west virginia department of environmental protection



# Appendix D Emissions Inventory Preparation and Results

Promoting a healthy environment.

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# Contents

Appendix D.1. VISTAS Emissions Inventory Documentation

Appendix D.1.a. Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 version), Pechan

Appendix D.1.b. Documentation of the Base G 2002 Base Year, 2009 and 2018 Emissions Inventory for VISTAS, MACTEC, Inc.

Appendix D.1.c. Memorandum to VISTAS Stat e Point Contacts and VISTAS EGU Special Interest Workgroup, from Gregory Stella, June 13, 2005 Appendix D.1.

Appendix D.2. Emission Inventory Summaries

Appendix D.2.a. VISTAS State Totals

Appendix D.2.b. West Virginia County Totals

Appendix D.3. Emissions Inventory

Appendix D.3.a. Point Source Emissions Inventory

Appendix D.3.b. Area Source Emission Inventory

Appendix D.3.c. Non-Road Mobile Source Emission Inventory

Appendix D.3.d. On-Road Mobile Source Emission Inventory

Appendix D.4. Emissions Modeling Documentation

Appendix D.4.a. SMOKE - Emissions Modeling Documentation

Appendix D.4.b. Temporal Profile Development for Electric Generating Units

Appendix D.4.c. White Paper on Mobile Source SMOKE Modeling

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# Appendix D.1 VISTAS Emissions Inventory Documentation

Promoting a healthy environment.

### [This page intentionally left blank.]west virginia department of environmental protection



# Appendix D.1.a Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 version), Pechan

Promoting a healthy environment.

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# PECHAN

5528-B Hempstead Way Springfield, VA 22151

703-813-6700 telephone 703-813-6729 facsimile

3622 Lyckan Parkway Suite 2002 Durham, NC 27707

919-493-3144 telephone 919-493-3182 facsimile

P.O. Box 1345 El Dorado, CA 95623

530-295-2995 telephone 530-295-2999 facsimile 

# Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version)

Prepared for:

VISTAS 59 Woodfin Place Asheville, NC 28801

Prepared by:

Maureen A. Mullen Kirstin B. Thesing E.H. Pechan & Associates, Inc. 5528-B Hempstead Way Springfield, VA 22151

February 9, 2004

Pechan Rpt. No. 04.01.002/9440.000

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# CONTENTS Page TABLES.........................................................................................................................

............... iv FIGURES....................................................................................................................................... v ACRONYMS AND ABBREVIATIONS.................................................................................... vi I. INTRODUCTION/BACKGROUND ................................................................................ 1 II. ONROAD METHODS AND DATA.................................................................................. 2 A. 2002 VMT DEVELOPMENT..................................................................................... 2 1. Conversion to Annual VMT................................................................................. 2 2. Projection to 2002................................................................................................. 3 3. Splitting VMT by Road Type............................................................................... 4 a. Allocation of VMT to Vehicle T ype using Default VMT Mix Data............. 4 b. Allocation of VMT to Vehicle Type using State-Provided VMT Mix Data . 6 c. Allocation of VMT by Month........................................................................ 6 B. 2002 ONROAD EMISSION FACTOR DE VELOPMENT USING MOBILE6.2 ..... 8 1. General MOBILE6.2 File Structure ..................................................................... 8 C. 2002 ONROAD EMISSION INVE NTORY CALCULATIONS ............................. 14 D. DATA PROVIDED BY STA TE AND LOCAL AGENCIES .................................. 14 1. Temperature........................................................................................................ 21 2. I/M and ATP Programs ...................................................................................... 21 3. RVP and Fuel Programs ..................................................................................... 21 III. NONROAD METHODS AND DATA............................................................................. 22 A. NONROAD MODEL CATEGORIES ...................................................................... 22 B. AIRCRAFT, COMMERCIAL MARINE VESSELS AND LOCOMOTIVES ........ 23 2. CMV Improvements........................................................................................... 28 a. Current Allocation Method.......................................................................... 28 b. Revised Port Allocation Method.................................................................. 29 3. Projection Methods............................................................................................. 40 IV. ONROAD REFUELING METHODS............................................................................. 42 A. CONTROLS .............................................................................................................. 42 B. METHODS................................................................................................................ 43 V. NONROAD REFUELING METHODS.......................................................................... 44 VI. SUMMARY OF RESULTS.............................................................................................. 45 A. ONROAD RESULTS................................................................................................ 45 B. NONROAD RESULTS............................................................................................. 47 VII. OBSERVATIONS AND RECOMMENDATIONS FOR IMPROVEMENT.............. 51 A. ONROAD SECTOR IMPROVEMENTS ................................................................. 51 B. NONROAD SECTOR IMPROVEMENTS .............................................................. 52 VIII. REFERENCES .................................................................................................................. 52

# TABLES

Table II-1. VMT Data Provide d by State/Local Agencies ............................................................ 3 Table II-2. VMT Growth Factors Used for Virginia ..................................................................... 4 Table II-3. Allocation of VMT from HPMS Vehi cle Categories to MOBILE6 Vehicle Types for 2001........................................................................................................................... ................ 5 Table II-4. Default VMT Seasonal and M onthly Temporal Allocation Factors............................ 7 Table II-5. Default Speeds Modeled by Road Type and Vehicle Type....................................... 13 Table II-6. Summary of Onroad Data Provided by Alabama ...................................................... 15 Table II-7. Summary of Onroad Data Provided by Florida......................................................... 15 Table II-8. Summary of Onroad Data Provided by Georgia........................................................ 16 Table II-9. Summary of Onroad Data Provided by Kentucky..................................................... 17 Table II-10. Summary of Onroad Data Provided by Mississippi ................................................ 18 Table II-11. Summary of Onroad Data Provided by North Carolina .......................................... 18 Table II-12. Summary of Onroad Data Provided by South Carolina .......................................... 19 Table II-13. Summary of Onroad Data Provided by Tennessee.................................................. 19 Table II-14. Summary of Onroad Data Provided by Virginia ..................................................... 20 Table II-15. Summary of Onroad Data Provided by West Virginia............................................ 20 Table III-1. Summary of Comments by S/L/ T Agencies on NONROAD Model Input Values Distributed in July 2003....................................................................................................... ... 22 Table III-2. Summary of S/L/T Agency Data In corporated into the Draft VISTAS 2002 Other Nonroad Inventory.................................................................................................................. 23 Table III-3a. Replacement Procedures for 1999 Locomotive Emissions for Pickens and Tuscaloosa County, Alabama ................................................................................................. 24 Table III-3b. Replacement Procedures for 1999 Aircraft, Locomotive, and Commercial Marine Vessel Emissions for Palm Beach County, Florida ................................................................ 25 Table III-3c. Replacement Procedures for 1999 Aircraft and Locomotive Emissions for Davidson County, Tennessee.................................................................................................. 26 Table III-3d. Replacement Procedures for 1999 Aircraft, Locomotive, and Commercial Marine Vessel Emissions for Sample Counties in Virginia ................................................................ 27 Table III-4. Port Areas Located in VISTAS and Adjoining States.............................................. 32 Table III-5. List of VISTAS Port s and Ports of Adjoining States ............................................... 33 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce ............................ 36 Table III-7a. Growth Factors for Ra ilroad Distillate Fuel Oil Use.............................................. 40 Table III-7b. 2002 National Rail Trans portation Energy Use by Fuel Type............................... 41 Table III-8. Growth Factors for Commercial Marine Vessel Distillate and Residual Fuel Oil Use ....................................................................................................................... ............. 42 Table IV-1. Onroad Stage II Control Programs........................................................................... 43 Table V-1. 2002 Draft Stage II Re fueling Emissions by State.................................................... 45 Table VI-1. 2002 VISTAS Onroad Emissions and VMT by State.............................................. 46 Table VI-2. 1999 NEI Version 2 Onro ad Emissions and VMT by State .................................... 46 Table VI-3. Change in Onroad Emissions and VMT from 1999 NEI Version 2 to VISTAS 2002 Inventory...................................................................................................................... ........... 47 Table VI-4. 2002 VISTAS Annual Onroad Refueling Emissions............................................... 47 Table VI-5. Summary of Dr aft 2002 Nonroad Sector Annua l Emissions by State ..................... 48 Table VI-6. Summary of Dr aft 2002 NONROAD Model Emission Estimates by State............. 49

### Table VI-7. Summary of Dr aft 2002 Other Nonroad* Emission Estimates by State.................. 50



# FIGURES

Figure II-1. Header Section of MOBILE6.2 Input File Including VOC Exhaust and PM 10 

### Emission Factors............................................................................................................... .............. 9 Figure II-2. Header Section of MOBILE6.2 Input File Including VOC Evaporative and PM 2.5 

### Emission Factors............................................................................................................... .............. 9 Figure II-3. Run Data Secti on of a MOBILE6.2 Input File......................................................... 10 Figure II-4. Run Data Section of a MOBILE6.2 Input File with Significant Local Inputs......... 10 Figure II-5. Sample Scenario fo r a Typical MOBILE6.2 Input File ........................................... 12 Figure III-1. VISTAS Re gion and Surrounding States, Underway NO x 

### Emissions ................... 30 Figure III-2. VISTAS Re gion and Surrounding States, Port NO x 

### Emissions ............................. 31 Figure III-3. VISTAS Region and Surrounding States, Revised Port Emissions of NO X 

### ............ 35

# ACRONYMS AND ABBREVIATIONS

ATADS Air Traffic Activity Data System ATP anti-tampering program BTS Bureau of Transportation Statistics BTU British thermal unit CMV commercial marine vessels CNG compressed natural gas CO carbon monoxide DOT Department of Transportation EIA Energy Information Administration EPA U.S. Environmental Protection Agency FHWA Federal Highway Administration FIPS Federal Information Processing Standards GF growth factor HDDV heavy-duty diesel vehicle HDGV heavy-duty gasoline vehicle HPMS Highway Performance Monitoring System I/M inspection and maintenance LDDT light-duty diesel truck LDDV light-duty diesel vehicle LDGT light-duty gasoline truck LDGV light-duty gasoline vehicle LPG liquified petroleum gas LTO landing and takeoff MC motorcycle mg milligram NAPAP National Acid Precipitation Assessment Program NEI National Emission Inventory NH 3 

### ammonia NO x 

### oxides of nitrogen OTAQ Office of Transportation and Air Quality Pechan E.H. Pechan & Associates, Inc. PM 2.5 

### particulate matter with an aerodynamic diameter less than or equal to 2.5 micrometers PM 10 

### particulate matter with an aerodynamic diameter less than or equal to 10 micrometers ppmv parts per million volume RFG reformulated gasoline RVP Reid vapor pressure SCC source classification code S/L/T State/Local/Tribal SO 2 

### sulfur dioxide USACE U.S. Army Corps of Engineers VISTAS Visibility Improvement-State and Tribal Association of the Southeast VMT vehicle miles traveled VOC volatile organic compound

### 1 

## I. INTRODUCTION/BACKGROUND

The Visibility Improvement – State and Tribal Association of the Southeast (VISTAS) has contracted with E.H. Pechan & Associates, Inc. (Pechan) to prepare a 2002 mobile source emissions inventory. The purpose of this emi ssions inventory is to support the modeling and assessment of speciated particulate matter with an aerodynamic diameter less than or equal to 2.5 micrometers (PM 2.5 

### ). Through this contract, Pechan first prepared an inventory review document. This document summarized several regional and national emission inventory efforts and identified strengths and weaknesses associated with the use of these inventories in regional haze modeling. This document also summarized data submittals by State and local air agencies within the VISTAS region that could be used in the VISTAS 2002 mobile source emissions inventory.
Since that time, the State and local air agencies have updated their submittals for the mobile source sectors, including both onroad vehicles a nd nonroad engines. In July of 2003, Pechan delivered sets of inputs to the NONROAD model option files and MOBILE6.2 input files and vehicle miles traveled (VMT) data for each State and local agency to review. For the onroad sector, the MOBILE6.2 input files and VMT data represented Pechan’s processing of the State and local inputs in a consistent manner for use in calculating the 2002 onroad emissions inventory. The MOBILE6.2 input files and VMT data included as much of the local data supplied by the State and local agencies as possible, with missing information filled in with appropriate default data. The data delivered by Pechan for the State and local agencies to review related to the nonroad sector was primarily in the form of temperature and fuel data that would be used as inputs to the NONROAD model. It should be noted that the nonroad sector inputs were completed first and did not include some of the later temperature and fuel updates that did get incorporated in the onroad data.
The State and local agencies were given a brief period to review, comment upon, and make updated submittals to the onroad and nonroad inputs that were delivered in July 2003. After receiving these comments and updated data, Pechan updated the appropriate MOBILE6.2 input files, VMT data, and nonroad inputs with the revised State and local data. Pechan then calculated 2002 onroad and nonroad emissions from these inputs. Pechan presented the preliminary results of these emission inventories at a VISTAS meeting on August 28, 2003. These draft August 2003 emission estimates, including inputs and methodology, were documented in a draft report circulated to VISTAS in October 2003. This October 2003 report also included documentation of draft 2002 refueli ng emissions from onroad and nonroad sources. The VISTAS States were asked to review this document, as well as the supporting files provided by Pechan, and provide comments or revisions by December 2003. Onroad and nonroad 2002 emissions for the VISTAS States have since been calculated based on the updates provided by the States. This report documents the inputs and methodologies used in the February 2004 version of the VISTAS 2002 onroad and nonroad mobile source emission inventories.

### 2 

## II. ONROAD METHODS AND DATA

A. 2002 VMT DEVELOPMENT

Table II-1 summarizes the type of VMT data submitted by each agency. Depending upon the data submitted by the individual State or agency, up to three different procedures were performed on the data. First, VMT data that were not provided at the annual level were converted from daily VMT to annual VMT. Second, VMT provided for years other than 2002 were grown from the base year provided. Fina lly, the VMT were allocated by vehicle type, if not already at that level of detail. The section discusses each of these procedures in more detail.
It should be noted that although the format a nd content of the VMT provided by the VISTAS State and Local agencies varied significantly fr om agency to agency, this draft 2002 VISTAS inventory is based at a minimum on county/ro adway type specific VMT, as provided by the individual agencies. This is a significant improvement over the spatial allocation methods used in the U.S. Environmental Protection Agency’s (EPA’s) National Emission Inventory (NEI) for onroad vehicles.

1. Conversion to Annual VMT
For use in the emission calculations, Pechan’s ultimate goal with the VMT data was to develop an annual 2002 VMT database by county, roadway type , and vehicle type. As indicated in Table II-1, the VMT data were submitted using three different time periods: annual, average annual day, and summer day. No temporal adjustments were applied to VMT data submitted as annual VMT. VMT data submitted as average annual day VMT were multiplied by 365 to convert from an average day to the annual time period. The Jefferson County, Kentucky VMT were submitted as summer day VMT. All annual VMT values were converted to units of millions of miles per year. Therefore, any VMT values submitted as miles were divided by a factor of 1,000,000 and VMT values submitted in units of 1,000 miles were divided by a factor of 1,000.
The Jefferson County, Kentucky VMT submittal included a single factor for converting the summer day VMT to average annual day VMT. Thus, the Jefferson County summer day VMT data were first multiplied by a factor of 0.97752 (the temporal conversion factor provided by Jefferson County) to obtain average annual day VMT. The VMT data were then multiplied by 365 to obtain the annual VMT.

### 3 Table II-1. VMT Data Provided by State/Local Agencies

State/Area Time Period 2002 Actual VMT by County/Road Type/Vehicle Type 2002 Actual VMT by County/Road Type 2002 Projected VMT by County/Road Type 2002 VMT from TDM by County/Road Type/Vehicle Type 1999 Actual VMT by County/Road Type/Vehicle Type

Alabama AAD X

Florida AAD X
Georgia AAD X
Kentucky AAD X Jefferson County, KY SD X

Mississippi ANN X

North Carolina AAD X

South Carolina ANN X

Tennessee AAD X
Virginia ANN X
West Virginia ANN X X
Time Period Codes: AAD=Average Annual Day, SD=Summer Day, ANN=Annual



### 2. Projection to 2002
As indicated in Table II-1, the Virginia VMT submittal was for a base year of 1999 rather than 2002. Thus, these VMT data needed to be projected to 2002 before calculating emissions. For Virginia, growth factors were developed by roadway type for the period from 1999 to 2001 based on historical VMT data by roadway type fr om Table VM-2 “Functional System Travel” in DOT’s Highway Statistics series (DOT, 1999 and 2001). The growth factors, presented in Table II-2, were calculated by dividing Virginia’s 2001 VMT for each of the 12 roadway types from Highway Statistics 2001 by the corresponding 1999 VMT from Highway Statistics 1999 . For the period from 2001 to 2002, the growth factors were developed using data obtained from the U.S. Department of Transportation’s Traffic Volu me Trends report (DOT, 2002). This monthly publication provides a comparison of preliminary 2002 VMT estimates with comparable 2001 VMT. For several roadway types, these data are provided only at a national level. However, for the combined rural interstates and arterials, these data are presented by State. The resultant data, used to project the 2001 Virginia VMT to 2002, are shown in Table II-2. The 2001 to 2002 growth factors represent the 2002 VMT divided by the 2001 VMT, based on the data Virginia for the rural interstates and arterials and on the national data for the remaining roadway types. Once the growth factors were developed, the Virginia 1999 VMT data were first multiplied by the appropriate 1999 to 2001 growth factor and then by the appropriate 2001 to 2002 growth factor.

### 4 Table II-2. VMT Growth Factors Used for Virginia

Roadway Type Roadway Type Portion of SCC Virginia 1999 to 2001 VMT Growth Factor Virginia 2001 to 2002 VMT Growth Factor Rural Interstate 110 1.043 1.035 Rural Other Principal Arterial 130 1.050 1.035 Rural Major Arterial 150 1.130 1.035 Rural Major Collector 170 0.982 1.011 Rural Minor Collector 190 1.032 1.011 Rural Local 210 0.923 1.011 Urban Interstate 230 1.050 1.024 Urban Other Freeway & Expressway 250 0.984 1.011 Urban Other Principal Arterial 270 1.061 1.011 Urban Minor Arterial 290 0.991 1.011 Urban Collector 310 0.925 1.013 Urban Local 330 0.690 1.013
Sources: U.S. Department of Transportation, Feder al Highway Administration, “Traffic Volume Trends, December 2002”, (http:// www.fhwa.dot.gov/ohi m/tvtw/tvtpage.htm); Highway Statistics 1999 , and Highway Statistics 2001 (http://www.fhwa.dot.gov/policy/ohpi/hss/hsspubs.htm)



### 3. Splitting VMT by Road Type
The final step in developing a consistent 2002 VMT data base was to allocate VMT from the county and roadway type level of detail to the county/roadway type/vehicle type level of detail. As shown in Table II-1, the Jefferson County, Kentucky; Mississippi; Virginia; and West Virginia VMT data supplied for these jurisdictions already included the vehicle type level of detail, so this final adjustment was not needed for these areas. For the remaining areas, some provided VMT mix by vehicle type fractions while others provided no information on the allocation of VMT by vehicle. In this latter case, default VMT fraction data from EPA’s MOBILE6 model were used.

The States for which MOBILE6 default VMT mix data were used are: Alabama, Florida, Georgia, Kentucky (excluding Boone County, Campbell County, Kenton County, and Jefferson County), and South Carolina. It should be noted that Georgia initially provided VMT fractions based on Georgia's HPMS classification count data, but after review of ten years of these data determined that they are not reflecting the trend towards increasing travel by light trucks. Georgia therefore decided it was more conservative to assume MOBILE6 default VMT fractions.
a. Allocation of VMT to Vehicle Type using Default VMT Mix Data
To calculate 2002 VMT at the county/roadway type/vehicle type level using national default data, the VMT totals by county and roadway type need to be allocated among the 28 MOBILE6 vehicle types. This was done based on the distribution of the 2001 rural and urban VMT among the six Highway Performance Monitoring System s (HPMS) vehicle types found in Table VM-1 (“Annual Vehicle Distance Traveled in Miles and Related Data - 1999 - by Highway Category and Vehicle Type”) of the Federal Highway Administration’s (FHWA’s) Highway Statistics

### 5 2001 ( http://www.fhwa.dot.gov/ohim/ hs01/index.htm) and a mapping of these HPMS vehicle categories to the 28 MOBILE6 vehicle types. This mapping of the MOBILE6 vehicle types to the HPMS vehicle types was developed by EPA’s Office of Transportation and Air Quality (OTAQ) and is used in the development of the NEI. The data first needed to be expanded to the 28 vehicle type level of detail to obtain the proper cross reference between the HPMS and MOBILE6 vehicle types since the eight vehicle t ypes used in the final VISTAS VMT data base cannot be directly mapped to the HPMS vehicle categories. First, the VMT totals for each of the six HPMS vehicle categories were calculated as a fraction of the total VMT. This calculation was performed separately for the rural VMT and the urban VMT. The resulting 2001 VMT fractions for rural VMT and urban VMT are shown in Table II-3. Note that 2002 VMT are not yet available at this level of detail. Using the default MOBILE6 VMT fractions for 2001 (since the HPMS data represents 2001), taken from a MOBILE6 output file for 2001, the MOBILE6 VMT fractions were renormalized among all MOBILE6 vehicle types mapped to a given HPMS vehicle category. This renormalization is shown in the final column of Table II-3.

Table II-3. Allocation of VMT fr om HPMS Vehicle Categories to MOBILE6 Vehicle Types for 2001

HPMS Vehicle Category HPMS 2001 Rural VMT Fractions HPMS 2001 Urban VMT Fractions MOBILE6 Vehicle Category MOBILE6 2001 VMT Fractions by

HPMS Category Passenger Cars 0.5454 0.6065 LDGV 0.9980 LDDV 0.0020 Motorcycles 0.0039 0.0031 MC 1.0000 Other 2-Axle 4-Tire Vehicles 0.3368 0.3375 LDGT1 0.1565 LDGT2 0.5211 LDGT3 0.1585 LDGT4 0.0729 LDDT12 0.0005 LDDT34 0.0032 HDGV2B 0.0658 HDDV2B 0.0216 Single-Unit 2-Axle 6-Tire or More Trucks 0.0332 0.0212 HDGV3 0.0376

HDGV4 0.0206 HDGV5 0.0436 HDGV6 0.0934 HDGV7 0.0437 HDDV3 0.1023 HDDV4 0.0867 HDDV5 0.0380 HDDV6 0.2138 HDDV7 0.3205 Combination Trucks 0.0770 0.0300 HDGV8A 0.0001 HDGV8B 0.0000 HDDV8A 0.2191 HDDV8B 0.7808 Buses 0.0037 0.0017 HDGB 0.1920 HDDBT 0.3258 HDDBS 0.4822 Total 1.0000 1.0000

### 6 To calculate VMT by vehicle type, each VMT value representing a given county and road type was multiplied by the product of the HPMS VMT fraction (selected depending upon whether the road type represent VMT on rural or urban roads) and the corresponding MOBILE6 VMT fraction by HPMS category. This process resulted in 28 VMT values at the county/roadway type/vehicle type level of detail for each county/roadway type VMT value in the original VMT file.
As an example, Table II-3 shows that the HPMS Passenger Car vehicle category accounts for 54.54 percent of the total VMT on rural road types and that the MOBILE6 LDGV category accounts for 99.8 percent of the VMT in the HPMS Passenger Car category. Therefore, a VMT value representing rural interstates would be multiplied by 0.5454 times 0.9980 (0.5443), to obtain the VMT total on rural interstates from LDGVs. Once all county/roadway type VMT values were expanded to the corresponding set of values of VMT at the county/roadway type/28 MOBILE6 vehicle type level of detail, the VMT da ta base was then totaled at the eight vehicle type level of detail (LDGV, LDGT1, LDGT2, HDGV, LDDV, LDDT, HDDV, MC).
b. Allocation of VMT to Vehicle Type using State-Provided VMT Mix Data
Both North Carolina and Tennessee provided VMT mix data at the eight vehicle type level of detail. The Tennessee data was provided for ten different county groupings, with a VMT mix provided for six aggregated roadway type categories. North Carolina provided statewide VMT mix fractions for each of the 12 roadway types. Since the VMT mix data for these two States were already at the eight vehicle type level, the procedure for allocating VMT by vehicle type was simpler than the procedure described above using the default data. Each county/roadway type VMT value was matched to the corresponding VMT mix for that county and roadway type and then separately multiplied by each of the eight VMT mix fractions to create eight VMT values by county/roadway type/vehicle type that would sum to the original VMT value at the county/roadway type level of detail.
c. Allocation of VMT by Month
The resulting annual county-level, vehicle, and roadway type-specific VMT data were temporally allocated to months during the emission calculations. National Acid Precipitation Assessment Program (NAPAP) temporal allocation factors were used to apportion the VMT to the four seasons. Monthly VMT data were obtained using a ratio between the number of days in a month and the number of days in the corresponding season. These temporal factors are shown in Table II-4. Several States provided some leve l of information on temporal adjustment factors for their VMT. These data were not used in this draft version of the 2002 VISTAS emission inventory due to time constraints. However, a ny State or locally supplied temporal adjustment factors will be included in the final versi on of the 2002 VISTAS onroad emission inventory.7Table II-4. Default VMT Seasonal and Monthly Temporal Allocation FactorsRoadway Seasonal VMT FactorsVehicle Type Roadway Type Winter Spring Summer FallLDV,LDT,MC Rural0.2160 0.2390 0.2890 0.2560LDV,LDT,MC Urban0.2340 0.2550 0.2650 0.2450HDV All 0.2500 0.2500 0.2500 0.2500Monthly VMT FactorsVehicle Type Roadway Type Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecLDV,LDT,MC Rural 0.0744 0.0672 0.0805 0.07790.0805 0.0942 0.0974 0.09740.0844 0.0872 0.0844 0.0744LDV,LDT,MC Urban 0.0806 0.0728 0.0859 0.0832 0.08590.0864 0.0893 0.0893 0.0808 0.0835 0.0808 0.0806HDV All 0.0861 0.0778 0.08420.0815 0.0842 0.0815 0.0842 0.0842 0.0842 0.0852 0.0824 0.0861

### 8 

## B. 2002 ONROAD EMISSION FACTOR DEVELOPMENT USING MOBILE6.2

The onroad emission factors used in the calculation of the VISTAS 2002 onroad emission inventory were generated using EPA’s MOBILE6.2 emission factor model. In the development of the MOBILE6.2 input files, Pechan attempted to include as much of the relevant data supplied by the State and local agencies as possible, while at the same time, maintaining a generally similar overall structure to the MOBILE6.2 input files, such that the output emission factors could easily be matched to the appropriate VMT values. This section first discusses the overall general structure of the MOBILE6.2 input files. This is followed by details explaining how this general structure was adapted to include the State and local agency data and summaries of the types of data provided by each agency.

