SEPA
United States
Environmental Protection
Agency
Hierarchical Bayesian Model (HBM)-
Derived Estimates of Air Quality
for 2007: Annual Report
Eric S. Hall (EPA/ORD), Alison M. Eyth
(EPA/OAR), and Sharon B. Phillips (EPA/OAR)
Office of Research and Development
National Exposure Research Laboratory
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Disclaimer
The information in this document has been funded wholly by the United States
Environmental Protection Agency under a 'funds-in' interagency agreement
RW75922615-01-3 with the Centers for Disease Control and Prevention
(CDC). It has been subjected to the Agency's peer and administrative review
and has been approved for publication as an EPA document.
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EPA/600/R-12/538 | June 06, 2012 | www.epa.gov/ord
United States
Environmental Protection
Agency
Hierarchical Bayesian Model (HBM)-
Derived Estimates of Air Quality for
2007: Annual Report
Developed by the U.S. Environmental Protection Agency
Office of Research and Development (ORD)
National Exposure Research Laboratory (NERL)
And
Office of Air and Radiation (OAR)
Office of Air Quality Planning and Standards (OAQPS)
Office of Research and Development
National Exposure Research Laboratory
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Contributors:
Eric S. Hall (EPA/ORD)
Alison M. Eyth (EPA/OAR)
Sharon B. Phillips (EPA/OAR)
Project Officer
Eric S. Hall
National Exposure Research Laboratory (NERL)
109 T. W. Alexander Dr.
Durham, NC 27711-0001
Acknowledgements
The following people served as reviewers of this document and provided
valuable comments that were included: Alexis Zubrow (EPA/OAR), Richard
Mason (EPA/OAR), Norm Possiel (EPA/OAR), Kirk Baker (EPA/OAR),
Carey Jang (EPA/OAR), Tyler Fox (EPA/OAR), Rachelle Duvall (EPA/ORD),
Melinda Beaver (EPA/ORD), and OAR/OAQPS support contractors from
Computer Sciences Corporation (CSC).
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Table of Contents
1.0 Introduction 1
2.0 Air Quality Data 3
2.1 Introduction to Air Quality Regulation in the United States 3
2.1.1 The Clean Air Act 3
2.1.2 Ozone 3
2.1.3 Particulate Matter 3
2.2 Ambient Air Quality Monitoring in the United States 4
2.2.1 Monitoring Networks 4
2.2.2 Air Quality System Database 4
2.2.3 Advantages and Limitations of the Air Quality Monitoring and Reporting System 5
2.2.4 Use of Air Quality Monitoring Data for EPHT 5
2.3 Air Quality Indicators Developed for the EPHT Network 6
2.3.1 Rationale for the Air Quality Indicators 6
2.3.2 Air Quality Data Sources 6
2.3.3 Use of Air Quality Indicators for Public Health Practice 6
3.0Emissions Data 7
3.1 Introduction to the 2007 Emissions Data Development 7
3.2 2007 Emission Inventories and Approaches 7
3.2.1Point Sources (ptipm and ptnonipm) 10
3.2.1.1 IPM Sector (ptipm) 10
3.2.1.2Non-IPM Sector (ptnonipm) 11
3.2.2 Nonpoint Sources (afdust, ag, nonpt) 12
3.2.2.1 Area Fugitive Dust Sector (afdust) 12
3.2.2.2 Agricultural Ammonia Sector (ag) 12
3.2.2.3 Other Nonpoint Sources (nonpt) 13
3.2.4 Day-Specific Point Source Fires (ptfire) 13
3.2.5 Biogenic Sources (beis) 15
3.2.6 2005 Mobile Sources (on_noadj, on_moves_runpm, on_moves_startpm, nonroad, alm_
no_c3, seca_c3) 15
3.2.7 Adjustments to Onroad Mobile Source PM Emissions (on_moves_runpm, on_moves_
startpm) 16
3.2.8 Onroad Mobile Sources without Adjustments (on_noadj) 17
3.2.9 Nonroad Mobile Sources—NMTM-Based Nonroad (nonroad) 18
3.2.10 Nonroad Mobile Sources: Aircraft, Locomotive and Commercial Marine (alm_no_c3) . 19
3.2.11 Nonroad mobile sources: C3 commercial marine (seca_c3) 19
3.2.12 Emissions from Canada, Mexico and Offshore Drilling Platforms (othpt, othar, othon) . 20
3.2.13 SMOKE-ready non-anthropogenic chlorine inventory 20
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3.3 Emissions Modeling Summary 20
3.3.1 The SMOKE Modeling System 21
3.3.2 Key Emissions Modeling Settings 21
3.3.3 Spatial Configuration 21
3.3.4 Chemical Speciation Configuration 21
3.3.5 Temporal Processing Configuration 25
3.3.6 Vertical Allocation of Emissions 26
3.3.7 Emissions Modeling Ancillary Files 28
3.3.7.1 Spatial Allocation Ancillary Files 28
3.3.7.2 Surrogates for U.S. Emissions 28
3.3.7.3 Allocation Method for Airport-Related Sources
in the U.S 28
3.3.7.4 Surrogates for Canada and Mexico Emission
Inventories 28
3.3.7.5 Chemical Speciation Ancillary Files 29
3.3.7.6 Temporal Allocation Ancillary Files 31
4.0 CMAQ Air Quality Model Estimates 33
4.1 Introduction to the CMAQ Modeling Platform 33
4.1.1 Advantages and Limitations of the CMAQ Air Quality Model 33
4.2 CMAQ Model Version, Inputs and Configuration 34
4.2.1 Model Version 34
4.2.2 Model Domain and Grid Resolution 35
4.2.3 Modeling Period / Ozone Episodes 36
4.2.4 Model Inputs: Emissions, Meteorology and Boundary Conditions 36
4.3 CMAQ Model Performance Evaluation 36
S.OBayesian Model-Derived Air Quality Estimates 49
5.1 Introduction 49
5.2 Hierarchical Bayesian Space-Time Modeling System 49
5.2.1 Introduction to the Hierarchical-Bayesian Approach 49
5.2.2 Advantages and Limitations of the Hierarchical-Bayesian Approach 49
5.3 Results for O3 and PM2 5 50
5.4 Overview of HB Model Predictions 50
5.5 Evaluation of HB Model Estimates 52
5.6 Use of EPAHB Model Predictions 56
Appendix A A-l
Appendix B B-l
Appendix C C-l
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List of Figures
Figure 3-1. SMARTFIRE System 14
Figure 3-2. MOVES exhaust temperature adjustment functions 17
Figure 3-3. CMAQ Modeling Domain 22
Figure 3-4. Process of integrating BAFM with VOC for use in VOC Speciation 24
Figure 3-5. Diurnal Profiles for Parking Areas 32
Figure 4-1. Map of the CMAQ Modeling Domain. The blue box denotes the 12 km national modeling
domain (Same as Figure 3-3.) 35
Figure 4-2. Normalized Mean Bias (%) of 8-hour daily maximum ozone greater than 60 ppb over the
period May-September 2007 at monitoring sites in the continental U.S. modeling domain. 39
Figure 4-3. Normalized Mean Error (%) of 8-hour daily maximum ozone greater than 60 ppb over the
period May-September 2007 at monitoring sites in the continental U.S. modeling domain. 39
Figure 4-4. Normalized Mean Bias (%) of annual PM2.5 mass at monitoring sites in the continental U.S.
modeling domain 42
Figure 4-5. Normalized Mean Error (%) of annual PM2.5 mass at monitoring sites in the continental U.S.
modeling domain 42
Figure 4-6. Normalized Mean Bias (%) of annual Sulfate at monitoring sites in the continental U.S.
modeling domain 43
Figure 4-7. Normalized Mean Error (%) of annual Sulfate at monitoring sites in the continental U.S.
modeling domain 43
Figure 4-8. Normalized Mean Bias (%) of annual Nitrate at monitoring sites in the continental U.S.
modeling domain 44
Figure 4-9. Normalized Mean Error (%) of annual Nitrate at monitoring sites in the continental U. S.
modeling domain 44
Figure 4-10. Normalized Mean Bias (%) of annual Total Nitrate at monitoring sites in the continental
U.S. modeling domain 45
Figure 4-11. Normalized Mean Error (%) of annual Total Nitrate at monitoring sites in the continental
U.S. modeling domain 45
Figure 4-11. Normalized Mean Error (%) of annual Total Nitrate at monitoring sites in the continental
U.S. modeling domain 46
Figure 4-13. Normalized Mean Error (%) of annual Ammonium at monitoring sites in the continental
U.S. modeling domain 46
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Figure 4-14. Normalized Mean Bias (%) of annual Elemental Carbon at monitoring sites in the
continental U.S. modeling domain 47
Figure 4-15. Normalized Mean Error (%) of annual Elemental Carbon at monitoring sites in the
continental U.S. modeling domain 47
Figure 4-16. Normalized Mean Bias (%) of annual Organic Carbon at monitoring sites in the
continental U.S. modeling domain 48
Figure 4-17. Normalized Mean Error (%) of annual Organic Carbon at monitoring sites in the
continental U.S. modeling domain 48
Figure 5-2. HB Prediction (PM25) on July 2, 2002 (12 km grid cells) 52
Figure 5-3. FIB Prediction (PM25) Temporarily Matches Figure 5-4. FIB Prediction (PM25) Compensates
When AQS Data is Unavailable 53
Figure 5-4. HB Prediction (PM2J) Compensates When AQS Data is Unavailable 53
Figure 5-5. HB Prediction (PM25) Mitigates CMAQ Bias when AQS and CMAQ Values Diverge .... 54
Figure 5-6. Plot of the Response Surface of PM25 Concentrations as Predicted by the HB Model on a
Specific Monitoring Day in the Northeast U.S., Along With PM25 Measurements on a Specific
Monitoring Day from FRM Monitors in the NAMS/SLAMS Network 54
Figure 5-7. Rotated View of the Response Surface of PM25 Concentrations as Predicted by the HBM on a
Specific Monitoring Day in the Northeast U.S., Along With PM25 Measurements on a Specific
Monitoring Day from FRM Monitors in the NAMS/SLAMS Network 55
Figure 5-8. Rotated View of the Response Surface of PM25 Concentrations as Predicted by the HBM on a
Specific Monitoring Day in the Northeast U.S., Along With PM25 Measurements on a Specific
Monitoring Day from FRM Monitors in the NAMS/SLAMS Network, and the Response
Surface as Predicted by the CMAQ Modeling System 55
Figure 5-9. Fused 36 km O3 Surface for the Continental U.S. (July 26, 2005) 56
Figure C-l. PM2 5 Monitoring Data and CMAQ Surface (Separately Displayed—White Spheres
Represent Monitor Locations and Associated Concentration Values) C-2
Figure C-2. Combined PM Monitoring Data and CMAQ Surface (Via HBM) C-2
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List of Tables
Table 2-1. Ozone Standard 3
Table 2-2. PM25 Standardw 4
Table 2-3. Public Health Surveillance Goals and Current Results 6
Table 2-4. Basic Air Quality Indicators 6
Table 3-1. Platform Sectors Used in the Emission 9
Table 3-2. 2007 Continental United States Emissions by Sector (tons/yr in 48 states + D.C.) 9
Table 3-3. 2007 Non-US Emissions by Sector (tons/yr for Canada, Mexico, Offshore) 9
Table 3-4. Pollutants covered by the MOVES2010 Model in the 2005 Platform 15
Table 3-5. Regional growth factors used to project 2002 C3 emissions to 2007 19
Table 3-6. HAP emission ratios for generation of HAP emissions from criteria emissions for
C3 commercial marine vessels 20
Table 3-7. Key emissions modeling steps by sector 21
Table 3-8. Model Species produced by SMOKE for CB05 with SOA for CMAQ 4.7 23
Table 3-9. Integration status of benzene, acetaldehyde, formaldehyde and methanol (BAFM)
for each platform sector 25
Table 3-10. Temporal Settings Used for the Platform Sectors in SMOKE 26
Table 3-11. U.S. Surrogates Available for the 2002 and 2005 Platforms 27
Table 3-12. Surrogate assignments to new mobile categories in the 2005 Platform 28
Table 3-13. Canadian Spatial Surrogates for 2005-based platform Canadian Emission 29
Table 3-14. Differences between two profiles used for coal combustion 31
Table 4-1. Geographic Information for 12 km Modeling Domain 35
Table 4-2. Vertical layer structure for 2007 WRF and CMAQ simulations (heights are layer top).. . 37
Table 4-4. Summary of CMAQ 2007 8-Hour Daily Maximum O3 Model Performance Statistics by
Subregion, by Season 38
Table 4-5. Summary of CMAQ 2007 Annual PM2 s Species Model Performance Statistic 41
Table 5-1. HB Model Prediction: Example Data File 51
Table 5-2. HB Model Domains for 12-km Applications 51
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Table B-la. Canada, Mexico, and Offshore Emissions Inventory (2007) B-l
Table B-lb. Total Emission Inventory for All US Sectors (2007) B-l
Table B-lc. Total Emission Inventory for All US Sectors (2002)—Individual Criteria Pollutants. . . B-2
Table B-ld. Total Emission Inventory for All US Sectors (2002)—Total of All Pollutants B-2
Table B-le. Total Emission Inventory for All US Sectors (2007)—Individual Criteria Pollutants. . . B-2
Table B-2a. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning
Model (IPM)—EMF: Criteria Air Pollutants and Hazardous Air Pollutants B-3
Table B-2b. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning
Model (IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-5
Table B-2bi. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning
Model (IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-7
Table B-2bii. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning
Model
(IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-9
Table B-2biii. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning
Model (IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-ll
Table B-2biv. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning
Model (IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-l3
Table B-2bv. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning
Model (IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-l5
Table B-2bvi. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning
Model (IPM)—Percent Change between EMF and SMOKE Calculations B-l7
Table B-3a. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
EMF: Criteria Air Pollutants and Hazardous Air Pollutants B-19
Table B-3b. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-21
Table B-3bi. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-23
Table B-3bii. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-25
Table B-3biii. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-27
Table B-3biv. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-29
Table B-3bv. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants. . . B-31
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Table B-3bvi. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
Percent Change between EMF and SMOKE Calculations B-33
Table B-3bvii. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—
Percent Change between EMF and SMOKE Calculations B-35
Table B-4a: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—EMF: Criteria Air
Pollutants and Hazardous Air Pollutants B-37
Table B-4b: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria
Air Pollutants and Hazardous Air Pollutants B-39
Table B-4bi: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria
Air Pollutants and Hazardous Air Pollutants B-41
Table B-4bii: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria
Air Pollutants and Hazardous Air Pollutants B-43
Table B-4biii: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria
Air Pollutants and Hazardous Air Pollutants B-45
Table B-4biv: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria
Air Pollutants and Hazardous Air Pollutants B-47
Table B-4c: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—Percent Change
between EMF and SMOKE Calculations B-49
Table B-5a: Point Source Emissions from Canada, Mexico, and Offshore Sources—Pre-SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-51
Table B-5ai: Point Source Emissions from Canada, Mexico, and Offshore Sources—Pre-SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-53
Table B-5aii: Point Source Emissions from Canada, Mexico, and Offshore Sources—Pre-SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-55
Table B-5aiii: Point Source Emissions from Canada, Mexico, and Offshore Sources—Pre-SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-57
Table B-5b: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada
and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants) B-59
Table B-5bi: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada
and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants) B-61
Table B-5bii: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada
and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants) B-63
Table B-5biii: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada
and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants) B-65
Table B-5biv: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada
and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants) B-67
Table B-5bv: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada
and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants) B-69
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Table B-5bvi: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada
and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants) B-71
Table B-6a: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—Pre-SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-73
Table B-6b: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-74
Table B-6bi: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-76
Table B-6bii: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-78
Table B-6biii: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-80
Table B-6biv: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-82
Table B-6bv: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-84
Table B-6bvi: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE
[Canada and Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants) B-86
Table B-7a: Canada and Mexico On-Road Mobile Emission Inventories—Pre-SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-88
Table B-7b: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-89
Table B-7bi: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants B-90
Table B-7bii: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-91
Table B-7biii: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-92
Table B-7biv: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-93
Table B-7bv: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-94
Table B-7bvi: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants B-95
Table B-8a: All Non-Point Emission Sources—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants B-96
Table B-8ai: All Non-Point Emission Sources—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants . . B-98
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Table B-8b: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants B-100
Table B-8bi: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants B-102
Table B-8bii: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants B-104
Table B-8biii: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants B-106
Table B-8biv: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants B-108
Table B-8bv: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants B-110
Table B-8c: All Non-Point Emission Sources—Percent Change between EMF and SMOKE
Calculations B-112
Table B-8ci: All Non-Point Emission Sources—Percent Change between EMF and SMOKE
Calculations B-114
Table B-8cii: All Non-Point Emission Sources—Percent Change between EMF and SMOKE
Calculations B-116
Table B-9a: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants . . B-118
Table B-9ai: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants . . B-120
Table B-9aii: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants . . B-122
Table B-9b: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-124
Table B-9bi: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-126
Table B-9bii: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-128
Table B-9biii: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-130
Table B-9biv: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-132
Table B-9bv: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants B-134
Table B-9c: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—Percent Change between EMF and SMOKE Calculations B-136
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Table B-9ci: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature
Adjustments—Percent Change between EMF and SMOKE Calculations B-138
Table B-lOa: Non-Road (Off-Road) Emissions—Pre-SMOKE: Criteria Air Pollutants and Hazardous
Air Pollutants B-140
Table B-lOb: Non-Road (Off-Road) Emissions—Pre-SMOKE: Criteria Air Pollutants and Hazardous
Air Pollutants B-142
Table B-lOb: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous
Air Pollutants B-144
Table B-lOb: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous
Air Pollutants B-146
Table B-lObi: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous
Air Pollutants B-148
Table B-lObii: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous
Air Pollutants B-150
Table B-lObiii: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous
Air Pollutants B-152
Table B-lObiv: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous
Air Pollutants B-154
Table B-lOc: Non-Road (Off-Road) Emissions—Percent Change between EMF and SMOKE
Calculations B-156
Table B-lOci: Non-Road (Off-Road) Emissions—Percent Change between EMF and SMOKE
Calculations B-158
Table B-ll: NH3 Emissions from Livestock and Fertilizer Application B-160
Table B-12a: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—Pre-SMOKE: Criteria Air
Pollutants and Hazardous Air Pollutants B-162
Table B-12ai: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—Pre-SMOKE: Criteria Air
Pollutants and Hazardous Air Pollutants B-164
Table B-12b: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air
Pollutants and Hazardous Air Pollutants B-166
Table B-12bi: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air
Pollutants and Hazardous Air Pollutants B-168
Table B-12bii: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air
Pollutants and Hazardous Air Pollutants B-170
fable B-12biii: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
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(CMV) Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air
Pollutants and Hazardous Air Pollutants B-172
Table B-12biv: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air
Pollutants and Hazardous Air Pollutants B-174
Table B-12bv: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air
Pollutants and Hazardous Air Pollutants B-176
Table B-12c: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—Percent Change between
EMF and SMOKE Calculations B-178
Table B-12ci: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle
(CMV) Emissions (Category 1 and Category 2 Emissions only)—Percent Change between
EMF and SMOKE Calculations B-180
Table B-13a: PM10 and PM25 Emissions from Fugitive Dust Sources [Construction, etc.] B-182
Table B-13b: PM10 and PM25 Emissions from Fugitive Dust Sources [Construction, etc.] B-184
Table B-14a: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle
(CMV) Emissions—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants. . .
B-186
Table B-14b: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle
(CMV) Emissions—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants . B-187
Table B-14bi: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle
(CMV) Emissions —SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants. B-188
Table B-14bii: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle
(CMV) Emissions —SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants. B-189
Table B-14biii: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle
(CMV) Emissions —SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants. B-190
Table B-14c: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle
(CMV) Emissions—Percent Change between EMF and SMOKE Calculations B-191
Table B-15: Biogenic Emission Inventory System Emissions [model calculated] B-192
Table B-15: Biogenic Emission Inventory System Emissions [model calculated] B-193
Table B-16a: Running Mode Emissions [calculated by MOVES 2010 Model]—Pre-SMOKE:
Particulate Air Pollutants B-194
Table B-16b: Running Mode Emissions [calculated by MOVES 2010 Model]—SMOKE: Particulate
Air Pollutants B-196
Table B-16bi: Running Mode Emissions [calculated by MOVES 2010 Model]—SMOKE: Particulate
Air Pollutants B-198
Table B-16c: Running Mode Emissions [calculated by MOVES 2010 Model]—Adjusted Particulate
Air Pollutants . . B-2001
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Table B-16d: Running Mode Emissions [calculated by MOVES 2010 Model]—Percent Change between
EMF and SMOKE Calculations B-202
Table B-16e: Running Mode Emissions [calculated by MOVES 2010 Model]—Percent Change
between SMOKE and Adjusted Calculations B-203
Table B-17a: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—Pre-SMOKE:
Particulate Air Pollutants B-204
Table B-17b: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—SMOKE:
Particulate Air Pollutants B-206
Table B-17bi: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—SMOKE:
Particulate Air Pollutants B-208
Table B-17c: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—Adjusted
Particulate Air Pollutants B-210
Table B-17d: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—Percent
Change between EMF and SMOKE Calculations B-212
Table B-17e: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—Percent
Change between SMOKE and Adjusted Calculations B-213
Table B-18: Column Merge Grid Emissions [to obtain domain totals] B-214
Table B-18i: Column Merge Grid Emissions [to obtain domain totals] B-215
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1.0
Introduction
This report describes EPA's Hierarchical Bayesian model-
generated (HBM) estimates of ozone (O3) and fine paniculate
matter (PM2.5, particles with aerodynamic diameter < 2.5
microns) concentrations throughout the continental United
States during the 2007 calendar year. HBM estimates provide
the spatial and temporal variance of O3 and PM2 5, allowing
estimation of their concentration values across the U.S.,
independent of where air quality monitors are physically
located. HBM estimates are generated through the statistical
'fusion' of measured air quality monitor concentration
values and air quality model predicted concentration values
from EPA's Community Multiscale Air Quality (CMAQ)
computer model. Information on EPA's air quality monitors.
CMAQ model, and HBM model is included to provide the
background and context for understanding the data output
presented in this report.
The data contained in this report are an outgrowth of a
collaborative research partnership between EPA scientists
from the Office of Research and Development's (ORD)
National Exposure Research Laboratory (NERL) and
personnel from EPA's Office of Air and Radiation's (OAR)
Office of Air Quality Planning and Standards (OAQPS).
NERL's Human Exposure and Atmospheric Sciences
Division (HEASD), Atmospheric Modeling and Analysis
Division (AMAD), and Environmental Sciences Division
(BSD), in conjunction with OAQPS, work together to
provide air quality monitoring data and model estimates to
the Centers for Disease Control and Prevention (CDC) for
use in their Environmental Public Health Tracking (EPHT)
Network.
CDC's EPHT Network supports linkage of air quality data
with human health outcome data for use by various public
health agencies throughout the U.S. The EPHT Network
Program is a multidisciplinary collaboration that involves the
ongoing collection, integration, analysis, interpretation, and
dissemination of data from: environmental hazard monitoring
activities; human exposure assessment information; and
surveillance of noninfectious health conditions. As part of
the National EPHT Program efforts, the CDC is leading
the initiative to build the National EPHT Network (http://
www.cdc.gov/nceh/tracking/default.htm). The National
EPHT Program, with the EPHT Network as its cornerstone.
is the CDC's response to requests calling for improved
understanding of how the environment affects human health.
The EPHT Network is designed to provide the means to
identify, access, and organize hazard, exposure, and health
data from a variety of sources and to examine, analyze and
interpret those data based on their spatial and temporal
characteristics. The EPHT Network is a standards-based.
secure information network that was created to be used by
many different entities, including epidemiologists, public
health practitioners, academic researchers, schools of public
health, along with local, state, and federal agencies such as
EPA. Levels of access to the data in the EPHT Network will
vary among stakeholders based upon their role and their
purpose for using the data. Data access will be carefully
controlled to ensure compliance with federal and state
privacy laws which address the use of health data and other
protected personal information. The CDC's National EPHT
Program is establishing the EPHT Network by collaborating
with a wide range of partners with expertise from federal,
state, and local health and environmental agencies;
nongovernmental organizations (NGOs); state public health
and environmental laboratories; and schools of public health.
Since 2002, EPA has collaborated with the CDC on the
development of the EPHT Network. On September 30.
2003, the Secretary of Health and Human Services (HHS)
and the Administrator of EPA signed a joint Memorandum
of Understanding (MOU) with the objective of advancing
efforts to achieve mutual environmental public health goals.'
HHS, acting through the CDC and the Agency for Toxic
Substances and Disease Registry (ATSDR), and EPA agreed
to expand their cooperative activities in support of the CDC
EPHT Network and EPA's Central Data Exchange Node on
the Environmental Information Exchange Network in the
following areas:
• Collecting, analyzing and interpreting environmental
and health data from both agencies (HHS and EPA).
• Collaborating on emerging information technology
practices related to building, supporting, and operating
the CDC EPHT Network and the Environmental
Information Exchange Network.
• Developing and validating additional environmental
public health indicators.
Sharing reliable environmental and public health data
between their respective networks in an efficient and
effective manner.
• Consulting and informing each other about
dissemination of results obtained through work carried
out under the MOU and the associated Interagency
Agreement (IAG) between EPA and CDC.
Under the auspices of the HHS/EPAMOU, a research project
was implemented between 2004 and 2006 to investigate the
utility of EPA-generated air quality estimates as an input to
the EPHT Network. The relationship between air pollutants
Available atwww.cdc.gov/nceh/tracking/epa mou.htm
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and human health is of interest to both Agencies. EPA
develops and funds ambient air quality monitoring networks
to monitor air pollution and to provide data that may be used
to mitigate its impact on our ecosystems and human health.
(Note: AQS and AIRNow are EPA databases containing
data collected from EPA's air quality monitoring networks.)
Air quality monitoring data has been used by researchers
to investigate the linkages between human health outcomes
and air quality, and by environmental and public health
professionals to develop environmental health indicators
which provide measures of potential human health impacts.
However, an analysis of the currently available methods for
generating and characterizing air quality estimates that could
be developed and delivered systematically, and which were
also readily available to link with public health surveillance
data, had not been previously attempted. EPA collaborated
with the CDC and state public health agencies in New York.
Maine, and Wisconsin on the Public Health Air Surveillance
Evaluation (PHASE) project to address this issue. The
project focused on generating concentration surfaces for O3
and PM2 5, which were subsequently linked with asthma and
cardiovascular disease data. Results of this research project
indicated that using a Hierarchical Bayesian approach to
statistically "combine" Community Multiscale Air Quality
(CMAQ) model estimates and air quality monitoring data
documented in EPA's AQS provided better overall estimates
of air quality at locations without monitors than those
obtained through other well-known, statistically-based
estimating techniques (e.g., kriging).
Ambient air quality monitoring data stored in the Air
Quality System (AQS), along with air quality modeling
estimates from CMAQ, can be statistically combined, via a
Hierarchical Bayesian statistical space-time modeling (HBM)
system, to provide air quality estimates (hereafter referred
to as Hierarchical Bayesian-derived air quality estimates).
These Hierarchical Bayesian-derived air quality estimates
serve as well-characterized inputs to the EPHT Network. The
air quality monitor data, CMAQ modeling estimates, and
the Hierarchical Bayesian-derived air quality estimates can
be used to develop meaningful environmental public health
indicators and to link ozone and PM2 5 concentrations with
health outcome data. The Hierarchical Bayesian-derived
air quality estimates are based on EPA's current knowledge
of predicting spatial and temporal variations in pollutant
concentrations derived from multiple sources of information.
EPA is continuing its research in this critical science area
and is implementing this project to establish procedures
for routinely generating the Hierarchical Bayesian-derived
air quality estimates developed in the PHASE project. This
effort will assist EPA in making both ambient air quality
monitoring (raw) data and the Hierarchical Bayesian-derived
air quality estimates available to the CDC EPHT Network
through EPA's Central Data Exchange (CDX) Node on the
Environmental Information Exchange Network.
Because of EPA's expertise related to measurement.
analysis, scientific visualization, and reporting of air
quality monitoring data, air quality modeling estimates.
and Hierarchical Bayesian-derived air quality estimates and
associated research, the CDC approached EPA to provide
technical support for incorporating air quality data and
estimates into its EPHT Network. Because the air quality data
generated could be used by EPA to achieve other research
goals related to linking air quality data and health effects
and performing cumulative risk assessments, EPA proposed
an interagency agreement under which each agency would
contribute funding and/or in-kind support to efficiently
leverage the resources of both agencies. The major objective
of this research is to provide data and guidance to CDC to
assist them in tracking estimated population exposure to
O3 and PM25; estimating health impacts to individuals and
susceptible subpopulations; guiding public health actions;
and conducting analytical studies linking human health
outcomes and environmental conditions.
This report is divided into five sections and three appendices.
The first section of the report describes the air quality data
obtained from EPA's nationwide monitoring network and the
importance of the monitoring data in determining potential
health risks. The second section of the report details the
emissions inventory data, how it is obtained and its role as a
key input into air quality computer models. The third section
of the report describes the CMAQ computer model and its
role in providing estimates of pollutant concentrations across
the U.S. based on 12-km grid cells (entire continental U.S.).
The fourth section of the report explains the Hierarchical
Bayesian statistical modeling system which is used to
combine air quality monitoring data and air quality estimates
from the CMAQ model into a continuous concentration
surface which includes regions without air quality monitors.
The fifth section of the report provides guidelines and
requisite understanding that users must have when using
the Hierarchical Bayesian statistical modeling system. The
appendices provide a list of acronyms used in this report.
detailed information on emissions inventory data, and
detailed information on the Hierarchical bayesian statistical
modeling system.
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2.0
Air Quality Data
To compare health outcomes with air quality measures, it is
important to understand the origins of those measures and
the methods for obtaining them. This section provides a brief
overview of the origins and process of air quality regulation
in this country. It provides a detailed discussion of ozone (O3)
and paniculate matter (PM). The PHASE project focused on
these two pollutants, since numerous studies found them to
be harmful to public health and the environment, and there
was more extensive monitoring and modeling data available.
2.1 Introduction to Air Quality Regulation in the
United States
2.1.1 The Clean Air Act
In 1970, the Clean Air Act (CAA) was signed into law.
Under this law, EPA sets limits on how much of a pollutant
can be present in the air anywhere in the United States. This
ensures that all Americans have the same basic health and
environmental protections. The CAA has been amended
several times to keep pace with new scientific information.
More information is available on the CAA at:
http://www.epa.gov/oar/caa/. Under the CAA, the U.S. EPA
has established standards or limits for six common/ubiquitous
air pollutants, known as the criteria air pollutants: carbon
monoxide (CO), lead (Pb), nitrogen dioxide (NO2), sulfur
dioxide (SO2), ozone (O3), and paniculate matter (PM). These
standards, called the National Ambient Air Quality Standards
(NAAQS), are designed to protect public health and the
environment. The CAA established two types of air quality
standards. Primary standards set limits to protect public
health, including the health of "sensitive" populations such as
asthmatics, children, and the elderly. Secondary standards set
limits to protect public welfare, including protection against
decreased visibility, damage to animals, crops, vegetation.
and buildings. The law requires EPA to periodically review
these standards. More specific information on the NAAQS
is available at: http ://www. epa. gov/air/criteria. html. General
information on the criteria pollutants is available at: http://
www.epa. gov/air/urbanair/. When these standards are not
met, the area is designated as a nonattainment area. States
must develop state implementation plans (SIPs) that explain
the regulations and controls it will use to clean up the
nonattainment areas. States with an EPA-approved SIP can
request that the area be redesignated from nonattainment
to attainment by providing three consecutive years of data
showing NAAQS compliance. The state must also provide
a maintenance plan to demonstrate how it will continue to
comply with the NAAQS and demonstrate compliance over
a 10-year period, and what corrective actions it will take
should a NAAQS violation occur after redesignation. EPA
must review and approve the NAAQS compliance data and
the maintenance plan before redesignating the area; thus.
a person may live in an area designated as non attainment
even though no NAAQS violation has been observed
for quite some time. More information attainment/non
attainment designations is available at: http://www.epa. gov/
ozonedesignations/ and http://www.epa.gov/pmdesignations/.
2.1.2 Ozone
Ozone (O3) is a colorless gas composed of three oxygen
atoms. Ground level ozone is formed when pollutants
released from cars, power plants, and other sources react in
the presence of heat and sunlight. It is the prime ingredient
of what is commonly called "smog." When inhaled, ozone
can cause acute respiratory problems, aggravate asthma.
cause inflammation of lung tissue, and even temporarily
decrease the lung capacity of healthy adults. Repeated
exposure may permanently scar lung tissue. Toxicological.
human exposure, and epidemiological studies were integrated
by EPA in "Air Quality Criteria for Ozone and Related
Photochemical Oxidants" available at: http://www.epa. gov/
ttn/naaqs/standards/ozone/s_o3_index.html. The current (as
of October 2008) NAAQS for ozone, in place since 1997,
is an 8-hour maximum of 0.075 parts per million [ppm] (for
details, see http://www.epa.gov/ozonedesignations/). An
8-hour maximum is the maximum of the 24 possible running
8-hour average concentrations for each calendar day. The
Clean Air Act requires EPA to review the NAAQS at least
every five years and revise them as appropriate in accordance
with Section 108 and Section 109 of the Act. The 'allowable'
ozone values are shown in the table below:
Parts Per Million:
Measurement—(ppm)
1-Hour Standard
8-Hour Standard
Table 2-1. Ozone Standard
0.12
0.12
0.075
2.1.3 Particulate Matter (PM)
PM air pollution is a complex mixture of small and large
particles of varying origin that can contain hundreds of
different chemicals, including cancer-causing agents like
polycyclic aromatic hydrocarbons (PAH), as well as heavy
metals such as arsenic and cadmium. PM air pollution results
from direct emissions of particles as well as particles formed
through chemical transformations of gaseous air pollutants.
The characteristics, sources, and potential health effects
of paniculate matter depend on its source, the season, and
atmospheric conditions.
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As practical convention, PM is divided by sizes2 into classes
with differing health concerns and potential sources. Particles
less than 10 micrometers in diameter (PM10) pose a health
concern because they can be inhaled and accumulate in the
respiratory system. Particles less than 2.5 micrometers in
diameter (PM2 5) are referred to as "fine" particles. Because of
their small size, fine particles can lodge deeply into the lungs.
Sources of fine particles include all types of combustion
(motor vehicles, power plants, wood burning, etc.) and some
industrial processes. Particles with diameters between 2.5 and
10 micrometers (PM10_2J) are referred to as "coarse" or PMc.
Sources of PMc include crushing or grinding operations and
dust from paved or unpaved roads. The distribution of PM10.
PM2 5 and PMc varies from the Eastern U.S. to arid western
areas.
Epidemiological and toxicological studies have demonstrated
associations between fine particles and respiratory and
cardiovascular health effects, including irritation of the
airways, coughing, decreased lung function, aggravated
asthma, development of chronic bronchitis, irregular
heartbeat, nonfatal heart attacks, and premature death
in people with heart or lung disease. These studies are
summarized and integrated in "Air Quality Criteria for
Paniculate Matter" (EPA 2004). This document and other
technical documents related to PM standards are available
at http://www.epa. gov/ttn/naaqs/standards/pm/s_pm_index.
html.
The current (as of March 2012) NAAQS for PM25 includes
both a 24-hour standard to protect against short-term effects.
and an annual standard to protect against long-term effects.
The annual average PM2 5 concentration must not exceed
15 ug/m3, and the 24-hr average concentration must not
exceed 35 micrograms per cubic meter (ug/m3). The current
annual PM2 5 NAAQS was set in 1997 and the current 24-hr
PM25 NAAQS was set in 2006 "(for details see http://
www.epa.gov/air/criteria.html) and http://www.epa.gov/
oar/particlepollution/naaqsrev2006.html). The EPA quality
assurance standards for PM2 5 monitors specify that the
coefficient of variation (CV = standard deviation/mean) of
a monitor measurement must be less than 10%. The relative
bias (tendency for measured values to be higher or lower
than 'true' value) for PM2 5 monitor measurements must be
between the range of -10% to +10%. The 'allowable' PM2 5
values are shown in the table below:
Micrograms Per Cubic Meter:
Measurement- (|ig/m3)
Annual Average
24-Hour Average
Table 2-2. PM25 Standards
1997 2006
15
15
2 The measure used to classify PM into sizes is the aerodynamic diameter.
The measurement instruments used for PM are designed and operated to
separate large particles from the smaller particles. For example, the PM2
instrument only captures and thus measures particles with an aerodynamic
diameter less than 2.5 micrometers. The EPA method to measure
PMc is designed around taking the mathematical difference between
measurements for PM,,, and PM,,
2.2 Ambient Air Quality Monitoring In the United States
2.2.1 Monitoring Networks
The Clean Air Act requires every state to establish a network
of air monitoring stations for criteria pollutants, following
specific guidelines for their location and operation. Federal
Reference Method (FRM) and Federal Equivalent Method
(FEM) monitors are used to measure criteria pollutants. The
monitoring stations in this network have been called the State
and Local Air Monitoring Stations (SLAMS). The SLAMS
network consists of approximately 4,000 monitoring sites
whose distribution is largely determined by the needs of
state and local air pollution control agencies. All ambient
monitoring networks selected for use in SLAMS are tested
periodically to assess the quality of the SLAMS data being
produced. Measurement accuracy and precision are estimated
for both automated and manual methods. The individual
results of these tests for each method or analyzer are reported
to EPA. Then, EPA calculates quarterly integrated estimates
of precision and accuracy for the SLAMS data.
The National Air Monitoring Station network (NAMS)
is about a 1,000-site subset of the SLAMS network, with
emphasis on areas of maximum concentrations and high
population density in urban and multi-source areas. The
NAMS monitoring sites are designed to obtain more timely
and detailed information about air quality in strategic
locations and must meet more stringent monitor siting.
equipment type, and quality assurance criteria. NAMS
monitors also must submit detailed quarterly and annual
monitoring results to EPA.
The SLAMS and NAMS networks experienced accelerated
growth throughout the 1970s. The networks were further
expanded in 1999 following the 1997 revision of the CAA
to include separate standards for fine particles (PM2 5)
based on their link to serious health problems ranging from
increased symptoms, hospital admissions, and emergency
room visits, to premature death in people with heart or lung
disease. While most of the monitors in these networks are
located in populated areas of the country, "background" and
rural monitors are an important part of these networks. For
criteria pollutants other than ozone and PM2 5, the number
of monitors has declined. More information on SLAMS and
NAMS, as well as EPA's other air monitoring networks are
available at: http://www.epa.gov/ttn/amtic.
In summary, state and local agencies and tribes implement
a quality-assured monitoring network to measure air quality
across the United States. EPA provides guidance to ensure a
thorough understanding of the quality of the data produced
by these networks. These monitoring data have been used
to characterize the status of the nation's air quality and the
trends across the U.S. (http://www.epa.gov/airtrends).
2.2.2 Air Quality System Database
The Air Quality System (AQS) database contains ambient
air pollution data collected by EPA, state, local, and tribal
air pollution control agencies from thousands of monitoring
stations (SLAMS and NAMS). AQS also contains
meteorological data, descriptive information about each
monitoring station (including its geographic location and
its operator), and data quality assurance and quality control
-------
information. State and local agencies are required to submit
their air quality monitoring data into AQS by the end of
the quarter following the quarter in which the data were
collected. This ensures timely submission of these data for
use by state, local, and tribal agencies, EPA, and the public.
EPA's Office of Air Quality Planning and Standards and other
AQS users rely upon the data in AQS to assess air quality.
assist in attainment vs. non-attainment designations, evaluate
SIPs, perform modeling for permit review analysis, and
perform other air quality management functions.
AQS was converted from a mainframe system to a UNIX-
based Oracle system which is easily accessible to users
through the Internet. This system became available in
January 2002. Today, state, local, and tribal agencies submit
their data directly to AQS. Registered users may also retrieve
data through the AQS application and through the use of
third-party software such as the Discoverer tool from Oracle
Corporation. For more detailed information about the AQS
database, go to http://www.epa.gov/ttn/airs/airsaqs/index.htm.
2.2.3 Advantages and Limitations of the Air Quality
Monitoring and Reporting System
Air quality data is required to assess public health outcomes
that are affected by poor air quality. The challenge is to get
surrogates for air quality on time and spatial scales that are
useful for Environmental Public Health Tracking activities.
The advantage of using ambient data from EPA monitoring
networks for comparing with health outcomes is that these
measurements of pollution concentrations are the best
characterization of the concentration of a given pollutant at
a given time and location, and require no further analysis.
Furthermore, the data are supported by a comprehensive
quality assurance program, ensuring data of known quality.
One disadvantage of using the ambient data is that it is
usually out of spatial and temporal alignment with health
outcomes. This spatial and temporal 'misalignment'
between air quality monitoring data and health outcomes
is influenced by the following key factors: the living and/
or working locations (microenvironments) where a person
spends their time not being co-located with an air quality
monitor; time(s)/date(s) when a patient experiences a health
outcome/symptom (e.g., asthma attack) not coinciding with
time(s)/date(s) when an air quality monitor records ambient
concentrations of a pollutant high enough to affect the
symptom (e.g., asthma attack either during or shortly after a
highPM25 day). To compare/correlate ambient concentrations
with acute health effects, daily local air quality data is
needed. Spatial gaps exist in the air quality monitoring
network, especially in rural areas, since the air quality
monitoring network is designed to focus on measurement
of pollutant concentrations in high population density areas.
Temporal limits also exist. Samples from Federal Reference
Method (FRM) PM2 5 monitors are generally collected only
one day in every three days, due in part to the time and costs
involved in collecting and analyzing the samples. However.
over the past several years Tapered Element Oscillating
Microbalance (TEOM) monitors, which can automatically
collect, analyze, and report PM2 5 measurements on an hourly
basis, have been introduced. These monitors are available
in most of the major metropolitan areas and (as of March
2012) are being assessed for their equivalency to the FRM.
Ozone is monitored daily, but mostly during the ozone season
(the warmer months, approximately April through October).
However, year-long data is extremely useful to evaluate
whether ozone is a factor in health outcomes during the
non-ozone seasons.
2.2.4 Use of Air Quality Monitoring Data for EPHT
Air quality monitoring data has been used to provide the
information for the following:
1. Assessing effectiveness of SIPs in addressing NAAQS
nonattainment areas
2. Characterizing local, state, and national air quality
status and trends
3. Associating health and environmental damage with air
quality levels/concentrations
For the EPHT effort, EPA is providing air quality data to
support efforts associated with (2), and (3) above. Data
supporting (3) is generated by EPA through the use of its
air quality data and its Hierarchical Bayesian space-time
statistical model (HBM).
Most studies that associate air quality with health outcomes
use air monitoring as a surrogate for exposure to the air
pollutants being investigated. Many studies have used the
monitoring networks operated by state and federal agencies
in the implementation of Clean Air Act requirements. Some
studies perform special monitoring that can better represent
exposure to the air pollutants: community monitoring, near
residences, in-house or work place monitoring, and personal
monitoring. For the EPHT program, special monitoring is
generally not supported, though it could be used on a case-
by-case basis.
Many approaches may be used to assign exposure from
monitors or estimate concentrations for a new time period
or location based on existing data. On the simplest level for
example, data from monitoring sites are averaged and applied
to the population in an entire county, or the nearest monitor is
assigned to a subject's address. At the next level, variogram
analysis may be used to describe the spatial correlation of
the data and interpolate concentrations across space. Such
approaches work well for temporally and spatially robust
data, but where data are missing (for example for PM2 5 data
with samples taken every third day), further assumptions
and modeling are needed which add uncertainty into the
interpolated concentrations. Finally, air quality monitoring
data can be used with air quality modeling estimates (using
emissions inventories) and incorporated into a Bayesian
model to enhance the prediction of ambient air concentrations
in space and time. There are two methods used in EPHT
to provide estimates of ambient concentrations of air
pollutants: air quality monitoring data and the Hierarchical
Bayesian-derived air quality estimate, which is a statistical
'combination' of air quality monitor data and air quality
modeling estimates.
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(1) Air data sets and metadata required for air quality
indicators are available to EPHT state Grantees.
(2) Estimate the linkage or association of PM25 and ozone
on health to:
A. Identify populations that may have higher risk of
adverse health effects due to PM2 5 and ozone,
B. Generate hypothesis for further research, and
C. Provide information to support prevention and
pollution control strategies.
(3) Produce and disseminate basic indicators and
other findings in electronic and print formats to provide
the public, environmental health professionals, and
policymakers, with current and easy-to-use information
about air pollution and the impact on public health.
AQS data is available through state agencies and EPA's AirData and
AirExplorer. EPA and CDC developed an interagency agreement, where EPA
provides air quality data along with HBM modeling data, associated metadata,
and technical reports that are delivered to CDC.
Regular discussions have been held on health-air linked indicators and CDC/
HE I/EPA convened a workshop in January 2008. CDC has collaborated on
a health impact assessment (HIA) with Emory University, EPA and state
grantees that can be used to facilitate greater understanding of these linkages.
Templates and "how to" guides for PM2 5 and ozone have been developed for
routine indicators. Calculation techniques and presentations for the indicators
have been developed.
Table 2-3. Public Health Surveillance Goals and Current Results
Ozone (daily 8-hr period with maximum concentration—ppm—by Federal Reference Method (FRM))
Number of days with maximum ozone concentration over the NAAQS (or other relevant benchmarks (by county and MSA)
Number of person-days with maximum 8-hr average ozone concentration over the NAAQS & other relevant benchmarks (by county
and MSA)
PM (daily 24-hr integrated samples by FRM)
Average ambient concentrations of particulate matter (< 2.5 microns in diameter) and compared to annual PM25 NAAQS (by state).
% population exceeding annual PM25 NAAQS (by state).
% of days with PM25 concentration over the daily NAAQS (or other relevant benchmarks (by county and MSA)
Number of person-days with PM25 concentration over the daily NAAQS & other relevant benchmarks (by county and MSA)
Table 2-4. Basic Air Quality Indicators
2.3 Air Quality Indicators Developed for the EPHT
Network
Air quality indicators have been developed for use in the
Environmental Public Health Tracking Network (EPHT). The
approach divides "indicators" into two categories. First, basic
air quality measures were developed to compare air quality
levels over space and time within a public health context
(e.g., using the NAAQS as a benchmark). Next, indicators
were developed that mathematically link air quality data
to public health tracking data (e.g., daily PM2 5 levels and
hospitalization data for acute myocardial infarction). Table
2-3 and Table 2-4 describe the issues impacting calculation of
basic air quality indicators.
2.3.1 Rationale for the Air Quality Indicators
The CDC EPHT Network is initially focusing on ozone and
PM25. These air quality indicators are based mainly around
the NAAQS health findings and program-based measures
(measurement, data and analysis methodologies). The
indicators will allow comparisons across space and time
for EPHT actions. They are in the context of health-based
benchmarks. By bringing population into the measures, they
roughly distinguish between potential exposures (at broad
scale).
2.3.2 Air Quality Data Sources
The air quality data will be available based on the state/
federal air program's data collection and processing. Air
quality data management (EPA's Air Quality System—AQS)
and delivery systems (AirData and Air Explorer) were used in
the PHASE project as the pilot test for air quality indicators.
The AirExplorer functionality is now fully integrated into the
AirData system, and AirExplorer is no longer a stand-alone
system/application.
2.3.3 Use of Air Quality Indicators for Public Health
Practice
The basic indicators will be used to inform policymakers
and the public regarding the degree of hazard within a state
and across states (national). For example, the number of
days per year that ozone is above the NAAQS can be used to
communicate to sensitive populations (such as asthmatics)
the number of days that they may be exposed to unhealthy
levels of ozone. This is the same level used in the Air Quality
Alerts that inform these sensitive populations when and how
to reduce their exposure. These indicators, however, are not
a surrogate measure of exposure and therefore will not be
linked with health data.
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3.0
Emissions Data
3.1 Introduction to the 2007 Emissions Data
Development
The U.S. EPA has developed a 2005-based air quality
modeling platform for emissions data. Version 4 of the
2005 platform (i.e., 2005v4) was used to develop the year
2007 emission data for this project, where there was not
2007-specific data available. This section is a summary of the
emissions inventory and emissions modeling for Criteria Air
Pollutants (CAPs), and describes the approach and data used
to produce emissions inputs to the air quality model. The
air quality modeling, meteorological inputs and boundary
conditions are described in a separate section. A complete
description of the 2005v4 Platform is available in "Technical
Support Document: Preparation of Emissions Inventories
for the Version 4, 2005-based Platform, U.S. EPA, Research
Triangle Park, NC 27711, July 2010" (available from http://
www.epa.gov/ttn/cMef/emch/index.htmM2005).
The Community Multiscale Air Quality (CMAQ) model
(http://www.epa. gov/AMD/CMAOA is one of the air quality
models supported by the 2005v4 platform for the purposes
of modeling ozone (O3) and paniculate matter (PM). The
version of CMAQ used for this study requires hourly and
gridded emissions of species from the following inventory
pollutants: carbon monoxide (CO),nitrogen oxides (NOX).
volatile organic compounds (VOC), sulfur dioxide (SO2).
ammonia (NH3), paniculate matter less than or equal to
10 microns (PM10), and individual component species for
paniculate matter less than or equal to 2.5 microns (PM25).
In addition, the CMAQ CB05 with chlorine chemistry,
which is part of the "base" version of CMAQ, allows
explicit treatment of the following substances, Benzene.
Acetaldehyde, Formaldehyde, and Methanol (BAFM), and
includes anthropogenic Hazardous Air Pollutant (HAP)
emissions ofHCl and Cl. Readers may note that the version of
CMAQ targeted by the 2005v4 platform does not support Hg.
but other versions of the modeling platform do support Hg.
The effort to create the 2007 emission inputs for this study
included development of emission inventories for a 2007
model evaluation case and application of the emissions
modeling tools to convert the inventories into the format and
resolution needed by CMAQ. The 2007 evaluation case uses
2007-specific fire emissions and 2007-specific continuous
emission monitoring (CEM) data for electric generating units
(EGUs).
The primary emissions modeling tool used to create the
CMAQ model-ready emissions was the Sparse Matrix
Operator Kernel Emissions (SMOKE) modeling system.
SMOKE version 2.6 was used to create emissions files for
a 12-km national grid. Electronic copies of some of the
data used with SMOKE for the criteria air pollutants (CAP)
2005v4 Platform are available at the emissions modeling
clearinghouse, http://www.epa.gov/ttn/chief/emch/. under the
section entitled "CAP BAFM 2005-Based Platform, Version 4."
This summary contains two additional sections. Section 3.2
describes the inventories input to SMOKE and the ancillary
files used along with the emission inventories. Section 3.3
describes the emissions modeling performed to convert the
inventories into the format and resolution needed by CMAQ.
3.2 2007 Emission Inventories and Approaches
This section describes the emissions inventories created
for input to SMOKE. The primary basis for the emission
inputs for the 2005v4 Platform is the 2005 National
Emission Inventory (NEI), Version 2. The 2005 NEI v2
includes emissions of CO, NOx, VOC, SO2, NH3, PM10,
and PM2 5 and hazardous air pollutants (HAPs). The 2005
platform utilizes select HAPs: the base version includes
chlorine, HC1, benzene, acetaldehyde, formaldehyde.
and methanol. Documentation for the 2005 NEI can be
found at: http://www.epa.gov/ttn/chief/net/2005inventory.
html#documentation. For inventories outside of the United
States, including Canada, Mexico and offshore emissions, the
latest available base year inventories were used.
The 2005 NEI includes five source sectors: a) nonpoint
(formerly called "stationary area") sources; b) point sources;
c) nonroad mobile sources; d) onroad mobile sources; and e)
fires. The fires portion of the inventory includes emissions
from wildfires and prescribed burning computed as hour-
specific point sources. For purposes of preparing the CMAQ-
ready emissions, the NEI is split into several additional
"platform" sectors for use in emissions modeling; biogenic
emissions are added along with emissions from other sources
and other NEI such as the Canadian, Mexican, and offshore
inventories. The significance of an emissions sector for the
platform is that it is run through all of the SMOKE programs.
except the final merge, independently from the other sectors.
The final merge program (i.e., Mrggrid) combines the sector-
specific gridded, speciated and temporalized emissions to
create the CMAQ emission inputs.
Table 3-1 presents the sectors in the 2005v4 platform used
to develop 2007 emissions for this project. The sector
abbreviations are provided in italics; these abbreviations
are used in the SMOKE modeling scripts and inventory
file names and throughout the remainder of this section.
Annual 2007 emission summaries for the U.S. anthropogenic
sectors are shown in Table 3-2 (i.e., excluding biogenic
emissions). Table 3-3 provides a summary of emissions for
the anthropogenic sectors containing Canadian, Mexican and
offshore sources.
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2005v4 Platform
Sector
2005
NEI
Sector
IPM sector: ptipm Point
Non-1 PM sector:
ptnonipm
Point source fire
sector: ptfire
Agricultural sector: ag
Area fugitive dust
sector: afdust
Remaining nonpoint
sector: nonpt
Nonroad sector:
nonroad
locomotive, and
non-C3 commercial
marine: aim no c3
Point
Fires
Nonpoint
Nonpoint
Nonpoint
Mobile:
Nonroad
Mobile:
Nonroad
C3 commercial
marine: seca_c3
Onroad California,
NMIM-based, and
MOVES sources not
subject to temperature
adjustments:
on_noadj
Onroad cold-start
gasoline exhaust
mode vehicle from
MOVES subject
to temperature
adjustments:
on_moves_startpm
Onroad running
gasoline exhaust
mode vehicle from
MOVES subject
to temperature
adjustments:
on_moves_runpm
Biogenic: beis
Other point sources
not from the NEI:
othpt
Mobile:
Nonroad
Mobile:
onroad
Mobile:
onroad
Mobile:
onroad
N/A
N/A
Description and resolution of the data input to SMOKE
2005v2 NEI point source EGUs mapped to the Integrated Planning Model (IPM) model using year
2007 continuous emission monitoring (CEM) NOX and S02 emissions from the National Electric
Energy Database System (NEEDS, 2006 version 3.02) database. Hourly files for CEM sources are
included for the 2007 evaluation case used for this project. Day-specific emissions for non-CEM
sources are year 2005 NEI-based estimates and were created for input into SMOKE.
Year 2005 emissions for all 2005v2 NEI point source records not matched to the ptipm sector, annual
resolution. Includes all aircraft emissions.
Point source day-specific wildfires and prescribed fires for 2007.
Primarily 2002 NEI nonpoint NH3 emissions from livestock and fertilizer application, county and
annual resolution.
Primarily 2002 NEI nonpoint PM10 and PM25 from fugitive dust sources (e.g., building construction,
road construction, paved roads, unpaved roads, agricultural dust), county/annual resolution.
Primarily 2002 NEI nonpoint sources not otherwise included in other SMOKE sectors, county and
annual resolution. Also includes updated Residential Wood Combustion emissions and year 2005
non-California Western Regional Air Partnership (WRAP) oil and gas "Phase II" inventory.
Year 2007 monthly nonroad emissions from the National Mobile Inventory Model (NMIM) using
NONROAD2005 version nr05c-BondBase for all states except California. Monthly emissions for
California created from annual emissions submitted by the California Air Resources Board (CARB) for
the 2005v2 NEI linearly-interpolated with year 2009 emissions to create year 2007.
Year 2002 non-rail maintenance locomotives, and category 1 and category 2 commercial marine
vessel (CMV) emissions sources, county and annual resolution. Unlike prior platforms, aircraft
emissions are now included in the ptnonipm sector and category 3 CMV emissions are now
contained in the seca c3 sector
Annual point source formatted year 2007 category 3 (C3) CMV emissions, developed for the EPA rule
called "Control of Emissions from New Marine Compression-Ignition Engines at or Above 30 Liters
per Cylinder", usually described as the Area (EGA) study, originally called S02 ("S") EGA.
Year 2007 emissions consisting of two, monthly, county-level components:
1. MOVES2010-based (December 2009) except for California and gasoline exhaust PM.
2. California onroad, created using annual EMFAC-based emissions submitted by CARB for the
2005v2 NEI, linearly-interpolated with year 2009 EMFAC-based submissions.
Year 2007 monthly, county-level MOVES2010-based onroad gasoline emissions subject to
temperature adjustments. Limited to exhaust mode only for PM species. California emissions not
included. This sector is limited to cold start mode emissions that contain different temperature
adjustment curves from running exhaust (see on_moves_runpm sector).
Year 2007 monthly, county-level MOVES2010-based onroad gasoline emissions subject to
temperature adjustments. Limited to exhaust mode only for PM species. California emissions
not included. This sector is limited to running mode emissions that contain different temperature
adjustment curves from cold start exhaust (see on_moves_startpm sector).
Hour-specific, grid cell-specific emissions generated from the BEIS3.14 model -includes emissions in
Canada and Mexico.
Point sources from Canada's 2006 inventory and Mexico's Phase III 1999 inventory, annual
resolution. Also includes annual U.S. offshore oil 2005v2 NEI point source emissions.
-------
2005v4 Platform
Sector
Other nonpoint and
nonroad not from the
NEI: othar
Other onroad sources
not from the NEI:
othon
2005
NEI
Sector
N/A
N/A
Description and resolution of the data input to SMOKE
Annual year 2006 Canada (province resolution) and year 1999 Mexico Phase III (municipio
resolution) nonpoint and nonroad mobile inventories, annual resolution.
Year 2006 Canada (province resolution) and year 1999 Mexico Phase I
onroad mobile inventories, annual resolution.
(municipio resolution)
Table 3-1. Platform Sectors Used in the Emission
Con.US
Total
270,007
7,376,314
17,902,244
37,903,749
33,600,784
578,111
3,222,221
58,225
3,251,990
773
134,080
2,042
163,735
550,283
20,997
159,003
1,683,490
2,010,786
8,001,667
397,094
3,360,926
2,247,228
688,087
59,366
1,349,685
192,016
179,470
3,363,355
612,992
653,957
58,042
1,076,954
182,151
102,494
2,850,301
507,501
442,656
53,398
154,016
1,252,645
103,787
66,370
233,739
9,083,244
2,117,649
452,318
67,690
7,474,512
2,514,819
3,147,282
7,910,324
40,075
1,310,085
24,233
100,911,655 4,282,903 20,314,203 15,327,874 6,302,535 13,463,767 22,489,021
Table 3-2. 2007 Continental United States Emissions by Sector (tons/yr in 48 states + B.C.)
Country &
Sector
Canada othar
Canada othon
Canada othpt
Canada Subtotal
Mexico othar
Mexico othon
Mexico othpt
Mexico Subtotal
Offshore othpt
Offshore seca_c3
2007 TOTAL
3,747,987
4,514,002
1,147,801
9,409,790
350,557
1,066,589
68,422
1,485,567
89,800
40,377
11,025,535
537,835
21,810
21,138
580,784
254,600
H
0
256,498
0
718,996
537,665
861,223
2,117,883
171,099
110,203
224,202
505,505
82,571
490,149
3,196,108
1,421,910
15,002
117,254
1,554,167
75,556
5,151
97,146
177,854
839
40,483
1,773,342
837,282
* VOC is approximated from a sum of speciated VOC within the modeling domain
Table 3-3. 2007 Non-US Emissions by Sector (tons/yr for Canada, Mexico, Offshore)
393,852
10,632
68,114
472,598
49,023
4,720
72,264
126,007
837
37,240
636,682
97,652
5,430
1,762,340
1,865,422
82,643
6,124
649,810
738,578
1,961
300,320
2,906,280
1,332,559
308,318
448,629
2,089,507
429,264
152,265
65,273
646,802
53,399
17,176
2,806,884
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3.2.1 Point Sources (ptipm andptnonipm)
Point sources are sources of emissions for which specific
geographic coordinates (e.g., latitude/longitude) are specified.
as in the case of an individual facility. A facility may have
multiple emission points, which may be characterized as
units such as boilers, reactors, spray booths, kilns, etc. A unit
may have multiple processes (e.g., a boiler that sometimes
burns residual oil and sometimes burns natural gas). Note
that this section describes only contiguous U.S. NEI point
sources. The offshore oil platform (othpt sector) and category
3 CMV emissions (seca_c3 sector) are point source formatted
inventories, but they are discussed later in this section.
After removing offshore oil platforms into the othpt sector.
two platform sectors were created from the remaining 2005
point source NEI, v2 for input into SMOKE: the Integrated
Planning Model (IPM) sector (ptipm) and the non-IPM sector
(ptnonipm). This split facilitates the use of different SMOKE
temporal processing and future year projection techniques
for these sectors. The inventory pollutants processed through
SMOKE for both ptipm and ptnonipm sectors were: CO,
NOX, VOC, SO2, NH3, PM10, PM25 and the following HAPs:
HC1 and Cl. BAFM from these sectors was not used and
instead the VOC was speciated without any integration of
VOC HAP (integration is discussed in detail in Section
3.3.4).
The ptnonipm emissions were provided to SMOKE as
annual emissions. In the 2007 model evaluation case used
in this study, for ptipm sector sources with CEM data that
could be matched to the NEI, 2007 hourly SO2 and NOX
emissions were used alongside annual emissions of all other
pollutants. The hourly data also contained heat input, which
was used to allocate the annual emissions to hourly values.
For the non-CEM sources, daily emissions were created, and
state-specific diurnal profiles were applied to create hourly
emissions.
Full documentation for the development of the 2005 point
source NEI, v2, is at:
http://www.epa.gov/ttn/chief/net/2005inventory.
html#documentation. A summary of this documentation
follows:
1. Electric generating unit (EGU) emissions are obtained
from emissions and heat input from EPA'S Acid Rain
Program. The following approach applied to units in
the 2002 NEI that matched to 2005 CEMS units. For
pollutants covered by the CEMS, the 2007 CEMS data
were used. For CEMS units with pollutants not covered
by CEMS (e.g., VOC, PM25, HC1) unit specific ratios
of 2007 to 2005 heat input were applied to 2005 NEI v2
emissions to obtain 2007 estimates.
2. Non-EGU Stationary Source enhancements focused on
improving the following sectors:
a. HAP data received from States and industry to
support the MACT program, including the recent
Risk and Technology Review rulemaking
b. 2005 State, local, and tribal data submitted to EPA
under the Consolidated Emissions Reporting Rule
(CERR)
c. HAP data from Toxic Release Inventory (TRI) for
missing facilities and pollutants
d. Off-shore platform data from Mineral Management
Services (MMS)
The changes made to the 2005 NEI point sources prior to
modeling are as follows:
• The tribal data, which do not use state/county Federal
Information Processing Standards (FIPS) codes in the
NEI, but rather use the tribal code, were assigned a
state/county FIPS code of 88XXX, where XXX is the
3-digit tribal code in the NEI. This change was made
because SMOKE requires the state/county FIPS code.
Stack parameters for some point sources were defaulted
when modeling in SMOKE. SMOKE uses an ancillary
file, called the PSTK file, which provides default stack
parameters by Source Classification Code (SCC) to
either 'gap fill' stack parameters if they are missing
in the NEI or to correct stack parameters if they are
outside the ranges specified in SMOKE for acceptable
values. The SMOKE PSTK file is contained in the
ancillary file directory of the 2005v4 website.
• A transport fraction was applied to all SCCs that
were identified as PM fugitive dust, to prevent the
overestimation of fugitive dust impacts in the grid
modeling.
3.2.1.1 IPM Sector (ptipm)
The ptipm sector contains emissions from EGUs in the
2005 NEI version 2 point inventory that could be matched
to the units found in the 2006 NEEDS database, version
3.02 (http://www.epa.gov/airmarkets/progsregs/epa-ipm/
index.html). which is used by the IPM, version 3.02. The
IPM model provides future year emission inventories for
the universe of EGUs contained in the NEEDS database.
As described below, this matching was done in order to (1)
provide consistency between the 2005 EGU sources and
future year EGU emissions for sources which are forecasted
by IPM and (2) avoid double counting in projecting point
source emissions.
The 2005 NEI point source inventory contains emissions
estimates for both EGU and non-EGU sources. The IPM
is used to predict the future year emissions for the EGU
sources. The remaining non-EGU point sources are projected
by applying projection and control factors to the base year
emissions. It was therefore necessary to identify and separate
into two sectors: (1) all sources that are projected via the IPM
and (2) those that are not. This procedure prevents double-
counting or dropping significant emissions when creating
the future-year emissions. The matching process relies on
imperfect data; consequently, a small degree of dropped and/
or double-counted emissions occurred for sources that we
could not match. We believe that the unmatched units are
small emissions sources because we have reviewed both the
NEI and the NEEDS database to ensure that all significant
EGUs have been captured in the matching process.
The methodology that follows describes how the point
inventory was split into the ptipm and ptnonipm sectors. The
-------
approach started with the splits identified for the 2002 NEI
(step 1) and then included additional steps to apply these to
the 2005 NEI.
The methodology used to split the EGU emission sources
from the non-EGU emission sources was implemented as
follows:
Step 1: Obtain facilities and units identified as EGUsfrom
the 2002 NEI
2005 NEI units were identified as IPM units using the 2006
NEEDS 3.0 database. This methodology is described in the
200 Platform documentation previously referenced. Since
some source identifiers are held constant between the 2002
and 2005 NEI, particularly "NEI Unique ID", it was easier
to compare the two inventories to ensure that improvements
were made in the 2005 matching rather than having
inadvertent omissions.
Step 2: Create the 2005 NEI v2 point modeling inventory
from the 2005v2 NEI and impacts on EGU
matching
The published 2005 NEI v2 point inventory was enhanced
to improve the ptipm and ptnonipm splits and make other
updates. What follows are the issues and their resolution.
These changes represent differences between the published
2005 v2 NEI and what was used for modeling.
1. Facilities with added HAP emissions records that were
clearly EGUs, but had not been flagged as "IPM"
sources were identified. These facilities had facility
identifiers (i.e., plant IDs) beginning with "EGU". It
was further confirmed that these records were EGU
emissions; and therefore, these units were moved to the
ptipm sector.
2. One additional unit with HAP emissions records
not flagged as an EGU was found, after confirming
that representing emissions were from a facility for
which CAP records were identified as ptipm sector
records. This unit (South Mississippi Electric Power.
plantid = 2807300021, unitid = 012, NEI_UNIQUE_
ID=NEI409) was moved into the ptipm inventory.
3. Several facilities and units closed between 2002
and 2005 and had not initially been removed in the
development of the 2005v2 NEI; these were removed
based on a list from the NEI developers.
