# Attachment 12_BASE G 2002 BY 2009_18 Emission Inventories f .pdfMACTEC, Inc. 

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

Prepared for:

Visibility Improvement State and Tr ibal Association of the Southeast (VISTAS)

Prepared by:

MACTEC, Inc.

______________________ ______________________
William R. Barnard Edward Sabo Sr. Principal Scientist Principal ScientistMACTEC, Inc. 2 

## Table of Contents

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

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

1.1 P OINT S OURCES

............................................................................................................................... ............4 1.1.1 Development of 2002 Po int Source Inventory ..................................................................................... ..4
1.1.1.1 Data Sources ................................................................................................................... ............................. 5 1.1.1.2 Initial Data Evaluation ........................................................................................................ ......................... 6 1.1.1.3 PM Augmen tation................................................................................................................ ........................ 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 Upda tes and Co rrections...................................................................................... ........ 12 1.1.1.7 Summary of Base G 2002 Inve ntory............................................................................................... ........... 15 1.1.2 Development of Typical Year EGU in ventory...................................................................................... 18 1.2 A REA S OURCES

............................................................................................................................... ..........20 1.2.1 Development of a “typical ” year fire inventory ................................................................................. .22 1.2.2 Development of n on-fire inve ntory .............................................................................................. ........31 1.2.3 2002 Base G inventory updates .................................................................................................. .........34
1.2.3.1 Changes resulting from St ate review and comment ................................................................................ ... 34 1.2.4 Ammonia and paved road emissions............................................................................................... .....37 1.2.5 Global Changes Ma de for Base G................................................................................................. ......38 1.2.6 Quality Assura nce steps........................................................................................................ ...............39 1.3 M OBILE S OURCES

............................................................................................................................... ......40 1.3.1 Development of on-road mobile so urce input files and VMT estim ates...............................................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 NONRO AD model s ources........................................................................................... ... 45 1.3.2.2 Emissions from Commercial Marine Vesse ls, Locomotives, a nd Airpla nes.............................................. 61 Base G R evision s: .............................................................................................................. ................................78
1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indian a, and Ohio .............................................. 85 1.3.3 Quality Assura nce steps........................................................................................................ ...............87

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

2.1 P OINT S OURCES

............................................................................................................................... ..........88 2.1.1 EGU Emission Projec tions ....................................................................................................... ...........88
2.1.1.1 Chronology of the Developm ent of EGU Projec tions............................................................................... . 88 2.1.1.2 VISTAS IPM runs for EGU sources................................................................................................ .......... 92 2.1.1.3 Post-Processing of IP M Parsed Files ............................................................................................ ............. 93 2.1.1.4 Eliminating Double C ounting 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 Inventor ies ............................................. 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 S hutdow ns............................................................................................................... ..................... 112 2.1.2.3 Control Programs applie d to non-E GU sour ces .................................................................................... ... 114MACTEC, Inc. 3 2.1.2.4 Quality Assurance steps........................................................................................................ ................... 117 2.1.2.5 Additional Base G Upda tes and Co rrections...................................................................................... ...... 117 2.1.2.6 Summary of Revised 2009/2018 non-E GU Point Source I nventorie s...................................................... 117 2.2 A REA S OURCES

............................................................................................................................... ........123 2.2.1 Stationary ar ea 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 be tween 2009/2018

.................................................................................................. ............. 127 2.2.2 Agricultural ar ea sources ...................................................................................................... ............128
2.2.2.1 Control assumptions for agri cultural area sources .............................................................................. ..... 128 2.2.2.2 Growth assumptions for agri cultural area sources ............................................................................... .... 128 2.2.3 Changes to Prescribed Fire for 2009/2018 Base G...........................................................................133 2.2.4 Quality Assura nce steps........................................................................................................ .............138 2.3 M OBILE S OURCES

............................................................................................................................... ....138 2.3.1 Development of on-road mobi le source inpu t 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 R evisions ...............................................................................................................................150 2.3.4 Development of non-road emission estimat es....................................................................................1 50
2.3.4.1 NONROAD model source s.......................................................................................................... ............ 151 2.3.4.2 Non-NONROAD m odel s ources...................................................................................................... ........ 153 2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indian a, and Ohio ............................................ 188 2.3.4.4 Differences be tween 2009/2018

.................................................................................................. ............. 188 2.3.5 Quality Assura nce 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 EmissionsDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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## List of Tables

Table I-1. Inventory Version in Use by Y ear and Source Sector Through Base G - 2002 Table I-2. Inventory Version in Use by Y ear and Source Sector Through Base G - 2009 Table I-3. Inventory Version in Use by Y ear 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 SO 2 

### (tons/year) Table 1.1-5. Base G 2002 VISTAS Point Source Inventory for NO x 

### (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 PM 10 

### -PRI (tons/year) Table 1.1-9. Base G 2002 VISTAS Point Source Inventory for PM 2.5 

### -PRI (tons/year) Table 1.1-10. Base G 2002 VISTAS Point Source Inventory for NH 3 

### (tons/year) Table 1.1-11. Comparison of SO 2 

### and NO x 

### Emissions (tons/year) for EGUs from Base G Actual 2002 Inventory a nd Typical 2002 Inventory. Table 1.2-1. Emissions from Fires in the VI STAS Region – Comparison between Original Base Year 2002 (VISTAS 3.1), 2002 Ac tual and Typical Year Base G Emissions. Table 1.2-2. Summary of St ate 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 da y 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 F ile 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-NO x 

### Ratios by Aircraft Type in In itial 2002 Base Year Inventory Table 1.3-8. Tucson, AZ PM-to-NO x 

### Ratios by Aircraft Type. Table 1.3-9. Non-Corresponding Ai rcraft 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 NO x 

### Records with No Corresponding PM Record.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 Comparis on of Aircraft Emissions (Airports with Aircraft NO x 

### > 200 tons per year) Table 1.3-17. Base G VA Ai rcraft 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 Comparis on of Aircraft Emissions (Airports with Aircraft NO x 

### > 200 tons per year) Table 1.3-22. Non-Default Files Used for MRPO Modeling Table 2.1-1. Adjustments to IPM Control Determ inations 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 SO 2 

### Emission Comparison for 2002/2009/2018 Table 2.1-4. EGU Point Source NO x 

### 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 PM 10 

### -PRI Emission Comparison for 2002/2009/2018 Table 2.1-8. EGU Point Source PM 2.5 

### -PRI Emission Comparison for 2002/2009/2018 Table 2.1-9. EGU Point Source NH 3 

### 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 Corr ections to the Base F 2009/2018 Inventories Incorporated into the Base G 2009/2018 Inventories Table 2.1-13. Non-EGU Point Source SO 2 

### Emission Comparison for 2002/2009/2018 Table 2.1-14. Non-EGU Point Source NO x 

### 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 PM 10 

### -PRI Emission Comparison for 2002/2009/2018 Table 2.1-18. Non-EGU Point Source PM 2.5 

### -PRI Emission Comparison for 2002/2009/2018. Table 2.1-19. Non-EGU Point Source NH 3 

### Emission Comparison for 2002/2009/2018 List of Tables (continued)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.2-1 2002 Base Year Emissions and Perc entage 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 Differe nce for Base F & Base G Table 2.2-4 Percentage Differe nce 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 Airc raft, Locomotive, and Non-R ecreational 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 Reduc tion 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. SO 2 

### 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, Locomotiv e, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-15. Base F 2018 Aircraft, Locomotiv e, 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)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 T ypical Base G Inventories. Figure 1.2-2. CO Emissions from Land Cleari ng Burning for the Original Base Year, 2002 Actual Base G and 2002 Typi cal Base G Inventories. Figure 1.2-3. CO Emissions from Prescribed Bu rning for the Original Base Year, 2002 Actual Base G and 2002 Typical Base G Inventories. Figure 1.2-4. CO Emissions from Wildfire Bu rning 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 Appa rent CAIR Inventory Discrepancy Figure 2.3-2. Total Aircraft, Locomotiv e, and CMV CO Emissions (Base F) Figure 2.3-3. Locomotive CO Emissions (Base F) Figure 2.3-4. Total Aircraft, Locomotive, and CMV NO x 

### Emissions (Base F) Figure 2.3-5. Locomotive NO x 

### Emissions (Base F) Figure 2.3-6. Total Aircraft, Locomotive, and CMV PM 10 

### Emissions (Base F) Figure 2.3-7. Locomotive PM 10 

### Emissions (Base F) Figure 2.3-8. Total Aircraft, Locomotive, and CMV PM 2.5 

### Emissions (Base F) Figure 2.3-9. Locomotive PM 2.5 

### Emissions (Base F) Figure 2.3-10. Total Aircraft, Locomotive, and CMV SO 2 

### Emissions (Base F) Figure 2.3-11. Locomotive SO 2 

### Emissions (Base F) Figure 2.3-12. Total Aircraft, Locomotiv e, and CMV VOC Emissions (Base F) Figure 2.3-13. Locomotive VOC Emissions (Base F) Figure 2.3-14. Total Aircraft, Locomotiv e, and CMV CO Emissions (Base G) Figure 2.3-15. Locomotive CO Emissions (Base G) Figure 2.3-16. Total Aircraft, Locomotive, and CMV NO x 

### Emissions (Base G) Figure 2.3-17. Locomotive NO x 

### Emissions (Base G) Figure 2.3-18. Total Aircraft, Locomotive, and CMV PM 10 

### Emissions (Base G) Figure 2.3-19. Locomotive PM 10 

### Emissions (Base G) Figure 2.3-20. Total Aircraft, Locomotive, and CMV PM 2.5 

### Emissions (Base G) Figure 2.3-21. Locomotive PM 2.5 

### Emissions (Base G) Figure 2.3-22. Total Aircraft, Locomotive, and CMV SO 2 

### Emissions (Base G) Figure 2.3-23. Locomotive SO 2 

### Emissions (Base G) Figure 2.3-24. Total Aircraft, Locomotiv e, and CMV VOC Emissions (Base G) Figure 2.3-25. Locomotive VOC Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 achievab le control technologyDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Acronyms and Abbreviations (continued) MACTEC MACTEC Engineer ing and Consulting, Inc. MOBILE 6 MOBILE emissions es timation model version 6 MRPO Midwest Regional Planning Organization
NH 3 

### 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) NO x 

### 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
PM 10 

### -FIL Particulate matter less than or equal to 10 microns in diameter that can be captured on a filter
PM 10 

### -PRI Particulate matter less than or equal to 10 microns in diameter that includes both the filterable and condensable components of particulate matter
PM 2.5 

### -FIL Particulate matter less than or equal to 2.5 microns in diameter that can be captured on a filter
PM 2.5 

### -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 co ndensation of hot materials to form particulates, usually less th an 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 CodeDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 Ke rnel Emissions Modeling System S/L State and Local SO 2 

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

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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 hist ory 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 develope d 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), MAC TEC Engineering and Consulting, Inc. (MACTEC), a nd 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 input s to the MOBILE6 model to pr oduce a draft version of the 2002 inventory. For non-road sources, a sim ilar approach was used. Updated State information on temperatures and fuel characte ristics 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 us ing appropriate growth surrogates. A draft version of these inventories wa s 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/documen ts/Pechan_drafton-roadinventory_082803.ppt while an overview of the non-road component can be found at: http://www.vistas-sesarm.org/docum ents/Pechan_Non-roadInventory_082803.ppt

. Similarly, draft versions of the 2002 point a nd 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 gr owth surrogates from Economic GrowthDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Analysis System (EGAS) version 4. Toxic Rel ease Inventory (TRI) data were used to augment the inventory for NH 3 

### . Continuous Emissions Monitor (CEM) data from the U.S. EPA’s Clean Air Markets Division wa s used to supply emissions for electric generating utilities (EGUs). Particulate matte r 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) ammoni a 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/documen ts/MACTEC_draftpointareainventory_82803.ppt

.
Three interim versions of th e 2002 base year inventory we re developed. The first was delivered in August of 2003, the second in Ap ril of 2004 and the final one in October of 2004. The August 2003 and April 2004 inventor ies 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 Oct ober 2004. That 2002 base year inventory was solely prepared by MACTEC. The Oct ober 2004 inventory incorporated 2002 Consolidated Emissions Reporting Rule (CERR) data into the inve ntory along with some updated data from the VISTAS States. This inve ntory is typically referred to as version 3.1 of the VISTAS inventory
Closely following the version 3.1 2002 ba se year inventory, a “preliminary” 2018 projection inventory was devel oped. 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 versi on of the 2002 base year inventory, States were asked to review and provide comments on that inventory to MACTEC for updateDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### and revision. At the same time MACTEC pr epared a revised draf t version of the 2018 projection inventory (January 2005) and a dr aft version of a 2009 projection inventory (April 2005). All of these were known as vers ion 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 we re provided to the VISTAS States. At that time to be consiste nt with the modeling nomenclature being used by AG in performing their modeling runs, th e inventory became the Base F VISTAS inventory. The Base F inventory was deliver ed for review and comment in August of 2005. In addition, MACTEC deliv ered 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 J une/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 a dditional updates to the inventory were prepared based on the comm ents 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 speci fic 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 whic h version of the inve ntory is in use for each sector of the inventory as of Base G.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 Area 1 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 appl y 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 f ugitive dust sources per WRAP methodology; C) addition of portable fuel container (PFC ) emissions to all States based on OTAQ report.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 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 EGU 1 Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-EGU Point 2 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 methodologyused for nonNONROAD model

sources. Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused 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 methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all

sources included in the NONROAD model.

Base F projection methodologyused 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 DO E AEO2006 fuel use projectionsDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 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 EGU 1 Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-EGU Point 2 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 methodologyused for nonNONROAD model

sources. Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused 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 methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

sources Base G for all sources included in the NONROAD model.

Base F projection methodologyused 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 DO E AEO2006 fuel use projectionsDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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## 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 Southeas t (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 th e 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 PM 10 

### -PRI and PM 2.5 

### -PRI; 4) evaluating the emissi ons 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 typica l year electric generati ng 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 em ission inventory in June 2004 ( Development of the Draft 2002 VISTAS Emission Inventory for Regi onal 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 (NEI 99V2). For several states, we replaced the NEI99V2 data with more recent inventorie s 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, incorpor ating 2002 Continuous Emissions Monitoring-(CEM)-based SO 2 

### and NO x 

### emissions for electric utilities, adding PM 10 

### and PM 2.5 

### emissions when they were missing from an S/L submittal, and performing a variety of additional Quality assurance/Quality control (QA/QC) checks.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 5 

### 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 i nventory (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 PM 10 

### and PM 2.5 

### 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 Ba se F point source inventor y: 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 inve ntory, 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 Ha milton County was based on the draft VISTAS 2002 inventory, which in turn wa s based on the 1999 NEI).

Table 1.1-1 summarizes the data used as the st arting point for the Base F 2002 inventory. Once all of the files were obtained, MACTEC ra n 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 particul ate matter (PM) and ammo nia emissions. MACTEC contacted each VISTAS State poin t 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 VIST AS point source files. S/L agencies completed a detailed review of the Base F inventory. A dditional updates and corrections to the Base F inventory were requested by S/L ag encies and incorporated into th e Base G inventory. The Base G changes are documented in more detail in Section 1.1.1.6.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.1-1. State Data Submittals Used fo r 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 ini tial review of the 2002 poi nt source CERR data in accordance with the QA procedures specified in th e Quality Assurance Proj ect Plan (QAPP) for this project. The following evaluations were co mpleted to identify potential data quality issues associated with the CERR data:

• 

### Compared the number of sites in the CERR su bmittal 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 inve ntory, since the CERR data was limited to major sources, while the VISTAS draft 2002 in ventory contained data for both major and minor sources; verified with S/L contacts th at minor sources not included in the CERR point source inventory were included in the CERR area source inventory.

• 

### Checked for correct pollutant codes and co rrected to make them NIF-compliant; for example, some S/L agencies reported ammoni a emissions using the CAS Number or as “ammonia”, rather than the NIF-compliant “NH 3 

### ” code.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Checked for types of particulate matter c odes reported (i.e., PM-FIL, PM-CON, PM-PRI,
PM 10 

### -PRI, PM10-FIL, PM 2.5 

### -PRI, PM 2.5 

### -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-zer o (but very small) but th e 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 outstan ding discrepancies.

• 

### Compared SO 2 

### and NO x 

### emissions for EGUs to EPA’s Clean Air Markets Division CEM database to identify any outstanding discre pancies. (A full discussion of the EGU emissions analysis is discu ssed 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 compar e emissions as repo rted in the 1999 NEI Version 2, the VISTAS draft 2002 i nventory, and the CERR submittals.

• 

### Prepared facility-level emissi on summaries by pollutant to al low 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 reso lve any QA/QC issues from these checks.

1.1.1.3 PM Augmentation Particulate matter emissions can be reporte d in many different forms, as follows:
PM Category Description PM-PRI Primary PM (include s filterable and condensable) PM-CON Primary PM, condensable por tion only (all less than 1 micron) PM-FIL Primary PM, filterable portion onlyDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### PM 10 

### -PRI Primary PM 10 

### (includes filterable and condensable)

PM 10 

### -FIL Primary PM 10 

### filterable portion only

PM 2.5 

### -PRI Primary PM 2.5 

### (includes filterable and condensable)

PM 2.5 

### -FIL Primary PM 2.5 

### 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, PM 10 

### -FIL, PM 10 

### -PRI, PM 2.5 

### -FIL, PM 2.5 

### -PRI, and/or PM-CON. From any one of these pollutants, EPA has developed augmentation procedures to estimate PM 10 

### -PRI, PM 10 

### -FIL, PM 2.5 

### -PRI, PM 2.5 

### -FIL, and PM-CON. If not included in a State/local inventory, PM 10 

### -PRI and PM 2.5 

### -PRI were calculated by adding PM 10 

### -FIL and PM-CON or PM 2.5 

### -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 a nd Ammonia – Point Sources , January 31, 2004). Briefly, the PM data augmentation procedure include s the following five steps:

• 

### Step 1: Prepare S/L/T PM and PM 10 

### Emissions for Input to the PM Calculator

• 

### Step 2: Develop and Apply Sour ce-Specific Conversion Factors

• 

### Step 3: Prepare Factor s from PM Calculator

• 

### Step 4: Develop and Apply Algorithms to Esti mate 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 co mplete 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 calcula ted using the above methodology. This table is intended to show that we took whatever States pr ovided in the way of PM and filled in gaps to add in PM-CON where emissions were missing in order to calculate PM 10 

### -PRI and PM 2.5 

### -PRI for all processes to get a complete set of pa rticulate data. We did not compare any other pollutants besides PM, since for other pollutant s CERR emissions equal VISTAS emissions. As noted in Table 1.1-2, we made si gnificant revisions to the PM emissions for Kentucky in the Base F inventory and for South Ca rolina in the Base G inventory.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.1-2. Comparison of Particulate Matte r Emissions from the S/L Data Submittals and the Base G 2002 VISTAS Point Source Inventory

State Database PM-PRI PM-FIL PM-CON PM 10 -PRI PM 10 -FIL PM 2.5 -PRI PM 2.5 -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 usin g the PM-PRI code should actually have been reported using the PM 10 -PRI code. MACTEC performed a subsequent PM augmentation in April 2005 using the PM 10 -PRI code. These changes were reflected in the Base F emission inventory. Note 3: South Carolina Department of Health and Envi ronmental Control (SC DHEC) initial CERR submittal reported particulate matter emissions using the PM-FIL, PM 10 -FIL, and PM 2.5 -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, PM 10 -FIL, and PM 2.5 -FIL pollutant codes should actually have been reported using the PM-PRI, PM 10 -PRI, and PM 2.5 _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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 10 

### After the PM augmentation process was perfor med, we executed a series of checks to identify potential inconsistencies in the PM inventory. These checks included:

• PM-PRI less than PM 10 

### -PRI, PM 2.5 

### -PRI, PM 10 

### -FIL, PM 2.5 

### -FIL, or PM-CON;

• PM-FIL less than PM 10 

### -FIL, PM 2.5 

### -FIL;

• PM 10 

### -PRI less than PM 2.5 

### -PRI, PM 10 

### -FIL, PM 2.5 

### -FIL or PM-CON;

• PM 10 

### -FIL less than PM 2.5 

### -FIL;

• PM25-PRI less than PM 2.5 

### -FIL or PM-CON;

• The sum of PM 10 

### -FIL and PM-CON not equal to PM 10 

### -PRI; and

• The sum of PM 2.5 

### -FIL and PM-CON not equal to PM 2.5 

### -PRI. S/L agencies were asked to review this in formation and provide corrections where the inconsistencies were significant. In general, co rrections (or general directions) were provided in the case of the potential inconsistency issues. In other cases, the ag ency provided specific process level pollutant corrections.
Note that for the Base G inventory, only the PM 10 

### -PRI and PM 2.5 

### -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 facilita te emissions modeling.

1.1.1.4 EGU Analysis We made a comparison of the annual SO 2 

### and NO x 

### 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 outstandi ng discrepancies. Facilities re port hourly CEM data to EPA for units that are subject to CEM reporting requirements of the NO x 

### State Implementation Plan (SIP) Call rule and Title IV of the Clean Air Act (C AA). EPA sums the hourly CEM emissions to the annual level, and we compared these annual CEM em issions to those in the S/L inventories. The 2002 CEM inventory containing NO x 

### and SO 2 

### 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 prep aring a crosswalk file to match facilities and units in the CAMD inventory to facilities and units in the S/L invent ories. In the CAMD inventory, the Office of Regulat ory Information Systems (ORI S) identification (ID) code identifies unique facilities and the unit ID identifies unique boilers and internal combustion engines (i.e., turbines and reci procating engines). In the S/L inventories, the State and county FIPS and State facility ID togeth er identify unique facilities and the emission unit ID identifies unique boilers or internal co mbustion engines. In most cases, there is a one-to-one correspondence between the CAMD id entifiers and the S/L identifiers. However, in some of the S/L inventories, the emissions for multiple emission units are summed and reported under oneDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 11 

### emission unit ID. We created an Excel spreadsheet that contained an initial crosswalk with the ORIS ID and unit ID in the CEM inventor y matched to the Stat e 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 emissi ons summed from the CAMD database as well as the S/L emission estimate. It should be noted that the initial matc hing of the IDs in both inventories was based on previ ous crosswalks that had been developed for the preliminary VISTAS 2002 inventory and in-house info rmation 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 pr epare an Excel spreadsheet that compared the annual emissions from the hourly CAMD inventor y to the annual emissions reported in the S/L inventory. The facility-level compar ison of CEM to emission inventory NO x 

### and SO 2 

### emissions found that for most facilities, the annual emissi ons from the S/L inventory equaled the CAMD CEM emissions. Minor differences could be explai ned because the facility in the S/L inventory contained additional small or emergency units th at were not included in the CAMD database.
The final step in the EGU analysis was to compare the SO 2 

### and NO x 

### emissions for select Southern Company units in the VISTAS region. Southern Company is a super-regional company that owns EGUs in four VISTAS States – Al abama, Florida, Georgia, and Mississippi – and participates in VISTAS as an industry stakeh older. Southern Compa ny independently provided emission estimates for 2002 as part of the de velopment of the preliminary VISTAS 2002 inventory. In most cases, these estimates were re viewed 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 CE M-based emissions for the actual 2002 emissions inventory for sources within the State when Sout hern 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 wh ere CAMD listed each unit individually. We compared SO 2 

### and NO x 

### 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 invent ory data set to ensure that all corrections provided by the S/L agencies and stakeholders were correctly incorporated into the S/LDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 12 

### 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 wa s 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 developm ent process, QA steps were pe rformed to ensure that no double counting of emissions occurred, and to en sure that a full and complete inventory was developed for VISTAS. QA was an important com ponent to the inventory development process and MACTEC performed the following QA steps on the point source com ponent of the VISTAS revised 2002 base year inventory:

1. Facility level emission summaries were pr epared and evaluated to ensure that emissions were consistent and th at there were no missing sources.