1. General MOBILE6.2 File Structure
Each MOBILE6.2 input file is divided into three sections: the header section, the run data section, and the scenario section. Information contained in the header section is primarily related to defining the output format and content desired by the user. For the processing of the VISTAS emission calculations, the database output format, aggregated to the daily level, was the desired output format. In addition, for proper modeling of the VOC emissions, it was desired to calculate the exhaust VOC emissions separately from the evaporative VOC emissions. However, within the constraints of MOBILE6.2 in the daily aggregated database output format, it is not possible to obtain evaporative and exhaust VOC emission factors broken out separately within each scenario. It is also not possibl e to obtain emission factors for both PM 10 

### and PM 2.5 

### within a single MOBILE6.2 scenario. Therefore, two sets of MOBILE6.2 input files were created—one set to model VOC exhaust, NO x 

### , CO, SO 2 

### , PM 10 

### , and NH 3 

### emission factors and a second set to model VOC evaporative and PM 2.5 

### emission factors. Figure II-1 illustrates the header section of a sample VISTAS MOBILE6.2 input file used to generate the VOC exhaust, NO x 

### , CO, SO 2 

### , PM 10 

### , and NH 3 

### emission factors. Similarly, Figure II-2 illustrates the header section of a sample VISTAS MOBILE6.2 input file used to generate the VOC evaporative and PM 2.5 

### emission factors. The primary difference between these tw o header sections is in the selection of the emission types included, using the DATABASE EMISSIONS command and in the selection of the pollutants to be included in the output. In Figure II-1, having the first two flags set to “2” following the DATABASE EMISSIONS command i ndicates that the startup and running exhaust emission factor components will be included in the output emission factor table. In Figure II-2, the last six flags of the DATABASE EMISSIONS command line are set to “2” to obtain the evaporative emission factor components in the emission factor output file. In Figure II-2, the pollutants SO 2 

### and NH 3 

### are eliminated from the PARTICULATES command line, as the emission factors for these pollutants will be reported in the output file resulting from the file shown in Figure II-1.

### 9 MOBILE6 INPUT FILE : > HEADER 01 0012002 - EXHAUST - PM 10.0

REPORT FILE : Vistas02/Output02/V0100110.TXT REPLACE DATABASE OUTPUT : WITH FIELDNAMES : DAILY OUTPUT : DATABASE EMISSIONS : 2211 1111 PARTICULATES : SO4 OCARBON ECARBON GASPM LEAD SO2 NH3 BRAKE TIRE AGGREGATED OUTPUT : EMISSIONS TABLE : Vistas02/TB1_02/V0100110.TB1 REPLACE

MOBILE6 INPUT FILE : > HEADER 01 0012002 - EVAPORATIVE - PM 2.50

REPORT FILE : Vistas02/Output02/V0100125.TXT REPLACE DATABASE OUTPUT : WITH FIELDNAMES : DAILY OUTPUT : DATABASE EMISSIONS : 1122 2222 POLLUTANTS : HC PARTICULATES : ECARBON SO4 OCARBON GASPM LEAD BRAKE TIRE AGGREGATED OUTPUT : EMISSIONS TABLE : Vistas02/TB1_02/V0100125.TB1 REPLACE



### The next section of the MOBILE6 input files is the run data section. This section includes data that applies to all scenarios in the input file. Figure II-3 shows an example of this section for a county using default data. The only commands included in this example tell MOBILE6 that the HC emission factors should be expressed in term s of VOC and that refueling emission factors should be excluded from the output. It should be noted that refueling emissions were calculated using a separate set of input files, but were excluded from the onroad input files here since refueling emissions are included in the area sour ce inventory rather than the onroad inventory. Chapter IV discusses the onroad refueling MOBI LE6 input files and emission calculations. Comments in Figure II-3 indicate that this input file is using default registration distributions and diesel sales fractions. For any input files that represent counties for which registration distribution, diesel sales fractions, or trip length di stributions have been provided or that have an inspection and maintenance (I/M) program, anti-tampering program (ATP), or low emission vehicle program in place in 2002, additional inputs are required in the run data section of the MOBILE6.2 input file. Figure II-4 shows an example of an input file including all of these data. Some of these data inputs are included directly in the MOBILE6.2 input file, while other data are contained in external text files that are named by the commands in the run data section. For questions regarding the specifics of any of the MOBILE6 input commands listed, the MOBILE6 User’s Guide should be consulted.

Figure II-1. Header Section of MOBILE 6.2 Input File Including VOC Exhaust and PM 10 

### Emission Factors

Figure II-2. Header Section of MOBILE 6.2 Input File Including VOC Evaporative and PM 2.5 

### Emission Factors

### 10 RUN DATA :
>

EXPRESS HC AS VOC : NO REFUELING :

* MOBILE6 Default Registration Distributions Applied * MOBILE6 Default Diesel Sales Fractions Applied

RUN DATA :

>

EXPRESS HC AS VOC : NO REFUELING :

REG DIST : Vistas02\ExtFiles\R02_ARLI.RDT

* Diesel Sales Fractions Source File - E:\TrendsM6_New\Vistas02\ExtFiles\D02_ARLI.DSF DIESEL FRACTIONS : 0.0012 0.0023 0.0026 0.0027 0.0029 0.0015 0.0008 0.0011 0.0001 0.0006 0.0013 0.0015 0.0006 0.0014 0.0006 0.0099 0.0087 0.0446 0.0685 0.0857 0.1922 0.1481 0.1132 0.0959 0.0126 0.0056 0.0221 0.0167 0.0235 0.0126 0.0119 0.0206 0.0136 0.0155 0.0127 0.0246 0.0206 0.0222 0.0184 0.0227 0.0115 0.0310 0.0568 0.0508 0.1211 0.1077 0.2126 0.0711 0.0286 0.0176 0.0056 0.0221 0.0167 0.0235 0.0126 0.0119 0.0206 0.0136 0.0155 0.0127 0.0246 0.0206 0.0222 0.0184 0.0227 0.0115 0.0310 0.0568 0.0508 0.1211 0.1077 0.2126 0.0711 0.0286 0.0176 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0115 0.0111 0.0145 0.0115 0.0129 0.0096 0.0083 0.0072 0.0082 0.0124 0.0135 0.0169 0.0209 0.0256 0.0013 0.0006 0.0011 0.0001 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0126 0.0115 0.0111 0.0145 0.0115 0.0129 0.0096 0.0083 0.0072 0.0082 0.0124 0.0135 0.0169 0.0209 0.0256 0.0013 0.0006 0.0011 0.0001 0.1998 0.1998 0.1998 0.1998 0.1998 0.1998 0.1998 0.2578 0.2515 0.3263 0.2784 0.2963 0.2384 0.2058 0.1756 0.1958 0.2726 0.2743 0.3004 0.2918 0.2859 0.0138 0.0000 0.0000 0.0000 0.6774 0.6774 0.6774 0.6774 0.6774 0.6774 0.6774 0.7715 0.7910 0.8105 0.8068 0.8280 0.8477 0.7940 0.7488 0.7789 0.7842 0.6145 0.5139 0.5032 0.4277 0.0079 0.0000 0.0000 0.0001 0.8606 0.8606 0.8606 0.8606 0.8606 0.8606 0.8606 0.8473 0.8048 0.8331 0.7901 0.7316 0.7275 0.7158 0.5647 0.3178 0.2207 0.1968 0.1570 0.0738 0.0341 0.0414 0.0003 0.0000 0.0000 0.4647 0.4647 0.4647 0.4647 0.4647 0.4647 0.4647 0.4384 0.3670 0.4125 0.3462 0.2771 0.2730 0.2616 0.1543 0.0615 0.0383 0.0333 0.0255 0.0111 0.0049 0.0060 0.0000 0.0000 0.0000 0.6300 0.6300 0.6300 0.6300 0.6300 0.6300 0.6300 0.6078 0.5246 0.5767 

### Figure II-3. Run Data Secti on of a MOBILE6.2 Input File

Figure II-4. Run Data Section of a MOBI LE6.2 Input File with Significant Local Inputs

### 11 0.5289 0.5788 0.5617 0.4537 0.4216 0.4734 0.4705 0.4525 0.4310 0.3569 0.3690 0.4413 0.3094 0.1679 0.1390 0.8563 0.8563 0.8563 0.8563 0.8563 0.8563 0.8563 0.8443 0.7943 0.8266 0.7972 0.8279 0.8177 0.7440 0.7184 0.7588 0.7567 0.7431 0.7261 0.6602 0.6717 0.7344 0.6107 0.4140 0.3610 0.9992 0.9992 0.9992 0.9992 0.9992 0.9992 0.9992 0.9989 0.9987 0.9989 0.9977 0.9984 0.9982 0.9979 0.9969 0.9978 0.9980 0.9979 0.9976 0.9969 0.9978 0.9982 0.9974 0.9965 0.9964 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 1.0000 0.9585 0.9585 0.9585 0.9585 0.9585 0.9585 0.9585 0.8857 0.8525 0.8795 0.9900 0.9105 0.8760 0.7710 0.7502 0.7345 0.6733 0.5155 0.3845 0.3238 0.3260 0.2639 0.0594 0.0460 0.0291

> ANTI-TAMP PROG : E:\TrendsM6_New\Vistas02\ExtFiles\VA_ATP2002.ATP ANTI-TAMP PROG : 89 68 50 22222 21111111 1 12 098. 22112222

> Exhaust I/M - IDLE test program #1 I/M PROGRAM : 1 1983 2050 2 TRC 2500/IDLE I/M MODEL YEARS : 1 1968 1980 I/M VEHICLES : 1 22222 21111111 1 I/M STRINGENCY : 1 35.0 I/M COMPLIANCE : 1 98.0 I/M WAIVER RATES : 1 2.0 2.0

> Exhaust I/M - ASM final program #2 I/M PROGRAM : 2 1983 2050 2 TRC ASM 2525/5015 PHASE-IN I/M MODEL YEARS : 2 1981 2050 I/M VEHICLES : 2 22222 11111111 1 I/M STRINGENCY : 2 35.0 I/M COMPLIANCE : 2 98.0 I/M WAIVER RATES : 2 2.0 2.0 I/M EFFECTIVENESS : 0.94 0.94 0.94

> Exhaust I/M - IDLE test program #1 I/M PROGRAM : 3 1983 2050 2 TRC 2500/IDLE I/M MODEL YEARS : 3 1981 2050 I/M VEHICLES : 3 11111 21111111 1 I/M STRINGENCY : 3 35.0 I/M COMPLIANCE : 3 98.0 I/M WAIVER RATES : 3 2.0 2.0

> Evap I/M - Gas Cap test program #3 I/M PROGRAM : 4 1998 2050 2 TRC GC I/M MODEL YEARS : 4 1973 2050 I/M VEHICLES : 4 22222 21111111 1 I/M COMPLIANCE : 4 98.0 I/M WAIVER RATES : 4 2.0 2.0

94+ LDG IMP : Vistas02\ExtFiles\NLEVNE.D

> WeekDay Trip Length Distribution WE DA TRI LEN DI : Vistas02\ExtFiles\WeekTLD2.wdt

### 12 The third and final section of the MOBILE6.2 input files contains the scenario data. For this VISTAS inventory, each speed and road type comb ination or speed distribution were modeled in twelve consecutive scenarios representing the temperature and fuel properties applicable in each month. Thus, if a State agency supplied an average speed/road type combination for each of the 12 HPMS road categories, the corresponding MOBILE6.2 input file would have 144 scenarios. The first scenario would represent January temperature and fuel conditions at the speed and MOBILE6 roadway type for the first speed/roadway type provided (typically rural interstates). This would be followed by the February scenario modeled for the same speed and roadway type, and so on through the twelfth scenario representing December conditions for the same speed and roadway type combination.
Figure II-5 illustrates a sample scenario from one of the VISTAS MOBILE6.2 input files. This is the first scenario in the file—therefore, it represents January temperature and fuel conditions. The month of a given scenario in the VISTAS MOBILE6.2 input files can be determined by the last two digits of the SCENARIO RECORD command line. In this case, the last two digits are “01” indicating January. It should be noted that the only options for the EVALUATION MONTH command are “1” indicating January or “7 ” indicating July. For the VISTAS input files, the EVALUATION MONTH was set to “1” for all months from January through June and to 7 for months from July through December. When this flag is set to “1”, it indicates that MOBILE6 will use a January registration distribution. When the flag is set to “7”, MOBILE6 ages the registration by a half year, applying a half year of fleet turnover to the distribution. The EVALUATION MONTH setting can also affect the re ductions from reformulated gas programs. However, by including the SEASON command, as shown in Figure II-5, the EVALUATION MONTH flag setting will not affect reformulated gasoline reductions. With the SEASON flag set to “2”, winter reformulated gasoline rules will be applied in areas with a reformulated gas program modeled (using the FUEL PROGRAM command). Summer reformulated gas rules and reductions will be applied when the SEASON flag is set to “1” if reformulated gas has been modeled. In all of the VISTAS input files, the SEASON flag was included for all areas, whether or not a reformulated gasoline program was modeled. This flag has no effect when the FUEL PROGRAM command is not used. The SEASON flag was set to “1” for the months of May through September and to “2” for the remaining months.

SCENARIO RECORD : 010010215.0_M01 >FV FILE: SCENARIO: 1 CALENDAR YEAR : 2002 EVALUATION MONTH : 1 MIN/MAX TEMPERATURE: 38.0 60.0 ALTITUDE : 1 PARTICULATE EF : PMGZML.CSV PMGDR1.CSV PMGDR2.CSV PMDZML.CSV PMDDR1.CSV PMDDR2.CSV SEASON : 2 AVERAGE SPEED : 15.0 Arterial FUEL RVP : 12.5 PARTICLE SIZE : 10.0 DIESEL SULFUR : 500.0 

### Figure II-5. Sample Scenario fo r a Typical MOBI LE6.2 Input File

### 13 Local speed data were provided by the agencies in Georgia, Kentucky, North Carolina, Tennessee, and Virginia. A set of 12 monthly scenarios was developed for each speed input for these States, with one exception. The Northern Kentucky (Boone County, Campbell County, and Kenton County) and Jefferson County, Kentucky i nputs were speed distribution files, rather than average speeds by individual roadway types (one for Northern Kentucky and one for Jefferson County, Kentucky). In this case, only 12 scenarios were modeled in total in the Jefferson County and Northern Kentucky input f iles, with the Jefferson County or Northern Kentucky speed distribution referenced in each scenario, respectively. No speed information was provided for Alabama, Florida, Mississippi, South Carolina, or West Virginia. The average speeds modeled in these files were the default speeds used in the NEI. These speeds are shown in Table II-5 and vary by both roadway type a nd vehicle category. It should be noted that several agencies provided speed information for ramps. Since the VMT data file is organized by SCC and no SCC currently exists for ramp VMT, the ramp speed information could not be used directly. In some cases, the fraction of VMT occurring on ramps was provided. In these cases, this information was combined with the freeway speeds, following the guidance in the MOBILE6 user’s guide to determine the overall freeway speed including the ramp speed, at 34.6 mph (the assumed value for ramp speeds in MOBILE6), and the fraction of VMT occurring on the ramps.
Table II-5. Default Speeds Modeled by Road Type and Vehicle Type (mph)

Speed (mph) and MOBILE6 Road Type
HPMS Road Type Light Duty Vehicles Light Duty Trucks Heavy Duty Trucks Rural Interstate 60 Freeway 55 Freeway 40 Freeway Rural Principal Arterial 45 Arterial 45 Arterial 35 Arterial Rural Minor Arterial 40 Arterial 40 Arterial 30 Arterial Rural Major Collector 35 Arterial 35 Arterial 25 Arterial Rural Minor Collector 30 Arterial 30 Arterial 25 Arterial Rural Local 30 Arterial 30 Arterial 25 Arterial Urban Interstate 45 Freeway 45 Freeway 35 Freeway Urban Other Freeway and Expressway 45 Freeway 45 Freeway 35 Freeway Urban Principal Arterial 20 Arterial 20 Arterial 15 Arterial Urban Minor Arterial 20 Arterial 20 Arterial 15 Arterial Urban Collector 20 Arterial 20 Arterial 15 Arterial Urban Local Local Local Local



### Another optional input included in the scenario section of the MOBILE6 input files is the VMT mix by 16 MOBILE6 vehicle categories. These vehicle categories are based on the 28 MOBILE6 vehicle categories, but with gasoline and diesel vehicles of the same weight class combined together. When no information was provided on VMT mix, the MOBILE6 defaults were used. Local VMT mix information provided by Tennessee, Virginia, and Jefferson County, Kentucky were included in the MOBILE6.2 input files. In some cases, the same VMT mix was applied to all scenarios. In other cases, the VMT mixes were specific to roadway type, so the VMT mix would vary according to the roadway type being represented in the scenario.

### 14 

## C. 2002 ONROAD EMISSION INVENTORY CALCULATIONS

Once the MOBILE6.2 input files were set up and run through the MOBILE6.2 model, onroad emissions were calculated by multiplying the monthly VMT for a given county, roadway type, and vehicle type by the emission factor modele d for the same month, county, vehicle type and roadway type. Because the MOBILE6.2 input files were set up to create output files in the form of database tables, the output is provided by each of the 28 MOBILE6 vehicle types. Thus, the emission factors first were aggregated to the eight vehicle categories included in the VMT files. This was done using the VMT Fraction data provide d in each of the MOBILE6 output files. For each of the MOBILE6 vehicle types included in one of the eight vehicle types needed, the VMT fractions were renormalized within that category. These eight vehicle categories are sometimes referred to as the MOBILE5 vehicle categories. For example, the LDGT1 and LDGT2 MOBILE6 vehicle categories are both included in the MOBILE5 LDGT1 category. In this case, the MOBILE6 LDGT1 VMT fraction was divided by the sum of the MOBILE6 LDGT1 and LDGT2 VMT fractions. The same was done with the MOBILE6 LDGT2 VMT fraction, so that the renormalized MOBILE6 LDGT1 and LDGT2 VM T fractions should now sum to 1. Next, these normalized VMT fractions were multiplied by the corresponding MOBILE6 emission factor and all of these weighted emission factor s for a given scenario, within a MOBILE5 vehicle category were summed to obtain the weighted emission factors at the MOBILE5 vehicle category level. The VMT fractions included in the MOBILE6 output files are affected by the registration distribution, diesel sales fracti ons, and VMT mixes supplied in the MOBILE6.2 input files. Areas that used the MOBILE6 defaults for each of these inputs should all have the same VMT fractions, although even in these cases, there are two sets of VMT fractions—one for the months from January through June and another for the months July through December. This occurs due to the aging of the registration distribution caused by the use of the EVALUATION MONTH flag, as discussed above. These emi ssion factors, now at the MOBILE5 vehicle category level, were multiplied by the corresponding VMT values to obtain monthly emissions by county, roadway type, and vehicle category.



## D. DATA PROVIDED BY STATE AND LOCAL AGENCIES

The sections above describe some of the data that was supplied by the VISTAS State and local agencies for use in the development of the 2002 onroad emission inventory. Tables II-6 through II-15 summarize the data supplied by each agency in a consistent fashion. These tables primarily list the data that were actually used in this analysis. This section provides additional information on the data supplied by these agencies as well discussing why some of the data supplied could not be used.

### 15 Table II-6. Summary of Onroad Data Provided by Alabama

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Monthly Temperatures Monthl y 2002 temperatures by county RVP Data March-September RVP values Speed Data Registration Data Fuel Information I/M Program Information N/A Other



### Table II-7. Summary of Onroad Data Provided by Florida

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Supplied counties in each of 3 temperature regions Monthly Temperatures RVP Data Summer RVP values provided Speed Data Registration Data Fuel Information I/M Program Information N/A Other

### 16 Table II-8. Summary of Onroad Data Provided by Georgia

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual average annual daily VMT by county and functional classification prepared by Georgia DOT MOBILE6 Input Files Provided MOBILE6 sample input files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Monthly Temperatures RVP Data Provided summer RVP values Speed Data Provided 2002 statewi de speeds by road type (speeds based on VMT-weighted average speeds, from a 2002 loaded highway network for the 13-county Atlanta area) Registration Data Provided one MOBILE 6 registration distribution for 13- county Atlanta area and one MOBILE6 registration distribution for rest-of-state Fuel Information Provided information on Georgia gasoline program, applied to 25 counties I/M Program Information Provided I/M inputs for 13-county Atlanta area in MOBILE6 format Other Provided VMT temporal adj ustment factors by month and day of week for each road type (not used in the 01/04 inventory)

### 17 Table II-9. Summary of Onroad Data Provided by Kentucky

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files Provided sample MO BILE6 input files for several counties MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Provided temperature stations to be used for several counties Monthly Temperatures RVP Data Provided summer RVP for several counties Speed Data Provided average speed by road type for several county groupings Registration Data Fuel Information Verified counties in reformulated gasoline program I/M Program Information I/M program information provided Other Jefferson County, Kentucky Data Element Data Supplied by Responsible Agency VMT Data 2002 summer day VMT from TD M by county/road type/vehicle type
MOBILE6 Input Files Provided MOBILE6 input files repres enting the four different vehicle control combinations found in Jefferson County MOBILE5 Input Files VMT Mix Information Provided Jefferson County VMT mix in MOBILE6 format Counties by Temperature Region Monthly Temperatures Provided 2002 actual monthly temperature data for Louisville area RVP Data Provided summer and winter RVP values Speed Data Provided speed distribution file for Jefferson County
Registration Data Provided registration distribution for Jefferson County in MOBILE6 format Fuel Information Reformulated gasoline modeled I/M Program Information I/M program information provided Other Provided absolute humidity data Boone County, Campbell County, and Kenton County, Kentucky Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files Provided MOBILE5 input file for Northern Kentucky counties VMT Mix Information Counties by Temperature Region Monthly Temperatures RVP Data Provided summer and winter RVP values Speed Data Provided speed distribution file for Northern Kentucky
Registration Data Provided registration distribution for Northern Kentucky in MOBILE6 format—LDGVs and LDGT1s only Fuel Information Reformulated gasoline modeled I/M Program Information I/M program inform ation extracted from MOBILE5 input file

Other Provided Northern Kentucky VMT di stributions by facility type and by hour in MOBILE6 format

### 18 Table II-10. Summary of Onroad Data Provided by Mississippi

Data Element Data Supplied by Responsible Agency VMT Data Provided 2002 actual annual VM T by county/road type/vehicle type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Monthly Temperatures RVP Data Provided statewide RVP by season Speed Data Registration Data Fuel Information I/M Program Information N/A Other


### Table II-11. Summary of Onroad Data Provided by North Carolina

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Indicated counties within each of several temperature regions in state Monthly Temperatures RVP Data Speed Data Provided average speed data by road type for several groups of counties and rest-of-state Registration Data Provided registration data for several groups of counties and rest-of-state based on 2001 data Fuel Information I/M Program Information Provided written description of I/M program Other

### 19 Table II-12. Summary of Onroad Data Provided by South Carolina

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual annual VMT by county/road type MOBILE6 Input Files MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Supplied counties in each of 7 temperature regions Monthly Temperatures RVP Data Speed Data Registration Data Fuel Information I/M Program Information N/A Other


### Table II-13. Summary of Onroad Data Provided by Tennessee

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual daily VMT by county/road type
MOBILE6 Input Files Provided MOBILE6 input file s for groups of counties covering state MOBILE5 Input Files VMT Mix Information Provided VMT mix fractions by road type Counties by Temperature Region Monthly Temperatures RVP Data Provided summer RVP information
Speed Data Provided average speed data by road type for groups of counties Registration Data Provided registration data for most counties Fuel Information I/M Program Information Provided in MOBILE6 input files Other

