Attachment 12_BASE G 2002 BY 

2009_18 Emission Inventories f.pdf
MACTEC, Inc. 

Documentation of the Base G 2002 Base Year, 2009 and 2018, 

Emission Inventories for VISTAS 

Prepared for: 

Visibility Improvement State and Tribal Association of the Southeast 

(VISTAS) 

Prepared by: 

MACTEC, Inc. 

______________________ ______________________ 

William R. Barnard Edward Sabo 

Sr. Principal Scientist Principal Scientist

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Table of Contents 

Introduction .................................................................................................................................................................1 

1.0 2002 BASE YEAR INVENTORY DEVELOPMENT ........................................................................................4

1.1 POINT SOURCES...........................................................................................................................................4

1.1.1 Development of 2002 Point Source Inventory .......................................................................................4

1.1.1.1 Data Sources ................................................................................................................................................ 5

1.1.1.2 Initial Data Evaluation ................................................................................................................................. 6

1.1.1.3 PM Augmentation........................................................................................................................................ 7

1.1.1.4 EGU Analysis ............................................................................................................................................ 10

1.1.1.5 QA Review of Base F Inventory................................................................................................................ 11

1.1.1.6 Additional Base G Updates and Corrections.............................................................................................. 12

1.1.1.7 Summary of Base G 2002 Inventory.......................................................................................................... 15

1.1.2 Development of Typical Year EGU inventory......................................................................................18

1.2 AREA SOURCES .........................................................................................................................................20

1.2.1 Development of a “typical” year fire inventory ..................................................................................22

1.2.2 Development of non-fire inventory ......................................................................................................31

1.2.3 2002 Base G inventory updates ...........................................................................................................34

1.2.3.1 Changes resulting from State review and comment ................................................................................... 34

1.2.4 Ammonia and paved road emissions....................................................................................................37

1.2.5 Global Changes Made for Base G.......................................................................................................38

1.2.6 Quality Assurance steps.......................................................................................................................39

1.3 MOBILE SOURCES .....................................................................................................................................40

1.3.1 Development of on-road mobile source input files and VMT estimates...............................................41

1.3.1.1 Emissions from on-road mobile sources .................................................................................................... 42

1.3.2 Development of non-road emission estimates......................................................................................45

1.3.2.1 Emissions from NONROAD model sources.............................................................................................. 45

1.3.2.2 Emissions from Commercial Marine Vessels, Locomotives, and Airplanes.............................................. 61

Base G Revisions: ..............................................................................................................................................78

1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio .............................................. 85

1.3.3 Quality Assurance steps.......................................................................................................................87

2.0 PROJECTION INVENTORY DEVELOPMENT............................................................................................88

2.1 POINT SOURCES.........................................................................................................................................88

2.1.1 EGU Emission Projections ..................................................................................................................88

2.1.1.1 Chronology of the Development of EGU Projections................................................................................ 88

2.1.1.2 VISTAS IPM runs for EGU sources.......................................................................................................... 92

2.1.1.3 Post-Processing of IPM Parsed Files ......................................................................................................... 93

2.1.1.4 Eliminating Double Counting of EGU Units ............................................................................................. 95

2.1.1.5 Quality Assurance steps............................................................................................................................. 96

2.1.1.6 S/L Adjustments to IPM Modeling Results for Base G Projections........................................................... 97

2.1.1.7 Summary of Base F and Base G 2009/2018 EGU Point Source Inventories ............................................. 98

2.1.2 Non-EGU Emission Projections ........................................................................................................110

2.1.2.1 Growth assumptions for non-EGU sources.............................................................................................. 110

2.1.2.2 Source Shutdowns.................................................................................................................................... 112

2.1.2.3 Control Programs applied to non-EGU sources ....................................................................................... 114

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2.1.2.4 Quality Assurance steps........................................................................................................................... 117

2.1.2.5 Additional Base G Updates and Corrections............................................................................................ 117

2.1.2.6 Summary of Revised 2009/2018 non-EGU Point Source Inventories...................................................... 117

2.2 AREA SOURCES .......................................................................................................................................123

2.2.1 Stationary area sources .....................................................................................................................123

2.2.1.1 Stationary area source controls ................................................................................................................ 125

2.2.1.2 Stationary area source growth.................................................................................................................. 127

2.2.1.3 Differences between 2009/2018............................................................................................................... 127

2.2.2 Agricultural area sources ..................................................................................................................128

2.2.2.1 Control assumptions for agricultural area sources ................................................................................... 128

2.2.2.2 Growth assumptions for agricultural area sources ................................................................................... 128

2.2.3 Changes to Prescribed Fire for 2009/2018 Base G...........................................................................133

2.2.4 Quality Assurance steps.....................................................................................................................138

2.3 MOBILE SOURCES ...................................................................................................................................138

2.3.1 Development of on-road mobile source input files............................................................................141

2.3.1.1 Preparation of revised 2018 input data files............................................................................................. 141

2.3.1.2 Preparation of initial 2009 input data files ............................................................................................... 144

2.3.2 VMT Data ..........................................................................................................................................145

2.3.3 Base G Revisions ...............................................................................................................................150

2.3.4 Development of non-road emission estimates....................................................................................150

2.3.4.1 NONROAD model sources...................................................................................................................... 151

2.3.4.2 Non-NONROAD model sources.............................................................................................................. 153

2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio ............................................ 188

2.3.4.4 Differences between 2009/2018............................................................................................................... 188

2.3.5 Quality Assurance steps.....................................................................................................................189

Appendix A: State Emission Totals by Pollutant and Sector

Appendix B: State VMT totals

Appendix C: State Tier 1 Emission Totals

Appendix D: VISTAS Tier 1 Emission Totals 

Appendix E: Aircraft PM Excerpt from 2001 Tucson Report 

Appendix F: Comparison of Base F and Base G On-Road Mobile Emissions

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List of Tables 

Table I-1. Inventory Version in Use by Year and Source Sector Through Base G - 2002 

Table I-2. Inventory Version in Use by Year and Source Sector Through Base G - 2009 

Table I-3. Inventory Version in Use by Year and Source Sector Through Base G - 2018 

Table 1.1-1. State Data Submittals Used for the Base F 2002 Point Source Inventory 

Table 1.1-2. Comparison of Particulate Matter Emissions from the S/L Data Submittals and 

the Base G 2002 VISTAS Point Source Inventory 

Table 1.1-3. Summary of Updates and Corrections to the Base F 2002 Inventory Incorporated 

into the 2002 Base G Inventory 

Table 1.1-4. Base G 2002 VISTAS Point Source Inventory for SO2 (tons/year) 

Table 1.1-5. Base G 2002 VISTAS Point Source Inventory for NOx (tons/year) 

Table 1.1-6. Base G 2002 VISTAS Point Source Inventory for VOC (tons/year) 

Table 1.1-7. Base G 2002 VISTAS Point Source Inventory for CO (tons/year) 

Table 1.1-8. Base G 2002 VISTAS Point Source Inventory for PM10-PRI (tons/year) 

Table 1.1-9. Base G 2002 VISTAS Point Source Inventory for PM2.5 -PRI (tons/year) 

Table 1.1-10. Base G 2002 VISTAS Point Source Inventory for NH3 (tons/year) 

Table 1.1-11. Comparison of SO2 and NOx Emissions (tons/year) for EGUs from Base G 

Actual 2002 Inventory and Typical 2002 Inventory. 

Table 1.2-1. Emissions from Fires in the VISTAS Region – Comparison between Original 

Base Year 2002 (VISTAS 3.1), 2002 Actual and Typical Year Base G 

Emissions. 

Table 1.2-2. Summary of State Data Submittals for the 2002 VISTAS Area Source 

Base F Inventory 

Table 1.2-3. Data Source Codes and Data Sources for VISTAS 2002 Base F Area Source 

Emissions Inventory. 

Table 1.3-1. Representative day mapping for January episode 

Table 1.3-2. Summary of Base F NONROAD Modeling Revisions

Table 1.3-3. Base F NONROAD Input File Sequence and Structural Revisions 

Table 1.3-4. Summary of Base G NONROAD Modeling Revisions

Table 1.3-5. Spring 2006 NONROAD Input File Sequence and Structural Revisions 

Table 1.3-6. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine 

Emissions as Reported in February 2004 Pechan Report (annual tons) 

Table 1.3-7. PM-to-NOx Ratios by Aircraft Type in Initial 2002 Base Year Inventory 

Table 1.3-8. Tucson, AZ PM-to-NOx Ratios by Aircraft Type. 

Table 1.3-9. Non-Corresponding Aircraft Emissions Records 

Table 1.3-10. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine 

Emissions with Modified Aircraft PM Emission Rates (annual tons) 

Table 1.3-11. Change in Initial 2002 Base Year Emissions due to Aircraft PM Emission Rate 

Modifications 

Table 1.3-12. CERR Aircraft NOx Records with No Corresponding PM Record. 

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List of Tables (continued) 

Table 1.3-13. Calculated Emission Ratios for VA. 

Table 1.3-14. Base F 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine 

Emissions (tons/year) 

Table 1.3-15. Change in 2002 Emissions, Base F Inventory Relative to Initial Inventory 

Table 1.3-16. Base F Comparison of Aircraft Emissions (Airports with Aircraft NOx > 200 

tons per year)

Table 1.3-17. Base G VA Aircraft Records Updates 

Table 1.3-18. Calculated Base G Emission Ratios for VA 

Table 1.3-19. Base G-Revised 2002 Base Year Aircraft, Locomotive, and Non-Recreational 

Marine Emissions (tons/year) 

Table 1.3-20. Change in 2002 Emissions, Base G Inventory 

Relative to Base F Inventory 

Table 1.3-21. Base G Comparison of Aircraft Emissions (Airports with Aircraft NOx > 200 

tons per year)

Table 1.3-22. Non-Default Files Used for MRPO Modeling 

Table 2.1-1. Adjustments to IPM Control Determinations Specified by S/L Agencies for the 

Base G 2009/2018 EGU Inventories. 

Table 2.1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 

2009/2018 EGU Inventories. 

Table 2.1-3. EGU Point Source SO2 Emission Comparison for 2002/2009/2018 

Table 2.1-4. EGU Point Source NOx Emission Comparison for 2002/2009/2018 

Table 2.1-5. EGU Point Source VOC Emission Comparison for 2002/2009/2018 

Table 2.1-6. EGU Point Source CO Emission Comparison for 2002/2009/2018 

Table 2.1-7. EGU Point Source PM10-PRI Emission Comparison for 2002/2009/2018 

Table 2.1-8. EGU Point Source PM2.5 -PRI Emission Comparison for 2002/2009/2018 

Table 2.1-9. EGU Point Source NH3 Emission Comparison for 2002/2009/2018 

Table 2.1-10. Summary of Source Shutdowns Incorporated in Base G Inventory 

Table 2.1-11. Non-EGU Point Source Control Programs Included in 2009/2018 

Projection Inventories. 

Table 2.1-12. Summary of Updates and Corrections to the Base F 2009/2018 Inventories 

Incorporated into the Base G 2009/2018 Inventories 

Table 2.1-13. Non-EGU Point Source SO2 Emission Comparison for 2002/2009/2018 

Table 2.1-14. Non-EGU Point Source NOx Emission Comparison for 2002/2009/2018 

Table 2.1-15. Non-EGU Point Source VOC Emission Comparison for 2002/2009/2018 

Table 2.1-16. Non-EGU Point Source CO Emission Comparison for 2002/2009/2018 

Table 2.1-17. Non-EGU Point Source PM10-PRI Emission Comparison for 2002/2009/2018 

Table 2.1-18. Non-EGU Point Source PM2.5-PRI Emission Comparison for 2002/2009/2018. 

Table 2.1-19. Non-EGU Point Source NH3 Emission Comparison for 2002/2009/2018 

List of Tables (continued) 

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Table 2.2-1 2002 Base Year Emissions and Percentage Difference for Base F and Base G 

 (based on actual emissions). 

Table 2.2-2 2019 Projection Year Emissions &Percentage Difference for Base F & Base G 

Table 2.2-3 2018 Projection Year Emissions & Percentage Difference for Base F & Base G 

Table 2.2-4 Percentage Difference Between Base F and Base G Fire Emissions by State 

Table 2.3-1. 2002 versus 2018 VMT (million miles per year) 

Table 2.3-2. VMT and HDD Rule Estimates for North Carolina (million miles per year) 

Table 2.3-3. VMT and HDD Rule Estimates for South Carolina (million miles per year) 

Table 2.3-4. VMT and HDD Rule Estimates for Tennessee (million miles per year) 

Table 2.3-5. VMT and HDD Rule Estimates for Virginia (million miles per year) 

Table 2.3-6. Pre-Base F 2002 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons, as of the fall of 2004) 

Table 2.3-7. Locally Generated Growth Factors for North Carolina 

Table 2.3-8. Estimated Emission Reduction Impacts based on T-4 Rule 

Table 2.3-9. Estimated Emission Reduction Impacts Relative to VISTAS 2002 Base 

Year Values 

Table 2.3-10. Diesel CMV Adjustment Ratios for Palm Beach County, FL 

Table 2.3-11. Overall Adjustment Factors for Palm Beach County, FL 

Table 2.3-12. SO2 Emissions for Diesel Rail in Autauga County, AL from the CAIR 

Projections 

Table 2.3-13 Growth Options based on CAIR Data 

Table 2.3-14. Base F 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories 

Table 2.3-15. Base F 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories 

Table 2.3-16. Change in Emissions between 2009 and 2002 Base F Inventories (Based on 

Growth Using 1996 and 2020 EPA Inventories) 

Table 2.3-17. Change in Emissions between 2018 and 2002 Base F Inventories (Based on 

Growth Using 1996 and 2020 EPA Inventories) 

Table 2.3-18. Base G 2002 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) 

Table 2.3-19. Locally Generated Growth Factors for Kentucky 

Table 2.3-20. Base G 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories 

Table 2.3-21. Base G 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories 

Table 2.3-22. Change in Emissions between 2009 Base G and 2002 Base F Inventories (Based 

on Growth Using 1996 and 2020 EPA Inventories) 

Table 2.3-23. Change in Emissions between 2018 Base G and 2002 Base F Inventories (Based 

on Growth Using 1996 and 2020 EPA Inventories) 

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List of Figures 

Figure 1.2-1. CO Emissions from Agricultural Burning for the Original Base Year, 2002 

Actual Base G, and 2002 Typical Base G Inventories.

Figure 1.2-2. CO Emissions from Land Clearing Burning for the Original Base Year, 2002 

Actual Base G and 2002 Typical Base G Inventories. 

Figure 1.2-3. CO Emissions from Prescribed Burning for the Original Base Year, 2002 Actual 

Base G and 2002 Typical Base G Inventories. 

Figure 1.2-4. CO Emissions from Wildfire Burning for the Original Base Year, 2002 Actual 

Base G and 2002 Typical Base G Inventories. 

Figure 2.2-1. Prescribed Fire Projection for Okeefenokee NWR for 2009 

Figure 2.3-1. Impacts of the Apparent CAIR Inventory Discrepancy 

Figure 2.3-2. Total Aircraft, Locomotive, and CMV CO Emissions (Base F) 

Figure 2.3-3. Locomotive CO Emissions (Base F) 

Figure 2.3-4. Total Aircraft, Locomotive, and CMV NOx Emissions (Base F) 

Figure 2.3-5. Locomotive NOx Emissions (Base F) 

Figure 2.3-6. Total Aircraft, Locomotive, and CMV PM10 Emissions (Base F) 

Figure 2.3-7. Locomotive PM10 Emissions (Base F) 

Figure 2.3-8. Total Aircraft, Locomotive, and CMV PM2.5 Emissions (Base F) 

Figure 2.3-9. Locomotive PM2.5 Emissions (Base F) 

Figure 2.3-10. Total Aircraft, Locomotive, and CMV SO2 Emissions (Base F) 

Figure 2.3-11. Locomotive SO2 Emissions (Base F) 

Figure 2.3-12. Total Aircraft, Locomotive, and CMV VOC Emissions (Base F) 

Figure 2.3-13. Locomotive VOC Emissions (Base F) 

Figure 2.3-14. Total Aircraft, Locomotive, and CMV CO Emissions (Base G) 

Figure 2.3-15. Locomotive CO Emissions (Base G) 

Figure 2.3-16. Total Aircraft, Locomotive, and CMV NOx Emissions (Base G) 

Figure 2.3-17. Locomotive NOx Emissions (Base G) 

Figure 2.3-18. Total Aircraft, Locomotive, and CMV PM10 Emissions (Base G) 

Figure 2.3-19. Locomotive PM10 Emissions (Base G) 

Figure 2.3-20. Total Aircraft, Locomotive, and CMV PM2.5 Emissions (Base G) 

Figure 2.3-21. Locomotive PM2.5 Emissions (Base G) 

Figure 2.3-22. Total Aircraft, Locomotive, and CMV SO2 Emissions (Base G) 

Figure 2.3-23. Locomotive SO2 Emissions (Base G) 

Figure 2.3-24. Total Aircraft, Locomotive, and CMV VOC Emissions (Base G) 

Figure 2.3-25. Locomotive VOC Emissions (Base G) 

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Acronyms and Abbreviations 

AEO Annual Energy Outlook 

AF&PA American Forest and Paper Association 

APCD Air Pollution Control District 

ATP Anti-Tampering Program 

BLRID Boiler Identification (Boiler ID) 

CAA Clean Air Act 

CAIR Clean Air Interstate Rule 

CEM Continuous Emissions Monitoring 

CAMD Clean Air Markets Division 

CERR Consolidated Emissions Reporting Rule 

CMU Carnegie Mellon University 

CMV commercial marine vessels 

CE Control Efficiency 

CO carbon monoxide 

DENR North Carolina Department of Environment and Natural Resources 

DHEC South Carolina Department of Health and Environmental Control 

EDMS Emissions Data Management Systems 

ESD Emissions Standards Division 

EPA Environmental Protection Agency 

EGU Electric Generating Unit 

ICF ICF International, Inc. 

FIP Federal Implementation Plan 

FLM Federal Land Manager 

FTP File transfer protocol 

FR Federal Register 

FS Forest Service 

HDD Heavy Duty Diesel 

HDD RULE Heavy Duty Diesel Rule 

ICF ICF International, Inc. 

ID Identification 

I/M Inspection and Maintenance 

IPM® Integrated Planning Model®

IAQTR Interstate Air Quality Transport Rule 

LTO Landing and take off 

MACT Maximum achievable control technology 

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Acronyms and Abbreviations (continued) 

MACTEC MACTEC Engineering and Consulting, Inc. 

MOBILE 6 MOBILE emissions estimation model version 6 

MRPO Midwest Regional Planning Organization 

NH3 Ammonia 

NEI National Emission Inventory 

NIF National Emission Inventory Format 

NLEV National Low Emission Vehicle regulation 

NMIM National Mobile Inventory Model 

NONROAD no acronym (model name) 

NOx Oxides of nitrogen 

NWR National Wildlife Refuge 

OTB On the books 

OTW On the way 

ORIS Office of Regulatory Information Systems 

OTAQ Office of Transportation and Air Quality 

OTC Ozone Transport Commission 

PFC Portable fuel containers 

PM Particulate matter 

PM10-FIL Particulate matter less than or equal to 10 microns in diameter that can be 

captured on a filter 

PM10-PRI Particulate matter less than or equal to 10 microns in diameter that includes 

both the filterable and condensable components of particulate matter 

PM2.5-FIL Particulate matter less than or equal to 2.5 microns in diameter that can be 

captured on a filter 

PM2.5-PRI Particulate matter less than or equal to 2.5 microns in diameter that includes 

both the filterable and condensable components of particulate matter 

PM-CON Particulate matter created by the condensation of hot materials to form 

particulates, usually less than 2.5 microns in diameter 

ppmW parts per million by weight 

PRI Primary 

QA/QC Quality Assurance/Quality Control 

QAPP Quality Assurance Project Plan 

REMI Regional Economic Models, Inc. 

RFG Reformulated gasoline 

RVP Reid Vapor Pressure 

SCC Source Classification Code 

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Acronyms and Abbreviations (continued) 

SCR Selective Catalytic Reduction 

SIP State Implementation Plan 

SIWG Special Interest Workgroup 

S/L/T State/Local/Tribal 

SMOKE Sparse Matrix Operator Kernel Emissions Modeling System 

S/L State and Local 

SO2 Oxides of Sulfur 

T4 Tier 4 

VISTAS Visibility Improvement State and Tribal Association of the Southeast 

VMT Vehicle Miles Traveled 

VOC Volatile organic compounds 

WRAP Western Regional Air Partnership 

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Documentation of the Base G 2002 Base Year, 2009 and 2018, 

Emission Inventories for VISTAS 

Introduction

History of VISTAS Base and Projection Year Emission Inventory Development 

This section is provided to supply the history behind the development of the base and 

projection year inventories provided to VISTAS. Through the various iterations, the 

inventories that have been developed have typically had version numbers provided by the 

contractors who developed the inventories and to a certain extent these were also based 

on their purpose. Different components of the 2002 base year inventories have been 

supplied by E.H. Pechan and Associates, Inc. (Pechan), MACTEC Engineering and 

Consulting, Inc. (MACTEC), and by Alpine Geophysics, Inc. 

The initial 2002 base year inventory was jointly developed by Pechan and MACTEC. 

Pechan developed the on-road and non-road mobile source components of the inventory 

while MACTEC developed the point and area source component of the inventory. This 

version of the inventory included updates to on-road mobile that incorporated 

information from the 1999 NEI Version 2 final along with updated information on VMT, 

fuel programs, and other inputs to the MOBILE6 model to produce a draft version of the 

2002 inventory. For non-road sources, a similar approach was used. Updated State 

information on temperatures and fuel characteristics were obtained from VISTAS States 

and used with the NONROAD 2002 model to calculate 2002 emissions for NONROAD 

model sources. These estimates were coupled with data for commercial marine vessels, 

locomotives and airplanes projected to 2002 using appropriate growth surrogates. A draft 

version of these inventories was prepared in late 2003, with a final version in early 2004. 

An overview of the development of the on-road component can be found at: 

http://www.vistas-sesarm.org/documents/Pechan_drafton-roadinventory_082803.ppt

while an overview of the non-road component can be found at: 

http://www.vistas-sesarm.org/documents/Pechan_Non-roadInventory_082803.ppt. 

Similarly, draft versions of the 2002 point and area source base year inventories were 

prepared by MACTEC in the same timeframe (late 2003 for the draft, final in early 

2004). The point source component was based on data submitted by the VISTAS States 

or on the 1999 NEI. The data submitted by the States ranged from 1999 to 2001 and was 

all projected to 2002 using appropriate growth surrogates from Economic Growth 

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Analysis System (EGAS) version 4. Toxic Release Inventory (TRI) data were used to 

augment the inventory for NH3. Continuous Emissions Monitor (CEM) data from the 

U.S. EPA’s Clean Air Markets Division was used to supply emissions for electric 

generating utilities (EGUs). Particulate matter emissions were augmented (when missing) 

by using emission factor ratios. Details on all these calculations are discussed in Section 

1.1.1.3 of this document. 

The area source component of the 2002 draft base year emissions was prepared similarly 

to the point sources, using State submittals and the 1999 NEI Version 2 final as the basis 

for projecting emissions to 2002 using EGAS growth factors. For ammonia area sources 

the Carnegie Mellon University (CMU) ammonia model was used to calculate emissions. 

Finally, data on acreage burned on a fire by fire basis was solicited from State forestry 

agencies in order to calculate fire emissions on a fire by fire basis. Virtually all VISTAS 

State forestry agencies provided data for these calculations at least for wild and 

prescribed fires. An overview of the point and area source development methods can be 

found at: 

http://www.vistas-sesarm.org/documents/MACTEC_draftpointareainventory_82803.ppt. 

Three interim versions of the 2002 base year inventory were developed. The first was 

delivered in August of 2003, the second in April of 2004 and the final one in October of 

2004. The August 2003 and April 2004 inventories were prepared by MACTEC and 

Pechan. A draft version of the revised 2002 base year inventory was released in June of 

2004, with a final version released in October 2004. That 2002 base year inventory was 

solely prepared by MACTEC. The October 2004 inventory incorporated 2002 

Consolidated Emissions Reporting Rule (CERR) data into the inventory along with some 

updated data from the VISTAS States. This inventory is typically referred to as version 

3.1 of the VISTAS inventory 

Closely following the version 3.1 2002 base year inventory, a “preliminary” 2018 

projection inventory was developed. This “preliminary” 2018 inventory was developed in 

late 2004 (Oct/Nov) and was designed solely for use in modeling sensitivity runs to 

provide a quick and dirty assessment of what “on the books” and “on the way” controls 

could be expected to provide in terms of improvements to visibility and regional haze 

impairment. A brief overview of the history of the three versions of the 2002 base year 

and the 2018 preliminary inventory use can be found at: http://www.vistassesarm.org/documents/STAD1204/2002and2018Emissions14Dec2004.ppt. 

Following preparation of the final 3.1 version of the 2002 base year inventory, States 

were asked to review and provide comments on that inventory to MACTEC for update 

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and revision. At the same time MACTEC prepared a revised draft version of the 2018 

projection inventory (January 2005) and a draft version of a 2009 projection inventory 

(April 2005). All of these were known as version 3.1 and were provided to the VISTAS 

States for review and comment. Comments were received and updates to the inventories 

based on these comments were prepared. The revised inventories were provided to the 

VISTAS States. At that time to be consistent with the modeling nomenclature being used 

by AG in performing their modeling runs, the inventory became the Base F VISTAS 

inventory. The Base F inventory was delivered for review and comment in August of 

2005. In addition, MACTEC delivered a report entitled Documentation of the Revised 

2002 Base Year, Revised 2018, and Initial 2009 Emission Inventories for VISTAS on 

August 2, 2005 that described the methods used to develop the Base F inventories. For 

the Electric Generating Utilities (EGU) different versions of the Integrated Planning 

Model were used between Base D and Base F, resulting in different projections of future 

EGU emissions. 

Over the period from August 2005 until June/July 2006 MACTEC received comments 

and updates to some categories from VISTAS States, particularly EGU. In addition, a 

new NONROAD model (NONROAD05) was released. Thus additional updates to the 

inventory were prepared based on the comments received along with revised NONROAD 

emission estimates from NONROAD05. The resultant inventory became the Base G 

inventory. 

This document details the development of the Base G inventories for 2002, 2009 and 

2018. The information that follows describes the development of the VISTAS inventory 

by sector from version 3.1 forward. Unless specific updates were made to an inventory 

sector, the methods used for version 3.1 were retained. Similarly unless specific changes 

were made to methods used for Base F, Base G methods were the same as Base F/version 

3.1 (if unchanged in Base F). 

Table I-1 through Table I-3 indicate roughly which version of the inventory is in use for 

each sector of the inventory as of Base G. 

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Table I-1: Inventory Version in Use by Year and Source Sector Through Base G - 2002 

Source AL FL GA KY MS NC SC TN VA WV 

EGU Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G 

Non-EGU 

Point 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Area1 Base F for 

ammonia 

sources 

(CMU 

Model) and 

for some area 

sources, 

Base G for 

selected 

sources 

updated by 

the State with 

State 

supplied data 

Base F except 

for some 

emissions 

zeroed out 

(and records 

removed) for 

some 

southern FL 

counties for 

Base G. 

Base F Base F Base F Base F for 

ammonia 

sources 

(CMU 

Model) and 

for some area 

sources, 

Base G for 

selected 

sources 

updated by 

the State with 

State 

supplied data. 

Some 

corrections 

applied by 

MACTEC to 

correct PM 

values 

Base F Base F Base F for 

ammonia 

Sources 

(CMU 

Model) and 

for some area 

sources, 

Base G for 

selected 

sources 

updated by 

the State with 

State 

supplied data. 

Base F 

On-road Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G 

Non-road Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources, 

except 

aircraft and 

locomotives 

updated for 

Base G. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

except for 

aircraft in 

Cincinnati/N. 

KY Int. 

Airport, 

which are 

Base G. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. NC 

moved from 

Southern to 

Mid-Atlantic 

State in 

seasonal 

adjustment 

file. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources, 

except for 

aircraft 

emissions 

which are 

Base G. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Fires Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Notes: 

Base G global Area Source changes that apply to ALL States: A) removal of Stage II refueling from area source file to non-road and on-road; B) 

modification of PM2.5 ratio for several fugitive dust sources per WRAP methodology; C) addition of portable fuel container (PFC) emissions to all 

States based on OTAQ report. 

Appendix G Attachment 12 - Page Number:

14
Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS 

MACTEC, Inc. 2

Table I-2: Inventory Version in Use by Year and Source Sector Through Base G - 2009 

Source AL FL GA KY MS NC SC TN VA WV 

EGU1 Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G 

Non-EGU 

Point2

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Area Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Some 

specific 

source 

categories 

updated using 

State 

supplied file 

to override 

projected 

values. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

On-road Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G 

Non-road Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

except for 

aircraft in 

Cincinnati/N. 

KY Int. 

Airport, 

which are 

Base G using 

State 

supplied 

growth 

factors. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Fires Base F 

typical except 

for Rx fires 

Base F 

typical 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Notes: 

1. All EGU emissions updated with new IPM runs in Base G 

2. Revised growth factors from DOE AEO2006 fuel use projections 

Appendix G Attachment 12 - Page Number:

15
Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS 

MACTEC, Inc. 3

Table I-3: Inventory Version in Use by Year and Source Sector Through Base G - 2018 

Source AL FL GA KY MS NC SC TN VA WV 

EGU1 Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G 

Non-EGU 

Point2

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G 

Area Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Some 

specific 

source 

categories 

updated 

using State 

supplied file 

to override 

projected 

values. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

On-road Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G 

Non-road Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources. 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

except for 

aircraft in 

Cincinnati/N. 

KY Int. 

Airport, 

which are 

Base G using 

State 

supplied 

growth 

factors. 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Fires Base F 

typical 

except for Rx 

fires 

Base F 

typical 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Notes: 

1. All EGU emissions updated with new IPM runs in Base G 

2. Revised growth factors from DOE AEO2006 fuel use projections 

Appendix G Attachment 12 - Page Number:

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Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS 

MACTEC, Inc. 4

1.0 2002 Base Year Inventory Development 

1.1 Point Sources 

This section details the development of the 2002 base year inventory for point sources. There 

were two major components to the development of the point source sector of the inventory. The 

first component was the incorporation of data submitted by the Visibility Improvement State and 

Tribal Association of he Southeast (VISTAS) States and local (S/L) agencies to the United States 

Environmental Protection Agency (EPA) as part of the Consolidated Emissions Reporting Rule 

(CERR) requirements Work on incorporating the CERR data into the revised base year 

involved: 1) obtaining the data from EPA or the S/L agency, 2) evaluating the emissions and 

pollutants reported in the CERR submittals, 3) augmenting CERR data with annual emission 

estimates for PM10-PRI and PM2.5-PRI; 4) evaluating the emissions from electric generating 

units, 5) completing quality assurance reviews for each component of the point source inventory, 

and 6) updating the database with corrections or new information from S/L agencies based on 

their review of the 2002 inventory. The processes used to perform those operations are described 

in the first portion of this section. 

The second component was the development of a “typical” year inventory for electric generating 

units (EGUs). VISTAS determined that a typical year electric generating units (EGU) inventory 

was necessary to smooth out any anomalies in emissions from the EGU sector due to 

meteorology, economic, and outage factors in 2002. The typical year EGU inventory is intended 

to represent the five year (2000-2004) period that will be used to determine the regional haze 

reasonable progress goals. The second part of this section discusses the development of the 

typical year EGU inventory. 

1.1.1 Development of 2002 Point Source Inventory 

MACTEC developed a draft 2002 emission inventory in June 2004 (Development of the Draft 

2002 VISTAS Emission Inventory for Regional Haze Modeling – Point Sources, MACTEC, June 

18, 2004). The starting point for the draft 2002 emission inventory was EPA’s 1999 National 

Emission Inventory (NEI), Version 2 Final (NEI99V2). For several states, we replaced the 

NEI99V2 data with more recent inventories for either calendar year 1999, 2000, or 2001 as 

submitted by the S/L agencies. We also performed several other updates, including updating 

emission estimates for selected large source of ammonia, incorporating 2002 Continuous 

Emissions Monitoring-(CEM)-based SO2 and NOx emissions for electric utilities, adding PM10

and PM2.5 emissions when they were missing from an S/L submittal, and performing a variety of 

additional Quality assurance/Quality control (QA/QC) checks. 

Appendix G Attachment 12 - Page Number:

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The next version of the 2002 inventory (referred to as Base F) was released in August 2005 

(Documentation of the Revised 2002 Base Year, Revised 2018, and Initial 2009 Emission 

Inventories for VISTAS, MACTEC, August 2, 2005). The primary task in preparing the Base F 

2002 base year inventory was the replacement of NEI99V2 data with data submitted by the 

VISTAS S/L agencies as part of the CERR submittal and included in EPA’s 2002 NEI. 

The current version of the 2002 inventory (referred to as Base G) was released in August 2006 

and is documented in this report. The primary task in preparing the Base G 2002 base year 

inventory was the incorporation of corrections and new information as submitted by the S/L 

agencies based on their review of the Base F inventory. The following subsections document the 

data sources for the Base G inventory, the checks made on the CERR submittals, the process for 

augmenting the inventory with PM10 and PM2.5 emissions, the evaluation of EGU emissions, 

other QA/QC checks, and other Base G updates. The final subsection summarizes the Base G 

2002 inventory by state, pollutant, and sector (EGU and non-EGU). 

1.1.1.1 Data Sources 

Several data sources were used to compile the Base F point source inventory: 1) the inventories 

that the S/L submitted to EPA from May through July 2004 as required by the CERR; 

2) supplemental data supplied by the S/L agencies that may have been revised or finalized after 

the CERR submittal to EPA, and 3) the draft VISTAS 2002 inventory in cases where S/L CERR 

data were not available. For the Base G inventory, we replaced data from Hamilton County, 

Tennessee, using data from Hamilton County’s CERR submittal as contained in EPA’s 2002 NEI 

inventory (in Base F, the inventory for Hamilton County was based on the draft VISTAS 2002 

inventory, which in turn was based on the 1999 NEI). 

Table 1.1-1 summarizes the data used as the starting point for the Base F 2002 inventory. Once 

all of the files were obtained, MACTEC ran the files through the EPA National Emission 

Inventory Format (NIF) Basic Format and Content checking tool to ensure that the files were 

submitted in standard NIF format and that there were no referential integrity issues with those 

files. In a couple of cases small errors were found. For example, in one case non-standard 

pollutant designations were used for particulate matter (PM) and ammonia emissions. MACTEC 

contacted each VISTAS State point source contact person to resolve the issues with the files and 

corrections were made. Once all corrections to the native files were made, MACTEC continued 

with the incorporation of the data into the VISTAS point source files. S/L agencies completed a 

detailed review of the Base F inventory. Additional updates and corrections to the Base F 

inventory were requested by S/L agencies and incorporated into the Base G inventory. The Base 

G changes are documented in more detail in Section 1.1.1.6. 

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MACTEC, Inc. 6

Table 1.1-1. State Data Submittals Used for the Base F 2002 Point Source Inventory. 

State / Local Program Point Source Emissions Data Source 

AL C 

FL B 

GA B 

KY C 

MS B 

NC C 

SC C 

TN C 

VA B 

WV B 

Davidson County, TN B 

Hamilton County, TN D 

Memphis/Shelby County, TN B 

Knox County, TN B 

Jefferson County, AL B 

Jefferson County, KY B 

Buncombe County, NC B 

Forsyth County, NC B 

Mecklenburg County, NC B 

Key 

A = Draft VISTAS 2002 

B = CERR Submittal from EPA's file transfer protocol (FTP) site 

C = Other (CERR or other submittal sent directly from S/L agency to MACTEC) 

D = CERR Submittal from EPA’s NEI 2002 Final Inventory 

1.1.1.2 Initial Data Evaluation 

For the Base F inventory, we conducted an initial review of the 2002 point source CERR data in 

accordance with the QA procedures specified in the Quality Assurance Project Plan (QAPP) for 

this project. The following evaluations were completed to identify potential data quality issues 

associated with the CERR data: 

• Compared the number of sites in the CERR submittal to the number of sites in the 

VISTAS draft 2002 inventory; for all States, the number of sites in the CERR submittal 

was less than in the VISTAS draft 2002 inventory, since the CERR data was limited to 

major sources, while the VISTAS draft 2002 inventory contained data for both major and 

minor sources; verified with S/L contacts that minor sources not included in the CERR 

point source inventory were included in the CERR area source inventory. 

• Checked for correct pollutant codes and corrected to make them NIF-compliant; for 

example, some S/L agencies reported ammonia emissions using the CAS Number or as 

“ammonia”, rather than the NIF-compliant “NH3” code. 

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MACTEC, Inc. 7

• Checked for types of particulate matter codes reported (i.e., PM-FIL, PM-CON, PM-PRI, 

PM10-PRI, PM10-FIL, PM2.5-PRI, PM2.5-FIL); corrected codes with obvious errors 

(i.e., changed PMPRI to PM-PRI). (The PM augmentation process for filling in missing 

PM pollutants is discussed later in Section 1.1.1.3) 

• Converted all emission values that weren’t in tons to tons to allow for preparation of 

emission summaries using consistent units. 

• Checked start and end dates in the PE and EM tables to confirm consistency with the 

2002 base year. 

• Compared annual and daily emissions when daily emissions were reported; in some 

cases, the daily value was non-zero (but very small) but the annual value was zero. This 

was generally the result of rounding in an S/L agency’s submittal. 

• Compared ammonia emissions as reported in the CERR submittals and the 2002 Toxics 

Release Inventory; worked with S/L agencies to resolve any outstanding discrepancies. 

• Compared SO2 and NOx emissions for EGUs to EPA’s Clean Air Markets Division CEM 

database to identify any outstanding discrepancies. (A full discussion of the EGU 

emissions analysis is discussed later in Section 1.1.1.4) 

• Prepared State-level emission summaries by pollutant for both the EGU and non-EGU 

sectors to allow S/L agencies to compare emissions as reported in the 1999 NEI 

Version 2, the VISTAS draft 2002 inventory, and the CERR submittals. 

• Prepared facility-level emission summaries by pollutant to allow S/L agencies to review 

facility level emissions for reasonableness and accuracy. 

We communicated the results of these analyses through email/telephone exchanges with the S/L 

point source contacts as well as through Excel summary spreadsheets. S/L agencies submitted 

corrections and updates as necessary to resolve any QA/QC issues from these checks. 

1.1.1.3 PM Augmentation 

Particulate matter emissions can be reported in many different forms, as follows: 

PM Category Description 

PM-PRI Primary PM (includes filterable and condensable) 

PM-CON Primary PM, condensable portion only (all less than 1 micron) 

PM-FIL Primary PM, filterable portion only 

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PM10-PRI Primary PM10 (includes filterable and condensable) 

PM10-FIL Primary PM10 filterable portion only 

PM2.5 -PRI Primary PM2.5 (includes filterable and condensable) 

PM2.5 -FIL Primary PM2.5 filterable portion only 

S/L agencies did not report PM emissions in a consistent manner. The State/local inventories 

submitted for VISTAS included emissions data for either PM-FIL, PM-PRI, PM10-FIL, 

PM10-PRI, PM2.5 -FIL, PM2.5 -PRI, and/or PM-CON. From any one of these pollutants, EPA has 

developed augmentation procedures to estimate PM10-PRI, PM10-FIL, PM2.5 -PRI, PM2.5 -FIL, 

and PM-CON. If not included in a State/local inventory, PM10-PRI and PM2.5 -PRI were 

calculated by adding PM10-FIL and PM-CON or PM2.5 -FIL and PM-CON, respectively. 

The procedures for augmenting point source PM emissions are documented in detail in 

Appendix C of Documentation for the Final 1999 National Emissions Inventory {Version 3} for 

Criteria Air Pollutants and Ammonia – Point Sources, January 31, 2004). Briefly, the PM data 

augmentation procedure includes the following five steps: 

• Step 1: Prepare S/L/T PM and PM10 Emissions for Input to the PM Calculator 

• Step 2: Develop and Apply Source-Specific Conversion Factors 

• Step 3: Prepare Factors from PM Calculator 

• Step 4: Develop and Apply Algorithms to Estimate Emissions from S/L/T Inventory Data 

• Step 5: Review Results and Update the NEI with Emission Estimates and Control 

Information. 

Please refer to the EPA documentation for a complete description of the PM augmentation 

procedures. 

Table 1.1-2 compares the original PM emission estimates from the S/L CERR submittals and the 

revised 2002 VISTAS emissions estimates calculated using the above methodology. This table is 

intended to show that we took whatever States provided in the way of PM and filled in gaps to 

add in PM-CON where emissions were missing in order to calculate PM10-PRI and PM2.5 -PRI 

for all processes to get a complete set of particulate data. We did not compare any other 

pollutants besides PM, since for other pollutants CERR emissions equal VISTAS emissions. As 

noted in Table 1.1-2, we made significant revisions to the PM emissions for Kentucky in the 

Base F inventory and for South Carolina in the Base G inventory. 

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MACTEC, Inc. 9

Table 1.1-2. Comparison of Particulate Matter Emissions from the S/L Data Submittals 

and the Base G 2002 VISTAS Point Source Inventory 

State Database PM-PRI PM-FIL PM-CON PM10-PRI PM10-FIL PM2.5 -PRI PM2.5 -FIL 

AL CERR 28,803 9,174 0 16,522 6,548 8,895 4,765 

 VISTAS 43,368 33,336 10,129 32,791 22,661 23,290 13,328 

FL CERR 0 33,732 0 0 32,254 0 0 

 VISTAS 61,728 37,325 24,403 57,243 32,840 46,147 21,744 

GA CERR 42,846 0 0 27,489 0 15,750 0 

 VISTAS 44,835 37,088 7,799 33,202 25,403 22,777 15,085 

KY CERR 0 3,809 0 19,748 1,360 0 0 

 VISTAS 27,719 22,349 5,329 21,326 15,963 14,173 8,749 

MS CERR 23,925 0 0 20,968 0 10,937 0 

 VISTAS 23,928 17,632 6,296 21,089 14,793 11,044 5,739 

NC CERR 48,110 0 0 36,222 0 24,159 0 

 VISTAS 48,114 41,407 6,708 36,992 30,284 27,512 21,113 

SC CERR 0 43,837 0 0 32,656 0 21,852 

 VISTAS 43,844 38,633 5,210 34,799 29,588 26,418 21,207 

TN CERR 1,660 25,500 21,482 43,413 22,164 34,167 12,140 

 VISTAS 56,797 32,085 24,715 50,937 26,269 41,442 16,774 

VA CERR 0 0 0 17,065 0 12,000 0 

 VISTAS 40,856 36,414 4,442 17,065 12,623 12,771 8,607 

WV CERR 0 29,277 0 0 14,778 0 8445 

 VISTAS 36,188 29,392 6,795 22,053 15,258 15,523 8,733 

Note 1: CERR refers to data as submitted by S/L agencies; VISTAS refers to data calculated by MACTEC using 

the PM augmentation methodologies described in this document. 

Note 2: KY DEP’s initial CERR submittal reported particulate matter emissions using only PM-PRI pollutant code. 

MACTEC used this pollutant code during the initial PM augmentation routine. In February 2005, KY DEP 

indicated that data reported using the PM-PRI code should actually have been reported using the PM10-PRI 

code. MACTEC performed a subsequent PM augmentation in April 2005 using the PM10-PRI code. These 

changes were reflected in the Base F emission inventory. 

Note 3: South Carolina Department of Health and Environmental Control (SC DHEC) initial CERR submittal 

reported particulate matter emissions using the PM-FIL, PM10-FIL, and PM2.5 -FIL pollutant codes. 

MACTEC used these pollutant codes during the initial PM augmentation routine. In August 2005, SC 

DHEC indicated that data reported using the PM-FIL, PM10-FIL, and PM2.5 -FIL pollutant codes should 

actually have been reported using the PM-PRI, PM10-PRI, and PM2.5 _PRI codes. MACTEC performed a 

subsequent PM augmentation in April 2006 using the revised pollutant codes. These changes were reflected 

in the Base G emission inventory. 

Note 4: The emission values in the VISTAS emission rows above differ slightly from the final values in the Base G 

inventory. This is due to several corrections and updates to the 2002 inventory submitted by S/L agencies 

after the PM augmentation was performed as discussed in Section 1.1.1.6. 

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After the PM augmentation process was performed, we executed a series of checks to 

identify potential inconsistencies in the PM inventory. These checks included: 

• PM-PRI less than PM10-PRI, PM2.5 -PRI, PM10-FIL, PM2.5 -FIL, or PM-CON; 

• PM-FIL less than PM10-FIL, PM2.5 -FIL; 

• PM10-PRI less than PM2.5 -PRI, PM10-FIL, PM2.5 -FIL or PM-CON; 

• PM10-FIL less than PM2.5 -FIL; 

• PM25-PRI less than PM2.5 -FIL or PM-CON; 

• The sum of PM10-FIL and PM-CON not equal to PM10-PRI; and 

• The sum of PM2.5 -FIL and PM-CON not equal to PM2.5 -PRI. 

S/L agencies were asked to review this information and provide corrections where the 

inconsistencies were significant. In general, corrections (or general directions) were provided in 

the case of the potential inconsistency issues. In other cases, the agency provided specific 

process level pollutant corrections. 

Note that for the Base G inventory, only the PM10-PRI and PM2.5 -PRI emission estimates were 

retained since they are the only two PM species that are included in the air quality modeling. 

Other PM species were removed from the Base G inventory to facilitate emissions modeling. 

1.1.1.4 EGU Analysis 

We made a comparison of the annual SO2 and NOx emissions for EGUs as reported in the S/L 

agencies CERR submittals and the data from EPA’s Clean Air Markets Division (CAMD) CEM 

database to identify any outstanding discrepancies. Facilities report hourly CEM data to EPA for 

units that are subject to CEM reporting requirements of the NOx State Implementation Plan (SIP) 

Call rule and Title IV of the Clean Air Act (CAA). EPA sums the hourly CEM emissions to the 

annual level, and we compared these annual CEM emissions to those in the S/L inventories. The 

2002 CEM inventory containing NOx and SO2 emissions and heat input data were downloaded 

from the EPA CAMD web site (www.epa.gov/airmarkets). The data were provided by quarter 

and emission unit. 

The first step in the EGU analysis involved preparing a crosswalk file to match facilities and 

units in the CAMD inventory to facilities and units in the S/L inventories. In the CAMD 

inventory, the Office of Regulatory Information Systems (ORIS) identification (ID) code 

identifies unique facilities and the unit ID identifies unique boilers and internal combustion 

engines (i.e., turbines and reciprocating engines). In the S/L inventories, the State and county 

FIPS and State facility ID together identify unique facilities and the emission unit ID identifies 

unique boilers or internal combustion engines. In most cases, there is a one-to-one 

correspondence between the CAMD identifiers and the S/L identifiers. However, in some of the 

S/L inventories, the emissions for multiple emission units are summed and reported under one 

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emission unit ID. We created an Excel spreadsheet that contained an initial crosswalk with the 

ORIS ID and unit ID in the CEM inventory matched to the State and county Federal 

Implementation Plan (FIPS), State facility ID, and emission unit ID in the S/L inventory. The 

initial crosswalk contained both the annual emissions summed from the CAMD database as well 

as the S/L emission estimate. It should be noted that the initial matching of the IDs in both 

inventories was based on previous crosswalks that had been developed for the preliminary 

VISTAS 2002 inventory and in-house information compiled by MACTEC and Alpine 

Geophysics. The matching at the facility level was nearly complete. In some cases, however, S/L 

agency or stakeholder assistance was needed to match some of the CEM units to emission units 

in the S/L inventories. 

The second step in the EGU analysis was to prepare an Excel spreadsheet that compared the 

annual emissions from the hourly CAMD inventory to the annual emissions reported in the S/L 

inventory. The facility-level comparison of CEM to emission inventory NOx and SO2 emissions 

found that for most facilities, the annual emissions from the S/L inventory equaled the CAMD 

CEM emissions. Minor differences could be explained because the facility in the S/L inventory 

contained additional small or emergency units that were not included in the CAMD database. 

The final step in the EGU analysis was to compare the SO2 and NOx emissions for select 

Southern Company units in the VISTAS region. Southern Company is a super-regional company 

that owns EGUs in four VISTAS States – Alabama, Florida, Georgia, and Mississippi – and 

participates in VISTAS as an industry stakeholder. Southern Company independently provided 

emission estimates for 2002 as part of the development of the preliminary VISTAS 2002 

inventory. In most cases, these estimates were reviewed by the States and incorporated into the 

States CERR submittal. The exception to this was a decision made by Georgia’s Department of 

Environmental Protection (GDEP) to utilize CEM-based emissions for the actual 2002 emissions 

inventory for sources within the State when Southern Company also provided data. There were 

no major inconsistencies between the Southern Company data, the CAMD data, and the S/L 

CERR data. 

The minor inconsistencies found included small differences in emission estimates (<2 percent 

difference), exclusion/inclusion of small gas-fired units in the different databases, and grouping 

of emission units in S/L CERR submittals where CAMD listed each unit individually. We 

compared SO2 and NOx emissions on a unit by unit basis and did not find any major 

inconsistencies. 

1.1.1.5 QA Review of Base F Inventory 

QA checks were run on the Base F point source inventory data set to ensure that all corrections 

provided by the S/L agencies and stakeholders were correctly incorporated into the S/L 

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inventories and that there were no remaining QA issues. After exporting the inventory to ASCII 

text files in NIF 3.0, the EPA QA program was run on the ASCII files and the QA output was 

reviewed to verify that all QA issues that could be addressed were resolved 

Throughout the inventory development process, QA steps were performed to ensure that no 

double counting of emissions occurred, and to ensure that a full and complete inventory was 

developed for VISTAS. QA was an important component to the inventory development process 

and MACTEC performed the following QA steps on the point source component of the VISTAS 

revised 2002 base year inventory: 

1. Facility level emission summaries were prepared and evaluated to ensure that 

emissions were consistent and that there were no missing sources. 

2. State-level EGU and non-EGU comparisons (by pollutant) were developed between 

the Base F 2002 base year inventory, the draft VISTAS 2002 inventory, and the 1999 

NEI Version 2 inventory. 

3. Data product summaries and raw NIF 3.0 data files were provided to the VISTAS 

Emission Inventory Technical Advisor and to the Point Source, EGU, and non-EGU 

Special Interest Work Group representatives for review and comment. Changes based 

on these comments were reviewed and approved by the S/L point source contact prior 

to implementing the changes in the files. 

4. Version numbering was used for all inventory files developed. The version 

numbering process used a decimal system to track major and minor changes. For 

example, a major change would result in a version going from Base F1 to Base F2. 

1.1.1.6 Additional Base G Updates and Corrections 

S/L agencies completed a detailed review of the Base F inventory. Table 1.1-3 summarizes the 

updates and corrections to the Base F inventory that were requested by S/L agencies and 

incorporated into the Base G inventory. 

There was a discrepancy between the base year 2002 and 2009/2018 emissions for PM10-PRI, 

PM2.5-PRI, and NH3. The 2002 emissions were provided directly by the S/L agencies and were 

estimated using a variety of techniques (i.e., EPA emission factors, S/L emission factors, sitespecific emission factors, and source test data). The 2009/2018 emissions, on the other hand, 

were estimated by Pechan (see Section 2.1.1.3) using an emission factor file based solely on 

AP-42 emission factors. An adjustment was made for 2002 EGU PM and NH3 emissions to 

reconcile these differences. The post-processed Integrated Planning Model® (IPM®) 2009/2018 

output uses a set of PM and NH3 emission factors that are “the most recent EPA approved 

uncontrolled emission factors” – these are most likely not the same emission factors used by 

States and emission inventory preparation contractors for estimating these emissions in 2002 for 

EGUs in the VISTAS domain. VISTAS performed a set of modifications to replace 2002 base 

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year PM and NH3 emission estimates with estimates derived from the most recent EPA-approved 

emission factors. For further details of the methodology used to make this adjustment, see EGU 

Emission Factors and Emission Factor Assignment, memorandum from Greg Stella to VISTAS 

State Point Source Contacts and VISTAS EGU Special Interest Workgroup, June 13, 2005. 

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Table 1.1-3. Summary of Updates and Corrections to the Base F 2002 Inventory 

Incorporated into the 2002 Base G Inventory. 

Affected 

State(s) Nature of Update/Correction 

TN, WV The latitude and longitude values for TN (except the four local programs) and WV were truncated to two 

decimal places in the Base F inventory. MACTEC re-exported the NIF ER tables in a manner that so that 

the latitude and longitude were not truncated in the Base G inventory. 

AL Corrected the latitude and longitude for two facilities: Ergon Terminalling (Site ID: 01-073-010730167) 

and Southern Power Franklin (Site ID: 01-081-0036). 

 Corrections to stack parameters at 10 facilities for stacks with parameters that do not appear to fall into the 

ranges typically termed "acceptable" for AQ modeling. 

FL Corrected emission values for the Miami Dade RRF facility (Site ID: 12-086-0250348). 

GA Hercules Incorporated (12-051-05100005) had an erroneous process id (#3) within emission unit id SB9 

and was deleted. This removes about 6,000 tons of SO2 from the 2002 inventory. 

 Provided a revised file of location coordinates at the stack level that was used to replace the location 

coordinated in the ER file. 

NC Made several changes to Base F inventory to correct the following errors: 

1. Corrected emissions at Hooker Furniture (Site ID: 37-081-08100910), release point G-29, 9211.38 tons 

volatile organic compounds (VOC's) should be 212.2 tons, 529.58 tons PM10 should be 17.02 tons, 529.58 

tons PM2.5 should be 15.79 tons in 2002 inventory. 

2. Identified many stack parameters in the ER file that were unrealistic. Several have zero for height, 

diameter, gas velocity, and flow rate. NC used the procedures outlined in Section 8 of the document 

""National Emission Inventory QA and Augmentation Report" to correct unrealistic stack parameters. 

3. Identified truncated latitude and longitude values in Base F inventory. NC updated all Title V facility 

latitude and longitude that was submitted to EPA for those facilities in 2004. Smaller facilities with only 

two decimal places were not corrected. 

4. Corrected emissions for International Paper (3709700045) Emission Unit ID, G-12, should be 1.8844 

tons VOCs instead of 2819.19 tons in 2002 

SC Corrected PM species emission values. SC DHEC’s initial CERR submittal reported particulate matter 

emissions using the PM-FIL, PM10-FIL, and PM25-FIL pollutant codes. In August 2005, SC DHEC 

indicated that data reported using the PM-FIL, PM10-FIL, and PM25-FIL pollutant codes should actually 

have been reported using the PM-PRI, PM10-PRI, and PM25_PRI codes. MACTEC performed a 

subsequent PM augmentation in April 2006 using the revised pollutant codes. These changes were 

reflected in the Base G emission inventory. 

TN Identified six facilities that closed in 2000/2001 but had non-zero emissions in the 2002 Base F inventory. 

MACTEC changed emissions to zero for all pollutants in the Base G 2002 inventory. 

 Supplied updated emission inventory for the Bowater facility (47-107-0012) based on the facility’s updated 

2002 emission inventory update. 

 Replaced data from Hamilton County, Tennessee, using data from Hamilton County’s CERR submittal as 

contained in EPA’s 2002 NEI (in Base F, the inventory for Hamilton County was based on the draft 

VISTAS 2002 inventory, which in turn was based on the 1999 NEI). 

 Updated emissions for PCS Nitrogen Fertilizer LP (Site ID: 47-157-00146) 

WV Updated emissions for Steel of West Virginia (Site ID: 54-011-0009) 

 Made changes to several Site ID names due to changes in ownership 

 Made corrections to latitude/longitude and stack parameters at a few facilities for stacks with parameters 

that do not appear to fall into the ranges typically termed "acceptable" for AQ modeling. 

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1.1.1.7 Summary of Base G 2002 Inventory 

Tables 1.1-4 through 1.1-10 summarize the Base G 2002 base year inventory. All values are in 

tons. For the purposes of Tables 1.1-4 through 1.1-10, EGU emissions include the emissions 

from all processes with a Source Classification Code (SCC) of either 1-01-xxx-xx (External 

Combustion Boilers – Electric Generation) or 2-01-xxx-xx (Internal Combustion Engines – 

Electric Generation). Emissions for all other SCCs are included in the non-EGU column. Note 

that aggregating emissions into EGU and non-EGU sectors based on the above SCCs causes a 

minor inconsistency with the EGU emissions reported in EPA’s CAMD database. The EGU 

emissions summarized in these tables may include emissions from some smaller electric 

generating units in the VISTAS inventory that are not in CAMD’s 2002 CEM database or the 

IPM forecasted emissions. The minor inconsistencies result in a less than 2 percent difference 

between the summary tables below and the data from CAMD’s CEM database. 

Table 1.1-4. Base G 2002 VISTAS Point Source Inventory for SO2 (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 544,309 447,828 96,481 

FL 518,721 453,631 65,090 

GA 568,731 514,952 53,778 

KY 518,086 484,057 34,029 

MS 103,388 67,429 35,960 

NC 522,113 477,990 44,123 

SC 259,916 206,399 53,518 

TN 413,755 334,151 79,604 

VA 305,106 241,204 63,903 

WV 570,153 516,084 54,070 

Total 4,324,278 3,743,725 580,556 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

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Table 1.1-5. Base G 2002 VISTAS Point Source Inventory for NOx (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 244,348 161,038 83,310 

FL 302,834 257,677 45,156 

GA 196,767 147,517 49,251 

KY 237,209 198,817 38,392 

MS 104,661 43,135 61,526 

NC 196,782 151,854 44,928 

SC 130,394 88,241 42,153 

TN 221,652 157,307 64,344 

VA 147,300 86,886 60,415 

WV 277,589 230,977 46,612 

Total 2,059,536 1,523,449 536,087 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

Table 1.1-6. Base G 2002 VISTAS Point Source Inventory for VOC (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 49,332 2,295 47,037 

FL 40,995 2,524 38,471 

GA 34,952 1,244 33,709 

KY 46,321 1,487 44,834 

MS 43,852 648 43,204 

NC 62,170 988 61,182 

SC 38,927 470 38,458 

TN 85,254 926 84,328 

VA 43,906 754 43,152 

WV 15,775 1,180 14,595 

Total 461,484 12,516 448,970 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

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Table 1.1-7. Base G 2002 VISTAS Point Source Inventory for CO (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 185,550 11,279 174,271 

FL 139,045 57,113 81,933 

GA 140,561 9,712 130,850 

KY 122,555 12,619 109,936 

MS 59,871 5,303 54,568 

NC 64,461 13,885 50,576 

SC 63,305 6,990 56,315 

TN 122,348 7,084 115,264 

VA 70,688 6,892 63,796 

WV 100,220 10,341 89,879 

Total 1,068,604 141,218 927,388 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

Table 1.1-8. Base G 2002 VISTAS Point Source Inventory for PM10-PRI (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 32,886 7,646 25,240 

FL 57,243 21,387 35,857 

GA 32,834 11,224 21,610 

KY 21,326 4,701 16,626 

MS 21,106 1,633 19,472 

NC 36,592 22,754 13,838 

SC 35,542 21,400 14,142 

TN 49,814 14,640 35,174 

VA 17,211 3,960 13,252 

WV 22,076 4,573 17,503 

Total 326,630 113,918 212,714 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

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Table 1.1-9. Base G 2002 VISTAS Point Source Inventory for PM2.5 -PRI (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 23,291 4,113 19,178 

FL 46,148 15,643 30,504 

GA 22,401 4,939 17,462 

KY 14,173 2,802 11,372 

MS 11,044 1,138 9,906 

NC 26,998 16,498 10,500 

SC 27,399 17,154 10,245 

TN 39,973 12,166 27,807 

VA 12,771 2,606 10,165 

WV 15,523 2,210 13,313 

Total 239,721 79,269 160,452 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

Table 1.1-10. Base G 2002 VISTAS Point Source Inventory for NH3 (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 2,200 317 1,883 

FL 1,657 234 1,423 

GA 3,697 83 3,613 

KY 1,000 326 674 

MS 1,359 190 1,169 

NC 1,234 54 1,180 

SC 1,553 142 1,411 

TN 1,817 204 1,613 

VA 3,230 127 3,104 

WV 453 121 332 

Total 18,200 1,798 16,402 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 

1.1.2 Development of Typical Year EGU inventory 

VISTAS developed a typical year 2002 emission inventory for EGUs to avoid anomalies in 

emissions due to variability in meteorology, economic, and outage factors in 2002. The typical 

year inventory represents the five year (2000-2004) starting period that would be used to 

determine the regional haze reasonable progress goals. 

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Data from EPA’s CAMD were used to develop normalization factors for producing a 2002 

typical year inventory for EGUs. We used the ratio of the 2000-2004 average heat input and the 

2002 actual heat input to normalize the 2002 actual emissions. MACTEC obtained data from 

EPA’s CAMD for utilities regulated by the Acid Rain program. Annual data for the period 2000 

to 2004 were obtained from the CAMD web site (www.epa.gov/airmarkets). The parameters 

available were the SO2 and NOx emission rates, heat input, and operating hours. 

We used the actual 2002 heat input and the average heat input for the 5-year period from 2000-

2004 as the normalization factor, as follows: 

Normalization Factor: 2000-2004 average heat input 

 2002 actual heat input

If the unit did not operate for all five years, then the 2000-2004 average heat input was calculated 

for the one or two years in which the unit did operate. For example, if the unit operated only 

during 2002, then the normalization factor would be 1.0. The annual actual emissions were 

multiplied by the normalization factor to determine the typical emissions for 2002, as follows: 

Typical Emissions = 2002 actual emissions x Normalization Factor 

After applying the normalization factor, some adjustments were needed for special 

circumstances. For example, a unit may not have operated in 2002 and thus have zero emissions. 

If the unit had been permanently retired prior to 2002, then we used zero emissions for the 

typical year. If the unit had not been permanently retired and would normally operate in a typical 

year, then we used the 2001 (or 2000) heat input and emission rate to calculate the typical 

year emissions. 

The Southern Company provided typical year data for their sources. Hourly emissions data for 

criteria pollutants were provided. MACTEC aggregated the hourly emissions into annual values. 

Further documentation of how Southern Company created the typical year inventory for their 

units can be found in Developing Southern Company Emissions and Flue Gas Characteristics 

for VISTAS Regional Haze Modeling (April 2005, presented at 14th International Emission 

Inventory Conference http://www.epa.gov/ttn/chief/conference/ei14/session9/kandasamy.pdf ). 

Since Southern Company only supplied filterable particulate emissions, we ran the PM10/PM2.5

augmentation routine to calculate annual emission estimates for PM10-PRI and PM2.5-PRI. 

The Southern Company typical year data were used for Southern Company sources in Alabama, 

Florida, and Mississippi. Georgia EPD elected to use the typical year normalization factor 

derived from the CAMD data instead of the Southern Company typical year data (as was used in 

the Base F inventory). 

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The final step was to replace the 2002 actual emissions with the 2002 typical year data described 

above. MACTEC provided the raw data and results of the typical year calculations in a 

spreadsheet for S/L agency review and comment. Any comments made were incorporated into 

the Base G inventory. 

Table 1.1-11 summarizes emissions by State and pollutant for the actual 2002 EGU inventory 

and the typical year EGU inventory. For the entire VISTAS region, actual 2002 SO2 emissions 

were about 0.5 percent higher than the typical year emissions. The differences on a state-be-state 

basis ranged from actual emissions being 6.6 percent lower in Florida to 10.9 percent higher in 

Mississippi. For the entire VISTAS region, actual 2002 NOx emissions were about 0.1 percent 

lower than the typical year emissions. The differences on a state-be-state basis ranged from 

actual emissions being 9.6 percent lower in Florida to 6.3 percent higher in Mississippi. 

Table 1.1-11. Comparison of SO2 and NOx Emissions (tons/year) for EGUs from Base G 

Actual 2002 Inventory and Typical 2002 Inventory. 

SO2 Emissions (tons/year) NOx Emissions (tons/year) 

State Actual 2002 Typical 2002 Percentage 

Difference Actual 2002 Typical 2002 Percentage Difference 

AL 447,828 423,736 5.4 161,038 154,704 3.9 

FL 453,631 483,590 -6.6 257,677 282,507 -9.6 

GA 514,952 517,633 -0.5 147,517 148,126 -0.4 

KY 484,057 495,153 -2.3 198,817 201,928 -1.6 

MS 67,429 60,086 10.9 43,135 40,433 6.3 

NC 477,990 478,489 -0.1 151,854 148,812 2.0 

SC 206,399 210,272 -1.9 88,241 88,528 -0.3 

TN 334,151 320,146 4.2 157,307 152,137 3.3 

VA 241,204 233,691 3.1 86,886 85,081 2.1 

WV 516,084 500,381 3.0 230,977 222,437 3.7 

Total 3,743,725 3,723,177 0.5 1,523,449 1,524,693 -0.1 

1.2 Area Sources 

This section details the development of the Base G 2002 base year inventory for area sources. 

There are three major components of the area source sector of the inventory. The first component 

is the “typical” year fire inventory. Version 3.1 of the VISTAS base year fire inventory provided 

actual 2002 emissions estimates. Since fire emissions are not easily grown or projected, in order 

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to effectively represent fires in both the base and future year inventories, VISTAS determined 

that a typical year fire inventory was necessary. Development of the “typical” year fire inventory 

covered wildfire, prescribed burning, agricultural fires and land clearing fires. The first part of 

this section of the report discusses the development of the typical year fire inventory. The 

methodology provided in that section is identical to the documentation provided for Base F since 

the “typical” year inventory was developed as part of the Base F development effort. The major 

change in Base G for the fire component of the inventory was the development of projection year 

inventories that represent alternatives to the “typical” year inventory. These alternative 

projections incorporated projected changes in the acreage burned for prescribed fires on Federal 

lands. These projections are an augmentation of the “typical” year inventory. 

The second component of the area source inventory was the incorporation of data submitted by 

the VISTAS States to the United States Environmental Protection Agency (EPA) as part of the 

CERR. Work on incorporating the CERR data into the revised base year involved: 1) obtaining 

the data from EPA, 2) evaluating the emissions and pollutants reported in order to avoid double 

counting and 3) backfilling from the existing VISTAS 2002 base year inventory for missing 

sources/pollutants. The processes used to perform those operations are described in the second 

portion of this section. That work was performed as part of the Base F inventory effort. In 

general no changes to that method were made as part of the Base G inventory updates. The 

methods used for the Base F inventory development effort using the CERR submittals have been 

maintained in this document. Where necessary, additional documentation has been added to 1) 

reflect changes that resulted from VISTAS States review of the Base F inventory and the 

incorporation of those changes into Base G, 2) changes made to how certain sources were 

estimated or 3) addition of new sources not found in Base F. 

The final component of the area source inventory was related to the development of NH3

emission estimates for livestock and fertilizers and paved road PM emissions. For the NH3

emission estimates for livestock and fertilizers we used version 3.6 of the Carnegie Mellon 

University (CMU) NH3 model. For the paved road PM emissions, we used the most recent 

estimates developed by EPA as part of the National Emission Inventory (NEI) development 

effort. EPA had developed an improved methodology for estimating paved road emissions so 

those values were substituted directly into the inventory after receiving consensus from all of the 

VISTAS States to perform the replacement. Details on these methods are provided in the third 

portion of this section of the document. That section is virtually identical to that from the Base F 

inventory document as there were only a couple of changes to the ammonia portion of the 

inventory and some updates to all fugitive dust categories including paved roads on a global 

basis between Base F and Base G. 

Finally, quality assurance steps for each component of the area source inventory are discussed. 

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1.2.1 Development of a “typical” year fire inventory 

Typical year fire emissions were developed starting from the actual fire acreage data and 

emission calculated for each VISTAS State. The table below shows the data submitted by each 

State in the VISTAS region indicating what data was received from each State for the purposes 

of calculating actual fire emissions. 

Fire Type AL FL GA KY MS NC SC TN VA WV 

Land Clearing 9 9 9 9 

Ag Burning 9 9 9 9 

Wildfires 9 9 9 9 9 9 9 9 9 9

Prescribed 9 9 9 9 9 9 9 9 9

In order to effectively characterize fire emissions in the VISTAS region, a typical (as opposed to 

strictly 2002 year based inventory) was required. Development of a typical year fire inventory 

provided the capability of using a comparable data set for both the base year and future years. 

Thus fire emissions would remain the same for air quality and visibility modeling in both the 

base and any future years. MACTEC originally proposed five different methods for developing 

the typical fire year to the VISTAS Fire Special Interest Work Group (SIWG) and requested 

their feedback and preference for developing the final typical year inventory. The method that 

was selected by SIWG members was to use a method similar to that used to develop an early 

version of a 2018 projection inventory. For that early 2018 inventory, State level ratios of acres 

over a longer term record (three or more years) developed for each fire type relative to 2002. The 

2002 acreage was then scaled up or down based on these ratios to develop a typical year 

inventory. For Base F and G, the decision of the VISTAS Fire SIWG was to base the ratio on 

county level data for States that supplied long term fire-by-fire acreage data rather than Statelevel ratios. Where States did not supply long term fire-by-fire acreage data, MACTEC reverted 

to using State-level ratios. With one broad exception (wildfires) this method was implemented 

for all fires. MACTEC solicited long term fire-by-fire acreage data by fire type from each 

VISTAS State. A minimum of three or more years of data were used to develop the ratios. Those 

data were then used to develop a ratio for each county based on the number of acres burned in 

each county for each fire type relative to 2002. 

