 7-43
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Public Review Draft
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: 2003
Facts and Figures (EPA 2005), which provides data for 1960, 1970, 1980, 1990, 1995, and 2000 through 2003. To
provide data for some of the missing years in the 1990 through 1999 period, two earlier reports were used
(Characterization of Municipal Solid Waste in the United States: 1998 Update (EPA 1999), and Municipal Solid
Waste in the United States: 2001 Facts and Figures (EPA 2003)). Remaining years in the time series for which
data were not provided were estimated using linear interpolation. Values for 2004 and 2005 are assumed to be
equal to values for 2003. The reports do not subdivide discards of individual materials into volumes landfilled and
combusted, although they provide an estimate of the proportion of overall wastestream discards managed in landfills
and combustors (i.e., ranging from 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) (Table 7-36).
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), a portion of the initial C resists decomposition and is essentially persistent
in the landfill environment; the modeling approach applied here builds on his findings. Barlaz (1998, 2005)
conducted a series of experiments designed to measure biodegradation of yard trimmings, food scraps, and other
materials, in conditions designed to promote decomposition (i.e., by providing ample moisture and nutrients). After
measuring the initial C content, the materials were placed in sealed containers along with a "seed" containing
methanogenic microbes from a landfill. Once decomposition was complete, the yard trimmings and food scraps
were re-analyzed for C content; the C remaining in the solid sample can be expressed as a proportion of initial C
(shown in the row labeled "CS" in Table 7-36).
For purposes of simulating U.S. landfill C flows, the proportion of C stored is assumed to persist in landfills; the
remaining portion is assumed to degrade (and results in emissions of CH4 and C02; the CH4 emissions resulting
from decomposition of yard trimmings and food scraps are accounted for in the Waste chapter). The degradable
portion of the C is assumed to decay according to first order kinetics. Grass and food scraps are assumed to have a
half-life of 5 years; leaves and branches are assumed to have a half-life of 20 years.
For each of the four materials (grass, leaves, branches, food scraps), the stock of C in landfills for any given year is
calculated according to the following formula:
LFCjt = E W1>n x (1 - MQ) x ICQ x {[CS; x ICQ] + [(1 - (CS, x ICQ)) x e"k(t"n) ]}
where,
t = the year for which C stocks are being estimated,
LFCl t = the stock of C in landfills in year I. for waste i (grass, leaves, branches, food scraps)
\VI M = the mass of waste i disposed in landfills in year n. in units of wet weight
n = the year in which the waste was disposed, where 1960 < n < t
MQ = moisture content of waste
CS! = the proportion of initial C that is stored for waste
7-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Public Review Draft
ICC! = the initial C content of waste
e = the natural logarithm, and
k = the first order rate constant for waste which is equal to 0.693 divided by the half-life for
decomposition.
For a given year I. the total stock of C in landfills (TLFCt) is the sum of stocks across all four materials. The annual
flux of C in landfills (Ft) for year t is calculated as the change in stock compared to the preceding year:
Ft = TLFCt-TLFQ.!
Thus, the C placed in a landfill in year n is tracked for each year t through the end of the inventory period (2005).
For example, disposal of food scraps in 1960 resulted in depositing about 1,140,000 metric tons of C. Of this
amount, 16 percent (180,000 metric tons) is persistent; the remaining 84 percent (960,000 metric tons) is
degradable. By 1965, half of the degradable portion (480,000 metric tons) decomposes, leaving a total of 660,000
metric tons (the persistent portion, plus the remaining half of the degradable portion).
Continuing the example, by 2005, the total food scraps C originally disposed in 1960 had declined to 181,000
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 2005), the total landfill C from food
scraps in 2005 was 31.3 million metric tons. This value is then added to the C stock from grass, leaves, and
branches to calculate the total landfill C stock in 2005, yielding a value of 220.6 million metric tons (as shown in
Table 7-37). 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 7-35) 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 2005 shown in
Table 7-35 (2.4 Tg C) is equal to the stock in 2005 (220.6 Tg C) minus the stock in 2004 (218.2 Tg C).
When applying the C storage data reported by Barlaz (1998), 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 methane (CH4-C, measured),
• C output as C02 (C02-C, not measured), and
• Residual stored C (CS, measured).
In a simple system where the only C fates are CH4, C02, and C storage, the following equation is used to attain a
mass balance:
CH4-C + C02-C + CS = ICC
The experiments by Barlaz and his colleagues (Barlaz 1998, Eleazer et al. 1997) did not measure C02 outputs in
experiments. However, if the only decomposition is anaerobic, then CH4-C = C02-C.14 Thus, the system should be
defined by:
2 x CH4-C + CS = ICC
The C outputs (=2 x CH4-C + CS ) were less than 100 percent of the initial C mass for food scraps, leaves, and
branches (75, 86, and 90 percent, respectively). For these materials, it was assumed that the unaccounted for C had
exited the experiment as CH4 and C02, and no adjustment was made to the measured value of CS.
14 The molar ratio of CH4 to C02 is 1:1 for carbohydrates (e.g., cellulose, hemicellulose). For proteins as C3 2H5ON0 g6, the
molar ratio is 1.65 CH4 per 1.55 C02 (Barlaz et al. 1989). Given the predominance of carbohydrates, for all practical purposes,
the overall ratio is 1:1.
Land Use, Land-Use Change, and Forestry 7-45
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Public Review Draft
In the case of grass, the outputs were slightly more (103 percent) than initial C mass. To resolve the mass balance
discrepancy, it was assumed that the measurements of initial C content and methane mass were accurate. Thus, the
value of CS was calculated as the residual of ICC (initial C content) minus (2 x CH4-C). This adjustment reduced
the C storage value from the 71 percent reported by Barlaz (1998) to 68 percent (as shown in Table 7-36).
Table 7-36: 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 (% H20)
70
30
10
70
CS, proportion of initial C stored (%)
68
72
77
16
Initial C Content (%)
45
42
49
51
Half-life (years)
5
20
20
5
Table 7-37: Carbon Stocks in Yard Trimmings and Food Scraps in Landfills (Tg C)
Carbon Pool
1990
1995
2000
2001
2002
2003
2004
2005
Yard Trimmings
149.8
171.5
181.4
182.9
184.4
186.0
187.7
189.3
Grass
18.:
20.7
21.7
21.8
22.0
22.2
22.4
22.6
Leaves
61.3
70.1
74.1
74.7
75.3
75.9
76.6
77.2
Branches
70.3
80.7
85.6
86.4
87.1
87.9
88.7
89.5
Food Scraps
20.3
23.4
27.2
28.1
28.9
29.8
30.5
31.3
Total Carbon
Stocks
170.1
195.0
208.6
210.9
213.3
215.8
218.2
220.6
Note: Totals may not sum due to independent rounding.
Uncertainty
The estimation of C storage in landfills is directly related to the following yard trimming and food scrap 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
uncertainties associated with each of these factors.
A Monte Carlo (Tier 2) uncertainty analysis was then applied to estimate the overall uncertainty of the sequestration
estimate. The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 7-38. Total yard
trimmings and food scraps C02 flux in 2005 was estimated to be between -17.1 and -5.3 Tg C02 Eq. at a 95 percent
confidence level (or 19 of 20 Monte Carlo stochastic simulations). This indicates a range of 94 percent below to 40
percent above the 2005 flux estimate of -8.8 Tg C02 Eq.
Table 7-38: Tier 2 Quantitative Uncertainty Estimates for C02 Flux from Yard Trimmings and Food Scraps in
Landfills (Tg C02 Eq. and Percent)
7-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
2005 Flux
Estimate
Uncertainty Range Relative to Flux Estimate"
Source
Gas
(Tg C02 Eq.)
(Tg C02 Eq.)
(%)
Lower Upper
Bound Bound
Lower Upper
Bound Bound
Yard Trimmings and
Food Scraps
C02
(8.8)
(17.1) (5.3)
-94% +40%
1 aRange of flux estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
2 Note: Parentheses indicate negative values or net C sequestration.
3
4 QA/QC and Verification
5 A QA/QC analysis was performed for data gathering and input, documentation, and calculation. The QA/QC check
6 revealed the need to update one of the input values, addressed in the recalculations discussion below.
7 Recalculations Discussion
8 The only recalculation performed for the current inventory was a correction. The value for the initial C content
9 (ICC) of leaves was updated for the current inventory (41.6 percent) based on updated experimental results
10 provided by Barlaz (2005). Although the previous inventory used an updated value for the carbon stored (CS) for
11 leaves, the initial C content had not been updated (i.e., the earlier experimental value of 49.4 percent was used).
12 This recalculation fixed that problem, and has the effect of reducing the stocks of C from leaves, and also reducing
13 (by about 5 percent) the annual flux for yard trimmings and food scraps.
14 In the previous inventory, Changes in Yard Trimming and Food Scrap C Stocks in Landfills was included in the
15 Settlements Remaining Settlements section of this chapter. However, although C stock changes in yard trimmings
16 and food scraps are associated with settlements, removals do not occur within settlements. Therefore, yard
17 trimming and food scrap C storage is now reported under "Other."
18 Planned Improvements
19 Future work may evaluate the potential contribution of inorganic C to landfill sequestration, as well as the
20 consistency between the estimates of C storage described in this chapter and the estimates of landfill CH4 emissions
21 described in the Waste chapter.
Land Use, Land-Use Change, and Forestry 7-47
-------
-------
Atmosphere
Combustion from
forest fires (carbon
dioxide, methane)
Methane
Flaring
and
Utilization
Legend
] Carbon Pool
—~ Carbon transfer or flux
Combustion
Source: Heath et al. 2003
-------
Year
/ ^ / / / / / ^ ^ ^ #
$ -C?> j3" jS> -CS^ J?
Soil
Harvested Wood
Forest, Nonsoil
Total Net Change
Figure 7-2: Estimates of Net Annual Changes in Carbon Stocks for Major Carbon Pools
-------
Figure 7-3
Average Carbon Density in the Forest Tree Pool in the Conterminous U.S., 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.)
Land Use, Land-Use Change, and Forestry 7-11
-------
Figure 7-4
Net Soil C Stock Change for Mineral Soils in Cropland Remaining Cropland, 2005
Tg C02 Eq/yr
~ 0 to 1
~ -0.1 toO
~ -0.5 to -0.1
~ -1 to -0.5
H-2to-1
¦ -4 to-2
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 Inventory computations. See Methodology for additional details.
7-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Figure 7-5
Net Soil C Stock Change for Organic Soils in Cropland Remaining Cropland, 2005
Tg C02 Eq/yr
¦ 2 to 8
~ 1 to 2
~ 0.5 to 0.1
~ 0.1 to 0.5
~ 0 to 0.1
I I No organic soils
Note: Values greater than zero represent emissions.
Land Use, Land-Use Change, and Forestry 7-3
-------
Figure 7-6
Net Soil C Stock Change for Mineral Soils in Land Converted to Cropland, 2005
7-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Figure 7-7
Net Soil C Stock Change for Organic Soils in Land Converted to Cropland, 2005
Land Use, Land-Use Change, and Forestry 7-5
-------
Figure 7-8
Net Soil C Stock Change for Mineral Soils in Grassland Remaining Grassland, 2005
Note: Values greater than zero represent emissions, and values less than zero represent sequestration. Map accounts for fluxes associated with the
Tier 2 and 3 Inventory computations. See Methodology for additional details.
7-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Figure 7-9
Net Soil C Stock Change for Organic Soils in Grassland Remaining Grassland, 2005
Tg C02 Eq/yr
¦ 0.5 to 0.6
~ 0.1 to 0.5
~ 0 to 0.1
I I No organic soils
Note: Values greater than zero represent emissions.
Land Use, Land-Use Change, and Forestry 7-7
-------
Figure 7-10
Net Soil C Stock Change for Mineral Soils in Land Converted to Grassland, 2005
7-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Figure 7-11
Net Soil C Stock Change for Organic Soils in Land Converted to Grassland, 2005
Land Use, Land-Use Change, and Forestry 7-9
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Public Review Draft
8. Waste
Waste management and treatment activities are sources of greenhouse gas emissions (see Figure 8-1). Landfills
accounted for approximately 25 percent of total U.S. anthropogenic CH4 emissions in 2005,1 the largest
contribution of any CH4 source in the U.S. Additionally, wastewater treatment accounts just under 5 percent of U.S.
CH4 emissions. Nitrous oxide (N20) emissions from the discharge of wastewater treatment effluents into aquatic
environments were estimated, as were N20 emissions from the treatment process itself. Nitrogen oxide (NOx),
carbon monoxide (CO), and non-CH4 volatile organic compounds (NMVOCs) are emitted by waste activities, and
are addressed separately at the end of this chapter. A summary of greenhouse gas and indirect greenhouse gas
emissions from the Waste chapter is presented in Table 8-1 and Table 8-2.
Figure 8-1: 2005 Waste Chapter Greenhouse Gas Sources
Overall, in 2005, waste activities generated emissions of 165.4 Tg C02 Eq., or just over 2 percent of total U.S.
greenhouse gas emissions.
Table 8-1: Emissions from Waste (Tg C02 Eq.)
Gas/Source
1990
1995
2000
2001
2002
2003
2004
2005
ch4
1S5.S
182.2
158.3
153.5
156.2
160.5
157.8
157.4
Landfills
161.li
157.1
131.9
127.6
130.4
134.9
132.1
132.0
Wastewater Treatment
24.:-
25.1
26.4
25.9
25.8
25.6
25.7
25.4
n2o
6.4
6.9
7.6
7.6
7.7
7.8
7.9
8.0
Domestic Wastewater
11111
Treatment
(> 4
6.9
7.6
7.6
7.7
7.8
7.9
8.0
Total
192.2
189.1
165.9
161.1
163.9
168.4
165.7
165.4
Note: Totals may not sum due to independent rounding.
Table 8-2: Emissions from Waste (Gg)
Gas/Source
1990
1995
2000
2001
2002
2003
2004
2005
ch4
8,848
8,674
7,537
7,310
7,439
7,645
7,514
7,496
Landfills
7,668
7,479
6,280
6,078
6,210
6,425
6,292
6,286
Wastewater Treatment
1,180
1,195
1,257
1,232
1,229
1,220
1,222
1,210
n2o
21
22 ,
24
25
25
25
26
26
Domestic Wastewater
Treatment
21
22
24
25
25
25
26
26
NOx
+111111
1
2
2
2
2
2
2
CO
1
2
8
8
7
7
7
7
NMVOCs
673
731
119
122
116
116
116
116
Note: Totals may not sum due to independent rounding.
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.
Waste 8-1
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
8.1. Landfills (IPCC Source Category 6A1)
In 2005, landfill CH4 emissions were approximately 132 Tg C02 Eq. (6,286 Gg), representing the largest source of
CH4 emissions in the United States. 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 89 percent of total landfill
emissions, while industrial landfills accounted for the remainder. Approximately 1,800 operational landfills exist in
the United States, with the largest landfills receiving most of the waste and generating the majority of the CH4
(BioCycle 2006, adjusted to include missing data from five states).
After being placed in a landfill, waste (such as paper, food scraps, and yard trimmings) is initially decomposed by
aerobic bacteria. After the oxygen has been depleted, the remaining waste is available for consumption by
anaerobic bacteria, which break down organic matter into substances such as cellulose, amino acids, and sugars.
These substances are further broken down through fermentation into gases and short-chain organic compounds that
form the substrates for the growth of methanogenic bacteria. These CH4-producing anaerobic bacteria convert the
fermentation products into stabilized organic materials and biogas consisting of approximately 50 percent carbon
dioxide (C02) and 50 percent CH4, by volume.2 Significant CH4 production typically begins one or two years after
waste disposal in a landfill and continues for 10 to 60 years.
From 1990 to 2005, net CH4 emissions from landfills decreased by approximately 18 percent (see Table 8-3 and
Table 8-4), with small increases occurring in some interim years. This downward trend in overall emissions is the
result of increases in the amount of landfill gas collected and combusted,3 which has more than offset the additional
CH4 emissions 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 municipal
solid waste in landfills, which is related to total municipal solid waste landfilled annually; (2) the characteristics of
landfills receiving waste (i.e., composition of waste-in-place, size, climate); (3) the amount of CH4 that is recovered
and either flared or used for energy purposes; and (4) the amount of CH4 oxidized in landfills instead of being
released into the atmosphere. The estimated annual quantity of waste placed in landfills increased from about 209
Tg in 1990 to 304 Tg in 2005, an increase of 45 percent (see Annex 3.14). During this period, the estimated CH4
recovered and combusted from landfills increased as well. In 1990, for example, approximately 1,079 Gg of CH4
were recovered and combusted (i.e., used for energy or flared) from landfills. In 2005, the estimated quantity of
CH4 recovered and combusted increased to 5,668 Gg, a 7 percent increase from 2004 levels.
Over the next several years, the total amount of municipal solid waste generated is expected to increase as the U.S.
population continues to grow. The percentage of waste landfilled, however, may decline due to increased recycling
and composting practices. In addition, the quantity of CH4 that is recovered and either flared or used for energy
purposes is expected to increase as a result of 1996 federal regulations that require large municipal solid waste
landfills to collect and combust landfill gas (see 40 CFR Part 60, Subpart Cc 2005 and 40 CFR Part 60, Subpart
WWW 2005), voluntary programs encouraging CH4 recovery and use such as EPA's Landfill Methane Outreach
Program (LMOP), and federal and state economic incentives.
Table 8-3. CH4 Emissions from Landfills (Tg C02 Eq.)
Activity W90 W95 2000 2001 2002 2003 2004 2005
MSW Landfills 18S " 2i>4 " 217.3 221.4 227.2 234.9 242.4 249.6
Industrial Landfills 12.') 13.>> 15.4 15.6 15.7 15.9 16.0 16.1
Recovered
2 The percentage of C02 in biogas released from a landfill may be smaller because some C02 dissolves in landfill water
(Bingemer and Crutzen 1987). Additionally, less than 1 percent of landfill gas is typically composed of non-methane volatile
organic compounds (NMVOCs).
3 The C02 produced from combusted landfill CH4 at landfills is not counted in national inventories as it is considered part of the
natural C cycle of decomposition.
8-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
Gas-to-Energy (17,<.) (22. -1 (49.0) (54.3) (54.4) (54.9) (57.1) (58.6)
Flared (5.0) (21.8) (37.1) (40.8) (43.7) (46.0) (54.4) (60.4)
Oxidized3 (17.9) (17.5) (14.7) (14.2) (14.5) (15.0) (14.7) (14.7)
Total 161.1) 157.1 131.9 127.6 130.4 134.9 132.1 132.0
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
a Includes oxidation at both municipal and industrial landfills.
Table 8-4. CH4 Emissions from Landfills (Gg)
Activity
1990
1995
2000
2001
2002
2003
2004
2005
MSW Landfills
8,985
<>745
10,348
10,541
10,820
11,188
11,543
11,885
Industrial Landfills
614
664
731
744
749
757
761
767
Recovered
Gas-to-Energy
Flared
Oxidized3
(840)
(239)
(852)
'' (1,061)
¦ (1,039)
/ (831) '
(2,335)
(1,766)
(698)
(2,588)
(1,943)
(675)
(2,590)
(2,080)
(690)
(2,614)
(2,192)
(714)
(2,720)
(2,593)
(699)
(2,790)
(2,877)
(698)
Total
7,668
7,479
6,280
6,078
6,210
6,425
6,292
6,286
Note: Totals may not sum due to independent rounding. Parentheses indicate negative values.
a Includes oxidation at municipal and industrial landfills.
Methodology
CH4 emissions from landfills were estimated to equal the CH4 produced from municipal solid waste landfills, plus
the CH4 produced by industrial landfills, minus the CH4 recovered and combusted, minus the CH4 oxidized before
being released into the atmosphere:
CH4 Solid Waste I CHj\|^\y + CHjmd R] Ox
where,
CH4, solid waste = CH4 emissions from solid waste
CH4 MSW = CH4 generation from municipal solid waste landfills,
CH4 md = CH4 generation from industrial landfills,
R = CH4 recovered and combusted, and
Ox = CH4 oxidized from MSW and industrial landfills before release to the atmosphere.
The methodology for estimating CH4 emissions from municipal solid waste landfills is based on the first order
decay model described in the IPCC (2006). Values for the CH4 generation potential (L0) and rate constant (k) were
obtained from an analysis of CH4 recovery rates for a database of 52 landfills and from published studies of other
landfills (RTI 2004; EPA 1998; SWANA 1998; Peer, Thorneloe, and Epperson 1993). The rate constant was found
to increase with average annual rainfall; consequently, values of k were developed for 3 ranges of rainfall. The
annual quantity of waste placed in landfills was apportioned to the 3 ranges of rainfall based on the percent of the
U.S. population in each of the 3 ranges, and historical census data were used to account for the shift in population to
more arid areas over time. For further information, see Annex 3.14.
National landfill waste generation and disposal data for 1989 through 2005 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 (2006) and national per capita solid waste
generation from BioCycle (2006). Estimates of the annual quantity of waste landfilled for 1960 through 1988 were
obtained from EP A's Anthropogenic Methane Emissions in the United States, Estimates for 1990: Report to
Congress (EPA 1993) and an extensive landfill survey by the EPA's Office of Solid Waste in 1986 (EPA 1988).
Although waste placed in landfills in the 1940s and 1950s contributes very little to current CH4 generation,
estimates for those years were included in the first order decay model for completeness in accounting for CH4
generation rates and are based on the population in those years and the per capita rate for land disposal for the
1960s.
Waste 8-3
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
Public Review Draft
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 2006), and a database
maintained by the Energy Information Administration (EIA) for the voluntary reporting of greenhouse gases (EIA
2006). The three databases were carefully compared to identify landfills that were in two or all three of the
databases to avoid double-counting reductions. Based on the information provided by the EIA and flare vendor
databases, the CH4 combusted by flares in operation from 1990 to 2005 was estimated. This quantity likely
underestimates flaring because these databases do not have information on all flares in operation. Additionally, the
EIA and LMOP databases provided data on landfill gas flow and energy generation for landfills with LFGTE
projects. If a landfill in the EIA database was also in the LMOP and/or the flare vendor database, the emissions
avoided were based on the EIA data because landfill owners or operators reported the amount recovered based on
measurements of gas flow and concentration, and the reporting accounted for changes over time. If both flare data
and LMOP recovery data were available for any of the remaining landfills (i.e., not in the EIA database), then the
emissions recovery was based on the LMOP data, which provides reported landfill-specific data on gas flow for
direct use projects and project capacity (i.e., megawatts) for electricity projects. The flare data, on the other hand,
only provided a range of landfill gas flow for a given flare size. Given that each LFGTE project is likely to also
have a flare, double counting reductions from flares and LFGTE projects in the LMOP database was avoided by
subtracting emissions reductions associated with LFGTE projects for which a flare had not been identified from the
emissions reductions associated with flares.
A destruction efficiency of 99 percent was applied to CH4 recovered to estimate CH4 emissions avoided. The value
for efficiency was selected based on the range of efficiencies (98 to 100 percent) recommended for flares in EPA's
AP-42 Compilation of Air Pollutant Emission Factors, Chapter 2.4 (EPA 1998) efficiencies used to establish new
source performance standards (NSPS) for landfills, and in recommendations for closed flares used in LMOP.
Emissions from industrial landfills were estimated from activity data for industrial production, waste disposal
factors, and the first order decay model. The amount of CH4 oxidized by the landfill cover at both municipal and
industrial landfills was assumed to be ten percent of the CH4 generated that is not recovered (IPCC 2006, Mancinelli
and McKay 1985, Czepiel et al. 1996). To calculate net CH4 emissions, both CH4 recovered and CH4 oxidized were
subtracted from CH4 generated at municipal and industrial landfills.
Uncertainty
Several types of uncertainty are associated with the estimates of CH4 emissions from landfills. The primary
uncertainty concerns the characterization of landfills. Information is not available on two fundamental factors
affecting CH4 production: the amount and composition of waste placed in every landfill for each year of its
operation. The approach used here assumes that the CH4 generation potential and the rate of decay that produces
CH4 as determined from several studies of CH4 recovery at landfills are representative of U.S. landfills. Also, the
approach used to estimate the contribution of industrial wastes to total CH4 generation introduces uncertainty.
Aside from uncertainty in estimating CH4 generation potential, uncertainty exists in the estimates of oxidation by
cover soils.
N20 emissions from the application of sewage sludge on landfills are not explicitly modeled as part of greenhouse
gas emissions from landfills. N20 emissions from sewage sludge applied to landfills would be relatively small
because the microbial environment in landfills is not very conducive to the nitrification and denitrification processes
that result in N20 emissions. The total nitrogen (N) in sewage sludge increased from 189 to 268 Gg total N
between 1990 and 2005, however; the quantity of sewage sludge applied to landfills decreased from 28 to 10
percent from 1990 to 2005.4
The results of the Tier 2 quantitative uncertainty analysis are summarized in Table 8-5. Landfill CH4 emissions in
4 The methodology for estimating the quantity of N in sewage sludge disposed via incineration, land application, surface
disposal, landfill, ocean dumping, and other is described in Annex 3.11 Methodology for Estimating N20 Emissions From
Agricultural Soil Management.
8-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
2005 were estimated to be between 80.5 and 174.2 Tg C02 Eq., which indicates a range of 39 percent below to 32
percent above the actual 2005 emission estimate of 132 Tg C02 Eq.
Table 8-5. Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Landfills (Tg C02 Eq. and Percent)
2005 Emission
Source Gas Estimate Uncertainty Range Relative to Emission Estimate"
(Tg CQ2 Eq.) (Tg CP2 Eq.) (%)
Lower Bound Upper Bound Lower Bound Upper Bound
Landfills CH4 132.0 805 174.2 -39% +32%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
Two recalculations affected the estimates of CH4 generation from landfills. For MSW landfills, the more accurate
integrated form of the first order decay model was applied, and a delay time of 6 months was incorporated. These
changes reduced the estimate of CH4 generation from MSW landfills by 4 percent over the time series. The second
change was an improvement in the estimate of CH4 generation from industrial landfills, which was based on
industrial production, waste disposal factors, and the first order decay model. For previous inventories, the
generation rate was estimated as simply 7 percent of CH4 generation from MSW landfills. This change resulted in a
decrease of 2 percent in the estimated CH4 generation at industrial landfills relative to the previous inventory.
Another recalculation affecting estimates of CH4 recovery was associated with updating the EIA, LMOP, and flare
vendor databases. The estimates of gas recovery by LFGTE projects and flares from 1990 to 2004 increased by 0.7
percent based on changes to the current inventory. This change is due in part to updating the EIA database and
identifying additional flares installed in 2004 that were not included in the previous inventory. The EIA database
for 2004 did not become available until late in 2005; consequently, the gas recovery rate for 2004 was estimated
from the 2003 data. The 2004 update showed that LFGTE projects in the EIA 2003 database reported more gas
recovery in 2004 than 2003, and additional landfills were included in the 2004 database, both of which increased the
estimate of CH4 recovery. A recalculation that had a minor effect was the application of a destruction efficiency of
99 percent to CH4 recovered to estimate CH4 emissions avoided.
The overall effect of these recalculations was an average decrease of 5 percent in the estimated CH4 emissions from
landfills over the 1990 to 2004 time series.
Planned Improvements
For future inventories, additional efforts will be made to improve the estimates of CH4 generation at industrial
landfills. Improvements to the flare database will be investigated, and an effort will be made to identify additional
landfills that have flares.
[Begin Text Box]
Box 8-1: Biogenic Emissions and Sinks of Carbon
C02 emissions from the combustion or decomposition of biogenic materials (e.g., paper, wood products, and yard
trimmings) grown on a sustainable basis are considered to mimic the closed loop of the natural carbon cycle - that
is, they return to the atmosphere C02 that was originally removed by photosynthesis. In contrast, CH4 emissions
from landfilled waste occur due to the man-made anaerobic conditions conducive to CH4 formation that exist in
landfills, and are consequently included in this inventory.
Depositing wastes of biogenic origin in landfills causes the removal of carbon from its natural cycle between the
atmosphere and biogenic materials. As empirical evidence shows, some of these wastes degrade very slowly in
landfills, and the carbon they contain is effectively sequestered in landfills over a period of time (Barlaz 1998,
2005). Estimates of carbon removals from landfilling of forest products, yard trimmings, and food scraps are
further described in the Land Use, Land-Use Change, and Forestry chapter, based on methods presented in IPCC
Waste 8-5
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Public Review Draft
(2003) and IPCC (2006).
[End Box]
8.2. Wastewater Treatment (IPCC Source Category 6B)
Wastewater treatment processes can produce anthropogenic CH4 and N20 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,5 or off site at centralized treatment systems. Centralized wastewater treatment systems may
include a variety of processes, ranging from lagooning to advanced tertiary treatment technology for removing
nutrients. In the United States, approximately 21 percent of domestic wastewater is treated in septic systems or
other on-site systems, while the rest is collected and treated centrally (U.S. Census Bureau 2006b).
Soluble organic matter is generally removed using biological processes in which microorganisms consume the
organic matter for maintenance and growth. The resulting biomass (sludge) is removed from the effluent prior to
discharge to the receiving stream. Microorganisms can biodegrade soluble organic material in wastewater under
aerobic or anaerobic conditions, where the latter condition produces CH4. During collection and treatment,
wastewater may be accidentally or deliberately managed under anaerobic conditions. In addition, the sludge may be
further biodegraded under aerobic or anaerobic conditions. The generation of N20 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 (N03) through the aerobic process
of nitrification. Denitrification occurs under anoxic conditions (without free oxygen), and involves the biological
conversion of nitrate into dinitrogen gas (N2). N20 can be an intermediate product of both processes, but is more
often associated with denitrification.
The principal factor in determining the CH4 generation potential of wastewater is the amount of degradable organic
material in the wastewater. Common parameters used to measure the organic component of the wastewater are the
Biochemical Oxygen Demand (BOD) and Chemical Oxygen Demand (COD). Under the same conditions,
wastewater with higher COD (or BOD) concentrations will generally yield more CH4than wastewater with lower
COD (or BOD) concentrations. BOD represents the amount of oxygen that would be required to completely
consume the organic matter contained in the wastewater through aerobic decomposition processes, while COD
measures the total material available for chemical oxidation (both biodegradable and non-biodegradable). Because
BOD is an aerobic parameter, it is preferable to use COD to estimate methane production. The principal factor in
determining the N20 generation potential of wastewater is the amount of N in the wastewater.
In 2005, CH4 emissions from domestic wastewater treatment were estimated to be 17.0 Tg C02 Eq. (809 Gg).
Emissions fluctuated from 1990 through 1996, and have decreased since 1997 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 2005, CH4 emissions from industrial wastewater treatment were estimated to be 8.4 Tg C02
Eq. (400 Gg). Industrial emission sources have increased across the time series through 1999 and then slightly
decreased in keeping with production changes associated with the treatment of wastewater from the pulp and paper,
meat and poultry, and the vegetables, fruits and juices processing industries.6 Table 8-6 and Table 8-7 provide CH4
and N20 emission estimates from domestic and industrial wastewater treatment. With respect to N20, the United
States identifies two distinct sources for N20 emissions from domestic wastewater: emissions from centralized
wastewater treatment processes, and emissions from effluent from centralized treatment systems that has been
5Package plants are treatment plants assembled in a factory, skid mounted, and transported to the treatment site.
6Emissions associated with refinery wastewater are estimated in Annex 2.3 Methodology for Estimating Carbon Emitted from
Non-Energy Uses of Fossil Fuels. Other industrial sectors include organic chemicals, starch production, alcohol refining,
creameries, and textiles; however, emissions from these sectors are considered to be insignificant.
8-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Public Review Draft
discharged into aquatic environments. The 2005 emissions of N20 from centralized wastewater treatment processes
and from effluent were estimated to be 0.2 Tg C02 Eq. (1 Gg) and 7.8 Tg C02 Eq. (25 Gg), respectively. Total N20
emissions from domestic wastewater were estimated to be 8.0 Tg C02 Eq. (26 Gg). N20 emissions from
wastewater treatment processes gradually increased across the time series as a result of increasing U.S. population
and protein consumption.
Table 8-6. CH4 and N2Q Emissions from Domestic and Industrial Wastewater Treatment (Tg C02 Eq.)
Activity
1990
I 1995
2000
2001
2002
2003
2004
2005
ch4
24.8
25,1
26.4
25.9
25.8
25.6
25.7
25.4
Domestic
17.4
161
17.7
17.5
17.3
17.2
17.1
17.0
Industrial*
7.4
8.4
8.7
8.4
8.5
8.4
8.5
8.4
n2o
6.4
6.9
7.6
7.6
7.7
7.8
7.9
8.0
Domestic
6.4
6.9 ¦
7.6
7.6
7.7
7.8
7.9
8.0
Total
31.2
32.0
I 34.0
33.5
33.5
33.4
33.6
33.4
* Industrial activity includes the pulp and paper, meat and poultry, and the vegetables, fruits and juices processing industries.
Note: Totals may not sum due to independent rounding.
Table 8-7. CH4 and N2Q Emissions from Domestic and Industrial Wastewater Treatment (Gg)
Activity
1990
1 1995
2000
2001
2002
2003
2004
2005
ch4
1,180
1195
1,257
1,232
1,229
1,220
1,222
1,210
Domestic
826
797
842
832
826
820
815
809
Industrial*
354
398
415
400
402
400
407
400
n2o
21
22
24
25
25
25
26
26
Domestic
21
1 22
24
25
25
25
26
26
* Industrial activity includes the pulp and paper, meat and poultry, and the vegetables, fruits and juices processing industries.
Note: Totals may not sum due to independent rounding.
Methodology
Domestic and Industrial Wastewater CH4 Emission Estimates
Domestic wastewater CH4 emissions originate from both septic systems and from centralized treatment systems,
such as publicly owned treatment works (POTWs). Within these centralized systems, CH4 emissions can arise from
aerobic systems that are not well managed, anaerobic systems (anaerobic lagoons and facultative lagoons), and from
anaerobic digesters when the captured biogas is not completely combusted. CH4 emissions from septic systems
were estimated by multiplying the total BOD5 produced in the United States by the percent of wastewater treated in
septic systems (21 percent), the maximum CH4 producing capacity for domestic wastewater (0.60 kg CH4/kg BOD),
and the CH4 correction factor (MCF) for septic systems (0.5). CH4 emissions from POTWs were estimated by
multiplying the total BOD5 produced in the United States by the percent of wastewater treated centrally (79
percent), the relative percentage of wastewater treated by aerobic and anaerobic systems, the maximum methane
producing capacity of domestic wastewater, and the relative MCFs for aerobic (zero or 0.3) and anaerobic (0.8)
systems. CH4 emissions from anaerobic digesters were estimated by multiplying the amount of biogas generated by
wastewater sludge treated in anaerobic digesters by the proportion of CH4 in digester biogas, the density of CH4,
and the destruction efficiency associated with burning the biogas in an energy/thermal device.7 The methodological
equations are:
7 Anaerobic digesters at wastewater treatment plants generated 799 Gg CH4 in 2005, 791 Gg of which was combusted in flares
or energy devices (assuming a 99% destruction efficiency).
Waste 8-7
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Public Review Draft
Emissions from Septic Systems = A
= (% onsite) x (total BOD5 produced) x (B0) x (MCF-septic) x 1/10A6
Emissions from Centrally Treated Aerobic Systems = B
= (% collected) x (total BOD5 produced) x (% aerobic) x (% operations not well managed) x (B0) x (MCF-
aerobicnotwellman) x 1/10A6
Emissions from Centrally Treated Anaerobic Systems = C
= (% collected) x (total BOD5 produced) x (% anaerobic) x (B0) x (MCF-anaerobic) x 1/10A6
Emissions from Anaerobic Digesters = D
= [(POTWflowAD) x (digester gas)/(per capita flow)] x 0.0283 x (FRAC_CH4) x (365.25) x (density of
methane) x (1-DE) x 1/10A9
Total CH4 Emissions (Gg) = A + B + C + D
where:
% onsite =
% collected =
% aerobic =
% anaerobic =
% operations not well managed =
Total BOD5 produced =
B0 =
MCF-septic =
1/10A6 =
MCF-aerobic not well man. =
MCF-anaerobic =
DE =
POTWflowAD =
digester gas =
per capita flow =
0.0283 =
FRAC_CH4 =
density of methane =
1/10A9 =
flow to septic systems / total flow
flow to POTWs / total flow
flow to aerobic systems / total flow to POTWs
flow to anaerobic systems / total flow to POTWs
percent of aerobic systems that are not well managed and in which
some anaerobic degradation occurs
kg BOD/capita/day x U.S. population x 365.25 days/yr
maximum methane producing capacity for domestic wastewater (0.60
kg CH4/kg BOD)
CH4 correction factor for septic systems (0.5)
conversion factor, kg to Gg
CH4 correction factor for aerobic systems that are not well managed
(0.3)
CH4 correction factor for anaerobic systems (0.8)
methane destruction efficiency from flaring or burning in engine (0.99
for enclosed flares)
wastewater influent flow to POTWs that have anaerobic digesters (gal)
cubic feet of digester gas produced per person per day (1.0
ft3/person/day) (Metcalf and Eddy 1991)
wastewater flow to POTW per person per day (100 gal/person/day)
conversion factor, ft3 to m3
proportion CH4 in biogas (0.65)
662 (g CH4/m3 CH4)
conversion factor, g to Gg
U.S. population data were taken from the U.S. Census Bureau International Database (US Census 2006a) and
include the populations of the United States, American Samoa, Guam, Northern Mariana Islands, Puerto Rico, and
the Virgin Islands. Table 8-8 presents U.S. population and total BOD5 produced for 1990 through 2005. The
proportions of domestic wastewater treated onsite versus at centralized treatment plants were based on data from the
1993, 1995, 1997, 1999, 2001, 2003, and 2005 American Housing Surveys conducted by the U.S. Census Bureau
(US Census 2006b), 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, collected by EPA (EPA 1992, 1996,
8-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Public Review Draft
2000, and 2004a).8 Data for intervening years were obtained by linear interpolation. The BOD5 production rate per
capita (0.09 kg/capita/day) for domestic wastewater was obtained from Metcalf and Eddy (1991and 2003). The
CH4 emission factor (0.6 kg CH4/kg BOD5) and the MCF data were taken from IPCC (2006a). The CH4 destruction
efficiency, 99 percent, was selected based on the range of efficiencies (98-100 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
the Landfill Methane Outreach Program (LMOP). The cubic feet of digester gas produced per person per day (1.0
ft3/person/day) and the proportion of methane inbiogas (0.65) come from Metcalf and Eddy 1991. The wastewater
flow to a POTW per person per day (100 gal/person/day) was taken from the Great Lakes-Upper Mississippi River
Board of State and Provincial Public Health and Environmental Managers, "Recommended Standards for
Wastewater Facilities (Ten-State Standards)" (2004).
Table 8-8. U.S. Population (Millions) and Domestic Wastewater BOD5 Produced (Gg)
Year Population BODs
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
Source: U.S. Census Bureau (2006a); Metcalf & Eddy 1991 and 2003.
CH4 emissions estimates from industrial wastewater were developed according to the methodology described in
IPCC (2006a). Industry categories that are likely to produce significant CH4 emissions from wastewater treatment
were identified. High volumes of wastewater generated and a high organic wastewater load were the main criteria.