### 20 Table II-14. Summary of Onroad Data Provided by Virginia

Data Element Data Supplied by Responsible Agency VMT Data 1999 actual annual VMT by county/road type/vehicle type MOBILE6 Input Files Provided MOBILE6 i nput files for representative counties MOBILE5 Input Files VMT Mix Information Counties by Temperature Region Provided listing of counties within each of several temperature regions Monthly Temperatures RVP Data Provided summer RVP data Speed Data Speed data provided for each VMT record Registration Data 2002 county-level regi stration data provided for nonattainment counties Fuel Information Verified counties in reformulated gasoline program I/M Program Information I/M and ATP inputs prov ided in MOBILE6 formats; verified counties that implement I/M Other LEV progam modeled statewide; provided diesel sales fractions



### Table II-15. Summary of Onroad Data Provided by West Virginia

Data Element Data Supplied by Responsible Agency VMT Data 2002 actual annual VMT by county/road type/vehicle type MOBILE6 Input Files Supplied several sample MOBILE6 input files MOBILE5 Input Files VMT Mix Information VMT data included vehicle type splits Counties by Temperature Region Supplied counties in each of 4 temperature regions Monthly Temperatures RVP Data Supplied summer RVP value statewide Speed Data Supplied speed data in MOBILE6 input files--speed data determined to be inappropriate for this analysis Registration Data Fuel Information I/M Program Information N/A Other

### 21 1. Temperature
The default average daily maximum and minimum temperature data for each month used in this analysis was obtained from the National Climatic Data Center. This temperature data was actual 2002 data. It should be noted that a number of agencies provided information on ozone season or summer temperatures. This information could not be used in this analysis, as the ozone season temperature data are based on several years of temperature data and do not represent the average daily minimum and maximum monthly temperatures that were needed for this analysis. Information was provided by Alabama, Kentucky, North Carolina, South Carolina, Virginia, and West Virginia related to monthly temperature. In some cases, this data divided the counties within the State into several temperature regions and listing a city that should be used for obtaining the temperature data. In these cases, a temperature station from the National Climatic Data Center database was selected from the de sired city, and this corresponding temperature set was applied to the counties listed by the States. Several of the States provided their own full set of 2002 temperature data either Statewide or by county. These data were included in the analysis, replacing the default temperature data for those States.
2. I/M and ATP Programs
Several agencies provided I/M and ATP inputs in the form of MOBILE5 input files. Pechan converted these inputs to MOBILE6 inputs, following the guidance in the MOBILE6 user’s guide. Agencies that provided the data in MOBILE5 format should review the MOBILE6 I/M and ATP inputs carefully to make sure that the conversions fully capture the actual programs as they were implemented in 2002. In addition, from information provided by North Carolina, Tennessee, and Jefferson County, Kentucky, the I/M and ATP programs should only be applied to a portion of the VMT in the corresponding counties. For the North Carolina and Tennessee I/M counties, duplicate MOBILE6.2 input files were created that eliminate the I/M and ATP programs. The VMT from these counties was divided according to the fraction of the VMT subject to I/M and the fraction of the VMT not subject to I/M. These fractions were provided by the corresponding agencies in North Carolina and Tennessee. The VMT data for each I/M county was then divided according to these VMT fractions to obtain one set of VMT for the portion of vehicles subject to I/M and another set for those not subject to I/M. The emission factors from the I/M files were multiplied by the portion of the VMT subject to I/M while the emission factors from the files without the I/M were multiplied by the remaining portion of the VMT. In Jefferson County, Kentucky, a similar pro cedure was followed. However, in this case, the county also has a significant portion of VMT from vehicles registered in Indiana that are not subject to I/M or that do not have reformulat ed gasoline. Thus, the Jefferson County VMT was divided into four subsets and four MOBILE6 i nput files were developed representing the four groups of vehicle types traveling in the county.
3. RVP and Fuel Programs
Default RVP by county and month were obtained from the data used in the 2002 NEI. The NEI fuel data are based on year 2000 fuel survey data for January and July, with data for intermediate months calculated by interpolation. RVP data for July were applied from May through September, the months when Phase II RVP regulations are in effect. For States that supplied

### 22 July, summer, or ozone season RVP values, these values were also applied from May through September. If winter RVP values were supplied, these values were applied directly in each of the remaining months. As mentioned above, reformulated gasoline programs were modeled where appropriate. Georgia provided additional fuel inputs to capture the RVP and sulfur content values of its low sulfur gasoline program.


## III. NONROAD METHODS AND DATA

A. NONROAD MODEL CATEGORIES

Pechan used EPA’s draft NONROAD2002a model to generate 2002 annual emissions for the majority of nonroad engines. To improve the accuracy of these model runs, we asked State/ Local/Tribal (S/L/T) contacts to provide seasonal or monthly gasoline Reid Vapor Pressure (RVP) and temperature; appropriate data on reformulated gasoline (RFG), oxygenated fuel and Stage II programs, and diesel fuel sulfur levels. In addition, to improve the activity data inputs, we asked whether S/L/T agencies had collected information on equipment populations or activity (e.g., hours of use or load factors) to use in place of default populations in the NONROAD model. No S/L/T agencies provided activity data to replace the model defaults.
Seasonal average RVP and average, maximum and minimum temperature values were calculated based on the county-level, monthly RVP and temperature data set prepared for onroad mobile sources. Information on RFG programs and oxyge nated fuels programs obtained for the onroad mobile sector was also used. In July 2003, Pechan distributed the input values (RVP, percent O2, temperature, and Stage II control efficiency) to be used for the draft NONROAD model 2002 inventory for review and comment by the VISTAS S/L/T agencies. Pechan obtained comments from the S/L/T agencies listed in Table III-1.
Table III-1. Summary of Comments by S/L/T Agencies on NONROAD Model Input Values Distributed in July 2003

State Comment Alabama Provided region specific data to repl ace the statewide default values for RVP and ambient temperature Georgia Changed oxygen weight percent to zero for all counties Kentucky No Stage II programs in Bullitt and Oldham Counties Tennessee Revised RVP value for Davidson County Mississippi Revised statewide RVP by season Virginia No Stage II program in Charles City County


### Additional comments on the August 2003 NONROAD model temperature and RVP inputs were incorporated for consistency with data submitted for the onroad mobile modeling (e.g., North Carolina). In addition, the State of West Virg inia provided revised geographic allocation files for certain nonroad categories to improve upon the NONROAD model’s default county allocation.
Using the inputs shown in the file “VISTA S NONROAD County Inputs.xls,” Pechan prepared seasonal option files for each of four seasons (winter, spring, summer, and autumn), and ran the

### 23 NONROAD model at the county level. Model default values were used for all other inputs, with the exception of diesel fuel sulfur. A value of 2,500 parts per million volume (ppmv) was used instead of the default 2,318 ppm, since the default represented a national average including California’s lower diesel fuel sulfur level. Pechan summed the seasonal results, and then processed the model output to develop a county-le vel, SCC-level annual emissions inventory for all pollutants except NH 3 

### .
The NH 3 

### emissions for NONROAD model categories were developed using the following procedures. OTAQ recently reviewed the basis of NH 3 

### data summarized in a report entitled, “A Study of the Potential Impact of Some Unregulated Motor Vehicle Emissions” (Harvey, 1983). In conducting this review, OTAQ performe d an analysis of the available light-duty noncatalyst engine data to develop defensible gasoline nonroad emission factors on a mg/gallon basis (Harvey, 2003). For both gasoline noncatalyst and diesel engines, fuel based emission factors were developed from emission factors expressed on a gram/mile basis by accounting for the reported fuel economy of each tested engine. For gasoline non-catalyst engines, this resulted in a value of 115.8 mg/gallon, which is applied to county-level fuel consumption estimates for 2-stroke gasoline, 4-stroke gasoline and liquified petroleum gas (LPG) equipment. From the diesel engine test data, a value of 83.3 mg/gall on was derived, which is applied to diesel fuel consumption estimates. County-level fuel consumption for these engines, expressed in gallons, is an output from EPA’s NONROAD model.


## B. AIRCRAFT, COMMERCIAL MARINE VESSELS AND LOCOMOTIVES

For 2002 aircraft, commercial marine vessels (CMVs), and locomotives, Pechan used 1999 emission estimates developed for EPA’s 1999 NEI Version 2 as base year estimates for the VISTAS region. These categories are not incl uded in the NONROAD model, and are hereafter referred to as “other nonroad.” Pechan then incorporated revised S/L/T estimates summarized in Table III-2, using the replacement procedures summarized in Tables III-3a through III-3d. Pechan tracked changes by labeling the default 1999 NEI records as Version 2 (V2) and the revised S/L/T records as Version 3 (V3). In cases where PM2.5 estimates were not provided, they were developed using the following category-specific fractions applied to the available PM 10 

### emission estimates: 1) Aircraft: 0.69; 2) Locomotive: 0.90; and 3) CMV: 0.92 (EPA, 2002). Commercial marine adjustments are described in detail in the following section.
Table III-2. Summary of S/L/T Agency Data Incorporated into the Draft VISTAS 2002 Other Nonroad Inventory

State Description of Inventory Pollutants Alabama 1999 Locomotive emissions for Pickens and Tuscaloosa counties VOC, NO x , and CO

Florida 2001 Aircraft, Locomotive and Commercial Marine Vessel emissions for Palm Beach County VOC, NO x , CO, PM10, and SO x Tennessee 1999 Aircraft and Locomotive emissions for Davidson County VOC, NO x , CO, SO x , and primary PM 10 Virginia 1999 Statewide Inventory for Aircraft, Locomotive and Commercial Marine Vessels VOC, NO x , CO

### 24 Table III-3a. Replacement Procedur es for 1999 Locomotive Emissions for Pickens and Tuscaloosa County, Alabama

STATE_

FIPS COUNTY_ FIPS SCC Version Notes START_ DATE END_ DATE VOC NOX CO
01 107 2285002005 V3 7.73 179.7 22.81

01 107 2285002005 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 1962.9 45643 5794.5

01 107 2285002010 V3 5.39 53.48 9.47

01 107 2285002010 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 5.39 53.48 9.48

01 125 2285002005 V3 16.31 379.15 48.13

01 125 2285002005 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 3384.9 78711.4 9992.6

01 125 2285002010 V3 9.29 92.15 16.33

01 125 2285002010 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 9.29 92.15 16.3325Table III-3b. Replacement Procedures for 1999 Aircraft, Locomotive, and Commercial Marine Vessel Emissionsfor Palm Beach County, FloridaSTATE_FIPSCOUNTY_FIPSSCC VersionNotesSTART_DATEEND_DATEVOC NOX CO SO2PM10-PRIPM25-PRI12 099 2275000000 V3 Apply a Growth Factor to 2001state-supplied aircraft emissions tobackcast to 1999Estimate PM2.5-PRI off PM10-PRI19990101 19991231 470.39 805.94 4,121.41 1.98 0.0012 099 2275001000 V2 Delete all records for this SCC19990101 19991231 0.44 0.05 9.03 0 0.19 0.1312 099 2275020000 V2 Delete all records for this SCC19990101 19991231 79.1 275.5 330.6 26.3412 099 2275050000 V2 Delete all records for this SCC19990101 19991231 13.93 2.37 437.43 0.36 8.62 5.9512 099 2275060000 V2 Delete all records for this SCC19990101 19991231 9.23 1.19 212.32 0.11 4.55 3.1412 099 2280000000 V3 Apply a Growth Factor to 2001state-supplied cmv emissions tobackcast to 1999Estimate PM2.5-PRI off PM10-PRI19990101 19991231 10.42 115.60 0.97 9.94 33.9112 099 2280002100 V2 Delete all records for this SCC19990101 19991231 25.5 815.4 107.51 36.95 34.3 31.5512 099 2280002200 V2 Delete all records for this SCC19990101 19991231 0.22 7.05 0.93 0.32 0.3 0.2712 099 2280003100 V2 Delete all records for this SCC19990101 19991231 6.8 217.5 28.63 115.6 9.48 8.7312 099 2280003200 V2 Delete all records for this SCC19990101 19991231 0.06 1.93 0.25 1.43 0.11 0.112 099 2285002000 V3 Apply a Growth Factor to 2001state-supplied locomotive emissions tobackcast to 1999Estimate PM2.5-PRI off PM10-PRI19990101 19991231 28.19 658.78 83.64 48.09 15.5012 099 2285002006 V2 Delete all records for this SCC19990101 19991231 6.11 164.1 16.17 10.26 4.07 3.6612 099 2285002008 V2 Delete all records for this SCC19990101 19991231 0.45 12.15 1.2 0.76 0.3 0.2712 099 2285002009 V2 Delete all records for this SCC19990101 19991231 6.78 182.2 17.95 11.39 4.52 4.0712 099 2285002010 V2 Delete all records for this SCC19990101 19991231 3.75 64.36 6.77 3 1.64 1.471Palm Beach County provided emission estimates corresponding to 2001; as such, 2001 emission estimates were backcast to 1999 using growth factors presented in this reportbefore incorporation.

### 26 Table III-3c. Replacement Procedures for 1999 Aircraft and Locomotive Emissions for Davidson County, Tennessee

STATE_

FIPS COUNTY_ FIPS SCC Version Notes START_ DATE END_ DATE VOC NOX CO SO2 PM10- PRI PM25- PRI

47 037 2275000000 V3 Estimate PM2.5-PRI off PM10-PRI 19990101 19991231 232.125 634.35 1766 32.13 39.25

47 037 2275001000 V2 Delete all records for this SCC 19990101 19991231 1.7 0.2 35 0.02 0.75 0.52

47 037 2275020000 V2 Delete all records for this SCC 19990101 19991231 187.45 649.92 782.93 62.34

47 037 2275050000 V2 Delete all records for this SCC 19990101 19991231 4.72 0.8 148.3 0.12 2.92 2.02

47 037 2275060000 V2 Delete all records for this SCC 19990101 19991231 15.22 1.97 349.97 0.19 7.51 5.18

47 037 2285002000 V3 Estimate PM2.5-PRI off PM10-PRI 19990101 19991231 20.803 363.117 50.701 26.36 8.893

47 037 2285002006 V2 Delete all records for this SCC 19990101 19991231 31.91 857.26 84.46 53.6 21.27 19.15

47 037 2285002010 V2 Delete all records for this SCC 19990101 19991231 19.6 336.23 35.39 15.68 8.54 7.69

### 27 Table III-3d. Replacement Procedures for 1999 Aircraft, Locomotive, and

Commercial Marine Vessel Emissions for Sample Counties in Virginia

STATE_

FIPS COUNTY_ FIPS SCC Version Notes START_ DATE END_ DATE VOC NOX CO SO2 PM10- PRI PM25- PRI 51 001 2275001000 V3 19990101 19991231 3.47 0.78 3.74 51 001 2275001000 V2 Replace VOC, NOx, and CO emissions Keep SO2, PM10-PRI, and PM2.5-PRI emissions 19990101 19991231 0.31 0.04 6.38 0 0.14 0.09

51 013 2275020000 V3 19990101 19991231 145.821 992.23 1634.2 51 013 2275020000 V2 Replace VOC, NOx, and CO emissions Keep SO2 emissions 19990101 19991231 271.17 940.36 1132.7 90.2

51 001 2275050000 V3 19990101 19991231 1.25 0.21 39.34 51 001 2275050000 V2 Replace VOC, NOx, and CO emissions Keep SO2, PM10-PRI, and PM2.5-PRI emissions 19990101 19991231 0.25 0.04 7.81 0.01 0.15 0.11

51 001 2275060000 V3 19990101 19991231 0.05 0.01 1.26 51 001 2275060000 V2 Replace VOC, NOx, and CO emissions Keep SO2, PM10-PRI, and PM2.5-PRI emissions 19990101 19991231 1.47 0.19 33.8 0.02 0.72 0.5

51 670 2280002000 V3 Add SCC to the Inventory 19990101 19991231 3.3 18.16 6.94 51 670 2280002100 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2280002100 and 2280002200 and add to SCC 280002000. After that, delete all records for SCC 2280002100 and 2280002200 19990101 19991231 10.12 323.52 42.66 14.7 13.61 12.52

51 670 2280002200 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2280002100 and 2280002200 and add to SCC 2280002000. After that, delete all records for SCC 2280002100 and 2280002200 19990101 19991231 0.17 5.39 0.71 0.24 0.23 0.21

51 670 2280003000 V3 Add SCC to the Inventory 19990101 19991231 0.14 1.64 0 51 670 2280003100 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2280003100 and 2280003200 and add to SCC 2280003000. After that, delete all records for SCC 2280003100 and 2280003200 19990101 19991231 2.7 86.31 11.36 45.9 3.76 3.46

51 670 2280003200 V2 Sum up SO2, PM10, and PM2.5 Emissions for SCCs 2280003100 and 2280003200 and add to SCC 2280003000. After that, delete all records for SCC 2280003100 and 2280003200 19990101 19991231 0.05 1.48 0.19 1.09 0.08 0.08

51 199 2283002000 V3 19990101 19991231 8.46 53.47 15.51 51 199 2283002000 V2 Replace VOC, NOx, and CO emissions 19990101 19991231 7.43 47.26 13.63 51 740 2285002005 V3 Add SCC to the Inventory 19990101 19991231 3.76 100.99 9.95 51 740 2285002006 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2285002006 and 2285002007 and add to SCC 285002005. After that, delete all records for SCC 2285002006 and 2285002007. 1 19990101 19991231 0.7 18.77 1.85 1.17 0.47 0.42

51 740 2285002007 V2 Sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2285002006 and 2285002007 and add to SCC 285002005. After that, delete all records for SCC 2285002006 and 2285002007. 1 19990101 19991231 0.08 2.26 0.22 0.14 0.06 0.05

51 036 2285002010 V3 19990101 19991231 0.59 10.13 1.06 51 036 2285002010 V2 Replace VOC, NOx, and CO emissions Keep SO2, PM10-PRI, and PM2.5-PRI emissions 19990101 19991231 1.99 34.15 3.59 1.59 0.87 0.78

1 Other counties may also have emissions for SCCs 2285002008 and 2285002009. In these cases, sum up SO2, PM10-PRI, and PM2.5-PRI emissions for SCCs 2285002006, 2285002007, 2285002008, and 2285002009 and add to SCC 2285002005. After that, delete all records for SCC 2285002006, 2285002007, 2285002008, and 2285002009.

### 28 2. CMV Improvements
This section describes procedures for improving the spatial distribution of CMV emission estimates for the VISTAS region. States that share borders with non-VISTAS States along the Mississippi and Ohio Rivers have expressed concern about the representativeness of port emission estimates at a county-level. Revising the county-level emissions estimates would allow more accurate modeling of emissions in the VISTAS States.
Ideally, CMV emission estimates would be developed using local activity data that account for vessel type, engine type and mode of operation (cruise, maneuvering, and hotelling). Creating this type of “bottom-up” emission inventory require s a large amount of effort. Therefore, Pechan utilized port-specific emission estimates develope d for the 1999 NEI, distributed using a revised allocation methodology, which incorporates information on the number of port facilities in each county.

a. Current Allocation Method
The current 2002 VISTAS commercial marine inventory is based on EPA’s 1999 NEI Version 2.0, projected to 2002 using appropriate growth fact ors. State-supplied data were incorporated by EPA or by Pechan for some VISTAS States for this category, including Alabama, Virginia, West Virginia, and Palm Beach County, Florida.
The 1999 NEI estimated emissions for these categories according to the following SCCs:

SCC Descriptor 1 Descriptor 3 Descriptor 6 Descriptor 8 2280002100 Mobile Sources Marine Vessels, Commercial Diesel Port emissions 2280002200 Mobile Sources Marine Vessels, Commercial Diesel Underway emissions 2280003100 Mobile Sources Marine Vessels, Commercial Residual Port emissions 2280003200 Mobile Sources Marine Vessels, Commercial Residual Underway emissions


### For the 1999 NEI, commercial marine diesel emissions were developed by obtaining 2000 emission estimates for all pollutants except SO 2 

### from OTAQ’s marine diesel regulatory background documentation ( Draft Regulatory Impact Analysis - Control of Emissions from Compression-Ignition Marine Engines ). To estimate emissions for 1999, 2000 estimates were backcast using growth factors obtained from the draft RIA cited above. Steam-powered residual CMV emission estimates were developed by obtai ning fuel usage data from OTAQ and applying fuel-based emission factors (EPA, 1989). A similar method was used for diesel SO 2 

### emissions. National diesel usage was estimated assuming a sulfur content of 0.25 percent and EPA emission factors (EPA, 2002).
National diesel emissions were disaggregated into port and underway emissions estimates based on the assumption that 75 percent of distillate fuel is consumed within the port, while the remaining fuel is consumed while underway, consistent with EPA guidance. National residual emissions were disaggregated into port and underway emissions estimates based on the assumption that 25 percent of residual fuel is consumed within the port, while the remaining fuel is consumed while underway (EPA, 1989).

### 29 To allocate to counties, port emissions were assigned to the 150 largest U.S. ports based on activity obtained from the U.S. Army Corps of Engineers (USACE). The percentage of total traffic for each port was calculated by dividing th e port-level traffic by the total traffic. Emissions for each port were then assigned to a single county.

Underway emissions are assigned to counties based on a county = s shipping lane traffic. The Bureau of Transportation Statistics’ (BTS = ) National Transportation Atlas Databases-1999 contains data on the thousand tons per mile traveled for each shipping lane link in the United States (BTS-CD26). Where navigable rivers fo rm a county or State boundary, the shipping lane traffic is proportioned to individual counties based on the length of shoreline that is shared. For example, if two counties share a navigable river, and both counties have the same length of shoreline, the shipping traffic is split evenly between the two counties. Shipping lanes that are not within counties, for example in the ocean, are associated to States based on BTS assignments. These waterway weights are then evenly distributed among the counties within these States that have navigable waterways. All shipping activity is summed at the county-level and compared with national shipping activity to determine what portion of activity can be attributed to individual counties. These proportions were used in disaggregating the national CMV emission estimates to the county level.

b. Revised Port Allocation Method
Figures III-1 and III-2 present emission maps for CMV port and underway NO x 

### emissions created from the 1999 NEI Version 2.0 data. For underway emissions, Pechan believes that the allocation procedure results in a reasonable distribution of county-level emissions. However, the methodology to allocate port emissions results in all the emissions being assigned to a single county. For example, Cabell County in West Virginia is assigned all emissions for Huntington Port, but no emissions are allocated to Lawrence County in Ohio, the county on the opposite river bank.
Port areas encompass multiple States and counties and in some cases, multiple waterways. Therefore, the emissions allocation process must incorporate all counties in the vicinity of the port where activity is occurring. This is especially true for inland rivers where activity takes place on both riverbanks and for 10 river miles or more outside the port city. The revised methodology allocates port emissions based on a surrogate for port-related activity in each county, rather than using a single county to define the port.30

Figure 1. VISTAS Region and Surrounding States VISTAS Region an d Surrounding States Underway NOx EmissionsNOx Emissions(Tons per Year)00 - 400400 - 800800 - 1,3001,300 - 2,4002,400 - 3,680E.H. Pechan & Associates, Inc.Date: December 11, 2003.Figure III-1. VISTAS Region and Surrounding States,Underway NOxEmissions31

Figure 2. VISTAS Region and Surrounding States VISTAS Region and Surrounding States Port NOx EmissionsNOx Emissions(Tons per Year)00 - 3,0003,000 - 7,0007,000 - 13,00013,000 - 26,00026,000 - 67,000E.H. Pechan & Associates, Inc.Date: December 11, 2003.Figure III-2. VISTAS Region and Surrounding States,Port NOxEmissions

### 32 The report, Waterborne Commerce of the United States, Calendar Year 1999 (USACE, 2000), hereafter referred to as Waterborne Commerce
, presents the cargo tonnage and number of vessel trips in major waterways of the United States. The report defines port areas, which USACE uses to develop the Top 150 Ports in the United States by amount of cargo tonnage. As discussed in the previous section, the 1999 NEI allocates all th e port emissions to these 150 ports based on the cargo tonnage handled by the port.
Pechan uses this allocation of emissions to each port area as the starting point of its revised allocation process. Table III-4 presents the ports that are located in VISTAS and adjoining States, which are part of the Top 150 Ports.

Table III-4. Port Areas Located in VISTAS and Adjoining States

Port State Port State

Mobile AL Pascagoula MS Guntersville AL Vicksburg MS
Helena AR Biloxi MS Port Everglades FL Greenville MS Jacksonville FL Gulfport MS
Miami FL Wilmington NC Port Canaveral FL Morehead City NC
Palm Beach FL Cincinnati OH Panama City FL Pittsburgh PA
Pensacola FL Charleston SC Tampa FL Georgetown SC Port Manatee FL Memphis TN
Weedon Island FL Nashville TN Savannah GA Chattanooga TN
Brunswick GA Norfolk Harbor VA Mount Vernon IN Newport News VA Louisville KY Hopewell VA New Orleans LA Huntington WV Baton Rouge LA



### The next step was to develop a list of counties that make up the port area. Port area definitions were obtained from Waterborne Commerce . Table III-6 presents the port definitions for the VISTAS States and adjoining Stat es. Using the port definitions by river mile, Pechan established which counties are included in each port area. In many cases, these port areas encompass multiple counties. For example, Pittsburgh is defined in Waterborne Commerce as:
Ohio River from Pittsburgh, PA to mile 40 (Pennsylvania/Ohio State Line); Allegheny River from Pittsburgh, PA to mile 72 (to head of project); Monongahela River from Pittsburgh, PA to mile 91 (to head of project).