4. Inspection of CEM and 2005 NEI v2 point inventory
revealed some duplication of sources with state and
non-state reported data. This can occur because EPA
created the EGU records in the 2005 NEI, but the states
sometimes still submitted these emissions records.
These duplicates were removed.
5. ORIS facility and boiler codes (used to match to
the CEM hourly data) were unintentionally dropped
between a preliminary and final 2005 NEI v2 point
dataset. These ORIS facility and boiler codes were
repopulated based on available data.
Another reason the ptipm sources were separated from the
other sources was due to the difference in the temporal
resolution of the data input to SMOKE. The ptipm sector
uses the available hourly CEM data via a method first
implemented in the 2002 platform that was also used for
the 2005 platform. For sources with CEMs, the actual year
2007 hourly CEM data were used. The hourly CEM data
were obtained from the CAMD Data and Maps website3. The
SMOKE modeling system matches the ORIS Facility and
Boiler IDs in the NEI SMOKE-ready file to the same fields
in the CEM data. This allowed us to use the hourly SO2 and
NOX CEM emissions directly from the CEM data file. The
heat input from the hourly CEM data was used to allocate
the NEI annual values for all other pollutants from CEM
sources, because hourly data for these other pollutants are not
available with the hourly CEM data.
For sources not matching the CEM data ("non-CEM"
sources), daily emissions were computed from the NEI
annual emissions using a structured query language (SQL)
program and state-average CEM data. To allocate annual
emissions to each month, state-specific, three-year averages
of 2006-2008 CEM data were created. These average annual-
to-month factors were assigned to non-CEM sources by
state. To allocate the monthly emissions to each day, the
2007 CEM data were used to compute state-specific month-
to-day factors, which were then averaged across all units
in each state. The resulting daily emissions were input into
SMOKE. The daily-to-hourly allocation was performed in
SMOKE using diurnal profiles. The development of these
diurnal ptipm-specific profiles, considered ancillary data for
SMOKE, is described in a later section.
3.2.1.2 Non-IPMSector (ptnonipm)
The non-IPM (ptnonipm) sector contains all 2005 NEI v2
point sources not included in the IPM (ptipm) sector4. The
ptnonipm sector contains fugitive dust PM emissions from
vehicular traffic on paved or unpaved roads at industrial
facilities or coal handling at coal mines. Prior to input to
SMOKE, the fugitive dust PM emissions were reduced to
estimate the emissions that remain aloft by applying county-
specific fugitive dust transportable fraction factors. This is
discussed further in Section 3.2.2.1.
For some geographic areas, some of the sources in the
ptnonipm sector belong to source categories that are
contained in other sectors. This occurs in the inventory
when states, tribes or local programs report certain inventory
emissions as point sources because they have specific
geographic coordinates for these sources. They may use
point source SCCs (8-digit) or non-point, onroad or nonroad
(10-digit) SCCs. In the 2005 NEI, examples of these types
of sources include: aircraft emissions in all states, waste
disposal emissions in several states, firefighting training
in New Mexico, several industrial processes and solvent
utilization sources in North Carolina and Tennessee, livestock
(i.e., animal husbandry) in primarily Kansas and Minnesota.
3 http://camddataandmaps.epa.gov/gdm/index.cfm?fuseaction=emissions.
wizard
4 Except for the offshore oil and day-specific point source fire emissions
data which are included in separate sectors, as discussed in sections 2.6
and 2.3.1, respectively.
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and petroleum product working losses.
The most significant changes made to the ptnonipm
emissions involved moving some HAP records that should
have been nagged as IPM into the ptipm sector. The other
modifications are listed here and represent differences
between the published 2005 NEI v2 and the 2005 inventory
used for modeling:
1. Removed duplicate annual records (not sub-annual.
non-repeating records).
2. Removed a source with a state/county FIPS code of
30777; the "777" county FIPS represents portable
facilities that move across counties, but is not currently
a valid state/county FIPS code in the SMOKE ancillary
file "COSTCY". This Montana FIPS code was located
in northern Wyoming and contained very small
emissions.
3. Dropped sources with coordinates located well into the
oceans or lakes.
4. Fixed the coordinates for several larger sources that had
a state/county FIPS code mismatch with their inventory
coordinates greater than 10 km and emissions greater
than 10 tons per year of either NOX, VOC, SO2, or 5
tons/yr of PM2 5. These corrections were limited to a
small number of plants in Arizona, Indiana, Kentucky.
Ohio, and Virginia.
3.2.2 Nonpoint Sources (afdust, ag, nonpt)
The nonpoint portion of the 2005 NEI v2 generally did
not include updated emissions from the values used in
the 2002 NEI, and this modeling platform took a similar
approach. Consequently, several sectors were created from
the 2002 nonpoint NEI prior to modeling. The nonpoint
tribal-submitted emissions were removed to prevent possible
double counting with the county-level emissions. Because the
tribal nonpoint emissions are small, these omissions should
not impact results at the 12-km scale used for modeling. This
omission also eliminated the need to develop costly spatial
surrogate data to allocate tribal data to grid cells during the
SMOKE processing. The documentation for the nonpoint
sector of the 2005 NEI is available at: http://www.epa. gov/
ttn/chief/net/2005inventory.html
In the rest of this section, each of the platform sectors into
which the 2005 nonpoint NEI was divided is described, as
are the changes made to these data. See the 2002 platform
documentation for sectors that did not change
3.2.2.1 Area Fugitive Dust Sector (afdust)
The area-source fugitive dust (afdust) sector contains
PM10 and PM2 5 emission estimates for 2002 NEI nonpoint
SCCs identified by EPA staff as dust sources. This sector is
separated from other nonpoint sectors to make it easier to
apply a "transport fraction," that reduces emissions to reflect
observed diminished transport from these sources at the
scale of our modeling. Application of the transport fraction
prevents the overestimation of fugitive dust impacts in the
grid modeling as compared to ambient samples. Categories
included in this sector are paved roads, unpaved roads and
airstrips, construction (residential, industrial, road and total).
agriculture production and all of the mining 10-digit SCCs
beginning with the digits "2325." It does not include fugitive
dust from grain elevators because these are elevated point
sources.
The afdust sector was created from the 2002 NEI based on
SCCs and pollutant codes (i.e., PM10 and PM25) that are
considered "fugitive". A complete list of all possible fugitive
dust SCCs (including both 8-digit point source SCCs and
10-digit nonpoint SCCs) is provided at: http://www.epa.
gov/ttn/chief/emch/dustfractions/tf_scc_list2002nei_v2.xls.
However, not all of the SCCs in this file are present in the
2002 NEI.
Our approach was to apply the transportable fractions by
county such that all afdust SCCs in the same county receive
the same factor. The approach used to calculate the county-
specific transportable fractions is based on land use data
and is described by: http://www.epa.gov/ttn/chief/emch/
dustfractions/transportable_fraction_080305_rev.pdf
As the paper describing the approach mentions, a limitation
of the transportable fraction approach is the lack of monthly
variability, which would be expected due to seasonal changes
in vegetative cover. Further, the variability due to soil
moisture, precipitation, and wind speeds is not accounted
for by the methodology. An electronic version of the county-
level transport fractions can be found at: http://www.epa. gov/
ttn/chief/emch/dustfractions/transportfractions052506rev.xls
3.2.2.2 Agricultural Ammonia Sector (ag)
The agricultural NH3 "ag" sector comprises livestock
and agricultural fertilizer application emissions from the
nonpoint sector of the 2002 NEI. This sector is unchanged
in the 2005 platform. In building this sector, livestock and
fertilizer emissions were extracted based on the SCC. The
"ag" sector includes all of the NH3 emissions from fertilizer
from the NEI. However, the "ag" sector does include all of
the livestock ammonia emissions, as there are also significant
NH3 emissions from livestock in the point source inventory.
Most of the point source livestock NH3 emissions were
reported by the states of Kansas and Minnesota. For these
two states, farms with animal operations were provided as
point sources.5
The "ag" sector includes all of the NH3 emissions from
fertilizer from the NEI. However, the "ag" sector does not
include all of the livestock ammonia emissions, as there
are also significant NH3 emissions from livestock in the
point source inventory retained from the 2002 NEI. Note
that in these cases, emissions were not also in the nonpoint
inventory for counties for which they were in the point source
inventory; therefore no double counting occurred. Most of
the point source livestock NH3 emissions were reported by
the states of Kansas and Minnesota. For these two states,
farms with animal operations were provided as point sources
using the following SCCs6:
5 These point source emissions are also identified by the segment ID, which
is one of the following: "SWINE," "CATTLE," "DAIRY," or "PLTRY."
6 These point source emissions are also identified by the segment ID, which
is one of the following: "SWINE", "CATTLE", "DAIRY", or "PLTRY".
-------
30202001: Industrial Processes; Food and Agriculture;
Beef Cattle Feedlots; Feedlots General
30202101: Industrial Processes; Food and Agriculture;
Eggs and Poultry Production; Manure Handling: Dry
30203099: Industrial Processes; Food and Agriculture;
Dairy Products; Other Not Classified
There are also livestock NH3 emissions in the point source
inventory with SCCs of 39999999 (Industrial Processes;
Miscellaneous Manufacturing Industries; Miscellaneous
Industrial Processes; Other Not Classified) and 30288801
(Industrial Processes; Food and Agriculture; Fugitive
Emissions; Specify in Comments Field). These sources
were identified as livestock NH3 point sources based on
their facility name. The reason the livestock NH3 emissions
in the ptnonipm sector had to be identified was to properly
implement the emission projection techniques for livestock
sources in future years. The projection techniques cover all
livestock sources, including those in the ag and ptnonipm
sectors.
3.2.2.3 Other Nonpoint Sources (nonpt)
Nonpoint sources that were not subdivided into the afdust.
ag or nonpt sectors were assigned to the "nonpt" sector.
In preparing the nonpt sector, catastrophic releases were
excluded since these emissions were dominated by tire
burning, which is an episodic, location-specific emissions
category. Tire burning accounts for significant emissions of
paniculate matter in some parts of the country. Because such
sources are reported by a very small number of states, and are
inventoried as county annual totals without the information in
the NEI to temporally and spatially allocate the emissions to
the time and location where the event occurred, catastrophic
releases were excluded.
The nonpt sector includes emission estimates for
Portable Fuel Containers (PFCs), also known as "gas
cans." Inventories for PFCs were recently developed for
EPA's Mobile Source Air Toxics (MSAT) rule and were
incorporated into the 2002 NEI v3. The PFC inventory
consists of five distinct sources of PFC emissions, further
distinguished by residential or commercial use. The five
sources are: (1) displacement of the vapor within the can;
(2) spillage of gasoline while filling the can; (3) spillage of
gasoline during transport; (4) emissions due to evaporation
(i.e., diurnal emissions); and (5) emissions due to permeation.
Note that spillage and vapor displacement associated with
using PFCs to refuel nonroad equipment are included in the
nonroad inventory.
Statewide total annual VOC inventories were allocated to
counties using county-level fuel consumption ratios from
the NONROAD model. Of note from this documentation.
the developers derived the 2002 PFC inventory by linearly
interpolating inventories developed for 1999 and 2010.
3.2.4 Day-Specific Point Source Fires (ptfire)
Wildfire and prescribed burning emissions are contained in
the ptfire sector. The ptfire sector has emissions provided
at geographic coordinates (point locations) and has daily
emissions values.
For the 2005 Platform, the following SCCs from the
2005 NEI are considered "fires" (note that the actual SCC
description includes "Miscellaneous Area Sources" as the
first tier level description):
• 2810001000: Miscellaneous Area Sources; Other
Combustion; Forest Wildfires; Total
• 2810015000: Miscellaneous Area Sources; Other
Combustion; Prescribed Burning for Forest
Management; Total
• 2810005000: Miscellaneous Area Sources; Managed
Burning, Slash (Logging Debris); Total
The ptfire sector for the 2005 Platform excludes agricultural
burning and other open burning sources, which are included
in the nonpt sector. The agricultural burning and other
open burning sources are in the nonpt sector because these
categories were not factored into the development of the
ptfire sector. Additionally, their year-to-year impacts are
not as variable as wildfires and non-agricultural prescribed/
managed burns.
The ptfire sector includes wildfire and prescribed7 burning
emissions occurring in 2007, which were used for the 2007
model evaluation case. This sector includes emissions for
all 2007 wildfires and many prescribed burns with daily
estimates of each fire's emissions. It includes a satellite
derived latitude/longitude of the fire's origin and other
parameters associated with the emissions such as acres
burned and fuel load, which allow estimation of plume rise.
Note that Agricultural Burning is not included in the ptfire
sector as it is included in the nonpt sector.
The SCCs in the ptfire sector are the following:
• 2810001000: Miscellaneous Area Sources; Other
Combustion; Forest Wildfires; Total
• 2810005000: Miscellaneous Area Sources; Other
Combustion; Managed Burning, Slash (Logging
Debris);Total
The point source day-specific emission estimates for 2007
fires rely on Sonoma Technology, Inc. 's Satellite Mapping
Automated Reanalysis Tool for Fire Incident Reconciliation
(SMARTFIRE) system (Sullivan, et al., 2008). Figure 3-1
shows a functional diagram of the SMARTFIRE process.
SMARTFIRE involves the use the National Oceanic and
Atmospheric Administration's (NOAA's) Hazard Mapping
System (HMS) fire location information as input combined
with CONSUMEvS.O, a computer program designed to
predict emissions, fuel consumption, and heat release from
naturally burning fuels such as wood (Joint Fire Science
Program, 2009), and the Fuel Characteristic Classification
System (FCCS) fuel-loading database to estimate fire
emissions from wildfires and prescribed burns on a daily
basis.
The method involves the reconciliation of ICS-209 reports
(Incident Status Summary Reports) with satellite-based fire
detections to determine spatial and temporal information
about the fires. The ICS-209 reports for each large wildfire
7 For purposes of this document prescribed burning also includes managed
burning, i.e., "Other Combustion; Managed Burning, Slash (Logging
Debris)"
-------
are created daily to enable fire incident commanders to track
the status and resources assigned to each large fire (100 acre
timber fire or 300 acre rangeland fire). The SMARTFIRE
system of reconciliation with ICS-209 reports is described in
an Air and Waste Management Association report (Raffuse, et
al., 2007). Once the fire reconciliation process is completed,
the emissions are calculated using the U.S. Forest Service's
CONSUMEvS.O fuel consumption model and the FCCS fuel-
loading database in the Bluesky Framework (Ottmar, et al.,
2007).
The detection of fires with this method is satellite-based.
Note that the distinction between wildfire and prescribed burn
is not as precise as with ground-based methods. The fire size
was based on the number of satellite pixels and a nominal
fire size of 100 acres/pixel was assumed for a significant
number of fire detections when the first detections were not
matched to ICS 209 reports, so the fire size information is
not as precise as ground-based methods. Because the HMS
satellite product from NOAA is based on daily detections,
the emission inventory represents a time-integrated emission
estimate. For example, a large smoldering fire will show up
SMARTFIRE System
Functional Diagram
C
Start
Retrieve satellite
fire location point
data (FirePixete)
Projeo FirePixd
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area protection
(Alters Conic}
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perimeter (bum
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Retrieve ex sting
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r
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and associated data throua
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(Optional) Query
g&odalabase to
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{e.g. fuel loadings)
& add to snapshot
a web-based user interface
and if necessary, make
manual modifications.
Figure 3-1. SMARTFIRE System
-------
on satellite for many days and would count as acres burned
on a daily basis whereas a ground-based method would
count the area burned only once even it burns over many
days. Additional references for this method are provided in
McKenzie, et al., 2007; Ottmar et al., 2003; Ottmar et al.,
2006; and Anderson et al., 2004.
The SMOKE-ready "ORL" inventory files created from the
raw daily fires contain both CAPs and HAPs. The HAPs were
generated using the same emission factors as were used in
the 2002 Platform and described in Section 2.3 of the CAP
and HAP 2002-Based Platform, Version 3 (ftp://ftp.epa.
gov/EmisInventory/2002v3CAPHAP/documentation). The
BAFM HAP emissions from the inventory were obtained
using VOC speciation profiles (i.e., a "no-integrate noHAP"
use case).
3.2.5 Biogenic Sources (beis)
For CMAQ, biogenic emissions were computed based on
2005 meteorology data using the BEIS3.14 model from
SMOKE. The 2002 platform used the BEIS3.13 model;
otherwise, all underlying land use data and parameters are
unchanged for the 2005 platform.
The BEIS3.14 model creates gridded, hourly, model-species
emissions from vegetation and soils. It estimates CO, VOC.
and NOX emissions for the U.S., Mexico, and Canada. The
BEIS3.14 model is described further in:
http://www.cmascenter.org/conference/2008/slides/pouliot_
tale_two_cmas08.ppt.
The inputs to BEIS include:
• Temperature data at 2 meters which were obtained from
the CMAQ meteorological input files.
• Land-use data from the Biogenic Emissions Landuse
Database, version 3 (BELD3). BELD3 data provides
data on the 230 vegetation classes at 1-km resolution
over most of North America, which is the same land-
use data were used for the 2002 platform.
3.2.6 2005 Mobile Sources (on_noadj, on_moves_runpm,
on_moves_startpm, nonroad, alm_no_c3, seca_c3)
The 2005v4 platform onroad emissions are broken out into
three sectors: (1) "on_moves_startpm"; (2) "on_moves_
runpm"; and (3) "on_noadj". The aircraft, locomotive, and
commercial marine emissions are divided into two nonroad
sectors: "alm_no_c3" and "seca_c3", and as previously
mentioned, the aircraft emissions are now in the nonEGU
point inventory.
While the previous EPA platforms used NMDVI for the
onroad and nonroad sectors8, some of the onroad emissions
in the 2005 platform were based on an initial version9
of the MOVES2010 model run for the year 2007. This
MOVES2010 model was used to make sure to include
the exhaust mode PM2 5 emissions from onroad gasoline
vehicles, including temperature effects that are much larger
than were found in previous versions of onroad PM2 5. The
onroad gasoline emissions are based on MOVES2010 for
the pollutants listed in Table 3-4. MOVES2010 was used
to create 2007 emissions by state and month and these
emissions were then allocated to counties based on 2005
NMIM-based county-level data. The reason for the state
resolution was due to (a) run time issues that made a county
run done for the nation infeasible in the timeframe required
and (b) uncompleted efforts to create a national database of
county-specific inputs to MOVES2010. The emissions that
did not come from the MOVES2010 model were obtained
from the 2005 NMIM runs, which are consistent with the
2005NEIv2
Included in the 2005 CAP-BAFM Platform
PM2S; exhaust, partially speciated2
PM10, total exhaust
PM2S and PM10 brake and tire wear, not speciated
VOC; except refueling
CO
Other than California which were provided by CARB and were based on
the mobile models used by California, EMFAC and OFFROAD, for onroad
and nonroad emissions, respectively.
The version of MOVES is "MOVES2010" released in December 2009,
this initial version was replaced by the publicly released MOVES2010a
version in August 2010 and is available at www.epa. gov/otaq/models/
moves/
Benzene; except refueling
Formaldehyde
Acetaldehyde
Table 3-4. Pollutants covered by the
MOVES2010 model in the 2005 Platform1
1 MOVES2010 data were used only for onroad gasoline
vehicles with the exception of motorcycles. MOVES2010
data were not used for any California onroad emissions
2 Exhaust mode PM2 5 species from MOVES consist of: PEC.
PSO4 and the difference between PM2 5 and PEC (named
as "PM25OC"). Brake wear and tire wear PM2 5 emissions
were not available from draft MOVES.
For onroad mobile emissions in California, year 2007
emissions were generated by linearly interpolating year 2005
and year 2009 EMFAC-based emissions. For nonroad mobile
emissions in California, year 2007 emissions were generated
by linearly interpolating year 2005 and year 2009 OFFROAD
model-based emissions. The 2005 v2 NEI contains onroad
and nonroad mobile emissions generated using NMIM (EPA.
2005b) for all of the U.S. except for California.10 NMIM
data was used for some of the nonroad mobile sources.
NMIM relies on calculations from the MOBILE6 and
NONROAD2005 models as described below, and in the NEI
documentation. Inputs to NMIM are posted with the 2005
Emission Inventory. The direct link is: ftp://ftp.epa.gov/
Emislnventory/2005_nei/mobile_sector/ncd/ncd20080522.
zip.
NMIM creates the onroad and nonroad emissions on a
month-specific basis that accounts for temperature, fuel
types, and other variables that vary by month. Inventory
10 Although OTAQ generated emissions using NMIM for California, these
were not used in the 2005 NEI version 2, but rather were replaced by
state-submitted emissions.
-------
documentation for the 2005 NEI v2 onroad and nonroad
sectors is also posted with other 2005 NEI documentation;
the direct link is: ftp://ftp.epa.gov/EmisInventory/2005_nei/
mobile/2005_mobile_nei_version_2_report.pdf. The year
2007 NMIM nonroad emissions were generated using
updated activity (fuels, vehicle population, etc) data, but are
otherwise similar in methodology to those generated for the
2005 NEI.
The residual fuel commercial marine vessel (CMV).
also referred to as Category 3 (C3) consists of a set of
approximately 4-km resolution point source format
emissions; these are now modeled separately as point sources
in the "seca_c3" sector for the 2005 platform, and were
projected to year 2007 using OTAQ-supplied growth factors.
The nonroad sector is the only 2002 mobile sector with U.S.
emissions that was left intact in the 2005v4 platform and
is still based on NMIM. For this study, NMIM was run for
2007.
With the exception of the seca_c3 point source-formatted
sector, the mobile sectors are at county and SCC resolution.
Tribal data from the alm_no_c3 sector have been dropped
because spatial surrogate data is not available, and the
emissions are small. Thus, these data were removed from the
SMOKE input inventories for 2005.
All mobile sectors that have benzene, acetaldehyde.
formaldehyde or methanol present in the inventory data, use
these HAPs via "integration" for input into the air quality
model. A few categories of nonroad sources (CNG and
LPG-fueled equipment) do not have BAFM and therefore
utilize the "no-integrate", "no-hap-use" case which means
VOC from these sources is speciated to provide BAFM.
3.2.7 Adjustments to Onroad Mobile Source PM Emissions
(on_moves_runpm, on_moves_startpm)
The on_moves_rupm and on_moves_startpm sectors contain
MOVES2010 emissions for PM for non-California onroad
gasoline cold-start exhaust except for motorcycles. These
emissions (and the on_moves_runpm sector discussed in the
next section) are processed separately from the remainder
of the onroad mobile emissions because they are subject
to hourly temperature adjustments, and these temperature
adjustments are different for cold-start and running exhaust
modes.
Temperature adjustments were applied to account for the
strong sensitivity of PM exhaust emissions to temperatures
below 72 °F. Because it was not feasible to run MOVES
directly for all of the gridded, hourly temperatures needed
for modeling, emissions of PM exhaust at 72 °F were created
and temperature adjustments applied after the emissions were
spatially and temporally allocated. The PM2 5 adjustments
were different for starting and running exhaust and applied to
SMOKE gridded, hourly intermediate files using the gridded
hourly temperature data also input to the CMAQ model. One
result of this approach is that inventory summaries based
on the raw SMOKE inputs for the on_moves_startpm and
on_moves_runpm sectors will not be consistent with the
final modeled emissions because they will not include the
temperature adjustments. As a result, the post-processing for
temperature adjustments included computing the emissions
totals at state, county, and month resolution to use for
summaries.
Figure 3-2 shows how PM emissions increase with colder
temperatures and how start exhaust emissions increase more
than running exhaust emissions.
A number of features of the MOVES output required
additional processing to develop county-level monthly ORL
files for SMOKE. As stated earlier, the spatial resolution of
the MOVES data was at the state level and these data were
allocated to county level prior to input into SMOKE. In
addition, the exhaust PM2 5 emissions from MOVES were
partially speciated. To retain the speciated elemental carbon
and sulfate emissions from MOVES, the speciation step that
is usually done in SMOKE was performed prior to SMOKE.
and it was modified to allow the temperature adjustments to
be done only on the species affected by temperature. Finally.
because the start emissions were broken out separately
from running exhaust emissions, they were assigned to new
SCCs (urban and rural parking areas) that allowed for the
appropriate spatial and temporal profiles to be applied in
SMOKE.
A list of the procedures performed to prepare the MOVES
data for input into SMOKE is provided below.
i. State-level emissions were allocated to counties using
state-county emission ratios by SCC, pollutant, and
emissions mode (e.g., evaporative, exhaust) for each
month. The ratios were computed using NMIM 2007
data.
ii. Start and run emissions were assigned to urban
and rural SCCs based on the county-level ratio of
emissions from urban versus rural local roads from
the NMIM onroad gasoline data. For example, the
LDGV start emissions in the state-total MOVES
data (assigned SCC 2201001000) were split into
urban (2201001370) and rural (2201001350) based
on the ratio of LDGV urban (2201001330) and rural
(2201001210) local roads.
iii. MOVES-based PM2 5 species at 72 °F were converted
to SMOKE-ready PM species. The SMOKE-ready
species are listed below and the speciation technique
used to obtain the SMOKE-ready species is further
discussed in Appendix B of the 2005v4 emissions
modeling platform documentation.
• PEC_72: unchanged from MOVES-based PM25EC,
subject to temperature adjustment below 72 °F
-------
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70
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3
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10
0
• Run Exhaust
• Start Exhaust
\
\
\
-20 -10
11
21
31
41
51
61
71
Temperature (°F)
Figure 3-2. MOVES exhaust temperature adjustment functions.
• POC_72: modified MOVES-based PM25OC to
remove metals, PNO3 (computed from MOVES-
based PM25EC), NH4 (computed from MOVES-
based PM25SO4 and PNO3), and MOVES-based
PM25SO4. Subject to temperature adjustment
below 72 °F.
• PSO4: unchanged from MOVES-based PM25SO4,
not subject to temperature adjustment.
• PNO3: computed from MOVES-based PM25EQ
not subject to temperature adjustment.
• OTHER: sum of computed metals (fraction of
MOVES-based PM25EC) and NH4 (computed
from PNO3 and PSO4), not subject to temperature
adjustment.
• PMFINE_72: Computed from OTHER and fraction
of POC_72. Subject to temperature adjustment
below 72 °F.
• PMC_72: Computed as fraction of sum of
PMFINE_72, PEC_72, POC_72, PSO4, and PNO3.
Subject to temperature adjustment below 72 °F.
The result of these preprocessing steps is that SMOKE-
ready PM emissions that do not exactly match what MOVES
provides. The emissions are conserved during allocation from
the state to county and from the generic total "start" SCCs
to the two new parking SCCs that end in "350" and "370".
Primary paniculate elemental carbon (PEC) and primary
paniculate sulfur (PSO4) components of PM2 5 emissions are
also conserved as they are simply renamed from the MOVES
specie "PM25EC". However, as seen above, POC, PNO3.
and PMFINE components involve multiplying the MOVES
PM species by components of an onroad gasoline exhaust
speciation profile described in Appendix B of the 2005v4
platform documentation.
3.2.8 Onroad Mobile Sources without Adjustments
(on_noadj)
The on_noadj sector consists of the remaining onroad mobile
emissions not covered by the on_moves_startpm and on_
moves_runpm sectors. These emissions did not receive any
temperature adjustments in our processing. There are four
sources of data that are pre-processed to create two sets of
monthly inventories for this sector.
1. MOVES-based onroad excluding gasoline exhaust PM:
These are the monthly MOVES-based emissions from
three MOVES inventories:
a. Diesel Exhaust: VOC, NOX, SO2, PM25, PM10,
NH3, CO, 1,3-butadiene (106990), acetaldehyde
(75070), acrolein (107028), benzene (71432), and
formaldehyde (50000)
b. Gasoline Exhaust: VOC, NOX, SO2, NH3, CO,
1,3-butadiene (106990), acetaldehyde (75070),
acrolein (107028), benzene (71432), and
formaldehyde (50000)
c. Evaporative: Non-refueling VOC and benzene
d. Brake and tire wear: Total (not speciated) PM2 5 and
PM10 from gasoline and diesel vehicles
-------
e. For these pollutants listed, these non-California
MOVES emissions do not require the same
intermediate temperature adjustments and can
therefore be processed with the remaining "no
adjust" onroad mobile emissions. These emissions
contain both running and parking sources and are
pre-processed from state-level to county-level much
like the on_moves_startpm and on_moves_runpm
sectors already discussed. The preprocessing for
these emissions did not require species calculations
because the raw MOVES emissions translated
directly to SMOKE inventory species.
2. California onroad inventory: California year 2007
complete CAP/HAP onroad inventory. California
monthly onroad emissions are year 2007 and are based
on September 2007 California Air Resources Board
(CARB) submitted 2005 and 2009 data which has been
interpolated to provide 2007 values. NH3 emissions
are from NMIM runs for California. Only those HAPs
that are also estimated by NMIM for nonroad mobile
sources were retained; all other HAPs provided by
California were dropped. The California onroad
inventory does not use the SCCs for Heavy Duty
Diesel Vehicles (HDDV) class 6 & 7 (2230073XXX)
emissions. California does not specify road types, so
NMIM California ratios were used to break out vehicle
emissions to the match the more detailed NMIM level.
The remainder of this section discusses the pre-processing
required to create monthly ORL files for the remainder of the
on_noadj sector (#3 above).
EPA/OTAQ created the NMIM 2005v2 onroad mobile
CAP/HAP emissions for all states and sources using the
MOBILE6 model version M6023ChcOxFixNMIM. The CO2
emissions were removed, along with emissions of dioxins
and furans and emissions that were replaced by MOVES and
California-submitted data. The onroad refueling emissions
were also removed since the NEI treats onroad refueling as a
stationary source that is included in the nonpt sector (gasoline
distribution, Stage II, SCC=2501060100), and can be found
in the point sector in a handful of states (gasoline distribution
Stage II; vapor loss or unclassified, SCC=40600401,
40600402, 40600403, and 40600499 in California, Colorado,
Kentucky, and North Carolina).
Emissions were converted from monthly totals to monthly
average-day based the on number of days in each month.
Furthermore, this sector includes exhaust, evaporative, brake
wear and tire wear emissions from onroad sources, which
allowed us to use speciation profiles that are specific to
each of these processes. The 2007 VMT database was based
on 2002 VMT grown to 2007 based on Federal Highway
Administration (FWHA) data, unless state-provided VMT
was available.
3.2.9 Nonroad Mobile Sources—NMIM-Based Nonroad
(nonroad)
The nonroad sector includes monthly exhaust, evaporative
and refueling emissions from nonroad engines (not including
commercial marine, aircraft, and locomotives) derived
from NMIM for all states except California. The NMIM
configuration relied on the version of the NONROAD2005
model (NR05c-BondBase) used for the marine spark ignited
(SI) and small SI engine proposed rule, published May 18,
2007 (EPA, 2007c). For 2007, the NONROAD2005 model
(NR05c-BondBase) is equivalent to NONROAD2008a, since
it incorporated Bond rule revisions to some of the base case
inputs and the Bond rule controls did not take effect until
future years. As with the onroad emissions, NMIM provides
nonroad emissions for VOC by three emission modes:
exhaust, evaporative and refueling. Unlike the onroad sector,
refueling emissions for nonroad sources are not dropped from
processing for this sector.
EPA/OTAQ ran NMIM to create county-SCC emissions
for the 2007 nonroad mobile CAP/HAP inventory. In a
similar process as for the on_noadj sector, California NMIM
emissions were removed and replaced with emissions
submitted by California, but scaled to 2007 using linear
interpolation of year 2005 and 2009 inventories. Emissions
were converted from monthly totals to monthly average-
day based the on number of days in each month. Similar to
onroad NMIM emissions, EPA default inputs were replaced
by state inputs where provided. The NMIM inventory
documentation describes this and all other details of the
NMIM nonroad emissions development for the 2005v4
platform:
ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/2005_
mobile_nei_version_2_report.pdf
California monthly nonroad emissions are year 2007 and are
based on linearly-interpolated September 2007 California
Air Resources Board (CARB) submitted inventories for
the years 2005 and 2009. NH3 emissions are from NMIM
runs for California because these were not included in the
California NEI submittal. HAP emissions were estimated
by applying HAP-to-CAP ratios computed from California
data in the NEI 2005 v2 submittal. Only those HAPs that are
also estimated by NMIM for nonroad mobile sources were
retained; all other HAPs were dropped.
The CARB-based nonroad data did not have mode-specific
data for VOC (exhaust, evaporative, and refueling). The
annual total California data was split into monthly, mode-
specific nonroad emissions for California using the NMIM
results. Details on this process are documented separately
(Strum, 2007). Nonroad refueling emissions for California
were computed as Gasoline Transport (SCC=2505000120)
emissions multiplied by a factor of 0.46 (to avoid double
counting with portable fuel container (PFC) emissions in the
nonpt sector) and were allocated to the gasoline equipment
types based on ratios of evaporative-mode VOC. The factor
of 0.46 was computed by dividing the NMIM-derived
California refueling for 2005 by the sum of portable fuel
container emissions and NMIM-derived refueling for 2005.
-------
3.2.10Nonroad Mobile Sources: Aircraft, Locomotive and
Commercial Marine (alm_no_c3)
The alm_no_c3 sector contains CAP and HAP emissions
from locomotive and commercial marine sources, except for
category 3/residual-fuel (C3) commercial marine vessels.
In previous modeling platforms, this sector also contained
aircraft emissions, but here aircraft emissions have been
removed from the sector because point-source airports were
provided in the 2005 NEI v2 point source inventory and
are included as part of the ptnonipm sector. Note that the
C3 commercial marine vessel emissions are in the seca_c3
sector. Note that the "a" in the "alm_no_c3" sector name is
now misleading because aircraft are no longer in this sector.
The remaining emissions in the alm_no_c3 sector are year
2002 emissions unchanged from the 2002 platform. The
2005v4 platform documentation has a complete list of SCCs
found in the alm_no_c3 sector. The documentation of the
2002 NEI for the aim sector is available at: http://www.epa.
gov/ttn/chief/net/2002inventory.html#documentation.
For modeling purposes, the following additional changes
were made to the data in this sector for the 2005v4 platform:
• Removed C3 CMV SCCs (residual fuel) and aircraft
SCCs.
• Removed railway maintenance emissions (SCCs
2285002015, 2285004015, and 2285006015) because
these are included in the nonroad NMIM monthly
inventories. This change was made for the 2002
platform and is retained here in the 2005 platform.
• For the purpose of CAP-HAP VOC integration.
removed benzene, formaldehyde, and acetaldehyde for
all sources for which these HAPs were not integrated
with VOC. These sources are considered no-integrate
when the source of data between VOC and VOC HAPs
is inconsistent or VOC analysis of VOC and VOC
HAPs indicates the source is not integrated. Although
the CAP-HAP integration approach also required the
removal of methanol for no-integrate sources, the only
sources in this sector that included methanol were in
California, where the integrate approach was used for
all sources and therefore did not need to remove it.
The 2002 platform documentation goes into greater detail on
the locomotives and C1/C2 CMV emissions.
3.2.11 Nonroad mobile sources: C3 commercial marine
(seca_c3)
The raw seca_c3 sector emissions data were developed in
an ASCII raster format used since the Emissions Control
Area-International Marine Organization (ECA-IMO) project
began in 2005, then known as the Sulfur Emissions Control
Area (SECA). These emissions consist of large marine
diesel engines (at or above 30 liters/cylinder) that until very
recently, were allowed to meet relatively modest emission
requirements, often burning residual fuel. The emissions in
this sector are comprised of primarily foreign-flagged ocean-
going vessels, referred to as Category 3 (C3) ships. The
seca_c3 (EGA) inventory includes these ships in ports and
underway mode and includes near-port auxiliary engines. An
overview of the ECA-IMO project and future year goals for
reduction of NOX, SO2, and PM C3 emissions can be found at:
http ://www. epa. gov/oms/re gs/nonroad/marine/ci/420f09015.
htm
The base year EGA inventory is 2002 and consists of these
CAPs: PM10, CO, CO2, NH3, NOX, SOX (assumed to be SO2),
and Hydrocarbons (assumed to be VOC). EPA developed
regional growth (activity-based) factors that were applied to
create a 2007 inventory from the 2002 data. These growth
factors are provided in Table 3-5 and are mapped and
documented in the following report:
http://www.epa.gov/oms/regs/nonroad/marine/ci/420r09007-
chap2.pdf
These growth factors are the same for all pollutants except
which includes a Tier 1 Standard.
Region
Alaska
East Coast
Gulf Coast
Hawaii
North Pacific (Washington)
1.114
1.182
1.092
1.212
1.114
All_other
pollutants
1.179
South Pacific (Oregon and California) 1.212
Great Lakes 1.082
Table 3-5. Regional growth factors used to project 2002
C3 emissions to 2007
The raw EGA inventory started as a set of ASCII raster (pixel
image) dataset emissions at approximately 4-km resolution
that was converted to SMOKE point-source ORL input
format as described in this conference paper:
http://www.epa.gov/ttn/chief/conference/eil7/session6/
masoapdf
This paper describes how the ASCII raster dataset was
converted to latitude-longitude, mapped to state/county FIPS
codes that extend up to 200 nautical miles (nm) from the
coast, assigned stack parameters, and how the monthly ASCII
raster dataset emissions were used to create monthly temporal
profiles. Counties were assigned as extending up to 200nm
from the coast because of this was the distance through the
Exclusive Economic Zone (EEZ), a distance that would be
used to define the outer limits of the Emissions Control Area-
International Marine Organization (ECA-IMO) controls for
these vessels.
The 2007 EGA-based C3 inventory does not delineate
between ports and underway (or other C3 modes such as
hoteling, maneuvering, reduced-speed zone, and idling)
emissions. Therefore, these emissions were assigned to the
broad ("total") SCC for C3 CMV (2280003000). This has
no effect on temporal allocation or speciation compared
to existing profiles for underway and port C3 emissions
(2280003100 and 2280003200).
Factors were applied to compute HAP emissions (based on
emissions ratios) to VOC to obtain HAP emissions values.
Table 3-6 shows these factors. Because HAPs were computed!
-------
directly from the CAP inventory and the calculations are
therefore consistent, the entire seca_c3 sector utilizes
CAP-HAP VOC integration to use the VOC HAP species
directly, rather than VOC speciation profiles.
Pollutant
Acetaldehyde
Benzene
Formaldehyde
Apply to
VOC
VOC
VOC
Pollutant Code
75070
71432
50000
Factor
0.0002286
9.795E-06
0.0015672
Table 3-6. HAP emission ratios for generation of HAP
emissions from criteria emissions for C3 commercial
marine vessels
The emissions were converted to SMOKE point source
ORL format, allowing for the emissions to be allocated
to modeling layers above the surface layer. All non-US
emissions (i.e., in waters considered outside of the 200nm
EEZ, and hence out of the U.S. territory) are assigned a
dummy state/county FIPS code=98001. The SMOKE-ready
data have also been cropped from the original ECA-IMO data
to cover only the 36-km CMAQ domain, which is the largest
domain used for this effort, and larger than the 12km domain
used in this project.
3.2.12 Emissions from Canada, Mexico and Offshore
Drilling Platforms (othpt, othar, othon)
The emissions from Canada, Mexico, and Offshore Drilling
Platforms are included as part of three sectors: othpt, othar,
and othon. The "oth" refers to the fact that these emissions
are "other" than those in the 2005 NEI, and the third and
fourth characters provide the SMOKE source types: "pt"
for point, "ar" for "area and nonroad mobile", and "on" for
onroad mobile. Mexico's emissions are unchanged from the
2002 Platform with one exception -one stack diameter was
updated (recomputed from stack velocity and flowrate) in the
Mexico border states point inventory.
For Canada, year 2006 emissions were used, with several
modifications:
i. Wildfires and prescribed burning emissions were not
included because Canada does not include these inven-
tory data in their modeling.
ii. In-flight aircraft emissions were not included because
these are also not included for the U.S. modeling.
iii. A 75% reduction ("transport fraction") to PM for the
road dust, agricultural, and construction emissions
in the Canadian "afdust" inventory. This approach is
more simplistic than the county-specific approach used
for the U.S., but a comparable approach was not avail-
able for Canada.
iv. Speciated VOC emissions from the ADOM chemical
mechanism were not included.
v. Residual fuel CMV (C3) SCCs (22800030X0) were
removed because these emissions are included in the
seca_c3 sector, which covers not only emissions close
to Canada but also emissions far at sea. Canada was
involved in the inventory development of the seca_c3
sector emissions.
vi. Wind erosion (SCC=2730100000) and cigarette
smoke (SCC=2810060000) emissions were removed
from the nonpoint (nonpt) inventory; these emissions
are also absent from the U.S. inventory.
vii. Quebec PM2 5 emissions (2,000 tons/yr) were removed
for one SCC (2305070000) for Industrial Processes,
Mineral Processes, Gypsum, Plaster Products due
to corrupt fields after conversion to SMOKE input
format. This error should be corrected in a future
inventory.
viii. Excessively high CO emissions were removed from
Babine Forest Products Ltd (British Columbia plan-
tid='5188') in the point inventory. This change was
made because the value of the emissions was impos-
sibly large.
ix. The county part of the state/count FIPS code field in
the SMOKE inputs were modified in the point inven-
tory from "000" to "001" to enable matching to exist-
ing temporal profiles.
For Mexico emissions for 1999 (Eastern Research Group
Inc., 2006) were used as these were developed as part of a
partnership between Mexico's Secretariat of the Environment
and Natural Resources (Secretaria de Medio Ambiente y
Recursos Naturales-SEMARNAT) and National Institute
of Ecology (Institute Nacional de Ecologia-INE), the U.S.
EPA, the Western Governors' Association (WGA), and the
North American Commission for Environmental Cooperation
(CEC). This inventory includes emissions from all states in
Mexico.
The offshore emissions include point source offshore oil and
gas drilling platforms. Updated offshore emissions from the
2005 NEI v2 point source inventory were used. The offshore
sources were provided by the Mineral Management Services
(MMS).
3.2.13 SMOKE-ready non-anthropogenic chlorine
inventory
For the ocean chlorine, the same data as in the CAP and
HAP 2002-based Platform was used. See ftp://ftp.epa.gov/
EmisInventory/2002v3CAPHAP/documentation for details.
3.3 Emissions Modeling Summary
The CMAQ model requires hourly emissions of specific gas
and particle species for the horizontal and vertical grid cells
contained within the modeled region (i.e., modeling domain).
To provide emissions in the form and format required by
CMAQ, it is necessary to "pre-process" the "raw" emissions
(i.e., emissions input to SMOKE) for the sectors described
above. In brief, this processing step transforms these
emissions from their original temporal resolution, pollutant
resolution, and spatial resolution into the data required by
CMAQ. The temporal resolution of the emissions input to
-------
SMOKE for the 2005 Platform varies across sectors, and may
be hourly, monthly, or annual total emissions. The spatial
resolution, which also can be different for different sectors.
may be individual point sources or county totals (province
totals for Canada, municipio totals for Mexico).
The pollutants for all sectors except for biogenics and
ocean chlorine are those inventoried for the NEI. The
pre-processing steps involving temporal allocation, spatial
allocation, pollutant speciation, and vertical allocation of
point sources are referred to as emissions modeling. This
section provides some basic information about the tools and
data files other than inventories used for emissions modeling
as part of the 2005 Platform.
3.3.1 The SMOKE Modeling System
SMOKE version 2.6 was used to pre-process the raw
emissions to create the emissions inputs for CMAQ.
SMOKE executables and source code are available from the
Community Multiscale Analysis System (CMAS) Center at
http ://www. cmascenter.org.
3.3.2 Key Emissions Modeling Settings
Emissions inventories for each sector are processed
separately through SMOKE to create gridded, hourly.
speciated emissions. The final merge program (Mrggrid)
is then run to combine the model-ready, sector-specific
emissions across sectors. The SMOKE settings in the "run
scripts" and the data in the SMOKE ancillary files control
the approaches used by the individual SMOKE programs
for each sector. Table 3-7 summarizes the major processing
steps of each platform sector. The "Spatial" column shows
the spatial approach: "point" indicates that SMOKE maps
the source from a point (i.e., latitude and longitude) location
to a grid cell, "surrogates" indicates that some or all of the
sources use spatial surrogates to allocate county emissions
to grid cells, and "area-to-point" indicates that some of
the sources use the SMOKE area-to-point feature to grid
the emissions. The "Speciation" column indicates that all
sectors use the SMOKE speciation step, though speciation
of biogenic emissions is done within BEIS3 and not as a
separate SMOKE step. The "Inventory resolution" column
shows the inventory temporal resolution from which SMOKE
needs to calculate hourly emissions.
Finally, the "plume rise" column indicates the sectors for
which the in-line approach is used. These sectors are the
only ones which will have emissions in aloft layers, based
on plume rise. For the 2005 Platform, SMOKE was not used
to compute vertical plume rise; this was done in CMAQ
using stack data in SMOKE output files for each model-
ready sector. The one sector with "in-line" only, seca_c3.
was processed so that the entire emissions would be in
aloft layers. Thus, there were no seca_c3 emissions in the
2-dimensional, layer-1 files created by SMOKE. Rather the
speciated and temporalized source-based CMAQ inputs for
seca c3 were used for the vertical allocation.
ptipm
ptnonipm
othpt
nonroad
othar
seca_c3
alm_no_c3
on_noadj
on_moves_
startpm
on_moves_
runpm
othon
nonpt
afdust
beis
ptfire
point
Yes
point Yes
point Yes
surrogates
& Yes
area-to-point
surrogates Yes
point Yes
surrogates
& Yes
area-to-point
surrogates Yes
surrogates Yes
surrogates Yes
surrogates Yes
surrogates
& Yes
area-to-point
surrogates Yes
surrogates Yes
pre-gridded
landuse
point Yes
daily &
hourly
annual
annual
in-line
in-line
in-line
annual
annual
annual
monthly
monthly
monthly
annual
in-line
in BEIS
annual
annual
hourly
in-line
Table 3-7. Key emissions modeling steps by sector
One of the issues found was that when using in-line
processing, the PELVCONFIG file cannot allow grouping.
otherwise the "inline" versus "offline" (i.e., processing
whereby SMOKE creates 3-dimensional files) will not give
identical results. Since a PELVCONFIG file with grouping
was used, the in-line approach should be used to exactly
replicate our results.
3.3.3 Spatial Configuration
For this project, we ran SMOKE and CMAQ were run for a
12-km modeling domain as shown in Figure 3-3. The grid
used a Lambert-Conformal projection, with Alpha =33, Beta
= 45 and Gamma = -97, with a center of X = -97 and Y = 40.
Later sections provide details on the spatial surrogates and
area-to-point data used to accomplish spatial allocation with
SMOKE.
3.3.4 Chemical Speciation Configuration
The emissions modeling step for chemical speciation
creates "model species" needed by the air quality model for
a specific chemical mechanism. These model species are
either individual chemical compounds or groups of species.
called "model species." The chemical mechanism used for
the 2005 Platform is the Carbon Bond 05 (CB05) mechanism
(Yarwood, 2005) with secondary organic aerosol (SOA) and
-------
12km CONUS nationwide)d<"iia
x,y: -255BOOO.-1728000
col: 459 row: 299
Figure 3-3. CMAQ Modeling Domain
HONO enhancements as described in
http://www.cmascenter.org/help/model_docs/cmaq/4.7/
RELEASE_NOTES.txt.
From the perspective of emissions preparation, it is the same
mechanism used in the 2002 Platform except that additional
input model species are needed to support the nitrous acid
(HONO) chemistry enhancements and additional input model
species are needed to support SOA. Table 3-8 lists the model
species produced by SMOKE for use in CMAQ. The only
three input species that were not in the CAP 2002-Based
Platform described in 2002 "CAP-only" Platform (http://
www.epa. gov/scramOO l/reports/Emissions%20TSD%20
Voll_02-28-08.pdf) are nitrous acid (HONO), BENZENE
and sesquiterpenes (SESQ). It should be noted that the
BENZENE model species is not part of CB05 in that the
concentrations of BENZENE do not provide any feedback
into the chemical reactions (i.e., it is not "inside" the
chemical mechanism). Rather, benzene is used as a reactive
tracer and as such is impacted by the CB05 chemistry.
BENZENE, along with several reactive CBO5 species
(such as TOL and XYL) plays a role in SOA formation in
CMAQ4.7.
The approach for speciating PM2 5 emissions is the same
as that described for the 2002 platform except that two
of the onroad sectors, and Canadian emissions contained
pre-speciated PM emissions which were not further speciated
in SMOKE . The approach for speciating VOC emissions
from non-biogenic sources is different in two major ways: 1)
for some sources, HAP emissions are used in the speciation
process to allow integration of VOC and HAP emissions
in the NEI. This has the result of modifying the speciation
profiles based on the HAP emission estimates which are
presumed to be more accurate than the speciated VOC
results for the HAPs; and, 2) for some mobile sources,
"combination" profiles are specified by county and month
and emission mode (e.g., exhaust, evaporative). SMOKE
computes the resultant profile on the fly given the fraction
of each specific profile to use for the county, month and
emission mode. A new feature and new profile file in
SMOKE (the GSPRO_COMBO file) allowed the use of this
approach for the 2005 Platform.
-------
Inventory
Pollutant
CO
Model
Species
ALDX
IDLE
ISOP
MEOH
XYL
Various SESQ
additional VOC
species from the
biogenics model
which do not
map to the above
model species
PM,
PM.
PMC
PEC
Model species description
Carbon monoxide
Nitrogen oxide
Nitrogen dioxide
Nitrous acid
Sulfur dioxide
Sulfuric acid vapor
Ammonia
Acetaldehyde
Propionaldehyde and higher
aldehydes
Benzene (not part of CB05)
Ethene
Ethane
Ethanol
Formaldehyde
Internal olefin carbon bond
(R-C=C-R)
Isoprene
Methanol
Terminal olefin carbon bond
(R-C=C)
Paraffin carbon bond
Toluene and other monoalkyl
aromatics
Xylene and other polyalkyl
aromatics
Sesquiterpenes
Terpenes
Coarse PM > 2.5 microns and
Particulate elemental carbon
< 2.5 microns
Particulate nitrate < 2.5 microns
Particulate organic carbon
(carbon only) < 2.5 microns
Particulate Sulfate
< 2.5 microns
Other particulate matter < 2.5
microns
The VOC speciation approach for the 2005 Platform differed
from the 2002 Platform in that, for some of the U. S. platform
sectors, HAP emissions from the NEI were included in the
speciation process. That is, instead of speciating VOC to
generate all of the species listed in Table 3-8 as was done
for the 2002 platform, emissions of the 4 HAPs, benzene.
acetaldehyde, formaldehyde and methanol (BAFM) from
the NEI were integrated with the NEI VOC. The integration
process (described in more detail below) combines the
BAFM HAPs with the VOC in a way that does not double
count emissions and uses the BAFM directly in the speciation
process. Generally, the HAP emissions from the NEI are
believed to be more representative of emissions of these
compounds than their generation via VOC speciation.
The BAFM HAPs were chosen because, with the exception
of BENZENE, they are the only explicit VOC HAPs in
the base version of CMAQ 4.7 (CAPs only with chlorine
chemistry) model. By "explicit VOC HAPs," we mean model
species that participate in the modeled chemistry using the
CB05 chemical mechanism. The use of these HAP emission
estimates along with VOC is called "HAP-CAP integration".
BENZENE was chosen because it was added as a model
species in the base version of CMAQ 4.7, and there was
a desire to keep its emissions consistent between multi-
pollutant and base versions of CMAQ.
The integration of HAP VOC with VOC is a feature available
in SMOKE for all inventory formats other than PTDAY (the
format used for the ptfire sector). SMOKE allows the user
to specify the particular HAPs to integrate and the particular
sources to integrate. The particular HAPs to integrate are
specified in the INVTABLE file, and the particular sources
to integrate are based on the NHAPEXCLUDE file (which
actually provides the sources that are excluded from
integration11). For the "integrate" sources, SMOKE subtracts
the "integrate" HAPs from the VOC (at the source level) to
compute emissions for the new pollutant "NONHAPVOC."
The user provides NONHAPVOC-to-NONHAPTOG factors
and NONHAPTOG speciation profiles. SMOKE computes
NONHAPTOG and then applies the speciation profiles to
allocate the NONHAPTOG to the other CMAQ VOC species
not including the integrated HAPs. This process is illustrated
in Figure 3-4. Note that BAFM emissions do not need to
be removed from no-integrate sources in a sector where
all sources are no-integrate because this is accomplished
by through use of a SMOKE ancillary "INVTABLE"
which essentially drops all the BAFM in that sector.
CAP-HAP integration was considered for all sectors and
developed "integration criteria" for some of those. Table 3-9
summarizes the integration approach for each platform sector
used in Step 1 of Figure 3-4.
Table 3-8. Model Species produced by SMOKE for CB05
with SOAfor CMAQ 4.7
11 In SMOKE version 2.6 the options to specify sources for integration are
expanded so that a user can specify the particular sources to include or
exclude from integration, and there are settings to include or exclude all
sources within a sector.
-------
Step 1: Analyze Inventory to determine which sources will be "integrate" sources
For each Sector,
ExamineEmissions
Sources of VOC and
B,A,F,M
Determine which sources
will not be Integrated (cither
whole sector or some
sources within a sector)
based on "Integration
Criteria"
Create list of
"no-integrate"
sources
NHAPEXCLUDE
Ancillary file
Ready for SMOKE
Remove B,F,A,M from
all sources that will
NOT be integrated
Emissions ready for
SMOKE
Emissions ready for
SMOKE
Step 2: Run SMOKE
I Emissions ready for SMOKE :
SMOKE
Compute NONHAPVOC= VOC - (B + F + A+M)
emissions for each integrate source
Retain VOC emissions for each no-integrate source
Assign speciation profile code to each emission source I
Compute: NONHAPTOG emissions from NONHAPVOCfor
each integrate source
Compute: TOG emissions from VOC for each no-integrate
source
Compute moles of each CBO5 model species.
Use NONHAPTOG profiles applied to NONHAPTOG
emissions and B, F, A, M emissions for integrate sources.
Use TOG profiles applied to TOG for no-integrate sources
list of "no-integrate"
sources (NHAPEXCLUDE)
Speciation Cross
Reference File (GSREF)
VOC-to-TOG factors
NON HAPVOC-to-NON HAPTOG
factors (GSCNV)
TOG and NONHAPTOG
speciation factors
(GSPRO)
Speciated Emissions for VOC species
Figure 3-4. Process of integrating BAFM with VOC for use in VOC Speciation
-------
PLATFORM Approach for Integrating NEI emissions of Benzene (B), Acetaldehyde (A), Formaldehyde (F) and
SECTOR Methanol (M)
ptipm
ptnonipm
ptfire
ag
afdust
nonpt
nonroad
No integration because emissions of BAFM are relatively small for this sector
No integration because emissions of BAFM are relatively small for this sector and it is not expected that criteria for
integration would be met by a significant number of sources
Full integration (However, NONHAPVOC computed outside of SMOKE since SMOKE cannot do this calculation for the
day-specific fire formatted files)
N/A—sector contains no VOC
N/A—sector contains no VOC
Partial integration; details provided below table
For other than California: Partial integration—did not integrate CNG or LPG sources (SCC beginning with 2268 or 2267)
because NMIM computed only VOC and not any HAPs for these SCCs.
For California: Full integration
Partial integration; details provided below table
Full integration
Full integration
N/A—sector contains no inventory pollutant "VOC"; but rather specific VOC species
No integration—not the NEI
No integration—not the NEI
No integration—not the NEI
Table 3-9. Integration status of benzene, acetaldehyde, formaldehyde and methanol (BAFM) for each platform sector
For the nonpt sector, the following integration criteria were
used to determine the sources to integrate (Step 1):
1. Any source for which B, A, F or M emissions were
from the 1996 NEI were not integrated (data source
code contains a "96"),
2. Any source for which the sum of B, A, F, or M is
greater than the VOC was not integrated, since this
clearly identifies sources for which there is an incon-
sistency between VOC and VOC HAPs. This includes
some cases in which VOC for a source is zero.
3. For certain source categories (those that comprised
80% of the VOC emissions), sources were selected for
integration in the category per the criteria specified in
the first column in Table 3-5. For most of these source
categories, sources are allowed to be integrated if they
had the minimum combination of B,A,F and M speci-
fied in the first column. For a few source categories, all
sources were designated as "no-integrate".
4. For source categories not covered in Table 3-5 (i.e., that
do not comprise the top 80%of VOC emissions), then
as long as the source has emissions of one of the B, F, A
or M pollutants, then it can be integrated.
For the alm_no_c3 sector, the integration criteria were (1)
that the source had to have at least one of the 4 HAPs and (2)
that the sum of BAFM could not exceed the VOC emissions.
The criteria for this sector were less complex than the nonpt
sector because it has much fewer source categories.
The SMOKE feature to compute speciation profiles from
mixtures of other profiles in user-specified proportions was
used in this project. The combinations are specified in the
GSPRO_COMBO ancillary file by pollutant (including
pollutant mode, e.g., EXH VOC), state and county (i.e..
state/county FIPS code) and time period (i.e., month).
This feature was used for onroad and nonroad mobile and
gasoline-related related stationary sources. These emission
sources use fuels with varying ethanol content, and therefore
the speciation profiles require different combinations of
gasoline, E10 anE85 profiles. Since the ethanol content
varies spatially (e.g., by state or county), temporally (e.g..
by month) and by modeling year (future years have more
ethanol) the combo feature allows combinations to be
specified at various levels for different years.
3.3.5 Temporal Processing Configuration
Table 3-10 summarizes the temporal aspect of the emissions
processing configuration. It compares the key approaches
used for temporal processing across the sectors. The temporal
aspect of SMOKE processing is controlled through (a) the
scripts T_TYPE (Temporal type) and M_TYPE (Merge
type) settings and (b) ancillary data files. In addition to the
resolution, temporal processing includes a ramp-up period
for several days prior to January 1, 2007, intended to mitigate
the effects of initial condition concentrations. The ramp up
period for the national 12km grid was 10 days. For most
sectors, the emissions from late December of 2007 were used
to provide emissions for the end of December, 2006.
3.3.6 Vertical A llocation of Emissions
Table 3-7 specifies the sectors for which plume rise is
calculated. If there is no plume rise for a sector, the emissions
are placed into layer 1 of the air quality model. Vertical
plume rise was performed in-line within CMAQ for this
-------
Platform sector
ptipm
ptnonipm
othpt
nonroad
othar
alm_no_c3
seca_c3
on_noadj
on_moves_startpm
on_moves_runpm
othon
nonpt
ag
afdust
beis
Inventory
resolution
daily & hourly
annual
annual
monthly
annual
annual
Monthly
profiles
used?
Daily
temporal
approach 1,2
Merge
processing
approach 1,3
Process Holidays
as separate
days?
annual
monthly
monthly
monthly
annual
annual
annual
annual
hourly
daily
1 Definitions for processing resolution:
all = hourly emissions computed for every day of the year, inventory is already daily
week = hourly emissions computed for all days in one "representative" week, representing all weeks for each month, which means emissions have
day-of-week variation, but not week-to-week variation within the month
mwdss= hourly emissions for one representative Monday, representative weekday, representative Saturday and representative Sunday for each month,
which means emissions have variation between Mondays, other weekdays, Saturdays and Sundays within the month, but not week-to-week
variation within the month. Also Tuesdays, Wednesdays and Thursdays are treated the same.
aveday = hourly emissions computed for one representative day of each month, which means emissions for all days of each month are the same.
2 Daily temporal approach refers to the temporal approach for getting daily emissions from the inventory using the Temporal
program. The values given are the values of the L_TYPE setting.
3 Merge processing approach refers to the days used to represent other days in the month for the merge step. If not "all", then the
SMOKE merge step just run for representative days, which could include holidays as indicated by the rightmost column. The values given
are the values of the M_TYPE setting.
Table 3-10. Temporal Settings Used for the Platform Sectors in SMOKE
study for all of the SMOKE point-source sectors (ptipm.
ptnonipm, othpt, and seca_c3). The in-line plume rise
computed within CMAQ is nearly identical to the plume rise
that would be calculated within SMOKE using the Laypoint
program. See http://www. smoke-model.org/version2.61
html/ch06s07. html for full documentation of Laypoint. The
selection of point sources for plume rise is pre-determined in
SMOKE using the Elevpoint program (http ://www. smoke-
model.org/version2.6/html/ch06s03.html). The calculation
is done in conjunction with the CMAQ model time steps
with interpolated meteorological data and is therefore more
temporally resolved than it is when done in SMOKE. Also.
the calculation of the location of the point source is slightly
different than the one used in SMOKE and this can result in
slightly different placement of point sources near grid cell
boundaries.
For point sources, the stack parameters are used as inputs
to the Briggs algorithm, but point fires do not have stack
parameters. However, the ptfire inventory does contain data
on the acres burned (acres per day) and fuel consumption
(tons fuel per acre) for each day. CMAQ uses these additional
parameters to estimate the plume rise of emissions into
layers above the surface model layer. Specifically, these
data are used to calculate heat flux, which is then used to
estimate plume rise. In addition to the acres burned and fuel
consumption, heat content of the fuel is needed to compute
heat flux. The heat content was assumed to be 8000 Btu/lb
of fuel for all fires because specific data on the fuels were
unavailable in the inventory.
The plume rise algorithm applied to the fires is a modification
of the Briggs algorithm with a stack height of zero and a
heat release estimated from the fuel loading and fire size.
CMAQ uses the Briggs algorithm to determine the plume
top and bottom, and then computes the plumes' distributions
into the vertical layers that the plumes intersect. The
pressure difference across each layer divided by the pressure
-------
Code Surrogate Description
N/A Area-to-point approach (see 3.3.1.2)
100 Population
110 Housing
Code Surrogate Description
120
130
515
520
525
137 Housing Change
Urban Population
Rural Population
140
150
160
165
170
180
190
200
210
220
230
240
250
255
260
270 Class 1 Railroad Miles
280 Class 2 and 3 Railroad Miles
300 Low Intensity Residential
310 Total Agriculture
312 Orchards/Vineyards
320 Forest Land
330 Strip Mines/Quarries
340 Land
350 Water
400 Rural Land Area
500 Commercial Land
505 Industrial Land
510 Commercial plus Industrial
Table 3-11. U.S. Surrogates Available for the 2002 and 2005 Platforms
Housing Change and Population 540
Residential Heating - Wood 550
0.5 Residential Heating - Wood plus 0.5 Low Intensity Residential 555
Residential Heating - Distillate Oil
Residential Heating - Coal
Residential Heating - LP Gas
Urban Primary Road Miles
Rural Primary Road Miles
Urban Secondary Road Miles
Rural Secondary Road Miles
Total Road Miles
Urban Primary plus Rural Primary
0.75 Total Roadway Miles plus 0.25 Population
Total Railroad Miles
Commercial plus Institutional Land
Commercial plus Industrial plus Institutional
Golf Courses + Institutional +lndustrial +
Commercial
Single Family Residential
Residential - High Density
Residential + Commercial + Industrial + Institutional
+ Government
Retail Trade
Personal Repair
Retail Trade plus Personal Repair
Professional/Technical plus General Government
Hospital
Medical Office/Clinic
Heavy and High Tech Industrial
Light and High Tech Industrial
Food, Drug, Chemical Industrial
Metals and Minerals Industrial
Heavy Industrial
Light Industrial
Industrial plus Institutional plus Hospitals
Gas Stations
Refineries and Tank Farms
Refineries and Tank Farms and Gas Stations
Airport Areas
Airport Points
Military Airports
Marine Po
Navigable Waterway Miles
Navigable Waterway Activity
Golf Courses
Mines
Wastewater Treatment Facilities
Drycleaners
Commercial Timber
-------
difference across the entire plume is used as a weighting
factor to assign the emissions to layers. This approach gives
plume fractions by layer and source.
3.3.7 Emissions Modeling Ancillary Files
In this section the ancillary data that SMOKE used to
perform spatial allocation, chemical speciation, and temporal
allocation for the 2005 Platform is summarized. The ancillary
data files, particularly the cross-reference files, provide the
specific inventory resolution at which spatial, speciation, and
temporal factors are applied. For the 2005 Platform, spatial
factors were generally applied by country/SCC, speciation
factors by pollutant/SCC or (for combination profiles) state/
county FIPS code and month, and temporal factors by some
combination of country, state, county, SCC, and pollutant.
3.3.7.1 Spatial Allocation Ancillary Files
Spatial allocation was performed for a national 12-km
domain. To do this, SMOKE used national 12-km spatial
surrogates and a SMOKE area-to-point data file. For the
U.S. and Mexico, the same spatial surrogates were used as
were used for the 2002 Platform. For Canada, a new set of
Canadian surrogates provided by Environment Canada was
used as they were provided along with their 2006 emissions
data.
3.3.7.2 Surrogates for U.S. Emissions
There are 66 spatial surrogates available for spatially
allocating U.S. county-level emissions to the CMAQ 36-km
and 12-km grid cells; they are the same as for the 2002
Platform. An area-to-point approach overrides the use of
surrogates for some sources. The Surrogate Tool was used
to generate all of the surrogates. The shapefiles input to the
Surrogate Tool are provided and documented at http://www.
epa.gov/ttn/chief/emch/spatial/spatialsurrogate.html. The
document ftp://ftp.epa. gov/EmisInventory/emiss_shp2006/
usZlist_of_shapefiles.pdf provides a list and summary of
these shapefiles. The detailed steps in developing the county
boundaries for the surrogates are documented at ftp://ftp.epa.
gov/EmisInventory/emiss_shp2006/us/metadata_for_2002_
county_boundary_shapefiles_rev.pdf. Table 3-11 lists the
codes and descriptions of the surrogates.
The onroad off-network (parking area) emissions from the
MOVES model, new to the 2005 platform, were spatially
allocated as shown in Table 3-12.
3.3.7.3 A llocation Meth odfor A irport-Related Sources
in the U.S.
There are numerous airport-related emission sources in the
2005 NEI, such as aircraft, airport ground support equipment.
and jet refueling. Unlike the 2002 platform in which most
of these emissions were contained in sectors with county-
level resolution—aim (aircraft), nonroad (airport ground
support) and nonpt (jet refueling), the 2005 platform includes
the aircraft emissions as point sources. Aircraft emissions
are part of the ptnonipm sector, since the 2005v2 inventory
SCC & Description
2201001350 Light Duty Gas
Vehicles- parking areas rural
2201002350 Light Duty Gas Trucks
1 &2- parking areas rural
2201004350 Light Duty Gas Trucks
3&4- parking areas rural
2201001370 Light Duty Gas
Vehicles- parking areas urban
2201002370 Light Duty Gas Trucks
1 &2- parking areas urban
2201004370 Light Duty Gas Trucks
3&4- parking areas urban
2201070350 Heavy Duty Gasoline
Vehicles 2B thru 8B & Buses
(HDGV)- parking areas rural
2201070370 Heavy Duty Gasoline
Vehicles 2B thru 8B & Buses
(HDGV)- parking areas urban
Surrogate
Rural population (same as
rural local roads),
code= 130
Urban population (same
as urban local roads),
code =120
Commercial plus
Industrial plus Institutional,
code = 520
Table 3-12. Surrogate assignments to new mobile
categories in the 2005 Platform
included them as point sources.