2. State-level EGU and non-E GU 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 representative s for review and comment. Changes based on these comments were reviewed and approve d by the S/L point source contact prior to implementing the changes in the files.

4. Version numbering was used for all i nventory 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 th e Base F inventory. Table 1.1-3 summarizes the updates and corrections to the Base F inventor y that were requested by S/L agencies and incorporated into the Base G inventory.
There was a discrepancy between the ba se year 2002 and 2009/2018 emissions for PM 10 

### -PRI, PM 2.5 

### -PRI, and NH 3 

### . The 2002 emissions were provided dire ctly by the S/L agencies and were estimated using a variety of techniques (i.e., EP A emission factors, S/L emission factors, sitespecific emission factors, and source test da ta). The 2009/2018 emissions, on the other hand, were estimated by Pechan (see Section 2.1.1.3) usi ng an emission factor file based solely on AP-42 emission factors. An adjustme nt was made for 2002 EGU PM and NH 3 

### emissions to reconcile these differences. The post- processed Integrated Planning Model ® ( 

### IPM ® 

### ) 2009/2018 output uses a set of PM and NH 3 

### emission factors that are “t he most recent EPA approved uncontrolled emission factors” – these are most likely not the same emission factors used by States and emission inventory pr eparation contractors for estimating these emissions in 2002 for EGUs in the VISTAS domain. VISTAS performe d a set of modifications to replace 2002 baseDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### year PM and NH 3 

### emission estimates with estimates deri ved from the most recent EPA-approved emission factors. For further details of the me thodology 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 EG U Special Interest Workgroup, June 13, 2005.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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-e xported 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 stack s 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 errone ous process id (#3) within emission unit id SB9 and was deleted. This removes about 6,000 tons of SO 2 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 (S ite ID: 37-081-08100910), release point G-29, 9211.38 tons volatile organic compounds (VOC's) should be 212.2 tons, 529.58 tons PM 10 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, PM 10 -FIL, and PM25-FIL pollutant c odes. In August 2005, SC DHEC indicated that data reported using the PM-FIL, PM 10 -FIL, and PM25-FIL pollutant codes should actually have been reported using the PM-PRI, PM 10 -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, us ing 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 para meters at a few facilities for stacks with parameters that do not appear to fall into the ranges typically termed "acceptable" for AQ modeling.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1.1.1.7 Summary of Base G 2002 Inventory Tables 1.1-4 through 1.1-10 summar ize 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 Sour ce 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 S CCs 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 inconsistenc ies 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 SO 2 

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

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### Table 1.1-5. Base G 2002 VISTAS Point Source Inventory for NO x 

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

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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 PM 10 

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

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### Table 1.1-9. Base G 2002 VISTAS Point Source Inventory for PM 2.5 

### -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 NH 3 

### (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 y ear 2002 emission inventory for EGUs to avoid anomalies in emissions due to variability in meteorology, eco nomic, 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Data from EPA’s CAMD were used to de velop normalization fact ors 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 actua l 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 SO 2 

### and NO x 

### emission rates, heat i nput, and operating hours.
We used the actual 2002 heat input and the av erage heat input for th e 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 he at 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 w ould be 1.0. The annual actual emissions were multiplied by the normalization factor to dete rmine the typical emissions for 2002, as follows:
Typical Emissions = 2002 actual em issions 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 prio r 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 (o r 2000) heat input and emission rate to calculate the typical year emissions.
The Southern Company provided ty pical year data for their sour ces. Hourly emissions data for criteria pollutants were provide d. 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 Mode ling (April 2005, presented at 14 th 

### International Emission Inventory Conference http://www.epa.gov/ttn/chief/conf erence/ei14/session9/kandasamy.pdf ). Since Southern Company only supplied filter able particulate emissions, we ran the PM 10 

### /PM 2.5 

### augmentation routine to calculate annual emission estimates for PM 10 

### -PRI and PM 2.5 

### -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 Southe rn Company typical year data (as was used in the Base F inventory).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The final step was to replace the 2002 actual emi ssions with the 2002 typical year data described above. MACTEC provided the raw data and resu lts of the typical ye ar 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. Fo r the entire VISTAS region, actual 2002 SO 2 

### 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 per cent lower in Florida to 10.9 percent higher in Mississippi. For th e entire VISTAS region, actual 2002 NO x 

### emissions were about 0.1 percent lower than the typical year emissions. The diffe rences on a state-be-state basis ranged from actual emissions being 9.6 percen t lower in Florida to 6.3 per cent higher in Mississippi.

Table 1.1-11. Comparison of SO 2 

### and NO x 

### Emissions (tons/year) for EGUs from Base G Actual 2002 Inventory and Typical 2002 Inventory.

SO 2 Emissions (tons/year) NO x 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 Ba se 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 inve ntory. Version 3.1 of the VISTAS ba se year fire inventory provided actual 2002 emissions estimates. Since fire emissions are not easily grown or projected, in orderDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### to effectively represent fires in both the base and future year inventories, VISTAS determined that a typical year fire inventor y was necessary. Development of th e “typical” year fire inventory covered wildfire, prescribed burni ng, agricultural fires and land cl earing fires. The first part of this section of the report disc usses the development of the ty pical year fire inventory. The methodology provided in that sectio n 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 developm ent of projection year inventories that represent alternatives to th e “typical” year inventory. These alternative projections incorporated projec ted changes in the acreage burned for prescribed fires on Federal lands. These projections are an augmen tation of the “typical” year inventory.
The second component of the area source inventor y was the incorporation of data submitted by the VISTAS States to the United States Environm ental 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 perf orm 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 Stat es 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 invent ory was related to the development of NH 3 

### emission estimates for livestock and fertiliz ers and paved road PM emissions. For the NH 3 

### emission estimates for livestock and fertilizer s we used version 3.6 of the Carnegie Mellon University (CMU) NH 3 

### 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 method ology for estimating paved road emissions so those values were substituted dir ectly into the inventory after receiving consensus from all of the VISTAS States to perform the replacement. Deta ils on these methods are provided in the third portion of this section of the docum ent. That section is virtually identical to that from the Base F inventory document as there were only a c ouple of changes to the ammonia portion of the inventory and some updates to all fugitive dus t 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1.2.1 Development of a “typical” year fire inventory Typical year fire emissions were developed st arting from the actual fire acreage data and emission calculated for each VISTAS State. Th e 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 actua l 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 VI STAS region, a typical (as opposed to strictly 2002 year based inventory) was required. Development of a typica l 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 visibili ty 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 Sp ecial Interest Work Group (SIWG) and requested their feedback and preference fo r developing the final typical y ear inventory. The method that was selected by SIWG members was to use a met hod similar to that used to develop an early version of a 2018 projection invent ory. For that early 2018 inventor y, 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 th e 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 ex ception (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:

acreage Rx level county actual 2002 acres Rx level county average term Long

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

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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 th e ratio was then used with the fuel loading and emission factor values that we already had (and had been revi ewed by the SIWG) to calculate emissions using the same method used for th e 2002 actual values (whi ch were previously documented). The following lists indicate which c ounties 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 CountyDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### There were three exceptions to this method.
Exception 1: Use of St ate 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 Bla ckened Acres on Forest Service Lands
Following discussions with the United States Fo rest Service (Forest Se rvice) (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 prescr ibed fires on Forest Service lands, a further correction was implemented to correct the peri meter 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 per cent of the initial re ported value. For pres cribed fires of 100 acres or less the acreage values were maintain ed as reported. For wildfi res, all reported acreage values were adjusted to be 66 percent of their initially reported values. These changes were made to all values reported for Fo rest 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 te rm acreage data was reported for a particular State, MACTEC determined an overall VISTAS re gional average ratio that was used to multiply times the 2002 values to produce th e “typical” values. This techni que 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 a nd those ratios were applied to each State with missing data depending upon whether they were consid ered a “northern” or “southern” tier State. Development of “southern” and “nor thern” tier data was an attempt to account for a change from a predominantly pine/evergreen ecosystem (southe rn) 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Finally for land clearing and agri cultural fires, there are no NH 3 

### and SO 2 

### emissions. This is due to the lack of emission factors for th ese pollutants for these fire types.
Table 1.2-1 shows fire emissions from the orig inal base year emissi on inventory (VISTAS 3.1), the actual 2002 emissions and th e typical year emissions for the entire VISTAS region. The actual 2002 and typical fire emissions represen t 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 typi cal year prescribed fi re 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. Valu es for fires in those ta bles are “typical” year values.
Figures 1.2-1 through 1.2-4 show the State by Stat e changes in emissions between the original 2002 base year fire inventorie s, 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 c hosen to represent the distribution of fires in the example plots.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.26Table 1.2-1. Emissions from Fires in theVISTAS Region – Comparison betweenOriginal Base Year 2002 (VISTAS 3.1), 2002Actual and Typical Year Base G Emissions.CONH3NOXPM10-FILPM10-PRIPM2.5-FILPM2.5-PRISO2VOCTotal LCActual (Base G) 492,409 0 14,568 62,146 62,146 62,146 62,146 0 33,799Typical (Base G) 675,838 0 19,995 80,598 80,598 80,598 80,598 0 46,389VISTAS 3.1 484,240 0 14,327 61,325 61,325 61,325 61,325 0 33,238Total AgActual (Base G) 164,273 0 903 30,958 30,958 30,385 30,385 0 21,946Typical (Base G) 161,667 0 903 30,465 30,465 29,892 29,892 0 21,595VISTAS 3.1 331,073 0 903 41,480 41,480 40,192 40,192 0 41,875Total WFActual (Base G) 298,835 1,333 6,628 28,923 28,923 24,926 24,926 1,611 16,804Typical (Base G) 547,174 2,451 11,955 53,070 53,070 45,635 45,635 3,072 28,491VISTAS 3.1 275,766 1,230 6,133 26,680 26,680 23,002 23,002 1,476 15,718Total RXActual (Base G) 1,678,216 7,616 36,561 168,938 168,938 145,175 145,175 9,839 78,988Typical (Base G) 1,635,776 7,425 35,650 164,811 164,811 141,636 141,636 9,590 76,990VISTAS 3.1 1,724,940 7,822 37,556 173,590 173,590 149,181 149,181 10,101 81,188Key: LC = Land Clearing; Ag = Agricultural burning; WF = wildfires; RX = prescribed burning.Actual and Typical represent BaseF and Base G (e.g., nochange in methodology for Base F and Base G) for 2002.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.27Figure 1.2-1. CO Emissions from Agricultural Burning for the Original Base Year, 2002 Actual Base G, and 2002 TypicalBase G Inventories.CO Emissions0.0020,000.0040,000.0060,000.0080,000.00100,000.00120,000.00140,000.00160,000.00AL FL GA KY MS NC SC TN VA WV

tonsAg Burning - 2002 ActualAg Burning - TypicalAg Burning - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.28Figure 1.2-2. CO Emissions from Land Clearing Burning for the Original Base Year, 2002 Actual Base G and 2002 TypicalBase G Inventories.CO Emissions0.0020,000.0040,000.0060,000.0080,000.00100,000.00120,000.00140,000.00160,000.00180,000.00AL FL GA KY MS NC SC TN VA WV

tonsLand Clearing - 2002 ActualLand Clearing - TypicalLand Clearing - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.29Figure 1.2-3. CO Emissions from Prescribed Burning for the Original Base Year, 2002 Actual Base G and 2002 TypicalBase G Inventories.CO Emissions0.00100,000.00200,000.00300,000.00400,000.00500,000.00600,000.00700,000.00AL FL GA KY MS NC SC TN VA WV

tonsPrescribed - 2002 ActualPrescribed - TypicalPrescribed - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.30Figure 1.2-4. CO Emissions from Wildfire Burning for the Original Base Year, 2002 Actual Base G and 2002 TypicalBase G Inventories.CO Emissions0.0050,000.00100,000.00150,000.00200,000.00250,000.00AL FL GA KY MS NC SC TN VA WV

tonsWildfires - 2002 ActualWildfires - TypicalWildfires - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1.2.2 Development of non-fire inventory The second task in preparing the area source co mponent 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 Ba se G inventories for this component of the inventory are identical. Modi fications to the Base F met hodology (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 revi ews 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 2 002 Base F inventory invo lved: 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 vers ion 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 emi ssion estimates described above. In addition it did not include emission estimates for ammonia from ag ricultural 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 af ter 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 submi tted in standard NIF format and that there were no issues with those files. In a couple of cases small errors were found. Fo r example, in one case a county FIPs code that was no longer in us e was found. MACTEC contacted each VISTAS State area source contact person to resolve the issu es with the files and corrections were made. Once all corrections to the native files we re 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. Wh ere 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 cl earing 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 estim ated using methods described earlier. 2. All fertilizer and agricult ural 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 alternat ive data were used to prepare the Base F inventory. In general, these alternatives involve d 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 fr om one of the following sources: 1. CERR submittal obtained from EPA FTP s ite as directed by VISTAS States; 2. State submitted file (either revised from CERR submittal or separate format); 3. VISTAS original 2002 base year (VISTA S version 3.1 base year file); or 4. EPA’s preliminary 2002 NEI. Table 1.2-2. Summary of State Data Submitta ls 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 responseDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 ta ble. A series of codes were a dded to this field to mark the source of each emissions value in the Base F and Base G inventories. Valu es 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 Ba se F. Virginia’s inventory required a two stage update. Virginia’s CERR submittal only containe d 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 subm ittal that weren’t in the original 2002 VISTAS base year inventory that should have PM or SO 2 

### emissions. For those records, MACTEC used anDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### emissions ratio to build records for emissions of these pollutants. Data for Virginia PM and SO 2 

### emissions were generated by de veloping SCC level ratios to NO x 

### from the VISTAS 2002 base year inventory (version 3.1) or from emission f actors and then calculati ng the emissions based on that ratio.

1.2.3 2002 Base G inventory updates After the Base F inventory was submitted and us ed 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 th e inventory were made globally across the entire VISTAS region. This section discusses the specif ic 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 questi ons 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 (Instit utional/Commercial Heating: Liquefied Petroleum Gas) the Alabam a noted that the Base F VISTAS inventory had values for NO x 

### , VOC and CO for the State, but no values for SO 2 

### , PM 10 

### or PM 2.5 

### .
MACTEC evaluated this information and found th at there were actually emissions for two counties in AL for that SCC that had either SO 2 

### and/or PM emissions. The data used to develop the 2002 Base F inventory for AL came from th e preliminary 2002 CERR submittals (see above) which should have included SO 2 

### and PM but did not except fo r 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 th e 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 SO 2 

### and PM. The revised file was used to update the Base F data for Base G.

2. AL noted that the Base F inve ntory included SCC 2401002000 (Solvent Utilization, Surface Coating, Architectural Coatings - Solvent-based, Total: All Solvent Types) and 2401003000 (Solve nt Utilization, Surface Coating,Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Architectural Coatings - Water-based, To tal: 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 sugge sted removal of the breakdown SCCs and use of the total SCC.

MACTEC deleted records for the breakdown SC Cs 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 a nd Other Electrical, all coating types 2430000000 504.29 Solvent Utilization, Rubber/Plasti cs, 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 pr ovided 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 Ba se 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 potentia l 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 fo r CO and PM and were likely zero:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 se t 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 ch anges were implemented.

South Carolina South Carolina had two issues concerning the Ba se 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, bu t not in the VISTAS 2002, 2009, or 2018 Base F inventory.
MACTEC investigated the additional SCCs f ound 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 in ventory 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 pe r 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 emissi ons file. The data in that file were used to update the Base F inventory emission values to t hose for Base G. In addition, Virginia providedDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### information on several source catego ries that required controls fo r future year projections since the sources were located in countie s/cities in northern Virginia a nd 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 cate gories so that they coul d be estimated correctly in future years. The controls added were fo r 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 inve ntory development was estimation of NH 3 

### emission estimates for livestock and fertilizers and paved road PM emissions. For the NH 3 

### emission estimates for livestock and fertilizer s we used version 3.6 of the CMU NH 3 

### 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 st atistics. Prior to inclusion of the CMU model estimates, MACTEC removed any a mmonia records for agricultural livestock or fertilizer emissions from the VISTAS 2002 initia l 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 em issions 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 estimate s and wildlife was dropped because VISTAS felt the activity data was too uncertain. Thus all emi ssions from these two categories were deleted in the Base G 2002 inventory.
For the paved road PM Base F emissions, we us ed 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 estima ting 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 ma de 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 gl obal changes made as part of the Base G inventory updates.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 a nd human perspiration NH 3 

### emissions). These changes were:

1. Removal of Stage II emissions from the area s ource inventory and inclusion in the mobile sector of the inventory,

2. Adjustment of fugitive dust PM 2.5 

### 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 th e 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 thei r CERR submittals and 2) because the non-road and on-road mobile estimates had differing activity f actor units and could not be easily combined. However for Base G, the VISTAS States all agree d, 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 sect ors. Thus all records related to Stage II refueling were removed from the area source component of the Base G inventory.

PM 2.5 

### 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
PM 2.5 

### / PM 10 

### ratio in several fugitive dust categories a nd 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 PM 2.5 

### emissions from construction, paved roads and unpaved road sources. PM 2.5 

### emissions in Base F were multiplied by 0.67, 0.6, and 0.67 for construction, paved roads and unpave d roads respectively to produce the values found in Base G. No changes were made to PM 10 

### , only to PM 2.5 

### . 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 a dd these emissions to the Base G area source inventory. In investigating options for a met hod of estimating emissions, MACTEC found that the U.S. EPA had prepared a national invent ory of emissions by St ate for portable fuel containers. Data on emissions from this sour ce prepared by U.S. EPA were presented in, “Estimating Emissions Associated with Portable Fu el Containers (PFCs), Dr aft Report, Office of Transportation and Air Quality, United States Environmenta l Protection Agency, Report # EPA420-D-06-003, February 2006”.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State-level emission estimates for 2005 derive d from Appendix Table B-2 of the PFCs report were used as the starting point for developi ng 2002 county-level emi ssions estimates. State emissions were derived from that table by using al l 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 se ctor. 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 refuelin g component from Appendix Table B-2 of the report were summed for each State and then allo cated to the county-level. The county-level allocation was based on the fuel usage info rmation obtained from th e 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 th e 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 refu eling. The spillage file contains information by SCC and horsepower indicating whet her 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 we re summed for those SCCs by county. The county level fuel use was then divided by the State total fuel use for the sa me 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 developm ent process, quality assuran ce steps were performed to ensure that no double counting of emissions occurred, and to ensu re 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 th ere were no missing sources.

3. Tier comparisons (by pollutant) were deve loped between the revised 2002 base year inventory and the previous (ver sion 3.1) base year inventory.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 Fi res SIWG representatives for review and comment. Changes based on these comments were implemented in the files.