### 33 Therefore, the Port of Pittsburgh includes the following counties in Pennsylvania; Allegheny, Westmoreland, Armstrong, Washington, Fayette, Greene, Beaver. This process was repeated for all the port areas listed in Table III-4.
The next step in allocating emissions is to develop a surrogate for the amount of CMV activity in each county of the port area. Pechan assumed that the activity of vessels in each county is related to the number of port facilities operating in a given county. Port facilities include terminals, piers, wharves, and docks that are involved in all types of commercial activity and support services. Pechan obtained the number of port facilities in each county from The Port Series Reports (USACE, 2003). The USACE periodically surveys the commercial marine industry to obtain information on port facilities and publishes it in The Port Series Reports . The reports give the name, location, operations, and describe the physical and inter-modal characteristics of the facilities. The data includes the location of the facility by river mile, State, and county.
For each port area, Pechan calculated the ratio between the number of port facilities in each county to the total number of facilities in all counties that make up the port area. This ratio was used to allocate emissions for each port area to the county-level. Table III-5 presents the allocation ratios for each county in the port areas. Some port areas were still encompassed by one county using the definition of the port from Waterborne Commerce . However, a number of port areas include multiple counties. Note that New Orleans and Pittsburgh do not include any counties in VISTAS States.

Table III-5. List of VISTAS Po rts and Ports of Adjoining States

Port State County Ratio Port State County Ratio Port State County Ratio Port Everglades FL Broward 1.0 AR Phillips 0.7778 TN Hamilton 0.7692 Jacksonville FL Duval 1.0 Helena MS Coahoma 0.2222 Chattanooga TN Marion 0.2308 Miami FL Miami-Dade 1.0 FL Charlotte 0.7500 VA Norfolk City 0.5568
Port Canaveral FL Brevard 1.0 Charlotte FL Lee 0.2500 VA Chesapeake City 0.3068
Palm Beach FL Palm Beach 1.0 IN Vanderburgh 0.3182 Norfolk

VA Portsmouth 0.1364 Panama City FL Bay 1.0 IN Posey 0.4773 VA Newport News 0.6500 Pensacola FL Escambia 1.0 Mount Vernon KY Henderson 0.2045 Newport News VA Hampton 0.3500 Tampa FL Hillborough 1.0 KY Jefferson 0.6596 VA Hopewell 0.5000 Port Manatee FL Manatee 1.0 Louisville IN Clark 0.3404 Hopewell VA Charles City 0.5000 Weedon Island FL Pinellas 1.0 LA St. Bernard 0.0858 PA Allegheny 0.5206 Savannah GA Chatham 1.0 LA Plaquemines 0.1231 PA Westmoreland 0.0412 Brunswick GA Glynn 1.0 LA Orleans 0.3284 PA Armstrong 0.0309 Pascagoula MS Jackson 1.0 LA Jefferson 0.4366 PA Washington 0.1340 Vicksburg MS Warren 1.0 LA St. Tammany 0.0224 PA Fayette 0.0412 Biloxi MS Harrison 1.0 New Orleans

LA Tangipahoa 0.0037 PA Greene 0.0567 Greenville MS Washington 1.0 NC New Hanover 0.8974 Pittsburgh

PA Beaver 0.1753 Gulfport MS Harrison 1.0 Wilmington NC Brunswick 0.1026 KY Greenup 0.0795 Morehead City NC Carteret 1.0 OH Hamilton 0.7931 KY Boyd 0.1023 Georgetown SC Georgetown 1.0 KY Kenton 0.0862 OH Gallia 0.1136 Nashville TN Davidson 1.0 Cincinnati KY Boone 0.1207 OH Lawrence 0.2273 Mobile AL Mobile 1.0 SC Charleston 0.7097 OH Scioto 0.1364 Guntersville AL Marshall 1.0 Charleston SC Berkeley 0.2903 WV Wayne 0.1136 TN Shelby 0.9123 WV Cabell 0.0795 Memphis AR Crittenden 0.0877 Huntington

WV Mason 0.1477

### 34 Pechan was directed to perform the reallocation for all VISTAS ports. Figure III-3 presents the reallocation of port emissions in all States except Alabama. Alabama’s CMV data were provided to EPA and already incorporated into the 1999 NEI Version 2, and Pechan did not have access to the default 1999 NEI estimates for this State and category. Since State data take precedence, the inventory prepared by Pechan refl ects the incorporation of State data for those areas that developed independent CMV emission estimates, including Virginia and Palm Beach County, Florida. In addition, West Virginia provided their own county fractions to allocate emissions for the Port of Huntington, using District -level data from the Army Corps of Engineers on tonnage of freight shipped and received. West Virginia also requested that residual-fueled CMV activity/emissions be zeroed out for their State. States providing their own data are encouraged to review the allocations Pechan developed for their port areas, and to provide further comment or direction as needed.35Figure III-3. VISTAS Region and Surrounding States,Revised Port Emissions of NOX

### 36 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce (USACE, 2000)

VISTAS PORTS

MOBILE, AL Entrance. bay and river channels, and channels into Chickasaw and Three Mile Creeks; Branch Channels; Theodore Ship Channel.

GUNTERSVILLE, AL Both banks of the Tennessee River at mile 358 to mile 363.

JACKSONVILLE HARBOR, FL Atlantic Ocean to the Florida East Coast Railway Bridge at Jacksonville, 26.8 miles.

TAMPA, FL Gulf of Mexico to and including the channels of upper Tampa Harbor, 49.8 miles; Channel to Port Tampa and thence to Courtney Campbell Parkway, 17.5 miles; Natural channel leading from Port Tampa Channel toward St. Petersburg, 1.8 miles; Alafia River Channel, 3.6 miles; Hillsborough River to City Waterworks Dam, 10 miles; Channels in “Little M anatee River, Fl; Port Manatee, Fl Harbor.”

MIAMI HARBOR, FL Atlantic Ocean to inner end of turning basin at Miami, 6 miles; Meloy Channel and thence natural channels along the easterly side of Biscayne Bay to Bakers Haulover Inlet, FL, about 11 miles; channel from turning basin to mouth of Miami River, 1.1 miles; existing Florida East Coast Railway Channel, Fishermans Channel from mouth of Miami River to Government Cut, 3.8 miles; and the channels reported under “Miami River, FL.”

EVERGLADES HARBOR, COLLIER COUNTY, FL - No definition given

CANAVERAL HARBOR, FL Entrance Channel (Atlantic Ocean) to Barrier Beac h inner channel and Turning Basins, thence a Barge canal through a lock in the perimeter dike and conti nuing to the Intracoastal Waterway, Jacksonville to Miami.

CHARLOTTE HARBOR, FL Gulf of Mexico to Municipal Terminal at Punta Go rda, about 29.5 miles; waterfront on Gasparilla Island from Port Boca Grande to Boca Grande, 4.5 miles; and Myakka River to El Jobean, 4 miles.

PALM BEACH HARBOR, FL Atlantic Ocean to Port of Palm Beach Terminals, 1. 7 miles; Lake Worth from Riviera Bridge to Southern Boulevard Bridge at West Palm Beach, 7.5 mile s; and “Palm Beach, FL side channel and basin.”

PORT MANATEE, FL 40 feet deep by 400 feet wide entrance channel and bas in. The entrance channel extends approximately 3 miles in length from the turning basin to its in tersection with Tampa Harbor main channel. Controlling Depth: 40 feet in entrance channel and turning basin.

PANAMA CITY HARBOR, FL Entrance channel, inside bay and Watson Bayou. Pr oject Depth: Approach channel, 34 feet; across Lands End, 32 feet; Watson Bayou, 10 feet.

### 37 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce (USACE, 2000)

PENSACOLA HARBOR, FL Entrance channel and entire harbor, including Bayou Chico. Project Depth: entrance, 35 feet; Inner Ha rbor, 33 feet; Bayou Chico, 15 and 14 feet.

WEEDON ISLAND, FL – no definition

BRUNSWICK HARBOR, GA From 32-foot contour in the ocean across the Bart hrough St. Simon Sound, Brunswick River, and Turtle River to the upper end of the Allied Chemical Com pany’s Wharf, formerly Atlantic Refining Company Wharf, 20.4 miles; from Brunswick River through East River, to the upper end of the project in Academy Creek, 2.7 miles; from St. Simon Sound through Ba ck River to Mill Creek, the upper end of Back River improvement, 2.9 miles; from Back River through Terry Creek to the Glynn Canning Company’s Wharf, 1.8 miles; a total distance of 27.8 miles.

SAVANNAH HARBOR, GA From the 40-foot contour in the ocean to t he Continental Can Company Plant, 32.15 miles.

LOUISVILLE, KY Both banks of the Ohio River from mile 606 to mile 616 Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

BILOXI HARBOR, MS Mississippi Sound, Biloxi Bay, Back Bay, and land cut to Gulfport Lake. Project Depth: East entrance channel, Mississippi Sound to Gulfport Lake, 12 feet: West entrance channel, Mississippi Sound to Biloxi Harbor, 10 feet; Ott Bayou, 12 feet.

GREENVILLE, MS From Mississippi River mile 537 AHP left descending bank in an easterly direction, an entrance channel, 8,000 feet long and 250 feet wide transitioning into the harbor and port area 10,000 feet long and 500 feet wide, then transitioning into Lake Ferguson, a channel 5,700 feet long and 250 feet wide.

GULFPORT HARBOR, MS Mississippi Sound Channel, Ship Island Pass Channel, and Small Craft Harbor about 4,300 feet long west of the anchorage basin. Project Depth: Mississippi Sound, 30 feet; Ship Island Pass, 32 feet; Small Craft Harbor, 8 feet.

PASCAGOULA HARBOR, MS Lower 4 miles of Dog River and lower 6.8 miles of Pascagoula River, Mississippi Sound, Bayou Casotte, and Horn Island Pass Channels.

VICKSBURG, MS From Mississippi River mile 437 AHP on left descending bank in a northerly direction, a channel 14,500 feet long by 150 feet wide in the Yazoo Divers ion Canal, thence a dredged entrance channel 4,800 feet long and 150 feet wide, transitioning into a 300-foot wide dredged slack water harbor and turning basin 10,700 feet long.

MOREHEAD CITY HARBOR, NC Morehead City Harbor, NC.

### 38 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce (USACE, 2000)

PORT OF WILMINGTON, NC (see also Wilmington Harbor NC for waterway data) Both banks of the Cape Fear River extending from a poi nt about 18 miles below the foot of Castle St. in Wilmington to a point about 2 miles above the Ra ilroad Bridge at Navassa, and both banks of Northeast (Cape Fear) River from its mouth to a point about 1.67 miles above the Hilton Railroad Bridge.

CHARLESTON HARBOR, SC (Including Ashley River, Cooper River, Shem Creek And Shipyard River, SC) Ocean to Goose Creek via Cooper River and Town Creek ; to the Standard Wharf on Ashley River; to the Mount Pleasant Memorial Highway Bridge on Shem Creek ; to the Airco Alloys Wharf on Shipyard River; Wando River to Cainhoy.
GEORGETOWN HARBOR, SC (Winyah Bay) Atlantic Ocean Entrance to Winyah Bay, SC, to and including turning basin in Sampit River at the City of Georgetown, SC.

MEMPHIS, TN Section Inlcuded: From mile 715.5 to mile 741. 0 on Lower Mississippi River and includes Memphis Harbor (McKellar Lake) and Wolf River Harbor, Tennessee. Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

PORT OF NASHVILLE, TN (included in traffic of Cumberland River, TN and KY) Both banks of Cumberland River, mile 182 to mile 194 Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

CHATTANOOGA, TN Section Included: Both banks of the Tennessee River at mile 454 to 471. Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

PORT OF RICHMOND, VA (Included in James River, VA Consolidated Report)

PORT OF NEWPORT NEWS, VA (Including Newport News Creek, VA) Lower east shore of James River from mouth to 1.8 miles, and portion of north shore of Hampton Roads covering approximately 15,000 linear feet of waterf ront at Newport News; and Newport News Creek.

PORT OF HOPEWELL, VA (Included In James River VA Consolidated Report) South side of James River, from City Point, at m outh of Appomattox River, 2 miles downstream to the mouth of Baileys Creek. Controlling Depth: 25 feet at mean low water. Project Depth: 35 feet, maintained to 25 feet.

NORFOLK HARBOR, VA From 55-foot contour in Hampton Roads to Norfolk & Western (formerly Virginia) Railway Bridge Crossing Southern Branch of Elizabeth River, 14.78 miles; t hence upstream in Southern Branch, 4.61 miles. In Eastern Branch, 2.54 miles upstream from the mouth of that branch; in Western Branch, 1.78 miles upstream from the mouth of that branc h; and 0.73 miles in Scotts Creek.

HUNTINGTON, WV Both banks of the Ohio River from mile 303 to mile 317 Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

### 39 Table III-6. Definition of Port Areas Obtained from Waterborne Commerce (USACE, 2000)

NON-VISTAS PORTS

HELENA, AR Mile 659 through mile 663 on the Lower Mississippi River. The project provides for maintenance of an off-rive r harbor with dimensions of 9 feet deep and 450 feet wide for a length of 3,200 feet.

MOUNT VERNON, IN Section Included: Right Bank of Ohio River from mile 151 to mile 154. Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

CINCINNATI, OH Both banks of the Ohio River from mile 465 to mile 491. Controlling Depth: 9 feet. Project Depth: 9 feet at low water stages.

PORT OF PITTSBURGH, PA Ohio River from Pittsburgh, PA to mile 40 (Pennsylvania/Ohio State Line); Allegheny River from Pittsburgh, PA to mile 72(to head of project); Monongahela River from Pittsburgh, PA to mile 91(to head of project). Includes Aliquippa-Roches ter, Pittsburgh, Clairton-Elizabeth. Controlling Depth: 9 feet. Project Depth: 9 feet.

PORT OF PLAQUEMINES, LA Both banks of Mississippi River from mile 0 A.H.P. through mile 81.2 A.H.P Controlling and Project Depths: 45 feet.

PORT OF BATON ROUGE, LA Both banks of Mississippi River from mile 168.5 A. H.P. through mile 253 A.H.P; including the Baton Rouge Barge Canal from a point on the east bank of the Mississippi River at mile 234.5 A.H.P., for a distance of 5 miles.

PORT OF NEW ORLEANS, LA Both banks of the Mississippi River from mile 81.2 A.H.P. through mile 114.9 A.H.P.; Innerharbor Navigation Canal, 5.5 miles; Mississippi River-Gulf Outl et from its junction with the Innerharbor Navigation Canal to Bayou Bienvenue, 7 miles; and Harvey Canal, 5.5 miles.
PORT OF SOUTH LOUISIANA (LA) Both banks of Mississippi River from mile 114.9 A.H.P. through mile 168.5 A.H.P. Controlling and Project Depths: 45 feet.

### 40 3. Projection Methods
Pechan then projected the revised 1999 inventory to 2002 using surrogate growth indicators. For the aircraft category, 1999 and 2002 approach opera tions by airport and aircraft type were compiled from the Federal Aviation Administration’s Air Traffic Activity Data System (ATADS). The airport-level landing and takeoffs (LTOs) were assigned to counties and summed for the county. For counties with aircraft em issions without a county match in ATADS, Stateaverage growth factors were calculated and app lied. The county-level growth factors are not presented in this report, but could be provided to VISTAS S/L/Ts if requested.
For locomotives, projected emissions were developed in two steps as described below. For 1999 to 2001, State-level vessel bunkering and rail fuel consumption was obtained from the Energy Information Administration’s (EIA’s) Fuel Oil and Kerosene Sales. For 2001 to 2002, Pechan applied national growth factors developed from fuel consumption projections in EIA’s Annual Energy Outlook. Table III-7a lists the growth factors for locomotives that were applied to the 1999 emissions to first develop 2001 emissions. Table III-7b lists the growth factors used to generate 2002 emissions. Locomotive emissions were not revised from the August 2003 draft VISTAS 2002 inventory.

Table III-7a. Growth Factors for Railroad Distillate Fuel Oil Use

Rail Distillate Fuel Oil Sales (Thousand Gallons) FIPSST State

1999 2001 Growth Factor (GF)

01 Alabama 42,137 55,777 1.3 12 Florida 127,269 107,084 0.8 13 Georgia 73,494 70,538 1.0 21 Kentucky 98,941 99,812 1.0 28 Mississippi 14,267 24,812 1.7 37 North Carolina 53,900 77,762 1.4 45 South Carolina 13,051 15,936 1.2 47 Tennessee 44,083 91,363 2.1 51 Virginia 32,202 61,154 1.9 54 West Virginia 9,160 8,787 1.0 Source: Department of Energy, Energy Information Administ ration Fuel Oil and Kerosene Sales 1999 & Fuel Oil and Kerosene Sales 2001 Table 23. Adjusted Sales for Transportati on Use: Distillate Fuel Oil and Residual Fuel Oil ( http://tonto.eia.doe.gov/FTPROOT/pertroleum/053599.pdf ), ( http://tonto.eia.doe.gov/FTPROOT/pertroleum/053501.pdf )

### 41 Table III-7b. 2002 National Rail Transportation Energy Use by Fuel Type (Trillion BTU)

2001 2002 Growth Factor (GF) Intercity Rail (Electric) 10.17 10.40 1.0226 Intercity Rail (Diesel) 16.60 16.88 1.0169 Transit Rail (Electric) 46.36 47.40 1.0224 INTERCITY/TRANSIT RAIL AVERAGE (SCC 2285002008) 1.0206 Commuter Rail (Electric) 16.13 16.49 1.0223 Commuter Rail (Diesel) 26.31 26.76 1.0171 COMMUTER RAIL AVERAGE (SCC 2285002009) 1.0197 Freight Rail (Distillate) (SCCs 2285002000, 2285002005, 2285002006, 2285002007, 2285002010) 512.81 492.32 0.9600

Source: Department of Energy, Energy Information Administration, Annual Energy Outlook 2003: Table 34. Transportation Sector Energy Use by Fuel Type Within a Mode ( http:// www.ei a.doe.gov/oiaf/aeo/supplement/sup_tran.pdf )



### Since the CMV emissions were revised for the 1999 base year, these emissions were projected using 2002 Fuel Oil and Kerosene Sales data, which became available in November 2003. Table III-8 lists the growth factors for CMVs that were applied to 1999 emissions to generate 2002 emissions. The same regional growth factor that accounts for an average regional growth rate was applied to CMV emissions for all VISTAS States. Because the State-level data represents sales and not use, and CMV activity spans State borders, a regional growth factor was deemed more appropriate. Pechan could make a similar adjustment for the locomotive growth factors, which are also based on fuel sales for 1999 to 2001, if requested by VISTAS.

### 42 Table III-8. Growth Factors for Commerc ial Marine Vessel Distillate and Residual Fuel Oil Use

Fuel Oil Sales (Thousand Gallons) Growth Factor (GF) FIPSST State

1999 2002 DISTILLATE 01 Alabama 67,455 73,400 1.1 12 Florida 139,809 143,577 1.0 13 Georgia 17,697 22,327 1.3 21 Kentucky 81,811 56,169 0.7 28 Mississippi 12,749 68,668 5.4 37 North Carolina 11,279 10,057 0.9 45 South Carolina 12,732 19,782 1.6 47 Tennessee 43,867 112,364 2.6 51 Virginia 29,444 28,235 1.0 54 West Virginia 54,560 46,981 0.9 Regional Distillate GF 471,403 581,560 1.2 RESIDUAL 01 Alabama 46,093 93,487 2.0 12 Florida 404,228 460,600 1.1 13 Georgia 40,117 79,191 2.0 21 Kentucky 1 69 1.2 28 Mississippi 48,644 54,031 1.1 37 North Carolina 6,989 35,210 5.0 45 South Carolina 20,056 22,758 1.1 47 Tennessee 1 124 1.2 51 Virginia 60,090 36,445 0.6 54 West Virginia 1.2 Regional Residual GF 626,217 781,915 1.2

1 For Kentucky, Tennessee and West Virginia, Pechan summed the 1999 and 2002 CMV residual fuel oil use to develop a total VISTAS State growth factor, which was then applied to the three States. Source: Department of Energy, Energy Information Administ ration, Fuel Oil and Kerosene Sales 1999 & Fuel Oil and Kerosene Sales 2002, Table 23. Adjusted Sales for Transportati on Use: Distillate Fuel Oil and Residual Fuel Oil. 

# IV. ONROAD REFUELING METHODS

Emissions were separately calculated from onroad refueling, also known as Stage II emissions. Since refueling is a category of evaporative rather than exhaust emissions, VOC is the only criteria pollutant of concern for this category. This chapter discusses the controls modeled for this emission category and the methods used to calculate these emissions. Refueling emissions for onroad sources were updated in February 2004 to account for the VMT updates provided by several States.



## A. CONTROLS

Based on default information from the NEI as well as some information provided by VISTAS agencies, portions of five of the VISTAS States ha ve onroad Stage II refueling controls in place. These States, along with the specific counties with onroad Stage II controls, are listed in Table IV-1. This table also shows information about the Stage II control program in each State including the year a Stage II program began, the number of years that the program was phased-in over, and the control efficiency of the program in reducing VOC emissions from Stage II

### 43 refueling for the LDGV, LDGT, and HDGV vehicle cat egories. These are the inputs required for modeling a Stage II control program using MOBILE6. States with Stage II programs should review this information and provide any corrections for the next round of emissions modeling.
Table IV-1. Onroad Stage II Control Programs

State Start Year Phase-In Years Control Efficiency Counties Florida 1993 2 95% Broward, Miami-Dade, Palm Beach Georgia 1992 3 81% Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding, Rockdale Kentucky 1999 2 86% B oone, Campbell, Kenton Kentucky 1992 2 95% Jefferson Tennessee 1993 3 95% Davidson, Ruther ford, Sumner, Williamson, Wilson Virginia 1993 2 95% Counties: Arlingt on, Chesterfield, Fairfax, Hanover, Henrico, Loudoun, Prince William, Stafford Independent Cities: Alexandria, Colonial Heights, Fairfax, Falls Church, Hopewell, Manassas, Manassas Park, Richmond



## B. METHODS

A simplified set of MOBILE6.2 input files was creat ed to simulate the onroad refueling emission factors. These input files were simplified becau se several of the inputs used for calculating the onroad exhaust and evaporative emission factors do not affect the refueling emission factors. For example, the refueling emission factors ar e unaffected by vehicle speed or I/M program. Thus, for each group of counties in a State with the same fuel parameters, temperature parameters, fleet characteristics (registration distribution, diesel sales fractions), and Stage II control program parameters, a MOBILE6.2 input file was created to model the onroad refueling emission factors. As mentioned above, speed does not affect the refueling emission factors, so each input file contained only 12 scenarios—one for each month of the year. Within each scenario, the temperature and fuel parameters were varied, using the same temperature and fuel data modeled in the onroad exhaust and evaporative MOBILE6.2 input files. Other fleet characteristics, such as registration distributions and diesel sales fractions, were included in the input files where applicable. The inputs shown in Table IV-1 were included for the input files representing counties with Stage II control programs. The header section of the MOBILE6.2 input files was set up so that only refueling emission factors would be included in the tabular output file.
After the MOBILE6.2 input files were generated, they were run through the MOBILE6.2 model to obtain refueling VOC emission factors in the database table format. These emission factors are produced for the 28 MOBILE6 vehicle types. The emission factors were then weighted using the VMT fraction information included in the MO BILE6 output tables to obtain VOC refueling emission factors for the 8 vehicle types incl uded in the VISTAS VMT database. The VMT fraction information contained in the MOBILE6 input files is based on the default MOBILE6 registration distributions, diesel sales fractions, and VMT fractions, or, when this information is

### 44 provided in the input files, based on area-specific fleet parameters. A database of emission factors by month, county, and 8 vehicle types was then prepared. In calculating monthly onroad refueling emissions, the VISTAS annual VMT data were temporally allocated by month in the same manner as described in Chapter II for the onroad exhaust and evaporative emission calculations. These VMT were then multiplied by the corresponding monthly emission factor (in terms of grams per mile) to obtain refueling emissions from onroad vehicles. The monthly emissions for each county were then summed to obtain annual refueling emissions. Also, since refueling emissions are included in the area sour ce inventory and are not distinguished by vehicle type, all refueling emissions from onroad vehicl es were summed for each county in the VISTAS region. Summaries of the refueling emissions from onroad vehicles are presented in Chapter VI.


# V. NONROAD REFUELING METHODS

The NONROAD model accounts for refueling emissions from nonroad equipment under two separate components, vapor displacement and spillage. Vapor displacement emissions result when new liquid fuel being added to a fuel tank di splaces fuel vapors already present in the tank. Spillage emissions result when fuel is spilled during the refueling process.
Nonroad equipment may be fueled from a gaso line pump or a portable container. Refueling nonroad equipment from a portable container results in different emissions for both spillage and vapor displacement compared to refueling from a gasoline pump. In addition, the use of portable containers also results in extra refueling events. Both spillage and displacement emissions will also occur when the container is filled from a gasoline pump. However, due to lack of data, the NONROAD2002 model does not attempt to quantify this set of refueling emissions. As such, the NONROAD model refueling emissions associated with nonroad equipment being filled directly at the gasoline pumps will be used to represent the nonroad Stage II emission component. Stage II control factors listed in Table IV-1 were input in the county-specific NONROAD model option files. Once the model runs were performed, Pechan extracted the refueling and spillage emissions corresponding only to those engines (typically the larger horsepower engines) within each SCC assumed to be refueled at the pump. The list of SCC and horsepower ranges associated with pump versus container refueling is specified in the model since different emission rates are assumed for these two types of refueling.
Table V-1 presents draft annual Stage II VOC emission estimates by State. These emissions were combined with the onroad vehicle Stage II estimates described in Section IV of this report.