The top three industries that meet these criteria are pulp and paper manufacturing; meat and poultry processing; and
vegetables, fruits, and juices processing. Table 8-9 contains production data for these industries.
Table 8-9. U.S. Pulp and Paper, Meat and Poultry, and Vegetables, Fruits and Juices Production (Tg)
Meat Poultry Vegetables,
Year Pulp and Paper (Live Weight Killed) (Live Weight Killed) Fruits and Juices
1990 128.9 27.3 14.6 40.5
1995 140.9 30.8 18.9 49.0
2000 142.8 32.1 22.2 52.7
2001 134.3 31.6 22.8 46.7
2002 132.7 32.7 23.5 49.1
2003 131.9 32.3 23.7 46.2
2004 136.4 31.2 24.4 49.1
2005 131.4 31.4 25.1 43.6
8 Aerobic and anaerobic treatment were determined based on unit processes in use at the facilities. Because the list of unit
processes became more extensive in the 2000 and 2004 surveys, the criteria used to identify aerobic and anaerobic treatment
differ slightly across the time series. Once facilities were identified as aerobic or anaerobic, they were separated by whether or
not they had anaerobic digestion in place. Once these classifications were determined, the flows associated with facilities in each
category were summed.
Waste 8-9
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Public Review Draft
CH4 emissions from these categories were estimated by multiplying the annual product output by the average
outflow, the organics loading (in COD) in the outflow, the percentage of organic loading assumed to degrade
anaerobically, and the emission factor. Ratios of BOD :COD in various industrial wastewaters were obtained from
the World Bank (1999) and used to estimate COD loadings. The B0 value used for all industries is the IPCC default
value of 0.25 kg CH4/kg COD (IPCC 2006a). The methodological equation is:
CH4 (industrial wastewater) = P x W x (COD) x TA xB0x MCF
where,
CH4 (industrial wastewater)
= Total CH4 emissions from industrial wastewater (kg/year)
P
= Industry output (metric tons/year)
W
= Wastewater generated (m3/metric ton of product)
COD
= Organics loading in wastewater (kg /m3)
TA
= Percent of wastewater treated anaerobically on site
MCF
= CH4 correction factor, indicating the extent to which the organic content
(measured as COD) degrades anaerobically
Bo
= Maximum CH4 producing potential of industrial wastewater (default value of
0.25 kg CH4/kg COD)
Wastewater treatment for the pulp and paper industry typically includes neutralization, screening, sedimentation,
and flotation/hydrocycloning to remove solids (World Bank 1999, Nemerow and Dasgupta 1991). Secondary
treatment (storage, settling, and biological treatment) mainly consists of lagooning. In determining the percent that
degrades anaerobically, both primary and secondary treatment were considered. Primary treatment lagoons are
aerated to reduce anaerobic activity. However, the lagoons are large and zones of anaerobic activity may occur and,
consequently, the primary lagoons are assumed to be 1.4 percent anaerobic (based on expert judgment).
Approximately 42 percent of the BOD passes on to secondary treatment, which is less likely to be aerated (EPA
1993a,b). Twenty-five percent of the BOD in secondary treatment lagoons was assumed to degrade anaerobically,
while 10 percent passes through to be discharged with the effluent (EPA 1997a). Consequently, the overall
percentage of wastewater organics that degrade anaerobically was determined to be 10.3 percent (i.e., 58% x 1.4%
+ 42% x 90% x 25%). A time series of CH4 emissions for 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 (AF&PA) and data published by Paper Loop were used to estimate production for 2002
through 2005 (Pulp and Paper 2005, 2006 and monthly reports from 2003-2006). The overall wastewater outflow
was estimated to be 85 m3/metric ton, and the average BOD loading entering the secondary treatment lagoons was
estimated to be 0.4 gram BOD/liter (EPA 1997b, EPA 1993a,b, 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 (US Poultry 2006) perform on-site treatment in
anaerobic lagoons. The IPCC default B0 of 0.25 kg COD/kg CH4 and default MCF of 0.8 for anaerobic lagoons
were used to estimate the methane produced from these on-site treatment systems. Production data, in carcass
weight and live weight killed for the meat and poultry industry, were obtained from the USD A Agricultural
Statistics Database and the Agricultural Statistics Annual Reports (USDA 2006). Data collected by EPA's Office of
Water provided estimates for wastewater flows into anaerobic lagoons: 5.3 and 12.5 m3/metric ton for meat and
poultry production (live weight killed), respectively (EPA 2002). The loadings are 2.8 and 1.5 g BOD/liter for meat
and poultry, respectively.
Treatment of wastewater from fruits, vegetables, and juices processing includes screening, coagulation/settling and
biological treatment (lagooning). The flows are frequently 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. EPA used the IPCC default B0 of 0.25 kg COD/kg CH4 and default
MCF of 0.8 for anaerobic treatment to estimate the methane produced from these on-site treatment systems. The
USD A National Agricultural Statistics Service (USD A 2006) provided production data for potatoes, other
8-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 vegetables, citrus fruit, non-citrus fruit, and grapes processed for wine. Outflow and BOD data, presented in Table
2 8-10, were obtained from EPA (1974) for potato, citrus fruit, and apple processing, and from the World Bank
3 (1999) for all other sectors.
4 Table 8-10. Wastewater Flow (m3/ton) and BOD Production (g/L) for U.S. Vegetables, Fruits and Juices
5 Production
Wastewater Outflow
BOD
Commodity
(m3/ton)
(g/L)
Vegetables
Potatoes
10.27
1.765
Other Vegetables
8.64
0.817
Fruit
Apples
3.66
1.317
Citrus
10.11
0.317
Non-citrus
11.7
0.982
Grapes (for wine)
1.53
2.346
6
7 Domestic Wastewater N20 Emission Estimates
8 The IPCC default methodology assumes that N disposal, and thus N20 emissions associated with land disposal,
9 subsurface disposal, and domestic wastewater treatment are negligible and all N is discharged directly into aquatic
10 environments. For the United States, N20 emissions from domestic wastewater (wastewater treatment) were
11 estimated using the IPCC methodology with three modifications:
12 • In the United States, a certain amount of N is removed with sewage sludge, which is applied to land,
13 incinerated or landfilled (NSLUDGE)- The N disposal into aquatic environments is reduced to account for the
14 sewage sludge application.9
15 • The IPCC methodology uses annual, per capita protein consumption (kg protein/(person-year)). This number is
16 likely to underestimate the amount of protein entering the sewer or septic system. Food (waste) that is not
17 consumed is often washed down the drain, as a result of the use of garbage disposals. Also, bath and laundry
18 water can be expected to contribute to N loadings. As a result, a factor of 1.4 for non-consumption N is
19 introduced for each year in the Inventory.10 Furthermore, a significant quantity of industrial wastewater (N) is
20 co-discharged with domestic wastewater. To account for this, a factor of 1.25 is used.11
21 • Small amounts of gaseous nitrogen oxides are formed as by-products in the conversion of nitrate to N gas in
22 anoxic biological treatment systems. Approximately 7 grams N20 is generated per capita per year if
23 wastewater treatment includes nitrification and denitrification (Scheehle and Doom 2001). Analysis of the
24 2000 CWNS shows 88 treatment plants in the United States, serving a population of 2,636,668 persons, with
25 denitrification as one of their unit operations. Based on an emission factor of 7 grams/capita/year,
26 approximately 17.5 metric tons of additional N20 may have been emitted via denitrification in 2000. Similar
9 The methodology for estimating the quantity of sewage sludge N not entering aquatic environments is described in Annex 3.11
10 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.
11 The type, composition, and quantity of this co-discharged wastewater vary greatly between municipalities. Metcalf & Eddy
(1991) provide a range of influent nitrogen concentrations of 20 to 85 mg/L TKN (average 55) for combined residential and
industrial wastewater, while residential wastewater loading was roughly estimated at 40 mg TKN/liter (see previous footnote).
Until better data become available, the amount of N in wastewater is increased by 10 mg/L to account for industrial co-discharge
(factor of 1.25).
Waste 8-11
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Public Review Draft
analysis was done for each year in the Inventory using data from CWNS on the amount of wastewater in
centralized systems treated in denitrification units.
With the modifications described above, N20 emissions from domestic wastewater were estimated using the
following methodology:
N2OTOtal —
N2Oplant —
N2C^\rr!)i ;\n —
N2Owoutmt/deNIT "
N2Oeffluent —
where,
N2Ototal =
N2OpLANT =
N2Omt/denit =
N2OwOUT nit/denit =
N2Oeffluent =
USpop =
USpoPND =
WWTP =
EFi =
EF2 =
Protein =
Fnpr =
Fnon-con =
Find-com =
NslUDGE =
EF3 =
44/28 =
N2Oplant + N20
EFFLUENT
N20Mt/denit N20WOutmt/denit
[(USP0PND) x EF2] x 1/10A9
[((USpop x WWTP) - USP0PND) x EFJ x 1/10*9
[(USpop x Protein
X Fm'K X Fnon-CON X Fjnd.com,
) - Ns]
: EF3 x 44/28} x 1/10A6
Annual emissions of N20
N20 emissions from centralized wastewater treatment plants
N20 emissions from centralized wastewater treatment plants with
nitrification/denitrification
N20 emissions from centralized wastewater treatment plants without
nitrification/denitrification
N20 emissions from wastewater effluent discharged to aquatic environments
U.S. population
U.S. population that is served by biological denitrification (from CWNS)
Fraction of population using WWTP (as opposed to septic systems)
Emission factor (3.2 g N20/person-year)
Emission factor (7 g N20/person-year)
Annual per capita protein consumption (kg/person/year)
Fraction of N in protein, default = 0.16 (kg N/kg protein)
Factor for non-consumed protein added to wastewater
Factor for industrial and commercial co-discharged protein into the sewer system
N removed with sludge, kg N/yr
Emission factor (0.005 kg N20 -N/kg sewage-N produced)
Molecular weight ratio of N20 to N2
U.S. population data were taken from the U.S. Census Bureau International Database (US Census 2006a) 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
1993, 1995, 1997, 1999, 2001, and 2003 American Housing Survey (US Census 2006b). Data for intervening years
were obtained by linear interpolation. The emission factor (EFi) to estimate emissions from wastewater treatment
was taken from IPCC (2006a). Data on annual per capita protein intake were provided by the United Nations Food
and Agriculture Organization for the 1990 to 2003 time frame (FAO 2006). Protein consumption data for 2004 and
2005 were extrapolated from data for 1990 through 2003. Table 8-11 presents the data for U.S. population and
average protein intake. An emission factor to estimate emissions from effluent (EF3) has not been specifically
estimated for the United States, thus the newly-revised default IPCC value (0.005 kg N20-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).
An estimate for the nitrogen removed as sludge (NSLUDGE) was obtained by determining the amount of sludge
disposed by incineration, by land application (agriculture or other), through surface disposal, in landfills, or through
ocean dumping.
Table 8-11. U.S. Population (Millions) and Average Protein Intake [kg/(person-year)]
8-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Public Review Draft
Year Population Protein
1990 254 39.2
1995
271
287
289
292
295
297
300
40.0
41.6
41.3
41.3
41.7
41.9
42.1
Source: U.S. Census Bureau 2006a, FAO 2006.
Uncertainty
The overall uncertainty associated with both the 2005 CH4 and N20 emissions estimates from wastewater treatment
and discharge was calculated using the IPCC Good Practice Guidance Tier 2 methodology (2000). Uncertainty
associated with the parameters used to estimate CH4 emissions included that of numerous input variables used to
model emissions from domestic wastewater, and wastewater from the pulp and paper industry, meat and poultry
processing, as well as from fruits, vegetables and juices processing. Uncertainty associated with the parameters
used to estimate N20 emissions included that of sewage sludge disposal, total U.S. population, average protein
consumed per person, fraction of N in protein, non-consumption nitrogen factor, emission factors per capita and per
mass of sewage-N, and for the percentage of total population using centralized wastewater treatment plants.
The results of this Tier 2 quantitative uncertainty analysis are summarized in Table 8-12. CH4 emissions from
wastewater treatment were estimated to be between 15.8 and 37.3 Tg C02 Eq. at the 95 percent confidence level (or
in 19 out of 20 Monte Carlo Stochastic Simulations). This indicates a range of approximately 38 percent below to
47 percent above the 2005 emissions estimate of 25.4 Tg C02 Eq. N20 emissions from wastewater treatment were
estimated to be between 1.7 and 15.4 Tg C02 Eq., which indicates a range of approximately 79 percent below to 93
percent above the actual 2005 emissions estimate of 8.0 Tg C02 Eq.
Table 8-12. Tier 2 Quantitative Uncertainty Estimates for CH4 Emissions from Wastewater Treatment (Tg C02 Eq.
and Percent)
2005 Emission
Source Gas Estimate Uncertainty Range Relative to Emission Estimate"
(Tg CQ2 Eq.) (Tg CQ2 Eq.) (%)
Lower
Bound
Upper
Bound
Lower
Bound
Upper
Bound
Wastewater Treatment
ch4
25.4
15.8
37.3
-38%
+47%
Domestic
ch4
17.0
8.6
28.2
-49%
+66%
Industrial
ch4
8.4
4.6
13.5
-45%
+60%
Domestic Wastewater
Treatment
n2o
8.0
1.7
15.4
-79%
+93%
a Range of emission estimates predicted by Monte Carlo Stochastic Simulation for a 95 percent confidence interval.
Recalculations Discussion
The 2005 estimates for CH4 emissions from domestic wastewater include two major methodological refinements
and one major data change. First, CH4 emissions were estimated from four distinct source categories (septic
systems, centrally treated aerobic systems, centrally treated anaerobic systems, and anaerobic digesters) rather than
calculating an overall percentage of wastewater treated anaerobically from which to calculate emissions.
Calculating emissions from anaerobic digesters constitutes the second methodological refinement to the inventory.
Emissions from anaerobic digesters were included to account for the increasing number of facilities that produce
and use digester biogas. The major data adjustment for the current inventory estimates involves the BOD per capita
rate. In previous inventories, the BOD per capita rate varied across the time series. However, the 2005 estimates
Waste 8-13
-------
Public Review Draft
1 employ a standard value for the BOD per capita rate (0.09 kg/capita/day). This change resulted in varying
2 differences in emissions estimates over time, ranging from an increase of 52 percent (1990) to a decrease of 15
3 percent (2004).
4 For industrial wastewater, production data for the entire time series were updated and other factors, such as
5 wastewater outflow, BOD, and percent of waste treated anaerobically, were revised. Production data for potato
6 processing, which accounts for about 45 percent of all vegetable processing in the United States, and about 25
7 percent of all fruit and vegetable processing, had not been included in previous inventories. However, the increase
8 in industrial wastewater emissions due to the inclusion of potatoes was offset by other changes made to the
9 inventory. Flow and BOD data for fruits and vegetable processing wastewater were updated to reflect commodity -
10 specific data, which resulted in a decrease in emissions. In addition, the amount of meat and poultry processing
11 wastewater treated on site anaerobically was substantially revised. Previously, it was assumed that all wastewater
12 from meat and poultry processing was treated anaerobically. However, data from EPA's Office of Water and from
13 U.S. Poultry and Egg Association became available to show that indirect dischargers do not treat wastewater
14 anaerobically. Therefore, the percent of waste treated anaerobically was reduced (to 33 percent for meat processors
15 and 25 percent for poultry processors), which resulted in a significant decrease in emission estimates. These
16 changes resulted in overall decreases of industrial wastewater emissions between 45 and 50 percent across the time
17 series.
18 Overall, the CH4 emission estimates for wastewater treatment are on average 17 percent lower than the previous
19 inventory.
20 For N20 emissions from domestic wastewater, minor changes were made to the time series to include more specific
21 estimates of the percent of U. S. population using centralized wastewater treatment, and a factor was introduced to
22 account for the amount of biological denitrification occurring at centralized treatment plants. The calculation
23 estimates for protein consumed were updated for the entire time series. These improvements resulted in minor
24 decreases to the emission estimates across the time series, from 3 to 4 percent.
25 Finally, the default factor for N20 emissions from N in effluent discharged to aquatic environments was updated
26 from 0.01 to 0.005 kg N20 -N/kg sewage-N, which resulted in a decrease of approximately 50 percent in emission
27 estimates over the time series compared to the previous inventory. The effect of all changes was an overall decrease
28 in emission estimates from 50.1 to 51.4 percent across the time series.
29 Overall, emissions from wastewater treatment and discharge (CH4 and N20) decreased by an average of 28 percent
30 from the previous inventory.
31 Planned Improvements Discussion
32 The methodology to estimate CH4 emissions from domestic wastewater treatment currently utilizes estimates for the
33 percentage of centrally treated wastewater that is treated by aerobic systems and anaerobic systems. These data
34 come from the 1992, 1996, 2000, and 2004 CWNS. The designation of systems as aerobic or anaerobic could be
35 further refined to differentiate aerobic systems with the potential to generate small amounts of CH4 (aerobic
36 lagoons) versus other types of aerobic systems, and to differentiate between anaerobic systems to allow for the use
37 of different MCFs for different types of anaerobic treatment systems. Currently it is assumed that all aerobic
38 systems are well managed and produce no CH4 and that all anaerobic systems have an MCF of 0.8. Efforts to
3 9 obtain better data are currently being pursued.
40 Currently, BOD removal is not explicitly included in inventory calculations. The appropriateness of including a
41 factor to account for BOD that is not removed through treatment and therefore does not contribute to CH4 emissions
42 is being investigated.
43 The methodology to estimate emissions for industrial wastewater currently accounts for pulp and paper, meat and
44 poultry processing, and fruits and vegetables processing wastewater treatment. Information is currently being
45 collected on ethanol production in the U.S. to determine if this should be included in future Inventories.
8-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
Public Review Draft
With respect to estimating N20 emissions, the default emission factor for N20 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, more research may be conducted to update the protein consumption data.
8.3. Waste Sources of Indirect Greenhouse Gases
In addition to the main greenhouse gases addressed above, waste generating and handling processes are also sources
of indirect greenhouse gas emissions. Total emissions of NOx, CO, and NMVOCs from waste sources for the years
1990 through 2005 are provided in Table 8-13.
Table 8-13: Emissions of NOx, CO, and NMVOC from Waste (Gg)
Gas/Source
1990
I 1995
2000
2001
2002
2003
2004
2005
NOx
+
1
2
2
2
2
2
2
Landfills
+11
'
2
2
2
2
2
2
Wastewater Treatment
+1I
+
+
+
+
+
+
Miscellaneous3
+11
¦
+
+
+
+
+
+
CO
m
J
8
8
7
7
7
7
Landfills
¦
J
7
7
6
6
6
7
Wastewater Treatment
+il
+ii
1
1
+
+
+
+
Miscellaneous3
+
ilill
+
+
+
+
+
+
NMVOCs
673
731
119
122
116
116
116
116
Wastewater Treatment
57 ¦
61
51
53
50
50
50
50
Miscellaneous3
558
602
46
46
44
44
44
44
Landfills
58
23
23
22
22
22
22
3 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.
Methodology and Data Sources
These emission estimates were obtained from preliminary data (EPA 2006), 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.
Waste 8-15
-------
-------
Figure 8-1: 2005 Waste Chapter Greenhouse Gas Sources
-------
Public Review Draft
1 9. Other
2 The United States does not report any greenhouse gas emissions under the "other" Intergovernmental Panel on
3 Climate Change (IPCC) sector.
Other 9-1
-------
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
Public Review Draft
10. Recalculations and Improvements
Each year, emission and sink estimates are recalculated and revised for all years in the Inventory of U.S.
Greenhouse Gas Emissions and Sinks, as attempts are made to improve both the analyses themselves, through the
use of better methods or data, and the overall usefulness of the report. In this effort, the United States follows the
Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance (IPCC 2000), which states, "It is
good practice to recalculate historic emissions when methods are changed or refined, when new source categories
are included in the national inventory, or when errors in the estimates are identified and corrected."
The results of all methodology changes and historical data updates are presented in this section; detailed
descriptions of each recalculation are contained within each source's description contained in this report, if
applicable. Table 10-1 summarizes the quantitative effect of these changes on U.S. greenhouse gas emissions and
Table 10-2 summarizes the quantitative effect on U.S. sinks, both relative to the previously published U.S.
Inventory (i.e., the 1990 through 2004 report). These tables present the magnitude of these changes in units of
teragrams of carbon dioxide equivalent (Tg C02 Eq). In addition to the changes summarized by the tables below,
the following sources and gases were added to the current inventory:
• methane (CH4) emissions from Ferroalloy Production;
• CH4 and nitrous oxide (N20) emissions from Forest Land Remaining Forest Land to account for emissions
from forest fires;
• C02 emissions from Silicon Carbide Production; and
• CH4 emissions from Silicon Carbide Consumption.
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 2004) 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 2004, 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 (1) modifying nitrogen (N) inputs to be
consistent with the agricultural soil carbon (C) inventory, (2) modeling within county variation in soil
characteristics and weather, and (3) incorporating revised methods and emission factors from IPCC (2006).
Overall, changes resulted in an average annual increase in N20 emissions from agricultural soil management of
90.4 Tg C02 Eq. (33 percent) for the period 1990 through 2004.
• Net C02 Flux from Land Use, Land-Use Change, and Forestry. Influential changes in the Land Use, Land-Use
Change, and Forestry sector occurred in calculations for forest C stock and flux estimates. Changes for the
period 1990 through 2004, as compared to the estimates presented in the previous inventory, are based on the
cumulative effects of (1) incorporating additional state and sub-state inventory data, and (2) adjusting total
stock estimates used in earlier years to account for inclusion or removal of different ecological community
types in subsequent state and sub-state inventory years. Overall, these changes, in combination with
adjustments in the other sources/sinks within the sector, resulted in an average annual decrease in net flux of
C02 to the atmosphere from the Land Use, Land-Use Change, and Forestry sector of 37.7 Tg C02 Eq. (7
percent) for the period 1990 through 2004. However, the most consequential changes from these recalculations
occurred in 1990, which saw a 197.4 Tg C02 Eq. (21.7 percent) decrease in sequestration.
• CO2 from Fossil Fuel Combustion. The most important update that affected the historical estimates for C02
emissions from fossil fuel combustion was the change to the C oxidation factor for all fuel types to 100 percent.
Recalculations and Improvements 10-1
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Public Review Draft
This change was made according to IPCC (2006) and impacted emission estimates for all fuel types.
Additionally, silicon carbide used for petroleum coke manufacturing was reallocated to the Industrial Processes
chapter. Overall, changes resulted in an average annual increase of 36.9 Tg C02 Eq. (0.7 percent) in C02
emissions from fossil fuel combustion for the period 1990 through 2004.
• Natural Gas Systems. The inventory now contains estimates for non-combustion-related (vented, fugitive,
flared) C02 emissions from the natural gas industry. The estimation uses the same activity and emission factors
from the methane (CH4) emission estimates but adjusts the emission factors for the ratio of C02/CH4 content of
the natural gas. Efforts were made to ensure that there was no double-accounting of C02 emissions from other
system inventories in the overall Inventory. Overall, changes resulted in an average annual increase in C02
emissions from natural gas systems of 24.4 Tg C02 Eq. (376 percent) for the period 1990 through 2004.
• Manure Management. A few changes have been incorporated into the overall methodology for the manure
management emission estimates. State temperatures are now calculated using data from every county in the
state. Another major change in methodology was using climate-specific CH4 conversion factors for dry manure
management systems. The percentage of dairy cattle, swine, and sheep on each type of manure management
system was also updated for the current inventory, based on farm size data from the 2002 USD A Census of
Agriculture (USDA 2005e). Changes were also made to the current calculations involving animal population
data. N20 emission estimates from manure management systems have decreased for all years of the current
Inventory compared to the previous inventory due to the use of updated emission factors from IPCC (2006).
Overall, the changes resulted in an average annual decrease in N20 emissions from manure management of 8.1
Tg C02 Eq. (47 percent) for the period 1990 through 2004.
• 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 increase in hydrofluorocabon (HFC) and perfluorocarbon (PFC) emissions from
the substitution of ozone depleting substances of 7.6 Tg C02 Eq. (21 percent) for the period 1990 through
2004.
• N20 Emissions from Wastewater Treatment. For N20 emissions from domestic wastewater, a minor change
made to the time series was to include more specific estimates of the percent of U.S. population that uses
centralized wastewater treatment. Also, a factor was introduced to account for the amount of biological
denitrification used at centralized treatment plants. The calculation estimates for protein consumed were
updated for the entire time series. Additionally, the default factor for N20 emissions from N in effluent
discharged to aquatic environments was updated from 0.01 to 0.005 kg N20-N/kg sewage-N. Overall, the
changes resulted in an average annual decrease in N20 emissions from wastewater treatment of 7.5 Tg C02 Eq.
(51 percent) for the period 1990 through 2004.
• Landfills. For municipal solid waste landfills, changes to historical data resulted from the application of a more
accurate integrated form of the first order decay model, and incorporating a delay time of 6 months. Another
improvement was made in the estimate of CH4 generation from industrial landfills, which was based on
industrial production, waste disposal factors, and the first order decay model. Additionally, EIA, LMOP, and
flare vendor databases were updated, affecting estimates of CH4 recovery. Overall, changes resulted in an
average annual decrease in CH4 emissions from landfills of 7.5 Tg C02 Eq. (4.9 percent) for the period 1990
through 2004.
• CH4 Emissions from Wastewater Treatment. Two methodological refinements and one major data change
resulted in a decrease in CH4 emissions from wastewater treatment for the period 1990 through 2004 relative to
the previous inventory. First, the current estimates are based on four distinct source categories (septic systems,
centrally treated aerobic systems, centrally treated anaerobic systems, and anaerobic digesters), whereas in
previous inventories, emissions were calculated based on an overall percentage of anaerobically treated
wastewater. Calculating emissions from anaerobic digesters constitutes the second methodological refinement
to this category. The major data adjustment involves the Biochemical Oxygen Demand (BOD) per capita rate.
The current estimates employ a standard value for the BOD per capita rate across the time series (0.09
kg/capita/day). For industrial wastewater, production data for the entire time series were updated and other
10-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
Public Review Draft
factors such as wastewater outflow, BOD, and percent of waste treated anaerobically, were revised. Overall,
changes resulted in an average annual decrease in CH4 emissions from wastewater treatment of 5.6 Tg C02 Eq.
(16.7 percent) for the period 1990 through 2004.
Wood Biomass and Ethanol Consumption. Commercial wood consumption values were revised for the full
timeseries, based on updated information from EIA's Commercial Building Energy Consumption Survey (EIA
2006). EIA (2006) also reported minor changes in wood consumption by the residential and industrial sectors
for the full timeseries, and in ethanol consumption for 2001 through 2004. Overall, changes resulted in an
average annual increase in emissions from wood biomass and ethanol consumption of 2.9 Tg C02 Eq. (1
percent) from 1990 through 2004.
Table 10-1: Revisions to U.S. Greenhouse Gas Emissions (Tg C02 Eq.)
Gas/Source 199?" 1995
C02 56.4 59.3
Fossil Fuel Combustion 27.6 33.3
Non-Energy Use of Fuels 0.1 0.41
Natural Gas Systems 27.9 24.8
Cement Manufacture NC NC
Lime Manufacture + +
Limestone and Dolomite Use + NC
Soda Ash Manufacture and Consumption NC NC
C02 Consumption 0.6 0.6
Municipal Solid Waste Combustion + +
Titanium Dioxide Production NC NC
Aluminum Production (0.2) (0.2)
Iron and Steel Production + +
Ferroalloy Production 0.2 0.2
Ammonia Production and Urea Application NC NC
Phosphoric Acid Production NC NC
Petrochemical Production NC NC
Silicon Carbide Production and Consumption 0.3 0.2
Lead Production NC NC
Zinc Production NC NC |
Net C02 Flux from Land Use, Land-Use
Change, and Forestry 197.4 (213.6)
International Bunker Fuelsb 0.2
Wood Biomass and Ethanol Consumptionh 2.6 (5.1)
CH4 (9.0) (10.3) |
Stationary Combustion 0.2 (0.3)
Mobile Combustion + +
Coal Mining + 0.7
Abandoned Underground Coal Mines NC NC
Natural Gas Systems (2.3) +
Petroleum Systems + +
Petrochemical Production (0.3) (0.4)
Silicon Carbide Production and Consumption NC NC
Iron and Steel Production NC NC
Ferroalloy Production3 + +
Enteric Fermentation (2.2) (2.4)
Manure Management (0.3) (1.0)
Rice Cultivation NC NC
Field Burning of Agricultural Residues + +
Forest Land Remaining Forest Land3 7.1 4.0
Landfills (11.3) (6.2) j
2000 2001 2002 2003 2004
75.6
51.2
0.3
23.6
NC
+
NC
NC
0.5
+
NC
(0.2)
(0.1)
0.2
+
NC
NC
0.1
NC
NC
4.8
(0.2)
1.5
(3.3)
0.1
+
(0.4)
0.1
(0.1)
+
(0.5)
NC
NC
+
(2.2)
0.7
NC
+
14.0
(7.1)
47.9
24.8
0.3
22.7
NC
+
NC
NC
+
(0.3)
NC
(0.1)
0.2
0.1
+
NC
NC
0.1
NC
NC
2.5
(0.3)
2.7
(12.6)
0.2
(0.1)
+
0.1
(0.2)
+
(0.4)
NC
NC
+
(2.2)
1.3
NC
+
6.0
(8.5)
76.9
55.5
(1.2)
23.4
NC
+
NC
NC
+
(0.3)
NC
(0.1)
0.2
0.1
(0.7)
NC
NC
0.1
NC
NC
(41.3)
(0.4)
10.0
(10.1)
0.6
(0.1)
(0.5)
0.1
(0.4)
+
(0.4)
NC
NC
+
(2.1)
1.8
NC
+
10.4
(9.4)
75.0
53.4
(2.2)
22.4
NC
+
NC
NC
+
0.1
NC
(0.1)
0.2
0.1
0.9
NC
NC
0.1
NC
NC
(36.7)
(0.4)
7.5
(15.1)
0.5
(0.2)
(2.8)
0.1
(1.0)
(0.1)
(0.4)
NC
NC
+
(2.1)
1.3
+
+
8.1
(7.5)
76.5
56.5
(3.2)
22.2
+
+
NC
NC
+
0.8
NC
(0.1)
0.2
0.1
+
NC
NC
0.1
NC
+
(44.8)
2.7
13.6
(16.5)
0.7
(0.2)
(1.8)
0.1
0.2
(0.3)
(0.5)
NC
NC
+
(2.1)
0.3
+
+
6.9
(8.8)
Recalculations and Improvements 10-3
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Public Review Draft
Wastewater Treatment +1
International Bunker Fuelsb NC
N20 87.1
Stationary Combustion +1
Mobile Combustion 0.3
Adipic Acid Production NC 1
Nitric Acid Production NC
Manure Management (7.6) |
Agricultural Soil Management 100>
Field Burning of Agricultural Residues +1
Wastewater Treatment (6.5)
N20 Product Usage NC
Municipal Solid Waste Combustion NC
Settlements Remaining Settlements (0.5)
Forest Land Remaining Forest Land 0.7
International Bunker Fuelsb NC
HFCs, PFCs, and SF„ (1.4)
Substitution of Ozone Depleting Substances (0.1) J
Aluminum Production 0.1
HCFC-22 Production NC I
Semiconductor Manufacture NC
Electrical Transmission and Distribution (1.5)
Magnesium Production and Processing NC 1
Net Change in Total Emissionsb
Percent Change
133.1
6.4%
(4.8)
NC I
30.0
(0.1)1
0.3
NCI
NC
(8.1)|
45.3
+1
(7.3)
NC
NC
(0.4)
0.4
NC 1
8.6 I
8.1
(0.1)1
NC
NC
0.6
NC
87.7
-2.1%
(7.9)
NC
83.6
+
0.1
NC
NC
(8.3)
98.6
+
(7.9)
NC
NC
(0.4)
1.4
NC
9.1
9.7
(0.4)
NC
NC
(0.1)
(0-2)
165.0
2.7%
(8.8)
NC
89.7
+
(0.2)
NC
NC
(8.3)
106.0
+
(8.0)
NC
+
(0.4)
0.6
NC
8.9
9.9
(0.5)
NC
NC
(0.3)
(0-2)
(10.0)
NC
71.9
0.2
(0.4)
NC
+
(8.3)
88.3
+
(8.0)
(0.5)
+
(0.4)
1.0
NC
10.3
10.7
+
NC
NC
(0.2)
(0-2)
(11.0)
NC
73.8
0.1
(1.0)
NC
NC
(8.2)
91.0
+
(8.0)
(0.5)
+
(0.4)
0.8
NC
11.6
12.0
+
NC
NC
(0.2)
(0-1)
134.0
2.2%
149.0 145.3
1.8% 1.8%
(11.3)
+
58.6
0.2
(1.6)
NC
(0.6)
(8.3)
77.3
+
(8.1)
(0.5)
+
(0.5)
0.7
+
10.9
11.2
+
NC
NC
(0.2)
(0-1)
129.5
1.3%
+ Absolute value does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
NC (No Change)
aNew source category relative to previous inventory.
b Excludes net C02 flux from Land Use, Land-Use Change, and Forestry, and emissions from International Bunker Fuels and
Wood Biomass and Ethanol Consumption.
Note: Totals may not sum due to independent rounding.
Table 10-2: Revisions to Net Flux of C02 to the Atmosphere from Land Use, Land-Use Change, and Forestry (Tg
Component: Net C02 Flux From
Land Use, Land-Use Change, and
Forestry
1990
1995
1 2000
2001
2002
2003
2004
Forest Land Remaining Forest Land
174.9
(228.9)
(7.7)
(11.7)
(53.5)
(51.2)
(60.1)
Cropland Remaining Cropland
5.0
(11.0)
(10.4)
(10.3)
(10.3)
(9.6)
(10.4)
Land Converted to Cropland
7.2
10.0
I 100
10.0
10.0
10.0
10.0
Grassland Remaining Grassland
4.6
8.8
8.8
8.9
8.9
8.9
8.9
Land Converted to Grassland
3.1
4.8
4.8
4.8
4.8
4.8
4.8
Settlements Remaining Settlements
25.7
15.7
7.7
9.5
7.6
9.4
10.9
Other
(23.0)
(13.0)
1 (8.5)
(8.6)
(8.9)
(9.0)
(8.9)
Net Change in Total Flux
Percent Change
197.4
21.7%
(213.6)
-34.7%
1 4,8
0.6%
2.5
0.3%
(41.3)
-5.4%
(36.7)
-4.7%
(44.8)
-5.7%
+ Absolute value does not exceed 0.05 Tg C02 Eq. or 0.05 percent.
NC (No Change)
Note: Numbers in parentheses indicate a decrease in estimated net flux of C02 to the atmosphere, or an increase in net
sequestration.
Note: Totals may not sum due to independent rounding.
10-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 11. References
2 Executive Summary
3 BEA (2006) 2005 Comprehensive Revision of the National Income and Product Accounts: Current-dollar and
4 "real" GDP, 1929 - 2005. Bureau of Economic Analysis (BEA), U.S. Department of Commerce, Washington, DC.
5 July 29, 2006. Available online at .
6 EIA (2006a) Monthly Energy Review, September 2006 and Unpublished Supplemental Tables on Petroleum Product
7 detail. Energy Information Administration, U.S. Department of Energy, Washington, DC, DOE/EIA-
8 0035(2006/09).
9 EIA (2006b) International Energy Annual 2004. Energy Information Administration, U.S. Department of Energy,
10 Washington, DC. Updated May-July 2006. < http://www.eia.doe.gov/iea/carbon.html>.
11 EPA (2006) Air Emissions Trends - Continued Progress Through 2005. U.S. Environmental Protection Agency,
12 Washington DC. December 19, 2006. < http://www.epa.gov/air/airtrends/index.html>.
13 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
14 OAQPS. December 22, 2003.
15 Hofmann, D (2004) Long-lived Greenhouse Gas Annual Averages for 1979-2004. NOAA/ESRL Global
16 Monitoring Division, Boulder, CO.
17 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
18 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
19 Published: IGES, Japan.
20 IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry. J. Penman and others,
21 editors. IPCC National Greenhouse Gas Inventories Programme. Available online at , August 13, 2004.
23 IPCC (2001) Climate Change 2001: A Scientific Basis, Intergovernmental Panel on Climate Change; J.T. Houghton,
24 Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell, eds.; Cambridge
25 University Press. Cambridge, U.K.
26 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
27 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
28 XVI/Doc. 10 (1.IV.2000). May.
29 IPCC (1996) Climate Change 1995: The Science of Climate Change. Intergovernmental Panel on Climate Change;
30 J.T. Houghton, L.G. Meira Filho, B.A. Callander, N. Harris, A. Kattenberg, and K. Maskell, eds.; Cambridge
31 University Press. Cambridge, U.K.
32 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris:
33 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
34 Co-Operation and Development, International Energy Agency.
35 UNFCCC (2003) National Communications: Greenhouse Gas Inventories from Parties included in Annex I to the
36 Convention, UNFCCC Guidelines on Reporting and Review. Conference of the Parties, Eighth Session, New Delhi.
37 (FCCC/CP/2002/8) March 28, 2003.
38 U.S. Census Bureau (2006) U.S. Census Bureau International Database (IDB). Available online at
References 11-1
-------
Public Review Draft
1 . Updated: April 26, 2006. Accessed: August 15, 2006.
2 Introduction
3 Biasing and Jones (2004). Current Greenhouse Gas Concentrations. In Trends: A Compendium of Data on Global
4 Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory. Oak Ridge, TN.
5 EPA (2005) Air Emissions Trends—Continued Progress Through 2003. U.S. Environmental Protection Agency,
6 Washington, DC Available online at .
7 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
8 OAQPS. December 22, 2003.
9 UNFCCC (2006) Updated UNFCCC reporting guidelines on annual inventories following incorporation of the
10 provisions of decision 14/CP. 11. Substidiary Body for Scientific and Technical Advice. (FCCC/SBSTA/2006/9)
11 18 August 2006.
12 UNFCCC (2003) National Communications: Greenhouse Gas Inventories from Parties included in Annex I to the
13 Convention, UNFCCC Guidelines on Reporting and Review. Conference of the Parties, Eighth Session, New
14 Delhi. (FCCC/CP/2002/8) March 28, 2003.
15 IPCC (2001) Climate Change 2001: A Scientific Basis, Intergovernmental Panel on Climate Change; J.T. Houghton,
16 Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell, eds.; Cambridge
17 University Press. Cambridge, U.K.
18 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
19 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
20 XVI/Doc. 10 (1.IV.2000). May.
21 IPCC (1999) Aviation and the Global Atmosphere. Intergovernmental Panel on Climate Change; Penner, J.E., et al.,
22 eds.; Cambridge University Press. Cambridge, U.K.