6. Version numbering was used for all i nventory 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 invent ory, 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 th e VISTAS Fire SIWG included representatives from most State Divisions of Forestry (or equiva lent) as well as U.S. Forest Service and National Park Service personnel.
For Base G, similar QA steps to those outlined ab ove for Base F were undertaken. In addition, all final NIF files were checked using the EPA Form at 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 re visions 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 contract or. 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 init ial 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 estimat es and that the 2002 input data files would beDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 pr ovided with the CERR emissions estimates we used it as the starting point for revision of the 2002 Base Y ear 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 begi n compiling the appropria te input file data.
In those cases where States did not provide CE RR on-road mobile source input data files, our default approach was to maintain the data inpu t files and VMT estimates for the initial 2002 Base Year inventory prepared by Pechan.

1.3.1 Development of on-road mobile sour ce 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 pro cess 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 init ial 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 neces sary external files n eeded 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 th e 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 fo r other States in the VISTAS region.
KY – For Kentucky, the Inspection and Maintenance (I/M) records in the i nput 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 th ese input files based on input from the State. The modifications necessary to reflect the desires of the State led to comp lete replacement of the previous input files. Among the changes made were:

• The regrouping of counties (including th e movement of some counties from one county group to another and the creation of new input files for previously groupedDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### counties). There were originally 32 input f iles; after the change s 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 i nput files. In addition, revised VMT data were developed for each State.

Base G Revisions For the production of the VISTAS 2002 Base G i nventory, VISTAS states reviewed the Base F inputs, and provided corrections, updates and supplemental data.

For all states modeled, th e Base G updates include:
Adding Stage II refueling emissions cal culations 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 re gistration distributions.
TN - revised VMT and vehicle registrati on distributions for selected counties.

VA – revised winter RFG calcula tions 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 Op erator Kernel Emissions (SMOKE) model was used to develop the on-road mobile source emissions estimates for CO, NO X 

### , NH 3 

### , SO 2 

### , PM, andDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### VOC emissions. The MOBILE6 parameters, vehicl e fleet descriptions, and VMT estimates are combined with gridded, episode-specific temperatur e data to calculate the gridded, temporalized emission estimates. The MOBILE6 emissions fact ors 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 emi ssions 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 main tenance program in effect, type of oxygenated fuel program in effect, alternative vehicle mix pr ofiles, 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 variab ility in each month. The modeled weeks were selected from mid-m onth, 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 April16-22Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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, -1 620) kilometers with 168 rows by 177 columns and 12-km square grid cells. CMAQ model species: The CMAQ configuration was CB-IV w ith 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 follo wing five types of MCIP outputs: (1) Grid cross 2-d, (2) Grid cross 3-d, (3) Me t cross 2-d, (4) Met cross 3-d, and (5), Met dot 3-d.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The reconstructed emissions based on the repres entative week run were calculated by mapping each day of week (Mon, Tue, Wed, etc.) from th e modeled month to the same day of week generated in the representative week run. In the case of holiday s, these days were mapped to representative week Sundays. An example of th is mapping for the January episode is presented in Table 1.3-1 below. Note that although the em issions were generated for individual calendar years (2002, 2009 and 2018) the me teorology 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 deve loped. Second, emissions from sources not included in the NONR OAD 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 inventor y 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 inventor y are presented in a February 9, 2004 report

“ Development of the VISTAS Draft 2002 Mobi le Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc. Except as otherwise stated below, all aspects of the preparation met hodology documented in that repor t continue to apply to the revised NONROAD mo deling discussed in this section.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Revisions to the initial 2002 NONROAD emissions inventory we re implemented to ensure that the latest State and local data were considere d, as well as to more accu rately reflect gasoline sulfur contents for 2002 and correct other State-specific discrepanc ies. Those revisions comprise the Base F VISTAS non-road inventory. This sec tion 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 Ba se G inventories and the prev ious version employed for the initial 2002 base year inve ntory 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 inventor y. 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 invent ories that resulted from the Base F revisions served as the starting poin t for the Base G revisions.
For Base F, three VISTAS States provided de tailed data revisions for consideration in developing revised model i nputs. These States were:

1. North Carolina 2. Tennessee (including a separate su bmission for Davidson County), and 3. Virginia. The remaining seven VISTAS States indicated th at the initial 2002 VISTAS input files prepared by Pechan continued to reflect the most re cent 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Before presenting the specific implemented revisi ons, 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 Dr aft NONROAD2004 model, which was released by the EPA in May of 2004. This model is no lo nger available on EPA’s website. The initial 2002 base year inventory (prepared by Pech an) was based on the Draft NONROAD2002a version of the model (which is also no longe r available on EPA’s website). Key differences between the models are as follows:

• Draft NONROAD2004 included the effects of th e Tier 4 non-road engine and equipment standards (this did not impact the Base F 2002 i nventory estimates, but did affect Base F future year forecasts).

• Draft NONROAD2004 included the exhaust emission impacts of the large spark-ignition engine standards; the evaporativ e 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 PM 2.5 

### fraction for diesel equipment in Draft NONROAD2004 had been updated from 0.92 to 0.97.

• Draft NONROAD2004 included revisi ons to recreational marine activity, useful life, and emission rates.

To the extent that these revisions affect 2002 em issions estimates, they will be reflected as differentials between the initial and Base F 2002 VI STAS 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 re flected 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, th e EPA released another updated version of the NONROAD model, designate d as Final NONROAD2005 (which can be downloaded from: http://www.epa.gov/OMSW WW/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 NONROAD 2005 and Draft NONROAD2004 are as follows:

• Final NONROAD2005 reflects the latest basic emission rate and deterioration data.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • Final NONROAD2005 includes emission estimates for a range of evaporative emissions categories not included in Draft NONROAD 2004 (tank and hose permeation, hot soak, and running loss emissions).

• Final NONROAD2005 includes a revise d 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 convers ion factors for hydrocarbon emissions.

• Final NONROAD2005 includes the evapora tive 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 VI STAS NONROAD modeling process involves the consideration of over 200 unique sets of input data. To avoid crea ting new input files for each of these datasets, a conversion process was unde rtaken 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 th e following two line EPA-developed comment at the end of the i nput file header (thi s is a nonsubstantive change implemented solely for consistency wi th 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 deve loped by comparing substantively identical input files created using the

graphical user interfaces for both Draft NONROAD2004 and Final NONROAD2005. The di fferences between the input files indicated the specific revisions necessary to convert existing VISTAS input files into Final NONROAD2005 format.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • Revise the Draft NONROAD2004 (Base F) in put 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) inpu t 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 millio n 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 a nd 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-base d 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 ppmWsulfur was used for all 2002 VISTAS NONROAD modeling. Given the ability of Final NONROAD2005 to distinguish a separate sulfur content for marine equi pment 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 modifi ed (for marine equipment only).

• Replace the Draft NONROAD2004 (Base F) in put 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) in put files to include the following two command lines after the “EPS2 AMS” command in the RUNFILES packet:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 50 US COUNTIES FIPS : c:\non-road\data\allocate\fips.dat
RETROFIT :



### • Revise the Draft NONROAD2004 (Base F) inpu t 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. Fo r 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) in put 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) inpu t 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-ro ad input files develope d for use with Draft NONROAD2004 (Base F) were ex ecutable under the Final N ONROAD2005 model (Base G).
The only additional revisions implemented to develop a Final NONRO AD2005-based inventory (Base G) involved elimination of non-default equipment allocation files for North Carolina and West Virginia. Due to concerns about imprope r equipment allocation acr oss counties under the Draft NONROAD2004 model (used for Base F), as well as for earlier versions of the NONROAD model, North Carolina had produced alte rnative allocation data files indicating the number of employees in air tr ansportation by county, the number of wholesale es tablishments by county, and the number of employees in landsca ping services by county. For the same reason, West Virginia had produced alternative equipm ent allocation files indicating the number ofDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### employees in air transportation by county, the tonnage of underg round coal production by county, the number of golf courses and count ry clubs by county, the number of wholesale establishments by county, the number of employ ees in logging operations by county, the number of employees in landscaping services by count y, 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 ve hicle parks and campgrounds by county. These alternative equipment allocation files were us ed for all VISTAS inventory modeling conducted prior to the release of Fi nal NONROAD2005 (i.e., through Base F). However, both North Carolina and West Virginia determined that the de fault allocation file revisions associated with the release of Final NONROAD2005 we re 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 N ONROAD2005 (Base G) input files for North Carolina and West Virginia, so that the entire region under the Base G i nventory is now modeled using the default allocation f iles provided with NONROAD2005.

In addition to the alternativ e 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 ear lier model versions). The alternative data file implemen ted 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-A tlantic state, North Carolina requested that the southeastern re classification be con tinued for all NONROAD2005 modeling (Base G). To ensure that any other revi sions associated with the seasonal adjustment file released with NONROAD2005 we re not overlooked, the previ ously developed alternative seasonal adjustment file for North Carolina was scrapped and a new altern ative 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 VIST AS NONROAD2005-based (Base G) modeling.

The remainder of this section documents all chan ges 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 belo w, all values from that report continue to be used without change in th e latest VISTAS modeling.

Base F Revisions: For the initial 2002 base year inventory (devel oped by Pechan), all NONROAD modeling runs for VISTAS were performed utilizing a gasoline sulfur content of 339 ppmW and a diesel sulfurDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### content of 2,500 ppmW. Although th e EPA-recommended non-road dies el fuel sulfur content for 2002 is 2,283 ppmW, the 2,500 ppmW sulfur content us ed 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 Mode l 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 i nventory continued to assume a di esel fuel sulfur content of 2,500 ppmW across the VISTAS region.
However, 339 ppmW is not the EPA recomme nded 2002 gasoline sulfur content for either eastern conventional gasoline areas or Fede ral Reformulated Gasoline (RFG) areas. The recommended sulfur content for eastern conv entional 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 valu es 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 perfor med on a seasonal basis, and since gasoline sulfur content in RFG areas varies with th e RFG season, seasonally-spe cific 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 lim it 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 empl oyed in the NONROAD m odel, 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 ppmWDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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), a nd that the transition betw een summer and winter seasons is also not considered. Additionally, th e summer fuel control s eason 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 expect ed that this error is small rela tive 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 inve ntory preparation process are presented in Table 1.3-2. Due to more involve d 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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), Cl ayton (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) allocati on 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 -Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-2. Summary of Base F NONRO AD 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 effectivene ss for counties subject to St age 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., Chesap eake 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 convention al gasoline area and it is modeled as such.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 ch anges summarized in Table 1.3-3 above. This table is intended t o 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 them selves) result in emission estimate changes.
(2) The NONROAD model imposes an eight digit input file name li mit, so all input files for the revised 2002 base year inventor y follow a modified naming convention to allow each to be distingui shed from the input files for the initial 2002 base year inven tory. 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Base G Revisions: As described above, the primary modeling revi sion 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 we re other minor revisions implemented for 13 Georgia counties and somewhat more significant revisions implemented for Tennessee. In Georgia, Stage II refueling control was assume d for 13 counties that previous ly were modeled as having no refueling control under Base F. In addition, to accommodate th is Stage II change as well as forecast year changes in gasoline vapor pressu re, corresponding changes in the structure and sequence of Georgia NONROAD input files were ma de. With the exceptio n of the minor Stage II impacts, these structural and sequence cha nges have no impact on 2002 emission estimates, but allow for consistency between 2002 and forecas t year input file structure and sequence. In Tennessee, more significant changes were implem ented to gasoline vapor pressure assumptions, as well as similar minor changes in St age 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 cont rol efficiency value of 81 percent for the Base G inventory:
Cherokee, Clayton, Cobb, Coweta, DeKa lb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding, and Rockdale.
No Stage II control was assumed in th ese counties in pr ior inventories.
Tennessee regulators provided revi sed monthly values for gasoline vapor pressure. Based on the seasonal definitions employed in the NONROAD model, monthly va por pressures were averaged to estimate seasonal vapor pressures as follows:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 58 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 co nsists of Shelby County.



### As with the Base F revisions, the seasonal data are based on simple arithmetic averages and do not consider any monthly varia tion in activity (and fuel sales) , nor is the transition between summer and winter seasons considered. Additiona lly, a monthly average of the September 1-15 and September 16-30 data is cal culated prior to averaging th e September-November data to estimate a fall average vapor pressure, so that the month of September is we ighted identically to the months of October and November.
Tennessee regulators also indicate d that Stage II vapor recovery was not in effect in Shelby County, so the Base F NONROAD input files for th e county (which assu med Stage II was in place) were revised accordingly.
All Base G NONROAD modeling re visions are presented in Tabl e 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 createDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 Mobi le 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 ar e 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 alloca tion 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 alloca tion files for all equipment categories.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 ch anges summarized in Table 1.3-5 above. This table is intended t o 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 them selves) result in emission estimate changes.
(2) The NONROAD model imposes an eight digit input file name li mit, so all input files for the revised 2002 base year inventor y follow a modified naming convention to allow each to be di stinguished 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, th e 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1.3.2.2 Emissions from Commercial Marine Ve ssels, Locomotives, and Airplanes An initial 2002 base year emissions inventory for aircraft, locomotives, and commercial marine vessels (CMV) was prepared for VISTAS in ear ly 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 ba se 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 implemente d in the fall of 2004. Those revisions constitute the Base F inventory. These were followed by a s econd 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 ot herwise indicated, all re visions implemented for Base F were carried directly into the Base G revision pro cess 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 we re 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 provi ding CERR data were Alabama, Georgia, Mississippi, North Ca rolina, Tennessee (excluding Davidson, Hamilton, Knox, and Shelby Counties), Virginia, and West Virginia.
In many cases, the CERR data were only margina lly different than the initial 2002 base year inventory data, but there were several instances where signific ant updates were evident. The remaining three VISTAS States (Florida, Ke ntucky, 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. Flor ida did provide updated aircraft emissions data for one county (Miami-Dade) and th ese data were incorpor ated into the Base F 2002 inventory as described below.

Since several States recommended re taining the initial 2002 base year inventory data for Base F, the initial step toward revising the 2002 inventory cons isted of modifying the estimated aircraft PM emissions of the initial inve ntory. The overestimation of aircraft PM became evident shortlyDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### after the release of th e initial 2002 base year inventory, wh en 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 em ission sources. In addition, unexpected relationships across airports we re also observed, with emissi ons for Atlanta’s Hartsfield International being substantially less than thos e 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 St ates was based on the initial 2002 VISTAS inventory data, aircraft PM emissions for th e entire VISTAS regi on were recalculated.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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 VA 136 387 28 26 30 59 Military Marine (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 26,877Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Aircraft do emit PM while operating. However, offi cial EPA inventory procedures for aircraft generally do not include PM emi ssion factors and, therefore, aircra ft 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) estim ated PM emission rates for aircraft using estimated NO x 

### emissions and an unreported PM-to-NO x 

### ratio (i.e., PM = NO x 

### times a PM-to-NO x 

### ratio). According to the initial 2002 ba se year inventory documentation, this approach was applied only to commercial aircraft NO x 

### , but a review of that inventory indicates that the technique was also applied to military, ge neral aviation, and air taxi aircraft in many, but not all, instances. Although there is nothing inhere ntly incorrect with this approach, the accuracy and inconsistent applicati on of the assumed PM-to-NO x 

### ratio results in grossly overestimated aircraft PM.
Through examination of the initial 2002 base year aircraft inve ntory (prepared by E.H. Pechan and Associates, Inc.), it is apparent that the commercial aircraft PM-to-NO x 

### ratio used to generate PM emission estimates was appr oximately equal to 3.95 (i.e., PM = NO x 

### times 3.95). While the majority of observed commercial aircraft PM-to-NO x 

### 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-NO x 

### ratios range from 0 to 123.0, and average 3.43 as illust rated in Table 1.3-7

Table 1.3-7 PM-to-NO x 

### Ratios by Aircraft Type In Initial 2002 Base Year Inventory.

Aircraft Type Average PM-to-NO x Range of PM-to-NO x Average PM 2.5 / PM 10 Range of PM 2.5 / PM 10
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 emi ssions as SCC 2275000000 “all aircraft.”



### As indicated, the aggregate PM-to-NO x 

### ratio is similar in magnitude to the ratio for commercial aircraft. This results from the domin ant nature of commercial aircraft NO x 

### emissions relative to NO x 

### from other aircraft types. It is surmised that ratios that deviate from 3.95 are based on PM emission estimates generated by local planners, wh ich were retained without change in the PM estimation process (although a considerable numbe r of unexplained “zero PM ” records also existDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### in the initial 2002 base year inve ntory dataset). Regardless, based on previous statistical analyses performed in support of aircraft emissions inve ntory development outside the VISTAS region, a PM-to-NO x 

### ratio of 3.95 is too large by over an order of magnitude.
In analyses performed for the Tucs on, Arizona planning area, PM-to-NO x 

### ratios for aircraft over a standard aircraft landing and takeoff (LTO) cycl e are shown in Table 1.3-8. Data for this table is taken from “Emissions Inventories for th e Tucson Air Planning Ar ea, Volume I., Study Description and Results,” prepared for the Pi ma 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 include d in this report as Appendix E.
Table 1.3-8. Tucson, AZ PM-to-NO x 

### Ratios by Aircraft Type.

Aircraft Type PM-to-NO x Commercial Aircraft 0.26

Military Aircraft 0.88
Air Taxi Aircraft 0.50
General Aviation Aircraft 1.90
Note: The PM and NO x 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 em ission 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-NO x 

### 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-sp ecific analysis for all airports in the VISTAS region was beyond the scope of this work. While local PM-to-NO x 

### 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 associat ed with the 3.95 commercial aircra ft ratio used for the initial 2002 base year inventory.
It should be recognized that wh ile the Tucson area is far removed from the VISTAS region, the data analyzed to generate the PM-to-NO x 

### 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 approa ch 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).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### employed for inventory purposes th roughout the United States (as encoded in models such as the Federal Aviation Administration’s Emissions Da ta Management Systems [EDMS]). With the exception of aircraft operating conditions, ther e 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-NO x 

### ratios in the Base F inventory, all aircraft PM records were removed from the initial 2002 base year inventory (prepared by P echan). 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 planne rs may be no better than that used to generate the presented PM-to-NO x 

### ratio data, so the consistent app lication 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 NO x 

### and PM records in the initial 2002 base year inventory. Whereas there were 1,531 NO x 

### records in the NIF emission data sets for this source category, there were only 1,212 PM records. The imbalance was distri buted between three States, South Carolina, Tennessee, and Virginia as follows:
Table 1.3-9 Non-Corresponding Aircraft Emissions Records

Aircraft NO x 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 NO x 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 si nce there was no corresponding NO x 

### record with which to estimate revised PM emissions. It is unclear how this orph aned record originated, but clearly there can be no air taxi PM emissions without other combusti on-related emissions. Thus, the removal of theDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### PM 10 

### and PM 2.5 

### 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 NO x 

### records, 269 were records for whic h the reported emission rate was zero. Therefore, even though associated PM reco rds were missing, the overall inventory was not affected. However, the 51 missing records for which NO x 

### emissions were non-zero, did impact PM estimates for the overall inventory.
Replacement PM 10 

### records were calculated for all aircraft NO x 

### records using the PM-to-NO x 

### ratios presented above. Aircraft type-specific ratios were utilized in all cases, except for two counties where aircraft emissions were report ed under the generic aircraft SCC 2275000000. For these counties (Palm Beach County, Florida a nd Davidson County, Tenne ssee), the commercial aircraft PM-to-NO x 

### ratio was applied since both contain commercial airports (Palm Beach International and Nashvi lle International).
Replacement aircraft PM 2.5 

### records were also developed. Th e initial 2002 base year inventory assumed that aircraft PM 2.5 

### was 69 percent of aircraft PM 10 

### . 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 (PM 1.0 

### ), so that typical inte rnal combustion engine
PM 2.5 

### fractions approach 100 percent. For ex ample, the EPA NONROAD model assumes 92 percent for gasoline engine pa rticulate and 97 percen t for diesel engine particulate. Based on recent correspondence from the EPA, it appears th at the agency is preparing to recommend a
PM 2.5 

### fraction of 98 percent for aircraft. (Augus t 12, 2004 e-mail correspondence from U.S. EPA to Gregory Stella of Alpine Geophys ics.) This is substant ially 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 PM 2.5 

### 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 extr acted from the inventory for area s not supplying CERR data for the Base F update would be accurate. Therefore, in no case is the aggregated St ate data reported for the Base F inventory identical to that of the in itial 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 PM 10 

### and PM 2.5 

### 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 NO x 

### ratios. Table 1.3-11 presents a summary of the netDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### impacts of these changes, where an over 90 percen t 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 NO x 

### inventories for both include a large share of military aircraft NO x 

### 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 airc raft PM offsets a portion of the reduction in commercial aircraft PM. In Virgin ia, zero (or near zero) PM milita ry operations were responsible for about 35 percent of total aircraft NO x 

### , while the corresponding frac tion in South Carolina was almost 70 percent. As indicated, aggregate aircraft, locomotive, and commercial marine vessel PM is 70-75 percent lower in th e updated 2002 base year inventory.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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 VA 136 387 28 26 30 59 Military Marine (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 26,877Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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% VA 0% 0% 0% 0% 0% 0% Military Marine (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 al l 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 provi ded for the Base F 2002 base year inventory (specifically those for Tennessee, Virginia, a nd West Virginia) included both annual and daily emissions data. Only the annual data were used. Daily values were removed.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Several important observations resu lted from this analysis. First, it was clear that all of the CERR data continued to rely on the inaccurate ai rcraft PM estimation approach employed for the initial 2002 base year inventory. Therefore, an id entical aircraft PM replacement procedure as described above for updating the initial 2002 ba se 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 inve ntory due to PM replacement procedures.