Thus, for the 2005 platform, the SMOKE "area-to-
point" approach was used for only airport ground support
equipment (nonroad sector), and jet refueling (nonpt sector).
The approach is described in detail in the 2002 Platform
documentation: http://www.epa.gov/scram001/reports/
Emissions%20TSD%20Voll_02-28-08.pdf.
Nearly the same ARTOPNT file was used to implement
the area-to-point approach as was done for the CAP and
HAP-2002-Based Platform. This was slightly updated
from the CAP-only 2002 Platform by further allocating
the Detroit-area airports into multiple sets of geographic
coordinates to support finer scale modeling that was done
under a different project. The updated file was retained for
the 2005 Platform.
3.3.7.4 Surrogates for Canada and Mexico Emission
Inventories
The Mexican emissions and single surrogate (population)
were the same as were used in the 2002 Platform. For
Canada, an updated set of surrogates was used to spatially
allocate the 2006 Canadian emissions for the 2005 Platform.
The updated set completely replaced the 2002 Platform
surrogates for allocating the 2006 province-level Canadian
emissions.
The updated surrogate data provided in the 2005v4 zip files
and described in Table 3-13 came from Environment Canada.
They provided both the surrogates and cross references; the
surrogates were outputs from the Surrogate Tool (previously
-------
referenced). Per Environment Canada, the surrogates are
based on 2001 Canadian census data. The cross-references
that Canada originally provided were updated as follows: all
assignments to surrogate '978' (manufacturing industries)
were changed to '906' (manufacturing services), and all
assignments to '985' (construction and mining) and '984'
(construction industries) were changed to '907' (construction
services) because the surrogate fractions in 984, 978 and 985
did not sum to 1. Codes for surrogates other than population
that did not begin with the digit "9" were also changed.
3.3.7.5 Chemical Speciation Ancillary Files
The following data file, provided at the 2005v4 website.
contains the SMOKE inputs used for chemical speciation of
the inventory species to the CMAQ model species. SMOKE
environmental variable names, used in the file names, are
shown using capital letters in parentheses:
• ancillary_2005v4_smokeformat.zip: inventory table
Surrogate description
Population
Total dwelling
Agriculture and Forestry and Fishing
Waste Management Service
Upstream Oil and Gas (UOG)
Mining and Oil and Gas services
Manufacturing services
Construction services
Transportation of Passengers and goods
Electric and Gas and Water utilities
Wholesaling Merchandise services
Retailing Merchandise services
Government Services
All Sales
Intersection of AGRFORFISH and MANUFACT
Intersection of Forest and Housing
Intersection of MININGOILG and MANUFACT
Intersection of UTILITIES and DWELLING
Filename of 2005
Platform Surrogate
CA_100_NOFILL.txt
CA_901_NOFILL.txt
CA_902_NOFILL.txt
CA 903 NOFILL.txt
CA 904 NOFILL.txt
CA_905_NOFILL.txt
CA_906_NOFILL.txt
CA_907_NOFILL.txt
CA_908_NOFILL.txt
CA_909_NOFILL.txt
CA_910_NOFILL.txt
CA_911_NOFILL.txt
CA 915 NOFILL.txt
CA_920_NOFILL.txt
CA_921_NOFILL.txt
CA_922_NOFILL.txt
CA_923_NOFILL.txt
CA 924 NOFILL.txt
Intersection of PUBADMIN and DWELLING
Commercial Marine Vessels
HIGHJET
LOWMEDJET
OTHERJET
CAN RAIL
LDGV
PAVED ROADS
UNPAVED ROADS
Oil Sands
CA_926_NOFILL.txt
CA_928_NOFILL.txt
CA_929_NOFILL.txt
CA_930_NOFILL.txt
CA_931_NOFILL.txt
CA_932_NOFILL.txt
CA 934 NOFILL.txt
CA 941 NOFILL.txt
CA_942_NOFILL.txt
CA 950 NOFILL.txt
Surrogate description
asphalt
cement
chemical
commfuelcomb
downstream_petroleum
egu
grain
manufacturing
mining
stibution
smelting
waste
wood
asphalt industries
cement industries
chemical industries
commercial fuel combustion
downstream petroleum industries
Intersection of CONSTRUCTION and DWELLING CA 925 NOFILL.txt Electric utilities
grain industries
manufacturing industriesl
mining industries
smelting industries
waste management
construction industriesl
construction and miningl
TOTALBEEF2
TOTALPOUL2
TOTALSWIN2
TOTALFERT2
Filename of 2005
Platform Surrogate
CA_951_NOFILL.txt
CA_952_NOFILL.txt
CA_953_NOFILL.txt
CA_954_NOFILL.txt
CA_955_NOFILL.txt
CA_956_NOFILL.txt
CA_957_NOFILL.txt
CA_958_NOFILL.txt
CA_959_NOFILL.txt
CA_960_NOFILL.txt
CA_961_NOFILL.txt
CA_962_NOFILL.txt
CA_963_NOFILL.txt
CA_971_NOFILL.txt
CA_972_FILL.txt
CA_973_FILL.txt
CA_974_FILL.txt
CA_975_FILL.txt
CA_976_FILL.txt
CA_977_FILL.txt
CA_978_FILL.txt
CA_979_FILL.txt
CA_981_FILL.txt
CA_982_NOFILL.txt
CA_984_NOFILL.txt
CA_985_NOFILL.txt
CA_986_NOFILL.txt 2
CA_987_NOFILL.txt2
CA_988_NOFILL.txt2
CA_989_NOFILL.txt2
1: Not used because fractions did not sum to 1;
2: Surrogates 986, 987, 988 and 989 were originally numbered by Canada as 611, 615, 620 and 65, respectively. We changed the numbers
so that all Canadian surrogates would begin with "9".
Table 3-13. Canadian Spatial Surrogates for 2005-based platform Canadian Emission
-------
(INVTABLE), NONHAPVOC emissions calculation
exclusions file (NHAPEXCLUDE), speciation
cross references (GSREF), speciation VOC-to-TOG
conversion factors (GSCNV), speciation profiles
(GSPRO), and combined, monthly speciation profiles
(GSPRO_COMBO).
For VOC speciation, SMOKE-ready profiles for the CB05
chemical mechanism were generated using the Speciation
Tool (Eyth, 2006):
• TOG-to-model species (used only for no-integrate
sources)
• NONHAPTOG-to-model species (used only for the
integrate sources)
• TOG-to-BENZENE (used only for no-integrate sources)
Speciation profile entries were added that map NEI emissions
of benzene, acetaldehyde, formaldehyde and methanol to the
model species BENZENE, ALD2, FORM and METHANOL,
respectively. These profiles were used only for the integrate
sources. Note that the integrate and no-integrate sources
were processed using the same GSREF and GSPRO files.
Thus, to avoid double counting of these HAP species, B, A,
F and M emissions were removed for all no-integrate sources
in the inventory. If the entire sector was no-integrate, then
these could be removed in SMOKE (by using "N" in the
INVTABLE); but if a sector was partially integrated, these
HAPS had to be removed from the actual inventory input to
SMOKE, but only for the no HAP use, no-integrate sources.
In addition to the speciation profiles, the Speciation Tool
generates the SMOKE-ready speciation conversion files
(GSCNV). Two of these were generated: one containing
profile-specific VOC-to-TOG conversion factors and
the other containing profile-specific NONHAPVOC-to-
NONHAPTOG conversion factors.
The TOG and PM2 5 speciation factors that are the basis
of the chemical speciation approach were developed from
the SPECIATE 4.2 database (http://www.epa.gov/ttn/chief/
software/speciate/index.html) which is EPA's repository of
TOG and PM speciation profiles of air pollution sources. The
2002-based platform utilized an earlier version, SPECIATE
4.0. Note that this update did not impact the PM2 5 profiles we
used with the 2005-based platform; they were the same as
those used for the 2002-based platform.
As with SPECIATE 4.0, SPECIATE 4.2 development was
a collaboration involving EPA's ORD and EPA's Office of
Air Quality Planning and Standards (OAQPS) at Research
Triangle Park, NC, and Environment Canada (EPA, 2006c).
The SPECIATE database contains speciation profiles for
TOG, speciated into individual chemical compounds,
VOC-to-TOG conversion factors associated with the TOG
profiles, and speciation profiles forPM25. The database also
contains the PM2 5 speciated into both individual chemical
compounds (e.g., zinc, potassium, manganese, lead), and into
the "simplified" PM2 5 components used in the air quality
model. These simplified components are:
• PSO4 : primary paniculate sulfate
• PNO3: primary paniculate nitrate
• PEC: primary paniculate elemental carbon
• POC: primary paniculate organic carbon
• PMFINE: other primary paniculate, less that 2.5
microns in diameter
One minor issue found with the PM2 5 speciation which was
similarly an issue with the 2002-based platform is that a
bituminous coal combustion profile (92095) that is applicable
to numerous inventory sources was used, but only for a single
nonpoint SCC (2101002000). For the other SCCs pertaining
to bituminous coal combustion we used the sub-bituminous
coal combustion profile (92084). Table 3-14 shows the
differences are shown below, though these are quite small
and represent only a minor change to the SMOKE results:
Another issue was that profile 92095 was inadvertently left
out of SPECIATE4.2 (and 4.0). It was obtained from EPA
ORD staff using it in their modeling applications.
Key changes to the TOG profiles from the 2002 Platform are
as follows:
• Updated the profile for aircraft from 1098 (Aircraft
Landing/Takeoff (LTO)—Commercial) which is from
SPECIATE3.2 and has a profile date of 1989, to 5565
(Aircraft Exhaust), which has a profile date of 8/2008
and is based on testing conducted in 2005).
• Updated the profile for forest fires from 0307
(Miscellaneous Burning - Forest Fires) which was from
SPECIATE3.2 and has a profile date of 1989) to 5560
(Biomass Burning - Extratropical Forest, dated 2/2008
and was based on testing conducted in 2001)
Changed the assignment of residential wood
combustion (including woodstove and fireplace
emissions) and other profiles that formerly used 4641
(Fireplace wood combustion-oak wood) to 4642
(Fireplace wood combustion-pine wood) because
of all three woods tested in the study (oak, pine and
eucalyptus), the most complete testing was done for the
pine wood (for example, benzene was only measured
for pine)
• Updated the profiles for mobile onroad and nonroad
sources to use more up-to-date test data. The updated
profiles are:
- 8750: Gasoline Exhaust—Reformulated gasoline
- 8751: Gasoline Exhaust—E10 ethanol gasoline
- 875212: Gasoline Exhaust—E85 ethanol gasoline
- 8753: Gasoline Vehicle - Evaporative emission -
Reformulated gasoline
12 Profile not used in 2005, but used in future years built off of the 2005 base
year.
-------
««!!,,*-.«* o««~i«o split factors split factors
pollutant species sub-bituminous 92084 bituminous 92095
PM2_5
PM2_5
PM2_5
PM2_5
PM2 5
PEC
PMFINE
PNO3
POC
PSO4
0.0188
0.8266
0.0016
0.0263
0.1267
0.01696
0.827928
0.00208
0.026307
0.126725
Table 3-14. Differences between two profiles used for coal combustion
- 8754: Gasoline Vehicle - Evaporative emission - E10
ethanol gasoline
- 87559: Gasoline Vehicle - Evaporative emission - E85
ethanol gasoline
- 87569'13: Composite Profile for Tier 2 vehicles EO,
exhaust
- 87579-10: Composite Profile for Tier 2 vehicles E10,
exhaust
• Utilized combination profiles comprised of the
above updated exhaust and evaporative profiles to
match the average ethanol content of fuels used by
different counties and for different months of the year.
Combinations were created based on the fuel properties
data in the NMIM county database.
Speciation profiles for use with BEIS are not included in
SPECIATE. The 2005 Platform uses BEIS 3.14 and includes
a new species (SESQ) that was not in BEIS 3.13 (the version
used for the 2002 Platform). This species was therefore added
(it is mapped to the CMAQ species SESQT) to the set of
profiles that had been used in the 2002 Platform. The profile
code associated with BEIS3.14 profiles for use with CB05
uses the same as in the 2002 Platform: "B10C5."
The INVTABLE and NHAPEXCLUDE SMOKE input files
have a critical function in the VOC speciation process for
emissions modeling cases utilizing HAP-CAP integration, as
is done for the 2005 Platform.
Two different INVTABLE files were prepared to use with
different sectors of the platform. For sectors in which we
chose no integration across the entire sector, a "no HAP
use" INVTABLE that set the "KEEP" flag to "N" for BAFM
was created. Thus, any BAFM in the inventory input into
SMOKE would be dropped. This approach both avoids
double-counting of these species and assumes that the VOC
speciation is the best available approach for these species
for the sectors using the approach. The second INVTABLE.
used for sectors in which one or more sources are integrated.
3 Profile not included in SPECIATE4.2 (Nov. 2008), per OTAQ
documentation, profiles were created October 2008, by OTAQ with EPAct
Phase 1 data, 22 out of 22 valid test cycles. Three vehicles tested: Honda
Civic, Toyota Sienna, Chevy Silverado. Composite emission factors
calculated using straight weighting for an LA92 drive cycle (1.19 miles.
8.63 miles, 1.19 miles for Bags 1,2 and 3, respectively).
causes SMOKE to keep the BAFM pollutants and indicates
that they are to be integrated with VOC (by setting the "VOC
or TOG component" field to "V for all four HAP pollutants.
Sector-specific NHAPEXCLUDE files were developed
that provide the specific sources that are excluded from
integration.
3.3.7.6 Temporal Allocation Ancillary Files
The emissions modeling step for temporal allocation creates
the 2005 hourly emission inputs for CMAQ by adjusting the
emissions from the inventory resolution (annual, monthly.
daily or hourly) that are input into SMOKE. The temporal
resolution of each of the platform sectors prior to their input
into SMOKE is included in the sector descriptions from Table
3-1 and were repeated in the discussion of temporal settings.
The starting point for the temporal profiles was the 2002
Platform. The monthly, weekly, and diurnal temporal profiles
and associated cross references used to create the 2005
hourly emissions inputs for CMAQ were generally based
on the temporal allocation data used for the 2002 Platform.
New profile assignments were added for SCCs in the 2005
inventory that were not in the 2002 inventory, and the profiles
used for ptipm sources without CEM data were updated to
represent the year 2007. Temporal profiles were assigned
for the new parking area SCCs provided by the draft version
of MOVES and are shown in Figure 3-5. The remainder of
this section discusses the development of the new temporal
profiles or profile assignments used in the 2005 Platform.
The next development for the 2005 Platform included the
addition of diurnal profiles for electric generating units
(ptipm). The state-specific and pollutant-specific diurnal
profiles for use in allocating the day-specific emissions for
non-CEM sources in the ptipm sector were updated. The
2007 CEM data was used to create state-specific, day-to-hour
factors, averaged over the whole year and all units in each
state. Diurnal factors were calculated using CEM SO2 and
NOX emissions and heat input. SO2 and NOx-specific factors
were computed from the CEM data for these pollutants. All
other pollutants used factors created from the hourly heat
input data. The resulting profiles were assigned by state and
pollutant.
-------
Weekly Diurnal (SO.)
- Rural Local: coae =2006
Urban Loal. code • 2013
S 8 10 12 14 16 18 20 22 24
Hours of the Day
Weekly Diurnal (NO )
6 8 10 12 14 16 18 20 22 24
Hours of the Day
Figure 3-5. Diurnal Profiles for Parking Areas (Pollutants: SO and NOx)
Canadian emission inventories were also included in the 2005
Platform. The temporal profile assignments for the Canadian
2006 inventory were provided by Environment Canada
along with the inventory. They provided profile assignments
that rely on the existing set of temporal profiles in the 2002
Platform. For point sources, they provided profile assignments
by PLANTID.
Finally, WPxAP oil and gas inventory profiles were included
in the 2005 Platform. The WRAP 2005 oil and gas inventory
SCCs14 utilized uniform monthly and day of week profiles
(codes 262 and 7, respectively) and an hourly profile (code
26) that put emissions in every hour, but weighted towards
the day light hours.
14 See Table 2-9: 2310000220, 2310000330, 2310000440,
2310010100, 2310010200,2310010300,2310010700,
2310010800, 2310020600,2310020700,2310020800,
2310021100, 2310021300, 2310021400, 2310021500,
2310021600, 2310023000,2310030210, 2310030220
-------
4.0
CMAQ Air Quality Model Estimates
4.1 Introduction to the CMAQ Modeling Platform
The Clean Air Act (CAA) provides a mandate to assess and
manage air pollution levels to protect human health and the
environment. EPA has established National Ambient Air
Quality Standards (NAAQS), requiring the development of
effective emissions control strategies for such pollutants as
ozone and paniculate matter. Air quality models are used
to develop these emission control strategies to achieve the
objectives of the CAA.
Historically, air quality models have addressed individual
pollutant issues separately. However, many of the same
precursor chemicals are involved in both ozone and aerosol
(paniculate matter) chemistry; therefore, the chemical
transformation pathways are dependent. Thus, modeled
abatement strategies of pollutant precursors, such as volatile
organic compounds (VOC) and NOx to reduce ozone levels.
may exacerbate other air pollutants such as paniculate matter.
To meet the need to address the complex relationships
between pollutants, EPA developed the Community
Multiscale Air Quality (CMAQ) modeling system. The
primary goals for CMAQ are to:
• Improve the environmental management community's
ability to evaluate the impact of air quality management
practices for multiple pollutants at multiple scales.
• Improve the scientist's ability to better probe.
understand, and simulate chemical and physical
interactions in the atmosphere.
The CMAQ modeling system brings together key physical
and chemical functions associated with the dispersion and
transformations of air pollution at various scales. It was
designed to approach air quality as a whole by including
state-of-the-science capabilities for modeling multiple
air quality issues, including tropospheric ozone, fine
particles, toxics, acid deposition, and visibility degradation.
CMAQ relies on emission estimates from various sources.
including the U.S. EPA Office of Air Quality Planning and
Standards' current emission inventories, observed emission
from major utility stacks, and model estimates of natural
emissions from biogenic and agricultural sources. CMAQ
also relies on meteorological predictions that include
assimilation of meteorological observations as constraints.
Emissions and meteorology data are fed into CMAQ and run
through various algorithms that simulate the physical and
chemical processes in the atmosphere to provide estimated
concentrations of the pollutants. Traditionally, the model has
been used to predict air quality across a regional or national
domain and then to simulate the effects of various changes
in emission levels for policymaking purposes. For health
studies, the model can also be used to provide supplemental
information about air quality in areas where no monitors
exist.
CMAQ was also designed to have multi-scale capabilities so
that separate models were not needed for urban and regional
scale air quality modeling. The grid spatial resolutions in past
annual CMAQ runs have been 36 km x 36 km per grid for the
"parent" domain, and nested within that domain are 12 km x
12 km grid resolution domains. The parent domain typically
covered the continental United States, and the nested 12 km x
12 km domain covered the Eastern or Western United States.
The CMAQ simulation performed for this 2007 assessment
used a single domain that covers the entire continental U.S.
(CONUS) and large portions of Canada and Mexico using 12
km by 12 km horizontal grid spacing. For urban applications.
CMAQ has also been applied with a 4-km x 4-km grid
resolution for urban core areas; however, the uncertainties
in emissions and meteorology information can actually
increase at this high of a resolution. Currently, 12 km x 12
km resolution is recommended for most applications as the
highest resolution. With the temporal flexibility of the model.
simulations can be performed to evaluate longer term (annual
to multi-year) pollutant climatologies as well as short-term
(weeks to months) transport from localized sources. By
making CMAQ a modeling system that addresses multiple
pollutants and different temporal and spatial scales, CMAQ
has a "one atmosphere" perspective that combines the efforts
of the scientific community. Improvements will be made to
the CMAQ modeling system as the scientific community
further develops the state-of-the-science.
For more information on CMAQ, go to http://www.epa. gov/
asmdnerl/CMAO or http://www.cmascenter.org.
4.1.1 Advantages and Limitations of the CMAQAir Quality
Model
An advantage of using the CMAQ model output for
comparing with health outcomes is that it has the potential
to provide complete spatial and temporal coverage.
Additionally, meteorological predictions, which are also
needed when comparing health outcomes, are available for
every grid cell along with the air quality predictions.
A disadvantage of using CMAQ is that, as a deterministic
model, it has none of the statistical qualities of interpolation
techniques that fit the observed data to one degree or another.
Furthermore, the emissions and meteorological data used
in CMAQ each have large uncertainties, in particular for
unusual emission or meteorological events. There are also
uncertainties associated with the chemical transformation
and fate process algorithms used in air quality models.
-------
Thus, emissions and meteorological data plus modeling
uncertainties cause CMAQ to predict best on longer time
scale bases (e.g., synoptic, monthly, and annual scales)
and be most error prone at high time and space resolutions
compared to direct measures.
One practical disadvantage of using CMAQ model output
for health outcome research is that the regularly spaced
grid cells do not line up directly with counties or ZIP codes
which are the geographical units over which health outcomes
are likely to be aggregated. But it is possible to overlay grid
cells with county or ZIP code boundaries and devise means
of assigning an exposure level that nonetheless provides
more complete coverage than that available from ambient
data alone. Another practical disadvantage is that CMAQ
requires significant data and computing resources to obtain
results for daily environmental health surveillance.
This section describes the air quality modeling platform
used for the 2007 CMAQ simulation. A modeling platform
is a structured system of connected modeling-related
tools and data that provide a consistent and transparent
basis for assessing the air quality response to changes in
emissions and/or meteorology. A platform typically consists
of a specific air quality model, emissions estimates, a
set of meteorological inputs, and estimates of "boundary
conditions" representing pollutant transport from source
areas outside the region modeled. We used the CMAQ15
model as part of the 2007 Platform to provide a national
scale air quality modeling analysis. The CMAQ model
simulates the multiple physical and chemical processes
involved in the formation, transport, and destruction of
ozone and fine paniculate matter (PM25).
This section provides a description of each of the main
components of the 2007 CMAQ simulation along with the
results of a model performance evaluation in which the 2007
model predictions are compared to corresponding measured
concentrations.
4.2 CMAQ Model Version, Inputs and Configuration
4.2.1 Model Version
CMAQ is a non-proprietary computer model that simulates
the formation and fate of photochemical oxidants, including
PM2 5 and ozone, for given input sets of meteorological
conditions and emissions. The CMAQ model version 4.7
was most recently peer-reviewed in February of 2009 for
the U.S. EPA.16 As mentioned previously, CMAQ includes
numerous science modules that simulate the emission.
production, decay, deposition and transport of organic and
inorganic gas-phase and particle-phase pollutants in the
atmosphere. This analysis employed a version of CMAQ
5 Byun, D.W., and K. L. Schere, 2006: Review of the Governing Equations.
Computational Algorithms, and Other Components of the Models-3
Community Multiscale Air Quality (CMAQ) Modeling System. Applied
Mechanics Reviews, Volume 59, Number 2 (March 2006), pp. 51-77.
6 Allen, D., Burns, D., Chock, D., Kumar, N., Lamb, B., Moran, M.
(February 2009 Draft Version). Report on the Peer Review of the
Atmospheric Modeling and Analysis Division, NERL/ORD/EPA. U.S.
EPA, Research Triangle Park, NC. CMAQ version 4.7 was released
on December, 2008. It is available from the Community Modeling and
Analysis System (CMAS) as well as previous peer-review reports at:
http://www.cmascenter.org.
based on the latest publicly released version of CMAQ (i.e..
version 4.7.117) at the time of the 2007 air quality modeling.
CMAQ version 4.7.1 reflects updates to version 4.7 to
improve the underlying science which include aqueous
chemistry mass conservation improvements and improved
vertical convective mixing. The model enhancements in
version 4.7.1 also include:
1. Aqueous chemistry
- Mass conservation improvements
+ Imposed 1 second minimum timestep for
remainder of the cloud lifetime
after 100 "iterations" in the solver
+ Force mass balance for the last timestep in
the cloud by limiting oxidized amount to mass
available
- Implemented steady state assumption for OH
- Only allow sulfur oxidation to control the aqueous
chemistry solver timestep (previously, reactions of
OH, GLY, MGLY, and Hg for multipollutant model
also controlled the timestep)
2. Advection
- Added additional divergence-based constraint on
advection timestep
- Vertical advection in the Yamo module is now
represented with the PPM scheme to limit numerical
diffusion
3. Model time step determination
- Fixed a potential advection time step error
+ The sum of the advection steps for a given layer
time step might not equal the output time step
duration in some extreme cases
+ Ensured that the advection steps sum up to the
synchronization step
4. Horizontal diffusion
- Fixed a potential error
+ Concentration data may not be correctly initialized
if multiple sub-cycle time steps are required
+ Fix to initialize concentrations with values
calculated in the previous sub-time step
5. Emissions
- Bug fix in EMIS_DEFN.F to include point source
layer 1 NH3 emissions
- Bug fix to calculate soil NO "pulse" emissions in
BEIS
17 CMAQ version 4.7.1 model code is available from the Community
Modeling and Analysis System (CMAS) at: http://www.cmascenter.org.
-------
- Remove excessive logging of cases where ambient
air temperature exceeds 315.0 Kelvin. When this
occurs, the values are just slightly over 315
- Bug fix for parallel decomposition errors in plume
rise emissions
6. Photolysis
- JPROC/phot_table and phot_sat options
+ Expanded lookup tables to facilitate applications
across the globe and vertical extent to 20km
+ Updated temperature adjustments for absorption
cross sections and quantum yields
+ Revised algorithm that processes TOMS datasets
for OMI data format
- In-line option
+ Asymmetry factor calculation updated using
values from Mie theory integrated over log normal
particle distribution; added special treatment for
large particles in asymmetry factor algorithm to
avoid numerical instabilities
National 12 km CMAQ Modeling
Configuration
12km
97 W, 40 N
Map Projection Lambert Conformal Projection
Grid
Resolution
Coordinate
Center
True Latitudes 33 and 45 N
Dimensions
Vertical extent
459 x 299 x 24
24 Layers: Surface to 50 mb level (see Table
4-2)
Table 4-1. Geographic Information for 12 km Modeling
Domain
4.2.2 Model Domain and Grid Resolution
The CMAQ modeling analyses were performed for a domain
covering the continental United States, as shown in Figure
4-1. This single domain covers the entire continental U.S.
(CONUS) and large portions of Canada and Mexico using
12 km by 12 km horizontal grid spacing. The model extends
vertically from the surface to 50 millibars (approximately 19
km) using a sigma-pressure coordinate system. Air quality
conditions at the outer boundary of the 12 km domain were
taken from a global model. Table 4-1 provides some basic
geographic information regarding the 12 km CMAQ domain.
I2km CONUS nation*
x,y: -25S6000,-172SOOO
col: 459 row; 299
Figure 4-1. Map of the CMAQ Modeling Domain. The blue box denotes the 12 km national modeling domain
(Same as Figure 3-3.)
-------
4.2.3 Modeling Period/Ozone Episodes
The 12 km CMAQ modeling domain was modeled for
the entire year of 2007. The 2007 annual simulation was
performed in two half-year segments (i.e., January through
June, and July through December) for each emissions
scenario. With this approach to segmenting an annual
simulation we were able to reduce the overall throughput
time for an annual simulation. The annual simulation
included a "ramp-up" period, comprised of 10 days before
the beginning of each half-year segment, to mitigate the
effects of initial concentrations. All 365 model days were
used in the annual average levels of PM2 5. For the 8-hour
ozone, we used modeling results from the period between
May 1 and September 30. This 153-day period generally
conforms to the ozone season across most parts of the U.S.
and contains the majority of days that observed high ozone
concentrations.
4.2.4 Model Inputs: Emissions, Meteorology and Boundary
Conditions
2007 Emissions: The emissions inventories used in the 2007
air quality modeling are described in Section 3, above.
Meteorological Input Data: The gridded meteorological data
for the entire year of 2007 at the 12 km continental United
States scale domain was derived from version 3.1 of the
Weather Research and Forecasting Model (WRF), Advanced
Research WRF (ARW) core.1S Previous CMAQ annual
simulations have typically utilized meteorology provided
by the 5th Generation Mesoscale Model (MM5).19 The WRF
Model is a next-generation mesoscale numerical weather
prediction system developed for both operational forecasting
and atmospheric research applications (http://wrf-model.
org). The 2007 WRF simulation included the physics options
of the Pleim-Xiu land surface model (LSM), Asymmetric
Convective Model version 2 planetary boundary layer (PEL)
scheme, Morrison double moment microphysics, Kain-
Fritsch cumulus parameterization scheme and the RRTMG
long-wave radiation (LWR) scheme.20
The WRF meteorological outputs were processed to create
model-ready inputs for CMAQ using the Meteorology-
Chemistry Interface Processor (MCIP) package21, version
3.6, to derive the specific inputs to CMAQ: horizontal wind
components (i.e., speed and direction), temperature, moisture.
vertical diffusion rates, and rainfall rates for each grid cell
in each vertical layer. The WRF simulation used the same
CMAQ map projection, a Lambert Conformal projection
centered at (-97, 40) with true latitudes at 33 and 45 degrees
north. The 12 km WRF domain consisted of 459 by 299
18 Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, D.O., Barker, D.M.,
Duda, M.G., Huang, X., Wang, W., Powers, J.G., 2008. A Description of
the Advanced Research WRF Version 3.
19 Grell, G. A., Dudhia, A. J., and Stauffer, D. R., 1994. A description of
the Fifth-Generation PennState/NCAR Mesoscale Model (MM5). NCAR
Technical Note NCAR/TN-398+STR. Available at http'.//WWW.mmm.
ucar.edu/mm5/docl.html.
20 Gilliam, R.C., Pleim, J.E., 2010. Performance Assessment of New Land
Surface and Planetary Boundary Layer Physics in the WRF-ARW. Journal
of Applied Meteorology and Climatology 49, 760-774.
21 Otte T.L., Pleim, J.E., 2010. The Meteorology-Chemistry Interface
Processor (MCIP) for the CMAQ modeling system: updates through
v3.4.1. Geoscientific Model Development 3, 243-256.
grid cells. The WRF simulation utilized 34 vertical layers
with a surface layer of approximately 38 meters. Table 4-2
shows the vertical layer structure used in WRF and the layer
collapsing approach to generate the CMAQ meteorological
inputs. CMAQ resolved the vertical atmosphere with 24
layers, preserving greater resolution in the PEL.
In terms of the 2007 WRF meteorological model performance
evaluation, an approach which included a combination of
qualitative and quantitative analyses was used to assess the
adequacy of the WRF simulated fields.22 The qualitative
aspects involved comparisons of the model-estimated
synoptic patterns against observed patterns from historical
weather chart archives. Additionally, the evaluations
compared spatial patterns of monthly average rainfall and
monthly maximum planetary boundary layer (PEL) heights.
The statistical portion of the evaluation examined the model
bias and error for temperature, water vapor mixing ratio.
solar radiation, and wind fields. These statistical values were
calculated on a monthly basis.
Initial and Boundary Conditions: The lateral boundary
and initial species concentrations are provided by a three-
dimensional global atmospheric chemistry model, the
GEOS-CHEM23 model version 8-02-03. The global GEOS-
CHEM model simulates atmospheric chemical and physical
processes driven by assimilated meteorological observations
from the NASA's Goddard Earth Observing System (GEOS).
This model was run for 2007 with a grid resolution of 2.0
degrees x 2.5 degrees (latitude-longitude) and 47 vertical
layers. The predictions were used to provide one-way
dynamic boundary conditions at three-hour intervals and
an initial concentration field for the CMAQ simulations. A
GEOS-Chem evaluation was conducted for the purpose of
validating the 2007 GEOS-Chem simulation for selected
measurements relevant to their use as boundary conditions
for CMAQ and reproducing GEOS-Chem evaluation plots
reported in the literature for previous versions of the model.24
More information is available about the GEOS-CHEM model
and other applications using this tool at: http://www-as.
harvard.edu/chemistry/trop/geos.
4.3 CMAQ Model Performance Evaluation
An operational model performance evaluation for ozone and
PM2 5 and its related speciated components was conducted for
the 2007 simulation using state/local monitoring sites data in
order to estimate the ability of the CMAQ modeling system
to replicate the 2007 base year concentrations for the 12 km
continental U.S. domain.
There are various statistical metrics available and used by
the science community for model performance evaluation.
For a robust evaluation, the principal evaluation statistics
used to evaluate CMAQ performance were two bias
metrics, normalized mean bias and fractional bias; and two
22 U.S. Environmental Protection Agency, 2011. Meteorological Model
Performance for Annual 2007 Simulations, Office of Air Quality Planning
and Standards, Research Triangle Park, NC., 27711, EPA-454/R-11-007.
23 Yantosca, B., 2004. GEOS-CHEMv7-01-02 User's Guide, Atmospheric
Chemistry Modeling Group, Harvard University, Cambridge, MA, October
15, 2004.
24 Lam, Y-F, Fu, J.S., Jacob, D.J., Jang, C., Dolwick, P., 2010. 2006-2008
GEOS-Chem for CMAQ Initial and Boundary Conditions. 9th Annual
CMAS Conference, October 11-13, 2010, Chapel Hill, NC.
-------
Height
(m)
17,145
14,490
12,593
11,094
9,844
8,766
7,815
6,962
6,188
5,477
4,820
4,208
3,635
3,095
2,586
2,198
1,917
1,644
1,466
1,292
1,121
952
787
705
624
544
465
386
307
230
153
114
76
Pressure
(mb)
50
95
140
185
230
275
320
365
410
455
500
545
590
635
680
716
743
770
788
806
824
842
860
869
878
887
896
905
914
923
932
937
941
WRF
34
33
32
31
30
29
28
27
26
25
24
23
22
21
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
Depth
(m)
2,655
1,896
1,499
1,250
1,078
951
853
775
711
657
612
573
539
509
388
281
273
178
174
171
168
165
82
81
80
80
79
78
78
77
38
38
38
CMAQ
24
HH
23
22
21
^^B
20
Depth 1
(m) •
4,552
HIM
2,749
^^m
2,029
1,627
^^m
1,368
Normalized mean error (NME) is also similar to NMB.
where the performance statistic is used as a normalization
of the mean error. NME calculates the absolute value of
the difference (model - observed) over the sum of observed
values. Normalized mean error is denned as:
n
V
NME= i
P-O\
* 1 00. where P = nredicted
y> fQ\ concentrations and O = observed
ta^ •• -
i
Fractional Bias (FB) is denned as:
, E (P-0)
19
18
17
16
15
14
13
12
11
10
9
8
^^M
i
6
^H
5
4
3
2
1,185
539
509
388
281
273
178
174
171
168
FR=1 i
n ^
\ i
* 1 DO fl;Viprp P = prprjirfpr) rnnrpntratinnc
L£_r_2 and f = observed
FB is a useful model performance indicator because it has the
advantage of equally weighting positive and negative bias
estimates. The single largest disadvantage in this estimate
of model performance is that the estimated concentration
(i.e., prediction, P) is found in both the numerator and
denominator.
Fractional error (FE) is similar to fractional bias except the
1 65 absolute value of the difference is used so that the error is
163
^^H
160
HH
157
^M
78
77
76
38
always positive. Fractional error is denned as:
f n
FF —
"£
^ i
\
' \P-O\
^ 1 (1 0 ivlipfp P — nfpHir'tpH
( p~\~ (~y\
conccntrutions mid O — observed
^ /
In addition to the performance statistics, regional maps which
show the normalized mean bias and error were prepared for
the ozone season, May through September, at individual
monitoring sites as well as on an annual basis for PM2.5 and
-ftc* /->/-vmv\/-vM£^M+ c'naf^-tac'
Table 4-2. Vertical layer structure for 2007 WRF and
CMAQ simulations (heights are layer top).
error metrics, normalized mean error and fractional error.
Normalized mean bias (NMB) is used as a normalization to
facilitate a range of concentration magnitudes. This statistic
averages the difference (model - observed) over the sum
of observed values. NMB is a useful model performance
indicator because it avoids overinnating the observed range
of values, especially at low concentrations. Normalized mean
bias is denned as:
NMB =
^ (O)
*100, where P = predicted concentrations
and O = observed
Evaluation for 8-hour Daily Maximum Ozone: The
operational model performance evaluation for hourly and
eight-hour daily maximum ozone was conducted using
the statistics denned above. Ozone measurements from
1176 sites for 2007 in the continental U.S. were included
in the evaluation and were taken from the 2007 State/
local monitoring site data in the Air Quality System (AQS)
Aerometric Information Retrieval System (AIRS). The
performance statistics were calculated using predicted and
observed data that were paired in time and space on an
hourly and/or 8-hour basis. Statistics were generated for the
following geographic groupings: domain wide and four large
sub-regions25: Midwest, Northeast, Southeast, Central, and
Western U.S.
25 The subregions are denned by States where: Midwest is IL.
IN, MI, OH, and WI; Northeast is CT, DE, MA, MD, ME,
NH, NJ, NY, PA, RI, and VT; Southeast is AL, FL, GA, KY
MS, NC, SC, TN, VA, and WV; Central is AR, IA, KS, LA,
MN, MO, ME, OK, and TX; West is AK, CA, OR, WA, AZ,
MM, CO, UT, WY, SD, ND, MT, ID, and NV.
-------
The 8-hour ozone model performance bias and error statistics
for each subregion and each season are provided in Table
4-4. Seasons were defined as: winter (December-January-
February), spring (March-April-May), summer (June, July.
August), and fall (September-October-November). Spatial
plots of the normalized mean bias and error for individual
monitors are shown in Figures 4-2 through 4-3. The statistics
shown in these two figures were calculated over the ozone
season using data pairs on days with observed 8-hour ozone
of > 60 ppb.
In general, the model performance statistics indicate that the
8-hour daily maximum ozone concentrations predicted by
the 2007 CMAQ simulation closely reflect the corresponding
Subregion
Central States
No. of NMB NME FB FE
Obs (%) (%) (%) (%)
Midwest
Winter 11,223 -8.68
Spring 15,214 0.2
Summer 16,619 19.6
Fall 14,568 6.4
Winter 2,824 -22.1
Spring 11,850 -1.8
Summer 16,592 9.6
Fall 9,589 4.9
Southeast
Winter 6,431
Spring 18,516
Summer 20,465
Fall 15,848
-1.1
-0.5
14.3
12.0
Northeast
Winter 5,085 -23.5
Spring 12,276 -3.9
Summer 15,973 11.3
Fall 11,066 6.7
West
Winter 23,908
Spring 27,771
Summer 30,806
Fall 27,746
3.0
-1.4
11.0
6.4
20.2
14.0
25.8
18.8
26.1
12.2
16.6
16.0
15.6
10.3
18.6
17.9
25.9
13.3
17.7
17.6
•
18.4
12.3
18.7
18.6
-10.3 24.7
1.1 15.1
19.7 26.4
6.8 20.4
-28.1 33.1
-1.4 13.5
9.6 16.7
5.9 17.7
-1.1
-0.2
15.8
12.9
3.4
-1.4
10.6
6.2
Table 4-4. Summary of CMAQ 2007 8-Hour Daily
Maximum O3 Model Performance Statistics by
Subregion, by Season.
16.8
11.0
19.5
18.8
-30.0 34.4
-4.3 14.8
10.8 17.7
6.3 19.1
20.9
13.1
18.7
20.0
8-hour observed ozone concentrations in space and time in
each subregion of the 12 km modeling domain. As indicated
by the statistics in Table 4-4, bias and error for 8-hour daily
maximum ozone are relatively low in each subregion, not
only in the summer when concentrations are highest, but also
during other times of the year. Specifically, 8-hour ozone in
the summer is slightly over predicted with the greatest over
prediction in the Central States (NMB is 19.6 percent). In the
spring, ozone is slightly under predicted in all the subregions
except in the Central states where NMB is near negligible
(NMB is 0.2 percent). In the winter, when concentrations are
generally low, the model under predicts 8-hour ozone with
the exception of the West (NMB is 3.0). In the fall, when
concentrations are also relatively low, ozone is slightly over
predicted; with NMBs less than 12 percent in each subregion.
Model bias at individual sites during the ozone season is
similar to that seen on a subregional basis for the summer.
The information in Figure 4-2 indicates that the bias for days
with observed 8-hour daily maximum ozone greater than 60
ppb is within ± 20 percent at the vast majority of monitoring
sites across the U.S. domain. The exceptions are sites in and/
or near Minneapolis, Duluth, District of Columbia, New
York City, New Orleans, and San Antonio, as well as a few
areas along the California coast. At these sites observed
concentrations greater than 60 ppb are generally predicted
in the range of ±20 to 40 percent. Looking at the map of
bias, Figure 4-2 indicates that the low bias at these sites is
not evident at other sites in these same areas. This suggests
that the under prediction at these sites is likely due to very
local features (e.g., meteorology and/or emissions) and not
indicative of a systematic problem in the modeling platform.
Model error, as seen from Figure 4-3, is 14 percent or less at
most of the sites across the U.S. modeling domain. Somewhat
greater error is evident at sites in several areas most notably
along portions of the Northeast Corridor and in portions of
Michigan, Minnesota, Louisiana, Texas, and the western most
part of the modeling domain, (e.g., New Mexico, California.
and Washington).
PM2 s: The PM2 5 evaluation focuses on PM2 5 total mass
and its components, including sulfate (SO4), nitrate (NO3).
total nitrate (TNO3 = NO3 + HNO3), ammonium (NH4),
elemental carbon (EC), and organic carbon (OC). The PM2 5
bias and error performance statistics were calculated on an
annual basis for each subregion (Table 4-5). PM25 ambient
measurements for 2007 were obtained from the following
networks for model evaluation: Chemical Speciation
Network (CSN—total of 211 sites, 24 hour average),
Interagency Monitoring of PROtected Visual Environments
(IMPROVE—total of 163 sites, 24 hour average), and
Clean Air Status and Trends Network (CASTNet—total of
86, weekly average). For PM2 5 species that are measured
by more than one network, we calculated separate sets of
statistics for each network by subregion. For brevity, Table
4-5 provides annual model performance statistics for PM2 5
and its component species for the 12 km continental U.S.
domain and the five sub-regions defined above (Northeast.
-------
03_8hrmax NMB (%) for run 2007aq_07c_12US1 for 20070501 to 20070930
units = %
coverage limil - 75%
>100
I so
160
140
120
0
-20
-40
I-60
I-80
U-100
CIRCLE=AQS_Daily;
Figure 4-2. Normalized Mean Bias (%) of 8-hour daily maximum ozone greater than 60 ppb over the period May-
September 2007 at monitoring sites in the continental U.S. modeling domain.
O3_8hrmax NME (%) for run 2007aq_07c_12US1 for 20070501 to 20070930
units = %
coverage limit - 75%
>20
118
116
14
12
10
8
6
4
2
CIRCLE=AQS_Daily;
Figure 4-3. Normalized Mean Error (%) of 8-hour daily maximum ozone greater than 60 ppb over the period May-
September 2007 at monitoring sites in the continental U.S. modeling domain.
-------
Midwest, Southeast, Central, and West). In addition to the
tabular summaries of bias and error statistics, annual spatial
maps which show the normalized mean bias and error by site
for each PM2 5 species are provided in Figures 4-4 through
4-17.
As indicated by the statistics in Table 4-5, annual CMAQ
PM2 5 for 2007 shows a slight under prediction at rural
IMPROVE monitoring sites in each subregion except the
Northeast which shows an over prediction in NMB of 18.1
percent. Annual PM2 5 at urban CSN monitoring sites show
slight over predictions in the Midwest, Central and West
whereas annual PM2 5 is under predicted in the Southeast
(NMB is -2.1 percent) and Northeast (NMB is -42.3).
Although not shown here, the mean observed concentrations
of PM2 5 are more than twice as high at the CSN sites (~16ug
m3) as the IMPROVE sites (~ 6ug nr3), thus illustrating
the statistical differences between the urban CSN and rural
IMPROVE networks.
Annual average sulfate is consistently under-predicted at
CSN, IMPROVE, and CASTNet monitoring sites across
the modeling domain, with NMB values ranging from -8
percent to -34 percent. Overall, sulfate bias performance is
slightly better at urban CSN sites than at rural IMPROVE
and/or suburban CASTNet sites. Sulfate performance shows
moderate error, ranging from 22 to 45 percent. Annual model
bias and error at individual sites, as displayed in Figures 4-6
CMAQ 2007 Annual
CSN
Nitrate
IMPROVE
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
West
No. ofObs. NMB(%) NME (%) FB(%)
FE (%)
-------
CMAQ 2007 Annual
No. ofObs. NMB(%) NME (%) FB (%) FE (%)
Total Nitrate
(N03 + HN03)
CASTNet
CSN
Ammonium
CASTNet
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
Northeast
Midwest
Southeast
Central
Elemental
Carbon
IMPROVE
West
Northeast
Midwest
Southeast
Central
Vest
Northeast
Midwest
Southeast
Central
West
Northeast
Midwest
Southeast
Central
West
Table 4-5. Summary of CMAQ 2007 Annual PM
CSN
Organic
Carbon
IMPROVE
I Performance Statistic
-------
and 4-7, suggest spatial patterns vary by region. The model
bias for most of the Southeast, Central and Southwest states
are within -20 to -40 percent. The model bias appears to
be much less (±20 percent) in the Northeast, Midwest, and
Northwest states. A few sites in the Northwest have biases
much greater than 20 percent. Model error also shows a
spatial trend by region, where much of the Eastern states are
20 to 30 percent, the Central U.S. states are 30 to 40 percent,
and the Western states are greater than 40 percent.
Annual average nitrate is over predicted at the urban and
rural monitoring sites in most of the subregions in the!2
km modeling domain (NMB in the range of 24% to 93%),
while nitrate is under predicted in the West (NMB in the
range of -23% to -32%). The bias statistics indicate that
the model performance for nitrate is generally best at the
urban CSN monitoring sites. Model performance of total
nitrate at suburban CASTNet monitoring sites shows an
PH_TOT NME (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
units-%
coverage limit - 75%
CIRCLE=IMPROVE; TR1ANGLE=CSN;
Figure 4-4. Normalized Mean Bias (%) of annual PM2.5 mass at monitoring sites in the continental U.S. modeling
domain.
SO4 NMB (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
units = %
coverage Bmit« 75%
>100
180
160
40
120
0
-20
-40
-60
-80
<-100
CIRCLE=IMPROVE; TRIANGLE=CSN; SQUARE=CASTNET;
Figure 4-5. Normalized Mean Error (%) of annual PM2.5 mass at monitoring sites in the continental U.S. modeling
domain.
-------
over prediction across all subregions. Model error for nitrate
is somewhat greater for each subregion as compared to
sulfate. Model bias at individual sites indicates mainly over
prediction of greater than 20 percent at most monitoring sites
in the Eastern half of the U. S. as well and in the extreme
Northwest, as indicated in Figure 4-8. The exception to this
is in the Southwest of the modeling domain where there
appears to be a greater number of sites with under prediction
of nitrate of 20 to 80 percent. Model error for annual nitrate,
as shown in Figure 4-9, is least at sites in portions of the
Midwest and extending eastward to the Northeast corridor.
Nitrate concentrations are typically higher in these areas than
in other portions of the modeling domain.
Annual average ammonium model performance as indicated
in Table 4-5 has a tendency for the model to slightly over
predict in the Northeast, Midwest, and Central U.S. states
across the CSN and CASTNet monitoring sites (NMB
SO4 NMB (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
units = %
coverage limit > 75%
>100
80
60
40
20
0
-20
-40
-60
-80
<-too
CIRCLE=IMPROVE; TRIANGLE=CSN; SQUARE=CASTNET;
Figure 4-6. Normalized Mean Bias (%) of annual Sulfate at monitoring sites in the continental U.S. modeling domain.
TN03 NMB (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
onils - %
coverage lirral = 75%
CIRCLE=CASTNET;
Figure 4-7. Normalized Mean Error (%) of annual Sulfate at monitoring sites in the continental U.S. modeling domain.
-------
ranging from -0.4 to -10 percent). In contrast, the model tends
to slightly under predict in the Southeast and Western states at
CSN and CASTNet sites (NMB ranging from 5 to 18 percent).
There is not a large variation from subregion to subregion or at
urban versus rural sites in the error statistics for ammonium.
Annual average elemental carbon is under predicted in all
subregions at urban sites with the exception of the slight over
prediction in the Northeast. At rural sites, elemental carbon is
over predicted in the Northeast, Central and West, although
elemental carbon is under predicted in the Midwest and
Southeast. Similar to ammonium error model performance,
there is not a large variation from subregion to subregion or
at urban versus rural sites.
Annual average organic carbon is under predicted in the
Midwest, Southeast and Central states at the urban and rural
monitoring sites. In contrast, organic carbon model bias
tends to show a slight over prediction in the Northeast and
West. Similar to ammonium and elemental carbon, error
model performance does not show a large variation from
subregion to subregion or at urban versus rural sites.
SO4 NME (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
**"*2 \ -A.
. f V-H»- . •
^ •
units • %
coverage limit - 75%
CIRCLE=IMPROVE; TRIANGLE=CSN; SQUARE=CASTNET;
Figure 4-8. Normalized Mean Bias (%) of annual Nitrate at monitoring sites in the continental U.S. modeling domain.
NO3 NMB (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
units m %
coverage limit« 75%
l>100
180
60
40
120
0
-20
-40
-60
-80
<-100
CIRCLE=IMPROVE; TRIANGLE=CSN;
Figure 4-9. Normalized Mean Error (%) of annual Nitrate at monitoring sites in the continental U.S. modeling domain.
-------
NO3 NME (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
units =
coverage limit - 75%
'"^ A %
t Tfta*.:'
\ /
\ L M,
W^ >*-<2
. vr
CIRCLE=IMPROVE; TRIANGLE=CSN;
Figure 4-10. Normalized Mean Bias (%) of annual Total Nitrate at monitoring sites in the continental U.S. modeling
domain.
TNO3 NME (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
units -.%
coverage limit» 75%
>100
CIRCLE=CASTNET;
Figure 4-11. Normalized Mean Error (%) of annual Total Nitrate at monitoring sites in the continental U.S. modeling
domain.
-------
NH4 NMB (%) for run 2007aqJ37c_12US1 for 20070101 to 20071231
rT [T
units = %
coverage limit - 76%
>100
180
160
40
120
0
-20
-40
I-60
I-80
U-100
CIRCLE=CSN; TRIANGLE=CASTNET;
Figure 4-11. Normalized Mean Error (%) of annual Total Nitrate at monitoring sites in the continental U.S. modeling
domain.
NH4 NME (%) for run 2007aq_07c_12USl for 20070101 to 20071231
unite - %
coverage limil - 75%
>100
190
180
70
160
150
140
130
120
10
CIRCLE=CSN; TRIANGLE=CASTNET;
Figure 4-13. Normalized Mean Error (%) of annual Ammonium at monitoring sites in the continental U.S. modeling
domain.
-------
EC NMB (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
units . %
coverage limit« 75%
>100
180
I 60
40
20
|o
-20
I-40
-60
I-80
<-100
CIRCLE=IMPROVE; TRIANGLE=CSN;
Figure 4-14. Normalized Mean Bias (%) of annual Elemental Carbon at monitoring sites in the continental U.S.
modeling domain.
EC NME (%) for run 2007aq_07c_12US1 for 20070101 to 20071231
units = %
coverage limit. 75%
>100
90
80
70
60
50
140
30
20
110
CIRCLE=IMPROVE; TRIANGLE=CSN;
Figure 4-15. Normalized Mean Error (%) of annual Elemental Carbon at monitoring sites in the continental U.S.
modeling domain.
-------
PC NMB (%) for run 2Q07aq_07c_12USl for 20070101 to 20071231
UfWS-%
coverage limit .75%
> 100
80
I 60
40
120
0
-20
-40
-60
-80
U-100
CIRCLE=IMPROVE; TRIANGLE=CSN;
Figure 4-16. Normalized Mean Bias (%) of annual Organic Carbon at monitoring sites in the continental U.S.
modeling domain.
PC NME (%) for run 2007aq_07c_12US1 tor 20070101 to 20071231
CIRCLE=IMPROVE; TRIANGLE=CSN;
units - %
coverage limit - 75%
>100
90
180
70
160
150
140
130
120
110
'o
Figure 4-17. Normalized Mean Error (%) of annual Organic Carbon at monitoring sites in the continental U.S.
modeling domain.
-------
5.0
Bayesian Model-Derived Air Quality Estimates
5.7 Introduction
The need for improved spatial and temporal estimates of air
quality has grown rapidly in recent years, as the development
of more thorough air quality related health studies have
begun requiring more thorough characterizations of ground-
level air pollution levels. The most direct way to obtain
accurate air quality information is from measurements made
at surface monitoring stations across the country. However.
many areas of the U.S. are not monitored and typically, air
monitoring sites are sparsely and irregularly spaced over
large areas. One way to address the limits to ambient air
quality data is to combine air quality monitoring data and
numerical model output in a scientifically coherent way for
improved spatial and temporal predictions of air quality. This
type of statistical modeling could provide spatial predictions
over the temporal scales used to assess the associations
between ambient air quality and public health outcomes and
for assessing progress in air quality under new emission
control programs. Hierarchical Bayesian Modeling (HBM)
is used in numerous applications to combine different data
sources with varying levels of uncertainty. This section
will briefly introduce the Hierarchical-Bayesian approach
developed by EPA for use in the EPHT program.
The approach discussed in this section combines the strength
of both modeled and monitored pollution concentration
values to characterize air quality with estimated accuracy
and enhanced spatial and temporal coverage. The statistical
approach is explained in McMillan, N., Holland, D.M..
Morara, M, and Feng, I, "Combining Different Sources of
Paniculate Data Using Bayesian Space-Time Modeling,"
Environmetrics, 2010, 21: pp 48—65, DOI: 10.1002/env.984.
5.2 Hierarch ical Bayesian Space- Time Modeling System
5.2.1 Introduction to the Hierarchical-Bayesian Approach
EPA's Hierarchical-Bayesian (HB) space-time statistical
model combines ambient air quality data from monitors
with modeled CMAQ air quality output to produce daily
predictions of pollution concentrations for defined time and
space boundaries. Bayesian analysis decomposes a complex
problem into appropriate linked stages (functions), i.e., a) air
quality data; b) CMAQ model output; c) measurement errors
and model bias; and d) the underlying 'true' concentration
surface. A Bayesian approach incorporates 'prior knowledge'
(e.g., numerical information describing known attributes/
behaviors, statistical distributions, etc.) of the unknown
parameters in the hierarchical model, which results in an
improved estimation of the uncertainty of the 'true' air
pollutant concentration at any location in space and time. A
hierarchical model builds a combined solution, superior to
either air quality monitor data or air quality modeling data
alone.
The predictions of the ambient concentration 'surface'
provided by EPA's HB Model are for a selected year and
with spatial scope spanning across the contiguous U.S.
(i.e., the 'lower 48' states). The HB Model methodology
blends the best characteristics of monitored concentration
values and modeled concentration values for prediction of
the 'true' concentration values (surface) overtime when
both sources of data are available. Air quality monitors are
assumed to measure the true pollutant concentration surface
with some measurement error, but no bias. In contrast.
numerical output from source-oriented air quality models is
assumed to approximate the variability of the true surface
while exhibiting both measurement error and bias (additive
and multiplicative) across space and time. Given the
typical exponentially distributed nature of air quality data.
the HB Model performs its analysis with log-transformed
monitoring and modeling inputs. The HB Model gives
more weight to accurate monitoring data in areas where
monitoring data exists, and relies on bias-adjusted model
output in non-monitored areas. The HB Model approach
offers the ability to predict important pollution gradients
and uncertainties that might otherwise be unknown using
interpolation results based solely on air quality monitoring
data. EPA's HB Model can be used to obtain surrogate
measures of air quality for studies addressing health
outcomes.
5.2.2 Advantages and Limitations of the Hierarchical-
Bayesian Approach
At a high level, the advantage of HB modeling methodology
is its inherent ability to predict air quality estimates for
selected times and spatial scales using air quality monitoring
and air quality modeling data as input, while minimizing
the limitations which arise when either of these methods
are applied separately. Another important advantage of the
HB modeling approach is the ability to predict estimates of
errors in air quality. The HB modeling approach generates
estimates of air quality for days when monitoring data is
missing, in addition to estimating air quality in areas without
monitors. An important disadvantage of HB modeling is the
computational burden imposed on model users. Typically.
these models are 'adjusted' by running numerous simulations.
and at times the solutions are difficult to program and require
significant computer resources. Thus, there is the need for
EPA to develop an operational approach to HB modeling.
It requires experience and statistical expertise to ensure
-------
that proper (initial) modeling assumptions have been used.
that proper convergence criteria have been used for the HB
Model, and that the results are reasonable.
In setting up the procedures for developing the HB Model
estimates, EPA selected a set of data quality objectives.
DQOs, to guide the acceptance of the results. Based on
an independent data set (not used in the predictions), EPA
calculates (1) the Bias as the absolute difference between
the (log-transformed) measurement generated from the
monitor at that location (i.e., the "true" value) and the
log-transformed prediction that is made by the particular
model; and (2) the Mean Square Error (MSE), calculated as
the square of the bias. EPA presents three different types of
MSE summaries: (a) day-specific MSE, averaged over all
monitoring locations; (b) location-specific MSE, averaged
over all monitoring days; and (c) the overall MSE (i.e.,
averaged across locations and time). MSE is a statistical
score that represents overall (average) performance in
which large deviation from the "true" value yields larger
penalties compared to small errors. While these performance
measures were used in evaluating the results, they have no
absolute acceptance/rejection values and are considered on
a case-by-case basis when evaluating the performance of
any years of HB Model application. In general, while the
DQO's usefulness is still being studied and EPA attempts to
achieve these DQOs, these measures are helpful at this time
to describe the quality of the HB predictions from one model
year to another.
In developing and providing the HB Model results, EPA
is attempting to advance the use of improved air quality
estimates. As such, the proper use of the EPA results is
important and discussed further in Section 5.6.
5.3 Results for O3 and PM2 5
The HB Model yields a predicted daily concentration
and error estimate for those predictions within each grid
cell for each day within the time period of interest. The
concentrations are daily PM2 5 or 8-hour maximum ozone
levels. These predictions fall along a smooth (congruent)
response surface across the entire region. The grid used by
the HB Model is the same as that used in generating the
CMAQ estimates. The smoothness of the surface is achieved
by: 1) the choice of prior distributions for air data, CMAQ
output, and the true underlying predictive surface; and 2) the
conditional autoregressive model (CAR) spatial covariance
structure where a grid's predicted concentration is assumed
to be correlated with neighboring cells (note the HB Model
can handle different size neighborhoods). The resulting HB
Model prediction surface approximates the true underlying
response surface while accounting for such factors as
measurement error and potential space-time bias in the
CMAQ output.
EPA stores the set of back-transformed predictions (pm25_
pred, O3_pred) and standard errors (pm25_stdd, O3_stdd)
from a given execution of the HB Model in tabular (comma-
delimited) format within a file named as in the following
example: pm25_surface_12km_2007.csv. Table 5-1 presents
an example of the output that can be obtained from this file.
One row exists in this file for each grid cell-date combination
within the study area. The relevant variables in this file, in
the order in which they exist (and are portrayed within the
column headings of the table), are as follows:
• Date: Represented by the data given in this row, in
MM/DD/YYYY format.
• Longitude: The x-coordinate value transformed to
longitude (degrees).
• Latitude: The y-coordinate value transformed to latitude
(degrees).
Column: The column associated with model results.
• Row: The row associated with model results.
• pm25_pred or O3_pred
• pm25_stdd or O3_stdd
5.4 Overview ofHB Model Predictions
Below is a short description of the inputs and outputs for
a HB Model application for 2007, 12 km grid, PM2 5. A
description of the input metadata and HB Model application
can be found in Appendix E. The air quality data come
from EPA AQS, the CMAQ was run by EPA as documented
elsewhere in this report and the HB Model was applied
at EPA's NERL. The domain of the CMAQ model (and
therefore the HB Model predictions) is found in the following
table.
Figure 5-1 shows the HB Model prediction for PM25 during
July 1-4, 2002. On July 1, the PM25 levels were the highest
along the U.S.-Canada border northeast of Lake Erie and into
the mid- Atlantic region. As the days passed, the elevated
PM2 5 decreased in intensity and moved southeast. Examining
the figure, it is possible to see the change in PM2 5 level at
any point in the domain. Figure 5-2 shows a close up of the
HB Model predictions for July 2. The 12-km grid can be
seen as small squares. Within each grid the predicted PM2 5
concentrations are constant. As such, the PM2 5 concentrations
represent an average over the area where the public is
exposed to ambient PM2 5. Although actual concentrations
within grid cells vary over space and time during a day.
the ambient exposure is likely to be somewhat averaged as
people move about within and between grid cells. Given
the relationship between ambient concentrations, ambient
exposures and personal exposure is not understood well.
one area of study is the degree of misclassification between
exposure and health outcomes based on varying grid sizes.
The HB Model results can track with the AQS data and
CMAQ estimates and the predictions can differ from either
the AQS data or the CMAQ estimates. Figure 5-3 shows HB
predictions for a location where the predictions generally
follow temporally the CMAQ and AQ data. This figure shows
a series of days where AQS data and CMAQ estimates are
fairly consistent. In such cases, the HB Model predictions
track closely to both inputs. Figure 5-4 shows how the HB
Model fills in PM2 5 predictions for days when AQS data
are not available (many PM2 5 monitors are operational and
-------
Date
01/01/2007
01/01/2007
01/01/2007
01/01/2007
01/01/2007
01/01/2007
01/01/2007
01/01/2007
01/01/2007
01/01/2007
Longitude
-119.315
-119.398
-119.483
-119.567
-119.653
-119.739
-119.826
-119.913
-120.001
-120.09
Latitude
23.43627
23.74126
24.04658
24.35223
24.6582
24.96448
25.27106
25.57793
25.88509
26.19253
Column
12
12
12
12
12
12
12
12
12
12
Row
15
16
17
18
19
20
21
22
23
24
03 pred (ppb)
23.011
22.979
22.919
22.987
23.19
23.018
23.12
22.997
22.968
22.949
O3_stdd (ppb)
4.6122
4.6784
4.8484
4.7917
4.84
4.8264
4.8651
4.84
4.8308
4.8357
Note: The exact contents of this table may change over time. Please check the accompanying metadata files.
Table 5-1. HB Model Prediction: Example Data File
Study Year
2007
Bounding West
Longitude
111.1 deg W Ion
Bounding East
Longitude
65.4 deg W Ion
Bounding North
Latitude
51.25degNlat
Bounding South
Latitude
23.0 deg N lat
Table 5-2. HB Model Domains for 12-km Applications
July 1,2002
"Vf•••'•*'
C A N /ft D A
July 2, 2002
MANITOBA
C A N.-ft' D A
July 3, 2002
July 4, 2002
Figure 5-1. HB Prediction (PM ) During July 1-4, 2002 (12 km grid cells)
-------
0 10 20 30 40+
Figure 5-2. HB Prediction (PM2 5) on July 2,2002 (12 km
grid cells)
collect samples during 1 day in every 3-day time period).
On the unmonitored days, the HB Model predictions track
well with the CMAQ estimates. Figure 5-5 shows a situation
where AQS and CMAQ do not agree well and, while the HB
Model tends to mitigate the bias of CMAQ, the HB Model
the predictions can be highly affected by CMAQ, although
Another way to view the ability of the HB Model to fill in
estimates of air quality where no monitor exists can be seen
in the following figures. The HB Model response surface
is plotted with the grid demarcations in Figure 5-6 along
with the measurements taken at the monitoring stations.
Figure 5-7 rotates this plot to portray its 3-dimensionality.
so that differences between the HB Model predictions and
the monitoring data points can be better seen. The view
portrayed in Figure 5-7 is as seen from the position of the
red arrow in Figure 5-6. As in the previous figures, different
colors represent different concentration gradients (as noted
within the legend included in the plot). These figures show
how the HB Model prediction surface aligns closely with the
monitoring station data in most instances, except for a cluster
of data points in the upper center of the plot. Figure 5-8
portrays the same plot as Figure 5-6, but with the CMAQ-
estimated PM2 5 surface added. The CMAQ surface features
have more yellow shading within them, implying that the
CMAQ concentration values somewhat underestimate the
concentrations relative to the HB Model and the monitoring
stations. However, in areas in which there are few or no
monitoring stations, the HB Model surface corresponds
closely with the CMAQ surface. This is to be expected, as
the HB Model weighs (uses a bias adjustment of) the CMAQ
data more heavily in areas without monitoring data.
Figure 5-9 displays the ozone concentration for the
continental U.S. on July 26, 2005. The spheres represent
the concentrations recorded at monitor locations. The green.
blue, and yellow represent the HB concentration surface.
which combines the CMAQ model estimates and the PM2 5
monitor measurements.
5.5 Evaluation ofHB Model Estimates
As reported in the McMillan paper (Environmetrics, 2010).
model validation analysis was performed to compare the HB
predictive results at 2001 STN/IMPROVE monitoring sites
to predictions at those locations from two other approaches:
(1) traditional kriging predictions based solely on the FRM
monitoring data and (2) CMAQ output at these locations. In
doing so, it was assumed the STN/IMPROVE measurements
represent the "truth." The IMPROVE measurements are
representative of rural areas (with few monitors) and may
help assess the HBM results for these areas of interest. The
potential bias in either the STN or IMPROVE gravimetric
mass measurements compared to FRM data were not
considered, although for gravimetric mass the monitors
generally produce the same results. STN data collocated with
FRM monitoring sites used in fitting the HB Model were
eliminated from the validation data set, leaving 44 sites for
the validation analysis.
In the validation analysis, mean squared prediction error and
bias were calculated to evaluate the predictive capability of
these three different models. To assess the ability of the HB
Model to accurately characterize prediction uncertainty, the
percentage of validation data within the 95 percent prediction
credible interval was calculated. In the analysis, a similar
analysis was performed for the kriging model by calculating
95 percent confidence intervals at the validation sites. An
exponential variogram model was used for the kriging model.
The exponential parameters were estimated by fitting this
model to an empirical variogram based on combining the
daily empirical variograms.
In this analysis, predictions for each day were obtained
for the STN/IMPROVE site locations from the three
modeling approaches and the validations statistics were
calculated across all days and sites. The validation only
occurs every third day, according to the sampling schedule
of STN/IMPROVE. This corresponds to the full network
FRM schedule. Thus, the analysis did not evaluate sparse
monitoring days where data fusion is expected to outperform
interpolation techniques based solely on the monitoring data.