23 IPCC (1996) Climate Change 1995: The Science of Climate Change. Intergovernmental Panel on Climate Change;
24 J.T. Houghton, L.G. Meira Filho, B.A. Callander, N. Harris, A. Kattenberg, and K. Maskell, eds.; Cambridge
25 University Press. Cambridge, U.K.
26 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris:
27 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
28 Co-Operation and Development, International Energy Agency.
29 Jacobson, M.Z. (2001) Strong Radiative Heating Due to the Mixing State of Black Carbon in Atmospheric
30 Aerosols. Nature, 409, pp. 695 - 697, Macmillan Publishers.
31 NRC(2001) Climate Change Science: An Analysis of Some Key Questions. Committee of the Science of Climate
32 Change, National Research Council (available on the internet at .)
33 UNEP/WMO (1999) Information Unit on Climate Change. Framework Convention on Climate Change. Available
34 online at .
35 WMO (1999) Scientific Assessment of Ozone Depletion, Global Ozone Research and Monitoring Project-Report
36 No. 44, World Meteorological Organization, Geneva, Switzerland.
11-2 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Trends in Greenhouse Gas Emissions
2 BEA (2006) 2005 Comprehensive Revision of the National Income and Product Accounts: Current-dollar and
3 "real" GDP, 1929 - 2005. Bureau of Economic Analysis (BEA), U.S. Department of Commerce, Washington, DC.
4 July 29, 2006. Available online at .
5 Duffield, J. (2005) Telephone and email conversations between Lauren Flinn of ICF Consulting and Jim Duffield,
6 Office of Energy Policy and New Uses, USD A. April and December.
7 EIA (2006a) Monthly Energy Review, September 2006 and Unpublished Supplemental Tables on Petroleum Product
8 detail. Energy Information Administration, U.S. Department of Energy, Washington, DC, DOE/EIA-
9 0035(2006/09).
10 EIA (2006b) Short-Term Energy Outlook. Energy Information Administration, U.S. Department of Energy,
11 Washington, DC. December.
12 EIA. (2006c) Annual Energy Review. "Appendix A. Table A3: Approximate Heat Content of Petroleum
13 Consumption." Energy Information Administration. Available online at
14 http://tonto.eia.doe.gov/bookshelf/SearchResults.asp?title=Annual+Energy+Review
15 EIA (1991 through 2005) Fuel Oil and Kerosene Sales. "Table 22: Adjusted Sales for Farm Use: Distillate Fuel Oil
16 and Kerosene; Sales for Electric Power and Oil Company Uses: Distillate Fuel Oil and Residual Fuel Oil, 2004."
17 Energy Information Administration. U.S. Department of Energy, Washington, DC. Available online at
18 .
20 EPA (2005) Air Emissions Trends—Continued Progress Through 2003. U.S. Environmental Protection Agency,
21 Washington DC. Available online at .
22 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
23 OAQPS. December 22, 2003.
24 Hoffman, D (2004) Long-lived Greenhouse Gas Annual Averages for 1979-2004. NOAA/ESRL Global Monitoring
25 Division, Boulder, CO.
26 IPCC (2001) Climate Change 2001: A Scientific Basis, Intergovernmental Panel on Climate Change; J.T. Houghton,
27 Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, C.A. Johnson, and K. Maskell, eds.; Cambridge
28 University Press. Cambridge, U.K.
29 Keeling, C.D. and T.P. Whorf (2005) Atmospheric C02 records from sites in the SIO air sampling network. In
30 Trends: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge
31 National Laboratory. U.S. Department of Energy, Oak Ridge, Tenn., U.S.A.
32
33 U.S. Census Bureau (2006) U.S. Census Bureau International Database (IDB). Available online at
34 . Updated: April 26, 2006. Accessed: August 15, 2006.
35 Energy
36 EIA (2006) International Energy Annual 2004. Energy Information Administration, U.S. Department of Energy,
37 Washington, DC. Updated May-July 2006. < http://www.eia.doe.gov/iea/carbon.html>.
38 Carbon Dioxide Emissions from Fossil Fuel Combustion
References 11-3
-------
Public Review Draft
1 AAR (2005) Railroad Facts, 2002 Ed. Policy and Economics Department, Association of American Railroads,
2 Washington, DC.
3 BEA (2006) 2005 Comprehensive Revision of the National Income and Product Accounts: Current-dollar and
4 "real" GDP, 1929 - 2005. Bureau of Economic Analysis (BEA), U.S. Department of Commerce, Washington, DC.
5 July 29, 2006. Available online at .
6 BEA (1991 through 2006) Unpublished BE-36 survey data. Bureau of Economic Analysis (BEA), U.S. Department
7 of Commerce, Washington, DC.
8 Benson, D. (2002 through 2004) Personal communication. Unpublished data developed by the Upper Great Plains
9 Transportation Institute, North Dakota State University and American Short Line & Regional Railroad Association.
10 Corathers, L. (2006) Personal communication between Erin Fraser of ICF International and Lisa Corathers,
11 Commodity Specialist, U.S. Geological Survey, October.
12 Dakota Gasification Company (2006), C02 Pipeline Route and Designation Information, Bismarck, ND,
13 .
14 DESC (2006) Unpublished data from the Defense Fuels Automated Management System (DFAMS). Defense
15 Energy Support Center, Defense Logistics Agency, U.S. Department of Defense, Washington, DC.
16 DOC (1991 through 2006) Unpublished "Report of Bunker Fuel Oil Laden on Vessels Cleared for Foreign
17 Countries." Foreign Trade Division, Bureau of the Census, U.S. Department of Commerce, Washington, DC.
18 Form-563.
19 DOE (1993 through 2004) Transportation Energy Data Book. Office of Transportation Technologies, Center for
20 Transportation Analysis, Energy Division, Oak Ridge National Laboratory, ORNL-6959.
21 DOT (1991 through 2006) Fuel Cost and Consumption, Federal Aviation Administration, U.S. Department of
22 Transportation, Bureau of Transportation Statistics, Washington, DC, DAI-10.
23 EFMA (1995) Production of Ammonia. European Fertilizer Manufacturers Association. March 1.
24 EIA (2006a) Annual Energy Review 2005. Energy Information Administration, U.S. Department of Energy,
25 Washington, DC, DOE/EIA-0384(2005). July.
26 EIA (2006b) Monthly Energy Review, December 2006 and Unpublished Supplemental Tables on Petroleum Product
27 detail. Energy Information Administration, U.S. Department of Energy, Washington, DC, DOE/EIA-
28 0035(2006/12).
29 EIA (2006c) Emissions of Greenhouse Gases in the United States 2005, Draft Report. Office of Integrated Analysis
30 and Forecasting, Energy Information Administration, U.S. Department of Energy, Washington, DC. DOE-EIA-
31 0573(2005).
32 EIA (2006d) International Energy Annual, "World Petroleum Supply and Disposition " Available online at
33 . Table 3.1.
34 EIA (2006e) Natural Gas Annual 2005. Energy Information Administration, U.S. Department of Energy,
35 Washington, DC, DOE/EIA-0131(04). December.
36 EIA (2006f) Short-Term Energy Outlook. Energy Information Administration, U.S. Department of Energy,
37 Washington, DC, December.
11-4 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 EIA (2006g) Personal Communication between Joseph Aamidor of ICF International and Joel Lou of Energy
2 Information Administration. Residual and Distillate Fuel Oil Consumption for Vessel Bunkering (Both International
3 and Domestic) for American Samoa, U.S. Pacific Islands, and Wake Island. September 19, 2006.
4 EIA (2005a) Quarterly Coal Report, Energy Information Administration, U.S. Department of Energy, Washington,
5 DC. DOE/EIA-0121
6 EIA (2005b) Manufacturing Consumption of Energy 2002. Energy Information Administration, U.S. Department of
7 Energy, Washington, DC.
8 EIA (2004) Natural Gas Annual. Energy Information Administration, U.S. Department of Energy, Washington, DC.
9 EIA (2002a) Alternative Fuels Data Tables. Energy Information Administration, U.S. Department of Energy,
10 Washington, DC. Available online at .
11 EIA (2001a) Historical Natural Gas Annual, 1930 - 2003. Energy Information Administration, U.S. Department of
12 Energy, Washington, DC.
13 EIA (2001b) U.S. Coal, Domestic and International Issues, Energy Information Administration, U.S. Department of
14 Energy, Washington, DC, March.
15 EIA (1991 through 2005) Fuel Oil and Kerosene Sales. Energy Information Administration, U.S. Department of
16 Energy, Washington, DC, DOE/EIA-0535-annual.
17 EPA (2005) Air Emissions Trends—Continued Progress Through 2004. U.S. Environmental Protection Agency,
18 Washington DC. August 18, 2005. Available online at
19 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
20 OAQPS. December 22, 2003.
21 EPA (2004) NONROAD Model. Office of Transportation and Air Quality, U.S. Environmental Protection Agency.
22 Available online at .
23 Erickson, T. (2003) Plains C02 Reduction (PCOR) Partnership, Presented at the Regional Carbon Sequestration
24 Partnership Meeting Pittsburgh, Pennsylvania, November 3, 2003, Energy and Environmental Research Center,
25 University of North Dakota, available online at .
30 Fitzpatrick, E. (2002) The Weyburn Project: A Model for International Collaboration, available online at
31 .
32 FHWA (1996 through 2006) Highway Statistics. Federal Highway Administration, U.S. Department of
33 Transportation. Washington, DC, report FHWA-PL-96-023-annual.
34 FRB (2006) Industrial Production and Capacity Utilization. Federal Reserve Board, Federal Reserve Statistical
35 Release, G. 17. Available online at November 7, 2006
36 Annual Revision.
37 Gambogi, J.(2006). Personal communication between Erin Fraser of ICF International and Joseph Gambogi,
38 Commodity Specialist, U.S. Geological Survey, September.
References 11-5
-------
Public Review Draft
1 Grillot, M. (2006) Personal communication between Lauren Pederson of ICF International and Mike Grillot of
2 Energy Information Administration. U.S. Territories Fossil Fuel Consumption, 1990 2005. Unpublished data
3 developed by the U.S. Energy Information Administration, Washington, DC.
4 Johnson, G. L. (2006) Personal communication between Erin Fraser of ICF International and Greg Johnson of
5 Liskow & Lewis, on behalf of the International Carbon Black Association (ICBA). October, 2006.
6 Kass (2005) Personal communication between Nathaniel Kass of EIA and Erin Fraser of ICF. October.
7 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
8 Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T., and Tanabe K. (eds.).
9 Published: IGES, Japan.
10 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris:
11 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
12 Co-Operation and Development, International Energy Agency.
13 Marland, G., and A. Pippin (1990) United States Emissions of Carbon Dioxide to the Earth's Atmosphere by
14 Economic Activity. Energy Systems and Policy, 14(4):323.
15 Onder, H., and E.A. Bagdoyan (1993) Everything You've Always Wanted to Know about Petroleum Coke. Allis
16 Mineral Systems.
17 SAIC/EIA (2001) Monte Carlo Simulations of Uncertainty in U.S. Greenhouse Gas Emission Estimates. Final
18 Report. Prepared by Science Applications International Corporation (SAIC) for Energy Information Administration
19 (EIA), Office of Integrated Analysis and Forecasting, U.S. Department of Energy, Washington, DC. 22 June.
20 USAF (1998) Fuel Logistics Planning. U.S. Air Force document AFPAM23-221, 1 May.
21 U.S. Census Bureau (2005) Current Industrial Reports Fertilizer Materials and Related Products: Fourth Quarter
22 Report 2004 Summary. Available online at .
23 U.S. Census Bureau (2004) International Data Base (IDB): World Population Information, Washington DC.
24 September 30. Available online at
25 U.S. Census Bureau (2006a) Current Industrial Reports Fertilizer and Related Chemicals Summary:2005.
26 Available online at .
27 U.S. Census Bureau (1991 through 1994) Current Industrial Reports Fertilizer Materials Annual Report, Report
28 No. MQ28B.
29 USITC (2006) USITC Interactive Tariff and Trade DataWeb, United States International Trade Commission, U.S.
30 Department of Commerce. Washington, DC. Accessible online at .
31 US AA (2006) Primary Aluminum Statistics. Aluminum Association, Washington, DC. January 2006.
32 USGS (1998 through 2002) Mineral Yearbook: Aluminum Annual Report. U.S. Geological Survey, Reston, VA.
33 USGS (1995) Mineral Industry Surveys: Aluminum Annual Review 1994. U.S. Geological Survey, U.S. Department
34 of the Interior, formerly Bureau of Mines. Washington, DC. May.
35 USGS (1991 through 2005) Silicon: Annual Report. U.S. Geological Survey, U.S. Department of the Interior,
36 formerly Bureau of Mines. Washington, DC.
11-6 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 USGS (1991 through 2005) Mineral Yearbook: Titanium Annual Report. U.S. Geological Survey, Reston, VA.
2 U.S. International Trade Commission (2006) HTS—2707995010: Carbon Black Feedstock. U.S. Domestic Exports.
3 Available online at .
4 U.S. International Trade Commission (2004) HTS—2707: Oils and Other Products of the Distillation of High
5 Temperature Coal Tar; Similar Products in which the Weight of Aromatic Constituents Predominate. U.S. General
6 Imports. Available online at .
7 Carbon Emitted from Non-Energy Uses of Fossil Fuels
8 ACC (2006) "Guide to the Business of Chemistry, 2005," American Chemistry Council.
9 ACC (2005) "Guide to the Business of Chemistry, 2003," American Chemistry Council.
10 Adler, B. (2001) Personal communication between Robert Lanza of ICF International and Bob Adler of the U.S.
11 Energy Information Administration (EIA). September 14, 2001.
12 APC (2006) "APC Year-End Statistics for 2005," American Plastics Council website, accessed April 2006.
13 Available online at .
14 APC (2005) "APC Year-End Statistics for 2004," American Plastics Council website, accessed April 2005.
15 Available online at .
16 APC (2004) "APC Year-End Statistics for 2003," American Plastics Council website, accessed March 2004.
17 Available online at .
18 APC (2003) "APC Year-End Statistics for 2002," American Plastics Council website, accessed June 2003.
19 Available online at .
20 APC (2001) as cited in ACS (2001) "Production: slow gains in output of chemicals and products lagged behind
21 U.S. economy as a whole" Chemical & Engineering News, American Chemical Society, 25 June. Available online
22 at .
23 APC (2000) as reported in "Facts & Figures for the Chemical Industry," Chemical and Engineering News, Vol. 78
24 (26), June 26, 2000. American Plastics Council. Arlington, VA. Available online at
25 .
26 Bank of Canada (2006) "Financial Markets Department Year Average of Exchange Rates," Available online at
27 .
28 CMA (1999) U.S. Chemical Industry Statistical Handbook. Chemical Manufacturer's Association. Washington,
29 DC.
30 Connolly, U. (2000) Personal communication between Suzanne Bratis of ICF International and Una Connelly of
31 National Asphalt Pavement Association. August 2000. (Tel: 859-288-4960).
32 EIA (2006) Monthly Energy Review, December 2006 and Unpublished Supplemental Tables on Petroleum Product
33 detail. Energy Information Administration, U.S. Department of Energy, Washington, DC, DOE/EIA-
34 0035(2006/12).
35 EIA (2005) EIA Manufacturing Consumption of Energy (MECS) 2002, U.S. Department of Energy, Energy
36 Information Administration, Washington, DC.
References 11-7
-------
Public Review Draft
1 EIA (2001a) Manufacturing Energy Consumption Survey (MECS) 1998, U.S. Department of Energy, Energy
2 Information Administration, Washington, DC. Available online at
3 .
4 EIA (1997) Manufacturing Energy Consumption Survey (MECS) 1994, U.S. Department of Energy, Energy
5 Information Administration, Washington, DC. December. DOE/EIA-0512(94).
6 EIA (1994) Manufacturing Energy Consumption Survey (MECS) 1991, U.S. Department of Energy, Energy
7 Information Administration, Washington, DC. December. DOE/EIA-0512(91).
8 EIIP (1999) Methods for Estimating Greenhouse Gas Emissions from Combustion of Fossil Fuels, Emissions
9 Inventory Improvement Program: State and Territorial Air Pollution Program Administrators/Association of Local
10 Air Pollution Control Officials and U.S. Environmental Protection Agency, EIIP Document Series Volume VIII,
11 Chapter 1. (STAPPA/ALAPCO/EPA), Washington, DC, August 2000. Available online at
12 . Accessed August 28, 2000.
13 EIIP (1998) "Area Sources" Asphalt Paving, Emissions Inventory Improvement Program: State and Territorial Air
14 Pollution Program Administrators/Association of Local Air Pollution Control Officials and U.S. Environmental
15 Protection Agency, EIIP Document Series Volume III, Chapter 17. (STAPPA/ALAPCO/EPA), Washington, DC,
16 August 2000. Accessed July 27, 2000 .
17 Eldredge-Roebuck (2000) Personal communication between Joe Casola of ICF International and Brandt Eldredge-
18 Roebuck of the American Plastics Council. July, 11 2000. (Tel: 703-253-0611).
19 EPA (2006a) Air Emissions Trends - Continued Progress Through 2005. U.S. Environmental Protection Agency,
20 Washington DC. December 19, 2006. < http://www.epa.gov/air/airtrends/index.html>
21 EPA (2006b) Biennial Reporting System (BRS) Database. U.S. Environmental Protection Agency, Envirofacts
22 Warehouse. Washington, DC. Available online at .
23 EPA (2004a) Biennial Reporting System (BRS). U.S. Environmental Protection Agency, Envirofacts Warehouse.
24 Washington, DC. Available online at .
25 EPA (2004b) Pesticides Industry Sales and Usage: 2000 and 2001 Market Estimates. U.S. Environmental
26 Protection Agency, Office of Prevention, Pesticides and Toxic Substances, Washington, DC. Available online at
27 .
28 EPA (2002) Pesticides Industry Sales and Usage, 1998 and 1999 Market Estimates, U.S. Environmental Protection
29 Agency, Office of Prevention, Pesticides and Toxic Substances, Washington, DC. Available online at
30 . Accessed July 2003.
31 EPA (2001) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-1999, U.S. Environmental Protection
32 Agency, Office of Atmospheric Programs, Washington, DC. EPA 236-R-01-001.
33 EPA (2000b) Toxics Release Inventory, 1998. U.S. Environmental Protection Agency, Office of Environmental
34 Information, Office of Information Analysis and Access, Washington, DC. Available online at
3 5 .
36 EPA (2000c) Hot Mix Asphalt Plants Emission Assessment Report (Draft Report), AP-42. U.S. Environmental
37 Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, June. Available
38 online at Accessed July 25, 2000.
39 EPA (1999) Pesticides Industry Sales and Usage: 1996 and 1997Market Estimates. U.S. Environmental Protection
40 Agency, Office of Prevention, Pesticides and Toxic Substances, Washington, DC. Available online at
41 .
11-8 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 EPA (1998) Pesticides Industry Sales and Usage, 1994 and 1995 Market Estimates, U.S. Environmental Protection
2 Agency, Office of Prevention, Pesticides and Toxic Substances, Washington, DC. Available online at
3 . Accessed July 2003.
4 EPA (1995) Asphalt Paving Operations, AP-42, U.S. Environmental Protection Agency, Office of Air Quality
5 Planning and Standards, Research Triangle Park, NC.
6 FEB (2006) Fiber Economics Bureau, as cited in C&EN (2006) "Production: Growth in the Norm," Chemical &
7 Engineering News, American Chemical Society, 10 July. Available online at .
8 FEB (2005) Fiber Economics Bureau, as cited in C&EN (2005) "Production: Growth in Most Regions," Chemical
9 & Engineering News, American Chemical Society, 11 July. Available online at .
10 FEB (2003) Fiber Economics Bureau, as cited in C&EN (2003) "Production Inches Up in Most Countries,"
11 Chemical & Engineering News, American Chemical Society, 7 July. Available online at .
13 FEB (2001) as reported in "Production: slow gains in output of chemicals and products lagged behind U.S.
14 economy as a whole," Chemical and Engineering News, Vol. 79 (26), June 25, 2001. Fiber Economics Bureau.
15 Washington, DC. Available online at .
16 The Financial Planning Association (2006) "Canada/US Cross-Border Tools: US/Canada Exchange Rates."
17 Available from: http://www.fpanet.org/global/planners/US_Canada_ex_rates.cfm. Accessed August 16, 2006.
18 Gosselin, Smith, and Hodge (1984) "Clinical Toxicology of Commercial Products." Fifth Edition, Williams &
19 Wilkins, Baltimore.
20 IISRP (2003) "IISRP Forecasts Moderate Growth in North America to 2007" International Institute of Synthetic
21 Rubber Producers, Inc. New Release. Available online at .
23 IISRP (2000) as reported in ACS (2001) "Facts & Figures for the Chemical Industry," Chemical and Engineering
24 News, Vol. 78 (26), June 26, 2000. International Institute of Synthetic Rubber Producers. Houston, Texas.
25 Available online in IISRP's February 18, 2000, News Release:
26 .
27 INEGI (2006) "Production bruta total de las unidades economicas manufactureras por Subsector, Rama, Subrama y
28 Clase de actividad,"
29 http://www.inegi.gob.mx/est/contenidos/espanol/proyectos/censos/ce2004/tb_manufacturas.asp. Accessed August
30 15,2006.
31 IPCC/UNEP/OECD/IEA (1997) Revised 19961PCC Guidelines for National Greenhouse Gas Inventories. Paris:
32 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
33 Co-Operation and Development, International Energy Agency.
34 IPCC/UNEP/WMO (2006) 20061PCC Guidelines for National Greenhouse Gas Inventories. Japan:
35 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Eggleston H.S.,
36 Buendia L., Miwa K., Ngara T., and Tanabe K. (eds).
37 Marland, G. and R. M. Rotty (1984) "Carbon dioxide emissions from fossil fuels: a procedure for estimation and
38 results for 1950-1982." Tellus. 36B, 4, 232-261.
39 Miller, T. (1999) Material Safety Data Sheet, Carbon Black. Continental Carbon Company. Published September
40 1, 1999. Downloaded from , October 10, 2003.
References 11-9
-------
Public Review Draft
1 NPRA(2001) Selected Petrochemical Statistics—U.S. Trade, Production and Consumption. National
2 Petrochemical & Refiners Association, Washington, DC.
3 PAN (2002) "Pesticides Database." Pesticide Action Network North America. Available online at
4 . Accessed summer-fall 2003.
5 RMA (2006). Scrap Tire Markets in the United States 2005 Edition. Rubber Manufacturers Association,
6 Washington, DC. November 2006.
7 RMA (2002) U.S. Scrap Tire Markets 2001. Rubber Manufacturers Association, Washington, DC. December 2002.
8 Schneider, S. (2007) E-mail between Shelly Schneider of Franklin Associates, A Division of ERG and Sarah
9 Shapiro of ICF International, January 10, 2007.
10 SPI (2000) The Society of the Plastics Industry Website, .
11 Accessed June 28, 2000.
12 Statistics Canada (2006) "Canadian Trade by Industry - NAICS Codes: NAICS 3252 - Resin, Synthetic Rubber, and
13 Artificial and Synthetic Fibres and Filaments Manufacturing (NAICS 3252)," Available online at
14 .
20 STMC (2003) Scrap Tire Facts and Figures. Scrap Tire Management Council of the Rubber Manufacturers
21 Association. Washington, DC. Downloaded from
22 and
23 . Accessed July 7, 2003.
24 Tooly, L. (2001) Personal communication between Robert Lanza of ICF International and Lee Tooly of EPA's
25 Office of Air Quality Planning and Standards. Access file sent in an email on August 20, 2001.
26 U.S. Bureau of the Census (2004) Soap and Other Detergent Manufacturing: 2002, Issued December 2004,
27 document number EC02-311-325611 (RV). Downloaded from
28 .
29 U.S. Bureau of the Census (2003) U.S International Trade Commission (USITC) Trade Dataweb,
30 . Accessed fall 2002-spring 2003.
31 U.S. Census Bureau (1999) 1997 Economic Census, Manufacturing—Industry Series, Petroleum Lubricating Oil
32 and Grease Manufacturing, document number EC97M-3241D, and Petroleum Refining, document number EC97M-
33 3241A(2 reports).
34 U.S. International Trade Commission (2006) Available online at: http://dataweb.usitc.gov/. Accessed September
35 27,2006.
36 Wood, A. (2003) "Compendium of Pesticide Common Names" on Alan Wood's Web Site,
37 . Accessed summer-fall 2003.
38 Mobile Combustion (excluding C02)
39 AAR (2006) Railroad Facts, 2006 Ed. Policy and Economics Department, Association of American Railroads,
11-10 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Washington, DC.
2 ANL (2006) Argonne National Laboratory (2006) GREET model Version 1.7, June 2006.
3 APTA (2006) Commuter Rail National Totals. American Public Transportation Association, Washington, DC,
4 2006. Available online at < http://www.apta.com/research/stats/rail/crsum.cfm>.
5 Benson, D. (2002 through 2004) Personal communication. Unpublished data developed by the Upper Great Plains
6 Transportation Institute, North Dakota State University and American Short Line & Regional Railroad Association.
7 BEA (1991 through 2005) Unpublished BE-36 survey data. Bureau of Economic Analysis (BEA), U.S. Department
8 of Commerce.
9 Browning, L. (2005) Personal communication regarding emission control technologies for diesel highway vehicles.
10 ICF International.
11 Browning, L. (2003) "VMT Projections for Alternative Fueled and Advanced Technology Vehicles through 2025,"
12 13th CRC On-Road Vehicle Emissions Workshop, April 2003.
13 Census (2000) Vehicle Inventory and Use Survey. U.S. Census Bureau. Washington, DC, database CD-EC97-VIUS.
14 DESC (2006) Unpublished data from the Defense Fuels Automated Management System (DFAMS), Defense
15 Energy Support Center, Defense Logistics Agency, U.S. Department of Defense.
16 DOC (1991 through 2006) Unpublished "Report of Bunker Fuel Oil Laden on Vessels Cleared for Foreign
17 Countries." Form-563, Foreign Trade Division, Bureau of the Census, U.S. Department of Commerce.
18 DOE (1993 through 2006) Transportation Energy Data Book. Office of Transportation Technologies, Center for
19 Transportation Analysis, Energy Division, Oak Ridge National Laboratory, ORNL-6959.
20 DOT (1991 through 2006) Fuel Cost and Consumption, Federal Aviation Administration, U.S. Department of
21 Transportation, Bureau of Transportation Statistics, Washington, DC, DAI-10.
22 EIA (2006a) Monthly Energy Review, December 2006 and Unpublished Supplemental Tables on Petroleum Product
23 detail. Energy Information Administration, U.S. Department of Energy, Washington, DC, DOE/EIA-
24 0035(2005/12).
25 EIA (2006b) International Energy Annual, "World Petroleum Supply and Disposition " Available online at
26 . Table 3.1.
27 EIA (2006c) Annual Energy Review 2005. Energy Information Administration, U.S. Department of Energy,
28 Washington, DC, DOE/EIA-0384(2005). July.
29 EIA (2004) Natural Gas Annual 2004. Energy Information Administration, U.S. Department of Energy,
30 Washington, DC, DOE/EIA-0131(04).
31 EIA (2003 through 2004) Personal Communication with Charles Esser. Residual and Distillate Fuel Oil
32 Consumption for Vessel Bunkering (Both International and Domestic) for American Samoa, U.S. Pacific Islands,
33 and Wake Island.
34 EIA (2002a) Alternative Fuels Data Tables. Energy Information Administration, U.S. Department of Energy,
35 Washington, DC. Available online at .
36 EIA (2002b) Personal Communication with Joel Lou. Residual and Distillate Fuel Oil Consumption for Vessel
References 11-11
-------
Public Review Draft
1 (Both International and Domestic) for American Samoa, U.S. Pacific Islands, and Wake Island.
2 EIA (1991 through 2006) Fuel Oil and Kerosene Sales. Energy Information Administration, U.S. Department of
3 Energy, Washington, DC, DOE/EIA-0535-annual.
4 EPA (2006a) Annual Certification Test Results Report. Office of Transportation and Air Quality, U.S.
5 Environmental Protection Agency. Available online at .
6 EPA (2006b) Confidential engine family sales data submitted to EPA by manufacturers. Office of Transportation
7 and Air Quality, U.S. Environmental Protection Agency.
8 EPA (2006c) Air Emissions Trends - Continued Progress Through 2005. U.S. Environmental Protection Agency,
9 Washington DC. December 19, 2006. < http://www.epa.gov/air/airtrends/index.html>
10 EPA (2006d) NONROAD Model. Office of Transportation and Air Quality, U.S. Environmental Protection
11 Agency. Available online at .
12 EPA (2006e) Motor Vehicle Emission Simulator (MOVES). Office of Transportation and Air Quality, U.S.
13 Environmental Protection Agency. Available online at .
14 EPA (2005) National Emissions Inventory Air Pollutant Emissions Trends Data. Available online at
15
16 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
17 OAQPS. December 22, 2003.
18 EPA (2000) Mobile6 Vehicle Emission Modeling Software. Office of Mobile Sources, U.S. Environmental
19 Protection Agency. Ann Arbor, Michigan.
20 EPA (1999a) Emission Facts: The History of Reducing Tailpipe Emissions. Office of Mobile Sources, May, EPA
21 420-F-99-017. Available online at .
22 EPA (1999b) Regulatory Announcement: EPA's Program for Cleaner Vehicles and Cleaner Gasoline. Office of
23 Mobile Sources, December, EPA420-F-99-051. Available online at .
32 EPA (1994b) Milestones in Auto Emissions Control. Office of Mobile Sources, August, EPA 400-F-92-014.
33 Available online at .
34 EPA (1993) Automobiles and Carbon Monoxide. Office of Mobile Sources, January, EPA 400-F-92-005. Available
35 online at .
36 FAA (2006a). FAA Aerospace Forecasts Fiscal Years 2006-2017, Table 30 "General Aviation Aircraft Fuel
37 Consumption," Federal Aviation Administration. Available online at <
11-12 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 http://www.faa.gov/data_statistics/aviation/aerospace_forecasts/2006-
2 2017/media/FAA%20Aerospace%20Forecast.pdf/>.
3 FAA (2006b) Email correspondence containing aviation emissions estimates from the System for Assessing
4 Aviation's Global Emissions (SAGE). August, 2006.
5 FHWA (1996 through 2006) Highway Statistics. Federal Highway Administration, U.S. Department of
6 Transportation. Washington, DC, report FHWA-PL-96-023-annual. Available online at
7 .
8 ICF (2006a) Revisions to Alternative Fuel Vehicle (AFV) Emission Factors for the U.S. Greenhouse Gas Inventory.
9 Memorandum from ICF International to John Davies, Office of Transportation and Air Quality, U.S. Environmental
10 Protection Agency. November 2006.
11 ICF (2006b) Revised Gasoline Vehicle EFs for LEV and Tier 2 Emission Levels. Memorandum from ICF
12 International to John Davies, Office of Transportation and Air Quality, U.S. Environmental Protection Agency.
13 November 2006.
14 ICF (2004) "Update of Methane and Nitrous Oxide Emission Factors for On-Highway Vehicles," Final Report to
15 U.S. Environmental Protection Agency, February 2004.
16 IPCC/UNEP/OECD/IEA (1997) Revised 1996IPCC Guidelines for National Greenhouse Gas Inventories, Paris:
17 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
18 Co-Operation and Development, International Energy Agency.
19 Lipman, T. and M. Delucchi (2002) "Emissions of Nitrous Oxide and Methane from Conventional and Alternative
20 Fuel Motor Vehicles," Climate Change, Volume 53, pp.477-516. Available online at
22 Unnasch, S., L. Browning and E. Kassoy (2001) "Refinement of Selected Fuel-Cycle Emissions Analyses, Final
23 Report to ARB."
24 Whorton, D. (2006) Personal communication. Class II and III Rail energy consumption. American Short Line and
25 Regional Railroad Association.
26 Coal Mining
27 AAPG (1984). Coalbed Methane Resources of the United States, AAPG Studies in Geology Series #17, 1984.
28 DOE (1983). Methane Recovery from Coalbeds: A Potential Energy Source, U.S. Department of Energy,
29 (DOE/METC/83-76).
30 EIA (2006). Annual Coal Report 1991-2005 (Formerly called Coal Industry Annual). U.S. Department of Energy,
31 Energy Information Administration, Washington, DC, Table 3.
32 EPA (1996). Evaluation and Analysis of Gas Content and Coal Properties of Major Coal Bearing Regions of the
33 United States, U.S. Environmental Protection Agency, EPA/600/R-96-065.
34 GRI (1988). A Geologic Assessment of Natural Gas from Coal Seams Topical Reports, Gas Research Institute 1986-
35 88.
36 Mutmansky, Jan M. and Yanebi Wang (2000). Analysis of Potential Errors in Determination of Coal Mine Annual
37 Methane Emissions, Mineral Resources Engineering, Vol. 9, No. 4, December 2000.
References 11-13
-------
Public Review Draft
1 USBM (1986). Circular 9067, Results of the Direct Method Determination of the Gas Contents of U.S. Coal Basins.
2 U.S. Bureau of Mines.
3 Abandoned Coal Mines
4 EPA (2003) "Methane Emissions Estimates & Methodology for Abandoned Coal Mines in the U.S.," Draft Final
5 Report, Washington DC, June 2003.
6 Mutmansky, Jan M., and Yanbei Wang (2000) Analysis of Potential Errors in Determination of Coal Mine Annual
7 Methane Emissions, Pennsylvania State University, Department of Energy and Geo-Environmental Engineering,
8 University Park, PA.
9 U.S. Department of Labor, Mine Health & Safety Administration (2006) Data Retrieval System. Available online at
10 .
11 Petroleum Systems
12 EIA (1990-2005) Petroleum Supply Annual 1990-2005 Volume 1. Energy Information Administration, U.S.
13 Department of Energy, Washington, DC.
14 EIA (1990-2006) Refinery Capacity Report. Energy Information Administration, U.S. Department of Energy,
15 Washington, DC. Available online at
16 .
17 EIA (1995-2005) Annual Energy Review. Energy Information Administration, U.S. Department of Energy,
18 Washington, DC. Available online at .
19 EIA (1995-2006) Monthly Energy Review. Energy Information Administration, U.S. Department of Energy,
20 Washington, DC. Available online at .
21 EPA (1995) Compilation of Air Pollutant Emission Factors AP-42, Fifth Edition, Volume I: Stationary Point and
22 Area Sources. U.S. Environmental Protection Agency. Available online at
23 .
24 EPA (1996) Methane Emissions from the U.S. Petroleum Industry. Draft. Prepared by Radian. June 1996.
25 EPA (1999) Estimates of Methane Emissions from the U.S. Oil Industry (Draft Report). Office of Air and
26 Radiation, U.S. Environmental Protection Agency. Prepared by ICF International. October 1999.
27 EPA (2005) Incorporating the Mineral Management Service Gulfwide Offshore Activities Data System (GOADS)
28 2000 data into the methane emissions inventories. Prepared by ICF International. 2005.
29 EPA & GRI (1996a) Methane Emissions from the Natural Gas Industry, V7: Blow and Purge Activities. Prepared
30 by Radian. April 1996.
31 EPA & GRI (1996b) Methane Emissions from the Natural Gas Industry, VI1: Compressor Driver Exhaust.
32 Prepared by Radian. April 1996.
33 EP A & GRI (1996c) Methane Emissions from the Natural Gas Industry, VI2: Pneumatic Devices. Prepared by
34 Radian. April 1996.
35 EPA & GRI (1996d) Methane Emissions from the Natural Gas Industry, VI3: Chemical Injection Pumps.
36 Prepared by Radian. April 1996.
11-14 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 MMS (2001) Field and Reserve Information. Minerals Management Service, U.S. Department of Interior.
2 Available online at .
3 MMS (2005a) OCSPlatform Activity. Minerals Management Service, U.S. Department of Interior. Available
4 online at .
5 MMS (2005b) Platform Information and Data. Minerals Management Service, U.S. Department of Interior.
6 Available online at .
7 MMS (2005c). Gulfwide Emission Inventory Study for the Regional Haze and Ozone Modeling Effort, OCS Study
8 MMS 2004-072.
9 MMS (2005d) Pacific OCS Region . Minerals Management Service, U.S. Department of Interior. Available online
10 at .
11 OGJ (2005) Oil and Gas Journal 1990-2006, Pipeline Economics Issue, August or September.
12 OGJ (2006) Oil and Gas Journal 1990-2005, Worldwide Refining Issue, January 1, 2006.
13 United States Army Corps of Engineers (1995-2004) Waterborne Commerce of the United States, Part 5: National
14 Summaries. U.S. Army Corps of Engineers, Washington, DC.
15 Natural Gas Systems
16 AAPG (2004). Shale Gas Exciting Again. American Association of Petroleum Geologists. Available online at
17 .
18 AGA (1991 through 1998) Gas Facts. American Gas Association. Washington, DC.
19 API (2005) "Table 12—Section III—Producing Oil Wells in the United States by State." Basic Petroleum Data
20 Book. American Petroleum Institute. Volume XXV, Number 1. February 2005.
21 Alabama (2006). Alabama State Oil and Gas Board. Available online at .
22 Brookhaven (2004) Natural Gas Field Subject of Interest at Brookhaven College. Brookhaven College. Available
23 online at .
24 EIA (2004) Report "US LNG Markets and Uses" Energy Information Administration, Department of Energy,
25 Washington, DC. June 2004. Available online at .
27 EIA (2005). "Table 5—U.S. Crude Oil, Natural Gas, and Natural Gas Liquids Reserves, 1977-2003." Energy
28 Information Administration, Department of Energy, Washington, DC.
29 EIA (2006a). "Documentation of the Oil and Gas Supply Module (OGSM)." Department of Energy, Washington,
30 DC. Available online at .
31 EIA (2006b) Number of Producing Gas and Gas Condensate Wells, 1989-2004, Natural Gas Navigator. Energy
32 Information Administration, Department of Energy, Washington, DC. Available online at
33 .
34 EIA (2006c). "Table 2—Supply and Disposition of Dry Natural Gas in the United States 1999-2005." Natural Gas
35 Monthly. Energy Information Administration, Department of Energy, Washington, DC. Available online at
36 .
References 11-15
-------
Public Review Draft
1 EIA (2006d). "Table 3—Natural Gas Consumption in the United States." Natural Gas Monthly. Energy
2 Information Administration, Department of Energy, Washington, DC. Available on line at
3 .