Thus if we had long term county prescribed fire data from a State, we developed a county 

acreage ratio of: 

2002 actual county levelRx acreage

Long term average county levelRx acres Ratio =

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This ratio was then multiplied times the actual 2002 acreage to get a typical value (basically the 

long term average county level acres). Wherever possible this calculation was performed on a 

fire by fire basis. The acreage calculated using the ratio was then used with the fuel loading and 

emission factor values that we already had (and had been reviewed by the SIWG) to calculate 

emissions using the same method used for the 2002 actual values (which were previously 

documented). The following lists indicate which counties used the State ratios by fire type. 

Land Clearing Agricultural Fires Prescribed Burning 

FIPS COUNTY FIPS COUNTY FIPS COUNTY 

12086 Miami-Dade County 

12037 Franklin County 

12043 Glades County 

12045 Gulf County 

12049 Hardee County 

12057 Hillsborough County 

12073 Leon County 

12077 Liberty County 

12081 Manatee County 

12095 Orange County 

12097 Osceola County 

12103 Pinellas County 

12115 Sarasota County 

13015 Bartow County 

13021 Bibb County 

13045 Carroll County 

13047 Catoosa County 

13057 Cherokee County 

13059 Clarke County 

13063 Clayton County 

13073 Columbia County 

13077 Coweta County 

13083 Dade County 

13089 Dekalb County 

13097 Douglas County 

13117 Forsyth County 

13121 Fulton County 

13129 Gordon County 

13135 Gwinnett County 

13137 Habersham County 

13143 Haralson County 

13147 Hart County 

13151 Henry County 

13169 Jones County 

13215 Muscogee County 

13237 Putnam County 

13241 Rabun County 

13291 Union County 

13311 White County 

13063 Clayton County 

13083 Dade County 

13089 Dekalb County 

13097 Douglas County 

13121 Fulton County 

13135 Gwinnett County 

13137 Habersham County 

13215 Muscogee County 

13227 Pickens County 

13241 Rabun County 

13247 Rockdale County 

13311 White County 

13059 Clarke County 

13083 Dade County 

13089 Dekalb County 

13097 Douglas County 

13121 Fulton County 

13123 Gilmer County 

13135 Gwinnett County 

13139 Hall County 

13215 Muscogee County 

13241 Rabun County 

13247 Rockdale County 

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There were three exceptions to this method. 

Exception 1: Use of State Ratios for Wildfires 

The first exception was that wildfires estimates were developed using State ratios rather than 

county ratios. This change was made after initial quality assurance of the draft estimates revealed 

that some counties were showing unrealistic values created by very short term data records or 

missing data that created unrealistic ratios. In addition, exceptionally large and small fires were 

removed from the database since they were felt to be atypical. For example the Blackjack 

Complex fire in Georgia was removed from the dataset because the number of acres burned was 

“atypical” in that fire. We also removed all fires less than 0.1 acres from the dataset. 

Exception 2: Correction for Blackened Acres on Forest Service Lands 

Following discussions with the United States Forest Service (Forest Service) (memo from Cindy 

Huber and Bill Jackson, dated August 13, 2004), it was determined that the acres submitted by 

the Forest Service for wildfires and prescribed fires represented perimeter acres rather than 

“blackened” acres. Thus for wildfires and prescribed fires on Forest Service lands, a further 

correction was implemented to correct the perimeter acre values to blackened acres. The 

correction was made based on the size of the fire. For prescribed fires over 100 acres in size the 

acreage was adjusted to be 80 percent of the initial reported value. For prescribed fires of 100 

acres or less the acreage values were maintained as reported. For wildfires, all reported acreage 

values were adjusted to be 66 percent of their initially reported values. These changes were made 

to all values reported for Forest Service managed lands. 

Exception 3: Missing/Non-reported data 

When we did not receive data from a VISTAS State for a particular fire type, a composite 

average for the entire VISTAS region was used to determine the typical value for that type fire. 

For example, if no agricultural burning long term acreage data was reported for a particular 

State, MACTEC determined an overall VISTAS regional average ratio that was used to multiply 

times the 2002 values to produce the “typical” values. This technique was applied to all fire 

types when data was missing. 

In addition, for wildfires and prescribed burning, ratios were developed for “northern” and 

“southern” tier States within the VISTAS region and those ratios were applied to each State with 

missing data depending upon whether they were considered a “northern” or “southern” tier State. 

Development of “southern” and “northern” tier data was an attempt to account for a change from 

a predominantly pine/evergreen ecosystem (southern) to a pine/deciduous ecosystem (northern). 

States classified as “southern” included: AL, FL, GA, MS, and SC. States classified as 

“northern” included: KY, NC, TN, VA, and WV. 

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Finally for land clearing and agricultural fires, there are no NH3 and SO2 emissions. This is due 

to the lack of emission factors for these pollutants for these fire types. 

 Table 1.2-1 shows fire emissions from the original base year emission inventory (VISTAS 3.1), 

the actual 2002 emissions and the typical year emissions for the entire VISTAS region. The 

actual 2002 and typical fire emissions represent the Base F and Base G 2002 emissions. The 

typical emissions also represent the 2009 and 2018 emissions for all fire types with the exception 

of prescribed burning. Revisions made to the typical year prescribed fire emissions for 2009 and 

2018 are detailed in the projection section. Also, State level Base G emissions from fires for all 

years can be found in the tables in Appendix A. Values for fires in those tables are “typical” year 

values. 

Figures 1.2-1 through 1.2-4 show the State by State changes in emissions between the original 

2002 base year fire inventories, the actual 2002 and the typical year inventories for carbon 

monoxide (CO) by fire type. Due to the relative magnitude of CO emissions compared to other 

criteria and PM pollutants from fires; this pollutant is normally chosen to represent the 

distribution of fires in the example plots. 

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Table 1.2-1. Emissions from Fires in the VISTAS Region – Comparison between Original Base Year 2002 

Actual and Typical Year Base G Emissions. 

CO NH3 NOX PM10-FIL PM10-PRI PM2.5-FIL PM2.5-PRI 

Total LC Actual (Base G) 492,409 0 14,568 62,146 62,146 62,146 62,146 

Typical (Base G) 675,838 0 19,995 80,598 80,598 80,598 80,598 

VISTAS 3.1 484,240 0 14,327 61,325 61,325 61,325 61,325 

Total Ag Actual (Base G) 164,273 0 903 30,958 30,958 30,385 30,385 

Typical (Base G) 161,667 0 903 30,465 30,465 29,892 29,892 

VISTAS 3.1 331,073 0 903 41,480 41,480 40,192 40,192 

Total WF Actual (Base G) 298,835 1,333 6,628 28,923 28,923 24,926 24,926 

Typical (Base G) 547,174 2,451 11,955 53,070 53,070 45,635 45,635 

VISTAS 3.1 275,766 1,230 6,133 26,680 26,680 23,002 23,002 

Total RX Actual (Base G) 1,678,216 7,616 36,561 168,938 168,938 145,175 145,175 

 Typical (Base G) 1,635,776 7,425 35,650 164,811 164,811 141,636 141,636  VISTAS 3.1 1,724,940 7,822 37,556 173,590 173,590 149,181 149,181 

Key: LC = Land Clearing; Ag = Agricultural burning; WF = wildfires; RX = prescribed burning. Actual and Typical represent Base F 

change in methodology for Base F and Base G) for 2002. 

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Figure 1.2-1. CO Emissions from Agricultural Burning for the Original Base Year, 2002 Actual Base G

Base G Inventories.

CO Emissions

0.00

20,000.0040,000.0060,000.0080,000.00

100,000.00120,000.00140,000.00160,000.00

AL FL GA KY MS NC SC TN VA 

tons

Ag Burning - 2002 Actual Ag Burning - Typical Ag Burning - VISTAS 3.1

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Figure 1.2-2. CO Emissions from Land Clearing Burning for the Original Base Year, 2002 Actual Base G 

Base G Inventories. 

CO Emissions

0.00

20,000.0040,000.0060,000.0080,000.00

100,000.00120,000.00140,000.00160,000.00180,000.00

AL FL GA KY MS NC SC TN 

tons

Land Clearing - 2002 Actual Land Clearing - Typical Land Clearing - VISTAS 

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Figure 1.2-3. CO Emissions from Prescribed Burning for the Original Base Year, 2002 Actual Base G 

Base G Inventories. 

CO Emissions

0.00

100,000.00200,000.00300,000.00400,000.00500,000.00600,000.00700,000.00

AL FL GA KY MS NC SC TN 

tons

Prescribed - 2002 Actual Prescribed - Typical Prescribed - VISTAS 3.1

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Figure 1.2-4. CO Emissions from Wildfire Burning for the Original Base Year, 2002 Actual Base G a

Base G Inventories.

CO Emissions

0.00

50,000.00

100,000.00150,000.00200,000.00250,000.00

AL FL GA KY MS NC SC TN VA 

tons

Wildfires - 2002 Actual Wildfires - Typical Wildfires - VISTAS 3.1

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1.2.2 Development of non-fire inventory 

The second task in preparing the area source component of the Base F and Base G 2002 base 

year inventory was the incorporation of data submitted by the VISTAS States to the EPA as part 

of the CERR. With few exceptions, Base F and Base G inventories for this component of the 

inventory are identical. Modifications to the Base F methodology (described below) only 

resulted from modifications from the VISTAS States during review of the Base F inventory. The 

changes made to the inventory based on these reviews are described in the last portion of this 

section of the report. The information presented below describes the method used to incorporate 

CERR data as part of Base F. 

Work on incorporating the CERR data into the 2002 Base F inventory involved: 1) obtaining the 

data from EPA, 2) evaluating the emissions and pollutants reported in order to avoid double 

counting and 3) backfilling from the earlier version of the VISTAS 2002 base year inventory for 

missing sources/pollutants. The processes used to perform those operations are described below. 

This work did not include any of the fire emission estimates described above. In addition it did 

not include emission estimates for ammonia from agricultural and fertilizer sources. Finally it did 

not include PM emissions from paved roads. Each of those categories was estimated separately. 

Data on the CERR submittals was obtained from EPA’s Draft NEI download file transfer 

protocol (FTP) site where the data are stored after they’ve been processed for review. The data 

submitted in National Emission Inventory Format (NIF) was downloaded from that site. Once all 

of the files were obtained, MACTEC ran the files through the EPA NIF Format and Content 

checking tool to ensure that the files were submitted in standard NIF format and that there were 

no issues with those files. In a couple of cases small errors were found. For example, in one case 

a county FIPs code that was no longer in use was found. MACTEC contacted each VISTAS 

State area source contact person to resolve the issues with the files and corrections were made. 

Once all corrections to the native files were completed, MACTEC continued with the 

incorporation of the data into the VISTAS area source files. 

Our general assumption was that unless we determined otherwise, the CERR submittals 

represented full and complete inventories. Where a State submitted a complete inventory, our 

plan was to simply delete the previous 2002 base year data and replace it with the CERR 

submittal. Prior to this replacement however, we stripped out the following emissions: 

1. All wildfire, prescribed burning, land clearing and agricultural burning emissions 

submitted to EPA by the States as part of the CERR process were removed since they 

were to be replaced with emissions estimated using methods described earlier. 

2. All fertilizer and agricultural ammonia emission records submitted to EPA by the 

States as part of the CERR process were removed. These were replaced with the 

estimates developed using the CMU Ammonia model. 

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3. All emissions from paved roads submitted to EPA by the States as part of the CERR 

process were removed. These emissions were replaced with updated emissions 

developed by U.S. EPA as part of their 2002 NEI development effort. 

This approach was used for most State and Local emission submittals to prepare the Base F 

inventory. There were a few cases where alternative data were used to prepare the Base F 

inventory. In general, these alternatives involved submittal of alternative files to the CERR data 

by S/L agencies. Table 1.2-2 below summarizes the data used to prepare the Base F inventory. In 

general the data were derived from one of the following sources: 

1. CERR submittal obtained from EPA FTP site as directed by VISTAS States; 

2. State submitted file (either revised from CERR submittal or separate format); 

3. VISTAS original 2002 base year (VISTAS version 3.1 base year file); or 

4. EPA’s preliminary 2002 NEI. 

Table 1.2-2. Summary of State Data Submittals for the 2002 VISTAS Area Source 

Base F Inventory 

State / Local Program Area Source Emissions Data Source 

AL B 

FL B 

GA C 

KY A 

MS B 

NC C 

SC B 

TN B 

VA B 

WV A/C 

Davidson County, TN B 

Hamilton County, TN C 

Memphis/Shelby County, TN A 

Knox County, TN B 

Jefferson County, AL * so B from State 

Jefferson County, KY B 

Buncombe County, NC * so C from State 

Forsyth County, NC * so C from State 

Mecklenburg County, NC * so C from State 

A = VISTAS 2002 (version 3.1) 

B = CERR Submittal from EPA's ftp site 

C = Other (CERR or other submittal sent directly from State to MACTEC) 

* = No response 

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In order to track the sources of data in the final Base F and Base G NIF files, a field was added to 

the NIF format files developed for VISTAS to track each data source. A field named 

Data_Source was added to the EM table. A series of codes were added to this field to mark the 

source of each emissions value in the Base F and Base G inventories. Values in this field are 

detailed in Table 1.2-3. 

Table 1.2-3: Data Source Codes and Data Sources for VISTAS 2002 Base F Area Source 

Emissions Inventory. 

Data Source Codes Data Source 

Base F Codes 

CMU Model CMU Ammonia model v 3.6 

E-02-X or E-99-F or L-02-X or S-02-X EPA CERR submittal (from FTP site) 

EPA Paved EPA Paved Road emissions estimates 

EPAPRE02NEI EPA Preliminary 2002 NEI 

STATEFILE State submitted file 

VISTBASYR31 VISTAS 2002 Base Year version 3.1 

VISTRATIO Developed from VISTAS Ratios (used only 

for missing pollutants) 

Additional Base G Codes 

ALBASEGFILE Base G update file provided by AL 

NCBASEGFILE Base G update file provided by NC 

OTAQRPT Portable Fuel Container Emissions from 

OTAQ Report 

STELLA Revised data provided by VISTAS EI Advisor 

Greg Stella 

VABASEGFILE Base G update file provided by VA 

VAStateFile Revisions/additions to Base G update file 

provided by VA 

Most States submitted complete inventories for Base F. Virginia’s inventory required a two stage 

update. Virginia’s CERR submittal only contained ozone precursor pollutants (including CO). 

For Virginia, MACTEC’s original plan was to maintain the previous 2002 VISTAS base year 

emissions for non-ozone pollutants and then do a simple replacement for ozone pollutants. 

However during the QA phase of the work, MACTEC discovered that there were categories that 

had ozone precursor or CO emissions in the submittal that weren’t in the original 2002 VISTAS 

base year inventory that should have PM or SO2 emissions. For those records, MACTEC used an 

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emissions ratio to build records for emissions of these pollutants. Data for Virginia PM and SO2

emissions were generated by developing SCC level ratios to NOx from the VISTAS 2002 base 

year inventory (version 3.1) or from emission factors and then calculating the emissions based on 

that ratio. 

1.2.3 2002 Base G inventory updates 

After the Base F inventory was submitted and used for modeling, VISTAS States were provided 

an opportunity for further review and comment on the Base F inventory. As a result of this 

review and comment period, several VISTAS States provided revisions to the Base F inventory. 

In addition to and as an outgrowth of some of the comments provided by the States during the 

review process, some of the changes made to the inventory were made globally across the entire 

VISTAS region. This section discusses the specific State changes followed by the global changes 

made to the area source component of the inventory for all VISTAS States. 

1.2.3.1 Changes resulting from State review and comment 

Alabama

Alabama suggested several changes and had questions concerning a few categories in the Base F 

inventory. The changes/questions were: 

1. For Source Classification Code (SCC) 2102005000 (Industrial Boilers: 

Residual Oil) and SCC 2103007000 (Institutional/Commercial Heating: 

Liquefied Petroleum Gas) the Alabama noted that the Base F VISTAS 

inventory had values for NOx, VOC and CO for the State, but no values for 

SO2, PM10 or PM2.5. 

MACTEC evaluated this information and found that there were actually emissions for two 

counties in AL for that SCC that had either SO2 and/or PM emissions. The data used to develop 

the 2002 Base F inventory for AL came from the preliminary 2002 CERR submittals (see above) 

which should have included SO2 and PM but did not except for two counties. According to 

MACTEC’s protocol for use of these files, the files received from EPA were to be used “as is” 

unless the States provided comments during the Base F comment period to correct the CERR 

submittal. No comments were received from AL on the CERR submittal used for Base F. For 

2002 Base G, AL provided an updated database file for these SCCs for all counties in the State 

that provided revised values for emissions and included SO2 and PM. The revised file was used 

to update the Base F data for Base G. 

2. AL noted that the Base F inventory included SCC 2401002000 (Solvent 

Utilization, Surface Coating, Architectural Coatings - Solvent-based, Total: 

All Solvent Types) and 2401003000 (Solvent Utilization, Surface Coating, 

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Architectural Coatings - Water-based, Total: All Solvent Types) as well as 

SCC 2401001000 (Solvent Utilization, Surface Coating, Architectural 

Coatings, Total: All Solvent Types). This resulted in double counting of the 

emissions for this category. AL suggested removal of the breakdown SCCs 

and use of the total SCC. 

MACTEC deleted records for the breakdown SCCs and retained the total all solvents 

SCC emissions. 

3. AL found the SCCs listed below missing from the Base F VISTAS inventory. 

SCC 

VOC 

Emissions SCC Description 

2401025000 1139.91 Surface Coatings: Metal Furniture, all coating types 

2401030000 425.27 Surface Coatings: Paper, all coating types 

2401065000 344.08 Surface Coatings: Electronic and Other Electrical, all coating 

types 

2430000000 504.29 Solvent Utilization, Rubber/Plastics, All Processes, Total: All 

Solvent Types 

2440020000 3043.78 Solvent Utilization, Miscellaneous Industrial, Adhesive 

(Industrial) Application, Total: All Solvent Types 

Total for AL 5457.32 

MACTEC found that the emissions for these SCCs were included in the Base F inventory, but 

with slightly different total emissions. AL provided an updated county-level emissions file for 

use in updating the Base G inventory. That file was used to update the NIF records for AL for 

those SCCs. 

4. AL noted that emissions in the Base F inventory were found for SCC 

2465000000 and SCCs 2465100000, 2465200000, 2465400000, 2465600000, 

and 2465800000. These last five SCCs represent a subset of the emissions in 

the 246500000 SCC resulting in potential double counting of emissions. 

MACTEC deleted all emissions associated with the Total SCC 2465000000 and retained the 

subset SCCs for the Base G inventory. 

Florida

Florida provided comments indicating that they felt that emissions from the following sources 

and counties were too high, especially for CO and PM and were likely zero: 

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• motor vehicle fire - Palm Beach County 

• woodstoves - Miami Dade, Hillsborough, Orange, Polk, Ft Myers, Pasco and Sarasota 

Counties 

• fireplaces - Miami Dade and Hillsborough Counties 

Emissions from these sources in the counties specified were set to zero by MACTEC for the 

Base G inventory. 

North Carolina

North Carolina provided corrected emission files for 2002 Base F. A text file with emission 

values was provided and used to update the Base F emissions to Base G. The updated emissions 

were applied directly to the Base F NIF file. The file provided was similar to the “EM” NIF 

table. An update query was used to update the data supplied in the text file to the Access 

database NIF file. All changes were implemented. 

South Carolina

South Carolina had two issues concerning the Base F inventory. These issues related to 1) 

additional SCCs that were in BASE F 2009 and 2018, but not in 2002 Base F and 2) SCCs that 

were in the U.S. EPA 2002 NEI inventory, but not in the VISTAS 2002, 2009, or 2018 Base F 

inventory. 

MACTEC investigated the additional SCCs found in 2009 and 2018 Base F and found that the 

SCCs actually were not missing in the 2002 Base F inventory but only had emissions for PM. 

Thus the emissions were maintained as they were provided in Base F. 

With respect to the SCCs that were found in the U.S. EPA 2002 NEI, MACTEC investigated and 

found that they were not included in the Base F inventory because they were not included in the 

2002 CERR submittal used to produce the Base F updates. The SCCs were apparently added by 

EPA later in the NEI development process. In addition, MACTEC also evaluated whether or not 

the SCCs were found in other VISTAS States Base F inventories. MACTEC found that some 

States included them and some did not, there was no consistency between the States. MACTEC 

also found that typically emissions for these SCCs were low in emissions, generally with 

emissions of only a few tons to tens of tons per year. The decision was made with South Carolina 

concurrence not to add these SCCs to the Base G inventory. These SCCs were: 210205000, 

2102011000, 2103007000, 2103011000, 2104007000, 2104011000, 2302002100, 2302002200, 

2302003100, 2302003200, 2610000500, 2810001000, and 281001500. 

Virginia

Virginia provided an updated 2002 base year emissions file. The data in that file were used to 

update the Base F inventory emission values to those for Base G. In addition, Virginia provided 

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information on several source categories that required controls for future year projections since 

the sources were located in counties/cities in northern Virginia and were subject to future year 

Ozone Transport Commission (OTC) regulations. MACTEC added in the base year control 

levels to the Base G inventory file for these categories so that they could be estimated correctly 

in future years. The controls added were for mobile equipment repair/refinishing sources, 

architectural and industrial maintenance coating sources, consumer products sources, and solvent 

metal cleaning sources. Minor errors were found in some entries for the initial file provided and 

VA provided a revised file with corrections and minor additions. 

1.2.4 Ammonia and paved road emissions 

The final component of the Base F inventory development was estimation of NH3 emission 

estimates for livestock and fertilizers and paved road PM emissions. For the NH3 emission 

estimates for livestock and fertilizers we used version 3.6 of the CMU NH3 model 

(http://www.cmu.edu/ammonia/). Results from this model were used for all VISTAS States. The 

CMU model version 3.6 was used in large part because it had been just recently been updated to 

include the latest (2002) Census of Agriculture animal population statistics. Prior to inclusion of 

the CMU model estimates, MACTEC removed any ammonia records for agricultural livestock or 

fertilizer emissions from the VISTAS 2002 initial base year inventory. MACTEC also generated 

emissions from human perspiration and from wildlife using the CMU model and added those 

emissions for each State. 

For the Base G ammonia inventory, MACTEC removed all wildlife and human perspiration 

emissions. VISTAS decided to remove these emissions from the inventory. Human perspiration 

was dropped due to a discrepancy in the units used for the emission factor that was not resolved 

prior to preparing the estimates and wildlife was dropped because VISTAS felt the activity data 

was too uncertain. Thus all emissions from these two categories were deleted in the Base G 2002 

inventory. 

For the paved road PM Base F emissions, we used the most recent estimates developed by EPA 

as part of the NEI development effort (Roy Huntley, U.S. EPA, email communication, 

8/30/2004). EPA had developed an improved methodology for estimating paved road emissions 

for 2002 and had used that method to calculate emissions for that source category. MACTEC 

obtained those emissions from EPA and those values were substituted directly into the inventory 

after receiving consensus from all of the VISTAS States to perform the replacement. These files 

were obtained in March of 2005 in NIF format from the EPA FTP site. 

For the Base G emissions, modifications were made to the emissions estimates based on changes 

suggested by work of the Western Regional Air Partnership and U.S. EPA. Details of these 

changes are provided below in the section on global changes made as part of the Base G 

inventory updates. 

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1.2.5 Global Changes Made for Base G 

There were three global changes made between the Base F and the Base G inventory (beyond the 

removal of wildlife and human perspiration NH3 emissions). These changes were: 

1. Removal of Stage II emissions from the area source inventory and inclusion in the mobile 

sector of the inventory, 

2. Adjustment of fugitive dust PM2.5 emissions, and 

3. Addition of emissions from portable fuel containers. 

As part of the Base F review process, several VISTAS States had expressed surprise that the 

Stage II refueling emission estimates were in the area source component of the inventory. This 

decision had been made with SIWG agreement early on in the inventory development process 

because 1) some States had included it in their CERR submittals and 2) because the non-road and 

on-road mobile estimates had differing activity factor units and could not be easily combined. 

However for Base G, the VISTAS States all agreed, especially in light of the different ways in 

which the emissions were reported in the CERR, to remove the Stage II refueling emissions from 

the area source inventory and include them in the non-road and on-road sectors. Thus all records 

related to Stage II refueling were removed from the area source component of the Base 

G inventory. 

PM2.5 emissions from several fugitive dust sources were also updated for Base G. The Western 

Regional Air Partnership (WRAP) and U.S. EPA had been investigating overestimation of the 

PM2.5 / PM10 ratio in several fugitive dust categories and U.S. EPA was in the process of making 

revisions to AP-42 for several categories during preparation of the Base G inventory. Based on 

data received from U.S. EPA, VISTAS decided to revise the PM2.5 emissions from construction, 

paved roads and unpaved road sources. PM2.5 emissions in Base F were multiplied by 0.67, 0.6, 

and 0.67 for construction, paved roads and unpaved roads respectively to produce the values 

found in Base G. No changes were made to PM10, only to PM2.5. 

Finally, as part of Virginia’s comments on the Base F inventory, emissions from portable fuel 

containers were mentioned as being absent from the inventory. MACTEC was tasked with 

developing a methodology that could be used to add these emissions to the Base G area source 

inventory. In investigating options for a method of estimating emissions, MACTEC found that 

the U.S. EPA had prepared a national inventory of emissions by State for portable fuel 

containers. Data on emissions from this source prepared by U.S. EPA were presented in, 

“Estimating Emissions Associated with Portable Fuel Containers (PFCs), Draft Report, Office of 

Transportation and Air Quality, United States Environmental Protection Agency, Report # 

EPA420-D-06-003, February 2006”. 

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State-level emission estimates for 2005 derived from Appendix Table B-2 of the PFCs report 

were used as the starting point for developing 2002 county-level emissions estimates. State 

emissions were derived from that table by using all of the emission estimates in that table with 

the exception of values for vapor displacement and spillage from refueling operations. Those 

components of the State emissions were left out of the State-level emissions to avoid double 

counting refueling emissions in the non-road sector. For the purposes of 2002 emission estimates 

for Base G, the 2005 values were assumed equal to 2002 values. 

The 2005 State-level estimates minus the refueling component from Appendix Table B-2 of the 

report were summed for each State and then allocated to the county-level. The county-level 

allocation was based on the fuel usage information obtained from the NONROAD 2005 model 

runs conducted as part of the Base G inventory development effort (see the 2002 base year Base 

G non-road section below). MACTEC used the spillage file from the NONROAD model 

(normally located in the DATA\EMSFAC directory in a standard installation of NONROAD) to 

determine the SCCs that used containers for refueling. The spillage file contains information by 

SCC and horsepower indicating whether or not the refueling occurs using a container or a pump. 

All SCC and horsepower classes using containers were extracted from the file and crossreferenced with the fuel usage by county for those SCC/horsepower combinations from the 

appropriate year model runs (2002, 2009 or 2018). Then the fuel usages by county from the 

NONROAD 2005 runs prepared for VISTAS were summed for those SCCs by county. The 

county level fuel use was then divided by the State total fuel use for the same SCCs to determine 

the fraction of total State fuel usage and that fraction was used to allocate the State-level 

emissions to the county. 

1.2.6 Quality Assurance steps 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, and to ensure that a full and complete 

inventory was developed for VISTAS. Quality assurance was an important component to the 

inventory development process and MACTEC performed the following QA steps on the area 

source component of the 2002 Base F inventory: 

1. All CERR and NIF format State supplied data submittals were run through EPA’s 

Format and Content checking software. 

2. SCC level emission summaries were prepared and evaluated to ensure that emissions 

were consistent and that there were no missing sources. 

3. Tier comparisons (by pollutant) were developed between the revised 2002 base year 

inventory and the previous (version 3.1) base year inventory. 

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4. Fields were either added or used within each NIF data table to track the sources of 

data for each emission record. 

5. Data product summaries were provided to both the VISTAS Emission Inventory 

Technical Advisor and to Area Source and Fires SIWG representatives for review and 

comment. Changes based on these comments were implemented in the files. 

6. Version numbering was used for all inventory files developed. The version 

numbering process used a decimal system to track major and minor changes. For 

example, a major change would result in a version going from 1.0 to 2.0. A minor 

change would cause a version number to go from 1.0 to 1.1. Minor changes resulting 

from largely editorial changes would result in a change from 1.00 to 1.01. 

In addition, for the fires inventory, data related to fuel loading and fuel consumption was 

reviewed and approved by the VISTAS Fire SIWG to ensure that values used for each type of 

fire and each individual fire were appropriate. Members of the VISTAS Fire SIWG included 

representatives from most State Divisions of Forestry (or equivalent) as well as U.S. Forest 

Service and National Park Service personnel. 

For Base G, similar QA steps to those outlined above for Base F were undertaken. In addition, all 

final NIF files were checked using the EPA Format and Content checking software and summary 

information by State and pollutant were prepared comparing the Base F and Base G inventories. 

1.3 Mobile Sources 

This section describes the revisions made to the initial 2002 VISTAS Base Year emission 

inventory on-road mobile source input files. For this work actual emission estimates were not 

made, rather data files consistent with Mobile Emissions Estimation Model Version 6 

(MOBILE6) were developed and provided to the VISTAS modeling contractor. These input data 

files were then run during the VISTAS modeling to generate on-road mobile source emissions 

using episodic and meteorological specific conditions configured in the sparse matrix operator 

Kernel Emissions modeling system (SMOKE) emissions processor. 

During initial discussions with the VISTAS Mobile Source SIWG, some States indicated a desire 

to use CERR mobile source emissions data in place of the VISTAS 2002 inventories generated 

by E.H. Pechan and Associates, Inc. (the initial VISTAS 2002 Base Year inventory files). 

However, the CERR emissions data by itself were not sufficient for an inventory process that 

includes both base and future year inventories. MACTEC needed to be able to replicate the 

CERR data rather than simply obtain CERR emissions estimates. The reason for this is that only 

input files were being prepared to provide revised 2002 estimates during the VISTAS modeling 

process, rather than the actual emission estimates and that the 2002 input data files would be 

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used as a starting point for the projected emission estimates. This meant that the appropriate 

vehicle miles traveled (VMT), MOBILE6, and/or NONROAD model input data needed to be 

provided. If these data were provided with the CERR emissions estimates we used it as the 

starting point for revision of the 2002 Base Year inventory. However MACTEC did not have 

access to the on-road mobile CERR submissions from EPA, so re-submittal of these data directly 

to MACTEC was requested in order to begin compiling the appropriate input file data. 

In those cases where States did not provide CERR on-road mobile source input data files, our 

default approach was to maintain the data input files and VMT estimates for the initial 2002 Base 

Year inventory prepared by Pechan. 

1.3.1 Development of on-road mobile source input files and VMT estimates 

Development of the 2002 on-road input files and VMT was a multi-step process depending upon 

what the State mobile source contacts instructed us to use as their data. Information provided 

below provides incremental revisions made to on-road mobile source inventories or inputs in 

series from one inventory version to the next. In general the process involved one of three steps 

from the original 2002 on-road mobile source data. 

Base F Revisions 

1. The first step was to evaluate the initial 2002 base year files and make any nonsubstantive changes (i.e., changes only to confirm that the files posted for 2002 by 

Pechan were executable and that all the necessary external files needed to run MOBILE6 

were present). This approach was taken for AL, FL, GA, MS, SC, and WV. For these 

States the determination was made that the previous files would be okay to use as 

originally prepared. For SC, the VMT file was updated, but that did not affect the 

MOBILE6 input files. 

2. For other States, modification to the input files was required. The information below 

indicates what changes were made for other States in the VISTAS region. 

KY – For Kentucky, the Inspection and Maintenance (I/M) records in the input files for Jefferson 

County were updated in order to better reflect the actual I/M program in the Louisville 

metropolitan area. 

NC - Substantial revisions were implemented to these input files based on input from the State. 

The modifications necessary to reflect the desires of the State led to complete replacement of the 

previous input files. Among the changes made were: 

• The regrouping of counties (including the movement of some counties from one 

county group to another and the creation of new input files for previously grouped 

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counties). There were originally 32 input files; after the changes there were 49. The 

pointer file was corrected to reflect these changes. 

• Travel speeds were updated in over 3000 scenarios. 

• All I/M records were updated. 

• All registration distributions were updated. 

• I/M VMT fractions were updated (which only affected the pointer file). 

• VMT estimates were updated (which has no direct effect on the MOBILE6 input files 

but does ultimately affect emissions). 

3. VA and TN – For these States, new input files were provided due to substantive changes 

that the State wanted to make relative to the 2002 initial base year input files. In addition, 

revised VMT data were developed for each State. 

Base G Revisions

For the production of the VISTAS 2002 Base G inventory, VISTAS states reviewed the Base F 

inputs, and provided corrections, updates and supplemental data. 

For all states modeled, the Base G updates include: 

Adding Stage II refueling emissions calculations to the SMOKE processing. 

Revised the HDD compliance for all states. (REBUILD EFFECTS = .1) 

In addition to the global changes, individual VISTAS states made the following updates: 

KY – updated VMT and M6 input values for selected counties. 

NC – revised VMT and registration distributions. 

TN - revised VMT and vehicle registration distributions for selected counties. 

VA – revised winter RFG calculations in Mobile 6 inputs. 

WV – revised VMT input data. 

AL, FL, and GA did not provide updates for Base G and therefore the Base F inputs were used 

for these States. 

1.3.1.1 Emissions from on-road mobile sources 

The MOBILE6 module of the Sparse Matrix Operator Kernel Emissions (SMOKE) model was 

used to develop the on-road mobile source emissions estimates for CO, NOX, NH3, SO2, PM, and 

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VOC emissions. The MOBILE6 parameters, vehicle fleet descriptions, and VMT estimates are 

combined with gridded, episode-specific temperature data to calculate the gridded, temporalized 

emission estimates. The MOBILE6 emissions factors are based on episode-specific temperatures 

predicted by the meteorological model. Further, the MOBILE6 emissions factors model accounts 

for the following: 

• Hourly and daily minimum/maximum temperatures; 

• Facility speeds; 

• Locale-specific inspection/maintenance (I/M) control programs, if any; 

• Adjustments for running losses; 

• Splitting of evaporative and exhaust emissions into separate source categories; 

• VMT, fleet turnover, and changes in fuel composition and Reid vapor pressure 

(RVP). 

The primary input to MOBILE6 is the MOBILE shell file. The MOBILE shell contains the 

various options (e.g. type of inspection and maintenance program in effect, type of oxygenated 

fuel program in effect, alternative vehicle mix profiles, RVP of in-use fuel, operating mode) that 

direct the calculation of the MOBILE6 emissions factors. The shells used in these runs were 

based on VISTAS Base F modeling inputs as noted in the previous section. 

For this analysis, the on-road mobile source emissions were produced using selected weeks 

(seven days) of each month and using these days as representative of the entire month. This 

selection criterion allows for the representation of day-of-the-week variability in the on-road 

motor vehicles, and models a representation of the meteorological variability in each month. The 

modeled weeks were selected from mid-month, avoiding inclusion of major holidays. 

The parameters for the SMOKE runs are as follows: 

 Episodes: 

 2002 Initial Base Year, and 

2009 and 2018 Future years, using 2009/2018 inventories and modeled using the 

same meteorology and episode days as 2002. 

 Episode represented by the following weeks per month: 

 January 15-21 

 February 12-18 

 March 12-18 

 April16-22 

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 May 14-20 

 June 11-17 

 July 16-22 

 August 13-19 

 September 17-23 

 October 15-21 

 November 12-18 

 December 17-23 

 Days modeled as holidays for annual run: 

 New Year’s Day - January 1 

 Good Friday – March 29 

 Memorial Day – May 27 

 July 4th 

 Labor Day – September 2 

 Thanksgiving Day – November 28, 29 

 Christmas Eve – December 24 

 Christmas Day – December 25 

 Output time zone: 

 Greenwich Mean Time (zone 0) 

 Projection: 

 Lambert Conformal with Alpha=33, Beta=45, Gamma=-97, and center at 

 (-97, 40). 

 Domain: 

36 Kilometer Grid: Origin at (-2736, -2088) kilometers with 148 rows by 112 

columns and 36-km square grid cells. 

12 Kilometer Grid: Origin at (108, -1620) kilometers with 168 rows by 177 

columns and 12-km square grid cells. 

 CMAQ model species: 

The CMAQ configuration was CB-IV with PM. The model species produced 

were: CO, NO, NO 

2, ALD 2, ETH, FORM, ISOP, NR, OLE, PAR, TERPB, TOL, 

XYL, NH 

3, SO 2, SULF, PEC, PMFINE, PNO 3, POA, PSO 4, and PMC. 

 Meteorology data: 

Daily (25-hour). SMOKE requires the following five types of MCIP outputs: (1) 

Grid cross 2-d, (2) Grid cross 3-d, (3) Met cross 2-d, (4) Met cross 3-d, and (5), 

Met dot 3-d. 

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The reconstructed emissions based on the representative week run were calculated by mapping 

each day of week (Mon, Tue, Wed, etc.) from the modeled month to the same day of week 

generated in the representative week run. In the case of holidays, these days were mapped to 

representative week Sundays. An example of this mapping for the January episode is presented 

in Table 1.3-1 below. Note that although the emissions were generated for individual calendar 

years (2002, 2009 and 2018) the meteorology is based on 2002. 

Table 1.3-1. Representative day mapping for January episode 

(Highlighted representative week). 

Modeled Representative Modeled Representative Modeled Representative 

Date Day Date Day Date Day 

1/1/2002* 1/20/2002 1/11/2002 1/18/2002 1/22/2002 1/15/2002 

1/2/2002 1/16/2002 1/12/2002 1/19/2002 1/23/2002 1/16/2002 

1/3/2002 1/17/2002 1/13/2002 1/20/2002 1/24/2002 1/17/2002 

1/4/2002 1/18/2002 1/14/2002 1/21/2002 1/25/2002 1/18/2002 

1/5/2002 1/19/2002 1/15/2002 1/15/2002 1/26/2002 1/19/2002 

1/6/2002 1/20/2002 1/16/2002 1/16/2002 1/27/2002 1/20/2002 

1/7/2002 1/21/2002 1/17/2002 1/17/2002 1/28/2002 1/21/2002 

1/8/2002 1/15/2002 1/18/2002 1/18/2002 1/29/2002 1/15/2002 

1/9/2002 1/16/2002 1/19/2002 1/19/2002 1/30/2002 1/16/2002 

1/10/2002 1/17/2002 1/20/2002 1/20/2002 1/31/2002 1/17/2002 

 1/21/2002 1/21/2002 

* Modeled holiday 

1.3.2 Development of non-road emission estimates 

Emissions from non-road sources were estimated in two steps. First, emissions for non-road 

sources that are included in the NONROAD model were developed. Second, emissions from 

sources not included in the NONROAD model were estimated. The sections below detail the 

procedures used for each group of sources. 

1.3.2.1 Emissions from NONROAD model sources 

An initial 2002 base year emissions inventory for non-road engines and equipment covered by 

the EPA NONROAD model was prepared for VISTAS in early 2004. The methods and 

assumptions used to develop the inventory are presented in a February 9, 2004 report 

“Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 

Version)” as prepared by E.H. Pechan & Associates, Inc. Except as otherwise stated below, all 

aspects of the preparation methodology documented in that report continue to apply to the 

revised NONROAD modeling discussed in this section. 

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Revisions to the initial 2002 NONROAD emissions inventory were implemented to ensure that 

the latest State and local data were considered, as well as to more accurately reflect gasoline 

sulfur contents for 2002 and correct other State-specific discrepancies. Those revisions comprise 

the Base F VISTAS non-road inventory. This section details the specific revisions made to the 

NONROAD model input files for the Base F and Base G VISTAS base year inventories, and 

provides insight into some key differences between the versions of the NONROAD model 

employed for the Base F and Base G inventories and the previous version employed for the 

initial 2002 base year inventory prepared by Pechan. 

Revisions to the initial 2002 emissions inventory prepared by Pechan were actually implemented 

in two stages. An initial set of revisions was implemented in the fall of 2004. Those revisions 

resulted in the Base F inventory. These were followed by a second set of revisions in the spring 

of 2006. Those estimates produced the Base G base year inventory. To accurately document the 

combined effects of both sets of revisions, each set is discussed separately below. Unless 

otherwise indicated, all revisions implemented in Base F were carried directly into the Base G 

revision process without change. Thus, the inventories that resulted from the Base F revisions 

served as the starting point for the Base G revisions. 

For Base F, three VISTAS States provided detailed data revisions for consideration in 

developing revised model inputs. These States were: 

1. North Carolina 

2. Tennessee (including a separate submission for Davidson County), and 

3. Virginia. 

The remaining seven VISTAS States indicated that the initial 2002 VISTAS input files prepared 

by Pechan continued to reflect the most recent data available. These States were: 

1. Alabama, 

2. Florida, 

3. Georgia, 

4. Kentucky, 

5. Mississippi, 

6. South Carolina, and 

7. West Virginia. 

However, it should be recognized that the NONROAD input files for all ten VISTAS States were 

updated to reflect gasoline sulfur content revisions for the Base F 2002 base year inventory (as 

discussed below). The original files prepared by Pechan are available on their FTP site in the 

/pub/VISTAS/MOB_0104/ directory. 

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Before presenting the specific implemented revisions, it is important to note that the Base F 2002 

base year inventory utilized a newer release of the NONROAD model than was used for the 

initial 2002 base year inventory (prepared by Pechan). The Base F 2002 base year inventory, as 

developed in spring 2004, was based on the Draft NONROAD2004 model, which was released 

by the EPA in May of 2004. This model is no longer available on EPA’s website. The initial 

2002 base year inventory (prepared by Pechan) was based on the Draft NONROAD2002a 

version of the model (which is also no longer available on EPA’s website). Key differences 

between the models are as follows: 

• Draft NONROAD2004 included the effects of the Tier 4 non-road engine and equipment 

standards (this did not impact the Base F 2002 inventory estimates, but did affect Base F 

future year forecasts). 

• Draft NONROAD2004 included the exhaust emission impacts of the large spark-ignition 

engine standards; the evaporative impacts of these standards are not incorporated (this 

does not impact 2002 inventory estimates, but does affect future year forecasts). 

• Draft NONROAD2004 included revised equipment population estimates. 

• The PM2.5 fraction for diesel equipment in Draft NONROAD2004 had been updated from 

0.92 to 0.97. 

• Draft NONROAD2004 included revisions to recreational marine activity, useful life, and 

emission rates. 

To the extent that these revisions affect 2002 emissions estimates, they will be reflected as 

differentials between the initial and Base F 2002 VISTAS base year inventories. It is perhaps 

important to identify that, at the time of the Base F inventory revisions; the EPA recognized the 

Draft NONROAD2004 model as an appropriate mechanism for SIP development. Although the 

model was designated as a draft update, it reflected the latest and most accurate NONROAD 

planning data at that time, as evidenced by the EPA’s use of that version for the Tier 4 Final 

Rulemaking. 

Prior to the Base G inventory revisions implemented in 2006, the EPA released another updated 

version of the NONROAD model, designated as Final NONROAD2005 (which can be 

downloaded from: http://www.epa.gov/OMSWWW/nonrdmdl.htm#model). This version 

ostensibly represents the final version of the model, although certain components of it have been 

updated since its first release in December 2005. For the Base G inventory developed in the first 

half of 2006, all updates of the Final NONROAD2005 model through March 2006 are included. 

Key differences between Final NONROAD2005 and Draft NONROAD2004 are as follows: 

• Final NONROAD2005 reflects the latest basic emission rate and deterioration data. 

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• Final NONROAD2005 includes emission estimates for a range of evaporative emissions 

categories not included in Draft NONROAD2004 (tank and hose permeation, hot soak, 

and running loss emissions). 

• Final NONROAD2005 includes a revised diurnal emissions algorithm. 

• Final NONROAD2005 includes a revised equipment scrappage algorithm. 

• Final NONROAD2005 includes revised state and county equipment allocation data. 

• Final NONROAD2005 allows separate sulfur content inputs for marine and land-based 

diesel fuel. 

• Final NONROAD2005 includes revised conversion factors for hydrocarbon emissions. 

• Final NONROAD2005 includes the evaporative emission impacts of the large 

spark-ignition engine standards (this does not impact 2002 inventory estimates, but does 

affect future year forecasts). 

Unfortunately, due to the extensive revisions associated with Final NONROAD2005, input files 

created for use with Draft NONROAD2004 (e.g., Base F input files) and earlier versions of the 

model cannot be used directly with Final NONROAD2005 (used for Base G). This created a 

rather significant impact in that the VISTAS NONROAD modeling process involves the 

consideration of over 200 unique sets of input data. To avoid creating new input files for each of 

these datasets, a conversion process was undertaken wherein each of the Draft NONROAD2004 

(Base F) input data files were converted into the proper format required for proper execution in 

Final NONROAD2005 (Base G).1

 This process consisted of the following steps: 

• Revise the Draft NONROAD2004 (Base F) input files to include the following two line 

EPA-developed comment at the end of the input file header (this is a nonsubstantive 

change implemented solely for consistency with input files produced directly using Final 

NONROAD2005): 

9/2005 epa: Add growth & tech years to OPTIONS packet 

 and Counties & Retrofit files to RUNFILES packet. 

 

1

 The necessary conversions where developed by comparing substantively identical input files created using the 

graphical user interfaces for both Draft NONROAD2004 and Final NONROAD2005. The differences between the 

input files indicated the specific revisions necessary to convert existing VISTAS input files into Final 

NONROAD2005 format. 

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• Revise the Draft NONROAD2004 (Base F) input files to include the following two 

command lines after the “Weekday or weekend” command in the PERIOD packet: 

Year of growth calc: 

Year of tech sel : 

• Revise the Draft NONROAD2004 (Base F) input files to include the following command 

line after the “Diesel sulfur percent” command in the OPTIONS packet: 

Marine Dsl sulfur %: 0.2638 

Note that the value 0.2638 (2638 parts per million by weight [ppmW]) is applicable only 

for 2002 modeling and was accordingly revised (as described below) for both the 2009 

and 2018 Base G forecast inventories. The 2638 ppmW sulfur value for 2002 marine 

diesel fuel was taken from the 48-State (excludes Alaska and Hawaii) tabulation 

presented in the April 27, 2004 EPA document “Diesel Fuel Sulfur Inputs for the Draft 

NONROAD2004 Model used in the 2004 Non-road Diesel Engine Final Rule.” It should 

also be noted that this value differs by about 5 percent from the 2500 ppmW value 

previously used for the initial 2002 VISTAS modeling (performed by Pechan). Prior to 

Final NONROAD2005 (used for Base G), the NONROAD model allowed only a single 

diesel fuel sulfur input that was applied to both land-based and marine equipment. As 

documented in the February 9, 2004 report “Development of the VISTAS Draft 2002 

Mobile Source Emission Inventory (February 2004 Version)” as prepared by E.H. Pechan 

& Associates, Inc., a value of 2500 ppmW sulfur was used for all 2002 VISTAS 

NONROAD modeling. Given the ability of Final NONROAD2005 to distinguish a 

separate sulfur content for marine equipment and the existing EPA guidance document 

suggesting an appropriate marine sulfur value of 2638 ppmW for 2002, the existing 

modeling value of 2500 ppmW was modified (for marine equipment only). 

• Replace the Draft NONROAD2004 (Base F) input files RUNFILES packet command 

line: 

TECHNOLOGY : c:\non-road\data\tech\tech.dat 

with the command lines: 

EXH TECHNOLOGY : c:\non-road\data\tech\tech-exh.dat 

EVP TECHNOLOGY : c:\non-road\data\tech\tech-evp.dat 

• Revise the Draft NONROAD2004 (Base F) input files to include the following two 

command lines after the “EPS2 AMS” command in the RUNFILES packet: 

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US COUNTIES FIPS : c:\non-road\data\allocate\fips.dat 

RETROFIT : 

• Revise the Draft NONROAD2004 (Base F) input files to include the following command 

line after the “Rec marine outbrd” command in the ALLOC FILES packet: 

Locomotive NOx : c:\non-road\data\allocate\XX_rail.alo 

Where “XX” varies across input files. For any given file, “XX” is the two digit 

abbreviation of the state associated with the scenario being modeled (e.g., for Alabama 

modeling, XX=AL). 

• Replace the Draft NONROAD2004 (Base F) input files EMFAC FILES packet command 

line: 

Diurnal : c:\non-road\data\emsfac\diurnal.emf 

with the eight command lines: 

Diurnal : c:\non-road\data\emsfac\evdiu.emf 

TANK PERM : c:\non-road\data\emsfac\evtank.emf 

NON-RM HOSE PERM : c:\non-road\data\emsfac\evhose.emf 

RM FILL NECK PERM : c:\non-road\data\emsfac\evneck.emf 

RM SUPPLY/RETURN : c:\non-road\data\emsfac\evsupret.emf 

RM VENT PERM : c:\non-road\data\emsfac\evvent.emf 

HOT SOAKS : c:\non-road\data\emsfac\evhotsk.emf 

RUNINGLOSS : c:\non-road\data\emsfac\evrunls.emfEVP 

• Revise the Draft NONROAD2004 (Base F) input files to include the following command 

line after the “PM exhaust” command in the DETERIORATE FILES packet: 

Diurnal : c:\non-road\data\detfac\evdiu.det 

Once revised in this format, the VISTAS non-road input files developed for use with Draft 

NONROAD2004 (Base F) were executable under the Final NONROAD2005 model (Base G). 

The only additional revisions implemented to develop a Final NONROAD2005-based inventory 

(Base G) involved elimination of non-default equipment allocation files for North Carolina and 

West Virginia. Due to concerns about improper equipment allocation across counties under the 

Draft NONROAD2004 model (used for Base F), as well as for earlier versions of the 

NONROAD model, North Carolina had produced alternative allocation data files indicating the 

number of employees in air transportation by county, the number of wholesale establishments by 

county, and the number of employees in landscaping services by county. For the same reason, 

West Virginia had produced alternative equipment allocation files indicating the number of 

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employees in air transportation by county, the tonnage of underground coal production by 

county, the number of golf courses and country clubs by county, the number of wholesale 

establishments by county, the number of employees in logging operations by county, the number 

of employees in landscaping services by county, the number of employees in manufacturing 

operations by county, the number of employees in oil and gas drilling and extraction operations 

by county, and the number of recreational vehicle parks and campgrounds by county. These 

alternative equipment allocation files were used for all VISTAS inventory modeling conducted 

prior to the release of Final NONROAD2005 (i.e., through Base F). However, both North 

Carolina and West Virginia determined that the default allocation file revisions associated with 

the release of Final NONROAD2005 were appropriate to address the concerns that led to the 

development of the alternative allocation files. As a result, all alternative allocation file 

commands were removed from VISTAS NONROAD2005 (Base G) input files for North 

Carolina and West Virginia, so that the entire region under the Base G inventory is now modeled 

using the default allocation files provided with NONROAD2005. 

In addition to the alternative equipment allocation files, North Carolina had previously 

developed an alternative seasonal adjustment file that was used for the Base F inventory in place 

of the default file provided with Draft NONROAD2004 (and earlier model versions). The 

alternative data file implemented a single change, namely reclassifying North Carolina as a 

southeastern state rather than a mid-Atlantic state (as identified in the default data file). Since 

Final NONROAD2005 continues to identify North Carolina as a mid-Atlantic state, North 

Carolina requested that the southeastern reclassification be continued for all NONROAD2005 

modeling (Base G). To ensure that any other revisions associated with the seasonal adjustment 

file released with NONROAD2005 were not overlooked, the previously developed alternative 

seasonal adjustment file for North Carolina was scrapped and a new alternative file was created 

from the default seasonal adjustment file provided with Final NONROAD2005 for Base G 

inventory development. The alternative file, which was used for all North Carolina modeling, 

reclassifies North Carolina from a mid-Atlantic to a southeastern state. This represents the only 

non-default data file used for VISTAS NONROAD2005-based (Base G) modeling. 

The remainder of this section documents all changes to the originally established VISTAS input 

file values as documented in the February 9, 2004 report “Development of the VISTAS Draft 

2002 Mobile Source Emission Inventory (February 2004 Version)” as prepared by E.H. Pechan 

& Associates, Inc. Unless specifically stated below, all values from that report continue to be 

used without change in the latest VISTAS modeling. 

Base F Revisions:

For the initial 2002 base year inventory (developed by Pechan), all NONROAD modeling runs 

for VISTAS were performed utilizing a gasoline sulfur content of 339 ppmW and a diesel sulfur 

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content of 2,500 ppmW. Although the EPA-recommended non-road diesel fuel sulfur content for 

2002 is 2,283 ppmW, the 2,500 ppmW sulfur content used for the initial 2002 base year VISTAS 

inventory was designed to remove the effect of lower non-road diesel fuel sulfur limits 

applicable only in California. (The EPA recommended inputs can be found in “Diesel Fuel 

Sulfur Inputs for the Draft NONROAD2004 Model used in the 2004 Non-road Diesel Engine 

Final Rule,” EPA, April 27, 2004.) This correction is appropriate and was retained for the Base 

F 2002 inventory. Thus, the Base F inventory continued to assume a diesel fuel sulfur content of 

2,500 ppmW across the VISTAS region. 

However, 339 ppmW is not the EPA recommended 2002 gasoline sulfur content for either 

eastern conventional gasoline areas or Federal Reformulated Gasoline (RFG) areas. The 

recommended sulfur content for eastern conventional gasoline is 279 ppmW year-round, while 

the recommended sulfur content for RFG areas is 129 ppmW during the summer season and 279 

ppmW during the winter season. (Conventional gasoline and RFG sulfur contents for 2002 can 

be found in “User’s Guide to MOBILE6.1 and MOBILE6.2, Mobile Source Emission Factor 

Model,” EPA420-R-03-010, U.S. EPA, August 2003 [pages 149-155] (available at link at 

http://www.epa.gov/otaq/m6.htm) and in the source code for MOBILE6.2 at Block Data BD05.) 

Given the differences in the EPA-recommended values and the value used to generate the initial 

2002 base year inventory, the input files for Base F for all VISTAS areas were updated to reflect 

revised gasoline sulfur content assumptions. 

Since the VISTAS NONROAD modeling is performed on a seasonal basis, and since gasoline 

sulfur content in RFG areas varies with the RFG season, seasonally-specific gasoline sulfur 

content values were estimated for use in RFG area modeling. In addition, 25 counties in Georgia 

are subject to a summertime gasoline sulfur limit of 150 ppmW, so that seasonal sulfur content 

estimates were also estimated for these counties. The initial 2002 base year NONROAD 

inventory (prepared by Pechan) for these Georgia counties was based on a year-round 339 

ppmW gasoline sulfur content, but that oversight was corrected in the Base F 2002 base year 

inventory. Based on the seasonal definitions employed in the NONROAD model, monthly sulfur 

contents were averaged to estimate seasonal gasoline sulfur contents as follows: 

Month/Season RFG Areas 

Conventional 

Gasoline Areas 

Georgia Gasoline 

Control Areas 

March 279 ppmW 279 ppmW 279 ppmW 

April 279 ppmW 279 ppmW 279 ppmW 

May 129 ppmW 279 ppmW 150 ppmW 

Spring 229 ppmW 279 ppmW 236 ppmW 

June 129 ppmW 279 ppmW 150 ppmW 

July 129 ppmW 279 ppmW 150 ppmW 

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August 129 ppmW 279 ppmW 150 ppmW 

Summer 129 ppmW 279 ppmW 150 ppmW 

September 129 ppmW 279 ppmW 150 ppmW 

October 279 ppmW 279 ppmW 279 ppmW 

November 279 ppmW 279 ppmW 279 ppmW 

Fall 229 ppmW 279 ppmW 236 ppmW 

December 279 ppmW 279 ppmW 279 ppmW 

January 279 ppmW 279 ppmW 279 ppmW 

February 279 ppmW 279 ppmW 279 ppmW 

Winter 279 ppmW 279 ppmW 279 ppmW 

Note that the seasonal data are based on simple arithmetic averages and do not consider any 

monthly variation in activity (and fuel sales), and that the transition between summer and winter 

seasons is also not considered. Additionally, the summer fuel control season is treated as though 

it applies from May through September, while the summer RFG season actually ends on 

September 15 and the Georgia fuel control season does not officially begin until June 1. This 

treatment is consistent with the treatment of both fuel control programs in the VISTAS on-road 

vehicle modeling. Each of these influences will result in some error in the estimated sulfur 

content estimates, but it is expected that this error is small relative to the overall correction from 

a year-round sulfur content estimate of 339 ppmW. 

All NONROAD modeling revisions made as part of the Base F inventory preparation process are 

presented in Table 1.3-2. Due to more involved updates in several areas, the number of 

NONROAD input files as well as sequence numbers used to represent these files was also 

updated in a few instances (as compared to the files used to create the initial 2002 VISTAS nonroad inventory, as documented in the February 9, 2004 report “Development of the VISTAS Draft 

2002 Mobile Source Emission Inventory (February 2004 Version)” as prepared by E.H. Pechan 

& Associates, Inc. These structural revisions are presented in Table 1.3-3, and are provided 

solely for the benefit of NONROAD modelers as the indicated revisions have no impact on 

generated emission estimates. 

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Table 1.3-2. Summary of Base F NONROAD Modeling Revisions

State Revisions Implemented 

AL (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

FL (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

GA 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all seasons for conventional 

gasoline counties. 

(2) Gasoline sulfur content changed from 339 ppmW to 150 ppmW in the summer for all gasoline 

control counties. 

(3) Gasoline sulfur content changed from 339 ppmW to 236 ppmW in the spring and fall for all gasoline 

control counties. 

(4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control 

counties. 

Gasoline control counties: Barrow, Bartow, Butts, Carroll, Cherokee (a), Clayton (a), Cobb (a), 

Coweta (a), Dawson, De Kalb (a), Douglas (a), Fayette (a), Forsyth (a), Fulton (a), Gwinnett 

(a), Hall, Haralson, Henry (a), Jackson, Newton, Paulding (a), Pickens, Rockdale (a), Spalding, 

and Walton 

KY 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all seasons for conventional 

gasoline counties. 

(2) Gasoline sulfur content changed from 339 ppmW to 129 ppmW in the summer for all gasoline 

control counties. 

(3) Gasoline sulfur content changed from 339 ppmW to 229 ppmW in the spring and fall for all gasoline 

control counties. 

(4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control 

counties. 

Gasoline control counties: Boone, Bullitt (b), Campbell, Jefferson, Kenton, and Oldham (b) 

MS (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

NC 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

(2) Utilize revised (i.e., local) allocation files for three equipment categories. 

(3) Utilize revised (i.e., local) seasonal activity data. 

SC (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

TN 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

(2) Gasoline Reid Vapor Pressure (RVP) values changed in accordance with local recommendations. 

(3) Temperature data changed in accordance with local recommendations. 

(4) Counties regrouped in accordance with local recommendations. 

- continued -

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Table 1.3-2. Summary of Base F NONROAD Modeling Revisions (continued) 

State Revisions Implemented 

VA 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all seasons for conventional 

gasoline counties. 

(2) Gasoline sulfur content changed from 339 ppmW to 129 ppmW in the summer for all gasoline 

control counties. 

(3) Gasoline sulfur content changed from 339 ppmW to 229 ppmW in the spring and fall for all gasoline 

control counties. 

(4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control 

counties. 

(5) Gasoline RVP values changed in accordance with local recommendations. 

(6) Counties regrouped in accordance with local recommendations. 

(7) The control effectiveness for counties subject to Stage II controls revised to 77 percent in accordance 

with local recommendations. 

Gasoline control counties: Arlington Co., Fairfax Co., Loudoun Co., Prince William Co., 

Stafford Co., Alexandria City, Fairfax City, Falls Church City, Manassas City, Manassas Park 

City, Chesterfield Co., Hanover Co., Henrico Co., Colonial Heights City, Hopewell City, 

Richmond City, James City, York Co., Chesapeake City, Hampton City, Newport News City, 

Norfolk City, Poquoson City, Portsmouth City, Suffolk City, Virginia Beach City, and 

Williamsburg City (c) 

WV 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

(2) Continue to utilize local allocation files for nine equipment categories. 

Notes: 

(a) County is subject to local control currently, but is scheduled to join the RFG program in January 2005. 

(b) Control area is a portion of the county, but modeling is performed as though the control applies countywide. 

(c) The EPA also lists Charles City County as an RFG area, but local planners indicate that Charles City County is a conventional gasoline 

area and it is modeled as such. 

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Table 1.3-3. Base F NONROAD Input File Sequence and Structural Revisions

State 

Initial 2002 Base Year 

Inventory 

Input File 

Sequence Numbers 

Revised 2002 

Inventory 

Input File 

Sequence Numbers 

Reason(s) for Change 

Number of 

Revised 2002 Inventory 

NONROAD Input Files 

AL 01-08 01-08 No Structural Changes 32 (at 8 per season) 

FL 09-10 09-10 No Structural Changes 8 (at 2 per season) 

GA 11-13 11-13 No Structural Changes 12 (at 3 per season) 

KY 14-22 14-22 No Structural Changes 36 (at 9 per season) 

MS 48 48 No Structural Changes 4 (at 1 per season) 

NC 23-25 23-25 No Structural Changes 12 (at 3 per season) 

SC 26-32 26-32 No Structural Changes 28 (at 7 per season) 

TN 33-34 33-34, 49-52 Counties Regrouped 24 (at 6 per season) 

VA 35-43 35-38, 40-43 Counties Regrouped 32 (at 8 per season) 

WV 44-47 44-47 No Structural Changes 16 (at 4 per season) 

All 01-48 01-38, 40-52 204 (at 51 per season) 

Note: (1) All files include internal revisions to reflect the data changes summarized in Table 1.3-3 above. This table is intended to present 

structural revisions that are of interest in assembling the NONROAD model input files into a complete VISTAS region inventory. 

The indicated revisions do not (in and of themselves) result in emission estimate changes. 

 (2) The NONROAD model imposes an eight digit input file name limit, so all input files for the revised 2002 base year inventory 

follow a modified naming convention to allow each to be distinguished from the input files for the initial 2002 base year inventory. 

For the initial 2002 base year inventory, the naming convention was: 

ss02aaqq, where: ss = the two character State abbreviation, 

 aa = a two character season indicator as follows: AU = autumn, 

WI = winter, SP = spring, and SU = summer, and 

 qq = the two digit sequence number indicated above. 

For the revised 2002 inventory, the naming convention was modified to: 

ss02aFqq, where: ss = the two character State abbreviation, 

 a = a one character season indicator as follows: A = autumn, 

W = winter, S = spring, and X = summer, and 

 qq = the two digit sequence number indicated above. 

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Base G Revisions:

As described above, the primary modeling revision implemented for the Base G 2002 inventory 

was the use of the Final NONROAD2005 model (in place of the Base F use of Draft 

NONROAD2004). However, there were other minor revisions implemented for 13 Georgia 

counties and somewhat more significant revisions implemented for Tennessee. In Georgia, Stage 

II refueling control was assumed for 13 counties that previously were modeled as having no 

refueling control under Base F. In addition, to accommodate this Stage II change as well as 

forecast year changes in gasoline vapor pressure, corresponding changes in the structure and 

sequence of Georgia NONROAD input files were made. With the exception of the minor Stage 

II impacts, these structural and sequence changes have no impact on 2002 emission estimates, 

but allow for consistency between 2002 and forecast year input file structure and sequence. In 

Tennessee, more significant changes were implemented to gasoline vapor pressure assumptions, 

as well as similar minor changes in Stage II refueling control assumptions. 

In accordance with instructions from Georgia regulators, Stage II refueling control was assumed 

in the following 13 Georgia counties at a control efficiency value of 81 percent for the 

Base G inventory: 

Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, 

Gwinnett, Henry, Paulding, and Rockdale. 

No Stage II control was assumed in these counties in prior inventories. 

Tennessee regulators provided revised monthly values for gasoline vapor pressure. Based on the 

seasonal definitions employed in the NONROAD model, monthly vapor pressures were averaged 

to estimate seasonal vapor pressures as follows: 

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Month/Season Nashville Area Memphis Area 

Remainder of 

Tennessee 

March 13.5 psi 13.5 psi 13.5 psi 

April 13.5 psi 13.5 psi 13.5 psi 

May 9.0 psi 9.0 psi 9.0 psi 

Spring 12.0 psi 12.0 psi 12.0 psi 

June 7.8 psi 7.8 psi 9.0 psi 

July 7.8 psi 7.8 psi 9.0 psi 

August 7.8 psi 7.8 psi 9.0 psi 

Summer 7.8 psi 7.8 psi 9.0 psi 

September 1-15 7.8 psi 7.8 psi 9.0 psi 

September 16-30 11.5 psi 11.5 psi 11.5 psi 

October 13.5 psi 13.5 psi 13.5 psi 

November 13.5 psi 13.5 psi 13.5 psi 

Fall 12.2 psi 12.2 psi 12.4 psi 

December 15.0 psi 15.0 psi 15.0 psi 

January 15.0 psi 15.0 psi 15.0 psi 

February 13.5 psi 13.5 psi 13.5 psi 

Winter 14.5 psi 14.5 psi 14.5 psi 

Note: The Nashville area consists of Davidson, Rutherford, Sumner, Williamson and Wilson 

counties, the Memphis area consists of Shelby County. 

As with the Base F revisions, the seasonal data are based on simple arithmetic averages and do 

not consider any monthly variation in activity (and fuel sales), nor is the transition between 

summer and winter seasons considered. Additionally, a monthly average of the September 1-15 

and September 16-30 data is calculated prior to averaging the September-November data to 

estimate a fall average vapor pressure, so that the month of September is weighted identically to 

the months of October and November. 

Tennessee regulators also indicated that Stage II vapor recovery was not in effect in Shelby 

County, so the Base F NONROAD input files for the county (which assumed Stage II was in 

place) were revised accordingly. 

All Base G NONROAD modeling revisions are presented in Table 1.3-4. As indicated above, the 

differentiation of inputs across previously grouped counties also required revision to the overall 

number and sequence of VISTAS NONROAD input files (as compared to the files used to create 

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both the initial VISTAS non-road inventory, as documented in the February 9, 2004 report 

“Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 

Version)” as prepared by E.H. Pechan & Associates, Inc., and the Base F revised inventory as 

documented above. These structural revisions are presented in Table 1.3-5, and are provided 

solely for the benefit of NONROAD modelers as the indicated revisions have no impact on 

generated emission estimates. 

Table 1.3-4. Summary of Base G NONROAD Modeling Revisions

State Revisions Implemented 

AL (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

FL (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

GA 

(1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

(2) Stage II refueling vapor recovery implemented in 13 counties at an efficiency of 81 percent. 

(3) Counties regrouped to accommodate base and forecast year data differentiations. 

Stage II control counties: Cherokee, Clayton, Cobb, Coweta, De Kalb, Douglas, Fayette, 

Forsyth, Fulton, Gwinnett, Henry, Paulding, and Rockdale 

KY (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

MS (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

NC 

(1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

(2) Revert to default equipment allocation files for all equipment categories. 

(3) Utilize revised (i.e., local) seasonal activity data. 

SC (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

TN 

(1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

(2) Gasoline RVP values changed in accordance with local recommendations. 

(3) Stage II vapor recovery eliminated from Shelby County modeling. 

VA (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

WV (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

(2) Revert to default equipment allocation files for all equipment categories. 

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Table 1.3-5. Spring 2006 NONROAD Input File Sequence and Structural Revisions

State 

2002 Inventory 

Input File 

Sequence Numbers 

(Fall 2004) 

2002 Inventory 

Input File 

Sequence Numbers 

(Spring 2006) 

Reason(s) for Change 

Number of 

Final 2002 Inventory 

NONROAD Input Files 

AL 01-08 01-08 No Structural Changes 32 (at 8 per season) 

FL 09-10 09-10 No Structural Changes 8 (at 2 per season) 

GA 11-13 11-13, 53-54 Counties Regrouped 20 (at 5 per season) 

KY 14-22 14-22 No Structural Changes 36 (at 9 per season) 

MS 48 48 No Structural Changes 4 (at 1 per season) 

NC 23-25 23-25 No Structural Changes 12 (at 3 per season) 

SC 26-32 26-32 No Structural Changes 28 (at 7 per season) 

TN 33-34, 49-52 33-34, 49-52 No Structural Changes 24 (at 6 per season) 

VA 35-38, 40-43 35-38, 40-43 No Structural Changes 32 (at 8 per season) 

WV 44-47 44-47 No Structural Changes 16 (at 4 per season) 

All 01-38, 40-52 01-38, 40-54 212 (at 53 per season) 

Note: (1) All files include internal revisions to reflect the data changes summarized in Table 1.3-5 above. This table is intended to present 

structural revisions that are of interest in assembling the NONROAD model input files into a complete VISTAS region inventory. 