In the analysis, the HBM was run several times using a range
of reasonable priors. Then, the validation analysis assessed
the relative predictive performance of the HBM, traditional
kriging, and CMAQ as described above. In terms of mean
squared prediction error (MSB), the HBM and kriging
approaches provided similar results across all HBM runs.
For bias, the HBM outperformed kriging by 10 to 15 percent
y y
depending on the prior assumptions for T and T . CMAQ
was nearly unbiased for this analysis.
Kriging uncertainties were reflected in the small percentage
(59%) of kriging prediction intervals capturing the validation
data. This compares to HBM predictive interval results of 80
-------
ID-I8136
1
0>
u
Q>
a
47/WM02
pun
LM ',/; j.:
PMIi.stdd ..*•*-* Ca«ipt(er,ditn +
Dl/tH/ZtDi
-+ -i- Ita I liar.ll 11
Figure 5-3. HB Prediction (PM25) Temporarily Matches Figure 5-4. HB Prediction (PM25)
Compensates When AQS Data is Unavailable
ID-90B4
I
e
01
2
it
••
u
it
14
:
• ;
•
I
•
E
5;
;
g
:
1
.
07/16/1061
,• -A-& PK23_!tdd ..*•*-* Compulef.lHto -» + 1- Ml 11 tor.lr ll
Figure 5-4. HB Prediction (PM ) Compensates When AQS Data is Unavailable
-------
4J/01/200J
PLOT
07/16/2062
PH25_»td
-------
Figure 5-7. Rotated View of the Response Surface of PM25 Concentrations as Predicted
by the HBM on a Specific Monitoring Day in the Northeast U.S., Along With PM2 5
Measurements on a Specific Monitoring Day from FRM Monitors in the NAMS/SLAMS
Network
Figure 5-8. Rotated View of the Response Surface of PM25 Concentrations as Predicted by the
HBM on a Specific Monitoring Day in the Northeast U.S., Along With PM2 5 Measurements
on a Specific Monitoring Day from FRM Monitors in the NAMS/SLAMS Network, and the
Response Surface as Predicted by the CMAQ Modeling System
-------
Fused 36 km 0? Surface, 7/26/05
Figure 5-9. Fused 36 km O3 Surface for the Continental
U.S. (July 26,2005).
to 90 percent depending on the HBM ran. This occurs from
the difference between the HBM results and the 95 percent
nominal rate to the difference in the measurement errors in
the validation to those in the FRM data used in fitting the
HBM model. Unfortunately, error-free PM2 5 monitoring data
are not available with current PM2 5 monitoring approaches.
5.6 Use of EPA HB Model Predictions
Over the next several years, NERL will be working to
improve spatial and temporal estimates of ambient pollutant
concentrations to facilitate improved modeling of human
exposure. The goal is to improve exposure modeling for
intracity and intercity exposure comparisons and to develop
better understood exposure surrogates for use in air pollution
health studies. Given the uncertain characterization of air
quality, especially at locations at a distance from central
monitoring sites, NERL has been working to develop the HB
Model (and other approaches) for estimating ambient and
exposure concentrations for use in health studies, benefits
assessments, and other air program analyses.
The HB Model as developed by NERL is part of a
continuing research program. Accordingly, it should
be understood by users of the HB predictions that the
underlying statistical model is continuing to be studied and
improved. However, given the uncertain nature of air quality,
especially at locations well-removed from monitoring sites,
NERL has been working to develop the HB Model (and
other approaches) for estimating ambient and exposure
concentrations for use in health studies, benefits assessments,
and other air program analyses. To encourage assessments
of these predictions from the HB Model, NERL is making
the predictions available based on a general DQO approach
of determining whether the predictions from the HB Model
are appropriate for use for these purposes. This approach
allows use of uncertain results by providing the statistical
error estimates for the predictions and an assessment of the
predictions. In this manner, users can assess the effects of the
uncertainty for the predictions with their studies.
Based on NERL's current model evaluation results, the HB
Model predictions provide credible predictive surfaces of air
quality (ozone and PM2 5), in particular away from monitoring
sites. The HB Model, as initially configured, predicts to the
central tendency with the potential distributions (that is,
each estimate represents a mean value from the distribution
of possible values for each space-time point). This means
that the HB Model will tend to under-predict very high
values (the implications of this are being investigated).
Nevertheless, the HB predictions, by "filling-in" pollutant
concentration values for missing (non-monitored) locations
and missing (unsampled) days of air quality estimates, are
likely to be an improvement compared to simply using the
monitoring results. In addition, as the HB Model is a space-
time model, it is more credible than statistical interpolation
of the monitoring data where there are missing monitoring
data (this is the predominate issue for 1 in 3 day PM2 5
monitoring sites across the U.S.). The HB Model, and other
statistical methods, is more scientifically credible than simple
mathematical techniques, such as inverse distance weighting.
Given the uncertainty and the complexity of using the HB
Model predictions, careful use of the HB predictions is
needed. Until a thorough study of several prediction years
and scales (grid sizes) is completed, the results should
be used by professionals with an ability to understand
anomalous outcomes when using the predictions in a health
study. An exception-based review of the HB predictions
should be undertaken by each researcher, in the context of
a study's data needs, to ensure "outliers" do not influence
subsequent analyses. The HB predictions include a few very
high values which cannot be rejected out-of-hand without
further study. Studies of the representativeness of the HB
Model predictions and additional experience with the
prediction will provide a better understanding of the limits of
using these predictions. The HB Model was initially designed
for use as a source of air quality estimates in case-crossover
analyses where temporal and spatial variability was needed.
The predictions could be used within the EPHT program
in health surveillance activities, to generate hypotheses
for further studies, and as a basis for indicators in counties
without monitors. They also can be used in Health Impact
Assessments in place of interpolated monitoring data.
EPA continues to research approaches to combining air
quality data and model results to predict statistically air
quality estimates for use in health studies and elsewhere
in the air program. There are key scientific questions that
the HB Model (and other techniques) may help address.
For example, determining the most representative scale (12
km or smaller scale) of ambient air quality measures (as
surrogate for ambient exposure or personal exposure) for use
in associating health outcome data with air quality changes
needs to be better understood. The effect of (monitor)
measurement variability and CMAQ bias on the usefulness
of the HB predictions is also an important aspect for further
improvement of air quality measures used in health studies.
-------
Appendix A
Acronyms
ARW
CAR
CARB
CEM
CHIEF
CMAQ
OAQPS
ACRONYMS
Advanced Research WRF core model
Biogenic Emissions Inventory System
Emissions modeling framework
Clean Air Interstate Rule
EPA's Clean Air Markets Division
Criteria Air Pollutant
Conditional Auto Regressive spatial covariance structure (model)
California Air Resources Board
Continuous Emissions Monitoring
Clearinghouse for Inventories and Emissions Factors
Community Multiscale Air Quality model
Commercial marine vessel
Carbon monoxide
Chemical Speciation Network
Data Quality Objectives
Electric Generating Units
Listing of elements contributing to atmospheric release of pollutant substances
Environmental Protection Agency
Emission Factor (California's onroad mobile model)
Federal Aviation Administration
Four Dimensional Data Assimilation
Federal Information Processing Standards
Hazardous Air Pollutant
Hazard Mapping System
Incident Status Summary form
Integrated Planning Model
Itinerant
Land Surface Model
OTAQ's model for estimation of onroad mobile emissions factors
Moderate Resolution Imaging Spectroradiometer
Motor Vehicle Emission Simulator
National Electric Energy Database System
National Emission Inventory
National Exposure Research Laboratory
National Emission Standards for Hazardous Air Pollutants
Ammonia
National Mobile Inventory Model
OTAQ's model for estimation of nonroad mobile emissions
Nitrogen oxides
EPA's Office of Air Quality Planning and Standards
-------
OAR
ORD
ORIS
ACRONYMS
EPA's Office of Air and Radiation
EPA's Office of Research and Development
Office of Regulatory Information Systems (code) - is a 4 or 5 digit number assigned by the
Department of Energy's (DOE) Energy Information Agency (EIA) to facilities that generate
electricity
One Record per Line
EPA's Office of Transportation and Air Quality
Polycyclic Aromatic Hydrocarbon
Portable Fuel Container
Particulate matter less than or equal to 2.5 microns
Particulate matter less than or equal to 10 microns
Particulate matter greater than 2.5 microns and less than 10 microns
Intentionally set fire to clear vegetation
Regulatory Impact Analysis
Regional Planning Organization
Rapid Radiative Transfer Model
Source Classification Code
Satellite Mapping Automatic Reanalysis Tool for Fire Incident Reconciliation
Sparse Matrix Operator Kernel Emissions
Texas Commission on Environmental Quality
Technical support document
anic compounds
Vehicle miles traveled
Uncontrolled forest fire
Western Regional Air Partnership
Weather Research and Forecasting Model
-------
Appendix B
U.S. 2007 Emissions Inventory Totals by:
Sector, Pollutant, and Region
All Sectors
2007 Country
& Sector
Canada othar
Canada othon
Canada othpt
Canada
Subtotal
Mexico othar
Mexico othon
Mexico othpt
Mexico Subtotal
Offshore othpt
Offshore
seca_c3
2007 TOTAL
[tons/yr]
CO
3,747,987
4,514,002
1,147,801
9,409,790
350,557
1,066,589
68,422
1 ,485,567
89,800
40,377
11,025,535
[tons/yr]
NH3
537,835
21,810
21,138
580,784
254,600
1,898
0
256,498
0
0
837,282
[tons/yr]
NOX
718,996
537,665
861 ,223
2,117,883
171,099
110,203
224,202
505,505
82,571
490,149
3,196,108
[tons/yr]
PM10
1,421,910
15,002
117,254
1,554,167
75,556
5,151
97,146
177,854
839
40,483
1 ,773,342
[tons/yr]
PM2.5
393,852
10,632
68,114
472,598
49,023
4,720
72,264
126,007
837
37,240
636,682
[tons/yr]
S02
97,652
5,430
1 ,762,340
1 ,865,422
82,643
6,124
649,810
738,578
1,961
300,320
2,906,280
[tons/yr]
VOC*
1 ,332,559
308,318
448,629
2,089,507
429,264
152,265
65,273
646,802
53,399
17,176
2,806,884
* VOC is approximated from a sum of speciated VOC within the modeling domain
Table B-la. Canada, Mexico, and Offshore Emissions Inventory (2007)
All Sectors
All CAPS
9,889,383
3,251,990
2,533,464
20,347,679
22,907,847
49,564,767
48,905,880
14,203,845
10,152,800
1,334,304
183,091,958
CHLORINE
sum ofon_noadj, runpm, startpm. NOT SMOKE-MOVES based
6,413
429,956
109
Table B-lb. Total Emission Inventory for All US Sectors (2007)
-------
All Sectors
2002 Sector
Comparison
afdust
Ag
Aim
avefire
nonpt
nonroad
onroad
ptipm
ptnonipm
2002 Total
2007-2002
[tons/yr]
806,471
8,554,550
7,526,723
21,386,059
59,810,866
305,148
3,195,469
101,885,285
-588,349
[tons/yr]
0
3251990
904
36,777
135,542
[tons/yr]
[tons/yr]
8,901,461
[tons/yr]
1,830,271
[tons/yr]
2,259,844
189,428
1,531,602
1,859
290,708
29,991
154,180
3,901,951
381,707
2,176,159
7,786,709
4,618,944
2,368,987
20,931,673
632,683
Table B-lc. Total Emission Inventory for All US Sectors (2002)—Individual Criteria Pollutants
All Sectors
2002 Sector
Comparison
TOTAL CAPs
10,731,732
3,251,990
3,686,966
10,761,239
20,851,988
27,069,516
73,330,569
16,766,279
10,369,280
176,819,560
8,740,230
Delta CAPS
-842,349
-1,153,502
38,144,641
-504,309
-4,161,669
-23,765,802
-2,56
-216,480
6,272,398
Table B-ld. Total Emission Inventory for All US Sectors (2002)—Total of All Pollutants
270,007
7,376,314
17,902,244
37,903,749
33,600,784
578,111
3,222,221
58,225
100,911,655
3,251,990
773
134,080
2,042
163,735
550,283
20,997
159,003
•
4,282,903
1,924,925
1,683,490
2,010,786
8,001,667
397,094
3,360,926
2,247,228
688,087
20,314,203
59,366
1,349,685
192,016
179,470
3,363,355
612,992
653,957
58,042
15,327,874
56,687
1,076,954
182,151
102,494
2,850,301
507,501
442,656
53,398
6,302,535
154,016
1,252,645
103,787
66,370
233,739
9,083,244
2,117,649
452,318
13,463,767
67,690
7,474,512
2,514,819
3,147,282
7,910,324
40,075
1,310,085
24,233
22,489,021
Table B-le. Total Emission Inventory for All US Sectors (2007)—Individual Criteria Pollutants
-------
EMF (CAPs Allan; HAPs 2007aq)
CHLORINE
11286 121856
7077 82207
4455 37712
13915 7160
7517 71069
0.00017
24.02877396
187024
106688
19
120641
202137
54117
71303
175437
51901
82137 30
69836 293
267915
0.058655841
0.228199
0.357981
1.602507483
11.31970503
11894.34948
9436.252264
9255.121873
9.000552195
262.6793018
710.8075173
954.4006053
14696.15136
22845.55158
13870.87746
24197.27919
1812.129367
11934.78281
19024.47572
8860.019383
0.268928
6445.093641
1117.041165
15951.67487
0.2276199
1150.0036
2725.641877
6948.128171
5702.079344
4908.206281
1061.155085
1606.873727
8482.491848
4792.85767
28531.72288
14455.15146
32345.00547
124.8770086
26831.9864
HG (ALL)
2.648276708
0.724642783
0.556254157
0.004798069
0.425687095
0.11089239
0.207180345
0.000513285
1.14966177
1.791023188
4.230803099
2.800385666
1.143613123
0.995962134
1.827754351
0.562065999
0.002581264
0.89792433
0.175263271
1.931167003
0.668806628
0.323509395
1.776256877
0.51300761
0.319061926 413.8236483
0.302924542 766.2286542
0.028230392
0.112393565
0.939515138
0.475898684
1.740943417
1.058625398
3.840422582
0.875736749
0.097934942
5.005906635
8393.798537 0.530806269
925.2299453 0.041491004
13380.60629 1.313491902
3122.423236 5.203198399
1792.14753 0.16121658
38.54131921 0.007099717
5623.911513 0.603739082
Table B-2a. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning Model
(IPM)—EMF: Criteria Air Pollutants and Hazardous Air Pollutants
-------
EMF (CAPs Allan; HAPs 2007aq)
State CO
WA
WV
Wl
WY
1599
10561
10549
7165
12680
151172
55409
80027
VOC SCX
209
1173
957
853
2184
374321
136061
84750
NHL PM,
45
160
343
383
2541
29339
5542
9809
2105
27099
5131
8114
TOTAL 578111 3360926 40075 9083244 20997 612992 507501
CHLORINE
0.000206627
17.77954453
102
34.80750306
3394.176361
2042.778522
168.1865476
352,291
HG (ALL)
0.27842695
2.490127087
1.134734917
0.957139771
53
-------
SMOKE (2007aq_07c 21 apr201 0) |
State
AL
AK
AR
CA
CO
ALD2
0
2.80E-05
0
0.070458916
0.414653824
CT 0.03613224
DE
DC
FL
GA
ID
'L
IN
,A
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
R,
SC
SD
TN
TX
Tribal
UT
VT
VA
0.014036704
0
0.012735294
0
0
0.062492988
0
0.000684697
0.10011464
0.011676434
0
9.99E-05
0
0.158020703
0.013938263
0.015828933
0.000694461
0.007440895
0
0.000579899
0
0.000445657
0.261332752
0
0.317812076
0
0
0
0.008770935
0
0.07121038
o
0.000374681
0
0
0.064123473
0
4.10E-06
0
0.006609495
ALDX
0.009291538
3.28E-05
0
0.075452381
0.114973056
0.04963954
0.01305193
0
0.017372355
°
0
0.017689108
0
0.003805543
0.042761172
0.013706617
0
0.003305922
0
0.147067993
0.003864714
0.010803694
0.00051068
0.002063217
0
0.000160791
0.186243157
0.000609941
0.319103532
0
0.434923373
0.001364333
0
0
0.002431955
0
0.019744894
0
0.004768319
0.013185135
0
0.046665972
0
4.81 E-06
0.00788047
0.005039387
BENZENE
58.12108246
26.99346838
22.50425855
42.25660373
24.49635334
5.612022405
4.160893582
0.009311689
77.00599863
62.00373879
0
74.71698885
128.8250026
29.7392417
51 .4429891 6
65.68133104
22.6970348
3.892180414
19.80240231
12.24609382
54.45726677
34.351 74485
37.07519757
70.83327345
18.7835715
29.70707946
1 3.5296903
4.550999677
32.44433182
23.20991114
20.90592796
44.00873669
32.78820696
80.74917591
45.98952953
3.635988302
49.791 9486
0.055961882
36.79379154
4.135150714
37.64892927
179.6137352
0
19.08184779
9.508834455
25.94028141
CH4
306.4601042
163.0001219
84.81972167
1640.966427
1654.922689
257.8323795
1 9.940721 24
0.013636613
1137.499951
61 .97496828
0.442196356
343.8227466
692.8977159
29.44087479
226.3054138
128.0648106
145.6884494
76.51379774
35.73256224
461.1944633
324.4981096
91 .44064595
506.2985089
256.0760683
12.26448268
1 0.55264926
101.1174338
41.31092644
801 .6480749
179.8191196
525.2076822
94.94076908
0
38.36642978
689.198018
167.2548938
358.8718261
79.28457195
189.1743625
0.181816565
57.43124941
2772.63984
308.9966543
45.34271973
19.25314142
240.5631045
CL2
0
0
0
0.000170005
24.03156889
0
0
0
0
0
0
0
0
0
0.330937643
0
0
0.011182118
0
0
0.052985528
0
0
0
0
6.829774424
0
0
0
0
0.058677704
0.22819875
0
0
0
0
25.08260348
0
0
0
0
14.61465273
0
0.357980992
1 .603238343
11.31148375
CO
11284.68284
7072.439139
4454.625068
13865.71436
7516.751989
1720.440983
868.0364142
6.921681023
34801 .07966
10414.26598
4.41 0377278
15363.00378
22308.20071
4799.340104
6464.163785
12491.63361
8527.031517
438.1624639
4298.403164
7189.452694
13098.70236
7201 .406383
5042.517613
11556.85642
3432.813472
3253.985787
2692.144646
1009.917174
4151.93252
5005.691306
9667.526591
12076.25973
4868.409379
15111.15044
12753.20852
1688.883191
17233.37655
309.5495596
4684.16141
652.8389107
6520.625632
221190.6516
441 .31 55834
4693.039192
1008.393381
4902.246124
ETH
0.648354489
0.298069516
2.044711403
23.748061
14.19623256
0.445857184
2.2584595
0.039914348
1 41 .3359984
0.049475401
0
7.177003181
5.94634366
10.95194911
65.21608696
2.00670521
3.774117616
4.179389596
7.29747976
1 2.435641 74
5.887670094
1 6.33389305
47.18280517
1 4.631 56532
2.050227686
9.134624716
0.528404396
2.077703403
11.54048502
0.128173824
19.10581286
5.234505663
0
0.949435199
2.689445081
ETHA
273.2483166
106.8536347
100.7899505
23.42785241
247.6682023
19.9908381
16.57295412
0.003303749
1 94.04821 02
288.0865182
0
359.2532457
434.2279117
110.7833655
196.3026055
307.2999326
91 .97969537
1 .076971 985
80.45436013
53.51850573
229.503033
1 24.5286688
50.60781879
320.4019606
87.63348477
130.5323611
80.39265278
1 8.77566554
128.8926972
95.179436
55.11786011
196.2089329
154.6453614
379.9988889
83.91657763
0.510918291 16.5239188
7.969171667
0.151419472
21 .64409834
0.055381875
2.869283288
31 .65208895
0
11.5064672
9.718398115
33.01229121
247.8485398
0.012533141
97.67846413
1 9.44707674
1 74.6365844
467.3712041
0
73.401 48039
2.62253291
90.22048518
Table B-2b.Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning Model
(IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 21apr2010)
WA
WV
Wl
WY
TOTAL
0 0
0.008840497 0.010384035
0.042075516 0.079576369
BENZENE
8.433377552
53.89321999
113.5506385
38.12625003
1,856
63.61692841
3.861132625
448.0319406
54.58199419
15,949
0.000206627
17.77757314
0
102
1598.597901
10557.48496
10548.49593
7163.616492
578,005
0.016219549
0.17948119
93.98001378
0
655
39.3564369
253.3661714
182.9152598
179.8221384
6,887
-------
SMOKE (2007aq_07c 21apr2010)
HGIIGAS HGNRVA MONO
AL
AK
AR
CA
CO
CT
DE
DC
FL
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
R,
SC
SD
0
2.18E-05
0
0.006940302
0
0
0.015000392
0
0.588674871
3.496710587
0.013026842
0.009095619
0
3.296243515
0
0
0
MN 6.673016392
MS 5.37E-06
MO 0
MT 0
0
0
0.202476183
0
0.035711113
1.419245657
0
0
0
0
4.502982973
0
TN 0
0.002309126
0
3.19E-06
VT 8.197683382
131.1825985
52.55853664
33.37345724
468.7438509
358.5668836
133.71406
10.78166047
0.231050309
517.988894
23.88559894
0.189218822
88.05629349
144.1285469
3.815386141
15.10054826
54.17417683
283.9386938
35.2565971
27.63039032
219.4057145
116.3365417
8.348120507
145.8163362
85.57389657
0
4.705310811
76.3190937
22.00550648
342.8959264
64.96882385
303.8509828
38.65371745
0
16.85589977
285.5650507
71.41163712
100.0051105
33.82208002
25.36631348
0.074614227
24.88268913
846.0004221
132.2217126
13.62148201
6.02E-05
112.5625732
11892.5276
9433.458356
9253.17784
9.000782098
262.6819968
710.8597746
953.9142029
0
14694.59757
22844.06739
0
13869.15677
24195.61943
1810.805239
11932.28512
19021.47152
8859.585355
0.2689312
6444.367594
1117.067821
15949.63494
430.364044
1150.017981
2725.796313
6946.809186
5700.907383
4908.210279
1061.142505
1606.453583
8482.514623
4792.138154
28525.6047
14454.64496
32339.96748
124.874647
0
26832.46069
0
8391.920422
925.1421988
13377.18827
3122.42895
0
1791.930418
38.55890967
5622.057339
1.123118089
0.05248058
0.157273452
0.000949526
0.105332055
0.033632188
0.127120376
0.000153984
0.537166393
1.005947601
0
1.383250053
1.14352209
0.277560809
0.17028617
0.84015477
0.141888064
0.000774371
0.547030224
0.111436818
1.028568499
0.081394696
0.138546655
0.664151735
0.030920845
0.110216564
0.089619685
0.014317483
0.048348239
0.03892167
0.228190155
1.132479221
0.120549265
1.712927402
0.189078394
0.030193078
2.871270005
0
0.283023483
0.01279019
0.664300633
1.518856243
0
0.070088769
0.002130871
0.389842896
1.445134219
0.665187913
0.397864771
0.002844204
0.315582662
0.07472488
0.062190164
0.000256649
0.538401837
0.708778906
0
2.789232822
1.585516595
0.862464365
0.818749526
0.921866365
0.418327102
0.001290621
0.297758535
0.05023799
0.812190532
0.578854027
0.173484121
1.090959964
0.474909077
0.207402124
0.211823646
0.01046817
0.055220999
0.891323423
0.219847887
0.502967311
0.932706032
1.963758599
0.68484995
0.067536118
1.842166369
0
0.222165744
0.028625429
0.600556578
3.604325146
0
0.084651751
0.003551501
0.173615572
0.000532145
1.05E-05
0
0.34532784
3.253195155
0.01877552
0.05057778
0
0.007141547
0.487877687
0
0.003967347
0.660420441
0.00437716
0
0.000230835
0
0.549944368
0.112677167
0.155629513
0.001450486
0.058377924
0
0.004549646
0.010705031
0.000247087
0.101002905
0
0.312344526
7.70E-05
0
0
0.068812972
0
0.558684619
0
0.000384892
0.000498544
0
0.258777782
0
1.54E-06
0.000445018
0.051976404
Table B-2bi. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning Model
(IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 21apr2010)
WA 0
WV 0.007678178
Wl 45.43737546
TOTAL
74
26.90847366
1.885987197
11.9453922
23.35601313
5,539
34.80124674
3393.760968
2042.603429
168.1860612
352,245
HGIIGAS HGNRVA MONO
0.0858219
1.515224469
0.357116733
0.073128646
21
0.192113252
0.839492008
0.769209213
0.879429049
30
0.003318174
0.183573952
0.001977688
0.006070226
0
0
-------
SMOKE (2007aq_07c 21apr2010)
MEOH
AL
DE
DC
FL
PA
0.060695991
0
0.005988783
0.000294249
0.301173361
0
0.000970309
0
3.22E-06
0
0.073248075
726.8560559
464.7365829
279.2167486
422.2331986
409.2099283
34.91188803
25.5630354
0.977645664
2807.567372
649.7553662
0
149.2301315
1025.810933
330.0012393
389.927678
830.8800226
750.510461
71.66454064
217.3621422
398.1288839
124.2835776
30.41019164
292.6453516
783.6196534
12.34072286
187.1395964
390.8639715
149.1495169
71.03394827
6.780983803
1958.279392
123.3287172
252.8059556
82.35450553
813.5302407
245.7800827
340.1295166
28.73294975
293.2723363
0
421.936046
2998.693608
34.52100572
344.2592525
0
92.98721066
109630.7195
73953.44272
33942.2579
6443.308226
63961.88159
4390.075904
9611.697401
243.699406
168184.3911
95953.38606
17.3174417
108494.6368
181741.634
48707.73572
64227.65881
157935.2207
46719.07403
639.793775
47129.40576
13802.95105
100224.509
65836.06152
45694.25157
101584.4431
31331.30834
37413.39387
19294.04977
4363.3443
15351.55488
64245.76302
43478.6854
55501.83858
63148.43365
219649.6376
69671.34366
10443.74101
166388.1058
473.3105574
42313.923
10678.82563
93877.81828
145771.9039
70.53968997
63083.20054
339.056807
52500.0756
12181.19241
8217.049693
3771.362236
715.923183
7106.876216
487.7862443
1067.966441
27.07770464
18687.15536
10661.48796
1.924162889
12054.96011
20193.51606
5411.971407
7136.407218
17548.35865
5191.008569
71.08822511
5236.600971
1533.661327
11136.05705
7315.118246
5077.13933
11287.1611
3481.256609
4157.043875
2143.78342
484.8161072
1705.728425
7138.418788
4830.965367
6166.871336
7016.493067
24405.51654
7741.260865
1160.415764
18487.56826
52.59004402
4701.547318
.536144
10430.86996
16196.87894
7.837741553
7009.244576
37.67294694
5833.342152
121811.9119
82170.49241
37713.62013
7159.231409
71068.75781
4877.862149
10679.66384
270.7771106
186871.5465
106614.874
19.24160459
120549.5969
201935.15
54119.70713
71364.06603
175483.5794
51910.0826
710.882000
52366.00673
15336.61238
111360.5661
73151.17976
50771.3909
112871.6042
34812.56495
41570.43775
21437.83319
4848.160408
17057.28331
71384.18181
48309.65076
61668.70992
70164.92672
244055.1541
77412.60452
11604.1567
184875.6741
525.9006014
47015.47031
11865.36177
104308.6882
161968.7828
78.37743152
70092.44511
376.7297539
58333.41776
0
0
0
0
0.003657276
0.002553624
0
o
0
0
0
63.02893079
24.91417597
24.90592139
4.78113844
42.53483296
4.93006733
5.656951827
0.034594514
106.5969999
66.27604594
0
84.71563469
101.5285861
31.34871865
95.11814061
72.36633799
24.33932865
0.607176125
24.68325849
18.65919927
56.3914986
32.15974262
51.62447028
80.86103309
20.09655559
37.71706161
12.3916146
6.07729101
39.0462706
21.99136965
22.40286998
48.07775344
35.55455296
88.38407742
21.0138434
4.232117646
58.16244517
0.131237547
22.92119884
4.527949688
42.58302029
125.7658038
0
26.62961846
0.92476559
48.39731937
Table B-2bii. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning Model
(IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 21 apr201 0) |
State
WA
WV
Wl
WY
TOTAL
MEOH
0
0.006931413
0.021241469
0
1
NH3
44.67263855
160.3079565
342.8528166
382.6995697
20,994
NO
11407.86138
135796.9649
50526.45461
72026.90476
3,028,218
NO2
1 267.540356
15088.55245
5614.050989
8002.989946
336,469
NOX
12675.40174
150885.5174
56140.50559
80029.89471
3,364,686
NVOL
0
0.001927234
0.005915389
0
0
OLE
9.062211705
58.41327633
46.02233644
41 .34299951
1,860
-------
SMOKE (2007aq_07c 21 apr201 0) |
State
AL
AK
AR
CA
CO
CT
DE
DC
FL
GA
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Rl
sc
SD
TN
TX
Tribal
UT
VT
VA
PAR
693.1172725
306.8522354
262.1207018
339.4364157
316.3294993
97.69962495
47.97759449
0.309372062
941 .9795672
738.0945738
0
880.0061233
1401.687159
290.4998738
489.6672452
779.7436917
540.5194408
8.952978304
239.5920443
231.0212722
638.2767395
305.6333885
287.9986138
814.5552047
221.0201275
338.4347072
357.2749755
56.0162668
370.7187137
266.1491401
314.574741
498.6064013
391.4151905
963.9068601
580.3178981
42.27318698
602.9506398
0.280679815
242.2836709
50.83503278
444.377231
1809.543141
0
200.2805618
3.286241777
268.2887617
PEC
488.8057233
173.6132284
75.08611628
563.0535391
200.5339387
30.82409024
66.62354283
4.219643089
1201.709465
575.549061 9
0.222925434
370.0142284
925.3289838
188.0627873
122.9532687
441.368183
289.4759823
23.5382352
371 .3837444
146.7590483
357.038582
70.85606078
468.9233037
149.4215818
46.44049538
29.48981189
87.90051555
94.99823167
290.3260917
134.9353251
450.7125994
353.0055719
117.2763342
1033.860143
276.8253331
34.22692698
1136.833295
21 .3584541 2
265.1550902
6.69702375
292.0614853
1920.753129
6.588260647
114.6331573
6.379469055
327.1155726
Table B-2biii. Point Source Electricity G<
PHGI
0.07961321
0.006838182
0.000978372
0.001004472
0.00477743
0.002539374
0.017750157
0.000102657
0.073966468
0.076187536
0
0.058794129
0.071130365
0.003460836
0.006722471
0.06532451 8
0.001822132
0.000516249
0.053075477
0.013606911
0.090256342
0.008358352
0.011374534
0.021234108
0.007077272
0.001413724
0.001516298
0.00344496
0.008810962
0.009353868
0.027719654
0.105146106
0.005319599
0.163126143
0.0017625
0.000211451
0.292311778
0
0.025439778
7.14E-05
0.048267368
0.079417156
0
0.006419077
0.001420592
0.040063281
merating Unit
PM10
26546.1678
9600.287443
2157.748875
1536.828412
5510.569692
735.8281761
2808.124965
8.352923533
27505.31016
36244.24852
0.580534662
22435.4708
43376.62631
9231.411628
6605.646449
23329.70672
6838.148222
96.43531639
17221.66419
3561 .034237
13633.91151
7193.802206
3701 .488253
9650.906361
2829.444218
1530.788073
3650.056048
3025.703637
5221 .4826
7829.873857
11003.29687
24290.79815
7030.216523
60645.58989
3395.693855
1123.710619
67115.14966
48.11367856
16953.56085
374.0751394
15952.28538
34692.66746
17.15692521
6874.606186
47.40308801
12544.1758
(EGU) Emissions
PM25
22868.75987
7628.318511
1895.267596
1491.044018
4493.29851 9
492.0414069
2468.124559
7.436394188
23977.76128
29118.33058
0.580534662
17824.79073
35545.338
8428.228943
5429.918036
20915.71166
5362.086214
82.7677606
15156.2595
3075.069155
11413.30748
2896.04831 6
3108.847541
6326.252436
2446.55551 8
1166.392445
3294.661 033
2673.674295
4438.886066
5282.559164
9692.673353
17609.56827
5952.518172
54009.84845
1 874.088989
558.3203312
56649.18674
46.76939998
13168.48823
343.2291574
13726.24508
24995.21589
17.15692521
5267.61111
46.2280369
11707.32259
Mapped to Integi
PMC
3677.407931
1971.968932
262.4812789
45.78439403
1017.271172
243.7867693
340.0004054
0.916529345
3527.548883
7125.917935
0
4610.680069
7831 .288309
803.182685
1175.728413
241 3.995062
1476.062009
13.66755579
2065.404681
485.9650825
2220.604037
4297.75389
592.6407124
3324.653925
382.8887003
364.3956277
355.3950146
352.0293416
782.5965338
2547.314693
1310.62352
6681 .22988
1077.698351
6635.741 445
1521.604866
565.3902879
10465.96292
1 .344278576
3785.072615
30.84598207
2226.040305
9697.451 574
0
1606.995076
1.17505111
836.8532095
rated Plannin
PMFINE
18812.61639
6243.684689
1 504.098905
403.4218529
3541.711193
346.7839527
2001 .598686
1 .2930471 43
16931.99996
24022.78917
0.152100075
1 4682.78823
28986.3842
6932.746269
4398.949595
17219.29869
3753.924868
27.89739965
1 2343.84026
2315.642137
9169.669006
2363.385222
1 974.8221 45
5184.781827
1990.82224
950.2763863
2677.180296
2128.006546
3333.589904
4312.984786
7343.126406
1 4522.65431
2845.588296
44616.79466
1094.1654
424.7736312
46647.24339
10.38507228
10851.90795
283.3398907
11307.51006
1 3967.09428
4.495114085
4329.540863
21.1724426
9426.583169
g Model
(IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 21apr2010)
State PAR PEC
WA
WV
Wl
WY
TOTAL
100.3734925
643.5496863
424.6926529
455.1388789
20,299
61 .33887498
513.3735903
195.0264565
152.5092125
15,275
PHGI
0.000432474
0.134592624
0.008259161
0.004382108
2
PM10
2540.155071
29331 .30264
5541.670148
9807.19494
612,946
PM25
2104.179511
27092.741 47
5131.134472
8112.192884
507,413
PMC
435.9755603
2238.561168
410.535676
1695.002056
105,533
PMFINE
1593.098216
22386.59907
4089.677559
6705.538709
401 ,028
-------
SMOKE (2007aq_07c 21apr2010)
AL
AK
AR
CA
CO
ID
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
39.67127598
14.88988916
4.802901172
29.54158115
12.61997939
1.601233905
4.376305384
0.005696579
66.72693354
47.82792253
0.012191228
30.03040262
70.28314247
13.62586848
10.08367411
35.52327232
15.81877699
1.227135369
26.83522578
7.874364986
24.99565535
4.736767
22.3094575
11.42829864
636.7690755
249.23252
74.27795742
4.271208739
2.058676125
6.304639737
6.056715664
16.40287196
10.18764409
27.33260537
28.69918032
32.14681537
87.27693337
13.19942404
2.151833339
92.24551442
0.807502902
21.31549893
0.558832648
22.26138527
157.8146623
0.360294993
9.219585421
0
20.16307258
366.9851911
182.7856197
598351
73.16463412
1.473931255
987.7072399
780.8541482
0.143392042
487.6490654
1088.752857
230.9570526
155.7380488
575.4286725
515.3725771
15.48853376
438.6780463
121.0492474
393.3347609
1946009
298.2790618
182.6079911
97.06202605
33.47227104
99.70406885
93.09055816
229.399375
159.2759933
396.9125006
476.9482387
2336.001682
1430.959184
246.6235227
29.05802539
1523.829561
10.92554143
359.658746
9.222957419
370.4704387
6239.801249
4.23776023
147.7114054
15.07033931
340.8710392
2890.897408
946.8981843
237.0017163
128.0418539
555.6477888
89.55614654
322.3613913
0.444076121
4789.617679
3691.310281
0.049925884
2254.308811
4474.588821
1062.836966
742.1934492
2644.092836
787.4940097
14.61645662
1975.522226
483.7443574
1468.269472
363.1508055
344.5135728
798.0127373
307.9595479
151.0952999
423.5715134
351.5222432
569.1678239
665.1754152
1474.589241
2228.260968
621.5050453
6840.957532
243.2753091
68.10991435
7249.034977
3.292829247
1670.450946
43.41045289
1733.941704
2709.752569
1.475495255
666.5060984
3.605785935
1592.589741
447112.0278
54900.07145
72421.27112
652.2409643
65908.57373
7615.61751
34525.59365
389.4184292
319305.9551
635438.6392
0.170014577
277005.6155
722028.6569
132847.5975
115854.2814
380294.3007
84267.77771
1682.722376
274337.0369
59956.10845
341327.9256
82486.79061
69849.83174
270745.6726
22134.44376
69365.32618
8551.27126
42569.82213
37090.89833
26853.69437
112716.5339
379800.3716
136262.253
989409.62
106197.521
14080.81584
968051.5333
177.1126173
173043.2107
10615.63834
237227.5533
503483.0818
3.349638086
24486.50239
5.634334021
185419.093
6522.832782
1179.819568
1702.227036
2.084375853
1604.462058
156.1330553
778.7495135
2.188695045
6053.765256
14357.09164
0
6216.945159
16504.62973
3143.283199
2821.167526
8593.459251
1846.663503
25.70326152
6031.963698
1230.9586
7959.916649
2009.717706
1022.963351
6497.591056
546.1756372
1689.472987
192.0888055
944.78043
500.2409533
657.2943078
2273.05949
8573.726638
3897.100634
19793.56452
1276.79
344.0590954
20021.58101
0
3903.226448
240.8294856
5360.666609
13360.39115
0
445.5689583
0.004158627
4133.480585
0.015690334
1.07E-05
0
0.04027314
0
°
0.000322974
0.005820553
0.006374194
0.004450715
0
0.005353534
0
0.010837675
0
0.314480933
0.112896361
0
0.004018976
0.002305019
0
0.007455775
0.014689817
0
0.064153772
0
1.56E-06
0.013314012
0.003572656
Table B-2biv. - Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning Model
(IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 21 apr201 0) |
State
WA
WV
Wl
WY
TOTAL
PNO3
5.702214212
43.50230471
12.42832135
12.97950859
1,132
POC
187.1207857
716.4400515
1 97.33094
213.3506694
23,938
PSO4
256.9194196
3432.826459
636.6711957
1027.814785
66,039
S02
2183.484342
374230.6548
137924.3459
84739.5872
9,097,577
SULF
52.15384956
8456.032828
3221 .498582
2075.987986
198,224
TERP
0
0.003360245
0.084070812
°
1
-------
SMOKE (2007aq_07c 21apr2010)
ID
216.4608152
86.67622722
80.01954003
20.06483817
77.7397172
16.50581344
13.10718617
°
144.7536128
228.5312187
0
267.1976346
362.0640401
86.79389563
128.6209997
243.2077525
73.80836122
0.012631369
63.83021542
25.14981417
179.8570536
92.01724886
45.52546022
250.5027095
69.07694402
102.6226451
42.30480487
14.79128255
104.1799455
76.92775453
43.27797951
154.735
122.4179918
300.3822705
78.76010245
13.05876298
175.749041
0.01094135
73.01843095
16.70943782
138.056712
401.8435996
0
57.90071924
0.024170941
67.65590569
402.2218025
168.1189689
151.1445842
114.0480078
182.8775593
32.93523152
26.1857849
0.036836083
363.7423111
425.8369376
0
508.1853793
731.3729497
174.6160393
294.5490487
453.2159657
148.7363754
6.816122515
125.7757856
64.60023317
348.5566919
143.7858077
475.3185267
128.854642
197.3276287
125.0686257
29.15028106
203.8781844
147.6428303
99.29192113
2.8546291
227.3193996
559.0414926
195.9886633
24.65127257
338.3995757
0.161439979
164.8433298
28.81028253
258.4518999
885.6129377
0
117.4089766
16.43108163
149.8062527
225.9839014
18.15407816
83.20996932
0.665845607
80.88874518
16.52976574
13.54625088
0
144.0572961
238.2347452
0
278.1669403
358.3377178
90.10828872
133.1851233
254.0143781
75.78058575
0.00828192
66.03361503
24.54506116
184.7685922
73161
38.60257135
261.2879175
72.16271957
107.1487356
42.64246507
15.38435481
106.5867155
78.70148561
45.20780782
161.626135
127.8866168
313.7532652
66.61143031
13.62975282
182.9472696
0
76.16111642
16.54699883
144.2221566
378.0366696
0
59.91307612
0.020444292
70.32413239
Table B-2bv. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning Model
(IPM)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 21apr2010)
WA
31.19901615
200.6474663
122.1709376
142.348012
5,252
58.08035223
372.960808
366.6340745
264.3277198
10,786
32.54538361
209.5319465
127.8924682
148.7069704
5,351
-------
EMF (CAPs Allan; HAPs 2007aq)
CHLORINE
HG (ALL)
bfam/
AL
AK
AR
;A
CO
CT
DE
DC
FL
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
0.0%
0.0%
0.0%
0.0%
.1%
-0.1%
0.0%
0.1%
0.0%
0.0%
-0.1%
0.0%
4.3%
-1.4%
0.3%
0.0%
2.2%
0.0%
-3.6%
0.0%
-5.9%
0.0%
0.5%
-0.4%
0.0%
0.0%
0.0%
-0.4%
0.0%
-0.1% 0.0% -0.1%
-0.1% 0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
3.2%
-0.3%
0.4%
0.0%
1.0%
0.0%
-1.1%
0.0%
0.0%
-0.1%
0.3%
1.8%
-0.5%
0.0%
0.4%
0.0%
-2.0%
0.0%
0.8%
0.0%
0.0%
0.0%
1.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
-0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0'
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.8%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
.0%
BFAM
/voc
should be
<=100%
Table B-2bvi. Point Source Electricity Generating Unit (EGU) Emissions Mapped to Integrated Planning Model
(IPM)—Percent Change between EMF and SMOKE Calculations
-------
EMF (CAPs Allan; HAPs 2007aq)
VT
CO SCX
0.0% 2.2%
0.0% 0.2%
0.0% 0.0%
0.0% 0.0%
1.4%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
CHLORINE
0.0%
-0.1%
0.0%
HCL HG (ALL)
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
bfam /
-------
EMF (2005ck_05b) |
State
AL
AK
AZ
AR
CA
CO
CT
DEE
DC
-
GA
H,
ID
IL
IN
,A
KS
KY
LA
MA
MD
MA
Ml
MN
MS
MO
MT
NE
NE
NH
NJ
NM
NY
NC
ND
OH
OK
Oregon
PA
R,
SC
SD
TN
TX
Tribal Data
UT
VOC
38407
7555
5968
35010
53036
25793
2352
4218
76
36598
36754
3101
1759
65037
51685
30382
23990
49396
76315
4811
5283
7664
41246
24972
42117
24523
7083
6501
3105
968
12074
11557
12720
58850
1048
34886
45228
18548
35683
1584
19931
3099
80622
1 46064
1215
5877
NOX
74830
78764
15975
37478
90687
20971
5824
5567
501
53778
53297
11210
10354
97504
73647
39299
70785
35432
165162
18309
24621
18429
94139
64438
53985
38604
5356
12156
17191
3241
20598
43925
55122
44502
7545
71715
73465
22927
89208
2164
29069
5035
60353
292806
13322
19466
CO
166366
37942
24973
65262
132667
S02
70346
8622
23966
13066
33097
24524 1549
4011
10443
340
105558
94672
7561
27535
96766
350925
35879
36018
46896
144363
16208
107881
21389
94830
32005
51385
78447
25092
8997
24198
4023
16925
30362
78887
63887
5797
229812
52731
51230
103287
2942
46600
8161
107508
258680
2482
49130
1831
34859
686
57475
56116
5514
17151
156154
95200
61241
13142
25811
1 65737
18519
34988
19620
76510
25169
29892
78307
11056
6429
2253
3245
7640
7831
58562
66150
9458
118468
40482
9825
85411
2743
31495
1698
78206
223625
1511
9132
PM10
26171
3748
6821
15335
38020
14025
302
2585
267
31346
17280
2502
3147
25062
27089
11017
12790
15978
48285
5463
9906
3207
20526
20975
17961
12447
6328
3610
6967
661
3260
1858
7117
16724
653
17879
10410
12298
23509
397
7472
4104
29777
47805
4057
7948
PM25
19871
2616
3940
10872
21516
7114
224
2225
172
25196
12964
1718
2072
15683
15553
5804
7631
10450
39591
3785
6768
2245
12918
10651
10602
6948
2729
1857
4095
572
2599
1457
5000
12665
564
12891
6246
8852
14772
256
4779
2873
23039
37563
1569
3595
NH3
2394
747
140
2011
11804
123
149
174
4
2476
5573
22
1236
1238
1185
1072
60212
983
5569
643
148
380
1155
27515
1249
1346
213
1487
361
52
463
28
2050
1821
153
5744
3110
773
1855
16
1560
228
1741
3645
437
CHLORINE
72
2
1
33
97
2
1
3
1
3
5
0
4
253
56
37
6
53
290
9
25
1
23
159
63
240
30
1
0
10
0
69
96
0
128
3
5
77
1
51
148
461
0
1527
HCL
1718
0
41
1337
1098
174
329
149
2379
1209
260
21
2344
1138
1260
308
486
973
377
625
395
2084
1569
603
1123
63
36
13
44
249
15
1521
1154
2
3002
187
412
1910
4
1550
2
2479
3450
1649
HG_ALL
1.29011439
0.038090587
0.066916806
0.83036383
2.28452259
0.391975088
0.180544106
0.167876622
7.46E-07
0.813186486
0.47203701
0.107859509
0.36945541 2
2.00341 8055
2.18325274
0.307405778
0.45797766
0.25471 2996
1 .530688327
0.076057397
0.414272198
0.207092348
1.164076214
1 .65047961 4
0.151465091
1.189304886
0.076114675
2.573738879
2.418421846
0.042549566
0.708216786
0.008338384
1.419547609
0.562488305
0.009964042
7.511957829
0.081772807
0.989379654
1 .533957642
0.051 849646
0.839347698
0.019330695
1.462188107
4.441 935882
0.0007649
1 .586709699
Table B-3a. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—EMF: Criteria
Air Pollutants and Hazardous Air Pollutants
-------
EMF (2005ck_05b)
VT
TOTAL
Continental
U.S.
799
60101
25427
36913
40688
2337202
2125
74575
56465
74247
55493
19241
3267724
902
69440
24211
48314
66807
22321
2131784
465
14769
6225
7928
12099
13632
660207
337
11504
4618
5161
7973
10296
446991
20
1957
810
746
484
469
159773
CHLORINE HCL
1310085 2247228 3222221 2117649 653957 442656
159003
33
24
26
43
"
4175
4174
2
4821
1132
1386
1315
526
48924
48664
HG ALL
0.000899226
1.495832419
0.136359067
0.314364133
0.774468296
0.19702105
48
48
-------
SMOKE (2007aq 1 5mar201 0) |
State
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Puerto
Rico
Rl
SC
SD
TN
TX
Tribal
Data
ALD2
384.3505193
0.000105136
66.553027
264.2681167
410.2723288
351.0435146
30.83174312
17.67865235
0.002029839
364.6636644
264.9247772
0
14.73131222
601 .0757305
394.7680816
281.1361329
156.9882021
129.9691228
263.5084708
50.51943372
63.29672078
59.0635361
360.3127401
146.1372941
265.5194339
250.3121384
21.61174821
75.85174543
42.9207307
9.537762463
81.12534969
34.39869773
132.0696583
357.2109713
19.9840336
434.5492862
135.4774892
107.1922406
247.1231805
0
11.13938069
160.8214392
17.39588838
581.1578381
91 1 .6376539
5.088505445
ALDX
389.5472208
0.000144441
75.71691344
366.5704249
473.2684438
112.0013772
18.97289023
30.90293402
0.623125099
459.0496825
353.499488
o
20.34372773
724.8367726
432.5997908
307.7495112
159.2681821
199.0816174
442.2179831
60.64203242
60.85325518
75.28342215
400.2487329
202.648181
340.4199051
287.96962
46.24197327
70.10912828
56.65124042
11.72559912
1 01 .7769566
48.843321
157.9696187
471.8855819
20.30773961
434.9287513
1 71 .6739005
139.7897903
288.2851734
^H
20.31695577
198.1987171
25.27309561
683.0245204
949.8610484
5.606889924
BENZENE
1609.372567
3.79E-05
132.0557005
1747.562788
1661.771788
698.2190092
79.47565355
144.3611558
3.32546253
1761.832919
1243.160725
o
147.5943421
1887.888816
1741.30036
1013.455687
629.6386079
837.026722
3319.619366
238.7845398
1 34.4602267
198.9868927
1390.559251
642.9428121
2151.826296
567.8746243
689.2591397
602.8045739
87.38351916
18.77528662
331 .0333457
176.2219119
438.6108469
2391 .050549
42.82909296
1494.993897
848.1642006
963.9837523
2076.58944
^^M
75.02170913
528.7209538
54.23327713
1689.370059
6366.345256
49.15582286
CH4
16173.81507
0
7823.234665
5492.807568
77777.2745
32485.16242
711.6371986
787.3942819
27.46844888
38077.67377
9118.484074
o
641 .88598
62153.0847
7959.857516
10339.46116
33470.56914
6172.059787
61771.87603
555.4967245
3140.020372
2038.600652
12478.4203
16540.68454
1 6604.67203
28819.50507
4223.364653
5860.008975
874.3503528
1 44.34921 74
4857.858138
32009.97897
35773.78547
20815.39471
886.8994862
18085.00728
31785.45371
16587.77181
15865.46141
^^1
7359.763421
10570.43771
76.69157493
29676.48091
86028.73622
2998.475671
CL2
71.79651472
0
0.687548772
33.22509688
97.07932579
2.288776511
0.757144273
2.751953486
0.531003683
3.062057297
4.87471 0856
o
3.85642423
253.1540973
56.10332979
36.55036344
5.645177316
52.88756439
289.8269373
9.30995613
25.34835075
1 .277495804
23.14600309
159.1527322
62.66345742
239.7110836
0
29.9536781
1.090081061
0.018498968
9.854490933
0.317312645
68.74175333
95.85713202
0.357511667
1 27.6573536
3.175943517
5.249870197
77.39841136
0
0.777504425
50.92382048
0
1 47.7257704
461.3795104
0.077798944
CO
166360.6916
0.025500169
24972.65679
65257.08093
132598.6826
24521 .2828
4010.006377
10442.70625
339.8968515
105548.1263
94664.14034
0
27534.67283
96753.44559
350905.1693
35877.36255
36017.59164
46891 .9764
144333.5041
16202.90849
107879.6067
21384.32344
94816.61636
32000.04083
51373.04439
78445.89764
25091 .43957
8994.70081 8
24197.01616
4019.670688
16911.8381
30360.98957
78879.81986
63879.4993
5796.529037
229806.4172
52706.33945
51227.95284
103193.0958
0
2940.300971
46599.84121
8161.494618
107502.4818
258661 .0554
2480.922619
ETH
1846.208814
0.000411013
272.6613398
1464.276482
2774.20864
392.4195469
111.1162897
86.92013626
0.007938604
2244.334754
1096.015131
0
89.9882235
2301 .48973
1594.308457
1502.651473
279.7946793
1421.201093
3005.125723
217.6329898
241 .2663099
324.4892296
1812.148216
951.5010025
1152.726104
604.5705796
355.3929798
154.928655
307.805554
44.49590327
255.1975721
557.4266837
698.321575
2758.714099
72.6027886
1256.036878
551.215285
534.8401647
1317.44746
0
105.3881583
513.2746875
39.80653137
2295.798169
7638.048839
56.35553164
ETHA
1835.361121
1.18E-05
258.3081144
1 822.970539
3013.262072
2637.939182
54.51347781
149.399925
0.174718359
1335.900212
1 529.330857
0
143.2418616
2857.492222
656.1519566
1194.685727
791 .8456871
1096.431824
941 3.526258
264.31 95242
129.0911604
248.7044298
1 759.498965
349.5076057
2585.167979
420.5940983
766.1432098
190.0442767
69.22669863
23.14439279
254.2792763
4898.321905
760.1623684
1557.401167
110.4438788
1226.116417
10006.31109
1188.641802
2323.530239
0
87.6894985
780.4931112
7.352272183
1 706.790425
721 8.543243
188.9474135
Table B-3b. Point Source Electricity Generating Unit (ECU) Emissions Not Matched to ptipm Sector—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq 1 5mar201 0) |
State
UT
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
ALD2
75.90111014
3.923742932
0
294.861 4349
1 51 .3797804
60.9017407
452.9146744
122.2629823
9,740
ALDX
67.19131659
7.412854313
0
385.0781034
163.1184001
83.50525597
435.1829105
165.2898945
11,204
BENZENE
167.8328827
15.20269673
0
3002.614113
519.7275211
477.9960841
1483.437671
442.7954165
49,017
CH4
16189.49636
30.60303687
0
17362.26967
21262.96145
12603.41801
12146.05639
9729.943582
864,966
CL2
1526.659529
0
0
32.73116523
23.50419753
25.85802558
42.70010986
5.27403715
4,173
CO
49128.53847
2124.087386
0
74566.38984
56459.51235
74245.47203
55319.05698
19240.18824
3,221 ,626
ETH
183.0210333
24.30290199
0
1046.292272
469.5529583
988.7948039
832.621777
891.114972
49,736
ETHA
559.721 0042
3.710903626
0
1378.515034
664.4132161
1948.776034
811.4973371
1780.197347
75,058
-------
SMOKE (2007aq 1 5mar201 0) |
State
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
ETOH
610.6479853
0
147.2556517
781 .3427262
840.3249742
245.7906778
10.56119293
19.2101666
0.703418422
1049.078355
566.0986072
0
79.96446581
9332.696604
2519.725999
3018.62812
600.4814902
15631.32309
430.1859973
113.470786
234.53457
150.3999624
637.6305275
1206.270397
782.9759892
508.1375959
158.9232068
205.4780882
62.12582483
41 .99547955
77.13730955
11.65475048
266.435444
1714.547554
8.442490015
832.4638807
94.73382721
388.4031805
463.8966361
FORM
708.4186498
0.00031841
318.9603334
444.7941449
1935.078607
1035.174265
58.9133541
62.46230746
4.030231344
931.1860803
1272.520675
o
63.65892709
2077.993317
1029.884557
567.2185386
3211.783021
588.5535466
2644.489115
212.6304543
419.8282999
390.4663869
868.1181692
693.0811925
1426.425866
694.5870608
458.7122185
304.2465117
217.141843
27.26586269
460.5840119
1084.457662
543.7631531
863.4871752
84.06463682
666.620247
8114.898654
329.3886813
886.7894063
HCL
1717.426584
0
40.88520874
1336.913175
1097.24025
1 74.2225055
328.587193
149.2150212
0
2378.419652
1209.348895
o
21.14815039
2343.5245
1133.445243
1259.244953
307.7360968
485.6455884
972.7093222
376.7767803
625.1479664
393.7931229
2083.032064
1567.547302
602.261945
1122.692853
63.41165593
36.29953235
13.22333065
44.403681 03
248.7058825
15.34691561
1520.148077
1153.400076
1 .685079089
3001 .973347
187.0661427
412.3725732
1908.660091
HGIIGAS
0.183279495
2.91 E-10
0.015468946
0.284691446
0.658573663
0.044519445
0.097813564
0.014698524
2.24E-07
0.290095415
0.142289693
o
0.110198079
0.499956178
0.949257458
0.069476663
0.239950269
0.114055918
0.374834637
0.027397748
0.191271388
0.081690987
0.225108531
0.730327541
0.07880036
0.511952397
0.011606154
1.447796414
0.010507932
0.014953489
0.225367763
0.001038285
0.611712238
0.109602291
0.002125595
3.847102539
0.020707191
0.137946025
0.448777022
HGNRVA
0.98158721
5.62E-10
0.040484848
0.4085704
1 .23561 7242
0.305428089
0.047070752
0.147401837
3.73E-07
0.390381769
0.236186292
o
0.185670364
1.22667147
0.84227524
0.187832115
0.131548089
0.094396159
0.982477188
0.033954089
0.151401874
0.096133861
0.771294791
0.635614064
0.043271662
0.474377678
0.054819819
0.619702361
2.398584855
0.019120974
0.372593882
0.006337243
0.557232181
0.375437545
0.00656443
2.240002704
0.04743373
0.72912606
0.855156152
MONO
2.514161632
0.000244792
14.73279979
1 .5682536
31.10359783
15.99130241
2.841925164
0.084256995
5.20E-05
38.09434944
32.39712583
o
1 .364724675
80.89570947
4.610997691
1 .438487645
0.72795945
12.01202112
4.880863242
0.800475096
7.339516681
9.397927501
14.68222482
14.60957637
1.145494542
16.50331441
1 .225479886
1.634491551
13.61198153
1 .39021 5799
10.85635951
2.778591974
22.3311027
13.14503578
0.634013292
9.701353528
3.022886335
5.643970326
17.16058171
IDLE
239.1680242
5.46E-05
47.29878306
151.4065947
435.9536153
716.749226
51 .591 40072
1 4.8360308
0.041140235
239.5513573
144.1685633
• o
11.11510097
341 .0236585
217.7508432
193.3638288
126.1100777
124.6943451
379.2340179
27.16355677
46.92876313
42.67556688
170.4573818
145.8797035
167.5310722
156.8213174
23.48364423
19.31118049
27.76496641
7.391616406
88.25485237
125.3019785
96.22971726
193.3517104
17.55601773
154.4033166
152.229781
77.31879177
194.8165324
Puerto
Rico
Rl
SC
SD
TN
TX
Tribal
Data
22.35504079
220.8915904
45.24829815
9929.060289
1099.593469
32.52665791
33.08272174
287.3191603
44.66990819
1001.210154
12434.49518
154.8057359
3.563251472
1550.089032
1.544116578
2478.676427
3449.874881
0.015551687
0.287028716
0.00578118
0.429772264
1.208488057
0.025927593
0.418771914
0.009692801
0.771524571
2.618687818
2.066043133
2.104090103
0.525885999
11.57144316
47.2586522
0.000101528
0.000570592
6.506683518
110.7809715
20.69068289
289.1363016
1122.529993
4.685865557
Table B-3bi. Point Source Electricity Generating Unit (ECU) Emissions Not Matched to ptipm Sector—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
UT
Virgin
Islands
TOTAL
49.58098805
63.94611022
0
1007.230826
232.2623887
176.1324548
711.7310993
97.97939252
57,532
FORM
235.3621832
15.75256394
0
793.5673674
260.3618442
705.6411008
464.3326513
258.7829979
52,391
1649.202655
2.031480136
0
4820.167918
1131.869913
1385.999363
1313.993084
525.9246637
48,647
HGIIGAS
0.838115714
0.000200895
0
0.478379926
0.027574528
0.064713124
0.24339496
0.051208011
16
HGNRVA
0.445252399
0.00056054
0
0.74196076
0.090233781
0.217618122
0.381430049
0.110147665
24
MONO
6.847148818
0.392475173
0
13.35318161
11.72084675
0.289380481
4.228664539
0.252618967
513
45.60626541
3.446706904
0
229.704454
129.3244434
84.59727477
105.6709707
83.43194454
7,605
-------
SMOKE (2007aq 1 5mar201 0) |
State
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
ISOP
69.22775224
0
2.541561497
60.24290015
25.30209433
16.38343064
1 .533730667
1.188036755
0
58.44315223
47.56346438
0
1.404211738
83.05576395
37.86846737
39.89233645
14.17645046
14.52178067
57.42218334
9.440328673
6.04264549
2.277022178
37.63716225
12.19024493
34.418776
34.471 04542
2.23508406
2.141539297
3.255447015
1 .005799282
4.020731917
1.531978219
13.64479025
62.03872954
2.495567714
34.08784897
14.77411441
21.66222126
20.49423441
MEOH
296.4480374
4.07E-05
72.67923698
428.353848
458.1183648
165.9267188
37.00577589
1 6.84274057
0.003296714
341 .0038429
498.4268161
o
7.480700056
401.6615619
309.0664118
511.9682993
149.3756938
1050.457125
268.5457277
39.64247204
54.92340901
183.0330158
334.7333547
326.4920791
302.7003454
254.667791
21.21294686
1 31 .4079435
26.70188065
6.420925214
428.488986
503.3341601
137.0678431
549.2066893
1 2.78652888
280.7849319
123.8895123
59.54333725
179.8443211
NH3
2393.799506
0
1 39.6477783
2011.135653
11778.42156
1 22.6349063
148.6133016
173.9971086
4.24544991 4
2475.813886
5573.364938
o
1236.42227
1237.801661
1185.169761
1071.956661
60178.8902
983.1234295
5568.556379
642.5696086
1 48.4049488
379.1372518
1154.605456
27509.02696
1249.051222
1345.797957
212.9229813
1486.981675
360.9324881
51 .76030909
462.9791751
28.03822704
2049.607417
1821.07886
153.1987301
5743.157949
3110.444545
772.5458873
1 854.968648
NO
67336.96554
0.027539665
14375.45469
33726.47139
81587.30102
18870.63952
5235.776857
5010.058893
450.6975073
48384.81207
47964.15944
o
9318.073816
87736.36347
66261 .36687
35366.5767
63705.35818
31886.67852
148545.8514
16472.57094
22151.75384
16579.9205
84706.40457
57986.96573
48569.35883
34741.19469
4811.78914
10937.71634
15462.16354
2914.164389
18531.26184
39531 .25702
49604.7998
40037.2453
6790.045293
64530.67307
66102.27136
20627.978
80275.87651
NO2
7479.370635
0.00281527
1582.540822
3745.816308
9034.164545
2080.745888
578.9115909
556.5880536
50.07745631
5337.995886
5296.954147
o
1033.97736
9667.611742
7357.752103
3928.182551
7077.645202
3530.952714
16500.2422
1829.485054
2453.9659
1832.822487
9397.129835
6428.400314
5395.451805
3843.635333
533.4178883
1213.666827
1 704.403956
322.4058026
2048.170585
4389.5791 75
5489.31264
4435.436893
753.8156403
7160.375136
7341 .668677
2286.352859
8902.389895
NOX
74818.85034
0.030599726
15972.72831
37473.85595
90652.56916
20967.37671
5817.530373
5566.731204
500.7750157
53760.9023
53293.51071
o
10353.4159
97484.87092
73623.72997
39296.19774
70783.73134
35429.64326
165050.9745
1 8302.85646
24613.05926
18422.14091
94118.21663
64429.97562
53965.95613
38601 .33334
5346.432508
12153.01766
17180.17948
3237.960408
20590.28879
43923.61479
55116.44354
44485.82723
7544.494946
71700.74955
73446.96293
22919.97483
891 95.42698
NVOL
57.7080079
°
3.265972013
48.83933481
37.61611531
13.46565433
2.816518798
1 .207680702
0
56.38513302
44.35978277
o
1.237873149
83.01005139
38.05165492
39.06162483
13.62654809
26.43735416
36.5240589
16.52581346
6.223676979
9.489633393
38.4807219
12.45035979
99.21709016
36.88029349
2.169998545
2.116358644
3.169910905
0.934449968
14.23256684
1.514639554
16.97165529
151.55541
2.393376732
39.81452296
13.64999362
1 4.2707769
25.51858992
Puerto
Rico
Rl
SC
SD
TN
TX
Tribal
Data
0.599464441
33.64692571
1.503118039
93.51802464
94.79574649
0.76951067
10.05603153
237.4716936
138.3765702
500.4802222
653.5001103
2.939524441
15.50728462
1559.827683
228.1729493
1740.914102
3643.969484
1945.693851
26161.83684
4531.35251
54307.76275
263496.4773
214.1220809
2904.767411
502.9570842
6022.626104
29230.06782
1331.943332
2161.881976
29068.70834
5034.83548
60341.9603
292773.8038
13319.43401
12.37240609
168.2459748
1.399059436
117.666087
86.4590063
0.738248751
Table B-3bii. Point Source Electricity Generating Unit (ECU) Emissions Not Matched to ptipm Sector—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
UT
Virgin
Islands
WA
Wl
TOTAL
6.321023856
0.200549709
0
43.87760353
21.79776517
9.194492766
28.14129949
'91
1,211
MEOH
67.61520263
9.320268391
0
361.3506908
96.20353776
84.16462265
278.5907016
315.0712695
11,725
437.1663527
20.45522468
0
1957.175942
809.7157858
745.4146811
484.4388425
469.3347542
158,933
17515.38617
718.730274
0
54078.58657
22882.07825
33220.88566
36616.04358
27464.31333
2,022,055
1939.304487
79.46642041
0
5995.380749
2530.733639
3690.919365
4064.223133
3051.341162
224,159
19461.53781
798.5891696
0
60087.3205
25424.53273
36912.09441
40684.49537
30515.90711
2,246,727
6.723019197
0.193069433
0
63.84382857
19.97421803
9.185034343
26.74762136
25.06372007
1,550
-------
SMOKE (2007aq 1 5mar201 0) |
State
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Puerto
Rico
Rl
SC
SD
TN
TX
Tribal
Data
OLE
1594.647908
0.000223118
528.6518535
2290.614619
3527.907544
836.5396328
131.3069903
162.3693978
0.753197789
2775.511291
1995.823229
0
89.58579828
4105.239461
2818.925701
1541.095922
717.2504884
1201.519952
3353.16226
226.7534485
454.1074263
446.8576334
2369.120968
1016.762467
2575.783089
1066.83109
413.2246489
221 .0735534
229.4598323
39.07480203
430.2889512
767.79595
870.1507917
2468.141986
61.18400489
1805.260129
1252.643362
631.4871692
2553.567524
0
101.5202937
902.7766739
52.202135
3415.415224
7311.733627
25.74933633
PAR
20380.55806
0.000998611
2890.890144
16939.23619
30029.03105
20393.14202
1629.892506
3295.416475
44.03156181
17425.00952
17146.18674
o
879.3009633
31874.65918
26049.16022
14793.98106
14145.2129
1 7226.2708
49978.95661
2484.684489
2570.038432
4479.265095
20546.90915
14418.94414
21286.44852
13170.06192
3729.605369
3610.111951
1615.204475
500.0560027
6632.23467
5534.998946
6944.860685
29858.84171
585.2387371
1 8006.0246
28995.20683
8000.543046
18609.78679
^^H
859.0724372
10559.93694
1683.302391
35857.05901
90749.04621
554.1133982
PEC
1000.909019
0.000826919
418.624885
647.201139
2995.325701
602.0679647
58.46067539
417.5331769
47.77477835
2114.977108
997.3983384
o
122.2613623
1142.128077
1 224.826085
319.1893635
495.8201949
598.8300465
4562.587398
282.3360122
461.2512674
385.1330522
949.3447771
1249.252102
1004.52992
432.0387603
247.6196079
160.461378
484.457444
72.17737264
425.4867081
192.9189039
507.9762801
1089.033828
207.3413889
968.1834659
534.5468262
630.6816063
1444.485251
^^1
44.26642592
309.9189366
86.9181835
2037.535506
4743.524754
82.45828458
PHGI
0.125257252
1.50E-10
0.010961586
0.137104857
0.388354029
0.042026764
0.035591165
0.005776219
1 .49E-07
0.132677624
0.093560134
o
0.073588618
0.276698083
0.391659783
0.050093355
0.086478778
0.046258415
0.173369588
0.014594204
0.071597491
0.028887562
0.167437832
0.284530079
0.029389936
0.202974366
0.009689671
0.506221113
0.009313547
0.008462956
0.110254678
0.00096311
0.250597684
0.077392208
0.001274131
1 .424870671
0.013632709
0.122306002
0.22885202
^^H
0.010368232
0.133542056
0.003856836
0.260890667
0.614725221
9.28E-05
PM10
26156.1812
0.0010985
6818.410769
15325.13515
37952.33581
13872.29823
301.8901123
2584.401349
266.9183884
31338.02366
17273.05062
o
3146.108096
25051.15031
27065.13948
11009.44465
12783.13055
15955.77259
48264.27384
5455.64816
9898.7311
3202.961195
20497.25798
21102.79439
17937.08204
1 2440.0932
6325.364646
3607.714441
6959.697574
660.2450338
3256.769379
1856.617368
7114.493928
16715.67446
652.8215596
1 7864.09445
10405.5151
12295.53695
23495.51962
°
396.2679125
7471.321095
4103.704049
29763.48761
47781.00417
4053.154602
PM25
1 9859.52725
0.001072132
3937.65853
1 0862.39989
21476.36938
7041.124773
223.7095925
2224.356384
171.812091
25191.55222
1 2958.60509
o
2071.270818
1 5676.65367
15536.37178
5796.681482
7626.40099
1 0436.69768
39574.32207
3780.280779
6764.231629
2242.187454
1 2902.94939
1 0643.77785
10594.01239
6944.761583
2728.075475
1855.590245
4092.906285
571.5046618
2596.635254
1455.497108
4998.145463
1 2659.64853
563.7664199
1 2880.04482
6243.477905
8849.742507
1 4763.65427
•
255.0922219
4778.918478
2872.834139
23026.92846
37546.53001
1567.375643
PMC
6296.653954
2.64E-05
2880.752239
4462.735267
16475.96643
6831.173456
78.18051974
360.0449647
95.10629739
6146.471435
431 4.44553
• o
1074.837278
9374.496648
11528.76771
5212.763164
5156.729565
5519.074913
8689.951769
1675.367381
3134.499471
960.7737412
7594.308581
10459.01654
7343.069646
5495.331621
3597.289171
1752.124196
2866.79129
88.74037203
660.1341252
401.1202605
2116.348465
4056.025931
89.05513969
4984.049633
4162.037199
3445.794442
8731 .865346
•
141.1756906
2692.402617
1230.869911
6736.559152
10234.47416
2485.778959
Table B-3biii. Point Source Electricity Generating Unit (ECU) Emissions Not Matched to ptipm Sector—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
UT
Virgin
Islands
TOTAL
325.2454995
22.94697304
0
2129.505348
986.5291815
621.579899
1456.763315
740.7415681
65,663
3776.002037
567.0231699
0
23487.57987
7512.552306
6914.911791
16971.01284
6902.499604
703,094
257.6823268
47.45806037
0
859.6206649
661.1631494
273.5558273
524.3053051
208.8600256
39,632
0.303337577
0.000137801
0
0.275491019
0.018550056
0.031471493
0.149644152
0.03566735
7
7942.296725
465.3744947
0
14764.18221
6223.228375
7912.116467
12089.13279
13630.96971
653,505
3593.562301
337.3885275
0
11500.23891
4617.042091
5151.178424
7967.684937
10294.64403
442,306
4348.734424
127.9859673
0
3263.943301
1606.186284
2760.938042
4121.447848
3336.325677
211,199
-------
SMOKE (2007aq 1 5mar201 0) |
State
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
PMFINE
12739.55331
5.26E-05
2940.201938
5551 .707895
12549.06698
5528.935746
99.87639743
1021.381228
71 .37397455
15667.1793
7422.178259
0
1523.579429
10772.68056
9772.056434
4156.269631
5017.198384
7547.949025
20442.36226
1759.762253
4672.177014
1140.537876
8030.582688
6609.260908
5708.497626
5097.062296
1601.25751
1366.998346
2729.548658
300.9841648
1405.358126
1002.721539
3259.038459
7364.296758
179.7011994
8050.735488
3576.981278
3949.515419
8594.284725
PNO3
141.1576503
1.18E-06
58.26679575
197.4277011
210.7098776
59.50318369
1.316843312
22.29446353
2.597031146
123.5302138
156.7642842
o
5.868781781
150.4432697
115.136802
55.87546708
88.4369498
71 .39692885
428.9115713
13.29218803
47.72452598
11.47355071
118.4142399
67.91373303
93.84657407
128.9447181
17.55732337
1 0.86950997
83.1314055
1 .597563452
1 8.94934594
9.499179109
47.3981 9926
54.89584726
10.04592018
117.8362834
81 .65237928
43.45812155
175.7029111
POC
2748.830182
0.000188281
281 .2495473
1592.079852
3433.746637
519.3606015
31.5860141
537.8839429
32.7487464
4397.603397
2352.513324
o
220.031 3442
1 494.637798
1990.747194
567.4484509
852.9988363
1195.3561
7077.647418
590.1938114
661 .859375
289.7806298
1596.177653
1417.82944
2259.029861
529.9858205
527.0462952
183.3281624
41 3.9342365
76.45283255
367.9977027
128.1885319
517.8021593
2059.504957
124.3246611
1612.852873
665.3583039
2423.164364
1748.650225
PSO4
3229.077085
3.11E-06
239.3153645
2873.9833
2287.520182
331 .2572777
32.46966231
225.2635731
17.31756059
2888.262203
2029.750888
o
199.5299005
2116.763957
2433.605261
697.8985699
1171.946625
1023.165582
7062.813417
1134.696514
921.2194471
415.2623447
2208.430036
1299.521667
1528.108411
756.7299877
334.5947383
133.9328485
381 .8345406
120.2927284
378.843371
122.1689544
665.9303653
2091.91714
42.35325022
2130.436708
1384.939117
1802.922996
2800.53116
S02
70344.02951
0.002040003
23965.43875
13065.80054
33086.45234
1548.798434
1830.560821
34858.55522
684.51 76955
57472.12198
56113.06644
o
17149.64928
156125.5842
95197.62759
61228.15269
13141.8412
25810.49496
165733.4647
18512.34035
34985.09298
19614.91154
76487.32904
25165.78288
29877.91966
78299.10383
11051.47942
6428.660996
2252.858519
3244.726623
7637.97443
7830.395947
58557.56388
66092.16184
9457.691128
118467.5665
40459.46012
9823.707311
85401 .49747
SULF
148.5486892
0
37.25629579
72.85225704
6.099266743
0.765233316
15.99067767
162.5342723
14.89422404
204.6627297
633.9950167
o
48.29359326
1573.61446
783.8282919
990.9073362
15.37197762
1 51 .2565889
64.42160067
214.6937875
484.1372734
263.5428961
767.8113357
231 .4743396
84.28485039
294.0128011
9.699105431
10.96728334
1 .40851 5434
43.46385908
13.2082116
0.083423026
649.6391735
896.2076855
15.71429841
1689.099302
90.55924426
38.62110447
656.5446364
TERP
1451.752804
o
27.05411992
1412.815879
664.8339704
54.47777335
4.400573205
8.928389107
1.050866412
519.4966785
3235.406295
o
6.522943408
279.8844351
205.298313
136.8703371
87.64522694
265.4708338
3917.414283
165.6449611
13.41267955
47.27497722
1560.800192
453.1511074
1 587.45964
158.7265504
459.549391
30.58477385
15.12801606
2.375166087
49.82968316
29.97298892
167.0340803
2220.36049
4.17912984
263.3956292
604.4980098
3894.541 624
486.4965773
Puerto
Rico
Rl
SC
SD
TN
TX
Tribal
Data
112.8994616
2556.401027
2246.561433
14823.6271
21546.62017
981.3342052
0.682743542
54.48871851
14.86304535
171.3330041
373.1067144
7.808296544
24.56415748
674.6322387
241.1967928
3542.760118
5605.162181
432.0905487
72.6794333
1183.477557
283.2946834
2451.672735
5278.116196
63.68430805
2738.856728
31495.0083
1698.264574
78204.91299
223554.2156
1510.949117
39.79992396
250.4082484
0
1278.398914
1570.905426
0.212645368
6.70360121
1243.512901
10.40203273
423.7030946
4093.526884
236.6779578
Table B-3biv. Point Source Electricity Generating Unit (ECU) Emissions Not Matched to ptipm Sector—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
UT
Virgin
Islands
WA
Wl
TOTAL
PMFINE
2703.776012
166.2209475
0
6973.972118
2260.545316
3643.146602
5008.829679
3441.395147
270,688
24.04863572
0.2107474
0
69.84325645
39.61162122
60.30327232
42.44683587
134.6557226
4,037
269.2464411
90.85486356
0
1924.557993
893.2561776
464.5171128
1111.008893
826.7732412
63,621
338.8088863
32.64390857
0
1672.244874
762.4658266
709.6556093
1281.094225
682.9598923
64,327
9131.372498
902.1865644
0
69426.92153
24210.98267
48313.67927
66805.12443
22320.82005
2,117,318
72.85747472
13.53169689
0
721.728742
40.52943865
533.2254122
1224.83311
237.7116372
17,365
45.03124531
3.603927144
0
1025.85508
272.2942652
81.0762887
649.204349
80.42172972
32,666
-------
SMOKE (2007aq 15mar2010)
GA
HI
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Puerto
Rico
Rl
SC
SD
TN
TX
Tribal
Data
3528.287356
5.00E-05
1118.255988
4455.24063
7446.77909
1866.346606
301.9688771
301.6299692
7.493963758
6317.739179
5594.815332
°
224.775996
6411.892768
9465.837489
4266.568795
2660.348497
7359.264872
5065.780911
497.2328788
791.6136294
I73.3385372
6764.337604
3782.891994
6028.714969
520.948115
547.6592651
886.3645311
293.4563007
177.9631802
2505.374188
.850402
1732.967671
9305.942958
59.12089309
5200.175611
1669.905608
1947.854275
5434.310198
'
263.2233909
2724.453637
766.2451874
12727.47739
10435.61328
0
0.028399707
8.31 E-09
0.003365996
1.43E-05
0
0.07527411
0
0.420636093
0
7961.104314
0.000186802
569.9221334
7625.168577
7380.768484
3034.616581
273.2134967
820.5962049
12.5336489
6572.313659
6164.597954
0
425.744222
9180.122621
6920.358438
4428.64047
3162.591139
4687.915363
17350.18967
1043.329205
770.0120262
905.
5596.260329
3011.464102
7832.403253
3254.429556
2113.63071
1700.47057
538.3841224
109.3563559
1396.170761
1830.389737
1838.498509
9418.029012
191.6193193
6628.508192
11580.47188
3665.292334
8049.505673
'
259.9321014
3253.871272
272.1393341
11687.47644
27632.00954
3735.000811
6.45E-05
502.4113426
3188.728319
3498.141733
1127.447081
118.4108614
179.6738153
11.96430912
2273.608782
3203.53811
0
131.94697
3874.973075
5414.713142
2214.734941
1324.818875
4405.057803
3290.109931
379.0406228
254.0928373
564.5061921
4462.944897
1883.420442
4603.815777
2831.765763
244.5526324
370.258324
126.6974735
67.00020701
1309.414993
857.3992735
880.5345936
5444.580597
40.46868653
3733.400028
734.5855899
1390.692718
2778.369731
•
95.77433985
1687.813716
354.2003232
8650.343523
4984.927914
30.07067275
Table B-3bv. Point Source Electricity Generating Unit (ECU) Emissions Not Matched to ptipm Sector—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
UT
Virgin
Islands
TOTAL
603.4015368
263.806639
0
6018.32532
1816.934197
1339.611275
5644.920483
1678,
165,110
0.011501668
0
1073.939748
75.44677694
0
9461.096057
2392.90891
2811.387568
5369.751182
2566.305973
225,148
352.5018439
131.9088458
0
3232.484949
946.977416
769.2526327
3688.745887
769.8624757
97,148
-------
SMOKE (2007aq 15mar2010)
State MONO
-0.1%
-244029345.2%
0.0%
-7561434000000000
00000000000000000
0000000000000.0%
0.10%
0.01%
0.01%
0.02%
0.02%
Tribal
Data
Table B-3bvi. Point Source
Change between EMF and
Electricity Generating
SMOKE Calculations
0.0% -0.1%
Unit (EGU) Emissions Not Matched to ptipm Sector—Percent
-------
SMOKE (2007aq 15mar2010)
UT
Virgin
Islands
MONO
0.04%
0.05%
0.0%
-------
SMOKE (2007aq 15mar2010)
AL
AZ
AR
CA
CO
CT
DE
DC
FL
GA
CHLORINE
0.0%
-422634916.9%
0.0%
-1566000000000
00000000000000
00000000000000
00.0%
0.0%
-3275000000000000000000000
00000000000000000.0%
HG ALL
0.0%
-3797957943.5%
bfam / voc
7.8%
-55136148900000
000000000000000
000000000000000
00.0%
-25000000000000
000000000000000
00000000000.0%
-2597124050000000000000000
00000000000000000000.0%
-1078595090000000000000000
00000000000000000.0%
0.0%
Table B-3bvii. Point Source Electricity Generating Unit (EGU) Emissions Not Matched to ptipm Sector—Percent
Change between EMF and SMOKE Calculations
-------
SMOKE (2007aq 15mar2010)
SD
Virgin
Islands
0.0%
CHLORINE
0.0%
0.0%
HG ALL
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
bfam / voc
8.2%
4.7%
13.9%
17.5%
9.3%
4.0%
TOTAL
-------
Table B-4a: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—EMF: Criteria Air Pollutants and
Hazardous Air Pollutants
-------
Wl
TOTAL
45,056
834,296
33,600,784
744
7,356
397,094
4,699
81,275
3,363,355
3,982
68,877
2,850,301
10,666
195,712
7,910,324
-------
SMOKE (2007aq 1 5mar201 0) I
State
AL
AZ
AR
CA
CO
CT
DE
FL
GA
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VT
VA
WA
WV
ALD2
14911.28574
2717.845926
14980.17601
40141.28
701.8173809
4.864712419
18.82399243
22635.32211
27310.58008
150630.8819
531.1668012
236.5483243
127.7645185
ALDX
8331 .603694
1519.552239
8584.183596
23047.81404
393.5830014
2.725279521
10.53959153
1 2984.75222
15220.69448
87584.3475
300.365921
1 31 .7289023
71 .34488057
1765.785537 972.4639237
2655.370166
26655.20611
52.14685944
193.5865826
21 .33895366
3590.041974
9726.024083
12343.57073
4640.433103
79298.43179
537.4270912
2171.707288
27.36986119
894.7103036
2389.808358
182.4177796
5530.19268
550.6059602
182.2779793
5626.978411
42513.94643
245.9780586
1.514798459
5672.62728
2700.067548
4603.405333
10103.29598
4728.76979
1 7.9899038
3296.1179
15258.76145
1642.01122
1496.730492
15603.49476
29.41515301
108.2207549
11.91079879
2085.104476
5623.581569
6964.106648
2608.249633
45824.98226
313.448214
1178.811599
15.45578448
520.2883697
1358.192319
1 01 .7322472
3099.756893
322.4595433
102.8249056
3169.976442
24706.90113
138.9353448
0.850162888
3177.318435
1591.2469
2628.057025
5722.501999
2679.001184
10.06423352
1869.421808
8898.15803
933.592052
BENZENE
4758.246455
863.3263477
3908.625276
10288.77195
218.0647019
1.523243171
5.918091403
5849.445948
8873.487277
34142.85626
154.9252867
77.27990935
40.94462754
621.1159008
794.1837716
5615.041047
15.50698304
61 .5492871 2
6.859108675
823.2045112
2333.264614
3665.290007
1417.953026
19126.75474
117.9025688
833.940834
8.0701 53485
202.5593
669.3676158
58.99479874
1724.8464
115.3999453
54.18382617
1690.017057
9688.682404
72.400435
0.46799661
1778.533771
525.3221251
1241.266968
2909.137257
1359.041298
5.689935995
938.8956682
3352.977629
458.3158534
CH4
60913.86069
11109.72025
62760.5186
168506.7343
2877.556629
19.92501904
77.05690901
94933.86425
111281.2426
640344.3073
2196.029529
963.0937743
521.6153565
7109.859819
10942.86687
114079.9661
215.059443
791.2213081
87.08206242
1 5244.57594
41115.02059
50915.84258
19069.38633
335034.72
2291 .676578
8618.509672
112.9999654
3803.922396
9929.989485
743.7829118
22662.88289
2357.560166
751.7714671
23176.27081
180636.6285
1015.781471
6.215695365
23229.94932
11633.89728
19214.19946
41838.24624
19586.65962
73.58139652
13667.68052
65056.04365
6825.660042
CO
915020.7648
1 66844.3353
933831.1063
2505424.286
43164.80155
299.0021167
1156.603432
1411975.069
1 673234.765
9476236.178
32838.3414
1 4485.451 98
7837.158018
107392.8176
1 63834.0349
1 68401 7.895
3218.882457
11883.09187
1308.600387
225695.5093
609709.5133
762032.1982
285808.1217
4969409.057
33875.46406
130908.5877
1690.610364
56290.69729
148207.4688
11180.67076
340023.2629
34796.34965
11251.9362
347063.7071
2673662.296
15196.14346
93.21035599
348625.1548
171313.6351
286294.9649
625247.7155
292685.6665
1104.771091
204152.6631
961692.5016
101859.1988
ETH
17153.26416
3128.482771
17673.28041
47451 .27973
810.3162288
5.610864213
21.69912435
26733.25336
31336.65502
180320.2634
618.3990593
271 .2059447
146.8861889
2002.127292
3081.497111
32124.77097
60.56046142
222.8068914
24.52219165
4292.852697
11577.93621
14337.83556
5369.914164
94345.34086
645.3330715
2426.958783
31 .82064633
1071.17968
2796.271991
209.4482884
6381 .838379
663.8858515
211.6978767
6526.407783
50867.03889
286.0427104
1 .750333736
6541 .523561
3276.089673
5410.693752
11781.59577
5515.578176
20.7204172
3848.801149
18319.69815
1922.097057
ETHA
7814.919543
1425.317134
8051 .835935
21618.5049
369.1749938
2.556271163
9.885990534
12179.50292
14276.78395
82152.81332
281 .7387473
123.5597493
66.92045006
912.1566301
1403.910783
14635.84428
27.59096459
1 01 .5094393
11.17216038
1955.797082
5274.835629
6532.228069
2446.499231
42983.15141
294.0097227
1105.707932
14.49728923
488.0227192
1273.963916
95.42334825
2907.52561
302.4622017
96.44822739
2973.390545
231 74.70354
130.319262
0.797440886
2980.277169
1492.565964
2465.078193
5367.62148
2512.863058
9.44009506
1753.489702
8346.339632
875.6953636
Table B-4b: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria Air Pollutants
and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
State ALD,
Wl
WY
TOTAL
729.6207901
13233.89685
538731.7924
411.5419423
7720.415302
310182.4477
BENZENE
217.0686053
2895.579483
134582.8003
3008.85746
56445.35076
2267799.244
45035.86263
834293.7816
33683203.9
847.2903838
15894.93816
638609.4612
386.0201531
7241.63396
290946.5061
-------
SMOKE (2007aq 15mar2010)
AL
AZ
AR
CA
CO
CT
DE
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VT
VA
WA
WV
231.4589761
42.2144464
238.4758539
640.2877199
10.93408124
0.07571026
0.292795268
360.7273131
422.8436438
2433.165664
8.344421351
3.659546461
1.982027825
27.01586253
41.58042327
433.478204
0.817176017
3.006464848
0.330891657
57.92595573
156.2278151
193.4687141
72.45934564
1273.056498
8.707859672
32.7483825
0.429375624
14.45403681
37.73173257
2.82620751
86.11382823
8.958198703
2.856570796
88.06461694
686.3785192
3.859747342
0.023618144
88.26855714
44.20618211
73.00960344
158.9759432
74.42490576
0.279594499
51.93410035
247.1983147
25.93596091
FORM
11582.03666
2102.117781
9667.841317
25488.80993
531.8301779
3.712860931
14.42087924
14480.60016
21570.94254
85565.05923
379.675779
187.7897584
99.63248808
1501.680338
1942.504428
14177.862
37.94557968
149.8565812
16.68692143
2060.672172
5815.383982
8969.971194
3462.527068
47646.94017
296.4471204
2005.012251
19.76070148
507.6915724
1645.764014
143.4607956
4205.481193
291.5396833
132.5915308
4132.303705
24267.73026
177.3051421
1.141867976
4334.707581
1338.049748
3061.560556
7136.707129
3334.505996
13.85878027
2305.295402
8429.12204
1127.175772
HFLUX
25723956.88
7298532.912
18786211.59
75494571.31
1268041.903
5525.927391
25400.12776
35422859.97
66402142.28
183142774.6
607812.7186
383305.3232
170609.5029
3252902.952
3561956.373
13996428.69
56633.7018
236100.6419
25489.84541
4742526.527
14753264.75
MONO
MEOH
Table B-4bi: Point Source Day—Specific
and Hazardous Air Pollutants
17273802.45
6383108.842
129058682.9
365913.3611
10621315.89
27708.20144
1082627.446
4940912.074
289941.0632
9982546.253
330336.1061
193252.472
9641647.876
37943126.11
250212.0784
1676.580155
8994156.533
1673148.918
5061678.636
12746708.49
12313297.67
23808.26538
3949739.7
12663143.01
1820733.421
Wild Fire and Prescribed
1578.302887
287.8573762
1626.150556
4366.078504
74.55867984
0.516261893
1.996592759
2459.775263
2883.342416
16591.5905
56.90001248
24.95416253
13.51523551
184.2193684
283.5341294
2955.858446
5.57228679
20.50088469
2.256333204
394.9931481
1065.306955
1319.250194
494.0955586
8680.88669
59.37826721
223.3089929
2.927863753
98.56117997
257.2900936
19.27175426
587.2045786
61.08534685
19.47872415
600.5066307
4680.36873
26.31930748
0.161049893
601.8974354
301.4390286
497.8477397
1084.046003
507.4984267
1.906537426
354.1351914
1685.628666
176.8556395
1298.87164
236.8935316
1338.248012
3593.083604
61.35843446
0.424856516
1.643094679
2024.283045
2372.859684
13654.12335
46.82611775
20.53612238
11.12247956
151.6042108
233.3357305
2432.537075
4.585731422
16.87130194
1.856866606
325.0614606
876.6991571
1085.682949
406.6181379
7143.974739
48.86560599
183.7732109
2.409511748
81.11135549
211.7380301
15.85968607
483.242591
50.27046433
16.03008121
494.1896199
3851.730647
21.65956307
0.132535961
495.3343057
248.0706337
409.7060241
892.1205436
417.6480586
1.5689742
291.4371878
1387.195657
145.5441318
Fire Emissions—SMOKE: Criteria Air Pollutants
-------
SMOKE (2007aq 15mar2010)
Wl 11.43299319
WY 214.4796106
TOTAL 8617.128011
FORM
531.147742
7282.45173
334177.3123
HFLUX
1070574.284
15858116.94
759918964.1
MONO
77.9607231
1462.521992
58759.61234
64.15815722
1203.589083
48356.48699
-------
SMOKE (2007aq 15mar2010)
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
Rl
SC
SD
TN
TX
UT
VT
VA
WA
WV
15107.43904
2754.217494
15312.96255
41061.80742
711.9675954
4.933252203
19.08544352
23146.9771
27645.16464
154780.6752
540.4228744
239.3805064
15387.89605
2784.133945
10836.71725
28048.32391
693.2118043
4.869218539
18.95683383
16079.96132
29029.77854
81667.48774
470.9777986
253.7246235
129.4179791 132.8520068
1780.035446 2127.136013
2698.578255 2458.556813
27455.98273
53.00929755
196.1681418
21.61194277
3687.469654
9973.923484
12548.54958
4711.261341
81303.56327
552.8419553
2178.333263
27.83326047
919.39606
2435.764754
184.6954125
5609.150127
12196.28827
47.82942266
198.563571
22.29767913
1994.267381
5959.104849
11287.20442
4455.618383
1709.766393
309.3482108
1204.079762
3116.480687
77.02353954
0.541029133
2.106309011
1786.662507
3225.53122
9074.16722
52.33089068
28.19164473
14.76131905
236.3484763
273.1730373
1355.14323
5.314371732
22.0626194
2.47752663
221.5852965
662.1228515
1254.133862
495.0687265
49105.0519 5456.117841
270.4234797 30.04705875
567.2390499
185.2957724
5717.442662
43677.02905
250.1625078
1.537121866
5752.177659
2787.950249
39.418417
10285.22993
4814.324923
18.2344955
3357.05886
15695.57404
1673.834829
2987.547439
24.74421173
483.7037067
1972.748816
192.5147651
5495.645773
248.4953902
167.022932
5245.709317
23349.70042
221.5762699
1.482769005
5686.833745
1003.36755
3542.618954
8758.017544
4085.17494
18.30771452
2803.016968
7719.322847
1346.451993
331.9495819
2.749360144
53.74484458
219.1943372
21.39055143
610.6273624
27.61058555
18.55810556
582.8565919
2594.411256
24.61958511
0.164754422
631.8704493
111.4852944
393.6243683
973.1131069
453.908354
2.034188925
311.4463475
857.7026232
149.6057833
17097.66244
3093.482156
12040.79702
31164.8046
770.2353439
5.410247672
21.06314284
17866.62383
32255.30976
90741.65496
523.3086893
281.9162683
147.6133259
2363.48449
2731.72985
13551.4315
53.1437944
220.6261904
24.77520576
2215.852677
6621.227701
12541.33828
4950.68711
54561.16974
300.4705385
3319.497021
27.49357188
537.4485513
2191.943154
213.9053166
6106.273136
276.1059758
185.5810376
5828.565909
25944.11168
246.195855
1.647523427
6318.704195
1114.852845
3936.243323
9731.130651
4539.083294
20.34190345
3114.463316
8577.02547
1496.057776
24123.13964
4399.677375
24854.45401
66732.14014
1139.571485
7.890719258
30.51612147
37595.76072
44069.66082
253589.5878
869.6728064
381.4049092
206.5703928 454.4376179
2815.650347 6207.833518
4333.600139 9519.538774
45178.01071 98665.12494
53063.86564
9677.03146
54457.46878
146169.2581
2505.271805
17.35009103
67.10466831
82360.76139
96979.50062
554387.4974
1909.430572
839.422755
85.16795967
313.3398794
34.48628045
6037.164659
16282.39284
20163.71905
7551.868415
132680.623
907.5509701
3413.105633
44.75031064
1506.431373
3932.479682
294.5532664
8974.966985
933.6421428
297.7169741
9178.279507
71535.81155
402.2703019
2.461544944
9199.536795
4607.261786
7609.217574
16568.80467
7756.719767
29.13975662
5412.682182
25763.52905
2703.101593
187.065009
689.2007893
75.87203663
13200.44887
35626.42515
44286.78604
16596.40291
290334.2697
1983.122878
7542.612526
98.27385255
3293.241786
8627.302592
648.1248781
19732.4718
2038.860598
653.9078213
20163.4836
156401.0621
883.3739734
5.410880052
20228.49211
10051.65376
16681.87201
36368.83909
17025.52578
64.08640731
11878.45991
56298.12205
5929.833233
Table B-4bii: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria Air Pollutants
and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
Wl 741.672438
WY 13614.68632
TOTAL 551631.4874
669.7105999
6620.502035
358175.4499
74.41231258
735.611358
39797.27673
744.1229125
7356.11
397972.7267
1191.569362 2617.216776
22353.5177 48843.66906
898095.1707 1966336.388
-------
SMOKE (2007aq 1 5mar201 0) I
State
AL
AZ
AR
CA
CO
CT
DE
^
GA
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VT
VA
WA
WV
PEC
8979.312207
1 506.382666
8731.889198
21157.55097
407.3366292
2.927510045
11.33540535
1 2574.93333
15629.86951
75725.50448
315.6546822
140.9831191
77.21323732
1 073.528754
1571.08846
15088.48458
31 .09398436
116.7023261
12.90315702
1 837.928973
5131.432261
7350.737996
2774.967311
40222.47547
273.9298324
1 205.383699
1 6.29646456
479.4198771
1 285.889793
110.332673
3247.786081
278.5903808
108.6757518
3347.697392
23568.74089
145.6711495
0.909385517
341 3.906886
1326.372114
2683.033376
5985.843471
2505.470018
10.84583619
1 941 .653576
8059.950809
961 .4358383
PM10
97203.19188
17702.4515
94371 .49337
252176.0872
4552.983396
31 .60526358
122.3767615
142388.9087
178632.8181
929571 .931
3407.799985
1548.842799
833.5924294
11727.03587
17109.83871
1 62894.8824
335.6898634
1261.083801
1 39.3020706
22188.42144
60508.58309
79435.03778
3001 3.44766
493703.8824
3301.661837
1 4686.48022
175.9361947
5520.43172
15228.52162
1192.1842
35900.0631
3362.362525
1173.2703
36282.47799
262578.3367
1580.581076
9.81768647
36860.01561
1 6335.63398
29151.10366
64677.20823
30261.71279
117.0913192
21061.90631
93745.0087
1 0456.87825
PM25
82375.58437
15002.0777
79975.84644
213708.5532
3858.46105
26.7841735
103.7091038
120668.581
151383.7548
787772.7843
2887.965782
1312.578445
706.4339724
PMC
14827.60752
2700.373796
14395.64693
38467.53407
694.522346
4.821 090075
18.66765775
21720.32767
27249.06332
141799.1467
519.8342031
236.2643536
127.158457
9938.157127 1788.878746
14499.86245
138046.5137
284.4829262
1068.715042
118.0526669
18803.74669
51278.46028
67317.82862
25435.1321
418393.1193
2798.017674
12446.17338
149.0984759
4678.332221
12905.5285
1010.325845
30423.78561
2849.459687
994.2968965
30747.8668
222524.0158
1339.475437
8.320087413
31237.30653
13843.75623
24704.32642
5481 1 .20791
25645.52033
99.22997011
17849.07441
79468.62639
8861 .762347
2609.976259
24848.36868
51.20693717
192.3687582
21 .2494037
3384.674751
9230.122801
12117.20915
4578.315559
75310.76309
503.6441629
2240.306838
26.83771877
842.0994992
2322.993117
1 81 .8583547
5476.277489
512.9028382
178.9734036
5534.611187
40054.32091
241.105639
1 .497599056
5622.709083
2491 .877752
4446.777247
9866.000327
4616.19246
17.86134912
3212.831909
14276.38231
1595.115901
PMFINE
19736.72958
4464.568253
19066.19249
65632.49779
1013.924335
6.363919377
24.641 2832
32816.32164
42154.31196
257226.4319
686.1806904
328.6201892
167.8487169
2447.111351
3537.956913
32799.85221
67.59314418
254.6572931
28.04931497
5934.683905
15378.55938
16042.6495
6077.763985
136588.4561
880.0900176
4003.348262
35.42579816
1327.044181
3907.973044
240.7010391
7752.044828
898.8067827
236.2510597
7393.74455
57955.36797
323.2106698
1 .976852682
7424.21753
4549.84045
5985.508319
13057.04099
8102.075916
23.57704129
4303.380145
23107.04635
2153.849916
PN03
865.5305275
73.4780024
849.5589249
850.0531103
31 .88998564
0.286590717
1.10968755
890.2549468
1021.616959
1 654.628822
30.90123591
1 2.4245855
7.558843676
98.04026404
146.175063
1 477.09776
3.043967438
11.36459708
1 .2631 63633
59.33816511
239.7176534
715.6652689
268.8314446
881.3790144
9.119435473
32.00438553
1 .595353759
29.22028451
56.69796608
1 0.74785904
274.9221691
9.041827654
1 0.63838677
320.4869368
1 889.377203
1 3.85355869
0.089024951
334.0231 952
26.22177386
253.1413697
583.2018029
80.15006598
1.061760501
1 84.9466673
441 .6948639
90.15034021
POC
52635.54995
8831.210977
51185.07764
124039.2695
2387.855875
17.16062027
66.44642195
73717.06232
91626.95886
443971 .41 53
1850.319631
826.4406504
452.6122373
6292.959714
9209.586836
88446.40006
182.2682095
684.0920819
75.63634176
1 0775.32979
30083.31325
43088.96032
1 6266.47465
235820.3742
1605.980163
7066.964653
95.52739188
2810.531647
7538.649151
646.7540965
19038.62331
1633.306765
637.0407079
1 9623.79246
138162.1575
853.9077132
5.330680071
20011.80503
7776.427933
1 5727.66464
35088.14132
1 4688.971 49
63.57664148
11381.74857
47251.01294
5635.845443
Table B-4biii: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria Air Pollutants
and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
Wl
WY
TOTAL
427.8315013
6767.679461
288625.5825
4697.205696
81274.92551
3371492.103
3980.682929
2857220.431
716.5227664
12397.86988
514271.672
PMFINE
994.7961498
21499.11782
838638.4016
37.85599178
240.493334
15121.94414
2507.938853
I9676.95553
1692061.43
-------
SMOKE (2007aq 1 5mar201 0) I
State
AL
AZ
AR
CA
CO
CT
DE
FL
GA
ID
IL
IN
IA
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Rl
SC
SD
TN
TX
UT
VT
VA
WA
WV
PS04
158.462105
126.4378062
143.1281856
2029.18181
17.45422495
0.045533094
0.176305704
670.0087547
950.9975385
91 94.803845
4.909542343
4.109901123
1 .200937273
26.51704522
35.05517695
234.6790868
0.483620805
1.898744214
0.200689529
196.4658572
445.4377324
119.8155428
47.09470685
4880.434438
28.89822582
138.4723837
0.25346754
32.1162313
116.3185473
1.790177704
110.4092261
29.71393096
1 .690990272
62.14546082
948.3721434
2.832346126
0.014144193
53.35388857
164.8939568
54.97871 665
96.98031755
268.8528441
0.168690653
37.34544752
608.9214299
20.48081029
S02
8286.759535
1503.636309
6803.324712
1 7904.37878
379.8097976
2.653814602
10.30686107
10183.01646
15456.15176
59422.77918
269.7852537
1 34.6248291
71.33441474
1081.681078
1382.954939
9772.8223
27.0100473
107.1844735
11.9500064
1431.98536
4062.690364
6382.122971
2469.18657
33294.77045
205.1117312
1452.629658
14.05815131
352.5012901
1165.663248
102.781516
3003.77082
200.7402853
94.35869738
2942.384816
16870.31564
126.0777279
0.815350342
3097.480702
913.5395937
2160.61686
5065.589272
2366.31692
9.913076076
1634.758283
5837.280343
797.9467956
SULF
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
TERP
2830.334067
516.2079597
2916.138221
7829.587545
1 33.7043544
0.925818271
3.580411348
4411.057858
5170.631329
29753.31673
1 02.0374894
44.7496741 3
24.23658666
330.3563205
508.4552138
5300.672657
9.992654556
36.76372624
4.04624305
708.33206
1910.390322
2365.780847
886.0501259
15567.23304
106.48166
400.45501 03
5.25048711
176.74748
461 .3923909
34.5596655
1053.020303
1 09.5429245
34.93067667
1076.874646
8393.196554
47.19777492
0.288812183
1079.368755
540.5635849
892.7788878
1943.994593
910.0851575
3.418903492
635.0623463
3022.798651
317.1512158
TOL
9155.889384
1669.888667
9433.458423
25328.0472
432.5221067
2.994907755
11.58234666
14269.39573
16726.5513
96249.46946
330.0825998
144.7615177
78.40334186
1068.674605
1 644.8091 6
17147.22334
32.32532688
118.9275229
13.08918838
2291 .39398
6179.949807
7653.099102
2866.296465
50358.67212
344.4591342
1295.437733
16.98492614
571 .7630366
1492.564749
111.7972446
3406.43075
354.36201 85
112.9979061
3483.597411
27151.27369
152.6807933
0.934274928
3491 .665878
1748.677021
2888.063332
6288.65672
2944.04768
11.05990149
2054.372582
9778.49621
1025.956945
UNK
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
UNR
61209.78277
11156.22807
61417.75052
164560.7542
2880.405742
19.96679773
77.26355837
92798.4966
112121.6344
617133.3754
2179.151399
971.1684959
524.4793067
7253.373633
1 0895.54541
109169.6041
213.9619218
794.6398589
87.59916537
14709.19324
39858.51991
50646.00741
1 9043.25961
324984.2316
2201 .499865
8926.804294
112.2943415
3665.602697
9801.991927
748.8795236
22697.63223
2255.022839
747.8964922
23089.28987
174183.9078
1009.199807
6.216816526
23283.02249
11054.72167
18877.1105
41446.28985
1 9398.39837
73.84294888
13520.6404
62505.99857
6734.70485
XYL
2000.777032
364.9099563
2061 .432329
5534.773233
94.51622067
0.654449969
2.531016322
3118.198351
3655.144576
21032.7656
72.13080951
31 .63382023
17.1329505
233.5305107
359.4294184
3747.071 342
7.063865161
25.98845962
2.860317231
500.7233834
1350.464235
1672.382096
626.3531064
11004.55237
75.27239784
283.0833517
3.711620345
124.9436432
326.160522
24.43038254
744.3851 637
77.43640378
24.692721
761 .2479396
5933.191432
33.36435324
0.204154897
763.0109783
382.1269973
631.1096328
1374.219285
643.343617
2.416844864
448.9287167
2136.831213
224.195616
Table B-4biv: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—SMOKE: Criteria Air Pollutants
and Hazardous Air Pollutants
-------
SMOKE (2007aq 15mar2010)
SULF TERP
Wl 12.26043312
WY 692.8094931
TOTAL 22773.07243
378.0787564
5038.103941
234283.7537
139.8051897
2622.706745
105372.2537
452.2577731 0 2993.689648 98.82893081
8484.233148 0 54210.26643 1854.00424
340870.2785 0 2208251.317 74488.15961
-------
SMOKE (2007aq 15mar2010)
Table B-4c: Point Source Day—Specific Wild Fire and Prescribed Fire Emissions—Percent Change between EMF and
SMOKE Calculations
-------
SMOKE (2007aq 15mar2010)
Wl
TOTAL
-0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
-------
48
478929.0826
11580.10221
314
613091.5301
525
24260.87788
332
16059.64714
1,700
464052.1738
873
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
^ampeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\layarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Zacatecas
Canada
Table B-5a: Point Source Emissions from Canada, Mexico, and Offshore Sources—Pre-SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants
321702.2726
15,285
2,120
15,236
19,900
2,345
1,360
4,070
2,2
4403.401102
6841.98
3367.02
11,741
6,891
31135.70618
177.26
9,003
20132.38772
2,359
1,038
10,152
7718.866836
8,683
34,040
6881.533228
8.81
-------
Mexico
TOTAL
US offshore
888,279
1,747,033
89,813
213,641
298,343
837
3,553,108
4,889,733
1,961
-------
Pre-SMOKE (Allan)
FORM
2,312
219007.972
28.19666813 44.52436646 129.8738587 28.49716515 42.78422701 14.28833144
1.495919965 2.710833694 132.7033391 19.29517694 22.3255733 25.22993975
0.483191619 1.30971413 17.49741117 4.286515619 22.53821525 4.227992376
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
^ampeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\layarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Zacatecas
Canada
Table B-5ai: Point Source Emissions from Canada, Mexico, and Offshore Sources—Pre-SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants
0.020877199
0.043603629
12.15761754
0.345719618
0.432447653
0.356084401
5.966728478
0.080082836
19.67166607 12.55102012 26.75744169 0.048475837
13.24816795 2.920694543 0.787005823 0.159306714
11.05055108 8.369048354 6.750405398 0.165419505
121.5095733 80.35978507 49.86584654 1.527611303
0.05 0.03 0.000972601 0.005478435
1.204874379 0.981697707 45.66824211 31.45126041 72.76975527 0.905304192
0.010433534 2.046563472 16.05258161 1.403147182 8.609930803 1.627960776
-------
Pre-SMOKE (Allan)
Mexico
TOTAL
US offshore
546,745
847,335
51,241
141
189
188
253
-------
Pre-SMOKE (Allan)
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\layarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Zacatecas
Canada
4.331484044
MEOH
32.95241587
18.18275263
145.0967523
0.063217252
2.450018782
0.282575234
11.00003604
0.000135112
0.000359731
0.176693058
7.31218E-07
0.020863877
0.02231493
36.45553242
0.18
0.000442583
0.004464963
6.809090242
3.11877758
2.707968425
2.532460981
95.29679901
0.114237551
46
2394.869478
412.1442033
140.3332247
86.05829222
189.0573201
1795.876859
6.71
Table B-5aii: Point Source Emissions from Canada, Mexico, and
Criteria Air Pollutants and Hazardous Air Pollutants
19 199
Offshore Sources—Pre-SMOKE [Canada and Mexico]:
-------
Pre-SMOKE (Allan)
Mexico
TOTAL
US offshore
-------
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\layarit
New Brunswick
Newfoundland
Nova Scotia
15.19219884
55.95125316
610.2578566
40.95696186
Nuevo Leon
Oaxaca
Dntario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Zacatecas
Canada
0.157623646
0.222099897
0.144368236
15.64315055
0.040065593
39
1.114701494
1.255034493
1.896205038
66.05255918
0.29
59.90735843
34.49472367
49.6322821
626.0083492
1.19
1.822331226
2.003681033
2.095318987
29.20836864
0.343533699
Table B-5aiii: Point Source Emissions from Canada, Mexico, and Offshore Sources—Pre-SMOKE
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants
46
[Canada and
-------
Mexico
TOTAL
US offshore
-------
SMOKE (2007aq 15mar2010)
ALD2 ALDX
BENZENE
ETHA ETOH
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\IWTerritories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Table B-5b: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants)
-------
SMOKE (2007aq 15mar2010)
ALD2 ALDX
Canada Total
Mexico Total
TOTAL
US offshore
19
581
601
901
528
1,428
BENZENE
33,877
1,182
35,188
363,989
6,519
412,036
41,528
1,147,801
68,422
1,306,023
89,800
2,014
1,203
3,354
138
ETHA ETOH
51,774
802
58,837
6,262
166
719
885
0
-------
SMOKE (2007aq 15mar2010)
FORM MONO
MEOH
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\IWTerritories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Table B-5bi: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants)
-------
SMOKE (2007aq 15mar2010)
FORM MONO
Canada Total
Mexico Total
TOTAL
US offshore
0 78
0 507
0 585
0 0
1
104
105
MEOH
61
346
407
21,138
0
21,138
775,101
201,782
74,314
86,122
22,420
8,257
861,223
224,202
1,051,197 116,800 1,167,996
82,571
-------
SMOKE (2007aq 15mar2010)
PMFINE
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\IWTerritories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Table B-5bii: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants)
-------
SMOKE (2007aq 15mar2010)
Canada Total
Mexico Total
TOTAL
US offshore
13
168
181
13,945
2,377
16,442
117,254
97,146
215,240
839
PMFINE
53,858
51,512
105,606
98
230
337
235
-------
SMOKE (2007aq 15mar2010)
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\IWTerritories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Table B-5biii: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants)
-------
SMOKE (2007aq 15mar2010)
Canada Total
Mexico Total
TOTAL
US offshore
7,821
12,755
20,611
35
1,762,340
649,810
2,414,111
1,961
0
10,938
10,938
0
1,579
182
1,761
12,050
3,839
15,891
2
-------
o
228
217
-32.2%
0.0%
-1.5%
-168.7%
-43.3%
0.0%
-0.5%
-248.6%
-29.0%
-5.2%
0.0% 0.0% 0.0%
0.0% 0.0% 0.0%
-43.2%
0.0%
-0.1%
-32.9%
0.4% 0.0%
0.0% 0.0%
0.3% -6.8% -26.1%
0.0% 0.0% 0.0%
-0.1% 0.1% 0.0% 0.0% 0.7% 0.1%
SMOKE (2007aq 15mar2010)
State XYL VOC approx VOC
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\IWTerritories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Table B-5biv: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants)
-------
SMOKE (2007aq 15mar2010)
State XYL VOC approx VOC
Canada Total
Mexico Total
TOTAL
US offshore
448,629
65,273
567,301
53,399
-------
SMOKE (2007aq 15mar2010)
FORM
MEOH
-548.2%
88.2%
91.3%
-204.0%
-253.2%
42.2%
-570.0%
-519.8%
93.7%
4.2%
0.0%
0.9%
20.7%
0.0%
0.1%
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\IWTerritories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Table B-5bv: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants)
0.2%
0.2%
-319.7%
0.0%
0.1%
-0.1%
-0.1%
-44.3%
72.5%
0.4%
-0.1%
0.0%
-9.6%
0.0%
0.0%
0.0%
0.0%
-254.4%
0.0%
0.1%
0.0%
-------
SMOKE (2007aq 15mar2010)
Canada Total
Mexico Total
TOTAL
US offshore
FORM
-------
SMOKE (2007aq 15mar2010)
-556.0%
97.7%
98.5%
97.6%
98.9%
-0.1%
96.1%
95.3%
98.8%
97.1%
-0.1%
0.1%
0.1%
-286.7%
90.9%
0.7%
0.0%
0.3%
-538.3%
59.2%
49.5%
0.2%
98.9%
98.2%
98.1%
91.5%
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Gulf of Mexico
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
\IWTerritories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Table B-5bvi: Point Source Emissions from Canada, Mexico, and Offshore Sources—SMOKE [Canada and Mexico]:
Criteria Air Pollutants and Hazardous Air Pollutants)
0.1%
-84.8%
59.2%
0.0%
-315.0%
0.0%
-------
SMOKE (2007aq 15mar2010)
Canada Total
Mexico Total
TOTAL
US offshore
-------
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Daxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Zacatecas
Canada
Mexico
TOTAL
5,735
176,384
24,558
7,697
101,066
19,808
10,510
35,635
Table B-6a: Canada and Mexico
Mexico]: Criteria Air Pollutants
Non-Point and Non-Road Mobile Emission Inventories—Pre-SMOKE [Canada and
and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
BENZENE
3467.369958
712.0590711
97.10210314
2893.158027
»
0
1872.270884
737.5954397
689.8973828
0
3569.77426
452.2696795
68.28209097
2193.791332
o
0
1238.18041
406.8439234
8617.359525
1114.127163
171.6956491
4479.348576
o
0
157697.1231
283.4527343
94.83954871
282950.8699
o
0
389895.1326
42321.26408
3818.642762
479423.8556
0
7641.872569
424.9354966
53.474372
5188.865252
0
1302.95113 2273.465171
803.6664908 478.1093903
478.8355859 480.6300073 1142.104891
0
69410.8608
27293.99643
0
0
25506.55134
0
1047.82168
341.2562403
417.0850115 140.7452688
3362.601028 1697.998173
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Table B-6b: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants
3945.833073
86.23937584
18.09449148
3643.996252
0
291.0979715
88.20408363
1069.780972
241.2220992
1059.807134
816.0393352
0.063364456
0
7535.262204
184.2271552
0
10087.9318
0
0
0.073249592
2011.52945
1468.820723
1543.354272
0
498.0191007
0
749.4557721
167.6426442
796.0026955
610.7832856
0.017498114
o
5673.605732
138.3141371
0
7555.023263
0
0
0.053457714
1953.441484
1003.892219
925.0681163
0
353.1356625
0
2556.25582
571.2321957
2590.188993
1277.865523
0.183538479
o
13565.01984
483.5159468
0
16553.2739
0
0
0.023077967
4106.515401
830.2623539
958.524343
0
498.1152681
0
94779.99641
21009.89269
72411.24491
483.4279526
0.590033724
o
578505.8902
16784.05205
0
627286.7602
0
0
0.122971483
96795.88833
1953.928067
1076.047065
0
212.4532923
0
106637.9963
25882.81139
117666.5609
29719.95284
11.66928245
2853.443549
697.5546033
2624.353359
454.7259782
0.280880583
»
16810.52939
529.1752279
0
19751.25525
0
0
0.043347407
4726.117626
847.6917607
920.1282913
0
234.2419447
0
1485.711424
329.8512872
1227.379739
108.8635496
0.090831414
»
8881.814374
266.625809
0
9879.199514
0
0
0.013360891
2237.097314
232.2436117
150.154687
0
45.20829317
0
-------
SMOKE Totals (2007aq_07c 19apr2010) |
State
Zacatecas
Canada Total
Mexico Total
TOTAL
ALD2
33.36270131
29,963
8,469
38,431
ALDX
23.16608496
24,071
5,561
29,631
BENZENE
9.7087917
56,664
7,448
64,111
CH4
49.88490824
2,041 ,668
8,048
2,049,716
CO
1038.340307
3,747,987
350,557
4,098,544
ETH
18.49236142
64,186
4,760
68,946
ETHA
5.44930246
33,596
1,166
34,762
-------
SMOKE Totals (2007aq_07c 19apr2010)
FORM
MONO
MEOH
4087.80938
2203.382776
171.9553966
4999.672593
0
3456.901477
563.0999993
79.47427811
3170.488616
0
1069.585504
154.2839802
50.98400392
532.3358512
0
1406.253248
747.8305283
65.65546196
772.7212004
0
546.8982008
19.51237486
2.119070054
107.8178348
0
3817.84127
1554.758973
139.1695533
2494.988011
0
0
2853.187876
1904.910475
600.0750745
0
0
1562.675577
493.6061548
0
215.1803266
125.1040833
0
1071.776061
856.7098481
668.2724537 56.27485706 185.4056846
0
39.6710716
16.28272175
0
0
16.28095691
0
2112.461334
1352.995919
566.2611265
0
126605.1111
8692.42862
3964.850749
23173.36898
0
0
42772.59399
26782.40854
40253.50711
0
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Table B-6bi: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants
1679.033816
382.2941924
1670.821081
3088.468907
0.000879159
»
13230.54376
265.3616648
0
11931.85056
0
0
0.020345381
2057.785299
1019.488979
1571.46505
0
1344.400052
0
1206.470697
273.9939548
1166.537881
611.700336
0.092002648
o
8492.535326
201.778348
0
10922.9545
0
0
0.06955035
1995.578316
1399.939845
1588.595103
0
328.3210306
0
76.82104709
20.6298245
93.37606773
141.0891955
0.003527222
o
1395.992678
20.09633433
0
671.0644704
0
0
0.011507127
594.5104174
123.0179143
156.0396911
0
102.2040558
0
273.7552776
54.55006669
219.2876137
769.0711023
0.05081556
o
2636.715076
162.4909982
0
0
0
0
0
26.09163125
4.848493146
30.13926732
15.47516115
7.38E-05
0
304.0050029
54.3699364
0
2060.174394
0
0
0.010421065
817.4940325
480.24941
758.5889091
0
367.724064
0
0
530.721403
100.8372405
631.3550458
2217.546729
0.001929619
»
9228.48591
105.3119705
0
5626.212042
0
0
4217.276992
213.379699
6769.160793
17332.31556
0.001072831
»
106725.1073
2293.0263
0
85727.22077
0
0.017518872 1.638697309
1910.340683 115249.9116
856.9301723 51541.57408
1208.685022 51474.48312
0 0
926.3281981 9840.379834
0 0
-------
SMOKE Totals (2007aq_07c 19apr2010)
FORM
MONO
Zacatecas
Canada Total
Mexico Total
TOTAL
MEOH
12.11411141
25,811
10,947
36,758
1944.027561
537,835
254,600
792,435
-------
SMOKE Totals (2007aq_07c 19apr2010)
138041.9838
22104.59174
6090.198011
74814.42715
0
0
32080.73269
17205.73658
14267.84138
2301.763231
625.6973764
7778.922528
0
0
3349.318386
153379.4107
24560.63895
6766.879392
83125.68553
o
0
35645.23141
1786.649335
19117.49
533.1542795
68.01528848
4.649921642
95.80134142
o
0
110.3246472
58.64858417
11435.14374
710.9780359
105.4058856
5122.886348
0
110222.9289
44351.71567
3556.822221
70613.6672
0
786.3757615 8426.507595 22.27930571
0
1241.469578
572.3162154
0
0
501.6204438
0
55406.26574
40521.23498
7533.453929
1294.012069
252.5650134
4966.582443
0
0
2544.951055
1053.976743
11808.71053 812.2300912
0
0
0
0
0
38223.58595 3947.213718 42472.41314 162.3704719
38698.20867 2748.748948
13384.70076
2734.915733
13777.40145
19394.3998
0.397104203
»
197890.7465
2773.399897
0
93788.1849
0
0
1.325294234
71659.75375
15302.2655
20250.97873
0
13598.17942
0
0
1410.526869
283.2776175
1437.552828
2013.844308
0.040595712
o
20596.14018
288.0584514
0
9752.295577
0
0
0.135747712
7368.685392
1577.245324
2094.078249
0
1408.705468
0
0
14872.04868
3038.823174
15308.33034
21549.3333
0.441227137
o
219882.8793
3081.554683
0
104211.5449
0
0
1.472549073
79622.94955
17002.52874
22501.09667
0
15109.08895
0
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Table B-6bii: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants
13.75510326
0.996784712
16.71373521
91.30707568
2.62E-05
0
348.4196199
8.131030242
0
183.9604875
0
0
0.001195173
297.2336012
36.57024187
52.30193429
0
53.50948144
0
0
0
0
»
4120.290641
0
0
0
0
0
1930.921035
368.6820664
1620.741797
851.0550947
0.330052248
0
16731.07588
412.7604569
0
14086.64531
0
0
0.034613533
6336.952636
865.1898825
944.8583665
0
393.2380596
0
0
18654.36485
2909.882563
17705.89972
53949.54979
1.806922847
»
233657.2932
3361.521033
0
157900.6187
0
0
1087.93149
272.1381567
1302.873598
1405.683478
0.024237385
»
11813.64206
258.0292054
0
9071.594665
0
0.492912224 0.057885385
54177.37652
21568.30183
33429.34418
0
24253.3728
0
5434.639884
1628.655093
1873.319119
0
1296.615754
0
-------
SMOKE Totals (2007aq_07c 19apr2010)
Zacatecas
Canada Total
Mexico Total
TOTAL
376.6143422
47,089
153,989
801,078
38.80671219
67,131
15,983
83,113
418.4601632
718,996
171,099
890,095
383.9392647
707,902
289,232
997,133
36.10568859
44,490
12,198
56,688
-------
SMOKE Totals (2007aq_07c 19apr2010)
PMFINE
354443.4113
6006.972663
880.9332009
84791.25111
0
0
17112.82204
4951.904274
71411.21196
4486.825832
647.8739924
45810.17836
o
0
10677.08721
3391.921438
283032.1993
1520.146831
233.0592085
38981.07275
o
0
6435.73483
1559.982836
4237.131739 3130.507588
52304.68595
1500.130913
172.050204
19329.50106
0
0
4125.568363
1047.218428
1782.668072
0
153.2400771
11.85536809
1.170737942
259.5833431
0
0
19.81176232
8.335972266
0
0
8.899008251
0
0
0
10779.25213
1376.795693
203.0874607
20150.22516
»
0
3527.085818
1134.685393
1593.470574
0
640.5798671
304.0317891
19.0005764
1104.286351
0
0
459.6702097
147.7049015
39.86399334
0
0
0
98600.24267 18782.42777 79817.81491 12066.00525 36.05195269 3660.290061 271.3315546
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Table B-6biii: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants
33508.73185
10056.62274
33220.5088
3062.853208
3.287936741
»
347163.9948
6402.382289
0
231762.6728
0
0
0.68034481
221960.3806
14538.17652
11620.59669
0
6553.013984
0
12375.78264
3243.099567
12792.19077
4618.528412
0.643801311
o
101045.4745
2049.951888
0
94178.23915
0
0
0.380518524
32163.51211
8391.677002
9093.006059
0
3266.551405
0
21132.94921
6813.523171
20428.31803
1444.324796
2.64413543
o
246118.5203
4352.430401
0
137584.4336
0
0
0.299826287
189796.8685
6146.499516
2527.59063
0
3286.462579
0
7086.039769
2013.432875
7288.263968
1359.328259
0.530428523
o
60806.82295
1179.85725
0
50417.14129
0
0
0.178896245
21922.13759
3706.506957
3658.895155
0
1188.467495
0
19.10882091
3.756561892
14.71998765
9.759410043
0.000772307
3926.526231
887.0565566
3913.320396
1597.25976
0.087132393
»
25532.36279
570.5683981
0
32597.06728
0
0
0.141768604
4513.037929
2989.07681
3430.17948
0
755.8157203
0
256.1763301
66.71541626
273.0128195
246.4975049
0.001230702
•
2692.691411
39.18228002
0
1942.456064
0
0
0.001391278
243.8337638
50.03660422
104.9139905
0
20.13505481
0
-------
SMOKE Totals (2007aq_07c 19apr2010)
Zacatecas
Canada Total
Mexico Total
TOTAL
457.1844761
1,421,910
75,556
1,497,466
210.892811
393,852
49,023
442,875
246.2916651
1,028,058
26,534
1,054,592
PMFINE
109.3043782
234,414
18,651
253,065
1.7632624
7,530
1,394
8,924
-------
SMOKE Totals (2007aq_07c 19apr2010)
0
9531.295062
18780.20028
1362.037568
11346.75227
«
0
27879.90202
9952.188779
0
0
1533.71599
0
0
22.07250246
287.0080943
19.78916084
0
1292.039215
1600.640821
88.19886572
0
21156.98906
6324.095998
430.9492899
29.08834145 443.5425189 20404.86385
0
426.0115963
151.1012792
0
0
22.04410337
0
0
2259.331534
1224.438749
0
0
362.156151
0
0
7744.058505
5252.195873
0
0
1721.019524
0
0
1.62931369
4.056943503
0.644094833
1.948106947
0
0
9.599208421
4.176695447
0
0
2.834652133
0
0
0
0
0.937289567
0 0
42833.10026 15225.82446
8933.79607 4411.701266
875.4941297 324.5766684
22862.45546 12917.6945
0
11206.17453
6785.192305
0
0
3255.977577
0
0
5513.362885
3866.97681
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxac
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Table B-6biv: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants
o
8982.275903
953.7323126
7831.951373
17510.48203
0.017443033
0
24357.22557
1049.649927
0
19664.86145
0
0
0.025611647
11140.5825
1813.29971
2253.87939
0
1479.221107
0
0
100.1092818
7.269226982
71.72889942
267.2177192
0
0
168.8463242
5.333874087
0
186.7241877
0
o
0.000136436
95.00050442
24.17668539
30.70976379
0
20.2468215
0
0
100.7912665
16.50340917
124.5217182
2167.14361
0.000428078
0
1500.515106
27.33526382
0
1022.490136
0
o
0.005657205
648.1400648
341.8666748
958.5802792
0
1006.23766
0
5143.130231
777.7732349
4220.421421
8227.528671
0.564896934
«
52818.6079
796.4976548
0
38706.63585
0
o
0.083246633
10405.72226
2747.511197
4116.95989
0
3703.999469
0
0.250220063
0.057771171
0.153900659
5.29443451
6.34E-06
0
4.920929783
0.00484624
0
1.563861844
0
0
0.000256938
1.289489668
5.582495197
5.426235921
0
5.444631179
0
8173.878359
1553.677364
8428.104621
11719.6136
0.475614429
3639.283592
581.5145224
2824.531322
5827.461899
0.61105478
76260.70704
1559.537307
0
66116.5801
0
•
0.170174376
20963.52616
5342.069132
6563.975911
0
4861.439741
0
38711.84019
609.2492332
0
26367.95186
0
•
0.058655742
8100.16989
1860.328869
2880.539276
0
2785.071432
0
-------
SMOKE Totals (2007aq_07c 19apr2010)
Zacatecas
Canada Total
Mexico Total
TOTAL
78.37712661
97,652
82,643
180,296
1.127694448
694
1,249
1,943
4.938713066
5,575
10,014
15,588
47.50538583
162,097
40,316
202,413
0.139567391
89.46446443
263,612
59,634
323,246
39.25828832
114,846
28,727
143,573
-------
0.60%
0.65%
0.67%
SMOKE Totals (2007aq_07c 19apr2010)
State VOC APPROX
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
So nor;
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Table B-6bv: Canada and Mexico Non-Point and Non-Road Mobile Emission
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants
0.64%
0.78%
0.75%
0.72%
0.690/
0.68%
-15.0%
0.0%
-13.8%
-21.6%
0.0%
0.0%
-41.9%
-982989.1%
-1.5%
-27.8%
0.0%
-112.3%
-19.2%
0.0%
-36.1%
-13.4%
0.0%
0.0%
-77.1%
-0.3%
-258.9%
-3.0%
-2.0%
100.0%
-0.3%
-221.5%
-0.9%
-12.0%
100.0%
-1.6%
-4551424.4%
-5.8%
-20.0%
0.0%
-156.1%
Inventories—SMOKE [Canada and
-------
SMOKE Totals (2007aq_07c 19apr2010)
Zacatecas
Canada Total
Mexico Total
TOTAL
VOC APPROX
1,332,559
429,264
1,761,824
0.73%
-3400.0%
-3288.7%
-------
SMOKE Totals (2007aq_07c 19apr2010)
-11.8°,
0.0%
-27.9%
-15.1%
0.0%
-56.7%
-98.7%
-12.0%
0.0%
-43.8%
-10.9%
0.0%
0.0%
-21.5%
-0.3%
-286.6%
0.0%
0.0%
-57.5%
-3.0%
-115.3%
-66.1%
Aguascalientes
3rta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Table B-6bvi: Canada and Mexico Non-Point and Non-Road Mobile Emission Inventories—SMOKE [Canada and
Mexico]: Criteria Air Pollutants and Hazardous Air Pollutants)
-0.2%
-179.3%
-0.6%
-12.3%
100.0%
-1.7%
3562127.6%
-4.7%
-18.8%
0.0%
-149.3%
-------
SMOKE Totals (2007aq_07c 19apr2010)
Zacatecas
Canada Total
Mexico Total
TOTAL
-4518.6%
-2002.6%
-3342.0%
-3273.8%
-------
Canada - 2006 (Allan); Mexico - 2002ac
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Oaxaca
Ontario
Prince Edward
Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Zacatecas
Canada
Mexico
TOTAL
5,915
50,394
17,696
1,713
42,481
3,116
14,224
19,447
13,901
2,257
97,578
7,482
24,259
12,738
7,612
65,657
16,827
106,628
15,363
8,026
3,924
9,081
4,125
8,194
52,458
11,800
64,827
1,669
24,699
58,668
6,750
4,976
10,865
27,613
11,806
10,537
7,030
16,220
5,001
28,823
8,644
4,450
283,879
631,594
915,473
51,156
787,448
135,646
13,074
587,324
23
110,136
161,063
115,759
16,569
813,226
66,416
206,136
97,332
64,276
547,239
262,215
894,875
128,606
66,134
29,792
147,496
79,015
136,611
391,398
96,671
1,212,175
27,533
5,535
26,902
32,437
10,853
20,724
31,577
Table B-7a: Canada and Mexico On-Road Mobile Emission Inventories—Pre-SMOKE [Canada and Mexico]: Criteria
Air Pollutants and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
ALD2 ALDX BENZENE
ETHA ETOH FORM
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
0
759,578
135,653
9,907
575,031
147,460
17,178
136,578
389,734
0
1,569
39
0
592
14
0
544
0
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewa
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
fukon
Zacatecas
Canada Total
Mexico Total
TOTAL
Table B-7b: Canada and Mexico On-Road
Pollutants and Hazardous Air Pollutants
2,950
76
0
2,667
0
7,622
198
0
6,890
0
1,172
30
0
1,059
0
0
1,555
492
594
0
525
0
3
12,679
6,262
18,941
9
32,778
16,187
48,965
740
4,514,002
1,066,589
5,580,591
4
15,644
7,726
23,370
5,038
2,488
7,526
1,482
37
0
1,347
0
0
502
159
192
0
170
0
0
0
0
0
0
0
0
0
617
192
234
0
206
0
2
6,296
3,108
9,403
Mobile Emission Inventories—SMOKE [Canada and Mexico]: Criteria Air
-------
SMOKE Totals (2007aq_07c 19apr2010)
ALD2 ALDX BENZENE
ETH ETHA ETOH FORM
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Canada Total
Mexico Total
TOTAL
147,460
17,178
136,578
389,734
0
0
641
198
242
0
212
0
0
233
70
87
0
76
0
0
1,262
400
483
0
426
0
0
3,266
1,035
1,250
0
1,104
0
398,843
67,402
81,054
0
71,850
0
0
1,555
492
594
0
525
0
0
502
159
192
0
170
0
0
0
0
0
0
0
0
1
2,457
1,211
3,668
3
12,679
6,262
18,941
9
32,778
16,187
740
4,514,002
1,066,589
5,580,591
4
15,644
7,726
23,370
5,038
2,488
7,526
Table B-7bi: Canada and Mexico On-Road
Pollutants and Hazardous Air Pollutants
48,965
Mobile Emission Inventories—SMOKE [Canada and Mexico]:
0
617
192
234
0
206
0
0
0
2
6,296
3,108
9,403
Criteria Air
-------
SMOKE Totals (2007aq_07c 19apr2010)
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
NOX NVOL
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewa
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
fukon
Zacatecas
Canada Total
Mexico Total
TOTAL
Table B-7bii: Canada and Mexico On-Road
Pollutants and Hazardous Air Pollutants
647,868 104
Mobile Emission Inventories—SMOKE [Canada and Mexico]: Criteria Air
-------
SMOKE Totals (2007aq_07c 19apr2010)
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Canada Total
Mexico Total
TOTAL
I Table B-7biii: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE
Pollutants and Hazardous Air Pollutants
PMFINE PNO3
-------
SMOKE Totals (2007aq_07c 19apr2010)
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Canada Total
Mexico Total
TOTAL
Table B-7biv: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and Mexico]:
Pollutants and Hazardous Air Pollutants
0
1,056
104
953
6,081
0
0
1,385
139
1,261
8,022
0
-------
SMOKE Totals (2007aq_07c 19apr2010)
State VOC approx
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
Mexico
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
Yukon
Zacatecas
Canada Total
Mexico Total
MONO
308,318
152,265
0.80%
0.80%
0.80%
0.80%
0.0%
0.0%
-84.3%
0.0%
9033844.0%
-0.1%
-35.6%
0.0%
0.0%
0.0%
-98.7%
0.0%
-8632781.1%
-0.1%
-35.6%
0.0%
TOTAL 460,583
Table B-7bv: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and Mexico]: Criteria Air
Pollutants and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
Aguascalientes
Alberta
Baja Calif Norte
Baja Calif Sur
British Columbia
Campeche
Chiapas
Chihuahua
Coahuila
Colima
Distrito Federal
Durango
Guanajuato
Guerrero
Hidalgo
Jalisco
Manitoba
0.0%
0.0%
-84.4%
0.0%
-8987143.5%
-0.1%
-35.3%
0.0%
-74.9%
0.0%
-81.2%
-11195857.2%
-0.1%
-26.3%
-81.5%
0.0%
0.0%
-84.3%
0.0%
-8961951.2%
-0.1%
-35.3%
0.0%
-74.9%
0.0%
0.0%
-84.3%
Michoacan
Morelos
NW Territories
Nayarit
New Brunswick
Newfoundland
Nova Scotia
Nuevo Leon
Nunavut
Oaxaca
Ontario
Prince Edward Island
Puebla
Quebec
Queretaro
Quintana Roo
San Luis Potosi
Saskatchewan
Sinaloa
Sonora
Tabasco
Tamaulipas
Tlaxcala
Veracruz
Yucatan
fukon
Zacatecas
Canada Total
Mexico Total
TOTAL
Table B-7bvi: Canada and Mexico On-Road Mobile Emission Inventories—SMOKE [Canada and Mexico]: Criteria Air
Pollutants and Hazardous Air Pollutants
0.0%
-8940788.0%
-0.1%
-35.2%
0.0%
-74.9%
-------
EMF (2005ck)
ACETALD BENZENE
96805
461331
101639
79234
11875
4001
454526
242945
14252
129629
257595
175821
73609
123184
100019
134050
48204
102392
95417
9956
74953
68958
850802
108397
139222
104033
141960
136753
94909
139234
129408
168352
36832
66672
134708
229804
103716
145945
156430
29853
39234
20784
35842
124235
250176
397374
223576
21776
283520
11358
1061
3689
198338
169357
272518
16355
148680
17831
143122
687646
95498
14536
163746
116240
35624
Table B-8a: All Non-Point Emission Sources—Pre-SMOKE
31983
Criteria Air Pollutants and Hazardous Air Pollutants
-------
EMF (2005ck) |
State
WV
Wl
WY
TOTAL
CO
70069
1 66779
29196
7376314
NH3
72
266
91
1 34080
NOX
14519
21994
40480
1683490
PM10
12220
26104
3717
1349685
PM25
11130
25407
2922
1076954
S02
14589
6369
6721
1252645
voc
57244
156290
181323
747451 2
ACETALD
71
563
34
11399
BENZENE
522
3462
246
100629
-------
EMF (2005ck)
CHLORINE
FORMALD
225
204
0
378
792
HGSUM
0.088590977
0.031223489
0.332466877
0.023254157
2.014760435
0.03828326
0.187136463
0.002750469
0.008229281
0.190282333
0.138146333
0.012770895
0.049255448
0.142914176
0.095910857
0.090864523
0.072492147
0.088100095
0.032643034
0.144804576
0.166205273
365338029
0.099110873
0.123022855
0.049666651
0.047494427
0.02418807
0.058185441
0.025760745
0.070673443
0.281978189
0.022393683
0.66853846
0.152908332
0.044274943
0.150646212
0.027383797
0.099275192
0.376162844
0.038095458
0.058061584
0.029063241
0.051456015
0.236102845
METHANO
2057.921256
255.0651096
2138.054579
1941.140951
12492.20347
2345.057697
1085.888996
198.2526767
198.8448603
17815.24438
3350.05882
454.8393395
716.2954279
7134.629047
2815.110074
2274.019343
1959.276492
3269.487173
4366.847544
519.4934434
2583.367962
5137.370748
1081.627749
2032.490566
3198.609242
412.2869293
944.419485
974.2887961
852.7906866
846.6527207
788.3331038
13482.41901
7996.011698
280.253118
8033.142172
1796.977969
2418.887757
3605.162292
492.7479526
2378.552745
401.0049595
4879.018717
9276.713563
TX 0 2047 990
Table B-8ai: All Non-Point Emission Sources—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
EMF (2005ck)
UT
WY
TOTAL
CHLORINE
FORMALD
HGSUM
0.030997375
0.046117447
0.188059658
0.093132899
0.207706501
0.307642354
0.042062044
METHANO
857.1294591
353.3339236
1366.920412
2716.247518
771.3128355
3118.207802
305.4798823
154265
-------
SMOKE Totals (2007aq_07c 19apr2010)
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
1307.077418
0
712.7485158
GA
1618.026181
10933.38112
904.3780811
757.2435055
148.6094088
39.55788462
5454.136356
1759.16676
1543.918365
0
697.5798033
1287.475612
8128.806812
1962.335604
2197.093704
343.0732778
38.56519901
4075.349476
2178.691215
BENZENE
3430.190728
0
807.9307922
935.119596
9955.464439
1207.61604
1100.476736
152.1540646
50.42305967
3148.470741
3864.463948
33802.34211
0
3623.647811
1872.693422
1084083.825
19564.5295
64588.74354
7622.921063
158.8862849
43115.82891
6191.461462
0.011879966
°
0.004279527
0.045345866
2039.75145
0.030207753
0.003862986
°
0
0.009186717
0.018998246
188557.4958
°
44115.3197
174756.1669
458856.5291
94517.50943
69760.62764
11636.61619
1817.027423
201970.7532
194306.9268
KY
LA
ME
MD
804.758507
1239.855448
1016.262713
782.6486545
8489.5218
1051.59835
2125.846794
894.0403824
931.0928625
MA 1462.782731
Ml 1637.030468
MN 1349.68066
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Puerto
Rico
Rl
SC
SD
1889.069452
1670.036961
323.2937098
830.4824605
268.2388725
599.3522528
856.9084359
427.6270483
1916.040493
3692.991263
199.2762814
1640.231203
4341.221832
6620.224994
1984.667101
•
119.1525673
1785.743842
244.1285603
1390.234769
4153.334389
1219.525216
1034.259306
3150.993225
1562.873546
1443.101165
5320.614226
1832.157054
1379.714424
2756.22531
2381.077804
3874.152691
2578.042113
2603.887913
2740.007456
3088.708304
694.4545217
781.2898231
294.980061
1789.575941
2153.841659
466.8994874
3926.320785
3949.030006
474.9180466
2788.611569
3152.274028
6091.136459
3422.641383
•
148.309426
2348.131244
523.5141483
1858.650116
4349.028669
919.0838983
1636.377111
12357.25868
4542.922136
1351.799848
3617.649758
1827.799175
2319.267313
521.8394849
1630.262265
1340.552708
2931.619361
5914.430868
4202.994308
3570.277836
626.7531851
639.0817247
308.3499996
405.5245023
1238.321468
625.4927935
3343.825435
3961.671093
381.0680613
3834.981465
1807.685037
4010.336246
6459.646505
•
130.5467367
1629.24057
358.7897806
2430.578486
5011.049408
655.0400605
1378.182458
12091.95311
10799.06133
4674.990072
3070.284562
5153.585042
4638.81394
11778.30159
29905.27163
242162.8919
36552.96665
6940.493095
5185.242103
150700.2947
2550.723115
1600.273841
1930.884951
15241.81729
6467.565667
82724.12585
7627.060991
8794.786759
1663.2885
53665.22506
2552.296363
490967.9104
1516456.169
^H
313.0389096
5149.016988
1496.096589
7542.614607
878506.1187
27502.02926
92.5614665
0.017745771
0.17378017
0.008248075
0.000835078
0.050021962
0.008248075
°
0.153654982
0.000626237
0.022652962
0.240292857
0.006576206
0.012088237
0
0.008456345
0.000417682
0.583667891
0.013965522
0.150000267
0.303380374
0.00970882
0
0.493058545
0.008664615
0.019500377
0.284990806
0.032444519
0
0.086954278
0.118000818
95409.66058
99504.79864
74906.49657
68941.44723
850772.0166
108366.6793
139172.1743
104018.04
141934.1452
136670.0707
94857.8992
139186.6756
129351.3881
168327.2359
36827.35965
66658.09234
14692.7386
74106.36709
84117.99003
61660.12758
200345.2585
320996.6547
20522.96192
150246.0592
385212.7394
342426.3612
264992.274
•
5419.25503
145267.
24115.82788
119935.378
463496.9412
80653.17374
Table B-8b: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
VT
Virgin
Islands
1275.773881
1875.574631
506.2466272
1538.520116
206.6511176
87240.95426
BENZENE
2636.106489
3936.744651
844.9539936
3801.295003
354.7942603
110642.1591
6448.938416
2389.961065
772.9711714
3664.494416
376.9740295
124326.2287
28978.49584
11192.88066
3197.137953
9613.08859
63367.6579
5020801.885
0.009289426
0.008456345
0.021671524
3.83E-08
0.000417682
2135.284494
43086.86059
0
207884.8625
204100.6836
70045.98793
166742.5649
29190.57639
7374457.936
-------
SMOKE Totals (2007aq_07c 19apr2010)
AL
AZ
AR
CA
CO
CT
DE
DC
-
GA
4305.866394
0
1132.872613
2547.156789
7756.358905
2142.934161
2620.611924
317.0931655
30.63655234
5553.597573
5544.506329
646.3172627
°
196.3855345
164.1180763
119150.4901
21274.90788
976.3178447
156.0878097
9.17548408
745.6931135
821.2181157
6293.144152
0
4380.168692
3241.298607
39936.57895
2177.791263
3421.146061
597.349952
227.3931109
23532.10712
6264.622886
1611.401053
0
661.1017634
2049.014043
7830.838661
15518.79714
1531.326154
261.5915185
28.28852749
5589.187529
1861.834888
204.241486
°
169.7536542
307.973774
600.3137664
224.1549394
120.9610441
199.4453774
9.606096428
350.5518165
1622.67872
HGIIGAS
0.018209814
0
0.092828493
0.002301061
0.619854686
0.009654902
0.050613594
0.000814375
0.001864534
0.038097
0.02344954
MD
MA
Ml
MN
MS
OK
OR
PA
Puerto
Rico
1446.855086
2597.374672
2205.388494
2229.385391
7228.577286
3603.181421
3730.798008
2541.477867
3780.370701
4294.034809
5356.982413
3252.374093
3409.432019
4950.859594
953.5520907
1167.533841
421.0993249
1763.058791
1816.263542
859.4002803
5529.942901
8552.149565
529.5528813
6796.907904
4217.630058
6953.688296
9347.289916
•
134.5693702
5934.821455
711.2160187
4684.93173
3634.922364
946.4833908
135.8371093
868.3748155
586.5708041
438.5642049
393.5158837
578.3197075
430.6474124
880.1059769
806.1287714
2565.250806
9408.029367
676.7410123
911.8955597
1741.220046
1481.326324
154.8536959
98.27294896
579.3631185
704.8601659
122921.164
645.9149174
793.7217888
1068.212129
1266.E
7498.687951
4856.680624
11813.55196
^H
34.44389466
604.3557256
186.6774504
589.9023107
28159.36988
25214.03847
2729.331146
14387.97132
7492.008608
1752.23606
1935.651471
2633.769865
3814.528062
1300.674277
3553.342626
5466.451908
11481.70212
5015.419555
3917.115343
4225.300564
470.5310934
927.3513742
950.327489
944.9593021
6280.757671
1161.173452
15135.20085
7118.590272
291.5440173
10563.37375
1681.275546
5092.310972
9898.821299
•
704.5988287
5894.148688
409.966833
4122.285455
19235.27867
2743.872554
1963.264817
2230.043382
1216.566092
1217.606364
12676.80664
1577.586233
2338.6711
2036.455238
1771.593235
2868.663537
7689.024875
2054.498559
2930.975287
2995.986493
1237.674697
1136.190274
280.5955437
1335.186195
1722.786834
81508.2716
2679.907101
5154.24332
768.662599
1980.014723
6061.33474
8020.232638
2813.828502
•
100.0108256
2394.065903
469.9408199
1654.274235
4672.264575
18209.21968
616.3745574
120.3583912
1298.753139
178.6112335
181.9006937
594.5769325
145.4826041
18.49559331
693.3998155
112.6135314
1426.585632
360.5927378
150.1739286
2782.020303
34.98214791
367.3213628
104.3898448
66.3796543
151.7897097
72.08210946
1460.796135
358.1125366
59.30993858
522.6609253
116.0981514
534.5369539
5363.385767
•
19.32699312
764.8080509
262.373223
789.8358795
988.3051722
160.4191048
0.014729811
0.022879136
0.017534403
0.021627241
0.016263691
0.020465626
0.003656527
0.036115752
0.043027001
0.083934904
0.014539613
0.033128698
0.01049869
0.014206372
0.005907148
0.014783409
0.005339572
0.019327303
0.101702426
0.004244174
0.112547555
0.033026942
0.011573894
0.025289462
0.002666396
0.024097732
0.097050461
'
0.010234891
0.011398647
0.007090255
0.007172443
0.050061167
0.005193782
-8bi: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
VT
Virgin
Islands
5283.366347
4175.619553
2323.754252
3950.207613
481.059485
164628.3886
1522.470698
1134.373634
371.8162352
968.8450676
94552.15475
471993.7333
5578.798036
4316.622186
2809.851808
7793.56377
295.7996554
274504.6117
2327.239972
4264.719798
729.9336342
3401.292319
62617.05799
298722.2321
3746.816834
139.1213542
161.0238718
104.5041017
83.038179
28931.05093
HGIIGAS
0.013399134
0
0.045414906
0.018843566
0.059045611
0.081913957
0.011722681
1.989343494
-------
SMOKE Totals (2007aq_07c 19apr2010)
State HGNRVA MONO
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
GA
H,
ID
'L
IN
,A
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Puerto
Rico
Rl
SC
SD
TN
TX
0.058133632
0
0.177499591
0.019526672
0.990518167
0.022091599
0.102931834
0.001383342
0.005107718
0.12923982
0.099139643
°
0.024549398
0.104669226
0.066806353
0.054766751
0.045382137
0.053897138
0.026648265
0.086916363
0.094707154
0.229946407
0.075759399
0.068373134
0.032118435
0.023677175
0.014443913
0.03349433
0.017154642
0.038562584
0.131778333
0.015453712
0.483155891
0.098030498
0.024907866
0.110032333
0.023053859
0.059536459
0.214978347
0.021142438
0.039147183
0.017215382
0.039580298
0.152147245
0.022363325
1859.000384
0
1201.3134
1494.578403
4200.767691
801.1866207
621.2268691
170.228979
34.62266992
5940.48207
3119.973845
0
1141.506363
2034.24216
2053.360104
1110.18318
1622.889923
1536.481598
2230.005903
531.2937023
1206.316017
1020.693347
2960.807822
1662.684149
1711.474972
2154.727107
443.5875128
661.9861911
298.9300984
372.2904858
1140.969148
746.2759276
3430.812128
2967.044225
252.0933328
.55377
1687.500233
1525.106501
2804.727837
56.97562251
0
29.38215575
69.30308236
162.7248556
56.97271966
61.24004266
10.67070103
0.888208636
206.240792
70.89105018
0
47.62693384
69.99556391
46.37935004
46.08849323
364.0770272
59.61706416
82.08096149
78.41063959
67.40737582
105.8868466
91.87569302
84.45459051
103.0480828
103.182807
21.62051833
38.20803466
13.18987518
50.9265963
66.42070145
18.495347
87.10368978
169.6336893
14.34233735
87.85877002
187.4597296
187.8245878
117.2882603
3245.698981
°
2253.910502
2349.014903
12874.7401
2475.734815
2874.206253
345.2843228
213.2015569
20322.16048
6629.965354
0
1605.513114
7892.793261
3457.181787
2407.632415
2066.757809
3455.606935
4623.135728
661.0851881
2935.883319
4685.976203
5776.080097
1123.411922
2289.927535
3823.054644
436.0213293
1109.295174
1051.13599
1043.210367
4227.25447
856.690641
13801.38702
8392.322219
301.0419899
8325.158255
1923.739617
2488.716271
8702.173705
424.9004532
0
4390.62729
7385.765525
14744.23675
71.17892
1437.897128
28787.99073
°
7766.987287
19258.9273
109493.6793
D197
11284.87451
278.3869168
12.59124732
446.8689202
60.31558436
0
1683.437649
1629.446446
4213.417876
7403.474638
12466.02257
230.6948881
23167.00996
1616.227774
605.4355884
4068.003896
428.4894276
1225.208425
195.3931655
3828.231271
49.76126005
3142.302684
198.032757
834.8275827
2647.989991
38.41313767
2499.147534
235.8252664
69.09173586
8524.661827
11357.32543
1060.251171
3687.051487
2926.392712
1562.950841
26522.75198
34948.96079
0
27206.65226
42816.80701
27112.41726
13610.53371
38033.04634
15769.67915
24748.84438
6672.513821
19513.65251
30881.77235
39095.63721
50897.77576
10971.61243
29572.93147
12967.40478
12415.29421
4832.131465
10090.07705
23720.61839
62246.08342
78702.55474
16958.91562
9033.961188
37265.22763
85101.97402
15336.88813
48014.64638
158.1356712
2170.719977
310.3140403
2259.701684
6682.605169
667.478129
3.765564534
87.03886084
16.97438132
68.88461926
147.3235743
51.78384699
780.62096
3274.774563
431.6260009
5170.744098
10282.82311
1067.209459
15.30411702
222.8877283
50.43052057
163.9102621
1981.159132
1265.986296
2665.109234
18210.71858
5178.821349
16778.13572
246763.5361
12454.35036
Table B-8bii: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
State HGNRVA MONO
VT
Virgin
Islands
VA
WA
WV
WY
0.024500134
0
0.112445312
0.062497024
0.108754988
0.170846867
0.022442682
TOTAL 4.651455006
2126.320511
1558.679228
777.12061
1672.114967
328.8358173
80308.28531
20.7622865
'
79.82441507
132.3855653
31.56893981
103.0782562
11.75087557
3890.933982
378.2165181
•
4045.345621
2937.134391
1046.960754
3225.287674
319.6300609
186006.4775
213.7339258
'
1616.287828
1710.420977
72.17816201
265.2852956
90.26261204
134025.791
3090.699899
0
48121.99784
15194.93869
13036.00817
19763.93242
36420.75901
1513093.977
-------
SMOKE Totals (2007aq_07c 19apr2010)
AL
AK
AZ
AR
CA
CO
CT
DE
DC
FL
GA
3198.666437
0
863.0005093
2139.880008
12165.97541
4363.532035
1253.875356
325.1548601
173.6611921
2946.975258
3883.216843
31986.65716
°
8629.987797
21398.80731
121659.6547
43635.334
12538.74987
3251.547572
1736.612033
29469.727:
38832.17763
152.3580771
°
44.13482174
54.81097369
342.254682
88.09735558
70.84461512
8.987904033
3.326965786
342.5778647
133.7111892
2897.219354
0
1368.493945
1639.808252
8125.078945
1337.232978
1651.711205
225.5432751
29.53834706
4964.338987
3524.197619
109693.1441
0
55198.16924
68949.78607
306986.1205
54478.89606
52304.81895
8007.478931
2752.955296
329242.0183
185512.5991
2130.907615
0
618.1922859
2296.076167
4629.880672
718.902018
615.0730456
105.5638144
27.98262394
3505.400929
3477.643368
0.012053978
°
0.061120213
0.001406595
0.402559996
0.006436729
0.033438531
0.000544298
0.001243095
0.022668717
0.015325552
ID
'L
IN
,A
KS
KY
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Puerto
Rico
Rl
SC
SD
TN
TX
UT
3022.958952
4757.42373
3012.490848
1512.281399
4225.894748
1752.187175
2749.870716
741.3904809
2168.183335
3431.307354
4343.961278
5655.30676
1219.067931
3285.881212
1440.821048
1379.477908
536.9083583
1121.119189
2635.623882
6916.214345
8744.731106
1884.324075
1003.772202
4140.581546
9455.77331
1704.098323
5334.961956
0
296.1233451
2023.414079
575.425005
1864.237011
27418.15165
1383.822064
30229.61121
47574.23074
30124.90811
15122.81511
42258.94108
17521.86633
27498.71509
7413.904302
21681.83585
34313.07971
43439.59849
56553.08252
12190.68036
32858.81268
14408.22582
13794.77212
5369.039823
11211.19624
26356.24228
69162.29777
87447.28585
18843.2397
10037.73339
41405.80917
94557.74733
17040.98646
53349.60833
•
2961.232579
20234.13266
5754.246354
18642.37273
274181.6877
13838.17243
81.09534741
344.812402
157.9404066
89.96046958
112.2529484
98.98353051
73.33269429
28.74475712
65.99918001
97.38473384
130.6939461
160.7226389
100.72099
184.3391669
16.04457637
43.26318692
16.71228225
25.50332062
89.24804071
17.52911268
201.3431485
180.7565162
11.27224706
191.7236367
61.75529959
211.3610748
209.6273257
•
21.94517585
143.6244966
16.9086852
109.0901456
138.4697355
40.37059224
1283.571921
3532.095997
3219.781445
1409.250729
4627.697217
2182.79355
2392.257543
1637.547471
2285.192007
2695.065942
3765.317271
2575.447276
3546.023462
3338.655244
660.7089518
780.151716
379.0058006
1088.395791
1333.050272
718.4595153
4812.028881
4996.281809
410.3230839
3742.600247
3127.569858
4145.682158
4402.747503
•
215.0275856
3994.46797
449.9104291
2777.762971
5978.090512
817.9473571
93338.38677
170335.4817
119640.0337
50582.737
62634.90338
69356.11735
99448.64184
26656.68932
71698.82142
88084.78211
162605.2675
65765.044
94615.99983
102926.7197
21552.28253
26869.10904
14516.45298
20990.46983
89006.03622
107272.3533
276547.2605
152662.0061
16409.10299
204912.5616
154357.3058
94052.62382
188275.1842
0
11798.17325
100541.7906
11841.85836
102615.8332
568761.57
49719.61219
2852.860094
747.8132802
1077.265119
821.0444482
8730.620802
1438.365325
1750.906888
838.8642105
1479.773304
2313.885761
1701.561968
1852.211979
1502.593675
2130.621881
415.2659301
727.7574093
161.6610001
1033.80652
758.206694
425.4973437
2063.875683
3463.542493
226.6647454
1877.643397
4539.380433
3195.971237
2468.321877
•
79.47993055
1523.903551
294.3751286
1634.829079
3669.298744
818.9018057
0.009819672
0.01525203
0.011431096
0.014266026
0.010681559
0.013548196
0.002305163
0.02169323
0.028345709
0.051276817
0.008777293
0.021271286
0.006942997
0.009471059
0.003785506
0.009758588
0.003223999
0.012713436
0.048334791
0.002655486
0.072655583
0.021650884
0.007689688
0.015191187
0.00163977
0.015509364
0.063767514
•
0.006701263
0.007424141
0.004693273
0.004654418
0.033369481
0.003383493
Table B-8biii: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
5346.889032
1688.325848
1448.445719
2195.992934
4046.743711
168121.5324
53468.88687
16883.26453
14484.45389
21959.92536
40467.50272
1681215.51
164.2359766
119.0243519
41.4408559
124.4598968
7.059604557
5192.366648
3179.717664
2982.249915
1431.076928
2817.075096
400.7310002
120416.3619
112708.9672
70908.22333
38948.0109
101020.8751
74163.58034
5069262.358
2075.081297
2266.228806
987.6681976
1510.969274
205.9816152
84179.10453
0.029912654
0.011652612
0.039320122
0.054107539
0.00777653
1.271624565
-------
SMOKE Totals (2007aq_07c 19apr2010)
AL
AZ
AR
CA
CO
CT
DE
DC
-
GA
H,
ID
'L
IN
,A
KS
KY
LA
ME
MD
OK
OR
PA
Puerto
Rico
Rl
SC
SD
TN
TX
UT
27771.79403
0
12451.5576
24090.39125
90469.94344
15052.89566
10713.90691
2006.212607
489.0374184
41346.43026
46716.89252
0
56374.39503
16969.83599
60102.66454
12828.64374
108564.5432
23265.66392
19037.2625
13873.61029
25036.271
28514.06397
30965.05558
26949.30986
17818.74469
32382.55015
5764.899895
12667.60401
4386.250015
13336.58168
15985.56264
5982.675012
56014.87585
40934.79434
3748.895249
25438.90153
54337.89599
50678.54038
41796.00059
•
1171.269308
19385.67965
6674.859442
26819.57933
72174.53687
10382.02889
23968.71869
0
8593.844282
23060.23419
73853.54734
13543.5981
10443.94556
1825.074031
426.2883595
38824.71525
41822.13387
0
27343.52241
15179.55293
32540.434
11474.50085
83171.5662
18585.48055
17861.72974
13723.97456
19757.18582
26503.60752
24204.47309
24482.56529
16762.99827
28210.50392
5568.515333
8651.812582
2733.925352
12645.33414
13072.71731
5345.107956
34867.40251
38380.93953
3240.340303
23758.14509
43885.33091
49404.62095
31247.38766
^H
1107.287267
18133.58912
3803.075341
0
3857.713323
1030.157068
16616.3961
1509.297559
269.9613445
181.1385761
62.7490589
2521.715011
4894.758655
0
29030.87262
1790.283066
27562.23054
1354.142893
25392.97703
4680.183369
1175.532763
149.6357292
5279.085188
2010.456453
6760.582491
2466.744568
4461.234536
20657.69364
47374.25388
9077.894396
1055.746417
4172.046229
196.384562
4015.791425
1652.324663
691.2475362
2912.845324
637.5670559
21147.47334
2553.85481
508.5549458
1680.756434
10452.56508
1273.919434
10548.61293
0
63.98204104
1252.090539
2213.624907
6161.885689
24800.28299
1304.134496
PMFINE
11365.79601
0
3606.544534
10891.74198
33049.60482
5328.552749
4138.736014
753.7703371
120.1450114
17101.54661
21029.63727
13440.75103
6852.60419
23049.11417
5094.964608
39721.05951
8559.575584
8164.250474
5567.724766
9043.951532
11003.19987
11556.19057
10914.85719
7565.934422
13155.80683
2383.618959
4128.438332
1384.438047
5329.283546
5054.162317
2443.460107
16839.41679
17254.17952
1388.608943
9970.417972
20710.81641
20977.64957
14328.59822
•
411.8935563
8115.452358
2082.261279
9603.634325
22501.14787
4013.577654
83.00744931
°
56.03270391
75.09420339
211.0746001
30.73778744
21.27906767
3.898067208
1.518639969
129.1900512
9555.504131
0
4131.168095
128.9936303
0
65.86578581
66.40745184
81.18808104
34.8643883
284.9516319
53.46851789
61.27097251
27.41800956
54.35276851
37.37063047
71.97832129
57.82121849
51.19315674
80.03858188
14.96497726
25.8335226
6.80099682
18.21375883
25.54141206
18.07571355
97.82865017
119.9165639
8.048681912
73.23303516
150.1020675
111.1112827
84.74094369
•
3.157381901
52.963187
11.16229876
61.57447081
152.8826525
28.91237245
9377.865701
33950.70941
7344.52306
5456.59337
874.7186443
263.0432396
16886.13151
15834.00584
0
10024.41551
7168.417436
5303.225845
5317.732838
33028.90937
8147.565378
7605.69352
7152.498875
8710.391109
12208.22827
10201.94901
10773.79014
7351.119088
12244.11193
2687.149113
3540.230558
1098.402158
5874.107995
7039.732108
2330.957969
14149.03656
16940.77394
1547.47503
11446.82798
17795.48811
24734.60635
13213.43399
•
574.3657664
7832.170936
1949.230447
8933.771285
19643.9955
4071.986158
833.5034877
0
181.906663
419.4561309
2012.277836
120.8824816
212.2640664
87.12316826
13.59884456
1202.446153
1351.853754
0
959.6299988
344.3105684
3029.640787
205.8945648
1406.024895
386.50575
279.6078841
137.4686953
468.7171024
940.9229885
672.7932191
883.8847665
292.1579284
599.9246994
67.51635322
229.5527605
82.62315018
389.922323
195.0747824
127.1168221
1717.244826
602.5270118
69.54290305
390.0227058
689.5438892
385.2825027
1152.292627
•
38.39063223
609.0990835
124.2053825
423.884482
1406.929116
144.5164059
Table B-8biv: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
VT
Virgin
Islands
53842.70153
35620.30839
12215.0968
26099.78607
3713.430425
1348787.071
29922.8831
31980.92101
11126.73884
25403.24627
2920.956504
1076547.176
23919.81843
3639.387378
1088.357957
696.539799
792.4739211
272239.8947
PMFINE
15196.73001
13380.83818
5171.907215
10405.97204
1323.302121
497761.8482
80.03636965
81.94659733
33.2054905
55.89894167
7.744299895
11292.33663
15935.37368
4676.764238
13166.07645
1304.900752
3105.450097 463336.4437
80.46194514
0
1278.698799
316.5337413
257.193699
264.3295648
79.02771607
28164.32966
-------
SMOKE Totals (2007aq_07c 19apr2010)
AL
AZ
AR
CA
CO
CT
D
DC
FL
GA
ID
IL
IN
,A
KS
KY
LA
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Puerto
Rico
Rl
SC
SD
TN
TX
UT
52148.22706
0
2562.610802
27175.25307
77475.74776
6789.951188
18433.58317
43.449761
1555.118955
70343.13544
56654.54181
°
2908.88088
5384.58841
59599.30818
19775.62653
36302.25032
34125.81687
2372.819663
'60.813437
40750.23846
25243.60807
41944.88237
844.5002179
0
44.46241479
546.3031624
919.2485233
115.0119773
276.4121228
88.74872049
22.07361945
1083.730405
1117.439171
°
55.08823184
52.77965092
1268.371486
382.5841314
515.5708395
704.2452075
10.18652522
124.7399193
802.8676237
373.1341263
897.1284816
14708.24177 267.2137546
6775.945115 110.284825
44436.8086
2595.101871
29484.19042
12437.12385
7398.763766
10713.2023
3185.376259
124867.2567
979.3112556
28.7529106
614.9579643
225.9702394
101.0740598
144.9931284
41.49694539
2198.668773
21966.53734 212.164812
6439.014338 97.43162949
19751.17394
7539.496231
9826.582914
68225.14911
0
3363.012741
29926.27871
10315.71751
32616.3324
108876.6885
3567.38556
343.9848126
9.712922017
98.41840815
887.7187057
^H
49.21167896
511.7863803
208.06363
704.0208906
2324.503664
65.07747694
2091.58085
0
493.2066141
1201.00771
5656.003667
634.3339994
1512.508979
195.4642689
70.29639194
6947.20066
2821.446369
0
2202.442846
2875.933789
1870.755154
586.9760164
725.0976187
845.5080689
1185.238353
473.3134704
1120.050075
1372.043486
1882.522341
1230.143658
991.0537791
1879.609686
182.4985286
302.5119648
315.900838
515.4283001
1338.919738
357.8553836
4443.097301
1838.956658
149.6192146
3820.384442
1215.601121
1506.259942
2919.340255
0
365.0867476
2400.564477
131.2450145
1250.869838
4290.147187
576.5618887
21083.77072
0
5225.024033
10607.16588
31799.55319
4582.660789
8856.898698
1051.008618
251.1596431
41846.77497
22726.04165
°
6137.902599
18942.98316
15060.69278
5818.575477
6270.307716
7671.618336
9986.492015
4702.990118
10861.95758
16866.94043
18145.01772
5895.034766
15262.194
16494.97958
1607.984129
2834.376732
1370.754235
4232.243801
12173.3692
2741.213147
45043.24189
18016.72431
1070.306841
35021.5337
7720.165603
19242.95491
32599.59674
'
1227.434549
12878.3897
1387.277052
11792.70148
39813.52721
4765.986724
24416.98759
0
8091.907803
10660.47804
64530.17217
28713.12229
12779.88216
9595
532.157145
46916.09507
29635.33835
0
11150.04188
53217.48352
22395.74206
10943.09782
16932.73738
13950.28879
15444.98792
8112.026584
15704.14833
20463.38105
35220.76847
20776.42356
21585.43804
23125.44743
5399.106246
5187.368452
2671.10304
5835.997904
17130.27201
113683.0577
66664.79034
29402.04825
4103.778822
41139.85531
30757.67057
29223.50462
42081.0999
2061.72097
16463.52277
2689.293871
18197.23223
101000.7121
28002.60069
11222.53972
°
5055.778341
7393.794668
24173.50814
3544.501046
5753.669217
659.7099306
219.9143562
34555.75562
18392.37368
0
25596.68712
18492.02407
20332.89675
4781.643602
4947.044369
6265.070204
8284.7531
3418.691903
7040.512077
10655.38926
13480.69567
4826.363142
12172.56599
12396.87425
930.0280923
2363.662113
971.0908567
2739.314429
9435.743573
2702.469236
34125.78416
11910.41899
623.8576254
23025.17945
9601.950151
10619.81384
20189.15559
•
1005.738363
11206.38559
1055.995271
10059.99426
38106.51634
4698.435661
Table B-8bv: All Non-Point Emission Sources—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE Totals (2007aq_07c 19apr2010)
VT
Virgin
Islands
602.4953508
32839.66269
7236.79718
14546.59476
6360.937767
6701.994743
1249424.566
517.9542492
104.2716392
191.0700064
86.80439189
106.3772265
21524.08202
954.0973606
896.9264153
703.4185787
2139.289713
150.1010744
73733.17506
15468.59815
9585.746503
5515.505001
15806.13218
1364.433602
610542.0169
30311.83092
17884.10943
7254.598302
23741.89623
86535.04284
11582.77282
6529.445893
3879.889186
12628.81133
1084.960589
-------
SMOKE Totals (2007aq_07c 19apr2010)
0.0%
#DIV/0!
-0.1%
#DIV/0!
-0.2%
-0.3%
-0.2%
; All Non-Point Emission Sources—Percent Change between EMF and SMOKE Calculations
-------
SMOKE Totals (2007aq_07c 19apr2010)
-0.1%
0.0%
-0.2%
0.0%
0.0%
0.0%
-------
SMOKE Totals (2007aq_07c 19apr2010)
AL
AK
ACETALD
92.6%
#DIV/0!
BENZENE
15.2%
#DIV/0!
CHLORIN
0.0%
#DIV/0!
FORMALD
86.0%
-93485925690000
00000000000000
00000000000000
00.0%
-0.1%
-27221784130000
000000000000000
00000000000000
00.0%
HGSUM
-0.2%
-312234890000000
0000000000000000
0000000000.0%
76.2%
93.9%
58.9%
5.5%
80.3%
81.6%
66.1%
94.3%
79.5%
0.0%
#DIV/0!
#DIV/0!
-19850111370000
00000000000000
00000000000000
00.0%
-91331703960000
00000000000000
00000000000000
00.0%
-127708950000000
0000000000000000
0000000000.0%
54.1%
84.0%
89.5%
82.7%
98.6%
83.5%
97.1%
48.6%
68.0%
66.3%
87.8%
79.0%
94.1%
84.2%
78.5%
93.8%
89.4%
50.5%
74.7%
90.7%
75.8%
93.2%
77.0%
87.0%
98.2%
4.8%
29.8%
6.0%
24.3%
0.0%
-0.3%
-0.3%
-0.2%
Table B-8ci: All Non-Point Emission Sources—Percent Change between EMF and SMOKE Calculations
-------
SMOKE Totals (2007aq_07c 19apr2010)
TX
ACETALD
BENZENE
CHLORIN
FORMALD
HGSUM
-0.2%
81.6%
71.4%
86.0%
63.4%
83.6%
76.7%
62.8%
76.1%
63.3%
99.9%
-------
SMOKE Totals (2007aq_07c 19apr2010)
State bfam / voc
Puerto
Rico
Rl
VOC sum
168549.947
0
78724.47379
104181.5421
472863.9223
91191.03732
83751.66932
12289.79614
3917.144412
484430.62
261449.3284
0
138766.0408
257263.1126
181846.3475
74932.88837
121802.4986
103053.3971
142756.1928
47737.4209
110143.8293
143421.372
238499.4632
102122.7315
148790.8277
161739.3631
29958.49236
40138.7185
21124.15113
37354.50828
131451.7232
200104.8218
410378.8558
231543.1069
21726.09009
305394.5664
199867.1122
169050.6517
291017.7685
'
16526.0837
154139.7189
18211.51169
150886.5771
710828.334
86481.67817
VOC diff
1.0%
3.7%
2.1%
5.4%
3.4%
-9.4%
Table B-8cii: All Non-Point Emission Sources—Percent Change between EMF and SMOKE Calculations
-------
SMOKE Totals (2007aq_07c 19apr2010)
VT
Virgin
Islands
bfam / voc
11.7%
VOC sum
14042.50938
•
172741.7695
15593.1067
59617.84381
161422.7479
142006.2588
VOC diff
-3.4%
5.5%
-21.7%
-------
EMF Inventory
AL
ACETALD
483
BENZENE
1747
FORMALD
935
706801
121991
728024
465717
2478103
624943
389848
119471
44417
2470638
1462176
135857
210926
1542724
967516
489531
388341
549790
203948
682370
88388
1588827
854121
446088
979163
164636
265502
214179
171892
969444
343597
2014449
1194006
120204
08292
626169
478592
1620133
128109
92935
298207
16076
147751
29058
233369
715274
74353
14258
Table B-9a: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—Pre-SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
EMF Inventory
VA
WA
WV
Wl
WY
TOTAL
ACETALD
685
506
169
790
94
28177
BENZENE
FORMALD
1166020
835349
295749
796259
131350
37903749
574
120498
-------
Table B-9ai: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—Pre-SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
-------
Table B-9aii: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments-
Criteria Air Pollutants and Hazardous Air Pollutants
-Pre-SMOKE:
-------
-------
AL
942.2373948
0
963.3178882
521.9217035
4557.627243
822.1792799
611.1850587
173.5029168
62.14311163
3019.553076
1685.637312
978.4642617
0
1115.097944
635.5328217
3193.670894
676.4601015
322.3536661
146.7427473
43.02159844
2534.453743
1889.01664
1794.898908
0
2077.555823
1190.744688
5619.169925
1923.261949
1110.154399
302.2466049
106.9915497
6589.191074
4016.894112
7887.040979
0
8114.669155
4887.411549
23639.6255
7161.787809
5308.791882
1407.476244
518.2962611
26630.73015
15694.63171
704224.6128
721465.487
467026.7064
2463593.288
611367.8866
393802.1051
120523.0764
44607.53952
2465414.187
1464939.497
3900.384047
0
4051.801355
2427.151379
11766.40865
3474.016904
2516.614273
686.725868
249.07238
12899.34418
7743.588004
1214.942105
0
1249.640178
752.9288326
3640.633161
110:
817.342733
216.8280691
79.84603278
4102.590636
2417.832803
MD
MT
OK
251.7376274
2395.248984
1556.212026
749.0177691
509.9895387
856.118709
731.3193641
236.2618517
993.0380562
990.8576003
2031.016777
1308.873537
617.5949695
1318.963211
176.7713359
436.9908297
267.7224183
227.2870346
1378.095643
473.1023987
2515.529011
1161.237876
195.4201288
2049.039187
747.6316624
557.2292968
1834.730922
148.7142772
746.1538888
200.6162683
1249.649469
4039.123059
426.3605952
98.92364477
260.8579052
1958.302718
1440.005038
501.6648254
452.3318312
992.4728852
832.4771372
226.6809078
727.8884654
773.1339746
1749.196538
859.1061611
734.0772472
1304.194599
232.5246623
365.5088776
203.9829836
175.6727088
763.7651036
563.9320715
1422.746273
1262.759243
139.106548
1804.610796
728.7226681
514.3833528
1586.512557
75.34539932
837.0035897
153.6414711
1272.157265
5211.788513
359.5423431
65.66606377
671.0689926
3879.114234
2346.671955
1188.493064
1098.995472
1599.360383
1401.437592
561.5596648
1999.662424
1754.794044
4717.810675
2190.946843
1137.031312
2644.157596
513.6727491
699.1491078
668.6888079
443.8903947
2467.397899
1010.436382
5208.971743
3012.063421
309.5962271
3976.736819
1556.4803
1682.862856
4249.830038
271.8868308
1869.969895
323.3745516
2529.771169
6811.823614
1211.369971
230.4631019
2333.627301
18752.33537
11185.40281
5735.332405
4390.553465
6724.496603
5844.763463
2294.059746
8607.211576
8315.579364
18749.76897
10112.11975
4818.306065
11119.84554
1763.025524
3184.38158
2612.445804
2036.977192
12187.69601
3764.334724
24546.37046
12149.73511
1445.711024
17434.72321
6472.376537
5127.51514
18219.7814
1304.354505
7503.832969
1492.957137
10833.19003
28985.21299
4357.089776
1005.757042
210977.5547
1541062.811
967169.9151
485247.6262
385758.3954
613185.8287
552039.7959
204475.6118
687316.0088
690604.2422
1600665.256
843462.6927
446441.4794
977194.1262
165563.6084
262120.7651
213407.2361
172002.4128
978801.5577
341714.1531
2037900.684
1203892.429
118783.3182
1618628.197
622430.6816
475923.9615
1636989.117
109961.8974
756131.9665
121581.1711
1092851.082
2638966.072
390181.2253
87340.19669
1145.21614
9161.500759
5557.292484
2770.273918
2141.463303
3380.713883
2924.682115
1116.038872
4143.916716
4026.779578
9086.308235
4875.885924
2427.188566
5478.623695
877.3915333
1567.303497
1253.136169
982.0335391
5781.846582
1894.758772
11607.33722
5927.659324
702.5879042
8508.749563
3174.9584
2497.118803
8790.008033
615.8143233
3679.346459
728.8712566
5333.245854
14869.17286
2095.443333
477.7708551
359.506346
2887.671484
1722.245203
883.0440203
676.2694444
1035.760767
900.4133712
353.410816
1325.981208
1280.997883
2888.172283
1556.913829
742.2829548
1712.705989
271.5876895
490.2853705
402.2862636
313.8059468
1876.912582
579.8310797
3780.424014
1871.724294
222.589889
2685.393111
997.1002243
789.737753
2806.801424
200.9363037
1156.001412
229.8640565
1668.904204
4465.226538
671.1580037
154.9416383
Table B-9b:Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE
State
VA
WA
WV
Wl
WY
TOTAL
ALD,
1378.740066
930.6832422
333.1656138
1224.567329
165.2489771
50,868
ALDX
1157.576857
947.6745937
293.3183826
827.4453024
203.0355958
45,516
BENZENE
3074.287077
2748.796764
782.4373553
2079.705732
41 0.2282243
100,066
CH.
13284.14193
8577.856105
3206.320198
9897.113627
1416.63676
423,043
CO
1180486.673
827175.9855
298368.191
796823.901
130153.5457
37,940,746
ETH
6407.226475
4206.042247
1551.346833
4766.801428
71 0.2375348
206,957
ETHA
2046.48492
1321.325376
493.9488154
1523.991466
218.2393883
65,160
-------
SMOKE
AL
329.3879081
FORM
1514.009071
HGIIGAS
0.00060705
HGNRVA
0.006372048
MONO
1279.35603
995.7585538
0.413039965
1899.760154
0
7306.347958
1091.250517
1479.378565
1.009973109
0
GA
1674.096908
952.9703801
8412.154406
1240.987947
807.3968998
258.600744
87.50081402
4532.737266
2950.071126
0.000644854
0.006730651
0.000343716 0.003614328
0.103840319 0.200519443
0.00048818 0.005139131
0.000341884
0.003635632
9.84E-05 0.001037173
4.13E-05 0.000437659
0.002139286 0.022595095
0.001120638 0.011739551
1597.611319
754.360799
4787.27907
1028.77253
579.5070553
193.3665144
70.64629684
3874.335558
2490.29069
1017.695729
601.1118199
3783.737699
813.7495291
548.0320187
173.0918437
66.66280177
3645.508486
1911.110706
0.359535488
0.238992419
2.060002311
0.241580652
0.099163354
0.070755448
0.030591436
1.850393621
0.749926867
MD
NJ
NY
UT
3606.361259
2795.540782
1476.261614
369.8888672
625.8254011
0
0
0.931137388
169.6641799
916.2412371
2490.109656
0
205.270764
39.92444029
896.5673165
758.1151789
0
2079.450277
296.1842107
3164.256973
°
326.2394204
484.995018
0
557.5392069
122.8800481
19.83863315
0
386.4343156
0
367.7109135
236.6793586
431.6924054
3425.122103
2197.03904
949.0234028
783.4662671
1426.623278
1196.467314
395.7480231
1487.084625
1456.783701
3164.926326
1661.183471
1024.706221
2101.810959
347.8393957
597.2634729
417.5196831
343.8391268
1851.413115
797.9905971
3564.898229
2110.727968
249.4129634
3055.86306
1181.144029
878.0804787
2991.027652
194.0500854
1346.16812
267.3469583
1994.742312
6862.680455
708.4153209
149.963896
0.000145231
0.001118062
0.000735096
0.000330743
0.0003086
0.000504998
0.000465876
0.000152283
0.000591471
0.000594513
0.001065599
0.00057078
0.000427492
0.001529186
0.011761287
0.007722511
0.003478017
0.003240367
0.005282118
0.004892423
0.001593359
0.00624264
0.006280758
0.011181485
0.006002381
0.004464026
0.000722901
0.000114669
0.000200301
0.000206163
0.000138547
0.000821267
0.000280292
0.001555109
0.000881906
7.99E-05
0.001139588
0.000489418
0.000349186
0.001131935
9.41 E-05
0.00053194
9.14E-05
0.000719016
0.002407869
0.000284139
7.41 E-05
0.007592718
0.001195896
0.002081983
0.00219148
0.001456303
0.00872825
0.002931221
0.016536168
0.009244208
0.000834643
0.011988458
0.005142344
0.003682776
0.011931123
0.001004808
0.005586926
0.000953265
0.007496709
0.02514764
0.00300052
0.000780123
337.8609426
2536.641461
1689.739139
740.022942
665.8609234
1198.547688
1000.531121
345.8297935
1162.688056
1104.97205
2459.901286
1247.582992
914.5865593
1654.279418
301.897551
520.0317684
345.755889
281.2930386
1368.93095
717.1013998
2549.949869
1925.144447
198.7622231
2454.269301
1024.885197
735.5853238
2371.590666
127 8727439
1162.097962
231.38341
1834.370459
5726.569569
581.849641
113.7471892
266.5959427
2049.80802
1216.321819
598.4269276
517.0303395
805.9667422
789.9607667
252.7873556
1011.631525
988.8235923
2096.826976
1037.151898
651.4749332
1276.873681
194.2170551
345.5780534
305.7338177
233.5934823
1358.665367
465.313701
2646.308425
1464.789364
145.5200221
1974.402438
831.9805862
576.4865336
2060.562908
164.9295092
932.1135288
156.983776
1349.497918
3946.716199
495.0245927
115.3918864
0.088994449
0.501544525
0.257249782
0.111125611
0.179892878
0.275521399
0.377398769
0.076640003
0.379083747
0.373315712
0.649223678
0.178617858
0.308841091
0.39453395
0.054647528
0.071367736
0.089464619
0.081717996
0.394112822
0.174256346
0.710808355
0.57173958
0.022243853
0.610052995
0.370940062
0.170939351
0.688110682
0.074381908
0.386878879
0.02919766
0.560173874
1.839671522
0.16272117
0.041569041
Table B-9bi:Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE
State
VA
WA
WV
Wl
WY
TOTAL
ETOH
0
387.6578705
0
2020.021903
0
38,908
FORM
2247.55933
1531.327156
537.6376255
1648.121898
295.0654581
80,302
HGIIGAS
0.000896188
0.000581338
0.000214085
0.000612411
9.47E-05
o
HGNRVA
0.009469588
0.00609371
0.002250424
0.006436465
0.000986334
0
MONO
1756.197704
1331.065925
459.024862
1286.361096
260.364665
63,381
IDLE
1560.817798
974.6506666
371 .2897295
1044.310654
162.3189671
50,993
ISOP
0.582525937
0.310443164
0.132541726
0.223759124
0.052252413
19
-------
AL
2799.699291
0
2993.906374
1551.672857
36674.54548
2267.506515
1551.037033
447.252757
188.1530658
9931.017364
5110.013119
143927.5415
0
179731.5186
84865.59643
538569.1842
115736.8608
65194.50761
21753.71907
7947.701717
435862.6366
280157.6487
14712.59361
0
18372.50185
8675.149611
55053.81098
11830.88541
6664.324392
2223.713306
812.4315162
44554.85089
28638.32824
159919.4911
0
199701.6318
94295.10684
598410.2743
128596.5187
72438.33906
24170.79889
8830.77953
484291.8231
311286.2676
34.85143256
0
41.44150088
22.94626495
115.4412876
22.5499204
8.89352111
4.937971064
1.297772588
80.60850702
66.78067127
4677.390417
0
4819.795575
2907.902289
14157.8169
4151.21795
2999.389685
826.0437715
301.3126979
15623.82276
9286.957781
MD
MT
OK
656.7145996
5120.352076
3386.365261
1504.662721
1424.475311
2332.836119
2158.409737
697.5335637
2690.600426
2769.696439
4867.233184
2594.477563
1985.669229
3290.548814
529.2934901
925.9558505
958.6311684
639.2873832
3771.756823
1293.835944
7072.771026
4010.967686
367.581144
5284.937224
2255.673438
1587.309203
5134.760358
437.0155146
2426.477093
422.6684148
3286.923519
11259.36268
1309.325346
341.3735916
38009.34248
285372.1349
190095.6903
83252.58611
74909.35277
134836.6016
112559.7793
38905.82915
130802.4206
124309.39
276738.7728
140353.055
102890.949
186106.4468
33963.48892
58503.54326
38897.29431
31645.46872
154004.7604
80673.89806
286869.3232
216578.6734
22360.75147
276105.2608
115299.555
82753.32953
266803.8472
14385.67616
130735.9492
26030.64135
206366.6725
644239.3291
65458.04821
12796.5402
3885.400191
29171.37352
19432.00067
8510.263896
7657.400414
13783.29088
11506.10613
3977.040206
13370.91581
12707.17912
28288.85915
14347.2055
10517.74409
19024.21373
3471.823117
5980.363564
3976.173783
3234.867915
15742.7172
8246.66176
29324.43274
22139.16543
2285.765285
28224.09688
11786.18195
8459.231969
27273.2811
1470.534786
13364.12835
2660.909651
21095.27135
65855.55186
6691.263689
1308.090746
42232.60361
317080.1499
211217.4301
92502.87295
83232.6141
149818.4402
125066.4166
43228.69915
145336.0245
138121.5412
307487.5333
155947.8435
114323.2797
206784.94
37737.20959
65003.9386
43219.22398
35161.62967
171116.4085
89637.66122
318743.7058
240642.9833
24845.27898
306783.6269
128110.6222
91948.14682
296448.719
15984.08369
145262.1755
28922.93441
229296.3143
715821.4505
72731.16154
14218.37813
9.086994289
68.16667574
53.41352952
16.6013029
15.37118831
37.30626174
30.45663811
7.605141666
22.60223949
25.0551863
57.51828089
28.12537773
27.30772529
46.47425308
8.541731474
13.19929863
6.3578868
5.532322261
20.68801925
21.19033751
36.40803886
42.5726472
4.769357995
61.76321292
25.02617953
17.47303937
50.35027517
1.76934119
28.79966666
5.378713312
44.49743782
200.9341181
11.1827024
1.760948858
1371.287436
10899.52072
6574.935558
3291.613707
2564.877731
4023.919463
3513.600687
1336.897158
4989.7817
4841.845735
10885.59968
5793.585432
2911.561738
6535.23896
1044.979992
1856.243674
1496.881301
1180.825453
6934.503391
2258.526353
13928.82837
7124.060122
833.2830326
10172.12943
3822.385988
2983.602422
10559.33401
747.1176978
4422.912949
864.2308216
6406.021838
17762.82046
2515.974947
576.4691163
Table B-9bii:Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE
State
VA
WA
WV
Wl
WY
TOTAL
MEOH
0
0
0
0
0
o
NH,
4078.467827
2678.632211
972.2855685
2819.172748
440.5676682
163,299
NO
197572.1954
149744.9004
51640.28052
144715.6421
29290.97637
7,130,325
NO,
20196.27118
15307.26958
5278.783507
14793.15658
2994.192986
728,878
NO..
219524.6643
166383.2359
57378.08889
160795.1598
32545.53402
7,922,584
NVOL
36.45848959
33.02776951
9.465409329
26.67622266
7.572618863
1,566
OLE
7711.898193
5029.299114
1864.680476
5678.872948
846.4004532
247,908
-------
AL
37483.64422
40166.31708
22539.16006
149019.6724
1199.04138
21229.67839
6413.358756
2444.335645
134323.5631
71445.98277
31.10921234
0
35.9635102
16.44939632
11288.65868
25.41969664
16.34035649
5.545316225
2.510967113
118.859385
60.43279265
3.28E-05
°
3.68E-05
1.82E-05
0.05371079
2.56E-05
1.60E-05
5.07E-06
2.02E-06
0.000108219
6.18E-05
1790.482702
0
2212.51512
925.7010487
28212.73189
1494.455344
932.2017101
343.4353417
163.5796733
7243.94886
3672.871781
447.736485
553.9933317
231.0127325
21196.02052
374.8853281
235.9599753
86.40156654
41.42775201
1829.938793
918.1671388
1342.746217
0
1658.521789
694.6883163
7016.71137
1119.570016
696.2417348
257.0337751
122.1519213
5414.010066
2754.704642
297.4809458
0
373.3030753
152.0042341
3880.107274
253.6667837
162.7838252
60.09739888
29.57760104
1268.895136
619.3472732
MT
ND
OK
9972.167107
79274.25029
48166.31593
23332.67771
19533.65119
31055.3216
29633.38121
9391.688544
37247.24116
36632.35155
78453.94626
40296.17874
24525.23118
8606.054736
51340.71269
17884.26911
99003.93032
54381.8692
5651.105741
'288
30916.46685
21993.65891
76138.79351
6006.562582
34679.8096
6166.753012
50288.80735
150408.6117
18481.10927
4213.830253
7.935452416
63.35706377
36.87990223
16.52379162
15.34147809
25.2202683
23.65103237
7.147208893
30.55147858
32.03768779
60.46144789
29.19993232
21.0031956
6.933033725
43.09129318
14.09055694
77.07235779
44.99228019
3.776901294
58.28382976
24.49284424
17.96209979
58.65941743
4.458727823
27.61306459
4.266566577
39.1070463
131.3703647
14.55381229
3.032899353
7.59E-06
5.90E-05
3.94E-05
1.75E-05
1.66E-05
2.82E-05
2.50E-05
8.49E-06
3.02E-05
3.00E-05
5.77E-05
3.02E-05
2.43E-05
48848.12098
7375.706211
13715.58343
12020.27981
37.61217976
5.31752465
10.74658862
9.479647371
3.88E-05
6.60E-06
1.19E-05
9.71 E-06
7.37E-06
3.87E-05
1.57E-05
7.29E-05
4.83E-05
4.51 E-06
6.01 E-05
2.62E-05
1.79E-05
5.86E-05
4.19E-06
2.86E-05
5.24E-06
4.14E-05
0.000136667
1.44E-05
3.90E-06
488.1371333
3987.333176
2098.092919
954.188341
865.2295684
1427.403251
1359.770317
381.4737615
1823.636899
1933.586254
3775.401214
1709.888694
1145.861123
2242.570931
281.9756093
632.2970922
515.2434553
393.053301
2591.690814
804.6545756
4461.405406
2593.199279
202.9179079
3380.044311
1388.001335
1065.627356
3478.335923
252.5678988
1645.932136
227.7264439
2344.968348
7898.671386
861.4670686
146.6364548
122.5294138
1000.56408
524.6215879
238.5255779
216.4610249
355.3233852
340.5418362
94.77781974
458.5613061
487.3731215
946.6991784
427.7562001
285.1366744
560.8669274
69.75831887
157.2293238
130.1765285
98.45095201
656.5883175
200.4247327
1130.142024
649.2226668
50.37677761
847.6883622
347.5964078
267.3596389
875.2858325
64.10150248
411.91209
56.4494166
586.9036743
1968.005985
216.785511
36.79372849
365.6077195
2986.769096
1573.471331
715.6627631
648.7685435
1072.079866
1019.228481
286.6959417
1365.075593
1446.213132
2828.702035
1282.132493
860.7244483
1681.704004
212.2172904
475.0677684
385.0669268
294.602349
1935.102497
604.229843
3331.263382
1943.976612
152.5411303
2532.355949
1040.404927
798.2677168
2603.05009
188.4663963
1234.020046
171.2770273
1758.064674
5930.665401
644.6815576
109.8427263
84.21307065
691.4218
346.8014099
159.1939803
142.6294786
230.5184849
225.6864468
60.11303251
314.615007
336.7181921
650.494269
287.5182133
182.4673438
377.5685855
43.19403969
102.7257137
88.07186924
65.44297789
460.8546517
130.4404609
786.9926938
430.7580025
31.80648567
568.7141705
230.099389
182.0345088
596.4061815
44.66220969
277.3770579
35.22281321
389.3578186
1306.182067
148.1578171
23.39955511
Table B-9biii: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE
State
VA
WA
WV
Wl
WY
TOTAL
PAR
57531 .58697
36824.5146
1 3726.29969
40164.85654
6155.433537
1 ,930,923
PEC
45.35825614
32.08968402
9.950720746
30.80659579
4.384374631
12,730
PHGI
4.52E-05
3.18E-05
1.14E-05
3.26E-05
5.51 E-06
0
PM10
2669.307954
1978.057149
542.0818093
1747.399247
233.7229126
113,521
PM,fi
672.236842
494.6486014
135.5908267
437.6390206
57.79339561
42,594
PMC
1997.071112
1483.408548
406.4909827
1309.760227
175.929517
70,927
PMFINE
459.4537393
336.6282294
88.28853663
290.8102614
35.6103863
18,340
-------
IN
MD
MT
OK
4.794340074
0
6.586587631
2.543611942
24.56561396
3.577488495
1.491846206
0.696471657
0.269420251
13.9455465
10.077314
0
1.123615911
9.310482096
5.62008587
2.497336265
2.374675177
4.492605698
3.654690388
1.266222435
3.991238612
3.84987362
9.266864421
4.347716067
3.747659298
5.865452471
1.073860348
2.175094275
0.871644703
1.019204903
3.913849766
2.537350485
7.077804307
7.193654326
0.703576558
8.370152174
3.672432855
2.460923406
7.883085699
0.315372642
4.315293793
0.844891505
7.137413097
24.25058406
1.867395515
0.395780221
82.99881369
0
97.83752046
43.54698016
5849.242199
68.49887608
44.01496784
15.24850444
7.056370751
325.6044586
163.8934691
0
21.70612609
174.5261638
98.01853139
44.16111047
40.66932213
66.60363476
63.06982258
18.54041359
82.9522696
87.42417456
165.9511012
78.43692951
54.85698386
101.4972724
13.69586325
28.66917387
25.12623511
18.44245859
118.097539
37.31742533
208.8355038
120.0719014
9.800109019
156.2298568
65.08242486
48.58161323
158.778641
12.02573389
74.52624151
11.02528977
105.3246934
353.6994355
39.40595535
7.73222033
31.35317306
0
40.30263805
16.46850995
153.4467575
23.72248318
11.32897954
4.81387534
2.013392858
102.6342675
64.41628984
0
7.551148773
61.94857047
37.30165854
16.14935928
15.44607098
28.48839156
24.47984413
7.710942311
26.45131236
27.3431934
60.52549601
28.25340895
23.06149187
38.32343723
6.477030925
12.9127533
6.627132062
6.613276895
30.63098387
16.03893903
50.16366441
46.20682838
4.289705077
56.09035302
24.24931684
16.32049361
53.55850692
2.639458435
28.08043222
5.089855542
45.97670288
152.5035329
12.80053076
2.233273478
1352.348533
°
1194.069577
771.8735667
3421.217393
1192.311107
606.3122613
213.9497245
89.65147881
5005.625227
2037.283915
0
415.793732
2640.834755
1755.632309
807.3289889
745.4053407
1111.421798
1075.322767
359.3360225
1324.380106
936.58382
3230.618743
1167.952003
932.7123248
1926.524644
320.3724224
516.8315931
302.2463096
244.5743508
1465.968966
706.3670021
3094.014163
2173.906597
194.6585413
2963.091243
1180.628516
704.31803
2589.862836
130.4895438
1324.841849
225.6338542
1930.862515
5315.654304
776.4321112
147.8165463
52.23133028
0
62.10732765
34.3891686
173.0103421
33.79520767
13.3285063
7.400447547
1.944950825
0.806353
100.0830059
0
13.61859258
102.1602521
80.04940505
24.88008397
23.03653349
55.91015851
45.64483323
11.39766697
33.87359119
37.54973049
86.20157788
42.15107324
40.92566335
69.650282
12.80136426
19.78161745
9.528484955
8.291241239
31.00479116
31.75767176
54.56435997
63.80327124
7.14775048
92.56315122
37.50632681
26.18655446
75.45862692
2.651682214
43.16155809
8.060986765
66.68732189
301.1368754
16.75923414
2.639107784
Table B-9biv:Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
VA
WA
WV
Wl
WY
TOTAL
5.666254182
5.240806561
1.525535916
4.531354354
0.926767528
236
122.6648082
87.52527015
26.10775674
81.9489684
11.29220049
9,738
39.09378418
33.1646113
9.718276647
29.54184064
5.579666661
2022.427972
1282.289625
510.7523039
1355.428429
266.178835
66,060
54.64003085
49.49841546
14.18564344
39.97926548
11.34890172
>,347
-------
AL
GA
9873.370366
°
10594.13351
5997.100032
37352.41481
8514.497862
5894.155172
1715.691059
645.3692916
34548.43791
19098.24538
22.27922456
0
26.49221291
14.6686987
73.79748987
14.41540002
5.685287222
3.156671309
0.829621041
51.53009142
42.69056306
5992.119393
6713.347969
3848.258381
19347.25769
5757.12402
3604.389279
1012.279941
358.3756636
20583.46301
12549.21893
10033.27702
0
10000.8562
6187.384613
34100.38129
8377.
5597.713747
1776.092872
668.5606919
35606.83911
19741.4697
MD
Ml
MS
MT
2730.756242
21640.85824
13051.97952
6422.932167
5262.003976
8276.868945
7610.139767
2620.779332
10163.96243
9922.519642
21618.6829
11115.12807
6290.123309
13259.50887
2032.562491
3729.526159
3295.919938
2372.445659
14121.29459
4714.69679
27641.92356
14636.14443
1557.153194
20352.69268
8116.446069
5985.438032
21064.45742
1601.116929
9217.752733
1687.870158
13349.93177
38361.61972
5075.290955
1165.103686
5.809020435
43.57645661
34.14525783
10.61262883
9.826246419
23.84866034
19.46992238
4.861675727
14.44875582
16.01688212
36.76940322
17.97948929
17.45682157
29.70933006
5.460430008
8.437868071
4.064405712
3.536627099
13.22505728
13.54622671
23.27426914
27.21530135
3.04888143
39.4831262
15.99824175
11.16988919
32.18703203
1.131074936
18.41063288
3.438424662
28.44565684
128.4499117
7.148677279
1.125712789
1964.005923
13288.00069
8223.575249
3993.514732
3419.138904
5344.75466
4656.14077
1739.9467
6284.954791
5846.56980
14409.62163
7161.55098
3845.897579
8552.44327
1520.87454
2363.074991
2037.431819
1438.555819
8150.608655
3193.285183
16623.11222
9388.689731
1027.159409
12900.6864
4990.88494
4636.086522
13334.29889
879.9447066
5872.775673
1081.620301
8248.977876
23748.03215
3507.68643
712.4783446
2836.029546
21070.16304
12390.773
6131.470845
5304.242591
8250.502288
7800.132817
2732.5338
10580.65782
10240.11422
22170.84465
10686.49735
6438.7042
13225.0776
2093.323838
3500.000279
3062.260756
2472.664889
13906.75353
4715.395462
27730.25828
15172.52218
1512.388232
20568.83862
8374.332468
5997.314702
21919.14219
1657.101437
9529.690103
1606.371347
13788.27998
38935.92906
5192.672289
1218.076012
Table B-9bv:Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—SMOKE:
Criteria Air Pollutants and Hazardous Air Pollutants
-------
15694.59203
10027.49363
3760.706102
11095.41712
1674.489269
516,552
23.3066371
21.1134974
6.050909045
17.05317512
4.840889532
9707.189704
7692.419181
2418.246078
6889.719858
1232.127861
322,092
16332.84099
10261.65159
3914.382646
10811.03276
1730.764668
517,95
-------
SMOKE
State ACETALD BENZENE FORMALD
1.94%
1.62%
0.29%
1.44%
1.10%
0.49%
0.83%
1.69%
1.66%
1.84%
1.43%
1.21%
1.38%
0.60%
0.47%
1.50%
0.01%
0.66%
1.13%
0.79%
0.78%
1.12%
0.97%
1.00%
0.87%
0.59%
2.13%
0.84%
0.35%
0.45%
-0.10%
1.54%
0.89%
1.15%
0.00%
1.07%
0.59%
0.57%
1.71%
0.47%
1.78%
-0.08%
2.23%
0.28%
Table B-9c: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—Percent Change
between EMF and SMOKE Calculations
-------
SMOKE
State ACETALD BENZENE FORMALD
-------
Table B-9ci: Onroad (MOVES-calculated) Emission Sources Not Subject to Temperature Adjustments—Percent Change
between EMF and SMOKE Calculations
-------
-------
EMF 2007
State ACETALD BENZENE
FORMALD
HGIIGAS
AL
AZ
Puerto
Rico
Rl
78
1281
286
1168
835
3941
864
509
139
36
5269
1848
149
460
1714
976
675
469
898
1359
498
909
865
2737
1348
832
1375
278
332
482
371
1299
310
2927
2058
220
1854
875
866
2077
632
63800
388196
1298053
152506
Table B-lOa: Non-Road (Off-Road) Emissions—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air
Pollutants
26770
34790
25742
243321
32312
16566
2790
110283
52339
351204
807992
413847
186591
389426
78823
117616
166597
107694
509231
96206
967958
651150
71079
759070
252576
250425
726579
-------
EMF 2007
State ACETALD BENZENE
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
FORMALD
HGIIGAS
479580
412660
106319
483093
46801
17902244
630
593
130
832
89
34430
40605
39136
7552
48799
4958
2010786
-------
6760
42006
11299
54487
146346
25048
Table B-lOb: Non-Road (Off-Road) Emissions—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
-------
SMOKE (2007aq_07c 15mar2010)
AL
524.386291 4
°
539.9112926
383.949921 8
4877.520087
452.4720377
276.6127133
85.90755098
30.23922015
2240.762539
845.2694157
396.8900221
0
500.7874055
300.5735368
3450.261 339
416.7458083
214.491301
64.76046778
36.80320667
1773.844543
725.9215348
BENZENE
1354.379629
0
1212.785005
885.7275051
4010.905072
898.4014834
556.4442733
148.1241024
37.70844314
5447.774993
1947.849387
6713.623933
°
5592.238221
4713.207981
14464.42997
4886.727175
3714.029462
968.829534
163.8578398
24935.4578
9112.073945
316477.4807
0
393174.4311
211938.0704
952903.0438
312631.3819
197786.7843
54670.88074
15042.56411
1 425844.458
607014.8914
3225.874207
0
2725.38276
2426.303411
8647.169623
2466.881507
1 760.35566
471 .9354278
86.55051348
11947.6824
4455.582698
MS
MT
229.515256
1209.989476
673.0901581
583.3584185
397.8774957
431.1099143
568.637816
229.6094302
490.839381 2
504.6643876
1309.861456
1043.940527
361.4116606
677.2496646
177.4779234
309.2467299
239.5681571
181.6239138
712.1461209
140.8406557
1367.152263
877.0459133
275.6741 752
1107.913161
398.2630088
376.8599966
958.0552258
193.4641863
1005.49966
535.8802788
491 .9657471
344.3517452
364.3114196
409.7155352
179.4354626
372.0318876
378.1158324
1 005.778272
764.9703183
265.3510203
542.9863874
153.3916647
280.7039562
244.7894237
136.7601253
536.3757431
122.4354633
1079.761706
742.781389
240.4909754
854.3399779
319.631568
323.0943201
759.5366147
477.5649553
1868.605912
1093.043757
722.3648146
504.1493753
961.253488
1418.355043
519.3839165
947.0590425
937.82229
2921.398902
1432.87967
881.5262745
1450.963014
284.5885344
351.8537823
493.6251774
394.4710693
1381.519193
320.4336609
3091.221964
2188.891191
225.0497235
2031.062983
916.7188828
911.4933305
2230.545582
3418.494098
11344.30253
6708.268249
5550.880613
2466.187373
4962.449596
7516.825718
4868.590997
5594.752386
6210.250556
22001.00831
14124.90355
4594.769111
7380.161524
1811.476678
1907.063955
2308.089002
3152.202278
8869.814318
1562.895713
19101.72664
10150.59639
1538.811607
11763.68517
4292.18527
5001.603192
12030.6525
121563.8509
704312.84
385301 .951
241310.9411
1 90994.2988
241704.6112
311373.5006
1 31 764.5698
334873.2618
351523.9066
815117.4133
416509.5865
187982.1967
389955.1563
79098.40118
117384.1477
166183.4797
108428.3053
509372.5619
970328.739
651588.1479
71016.67429
758817.4947
1725.079208
6059.137533
3527.471398
3292.659396
1714.871669
2498.043692
3627.57952
2279.448071
2693.815755
2947.268966
10492.24543
7157.052957
2275.779099
3861 .702781
1095.024706
1399.008686
1142.794772
1478.451087
4213.933217
771.2314376
9124.836028
4959.641517
1284.203211
5877 675885
253159.9793
250788.1581
727162.657
2247.85666
2456.06436
5814.030479
SD
76.38276294
471.0158899
214.9201571
613.679475
1970.190716
249.1108256
56.90439542
383.0507189
183.2395912
487.2375433
1 696.347354
220.6677223
146.4998117
1199.553601
207.2322151
1 504.558557
3998.686348
579.21151
968.6938968
5592.93134
1466.2587
7217.71142
18250.13923
3656.473951
54411.08008
328798.3776
63825.69109
389264.469
1 297863.327
153123.324
458.8375974
2697.943778
1069.204754
3544.791 596
9287.71829
1756.685418
Table B-lOb: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 15mar2010)
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
86.39450189
673.9306942
610.1840216
168.1858031
968.8894037
87.44380496
32280.38141
68.99245845
0
560.9477469
526.8294036
131.2574239
698.3549945
74.81200249
25617.6712
BENZENE
190.7382983
1472.650582
1400.108197
438.9873689
1824.504872
179.3542537
60600.03104
7435.391961
7927.073847
2478.630686
16442.65278
1435.108355
340019.1942
52841.88084
0
479766.8071
413412.5876
106815.9287
487808.5113
47142.35725
17946550.85
3625.905753
3896.518113
1184.286928
7921.13572
709.0408399
171166.5404
-------
SMOKE (2007aq_07c 15mar2010)
MD
MS
Rl
1034.715876
0
862.1621352
725.7429668
2226.132617
753.099621
572.3206306
149.3466951
25.28064555
3844.808769
1404.916296
0
526.4391108
1746.194047
1032.593469
852.738108
378.3292138
764.4394328
1158.325663
750.2387101
862.7645732
957.4845021
3390.082621
2173.683694
707.8126757
1136.385433
278.3004025
292.1309706
355.8493711
485.8183797
1367.349989
240.8967748
2943.823263
1564.761741
235.024686
1812.682062
661.0308186
770.6243584
1854.645457
0
149.349084
862.2095355
238.5090134
0
841.8050433
1.162519192
3616.873127
354.4793561
801.7028898
0.706670743
0.086696745
8.504579322
3.583239741
0
0.678804269
1886.527681
1421.839144
1008.374102
168.3703389
189.2736803
1.650397045
0.651544447
2.950344153
110.579853
299.3211023
2591.097396
1.041649096
382.2819779
17.92831392
427.3396346
439.4032005
0.559888943
989.3332591
94.55417371
1728.625334
3.6244945
263.3081933
929.4310792
1.529977477
347.706488
51.87862365
«
9.526163382
1.830492528
821.5413794
0
928.342043
653.2633284
9542.078206
833.0828054
464.0020781
131.9264459
52.54600888
3402.575317
1400.138809
o
439.5410314
2137.602942
1157.606219
1104.426776
742.5449719
728.7971946
865.0985488
463.0989032
772.8631075
805.0811407
2417.307927
1891.144666
569.3284614
1160.31992
355.3544229
607.0217722
430.7879913
327.7188678
1136.6072
239.6549938
2388.970499
1468.202552
564.8598965
1839.126016
676.6833784
676.9266627
1643.954876
•
119.2040162
757.7326367
HGIIGAS
3.25E-05
0
3.96E-05
2.50E-05
0.093725878
3.48E-05
2.00E-05
5.87E-06
2.35E-06
0.000145003
5.88E-05
1.62E-05
9.47E-05
5.18E-05
4.79E-05
3.14E-05
2.84E-05
3.41 E-05
1.56E-05
3.33E-05
3.39E-05
9.49E-05
6.76E-05
2.18E-05
4.75E-05
1.39E-05
2.56E-05
1.88E-05
1.18E-05
4.96E-05
1.00E-05
9.72E-05
6.09E-05
2.30E-05
8.18E-05
2.86E-05
2.74E-05
6.57E-05
5.19E-06
3.12E-05
HGNRVA
0.000242939
0
0.000268608
0.00016111
0.180987509
0.000232694
0.000158483
4.40E-05
1.15E-05
0.001073049
0.000408085
0
0.000110754
0.000575485
0.000319048
0.000268034
0.000145986
0.000187349
0.000257036
0.000137233
0.000253785
0.000267111
0.000755751
0.000463671
0.000152452
0.000306233
7.02E-05
0.000109499
0.000119138
0.000100045
0.000394767
6.94E-05
0.000768503
0.000428127
8.50E-05
0.000553876
0.000186807
0.000194261
0.000497067
0
4.15E-05
0.000225558
212.5799856
0
275.1112047
203.9704858
1928.408888
255.721808
131.6372916
38.87240018
22.05870284
876.1030136
414.4327023
0
114.6338244
822.3432958
462.8370432
465.5216378
346.2139394
228.6449551
210.787259
60.07008207
203.4655677
216.6858171
528.0587845
504.0418847
159.4543248
388.1375428
137.5092339
293.4116935
138.0810084
59.22815457
302.1451499
69.77036062
578.3294369
435.5096707
281.0337823
636.9271701
225.9836752
191.6872889
439.9148114
0
33.71787552
212.494373
Table B-lOb: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 1 5mar201 0) |
State
SD
TN
TX
UT
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
ETHA
224.5077075
1112.3694
2812.7677
563.4696608
254.3976178
0
1146.470105
1221.535444
382.0326533
2532.001389
221.0304862
52381.11656
ETOH
276.5418518
2.281300265
90.21484879
76.26277736
0.261779915
0
3.047063744
204.0714316
0.621501834
2061.07462
0.226680202
21953.23432
FORM
429.3369109
989.6785401
3244.112621
452.4644358
172.2253118
0
1118.746265
1089.987639
281.0992774
1786.271701
171.8436685
56452.83038
HGIIGAS
1.73E-05
3.97E-05
0.000139782
1.66E-05
5.95E-06
0
4.72E-05
4.47E-05
1.01E-05
6.41 E-05
6.23E-06
9.57E-002
HGNRVA
7.14E-05
0.000279376
0.000911489
0.000121201
4.93E-05
0
0.000337112
0.000317598
7.87E-05
0.000495451
4.49E-05
0.194338223
MONO
200.9117141
293.5105911
1087.542604
108.1265574
29.99930627
• ° •
321.8396261
310.4089289
59.93419424
387.5341226
39.32054809
15944.66432
-------
SMOKE (2007aq_07c 15mar2010)
AL
IN
MS
OK
847.380946
0
733.4901514
556.4704798
2343.140157
579.7941952
412.1138739
118.6738664
25.55729258
3383.082343
1179.151199
0
361.4192051
1314.485038
777.502852
578.8496968
310.6868095
598.3985578
935.9152106
479.0895416
701.4261119
726.5961719
2312.356365
1416.874797
569.1098293
889.1442611
192.4311135
220.9113343
295.5109329
326.3847652
1052.144682
197.11761
2129.472998
1268.726263
157.6281914
1409.248794
537.984418
562.83117
1425.067922
113.0711011
710.3286143
153.3630291
916.708908
2462.960773
403.9901379
1.384294786
0
1.703712714
MEOH
0
0.789360212
4.239325271
1.334377006
0.827719792
0.235102998
0.062563803
6.423917211
2.507110675
0
0.436507349
2.651688044
1.532105833
0.83165565
0.66364217
0.956400368
1.297890657
0.459998844
1.590421626
1.424692521
2.785471701
1.53487064
0.786341002
1.576624017
0.234269668
0.4111236
0.758350028
0.396644544
2.173151971
0.408748296
3.620830199
2.525704039
0.180164509
3.064428311
1.011058128
0.982142549
2.893780341
0.211615008
1.325466208
0.190763497
1.64079484
5.34431476
0.552476765
29.9127048
°
38.55008626
24.9986435
187.0461736
34.02057199
17.70112667
5.384372614
2.614329348
134.2046957
56.4597306
0
15.74904204
97.10375601
52.79319797
50.84691314
35.6361159
27.93806181
31.18470136
12.79773365
30.22132773
30.18169414
83.74612058
65.38654596
20.88401517
47.34509698
15.34428843
29.68685704
18.86268137
10.01649928
43.79114062
1928
86.22764254
58.06324013
27.74610405
79.59364639
28.30212492
25.95056367
59.97620463
4.577838578
29.34623302
20.31688939
37.77400806
138.6602329
15.53210106
23915.22852
0
30950.00382
22946.69792
216946.1296
28768.7047
14809.20048
4373.127707
2481.602013
98561.54587
46623.73358
°
12896.29555
92513.6536
52069.16375
52371.14556
38949.05325
25722.56266
23713.56447
6757.889782
22889.87788
24377.12537
59406.63936
56704.71678
17938.60484
43665.48749
15469.77583
33008.85084
15534.17029
6663.133428
33991.33229
7849.134778
65062.01817
48994.78623
31616.31781
71654.29419
25423.16293
21564.83575
49490.42386
3793.260718
23905.6188
22602.54387
33019.93765
122348.7025
12164.27353
2444.669132
0
3163.775038
2345.662595
22176.70655
2940.803221
1513.826491
447.03062
253.6745713
10075.19358
4765.982148
0
1318.287044
9456.951238
5322.625918
5353.487555
3981.459068
2629.419184
2424.053149
690.8074726
2339.851181
2491.885125
6072.67953
5796.48389
1833.72406
4463.583026
1581.354644
3374.238623
1587.941342
681.1196475
3474.668592
802.3610765
6650.782554
5008.36117
3231.885528
7324.664038
2598.811494
2204.407357
5059.025283
387.7542285
2443.679857
2310.477921
3375.371565
12506.79091
1243.45485
Table B-lObi: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 15mar2010)
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
926.871024
892.0616526
288.2019771
1621.39127
147.7674568
40728.87432
0.179811009
0
2.068646845
1.57986963
0.448038937
1.609143505
0.150941387
71.99807346
MEOH
5.106637268
0
44.59154616
42.34073293
9.008253686
57.66128055
5.85169089
:036.694388
36206.9482
34920.96542
6742.615948
43597.5569
4423.571526
1793774.908
3701.155335
3569.699536
689.2452468
4456.638914
452.1874817
183363.6904
-------
SMOKE (2007aq_07c 15mar2010)
26572.47763
0
34388.89007
25496.331
241051.245
31965.22973
16454.66426
4859.030727
2757.335287
109512.8425
51804.14843
10.08612443
0
17.12232745
6.337406098
131.6149099
13.02835451
6.199354764
1.807667448
1.510430331
52.43189861
22.56815698
3850.710729
0
3252.127247
2722.33372
9247.997284
2840.560931
2103.742493
558.2978085
103.3544492
14440.85525
5297.41769
29803.94931
0
26026.65358
19801.98419
91503.10748
20332.47383
14612.29205
4103.317606
919.2858489
117709.8208
40896.56156
1308.218222
0
1914.086886
1494.570265
7604.993952
1837.588293
670.8615896
238.671952
160.7476963
5801.847
2755.313815
NV
OK
14329.21641
102792.9481
57854.62671
58190.15475
43276.72626
28580.6268
26348.40488
7508.767337
25433.19463
27085.69631
66007.37767
63005.24256
19931.78323
48517.20806
17188.63971
36676.50116
17260.19264
7403.48123
37768.14603
8721.266216
72291.13016
54438.65707
35129.23712
79615.8854
28247.9581
23960.9304
54989.36395
3.881547747
28.39762417
14.5535371
10.05800592
7.831658367
9.820524314
9.098334443
2.782460477
10.85277264
10.76998436
20.08045113
14.78542908
5.657322829
13.21352807
2.555362238
6.054947532
8.899253933
2.806138408
15.46012778
3.728009782
28.5493234
21.88324159
3.749102168
24.37042163
7.75594318
8.699554378
21.03470176
1955.778774
6617.082136
3885.86494
3259.20638
1525.189369
2872.752483
4305.666098
2732.78843
3223.284494
3551.665282
12448.30526
8015.272684
2641.755861
4286.547518
1069.812573
1182.646581
1351.830925
1778.496726
5061.191245
906.1123698
10864.62055
5873.835358
972.1673928
6792.013451
2501.883754
2865.516156
6905.324394
12830.41115
47738.93092
28381.79807
21848.23298
11767.01495
21309.79756
32934.52459
16732.58086
23989.05585
25028.55086
81149.49577
51811.95348
20129.83714
31740.30391
7156.234225
8829.247867
10540.78254
11364.98297
36726.61114
6925.272788
74990.03718
44112.62057
6642.790096
49337.43943
18982.50073
19858.53448
49156.78738
895.7137274
5518.228071
2883.664516
3629.196106
2835.58491
1571.36127
1350.168008
379.0688089
1280.619353
1158.799904
3093.934365
3709.628088
1071.130677
2809.800001
1208.500083
2479.331694
1004.5897
327.4316577
1668.276947
485.2677123
3441.164822
2798.629573
2514.72128
3753.901737
1639.518336
1275.05589
2663.458627
7.46E-06
6.30E-06
1.34E-05
4214.732822
26561 .79303
25113.9335
36688.81981
135943.036
13515.85494
1.574676718
10.99661972
3.037874925
1 3.04681 245
52.93792378
5.842358283
553.4539568
3227.559878
897.1670766
4170.247946
1 0733.56646
2088.156456
3899.705499
24725.21365
6185.646626
32060.09063
86216.36835
14242.20328
168.6879082
1325.953618
1760.093738
1868.504128
7476.479714
738.2217165
9.43E-07
6.99E-06
6.84E-06
9.25E-06
3.67E-05
3.66E-06
Table B-lObii: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 15mar2010)
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
40229.94316
38801.07389
7491.795389
48441.72994
4915.079556
1993083.262
17.20959662
14.41378462
3.094857002
11.96221997
1.469928653
716.8542493
930.8922486
0
4306.101368
4552.070256
1413.474604
9244.082568
816.7714852
196797.5531
5806.328254
0
31936.87738
31238.20353
10042.62989
58047.2864
5243.647126
1447369.976
9.80E-07
2104.055813
2071.599175
401.1431799
2376.395782
303.2377151
102019.674
1.08E-05
1.03E-05
1.92E-06
1.25E-05
1.39E-06
4.89E-002
-------
SMOKE (2007aq_07c 15mar2010)
GA
Ml
MS
2804.340864
0
3604.492654
2731.979729
14597.81973
3350.029389
1485.13305
475.4930709
242.3275953
11559.40935
5314.133
0
1700.821388
9234.094002
4951.941777
5562.161788
4183.180081
2875.611256
2861.856586
1162.145756
2679.015384
2504.662819
7173.953006
6793.904338
2123.479727
4890.507335
1871.620896
3604.090084
1807.033497
873.8674834
3624.757305
915.4891929
7299.3609
5425.480131
3546.523311
7042.356082
2865.266027
2512.355586
5572.780821
2662.492579
0
3438.468708
2609.965242
12756.46335
3200.203299
1409.092415
452.6614048
233.5695647
11000.03763
5065.647345
0
1621.631026
8858.225917
4746.011156
5356.733565
4036.986322
2747.523681
2717.439178
1090.507393
2544.984763
2378.23872
6792.106268
6488.640057
2021.94883
4682.028233
1801.083478
3480.316042
1726.807936
823.6211667
3440.074518
873.2580999
6933.05089
5171.85569
3429.81136
6723.663832
2742.505057
2392.647784
5297.453718
141.8482844
°
166.0239459
122.0144868
1841.356379
149.8260894
76.04063581
22.83166609
8.758030611
559.3717232
248.4856551
0
79.19036194
375.8680848
205.9306211
205.4282229
146.1937595
128.0875749
144.4174084
71.63836318
134.0306208
126.4240992
381.8467377
305.2642805
101.5308973
208.4791023
70.53741762
123.7740429
80.2255605
50.24631668
184.6827877
42.231093
366.3100109
253.6244414
116.7119513
318.6922499
122.7609701
119.7078017
275.3271027
PMFINE
292.138221
0
330.3407562
240.2109081
1117.128136
294.8224455
157.6050145
46.1763605
15.63684023
1132.156499
497.8510436
0
158.0497681
712.8139564
394.8719007
371.0214327
256.5116748
252.153297
296.788854
155.8845924
274.6070413
260.7059012
799.2070543
601.7020376
205.0573526
402.7559394
128.4669896
214.7577752
157.2008163
107.5449593
381.4492733
84.07711922
752.5698645
508.6931449
197.1442888
632.2828074
237.5940205
241.3824092
563.5408317
6.45797285
0
7.037394578
5.357389617
23.61008196
6.34907213
3.756372846
1.016778827
0.353559583
23.20933382
11.06823063
0
3.245319863
16.92204016
9.812519828
8.385921504
6.034116305
5.812396259
6.255000248
3.061332033
5.760390439
6.150283239
17.44768112
12.88988508
4.534337869
9.042860717
2.707549067
4.874512586
3.230171575
2.300086311
8.55790142
1.791157151
16.74544035
1044.870698
0
1174.953528
11.75777862
4.329425972
15.31212421
5.282855757
5.278426892
13.21851089
859.9824722
3968.572277
1050.194919
570.0933339
165.0433434
56.05431395
4006.321118
1781.781959
0
559.3463606
2575.226423
1436.950487
1330.04694
924.8667226
907.1584483
1054.343159
548.7486958
974.8948108
941.5174698
2853.671291
2141.79106
733.3500199
1443.133062
455.9648947
770.1018939
556.3184721
382.9405836
1367.287383
299.0587082
2694.191804
1831.081855
703.3822733
2292.09985
850.1319073
861.8519815
2033.302949
SD
364.5888848
2652.674401
2542.986114
3652.854249
13151.25767
1547.870693
346.286518
2525.39695
2456.182003
3481.112039
12585.83534
1470.513402
18.30236688
127.277451
86.80411008
171.74221
565.4223298
77.35729085
37.72721055
257.6132978
149.940555
345.2821008
1096.766257
158.544623
0.930211258
5.872824617
3.303122406
8.044413984
25.02448387
3.408368525
137.1889027
925.4444042
535.307379
1 244.37855
3939.308616
564.7781981
Table B-lObiii: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 15mar2010)
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
484.2830578
0
4125.21314
3995.210295
958.0740473
5285.956726
606.2195091
191190.6638
457.1588137
0
3929.502573
3808.078692
905.9766662
5011.636349
576.7681541
181302.2037
27.12424412
0
195.710567
187.131603
52.09738113
274.3203774
29.45135502
9888.460063
PMFINE
57.60481026
0
394.0652595
374.9854916
109.6434082
569.5323644
59.67156357
17084.27827
8.648367312
8.206980936
2.30503712
12.42071926
1.207777465
379.5500669
204.8623895
0
1407.754481
1338.987567
389.4372404
2033.17114
210.7891543
61132.03549
-------
SMOKE (2007aq_07c 15mar2010)
AL
AK
AZ
AR
CA
CO
CT
DE
DC
-
GA
H,
ID
IL
IN
IA
KS
LA
ME
MD
MA
Ml
MN
MS
MO
MT
NE
NV
NH
NJ
NM
NY
NC
ND
OH
OK
OR
PA
Puerto
Rl
C
SD
TN
TX
T
10.80746463
°
12.05014336
9.844207742
42.15890056
11.24856892
6.776103661
1.752970012
0.777154605
36.50294901
19.63229606
0
5.27585024
35.03542607
20.71173377
18.08316473
13.98889752
11.03826926
9.884156484
3.743964131
9.103167821
11.06516212
27.8458762
22.62898615
7.876443173
17.29637009
5.443961375
11.25016639
5.46877638
3.403879804
14.50301262
3.063403055
28.37895898
21.69333796
10.23409117
30.06731416
9.977937576
9.079076594
23.93279993
1.752285256
10.51280566
7.537208838
14.90284628
48.25626647
5.560495819
1471.288856
0
2161.174513
1496.162692
1189.162562
1948.726415
772.3138562
261.9764798
190.452179
6710.592874
3076.12974
0
885.2029255
6133.604294
3307.915308
3422.303619
2667.66583
1625.34729
1509.714832
414.3621458
1429.381144
1330.20344
3640.034867
3628.836967
1137.196933
2833.449855
1101.672621
2298.61378
1135.849504
370.4911064
1889.604937
532.4934817
3789.490812
3138.139217
2257.761846
4532.922018
1667.969032
1376.044361
2880.999551
0
196.0485608
1529.110214
1594.872437
2037.787246
8166.032311
798.018775
16.19073882 7812.760037
25.14052976
16.9576392
234.2090873
23.034009
8.668437253
2.978853994
2.211688569
76.01676504
35.22526391
i 0
I 0
i 0
I 0
0
0
! 0
i 0
0
0
0
0
i 0
i 0
0
0
0
0
0
0
! 0
0
i 0
i 0
! 0
0
0
10.13612448
64.76051966
33.4371262
40.34738712
31 .72468603
19.33482339
16.29100714
4.211650526
16.27358759
15.07310848
35.21666969
41 .83254945
12.38157894
32.73322567
13.11808046
27.4889834
13.24600864
3.975293877
21 .72964077
6.165592463
43.78130908
35.33966876
27.05348079
44.74329684
19.13476379
15.56274028
33.42538971
2.197044623
16.88754293
19.01951166
22.96064631
94.11855619
9.341525716
6574.864017
5299.749248
21550.23257
5320.817387
3816.815261
1089.324506
217.5799575
30032.12076
10561.97822
0
3624.678077
12233.4967
7265.781011
5595.945007
2824.416875
5633.38326
8739.928454
4982.610602
6298.86839
6767.665188
23215.2382
13998.88939
5327.172645
8292.51067
1927.362062
2100.443198
2646.520358
3295.136096
9667.743402
5.984588226
0
10.31372794
3.788595322
82.77615872
7.813847939
3.636906212
1.070466999
0.943401081
31.35633785
13.52626326
0
2.327874608
17.13328801
8.71399
6.10760241
4.761089734
5.947469466
5.409849749
1.614137981
6.348899014
6.355798741
11.85053704
8.872297208
3.369403308
7.883654359
1.5508931
3.712488172
5.396455453
1.651261985
9.063274596
1790.804141 2.234522141
20393.81013 16.89515731
11569.23958
1567.463331
12859.43341
4916.920007
5346.693722
13213.18894
^H
1060.276939
6468.054321
1513.483878
8369.912072
21732.96145
3958.48801
13.08283946
2.328103951
14.41878696
4.602596845
5.195140517
12.37213768
«
0.928918802
6.568434016
1.869816411
7.77749793
31.94707987
3.540511254
4468.621427
0
4026.712289
3060.082706
14116.09341
3211.423094
2137.928883
569.5497834
139.6997211
17556.086'
6391.717967
0
1899.975108
7238.022339
4220.53888
3275.528763
1926.138472
3302.60335
4804.472714
2311.138657
3437.567318
3573.232734
11663.39777
6991.316241
2984.635949
4986.423186
1141.011953
1458.932609
1681.378677
1615.313657
5212.839602
1075.370555
11303.01397
7084.336881
1113.708468
7404.27073
3023.782208
3169.872132
7655.440236
^H
555.8592858
3871.6636i
981.3795284
4936.346595
13274.61806
2143.995822
8061.173895
0
6479.3779
5551.492765
19880.22633
5437.629761
3757.041692
1139.528006
220.0142505
189.80531
10995.91213
0
3825.349452
12126.61742
7083.415136
5580.432756
2858.357493
5812.24251
9133.939535
5294.864783
6586.209279
7074.126373
24434.47707
14053.90174
5566.918935
8524.841393
2019.857284
2016.599053
2571.632049
3488.975453
9791.853807
1829.505306
20855.54188
12077.25577
1552.983677
13147.32624
5130.469327
5506.997441
13846.08039
•
1110.556788
'47.128584
1491.684017
8730.839768
22493.26053
4137.187965
Table B-lObiv: Non-Road (Off-Road) Emissions—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 1 5mar201 0) |
State
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
PSO4
1.814774715
0
1 4.97865309
1 4.29947773
3.447800504
20.11634363
1.861943705
686.665844
SO2
200.6628381
0
2349.983752
2243.407217
407.1157543
2660.506466
304.5038284
102703.3013
SULF
0
0
0
0
0
0
0
0
TERP
2.187137496
0
26.83736967
25.53275254
4.975666121
26.21946167
3.490304525
1372.918826
TOL
1 704.275554
0
8373.873919
8513.807586
2742.637058
1 6224.90575
1508.596191
380542.8575
UNK
0.722556522
0
1 0.23476565
8.626347308
1 .822576355
7.049904203
0.88789627
432.3861479
UNR
818.0900359
0
4979.379888
4948.313989
1520.469258
8109.853217
752.3185249
218124.4669
XYL
1807.835238
«
8746.648021
8884.876232
2881.015666
16673.40278
1594.905203
389802.3144
-------
SMOKE (2007aq_07c 15mar2010)
State MONO VOC
0.80%
-0.7%
0.5%
-1.0%
0.1%
-0.2%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
Table B-lOc: Non-Road (Off-Road) Emissions—Percent Change between EMF and SMOKE Calculations
-------
SMOKE (2007aq_07c 15mar2010)
TX
UT
VT
Virgin
Islands
VA
WA
WV
Wl
WY
TOTAL
MONO
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
-1.0%
-1.0%
-0.8%
0.0%
0.4%
0.8%
-1.1%
-1.1%
-1.0%
-0.4%
-0.2%
0.0%
0.1%
-------
SMOKE (2007aq_07c
15mar2010)
AL
-0.2%
acetald
67.3%
benzene
5.4%
formald
52.1%
1.0%
bfam / voc
41.0%
.2%
13.3%
38.6%
51.0%
Table B-lOci: Non-Road (Off-Road) Emissions—Percent Change between EMF and SMOKE Calculations
-------
SMOKE (2007aq_07c
15mar2010)
acetald
benzene
formald
bfam / voc
-------
SMOKE (2007aq 15mar2010)
% Difference
AL
57801.93022
29492.1221
110953.1373
152307.036
62904.99895
4029.389579
12535.59944
37098.93117
80732.53061
62375.23617
106683.9529
90814.42859
245775.9937
97383.08954
50821.09647
35158.8546
6154.144094
24561.79623
2208.131993
55272.28166
134829.0026
58575.04461
107022.3844
45889.38724
166771.0671
5598.167836
1353.701803
3827.259966
36339.82553
49280.86974
158186.0109
71301.27094
98710.15122
95059.98021
40653.94821
76674.96414
234.7013439
27944.29961
101948.1837
34209.95414
354868.0602
20447.24584
8821.29696
43810.83809
42132.60641
9879.303454
Table B-ll: NH Emissions from Livestock and Fertilizer Application
-------
SMOKE (2007aq 15mar2010)
% Difference
Wl
WY
TOTAL
113,949
18,575
3,251,990
Wl
WY
TOTAL
113947.9071
18574.83303
3,251,957
0.0%
0.0%
-------
7145
114354
48235
32213
41010
Table B-12a: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV) Emissions
(Category 1 and Category 2 Emissions only)—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
56687
154016
-------
ACETALD
CHLORIN
FORMALD
METHANOL
AL
Table B-12ai: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV) Emissions
(Category 1 and Category 2 Emissions only)—Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
WA
WV
Wl
WY
TOTAL
ACETALD
CHLORIN
FORMALD
METHANOL
0.012278362
-------
SMOKE (2007aq_07c 15mar2010)
AL
50.63864879
°
42.94672597
60.19470957
603.6081311
4.173C
20.69946328
4.579189008
0.393220133
82.84116139
37.2017917
202.3634417
0
176.6760616
163.579225
347.3301555
409
12.28210868
8.709792358
3.279256546
95.86952716
154.6709533
BENZENE
12.00006772
0
3.159748602
9.145797103
156.6823078
1.273170635
2.264025558
0.982935123
0.036415364
19.43682237
5.684341851
4533.709545
0
2823.942417
4593.299034
26968.68097
1801.048381
75.21896873
0
59.39369996
57.38541036
171.0549592
40.06191493
354.6292741 4.732798128
861.5354579
77.84316981
7435.960857
3471.147687
3.455376786
1.102481739
33.0928304
54.44755436
5.04125438
78.7446074
0
1.267731301
1.109809862
0.000295376
1.821546283
5.162723094
MD
MT
OK
PA
34.33591495
134.7432815
79.20710091
30.71496817
33.3492399
.96906761
380.7266423
17.10657273
11.57479039
31.17629524
28.98728087
76.98324906
81.80929513
90.34667041
18.95018635
56.10490385
7.897731179
3.032142793
46.37937598
29.62661287
28.28217398
18.56380139
18.82967642
153.1232588
21.8273609
36.73104979
93.21254717
2.654231188
22.35647481
3.424176656
70.12736388
337.4108547
13.42085187
71.34564394
38.22512023
553.1468268
235.4996686
212.4815362
286.9951283
185.3451641
139.5442857
1.160777612
73.2478597
54.54452719
65.42033786
177.6948597
139.8999332
354.3678152
166.5859219
500.4131512
67.55439321
1.739566781
29.09476303
261.6012738
117.6199358
97.46295232
168.8875361
308.2208713
179.5212418
99.67759586
152.6442284
1.746400183
82.28969328
29.99087055
134.0635865
458.6300027
83.76508694
92.40934076
2.254722936
21.39571565
10.76507064
3.855873841
3.018009332
21.35548809
95.39272859
4.4090027
1.716490844
9.627270632
8.879124244
16.38204253
18.70266952
16.29875893
1.668092068
4.924103949
0.704045039
0.735284248
9.008143444
2.602314139
5.750025903
2.980296001
1.641661309
26.75169923
2.152614092
8.04331072
20.91581351
0.163301867
4.144066548
0.302470345
14.88828034
75.65294247
1.055878991
12.1770061
891.9880047
14998.60268
6451.6018
3752.552694
4378.255278
9389.114456
34214.02659
476.7947662
1474.601851
2289.628784
3182.950329
7636.042291
6773.827063
9801.714803
2455.652455
7353.56029
1041.619074
259.1790693
4129.992592
3887.11262
3998.253578
2109.767553
2464.875616
12991.81888
2793.957848
4730.696769
9342.00164
89.20003968
2447.510119
443.1083142
5549.613719
23122.76056
1630.587856
5437.281985
12.85398566
186.8974496
79.78848615
71.55397339
96.48180145
65.0669849
52.65634115
2.975012026
25.24345448
24.77334425
31.17348393
60.60559886
60.4617691
119.9460285
55.9990513
168.2182256
22.70912085
0.618401376
15.18069837
87.93858011
45.38361602
34.17688063
56.77147037
105.7941982
60.35256502
38.71284506
52.72958779
0.588556701
27.90696853
10.08180023
50.49889477
198.9365332
28.15867061
38.82471266
0.001640978
2.00344659
1.047900717
0.269386846
0.016321374
5.811363603
12.0915262
5.437511241
1.307453871
13.55411608
2.3732537
1.836078931
28.2599445
1.734471503
0
0.005993506
0
0.070731607
11.35690086
°
12.29825311
2.975680721
0
3.247383169
0.013277996
10.9539832
2.982947045
0.002419686
0.515073366
0.000164582
11.42883746
94.17397918
0
16.32258547
Table B-12b
(Category 1
: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV) Emissions
and Category 2 Emissions only)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 1 5mar201 0) |
State
WA
WV
Wl
WY
TOTAL
ALD2
51.01524232
34.06100167
165.5741579
24.77420526
3,374
ALDX
114.9005524
77.74858689
109.5717198
222.8605423
7,361
BENZENE
10.27091149
8.82491951
11.53051264
2.156793986
674
CH4
0
0
1.198335863
0
16
CL2
0
o
0
0
1
CO
5955.07955
2838.538153
3053.367205
3247.918332
270,007
ETH
44.55126788
30.68767721
39.73378825
74.91532813
2,680
ETHA
12.46780067
9.580769099
1.800516414
374
-------
SMOKE (2007aq_07c 15mar2010)
AL
79.30102531
°
65.19576702
107.2986097
1163.656442
37.99938541
15.30946841
9.425921565
1.050501894
165.3821987
86.49861682
HGIIGAS HGNRVA
0.036914963
0
0
0.000529674
0
0
0.071287685
0
0
0.001022546
0
251.4710528
0
211.3664975
291.2665278
1196.774894
136.4469166
22.68131087
41.26684524
4.562173096
46.1514134
263.4696605
13.69106657
0
7.171489873
8.470198807
44.14238828
4.837284727
0.95728888
0.756820017
0.133212783
4.553157382
8.154032044
4.514904975
0
0
1.501305913
22.75418514 3
0.377730793
0.330466494
8.79E-05
0.542374948
1.537254179
ID
IN
0.000129123
MD
MT
OK
PA
0.008475321
0
0.000669256
0
26.98465236
278.2579493
132.5494387
77.63726649
89.70583376
200.319931
731.517342
32.29472572
23.31187167
47.20720178
63.76006867
161.8609969
166.6128749
203.7641403
51.25532069
152.1575416
21.24510546
5.910855107
70.9329079
80.20328064
64.35967708
44.15036073
51.138629
266.1233122
57.90313795
79.56568688
190.4336186
1.555488186
49.9031407
9.253650948
145.9825061
683.7796141
27.13262223
126.5455203
57.16319604
914.835081
385.8816548
257.7044803
328.0785452
483.0684282
1419.217094
9.362541598
88.60980175
91.6932015
153.4016499
395.7190077
457.4462276
577.9782856
181.7595672
549.4559125
76.64450801
11.48464613
206.3712418
290.9315366
250.6493064
160.6458672
183.9453386
690.8259145
206.4027051
300.9516604
454.294349
2.805782723
141.7012814
32.78471977
347.4080932
1557.68136
101.3931403
257.2843532
1.552332083
23.1796294
9.950269383
8.722509229
11.65500602
9.634742677
10.05793
2.023066791
3.445349984
7.121428281
4.199117539
7.879694522
15.94762063
15.01402757
6.761652309
20.31365891
2.742040245
0.096314052
5.308086184
10.61839733
9.240257335
5.036863606
6.855100613
13.74450767
7.291415196
8.02253693
7.279845406
0.071781648
3.527228498
1.21740891
9.594693403
52.83834124
3.399960807
9.682134317
0.000488535
0.596543944
0.306965525
0.080212309
0.004860688
1.730393912
3.600306553
1.619096764
0.389677015
4.037878057
0.374672623
0.546704084
8.414963078
0.516482333
0
0.001784536
0
0.021062067
3.381657799
0
3.662503629
0.886102846
0
0.940771715
0.003953761
3.262195572
0.888212614
0.000721157
0.153369223
4.90E-05
3.403029481
28.04074373
0
4.86013985
0
0
0.009123336
0.598747219
0
0
0
0
0
0
0
0
o
0
0
0
0.047282175
0
0
0
Table B-12bi: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV) Emissions
(Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 15mar2010)
State ETOH FORM
WA
WV
Wl
WY
TOTAL
0
0
0.00213083
0
0
HGIIGAS
108.2501883 0.003560752
71 .94583988
97.4381372
67.32388658
6,491
0
0
0
0
HGNRVA MONO
0.006876158 374.5534858
0
0
°
0
198.4832168
192.6269224
242.696504
15,399
IDLE
9.194645662
6.630157195
5.271300591
9.045795863
437
ISOP
3.712644885
2.853667637
0.453017969
0
110
MEOH
0
0
0.150530214
0
4
-------
SMOKE (2007aq_07c 15mar2010)
AL
13.186527
°
12.01486246
19.07220909
179.8816289
4.619490953
0.932338553
0.342846966
0.260037027
10.62090312
11.53060181
28290.56099
0
23778.77723
32767.52861
134637.1715
15350.38101
2551.692817
4642.563583
513.2361448
38941.91443
29640.30979
2891.923584
0
2430.718422
3349.569696
13762.91057
1569.150645
260.8397019
474.5733472
52.46406521
3980.728299
3029.897395
31433.95563
0
26420.86215
36408.36484
149596.857
17055.97857
2835.21383
5158.403775
570.2623831
43268.79414
32933.67685
9.133370757
0
8.103411597
7.453449792
15.11609005
5.466012451
0.55109852
0.388601672
0.150399626
4.379181633
7.043385307
80.00020178
0
56.60794992
57.45916798
197.3480314
38.18135331
5.207765048
3.901957567
1.050896915
32.53862233
54.72357408
982.6365371
°
593.1091778
650.7392332
2788.728651
399.8854719
66.91083671
51.48525196
11.00924106
361.8831575
622.5072717
MD
3.222932478
45.31599012
19.36239069
8.259106467
10.60106759
15.04012357
42.36528327
0.666426104
22.35943606
7.452689363
4.979816333
12.30555565
17.50178189
18.94156815
6.280888022
17.60574745
2.547908696
0.351437805
11.05318099
9.379472214
28.81624476
7.156524303
5.933218969
31.67444887
6.647845423
8.730371424
14.49567233
0.120264902
4.469082877
1.159626427
12.46492391
56.9929645
5.447316755
13.41566163
6430.855853
102919.0105
43411.67996
28991.8401
36908.79173
54345.24667
159661.9369
1053.282691
9968.535889
10315.5083
17257.63792
44518.4587
51462.60807
65022.66355
20447.88931
61813.86974
8622.571929
1292.02963
23216.74378
32729.79231
28198.03974
18072.66838
20693.90982
77717.94342
23220.25805
33856.95444
51108.05781
315.6487056
15941.43765
3688.195838
39083.42806
175239.2132
11406.67906
28944.54341
657.3767545
10520.60731
4437.639215
2963.611703
3772.898643
5555.290625
16320.99861
107.6691358
1019.006242
1054.474593
1764.114586
4550.769334
5260.624214
6646.760463
2090.226695
6318.752248
881.4173945
132.073523
2373.266505
3345.714521
2882.466098
1847.428398
2115.376946
7944.501753
2373.627407
3460.93484
5224.374834
32.26650132
1629.569363
377.0150234
3995.195848
17913.31436
1166.015561
2958.777465
7145.395804
114354.4529
48235.20083
32213.15628
41009.76892
60383.60573
177402.1526
1170.314368
11076.15193
11461.6761
19175.15415
49464.94704
57180.67851
72247.4023
22719.87557
68682.0779
9580.633831
1435.587799
25796.38153
36366.43837
31331.15515
20080.74265
22993.2321
86353.27108
25800.28816
37618.84095
56786.727
350.7209897
17712.7083
4097.995581
43426.032
194710.2089
12674.08776
32160.60523
1.753489476
25.35042957
10.7909013
9.742390086
13.16236628
8.443745928
6.281663338
0
3.346663569
2.369034012
2.956750459
8.13155955
6.139708097
16.23561087
7.640249839
22.95081665
3.098321864
0.079095746
1.223412358
11.99806462
5.274158567
4.440979183
7.745804659
14.1034035
8.233276013
4.464393161
6.971735974
0.080106513
3.769138742
1.375539245
6.036840126
20.11299129
3.84187561
4.078638271
12.25442101
179.2249359
76.55603628
68.34306294
91.96273946
65.1994042
56.81588105
5.817653037
24.77629342
31.04541692
26.77280254
58.76783451
73.12287973
115.2679202
53.36942261
160.3252959
21.64303125
0.628159937
20.69824418
83.81053969
49.9983392
34.20467049
54.10757811
102.2775725
57.52674559
42.90268947
51.89051246
0.562505683
26.87899695
9.608627364
54.39738212
241.2494917
26.83741073
45.95537834
128.7131299
1899.20825
813.0084845
718.6536916
963.2885338
741.6479171
728.9741327
112.9686437
271.9984941
454.6324946
280.0659874
635.8752958
1035.078087
1226.232673
558.9323214
1679.097951
226.6648451
7.398650606
325.344798
877.7277395
640.2086843
386.6180819
566.6423939
1104.79142
602.6735028
553.8101786
575.6641103
5.941427179
287.0630198
100.6314397
680.0013349
3426.765435
281.1018058
637.0550274
Table B-12bii: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV)
Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 1 5mar201 0) |
State
WA
WV
Wl
WY
TOTAL
NH3
20.20762248
8.065539003
10.97813202
7.758430199
773
NO
42137.28936
22329.358
21670.57863
27303.24566
1 ,732,433
NO2
4307.37249
2282.557918
2215.214017
2790.998692
177,093
NOX
46819.21534
24810.39914
24078.41957
30336.94085
1 ,924,925
NVOL
5.147748673
3.472049902
5.00451398
10.221545
334
OLE
49.29787122
34.50097235
37.80590232
71 .39835094
2,745
PAR
635.4122427
453.1719394
408.7664794
747.7315241
32,308
-------
SMOKE (2007aq_07c 15mar2010)
914.1286865
0
557.5798718
716.417068
4571.857489
350.878644
87.88011155
89.45550378
9.96954921
947.31101
646.09435
0.019094821
0.000273956
0
1301.33598
0
733.6521123
1006.965252
6320.090698
462.7332388
113.9498488
128.6959862
13.11576283
1229.56967
925.0759623
1185.21413
0
722.9306635
928.8711804
5927.9434
454.9319992
113.9410597
115.983621
12.92601763
1228.236786
837.694113
116.12185
°
10.72144877
78.09407122
392.1472986
7.801239549
0.008789194
12.71236517
0.189745201
1.33288359
87.38184935
PMFINE
58.19979387
0
35.49941192
45.61215518
291.1425876
22.33939935
5.595069363
5.695373601
0.634737126
60.31245942
41.13487657
1.303874623
°
0.795312422
1.021872055
6.522194701
0.500475096
0.125346098
0.127595198
0.014220027
1.35119022
0.921567817
MD
MS
MT
OK
288.549663
2335.06608
959.0107147
686.3195765
873.5198741
1342.197119
3900.653493
125.0195159
240.9335957
350.2425468
418.5239116
1073.044597
1413.075159
1564.270138
486.4678687
1455.369509
209.3664479
30.43925825
623.9776562
773.3222975
578.216312
391.2554088
487.1510078
1762.706616
549.1594658
733.4916175
1244.516837
0.077121205
382.5823551
87.75067765
978.1314809
4830.839586
39.32875654
1126.763331
374.2528507
3201.48797
1343.531643
890.3608068
1133.006189
1756.566679
5057.962268
176.224612
332.2774946
517.4494296
544.0394259
1391.810097
2003.986576
2028.937023
631.0093534
1887.273542
271.5202324
39.86151165
846.2641751
1002.814986
1021.115931
560.5128353
631.8620722
2423.668329
712.3352206
991.5031262
1614.700107
8.339986445
496.3395075
113.9561717
1358.51251
6850.177909
56.16984612
1463.996478
374.1192767
3027.531775
1243.409393
889.8482614
1132.562968
1740.226825
5057.396493
162.0941469
312.3826137
454.1072833
543.2451063
1391.256915
1832.123975
2028.155753
630.7303483
1886.960378
271.4542561
39.46603614
809.0188338
1002.651703
749.686805
507.2825873
631.6160673
2285.454995
712.0131366
951.009384
1613.579219
0.099991295
496.0375528
113.773218
1268.197255
6263.427215
50.99172534
1460.905876
0.133574023
173.9561953
100.1222496
0.512545401
0.443221614
16.33985405
0.565775448
14.13046512
19.89488087
63.34214631
0.794319571
0.553182096
171.8626008
0.781270634
0.279005109
0.313164073
0.065976289
0.395475509
37.24534136
0.163283068
271.4291256
53.23024796
0.246004894
138.2133342
0.322084029
40.49374218
1.120888793
8.23999515
0.301954783
0.182953642
90.31525543
586.7506941
5.17812078
3.090601696
18.37108528
148.6666523
61.05805541
43.69591373
55.61441492
85.45369853
248.343355
7.959601956
15.33950738
22.29888336
26.78129081
68.31748596
89.9663029
99.59241169
30.97196107
92.65898687
13.32972106
1.937968
39.72683521
49.23513782
36.81330489
24.91009276
31.0154544
112.2298465
34.96332942
46.69928736
79.23463461
0.0049102
24.35787629
5.586821321
62.27468873
307.5651014
2.50394462
71.73764723
0.41155718
3.330599602
1.367887476
0.978942002
1.245937157
1.914430904
5.563686569
0.178322668
0.343653665
0.499549706
0.599301245
1.530554958
2.015539829
2.231195952
0.693881623
2.075851122
0.298627402
0.043416889
0.890024085
1.103024741
0.824723733
0.558050453
0.694847247
2.514285069
0.783282351
1.046213837
1.775099346
0.000110001
0.545698507
0.125165044
1.395166366
6.890454538
0.056094733
1.607161163
Table B-12biii: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV)
Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 1 5mar201 0) |
State
WA
WV
Wl
WY
TOTAL
PEC
799.3967244
574.059814
468.1957537
641 .8850808
43,716
PHGI
0.001841768
0
0
0
PM10
1076.316165
816.1503485
666.8802984
832.3665823
59,361
PM25
1 036.458609
744.2977115
607.0874695
832.236734
56,682
PMC
39.85755662
71 .852637
59.79282892
0.129848322
2,679
PMFINE
50.89524739
36.54868357
29.81927424
40.86691579
2,784
PN03
1.140201282
0.818809284
0.668001676
0.915532664
62
-------
SMOKE (2007aq_07c 15mar2010)
208.1443132
0
126.9593749
163.1260735
1041.228514
'9.8940354
20.01007182
20.36876106
2.270022101
215.699898
147.1137673
°
65.70193125
531.687739
218.3664907
156.2729967
198.8979687
305.6144193
888.1680425
28.46656801
54.8598599
'9.7492722
95.76530961
244.329214
321.7533028
356.1797853
110.7673418
331.3833143
47.67215397
6.930930295
142.0779314
176.0832647
131.6581598
89.08778584
110.9228878
401.375769
125.0420309
167.0140798
283.3727895
0.01755988
87.11296318
19.98058004
222.7177748
1099.966304
8.955040041
256.5606982
3.437462039
0
2.096692516
2.694011696
17.19261474
1.319445317
0.330460821
0.336387341
0.037489162
3.562228763
2.429551304
0
1.085039986
8.780704597
3.606245143
2.580832465
3.284772676
5.047157967
14.66791559
0.470138395
0.905997123
1.317031256
1.575293132
4.035062859
5.31367031
5.882221928
1.829295017
5.472716701
0.787305787
0.114462706
2.3463869
2.907977976
2.17430458
1.471249525
1.831870015
6.628478756
2.065028081
2.758185486
4.679858574
0.000290009
1.4386597
0.329973985
3.678143929
18.16576939
0.147889405
4.237039303
2210.025924
°
1978.077786
2776.219166
32154.71316
1131.611409
235.0896366
1214.631935
43.89084917
2721.714173
1902.833755
0
590.2797776
7515.006902
3091.280784
2199.040981
2849.776573
3801.032513
10769.32089
117.0311061
3934.777934
1304.051332
1293.702921
3206.689388
2965.798279
4989.749663
1670.643567
4727.138443
681.6252738
80.79057745
2158.31738
2511.887846
5535.404717
1162.900216
1591.233188
5483.341514
1784.911699
1789.531247
3734.03774
19.90010329
1176.861857
309.4324179
2362.973109
9632.54403
901.9138191
3484.866474
19.16525022
°
12.1457786
12.98718511
49.8641504
8.19
1.284767169
0.981947347
0.22550884
7.219008251
12.41453119
0
2.629936077
38.71443271
16.54207351
14.6981171
19.73249664
14.74678457
13.7674869
1.957730148
5.488609269
8.44434703
4.73945466
12.84821244
19.37668334
24.95667931
11.45037451
34.3987095
4.643417517
0.14400164
5.922831264
17.98154917
12.33450024
7.727312952
11.60881417
22.26428665
12.34423373
10.63762774
11.52229422
0.121052224
5.834148316
2.061554087
13.162388
64.0463923
5.757902611
11.99004269
Table B-12biv: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV)
Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 15mar2010)
WA
WV
Wl
WY
TOTAL
182.0204065
130.711711
106.6437337
146.1554655
9,955
3.00602909
2.158693651
1.76070614
2.413739204
164
3201.261291
1332.778016
1601.019509
2084.216648
154,016
12.20363882
8.658483904
8.021480778
15.31835698
633
-------
SMOKE (2007aq_07c 15mar2010)
GA
IN
MD
MT
OK
SC
162.9670915
0
97.42726043
107.2898788
464.7499564
65.7127905
11.07805146
8.563457206
1.809116323
59.03419799
102.7772101
21.09436787
311.7908187
133.4594051
118.0723269
158.2971869
121.889227
117.9190219
19.06759783
44.8240085
76.03139283
47.14893432
104.2001944
172.9083278
201.269743
91.85324972
275.9371152
37.2479924
1.198884009
54.53725282
144.2403024
106.5351467
63.82596036
93.12292917
181.2084096
99.03106605
92.08910349
94.27468174
0.972228538
47.11965184
16.53727999
112.6516211
572.0279348
46.18802945
106.2717767
5.838599684
°
5.180287963
4.764713625
9.663273096
3.4941705
0.352394562
0.248422995
0.096144988
2.7994199
4.502551581
°
1.121086569
16.20612312
6.898307157
6.228085425
8.414423294
5.397787463
4.015658958
°
2.139406752
1.514556493
1.89014722
5.198436553
3.924916012
10.37900809
4.8842391
14.67200018
1.980606595
0.050560836
0.782133307
7.67004756
3.371525823
2.838978156
4.951729167
9.016020673
5.263374474
2.85386567
4.45675475
0.051227229
2.409508804
0.87932751
3.859127375
12.85728303
2.456014564
2.607441856
233.7164342
0
147.7613151
163.9488258
797.8605367
98.24945744
17.8933788
12.3599887
2.706671837
115.6405587
151.4283583
°
34.57899883
488.373259
211.2830375
178.6972382
236.5727472
204.3175638
311.0734362
26.39770962
66.2985584
105.2083989
73.03861097
176.630814
238.198376
318.6742926
137.1478352
411.8592913
55.66215298
2.858397185
76.31597442
215.344123
145.4708459
93.49657754
138.9599944
303.6400219
148.4303238
130.3097738
167.7680112
1.687631878
74.9717045
24.6960098
170.9807121
809.7579749
69.32264466
149.2181285
127.772833
0
65.44547749
78.1591704
411.6523232
44.14488886
8.971946516
7.092740786
1.215672878
41.8569504
75.2778678
0
14.17100928
211.8744159
90.95025315
79.64148437
106.3626058
88.89936838
93.81556353
19.37401903
31.68994307
67.44090015
36.62662892
72.21675788
150.2750608
137.3026207
61.70460821
185.3769573
25.02260008
0.890791757
50.34604849
96.89860117
86.41715031
46.46922734
62.5554038
25.8147055
66.54186357
75.0892894
66.93217701
0.655902005
32.27541323
11.1094608
89.47387468
497.974169
31.02816443
91.09652607
Table B-12bv: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV)
Emissions (Category 1 and Category 2 Emissions only)—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 15mar2010)
105.6074553
75.3474169
67.35245881
122.8798128
5,337
3.290849672
2.219515759
3.200106726
6.534201084
151.3366562
109.3329108
112.9220957
183.3542477
8,296
85.99613805
62.18263254
47.93464795
82.54910024
4,045
-------
SMOKE (2007aq_07c 15mar2010)
MONO
AL
Table B-12c: Aircraft/Locomotive/Marine Emissions with No Category 3 Commercial Marine Vehicle (CMV) Emissions
(Category 1 and Category 2 Emissions only)—Percent Change between EMF and SMOKE Calculations
-------
SMOKE (2007aq_07c 15mar2010)
WA
WV
Wl
WY
TOTAL
MONO
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
-------
SMOKE (2007aq_07c 15mar2010)
State ACETALD
AL
BENZENE
CHLORIN
FORMALD METHANOL bfam / voc
0.0%
12.5%
0.0%
98.4%
0.0%
Table B-12ci: Aircraft/Locomotive/Marine Emissions with No Category
(Category 1 and Category 2 Emissions only)—Percent Change between
3 Commercial Marine Vehicle (CMV) Emissions
EMF and SMOKE Calculations
-------
SMOKE (2007aq_07c 15mar2010)
State ACETALD
WA
WV
Wl
WY
TOTAL
13.4%
13.5%
99.9%
36.7%
BENZENE
CHLORIN
FORMALD METHANOL bfam / voc
-------
EMF (2002ad)
SMOKE (2007aq)
39.70839564
0
15.72612675
11.22270485
42.9994419
.14493372
2.261204495
1.059227831
0.115697085
69.51998644
28.26396126
100158.1668
0
121275.6351
90284.73853
190894.0954
107536.7828
12530.50317
6259.808658
2255.701845
145522.8466
181135.5926
11585.83173
°
12810.34305
11686.8284
20334.5588
11801.32473
1014.771192
497.7304781
162.5339985
14112.22151
21293.79007
88572.33507
°
108465.292
78597.91013
170559.5366
95735.45804
11515.73198
5762.07818
2093.167846
131410.6251
159841.8025
93.36570655
40.02600054
37.05208794
34.00194922
45.3719647
13.88242299
10.14935785
2.334444794
4.894261479
6.420093256
31.13691827
43.50439558
34.80125873
50.9881743
16.25927413
33.78792055
6.453978406
1.214249244
3.35484394
47.5095383
18.96583784
19.87734409
17.99144552
37.30361525
41.16345112
10.80775674
21.31345029
0.427959711
19.2712751
15.02701312
15.45420879
458.7866322
8.377163203
1.450950578
7.703118438
6.630823702
138595.6087
445147.6973
345741.8741
341704.6578
456165.9998
99402.39531
79092.68882
12756.40088
35405.23346
49649.84242
208830.0071
432188.1418
139262.8391
452014.3185
188184.0149
320750.3372
61119.98509
6159.333506
16303.67902
440408.7922
139931.222
91300.11127
269914.2672
236404.9178
395697.7645
76314.86476
130419.2807
2501.972145
82097.43045
202445.3366
95792.06909
1282259.588
54046.1988
13636.8295
60229.60606
104861.2466
14128.8856
58900.8951
41851.01328
42861.29913
55290.90084
12661.98866
10307.79972
1312.174224
3561.306592
4580.741585
23515.01674
49515.90304
17455.63445
48216.40812
24540.05923
37498.26391
7188.249933
658.5337981
548.8956409
45364.71475
13652.39674
11168.27234
38288.74846
28602.31291
44258.14241
8741.496207
13350.52598
181.6740872
9162.541586
29234.09717
11906.61127
143744.0823
5685.436267
1528.395605
8198.12938
13624.2983
124466.7231
386246.8022
303890.8608
298843.3586
400875.0989
86740.40665
68784.8891
11444.22666
31843.92687
45069.10083
185314.9903
382672.2388
121807.2047
403797.9104
163643.9557
283252.0732
53931.73516
5500.799708
15754.78338
395044.0774
126278.8252
80131.83893
231625.5188
207802.6049
351439.6221
67573.36855
117068.7548
2320.298058
72934.88886
173211.2394
83885.45782
1138515.506
48360.76253
12108.43389
52031.47668
91236.9483
liable B-13a: PM10 and
PM25 Emissions from Fugitive Dust Sources [Construction, etc.]
-------
EMF (2002ad)
State
wv
Wl
WY
TOTAL
P"i10
21 ,732
103,088
272,300
8,858,992
P"i25
3,649
11,870
28,723
1 ,030,391
SMOKE (2007aq) |
State
WV
W,
WY
US
Total
PEC
2.9868685
18.71593115
28.61828491
1,530
PM10
21743.36969
103139.3988
272349.3257
8,861 ,823
PM25
3651 .023696
11876.67923
28730.72911
1 ,030,844
PMC
18092.34599
91262.71957
243618.5966
7,830,978
-------
SMOKE (2007aq)
AL
PMFINE
10827.49969
0
12191.3672
11253.14415
19105.39124
11257.74531
963.7617773
470.8182135
154.0746493
12962.69038
20345.07705
52.06900908
•
9.49328417
9.350073249
16.90016061
7.584778298
0.631045707
0.239750756
0.065013773
96.00542392
17.88892475
613.7925214
°
562.7861167
374.0491502
1129.977718
507.0801798
44.97040251
24.8796886
8.078712721
.3651536
838.1365103
52.76210817
0
30.970327
39.06231651
39.29023264
16.7695329
3.146762347
0.733597447
0.199925649
76.64056593
64.42361492
0.0%
0.0%
MD
12635.47842
56576.56498
40043.00346
41033.46444
52786.2399
12193.91147
9942.371926
1257.742312
3385.194754
4310.55833
22408.26916
47114.53164
16554.36759
45663.57603
23604.00679
35705.97113
6895.695559
633.8760256
501.5320231
42796.68437
13019.81298
10716.00344
36970.69437
27350.09283
42098.97232
8321.406875
12746.56539
170.405325
8652.490394
28285.04877
11451.36011
133727.2624
5382.899644
1464.684157
7972.200773
13107.9356
150.8062823
41.42593947
33.40905504
32.51769363
46.1787006
7.675282219
6.950339016
0.943709387
1.746652447
4.331019142
19.74776082
46.04254843
44.18796662
50.09666353
19.86991661
34.73400662
5.089267349
0.418233469
0.384434211
53.75820577
9.959005826
6.26974939
25.85712936
18.9410526
43.63360494
7.9546625
8.697105772
0.094982369
19.40756869
19.34460325
6.860235123
688.227962
3.105895159
1.398542414
4.898903641
10.09005065
1155.760772
2140.72369
1653.390171
1690.65722
2316.980239
408.2502533
316.0730742
46.08190612
164.6807956
250.2151355
998.3579354
2225.533119
765.8729664
2349.280665
832.8265488
1651.72011
257.7510928
20.19147925
42.22567293
2359.946815
566.6981192
392.6925921
1197.146207
1135.634292
1971.455378
379.2773918
536.9863704
10.44474236
440.872218
842.5432223
400.0230019
8269.221137
282.7027756
55.65288315
177.2243966
473.9058429
93.47442429
102.1544905
84.15850681
70.65783264
96.13003941
38.269227
32.25502329
5.071851276
4.790128474
9.217007005
57.50496327
86.29133584
56.40465936
102.466586
67.09670817
72.05074709
23.2600356
2.833810524
1.398666645
106.8158204
36.96079355
33.42920815
77.05930136
60.34112061
102.9176638
22.0495211
36.96367158
0.301077707
30.50013073
72.13355721
32.91371429
600.5841767
8.350788869
5.209071689
36.10218875
25.73597954
0.0%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.1%
0.1%
0.1%
0.1%
0.0%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.1%
0.0%
0.0%
0.0%
0.0%
0.0%
0.1%
0.1%
0.0%
0.1%
0.0%
0.1%
0.1%
Table B-13b: PM and PM Emissions from Fugitive Dust Sources [Construction, etc.]
-------
SMOKE (2007aq)
wv
Wl
WY
TOTAL
PMFINE
3570.956287
11304.69108
27176.2612
979,064
5.253716497
7.242432359
33.18904204
51.69228415
527.9743436
1420.101294
45,790
20.13454058
18.05543974
72.55928184
2,729
0.1%
0.0%
0.0%
0.1%
0.1%
0.0%
-------
EMF (2007aq)
st State
Con US
Total
Acetald
0.017839523
0.724989257
0.962754199
0.010506275
0.047572346
1.06E-05
1.024734287
0.063764367
0.030504335
0.000807668
0.000351703
0.809491153
0.037985386
0.15688613
0.295896308
0.085518811
0.002437691
0.009746944
0.000231237
0.203783933
0.114915818
9.776260505
0.498083228
0.01983584
0.144992864
0.024239
0.025622895
0.192840822
0.330261293
0.141735184
0.309466251
O.OOC
0.006103292
6
Benzene
0.000764551
0.031070959
0.041260896
0.000450269
0.002038815
4.55E-07
0.043917191
0.002732759
0.001307329
3.46E-05
1.51E-05
0.03469248
0.001627945
0.006723691
0.01268127
0.003665092
0.000104473
0.000417726
9.91 E-06
0.008733597
0.004924963
0.418982619
0.021346426
0.000850107
0.006213981
0.00103882
0.001098124
0.008264605
0.014154056
0.006074365
0.013262838
9.21 E-C
0.00026157
Formald
0.122328173
4.971353103
6.601743514
0.072043023
0.326210366
7.28E-05
7.02674983
0.437241402
0.20917259
0.005538293
0.002411675
5.550796678
0.260471173
1.075790598
2.029003283
0.586414683
0.016715599
0.066836187
0.00158562
1.397375373
0.787994158
67.0372187
3.415427942
0.136017187
0.994236995
0.166211246
0.175699843
1.32233685
2.264649004
0.971898488
2.122054072
0.001473591
0.041851152
38
Table B-14a: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle (CMV) Emissions—
Pre-SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 19apr2010)
AL
AK
CA
CT
DE
DC
FL
GA
HI
-
IN
LA
ME
MD
MA
Ml
MN
MS
NH
NJ
NY
Non-US
SECAC3
NC
OH
OR
PA
Rl
SC
TX
VA
WA
WV
Wl
TOTAL
0.018951956
0
0.996305934
0.011161319
0.050539078
1.13E-'
1.088650536
0.06774169
0
0.000858026
0.000373651
0.85997856
0.040354602
0.166664603
0.314346436
0.090852219
0.00258971
0.010354429
0.000245666
0.216493498
0.122081598
4.16397865
0.552163621
0
29.0261184
0.325180082
1.472446535
3613
31.71630887
1.973584427
0
0.024998577
0.010885627
25.05452035
1.175702341
4.855728397
9.15893793
2.646914524
0.075450717
0.301680327
0.007157325
6.307446406
3.556874362
121.5318629
0.529073772 15.41495341
0.021072796 0.613950427
0.154022672 4.487394827
0.02575097 0.750237018
0.027221042 0.793071642
0.204870594 5.968710062
0.350855063
0.150576285
0.328762333
0.000228279
0.00648345
10
10.22218383
4.386913604
9.578536058
0.006651547
0.188907575
292
BENZENE
0.000764613
0
0.04019139
0.000450272
0.002038776
4.55E-07
0.043917631
0.002732733
0
3.46E-05
1.51E-05
0.034691865
0.001627931
0.006723572
0.012680281
0.003664306
0.000104466
0.000417686
9.91 E-06
0.008733331
0.004924543
0.168263211
0.021345169
0.00085
0.006213392
0.001038788
0.00109809
0.0082640
0.014153925
0.006074171
0.013262823
9.21 E-06
0.000261567
0
0
0
O.OOE+00
0
0
0
0
O.OOE+00
0
0
0
0
0
0
0
O.OOE+00
O.OOE+00
0
454.5522565
0
10132.14989
112.2822361
492.6637447
0.109422612
10682.98243
650.2662302
0
8.38828993
3.839161318
8598.947345
396.8854882
1620.862479
3058.283573
881.3980796
25.40815159
105.6402344
2.383131379
2089.60101
1168.462804
40376.8042
5135.085196
204.4288986
1438.354375
266.179219
265.2474629
1984.380017
3647.14806
1460.155529
3017.045132
2.214808843
62.91957429
98,345
1.415129762
•
74.39250586
0.833418876
3.773721811
0.0008422
81.28913916
5.058168992
0
0.064069291
0.027898949
64.21417514
3.01321521
12.44490858
23.47397263
6.78385975
0.193370391
0.773187008
0.018343078
16.165301
9.115977928
311.1091689
39.50986698
1.573480781
11.50092344
1.922815974
2.032578293
15.29765291
26.19865265
11.24319708
24.54869325
0.017047052
0.484150197
748
Table B-14b: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle (CMV)
SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
2.586556471
°
135.9733744
1.523287247
6.897449747
0.001539319
148.576269
9.245100771
0
0.11710306
0.050992841
117.3699994
5.507456078
22.74709741
42.89709454
12.39930014
0.353438405
1.413189832
0.033526808
29.54640898
16.66166731
568.6006742
72.21628989
2.875962869
21.02070844
3.514411612
3.715016564
27.96052219
47.88470586
20.55023222
44.86898571
0.031157768
0.884909375
1,368
Emissions—
-------
SMOKE (2007aq_07c 19apr2010)
AL
0.125691639
0
6.607029056
0.074023015
0.335173863
7.48E-05
7.219937115
0.449256148
0
0.005690362
0.002477835
5.703710797
0.267628739
1.105340033
2.084967538
0.602528646
0.017174864
0.068673054
0.001629142
1.43573163
0.809614948
27.35391951
3.508208659
9755807
1.021465982
0.170779185
0.180530596
1.358565679
2.326875128
0.998591907
2.180328098
0.001514144
0.043001235
66
17.62853094
0
945.2340691
10.86327483
46.01934953
0.010598444
1035.686523
61.88621461
0
0.848777467
0.372004074
808.568583
38.35664809
156.672161
295.8735455
89.72824088
2.535880664
10.02355965
0.23082773
197.3086559
114.7983106
3917.842258
497.1600553
20.71561805
134.9016774
25.98331564
25.66063085
190.1283641
321.2711628
141.297142
283.3947287
0.21452261
6.402004751
9,398
0.962332345
0
50.59092476
0.566750068
2.566220888
0.000572756
55.279061
3.439710778
0
0.043568574
0.018972468
43.66788059
2.049090163
8.462888139
15.96214565
4.613194108
0.131499174
0.525792828
0.012474093
10.99296715
6.199126434
212.0047539
26.86716777
1.070025451
7.820676401
1.307558239
1.382195394
10.4024714
17.81569368
7.645820177
16.69399522
0.011592283
0.329237883
509
0.770175467
40.4868851
0.453576095
2.053797467
0.00045841
44.24127495
2.752839085
0
0.034868993
0.015183353
34.94782086
1.639913624
6.773087118
12.7745071
3.692036638
0.105240764
0.4207953
0.009983263
8.797771428
4.961373465
169.0825371
21.50485977
0.856355895
6.259211875
1.046455925
1.106196121
8.325488017
14.25812301
6.118916199
13.36024735
0.00927745
0.263490838
407
MEOH NO
1,983
106,338
I5 0
17 0
1 0
15 0
15 0
0
13 0
13 0
16 0
!4 0
8 0
1 0
18 0
14 0
•1 0
13 0
!8 0
15 0
'1 0
7 0
I5 0
'5 0
!5 0
!1 0
7 0
11 0
i9 0
I5 0
5 0
I8 0
0
1,222
5,177
1
116,509
6,962
0
95
42
90,969
4,315
17,626
33,287
10,094
285
1,128
26
22,197
12,915
441 ,047
55,929
2,330
15,176
2,923
2,887
21 ,390
36,143
15,896
31 ,882
24
720
1,057,520
203
°
10,870
125
529
4
9,299
441
1,802
3,403
1,032
29
115
3
2,269
1,320
45,184
5,717
238
1,551
299
295
2,186
3,695
1,625
3,259
2
74
108,202
Table B-14bi: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle (CMV) Emissions
—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 19apr2010)
PM2 5 PMC
PMFINE
Table B-14bii: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle (CMV) Emissions
—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
-------
SMOKE (2007aq_07c 19apr2010)
AL
CA
DE
FL
HI
IN
NY
Non-US
SECA C3
NC
WA
Wl
TOTAL
89
101
77
°
3,912
47
197
°
4,456
263
0
SULF TERP
1,429 0 1
72,584 0
918 0
10,885 0
I
84,015 0
6,016 0
0 0
66
31 0
63,153 0
3,088 0
12,217 0
23,555 0
6,553 0
200 0
882
18
19,420
8,557
16,413 300,320
1
904
26
39,804
38,951 0
1,536 0
10,266 0
2,925 0
2,303 0
17,926 0
28,977 0
11,407 0
22,036 0
16
476 0
750,725 0
Table B-14biii: Offshore Ship Emission Control Area with Category
—SMOKE: Criteria Air Pollutants and Hazardous Air Pollutants
(CMV) Emissions
-------
Difference
Acetald Benzene Formald
AL
0.80%
0.0%
0.0%
0.0%
0.0%
0.0%
5.9%
0.0%
0.80%
-2.6%
-2.5%
-2.6%
-2.7%
Non-US
SECAC3
-2.7%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.80% -149.3% -149.5% -149.1% -149.1% -149.2%
CT
DE
DC
FL
GA
HI
IL
IN
LA
ME
MD
MA
Ml
MN
MS
NH
NJ
NY
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.80%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
3.4%
5.9%
5.9%
5.9%
-2.7%
0.0%
0.0%
0.0%
5.9%
0.0%
5.9%
5.9%
0.0%
0.0%
5.9%
0.0%
5.9% 0.0%
5.9% 0.0%
5.9% 0.0%
5.9%
5.9%
5.9%
5.9%
5.9%
5.9%
5.9%
2.7%
ALD2 and FORM
don't match up exactly
due to molecular
weights
ALD2 should be
5.9%, FORM should
be 2.7%
0.1%
2.7%
2.7%
2.7%
2.7%
2.7%
2.7%
Table B-14c: Offshore Ship Emission Control Area with Category 3 Commercial Marine Vehicle (CMV) Emissions—
Percent Change between EMF and SMOKE Calculations
-------
11752
9100
19726
38195
26492
172531
381578
144882
440249
157308
7369
3477
146
224728
200711
195464
89781
59248
77180
136682
81560
140527
67176
18410
11433
93374
125000
158682
132441
265833
113329
227009
15829
85481
76300
74404
34138
22519
37974
16183
32430
101194
43123
86419
6017
13546
255107
67965
131274
77737
63033
132357
229510
65476
1645
97754
107575
100184
709679
170143
15877
86650
166035
41597
81520
138753
6495352
8042
12838
2756
19332
11518
1065030
2974
4962
234474
Table B-15: Biogenic Emission Inventory System Emissions [model calculated]
-------
MEOH
SESQ
AL
867634
376591
601468
877073
205878
325
13367
816
669279
910194
113116
217977
150178
106544
318217
551855
39396
82411
34221
224578
394371
768476
688037
96784
111498
129103
70700
175612
90835
528980
58883
132152
375624
68778
217737
523835
879959
157215
72894
522219
136226
11541
62733
173219
30300
65319
146144
5716885
424153
26947
219216
244925
121402
13582326
Emission Inventory
Svstem Emissions
Biogenic
[model calculated]
-------
EMF Inventory
OTHER
AL
PEC 72
61
PMC 72 PMFINE 72
42
77
POC 72
342
Table B-16a: Running Mode Emissions [calculated by MOVES 2010 Model]—Pre-SMOKE: Particulate Air Pollutants
-------
EMF Inventory
WY
TOTAL
OTHER
PEC 72
PMC 72
PMFINE 72
369
-------
SMOKE
AL
NM
OTHER
8.827499573
0
8.82573808
4.796041711
7.760227848
4.929890485
1.395197892
0.594202616
32.72057508
14.67535541
0
2.190883998
16.41838335
0.98140765
4.775141344
4.687356272
7.242688757
6.972055645
2.182161522
8.780095019
8.732915998
7415
7.949716761
6.193220677
10.99860977
1.737029713
2.900807333
3.092362197
1.9429047
12.24263728
4.163851695
23.25158209
12.78969879
1.154479627
18.33633096
7.357718547
4.872632153
16.29288833
1.557093537
7.784283581
1.344295706
10.39795169
35.67142645
4.642000143
1.157676439
13.23402625
PEC 72
61.44853453
0
66.08250258
32.61905719
52.76228068
35.39784234
9.518619245
4.025445306
223.4490037
107.91145
0
13.44166691
111.1872959
74.74035572
31.54853982
31.94558916
51.22116404
48.48886644
14.81012429
59.88420928
66.77247111
105.2753306
55.91205487
44.07671489
71.57431252
11.28243699
19.45591406
23.7391833
14.41790252
88.81691121
28.03438064
161.3958311
84.93726307
7.817089899
122.5748405
49.90040918
34.02284286
109.6159293
12.15891323
51.53991578
9.177031146
67.82180415
257.6450193
29.9987976
8.269979552
89.7177978
6.06605096
0
4.746350436
3.513215199
5.689344908
02311
1.013636509
0.439769174
23.71084509
8.451197165
0
2.018938089
12.16256331
8.029079647
3.761361564
3.414948417
4.748692053
4.80349602
1.607365344
6.383771722
4.303378473
15.37654789
5.300022972
3.981859036
8.973333256
1.423251167
2.202433947
1.496934131
1.081635124
7.39254355
3.130993502
16.1082885
9.950115092
0.855561293
14.03767468
5.429780265
3.318756119
12.27433269
0.695423712
6.100293953
0.975034768
8.438917398
21.8634542
3.846649647
0.735550022
9.776550483
6.06605096
0
4.746350436
3.513215199
5.689344908
3.08102311
1.013636509
0.439769174
23.71084509
8.451197165
0
2.018938089
12.16256331
8.029079647
3.761361564
3.414948417
4.748692053
4.803496023
1.607365344
6.383771722
4.303378473
15.37654789
5.300022972
3.981859036
8.973333256
1.423251167
2.202433947
1.496934131
1.081635124
7.39254355
3.130993502
16.1082885
9.950115092
0.855561293
14.03767468
5.42978026
3.318756119
12.27433269
0.695423712
6.100293953
0.975034768
8.438917398
21.8634542
3.846649647
0.735550022
9.776550483
PMC 72
41.79941622
°
47.4442946
25.06249431
35.72172886
26.78540959
6.912823294
3.083301311
150.9941633
82.80438532
0
10.64104951
84.07553288
50.94020569
23.50747852
21.76867453
35.0838227
32.96001356
10.16709249
46.30503095
44.8075063
79.55197683
41.57279441
26.99090704
54.71128171
7.771543621
13.61695277
14.91439001
9.7762129
62.75223455
19.73021357
117.9967793
63.37525411
5.366038349
83.27803546
34.01738289
25.69107029
84.86494827
7.575977006
39.34055369
6.295200869
52.9757302
171.3016192
21.79225582
4.763405039
68.65567211
Table B-16b: Running Mode Emissions [calculated by MOVES 2010 Model]—SMOKE: Particulate Air Pollutants
-------
SMOKE
WA
WV
Wl
WY
TOTAL
8.589003015
3.091573163
8.974186412
1.463839129
408
60.17520164
20.58686519
62.26669577
9.615996076
2,809
5.792383913
2.389431108
6.224444705
1.168754527
288
5.792383913
2.389431108
6.224444705
1.168754527
288
PMC 72
44.36090919
15.3656758
42.39105552
6.611345205
2,008
-------
AL
77.1104369
°
87.49623737
46.54537421
65.9530841
49.60481104
12.80423078
5.726360445
278.6982063
153.3092813
0
19.87116145
156.060752
94.07758759
43.65143438
40.20006074
64.699165
60.80398485
18.78589869
86.01053137
82.26771022
148.2246758
76.99017984
49.45921725
101.7704872
14.39103568
25.1970651
27.27481737
17.98197865
115.7801739
36.51249955
218.4682128
117.6637994
9.915922441
153.9030468
62.83489321
47.62580664
157.7292768
13.83730397
73.12160199
11.62824022
98.62095758
315.1212582
40.46047741
8.695217624
127.499602
0.299840429
°
0.322451562
0.159166355
0.257455491
0.172725354
0.046446465
0.01964232
1.090328213
0.526558861
0
0.065588992
0.542543583
0.364698182
0.153942459
0.15587998
0.24993579
0.236603493
0.072266219
0.292207047
0.325818769
0.513695222
0.272825433
0.215073761
0.349249745
0.055052729
0.094935807
0.11583623
0.070352971
0.433386928
0.136794854
0.787535618
0.414453347
0.038143677
0.598108765
0.24349103
0.166015939
0.534873262
0.059329751
0.251491118
0.044779969
0.330939422
1.257194288
0.146380352
0.040353453
0.437782205
341.414789
0
393.3525429
208.7466629
290.9642844
223.37.
57.04518362
25.66079234
1229.887723
693.169725
0
88.40139189
698.2116973
415.480895
194.3814603
177.5635317
287.2823612
269.1596358
83.01864008
386.1521926
367.6738327
656.1464368
345.2024014
216.3300039
453.8595363
63.27003797
111.4812693
120.9120357
80.19538264
517.6875633
161.743224
976.0832589
524.3704422
43.80720481
677.8335841
277.3859682
213.7659172
707.1819295
61.40108677
326.6864986
51.41972089
441.1150105
1397.249314
179.0923543
37.68769953
571.3278922
5.76621053
0
4.423898874
3.354048843
5.431889416
2.908297756
0.967190044
0.420126854
22.62051687
7.924638304
0
1.953349096
11.62001973
7.664381466
3.607419104
3.259068437
4.498756263
4.56689253
1.535099125
6.091564675
3.977559704
14.86285267
5.02719754
3.766785275
8.624083511
1.368198438
2.10749814
1.381097902
1.011282153
6.959156622
2.994198647
15.32075288
9.535661745
0.817417616
13.43956591
5.186289235
3.15274018
11.73945943
0.636093961
5.848802835
0.930254799
8.107977976
20.60625991
3.700269295
0.69519657
9.338768278
Table B-16M: Running Mode Emissions [calculated by MOVES 2010 Model]—SMOKE: Particulate Air Pollutants
-------
82.13364022
28.52537983
78.21650215
12.23509273
3,715
0.29362743
0.100454439
0.303832923
0.046921715
14
367.723226
127.1690203
346.2116492
53.85623649
16,539
5.498756483
2.28897667
5.920611783
1.121832812
275
-------
DC
IL
MN
NM
NC
8.827544332
8.826135134
4.796116099
7.760246397
4.929565666
.6
0.594198842
32.72079282
14.67524544
2.190836847
16.4180898
10.98138518
4.775213648
4.687427048
7.242888855
6.971999787
2.182188175
8.779835461
8.733108092
16.99513306
7.949522827
6.193196091
10.99867196
1.737033856
2.90091712
3.092372969
1.942929555
12.24236124
4.163784192
23.25203409
12.78960853
1.154569166
18.336489
7.357590129
4.872797534
16.29276736
1.557113709
7.784318497
1.344288655
10.39817342
35.67179001
4.64207768
1.157563383
13.23412007
8.589013042
3.09195917
85.93404648
87.79995179
50.41071761
121.4043311
77.59492152
17.55502368
7.255419534
247.879209
154.5685157
30.62461318
244.5935184
155.9767767
76.0144688
62.14444197
90.93802577
62.06330897
39.21328207
112.3443656
153.422665
248.4688715
160.6681111
60.29746832
133.3074542
28.60310823
44.57134711
39.33502386
36.03979813
177.1701951
57.96269952
62.44183696
38.35851801
80.76379542
57.89796015
12.55807339
5.487927538
104.3558846
112.9415354
69.34560364
141.8037181
102.8613379
22.41037706
9.850245223
167.0296548
117.8171598
23.81949369
182.0298948
104.5680185
55.6494539
41.71091267
61.49701465
41.91288952
26.41396722
85.71067423
101.5402343
184.1240777
117.360493
305.7035972
213.3830964
42.54585442
323.6450916
184.482153
98.52666848
73.8232765
109.2667713
75.89183916
46.20567995
153.6293088
177.7675925
327.0119118
206.3886152
36.61947535 65.41898573
100.4742704 180.1619339
19.30471366 33.85574888
30.6396835
24.77208157
24.07464656
123.5118321
50.66593643
35.17359867
357.0519329
130.6083483
24.89497442
261.575822
81.2268941
65.58926666
231.9939977
258.700048
96.45643673
16.73087844
174.6341459
54.69715323
48.89430854
177.0288179
26.80085244
71.83511776
24.1018461
107.3906534
346.3257526
66.54900449
22.65857045
154.1778985
120.5189256
39.53295425
16.46910844
54.38508847
16.22275106
82.97630774
228.5518328
47.46221107
12.79418012
116.6210941
87.60778603
29.09524549
54.00783726
43.77982029
42.07941198
218.7951909
62.66951294
458.5571793
174.1639104
29.10361417
307.7970174
97.69202802
87.32992633
315.9269572
28.63878836
98.89528876
28.38127707
150.1629407
411.291674
84.11704251
21.8752653
209.7117703
155.8909106
51.97380748
0.299842341
0.322466352
0.159168544
0.257456415
0.172714106
0.046450837
0.019642278
1.09033564
0.526554465
0.065587563
0.542533279
0.364697692
0.153944436
0.15588219
0.249942156
0.236601291
0.072267461
0.29219905
0.325825865
0.513687844
0.272818769
0.215073545
0.349251788
0.055053286
0.094939745
0.115837304
0.070353701
0.43337594
0.136792581
0.78755304
0.414451807
0.038146892
0.598114619
0.243486822
0.166021806
0.534872163
0.059330799
0.251492367
0.04477953
0.330946939
1.257203304
0.146382965
0.040349377
0.437784785
0.293627825
0.100467262
477.6246801
520.5823743
322.7632498
670.2162994
489.6872121
105.0445476
46.26241391
1364.910481
993.5864228
201.7768135
1536.237974
867.4239997
468.7771964
345.6317347
510.1678655
344.5994292
220.1066628
724.2859799
845.223733
1550.100328
992.3456412
296.1108234
845.8484942
160.5910088
255.4886757
203.4384975
200.7459812
1032.880275
292.5256659
2176.395311
806.8617615
139.6697236
1447.182284
451.6643242
412.3052244
1498.25615
135.369612
455.5490363
135.1793769
698.8289774
1878.101766
397.3690592
103.4882935
982.4027957
736.4929896
244.413129
5.766242621
4.424111752
3.354099636
5.431910364
2.908096885
0.967273952
0.42012087
22.62066825
7.92459808
1.953312178
11.61980553
7.664378488
3.60748641
3.259120049
4.498944502
4.56686477
1.535118186
6.091379897
3.977676636
14.86265933
5.027085932
3.766759823
8.624134665
1.368202669
2.107567918
1.381092231
1.011284503
6.959021732
2.994160158
15.32105958
9.535610637
0.817471996
13.43965933
5.186207593
3.152847735
11.73931397
0.636100306
5.848819284
0.930251461
8.108103924
20.60649314
3.700314856
0.695152733
9.338846423
5.498771858
2.289234558
Table B-16c: Running Mode Emissions [calculated by MOVES 2010 Model]—Adjusted Particulate Air Pollutants
-------
Wl
WY
TOTAL
8.974334245
1.463854524
407.6685293
408
161.0387924
25.42443048
5176.160951
107.6473922
17.12371047
3665.323548
3,665
46,693
PM10
188.2310519
29.97343675
6532.322487
6,532
42,753
0.303838044
0.046922233
13.70706904
896.2096269
142.5453656
30623.26927
30,623
5.920712387
1.121849169
274.579999
275
-------
SMOKE
STATE
OTHER
PEC 72
PMC 72 PMFINE 72
-0.02%
-0.26%
0.14%
-0.26%
-0.32%
-0.32%
-0.61%
-0.41%
-0.12%
-0.18
-0.30%
-0.04%
0.12%
-0.06%
0.06%
-0.10%
0.29%
-0.33%
-0.51%
-0.30%
-0.07%
0.15%
-0.14%
0.38%
0.09%
-0.18%
-0.11%
-0.48%
0.07%
-0.39%
-0.09%
0.30%
-0.26%
-0.32%
-0.32%
-0.61 %
-0.41 %
-0.11%
-0.18%
-0.30%
-0.04%
0.13%
-0.05%
0.06%
-0.10%
0.29%
-0.33%
-0.51 %
-0.30%
-0.07%
0.15%
-0.14%
0.38%
0.09%
-0.17%
-0.10%
-0.48%
0.08%
-0.38%
-0.09%
0.31 %
-0.24%
-0.04%
-0.10%
-0.21 %
-0.60%
-0.38%
-0.07%
-0.12%
-0.27%
-0.01 %
0.17%
-0.03%
0.09%
-0.08%
0.32%
-0.30%
-0.49%
-0.27%
-0.03%
0.18%
-0.10%
0.42%
0.14%
-0.16%
-0.08%
-0.47%
0.13%
-0.37%
-0.05%
.34%
-0.24%
-0.04%
-0.10%
-0.21
-0.45%
0.02%
0.33%
-0.12%
-0.20%
-0.23%
0.38%
-0.18%
-0.27%
0.20%
-0.03%
.37%
-0.46%
-0.01 %
0.30%
-0.46%
-0.01%
0.29%
-0.16%
-0.21%
-0.25%
0.30%
-0.21%
-0.31%
0.15%
-0.06%
0.33%
-0.15%
-0.21 %
-0.25%
0.31 %
-0.21 %
-0.31 %
0.15%
-0.06%
0.33%
-0.22%
-0.01 %
-0.07%
-0.18%
-0.45%
0.02%
0.33%
-0.12%
-0.20%
-0.23%
0.37%
-0.18%
-0.27%
0.20%
-0.03%
0.37%
POC 72
-0.03%
-0.26%
0.14%
-0.26%
-0.32%
-0.33%
-0.61 %
-0.41 %
-0.12%
-0.18%
-0.31 %
-0.04%
0.12%
-0.06%
0.06%
-0.10%
0.29%
-0.33%
-0.52%
-0.30%
-0.07%
0.14%
-0.14%
0.38%
0.08%
-0.18%
-0.11%
-0.49%
0.07%
-0.39%
-0.09%
0.30%
-0.24%
-0.04%
-0.10%
-0.21 %
-0.46%
-0.02%
0.29%
-0.16%
-0.21 %
-0.25%
0.30%
-0.21 %
-0.32%
0.15%
-0.06%
0.33%
-0.06%
-0.30%
0.13%
-0.29%
-0.33%
-0.33%
-0.62%
-0.44%
-0.15%
-0.23%
-0.35%
-0.06%
0.07%
-0.08%
0.03%
-0.15%
0.25%
-0.34%
-0.53%
-0.32%
-0.07%
0.12%
-0.15%
0.32%
0.03%
-0.20%
-0.12%
-0.51%
0.02%
-0.39%
-0.10%
0.25%
-0.26%
-0.07%
-0.13%
-0.23%
-0.48%
-0.06%
0.25%
-0.19%
-0.22%
-0.29%
0.25%
-0.24%
-0.34%
0.12%
-0.08%
0.26%
liable B-16d: Running Mode Emissions [calculated by MOVES 2010 Model]—Percent Change between EMF and
SMOKE Calculations
-------
Adjusted
PMC 72
0.00%
0.00%
0.00%
0.00%
-0.01 %
0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
-0.01 %
0.00%
0.00%
0.01%
0.00%
0.00%
129.77%
136.02%
187.36%
36.80%
86.25%
153.52%
65.70%
149.97%
99.48%
80.73%
121.23%
53.77%
218.47%
113.40%
62.78%
92.78%
111.64%
120.42%
39.38%
162.63%
58.34%
34.42%
121.84%
173.99%
66.10%
146.26%
96.82%
78.27%
119.24%
52.20%
211.79%
71.85%
100.28%
92.03%
158.63%
164.40%
PMFINE 72
35.33%
29.08%
48.98%
115.01%
107.36%
72.02%
9.69%
39.18%
114.11%
107.38%
96.10%
125.71%
83.64%
68.88%
24.81 %
145.96%
78.62%
116.08%
120.62%
168.07%
32.27%
77.03%
135.26%
114.34%
60.51 %
134.01%
88.97%
71.64%
109.90%
48.02%
193.50%
99.99%
55.47%
83.37%
100.30%
106.97%
35.25%
144.07%
52.26%
30.52%
107.90%
151.58%
64.48%
89.80%
82.20%
140.65%
144.98%
0.00%
0.00%
0.00%
0.00%
-0.01%
0.01 %
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
o.oos
0.00%
0.00%
-0.01%
0.00%
0.00%
0.01 %
0.00%
39.90%
32.34%
54.62%
130.34%
119.22%
84.14%
80.28%
10.98%
43.34%
128.25%
120.02%
108.78%
141.16%
94.65%
77.58%
28.03%
165.13%
87.56%
129.88%
136.24%
187.47%
86.37%
153.82%
129.18%
68.25%
150.32%
99.52%
80.86%
122.97%
53.87%
218.83%
113.50%
62.83%
92.88%
111 86%
120.47%
39.45%
162.89%
58.42%
34.41 %
121.88%
174.59%
71.95%
100.28%
92.20%
158.86%
164.68%
0.00%
0.00%
0.00%
0.00%
-0.01 %
0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
-0.01 %
0.00%
0.01%
0.00%
0.00%
Table B-16e: Running Mode Emissions [calculated by MOVES 2010 Model]—Percent Change between SMOKE and
Adjusted Calculations
-------
EMF Inventory
AL
OTHER
PEC 72
44
PMC 72 PMFINE 72
11
19
WV
Table B-17a: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]-
Air Pollutants
POC 72
27
Pre-SMOKE: Particulate
-------
EMF Inventory
Wl
WY
TOTAL
OTHER
229
PEC 72
45
2076
PMC 72 PMFINE 72
12
2
537
19
882
0.22
0.03
10.13
70
3268
0.21
0.04
9.82
-------
SMOKE
OH
WA
OTHER
4.825021578
0
5.274235024
2.996637621
3.962664837
2.918654519
0.823120642
0.351146315
17.16713151
9.540179456
0
1.259062044
9.509440302
5.816606756
2.832713945
2.504565221
3.986637455
3.690261744
1.230914532
5.14252319
4.648436427
9.0831385
4.825156611
3.144978477
6.223323247
0.937288205
1.64007154
1.559537911
1.112833546
6.733301477
2.269104207
12.89703148
7.37401842
WV
0.647287929
9.032719897
018188
2.964231992
9.765923378
0.70387308
4.612679112
0.753787596
6.20614373
18.82044192
2.404953234
0.532633476
7.866446645
4.882274949
1.862014584
PEC 72
43.79823575
48.11191565
27.20017813
35.88597276
26.55796414
7.475017224
3.190333063
155.6999307
87.00498322
0
11.37575842
86.29780993
52.71724929
25.66625143
22.69341766
36.21426115
33.4805624
11.1554835
46.66855482
42.41535233
81.9643829
43.87600842
28.5494349
56.31109344
8.466514438
14.86068398
14.22214135
10.13957759
61.28011497
20.5568238
117.1334619
66.82838164
5.864958415
81.70353919
35.33747439
26.94938871
88.62599756
6.419746799
41.80192838
6.830253697
56.23053931
171.085475
21.72697432
4.827623032
71.37430546
44.35811317
0.417920049
0
0.389846206
0.259901001
0.367175152
0.23451653
0.070355331
0.029598713
1.524250181
0.711170125
0
0.124135639
0.830003483
0.527057689
0.258741591
0.228646891
0.33783559
0.324480475
0.111696159
0.448751997
0.340176921
0.92468186
0.396209803
0.271975242
0.590102008
0.092973461
0.149646026
0.116402575
0.085591836
0.537843869
0.208042296
1.09918197
0.669326742
0.059092237
0.864469629
0.35601799
0.244793113
0.85221742
0.052319529
0.41906675
0.068724378
0.567219553
1.560194117
0.2376839
0.048192042
0.690400635
0.411471486
0.169074367
PM2 5
0.417920049
0.389846206
0.259901001
0.367175152
0.234516532
0.070355331
0.029598713
1.524250181
0.711170125
0
0.124135639
0.830003483
0.527057689
0.258741591
0.228646891
0.33783559
0.324480475
0.111696159
0.448751997
0.340176921
0.924681868
0.396209803
0.271975242
0.590102008
0.092973461
0.149646026
0.116402575
0.085591836
0.537843869
0.208042296
1.099181975
0.669326742
0.059092237
0.864469629
0.35601799
0.244793113
0.85221742
0.052319529
.41906675
0.068724378
0.567219553
1.560194117
0.237683945
0.048192042
0.690400635
0.411471486
0.169074367
Table B-17b: Cold Start Mode
Air Pollutants
16.87463571
Vehicle Emissions [calculated by MOVES 2010 Model]—SMOKE:
PMC 72
11.29387887
°
12.45042378
7.068016446
9.253652673
6.893436179
1.936662643
0.829456946
40.14912184
22.60484719
0
2.96124991
22.41566108
13.59732998
6.657508557
5.853278659
9.341336332
8.633220787
2.87760545
12.1324754
10.93002838
21.29744308
11.37952523
7.299983245
14.63502042
2.184784801
3.839473206
3.647031752
2.613486444
15.84824892
5.312581447
30.35463582
17.33775349
1.512906188
21.07511886
9.114874033
6.99505845
23.0444109
1.648191604
10.85998843
1.761851221
14.63081808
44.04778452
5.630218643
1.228393327
18.54568296
11.50249651
4.376834163
Particulate
-------
SMOKE
Wl
WY
TOTAL
4.929050304
0.770633112
226
44.73014644
6.962701654
2,053
0.430451474
0.075994616
20
0.430451474
0.075994616
20
PMC 72
11.53517397
1.796652722
531
-------
AL
CO
MA
18.53884742
°
20.44030964
11.6182212
15.19346947
11.32617834
3.18159306
1.363440864
65.91028853
37.13863776
0
4.871425343
36.84443548
22.32454152
10.94191218
9.610356322
15.33354299
14.17209081
4.724645359
19.94509841
17.9299984
35.02854897
18.69560729
11.96449434
24.06501496
3.588568153
6.305839823
5.977764734
4.28806605
26.02175146
8.725816124
49.86890381
28.49569492
2.484059481
34.60919085
14.96558596
11.49414629
37.88494541
2.7020557
17.85355787
2.892765643
24.05979067
72.27335714
9.254628439
2.011831324
30.48582968
18.898622
7.193297839
0.213715372
0
0.234763935
0.132724648
0.175107062
0.129590965
0.036474625
0.015567377
0.759744264
0.424544475
0
0.055508336
0.421093437
0.257236098
0.12523935
0.110733632
0.176709117
0.16336971
0.054433748
0.227721259
0.206967289
0.399947552
0.214094788
0.139308223
0.274771915
0.041312818
0.072513148
0.069397554
0.049476645
0.299018877
0.100307864
0.571557621
0.326091734
0.028618265
0.398674669
0.17243080
0.1315004
0.432451319
0.031325431
0.203973996
0.033328478
0.274379184
0.834818697
0.106017582
0.023556597
0.348273594
0.216447086
0.082340713
68.56913375
°
75.83036084
43.10791834
56.15401015
42.03762044
11.79235647
5.061477648
243.7157725
137.9922682
0
18.06182113
136.6749986
82.53965828
40.54600263
35.52896752
56.73453342
52.40914036
17.46867078
74.01287643
66.40782332
129.7270476
69.35224282
44.09760677
89.20846057
13.25639963
23.32885497
22.09112408
15.87616352
96.44226856
32.28355727
184.8593601
105.6083673
9.183858199
127.8823398
55.32784338
42.64956089
140.5951031
9.990914863
66.2043614
10.69490578
89.26823845
267.264557
34.24838506
7.396001036
113.0969135
70.08173052
26.65641143
Table B-17bi: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—SMOKE:
Air Pollutants
0.204204677
0
0.155082271
0.127176353
0.19206809
0.104925566
0.033880706
0.014031335
0.764505917
0.28662565
0
0.068627303
0.408910046
0.269821591
0.13350224
0.117913259
0.161126474
0.161110766
0.057262411
0.221030738
0.133209632
0.524734315
0.182115015
0.132667019
0.315330093
0.051660643
0.077132878
0.047005021
0.036115191
0.238824992
0.107734431
0.527624354
0.343235007
0.030473972
0.465794959
0.113292713
0.419766101
0.020994098
0.215092754
0.035395901
0.292840369
0.72537542
0.131666364
0.024635446
0.342127041
0.1950244
.086733654
Particulate
-------
Wl
WY
TOTAL
18.93576646
2.950963365
872
0.218262493
0.033974823
10
70.03356283
10.90165247
3,231
0.21218898
0.042019793
10
-------
MN
SD
4.824998912
5.274564701
2.996684164
3.962676845
2.918398661
0.823171881
0.351122717
17.16724216
9.540192145
1.259054604
9.509056569
5.816697329
2.832846939
2.504594733
3.986639281
3.690262063
1.230908164
5.142350605
4.648564524
9.083078851
4.825154296
3.144927872
6.223433591
0.937291723
1.640084578
1.559389292
1.112780506
6.733349309
2.269082258
12.89732389
7.373964568
0.647309844
9.03272514
78.95329253
82.31326346
19.99817668
20.94789312
57.56955763
14.64747546
3.899956476
2.964267502
9.765703211
0.703867207
4.612633115
0.753791521
6.20628671
18.82049956
2.404972361
0.532632252
7.866554067
4.882289786
1.862255161
144.1175385 36.04460684
97.12310941 24.48838815
20.74699689 5.238084625
8.549331176
2.16761776
186.8098887
158.6254891
45.67022083
328.5373916
184.9128951
115.944987
70.59970734
95.37640132
51.46339327
55.4908014
133.5168421
164.6326996
342.1022442
263.2883898
49.25105158
162.4495292
38.33021217
60.74431887
30.92404564
46.05432601
192.3806544
57.66030696
442.2459854
136.789681
41.5322457
292.3316088
81.66715515
75.49470741
316.3086196
23.30698348
73.38345673
34.8965657
122.9329666
288.8368184
82.15332919
25.43406688
47.85200199
40.48909562
11.53130294
82.83981668
46.32837103
29.14206543
17.71460837
23.99468336
13.08513104
13.85693299
33.81483394
41.18996865
86.16525982
66.04415586
12.38073822
41.11702281
9.579823425
15.21952626
7.771642969
11.50688909
48.41544538
14.51805812
111.3373659
34.765946
10.34561192
73.21487518
20.5858494
19.0995709
79.90622392
5.81289191
18.73862306
8.711779443
31.29692559
73.16528525
20.65755512
6.260310954
176.4920879 44.77816328
131.9143236 33.3085331
50.89658272 12.8498837
29.54877911
31.20819517
21.2453285
49.07534555
33.66308716
7.368168284
3.063489922
75.65347823
59.86088979
15.76406386
113.5698754
63.72543339
39.46974774
24.61421343
33.87168104
19.80264183
18.61333747
47.48988289
56.2034544
117.3841094
88.06335046
18.36107915
57.69588916
12.94279926
20.71383001
11.1875035
15.53668586
67.28688691
20.38189736
152.6265257
50.61116212
13.65897426
100.552013
29.47460855
26.86157192
233
7.959170293
27.85858394
11.68414496
45.2408272
109.0775443
28.30629099
8.33092451
63.80446776
46.56591121
17.94350818
0.213714267
0.234778726
0.132726529
0.175107549
0.129579349
0.036477004
0.015566344
0.759749126
0.424544871
0.055508137
0.421076764
0.257239871
0.125245452
0.110734902
0.176709088
0.163369859
0.05443341
0.227713499
0.206973211
0.39994597
0.214094642
0.139306015
0.274777193
0.041312845
0.072513926
0.069391313
0.049474155
0.299021003
0.100306935
0.571570474
0.326089298
0.028619319
0.398675914
0.172428011
0.13150218
0.432444409
0.031325144
0.203971956
0.033328713
0.274385585
0.834821252
0.106018568
0.023556563
0.348278641
0.216447995
0.082351033
123.6166484
129.6690999
91.24486523
225.5632654
153.7274599
32.72257311
13.56391622
292.430896
251.6076025
72.52582309
520.3173042
289.5367578
183.1867942
110.5421392
149.4241259
80.56201304
86.91068386
211.7385629
257.778108
541.509
416.2123007
76.07814529
257.3678029
60.0272892
95.36355898
48.14003155
72.12557114
302.7666316
90.56396856
698.6479542
216.1848682
65.04459287
457.5852987
127.8724309
119.487315
501.8473982
36.27336615
116.2293718
54.65003278
195.1754976
451.2849652
129.5066965
38.98000251
279.6894451
208.4170904
80.40833522
0.204203793
0.155091765
0.127178333
0.192068402
0.104916009
0.033883012
0.014030402
0.76450796
0.286626464
0.068626471
0.408892124
0.26982598
0.133508099
0.117914722
0.161126686
0.161110717
0.057262137
0.221022385
0.133213984
0.524732192
0.182114935
0.132665025
0.315335039
0.051661089
0.077133881
0.047000838
0.036113847
0.238826762
0.107733206
0.527633965
0.343232539
0.030474926
0.46579358
0.183584303
0.113294537
0.419754874
0.020993789
0.215090648
0.035396037
0.292846037
0.725377107
0.131667125
0.024635173
0.342132154
0.195025213
0.086744824
Table B-17c: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—Adjusted Particulate Air
Pollutants
-------
Wl
TOTAL
4.929097214
0.770643127
226.935372
219.7812988
34.80682859
5975.344197
5,975
54.87987039
8.691407966
1506.49629
73.76362906
11.67227244
2109.490878
2,109
17,735
M2.5
0.218264536
0.033975204
10.04944675
10
344.1620332
54.50773307
9412.777366
9,413
0.212190951
0.042020289
9.736214334
10
-------
SMOKE
GA
MN
VT
OTHER
0.06%
-0.21%
0.17%
-0.28%
-0.26%
-0.26%
-0.64%
-0.48%
-0.12%
-0.13%
-0.29%
-0.25%
-0.13%
PEC 72
PMC 72 PMFINE 72
-0.11%
0.02%
0.20%
0.37%
-0.20%
-0.56%
-0.38%
-0.13%
0.25%
-0.27%
0.19%
-0.05%
-0.04%
-0.08%
-0.55%
0.26%
-0.38%
0.00%
0.25%
-0.27%
-0.23%
-0.18%
-0.02%
-0.54%
0.01 %
0.20%
-0.22%
WY
Table B-17d:
I and SMOKE
-0.27%
0.18%
-0.05%
-0.04%
-0.08%
-0.55%
0.26%
-0.38%
0.00%
0.25%
-0.27%
-0.23%
-0.18%
-0.02°,
-0.54%
0.01%
0.20%
-0.22%
-0.08%
-0.43%
0.25%
-0.19%
-0.45%
0.17%
-0.20%
0.050/
0.06%
-0.22%
0.17%
-0.28%
-0.26%
-0.26%
-0.64%
-0.48%
-0.12%
-0.13%
-0.29%
-0.25%
-0.13%
-0.11%
0.02%
0.20%
0.36%
-0.20%
-0.56%
-0.38%
-0.13%
125%
-0.27%
0.18%
-0.06%
-0.04%
-0.08%
-0.55%
0.26%
-0.39%
0.00%
0.24%
-0.27%
-0.23%
-0.19%
-0.03%
-0.54%
0.01 %
0.20%
-0.22%
-0.08%
-0.44%
0.24%
-0.19%
-0.45%
0.17%
-0.20%
105%
0.06%
-0.22%
0.17%
-0.28%
-0.26%
-0.26%
-0.64%
-0.48%
-0.12%
-0.13%
-0.29%
-0.26%
-0.13%
-0.11%
0.02%
0.20%
0.36%
-0.20%
-0.56%
-0.38%
-0.13%
0.25%
-0.27%
0.18%
-0.06%
-0.04%
-0.08%
-0.55%
0.26%
-0.39%
0.00%
0.24%
-0.27%
-0.23%
-0.19%
-0.03%
-0.54%
0.01 %
0.20%
-0.220/
-0.08%
-0.44%
0.24%
-0.19%
-0.45%
0.17%
-0.20%
0.05%
0.06%
-0.21 %
0.17%
-0.28%
-0.26%
L26%
-0.64%
-0.48%
-0.12%
-0.13%
-0.29%
-0.25%
-0.13%
-0.11%
0.02%
0.20%
0.37%
120%
-0.56%
-0.38%
-0.13%
0.25%
-0.27%
0.19%
-0.05%
-0.04%
-0.08%
-0.55%
0.26%
-0.38%
0.00%
0.25%
-0.27%
-0.23%
-0.18%
102%
-0.54%
0.01%
0.20%
-0.22%
-0.08%
-0.43%
0.25%
3.19%
-0.45%
0.17%
-0.20%
0.05%
POC 72
0.05%
-0.22%
0.17%
-0.28%
-0.26%
-0.26%
-0.64%
0.07%
-0.19%
0.18%
-0.27%
-0.27%
-0.26%
-0.63%
-0.47%
-0.11%
-0.11%
-0.28%
-0.24%
-0.12%
-0.10%
0.04%
0.20%
0.38%
-0.20%
-0.55%
-0.37%
-0.10%
0.26%
-0.26%
0.20%
-0.04%
-0.03%
-0.06%
-0.55%
0.27%
-0.38%
0.02%
0.26%
-0.26%
-0.22%
-0.17%
-0.01%
-0.52%
0.03%
0.21 %
-0.21c
-0.07%
-0.42%
0.26%
-0.18%
-0.43%
0.19%
-0.19%
0.06%
Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—Percent Change between EMF
Calculations
-------
SMOKE
AL
AR
PMC 72 PMFINE 72
ME
MN
MO
Oregon
Rl
SD
TX
VT
WA
Wl
80.27%
71.09%
111.65%
301.60%
265.70%
177.55%
167.98%
19.98%
82.32%
301.47%
280.70%
250.76%
351.74%
211.10%
163.37%
53.71%
397.43%
186.10%
288.14%
317.38%
500.07%
72.51%
188.49%
352.73%
308.76%
117.44%
354.20%
213.94%
180.49%
277.56%
104.69%
608.14%
257.80%
131.11%
180.14%
256.90%
263.05%
75.55%
410.91%
118.62'
68.83%
278.12%
426.84%
147.28%
197.38%
201.62%
391.35%
399.90%
252.68%
72.55%
394.47%
113.91%
66.10%
266.91 %
409.63%
141.45%
189.58%
193.59%
375.76%
383.76%
228.49%
87.15%
262.32%
158.58%
133.58%
206.06%
77.61%
449.87%
190.54%
96.95%
133.70%
190.71%
194.56%
56.04%
303.91 %
88.03%
50.92%
205.86%
314.10%
109.29%
146.40%
149.45%
289.55%
295.54%
0.00%
0.01 %
0.00%
0.00%
-0.01%
0.01 %
-0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
-0.01%
-0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01 %
0.00%
0.00%
80.28%
71.00%
111.67%
301.69%
265.69%
177.49%
167.98%
19.99%
82.33%
301.54%
280.70%
250.79%
351.80%
211.13%
163.37%
53.72%
397.52%
186.08%
288.17%
317.42%
500.14%
72.52%
188.50%
352.82%
308.78%
117.92%
354.30%
213.94%
180.53%
277.93%
104.70%
608.25%
257.82%
131.12%
180.16%
256.95%
263.06%
75.56%
410.99%
118.64%
68.85%
278.14%
427.04%
147.30%
197.39%
201.65%
391.42%
400.00%
0.00%
0.01 %
0.00%
0.00%
-0.01%
0.01 %
-0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
-0.01%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.00%
0.01 %
0.00%
0.00%
Table B-17e: Cold Start Mode Vehicle Emissions [calculated by MOVES 2010 Model]—Percent Change between
SMOKE and Adjusted Calculations
-------
Emission Sector
alm_no c3
afdust
seca_c3
beis
ocean_c!2
on_moves_runpm
on_moves_startpm
"
SMOKE TOTAL
US
Low level totals
ptipm elevated
ptnonipm elevated
seca elevated
othpt elevated
ptfire elevated
Model-Ready
Domain Totals
85,223
85,223
81,972
102
3,149
578,005
3,221,626
1,306,023
33,683,204
7,374,458
37,940,746
17,946,551
4,098,544
5,580,591
270,007
352,245
48,647
15,399
3,028,218
2,022,055
1,051,197
358,175
1,513,094
7,130,325
1,793,775
801,078
583,081
1,732,433
121,308,326
110,323,168
83,948,885
574,983
2,049,781
98,470
968,174
33,599,600
429,823
429,823
35,186
350,915
43,720
85,224
121,239,893
429,821
115,796
5,120,931
4,283,650
4,481,893
20,829
46,513
•
21,138
550263
5,120,637
23,147,732
20,712,376
16,418,089
3,022,918
1,591,461
1,058
708,006
357367
336,469
224,159
116,800
39,707
168,122
728,878
183,364
83,113
59,604
•
177,093
2,225,510
1,965,993
1,487,096
335,879
176,831
108,189
78,668
39707.4
23,156,594
2,226,371
% Difference
0.00%
-0.06%
0.00%
0.06%
Actual Difference 0.38 -68,433.91 -1.71 74.06
Table B-18: Column Merge Grid Emissions [to obtain domain totals]
-0.01 %
-294.49
0.04%
8,861.47
0.040/
860.79
-------
PMC PMFINE PNO3
SO2 SULF
ptipm
ptnonipm
othpt
ptfi,
nonpt
on_noadj
nonroad
othar
othon
3,364,686
2,246,214
1,167,996
397,883
1,681,216
7,859,203
1,977,139
642,685
15,275
39,632
6,248
288,626
84,179
12,730
102,020
56,688
8,790
105,533
211,199
74,025
514,272
272,240
70,927
9,888
1,054,592
4,801
401,028
270,688
105,606
838,638
497,762
18,340
17,084
253,065
1,715
1,132
4,037
337
15,122
3,105
236
380
997
18
23,938
63,621
8,412
1,692,061
463,336
9,738
61,132
123,201
4,755
66,039
64,327
20,611
22,773
28,164
1,550
687
8,924
75
1,943
alm_no_c3
afdust
seca c3
ocean_c!2
on_moves_runpm
on_moves_
startpm
1,909,526
^m
1,165,721
2,076,782
43,716
1,530
904
5,176
5,975
2,679 2,784
7,830,978 979,064
7,866 48,790
3,665
1,506
6,532
2,109
62 9,955 164 154,016
1,731 45,790 2,729
0 904 39,804 750,725
14 30,623 275
10 9,413 10
SMOKE TOTAL
US
Low level totals
ptipm elevated
ptnonipm
elevated
seca elevated
othpt elevated
ptfire elevated
Model-Ready
Domain Totals
% Difference
671,490
599,764
339,992
15,137
24,347
2,872
288625.5825
10,164,172 3,443,206
27,181
9,030,754 3,082,820 25,829
9,367,308
105,290
94,026
72,542
514272
1,912,445
400,655
142,049
48,864
98,291
838,638
8,122
1,128
2,620
0
196
15121.94414
671,879 10,161,307 3,440,942
0.06%
-0.03%
-0.07%
27,188
0.03%
Actual Difference 388.88 -2,864.36 -2,264.09 6.80
Table B-18i: Column Merge Grid Emissions [to obtain domain totals]
2,546,880 256,132 16,378,068 249,993
2,410,512 226,522 13,772,107 237,113
787,358 62,811 1,997,526 23,957
23,855 65,979 9,093,304 198,170
38,221 46,415 1,925,561 16,929
905 39,806 751,261 0
5,309 18,384 2,377,075 10,938
1.69E+06 22761.1 233729
2,547,709 256,155 16,378,456 249,993
0.03% 0.01% 0.00% 0.00%
829.75 23.44 387.75 0.15
-------
-------
Appendix C
Metadata
Output Data
The pm25_surface_12km_2007.csv (or o3_
surface_12km_2007.csv) file is the output file from EPA's
Hierarchical Bayesian Model (HBM) that combines PM2 5 (or
O3) monitoring data from National Air Monitoring Stations/
State and Local Air Monitoring Stations (NAMS/SLAMS)
and Models-3/Community Multiscale Air Quality (CMAQ)
computer-simulated PM2 5 or O3 data. This file provides a
spatial interpolation of air quality that takes advantage of the
strengths of monitoring network observations and modeling
estimates to generate daily surrogate measures for PM2 5
and relates these measures to available public health data.
The file covers the contiguous lower 48 states of the United
States. The time frame covered is January 1, 2007 through
December 31, 2007. The standard errors of the estimates
should be taken in to account when using the results. This
file is a comma-separated values (CSV) file. This is a flat
file that is platform-independent. In the Microsoft Windows
computing environment, this file can be read easily by Excel.
The file contains the posterior means and standard errors of
the estimated space-time surface, the posterior means and
standard errors of the estimated space-time bias surface, and
the posterior means and standard errors for a surface made up
of 12 km x 12 km contiguous grids. The contiguous 12 km
x 12 km grids cover the whole lower 48 contiguous states of
the United States. The file includes the following variables:
Date, Latitude, Longitude, posterior mean estimated PM2 5
or O3 concentration on natural log scale (PredAvg), row
position of grid cell, column position of grid cell, standard
error of the estimated PM2 5 or O3 concentration on the
natural log scale (PredStd), the natural log of the estimated
CMAQ model data bias (Bias), and the standard error of the
estimated CMAQ model data bias (BiasStd). Values of -999
in the data set represent missing (or intentionally excluded)
values. Excluded values are generated when grid cells are
not included in the model calculation. These are not actual
missing values but intentionally not included in the grid for
calculation of the estimated surface. An example of such a
grid cell not included is grid cells that fall over water.
Input Data
The actual monitoring data from the NAMS/SLAMS network
were downloaded from the Air Quality System (AQS)
database. Only Federal Reference Method (FRM) samplers
and only those samplers with sample duration of one day
(24-hour integrated sample) were included in the data set.
The CMAQ data was created from version 4.7 (4.7.1) of
the model which includes improved aqueous chemistry
and photolysis mechanisms. The PM2 5 data is a 24-hour
integrated PM2 5 concentration calculated on a 12-km x
12- km grid for the entire United States. These CMAQ
results are based on emission inputs for the 2005v4
Platform from the 2005 National Emission Inventory (NEI).
Version 2, which includes emissions of CO, NOx, VOC.
SO2, NH3, PM10, and PM2 5 and hazardous air pollutants
(HAPs), including chlorine, HC1, benzene, acetaldehyde.
formaldehyde, and methanol. In addition, the meteorological
data used for these model results is from the Weather
Research and Forecasting Model (WRF) version 3.1
simulations (Advanced Research WRF [ARW] core).
The HBM combines the actual monitoring data (NAMS/
SLAMS), the estimated PM2 5 or O3 concentration surface
(CMAQ), and the prediction of PM2 5 or O3 through space
and time. The model assumes that both the actual monitoring
data and the CMAQ data provide good information about
the same underlying pollutant surface, but with different
measurement error structures. It gives more weight to the
accurate monitoring data in areas where monitoring data
exists and relies on the CMAQ data and satellite data in
areas where no monitoring data is available. The modeling
is divided into hierarchical components where each level of
the hierarchy is modeled conditional on the preceding levels.
To fit the model, a custom-designed Monte Carlo Markov
Chain (MCMC) software algorithm was used. Model-specific
input parameters of statistical distributions for the model and
simulation parameters (priors) are specified for each run of
the model. The projections for the grid cell structure are as
follows:
Projection: Lambert conformal with spherical earth.
radius = 6370.0 km
12-km Resolution
NCOLS = 459
NROWS = 299
P_ALP= 33.00
P_BET = 45.00
P_GAM = -97.00
XCENT = -97.00
YCENT = 40.00
XORIG = -2556000.0
YORIG = -1728000.0
XCELL = 12000.00
YCELL = 12000.00
These values are for the 12-km grid resolution of CMAQ.
-------
Monitor and HBM Concentration (us/
Figure C-1. PM25 Monitoring Data and CMAQ Surface (Separately Displayed—White Spheres Represent Monitor
Locations and Associated Concentration Values)
Monitor and HBM Concentration (ug/m1)
Figure C-2. Combined PM25 Monitoring Data and CMAQ Surface (Via HBM)
-------
The geographic boundaries of the HB output cover the
following region:
111.1 degrees W longitude—West Bounding Coordinate
65.4 degrees W longitude—East Bounding Coordinate
51.25 degrees N latitude—North Bounding Coordinate
23.0 degrees N latitude—South Bounding Coordinate
The definitions for the 12-km x 12-km CMAQ grid cells are
contained in a text (*.txt) file. The file contains the latitude
and longitude coordinates of the following points for each
grid cell: 1) center; 2) southwest corner; 3) southeast corner;
4) northwest corner; and 5) northeast corner. The AQS data
for PM25 and O3 are contained in separate text (*.txt) files.
These files contain the following data: parameter occurrence
code (for pollutant); state code; city code; site ID; sampling
frequency; data; sample value; monitor protocol (i.e., 1
in 3 days); partition, etc. Example figures of a) a separate
air quality monitor with CMAQ data, and b) combined air
quality monitor data and CMAQ data for PM2 5 are shown
below.
Use of HB Data to Generate Health Indicators
The HB output data can be used to generate health (air)
indicators which are useful to researchers when developing
health impact assessments (HIA). The HB output is provided
in a gridded (x-y/row-column) format and that format must
be translated to different coordinate systems (e.g., county-
based/relevant coordinates) to provide health indicator data
for the area(s) of interest. An important coordinate projection
system used as a standard coordinate representation format to
express different location designation systems in consistent
terms is the Lambert Conformal Conic (LCC) projection
coordinate system. The North American Datum (NAD)
geodetic system describes the Earth's ellipsoid based on the
latitude and longitude location of an initial point, and serves
as the basis of maps and surveys of the Earth's surface.
The NAD-27 datum is based on the Clarke Ellipsoid (Earth
spheroid) of 1866 and is centered at a base station on the
Meades Ranch in Kansas. The NAD-83 grid projection/
datum is based on the Geodetic Reference Spheroid (GRS)
of 1980 and is geocentric (e.g., based on the Earth's center
with no directionality or initial point located on the Earth's
surface). The NAD coordinate system is important because
health-related data (used to calculate health indicators) are
collected and cataloged based on this coordinate system (e.g..
U.S. Census data is based on NAD-83 coordinates).
The HB output provides ambient concentration data for both
ozone and fine paniculate matter in x-y-based grid cells, and
to correlate this concentration data with health data, the x-y
locations must be 'mapped' to latitude/longitude locations
and then mapped to the correct datum/projection system
linked with the health data. The typical latitude and longitude
grids are based on the World Geodetic System (WGS)
projection for 1984 (WGS-84), while the U.S. Census uses
the NAD-83 grid and the SAS statistical analysis software
uses NAD-83 grid projection. When generating the linkage
between the ambient concentration data and the health data.
a methodology or protocol must be developed to relate
the appropriate coordinate system/geocoding information
between them.
CDC, EPA, and the state departments of air and/or health
of New York, New Jersey, Massachusetts, and Minnesota
have developed an initial set of health indicators using
the HB output data correlated with available health data/
information. They have developed a 'relationship file' to
map the x-y-based grid cells to latitude/longitude format
with the appropriate datum/projection system(s). Shapefile
information also resides in this file allowing compatibility
with GIS map formats/applications. The relationship file has a
grid ID, representing the row and column of the grid cell. This
grid ID is a six-digit identifier from the HB raw data set that
concatenates column and row designation. There are 66,000
grid cells per day times 365 days worth of data (the New York
State Health Department uses SAS to process this data and
CDC uses ArcGIS to process the data). The relationship file
recognizes the importance of having consistent geocoding
data for HB grids for Health Impact Analyses (HIA). The U.S.
Census files (TIGER2000 files) are in NAD-83 format, which
is what the SAS statistical software processes. The WGS-84
format is almost exactly like NAD-83 format except there is
an offset of a few feet for grid points (centroids). WGS-84
is used by the CMAQ air quality model. Air Quality models
such as CMAQ, which serve as input to the HB model, uses
the meteorological software MM5 which is based on the
Lambert Conformal Conic (LCC) projection. As long as the
HB output data (latitude and longitude grid coordinates)
can be mapped to the NAD-83 or NAD-84 (WGS-84) to
match census data, air indicators can be generated for HIA.
The x and y coordinates given in the HB are used to plot the
latitude and longitude with an offset to match non-NAD-83
grid references. When defining Earth points, coordinate
information should be modified into a format compatible
with county-based maps and transformed into an elliptical
projection. NetCDF file can be converted in ArcGIS to make
shape files. The New Jersey state air department used the
Theissen Polygon tool on HB data to generate shapefiles.
How CMAO and HB x-y grid locations are transformed to
latitude and longitude values:
There is an IOAPI file providing rows/columns, cell height/
width, origin in LCC, offset by 1A cell width/height to get
center cell (centroid). Conversion uses an LCC routine in
IOAPI library, passing parameters (Earth radius, central
meridian [longitude: -97 degrees]), two key latitude values
33 degrees and 45 degrees, central meridian, -97 and latitude
of origin, 40.0. These arguments are required for the LCC
routine, which returns latitude and longitude. The code for
transforming an LCC projection (e.g., CMAQ and HB Model
x-y grid coordinates) to latitude and longitude values:
-------
LCPGEO Fortran Code—LCC Conversion Program
Fortran Code for converting Lambert Conformal Conic to
geodetic (lat/lon):
subroutine lcpgeo(iway,phic,xlonc,truelatl ,truelat2,xloc.
yloc, & xlon,ylat)
write(*,*)'INCALL:',phic,xlonc,truelatl,truelat2
LCPGEO performs Lambert Conformal to geodetic
(lat/lon) translation
Code based on the TERRAIN preprocessor for MM5
v2.0, developed by Yong-Run Guo and Sue Chen,
National Center for Atmospheric Research, and
Pennsylvania State University
10/21/1993
Input arguments:
iway Conversion type
0 = geodetic to Lambert Conformal
1 = Lambert Conformal to geodetic
phic Central latitude (deg, neg for southern hem)
xlonc Central longitude (deg, neg for western hem)
truelatl First true latitude (deg, neg for southern hem)
truelat2 Second true latitude (deg, neg for southern
hem)
xloc/yloc Projection coordinates (km)
xlon/ylat Longitude/Latitude (deg)
Output arguments:
xloc/yloc Projection coordinates (km)
xlon/ylat Longitude/Latitude (deg)
data conv/57.29578/, a/6370./
c—Entry Point
c
if (phic.lt.O) then
sign= -1.
else
sign= 1.
endif
pole = 90.
if (abs(truelatl).gt.90.) then
truelatl = 60.
truelat2 = 30.
truelatl = sign*truelatl
truelat2 = sign*truelat2
endif
xn = aloglO(cos(truelatl/conv)) - aloglO(cos(truelat2/
conv))
xn= xn/(aloglO(tan((45. - sign*truelatl/2.)/conv)) -
& aloglO(tan((45. - sign*truelat2/2.)/conv)))
psil= 90. - sign*truelatl
psil = psil/conv
if (phic.lt.O.) then
psil = -psil
pole = -pole
endif
psiO = (pole - phic)/conv
xc = 0.
yc = -a/xn*sin(psil)*(tan(psiO/2.)/tan(psil/2.))**xn
c—Calculate lat/lon of the point (xloc,yloc)
c
if (iway.eq.l) then
xloc = xloc + xc
yloc = yloc + yc
if (yloc.eq.O.) then
if (xloc.ge.O.) flp = 90./conv
if (xloc.lt.0.) flp = -90./conv
else
if (phic.lt.O.) then
flp = atan2(xloc,yloc)
else
flp = atan2(xloc,-yloc)
endif
endif
flpp = (flp/xn)*conv + xlonc
if (flpp.lt.-180.) flpp = flpp + 360.
if (flpp.gt. 180.) flpp = flpp - 360.
xlon = flpp
c
r = sqrt(xloc*xloc + yloc*yloc)
if(phic.lt.0.)r=-r
cell = (r*xn)/(a*sin(psil))
rxn= 1.0/xn
cell = tan(psil/2.)*cell**rxn
ce!2 = atan(cell)
psx = 2.*cel2*conv
ylat = pole - psx
c
c—Calculate x/y from lat/lon
c
else
ylon = xlon - xlonc
if (yloagt. 180.) ylon = ylon - 360.
if (ylon.lt.-180.) ylon = ylon + 360.
flp = xn*ylon/conv
psx = (pole - ylat)/conv
r = -a/xn*sin(psil)*(tan(psx/2.)/tan(psil/2.))**xn
if(phic.lt.0.)then
xloc = r*sin(flp)
yloc = r*cos(flp)
else
xloc = -r*sin(flp)
yloc = r*cos(flp)
endif
endif
write(*,*)xloc,xc,yloc,yc
xloc = xloc - xc
yloc = yloc - yc
return
end
*****************************************
CMAQ Projection Information—Source:
http: //www.b aronam s. com/products/i oapi/GRID-
DESC.html
-------
Coordinate Information
COORD-NAME
COORDTYPE
P ALP
P BET
P GAM
XCENT
YCENT
'LAM 40N97W
33.000
45.000
-97.000
-97.000
40.000
Grid Information
GRID-
NAME
COORD-NAME
XORIG
YORIG
XCELL
YCELL
NCOLS
NROWS
NTH IK
12US1
'LAM 40N97W
-1008000 -1620000
12000 12000
279
240
P_ALP = "PROJ ALPHA"
P_BET = "PROJ_BETA"
LAMGRD3 = P_ALP <= P_BET. These are the
two latitudes which determine the projection
cone.
P_GAM = the central meridian
XCENT, YCENT = lat/lon coordinates for the
center (0, 0) of the Cartesian coordinate sys-
tem.
X_ORIG is the X coordinate of the grid
origin (lower left corner of the cell at
column=row=l), given in map projection units
(meters, except in Lat-Lon coordinate systems).
Y_ORIG is the Y coordinate of the grid
origin (lower left corner of the cell at
column=row=l), given in map projection units
(meters, except in Lat-Lpn coordinate systems).
X_CELL is the cell dimension parallel to the X
coordinate axis, given in map projection units
(meters, except for Lat-Lon coordinate sys-
tems).
Y_CELL is the cell dimension parallel to the Y
coordinate axis, given in map projection units
(meters, except for Lat-Lon coordinate sys-
tems).
NCOLS is the number of columns (dimensionality
in the X direction).
NROWS is the number of rows (dimensionality in
the Y direction).
NTHIK is the thickness (number) of cells on the
boundary domain required to accurately de-
scribe boundary mass flux (e.g., CMAQ uses
NTHIK = 1)
ArcMap Projection Information (HB grid ex-
ample):
Data Type: File Geodatabase
Feature Class
Location: U:\Projects\MMc-
courtney\Gri ds\templ ate s\grid_templ ate s. gdb
Feature Class: template_mdhi_12_
nb
Feature Type: Simple
Geometry Type: Polygon
Projected Coordinate System: NAD 1983 Lam-
bert_Conformal_Conic
Projection: Lambert_Conformal_Conic
False_Easting: 0.00000000
False_Northing: 0.00000000
Central Meridian: -97.00000000
Standard_Parallel_l: 3300000000
Standard_Parallel_2: 45.00000000
Latitude_Of_Origin: 40.00000000
Linear Unit: Meter
Geographic Coordinate System: Custom -
SpheroidGC S_North_American_l 983
Datum:
Prime Meridian: Greenwich
Angular Unit: Degree
-------
Changing a data set's spheroid to a sphere.
1) In ArcCatalog, right click the data set of interest,
and choose Properties. Click the XY Coordinate
System tab. Click Modify...
2) From the Geographic Coordinate System of the
Projected Coordinate System Properties window,
click Modify...
Projected Coordinate System Properties
General
Name:
3) From the Geographic Coordinate System window,
first choose in the list of datum (it's at
the top) and then choose for the spheroid.
Enter 6370000 in both the semimajor and semiminor
boxes.
Geographic Coordinate System Properties
General |
Name:
[7.1®
|NAD_
Projection
Name:
| Value
e_Ea sting
False_North»ng
Central_Meridian
Standard_Parallel_1
Standaret_Parallel_2
0 .OOOOOOOOOOOOOOOOOO
0.000000000000000000
-97 -OOOOOOOOOOOOOOOOOO
33 .OOOOOOOOOOOOOOOOOO
45.000000000000000000
I
~
Linear Link
Name:
Meiers per unit:
Meter
Geographic Coordriale System
Name: Customs pliero
Spheroid:
S emmajor Axis: 6370000. OOOOOOOOOOOOOOOC
New
OK Cancel | Applj
| CustonVSpheroidG CS_N orth_Ame»ican_t383
Datum
Name:
I*
Name: |
£emimajor Axis:
••• Semirnirior Axis:
r Inverse Flattening
6370000
|6370000
!
Angular Unit
Name: {Degree
Radians per unit:
0.017453292519943299
Prime Meridan
Name: {Greenwich
Longitude: jj
OK
Cancel
Projection Information for HB Grid—Example #1
_ , . Lambert
Spherical _ ,
2001 Lat/Lon NA Degrees Conformal 0.0 0.0 -97.0 33.0 45.0 1.0 40.0 Meters
R=6370997 _
Conic
2002
2003
2004
2005
2006
2007
Spherical
R=6370000
-------
Grid Descriptive Parameters
Grid
Resolution
(km)
XORIG
-252000
2736000
•1008000
2736000
•1008000
2736000
•1008000
2736000
•1008000
2736000
•1008000
2736000
•1008000
YORIG
-1284000
-2088000
-1620000
-2088000
-1620000
-2088000
-1620000
-2088000
-1620000
-2088000
-1620000
-2088000
-1620000
XCELL
12000
36000
12000
36000
12000
36000
12000
36000
12000
36000
12000
36000
12000
YCELL
12000
36000
12000
36000
12000
36000
12000
36000
12000
36000
12000
36000
12000
NCOLS
213
148
279
148
279
148
279
148
279
148
279
148
279
NROWS
188
112
240
112
240
112
240
112
240
112
240
112
240
Projection Information for HB Grid—Example #2
CO
2001 CD
00
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s.
8
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s.
CD
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0s
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0s
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id
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-^N.
e., meters
*i.
-------
I • •:'ad/Recyclable Printed on paper that
contains a minnmum of 50% post-con
Tuber content processed diloiine free
SEPA
United States
Environmental Protection
Agency
PRESORTED STANDARD
POSTAGE & FEES PAID
EPA
PERMIT NO.G-35
Office of Research and Development (8101R)
Washington, DC 20460
Official Business
Penalty for Private Use
$300
------- |