4 EIA (2006e). Table 5.2. Monthly Energy Review. Energy Information Administration, Department of Energy,
5 Washington, DC. Available online at .
6 EIA (2006f). "Table 7—Marketed Production of Natural Gas by State." Natural Gas Monthly. Energy Information
7 Administration, Department of Energy, Washington, DC. Available online at .
8 EIA (2006g) U.S. Imports by Country. Energy Information Administration, Department of Energy, Washington,
9 DC. Available online at .
10 EPA/GRI (1996) Methane Emissions from the Natural Gas Industry, Prepared by Harrison, M., T. Shires, J.
11 Wessels, and R. Cowgill, eds. Radian International LLC for National Risk Management Research Laboratory, Air
12 Pollution Prevention and Control Division, Research Triangle Park, NC, EPA-600/R-96-080a.
13 EPA (1999) Estimates of Methane Emissions from the U.S. Oil Industry (Draft Report). Prepared by ICF-Kaizer.
14 Office of Air and Radiation, U.S. Environmental Protection Agency. October 1999.
15 EPA (2006). Natural Gas STAR Reductions 1990-2005. Natural Gas STAR Program.
16 GRI (2001). Gas Resource Database: Unconventional Natural Gas and Gas Composition Databases. Second
17 Edition. GRI-01/0136.
18 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
19 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
20 Published: IGES, Japan.
21 Kansas (2006). Kansas Geological Survey. Oil and Gas Production Data, All Wells. University of Kansas.
22 Available online at .
23 Lippman (2003). Rocky Mountain Region Second Quarter 2003 Production Report. Lippman Consulting, Inc.
24 MMS (2006a) Gulf of Mexico Region Offshore Information. Minerals Management Service, U.S. Department of
25 Interior. Available online at .
26 MMS (2006b) Gulf of Mexico Region Products/Free Data. Minerals Management Service, U.S. Department of
27 Interior. Available online at .
28 MMS (2006c) Gulfwide Emission Inventory Study for the Regional Haze and Ozone Modeling Effort, OCS Study
29 MMS 2004-072.
30 MMS (2006d) OCS Platform Activity. Minerals Management Service, U.S. Department of Interior. Available
31 online at .
32 MMS (2006e) Pacific OCS Region. Minerals Management Service, U.S. Department of Interior. Available online
33 at .
34 Montana (2006) Montana Online Oil and Gas Information System. Montana Board of Oil and Gas Conservation,
35 Billing Office. Available online at .
36 Morgan Stanley (2005). Barnett Shale Update: None-Core Confidence Rises. Available online at
37
-------
Public Review Draft
1 Shale.pdf>.
2 New Mexico (2006a). Annual Gas Well Counts by State District. Available online at
3 .
4 New Mexico (2006b). Districts. Available online at .
5 OGJ (1997-2006) "Worldwide Gas Processing." Oil & Gas Journal. PennWell Corporation, Tulsa, OK.
6 Oklahoma (2006). Oklahoma Petroleum Information Center - Coalbed-Methane Completions database. Oklahoma
7 Geological Survey. Available online at .
8 OPS (2006a) Natural Gas Transmission Pipeline Annual Mileage. Office of Pipeline Safety, Department of
9 Transportation. Washington, DC. Available online at .
10 OPS (2006b) Distribution Annuals Data. Office of Pipeline Safety, Department of Transportation. Washington, DC.
11 Available online at .
12 Texas (2006a) Gas Well Counts by County. Texas Railroad Commission. Available online at
13 .
14 Texas (2006b) Oil Well Counts by County. Texas Railroad Commission. Available online at
15 .
16 Texas (2006c) The Barnett Shale Regional Report. Foster, Brad, Devon Energy. Texas Railroad Commission.
17 Available online at .
18 Texas (2006d) Oil and Gas District Boundaries. Texas Railroad Commission. Available online at
19 .
20 Utah (2006) Oil and Gas Data Download. Utah Division of Oil, Gas and Mining - Department of Natural
21 Resources. Available online at .
22 World Oil Magazine (2006a). Outlook 2006: United States Producing gas wells. February 2006. Vol. 227 No. 2.
23 Available online at .
25 World Oil Magazine (2006b). Outlook 2006: United States Producing oil wells. February 2006. Vol. 227 No. 2.
26 Available online at .
27 Wyoming (2006) Wyoming Oil and Gas Conservation Commission. Available online at
28 .
29 Municipal Solid Waste Combustion
30 De Soete, G. G. (1993) Nitrous Oxide from Combustion and Industry: Chemistry, Emissions and Control. In Van
31 Amstel, A. R. (ed) Proc. of the International Workshop Methane and Nitrous Oxide: Methods in National Emission
32 Inventories and Options for Control, Amersfoort (NL) 3-5 February.
33 DeZan, D. (2000) Personal communication between Diane DeZan of the Fiber Economics Bureau and Joe Casola of
34 ICF International, August 4, 2000.
35 EPA (2006a) Solid Waste Management and Greenhouse Gases: A Life-Cycle Assessment of Emissions and Sinks.
36 U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, Washington, DC.
References 11-17
-------
Public Review Draft
1 EPA (2006b) Municipal Solid Waste in the United States: Facts and Figures for 2005. U.S. Environmental
2 Protection Agency, Office of Solid Waste and Emergency Response, EPA. Washington, DC. Available online at <
3 http://www.epa.gov/epaoswer/non-hw/muncpl/msw99.htm>.
4 EPA (2005a) Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and Figures
5 for 2003. U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response, EPA.
6 Washington, DC. Available online at .
7 EPA (2003) Characterization of Municipal Solid Waste in the United States: 2001 Update. (Draft) U.S.
8 Environmental Protection Agency, Office of Solid Waste and Emergency Response, EPA. Washington, DC.
9 EPA (2002) Characterization of Municipal Solid Waste in the United States: 2000 Update. U.S. Environmental
10 Protection Agency, Office of Solid Waste and Emergency Response, EPA. Washington, DC, EPA530-R-02-001.
11 EPA (2000a) Characterization of Municipal Solid Waste in the United States: 1999 Update Fact Sheet (and Data
12 Tables). U.S. Environmental Protection Agency, Office of Solid Waste, EPA. Washington, DC, EPA530-F-00-
13 024.
14 EPA (2000b) Characterization of Municipal Solid Waste in the United States: Source Data on the 1999 Update.
15 U.S. Environmental Protection Agency, Office of Solid Waste, EPA. Washington, DC, EPA530-F-00-024.
16 EPA (1999) Characterization of Municipal Solid Waste in the United States: 1998 Update. Report No. EPA530-R-
17 99-021. U.S. Environmental Protection Agency, Office of Solid Waste, EPA. Washington, DC.
18 EPA (1998) Characterization of Municipal Solid Waste in the United States: 1997 Update. U.S. Environmental
19 Protection Agency, Office of Solid Waste, EPA. Washington, DC, EPA530-R-98-007.
20 EPA (1997) Characterization of Municipal Solid Waste in the United States: 1996 Update. U.S. Environmental
21 Protection Agency, Office of Solid Waste, EPA. Washington, DC, EPA530-R-97-015.
22 EPA (1996) Characterization of Municipal Solid Waste in the United States: 1995 Update. U.S. Environmental
23 Protection Agency, Office of Solid Waste, EPA. Washington, DC.
24 EPA (1995) Compilation of Air Pollutant Emission Factors, AP-42, Fifth Edition, Volume I: Stationary Point and
25 Area Sources, Introduction. Office of Air Quality Planning and Standards, U.S. EPA. Research Triangle Park, NC.
26 October.
27 FEB (2006) Fiber Economics Bureau, as cited in C&EN (2006) "Production: Growth in Most Regions," Chemical
28 & Engineering News, American Chemical Society, 11 July. Available online at .
29 Glenn, Jim (1999) "11th Annual BioCycle Nationwide Survey: The State of Garbage in America." BioCycle, April
30 1999. JG Press, Emmaus, PA.
31 Goldstein, N. and C. Madtes (2001) "13th Annual BioCycle Nationwide Survey: The State of Garbage in America,"
32 BioCycle, December 2001. JG Press, Emmaus, PA.
33 Goldstein, N. and C. Madtes (2000) "12th Annual BioCycle Nationwide Survey: The State of Garbage in America,
34 Part I," BioCycle, November 2000. JG Press, Emmaus, PA.
35 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
36 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
37 XVI/Doc. 10 (1.IV.2000). May.
38 Johnke (1999), as cited in Good Practice Guidance and Uncertainty Management in National Greenhouse Gas
39 Inventories, Intergovernmental Panel on Climate Change, 2000.
11-18 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Kaufman, et al. (2004a) "14th Annual BioCycle Nationwide Survey: The State of Garbage in America 2004"
2 Biocycle, January, 2004. JG Press, Emmaus, PA.
3 Kaufman, et al. (2004b) "Corrections to State of Garbage 2004" Biocycle, April, 2004. JG Press, Emmaus, PA.
4 Miller, T. (1999) Material Safety Data Sheet, Carbon Black. Continental Carbon Company. Published September
5 1, 1999. Downloaded from , October 10, 2003.
6 RMA (2006) U.S. Scrap Tire Markets in the United States 2005 Edition. Rubber Manufacturers Association,
7 Washington, DC. November 2006.
8 Schneider, S. (2007) E-mail between Shelly Schneider of Franklin Associates, A Division of ERG and Sarah
9 Shapiro of ICF International, January 10, 2007.
10 Simmons, et al. (2006) "15th Nationwide Survey of Municipal Solid Waste Management in the United States: The
11 State of Garbage in America" BioCycle, April 2006. JG Press, Emmaus, PA.
12 STMC (2006) Scrap Tire Facts and Figures. Scrap Tire Management Council of the Rubber Manufacturers
13 Association. Washington, DC. Downloaded from
14 and
15 , January 3, 2007.
16 STMC (2003) Scrap Tire Facts and Figures. Scrap Tire Management Council of the Rubber Manufacturers
17 Association. Washington, DC. Downloaded from
18 and
19 , July 7, 2003.
20 STMC (2002) Scrap Tire Facts and Figures. Scrap Tire Management Council of the Rubber Manufacturers
21 Association. Washington, DC. Downloaded from , October 22,
22 2002.
23 STMC (2001) Scrap Tire Facts and Figures. Scrap Tire Management Council of the Rubber Manufacturers
24 Association. Washington, DC. Downloaded from , September
25 5,2001.
26 STMC (2000) Scrap Tire Facts and Figures. Scrap Tire Management Council of the Rubber Manufacturers
27 Association. Washington, DC. Downloaded from , July 26, 2000.
28 UK: Environment Agency (1999), as cited in Good Practice Guidance and Uncertainty Management in National
29 Greenhouse Gas Inventories, Intergovernmental Panel on Climate Change, 2000.
30 Yasuda (1993), as cited in Good Practice Guidance and Uncertainty Management in National Greenhouse Gas
31 Inventories, Intergovernmental Panel on Climate Change, 2000.
32 Energy Sources of Indirect Greenhouse Gas Emissions
33 EPA (2006) Air Emissions Trends - Continued Progress Through 2005. U.S. Environmental Protection Agency,
34 Washington DC. December 19, 2006. Available online at < http://www.epa.gov/air/airtrends/index.html>.
35 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
36 OAQPS. December 22, 2003.
37 EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42, U.S. Environmental Protection Agency, Office
38 of Air Quality Planning and Standards, Research Triangle Park, NC, October.
References 11-19
-------
Public Review Draft
1 International Bunker Fuels
2 ASTM (1989) Military Specification for Turbine Fuels, Aviation, Kerosene Types, NATO F-34 (JP-8), and NATO
3 F-35. February 10, 1989. Available online at .
4 BEA (1991 through 2006) Unpublished BE-36 survey data. Bureau of Economic Analysis (BEA). U.S. Department
5 of Commerce, Washington, DC.
6 Chevron (2000) Aviation Fuels Technical Review (FTR-3). Chevron Products Company, Chapter 2. Available
7 online at .
8 DESC (2006) Unpublished data from the Defense Fuels Automated Management System (DFAMS). Defense
9 Energy Support Center, Defense Logistics Agency, U.S. Department of Defense, Washington, DC.
10 DOC (1991 through 2006) Unpublished "Report of Bunker Fuel Oil Laden on Vessels Cleared for Foreign
11 Countries." Foreign Trade Division, Bureau of the Census, U.S. Department of Commerce, Washington, DC. Form-
12 563.
13 DOT (1991 through 2006) Fuel Cost and Consumption. Airline Information, Bureau of Transportation Statistics,
14 U.S. Department of Transportation, Washington, DC.
15 EIA (2006) Monthly Energy Review, December 2006 and Unpublished Supplemental Tables on Petroleum Product
16 detail. Energy Information Administration, U.S. Department of Energy, Washington, DC, DOE/EIA-
17 0035(2006/12).
18 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
19 Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T., and Tanabe K. (eds.).
20 Published: IGES, Japan.
21 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris:
22 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
23 Co-Operation and Development, International Energy Agency.
24 USAF (1998) Fuel Logistics Planning. U.S. Air Force pamphlet AFPAM23-221, May 1,1998.
25 Wood Biomass and Ethanol Consumption
26 EIA (2006) Annual Energy Review 2005. Energy Information Administration, U.S. Department of Energy.
27 Washington, DC. July. Tables 10.2a and 10.2b. DOE/EIA-0384(2005).
28 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris:
29 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
30 Co-Operation and Development, International Energy Agency.
31 Lindstrom, P. (2006) Personal communication between Jean Kim of ICF Consulting and Perry Lindstrom of the
32 Energy Information Administration.
33 Industrial Processes
34 Cement Manufacture
35 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
36 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
37 XVI/Doc. 10 (1.IV.2000). May.
11-20 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Public Review Draft
IPCC (1996) Climate Change 1995: The Science of Climate Change, Intergovernmental Panel on Climate Change;
J.T. Houghton, L.G. MeiraFilho, B.A. Callander, N. Harris, A. Kattenberg, andK. Maskell, eds.; Cambridge
University Press. Cambridge, U.K.
USGS (2005) Minerals Yearbook: Cement Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Cement Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Cement Annual Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Cement Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Cement Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Cement Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Cement Annual Report 1998. 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 (1996) Minerals Yearbook: Cement Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Cement Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Cement Annual Report 1993. U.S. Geological Survey, Reston, VA.
USGS (1993) Minerals Yearbook: Cement Annual Report 1992. U.S. Geological Survey, Reston, VA.
Van Oss (2006) Electronic mail from Hendrik Van Oss, Commodity Specialist, USGS to Mr. Erin Fraser, ICF
International, September 20, 2006.
Iron and Steel Production
AISI (2006) 2005 Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
AISI (2005) 2004 Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
AISI (2004) 2003 Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
AISI (2003) 2002 Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
AISI (2002) 2001 Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
AISI (2001) 2000 Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
AISI (1996) 1995 Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
AISI (1995) 1994 Annual Statistical Report, American Iron and Steel Institute, Washington, DC.
DOE (1997) Office of Industrial Technologies—Energy and Environmental Profile of the U.S. Aluminum Industry,
July 1997.
References 11-21
-------
Public Review Draft
1 EIA (2006a) Annual Energy Review 2005, Energy Information Administration, U.S. Department of Energy,
2 Washington, DC. DOE/ EIA-0384.
3 EIA (2006b) Emissions of Greenhouse Gases in the United States 2005. Energy Information Administration, U.S.
4 Department of Energy, Washington DC. DOE/EIA-0573 (2005).
5 EIA (2006c) Quarterly Coal Report January-March 2006, Energy Information Administration, U.S. Department of
6 Energy, Washington, DC. DOE/EIA-0121.
7 EIA (2004a) Quarterly Coal Report October-December 2003, Energy Information Administration, U.S. Department
8 of Energy, Washington, DC. DOE/EIA-0121.
9 EIA (2004b) Emissions of Greenhouse Gases in the United States 2003. Energy Information Administration, U.S.
10 Department of Energy, Washington DC. DOE/EIA-0573.
11 EIA (2003) Quarterly Coal Report October-December 2002, Energy Information Administration, U.S. Department
12 of Energy, Washington, DC. DOE/EIA-0121.
13 EIA (2002) Quarterly Coal Report October-December 2001, Energy Information Administration, U.S. Department
14 of Energy, Washington, DC. DOE/EIA-0121.
15 EIA (2001) Quarterly Coal Report October-December 2000, Energy Information Administration, U.S. Department
16 of Energy, Washington, DC. DOE/EIA-0121.
17 EIA (2000) Quarterly Coal Report October-December 1999, Energy Information Administration, U.S. Department
18 of Energy, Washington, DC. DOE/EIA-0121 (2000/4Q).
19 EIA (1999) Quarterly Coal Report October-December 1998, Energy Information Administration, U.S. Department
20 of Energy, Washington, DC. DOE/EIA-0121.
21 EIA (1998) Quarterly Coal Report October-December 1997, Energy Information Administration, U.S. Department
22 of Energy, Washington, DC. DOE/EIA-0121.
23 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
24 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
25 Published: IGES, Japan.
26 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
27 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
28 XVI/Doc. 10 (1.IV.2000). May.
29 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, Paris:
30 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
31 Co-Operation and Development, International Energy Agency.
32 IPCC/UNEP/OECD/IEA (1995) IPCC Guidelines for National Greenhouse Gas Inventories, Volume 3, Greenhouse
33 Gas Inventory Reference Manual. Table 2-2. Intergovernmental Panel on Climate Change, United Nations
34 Environment Programme, Organization for Economic Co-Operation and Development, International Energy
35 Agency. IPCC WG1 Technical Support Unit, UK.
36 Jorgenson, J. (2006) Telephone Conversation between Chris Steuer of ICF International and John Jorgenson,
37 Commodity Specialist, USGS, 20 September 2006.
38 USAA (2006) Primary Aluminum Statistics. U.S. Aluminum Association, Washington, DC. January 2006.
11-22 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
USAA (2005) Primary Aluminum Statistics. U.S. Aluminum Association, Washington, DC. January 2005.
USAA (2004) Primary Aluminum Statistics. U.S. Aluminum Association, Washington, DC. January 2004.
U.S. Bureau of the Census (2006) U.S International Trade Commission (USITC) Trade Dataweb,
. Accessed Fall 2006.
USGS (2006) Minerals Yearbook: Iron Ore Report 2005. U.S. Geological Survey, Reston, VA.
USGS (2005) Minerals Yearbook: Iron Ore Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Iron Ore Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Iron Ore Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Iron Ore Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Iron Ore Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Iron Ore Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Iron Ore Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Iron Ore Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1991) Minerals Yearbook: Iron Ore Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Iron Ore Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Iron Ore Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Iron Ore Report 1993. U.S. Geological Survey, Reston, VA.
Ammonia Manufacture and Urea Application
Bark (2004) Coffeyville Nitrogen Plant. Available online at
Accessed: December 15, 2004.
Coffeyville Resources Nitrogen Fertilizers, LLC. (2006) Business Data. Available online at
Accessed: September 7, 2006.
Coffeyville Resources Nitrogen Fertilizers, LLC. (2005) Business Data. Available online at
Accessed: September 12, 2005.
EFMA (1995) Production of Ammonia. European Fertilizer Manufacturers Association. March 1.
EIA (1998) Manufacturing Energy Consumption Survey (MECS) U.S. Department of Energy, Energy Information
Administration, Washington DC. Available online at
.
EIA (1994) Manufacturing Energy Consumption Survey (MECS) U.S. Department of Energy, Energy Information
Administration, Washington DC.
IPCC/UNEP/OECD/IEA (1997) Revised 1996IPCC Guidelines for National Greenhouse Gas Inventories, Paris:
References 11-23
-------
Public Review Draft
1 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
2 Co-Operation and Development, International Energy Agency.
3 TFI (2002) U.S. Nitrogen Imports/Exports Table, The Fertilizer Institute. Accessed online at
4 , August 2002.
5 U.S. Census Bureau (2006) Current Industrial Reports Fertilizer Materials and Related Products: 2005 Summary.
6 Available online at .
7 U.S. Census Bureau (2005) Current Industrial Reports Fertilizer Materials and Related Products: Fourth Quarter
8 Report 2004 Summary. Available online at .
9 U.S. Census Bureau (2004) Current Industrial Reports Fertilizer Materials and Related Products: Fourth Quarter
10 Report 2003 Summary. Available online at .
11 U.S. Census Bureau (2003) Current Industrial Reports Fertilizer Materials and Related Products: Annual Reports
12 2002 Summary. Available online at .
13 U.S. Census Bureau (2002a) Current Industrial Reports Fertilizer Materials and Related Products: First Quarter
14 2002, June 2002. Available online at .
15 U.S. Census Bureau (2002b) Current Industrial Reports Fertilizer Materials and Related Products: Fourth Quarter
16 2001, March 2002. Available online at .
17 U.S. Census Bureau (2002c) Current Industrial Reports Fertilizer Materials and Related Products: Third Quarter
18 2001, January 2002. Available online at .
19 U.S. Census Bureau (2001a) Current Industrial Reports Fertilizer Materials and Related Products: Second Quarter
20 2001, September 2001. Available online at .
21 U.S. Census Bureau (200 lb) Current Industrial Reports Fertilizer Materials and Related Products: Annual Report
22 2000. Available online at .
23 U.S. Census Bureau (2000) Current Industrial Reports Fertilizer Materials and Related Products: Annual Report
24 1999. Available online at .
25 U.S. Census Bureau (1999) Current Industrial Reports Fertilizer Materials and Related Products: Annual Report
26 1998. Available online at .
27 U.S. Census Bureau (1998) Current Industrial Reports Fertilizer Materials and Related Products: Annual Report
28 1997. Available online at .
29 U.S. Census Bureau (1994) Current Industrial Reports Fertilizer Materials Annual Report 1993, Report No.
30 MQ28B.
31 U.S. Census Bureau (1993) Current Industrial Reports Fertilizer Materials Annual Report 1992, Report No.
32 MQ28B.
33 U.S. Census Bureau (1992) Current Industrial Reports Fertilizer Materials Annual Report 1991, Report No.
34 MQ28B.
35 U.S. Census Bureau (1991) Current Industrial Reports Fertilizer Materials Annual Report 1990, Report No.
36 MQ28B.
11-24 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
U.S. ITC (2002) United States International Trade Commission Interactive Tariff and Trade DataWeb, Version
2.5.0. Accessed online at . Accessed August, 2002.
Lime Manufacture
IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc. 10 (1.IV.2000). May.
Males, E. (2003) Public review comments received in a memorandum from Eric Males, National Lime Association
to Mr. William N. Irving & Mr. Leif Hockstad, Environmental Protection Agency. Memorandum dated March 6,
2003.
USGS (2006) Minerals Yearbook: Lime Annual Report 2005. U.S. Geological Survey, Reston, VA.
USGS (2005) Minerals Yearbook: Lime Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Lime Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Lime Annual Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Lime Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Lime Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Lime Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Lime Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Lime Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Lime Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Lime Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Lime Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Lime Annual Report 1993. U.S. Geological Survey, Reston, VA.
USGS (1992) Minerals Yearbook: Lime Annual Report 1991. U.S. Geological Survey, Reston, VA.
Limestone and Dolomite Use
USGS (2006) Minerals Yearbook: Magnesium Annual Report 2005. U.S. Geological Survey, Reston, VA.
USGS (2005a) Minerals Yearbook: Magnesium Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2005b) Minerals Yearbook: Magnesium Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004a) Minerals Yearbook: Crushed Stone Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2004b) Minerals Yearbook: Magnesium Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003a) Minerals Yearbook: Crushed Stone Annual Report 2002. U.S. Geological Survey, Reston, VA.
References 11-25
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Public Review Draft
USGS (2003b) Minerals Yearbook: Magnesium Annual Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002a) Minerals Yearbook: Crushed Stone Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2002b) Minerals Yearbook: Magnesium Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001a) Minerals Yearbook: Crushed Stone Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2001b) Minerals Yearbook: Magnesium Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000a) Minerals Yearbook: Crushed Stone Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (2000b) Minerals Yearbook: Magnesium Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999a) Minerals Yearbook: Crushed Stone Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1999b) Minerals Yearbook: Magnesium Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998a) Minerals Yearbook: Crushed Stone Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1998b) Minerals Yearbook: Magnesium Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997a) Minerals Yearbook: Crushed Stone Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1997b) Minerals Yearbook: Magnesium Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996a) Minerals Yearbook: Crushed Stone Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1996b) Minerals Yearbook: Magnesium Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995a) Minerals Yearbook: Crushed Stone Annual Report 1993. U.S. Geological Survey, Reston, VA.
USGS (1995b) Minerals Yearbook: Crushed Stone Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1995c) Minerals Yearbook: Magnesium Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1993) Minerals Yearbook: Crushed Stone Annual Report 1991. U.S. Geological Survey, Reston, VA.
Weaver (2006) Electronic mail from Susan Weaver, Commodity Specialist, U.S. Geological Survey, to Erin Fraser
of ICF International. 14 September.
Soda Ash Manufacture and Consumption
USGS (2006) Minerals Yearbook: Soda Ash Annual Report 2005. U.S. Geological Survey, Reston, VA.
USGS (2005) Minerals Yearbook: Soda Ash Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Soda Ash Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Soda Ash Annual Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Soda Ash Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Soda Ash Annual Report 2000. U.S. Geological Survey, Reston, VA.
11-26 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Public Review Draft
USGS (2000) Minerals Yearbook: Soda Ash Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Soda Ash Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Soda Ash Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Soda Ash Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Soda Ash Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Soda Ash Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Soda Ash Annual Report 1993. U.S. Geological Survey, Reston, VA.
Titanium Dioxide Production
Kramer, D. (2006). Telephone conversation between Erin Fraser of ICF Consulting and Deborah Kramer,
Commodity Specialist, U.S. Geological Survey, September.
Gambogi, J. (2002). Telephone conversation between Philip Groth of ICF Consulting and Joseph Gambogi,
Commodity Specialist, U.S. Geological Survey, November.
Onder, H, and E.A. Bagdoyan (1993) Everything You've Always Wanted to Know about Petroleum Coke. Allis
Mineral Systems.
USGS (2006) Minerals Commodity Summaries: Titanium Mineral Concentrates 2005. U.S. Geological Survey,
Reston, VA.
USGS (2005) Mineral Yearbook: Titanium Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Mineral Yearbook: Titanium Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Mineral Yearbook: Titanium Annual Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002) Mineral Yearbook: Titanium Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Mineral Yearbook: Titanium Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Mineral Yearbook: Titanium Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Titanium Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Titanium Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Titanium Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Titanium Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Titanium Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Titanium Annual Report 1993. U.S. Geological Survey, Reston, VA.
USGS (1993) Minerals Yearbook: Titanium Annual Report 1992. U.S. Geological Survey, Reston, VA.
References 11-27
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
Public Review Draft
USGS (1992) Minerals Yearbook: Titanium Annual Report 1991. U.S. Geological Survey, Reston, VA.
USGS (1991) Minerals Yearbook: Titanium Annual Report 1990. U.S. Geological Survey, Reston, VA.
Ferroalloy Production
Corathers, L. (2006) Personal communication between Erin Fraser of ICF International and Lisa Corathers,
Commodity Specialist, U.S. Geological Survey, October.
IPCC (2006) 20061PCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
Published: IGES, Japan.
Onder, H, and E.A. Bagdoyan (1993) Everything You've Always Wanted to Know about Petroleum Coke. Allis
Mineral Systems.
USGS (2005) Minerals Yearbook: Silicon Annual Report 2004. U.S. Geological Survey, Reston, VA
USGS (2004) Minerals Yearbook: Silicon Annual Report 2003. U.S. Geological Survey, Reston, VA
USGS (2003) Minerals Yearbook: Silicon Annual Report 2002. U.S. Geological Survey, Reston, VA
USGS (2002) Minerals Yearbook: Silicon Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Silicon Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Silicon Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Silicon Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Silicon Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Silicon Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Silicon Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Silicon Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1994) Minerals Yearbook: Silicon Annual Report 1993. U.S. Geological Survey, Reston, VA.
USGS (1993) Minerals Yearbook: Silicon Annual Report 1992. U.S. Geological Survey, Reston, VA.
USGS (1992) Minerals Yearbook: Silicon Annual Report 1991. U.S. Geological Survey, Reston, VA.
USGS (1991) Minerals Yearbook: Silicon Annual Report 1990. U.S. Geological Survey, Reston, VA.
Phosphoric Acid Production
EFMA (2000) European Fertilizer Manufacturers Association Best Available Techniques for Pollution Prevention
and Control in the European Fertilizer Industry ~ Booklet No. 4 of 8: Production of Phosphoric Acid. Available
online at .
FIPR (2003) Florida Institute of Phosphate Research, Analyses of Some Phosphate Rocks, facsimile from Mr. Gary
Albarelli, FIPR, Bartow, Florida, to Mr. Robert Lanza, ICF Consulting, July 29, 2003.
11-28 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Public Review Draft
FIPR (2003a) Florida Institute of Phosphate Research, personal communication of Mr. Michael Lloyd, Laboratory
Manager, FIPR, Bartow, Florida, to Mr. Robert Lanza, ICF Consulting, August 2003.
USGS (2006). Minerals Yearbook. Phosphate Rock Annual Report 2005. U.S. Geological Survey, Reston, VA.
USGS (2005). Minerals Yearbook. Phosphate Rock Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook. Phosphate Rock Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Electronic mails from Mr. Stephen M Jasinski, USGS Commodity Specialist, Phosphate Rock to Mr.
Robert Lanza, ICF Consulting, July-August, 2003.
USGS
(2002)
Minerals
Yearbook.
Phosphate Rock Annual Report 2001.
U.S.
Geological
Survey,
Reston,
VA.
USGS
(2001)
Minerals
Yearbook.
Phosphate Rock Annual Report 2000.
U.S.
Geological
Survey,
Reston,
VA.
USGS
(2000)
Minerals
Yearbook.
Phosphate Rock Annual Report 1999.
U.S.
Geological
Survey,
Reston,
VA.
USGS
(1999)
Minerals
Yearbook.
Phosphate Rock Annual Report 1998.
U.S.
Geological
Survey,
Reston,
VA.
USGS
(1998)
Minerals
Yearbook.
Phosphate Rock Annual Report 1997.
U.S.
Geological
Survey,
Reston,
VA.
USGS
(1997)
Minerals
Yearbook.
Phosphate Rock Annual Report 1996.
U.S.
Geological
Survey,
Reston,
VA.
USGS
(1996)
Minerals
Yearbook.
Phosphate Rock Annual Report 1995.
U.S.
Geological
Survey,
Reston,
VA.
USGS
(1995)
Minerals
Yearbook.
Phosphate Rock Annual Report 1994.
U.S.
Geological
Survey,
Reston,
VA.
USGS
(1994)
Minerals
Yearbook.
Phosphate Rock Annual Report 1993.
U.S.
Geological
Survey,
Reston,
VA.
Carbon Dioxide Consumption
Allis, R. et al. (2000) Natural C02 Reservoirs on the Colorado Plateau and Southern Rocky Mountains: Candidates
for C02 Sequestration. Utah Geological Survey and Utah Energy and Geoscience Institute, Salt Lake City, Utah.
ARI (2006) C02-EOR: An Enabling Bridge for the Oil Transition. Presented to: Modeling the Oil Transition - a
DOE/EPA Workshop on the Economic and Environmental Implications of Global Energy Transitions. Washington,
DC. April 20-21, 2006.
Broadhead, R. (2006) Electronic mail from Mr. Ron Broadhead, New Mexico Bureau of Geology and Mineral
Resources to Mr. Erin Fraser, ICF International, September 2006.
Denbury Resources Inc. (2006) Annual Report, 2004, Page 34.
Denbury Resources Inc. (2005) Annual Report, 2004, Page 32.
Denbury Resources Inc. (2004) Annual Report, 2003, Page 41.
Denbury Resources Inc. (2003) Annual Report, 2002, Page 14.
Denbury Resources Inc. (2002) Annual Report, 2001, Page 22.
Zinc Production
References 11-29
-------
Public Review Draft
1 Gabby, P. (2006) Telephone Conversation between Erin Fraser of ICF International and Peter Gabby, Commodity
2 Specialist, USGS, 29 September 2006.
3 Queneau P.B., James S.E., Downey J.P., Livelli G.M. (1998) Recycling Lead and Zinc in the United States. Zinc
4 and Lead Processing. The Metallurgical Society of CIM.
5 Recycling Today (2005). Horsehead Sales Complete. Available at
6 . January 5, 2005.
7 Sjardin (2003) CO2 Emission Factors for Non-Energy Use in the Non-Ferrous Metal, Ferroalloys and Inorganics
8 Industry. Copernicus Institute, Utrecht, The Netherlands.
9 Stuart (2005). Telephone Conversation between Chris Steuer of ICF Consulting and Eric Stuart of the Steel
10 Manufacturers Association. October 31st, 2005.
11 USGS (2005) Minerals Yearbook: Zinc Annual Report 2004. U.S. Geological Survey, Reston, VA.
12 USGS (2004) Minerals Yearbook: Zinc Annual Report 2003. U.S. Geological Survey, Reston, VA.
13 USGS (2003) Minerals Yearbook: Zinc Annual Report 2002. U.S. Geological Survey, Reston, VA.
14 USGS (2002) Minerals Yearbook: Zinc Annual Report 2001. U.S. Geological Survey, Reston, VA.
15 USGS (2001) Minerals Yearbook: Zinc Annual Report 2000. U.S. Geological Survey, Reston, VA.
16 USGS (2000) Minerals Yearbook: Zinc Annual Report 1999. U.S. Geological Survey, Reston, VA.
17 USGS (1999) Minerals Yearbook: Zinc Annual Report 1998. U.S. Geological Survey, Reston, VA.
18 USGS (1998) Minerals Yearbook: Zinc Annual Report 1997. U.S. Geological Survey, Reston, VA.
19 USGS (1997) Minerals Yearbook: Zinc Annual Report 1996. U.S. Geological Survey, Reston, VA.
20 USGS (1996) Minerals Yearbook: Zinc Annual Report 1995. U.S. Geological Survey, Reston, VA.
21 USGS (1995) Minerals Yearbook: Zinc Annual Report 1994. U.S. Geological Survey, Reston, VA.
22 Viklund-White C. (2000) The Use of LCA for the Environmental Evaluation of the Recycling of Galvanized Steel.
23 ISIJ International. Volume 40 No. 3: 292-299.
24 Lead Production
25 Gabby, P. (2006) Telephone Conversation between Erin Fraser of ICF International and Peter Gabby, Commodity
26 Specialist, USGS, 29 September 2006.
27 Dutrizac, J.E., Ramachandran, V., and Gonzalez, J. A. (2000) Lead-zinc 2000. The Minerals, Metals, and Materials
28 Society.
29 Morris, D., Steward, F.R., and Evans, P. (1983) Energy Efficiency of a Lead Smelter. Energy 8 (5) pp: 337-349
30 Sjardin, M. (2003) CO2 Emission Factors for Non-Energy Use in the Non-Ferrous Metal, Ferroalloys and
31 Inorganics Industry. Copernicus Institute, Utrecht, The Netherlands.
32 Ullman's Encyclopedia of Industrial Chemistry: Fifth Edition (1997) Volume A5. John Wiley and Sons.
11-30 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
USGS (2005) Minerals Yearbook: Lead Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004) Minerals Yearbook: Lead Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003) Minerals Yearbook: Lead Annual Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002) Minerals Yearbook: Lead Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001) Minerals Yearbook: Lead Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000) Minerals Yearbook: Lead Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999) Minerals Yearbook: Lead Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998) Minerals Yearbook: Lead Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997) Minerals Yearbook: Lead Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996) Minerals Yearbook: Lead Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995) Minerals Yearbook: Lead Annual Report 1994. U.S. Geological Survey, Reston, VA.
Petrochemical Production
ACC (2006) Guide to the Business of Chemistry 2005. American Chemistry Council. Arlington, VA.
ACC (2005) Guide to the Business of Chemistry 2005. American Chemistry Council. Arlington, VA.
ACC (2003) Guide to the Business of Chemistry 2003. American Chemistry Council. Arlington, VA.
ACC (2002) Guide to the Business of Chemistry 2002. 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.
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.
European IPPC Bureau (2004) Draft Reference Document on Best Available Techniques in the Large Volumen
Inorganic Chemicals—Solid and Others Industry. European Commission. Page 224, Table 4.21. August 2004.
IPCC/UNEP/OECD/IEA (1997) Revised 19961PCC Guidelines for National Greenhouse Gas Inventories, Paris:
Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
Co-Operation and Development, International Energy Agency.
Johnson, G. L. (2006) Personal communication between Erin Fraser of ICF International and Greg Johnson of
Liskow & Lewis, on behalf of the International Carbon Black Association (ICBA). October, 2006.
Johnson, G. L. (2005) Personal communication between Erin Fraser of ICF International and Greg Johnson of
Liskow & Lewis, on behalf of the International Carbon Black Association (ICBA). October, 2005.
References 11-31
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Public Review Draft
Johnson, G. L. (2003) Personal communication between Caren Mintz of ICF International and Greg Johnson of
Liskow & Lewis, on behalf of the International Carbon Black Association (ICBA). November, 2003.
Othmer, K. (1992) Carbon (Carbon Black). Volume 4. Page 1045.
Srivastava, Manoj, I.D. Singh, and Himmat Singh (1999) Structural Characterization of Petroleum Based
Feedstocks for Carbon Black Production. Petroleum Science and Technology. 17(1&2), 67-80, Table-1.
The Innovation Group (2004) Carbon Black Plant Capacity. .
U.S. Census Bureau (2006) U.S International Trade Commission (USITC) Trade DataWeb,
. Accessed Fall 2006.
U.S. Census Bureau (2004) 2002 Economic Census: Manufacturing—Industry Series: Carbon Black
Manufacturing. Department of Commerce, Washington, DC. EC02-311-325182. September 2004.
U.S. Census Bureau (1999) 1997Economic Census: Manufacturing—Industry Series: Carbon Black
Manufacturing. Department of Commerce, Washington, DC. EC97M-3251F. August 1999.
Silicon Carbide Production
Corathers, L. (2006) Personal communication between Erin Fraser of ICF International and Lisa Corathers,
Commodity Specialist, U.S. Geological Survey, October.
IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
Published: IGES, Japan.
U.S. Census Bureau (2006) U.S International Trade Commission (USITC) Trade DataWeb,
. Accessed Fall 2006.
U.S. Census Bureau (2005) U.S International Trade Commission (USITC) Trade DataWeb,
. Accessed fall 2005.
USGS (2006) Minerals Yearbook: Manufactured Abrasives Annual Report 2004. U.S. Geological Survey, Reston,
VA.
USGS (2005a) Minerals Yearbook: Manufactured Abrasives Annual Report 2004. U.S. Geological Survey, Reston,
VA.
USGS (2005b) Minerals Yearbook: Silicon Annual Report 2004. U.S. Geological Survey, Reston, VA.
USGS (2004a) Minerals Yearbook: Manufactured Abrasives Annual Report 2003. U.S. Geological Survey, Reston,
VA.
USGS (2004b) Minerals Yearbook: Silicon Annual Report 2003. U.S. Geological Survey, Reston, VA.
USGS (2003a) Minerals Yearbook: Manufactured Abrasives Annual Report 2002. U.S. Geological Survey, Reston,
VA.
USGS (2003b) Minerals Yearbook: Silicon Annual Report 2002. U.S. Geological Survey, Reston, VA.
USGS (2002a) Minerals Yearbook: Manufactured Abrasives Annual Report 2001. U.S. Geological Survey, Reston,
11-32 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
Public Review Draft
VA.
USGS (2002b) Minerals Yearbook: Silicon Annual Report 2001. U.S. Geological Survey, Reston, VA.
USGS (2001a) Minerals Yearbook: Manufactured Abrasives Annual Report 2000. U.S. Geological Survey, Reston,
VA.
USGS (2001b) Minerals Yearbook: Silicon Annual Report 2000. U.S. Geological Survey, Reston, VA.
USGS (2000a) Minerals Yearbook: Manufactured Abrasives Annual Report 1999. U.S. Geological Survey, Reston,
VA.
USGS (2000b) Minerals Yearbook: Silicon Annual Report 1999. U.S. Geological Survey, Reston, VA.
USGS (1999a) Minerals Yearbook: Manufactured Abrasives Annual Report 1998. U.S. Geological Survey, Reston,
VA.