The indicated revisions do not (in and of themselves) result in emission estimate changes. 

 (2) The NONROAD model imposes an eight digit input file name limit, so all input files for the revised 2002 base year inventory 

follow a modified naming convention to allow each to be distinguished from the input files for the initial 2002 and fall 

2004-revised 2002 base year inventory. For the initial 2002 base year inventory, the naming convention was: 

ss02aaqq, where: ss = the two character State abbreviation, 

 aa = a two character season indicator as follows: AU = autumn, 

WI = winter, SP = spring, and SU = summer, and 

 qq = the two digit sequence number indicated above. 

For the fall 2004-revised 2002 inventory, the naming convention was modified to: 

ss02aFqq, where: ss = the two character State abbreviation, 

 a = a one character season indicator as follows: A = autumn, 

W = winter, S = spring, and X = summer, and 

 qq = the two digit sequence number indicated above. 

For the spring 2006-revised 2002 inventory, the naming convention was modified to: 

ss02aCqq, where: ss = the two character State abbreviation, 

 a = a one character season indicator as follows: A = autumn, 

W = winter, S = spring, and X = summer, and 

 qq = the two digit sequence number indicated above. 

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1.3.2.2 Emissions from Commercial Marine Vessels, Locomotives, and Airplanes 

An initial 2002 base year emissions inventory for aircraft, locomotives, and commercial marine 

vessels (CMV) was prepared for VISTAS in early 2004. The methods and data used to develop 

the inventory are presented in a February 9, 2004 report “Development of the VISTAS Draft 2002 

Mobile Source Emission Inventory (February 2004 Version)” as prepared by E.H. Pechan & 

Associates, Inc. A summary of the initial 2002 base year emissions inventory is presented in 

Table 1.3-6. Except as otherwise stated below, all aspects of the preparation methodology 

continue to apply to the Base F and Base G emission inventories. 

Revisions to the initial 2002 emissions inventory (prepared by Pechan) were implemented to 

ensure that the latest State and local data were incorporated as well as to correct an 

overestimation of PM emissions from aircraft. Revisions were actually implemented in two 

stages. An initial set of revisions was implemented in the fall of 2004. Those revisions constitute 

the Base F inventory. These were followed by a second set of revisions in 2006, which constitute 

the Base G inventory. To accurately document the combined effects of both sets of revisions, 

each set is discussed separately below. Unless otherwise indicated, all revisions implemented for 

Base F were carried directly into the Base G revision process without change. Thus, the 

inventories that resulted from the Base F revisions served as the starting point for the Base G 

revisions. 

Base F Revisions:

Revisions to the initial 2002 base year emissions inventory were implemented to ensure that the 

latest State and local data were incorporated as well as to correct an overestimation of PM 

emissions from aircraft. Seven of the ten VISTAS States provided revised inventory data in the 

form of emissions reported to the EPA under the CERR. States providing CERR data were 

Alabama, Georgia, Mississippi, North Carolina, Tennessee (excluding Davidson, Hamilton, 

Knox, and Shelby Counties), Virginia, and West Virginia. 

In many cases, the CERR data were only marginally different than the initial 2002 base year 

inventory data, but there were several instances where significant updates were evident. The 

remaining three VISTAS States (Florida, Kentucky, and South Carolina), plus Davidson, 

Hamilton, Knox, and Shelby counties in Tennessee, indicated that the initial 2002 VISTAS 

inventory continued to reflect the most recent data available. Florida did provide updated aircraft 

emissions data for one county (Miami-Dade) and these data were incorporated into the Base F 

2002 inventory as described below. 

Since several States recommended retaining the initial 2002 base year inventory data for Base F, 

the initial step toward revising the 2002 inventory consisted of modifying the estimated aircraft 

PM emissions of the initial inventory. The overestimation of aircraft PM became evident shortly 

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after the release of the initial 2002 base year inventory, when it was determined that VISTAS 

region airports would constitute the top seven, and 11 of the top 15, PM sources in the nation. 

Moreover, PM emissions for one airport (Miami International) were a full order of magnitude 

larger than all other modeled elemental carbon PM emission sources. In addition, unexpected 

relationships across airports were also observed, with emissions for Atlanta’s Hartsfield 

International being substantially less than those of Miami International, even though Atlanta 

handles over twice as many aircraft operations annually. Given the pervasiveness of this 

problem, and since the CERR data submitted by States was based on the initial 2002 VISTAS 

inventory data, aircraft PM emissions for the entire VISTAS region were recalculated. 

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Table 1.3-6. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine 

Emissions as Reported in February 2004 Pechan Report (annual tons)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 3,787 175 688 475 17 196 

FL 28,518 11,955 46,352 31,983 1,050 3,703 

GA 3,175 992 3,919 2,704 94 353 

KY 2,666 657 2,597 1,792 63 263 

MS 1,593 140 553 381 13 96 

NC 6,088 1,548 6,115 4,219 148 613 

SC 6,505 515 452 312 88 863 

TN 6,854 2,665 7,986 5,510 225 920 

VA 17,676 5,607 14,476 9,988 234 3,229 

WV 1,178 78 310 214 8 66 

Aircraft 

(2275) 

Total 78,040 24,332 83,448 57,578 1,940 10,302 

AL 1,195 9,217 917 843 3,337 736 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,874 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,687 43,233 1,903 1,750 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 4,129 31,397 1,390 1,278 5,753 980 

VA 1,198 3,426 929 855 3,258 596 

WV 2,094 15,882 668 614 720 497 

Commercial 

Marine 

(2280) 

Total 29,503 218,760 10,858 9,989 40,146 7,779 

Military Marine VA 136 387 28 26 30 59 

(2283) Total 136 387 28 26 30 59 

AL 3,490 26,339 592 533 1,446 1,354 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 4,530 44,793 1,110 999 2,689 1,805 

VA 1,928 19,334 1,407 1,266 3,443 798 

WV 1,105 11,150 277 249 681 436 

Locomotives 

(2285) 

Total 21,980 211,588 6,118 5,505 14,947 8,738 

Grand Total 129,659 455,067 100,452 73,099 57,062 26,877 

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Aircraft do emit PM while operating. However, official EPA inventory procedures for aircraft 

generally do not include PM emission factors and, therefore, aircraft PM is generally erroneously 

reported as zero. In an effort to overcome this deficiency, the developers of the initial VISTAS 

2002 base year aircraft inventory (Pechan) estimated PM emission rates for aircraft using 

estimated NOx emissions and an unreported PM-to-NOx ratio (i.e., PM = NOx times a 

PM-to-NOx ratio). According to the initial 2002 base year inventory documentation, this 

approach was applied only to commercial aircraft NOx, but a review of that inventory indicates 

that the technique was also applied to military, general aviation, and air taxi aircraft in many, but 

not all, instances. Although there is nothing inherently incorrect with this approach, the accuracy 

and inconsistent application of the assumed PM-to-NOx ratio results in grossly overestimated 

aircraft PM. 

Through examination of the initial 2002 base year aircraft inventory (prepared by E.H. Pechan 

and Associates, Inc.), it is apparent that the commercial aircraft PM-to-NOx ratio used to 

generate PM emission estimates was approximately equal to 3.95 (i.e., PM = NOx times 3.95). 

While the majority of observed commercial aircraft PM-to-NOx ratios in that inventory are equal 

to 3.95, a few range as low as 3.00. If all aircraft estimates are included (i.e., commercial plus 

military, general aviation, and air taxi), observed PM-to-NOx ratios range from 0 to 123.0, and 

average 3.43 as illustrated in Table 1.3-7 

Table 1.3-7 PM-to-NOx Ratios by Aircraft Type In Initial 2002 Base Year Inventory. 

Aircraft Type Average 

PM-to-NOx

Range of 

PM-to-NOx

Average 

PM2.5 / PM10

Range of 

PM2.5 / PM10

Undefined (1) 0.046 0-0.062 0.690 0.690-0.690 

Military 0.073 0-92.3 0.688 0.333-1.000 

Commercial 3.953 3.00-3.953 0.690 0.667-0.696 

General Aviation 2.059 0-9.00 0.689 0.500-1.000 

Air Taxi 2.734 0-123.0 0.690 0.500-1.000 

Aggregate 3.427 0-123.0 0.690 0.333-1.000 

Note: (1) Two counties report aircraft emissions as SCC 2275000000 “all aircraft.” 

As indicated, the aggregate PM-to-NOx ratio is similar in magnitude to the ratio for commercial 

aircraft. This results from the dominant nature of commercial aircraft NOx emissions relative to 

NOx from other aircraft types. It is surmised that ratios that deviate from 3.95 are based on PM 

emission estimates generated by local planners, which were retained without change in the PM 

estimation process (although a considerable number of unexplained “zero PM” records also exist 

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in the initial 2002 base year inventory dataset). Regardless, based on previous statistical analyses 

performed in support of aircraft emissions inventory development outside the VISTAS region, a 

PM-to-NOx ratio of 3.95 is too large by over an order of magnitude. 

In analyses performed for the Tucson, Arizona planning area, PM-to-NOx ratios for aircraft over 

a standard aircraft landing and takeoff (LTO) cycle are shown in Table 1.3-8. Data for this table 

is taken from “Emissions Inventories for the Tucson Air Planning Area, Volume I., Study 

Description and Results,” prepared for the Pima Association of Governments, Tucson, AZ, 

November 2001. Pages 4-40 through 4-42 of that report, which document the statistical 

derivation of these ratios, are included in this report as Appendix E. 

Table 1.3-8. Tucson, AZ PM-to-NOx Ratios by Aircraft Type. 

Aircraft Type PM-to-NOx

Commercial Aircraft 0.26 

Military Aircraft 0.88 

Air Taxi Aircraft 0.50 

General Aviation Aircraft 1.90 

Note: 

The PM and NOx emission estimates presented in the Tucson study are for local aircraft operating mode times. 

For this work, emission estimates for Tucson were recalculated for a standard LTO cycle, so that the ratios 

presented are applicable to the standard LTO cycle and not a Tucson-specific cycle. Thus, the ratios presented 

herein vary somewhat from those associated with the emission estimates presented in the Tucson study report. 

In reviewing these data, it should be considered that they apply to a standard (i.e., EPA-defined) 

commercial aircraft LTO cycle.2

 Aircraft PM-to-NOx ratios vary with operating mode, so that 

aircraft at airports with mode times that differ from the standard cycle will exhibit varying ratios. 

However, conducting an airport-specific analysis for all airports in the VISTAS region was 

beyond the scope of this work. While local PM-to-NOx ratios could vary somewhat from the 

indicated standard cycle ratios, any error due to this variation will be significantly less than the 

order of magnitude error associated with the 3.95 commercial aircraft ratio used for the initial 

2002 base year inventory. 

It should be recognized that while the Tucson area is far removed from the VISTAS region, the 

data analyzed to generate the PM-to-NOx ratios is standard aircraft emission factor data routinely 

 

2 As defined in AP-42, Compilation of Air Pollutant Emission Factors, Volume II, Mobile Sources, a standard 

commercial aircraft LTO cycle consists of 4 minutes of approach time, 26 minutes of taxi (7 minutes in plus 19 

minutes out), 0.7 minutes of takeoff, and 2.2 minutes of climbout time (approach and climbout times being based 

on a 3000 foot mixing height).

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employed for inventory purposes throughout the United States (as encoded in models such as the 

Federal Aviation Administration’s Emissions Data Management Systems [EDMS]). With the 

exception of aircraft operating conditions, there are no inherent geographic implications 

associated with the use of data from the Tucson study. As indicated above, issues associated with 

local operating conditions have been eliminated by recalculating the Tucson study ratios for a 

standard LTO cycle. 

To implement the revised PM-to-NOx ratios in the Base F inventory, all aircraft PM records were 

removed from the initial 2002 base year inventory (prepared by Pechan). This includes records 

for which local planners may have estimated PM emissions. This approach was taken for two 

reasons. First, there is no way to distinguish which records may have been generated by local 

planners. Second, the data available to local planners may be no better than that used to generate 

the presented PM-to-NOx ratio data, so the consistent application of these data to the entire 

VISTAS region was determined to be the most appropriate approach to generating consistent 

inventories throughout the region. In undertaking this removal, it became apparent that there was 

an imbalance in the aircraft NOx and PM records in the initial 2002 base year inventory. Whereas 

there were 1,531 NOx records in the NIF emission data sets for this source category, there were 

only 1,212 PM records. The imbalance was distributed between three States, South Carolina, 

Tennessee, and Virginia as follows: 

Table 1.3-9 Non-Corresponding Aircraft Emissions Records 

 Aircraft NOx records with no corresponding PM record:

Aircraft Type South Carolina Virginia Total 

Military Aircraft 8 100 108 

General Aviation Aircraft 14 94 108 

Air Taxi Aircraft 5 99 104 

Aggregate 27 293 320 

 Aircraft PM records with no corresponding NOx record:

Aircraft Type Tennessee Total 

Air Taxi Aircraft 1 1 

Aggregate 1 1 

The unmatched PM record was for Hamilton County (Chattanooga), Tennessee and when 

removed, was not replaced since there was no corresponding NOx record with which to estimate 

revised PM emissions. It is unclear how this orphaned record originated, but clearly there can be 

no air taxi PM emissions without other combustion-related emissions. Thus, the removal of the 

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PM10 and PM2.5 records for Hamilton County permanently reduced the overall size of the 2002 

initial base year inventory database used as a starting point for Base F by two records. 

Of the 320 unmatched NOx records, 269 were records for which the reported emission rate was 

zero. Therefore, even though associated PM records were missing, the overall inventory was not 

affected. However, the 51 missing records for which NOx emissions were non-zero, did impact 

PM estimates for the overall inventory. 

Replacement PM10 records were calculated for all aircraft NOx records using the PM-to-NOx

ratios presented above. Aircraft type-specific ratios were utilized in all cases, except for two 

counties where aircraft emissions were reported under the generic aircraft SCC 2275000000. For 

these counties (Palm Beach County, Florida and Davidson County, Tennessee), the commercial 

aircraft PM-to-NOx ratio was applied since both contain commercial airports (Palm Beach 

International and Nashville International). 

Replacement aircraft PM2.5 records were also developed. The initial 2002 base year inventory 

assumed that aircraft PM2.5 was 69 percent of aircraft PM10. The origin of this fraction is not 

clear, but it is very low for combustion related PM. The majority of internal combustion engine 

related PM is typically 1 micron or smaller (PM1.0), so that typical internal combustion engine 

PM2.5 fractions approach 100 percent. For example, the EPA NONROAD model assumes 

92 percent for gasoline engine particulate and 97 percent for diesel engine particulate. Based on 

recent correspondence from the EPA, it appears that the agency is preparing to recommend a 

PM2.5 fraction of 98 percent for aircraft. (August 12, 2004 e-mail correspondence from U.S. EPA 

to Gregory Stella of Alpine Geophysics.) This is substantially more consistent with expectations 

based on emissions test data for other internal combustion engine sources and was used as the 

basis for the recalculated aircraft PM2.5 emission estimates in the Base F inventory. 

Although a substantial portion of the initial 2002 base year inventory was ultimately replaced 

with data prepared by State and local planners under CERR requirements in developing the Base 

F inventory, it was necessary to first revise the initial 2002 base year aircraft inventory as 

described so that records extracted from the inventory for areas not supplying CERR data for the 

Base F update would be accurate. Therefore, in no case is the aggregated State data reported for 

the Base F inventory identical to that of the initial 2002 base year inventory. Even areas relying 

on the initial 2002 base year inventory will reflect updates in Base F due to changes in emissions 

of PM10 and PM2.5 from aircraft. 

Table 1.3-10 presents the updated initial 2002 base year inventory estimates. These estimates do 

not reflect any changes related to modifications made to incorporate the CERR data, but instead 

indicate the impacts associated solely with the recalculation of aircraft PM emissions alone to 

apply the more appropriate PM to NOx ratios. Table 1.3-11 presents a summary of the net 

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impacts of these changes, where an over 90 percent reduction in aircraft PM is observed for all 

VISTAS areas except South Carolina and Virginia. The reasons for the lesser changes in these 

two States is that the overall aircraft NOx inventories for both include a large share of military 

aircraft NOx to which no (or very low) particulate estimates were assigned in the initial 2002 

base year inventory. Since these operations are assigned non-zero PM emissions under the 

revised approach, the increase in military aircraft PM offsets a portion of the reduction in 

commercial aircraft PM. In Virginia, zero (or near zero) PM military operations were responsible 

for about 35 percent of total aircraft NOx, while the corresponding fraction in South Carolina was 

almost 70 percent. As indicated, aggregate aircraft, locomotive, and commercial marine vessel 

PM is 70-75 percent lower in the updated 2002 base year inventory. 

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Table 1.3-10. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine 

Emissions with Modified Aircraft PM Emission Rates (annual tons)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 3,787 175 64 62 17 196 

FL 28,518 11,955 3,193 3,129 1,050 3,703 

GA 3,175 992 269 264 94 353 

KY 2,666 657 179 175 63 263 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 6,854 2,665 707 692 225 920 

VA 17,676 5,607 2,722 2,667 234 3,229 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 78,040 24,332 8,030 7,870 1,940 10,302 

AL 1,195 9,217 917 843 3,337 736 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,874 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,687 43,233 1,903 1,750 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 4,129 31,397 1,390 1,278 5,753 980 

VA 1,198 3,426 929 855 3,258 596 

WV 2,094 15,882 668 614 720 497 

Commercial 

Marine 

(2280) 

Total 29,503 218,760 10,858 9,989 40,146 7,779 

Military Marine VA 136 387 28 26 30 59 

(2283) Total 136 387 28 26 30 59 

AL 3,490 26,339 592 533 1,446 1,354 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 4,530 44,793 1,110 999 2,689 1,805 

VA 1,928 19,334 1,407 1,266 3,443 798 

WV 1,105 11,150 277 249 681 436 

Locomotives 

(2285) 

Total 21,980 211,588 6,118 5,505 14,947 8,738 

Grand Total 129,659 455,067 25,034 23,390 57,062 26,877 

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Table 1.3-11. Change in Initial 2002 Base Year Emissions due to Aircraft PM Emission 

Rate Modifications.

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 0% 0% -91% -87% 0% 0% 

FL 0% 0% -93% -90% 0% 0% 

GA 0% 0% -93% -90% 0% 0% 

KY 0% 0% -93% -90% 0% 0% 

MS 0% 0% -92% -89% 0% 0% 

NC 0% 0% -93% -90% 0% 0% 

SC 0% 0% -9% +29% 0% 0% 

TN 0% 0% -91% -87% 0% 0% 

VA 0% 0% -81% -73% 0% 0% 

WV 0% 0% -92% -89% 0% 0% 

Aircraft 

(2275) 

Total 0% 0% -90% -86% 0% 0% 

AL 0% 0% 0% 0% 0% 0% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA 0% 0% 0% 0% 0% 0% 

WV 0% 0% 0% 0% 0% 0% 

Commercial 

Marine 

(2280) 

Total 0% 0% 0% 0% 0% 0% 

Military Marine VA 0% 0% 0% 0% 0% 0% 

(2283) Total 0% 0% 0% 0% 0% 0% 

AL 0% 0% 0% 0% 0% 0% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA 0% 0% 0% 0% 0% 0% 

WV 0% 0% 0% 0% 0% 0% 

Locomotives 

(2285) 

Total 0% 0% 0% 0% 0% 0% 

Grand Total 0% 0% -75% -68% 0% 0% 

As indicated above, for the Base F 2002 base year inventory, data for all or portions of seven 

VISTAS States were replaced with corresponding data from recent (as of the fall of 2004) CERR 

submissions for 2002. Before replacing these data, however, an analysis of the CERR data was 

performed to ensure consistency with VISTAS inventory methods. It should perhaps also be 

noted that three of the CERR datasets provided for the Base F 2002 base year inventory 

(specifically those for Tennessee, Virginia, and West Virginia) included both annual and daily 

emissions data. Only the annual data were used. Daily values were removed. 

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Several important observations resulted from this analysis. First, it was clear that all of the 

CERR data continued to rely on the inaccurate aircraft PM estimation approach employed for the 

initial 2002 base year inventory. Therefore, an identical aircraft PM replacement procedure as 

described above for updating the initial 2002 base year inventory was undertaken for CERR 

supplied data. As a result, the CERR data for all VISTAS States has been modified for inclusion 

in the Base F 2002 VISTAS base year inventory due to PM replacement procedures. 

As was the case with the initial VISTAS 2002 base year inventory, there were a substantial 

number of aircraft NOx records without corresponding PM records, so that the number of 

recalculated PM records added to the CERR dataset is greater than the number of PM records 

removed. The aggregated CERR inventory data, reflecting data for all or parts of seven States, 

consisted of 13,656 records, of which 1,211 were aircraft NOx records. However, the number of 

corresponding aircraft PM records was 662 (662 PM10 records and 662 PM2.5 records). This 

imbalance was distributed as follows: 

Table 1.3-12 CERR Aircraft NOx Records with No Corresponding PM Record. 

Aircraft Type Georgia Tennessee Virginia Total 

Military Aircraft 136 136 

Commercial Aircraft 4 136 140 

General Aviation Aircraft 1 136 137 

Air Taxi Aircraft 136 136 

Aggregate 1 4 544 549 

From this tabulation, it is clear that virtually the entire imbalance is associated with the Virginia 

CERR submission, with minor imbalances in Georgia and Tennessee. Of the 549 unmatched 

NOx records, 461 were records for which the reported emission rate was zero. Therefore, even 

though the associated PM records were missing, the overall inventory was not affected. 

However, the 88 missing records for which NOx emissions were non-zero do impact PM 

emission estimates for the overall inventory. 

Replacement aircraft PM records (both PM10 and PM2.5) were generated for the CERR dataset 

using procedures identical to those described above for the updated initial 2002 base 

year inventory. 

Further analysis revealed that the CERR data for Virginia included only VOC, CO, and NOx

emissions for all aircraft, locomotives, and non-recreational marine vessels. Since SO2, PM10, 

and PM2.5 records are included in the 2002 VISTAS inventory, an estimation method was 

developed for these emission species and applied to the Virginia CERR data. For PM, the 

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developed methodology was only employed for locomotive and marine vessel data since aircraft 

PM was estimated using the PM-to-NOx ratio methodology described above. 

Consideration was given to simply adding the Virginia SO2 and non-aircraft PM records from the 

initial 2002 VISTAS inventory dataset, but it is very unlikely that either the source distribution 

or associated emission rates are identical across the CERR and initial VISTAS inventories. This 

was confirmed through a comparative analysis of dataset CO records. Therefore, an estimation 

methodology was developed using Virginia source-specific SO2/CO, PM10/CO, and PM2.5/PM10

ratios from the initial 2002 base year VISTAS inventory. The calculated ratios were then applied 

to the source-specific CERR CO emission estimates to derive associated source-specific SO2, 

PM10, and PM2.5 emissions for the Base F inventory. 

Initially, the development of the emissions ratios from the initial 2002 base year inventory was 

performed at the State (i.e., Virginia), county, and SCC level of detail. However, it readily 

became clear that there were substantial inconsistencies in ratios for identical SCCs across 

counties. For example, in one county, the SO2/CO ratio might be 0.2, while in the next county it 

would be 2.0. Since the sources in question are virtually identical (e.g., diesel locomotives) and 

since the fueling infrastructure for these large non-road equipment sources is regional as opposed 

to local in nature, such variations in emission rates are not realistic. Therefore, a more aggregated 

approach was employed in which SCC-specific emission ratios were developed for the State as a 

whole. Through this approach county-to-county variation in emission ratios is eliminated, but the 

underlying variation in CO emissions does continue to influence the resulting aggregate emission 

estimates. The applied emission ratios are as follows: 

Table 1.3-13 Calculated Emission Ratios for VA.

Source SCC SO2/CO PM10/CO PM2.5/CO PM2.5/PM10

Military Aircraft 2275001000 0.0215 

Commercial Aircraft 2275020000 0.3292 

General Aviation Aircraft 2275050000 0.0002 

Air Taxi Aircraft 2275060000 0.0015 

Emissions estimated using 

PM-to-NOx ratios as 

described previously. 

Aircraft Refueling 2275900000 0.0000 0.0000 0.0000 

Diesel Commercial Marine 2280002000 0.3697 0.3434 0.3157 0.92 

Residual Commercial Marine 2280003000 0.3697 0.3434 0.3157 0.92 

Diesel Military Marine 2283002000 0.2422 0.2248 0.2068 0.92 

Line Haul Locomotives 2285002005 3.2757 1.2999 1.1696 0.90 

Yard Locomotives 2285002010 2.2908 1.2461 1.1205 0.90 

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It is important to recognize that the inconsistency of emissions ratios across Virginia counties for 

sources of virtually identical design, which utilize a regional rather than local fueling 

infrastructure, has potential implications for other VISTAS States. There is no immediately 

obvious reason to believe that such inconsistencies would be isolated to Virginia. 

One final revision to the CERR dataset was undertaken as part of the Base F effort, and that was 

the removal of two records for unpaved airstrip particulate (SCC 2275085000) in Alabama. 

Otherwise identical records for these emissions were reported both in terms of filterable and 

primary particulate. The filterable particulate records were removed as all other particulate 

emissions in the VISTAS inventories are in terms of primary particulate. It is also perhaps worth 

noting that a series of aircraft refueling records (SCC 2275900000) for Virginia were left in 

place, even through typically such emissions would be reported under SCC 2501080XXX in the 

area source inventory. If additional VISTAS aircraft refueling emissions are reported under SCC 

2501080XXX, then it may be desirable to recode these records. 

Finally, data for areas of the VISTAS region not represented in the CERR dataset were added to 

the CERR data by extracting the appropriate records from the initial 2002 base year inventory 

(with revisions for aircraft PM to NOx ratios). Specifically, records applicable to the States of 

Florida, Kentucky, South Carolina, and the Tennessee counties of Davidson, Hamilton, Knox, 

and Shelby were extracted from the revised initial 2002 inventory and added to the CERR 

dataset to establish the 2002 Base F inventory. 

Following this aggregation, one last dataset revision was implemented to complete the 

development of the 2002 Base F inventory. As indicated in the introduction of this section, the 

initial 2002 base year emission estimates for Miami International Airport were determined to be 

excessive. Although the reason for this inaccuracy was not apparent, revised estimates for 

aircraft emissions in Miami-Dade County were obtained from Florida planners and used to 

overwrite the erroneous estimates. (Aircraft emission estimates were provided in an August 10, 

2004 e-mail transmittal from Bruce Coward of Miami-Dade County to Martin Costello of the 

Florida Department of Environmental Protection.) 

Table 1.3-14 presents a summary of the resulting Base F VISTAS 2002 base year inventory 

estimates for aircraft, locomotives, and non-recreational marine vessels. Table 1.3-15 provides a 

comparison of the Base F 2002 base year inventory estimates to those of the initial 2002 base 

year inventory. As indicated, total emissions for VOC, CO, NOx, and SO2 are generally within 

10 percent, but final PM emissions are reduced by 70-80 percent due to the approximate 90 

percent reductions in aircraft PM estimates. In addition, the significant changes in Georgia 

aircraft emissions are due to the CERR correction of Atlanta Hartsfield International Airport 

emissions, which were significantly underestimated in the initial 2002 base year inventory. The 

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reduction in Florida aircraft emissions due to the correction of Miami International estimates is 

also apparent. 

Lastly, Table 1.3-16 provides a direct comparison of emission estimates from the initial and Base 

F 2002 base year inventories for all 16 VISTAS region airports with estimated annual aircraft 

NOx emissions of 200 tons or greater (as identified at the conclusion of the Base F revisions).3 

The table entries are sorted in order of decreasing NOx and once again, the dramatic reduction in 

PM emissions is evident. However, in addition, the appropriate reversal of the relationship 

between Atlanta’s Hartsfield and Miami International Airport is also depicted. As a rough 

method of quality assurance, Table 1.3-15 also includes a gross estimate of expected airport NOx

emissions using detailed NOx estimates developed for Tucson International Airport in 

conjunction with the ratio of local to Tucson LTOs. (The Tucson NOx estimates are revised to 

reflect a standard LTO cycle rather than the Tucson-specific LTO cycle. This should provide for 

a more realistic comparison to VISTAS estimates.) This is not meant to serve as anything other 

than a crude indicator of the propriety of the developed VISTAS estimates, and it is clear that the 

range of estimated-to-expected NOx emissions has been substantially narrowed in the Base F 

2002 base year inventory. Whereas estimated-to-expected ratios varied from about 0.2 to over 

3.5 in the initial 2002 base year inventory, the range of variation is tightened on both ends, from 

about 0.5 to 1.75 for the Base F 2002 base year inventory. In effect, all estimates are now within 

a factor of two of the expected estimates, which is quite reasonable given likely variation in local 

and standard LTO cycles and variations in aircraft fleet mix across airports. 

It is perhaps important to note that some shifting in county emissions assignments is evident 

between the initial and Base F 2002 base year aircraft inventories. For example, for the initial 

2002 base year inventory, Atlanta Hartsfield estimates were assigned to Fulton County (FIP 

13121), while they are assigned to Clayton County (FIP 13063) for the Base F 2002 base year 

inventory. Similarly, Dulles International Airport emissions were assigned solely to Fairfax 

County, Virginia (FIP 51059) in the initial 2002 base year inventory, but are split between 

Fairfax and Loudoun County (FIP 51107) for Base F. Such shifts reflect local planner 

decision-making and are not an artifact of the revisions described above. 

 

3 Subsequent revisions performed for Base G result in the addition of the Cincinnati/Northern Kentucky 

International Airport to the group of airports with aircraft operations generating at least 200 tons of NOx. These 

revisions are discussed below, including the addition of an appropriately modified version of the aircraft 

emissions table.

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Table 1.3-14. Base F 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine 

Emissions (tons/year)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 3,787 175 226 87 17 196 

FL 25,431 8,891 2,424 2,375 800 3,658 

GA 6,622 5,372 1,475 1,446 451 443 

KY 2,666 657 179 175 63 263 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 7,251 2,766 734 719 235 943 

VA 9,763 2,756 1,137 1,115 786 2,529 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 70,884 22,899 7,072 6,797 2,607 9,670 

AL 1,196 9,218 917 844 3,337 737 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,875 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,688 43,233 1,903 1,751 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 3,624 27,555 1,217 1,120 4,974 860 

VA 972 2,775 334 307 359 483 

WV 1,528 11,586 487 448 525 362 

Commercial 

Marine 

(2280) 

Total 28,207 209,972 9,911 9,118 36,275 7,413 

Military Marine VA 110 313 25 23 27 48 

(2283) Total 110 313 25 23 27 48 

AL 3,490 26,339 592 533 1,446 1,354 

FL 1,006 9,969 247 222 605 404 

GA 2,725 27,453 682 614 1,667 1,086 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 2,626 25,627 633 570 1,439 1,041 

VA 1,186 11,882 1,529 1,375 3,641 492 

WV 1,311 13,224 329 296 808 517 

Locomotives 

(2285) 

Total 19,611 187,764 5,833 5,248 14,066 7,777 

Grand Total 118,812 420,948 22,841 21,186 52,976 24,908 

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Table 1.3-15. Change in 2002 Emissions, Base F Inventory Relative to Initial Inventory

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 0% 0% -67% -82% 0% 0% 

FL -11% -26% -95% -93% -24% -1% 

GA +109% +442% -62% -47% +379% +26% 

KY 0% 0% -93% -90% 0% 0% 

MS 0% 0% -92% -89% 0% 0% 

NC 0% 0% -93% -90% 0% 0% 

SC 0% 0% -9% +29% 0% 0% 

TN +6% +4% -91% -87% +4% +2% 

VA -45% -51% -92% -89% +236% -22% 

WV 0% 0% -92% -89% 0% 0% 

Aircraft 

(2275) 

Total -9% -6% -92% -88% +34% -6% 

AL +0% +0% +0% +0% +0% +0% 

FL 0% 0% 0% 0% 0% 0% 

GA +0% +0% +0% +0% +0% +0% 

KY 0% 0% 0% 0% 0% 0% 

MS +0% +0% +0% +0% +0% +0% 

NC +0% +0% +0% +0% +0% +0% 

SC 0% 0% 0% 0% 0% 0% 

TN -12% -12% -12% -12% -14% -12% 

VA -19% -19% -64% -64% -89% -19% 

WV -27% -27% -27% -27% -27% -27% 

Commercial 

Marine 

(2280) 

Total -4% -4% -9% -9% -10% -5% 

Military Marine VA -19% -19% -12% -12% -12% -19% 

(2283) Total -19% -19% -12% -12% -12% -19% 

AL 0% 0% 0% 0% 0% 0% 

FL 0% 0% 0% 0% 0% 0% 

GA +3% +3% +3% +3% +3% +3% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN -42% -43% -43% -43% -46% -42% 

VA -38% -39% +9% +9% +6% -38% 

WV +19% +19% +19% +19% +19% +19% 

Locomotives 

(2285) 

Total -11% -11% -5% -5% -6% -11% 

Grand Total -8% -7% -77% -71% -7% -7% 

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Table 1.3-16. Base F Comparison of Aircraft Emissions 

(Airports with Aircraft NOx > 200 tons per year)

Airport FIP CO NOx PM10 PM2.5 SO2 VOC Approx. 

LTOs 

Predicted 

NOx

VISTAS

to 

Predicted 

Initial 2002 Base Year Inventory 

Miami 12086 9,757 5,997 23,706 16,357 525 1,641 150,000 1,680 3.57 

Orlando 12095 3,456 2,170 8,578 5,919 204 642 150,000 1,680 1.29 

Memphis 47157 3,462 1,934 7,645 5,275 185 603 125,000 1,400 1.38 

Reagan 51013 3,892 1,806 7,138 4,925 164 302 100,000 1,120 1.61 

Hampton 51650 2,690 1,705 0 0 0 611 Military 

Dulles 51059 2,032 1,330 5,246 3,620 0 272 75,000 840 1.58 

Orlando-Sanford 12117 3,615 1,225 4,837 3,337 100 351 

Atlanta 13121 1,457 913 3,608 2,490 86 274 420,000 4,704 0.19 

Fort Lauderdale 12011 1,930 809 3,196 2,206 75 257 75,000 840 0.96 

Charlotte 37119 1,643 788 3,113 2,148 75 255 150,000 1,680 0.47 

Tampa 12057 1,399 785 3,101 2,140 74 240 75,000 840 0.93 

Nashville 47037 1,819 653 40 28 33 239 60,000 672 0.97 

Raleigh 37183 1,584 592 2,338 1,613 56 204 75,000 840 0.70 

Louisville 21111 1,073 468 1,851 1,277 45 155 60,000 672 0.70 

Jacksonville 12031 871 325 1,284 886 31 112 30,000 336 0.97 

Palm Beach 12099 1,156 226 0 0 1 132 30,000 336 0.67 

Aggregate 41,836 21,724 75,682 52,220 1,655 6,290 0.19-3.57 

Base F 2002 Base Year Inventory 

Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 

Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 

Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 

Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 

Orlando-Sanford 12117 3,615 1,225 338 332 100 351 

Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 

Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 

Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 

Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 

Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 

Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 

Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 

Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 

Hampton 51650 858 535 471 461 18 305 Military 

Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 

Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 

Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 

Aggregate 37,829 20,550 5,838 5,721 2,312 5,793 0.47-1.75 

Net Change -10% -5% -92% -89% +40% -8% 

Note: For the Base F inventory, Dulles International Airport emissions are split between two Virginia counties. 

 Predicted NOx is based on the ratio of airport LTOs to test airport (Tucson International Airport) LTOs and NOx. This is not a rigorous 

comparison, but rather an approximate indicator of expected magnitude. 

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Base G Revisions: 

Further revisions to the 2002 base year emissions inventory were implemented in response to 

additional state data submittals in the spring of 2006. The inventories developed through the 

Base F revision process (as described above) served as the starting point for the 2006 revisions. 

Thus, unless otherwise indicated below, all documented Base F revisions continue to apply to the 

Base G-revised 2002 base year inventory. 

As part of the Base G review and update process, Virginia regulators provided 443 updated 

emission records for aircraft. These records reflected revisions to aircraft VOC, CO, and NOx, 

and in a few cases SO2, emissions records that were already in the Base F VISTAS 2002 

inventory (as opposed to the addition of previously unreported data). The specific revisions 

broke down as follows: 

Table 1.3-17 Base G VA Aircraft Records Updates 

Aircraft Type VOC CO NOx SO2 Total 

Military Aircraft 9 9 9 1 28 

Commercial Aircraft 12 12 12 17 53 

General Aviation Aircraft 65 66 66 0 197 

Air Taxi Aircraft 56 56 53 0 165 

Aggregate 142 143 140 18 443 

Emissions values for each of the 443 records in the Base F 2002 VISTAS inventory were 

updated for Base G to reflect the revised data. However, as described above for the Base F 

revisions, all aircraft SO2, PM10, and PM2.5 emissions in Virginia are estimated on the basis of 

CO (in the case of SO2) and NOx emissions (in the cases of PM10 and PM2.5). Therefore, since 

Virginia regulators did not provide updated SO2 emissions for all updated CO emissions records, 

or updated PM10 or PM2.5 emissions for all updated NOx emissions records, it was necessary to 

re-estimate aircraft SO2, PM10, and PM2.5 emissions in all cases where updated CO or NOx

emissions were provided for Base G (and explicit SO2 and/or PM10 and PM2.5 emissions 

were not). 

The procedure used to estimate the SO2, PM10, and PM2.5 emissions revisions was identical to 

that described above for the Base F inventory revisions, except that revised SO2-to-CO emissions 

ratios were calculated for commercial aircraft, where 12 pairs of revised CO and SO2 emissions 

estimates were available. Although a single pair of revised CO and SO2 emissions records was 

available for military aircraft, this was deemed an insufficient sample with which to replace the 

military aircraft SO2-to-CO emissions ratios previously calculated in Base F. However, it is 

worth noting that the SO2-to-CO emissions ratio for the revised military aircraft emissions pair 

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was within 16 percent of the previously calculated ratio, so any error associated with retention of 

the Base F ratio will be minor. Table 1.3-18 presents the emissions ratios. 

Table 1.3-18 Calculated Base G Emission Ratios for VA.

Source SCC 

SO2/CO 

(fall 2004) 

SO2/CO 

(spring 2006)

SO2/CO 

(used in 2006) PM10/NOx PM2.5/PM10

Military Aircraft 2275001000 0.0215 0.0180 0.0215 0.88 0.98 

Commercial Aircraft 2275020000 0.3292 0.0696 0.0696 0.26 0.98 

General Aviation Aircraft 2275050000 0.00016 n/a 0.00016 1.9 0.98 

Air Taxi Aircraft 2275060000 0.0015 n/a 0.0015 0.5 0.98 

Application of the SO2-to-CO emissions ratios to the 130 revised aircraft CO records, for which 

no corresponding SO2 emission revisions were provided, resulted in an additional 130 aircraft 

SO2 emission records updates for Virginia. Similarly, application of the PM10-to-NOx emissions 

ratios to the 140 revised aircraft NOx records for which no corresponding PM10 emission 

revisions were provided, resulted in an additional 140 aircraft PM10 emission records updates for 

Virginia. Application of the PM2.5-to-PM10 emissions ratios to the 140 revised aircraft PM10

records resulted in an additional 140 aircraft PM2.5 emission records updates for Virginia. Thus, 

in total, 853 (443+130+140+140) Virginia aircraft emissions records were updated for Base G. 

Also as part of the Base G review and update process, Alabama regulators provided 178 updated 

PM emission records for aircraft (89 records for PM10 and 89 records for PM2.5), 42 additional 

emissions records for locomotives (14 records for VOC, 14 records for CO, and 14 records for 

NOx), and 179 additional emission records for aircraft (30 records for VOC, 30 records for CO, 

30 records for NOx, 29 records for SO2, 30 records for PM10, and 30 records for PM2.5). After 

review, it was determined that the 178 updated PM emission records for aircraft actually 

reflected the original (overestimated) aircraft PM data that was replaced universally throughout 

the VISTAS region for Base F. Implementing these latest revisions would, in effect, “undo” the 

Base F aircraft PM revisions. Following discussions with Alabama regulators, it was determined 

that the 178 aircraft PM records would not be updated for the Base G revisions. 

The 42 additional emissions records for locomotives were determined to correspond exactly to 

existing SO2, PM10, and PM2.5 emissions records already in the Base F VISTAS 2002 inventory. 

It is not clear why these existing records contained no corresponding data for VOC, CO, and 

NOx, but those data are now reflected through the additional 42 records that have now been 

added to the Base G 2002 VISTAS inventory for Alabama. 

After examining the 179 additional aircraft emissions records in conjunction with Alabama 

regulators, it was determined that 17 of the records (commercial aircraft records in Dale, 

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Limestone, and Talladega counties) were erroneous and should be excluded from the update. The 

remaining 162 records reflected additional general aviation, air taxi, and military aircraft activity 

in 20 counties and were specifically comprised of 27 records each for VOC, CO, NOx, SO2, 

PM10, and PM2.5. There were no further issues with the VOC, CO, NOx, and SO2 records and 

these were added to the Base G 2002 VISTAS inventory without change. It was, however, 

apparent that the PM10 and PM2.5 records reflected an overestimation of aircraft PM similar to 

that which was previously corrected throughout the VISTAS region for Base F (as documented 

above). To overcome this overestimation, the additional aircraft PM10 and PM2.5 records 

provided by Alabama regulators were replaced with revised emission estimates developed on the 

basis of the PM10-to-NOx and PM2.5-to-PM10 ratios documented under the Base F revisions 

above. So although 27 aircraft PM10 records and 27 aircraft PM2.5 records were added to the 

2002 Alabama inventory, they reflected different emissions values than those provided directly 

by Alabama regulators. 

In total, 204 additional emissions records (42 for locomotives and 162 for aircraft) were added to 

the Base G 2002 Alabama inventory. 

Finally, as part of the Base G review and update process, Kentucky regulators provided 12 

updated aircraft emission records for Boone County, to correct previously underestimated 

aircraft emissions associated with the Cincinnati/Northern Kentucky International Airport. VOC, 

CO, and NOx emissions data were provided for military, commercial, general aviation, and air 

taxi aircraft. No associated updates for SO2, PM10, or PM2.5 emissions were provided. 

Corresponding PM10 emission estimates were developed by applying the PM10-to-NOx ratios 

presented in Table 1.3-17 above to the updated NOx emission estimates. PM2.5 emission 

estimates were developed by applying the PM2.5-to-PM10 ratios from that same table to the 

estimated PM10 emissions. SO2 emission estimates were developed by applying the SO2-to-PM10

ratios developed from the older data (i.e., the data being replaced) for Boone County aircraft to 

the updated PM10 emissions. Thus, a total of 24 inventory records for Kentucky were updated 

(VOC, CO, NOx, SO2, PM10, and PM2.5 for four aircraft types). 

Upon implementation of the universe of updates, 877 existing emission records were revised 

(853 in Virginia and 24 in Kentucky) and 204 additional emission records (all in Alabama) were 

added to the 2002 VISTAS inventory. The total number of aircraft, locomotive, and commercial 

marine inventory records thus changed from 22,838 records in Base F to 23,042 records in 

Base G. 

Table 1.3-19 presents a summary of the resulting Base G VISTAS 2002 base year inventory 

estimates for aircraft, locomotives, and non-recreational marine vessels. Table 1.3-20 provides a 

comparison of the Base G 2002 base year inventory estimates to those of the Base F 2002 base 

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year inventory. As indicated, total emissions for VOC, CO, NOx, and SO2 are generally within 

about 5 percent, with changes restricted to the states of Alabama, Kentucky, and Virginia. 

Lastly, Table 1.3-21 provides an updated comparison of emission estimates from the Base F and 

Base G 2002 base year inventories for all 17 VISTAS region airports with estimated annual 

aircraft NOx emissions of 200 tons or greater. As compared to Table 1.3-16, the table reflects the 

Base G addition of the Cincinnati/Northern Kentucky International Airport. Aircraft emission 

estimates for the other 16 airports are unchanged from their Base F values. 

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Table 1.3-19. Base G-Revised 2002 Base Year Aircraft, Locomotive, and Non-Recreational 

Marine Emissions (tons/year)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 5,595 185 238 99 18 276 

FL 25,431 8,891 2,424 2,375 800 3,658 

GA 6,620 5,372 1,475 1,446 451 443 

KY 5,577 925 251 246 88 397 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 7,251 2,766 734 719 235 943 

VA 11,873 3,885 2,010 1,970 272 2,825 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 77,712 24,305 8,029 7,734 2,121 10,179 

AL 1,196 9,218 917 844 3,337 737 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,875 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,688 43,233 1,903 1,751 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 3,624 27,555 1,217 1,120 4,974 860 

VA 972 2,775 334 307 359 483 

WV 1,528 11,586 487 448 525 362 

Commercial 

Marine 

(2280) 

Total 28,207 209,972 9,911 9,118 36,275 7,413 

Military Marine VA 110 313 25 23 27 48 

(2283) Total 110 313 25 23 27 48 

AL 3,518 26,623 592 533 1,446 1,365 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 2,626 25,627 633 570 1,439 1,041 

VA 1,186 11,882 1,529 1,375 3,641 492 

WV 1,311 13,224 329 296 808 517 

Locomotives 

(2285) 

Total 19,568 187,328 5,815 5,232 14,022 7,761 

Grand Total 125,597 421,918 23,780 22,107 52,444 25,401 

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Table 1.3-20. Change in 2002 Emissions, Base G Inventory 

Relative to Base F Inventory

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL +48% +6% +5% +14% +7% +41% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY +109% +41% +40% +40% +41% +51% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA +22% +41% +77% +77% -65% +12% 

WV 0% 0% 0% 0% 0% 0% 

Aircraft 

(2275) 

Total +10% +6% +14% +14% -19% +5% 

AL 0% 0% 0% 0% 0% 0% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA 0% 0% 0% 0% 0% 0% 

WV 0% 0% 0% 0% 0% 0% 

Commercial 

Marine 

(2280) 

Total 0% 0% 0% 0% 0% 0% 

Military Marine VA 0% 0% 0% 0% 0% 0% 

(2283) Total 0% 0% 0% 0% 0% 0% 

AL +1% +1% 0% 0% 0% +1% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA 0% 0% 0% 0% 0% 0% 

WV 0% 0% 0% 0% 0% 0% 

Locomotives 

(2285) 

Total +0% +0% 0% 0% 0% +0% 

Grand Total +6% +0% +4% +4% -1% +2% 

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Table 1.3-21. Base G Comparison of Aircraft Emissions 

(Airports with Aircraft NOx > 200 tons per year)

Airport FIP CO NOx PM10 PM2.5 SO2 VOC Approx. 

LTOs 

Predicted 

NOx

VISTAS

to 

Predicted 

Base F 2002 Base Year Inventory 

Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 

Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 

Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 

Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 

Orlando-Sanford 12117 3,615 1,225 338 332 100 351 

Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 

Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 

Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 

Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 

Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 

Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 

Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 

Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 

Hampton 51650 858 535 471 461 18 305 Military 

Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 

Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 

Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 

Cincinnati 21015 467 144 38 37 14 54 50,000 560 0.26 

Aggregate 38,296 20,694 5,876 5,758 2,326 5,847 0.26-1.75 

Base G 2002 Base Year Inventory 

Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 

Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 

Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 

Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 

Orlando-Sanford 12117 3,615 1,225 338 332 100 351 

Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 

Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 

Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 

Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 

Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 

Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 

Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 

Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 

Hampton 51650 858 535 471 461 18 305 Military 

Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 

Cincinnati 21015 3,378 411 110 107 39 187 50,000 560 0.73 

Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 

Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 

Aggregate 41,207 20,961 5,947 5,828 2,352 5,981 0.47-1.75 

Net Change +8% +1% +1% +1% +1% +2% 

Note: For the revised inventory, Dulles International Airport emissions are split between two Virginia counties. 

 Predicted NOx is based on the ratio of airport LTOs to test airport (Tucson International Airport) LTOs and NOx. This is not a rigorous 

comparison, but rather an approximate indicator of expected magnitude. 

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1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio 

As part of the Base G update process, VISTAS requested that emissions estimates for 2002 be 

produced for the states of Illinois, Indiana, and Ohio. These estimates were to be produced at the 

same spatial (i.e., county level by SCC) and temporal resolution as estimates for the 

VISTAS region. 

The requested estimates were produced by extracting a complete set of county-level input data 

applicable to each of the three states from the latest version of the EPA’s NMIM (National 

Mobile Inventory Model) model. This included appropriate consideration of all non-default 

NMIM input files generated by the Midwest Regional Planning Organization (MRPO), as 

described below. These input data were then assembled into appropriate input files for the Final 

NONROAD2005 model and emission estimates were produced using the same procedure 

employed for the VISTAS region as part of the Base G updates. 

A complete set of monthly input data was developed for each county in Illinois, Indiana, and 

Ohio by extracting data from the following NMIM database files (using the NMIM MySQL 

query browser): 

county, countrynrfile, countyyear, countyyearmonth, countyyearmonthhour, 

gasoline, diesel, and natural gas 

The database files: 

countrynrfile, countyyear, countyyearmonth, and gasoline 

were non-default database files provided to VISTAS by the MRPO, and are intended to reflect 

the latest planning data being used by MRPO modelers. 

From these files, monthly data for gasoline vapor pressure, gasoline oxygen content, gasoline 

sulfur content, diesel sulfur content for land-based equipment, diesel sulfur content for 

marine-based equipment, natural gas sulfur content, minimum daily temperature, maximum daily 

temperature, and average daily temperature were developed. In addition, the altitude and Stage II 

refueling control status of each county, as well as the identity of the associated equipment 

population, activity, growth, allocation, and seasonal distribution files, was determined. These 

data were then assembled into Final NONROAD2005 input files on a seasonal basis, with 

monthly data being arithmetically averaged to produce seasonal equivalents as follows: 

Winter = Average of December, January, and February 

Spring = Average of March, April, and May 

Summer = Average of June, July, and August, 

Fall = Average of September, October, and November 

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Unlike the VISTAS Base G approach, this approach results in the use of the following 

non-default data files during the Final NONROAD2005 modeling process: 

Table 1.3-22 Non-Default Files Used for MRPO Modeling 

Data File Illinois Indiana Ohio 

Activity File 1700002.act 1800002.act 3900002.act 

Growth File 17000.grw 18000.grw 39000.grw 

Population File 17000.pop 18000.pop 39000.pop 

Season File 17000.sea 18000.sea 39000.sea 

Inboard Marine 

Allocation File 17000wib.alo 18000wib.alo 39000wib.alo 

Outboard Marine 

Allocation File 17000wob.alo 18000wob.alo 39000wob.alo 

Specific Fuel 

Consumption 

MRPO-specific file provided by MRPO modelers (arbitrarily 

named “mrpoBSFC.emf” for this work) 

One compromise was made relative to the level of resolution that is available through the basic 

approach described above, that being the treatment of ambient temperature data. Because NMIM 

offers a unique temperature profile for every U.S. county -- developed by aggregating 

temperature data from included and surrounding weather stations on the basis of their distances 

from the county population centroid -- it is not possible to explicitly group counties with 

otherwise identical input streams. Ungrouped however, there would be 1,128 distinct input 

streams to be processed (102 Illinois counties plus 92 Indiana counties plus 88 Ohio counties at 

four seasons each), or over five times the number of files processed for the entire 

VISTAS region. 

To surmount this problem and allow counties with similar temperature profiles to be grouped an 

approach was employed wherein counties were considered groupable if all temperature inputs4

are within ± 2 oF of the corresponding group average. This criterion is quite stringent in that it 

results in less tolerant grouping than that employed for VISTAS modeling, which uses 

temperature data from the nearest meteorological station as opposed to "unique" meteorological 

 

4

 Non-road temperature inputs used for county grouping are: winter minimum, spring minimum, summer minimum, 

fall minimum, winter maximum, spring maximum, summer maximum, fall maximum, winter average, spring 

average, summer average, and fall average.

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data for each county. Under this approach, the actual deviation for grouped counties is much less 

that ± 2 oF for the overwhelming majority of the 12 grouped temperature inputs. 

In addition to the required temperature consistency, all other input data for counties to be 

grouped had to be identical for all four seasons. Using this criterion, Illinois emissions were 

modeled using 12 county groups, Indiana emissions were modeled using 9 county groups, and 

Ohio emissions were modeled using 10 county groups. Thus, 31 iterations of NONROAD2002 

were required per season, as compared to the 53 iterations per season required for the 

VISTAS region. 

It should be noted that a potential quality assurance issue was noted in assembling the 

NONROAD2005 input data for a number of Indiana counties. Specifically, the gasoline vapor 

pressure for most Indiana counties reflects a value of 9.0 psi in all spring, summer, fall, and 

winter months. This is likely to indicate a problem with the accuracy of the NMIM databases for 

these counties, but these data were used as defined for this work. 

1.3.3 Quality Assurance steps 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, and to ensure that a full and complete 

inventory was developed for VISTAS. Quality assurance was an important component to the 

inventory development process and MACTEC performed the following QA steps on the area 

source component of the 2002 base year revised: 

1. All CERR and NIF format State supplied data submittals were run through EPA’s 

Format and Content checking software. 

2. SCC level emission summaries were prepared and evaluated to ensure that emissions 

were consistent and that there were no missing sources. 

3. Tier comparisons (by pollutant) were developed between the revised 2002 base year 

inventory and the initial base year inventory. 

4. Data product summaries were provided to both the VISTAS Emission Inventory 

Technical Advisor and to Mobile Source SIWG representatives for review and 

comment. Changes based on these comments were implemented in the files. 

5. Version numbering was used for all inventory files developed. The version 

numbering process used a decimal system to track major and minor changes. For 

example, a major change would result in a version going from 1.0 to 2.0. A minor 

change would cause a version number to go from 1.0 to 1.1. Minor changes resulting 

from largely editorial changes would result in a change from 1.00 to 1.01. 

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2.0 Projection Inventory Development 

2.1 Point Sources 

We used different approaches for different sectors of the point source inventory: 

• For the EGUs, VISTAS relied primarily on the Integrated Planning Model® (IPM®) to 

project future generation as well as to calculate the impact of future emission control 

programs. The IPM results were adjusted based on S/L agency knowledge of planned 

emission controls at specific EGUs. 

• For non-EGUs, we used recently updated growth and control data consistent with the data 

used in EPA’s CAIR analyses, and supplemented these data with available S/L agency 

input and updated fuel use forecast data for the U.S. Department of Energy. 

For both sectors, we generated 2009 and 2018 inventories for a combined on-the-books (OTB) 

and on-the-way (OTW) control scenario. The OTB/OTW control scenario accounts for post2002 emission reductions from promulgated and proposed federal, State, local, and site-specific 

control programs as of July 1, 2004. Section 2.1.1 discusses the EGU projection inventory 

development, while Section 2.1.2 discusses the non-EGU projection inventory development. 

2.1.1 EGU Emission Projections 

The following subsections discuss the following specific aspects of the development of the EGU 

projections. First, we present a chronology of the EGU development process and discuss key 

decisions in selecting the final methods for performing the emissions projections. Next, we 

describe the development of the final set of IPM runs that are included in the VISTAS Base G 

inventory. Next, we describe the process of transforming the IPM parsed files into NIF format. 

Fourth, we discuss the process for ensuring that units accounted for in IPM were not doublecounted in the non-EGU inventory. Fifth, we describe the QA/QC checks that were made to 

ensure that the IPM results were properly incorporated into the VISTAS inventory. Sixth, we 

document the changes to the IPM results that S/L agencies specified they wanted included in the 

VISTAS inventory based on new information that was not accounted for in the IPM runs. 

Finally, we present summarize the Base G projected EGU emissions by year, state, and pollutant. 

2.1.1.1 Chronology of the Development of EGU Projections 

At the beginning of the EGU inventory development process, VISTAS considered three options 

for developing the VISTAS 2009 and 2018 projection inventories for EGUs: 

• Option 1 – Use the results of IPM modeling conducted in support of the proposed Clean 

Air Interstate Rule (CAIR) base and control case analyses as the starting point and refine 

the projections with readily available inputs from stakeholders; these IPM runs were 

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conducted for 2010 and 2015, which VISTAS would use to represent projected emissions 

in 2009 and 2018 respectively. 

• Option 2 – Use the VISTAS 2002 typical year as the starting point, apply growth factors 

from the Energy Information Administration, and refine future emission rates with 

stakeholder input regarding utilization rates, capacity, retirements, and new unit 

information. 

• Option 3 – Use the results of a new round of IPM modeling sponsored by VISTAS and 

the Midwest Regional Planning Organization (MRPO). These runs incorporated VISTAS 

specific unit and regulation modified parameters, and generate results for 2009 and 2018 

explicitly. 

An additional consideration for each of the three options was the inclusion of emission 

projections developed by the Southern Company specifically for their units. Southern Company 

is a super-regional company which owns EGUs in Alabama, Florida, Georgia, and Mississippi 

and participates in VISTAS as an industry stakeholder. Southern Company used their energy 

budget forecast to project net generation and heat input for every existing and future Southern 

Company EGU for the years 2009 and 2018. Further documentation of how Southern Company 

generated the 2009/2018 inventory for their units can be found in Developing Southern Company 

Emissions and Flue Gas Characteristics for VISTAS Regional Haze Modeling (April 2005, 

presented at 14th International Emission Inventory Conference). 

Each of these three options and the Southern Company projections were discussed in a series of 

conference calls with the VISTAS EGU Special Interest Work Group (SIWG) during the fall of 

2004. During a conference call on December 6, 2004, the VISTAS EGU SIWG approved the use 

of the latest VISTAS/MRPO sponsored IPM runs (Option 3) to represent the 2009 and 2018 

EGU forecasts of emissions for the OTB and OTW cases. During the call, Alabama and Georgia 

specified that they did not wish to use Southern Company provided emissions forecasts of 2009 

and 2018 to represent the sources in their States. Mississippi decided to utilize the Southern 

Company projections to represent activity at Southern Company facilities in Mississippi. After 

the call, Florida decided against using Southern Company provided emissions forecasts of 2009 

and 2018 to represent the sources in their State. Thus, Southern Company data was used only for 

Southern Company units in Mississippi for both the Base F and Base G projections. 

The Option 3 IPM modeling resulted from a joint agreement by VISTAS and MRPO to work 

together to develop future year utility emissions based on IPM modeling. The decision to use 

IPM modeling was based in part on a study of utility forecast methods by E.H. Pechan and 

Associates, Inc. (Pechan) for MRPO, which recommended IPM as a viable methodology (see 

Electricity Generating Unit {EGU} Growth Modeling Method Task 2 Evaluation, February 11, 

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2004). Although IPM results were available from EPA’s modeling to support their rulemaking 

for the Clean Air Interstate Rule (CAIR), VISTAS stakeholders felt that certain model inputs 

needed to be improved. Thus, VISTAS and MRPO decided to hire contractors to conduct new 

IPM modeling and to post-process the IPM results. Southern Company projections in 2009 were 

roughly comparable with IPM. For 2018, Southern Company projections were generally less 

than IPM because of assumptions made by Southern Company on which units would be 

economical to control and incorrect data in the NEEDS database which feeds IPM. 

In August 2004, VISTAS contracted with ICF International, Inc., to run IPM to provide utility 

forecasts for 2009 and 2018 under two future scenarios – Base Case and CAIR Case. The Base 

Case represents the current operation of the power system under currently known laws and 

regulations (as known at the time the run was made), including those that come into force in the 

study horizon. The CAIR Case is the Base Case with the proposed CAIR rule superimposed. The 

run results were parsed at the unit level for the 2009 and 2018 run years. Also in August 2004, 

MRPO contracted with E.H. Pechan to post-process the IPM outputs generated by ICF to provide 

model-ready emission files. The IPM output files were delivered by ICF to VISTAS in 

November (Future Year Electricity Generating Sector Emission Inventory Development Using 

the Integrated Planning Model (IPM®) in Support of Fine Particulate Mass and Visibility 

Modeling in the VISTAS and Midwest RPO Regions, January 2005), and the post-processed data 

files were delivered by Pechan to the MRPO in December 2004 (LADCO IPM Model Parsed 

File Post-Processing Methodology and File Preparation, February 8, 2005). 

On March 10, 2005, EPA issued the final Clean Air Interstate Rule. VISTAS and MRPO, in 

conjunction with other RPOs, conducted another round of IPM modeling which reflected 

changes to control assumptions based on the final CAIR as well as additional changes to model 

inputs based on S/L agency and stakeholder comments. Several conference calls were conducted 

in the spring of 2005 to discuss and provide comments on IPM assumptions related to six main 

topics: power system operation, generating resources, emission control technologies, set-up 

parameters and rule, financial assumptions, and fuel assumptions. Based on these discussions, 

VISTAS sponsored a new set of IPM runs to reflect the final CAIR requirements as well as 

certain changes to IPM assumptions that were agreed to by the VISTAS states. This set of IPM 

runs is documented in Future Year Electricity Generating Sector Emission Inventory 

Development Using the Integrated Planning Model (IPM®) in Support of Fine Particulate Mass 

and Visibility Modeling in the VISTAS and Midwest RPO Regions, April 2005 (these runs are 

referred to as the VISTAS Phase I analysis). 

Further refinements to the IPM inputs and assumptions were made by the RPOs, and ICF 

performed the following four runs using IPM during the summer of 2005 (these runs are referred 

to as the VISTAS/CENRAP Phase II analysis): 

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 Base Case with EPA 2.1.9 coal, gas and oil price assumptions. 

• Base Case with EPA 2.1.9 coal and gas supply curves adjusted for AEO 2005 reference 

case price and volume relationships. 

• Strategy Case with EPA 2.1.9 coal, gas and oil price assumptions. 

• Strategy Case with EPA 2.1.9 coal and gas supply curves adjusted for AEO 2005 

reference case price and volume relationships. 

The above runs were parsed for 2009 and 2018 run years. The above four runs were based on 

VISTAS Phase I and the EPA 2.1.9 assumptions. The changes that were implemented in the 

above four runs are summarized below: 

• Unadjusted AEO 2005 electricity demand projections were incorporated in the above 

four runs. 

• The gas supply curves were adjusted for AEO 2005 reference case price and volume 

relationships. The EPA 2.1.9 gas supply curves were scaled such that IPM will solve for 

AEO 2005 gas prices when the power sector gas demand in IPM is consistent with AEO 

2005 power sector gas demand projections. 

• The coal supply curves used in EPA 2.1.9 were scaled in such a manner that the average 

mine mouth coal prices that the IPM is solving in aggregated coal supply regions are 

comparable to AEO 2005. Due to the fact that the coal grades and supply regions 

between AEO 2005 and the EPA 2.1.9 are not directly comparable, this was an 

approximate approach and had to be performed in an iterative fashion. The coal 

transportation matrix was not updated with EIA assumptions due to significant 

differences between the EPA 2.1.9 and EIA AEO 2005 coal supply and coal demand 

region configurations. 

• The cost and performance of new units were updated to AEO 2005 reference case levels 

in all of the above four funs. 

• The run years 2008, 2009, 2012, 2015, 2018, 2020 and 2026 were modeled. 

• The AEO 2005 life extension costs for fossil and nuclear units were incorporated in the 

above runs. 

• The extensive NEEDS comments provided by VISTAS, MRPO, CENRAP and MANEVU were incorporated into the VISTAS Phase I NEEDS. 

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• MANE-VU’s comments in regards to the state regulations in the northeast were 

incorporated. 

• Renewable Portfolio Standards (RPS) in the northeast was modeled based on the 

Regional Greenhouse Gas Initiative analysis. A single RPS cap was modeled for MA, RI, 

NY, NJ, MD and CT. These states could buy credits from NY, PJM and New England 

model regions. 

• The investments required under the Illinois power, Mirant and First Energy NSR 

settlements were incorporated in the above runs. 

For the VISTAS/CENRAP Phase II set of IPM runs, ICF generated two different parsed files. 

One file includes all fuel burning units (fossil, biomass, landfill gas) as well as non-fuel burning 

units (hydro, wind, etc.). The second file contains just the fossil-fuel burning units (e.g., 

emissions from biomass and landfill gas are omitted). The RPOs decided to use the fossil-only 

file for modeling to be consistent with EPA, since EPA used the fossil only results for CAIR 

analyses. For the 10 VISTAS states, non-fossil fuels accounted for only 0.13 percent of the NOx 

emissions and 0.04 percent of the SO2 emissions in the 2009 IPM runs. 

S/L agencies reviewed the results of the VISTAS/CENRAP Phase II set of IPM runs, which were 

incorporated into the VISTAS Base F inventory. S/L agencies primarily reviewed and 

commented on the IPM results with respect to IPM decisions on NOx post-combustion controls 

and SO2 scrubbers. S/L agencies provided the latest information on when and where new SO2

and NOx controls are planned to come online. S/L agencies also reviewed the IPM results to 

verify that existing controls and emission rates were properly reflected in the IPM runs. As 

directed by the S/L agencies, adjustments to the IPM results were made to specific units with any 

new information they had as part of the permitting process or other contact with the industry that 

indicates which units will install controls as a result of CAIR and when these new controls will 

come on-line. Mississippi decided to continue to use the Southern Company projections instead 

of the IPM projections to represent emissions at Southern Company facilities in Mississippi. The 

state-specified changes to the VISTAS/CENRAP Phase II set of IPM runs were used to create 

the Base G projection inventory (and are documented later in Section 2.1.1.6). 

2.1.1.2 VISTAS IPM runs for EGU sources 

The following general summary of the VISTAS IPM® modeling is based on ICF’s 

documentation Future Year Electricity Generating Sector Emission Inventory Development 

Using the IPM® in Support of Fine Particulate Mass and Visibility Modeling in the VISTAS and 

Midwest RPO Regions, April 2005. The ICF documentation is to be used as an extension to 

EPA's proposed CAIR modeling runs documented in Documentation Supplement for EPA 

Modeling Applications (V.2.1.6) Using the IPM, EPA 430/R-03-007, July 2003. 

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IPM provides “forecasts of least-cost capacity expansion, electricity dispatch, and emission 

control strategies for meeting energy demand and environmental, transmission, dispatch, and 

reliability constraints.” The underlying database in this modeling is U.S. EPA’s National 

Electric Energy Data System (NEEDS) released with the CAIR Notice of Data Availability 

(NODA). The NEEDS database contains the existing and planned/committed unit data in EPA 

modeling applications of IPM. NEEDS includes basic geographic, operating, air emissions, and 

other data on these generating units. VISTAS States and stakeholders provided changes for: 

• NOx post-combustion control on existing units 

• SO2 scrubbers on existing units 

• SO2 emission limitations 

• PM controls on existing units 

• Summer net dependable capacity 

• Heat rate for existing units 

• SO2 and NOx control plans based on State rules or enforcement settlements 

The years 2009 and 2018 were explicitly modeled. 

2.1.1.3 Post-Processing of IPM Parsed Files 

The following summary of the VISTAS/Midwest Regional Planning Organization (MRPO) IPM 

modeling is based on Pechan’s documentation LADCO IPM Model Parsed File Post-Processing 

Methodology and File Preparation, February 8, 2005. The essence of the IPM model postprocessing methodology is to take an initial IPM model output file and transform it into air 

quality model input files. ICF via VISTAS/MRPO provides an initial spreadsheet file containing 

unit-level records of both 

(1) “existing” units and 

(2) committed or new generic aggregates. 

All records have unit and fuel type data; existing, retrofit (for SO2 and NOx), and separate NOx

control information; annual SO2 and NOx emissions and heat input; summer season (MaySeptember) NOx and heat input; July day NOx and heat input; coal heat input by coal type; 

nameplate capacity megawatt (MW), and State FIPS code. Existing units also have county FIPS 

code, a unique plant identifier (ORISPL) and unit ID (also called boiler ID) (BLRID); generic 

units do not have these data. The processing includes estimating various types of emissions and 

adding in control efficiencies, stack parameters, latitude-longitude coordinates, and State 

identifiers (plant ID, point ID, stack ID, process ID). Additionally, the generic units are sited in a 

county and given appropriate IDs. This processing is described in more detail below. 

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The data are prepared by transforming the generic aggregates into units similar to the existing 

units in terms of the available data. The generic aggregates are split into smaller generic units 

based on their unit types and capacity, are provided a dummy ORIS unique plant and boiler ID, 

and are given a county FIPS code based on an algorithm that sites each generic by assigning a 

sister plant that is in a county based on its attainment/nonattainment status. Within a State, plants 

(in county then ORIS plant code order) in attainment counties are used first as sister sites to 

generic units, followed by plants in PM nonattainment counties, followed by plants in 8-hour 

ozone nonattainment counties. Note that no LADCO or VISTAS States provided blackout 

counties that would not be considered when siting generics, so this process is identical to the one 

used for EPA IPM post-processing. 