As was the case with the initial VISTAS 2002 ba se year inventory, ther e were a substantial number of aircraft NO x 

### 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 inve ntory data, reflecting data for all or parts of seven States, consisted of 13,656 records, of which 1,211 were aircraft NO x 

### records. However, the number of corresponding aircraft PM records was 662 (662 PM 10 

### records and 662 PM 2.5 

### records). This imbalance was distributed as follows:

Table 1.3-12 CERR Aircraft NO x 

### 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 th at virtually the entire imbalance is associated with the Virginia CERR submission, with minor imbalances in Georgia and Tennessee. Of the 549 unmatched NO x 

### records, 461 were records for which the repo rted emission rate was zero. Therefore, even though the associated PM records were missi ng, the overall inventory was not affected. However, the 88 missing records for which NO x 

### emissions were non-zero do impact PM emission estimates for the overall inventory.
Replacement aircraft PM records (both PM 10 

### and PM 2.5 

### ) were generated for the CERR dataset using procedures identical to those descri bed above for the upda ted initial 2002 base year inventory.
Further analysis revealed that the CERR da ta for Virginia incl uded only VOC, CO, and NO x 

### emissions for all aircraft, locomotives, a nd non-recreational marine vessels. Since SO 2 

### , PM 10 

### , and PM 2.5 

### records are included in the 2002 VISTAS inventory, an estimation method was developed for these emission species and appl ied to the Virginia CERR data. For PM, theDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### developed methodology was only employed for locomo tive and marine vessel data since aircraft PM was estimated using the PM-to-NO x 

### ratio methodology described above.
Consideration was given to si mply adding the Virginia SO 2 

### and non-aircraft PM records from the initial 2002 VISTAS inventory datase t, 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. Th erefore, an estimation methodology was developed using Virginia source-specific SO 2 

### /CO, PM 10 

### /CO, and PM 2.5 

### /PM 10 

### ratios from the initial 2002 base year VISTAS inventory. The calculated ra tios were then applied to the source-specific CERR CO emission estima tes to derive associated source-specific SO 2 

### , PM 10 

### , and PM 2.5 

### emissions for the Base F inventory.
Initially, the development of the emissions ratio s from the initial 2002 base year inventory was performed at the State (i.e., Vi rginia), county, and SCC level of detail. However, it readily became clear that there were s ubstantial inconsistencies in ra tios for identical SCCs across counties. For example, in one county, the SO 2 

### /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 equipmen t 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 emi ssion ratios were developed for the State as a whole. Through this approach county-to-county vari ation in emission ratios is eliminated, but the underlying variation in CO emissi ons does continue to influence the resulting aggregate emission estimates. The applied emission ratios are as follows:

Table 1.3-13 Calculated Em ission Ratios for VA.

Source SCC SO 2 /CO PM 10 /CO PM 2.5 /CO PM 2.5 /PM 10 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-NO x 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 0.90Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### It is important to recognize that the inconsistenc y of emissions ratios ac ross Virginia counties for sources of virtually identical design, which utilize a regiona l rather than local fueling infrastructure, has potential im plications for other VISTAS States. There is no immediately obvious reason to believe that such inconsis tencies 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 airs trip 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 inventorie s are in terms of prim ary particulate. It is also perhaps worth noting that a series of aircraft refueling r ecords (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 additiona l VISTAS aircraft refueling emissions are reported under SCC 2501080XXX, then it may be desirabl e 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 a ppropriate records from the initial 2002 base year inventory (with revisions for aircraft PM to NO x 

### ratios). Specifically, records applicable to the States of Florida, Kentucky, South Carolina, and the Te nnessee 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 indi cated 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-Da de County were obtained from Florida planners and used to overwrite the erroneous estimates. (Aircraft emi ssion estimates were provided in an August 10, 2004 e-mail transmittal from Bruce Coward of Miam i-Dade County to Martin Costello of the Florida Department of Environmental Protection.)
Table 1.3-14 presents a summary of the resul ting Base F VISTAS 2002 base year inventory estimates for aircraft, locomotives, and non-recr eational marine vessels. Table 1.3-15 provides a comparison of the Base F 2002 base year inventor y estimates to those of the initial 2002 base year inventory. As indicated, total emissions for VOC, CO, NO x 

### , and SO 2 

### 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 correcti on of Atlanta Hartsfield International Airport emissions, which were significantly underestimated in the initial 2002 base year inventory. TheDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### reduction in Florida aircraft emi ssions 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 es timated annual aircraft NO x 

### emissions of 200 tons or greater (as identifie d at the conclusion of the Base F revisions). 3


### The table entries are sorted in order of decreasing NO x 

### and once again, the dramatic reduction in PM emissions is evident. However, in additi on, the appropriate reversal of the relationship between Atlanta’s Hartsfield and Miami Intern ational Airport is also depicted. As a rough method of quality assurance, Table 1.3-15 also includes a gross estimate of expected airport NO x 

### emissions using detailed NO x 

### estimates developed for Tucs on International Airport in conjunction with the ratio of local to Tucson LTOs. (The Tucson NO x 

### estimates are revised to reflect a standard LTO cycle rather than the Tu cson-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 deve loped VISTAS estimates, and it is clear that the range of estimated-to-expected NO x 

### emissions has been substantia lly 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 i nventory, the range of variation is tightened on both ends, from about 0.5 to 1.75 for the Base F 2002 base year inve ntory. In effect, all es timates are now within a factor of two of the expected estimates, which is quite reasonable given likely variation in local and standard LTO cycles a nd variations in aircraft fleet mix across airports.
It is perhaps important to note that some shif ting in county emissions assignments is evident between the initial and Base F 2002 base year airc raft inventories. For example, for the initial 2002 base year inventory, Atlanta Hartsfield es timates were assigned to Fulton County (FIP 13121), while they are assigned to Clayton Count y (FIP 13063) for the Base F 2002 base year inventory. Similarly, Dulles Intern ational Airport emissions were assigned solely to Fairfax County, Virginia (FIP 51059) in the initial 2002 base year inve ntory, but are split between Fairfax and Loudoun County (FIP 51107) for Base F. Such shifts reflect local planner decision-making and are not an artifac t 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 ai rcraft operations generating at least 200 tons of NO x . These revisions are discussed below, including the addition of an appropriately modified version of the aircraft emissions table.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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 VA 110 313 25 23 27 48 Military Marine (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 24,908Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

Source State CO NO x PM 10 PM 2.5 SO 2 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% VA -19% -19% -12% -12% -12% -19% Military Marine (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%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-16. Base F Comparison of Aircraft Emissions (Airports with Aircraft NO x 

### > 200 tons per year)

Airport FIP CO NO x PM 10 PM 2.5 SO 2 VOC Approx. LTOs Predicted NO x 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 13 2 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 13 2 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 Ai rport emissions are split between two Virginia counties. Predicted NO x is based on the ratio of airport LTOs to test airport (Tucson International Airport) LTOs and NO x . This is not a rigorous comparison, but rather an approximate indicator of expected magnitude.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Base G Revisions: Further revisions to the 2002 base year emission s 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) serv ed as the starting point for the 2006 revisions. Thus, unless otherwise indicated below, all documen ted Base F revisions con tinue to apply to the Base G-revised 2002 base year inventory.
As part of the Base G review and update pro cess, Virginia regulators provided 443 updated emission records for aircraft. These records re flected revisions to ai rcraft VOC, CO, and NO x 

### , and in a few cases SO 2 

### , emissions records that were al ready in the Base F VISTAS 2002 inventory (as opposed to the addition of previous ly unreported data). Th e specific revisions broke down as follows:

Table 1.3-17 Base G VA Aircraft Records Updates

Aircraft Type VOC CO NO x SO 2 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 record s 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 SO 2 

### , PM 10 

### , and PM 2.5 

### emissions in Virginia are estimated on the basis of CO (in the case of SO 2 

### ) and NO x 

### emissions (in the cases of PM 10 

### and PM 2.5 

### ). Therefore, since Virginia regulators did not provide updated SO 2 

### emissions for all updated CO emissions records, or updated PM 10 

### or PM 2.5 

### emissions for all updated NO x 

### emissions records, it was necessary to re-estimate aircraft SO 2 

### , PM 10 

### , and PM 2.5 

### emissions in all cases where updated CO or NO x 

### emissions were provided for Base G (and explicit SO 2 

### and/or PM 10 

### and PM 2.5 

### emissions were not).
The procedure used to estimate the SO 2 

### , PM 10 

### , and PM 2.5 

### emissions revisions was identical to that described above for the Base F in ventory revisions, except that revised SO 2 

### -to-CO emissions ratios were calculated for commercial airc raft, where 12 pairs of revised CO and SO 2 

### emissions estimates were available. Although a single pair of revised CO and SO 2 

### emissions records was available for military aircraft, this was deemed an insufficient sample with which to replace the military aircraft SO 2 

### -to-CO emissions ratios previously calc ulated in Base F. However, it is worth noting that the SO 2 

### -to-CO emissions ratio for the revised military aircraft emissions pairDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### was within 16 percent of the previously calculated ratio, so any error associ ated 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 SO 2 /CO (fall 2004) SO 2 /CO (spring 2006) SO 2 /CO (used in 2006) PM 10 /NO x PM 2.5 /PM 10 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 SO 2 

### -to-CO emissions ratios to the 130 revi sed aircraft CO records, for which no corresponding SO 2 

### emission revisions were provided, resulted in an additional 130 aircraft SO 2 

### emission records updates for Virgin ia. Similarly, application of the PM 10 

### -to-NO x 

### emissions ratios to the 140 revised aircraft NO x 

### records for which no corresponding PM 10 

### emission revisions were provided, resulted in an additional 140 aircraft PM 10 

### emission records updates for Virginia. Application of the PM 2.5 

### -to-PM 10 

### emissions ratios to the 140 revised aircraft PM 10 

### records resulted in an additional 140 aircraft PM 2.5 

### 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 PM 10 

### and 89 records for PM 2.5 

### ), 42 additional emissions records for locomotives (14 records for VOC, 14 records for CO, and 14 records for NO x 

### ), and 179 additional emission records for airc raft (30 records for VOC, 30 records for CO, 30 records for NO x 

### , 29 records for SO 2 

### , 30 records for PM 10 

### , and 30 records for PM 2.5 

### ). After review, it was determined that the 178 update d PM emission records for aircraft actually reflected the original (overestimated) aircraft PM data that was repla ced universally throughout the VISTAS region for Base F. Implementing thes e 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 locomotiv es were determined to correspond exactly to existing SO 2 

### , PM 10 

### , and PM 2.5 

### 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 NO x 

### , 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 em issions records in c onjunction with Alabama regulators, it was determined that 17 of the records (commercial aircraft records in Dale,Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 m ilitary aircraft activity in 20 counties and were specifically comp rised of 27 records each for VOC, CO, NO x 

### , SO 2 

### , PM 10 

### , and PM 2.5 

### . There were no further i ssues with the VOC, CO, NO x 

### , and SO 2 

### records and these were added to the Base G 2002 VISTAS inventory without change. It was, however, apparent that the PM 10 

### and PM 2.5 

### 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 PM 10 

### and PM 2.5 

### records provided by Alabama regulators were replaced with revised emission estimates developed on the basis of the PM 10 

### -to-NO x 

### and PM 2.5 

### -to-PM 10 

### ratios documented under the Base F revisions above. So although 27 aircraft PM 10 

### records and 27 aircraft PM 2.5 

### records were added to the 2002 Alabama inventory, they reflected different em issions 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 Co unty, to correct previously underestimated aircraft emissions associated with the Cincinna ti/Northern Kentucky Inte rnational Airport. VOC, CO, and NO x 

### emissions data were provided for military, commercial, general aviation, and air taxi aircraft. No associated updates for SO 2 

### , PM 10 

### , or PM 2.5 

### emissions were provided. Corresponding PM 10 

### emission estimates were developed by applying the PM 10 

### -to-NO x 

### ratios presented in Table 1.3-17 above to the updated NO x 

### emission estimates. PM 2.5 

### emission estimates were developed by applying the PM 2.5 

### -to-PM 10 

### ratios from that same table to the estimated PM 10 

### emissions. SO 2 

### emission estimates were developed by applying the SO 2 

### -to-PM 10 

### ratios developed from the older data (i.e., the da ta being replaced) for Boone County aircraft to the updated PM 10 

### emissions. Thus, a total of 24 invent ory records for Kentucky were updated (VOC, CO, NO x 

### , SO 2 

### , PM 10 

### , and PM 2.5 

### 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 add itional emission records (all in Alabama) were added to the 2002 VISTAS inventory. The total nu mber 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 resul ting Base G VISTAS 2002 base year inventory estimates for aircraft, locomotives, and non-recr eational marine vessels. Table 1.3-20 provides a comparison of the Base G 2002 base year inventor y estimates to those of the Base F 2002 baseDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### year inventory. As indicated, total emissions for VOC, CO, NO x 

### , and SO 2 

### 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 comparis on of emission estimates from the Base F and Base G 2002 base year inventories for all 17 VI STAS region airports with estimated annual aircraft NO x 

### emissions of 200 tons or greater. As comp ared to Table 1.3-16, the table reflects the Base G addition of the Cincinnati/Northern Kent ucky International Airport. Aircraft emission estimates for the other 16 airports ar e unchanged from their Base F values.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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 VA 110 313 25 23 27 48 Military Marine (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 25,401Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-20. Change in 2002 Emissions, Base G Inventory Relative to Base F Inventory

Source State CO NO x PM 10 PM 2.5 SO 2 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% VA 0% 0% 0% 0% 0% 0% Military Marine (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%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 1.3-21. Base G Comparison of Aircraft Emissions (Airports with Aircraft NO x 

### > 200 tons per year)

Airport FIP CO NO x PM 10 PM 2.5 SO 2 VOC Approx. LTOs Predicted NO x 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 13 2 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 13 2 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 Ai rport emissions are split between two Virginia counties. Predicted NO x is based on the ratio of airport LTOs to test airport (Tucson International Airport) LTOs and NO x . This is not a rigorous comparison, but rather an approximate indicator of expected magnitude.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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) a nd temporal resolution as estimates for the VISTAS region.
The requested estimates were produced by extracti ng a complete set of c ounty-level input data applicable to each of the three states from th e latest version of th e EPA’s NMIM (National Mobile Inventory Model) model. This included appropriate consideration of all non-default NMIM input files generated by the Midwest Regional Planni ng Organization (MRPO), as described below. These input data were then asse mbled into appropriate i nput files for the Final NONROAD2005 model and emission estimates we re 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 deve loped for each county in Illinois, Indiana, and Ohio by extracting data from the following NM IM database files (using the NMIM MySQL query browser):
county, countrynrfile, countyyear, countyyearmonth, countyyearmonthhour, gasoline, diesel, and natural gas

The database files:
countrynrfile, countyyear, c ountyyearmonth, and gasoline
were non-default database files provided to VI STAS by the MRPO, and are intended to reflect the latest planning data bei ng used by MRPO modelers.
From these files, monthly data for gasoline va por pressure, gasoline oxygen content, gasoline sulfur content, diesel sulfur content for la nd-based equipment, diesel sulfur content for marine-based equipment, natural gas sulfur cont ent, minimum daily temperature, maximum daily temperature, and average daily temperature were developed. In addition, th e altitude and Stage II refueling control status of each county, as well as the identity of the associated equipment population, activity, growth, alloca tion, and seasonal distribution f iles, was determined. These data were then assembled into Final NONRO AD2005 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 NovemberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Unlike the VISTAS Base G approach, this appr oach results in the use of the following non-default data files during the Final NONROAD 2005 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 treatme nt of ambient temperature data. Because NMIM offers a unique temperature profile for ev ery U.S. county -- developed by aggregating temperature data from included and surrounding weat her stations on the basis of their distances from the county population centroid -- it is not possible to explicitly group counties with otherwise identical i nput streams. Ungrouped however, th ere would be 1,128 distinct input streams to be processed (102 Illinois counties pl us 92 Indiana counties plus 88 Ohio counties at four seasons each), or over five times th e 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 inputs 4


### are within ± 2 oF of the corres ponding group average. This criteri on is quite stringent in that it results in less tolerant grouping than that employed for VISTAS modeling, which uses temperature data from the nearest meteorologica l 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### data for each county. Under this approach, th e actual deviation for grouped counties is much less that ± 2 oF for the overwhelming major ity of the 12 grouped temperature inputs.
In addition to the required temperature consis tency, 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 count y groups. Thus, 31 iterations of NONROAD2002 were required per season, as compared to the 53 iterations per s eason required for the VISTAS region.
It should be noted that a pot ential quality assurance issue was noted in assembling the NONROAD2005 input data for a numb er of Indiana counties. Specifically, the gasoline vapor pressure for most Indiana countie s reflects a value of 9.0 psi in all spring, summer, fall, and winter months. This is likely to indicate a problem with the accu racy 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 developm ent process, quality assuran ce steps were performed to ensure that no double counting of emissions occurred, and to ensu re 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 th ere were no missing sources.

3. Tier comparisons (by pollutant) were deve loped 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 i nventory 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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## 2.0 Projection Inventory Development

2.1 Point Sources
We used different approaches for differen t sectors of the point source inventory:

• For the EGUs, VISTAS relied primar ily on the Integrated Planning Model ® 

### (IPM ® 

### ) to project future generation as well as to calcu late 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 inve ntories 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 propos ed 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 fina l methods for performing the em issions projecti ons. Next, we describe the development of the final set of IP M 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 th at units accounted for in IPM were not doublecounted in the non-EGU inventor y. Fifth, we describe the QA/Q C checks that were made to ensure that the IPM results were properly inco rporated into the VIST AS 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 th at 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 i nventory development process, VI STAS considered three options for developing the VISTAS 2009 and 2018 pr ojection 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 input s from stakeholders; these IPM runs wereDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 (M RPO). These runs incorporated VISTAS specific unit and regulation modified parame ters, 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 S outhern Company specifically for their units. Southern Company is a super-regional company which owns EGUs in Alabama, Florida, Ge orgia, and Mississippi and participates in VISTAS as an industry st akeholder. Southern Company used their energy budget forecast to project net ge neration and heat input for ever y existing and future Southern Company EGU for the years 2009 and 2018. Furthe r documentation of how Southern Company generated the 2009/2018 inventory fo r their units can be found in Developing Southern Company Emissions and Flue Gas Characteristics fo r VISTAS Regional Haze Modeling (April 2005, presented at 14 th 

### 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 ru ns (Option 3) to re present the 2009 and 2018 EGU forecasts of emissions for the OTB and OT W cases. During the call, Alabama and Georgia specified that they did not wish to use Sout hern Company provided emissions forecasts of 2009 and 2018 to represent the sources in their States. Missi ssippi decided to u tilize the Southern Company projections to represent activity at Southern Company f acilities in Mississippi. After the call, Florida decided agains t using Southern Company provi ded 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 fo r both the Base F and Base G projections.
The Option 3 IPM modeling resulted from a jo int agreement by VISTAS and MRPO to work together to develop future year utility emi ssions 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} Grow th Modeling Method Task 2 Evaluation , February 11,Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2004). Although IPM results were available from EPA’s modeling to su pport 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 Co mpany projections in 2009 were roughly comparable with IPM. For 2018, Southe rn 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 Intern ational, Inc., to run IPM to provide utility forecasts for 2009 and 2018 under two future scenar ios – 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 w ith the proposed CAIR rule superimposed. The run results were parsed at th e unit level for the 2009 and 2018 run years. Also in August 2004, MRPO contracted with E.H. Pechan to post-pr ocess the IPM outputs gene rated by ICF to provide model-ready emission files. The IPM output f iles were delivered by ICF to VISTAS in November ( Future Year Electricity Generating Sect or Emission Inventory Development Using the Integrated Planning Model (IPM ® 

### ) in Support of Fine Par ticulate 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 Methodol ogy 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 anot her 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 comme nts. Several conference calls were conducted in the spring of 2005 to discuss and provide co mments on IPM assumptions related to six main topics: power system operation, generating res ources, emission control technologies, set-up parameters and rule, financial assumptions, a nd fuel assumptions. Based on these discussions, VISTAS sponsored a new set of IPM runs to re flect the final CAIR requirements as well as certain changes to IPM assumptions that were ag reed 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 a ssumptions were made by the RPOs, and ICF performed the following four runs using IPM dur ing the summer of 2005 (t hese runs are referred to as the VISTAS/CENRAP Phase II analysis):Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 suppl y 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. Th e changes that were implemented in the above four runs are summarized below:

• Unadjusted AEO 2005 electricity demand projec tions were incorpor ated in the above four runs.

• The gas supply curves were adjusted fo r AEO 2005 reference case price and volume relationships. The EPA 2.1.9 gas supply curves were scaled such th at IPM will solve for AEO 2005 gas prices when the power sector ga s 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 solv ing 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 perf ormed 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 EI A AEO 2005 coal supply and coal demand region configurations.

• The cost and performance of new units we re 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 a nd nuclear units were incorporated in the above runs.

• The extensive NEEDS comments provide d by VISTAS, MRPO, CENRAP and MANEVU were incorporated into the VISTAS Phase I NEEDS.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • MANE-VU’s comments in regards to the st ate regulations in the northeast were incorporated.