USGS (1999b) Minerals Yearbook: Silicon Annual Report 1998. U.S. Geological Survey, Reston, VA.
USGS (1998a) Minerals Yearbook: Manufactured Abrasives Annual Report 1997. U.S. Geological Survey, Reston,
VA.
USGS (1998b) Minerals Yearbook: Silicon Annual Report 1997. U.S. Geological Survey, Reston, VA.
USGS (1997a) Minerals Yearbook: Manufactured Abrasives Annual Report 1996. U.S. Geological Survey, Reston,
VA.
USGS (1997b) Minerals Yearbook: Silicon Annual Report 1996. U.S. Geological Survey, Reston, VA.
USGS (1996a) Minerals Yearbook: Manufactured Abrasives Annual Report 1995. U.S. Geological Survey, Reston,
VA.
USGS (1996b) Minerals Yearbook: Silicon Annual Report 1995. U.S. Geological Survey, Reston, VA.
USGS (1995a) Minerals Yearbook: Manufactured Abrasives Annual Report 1994. U.S. Geological Survey, Reston,
VA.
USGS (1995b) Minerals Yearbook: Silicon Annual Report 1994. U.S. Geological Survey, Reston, VA.
USGS (1994a) Minerals Yearbook: Manufactured Abrasives Annual Report 1993. U.S. Geological Survey, Reston,
VA.
USGS (1994b) Minerals Yearbook: Silicon Annual Report 1993. U.S. Geological Survey, Reston, VA.
USGS (1993a) Minerals Yearbook: Manufactured Abrasives Annual Report 1992. U.S. Geological Survey, Reston,
VA.
USGS (1993b) Minerals Yearbook: Silicon Annual Report 1992. U.S. Geological Survey, Reston, VA.
USGS (1992a) Minerals Yearbook: Manufactured Abrasives Annual Report 1991. U.S. Geological Survey, Reston,
VA.
USGS (1992b) Minerals Yearbook: Silicon Annual Report 1991. U.S. Geological Survey, Reston, VA.
References 11-33
-------
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Public Review Draft
USGS (1991a) Minerals Yearbook: Manufactured Abrasives Annual Report 1990. U.S. Geological Survey, Reston,
VA.
USGS (1991b) Minerals Yearbook: Silicon Annual Report 1990. U.S. Geological Survey, Reston, VA.
Nitric Acid Production
C&EN (2006) "Facts and Figures in the Chemical Industry." Chemical and Engineering News, July 10, 2006, pg
64.
C&EN (2005) "Facts and Figures in the Chemical Industry." Chemical and Engineering News, July 11, 2005, pg
72.
C&EN (2004) "Facts and Figures in the Chemical Industry." Chemical and Engineering News, July 5, 2004, pg 54.
C&EN (2003) "Facts and Figures in the Chemical Industry." Chemical and Engineering News, July 27, 2003, pg
56.
C&EN (2002) "Facts and Figures in the Chemical Industry." Chemical and Engineering News, June 24, 2002, pg
62.
C&EN (2001) "Facts and Figures in the Chemical Industry." Chemical and Engineering News, June 25, 2001, pg
46.
Choe, J.S., P.J. Cook, and F.P. Petrocelli (1993) "Developing N20 Abatement Technology for the Nitric Acid
Industry." Prepared for presentation at the 1993 ANPSG Conference. Air Products and Chemicals, Inc.,
Allentown, PA.
IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
XVI/Doc. 10 (1.IV.2000). May. Pg3.35.
EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42, U.S. Environmental Protection Agency, Office
of Air Quality Planning and Standards, Research Triangle Park, NC, October.
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 and 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 and Engineering News, 70(15): 17.
April 13, 1992.
Childs, D. (2003). Personal communication between Dave Childs of DuPont, USA and Duncan Rotherham of ICF
Consulting, USA. August 7, 2003.
11-34 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Childs, D. (2002). Personal communication between Dave Childs of DuPont, USA and Laxmi Palreddy of ICF,
2 Consulting, USA. August 8, 2002.
3 CMR (2001) "Chemical Profile: Adipic Acid." Chemical Market Reporter, July 16, 2001.
4 CMR (1998) "Chemical Profile: Adipic Acid." Chemical Market Reporter, June 15, 1998.
5 CW (2005) "Product Focus: Adipic Acid." Chemical Week, May, 4, 2005.
6 CW (1999) "Product Focus: Adipic Acid/Adiponitrile." Chemical Week, March 10, 1999, pg. 31.
7 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
8 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
9 XVI/Doc. 10 (1.IV.2000). May. Pg3.34.
10 Reimer, R. (1999). Personal communication between Ron Reimer of DuPont, USA and Heike Mainhardt of ICF,
11 Consulting. May 19, 1999.
12 Thiemens, M.H., and W.C. Trogler (1991) "Nylon production; an unknown source of atmospheric nitrous oxide."
13 Science: 251:932-934.
14 Subsitution of Ozone Depleting Substances
15 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, Paris:
16 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
17 Co-Operation and Development, International Energy Agency.
18 HCFC-22 Production
19 ARAP (2006) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
20 Atmospheric Policy, to Sally Rand, EPA. July 11, 2006.
21 ARAP (2005) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
22 Atmospheric Policy, to Deborah Ottinger, EPA. August 9, 2005.
23 ARAP (2004) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
24 Atmospheric Policy, to Deborah Ottinger, EPA. June 3, 2004.
25 ARAP (2003) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
26 Atmospheric Policy, to Sally Rand, EPA. August 18, 2003.
27 ARAP (2002) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
28 Atmospheric Policy, to Deborah Ottinger, EPA. August 7, 2002.
29 ARAP (2001) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
30 Atmospheric Policy, to Deborah Ottinger, EPA. August 6, 2001.
31 ARAP (2000) Electronic mail communication from Dave Stirpe, Executive Director, Alliance for Responsible
32 Atmospheric Policy, to Sally Rand, EPA. August 13, 2000.
33 ARAP (1999) Facsimile from Dave Stirpe, Executive Director, Alliance for Responsible Atmospheric Policy, to
34 Deborah Ottinger Schaefer, EPA. September 23, 1999.
35 ARAP (1997) Letter from Dave Stirpe, Director, Alliance for Responsible Atmospheric Policy, to Elizabeth
References 11-35
-------
Public Review Draft
1 Dutrow, EPA. December 23, 1997.
2 Rand, S., M. Branscome, and D. Ottinger (1999) "Opportunities for the Reduction of HFC-23 Emissions from the
3 Production of HCFC-22." In: Proceedings from the Joint IPCC/TEAP Expert Meeting On Options for the
4 Limitation of Emissions of HFCs and PFCs. Petten, the Netherlands, 26-28 May 1999.
5 RTI (1997) "Verification of Emission Estimates of HFC-23 from the Production of HCFC-22: Emissions from
6 1990 through 1996." Report prepared by Research Triangle Institute for the Cadmus Group. November 25, 1997;
7 revised February 16, 1998.
8 Electrical Transmission and Distribution
9 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
10 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
11 XVI/Doc. 10 (1.IV.2000). May.
12 IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
13 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
14 Published: IGES, Japan.
15 Maiss, M. and C.A.M. Brenninkmeijer (2000) "A reversed trend in emissions of SF6 to the atmosphere?" Non-C02
16 Greenhouse Gases: Scientific Understanding, Control, and Implementation, Proceedings of the Second
17 International Symposium, Noordwijkerhout, The Netherlands, 8-10 September 1999, Kluwer Academic Publishers,
18 2000, p. 199.
19 O'Connell, P., F. Heil, J. Henriot, G. Mauthe, H. Morrison, L. Neimeyer, M. Pittroff, R. Probst, J.P. Tailebois
20 (2002) SF6 in the Electric Industry, Status 2000, Cigre, February 2002.
21 RAND (2004) Katie D. Smythe, RAND Environmental Science and Policy Center, "Trends in SF6 Sales and End-
22 Use Applications: 1961-2003," International Conference on SF6 and the Environment: Emission Reduction
23 Strategies. Scottsdale, AZ, December 1-3, 2004.
24 UDI (2004) 2004 UDI Directory of Electric Power Producers and Distributors, 112th Edition, Platts.
25 UDI (2001) 2001 UDI Directory of Electric Power Producers and Distributors, 109th Edition, Platts.
26 Semiconductor Manufacture
27 Burton, C.S., and R, Beizaie (2001) "EPA's PFC Emissions Model (PEVM) v. 2.14: Description and
28 Documentation" prepared for Office of Global Programs, U. S. Environmental Protection Agency, Washington, DC.
29 20001 November 2001.
30 Burton, C.S., and H. Mallya (2005) "PFC Reduction/Climate Partnership for the Semiconductor Industry: Trends in
31 Emissions and Documentation," Draft Report, prepared for Office of Atmospheric Programs, U. S. Environmental
32 Protection Agency, Washington, DC. 20001. August 2005.
33 Citigroup Smith Barney (2005) Global Supply/Demand Model for Semiconductors. March 2005.
34 ITRS (2005) International Technology Roadmap for Semiconductors: 2004 Update. January 2005. This and earlier
35 editions and updates are available at Information about the number of interconnect layers for
36 years 1990 - 2010 is contained in Burton and Beizaie, 2001. PEVM is updated using new editions and updates of
37 the ITRS, which are published annually.
38 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
11-36 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
2 XVI/Doc. 10 (1.IV.2000). May.
3 Semiconductor Equipment and Materials Industry (2006) World Fab Watch, April 2006 Edition, April 2006.
4 Strategic Marketing Associates (2003) Personal communication September 5, 2003 between C. S. Burton and
5 George Burns, President of Strategic Marketing Associates, PO Box 1217, Santa Cruz, CA 95061.
6 VLSI Research, Inc. (2005) Document 327202, V5.061—Worldwide Silicon Demand by Wafer Size, by Linewidth
7 and by Device Type. June 2005. Available online at .
8 VSLI Research, Inc. (2003) Personal communication September 5, 2003 between C. S. Burton and Marta
9 Hernandez, Analyst at VLSI Research Inc., 1754 Technology Drive, Suite 117, San Jose, CA 95110.
10 Aluminum Production
11 Kantamaneni R. and D. Pape (2001) "2000 Aluminum Inventory—Uncertainty Analysis", Under EPA Contract No.
12 68-W6-0029, Task Order 408. Memorandum to EPA from ICF Consulting. October, 18, 2001.
13 Gariepy, B. and G. Dube (1992) "Treating Aluminum with Chlorine." U.S. Patent 5,145,514. Issued September 8,
14 1992.
15 IAI (2003) Aluminum Sector Greenhouse Gas Protocol: Greenhouse Gas Emissions Monitoring and Reporting by
16 the Aluminum Industry, International Aluminum Institute, May 2003. Available at .
18 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
19 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
20 Published: IGES, Japan.
21 IPCC (2001) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
22 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
23 XVI/Doc. 10 (1.IV.2000), May 2000.
24 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)
25 "Atmospheric Sulfur Hexafluoride: Sources, Sinks, and Greenhouse Warming." Journal of Geophysical Research,
26 98, 10499-10507.
27 MacNeal, J., T. Rack, and R. Corns (1990) "Process for Degassing Aluminum Melts with Sulfur Hexafluoride."
28 U.S. Patent 4,959,101. Issued September 25, 1990.
29 Ten Eyck, N. and M. Lukens (1996) "Process for Treating Molten Aluminum with Chlorine Gas and Sulfur
30 Hexafluoride to Remove Impurities." U.S. Patent 5,536,296. Issued July 16, 1996.
31
USAA (2006) Primary Aluminum Statistics. U.S. Aluminum Association, Washington,
DC.
January
2006
32
USAA (2005) Primary Aluminum Statistics. U.S. Aluminum Association, Washington,
DC.
January
2005
33
USAA (2004) Primary Aluminum Statistics. U.S. Aluminum Association, Washington,
DC.
January
2004
34 USGS (2006) Mineral Commodity Summaries. U.S. Geological Survey, Reston, VA.
35 USGS (2002) Mineral Yearbook: Aluminum Annual Report 2001. U.S. Geological Survey, Reston, VA.
References 11-37
-------
Public Review Draft
1
USGS
(2001)
Minerals
Yearbook:
Aluminum Annual Report 2000.
U.S.
Geological
Survey, Reston,
VA.
2
USGS
(2000)
Minerals
Yearbook:
Aluminum Annual Report 1999.
U.S.
Geological
Survey, Reston,
VA.
3
USGS
(1998)
Minerals
Yearbook:
Aluminum Annual Report 1997.
U.S.
Geological
Survey, Reston,
VA.
4
USGS
(1995)
Minerals
Yearbook:
Aluminum Annual Report 1994.
U.S.
Geological
Survey, Reston,
VA.
5 Victor, D.G. and G.J. MacDonald (1998) "A Model for Estimating Future Emissions of Sulfur Hexafluoride and
6 Perfluorcarbons." Interim Report for the International Institute for Applied Systems Analysis (IIASA), July, 1998.
7 Downloaded from the IIASA website , May 23, 2000.
8 Zurecki, Z. (1996) "Effect of Atmosphere Composition on Homogenizing Al-Mg and Al-Li Alloys." Gas
9 Interactions in Nonferrous Metals Processing—Proceedings of the 1996 125th The Minerals, Metals & Materials
10 Society (TMS) Annual Meeting (Anaheim, CA, USA), pp. 77-93.
11 Magnesium Production and Processing
12 Bartos S., J. Marks, R. Kantamaneni, C. Laush (2003) "Measured SF6 Emissions from Magnesium Die Casting
13 Operations," Magnesium Technology, Magnesium Technology 2003, Proceedings of The Minerals, Metals &
14 Materials Society (TMS) Conference, March 2003.
15 EPA (2004) "Characterization of Cover Gas Emissions from U.S. Magnesium Die Casting", Environmental
16 Protection Agency, Office of Air and Radiation. EPA430-R-04-004.
17 Gjestland, H. and D. Magers (1996) "Practical Usage of Sulphur [Sulfur] Hexafluoride for Melt Protection in the
18 Magnesium Die Casting Industry," #13,1996Annual Conference Proceedings, Ube City, Japan, International
19 Magnesium Association.
20 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
21 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
22 XVI/Doc. 10 (1.IV.2000). May.
23 RAND (2002) Katie D. Smythe, RAND Environmental Science and Policy Center, "Production and Distribution of
24 SF6 by End-Use Application," International Conference on SF6 and the Environment: Emission Reduction
25 Strategies. San Diego, CA, November 21-22.
26 USGS (2002) Minerals Yearbook: Magnesium Annual Report 2001. U.S. Geological Survey, Reston, VA.
27 Available online at .
28 USGS (2003) Minerals Yearbook: Magnesium Annual Report 2002. U.S. Geological Survey, Reston, VA.
29 Available online at .
30 USGS (2005a) Minerals Yearbook: Magnesium Annual Report 2004. U.S. Geological Survey, Reston, VA.
31 Available online at .
32 USGS (2005b) Personal communication between Jeremy Scharfenberg of ICF International and Deborah A. Kramer
33 of the U.S. Geological Survey, Reston, VA. September, 2005.
34 USGS (2006) Minerals Yearbook: Magnesium Annual Report 2005. U.S. Geological Survey, Reston, VA.
35 Available online at .
36 Industrial Sources of Indirect Greenhouse Gases
11-38 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 EPA (2006) Air Emissions Trends - Continued Progress Through 2005. U.S. Environmental Protection Agency,
2 Washington DC. December 19, 2006. < http://www.epa.gov/air/airtrends/index.html>.
3 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
4 OAQPS. December 22, 2003.
5 EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42, U.S. Environmental Protection Agency, Office
6 of Air Quality Planning and Standards, Research Triangle Park, NC, October.
7 Solvent and Other Product Use
8 Nitrous Oxide Product Usage
9 CGA (2003) "CGA Nitrous Oxide Abuse Hotline." Compressed Gas Association. November 3, 2003. Available
10 online at < http://www.cganet.com/n2o/factsht.asp>.
11 CGA (2002) "CGA/NWSA Nitrous Oxide Fact Sheet." Compressed Gas Association. March 25, 2002.
12 Heydorn, B. (1997) "Nitrous Oxide—North America." Chemical Economics Handbook, SRI Consulting. May
13 1997.
14 Kirt-Otthmer (1990) "Anesthetics." Kirk-Otthmer Encyclopedia of Chemical Technology, Volume 2, pp. 781-782.
15 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
16 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
17 XVI/Doc. 10 (1.IV.2000). May.
18 Tupman, M. (2002) Personal communication between Martin Tupman of Airgas Nitrous Oxide and Laxmi Palreddy
19 of ICF Consulting, USA. July 3, 2002.
20 Tupman, M. (2003) Personal communication between Martin Tupman of Airgas Nitrous Oxide and Daniel
21 Lieberman of ICF Consulting, USA. August 8, 2003.
22 Solvent Use
23 EPA (2006) Air Emissions Trends - Continued Progress Through 2005. U.S. Environmental Protection Agency,
24 Washington DC. December 19, 2006. < http://www.epa.gov/air/airtrends/index.html>.
25 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
26 OAQPS. December 22, 2003.
27 EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42, U.S. Environmental Protection Agency, Office
28 of Air Quality Planning and Standards, Research Triangle Park, NC, October.
29 Agriculture
30 Enteric Fermentation
31 Crutzen, P. J., I. Aselmann, and W. Seiler (1986). "Methane Production by Domestic Animals, Wild Ruminants,
32 Other Herbivores, Fauna, and Humans." Tellus 38B:271-284.
33 Donovan, K. (1999) Personal Communication between Kacey Donovan of University of California, Davis and Staff
34 at ICF Consulting.
References 11-39
-------
Public Review Draft
1 Donovan, K. and L. Baldwin (1999) Results of the AAMOLLY model runs for the Enteric Fermentation Model.
2 University of California, Davis.
3 EPA (2000) Draft Enteric Fermentation Model Documentation. U.S. Environmental Protection Agency, Office of
4 Air and Radiation, Washington, DC. June 13.
5 EPA (1993) Anthropogenic Methane Emissions in the United States: Estimates for 1990, Report to Congress.
6 Office of Air and Radiation, U.S. Environmental Protection Agency, Washington, DC.
7 FAO (2006) FAOSTAT Statistical Database. Food and Agriculture Organization of the United Nations. Available
8 online at .
9 Feedstuffs (1998) "Nutrient requirements for pregnant replacement heifers." Feedstuff's, Reference Issue, p. 50.
10 ICF (2006). Cattle Enteric Fermentation Model: Model Documentation. Prepared by ICF International for the
11 Environmental Protection Agency, June 2006.
12 ICF (2003). Uncertainty Analysis of2001 Inventory Estimates of Methane Emissions from Livestock Enteric
13 Fermentation in the U.S. Memo from ICF International to the Environmental Protection Agency, May 2003.
14 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
15 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
16 Published: IGES, Japan.
17 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
18 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
19 XVI/Doc. 10 (1.IV.2000). May.
20 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, Paris:
21 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
22 Cooperation and Development, International Energy Agency.
23 Johnson, D. (2002) Personal Communication between Don Johnson of Colorado State University, Fort Collins, and
24 ICF Consulting.
25 Johnson, D. (2000) Enteric Fermentation Model Progress and Changes. Comments prepared by Don Johnson of
26 Colorado State University, Fort Collins, for ICF Consulting.
27 Johnson, D. (1999) Personal Communication between Don Johnson of Colorado State University, Fort Collins, and
28 David Conneely of ICF Consulting.
29 Lange, J. (2000) Telephone conversation between Lee-Ann Tracy of ERG and John Lange, Agricultural Statistician,
30 U. S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC, 8 May.
31 NRC (1999) 1996 Beef NRC, Appendix Table 22. National Research Council.
32 NRC (2000) Nutrient Requirements of Beef Cattle: Seventh Revised Edition: Update 2000, Table 11-1, Appendix
33 Table 1. National Research Council.
34 USDA (2006a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
35 August 2, 2006. Data also available from .
36 USDA (2006b) Livestock Slaughter, U.S. Department of Agriculture, National Agriculture Statistics Service,
37 Washington, DC. August 2, 2006. Data also available from
11-40 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 USDA (2006c) Milk Production, U.S. Department of Agriculture, National Agriculture Statistics Service,
2 Washington, DC. August 2, 2006. Data also available from .
3 USDA (2006d) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
4 Washington, DC. August 2, 2006. Data also available from .
5 USDA (2006e) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
6 Washington, DC. August 2, 2006. Data also available from .
7 USDA (2006f) Hogs and Pigs, U.S. Department of Agriculture, National Agriculture Statistics Service,
8 Washington, DC. August 2, 2006. Data also available from < www.nass.usda.gov/QuickStats/>.
9 USDA (2005a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
10 August 8, 2005. Data also available from .
11 USDA (2005b) Livestock Slaughter, U.S. Department of Agriculture, National Agriculture Statistics Service,
12 Washington, DC. August 8, 2005. Data also available from .
13 USDA (2005c) Milk Production, U.S. Department of Agriculture, National Agriculture Statistics Service,
14 Washington, DC. August 8, 2005. Data also available from .
15 USDA (2005d) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
16 Washington, DC. August 8, 2005. Data also available from .
17 USDA (2005e) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
18 Washington, DC. August 8, 2005. Data also available from .
19 USDA (2005f) Hogs and Pigs, U.S. Department of Agriculture, National Agriculture Statistics Service,
20 Washington, DC. August 8, 2005. Data also available from .
21 USDA (2005i) Census of Agriculture, U.S. Department of Agriculture, National Agriculture Statistics Service,
22 Washington, DC. Data for 1992, 1997, and 2002 accessed from in June 2005.
23 USDA (2004a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
24 July 1,2004. Data also available from .
25 USDA (2004b) Hogs and Pigs, U.S. Department of Agriculture, National Agriculture Statistics Service,
26 Washington, DC. June 27, 2003. Data also available from .
27 USDA (2004c) Livestock Slaughter, U.S. Department of Agriculture, National Agriculture Statistics Service,
28 Washington, DC. July 6-7, 2004. Data also available from .
29 USDA (2004d) Milk Production, U.S. Department of Agriculture, National Agriculture Statistics Service,
30 Washington, DC. July 1, 2004. Data also available from .
31 USDA (2004e) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
32 Washington, DC. January 31, 2003. Data also available from .
33 USDA (2004f) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
34 Washington, DC. July 1, 2004. Data also available from .
35 USDA (2004g) Chicken and Eggs—Final Estimates 1998-2003, U.S. Department of Agriculture, National
36 Agriculture Statistics Service, Washington, DC. April. Data also available from
37 .
References 11-41
-------
Public Review Draft
1 USDA (2004h) Poultry Production and Value—Final Estimates 1998-2002, U.S. Department of Agriculture,
2 National Agriculture Statistics Service, Washington, DC. April. Data also available from
3 .
4 USDA (2003a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
5 January 31, 2003. Data also available from .
6 USDA (2003b) Hogs and Pigs, U.S. Department of Agriculture, National Agriculture Statistics Service,
7 Washington, DC. June 27, 2003. Data also available from .
8 USDA (2003c) Livestock Slaughter, U.S. Department of Agriculture, National Agriculture Statistics Service,
9 Washington, DC. January 24 - June 20, 2003. Data also available from .
10 USDA (2003d). Milk Production, U.S. Department of Agriculture, National Agriculture Statistics Service,
11 Washington, DC. February 14, 2003. Data also available from .
12 USDA (2003e) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
13 Washington, DC. January 31, 2003. Data also available from .
14 USDA (2003f) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
15 Washington, DC. February 14, 2003. Data also available from .
16 USDA (2002a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
17 February 1,2002. Data also available from .
18 USDA (2002b) Hogs and Pigs, U.S. Department of Agriculture, National Agriculture Statistics Service,
19 Washington, DC. June 28, 2002. Data also available from .
20 USDA (2002c) Livestock Slaughter, U.S. Department of Agriculture, National Agriculture Statistics Service,
21 Washington, DC. January 25 - June 21, 2002. Data also available from .
22 USDA (2002d) Milk Production, U.S. Department of Agriculture, National Agriculture Statistics Service,
23 Washington, DC. February 15, 2002. Data also available from .
24 USDA (2002e) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
25 Washington, DC. February 1, 2002. Data also available from .
26 USDA (2002f) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
27 Washington, DC. February 15, 2002. Data also available from .
28 USDA (2001a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
29 January 26, 2001. Data also available from .
30 USDA (2001b) Hogs and Pigs, U.S. Department of Agriculture, National Agriculture Statistics Service,
31 Washington, DC. December 28, 2001. Data also available from .
32 USDA (2001c) Livestock Slaughter, U.S. Department of Agriculture, National Agriculture Statistics Service,
33 Washington, DC. January 19-December21, 2001. Data also available from.
34 USDA (2001d) Milk Production, U.S. Department of Agriculture, National Agriculture Statistics Service,
35 Washington, DC. February 16, 2001. Data also available from .
36 USDA (2001e) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
37 Washington, DC. January 26, 2001. Data also available from .
11-42 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 USDA (2001f) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
2 Washington, DC. February 16, 2001. Data also available from .
3 USDA (2000a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
4 January 28, 2000. Data also available from < www.nass.usda.gov/QuickStats/>.
5 USDA (2000b) Chicken and Eggs—Final Estimates 1988-1993, U.S. Department of Agriculture, National
6 Agriculture Statistics Service, Washington, DC. Downloaded from , May 3, 2000.
8 USDA (2000c) Livestock Slaughter, U.S. Department of Agriculture, National Agriculture Statistics Service,
9 Washington, DC. January 21-December22, 2000. Data also available from.
10 USDA (2000d) Milk Production, U.S. Department of Agriculture, National Agriculture Statistics Service,
11 Washington, DC. February 16, 2000. Data also available from .
12 USDA (2000e) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
13 Washington, DC. February 18, 2000. Data also available from .
14 USDA (2000f) Chicken and Eggs—Final Estimates 1988-1993, U.S. Department of Agriculture, National
15 Agriculture Statistics Service, Washington, DC. Downloaded from , May 3, 2000.
17 USDA (1999a) Cattle, Final Estimates 1994-1998, U.S. Department of Agriculture, National Agriculture Statistics
18 Service, Washington DC. 1999. Data also available from .
19 USDA (1999b) Poultry Production and Value—Final Estimates 1994-97, U.S. Department of Agriculture, National
20 Agriculture Statistics Service, Washington, DC. March. Data also available from
21 .
22 USDA (1999c) Livestock Slaughter, U.S. Department of Agriculture, National Agriculture Statistics Service,
23 Washington, DC. January 22-December23, 1999. Data also available from.
24 USDA (1999d )Milk Cows and Milk Production—Final Estimates 1993-1997, U.S. Department of Agriculture,
25 National Agriculture Statistics Service, Washington, DC. January 1999. Data also available from
26 .
27 USDA (1999e) Sheep and Goats, Final Estimates 1994-98, U.S. Department of Agriculture, National Agriculture
28 Statistics Service, Washington, DC, 1999. Data also available from .
29 USDA (1999f) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
30 Washington, DC. Data also available from < www.nass.usda.gov/QuickStats/>.
31 USDA (1999g) Miscellaneous Livestock and Animal Specialties Inventory and Sales: 1997 and 1992, Table 25,
32 U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC. Accessed May 2000
33 .
34 USDA (1998a) Hogs and Pigs, Final Estimates 1993-97, U.S. Department of Agriculture, National Agriculture
35 Statistics Service, Washington, DC. Data also available from .
36 USDA (1998b) Chicken and Eggs—Final Estimates 1994-97, U.S. Department of Agriculture, National Agriculture
37 Statistics Service, Washington, DC. December. Data also available from
38 .
References 11-43
-------
Public Review Draft
1 USDA (1996) Beef Cow/Calf Health and Productivity Audit (CHAPA): Forage Analyses from Cow/Calf Herds in
2 18 States, National Animal Health Monitoring System, Washington DC. March 1996. Data also available from
3 .
4 USDA (1995a) Cattle, Final Estimates 1989-93, U.S. Department of Agriculture, National Agriculture Statistics
5 Service, Washington, DC. January. Data also available from .
6 USDA (1995b) Dairy Outlook, U.S. Department of Agriculture, National Agriculture Statistics Service,
7 Washington, DC. February 27. Data also available from .
8 USDA (1995c) Poultry Production and Value—Final Estimates 1988-1993, U.S. Department of Agriculture,
9 National Agriculture Statistics Service, Washington, DC. January. Data also available from
10 .
11 USDA (1994a) Hogs and Pigs, Final Estimates 1988-92, U.S. Department of Agriculture, National Agriculture
12 Statistics Service, Washington, DC. December. Data also available from .
13 USDA (1994b) Sheep and Goats, Final Estimates 1988-93, U.S. Department of Agriculture, National Agriculture
14 Statistics Service, Washington, DC. January 31. Data also available from .
15 USD A: APHIS: VS (2002) Reference of2002 Dairy Management Practices, National Animal Health Monitoring
16 System, Fort Collins, CO. 2002. Data also available from .
17 USDA:APHIS:VS (1998) Beef '97, National Animal Health Monitoring System, Fort Collins, CO. 1998. Data also
18 available from .
19 USDA:APHIS:VS (1996) Reference of1996 Dairy Management Practices, National Animal Health Monitoring
20 System, Fort Collins, CO. 1996. Data also available from .
21 U SD A: APHIS: VS (1994) Beef Cow/Calf Health and Productivity Audit. National Animal Health Monitoring
22 System, Fort Collins, CO. Data also available from .
23 USDA:APHIS:VS (1993) Beef Cow/Calf Health and Productivity Audit. National Animal Health Monitoring
24 System, Fort Collins, CO. August. Data also available from .
25 Western Dairyman (1998) "How Big Should Heifers Be at Calving?" The Western Dairyman, Sept. 1998, p. 12.
26 Manure Management
27 Anderson, S. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Steve Anderson, Agricultural
28 Statistician, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC. 31 May.
29 ASAE (1999) ASAE Standards 1999, 46th Edition, American Society of Agricultural Engineers, St. Joseph, MI.
30 Bryant, M.P., V.H. Varel, R.A. Frobish, and H.R. Isaacson (1976) In: H.G. Schlegel (ed.). Seminar on Microbial
31 Energy Conversion. E. Goltz KG. Gottingen, Germany.
32 Deal, P. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Peter B. Deal, Rangeland
33 Management Specialist, Florida Natural Resource Conservation Service, 21 June.
34 EPA (2006) AgSTAR Digest, U.S. Environmental Protection Agency, Office of Air and Radiation. Winter.
35 Accessed July 2006.
36 EPA (2004) National Emission Inventory—Ammonia Emissions from Animal Husbandry Operations. Office of Air
11-44 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 and Radiation, U.S. Environmental Protection Agency. Available online at
2 .
3 EPA (2003a) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2001. EPA 430-R-03-004. U.S.
4 Environmental Protection Agency. Washington, DC. 15 April.
5 EPA (2003b) AgSTAR Digest, U.S. Environmental Protection Agency, Office of Air and Radiation. Winter.
6 Accessed July 2006.
7 EPA (2002a) Development Document for the Final Revisions to the National Pollutant Discharge Elimination
8 System (NPDES) Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations (CAFOS).
9 EPA-821-R-03-001. December.
10 EPA (2002b) Cost Methodology for the Final Revisions to the National Pollutant Discharge Elimination System
11 Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations. EPA-821-R-03-004.
12 December.
13 EPA (2000) AgSTAR Digest, U.S. Environmental Protection Agency, Office of Air and Radiation. Spring.
14 EPA (1992) Global Methane Emissions from Livestock and Poultry Manure, U.S. Environmental Protection
15 Agency, Office of Air and Radiation, February.
16 ERG (2003) Methodology for Estimating Uncertainty for Manure Management Greenhouse Gas Inventory.
17 Contract No. GS-10F-0036, Task Order 005. Memorandum to EPA from ERG. September 26, 2003.
18 ERG (2001) Summary of development of MDP Factor for methane conversion factor calculations. September
19 2001.
20 ERG (2000a) Calculations: Percent Distribution of Manure for Waste Management Systems. August 2000.
21 ERG (2000b) Discussion of Methodology for Estimating Animal Waste Characteristics (Summary of B0 Literature
22 Review). June 2000.
23 FAO (2006) Yearly U.S. total horse population data from the Food and Agriculture Organization of the United
24 Nations database. Available online at Accessed May 2006.
25 Garrett, W.N. and Johnson, D.E. (1983) Nutritional energetics of ruminants. Champaign, 111. American Society of
26 Animal Science. Journal of animal science. July 1983. v. 57 (suppl.2) p. 478-497.
27 Groffman, P.M., R. Brumme, K. Butterbach-Bahl, K.E. Dobbie, A.R. Mosier, D. Ojima, H. Papen, W.J. Parton,
28 K. A. Smith, and C. Wagner-Riddle. (2000) "Evaluating annual nitrous oxide fluxes at the ecosystem scale." Global
29 Biogeochemcial Cycles, 14(4): 1061-1070.
30 Hashimoto, A.G. (1984) "Methane from Swine Manure: Effect of Temperature and Influent Substrate Composition
31 on Kinetic Parameter (k)." Agricultural Wastes. 9:299-308.
32 Hashimoto, A.G., V.H. Varel, and Y.R. Chen (1981) "Ultimate Methane Yield from Beef Cattle Manure; Effect of
33 Temperature, Ration Constituents, Antibiotics and Manure Age." Agricultural Wastes. 3:241-256.
34 Hill, D.T. (1984) "Methane Productivity of the Major Animal Types." Transactions of theASAE. 27(2):530-540.
35 Hill, D.T. (1982) "Design of Digestion Systems for Maximum Methane Production." Transactions of the ASAE.
36 25(l):226-230.
References 11-45
-------
Public Review Draft
1 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
2 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
3 Published: IGES, Japan.
4 Johnson, D. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Dan Johnson, State Water
5 Management Engineer, California Natural Resource Conservation Service, 23 June.
6 Lange, J. (2000) Telephone conversation between Lee-Ann Tracy of ERG and John Lange, Agricultural Statistician,
7 U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC. 8 May.
8 Miller, P. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Paul Miller, Iowa Natural Resource
9 Conservation Service, June 12, 2000.
10 Milton, B. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Bob Milton, Chief of Livestock
11 Branch, U.S. Department of Agriculture, National Agriculture Statistics Service, May 1, 2000.
12 Morris, G.R. (1976) Anaerobic Fermentation of Animal Wastes: A Kinetic and Empirical Design Fermentation.
13 M.S. Thesis. Cornell University.
14 NOAA (2005) National Oceanic and Atmospheric Administration (NOAA), National Climate Data Center (NCDC)
15 Downloaded data in June 2005 from (for all states except Alaska and
16 Hawaii); downloaded data in June 2005 from (for Alaska and
17 Hawaii).
18 Pederson, L. and D. Pape. (2006) 1990-2005 Volatile Solids and Nitrogen Excretion Rates, Deliverable Under EPA
19 Contract GS-10F-0124J, Task Order 056-01. Memorandum to EPA from ICF Consulting. August 5, 2006.
20 Poe, G., N. Bills, B. Bellows, P. Crosscombe, R. Koelsch, M. Kreher, and P. Wright (1999) Staff Paper
21 Documenting the Status of Dairy Manure Management in New York: Current Practices and Willingness to
22 Participate in Voluntary Programs, Department of Agricultural, Resource, and Managerial Economics, Cornell
23 University, Ithaca, New York, September.
24 Safley, L.M., Jr. and P.W. Westerman (1990) "Psychrophilic Anaerobic Digestion of Animal Manure: Proposed
25 Design Methodology." Biological Wastes. 34:133-148.
26 Safley, L.M., Jr. (2000) Telephone conversation between Deb Bartram of ERG and L.M. Safley, President, Agri-
27 Waste Technology, June and October.
28 Stettler, D. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Don Stettler, Environmental
29 Engineer, National Climate Center, Oregon Natural Resource Conservation Service, 27 June.
30 Sweeten, J. (2000) Telephone conversation between Indra Mitra of ERG and John Sweeten, Texas A&M
31 University, June 2000.
32 UEP (1999) Voluntary Survey Results—Estimated Percentage Participation/Activity, Caged Layer Environmental
33 Management Practices, Industry data submissions for EPA profile development, United Egg Producers and National
34 Chicken Council. Received from John Thorne, Capitolink. June 2000.
35 USDA (2006a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, >Washington, DC.
36 January. Data also available from .
37 USDA (2006b) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
38 Washington, DC. April 2006. Data also available from .
11-46 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 USDA (2006c) Chicken and Eggs 2005 Summary, U.S. Department of Agriculture, National Agriculture Statistics
2 Service, Washington, DC. February. Data also available from .
3 USDA (2006d) Poultry - Production and Value 2005 Summary, U.S. Department of Agriculture, National
4 Agriculture Statistics Service, Washington, DC. April. Data also available from .
5 USDA (2006e) Published Estimates Database, U.S. Department of Agriculture, National Agricultural Statistics
6 Service, Washington, DC. Downloaded from QuickStats, Accessed May 2006.
7 USDA (2005a) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
8 Washington, DC. January 21, 2005. Data also available from .
9 USDA (2005b) Poultry Production and Value Annual Summary, U.S. Department of Agriculture, National
10 Agriculture Statistics Service, Washington, DC. April 28, 2005. Data also available from
11 .
12 USDA (2005c) Quarterly Hogs and Pigs, U.S. Department of Agriculture, National Agriculture Statistics Service,
13 Washington, DC. December. Data also available from .
14 USDA (2005d) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
15 Washington, DC. January 28, 2005. Data also available from .
16 USDA (2005e) 1992, 1997, and 2002 Census of Agriculture, U.S. Department of Agriculture, National Agriculture
17 Statistics Service, Washington, DC. Available online at Accessed March
18 2006.
19 USDA (2004a) Cattle—Final Estimates 1999-2003, U.S. Department of Agriculture, National Agriculture Statistics
20 Service, Washington, DC. April. Data also available from .
21 USDA (2004b) Hogs and Pigs—Final Estimates 1998-2002, U.S. Department of Agriculture, National Agriculture
22 Statistics Service, Washington, DC. March. Data also available from
23 .
24 USDA (2004c) Chicken and Eggs—Final Estimates 1998-2003, U.S. Department of Agriculture, National
25 Agriculture Statistics Service, Washington, DC. April. Data also available from
26 .
27 USDA (2004d) Poultry Production and Value—Final Estimates 1998-2002, U.S. Department of Agriculture,
28 National Agriculture Statistics Service, Washington, DC. April. Data also available from
29 .
30 USDA (2004e) Sheep and Goats—Final Estimates 1999-2003, U.S. Department of Agriculture, National
31 Agriculture Statistics Service, Washington, DC. April. Data also available from
32 .