SCCs were assigned for all units; unit/fuel/firing/bottom type data were used for existing units’ 

assignments, while only unit and fuel type were used for generic units’ assignments. Latitudelongitude coordinates were assigned, first using the EPA-provided data files, secondly using the 

September 17, 2004 Pechan in-house latitude-longitude file, and lastly using county centroids. 

These data were only used when the data were not provided in the 2002 NIF files. Stack 

parameters were attached, first using the EPA-provided data files, secondly using a March 9, 

2004 Pechan in-house stack parameter file based on previous EIA-767 data, and lastly using an 

EPA June 2003 SCC-based default stack parameter file. These data were only used when the 

data were not provided in the 2002 NIF files. 

Additional data were required for estimating VOC, CO, filterable primary PM10 and PM2.5, PM 

condensable, and NH3 emissions for all units. Thus, ash and sulfur contents were assigned by 

first using 2002 EIA-767 values for existing units or SCC-based defaults; filterable PM10 and 

PM2.5 efficiencies were obtained from the 2002 EGU NEI that were based on 2002 EIA-767 

control data and the PM Calculator program (a default of 99.2 percent is used for coal units if 

necessary); fuel use was back calculated from the given heat input and a default SCC-based heat 

content; and emission factors were obtained from an EPA-approved October 7, 2004 Pechan 

emission factor file based on AP-42 emission factors. Note that this updated file is not the one 

used for estimating emissions for previous EPA post-processed IPM files. Emissions for 28 

temporal-pollutant combinations were estimated since there are seven pollutants (VOC, CO, 

primary PM10 and PM2.5, NH3, SO2 and NOx) and four temporal periods (annual, summer season, 

winter season, July day). 

The next step was to match the IPM unit IDs with the identifiers in VISTAS 2002 inventory. A 

crosswalk file was used to obtain FIPS State and county, plant ID (within State and county), and 

point ID. If the FIPS State and county, plant ID and point ID are in the 2002 VISTAS NIF tables, 

then the process ID and stack ID are obtained from the NIF; otherwise, defaults, described 

above, were used. 

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Pechan provided the post-processed files in NIF 3.0 format. Two sets of tables were developed : 

“NIF files” for IPM units that have a crosswalk match and are in the 2002 VISTAS inventory, 

and “NoNIF files” for IPM units that are not in the 2002 VISTAS inventory (which includes 

existing units with or without a crosswalk match as well as generic units). 

For Base F and Base G projections, VISTAS reviewed the PM and NH3 emissions from EGUs as 

provided by Pechan and identified significantly higher emissions in 2009/2018 than in 2002. 

VISTAS determined that Pechan used a set of PM and NH3 emission factors that are “the most 

recent EPA approved uncontrolled emission factors” for estimating 2009/2018 emissions. These 

factors are most likely not the same emission factors used by States for estimating these 

emissions in 2002 for EGUs in the VISTAS domain. Thus, the emission increase from 2002 to 

2009/2018 was simply an artifact of the change in emission factor, not anything to do with 

changes in activity or control technology application. Also, VISTAS identified an inconsistent 

use of SCCs for determining emission factors between the base and future years. 

VISTAS resolution of the PM and NH3 problem is fully documented in EGU Emission Factors 

and Emission Factor Assignment, memorandum from Greg Stella to VISTAS State Point Source 

Contacts and VISTAS EGU Special Interest Workgroup, June 13, 2005. The first step was the 

adjustment of the 2002 base year emissions inventory. Using the latest “EPA-approved” 

uncontrolled emission factors by SCC, Alpine Geophysics utilized CERR or VISTAS reported 

annual heat input, fuel throughput, heat, ash and sulfur content to estimate annual uncontrolled 

emissions for units identified as output by IPM. This step was conducted for non-CEM pollutants 

(CO, VOC, PM, and NH3) only. For PM emissions, the condensable component of emissions 

was calculated and added to the resulting PM primary estimations. The resulting emissions were 

then adjusted by any control efficiency factors reported in the CERR or VISTAS data collection 

effort. The second adjustment was to the future year inventories. Alpine Geophysics updated the 

SCCs in the future year inventory to assign the same base year SCC. Using the same methods as 

described for the 2002 revisions, those non-IPM generated pollutants were estimated using IPM 

predicted fuel characteristics and base year 2002 SCC assignments. 

2.1.1.4 Eliminating Double Counting of EGU Units 

The following procedures were used to avoid double counting of EGU emissions in the 

2009/2018 point source inventory. The 2002 VISTAS point source emission inventory contains 

both EGUs and non-EGUs. Since this file contains both EGUs and non-EGU point sources, and 

EGU emissions are projected using the IPM, it was necessary to split the 2002 point source file 

into two components. The first component contains those emission units accounted for in the 

IPM forecasts. The second component contains all other point sources not accounted for in IPM. 

As described in the previous section, Pechan developed 2009/2018 NIF files for EGUs from the 

IPM parsed files. All IPM matched units were initially removed from the 2009/2018 point source 

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inventory to create the non-EGU inventory (which was projected to 2009/2018 using the nonEGU growth and control factors described in Section 2.1.2). This was done on a unit-by-unit 

basis based on a cross-reference table that matches IPM emission unit identifiers (ORISPL plant 

code and BLRID emission unit code) to VISTAS NIF emission unit identifiers (FIPSST state 

code, FIPSCNTY county code, State Plant ID, State Point ID). When there was a match between 

the IPM ORISPL/BLRID and the VISTAS emission unit ID, the unit was assigned to the EGU 

inventory; all other emission units were assigned to the non-EGU inventory. 

If an emission unit was contained in the NIF files created by Pechan from the IPM output, the 

corresponding unit was removed from the initial 2009/2018 point source inventory. The NIF 

2009/2018 EGU files from the IPM parsed files were then merged with the non-EGU 2009/2018 

files to create the 2009/2018 Base F point source files. 

Next, we prepared several ad-hoc QA/QC queries to verify that there was no double-counting of 

emissions in the EGU and non-EGU inventories: 

• We reviewed the IPM parsed files {VISTASII_PC_1f_AllUnits_2009 (To Client).xls and 

VISTASII_PC_1f_AllUnits_2018 (To Client).xls} to identify EGUs accounted for in 

IPM. We compared this list of emission units to the non-EGU inventory derived from the 

VISTAS cross-reference table to verify that units accounted for in IPM were not doublecounted in the non-EGU inventory. As a result of this comparison, we made a few 

adjustments in the cross-reference table to add emission units for four plants to ensure 

these units accounted for in IPM were moved to the EGU inventory. 

• We reviewed the non-EGU inventory to identify remaining emission units with an 

Standard Industrial Classification (SIC) code of “4911 Electrical Services” or Source 

Classification Code of “1-01-xxx-xx External Combustion Boiler, Electric Generation”. 

We compared the list of sources meeting these selection criteria to the IPM parsed file to 

ensure that these units were not double-counted. 

S/L agencies also reviewed the 2009/2018 point source inventory to verify whether there was 

any double counting of EGU emissions. In two instances, S/L agencies provided corrections 

where an emission unit was double counted. 

2.1.1.5 Quality Assurance steps 

Quality assurance was an important component to the inventory development process and 

MACTEC performed the following QA steps on the EGU component of the VISTAS revised 

2009/2018 EGU inventory: 

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1. Provided parsed files (i.e., Excel spreadsheets that provide unit-level results derived from 

the model plant projections obtained by the IPM) to the VISTAS EGU SIWG for review 

and comment. 

2. Provided facility level emission summaries for 2009/2018 for both the base case and 

CAIR case to the VISTAS EGU SIWG to ensure that emissions were consistent and that 

there were no missing sources. 

3. Compared, at the State-level, emissions from the IPM parsed files and the post-processed 

NIF files to verify that the post-processed NIF files were consistent with the IPM parsed 

file results. 

VISTAS requested S/L review of these files – the changes specified by states as a result of this 

review are documented in the following subsection. 

2.1.1.6 S/L Adjustments to IPM Modeling Results for Base G Projections 

After S/L agency review of the final set of IPM runs (as incorporated into the Base F inventory), 

S/L agencies specified a number of changes to the IPM results to better reflect current 

information on when and where future controls would occur. These changes to the IPM results 

primarily involved S/L agency addition or subtraction future emission controls based on the best 

available data from state rules, enforcement agreements, compliance plans, permits, and 

discussions/commitments from individual companies. 

For example, Dominion Virginia Power released their company-wide plan to reduce emission to 

meet the requirements of CAIR and other programs. This plan varies substantially from the IPM 

results both in terms current and future controls and timing of these controls. As a result, VA 

DEQ developed their best estimates of future controls on EGUs in Virginia. Also, Duke Energy 

and Progress Energy have updated their plans for complying with North Carolina’s Clean 

Smokestack Act. These plans vary substantially from the IPM results both in terms current and 

future controls and timing of these controls. As a result, NC DENR replaced the IPM emission 

projections for 2009 with projections from the Duke Energy and Progress Energy compliance 

plan. NC DENR elected to use the IPM results for 2018. 

Some S/L agencies specified changes to the controls assigned by IPM to reflect their best 

estimates of emission controls. The changes specified by the S/L agencies are summarized in 

Table 2.1-1. These changes involved either 1) adding selective catalytic reduction (SCR) or 

scrubber controls to units where IPM did not predict SCR or scrubber controls, or 2) removing 

IPM-assigned SCR or scrubber controls at units where the S/L agency indicated their were no 

firm plans for controls at those units. We used a scrubber control efficiency of 90 percent when 

adding or removing SO2 scrubber controls. We used a control efficiency of 90 percent when 

adding or removing NOx SCR controls at coal-fired plants, 80 percent when adding or removing 

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NOx SCR controls at gas-fired plants, and 35 percent when adding or removing NOx

SNCR controls. 

In addition to the changes to the IPM-assigned controls, the S/L agencies also specified other 

types of changes to the IPM results. These other specific changes to the IPM results are 

summarized in Table 2.1-2. 

S/L agencies provided information and/or comment on changes in stack parameters from the 

2002 inventory for 2009/2018 inventory. Changes to stack parameters were also made in cases 

where new controls are scheduled to be installed. In cases where an emission unit projected to 

have a SO2 scrubber in either 2009 or 2018, some states were able to provide revised stack 

parameters for some units based on design features for the new control system. Other units 

projected to install scrubbers by 2009 or 2018 are not far enough along in the design process to 

have specific design details. For those units, the VISTAS EGU SIWG made the following 

assumptions: 1) the scrubber is a wet scrubber; 2) keep the current stack height the same; 3) keep 

the current flow rate the same, and 4) change the stack exit temperature to 169 degrees F (this is 

the virtual temperature derived from a wet temperature of 130 degrees F). VISTAS determined 

that exit temperature (wet) of 130 degrees F +/- 5 degrees F is representative of different size 

units and wet scrubber technology. 

2.1.1.7 Summary of Base F and Base G 2009/2018 EGU Point Source Inventories 

Tables 2.1-3 through 2.1-9 compare the Base G 2002 base year inventory to the Base F4 and 

Base G 2009/2018 projection inventories. The Base F4 projections rely primarily on the results 

of the IPM, while the Base G projections include the adjustments to the IPM results specified by 

the S/L agencies in the previous section. 

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Table 2.1-1 Adjustments to IPM Control Determinations Specified by S/L Agencies for the Base G 2009/20

NOx Emission Controls SO2 Emission Con

State Plant Name and ID Unit 2009 2018 2009 

IPM State IPM State IPM State IP

AL James H. Miller 

ORISID=6002 

1 & 2 SCR 

during ozone season 

SCR probable year round due to CAIR 

SCR during ozone season 

SCR probable year round due to CAIR 

None None None 

 3 & 4 SCR 

during ozone season 

SCR year round from Consent Decree 

SCR during ozone season 

SCR year round from Consent Decree 

None None None 

 Barry 1, 2, 3 None SNCR SCR SNCR None None None  ORISID=3 4 None SNCR SCR SNCR None None Scrub 5 None None SCR SCR None None Scrub E C Gaston 1 - 4 SCR None SCR None None None Scrub ORISID=26 5 SCR SCR SCR SCR Scrubber None Scrub Gorgas 6 & 7 None None None None None None None  ORISID=8 8 & 9 None None None None None Scrubber None  10 SCR SCR SCR SCR None Scrubber Scrub Charles R. Lowman 1 None None None None None Scrubber None  ORISID=56 2 & 3 SCR SCR SCR SCR Scrubber Scrubber Scrub

GA Bowen 1BLR SCR SCR SCR SCR None Scrub

 ORISID=703 2BLR SCR SCR SCR SCR None Scrub 3BLR SCR SCR SCR SCR Scrubber Scrub 4BLR SCR SCR SCR SCR 

IPM had retrofit scrubbers but little emission reductions 

Scrubber Scrub

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Table 2.1-1 (continued) 

NOx Emission Controls SO2 Emission Con

State Plant Name and ID Unit 2009 2018 2009 

IPM State IPM State IPM State IP

GA Wansley 1 SCR SCR SCR SCR Scrubber Scrub

 ORISID=6052 2 SCR SCR SCR SCR 

IPM had retrofit scrubbers but little emission reductions 

None Scrub

 Kraft 1, 2 None None None None None None None  ORISID=733 3 None None SCR None None None None  McIntosh 

ORISID=6124 

1 None None SCR None None None None 

 Yates 1 None None None None Scrubber Scrubber Scrub ORISID=728 2, 3 None None None None None None None  4 – 7 None None SCR SCR None None Scrub Hammond 1 None None SCR SCR None Scrubber Scrub ORISID=708 2 None None SCR SCR None Scrubber Scrub 3 None None SCR SCR None Scrubber Scrub 4 SCR SCR SCR SCR Scrubber Scrubber Scrub

KY Ghent 1 None SCR SCR SCR Scrubber Scrubber Scrub

 ORISID=1356 2 None None SCR SCR None Scrubber Scrub 3, 4 None SCR SCR SCR None Scrubber Scrub Coleman C1 None None SCR SCR None Scrubber Scrub ORISID=1381 C2 None None SCR SCR None Scrubber Scrub C3 None None SCR SCR None Scrubber Scrub HMP&L Station 2 H1 SCR SCR SCR SCR Scrubber Scrubber Scrub H2 None SCR SCR SCR Scrubber Scrubber Scrub

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Table 2.1-1 (continued) 

NOx Emission Controls SO2 Emission Con

State Plant Name and ID Unit 2009 2018 2009 

IPM State IPM State IPM State IP

KY E W Brown 1 None None None None None Scrubber None 

 ORISID=1355 2 None None SCR SCR None Scrubber Scrub 3 None None SCR SCR None Scrubber Scrub

SC Jeffries 3 SCR None SCR None None None None 

 ORISID=3319 4 None None None None None None None  Wateree WAT1 SCR SCR SCR SCR None Scrubber None  ORISID=3297 WAT2 SCR SCR SCR SCR None Scrubber Scrub Canadys CAN1 None None None None None None None  ORISID=3280 CAN2 None None None None None None None  CAN3 None None None None None Scrubber None  Rainey CT1A None SCR None SCR None None None  ORISID=7834 CT1B None SCR None SCR None None None 

TN Kingston 1 – 8 SCR SCR SCR SCR None None Scrub

 ORISID=3407 9 None SCR SCR SCR None None Scrub Johnsonville 1 – 10 SCR None SCR SCR None None None  ORISID=3406 

WV Willow Island 2 SCR None SCR SCR Scrubber None Scrub

 ORISID=3946  Kammer 1 -3 SCR None SCR SCR Scrubber None Scrub ORISID=3947 

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Table 2.1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 

2009/2018 EGU Inventories. 

State Plant Name and ID Unit Nature of Update/Correction 

FL Central Power and Lime 

ORISID= 10333 

GEN1 Central Power and Lime (ORIS10333) is a duplicate entry. 

This is point 18 in Florida Crushed Stone (12-053-0530021). 

Removed IPM emissions for Central Power and Lime. 

 Cedar Bay Generating 

ORISID=10672 

GEN1 FLDEP disagrees with IPM projections - no knowledge of 

expansion of this facility and the cogeneration facility 

should not grow faster than the underlying industry. Cedar 

Bay is connected to Stone Container (12-031-0310067). 

Replaced IPM emissions with 2002 emissions for Cedar Bay 

(12-031-0310337) times the growth factors for Stone 

Container. 

 Indiantown Cogeneration 

ORISID=50976 

GEN1 FLDEP disagrees with IPM projections - no knowledge of 

expansion of this facility and the cogeneration facility 

should not grow faster than the underlying industry. 

Indiantown is connected to Louis Dreyfus Citrus (12-085-

0850002). Replaced IPM emissions with 2002 emissions for 

Indiantown (12-085-0850102) times the growth factors for 

Louis Drefus Citrus. 

GA Bowen 

ORISID=703 

1BLR 

2BLR 

3BLR 

4BLR 

IPM indicated retrofit scrubbers on all 4 units in 2009, but 

the IPM emissions showed little reductions from 2002 

levels. Changed emissions to reflect scrubbers on 3BLR and 

4BLR by 2009. 

 Wansley 

ORISID=6052 

1, 2 IPM indicated retrofit scrubbers on both units in 2009, but 

the IPM emissions showed little reductions from 2002 

levels. Changed emissions to reflect one scrubber on Unit 1 

by 2009. 

 Riverside 

ORISID=734 

4 All of plant Riverside was retired from service June 1, 2005; 

emissions set to zero in 2009 and 2018. 

 McIntosh 

ORISID=727 

CT10A 

CT10B 

CT11A 

CT11B 

The McIntosh Combined Cycle facility became commercial 

June 1, 2005. Added 346 tons of NOx and 121 tons of SO2

per unit to the 2009 and 2018 inventories. 

 Longleaf Energy Station 1, 2 Longleaf Energy Station is being proposed by LS Power 

Development, Inc. GA specified that the emissions from this 

proposed plant be included in the 2018 projections. Boilers 1 

and 2 added 1,882 tons of NOx and 3,227 tons of SO2 per 

unit to the 2018 inventory. 

 Duke Murray (55382) 1 Corrected coordinates to 34.7189 and -84.9353 

MS R D Morrow 

ORISID=6061 

1, 2 Revised the 2018 emissions to reflect controls not indicated 

by IPM. The SO2 emissions are much lower than IPM, but 

their expected NOx emissions are actually higher than IPM. 

The controls will be coming online 2009 or 2010, so the 

2009 inventory did not change. 

 Jack Watson (2049) 

Victor J Daniel (6073) 

Chevron Oil (2047) 

All MS DEQ specified that the emission projections provided by 

the Southern Company for their units in Mississippi were to 

be used instead of the IPM results. 

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Table 2.1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

NC G G Allen (2718) 

Belews Creek (8042)1 

Buck (2720) 

Cliffside (2721) 

Dan River (2723) 

Marshall (2727) 

Riverbend (2732) 

All Replaced all IPM 2009 results with emission projections 

from Duke Power’s NC Clean Air Compliance Plan for 

2006. Used IPM results for 2018 

 Asheville (2706) 

Cape Fear (2708) 

Lee (2709) 

Mayo (6250) 

Roxboro (2712) 

Sutton (2713) 

Weatherspoon (2716) 

All Replaced all IPM 2009 results with emission projections 

from Progress Energy’s NC Clean Smokestacks Act 

Calendar Year 2005 Progress Report. Used IPM results for 

2018 

 Dwayne Collier Battle 

Cogeneration Facility 

ORISID=10384 

GEN1 

GEN2 

Dwayne Collier Battle is a duplicate entry. This is Cogentrix 

of Rocky Mount (37-065-3706500146, stacks G-26 and G27). Duplicate entries were removed both the 2009 and 2018 

inventories. 

 Kannapolis Energy 

Partners 

ORISID=10626 

GEN2 

GEN3 

Kannapolis Energy emissions are being used as credits for 

another facility. IPM emissions from this facility (37-025-

ORIS10626) were removed from the EGU inventory for 

2009 and 2018. Emissions from Kannapolis Energy (37-025-

3702500113) were carried forward in the 2009/2018 

inventory. 

SC Cross 

ORISID=130 

1, 2 Unit 1: upgrade scrubber from 82 percent to 95 percent 

removal efficiency by June 30, 2006. Recalculate emissions 

based on upgrade in control efficiency. 

Unit 2: upgrade scrubber from 70 percent to 87 percent 

removal efficiency by June 30, 2006. Recalculate emissions 

based on upgrade in control efficiency. 

 Winyah 

ORISID=6249 

1 – 4 Unit 1: Install scrubber that meets 95 percent removal 

efficiency by Dec. 31, 2008; Upgrade ESP from 0.38 to 0.03 

lb/mmBTU by Dec. 31, 2008 

Unit 2: Replace scrubber with one that meets 95 percent 

removal efficiency from 45 percent by Dec. 31, 2008; 

Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 

2008 

Unit 3: Upgrade scrubber from 70 percent to 90 percent 

removal efficiency by Dec. 31, 2012; Upgrade ESP from 

0.10 to 0.03 lb/mmBTU by Dec. 31, 2012 

Unit 4: Upgrade scrubber from 70 percent to 90 percent 

removal efficiency by Dec. 31, 2007; Upgrade ESP from 

0.10 to 0.03 lb/mmBTU by Dec. 31, 2007 

Recalculated SO2 and PM emissions based on upgrade in 

control efficiencies. 

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Table 2.1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

SC Dolphus Grainger 

ORISID=3317 

1, 2 Unit 1: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 95 

percent based on change in allowable emission rate 

Unit 2: Install low NOx burners that meet 0.46 lb/mmBTU 

from 0.9 by May 1, 2004. Recalculated NOx emissions using 

0.46/lbs/mmBtu and IPM heat input 

Unit 2: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 95 

percent based on change in allowable emission rate 

SC Jeffries 

ORISID=3319 

3, 4 Unit 3: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 

94.44 percent based on change in allowable emission rate 

Unit 4: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 

94.44 percent based on change in allowable emission rate 

 W S Lee 

ORISID=3264 

1, 2 IPM does not indicate that these units are installing SOFA 

NOx control technology by April 30, 2006 to meet 0.27 

lb/mmBTU, down from 0.45 lb/mmBtu. Calculated NOx

emissions using IPM heat input and 0.27 lbs/mmBtu 

 Generic Unit 

ORISID=900545 

All All predictions for generic units appear reasonable with the 

exception of Plant ID ORIS900545 Point ID GSC45 which 

was modeled in Georgetown County. It will be very difficult 

to add new generation this close to the Cape Romain Class I 

area. Santee Cooper has no plans for future generation in 

Georgetown County, but does have plans for new future 

generation in Florence County. This unit was moved to 

coordinates specified in Florence County. 

VA AEP Clinch River 

ORISID=3775 

1, 2, 3 Used IPM results for 2009; replaced all 2018 IPM results 

with VADEQ’s growth and control estimates (no SCR or 

scrubbers). 

 AEP Glen Lyn 

ORISID=3776 

51, 52, 

6 

Used 2009/2018 IPM results for units 51 and 52; used 2009 

IPM for unit 6; replaced 2018 IPM for unit 6 with VADEQ’s 

growth and control estimates (nor SCR or scrubber). 

 Dominion Clover 

ORISID=7213 

1, 2 Used 2009/2018 IPM results. 

 Dominion Bremo 

ORISID=3796 

3, 4 Used 2009/2018 IPM results. 

 Dominion Chesterfield 

ORISID=3797 

3, 4, 

5, 6 

Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

 Dominion Yorktown 

ORISID=3809 

1, 2, 3 Units 1, 2: Used 2009/2018 IPM results for NOx and used 

VADEQ’s growth and control estimates for SO2. 

Unit 3: IPM predicts zero heat input for this 880 MW #6 oil 

fired unit. Dominion plans to continue to operate Unit 3. 

Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

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Table 2.1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

VA Dominion Chesapeake 

ORISID=3803 

1 – 4 Unit 1: Used 2009/2018 IPM for NOx; used 2009 IPM for 

SO2; used VADEQ’s growth and control estimates for SO2 

(added scrubber that IPM did not have) 

Unit 2: Used 2009/2018 IPM for NOx; used 2009 IPM for 

SO2; used VADEQ’s growth and control estimates for SO2 

(added scrubber that IPM did not have) 

Unit 3: Used VA DEQ’s growth and control estimates for 

2009 NOx (added SCR that IPM did not have); used IPM 

result for 2018 NOx; Used 2009/2018 IPM for SO2. 

Unit 4: Used VA DEQ’s growth and control estimates for 

2009 NOx (added SCR that IPM did not have); used IPM 

result for 2018 NOx; Used 2009/2018 IPM for SO2. 

 Dominion Possum Point 

ORISID=3804 

3 & 4 

5 

6 

Unit 3&4: IPM had 137 tons of NOx for these units in 2009 

and 111 tons in 2018. VA DEQ specified that the permitted 

emission rates should be used, which equates to 3,066 tons 

in 2009 and 2018. 

Unit 5: IPM had zero heat input. Replaced all 2009/2018 

IPM results using VADEQ’s growth and control estimates. 

Unit 6: Replaced all 2009/2018 IPM results using VADEQ’s 

growth and control estimates. 

 Potomac River 

ORISID=3788 

1 - 5 Units 1&2: IPM retired these units. Mirant has no plans at 

this time to retire any units. Replaced all 2009/2018 IPM 

results using VADEQ’s growth and control estimates. 

Units 3, 4, 5: Replaced all 2009/2018 IPM results using 

VADEQ’s growth and control estimates. 

WV Albright 

ORISID=3942 

1, 2 IPM predicted early retirement for these units. AEP 

indicated there are no plans for early retirement. For 2009, 

used 2002 actual emissions as these units are not likely to 

retire by 2009. For 2018, used IPM prediction of retirement. 

 Rivesville 

ORISID=3945 

7, 8 IPM predicted early retirement for these units. AEP 

indicated there are no plans for early retirement. For 2009, 

used 2002 actual emissions as these units are not likely to 

retire by 2009. For 2018, used IPM prediction of retirement. 

 Willow Island 

ORISID=3946 

1, 2 Unit 1: IPM predicted early retirement for these units. AEP 

indicated there are no plans for early retirement. For 2009, 

used 2002 emissions as these units are not likely to retire by 

2009. For 2018, used IPM prediction of retirement. 

Unit 2: IPM predicted SCR and scrubber for 2009. These 

controls will not be in place by 2009. 

 North Branch Power 

Station 

ORISID=7537 

1A, 1B SO2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. 

Used SO2 Permit Rate of 0.678 lb/MMBtu and IPM 

predicted total fuel used to calculate SO2 emissions in 2009 

and 2018 

 Mt. Storm 

ORISID=3954 

1, 2, 3 SO2 Permit Rate was corrected from 2.7 to 0.15 lb/MMBtu. 

Used SO2 Permit Rate of 0.15 lb/MMBtu and IPM predicted 

total fuel used to calculate SO2 emissions in 2009 and 2018 

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Table 2.1-3 EGU Point Source SO2 Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

2002 

VISTAS 

BaseG 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

AL 447,828 340,194 378,052 190,099 305,262 

FL 453,631 195,790 186,055 141,551 132,177 

GA 514,952 534,469 417,449 180,178 230,856 

KY 484,057 371,944 290,193 229,603 226,062 

MS 67,429 85,629 76,579 27,230 15,146 

NC 477,990 205,018 242,286 110,382 108,492 

SC 206,399 171,206 124,608 121,694 93,274 

TN 334,151 255,400 255,410 112,662 112,672 

VA 241,204 169,714 225,653 90,935 140,233 

WV 516,084 226,127 277,489 124,466 115,324 

Total 3,743,725 2,555,491 2,473,774 1,328,800 1,479,498 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 

Table 2.1-4 EGU Point Source NOx Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

2002 

VISTAS 

BaseG 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

AL 161,038 70,852 82,305 42,769 64,358 

FL 257,677 89,610 86,165 77,080 73,125 

GA 147,517 97,146 98,497 58,095 75,717 

KY 198,817 107,890 92,021 64,378 64,378 

MS 43,135 11,475 36,011 8,945 10,271 

NC 151,854 66,431 66,522 60,914 62,353 

SC 88,241 43,817 46,915 48,346 51,456 

TN 157,307 41,767 66,405 31,725 31,715 

VA 86,886 63,220 66,219 49,420 75,594 

WV 230,977 63,510 86,328 51,241 51,241 

Total 1,523,449 655,718 727,388 492,913 560,208 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 

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Table 2.1-5 EGU Point Source VOC Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

2002 

VISTAS 

BaseG 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

AL 2,295 2,441 2,473 2,952 2,952 

FL 2,524 1,867 1,910 2,324 2,376 

GA 1,244 1,571 2,314 1,903 2,841 

KY 1,487 1,369 1,369 1,426 1,426 

MS 648 406 404 1,124 1,114 

NC 988 974 954 1,272 1,345 

SC 470 660 660 906 906 

TN 926 932 932 977 976 

VA 754 685 778 903 996 

WV 1,180 1,342 1,361 1,387 1,387 

Total 12,516 12,247 13,155 15,174 16,319 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 

Table 2.1-6 EGU Point Source CO Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

2002 

VISTAS 

BaseG 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

AL 11,279 14,948 14,986 24,342 24,342 

FL 57,113 45,391 35,928 63,673 53,772 

GA 9,712 20,066 23,721 32,744 44,476 

KY 12,619 15,812 15,812 17,144 17,144 

MS 5,303 5,078 5,051 15,364 15,282 

NC 13,885 15,141 14,942 19,612 20,223 

SC 6,990 11,135 11,135 14,786 14,786 

TN 7,084 7,221 7,213 7,733 7,723 

VA 6,892 11,869 12,509 14,755 15,420 

WV 10,341 11,328 11,493 11,961 11,961 

 Total 141,218 157,989 152,790 222,114 225,129 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 

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Table 2.1-7 EGU Point Source PM10-PRI Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

2002 

VISTAS 

BaseG 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

AL 7,646 6,959 6,969 7,822 7,822 

FL 21,387 9,384 9,007 10,310 9,953 

GA 11,224 17,088 17,891 18,329 20,909 

KY 4,701 6,463 6,463 6,694 6,694 

MS 1,633 5,487 4,957 7,624 7,187 

NC 22,754 22,888 22,152 33,742 37,376 

SC 21,400 28,650 19,395 37,864 28,826 

TN 14,640 15,608 15,608 15,941 15,941 

VA 3,960 4,479 5,508 12,744 13,775 

WV 4,573 5,471 5,657 6,349 6,349 

Total 113,918 122,477 113,607 157,419 154,832 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 

Table 2.1-8 EGU Point Source PM2.5 -PRI Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

2002 

VISTAS 

BaseG 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

AL 4,113 3,916 3,921 4,768 4,768 

FL 15,643 6,250 5,910 7,171 6,843 

GA 4,939 10,104 10,907 11,403 13,983 

KY 2,802 4,279 4,279 4,434 4,434 

MS 1,138 5,310 4,777 7,469 7,033 

NC 16,498 16,514 15,949 26,966 29,792 

SC 17,154 23,366 16,042 32,180 25,032 

TN 12,166 13,092 13,092 13,387 13,387 

VA 2,606 3,194 4,067 11,101 11,976 

WV 2,210 2,850 2,940 3,648 3,648 

Total 79,269 88,875 81,884 122,527 120,896 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 

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Table 2.1-9 EGU Point Source NH3 Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

2002 

VISTAS 

BaseG 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

Base F4 

IPM Based 

Base G 

IPM Based 

with S/L 

Adjustments 

AL 317 359 359 1,072 1,072 

FL 234 1,659 1,631 3,004 2,976 

GA 83 686 686 1,677 1,677 

KY 326 400 400 476 476 

MS 190 333 333 827 827 

NC 54 423 445 691 663 

SC 142 343 343 617 617 

TN 204 227 227 241 241 

VA 127 632 694 558 622 

WV 121 330 330 180 180 

Total 1,798 5,392 5,448 9,343 9,351 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 

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2.1.2 Non-EGU Emission Projections 

The general approach for assembling future year data was to use growth and control data 

consistent with the data used in EPA’s Clean Air Interstate Rule analyses, supplement these data 

with available stakeholder input, and provide the results for stakeholder review to ensure 

credibility. We used the revised 2002 VISTAS base year inventory, based on the 2002 CERR 

submittals as the starting point for the non-EGU projection inventories. As described in Section 

2.1.1.4, we split the point source inventory into EGU and non-EGU components. MACTEC 

performed the following activities to apply growth and control factors to the 2002 inventory to 

generate the 2009 and 2018 projection inventories: 

• Obtained, reviewed, and applied the most current growth factors developed by EPA, 

based on forecasts from an updated Regional Economic Models, Inc. (REMI) model 

(version 5.5) and the latest Annual Energy Outlook published by the Department of 

Energy (DOE); 

• Obtained, reviewed, and applied any State-specific or sector-specific growth factors 

submitted by stakeholders; 

• Obtained and incorporated information regarding sources that have shut down after 2002 

and set the emissions to zero in the projection inventories; 

• Obtained, reviewed, and applied control assumptions for programs “on-the-books” and 

“on-the-way”; 

• Provided data files in NIF3.0 format and emission summaries in EXCEL format for 

review and comment; and 

• Updated the database with corrections or new information from S/L agencies based on 

their review of the Base F 2009/2018 inventories. 

The following sections discuss each of these steps. 

2.1.2.1 Growth assumptions for non-EGU sources 

This section describes the growth factor data used in developing the Base F inventory for 2009 

and 2018, as well as the changes to the growth factor data made for the Base G inventory. 

The growth factor data used in developing the Base F inventory were consistent with EPA’s 

analyses for the CAIR rulemaking. These growth factors are fully documented in the reports 

entitled Development of Growth Factors for Future Year Modeling Inventories (dated April 30, 

2004) and CAIR Emission Inventory Overview (dated July 23, 2004). Three sources of data were 

used in developing the growth factors for the Base F inventory: 

• State-specific growth rates from the Regional Economic Model, Inc. (REMI) Policy 

Insight® model, version 5.5 (being used in the development of the EGAS Version 5.0). 

The REMI socioeconomic data (output by industry sector, population, farm sector value 

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added, and gasoline and oil expenditures) are available by 4-digit SIC code at the 

State level. 

• Energy consumption data from the DOE’s Energy Information Administration’s (EIA) 

Annual Energy Outlook 2004, with Projections through 2025 for use in generating 

growth factors for non-EGU fuel combustion sources. These data include regional or 

national fuel-use forecast data that were mapped to specific SCCs for the non-EGU fuel 

use sectors (e.g., commercial coal, industrial natural gas). Growth factors for the 

residential natural gas combustion category, for example, are based on residential natural 

gas consumption forecasts that are reported at the Census division level. These Census 

divisions represent a group of States (e.g., the South Atlantic division includes eight 

southeastern States and the District of Columbia). Although one would expect different 

growth rates in each of these States due to unique demographic and socioeconomic 

trends, EIA’s projects all States within each division using the same growth rate.

• Specific changes for sectors (e.g., plastics, synthetic rubber, carbon black, cement 

manufacturing, primary metals, fabricated metals, motor vehicles and equipment) where 

the REMI-based rates were unrealistic or highly uncertain. Growth projections for these 

sectors were based on industry group forecasts, Bureau of Labor Statistics (BLS) 

projections and Bureau of Economic Analysis (BEA) historical growth from 1987-2002. 

In addition to the growth data described above, we received two sets of growth projections from 

VISTAS stakeholders. 

The American Forest and Paper Association (AF&PA) supplied growth projections for the pulp 

and paper sector, which were applied to SIC 26xx Paper and Allied Products. The AF&PA 

projection factors are for the U.S. industry and apply to all States equally. The numbers come 

from the 15-year forecast for world pulp and recovered paper prepared by Resource Information 

Systems Inc. (RISI). 

AF&PA Growth Factor 

SIC Code Sector 

2002 to 2009 2002 to 2018 

2611 Pulp Mills 1.067 1.169 

2621 Paper Mills 1.067 1.169 

2631 Paperboard Mills 1.067 1.169 

For both the Base F and Base G inventories, we used the above AF&PA growth factors by SIC 

instead of the factors obtained from EPA’s CAIR analysis. 

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For the Base F inventory, the NCDENR supplied recent projections for three key sectors in 

North Carolina where declining production was anticipated – SIC 22xx Textile Mill Products, 

23xx Apparel and Other Fabrics, and 25xx Furniture and Fixtures. For the Base G inventory, 

NCDENR decided to use a growth factor of 1.0 for these SIC codes for both 2009 and 2018. 

Although NCDENR has data that shows a steady decline in these industries in NC, NCDENR 

wanted to maintain the emission levels at 2002 levels so the future emission reduction credits 

were available in the event that they are needed for nonattainment areas. The specific growth 

factors for these industrial sectors in North Carolina were: 

NCDENR Growth Factors for Specific Industrial Sectors 

2009 2018 

SIC Code Industrial 

Sector Base F Base G Base F Base G 

22xx Textile Mill 

Products 0.6239 1.00 0.2792 1.00 

23xx Apparel and 

Other Fabrics 0.5867 1.00 0.2247 1.00 

25xx Furniture and 

Fixtures 0.8970 1.00 0.7647 1.00 

For the Base G inventory, we made one additional change to the growth factors. The Base F 

inventory relied on DOE’s AEO2004 forecasts for projecting emissions for fuel-burning SCCs 

(applies mainly to ICI boilers 1-02-xxx-xx and 1-03-xxx-xx, as well as in-process fuel use). We 

replaced the AEO2004 data with the more recent AEO2006 forecasts (released in February 

2006) to reflect changes in the energy market and to improve the emissions growth factors 

produced. We obtained the corresponding AEO2006 projection tables from DOE’s web site 

located at http://www.eia.doe.gov/oiaf/aeo/supplement/supref.html. We developed tables comparing 

the growth factors based on AEO2004 and AEO2006. These comparison tables were reviewed 

by the S/L agencies. Based on this review, VISTAS decided to use the AEO2006 growth factors 

for fuel burning SCCs. 

We used the EPA’s EGAS model and updated the corresponding AEO2006 projection tables to 

create growth factors by SCC. We applied the updated growth factors to 2002 actual emissions 

and replaced the 2009 and 2018 emissions in NIF EM tables for the affected SCCs. 

2.1.2.2 Source Shutdowns 

A few states indicated that significant source shutdowns have occurred since 2002 and that 

emissions from these sources should not be included in the future year inventories. These sources 

are identified in Table 2.1-10. 

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Table 2.1-10. Summary of Source Shutdowns Incorporated in Base G Inventory. 

State Description of Source Shutdowns 

AL None specified. 

FL The following facilities are shutdown and projected emissions were set to zero in 2009/2018. 

 0570075 CORONET INDUSTRIES, INC. 

 1050050 U S AGRI-CHEMICALS CORP. 

 1050051 U.S. AGRI-CHEMICALS CORPORATION 

These facilities emitted 2,417 tons of SO2 and 113 tons of NOx in 2002. 

GA Georgia indicated that the former Blue Circle (now LaFarge) facility in downtown Atlanta will likely 

shut down before 2009. The facility has two cement kilns, one of which is already shut down. The 

second kiln will continue to operate until the new facility in Alabama has enough milling capacity, 

after which the entire Atlanta facility will be completely closed down. This facility emitted 1,617 tons 

of SO2 and 587 tons of NOx in 2002. 

KY None specified. 

MS AF&PA indicated that the International Paper Natchez Mill (28-001-2800100010) has shut down. 

This facility emitted 1,398 tons of SO2 and 1,773 tons of NOx in 2002. 

 The Magnolia Resources - Pachuta Harmony Gas Plant (28-023-00031) is out of business and no 

longer holds an air permit. This facility emitted 2,257 tons of SO2and 134 tons of NOx in 2002. 

NC In Base F, two paper mills were identified as being shut down in the 2018 inventory. NCDENR 

indicated that these mills are not expected to close. The two facilities are Ecusta Business 

Development (37-175-3717500056) and International Paper (37-083-00007). Their emissions were 

added back into the Base G 2018 inventory. 

 BASF Corporation (37-021-724) in Buncombe County is currently operating but has plans to shut 

down in 2007. This facility emitted 461 tons of SO2 and 266 tons of NOx in 2002. 

SC South Carolina provided a list of facilities that were identified as closing down on or after Jan. 1, 

2003. The emissions for these facilities were set to zero in the 2009 and 2018 projection inventories. 

Emissions from these plants in 2002 were: 6,195 tons of SO2, 2,994 tons of NOx, and 2,836 tons of 

VOC. Most of the emissions were from one facility – Celanese Acetate (45-091-2440-0010) in York 

County. 

TN Davidson County (Nashville) indicated that significant source shutdowns have occurred since data 

were submitted for the 2002 CERR. Source number 47-037-00002 (Dupont) shut down a portion of 

their facility, which was permanently taken out of service. Source 47-037-00050 (Nashville Thermal 

Transfer Corp.) shut down their municipal waste combustors and replaced them with natural gas fired 

boilers with propane stand by. 

 Weyerhaeuser (AKA Willamette) Power Boiler 7 (47-163-0022, EU ID = 017) is being shut down. 

This emission unit emitted 4,297 tons of SO2 and 1,443 tons of NOx in 2002. 

 Liberty Fibers (47-063-0197) in Hamblen County has recently shut down. This facility emitted 5,377 

tons of SO2; 2,057 tons of NOx; and 9,059 tons of VOC in 2002. 

VA Rock-Tenn (51-680-00097) received a permit dated 9/13/2003 which required the shutdown of units 1 

and 2 by 2/27/2004. This permit was part of a netting exercise that allowed the installation of a new 

NG/DO boiler. These two units emitted 507 tons of SO2 and 276 tons of NOx in 2002. 

WV None specified. 

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2.1.2.3 Control Programs applied to non-EGU sources 

We used the same control programs for both the 2009 and 2018 non-EGU point inventory. Two 

control scenarios were developed: on-the-books (OTB) controls and on-the-way (OTW) controls. 

The OTB control scenario accounts for post-2002 emission reductions from promulgated federal, 

State, local, and site-specific control programs. The OTW control scenario accounts for proposed 

(but not final) control programs that are reasonably anticipated to result in post-2002 emission 

reductions. The methodologies used to account for the emission reductions associated with these 

emission control programs are discussed in the following sections. 

Table 2.1-11. Non-EGU Point Source Control Programs Included in 2009/2018 

Projection Inventories. 

On-the-Books (Cut-off of July 1, 2004 for Base 1 adoption) 

• Atlanta / Northern Kentucky / Birmingham 1-hr SIPs 

• Industrial Boiler/Process Heater/RICE MACT 

• NOx RACT in 1-hr NAA SIPs 

• NOx SIP Call (Phase I- except where States have adopted II already e.g. NC) 

• Petroleum Refinery Initiative (October 1, 2003 notice; MS & WV) 

• RFP 3 percent Plans where in place for one hour plans 

• VOC 2-, 4-, 7-, and 10-year maximum achievable control technology (MACT0 

Standards 

• Combustion Turbine MACT 

On-the-Way 

• NOx SIP Call (Phase II – remaining States & IC engines) 

2.1.2.3.1 OTB - NOx SIP Call (Phase I) 

Phase I of the NOx SIP call applies to certain large non-EGUs, including large industrial boilers 

and turbines, and cement kilns. States in the VISTAS region affected by the NOx SIP call have 

developed rules for the control of NOx emissions that have been approved by EPA. We reviewed 

the available State rules and guidance documents to determine the affected sources and ozone 

season allowances. We also obtained and reviewed information in the EPA’s CAMD NOx

Allowance Tracking System – Allowances Held Report. Since these controls are to be in effect 

by the year 2007, we capped the emissions for NOx SIP call affected sources at 2007 levels and 

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carried forward the capped levels for the 2009/2018 future year inventories. Since the NOx SIP 

call allowances are given in terms of tons per ozone season (5 month period from May to 

September), we calculated annual emissions by multiplying the 5-month allowances by a factor 

of 12 divided by 5. 

2.1.2.3.2 OTB - Industrial Boiler/Process Heater MACT 

EPA anticipates reductions in PM and SO2 as a result of the Industrial Boiler/Process Heater 

MACT standard. The methods used to account for these reductions are the same as those used 

for the CAIR analysis. Reductions were included for existing units firing solid fuel (coal, wood, 

waste, biomass) which had a design capacity greater than 10 mmBtu/hr. EPA prepared a list of 

SCCs for solid fuel industrial and commercial/ institutional boilers and process heaters. We 

identified boilers greater than 10 mmBtu/hr using either the boiler capacity from the VISTAS 

2002 inventory, or if the boiler capacity was missing, a default capacity based on a methodology 

developed by EPA for assigning default capacities based on SCC. The applied MACT control 

efficiencies were 4 percent for SO2 and 40 for percent for PM10 and PM2.5 to account for the cobenefit from installation of acid gas scrubbers and other control equipment to reduce HAPs. 

2.1.2.3.3 OTB - 2, 4, 7, and 10-year MACT Standards 

Maximum achievable control technology (MACT) requirements were also applied, as 

documented in the report entitled Control Packet Development and Data Sources, dated July 14, 

2004. The point source MACTs and associated emission reductions were designed from Federal 

Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD) staff. We 

did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, 

assuming that the effects of these controls are already accounted for in the 2002 inventories 

supplied by the States. Emission reductions were applied only for MACT standards with an 

initial compliance date of 2002 or greater. 

2.1.2.3.4 OTB Combustion Turbine MACT 

The projection inventories do not include the NOx co-benefit effects of the MACT regulations 

for Gas Turbines or stationary Reciprocating Internal Combustion Engines, which EPA estimates 

to be small compared to the overall inventory. 

2.1.2.3.5 OTB - Petroleum Refinery Initiative (MS and WV) 

Three refineries in the VISTAS region are affected by two October 2003 Clean Air Act 

settlements under the EPA Petroleum Refinery Initiative. The refineries are: (1) the Chevron 

refinery in Pascagoula, MS; (2) the Ergon refinery in Vicksburg, MS; and (3) the Ergon refinery 

in Newell, WV. 

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The first consent decree pertained to Chevron refineries in Richmond and El Segundo, CA; 

Pascagoula, MS; Salt Lake City, UT; and Kapolei, HI. Actions required under the Consent 

Decree will reduce annual emissions of NOx by 3,300 tons and SO2 by 6,300 tons. The consent 

decree requires a program to reduce NOx emissions from refinery heaters and boilers through the 

installation of NOx controls that meet at least an SNCR level of control. The refineries are to 

eliminate fuel oil burning in any combustion unit. The consent decree also requires reductions of 

NOx and SO2 from the fluid catalytic cracking unit and control of acid gas flaring incidents. The 

consent decree does not provide sufficient information to calculate emission reductions for the 

FCCU or flaring at the Pascagoula refinery. Therefore, we calculated a general percent reduction 

for NOx and SO2 by dividing the expected emission reductions at the five Chevron refineries by 

the total emissions from these five refineries (as reported in the 1999 NEI). This resulted in 

applying percent reductions of 45 percent for SO2 and 28 percent for NOx to FCCU and flaring 

emissions at the Chevron Pascagoula refinery. 

The second consent decree pertained to the Ergon-West Virginia refinery in Newell, WV; and 

the Ergon Refining facility in Vicksburg, MS. The consent decree requires the two facilities to 

implement a 6-year program to reduce NOx emission from all heaters and boilers greater than 40 

mmBtu/hr, and to eliminate fuel oil burning in any combustion unit (except during periods of 

natural gas curtailment). Specifically, ultra low NOx burners are required on Boilers A and B at 

Newell, a low NOx-equivalent level of control for heater H-101 at Newell and heaters H-1 and 

H-3 at Vicksburg, and an ultra low NOx burner level of control for heater H-451 at Vicksburg. 

2.1.2.3.6 OTW - NOx SIP Call (Phase II) 

The final Phase II NOx SIP call rule was finalized on April 21, 2004. States had until April 21, 

2005, to submit SIPs meeting the Phase II NOx budget requirements. The Phase II rule applies to 

large IC engines, which are primarily used in pipeline transmission service at compressor 

stations. We identified affected units using the same methodology as was used by EPA in the 

proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than 1 ton per 

day during 2002). The final rule reflects a control level of 82 percent for natural gas-fired IC 

engines and 90 percent for diesel or dual fuel categories. As shown later in Table 2.1-12, several 

S/L agencies provided move specific information on the anticipated controls at the compressor 

stations. This information was used in the Base G inventory instead of the default approach used 

by EPA in the proposed Phase II rule. 

2.1.2.3.7 Clean Air Interstate Rule 

CAIR does not require or assume additional emission reductions from non-EGU boilers and 

turbines. 

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2.1.2.4 Quality Assurance steps 

Final QA checks were run on the revised projection inventory data set to ensure that all 

corrections provided by the S/L agencies and stakeholders were correctly incorporated into the 

S/L inventories and that there were no remaining QA issues that could be addressed during the 

duration of the project. After exporting the inventory to ASCII text files in NIF 3.0, the EPA QA 

program was run on the ASCII files and the QA output was reviewed to verify that all QA issues 

that could be addressed were resolved 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, and to ensure that a full and complete 

inventory was developed for VISTAS. Quality assurance was an important component to the 

inventory development process and MACTEC performed the following QA steps on the point 

source component of the VISTAS revised 2002 base year inventory: 

1. Facility level emission summaries were prepared and evaluated to ensure that 

emissions were consistent and reasonable. The summaries included base year 2002 

emissions, 2009/2018 projected emissions accounting only for growth, 2009/2018 

projected emissions accounting for both growth and emission reductions from OTB 

and OTW controls. 

2. State-level non-EGU comparisons (by pollutant) were developed for the base year 

2002 emissions, 2009/2018 projected emissions accounting only for growth, 

2009/2018 projected emissions accounting for both growth and emission reductions 

from OTB and OTW controls. 

3. Data product summaries and raw NIF 3.0 data files were provided to the VISTAS 

Emission Inventory Technical Advisor and to the Point Source, EGU, and non-EGU 

Special Interest Work Group representatives for review and comment. Changes 

based on these comments were reviewed and approved by the S/L point source 

contact prior to implementing the changes in the files. 

4. Version numbering was used for all inventory files developed. The version 

numbering process used a decimal system to track major and minor changes. For 

example, a major change would result in a version going from Base F1 to Base F2. 

2.1.2.5 Additional Base G Updates and Corrections 

Table 2.1-12 summarizes the updates and corrections to the Base F inventory that were requested 

by S/L agencies and incorporated into the Base G 2009/2018 inventories. 

2.1.2.6 Summary of Revised 2009/2018 non-EGU Point Source Inventories 

Tables 2.1-13 through 2.1-19 summarize the revised 2009/2018 non-EGU point source 

inventories. The “growth only” column does not include the shutdowns (section 2.1.2.2) or 

control factors (section 2.1.2.3), only the growth factors described in section 2.1.2.1. 

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Table 2.1-12. Summary of Updates and Corrections to the Base F 2009/2018 Inventories 

Incorporated into the Base G 2009/2018 Inventories. 

State Nature of Update/Correction 

AL Corrected the latitude and longitude for two facilities: Ergon Terminalling (Site ID: 01-073-

010730167) and Southern Power Franklin (Site ID: 01-081-0036). 

AL Corrections to stack parameters at 10 facilities for stacks with parameters that do not appear to fall 

into the ranges typically termed "acceptable" for AQ modeling. 

FL Corrected 2009/2018 emission values for the Miami Dade RRF facility (Site ID: 12-086-0250348) 

based on revised 2002 emissions and application of growth control factors for 2009/2018. 

GA Hercules Incorporated (12-051-05100005) had an erroneous process id (#3) within emission unit id 

SB9 and was deleted. This removes about 6,000 tons of SO2 from the 2009/2018 inventories. 

 Provided a revised file of location coordinates at the stack level that was used to replace the location 

coordinated in the ER file. 

 There are several sources that have updated their emissions from their BART eligible units. most of 

these changes were for fairly small (<50 tpy) sources. 

NC Made several changes to Base F inventory to correct the following errors: 

1. Corrected emissions at Hooker Furniture (Site ID: 37-081-3708100910), release point G-29, to use 

the corrected values in 2002 and carry those same numbers through to 2009 and 2018 since NCDENR 

assumes zero growth for furniture industry. 

2. Identified many stack parameters in the ER file that were unrealistic. Several have zero for height, 

diameter, gas velocity, and flow rate. NC used the procedures outlined in Section 8 of the document 

""National Emission Inventory QA and Augmentation Report" to correct unrealistic stack parameters. 

3. Identified truncated latitude and longitude values in Base F inventory. NC updated all Title V 

facility latitude and longitude that was submitted to EPA for those facilities in 2004. Smaller facilities 

with only two decimal places were not corrected. 

4. Corrected 2018 VOC emissions for International Paper (3709700045) Emission Unit ID, G-12, to 

reflect changes to the 2002 inventory. 

 There are three Transcontinental Natural Gas Pipeline facilities in NC that are subject to the NOx SIP 

call. NCDENR took 2004 emissions and grew them to 2009 & 2018 and capped those units that are 

subject to the NOx SIP Call Rule. These facility IDs are 37-057-3705700300, 37-097-3709700225, 

and 37-157-3715700131. 

 NCDENR applied NOx RACT to a two facilities located in the Charlotte nonattainment area. 

NCDENR provided 2009 & 2018 emissions for Philip Morris USA (37-025-3702500048) and 

Norandal USA (37-159-3715900057). 

SC Corrected PM species emission values. SC DHEC’s initial CERR submittal reported particulate 

matter emissions using the PM-FIL, PM10-FIL, and PM2.5 -FIL pollutant codes. In August 2005, SC 

DHEC indicated that data reported using the PM-FIL, PM10-FIL, and PM2.5 -FIL pollutant codes 

should actually have been reported using the PM-PRI, PM10-PRI, and PM2.5 _PRI codes. MACTEC 

performed a subsequent PM augmentation in April 2006 using the revised pollutant codes. These 

changes were reflected in the Base G 2009/2018 emission inventory. 

 Specified that the Bowater Inc. facility (45-091-2440-0005) in York County conducted an expansion 

in 2003/2004 and plans a future expansion. SC provided updated emissions for 2009 and 2018 for this 

facility. 

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Table 2.1-12. Continued. 

State Nature of Update/Correction 

TN Updated 2009/2018 emissions for Eastman Chemical (47-163-0003) based on final (Feb. 2005) 

BART rule. 

 Updated 2009/2018 emission inventory for the Bowater facility (47-107-0012) based on the facility’s 

updated 2002 emission inventory update. 

 Replaced 2009/2018 data from Hamilton County, Tennessee, using data from Hamilton County’s 

CERR submittal as contained in EPA’s 2002 NEI (in Base F, the inventory for Hamilton County was 

based on the draft VISTAS 2002 inventory, which in turn was based on the 1999 NEI); applied 

growth and control factors to revised 2002 inventory to generate emission projections for 2009/2018. 

 Updated 2009/2018 emissions for PCS Nitrogen Fertilizer LP (Site ID: 47-157-00146) based on the 

facility’s updated 2002 emission inventory update. 

 The 2002 NEI correctly reports the actual emissions for CEMEX (47-093-0008) after the NOx SIP 

call. There is no reason to suspect that that rate would change in 2008, 2009, or 2018. Emissions for 

2009/2018 were set equal to 2002 emissions. 

 In the Base F 2009/2018 inventories, NOx controls were applied for two units at Columbia Gulf 

Transmission (47-111-0004). There are no plans for controls at these units, EO3 and EO4. The 

assumed control efficiency of 82 percent was backed out in the 2009/2018 inventories. 

VA VADEQ provided 2009/2018 NOx emission estimates for NOx Phase II gas transmission sources at 

three Transco facilities (51-011-00011, 51-137-00027, 51-143-00120) which were used to replace the 

default NOx Phase II control assumptions for these facilities. 

 VADEQ provided updated 2009/2018 NOx and SO2 emissions based on new controls required by a 

November 2005 permit modification and netting exercise. The entire power plant facility is limited to 

213 tons of NOx and 107 tons of SO2 per year. The permit also allowed the installation of 3 new 

boilers, also under the 213 tons of NOx /year cap. 

WV Updated 2009/2018 emissions for Steel of West Virginia (Site ID: 54-011-0009) based on the 

facility’s updated 2002 emission inventory update. 

 Made changes to several Site ID names due to changes in ownership 

 Base F emissions were much too high for Weirton Steel (54-021-0029). WV believes that the source 

is very unlikely to emit the NOx SIP Call budgeted amounts in 2009 or 2018. WV provided revised 

emission estimates based on EGAS for 2009/2018. 

 Made corrections to latitude/longitude and stack parameters at a few facilities for stacks with 

parameters that do not appear to fall into the ranges typically termed "acceptable" for AQ modeling. 

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Table 2.1-13 Non-EGU Point Source SO2 Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F4 Base G Base F4 Base G 

AL 96,481 100,744 101,246 112,703 113,224 

FL 65,090 68,549 65,511 79,015 75,047 

GA 53,778 61,535 53,987 68,409 59,349 

KY 34,029 35,470 36,418 38,806 40,682 

MS 35,960 27,488 25,564 40,195 39,221 

NC 44,123 48,751 42,536 50,415 46,314 

SC 53,518 55,975 48,324 56,968 53,577 

TN 79,604 89,149 70,678 96,606 77,247 

VA 63,903 63,075 62,560 69,776 68,909 

WV 54,070 54,698 55,973 60,137 62,193 

Total 580,556 605,434 562,797 673,030 635,763 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 

Table 2.1-14 Non-EGU Point Source NOx Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State BaseG Base F4 Base G Base F4 BaseG 

AL 83,310 69,676 69,409 79,101 78,318 

FL 45,156 44,859 46,020 50,635 51,902 

GA 49,251 51,556 50,353 57,323 55,824 

KY 38,392 36,526 37,758 40,363 41,034 

MS 61,526 55,877 56,397 62,132 61,533 

NC 44,928 44,877 34,767 47,200 37,801 

SC 42,153 42,501 40,019 44,480 44,021 

TN 64,344 63,431 57,883 70,313 63,453 

VA 60,415 51,335 51,046 56,876 55,945 

WV 46,612 40,433 38,031 44,902 43,359 

Total 536,087 501,071 481,683 553,325 533,190 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 

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Table 2.1-15 Non-EGU Point Source VOC Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F4 Base G Base F4 Base G 

AL 47,037 46,660 46,644 54,268 54,291 

FL 38,471 36,675 36,880 42,787 42,811 

GA 33,709 34,082 34,116 40,267 40,282 

KY 44,834 47,648 47,785 55,564 55,861 

MS 43,204 37,921 37,747 45,769 45,338 

NC 61,182 70,464 61,925 76,027 70,875 

SC 38,458 38,273 35,665 44,545 43,656 

TN 84,328 89,380 74,089 111,608 93,266 

VA 43,152 43,620 43,726 53,065 53,186 

WV 14,595 14,012 13,810 16,632 16,565 

Total 448,970 458,735 432,387 540,532 516,131 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 

Table 2.1-16 Non-EGU Point Source CO Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F4 Base G Base F4 Base G 

AL 174,271 176,899 180,369 194,280 201,794 

FL 81,933 83,937 87,037 96,642 96,819 

GA 130,850 147,362 147,427 168,570 167,904 

KY 109,936 121,727 122,024 139,121 139,437 

MS 54,568 58,023 57,748 67,764 66,858 

NC 50,576 53,955 53,744 61,127 62,197 

SC 56,315 62,144 60,473 71,318 68,988 

TN 115,264 123,844 119,665 146,407 140,942 

VA 63,796 67,046 68,346 74,364 76,998 

WV 89,879 100,248 100,045 119,318 119,332 

 Total 927,388 995,185 996,878 1,138,911 1,141,269 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 

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Table 2.1-17 Non-EGU Point Source PM10-PRI Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F4 Base G Base F4 Base G 

AL 25,240 25,450 25,421 29,973 29,924 

FL 35,857 39,363 39,872 46,573 46,456 

GA 21,610 23,509 23,103 27,781 27,273 

KY 16,626 17,164 17,174 20,142 20,153 

MS 19,472 19,200 19,245 22,952 22,859 

NC 13,838 14,738 13,910 15,816 15,737 

SC 14,142 17,631 13,370 20,197 15,139 

TN 35,174 37,040 34,833 45,168 42,280 

VA 13,252 13,043 13,048 15,150 15,112 

WV 17,503 17,723 17,090 21,699 21,735 

Total 212,714 224,861 217,066 265,451 256,668 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 

Table 2.1-18 Non-EGU Point Source PM25-PRI Emission Comparison for 

2002/2009/2018. 

2002 2009 2018 

State Base G Base F4 Base G Base F4 Base G 

AL 19,178 19,256 19,230 22,628 22,598 

FL 30,504 33,387 33,946 39,436 39,430 

GA 17,462 19,361 18,982 22,882 22,416 

KY 11,372 11,680 11,686 13,734 13,739 

MS 9,906 9,144 9,199 10,768 10,739 

NC 10,500 11,192 10,458 11,927 11,825 

SC 10,245 13,101 9,390 14,947 11,086 

TN 27,807 29,302 27,577 35,750 33,532 

VA 10,165 9,980 9,988 11,604 11,594 

WV 13,313 13,364 12,769 16,474 16,516 

Total 160,452 169,767 163,225 200,150 193,475 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 

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Table 2.1-19 Non-EGU Point Source NH3 Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F4 Base G Base F4 Base G 

AL 1,883 2,132 2,132 2,464 2,464 

FL 1,423 1,544 1,544 1,829 1,829 

GA 3,613 3,963 3,963 4,799 4,797 

KY 674 733 760 839 901 

MS 1,169 667 668 761 764 

NC 1,180 1,288 1,285 1,422 1,466 

SC 1,411 1,578 1,578 1,779 1,779 

TN 1,613 1,861 1,841 2,240 2,214 

VA 3,104 3,050 3,049 3,613 3,604 

WV 332 341 341 416 413 

Total 16,402 17,157 17,161 20,162 20,231 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 

2.2 Area Sources 

This section describes the methodology used to develop the 2009 and 2018 projection Base F 

and Base G projection inventories. This section describes two approaches to these projections. 

Separate methods for projecting emissions were used for non-agricultural (stationary area) and 

agricultural area sources (predominantly NH3 emissions). The two methods used for these 

sectors are described in the sections that follow. 

2.2.1 Stationary area sources 

The general approach used to calculate Base F projected emissions for stationary area sources 

was as follows: 

1. Use the VISTAS Base F 2002 base year inventory as the starting point for projections. 

2. MACTEC then worked with the VISTAS States (via the Stationary Area Source SIWG) 

to obtain any State specific growth factors and/or future controls from the States to use in 

developing the projections. 

3. MACTEC then back calculated uncontrolled emissions from the Base F 2002 base year 

inventory based on existing controls reported in the 2002 Base F base year inventory. 

4. Controls (including control efficiency, rule effectiveness and rule penetration) provided 

by the States or originally developed for use in estimating projected emissions for U.S. 

EPA’s Heavy Duty Diesel (HDD) rulemaking emission projections and used in the Clean 

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Air Interstate Rule (CAIR) projections were then used to calculate controlled emissions. 

State submitted controls had precedence over the U.S. EPA developed controls. 

5. Growth factors supplied from the States or the U.S. EPA’s CAIR emission projections 

were then applied to project the controlled emissions to the appropriate year. In some 

cases EGAS Version 5 growth factors were used if no growth factor was available from 

either the States or the CAIR growth factor files. The use of EGAS Version 5 growth 

factors was on a case-by-case basis wherever State-supplied or CAIR factors were not 

available for SCCs found in the 2002 Base F inventory. Use of the EGAS factors was 

necessitated due to the CERR submittals used in constructing the Base F 2002 inventory. 

Use of the CERR data resulted in SCCs that were not found in the CAIR inventory and if 

no State-supplied growth factor was provided required the use of an EGAS growth factor. 

6. MACTEC then provided the final draft Base F projection inventory for review and 

comment by the VISTAS States. 

For Base F stationary area sources, no State-supplied growth or control factors were provided. 

Thus for all of the sources in this sector of the inventory, growth and controls for Base F were 

applied based on controls initially identified for the CAIR and growth factors identified for the 

CAIR projections. 

For the Base G projections, the Base G 2002 base year inventory (see section 1.2.3) was used as 

a starting point. States provided some updated future controls but growth factors used were 

identical to those used for Base F. The revised controls for Base G were largely for new sources 

added as part of the 2002 Base F comments. The calculation of Base G projections was identical 

to the six steps outlined above with the exception of revisions made to prescribed fire for 2009 

and 2018 and for the State of North Carolina. North Carolina provided 2009 and 2018 updated 

emission files used to update the emissions for each year for several source categories. However 

not all sources in the inventory were included in these NC updates. As a consequence, the final 

Base G 2009 and 2018 inventory for NC included emissions updated using the NC supplied files 

and emissions developed using growth and control factors as outlined above. 

In a few cases, additional growth factors had to be added for source categories that had not 

initially been included in the Base F inventory. These growth factors were obtained from EGAS 

5.0. Finally updates to growth factors from EGAS 5.0 were made for fuel fired emission sources. 

The updated growth factors reflected the most recent data from the Department of Energy’s 

Annual Energy Outlook (AEO). These data were used to reflect changes in energy efficiency 

resulting from new or updated fuel firing technologies. 

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2.2.1.1 Stationary area source controls 

The controls obtained by MACTEC for the HDD rulemaking were controls for the years 2007, 

2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, control values for 

intermediate years were prepared using a straight line interpolation of control level between 2007 

and 2020. The equation used to calculate the control level was as follows: 

 CE = (((2020 CE – 2007 CE)/13)*YRS) + 2007 CE 

 Where: 

CE = Control Efficiency for either 2009 or 2018 

2020 CE = HDD Control Efficiency value for 2020 

2007 CE = HDD Control Efficiency value for 2007 

13 = Number of years between 2020 and 2007 

YRS = Number of years beyond 2007 to VISTAS Projection year 

For 2009 the value of YRS would be two (2) and for 2018 the value would be eleven (11). 

Control efficiency values were determined for VOC, CO and PM. Rule penetration values for 

each year in the HDD controls tables obtained by MACTEC were always 100 percent so those 

values were maintained for the VISTAS projections. 

Prior to performing the linear interpolation of the controls, MACTEC evaluated controls from 

the CAIR projections (NOTE: Initially the controls came from the IAQTR projections, however 

the controls used in CAIR were virtually identical to those in IAQTR). Those controls appeared 

to be identical to those used for the HDD rulemaking. In addition, MACTEC received some 

additional information on some controls for area source solvents (email from Jim Wilson, E.H. 

Pechan and Associates, Inc. to Gregory Stella, VISTAS Emission Inventory Technical Advisor, 

3/5/04) that were used to check against the controls in the HDD rulemaking files. Where those 

controls proved to be more stringent than the HDD values, MACTEC updated the control file 

with those values (which were then used in the interpolation to develop 2009 and 2018 values). 

Finally, for VOC the HDD controls were initially provided at the State-county-SCC level. 

However, upon direction from the VISTAS Emission Inventory Technical advisor, the VOC 

controls were consolidated at the SCC level and applied across all counties within the VISTAS 

region (email from Gregory Stella, Alpine Geophysics, 3/3/2004) to ensure that no controls were 

missed due to changes in county FIPS codes and/or SCC designations between the time the HDD 

controls were developed and 2002. 

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The equation below indicates how VOC emissions were projected for stationary area sources. 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ ⎟

⎠

⎞ ⎜

⎝

⎛

⎟

⎠

⎞ ⎜

⎝

⎛

⎟

⎠

⎞ ⎜

⎝

⎛ = − 100

_

100

_

100

_ 1 2018 2018 2018

2018 2002

VOC CE VOC RE VOC RP VOC VOC x

 Where: 

 VOC2018 = VOC emissions for 2018 

 VOC2002 = Uncontrolled VOC emissions for 2002 

 VOC_CE2018 = Control Efficiency for VOC (in this example for 2018) 

 VOC_RE2018 = Rule Effectiveness for VOC (in this example for 2018) 

 VOC_RP2018 = Rule Penetration for VOC (in this example for 2018) 

A similar equation could be constructed for either PM or CO. It should be noted that the control 

efficiencies calculated based on the HDD rulemaking were only applied if they were greater than 

any existing 2002 base year controls. No controls were found for SO2 or NOx area sources. 

In the pre-Base F 2018 emission estimates, an energy efficiency factor was applied to energy 

related stationary area sources. The energy efficiency factor was applied along with the growth 

factor to account for both growth and changes in energy efficiency. That factor was not applied 

to the Base F projections since information supplied by U.S. EPA related to the CAIR growth 

factors indicated that growth values for those categories were derived from U.S. Department of 

Energy (DOE) and were felt to account for changes in growth and projected energy efficiency. 

For the Base G inventory, these energy efficiency factors were re-instituted and used in 

conjunction with EGAS 5.0 growth factors in a manner identical to that used for the pre-Base F 

inventories. The energy efficiency factors were derived from U.S. DOE’s Annual Energy 

Outlook report. 

One significant difference between the Base F and Base G control factors was for counties and 

independent cities in northern Virginia. Several counties and independent cities in northern 

Virginia are subject to Ozone Transport Commission rules. For these counties and independent 

cities, controls for portable fuel containers, mobile equipment repair/refinishing, consumer 

products, solvent metal cleaning, and the architectural and industrial maintenance rules 

were added. The counties/independent cities (FIPS code) included in the changes for Base G 

were: Alexandria City (51510), Arlington (51013), Fairfax City (51600), Fairfax (51059), Falls 

Church City (51610), Fredericksburg City (51630), Loudoun (51107), Manassas City (51683), 

Manassas Park City (51685), Prince William County (51153), Spotsylvania (51177), and 

Stafford (51179). Not all OTC rules applied to all counties/cities. 

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2.2.1.2 Stationary area source growth 

As indicated above, growth factors for the Base F and Base G 2009 and 2018 inventories were 

obtained from the U.S. EPA and are linear interpolations of the growth factors used for the Clean 

Air Interstate Rule (CAIR) projections. The growth factors for the CAIR obtained by MACTEC 

were developed using a base year of 2001 and provided growth factors for 2010 and 2015. 

MACTEC used the TREND function in Microsoft ExcelTM to calculate 2002, 2009 and 2018 

values from the 2001, 2010 and 2015 values. The TREND function provides a linear 

interpolation of intermediate values from a known series of data points (in this case the 2001, 

2010 and 2015 values) based on the equation for a straight line. These values were calculated at 

the State and SCC level with the exception of paved road emissions (SCC = 2294000000). The 

growth factors for paved roads were available in the CAIR data set at the State, county and SCC 

level so they were applied at that level. 

Prior to utilizing the growth factors from the CAIR projections, MACTEC confirmed that all 

SCCs found in the VISTAS 2002 base year inventory were in the CAIR file (for Base F the 

starting point was the version 3.1 2002 base year inventory, for Base G the starting point was the 

Base F 2002 base year inventory). Some SCCs were not found in the CAIR file. For those SCCs, 

the growth factors used were derived in one of five ways. First where possible, they were taken 

from a beta version of EGAS 5.0. In other cases, the growth factor was set to one (i.e., no 

growth). In other cases, a similar SCC that had a CAIR growth factor was used. In a few cases a 

growth factor based on an average CAIR growth at the 6 digit SCC level was calculated. Finally 

a number of records used population as the growth surrogate. For the Base G inventory, CAIR 

growth factors for fuel fired area sources were replaced with EGAS 5.0 growth factors (used in 

conjunction with AEO fuel efficiency factors). A comment field in the growth factor file was 

used to mark those records that were not taken directly from the CAIR projection growth factors. 

2.2.1.3 Differences between 2009/2018 

Methodologically, there was no difference in the way that 2009 and 2018 emissions were 

calculated for stationary area sources. The individual control and growth factors were different 

(due to the linear interpolation used to calculate the values) but the calculation methods were 

identical. This applies to both Base F and Base G. 

The only exception to this is for the State of North Carolina for Base G. North Carolina provided 

an emissions update file used to override calculated projections for a number of area source 

categories. The values in these files (provided for both 2009 and 2018) were used to overwrite 

the calculated projected emissions in the final NIF file. 

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2.2.2 Agricultural area sources 

The general approach used to calculate projected emissions for agricultural area sources 

(predominantly NH3 emission sources) was as follows: 

1. MACTEC used the version 3.1 2002 base year inventory data (which was based on the 

CMU ammonia model version 3.6). 

2. MACTEC worked with the VISTAS States (via the Agricultural Sources SIWG) to 

obtain any State specific growth and/or future controls from the States for agricultural 

sources. 

3. Since the base year emissions were uncontrolled, and no future controls for these sources 

were identified, MACTEC projected the agricultural emissions using State-specific 

growth if available, otherwise the U.S. EPA’s Interstate Air Quality Transport Rule 

(IAQTR)/Ammonia inventory was used to develop the growth factors used to project the 

revised 2002 base year inventory to 2009 or 2018. Since the IAQTR inventory was only 

used to construct growth factors rather than using the emissions directly, no updated 

growth factors were prepared from the CAIR inventory values. 

4. MACTEC then provided the final draft inventory for review and comment by the 

VISTAS States. 

No change in the agricultural area source emission projections were made between Base F and 

Base G other than the removal of wild animal and human perspiration as a result of their removal 

from the 2002 base year file for Base G. 

2.2.2.1 Control assumptions for agricultural area sources 

No controls were identified either by the individual VISTAS States or in the information 

provided in the EPA’s IAQTR or CAIR Ammonia inventory documents. Thus all projected 

emissions for agricultural area sources represent simple growth with no controls. 

2.2.2.2 Growth assumptions for agricultural area sources 

Growth for several agricultural area source livestock categories was developed using the actual 

emission estimates developed by the EPA as part of the NEI. That work included projections for 

the years 2002, 2010, 2015, 2020, and 2030. The actual emissions themselves were not used 

other than to develop growth factors since the 2002 NEI upon which the growth projections were 

based was prepared prior to the release of the 2002 Census of Agriculture data which was 

included in the CMU model (version 3.6) used to develop the Base F 2002 VISTAS base year 

inventory. Thus VISTAS Agricultural Sources SIWG decided to use the NEI ammonia inventory 

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projected emissions to develop the 2009 and revised 2018 growth factors used to project 

emission for VISTAS. Details on the NEI inventory and projections can be found at: 

http://www.epa.gov/ttn/chief/ap42/ch09/related/nh3inventorydraft_jan2004.pdf. The actual data 

files for the projected emissions can be found at: 

http://www.epa.gov/ttn/chief/ap42/ch09/related/nh3output01_23_04.zip. 

In order to use the NEI projected emissions as growth factors, several steps were required. These 

steps were as follows: 

1. NEI projected emissions were only available for the years 2002, 2010, 2015, 2020, 

and 2030, thus the first task was to calculate intermediate year emissions for 2009 and 

2018. These values were calculated based on linear interpolation of the existing data. 

2. Once the intermediate emissions were calculated, MACTEC developed emission 

ratios to provide growth factors for 2009 and 2018. Ratios of emissions were 

established relative to the 2002 NEI emissions. 

3. Once the growth factors were established, MACTEC then evaluated whether or not 

all agricultural SCCs within the revised 2002 base year inventory had corresponding 

growth factors. MACTEC established that not all SCCs within the base year 

inventory had growth factors. These SCCs fell into one of two categories: 

a. SCCs that had multiple entries in the NEI but only a single SCC in the 2002 

VISTAS base year inventory. The NEI was established using a process model 

and for some categories of animals, emissions were calculated for several 

aspects of the process. The CMU model version 3.6 which was the basis for 

the VISTAS 2002 Base F inventory did not use a process model. As a 

consequence a mapping of SCCs in the NEI projections and corresponding 

SCCs in the CMU inventory was made and for those SCCs an average growth 

factor was calculated from the NEI projections for use with the corresponding 

SCC in the CMU based 2002 Base F inventory. 

b. There were also State, county, SCC trios in the 2002 VISTAS Base F 

inventory which had no corresponding emissions in the NEI files. For these 

instances, MACTEC first developed State level average growth factors from 

the NEI projections for use in growing these records. Even after developing 

State level average growth factors there were still some State/SCC pairs that 

did not have matching growth. For these records, MACTEC developed 

VISTAS regional average growth factors at the SCC level from the NEI data. 

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4. Once all of the growth factors were developed, they were used to project the 

emissions to 2009 and 2018. Growth factors were first applied at the State, county 

and SCC level. Then remaining records were grown with the State/SCC specific 

growth factors. Finally, any remaining ungrown records were projected at the SCC 

level using the VISTAS regional growth factor. 

For the livestock categories, the NEI emission projections only had data for beef and dairy cattle, 

poultry and swine. Thus for other livestock categories and for fertilizers alternative growth 

factors were required. 

The growth factors for other livestock categories and fertilizers were obtained from growth 

factors used for the IAQTR projections made by the U.S. EPA. The methodology for these 

categories was identical to that used for dairy, beef, poultry and swine with the exception that 

State/SCC and VISTAS/SCC growth factors were not required for these categories since the 

IAQTR data contained State, county and SCC level growth factors. The IAQTR data provided 

growth factors for 1996, 2007, 2010, 2015 and 2020. Linear interpolation was used to develop 

the growth factors for the intermediate years 2009 and 2018 required for the 

VISTAS projections. 

There were a few exceptions to the methods used for projecting agricultural sources for the 

VISTAS projections. These exceptions were: 

1. All swine emissions for North Carolina were maintained at 2002 levels for each 

projection year to capture a moratorium on swine production in that State. 

2. Ammonia growth factors for a few categories (mainly feedlots) were assigned to be the 

same as growth factors for PM emissions from the NEI projections. This assignment was 

made because the CMU model showed emissions from these categories but the NEI 

projections did not show ammonia emissions but did show PM emissions. 

3. No growth factors were found for horse and pony emissions. These emissions were held 

constant at 2002 levels. 

There was no change in this method between Base F and Base G. Thus Base F and Base G 

agricultural emissions are the same in each inventory. Future efforts on the agricultural emissions 

category should look at any changes made to the CMU model to reflect the model farm approach 

used by EPA in their inventory plus any updated growth factors that may be more recent than the 

EPA inventory used to develop growth estimates for Base F/G. 

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2.2.2.2.1 Differences between 2009/2018 

Methodologically, there was no difference in the way that 2009 and 2018 emissions were 

calculated for agricultural area sources. The growth factors were different (due to the linear 

interpolation used to calculate the values) but the calculation methods were identical. In addition 

there was no difference between Base F and Base G for this category. Thus Base F and Base G 

agricultural emissions are the same in each inventory. 

Tables 2.2-1 show the differences between Base F and Base G emissions for all area sources 

(including agricultural sources but excluding fires) for the 2002 base year and 2009 and 2018 by 

State and pollutant. 

Table 2.2-1 2002 Base Year Emissions and Percentage Difference for Base F and Base G 

(based on actual emissions). 

Actual Area 2002 - Base G 

State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC 

AL 83,958 58,318 23,444 393,588 56,654 52,253 182,674 

FL 71,079 37,446 28,872 443,346 58,878 40,491 404,302 

GA 108,083 80,913 36,142 695,414 103,794 57,559 299,679 

KY 66,752 51,135 39,507 233,559 45,453 41,805 95,375 

MS 37,905 58,721 4,200 343,377 50,401 771 131,808 

NC 345,315 161,860 36,550 280,379 64,052 5,412 237,926 

SC 113,714 28,166 19,332 260,858 40,291 12,900 161,000 

TN 89,828 34,393 17,844 212,554 42,566 29,917 153,307 

VA 155,873 43,905 51,418 237,577 43,989 105,890 174,116 

WV 39,546 9,963 12,687 115,346 21,049 11,667 60,443 

Base F 

AL 83,958 59,486 23,444 393,093 73,352 47,074 196,538 

FL 105,849 44,902 29,477 446,821 81,341 40,537 439,019 

GA 107,889 84,230 36,105 695,320 133,542 57,555 309,411 

KY 66,752 51,097 39,507 233,559 52,765 41,805 100,174 

MS 37,905 59,262 4,200 343,377 63,135 771 135,106 

NC 373,585 164,467 48,730 303,492 69,663 7,096 346,060 

SC 113,714 29,447 19,332 260,858 51,413 12,900 187,466 

TN 89,235 35,571 17,829 211,903 49,131 29,897 161,069 

VA 155,873 46,221 51,418 237,577 52,271 9,510 129,792 

WV 39,546 10,779 12,687 115,346 25,850 11,667 61,490 

Percentage Difference (negative values means Base G increased from Base F) 

AL 0.00% 1.96% 0.00% -0.13% 22.76% -11.00% 7.05% 

FL 32.85% 16.61% 2.05% 0.78% 27.62% 0.12% 7.91% 

GA -0.18% 3.94% -0.10% -0.01% 22.28% -0.01% 3.15% 

KY 0.00% -0.07% 0.00% 0.00% 13.86% 0.00% 4.79% 

MS 0.00% 0.91% 0.00% 0.00% 20.17% 0.00% 2.44% 

NC 7.57% 1.59% 24.99% 7.62% 8.05% 23.74% 31.25% 

SC 0.00% 4.35% 0.00% 0.00% 21.63% 0.00% 14.12% 

TN -0.67% 3.31% -0.09% -0.31% 13.36% -0.07% 4.82% 

VA 0.00% 5.01% 0.00% 0.00% 15.84% -1013.45% -34.15% 

WV 0.00% 7.57% 0.00% 0.00% 18.57% 0.00% 1.70% 

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Table 2.2-2 2009 Projection Year Emissions and Percentage Difference for Base F and 

Base G (based on actual emissions). 

Actual Area 2009 - Base G 

State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC 

AL 66,654 64,268 23,930 413,020 58,699 48,228 143,454 

FL 57,011 38,616 28,187 503,230 64,589 36,699 420,172 

GA 94,130 89,212 37,729 776,411 112,001 57,696 272,315 

KY 57,887 53,005 42,088 242,177 46,243 43,087 94,042 

MS 27,184 63,708 4,249 356,324 51,661 753 124,977 

NC 301,163 170,314 39,954 292,443 69,457 5,751 187,769 

SC 90,390 30,555 19,360 278,299 41,613 13,051 146,107 

TN 74,189 35,253 18,499 226,098 44,124 30,577 154,377 

VA 128,132 46,639 52,618 252,488 44,514 105,984 147,034 

WV 31,640 10,625 13,439 115,089 20,664 12,284 55,288 

Base F 

AL 68,882 65,441 26,482 411,614 76,248 17,818 157,405 

FL 101,356 46,950 31,821 507,515 90,487 52,390 462,198 

GA 103,579 92,838 38,876 776,935 146,691 57,377 294,204 

KY 64,806 53,023 42,122 242,345 54,397 40,779 94,253 

MS 37,161 64,289 4,789 356,516 65,321 637 125,382 

NC 332,443 173,187 53,550 317,847 75,570 7,607 252,553 

SC 95,826 31,966 20,852 278,852 54,230 12,945 176,104 

TN 82,196 36,578 19,148 225,650 51,753 29,787 160,265 

VA 133,738 49,173 53,344 252,924 54,587 10,619 120,022 

WV 37,704 11,461 13,816 115,410 25,835 12,156 57,082 

Percentage Difference (negative values means Base G increased from Base F) 

AL 3.24% 1.79% 9.64% -0.34% 23.02% -170.67% 8.86% 

FL 43.75% 17.75% 11.42% 0.84% 28.62% 29.95% 9.09% 

GA 9.12% 3.91% 2.95% 0.07% 23.65% -0.56% 7.44% 

KY 10.68% 0.03% 0.08% 0.07% 14.99% -5.66% 0.22% 

MS 26.85% 0.90% 11.27% 0.05% 20.91% -18.10% 0.32% 

NC 9.41% 1.66% 25.39% 7.99% 8.09% 24.41% 25.65% 

SC 5.67% 4.41% 7.16% 0.20% 23.27% -0.82% 17.03% 

TN 9.74% 3.62% 3.39% -0.20% 14.74% -2.65% 3.67% 

VA 4.19% 5.15% 1.36% 0.17% 18.45% -898.09% -22.51% 

WV 16.08% 7.29% 2.73% 0.28% 20.02% -1.06% 3.14% 

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Table 2.2-3 2018 Projection Year Emissions and Percentage Difference for Base F and Base 

G (based on actual emissions). 

Actual Area 2018 - Base G 

State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC 

AL 59,626 71,915 25,028 445,256 62,323 50,264 153,577 

FL 53,903 40,432 30,708 578,516 72,454 38,317 489,975 

GA 93,827 99,885 41,332 880,199 123,704 59,729 319,328 

KY 54,865 55,211 44,346 256,052 47,645 44,186 103,490 

MS 22,099 69,910 4,483 375,495 53,222 746 140,134 

NC 290,809 180,866 43,865 315,294 71,262 6,085 189,591 

SC 83,167 33,496 20,592 304,251 44,319 13,457 161,228 

TN 68,809 36,291 19,597 246,252 46,692 31,962 182,222 

VA 121,690 50,175 56,158 275,351 46,697 109,380 150,919 

WV 28,773 11,504 14,828 121,549 21,490 12,849 60,747 

Base F 

AL 63,773 73,346 28,754 445,168 82,449 49,975 168,507 

FL 100,952 49,889 35,047 582,832 101,872 59,413 533,141 

GA 105,059 103,911 42,260 880,800 163,925 61,155 342,661 

KY 65,297 55,356 45,597 256,544 57,110 42,326 102,117 

MS 36,425 70,565 5,230 375,931 68,338 831 139,419 

NC 327,871 184,167 60,073 345,275 85,018 8,273 234,207 

SC 89,343 35,082 22,467 304,940 58,441 13,517 196,946 

TN 81,242 37,812 20,928 245,893 55,712 31,047 188,977 

VA 129,037 53,023 56,668 275,790 58,141 11,479 128,160 

WV 36,809 12,390 15,079 121,964 27,088 13,450 62,164 

Percentage Difference (negative values means Base G increased from Base F) 

AL 6.50% 1.95% 12.96% -0.02% 24.41% -0.58% 8.86% 

FL 46.61% 18.96% 12.38% 0.74% 28.88% 35.51% 8.10% 

GA 10.69% 3.87% 2.20% 0.07% 24.54% 2.33% 6.81% 

KY 15.98% 0.26% 2.74% 0.19% 16.57% -4.40% -1.34% 

MS 39.33% 0.93% 14.28% 0.12% 22.12% 10.19% -0.51% 

NC 11.30% 1.79% 26.98% 8.68% 16.18% 26.45% 19.05% 

SC 6.91% 4.52% 8.34% 0.23% 24.16% 0.44% 18.14% 

TN 15.30% 4.02% 6.36% -0.15% 16.19% -2.95% 3.57% 

VA 5.69% 5.37% 0.90% 0.16% 19.68% -852.83% -17.76% 

WV 21.83% 7.15% 1.66% 0.34% 20.66% 4.46% 2.28% 

2.2.3 Changes to Prescribed Fire for 2009/2018 Base G 

Just prior to release of version 3.1 of the VISTAS inventory. several Federal agencies indicated 

that they had plans for increased prescribed fire burning in future years and that the “typical” fire 

inventory would likely not adequately capture those increases (memo from Bill Jackson and 

Cindy Huber, August 13, 2004). However data were not readily available to incorporate those 

changes up through the Base F inventory. As a consequence MACTEC worked with Federal 

Land Managers to acquire the data necessary to provide 2009 and 2018 specific projections for 

the prescribed fire component of the Base G fire inventory. The 2009 and 2018 projections 

developed using the method described below are being used by VISTAS as the 2009 and 2018 

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base case inventories for all States except FL. For FL the supplied data from the FLMs is not 

being used as FL felt that their data adequately reflected current and future prescribed burning 

practices. The “typical” fire projection is the 2002 base prescribed fire projection. 

One of the biggest issues in preparing the projection was how best to incorporate the data. Two 

agencies submitted data: Fish and Wildlife Service (FWS) and Forest Service (FS). FWS 

submitted annual acreage data by National Wildlife Refuge (NWR) and county with estimates of 

acres burned per day for each NWR. FS provided fire-by-fire acreage estimates based on 

mapping projected burning acreage to current 2002 modeling days. However, FWS did not 

submit data for VISTAS original base year preparation process, thus there was no known FWS 

data in the 2002 actual or typical inventories. Thus MACTEC had to develop a method that 

could use the county level data submitted by FWS. 

In addition, despite the fact that the FS submitted fire-by-fire data for the 2002 actual inventory 

and had mapped the projections to current burn days in the 2002 actual inventory, MACTEC 

could not do a simple replacement of those records with the 2009/2018 projections. This 

situation was created because several VISTAS States run a prescribed fire permitting program. 

To avoid double counting, only State data was used in those States for the 2002 actual inventory. 

Thus there were no Federal data in those States since the Federal data could have potentially 

duplicated State-supplied prescribed fire data. In VISTAS States without permit programs, the 

FS supplied data for 2002 was used and those records were marked in database. Thus for those 

States, the FS supplied 2009/2018 data could be directly substituted for the 2002 data. 

The method used by MACTEC to include the FS data applied a county level data approach for 

FS data where a State had a prescribed fire permitting program and a fire-by-fire replacement for 

FS data in States without permit programs. MACTEC used a county level approach for all of the 

FWS data. The approach used for each data set is discussed below. 

For the FWS data MACTEC summed the annual acres burned supplied by the FWS across all 

NWRs in a county. We then subtracted out 2002 acreage for that county from the FWS projected 

acreage annual total to avoid double counting. The remaining acreage was then multiplied by 0.8 

to account for blackened acres instead of the total perimeter acres that were reported. The revised 

total additional FWS acreage was then added to the total county “typical” acreage to determine 

future acreage burned for either 2009 or 2018. MACTEC then allocated the increased acreage to 

current modeling days. The average daily acres burned data provided by FWS per NWR/county 

was used to allocate the acreage to the correct number of days required to burn all of the acres. 

Guidance supplied by FWS indicated that up to three times the average daily acres burned could 

potentially be allocated to any one day. Thus if the estimated acreage per day were 100 acres 

then up to 300 acres could actually be allocated to a particular day. This approach (use of up to 

three times the average daily acres burned) was used if there were an insufficient number of 2002 

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modeling days available to account for all of the acreage increase. MACTEC used an 

incremental approach to using the increase above the base average daily acres. First we used 

twice the average daily acreage if that was sufficient to completely allocate the increased acreage 

over the total number of days available. If that wasn’t sufficient then we used three times the 

average daily acres burned to allocate the acreage. We applied the highest increases to days in 

the database that already had the highest acreage burned since we felt those days were most 

likely to represent days with representative conditions for conducting prescribed burns. 

The approach used by MACTEC for the FS was slightly different. For States that had permit 

programs, we used similar approach to the FWS county level approach. First we summed the FS 

data at county level, we then added that value to the typical acreage and then we allocated the 

acres to current modeling days. The mapping to current modeling days was performed by Bill 

Jackson of the USFS and provided to MACTEC. For States that do not have a prescribed fire 

permit program, MACTEC simply replaced the current fire-by-fire records in the database with 

fire-by-fire records from the FS and recalculated emissions based on fuel model and fuel loading. 

We also applied the same 0.8 correction for blackened acres applied to all FS supplied acreage as 

the supplied values represented perimeter acres. 

An additional problem with developing year-specific prescribed fire projections was how to 

adequately capture the temporal profile for those fires. In the 2002 actual fire inventory, fires 

occur on same days as state/FLM records. In the 2002 “typical” year inventory, fire acreage 

increased or decreased from acreage on the same fire days as were in the 2002 actual inventory, 

since the acres were simply increased for each day based on a multiplier used to convert from 

actual to typical. 

When prescribed fires acreage was added to a future year, MACTEC added acreage to individual 

fire days proportional to the annual increase (if acreage on a day is 10 percent of annual, add 10 

percent of projected increase to that same day). 

The table below shows how the FWS data for Okefenokee NWR were allocated for 2009 for 

Clinch County (Okefenokee NWR is located in four different counties). You can see that the 

total additional acres for the Clinch County portion of Okefenokee NWR was 1,956 acres. Two 

hundred eighty (280) acres were the estimated average daily acres burned for that NWR/county 

combination. Thus to allocate the entire 1,956 acres would require almost 7 burn days (1,956 

divided by 280). However only 5 burn days were found for Clinch County in the 2002 actual fire 

database. Thus we allocated twice the average acreage to the burn day with the most acres 

burned in the 2002 actual fire database (since our method allowed us to increase the average 

daily acres burned up to three times the recommended level). Thus the first burn day received 

560 acres and all others received 280 except the final day which received 276 to make the total 

equal to the required 1,956 acres. The table also indicates that the increased acres burned 

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0

2000

4000

6000

8000

10000

12000

14000

16000

1/1/2002

2/1/2002

3/1/2002

4/1/2002

5/1/2002

6/1/2002

7/1/2002

8/1/2002

9/1/2002

10/1/2002

11/1/2002

12/1/2002

Date of Fire Event

Acres

Typical

FWS Add

USFS Add

provided increases of from 10-48 percent in the acres burned on the individual burn days and an 

average of approximately 14 percent for the year as a whole. 

CLINCH COUNTY 3/1/2002 4/1/2002 2/1/2002 1/1/2002 11/1/2002 12/1/2002

Total 

Annual

Acres (typical) 3,757 2,612 1,996 1,801 616 472 11,764

Add on FWS Projection 560 280 280 280 280 276 1,956

Total 4,316 2,891 2,276 2,080 895 747 13,720

Percent Increase 14.9% 10.7% 14.0% 15.6% 45.5% 58.5% 14.3%

The figure below shows the increases for prescribed burning in the four counties that comprise 

the Okefenokee NWR area (which also includes FS land). In this figure you can see the 

additional acreage added for the burn days from FWS and the individual day increases caused by 

projected increases in prescribed burning based on FS data. It should be noted that while the 

emissions represent 2009, all fire event dates listed are for 2002 to match up with the base year 

meteorology used in modeling exercises. 

Table 2.2-4 shows the percentage difference between the 2009 and 2018 projections developed 

for Base F and Base G. Base G includes the revised prescribed burning estimates described 

above. Values are calculated using Base F as the basis for change, thus negative values imply an 

increase in emissions for Base G. 

Figure 2.2-1 Prescribed Fire Projection for Okeefenokee NWR for 2009 

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Table 2.2-4 Percentage Difference Between Base F and Base G Fire Emissions by State 

State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC CO NH3 NOX PM10-PRI 

2009 Fires Base G 2018 Fires Base G AL 534,873 2,050 11,901 52,851 46,543 2,681 27,502 535,658 2,054 11,918 52,927 FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 GA 637,177 2,229 14,243 63,973 57,116 2,914 34,710 637,177 2,229 14,243 63,973 KY 31,810 143 682 3,093 2,653 187 1,497 33,296 150 714 3,237 MS 48,160 217 1,033 4,683 4,016 283 2,266 50,037 225 1,073 4,865 NC 96,258 433 2,065 9,359 8,027 566 4,530 111,266 501 2,387 10,819 SC 282,307 1,039 5,899 29,153 25,955 1,359 16,045 282,307 1,039 5,899 29,153 TN 17,372 78 373 1,689 1,449 102 817 18,860 85 405 1,834 VA 21,130 95 453 2,054 1,762 124 994 26,923 121 578 2,618 WV 3,949 18 85 384 329 23 186 5,013 23 108 487 2009 Fires Base F 2018 Fires Base F AL 514,120 1,957 11,456 50,833 44,812 2,559 26,526 514,120 1,957 11,456 50,833 FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 GA 620,342 2,153 13,882 62,336 55,712 2,815 33,918 620,342 2,153 13,882 62,336 KY 56,686 110 1,460 6,667 6,310 136 3,338 56,686 110 1,460 6,667 MS 128,471 177 3,328 14,693 13,680 100 13,625 128,471 177 3,328 14,693 NC 200,564 324 5,005 20,488 19,491 423 12,499 200,564 324 5,005 20,488 SC 253,005 908 5,270 26,304 23,511 1,187 14,666 253,005 908 5,270 26,304 TN 78,370 46 2,232 8,875 8,730 59 5,153 78,370 46 2,232 8,875 VA 19,159 159 978 18,160 17,361 99 912 19,159 159 978 18,160 WV 32,656 12 944 3,276 3,239 16 2,184 32,656 12 944 3,276 Percentage Difference (negative number means an increase in Base G emissions) AL -4.04% -4.77% -3.89% -3.97% -3.86% -4.77% -3.68% -4.19% -4.95% -4.03% -4.12% FL 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% GA -2.71% -3.52% -2.60% -2.63% -2.52% -3.52% -2.34% -2.71% -3.52% -2.60% -2.63% KY 43.88% -29.52% 53.25% 53.61% 57.96% -37.90% 55.15% 41.26% -35.57% 51.07% 51.44% MS 62.51% -22.07% 68.95% 68.13% 70.64% -183.85% 83.37% 61.05% -26.83% 67.74% 66.89% NC 52.01% -33.75% 58.74% 54.32% 58.82% -33.75% 63.76% 44.52% -54.60% 52.31% 47.19% SC -11.58% -14.52% -11.93% -10.83% -10.39% -14.52% -9.40% -11.58% -14.52% -11.93% -10.83% TN 77.83% -69.40% 83.30% 80.97% 83.41% -74.42% 84.14% 75.93% -83.92% 81.87% 79.34% VA -10.29% 40.36% 53.67% 88.69% 89.85% -25.40% -9.03% -40.53% 24.00% 40.97% 85.59% WV 87.91% -48.65% 91.03% 88.28% 89.83% -49.46% 91.49% 84.65% -88.70% 88.61% 85.12% 

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2.2.4 Quality Assurance steps 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, to ensure that a full and complete 

inventory was developed for VISTAS, and to make sure that projection calculations were 

working correctly. Quality assurance was an important component to the inventory development 

process and MACTEC performed the following QA steps on the stationary and agricultural area 

source components of the 2009 and revised 2018 projection inventories: 

1. All final files were run through EPA’s Format and Content checking software. 

2. SCC level emission summaries were prepared and evaluated to ensure that emissions 

were consistent and that there were no missing sources. 

3. Tier comparisons (by pollutant) were developed between the 2002 base year 

inventory and the 2009 and 2018 projection inventories. In addition, total VISTAS 

pollutant summaries were prepared to compare total emissions by pollutant between 

versions of the inventory (e.g., between Base F and Base G). 

4. Data product summaries were provided to both the VISTAS Emission Inventory 

Technical Advisor and to the SIWG representatives for review and comment. 

Changes based on these comments were implemented in the files. 

5. Version numbering was used for all inventory files developed. The version 

numbering process used a decimal system to track major and minor changes. For 

example, a major change would result in a version going from 1.0 to 2.0. A minor 

change would cause a version number to go from 1.0 to 1.1. Minor changes resulting 

from largely editorial changes would result in a change from 1.00 to 1.01. 

2.3 Mobile Sources 

Our general approach for assembling data was to use as much existing data from the pre-Base F 

preliminary projections as possible for these inventories, supplement these data with easily 

available stakeholder input, and provide the results for stakeholder review to ensure credibility. 

To develop the “base case” projections, MACTEC originally assembled data to develop two 

2009 and 2018 base case inventories: 1) an inventory that included all “on-the-books” control 

programs and 2) an “on-the-way” inventory that included controls that were likely to be “on-theway”. For the Base F and Base G emission forecasts to the mobile source sector, “on-the-books” 

and “on-the-way” are defined with the same strategies and therefore only a single projection 

scenario was developed for each forecast year. 

To ensure consistency across evaluation years, the 2009 and 2018 base case inventories were 

developed, to the maximum extent practical, using methodologies identical to those employed in 

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developing the 2002 on-road portion of the revised 2002 VISTAS base year inventory. All 

modifications to the 2002 inventory methods were developed in consultation with the Mobile 

Source Special Interest Workgroup (MSSIWG). Generally, modifications were only made to 

properly account for actual changes expected in the intervening period (i.e., between 2002 and 

2009 and between 2002 and 2018), but the underlying inventory development methodology was 

identical, except to the extent requested by VISTAS or the MSSIWG. 

MACTEC developed a preliminary 2018 inventory in early 2004. That inventory was designed 

to 1) be used for modeling sensitivity evaluations and 2) help establish the methods that would 

be used for the final 2018 inventory and the initial 2009 inventory. Since that work took place 

prior to the revision of the 2002 base year inventory data files, MACTEC provided a review of 

the data and methods used to develop on-road mobile source input files for the initial 2002 base 

year inventory prior to developing the preliminary 2018 inventory. Through this review, 

MACTEC determined the following: 

• On-road VMT. Most States provided local data for 2002 (or a neighboring year that 

was converted to 2002 using appropriate VMT growth surrogates such as population). 

Since these data were not applicable to 2018 due to intervening growth, input for 

2018 was solicited from the MSSIWG. At the same time we researched countyspecific growth rate data utilized for recent national rulemakings as a backstop 

approach to State supplied VMT projections. 

• Modeling Temperatures. Actual 2002 temperatures were used for the initial 2002 base 

year inventory. 

• Vehicle Registration Mix (age fractions by type of vehicle). A mix of State, local, and 

MOBILE6 default data were used for the 2002 initial base year inventory. Forecast 

data were solicited from the States, with a fallback position that we hold the fractions 

constant at their 2002 values. 

• Vehicle Speed by Roadway Type. For the 2002 initial base year inventory, speeds 

varying by vehicle and road type were used. 

• VMT Mixes (fraction of VMT by vehicle type). A mix of State, local, and quasi 

MOBILE6 default (i.e., MOBILE6 defaults normalized to better reflect local 

conditions) data were used for the 2002 initial base year inventory. Forecast data were 

solicited from the States. 

• Diesel Sales Fractions. As with the VMT mix data, the diesel sales fraction data 

employed for the 2002 initial base year inventory represents a mix of State, local, and 

quasi MOBILE6 default data. The issues related to updating these data to 2018 are 

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also similar, but are complicated by the fact that MOBILE6 treats diesel sales fraction 

on a model year, rather than age specific basis. Therefore, diesel sales fractions 

generally cannot be held constant across time. Once again, we solicited any local 

projections, with a fallback position that we would keep the data for 2002 and earlier 

model years constant for the forecast inventory, supplemented with MOBILE6 

default data for 2003 and newer model years. 

• State/Local Fuel Standards. For the 2002 initial base year inventory, these data were 

based on appropriate local requirements and updated data for 2018 was only required 

if changes were expected between 2002 and 2018. There are some national changes in 

required fuel quality for both on-road and non-road fuels that are expected to occur 

between 2002 and 2018 and these would be reflected in the 2018 inventory in the 

absence of more stringent local fuel controls. Expected changes in local fuel control 

programs were solicited. 

• Vehicle Standards. The 2002 initial base year inventory assumed NLEV applicability. 

This was altered to reflect Tier 2 for 2018, unless a State indicated a specific plan to 

adopt the California LEV II program. If so, we made the required changes to 

implement those plans for the preliminary 2018 inventory. 

• Other Local Controls. This includes vehicle emissions inspection (i.e., I/M) programs, 

Stage II vapor recovery programs, anti tampering programs, etc. By nature, the 

assumptions used for the 2002 initial base year inventory vary across the VISTAS 

region, but our presumption is that these data accurately reflected each State’s 

situation as it existed in 2002. If a State had no plans to change program requirements 

between 2002 and 2018, we proposed to maintain the 2002 program descriptions 

without change. However, if a State planned changes, we requested information on 

those plans. In the final implementation of the Base F and earlier inventories, Stage II 

controls were exercised in the area source component of the inventory, since the units 

used to develop Stage II refueling estimates are different between MOBILE6 and the 

NONROAD models. However, in the Base G inventories, Stage II refueling was 

moved to the on-road and non-road sectors. 

Once the preliminary 2018 (pre-Base F) base case projection inventory data were compiled, 

MACTEC applied the data and methods selected and proceeded to develop the preliminary (prebase F) base case 2018 projection inventories. The resulting inventories were provided to the 

MSSIWG in a user-friendly format for review. After stakeholder review and comment, the final 

preliminary 2018 base case inventories and input files were provided to VISTAS in formats 

identified by the VISTAS Technical Advisor (in this case, MOBILE input files and VMT, 

NONROAD input files and annual inventory files for NONROAD in NIF 3.0 format). Annual 

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inventory files for MOBILE were not developed as part of this work, only input files and VMT 

forecasts. MOBILE emissions were calculated by VISTAS air quality modeling contractor using 

the provided files. 

2.3.1 Development of on-road mobile source input files 

As indicated above, MACTEC prepared a preliminary version of the 2018 base case mobile 

inventory input data files. These files were then updated to provide a final set of 2018 base case 

inventory input data files as well as a set of input files for 2009. The information below describes 

the updates performed on the preliminary 2018 files and the development of the 2009 input 

data files for Base F emission estimation. 

Our default approach to preparing the revised 2018 and initial 2009 projection inventories for onroad mobile sources was to estimate the emissions by using either: 

1. the revised 2002 data provided by each State coupled with the projection methods 

employed for the preliminary 2018 inventory, or 

2. the same data and methods used to generate the preliminary 2018 inventory. 

We also investigated whether or not there was more recent VMT forecasting data available (e.g., 

from the CAIR and if appropriate revised the default VMT growth rates accordingly. This did 

not affect any State that provided local VMT forecasting data, but would alter the VMT 

estimates used for other areas. 

Since no preliminary 2009 inventory was developed there did not exist an option (2) above for 

2009. As a consequence, MACTEC crafted the 2009 initial inventory for on-road mobile sources 

using methods identical to those employed for the 2018 preliminary inventories coupled with any 

changes/revisions provided by the States during the review of the revised 2002 base year and the 

2018 preliminary inventories. Therefore, as was the case for 2018, we obtained from the States 

any input data revisions, methodological revisions, and local control program specifications (to 

the extent that they differed from 2002/2018). 

2.3.1.1 Preparation of revised 2018 input data files 

Preparation of the revised 2018 inventories required the following updates: 

1. The evaluation year was updated to 2018 in all files. 

2. The diesel fuel sulfur content was revised from 500 ppm to 11 ppm, consistent with 

EPA data for 2018 in all files. 

3. Since the input data is model year, rather than age, specific for diesel sales fractions 

(with data for the newest 25 model years required), we updated all files that included 

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diesel sales fractions. In the revised 2002 base year files, the data included applied to 

model years 1978-2002. For 2018, the data included would reflect model years 1994-

2018. To forecast the 2002 data, MACTEC took the data for 1994-2002 from the 

2002 files and added data for 2003-2018. To estimate the data for these years, we 

employed the assumption employed by "default" in MOBILE6 -- namely that diesel 

sales fractions for 1996 and later are constant. Therefore, we set the diesel sales 

fractions for 2003-2018 at the same value as 2002. 

4. VMT mix fractions must be updated to reflect expected changes in sales patterns 

between 2002 and 2018. If explicit VMT mix fractions are not provided, these 

changes are handled internally by MOBILE6 or externally through absolute VMT 

distributions. However, files that include explicit VMT mix fractions override the 

default MOBILE6 update and may or may not be consistent with external VMT 

distributions. MACTEC updated the VMT mix in such files as follows: 

First, we calculated the VMT fractions for LDV, LDT1, LDT2, HDV, and MC 

from the external VMT files for 2018. This calculation was performed in 

accordance with section 5.3.2 of the MOBILE6 Users Guide which indicates: 

LDV = LDGV + LDDV 

LDT1 = LDGT1 + LDDT 

LDT2 = LDGT2 

HDV = HDGV + HDDV 

MC = MC 

The resulting five VMT fractions were then split into the 16 fractions required by 

MOBILE6 using the distributions for 2018 provided in Appendix D of the 

MOBILE6 Users Guide. This approach ensures that explicit input file VMT 

fractions are consistent with the absolute VMT distributions prepared by 

MACTEC. These changes were made to all files that included VMT mixes. 

5. All other input data were retained at 2002 values, except as otherwise instructed by 

the States. This includes all control program descriptions (I/M, Anti-Tampering 

Program [ATP], Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all 

other vehicle descriptive data (registrations age distributions, etc.), and all scenario 

descriptive data. The State-specific updates performed are described below. 

Kentucky:

MACTEC revised the 2018 input files for the Louisville, Kentucky area (Louisville Air Pollution 

Control District [APCD]) based on comments received relative to several components of 

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MOBILE input data. Based on these comments, the input files for Jefferson County, Kentucky 

were updated accordingly as follows: 

a) I/M and tampering program definitions were removed since the program was 

discontinued at the end of 2003. 

b) The "Speed VMT", "Facility VMT" and "Registration Age Distribution" file pointers 

were updated to reflect revised 2002 files provided by the Louisville APCD. 

c) The "VMT Mix" data, which was previously based on the default approach of 

"growing" 2002 data, was replaced by 2018-specific data provided by the Louisville 

APCD. 

North Carolina:

North Carolina provided a wide range of revised input data, including complete MOBILE6 input 

files for July modeling. MACTEC did not use the provided input files directly as they did not 

match the 2002 NC input files for critical elements such as temperature distributions and 

gasoline RVP (while they were close, they were slightly different). To maintain continuity 

between 2002 and 2018 modeling, MACTEC instead elected to revise the 2002 input files to 

reflect all control program and vehicle-related changes implied by the new 2018 files, while 

retaining the basic temperature and gasoline RVP assumptions at their 2002 values. Under this 

approach, the following changes were made: 

a) NC provided a county cross reference file specific to 2018 that differed from that 

used for 2002. We removed files that were referenced in the 2002 input data and 

replaced those files with those referenced in the 2018 data. In addition, since NC only 

provided 2018 input files for July, we estimated the basic data for these new files for 

the other months by cross referencing the target files for 2002 by county against the 

target files for 2018 by county. 

b) We then revised the 2002 version of each input file to reflect the 2018 "header" data 

included in the NC-provided 2018 files. These data are exclusively limited to I/M and 

ATP program descriptions, so that the 2002 I/M and ATP data were replaced with 

2018 I/M and ATP data. 

c) We retained the registration age fractions at their 2002 "values" (external file 

pointers) as per NC instructions. 

d) We retained all scenario-specific data (i.e., temperatures, RVP, etc.) at 2002 values, 

which (as indicated above), were slightly different in most cases from data included 

in the 2018 files provided by NC. We believe these differences were due to small 

deviations between the data assembled to support VISTAS 2002 and the process used 

to generate the 2018 files provided by NC, and that revising the VISTAS 2002 data to 

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reflect these variations was not appropriate given the resulting inconsistencies that 

would be reflected between VISTAS 2002 and VISTAS 2018. 

e) NC also provided non-I/M versions of the 2018 input files that would generally be 

used to model the non-I/M portion of VMT. While these files were retained they were 

not used for the 2018 input data preparation. 

Finally, NC also provided a speed profile file and a speed profile cross reference file for 2018. 

We did not use these in our updates as they have no bearing on the MOBILE6 input files, but 

they were maintained in case they needed to be included in SMOKE control files for a future 

year control strategy scenario. 

Virginia:

In accordance with instructions from VA, the input files that referenced an external I/M 

descriptive program file (VAIM02.IM) were revised to reference an alternative external file 

(VAIM05.IM). This change was to make the I/M program more relevant to the year 2018. 

One additional important difference was made with respect to the revised 2018 and initial 2009 

on-road mobile source input data files for all States. MACTEC developed updated SMOKE 

ready input files rather than MOBILE6 files so that the input data could be used directly by the 

VISTAS modeling contractor to estimate on-road mobile source emissions during modeling runs. 

2.3.1.2 Preparation of initial 2009 input data files 

The methodology used to develop the 2009 on-road input files was based on forecasting the 

previously developed revised 2002 base year input files and is identical to that previously 

described for the revised 2018 methodology except as follows: 

1. The evaluation year was updated to 2009. 

2. Diesel fuel sulfur content was revised from 500 ppm to 29 ppm. The 29 ppm value 

was derived from an EPA report entitled "Summary and Analysis of the Highway 

Diesel Fuel 2003 Pre-compliance Reports" (EPA420-R-03-013, October 2003), 

which includes the Agency's estimates for the year-to-year fuel volumes associated 

with the transition from 500 ppm to 15 ppm diesel fuel. According to Table 2 of the 

report, there will be 2,922,284 barrels per day of 15 ppm diesel distributed in 2009 

along with 110,488 barrels per day of 500 ppm diesel. Treating the 15 ppm diesel as 

11 ppm on average (consistent with EPA assumptions and assumptions employed for 

the 2018 input files) and sales weighting the two sulfur content fuels results in an 

average 2009 diesel fuel sulfur content estimate of 29 ppm. 

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3. Diesel sales fractions were updated identically to 2018 except that the diesel sales 

fractions for 2003-2009 were set at the same value as those for 2002 (rather than 

2003-2018). 

4. VMT mix fractions were updated to 2009 using an identical method to that described 

for 2018. 

5. All other input data were retained at 2002 values, except as otherwise instructed by 

individual States (see below). This includes all control program descriptions (I/M, 

ATP, Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all other vehicle 

descriptive data (registration age distributions, etc.), and all scenario descriptive data. 

In addition to the updates described above that were applied to all VISTAS-region inputs, the 

following additional State-specific updates were performed: 

KY – Identical changes to those made for 2018 (but specific to 2009) were made for the 

2009 input files. 

NC – Identical changes to those made for 2018 (but specific to 2009) were made for the 2009 

input files. 

VA – Identical changes to those made for 2018 were made for 2009. 

2.3.2 VMT Data 

The basic methodology used to generate the 2009 and 2018 VMT for use in estimating on-road 

mobile source emissions was as follows: 

1. All estimates start from the final VMT estimates used for the 2002 revised base year 

inventory. 

2. Initial 2009 and 2018 VMT estimates were based on linear growth rates for each State, 

county, and vehicle type as derived from the VMT data assembled by the U.S. EPA for 

their most recent HDD (heavy duty diesel) rulemaking. The methodology used to derive 

the growth factors is identical to that employed for the preliminary 2018 VMT estimates 

(which is described in the next section). 

3. For States that provided no independent forecast data, the estimates derived in step 2 are 

also the final estimates. These States are: Alabama, Florida, Georgia, Kentucky, 

Mississippi, and West Virginia. For States that provided forecast data, the provided data 

were used to either replace or augment the forecast data based on the HDD rule. These 

States, and the specific approaches employed, are detailed following the growth method 

description. 

The steps involved in performing the growth estimates for VMT were as follows: 

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1. Linear growth estimates were used (although MACTEC investigated the potential use of 

nonlinear factors and presented that information to the MSSIWG, the decision was made 

to use linear growth factors instead of nonlinear). 

2. Estimates were developed at the vehicle class (i.e., LDGV, LDGT1, LDGT2, etc.) level 

of detail since the base year 2002 estimates were presented at that level of resolution. In 

effect, the county and vehicle class specific growth factors were applied to the 2002 

VMT estimates for each vehicle and road class. 

3. Overall county-specific VMT estimates for each year (developed by summing the vehicle 

and road class specific forecasts) were then compared to overall county-specific growth. 

Since overall county growth is a more appropriate controlling factor as it includes the 

combined impacts of all vehicle classes, the initial year-specific vehicle and road class 

VMT forecasts were normalized so that they matched the overall county VMT growth. 

Mathematically, this process is as follows: 

(Est_rv_f) = (Est_rv_i) * (C_20XX / Sum(Est_rv_i)) 

where: 

Est_rv_f = the final road/vehicle class-specific estimates, 

Est_rv_i = the initial road/vehicle class-specific estimates, and 

C_20XX = the county-specific growth target for year 20XX. 

Table 2.3-1 presents a basic summary of the forecasts for the preliminary 2018 inventory for 

illustrative purposes: 

Table 2.3-1 2002 versus 2018 VMT (million miles per year) 

State 2002 2018 Growth Factor 

Alabama 55,723 72,966 1.309 

Florida 178,681 258,191 1.445 

Georgia 106,785 148,269 1.388 

Kentucky 51,020 66,300 1.299 

Mississippi 36,278 46,996 1.295 

North Carolina 80,166 110,365 1.377 

South Carolina 47,074 63,880 1.357 

Tennessee 68,316 91,647 1.342 

Virginia 76,566 102,971 1.345 

West Virginia 19,544 24,891 1.274 

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The following States provided some types of forecast data for VMT. The information presented 

below indicates how those data were processed by MACTEC for use in the VISTAS projection 

inventories. 

Kentucky: 

Revised 2009 and 2018 VMT mix data were provided by the Louisville APCD. Therefore, the 

distribution of Jefferson County VMT by vehicle type within the KY VMT file was revised to 

reflect the provided mix. This did not affect the total forecasted VMT for either Jefferson County 

or the State, but does alter the fraction of that VMT accumulated by each of the eight vehicle 

types reflected in the VMT file. The following procedure was employed to make the 

VMT estimates consistent with the provided 2009/2018 VMT mix: 

a) The 16 MOBILE6 VMT mix fractions were aggregated into the following five vehicle 

types: LDV, LDT1, LDT2, HDV, and MC. 

b) The 8 VMT mileage classes were aggregated into the same five vehicle types (across all 

roadway types) and converted to fractions by normalizing against the total Jefferson 

County VMT. 

c) The ratio of the "desired" VMT fraction (i.e., that provided in the Louisville APCD VMT 

mix) to the "forecasted" VMT fraction (i.e., that calculated on the basis of the forecasted 

VMT data) was calculated for each of the five vehicle classes. 

d) All forecasted VMT data for Jefferson County were multiplied by the applicable ratio 

from step c as follows: 

new LDGV = old LDGV * LDV ratio 

new LDGT1 = old LDGT1 * LDT1 ratio 

new LDGT2 = old LDGT2 * LDT2 ratio 

new HDGV = old HDGV * HDV ratio 

new LDDV = old LDDV * LDV ratio 

new LDDT = old LDDT * LDT1 ratio 

new HDDV = old HDDV * HDV ratio 

new MC = old MC * MC ratio 

The total forecasted VMT for Jefferson County was then checked to ensure that it was 

unchanged. 

North Carolina: 

North Carolina provided both VMT and VMT mix data by county and roadway type for 2018. 

Therefore, these data replaced the data developed for North Carolina using HDD rule growth 

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rates in their entirety. Similar data were submitted for 2009. Table 2.3-2 presents the resulting 

VMT estimates which differ from the "default" HDD rule estimates as follows: 

Table 2.3-2 VMT and HDD Rule Estimates for North Carolina (million miles per year) 

North Carolina 

2002 106,795 

State Data HDD Data 

2009 123,396 124,626 

2018 129,552 146,989 

As indicated, there are substantial reductions in the State-provided forecast data relative to that 

derived from the HDD rule. The growth rates for both 2009 and 2018 are only about half that 

implied by the HDD data (1.15 versus 1.17 for 2009 and 1.21 versus 1.38 for 2018). The 

resulting growth rates are the lowest in the VISTAS region. 

NC did not provide VMT mix data for 2009. Therefore, the VMT mix fractions estimated using 

the "default" HDD rule growth rates were applied to the State-provided VMT estimates to 

generate vehicle-specific VMT. Essentially, the default HDD methodology produces VMT 

estimates at the county-road type-vehicle type level of detail, and these data can be converted 

into VMT fractions at that same level of detail. Note that these are not HDD VMT fractions, but 

VMT fractions developed from 2002 NC data using HDD vehicle-specific growth rates. In 

effect, they are 2002 NC VMT fractions "grown" to 2009. 

The default VMT mix fraction was applied to the State-provided VMT data at the county and 

road type level of detail to generate VMT data at the county-road type-vehicle type level of 

detail. The one exception was for county 063, road 110, for which no VMT data were included in 

the HDD rule. For this single county/road combination, State-aggregate VMT mix fractions 

(using the HDD growth methodology) were applied to the county/road VMT data. The difference 

between road 110 VMT fractions across all NC counties is minimal, so there is no effective 

difference in utilizing this more aggregate approach vis-à-vis the more resolved county/road 

approach. 

South Carolina: 

South Carolina provided county and roadway type-specific VMT data for several future years. 

Data for 2018 was included and was used directly. Data for 2009 was not included, but was 

linearly interpolated from data provided for 2007 and 2010. The data were disaggregated into 

vehicle type-specific VMT using the VMT mixes developed for South Carolina using the HDD 

rule VMT growth rates. Table 2.3-3 presents the resulting VMT estimates which differ from the 

"default" HDD rule estimates as follows: 

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Table 2.3-3 VMT and HDD Rule Estimates for South Carolina (million miles per year) 

South Carolina 

2002 47,074 

State Data HDD Data 

2009 55,147 54,543 

2018 65,133 63,880 

Tennessee: 

In general, Tennessee estimates are based on the HDD rule growth rate as described in step two. 

However, Knox County provided independent VMT estimates for 2018 and these were used in 

place of the HDD rule-derived estimates. The Knox County estimates were total county VMT 

data only, so these were disaggregated into roadway and vehicle-type VMT using the 

distributions developed for Knox County in step two using the HDD rule VMT growth rates. No 

data for Knox County were provided for 2009, so the estimates derived using the HDD rule 

growth factors were adjusted by the ratio of "Knox County provided 2018 VMT" to "Knox 

County HDD Rule-derived 2018 VMT." Table 2.3-4 presents the resulting VMT estimates 

which differ from the "default" HDD rule estimates as follows: 

Table 2.3-4 VMT and HDD Rule Estimates for Tennessee (million miles per year) 

Tennessee 

2002 68,316 

State Data HDD Data 

2009 78,615 78,813 

2018 91,417 91,647 

Virginia: 

Virginia provided county and roadway type-specific annual VMT growth rates and these data 

were applied to Virginia -provided VMT data for 2002 to estimate VMT in both 2009 and 2018. 

Virginia provided VMT mix data for 2002, but not 2009 or 2018. Therefore, the estimated VMT 

data for both 2009 and 2018 were disaggregated into vehicle type-specific VMT using the VMT 

mixes developed for VA using the HDD rule VMT growth rates. Table 2.3-5 presents the 

resulting VMT estimates which differ from the "default" HDD rule estimates as follows: 

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Table 2.3-5 VMT and HDD Rule Estimates for Virginia (million miles per year) 

Virginia 

2002 77,472 

State Data HDD Data 

2009 88,419 89,196 

2018 104,944 104,164 

2.3.3 Base G Revisions 

For the development of the VISTAS 2009 and 2018 Base G inventories and input files, VISTAS 

states reviewed the Base F inputs, and provided corrections, updates and supplemental data as 

noted below. 

For all states modeled, the Base G updates include: 

• Adding Stage II refueling emissions calculations to the SMOKE processing. 

• Revised the HDD compliance. (REBUILD EFFECTS = .1) 

• Revised Diesel sulfur values in 2009 to 43 ppm and 2018 to 11 ppm 

In addition to the global changes, individual VISTAS states made the following updates: 

KY – updated VMT and M6 input values for selected counties 

NC – revised VMT estimates, speeds and vehicle distributions and updated registration 

distributions for Mobile 6. 

TN - revised VMT and vehicle registration distributions for selected counties. 

WV – revised VMT input data 

AL, FL, and GA and VA did not provide updates for 2009/2018 Base G, and the Base F inputs 

were used for these States. 

2.3.4 Development of non-road emission estimates 

The sections that follow describe the projection process used to develop 2009 and 2018 non-road 

projection estimates, as revised through the spring of 2006, for sources found in the NONROAD 

model and those sources estimated outside of the model (locomotives, airplanes and commercial 

marine vessels). 

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2.3.4.1 NONROAD model sources 

NONROAD model input files were prepared in both the fall of 2004 (Base F) and the spring of 

2006 (Base G) based on the corresponding 2002 base year inventory input files available at the 

time the forecasts were developed, with appropriate updates for the projection years. Generally, 

this means that the Base F 2002 base year input files (as updated through the fall of 2004) were 

used as the basis for Base F projection year input file development and Base G 2002 base year 

input files as updated through the spring of 2006 were used as the basis for Base G projection 

year input file development. Thus, all base year revisions are inherently incorporated into the 

associated projection year revisions. Other specific updates for the projection years for 

NONROAD model sources consist of: 

1. Revise the emission inventory year in the model (as well as various output file naming 

commands) to be reflective of the projection year. 

2. Revise the fuel sulfur content for gasoline and diesel powered equipment. 

3. Implement a limited number of local control program charges (national control program 

changes are handled internally within the NONROAD model, so explicit input file changes 

are not required). 

All equipment population growth and fleet turnover impacts are also handled internally within 

the NONROAD model, so that explicit changes input file changes are not required. 

Base F Input File Changes: 

To correctly account for diesel fuel sulfur content differences between the base and projection 

years, two sets of input and output files were prepared for each forecast year, one set for landbased equipment and one set for marine equipment. This two-step projection process was 

required for Base F, because diesel fuel sulfur contents varied between land-based and 

marine-based non-road equipment and the Draft NONROAD2004 used for Base F allowed only 

a single diesel fuel sulfur input. Thus, the model was executed separately for land-based and 

marine-based equipment for Base F, and the associated outputs subsequently combined. The 

specific diesel fuel sulfur contents modeled were as follows: 

Diesel S (ppm) 2002 2009 2018 

 Land-Based 2500 348 11 

 Marine-Based 2500 408 56 

As indicated, the Draft NONROAD2004 model was run with both sets of input files and the 

output file results were then combined to produce a single NONROAD output set. 

To correctly account for the national reduction in gasoline sulfur content (a national control not 

explicitly handled by the NONROAD model), all NONROAD input files for both 2009 and 2018 

were revised to reflect a gasoline fuel sulfur content of 30 ppmW. 

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Base G Input File Changes: 

With the release of Final NONROAD2005 that was used for the Base G projection year 

inventory development, the NONROAD model is capable of handling separate diesel fuel sulfur 

inputs for land-based and marine-based non-road equipment in a single model execution. 

Therefore, the two step modeling process described above for Base F updates was no longer 

required. Instead, the differential diesel fuel sulfur values are assembled into a single 

NONROAD input file as follows: 

Diesel S (ppm) 2002 2009 2018 

 Land-Based 2500 348 11 

 Marine-Based 2638 408 56 

Additionally, revised gasoline vapor pressure data were provided by Georgia regulators for 20 

counties5

 where reduced volatility requirements were established in 2003. Since this requirement 

began after the 2002 base year, the vapor pressure values in the base year input files for these 

counties are not correct for either the 2009 or 2018 forecast years. Therefore, to correctly 

forecast emissions in these counties, the forecast year gasoline vapor pressure inputs were 

revised to: 

Gasoline RVP (psi) 2002 2009 2018 

 Spring 9.87 9.2 9.2 

 Summer 9.0 7.0 7.0 

 Fall 9.87 9.2 9.2 

 Winter 12.5 12.5 12.5 

The summer vapor pressure was simply set equal to the 2003 control value, while the spring and 

fall vapor pressures were adjusted to reflect a single month of the reduced volatility limit. The 

winter volatility was assumed to be unaffected by the summertime control requirement. 

2.3.4.1.1 Differences between 2009/2018 

Other than diesel fuel sulfur content and the year of the projections, there are no differences in 

the methodology used to estimate emissions from NONROAD model sources. As indicated 

above, however the Base F 2009/2018 projections were developed using Draft NONROAD2004, 

while the Base G 2009/2018 projections were made using Final NONROAD2005. 

 

5

 The specific counties are: Banks, Chattooga, Clarke, Floyd, Gordon, Heard, Jasper, Jones, Lamar, Lumpkin, 

Madison, Meriwether, Monroe, Morgan, Oconee, Pike, Polk, Putnam, Troup, and Upson. 

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2.3.4.2 Non-NONROAD model sources 

Using the 2002 base year emissions inventory for aircraft, locomotives, and commercial marine 

vessels (CMV) prepared as described earlier in this document, corresponding emission 

projections for 2009 and 2018 were developed in both the fall of 2004 (Base F) and the spring of 

2006 (Base G). This section describes the procedures employed in developing those inventories. 

The information presented is intended to build off of that presented in the section describing the 

2002 Base F base year inventory. It should be recognized that for both the Base F and Base G 

inventories, the base year inventory used to develop the emission forecasts was the latest 

available at the time of forecast development. Generally, this means that the 2002 base year 

inventory as updated through the fall of 2004 was used as the basis for the Base F projection year 

inventory development, and the Base F 2002 base year inventory was used as the basis for Base 

G projection year inventory development. Thus, all base year revisions (as described earlier in 

this document) are inherently incorporated into the associated projection year revisions. 

Base F Revisions: 

Table 2.3-6 shows the 2002 base year emissions for each State in the VISTAS region for aircraft, 

locomotives and CMV (as they existed prior to Base F development). 

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Table 2.3-6. Pre-Base F 2002 Aircraft, Locomotive, and Non-Recreational 

Marine Emissions 

(annual tons, as of the fall of 2004)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 3,787 175 226 87 17 196 

FL 25,431 8,891 2,424 2,375 800 3,658 

GA 6,620 5,372 1,475 1,446 451 443 

KY 2,666 657 179 175 63 263 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 7,251 2,766 734 719 235 943 

VA 9,763 2,756 1,137 1,115 786 2,529 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 70,882 22,899 7,072 6,797 2,607 9,670 

AL 1,196 9,218 917 844 3,337 737 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,875 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,688 43,233 1,903 1,751 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 3,624 27,555 1,217 1,120 4,974 860 

VA 972 2,775 334 307 359 483 

WV 1,528 11,586 487 448 525 362 

Commercial 

Marine 

(2280) 

Total 28,207 209,972 9,911 9,118 36,275 7,413 

Military Marine VA 110 313 25 23 27 48 

(2283) Total 110 313 25 23 27 48 

AL 3,490 26,339 592 533 1,446 1,354 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 2,626 25,627 633 570 1,439 1,041 

VA 1,186 11,882 1,529 1,375 3,641 492 

WV 1,311 13,224 329 296 808 517 

Locomotives 

(2285) 

Total 19,540 187,044 5,815 5,232 14,022 7,750 

Grand Total 118,739 420,228 22,823 21,170 52,931 24,881 

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Although some of the data utilized was updated, the methodology used to develop the Base F 

2009 and 2018 emissions forecasts for aircraft, locomotives, and CMV is identical to that used 

earlier to develop preliminary 2018 Base 1 (“On the Books”) and 2018 Base 2 (“On the Way”) 

inventories. Briefly, the methodology relies on growth and control factors developed from 

inventories used in support of recent EPA rulemakings, and consists of the following steps: 

(a) Begin with the 2002 base year emission estimates for aircraft, locomotive, and CMV as 

described above (at the State-county-SCC-pollutant level of detail). 

(b) Detailed inventory data (both before and after controls) for these same emission sources 

for 1996, 2010, 2015, and 2020 were obtained from the EPA's Clean Air Interstate Rule 

(CAIR) Technical Support Document (which can be found at 

http://www.epa.gov/cair/pdfs/finaltech01.pdf). Using these data, combined growth and 

control factors for the period 2002-2009 and 2002-2018 were estimated using straight 

line interpolation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This 

is done at the State-county-SCC-pollutant level of detail. 

(c) The EPA growth and control data are matched against the 2002 VISTAS base year data 

using State-county-SCC-pollutant as the match key. Ideally, there would be a one-to-one 

match and the process would end at this point. Unfortunately, actual match results were 

not always ideal, so additional matching criteria were required. For subsequent reference, 

this initial (highest resolution) matching criterion is denoted as the “CAIR-Primary” 

criterion. 

(d) A second matching criterion is applied that utilizes a similar, but higher-level SCC (lower 

resolution) matching approach. For example, SCC 2275020000 (commercial aircraft) in 

the 2002 base year inventory data would be matched with SCC 2275000000 (all aircraft) 

in the CAIR data. This criterion is applied to records in the 2002 base year emissions file 

that are not matched using the “CAIR-Primary” criterion, and is also performed at the 

State-county-SCC-pollutant level of detail. For subsequent reference, this is denoted as 

the “CAIR-Secondary” criterion. At the end of this process, a number of unmatched 

records remained, so a third level matching criterion was required. 

(e) In the third matching step, the most frequently used SCC in the EPA CAIR files for each 

of the aircraft, locomotive, and commercial marine sectors was averaged at the State level 

to produce a “default” State and pollutant-specific growth and control factor for the 

sector. The resulting factor is used as a “default” growth factor for all unmatched 

county-SCC-pollutant level data in each State. In effect, State-specific growth data are 

applied to county level data for which an explicit match between the VISTAS 2002 base 

year data and EPA CAIR data could not be developed. The default growth and control 

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SCCs are 2275020000 (commercial aircraft) for the aircraft sector, 2280002000 

(commercial marine diesel total) for the CMV sector, and 2285002000 (railroad 

equipment diesel total) for the locomotive sector. Matches made using this criterion are 

denoted as “CAIR-Tertiary” matches. 

(f) According to EPA documentation, the CAIR baseline emissions include the impacts of 

the (then proposed) Tier 4 (T4) non-road diesel rulemaking, which implements a low 

sulfur fuel requirement that affects both future CMV and locomotive emissions. 

However, the impacts of this rule were originally intended to be excluded from the initial 

VISTAS 2018 forecast, which was to include only “on-the-books” controls. (The T4 rule 

was finalized subsequent to the development of the preliminary 2018 inventory in March 

of 2004.) Given its final status, T4 impacts were moved into the “on the books” 

inventory for non-road equipment. In addition, since there are no other proposed rules 

affecting the non-road sector between 2002 and 2018, there is no difference between the 

2018 “on the books” and 2018 “on the way” inventories for the sector; so that only a 

single forecast inventory (for each evaluation year) was developed. Nevertheless, since 

the algorithms developed to produce the VISTAS forecasts were developed when there 

was a distinction between the “on the books” and “on the way” inventories, the distinct 

algorithms used to produce the two inventories have been maintained even though the 

conceptual distinctions have been lost. This approach was taken for two reasons. First, it 

allowed the previously developed algorithms to be utilized without change. Second, it 

allowed for separate treatment of the T4 emissions impact which was important as those 

impacts changed between the proposed and final T4 rules. Thus, previous EPA 

inventories that include the proposed T4 impacts would not be accurate. Therefore, the 

procedural discussion continues to reflect the distinctions between non-T4 and T4 

emissions, as these distinctions continue to be intrinsically important to the forecasting 

process. Therefore, a second set of EPA CAIR files that excluded the Tier 4 diesel 

impacts was obtained and the same matching exercise described above in steps (b) 

through (e) was performed using these “No T4” files. It is important to note that the 

matching exercise described in steps (b) through (e) cannot simply be replaced because 

the “No T4” files obtained from the EPA include only those SCCs specifically affected 

by the T4 rule (i.e., diesel CMV and locomotives). So in effect, the matching exercise 

was augmented (rather than replaced) with an additional three criteria analogous to those 

described in steps (c) through (e), and these are denoted as the “No T4-Primary,” “No 

T4-Secondary,” and “No T4-Tertiary” criteria. Because they exclude the impacts of the 

proposed T4 rule, matches using the “No T4” criteria supersede matches made using the 

basic CAIR criteria (as described in steps (c) through (e) above). 

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(g) The CAIR matching criteria were overridden for any record for which States provided 

local growth data. Only North Carolina provided these forecasts, as that State has 

provided specific growth factors for airport emissions in four counties. Because the 

provided data were based on forecasted changes in landings and takeoffs at major North 

Carolina airports, the factors were applied only to commercial (SCC 2275020000) and air 

taxi (SCC 2275060000) emissions. Emissions forecasts for military and general aviation 

aircraft operations, as well as all aircraft operations in counties other than the four 

identified in the North Carolina growth factor submission, continued to utilize the growth 

factors developed according to steps (b) through (f) above. Table 2.3-7 presents the 

locally generated growth factors applied in North Carolina. 

Table 2.3-7 Locally Generated Growth Factors for North Carolina 

FIP 2009 Factor 2018 Factor 

37067 0.71 0.84 

37081 0.97 0.89 

37119 1.15 1.01 

37183 0.88 0.81 

Note: 

Growth factor = Year Emissions/2002 Emissions. 

Under CAIR approach, 2009 = 1.16 to 1.17 for all 4 counties. 

Under CAIR approach, 2018 = 1.36 to 1.37 for all 4 counties. 

(h) Using this approach, each State-county-SCC-pollutant was assigned a combined growth 

and control factor using the EPA CAIR forecast or locally provided data. The 22,838 data 

records for aircraft, locomotives, and CMV in the 2002 revised base year emissions file 

were assigned growth factors in accordance with the following breakdown: 

 48 records matched State-provided growth factors, 

 4,179 records matched using the CAIR-Primary criterion, 

 240 records matched using the CAIR-Secondary criterion, 

 7,463 records matched using the CAIR-Tertiary criterion, 

 720 records matched using the No T4-Primary criterion, 

 3,858 records matched using the No T4-Secondary criterion, and 

 6,330 records matched using the No T4-Tertiary criterion. 

(i) Finally, the impacts of the T4 rule as adopted were applied to the grown “non T4” 

emission estimates. The actual T4 emission standards do not affect aircraft, locomotive, 

or CMV directly, but associated diesel fuel sulfur requirements do affect locomotives and 

CMV. Lower fuel sulfur content affects both SO2 and PM emissions. Expected fuel sulfur 

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contents were obtained for each evaluation year from the EPA technical support 

document for the final T4 rule (Final Regulatory Analysis: Control of Emissions from 

Non-road Diesel Engines, EPA420-R-04-007, May 2004). According to that document, 

the average diesel fuel sulfur content for locomotives and CMV is expected to be 408 

ppmW in 2009 and 56 ppmW in 2018. These compare to expected non-T4 fuel sulfur 

levels of 2599 ppmW in 2009 and 2336 ppmW in 2018. Table 2.3-8 uses calculated 

emissions estimates for base and T4 control scenarios to estimate emission 

reduction impacts. 

Table 2.3-8 Estimated Emission Reduction Impacts based on T-4 Rule 

2009 2018

CMV SO2 = Non-T4 SO2 × 0.1569 0.0241

Locomotive SO2 = Non-T4 SO2 × 0.1569 0.0241

CMV PM = Non-T4 PM × 0.8962 0.8762

Locomotive PM = Non-T4 PM × 0.8117 0.7734

However, since the diesel fuel sulfur content assumed for the 2002 VISTAS base year 

inventory, upon which both the 2009 and 2018 inventories were based, is 2500 ppmW, a 

small adjustment to the emission reduction multipliers calculated from the T4 rule is 

appropriate since they are measured relative to modestly different sulfur contents (2599 

ppmW for 2009 and 2336 ppmW for 2018). Correcting for these modest differences 

produces the emission reduction impact estimates relative to forecasts based on the 

VISTAS 2002 inventory shown in Table 2.3-9. 

Table 2.3-9 Estimated Emission Reduction Impacts Relative to VISTAS 2002 Base 

Year Values 

2009 2018

CMV SO2 = Non-T4 SO2 × 0.1632 0.0225

Locomotive SO2 = Non-T4 SO2 × 0.1632 0.0225

CMV PM = Non-T4 PM × 0.9004 0.8685

Locomotive PM = Non-T4 PM × 0.8187 0.7610

These factors were applied directly to the non-T4 emission forecasts to produce the final 

VISTAS 2009 and 2018 emissions inventories for aircraft, locomotive, and CMV. 

The only exception is for Palm Beach County, Florida, where CMV emissions are 

reported as “all fuels” rather than separately by residual and diesel fuel components. To 

estimate T4 impacts in Palm Beach County, the ratio of diesel CMV emissions to total 

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CMV emissions in the remainder of Florida was calculated and the T4 impact estimates 

for Palm Beach County were adjusted to reflect that ratio. Table 2.3-10 shows the 

calculated diesel CMV ratios. 

Table 2.3-10 Diesel CMV Adjustment Ratios for Palm Beach County, FL 

GROWTH BASIS SO2 PM

2009 (1996, 2020 Growth Basis) 0.2410 0.7861 

2009 (1996, 2010, 2015, and 2020 Growth Basis) 0.1279 0.7875 

2018 (1996, 2020 Growth Basis) 0.2432 0.7925 

2018 (1996, 2010, 2015, and 2020 Growth Basis) 0.2624 0.7918 

The differences between the growth bases are discussed in detail below. 

Combining these ratios with the T4 impact estimates for diesel engines, as presented 

above, yields the following impact adjustment factors for Palm Beach County: 

Table 2.3-11 Overall Adjustment Factors for Palm Beach County, FL 

GROWTH BASIS

2009 SO2 (19, 20 Growth Basis) 0.7894 [0.1632×0.2410+(1-0.2410)]

2009 SO2 (96, 10, 15, and 20 Growth Basis) 0.8930 [0.1632×0.1279+(1-0.1279)] 

2018 SO2 (96, 20 Growth Basis) 0.7623 [0.0225×0.2432+(1-0.2432)] 

2018 SO2 (96, 10, 15, and 20 Growth Basis) 0.7436 [0.0225×0.2624+(1-0.2624)] 

2009 PM (19, 20 Growth Basis) 0.9217 [0.9004×0.7861+(1-0.7861)] 

2009 PM (96, 10, 15, and 20 Growth Basis) 0.9216 [0.9004×0.7875+(1-0.7875)] 

2018 PM (96, 20 Growth Basis) 0.8958 [0.8685×0.7925+(1-0.7925)] 

2018 PM (96, 10, 15, and 20 Growth Basis) 0.8959 [0.8685×0.7918+(1-0.7918)]

The differences between the growth bases are discussed in detail below.

Utilizing this approach, emission inventory forecasts for both 2009 and 2018 were developed. As 

indicated in step (b) above, basic growth factors were developed using EPA CAIR inventory data 

for 1996, 2010, 2015, and 2020. From these data, equivalent EPA CAIR inventories for 2002 and 

2009 were developed through linear interpolation of the 1996 and 2010 inventories, while an 

equivalent CAIR inventory for 2018 was developed through linear interpolation of the 2015 and 

2020 inventories. Growth factors for 2009 and 2018 were then estimated as the ratios of the 

CAIR 2009 and 2018 inventories to the CAIR 2002 inventory. 

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During the development of the preliminary 2018 VISTAS inventory in March 2004, this process 

yielded reasonable results and exhibited no particular systematic concerns. However, when the 

2009 Base F inventory was developed, significant concerns related to SO2 and PM were 

encountered. Essentially, what was revealed by the Base F 2009 forecast was a series of apparent 

inconsistencies in the CAIR 2010 and 2015 emission inventories (as compared to the 1996 and 

2020 CAIR inventories) that were masked during the construction of the “longer-term” 

2018 inventory. 

The apparent inconsistencies are best illustrated by looking at the actual data extracted from the 

CAIR inventory files. Note that although a limited example is being presented, the same general 

issue applies throughout the CAIR files. For FIP 01001 (Autauga County, Alabama) and SCC 

2285002000 (Diesel Rail), the CAIR inventories indicate SO2 emission estimates as shown in 

Table 2.3-12. 

Table 2.3-12 SO2 Emissions for Diesel Rail in Autauga County, AL from the CAIR 

Projections 

YEAR TONS 

1996: 15.3445 

2010: 2.7271 

2015: 2.8178 

2020: 16.6232 

Clearly, there is a major drop in emissions between 1996 and 2010, followed by a major increase 

in emissions between 2015 and 2020. Several observations regarding these changes are 

important. First, the CAIR data were reported to exclude the T4 rule, so that the drop in 

emissions should be related to something other than simply a change in diesel fuel sulfur content. 

Second, if the T4 rule impacts were “accidentally” included in the estimates, there should be a 

resultant 90 percent drop in diesel sulfur between 2010 and 2015; so such inclusion is unlikely. 

Third, the rate of growth between 2015 and 2020 (43 percent per year compound or 97 percent 

per year linear) is well beyond any reasonable expectations for rail service; and fuel sulfur 

content during this period is constant both with and without T4. In short, there appeared to be no 

rational explanation for the data, yet the same basic relations are observed for thousands of CAIR 

inventory records. 

For the most part, the issue seems to be centered on SO2 and PM records, which are those 

records primarily affected by the T4 rule. But, as noted above, there does not seem to be any 

pattern of consistency that would indicate that either inclusion or exclusion of T4 rule impacts is 

the underlying cause. Moreover, where they occur, the observed growth extremes generally 

affect both SO2 and PM equally, while one would expect PM effects to be buffered if the T4 rule 

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was the underlying cause, since changes in diesel fuel sulfur content will only affect a fraction of 

PM (i.e., sulfate), while directly reducing SO2. 

The data presented in Figure 2.3-1 illustrates what this meant to the VISTAS forecasting process. 

Figure 2.3-1 depicts the same data presented above for Autauga County, Alabama, but 

normalized so that the interpolated 2002 CAIR emissions estimate equals unity. The “raw” CAIR 

data is depicted by the markers labeled A, B, C, and D. Interpolated data for 2002 and 2009, 

based on 1996 and 2010 CAIR data, is depicted by the markers labeled “i” and “ii.” Interpolated 

data for 2018, based on 2015 and 2020 CAIR data is depicted by the marker labeled “iii.” The 

relationship between marker “iii” and marker “i” is exactly the relationship used to construct the 

preliminary (e.g., pre-Base F) 2018 VISTAS inventory (i.e., a linear growth rate equal to 0.7 

percent per year). Thus, it is easy to see that although there is a major “dip and rise” between 

2002 and 2018, it is essentially masked unless data for intervening years are examined. Since no 

intervening year was examined for the preliminary 2018 inventory, the “dip and rise” was not 

discovered. However, upon the development of the 2009 inventory forecast, the issue became 

obvious, as the marker labeled “ii” readily illustrates. In effect, the 2009 inventory reflected very 

low negative “growth rates” for some SCCs and pollutants relative to the 2002 inventory, while 

the 2018 inventory reflected very high and positive growth rates for those same SCCs and 

pollutants. In effect, the path between 2002 and 2018 that previously looked like the dotted line 

connecting markers “i” and “iii,” now looks like the solid line connecting markers “i”, “ii,” and 

“iii.” For reference purposes, this path is hereafter referred to as the 1996, 2010, 2015, and 2020 

growth basis, since all interpolated data is based on CAIR data for those four years. 

Figure 2.3-1. Impacts of the Apparent CAIR Inventory Discrepancy 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

1990 1995 2000 2005 2010 2015 2020 2025

Year

Emissions

1

iii

ii

i

D

B C

A

3 2

A,B,C,D = EPA CAIR Data.

i,ii,iii = 96-10-15-20 Interpolations.

1,2,3 = 96-20 Interpolations.

All indicated growth is linear.

i to ii = -9.1%/yr ii to iii = 22.9%/yr

i to iii = 0.7%/yr

1 to 2 to 3 = 0.3%/yr

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In light of the apparent discrepancies inherent in the 1996, 2010, 2015, and 2020 growth basis 

data and the inconsistencies its use would impart into the 2009 and 2018 VISTAS inventories, a 

secondary forecasting method was developed. This second method relies on the apparent 

consistency between the 1996 and 2020 non-T4 CAIR inventories, interpolating equivalent 2002, 

2009, and 2018 inventories solely from these two inventories. In effect, the CAIR inventories for 

2010 and 2015 are ignored. In Figure 2.3-1, this secondary approach is depicted by the data 

points that lie along the lines connecting markers A and D. Markers A and D represent the 1996 

and 2020 CAIR inventories, and the markers labeled 1, 2, and 3 represent the interpolated 2002, 

2009, and 2018 CAIR equivalent inventories. The growth rate between 2009 and 2002 is then 

equal to the ratio of the 2009 and 2002 CAIR inventories, while that between 2018 and 2002 is 

equal to the ratio of the 2018 and 2002 CAIR inventories. For the example data, the resulting 

linear growth estimate is 0.3 percent per year. For reference purposes, this path is hereafter 

referred to as the 1996-2020 growth basis, since all interpolated data are based on CAIR data for 

only those two years. 

It is perhaps worth noting that the only elements of Figure 2.3-1 that have any bearing on the 

VISTAS inventories are the growth rates. The absolute CAIR data are of importance only in 

determining those rates, as all VISTAS inventories were developed on the basis of the VISTAS 

2002 base year inventory, not any of the CAIR inventories. So referring to Figure 2.3-1, the two 

growth options are summarized in Table 2.3-13. 

Table 2.3-13 Growth Options based on CAIR Data 

GROWTH BASIS PERCENT PER YEAR 

1996, 2010, 2015, 2020 Growth Basis: -9.1% per year (linear) between 2002 and 2009 

1996-2020 Growth Basis: +0.3% per year (linear) between 2002 and 2009 

1996, 2010, 2015, 2020 Growth Basis: +22.9% per year (linear) between 2009 and 2018 

1996-2020 Growth Basis: +0.3% per year (linear) between 2009 and 2018 

1996, 2010, 2015, 2020 Growth Basis: +0.7% per year (linear) between 2002 and 2018 

1996-2020 Growth Basis: +0.3% per year (linear) between 2002 and 2018 

Of course, these specific rates are applicable only to the example case (i.e., diesel rail SO2 in 

Autauga County, Alabama), but there are thousands of additional CAIR records that are virtually 

identical from a growth viewpoint. 

While forecast inventories for aircraft, locomotives, and CMV were developed for 2009 and 

2018 using both growth methods, it was ultimately decided to utilize the 1996-2020 growth basis 

for Base F since it provided more reasonable growth rates for 2009. Tables 2.3-14 and 2.3-15 

present a summary of each Base F inventory, while Tables 2.3-16 and 2.3-17 present the 

associated change in emissions for each Base F forecast inventory relative to the Base F 2002 

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base year VISTAS inventory. The larger reduction in CMV SO2 emissions in 2009 and 2018 

(relative to 2002) for Virginia and West Virginia is notable relative to the other VISTAS States, 

but this has been checked and is attributable to a high diesel contribution to total CMV SO2 in 

the 2002 inventories for these two States. 

Figures 2.3-2 through 2.3-13 graphically depict the relationships between the various Base F 

inventories and preliminary 2002 and 2018 projections prepared prior to Base F. There are two 

figures for each pollutant, the first of which presents a comparison of total VISTAS regional 

emission estimates for aircraft, locomotives, and CMV, and the second of which presents total 

VISTAS region emission estimates for locomotives only. This two figure approach is intended to 

provide a more robust illustration of the differences between the various inventories, as some of 

the differences are less distinct when viewed through overall aggregate emissions totals. All of 

the figures include the following emissions estimates: 

• The 2002 Base F base year VISTAS emissions inventory (labeled as “2002”), 

• The 2002 pre-Base F base year VISTAS emissions inventory (labeled as “2002 

Prelim”), 

• The Base F 2009 VISTAS emissions inventory developed using growth rates derived 

from 1996 and 2020 EPA CAIR data (labeled as “2009”), 

• The Base F 2018 VISTAS emissions inventory developed using growth rates derived 

from 1996 and 2020 EPA CAIR data (labeled as “2018”), and 

• The pre-Base F 2018 VISTAS emissions inventory estimates as developed using 

growth rates derived from 1996, 2010, 2015, and 2020 EPA CAIR data (labeled as 

“2018 Prelim”). 

All 12 figures generally illustrate a reduction in emissions estimates between the 2002 pre-Base 

F emission estimates published in February 2004 (the initial 2002 VISTAS inventory) and the 

2002 Base F emission estimates. This reduction generally results from emission updates reflected 

in the State 2002 CERR submittals used to develop the Base F 2002 base year inventory, 

although the major differences in aggregate PM emission estimates are driven to a greater extent 

by modifications in the methodology used to estimate aircraft PM in the Base F 2002 base year 

inventory (as documented under the base year inventory section of this report). 

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Table 2.3-14. Base F 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 4,178 202 278 102 19 217 

FL 29,258 10,316 2,812 2,756 928 4,235 

GA 7,635 6,233 1,712 1,678 523 512 

KY 3,075 762 207 203 73 304 

MS 1,765 162 51 50 16 108 

NC 6,551 1,601 436 427 153 644 

SC 7,372 559 446 437 98 975 

TN 8,020 3,096 824 807 268 1,050 

VA 10,994 3,094 1,239 1,214 907 2,892 

WV 1,312 91 28 28 9 74 

Aircraft 

(2275) 

Total 80,159 26,116 8,033 7,704 2,993 11,011 

AL 1,280 8,888 872 802 2,753 768 

FL 6,236 43,198 1,838 1,691 5,864 1,467 

GA 1,097 7,599 317 291 974 256 

KY 7,087 48,039 2,158 1,985 8,350 1,649 

MS 6,074 41,437 1,821 1,676 6,587 1,415 

NC 634 4,386 184 169 584 148 

SC 1,133 7,796 326 300 1,012 264 

TN 3,887 26,333 1,168 1,074 4,512 904 

VA 1,042 2,662 312 286 61 506 

WV 1,638 11,073 455 419 89 381 

Commercial 

Marine 

(2280) 

Total 30,109 201,412 9,450 8,693 30,786 7,759 

Military Marine VA 118 299 23 21 5 50 

(2283) Total 118 299 23 21 5 50 

AL 3,648 23,529 452 406 242 1,279 

FL 1,052 8,905 189 170 101 382 

GA 2,769 24,398 507 456 271 1,003 

KY 2,264 19,597 415 374 221 819 

MS 2,406 20,785 441 397 239 849 

NC 1,712 14,741 313 282 167 618 

SC 1,213 10,443 222 200 119 437 

TN 2,745 23,924 483 435 240 984 

VA 1,236 11,134 1,167 1,050 608 467 

WV 1,369 12,177 251 226 135 489 

Locomotives 

(2285) 

Total 20,412 169,635 4,440 3,995 2,343 7,328 

Grand Total 130,798 397,462 21,946 20,413 36,126 26,148 

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Table 2.3-15. Base F 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 4,681 236 345 122 23 245 

FL 34,178 12,147 3,312 3,246 1,093 4,976 

GA 8,939 7,340 2,016 1,976 616 601 

KY 3,602 898 244 239 86 357 

MS 1,986 190 60 58 18 122 

NC 6,728 1,454 400 392 139 615 

SC 8,487 616 493 484 112 1,119 

TN 9,009 3,519 939 921 309 1,187 

VA 12,578 3,528 1,370 1,342 1,063 3,358 

WV 1,484 106 33 33 10 85 

Aircraft 

(2275) 

Total 91,670 30,035 9,213 8,814 3,468 12,666 

AL 1,388 8,464 880 809 2,715 809 

FL 6,684 41,117 1,853 1,705 6,248 1,543 

GA 1,174 7,246 319 293 976 269 

KY 7,703 45,174 2,199 2,023 8,383 1,752 

MS 6,571 39,129 1,850 1,702 6,556 1,498 

NC 679 4,179 185 170 596 155 

SC 1,217 7,406 329 303 1,027 278 

TN 4,225 24,763 1,190 1,095 4,808 960 

VA 1,133 2,517 314 289 9 537 

WV 1,781 10,412 459 422 13 404 

Commercial 

Marine 

(2280) 

Total 32,554 190,407 9,578 8,811 31,330 8,205 

Military Marine VA 128 282 23 21 1 53 

(2283) Total 128 282 23 21 1 53 

AL 3,850 19,917 381 343 34 1,183 

FL 1,110 7,538 159 143 14 353 

GA 2,917 21,395 427 385 38 932 

KY 2,389 16,751 352 317 31 757 

MS 2,540 17,594 372 335 34 785 

NC 1,807 12,478 264 237 24 571 

SC 1,280 8,840 187 168 17 404 

TN 2,897 21,735 407 367 34 910 

VA 1,300 10,173 983 885 86 436 

WV 1,444 10,831 212 190 19 453 

Locomotives 

(2285) 

Total 21,534 147,252 3,744 3,368 333 6,785 

Grand Total 145,885 367,975 22,557 21,015 35,132 27,709 

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Table 2.3-16. Change in Emissions between 2009 and 2002 Base F Inventories (Based on 

Growth Using 1996 and 2020 EPA Inventories)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL +10% +15% +23% +18% +16% +11% 

FL +15% +16% +16% +16% +16% +16% 

GA +15% +16% +16% +16% +16% +16% 

KY +15% +16% +16% +16% +16% +16% 

MS +11% +16% +15% +15% +16% +12% 

NC +8% +3% +4% +4% +3% +5% 

SC +13% +9% +9% +9% +12% +13% 

TN +11% +12% +12% +12% +14% +11% 

VA +13% +12% +9% +9% +15% +14% 

WV +11% +16% +15% +15% +16% +12% 

Aircraft 

(2275) 

Total +13% +14% +14% +13% +15% +14% 

AL +7% -4% -5% -5% -18% +4% 

FL +6% -4% -5% -5% -12% +4% 

GA +6% -3% -5% -5% -17% +4% 

KY +7% -4% -4% -4% -13% +5% 

MS +7% -4% -4% -4% -15% +5% 

NC +6% -4% -5% -5% -15% +4% 

SC +6% -4% -5% -5% -16% +4% 

TN +7% -4% -4% -4% -9% +5% 

VA +7% -4% -7% -7% -83% +5% 

WV +7% -4% -7% -7% -83% +5% 

Commercial 

Marine 

(2280) 

Total +7% -4% -5% -5% -15% +5% 

Military Marine VA +7% -4% -7% -7% -83% +5% 

(2283) Total +7% -4% -7% -7% -83% +5% 

AL +5% -11% -24% -24% -83% -6% 

FL +5% -11% -24% -24% -83% -6% 

GA +4% -9% -24% -24% -83% -5% 

KY +5% -10% -23% -23% -83% -6% 

MS +5% -11% -24% -24% -83% -6% 

NC +5% -11% -24% -24% -83% -6% 

SC +5% -11% -24% -24% -83% -6% 

TN +5% -7% -24% -24% -83% -6% 

VA +4% -6% -24% -24% -83% -5% 

WV +4% -8% -24% -24% -83% -5% 

Locomotives 

(2285) 

Total +4% -9% -24% -24% -83% -5% 

Grand Total +10% -5% -4% -4% -32% +5% 

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Table 2.3-17. Change in Emissions between 2018 and 2002 Base F Inventories (Based on 

Growth Using 1996 and 2020 EPA Inventories)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL +24% +35% +53% +41% +36% +25% 

FL +34% +37% +37% +37% +37% +36% 

GA +35% +37% +37% +37% +37% +36% 

KY +35% +37% +37% +37% +37% +36% 

MS +25% +36% +35% +35% +36% +27% 

NC +10% -6% -5% -5% -6% 0% 

SC +30% +20% +21% +21% +27% +30% 

TN +24% +27% +28% +28% +31% +26% 

VA +29% +28% +20% +20% +35% +33% 

WV +26% +36% +35% +35% +36% +28% 

Aircraft 

(2275) 

Total +29% +31% +30% +30% +33% +31% 

AL +16% -8% -4% -4% -19% +10% 

FL +14% -8% -4% -4% -7% +9% 

GA +13% -8% -5% -5% -17% +9% 

KY +17% -10% -2% -2% -13% +12% 

MS +16% -9% -3% -3% -15% +11% 

NC +13% -8% -4% -4% -14% +9% 

SC +14% -9% -4% -4% -15% +10% 

TN +17% -10% -2% -2% -3% +12% 

VA +17% -9% -6% -6% -98% +11% 

WV +17% -10% -6% -6% -98% +12% 

Commercial 

Marine 

(2280) 

Total +15% -9% -3% -3% -14% +11% 

Military Marine VA +17% -10% -6% -6% -98% +12% 

(2283) Total +17% -10% -6% -6% -98% +12% 

AL +10% -24% -36% -36% -98% -13% 

FL +10% -24% -36% -36% -98% -13% 

GA +10% -20% -36% -36% -98% -12% 

KY +10% -23% -35% -35% -98% -13% 

MS +10% -24% -36% -36% -98% -13% 

NC +10% -24% -36% -36% -98% -13% 

SC +10% -24% -36% -36% -98% -13% 

TN +10% -15% -36% -36% -98% -13% 

VA +10% -14% -36% -36% -98% -11% 

WV +10% -18% -36% -36% -98% -12% 

Locomotives 

(2285) 

Total +10% -21% -36% -36% -98% -12% 

Grand Total +23% -12% -1% -1% -34% +11% 

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118,739

130,798

145,885

129,659

159,122

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

19,540 20,412

21,534 21,980

23,849

0

5,000

10,000

15,000

20,000

25,000

30,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

Figure 2.3-2. Total Aircraft, Locomotive, and CMV CO Emissions (Base F)

Figure 2.3-3. Locomotive CO Emissions (Base F)

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420,228

397,462

367,975

455,067

395,049

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

187,044

169,635

147,252

211,588

167,783

0

50,000

100,000

150,000

200,000

250,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

Figure 2.3-4. Total Aircraft, Locomotive, and CMV NOx Emissions (Base F) 

Figure 2.3-5. Locomotive NOx Emissions (Base F) 

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22,823 21,946 22,557

100,452

128,715

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

5,815

4,440

3,744

6,118

3,947

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

Figure 2.3-6. Total Aircraft, Locomotive, and CMV PM10 Emissions (Base F) 

Figure 2.3-7. Locomotive PM10 Emissions (Base F) 

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5,232

3,995

3,368

5,505

3,552

0

1,000

2,000

3,000

4,000

5,000

6,000

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21,170 20,413 21,015

73,099

92,207

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

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Figure 2.3-8. Total Aircraft, Locomotive, and CMV PM2.5 Emissions (Base F) 

Figure 2.3-9. Locomotive PM2.5 Emissions (Base F) 

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14,022

2,343

333

14,947

1,553

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

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52,931

36,126 35,132

57,062

41,284

0

10,000

20,000

30,000

40,000

50,000

60,000

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Figure 2.3-10. Total Aircraft, Locomotive, and CMV SO2 Emissions (Base F) 

Figure 2.3-11. Locomotive SO2 Emissions (Base F)

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7,750

7,328

6,785

8,738

7,544

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

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24,881

26,148

27,709

26,877

29,228

22,000

23,000

24,000

25,000

26,000

27,000

28,000

29,000

30,000

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Figure 2.3-12. Total Aircraft, Locomotive, and CMV VOC Emissions (Base F) 

Figure 2.3-13. Locomotive VOC Emissions (Base F) 

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Base G Revisions: 

Table 2.3-18 shows the Base G 2002 base year emissions for each State in the VISTAS region 

for aircraft, locomotives and CMV. Although some of these data are updated relative to those 

used as the basis of the Base F emissions forecasts, the methodology used to develop 2009 and 

2018 emissions forecasts for aircraft, locomotives, and CMV for Base G is identical to that used 

for Base F (as documented above). The only exceptions are as follows: 

(a) As indicated in the discussion of the Base F forecasts, the CAIR (growth rate) matching 

criteria were overridden for any record for which States provided local growth data. For 

Base F, only North Carolina provided such data. However, for Base G, Kentucky 

regulators provided growth data for aircraft emissions associated with 

Cincinnati/Northern Kentucky International Airport (located in Boone County, 

Kentucky). These data were applied to all pollutants and all aircraft types (i.e., military 

aircraft (SCC 2275001000), commercial aircraft (SCC 2275020000), general aviation 

aircraft (SCC 2275050000), and air taxi aircraft (SCC 2275060000)). Emissions forecasts 

for all aircraft operations in counties other than Boone continued to utilize the growth 

factors developed according to the CAIR matching criteria. Table 2.3-19 presents the 

locally generated growth factors applied in Kentucky. It should be recognized that 

although the locally provided growth factors presented in the table are significantly 

greater than those that would apply under the CAIR matching criteria, this is to be 

expected as local regulators noted a very significant decline in activity at the 

Cincinnati/Northern Kentucky International Airport in 2002 (relative to activity in 

preceding years). Moreover, this downward spike seems to have been alleviated since 

2002, so that the provided growth factors represent not only “routine” growth expected 

between 2002 and the two forecast years, but growth required to offset the temporary 

decline observed in 2002. 

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Table 2.3-18. Base G 2002 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 5,595 185 238 99 18 276 

FL 25,431 8,891 2,424 2,375 800 3,658 

GA 6,620 5,372 1,475 1,446 451 443 

KY 5,577 925 251 246 88 397 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 7,251 2,766 734 719 235 943 

VA 11,873 3,885 2,010 1,970 272 2,825 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 77,712 24,305 8,029 7,734 2,121 10,179 

AL 1,196 9,218 917 844 3,337 737 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,875 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,688 43,233 1,903 1,751 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 3,624 27,555 1,217 1,120 4,974 860 

VA 972 2,775 334 307 359 483 

WV 1,528 11,586 487 448 525 362 

Commercial 

Marine 

(2280) 

Total 28,207 209,972 9,911 9,118 36,275 7,413 

Military Marine VA 110 313 25 23 27 48 

(2283) Total 110 313 25 23 27 48 

AL 3,518 26,623 592 533 1,446 1,365 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 2,626 25,627 633 570 1,439 1,041 

VA 1,186 11,882 1,529 1,375 3,641 492 

WV 1,311 13,224 329 296 808 517 

Locomotives 

(2285) 

Total 19,568 187,328 5,815 5,232 14,022 7,761 

Grand Total 125,597 421,918 23,780 22,107 52,444 25,401 

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Table 2.3-19 Locally Generated Growth Factors for Kentucky 

FIP 2009 Factor 2018 Factor 

21015 1.31 1.81 

Note: 

Growth factor = Year Emissions/2002 Emissions. 

Under CAIR approach, 2009 = 0.99 to 1.17. 

Under CAIR approach, 2018 = 0.97 to 1.40. 

(b) Because of the additional emissions records added in Alabama, as discussed in the Base 

G 2002 base year inventory section of this report, the total number of emissions records 

in the Base G 2009 and 2018 forecasts increased to 23,042 (as compared to 22,838 for 

Base F). The 23,042 data records for aircraft, locomotives, and CMV were assigned 

growth factors in accordance with the following breakdown: 

 72 records matched State-provided growth factors, 

 4,287 records matched using the CAIR-Primary criterion, 

 240 records matched using the CAIR-Secondary criterion, 

 7,511 records matched using the CAIR-Tertiary criterion, 

 720 records matched using the No T4-Primary criterion, 

 3,858 records matched using the No T4-Secondary criterion, and 

 6,354 records matched using the No T4-Tertiary criterion. 

Tables 2.3-20 and 2.3-21 present a summary of the resulting Base G 2009 and 2018 inventories, 

while Tables 2.3-22 and 2.3-23 present the associated change in emissions for each forecast 

inventory relative to the Base G 2002 base year VISTAS. As was the case with Base F, the larger 

reduction in CMV SO2 emissions in 2009 and 2018 (relative to 2002) for Virginia and West 

Virginia is notable relative to the other VISTAS States, but is attributable to a high diesel 

contribution to total CMV SO2 in the 2002 inventories for these two States. 

Figures 2.3-14 through 2.3-25 graphically depict the relationships between the various 

inventories, as revised through Base G. There are two figures for each pollutant, the first of 

which presents a comparison of total VISTAS regional emission estimates for aircraft, 

locomotives, and CMV, and the second of which presents total VISTAS region emission 

estimates for locomotives only. This two figure approach is intended to provide a more robust 

illustration of the differences between the various inventories, as some of the differences are less 

distinct when viewed through overall aggregate emissions totals. All of the figures include the 

following emissions estimates: 

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• The Base G 2002 base year VISTAS emissions inventory (labeled as “2002”), 

• The pre-Base F 2002 base year VISTAS emissions inventory (labeled as “2002 

Prelim”), 

• The Base G 2009 VISTAS emissions inventory developed using growth rates derived 

from 1996 and 2020 EPA CAIR data (labeled as “2009”), 

• The Base G 2018 VISTAS emissions inventory developed using growth rates derived 

from 1996 and 2020 EPA CAIR data (labeled as “2018”), and 

• The pre-Base F 2018 VISTAS emissions inventory estimates developed using growth 

rates derived from 1996, 2010, 2015, and 2020 EPA CAIR data (labeled as “2018 

Prelim”). 

All 12 figures generally illustrate a reduction in emissions estimates between the pre-Base F 

2002 emission estimates published in February 2004 and the Base G 2002 base year emission 

estimates. This reduction generally results from emission updates reflected in the Base F State 

CERR submittals, although the major differences in aggregate PM emission estimates are driven 

to a greater extent by modifications in the methodology used to estimate aircraft PM in the Base 

F revisions to the 2002 Base F base year inventory (as documented under the base year inventory 

section of this report). 

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Table 2.3-20. Base G 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 6,265 213 292 116 21 309 

FL 29,258 10,316 2,812 2,756 928 4,235 

GA 7,635 6,233 1,712 1,678 523 512 

KY 6,959 1,135 307 301 108 487 

MS 1,765 162 51 50 16 108 

NC 6,991 1,795 486 477 171 709 

SC 7,372 559 446 437 98 975 

TN 8,020 3,096 824 807 268 1,050 

VA 13,141 4,244 2,124 2,082 306 3,153 

WV 1,312 91 28 28 9 74 

Aircraft 

(2275) 

Total 88,716 27,844 9,083 8,732 2,447 11,612 

AL 1,280 8,888 872 802 2,753 768 

FL 6,236 43,198 1,838 1,691 5,864 1,467 

GA 1,097 7,599 317 291 974 256 

KY 7,087 48,039 2,158 1,985 8,350 1,649 

MS 6,074 41,437 1,821 1,676 6,587 1,415 

NC 634 4,386 184 169 584 148 

SC 1,133 7,796 326 300 1,012 264 

TN 3,887 26,333 1,168 1,074 4,512 904 

VA 1,042 2,662 312 286 61 506 

WV 1,638 11,073 455 419 89 381 

Commercial 

Marine 

(2280) 

Total 30,108 201,412 9,450 8,693 30,786 7,759 

Military Marine VA 118 299 23 21 5 50 

(2283) Total 118 299 23 21 5 50 

AL 3,677 23,783 452 406 242 1,289 

FL 1,052 8,905 189 170 101 382 

GA 2,769 24,398 507 456 271 1,003 

KY 2,264 19,597 415 374 221 819 

MS 2,406 20,785 441 397 239 849 

NC 1,690 14,662 311 279 165 613 

SC 1,213 10,443 222 200 119 437 

TN 2,745 23,924 483 435 240 984 

VA 1,236 11,134 1,167 1,050 608 467 

WV 1,369 12,177 251 226 135 489 

Locomotives 

(2285) 

Total 20,420 169,808 4,437 3,993 2,341 7,333 

Grand Total 139,362 399,364 22,994 21,440 35,578 26,754

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Table 2.3-21. Base G 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

(annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 7,126 249 361 139 24 352

FL 34,178 12,147 3,312 3,246 1,093 4,976

GA 8,939 7,340 2,016 1,976 616 601

KY 9,078 1,446 391 383 138 623

MS 1,986 190 60 58 18 122

NC 8,150 2,114 572 561 202 831

SC 8,487 616 493 484 112 1,119

TN 9,009 3,519 939 921 309 1,187

VA 14,770 4,706 2,271 2,226 349 3,574

WV 1,484 106 33 33 10 85

Aircraft 

(2275) 

Total 103,206 32,435 10,450 10,027 2,871 13,472

AL 1,388 8,464 880 809 2,715 809

FL 6,684 41,117 1,853 1,705 6,248 1,543

GA 1,174 7,246 319 293 976 269

KY 7,703 45,174 2,199 2,023 8,383 1,752

MS 6,571 39,129 1,850 1,702 6,556 1,498

NC 678 4,179 185 170 596 155

SC 1,217 7,406 329 303 1,027 278

TN 4,225 24,763 1,190 1,095 4,808 960

VA 1,133 2,517 314 289 9 537

WV 1,781 10,412 459 422 13 404

Commercial 

Marine 

(2280) 

Total 32,554 190,407 9,578 8,811 31,330 8,205

Military Marine VA 128 282 23 21 1 53

(2283) Total 128 282 23 21 1 53

AL 3,881 20,131 381 343 34 1,192

FL 1,110 7,538 159 143 14 353

GA 2,917 21,395 427 385 38 932

KY 2,389 16,751 352 317 31 757

MS 2,540 17,594 372 335 34 785

NC 1,782 12,539 263 237 23 570

SC 1,280 8,840 187 168 17 404

TN 2,897 21,735 407 367 34 910

VA 1,300 10,173 983 885 86 436

WV 1,444 10,831 212 190 19 453

Locomotives 

(2285) 

Total 21,539 147,527 3,743 3,368 332 6,792

Grand Total 157,427 370,651 23,794 22,227 34,534 28,522 

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Table 2.3-22. Change in Emissions between 2009 Base G and 2002 Base F Inventories 

(Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL +12% +15% +23% +18% +16% +12%

FL +15% +16% +16% +16% +16% +16%

GA +15% +16% +16% +16% +16% +16%

KY +25% +23% +23% +23% +23% +23%

MS +11% +16% +15% +15% +16% +12%

NC +15% +16% +16% +16% +16% +16%

SC +13% +9% +9% +9% +12% +13%

TN +11% +12% +12% +12% +14% +11%

VA +11% +9% +6% +6% +12% +12%

WV +11% +16% +15% +15% +16% +12%

Aircraft 

(2275) 

Total +14% +15% +13% +13% +15% +14%

AL +7% -4% -5% -5% -18% +4%

FL +6% -4% -5% -5% -12% +4%

GA +6% -3% -5% -5% -17% +4%

KY +7% -4% -4% -4% -13% +5%

MS +7% -4% -4% -4% -15% +5%

NC +6% -4% -5% -5% -15% +4%

SC +6% -4% -5% -5% -16% +4%

TN +7% -4% -4% -4% -9% +5%

VA +7% -4% -7% -7% -83% +5%

WV +7% -4% -7% -7% -83% +5%

Commercial 

Marine 

(2280) 

Total +7% -4% -5% -5% -15% +5%

Military Marine VA +7% -4% -7% -7% -83% +5%

(2283) Total +7% -4% -7% -7% -83% +5%

AL +5% -11% -24% -24% -83% -6%

FL +5% -11% -24% -24% -83% -6%

GA +4% -9% -24% -24% -83% -5%

KY +5% -10% -23% -23% -83% -6%

MS +5% -11% -24% -24% -83% -6%

NC +3% -11% -24% -24% -83% -6%

SC +5% -11% -24% -24% -83% -6%

TN +5% -7% -24% -24% -83% -6%

VA +4% -6% -24% -24% -83% -5%

WV +4% -8% -24% -24% -83% -5%

Locomotives 

(2285) 

Total +4% -9% -24% -24% -83% -6%

Grand Total +11% -5% -3% -3% -32% +5%

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Table 2.3-23. Change in Emissions between 2018 Base G and 2002 Base F Inventories 

(Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL +27% +35% +52% +41% +36% +28%

FL +34% +37% +37% +37% +37% +36%

GA +35% +37% +37% +37% +37% +36%

KY +63% +56% +56% +56% +56% +57%

MS +25% +36% +35% +35% +36% +27%

NC +34% +37% +36% +36% +37% +36%

SC +30% +20% +21% +21% +27% +30%

TN +24% +27% +28% +28% +31% +26%

VA +24% +21% +13% +13% +28% +27%

WV +26% +36% +35% +35% +36% +28%

Aircraft 

(2275) 

Total +33% +33% +30% +30% +35% +32%

AL +16% -8% -4% -4% -19% +10%

FL +14% -8% -4% -4% -7% +9%

GA +13% -8% -5% -5% -17% +9%

KY +17% -10% -2% -2% -13% +12%

MS +16% -9% -3% -3% -15% +11%

NC +13% -8% -4% -4% -14% +9%

SC +14% -9% -4% -4% -15% +10%

TN +17% -10% -2% -2% -3% +12%

VA +17% -9% -6% -6% -98% +11%

WV +17% -10% -6% -6% -98% +12%

Commercial 

Marine 

(2280) 

Total +15% -9% -3% -3% -14% +11%

Military Marine VA +17% -10% -6% -6% -98% +12%

(2283) Total +17% -10% -6% -6% -98% +12%

AL +10% -24% -36% -36% -98% -13%

FL +10% -24% -36% -36% -98% -13%

GA +10% -20% -36% -36% -98% -12%

KY +10% -23% -35% -35% -98% -13%

MS +10% -24% -36% -36% -98% -13%

NC +9% -24% -36% -36% -98% -13%

SC +10% -24% -36% -36% -98% -13%

TN +10% -15% -36% -36% -98% -13%

VA +10% -14% -36% -36% -98% -11%

WV +10% -18% -36% -36% -98% -12%

Locomotives 

(2285) 

Total +10% -21% -36% -36% -98% -12%

Grand Total +25% -12% +0% +1% -34% +12%

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125,597

139,362

157,427

129,659

159,122

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

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19,568 20,420

21,539 21,980

23,849

0

5,000

10,000

15,000

20,000

25,000

30,000

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Figure 2.3-14. Total Aircraft, Locomotive, and CMV CO Emissions (Base G)

Figure 2.3-15. Locomotive CO Emissions (Base G)

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421,918

399,364

370,651

455,067

395,049

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

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187,328

169,808

147,527

211,588

167,783

0

50,000

100,000

150,000

200,000

250,000

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Figure 2.3-16. Total Aircraft, Locomotive, and CMV NOx Emissions (Base G) 

Figure 2.3-17. Locomotive NOx Emissions (Base G) 

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23,780 22,994 23,794

100,452

128,715

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

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5,815

4,437

3,743

6,118

3,947

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

2002 2009 2018 2002 Prelim 2018 Prelim

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Figure 2.3-18. Total Aircraft, Locomotive, and CMV PM10 Emissions (Base G) 

Figure 2.3-19. Locomotive PM10 Emissions (Base G) 

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22,107 21,440 22,227

73,099

92,207

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

100,000

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5,232

3,993

3,368

5,505

3,552

0

1,000

2,000

3,000

4,000

5,000

6,000

2002 2009 2018 2002 Prelim 2018 Prelim

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Figure 2.3-20. Total Aircraft, Locomotive, and CMV PM2.5 Emissions (Base G) 

Figure 2.3-21. Locomotive PM2.5 Emissions (Base G) 

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52,444

35,578 34,534

57,062

41,284

0

10,000

20,000

30,000

40,000

50,000

60,000

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14,022

2,341

332

14,947

1,553

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

2002 2009 2018 2002 Prelim 2018 Prelim

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Figure 2.3-22. Total Aircraft, Locomotive, and CMV SO2 Emissions (Base G) 

Figure 2.3-23. Locomotive SO2 Emissions (Base G)

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25,401

26,754

28,522

26,877

29,228

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

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7,761

7,333

6,792

8,738

7,544

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

8,000

9,000

10,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

Figure 2.3-24. Total Aircraft, Locomotive, and CMV VOC Emissions (Base G) 

Figure 2.3-25. Locomotive VOC Emissions (Base G) 

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2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio 

Base G projection inventories for 2009 and 2018 for NONROAD model sources in the states of 

Illinois, Indiana, and Ohio were produced using a methodology identical to that employed to 

develop a Base G 2002 base year inventory for the same states (as documented earlier in this 

report). This method consists of the extraction of a complete set of county-level input data 

applicable to each of the three states (in each of the two projection years) from the latest version 

of the EPA’s NMIM model. This includes appropriate consideration of all non-default NMIM 

input files generated by the Midwest Regional Planning Organization as documented earlier in 

the discussion of the Base G 2002 base year inventory. These input data were then assembled 

into appropriate input files for the Final NONROAD2005 model and emission estimates were 

produced using the same procedure employed for the VISTAS region. 

Changes noted between the base year (2002) and forecast year (2009 and 2018) input data 

extracted from NMIM include differences in gasoline vapor pressure, gasoline sulfur content, 

and diesel sulfur content in most counties. All temperature data (minimum, maximum, and 

average daily temperatures) was constant across years. 

As described in the discussion of the Base G 2002 base year inventory, counties in the three 

states were grouped for modeling purposes using a temperature aggregation scheme that allowed 

for county-specific temperature variations of no more that 2 oF from group average temperatures 

(for all temperature inputs). The same grouping scheme was applied to projection year modeling, 

so that Illinois emissions were modeled using 12 county groups, Indiana emissions were modeled 

using 9 county groups, and Ohio emissions were modeled using 10 county groups. Thus, 31 

iterations of NONROAD2002 were required per season per projection year, as compared to the 

53 iterations per season per projection year required for the VISTAS region. 

As was also described in the discussion of the Base G 2002 base year inventory, several 

non-default equipment population, growth, activity, seasonal distribution, and county allocation 

files are assigned by NMIM model inputs for these counties. As was the case for the base year 

inventory development, these same non-default assignments were retained for both 

projection inventories. 

2.3.4.4 Differences between 2009/2018 

Methodologically, there was no difference in the way that 2009 and 2018 emissions were 

calculated for non-road mobile sources. The actual value of the growth factors were different for 

each type of mobile source considered, but the calculation methods were identical. 

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2.3.5 Quality Assurance steps 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, to ensure that a full and complete 

inventory was developed for VISTAS, and to make sure that projection calculations were 

working correctly. Quality assurance was an important component to the inventory development 

process and MACTEC performed the following QA steps on mobile source components of the 

2009 and revised 2018 projection inventories: 

1. All final files (NONROAD only) were run through EPA’s Format and Content 

checking software. Input data files for MOBILE and VMT growth estimates were 

reviewed by the corresponding SIWG and by the VISTAS Emission Inventory 

Technical Advisor. 

2. SCC level emission summaries were prepared and evaluated to ensure that emissions 

were consistent and that there were no missing sources (NONROAD only). 

3. Tier comparisons (by pollutant) were developed between the 2002 base year 

inventory and the 2009 and 2018 projection inventories (NONROAD only). Total 

VISTAS level summaries by pollutant were developed for these sources to compare 

Base F and Base G emission levels. 

4. Data product summaries were provided to both the VISTAS Emission Inventory 

Technical Advisor and to the SIWG representatives for review and comment. 

Changes based on these comments were implemented in the files. 

5. Version numbering was used for all inventory files developed. The version 

numbering process used a decimal system to track major and minor changes. For 

example, a major change would result in a version going from 1.0 to 2.0. A minor 

change would cause a version number to go from 1.0 to 1.1. Minor changes resulting 

from largely editorial changes would result in a change from 1.00 to 1.01. 

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APPENDIX A: 

STATE EMISSION TOTALS BY POLLUTANT AND SECTOR 

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Annual CO Emissions by Source Sector

0

1,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

W

Tons per year

2002 Actual EGU and Fires

2002 Typical EGU and Fires

2009

2018

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Annual CO Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 

11,279 174,271 1,366,056 414,385 83,958 474,959 2002 Actual 

11,460 174,260 942,793 414,385 83,958 514,120 2002 Typical 

AL 14,986 180,369 942,793 454,686 66,654 534,873 2009 

24,342 201,794 797,966 488,924 59,626 535,658 2018 

 

57,113 81,933 4,693,893 1,920,729 71,079 790,620 2002 Actual 

55,899 81,928 3,446,095 1,920,729 71,079 923,310 2002 Typical 

FL 35,928 87,037 3,446,095 2,104,920 57,011 923,310 2009 

53,772 96,819 3,086,330 2,323,327 53,903 923,310 2018 

 

9,712 130,656 2,833,468 791,158 108,083 654,411 2002 Actual 

9,650 130,656 2,053,694 791,158 108,083 620,342 2002 Typical 

GA 23,721 147,215 2,053,694 882,970 94,130 637,177 2009 

44,476 167,644 1,765,020 973,872 93,827 637,177 2018 

 

12,619 109,936 1,260,682 325,993 66,752 8,703 2002 Actual 

12,607 109,937 942,350 325,993 66,752 24,900 2002 Typical 

KY 15,812 122,024 942,350 357,800 57,887 31,810 2009 

17,144 139,437 782,423 381,215 54,865 33,296 2018 

 

5,303 54,568 894,639 236,752 37,905 13,209 2002 Actual 

5,219 54,567 628,151 236,752 37,905 14,353 2002 Typical 

MS 5,051 57,748 628,151 257,453 27,184 48,160 2009 

15,282 66,858 528,898 270,726 22,099 50,037 2018 

 

13,885 50,531 3,176,811 808,231 345,315 34,515 2002 Actual 

14,074 50,531 2,184,901 808,231 345,315 71,970 2002 Typical 

NC 14,942 53,696 2,184,901 887,605 301,163 96,258 2009 

20,223 62,145 1,510,848 960,709 290,809 111,266 2018 

 

6,990 56,315 1,275,161 413,964 113,714 248,341 2002 Actual 

6,969 56,315 912,280 413,964 113,714 253,005 2002 Typical 

SC 11,135 60,473 912,280 448,625 90,390 282,307 2009 

14,786 68,988 800,619 481,332 83,167 282,307 2018 

 

7,084 114,681 1,967,658 505,163 89,828 4,302 2002 Actual 

6,787 114,681 1,361,408 505,163 89,828 10,124 2002 Typical 

TN 7,214 119,039 1,361,408 554,121 74,189 17,372 2009 

7,723 140,138 1,150,516 593,100 68,809 18,860 2018 

 

6,892 63,796 2,170,508 660,105 155,873 15,625 2002 Actual 

6,797 63,784 1,495,771 660,105 155,873 12,611 2002 Typical 

VA 12,509 68,346 1,495,771 726,815 128,132 21,130 2009 

15,420 76,998 1,310,698 797,683 121,690 26,923 2018 

 

10,341 89,879 560,717 133,113 39,546 6,738 2002 Actual 

10,117 89,878 385,994 133,113 39,546 2,652 2002 Typical 

WV 11,493 100,045 385,994 152,862 31,640 3,949 2009 

11,961 119,332 319,030 167,424 28,773 5,013 2018 

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Annual NH3 Emissions by Source Sector

0

50,000

100,000150,000200,000250,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

W

Tons per year

2002 Actual EGU and Fires

2002 Typical EGU and Fires

2009

2018

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Annual NH3 Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 

317 1,883 5,576 33 58,318 1,689 2002 Actual 

239 1,883 6,350 33 58,318 1,957 2002 Typical 

AL 359 2,132 6,350 36 64,268 2,050 2009 

1,072 2,464 7,296 42 71,915 2,054 2018 

 

234 1,423 18,078 134 37,446 3,102 2002 Actual 

222 1,423 21,737 134 37,446 3,157 2002 Typical 

FL 1,631 1,544 21,737 148 38,616 3,157 2009 

2,976 1,829 26,154 171 40,432 3,157 2018 

 

83 3,613 10,524 60 80,913 2,578 2002 Actual 

86 3,613 12,660 60 80,913 2,153 2002 Typical 

GA 686 3,963 12,660 68 89,212 2,229 2009 

1,677 4,797 14,871 79 99,885 2,229 2018 

 

326 674 5,044 31 51,135 39 2002 Actual 

321 674 5,795 31 51,135 112 2002 Typical 

KY 400 760 5,795 34 53,005 143 2009 

476 901 6,584 40 55,211 150 2018 

 

190 1,169 3,577 23 58,721 59 2002 Actual 

198 1,169 4,026 23 58,721 65 2002 Typical 

MS 334 668 4,026 25 63,708 217 2009 

827 764 4,565 29 69,910 225 2018 

 

54 1,179 10,455 65 161,860 155 2002 Actual 

55 1,179 12,637 65 161,860 324 2002 Typical 

NC 445 1,285 12,637 72 170,314 433 2009 

663 1,465 13,077 83 180,866 501 2018 

 

142 1,411 4,684 33 28,166 980 2002 Actual 

141 1,411 5,510 33 28,166 908 2002 Typical 

SC 343 1,578 5,510 36 30,555 1,039 2009 

617 1,779 6,472 41 33,496 1,039 2018 

 

204 1,542 6,616 43 34,393 19 2002 Actual 

197 1,542 7,738 43 34,393 46 2002 Typical 

TN 227 1,764 7,738 48 35,253 78 2009 

241 2,115 8,962 55 36,291 85 2018 

 

127 3,104 7,837 48 43,905 70 2002 Actual 

130 3,104 9,066 48 43,905 57 2002 Typical 

VA 694 3,049 9,066 53 46,639 95 2009 

622 3,604 10,757 61 50,175 121 2018 

 

121 332 1,933 9 9,963 30 2002 Actual 

121 332 2,183 9 9,963 12 2002 Typical 

WV 330 341 2,183 11 10,625 18 2009 

180 413 2,484 13 11,504 23 2018 

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Annual NOx Emissions by Source Sector

0

200,000400,000600,000800,000

1,000,0001,200,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

W

Tons per year

2002 Actual EGU and Fires

2002 Typical EGU and Fires

2009

2018

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Annual NOx Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 

 161,038 83,310 158,423 65,366 23,444 10,728 2002 Actual 

154,704 83,302 101,323 65,366 23,444 11,456 2002 Typical 

AL 82,305 69,409 101,323 56,862 23,930 11,901 2009 

64,358 78,318 46,222 43,799 25,028 11,918 2018 

 

257,677 45,156 466,098 180,627 28,872 15,942 2002 Actual 

282,507 45,150 314,307 180,627 28,872 19,791 2002 Typical 

FL 86,165 46,020 314,307 163,794 28,187 19,791 2009 

73,125 51,902 154,611 127,885 30,708 19,791 2018 

 

147,517 49,214 308,013 97,961 36,142 14,203 2002 Actual 

148,126 49,214 208,393 97,961 36,142 13,882 2002 Typical 

GA 98,497 50,312 208,393 85,733 37,729 14,243 2009 

75,717 55,775 99,821 64,579 41,332 14,243 2018 

 

198,817 38,392 154,899 104,571 39,507 187 2002 Actual 

201,928 38,434 97,912 104,571 39,507 534 2002 Typical 

KY 92,021 37,758 97,912 94,752 42,088 682 2009 

64,378 41,034 42,104 79,392 44,346 714 2018 

 

43,135 61,526 111,791 88,787 4,200 283 2002 Actual 

40,433 61,553 69,949 88,787 4,200 308 2002 Typical 

MS 36,011 56,398 69,949 80,567 4,249 1,033 2009 

10,271 61,533 29,717 68,252 4,483 1,073 2018 

 

151,850 44,881 341,198 84,284 36,550 740 2002 Actual 

148,809 44,881 207,648 84,284 36,550 1,544 2002 Typical 

NC 66,517 34,719 207,648 70,997 39,954 2,065 2009 

62,346 37,750 81,706 49,046 43,865 2,387 2018 

 

 88,241 42,153 140,428 50,249 19,332 4,932 2002 Actual 

 88,528 42,153 91,696 50,249 19,332 5,270 2002 Typical 

SC 46,915 40,019 91,696 43,235 19,360 5,899 2009 

51,456 44,021 42,354 31,758 20,592 5,899 2018 

 

157,307 64,331 233,324 96,827 17,844 92 2002 Actual 

152,137 64,331 147,757 96,827 17,844 217 2002 Typical 

TN 66,405 57,869 147,757 86,641 18,499 373 2009 

31,715 63,435 65,242 70,226 19,597 405 2018 

 

86,886 60,415 219,602 63,219 51,418 335 2002 Actual 

85,081 60,390 133,170 63,219 51,418 271 2002 Typical 

VA 66,219 51,046 133,170 54,993 52,618 453 2009 

75,594 55,945 61,881 40,393 56,158 578 2018 

 

230,977 46,612 59,612 33,239 12,687 145 2002 Actual 

222,437 46,618 36,049 33,239 12,687 57 2002 Typical 

WV 86,328 38,031 36,049 30,133 13,439 85 2009 

51,241 43,359 16,274 25,710 14,828 108 2018 

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Annual PM10 Emissions by Source Sector

0

200,000400,000600,000800,000

1,000,0001,200,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

W

Tons per year

2002 Actual EGU and Fires

2002 Typical EGU and Fires

2009

2018

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Annual PM10 Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 

 7,646 25,240 3,898 4,787 393,588 47,237 2002 Actual 

 7,845 25,239 3,188 4,787 393,588 50,833 2002 Typical 

AL 6,969 25,421 3,188 4,027 413,020 52,851 2009 

7,822 29,924 2,488 3,041 445,256 52,927 2018 

 

21,387 35,857 11,253 18,281 443,346 85,263 2002 Actual 

21,391 35,856 9,953 18,281 443,346 98,470 2002 Typical 

FL 9,007 39,872 9,953 15,613 503,230 98,470 2009 

9,953 46,456 8,489 12,497 578,516 98,470 2018 

 

11,224 21,516 7,236 8,618 695,414 65,227 2002 Actual 

11,467 21,516 6,103 8,618 695,414 62,336 2002 Typical 

GA 17,891 22,997 6,103 7,521 776,411 63,973 2009 

20,909 27,143 4,995 6,015 880,199 63,973 2018 

 

4,701 16,626 3,720 6,425 233,559 846 2002 Actual 

4,795 16,626 3,002 6,425 233,559 2,421 2002 Typical 

KY 6,463 17,174 3,002 5,544 242,177 3,093 2009 

6,694 20,153 2,283 4,556 256,052 3,237 2018 

 

1,633 19,472 2,856 5,010 343,377 1,284 2002 Actual 

1,706 19,469 2,290 5,010 343,377 1,396 2002 Typical 

MS 4,957 19,245 2,290 4,270 356,324 4,683 2009 

7,187 22,859 1,688 3,452 375,495 4,865 2018 

 

22,754 13,785 6,905 7,348 280,379 3,356 2002 Actual 

22,994 13,785 5,861 7,348 280,379 6,998 2002 Typical 

NC 22,152 13,855 5,861 6,055 292,443 9,359 2009 

37,376 15,678 4,299 4,298 315,294 10,819 2018 

 

21,400 14,142 3,446 4,152 260,858 25,968 2002 Actual 

21,827 14,142 2,878 4,152 260,858 26,304 2002 Typical 

SC 19,395 13,370 2,878 3,471 278,299 29,153 2009 

28,826 15,139 2,258 2,617 304,251 29,153 2018 

 

14,640 34,534 5,338 6,819 212,554 418 2002 Actual 

13,866 34,534 4,238 6,819 212,554 984 2002 Typical 

TN 15,608 34,145 4,238 5,877 226,098 1,689 2009 

15,941 41,397 3,199 4,672 246,252 1,834 2018 

 

3,960 13,252 4,537 8,728 237,577 1,519 2002 Actual 

3,892 13,252 3,760 8,728 237,577 1,226 2002 Typical 

VA 5,508 13,048 3,760 7,510 252,488 2,054 2009 

13,775 15,112 3,343 6,208 275,351 2,618 2018 

 

4,573 17,503 1,395 1,850 115,346 655 2002 Actual 

4,472 17,503 1,096 1,850 115,346 258 2002 Typical 

WV 5,657 17,090 1,096 1,640 115,089 384 2009 

6,349 21,735 844 1,292 121,549 487 2018 

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Annual PM2.5 Emissions by Source Sector

0

50,000

100,000150,000200,000250,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

W

Tons per year

2002 Actual EGU and Fires

2002 Typical EGU and Fires

2009

2018

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Annual PM2.5 Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 

 4,113 19,178 2,794 4,502 56,654 42,041 2002 Actual 

 4,176 19,177 2,049 4,502 56,654 44,812 2002 Typical 

AL 3,921 19,230 2,049 3,776 58,699 46,543 2009 

4,768 22,598 1,262 2,835 62,323 46,608 2018 

 

15,643 30,504 7,852 17,415 58,878 75,717 2002 Actual 

15,575 30,504 6,216 17,415 58,878 88,756 2002 Typical 

FL 5,910 33,946 6,216 14,866 64,589 88,756 2009 

6,843 39,430 4,242 11,868 72,454 88,756 2018 

 

4,939 17,394 5,158 8,226 103,794 57,293 2002 Actual 

5,070 17,394 3,869 8,226 103,794 55,712 2002 Typical 

GA 10,907 18,906 3,869 7,175 112,001 57,116 2009 

13,983 22,323 2,517 5,730 123,704 57,116 2018 

 

2,802 11,372 2,693 6,046 45,453 726 2002 Actual 

2,847 11,372 1,941 6,046 45,453 2,076 2002 Typical 

KY 4,279 11,686 1,941 5,203 46,243 2,653 2009 

4,434 13,739 1,160 4,256 47,645 2,777 2018 

 

1,138 9,906 2,109 4,690 50,401 1,102 2002 Actual 

1,147 9,902 1,522 4,690 50,401 1,197 2002 Typical 

MS 4,777 9,199 1,522 3,985 51,661 4,016 2009 

7,033 10,739 876 3,203 53,222 4,173 2018 

 

16,498 10,455 4,816 7,005 64,052 2,878 2002 Actual 

16,623 10,455 3,643 7,005 64,052 6,002 2002 Typical 

NC 15,949 10,411 3,643 5,760 69,457 8,027 2009 

29,791 11,775 2,158 4,069 71,262 9,279 2018 

 

17,154 10,245 2,496 3,945 40,291 22,953 2002 Actual 

17,521 10,245 1,870 3,945 40,291 23,511 2002 Typical 

SC 16,042 9,390 1,870 3,294 41,613 25,955 2009 

25,032 11,086 1,154 2,474 44,319 25,955 2018 

 

12,166 27,345 3,919 6,458 42,566 359 2002 Actual 

11,491 27,345 2,782 6,458 42,566 844 2002 Typical 

TN 13,092 27,079 2,782 5,557 44,124 1,449 2009 

13,387 32,893 1,643 4,403 46,692 1,573 2018 

 

2,606 10,165 3,090 8,288 43,989 1,303 2002 Actual 

2,650 10,165 2,254 8,288 43,989 1,052 2002 Typical 

VA 4,067 9,988 2,254 7,136 44,514 1,762 '2009 

11,976 11,594 1,641 5,891 46,697 2,245 2018 

 

2,210 13,313 1,003 1,728 21,049 562 2002 Actual 

2,163 13,313 703 1,728 21,049 221 2002 Typical 

WV 2,940 12,769 703 1,528 20,664 329 2009 

3,648 16,516 428 1,198 21,490 418 2018 

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Annual SO2 Emissions by Source Sector

0

100,000200,000300,000400,000500,000600,000700,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

W

Tons per year

2002 Actual EGU and Fires

2002 Typical EGU and Fires

2009

2018

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Annual SO2 Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 

 447,828 96,481 6,885 7,584 52,253 2,208 2002 Actual 

 423,736 96,481 635 7,584 52,253 2,559 2002 Typical 

AL 378,052 101,246 635 3,471 48,228 2,681 2009 

305,262 113,224 720 2,818 50,264 2,686 2018 

 

453,631 65,090 20,872 20,614 40,491 4,057 2002 Actual 

483,590 65,090 2,120 20,614 40,491 4,129 2002 Typical 

FL 186,055 65,511 2,120 8,967 36,699 4,129 2009 

132,177 75,047 2,533 7,536 38,317 4,129 2018 

 

514,952 53,774 12,155 9,005 57,559 3,372 2002 Actual 

517,633 53,774 1,254 9,005 57,559 2,815 2002 Typical 

GA 417,449 53,983 1,254 2,725 57,696 2,914 2009 

230,856 59,343 1,458 1,709 59,729 2,914 2018 

 

484,057 34,029 5,974 14,043 41,805 51 2002 Actual 

495,153 34,029 585 14,043 41,805 146 2002 Typical 

KY 290,193 36,418 585 9,180 43,087 187 2009 

226,062 40,682 651 8,592 44,186 196 2018 

 

67,429 35,960 4,604 11,315 771 78 2002 Actual 

60,086 35,954 397 11,315 771 84 2002 Typical 

MS 76,579 25,564 397 7,191 753 283 2009 

15,146 39,221 441 6,638 746 294 2018 

 

477,990 44,103 13,343 7,693 5,412 203 2002 Actual 

478,488 44,103 1,311 7,693 5,412 423 2002 Typical 

NC 242,286 42,516 1,311 1,892 5,751 566 2009 

108,492 46,292 1,323 905 6,085 655 2018 

 

206,399 53,518 5,958 4,866 12,900 1,281 2002 Actual 

210,272 53,518 556 4,866 12,900 1,187 2002 Typical 

SC 124,608 48,325 556 1,701 13,051 1,359 2009 

93,274 53,577 643 1,198 13,457 1,359 2018 

 

334,151 79,584 9,184 10,441 29,917 25 2002 Actual 

320,146 79,584 831 10,441 29,917 60 2002 Typical 

TN 255,410 70,657 831 5,651 30,577 102 2009 

112,672 77,219 944 5,207 31,962 111 2018 

 

241,204 63,903 7,218 8,663 105,890 92 2002 Actual 

233,691 63,900 900 8,663 105,890 74 2002 Typical 

VA 225,653 62,560 900 1,707 105,984 124 2009 

140,233 68,909 1,059 507 109,380 158 2018 

 

516,084 54,070 2,489 2,112 11,667 40 2002 Actual 

500,381 54,077 227 2,112 11,667 16 2002 Typical 

WV 277,489 55,973 227 359 12,284 23 2009 

115,324 62,193 255 56 12,849 29 2018 

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Annual VOC Emissions by Source Sector

0

200,000400,000600,000800,000

1,000,0001,200,0001,400,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

W

Tons per year

2002 Actual EGU and Fires

2002 Typical EGU and Fires

2009

2018

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Annual VOC Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 

 2,295 47,037 119,790 60,487 182,674 25,278 2002 Actual 

 2,288 47,035 72,848 60,487 182,674 26,526 2002 Typical 

AL 2,473 46,644 72,848 50,249 143,454 27,502 2009 

 2,952 54,291 47,296 40,407 153,577 27,539 2018 

 

 2,524 38,471 495,225 272,072 404,302 42,724 2002 Actual 

 2,531 38,471 323,290 272,072 404,302 51,527 2002 Typical 

FL 1,910 36,880 323,290 209,543 420,172 51,527 2009 

 2,376 42,811 216,620 183,452 489,975 51,527 2018 

 

 1,244 33,157 267,378 85,965 299,679 33,979 2002 Actual 

 1,256 33,157 184,239 85,965 299,679 33,918 2002 Typical 

GA 2,314 33,444 184,239 67,686 272,315 34,710 2009 

 2,841 39,485 105,507 56,761 319,328 34,710 2018 

 

 1,487 44,834 98,311 44,805 95,375 410 2002 Actual 

 1,481 44,834 63,258 44,805 95,375 1,172 2002 Typical 

KY 1,369 47,786 63,258 38,558 94,042 1,497 2009 

 1,426 55,861 39,084 30,920 103,490 1,567 2018 

 

 648 43,204 82,810 41,081 131,808 622 2002 Actual 

 629 43,203 49,670 41,081 131,808 675 2002 Typical 

MS 404 37,747 49,670 36,197 124,977 2,266 2009 

 1,114 45,338 30,734 28,842 140,134 2,355 2018 

 

 988 60,496 253,374 94,480 237,926 1,624 2002 Actual 

 986 60,496 163,803 94,480 237,926 3,387 2002 Typical 

NC 954 61,207 163,803 74,056 187,769 4,530 2009 

 1,345 70,100 88,620 61,327 189,591 5,236 2018 

 

 470 38,458 106,792 55,016 161,000 14,202 2002 Actual 

 470 38,458 67,281 55,016 161,000 14,666 2002 Typical 

SC 660 35,665 67,281 43,061 146,107 16,045 2009 

 906 43,656 44,700 36,131 161,228 16,045 2018 

 

 926 77,304 169,914 66,450 153,307 202 2002 Actual 

 890 77,304 108,200 66,450 153,307 476 2002 Typical 

TN 932 66,538 108,200 55,358 154,377 817 2009 

 976 83,573 64,665 45,084 182,222 888 2018 

 

 754 43,152 144,684 74,866 174,116 735 2002 Actual 

 747 43,152 89,678 74,866 174,116 593 2002 Typical 

VA 778 43,726 89,678 57,009 147,034 994 2009 

 997 53,186 60,454 49,052 150,919 1,267 2018 

 

 1,180 14,595 40,066 18,566 60,443 317 2002 Actual 

 1,140 14,595 23,907 18,566 60,443 125 2002 Typical 

WV 1,361 13,810 23,907 18,069 55,288 186 2009 

 1,387 16,565 15,463 14,086 60,747 236 2018 

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Annual CO Emissions by Source Sector

0

1,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

WV

Tons per year

2002

2009 OTB

2009 OTW

2018 OTB

2018 OTW

EGU and NonEGU values based on 2002 Typical Emiss

All Fire emissions based on Typical Year values

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Annual CO Emissions by Source Sector 

Name AREA EGU FIRES NONEGU NONROAD ONROAD YEAR Basis 

 83,958 10,812 514,120 174,306 367,038 1,366,056 2002 OTB - Typical 2002 

 68,882 16,494 514,120 177,145 408,424 942,793 2009 OTB - Typical 2002 

AL 68,882 19,205 514,120 177,145 408,424 942,793 2009 OTW - Typical 2002 

 63,773 26,600 514,120 194,801 443,100 797,966 2018 OTB - Typical 2002 

 63,773 29,893 514,120 194,801 443,100 797,966 2018 OTW - Typical 2002 

 

 105,849 51,165 923,310 84,920 1,731,519 4,693,893 2002 OTB - Typical 2002 

 101,356 40,642 923,310 98,325 1,934,550 3,446,095 2009 OTB - Typical 2002 

FL 101,356 40,641 923,310 98,325 1,934,550 3,446,095 2009 OTW - Typical 2002 

 100,952 59,793 923,310 113,923 2,179,296 3,086,330 2018 OTB - Typical 2002 

 100,952 57,759 923,310 113,923 2,179,296 3,086,330 2018 OTW - Typical 2002 

 

 107,889 8,098 620,342 131,417 700,427 2,833,468 2002 OTB - Typical 2002 

 103,579 19,170 620,342 147,835 783,990 2,053,694 2009 OTB - Typical 2002 

GA 103,579 20,024 620,342 147,835 783,990 2,053,694 2009 OTW - Typical 2002 

 105,059 27,152 620,342 169,156 868,018 1,765,020 2018 OTB - Typical 2002 

 105,059 28,895 620,342 169,156 868,018 1,765,020 2018 OTW - Typical 2002 

 

 66,752 12,888 56,686 110,141 289,967 1,260,682 2002 OTB - Typical 2002 

 64,806 15,273 56,686 121,981 306,884 942,350 2009 OTB - Typical 2002 

KY 64,806 15,119 56,686 121,981 306,884 942,350 2009 OTW - Typical 2002 

 65,297 16,974 56,686 139,395 349,285 782,423 2018 OTB - Typical 2002 

 65,297 14,954 56,686 139,395 349,285 782,423 2018 OTW - Typical 2002 

 

 37,905 3,831 128,471 57,711 213,779 894,639 2002 OTB - Typical 2002 

 37,161 6,714 128,471 60,709 237,297 628,151 2009 OTB - Typical 2002 

MS 37,161 6,954 128,471 60,709 237,297 628,151 2009 OTW - Typical 2002 

 36,425 10,553 128,471 70,454 252,658 528,898 2018 OTB - Typical 2002 

 36,425 12,928 128,471 70,454 252,658 528,898 2018 OTW - Typical 2002 

 

 373,585 12,027 200,564 52,542 725,734 3,176,811 2002 OTB - Typical 2002 

 332,443 11,091 200,564 54,791 797,360 2,184,901 2009 OTB - Typical 2002 

NC 332,443 11,170 200,564 54,791 797,360 2,184,901 2009 OTW - Typical 2002 

 327,871 13,482 200,564 63,699 863,536 1,510,848 2018 OTB - Typical 2002 

 327,871 13,777 200,564 63,699 863,536 1,510,848 2018 OTW - Typical 2002 

 