### 45 Table V-1. 2002 Draft Stage II Refueling Emissions by State

FIPSST NAME VOC Emissions, tpy 01 Alabama 167.25 12 Florida 842.60 13 Georgia 209.01 21 Kentucky 112.65 28 Mississippi 147.18 37 North Carolina 298.49 45 Tennessee 197.81 47 South Carolina 155.33 51 Virginia 174.70 54 West Virginia 39.33



# VI. SUMMARY OF RESULTS

This chapter presents the emission results from the February 2004 draft version of the 2002 mobile source emissions inventory for the VISTAS region. These emissions result from the data and procedures described in the preceding chapters of this report.



## A. ONROAD RESULTS

Table VI-1 summarizes the latest 2002 VISTAS onroa d emissions inventory by State. This table also summarizes the total VMT for each State. Tables VI-2 and VI-3 are provided here for the purpose of comparing this inventory with anot her existing onroad inventory. The emissions shown in Table VI-2 are taken from Version 2 of EPA’s 1999 NEI. Table VI-3 then shows the percentage change from the 1999 NEI to the 2002 draft VISTAS inventory. If the two inventories had been developed using comparable data, one would generally expect to see reductions in the onroad emissions from 1999 to 2002 due to fleet turnover resulting in the replacement of older, dirtier vehicles with vehicles meeting more stringent emission standards. However, this reduction in per-vehicle emissions also needs to overcome increases in VMT for the overall emissions to decrease. All of the VISTAS States show increases in VMT from 1999 to 2002, except North Carolina. This decrease in VMT needs to be further investigated by the State agency. States that were modeled with significant State or locally supplied inputs in the VISTAS modeling, such as Virginia and Georgia, would be expected to have more significant differences from the NEI data than States with no State-supplied information other than VMT. Some of the State inputs that cause significant de viations from the NEI estimates are registration distributions, VMT mixes by vehicle type, and speeds by road type. In addition, some of the pollutants are more affected by these inputs, while others (such as NH 3 

### ) are minimally affected by these inputs. The 2002 VISTAS onroad emissions will continue to undergo review. Any comments or questions on these emissions by the State or local agencies will be investigated as part of this review.

### 46 Table VI-1. 2002 VISTAS Onroad Emissions and VMT by State (February 2004 Version)

2002 Annual Emissions (tons per year) 2002 Annual VMT State VOC NOx CO SO2 PM10 PM2.5 NH3 (million miles) Alabama 99,650 154,908 1,275,969 6,515 4,344 3,231 5,619 55,723 Florida 457,309 463,419 4,678,471 19,739 12,666 9,232 18,240 178,681 Georgia 215,035 311,125 2,601,785 11,487 8,038 5,942 10,612 106,785 Kentucky 79,110 164,231 1,196, 211 5,718 4,083 3,048 5,103 51,020 Mississippi 68,508 107,047 845,990 4,354 3,152 2,399 3,603 36,278 North Carolina 147,977 278,265 2, 116,829 9,953 6,374 4,741 7,868 80,166 South Carolina 92,491 136,569 1, 192,894 5,647 3,825 2,867 4,719 47,074 Tennessee 126,959 255,090 1,785,136 8,115 5,445 4,059 6,855 68,316 Virginia 115,044 182,513 1,858, 629 6,110 4,413 3,032 7,937 76,566 West Virginia 34,197 57,941 512,592 2,361 1,550 1,155 1,947 19,544 VISTAS Total 1,436,279 2,111,108 18,064,506 79,999 53,890 39,705 72,504 720,153


### Table VI-2. 1999 NEI Version 2 Onroad Emissions and VMT by State

1999 Annual Emissions (tons per year) 1999 Annual VMT State VOC NOx CO SO2 PM10 PM2.5 NH3 (million miles) Alabama 121,201 163,024 1,412,343 6,280 4,712 3,599 5,249 52,914 Florida 328,412 424,969 3,379,563 16,581 12,259 9,318 14,162 141,903 Georgia 207,562 313,568 2,526,592 12,028 9,263 7,139 9,787 98,859 Kentucky 97,286 162,160 1,225, 414 6,006 4,772 3,715 4,703 47,816 Mississippi 74,579 126,344 830,477 4,478 3,908 3,106 3,406 34,955 North Carolina 187,346 285,380 2, 252,671 10,829 8,462 6,552 8,663 87,759 South Carolina 98,010 153,346 1, 207,336 5,616 4,515 3,527 4,330 44,146 Tennessee 138,629 211,133 1,697,778 7,876 6,108 4,716 6,392 64,570 Virginia 150,528 238,515 1,861, 417 8,972 6,892 5,307 7,320 73,904 West Virginia 40,060 68,580 539,578 2,471 2,023 1,589 1,859 19,033 VISTAS Total 1,443,613 2,147,019 16,933,170 81,137 62,913 48,567 65,871 665,859

### 47 Table VI-3. Change in Onroad Emissions and VMT from 1999 NEI Version 2 to VISTAS 2002 Inventory (February 2004 Version)

Change from 1999 NEI V2 to 2002 VISTAS Draft Inventory State VOC NOx CO SO2 PM10 PM2.5 NH3 VMT Alabama -18% -5% -10% 4% -8% -10% 7% 5% Florida 39% 9% 38% 19% 3% -1% 29% 26% Georgia 4% -1% 3% -4% -13% -17% 8% 8% Kentucky -19% 1% -2% -5% -14% -18% 9% 7% Mississippi -8% -15% 2% -3% -19% -23% 6% 4% North Carolina -21% -2% -6% -8% -25% -28% -9% -9% South Carolina -6% -11% -1% 1% -15% -19% 9% 7% Tennessee -8% 21% 5% 3% -11% -14% 7% 6% Virginia -24% -23% 0% -32% -36% -43% 8% 4% West Virginia -15% -16% -5% -4% -23% -27% 5% 3% VISTAS Total -1% -2% 7% -1% -14% -18% 10% 8%



### Table VI-4 presents the latest 2002 VISTAS onroad refueling emission estimates by State.These refueling emissions are NOT included in the emissions shown in Tables VI-1 through VI3.
Table VI-4. 2002 VISTAS Annual Onroad Refueling Emissions

State 2002 Annual Onroad VOC Refueling Emissions (tons per year) Alabama 8,408 Florida 28,367 Georgia 12,329 Kentucky 6,885 Mississippi 6,057 North Carolina 15,320 South Carolina 8,926 Tennessee 9,901 Virginia 8,657 West Virginia 3,383 VISTAS Total 108,233



## B. NONROAD RESULTS

Table VI-5 provides a summary of draft 2002 nonroad sector annual emissions by State, including Stage II refueling emission estimates. Table VI-6 provides a summary of the draft 2002 NONROAD model emission estimates by State, and compares the values to 2001 NONROAD model NEI Version 2 estimates by showing the percent difference. A similar comparison is shown in Table VI-7 for other nonroad emission estimates compared to the 1999 NEI Version 2.

### 48 For the NONROAD model categories, SO 2 

### , PM 10, 

### PM 2.5 

### , and NH 3 

### decrease consistently across all States. SO 2 

### emissions decrease due in part to a lower diesel fuel sulfur content input for the NONROAD model runs, which also contributes to decreases in particulate emissions. The decrease in NH 3 

### is due primarily to corrections made to compresses natural gas (CNG) engine NH 3 

### emissions, which involved zeroing out the estimates. The 1999 NEI erroneously applied emission factors on a grams per gallon basis to CNG fuel consumption. Although reported as uncompressed gallons in the NONROAD model, the CNG fuel consumption estimates represent a gaseous, not liquid, volume. Based on OTAQ’s recommendations, CNG NH 3 

### emissions are now reported as zero. CO and NO x 

### show little change for all States, and changes in VOC vary by State and are dependent on the contribution of specific equipment categories (detail not shown).
For other nonroad categories, the increase in PM 10 

### and PM 2.5 

### is due to the addition of commercial aircraft PM emissions. Commercial aircraft PM 10 

### and PM 2.5 

### emissions were zero in the 1999 NEI; hence, the large percent increase. To gap fill this portion of the inventory, Pechan calculated and applied an average air taxi PM/NO x 

### emission ratio to commercial aircraft NO x 

### emissions. States with a higher proportion of co mmercial aircraft show significant PM increases (e.g., FL, TN, VA). In addition, NO x 

### emissions decrease due to new State data for other nonroad from AL and VA.

Table VI-5. Summary of Draft 2002 Nonroa d Sector Annual Emissions by State, tons per year

FIPSST STATE VOC NOX CO PM10-PRI PM25-PRI SO2 NH3

01 Alabama 46,788 64,367 373,634 5,504 4,895 7,529 32 12 Florida 211,006 153,396 1,765,539 61,426 45,849 17,453 109 13 Georgia 66,712 87,053 712,159 10,411 8,666 7,914 55 21 Kentucky 35,537 100,989 294,929 8,538 7,249 13,771 28 28 Mississippi 33,443 90,190 217,407 5,795 5,194 11,537 23 37 North Carolina 75,020 81,264 742,822 12,814 10,379 7,281 62 45 South Carolina 43,231 46,518 375,469 4,115 3,678 4,465 29 47 Tennessee 52,333 118,690 461,976 14,727 11,692 12,478 41 51 Virginia 61,655 69,668 614,958 21,580 16,497 11,068 44 54 West Virginia 15,497 36,613 120,029 2,293 2,034 2,388 10

### 49 Table VI-6. Summary of Draft 2002 NONRO AD Model Emission Estimates by State

2002 DRAFT VISTAS NONROAD Model Inventory, tpy FIPSST STATE VOC_ANN NOX_ANN CO_ ANN PM10_ANN PM25_ANN SO2_ANN NH3_ANN

01 Alabama 44,501.18 28, 635.48 365,161.12 3,306.84 3,044.48 2,729.32 31.92 12 Florida 205,489.66 86, 654.40 1,730,125.77 12,890.06 11,862.13 9,113.26 109.02 13 Georgia 65,054.02 51, 452.93 705,292.75 5,493.33 5,057.34 5,025.11 54.97 21 Kentucky 32,836.91 28,253.72 283,488.53 3,152.29 2,901.82 2,777.69 28.00 28 Mississippi 31,097.14 23,549.89 207, 824.23 2,761.65 2,542. 05 2,375.53 23.37 37 North Carolina 73,610. 93 58,667.62 734,496. 85 6,095.96 5,613. 11 5,442.35 62.06 45 South Carolina 41,652. 41 26,212.76 366,737. 16 3,028.92 2,788. 66 2,461.79 29.29 47 Tennessee 48,626.66 39, 833.95 446,461.43 4,240.53 3,904.21 3,810.11 41.22 51 Virginia 56,973.85 40,914.48 594, 020.13 4,739.47 4,362. 61 4,103.01 44.22 54 West Virginia 14,498.68 9,502. 33 115,652.49 1,038.29 955.70 980.17 10.31 2001 NONROAD Model NEI Version 2, tpy FIPSST STATE VOC_ANN NOX_ANN CO_ ANN PM10_ANN PM25_ANN SOX_ANN NH3_ANN

01 Alabama 43,602.83 28, 786.95 360,439.36 3,422.60 3,150.91 3,110.79 581.69 12 Florida 188,868.96 86, 835.32 1,713,539.62 13,243.04 12,186.78 10,456.05 1,305.25 13 Georgia 63,927.85 51, 521.66 698,868.77 5,678.55 5,227.63 5,749.47 989.31 21 Kentucky 31,662.34 28,350.32 279,283.79 3,274.35 3,014.06 3,127.88 463.74 28 Mississippi 29,037.96 23,671.70 205, 664.64 2,877.28 2,648. 40 2,668.55 359.21 37 North Carolina 69,671. 36 58,742.13 724,908.46 6,300.02 5,800.72 6,196.92 1,223.82 45 South Carolina 39,310. 79 26,304.57 363,112. 01 3,130.17 2,881. 75 2,817.02 507.81 47 Tennessee 47,193.97 39, 916.38 440,915.76 4,395.90 4,047.06 4,337.42 749.51 51 Virginia 55,459.80 41,082.63 585, 850.58 4,887.90 4,499. 09 4,677.52 627.60 54 West Virginia 13,912.53 9,568. 82 113,766.38 1,076.32 990.67 1,113.21 179.75 Percent Difference FIPSST STATE VOC_ANN NOX_ANN CO_ ANN PM10_ANN PM25_ANN SOX_ANN NH3_ANN

01 Alabama 2.06% -0.53% 1.31% -3 .38% -3.38% -12.26% -94.51% 12 Florida 8.80% -0.21% 0.97% -2.67% -2.66% -12.84% -91.65% 13 Georgia 1.76% -0.13% 0.92% -3.26% -3.26% -12.60% -94.44% 21 Kentucky 3.71% -0.34% 1.51% -3.73% -3.72% -11.20% -93.96% 28 Mississippi 7.09% -0.51% 1.05% -4.02% -4.02% -10.98% -93.50% 37 North Carolina 5.65% -0.13% 1. 32% -3.24% -3.23% -12.18% -94.93% 45 South Carolina 5.96% -0.35% 1. 00% -3.23% -3.23% -12.61% -94.23% 47 Tennessee 3.04% -0.21% 1.26% -3.53% -3.53% -12.16% -94.50% 51 Virginia 2.73% -0.41% 1.39% -3.04% -3.03% -12.28% -92.95% 54 West Virginia 4.21% -0.69% 1.66% -3.53% -3.53% -11.95% -94.26%

### 50 Table VI-7. Summary of Draft 2002 Other Nonroad* Emission Estimates by State

2002 DRAFT VISTAS Other Nonroad Inventory, tpy

FIPSST STATE VOC_ANN NOX_A NN CO_ANN PM10_ANN PM25_ANN SO2_ANN

01 Alabama 2,286.81 35,731.80 8, 473.33 2,196.87 1, 850.82 4,799.75 12 Florida 5,516.71 66,741.52 35, 413.13 48,536.33 33, 987.28 8,340.05 13 Georgia 1,657.99 35,599.76 6,865.94 4,917.40 3,609.14 2,889.06 21 Kentucky 2,699. 92 72,735.57 11,440.23 5, 385.61 4,346.83 10,992.91 28 Mississippi 2,345.96 66,640.48 9,582.89 3,033.69 2,652.14 9,161.66 37 North Carolina 1,409.01 22,596. 53 8,325.56 6,718.49 4,766.12 1,838.68 45 South Carolina 1,578.34 20,304. 80 8,732.26 1,086. 01 889.24 2,002.78 47 Tennessee 3,706.17 78,855.60 15, 514.17 10,486.01 7, 787.92 8,667.84 51 Virginia 4,681.39 28,753.43 20,938.22 16,840.30 12,134.84 6,965.04 54 West Virginia 998.41 27,110. 49 4,376.64 1,254.86 1,077.93 1,408.05 1999 Other Nonroad NEI Version 2, tpy FIPSST STATE VOC_ANN NOX_A NN CO_ANN PM10_ANN PM25_ANN SO2_ANN

01 Alabama 7,309.83 152,338.93 25, 075.50 1,315.93 1, 176.15 3,854.54 12 Florida 3,945.18 56,197.72 25, 350.10 2,110.74 1, 881.95 6,878.28 13 Georgia 2,594.07 39,245.14 12,198.09 1, 072.08 953.43 3,070.41 21 Kentucky 2,676. 93 62,930.31 12,388.06 2, 370.31 2,153.93 8,965.67 28 Mississippi 1,755.99 48,927.22 8,072.51 1,917.16 1,747.89 7,051.91 37 North Carolina 1,447.95 17, 999.44 8,739.21 540. 09 470.85 1,508.40 45 South Carolina 2,470.03 18, 034.10 13,291.47 561. 99 503.60 1,858.19 47 Tennessee 2,426.97 51,133.47 11, 127.02 1,786.06 1, 616.72 6,266.91 51 Virginia 2,682.78 51,592.64 13,083.30 1,632.38 1,462.82 4,769.97 54 West Virginia 1,133.03 30,991. 75 4,858.71 1,151.55 1,048.38 4,097.15 Percent Difference FIPSST STATE VOC_ANN NOX_A NN CO_ANN PM10_ANN PM25_ANN SO2_ANN

01 Alabama -69% -77% -66% 67% 57% 25% 12 Florida 40% 19% 40% 2199% 1706% 21% 13 Georgia -36% -9% -44% 359% 279% -6% 21 Kentucky 1% 16% -8% 127% 102% 23% 28 Mississippi 34% 36% 19% 58% 52% 30% 37 North Carolina -3% 26% -5% 1144% 912% 22% 45 South Carolina -36% 13% -34% 93% 77% 8% 47 Tennessee 53% 54% 39% 487% 382% 38% 51 Virginia 74% -44% 60% 932% 730% 46% 54 West Virginia -12% -13% -10% 9% 3% -66% *Includes emissions from aircraft, co mmercial marine and locomotive SCCs

### 51 

# VII. OBSERVATIONS AND RECOMMENDATIONS FOR IMPROVEMENT

This chapter lists several areas where the onroad and nonroad emission inventories could be improved. Some of these improvements require a long lead-time for the States and would not likely be available for the final 2002 VISTAS modeling, but could improve future State and regional inventory efforts.



## A. ONROAD SECTOR IMPROVEMENTS

In the onroad sector, significant improvements have been made to the inventory due to the State and local agencies providing 2002 VMT data by county and roadway type. For this February 2004 version of the VISTAS onroad inventory, only the Virginia VMT were projected by Pechan. It is anticipated that this States will be able to provide 2002 VMT data for use in the next revision of the inventory.
Local registration distribution data were provided by fewer than half of the VISTAS States. In many cases, registration data can be obtained from State Departments of Motor Vehicles. States that do not already do so should request a downl oad of the data summarizing registrations by model year and vehicle class from their appropriate motor vehicle agency. Although it is probably too late in many cases to obtain 2002 data, 2003 registration data could be used with some adjustments in developing the 2002 emission inventories. Registration data will become even more important as VISTAS prepares to project a 2018 onroad emission inventory, since the 2018 projections will be affected by the number of vehicles that are subject to the Tier 2 emission standards and the new heavy duty vehicl e standards. The registration distributions directly determine the proportion of vehicles subject to these new emission standards.
A relatively small amount of data was obtained regarding the distribution of VMT by season or month. Many State Departments of Transportation collect data that could be used to better distribute VMT by season or month. States should check to see what is available. These distributions will affect the episodic modeling that will be conducted by VISTAS. Pechan is currently performing a VMT scoping study for VISTAS to determine what data are available for better allocating VMT and emissions by month, day, and hour. These temporal improvements are expected to be incorporated into the next update of the VISTAS onroad emission inventory.
Due to the direct relationship between the VMT mix by vehicle type and the overall emissions, States should investigate potential sources of information for this data to replace the default data used here in most States.
EPA is currently in the process of preparing guidance on estimating emissions from heavy duty vehicles during long-term idling (sometimes referred to as hotelling). While these emissions are theoretically included in the MOBILE6 HDDV emission factors, they are not currently accounted for in the appropriate locations. For example, these emissions would typically occur at rest stops, trucking centers, and warehouse and distribution centers. With the current modeling, these emissions are spread over all counties, based on the VMT traveled by HDDVs in each county. If significant sources of truck idling emissions occur in or near Class I areas, the

### 52 current modeling may be underestimating the effect of these emissions. If States are able to obtain data on the locations and utilization of truck rest stops, some of this emissions effect could be more appropriately accounted for in future versions of VISTAS modeling.



## B. NONROAD SECTOR IMPROVEMENTS

NH 3 

### emissions for aircraft, commercial marine and locomotives are still reported as zero. As a result of recent communications with OTAQ, Pechan would suggest applying the updated nonroad diesel NH 3 

### emission factors used for the NONROAD model categories to activity data for commercial marine vessels and locomotives. To develop ammonia from commercial marine vessels and locomotives, Pechan would need to obtain or compile the county-level fuel consumption estimates used as the basis for 1999 emissions for these categories to use as the activity data for calculating updated NH 3 

### emissions. The presence of State or local data in the 1999 NEI does not allow for this to be determined easily by backing out the reported emission factors, and in some cases (e.g., diesel commercial marine), actual emissions (instead of activity) were obtained at a national level and allocated to counties (EPA, 2002). Alternatively, Pechan could use county level fuel consumption estimates developed for these categories for 2000 or 2001. These activity data were used by Pechan to estimate dioxin/furan emission estimates for the 2000 and 2001 NEI. Pechan could normalize the 2000 or 2001 county distribution to national level fuel consumption estimates for 1999. Due to the characteristics of aircraft jet and piston engines, Pechan does not recommend estimating aircraft NH 3 

### emissions using the available NH 3 

### emission factors.


# VIII. REFERENCES

EPA, 1989: “Procedures for Emission Inventory Preparation, Volume IV: Mobile Sources.” U.S. Environmental Protection Agency, Office of Mobile Sources and Office of Air Quality Planning and Standards, EPA 450/4-81-026d (Revised). July 1989.

EPA, 2002. “Documentation for Aircraft, Commercial Marine Vessel, Locomotive, and Other Nonroad Components of the National Emi ssions Inventory,” prepared by Eastern Research Group, Morrisville, NC for the U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Re search Triangle Park, NC. September 30, 2002.
Harvey, 1983. Craig Harvey, et al. “A Study of the Potential Impact of Some Unregulated Motor Vehicle Emissions.,” SAE Paper 830987. June 1983.
Harvey, 2003. C. Harvey, U.S. Environmental Pr otection Agency, Office of Transportation and Air Quality, e-mail entitled “NH3 Emission Updates,” sent to K. Thesing, E.H. Pechan & Associates, Inc. June 30, 2003.

USACE, 2000: Waterborne Commerce of the United States, Calendar Year 1999 , IWR-WCUS99-2 U.S. Army Corps of Engineers. 2000.

### 53 USACE, 2003: U.S. Waterways Data, Port and Wa terway Facilities, [Data file]. Accessed from U.S. Army Corps of Engineers, http://www.iwr.usace.army.mil/ndc/data/datapwd.htm on December 12, 2003.

### [This page intentionally left blank.]west virginia department of environmental protection



# Appendix D.1.b. Documentation of the Base G 2002 Base Year, 2009 and 2018 Emissions Inventory for VISTAS, MACTEC, Inc.

Promoting a healthy environment.

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## 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)

July 2, 2007

Prepared by:

MACTEC, Inc.