• Renewable Portfolio Standards (RPS) in the northeast was modeled based on the Regional Greenhouse Gas Initiativ e 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 Illin ois power, Mirant and First Energy NSR settlements were incorpor ated in the above runs.

For the VISTAS/CENRAP Phase II se t 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 s econd file contains just the fo ssil-fuel burning units (e.g., emissions from biomass and landfill gas are omit ted). 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 fu els accounted for only 0.13 percent of the NOx emissions and 0.04 percent of the SO 2 

### emissions in the 2009 IPM runs.
S/L agencies reviewed the results of the VIST AS/CENRAP Phase II set of IPM runs, which were incorporated into the VISTAS Base F inventory. S/L agen cies primarily reviewed and commented on the IPM results with respect to IPM decisions on NO x 

### post-combustion controls and SO 2 

### scrubbers. S/L agencies provided the late st information on when and where new SO 2 

### and NO x 

### 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 IP M 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 instal l 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 repres ent emissions at Southern Comp any 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 ar e 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 mode ling runs documented in Documentation Supplement for EPA Modeling Applications (V.2.1.6) Using the IPM , EPA 430/R-03-007, July 2003.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### IPM provides “forecasts of least-cost capacity expansion, el ectricity dispatch, and emission control strategies for meeting energy demand and environmental, transmission, dispatch, and reliability constraints.” The underlying databa se 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 exis ting 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 stake holders provided changes for:

• NO x 

### post-combustion cont rol on existing units

• SO 2 

### scrubbers on existing units

• SO 2 

### emission limitations

• PM controls on existing units

• Summer net dependable capacity

• Heat rate for existing units

• SO 2 

### and NO x 

### control plans based on State ru les 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 IP M model output file and transform it into air quality model input files. ICF via VISTAS/MRPO provides an initial spre adsheet file containing unit-level records of both
(1) “existing” units and
(2) committed or new generic aggregates.

All records have unit an d fuel type data; exis ting, retrofit (for SO 2 

### and NO x 

### ), and separate NO x 

### control information; annual SO 2 

### and NO x 

### emissions and heat input; summer season (MaySeptember) NO x 

### and heat input; July day NO x 

### and heat input; coal heat input by coal type; nameplate capacity megawatt (MW), and State FIPS code. Existing units al so have county FIPS code, a unique plant identifier (ORISPL) and unit ID (also called boiler ID) (BLRID); generic units do not have these data. Th e processing includes estimating va rious types of emissions and adding in control efficiencies, stack paramete rs, latitude-longitude co ordinates, and State identifiers (plant ID, point ID, st ack ID, process ID). Additionally, the generic units are sited in a county and given appropriate IDs. This proce ssing is described in more detail below.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The data are prepared by transforming the generi c 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 cap acity, are provided a dummy OR IS 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 atta inment/nonattainment status. Within a State, plants (in county then ORIS plant code order) in attain ment counties are used first as sister sites to generic units, followed by plants in PM nonattain ment counties, followed by plants in 8-hour ozone nonattainment counties. Note that no LADCO or VISTAS Stat es 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 assi gned, first using the EPA-provided data files, secondly using the September 17, 2004 Pechan in-house la titude-longitude file, and la stly using county centroids. These data were only used when the data we re 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 PM 10 

### and PM2.5, PM condensable, and NH 3 

### emissions for all units. Thus, ash a nd 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 obtai ned from the 2002 EGU NEI that were based on 2002 EIA-767 control data and the PM Calculat or program (a default of 99.2 percent is used for coal units if necessary); fuel use was back calculated from th e 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 factor s. Note that this update d file is not the one used for estimating emissions for previous EP A post-processed IPM files. Emissions for 28 temporal-pollutant combinations were estimate d since there are seven pollutants (VOC, CO, primary PM 10 

### and PM 2.5 

### , NH 3 

### , SO 2 

### and NO x 

### ) and four temporal periods (annual, summer season, winter season, July day).
The next step was to match the IPM unit IDs wi th the identifiers in VISTAS 2002 inventory. A crosswalk file was used to obtain FIPS State an d 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Pechan provided the post-processe d files in NIF 3.0 format. Two sets of tables were developed : “NIF files” for IPM units that have a crosswalk match and ar e 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 crossw alk match as well as generic units).
For Base F and Base G projections , VISTAS reviewed the PM and NH 3 

### emissions from EGUs as provided by Pechan and identified significan tly higher emissions in 2009/2018 than in 2002. VISTAS determined that Pechan used a set of PM and NH 3 

### emission factors that are “the most recent EPA approved uncontrolled emission fact ors” 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 doma in. 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, VIST AS identified an inconsistent use of SCCs for determining emission fact ors between the base and future years.

VISTAS resolution of the PM and NH 3 

### 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 NH 3 

### ) only. For PM emissions, the cond ensable component of emissions was calculated and added to the resulting PM pr imary 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. Alpi ne Geophysics updated the SCCs in the future year inventor y to assign the same base year SCC. Using the same methods as described for the 2002 revisions, those non-IPM ge nerated pollutants were estimated using IPM predicted fuel characteristics a nd base year 2002 SCC assignments.

2.1.1.4 Eliminating Double Counting of EGU Units The following procedures were used to avoi d double counting of EGU emissions in the 2009/2018 point source inventory. The 2002 VISTAS poi nt source emission inventory contains both EGUs and non-EGUs. Since this file cont ains both EGUs and non-EGU point sources, and EGU emissions are projected using the IPM, it wa s necessary to split the 2002 point source file into two components. The first component cont ains those emission units accounted for in the IPM forecasts. The second component contains all ot her 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 sourceDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 matc hes 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, Stat e Point ID). When there was a match between the IPM ORISPL/BLRID and the VISTAS emissi on unit ID, the unit was assigned to the EGU inventory; all other emission units we re assigned to the non-EGU inventory.

If an emission unit was contained in the NIF f iles created by Pechan fr om the IPM output, the corresponding unit was removed from the in itial 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 Ba se 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 a nd non-EGU inventories:

• We reviewed the IPM parsed files {VIS TASII_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 thatunits accounted for in IPM were not doublecounted in the non-EGU invent ory. As a result of this comparison, we made a few adjustments in the cross-reference table to a dd 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 s ource inventory to verify whether there was any double counting of EGU emissions. In two in stances, 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 th e EGU component of the VISTAS revised 2009/2018 EGU inventory:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1. Provided parsed files (i.e., Excel spreadsheets that provide un it-level results derived from the model plant projections obtained by the IP M) to the VISTAS EGU SIWG for review and comment.

2. Provided facility level emission summar ies 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 th ese 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 ru ns (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 subtrac tion future emission cont rols based on the best available data from state rules, enforcemen t 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 c ontrols 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 projec tions 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 c ontrols assigned by IPM to reflect their best estimates of emission controls. The changes spec ified by the S/L agencies are summarized in Table 2.1-1. These changes involve d either 1) adding selective catalytic reduction (SCR) or scrubber controls to units wher e IPM did not predict SCR or sc rubber 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 SO 2 

### scrubber controls. We used a cont rol efficiency of 90 percent when adding or removing NO x 

### SCR controls at coal-fired plants , 80 percent when adding or removingDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### NO x 

### SCR controls at gas-fi red plants, and 35 percent when adding or removing NO x 

### SNCR controls.
In addition to the changes to th e 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 informati on and/or comment on changes in stack parameters from the 2002 inventory for 2009/2018 inventory. Changes to st ack parameters were also made in cases where new controls are scheduled to be installed. In cases wher e an emission unit projected to have a SO 2 

### 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 ar e 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 th e stack exit temperature to 169 degrees F (this is the virtual temperature derived from a wet temp erature 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 includ e the adjustments to the IPM results specified by the S/L agencies in the previous section.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.99Table 2.1-1 Adjustments to IPM Control Determinations Specified by S/L Agenciesfor the Base G 2009/2018 EGU Inventories.NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateAL James H. MillerORISID=60021 & 2 SCRduringozoneseasonSCRprobableyear rounddue toCAIRSCRduringozoneseasonSCRprobableyear rounddue toCAIRNone None None Scrubber3 & 4 SCRduringozoneseasonSCR yearround fromConsentDecreeSCRduringozoneseasonSCR yearround fromConsentDecreeNone None None ScrubberBarry 1, 2, 3 None SNCR SCR SNCR None None None NoneORISID=3 4 None SNCR SCR SNCR None None Scrubber Scrubber5 None None SCR SCR None None Scrubber ScrubberE C Gaston 1 - 4 SCR None SCR None None None Scrubber ScrubberORISID=26 5 SCR SCR SCR SCR Scrubber None Scrubber ScrubberGorgas 6 & 7 None None NoneNone None None None NoneORISID=8 8 & 9 None None None None None Scrubber None Scrubber10 SCR SCR SCR SCR None Scrubber Scrubber ScrubberCharles R. Lowman 1 None None None None None Scrubber None ScrubberORISID=56 2 & 3 SCR SCR SCR SCR Scrubber Scrubber Scrubber ScrubberGA Bowen 1BLR SCR SCR SCR SCR None Scrubber ScrubberORISID=703 2BLR SCR SCR SCRSCR None Scrubber Scrubber3BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber4BLR SCR SCR SCR SCRIPM hadretrofitscrubbersbut littleemissionreductionsScrubber Scrubber ScrubberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.100Table 2.1-1 (continued)NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateGA Wansley 1 SCR SCR SCR SCR Scrubber Scrubber ScrubberORISID=6052 2 SCR SCR SCR SCRIPM hadretrofitscrubbersbut littleemissionreductionsNone Scrubber ScrubberKraft 1, 2 None None NoneNone None None None NoneORISID=733 3 None None SCRNone None None None NoneMcIntoshORISID=61241 None None SCR None None None None NoneYates 1 None None None None Scrubber Scrubber Scrubber ScrubberORISID=728 2, 3 None None NoneNone None None None None4 – 7 None None SCR SCR None None Scrubber NoneHammond 1 None None SCR SCR None Scrubber Scrubber ScrubberORISID=708 2 None None SCR SCR None Scrubber Scrubber Scrubber3 None None SCR SCR None Scrubber Scrubber Scrubber4 SCR SCR SCR SCR ScrubberScrubber Scrubber ScrubberKY Ghent 1 None SCR SCR SCR Scrubber Scrubber Scrubber ScrubberORISID=1356 2 None None SCR SCR None Scrubber Scrubber Scrubber3, 4 None SCR SCR SCR NoneScrubber Scrubber ScrubberColeman C1 None None SCR SCR None Scrubber Scrubber ScrubberORISID=1381 C2 None None SCR SCR None Scrubber Scrubber ScrubberC3 None None SCR SCR None Scrubber Scrubber ScrubberHMP&L Station 2 H1 SCR SCR SCR SCR Scrubber Scrubber Scrubber ScrubberH2 None SCR SCR SCR ScrubberScrubber Scrubber ScrubberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.101Table 2.1-1 (continued)NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateKY E W Brown 1 None None None None None Scrubber None ScrubberORISID=1355 2 None None SCR SCR None Scrubber Scrubber Scrubber3 None None SCR SCR None Scrubber Scrubber ScrubberSC Jeffries 3 SCR None SCR None None None None NoneORISID=3319 4 None None NoneNone None None None NoneWateree WAT1 SCR SCR SCR SCRNone Scrubber None ScrubberORISID=3297 WAT2 SCR SCR SCR SCRNone Scrubber Scrubber ScrubberCanadys CAN1 None None NoneNone None None None NoneORISID=3280 CAN2 None None None None None None None NoneCAN3 None None None None None Scrubber None ScrubberRainey CT1A None SCR None SCR None None None NoneORISID=7834 CT1B None SCR None SCR None None None NoneTN Kingston 1 – 8 SCR SCR SCR SCR None None Scrubber ScrubberORISID=3407 9 None SCR SCR SCR None None Scrubber ScrubberJohnsonville 1 – 10 SCR None SCR SCR None None None NoneORISID=3406WV Willow Island 2 SCR None SCR SCRScrubber None Scrubber ScrubberORISID=3946Kammer 1 -3 SCR None SCR SCR Scrubber None Scrubber ScrubberORISID=3947Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 (ORI S10333) 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 Cycl e facility became commercial June 1, 2005. Added 346 tons of NO x and 121 tons of SO 2 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 NO x and 3,227 tons of SO 2 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 SO 2 emissions are much lower than IPM, but their expected NO x 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 em ission projections provided by the Southern Company for their units in Mississippi were to be used instead of the IPM results.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 resu lts 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 resu lts 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 Cogentrixof 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; Up grade 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 SO 2 and PM emissions based on upgrade in control efficiencies.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 PM 10 and PM25 emissions in 2018 by 95 percent based on change in allowable emission rate Unit 2: Install low NO x burners that meet 0.46 lb/mmBTU from 0.9 by May 1, 2004. Recalculated NO x 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 PM 10 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 PM 10 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 PM 10 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 NO x control technology by April 30, 2006 to meet 0.27 lb/mmBTU, down from 0.45 lb/mmBtu. Calculated NO x emissions using IPM heat input and 0.27 lbs/mmBtu

Generic Unit ORISID=900545 All All predictions for generic un its appear reason able 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 re sults 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 contro l 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 re sults using VADEQ’s growth and control estimates.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x 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 in put. 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 a ll 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 fo r 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 fo r 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 fo r 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 SO 2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. Used SO 2 Permit Rate of 0.678 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 2018

Mt. Storm ORISID=3954 1, 2, 3 SO 2 Permit Rate was corrected from 2.7 to 0.15 lb/MMBtu. Used SO 2 Permit Rate of 0.15 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-3 EGU Point Source SO 2 

### 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 NO x 

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

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### Table 2.1-5 EGU Point Source VOC Em ission 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 Em ission 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-7 EGU Point Source PM 10 

### -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 PM 2.5 

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

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### Table 2.1-9 EGU Point Source NH 3 

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

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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 Ai r 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 pr ojection inventories. As described in Section 2.1.1.4, we split the point source inventory in to EGU and non-EGU components. MACTEC performed the following activitie s to apply growth and control factors to the 2002 inventory to generate the 2009 and 2018 pr ojection inventories:

• 

### Obtained, reviewed, and applied the most current growth factors developed by EPA, based on forecasts from an updated Regi onal 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-sp ecific or sector-specific growth factors submitted by stakeholders;

• 

### Obtained and incorporated information regard ing 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 ne w information from S/L agencies based on their review of the Base F 2009/2018 inventories. The following sections discu ss each of these steps.

2.1.2.1 Growth assumptions for non-EGU sources This section describes the growth factor data used in develo ping 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 fo r Future Year Modeling Inventories (dated April 30, 2004) and CAIR Emission Inventory Overview (dated July 23, 2004). Thre e sources of data were used in developing the growth f actors for the Base F inventory:

• 

### State-specific growth rates from the Re gional 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 indus try sector, population, farm sector valueDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### added, and gasoline and oil expenditures) ar e 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, w ith 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 ma pped to specific SCCs for the non-EGU fuel use sectors (e.g., commercial coal, industria l natural gas). Growth factors for the residential natural gas combustion category, fo r 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 Atla ntic division includes eight southeastern States and the District of Columbia). Alt hough 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 me tals, motor vehicles and equipment) where the REMI-based rates were unrealistic or hi ghly uncertain. Growth projections for these sectors were based on industry group forecas ts, Bureau of Labor Statistics (BLS) projections and Bureau of Ec onomic Analysis (BEA) histor ical 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 (A F&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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### For the Base F inventory, the NCDENR supplie d recent projections for three key sectors in North Carolina where declining production wa s anticipated – SIC 22xx Textile Mill Products, 23xx Apparel and Other Fabrics, and 25xx Furniture and Fixtures. For th e Base G inventory, NCDENR decided to use a gr owth factor of 1.0 for thes e 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 le vels so the future emission reduction credits were available in the event that they are need ed for nonattainment areas. The specific growth factors for these industrial se ctors 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 ma de one additional change to th e growth factors. The Base F inventory relied on DOE’s AEO2004 forecasts for projecting emissions fo r 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 foreca sts (released in February 2006) to reflect changes in the energy market and to improve the emissions growth factors produced. We obtained the corresponding AEO 2006 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 AEO2 006. These comparison tables were reviewed by the S/L agencies. Based on this review, VIST AS decided to use the AEO2006 growth factors for fuel burning SCCs.

We used the EPA’s EGAS model and updated th e 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 si gnificant source shut downs 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 SO 2 and 113 tons of NO x in 2002. GA Georgia indicated that the former Blue Circle (n ow LaFarge) facility in do wntown 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 complete ly closed down. This facility emitted 1,617 tons of SO 2 and 587 tons of NO x 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 SO 2 and 1,773 tons of NO x 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 SO 2 and 134 tons of NO x 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 SO 2 and 266 tons of NO x 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 SO 2 , 2,994 tons of NO x , 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 signi ficant 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 co mbustors 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 SO 2 and 1,443 tons of NO x in 2002. Liberty Fibers (47-063-0197) in Hamblen County has recently shut down. This facility emitted 5,377 tons of SO 2 ; 2,057 tons of NO x ; 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 SO 2 and 276 tons of NO x in 2002. WV None specified.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.1.2.3 Control Programs applied to non-EGU sources We used the same control programs for bot h the 2009 and 2018 non-EGU point inventory. Two control scenarios were develope d: on-the-books (OTB) controls and on-the-way (OTW) controls. The OTB control scenario accounts for post-2002 em ission reductions from promulgated federal, State, local, and site-specific control programs. The OTW contro l scenario accounts for proposed (but not final) control programs that are reas onably anticipated to re sult in post-2002 emission reductions. The methodologies used to account for the emission reduc tions associated with these emission control programs are discussed in the following sections.

Table 2.1-11. Non-EGU Point Source Co ntrol 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

• NO x 

### RACT in 1-hr NAA SIPs

• NO x 

### 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

• NO x 

### SIP Call (Phase II – remaining States & IC engines)

2.1.2.3.1 OTB - NO x 

### SIP Call (Phase I)



### Phase I of the NO x 

### SIP call applies to certain large non-E GUs, including large industrial boilers and turbines, and cement kilns. States in the VISTAS region affected by the NO x 

### SIP call have developed rules for the control of NO x 

### 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 NO x 

### Allowance Tracking System – Allowances Held Repor t. Since these controls are to be in effect by the year 2007, we capped the emissions for NO x 

### SIP call affected sources at 2007 levels andDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### carried forward the capped levels for the 2009/ 2018 future year inve ntories. Since the NO x 

### SIP call allowances are given in te rms of tons per ozone season (5 month period from May to September), we calculated annual emissions by mu ltiplying 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 SO 2 

### as a result of the Industr ial 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 grea ter 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 usin g 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 capaciti es based on SCC. The applied MACT control efficiencies were 4 percent for SO 2 

### and 40 for percent for PM 10 

### and PM2.5 to account for the cobenefit from installati on of acid gas scrubbers and other co ntrol equipment to reduce HAPs.

2.1.2.3.3 OTB - 2, 4, 7, and 10-year MACT Standards



### Maximum achievable control technology (MACT) requirement s 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 em ission reductions were designed from Federal Register (FR) notices and discussions with EP A’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 NO x 

### co-benefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating In ternal 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 ar e affected by two October 2003 Clean Air Act settlements under the EPA Petroleum Refinery Initi ative. 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The first consent decree pertained to Chevr on refineries in Rich mond and El Segundo, CA; Pascagoula, MS; Salt Lake City, UT; and Kapol ei, HI. Actions required under the Consent Decree will reduce annual emissions of NO x 

### by 3,300 tons and SO 2 

### by 6,300 tons. The consent decree requires a pr ogram to reduce NO x 

### emissions from refinery heaters and boilers through the installation of NO x 

### controls that meet at least an SNCR le vel of control. The refineries are to eliminate fuel oil burning in any combustion unit. The consent decree also requires reductions of NO x 

### and SO 2 

### from the fluid catalytic cracking unit and control of acid gas flaring incidents. The consent decree does not provide sufficient inform ation to calculate emission reductions for the FCCU or flaring at the Pascagoula refinery. Ther efore, we calculated a general percent reduction for NO x 

### and SO 2 

### by dividing the expected emission reducti ons at the five Chevron refineries by the total emissions from these five refineries (as reported in the 1999 NE I). This resulted in applying percent reductions of 45 percent for SO 2 

### and 28 percent for NO x 

### to FCCU and flaring emissions at the Chevron Pascagoula refinery.
The second consent decree pertained to the Erg on-West Virginia refinery in Newell, WV; and the Ergon Refining facility in Vi cksburg, MS. The consen t decree requires the two facilities to implement a 6-year program to reduce NO x 

### 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 NO x 

### burners are required on Boilers A and B at Newell, a low NO x 

### -equivalent level of control for heat er H-101 at Newell and heaters H-1 and H-3 at Vicksburg, and an ultra low NO x 

### burner level of control fo r heater H-451 at Vicksburg.

2.1.2.3.6 OTW - NO x 

### SIP Call (Phase II)



### The final Phase II NO x 

### SIP call rule was finalized on Ap ril 21, 2004. States had until April 21, 2005, to submit SIPs meeting the Phase II NO x 

### budget requirements. The Phase II rule applies to large IC engines, which are primarily used in pipeline transmission service at compressor stations. We identified affect ed units using the same methodol ogy 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 contro l level of 82 percent for natural gas-fired IC engines and 90 percent for diesel or dual fuel categories. As show n 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.1.2.4 Quality Assurance steps Final QA checks were run on the revised projecti on inventory data set to ensure that all corrections provided by the S/L agencies and stake holders were correctly incorporated into the S/L inventories and that there we re no remaining QA issues that could be addressed during the duration of the project. After e xporting the inventory to ASCII te xt 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 developm ent process, quality assuran ce steps were performed to ensure that no double counting of emissions occurred, and to ensu re 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 re vised 2002 base year inventory:

1. Facility level emission summaries were pr epared and evaluated to ensure that emissions were consistent and reasonab le. The summaries included base year 2002 emissions, 2009/2018 projected emissions accounting only for growth, 2009/2018 projected emissions accounting for both gr owth and emission reductions from OTB and OTW controls.