 113,714 3,675 253,005 59,605 367,575 1,275,161 2002 OTB - Typical 2002 

 95,826 6,316 253,005 65,612 402,871 912,280 2009 OTB - Typical 2002 

SC 95,826 6,526 253,005 65,612 402,871 912,280 2009 OTW - Typical 2002 

 89,343 10,175 253,005 75,209 438,027 800,619 2018 OTB - Typical 2002 

 89,343 10,671 253,005 75,209 438,027 800,619 2018 OTW - Typical 2002 

 

 89,235 6,339 78,370 119,405 451,480 1,967,658 2002 OTB - Typical 2002 

 82,196 6,750 78,370 121,420 500,186 1,361,408 2009 OTB - Typical 2002 

TN 82,196 6,651 78,370 121,420 500,186 1,361,408 2009 OTW - Typical 2002 

 81,242 7,074 78,370 143,845 540,143 1,150,516 2018 OTB - Typical 2002 

 81,242 6,509 78,370 143,845 540,143 1,150,516 2018 OTW - Typical 2002 

 

 155,873 5,958 19,159 62,534 595,311 2,170,508 2002 OTB - Typical 2002 

 133,738 9,811 19,159 69,822 661,295 1,495,771 2009 OTB - Typical 2002 

VA 133,738 10,245 19,159 69,822 661,295 1,495,771 2009 OTW - Typical 2002 

 129,037 14,788 19,159 77,590 734,294 1,310,698 2018 OTB - Typical 2002 

 129,037 14,839 19,159 77,590 734,294 1,310,698 2018 OTW - Typical 2002 

 

 39,546 9,927 32,656 89,928 119,089 560,717 2002 OTB - Typical 2002 

 37,704 12,622 32,656 100,292 138,999 385,994 2009 OTB - Typical 2002 

WV 37,704 12,328 32,656 100,292 138,999 385,994 2009 OTW - Typical 2002 

 36,809 13,064 32,656 119,367 152,932 319,030 2018 OTB - Typical 2002 

 36,809 12,992 32,656 119,367 152,932 319,030 2018 OTW - Typical 2002 

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Annual NH3 Emissions by Source Sector

0

50,000

100,000150,000200,000250,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

WV

Tons per year

2002

2009 OTB

2009 OTW

2018 OTB

2018 OTW

EGU and NonEGU values based on 2002 Typical Emiss

All Fire emissions based on Typical Year values

Appendix G Attachment 12 - Page Number:220
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Annual NH3 Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 

 89 1,883 5,576 32 59,486 1,957 2002 OTB - Typical 2002 

 1,128 2,112 6,350 35 65,441 1,957 2009 OTB - Typical 2002 

AL 1,344 2,112 6,350 35 65,441 1,957 2009 OTW - Typical 2002 

 1,909 2,456 7,296 40 73,346 1,957 2018 OTB - Typical 2002 

 2,173 2,456 7,296 40 73,346 1,957 2018 OTW - Typical 2002 

 

 53 1,383 18,078 108 44,902 3,157 2002 OTB - Typical 2002 

 2,524 1,605 21,737 119 46,950 3,157 2009 OTB - Typical 2002 

FL 2,524 1,605 21,737 119 46,950 3,157 2009 OTW - Typical 2002 

 4,022 1,905 26,154 138 49,889 3,157 2018 OTB - Typical 2002 

 3,865 1,905 26,154 138 49,889 3,157 2018 OTW - Typical 2002 

 

 5 3,613 10,524 54 84,230 2,153 2002 OTB - Typical 2002 

 1,305 3,963 12,660 60 92,838 2,153 2009 OTB - Typical 2002 

GA 1,376 3,963 12,660 60 92,838 2,153 2009 OTW - Typical 2002 

 1,912 4,799 14,871 71 103,911 2,153 2018 OTB - Typical 2002 

 2,057 4,799 14,871 71 103,911 2,153 2018 OTW - Typical 2002 

 

 0 674 5,044 28 51,097 110 2002 OTB - Typical 2002 

 717 733 5,795 30 53,023 110 2009 OTB - Typical 2002 

KY 710 733 5,795 30 53,023 110 2009 OTW - Typical 2002 

 763 839 6,584 36 55,356 110 2018 OTB - Typical 2002 

 771 839 6,584 36 55,356 110 2018 OTW - Typical 2002 

 

 97 1,169 3,577 23 59,262 177 2002 OTB - Typical 2002 

 388 667 4,026 26 64,289 177 2009 OTB - Typical 2002 

MS 407 667 4,026 26 64,289 177 2009 OTW - Typical 2002 

 686 761 4,565 30 70,565 177 2018 OTB - Typical 2002 

 872 761 4,565 30 70,565 177 2018 OTW - Typical 2002 

 

 35 1,171 10,455 61 164,467 324 2002 OTB - Typical 2002 

 577 1,255 12,637 68 173,187 324 2009 OTB - Typical 2002 

NC 574 1,255 12,637 68 173,187 324 2009 OTW - Typical 2002 

 740 1,412 13,077 79 184,167 324 2018 OTB - Typical 2002 

 781 1,412 13,077 79 184,167 324 2018 OTW - Typical 2002 

 

 0 1,411 4,684 29 29,447 908 2002 OTB - Typical 2002 

 409 1,578 5,510 32 31,966 908 2009 OTB - Typical 2002 

SC 422 1,578 5,510 32 31,966 908 2009 OTW - Typical 2002 

 702 1,779 6,472 37 35,082 908 2018 OTB - Typical 2002 

 742 1,779 6,472 37 35,082 908 2018 OTW - Typical 2002 

 

 0 1,620 6,616 41 35,571 46 2002 OTB - Typical 2002 

 406 1,861 7,738 45 36,578 46 2009 OTB - Typical 2002 

TN 400 1,861 7,738 45 36,578 46 2009 OTW - Typical 2002 

 427 2,240 8,962 53 37,812 46 2018 OTB - Typical 2002 

 394 2,240 8,962 53 37,812 46 2018 OTW - Typical 2002 

 

 122 3,097 7,837 44 46,221 159 2002 OTB - Typical 2002 

 396 3,057 9,066 48 49,173 159 2009 OTB - Typical 2002 

VA 439 3,057 9,066 48 49,173 159 2009 OTW - Typical 2002 

 759 3,620 10,757 57 53,023 159 2018 OTB - Typical 2002 

 783 3,620 10,757 57 53,023 159 2018 OTW - Typical 2002 

 

 12 331 1,933 10 10,779 12 2002 OTB - Typical 2002 

 691 342 2,183 11 11,461 12 2009 OTB - Typical 2002 

WV 673 342 2,183 11 11,461 12 2009 OTW - Typical 2002 

 722 416 2,484 13 12,390 12 2018 OTB - Typical 2002 

 719 416 2,484 13 12,390 12 2018 OTW - Typical 2002 

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Annual NOx Emissions by Source Sector

0

200,000400,000600,000800,000

1,000,0001,200,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

WV

Tons per year

2002 

2009 OTB

2009 OTW

2018 OTB

2018 OTW

EGU and NonEGU values based on 2002 Typical Emiss

All Fire emissions based on Typical Year values

Appendix G Attachment 12 - Page Number:222
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Annual NOx Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 

 153,349 83,868 158,423 64,891 23,444 11,456 2002 OTB - Typical 2002 

 131,988 80,738 101,323 55,494 26,482 11,456 2009 OTB - Typical 2002 

AL 132,323 70,644 101,323 55,494 26,482 11,456 2009 OTW - Typical 2002 

 135,010 91,052 46,222 42,573 28,754 11,456 2018 OTB - Typical 2002 

 39,942 80,031 46,222 42,573 28,754 11,456 2018 OTW - Typical 2002 

 

 247,099 59,517 466,098 150,519 29,477 19,791 2002 OTB - Typical 2002 

 148,522 67,533 314,307 136,851 31,821 19,791 2009 OTB - Typical 2002 

FL 147,801 67,533 314,307 136,851 31,821 19,791 2009 OTW - Typical 2002 

 159,004 77,551 154,611 111,959 35,047 19,791 2018 OTB - Typical 2002 

 59,446 77,551 154,611 111,959 35,047 19,791 2018 OTW - Typical 2002 

 

 120,785 52,425 308,013 91,386 36,105 13,882 2002 OTB - Typical 2002 

 131,901 53,008 208,393 79,049 38,876 13,882 2009 OTB - Typical 2002 

GA 119,425 53,008 208,393 79,049 38,876 13,882 2009 OTW - Typical 2002 

 128,938 59,005 99,821 60,650 42,260 13,882 2018 OTB - Typical 2002 

 65,559 59,005 99,821 60,650 42,260 13,882 2018 OTW - Typical 2002 

 

 209,802 38,460 154,899 101,261 39,507 1,460 2002 OTB - Typical 2002 

 178,930 37,960 97,912 90,803 42,122 1,460 2009 OTB - Typical 2002 

KY 177,272 37,201 97,912 90,803 42,122 1,460 2009 OTW - Typical 2002 

 182,192 41,776 42,104 77,295 45,597 1,460 2018 OTB - Typical 2002 

 64,674 40,948 42,104 77,295 45,597 1,460 2018 OTW - Typical 2002 

 

 27,254 76,906 111,791 90,686 4,200 3,328 2002 OTB - Typical 2002 

 38,911 70,463 69,949 81,780 4,789 3,328 2009 OTB - Typical 2002 

MS 38,978 70,463 69,949 81,780 4,789 3,328 2009 OTW - Typical 2002 

 38,355 76,738 29,717 68,781 5,230 3,328 2018 OTB - Typical 2002 

 11,206 76,738 29,717 68,781 5,230 3,328 2018 OTW - Typical 2002 

 

 144,730 50,393 341,198 81,448 48,730 5,005 2002 OTB - Typical 2002 

 66,598 46,242 207,648 66,382 53,550 5,005 2009 OTB - Typical 2002 

NC 67,051 46,242 207,648 66,382 53,550 5,005 2009 OTW - Typical 2002 

 64,537 50,044 81,706 45,146 60,073 5,005 2018 OTB - Typical 2002 

 59,917 50,044 81,706 45,146 60,073 5,005 2018 OTW - Typical 2002 

 

 85,555 44,123 140,428 46,789 19,332 5,270 2002 OTB - Typical 2002 

 50,433 43,799 91,696 39,544 20,852 5,270 2009 OTB - Typical 2002 

SC 50,128 42,944 91,696 39,544 20,852 5,270 2009 OTW - Typical 2002 

 55,103 48,314 42,354 29,512 22,467 5,270 2018 OTB - Typical 2002 

 36,264 47,403 42,354 29,512 22,467 5,270 2018 OTW - Typical 2002 

 

 155,028 73,384 233,324 95,968 17,829 2,232 2002 OTB - Typical 2002 

 106,979 62,435 147,757 85,084 19,148 2,232 2009 OTB - Typical 2002 

TN 104,528 61,176 147,757 85,084 19,148 2,232 2009 OTW - Typical 2002 

 112,411 69,374 65,242 69,093 20,928 2,232 2018 OTB - Typical 2002 

 32,411 67,999 65,242 69,093 20,928 2,232 2018 OTW - Typical 2002 

 

 82,911 61,528 219,602 58,524 51,418 978 2002 OTB - Typical 2002 

 64,950 64,298 133,170 50,120 53,344 978 2009 OTB - Typical 2002 

VA 62,810 60,027 133,170 50,120 53,344 978 2009 OTW - Typical 2002 

 56,716 71,480 61,881 36,970 56,668 978 2018 OTB - Typical 2002 

 40,045 66,931 61,881 36,970 56,668 978 2018 OTW - Typical 2002 

 

 222,090 46,715 59,612 34,442 12,687 944 2002 OTB - Typical 2002 

 173,977 42,140 36,049 31,148 13,816 944 2009 OTB - Typical 2002 

WV 174,572 40,469 36,049 31,148 13,816 944 2009 OTW - Typical 2002 

 170,522 46,846 16,274 26,279 15,079 944 2018 OTB - Typical 2002 

 42,227 44,944 16,274 26,279 15,079 944 2018 OTW - Typical 2002 

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Annual PM10 Emissions by Source Sector

0

200,000400,000600,000800,000

1,000,0001,200,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

WV

Tons per year

2002

2009 OTB

2009 OTW

2018 OTB

2018 OTW

EGU and NonEGU values based on 2002 Actual Emissio

All Fire emissions based on Typical Year values

Appendix G Attachment 12 - Page Number:224
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Annual PM10 Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 

 5,737 24,957 3,898 5,331 393,093 50,833 2002 OTB - Typical 2002 

 29,053 25,161 3,188 4,597 411,614 50,833 2009 OTB - Typical 2002 

AL 23,250 25,161 3,188 4,597 411,614 50,833 2009 OTW - Typical 2002 

 31,815 29,278 2,488 3,690 445,168 50,833 2018 OTB - Typical 2002 

 20,450 29,278 2,488 3,690 445,168 50,833 2018 OTW - Typical 2002 

 

 33,182 28,882 11,253 17,692 446,821 98,470 2002 OTB - Typical 2002 

 25,779 27,531 9,953 15,630 507,515 98,470 2009 OTB - Typical 2002 

FL 24,493 27,531 9,953 15,630 507,515 98,470 2009 OTW - Typical 2002 

 27,320 31,890 8,489 13,827 582,832 98,470 2018 OTB - Typical 2002 

 22,204 31,890 8,489 13,827 582,832 98,470 2018 OTW - Typical 2002 

 

 5,447 22,058 7,236 8,295 695,320 62,336 2002 OTB - Typical 2002 

 39,580 23,861 6,103 7,368 776,935 62,336 2009 OTB - Typical 2002 

GA 28,118 23,861 6,103 7,368 776,935 62,336 2009 OTW - Typical 2002 

 41,221 28,177 4,995 6,068 880,800 62,336 2018 OTB - Typical 2002 

 26,905 28,177 4,995 6,068 880,800 62,336 2018 OTW - Typical 2002 

 

 6,000 15,613 3,720 6,389 233,559 6,667 2002 OTB - Typical 2002 

 32,406 15,858 3,002 5,312 242,345 6,667 2009 OTB - Typical 2002 

KY 29,606 15,858 3,002 5,312 242,345 6,667 2009 OTW - Typical 2002 

 33,784 18,587 2,283 4,602 256,544 6,667 2018 OTB - Typical 2002 

 25,733 18,587 2,283 4,602 256,544 6,667 2018 OTW - Typical 2002 

 

 4,783 19,680 2,856 5,551 343,377 14,693 2002 OTB - Typical 2002 

 5,864 19,439 2,290 4,754 356,516 14,693 2009 OTB - Typical 2002 

MS 5,883 19,439 2,290 4,754 356,516 14,693 2009 OTW - Typical 2002 

 6,268 23,145 1,688 3,873 375,931 14,693 2018 OTB - Typical 2002 

 6,459 23,145 1,688 3,873 375,931 14,693 2018 OTW - Typical 2002 

 

 22,689 14,507 6,905 7,449 303,492 20,488 2002 OTB - Typical 2002 

 23,028 14,301 5,861 6,210 317,847 20,488 2009 OTB - Typical 2002 

NC 21,459 14,301 5,861 6,210 317,847 20,488 2009 OTW - Typical 2002 

 21,417 16,002 4,299 4,474 345,275 20,488 2018 OTB - Typical 2002 

 20,258 16,002 4,299 4,474 345,275 20,488 2018 OTW - Typical 2002 

 

 23,492 18,149 3,446 4,211 260,858 26,304 2002 OTB - Typical 2002 

 18,023 17,368 2,878 3,593 278,852 26,304 2009 OTB - Typical 2002 

SC 17,493 17,368 2,878 3,593 278,852 26,304 2009 OTW - Typical 2002 

 19,290 20,272 2,258 2,889 304,940 26,304 2018 OTB - Typical 2002 

 19,182 20,272 2,258 2,889 304,940 26,304 2018 OTW - Typical 2002 

 

 14,537 35,982 5,338 7,145 211,903 8,875 2002 OTB - Typical 2002 

 17,735 33,838 4,238 6,218 225,650 8,875 2009 OTB - Typical 2002 

TN 17,159 33,838 4,238 6,218 225,650 8,875 2009 OTW - Typical 2002 

 19,103 41,466 3,199 5,019 245,893 8,875 2018 OTB - Typical 2002 

 12,432 41,466 3,199 5,019 245,893 8,875 2018 OTW - Typical 2002 

 

 3,790 12,799 4,537 7,928 237,577 18,160 2002 OTB - Typical 2002 

 15,343 13,470 3,760 6,763 252,924 18,160 2009 OTB - Typical 2002 

VA 12,804 13,470 3,760 6,763 252,924 18,160 2009 OTW - Typical 2002 

 14,390 15,661 3,343 5,564 275,790 18,160 2018 OTB - Typical 2002 

 12,653 15,661 3,343 5,564 275,790 18,160 2018 OTW - Typical 2002 

 

 7,145 14,866 1,395 2,072 115,346 3,276 2002 OTB - Typical 2002 

 36,442 14,926 1,096 1,819 115,410 3,276 2009 OTB - Typical 2002 

WV 31,780 14,926 1,096 1,819 115,410 3,276 2009 OTW - Typical 2002 

 37,425 18,433 844 1,381 121,964 3,276 2018 OTB - Typical 2002 

 24,253 18,433 844 1,381 121,964 3,276 2018 OTW - Typical 2002 

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Annual PM2.5 Emissions by Source Sector

0

50,000

100,000150,000200,000250,000300,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

WV

Tons per year

2002

2009 OTB

2009 OTW

2018 OTB

2018 OTW

EGU and NonEGU values based on 2002 Typical Emissions

All Fire emissions based on Typical Year values

Appendix G Attachment 12 - Page Number:226
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MACTEC, Inc. 214

Annual PM2.5 Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 

 3,131 19,016 2,794 4,877 73,352 44,812 2002 OTB - Typical 2002 

 24,875 19,184 2,049 4,144 76,248 44,812 2009 OTB - Typical 2002 

AL 19,190 19,184 2,049 4,144 76,248 44,812 2009 OTW - Typical 2002 

 27,280 22,268 1,262 3,231 82,449 44,812 2018 OTB - Typical 2002 

 16,279 22,268 1,262 3,231 82,449 44,812 2018 OTW - Typical 2002 

 

 25,761 24,569 7,852 16,739 81,341 88,756 2002 OTB - Typical 2002 

 19,307 23,063 6,216 14,786 90,487 88,756 2009 OTB - Typical 2002 

FL 18,186 23,063 6,216 14,786 90,487 88,756 2009 OTW - Typical 2002 

 20,848 26,622 4,242 13,044 101,872 88,756 2018 OTB - Typical 2002 

 16,278 26,622 4,242 13,044 101,872 88,756 2018 OTW - Typical 2002 

 

 2,137 17,893 5,158 7,899 133,542 55,712 2002 OTB - Typical 2002 

 33,111 19,562 3,869 7,014 146,691 55,712 2009 OTB - Typical 2002 

GA 22,163 19,562 3,869 7,014 146,691 55,712 2009 OTW - Typical 2002 

 34,361 23,110 2,517 5,769 163,925 55,712 2018 OTB - Typical 2002 

 20,549 23,110 2,517 5,769 163,925 55,712 2018 OTW - Typical 2002 

 

 3,605 10,729 2,693 5,998 52,765 6,310 2002 OTB - Typical 2002 

 26,640 10,837 1,941 4,978 54,397 6,310 2009 OTB - Typical 2002 

KY 23,915 10,837 1,941 4,978 54,397 6,310 2009 OTW - Typical 2002 

 27,857 12,738 1,160 4,289 57,110 6,310 2018 OTB - Typical 2002 

 19,915 12,738 1,160 4,289 57,110 6,310 2018 OTW - Typical 2002 

 

 4,384 10,187 2,109 5,200 63,135 13,680 2002 OTB - Typical 2002 

 5,511 9,459 1,522 4,440 65,321 13,680 2009 OTB - Typical 2002 

MS 5,530 9,459 1,522 4,440 65,321 13,680 2009 OTW - Typical 2002 

 5,919 11,068 876 3,597 68,338 13,680 2018 OTB - Typical 2002 

 6,110 11,068 876 3,597 68,338 13,680 2018 OTW - Typical 2002 

 

 16,428 11,204 4,816 7,079 69,663 19,491 2002 OTB - Typical 2002 

 17,449 10,888 3,643 5,889 75,570 19,491 2009 OTB - Typical 2002 

NC 16,034 10,888 3,643 5,889 75,570 19,491 2009 OTW - Typical 2002 

 15,636 12,136 2,158 4,215 85,018 19,491 2018 OTB - Typical 2002 

 14,702 12,136 2,158 4,215 85,018 19,491 2018 OTW - Typical 2002 

 

 19,238 13,565 2,496 3,985 51,413 23,511 2002 OTB - Typical 2002 

 14,471 12,977 1,870 3,396 54,230 23,511 2009 OTB - Typical 2002 

SC 14,079 12,977 1,870 3,396 54,230 23,511 2009 OTW - Typical 2002 

 15,601 15,092 1,154 2,718 58,441 23,511 2018 OTB - Typical 2002 

 15,509 15,092 1,154 2,718 58,441 23,511 2018 OTW - Typical 2002 

 

 11,918 29,130 3,919 6,756 49,131 8,730 2002 OTB - Typical 2002 

 15,770 27,313 2,782 5,873 51,753 8,730 2009 OTB - Typical 2002 

TN 15,228 27,313 2,782 5,873 51,753 8,730 2009 OTW - Typical 2002 

 17,103 33,502 1,643 4,724 55,712 8,730 2018 OTB - Typical 2002 

 10,514 33,502 1,643 4,724 55,712 8,730 2018 OTW - Typical 2002 

 

 2,559 9,868 3,090 7,486 52,271 17,361 2002 OTB - Typical 2002 

 13,451 10,368 2,254 6,388 54,587 17,361 2009 OTB - Typical 2002 

VA 11,237 10,368 2,254 6,388 54,587 17,361 2009 OTW - Typical 2002 

 12,366 12,062 1,641 5,241 58,141 17,361 2018 OTB - Typical 2002 

 10,755 12,062 1,641 5,241 58,141 17,361 2018 OTW - Typical 2002 

 

 3,356 12,154 1,003 1,941 25,850 3,239 2002 OTB - Typical 2002 

 29,773 12,138 703 1,699 25,835 3,239 2009 OTB - Typical 2002 

WV 25,251 12,138 703 1,699 25,835 3,239 2009 OTW - Typical 2002 

 30,628 15,045 428 1,284 27,088 3,239 2018 OTB - Typical 2002 

 17,548 15,045 428 1,284 27,088 3,239 2018 OTW - Typical 2002 

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Annual SO2 Emissions by Source Sector

0

100,000200,000300,000400,000500,000600,000700,000800,000

AL

AL

AL

FL

FL

FL

GA

GA

GA

KY

KY

KY

MS

MS

MS

NC

NC

NC

SC

SC

SC

TN

TN

TN

VA

VA

VA

WV

WV

Tons per year

2002

2009 OTB

2009 OTW

2018 OTB

2018 OTW

EGU and NonEGU values based on 2002 Typical Emissio

All Fire emissions based on Typical Year values

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Annual SO2 Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 

AL 421,734 96,447 6,885 7,539 47,074 2,559 2002 OTB - Typical 2002 

AL 465,576 100,845 635 3,463 17,818 2,559 2009 OTB - Typical 2002 

AL 314,841 100,845 635 3,463 17,818 2,559 2009 OTW - Typical 2002 

AL 375,305 112,771 720 2,815 49,975 2,559 2018 OTB - Typical 2002 

AL 226,506 112,771 720 2,815 49,975 2,559 2018 OTW - Typical 2002 

 

FL 443,152 70,165 20,872 17,023 40,537 4,129 2002 OTB - Typical 2002 

FL 219,072 76,851 2,120 8,380 52,390 4,129 2009 OTB - Typical 2002 

FL 199,834 76,851 2,120 8,380 52,390 4,129 2009 OTW - Typical 2002 

FL 215,177 87,065 2,533 7,511 59,413 4,129 2018 OTB - Typical 2002 

FL 126,280 87,065 2,533 7,511 59,413 4,129 2018 OTW - Typical 2002 

 

GA 433,513 62,032 12,155 8,145 57,555 2,815 2002 OTB - Typical 2002 

GA 582,078 63,348 1,254 2,588 57,377 2,815 2009 OTB - Typical 2002 

GA 394,425 63,348 1,254 2,588 57,377 2,815 2009 OTW - Typical 2002 

GA 554,013 70,386 1,458 1,702 61,155 2,815 2018 OTB - Typical 2002 

GA 221,615 70,386 1,458 1,702 61,155 2,815 2018 OTW - Typical 2002 

 

KY 508,139 34,026 5,974 13,739 41,805 136 2002 OTB - Typical 2002 

KY 483,235 35,479 585 9,092 40,779 136 2009 OTB - Typical 2002 

KY 342,670 35,479 585 9,092 40,779 136 2009 OTW - Typical 2002 

KY 429,418 38,816 651 8,536 42,326 136 2018 OTB - Typical 2002 

KY 225,772 38,816 651 8,536 42,326 136 2018 OTW - Typical 2002 

 

MS 57,263 36,071 4,604 11,551 771 100 2002 OTB - Typical 2002 

MS 76,855 35,028 397 7,232 637 100 2009 OTB - Typical 2002 

MS 76,855 35,028 397 7,232 637 100 2009 OTW - Typical 2002 

MS 74,505 40,318 441 6,638 831 100 2018 OTB - Typical 2002 

MS 23,768 40,318 441 6,638 831 100 2018 OTW - Typical 2002 

 

NC 472,192 51,049 13,343 7,207 7,096 423 2002 OTB - Typical 2002 

NC 182,356 52,693 1,311 1,798 7,607 423 2009 OTB - Typical 2002 

NC 132,054 52,693 1,311 1,798 7,607 423 2009 OTW - Typical 2002 

NC 133,691 58,671 1,323 838 8,273 423 2018 OTB - Typical 2002 

NC 78,205 58,671 1,323 838 8,273 423 2018 OTW - Typical 2002 

 

SC 203,978 56,329 5,958 4,449 12,900 1,187 2002 OTB - Typical 2002 

SC 163,560 53,746 556 1,633 12,945 1,187 2009 OTB - Typical 2002 

SC 143,492 53,746 556 1,633 12,945 1,187 2009 OTW - Typical 2002 

SC 178,938 60,300 643 1,195 13,517 1,187 2018 OTB - Typical 2002 

SC 152,457 60,300 643 1,195 13,517 1,187 2018 OTW - Typical 2002 

 

TN 325,779 90,374 9,184 10,413 29,897 59 2002 OTB - Typical 2002 

TN 436,453 85,275 831 5,649 29,787 59 2009 OTB - Typical 2002 

TN 279,931 85,275 831 5,649 29,787 59 2009 OTW - Typical 2002 

TN 323,654 92,396 944 5,205 31,047 59 2018 OTB - Typical 2002 

TN 103,602 92,396 944 5,205 31,047 59 2018 OTW - Typical 2002 

 

VA 234,714 68,038 7,218 8,796 9,510 99 2002 OTB - Typical 2002 

VA 220,686 76,081 900 2,248 10,619 99 2009 OTB - Typical 2002 

VA 140,665 76,081 900 2,248 10,619 99 2009 OTW - Typical 2002 

VA 181,338 85,351 1,059 1,217 11,479 99 2018 OTB - Typical 2002 

VA 115,987 85,351 1,059 1,217 11,479 99 2018 OTW - Typical 2002 

 

WV 497,991 54,045 2,489 2,305 11,667 16 2002 OTB - Typical 2002 

WV 598,555 54,701 227 392 12,156 16 2009 OTB - Typical 2002 

WV 246,851 54,701 227 392 12,156 16 2009 OTW - Typical 2002 

WV 482,959 60,141 255 56 13,450 16 2018 OTB - Typical 2002 

WV 111,937 60,141 255 56 13,450 16 2018 OTW - Typical 2002 

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Annual VOC Emissions by Source Sector

0

200,000400,000600,000800,000

1,000,0001,200,0001,400,000

AL

FL

GA

KY

MS

NC

SC

TN

VA

WV

Tons per year

2002

2009 OTB

2009 OTW

2018 OTB

2018 OTW

EGU and NonEGU values based on 2002 Typical Emiss

All Fire emissions based on Typical Year values

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Annual VOC Emissions by Source Sector 

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 

 1,501 47,893 119,790 44,978 196,538 26,526 2002 OTB - Typical 2002 

 1,261 47,600 72,848 35,498 157,405 26,526 2009 OTB - Typical 2002 

AL 1,312 47,600 72,848 35,498 157,405 26,526 2009 OTW - Typical 2002 

1,574 55,373 47,296 26,338 168,507 26,526 2018 OTB - Typical 2002 

1,612 55,373 47,296 26,338 168,507 26,526 2018 OTW - Typical 2002 

 

2,362 36,301 495,225 201,960 439,019 51,527 2002 OTB - Typical 2002 

1,562 39,255 323,290 144,749 462,198 51,527 2009 OTB - Typical 2002 

FL 1,559 39,255 323,290 144,749 462,198 51,527 2009 OTW - Typical 2002 

2,052 46,049 216,620 128,131 533,141 51,527 2018 OTB - Typical 2002 

1,988 46,049 216,620 128,131 533,141 51,527 2018 OTW - Typical 2002 

 

984 33,753 267,378 63,337 309,411 33,918 2002 OTB - Typical 2002 

1,497 34,153 184,239 46,722 294,204 33,918 2009 OTB - Typical 2002 

GA 1,499 34,153 184,239 46,722 294,204 33,918 2009 OTW - Typical 2002 

1,794 40,354 105,507 36,014 342,661 33,918 2018 OTB - Typical 2002 

1,790 40,354 105,507 36,014 342,661 33,918 2018 OTW - Typical 2002 

 

1,518 44,854 98,311 34,156 100,174 3,338 2002 OTB - Typical 2002 

1,594 47,733 63,258 23,980 94,253 3,338 2009 OTB - Typical 2002 

KY 1,580 47,733 63,258 23,980 94,253 3,338 2009 OTW - Typical 2002 

1,635 55,729 39,084 20,795 102,117 3,338 2018 OTB - Typical 2002 

1,616 55,729 39,084 20,795 102,117 3,338 2018 OTW - Typical 2002 

 

696 43,401 82,810 32,401 135,106 13,625 2002 OTB - Typical 2002 

584 38,119 49,670 27,650 125,382 13,625 2009 OTB - Typical 2002 

MS 590 38,119 49,670 27,650 125,382 13,625 2009 OTW - Typical 2002 

766 45,966 30,734 20,576 139,419 13,625 2018 OTB - Typical 2002 

827 45,966 30,734 20,576 139,419 13,625 2018 OTW - Typical 2002 

 

1,043 72,856 253,374 71,378 346,060 12,499 2002 OTB - Typical 2002 

1,100 70,146 163,803 52,430 252,553 12,499 2009 OTB - Typical 2002 

NC 1,093 70,146 163,803 52,430 252,553 12,499 2009 OTW - Typical 2002 

1,183 75,985 88,620 40,576 234,207 12,499 2018 OTB - Typical 2002 

1,172 75,985 88,620 40,576 234,207 12,499 2018 OTW - Typical 2002 

 

438 38,493 106,792 41,374 187,466 14,666 2002 OTB - Typical 2002 

 601 36,410 67,281 30,531 176,104 14,666 2009 OTB - Typical 2002 

SC 626 36,410 67,281 30,531 176,104 14,666 2009 OTW - Typical 2002 

745 44,586 44,700 24,989 196,946 14,666 2018 OTB - Typical 2002 

754 44,586 44,700 24,989 196,946 14,666 2018 OTW - Typical 2002 

 

819 87,975 169,914 49,056 161,069 5,153 2002 OTB - Typical 2002 

866 89,128 108,200 38,686 160,265 5,153 2009 OTB - Typical 2002 

TN 854 89,128 108,200 38,686 160,265 5,153 2009 OTW - Typical 2002 

899 111,372 64,665 28,667 188,977 5,153 2018 OTB - Typical 2002 

826 111,372 64,665 28,667 188,977 5,153 2018 OTW - Typical 2002 

 

672 42,589 144,684 57,050 129,792 912 2002 OTB - Typical 2002 

546 44,359 89,678 40,897 120,022 912 2009 OTB - Typical 2002 

VA 503 44,359 89,678 40,897 120,022 912 2009 OTW - Typical 2002 

694 53,968 60,454 34,412 128,160 912 2018 OTB - Typical 2002 

674 53,968 60,454 34,412 128,160 912 2018 OTW - Typical 2002 

 

1,128 14,599 40,066 14,805 61,490 2,184 2002 OTB - Typical 2002 

1,442 14,015 23,907 14,249 57,082 2,184 2009 OTB - Typical 2002 

WV 1,397 14,015 23,907 14,249 57,082 2,184 2009 OTW - Typical 2002 

1,471 16,636 15,463 9,500 62,164 2,184 2018 OTB - Typical 2002 

1,456 16,636 15,463 9,500 62,164 2,184 2018 OTW - Typical 2002 

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APPENDIX B: 

STATE VMT TOTALS 

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State VMT Totals 

Million Miles Per Year 

2002 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL 

AL 31,982 12,728 4,347 1,630 63 69 4,709 196 55,723 

FL 105,340 40,835 13,945 5,079 206 220 12,465 591 178,681 

GA 61,660 24,394 8,331 3,103 121 132 8,673 371 106,785 

KY 28,751 12,189 3,366 1,606 55 55 4,827 171 51,020 

MS 23,933 6,724 439 1,025 330 125 3,610 92 36,278 

NC 51,189 30,339 10,787 4,119 230 230 9,440 461 106,795 

SC 26,672 10,750 3,671 1,395 52 58 4,306 171 47,074 

TN 30,809 20,272 6,922 2,943 52 111 6,810 397 68,316 

VA 36,336 24,784 8,667 2,148 61 139 4,969 369 77,472 

WV 9,010 5,931 2,028 732 25 37 1,664 117 19,544 

 

2009 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL 

AL 30,638 18,598 5,511 2,069 65 72 5,976 249 63,178 

FL 107,641 62,449 18,697 6,820 215 230 16,743 794 213,590 

GA 61,569 36,641 10,933 4,077 126 137 11,374 487 125,343 

KY 28,006 16,984 4,428 1,983 58 57 5,983 231 57,729 

MS 23,641 10,131 573 1,341 356 135 4,719 120 41,017 

NC 48,495 43,484 15,122 4,576 40 224 10,928 527 123,396 

SC 26,451 16,119 4,796 1,824 55 61 5,617 223 55,147 

TN 28,775 28,650 8,521 3,627 52 111 8,391 490 78,615 

VA 33,663 34,814 10,597 2,624 61 137 6,073 451 88,419 

WV 8,128 8,205 2,427 878 25 37 1,995 140 21,835 

 

2018 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL 

AL 31,706 23,562 6,990 2,634 67 84 7,607 317 72,966 

FL 116,576 83,385 24,996 9,156 221 301 22,491 1,066 258,191 

GA 65,214 47,687 14,245 5,332 129 171 14,853 637 148,269 

KY 29,353 21,058 5,558 2,463 60 66 7,454 288 66,300 

MS 24,787 12,984 736 1,727 372 159 6,076 155 46,996 

NC 42,247 51,568 18,260 4,985 279 279 11,396 553 129,566 

SC 27,930 20,880 6,220 2,375 57 75 7,306 290 65,133 

TN 29,253 35,702 10,629 4,538 52 130 10,500 613 91,417 

VA 35,030 44,438 13,543 3,358 62 164 7,770 578 104,944 

WV 8,130 10,025 2,969 1,078 25 41 2,451 172 24,891 

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APPENDIX C: 

STATE TIER 1 EMISSION TOTALS 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

AL 2002 01 FUEL COMB. ELEC. UTIL. 11,460 239 154,704 7,845 4,176 423,736 2,288 

AL 2002 02 FUEL COMB. INDUSTRIAL 67,121 234 51,527 6,729 3,791 40,918 2,237 

AL 2002 03 FUEL COMB. OTHER 70,498 169 19,237 6,411 5,528 39,606 56,120 

AL 2002 04 CHEMICAL & ALLIED PRODUCT 5,721 35 2,032 1,220 888 12,770 7,273 

AL 2002 05 METALS PROCESSING 38,247 376 6,011 9,107 7,803 14,039 3,299 

AL 2002 06 PETROLEUM & RELATED 13,606 0 878 194 155 22,991 4,024 

AL 2002 07 OTHER INDUSTRIAL PROCESSES 47,676 1,468 25,252 22,689 9,516 17,904 25,304 

AL 2002 08 SOLVENT UTILIZATION 216 0 226 149 126 3 108,437 

AL 2002 09 STORAGE & TRANSPORT 174 0 230 1,086 636 13 16,522 

AL 2002 10 WASTE DISPOSAL & RECYCLING 86,302 10 3,465 13,960 13,073 489 11,334 

AL 2002 11 HIGHWAY VEHICLES 1,366,056 5,576 158,423 3,898 2,794 6,885 119,790 

AL 2002 12 OFF-HIGHWAY 414,385 33 65,366 4,787 4,502 7,584 60,487 

AL 2002 14 MISCELLANEOUS 442,778 59,864 9,343 408,115 79,127 2,559 21,686 

2002 

Total 2,564,239 68,005 496,695 486,190 132,115 589,499 438,800 

AL 2009 01 FUEL COMB. ELEC. UTIL. 14,986 359 82,305 6,969 3,921 378,052 2,473 

AL 2009 02 FUEL COMB. INDUSTRIAL 68,146 274 36,301 6,140 3,438 40,651 2,191 

AL 2009 03 FUEL COMB. OTHER 52,256 158 19,514 5,904 5,104 36,048 31,403 

AL 2009 04 CHEMICAL & ALLIED PRODUCT 6,118 38 2,273 1,257 912 13,660 6,613 

AL 2009 05 METALS PROCESSING 38,969 500 6,021 9,062 7,756 16,629 3,305 

AL 2009 06 PETROLEUM & RELATED 13,241 0 858 221 177 22,495 3,336 

AL 2009 07 OTHER INDUSTRIAL PROCESSES 52,004 1,571 26,340 24,196 10,197 19,383 26,519 

AL 2009 08 SOLVENT UTILIZATION 247 0 257 165 139 4 92,631 

AL 2009 09 STORAGE & TRANSPORT 192 0 253 1,146 584 14 17,738 

AL 2009 10 WASTE DISPOSAL & RECYCLING 87,225 11 3,634 14,504 13,485 590 11,207 

AL 2009 11 HIGHWAY VEHICLES 942,793 6,350 101,323 3,188 2,049 635 72,848 

AL 2009 12 OFF-HIGHWAY 454,686 36 56,862 4,027 3,776 3,471 50,249 

AL 2009 14 MISCELLANEOUS 463,498 65,899 9,788 428,698 82,679 2,681 22,657 

2009 

Total 2,194,361 75,195 345,729 505,475 134,217 534,314 343,169 

AL 2018 01 FUEL COMB. ELEC. UTIL. 24,342 1,072 64,358 7,822 4,768 305,262 2,952 

AL 2018 02 FUEL COMB. INDUSTRIAL 69,198 275 38,781 6,462 3,613 43,170 2,295 

AL 2018 03 FUEL COMB. OTHER 43,744 164 20,185 5,641 4,818 37,162 21,215 

AL 2018 04 CHEMICAL & ALLIED PRODUCT 7,384 46 2,804 1,523 1,106 16,509 8,040 

AL 2018 05 METALS PROCESSING 49,770 674 7,519 11,036 9,423 21,824 4,234 

AL 2018 06 PETROLEUM & RELATED 13,002 0 848 258 207 22,242 3,421 

AL 2018 07 OTHER INDUSTRIAL PROCESSES 60,452 1,732 30,831 27,727 11,812 21,843 30,267 

AL 2018 08 SOLVENT UTILIZATION 301 0 317 200 169 4 112,412 

AL 2018 09 STORAGE & TRANSPORT 234 0 307 1,366 699 17 18,900 

AL 2018 10 WASTE DISPOSAL & RECYCLING 88,758 13 3,867 15,343 14,143 718 11,938 

AL 2018 11 HIGHWAY VEHICLES 797,966 7,296 46,222 2,488 1,262 720 47,296 

AL 2018 12 OFF-HIGHWAY 488,924 42 43,799 3,041 2,835 2,818 40,407 

AL 2018 14 MISCELLANEOUS 464,235 73,529 9,803 458,551 85,538 2,686 22,686 

2018 

Total 2,108,311 84,843 269,643 541,458 140,394 474,974 326,063 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

FL 2002 01 FUEL COMB. ELEC. UTIL. 55,899 222 282,507 21,391 15,575 483,590 2,531 

FL 2002 02 FUEL COMB. INDUSTRIAL 64,794 131 45,153 20,442 18,547 42,524 4,219 

FL 2002 03 FUEL COMB. OTHER 49,230 99 11,593 8,464 8,074 20,031 16,123 

FL 2002 04 CHEMICAL & ALLIED PRODUCT 745 1,101 2,221 1,868 1,488 34,462 3,542 

FL 2002 05 METALS PROCESSING 1,404 1 194 449 334 882 82 

FL 2002 06 PETROLEUM & RELATED 1,070 0 560 259 129 470 724 

FL 2002 07 OTHER INDUSTRIAL PROCESSES 18,586 19 12,325 23,419 11,844 6,515 27,024 

FL 2002 08 SOLVENT UTILIZATION 0 0 1 128 110 0 304,582 

FL 2002 09 STORAGE & TRANSPORT 161 0 561 1,645 720 38 79,281 

FL 2002 10 WASTE DISPOSAL & RECYCLING 175,989 351 6,123 22,142 21,604 659 17,449 

FL 2002 11 HIGHWAY VEHICLES 4,693,893 18,078 466,098 11,253 7,852 20,872 495,225 

FL 2002 12 OFF-HIGHWAY 1,920,729 134 180,627 18,281 17,415 20,614 272,072 

FL 2002 14 MISCELLANEOUS 764,337 40,324 15,083 498,855 115,287 4,129 41,274 

2002 

Total 7,746,839 60,460 1,023,045 628,597 218,979 634,786 1,264,128 

FL 2009 01 FUEL COMB. ELEC. UTIL. 35,928 1,631 86,165 9,007 5,910 186,055 1,910 

FL 2009 02 FUEL COMB. INDUSTRIAL 69,972 146 44,480 16,265 14,827 38,225 4,473 

FL 2009 03 FUEL COMB. OTHER 33,014 100 10,800 7,555 7,174 19,882 10,907 

FL 2009 04 CHEMICAL & ALLIED PRODUCT 901 1,231 2,461 1,908 1,526 34,961 3,821 

FL 2009 05 METALS PROCESSING 1,545 1 176 361 251 993 82 

FL 2009 06 PETROLEUM & RELATED 1,190 0 612 304 156 519 748 

FL 2009 07 OTHER INDUSTRIAL PROCESSES 18,593 26 13,521 33,084 19,357 6,881 26,413 

FL 2009 08 SOLVENT UTILIZATION 0 0 1 132 113 0 319,723 

FL 2009 09 STORAGE & TRANSPORT 187 0 621 1,661 727 50 83,880 

FL 2009 10 WASTE DISPOSAL & RECYCLING 177,953 342 6,251 22,971 22,364 698 17,241 

FL 2009 11 HIGHWAY VEHICLES 3,446,095 21,737 314,307 9,953 6,216 2,120 323,290 

FL 2009 12 OFF-HIGHWAY 2,104,920 148 163,794 15,613 14,866 8,967 209,543 

FL 2009 14 MISCELLANEOUS 764,004 41,471 15,075 557,331 120,796 4,129 41,290 

2009 

Total 6,654,301 66,833 658,265 676,145 214,282 303,479 1,043,321 

FL 2018 01 FUEL COMB. ELEC. UTIL. 53,772 2,976 73,125 9,953 6,843 132,177 2,376 

FL 2018 02 FUEL COMB. INDUSTRIAL 76,847 156 47,835 17,808 16,255 40,443 4,892 

FL 2018 03 FUEL COMB. OTHER 27,094 110 12,344 7,254 6,852 20,975 8,878 

FL 2018 04 CHEMICAL & ALLIED PRODUCT 1,200 1,448 3,119 2,367 1,907 41,395 4,739 

FL 2018 05 METALS PROCESSING 1,973 2 225 466 323 1,325 106 

FL 2018 06 PETROLEUM & RELATED 1,513 0 778 387 198 659 918 

FL 2018 07 OTHER INDUSTRIAL PROCESSES 20,748 35 15,855 39,871 23,301 7,741 29,716 

FL 2018 08 SOLVENT UTILIZATION 0 0 1 158 135 0 387,657 

FL 2018 09 STORAGE & TRANSPORT 226 0 690 2,008 879 58 87,732 

FL 2018 10 WASTE DISPOSAL & RECYCLING 180,730 418 6,486 24,140 23,427 769 18,335 

FL 2018 11 HIGHWAY VEHICLES 3,086,330 26,154 154,611 8,489 4,242 2,533 216,620 

FL 2018 12 OFF-HIGHWAY 2,323,327 171 127,885 12,497 11,868 7,536 183,452 

FL 2018 14 MISCELLANEOUS 763,701 43,251 15,068 628,984 127,364 4,129 41,338 

2018 

Total 6,537,461 74,720 458,023 754,381 223,592 259,739 986,760 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

GA 2002 01 FUEL COMB. ELEC. UTIL. 9,650 86 148,126 11,467 5,070 517,633 1,256 

GA 2002 02 FUEL COMB. INDUSTRIAL 59,492 27 53,039 12,037 7,886 88,791 3,956 

GA 2002 03 FUEL COMB. OTHER 63,314 17 14,465 10,142 10,057 10,740 27,226 

GA 2002 04 CHEMICAL & ALLIED PRODUCT 5,387 920 2,277 391 305 2,721 2,668 

GA 2002 05 METALS PROCESSING 330 0 60 147 94 0 70 

GA 2002 06 PETROLEUM & RELATED 41 0 3 69 44 68 175 

GA 2002 07 OTHER INDUSTRIAL PROCESSES 27,960 2,666 12,215 39,630 13,073 8,701 26,999 

GA 2002 08 SOLVENT UTILIZATION 4 0 22 13 13 0 234,744 

GA 2002 09 STORAGE & TRANSPORT 39 0 6 583 360 0 26,334 

GA 2002 10 WASTE DISPOSAL & RECYCLING 203,892 16 6,872 29,227 28,311 312 18,964 

GA 2002 11 HIGHWAY VEHICLES 2,833,468 10,524 308,013 7,236 5,158 12,155 267,378 

GA 2002 12 OFF-HIGHWAY 791,158 60 97,961 8,618 8,226 9,005 85,965 

GA 2002 14 MISCELLANEOUS 498,622 83,032 10,279 687,028 116,756 2,815 25,618 

2002 

Total 4,493,357 97,349 653,338 806,587 195,354 652,942 721,352 

GA 2009 01 FUEL COMB. ELEC. UTIL. 23,721 686 98,497 17,891 10,907 417,449 2,314 

GA 2009 02 FUEL COMB. INDUSTRIAL 63,067 28 53,726 11,206 7,390 89,850 4,163 

GA 2009 03 FUEL COMB. OTHER 45,184 17 15,347 8,496 8,400 10,981 15,683 

GA 2009 04 CHEMICAL & ALLIED PRODUCT 6,044 1,032 2,531 436 341 2,743 2,814 

GA 2009 05 METALS PROCESSING 363 0 61 159 100 0 47 

GA 2009 06 PETROLEUM & RELATED 50 0 4 83 54 82 154 

GA 2009 07 OTHER INDUSTRIAL PROCESSES 29,976 2,902 12,528 45,339 14,758 7,662 28,441 

GA 2009 08 SOLVENT UTILIZATION 4 0 25 14 14 0 216,248 

GA 2009 09 STORAGE & TRANSPORT 45 0 7 649 401 0 27,821 

GA 2009 10 WASTE DISPOSAL & RECYCLING 218,460 18 7,419 31,955 30,900 360 18,711 

GA 2009 11 HIGHWAY VEHICLES 2,053,694 12,660 208,393 6,103 3,869 1,254 184,239 

GA 2009 12 OFF-HIGHWAY 882,970 68 85,733 7,521 7,175 2,725 67,686 

GA 2009 14 MISCELLANEOUS 515,329 91,406 10,637 765,043 125,665 2,914 26,388 

2009 

Total 3,838,907 108,817 494,908 894,896 209,973 536,020 594,708 

GA 2018 01 FUEL COMB. ELEC. UTIL. 44,476 1,677 75,717 20,909 13,983 230,856 2,841 

GA 2018 02 FUEL COMB. INDUSTRIAL 67,067 30 57,232 11,755 7,769 94,403 4,424 

GA 2018 03 FUEL COMB. OTHER 39,440 17 17,801 7,722 7,622 11,958 11,482 

GA 2018 04 CHEMICAL & ALLIED PRODUCT 7,076 1,208 2,982 517 405 3,436 3,524 

GA 2018 05 METALS PROCESSING 421 0 76 185 118 0 55 

GA 2018 06 PETROLEUM & RELATED 63 0 5 105 68 104 191 

GA 2018 07 OTHER INDUSTRIAL PROCESSES 33,611 3,559 14,460 55,130 17,899 8,748 33,333 

GA 2018 08 SOLVENT UTILIZATION 5 0 30 22 22 0 264,326 

GA 2018 09 STORAGE & TRANSPORT 54 0 9 764 470 0 29,409 

GA 2018 10 WASTE DISPOSAL & RECYCLING 235,690 22 8,120 35,280 34,038 423 20,411 

GA 2018 11 HIGHWAY VEHICLES 1,765,020 14,871 99,821 4,995 2,517 1,458 105,507 

GA 2018 12 OFF-HIGHWAY 973,872 79 64,579 6,015 5,730 1,709 56,761 

GA 2018 14 MISCELLANEOUS 515,220 102,075 10,635 859,835 134,730 2,914 26,368 

2018 

Total 3,682,015 123,537 351,467 1,003,235 225,372 356,010 558,631 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

KY 2002 01 FUEL COMB. ELEC. UTIL. 12,607 321 201,928 4,795 2,847 495,153 1,481 

KY 2002 02 FUEL COMB. INDUSTRIAL 14,110 182 60,716 2,155 1,463 41,825 1,566 

KY 2002 03 FUEL COMB. OTHER 40,806 55 4,997 7,679 7,352 9,647 12,711 

KY 2002 04 CHEMICAL & ALLIED PRODUCT 176 214 296 774 581 2,345 3,462 

KY 2002 05 METALS PROCESSING 89,197 6 1,082 3,396 2,720 12,328 1,508 

KY 2002 06 PETROLEUM & RELATED 4,304 335 2,519 308 205 5,747 2,895 

KY 2002 07 OTHER INDUSTRIAL PROCESSES 6,493 78 6,518 31,429 10,394 3,333 25,388 

KY 2002 08 SOLVENT UTILIZATION 0 10 9 317 241 1 61,834 

KY 2002 09 STORAGE & TRANSPORT 33 8 15 1,920 1,177 3 18,853 

KY 2002 10 WASTE DISPOSAL & RECYCLING 20,622 8 1,768 7,229 6,476 606 7,927 

KY 2002 11 HIGHWAY VEHICLES 1,260,682 5,044 154,899 3,720 2,693 5,974 98,311 

KY 2002 12 OFF-HIGHWAY 325,993 31 104,571 6,425 6,046 14,043 44,805 

KY 2002 14 MISCELLANEOUS 25,849 51,026 556 197,402 28,291 146 5,238 

2002 

Total 1,800,871 57,318 539,873 267,547 70,486 591,151 285,977 

KY 2009 01 FUEL COMB. ELEC. UTIL. 15,812 400 92,021 6,463 4,279 290,193 1,369 

KY 2009 02 FUEL COMB. INDUSTRIAL 14,986 195 61,683 2,105 1,456 42,433 1,476 

KY 2009 03 FUEL COMB. OTHER 30,045 54 5,178 7,035 6,725 10,123 9,148 

KY 2009 04 CHEMICAL & ALLIED PRODUCT 179 249 300 851 633 2,384 3,635 

KY 2009 05 METALS PROCESSING 99,428 7 1,156 3,246 2,550 13,735 1,772 

KY 2009 06 PETROLEUM & RELATED 4,818 377 2,828 344 230 6,460 3,052 

KY 2009 07 OTHER INDUSTRIAL PROCESSES 7,212 84 6,674 32,194 10,912 3,634 27,548 

KY 2009 08 SOLVENT UTILIZATION 0 10 11 371 283 1 62,595 

KY 2009 09 STORAGE & TRANSPORT 38 9 18 2,064 1,268 3 20,038 

KY 2009 10 WASTE DISPOSAL & RECYCLING 22,388 9 1,979 7,770 6,925 733 7,725 

KY 2009 11 HIGHWAY VEHICLES 942,350 5,795 97,912 3,002 1,941 585 63,258 

KY 2009 12 OFF-HIGHWAY 357,800 34 94,752 5,544 5,203 9,180 38,558 

KY 2009 14 MISCELLANEOUS 32,627 52,915 702 206,463 29,601 187 6,335 

2009 

Total 1,527,684 60,137 365,214 277,453 72,006 379,651 246,509 

KY 2018 01 FUEL COMB. ELEC. UTIL. 17,144 476 64,378 6,694 4,434 226,062 1,426 

KY 2018 02 FUEL COMB. INDUSTRIAL 15,692 205 64,533 2,203 1,528 43,772 1,555 

KY 2018 03 FUEL COMB. OTHER 24,764 53 5,550 6,469 6,169 9,947 7,479 

KY 2018 04 CHEMICAL & ALLIED PRODUCT 219 317 367 1,054 781 2,884 4,384 

KY 2018 05 METALS PROCESSING 114,470 9 1,508 3,898 3,065 15,800 2,343 

KY 2018 06 PETROLEUM & RELATED 5,495 434 3,244 392 262 7,426 3,394 

KY 2018 07 OTHER INDUSTRIAL PROCESSES 8,303 93 7,872 35,349 12,377 4,141 31,394 

KY 2018 08 SOLVENT UTILIZATION 0 12 14 464 352 1 73,525 

KY 2018 09 STORAGE & TRANSPORT 44 10 21 2,408 1,481 4 21,196 

KY 2018 10 WASTE DISPOSAL & RECYCLING 24,677 11 2,256 8,481 7,518 894 8,392 

KY 2018 11 HIGHWAY VEHICLES 782,423 6,584 42,104 2,283 1,160 651 39,084 

KY 2018 12 OFF-HIGHWAY 381,215 40 79,392 4,556 4,256 8,592 30,920 

KY 2018 14 MISCELLANEOUS 33,931 55,118 729 218,725 30,626 196 7,254 

2018 

Total 1,408,378 63,361 271,967 292,975 74,010 320,369 232,347 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

MS 2002 01 FUEL COMB. ELEC. UTIL. 5,219 198 40,433 1,706 1,147 60,086 629 

MS 2002 02 FUEL COMB. INDUSTRIAL 22,710 28 48,726 5,007 3,634 9,740 8,023 

MS 2002 03 FUEL COMB. OTHER 36,752 34 4,502 5,445 5,414 789 22,923 

MS 2002 04 CHEMICAL & ALLIED PRODUCT 15,410 361 1,725 849 440 1,663 2,375 

MS 2002 05 METALS PROCESSING 1,031 0 115 122 58 36 371 

MS 2002 06 PETROLEUM & RELATED 975 20 1,187 790 335 15,560 20,788 

MS 2002 07 OTHER INDUSTRIAL PROCESSES 13,884 747 9,219 27,617 8,051 8,866 15,525 

MS 2002 08 SOLVENT UTILIZATION 45 7 105 219 178 1 80,760 

MS 2002 09 STORAGE & TRANSPORT 74 0 80 124 38 40 23,327 

MS 2002 10 WASTE DISPOSAL & RECYCLING 1,414 9 89 447 324 31 886 

MS 2002 11 HIGHWAY VEHICLES 894,639 3,577 111,791 2,856 2,109 4,604 82,810 

MS 2002 12 OFF-HIGHWAY 236,752 23 88,787 5,010 4,690 11,315 41,081 

MS 2002 14 MISCELLANEOUS 14,529 58,746 312 323,622 43,028 84 708 

2002 

Total 1,243,435 63,753 307,072 373,815 69,446 112,814 300,206 

MS 2009 01 FUEL COMB. ELEC. UTIL. 5,051 334 36,011 4,957 4,777 76,579 404 

MS 2009 02 FUEL COMB. INDUSTRIAL 24,607 30 44,095 3,728 2,787 7,388 8,007 

MS 2009 03 FUEL COMB. OTHER 26,023 33 4,514 5,278 5,245 751 17,445 

MS 2009 04 CHEMICAL & ALLIED PRODUCT 16,141 405 1,955 941 488 1,880 2,614 

MS 2009 05 METALS PROCESSING 1,098 0 128 129 62 37 402 

MS 2009 06 PETROLEUM & RELATED 1,101 23 1,262 894 379 7,926 13,317 

MS 2009 07 OTHER INDUSTRIAL PROCESSES 14,181 197 8,376 31,381 8,629 8,254 16,282 

MS 2009 08 SOLVENT UTILIZATION 50 8 118 239 194 1 80,393 

MS 2009 09 STORAGE & TRANSPORT 92 0 100 172 59 49 23,494 

MS 2009 10 WASTE DISPOSAL & RECYCLING 1,486 10 95 473 339 32 743 

MS 2009 11 HIGHWAY VEHICLES 628,151 4,026 69,949 2,290 1,522 397 49,670 

MS 2009 12 OFF-HIGHWAY 257,453 25 80,567 4,270 3,985 7,191 36,197 

MS 2009 14 MISCELLANEOUS 48,314 63,886 1,037 337,018 46,695 283 2,295 

2009 

Total 1,023,747 68,978 248,207 391,770 75,160 110,767 251,261 

MS 2018 01 FUEL COMB. ELEC. UTIL. 15,282 827 10,271 7,187 7,033 15,146 1,114 

MS 2018 02 FUEL COMB. INDUSTRIAL 27,056 33 46,929 4,093 3,058 8,169 8,559 

MS 2018 03 FUEL COMB. OTHER 20,900 32 4,767 4,964 4,928 726 14,670 

MS 2018 04 CHEMICAL & ALLIED PRODUCT 20,175 475 2,337 1,132 588 2,242 3,290 

MS 2018 05 METALS PROCESSING 1,357 0 167 160 79 48 461 

MS 2018 06 PETROLEUM & RELATED 1,267 26 1,438 1,010 430 19,028 14,407 

MS 2018 07 OTHER INDUSTRIAL PROCESSES 16,267 216 9,996 38,494 10,494 9,657 20,301 

MS 2018 08 SOLVENT UTILIZATION 60 9 141 301 244 1 98,354 

MS 2018 09 STORAGE & TRANSPORT 115 0 124 210 73 62 24,537 

MS 2018 10 WASTE DISPOSAL & RECYCLING 1,638 12 114 533 372 34 870 

MS 2018 11 HIGHWAY VEHICLES 528,898 4,565 29,717 1,688 876 441 30,734 

MS 2018 12 OFF-HIGHWAY 270,726 29 68,252 3,452 3,203 6,638 28,842 

MS 2018 14 MISCELLANEOUS 50,160 70,096 1,076 352,321 47,869 294 2,377 

2018 

Total 953,900 76,320 175,329 415,546 79,246 62,486 248,517 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

NC 2002 01 FUEL COMB. ELEC. UTIL. 14,074 55 148,809 22,994 16,623 478,488 986 

NC 2002 02 FUEL COMB. INDUSTRIAL 23,578 301 48,590 5,596 4,334 33,395 2,540 

NC 2002 03 FUEL COMB. OTHER 217,008 2,318 16,460 31,777 26,746 3,971 87,985 

NC 2002 04 CHEMICAL & ALLIED PRODUCT 13,952 535 859 866 538 5,736 4,313 

NC 2002 05 METALS PROCESSING 5,876 60 201 564 467 1,010 2,512 

NC 2002 06 PETROLEUM & RELATED 461 0 174 104 52 283 140 

NC 2002 07 OTHER INDUSTRIAL PROCESSES 8,552 480 7,380 25,328 8,924 3,426 18,025 

NC 2002 08 SOLVENT UTILIZATION 130 307 229 524 484 26 151,383 

NC 2002 09 STORAGE & TRANSPORT 66 46 53 639 354 1 16,120 

NC 2002 10 WASTE DISPOSAL & RECYCLING 125,528 247 7,482 2,239 2,218 1,666 15,568 

NC 2002 11 HIGHWAY VEHICLES 3,176,811 10,455 341,198 6,905 4,816 13,343 253,374 

NC 2002 12 OFF-HIGHWAY 808,231 65 84,284 7,348 7,005 7,693 94,480 

NC 2002 14 MISCELLANEOUS 72,673 159,069 1,561 233,551 36,414 423 3,528 

2002 

Total 4,466,940 173,937 657,279 338,434 108,975 549,463 650,954 

NC 2009 01 FUEL COMB. ELEC. UTIL. 14,942 445 66,517 22,152 15,949 242,286 954 

NC 2009 02 FUEL COMB. INDUSTRIAL 24,871 312 38,160 5,159 3,871 30,788 2,509 

NC 2009 03 FUEL COMB. OTHER 158,837 2,723 18,441 25,334 19,467 4,060 49,819 

NC 2009 04 CHEMICAL & ALLIED PRODUCT 14,732 599 933 981 607 6,286 4,925 

NC 2009 05 METALS PROCESSING 6,358 67 207 627 528 1,130 2,790 

NC 2009 06 PETROLEUM & RELATED 556 0 212 127 64 349 162 

NC 2009 07 OTHER INDUSTRIAL PROCESSES 9,211 507 8,061 28,524 9,788 3,712 18,144 

NC 2009 08 SOLVENT UTILIZATION 142 335 246 549 506 28 136,114 

NC 2009 09 STORAGE & TRANSPORT 75 51 55 696 380 1 17,367 

NC 2009 10 WASTE DISPOSAL & RECYCLING 139,518 307 8,354 2,774 2,750 1,913 17,331 

NC 2009 11 HIGHWAY VEHICLES 2,184,901 12,637 207,648 5,861 3,643 1,311 163,803 

NC 2009 12 OFF-HIGHWAY 887,605 72 70,997 6,055 5,760 1,892 74,056 

NC 2009 14 MISCELLANEOUS 96,825 167,131 2,080 250,912 49,956 566 4,648 

2009 

Total 3,538,573 185,185 421,913 349,750 113,268 294,321 492,624 

NC 2018 01 FUEL COMB. ELEC. UTIL. 20,223 663 62,346 37,376 29,791 108,492 1,345 

NC 2018 02 FUEL COMB. INDUSTRIAL 26,872 341 40,897 5,594 4,222 32,507 2,702 

NC 2018 03 FUEL COMB. OTHER 131,365 2,857 20,027 21,847 16,231 4,050 34,104 

NC 2018 04 CHEMICAL & ALLIED PRODUCT 18,463 702 1,105 1,175 726 7,414 6,113 

NC 2018 05 METALS PROCESSING 7,576 76 255 771 657 1,335 3,516 

NC 2018 06 PETROLEUM & RELATED 712 0 272 162 82 448 207 

NC 2018 07 OTHER INDUSTRIAL PROCESSES 10,675 559 9,259 34,339 11,601 4,357 20,978 

NC 2018 08 SOLVENT UTILIZATION 169 375 277 588 540 31 152,979 

NC 2018 09 STORAGE & TRANSPORT 91 59 67 808 430 2 19,511 

NC 2018 10 WASTE DISPOSAL & RECYCLING 156,599 387 9,456 3,502 3,474 2,234 19,789 

NC 2018 11 HIGHWAY VEHICLES 1,510,848 13,077 81,706 4,299 2,158 1,323 88,620 

NC 2018 12 OFF-HIGHWAY 960,709 83 49,046 4,298 4,069 905 61,327 

NC 2018 14 MISCELLANEOUS 111,705 177,474 2,399 273,030 54,376 655 5,333 

2018 

Total 2,956,008 196,655 277,112 387,788 128,356 163,752 416,523 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

SC 2002 01 FUEL COMB. ELEC. UTIL. 6,969 141 88,528 21,827 17,521 210,272 470 

SC 2002 02 FUEL COMB. INDUSTRIAL 31,771 97 38,081 5,308 3,641 44,958 1,338 

SC 2002 03 FUEL COMB. OTHER 75,800 65 4,367 6,261 6,166 4,318 49,171 

SC 2002 04 CHEMICAL & ALLIED PRODUCT 2,526 173 25 501 318 59 8,784 

SC 2002 05 METALS PROCESSING 13,833 0 450 639 408 4,160 660 

SC 2002 06 PETROLEUM & RELATED 248 0 283 120 71 170 114 

SC 2002 07 OTHER INDUSTRIAL PROCESSES 9,502 1,237 15,145 15,224 6,981 12,128 16,342 

SC 2002 08 SOLVENT UTILIZATION 0 1 1 78 60 0 88,878 

SC 2002 09 STORAGE & TRANSPORT 10 0 4 1,025 626 0 21,009 

SC 2002 10 WASTE DISPOSAL & RECYCLING 67,908 10 4,063 9,172 8,641 625 15,291 

SC 2002 11 HIGHWAY VEHICLES 1,275,161 4,684 140,428 3,446 2,496 5,958 106,792 

SC 2002 12 OFF-HIGHWAY 413,964 33 50,249 4,152 3,945 4,866 55,016 

SC 2002 14 MISCELLANEOUS 221,436 28,903 4,335 262,974 47,136 1,187 12,535 

2002 

Total 2,119,129 35,343 345,960 330,728 98,009 288,701 376,401 

SC 2009 01 FUEL COMB. ELEC. UTIL. 11,135 343 46,915 19,395 16,042 124,608 660 

SC 2009 02 FUEL COMB. INDUSTRIAL 33,201 105 35,660 3,307 2,370 37,792 1,414 

SC 2009 03 FUEL COMB. OTHER 49,914 63 4,551 5,264 5,183 4,359 25,073 

SC 2009 04 CHEMICAL & ALLIED PRODUCT 2,798 173 26 543 345 60 7,409 

SC 2009 05 METALS PROCESSING 15,632 0 449 631 378 4,856 663 

SC 2009 06 PETROLEUM & RELATED 302 0 340 145 86 200 131 

SC 2009 07 OTHER INDUSTRIAL PROCESSES 10,241 1,403 15,069 18,267 8,045 13,443 15,697 

SC 2009 08 SOLVENT UTILIZATION 1 1 1 90 69 0 95,538 

SC 2009 09 STORAGE & TRANSPORT 13 0 5 569 352 0 21,989 

SC 2009 10 WASTE DISPOSAL & RECYCLING 70,379 11 4,215 9,526 8,977 666 15,998 

SC 2009 11 HIGHWAY VEHICLES 912,280 5,510 91,696 2,878 1,870 556 67,281 

SC 2009 12 OFF-HIGHWAY 448,625 36 43,235 3,471 3,294 1,701 43,061 

SC 2009 14 MISCELLANEOUS 250,690 31,416 4,962 282,480 51,151 1,359 13,906 

2009 

Total 1,805,210 39,061 247,124 346,565 98,163 189,601 308,820 

SC 2018 01 FUEL COMB. ELEC. UTIL. 14,786 617 51,456 28,826 25,032 93,274 906 

SC 2018 02 FUEL COMB. INDUSTRIAL 36,105 113 37,333 4,037 2,855 39,714 1,525 

SC 2018 03 FUEL COMB. OTHER 39,627 65 5,135 4,791 4,711 4,469 16,391 

SC 2018 04 CHEMICAL & ALLIED PRODUCT 3,296 212 32 664 423 74 9,107 

SC 2018 05 METALS PROCESSING 18,853 0 587 773 476 5,920 868 

SC 2018 06 PETROLEUM & RELATED 389 0 438 186 110 258 166 

SC 2018 07 OTHER INDUSTRIAL PROCESSES 12,136 1,566 17,507 20,215 9,044 15,863 18,636 

SC 2018 08 SOLVENT UTILIZATION 1 1 1 116 89 0 120,433 

SC 2018 09 STORAGE & TRANSPORT 16 0 6 1,380 842 0 22,742 

SC 2018 10 WASTE DISPOSAL & RECYCLING 73,403 13 4,512 10,038 9,443 735 17,167 

SC 2018 11 HIGHWAY VEHICLES 800,619 6,472 42,354 2,258 1,154 643 44,700 

SC 2018 12 OFF-HIGHWAY 481,332 41 31,758 2,617 2,474 1,198 36,131 

SC 2018 14 MISCELLANEOUS 250,637 34,345 4,961 306,342 53,367 1,359 13,896 

 2018 

Total 1,731,198 43,446 196,081 382,244 110,019 163,509 302,665 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

TN 2002 01 FUEL COMB. ELEC. UTIL. 6,787 197 152,137 13,866 11,491 320,146 890 

TN 2002 02 FUEL COMB. INDUSTRIAL 15,257 6 44,510 8,015 6,649 74,146 2,021 

TN 2002 03 FUEL COMB. OTHER 77,857 25 15,568 7,967 7,549 16,253 18,346 

TN 2002 04 CHEMICAL & ALLIED PRODUCT 36,920 1,518 1,772 3,246 2,201 6,516 24,047 

TN 2002 05 METALS PROCESSING 41,371 14 1,182 7,620 7,030 5,818 6,898 

TN 2002 06 PETROLEUM & RELATED 543 0 331 314 243 383 1,850 

TN 2002 07 OTHER INDUSTRIAL PROCESSES 9,420 44 11,794 30,484 12,867 5,845 27,336 

TN 2002 08 SOLVENT UTILIZATION 275 1 5,066 2,103 1,818 58 110,872 

TN 2002 09 STORAGE & TRANSPORT 22 24 105 1,249 736 134 21,962 

TN 2002 10 WASTE DISPOSAL & RECYCLING 22,143 31 1,839 7,068 6,469 349 15,505 

TN 2002 11 HIGHWAY VEHICLES 1,967,658 6,616 233,324 5,338 3,919 9,184 169,914 

TN 2002 12 OFF-HIGHWAY 505,163 43 96,827 6,819 6,458 10,441 66,450 

TN 2002 14 MISCELLANEOUS 10,824 34,318 225 180,006 25,193 60 2,252 

2002 

Total 2,694,242 42,836 564,680 274,095 92,622 449,332 468,342 

TN 2009 01 FUEL COMB. ELEC. UTIL. 7,214 227 66,405 15,608 13,092 255,410 932 

TN 2009 02 FUEL COMB. INDUSTRIAL 15,943 7 37,369 7,195 6,004 63,511 1,915 

TN 2009 03 FUEL COMB. OTHER 61,443 27 14,793 7,134 6,786 16,955 12,781 

TN 2009 04 CHEMICAL & ALLIED PRODUCT 35,440 1,719 1,958 3,519 2,400 7,056 15,594 

TN 2009 05 METALS PROCESSING 45,183 15 1,245 7,337 6,823 6,537 7,676 

TN 2009 06 PETROLEUM & RELATED 615 0 373 356 276 435 1,433 

TN 2009 07 OTHER INDUSTRIAL PROCESSES 9,911 62 12,635 32,661 13,737 6,240 28,598 

TN 2009 08 SOLVENT UTILIZATION 309 1 5,984 2,431 2,095 65 112,312 

TN 2009 09 STORAGE & TRANSPORT 26 31 12 1,218 733 42 23,687 

TN 2009 10 WASTE DISPOSAL & RECYCLING 23,810 35 1,993 7,618 6,968 393 14,922 

TN 2009 11 HIGHWAY VEHICLES 1,361,408 7,738 147,757 4,238 2,782 831 108,200 

TN 2009 12 OFF-HIGHWAY 554,121 48 86,641 5,877 5,557 5,651 55,358 

TN 2009 14 MISCELLANEOUS 17,921 35,200 379 192,464 26,830 102 2,814 

2009 

Total 2,133,342 45,108 377,545 287,655 94,083 363,228 386,222 

TN 2018 01 FUEL COMB. ELEC. UTIL. 7,723 241 31,715 15,941 13,387 112,672 976 

TN 2018 02 FUEL COMB. INDUSTRIAL 17,038 7 38,908 7,693 6,447 65,823 2,054 

TN 2018 03 FUEL COMB. OTHER 54,486 30 15,503 6,757 6,412 18,091 10,269 

TN 2018 04 CHEMICAL & ALLIED PRODUCT 45,455 2,053 2,424 4,443 3,044 9,088 20,071 

TN 2018 05 METALS PROCESSING 52,834 17 1,589 9,579 8,953 7,790 9,956 

TN 2018 06 PETROLEUM & RELATED 715 0 430 416 324 508 1,636 

TN 2018 07 OTHER INDUSTRIAL PROCESSES 10,946 88 14,157 38,250 16,286 7,286 35,587 

TN 2018 08 SOLVENT UTILIZATION 380 1 7,675 3,155 2,718 79 140,793 

TN 2018 09 STORAGE & TRANSPORT 33 41 14 1,572 939 49 25,493 

TN 2018 10 WASTE DISPOSAL & RECYCLING 26,712 42 2,326 8,562 7,828 468 17,530 

TN 2018 11 HIGHWAY VEHICLES 1,150,516 8,962 65,242 3,199 1,643 944 64,665 

TN 2018 12 OFF-HIGHWAY 593,100 55 70,226 4,672 4,403 5,207 45,084 

TN 2018 14 MISCELLANEOUS 19,210 36,213 408 209,058 28,209 111 3,293 

2018 

Total 1,979,148 47,749 250,619 313,294 100,592 228,116 377,408 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

VA 2002 01 FUEL COMB. ELEC. UTIL. 6,797 130 85,081 3,892 2,650 233,691 747 

VA 2002 02 FUEL COMB. INDUSTRIAL 64,386 100 75,807 18,480 8,453 137,448 5,332 

VA 2002 03 FUEL COMB. OTHER 98,788 13 15,648 11,572 11,236 5,508 54,496 

VA 2002 04 CHEMICAL & ALLIED PRODUCT 321 2,158 8,062 449 393 2,126 1,530 

VA 2002 05 METALS PROCESSING 3,580 0 937 1,575 1,349 5,251 513 

VA 2002 06 PETROLEUM & RELATED 23,384 0 182 255 153 170 501 

VA 2002 07 OTHER INDUSTRIAL PROCESSES 12,002 726 9,279 33,409 9,795 17,702 13,086 

VA 2002 08 SOLVENT UTILIZATION 0 4 0 225 210 2 111,511 

VA 2002 09 STORAGE & TRANSPORT 16 7 11 745 505 0 26,121 

VA 2002 10 WASTE DISPOSAL & RECYCLING 16,566 109 1,866 3,152 1,277 1,581 4,065 

VA 2002 11 HIGHWAY VEHICLES 2,170,508 7,837 219,602 4,537 3,090 7,218 144,684 

VA 2002 12 OFF-HIGHWAY 660,105 48 63,219 8,728 8,288 8,663 74,866 

VA 2002 14 MISCELLANEOUS 13,225 43,948 285 182,193 21,835 74 706 

2002 

Total 3,069,678 55,080 479,980 269,212 69,233 419,436 438,158 

VA 2009 01 FUEL COMB. ELEC. UTIL. 12,509 694 66,219 5,508 4,067 225,653 778 

VA 2009 02 FUEL COMB. INDUSTRIAL 67,422 105 67,263 18,346 8,345 135,612 5,483 

VA 2009 03 FUEL COMB. OTHER 66,037 14 15,966 10,062 9,742 5,258 28,063 

VA 2009 04 CHEMICAL & ALLIED PRODUCT 286 2,082 7,790 477 413 1,996 1,419 

VA 2009 05 METALS PROCESSING 3,397 0 827 1,563 1,332 4,813 390 

VA 2009 06 PETROLEUM & RELATED 26,288 0 197 275 169 187 557 

VA 2009 07 OTHER INDUSTRIAL PROCESSES 12,471 733 9,425 33,961 9,984 18,871 13,394 

VA 2009 08 SOLVENT UTILIZATION 0 5 0 248 231 3 110,127 

VA 2009 09 STORAGE & TRANSPORT 17 7 12 797 544 0 26,456 

VA 2009 10 WASTE DISPOSAL & RECYCLING 20,109 119 2,174 3,823 1,515 1,805 4,789 

VA 2009 11 HIGHWAY VEHICLES 1,495,771 9,066 133,170 3,760 2,254 900 89,678 

VA 2009 12 OFF-HIGHWAY 726,815 53 54,993 7,510 7,136 1,707 57,009 

VA 2009 14 MISCELLANEOUS 21,582 46,719 464 198,040 23,990 124 1,077 

2009 

Total 2,452,703 59,596 358,500 284,369 69,721 396,929 339,219 

VA 2018 01 FUEL COMB. ELEC. UTIL. 15,420 622 75,594 13,775 11,976 140,233 997 

VA 2018 02 FUEL COMB. INDUSTRIAL 72,218 114 70,343 19,248 8,892 140,995 5,861 

VA 2018 03 FUEL COMB. OTHER 53,171 14 17,852 9,427 9,086 5,369 18,603 

VA 2018 04 CHEMICAL & ALLIED PRODUCT 338 2,462 9,211 579 502 2,291 1,708 

VA 2018 05 METALS PROCESSING 4,034 0 1,017 1,861 1,592 5,948 469 

VA 2018 06 PETROLEUM & RELATED 30,284 0 228 315 194 217 642 

VA 2018 07 OTHER INDUSTRIAL PROCESSES 14,029 877 10,836 37,553 11,276 21,294 15,636 

VA 2018 08 SOLVENT UTILIZATION 0 6 0 314 293 3 127,953 

VA 2018 09 STORAGE & TRANSPORT 21 8 15 949 648 0 27,357 

VA 2018 10 WASTE DISPOSAL & RECYCLING 24,293 141 2,595 4,694 1,828 2,171 5,821 

VA 2018 11 HIGHWAY VEHICLES 1,310,698 10,757 61,881 3,343 1,641 1,059 60,454 

VA 2018 12 OFF-HIGHWAY 797,683 61 40,393 6,208 5,891 507 49,052 

VA 2018 14 MISCELLANEOUS 27,223 50,279 584 218,141 26,225 158 1,322 

2018 

Total 2,349,413 65,342 290,549 316,406 80,044 320,246 315,875 

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State Tier 1 Emission Totals 

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

WV 2002 01 FUEL COMB. ELEC. UTIL. 10,117 121 222,437 4,472 2,163 500,381 1,140 

WV 2002 02 FUEL COMB. INDUSTRIAL 8,685 97 33,831 1,583 1,332 37,118 1,097 

WV 2002 03 FUEL COMB. OTHER 29,480 13 15,220 3,814 3,683 3,990 9,275 

WV 2002 04 CHEMICAL & ALLIED PRODUCT 

MFG 50,835 80 1,627 950 831 9,052 5,755 

WV 2002 05 METALS PROCESSING 28,837 143 1,570 8,749 7,515 5,619 1,393 

WV 2002 06 PETROLEUM & RELATED 

INDUSTRIES 1 0 1,086 475 475 7,550 2,163 

WV 2002 07 OTHER INDUSTRIAL PROCESSES 2,003 56 5,347 18,751 5,567 2,316 1,803 

WV 2002 08 SOLVENT UTILIZATION 15 0 18 49 44 0 35,989 

WV 2002 09 STORAGE & TRANSPORT 15 0 3 1,952 947 0 12,432 

WV 2002 10 WASTE DISPOSAL & RECYCLING 9,395 8 599 4,153 3,731 100 5,098 

WV 2002 11 HIGHWAY VEHICLES 560,717 1,933 59,612 1,395 1,003 2,489 40,066 

WV 2002 12 OFF-HIGHWAY 133,113 9 33,239 1,850 1,728 2,112 18,566 

WV 2002 14 MISCELLANEOUS 2,811 9,909 61 92,633 10,458 16 157 

2002 

Total 836,024 12,371 374,650 140,825 39,478 570,742 134,936 

WV 2009 01 FUEL COMB. ELEC. UTIL. 11,493 330 86,328 5,657 2,940 277,489 1,361 

WV 2009 02 FUEL COMB. INDUSTRIAL 9,296 104 27,094 1,415 1,220 36,912 998 

WV 2009 03 FUEL COMB. OTHER 21,558 13 14,229 3,351 3,216 4,047 6,824 

WV 2009 04 CHEMICAL & ALLIED PRODUCT 

MFG 58,271 82 1,804 987 864 10,166 5,426 

WV 2009 05 METALS PROCESSING 30,939 142 1,517 7,985 6,724 5,971 1,380 

WV 2009 06 PETROLEUM & RELATED 

INDUSTRIES 1 0 1,221 535 535 8,495 2,172 

WV 2009 07 OTHER INDUSTRIAL PROCESSES 2,288 59 4,995 19,228 5,899 2,570 2,064 

WV 2009 08 SOLVENT UTILIZATION 17 0 20 52 47 0 32,305 

WV 2009 09 STORAGE & TRANSPORT 17 0 3 2,062 1,003 0 12,997 

WV 2009 10 WASTE DISPOSAL & RECYCLING 9,131 8 583 4,050 3,632 97 4,898 

WV 2009 11 HIGHWAY VEHICLES 385,994 2,183 36,049 1,096 703 227 23,907 

WV 2009 12 OFF-HIGHWAY 152,862 11 30,133 1,640 1,528 359 18,069 

WV 2009 14 MISCELLANEOUS 4,116 10,574 89 92,900 10,624 23 219 

2009 

Total 685,983 13,508 204,064 140,956 38,933 346,356 112,621 

WV 2018 01 FUEL COMB. ELEC. UTIL. 11,961 180 51,241 6,349 3,648 115,324 1,387 

WV 2018 02 FUEL COMB. INDUSTRIAL 9,917 111 28,710 1,493 1,290 38,531 1,072 

WV 2018 03 FUEL COMB. OTHER 18,891 16 17,254 3,160 3,024 4,065 6,270 

WV 2018 04 CHEMICAL & ALLIED PRODUCT 

MFG 70,252 99 2,183 1,188 1,041 12,280 6,560 

WV 2018 05 METALS PROCESSING 36,850 183 2,061 10,944 9,372 7,182 1,790 

WV 2018 06 PETROLEUM & RELATED 

INDUSTRIES 1 0 1,407 616 616 9,786 2,338 

WV 2018 07 OTHER INDUSTRIAL PROCESSES 2,756 68 5,949 21,347 6,794 3,101 2,561 

WV 2018 08 SOLVENT UTILIZATION 20 0 24 61 55 0 38,023 

WV 2018 09 STORAGE & TRANSPORT 19 0 4 2,522 1,225 0 13,394 

WV 2018 10 WASTE DISPOSAL & RECYCLING 9,237 10 592 4,134 3,692 98 5,272 

WV 2018 11 HIGHWAY VEHICLES 319,030 2,484 16,274 844 428 255 15,463 

WV 2018 12 OFF-HIGHWAY 167,424 13 25,710 1,292 1,198 56 14,086 

WV 2018 14 MISCELLANEOUS 5,175 11,453 112 98,307 11,316 29 268 

 2018 

Total 651,532 14,617 151,521 152,256 43,699 190,706 108,484 

 CO NH3 NOX PM10 PM2.5 SO2 VOC 

VISTAS 2002 Total 31,034,756 666,451 5,442,572 3,916,030 1,094,698 4,858,865 5,079,254 

VISTAS 2009 Total 25,854,812 722,418 3,721,469 4,155,033 1,119,806 3,454,666 4,118,474 

VISTAS 2018 Total 24,357,364 790,588 2,692,309 4,559,582 1,205,324 2,539,907 3,873,273 

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APPENDIX D: 

VISTAS TIER 1 EMISSION TOTALS 

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VISTAS Tier 1 Emission Totals 

Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC 

2002 01 FUEL COMB. ELEC. UTIL. 139,579 1,710 1,524,690 114,256 79,263 3,723,175 12,417 

2002 02 FUEL COMB. INDUSTRIAL 371,905 1,204 499,981 85,353 59,731 550,864 32,330 

2002 03 FUEL COMB. OTHER 759,534 2,810 122,058 99,532 91,805 114,852 354,375 

2002 04 CHEMICAL & ALLIED PRODUCT MFG 131,993 7,093 20,896 11,114 7,982 77,450 63,748 

2002 05 METALS PROCESSING 223,705 601 11,801 32,367 27,778 49,143 17,306 

2002 06 PETROLEUM & RELATED INDUSTRIES 44,633 355 7,204 2,887 1,863 53,392 33,374 

2002 07 OTHER INDUSTRIAL PROCESSES 156,077 7,520 114,474 267,980 97,013 86,736 196,831 

2002 08 SOLVENT UTILIZATION 687 331 5,677 3,805 3,284 90 1,288,990 

2002 09 STORAGE & TRANSPORT 610 85 1,069 10,968 6,100 230 261,959 

2002 10 WASTE DISPOSAL & RECYCLING 729,760 801 34,165 98,788 92,125 6,418 112,088 

2002 11 HIGHWAY VEHICLES 20,199,593 74,325 2,193,387 50,584 35,929 88,684 1,778,345 

2002 12 OFF-HIGHWAY 6,209,596 477 865,130 72,019 68,302 96,336 813,788 

2002 14 MISCELLANEOUS 2,067,084 569,139 42,039 3,066,378 523,524 11,494 113,703 

2002 Total 31,034,756 666,451 5,442,572 3,916,030 1,094,698 4,858,865 5,079,254 

2009 01 FUEL COMB. ELEC. UTIL. 152,790 5,449 727,384 113,607 81,884 2,473,773 13,155 

2009 02 FUEL COMB. INDUSTRIAL 391,510 1,305 445,832 74,864 51,709 523,163 32,629 

2009 03 FUEL COMB. OTHER 544,310 3,201 123,331 85,412 77,042 112,463 207,146 

2009 04 CHEMICAL & ALLIED PRODUCT MFG 140,910 7,611 22,031 11,898 8,528 81,191 54,270 

2009 05 METALS PROCESSING 242,911 732 11,788 31,098 26,505 54,700 18,507 

2009 06 PETROLEUM & RELATED INDUSTRIES 48,161 399 7,908 3,283 2,124 47,147 25,061 

2009 07 OTHER INDUSTRIAL PROCESSES 166,088 7,545 117,625 298,836 111,304 90,649 203,100 

2009 08 SOLVENT UTILIZATION 771 360 6,662 4,290 3,690 100 1,257,986 

2009 09 STORAGE & TRANSPORT 702 98 1,087 11,035 6,051 160 275,466 

2009 10 WASTE DISPOSAL & RECYCLING 770,459 869 36,697 105,463 97,855 7,287 113,566 

2009 11 HIGHWAY VEHICLES 14,353,436 87,703 1,408,206 42,370 26,848 8,817 1,146,174 

2009 12 OFF-HIGHWAY 6,827,857 530 767,707 61,528 58,279 42,845 649,786 

2009 14 MISCELLANEOUS 2,214,906 606,617 45,212 3,311,350 567,986 12,370 121,629 

2009 Total 25,854,812 722,418 3,721,469 4,155,033 1,119,806 3,454,666 4,118,474 

2018 01 FUEL COMB. ELEC. UTIL. 225,129 9,351 560,200 154,832 120,895 1,479,499 16,318 

2018 02 FUEL COMB. INDUSTRIAL 418,010 1,384 471,501 80,386 55,928 547,527 34,938 

2018 03 FUEL COMB. OTHER 453,482 3,358 136,418 78,031 69,853 116,812 149,363 

2018 04 CHEMICAL & ALLIED PRODUCT MFG 173,857 9,023 26,564 14,641 10,522 97,612 67,534 

2018 05 METALS PROCESSING 288,138 961 15,006 39,673 34,058 67,170 23,798 

2018 06 PETROLEUM & RELATED INDUSTRIES 53,442 460 9,088 3,846 2,491 60,676 27,321 

2018 07 OTHER INDUSTRIAL PROCESSES 189,922 8,793 136,722 348,275 130,883 104,030 238,409 

2018 08 SOLVENT UTILIZATION 936 404 8,480 5,378 4,618 119 1,516,454 

2018 09 STORAGE & TRANSPORT 855 119 1,258 13,988 7,686 192 290,271 

2018 10 WASTE DISPOSAL & RECYCLING 821,737 1,068 40,324 114,708 105,763 8,545 125,525 

2018 11 HIGHWAY VEHICLES 12,052,347 101,223 639,931 33,884 17,080 10,027 713,143 

2018 12 OFF-HIGHWAY 7,438,312 612 601,040 48,648 45,927 35,166 546,062 

2018 14 MISCELLANEOUS 2,241,196 653,831 45,776 3,623,293 599,620 12,532 124,137 

2018 Total 24,357,364 790,588 2,692,309 4,559,582 1,205,324 2,539,907 3,873,273 

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APPENDIX E: 

AIRCRAFT PM EXCERPT FROM 2001 TUCSON REPORT 

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247
Final Report 

EMISSIONS INVENTORIES FOR 

THE TUCSON AIR PLANNING AREA 

VOLUME I. STUDY DESCRIPTION AND RESULTS 

Prepared for 

Pima Association of Governments 

177 N. Church Avenue, Suite 405 

Tucson, AZ 85701 

Prepared by 

Marianne Causley 

Rumla, Inc. 

3243 Gloria Terrace 

Lafayette, CA 94549 

Daniel Meszler 

Energy and Environmental Analysis, Inc. 

1655 North Fort Myer Drive 

Arlington, VA 22209 

Russell Jones 

Stratus Consulting, Inc. 

P.O. Box 4059 

Boulder, CO 80306-4059 

Steven Reynolds 

Envair 

12 Palm Avenue 

San Rafael, CA 94901 

November 2001

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ACKNOWLEDGEMENTS

The authors extend their appreciation to the many individuals that contributed to this study. 

Particular thanks go to the staff of the Pima Association of Governments. Darcy Anderson was 

instrumental in providing definition at the outset of the study. Lee Comrie and Natalie Barnes 

provided considerable assistance with the emissions surveys, made many thoughtful suggestions 

and contributions throughout the study, and provided helpful comments on the draft final report. 

Kwame Agyare, Wayne Byrd and Bill Maxwell of the Pima County Department of 

Environmental Quality offered valuable assistance in providing socioeconomic and PDEQ permit 

data and in sharing their knowledge of emissions sources in the Tucson Air Planning Area. Dan 

Catlin of the Arizona Department of Environmental Quality provided insightful comments 

during the course of the study and reviewed the draft final report. 

Many individuals in the Tucson area participated in the annual and day-specific emissions 

surveys conducted as part of this study. The information they provided is sincerely appreciated. 

We also wish to acknowledge Patricia El-Gasseir and Helen Fugate of Rumla, Inc. for their 

dedicated efforts in building the facilities database. 

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TABLE OF CONTENTS

ACKNOWLEDGEMENTS ...................................................................................... i 

LIST OF TABLES .................................................................................................... viii 

LIST OF FIGURES................................................................................................... xiii 

ABBREVIATIONS AND ACRONYMS.................................................................. xiv 

EXECUTIVE SUMMARY....................................................................................... ES-1 

1 BACKGROUND................................................................................................... 1-1 

 1.1 Current Air Quality Status of the Tucson Area....................................... 1-1 

 1.1.1 Ozone ................................................................................................ 1-1 

 1.1.2 Carbon Monoxide.............................................................................. 1-3 

 1.1.3 Particulate Matter .............................................................................. 1-3 

 1.2 Overview of the Emissions Inventories................................................... 1-4 

 1.3 Emissions Support for Photochemical Modeling in Tucson................... 1-6 

 1.4 Organization of This Report.................................................................... 1-7 

2 POINT SOURCES ................................................................................................ 2-1 

 2.1 Identification of Sources ......................................................................... 2-1 

 2.2 Data Collection........................................................................................ 2-2 

 2.3 Data Entry ............................................................................................... 2-4 

 2.4 Calculation Methodologies ..................................................................... 2-5 

 2.4.1 Emissions Based on 2000 Actual Data ............................................. 2-6 

 2.4.2 Emissions Based on Adjustment of 1999 Data ................................. 2-7 

 2.4.3 Emissions Based on General Activity Data....................................... 2-7 

 2.4.4 Emissions Based on Evaporative Processes...................................... 2-8 

 2.5 Data Quality and Completeness .............................................................. 2-9 

 2.6 Future Year Estimations.......................................................................... 2-11 

 2.7 Point Source Emissions Summary .......................................................... 2-12 

 2.8 Temporal Activity Data........................................................................... 2-13 

 2.8.1 Point Source TAF Comparison ......................................................... 2-15 

 2.8.2 Point and Area TAF Comparison...................................................... 2-16 

3 STATIONARY AREA SOURCES ...................................................................... 3-1 

3.1 Architectural Coating .................................................................. 3-4 

3.1.1 Methodology....................................................................................... 3-4 

3.1.2 Calculations ........................................................................................ 3-5 

3.2 Asphalt Paving.......................................................................................... 3-6 

3.2.1 Methodology....................................................................................... 3-6 

3.2.2 Calculations ........................................................................................ 3-7 

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TABLE OF CONTENTS (Continued) 

3.3 Automobile Refinishing ........................................................................... 3-7 

3.3.1 Methodology....................................................................................... 3-7 

3.3.2 Calculations ........................................................................................ 3-8 

3.4 Commercial Bakeries ............................................................................... 3-9 

3.4.1 Methodology....................................................................................... 3-9 

3.4.2 Calculations ........................................................................................ 3-9 

3.5 Consumer Solvent Usage ......................................................................... 3-10 

3.5.1 Methodology....................................................................................... 3-10 

3.5.2 Calculations ........................................................................................ 3-10 

3.6 Dry Cleaning............................................................................................. 3-11 

3.6.1 Methodology....................................................................................... 3-11 

3.6.2 Calculations ........................................................................................ 3-12 

3.7 Forest Fires and Prescribed Burnings....................................................... 3-13 

3.7.1 Methodology....................................................................................... 3-13 

3.7.2 Calculations ........................................................................................ 3-13 

3.8 Gasoline Distribution ............................................................................... 3-15 

3.8.1 Methodology....................................................................................... 3-15 

3.8.2 Calculations ........................................................................................ 3-17 

3.9 Graphic Arts ............................................................................................. 3-18 

3.9.1 Methodology....................................................................................... 3-18 

3.9.2 Calculations ........................................................................................ 3-18 

3.10 Industrial Surface Coating........................................................................ 3-18 

3.10.1 Methodology....................................................................................... 3-19 

3.10.2 Calculations ........................................................................................ 3-19 

3.11 Misc. Residential/Commercial Fuel Combustion .................................... 3-20 

3.11.1 Methodology....................................................................................... 3-20 

3.11.2 Calculations ........................................................................................ 3-21 

3.12 Pesticide Application................................................................................ 3-23 

3.12.1 Methodology....................................................................................... 3-24 

3.12.2 Calculations ........................................................................................ 3-25 

3.13 Residential Wood Combustion................................................................. 3-25 

3.13.1 Methodology....................................................................................... 3-26 

3.13.2 Calculations ........................................................................................ 3-26 

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TABLE OF CONTENTS (Continued) 

3.14 Solvent Cleaning ...................................................................................... 3-28 

3.14.1 Methodology....................................................................................... 3-28 

3.14.2 Calculations ........................................................................................ 3-29 

3.15 Structure and Vehicle Fires ..................................................................... 3-29 

3.15.1 Methodology....................................................................................... 3-30 

3.15.2 Calculations ........................................................................................ 3-30 

3.16 Traffic Markings....................................................................................... 3-32 

3.16.1 Methodology....................................................................................... 3-32 

3.16.2 Calculations ........................................................................................ 3-33 

3.17 Area Source Annual Emissions Summaries............................................. 3-33 

3.18 Day-specific Area Source Emissions Summaries..................................... 3-41 

4 NONROAD MOBILE SOURCES........................................................................ 4-1 

 4.1 Introduction ............................................................................................. 4-1 

4.2 General Use Nonroad Equipment............................................................ 4-4 

 4.2.1 Basic Inventory Methodology ........................................................... 4-6 

 4.2.2 NONROAD Model Inputs................................................................. 4-11 

 4.2.3 Emission Estimates for Calendar Year 2000..................................... 4-14 

 4.2.4 Emissions Estimates for Tuesday August 22, 2000 .......................... 4-17 

 4.2.5 Emissions Estimates for Sunday September 10, 2000 ...................... 4-21 

 4.2.6 Emissions Estimates for Saturday April 14, 2001............................. 4-21 

 4.2.7 Emissions Estimates for Tuesday April 24, 2001 ............................. 4-22 

 4.2.8 Emissions Estimates for Calendar Year 2005 ................................... 4-24 

 4.2.9 Emissions Estimates for Calendar Year 2010 ................................... 4-25 

 4.2.10 Temporal Allocation Factors for General Use Nonroad Equipment. 4-27 

 4.3 Aircraft Operations........................................................................................ 4-28 

 4.3.1 Commercial Air Carrier Emission Estimates for Calendar Year 2000 4-30 

4.3.2 Commercial Air Carrier APU Emission Estimates for 

 Calendar Year 2000.................................................................. 4-44 

 4.3.3 Other Aircraft Emissions for Calendar Year 2000............................ 4-45 

 4.3.4 Other Potential Aircraft Emissions Sources Not Currently Considered 4-64 

 4.3.5 Aircraft Emissions Estimates for Tuesday August 22, 2000............. 4-68 

 4.3.6 Aircraft Emissions Estimates for Sunday September 10, 2000......... 4-69 

 4.3.7 Aircraft Emissions Estimates for Saturday April 14, 2001 ............... 4-70 

 4.3.8 Aircraft Emissions Estimates for Tuesday April 24, 2001................ 4-70 

 4.3.9 Aircraft Emissions Estimates for Calendar Year 2005 ..................... 4-77 

 4.3.10 Aircraft Emissions Estimates for Calendar Year 2010 ..................... 4-83 

 4.3.11 Day-Specific and Forecast Aircraft Emission Estimates for TIA ..... 4-88 

 4.3.12 Temporal Allocation Factors for Aircraft Emissions........................ 4-88 

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TABLE OF CONTENTS (Continued)

4.4 Aircraft Ground Support Equipment 4-88 

 4.4.1 GSE Emissions Estimates for Calendar Year 2000 .......................... 4-94 

 4.4.2 GSE Emissions Estimates for Tuesday August 22, 2000.................. 4-102 

 4.4.3 GSE Emissions Estimates for Sunday September 10, 2000.............. 4-104 

 4.4.4 GSE Emissions Estimates for Saturday April 14, 2001 .................... 4-104 

 4.4.5 GSE Emissions Estimates for Tuesday April 24, 2001..................... 4-108 

 4.4.6 GSE Emissions Estimates for Calendar Year 2005 .......................... 4-108 

 4.4.7 GSE Emissions Estimates for Calendar Year 2010 .......................... 4-108 

 4.4.8 Temporal Allocation Factors for GSE Emissions ............................. 4-108 

4.5 Commercial Marine Operations .................................................................... 4-113 

4.6 Locomotive Operations ................................................................................. 4-113 

 4.6.1 Locomotive Emission Estimates for Calendar Year 2000 ................ 4-114 

4.6.2 Day-Specific Locomotive Emission Estimates for 

 Calendar Year 2000................................................................. 4-124 

4.6.3 Day-Specific Locomotive Emission Estimates for 

 Calendar Year 2001.................................................................. 4-125 

4.6.4 Locomotive Emission Estimates for 

 Calendar Years 2005 and 2010 ................................................ 4-125 

 4.6.5 Temporal Allocation Factors for Locomotive Emissions ................. 4-125 

5 MODEL INVENTORY PREPARATION ........................................................... 5-1 

 5.1 Overview ....................................................................................................... 5-1 

 5.1.1 Spatial Resolution of Emissions........................................................ 5-2 

 5.1.2 Temporal Resolution of Emissions ................................................... 5-2 

 5.1.3 Chemical Resolution of Emissions ................................................... 5-3 

 5.2 Inventory Preparation .................................................................................... 5-3 

 5.2.1 Emission Data ................................................................................... 5-6 

 5.2.2 Spatial Allocation.............................................................................. 5-6 

 5.2.3 Temporal Allocation ......................................................................... 5-11 

 5.2.4 Chemical Speciation.......................................................................... 5-11 

 5.3 Emission Processing System......................................................................... 5-12 

 5.3.1 Output Formats.................................................................................. 5-12 

 5.4 Summary of Modeling Inventories................................................................ 5-14 

6 DATA QUALITY REVIEW................................................................................ 6-1 

 6.1 Point Sources................................................................................................. 6-1 

 6.2 Area Sources ................................................................................................. 6-3 

 6.3 Nonroad Mobile Sources............................................................................... 6-4 

 6.4 Photochemical Air Quality Model Input Files .............................................. 6-5 

 6.5 External Review ............................................................................................ 6-6 

 6.6 Overall Comments on the Inventories........................................................... 6-9 

7 REFERENCES..................................................................................................... 7-1 

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TABLE OF CONTENTS (Concluded) 

 APPENDIX 2A. LIST OF PAG MAJOR AND MINOR FACILITIES 

 CONTACTED DURING SURVEY ACTIVITIES .......................... 2A-1 

 APPENDIX 2B. REVISED ANNUAL SURVEY FORM FOR 

 MAJOR FACILITIES ....................................................................... 2B-1 

 APPENDIX 2C. REVISED ANNUAL SURVEY FORMS FOR 

 MINOR FACILITIES........................................................................ 2C-1 

 APPENDIX 2D. PAG 2000 TOTAL EMISSIONS BY FACILITY ................... 2D-1 

 APPENDIX 3A. ASC SPATIAL ALLOCATION SURROGATE ASSIGNMENT 3A-1 

 APPENDIX 4A. NONROAD MOBILE SOURCE EMISSIONS BY SCC........ 4A-1 

 

 APPENDIX 4B. NONROAD MOBILE SOURCE TEMPORAL 

 ALLOCATION FACTORS .............................................................. 4B-1 

APPENDIX 5A. NATIONAL EMISSION INVENTORY (NEI) 

 RECORD FORMATS....................................................................... 5A-1 

APPENDIX 5B. SPATIAL ALLOCATION OF EMISSIONS USING GIS....... 5B-1 

APPENDIX 5C. EDBsys EMISSION OUTPUT FORMATS............................. 5C-1 

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LIST OF TABLES

Table 1-1. Inventories for the Tucson Air Planning Area ........................................... 1-2 

Table 2-1. PDEQ Permitted Facilities Flagged as a Major Point Source.................... 2-2 

Table 2-2. PAG Survey Response Rates ..................................................................... 2-4 

Table 2-3. NEI Record Elements for the PAG Inventory............................................ 2-5 

Table 2-4. 2000 Emission Estimates Adjustments from Surveys ............................... 2-7 

Table 2-5. Resolution of Survey Data Issues and Possible Inventory Effect .............. 2-9 

Table 2-6. Ranges of EGAS Growth Factors from 2000 Baseline.............................. 2-12 

Table 2-7. Annual Emissions Estimates for Major and Minor Point Sources ............ 2-12 

Table 2-8. Day-specific Criteria Pollutant Totals (tons per day) ................................ 2-13 

Table 2-9. Survey Responses for Temporal Activity Profile Information .................. 2-14 

Table 3-1. TAPA Inventory Area Source Categories ................................................. 3-1 

Table 3-2. Socioeconomic Parameters Applied to 2000 and Projected Year 

 Emission Estimations........................................................................... 3-3 

Table 3-3. Projection Factors for the 2005 and 2010 Emission Estimates.................. 3-3 

Table 3-4. Allocation Adjustment Factors .................................................................. 3-3 

Table 3-5. Architectural Coatings Gallons Per Capita Calculations........................... 3-5 

Table 3-6. TAPA Annual Architectural Coating VOC Emission Estimates............... 3-6 

Table 3-7. Growth Factors for the Automobile Refinishing Employment 

 in the Tucson Area ............................................................................... 3-8 

Table 3-8. TAPA Annual Automobile Refinishing VOC Emissions.......................... 3-8 

Table 3-9. Commercial Bakery Process Emission Factors ......................................... 3-10 

Table 3-10. TAPA Bakeries VOC Emission Estimates .............................................. 3-10 

Table 3-11. TAPA Consumer Product Per Capita Factors and 

 Emission Estimates (tons) ................................................................... 3-11 

Table 3-12. Dry Cleaning Telephone Survey Responses ............................................ 3-12 

Table 3-13. Pima County Acres Burned During 2000 ................................................ 3-13 

Table 3-14. Emission Factors for Estimation of Forest Fire and Prescribed Burnings 3-14 

Table 3-15. TAPA 2000 Emissions from Forest Fires and Prescribed Burnings (tons) 3-14 

Table 3-16. TAPA 2005 and 2010 Emissions from Forest Fires and Prescribed 

 Burnings (tons/year) ............................................................................. 3-15 

Table 3-17. Year 2000 Gasoline Tax Sales (gallons) ................................................. 3-16 

Table 3-18. TAPA VOC Emissions from Gasoline Marketing Activities (tons) ....... 3-17 

Table 3-19. TAPA VOC Emissions from Graphic Arts (tons) .................................. 3-18 

Table 3-20. ZIP Codes Included for Dun & Bradstreet Extraction ............................. 3-19 

Table 3-21. TAPA VOC Emission Estimates for Industrial Surface Coating (tons) . 3-20 

Table 3-22. Natural Gas and LPG Emission Factors ................................................. 3-21 

Table 3-23. 2000 Natural Gas and LPG Sales for the Tucson Area............................ 3-22 

Table 3-24. TAPA 2000 Emissions from Miscellaneous Combustion (tons/year) .... 3-22 

Table 3-25. TAPA 2005 Emissions from Miscellaneous Combustion (tons/year) .... 3-23 

Table 3-26. TAPA 2010 Emissions from Miscellaneous Combustion (tons/year)..... 3-23 

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LIST OF TABLES (Continued) 

Table 3-27. Identified Survey Contacts and Responses for the Source 

 Category Pesticide Application........................................................... 3-24 

Table 3-28. Growth Factors for the Dwelling Units in the Tucson Area.................... 3-26 

Table 3-29. Tons of Wood Burned by Type................................................................ 3-27 

Table 3-30. Residential Wood Burning Emission Factors (lbs/ton burned) .............. 3-27 

Table 3-31. Annual Emissions from Residential Wood Burning by Device (tons) .... 3-28 

Table 3-32. TAPA Annual VOC Emission Estimates from Solvent Cleaning (tons) 3-29 

Table 3-33. 2000 Fire Incident Counts for Structural and Vehicle Fires .................... 3-31 

Table 3-34. Emission Factors for Structural and Vehicular Fires............................... 3-31 

Table 3-35. Annual TAPA Emissions from Structure and Vehicle Fires (tons) ........ 3-32 

Table 3-36. TAPA Emissions from Traffic Markings ................................................ 3-33 

Table 3-37. TAPA Inventory Area Source Categories Estimation Methods .............. 3-35 

Table 3-38. TAPA 2000 Annual Area Source Emissions by Source Category (tons) 3-36 

Table 3-39. TAPA 2005 Annual Area Source Emissions by Source Category (tons) 3-38 

Table 3-40. TAPA 2010 Annual Area Source Emissions by Source Category (tons) 3-40 

Table 3-41. TAPA August 22, 2000 Area Source Emissions by Source Category..... 3-43 

Table 3-42. TAPA September 10, 2000 Area Source Emissions by Source Category 3-45 

Table 3-43. TAPA April 24, 2001 Area Source Emissions by Source Category........ 3-47 

Table 4-1. Nonroad Mobile Source Equipment Categories ........................................ 4-2 

Table 4-2. NONROAD Model Equipment Allocation Parameters............................. 4-10 

Table 4-3. Retail Fuel Test Data for 2000................................................................... 4-12 

Table 4-4. NONROAD Model Fuel Input Parameters................................................ 4-14 

Table 4-5. NONROAD Model Temperature Input Parameters................................... 4-14 

Table 4-6. TAPA General Use Nonroad Equipment Emission Inventory 

 for 2000 (tons per year) ........................................................................... 4-15 

Table 4-7. Allocation Factors used to Convert County to TAPA Emission Estimates 4-18 

Table 4-8. NONROAD Model Input Parameters for Day-Specific Inventories....... 4-18 

Table 4-9. TAPA General Use Nonroad Equipment Emission Inventory for 

 Tuesday August 22, 2000 (tons per day)........................................... 4-19 

Table 4-10. NONROAD Model Monthly Activity Allocation Factors.................... 4-20 

Table 4-11. NONROAD Model Day-of-Week Activity Allocation Factors............ 4-20 

Table 4-12. TAPA General Use Nonroad Equipment Emission Inventory for 

 Sunday September 10, 2000 (tons per day)....................................... 4-22 

Table 4-13. TAPA General Use Nonroad Equipment Emission Inventory for 

 Saturday April 14, 2001 (tons per day) ............................................. 4-23 

Table 4-14. TAPA General Use Nonroad Equipment Emission Inventory for 

 Tuesday April 24, 2001 (tons per day).............................................. 4-24 

Table 4-15. NONROAD Model Fuel Input Parameters for 2005 and 2010 ............ 4-26 

Table 4-16. TAPA General Use Nonroad Equipment Emission Inventory for 

 2005 (tons per year)........................................................................... 4-26 

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LIST OF TABLES (Continued) 

Table 4-17. TAPA General Use Nonroad Equipment Emission Inventory for 

 2010 (tons per year)........................................................................... 4-28 

Table 4-18. 1999 FAA Commercial Air Carrier Data for TIA .................................. 4-31 

Table 4-19. 1999 Aircraft Operations Data Reported by TIA.................................... 4-33 

Table 4-20. 2000 Aircraft Operations Data for TIA................................................... 4-35 

Table 4-21. TIA Taxi Time Data as Reported by U.S. DOT (minutes) ..................... 4-35 

Table 4-22. TIA Mixing Height Data......................................................................... 4-37 

Table 4-23. Statistics for Aircraft and APU PM Relations ........................................ 4-42 

Table 4-24. TIA Emission Inventory for 2000 (tons per year)................................... 4-44 

Table 4-25. APU Usage Rates at TIA ........................................................................ 4-46 

Table 4-26. Aircraft Activity Other Than Commercial Air Carriers in 2000............. 4-47 

Table 4-27. National Distribution of General Aviation and Air Taxi Aircraft .......... 4-50 

Table 4-28. Comparison of LTO-Specific Emission Rates for General Aviation 

 and Air Taxi Aircraft (pounds per LTO)............................................. 4-50 

Table 4-29. Local Distribution of General Aviation and Air Taxi Aircraft ............... 4-51 

Table 4-30. EPA Default TIM Data for General Aviation and Air Taxi Aircraft 

 (minutes per LTO)............................................................................... 4-52 

Table 4-31. Methodology Used to Develop Taxi/Idle Times for Local General 

 Aviation and Air Taxi Aircraft............................................................ 4-53 

Table 4-32. Local Taxi/Idle TIM Data for General Aviation and Air Taxi Aircraft 

 (minutes per LTO)............................................................................... 4-54 

Table 4-33. Local TIM Data for General Aviation and Air Taxi Aircraft 

 (minutes per LTO)............................................................................... 4-55 

Table 4-34. Based General Aviation and Air Taxi Aircraft in 2000.......................... 4-56 

Table 4-35. Local Taxi/Idle TIM Data for General Aviation and Air Taxi Aircraft 

 (minutes per LTO)............................................................................... 4-58 

Table 4-36. Military Aircraft Distributions for 2000 ................................................. 4-61 

Table 4-37. EPA Default TIM Data for Military Aircraft (minutes per LTO)........... 4-61 

Table 4-38. Local and TIM Data for Military Aircraft (minutes per LTO)................ 4-62 

Table 4-39. Aircraft Emissions for Operations other than Commercial Air 

 Carriers in 2000 (tons per year)........................................................... 4-65 

Table 4-40. Total Aircraft and APU Emissions in 2000 by Airport (tons per year) .. 4-66 

Table 4-41. Total Aircraft and APU Emissions in 2000 by Aircraft Type 

 (tons per year)...................................................................................... 4-66 

Table 4-42. Other Potential Aircraft Activity Locations............................................ 4-68 

Table 4-43. Day-of-Week Allocation Factors for Aircraft......................................... 4-70 

Table 4-44. Aircraft Emissions for Operations other than Commercial Air Carriers 

 On Tuesday August 22, 2000 (tons per day)....................................... 4-71 

Table 4-45. Total Aircraft and APU Emissions on Tuesday August 22, 2000 by 

 Airport (tons per day) .......................................................................... 4-72 

Table 4-46. Total Aircraft and APU Emissions on Tuesday August 22, 2000 by 

 Aircraft Type (tons per day) ................................................................ 4-72 

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LIST OF TABLES (Continued) 

Table 4-47. Aircraft Emissions for Operations other than Commercial Air Carriers 

 On Sunday September 10, 2000 (tons per day)................................... 4-73 

Table 4-48. Total Aircraft and APU Emissions on Sunday September 10, 2000 

 By Airport (tons per day)..................................................................... 4-74 

Table 4-49. Total Aircraft and APU Emissions on Sunday September 10, 2000 

 By Aircraft Type (tons per day)........................................................... 4-74 

Table 4-50. Aircraft Emissions for Operations other than Commercial Air Carriers 

 On Saturday April 14, 2001 (tons per day) ......................................... 4-75 

Table 4-51. Total Aircraft and APU Emissions on Saturday April 14, 2001 by 

 Airport (tons per day) .......................................................................... 4-76 

Table 4-52. Total Aircraft and APU Emissions on Saturday April 14, 2001 by 

 Aircraft Type (tons per day) ................................................................ 4-76 

Table 4-53. Aircraft Emissions for Operations other than Commercial Air Carriers 

 On Tuesday April 24, 2001 (tons per day) .......................................... 4-78 

Table 4-54. Total Aircraft and APU Emissions on Tuesday April 24, 2001 by 

 Airport (tons per day) .......................................................................... 4-79 

Table 4-55. Total Aircraft and APU Emissions on Tuesday April 24, 2001 by 

 Aircraft Type (tons per day) ................................................................ 4-79 

Table 4-56. Aircraft Operational Growth Ratios (Forecast Year/2000 Activity)....... 4-80 

Table 4-57. Aircraft Operations Summary................................................................. 4-81 

Table 4-58. Based Aircraft Summary......................................................................... 4-82 

Table 4-59. Aircraft Emissions for Operations other than Commercial Air Carriers 

 in 2005 (tons per year)......................................................................... 4-84 

Table 4-60. Total Aircraft and APU Emissions in 2005 by Airport (tons per year) .. 4-85 

Table 4-61. Total Aircraft and APU Emissions in 2005 by Aircraft Type 

 (tons per year)...................................................................................... 4-85 

Table 4-62. Aircraft Emissions for Operations other than Commercial Air Carriers 

 in 2010 (tons per year)......................................................................... 4-86 

Table 4-63. Total Aircraft and APU Emissions in 2010 by Airport (tons per year) .. 4-87 

Table 4-64. Total Aircraft and APU Emissions in 2010 by Aircraft Type 

 (tons per year)...................................................................................... 4-87 

Table 4-65. TIA Emission Inventory for Tuesday August 22, 2000 (tons per day) ... 4-89 

Table 4-66. TIA Emission Inventory for Sunday September 10, 2000 

 (tons per day)....................................................................................... 4-89 

Table 4-67. TIA Emission Inventory for Saturday April 14, 2001 (tons per day) ..... 4-90 

Table 4-68. TIA Emission Inventory for Tuesday April 24, 2001 (tons per day) ...... 4-90 

Table 4-69. TIA Emission Inventory for 2005 (tons per year)................................... 4-91 

Table 4-70. TIA Emission Inventory for 2010 (tons per year)................................... 4-91 

Table 4-71. Aircraft Ground Support Equipment Reported by TIA .......................... 4-95 

Table 4-72. Aircraft Ground Support Equipment Reported by DM .......................... 4-97 

Table 4-73. Summary of Reported and Additional GSE Types................................. 4-99 

Table 4-74. Summary (Average) GSE Statistics for TIA........................................... 4-100 

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LIST OF TABLES (Concluded) 

Table 4-75. Summary (Average) GSE Statistics for DM........................................... 4-101 

Table 4-76. GSE Model LTO, Fuel, Temperature, and Humidity Input Parameters . 4-102 

Table 4-77. GSE Emission Inventories for Calendar Year 2000 (tons per year) ....... 4-103 

Table 4-78. GSE Emission Inventories for Tuesday August 22, 2000 

 (tons per day)....................................................................................... 4-105 

Table 4-79. GSE Emission Inventories for Sunday September 10, 2000 

 (tons per day)....................................................................................... 4-106 

Table 4-80. GSE Emission Inventories for Saturday April 14, 2001 (tons per day).. 4-109 

Table 4-81. GSE Emission Inventories for Tuesday April 24, 2001 (tons per day)... 4-110 

Table 4-82. GSE Emission Inventories for Calendar Year 2005 (tons per year) ....... 4-111 

Table 4-83. GSE Emission Inventories for Calendar Year 2010 (tons per year) ....... 4-112 

Table 4-84. Fuel Consumption Indices for Union Pacific Railroad........................... 4-115 

Table 4-85. Union Pacific Railroad Gross Ton Miles for Pima County Track 

 Segments ............................................................................................. 4-117 

Table 4-86. Union Pacific Railroad Fuel Consumption in the TAPA ....................... 4-118 

Table 4-87. Forecasted Union Pacific Railroad Fuel Consumption in the TAPA ..... 4-121 

Table 4-88. Locomotive Emission Control Impacts on Fleetwide Emission Rates 

 For Union Pacific Railroad ................................................................. 4-121 

Table 4-89. Locomotive Emission Factors for Union Pacific Railroad 

 (pounds per gallon of fuel consumed)................................................. 4-123 

Table 4-90. Annual Locomotive Emission Estimates for the TAPA (tons per year). 4-124 

Table 4-91. Day-Specific Locomotive Emission Estimates for the TAPA 

 (tons per year)...................................................................................... 4-126 

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LIST OF FIGURES 

Figure 2-1. Total Hours of Operation by Day of Week.............................................. 2-14 

Figure 2-2. PAG 190 Hourly Activity Profiles........................................................... 2-16 

Figure 2-3. PAG 095 Hourly Activity Profiles........................................................... 2-17 

Figure 2-4. PAG 095 Day-of-Week Activity Profiles................................................ 2-17 

Figure 2-5. PAG 095 Monthly Activity Profiles ........................................................ 2-18 

Figure 3-1. TAPA 2000 VOC Emissions................................................................... 3-34 

Figure 3-2. TAPA 2000 NOx Emissions ................................................................... 3-34 

Figure 3-3. TAPA August 22, 2000 Area Source VOC Emissions ........................... 3-49 

Figure 3-4. TAPA August 22, 2000 Area Source NOx Emissions ............................ 3-49 

Figure 3-5. TAPA September 10, 2000 Area Source VOC Emissions...................... 3-50 

Figure 3-6. TAPA September 10, 2000 Area Source NOx Emissions....................... 3-50 

Figure 3-7. TAPA April 24, 2001 Area Source VOC Emissions............................... 3-51 

Figure 3-8. TAPA April 24, 2001 Area Source NOx Emissions ............................... 3-51 

Figure 4-1. Relationship Used to Estimate Aircraft PM Emission Rates .................. 4-42 

Figure 4-2. Class I Railroad Freight Movement Since 1970.................................... 4-119 

Figure 4-3. Class I Railroad Energy Intensity Since 1970 ....................................... 4-120 

Figure 4-4. Fleetwide Locomotive Emission Reductions .......................................... 4-122 

Figure 5-1. Episodic Day Inventories for the Tucson Air Planning Area .................. 5-4 

Figure 5-2. Modeling Inventory Processing Input Data ............................................. 5-5 

Figure 5-3. Spatial Allocation Factor Surrogate Definition for the TAPA ................ 5-7 

Figure 5-4. Carbon-bond Mechanism Species Gram Molecular Weights 

 for Reporting ....................................................................................... 5-15 

Figure 5-5. Modeling Input Emissions Totals for the August 22nd 

 Typical Summer Day (tons/day)......................................................... 5-15 

Figure 5-6. Day-specific Modeling Input Emissions Totals (tons) ............................ 5-16 

Figure 6-1. Diurnal Variation of Stationary Area Source NO Emissions 

(g-mole/hour) in Grid Cell (105,120) from the Typical 

 Summer Day 2000 UAM Input File.................................................... 6-7 

Figure 6-2. Gridded Stationary Area Source Paraffin Emissions (g-mole/hour) 

 at 1 PM from the Typical Summer Day 2000 UAM Input File .......... 6-8 

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ABBREVIATIONS AND ACRONYMS 

ADEQ Arizona Department of Environmental Quality 

ADWM Arizona Department of Weights and Measures 

ALD2 High Molecular Weight Aldehydes (RCHO, R≠H) 

AML Arc Macro Language 

AQM Air Quality Model 

APU Aircraft Power Unit 

ARB California Air Resources Board 

ASC Area Source Category Code 

AT Air Taxi 

CNG Compressed Natural Gas 

CO Carbon Monoxide 

CSF Chemical Speciation Factor 

DM Davis-Monthan Air Force Base 

DOT Department of Transportation 

EDMS Emissions Dispersion Modeling System 

EEA Energy & Environmental Analysis, Inc. 

EIPP Emission Inventory Preparation Plan 

EPA The U.S. Environmental Protection Agency 

ETH Ethene (CH2═CH2) 

FAA Federal Aviation Administration 

FAEED FAA Aircraft Engine Emission Database 

FIPS Federal Information Processing System 

FIRE EPA’s Factor Information REtrieval Data System 

FORM Formaldehyde (CH2═O) 

GA General Aviation 

GIS Geographical Information System 

GSE Ground Support Equipment 

ICAO International Civil Aviation Organization 

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ABBREVIATIONS AND ACRONYMS 

ISOP Isoprene 

LPG Liquid Petroleum Gas 

LTO Landing and TakeOff 

NAD27 North American Datum - 1927 

NCDC National Climatic Data Center 

NEI US EPA National Emission Inventory 

NEVES Nonroad Engine and Vehicle Emission Study 

NG Natural Gas 

NO Nitric Oxide 

NO2 Nitrogen Dioxide 

NOX Oxides of Nitrogen 

OLE Olefinic Carbon Bond (C═C) 

ORNL Oak Ridge National Laboratory 

PAG Pima Association of Governments 

PAR Paraffinic Carbon Bond (C—C) 

PDEQ Pima County Department of Environmental Quality 

PM Particulate Matter 

PM2.5 Particulate Matter less than 2.5 microns 

PM10 Particulate Matter less than 10 microns 

RASP Regional Aviation System Plan 

RVP Reid Vapor Pressure 

SAF Spatial Allocation Factor 

SCC Source Category Code 

SCF Standard Cubic Foot 

SIC Standard Industrial Classification 

SIP State Implementation Plan 

SO2 Sulfur Dioxide 

SOX Oxides of Sulfur 

TAF Temporal Allocation Factor 

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ABBREVIATIONS AND ACRONYMS 

TAPA Tucson Air Planning Area 

TAZ Transportation Analysis Zone 

THC Total Hydrocarbon 

TIA Tucson International Airport 

TIM Time-In-Mode 

TOL Tolulene (C6H5—CH3) 

TTN EPA Technology Transfer Network 

UAM Urban Airshed Model 

UP Union Pacific Railroad 

VOC Volatile Organic Compounds as defined by the 1990 Clean Air 

Act Amendments 

XYL Xylene (C6H6—(CH3)2) 

 

 

 

 

 

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(Prior material unrelated to VISTAS modeling is intentionally omitted) 

While emission rates for HC, CO, and NOx are routinely measured from (new) commercial air 

carrier engines under the emissions certification component of International Civil Aviation 

Organization (ICAO) regulations, measurement of PM emissions is not required. As a result, 

almost all aircraft engine PM emission rate data have been collected under special studies. 

Currently, such data exists for only about 20 aircraft engines, with a considerable portion of these 

data collected by the U.S. Air Force for military aircraft engines. While emission factors for 

these engines are included in the AP-42 database upon which the FAEED and EDMS emission 

inventory models were developed, they have not been included in either model due to their 

limited applicability. To date, it has been standard EPA practice not to estimate PM emissions 

for aircraft engines. However, since the emissions models maintain a placekeeper for PM 

emission rates and include PM emission estimates for GSE, it can appear to the uninformed user 

that aircraft PM emission rates are zero. As a result, aircraft are often incorrectly considered to be 

insignificant PM sources even though those engines tested for PM have demonstrated significant 

emission rates. This policy of exclusion by omission is not appropriate in developing an accurate 

modeling inventory, even in the absence of a large emissions database. While a precise 

emissions estimate cannot be made with available data, it is clear that a zero emission rate is far 

from accurate. 

As an alternative for this study, measured emissions data for aircraft engines that have been 

tested for PM were statistically analyzed to determine whether or not a relationship to other 

measured emissions parameters could be established. Intuitively, it was hoped that an inverse 

relationship with NOx might be demonstrated, as such a relationship is theoretically attractive. 

While the level of sophistication of the statistical analysis is constrained by the quantity of data 

available, simple direct and indirect linear relationships can be examined. Because data are not 

available for each test engine in each of the four LTO cycle modes and because relationships 

might be expected to vary by operating mode (due to significant changes in engine and 

combustion efficiency), all statistical analysis was performed for each operating mode 

individually. 

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Statistically significant relationships were found for the direct linear analysis for three of the four 

LTO cycle modes. Significant in this context means that coefficient t-statistics for one or more 

of the other measured pollutants (HC, CO, or NOx) indicated a direct relationship with measured 

PM (at a confidence level exceeding 95 percent). In all cases, correlation coefficients were poor 

(as expected), suggesting a high level of variability and poor predictability of PM emissions for 

any given engine. Nevertheless, statistics were unbiased and should provide an accurate 

mechanism to initially assess PM emissions on a aggregate basis (i.e., over a range of aircraft 

engine models such as those associated with an analysis for an entire set of airport operations). 

Only at idle was no significant relation found, which is not surprising given relative engine 

inefficiency in this mode. 

The indirect linear analysis revealed a consistent and significant inverse relationship between PM 

and NOx based on calculated t-statistics. Correlation coefficients continue to be poor, but 

t-statistics are generally improved over those of the direct linear analysis (all developed inverse 

relations, including idle, were significant at the 99 percent confidence level). In selecting the 

most appropriate relationship for estimation of PM emission rates for non-tested aircraft engines, 

the statistical analysis that produced the best combination of a significant t-statistic, a relatively 

low root mean square error, and an intuitive engineering basis was identified. This was the 

inverse NOx relationship for the takeoff (i.e., full throttle) mode of operation. Figure 4-1 

illustrates the selected statistical relationship. 

With this relationship established, PM emission rate data for the other aircraft operating modes 

(i.e., the approach, taxi, and climbout modes) was statistically analyzed against observed PM 

emission rate data for the takeoff mode. Statistically significant relations were developed for all 

three modes. Table 4-23 presents the coefficients developed for these PM-to-PM regressions as 

well as the statistics for the PM-to-NOx regression developed for the takeoff mode. These four 

relations were used to develop a set of fleetwide PM emission factors based on measured takeoff 

NOx emission rates. These emission factors were then input into the EEA aircraft emissions 

model and used to generate PM emission estimates for TIA aircraft operations. 

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FIGURE 4-1. Relationship Used to Estimate Aircraft PM Emission Rates 

TABLE 4-23. Statistics for Aircraft and APU PM Relations 

Statistical Parameter Takeoff PM Climbout PM Approach PM Taxi PM 

Predictive Parameter 1/Takeoff NOx Takeoff PM Takeoff PM Takeoff PM 

Coefficient 28.42 1.42 1.53 3.10 

Coefficient t-statistic 5.1 11.8 14.9 5.7 

Correlation Coefficient 0.30 0.84 0.91 0.56 

F-statistic 7.4 86.1 135.7 21.9 

Number of Observations 18 17 15 18 

(Subsequent material unrelated to VISTAS modeling is intentionally omitted) 

0

1

2

3

4

5

6

7

8

9

10

0 5 10 15 20 25 30 35 40 45

Takeoff NOx (lb/KlbF)

Takeoff PM (lb/KlbF)

Diamond-shaped markers represent actual data

points used in takeoff mode PM statistical analysis.

The plotted regression line represents the statistical

best fit relation between takeoff PM and takeoff NOx,

the equation for which is:

 Takeoff PM = 28.42 (1/Takeoff NOx)

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MACTEC, Inc. 235

APPENDIX F: 

COMPARISON OF BASE F AND BASE G ON-ROAD MOBILE EMISSIONS

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236

Base G Onroad Mobile Emissions (Annual Tons)

FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 AL 125,768 76,065 44,503 156,460 100,693 42,622 1,303,508 902,469 594,725 6,827 802 654 3,861 3,136 2,193 2,768 

FL 520,757 336,707 199,050 460,503 312,321 136,040 4,493,820 3,308,863 2,263,190 20,687 2,584 2,302 11,148 9,801 7,516 7,779 

GA 279,975 192,773 99,464 304,309 207,024 92,113 2,699,650 1,956,263 1,303,529 12,043 1,568 1,325 7,165 6,005 4,406 5,110 

KY 102,362 73,142 42,810 154,634 100,025 46,993 1,214,191 950,912 711,211 6,238 751 694 3,682 2,944 2,348 2,667 

MS 86,811 51,600 28,699 110,672 69,952 27,620 853,774 602,257 394,247 4,566 532 401 2,828 2,250 1,479 2,089 

NC 260,895 166,844 91,720 323,606 199,281 79,433 2,839,283 1,966,195 1,207,391 12,286 1,487 1,346 6,505 5,510 3,994 4,571 

SC 114,861 71,781 41,866 138,940 91,471 39,348 1,226,555 878,825 588,536 5,909 713 584 3,414 2,831 1,986 2,473 

TN 177,943 114,032 61,339 235,869 150,179 62,446 1,893,704 1,320,562 863,682 9,127 1,065 862 5,312 4,160 2,813 3,904 

VA 157,989 95,694 55,992 219,835 132,699 57,192 2,136,288 1,435,359 954,463 8,196 1,067 949 4,499 3,706 2,922 3,067 

WV 41,703 24,570 14,652 58,340 35,234 15,530 526,841 360,865 243,683 2,438 276 231 1,366 1,057 747 984 

VISTAS 1,869,063 1,203,208 680,096 2,163,168 1,398,879 599,336 19,187,613 13,682,570 9,124,656 88,316 10,844 9,348 49,780 41,400 30,403 35,411 

Base F Onroad Mobile (Annual Tons)

FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 AL 118,978 73,137 47,151 157,626 101,299 46,598 1,300,754 934,442 675,902 6,898 637 720 3,905 3,195 2,488 2,799 

FL 438,761 293,423 192,096 402,099 284,737 134,465 4,022,000 3,090,443 2,306,759 18,802 1,911 2,289 10,185 9,027 7,691 7,126 

GA 265,972 187,102 104,678 306,998 208,568 100,707 2,712,473 2,044,169 1,474,029 12,182 1,256 1,458 7,252 6,116 4,995 5,169 

KY 96,202 63,210 38,814 154,093 97,731 43,014 1,195,656 932,296 669,891 5,988 587 651 3,728 3,008 2,283 2,699 

MS 81,701 49,986 30,337 110,242 69,949 29,829 849,049 624,575 445,150 4,614 398 441 2,863 2,296 1,688 2,114 

NC 272,594 167,894 87,718 290,873 207,670 83,399 2,677,118 2,192,253 1,238,802 12,482 1,314 1,323 6,733 5,874 4,299 4,754 

SC 107,236 69,026 44,121 139,403 91,832 42,641 1,220,825 921,308 663,597 5,972 558 643 3,454 2,884 2,258 2,502 

TN 168,389 109,716 63,916 233,324 147,591 66,879 1,881,893 1,359,880 961,929 9,202 833 944 5,349 4,247 3,199 3,927 

VA 143,969 91,230 59,737 222,830 133,039 64,079 1,996,287 1,483,125 1,091,546 7,234 902 1,059 4,546 3,768 3,343 3,097 

WV 39,581 23,914 15,375 60,335 36,000 16,940 533,258 379,272 273,900 2,495 228 255 1,399 1,099 844 1,005 

VISTAS 1,733,382 1,128,638 683,942 2,077,822 1,378,416 628,551 18,389,312 13,961,764 9,801,505 85,868 8,622 9,783 49,414 41,513 33,086 35,191 

Emissions Change (Base G - Base F, Annual Tons) -- Positive Value Indicates Increase from Base F

FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 AL 6,789 2,928 -2,647 -1,166 -606 -3,977 2,754 -31,973 -81,178 -71 165 -66 -45 -58 -295 -31 FL 81,997 43,284 6,955 58,404 27,584 1,575 471,820 218,420 -43,569 1,885 672 14 963 774 -175 653 

GA 14,003 5,671 -5,214 -2,689 -1,544 -8,594 -12,823 -87,906 -170,500 -139 312 -133 -86 -111 -589 -59 

KY 6,160 9,933 3,996 541 2,294 3,979 18,534 18,615 41,319 250 164 43 -46 -65 65 -32 MS 5,110 1,613 -1,638 430 3 -2,209 4,724 -22,319 -50,903 -48 134 -41 -35 -46 -209 -25 NC -11,699 -1,049 4,001 32,734 -8,389 -3,966 162,165 -226,057 -31,411 -196 174 23 -228 -364 -304 -183 

SC 7,625 2,755 -2,255 -462 -362 -3,293 5,731 -42,483 -75,061 -63 156 -59 -40 -53 -272 -29 TN 9,554 4,316 -2,577 2,545 2,589 -4,433 11,811 -39,318 -98,246 -75 232 -82 -37 -87 -385 -22 VA 14,020 4,464 -3,744 -2,995 -340 -6,887 140,001 -47,766 -137,084 962 165 -110 -47 -62 -420 -30 WV 2,122 656 -723 -1,995 -766 -1,410 -6,416 -18,407 -30,217 -57 49 -24 -32 -42 -97 -22 

VISTAS 135,680 74,570 -3,846 85,346 20,462 -29,215 798,301 -279,194 -676,850 2,448 2,222 -435 367 -114 -2,683 219 

Emissions Change (Base G - Base F/Base F, Annual %) -- Positive Value Indicates Increase from Base F

FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 AL 6% 4% -6% -1% -1% -9% 0% -3% -12% -1% 26% -9% -1% -2% -12% -1% FL 19% 15% 4% 15% 10% 1% 12% 7% -2% 10% 35% 1% 9% 9% -2% 9% GA 5% 3% -5% -1% -1% -9% 0% -4% -12% -1% 25% -9% -1% -2% -12% -1% KY 6% 16% 10% 0% 2% 9% 2% 2% 6% 4% 28% 7% -1% -2% 3% -1% MS 6% 3% -5% 0% 0% -7% 1% -4% -11% -1% 34% -9% -1% -2% -12% -1% NC -4% -1% 5% 11% -4% -5% 6% -10% -3% -2% 13% 2% -3% -6% -7% -4% SC 7% 4% -5% 0% 0% -8% 0% -5% -11% -1% 28% -9% -1% -2% -12% -1% TN 6% 4% -4% 1% 2% -7% 1% -3% -10% -1% 28% -9% -1% -2% -12% -1% VA 10% 5% -6% -1% 0% -11% 7% -3% -13% 13% 18% -10% -1% -2% -13% -1% WV 5% 3% -5% -3% -2% -8% -1% -5% -11% -2% 21% -9% -2% -4% -12% -2% VISTAS 8% 7% -1% 4% 1% -5% 4% -2% -7% 3% 26% -4% 1% 0% -8% 1% 

VOC NOx CO SO2 PM-10 VOC NOx CO SO2 PM-10 VOC NOx CO SO2 PM-10 VOC NOx CO SO2 PM-10 

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Annual Onroad Emissions Comparison

0

100,000200,000300,000400,000500,000600,000

AL FL GA KY MS NC SC TN VA 

Annual VOC Emissions (Tons)

20

20

20

20

20

20

Appendix G Attachment 12 - Page Number:269
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Annual Onroad Emissions Comparison

0

50,000

100,000150,000200,000250,000300,000350,000400,000450,000500,000

AL FL GA KY MS NC SC TN 

Annual NOx Emissions (Tons)

Appendix G Attachment 12 - Page Number:270
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Annual Onroad Emissions Comparison

0

500

1,0001,5002,0002,5003,0003,5004,0004,5005,000

AL FL GA KY MS NC SC TN VA 

Thousands

Annual CO Emissions (Tons)

20

20

20

20

20

20

Appendix G Attachment 12 - Page Number:271
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240

Annual Onroad Emissions Comparison

0

5,000

10,00015,00020,00025,000

AL FL GA KY MS NC SC TN VA 

Annual SO2 Emissions (Tons)

20

20

20

20

20

20

Appendix G Attachment 12 - Page Number:272
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241

Annual Onroad Emissions Comparison

0

2,0004,0006,0008,000

10,00012,000

AL FL GA KY MS NC SC TN VA 

Annual PM-10 Emissions (Tons)

20

20

20

20

20

20

Appendix G Attachment 12 - Page Number:273
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242

Annual Onroad Emissions Comparison

0

1,0002,0003,0004,0005,0006,0007,0008,0009,000

AL FL GA KY MS NC SC TN VA 

Annual PM-2.5 Emissions (Tons)

200

200

200

200

20

20

Appendix G Attachment 12 - Page Number:274
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243

Annual Onroad Emissions Comparison

0

5,000

10,00015,00020,00025,000

AL FL GA KY MS NC SC TN VA 

Annual NH3 Emissions (Tons)

20

20

20

20

20

20

Appendix G Attachment 12 - Page Number:275