______________________ ______________________
William R. Barnard Edward Sabo Sr. Principal Scientist Principal ScientistDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. i 

## Table of Contents

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

1.0 2002 BASE YEAR INVENTORY DEVELOPMENT ....................................................................................... .7

1.1 P OINT S OURCES

............................................................................................................................... ............7 1.1.1 Development of 2002 Po int Source Inventory ..................................................................................... ..7
1.1.1.1 Data Sources ................................................................................................................... ............................. 8 1.1.1.2 Initial Data Evaluation ........................................................................................................ ......................... 9 1.1.1.3 PM Augmen tation................................................................................................................ ...................... 10 1.1.1.4 EGU Analysis ................................................................................................................... ......................... 13 1.1.1.5 QA Review of Base F Inventory.................................................................................................. .............. 14 1.1.1.6 Additional Base G Upda tes and Co rrections...................................................................................... ........ 15 1.1.1.7 Summary of Base G 2002 Inve ntory............................................................................................... ........... 18 1.1.2 Development of Typical Year EGU in ventory...................................................................................... 21 1.2 A REA S OURCES

............................................................................................................................... ..........23 1.2.1 Development of a “typical ” year fire inventory ................................................................................. .25 1.2.2 Development of n on-fire inve ntory .............................................................................................. ........34 1.2.3 2002 Base G inventory updates .................................................................................................. .........37
1.2.3.1 Changes resulting from St ate review and comment ................................................................................ ... 37 1.2.4 Ammonia and paved road emissions............................................................................................... .....40 1.2.5 Global Changes Ma de for Base G................................................................................................. ......41 1.2.6 Quality Assura nce steps........................................................................................................ ...............42 1.3 M OBILE S OURCES

............................................................................................................................... ......43 1.3.1 Development of on-road mobile so urce input files and VMT estim ates...............................................44
1.3.1.1 Emissions from on-road mobile sources .......................................................................................... .......... 45 1.3.2 Development of non-road emission estimates..................................................................................... .48
1.3.2.1 Emissions from NONRO AD model s ources........................................................................................... ... 48 1.3.2.2 Emissions from Commercial Marine Vesse ls, Locomotives, a nd Airpla nes.............................................. 64 Base G R evision s: .............................................................................................................. ................................81
1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indian a, and Ohio .............................................. 88 1.3.3 Quality Assura nce steps........................................................................................................ ...............90

2.0 PROJECTION INVENTORY DEVELOPMENT........................................................................................... .91

2.1 P OINT S OURCES

............................................................................................................................... ..........91 2.1.1 EGU Emission Projec tions ....................................................................................................... ...........91
2.1.1.1 Chronology of the Developm ent of EGU Projec tions............................................................................... . 91 2.1.1.2 VISTAS IPM runs for EGU sources................................................................................................ .......... 95 2.1.1.3 Post-Processing of IP M Parsed Files ............................................................................................ ............. 96 2.1.1.4 Eliminating Double C ounting of EGU Units ....................................................................................... ...... 98 2.1.1.5 Quality Assurance steps........................................................................................................ ..................... 99 2.1.1.6 S/L Adjustments to IPM Modeling Results for Base G Projec tions......................................................... 100 2.1.1.7 Summary of Base F and Base G 2009/2018 EGU Point Source Inventor ies ........................................... 101 2.1.2 Non-EGU Emission Projections ................................................................................................... .....114
2.1.2.1 Growth assumptions for non-EGU sources......................................................................................... ..... 114 2.1.2.2 Source S hutdow ns............................................................................................................... ..................... 116 2.1.2.3 Control Programs applie d to non-E GU sour ces .................................................................................... ... 118Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. ii 2.1.2.4 Quality Assurance steps........................................................................................................ ................... 121 2.1.2.5 Additional Base G Upda tes and Co rrections...................................................................................... ...... 121 2.1.2.6 Summary of Revised 2009/2018 non-E GU Point Source I nventorie s...................................................... 121 2.2 A REA S OURCES

............................................................................................................................... ........127 2.2.1 Stationary ar ea sources ........................................................................................................ .............127
2.2.1.1 Stationary area source controls ................................................................................................ ................ 129 2.2.1.2 Stationary area source growth.................................................................................................. ................ 131 2.2.1.3 Differences be tween 2009/2018

.................................................................................................. ............. 131 2.2.2 Agricultural ar ea sources ...................................................................................................... ............132
2.2.2.1 Control assumptions for agri cultural area sources .............................................................................. ..... 132 2.2.2.2 Growth assumptions for agri cultural area sources ............................................................................... .... 132 2.2.3 Changes to Prescribed Fire for 2009/2018 Base G...........................................................................137 2.2.4 Quality Assura nce steps........................................................................................................ .............142 2.3 M OBILE S OURCES

............................................................................................................................... ....142 2.3.1 Development of on-road mobi le source inpu t files ............................................................................145
2.3.1.1 Preparation of revised 2018 input data files................................................................................... .......... 145 2.3.1.2 Preparation of initial 2009 input data files ................................................................................... ............ 148 2.3.2 VMT Data ....................................................................................................................... ...................149 2.3.3 Base G R evisions ............................................................................................................... ................154 2.3.4 Development of non-road emission estimat es....................................................................................1 54
2.3.4.1 NONROAD model source s.......................................................................................................... ............ 155 2.3.4.2 Non-NONROAD m odel s ources...................................................................................................... ........ 157 2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indian a, and Ohio ............................................ 192 2.3.4.4 Differences be tween 2009/2018

.................................................................................................. ............. 192 2.3.5 Quality Assura nce steps........................................................................................................ .............193



### 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

MACTEC, Inc. iii 

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

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### List of Tables (continued)

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

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### Acronyms and Abbreviations (continued)

SCC Source Classification Code 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

MACTEC, Inc. 2 

### 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.
Following release of the Base G inventory in early 2007, four States specified additional changes to reflect their best estimates of EGU emission levels and controls in 2018. The resulting 2018 EGU emission inventory is referred to as Base G2.
This document details the development of the Base G/G2 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 G2 Base G2 Base G Base G Base G2 Base G Base G Base G Base G2 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/G2 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

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### The next version of the 2002 inventory (referred to as Base F) was released in August 2005 ( Documentation of the Revised 2002 Base Year, Revised 2018, and Initial 2009 Emission Inventories for VISTAS , MACTEC, August 2, 2005). The primary task in preparing the Base F 2002 base year inventory was the replacement of NEI99V2 data with data submitted by the VISTAS S/L agencies as part of the CERR submittal and included in EPA’s 2002 NEI.

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

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### 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.

• 

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

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### PM-CON Primary PM, condensable por tion only (all less than 1 micron) PM-FIL Primary PM, filterable portion only

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

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

• PM-PRI less than 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

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### emission unit ID. We created an Excel spreadsheet that contained an initial crosswalk with the ORIS ID and unit ID in the CEM 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

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### inventories and that there were no remaining QA issues. After exporting the inventory to ASCII text files in NIF 3.0, the EPA QA program 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 compone nt 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 an d 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 prior to 2002, then we used zero emissions for the typical year. If the unit had not been permanently retired and would normally operate in a typical year, then we used the 2001 (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 y ear 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 maintained as reported. For wildfire s, 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.29Table 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.30Figure 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.31Figure 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.32Figure 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.33Figure 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 acc urately 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 invent ories. 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 th e 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:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### • Final NONROAD2005 reflects the latest basic emission rate and deterioration data.

• 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. 53 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 made. 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. 61 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, Rutherfo rd, Sumner, Williamson and Wilson counties, the Memphis area consists of Shelby County.



### As with the Base F revisions, the seasonal data are based on simple arithmetic averages and do not consider any monthly 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 N ONROAD input files (as compared to the files used to create both the initial VISTAS non-road inventory, as documented in the February 9, 2004 reportDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### “ 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 lo cal aircraft operating mode ti mes. For this work, emission estimates for Tucson were recalculated for a standard LTO cycle, so that the ratios presented are applicable to the standard LT O cycle and not a Tucson-specific cycle. Thus, the ratios presented herein vary somewhat from thos e associated with the emission estimates presented in the Tucson study report.



### In reviewing these data, it should be considered that they apply to a standard (i.e., EPA-defined) commercial aircraft LTO cycle. 2 

### Aircraft PM-to-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 employed for inventory purposes th roughout the United States (as encoded in models such as the

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

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

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### 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 previ ously unreported data). The 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:

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

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### 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 removing NO x 

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

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### 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.
Following release of the Base G inventory in ear ly 2007, four States spec ified additional changes to reflect their best estimates of emission cont rols in 2018. These additional changes are marked with an “*” in Tables 2.1-1 and 2.1-2. The fo llowing changes were requested and implemented in the VISTAS 2018 Base G2 EGU em issions and modeling inventories:

o Florida - Removed scrubbers from Smith units 1 & 2. Added scrubbers to Crist units 4, 5, & 6. Forecast emissions (from 2002 base) using growth factors for Northside units 1A and 2A. These units were estimated to be non operational in the IPM base case run.

o Georgia - Added scrubbers to Plant Sc herer (Units 1-4) and Pl ant Yates (Units 6 & 7).

o North Carolina - Remove scrubber from F Lee unit 3.

o West Virginia - Pleasants Units 1 and 2 had SO2 em issions reduced to account for the facility's inclusion of previously bypassed 15% effluent stream to the scrubber and the control efficiency and emissions will reflec t a change from 79.9% to 95% control.

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.102Table 2.1-1 Adjustments to IPM Control Determinations Specified by S/L Agenciesfor the Base G 2009/2018 EGU Inventories.NOxRetrofit Emission ControlsSO2Retrofit Emission 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 ScrubberFL Lansing Smith 1 None None SCR SCR None None Scrubber None*ORISID=643 2 None None SCR SCR None None Scrubber None*NorthsideORISID=6671A &1BNooperationNooperationNooperationNooperationNooperationNo control,emissionsforecastedusinggrowthrates*NooperationNo control,emissionsforecastedusinggrowthrates*Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.103Table 2.1-1 (continued)NOxRetrofit Emission ControlsSO2Retrofit Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateFL Crist 4 None None None None None None None Scrubber*ORISID=641 5 None None None None None None None Scrubber*6 None None None None None None None Scrubber*GA 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 ScrubberWansley 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, 5 None None SCR SCR None None Scrubber None6, 7 None None SCR SCR None None Scrubber Scrubber*Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.104Table 2.1-1 (continued)NOxRetrofit Emission ControlsSO2Retrofit Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateGA Hammond 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 ScrubberScherer 1 None None None None None None None Scrubber*ORISID=6257 2 None None None None None None None Scrubber*3 None None None None None None None Scrubber*4 None None None None None None None Scrubber*KY 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 ScrubberE 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 ScrubberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.105Table 2.1-1 (continued)NOxRetrofit Emission ControlsSO2Retrofit Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateSC Canadys 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, except for Lee #3* where IPM projected a retrofit scrubber but NC specified that no scrubber was to be applied.

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

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 ORISID=7537 1A, 1B SO 2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. Used SO 2 Permit Rate 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 2018
Pleasants Power Station ORISID=6004 1, 2 IPM applied a scrubber with a 79.9% control efficiency; WV indicated that the control e fficiency should be 95%.Documentation 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 Base G 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 447,828 340,194 378,052 190,099 135,851

FL 453,631 195,790 186,055 141,551 138,340
GA 514,952 534,469 417,449 180,178 98,248

KY 484,057 371,944 290,193 229,603 226,062
MS 67,429 85,629 76,579 27,230 15,146
NC 477,990 205,018 242,286 110,382 114,771
SC 206,399 171,206 124,608 121,694 93,274

TN 334,151 255,400 255,410 112,662 112,672
VA 241,204 169,714 193,112 90,935 114,255

WV 516,084 226,127 277,489 124,466 105,935 Total 3,743,725 2,555,491 2,441,233 1,328,800 1,154,554

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 Base G 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 74,640
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 62,547 49,420 66,074

WV 230,977 63,510 86,328 51,241 51,241

Total 1,523,449 655,718 723,716 492,913 552,203

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 2,422
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 1,014

WV 1,180 1,342 1,361 1,387 1,387

Total 12,516 12,247 13,155 15,174 16,383

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 54,146
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 15,564

WV 10,341 11,328 11,493 11,961 11,961

Total 141,218 157,989 152,790 222,114 225,647

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 10,022
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 13,832

WV 4,573 5,471 5,657 6,349 6,349

Total 113,918 122,477 113,607 157,419 154,958

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 6,886
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 81,884 122,527 120,939

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 the 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 forecas ts (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 reductions 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 were 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. MACT EC then allocated the 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/

20

02

3/1/20 02 4/ 1/

20

02

5/

1/

20

02 6/1/ 20

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02 8/1/20 02 9/ 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.141Table 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 in itial 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., th at 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 output 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 importa nt 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

MACTEC, Inc. 171 

### 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. 172 118,739 130,798 145,885

129,659 159,122

0 20,000 40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000

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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. 173 420,228 397,462 367,975 455,067

395,049

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169,635

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167,783

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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. 174 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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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. 175 5,232

3,995

3,368 5,505

3,552

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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. 176 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. 177 7,750 7,328 6,785 8,738

7,544

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2002 2009 2018 2002 Prelim 2018 Prelim T
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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. 178 

### 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. 179 

### 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. 180 

### 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. 181 

### • 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. 182 

### 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. 183 

### 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

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### Table 2.3-22. Change in Emissions between 2009 Base G and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO 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

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### Table 2.3-23. Change in Emissions between 2018 Base G and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO 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. 186 125,597 139,362 157,427

129,659 159,122

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19,568 20,420 21,539 21,980 23,849

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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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. 187 421,918 399,364 370,651 455,067

395,049

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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187,328 169,808
147,527 211,588

167,783

0 50,000 100,000 150,000 200,000 250,000

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. 188 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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5,815

4,437

3,743 6,118

3,947

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000

2002 2009 2018 2002 Prelim 2018 Prelim 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. 189 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. 190 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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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

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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. 191 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

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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

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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. 192 

### 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. 193 

### 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

Appendix A MACTEC, Inc. 194 

### APPENDIX A:

STATE EMISSION TOTALS BY POLLUTANT AND SECTORDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASAppendix AMACTEC, Inc.195Annual 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

Appendix A MACTEC, Inc. 196 

### Annual CO Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 11,279 174,271 1,303,508 414,385 83,958 474,959 2002 Actual 11,460 174,260 1,303,508 414,385 83,958 514,120 2002 Typical 14,986 180,369 902,469 454,686 66,654 534,873 2009 AL 24,342 201,794 594,725 488,924 59,626 535,658 2018 57,113 81,933 4,493,820 1,920,729 71,079 790,620 2002 Actual 55,899 81,928 4,493,820 1,920,729 71,079 923,310 2002 Typical 35,928 87,037 3,308,863 2,104,920 57,011 923,310 2009 FL 54,146 96,819 2,263,190 2,323,327 53,903 923,310 2018 9,712 130,656 2,699,650 791,158 108,083 654,411 2002 Actual 9,650 130,656 2,699,650 791,158 108,083 620,342 2002 Typical 23,721 147,215 1,956,263 882,970 94,130 637,177 2009 GA 44,476 167,644 1,303,529 973,872 93,827 637,177 2018 12,619 109,936 1,214,191 325,993 66,752 8,703 2002 Actual 12,607 109,937 1,214,191 325,993 66,752 24,900 2002 Typical 15,812 122,024 950,912 357,800 57,887 31,810 2009 KY 17,144 139,437 711,211 381,215 54,865 33,296 2018 5,303 54,568 853,774 236,752 37,905 13,209 2002 Actual 5,219 54,567 853,774 236,752 37,905 14,353 2002 Typical 5,051 57,748 602,257 257,453 27,184 48,160 2009 MS 15,282 66,858 394,247 270,726 22,099 50,037 2018 13,885 50,531 2,839,283 808,231 345,315 34,515 2002 Actual 14,074 50,531 2,839,283 808,231 345,315 71,970 2002 Typical 14,942 53,696 1,966,195 887,605 301,163 96,258 2009 NC 20,223 62,145 1,207,391 960,709 290,809 111,266 2018 6,990 56,315 1,226,555 413,964 113,714 248,341 2002 Actual 6,969 56,315 1,226,555 413,964 113,714 253,005 2002 Typical 11,135 60,473 878,825 448,625 90,390 282,307 2009 SC 14,786 68,988 588,536 481,332 83,167 282,307 2018 7,084 114,681 1,893,704 505,163 89,828 4,302 2002 Actual 6,787 114,681 1,893,704 505,163 89,828 10,124 2002 Typical 7,214 119,039 1,320,562 554,121 74,189 17,372 2009 TN 7,723 140,138 863,682 593,100 68,809 18,860 2018 6,892 63,796 2,136,288 660,105 155,873 15,625 2002 Actual 6,797 63,784 2,136,288 660,105 155,873 12,611 2002 Typical 12,509 68,346 1,435,359 726,815 128,132 21,130 2009 VA 15,564 76,998 954,463 797,683 121,690 26,923 2018 10,341 89,879 526,841 133,113 39,546 6,738 2002 Actual 10,117 89,878 526,841 133,113 39,546 2,652 2002 Typical 11,493 100,045 360,865 152,862 31,640 3,949 2009 WV 11,961 119,332 243,683 167,424 28,773 5,013 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASAppendix AMACTEC, Inc.197Annual 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

Appendix A MACTEC, Inc. 198 

### Annual NH 3 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 317 1,883 5,530 33 58,318 1,689 2002 Actual 239 1,883 5,530 33 58,318 1,957 2002 Typical 359 2,132 6,298 36 64,268 2,050 2009 AL

1,072 2,464 6,630 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 1,631 1,544 21,737 148 38,616 3,157 2009 FL 2,976 1,829 26,154 171 40,432 3,157 2018 83 3,613 10,436 60 80,913 2,578 2002 Actual 86 3,613 10,436 60 80,913 2,153 2002 Typical 686 3,963 12,554 68 89,212 2,229 2009 GA 1,677 4,797 13,511 79 99,885 2,229 2018 326 674 5,003 31 51,135 39 2002 Actual 321 674 5,003 31 51,135 112 2002 Typical 400 760 5,737 34 53,005 143 2009 KY 476 901 7,095 40 55,211 150 2018 190 1,169 3,549 23 58,721 59 2002 Actual 198 1,169 3,549 23 58,721 65 2002 Typical 334 668 3,995 25 63,708 217 2009 MS 827 764 4,147 29 69,910 225 2018 54 1,179 9,601 65 161,860 155 2002 Actual 55 1,179 9,601 65 161,860 324 2002 Typical 445 1,285 11,702 72 170,314 433 2009 NC 663 1,465 12,776 83 180,866 501 2018 142 1,411 4,646 33 28,166 980 2002 Actual 141 1,411 4,646 33 28,166 908 2002 Typical 343 1,578 5,466 36 30,555 1,039 2009 SC 617 1,779 5,878 41 33,496 1,039 2018 204 1,542 6,556 43 34,393 19 2002 Actual 197 1,542 6,556 43 34,393 46 2002 Typical 227 1,764 7,702 48 35,253 78 2009 TN

241 2,115 8,196 55 36,291 85 2018 127 3,104 7,770 48 43,905 70 2002 Actual 130 3,104 7,770 48 43,905 57 2002 Typical 694 3,049 8,990 53 46,639 95 2009 VA

622 3,604 9,653 61 50,175 121 2018 121 332 1,889 9 9,963 30 2002 Actual 121 332 1,889 9 9,963 12 2002 Typical 330 341 2,126 11 10,625 18 2009 WV

180 413 2,268 13 11,504 23 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASAppendix AMACTEC, Inc.199Annual NOx Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L FL GA K Y MS N C S C T N 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

Appendix A MACTEC, Inc. 200 

### Annual NO x 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 161,038 83,310 156,460 65,366 23,444 10,728 2002 Actual 154,704 83,302 156,460 65,366 23,444 11,456 2002 Typical 82,305 69,409 100,693 56,862 23,930 11,901 2009 AL 64,358 78,318 42,622 43,799 25,028 11,918 2018 257,677 45,156 460,503 180,627 28,872 15,942 2002 Actual 282,507 45,150 460,503 180,627 28,872 19,791 2002 Typical

86,165 46,020 312,321 163,794 28,187 19,791 2009 FL 74,640 51,902 136,040 127,885 30,708 19,791 2018 147,517 49,214 304,309 97,961 36,142 14,203 2002 Actual 148,126 49,214 304,309 97,961 36,142 13,882 2002 Typical 98,497 50,312 207,024 85,733 37,729 14,243 2009 GA 75,717 55,775 92,113 64,579 41,332 14,243 2018 198,817 38,392 154,634 104,571 39,507 187 2002 Actual 201,928 38,434 154,634 104,571 39,507 534 2002 Typical 92,021 37,758 100,025 94,752 42,088 682 2009 KY 64,378 41,034 46,993 79,392 44,346 714 2018 43,135 61,526 110,672 88,787 4,200 283 2002 Actual 40,433 61,553 110,672 88,787 4,200 308 2002 Typical 36,011 56,398 69,952 80,567 4,249 1,033 2009 MS 10,271 61,533 27,620 68,252 4,483 1,073 2018 151,850 44,881 323,606 84,284 36,550 740 2002 Actual 148,809 44,881 323,606 84,284 36,550 1,544 2002 Typical 66,517 34,719 199,281 70,997 39,954 2,065 2009 NC 62,346 37,750 79,433 49,046 43,865 2,387 2018 88,241 42,153 138,941 50,249 19,332 4,932 2002 Actual 88,528 42,153 138,941 50,249 19,332 5,270 2002 Typical 46,915 40,019 91,471 43,235 19,360 5,899 2009 SC 51,456 44,021 39,348 31,758 20,592 5,899 2018 157,307 64,331 235,869 96,827 17,844 92 2002 Actual 152,137 64,331 235,869 96,827 17,844 217 2002 Typical 66,405 57,869 150,179 86,641 18,499 373 2009 TN 31,715 63,435 62,446 70,226 19,597 405 2018 86,886 60,415 219,835 63,219 51,418 335 2002 Actual 85,081 60,390 219,835 63,219 51,418 271 2002 Typical 62,547 51,046 132,699 54,993 52,618 453 2009 VA 66,074 55,945 57,192 40,393 56,158 578 2018 230,977 46,612 58,340 33,239 12,687 145 2002 Actual 222,437 46,618 58,340 33,239 12,687 57 2002 Typical

86,328 38,031 35,234 30,133 13,439 85 2009 WV 51,241 43,359 15,530 25,710 14,828 108 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASAppendix AMACTEC, Inc.201Annual PM10Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L FL GA K Y MS N C S C T N 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

Appendix A MACTEC, Inc. 202 

### Annual PM 10 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 7,646 25,240 3,861 4,787 393,588 47,237 2002 Actual 7,845 25,239 3,861 4,787 393,588 50,833 2002 Typical 6,969 25,421 3,136 4,027 413,020 52,851 2009 AL

7,822 29,924 2,193 3,041 445,256 52,927 2018 21,387 35,857 11,148 18,281 443,346 85,263 2002 Actual 21,391 35,856 11,148 18,281 443,346 98,470 2002 Typical

9,007 39,872 9,801 15,613 503,230 98,470 2009 FL

10,022 46,456 7,516 12,497 578,516 98,470 2018 11,224 21,516 7,165 8,618 695,414 65,227 2002 Actual 11,467 21,516 7,165 8,618 695,414 62,336 2002 Typical 17,891 22,997 6,005 7,521 776,411 63,973 2009 GA

20,909 27,143 4,406 6,015 880,199 63,973 2018 4,701 16,626 3,682 6,425 233,559 846 2002 Actual 4,795 16,626 3,682 6,425 233,559 2,421 2002 Typical 6,463 17,174 2,944 5,544 242,177 3,093 2009 KY

6,694 20,153 2,348 4,556 256,052 3,237 2018 1,633 19,472 2,828 5,010 343,377 1,284 2002 Actual 1,706 19,469 2,828 5,010 343,377 1,396 2002 Typical 4,957 19,245 2,250 4,270 356,324 4,683 2009 MS

7,187 22,859 1,479 3,452 375,495 4,865 2018 22,754 13,785 6,505 7,348 280,379 3,356 2002 Actual 22,994 13,785 6,505 7,348 280,379 6,998 2002 Typical 22,152 13,855 5,510 6,055 292,443 9,359 2009 NC

37,376 15,678 3,994 4,298 315,294 10,819 2018 22,754 13,785 6,505 4,152 260,858 25,968 2002 Actual 22,994 13,785 6,505 4,152 260,858 26,304 2002 Typical 22,152 13,855 5,510 3,471 278,299 29,153 2009 SC

37,376 15,678 3,994 2,617 304,251 29,153 2018 21,400 14,142 3,414 6,819 212,554 418 2002 Actual 21,827 14,142 3,414 6,819 212,554 984 2002 Typical 19,395 13,370 2,831 5,877 226,098 1,689 2009 TN

28,826 15,139 1,986 4,672 246,252 1,834 2018 14,640 34,534 5,312 8,728 237,577 1,519 2002 Actual 13,866 34,534 5,312 8,728 237,577 1,226 2002 Typical 15,608 34,145 4,160 7,510 252,488 2,054 2009 VA

15,941 41,397 2,813 6,208 275,351 2,618 2018 3,960 13,252 4,499 1,850 115,346 655 2002 Actual 3,892 13,252 4,499 1,850 115,346 258 2002 Typical 5,508 13,048 3,706 1,640 115,089 384 2009 WV

13,832 15,112 2,922 1,292 121,549 487 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASAppendix AMACTEC, Inc.203Annual PM2.5Emissions by Source Sector050,000100,000150,000200,000250,000 AL FL GA KY M S N C S C TN VA 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

Appendix A MACTEC, Inc. 204 

### Annual PM 2.5 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 4,113 19,178 2,768 4,502 56,654 42,041 2002 Actual 4,176 19,177 2,768 4,502 56,654 44,812 2002 Typical AL 3,921 19,230 2,010 3,776 58,699 46,543 2009

4,768 22,598 1,085 2,835 62,323 46,608 2018 15,643 30,504 7,779 17,415 58,878 75,717 2002 Actual 15,575 30,504 7,779 17,415 58,878 88,756 2002 Typical FL 5,910 33,946 6,104 14,866 64,589 88,756 2009

6,886 39,430 3,671 11,868 72,454 88,756 2018 4,939 17,394 5,110 8,226 103,794 57,293 2002 Actual 5,070 17,394 5,110 8,226 103,794 55,712 2002 Typical GA 10,907 18,906 3,797 7,175 112,001 57,116 2009

13,983 22,323 2,166 5,730 123,704 57,116 2018 2,802 11,372 2,667 6,046 45,453 726 2002 Actual 2,847 11,372 2,667 6,046 45,453 2,076 2002 Typical KY 4,279 11,686 1,899 5,203 46,243 2,653 2009

4,434 13,739 1,158 4,256 47,645 2,777 2018 1,138 9,906 2,089 4,690 50,401 1,102 2002 Actual 1,147 9,902 2,089 4,690 50,401 1,197 2002 Typical MS 4,777 9,199 1,491 3,985 51,661 4,016 2009

7,033 10,739 746 3,203 53,222 4,173 2018 16,498 10,455 4,571 7,005 64,052 2,878 2002 Actual 16,623 10,455 4,571 7,005 64,052 6,002 2002 Typical NC 15,949 10,411 3,453 5,760 69,457 8,027 2009

29,791 11,775 1,931 4,069 71,262 9,279 2018 17,154 10,245 2,473 3,945 40,291 22,953 2002 Actual 17,521 10,245 2,473 3,945 40,291 23,511 2002 Typical SC 16,042 9,390 1,834 3,294 41,613 25,955 2009

25,032 11,086 988 2,474 44,319 25,955 2018 12,166 27,345 3,904 6,458 42,566 359 2002 Actual 11,491 27,345 3,904 6,458 42,566 844 2002 Typical TN 13,092 27,079 2,720 5,557 44,124 1,449 2009

13,387 32,893 1,405 4,403 46,692 1,573 2018 2,606 10,165 3,067 8,288 43,989 1,303 2002 Actual 2,650 10,165 3,067 8,288 43,989 1,052 2002 Typical VA 4,067 9,988 2,216 7,136 44,514 1,762 '2009

11,976 11,594 1,404 5,891 46,697 2,245 2018 2,210 13,313 984 1,728 21,049 562 2002 Actual 2,163 13,313 984 1,728 21,049 221 2002 Typical WV 2,940 12,769 676 1,528 20,664 329 2009

3,648 16,516 369 1,198 21,490 418 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASAppendix AMACTEC, Inc.205Annual SO2Emissions by Source Sector0100,000200,000300,000400,000500,000600,000700,000 AL FL GA KY M S N C S C TN VA 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

Appendix A MACTEC, Inc. 206 

### Annual SO 2 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 447,828 96,481 6,827 7,584 52,253 2,208 2002 Actual 423,736 96,481 6,827 7,584 52,253 2,559 2002 Typical 378,052 101,246 802 3,471 48,228 2,681 2009 AL 135,851 113,224 654 2,818 50,264 2,686 2018 453,631 65,090 20,687 20,614 40,491 4,057 2002 Actual 483,590 65,090 20,687 20,614 40,491 4,129 2002 Typical 186,055 65,511 2,584 8,967 36,699 4,129 2009 FL 138,340 75,047 2,302 7,536 38,317 4,129 2018 514,952 53,774 12,043 9,005 57,559 3,372 2002 Actual 517,633 53,774 12,043 9,005 57,559 2,815 2002 Typical 417,449 53,983 1,568 2,725 57,696 2,914 2009 GA 98,248 59,343 1,325 1,709 59,729 2,914 2018 484,057 34,029 6,238 14,043 41,805 51 2002 Actual 495,153 34,029 6,238 14,043 41,805 146 2002 Typical 290,193 36,418 751 9,180 43,087 187 2009 KY 226,062 40,682 694 8,592 44,186 196 2018 67,429 35,960 4,566 11,315 771 78 2002 Actual 60,086 35,954 4,566 11,315 771 84 2002 Typical 76,579 25,564 532 7,191 753 283 2009 MS 15,146 39,221 401 6,638 746 294 2018 477,990 44,103 12,286 7,693 5,412 203 2002 Actual 478,488 44,103 12,286 7,693 5,412 423 2002 Typical 242,286 42,516 1,487 1,892 5,751 566 2009 NC 114,771 46,292 1,346 905 6,085 655 2018 206,399 53,518 5,909 4,866 12,900 1,281 2002 Actual 210,272 53,518 5,909 4,866 12,900 1,187 2002 Typical 124,608 48,325 713 1,701 13,051 1,359 2009 SC 93,274 53,577 584 1,198 13,457 1,359 2018 334,151 79,584 9,127 10,441 29,917 25 2002 Actual 320,146 79,584 9,127 10,441 29,917 60 2002 Typical 255,410 70,657 1,065 5,651 30,577 102 2009 TN 112,672 77,219 862 5,207 31,962 111 2018 241,204 63,903 8,196 8,663 105,890 92 2002 Actual 233,691 63,900 8,196 8,663 105,890 74 2002 Typical 193,112 62,560 1,067 1,707 105,984 124 2009 VA 114,255 68,909 949 507 109,380 158 2018 516,084 54,070 2,438 2,112 11,667 40 2002 Actual 500,381 54,077 2,438 2,112 11,667 16 2002 Typical 277,489 55,973 276 359 12,284 23 2009 WV 105,935 62,193 231 56 12,849 29 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASAppendix AMACTEC, Inc.207Annual VOC Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,0001,400,000 AL FL GA K Y M S NC S C 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

Appendix A MACTEC, Inc. 208 

### Annual VOC Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 2,295 47,037 125,768 60,487 182,674 25,278 2002 Actual 2,288 47,035 125,768 60,487 182,674 26,526 2002 Typical 2,473 46,644 76,065 50,249 143,454 27,502 2009 AL 2,952 54,291 44,503 40,407 153,577 27,539 2018 2,524 38,471 520,757 272,072 404,302 42,724 2002 Actual 2,531 38,471 520,757 272,072 404,302 51,527 2002 Typical 1,910 36,880 336,707 209,543 420,172 51,527 2009 FL 2,422 42,811 199,050 183,452 489,975 51,527 2018 1,244 33,157 279,975 85,965 299,679 33,979 2002 Actual 1,256 33,157 279,975 85,965 299,679 33,918 2002 Typical 2,314 33,444 192,773 67,686 272,315 34,710 2009 GA 2,841 39,485 99,464 56,761 319,328 34,710 2018 1,487 44,834 102,362 44,805 95,375 410 2002 Actual 1,481 44,834 102,362 44,805 95,375 1,172 2002 Typical 1,369 47,786 73,142 38,558 94,042 1,497 2009 KY 1,426 55,861 42,810 30,920 103,490 1,567 2018 648 43,204 86,811 41,081 131,808 622 2002 Actual 629 43,203 86,811 41,081 131,808 675 2002 Typical 404 37,747 51,600 36,197 124,977 2,266 2009 MS 1,114 45,338 28,699 28,842 140,134 2,355 2018 988 60,496 260,895 94,480 237,926 1,624 2002 Actual 986 60,496 260,895 94,480 237,926 3,387 2002 Typical 954 61,207 166,844 74,056 187,769 4,530 2009 NC 1,345 70,100 91,720 61,327 189,591 5,236 2018 470 38,458 114,861 55,016 161,000 14,202 2002 Actual 470 38,458 114,861 55,016 161,000 14,666 2002 Typical 660 35,665 71,781 43,061 146,107 16,045 2009 SC 906 43,656 41,866 36,131 161,228 16,045 2018 926 77,304 177,943 66,450 153,307 202 2002 Actual 890 77,304 177,943 66,450 153,307 476 2002 Typical 932 66,538 114,032 55,358 154,377 817 2009 TN 976 83,573 61,339 45,084 182,222 888 2018 754 43,152 157,989 74,866 174,116 735 2002 Actual 747 43,152 157,989 74,866 174,116 593 2002 Typical 778 43,726 95,694 57,009 147,034 994 2009 VA 1,014 53,186 55,992 49,052 150,919 1,267 2018 1,180 14,595 41,703 18,566 60,443 317 2002 Actual 1,140 14,595 41,703 18,566 60,443 125 2002 Typical 1,361 13,810 24,570 18,069 55,288 186 2009 WV 1,387 16,565 14,652 14,086 60,747 236 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix B MACTEC, Inc. 209 

### APPENDIX B:

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

Appendix B MACTEC, Inc. 210 

### 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

Appendix C MACTEC, Inc. 211 

### APPENDIX C:

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

Appendix C MACTEC, Inc. 212 

### 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 MFG 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 INDUSTRIES 13,606 0 878 194 155 22,991 4,024 AL 2002 07 OTHER INDUSTRIAL PROCESSES 47,676 1,468 25,252 22,689 9,516 17,904 25,304 AL 2002 08 SOLVENT UTILIZATION 216 0 226 149 126 3 108,437 AL 2002 09 STORAGE & TRANSPORT 174 0 230 1,086 636 13 16,522 AL 2002 10 WASTE DISPOSAL & RECYCLING 86,302 10 3,465 13,960 13,073 489 11,334 AL 2002 11 HIGHWAY VEHICLES 1,303,508 5,530 156,460 3,861 2,768 6,827 125,768 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 2,501,691 67,959 494,732 486,153 132,089 589,440 444,777 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 MFG 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 INDUSTRIES 13,241 0 858 221 177 22,495 3,336 AL 2009 07 OTHER INDUSTRIAL PROCESSES 52,004 1,571 26,340 24,196 10,197 19,383 26,519 AL 2009 08 SOLVENT UTILIZATION 247 0 257 165 139 4 92,631 AL 2009 09 STORAGE & TRANSPORT 192 0 253 1,146 584 14 17,738 AL 2009 10 WASTE DISPOSAL & RECYCLING 87,225 11 3,634 14,504 13,485 590 11,207 AL 2009 11 HIGHWAY VEHICLES 902,469 6,298 100,693 3,136 2,010 802 76,065 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 2,154,038 75,143 345,100 505,423 134,178 534,480 346,386 AL 2018 01 FUEL COMB. ELEC. UTIL. 24,342 1,072 64,358 7,822 4,768 135,851 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 MFG 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 INDUSTRIES 13,002 0 848 258 207 22,242 3,421 AL 2018 07 OTHER INDUSTRIAL PROCESSES 60,452 1,732 30,831 27,727 11,812 21,843 30,267 AL 2018 08 SOLVENT UTILIZATION 301 0 317 200 169 4 112,412 AL 2018 09 STORAGE & TRANSPORT 234 0 307 1,366 699 17 18,900 AL 2018 10 WASTE DISPOSAL & RECYCLING 88,758 13 3,867 15,343 14,143 718 11,938 AL 2018 11 HIGHWAY VEHICLES 594,725 6,630 42,622 2,193 1,085 654 44,503 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 1,905,069 84,177 266,042 541,163 140,217 305,497 323,270Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 213 

### 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 MFG 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 INDUSTRIES 1,070 0 560 259 129 470 724

FL 2002 07 OTHER INDUSTRIAL PROCESSES 18,586 19 12,325 23,419 11,844 6,515 27,024 FL 2002 08 SOLVENT UTILIZATION 0 0 1 128 110 0 304,582 FL 2002 09 STORAGE & TRANSPORT 161 0 561 1,645 720 38 79,281

FL 2002 10 WASTE DISPOSAL & RECYCLING 175,989 351 6,123 22,142 21,604 659 17,449 FL 2002 11 HIGHWAY VEHICLES 4,493,820 17,922 460,503 11,148 7,779 20,687 520,757 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 7,546,765 60,303 1,017,450 628,492 218,906 634,601 1,289,660 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 MFG 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 INDUSTRIES 1,190 0 612 304 156 519 748

FL 2009 07 OTHER INDUSTRIAL PROCESSES 18,593 26 13,521 33,084 19,357 6,881 26,413
FL 2009 08 SOLVENT UTILIZATION 0 0 1 132 113 0 319,723 FL 2009 09 STORAGE & TRANSPORT 187 0 621 1,661 727 50 83,880
FL 2009 10 WASTE DISPOSAL & RECYCLING 177,953 342 6,251 22,971 22,364 698 17,241 FL 2009 11 HIGHWAY VEHICLES 3,308,863 21,549 312,321 9,801 6,104 2,584 336,707 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 6,517,070 66,645 656,279 675,993 214,170 303,943 1,056,738 FL 2018 01 FUEL COMB. ELEC. UTIL. 54,146 2,976 74,640 10,022 6,886 138,340 2,422 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 MFG 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 INDUSTRIES 1,513 0 778 387 198 659 918

FL 2018 07 OTHER INDUSTRIAL PROCESSES 20,748 35 15,855 39,871 23,301 7,741 29,716 FL 2018 08 SOLVENT UTILIZATION 0 0 1 158 135 0 387,657 FL 2018 09 STORAGE & TRANSPORT 226 0 690 2,008 879 58 87,732

FL 2018 10 WASTE DISPOSAL & RECYCLING 180,730 418 6,486 24,140 23,427 769 18,335 FL 2018 11 HIGHWAY VEHICLES 2,263,190 23,778 136,040 7,516 3,671 2,302 199,050 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 5,714,695 72,343 440,967 753,477 223,065 265,672 969,237Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 214 

### 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 PRODUC T MFG 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 INDUSTRIES 41 0 3 69 44 68 175 GA 2002 07 OTHER INDUSTRIAL PROCESSES 27,960 2,666 12,215 39,630 13,073 8,701 26,999 GA 2002 08 SOLVENT UTILIZATION 4 0 22 13 13 0 234,744 GA 2002 09 STORAGE & TRANSPORT 39 0 6 583 360 0 26,334 GA 2002 10 WASTE DISPOSAL & RECYCLING 203,892 16 6,872 29,227 28,311 312 18,964 GA 2002 11 HIGHWAY VEHICLES 2,699,650 10,436 304,309 7,165 5,110 12,043 279,975 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 4,359,540 97,261 649,635 806,517 195,306 652,829 733,949
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 PRODUC T MFG 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 INDUSTRIES 50 0 4 83 54 82 154 GA 2009 07 OTHER INDUSTRIAL PROCESSES 29,976 2,902 12,528 45,339 14,758 7,662 28,441 GA 2009 08 SOLVENT UTILIZATION 4 0 25 14 14 0 216,248 GA 2009 09 STORAGE & TRANSPORT 45 0 7 649 401 0 27,821 GA 2009 10 WASTE DISPOSAL & RECYCLING 218,460 18 7,419 31,955 30,900 360 18,711 GA 2009 11 HIGHWAY VEHICLES 1,956,263 12,554 207,024 6,005 3,797 1,568 192,773 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 3,741,476 108,711 493,539 894,798 209,901 536,335 603,242
GA 2018 01 FUEL COMB. ELEC. UTIL. 44,476 1,677 75,717 20,909 13,983 98,248 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 PRODUC T MFG 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 INDUSTRIES 63 0 5 105 68 104 191 GA 2018 07 OTHER INDUSTRIAL PROCESSES 33,611 3,559 14,460 55,130 17,899 8,748 33,333 GA 2018 08 SOLVENT UTILIZATION 5 0 30 22 22 0 264,326 GA 2018 09 STORAGE & TRANSPORT 54 0 9 764 470 0 29,409 GA 2018 10 WASTE DISPOSAL & RECYCLING 235,690 22 8,120 35,280 34,038 423 20,411 GA 2018 11 HIGHWAY VEHICLES 1,303,529 13,511 92,113 4,406 2,166 1,325 99,464 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 3,220,524 122,178 343,759 1,002,646 225,021 223,268 552,588Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 215 

### 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 MFG 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 INDUSTRIES 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 1,214,191 5,003 154,634 3,682 2,667 6,238 102,362 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 1,754,380 57,276 539,608 267,509 70,460 591,414 290,028
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 MFG 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 INDUSTRIES 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 950,912 5,737 100,025 2,944 1,899 751 73,142 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 1,536,246 60,079 367,327 277,394 71,963 379,816 256,393
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 MFG 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 INDUSTRIES 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 711,211 7,095 46,993 2,348 1,158 694 42,810 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 1,337,166 63,872 276,856 293,040 74,007 320,412 236,073Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 216 

### 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 PR ODUCT MFG 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 INDUSTRIES 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 853,774 3,549 110,672 2,828 2,089 4,566 86,811 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 1,202,570 63,725 305,953 373,786 69,426 112,776 304,207
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 PR ODUCT MFG 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 INDUSTRIES 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 602,257 3,995 69,952 2,250 1,491 532 51,600 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 997,853 68,946 248,210 391,729 75,129 110,902 253,191
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 PRODUC T MFG 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 INDUSTRIES 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 394,247 4,147 27,620 1,479 746 401 28,699 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 5,219 198 40,433 1,706 1,147 60,086 629Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 217 

### 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 MFG 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 INDUSTRIES 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 MFG 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 INDUSTRIES 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 62,353 37,376 29,791 114,771 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 MFG 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 INDUSTRIES 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 2,956,008 196,655 277,119 387,788 128,356 170,031 416,523Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 218 

### 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 MFG 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 INDUSTRIES 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 1,226,555 4,646 138,941 3,414 2,473 5,909 114,861 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 2,070,523 35,305 344,473 330,696 97,987 288,651 384,470
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 MFG 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 INDUSTRIES 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 878,825 5,466 91,471 2,831 1,834 713 71,781 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 1,771,756 39,017 246,899 346,518 98,127 189,758 313,319
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 MFG 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 INDUSTRIES 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 588,536 5,878 39,348 1,986 988 584 41,866 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 1,519,116 42,852 193,074 381,972 109,853 163,450 299,832Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 219 

### 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 MFG 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 INDUSTRIES 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 1,893,704 6,556 235,869 5,312 3,904 9,127 177,943 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 2,620,287 42,776 567,225 274,069 92,608 449,275 476,370
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 MFG 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 INDUSTRIES 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 1,320,562 7,702 150,179 4,160 2,720 1,065 114,032 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 2,092,496 45,072 379,967 287,577 94,020 363,462 392,054
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 MFG 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 INDUSTRIES 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 863,682 8,196 62,446 2,813 1,405 862 61,339 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 1,692,314 46,983 247,822 312,908 100,354 228,034 374,082Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 220 

### 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 PRODUC T MFG 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 INDUSTRIES 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 2,136,288 7,770 219,835 4,499 3,067 8,196 157,989 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 3,035,458 55,012 480,213 269,174 69,210 420,414 451,463
VA 2009 01 FUEL COMB. ELEC. UTIL. 12,509 694 62,547 5,508 4,067 193,112 778 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 PRODUC T MFG 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 INDUSTRIES 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 1,435,359 8,990 132,699 3,706 2,216 1,067 95,694 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 2,392,291 59,520 354,356 284,314 69,684 364,554 345,235
VA 2018 01 FUEL COMB. ELEC. UTIL. 15,564 622 66,074 13,832 11,976 114,255 1,014 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 PRODUC T MFG 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 INDUSTRIES 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 954,463 9,653 57,192 2,922 1,404 949 55,992 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 1,993,321 64,237 276,340 316,043 79,806 294,158 311,430Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 221 

### 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 PR ODUCT MFG 50,835 80 1,627 950 831 9,052 5,755 WV 2002 05 METALS PROCESSING 28,837 143 1,570 8,749 7,515 5,619 1,393

WV 2002 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,086 475 475 7,550 2,163
WV 2002 07 OTHER INDUSTRIAL PROCESSES 2,003 56 5,347 18,751 5,567 2,316 1,803 WV 2002 08 SOLVENT UTILIZATION 15 0 18 49 44 0 35,989 WV 2002 09 STORAGE & TRANSPORT 15 0 3 1,952 947 0 12,432 WV 2002 10 WASTE DISPOSAL & RECYCLING 9,395 8 599 4,153 3,731 100 5,098 WV 2002 11 HIGHWAY VEHICLES 526,841 1,889 58,340 1,366 984 2,438 41,703 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 802,148 12,326 373,378 140,796 39,459 570,690 136,573
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 PR ODUCT MFG 58,271 82 1,804 987 864 10,166 5,426 WV 2009 05 METALS PROCESSING 30,939 142 1,517 7,985 6,724 5,971 1,380

WV 2009 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,221 535 535 8,495 2,172
WV 2009 07 OTHER INDUSTRIAL PROCESSES 2,288 59 4,995 19,228 5,899 2,570 2,064 WV 2009 08 SOLVENT UTILIZATION 17 0 20 52 47 0 32,305 WV 2009 09 STORAGE & TRANSPORT 17 0 3 2,062 1,003 0 12,997 WV 2009 10 WASTE DISPOSAL & RECYCLING 9,131 8 583 4,050 3,632 97 4,898 WV 2009 11 HIGHWAY VEHICLES 360,865 2,126 35,234 1,057 676 276 24,570 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 660,854 13,451 203,249 140,916 38,906 346,405 113,284
WV 2018 01 FUEL COMB. ELEC. UTIL. 11,961 180 51,241 6,349 3,648 105,935 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 PRODUC T MFG 70,252 99 2,183 1,188 1,041 12,280 6,560 WV 2018 05 METALS PROCESSING 36,850 183 2,061 10,944 9,372 7,182 1,790

WV 2018 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,407 616 616 9,786 2,338
WV 2018 07 OTHER INDUSTRIAL PROCESSES 2,756 68 5,949 21,347 6,794 3,101 2,561 WV 2018 08 SOLVENT UTILIZATION 20 0 24 61 55 0 38,023 WV 2018 09 STORAGE & TRANSPORT 19 0 4 2,522 1,225 0 13,394 WV 2018 10 WASTE DISPOSAL & RECYCLING 9,237 10 592 4,134 3,692 98 5,272 WV 2018 11 HIGHWAY VEHICLES 243,683 2,268 15,530 747 369 231 14,652 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 576,185 14,400 150,776 152,159 43,641 181,293 107,674Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix C MACTEC, Inc. 222 

### State Tier 1 Emission Totals

CO NH3 NOX PM10 PM2.5 SO2 VOC VISTAS 2002 Total 30,022,776 665,027 5,412,353 3,915,226 1,094,179 4,858,497 5,169,972 VISTAS 2009 Total 25,183,946 720,833 3,708,470 4,154,063 1,119,158 3,424,152 4,175,508 VISTAS 2018 Total 21,430,190 783,297 2,643,715 4,556,228 1,203,209 2,214,284 3,840,290Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix D MACTEC, Inc. 223 

### APPENDIX D:

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

Appendix D MACTEC, Inc. 224 

### VISTAS Tier 1 Emission Totals

Year TIER1 TIER1NAME CO NH3 NOX PM10- PRI PM25- PRI 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 19,187,613 72,902 2,163,168 49,780 35,411 88,316 1,869,063 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 30,022,776 665,027 5,412,353 3,915,226 1,094,179 4,858,497 5,169,972 2009 01 FUEL COMB. ELEC. UTIL. 152,790 5,449 723,717 113,607 81,884 2,441,233 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 13,682,570 86,118 1,398,879 41,400 26,200 10,844 1,203,208 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 25,183,946 720,833 3,708,475 4,154,063 1,119,158 3,424,154 4,175,508 2018 01 FUEL COMB. ELEC. UTIL. 225,647 9,351 552,202 154,957 120,938 1,154,555 16,382 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 9,124,656 93,932 599,336 30,403 14,922 9,348 680,096 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 21,430,189 783,297 2,643,715 4,556,227 1,203,209 2,214,284 3,840,290Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix E MACTEC, Inc. 225 

### APPENDIX E:

AIRCRAFT PM EXCERPT FR OM 2001 TUCSON REPORTDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix E MACTEC, Inc. 226Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

Appendix F MACTEC, Inc. 227 

### 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 VISTASAppendix FMACTEC, Inc.228Base 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 VISTASAppendix FMACTEC, Inc.229Annual 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 VISTASAppendix FMACTEC, Inc.230Annual 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 BaseFAnnual 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 VISTASAppendix FMACTEC, Inc.231Annual 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 VISTASAppendix FMACTEC, Inc.232Annual 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 VISTASAppendix FMACTEC, Inc.233Annual 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 VISTASAppendix FMACTEC, Inc.234Annual 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 BaseFwest virginia department of environmental protection



# Appendix D.1.c. Memorandum to VISTAS State Point Contacts and VISTAS EGU Special Interest Workgroup, from Gregory Stella, dated June 13, 2005

Promoting a healthy environment.

### [This page intentionally left blank.]Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

## MEMORANDUM

To: VISTAS State Point Source Contacts a nd VISTAS EGU Special Interest Workgroup From: Gregory Stella, VISTAS Techni cal Advisor - Emission Inventories Date: June 13, 2005 Re: EGU Emission Factors and Em ission Factor Assignment

Purpose
The purpose of this memorandum is to discuss the differences currently known to exist in the base year (2002) and future year (2009 and 2018) forecasts of EGU emission factors for PM and NH3. In particular, it has been identified that E. H. Pechan & Associates, Inc. (Pechan) in their development of post-processed IPM output into NIF structure uses a set of PM and NH3 emission factors that are “the most recent EP A approved uncontrolled emission factors” and which are most likely not the same emission factors used by States and emission inventory preparation contractors for estim ating these emissions in 2002 for EGUs in the VISTAS domain. Additionally, through re view of the code used to post-proce ss the IPM parsed files, it has also been determined that emission factors are assigned in future years based on Pechan assigned SCCs and not necessarily initial base year SCCs as coded in the original VISTAS NIF files.
A second objective of this memorandum is to pr opose a resolution to the issues at hand and to recommend a set of modifications to be made to the base year PM and NH3 emission estimates for this source category.

Background
VISTAS Base Year EGU Emissions Preparation
A major component to the development of the VI STAS point source sector of the inventory was the incorporation of data submitted by the VISTAS States and local (S/L) agencies to the United States Environmental Protection Agency (EPA) as part of the Consolidated Emissions Reporting Rule (CERR). Work on incorporating the CERR da ta into the revised base year involved: 1) obtaining the data from EPA or the S/L agenc y, 2) evaluating the em issions and pollutants reported in the submittal, 3) augmenting CERR da ta with annual emission estimates for PM10- PRI and PM25-PRI; 4) evaluating the emissi ons from electric generating units, and 5) completing quality assurance reviews for each component of the point source inventory.
Data from several sources were used: 1) the inventories that the S/L submitted to EPA from May through July 2004; 2) supplemental data supplied by the S/L agencies that may have been revised or finalized after submitta l to EPA, and 3) the original VISTAS 2002 inventory in cases where S/L CERR data were not available.Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### 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 only PM10-PRI Primary PM10 (includes filterable and condensable) PM10-FIL Primary PM10, filterable portion only PM25-PRI Primary PM25 (includes filterable and condensable) PM25-FIL Primary PM25, filterable portion only
State/local agencies did not report PM emissi ons in a consistent manner. The State/local inventories submitted for VISTAS included emissions data for either PM-FIL, PM-PRI, PM10- FIL, PM10-PRI, PM25-FIL, PM25-PRI, and/or PM -CON. From any one of these pollutants, EPA has developed augmentation procedures to estimate PM10-PRI, PM10-FIL, PM25-PRI, PM25-FIL, and PM-CON. If not included in a State/local inventory, PM10-PRI and PM25-PRI were calculated by adding PM10-FIL and PM-C ON or PM25-FIL and PM-CON, respectively. The procedures for augmenting point source PM em issions are documented in detail in Appendix C of Documentation for the Final 1999 National Em issions Inventory (Version 3) for Criteria Air Pollutants and Ammonia – Point Sources , January 31, 2004 1



### .
Briefly, the PM data augmentation procedure includes the following five steps:

• 

### Step 1: Prepare S/L/T PM and PM10 Emi ssions 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. Ammonia (NH3) emissions from these sources were assigned using direct incorporation of S/L/T provided emission estimates or via the applica tion of emission factors using ratios of NH3 emission factors to other reported pollutants (e.g., VOC, CO, etc.).
IPM Post Processing ICF via VISTAS contracts provided an initial sp readsheet file containi ng unit-level records of both (1) “existing” units and (2) committed or new generic aggregates. All records have unit and 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 (May-September) NO x 

### and heat input; July day NO x 

### and heat input; coal heat input by coal type; nameplate capacity (MW), and State FIPS code. Existing units also have county FIPS code, a unique plant identifier (ORISPL) and unit ID (also called boiler ID) (BLRID); generic units do not have these data.

1 ftp://ftp.epa.gov/EmisInventory/finalnei99ver3/crite ria/documentation/point/point_99nei_finalv3_0204.pdfAtmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### The IPM data were further processed by Pech an using data files and methodology recently approved by EPA. The most current documentati on related to this subject is the EPA report titled, Documentation for the 2002 Electric Gene rating Unit (EGU) National Emissions Inventory (NEI), September 2004 2 

### . The processing includes estimating various types of emissions and adding in control efficiencies, stack parameters, latitude-longitude coordinates, and State identifiers (plant ID, point ID, stack ID, process ID). Additionally, the generic units were sited in a county and given IDs.

Pechan developed SCC assignments 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. Additional review of the source code used in deve loping these post-processed files confirmed this fact. In actuality, not only does it exist that the post-processing code assigns different emission factors for the same SCC but that SCCs assigned in future year IPM output are potentially different than thos e assigned in the base year i nventory, leading to additional, propagating differences in the base year and future year estimates. The full extent of these issues is currently under review by VISTAS and MRPO.
Stack parameters were attache d, first using matches to data in the VISTAS 2002 NIF files, secondly using the EPA-provided data files, thir dly using a March 9, 2004 Pechan in-house stack parameter file based on previ ous EIA-767 data, and lastly using an EPA June 2003 SCC-based default stack parameter file.
Plant ID (within State and county) , point ID, process ID , and stack ID were then attached, first using the VISTAS-provided data files, or seco ndly using EPA or Pechan-generated defaults. Default stack IDs within a plant were assi gned for each unique stack height-diameter combination. The process ID and stack ID default data were only used when the data were not matched to the original VISTAS 2002 NIF files.
Additional data were required for estimating VOC, CO, filterable primary PM 10 

### and PM 2.5 

### , PM condensable, and NH 3 

### emissions for all units. Thus, ash and sulfur contents were assigned by first using 2002 EIA-767 values for existing units or SCC-based defaults; filterable PM 10 

### and PM 2.5 

### efficiencies were obtained from the 200 2 EGU NEI that were based on 2002 EIA-767 control data and the PM Calcul ator program (a default of 99.2% was 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 obtaine d from an EPA-approved October 7, 2004 Pechan emission factor file based on AP-42 emission f actors. Table 1 provides the emission factor differences between the “old” emission factor fi le (used in development of EPA’s 1999 NEI v.3) and the updated factors as used in VISTAS latest IPM conversion. Note that this updated file was not the one used for estimating emissions for pr evious EPA post-processed IPM files (including estimates for CAIR). It should also be noted that this component of emission estimation is only for the filterable component of PM and that th e emission factors used for condensable PM did not change between the two versions.

2 ftp://ftp.epa.gov/EmisInventory/draftn ei2002/point/documentation/egu2002doc.pdfAtmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### Issue Identification
During a VISTAS TAWG meeting held at the Solu tion Center in Durham, NC on April 5 and 6, 2005, emission summaries were presented as co mparisons of 2002 to 2018 forecasts. Table 2 presents the slide originally used in identifying the increase in PM and NH3 emissions. In this comparison, it was noted that PM and NH3 emissions (highlighted in Tabl e 2) from EGUs were significantly higher in 2018 than in 2002 and based on known regulation and activity, no reason could be identified for this increase. After an initial review of the data, it was determined that the PM and NH3 emission factors used between the base year and future year were most likely the culprit. In fact, for some SCCs, the NH3 em ission factor increased by over 5,000% (0.000565 to 0.03 lbs/ton coal burned). Changes in PM emission factors were not as large and limited to only a few SCCs. However, this emissions increase was simply an artifact of the change in emission factor, not anything to do with changes in activity or control technology application.
Additionally, after further review of the post-processing code by VISTAS, it was determined that not only were differing emi ssion factors being used for similar SCCs between the base and future year estimates for those SCCs identified in Tabl e 2, but that the same S CCs were not necessarily being used for emission factor assignment in th e base and post-processed IPM scenarios. This issue has implications not only for the different PM and NH3 factors, but for other pollutants (CO, VOC) not initially estimated by IPM.
Table 3 presents those unit-segment (SCC) combinat ions which have been identified in the 2018 OTW run to have been assigned SCCs in the IPM post-processing step different than those in the 2002 base case. In some instances, the SCCs are comparable enough that the emission factors assigned were the same. However, there are additional instances where significant enough difference exists that review a nd correction may be warranted. An analysis of the differences in assignment of these SCCs and associated factors has not yet been completed.

Proposed Solution

There are two issues which need to be resolved in the estimation of relative differences in EGU emissions between VISTAS base year 2002 emissions inventory and any forecasts of this source sector using IPM and post-proces sing steps applied using exis ting programs provided by Pechan; (1) consistent use of emission f actors between the base and future years, and (2) the consistent use of SCCs for determining emission fact ors between the base and future years.
These issues can be resolved using a variety of ways but the proposal provided here positions VISTAS to regenerate some specific pollutant 2002 emissions for the EGU sector in a fashion consistent, and presumably, more up-to-date, than the estimates provided in the 2002 base year inventory. Additionally, this proposal allows for th e existing process to be completed in the postprocessing steps but adjusts the resulting non-IPM generated emissions using correct SCCs and emission factors.Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### Base Year Emissions Adjustment
The first step is the adjustment of the 2002 ba se year emissions inve ntory. Using the latest “EPA-approved” uncontrolled emission factors by SCC, VISTAS contactors will utilize CERR or VISTAS reported annual heat input, fuel th roughput, heat, ash and sulfur content to estimate annual uncontrolled emissions for units identified as output by IPM. This step will be conducted for non-CEM pollutants (CO, VOC, PM, and NH3) only. For PM emissions, the condensable component of emissions will also be calcula ted and added to the resulting PM primary estimations. When these fuel characteristic va riables are found to be zero, out of range (as identified by AP-42 factors), or invalid, average fuel data collected from EPA’s AP-42 documentation on heat, sulfur, and/or ash content will be used. The resulting emissions will then be adjusted by any control efficiency factors re ported in the CERR or VISTAS data collection effort.

Future Year Scenario Adjustment
Because the assignment of the SCCs to IPM output is a post-processing step which involves the cross-reference file developed to match IPM units to VISTAS 2002 base year inventory, it should be relatively straightforwar d to modify the code to assign the same base year SCC to the future year. Then, through assignment of SCCs and associated emission factors (via another cross-reference), similar base year and future year emission factor assi gnments could be made; just using the projected controls and fuel throughput as pred icted by IPM. If modifications can not be made directly to the code for this cro ss-reference step, VISTAS can modify the resulting post-processed NIF files for those sources identified with alternate SCCs assigned in the future year. Using the same methods as described for the 2002 revisions, those non-IPM generated pollutants would be estimated using IPM predic ted fuel characteristics and base year 2002 SCC assignments.Atmospheric Sciences Group

Alpine Geophysics, LLC ▪ 387 Pollard Mine Road ▪ Burnsville, NC 28714 ▪ (828) 675-9045 ▪ (828) 675-5801 FAX 

### Table 1. Comparison of “Old” vs. “New” Em ission Factors for IPM Post-Processing

SCCEMFACforMRPOoldvsnew.xls -- PM+NH3 EF , 12/17/04
This file lists the "Old" and "N ew" EPA-approved Uncontrolled PM 10 , PM 2.5 , and NH 3 Emission Factors for the SCCs in the MRPO Scenarios.

SCC 1 FUEL "New" PM10EF 4 "Old" PM10EF 3 "New" PM25EF 4 "Old" PM25EF 3 PMFLAG 2 "New" NH3EF 4 "Old" NH3EF 3
10100201 BIT 2.6000 2.6000 1.4800 1.4800 A 0.030000 0.000565 10100202 BIT 2.3000 2.3000 0.6000 0.6000 A 0.030000 0.000565 10100203 BIT 0.2600 0.2600 0.1100 0.1100 A 0.030000 0.000565 10100204 BIT 13.2000 13.2000 4.6000 4.6000 0.030000 0.000565 10100211 BIT 2.6000 2.6000 1.4800 1.4800 A 0.030000 0.000565 10100212 BIT 2.3000 2.3000 0.6000 0.6000 A 0.030000 0.000565 10100217 BIT 12.4000 12.4000 1.3640 3.2000 0.030000 0.000565 10100221 SUB 2.6000 2.6000 1.4800 1.4800 A 0.030000 0.000565 10100222 SUB 2.3000 2.3000 0.6000 0.6000 A 0.030000 0.000565 10100223 SUB 0.2600 0.2600 0.1100 0.1100 A 0.030000 0.000565 10100224 SUB 13.2000 13.2000 4.6000 4.6000 0.030000 0.000565 10100226 SUB 2.3000 2.3000 0.6000 0.6000 A 0.030000 0.000565 10100238 SUB 16.1000 16.1000 4.2000 4.2000 0.030000 0.000565 10100301 LIG 1.8170 1.8170 0.5214 0.5214 A 0.030000 0.000565 10100302 LIG 2.3000 2.3000 0.6600 0.6600 A 0.030000 0.000565 10100303 LIG 0.8710 0.8700 0.3690 0.1100 A 0.030000 0.000565 10100317 LIG 12.0000 12.0000 1.4000 1.4000 0.030000 0.000565 10100601 NG 1.9000 1.9000 1.9000 1.9000 3.200000 3.200000 10100801 PC 7.9000 7.9000 4.5000 4.5000 A 0.397000 --- 10102018 WC 12.0000 12.0000 1.4000 1.4000 0.030000 0.000565 20100201 NG 1.9380 1.9380 1.9380 1.9380 6.560000 --- 20100301 IGCC 11.5500 11.5500 11.5500 11.5500 6.560000 --- Notes: 1. SCCs beginning with 101002 (coal), 101003 (coal), 101008 (coke), or 101020 (waste coal), emission factors in LB/TON; SCCs beginning with 101006 (natural gas), 201002 (natural gas), or 201003 (IGCC), emission factors are in LB/E6FT3. 2. If PMFLAG = 'A', then apply ash content to PM emission factor. 3. "Old" emission factors are used for latest EPA IPM post-processing. 4. "New" emission factors are used for MRPO IPM post-processing.Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXTable 2. Annual Emissions Comparison of 2002 Typical with 2018 OTW; VISTAS Tier 1 Category Totals.19%9%13%-50%-8%-52%-19%VISTAS Total15%5%14%0%0%0%2%Miscellaneous35%-29%-29%-61%23%-30%-40%Off-highway36%-53%-34%-89%-19%-70%-47%Highway Vehicles52%10%11%37%9%13%11%Waste Disposal & Recycling40%2%-4%34%46%28%-19%Storage & Transport20%32%34%23%36%48%22%Solvent Utilization16%25%28%19%21%15%22%Other Industrial Processes12%33%35%11%15%23%-19%Petroleum & Related Industries60%20%20%37%29%27%43%Metals Processing27%36%36%31%32%29%50%Chemical & Allied Product Mfg23%-8%-16%15%-28%19%-55%Fuel Comb. Other28%7%5%7%15%0%12%Fuel Comb. Industrial3024%82%69%-63%53%-68%13%Fuel Comb. Elec. Util.NH3PM-2.5PM-10SO2CONOxVOCSource CategoryAnnual 2018 OTW - 2002Typical Emissions (Percent)Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXTable 3. Differences in VISTAS Base Year 2002 and IPMPost-Processed SCC Emission Factor AssignmentsFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC01039 0001 ALABAMA ELECTRIC COOPERATIVE - MCWILLIAMS005 002 01 10100201 2010020101055 0002 ALABAMA POWER COMPANY - GADSDEN002 001 01 10100202 2010020101055 0002 ALABAMA POWER COMPANY - GADSDEN003 001 01 10100201 2010020101063 0001 ALABAMA POWER COMPANY - GREENE COUNTY002 001 01 10100201 1010020201063 0001 ALABAMA POWER COMPANY - GREENE COUNTY003 001 01 10100201 1010020201071 0008 TVA - WIDOWS CREEK008 002 01 10100202 1010021201071 0008 TVA - WIDOWS CREEK009 003 01 10100202 1010021201085 0008 GENERAL ELECTRIC CO001 001 01 10200602 2010020101097 1001 ALABAMA POWER COMPANY - BARRY002 001 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY003 001 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY004 001 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY005 002 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY006 003 01 10100201 1010021201097 1001 ALABAMA POWER COMPANY - BARRY007 005 01 20200203 2010020101097 1001 ALABAMA POWER COMPANY - BARRY008 006 01 20200203 2010020101097 1001 ALABAMA POWER COMPANY - BARRY009 007 01 20200203 2010020101097 1001 ALABAMA POWER COMPANY - BARRY010 008 01 20200203 2010020101127 0001 ALABAMA POWER COMPANY - GORGAS004 003 01 10100201 1010020201127 0001 ALABAMA POWER COMPANY - GORGAS005 003 01 10100201 1010020201127 0001 ALABAMA POWER COMPANY - GORGAS006 004 01 10100201 1010021201127 0001 ALABAMA POWER COMPANY - GORGAS007 004 01 10100201 1010021201127 0001 ALABAMA POWER COMPANY - GORGAS008 004 01 10100201 1010021212001 0010001 PROGRESS ENERGY FLORIDA, INC. U OF FL COGEN11 1 20200203 2010020112009 0090006 FLORIDA POWER & LIGHT (PCC) CAPE CANAVERAL11 2 10100401 2010020112009 0090006 FLORIDA POWER & LIGHT (PCC) CAPE CANAVERAL22 2 10100401 2010020112027 0270016 DESOTO COUNTY GENERATING COMPANY, LLC22 1 20100101 2010020112031 0310047 JEA KENNEDY3 3 1 20100101 2010020112031 0310047 JEA KENNEDY4 4 1 20100101 2010020112031 0310047 JEA KENNEDY5 5 1 20100101 2010020112031 0310485 JEA BRANDY BRANCH FACILITY22 1 20100101 2010020112033 0330045 GULF POWER COMPANY CRIST ELECTRIC GENERATINGPLANT 2 1 1 10100601 2010020112033 0330045 GULF POWER COMPANY CRIST ELECTRIC GENERATINGPLANT 3 1 2 10100601 20100201Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC12049 0490043 VANDOLAH POWER COMPANY, LLC11 1 20100101 2010020112095 0950203 ORLANDO COGEN LIMITED, L.P.11 1 20200203 2010020112097 0970014 PROGRESS ENERGY FLORIDA, INC. INTERCESSION CITY PLANT 11 11 1 20100101 2010020112097 0970014 PROGRESS ENERGY FLORIDA, INC. INTERCESSION CITY PLANT 18 18 2 20100101 2010020112099 0990042 FLORIDA POWER & LIGHT (PRV) RIVIERA POWER PLANT33 3 10100401 2010020112099 0990042 FLORIDA POWER & LIGHT (PRV) RIVIERA POWER PLANT44 3 10100401 2010020112099 0990045 CITY OF LAKE WORTH UTILITIES TOM G. SMITH POWER PLANT 99 1 10100601 2010020112103 1030011 PROGRESS ENERGY FLORIDA, INC. BARTOW PLANT11 2 10100401 2010020112103 1030011 PROGRESS ENERGY FLORIDA, INC. BARTOW PLANT22 2 10100404 2010020112103 1030011 PROGRESS ENERGY FLORIDA, INC. BARTOW PLANT33 2 10100404 2010020112105 1050003 LAKELAND ELECTRIC CHARLES LARSEN MEMORIAL POWER PLANT 44 2 10100401 2010020112105 1050221 CALPINE/AUBURNDALE POWER PARTNERS, LP66 2 20100101 2010020112105 1050223PROGRESS ENERGY FLORIDA, INC. TIGER BAY COGENERATIONFACILITY3 3 1 10200602 2010020112105 1050233 TAMPA ELECTRIC COMPANY POLK POWER STATION11 2 20100201 2010030112121 1210003 PROGRESS ENERGY FLORIDA, INC. FL POWER SUWANNEE RVR PLANT 11 3 10100404 2010020112121 1210003 PROGRESS ENERGY FLORIDA, INC. FL POWER SUWANNEE RVR PLANT 22 3 10100401 2010020112121 1210003 PROGRESS ENERGY FLORIDA, INC. FL POWER SUWANNEE RVR PLANT 33 3 10100401 2010020112127 1270009 FLORIDA POWER & LIGHT (PSN) SANFORD POWER PLANT11 3 10100401 2010020112127 1270020 PROGRESS ENERGY FLORIDA, INC. TURNER PLANT10 10 1 20100101 2010020112127 1270020 PROGRESS ENERGY FLORIDA, INC. TURNER PLANT99 1 20100101 2010020112127 1270028 PROGRESS ENERGY FLORIDA, INC. DEBARY FACILITY17 17 1 20100101 2010020112127 1270028 PROGRESS ENERGY FLORIDA, INC. DEBARY FACILITY18 18 1 20100101 2010020113051 05100006 KRAFT STEAM - ELECTRIC GENERATING PLANTSG01 CS1 1 10100212 2010020113051 05100006 KRAFT STEAM - ELECTRIC GENERATING PLANTSG02 CS1 1 10100212 2010020113067 06700003GEORGIA POWER COMPANY, MCDONOUGH STEAM-ELECTRICGENERATING PLANTCT6M ST6M 1 20100101 2010020113067 06700003GEORGIA POWER COMPANY, MCDONOUGH STEAM-ELECTRICGENERATING PLANTCT7M ST7M 1 20100101 2010020113115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG01 ST1 1 10100212 1010020213115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG02 ST1 1 10100212 1010020213115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG03 ST1 1 10100212 10100202Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC13115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG04 ST2 1 10100212 1010020213207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG01 ST1 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG02 ST2 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG03 ST3 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG04 ST4 1 10100212 1010022613237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG01 ST1 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG02 ST1 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG03 ST2 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG04 ST2 1 10100212 1010020221111 0126 LOU GAS & ELEC, CANERUN 06 06 01 10100212 1010020221111 0127 LOUGAS & ELEC, MILL CREEK03 03 01 10100212 1010020221111 0127 LOUGAS & ELEC, MILL CREEK04 04 01 10100212 1010020221157 2115700053 DUKE ENERGY MARSHALL COUNTY,LLC001A 1 2 20100101 2010020121223 2122300002 LOUISVILLE GAS & ELECTRIC TRIMBLE COGEN STATION001 1 1 10100202 1010021228007 2800700032 ATTALA GENERATING COMPANY, LLC003 3 1 10100602 2010020128047 2804700055 MISSISSIPPI POWER COMPANY, PLANT JACK WATSON004 4 1 10100101 1010020228047 2804700055 MISSISSIPPI POWER COMPANY, PLANT JACK WATSON005 5 1 10100101 1010020228059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL001 1 1 10100223 1010021228059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL002 2 1 10100223 1010021228059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL003 3 1 20100101 2010020128059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL004 4 1 20100101 2010020128059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL005 5 1 20100101 2010020128059 2805900090 MISSISSIPPI POWER COMPANY, PLANT DANIEL006 6 1 20100101 2010020137017 3701700043 ELIZABETHTOWN POWER, LLCG-17A S-1 8 10101202 1010020437035 3703500073 DUKE ENERGY CORPORATION - MARSHALL STEAM STATIONG-1 S-3 5 10100202 1010021237035 3703500073 DUKE ENERGY CORPORATION - MARSHALL STEAM STATIONG-2 S-4 13 10100202 1010021237035 3703500073 DUKE ENERGY CORPORATION - MARSHALL STEAM STATIONG-4 S-1 11 10100202 10100212Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC37035 3703500073 DUKE ENERGY CORPORATION - MARSHALL STEAM STATIONG-5 S-2 12 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-14 S-1 1 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-15 S-2 3 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-16 S-3 5 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-17 S-4 7 10100202 1010021237071 3707100039 DUKE ENERGY CORPORATION - ALLEN STEAM STATIONG-18 S-5 9 10100202 1010021237071 3707100040 DUKE ENERGY CORPORATION - RIVERBEND STEAM STATIONG-17 S-5 20 10100202 1010021237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-29S-11101002121010020237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-35AS-35101002121010020237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-35BS-35101002121010020237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-36AS-47101002121010020237145 3714500029 CP&L - ROXBORO STEAM ELECTRICPLANT G-36BS-47101002121010020237145 3714500045 CP&L - MAYO FACILITYG-46A S-1 1 10100212 1010020237145 3714500045 CP&L - MAYO FACILITYG-46B S-1 1 10100212 1010020237155 3715500147 PROGRESS ENERGY CAROLINAS, INC., W.H. WEATHERSPOON PLANT G-26 S-2 9 10100202 1010021237155 3715500166 LUMBERTON POWER, LLCG-17A S-1 7 10101202 1010020437159 3715900004 DUKE ENERGY CORPORATION - BUCK STEAM STATIONG-4 S-6 8 10100202 1010021237159 3715900163 ROWAN COUNTY POWER LLCG-1 S-1 1 10100604 2010020137159 3715900163 ROWAN COUNTY POWER LLCG-2 S-2 3 10100604 2010020137159 3715900163 ROWAN COUNTY POWER LLCG-3 S-3 5 10100604 2010020137169 3716900004 DUKE ENERGY CORP - BELEWS CREEK STEAM STATIONG-17 S-1 1 10100215 1010020237169 3716900004 DUKE ENERGY CORP - BELEWS CREEK STEAM STATIONG-18 S-2 2 10100215 1010020237191 3719100017 PROGRESS ENERGY - F LEE PLANTG-3 S-1 3 10100212 1010020237191 3719100017 PROGRESS ENERGY - F LEE PLANTG-4 S-2 5 10100212 1010020245021 0600-0081 DUKE ENERGY:MILL CREEKCA1 1 2 20100101 2010020145021 0600-0081 DUKE ENERGY:MILL CREEKCA2 2 2 20100101 2010020145021 0600-0081 DUKE ENERGY:MILL CREEKCA3 3 2 20100101 2010020147145 0013 TVA KINGSTON FOSSIL PLANT001 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT002 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT003 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT004 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT005 S-1 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT006 S-2 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT007 S-2 1 10100202 10100212Atmospheric Sciences GroupAlpine Geophysics, LLC▪387 Pollard Mine Road▪Burnsville, NC 28714▪(828) 675-9045▪(828) 675-5801 FAXFIPS Plant ID Plant NamePoint IDStack ID Segment 2002 SCC IPM SCC47145 0013 TVA KINGSTON FOSSIL PLANT008 S-2 1 10100202 1010021247145 0013 TVA KINGSTON FOSSIL PLANT009 S-2 1 10100202 1010021247157 00528 ALLEN FOSSIL PLANTCTrb10 CTrb10 13 20100101 2010020147161 0011 TVA CUMBERLAND FOSSIL PLANT001 S-01 1 10100215 1010020247161 0011 TVA CUMBERLAND FOSSIL PLANT002 S-02 1 10100215 1010020251001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1A 1 1 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1B 1 2 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1C 1 3 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1D 1 4 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1E 1 5 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1F 1 6 20100101 2010020151001 00030 COMMONWEALTH CHESAPEAKE POWER STATION1G 1 7 20100101 2010020151083 00046 DOMINION - CLOVER POWER STATION11 4 10100501 1010021251083 00046 DOMINION - CLOVER POWER STATION22 4 10100501 1010021251153 00002 DOMINION - POSSUM POINT33 1 10100212 2010020151175 00051 DOMINION - SOUTHAMPTON POWER STATION11 1 10200219 1010020451191 00180 WOLF HILLS ENERGY LLC21 1 1 20100209 2010020151191 00180 WOLF HILLS ENERGY LLC22 2 1 20100202 2010020151191 00180 WOLF HILLS ENERGY LLC23 3 1 20100202 2010020151191 00180 WOLF HILLS ENERGY LLC24 4 1 20100202 2010020151191 00180 WOLF HILLS ENERGY LLC25 5 1 20100202 2010020151760 00389 DOMINION - BELLEMEADE 20 1 1 20100101 2010020151760 00389 DOMINION - BELLEMEADE 21 2 1 20100101 2010020154023 0014 NORTH BRANCH POWER STATION002 001 01 10100217 10100202