33 USDA (2000a) Chicken and Eggs—Final Estimates 1988-1993, U.S. Department of Agriculture, National
34 Agriculture Statistics Service, Washington, DC. Downloaded from , May 3, 2000.
36 USDA (2000b) Re-aggregated data from the National Animal Health Monitoring System's (NAHMS) Dairy '96
37 study provided by Stephen L. Ott of the U.S. Department of Agriculture, Animal and Plant Health Inspection
38 Service. June 19.
39 USDA (2000c) Layers '99—Part II: References of1999 Table Egg Layer Management in the U.S., U.S.
40 Department of Agriculture, Animal and Plant Health Inspection Service (APHIS), National Animal Health
References 11-47
-------
Public Review Draft
1 Monitoring System (NAHMS). January.
2 USDA (1999a) Cattle—Final Estimates 1994-98, U.S. Department of Agriculture, National Agriculture Statistics
3 Service, Washington, DC. January. Data also available from .
4 USDA (1999b) Poultry Production and Value—Final Estimates 1994-97, U.S. Department of Agriculture, National
5 Agriculture Statistics Service, Washington, DC. March. Data also available from
6 .
7 USDA (1999c) Sheep and Goats—Final Estimates 1994-1998, U.S. Department of Agriculture, National
8 Agriculture Statistics Service, Washington, DC. January. Data also available from
9 .
10 USDA (1998a) Hogs and Pigs—Final Estimates 1993-97, U.S. Department of Agriculture, National Agriculture
11 Statistics Service, Washington, DC. December. Data also available from
12 .
13 USDA (1998b) Chicken and Eggs—Final Estimates 1994-97, U.S. Department of Agriculture, National Agriculture
14 Statistics Service, Washington, DC. December. Data also available from
15 .
16 USDA (1998c) Re-aggregated data from the National Animal Health Monitoring System's (NAHMS) Swine '95
17 study aggregated by Eric Bush of the U.S. Department of Agriculture, Centers for Epidemiology and Animal
18 Health.
19 USDA (1996a) Agricultural Waste Management Field Handbook, National Engineering Handbook (NEH), Part
20 651, U.S. Department of Agriculture, Natural Resources Conservation Service. July.
21 USDA (1996b) Swine '95: Grower/Finisher Part 11: Reference of1995 U.S. Grower/Finisher Health &
22 Management Practices, U.S. Department of Agriculture, Animal Plant Health and Inspection Service, Washington,
23 DC. June.
24 USDA (1995a) Cattle—Final Estimates 1989-93, U.S. Department of Agriculture, National Agriculture Statistics
25 Service, Washington, DC. January. Data also available from .
26 USDA (1995b) Poultry Production and Value—Final Estimates 1988-1993, U.S. Department of Agriculture,
27 National Agriculture Statistics Service, Washington, DC. January. Data also available from
28 .
29 USDA (1994a) Hogs and Pigs—Final Estimates 1988-92, U.S. Department of Agriculture, National Agriculture
30 Statistics Service, Washington, DC. December. Data also available from
31 .
32 USDA (1994b) Sheep and Goats—Final Estimates 1989-1993, U.S. Department of Agriculture, National
33 Agriculture Statistics Service, Washington, DC. January 31, 1994. Data also available from
34 .
35 Wright, P. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Peter Wright, Cornell University,
36 College of Agriculture and Life Sciences, June 23, 2000.
37 Rice Cultivation
38 Bollich, P. (2000) Telephone conversation between Payton Deeks of ICF Consulting and Pat Bollich, Professor
39 with Louisiana State University Agriculture Center. May 17, 2000.
11-48 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Bossio, D. A., W. Horwath, R.G. Mutters, and C. van Kessel (1999) "Methane pool and flux dynamics in a rice field
2 following straw incorporation." Soil Biology and Biochemistry 31:1313-1322.
3 Cantens, G. (2005) Telephone conversation between Lauren Flinn of ICF Consulting and Janet Lewis, Assistant to
4 Gaston Cantens, Vice President of Corporate Relations, Florida Crystals Company. August 4, 2005.
5 Cantens, G. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Janet Lewis, Assistant to
6 Gaston Cantens, Vice President of Corporate Relations, Florida Crystals Company. July 30, 2004.
7 Cicerone R.J., C.C. Delwiche, S.C. Tyler, and P.R. Zimmerman (1992) "Methane Emissions from California Rice
8 Paddies with Varied Treatments." Global Biogeochemical Cycles 6:233-248.
9 Deren, C. (2002) Telephone conversation between Caren Mintz and Dr. Chris Deren, Everglades Research and
10 Education Centre at the University of Florida. August 15, 2002.
11 Guethle, D. (2006) Telephone conversation between Lauren Flinn of ICF International and David Guethle,
12 Agronomy Specialist, Missouri Cooperative Extension Service. July 2005.
13 Guethle, D. (2005) Email correspondence between Lauren Flinn of ICF Consulting and David Guethle, Agronomy
14 Specialist, Missouri Cooperative Extension Service. July 2005.
15 Guethle, D. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and David Guethle,
16 Agronomy Specialist, Missouri Cooperative Extension Service. June 23, 2004.
17 Guethle, D. (2003) Telephone conversation between Caren Mintz of ICF Consulting and David Guethle,
18 Agronomy Specialist, Missouri Cooperative Extension Service. June 19, 2003.
19 Guethle, D. (2002) Telephone conversation between Caren Mintz of ICF Consulting and David Guethle,
20 Agronomy Specialist, Missouri Cooperative Extension Service. August 19, 2002.
21 Guethle, D. (200 la) Telephone conversation between Caren Mintz of ICF Consulting and David Guethle,
22 Agronomy Specialist at Missouri Cooperative Extension Service. July 31, 2001.
23 Guethle, D. (2001b) Telephone conversation between Caren Mintz of ICF Consulting and David Guethle,
24 Agronomy Specialist at Missouri Cooperative Extension Service. September 4, 2001.
25 Guethle, D. (2000) Telephone conversation between Payton Deeks of ICF Consulting and David Guethle,
26 Agronomy Specialist, Missouri Cooperative Extension Service, May 17, 2000.
27 Guethle, D. (1999) Telephone conversation between Payton Deeks of ICF Consulting and David Guethle,
28 Agronomy Specialist, Missouri Cooperative Extension Service, August 6, 1999.
29 Holzapfel-Pschorn, A., R. Conrad, and W. Seiler (1985) "Production, Oxidation, and Emissions of Methane in Rice
30 Paddies." FEMSMicrobiology Ecology 31:343-351.
31 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
32 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
33 XVI/Doc. 10 (1.IV.2000). May.
34 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris:
35 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
36 Co-Operation and Development, International Energy Agency.
37 Kirstein, A. (2006) Telephone conversation between Lauren Flinn of ICF International and Arthur Kirstein,
References 11-49
-------
Public Review Draft
1 Coordinator, Agricultural Economic Development Program, Palm Beach County Cooperative Extension Service,
2 FL, August 17, 2006.
3 Kirstein, A. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Arthur Kirstein,
4 Coordinator, Agricultural Economic Development Program, Palm Beach County Cooperative Extension Service,
5 FL, June 30, 2004.
6 Kirstein, A. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Arthur Kirstein,
7 Coordinator, Agricultural Economic Development Program, Palm Beach County Cooperative Extension Service,
8 FL, August 13, 2003.
9 Klosterboer, A. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Arlen Klosterboer,
10 retired Extension Agronomist, Texas A&M University, July 7, 2003.
11 Klosterboer, A. (2002) Telephone conversation between Caren Mintz of ICF Consulting and Arlen Klosterboer,
12 Extension Agronomist, Texas A&M University, August 19, 2002.
13 Klosterboer, A. (2001a) Telephone conversation between Caren Mintz of ICF Consulting and Arlen Klosterboer,
14 Extension Agronomist, Texas A & M University, August 6, 2001.
15 Klosterboer, A. (2001b) Telephone conversation between Caren Mintz of ICF Consulting and Arlen Klosterboer,
16 Extension Agronomist, Texas A&M University, October 8, 2001.
17 Klosterboer, A. (2000) Telephone conversation between Payton Deeks of ICF Consulting and Arlen Klosterboer,
18 Extension Agronomist, Texas A&M University, May 18, 2000.
19 Klosterboer, A. (1999) Telephone conversation between Catherine Leining of ICF Consulting and Arlen
20 Klosterboer, Extension Agronomist, Texas A&M University, June 10, 1999.
21 Klosterboer, A. (1997) Telephone conversation between Holly Simpkins of ICF Incorporated and Arlen
22 Klosterboer, Texas A&M University, December 1, 1997.
23 Lee, D. (2006). Email correspondence between Lauren Flinn of ICF International and Danny Lee, OK Farm
24 Service Agency, July 13, 2006.
25 Lee, D. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Danny Lee, OK Farm Service
26 Agency, Stillwater, OK, July, September 2005.
27 Lee, D. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Danny Lee, OK Farm Service
28 Agency, Stillwater, OK, July 23, 2004.
29 Lee, D. (2003) Telephone conversation and email correspondence between Caren Mintz of ICF Consulting and
30 Danny Lee, OK Farm Service Agency, Stillwater, OK, July 2, 2003.
31 Lindau, C. W. and P.K. Bollich (1993) "Methane Emissions from Louisiana First and Ratoon Crop Rice." Soil
32 Science 156:42-48.
33 Lindau, C.W., P.K Bollich, and R.D. DeLaune (1995) "Effect of Rice Variety on Methane Emission from Louisiana
34 Rice." Agriculture, Ecosystems and Environment 54:109-114.
35 Linscombe, S. (2006). Email correspondence between Lauren Flinn of ICF International and Steve Linscombe,
36 Professor with the Rice Research Station at Louisiana State University Agriculture Center.
37 Slinscombe@agctr.lsu.edu, August 15, 2006.
11-50 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Linscombe, S. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Steve Linscombe,
2 Professor with the Rice Research Station at Louisiana State University Agriculture Center, July 2005.
3 Linscombe, S. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Steve Linscombe,
4 Professor with the Rice Research Station at Louisiana State University Agriculture Center, June 23, 2004.
5 Linscombe, S. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Steve Linscombe,
6 Professor with the Rice Research Station at Louisiana State University Agriculture Center, June 10, 2003.
7 Linscombe, S. (2002) Telephone conversation between Caren Mintz of ICF Consulting and Steve Linscombe,
8 Professor with the Rice Research Station at Louisiana State University Agriculture Center, August 21, 2002.
9 Linscombe, S. (2001a) Telephone conversation between Caren Mintz of ICF Consulting and Steve Linscombe,
10 Research Agronomist, Rice Research Station in Crowley, LA, July 30- August 1, 2001.
11 Linscombe, S. (200 lb) Email correspondence between Caren Mintz of ICF Consulting and Steve Linscombe,
12 Research Agronomist, Rice Research Station in Crowley, LA, October 4, 2001.
13 Linscombe, S. (1999) Telephone conversation between Catherine Leining of ICF Consulting and Steve Linscombe,
14 Research Agronomist, Rice Research Station in Crowley, LA, June 3, 1999.
15 Mayhew, W. (1997) Telephone conversation between Holly Simpkins of ICF Incorporated and Walter Mayhew,
16 University of Arkansas, Little Rock, November 24, 1997.
17 Mutters, C. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Mr. Cass Mutters, Rice
18 Farm Advisor for Butte, Glen, and Tehama Counties. University of California Cooperative Extension Service, July
19 2004.
20 Mutters, C. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Mr. Cass Mutters, Rice
21 Farm Advisor for Butte, Glen, and Tehama Counties. University of California Cooperative Extension Service, June
22 25,2004.
23 Mutters, C. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Mr. Cass Mutters, Rice
24 Farm Advisor for Butte, Glen, and Tehama Counties. University of California Cooperative Extension Service, June
25 23,2003.
26 Mutters, C. (2002) Telephone conversation between Caren Mintz of ICF Consulting and Mr. Cass Mutters, Rice
27 Farm Advisor for Butte, Glen, and Tehama Counties. University of California Cooperative Extension Service,
28 August 27, 2002.
29 Mutters, C. (2001) Telephone conversation between Caren Mintz of ICF Consulting and Cass Mutters, Rice Farm
30 Advisor for Butte, Glen, and Tehama Counties, University of California Cooperative Extension Service, September
31 5,2001.
32 Saichuk, J. (1997) Telephone conversation between Holly Simpkins of ICF Incorporated and John Saichuk,
33 Louisiana State University, November 24, 1997.
34 Sass, R.L., F.M Fisher, P. A. Harcombe, and F.T. Turner (1991a) "Mitigation of Methane Emissions from Rice
35 Fields: Possible Adverse Effects of Incorporated Rice Straw." Global Biogeochemical Cycles 5:275-287.
36 Sass, R.L., F.M. Fisher, F.T. Turner, and M.F. Jund (1991b) "Methane Emissions from Rice Fields as Influenced by
37 Solar Radiation, Temperature, and Straw Incorporation." Global Biogeochemical Cycles 5:335-350.
38 Sass, R.L., F.M. Fisher, P. A. Harcombe, and F.T. Turner (1990) "Methane Production and Emissions in a Texas
References 11-51
-------
Public Review Draft
1 Rice Field." Global Biogeochemical Cycles 4:47-68.
2 Schueneman, T. (200 la) Telephone conversation between Caren Mintz of ICF Consulting and Tom Schueneman,
3 Palm Beach County Agricultural Extension Agent, Florida, July 30, 2001.
4 Schueneman, T. (200 lb) Telephone conversation between Caren Mintz of ICF Consulting and Tom Schueneman,
5 Palm Beach County Agricultural Extension Agent, Florida, October 9, 2001.
6 Schueneman, T. (2000) Telephone conversation between Payton Deeks of ICF Consulting and Tom Schueneman,
7 Palm Beach County Agricultural Extension Agent, Florida, May 16, 2000.
8 Schueneman, T. (1999a) Telephone conversation between Catherine Leining of ICF Consulting and Tom
9 Schueneman, Palm Beach County Agricultural Extension Agent, Florida, June 7, 1999.
10 Schueneman, T. (1999b) Telephone conversation between Payton Deeks of ICF Consulting and Tom Schueneman,
11 Palm Beach County Agricultural Extension Agent, Florida, August 10, 1999.
12 Schueneman, T. (1999c) Telephone conversation between John Venezia of ICF Consulting and Tom Schueneman,
13 Palm Beach County Agricultural Extension Agent, Florida, August 7, 1999.
14 Schueneman, T. (1997) Telephone conversation between Barbara Braatz of ICF Incorporated and Tom
15 Schueneman, County Extension Agent, Florida, November 7, 1997.
16 Slaton, N. (200 la) Telephone conversation between Caren Mintz of ICF Consulting and Nathan Slaton, Extension
17 Agronomist—Rice, University of Arkansas Division of Agriculture Cooperative Extension Service, August 23,
18 2001.
19 Slaton, N. (2001b) Telephone conversation between Caren Mintz of ICF Consulting and Nathan Slaton, Extension
20 Agronomist—Rice, University of Arkansas Division of Agriculture Cooperative Extension Service, October 3,
21 2001.
22 Slaton, N. (2000) Telephone conversation between Payton Deeks of ICF Consulting and Nathan Slaton, Extension
23 Agronomist—Rice, University of Arkansas Division of Agriculture Cooperative Extension Service, May 20, 2000.
24 Slaton, N. (1999) Telephone conversation between Catherine Leining of ICF Consulting and Nathan Slaton,
25 Extension Agronomist—Rice, University of Arkansas Division of Agriculture Cooperative Extension Service, June
26 3, 1999.
27 Stansel, J. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Dr. Jim Stansel, Resident
28 Director and Professor Emeritus, Texas A&M University Agricultural Research and Extension Center, July 2005.
29 Stansel, J. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Dr. Jim Stansel, Resident
30 Director and Professor Emeritus, Texas A&M University Agricultural Research and Extension Center, July 12,
31 2004.
32 Stevens, G. (1997) Telephone conversation between Holly Simpkins of ICF Incorporated and Gene Stevens,
33 Extension Specialist, Missouri Commercial Agriculture Program, Delta Research Center, December 17, 1997.
34 Street, J. (2003) Telephone conversation and email correspondence between Caren Mintz of ICF Consulting and
35 Joe Street, Rice Specialist, Mississippi State University, Delta Research Center, June 19, 2003.
36 Street, J. (2002) Telephone conversation and email correspondence between Caren Mintz of ICF Consulting and
37 Joe Street, Rice Specialist, Mississippi State University, Delta Research Center, August 19, 2002.
11-52 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Street, J. (2001a) Telephone conversation between Caren Mintz of ICF Consulting and Dr. Joe Street, Mississippi
2 State University, Delta Research and Extension Center and Delta Branch Station, August 1, 2001.
3 Street, J. (200 lb) Telephone conversation between Caren Mintz of ICF Consulting and Dr. Joe Street, Mississippi
4 State University, Delta Research and Extension Center and Delta Branch Station, October 3, 2001.
5 Street, J. (2000) Telephone conversation between Payton Deeks of ICF Consulting and Joe Street, Rice Specialist,
6 Mississippi State University, Delta Research Center, May 17, 2000.
7 Street, J. (1999) Telephone conversation between Catherine Leining of ICF Consulting and Joe Street, Rice
8 Specialist, Mississippi State University, Delta Research Center, June 8, 1999.
9 Street, J. (1997) Telephone conversation between Holly Simpkins of ICF Incorporated and Dr. Joe Street,
10 Mississippi State University, Delta Research and Extension Center and Delta Branch Station, December 1, 1997.
11 Texas Agricultural Experiment Station (2006). "2005 - Texas Rice Crop Statistics Report." Agricultural Research
12 and Extension Center. Texas Agricultural Experiment Station. Texas A&M University System. Page 8. Available
13 online at http ://beaumont.tamu. edu/eLibrary/TRRFReport_default. htm.
14 USDA (2006) Crop Production 2005 Summary, National Agricultural Statistics Service, Agricultural Statistics
15 Board, U.S. Department of Agriculture, Washington, DC. Available online at .
16 USDA (2005) Crop Production 2004 Summary. National Agricultural Statistics Service, U.S. Department of
17 Agriculture. Available online at . Accessed June 2005.
18 USDA (2003) Field Crops, Final Estimates 1997-2002. Statistical Bulletin No. 982. National Agricultural
19 Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture, Washington, DC. Available online
20 at . Accessed September 2005.
21 USDA (1998) Field Crops Final Estimates 1992-97. Statistical Bulletin Number 947 a. National Agricultural
22 Statistics Service, U.S. Department of Agriculture. Available online at .
23 Accessed July 2001.
24 USDA (1994) Field Crops Final Estimates 1987-1992. Statistical Bulletin Number 896. National Agricultural
25 Statistics Service, U.S. Department of Agriculture. Available online at .
26 Accessed July 2001.
27 Walker, T. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Tim Walker, Assistant
28 Research Professor, Mississippi State University Delta Branch Exp. Station, July 2005.
29 Wilson, C. (2006) Email coorespondence between Lauren Flinn of ICF International and Dr. Chuck Wilson, Rice
30 Specialist at the University of Arkansas Cooperative Extension Service. (870) 673-2661. Wilson@uamont.edu. 8
31 August.
32 Wilson, C. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Dr. Chuck Wilson, Rice
33 Specialist at the University of Arkansas Cooperative Extension Service, August 2005.
34 Wilson, C. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Dr. Chuck Wilson, Rice
35 Specialist at the University of Arkansas Cooperative Extension Service, June 23, 2004.
36 Wilson, C. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Dr. Chuck Wilson, Rice
37 Specialist at the University of Arkansas Cooperative Extension Service, June 11, 2003.
38 Wilson, C. (2002) Telephone conversation between Caren Mintz of ICF Consulting and Dr. Chuck Wilson, Rice
References 11-53
-------
Public Review Draft
1 Specialist at the University of Arkansas Cooperative Extension Service, August 23, 2002.
2 Agricultural Soil Management
3 AAPFCO (2006) Commercial Fertilizers 2005. Association of American Plant Food Control Officials and The
4 Fertilizer Institute. University of Kentucky, Lexington, KY.
5 AAPFCO (2005) Commercial Fertilizers 2004. Association of American Plant Food Control Officials and The
6 Fertilizer Institute. University of Kentucky, Lexington, KY.
7 AAPFCO (2004) Commercial Fertilizers 2003. Association of American Plant Food Control Officials and The
8 Fertilizer Institute. University of Kentucky, Lexington, KY.
9 AAPFCO (2003) Commercial Fertilizers 2002. Association of American Plant Food Control Officials and The
10 Fertilizer Institute. University of Kentucky, Lexington, KY.
11 AAPFCO (2002) Commercial Fertilizers 2001. Association of American Plant Food Control Officials and The
12 Fertilizer Institute. University of Kentucky, Lexington, KY.
13 AAPFCO (2000a) 1999-2000 Commercial Fertilizers Data, ASCII files. Available from David Terry, Secretary,
14 AAPFCO.
15 AAPFCO (2000b) Commercial Fertilizers 2000. Association of American Plant Food Control Officials. University
16 of Kentucky, Lexington, KY.
17 AAPFCO (1999) Commercial Fertilizers 1999. Association of American Plant Food Control Officials. University
18 of Kentucky, Lexington, KY.
19 AAPFCO (1998) Commercial Fertilizers 1998. Association of American Plant Food Control Officials. University
20 of Kentucky, Lexington, KY.
21 AAPFCO (1997) Commercial Fertilizers 1997. Association of American Plant Food Control Officials. University
22 of Kentucky, Lexington, KY.
23 AAPFCO (1996) Commercial Fertilizers 1996. Association of American Plant Food Control Officials. University
24 of Kentucky, Lexington, KY.
25 AAPFCO (1995) Commercial Fertilizers 1995. Association of American Plant Food Control Officials. University
26 of Kentucky, Lexington, KY.
27 Alexander, R.B. and R.A. Smith (1990) County-Level Estimates of Nitrogen and Phosphorous Fertilizer Use in the
28 United States, 1945-1985. U.S. Geological Survey Open File Report 90-130.
29 Anderson, S. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Steve Anderson, Agricultural
30 Statistician, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC. May 31,
31 2000.
32 Anonymous (1924) Fertilizer Used on Cotton, 1923-1924. Table 753 in "Miscellaneous Agricultural Statistics."
33 1924 Yearbook of the Department of Agriculture, p. 1171.
34 ASAE (1999) ASAE Standards 1999. 46th Edition, American Society of Agricultural Engineers, St. Joseph, MI.
35 Bastian, R. (2006) Telephone conversation between Lauren Flinn of ICF International and Robert Bastian, Office
36 of Water, U.S. Environmental Protection Agency, Washington, DC, 17 July 2006.
11-54 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Bastian, R. (2005) Telephone conversation between Lauren Flinn of ICF Consulting and Robert Bastian, Office of
2 Water, U.S. Environmental Protection Agency, Washington, DC, September 2005.
3 Bastian, R. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Robert Bastian, Office of
4 Water, U.S. Environmental Protection Agency, Washington, DC, August 13, 2003.
5 Bastian, R. (2002) Telephone conversation between Caren Mintz of ICF Consulting and Robert Bastian, Office of
6 Water, U.S. Environmental Protection Agency, Washington, DC, 23 August.
7 Battaglin, W.A., and D. A. Goolsby (1994) Spatial Data in Geographic Information System Format on Agricultural
8 Chemical Use, Land Use, and Cropping Practices in the United States. U.S. Geological Survey Water-Resources
9 Investigations Report. 94-4176.
10 Bogue A.G. (1963) From Prairie to Corn Belt: Farming on the Illinois and Iowa prairies in the Nineteenth
11 Century. The University of Chicago Press, Chicago, IL.
12 Bonnen C.A., and F.F. Elliott (1931) Type of Farming Areas in Texas. Texas Agricultural Experiment Station
13 Bulletin Number 427. Agricultural and Mechanical College of Texas.
14 Bouwman, A.F., Boumans, L.J.M., and Batjes, N.H. 2002a. Emissions of N20 and NO from fertilised fields:
15 Summary of available measurement data. Glob. Biogeochem. Cycles, 16(4), art. no. 1058.
16 Bouwman, A.F., Boumans, L.J.M. and Batjes, N.H. 2002b. Modeling global annual N20 and NO emissions from
17 fertilised fields. Glob. Biogeochem. Cycles, 16(4), art. no. 1080.
18 Brenner, J., K. Paustian, G. Bluhm, J. Cipra, M. Easter, R. Foulk, K. Killian, R. Moore, J. Schuler, P. Smith, and S.
19 Williams (2002) Quantifying the Change in Greenhouse Gas Emissions Due to Natural Resource Conservation
20 Practice Application in Nebraska. Colorado State University Natural Resource Ecology Laboratory and USDA
21 Natural Resources Conservation Service, Fort Collins, CO.
22 Brenner, J., K. Paustian., G. Bluhm, J. Cipra, M. Easter, E.T. Elliott, T. Koutza, K. Killian, J. Schuler, S. Williams
23 (2001) Quantifying the Change in Greenhouse Gas Emissions Due to Natural Resource Conservation Practice
24 Application in Iowa. Final report to the Iowa Conservation Partnership. Colorado State University Natural
25 Resource Ecology Laboratory and U.S. Department of Agriculture Natural Resources Conservation Service, Fort
26 Collins, CO.
27 Brumme, R., Borken, W., and Finke, S., 1999. Hierarchical control on nitrous oxide emission in forest ecosystems.
28 Global Biochem. Cycles 13, 1137-1148.
29 Butterbach-Bahl, K., Gasche, R., Breuer, L., and Papen, H., 1997. Fluxes of NO and N20 from temperate forest
30 soils: impact of forest type, N deposition and of liming on the NO and N20 emissions. Nutr. Cycl. Agroecosyst. 48,
31 79-90.
32 Carpenter, G.H. (1992) "Current Litter Practices and Future Needs." In: 1992 National Poultry Waste Management
33 Symposium Proceedings. Blake, J.P., Donald, J.O., and Patterson, P.H. (eds.), pp. 268-273, Auburn University
34 Printing Service, Auburn, AL.
35 ChilcottE.C. (1910) A Study of Cultivation Methods and Crop Rotations for the Great Plains Area. U.S.
36 Department of Agriculture Bureau of Plant Industry Bulletin Number 187. Government Printing Office,
37 Washington, DC.
38 Clough, T., Bertram, J.E., Sherlock, R.R., Leonard, R.L., and Nowicki, B.L., 2006. Comparison of measured and
39 EF5-r-derived N20 fluxes from a spring-fed river. Glob. Change Biol. 12, 477-488.
40 Corre, M.D., Pennock, D.J., Kessel, C. van., and Elliott, D.K., 1999. Estimation of annual nitrous oxide emissions
References 11-55
-------
Public Review Draft
1 from a transitional grassland-forest region in Saskatchewan, Canada. Biogeochem. 44, 29-49.
2 CTIC (1998) 1998 Crop Residue Management Executive Summary. Conservation Technology Information Center.
3 Data available online at .
4 Daly, C., G.H. Taylor, W.P. Gibson, T. Parzybok, G.L. Johnson, and P. A. Pasteris (1998) "Development of high-
5 quality spatial datasets for the United States." in: Proc., 1st International Conference on Geospatial Information in
6 Agriculture and Forestry, Lake Buena Vista, FL. June 1-3, 1998, pp.1-512-1-519.
7 Daly, C., R.P. Neilson, and D.L. Phillips (1994) "A statistical-topographic model for mapping climatological
8 precipitation over mountainous terrain." Journal of Applied Meteorology, 33:140-158.
9 DAYMET (No date) Daily Surface Weather and Climatological Summaries. Numerical Terradynamic Simulation
10 Group (NTSG), University of Montana. Available online at .
11 Deal, P. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Peter B. Deal, Rangeland
12 Management Specialist, Florida Natural Resource Conservation Service, 21 June.
13 de Klein C.A.M. 2004. Review of the N20 emission factor for excreta deposited by grazing animals (EF3PRP). Paper
14 prepared as part of the 2006 Revised Guidelines for Greenhouse Gas Inventories of IPCC.
15 Del Grosso S.J., S.M. Ogle, F.J. Breidt (in prep.) "Uncertainty in estimating nitrous oxide emissions from cropped
16 and grazed soils in the USA." Manuscript in preparation.
17 Del Grosso, S.J., A.R. Mosier, W.J. Parton and D.S. Ojima (2005) "DAYCENT Model Analysis of Past and
18 Contemporary Soil N20 and Net Greenhouse Gas Flux for Major Crops in the USA." Soil Tillage and Research, 83:
19 9-24. doi: 10.1016/j.still.2005.02.007.
20 Del Grosso, S.J., W.J. Parton, A.R. Mosier, M.D. Hartman, J. Brenner, D.S. Ojima, D.S. Schimel (2001) "Simulated
21 Interaction of Carbon Dynamics and Nitrogen Trace Gas Fluxes Using the DAYCENT Model." In: Schaffer, M., L.
22 Ma, S. Hansen, (Eds.), Modeling Carbon and Nitrogen Dynamics for Soil Management. CRC Press, Boca Raton,
23 Florida, pp. 303-332.
24 Denier van der Gon, H., and Bleeker A. 2005. Indirect N20 emission due to atmospheric N deposition for the
25 Netherlands. Atmos. Environ. 39, 5827-5838.
26 Dong, L.F., Nedwell, D.B., Colbeck, I., and Finch, J. 2004. Nitrous oxide emission from some English and Welsh
27 rivers and estuaries. Water Air Soil Pollution: Focus 4, 127-134.
28 Edmonds, L., N. Gollehon, R.L. Kellogg, B. Kintzer, L. Knight, C. Lander, J. Lemunyon, D. Meyer, D.C. Moffitt,
29 and J. Schaeffer (2003) "Costs Associated with Development and Implementation of Comprehensive Nutrient
30 Management Plans." Parti. Nutrient Management, Land Treatment, Manure and Wastewater Handling and
31 Storage, and Recordkeeping. Natural Resource Conservation Service, U.S. Department of Agriculture.
32 Elliott F.F. (1933) Types of Farming in the United States. U.S. Department of Commerce. Government Printing
33 Office, Washington, DC.
34 Elliott F.F. and J.W. Tapp (1928) Types of Farming in North Dakota. U.S. Department of Agriculture Technical
3 5 Bulletin Number 102.
36 Ellsworth J.O. (1929) Types of Farming in Oklahoma. Agricultural Experiment Station Bulletin Number 181.
37 Oklahoma Agricultural and Mechanical College.
38 Engle, R.H., and B.R. Makela (1947) "Where is All the Fertilizer Going?" The Fertilizer Review. The National
11-56 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Fertilizer Association, Vol. XXII, 6:7-10.
2 EPA (2003) Clean Watersheds Needs Survey 2000—Report to Congress, U.S. Environmental Protection Agency,
3 Washington, DC. Available online at
4 EPA (2002) Cost Methodology for the Final Revisions to the National Pollutant Discharge Elimination System
5 Regulation and the Effluent Guidelines for Concentrated Animal Feeding Operations. EPA-821-R-03-004.
6 December.
7 EPA (1999) Biosolids Generation, Use and Disposal in the United States. Office of Solid Waste, U.S.
8 Environmental Protection Agency. Available online at .
9 EPA (1997) 1996 Clean Watersheds Needs Survey Report to Congress—Assessment of Needs for Publicly Owned
10 Wastewater Treatment Facilities, Correction of Combined Sewer Overflows, and management of Storm Water and
11 Nonpoint Source Pollution in the United States, U.S. Environmental Protection Agency, Washington, DC.
12 Available online at .
13 EPA (1993) Federal Register. Part II. Standards for the Use and Disposal of Sewage Sludge; Final Rules. U.S.
14 Environmental Protection Agency, 40 CFR Parts 257, 403, and 503.
15 EPA (1992) Global Methane Emissions from Livestock and Poultry Manure, U.S. Environmental Protection
16 Agency, Office of Air and Radiation, February.
17 ERG (2003) Methodology for Estimating Uncertainty for Manure Management Greenhouse Gas Inventory.
18 Contract No. GS-10F-0036, Task Order 005. Memorandum to EPA from ERG. September 26, 2003.
19 ERS (2003) Ag Chemical and Production Technology. Economic Research Service, U.S. Department of
20 Agriculture.
21 ERS (2002) Economic Research Service. U.S. Department of Agriculture. Available online at
22 .
23 ERS (1997) Cropping Practices Survey Data—1995. Economic Research Service, United States Department of
24 Agriculture. Available online at: .
25 ERS (1994) Fertilizer Use and Price Statistics. Stock #86012. Economic Research Service, U.S. Department of
26 Agriculture.
27 ERS (1988) Agricultural Resources—Inputs Situation and Outlook Report. AR-9. Economic Research Service.
28 USD A.
29 Eve, M. (2001) E-mail from Marlen Eve of the Natural Resources Ecology Laboratory to Barbara Braatz and Caren
30 Mintz of ICF Consulting, containing statistics on U.S. organic soil areas cultivated in 1982, 1992, and 1997, which
31 were extracted from the 1997 National Resources Inventory, September 21,2001.
32 FAO (2006) Yearly U.S. total horse population data from the Food and Agriculture Organization of the United
33 Nations database. Available online at .
34 Fraps G.S., and S.E. Asbury (1931) Commercial Fertilizers in 1930-1931 and Their Uses. Agricultural Experiment
35 Station Bulletin Number 434. Agricultural and Mechanical College of Texas.
36 Hardies E. W., and A.N. Hume (1927) Wheat in South Dakota. Agronomy Department Bulletin Number 222.
37 Agricultural Experiment Station, South Dakota State College of Agriculture and Mechanical Arts, Brookings, SD.
References 11-57
-------
Public Review Draft
1 Garey L.F. (1929) Types of Farming in Minnesota. Agricultural Experiment Station Bulletin Number 257.
2 University of Minnesota, St. Paul, MN.
3 Grant, W. R., and R. D. Krenz (1985) U. S. grain sorghum production practices and costs. Staff Report No. AGES
4 851024. National Economics Division, Economics Research Service, USD A.
5 Hargreaves M.W.M. (1993) Dry Farming in the Northern Great Plains: Years of Readjustment, 1920-1990.
6 University Press of Kansas, Lawrence, KS.
7 Hiscock, K.M., Bateman, A.S., Fukada, T., and Dennis, P.F. 2002. The concentration and distribution of
8 groundwater N20 in the Chalk aquifer of eastern England. In: Van Ham, J., Baede, A.P.M., Guicherit, R. and
9 Williams-Jacobse, J.G.F.M. (eds.), Proc. 3rd Internal Symp. Non-CCh Greenhouse Gases, Maastricht, The
10 Netherlands, 185-190.
11 Hiscock, K.M., Bateman, A.S., Muhlherr, I.H., Fukada, T., and Dennis, P.F. 2003. Indirect emissions of nitrous
12 oxide from regional aquifers in the United Kingdom. Environ. Sci. Technol. 37, 3507-3512.
13 Hodges J. A., F.F. Elliott, and W.E. Grimes (1930) Types of Farming in Kansas. Agricultural Experiment Station
14 Bulletin Number 251. Kansas State Agricultural College, Manhattan, KS.
15 Holmes C.L. (1929) Types of Farming in Iowa. Agricultural Experiment Station Bulletin Number 259. Iowa State
16 College of Agriculture and Mechanic Arts. Ames, IA.
17 Holmes G.K. (1902) "Practices in Crop Rotation." Yearbook of the Department of Agriculture, pp 519-532.
18 Hurd E.B. (1929) The Corn Enterprise in Iowa. Agricultural Experiment Station Bulletin Number 268. Iowa State
19 College of Agriculture and Mechanic Arts. Ames, IA.
20 Hurd E.B. (1930) Cropping Systems in Iowa Past and Present. Agricultural Experiment Station Bulletin Number
21 268. Iowa State College of Agriculture and Mechanic Arts. Ames, IA.
22 Hurt, R.D. (1994) American Agriculture: A Brief History. Iowa State University Press, Ames, IA.
23 Ibach, D.B. and J.R. Adams (1967) Fertilizer Use in the United States by Crops and Areas, 1964 Estimates.
24 Statistical Bulletin Number 408. U.S. Department of Agriculture.
25 Ibach, D.B., J.R. Adams, and E.I. Fox (1964) Commercial Fertilizer used on Crops and Pasture in the United
26 States, 1959 Estimates. U.S. Department of Agriculture Statistical Bulletin Number 348.
27 Iowa State College Staff Members (1946). I Century of Farming in Iowa 1846-1946. The Iowa State College Press,
28 Ames, IA.
29 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
30 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
31 Published: IGES, Japan.
32 IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry. J. Penman and others,
33 editors. IPCC National Greenhouse Gas Inventories Programme. Available online at , August 13, 2004.
35 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
36 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
37 XVI/Doc. 10 (1.IV.2000). May.
38 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, Paris:
11-58 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
2 Co-Operation and Development, International Energy Agency.
3 Johnson, D. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Dan Johnson, State Water
4 Management Engineer, California Natural Resource Conservation Service, June 23, 2000.
5 Kellogg R.L., C.H. Lander, D.C. Moffitt, and N. Gollehon (2000) Manure Nutrients Relative to Capacity of
6 Cropland and Pastureland to Assimilate Nutrients: Spatial and Temporal Trends for the United States. U.S.
7 Department of Agriculture Publication Number nps00-0579.
8 Kezer A. (ca 1917) Dry Farming in Colorado. Colorado State Board of Immigration. Denver.
9 Klemedtsson, L., Kasimir Klemedtsson, A., Escala, M. and Kulmala, A. 1999. Inventory of N20 emission from
10 farmed European peatlands. In: Freibauer, A. and Kaltschmitt, M. (eds.), Approaches to Greenhouse Gas
11 Inventories of Biogenic Sources in Agriculture, Proc. Workshop at Lokeberg, Sweden, 9-10 July 1998, pp. 79-91.
12 Kuchler, AW. (1964) The Potential Natural Vegetation of the Conterminous United States. Amer. Geographical
13 Soc. NY, Special Publication No. 36.
14 Lange, J. (2000) Telephone conversation between Lee-Ann Tracy of ERG and John Lange, Agricultural Statistician,
15 U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC, May 8, 2000.
16 Langston C.W., L.M. Davis, C.A. Juve, O.C. Stine, A.E. Wight, A.J. Pistor, and C.F. Langworthy (1922) "The
17 Dairy Industry." Yearbook of the Department ofAgriculture.
18 Larson, C. W., L. M. Davis, C. A. Juve, O. C. Stine, A. E. Wight, A. J. Pistor, and C. F. Langworthy. 1922. The
19 Dairy Industry Yearbook of the Department of Agriculture.
20 Latta W.C. (1938) Outline History of Indiana Agriculture. Alpha Lambda Chapter of Epsilon Sigma Phi, Purdue
21 University, Publishers.
22 McCarl, B.A., C.C. Chang, J.D. Atwood, W.I. Nayda (1993) Documentation of ASM: The U.S. Agricultural Sector
23 Model, Technical Report TR-93. Agricultural Experimental Station, College Station, Texas.
24 Metcalf and Eddy, Inc. (1991) Wastewater Engineering: Treatment, Disposal, and Reuse, Third Edition, McGraw-
25 Hill Publishing Company, NY, p. 772.
26 Miller, P. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Paul Miller, Iowa Natural Resource
27 Conservation Service, June 12, 2000.
28 Milton, B. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Bob Milton, Chief of Livestock
29 Branch, U.S. Department of Agriculture, National Agriculture Statistics Service, May 1, 2000.
30 Mosier, A.R. (2004) E-mail correspondence between Arvin Mosier of Agricultural Research Service, USDA and
31 Stephen Del Grosso of Natural Resource Ecology Laboratory, Colorado State University, regarding the uncertainty
32 in estimates of N application rates for specific crops (+/-20), September 20, 2004.