2. State-level non-EGU comparisons (by polluta nt) were developed for the base year 2002 emissions, 2009/2018 projected emi ssions accounting only for growth, 2009/2018 projected emissions accounting fo r 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 representati ves 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 i nventory 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 in to 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 th e revised 2009/2018 non-EGU point source inventories. The “growth only” column does not include the shutdow ns (section 2.1.2.2) or control factors (section 2.1.2.3), only the gr owth factors descri bed in section 2.1.2.1.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 SO 2 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 inve ntory 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 NO x SIP call. NCDENR took 2004 emissions and grew them to 2009 & 2018 and capped those units that are subject to the NO x SIP Call Rule. These facility IDs are 37-057-3705700300, 37-097-3709700225, and 37-157-3715700131. NCDENR applied NO x 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, PM 10 -FIL, and PM 2.5 -FIL pollutant codes. In August 2005, SC DHEC indicated that data reported using the PM-FIL, PM 10 -FIL, and PM 2.5 -FIL pollutant codes should actually have been reported using the PM-PRI, PM 10 -PRI, and PM 2.5 _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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 Bowa ter facility (47-107-0012) based on the facility’s updated 2002 emission inventory update. Replaced 2009/2018 data from Hamilton County, Tennessee, usin g 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 Fe rtilizer LP (Site ID: 47- 157-00146) based on the facility’s updated 2002 emission inventory update. The 2002 NEI correctly repor ts the actual emissions for CEMEX (47-093-0008) after the NO x 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, NO x 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 NO x emission estimates for NO x Phase II gas transmission sources at three Transco facilities (51-011-00 011, 51-137-00027, 51-1 43-00120) which were used to replace the default NO x Phase II control assumptions for these facilities. VADEQ provided updated 2009/2018 NO x and SO 2 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 NO x and 107 tons of SO 2 per year. The permit also allowed the installation of 3 new boilers, also under the 213 tons of NO x /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 NO x 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 ra nges typically termed "accep table" for AQ modeling.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-13 Non-EGU Point Source SO 2 

### 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 NO x 

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

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### Table 2.1-15 Non-EGU Point Source VOC Em ission 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 Em ission 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-17 Non-EGU Point Source PM 10 

### -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 PM 25-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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-19 Non-EGU Point Source NH 3 

### 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 a pproaches to these projections. Separate methods for projecting emissions were used for non-agricultural (stationary area) and agricultural area sources (predominantly NH 3 

### 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 invent ory as the starting point for projections.

2. MACTEC then worked with the VISTAS Stat es (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 reporte d in the 2002 Base F ba se year inventory.

4. Controls (including control efficiency, rule e ffectiveness and rule pe netration) provided by the States or originally developed for us e in estimating projected emissions for U.S. EPA’s Heavy Duty Diesel (HDD) rulemaking em ission projections and used in the CleanDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Air Interstate Rule (CAIR) projections were th en used to calculate controlled emissions. State submitted controls had precedence ove r 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 th e appropriate year. In some cases EGAS Version 5 growth factors were us ed if no growth factor was available from either the States or the CAIR growth factor files. The use of E GAS 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-s upplied growth or contro l factors were provided. Thus for all of the sources in this sector of th e 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 fu ture controls but grow th 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 pr ojections 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 s ource 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 em issions 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 ca tegories that had not initially been included in the Base F inventory. These growth factors were obtained from EGAS 5.0. Finally updates to growth fact ors 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 us ed to reflect changes in energy efficiency resulting from new or updated fuel firing technologies.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.1.1 Stationary area source controls The controls obtained by MAC TEC 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 lin e interpolation of c ontrol level between 2007 and 2020. The equation used to calculat e 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) an d 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 co ntrols came from the IAQTR projections, however the controls used in CAIR were virtually identi cal 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 ar ea 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 th e 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 initia lly provided at the State-county-SCC level. However, upon direction from the VISTAS Emi ssion Inventory Technical advisor, the VOC controls were consolidated at the SCC level a nd applied across all counties within the VISTAS region (email from Gregory Stella, Alpine Geophysic s, 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### The equation below indicates how VOC emissions we re projected for stationary area sources.

⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛

− = 100 _ 100 _ 100 _ 1 2018 2018 2018 2002 2018 

### RP VOC RE VOC CE VOC x VOC VOC



### Where:

VOC 2018 

### = VOC emissions for 2018

VOC 2002 

### = Uncontrolled VOC emissions for 2002

VOC_CE 2018 

### = Control Efficiency for VOC (in this example for 2018)

VOC_RE 2018 

### = Rule Effectiveness for VOC (in this example for 2018)

VOC_RP 2018 

### = 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 applie d if they were greater than any existing 2002 base year controls . No controls were found for SO 2 

### or NO x 

### area sources.
In the pre-Base F 2018 emission estimates, an en ergy efficiency factor was applied to energy related stationary area sources. The energy effici ency 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 s upplied by U.S. EPA related to the CAIR growth factors indicated that growth values for those ca tegories were derived from U.S. Department of Energy (DOE) and were felt to account for change s in growth and projected energy efficiency. For the Base G inventory, these energy effici ency factors were re-instituted and used in conjunction with EGAS 5.0 growth f actors in a manner identical to that used for the pre-Base F inventories. The energy effici ency factors were derived from U.S. DOE’s Annual Energy Outlook report.
One significant difference between the Base F a nd Base G control factors was for counties and independent cities in northern Virginia. Several counties and i ndependent cities in northern Virginia are subject to Ozone Transport Commis sion rules. For these counties and independent cities, controls for portable fuel containers, mobile equipment repair /refinishing, consumer products, solvent metal cleaning, and the archit ectural and industrial maintenance rules were added. The counties/independent cities (FI PS 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 Willia m County (51153), Spotsylvania (51177), and Stafford (51179). Not all OTC rules applied to all counties/cities.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.1.2 Stationary area source growth As indicated above, growth factors for the Ba se F and Base G 2009 and 2018 inventories were obtained from the U.S. EPA and ar e linear interpolations of the growth factors used for the Clean Air Interstate Rule (CAIR) projections. The gr owth 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 Micr osoft 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 know n series of data points (in this case the 2001, 2010 and 2015 values) based on the equation for a strai ght line. These values were calculated at the State and SCC level with the excepti on 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 th e CAIR projections, MACTEC confirmed that all SCCs found in the VISTAS 2002 base year inventor y 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 po ssible, they were taken from a beta version of EGAS 5.0. In other cases, the growth factor wa s 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 populati on as the growth surrogate. For the Base G inventory, CAIR growth factors for fuel fired area sources were replaced with EGAS 5.0 gr owth factors (used in conjunction with AEO fuel efficien cy factors). A comment field in the growth factor file was used to mark those records that were not taken di rectly from the CAIR pr ojection 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 indivi dual control and growth factors were different (due to the linear interpolation used to calculate th e 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 calcu lated projections for a number of area source categories. The values in thes e files (provided for both 2009 and 2018) were used to overwrite the calculated projected emi ssions in the final NIF file.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.2 Agricultural area sources The general approach used to calculate project ed emissions for agricu ltural area sources (predominantly NH 3 

### 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 uncontro lled, and no future controls for these sources were identified, MACTEC projected the agri cultural emissions us ing State-specific growth if available, otherwise the U.S. EP A’s Interstate Air Quality Transport Rule (IAQTR)/Ammonia inventory was used to devel op the growth factors used to project the revised 2002 base year inve ntory to 2009 or 2018. Since the IAQTR inventory was only used to construct growth f actors rather than using the emissions directly, no updated growth factors were prepared fr om 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 emi ssion projections were made between Base F and Base G other than the removal of wild animal a nd 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 indi vidual VISTAS States or in the information provided in the EPA’s IAQTR or CAIR Ammoni a inventory documents. Thus all projected emissions for agricultural area sources re present simple growth with no controls.

2.2.2.2 Growth assumptions for agr icultural area sources Growth for several agricultural area source live stock 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 th e 2002 NEI upon which the growth projections were based was prepared prior to th e 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 SI WG decided to use the NEI ammonia inventoryDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### projected emissions to develop the 2009 and re vised 2018 growth factors used to project emission for VISTAS. Details on the NEI i nventory and projections can be found at:
http://www.epa.gov/ttn/chief/ap42/c h09/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 gr owth factors, several st eps 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 calculat e intermediate year emissions for 2009 and 2018. These values were calculated based on li near interpolation of the existing data.

2. Once the intermediate emissions were calculated, MACTEC developed emission ratios to provide growth factors fo r 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 S CCs fell into one of two categories:

a. SCCs that had multiple entries in th e 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, em issions were calculated for several aspects of the process. The CMU mode l version 3.6 which was the basis for the VISTAS 2002 Base F inventory di d not use a process model. As a consequence a mapping of SCCs in th e NEI projections and corresponding SCCs in the CMU inventory was made and for those SCCs an average growth factor was calculated from the NEI pr ojections for use w ith 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 emi ssions in the NEI files. For these instances, MACTEC first developed Stat e 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 4. Once all of the growth factors were deve loped, they were used to project the emissions to 2009 and 2018. Growth factors we re first applied at the State, county and SCC level. Then remaining records we re grown with the State/SCC specific growth factors. Finally, any remaining ungr own records were projected at the SCC level using the VISTAS regional growth factor.
For the livestock categories, the NEI emission project ions only had data for beef and dairy cattle, poultry and swine. Thus for other livestock cate gories and for fertilizers alternative growth factors were required.
The growth factors for other livestock categorie s 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, c ounty and SCC level growth fact ors. The IAQTR data provided growth factors for 1996, 2007, 2010, 2015 and 2020. Linear interpolation was used to develop the growth factors for th e 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 moratori um on swine production in that State.

2. Ammonia growth factors for a few categories (m ainly feedlots) were assigned to be the same as growth factors for PM emissions fr om the NEI projections. This assignment was made because the CMU model showed emissions from these categories but the NEI projections did not show ammonia em issions 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 Ba se F and Base G. Thus Base F and Base G agricultural emissions are the same in each invent ory. 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 gr owth factors that may be more recent than the EPA inventory used to develop gr owth estimates for Base F/G.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 grow th factors were differe nt (due to the linear interpolation used to calculate the values) but the calculation met hods 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 2 002 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%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

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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 versi on 3.1 of the VISTAS inventory. seve ral 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 wo rked 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 invent ory. The 2009 and 2018 projections developed using the method described below ar e being used by VISTAS as the 2009 and 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 fu ture prescribed burning practices. The “typical” fire projection is the 2002 base prescribed fire projection.
One of the biggest issues in preparing the proj ection 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 provi ded 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 pr eparation process, thus there was no known FWS data in the 2002 actual or typi cal 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 submitte d fire-by-fire data for the 2002 actual inventory and had mapped the projections to current bu rn days in the 2002 act ual inventory, MACTEC could not do a simple replacement of thos e records with the 2009/2018 projections. This situation was created because several VISTAS St ates 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 reco rds 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 da ta applied a county level data approach for FS data where a State had a prescribed fire pe rmitting 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 eac h 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. Th e 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 th e total county “typical” acreage to determine future acreage burned for either 2009 or 2018. MA CTEC then allocated th e increased acreage to current modeling days. The average daily acre s burned data provided by FWS per NWR/county was used to allocate the acreage to the correct nu mber of days required to burn all of the acres. Guidance supplied by FWS indicated that up to thr ee 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 us ed if there were an insufficient number of 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 suffici ent to completely allocate the increased acreage over the total number of days avai lable. If that wasn’t sufficient then we used three times the average daily acres burned to allocate the acreag e. We applied the highest increases to days in the database that already had the highest acr eage burned since we felt those days were most likely to represent days with representative conditions for conducti ng prescribed burns.
The approach used by MACTEC for the FS was s lightly different. For States that had permit programs, we used similar approach to the FW S 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 re placed 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 corr ection 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 i nventory, fire acreage increased or decreased from acreag e on the same fire days as we re 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 fu ture 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 incr ease 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 f our different counties). You can see that the total additional acres for the Clinch County portion of Okef enokee 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 al most 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 da tabase (since our me thod allowed us to increase the average daily acres burned up to three times the recomm ended level). Thus the first burn day received 560 acres and all others received 280 except the fina l day which received 276 to make the total equal to the required 1,956 acres. The table also indicates that the increased acres burnedDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 0 2000 4000 6000 8000 10000 12000 14000 16000

1/1/20 02 2/ 1/

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02

3/1/20 02 4/ 1/

20

02

5/

1/

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11/1/2002 12/1 / 2002



# Date of Fire EventAcres Typical FWS Add USFS Add 

### provided increases of from 10-48 percent in the acres burned on th e 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 prescrib ed 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 prescrib ed burning based on FS data. It should be noted that while the emissions represent 2009, all fire event dates list ed are for 2002 to match up with the base year meteorology used in modeling exercises.
Table 2.2-4 shows the percentage difference be tween 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 Project ion for Okeefenokee NWR for 2009Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.137Table 2.2-4 Percentage Difference Between BaseF and Base G Fire Emissions by StateStateCONH3NOXPM10-PRIPM25-PRISO2VOCCONH3NOXPM10-PRIPM25-PRISO2VOC2009 Fires Base G2018 Fires Base GAL 534,873 2,050 11,901 52,851 46,543 2,681 27,502 535,658 2,054 11,918 52,927 46,608 2,686 27,539FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 88,756 4,129 51,527GA 637,177 2,229 14,243 63,973 57,116 2,914 34,710 637,177 2,229 14,243 63,973 57,116 2,914 34,710KY 31,810 143 682 3,093 2,653 187 1,497 33,296 150 714 3,237 2,777 196 1,567MS 48,160 217 1,033 4,683 4,016 283 2,266 50,037 225 1,073 4,865 4,173 294 2,355NC 96,258 433 2,065 9,359 8,027 566 4,530 111,266 501 2,387 10,819 9,279 655 5,236SC 282,307 1,039 5,899 29,153 25,955 1,359 16,045 282,307 1,039 5,899 29,153 25,955 1,359 16,045TN 17,372 78 373 1,689 1,449 102 817 18,860 85 405 1,834 1,573 111 888VA 21,130 95 453 2,054 1,762 124 994 26,923 121 578 2,618 2,245 158 1,267WV 3,949 18 85 384 329 23 186 5,013 23 108 487 418 29 2362009 Fires Base F2018 Fires Base FAL 514,120 1,957 11,456 50,833 44,812 2,559 26,526 514,120 1,957 11,456 50,833 44,812 2,559 26,526FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 88,756 4,129 51,527GA 620,342 2,153 13,882 62,336 55,712 2,815 33,918 620,342 2,153 13,882 62,336 55,712 2,815 33,918KY 56,686 110 1,460 6,667 6,310 136 3,338 56,686 110 1,460 6,667 6,310 136 3,338MS 128,471 177 3,328 14,693 13,680 100 13,625 128,471 177 3,328 14,693 13,680 100 13,625NC 200,564 324 5,005 20,488 19,491 423 12,499 200,564 324 5,005 20,488 19,491 423 12,499SC 253,005 908 5,270 26,304 23,511 1,187 14,666 253,005 908 5,270 26,304 23,511 1,187 14,666TN 78,370 46 2,232 8,875 8,730 59 5,153 78,370 46 2,232 8,875 8,730 59 5,153VA 19,159 159 978 18,160 17,361 99 912 19,159 159 978 18,160 17,361 99 912WV 32,656 12 944 3,276 3,239 16 2,184 32,656 12 944 3,276 3,239 16 2,184Percentage 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% -4.01% -4.95% -3.82%FL 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%GA -2.71% -3.52% -2.60% -2.63% -2.52% -3.52% -2.34% -2.71% -3.52% -2.60% -2.63% -2.52% -3.52% -2.34%KY 43.88% -29.52% 53.25% 53.61% 57.96% -37.90% 55.15%41.26% -35.57% 51.07% 51.44% 56.00% -44.34% 53.06%MS 62.51% -22.07% 68.95% 68.13% 70.64% -183.85% 83.37%61.05% -26.83% 67.74% 66.89% 69.50% -194.91% 82.72%NC 52.01% -33.75% 58.74% 54.32% 58.82% -33.75% 63.76%44.52% -54.60% 52.31% 47.19% 52.40% -54.60% 58.11%SC -11.58% -14.52% -11.93% -10.83% -10.39% -14.52% -9.40%-11.58% -14.52% -11.93% -10.83% -10.39% -14.52% -9.40%TN 77.83% -69.40% 83.30% 80.97% 83.41% -74.42% 84.14%75.93% -83.92% 81.87% 79.34% 81.98% -89.36% 82.78%VA -10.29% 40.36% 53.67% 88.69% 89.85% -25.40% -9.03%-40.53% 24.00% 40.97% 85.59% 87.07% -59.79% -38.93%WV 87.91% -48.65% 91.03% 88.28% 89.83% -49.46% 91.49%84.65% -88.70% 88.61% 85.12% 87.09% -89.73% 89.20%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.4 Quality Assurance steps Throughout the inventory developm ent process, quality assuran ce steps were performed to ensure that no double counting of emissions o ccurred, to ensure that a full and complete inventory was developed for VISTAS, and to ma ke sure that projecti on calculations were working correctly. Quality assurance was an impo rtant component to the inventory development process and MACTEC performed the following QA st eps on the stationary and agricultural area source components of the 2009 and re vised 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 th ere were no missing sources.

3. Tier comparisons (by pollutant) were developed between the 2002 base year inventory and the 2009 and 2018 projection i nventories. In addition, total VISTAS pollutant summaries were prepared to co mpare 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 repr esentatives for review and comment. Changes based on these comments were implemented in the files.

5. Version numbering was used for all i nventory 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 possibl e for these inventories, supple ment 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 inve ntory that included all “on-the-books” control programs and 2) an “on-the-way” in ventory that included controls th at were likely to be “on-theway”. For the Base F and Base G emission forecas ts to the mobile source sector, “on-the-books” and “on-the-way” are defined w ith the same strategies and th erefore 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, usin g methodologies identical to those employed inDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### developing the 2002 on-road portion of the revi sed 2002 VISTAS base year inventory. All modifications to the 2002 inventory methods were developed in consulta tion with the Mobile Source Special Interest Workgroup (MSSIWG). Ge nerally, modifications were only made to properly account for actual change s expected in the interveni ng period (i.e., between 2002 and 2009 and between 2002 and 2018), but the underlyi ng inventory development methodology was identical, except to the extent re quested 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 ba se year inventory data files, MACTEC provided a review of the data and methods used to develop on-road mo bile source input files for the initial 2002 base year inventory prior to developing the prel iminary 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 VM T growth surrogates such as population). Since these data were not applicable to 2018 due to intervenin g growth, input for 2018 was solicited from the MSSIWG. At th e same time we researched countyspecific growth rate data utilized for recent national rulemakings as a backstop approach to State supp lied VMT projections.

• Modeling Temperatures. Actual 2002 temperat ures 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 t ype). 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 initia l 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 areDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 acro ss 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 init ial 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 a nd 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 re flected in the 2018 inventory in the absence of more stringent local fuel contro ls. Expected changes in local fuel control programs were solicited.

• Vehicle Standards. The 2002 initial base ye ar 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 ta mpering 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 ma intain the 2002 program descriptions without change. However, if a State pla nned changes, we requested information on those plans. In the final implementation of th e 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 estima tes 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 cas e projection inventor y data were compiled, MACTEC applied the data and methods selected and proceeded to develop the preliminary (prebase F) base case 2018 projection inventories. Th e 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 fi les for NONROAD in NIF 3.0 format). AnnualDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 pre liminary version of the 2018 base case mobile inventory input data files. These files were then updated to provide a fina l set of 2018 base case inventory input data files as well as a set of i nput files for 2009. The info rmation 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 prepar ing 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 St ate 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 wa s more recent VMT forecasting data available (e.g., from the CAIR and if appropria te revised the default VMT grow th rates accordingly. This did not affect any State that pr ovided 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 th e 2018 preliminary inventor ies coupled with any changes/revisions provided by the States during the review of th e 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, met hodological revisions, and local cont rol 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 inventor ies required the following updates:

1. The evaluation year was update d 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, specifi c for diesel sales fractions (with data for the newest 25 model years re quired), we updated all files that includedDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 incl uded 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 consta nt. Therefore, we se t the diesel sales fractions for 2003-2018 at the same value as 2002.

4. VMT mix fractions must be updated to refl ect expected change s in sales patterns between 2002 and 2018. If explicit VMT mi x 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 upda ted the VMT mix in such files as follows:

First, we calculated the VMT fractio ns 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 fo r 2018 provided in Appendix D of the MOBILE6 Users Guide. This approach ensures that explic it input file VMT fractions are consistent with the absolute VMT di stributions prepared by MACTEC. These changes were made to all files that included VMT mixes.