33 NASS (2004) Agricultural Chemical Usage: 2003 Field Crops Summary. Report AgChl(04)a. National
34 Agricultural Statistics Service. USDA. Available online at: .
36 NASS (1999) Agricultural Chemical Usage: 1998 Field Crops Summary. Report AgCHl(99). National Agricultural
37 Statistics Service, USDA. Available online at: .
References 11-59
-------
Public Review Draft
1 NASS (1992) Agricultural Chemical Usage: 1991 Field Crops Summary. Report AgChl(92). National Agricultural
2 Statistics Service, USDA. Available online at: .
4 NFA (1946) Charting the Fertilizer Course: Results ofNFA's Third Practice Survey. National Fertilizer
5 Association. The Fertilizer Review. Vol. XXI, 2: 7-13.
6 Novoa, R. and Tejeda, H.R. 2006. Evaluation of the N20 emissions from N in plant residues as affected by
7 environmental and management factors. Nutr. Cycl. Agroecosyst. (in press; available on-line).
8 NRAES. (1992) On-Farm Composting Handbook (NRAES-54). Natural Resource, Agriculture, and Engineering
9 Service. Available online at: .
10 NRIAI (2003) Regional Budget and Cost Information. Natural Resources Inventory and Analysis Institute. Natural
11 Resources Conservation Service. U.S. Department of Agriculture.
12 Ogle, S. (2002) E-mail from Stephen Ogle of the Natural Resources Ecology Laboratory to Barbara Braatz of ICF
13 Consulting, containing revised statistics on U.S. histosol areas cultivated in 1982, 1992, and 1997, which were
14 extracted from the 1997 National Resources Inventory by Marlen Eve, January 9, 2002.
15 Ogle, S.M., F.J. Breidt, M. Easter, S. Williams and K. Paustian. (2007) "Empirically-Based Uncertainty Associated
16 with Modeling Carbon Sequestration Rates in Soils." Ecological Modeling, accepted for publication, but not yet
17 published.
18 Parton, W.J., M.D. Hartman, D.S. Ojima, D.S. Schimel (1998) "DAYCENT: Its Land Surface Submodel:
19 Description and Testing". Glob. Planet. Chang. 19: 35-48.
20 Piper C.V., R.A. Oakley, H.N. Vinall, A.J. Pieters, W.J. Morse, W.J. Spillman, O.C. Stine, J.S. Cotton., G.A.
21 Collier, M.R Cooper, E.C. Parker, E.W. Sheets, and A.T. Semple (1924) "Hay." Yearbook of the Department of
22 Agriculture, pp 285-376.
23 Poe, G., N. Bills, B. Bellows, P. Crosscombe, R. Koelsch, M. Kreher, and P. Wright (1999) Documenting the Status
24 of Dairy Manure Management in New York: Current Practices and Willingness to Participate in Voluntary
25 Programs. Staff Paper, Dept. of Agricultural, Resource, and Managerial Economics, Cornell University, Ithaca,
26 NY, September.
27 Reay, D.S., Smith, K.A. and Edwards, A.C. 2004. Nitrous oxide in agricultural drainage waters following field
28 fertilisation. Water Air Soil Pollution: Focus, 4, 437-451.
29 Reay, D., Smith, K.A., Edwards, A.C., Hiscock, K.M., Dong, L.F., and Nedwell, D. 2005. Indirect nitrous oxide
30 emissions: revised emission factors. Environ. Sciences, 2, 153-158.
31 Rochette, P., Angers, D.A., Belanger, G., Chantigny, M.H., Prevost, D., Levesque, G., (2004) "Emissions of N20
32 from alfalfa and soybean crops in eastern Canada." Soil Sci. Soc. Am. J. 68, 493-506.
33 Ross W.H. and A.L. Mehring (1938) "Mixed Fertilizers." In Soils and Men. Agricultural Yearbook 1938. U.S.
34 Department of Agriculture.
35 Russell E.Z., S.S. Buckley, C.E. Baker, C.E. Gibbons, R.H. Wilcox, H.W. Hawthorne, S.W. Mendum, O.C. Stine,
36 G.K. Holmes, A.V. Swarthout, W.B. Bell, G.S. Jamieson, C.W. Warburton, and C.F. Langworthy (1922) Hog
37 Production and Marketing. Yearbook of the U.S. Department of Agriculture.
38 Safley, L.M. (2000) Telephone conversation between Deb Bartram of ERG and L.M. Safley, President, Agri-Waste
39 Technology, June.
11-60 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Safley, L.M., M.E. Casada, J.W. Woodbury, and J.F. Roos (1992) Global Methane Emissions from Livestock and
2 Poultry Manure. EPA/400/1-91/048, Office of Air and Radiation, U.S. Environmental Protection Agency.
3 February.
4 Sawamoto, T., Nakajima, Y., Kasuya, M., Tsuruta, H., and Yagi, K. 2005. Evaluation of emission factors for
5 indirect N20 emission due to nitrogen leaching in agro-ecosystems. Geophys. Res. Lett. 32(3),
6 doi: 10.1029/2004GL021625.
7 Saxton, K.E., W.J. Rawls, J.S. Romberger, R.I. Papendick (1986) "Estimating Generalized Soil-Water
8 Characteristics From Texture." Soil Sci. Soc.Am.J. 50: 1031-1036.
9 Skinner, J.J. (1931) Fertilizers for Cotton Soils. Miscellaneous Publication Number 126. U.S. Department of
10 Agriculture.
11 Smalley, H.R., R.H. Engle, and H. Willett (1939) American Fertilizer Practices: Second Survey. The National
12 Fertilizer Association.
13 Smith C.B. (1911) Rotations in the Corn Belt. Yearbook of the Department of Agriculture, pp.325-336.
14 Smith, P., J. Brenner, K. Paustian, G. Bluhm, J. Cipra, M. Easter, E.T. Elliott, K. Killian, D. Lamm, J. Schuler, and
15 S. Williams (2002) Quantifying the Change in Greenhouse Gas Emissions Due to Natural Resource Conservation
16 Practice Application in Indiana. Final Report to the Indiana Conservation Partnership, Colorado State University
17 Natural Resource Ecology Laboratory and U.S. Department of Agriculture Natural Resources Conservation Service,
18 Fort Collins, CO, USA
19 Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. 2005. State
20 Soil Geographic (STATSGO) Database for State. Available online at
21 .
22 Spillman W.J. (1908) Types of Farming in the United States. Yearbook of the Department of Agriculture, pp. 351-
23 366.
24 Spillman W.J. (1907) Cropping Systems for Stock Farms. Yearbook of the Department of Agriculture, pp. 385-398.
25 Spillman W.J. (1905) Diversified Farming in the Cotton Belt. Yearbook of the Department of Agriculture, pp. 193-
26 218.
27 Spillman W.J. (1902) Systems of Farm Management in the United States. Yearbook of the Department of
28 Agriculture, pp. 343-364.
29 Stehfest, E. and Bouwman, A.F. 2006. N20 and NO emission from agricultural fields and soils under natural
30 vegetation: summarising available measurement data and modelling of global annual emissions. Nutr. Cycl.
31 Agroecosyst., (in press; available on-line).
32 Stettler, D. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Don Stettler, Environmental
33 Engineer, National Climate Center, Oregon Natural Resource Conservation Service, June 27, 2000.
34 Sweeten, J. (2000) Telephone conversation between Indra Mitra of ERG and John Sweeten, Texas A&M
35 University, June.
36 Taylor, H.H. (1994) Fertilizer Use and Price Statistics: 1960-93. Resources and Technology Division, Economic
37 Research Service, U.S. Department of Agriculture, Statistical Bulletin Number 893.
38 Thornton, P.E., H. Hasenauer, and M.A. White (2000) "Simultaneous Estimation of Daily Solar Radiation and
References 11-61
-------
Public Review Draft
1 Humidity from Observed Temperature and Precipitation: An Application Over Complex Terrain in Austria."
2 Agricultural and Forest Meteorology 104: 255-271.
3 Thornton, P.E. and S.W. Running (1999) "An Improved Algorithm for Estimating Incident Daily Solar Radiation
4 from Measurements of Temperature, Humidity, and Precipitation." Agriculture and Forest Meteorology. 93: 211-
5 228.
6 Thornton, P.E., S.W. Running, and M.A. White (1997) "Generating Surfaces of Daily Meteorology Variables Over
7 Large Regions of Complex Terrain." Journal of Hydrology. 190:214-251.
8 TVA (1991) Commercial Fertilizers 1991. Tennessee Valley Authority, Muscle Shoals, AL.
9 TVA (1992a) Commercial Fertilizers 1992. Tennessee Valley Authority, Muscle Shoals, AL.
10 TVA (1992b) Fertilizer Summary Data 1992. Tennessee Valley Authority, Muscle Shoals, AL.
11 TVA (1993) Commercial Fertilizers 1993. Tennessee Valley Authority, Muscle Shoals, AL.
12 TVA (1994) Commercial Fertilizers 1994. Tennessee Valley Authority, Muscle Shoals, AL.
13 USD A (2006a) Agriculture Statistics 2006. National Agriculture Statistics Service, U.S. Department of Agriculture,
14 Washington, DC.
15 USDA (2006b) Crop Production 2005 Summary. National Agricultural Statistics Service, U.S. Department of
16 Agriculture, Washington, DC. Available online at .
17 USDA (2005a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
18 January 28, 2005. Data also available from .
19 USDA (2005b) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
20 Washington, DC. January 21, 2005. Data also available from .
21 USDA (2005c) Hogs and Pigs, U.S. Department of Agriculture, National Agriculture Statistics Service,
22 Washington, DC. March 24, 2005. Data also available from .
23 USDA (2005d) Chicken and Eggs Annual Summary, U.S. Department of Agriculture, National Agriculture
24 Statistics Service, Washington, DC. February 2005. Data also available from
25 .
26 USDA (2005e) Poultry Production and Value Annual Summary, U.S. Department of Agriculture, National
27 Agriculture Statistics Service, Washington, DC. April 28, 2005. Data also available from
28 .
29 USDA (2005f) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
30 Washington, DC. January 28, 2005. Data also available from .
31 USDA (2005g) 1992, 1997, and 2002 Census of Agriculture, U.S. Department of Agriculture, National Agriculture
32 Statistics Service, Washington, DC. Data available from .
33 USDA (2005h) Agriculture Statistics 2005. National Agricultural Statistics Service, U.S. Department of
34 Agriculture. Available online at or
35 .
36 USDA (2005i) Crop Production 2004 Summary. National Agricultural Statistics Service, U.S. Department of
11-62 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Agriculture, Washington, DC. Available online at .
2 USDA (2004a) Cattle—Final Estimates 1999-2003, U.S. Department of Agriculture, National Agriculture Statistics
3 Service, Washington, DC. April. Data also available from .
4 USDA (2004b) Hogs and Pigs—Final Estimates 1998-2002, U.S. Department of Agriculture, National Agriculture
5 Statistics Service, Washington, DC. March. Data also available from
6 .
7 USDA (2004c) Chicken and Eggs—Final Estimates 1998-2003, U.S. Department of Agriculture, National
8 Agriculture Statistics Service, Washington, DC. April. Data also available from
9 .
10 USDA (2004d) Poultry Production and Value—Final Estimates 1998-2002, U.S. Department of Agriculture,
11 National Agriculture Statistics Service, Washington, DC. April. Data also available from
12 .
13 USDA (2004e) Sheep and Goats—Final Estimates 1999-2003, U.S. Department of Agriculture, National
14 Agriculture Statistics Service, Washington, DC. April. Data also available from
15 .
16 USDA (2004f) Statistics on county level total crop area data for 1990-2003, extracted from the Agricultural
17 Statistics Database, U.S. Department of Agriculture National Agricultural Statistics Service. Available online at
18 .
19 USDA (2003) Crop Production 2002 Summary. National Agricultural Statistics Service, U.S. Department of
20 Agriculture, Washington, DC. Available online at . Accessed May 2003.
21 USDA (2000a) Cattle on Feed, National Agriculture Statistics Service, U.S. Department of Agriculture,
22 Washington, DC. April 14, 2000. Data also available online at .
23 USDA (2000b) 1997 National Resources Inventory. U.S. Department of Agriculture, Natural Resources
24 Conservation Service, Washington, DC. Available online at .
25 USDA (2000c) Agricultural Statistics 2000. National Agricultural Statistics Service, U.S. Department of
26 Agriculture. Available online at .
27 USDA (1999a) Cattle—Final Estimates 1994-98, National Agriculture Statistics Service, U.S. Department of
28 Agriculture, Washington, DC. January. Data also available online at .
29 USDA (1999b) Poultry Production and Value—Final Estimates 1994-97, National Agriculture Statistics Service,
30 U.S. Department of Agriculture, Washington, DC. March.
31 USDA (1999c) Sheep and Goats—Final Estimates 1994-1998, National Agriculture Statistics Service, U.S.
32 Department of Agriculture, Washington, DC. January.
33 USDA (1998a) Chicken and Eggs—Final Estimates 1994-97, National Agriculture Statistics Service, U.S.
34 Department of Agriculture, Washington, DC. December.
35 USDA (1998b) Field Crops Final Estimates 1992-97. Statistical Bulletin Number 947a. National Agricultural
36 Statistics Service, U.S. Department of Agriculture, GPO, Washington, DC. Available online at
37 . Accessed July 2001.
38 USDA (1998c) Hogs and Pigs—Final Estimates 1993-97, National Agriculture Statistics Service, U.S. Department
References 11-63
-------
Public Review Draft
1 of Agriculture, Washington, DC. December. Data also available online at .
2 USD A (1996) Agricultural Waste Management Field Handbook, National Engineering Handbook (NEH), Part 651,
3 U.S. Department of Agriculture, Natural Resources Conservation Service. July.
4 USDA (1995a) Cattle—Final Estimates 1989-93, National Agriculture Statistics Service, U.S. Department of
5 Agriculture, Washington, DC. January. Data also available online at .
6 USDA (1995b) Poultry Production and Value—Final Estimates 1989-1993, National Agriculture Statistics Service,
7 U.S. Department of Agriculture, Washington, DC.
8 USDA (1994a) Field Crops: Final Estimates, 1987-1992. Statistical Bulletin Number 896. National Agriculture
9 Statistics Service, U.S. Department of Agriculture, GPO, Washington, DC. Available online at
10 .
11 USDA (1994b) Hogs and Pigs—Final Estimates 1988-92, National Agriculture Statistics Service, U.S. Department
12 of Agriculture, Washington, DC. December. Data also available online at .
13 USDA (1994c) Sheep and Goats—Final Estimates 1989-1993, National Agriculture Statistics Service, U.S.
14 Department of Agriculture, Washington, DC. January.
15 USDA. (1966) Consumption of Commercial Fertilizers and Primary Plant Nutrients in the United States, 1850-
16 1964 and By States, 1945-1964. Statistical Reporting Service. Statistical Bulletin Number 375. U.S. Department
17 of Agriculture.
18 USDA. (1957) Fertilizer Used on Crops and Pastures in the United States—1954 Estimates. Agricultural Research
19 Service Statistical Bulletin Number 216. U.S. Department of Agriculture.
20 USDA. (1954) Fertilizer Use and Crop Yields in the United States. The Fertilizer Work Group. Agricultural
21 Handbook Number 68. U.S. Department of Agriculture.
22 USDA. (1946) Fertilizers and Lime in the United States. Miscellaneous Publication Number 586. U.S. Department
23 of Agriculture.
24 VEMAP (1995) Members (J.M. Melillo, J. Borchers, J. Chaney, H. Fisher, S. Fox, A. Haxeltine, A. Janetos, D.W.
25 Kicklighter, T.G.F. Kittel, A.D. McGuire, R. McKeown, R. Neilson, R. Nemani, D.S. Ojima, T. Painter, Y. Pan,
26 W.J. Parton, L. Pierce, L. Pitelka, C. Prentice, B. Rizzo, N.A. Rosenbloom, S. Running, D.S. Schimel, S. Sitch, T.
27 Smith, I. Woodward). "Vegetation/Ecosystem Modeling and Analysis Project (VEMAP): Comparing Biogeography
28 and Biogeochemistry Models in a Continental-Scale Study of Terrestrial Ecosystem Responses to Climate Change
29 and CO2 Doubling." Global Biogeochemical Cycles 9: 407-437.
30 Vogelmann, J.E., S.M. Howard, L. Yang, C. R. Larson, B. K. Wylie, and J. N. VanDriel (2001) "Completion of the
31 1990's National Land Cover Data Set for the conterminous United States." Photogrammetric Engineering and
32 Remote Sensing 67:650-662.
33 Warren J. A. (1911) Agriculture in the Central Part of the Semiarid Portion of the Great Plains. U.S. Department of
3 4 Agriculture Bureau of Plant Industry Bulletin Number 215.
35 Williams, S. A. 2006. From an unpublished manuscript and data compiled for the Consortium for Agricultural Soils
36 Mitigation of Greenhouse Gases (CASMGS). Natural Resource Ecology Laboratory, Colorado State University.
37 Williams-Jacobse, J.G.F.M. (ed.), 2002. Proceedings 3rd International Symposium Non-C02 Greenhouse Gases,
38 Maastricht, The Netherlands, 185-190.
11-64 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Wright, P. (2000) Telephone conversation between Lee-Ann Tracy of ERG and Peter Wright, Cornell University,
2 College of Agriculture and Life Sciences, June 23, 2000.
3 Field Burning of Agricultural Residues
4 Anonymous (2006) Telephone conversation with Lauren Flinn of ICF International, August 11, 2006.
5 Barnard, G., and L. Kristoferson (1985) Agricultural Residues as Fuel in the Third World. Earthscan Energy
6 Information Programme and the Beijer Institute of the Royal Swedish Academy of Sciences. London, England.
7 Bollich, P. (2000) Telephone conversation between PaytonDeeks of ICF Consulting and Pat Bollich, Professor
8 with Louisiana State University Agriculture Center, May 17, 2000.
9 California Air Resources Board (2001) Progress Report on the Phase Down and the 1998-2000 Pause in the Phase
10 Down of Rice Straw Burning in the Sacramento Valley Air Basin, Proposed 2001 Report to the Legislature, June.
11 California Air Resources Board (1999) Progress Report on the Phase Down of Rice Straw Burning in the
12 Sacramento Valley Air Basin, Proposed 1999 Report to the Legislature, December.
13 Cantens, G. (2005) Telephone conversation between Lauren Flinn of ICF Consulting and Janet Lewis, Assistant to
14 Gaston Cantens, Vice President of Corporate Relations, Florida Crystals Company. July 2005.
15 Cantens, G. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Janet Lewis, Assistant to
16 Gaston Cantens, Vice President of Corporate Relations, Florida Crystals Company. July 30, 2004.
17 Cibrowski, P. (1996) Telephone conversation between Heike Mainhardt of ICF Incorporated and Peter Cibrowski,
18 Minnesota Pollution Control Agency, July 29, 1996.
19 Deren, C. (2002) Telephone conversation between Caren Mintz of ICF Consulting and Dr. Chris Deren, Everglades
20 Research and Education Centre at the University of Florida, August 15, 2002.
21 EPA (1994) International Anthropogenic Methane Emissions: Estimates for 1990, Report to Congress. EPA 230-
22 R-93-010. Office of Policy Planning and Evaluation, U.S. Environmental Protection Agency. Washington, DC.
23 EPA (1992) Prescribed Burning Background Document and Technical Information Document for Prescribed
24 Burning Best Available Control Measures. EPA-450/2-92-003. Office of Air Quality Planning and Standards, U.S.
25 Environmental Protection Agency. Research Triangle Park, NC.
26 Fife, L. (1999) Telephone conversation between Catherine Leining of ICF Consulting and Les Fife, President and
27 General Manager, Fife Environmental, June 9, 1999.
28 ILENR (1993) Illinois Inventory of Greenhouse Gas Emissions and Sinks: 1990. Office of Research and Planning,
29 Illinois Department of Energy and Natural Resources. Springfield, IL.
30 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
31 Intergovernmental Panel on Climate Change, National Greenhouse Gas Inventories Programme, Montreal, IPCC-
32 XVI/Doc. 10 (1.IV.2000). May.
33 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, Paris:
34 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
35 Co-Operation and Development, International Energy Agency.
36 Jenkins, B.M., S.Q. Turn, and R.B. Williams (1992) Atmospheric emissions from agricultural burning in California:
37 determination of burn fractions, distribution factors, and crop specific contributions. Agriculture, Ecosystems and
References 11-65
-------
Public Review Draft
1 Environment 38:313-330.
2 Ketzis, J. (1999) Telephone conversation between Marco Alcaraz of ICF Consulting and Jen Ketzis of Cornell
3 University, June/July.
4 Kirstein, A. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Arthur Kirstein,
5 Coordinator, Agricultural Economic Development Program, Palm Beach County Cooperative Extension Service,
6 Florida, June 30, 2004.
7 Kirstein, A. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Arthur Kirstein,
8 Coordinator, Agricultural Economic Development Program, Palm Beach County Cooperative Extension Service,
9 Florida, August 13, 2003.
10 Klosterboer, A. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Arlen Klosterboer,
11 retired Extension Agronomist, Texas A&M University, July 7, 2003.
12 Klosterboer, A. (2002) Telephone conversation between Caren Mintz of ICF Consulting and Arlen Klosterboer,
13 Extension Agronomist, Texas A&M University, August 19, 2002.
14 Klosterboer, A. (2001) Telephone conversation between Caren Mintz of ICF Consulting and Arlen Klosterboer,
15 Extension Agronomist, Texas A&M University, August 6, 2001.
16 Klosterboer, A. (2000) Telephone conversation between Payton Deeks of ICF Consulting and Arlen Klosterboer,
17 Extension Agronomist, Texas A&M University, May 18, 2000.
18 Klosterboer, A. (1999a) Telephone conversation between Catherine Leining of ICF Consulting and Arlen
19 Klosterboer, Extension Agronomist, Texas A&M University, June 10, 1999.
20 Klosterboer, A. (1999b) Telephone conversation between Payton Deeks of ICF Consulting and Arlen Klosterboer,
21 Extension Agronomist, Texas A&M University, August 12, 1999.
22 Lancero, J. (2006). Email correspondence between Lauren Flinn of ICF International and Jeff Lancero, California
23 Air Resources Board, August 11, 2006.
24 Lee, D. (2006). Email correspondence between Lauren Flinn of ICF International and Danny Lee, OK Farm
25 Service Agency, July 13, 2006.
26 Lee, D. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Danny Lee, OK Farm Service
27 Agency, Stillwater, OK. July and September.
28 Lee, D. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Danny Lee, OK Farm Service
29 Agency, Stillwater, OK, July 23, 2006.
30 Lee, D. (2003) Telephone conversation and email correspondence between Caren Mintz of ICF Consulting and
31 Danny Lee, OK Farm Service Agency, Stillwater, OK. July 2, 2003.
32 Lindberg, J. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Jeff Lindberg, California
33 Air Resources Board. July.
34 Lindberg, J. (2004) Email correspondence between Lauren Flinn of ICF Consulting and Jeff Lindberg, California
35 Air Resources Board. June-July.
36 Lindberg, J. (2003) Email correspondence between Caren Mintz of ICF Consulting and Jeff Lindberg, California
37 Air Resources Board. June-July.
11-66 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Lindberg, J. (2002) Telephone conversation and email correspondence between Caren Mintz of ICF Consulting and
2 Jeff Lindberg, California Air Resources Board, September 12-13, 2002.
3 Linscombe, S. (2006). Email correspondence between Lauren Flinn of ICF International and Steve Linscombe,
4 Professor with the Rice Research Station at Louisiana State University Agriculture Center.
5 Slinscombe@agctr.lsu.edu, August 15, 2006.
6 Linscombe, S. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Steve Linscombe,
7 Professor with the Rice Research Station at Louisiana State University Agriculture Center. July 2005.
8 Linscombe, S. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Steve Linscombe,
9 Professor with the Rice Research Station at Louisiana State University Agriculture Center, June 23, 2004.
10 Linscombe, S. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Steve Linscombe,
11 Professor with the Rice Research Station at Louisiana State University Agriculture Center, June 10, 2003.
12 Linscombe, S. (2002) Email correspondence between Caren Mintz of ICF Consulting and Steve Linscombe,
13 Research Agronomist, Louisiana State University Agricultural Center, August 21, 2002.
14 Linscombe, S. (2001) Email correspondence between Caren Mintz of ICF Consulting and Steve Linscombe,
15 Research Agronomist, Louisiana State University Agricultural Center, July 30 -August 1, 2001.
16 Linscombe, S. (1999a) Telephone conversation between Catherine Leining of ICF Consulting and Steve
17 Linscombe, Research Agronomist, Louisiana State University Agricultural Center, June 3, 1999.
18 Linscombe, S. (1999b) Telephone conversation between Payton Deeks of ICF Consulting and Steve Linscombe,
19 Research Agronomist, Louisiana State University Agricultural Center, August 9, 1999.
20 Najita, T. (2001) Telephone conversation between Caren Mintz of ICF Consulting and Theresa Najita, Air Pollution
21 Specialist, California Air Resources Board, July 31, 2001.
22 Najita, T. (2000) Telephone conversation between Payton Deeks of ICF Consulting and Theresa Najita, Air
23 Pollution Specialist, California Air Resources Board, August 17, 2000.
24 Noller, J. (1996) Telephone conversation between Heike Mainhardt of ICF Incorporated and John Noller, Missouri
25 Department of Natural Resources. 30 July.
26 Oregon Department of Energy (1995) Report on Reducing Oregon's Greenhouse Gas Emissions: Appendix D
27 Inventory and Technical Discussion. Oregon Department of Energy. Salem, OR.
28 Sacramento Valley Basinwide Air Pollution Control Council (2005) Report on the Conditional Rice Straw Burning
29 Permit Program. May 25, 2005. Available online at .
30 Schueneman, T. (2001) Telephone conversation between Caren Mintz of ICF Consulting and Tom Schueneman,
31 Palm Beach County Agricultural Extension Agent, Florida. 30 July.
32 Schueneman, T. (1999a) Telephone conversation between Catherine Leining of ICF Consulting and Tom
33 Schueneman, Palm Beach County Agricultural Extension Agent, Florida. 7 June.
34 Schueneman, T. (1999b) Telephone conversation between Payton Deeks of ICF Consulting and Tom Schueneman,
35 Palm Beach County Agricultural Extension Agent, Florida. 10 August.
36 Schueneman, T.J. and C.W. Deren (2002) "An Overview of the Florida Rice Industry" SS-AGR-77, Agronomy
37 Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of
References 11-67
-------
Public Review Draft
1 Florida. Revised November 2002.
2 Stansel, J. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Dr. Jim Stansel, Resident
3 Director and Professor Emeritus, Texas A&M University Agricultural Research and Extension Center. July.
4 Stansel, J. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Dr. Jim Stansel, Resident
5 Director and Professor Emeritus, Texas A&M University Agricultural Research and Extension Center. 12 July.
6 Street, J. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Joe Street, Rice Specialist,
7 Mississippi State University, Delta Research Center. 19 June.
8 Street, J. (2002) Telephone conversation and email correspondence between Caren Mintz of ICF Consulting and Joe
9 Street, Rice Specialist, Mississippi State University, Delta Research Center, August 19, 2002.
10 Street, J. (2001) Telephone conversation and email correspondence between Caren Mintz of ICF Consulting and Joe
11 Street, Rice Specialist, Mississippi State University, Delta Research Center. 1 August.
12 Strehler, A., and W. Stiitzle (1987) "Biomass Residues." In: Hall, D.O. and Overend, R.P. (eds.) Biomass. John
13 Wiley and Sons, Ltd. Chichester, UK.
14 Turn, S.Q., B.M. Jenkins, J.C. Chow, L.C. Pritchett, D. Campbell, T. Cahill, and S.A. Whalen (1997) "Elemental
15 characterization of particulate matter emitted from biomass burning: Wind tunnel derived source profiles for
16 herbaceous and wood fuels." Journal of Geophysical Research 102(D3):3683-3699.
17 University of California (1977) Emission Factors From Burning of Agricultural Waste Collected in California.
18 University of California, Davis.
19 USDA (2006) Crop Production 2005 Summary. National Agricultural Statistics Service, U.S. Department of
20 Agriculture. Available online at . Accessed July 2006.
21 USDA (2005) Crop Production 2004 Summary. National Agricultural Statistics Service, U.S. Department of
22 Agriculture. Available online at . Accessed June 2005.
23 USDA (2003) Field Crops, Final Estimates 1997-2002. Statistical Bulletin No. 982. National Agricultural
24 Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture, Washington, DC. Available online
25 at . Accessed September 2005.
26 USDA (1998) Field Crops, Final Estimates 1992-1997. Statistical Bulletin No. 947a. National Agricultural
27 Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture, Washington, DC. Available online
28 at .
29 USDA (1994) Field Crops, Final Estimates 1987-1992. Statistical Bulletin No. 896. National Agricultural
30 Statistics Service, Agricultural Statistics Board, U.S. Department of Agriculture, Washington, DC. Available online
31 at .
32 Walker, T. (2006). Telephone conversation between Lauren Flinn of ICF International and Tim Walker, Assistant
33 Research Professor, Mississippi State University Delta Branch Exp. Station, 17 August.
34 Walker, T. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Tim Walker, Assistant
35 Research Professor, Mississippi State University Delta Branch Exp. Station. July.
36 Walker, T. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Tim Walker, Assistant
37 Research Professor, Mississippi State University Delta Branch Exp. Station. July 12, 2004.
11-68 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Wilson, C. (2006) Email coorespondence between Lauren Flinn of ICF International and Dr. Chuck Wilson, Rice
2 Specialist at the University of Arkansas Cooperative Extension Service. (870) 673-2661. Wilson@uamont.edu. 8
3 August.
4 Wilson, C. (2005) Email correspondence between Lauren Flinn of ICF Consulting and Dr. Chuck Wilson, Rice
5 Specialist at the University of Arkansas Cooperative Extension Service. July 2005.
6 Wilson, C. (2004) Telephone conversation between Lauren Flinn of ICF Consulting and Dr. Chuck Wilson, Rice
7 Specialist at the University of Arkansas Cooperative Extension Service. 23 June.
8 Wilson, C. (2003) Telephone conversation between Caren Mintz of ICF Consulting and Dr. Chuck Wilson, Rice
9 Specialist, University of Arkansas Cooperative Extension Service. 11 June.
10 Wisconsin Department of Natural Resources (1993) Wisconsin Greenhouse Gas Emissions: Estimates for 1990.
11 Bureau of Air Management, Wisconsin Department of Natural Resources, Madison, WI.
12 Land Use, Land-Use Change, and Forestry
13 IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry. J. Penman and others,
14 editors. IPCC National Greenhouse Gas Inventories Programme. Copy at , August 13, 2004.
16 Forest Land Remaining Forest Land: Changes in Forest Carbon Stock
17 Barlaz, M.A. (1998) "Carbon storage during biodegradation of municipal solid waste components in laboratory-
18 scale landfills." Global Biogeochemical Cycles 12 (2), 373-380.
19 Eleazer, W.E., W.S. Odle, III, Y.S. Wang, and M.A. Barlaz (1997) "Biodegradability of municipal solid waste
20 components in laboratory-scale landfills." Env. Sci. Tech. 31(3):911-917.
21 EPA (2006) Municipal solid waste in the United States: 2005 Facts and figures. Office of Solid Waste (5306P)
22 EPA530-R-06-011. Washington, DC. 164 p. Available online at .
23 Freed, R. (2004) Open-dump and Landfill timeline spreadsheet (unpublished). ICF Consulting, Washington, DC.
24 Melosi, M. (1981): Garbage in The Cities: Refuse Reform and the Environment: 1880-1980, Texas A&M Press.
25 Melosi, M. (2000): The Sanitary City. Johns Hopkins University Press, Baltimore, MD.
26 Micales, J. A. and K.E. Skog (1997) The decomposition of forest products in landfills. International Biodeterioration
27 & Biodegradation. 39(2-3): 145-158.
28 AF&PA. 2006a (and earlier). Statistical roundup. (Monthly). Washington, DC: American Forest & Paper
29 Association.
30 AF&PA. 2006b (and earlier). Statistics of paper, paperboard and wood pulp. Washington, DC: American Forest &
31 Paper Association. 86 p.
32 Amichev, B. Y. and J. M. Galbraith (2004) A Revised Methodology for Estimation of Forest Soil Carbon from
33 Spatial Soils and Forest Inventory Data Sets. Environmental Management 33, Supplement 1: S74-S86.
34 Birdsey, R.A., and L.S. Heath (1995) "Carbon Changes in U.S. Forests." In: Productivity of America's Forests and
35 Climate Change. Gen. Tech. Rep. RM-271. Rocky Mountain Forest and Range Experiment Station, Forest
36 Service, U.S. Department of Agriculture, Fort Collins, CO, pp. 56-70.
References 11-69
-------
Public Review Draft
1 Birdsey, R. (1996) "Carbon Storage for Major Forest Types and Regions in the Conterminous United States". Pages
2 1-26 and 261-379 (appendices 262 and 263) in R. N. Sampson and D. Hair, editors. Forest and Global Change,
3 Volume 2: Forest Management Opportunities for Mitigating Carbon Emissions. American Forests, Washington DC.
4 Birdsey, R., and L. S. Heath (2001) Forest Inventory Data, Models, and Assumptions for Monitoring Carbon Flux.
5 Pages 125-135 in Soil Carbon Sequestration and the Greenhouse Effect. Soil Science Society of America, Madison,
6 WI.
7 Birdsey, R. A., and G. M. Lewis (2003) Current and Historical Trends in Use, Management, and Disturbance of U.
8 S. Forestlands. Pages 15-34 in J. M. Kimble, L. S. Heath, R. A. Birdsey, and R. Lai, editors. The Potential of U.S.
9 Forest Soils to Sequester Carbon and Mitigate the Greenhouse Effect. CRC Press, New York.
10 EPA (2006) Inventory ofU. S. Greenhouse Gas Emissions and Sinks: 1990-2004. EPA, Office of Atmospheric
11 Programs, Washington, DC, U. S. A.
12 Frayer, W.E., and G.M. Furnival (1999) "Forest Survey Sampling Designs: A History." Journal of Forestry 97(12):
13 4-10.
14 Gillespie, A.J.R. (1999) "Rationale for a National Annual Forest Inventory Program." Journal of Forestry 97(12):
15 16-20.
16 Hair. D. and Ulrich, A.H. (1963) The Demand and price situation for forest products - 1963. USDA Forest Service,
17 Misc Publication No. 953. Washington, DC. 50 p.
18 Hair, Dwight. (1958) Historical forestry statistics of the United States. Statistical Bull. 228. Washington, DC: U.S.
19 Department of Agriculture, Forest Service. 36 p.
20 Heath, L. S., and J.E. Smith (2000) "Soil Carbon Accounting and Assumptions for Forestry and Forest-related
21 LandUse Change." In: The Impact of Climate Change on America's Forests. Joyce, L.A., and Birdsey, R.A. Gen.
22 Tech. Rep. RMRS-59. Rocky Mountain Research Station, Forest Service, U.S. Department of Agriculture, Fort
23 Collins, CO, pp. 89-101.
24 Heath, L.S., J.E., Smith, and R.A. Birdsey (2003) Carbon Trends in U. S. Forestlands: A Context for the Role of
25 Soils in Forest Carbon Sequestration. Pages 35-45 in J. M. Kimble, L. S. Heath, R. A. Birdsey, and R. Lai, editors.
26 The Potential of U. S. Forest Soils to Sequester Carbon and Mitigate the Greenhouse Effect. Lewis Publishers
27 (CRC Press), Boca Raton, FL.
28 Heath, L.S., (2006a) E-mail correspondence between Linda Heath, USFS, and Kimberly Klunich, EPA regarding
29 the 95 percent CI for forest area estimates (+/-0.24%) and average carbon density for Lower 48 States (+/-0. 4%),
30 October 26.
31 Heath, L.S., (2006b) E-mail correspondence between Linda Heath, USFS, and Kimberly Klunich, EPA regarding
32 the 95 percent CI for average carbon density for Alaska (+/-1.2%), October 27.
33 Howard, James L. (2003) U.S. timber production, trade, consumption, and price statistics 1965 to 2002. Res. Pap.
34 FPL-RP-615. Madison, WI: USDA, Forest Service, Forest Products Laboratory. 90 p.
3 5 http://www.fpl.fs.fed.us/documnts/fplrp/fplrp615/fplrp615 .pdf
36 Howard, James L. (forthcoming) U.S. timber production, trade, consumption, and price statistics 1965 to 2005. Res.
37 Pap. FPL-RP-XXX. Madison, WI: USDA, Forest Service, Forest Products Laboratory.
38 IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry. J. Penman and others,
39 editors. IPCC National Greenhouse Gas Inventories Programme. Availible online at , Accessed September 2005.
11-70 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
2 Greenhouse Gas Inventories Programme, Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds).
3 Published: IGES, Japan.
4 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories, Paris:
5 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
6 Co-Operation and Development, International Energy Agency. Paris, France.
7 Jenkins, J,C., D.C. Chojnacky, L.S. Heath, and R.A. Birdsey (2003) "National-scale biomass estimators for United
8 States tree species." Forest Science 49(1): 12-35.
9 Johnson, D. W., and P. S. Curtis (2001) Effects of Forest Management on Soil C and N Storage: Meta Analysis.
10 Forest Ecology and Management 140:227-238.
11 Perry, C.H., C. W. Woodall, and M. Schoeneberger (2005) Inventorying trees in agricultural landscapes: towards an
12 accounting of "working trees". In: Brooks, K.N. and Ffolliott, P.F. (eds) Moving Agroforestry into the Mainstream.
13 Proc. 9th N. Am. Agroforestry Conf., 12-15 June 2005, Rochester, MN [CD-ROM], Dept. of Forest Resources,
14 Univ. Minnesota, St. Paul, MN, 12 p. Available online at (verified 23 Sept
15 2006).
16 Phillips, D.L., S.L. Brown, P.E. Schroeder, and R.A. Birdsey (2000) Toward Error Analysis of Large-Scale Forest
17 Carbon Budgets. Global Ecology and Biogeography 9:305-313.
18 Skog, K.E., and G. A. Nicholson (1998) "Carbon Cycling Through Wood Products: The Role of Wood and Paper
19 Products in Carbon Sequestration." Forest Products Journal 48:75-83.
20 Skog, K.E., K. Pingoud, and J.E. Smith (2004) "A method countries can use to estimate changes in carbon stored in
21 harvested wood products and the uncertainty of such estimates." Environmental Management 33(Supplement
22 1):S65-S73.
23 Skog, K. E. (in preparation) Sequestration of carbon in harvested wood products for the United States.
24 Smith, J.E., and L.S. Heath (2002) "A model of forest floor carbon mass for United States forest types." Res. Paper
25 NE-722. USDA Forest Service, Northeastern Research Station, Newtowne Square, PA.
26 Smith, J. E., L. S. Heath, and J. C. Jenkins (2003) Forest Volume-to-Biomass Models and Estimates of Mass for
27 Live and Standing Dead Trees of U.S. Forests. General Technical Report NE-298, USDA Forest Service,
28 Northeastern Research Station, Newtown Square, PA.
29 Smith, J. E., L. S. Heath, and P. B. Woodbury (2004 a) "How to estimate forest carbon for large areas from
30 inventory data," Journal of Forestry 102:25-31.