5. All other input data were re tained at 2002 values, except as otherwise instructed by the States. This includes all control pr ogram descriptions (I/M, Anti-Tampering Program [ATP], Stage II, etc.), all other fu el qualities (RVP, oxy content, etc.), all other vehicle descriptive data (registrations age distributions, etc.), and all scenario descriptive data. The Stat e-specific updates performe d are described below.
Kentucky: MACTEC revised the 2018 input files for the Lo uisville, Kentucky area (Louisville Air Pollution Control District [APCD]) based on comments received relative to several components ofDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 VM T" and "Registration Age Di stribution" file pointers were updated to reflect revised 2002 file s provided by the Louisville APCD.
c) The "VMT Mix" data, which was previous ly based on the default approach of "growing" 2002 data, was replaced by 2018-sp ecific data provided by the Louisville APCD.

North Carolina: North Carolina provided a wide range of revise d input data, including co mplete MOBILE6 input files for July modeling. MACTEC did not use the provided input files dir ectly as they did not match the 2002 NC input files for critical elem ents such as temperat ure distributions and gasoline RVP (while they were close, they were slightly different). To maintain continuity between 2002 and 2018 modeling, MA CTEC instead elected to revise the 2002 input files to reflect all control program a nd vehicle-related changes imp lied 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 t hose referenced in the 2018 data . In addition, since NC only provided 2018 input files for July, we estima ted 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 i nput file to reflect the 2018 "header" data included in the NC-provided 2018 files. Thes e data are exclusivel y limited to I/M and ATP program descriptions, so that the 2002 I/M and ATP da ta were replaced with 2018 I/M and ATP data.
c) We retained the registration age fractions at their 2002 "value s" (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), we re 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 toDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### reflect these variations was not appropriate given the resu lting 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. Wh ile 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 prof ile cross reference file for 2018. We did not use these in our updates as they ha ve 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 i nput files that referenced an external I/M descriptive program file (VAIM02.I M) 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 th at 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-ro ad 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 me thodology 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 Re ports" (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 di esel fuel. According to Table 2 of the report, there will be 2,922,284 barrels per da y 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 a ssumptions 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 3. Diesel sales fractions were updated identic ally 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 re tained at 2002 values, except as otherwise instructed by individual States (see below). This incl udes all control program descriptions (I/M, ATP, Stage II, etc.), all othe r fuel qualities (RVP, oxy conten t, etc.), all other vehicle descriptive data (registration age distributions, etc.), and a ll 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 200 9 and 2018 VMT for use in estimating on-road mobile source emissions was as follows:

1. All estimates start from the final VMT estim ates used for the 2002 revised base year inventory.

2. Initial 2009 and 2018 VMT estimates were base d on linear growth rates for each State, county, and vehicle type as derived from the VMT data as sembled by the U.S. EPA for their most recent HDD (heavy duty diesel) ru lemaking. 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 forecas t data, the estimates derived in step 2 are also the final estimates. These States ar e: Alabama, Florida, Georgia, Kentucky, Mississippi, and West Virginia. For States th at provided forecast da ta, the provided data were used to either replace or augment the forecast data based on the HDD rule. These States, and the specific approaches employe d, are detailed followi ng the growth method description. The steps involved in performing the grow th estimates for VMT were as follows:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 1. Linear growth estimates were used (although MACTEC investigated the potential use of nonlinear factors and presented that informa tion to the MSSIWG, the decision was made to use linear growth fact ors 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 appropr iate controlling factor as it includes the combined impacts of all vehicle classes, the initial year-specific ve hicle and road class VMT forecasts were normalized so that th ey 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 fo recasts 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 1.274Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 provid ed by the Louisville APCD. Therefore, the distribution of Jefferson County VMT by vehicle type within th e 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 th e fraction of that VMT accumulate d by each of the eight vehicle types reflected in the VMT file. The follo wing procedure was employed to make the VMT estimates consistent with the provided 2009/2018 VMT mix:

a) The 16 MOBILE6 VMT mix fractions were aggr egated 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 th e 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 mi x data by county and roadway type for 2018. Therefore, these data replaced the data deve loped for North Carolina using HDD rule growthDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### rates in their entirety. Similar data were s ubmitted 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. Theref ore, the VMT mix fractions estimated using the "default" HDD rule growth rates were appl ied to the State-provided VMT estimates to generate vehicle-specific VMT. Essen tially, 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 deta il. Note that these are not HDD VMT fractions, but VMT fractions developed from 2002 NC data us ing HDD vehicle-specific growth rates. In effect, they are 2002 NC VMT fractions "grown" to 2009.
The default VMT mix fraction was applied to th e State-provided VMT data at the county and road type level of detail to ge nerate VMT data at the county-ro ad 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 comb ination, 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 c ounties is minimal, so there is no effective difference in utilizing this more aggregate appr oach vis-à-vis the more resolved county/road approach.

South Carolina: South Carolina provided county and roadway type-s pecific 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 mixe s developed for South Carolina using the HDD rule VMT growth rates. Table 2.3-3 presents th e resulting VMT estimates which differ from the "default" HDD rule estimates as follows:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 adjust ed 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-spe cific annual VMT growth rates and these data were applied to Virginia -provided VMT da ta 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 in to vehicle type-specific VMT using the VMT mixes developed for VA using the HDD rule VM T growth rates. Table 2.3-5 presents the resulting VMT estimates which differ from the "default" HDD rule estimates as follows:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 Ba se G inventories and input files, VISTAS states reviewed the Base F inputs, and provide d corrections, updates and supplemental data as noted below.

For all states modeled, th e Base G updates include:

• Adding Stage II refueling emissions cal culations 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 ve hicle distributions and updated registration distributions for Mobile 6.
TN - revised VMT and vehicle registrati on distributions for selected counties.
WV – revised VMT input data
AL, FL, and GA and VA did not provide update s 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 descri be the projection process used to develop 2009 and 2018 non-road projection estimates, as revised through the sp ring of 2006, for sources found in the NONROAD model and those sources estimated outside of th e model (locomotives, ai rplanes and commercial marine vessels).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 ye ar inventory input f iles available at the time the forecasts were developed, with appropria te updates for the projection years. Generally, this means that the Base F 2002 base year inpu t files (as updated through the fall of 2004) were used as the basis for Base F projection year i nput 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 i nherently incorporated into the associated projection year re visions. 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 ga soline 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 an d fleet turnover impacts are al so handled internally within the NONROAD model, so that explicit chan ges input file changes are not required.
Base F Input File Changes:
To correctly account for diesel fuel sulfur cont ent differences between the base and projection years, two sets of input and out put files were prepared for each forecast year, one set for landbased equipment and one set for marine equipm ent. This two-step projection process was required for Base F, because diesel fuel sulf ur contents varied between land-based and marine-based non-road equipment and the Dr aft NONROAD2004 used for Base F allowed only a single diesel fuel sulfur input. Thus, the m odel was executed separately for land-based and marine-based equipment for Base F, and the a ssociated outputs subsequently combined. The specific diesel fuel sulfur cont ents 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 capab le of handling separate diesel fuel sulfur inputs for land-based and marine-based non-ro ad equipment in a single model execution. Therefore, the two step modeling process desc ribed 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 vapo r pressure data were provided by Georgia regulators for 20 counties 5 

### 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 ei ther the 2009 or 2018 forecast year s. Therefore, to correctly forecast emissions in these counties, the forecas t 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 unaff ected by the summertime control requirement.

2.3.4.1.1 Differences between 2009/2018


### Other than diesel fuel sulfur content and the ye ar of the projections, th ere are no differences in the methodology used to estimate emissions fr om NONROAD model sources. As indicated above, however the Base F 2009/2018 projections were developed us ing 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.3.4.2 Non-NONROAD model sources Using the 2002 base year emissions inventory fo r aircraft, locomotives, and commercial marine vessels (CMV) prepared as de scribed earlier in this doc ument, corresponding emission projections for 2009 and 2018 were de veloped in both the fall of 2004 (Base F) and the spring of 2006 (Base G). This section describes the procedur es employed in developing those inventories. The information presented is intended to build off of that presented in th e section describing the 2002 Base F base year inventory. It should be r ecognized 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 y ear inventory was used as the basis for Base G projection year inventory development. Thus, a ll base year revisions (a s described earlier in this document) are inherently incorporated in to the associated proj ection year revisions.

Base F Revisions:
Table 2.3-6 shows the 2002 base year emissions fo r each State in the VISTAS region for aircraft, locomotives and CMV (as they existed prior to Base F development).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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
VA 110 313 25 23 27 48 Military Marine (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 24,881Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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, loco motives, and CMV is identical to that used earlier to develop preliminar y 2018 Base 1 (“On the Books”) and 2018 Base 2 (“On the Way”) inventories. Briefly, the met hodology relies on growth and cont rol factors developed from inventories used in support of recent EPA rule makings, 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 a nd 2002-2018 were estimated using straight line interpolation betwee n 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the State-county-S CC-pollutant level of detail.
(c) The EPA growth and control data are matc hed 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 poin t. Unfortunately, actual match results were not always ideal, so additional matching criteri a were required. For s ubsequent reference, this initial (highest resolution) matching cr iterion is denoted as the “CAIR-Primary” criterion.
(d) A second matching criterion is applied that utilizes a simila r, but higher-level SCC (lower resolution) matching approach. For exam ple, SCC 2275020000 (commercial aircraft) in the 2002 base year inventory data would be matched with SCC 2275000000 (all aircraft) in the CAIR data. This criteri on 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 leve l matching criterion was required.
(e) In the third matching step, the most frequent ly used SCC in the EPA CAIR files for each of the aircraft, locomotive, and commercial ma rine sectors was averaged at the State level to produce a “default” State and pollutant-sp ecific growth and c ontrol factor for the sector. The resulting factor is used as a “default” grow th factor for all unmatched county-SCC-pollutant level data in each State. In effect, St ate-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 controlDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 s ector. Matches made usi ng 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 bo th future CMV and locomotive emissions. However, the impacts of this rule were origin ally intended to be excluded from the initial VISTAS 2018 forecast, which was to include on ly “on-the-books” controls. (The T4 rule was finalized subsequent to the developmen t of the preliminary 2018 inventory in March of 2004.) Given its final status, T4 impacts were m oved into the “on the books” inventory for non-road equipment. In addi tion, 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” invent ories for the sector; so that only a single forecast inventory (for each evaluati on year) was developed. Nevertheless, since the algorithms developed to produce the VIST AS forecasts were developed when there was a distinction between the “on the books” and “on the way” inventories, the distinct algorithms used to produce th e two inventories have been maintained even though the conceptual distinctions have been lost. This approach was taken fo r 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 im pacts 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” f iles. It is important to note that the matching exercise described in steps (b) th rough (e) cannot simply be replaced because the “No T4” files obtained from the EPA incl ude 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 thes e 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 describe d in steps (c) through (e) above).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### (g) The CAIR matching criteria were overridden for any record for which States provided local growth data. Only North Carolina pr ovided 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 factor s were applied only to commercial (SCC 2275020000) and air taxi (SCC 2275060000) emissions. Emissions for ecasts 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 fact or submission, continued to utilize the growth factors developed according to steps (b) through (f) above. Table 2.3-7 presents the locally generated growth factor s 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-S CC-pollutant was assigned a combined growth and control factor using the EPA CAIR for ecast 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 acco rdance 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 th e 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 st andards 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 SO 2 

### and PM emissions. Expected fuel sulfurDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### contents were obtained for each evaluati on year from the EPA technical support document for the final T4 rule ( Final Regulatory Analysis: C ontrol 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 co mpare 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 c ontrol scenarios to estimate emission reduction impacts.

Table 2.3-8 Estimated Emission Reduc tion Impacts based on T-4 Rule

2009 2018 CMV SO 2 = Non-T4 SO 2 × 0.1569 0.0241 Locomotive SO 2 = Non-T4 SO 2 × 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 c ontent assumed for the 2002 VISTAS base year inventory, upon which both the 2009 and 2018 inventories were ba sed, is 2500 ppmW, a small adjustment to the emission reduction mu ltipliers 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 estim ates 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 SO 2 = Non-T4 SO 2 × 0.1632 0.0225 Locomotive SO 2 = Non-T4 SO 2 × 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 C ounty, 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, th e ratio of diesel CMV emissions to totalDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 SO 2 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 es timates for diesel engines, as presented above, yields the following impact adju stment factors for Palm Beach County:
Table 2.3-11 Overall Adjustment Fact ors for Palm Beach County, FL

GROWTH BASIS

2009 SO 2 (19, 20 Growth Basis) 0.7894 [0.1632×0.2410+(1-0.2410)]

2009 SO 2 (96, 10, 15, and 20 Growth Basis) 0.8930 [0.1632×0.1279+(1-0.1279)]

2018 SO 2 (96, 20 Growth Basis) 0.7623 [0.0225×0.2432+(1-0.2432)]

2018 SO 2 (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 fo recasts for both 2009 and 2018 were developed. As indicated in step (b) above, basic growth factor s were developed using EP A CAIR inventory data for 1996, 2010, 2015, and 2020. From these data, equiva lent EPA CAIR inventories for 2002 and 2009 were developed through linear interpolati on of the 1996 and 2010 inventories, while an equivalent CAIR inventory for 2018 was develope d through linear interp olation of the 2015 and 2020 inventories. Growth factors for 2009 and 2018 we re then estimated as the ratios of the CAIR 2009 and 2018 inventories to the CAIR 2002 inventory.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### During the development of the preliminary 2018 VI STAS inventory in Ma rch 2004, this process yielded reasonable results and exhibited no partic ular systematic concerns. However, when the 2009 Base F inventory was developed, significant concerns related to SO 2 

### and PM were encountered. Essentially, what was revealed by th e Base F 2009 forecast was a series of apparent inconsistencies in the CAIR 2010 and 2015 emissi on 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 da ta extracted from the CAIR inventory files. Note th at although a limited example is be ing presented, the same general issue applies throughout the CAIR files. Fo r FIP 01001 (Autauga County, Alabama) and SCC 2285002000 (Diesel Rail), the CAIR inventories indicate SO 2 

### emission estimates as shown in Table 2.3-12.

Table 2.3-12 SO 2 

### Emissions for Diesel Rail in Au tauga 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 ob servations 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 we re “accidentally” included in th e estimates, there should be a resultant 90 percent drop in di esel sulfur between 2010 and 2015; so such inclusion is unlikely. Third, the rate of growth be tween 2015 and 2020 (43 percent per year compound or 97 percent

per year linear) is well beyond any reasonable expecta tions for rail service; and fuel sulfur content during this period is constant both with a nd without T4. In short, there appeared to be no rational explanation for the data, yet the same ba sic relations are observed for thousands of CAIR inventory records.
For the most part, the issue seems to be centered on SO 2 

### 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 eith er inclusion or exclusion of T4 rule impacts is the underlying cause. Moreover, where they occu r, the observed growth extremes generally affect both SO 2 

### and PM equally, while one would expect PM effects to be buffered if the T4 ruleDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### was the underlying cause, since changes in diesel fu el sulfur content will only affect a fraction of PM (i.e., sulfate), while directly reducing SO 2 

### . 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 presente d above for Autauga County, Alabama, but normalized so that the interpolated 2002 CAIR em issions 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 th e 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 invent ory (i.e., a linear growth rate equal to 0.7 percent per year). Thus, it is eas y 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 inventor y, 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 posi tive 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 c onnecting 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 Appa rent 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


### YearEmissions 1

iii

ii i D

C B 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%/yrDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### In light of the apparent discrepancies i nherent in the 1996, 2010, 2015, and 2020 growth basis data and the inconsistencies its use would impa rt 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, interpol ating equivalent 2002, 2009, and 2018 inventories solely from these two invent ories. In effect, the CAIR inventories for 2010 and 2015 are ignored. In Figure 2.3-1, this sec ondary 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 labe led 1, 2, and 3 represen t 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 i nventories, while that between 2018 and 2002 is equal to the ratio of the 2018 and 2002 CAIR inve ntories. For the exampl e data, the resulting linear growth estimate is 0.3 per cent per year. For reference pur poses, this path is hereafter referred to as the 1996-2020 growth basis, since a ll interpolated data are based on CAIR data for only those two years.
It is perhaps worth noting that the only elemen ts of Figure 2.3-1 that have any bearing on the VISTAS inventories are the growth rates. The ab solute CAIR data are of importance only in determining those rates, as all VISTAS inventor ies were developed on the basis of the VISTAS 2002 base year inventory, not any of the CAIR i nventories. 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 SO 2 

### in Autauga County, Alabama), but there are thousands of additional CAIR reco rds that are virtually identical from a growth viewpoint.

While forecast inventories for aircraft, lo comotives, 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 inventor y, 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 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### base year VISTAS inventory. Th e larger reduction in CMV SO 2 

### 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 cont ribution to total CMV SO 2 

### in the 2002 inventories for these two States.
Figures 2.3-2 through 2.3-13 graphi cally depict the relationships between the various Base F inventories and preliminary 2002 an d 2018 projections prepared prio r 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 th rough overall aggregate em issions totals. All of the figures include the following emissions estimates:

• The 2002 Base F base year VISTAS emissi ons inventory (labeled as “2002”),

• The 2002 pre-Base F base year VISTAS emissions inventory (labeled as “2002 Prelim”),

• The Base F 2009 VISTAS emissions inventor y developed using gr owth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2009”),

• The Base F 2018 VISTAS emissions inventor y developed using gr owth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2018”), and

• The pre-Base F 2018 VISTAS emissions i nventory 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 (t he initial 2002 VISTAS inventory) and the 2002 Base F emission estimates. This reduction gene rally results from emission updates reflected in the State 2002 CERR submittals used to de velop the Base F 2002 base year inventory, although the major differences in ag gregate PM emission estimates are driven to a greater extent by modifications in the methodology used to estima te aircraft PM in the Base F 2002 base year inventory (as documented under the base ye ar inventory section of this report).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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
VA 118 299 23 21 5 50 Military Marine (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 26,148Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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
VA 128 282 23 21 1 53 Military Marine (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 27,709Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 NO x PM 10 PM 2.5 SO 2 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% VA +7% -4% -7% -7% -83% +5% Military Marine (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%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-17. Change in Emissions between 20 18 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NO x PM 10 PM 2.5 SO 2 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% VA +17% -10% -6% -6% -98% +12% Military Marine (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%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 168 118,739 130,798 145,885

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
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0 5,000 10,000 15,000 20,000 25,000 30,000

2002 2009 2018 2002 Prelim 2018 Prelim T
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### Figure 2.3-2. Total Aircraft, Locomoti ve, and CMV CO Emissions (Base F)

Figure 2.3-3. Locomotive CO Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 169 420,228 397,462 367,975 455,067

395,049

0 50,000 100,000 150,000 200,000 250,000 300,000 350,000 400,000 450,000 500,000

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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
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### Figure 2.3-4. Total Aircraft, Locomotive, and CMV NO x 

### Emissions (Base F)

Figure 2.3-5. Locomotive NO x 

### Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 170 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

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5,815

4,440

3,744 6,118

3,947

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### Figure 2.3-6. Total Aircraft, Locomotive, and CMV PM 10 

### Emissions (Base F)

Figure 2.3-7. Locomotive PM 10 

### Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 171 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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### Figure 2.3-8. Total Aircraft, Locomotive, and CMV PM 2.5 

### Emissions (Base F)

Figure 2.3-9. Locomotive PM 2.5 

### Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 172 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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36,126 35,132 57,062

41,284

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### Figure 2.3-10. Total Aircraft, Locomotive, and CMV SO 2 

### Emissions (Base F)

Figure 2.3-11. Locomotive SO 2 

### Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 173 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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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)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 174 

### Base G Revisions:
Table 2.3-18 shows the Base G 2002 base year em issions 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 fo recasts, 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 su ch data. However, for Base G, Kentucky regulators provided growth data for aircraft emissions associated with Cincinnati/Northern Kentucky Internati onal Airport (located in Boone County, Kentucky). These data were applied to all po llutants and all aircraft types (i.e., military aircraft (SCC 2275001000), commercial ai rcraft (SCC 2275020000), general aviation aircraft (SCC 2275050000), and air taxi airc raft (SCC 2275060000)). Em issions forecasts for all aircraft operations in counties other than Boone con tinued to utilize the growth factors developed according to the CAIR ma tching criteria. Table 2.3-19 presents the locally generated growth fact ors applied in Kentucky. It should be recognized that although the locally provided gr owth 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 (relati ve to activity in preceding years). Moreover, this downward spike seems to have been alleviated since 2002, so that the provided growth factors repr esent not only “routine” growth expected between 2002 and the two forecast years, but growth required to offset the temporary decline observed in 2002.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 175 

### Table 2.3-18. Base G 2002 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons)

Source State CO NO x PM 10 PM 2.5 SO 2 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
VA 110 313 25 23 27 48 Military Marine (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 25,401Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 176 

### 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 re port, the total number of emissions records in the Base G 2009 and 2018 forecasts incr eased to 23,042 (as compared to 22,838 for Base F). The 23,042 data records for aircra ft, 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 th e 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 associ ated change in emissions for each forecast inventory relative to the Base G 2002 base year VISTAS. As was th e case with Base F, the larger reduction in CMV SO 2 