31 Smith, W. B., P. D. Miles, J. S. Vissage, and S. A. Pugh (2004b) Forest Resources of the United States, 2002.
32 General Technical Report NC-241, USDA Forest Service, North Central Research Station, St. Paul, MN.
33 Smith, James E., Linda S. Heath, and Michael C. Nichols. (In preparation). U.S. Forest Carbon Calculation Tool
34 User's Guide: Forestland Carbon Stocks and Net Annual Stock Change. Gen Tech Report, USDA Forest Service,
3 5 Northern Research Station.
36 Steer, Henry B. (1948) Lumber production in the United States. Misc. Pub. 669. Washington, DC: U.S. Department
37 of Agriculture, Forest Service. 233 p.
38 Ulrich, Alice. (1985) U.S. timber production, trade, consumption, and price statistics 1950-1985. Misc. Pub. 1453.
39 Washington, DC: U.S. Department of Agriculture, Forest Service. 81 p.Ulrich, A.H. (1989) U.S. Timber
40 Production, Trade, Consumption, and Price Statistics, 1950-1987. USDA Miscellaneous Publication No. 1471,
References 11-71
-------
Public Review Draft
1 U.S. Department of Agriculture, Forest Service, Washington, DC, pp. 77.
2 USDC Bureau of Census. (1976) Historical Statistics of the United States, colonial times to 1970. Volume 1.
3 Washington, DC.
4 USDA Forest Service. (2006a) Forest inventory and analysis national program, FIA library. Available online at
5 . Accessed September 20, 2006.
6 USDA Forest Service. (2006b) Forest Inventory and Analysis Data Center. Available online at
7 . Accessed September 20, 2006.
8 USDA Forest Service. (2006c) FIA Data Mart: Download. Available online at
9 . Click on documentation link to download Users Guide
10 to the Forest Inventory Snapshot Database Version 2.1. Accessed September 20, 2006.
11 USDA (1991) State Soil Geographic (STATSG0) Data Base Data use information. Miscellaneous Publication
12 Number 1492, USDA, Natural Resources Conservation Service, National Soil Survey Center, Fort Worth, TX.
13 Woodbury, P.B., Heath, L.S., and Smith, J.E. (2006) Land Use Change Effects on Forest Carbon Cycling
14 Throughout the Southern United States. Journal of Environmental Quality. 35: 1348-1363.
15 Forest Land Remaining Forest Land: N20 Fluxes from Soils
16 Binkley, D. (2004) E-mail correspondence between Dan Binkley, Department of Forest, Rangeland, and Watershed
17 Stewardship, Colorado State University and Stephen Del Grosso, Natural Resource Ecology Laboratory, Colorado
18 State University regarding the 95% CI for area estimates of southern pine plantations receiving N fertilizer (±20%)
19 and the rate applied for areas receiving N fertilizer (100 to 200 pounds/acre), 19 September.
20 Binkley, D., R. Carter, and H.L. Allen (1995) Nitrogen Fertilization Practices in Forestry. In: Nitrogen Fertilization
21 in the Environment, P.E. Bacon (ed.), Marcel Decker, Inc., New York.
22 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
23 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
24 Published: IGES, Japan.
25 North Carolina State Forest Nutrition Cooperative (2002) 31st Annual Report. Available online at
26 . Accessed October 2004.
27 USDA Forest Service (2001) U.S. Forest Facts and Historical Trends. FS-696. Washington, DC: USDA Forest
28 Service 18p. Available online at .
29 Cropland Remaining Cropland, Land Converted to Cropland, Grassland Remaining Grassland, and Land
30 Converted to Grassland: Changes in Agricultural Soil Carbon Stocks
31 Allmaras, R.R., H.H. Schomberg, C.L. Douglas, Jr., and T.H. Dao (2000) "Soil organic carbon sequestration
32 potential of adopting conservation tillage in U.S. croplands." J Soil Water Conserv 55:365-373.
33 Armentano, T.V. and J.T. A. Verhoeven (1990) "Biogeochemical Cycles: Global." In: Wetlands and Shallow
34 Continental Water Bodies. Patten, B.C., et al. (eds.), pp. 281-311, SPB Academic Publishing, The Hague,
35 Netherlands, Volume I.
36 Barbarika, A. (2006) Conservation Reserve Program Summary and Enrollment Statistics - 2005. U.S. Department
37 of Agriculture, Farm Service Agency, Washington, D.C.
11-72 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Brady, N.C. and R.R. Weil (1999) The Nature and Properties of Soils. Prentice Hall, Upper Saddle River, New
2 Jersey, pp. 881.
3 CTIC (1998) "1998 Crop Residue Management Executive Summary," Conservation Technology Information
4 Center, West Lafayette, Indiana.
5 Daly, C., R.P. Neilson, and D.L. Phillips (1994) "A Statistical-Topographic Model for Mapping Climatological
6 Precipitation Over Mountainous Terrain." Journal of Applied Meteorology 33:140-158.
7 Edmonds, L., R. L. Kellogg, B. Kintzer, L. Knight, C. Lander, J. Lemunyon, D. Meyer, D. C. Moffitt, and J.
8 Schaefer. (2003) Costs associated with development and implementation of Comprehensive Nutrient Management
9 Plans. Part I—Nutrient management, land treatment, manure and wastewater handling and storage, and
10 recordkeeping. Natural Resources Conservation Service. U. S. Department of Agriculture. Available online at
11 .
12 EPA (1999) Biosolids Generation, Use and Disposal in the United States. Office of Solid Waste, U.S.
13 Environmental Protection Agency. Available online at .
14 EPA (1993) Federal Register. Part II. Standards for the Use and Disposal of Sewage Sludge; Final Rules. U.S.
15 Environmental Protection Agency, 40 CFR Parts 257, 403, and 503.
16 ERS. (1997) Cropping Practices Survey Data—1995. Economic Research Service, United States Department of
17 Agriculture. Available online at .
18 Euliss, N., and R. Gleason (2002) Wetland restoration factor estimates and restoration activity data compiled and
19 provided by Ned Euliss and Robert Gleason. USGS, Jamestown, North Dakota, to Stephen Ogle of the National
20 Resource Ecology Laboratory, Fort Collins, Colorado. August.
21 FAO (2006) Yearly U.S. total horse population data from the Food and Agriculture Organization of the United
22 Nations database. Available online at . Accessed July 2006.
23 FSA (2006) Conservation Reserve Program: Summary and Enrollment Statistics - 2005. US Department of
24 Agriculture, Farm Services Agency, Washington, D.C.
25 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
26 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
27 Published: IGES, Japan.
28 IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry. IPCC National Greenhouse
29 Gas Inventories Programme. Hayama, Kanagawa, Japan. Available online at .
31 IPCC/UNEP/OECD/IEA (1997) Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Paris:
32 Intergovernmental Panel on Climate Change, United Nations Environment Programme, Organization for Economic
33 Co-Operation and Development, International Energy Agency. Paris, France.
34 Kellogg, R.L., C.H. Lander, D.C. Moffitt, and N. Gollehon (2000) "Manure Nutrients Relative to the Capacity of
35 Cropland and Pastureland to Assimilate Nutrients: Spatial and Temporal Trends for the United States." U.S.
36 Department of Agriculture, Publication number nps00-0579, Washington, DC.
37 Lange, J. (2000) Telephone conversation between Lee-Ann Tracy of ERG and John Lange, Agricultural Statistician,
38 U. S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC, May 8, 2000.
39 Metherell, A.K., L.A. Harding, C.V. Cole, and W.J. Parton (1993) "CENTURY Soil Organic Matter Model
40 Environment." Agroecosystem version 4.0. Technical documentation, GPSR Tech. Report No. 4, USDA/ARS, Ft.
References 11-73
-------
Public Review Draft
1 Collins, CO.
2 NASS. (2004) Agricultural Chemical Usage: 2003 Field Crops Summary. Report AgChl(04)a. National
3 Agricultural Statistics Service. USD A. Available online at .
5 NASS (1999) Agricultural Chemical Usage: 1998 Field Crops Summary. Report AgCHl(99). National Agricultural
6 Statistics Service, USDA. Available online at .
8 NASS (1992) Agricultural Chemical Usage: 1991 Field Crops Summary. Report AgChl(92). National Agricultural
9 Statistics Service, USDA. Available online at .
11 NRCS (1999) "Soil Taxonomy: A basic system of soil classification for making and interpreting soil surveys, 2nd
12 Edition." Agricultural Handbook Number 436, USDA Natural Resources Conservation Service, Washington, DC.
13 NRCS (1997) "National Soil Survey Laboratory Characterization Data," Digital Data, USDA-NRCS, Lincoln, NE.
14 NRCS (1981) "Land Resource Regions and Major Land Resource Areas of the United States," USDA Agriculture
15 Handbook 296, United States Department of Agriculture, Natural Resources Conservation Service, National Soil
16 Survey Center, Lincoln, NE, pp. 156.
17 Ogle, S., M. Eve, M. Sperrow, F.J. Breidt, and K. Paustian (2002) Agricultural Soil C Emissions, 1990-2001:
18 Documentation to Accompany EPA Inventory Tables. Natural Resources Ecology Laboratory, Fort Collins, CO,
19 Provided in 23 September 2002 e-mail from S.M. Ogle to B.V. Braatz at ICF Consulting.
20 Ogle, S.M., M.D. Eve, F.J. Breidt, and K. Paustian (2003) "Uncertainty in estimating land use and management
21 impacts on soil organic carbon storage for U.S. agroecosystems between 1982 and 1997." Global Change Biology
22 9:1521-1542.
23 Ogle, S.M., F.J. Breidt, and K. Paustian. (2006) "Bias and variance in model results due to spatial scaling of
24 measurements for parameterization in regional assessments." Global Change Biology 12:516-523.
25 Ogle, S.M., F.J. Breidt, M. Easter, S. Williams and K. Paustian. (2007) "Empirically-Based Uncertainty Associated
26 with Modeling Carbon Sequestration Rates in Soils." Ecological Modeling, accepted.
27 Parton, W.J., D.S. Schimel, C.V. Cole, D.S. Ojima (1987) "Analysis of factors controlling soil organic matter levels
28 in Great Plains grasslands." Soil Science Society of America Journal 51:1173-1179.
29 Parton, W.J., J.W.B. Stewart, C.V. Cole. (1988) "Dynamics of C, N, P, and S in grassland soils: a model."
30 Biogeochemistry 5:109-131.
31 Parton, W.J., D.S. Ojima, C.V. Cole, and D.S. Schimel (1994) "A General Model for Soil Organic Matter
32 Dynamics: Sensitivity to litter chemistry, texture and management." In: Quantitative Modeling of Soil Forming
33 Processes, Special Publication 39, pp. 147-167., Soil Science Society of America, Madison, WI.
34 Potter, C. S., J.T. Randerson, C.B. Fields, P.A. Matson, P.M. Vitousek, H.A. Mooney, and S.A. Klooster. (1993)
35 Terrestrial ecosystem production: a process model based on global satellite and surface data. Global
36 Biogeochemical Cycles 7:811-841.
37 Reilly, J.M. and K.O. Fuglie. (1998) "Future yield growth in field crops: What evidence exists?" Soil Till Res
38 47:275-290.
11-74 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Tepordei, V.V. (2006) "Crashed Stone," In: Minerals Yearbook 2004. U.S. Department of the Interior/U.S.
2 Geological Survey, Washington, DC. Available online at
3 . Accessed August 2006.
4 Tepordei, V.V. (2005) "Crashed Stone," In: Minerals Yearbook 2003. U.S. Department of the Interior/U.S.
5 Geological Survey, Washington, DC. Available online at
6 . Accessed August 2005.
7 Tepordei, V.V. (2004) "Crashed Stone," In: Minerals Yearbook 2002. U.S. Department of the Interior/U.S.
8 Geological Survey, Washington, DC. Available online at
9 . Accessed August 2004.
10 Accessed August 2004.
11 Tepordei, V.V. (2003) "Crashed Stone," In: Minerals Yearbook 2001. U.S. Department of the Interior/U.S.
12 Geological Survey, Washington, DC. Available online at
13 . Accessed June 2003.
14 Tepordei, V.V. (2002) "Crashed Stone," In: Minerals Yearbook 2000. U.S. Department of the Interior/U.S.
15 Geological Survey, Washington, DC. Available online at
16 . Accessed September 2002.
17 Tepordei, V.V. (2001) "Crashed Stone," In: Minerals Yearbook 1999. U.S. Department of the Interior/U.S.
18 Geological Survey, Washington, DC. Available online at
19 . Accessed August 2001.
20 Tepordei, V.V. (2000) "Crashed Stone," In: Minerals Yearbook 1998. U.S. Department of the Interior/U.S.
21 Geological Survey, Washington, DC. Available online at
22 . Accessed August 2000.
23 Tepordei, V.V. (1999) "Crashed Stone," In: Minerals Yearbook 1997. U.S. Department of the Interior/U.S.
24 Geological Survey, Washington, DC. Available online at
25 . Accessed August 2000.
26 Tepordei, V.V. (1998) "Crashed Stone," In: Minerals Yearbook 1996. U.S. Department of the Interior/U.S.
27 Geological Survey, Washington, DC. Available online at
28 . Accessed August 2000.
29 Tepordei, V.V. (1997) "Crashed Stone," In: Minerals Yearbook 1995. U.S. Department of the Interior/U.S.
30 Geological Survey, Washington, DC. pp. 783-809. Available online at
31 .
32 Tepordei, V.V. (1996) "Crashed Stone," In: Minerals Yearbook 1994. U.S. Department of the Interior/Bureau of
33 Mines, Washington, DC. Available online at
34 . Accessed August 2000.
35 Tepordei, V.V. (1995) "Crashed Stone," In: Minerals Yearbook 1993. U.S. Department of the Interior/Bureau of
36 Mines, Washington, DC, pp. 1107-1147.
37 Tepordei, V. V. (1994) "Crashed Stone," In: Minerals Yearbook 1992. U.S. Department of the Interior/Bureau of
38 Mines, Washington, DC, pp. 1279-1303.
39 Tepordei, V.V. (1993) "Crashed Stone," In: Minerals Yearbook 1991. U.S. Department of the Interior/Bureau of
40 Mines, Washington, DC, pp. 1469-1511.
41 Towery, D. (2001) Adjustments to the CTIC (1998) tillage data to reflect long-term trends provided by Dan Towery
References 11-75
-------
Public Review Draft
1 of the Conservation Technology Information Center, West Lafayette, Indiana, to Marlen Eve of the National
2 Resource Ecology Laboratory, Fort Collins, CO. February.
3 USDA (2005a) Cattle, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington, DC.
4 January 28, 2005. Data also available from .
5 USDA (2005b) Cattle on Feed, U.S. Department of Agriculture, National Agriculture Statistics Service,
6 Washington, DC. January 21, 2005. Data also available from .
7 USDA (2005c) Hogs and Pig, U.S. Department of Agriculture, National Agriculture Statistics Service, Washington,
8 DC. March 24, 2005. Data also available from .
9 USDA (2005d) Chicken and Eggs Annual Summary, U.S. Department of Agriculture, National Agriculture
10 Statistics Service, Washington, DC. February 2005. Data also available from
11 .
12 USDA (2005e) Poultry Production and Value Annual Summary, U.S. Department of Agriculture, National
13 Agriculture Statistics Service, Washington, DC. April 28, 2005. Data also available from
14 .
15 USDA (2005f) Sheep and Goats, U.S. Department of Agriculture, National Agriculture Statistics Service,
16 Washington, DC. January 28, 2005. Data also available from .
17 USDA (2005g) Census of Agriculture, U.S. Department of Agriculture, National Agriculture Statistics Service,
18 Washington, DC. Data for 1992, 1997, and 2002 available from in June 2005.
19 USDA (2004a) Cattle—Final Estimates 1999-2003, U.S. Department of Agriculture, National Agriculture Statistics
20 Service, Washington, DC. April. Data also available from .
21 USDA (2004b) Hogs and Pigs—Final Estimates 1998-2002, U.S. Department of Agriculture, National Agriculture
22 Statistics Service, Washington, DC. March. Data also available from
23 .
24 USDA (2004c) Chicken and Eggs—Final Estimates 1998-2003, U.S. Department of Agriculture, National
25 Agriculture Statistics Service, Washington, DC. April. Data also available from
26 .
27 USDA (2004d) Poultry Production and Value—Final Estimates 1998-2002, U.S. Department of Agriculture,
28 National Agriculture Statistics Service, Washington, DC. April. Data also available from
29 .
30 USDA (2004e) Sheep and Goats—Final Estimates 1999-2003, U.S. Department of Agriculture, National
31 Agriculture Statistics Service, Washington, DC. April. Data also available from
32 .
33 USDA (2000) Chicken and Eggs—Final Estimates 1988-1993, U.S. Department of Agriculture, National
34 Agriculture Statistics Service, Washington, DC. Downloaded from , May 3, 2000.
36 USDA (1999a) Cattle—Final Estimates 1994-98. National Agriculture Statistics Service, U.S. Department of
37 Agriculture, Washington, DC. January. Available online at .
38 USDA (1999b) Poultry Production and Value—Final Estimates 1994-97. National Agriculture Statistics Service,
39 U.S. Department of Agriculture, Washington, DC. March.
11-76 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 USDA (1999c) Sheep and Goats—Final Estimates 1994-1998. National Agriculture Statistics Service, U.S.
2 Department of Agriculture, Washington, DC. January.
3 USDA (1998a) Chicken and Eggs—Final Estimates 1994-97. National Agriculture Statistics Service, U.S.
4 Department of Agriculture, Washington, DC. December.
5 USDA (1998b) Hogs and Pigs—Final Estimates 1993-97. National Agriculture Statistics Service, U.S. Department
6 of Agriculture, Washington, DC. December. Available online at .
7 USDA (1995a) Cattle—Final Estimates 1989-93. National Agriculture Statistics Service, U.S. Department of
8 Agriculture, Washington, DC. January. Available online at .
9 USDA (1995b) Poultry Production and Value—Final Estimates 1989-1993. National Agriculture Statistics
10 Service, U.S. Department of Agriculture, Washington, DC.
11 USDA (1994a) Hogs and Pigs—Final Estimates 1988-92. National Agriculture Statistics Service, U.S. Department
12 of Agriculture, Washington, DC. December. Available online at .
13 USDA (1994b) Sheep and Goats—Final Estimates 1989-1993. National Agriculture Statistics Service, U.S.
14 Department of Agriculture, Washington, DC. January.
15 USDA-NRCS (2000) Digital Data And Summary Report: 1997 National Resources Inventory. Revised December
16 2000. United States Department of Agriculture, Natural Resources Conservation Service, Resources Inventory
17 Division, Beltsville, MD.
18 USGS (2005) Mineral Industry Surveys: Crushed Stone and Sand and Gravel in the First Quarter of2005. U.S.
19 Geological Survey, Reston, VA. Available online at
20 .
21 West, T.O., and A.C. McBride (2005) "The contribution of agricultural lime to carbon dioxide emissions in the
22 United States: dissolution, transport, and net emissions," Agricultural Ecosystems & Environment 108:145-154.
23 Settlements Remaining Settlements: Changes in Carbon Stocks in Urban Trees
24 Cairns, M.A., S. Brown, E.H. Helmer, and G.A. Baumgardner (1997) "Root Biomass Allocation in the World's
25 Upland Forests." Oceologia 111: 1-11.
26 deVries, R.E. (1987) A Preliminary Investigation of the Growth and Longevity of Trees in Central Park. New
27 Brunswick, NJ: Rutgers University, M.S. thesis.
28 Dwyer, J.F., D.J. Nowak, M.H. Noble, and S.M Sisinni (2000) Connecting People with Ecosystems in the 21st
29 Century: An Assessment of Our Nation's Urban Forests. General Technical Report PNW-GTR-490, U.S.
30 Department of Agriculture, Forest Service, Pacific Northwest Research Station, Portland, OR.
31 Fleming, L.E. (1988) Growth Estimation of Street Trees in Central New Jersey. New Brunswick, NJ: Rutgers
32 University, M.S. thesis. IPCC/UNEP/OECD/IEA (1997) Revised 1996IPCC Guidelines for National Greenhouse
33 Gas Inventories, Paris: Intergovernmental Panel on Climate Change, United Nations Environment Programme,
34 Organization for Economic Co-Operation and Development, International Energy Agency. Paris, France.
35 IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry. IPCC National Greenhouse
36 Gas Inventories Programme. Hayama, Kanagawa, Japan. Available online at .
38 Nowak, D.J. (2002a) E-mail from David Nowak of the USDA Forest Service to Barbara Braatz at ICF Consulting,
39 containing information on possible urban tree carbon and forest carbon overlap, January 10, 2002.
References 11-77
-------
Public Review Draft
1 Nowak, D.J. (2002b) E-mail from David Nowak of the USDA Forest Service to Barbara Braatz at ICF Consulting,
2 regarding significant digits, October 29, 2002.
3 Nowak, D.J. (1994) "Atmospheric Carbon Dioxide Reduction by Chicago's Urban Forest." In: McPherson, E.G.,
4 Nowak, D. J., and Rowntree, R.A. (eds.) Chicago's Urban Forest Ecosystem: Results of the Chicago Urban Forest
5 Climate Project. USDA Forest Service General Technical Report NE-186, Radnor, PA, pp. 83-94.
6 Nowak, D. J., (1986) "Silvics of an Urban Tree Species: Norway Maple (Acer platanoides L.)." Syracuse, NY: State
7 University of New York, College of Environmental Science and Forestry, M.S. thesis.
8 Nowak, D.J. and D.E. Crane (2002) "Carbon Storage and Sequestration by Urban Trees in the United States."
9 Environmental Pollution 116(3): 381-389.
10 Nowak, D.J., D.E. Crane, J.C. Stevens, and M. Ibarra (2002) Brooklyn's Urban Forest, USDA Forest Service
11 General Technical Report NE-290, Newtown Square, PA.
12 Nowak, D.J., M.H. Noble, S.M. Sisinni, and J.F. Dwyer (2001) "Assessing the U.S. Urban Forest Resource."
13 Journal of Forestry. 99(3): 37-42.
14 Nowak, D.J., J.T. Walton, L.G. Kaya, and J.F. Dwyer (2005) "The Increasing Influence of Urban Environments on
15 U.S. Forest Management." Journal of Forestry.
16 Smith, W.B. and S.R. Shifley (1984) Diameter Growth, Survival, and Volume Estimates for Trees in Indiana and
17 Illinois. Res. Pap. NC-257. St. Paul, MN: U.S. Department of Agriculture, Forest Service, North Central Forest
18 Experiment Station.
19 Settlements Remaining Settlements: Changes in Yard Trimming and Food Scrap Carbon Stocks in Landfills
20 Barlaz, M.A. (1998) "Carbon Storage during Biodegradation of Municipal Solid Waste Components in Laboratory -
21 Scale Landfills." Global Biogeochemical Cycles 12: 373-380.
22 Barlaz, M.A. (2005) "Decomposition of Leaves in Simulated Landfill." Letter report to Randall Freed, ICF
23 Consulting, June 29, 2005
24 Eleazer, W.E., W.S. Odle, Y. Wang, and M. Barlaz (1997) "Biodegradability of Municipal Solid Waste
25 Components in Laboratory-Scale Landfills" Environmental Science Technology, 31: 911-917.
26 EPA (2005) Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and Figures
27 for 2003 Facts and Figures. U.S. Environmental Protection Agency, Office of Solid Waste and Emergency
28 Response, Washington, DC. Available online at .
30 EPA (2005a) Municipal Solid Waste in the United States: 2003 Data Tables. U.S. Environmental Protection
31 Agency, Office of Solid Waste and Emergency Response, Washington, DC. Available online at
32 .
33 EPA (2003) Characterization of Municipal Solid Waste in the United States: 2001 Update. (Draft) U.S.
34 Environmental Protection Agency, Office of Solid Waste and Emergency Response, EPA. Washington, DC.
35 EPA (1999) Characterization of Municipal Solid Waste in the United States: 1998 Update. U.S. Environmental
36 Protection Agency, Office of Solid Waste and Emergency Response, Washington, DC.
37 IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change, and Forestry. IPCC National Greenhouse
38 Gas Inventories Programme. Hayama, Kanagawa, Japan. Available online at .
11-78 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
2 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
3 Published: IGES, Japan.
4 Oshins, C., and D. Block (2000) "Feedstock Composition at Composting Sites." Biocycle 41(9):31-34.
5 Schneider, S. (2007) E-mail between Shelly Schneider of Franklin Associates, A Division of ERG and Sarah
6 Shapiro of ICF International, January 10, 2007.
7 Tchobanoglous, G., H. Theisen, and S. A. Vigil (1993) Integrated Solid Waste Management, 1st edition. McGraw-
8 Hill, NY. Cited by Barlaz (1998).
9 Settlements Remaining Settlements: N20 Fluxes from Soils
10 AAPFCO (2006) Commercial Fertilizers 2005. Association of American Plant Food Control Officials and The
11 Fertilizer Institute, University of Kentucky, Lexington, KY.
12 AAPFCO (2005) Commercial Fertilizers 2004. Association of American Plant Food Control Officials and The
13 Fertilizer Institute, University of Kentucky, Lexington, KY.
14 AAPFCO (2004) Commercial Fertilizers 2003. Association of American Plant Food Control Officials and The
15 Fertilizer Institute, University of Kentucky, Lexington, KY.
16 AAPFCO (2003) Commercial Fertilizers 2002. Association of American Plant Food Control Officials and The
17 Fertilizer Institute, University of Kentucky, Lexington, KY.
18 AAPFCO (2002) Commercial Fertilizers 2001. Association of American Plant Food Control Officials and The
19 Fertilizer Institute, University of Kentucky, Lexington, KY.
20 AAPFCO (2000a) 1999-2000 Commercial Fertilizers Data. ASCII files. Available: David Terry, Secretary,
21 AAPFCO.
22 AAPFCO (2000b) Commercial Fertilizers 2000. Association of American Plant Food Control Officials, University
23 of Kentucky, Lexington, KY.
24 AAPFCO (1999) Commercial Fertilizers 1999. Association of American Plant Food Control Officials, University
25 of Kentucky, Lexington, KY.
26 AAPFCO (1998) Commercial Fertilizers 1998. Association of American Plant Food Control Officials, University
27 of Kentucky, Lexington, KY.
28 AAPFCO (1997) Commercial Fertilizers 1997. Association of American Plant Food Control Officials, University
29 of Kentucky, Lexington, KY.
30 AAPFCO (1996) Commercial Fertilizers 1996. Association of American Plant Food Control Officials, University
31 of Kentucky, Lexington, KY.
32 AAPFCO (1995) Commercial Fertilizers 1995. Association of American Plant Food Control Officials, University
33 of Kentucky, Lexington, KY.
34 IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
35 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
36 Published: IGES, Japan.
37 Qian, Y. (2004) Meeting between Yaling Qian of Horticulture and Landscape Architecture Department, Colorado
References 11-79
-------
Public Review Draft
1 State University and William Patron and Stephen Del Grosso of Natural Resource Ecology Laboratory, Colorado
2 State University, regarding the percentage of national fertilizer applied to turf grass (10% of national N) and the
3 confidence interval for this estimate (-50 to +20%), September 17, 2004.
4
TVA
(1991) Commercial Fertilizers
1991.
Tennessee
Valley
Authority,
Muscle
Shoals,
AL
5
TVA
(1992) Commercial Fertilizers
1992.
Tennessee
Valley
Authority,
Muscle
Shoals,
AL
6
TVA
(1993) Commercial Fertilizers
1993.
Tennessee
Valley
Authority,
Muscle
Shoals,
AL
7
TVA
(1994) Commercial Fertilizers
1994.
Tennessee
Valley
Authority,
Muscle
Shoals,
AL
8 Waste
9 Landfills
10 40 CFR Part 60, Subpart Cc (2005) Emission Guidelines and Compliance Times for Municipal Solid Waste
11 Landfills, 60.30c--60.36c, Code of Federal Regulations, Title 40. Available online at
12 .
13 40 CFR Part 60, Subpart WWW (2005) Standards of Performance for Municipal Solid Waste Landfills, 60.750—
14 60.759, Code of Federal Regulations, Title 40. Available online at
15 .
16 Barlaz, M. A. (2005) "Decomposition of Leaves in Simulated Landfill." Letter report to Randall Freed, ICF
17 Consulting, June 29, 2005
18 Barlaz, M.A. (1998) "Carbon Storage during Biodegradation of Municipal Solid Waste Components in Laboratory -
19 Scale Landfills." Global Biogeochemical Cycles 12: 373-380.
20 Bingemer, H. and J. Crutzen (1987) "The Production of Methane from Solid Wastes," Journal of Geophysical
21 Research, 92:2181-2187.
22 BioCycle (2006) "15th Annual BioCycle Nationwide Survey: The State of Garbage in America," P. Simmons, N.
23 Goldstein, S. Kaufman, N. Goldstein, N. Themelis, and J. Thompson. April.
24 Czepiel, P., B. Mosher, P. Ciill, and R. Harriss (1996) "Quantifying the Effect of Oxidation on Landfill Methane
25 Emissions," Journal of Geophysical Research, 101( Dll): 16721-16730.
26 Energy Information Agency (EIA) (2006) Voluntary Greenhouse Gas Reports for EIA Form 1605B (Reporting
27 Year 2004). Database available at .
28 EPA (2006) Landfill Gas-to-Energy Project Database, Landfill Methane and Outreach Program. July.
29 EPA (2005) Municipal Solid Waste in the United States: 2003 Facts and Figures, U.S. Environmental Protection
30 Agency, Office of Solid Waste and Emergency Response, Washington, DC. Available at
31 .
32 EPA (1998) Compilation of Air Pollution Emission Factors, Publication AP-42, Section 2.4 Municipal Solid Waste
33 Landfills. November.
34 EPA (1993) Anthropogenic Methane Emissions in the United States, Estimates for 1990: Report to Congress, U.S.
35 Environmental Protection Agency, Office of Air and Radiation, Washington, DC. EPA/430-R-93-003. April.
11-80 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 EPA (1988) National Survey of Solid Waste (Municipal) Landfill Facilities, U.S. Environmental Protection Agency,
2 Washington, DC. EPA/530-SW-88-011. September.
3 IPCC (2006) 2006IPCC Guidelines for National Greenhouse Gas Inventories, Prepared by the National
4 Greenhouse Gas Inventories Programme, Eggleston H.S., Buenida L., Miwa K., Ngara T., and Tanabe K. (eds.)
5 Published: IGES, Japan.
6 IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change and Forestry. Prepared by the National
7 Greenhous Gas Inventories Programme, Penman J., Gytarsky M., Hiraiski T., Krug T., Kruger D., Pipatti R.,
8 Buendia L., Miwa K., Ngara T., Tanabe K. and Wagner F. (eds). IGES, Japan.
9 Mancinelli, R. and C. McKay (1985) "Methane-Oxidizing Bacteria in Sanitary Landfills," Proceedings of the First
10 Symposium on Biotechnical Advances in Processing Municipal Wastes for Fuels and Chemicals, August 1984,
11 Minneapolis, Minnesota, pp. 437-450.
12 Peer, R., S. Thorneloe, and D. Epperson (1993) "A Comparison of Methods for Estimating Global Methane
13 Emissions from Landfills," Chemosphere, 26(1-4): 387-400.
14 RTI (2004) Documentation for Changes to the Methodology for the Inventory of Methane Emissions from
15 Landfills. September.
16 Solid Waste Association of North America (SWANA) (1998) "Comparison of Models for Predicting Landfill
17 Methane Recovery, " Publication No. GR-LG 0075, March.
18 U.S. Bureau of Census (2006) International Data Base. Available online at
19 April.
20 Wastewater Treatment
21 ARCADIS (2004) Memorandum from M.Doorn ARCADIS to D. Pape, ICF and E. Scheehle, EPA, "Response to
22 ERG Review and New US M&P estimates," dd. 16 August, 2004.
23 Doom, M., and E. Scheehle (2002) Estimate of U.S. Methane Emissions from Industrial Wastewater; Enhancing
24 Completeness of the Annual National Greenhouse Gas Inventory. Third Int. Symposium on Non-C02 Greenhouse
25 Gases (NCGG-3), Maastricht, Netherlands, 21-23 Jan., 2002.
26 Eckenfelder, W.W. (1980) Principles of Water Quality Management. CBI Publishing Company, Inc. Boston MA.
27 1980.
28 EPA (1974) Development Document for Effluent Limitations Guidelines and New Source Performance Standards
29 for the Apple, Citrus, and Potato Processing Segment of the Canned and Preserved Fruits and Vegetables Point
30 Source Category. Office of Water. EPA-440/l-74-027-a, Washington DC, March.
31 EPA (1992) Clean Watersheds Needs Survey 1992 - Report to Congress. Office of Wastewater Management,
32 Washington, DC.
33 EPA (1993a) Anthropogenic Methane Emissions in the U.S.: Estimates for 1990, Report to Congress. Office of Air
34 and Radiation, Washington, DC. April.
35 EPA (1993b) Development Document for the Proposed Effluent Limitations Guidelines and Standards for the Pulp,
36 Paper andPaperboardPoint Source Category. EPA-821-R-93-019. Office of Water, Washington, DC, October.
37 EPA (1996) 1996 Clean Water Needs Survey Report to Congress. Assessment of Needs for Publicly Owned
3 8 Wastewater Treatment Facilities, Correction of Combined Sewer Overflows, and Management of Storm Water and
39 Nonpoint Source Pollution in the United States. Office of Wastewater Management, Washington, DC. Downloaded
References 11-81
-------
Public Review Draft
1 from: .
2 EPA (1997a) Estimates of Global Greenhouse Gas Emissions from Industrial and Domestic Wastewater Treatment.
3 Office of Policy, Planning, and Evaluation. EPA-600/R-97-091, Washington, DC, September.
4 EPA (1997b) Supplemental Technical Development Document for Effluent Guidelines and Standards (Subparts B &
5 E). EPA-821-R-97-011. United States Environmental Protection Agency, Office of Water, Washington, DC,
6 October, 1997.
7 EPA (1998) "AP-42 Compilation of Air Pollutant Emission Factors." Chapter 2.4, Table 2.4-3, page 2.4-13.
8 Downloaded from: .
9 EPA (2000) Clean Watersheds Needs Survey 2000 - Report to Congress. Office of Wastewater Management,
10 Washington, DC. Downloaded from: .
11 EPA (2002) Development Document for the Proposed Effluent Limitations Guidelines and Standards for the Meat
12 and Poultry Products Industry Point Source Category (40 CFR 432). Office of Water. EPA-821-B-01-007,
13 Washington DC, January 2002.
14 EPA (2004a) Clean Watersheds Needs Survey 2004 - Report to Congress. Office of Wastewater Management,
15 Washington, DC.
16 EPA (2004b) Technical Development Document for the Final Effluent Limitations Guidelines and Standards for the
17 Meat and Poultry Products Point Source Category (40 CFR 432). Office of Water. EPA-821-R-04-011,
18 Washington DC, July.
19 FAO (2006) FAOSTAT Statistical Database, United Nations Food and Agriculture Organization. Available online
20 at: , accessed August 21, 2006.
21 Great Lakes-Upper Mississippi River Board of State and Provincial Public Health and Environmental Managers.
22 (2004) Recommended Standards for Wastewater Facilities (Ten-State Standards).
23 IPCC (2006a) 2006 IPCC Guidelines for National Greenhouse Gas Inventories—Volume 5, Chapter 6 (Wastewater
24 Treatment and Discharge), Prepared by the National Greenhouse Gas Inventories Programme, Eggleston H.S.,
25 Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). Published: IGES, Japan. Available at
27
28 IPCC (2006b) 2006 IPCC Guidelines for National Greenhouse Gas Inventories—Volume 4, Chapter 10 (Emissions
29 from Livestock and Manure Management), Prepared by the National Greenhouse Gas Inventories Programme,
30 Eggleston H.S., Buendia L., Miwa K., Ngara T. and Tanabe K. (eds). Published: IGES, Japan. Available at
31
32 IPCC (2000) Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories,
33 Intergovernmental Panel on Climate Change, Intergovernmental Panel on Climate Change, National Greenhouse
34 Inventories Porgramme, Montreal, IPCC-XVI/Doc. 10 (1.IV.2000), May.
35 Lockwood-Post (2002) Lockwood-Post's Directory of Pulp, Paper and Allied Trades, Miller-Freeman Publications,
36 San Francisco, CA.
37 Metcalf & Eddy, Inc. (1991) Wastewater Engineering: Treatment, Disposal and Reuse, 3rd ed., McGraw Hill
38 Publishing.
39 Metcalf & Eddy, Inc. (2003) Wastewater Engineering: Treatment, Disposal and Reuse, 4th ed. McGraw Hill
40 Publishing.
41 Nemerow, Nelson Leonard and Avijit Dasgupta (1991) Industrial and Hazardous Waste Treatment. VanNostrand
42 Reinhold. NY. ISBN 0-442-31934-7.
11-82 Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2005
-------
Public Review Draft
1 Pulp and Paper (2005) "U.S. paper/board production rises in 2004 to 91.47 million tons." April.
2
3 Pulp and Paper (2006) "AF&PA projects more capacity losses this year, small gains in 2007-08." April.
4 Pulp and Paper (2003-2006) "Month in Statistics." January 2003-June 2006.
5 Scheehle, E.A., and Doom, M.R. (2001) "Improvements to the U.S. Wastewater Methane and Nitrous Oxide
6 Emissions Estimate", July.
7 U.S. Census Bureau (2006a) International Database. Downloaded from:
8 and .
9 U.S. Census Bureau (2006b) "American Housing Survey." Table 1A-4: Selected Equipment and Plumbing-All
10 Housing Units. From 1989, 1991, 1993, 1995, 1997, 1999, 2001, 2003 and 2005 reports. Downloaded from:
11 .
12 USDA (2006) National Agricultural Statistics Service. Washington, DC. Downloaded from:
13 and
14 .
15 USPoultry (2006) Email from John Starkey, USPOULTRY to D. Bartram, ERG. 30 August 2006.
16 World Bank (1999) Pollution Prevention and Abatement Handbook 1998, Toward Cleaner Production. The
17 International Bank for Reconstruction and Development/The WORLDBANK. 1818 H Street, N.W. Washington,
18 DC. 20433, USA. ISBN 0-8213-3638-X.
19 Waste Sources of Indirect Greenhouse Gas Emissions
20 EPA (2006) Air Emissions Trends - Continued Progress Through 2005. U.S. Environmental Protection Agency,
21 Washington DC. December 19, 2006. .
22 EPA (2003) E-mail correspondence containing preliminary ambient air pollutant data between EPA OAP and EPA
23 OAQPS. December 22, 2003.
24 EPA (1997) Compilation of Air Pollutant Emission Factors, AP-42, U.S. Environmental Protection Agency, Office
25 of Air Quality Planning and Standards, Research Triangle Park, NC, October.
26
27
References 11-83
------- |