### emissions in 2009 and 2018 (relative to 2002) for Virginia and West Virginia is notable relative to the other VISTAS States, but is attribut able to a high diesel contribution to total CMV SO 2 

### 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 wh ich presents total VISTAS region emission estimates for locomotives only. This two figure a pproach 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 em issions totals. All of the figures include the following emissions estimates:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 177 

### • The Base G 2002 base year VISTAS emissi ons inventory (labeled as “2002”),

• The pre-Base F 2002 base year VISTAS emissions inventory (labeled as “2002 Prelim”),

• The Base G 2009 VISTAS emissions inventor y developed using gr owth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2009”),

• The Base G 2018 VISTAS emissions inventor y developed using gr owth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2018”), and

• The pre-Base F 2018 VISTAS emissions inve ntory 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 methodol ogy 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).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 178 

### 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 NO x PM 10 PM 2.5 SO 2 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
VA 118 299 23 21 5 50 Military Marine (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 26,754Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 179 

### 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 NO x PM 10 PM 2.5 SO 2 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
VA 128 282 23 21 1 53 Military Marine (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 28,522Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 180 

### 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 NO x PM 10 PM 2.5 SO 2 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%
VA +7% -4% -7% -7% -83% +5% Military Marine (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%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 181 

### 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 NO x PM 10 PM 2.5 SO 2 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%
VA +17% -10% -6% -6% -98% +12% Military Marine (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%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 182 125,597 139,362 157,427

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

Figure 2.3-15. Locomotive CO Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 183 421,918 399,364 370,651 455,067

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

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2002 2009 2018 2002 Prelim 2018 Prelim T

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### Figure 2.3-16. Total Aircraft, Locomotive, and CMV NO x 

### Emissions (Base G)

Figure 2.3-17. Locomotive NO x 

### Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 184 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

2002 2009 2018 2002 Prelim 2018 Prelim T

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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 T

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### Figure 2.3-18. Total Aircraft, Locomotive, and CMV PM 10 

### Emissions (Base G)

Figure 2.3-19. Locomotive PM 10 

### Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 185 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

2002 2009 2018 2002 Prelim 2018 Prelim T

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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 T

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### Figure 2.3-20. Total Aircraft, Locomotive, and CMV PM 2.5 

### Emissions (Base G)

Figure 2.3-21. Locomotive PM 2.5 

### Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 186 52,444

35,578 34,534 57,062

41,284

0 10,000 20,000 30,000 40,000 50,000 60,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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s

p

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Y

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a

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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 T

o

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### Figure 2.3-22. Total Aircraft, Locomotive, and CMV SO 2 

### Emissions (Base G)

Figure 2.3-23. Locomotive SO 2 

### Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 187 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

2002 2009 2018 2002 Prelim 2018 Prelim T

o

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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

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

Figure 2.3-25. Locomotive VOC Emissions (Base G)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 188 

### 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 us ing a methodology identical to that employed to develop a Base G 2002 base year inventory for th e 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 st ates (in each of the two projection years) from the latest version of the EPA’s NMIM model. This includes appr opriate consideration of all non-default NMIM input files generated by the Midw est Regional Planning Organizati on as documented earlier in the discussion of the Base G 2002 base year inve ntory. 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 gaso line vapor pressure, gaso line 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 vari ations of no more that 2 oF fr om 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 re quired per season per projection year, as compared to the 53 iterations per season pe r projection year required for the VISTAS region.

As was also described in th e discussion of the Base G 2002 base year inventory, several non-default equipment population, growth, activit y, 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 fact ors were different for each type of mobile source considered, but the calculation methods were identical.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 189 

### 2.3.5 Quality Assurance steps Throughout the inventory developm ent process, quality assuran ce steps were performed to ensure that no double counting of emissions o ccurred, to ensure that a full and complete inventory was developed for VISTAS, and to ma ke sure that projecti on calculations were working correctly. Quality assurance was an impo rtant 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 we re no missing sour ces (NONROAD only).

3. Tier comparisons (by pollutant) were developed between the 2002 base year inventory and the 2009 and 2018 projecti on inventories (NONR OAD 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 repr esentatives for review and comment. Changes based on these comments were implemented in the files.

5. Version numbering was used for all i nventory 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.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 190 

### APPENDIX A:

STATE EMISSION TOTALS BY POLLUTANT AND SECTORDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.191Annual CO Emissions by Source Sector01,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,000 A L FL GA KY MS N C SC TN V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 192 

### 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 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.193Annual NH3Emissions by Source Sector050,000100,000150,000200,000250,000 AL F L GA K Y MS NC S C TN V A WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 194 

### Annual NH 3 

### 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 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.195Annual NOx Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L FL GA KY MS N C SC TN V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 196 

### Annual NO x 

### 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 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.197Annual PM10Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L FL GA KY MS N C SC TN V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 198 

### Annual PM 10 

### 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 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.199Annual PM2.5Emissions by Source Sector050,000100,000150,000200,000250,000 AL F L GA K Y MS NC S C TN V A WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 200 

### Annual PM 2.5 

### 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 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.201Annual SO2Emissions by Source Sector0100,000200,000300,000400,000500,000600,000700,000 AL F L GA K Y MS NC S C TN V A WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 202 

### Annual SO 2 

### 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 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.203Annual VOC Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,0001,400,000 A L FL GA KY MS N C SC TN V A W V

Tons per yearFIRESAREANONROADONROADNONEGUEGU2002 Actual EGU and Fires2002 Typical EGU and Fires20092018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 204 

### 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 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.205Annual CO Emissions by Source Sector01,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,000 A L FL GA K Y M S NC S C TN V A WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 206 

### 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 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.207Annual NH3Emissions by Source Sector050,000100,000150,000200,000250,000 AL FL G A KY MS N C SC T N VA WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 208 

### Annual NH 3 

### 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 N C 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 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.209Annual NOx Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 AL FL GA KY MS NC SC TN VA WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 210 

### Annual NO x 

### 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 N C 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 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.211Annual PM10Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L FL GA K Y M S NC S C TN V A WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Actual EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 212 

### Annual PM 10 

### 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 N C 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 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.213Annual PM2.5Emissions by Source Sector050,000100,000150,000200,000250,000300,000 AL FL GA KY M S NC S C TN VA WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 214 

### Annual PM 2.5 

### 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 N C 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 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.215Annual SO2Emissions by Source Sector0100,000200,000300,000400,000500,000600,000700,000800,000 AL A L A L FL FL FL GA GA GA K Y KY KY MS MS MS NC N C N C SC SC SC TN TN TN VA VA V A W V WV WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 216 

### Annual SO 2 

### 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

N C 472,192 51,049 13,343 7,207 7,096 423 2002 OTB - Typical 2002 N C 182,356 52,693 1,311 1,798 7,607 423 2009 OTB - Typical 2002 N C 132,054 52,693 1,311 1,798 7,607 423 2009 OTW - Typical 2002 N C 133,691 58,671 1,323 838 8,273 423 2018 OTB - Typical 2002 N C 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 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.217Annual VOC Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,0001,400,000 A L FL GA K Y M S NC S C TN V A WV

Tons per yearFIRESAREANONROADONROADNONEGUEGU20022009 OTB2009 OTW2018 OTB2018 OTWEGU and NonEGU values based on 2002 Typical EmissionsAll Fire emissions based on Typical Year valuesDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

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### APPENDIX B:

STATE VMT TOTALSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 24,891Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX C:

STATE TIER 1 EMISSION TOTALSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 PROCESSE S 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 & TRANSPO RT 174 0 230 1,086 636 13 16,522 AL 2002 10 WASTE DISPOSAL & RECYCL ING 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 PROCESSE S 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 & TRANSPO RT 192 0 253 1,146 584 14 17,738 AL 2009 10 WASTE DISPOSAL & RECYCL ING 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 PROCESSE S 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 & TRANSPO RT 234 0 307 1,366 699 17 18,900 AL 2018 10 WASTE DISPOSAL & RECYCL ING 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, 643 541,458 140,394 474,974 326,063Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 PROCE SSES 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 & TRANSPO RT 161 0 561 1,645 720 38 79,281 FL 2002 10 WASTE DISPOSAL & RECYCL ING 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 PROCE SSES 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 & TRANSPO RT 187 0 621 1,661 727 50 83,880 FL 2009 10 WASTE DISPOSAL & RECYCL ING 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 PROCE SSES 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 & TRANSPO RT 226 0 690 2,008 879 58 87,732 FL 2018 10 WASTE DISPOSAL & RECYCL ING 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, 023 754,381 223,592 259,739 986,760Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 PROCESSE S 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 & RECYCL ING 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 PROCESSE S 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 & RECYCL ING 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 PROCESSE S 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 & RECYCL ING 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 1,003,235 225,372 356,010 558,631Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 74,010 320,369 232,347Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 62,486 248,517Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 227 

### 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, 112 387,788 128,356 163,752 416,523Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 228 

### 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 43,446 196,081 382,244 110,019 163,509 302,665Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 229 

### 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, 619 313,294 100,592 228,116 377,408Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 230 

### 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 80,044 320,246 315,875Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 231 

### 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 PROCE SSES 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 & RECY CLING 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 PROCE SSES 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 & TRANSPO RT 17 0 3 2,062 1,003 0 12,997 WV 2009 10 WASTE DISPOSAL & RECY CLING 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 PROCE SSES 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 & TRANSPO RT 19 0 4 2,522 1,225 0 13,394 WV 2018 10 WASTE DISPOSAL & RECY CLING 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 3,873,273Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX D:

VISTAS TIER 1 EMISSION TOTALSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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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 MF G 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 MF G 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 MF G 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 3,873,273Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX E:

AIRCRAFT PM EXCERPT FR OM 2001 TUCSON REPORT

### 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 2001Emissions Inventories for the Tucson Air Planning Area

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### i Final Report —November 2001 

### 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.Emissions Inventories for the Tucson Air Planning Area

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### iii Final Report —November 2001 

### 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 ........................................................................................ 3-7Emissions Inventories for the Tucson Air Planning Area

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### iv Final Report —November 2001 

### 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 ........................................................................................ 3-26Emissions Inventories for the Tucson Air Planning Area

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### v Final Report —November 2001 

### 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........................ 4-88Emissions Inventories for the Tucson Air Planning Area

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### vi Final Report —November 2001 

### 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..................................................................................................... 7-1Emissions Inventories for the Tucson Air Planning Area

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### vii Final Report —November 2001 

### 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-1Emissions Inventories for the Tucson Air Planning Area

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### viii Final Report —November 2001 

### 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)..... 3-23Emissions Inventories for the Tucson Air Planning Area

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### ix Final Report —November 2001 

### 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)........................................................................... 4-26Emissions Inventories for the Tucson Air Planning Area

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### x Final Report —November 2001 

### 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) ................................................................ 4-72Emissions Inventories for the Tucson Air Planning Area

Tucson Aircraft PM.doc 

### xi Final Report —November 2001 

### 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........................................... 4-100Emissions Inventories for the Tucson Air Planning Area

Tucson Aircraft PM.doc 

### xii Final Report —November 2001 

### 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)...................................................................................... 4-126Emissions Inventories for the Tucson Air Planning Area

Tucson Aircraft PM.doc 

### xiii Final Report —November 2001 

### 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 22 nd 

### 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 .......... 6-8Emissions Inventories for the Tucson Air Planning Area

Tucson Aircraft PM.doc 

### xiv Final Report —November 2001 

### 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 (CH 2 

### ═ CH 2 

### )
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 (CH 2 

### ═ O)
GA General Aviation GIS Geographical Information System GSE Ground Support Equipment ICAO International Civil Aviation OrganizationEmissions Inventories for the Tucson Air Planning Area

Tucson Aircraft PM.doc 

### xv Final Report —November 2001 

### 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
NO 2 

### Nitrogen Dioxide
NO X 

### 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

PM 2.5 

### Particulate Matter less than 2.5 microns

PM 10 

### 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
SO 2 

### Sulfur Dioxide
SO X 

### Oxides of Sulfur TAF Temporal Allocation FactorEmissions Inventories for the Tucson Air Planning Area

Tucson Aircraft PM.doc 

### xvi Final Report —November 2001 

### 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 (C 6 

### H 5 

### —CH 3 

### ) 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 (C 6 

### H 6 

### —(CH 3 

### ) 2 

### )Emissions Inventories for the Tucson Air Planning Area

PAGf-Sect4.doc 

### 4-40 Final Report – November 2001 

### (Prior material unrelated to VISTAS modeling is intentionally omitted)

While emission rates for HC, CO, and NO x 

### 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 NO x 

### 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.Emissions Inventories for the Tucson Air Planning Area

PAGf-Sect4.doc 

### 4-41 Final Report – November 2001 

### 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 NO x 

### ) 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 NO x 

### 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 NO x 

### 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-NO x 

### regression developed for the takeoff mode. These four relations were used to develop a set of fleetwide PM emission factors based on measured takeoff

NO x 

### 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.Emissions Inventories for the Tucson Air Planning Area

PAGf-Sect4.doc 

### 4-42 Final Report – November 2001 

### 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 NO x 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 NO x 

### (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 NO x , the equation for which is:

Takeoff PM = 28.42 (1/Takeoff NO x )Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 235 

### APPENDIX F:

COMPARISON OF BASE F AND BASE G ON-ROAD MOBILE EMISSIONSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.236Base G Onroad Mobile Emissions (Annual Tons)FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 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 3,1362,193 2,768 2,010 1,085 5,530 6,298 6,630FL 520,757 336,707 199,050 460,503 312,321136,040 4,493,820 3,308,863 2,263,19020,687 2,584 2,302 11,148 9,801 7,516 7,779 6,104 3,671 17,922 21,549 23,778GA 279,975 192,773 99,464 304,309 207,02492,113 2,699,650 1,956,263 1,303,52912,043 1,568 1,325 7,165 6,005 4,406 5,110 3,797 2,166 10,436 12,55413,511KY 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 2,9442,348 2,667 1,899 1,158 5,003 5,737 7,095MS 86,811 51,600 28,699 110,672 69,952 27,620 853,774 602,257 394,247 4,566 532 401 2,828 2,2501,479 2,089 1,491 746 3,549 3,995 4,147NC 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 3,9944,571 3,453 1,931 9,601 11,702 12,776SC 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 2,8311,986 2,473 1,834 988 4,646 5,466 5,878TN 177,943 114,032 61,339 235,869 150,17962,446 1,893,704 1,320,562 863,682 9,127 1,065 862 5,312 4,160 2,813 3,904 2,720 1,405 6,556 7,702 8,196VA 157,989 95,694 55,992 219,835 132,69957,192 2,136,288 1,435,359 954,463 8,196 1,067 949 4,499 3,706 2,922 3,067 2,216 1,404 7,770 8,990 9,653WV 41,703 24,570 14,652 58,340 35,234 15,530526,841 360,865 243,683 2,438 276 231 1,3661,057 747 984 676 369 1,889 2,126 2,268VISTAS 1,869,063 1,203,208 680,0962,163,168 1,398,879 599,336 19,187,61313,682,570 9,124,656 88,316 10,844 9,348 49,780 41,400 30,403 35,411 26,200 14,922 72,902 86,118 93,932Base F Onroad Mobile (Annual Tons)FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 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 3,1952,488 2,799 2,053 1,262 5,586 6,362 7,296FL 438,761 293,423 192,096 402,099 284,737134,465 4,022,000 3,090,443 2,306,75918,802 1,911 2,289 10,185 9,027 7,691 7,126 5,653 3,848 16,183 19,553 23,595GA 265,972 187,102 104,678 306,998 208,568100,707 2,712,473 2,044,169 1,474,02912,182 1,256 1,458 7,252 6,116 4,995 5,169 3,877 2,517 10,545 12,685 14,870KY 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 3,0082,283 2,699 1,946 1,160 5,055 5,807 6,584MS 81,701 49,986 30,337 110,242 69,949 29,829 849,049 624,575 445,150 4,614 398 441 2,863 2,2961,688 2,114 1,525 876 3,585 4,035 4,565NC 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 4,2994,754 3,651 2,158 9,711 12,663 13,077SC 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 2,8842,258 2,502 1,874 1,154 4,694 5,522 6,472TN 168,389 109,716 63,916 233,324 147,59166,879 1,881,893 1,359,880 961,929 9,202 833 944 5,349 4,247 3,199 3,9272,788 1,643 6,629 7,753 8,962VA 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 2,258 1,641 7,852 9,084 10,757WV 39,581 23,914 15,375 60,335 36,000 16,940533,258 379,272 273,900 2,495 228 255 1,399 1,099 844 1,005 705 428 1,938 2,188 2,484VISTAS 1,733,382 1,128,638 683,9422,077,822 1,378,416 628,551 18,389,31213,961,764 9,801,505 85,868 8,622 9,783 49,414 41,513 33,086 35,191 26,330 16,687 71,778 85,652 98,664Emissions Change (Base G - Base F, Annual Tons) -- Positive Value Indicates Increase from Base FFIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 6,789 2,928 -2,647 -1,166 -606 -3,977 2,754 -31,973 -81,178 -71 165 -66 -45 -58 -295 -31 -43 -178 -56 -63 -666FL 81,997 43,284 6,955 58,404 27,584 1,575471,820 218,420 -43,569 1,885 672 14 963774 -175 653 451 -177 1,738 1,996 183GA 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 -80 -352 -109 -131 -1,359KY 6,160 9,933 3,996 541 2,294 3,979 18,534 18,615 41,319 250 164 43 -46 -65 65 -32 -47 -2 -52 -70 512MS 5,110 1,613 -1,638 430 3 -2,209 4,724 -22,319 -50,903 -48 134 -41 -35 -46 -209 -25 -34 -130 -35 -40 -419NC -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 -198 -226 -111 -961 -302SC 7,625 2,755 -2,255 -462 -362 -3,293 5,731 -42,483 -75,061 -63 156 -59 -40 -53 -272 -29 -40 -166 -48 -56 -594TN 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 -68 -238 -73 -52 -766VA 14,020 4,464 -3,744 -2,995 -340 -6,887 140,001 -47,766 -137,084 962 165 -110 -47 -62 -420 -30 -42 -237 -83 -94 -1,104WV 2,122 656 -723 -1,995 -766 -1,410 -6,416 -18,407 -30,217 -57 49 -24 -32 -42 -97 -22 -29 -59 -49 -62 -217VISTAS 135,680 74,570 -3,846 85,346 20,462 -29,215798,301 -279,194 -676,850 2,448 2,222 -435 367 -114 -2,683 219 -130 -1,764 1,123 466 -4,732Emissions Change (Base G - Base F/Base F, Annual %) -- Positive Value Indicates Increase from Base FFIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 6% 4% -6% -1% -1% -9% 0% -3% -12% -1% 26% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%FL 19% 15% 4% 15% 10% 1% 12% 7% -2% 10% 35% 1% 9% 9% -2% 9% 8% -5% 11% 10% 1%GA 5% 3% -5% -1% -1% -9% 0% -4% -12% -1% 25% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%KY 6% 16% 10% 0% 2% 9% 2% 2% 6% 4% 28% 7% -1% -2% 3% -1% -2% 0% -1% -1% 8%MS 6% 3% -5% 0% 0% -7% 1% -4% -11% -1% 34% -9% -1% -2% -12% -1% -2% -15% -1% -1% -9%NC -4% -1% 5% 11% -4% -5% 6% -10% -3% -2% 13% 2% -3% -6% -7% -4% -5% -10% -1% -8% -2%SC 7% 4% -5% 0% 0% -8% 0% -5% -11% -1% 28% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%TN 6% 4% -4% 1% 2% -7% 1% -3% -10% -1% 28% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%VA 10% 5% -6% -1% 0% -11% 7% -3% -13% 13% 18% -10% -1% -2% -13% -1% -2% -14% -1% -1% -10%WV 5% 3% -5% -3% -2% -8% -1% -5% -11% -2% 21% -9% -2% -4% -12% -2% -4% -14% -3% -3% -9%VISTAS 8% 7% -1% 4% 1% -5% 4% -2% -7% 3% 26% -4% 1% 0% -8% 1% 0% -11% 2% 1% -5%VOC NOx CO SO2 PM-10 PM-2.5 NH3VOC NOx CO SO2 PM-10 PM-2.5 NH3VOC NOx CO SO2 PM-10 PM-2.5 NH3VOC NOx CO SO2 PM-10 PM-2.5 NH3Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.237Annual Onroad Emissions Comparison0100,000200,000300,000400,000500,000600,000AL FL GA KY MS NC SC TN VA WV

Annual VOC Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.238Annual Onroad Emissions Comparison050,000100,000150,000200,000250,000300,000350,000400,000450,000500,000AL FL GA KY MS NC SC TN VA WV

Annual NOx Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.239Annual Onroad Emissions Comparison05001,0001,5002,0002,5003,0003,5004,0004,5005,000AL FL GA KY MS NC SC TN VA WV

Thousands Annual CO Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.240Annual Onroad Emissions Comparison05,00010,00015,00020,00025,000AL FL GA KY MS NC SC TN VA WV

Annual SO2 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.241Annual Onroad Emissions Comparison02,0004,0006,0008,00010,00012,000AL FL GA KY MS NC SC TN VA WV

Annual PM-10 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.242Annual Onroad Emissions Comparison01,0002,0003,0004,0005,0006,0007,0008,0009,000AL FL GA KY MS NC SC TN VA WV

Annual PM-2.5 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.243Annual Onroad Emissions Comparison05,00010,00015,00020,00025,000AL FL GA KY MS NC SC TN VA WV

Annual NH3 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseF