### Appendix Q Supporting Documentation from VISTAS

### TABLE OF CONTENTS

**Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 version), by** 

**Pechan.............................................**

**................................................... ...................................................**  **.........1**

**Documentation of the Base G 2002 Base Year, 2009 an d 2018 Emissions Inventory for VISTAS, by** 
**MACTEC, Inc........................................**

**................................................... ...................................................**  **60**

**Memorandum to VISTAS State Point Contacts and VISTA S EGU Special Interest Workgroup, from**  **Gregory Stella (June 13, 2005).....................**

**................................................... ..........................................316** 

# Appendix Q Supporting Documentations From VISTAS

### Supporting Documentation from VISTAS Appendix Q i The Charlotte-Gastonia-Rock Hill, NC-SC 8-Hour Ozone April 5, 2007 Pre-Hearing Draft –North Caro lina Attainment Demonstration

### Supporting Documentation from VISTAS Appendix Q ii The Charlotte-Gastonia-Rock Hill, NC-SC 8-Hour Ozone April 5, 2007 Pre-Hearing Draft –North Caro lina Attainment Demonstration 

### TABLE OF CONTENTS

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

Documentation of the Base G 2002 Base Year, 2009 and 2018 Emissions Inventory for VISTAS, MACTEC, Inc............................................................................................................ ....60

Memorandum to VISTAS State Point Contacts and VISTAS EGU Special Interest Workgroup, from Gregory Stella, June 13, 2005............................................................................................. 316

### Supporting Documentation from VISTAS Appendix Q iii The Charlotte-Gastonia-Rock Hill, NC-SC 8-Hour Ozone April 5, 2007 Pre-Hearing Draft –North Caro lina Attainment Demonstration

# 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

### [ This page intentionally left blank]

# 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.MACTEC, Inc. 

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

Prepared for:

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

Prepared by:

MACTEC, Inc.

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

### 2 

## Table of Contents

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

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

1.1 P OINT 

### S OURCES



### ............................................................................................................................... ............4
1.1.1 Development of 2002 Po int Source Inventory ..................................................................................... ..4
1.1.1.1 Data Sources ................................................................................................................... ............................. 5
1.1.1.2 Initial Data Evaluation ........................................................................................................ ......................... 6
1.1.1.3 PM Augmen tation................................................................................................................ ........................ 7
1.1.1.4 EGU Analysis ................................................................................................................... ......................... 10
1.1.1.5 QA Review of Base F Inventory.................................................................................................. .............. 11
1.1.1.6 Additional Base G Upda tes and Co rrections...................................................................................... ........ 12
1.1.1.7 Summary of Base G 2002 Inve ntory............................................................................................... ........... 15 

### 1.1.2 Development of Typical Year EGU in ventory...................................................................................... 18
1.2 A REA 

### S OURCES



### ............................................................................................................................... ..........20
1.2.1 Development of a “typical ” year fire inventory ................................................................................. .22
1.2.2 Development of n on-fire inve ntory .............................................................................................. ........31
1.2.3 2002 Base G inventory updates .................................................................................................. .........34
1.2.3.1 Changes resulting from St ate review and comment ................................................................................ ... 34 

### 1.2.4 Ammonia and paved road emissions............................................................................................... .....37
1.2.5 Global Changes Ma de for Base G................................................................................................. ......38 1.2.6 Quality Assura nce steps........................................................................................................ ...............39
1.3 M OBILE 

### S OURCES



### ............................................................................................................................... ......40
1.3.1 Development of on-road mobile so urce input files and VMT estim ates...............................................41
1.3.1.1 Emissions from on-road mobile sources .......................................................................................... .......... 42 

### 1.3.2 Development of non-road emission estimates..................................................................................... .45
1.3.2.1 Emissions from NONRO AD model s ources........................................................................................... ... 45
1.3.2.2 Emissions from Commercial Marine Vesse ls, Locomotives, a nd Airpla nes.............................................. 61 

### Base G R evision s: ..............................................................................................................................................78
1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indian a, and Ohio .............................................. 85 

### 1.3.3 Quality Assura nce steps........................................................................................................ ...............87

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

2.1 P OINT 

### S OURCES



### ............................................................................................................................... ..........88
2.1.1 EGU Emission Projec tions ....................................................................................................... ...........88
2.1.1.1 Chronology of the Development of EGU Projec tions............................................................................... . 88
2.1.1.2 VISTAS IPM runs for EGU sources................................................................................................ .......... 92
2.1.1.3 Post-Processing of IP M Parsed Files ............................................................................................ ............. 93
2.1.1.4 Eliminating Double C ounting of EGU Units ....................................................................................... ...... 95
2.1.1.5 Quality Assurance steps........................................................................................................ ..................... 96
2.1.1.6 S/L Adjustments to IPM Modeling Results for Base G Projections........................................................... 97
2.1.1.7 Summary of Base F and Base G 2009/2018 EGU Point Source Inventor ies ............................................. 98 

### 2.1.2 Non-EGU Emission Projections ................................................................................................... .....110
2.1.2.1 Growth assumptions for non-EGU sources......................................................................................... ..... 110
2.1.2.2 Source S hutdow ns............................................................................................................... ..................... 112
2.1.2.3 Control Programs applie d to non-E GU sour ces .................................................................................... ... 114MACTEC, Inc. 

### 3 2.1.2.4 Quality Assurance steps........................................................................................................ ................... 117
2.1.2.5 Additional Base G Upda tes and Co rrections...................................................................................... ...... 117
2.1.2.6 Summary of Revised 2009/2018 non-E GU Point Source I nventorie s...................................................... 117 

### 2.2 A REA 

### S OURCES



### ............................................................................................................................... ........123
2.2.1 Stationary ar ea sources ........................................................................................................ .............123
2.2.1.1 Stationary area source controls ................................................................................................ ................ 125
2.2.1.2 Stationary area source growth.................................................................................................. ................ 127
2.2.1.3 Differences be tween 2009/2018

.................................................................................................. ............. 127 

### 2.2.2 Agricultural ar ea sources ...................................................................................................... ............128
2.2.2.1 Control assumptions for agri cultural area sources .............................................................................. ..... 128
2.2.2.2 Growth assumptions for agri cultural area sources ............................................................................... .... 128 

### 2.2.3 Changes to Prescribed Fire for 2009/201 8 Base G...........................................................................133
2.2.4 Quality Assura nce steps........................................................................................................ .............138
2.3 M OBILE 

### S OURCES



### ............................................................................................................................... ....138
2.3.1 Development of on-road m obile source i nput file s ............................................................................141
2.3.1.1 Preparation of revised 2018 input data files................................................................................... .......... 141
2.3.1.2 Preparation of initial 2009 input data files ................................................................................... ............ 144 

### 2.3.2 VMT Data ....................................................................................................................... ...................145
2.3.3 Base G R evisions ............................................................................................................... ................150
2.3.4 Development of non-road emission estimat es....................................................................................1 50
2.3.4.1 NONROAD model source s.......................................................................................................... ............ 151
2.3.4.2 Non-NONROAD m odel s ources...................................................................................................... ........ 153
2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indian a, and Ohio ............................................ 188
2.3.4.4 Differences be tween 2009/2018

.................................................................................................. ............. 188 

### 2.3.5 Quality Assura nce steps........................................................................................................ .............189



### Appendix A: State Emission Totals by Pollutant and Sector



### Appendix B: State VMT totals



### Appendix C: State Tier 1 Emission Totals



### Appendix D : VISTAS Tier 1 Emission Totals



### Appendix E: Aircraft PM Excerpt from 2001 Tucson Report

Appendix F : Comparison of Base F and Base G On-Road Mobile EmissionsDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. i 

## 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 and 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 Actual and Typical Year Base G Emissions. Table 1.2-2. Summary of State Data Submittals for the 2002 VISTAS Area Source Base F Inventory Table 1.2-3. Data Source Codes and Data Sources for VISTAS 2002 Base F Area Source Emissions Inventory. Table 1.3-1. Representative day mapping for January episode Table 1.3-2. Summary of Base F NONROAD Modeling Revisions Table 1.3-3. Base F NONROAD Input File Sequence and Structural Revisions Table 1.3-4. Summary of Base G NONROAD Modeling Revisions Table 1.3-5. Spring 2006 NONROAD Input File Sequence and Structural Revisions Table 1.3-6. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions as Reported in February 2004 Pechan Report (annual tons) Table 1.3-7. PM-to-NO x 

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

### Ratios by Aircraft Type. Table 1.3-9. Non-Corresponding Aircraft Emissions Records Table 1.3-10. Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions with Modified Aircraft PM Emission Rates (annual tons) Table 1.3-11. Change in Initial 2002 Base Year Em issions 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 Comparison of Aircraft Emissions (Airports with Aircraft NO x 

### > 200 tons per year) Table 1.3-17. Base G VA Aircraft Records Updates Table 1.3-18. Calculated Base G Emission Ratios for VA Table 1.3-19. Base G-Revised 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine Emissions (tons/year) Table 1.3-20. Change in 2002 Emissions, Base G Inventory Relative to Base F Inventory Table 1.3-21. Base G Comparison of Aircraft Emissions (Airports with Aircraft 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 Determinations Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. Table 2.1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. Table 2.1-3. EGU Point Source 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 Corrections to the Base F 2009/2018 Inventories Incorporated into the Base G 2009/2018 Inventories Table 2.1-13. Non-EGU Point Source SO 2 

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

### Emission Comparison for 2002/2009/2018 Table 2.1-15. Non-EGU Point Source VOC Emission Comparison for 2002/2009/2018 Table 2.1-16. Non-EGU Point Source CO Emission Comparison for 2002/2009/2018 Table 2.1-17. Non-EGU Point Source PM 10 

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

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

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

MACTEC, Inc. iii 

### Table 2.2-1 2002 Base Year Emissions and Per centage Difference for Base F and Base G (based on actual emissions). Table 2.2-2 2019 Projection Year Emissions &P ercentage Difference for Base F & Base G Table 2.2-3 2018 Projection Year Emissions & Pe rcentage Difference for Base F & Base G Table 2.2-4 Percentage Difference Between Base F and Base G Fire Emissions by State Table 2.3-1. 2002 versus 2018 VMT (million miles per year) Table 2.3-2. VMT and HDD Rule Estimates for North Carolina (million miles per year) Table 2.3-3. VMT and HDD Rule Estimates for South Carolina (million miles per year) Table 2.3-4. VMT and HDD Rule Estimates for Tennessee (million miles per year) Table 2.3-5. VMT and HDD Rule Estimates for Virginia (million miles per year) Table 2.3-6. Pre-Base F 2002 Aircraft, Locomotiv e, and Non-Recreational Marine Emissions (annual tons, as of the fall of 2004) Table 2.3-7. Locally Generated Growth Factors for North Carolina Table 2.3-8. Estimated Emission Reduction Impacts based on T-4 Rule Table 2.3-9. Estimated Emission Reduction Impacts Relative to VISTAS 2002 Base Year Values Table 2.3-10. Diesel CMV Adjustment Ratios for Palm Beach County, FL Table 2.3-11. Overall Adjustment Factors for Palm Beach County, FL Table 2.3-12. 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, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-15. Base F 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-16. Change in Emissions between 2009 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories) Table 2.3-17. Change in Emissions between 2018 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories) Table 2.3-18. Base G 2002 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) Table 2.3-19. Locally Generated Growth Factors for Kentucky Table 2.3-20. Base G 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-21. Base G 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories Table 2.3-22. Change in Emissions between 2009 Base G and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories) Table 2.3-23. Change in Emissions between 2018 Base G and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. iv 

## List of Figures

Figure 1.2-1. CO Emissions from Agricultura l Burning for the Original Base Year, 2002 Actual Base G, and 2002 Typical Base G Inventories. Figure 1.2-2. CO Emissions from Land Clearing Burning for the Original Base Year, 2002 Actual Base G and 2002 Typical Base G Inventories. Figure 1.2-3. CO Emissions from Prescribed 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 Burn ing for the Original Base Year, 2002 Actual Base G and 2002 Typical Base G Inventories. Figure 2.2-1. Prescribed Fire Projection for Okeefenokee NWR for 2009 Figure 2.3-1. Impacts of the Apparent CAIR Inventory Discrepancy Figure 2.3-2. Total Aircraft, Locomotive, and CMV CO Emissions (Base F) Figure 2.3-3. Locomotive CO Emissions (Base F) Figure 2.3-4. Total Aircraft, Locomotive, and CMV 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, Locomotive, and CMV VOC Emissions (Base F) Figure 2.3-13. Locomotive VOC Emissions (Base F) Figure 2.3-14. Total Aircraft, Locomotive, and CMV CO Emissions (Base G) Figure 2.3-15. Locomotive CO Emissions (Base G) Figure 2.3-16. Total Aircraft, Locomotive, and CMV 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, 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

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## Acronyms and Abbreviations

AEO Annual Energy Outlook AF&PA American Forest and Paper Association
APCD Air Pollution Control District ATP Anti-Tampering Program BLRID Boiler Identification (Boiler ID)
CAA Clean Air Act
CAIR Clean Air Interstate Rule CEM Continuous Emissions Monitoring
CAMD Clean Air Markets Division CERR Consolidated Emissions Reporting Rule CMU Carnegie Mellon University
CMV commercial marine vessels CE Control Efficiency
CO carbon monoxide DENR North Carolina Department of Environment and Natural Resources DHEC South Carolina Department of Health and Environmental Control EDMS Emissions Data Management Systems
ESD Emissions Standards Division EPA Environmental Protection Agency EGU Electric Generating Unit ICF ICF International, Inc. FIP Federal Implementation Plan FLM Federal Land Manager FTP File transfer protocol FR Federal Register
FS Forest Service HDD Heavy Duty Diesel HDD RULE Heavy Duty Diesel Rule ICF ICF International, Inc.
ID Identification I/M Inspection and Maintenance
IPM ® 

### Integrated Planning Model ® 

### IAQTR Interstate Air Quality Transport Rule LTO Landing and take off MACT Maximum achievable control 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 estimation 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 condensation of hot materials to form particulates, usually less than 2.5 microns in diameter ppmW parts per million by weight PRI Primary QA/QC Quality Assurance/Quality Control QAPP Quality Assurance Project Plan REMI Regional Economic Models, Inc. RFG Reformulated gasoline RVP Reid Vapor Pressure
SCC Source Classification CodeDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Acronyms and Abbreviations (continued)
SCR Selective Catalytic Reduction
SIP State Implementation Plan SIWG Special Interest Workgroup
S/L/T State/Local/Tribal SMOKE Sparse Matrix Operator Kernel 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 developed the inventories and to a certain extent these were also based on their purpose. Different components of th e 2002 base year inventories have been supplied by E.H. Pechan and Associates, Inc. (Pechan), MACTEC Engineering and Consulting, Inc. (MACTEC), and by Alpine Geophysics, Inc.

The initial 2002 base year inventory was jo intly 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 fi nal along with updated information on VMT, fuel programs, and other inputs to the MOBI LE6 model to produce a draft version of the 2002 inventory. For non-road sources, a similar approach was used. Updated State information on temperatures and fuel charact eristics 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 was prepared in late 2003, with a final version in early 2004. An overview of the development of th e on-road component can be found at: http://www.vistas-sesarm.org/documents/Pechan_drafton-roadinventory_082803.ppt while an overview of the non-road component can be found at: http://www.vistas-sesarm.org/documents/Pechan_Non-roadInventory_082803.ppt

. Similarly, draft versions of the 2002 point 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 th e 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 matter emissions were augmented (when missing) by using emission factor ratios. Details on all these calculations are discussed in Section
1.1.1.3 of this document.

The area source component of the 2002 draft base year emissions was prepared similarly to the point sources, using State submittals and the 1999 NEI Version 2 final as the basis for projecting emissions to 2002 using EGAS growth factors. For ammonia area sources the Carnegie Mellon University (CMU) 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 the 2002 base year inventory were developed. The first was delivered in August of 2003, the second in Apr il 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 Oc tober 2004 inventory incorporated 2002 Consolidated Emissions Reporting Rule (CERR) data into the inventory along with some updated data from the VISTAS States. This i nventory is typically referred to as version 3.1 of the VISTAS inventory

Closely following the version 3.1 2002 base year inventory, a “preliminary” 2018 projection inventory was developed. This “p reliminary” 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 comment s on that inventory to MACTEC for updateDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 3 

### and revision. At the same time MACTEC prep ared a revised draft 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 we re received and updates to the inventories based on these comments were prepared. The revised inventories were provided to the
VISTAS States. At that time to be 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 delivered a report entitled Documentation of the Revised 2002 Base Year, Revised 2018, and Initial 2009 Emission Inventories for VISTAS on August 2, 2005 that described the methods used to develop the Base F inventories. For the Electric Generating Utilities (EGU) different versions of the Integrated Planning Model were used between Base D and Base F, resulting in different projections of future
EGU emissions.

Over the period from August 2005 until 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 releas ed. Thus additional updates to the inventory were prepared based on the comments received along with revised NONROAD
emission estimates from NONROAD05. The re sultant inventory became the Base G inventory.

This document details the development of the Base G inventories for 2002, 2009 and
2018. The information that follows describes the development of the VISTAS inventory by sector from version 3.1 forward. Unless sp ecific 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 inventory 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 apply to ALL States: A) removal of Stage II refueling from area source file to non-road and on-road; B) modification of PM2.5 ratio for several 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 DOE AEO2006 fuel use projectionsDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

Source AL FL GA KY MS NC SC TN VA WV EGU 1 Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-EGU Point 2 Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Base F methodology but with revised growth factors for fuel fired sources in Base G Area Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model.

Some specific

source categories updated using State supplied file to override projected values. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model. Base F with updated AEO growth factors for fuel fired

sources. Agricultural ammonia sources from CMU model.

On-road Base G Base G Base G Base G Base G Base G Base G Base G Base G Base G Non-road Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

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

Base F projection methodologyused for nonNONROAD model

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

Base F projection methodologyused for nonNONROAD model

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

Base F projection methodologyused for nonNONROAD model

sources except for aircraft in Cincinnati/N. KY Int. Airport, which are Base G using State supplied growth factors. Base G for all sources included in the NONROAD model.

Base F projection methodologyused for nonNONROAD model

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

Base F projection methodologyused for nonNONROAD model

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

Base F projection methodologyused for nonNONROAD model

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

Base F projection methodologyused for nonNONROAD model

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

Base F projection methodologyused for nonNONROAD model

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

Base F projection methodologyused for nonNONROAD model

sources

Fires Base F typical except for Rx fires Base F typical Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Base F typical except for Rx fires Notes : 1. All EGU emissions updated with new IPM runs in Base G 2. Revised growth factors from DOE 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 Southeast (VISTAS) Stat es and local (S/L) agencies to the United States Environmental Protection Agency (EPA) as part of the Consolidated Emissions Reporting Rule (CERR) requirements Work on incorporating the CERR data into the revised base year involved: 1) obtaining the data from EPA or the S/L agency, 2) evaluating the emissions and pollutants reported in the CERR submittals, 3) augmenting CERR data with annual emission
estimates for PM 10 

### -PRI and PM 2.5 

### -PRI; 4) evaluating the emissions from electric generating units, 5) completing quality assurance reviews for each component of the point source inventory, and 6) updating the database with corrections or new information from S/L agencies based on their review of the 2002 inventory. The processes used to perform those operations are described in the first portion of this section.

The second component was the development of a “t ypical” year inventory for electric generating units (EGUs). VISTAS determined that a typical year electric generating units (EGU) inventory was necessary to smooth out any anomalies in emissions from the EGU sector due to meteorology, economic, and outage factors in 2002. Th e typical year EGU inventory is intended to represent the five year (2000-2004) period that will be used to determine the regional haze reasonable progress goals. The second part of this section discusses the development of the typical year EGU inventory.

1.1.1 Development of 2002 Point Source Inventory
MACTEC developed a draft 2002 emission inventory in June 2004 ( Development of the Draft 2002 VISTAS Emission Inventory for Regional Haze Modeling – Point Sources , MACTEC, June 18, 2004). The starting point for the draft 2002 emission inventory was EPA’s 1999 National Emission Inventory (NEI), Version 2 Final (N EI99V2). For several states, we replaced the NEI99V2 data with more recent inventories for either calendar year 1999, 2000, or 2001 as submitted by the S/L agencies. We also performed several other updates, including updating emission estimates for selected large source of ammonia, incorporating 2002 Continuous Emissions Monitoring-(CEM)-based 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 inventory (referred to as Base G) was released in August 2006 and is documented in this report. The primary task in preparing the Base G 2002 base year inventory was the incorporation of corrections and new information as submitted by the S/L agencies based on their review of the Base F inventory. The following subsections document the data sources for the Base G inventory, the checks made on the CERR submittals, the process for augmenting the inventory with 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 inventory: 1) the inventories that the S/L submitted to EPA from May through July 2004 as required by the CERR; 2) supplemental data supplied by the S/L agencies that may have been revised or finalized after the CERR submittal to EPA, and 3) the draft VISTAS 2002 inventory in cases where S/L CERR
data were not available. For the Base G i nventory, 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 was based on the 1999 NEI).

Table 1.1-1 summarizes the data used as the starting point for the Base F 2002 inventory. Once all of the files were obtained, MACTEC ran the files through the EPA National Emission Inventory Format (NIF) Basic Format and Content checking tool to ensure that the files were submitted in standard NIF format and that there were no referential integrity issues with those files. In a couple of cases small errors were found. For example, in one case non-standard pollutant designations were used for particulate matter (PM) and ammonia emissions. MACTEC contacted each VISTAS State point source contact person to resolve the issues with the files and corrections were made. Once all corrections to the native files were made, MACTEC continued with the incorporation of the data into the VISTAS point source files. S/L agencies completed a detailed review of the Base F inventory. Additional updates and corrections to the Base F inventory were requested by S/L agencies and incorporated into the Base G inventory. The Base G changes are documented in more detail in Section 1.1.1.6.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 for the Base F 2002 Point Source Inventory.

State / Local Program Point Source Emissions Data Source AL C FL B GA B KY C MS B NC C SC C TN C VA B WV B Davidson County, TN B Hamilton County, TN D Memphis/Shelby County, TN B Knox County, TN B Jefferson County, AL B Jefferson County, KY B Buncombe County, NC B

Forsyth County, NC B Mecklenburg County, NC B Key A = Draft VISTAS 2002 B = CERR Submittal from EPA's file transfer protocol (FTP) site C = Other (CERR or other submittal sent directly from S/L agency to MACTEC) D = CERR Submittal from EPA’s NEI 2002 Final Inventory



### 1.1.1.2 Initial Data Evaluation
For the Base F inventory, we conducted an initial review of the 2002 point source CERR data in accordance with the QA procedures specified in the Quality Assurance Project Plan (QAPP) for this project. The following evaluations were completed to identify potential data quality issues
associated with the CERR data:

• 

### Compared the number of sites in the CERR submittal to the number of sites in the VISTAS draft 2002 inventory; for all States, the number of sites in the CERR submittal was less than in the VISTAS draft 2002 inventory, since the CERR data was limited to major sources, while the VISTAS draft 2002 inventory contained data for both major and minor sources; verified with S/L contacts th at minor sources not included in the CERR point source inventory were include d in the CERR area source inventory.

• 

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

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

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### Checked for types of particulate matter codes 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-zero (but very small) but the annual value was zero. This was generally the result of rounding in an S/L agency’s submittal.

• 

### Compared ammonia emissions as reported in the CERR submittals and the 2002 Toxics Release Inventory; worked with S/L agencies to resolve any outstanding discrepancies.

• 

### Compared SO 2 

### and NO x 

### emissions for EGUs to EPA’s Clean Air Markets Division CEM database to identify any outstanding discrepancies. (A full discussion of the EGU emissions analysis is discussed later in Section 1.1.1.4)

• 

### Prepared State-level emission summaries by pollutant for both the EGU and non-EGU sectors to allow S/L agencies to compare emissions as reported in the 1999 NEI Version 2, the VISTAS draft 2002 inventory, and the CERR submittals.

• 

### Prepared facility-level emission summaries by pollutant to allow S/L agencies to review facility level emissions for reasonableness and accuracy.

We communicated the results of these analyses through email/telephone exchanges with the S/L point source contacts as well as through Excel summary spreadsheets. S/L agencies submitted corrections and updates as necessary to resolve any QA/QC issues from these checks.

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

PM Category Description
PM-PRI Primary PM (includes filterable and condensable)
PM-CON Primary PM, condensable portion only (all less than 1 micron)
PM-FIL Primary PM, filterable portion onlyDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### PM 10 

### -PRI Primary PM 10 

### (includes filterable and condensable)

PM 10 

### -FIL Primary PM 10 

### filterable portion only

PM 2.5 

### -PRI Primary PM 2.5 

### (includes filterable and condensable)

PM 2.5 

### -FIL Primary PM 2.5 

### filterable portion only

S/L agencies did not report PM emissions in a consistent manner. The State/local inventories submitted for VISTAS included emissions data for either PM-FIL, PM-PRI, PM 10 

### -FIL,
PM 10 

### -PRI, PM 2.5 

### -FIL, PM 2.5 

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

### -PRI, PM 10 

### -FIL, PM 2.5 

### -PRI, PM 2.5 

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

### -PRI and PM 2.5 

### -PRI were calculated by adding PM 10 

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

### -FIL and PM-CON, respectively.

The procedures for augmenting point source PM emissions are documented in detail in Appendix C of Documentation for the Final 1999 National Emissions Inventory {Version 3} for
Criteria Air Pollutants and Ammonia – Point Sources , January 31, 2004). Briefly, the PM data augmentation procedure includes the following five steps:

• 

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

### Emissions for Input to the PM Calculator

• 

### Step 2: Develop and Apply S ource-Specific Conversion Factors

• 

### Step 3: Prepare Factors from PM Calculator

• 

### Step 4: Develop and Apply Algorithms to Es timate Emissions from S/L/T Inventory Data

• 

### Step 5: Review Results and Update the NEI with Emission Estimates and Control Information.
Please refer to the EPA documentation for a complete description of the PM augmentation procedures.

Table 1.1-2 compares the original PM emission estimates from the S/L CERR submittals and the revised 2002 VISTAS emissions estimates calculated using the above methodology. This table is intended to show that we took whatever States provided in the way of PM and filled in gaps to add in PM-CON where emissions were missing in order to calculate PM 10 

### -PRI and PM 2.5 

### -PRI for all processes to get a complete set of particulate data. We did not compare any other pollutants besides PM, since for other pollutant s CERR emissions equal VISTAS emissions. As noted in Table 1.1-2, we made significant revisions to the PM emissions for Kentucky in the Base F inventory and for South Carolina in the Base G inventory.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 Matt er 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 using the PM-PRI c ode 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 Environmental 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 in itial 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 revi sed 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 i nventory 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 information and provide corrections where the inconsistencies were significant. In general, corrections (or general directions) were provided in the case of the potential inconsistency issues. In other cases, the agency provided specific process level pollutant corrections.

Note that for the Base G inventory, only the 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 facilitate 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 outstanding discrepancies. Facilities report 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 (CAA). EPA sums the hourly CEM emissions to the annual level, and we compared these annual CEM emissions to those in the S/L inventories. The 2002 CEM inventory containing 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 preparing a crosswalk file to match facilities and units in the CAMD inventory to facilities and units in the S/L inventories. In the CAMD inventory, the Office of Regulatory Informati on Systems (ORIS) identification (ID) code identifies unique facilities and the unit ID identifies unique boilers and internal combustion engines (i.e., turbines and reciprocating engines) . In the S/L inventories, the State and county FIPS and State facility ID together identify unique facilities and the emission unit ID identifies unique boilers or internal combustion engines. In most cases, there is a one-to-one correspondence between the CAMD identifiers and th e 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 inventory matched to the State and county Federal Implementation Plan (FIPS), State facility ID, and emission unit ID in the S/L inventory. The
initial crosswalk contained both the annual emissions summed from the CAMD database as well as the S/L emission estimate. It should be noted that the initial matching of the IDs in both inventories was based on previous crosswalks that had been developed for the preliminary VISTAS 2002 inventory and in-house information compiled by MACTEC and Alpine Geophysics. The matching at the facility level was nearly complete. In some cases, however, S/L agency or stakeholder assistance was needed to match some of the CEM units to emission units
in the S/L inventories.

The second step in the EGU analysis was to prepare an Excel spreadsheet that compared the annual emissions from the hourly CAMD inventory to the annual emissions reported in the S/L inventory. The facility-level comparison of CEM to emission inventory NO x 

### and SO 2 

### emissions found that for most facilities, the annual emissions from the S/L inventory equaled the CAMD CEM emissions. Minor differences could be explained because the facility in the S/L inventory contained additional small or emergency units that were not included in the CAMD database.

The final step in the EGU analysis was to compare the 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 stake holder. Southern Company independently provided emission estimates for 2002 as part of the development of the preliminary VISTAS 2002 inventory. In most cases, these estimates were reviewed by the States and incorporated into the States CERR submittal. The exception to this was a decision made by Georgia’s Department of Environmental Protection (GDEP) to utilize CE M-based emissions for the actual 2002 emissions inventory for sources within the State when Southern Company also provided data. There were no major inconsistencies between the Southern Company data, the CAMD data, and the S/L
CERR data.

The minor inconsistencies found included small differences in emission estimates (<2 percent difference), exclusion/inclusion of small gas-fired units in the different databases, and grouping of emission units in S/L CERR submittals where CAMD listed each unit individually. We compared 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 inventory 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 was run on the ASCII files and the QA output was reviewed to verify that all QA issues that could be addressed were resolved

Throughout the inventory development process, QA steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. QA was an important com ponent to the inventory development process and MACTEC performed the following QA steps on the point source component of the VISTAS revised 2002 base year inventory:

1. Facility level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.
2. State-level EGU and non-EGU comparisons (by pollutant) were developed between the Base F 2002 base year inventory, th e draft VISTAS 2002 inventory, and the 1999 NEI Version 2 inventory.
3. Data product summaries and raw NIF 3.0 data files were provided to the VISTAS Emission Inventory Technical Advisor and to the Point Source, EGU, and non-EGU Special Interest Work Group representatives for review and comment. Changes based on these comments were reviewed and approved by the S/L point source contact prior to implementing the changes in the files.
4. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from Base F1 to Base F2.
1.1.1.6 Additional Base G Updates and Corrections
S/L agencies completed a detailed review of the Base F inventory. Table 1.1-3 summarizes the updates and corrections to the Base F inventory that were requested by S/L agencies and incorporated into the Base G inventory.

There was a discrepancy between the base year 2002 and 2009/2018 emissions for PM 10 

### -PRI,
PM 2.5 

### -PRI, and NH 3 

### . The 2002 emissions were provided directly 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 data). The 2009/2018 emissions, on the other hand, were estimated by Pechan (see Section 2.1.1.3) using an emission factor file based solely on AP-42 emission factors. An adjustment was made for 2002 EGU PM and 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 “the most recent EPA approved uncontrolled emission factors” – these are most likely not the same emission factors used by States and emission inventory preparation contr actors 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 derived from the most recent EPA-approved emission factors. For further details of the methodology used to make this adjustment, see EGU Emission Factors and Emission Factor Assignment, memorandum from Greg Stella to VISTAS State Point Source Contacts and VISTAS EGU Special Interest Workgroup, June 13, 2005.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 (Site ID: 37-081-08100910), release point G-29, 9211.38 tons volatile organic compounds (VOC's) should be 212.2 tons, 529.58 tons 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 th e 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 th e 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 parameters 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 summarize the Base G 2002 base year inventory. All values are in tons. For the purposes of Tables 1.1-4 through 1.1-10, EGU emissions include the emissions from all processes with a Source Classificati on 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-E GU sectors based on the above SCCs causes a minor inconsistency with the EGU emissions reported in EPA’s CAMD database. The EGU emissions summarized in these tables may include emissions from some smaller electric generating units in the VISTAS inventory that are not in CAMD’s 2002 CEM database or the IPM forecasted emissions. The minor inconsistencies result in a less than 2 percent difference between the summary tables below and the data from CAMD’s CEM database.

Table 1.1-4. Base G 2002 VISTAS Point Source Inventory for SO 2 

### (tons/year).

State All Point Sources EGUs Non-EGUs

AL 544,309 447,828 96,481

FL 518,721 453,631 65,090

GA 568,731 514,952 53,778

KY 518,086 484,057 34,029

MS 103,388 67,429 35,960

NC 522,113 477,990 44,123

SC 259,916 206,399 53,518

TN 413,755 334,151 79,604

VA 305,106 241,204 63,903

WV 570,153 516,084 54,070
Total 4,324,278 3,743,725 580,556

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

### (tons/year).

State All Point Sources EGUs Non-EGUs

AL 244,348 161,038 83,310

FL 302,834 257,677 45,156

GA 196,767 147,517 49,251

KY 237,209 198,817 38,392

MS 104,661 43,135 61,526

NC 196,782 151,854 44,928

SC 130,394 88,241 42,153

TN 221,652 157,307 64,344

VA 147,300 86,886 60,415

WV 277,589 230,977 46,612
Total 2,059,536 1,523,449 536,087

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


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

State All Point Sources EGUs Non-EGUs

AL 49,332 2,295 47,037

FL 40,995 2,524 38,471

GA 34,952 1,244 33,709

KY 46,321 1,487 44,834

MS 43,852 648 43,204

NC 62,170 988 61,182

SC 38,927 470 38,458

TN 85,254 926 84,328

VA 43,906 754 43,152

WV 15,775 1,180 14,595
Total 461,484 12,516 448,970

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

State All Point Sources EGUs Non-EGUs

AL 185,550 11,279 174,271

FL 139,045 57,113 81,933

GA 140,561 9,712 130,850

KY 122,555 12,619 109,936

MS 59,871 5,303 54,568

NC 64,461 13,885 50,576

SC 63,305 6,990 56,315

TN 122,348 7,084 115,264

VA 70,688 6,892 63,796

WV 100,220 10,341 89,879
Total 1,068,604 141,218 927,388

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



### Table 1.1-8. Base G 2002 VISTAS Point Source Inventory for PM 10 

### -PRI (tons/year).

State All Point Sources EGUs Non-EGUs

AL 32,886 7,646 25,240

FL 57,243 21,387 35,857

GA 32,834 11,224 21,610

KY 21,326 4,701 16,626

MS 21,106 1,633 19,472

NC 36,592 22,754 13,838

SC 35,542 21,400 14,142

TN 49,814 14,640 35,174

VA 17,211 3,960 13,252

WV 22,076 4,573 17,503
Total 326,630 113,918 212,714

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

### -PRI (tons/year).

State All Point Sources EGUs Non-EGUs

AL 23,291 4,113 19,178

FL 46,148 15,643 30,504

GA 22,401 4,939 17,462

KY 14,173 2,802 11,372

MS 11,044 1,138 9,906

NC 26,998 16,498 10,500

SC 27,399 17,154 10,245

TN 39,973 12,166 27,807

VA 12,771 2,606 10,165

WV 15,523 2,210 13,313
Total 239,721 79,269 160,452

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


### Table 1.1-10. Base G 2002 VISTAS Point Source Inventory for NH 3 

### (tons/year).

State All Point Sources EGUs Non-EGUs

AL 2,200 317 1,883

FL 1,657 234 1,423

GA 3,697 83 3,613

KY 1,000 326 674

MS 1,359 190 1,169

NC 1,234 54 1,180

SC 1,553 142 1,411

TN 1,817 204 1,613

VA 3,230 127 3,104

WV 453 121 332
Total 18,200 1,798 16,402

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


### 1.1.2 Development of Typical Year EGU inventory
VISTAS developed a typical year 2002 emission inventory for EGUs to avoid anomalies in emissions due to variability in meteorology, economic, and outage factors in 2002. The typical year inventory represents the five year ( 2000-2004) starting period that would be used to determine the regional haze reasonable progress goals.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 factors for producing a 2002 typical year inventory for EGUs. We used the ratio of the 2000-2004 average heat input and the 2002 actual heat input to normalize the 2002 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 input, and operating hours.

We used the actual 2002 heat input and the average heat input for the 5-year period from 2000- 2004 as the normalization factor, as follows:

Normalization Factor: 2000-2004 average heat input 2002 actual heat input
If the unit did not operate for all five years, then the 2000-2004 average heat input was calculated for the one or two years in which the unit did operate. For example, if the unit operated only during 2002, then the normalization factor would be 1.0. The annual actual emissions were multiplied by the normalization factor to determine the typical emissions for 2002, as follows:

Typical Emissions = 2002 actual emissions x Normalization Factor
After applying the normalization factor, some adjustments were needed for special circumstances. For example, a unit may not have operated in 2002 and thus have zero emissions. If the unit had been permanently retired prior to 2002, then we used zero emissions for the typical year. If the unit had not been permanently retired and would normally operate in a typical year, then we used the 2001 (or 2000) heat input and emission rate to calculate the typical year emissions.

The Southern Company provided typical year data for their sources. Hourly emissions data for criteria pollutants were provided. MACTEC aggregated the hourly emissions into annual values. Further documentation of how Southern Company created the typical year inventory for their
units can be found in Developing Southern Company Emissions and Flue Gas Characteristics for VISTAS Regional Haze Modeling (April 2005, presented at 14 th 

### International Emission Inventory Conference http://www.epa.gov/ttn/chief/conference/ei14/session9/kandasamy.pdf ). Since Southern Company only supplied filterable particulate emissions, we ran the 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 emissions with the 2002 typical year data described above. MACTEC provided the raw data and results of the typical year calculations in a spreadsheet for S/L agency review and comment. Any comments made were incorporated into the Base G inventory.

Table 1.1-11 summarizes emissions by State and pollutant for the actual 2002 EGU inventory and the typical year EGU inventory. For the entire VISTAS region, actual 2002 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 percent lower in Florida to 10.9 percent higher in Mississippi. For the entire VISTAS region, actual 2002 NO x 

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

Table 1.1-11. Comparison of 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 Base G 2002 base year inventory for area sources. There are three major components of the area source sector of the inventory. The first component is the “typical” year fire inventory. Version 3.1 of the VISTAS base year fire inventory provided actual 2002 emissions estimates. Since fire emissions are not easily grown or projected, in 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 inventory was necessary. Development of the “typical” year fire inventory covered wildfire, prescribed burning, agricultural fires and land clearing fires. The first part of this section of the report discusses the development of the typical year fire inventory. The methodology provided in that section is identical to the documentation provided for Base F since the “typical” year inventory was developed as part of the Base F development effort. The major change in Base G for the fire component of the inventory was the development of projection year inventories that represent alternatives to the “typical” year inventory. These alternative projections incorporated projected changes in the acreage burned for prescribed fires on Federal lands. These projections are an augmentation of the “typical” year inventory.

The second component of the area source inventory was the incorporation of data submitted by the VISTAS States to the United States Environmental Protection Agency (EPA) as part of the CERR. Work on incorporating the CERR data into the revised base year involved: 1) obtaining the data from EPA, 2) evaluating the emissions and pollutants reported in order to avoid double counting and 3) backfilling from the existing VISTAS 2002 base year inventory for missing sources/pollutants. The processes used to perform those operations are described in the second portion of this section. That work was performed as part of the Base F inventory effort. In general no changes to that method were made as part of the Base G inventory updates. The methods used for the Base F inventory development effort using the CERR submittals have been maintained in this document. Where necessary, additional documentation has been added to 1) reflect changes that resulted from VISTAS States review of the Base F inventory and the incorporation of those changes into Base G, 2) changes made to how certain sources were estimated or 3) addition of new sources not found in Base F.

The final component of the area source inventory was related to the development of NH 3 

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

### emission estimates for livestock and fertilizers 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 methodol ogy for estimating paved road emissions so those values were substituted directly into the inventory after receiving consensus from all of the VISTAS States to perform the replacement. Details on these methods are provided in the third portion of this section of the document. That section is virtually identical to that from the Base F inventory document as there were only a couple of changes to the ammonia portion of the inventory and some updates to all fugitive dust categories including paved roads on a global
basis between Base F and Base G.

Finally, quality assurance steps for each component of the area source inventory are discussed.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 starting from the actual fire acreage data and emission calculated for each VISTAS State. The table below shows the data submitted by each State in the VISTAS region indicating what data was received from each State for the purposes of calculating actual fire emissions.

Fire Type AL FL GA KY MS NC SC TN VA WV Land Clearing 9 9 9 9 Ag Burning 9 9 9 9

Wildfires 9 9 9 9 9 9 9 9 9 9

Prescribed 9 9 9 9 9 9 9 9 9

In order to effectively characterize fire emissi ons in the VISTAS region, a typical (as opposed to strictly 2002 year based inventory) was required. Development of a typical year fire inventory provided the capability of using a comparable data set for both the base year and future years. Thus fire emissions would remain the same for air quality and visibility modeling in both the base and any future years. MACTEC originally proposed five different methods for developing the typical fire year to the VISTAS Fire Sp ecial Interest Work Group (SIWG) and requested their feedback and preference for developing the final typical year inventory. The method that was selected by SIWG members was to use a method similar to that used to develop an early version of a 2018 projection inventory. For that early 2018 inventory, State level ratios of acres over a longer term record (three or more years) developed for each fire type relative to 2002. The 2002 acreage was then scaled up or down based on these ratios to develop a typical year inventory. For Base F and G, the decision of the VISTAS Fire SIWG was to base the ratio oncounty level data for States that supplied long term fire-by-fire acreage data rather than Statelevel ratios. Where States did not supply long te rm fire-by-fire acreage data, MACTEC reverted to using State-level ratios. With one broad exception (wildfires) this method was implemented for all fires. MACTEC solicited long term fire-by-fire acreage data by fire type from each VISTAS State. A minimum of three or more years of data were used to develop the ratios. Those data were then used to develop a ratio for each county based on the number of acres burned in each county for each fire type relative to 2002.

Thus if we had long term county prescribed fi re data from a State, we developed a county acreage ratio of:

acreageRx levelcounty actual 2002 acresRx levelcounty average termLong

= 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 the ratio was then used with the fuel loading and emission factor values that we already had (and had been reviewed by the SIWG) to calculate emissions using the same method used for the 2002 actual values (which were previously documented). The following lists indicate which counties used the State ratios by fire type.

Land Clearing Agricultural Fires Prescribed Burning
FIPS COUNTY FIPS COUNTY FIPS COUNTY 12086 Miami-Dade County 12037 Franklin County 12043 Glades County 12045 Gulf County 12049 Hardee County 12057 Hillsborough County 12073 Leon County 12077 Liberty County 12081 Manatee County 12095 Orange County 12097 Osceola County 12103 Pinellas County 12115 Sarasota County 13015 Bartow County 13021 Bibb County 13045 Carroll County 13047 Catoosa County 13057 Cherokee County 13059 Clarke County 13063 Clayton County 13073 Columbia County 13077 Coweta County 13083 Dade County 13089 Dekalb County 13097 Douglas County 13117 Forsyth County 13121 Fulton County 13129 Gordon County 13135 Gwinnett County 13137 Habersham County 13143 Haralson County 13147 Hart County 13151 Henry County 13169 Jones County 13215 Muscogee County 13237 Putnam County 13241 Rabun County 13291 Union County 13311 White County 13063 Clayton County 13083 Dade County 13089 Dekalb County 13097 Douglas County 13121 Fulton County 13135 Gwinnett County 13137 Habersham County 13215 Muscogee County 13227 Pickens County 13241 Rabun County 13247 Rockdale County 13311 White County 13059 Clarke County 13083 Dade County 13089 Dekalb County 13097 Douglas County 13121 Fulton County 13123 Gilmer County 13135 Gwinnett County 13139 Hall County 13215 Muscogee County 13241 Rabun County 13247 Rockdale 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 State Ratios for Wildfires

The first exception was that wildfires estimates were developed using State ratios rather than county ratios. This change was made after initial quality assurance of the draft estimates revealed that some counties were showing unrealistic values created by very short term data records or missing data that created unrealistic ratios. In addition, exceptionally large and small fires were removed from the database since they were felt to be atypical. For example the Blackjack Complex fire in Georgia was removed from the dataset because the number of acres burned was “atypical” in that fire. We also removed all fires less than 0.1 acres from the dataset.
Exception 2: Correction for Blackened Acres on Forest Service Lands

Following discussions with the United States Fore st Service (Forest Service) (memo from Cindy Huber and Bill Jackson, dated August 13, 2004), it was determined that the acres submitted by the Forest Service for wildfires and prescribed fires represented perimeter acres rather than “blackened” acres. Thus for wildfires and prescribed fires on Forest Service lands, a further correction was implemented to correct the perimeter acre values to blackened acres. The correction was made based on the size of the fire. For prescribed fires over 100 acres in size the acreage was adjusted to be 80 percent of the initial reported value. For prescribed fires of 100 acres or less the acreage values were maintained as reported. For wildfires, all reported acreage values were adjusted to be 66 percent of their initially reported values. These changes were made to all values reported for Forest Service managed lands.
Exception 3: Missing/Non-reported data

When we did not receive data from a VISTAS State for a particular fire type, a composite average for the entire VISTAS region was used to determine the typical value for that type fire. For example, if no agricultural burning long term acreage data was reported for a particular State, MACTEC determined an overall VISTAS re gional average ratio that was used to multiply times the 2002 values to produce the “typical” values. This technique was applied to all fire types when data was missing.

In addition, for wildfires and prescribed burning, ratios were developed for “northern” and “southern” tier States within the VISTAS region and those ratios were applied to each State with missing data depending upon whether they were considered a “northern” or “southern” tier State. Development of “southern” and “northern” tier data was an attempt to account for a change from a predominantly pine/evergreen ecosystem (southern) to a pine/deciduous ecosystem (northern).
States classified as “southern” included: AL , FL, GA, MS, and SC. States classified as “northern” included: KY, NC, TN, VA, and WV.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

### and SO 2 

### emissions. This is due to the lack of emission factors for these pollutants for these fire types.

Table 1.2-1 shows fire emissions from the original base year emission inventory (VISTAS 3.1), the actual 2002 emissions and the typical year emissions for the entire VISTAS region. The actual 2002 and typical fire emissions 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 typical year prescribed fire emissions for 2009 and 2018 are detailed in the projection section. Also, State level Base G emissions from fires for all years can be found in the tables in Appendix A. Values for fires in those tables are “typical” year
values.

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

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

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

tonsPrescribed - 2002 ActualPrescribed - TypicalPrescribed - VISTAS 3.1Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.30Figure 1.2-4. CO Emissions from Wildfire Burning for theOriginal 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 component of the Base F and Base G 2002 base year inventory was the incorporation of data s ubmitted by the VISTAS States to the EPA as part of the CERR. With few exceptions, Base F and Base G inventories for this component of the inventory are identical. Modifications to th e Base F methodology (described below) only resulted from modifications from the VISTAS States during review of the Base F inventory. The changes made to the inventory based on these reviews are described in the last portion of this section of the report. The information presented below describes the method used to incorporate CERR data as part of Base F.

Work on incorporating the CERR data into the 2002 Base F inventory involved: 1) obtaining the data from EPA, 2) evaluating the emissions and pollutants reported in order to avoid double counting and 3) backfilling from the earlier versi on of the VISTAS 2002 base year inventory for missing sources/pollutants. The processes used to perform those operations are described below. This work did not include any of the fire emission estimates described above. In addition it did
not include emission estimates for ammonia from agricultural and fertilizer sources. Finally it did not include PM emissions from paved roads. Each of those categories was estimated separately.

Data on the CERR submittals was obtained from EPA’s Draft NEI download file transfer protocol (FTP) site where the data are stored after they’ve been processed for review. The data submitted in National Emission Inventory Format (NIF) was downloaded from that site. Once all of the files were obtained, MACTEC ran the files through the EPA NIF Format and Content checking tool to ensure that the files were submitted in standard NIF format and that there were no issues with those files. In a couple of cases small errors were found. For example, in one case a county FIPs code that was no longer in use was found. MACTEC contacted each VISTAS State area source contact person to resolve the issues with the files and corrections were made. Once all corrections to the native files were completed, MACTEC continued with the incorporation of the data into the VISTAS area source files.

Our general assumption was that unless we determined otherwise, the CERR submittals represented full and complete inventories. Where a State submitted a complete inventory, our plan was to simply delete the previous 2002 base year data and replace it with the CERR submittal. Prior to this replacement however, we stripped out the following emissions:

1. All wildfire, prescribed burning, land clearing and agricultural burning emissions submitted to EPA by the States as part of the CERR process were removed since they were to be replaced with emissions estimated using methods described earlier. 2. All fertilizer and agricultural ammonia emission records submitted to EPA by the States as part of the CERR process were removed. These were replaced with the estimates developed using the CMU Ammonia model.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 alternative data were used to prepare the Base F inventory. In general, these alternatives involved submittal of alternative files to the CERR data by S/L agencies. Table 1.2-2 below summarizes the data used to prepare the Base F inventory. In general the data were derived from one of the following sources: 1. CERR submittal obtained from EPA FTP site as directed by VISTAS States; 2. State submitted file (either revised from CERR submittal or separate format); 3. VISTAS original 2002 base year (VISTAS version 3.1 base year file); or 4. EPA’s preliminary 2002 NEI.
Table 1.2-2. Summary of State Data Submittals for the 2002 VISTAS Area Source Base F Inventory

State / Local Program Area Source Emissions Data Source
AL B
FL B GA C
KY A MS B NC C SC B
TN B VA B WV A/C Davidson County, TN B Hamilton County, TN C Memphis/Shelby County, TN A Knox County, TN B Jefferson County, AL * so B from State Jefferson County, KY B Buncombe County, NC * so C from State

Forsyth County, NC * so C from State Mecklenburg County, NC * so C from State

A = VISTAS 2002 (version 3.1) B = CERR Submittal from EPA's ftp site C = Other (CERR or other submittal sent directly from State to MACTEC) * = No 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 table. A series of codes were added to this field to mark the
source of each emissions value in the Base F and Base G inventories. Values in this field are
detailed in Table 1.2-3.

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

Data Source Codes Data Source

Base F Codes

CMU Model CMU Ammonia model v 3.6

E-02-X or E-99-F or L-02-X or S-02-X EPA CERR submittal (from FTP site)

EPA Paved EPA Paved Road emissions estimates

EPAPRE02NEI EPA Preliminary 2002 NEI

STATEFILE State submitted file

VISTBASYR31 VISTAS 2002 Base Year version 3.1

VISTRATIO Developed from VISTAS Ratios (used only for missing pollutants)

Additional Base G Codes

ALBASEGFILE Base G update file provided by AL

NCBASEGFILE Base G update file provided by NC
OTAQRPT Portable Fuel Container Emissions from OTAQ Report

STELLA Revised data provided by VISTAS EI Advisor Greg Stella

VABASEGFILE Base G update file provided by VA

VAStateFile Revisions/additions to Base G update file provided by VA



### Most States submitted complete inventories for Ba se F. Virginia’s inventory required a two stage update. Virginia’s CERR submittal only contained ozone precursor pollutants (including CO). For Virginia, MACTEC’s original plan was to maintain the previous 2002 VISTAS base year emissions for non-ozone pollutants and then do a simple replacement for ozone pollutants. However during the QA phase of the work, MACTEC discovered that there were categories that had ozone precursor or CO emissions in the submittal that weren’t in the original 2002 VISTAS base year inventory that should have PM or 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 developing SCC level ratios to NO x 

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

1.2.3 2002 Base G inventory updates
After the Base F inventory was submitted and 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 the inventory were made globally across the entire VISTAS region. This section discusses the specific State changes followed by the global changes made to the area source component of the inventory for all VISTAS States.

1.2.3.1 Changes resulting from State review and comment

Alabama

Alabama suggested several changes and had 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 (Institutional/Commercial Heating: Liquefied Petroleum Gas) the Alabama 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 that 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 the preliminary 2002 CERR submittals (see above)
which should have included SO 2 

### and PM but did not except for two counties. According to MACTEC’s protocol for use of these files, the f iles received from EPA were to be used “as is” unless the States provided comments during the Base F comment period to correct the CERR
submittal. No comments were received from AL on the CERR submittal used for Base F. For 2002 Base G, AL provided an updated database file for these SCCs for all counties in the State that provided revised values for emissions and included 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 inventory included SCC 2401002000 (Solvent Utilization, Surface Coating, Architectural Coatings - Solvent-based, Total: All Solvent Types) and 2401003000 (Solvent 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, Total: All Solvent Types) as well as SCC 2401001000 (Solvent Utilization, Surface Coating, Architectural Coatings, Total: All Solvent Types). This resulted in double counting of the emissions for this category. AL suggested removal of the breakdown SCCs
and use of the total SCC.

MACTEC deleted records for the breakdown S CCs and retained the total all solvents
SCC emissions.

3. AL found the SCCs listed below missing from the Base F VISTAS inventory.

SCC VOC Emissions SCC Description 2401025000 1139.91 Surface Coatings: Metal Furniture, all coating types 2401030000 425.27 Surface Coatings: Paper, all coating types 2401065000 344.08 Surface Coatings: Electronic and Other Electrical, all coating types 2430000000 504.29 Solvent Utilization, Rubber/Plastics, All Processes, Total: All Solvent Types 2440020000 3043.78 Solvent Utilization, Miscellaneous Industrial, Adhesive (Industrial) Application, Total: All Solvent Types
Total for AL 5457.32

MACTEC found that the emissions for these SCCs were included in the Base F inventory, but with slightly different total emissions. AL provided an updated county-level emissions file for use in updating the Base G inventory. That file was used to update the NIF records for AL for
those SCCs.

4. AL noted that emissions in the Base F inventory were found for SCC 2465000000 and SCCs 2465100000, 2465200000, 2465400000, 2465600000, and 2465800000. These last five SCCs represent a subset of the emissions in the 246500000 SCC resulting in potential double counting of emissions.

MACTEC deleted all emissions associated with the Total SCC 2465000000 and retained the subset SCCs for the Base G inventory.

Florida
Florida provided comments indicating that they felt that emissions from the following sources and counties were too high, especially for CO and PM and were likely zero: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 set to zero by MACTEC for the Base G inventory.

North Carolina
North Carolina provided corrected emission files for 2002 Base F. A text file with emission values was provided and used to update the Base F emissions to Base G. The updated emissions were applied directly to the Base F NIF file. The file provided was similar to the “EM” NIF table. An update query was used to update the data supplied in the text file to the Access database NIF file. All changes were implemented.

South Carolina
South Carolina had two issues concerning the Base F inventory. These issues related to 1) additional SCCs that were in BASE F 2009 and 2018, but not in 2002 Base F and 2) SCCs that were in the U.S. EPA 2002 NEI inventory, but not in the VISTAS 2002, 2009, or 2018 Base F inventory.

MACTEC investigated the additional SCCs found in 2009 and 2018 Base F and found that the SCCs actually were not missing in the 2002 Base F inventory but only had emissions for PM. Thus the emissions were maintained as they were provided in Base F.

With respect to the SCCs that were found in the U.S. EPA 2002 NEI, MACTEC investigated and found that they were not included in the Base F inventory because they were not included in the 2002 CERR submittal used to produce the Base F updates. The SCCs were apparently added by EPA later in the NEI development process. In addition, MACTEC also evaluated whether or not
the SCCs were found in other VISTAS States Base F inventories. MACTEC found that some States included them and some did not, there was no consistency between the States. MACTEC also found that typically emissions for these SCCs were low in emissions, generally with emissions of only a few tons to tens of tons 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 emissions 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 categories that required controls for future year projections since the sources were located in counties/cities in northern Virginia and were subject to future year Ozone Transport Commission (OTC) regulations. MACTEC added in the base year control levels to the Base G inventory file for these categories so that they could be estimated correctly in future years. The controls added were for mobile equipment repair/refinishing sources, architectural and industrial maintenance coating sources, consumer products sources, and solvent metal cleaning sources. Minor errors were found in some entries for the initial file provided and VA provided a revised file with corrections and minor additions.

1.2.4 Ammonia and paved road emissions
The final component of the Base F inventory development was estimation of NH 3 

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

### emission
estimates for livestock and fertilizers 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 statistics. Prior to inclusion of the CMU model estimates, MACTEC removed any ammonia records for agricultural livestock or
fertilizer emissions from the VISTAS 2002 initial base year inventory. MACTEC also generated emissions from human perspiration and from wildlife using the CMU model and added those
emissions for each State.

For the Base G ammonia inventory, MACTEC removed all wildlife and human perspiration emissions. VISTAS decided to remove these emissions from the inventory. Human perspiration was dropped due to a discrepancy in the units used for the emission factor that was not resolved prior to preparing the estimates and wildlife was dropped because VISTAS felt the activity data was too uncertain. Thus all emissions from these two categories were deleted in the Base G 2002 inventory.

For the paved road PM Base F emissions, we used the most recent estimates developed by EPA as part of the NEI development effort (Roy Huntley, U.S. EPA, email communication, 8/30/2004). EPA had developed an improved met hodology for estimating paved road emissions for 2002 and had used that method to calculate emissions for that source category. MACTEC
obtained those emissions from EPA and those values were substituted directly into the inventory after receiving consensus from all of the VISTAS States to perform the replacement. These files
were obtained in March of 2005 in NIF format from the EPA FTP site.

For the Base G emissions, modifications were made to the emissions estimates based on changes suggested by work of the Western Regional Air Partnership and U.S. EPA. Details of these changes are provided below in the section on global changes made as part of the Base G inventory updates.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 and human perspiration NH 3 

### emissions). These changes were:

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

2. Adjustment of fugitive dust 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 the area source component of the inventory. This decision had been made with SIWG agreement early on in the inventory development process because 1) some States had included it in thei r CERR submittals and 2) because the non-road and on-road mobile estimates had differing activity factor units and could not be easily combined. However for Base G, the VISTAS States all 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 sectors. 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 and U.S. EPA was in the process of making revisions to AP-42 for several categories during preparation of the Base G inventory. Based on data received from U.S. EPA, VISTAS decided to revise the 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 unpaved 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 add 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 State 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), Draft Report, Office of Transportation and Air Quality, United States Environmental 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 derived from Appendix Table B-2 of the PFCs report were used as the starting point for devel oping 2002 county-level emissions estimates. State emissions were derived from that table by using all of the emission estimates in that table with the exception of values for vapor displacement and spillage from refueling operations. Those components of the State emissions were left out of the State-level emissions to avoid double counting refueling emissions in the non-road sector. For the purposes of 2002 emission estimates for Base G, the 2005 values were assumed equal to 2002 values.

The 2005 State-level estimates minus the refueli ng component from Appendix Table B-2 of the report were summed for each State and then allocated to the county-level. The county-level allocation was based on the fuel usage information obtained from the NONROAD 2005 model runs conducted as part of the Base G inventory development effort (see the 2002 base year Base G non-road section below). MACTEC used the spillage file from the NONROAD model (normally located in the DATA\EMSFAC directory in a standard installation of NONROAD) to determine the SCCs that used containers for refueling. The spillage file contains information by SCC and horsepower indicating whether or not the refueling occurs using a container or a pump.All SCC and horsepower classes using containers were extracted from the file and crossreferenced with the fuel usage by county for those SCC/horsepower combinations from the appropriate year model runs (2002, 2009 or 2018). Then the fuel usages by county from the NONROAD 2005 runs prepared for VISTAS were summed for those SCCs by county. The county level fuel use was then divided by the State total fuel use for the same SCCs to determine the fraction of total State fuel usage and that fraction was used to allocate the State-level emissions to the county.

1.2.6 Quality Assurance steps
Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the area source component of the 2002 Base F inventory:

1. All CERR and NIF format State supplied data submittals were run through EPA’s Format and Content checking software.

2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.

3. Tier comparisons (by pollutant) were developed between the revised 2002 base year inventory and the previous (version 3.1) base year inventory.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 Fires SIWG representatives for review and comment. Changes based on these comments were implemented in the files.

6. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.

In addition, for the fires inventory, data relate d to fuel loading and fuel consumption was reviewed and approved by the VISTAS Fire SIWG to ensure that values used for each type of fire and each individual fire were appropriate . Members of the VISTAS Fire SIWG included representatives from most State Divisions of Forestry (or equivalent) as well as U.S. Forest Service and National Park Service personnel.

For Base G, similar QA steps to those outlined a bove for Base F were undertaken. In addition, all final NIF files were checked using the EPA Format and Content checking software and summary information by State and pollutant were prepared comparing the Base F and Base G inventories.

1.3 Mobile Sources

This section describes the revisions made to the initial 2002 VISTAS Base Year emission inventory on-road mobile source input files. For this work actual emission estimates were not made, rather data files consistent with Mobile Emissions Estimation Model Version 6 (MOBILE6) were developed and provided to the VISTAS modeling contractor. These input data files were then run during the VISTAS modeling to generate on-road mobile source emissions using episodic and meteorological specific conditions configured in the sparse matrix operator Kernel Emissions modeling system (SMOKE) emissions processor.

During initial discussions with the VISTAS Mobile Source SIWG, some States indicated a desire to use CERR mobile source emissions data in place of the VISTAS 2002 inventories generated by E.H. Pechan and Associates, Inc. (the initial VISTAS 2002 Base Year inventory files).

However, the CERR emissions data by itself were not sufficient for an inventory process that includes both base and future year inventories. MACTEC needed to be able to replicate the CERR data rather than simply obtain CERR emissions estimates. The reason for this is that only input files were being prepared to provide revised 2002 estimates during the VISTAS modeling process, rather than the actual emission estimates and that the 2002 input data files would 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 provided 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 begin compiling the appropriate input file data.

In those cases where States did not provide CERR on-road mobile source input data files, our default approach was to maintain the data input files and VMT estimates for the initial 2002 Base Year inventory prepared by Pechan.

1.3.1 Development of on-road mobile source input files and VMT estimates
Development of the 2002 on-road input files and VMT was a multi-step process depending upon what the State mobile source contacts instructed us to use as their data. Information provided below provides incremental revisions made to on-road mobile source inventories or inputs in series from one inventory version to the next. In general the process involved one of three steps from the original 2002 on-road mobile source data.

Base F Revisions

1. The first step was to evaluate the initial 2002 base year files and make any nonsubstantive changes (i.e., changes only to confirm that the files posted for 2002 by Pechan were executable and that all the necessary external files needed to run MOBILE6 were present). This approach was taken for AL, FL, GA, MS, SC, and WV. For these States the determination was made that the previous files would be okay to use as originally prepared. For SC, the VMT file was updated, but that did not affect the MOBILE6 input files.

2. For other States, modification to the input files was required. The information below indicates what changes were made for other States in the VISTAS region.

KY – For Kentucky, the Inspection and Maintenance (I/M) records in the input files for Jefferson County were updated in order to better reflect the actual I/M program in the Louisville metropolitan area.

NC - Substantial revisions were implemented to these input files based on input from the State. The modifications necessary to reflect the desires of the State led to complete replacement of the previous input files. Among the changes made were:

• The regrouping of counties (including the movement of some counties from one county group to another and the creation of new input files for previously 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 files; after the changes there were 49. The pointer file was corrected to reflect these changes.

• Travel speeds were updated in over 3000 scenarios.

• All I/M records were updated.

• All registration distributions were updated.

• I/M VMT fractions were updated (which only affected the pointer file).

• VMT estimates were updated (which has no di rect effect on the MOBILE6 input files but does ultimately affect emissions).

3. VA and TN – For these States, new input files were provided due to substantive changes that the State wanted to make relative to the 2002 initial base year input files. In addition, revised VMT data were developed for each State.

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

For all states modeled, the Base G updates include:

Adding Stage II refueling emissions calculations to the SMOKE processing.

Revised the HDD compliance for all states. (REBUILD EFFECTS = .1)

In addition to the global changes, individual VISTAS states made the following updates:

KY – updated VMT and M6 input values for selected counties.

NC – revised VMT and registration distributions.

TN - revised VMT and vehicle registrati on distributions for selected counties.

VA – revised winter RFG calculations in Mobile 6 inputs.

WV – revised VMT input data.

AL, FL, and GA did not provide updates for Base G and therefore the Base F inputs were used
for these States.

1.3.1.1 Emissions from on-road mobile sources
The MOBILE6 module of the Sparse Matrix 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 temperature data to calculate the gridded, temporalized
emission estimates. The MOBILE6 emissions factor s are based on episode-specific temperatures predicted by the meteorological model. Further, the MOBILE6 emissions factors model accounts for the following:

• Hourly and daily minimum/maximum temperatures;

• Facility speeds;

• Locale-specific inspection/maintenance (I/M) control programs, if any;

• Adjustments for running losses;

• Splitting of evaporative and exhaust emissions into separate source categories;

• VMT, fleet turnover, and changes in fuel composition and Reid vapor pressure (RVP).

The primary input to MOBILE6 is the MOBILE shell file. The MOBILE shell contains the various options (e.g. type of inspection and 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 variability in each month. The modeled weeks were selected from mid-month, avoiding inclusion of major holidays.

The parameters for the SMOKE runs are as follows:

Episodes: 2002 Initial Base Year, and 2009 and 2018 Future years, using 2009/2018 inventories and modeled using the same meteorology and episode days as 2002.
Episode represented by the following weeks per month: January 15-21 February 12-18
March 12-18 April16-22Documentation 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, -1620) kilometers with 168 rows by 177 columns and 12-km square grid cells.
CMAQ model species: The CMAQ configuration was CB-IV with PM. The model species produced were: CO, NO, NO 2 

### , ALD 2 

### , ETH, FORM, ISOP, NR, OLE, PAR, TERPB, TOL, XYL, NH 3 

### , SO 2 

### , SULF, PEC, PMFINE, PNO 3 

### , POA, PSO 4 

### , and PMC.
Meteorology data: Daily (25-hour). SMOKE requires the following five types of MCIP outputs: (1) Grid cross 2-d, (2) Grid cross 3-d, (3) Met cross 2-d, (4) Met cross 3-d, and (5),
Met dot 3-d.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 representative week run were calculated by mapping each day of week (Mon, Tue, Wed, etc.) from the modeled month to the same day of week generated in the representative week run. In the case of holidays, these days were mapped to representative week Sundays. An example of this mapping for the January episode is presented in Table 1.3-1 below. Note that although the emissions were generated for individual calendar years (2002, 2009 and 2018) the meteorology is based on 2002.

Table 1.3-1. Representative day mapping for January episode

(Highlighted representative week).

Modeled Representative Modeled Representative Modeled Representative

Date Day Date Day Date Day 1/1/2002* 1/20/2002 1/11/2002 1/18/2002 1/22/ 2002 1/15/2002 1/2/2002 1/16/2002 1/12/2002 1/19/2002 1/23/2002 1/16/2002 1/3/2002 1/17/2002 1/ 13/2002 1/20/2002 1/24/2002 1/17/2002 1/4/2002 1/18/2002 1/ 14/2002 1/21/2002 1/25/2002 1/18/2002 1/5/2002 1/19/2002 1/15/2002 1/15/2002 1/26/2002 1/19/2002 1/6/2002 1/20/2002 1/16/2002 1/16/2002 1/27/2002 1/20/2002 1/7/2002 1/21/2002 1/17/2002 1/17/2002 1/28/2002 1/21/2002 1/8/2002 1/15/2002 1/18/2002 1/18/2002 1/29/2002 1/15/2002 1/9/2002 1/16/2002 1/19/2002 1/19/2002 1/30/2002 1/16/2002 1/10/2002 1/17/2002 1/20/2002 1/20/2002 1/31/2002 1/17/2002 1/21/2002 1/21/2002 * Modeled holiday



### 1.3.2 Development of non-road emission estimates
Emissions from non-road sources were estimated in two steps. First, emissions for non-road
sources that are included in the NONROAD mode l were developed. Second, emissions from
sources not included in the NONROAD model were estimated. The sections below detail the procedures used for each group of sources.

1.3.2.1 Emissions from NONROAD model sources
An initial 2002 base year emissions inventory for non-road engines and equipment covered by the EPA NONROAD model was prepared for VISTAS in early 2004. The methods and assumptions used to develop the inventory are presented in a February 9, 2004 report

“ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc. Except as otherwise stated below, all aspects of the preparation methodology documented in that report continue to apply to the revised NONROAD modeling discussed in this section.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 were implemented to ensure that the latest State and local data were considered, as well as to more accurately reflect gasoline sulfur contents for 2002 and correct other State-sp ecific discrepancies. Those revisions comprise the Base F VISTAS non-road inventory. This section details the specific revisions made to the NONROAD model input files for the Base F and Ba se G VISTAS base year inventories, and provides insight into some key differences between the versions of the NONROAD model employed for the Base F and Base G inventories and the previous version employed for the initial 2002 base year inventory prepared by Pechan.

Revisions to the initial 2002 emissions inventory prepared by Pechan were actually implemented in two stages. An initial set of revisions was implemented in the fall of 2004. Those revisions resulted in the Base F inventory. These were followed by a second set of revisions in the spring of 2006. Those estimates produced the Base G base year inventory. To accurately document the combined effects of both sets of revisions, each set is discussed separately below. Unless otherwise indicated, all revisions implemented in Base F were carried directly into the Base G revision process without change. Thus, the invent ories that resulted from the Base F revisions served as the starting point for the Base G revisions.

For Base F, three VISTAS States provided detailed data revisions for consideration in developing revised model inputs. These States were:

1. North Carolina 2. Tennessee (including a separate submission for Davidson County), and 3. Virginia.
The remaining seven VISTAS States indicated that the initial 2002 VISTAS input files prepared by Pechan continued to reflect the most recent data available. These States were:

1. Alabama, 2. Florida, 3. Georgia, 4. Kentucky, 5. Mississippi, 6. South Carolina, and 7. West Virginia.
However, it should be recognized that the NONROAD input files for all ten VISTAS States were updated to reflect gasoline sulfur content revisi ons 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 revisions, it is important to note that the Base F 2002 base year inventory utilized a newer release of the NONROAD model than was used for the initial 2002 base year inventory (prepared by Pechan). The Base F 2002 base year inventory, as developed in spring 2004, was based on the Draft NONROAD2004 model, which was released by the EPA in May of 2004. This model is no longer available on EPA’s website. The initial 2002 base year inventory (prepared by Pechan) was based on the Draft NONROAD2002a version of the model (which is also no longer available on EPA’s website). Key differences
between the models are as follows:

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

• Draft NONROAD2004 included the exhaust emission impacts of the large spark-ignition engine standards; the evaporative impacts of these standards are not incorporated (this does not impact 2002 inventory estimates, but does affect future year forecasts).

• Draft NONROAD2004 included revised equipment population estimates.

• The PM 2.5 

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

• Draft NONROAD2004 included revisions to recrea tional marine activity, useful life, and
emission rates.

To the extent that these revisions affect 2002 emissions estimates, they will be reflected as differentials between the initial and Base F 2002 VISTAS base year inventories. It is perhaps important to identify that, at the time of the Base F inventory revisions; the EPA recognized the Draft NONROAD2004 model as an appropriate mechanism for SIP development. Although the model was designated as a draft update, it reflected the latest and most accurate NONROAD planning data at that time, as evidenced by the EPA’s use of that version for the Tier 4 Final Rulemaking.

Prior to the Base G inventory revisions implemented in 2006, the EPA released another updated version of the NONROAD model, designated as Final NONROAD2005 (which can be downloaded from: http://www.epa.gov/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 NONROAD2005 and Draft NONROAD2004 are as follows:

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

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### • Final NONROAD2005 includes emission estimates for a range of evaporative emissions categories not included in Draft NONROAD2004 (tank and hose permeation, hot soak, and running loss emissions).

• Final NONROAD2005 includes a revised diurnal emissions algorithm.

• Final NONROAD2005 includes a revised equipment scrappage algorithm.

• Final NONROAD2005 includes revised state and county equipment allocation data.

• Final NONROAD2005 allows separate sulfur c ontent inputs for marine and land-based
diesel fuel.

• Final NONROAD2005 includes revised convers ion factors for hydrocarbon emissions.

• Final NONROAD2005 includes the evaporative emission impacts of the large spark-ignition engine standards (this does not impact 2002 inventory estimates, but does affect future year forecasts).

Unfortunately, due to the extensive revisions associated with Final NONROAD2005, input files created for use with Draft NONROAD2004 (e.g., Base F input files) and earlier versions of the model cannot be used directly with Final NONROAD2005 (used for Base G). This created a rather significant impact in that the VISTAS NONROAD modeling process involves the consideration of over 200 unique sets of input data . To avoid creating new input files for each of these datasets, a conversion process was undertaken wherein each of the Draft NONROAD2004 (Base F) input data files were converted into the proper format required for proper execution in Final NONROAD2005 (Base G). 1 

### This process consisted of the following steps:

• Revise the Draft NONROAD2004 (Base F) input files to include the following two line EPA-developed comment at the end of the input file header (this is a nonsubstantive change implemented solely for consistency with input files produced directly using Final NONROAD2005):

9/2005 epa: Add growth & tech years to OPTIONS packet and Counties & Retrofit files to RUNFILES packet.

1 The necessary conversions where developed by comparing substantively identical input files created using the

graphical user interfaces for bot h Draft NONROAD2004 and Final NONROAD2005. The differences between the input files indicated the specific re visions necessary to convert existi ng 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) input files to include the following two command lines after the “Weekday or weekend” command in the PERIOD packet:

Year of growth calc:
Year of tech sel :



### • Revise the Draft NONROAD2004 (Base F) input files to include the following command line after the “Diesel sulfur percent” command in the OPTIONS packet:

Marine Dsl sulfur %: 0.2638



### Note that the value 0.2638 (2638 parts per million by weight [ppmW]) is applicable only for 2002 modeling and was accordingly revised (as described below) for both the 2009 and 2018 Base G forecast inventories. The 2638 ppmW sulfur value for 2002 marine diesel fuel was taken from the 48-State (excludes Alaska and Hawaii) tabulation presented in the April 27, 2004 EPA document “ Diesel Fuel Sulfur Inputs for the Draft NONROAD2004 Model used in the 2004 Non-road Diesel Engine Final Rule .” It should also be noted that this value differs by about 5 percent from the 2500 ppmW value previously used for the initial 2002 VISTAS modeling (performed by Pechan). Prior to Final NONROAD2005 (used for Base G), the NONROAD model allowed only a single diesel fuel sulfur input that was applied to both land-based and marine equipment. As documented in the February 9, 2004 report “ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc., a value of 2500 ppmW sulfur was used for all 2002 VISTAS NONROAD modeling. Given the ability of Final NONROAD2005 to distinguish a separate sulfur content for marine equipment and the existing EPA guidance document suggesting an appropriate marine sulfur value of 2638 ppmW for 2002, the existing modeling value of 2500 ppmW was modified (for marine equipment only).

• Replace the Draft NONROAD2004 (Base F) input files RUNFILES packet command
line:

TECHNOLOGY : c:\non-road\data\tech\tech.dat



### with the command lines:

EXH TECHNOLOGY : c:\non-road\data\tech\tech-exh.dat EVP TECHNOLOGY : c:\non-road\data\tech\tech-evp.dat



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

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RETROFIT :



### • Revise the Draft NONROAD2004 (Base F) input files to include the following command line after the “Rec marine outbrd” command in the ALLOC FILES packet:

Locomotive NOx : c:\non-road\data\allocate\XX_rail.alo



### Where “XX” varies across input files. For any given file, “XX” is the two digit abbreviation of the state associated with the scenario being modeled (e.g., for Alabama modeling, XX=AL).

• Replace the Draft NONROAD2004 (Base F) input files EMFAC FILES packet command
line:

Diurnal : c:\non-road\data\emsfac\diurnal.emf



### with the eight command lines:

Diurnal : c:\non-road\data\emsfac\evdiu.emf TANK PERM : c:\non-road\data\emsfac\evtank.emf NON-RM HOSE PERM : c:\non-road\data\emsfac\evhose.emf RM FILL NECK PERM : c:\non-road\data\emsfac\evneck.emf RM SUPPLY/RETURN : c:\non-road\data\emsfac\evsupret.emf RM VENT PERM : c:\non-road\data\emsfac\evvent.emf HOT SOAKS : c:\non-road\data\emsfac\evhotsk.emf RUNINGLOSS : c:\non-road\data\emsfac\evrunls.emfEVP



### • Revise the Draft NONROAD2004 (Base F) input files to include the following command line after the “PM exhaust” command in the DETERIORATE FILES packet:

Diurnal : c:\non-road\data\detfac\evdiu.det


### Once revised in this format, the VISTAS non-road input files developed for use with Draft NONROAD2004 (Base F) were executable under the Final NONROAD2005 model (Base G).

The only additional revisions implemented to develop a Final NONROAD2005-based inventory (Base G) involved elimination of non-default equipment allocation files for North Carolina and West Virginia. Due to concerns about improper equipment allocation across counties under the Draft NONROAD2004 model (used for Base F), as well as for earlier versions of the NONROAD model, North Carolina had produced alternative allocation data files indicating the number of employees in air transportation by county, the number of wholesale establishments by county, and the number of employees in landscaping services by county. For the same reason, West Virginia had produced alternative equipment allocation files indicating the number 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 underground coal production by county, the number of golf courses and country clubs by county, the number of wholesale establishments by county, the number of employees in logging operations by county, the number of employees in landscaping services by county, the number of employees in manufacturing operations by county, the number of employees in oil and gas drilling and extraction operations by county, and the number of recreational vehicle parks and campgrounds by county. These alternative equipment allocation files were used for all VISTAS inventory modeling conducted prior to the release of Final NONROAD2005 (i.e., through Base F). However, both North Carolina and West Virginia determined that the default allocation file revisions associated with the release of Final NONROAD2005 were appropriate to address the concerns that led to the development of the alternative allocation files. As a result, all alternative allocation file
commands were removed from VISTAS NONR OAD2005 (Base G) input files for North Carolina and West Virginia, so that the entire region under the Base G inventory is now modeled using the default allocation files provided with NONROAD2005.

In addition to the alternative equipment allocation files, North Carolina had previously developed an alternative seasonal adjustment file that was used for the Base F inventory in place of the default file provided with Draft NONROAD2004 (and earlier model versions). The alternative data file implemented a single change, namely reclassifying North Carolina as a southeastern state rather than a mid-Atlantic state (as identified in the default data file). Since Final NONROAD2005 continues to identify North Carolina as a mid-Atlantic state, North Carolina requested that the southeastern r eclassification be continued for all NONROAD2005 modeling (Base G). To ensure that any other revisions associated with the seasonal adjustment file released with NONROAD2005 were not overlooked, the previously developed alternative seasonal adjustment file for North Carolina was scrapped and a new alternative file was created from the default seasonal adjustment file provided with Final NONROAD2005 for Base G inventory development. The alternative file, which was used for all North Carolina modeling, reclassifies North Carolina from a mid-Atlantic to a southeastern state. This represents the only non-default data file used for VISTAS NONROAD2005-based (Base G) modeling.

The remainder of this section documents all changes to the originally established VISTAS input file values as documented in the February 9, 2004 report “ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc. Unless specifically stated below, all values from that report continue to be used without change in the latest VISTAS modeling.

Base F Revisions:
For the initial 2002 base year inventory (developed by Pechan), all NONROAD modeling runs for VISTAS were performed utilizing a gasoline sulfur content of 339 ppmW and a diesel 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 the EPA-recommended non-road diesel fuel sulfur content for 2002 is 2,283 ppmW, the 2,500 ppmW sulfur content used for the initial 2002 base year VISTAS inventory was designed to remove the effect of lower non-road diesel fuel sulfur limits applicable only in California. (The EPA recommended inputs can be found in “ Diesel Fuel Sulfur Inputs for the Draft NONROAD2004 Model used in the 2004 Non-road Diesel Engine
Final Rule ,” EPA, April 27, 2004.) This correction is appropriate and was retained for the Base F 2002 inventory. Thus, the Base F inventory continue d to assume a diesel fuel sulfur content of 2,500 ppmW across the VISTAS region.

However, 339 ppmW is not the EPA recommended 2002 gasoline sulfur content for either eastern conventional gasoline areas or Federal Reformulated Gasoline (RFG) areas. The recommended sulfur content for eastern conventional gasoline is 279 ppmW year-round, while the recommended sulfur content for RFG areas is 129 ppmW during the summer season and 279 ppmW during the winter season. (Conventional gasoline and RFG sulfur contents for 2002 can
be found in “ User’s Guide to MOBILE6.1 and MOBILE6.2, Mobile Source Emission Factor
Model ,” EPA420-R-03-010, U.S. EPA, August 2003 [pages 149-155] (available at link at http://www.epa.gov/otaq/m6.htm ) and in the source code for MOBILE6.2 at Block Data BD05.) Given the differences in the EPA-recommended values and the value used to generate the initial 2002 base year inventory, the input files for Base F for all VISTAS areas were updated to reflect revised gasoline sulfur content assumptions.

Since the VISTAS NONROAD modeling is performed on a seasonal basis, and since gasoline sulfur content in RFG areas varies with the RFG season, seasonally-specific gasoline sulfur content values were estimated for use in RFG area modeling. In addition, 25 counties in Georgia are subject to a summertime gasoline sulfur limit of 150 ppmW, so that seasonal sulfur content estimates were also estimated for these counties. The initial 2002 base year NONROAD inventory (prepared by Pechan) for these Georgia counties was based on a year-round 339 ppmW gasoline sulfur content, but that oversight was corrected in the Base F 2002 base year inventory. Based on the seasonal definitions em ployed in the NONROAD model, monthly sulfur contents were averaged to estimate seasonal gasoline sulfur contents as follows:

Month/Season RFG Areas Conventional Gasoline Areas Georgia Gasoline Control Areas

March 279 ppmW 279 ppmW 279 ppmW April 279 ppmW 279 ppmW 279 ppmW May 129 ppmW 279 ppmW 150 ppmW Spring 229 ppmW 279 ppmW 236 ppmW

June 129 ppmW 279 ppmW 150 ppmW July 129 ppmW 279 ppmW 150 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), and that the transition between summer and winter seasons is also not considered. Additionally, the summer fuel control season is treated as though it applies from May through September, while the summer RFG season actually ends on September 15 and the Georgia fuel control season does not officially begin until June 1. This
treatment is consistent with the treatment of both fuel control programs in the VISTAS on-road vehicle modeling. Each of these influences will result in some error in the estimated sulfur content estimates, but it is expected that this error is small relative to the overall correction from a year-round sulfur content estimate of 339 ppmW.

All NONROAD modeling revisions made as part of the Base F inventory preparation process are presented in Table 1.3-2. Due to more involved updates in several areas, the number of NONROAD input files as well as sequence numbers used to represent these files was alsoupdated 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 ppm W 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: Barro w, Bartow, Butts, Carroll, Chero kee (a), Clayton (a), Cobb (a), Coweta (a), Dawson, De Kalb (a), Douglas (a), Fayette (a), Forsyth (a), Fulton (a), Gwinnett (a), Hall, Haralson, Henry (a), Jackson, Newton, Paulding (a), Pickens, Rockdale (a), Spalding, and Walton

KY (1) Gasoline sulfur content changed from 339 ppm W to 279 ppmW in all seasons for conventional gasoline counties. (2) Gasoline sulfur content changed from 339 ppmW to 129 ppmW in the summer for all gasoline control counties. (3) Gasoline sulfur content changed from 339 ppmW to 229 ppmW in the spring and fall for all gasoline control counties. (4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control counties.
Gasoline control counties: Boone, Bullitt (b), Campbell, Jefferson, Kenton, and Oldham (b)

MS (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas).

NC (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas). (2) Utilize revised (i.e., local) allocation files for three equipment categories. (3) Utilize revised (i.e., local) seasonal activity data.

SC (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas).

TN (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas). (2) Gasoline Reid Vapor Pressure (RVP) values changed in accordance with local recommendations. (3) Temperature data changed in accordance with local recommendations. (4) Counties regrouped in accordan ce 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 ppm W 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 accordan ce with local recommendations. (7) The control effectiveness for c ounties subject to Stage II controls revised to 77 percent in accordance with local recommendations. Gasoline control counties: Arlington Co ., Fairfax Co., Loudoun Co., Prince William Co., Stafford Co., Alexandria City, Fairfax City, Falls Church City, Manassas City, Manassas Park City, Chesterfield Co., Hanover Co., Henrico Co., Colonial Heights City, Hopewell City, Richmond City, James City, York Co., Chesapeake City, Hampton City, Newport News City, Norfolk City, Poquoson City, Portsmouth City, Suffolk City, Virginia Beach City, and Williamsburg City (c)

WV (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all are conventional gasoline areas). (2) Continue to utilize local allocation files for nine equipment categories.

Notes:

(a) County is subject to local control currently, but is scheduled to join the RFG program in January 2005. (b) Control area is a portion of the county, but modeling is performed as though the control applies countywide. (c) The EPA also lists Charles City County as an RFG area, but local planners indicate that Charles City County is a 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 changes 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 in to a complete VISTAS region inventory. The indicated revisions do not (in and of themselves) result in emission estimate changes.

(2) The NONROAD model imposes an eight digit input file name lim it, 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 invent ory, 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 revision implemented for the Base G 2002 inventory was the use of the Final NONROAD2005 model (in place of the Base F use of Draft NONROAD2004). However, there were other minor revisions implemented for 13 Georgia counties and somewhat more significant revisions implemented for Tennessee. In Georgia, Stage II refueling control was assumed for 13 counties that previously were modeled as having no refueling control under Base F. In addition, to accommodate this Stage II change as well as forecast year changes in gasoline vapor pressure, corresponding changes in the structure and sequence of Georgia NONROAD input files were made. With the exception of the minor Stage II impacts, these structural and sequence changes have no impact on 2002 emission estimates, but allow for consistency between 2002 and forecast year input file structure and sequence. In Tennessee, more significant changes were implemented to gasoline vapor pressure assumptions, as well as similar minor changes in Stage II refueling control assumptions.

In accordance with instructions from Georgia regulators, Stage II refueling control was assumed in the following 13 Georgia counties at a control efficiency value of 81 percent for the Base G inventory:

Cherokee, Clayton, Cobb, Coweta, DeKa lb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding, and Rockdale.

No Stage II control was assumed in these counties in prior inventories.

Tennessee regulators provided revised monthly valu es for gasoline vapor pressure. Based on the seasonal definitions employed in the NONROAD mode l, monthly vapor 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

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March 13.5 psi 13.5 psi 13.5 psi April 13.5 psi 13.5 psi 13.5 psi May 9.0 psi 9.0 psi 9.0 psi Spring 12.0 psi 12.0 psi 12.0 psi

June 7.8 psi 7.8 psi 9.0 psi July 7.8 psi 7.8 psi 9.0 psi August 7.8 psi 7.8 psi 9.0 psi

Summer 7.8 psi 7.8 psi 9.0 psi September 1-15 7.8 psi 7.8 psi 9.0 psi September 16-30 11.5 psi 11.5 psi 11.5 psi

October 13.5 psi 13.5 psi 13.5 psi

November 13.5 psi 13.5 psi 13.5 psi

Fall 12.2 psi 12.2 psi 12.4 psi

December 15.0 psi 15.0 psi 15.0 psi

January 15.0 psi 15.0 psi 15.0 psi February 13.5 psi 13.5 psi 13.5 psi

Winter 14.5 psi 14.5 psi 14.5 psi

Note: The Nashville area consists of Davidson, Rutherford, Sumner, Williamson and Wilson counties, the Memphis area consists of Shelby County.



### As with the Base F revisions, the seasonal data are based on simple arithmetic averages and do not consider any monthly variation in activity (and fuel sales), nor is the transition between summer and winter seasons considered. Additionally, a monthly average of the September 1-15 and September 16-30 data is calculated prior to averaging the September-November data to estimate a fall average vapor pressure, so that the month of September is weighted identically to
the months of October and November.

Tennessee regulators also indicated that Stage II vapor recovery was not in effect in Shelby County, so the Base F NONROAD input files for the county (which assumed Stage II was in place) were revised accordingly.

All Base G NONROAD modeling revisions are presen ted in Table 1.3-4. As indicated above, the differentiation of inputs across previously groupe d counties also required revision to the overall number and sequence of VISTAS NONROAD input files (as compared to the files used to createDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### both the initial VISTAS non-road inventory, as documented in the February 9, 2004 report

“ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc., and the Base F revised inventory as documented above. These structural revisions are presented in Table 1.3-5, and are provided solely for the benefit of NONROAD modelers as the indicated revisions have no impact on generated emission estimates.

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

State Revisions Implemented
AL (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons.
FL (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons.

GA (1) Marine diesel sulfur content changed fro m 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, Clayt on, Cobb, Coweta, De Kalb, Douglas, Fayette, Forsyth, Fulton, Gwinnett, Henry, Paulding, and Rockdale
KY (1) Marine diesel sulfur content changed fro m 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 fro m 2500 ppmW to 2638 ppmW in all counties and seasons. (2) Revert to default equipment allocation files for all equipment categories. (3) Utilize revised (i.e., local) seasonal activity data.
SC (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons.

TN (1) Marine diesel sulfur content changed fro m 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 fro m 2500 ppmW to 2638 ppmW in all counties and seasons.

WV (1) Marine diesel sulfur content changed fro m 2500 ppmW to 2638 ppmW in all counties and seasons. (2) Revert to default equipment allocation 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 changes 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 in to a complete VISTAS region inventory. The indicated revisions do not (in and of themselves) result in emission estimate changes.

(2) The NONROAD model imposes an eight digit input file name lim it, 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, th e 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 Vessels, Locomotives, and Airplanes
An initial 2002 base year emissions inventory for aircraft, locomotives, and commercial marine vessels (CMV) was prepared for VISTAS in early 2004. The methods and data used to develop the inventory are presented in a February 9, 2004 report “ Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 Version) ” as prepared by E.H. Pechan & Associates, Inc. A summary of the initial 2002 base year emissions inventory is presented in Table 1.3-6. Except as otherwise stated below, all aspects of the preparation methodology continue to apply to the Base F and Base G emission inventories.

Revisions to the initial 2002 emissions inventory (prepared by Pechan) were implemented to ensure that the latest State and local data were incorporated as well as to correct an overestimation of PM emissions from aircraft. Revisions were actually implemented in two stages. An initial set of revisions was implemented in the fall of 2004. Those revisions constitute the Base F inventory. These were followed by a second set of revisions in 2006, which constitute the Base G inventory. To accurately document the combined effects of both sets of revisions, each set is discussed separately below. Unless otherwise indicated, all revisions implemented for Base F were carried directly into the Base G revision process without change. Thus, the
inventories that resulted from the Base F revisi ons served as the starting point for the Base G
revisions.

Base F Revisions:
Revisions to the initial 2002 base year emissions inventory were implemented to ensure that the latest State and local data were incorporated as well as to correct an overestimation of PM
emissions from aircraft. Seven of the ten VISTAS States provided revised inventory data in the form of emissions reported to the EPA under the CERR. States providing CERR data were Alabama, Georgia, Mississippi, North Carolina, Tennessee (excluding Davidson, Hamilton, Knox, and Shelby Counties), Virginia, and West Virginia.

In many cases, the CERR data were only marginally different than the initial 2002 base year inventory data, but there were several instances where significant updates were evident. The remaining three VISTAS States (Florida, Kentucky, and South Carolina), plus Davidson, Hamilton, Knox, and Shelby counties in Tennessee, indicated that the initial 2002 VISTAS inventory continued to reflect the most recent data available. Florida did provide updated aircraft emissions data for one county (Miami-Dade) and these data were incorporated into the Base F 2002 inventory as described below.

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

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### after the release of the initial 2002 base year inventory, when it was determined that VISTAS region airports would constitute the top seven, and 11 of the top 15, PM sources in the nation. Moreover, PM emissions for one airport (Miami International) were a full order of magnitude larger than all other modeled elemental carbon PM emission sources. In addition, unexpected relationships across airports were also obser ved, with emissions for Atlanta’s Hartsfield International being substantially less than those of Miami International, even though Atlanta handles over twice as many aircraft operations annually. Given the pervasiveness of this problem, and since the CERR data submitted by States was based on the initial 2002 VISTAS inventory data, aircraft PM emissions for the entire VISTAS region were recalculated.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 emission factors and, th erefore, aircraft PM is generally erroneously reported as zero. In an effort to overcome this deficiency, the developers of the initial VISTAS 2002 base year aircraft inventory (Pechan) estimated PM emission rates for aircraft using
estimated 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 base 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, general aviation, and air taxi aircraft in many, but not all, instances. Although there is nothing inherently incorrect with this approach, the accuracy and inconsistent application of the assumed PM-to-NO x 

### ratio results in grossly overestimated
aircraft PM.

Through examination of the initial 2002 base year aircraft inventory (prepared by E.H. Pechan and Associates, Inc.), it is apparent that the commercial aircraft PM-to-NO x 

### ratio used to generate PM emission estimates was approximately 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 illustrated 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 em issions 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 dominant 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, which were retained without change in the PM estimation process (although a considerable number 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 inventory dataset). Regardless, based on previous statistical analyses performed in support of aircraft emissions inventory 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 Tucson, 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 Area, Volume I., Study Description and Results,” prepared for the Pima Association of Governments, Tucson, AZ, November 2001. Pages 4-40 through 4-42 of that report, which document the statistical derivation of these ratios, are included in this report as Appendix E.

Table 1.3-8. Tucson, AZ PM-to-NO x 

### Ratios by Aircraft Type.

Aircraft Type PM-to-NO x Commercial Aircraft 0.26

Military Aircraft 0.88

Air Taxi Aircraft 0.50

General Aviation Aircraft 1.90
Note: The PM and NO x emission estimates presented in the Tucson study are for local aircraft operating mode times. For this work, emission estimates for Tucson were recalcu lated for a standard LTO cycle, so that the ratios presented are applicable to the sta ndard LTO cycle and not a Tucson-specifi c cycle. Thus, the ratios presented herein vary somewhat from those asso ciated with the emission estimates pr esented in the Tucson study report.



### In reviewing these data, it should be considered th at 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-specific 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 associated with the 3.95 commercial aircraft ratio used for the initial 2002 base year inventory.

It should be recognized that while the Tucson area is far removed from the VISTAS region, the data analyzed to generate the PM-to-NO x 

### ratios is standard aircraft emission factor data routinely

2 As defined in AP-42, Compilation of Air Pollutant Emission Factors, Volume II, Mobile Sources, a standard

commercial aircraft LTO cycle consists of 4 minutes of approach tim e, 26 minutes of taxi (7 minutes in plus 19 minutes out), 0.7 minutes of takeoff, and 2.2 minutes of climbout time (approach and climbout times being based on a 3000 foot mixing height).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### employed for inventory purposes throughout the United States (as encoded in models such as the
Federal Aviation Administration’s Emissions Da ta Management Systems [EDMS]). With the exception of aircraft operating conditions, there are no inherent geographic implications associated with the use of data from the Tucson study. As indicated above, issues associated with local operating conditions have been eliminated by recalculating the Tucson study ratios for a standard LTO cycle.

To implement the revised PM-to-NO x 

### ratios in the Base F inventory, all aircraft PM records were removed from the initial 2002 base year inventory (prepared by Pechan). This includes records for which local planners may have estimated PM emissions. This approach was taken for two reasons. First, there is no way to distinguish which records may have been generated by local planners. Second, the data available to local planners may be no better than that used to generate the presented PM-to-NO x 

### ratio data, so the consistent application of these data to the entire VISTAS region was determined to be the most appropriate approach to generating consistent inventories throughout the region. In undertaking this removal, it became apparent that there was
an imbalance in the aircraft 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 distributed 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 since there was no corresponding NO x 

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

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### PM 10 

### and PM 2.5 

### records for Hamilton County permanently reduced the overall size of the 2002 initial base year inventory database used as a starting point for Base F by two records.

Of the 320 unmatched NO x 

### records, 269 were records for which 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 reported under the generic aircraft SCC 2275000000. For these counties (Palm Beach County, Florida and Davidson County, Tennessee), the commercial
aircraft PM-to-NO x 

### ratio was applied since both contain commercial airports (Palm Beach International and Nashville International).

Replacement aircraft PM 2.5 

### records were also developed. The 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 internal combustion engine
PM 2.5 

### fractions approach 100 percent. For example, the EPA NONROAD model assumes 92 percent for gasoline engine particulate and 97 percent for diesel engine particulate. Based on recent correspondence from the EPA, it appears that the agency is preparing to recommend a
PM 2.5 

### fraction of 98 percent for aircraft. (August 12, 2004 e-mail correspondence from U.S. EPA to Gregory Stella of Alpine Geophysics.) This is substantially more consistent with expectations based on emissions test data for other internal combustion engine sources and was used as the
basis for the recalculated aircraft 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 extracted from the i nventory for areas not supplying CERR data for the Base F update would be accurate. Therefore, in no case is the aggregated State data reported for the Base F inventory identical to that of the initial 2002 base year inventory. Even areas relying on the initial 2002 base year inventory will reflect updates in Base F due to changes in emissions
of PM 10 

### and PM 2.5 

### from aircraft.

Table 1.3-10 presents the updated initial 2002 base year inventory estimates. These estimates do not reflect any changes related to modifications made to incorporate the CERR data, but instead indicate the impacts associated solely with the recalculation of aircraft PM emissions alone to apply the more appropriate PM to NO x 

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

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### impacts of these changes, where an over 90 percent reduction in aircraft PM is observed for all VISTAS areas except South Carolina and Virginia. The reasons for the lesser changes in these
two States is that the overall aircraft NO x 

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

### to which no (or very low) particulate estimates were assigned in the initial 2002 base year inventory. Since these operations are assigned non-zero PM emissions under the revised approach, the increase in military aircraft PM offsets a portion of the reduction in commercial aircraft PM. In Virginia, zero (or near zero) PM military operations were responsible for about 35 percent of total aircraft NO x 

### , while the corresponding fraction in South Carolina was almost 70 percent. As indicated, aggregate aircraft, locomotive, and commercial marine vessel PM is 70-75 percent lower in the updated 2002 base year inventory.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 all or portions of seven VISTAS States were replaced with corresponding data from recent (as of the fall of 2004) CERR submissions for 2002. Before replacing these data, however, an analysis of the CERR data was performed to ensure consistency with VISTAS inventory methods. It should perhaps also be noted that three of the CERR datasets provided for the Base F 2002 base year inventory (specifically those for Tennessee, Virginia, and West Virginia) included both annual and daily emissions data. Only the annual data were used. Daily values were removed.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Several important observations resulted from this analysis. First, it was clear that all of the CERR data continued to rely on the inaccurate aircraft PM estimation approach employed for the initial 2002 base year inventory. Therefore, an identical aircraft PM replacement procedure as described above for updating the initial 2002 base year inventory was undertaken for CERR supplied data. As a result, the CERR data for all VISTAS States has been modified for inclusion in the Base F 2002 VISTAS base year inventory due to PM replacement procedures.

As was the case with the initial VISTAS 2002 base year inventory, there were a substantial
number of aircraft 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 inventory data, refl ecting 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 that 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 reported emission rate was zero. Therefore, even though the associated PM records were missing, the overall inventory was not affected. However, the 88 missing records for which 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 described above for the updated initial 2002 base year inventory.

Further analysis revealed that the CERR data for Virginia included only VOC, CO, and NO x 

### emissions for all aircraft, locomotives, and 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 applied 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 locomotive and marine vessel data since aircraft PM was estimated using the PM-to-NO x 

### ratio methodology described above.

Consideration was given to simply adding the Virginia SO 2 

### and non-aircraft PM records from the initial 2002 VISTAS inventory dataset, but it is very unlikely that either the source distribution
or associated emission rates are identical across the CERR and initial VISTAS inventories. This was confirmed through a comparative analysis of dataset CO records. Therefore, an estimation methodology was developed using Virginia source-specific SO 2 

### /CO, PM 10 

### /CO, and PM 2.5 

### /PM 10 

### ratios from the initial 2002 base year VISTAS inventory. The calculated ratios were then applied to the source-specific CERR CO emission estimat es 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 ratios from the initial 2002 base year inventory was performed at the State (i.e., Virginia), county, and SCC level of detail. However, it readily
became clear that there were substantial inconsistencies in ratios for identical SCCs across counties. For example, in one county, the 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 equipment sources is regional as opposed to local in nature, such variati ons in emission rates are not realistic. Therefore, a more aggregated approach was employed in which SCC-specific emission ratios were developed for the State as a whole. Through this approach county-to-county variation in emission ratios is eliminated, but the underlying variation in CO emissions does continue to influence the resulting aggregate emission estimates. The applied emission ratios are as follows:

Table 1.3-13 Calculated Emission Ratios for VA.

Source SCC SO 2 /CO PM 10 /CO PM 2.5 /CO PM 2.5 /PM 10 Military Airc raft 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 inconsistency of emissions ratios across Virginia counties for sources of virtually identical design, which utilize a regional rather than local fueling infrastructure, has potential implications for other VISTAS States. There is no immediately obvious reason to believe that such inconsistencies would be isolated to Virginia.

One final revision to the CERR dataset was undertaken as part of the Base F effort, and that was the removal of two records for unpaved airstrip particulate (SCC 2275085000) in Alabama. Otherwise identical records for these emissions were reported both in terms of filterable and primary particulate. The filterable particulate records were removed as all other particulate
emissions in the VISTAS inventories are in terms of primary particulate. It is also perhaps worth noting that a series of aircraft refueling records (SCC 2275900000) for Virginia were left in place, even through typically such emissions would be reported under SCC 2501080XXX in the area source inventory. If additional VISTAS aircraft refueling emissions are reported under SCC 2501080XXX, then it may be desirable to recode these records.

Finally, data for areas of the VISTAS region not represented in the CERR dataset were added to the CERR data by extracting the appropriate records from the initial 2002 base year inventory (with revisions for aircraft PM to NO x 

### ratios). Specifically, records applicable to the States of Florida, Kentucky, South Carolina, and the Tennessee counties of Davidson, Hamilton, Knox, and Shelby were extracted from the revised initial 2002 inventory and added to the CERR dataset to establish the 2002 Base F inventory.

Following this aggregation, one last dataset revision was implemented to complete the development of the 2002 Base F inventory. As 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-Dade County were obtained from Florida planners and used to overwrite the erroneous estimates. (Aircraft emission estimates were provided in an August 10, 2004 e-mail transmittal from Bruce Coward of Miami-Dade County to Martin Costello of the Florida Department of Environmental Protection.)

Table 1.3-14 presents a summary of the resulti ng Base F VISTAS 2002 base year inventory estimates for aircraft, locomotives, and non-recreational marine vessels. Table 1.3-15 provides a comparison of the Base F 2002 base year inventory estimates to those of the initial 2002 base year inventory. As indicated, total emissions for VOC, CO, 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 emissions due to the correction of Miami International estimates is also apparent.

Lastly, Table 1.3-16 provides a direct comparison of emission estimates from the initial and Base F 2002 base year inventories for all 16 VISTAS re gion airports with estimated annual aircraft
NO x 

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

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

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

### emissions using detailed NO x 

### estimates developed for Tucson 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 developed VISTAS estimates, and it is clear that the range of estimated-to-expected NO x 

### emissions has been substantially narrowed in the Base F 2002 base year inventory. Whereas estimated-to-expected ratios varied from about 0.2 to over 3.5 in the initial 2002 base year inventory, the range of variation is tightened on both ends, from about 0.5 to 1.75 for the Base F 2002 base year inventory. In effect, all estimates are now within a factor of two of the expected estimates, which is quite reasonable given likely variation in local and standard LTO cycles and variations in aircraft fleet mix across airports.

It is perhaps important to note that some shifting in county emissions assignments is evident between the initial and Base F 2002 base year aircraft inventories. For example, for the initial 2002 base year inventory, Atlanta Hartsfield estimates were assigned to Fulton County (FIP 13121), while they are assigned to Clayton County (FIP 13063) for the Base F 2002 base year inventory. Similarly, Dulles International Airport emissions were assigned solely to Fairfax County, Virginia (FIP 51059) in the initial 2002 base year inventory, but are split between Fairfax and Loudoun County (FIP 51107) for Base F. Such shifts reflect local planner decision-making and are not an artifact of the revisions described above.

3 Subsequent revisions performed for Base G result in the addition of the Cincinnati/Northern Kentucky

International Airport to the group of airports with aircraft operations generating at least 200 tons of 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 1 132 30,000 336 0.67 Aggregate 41,836 21,724 75,682 52,220 1,655 6,290 0.19-3.57 Base F 2002 Base Year Inventory Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 Orlando-Sanford 12117 3,615 1,225 338 332 100 351 Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47

Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97

Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 Hampton 51650 858 535 471 461 18 305 Military Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 Aggregate 37,829 20,550 5,838 5,721 2,312 5,793 0.47-1.75 Net Change -10% -5% -92% -89% +40% -8% Note: For the Base F inventory, Dulles International Airport emissions are split betw een 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 emissions inventory were implemented in response to additional state data submittals in the spring of 2006. The inventories developed through the Base F revision process (as described above) served as the starting point for the 2006 revisions. Thus, unless otherwise indicated below, all documented Base F revisions continue to apply to the Base G-revised 2002 base year inventory.

As part of the Base G review and update pr ocess, Virginia regulators provided 443 updated
emission records for aircraft. These records re flected revisions to aircraft VOC, CO, and NO x 

### , and in a few cases SO 2 

### , emissions records that were already 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 records in the Base F 2002 VISTAS inventory were updated for Base G to reflect the revised data. However, as described above for the Base F revisions, all aircraft 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 inventory revisions, except that revised SO 2 

### -to-CO emissions ratios were calculated for commercial aircraft, 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 calculated 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 associated with retention of the Base F ratio will be minor. Table 1.3-18 presents the emissions ratios.

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

Source SCC 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 Aircra ft 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 revised 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 Virginia. 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 aircraft (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 updated PM emission records for aircraft actually reflected the original (overestimated) aircraft PM data that was replaced universally throughout the VISTAS region for Base F. Implementing these latest revisions would, in effect, “undo” the Base F aircraft PM revisions. Following discussi ons with Alabama regulators, it was determined that the 178 aircraft PM records would not be updated for the Base G revisions.

The 42 additional emissions records for locomotives were determined to correspond exactly to existing 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 emissions records in conjunction 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 errone ous and should be excluded from the update. The remaining 162 records reflected additional general aviation, air taxi, and military aircraft activity in 20 counties and were specifically comprised of 27 records each for VOC, CO, NO x 

### , SO 2 

### , PM 10 

### , and PM 2.5 

### . There were no further issues 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 County, to correct previously underestimated
aircraft emissions associated with the Cinci nnati/Northern Kentucky International 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 data being replaced) for Boone County aircraft to the updated PM 10 

### emissions. Thus, a total of 24 inventory 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 additional emission records (all in Alabama) were added to the 2002 VISTAS inventory. The total number of aircraft, locomotive, and commercial marine inventory records thus changed from 22,838 records in Base F to 23,042 records in
Base G.

Table 1.3-19 presents a summary of the resulti ng Base G VISTAS 2002 base year inventory estimates for aircraft, locomotives, and non-recreational marine vessels. Table 1.3-20 provides a comparison of the Base G 2002 base year inventory estimates to those of the Base F 2002 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 comparison 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 are 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 1 132 30,000 336 0.67 Cincinnati 21015 467 144 38 37 14 54 50,000 560 0.26 Aggregate 38,296 20,694 5,876 5,758 2,326 5,847 0.26-1.75 Base G 2002 Base Year Inventory Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 Orlando-Sanford 12117 3,615 1,225 338 332 100 351 Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47

Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97

Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 Hampton 51650 858 535 471 461 18 305 Military Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 Cincinnati 21015 3,378 411 110 107 39 187 50,000 560 0.73 Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 Aggregate 41,207 20,961 5,947 5,828 2,352 5,981 0.47-1.75 Net Change +8% +1% +1% +1% +1% +2% Note: For the revised inventory, Dulles International Ai rport emissions are split betw een 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) and temporal resolution as estimates for the VISTAS region.

The requested estimates were produced by extracting a complete set of county-level input data applicable to each of the three states from the latest version of the EPA’s NMIM (National Mobile Inventory Model) model. This included appropriate consideration of all non-default NMIM input files generated by the Midwest Regional Planning Organization (MRPO), as described below. These input data were then assembled into appropriate input files for the Final NONROAD2005 model and emission estimates were produced using the same procedure employed for the VISTAS region as part of the Base G updates.

A complete set of monthly input data was deve loped for each county in Illinois, Indiana, and Ohio by extracting data from the following NMIM database files (using the NMIM MySQL query browser):

county, countrynrfile, countyyear, countyyearmonth, countyyearmonthhour, gasoline, diesel, and natural gas

The database files:

countrynrfile, countyyear, countyyearmonth, and gasoline

were non-default database files provided to VI STAS by the MRPO, and are intended to reflect the latest planning data being used by MRPO modelers.

From these files, monthly data for gasoline vapor pressure, gasoline oxygen content, gasoline sulfur content, diesel sulfur content for land-based equipment, diesel sulfur content for marine-based equipment, natural gas sulfur content, minimum daily temperature, maximum daily temperature, and average daily temperature were developed. In addition, the altitude and Stage II refueling control status of each county, as well as the identity of the associated equipment population, activity, growth, allocation, and seasonal distribution files, was determined. These data were then assembled into Final NONROAD2005 input files on a seasonal basis, with monthly data being arithmetically averaged to produce seasonal equivalents as follows:

Winter = Average of December, January, and February Spring = Average of March, April, and May Summer = Average of June, July, and August, Fall = Average of September, October, and 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 approach results in the use of the following non-default data files during the Final NONROAD2005 modeling process:

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

Data File Illinois Indiana Ohio
Activity File 1700002.act 1800002.act 3900002.act
Growth File 17000.grw 18000.grw 39000.grw
Population File 17000.pop 18000.pop 39000.pop

Season File 17000.sea 18000.sea 39000.sea

Inboard Marine Allocation File 17000wib.alo 18000wib.alo 39000wib.alo

Outboard Marine Allocation File 17000wob.alo 18000wob.alo 39000wob.alo

Specific Fuel Consumption MRPO-specific file provided by MRPO modelers (arbitrarily named “mrpoBSFC.emf” for this work)

One compromise was made relative to the level of resolution that is available through the basic approach described above, that being the treatment of ambient temperature data. Because NMIM offers a unique temperature profile for every U.S. county -- developed by aggregating temperature data from included and surrounding 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 input streams. Ungrouped however, there would be 1,128 distinct input streams to be processed (102 Illinois counties plus 92 Indiana counties plus 88 Ohio counties at four seasons each), or over five times the number of files processed for the entire VISTAS region.

To surmount this problem and allow counties with similar temperature profiles to be grouped an approach was employed wherein counties were considered groupable if all temperature inputs 4 

### are within ± 2 oF of the corresponding group average. This criterion is quite stringent in that it results in less tolerant grouping than that employed for VISTAS modeling, which uses temperature data from the nearest meteorological station as opposed to "unique" meteorological

4 Non-road temperature inputs used for county grouping are: winter minimum, spring minimum, summer minimum,

fall minimum, winter maximum, spring maximum, summer maximum, fall maximum, winter average, spring average, summer averag e, 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, the actual deviation for grouped counties is much less that ± 2 oF for the overwhelming majority of the 12 grouped temperature inputs.

In addition to the required temperature consistency, all other input data for counties to be grouped had to be identical for all four seasons. Using this criterion, Illinois emissions were modeled using 12 county groups, Indiana emissi ons were modeled using 9 county groups, and Ohio emissions were modeled using 10 c ounty groups. Thus, 31 iterations of NONROAD2002 were required per season, as compared to the 53 iterations per season required for the VISTAS region.

It should be noted that a potential quality assurance issue was noted in assembling the NONROAD2005 input data for a number of Indiana counties. Specifically, the gasoline vapor pressure for most Indiana counties reflects a value of 9.0 psi in all spring, summer, fall, and winter months. This is likely to indicate a problem with the accuracy of the NMIM databases for these counties, but these data were used as defined for this work.

1.3.3 Quality Assurance steps
Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the area source component of the 2002 base year revised:

1. All CERR and NIF format State supplied data submittals were run through EPA’s Format and Content checking software.

2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.

3. Tier comparisons (by pollutant) were developed between the revised 2002 base year inventory and the initial base year inventory.

4. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to Mobile Source SIWG representatives for review and comment. Changes based on these comments were implemented in the files.

5. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.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 different sectors of the point source inventory:

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

### (IPM ® 

### ) to project future generation as well as to calculate the impact of future emission control programs. The IPM results were adjusted based on S/L agency knowledge of planned emission controls at specific EGUs.

• For non-EGUs, we used recently updated growth a nd control data consistent with the data used in EPA’s CAIR analyses, and supplemented these data with available S/L agency input and updated fuel use forecast data for the U.S. Department of Energy.

For both sectors, we generated 2009 and 2018 inventories for a combined on-the-books (OTB)and on-the-way (OTW) control scenario. The OTB/OTW control scenario accounts for post2002 emission reductions from promulgated and proposed federal, State, local, and site-specific control programs as of July 1, 2004. Section 2.1.1 discusses the EGU projection inventory development, while Section 2.1.2 discusses the non-EGU projection inventory development.

2.1.1 EGU Emission Projections
The following subsections discuss the following specific aspects of the development of the EGU projections. First, we present a chronology of the EGU development process and discuss key decisions in selecting the final methods for performing the emissions projections. Next, we describe the development of the final set of IPM runs that are included in the VISTAS Base G inventory. Next, we describe the process of tran sforming the IPM parsed files into NIF format.Fourth, we discuss the process for ensuring that units accounted for in IPM were not doublecounted in the non-EGU inventory. Fifth, we desc ribe the QA/QC checks that were made to ensure that the IPM results were properly inco rporated into the VISTAS inventory. Sixth, we document the changes to the IPM results that S/L agencies specified they wanted included in the VISTAS inventory based on new information that was not accounted for in the IPM runs. Finally, we present summarize the Base G projected EGU emissions by year, state, and pollutant.

2.1.1.1 Chronology of the Development of EGU Projections
At the beginning of the EGU inventory developmen t process, VISTAS 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 inputs 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 parameters, and generate results for 2009 and 2018 explicitly.

An additional consideration for each of the three options was the inclusion of emission projections developed by the Southern Company specifically for their units. Southern Company is a super-regional company which owns EGUs in Alabama, Florida, Georgia, and Mississippi and participates in VISTAS as an industry stakeholder. Southern Company used their energy budget forecast to project net generation and heat input for every existing and future Southern Company EGU for the years 2009 and 2018. Further documentation of how Southern Company generated the 2009/2018 inventory for their units can be found in Developing Southern Company Emissions and Flue Gas Characteristics 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 runs (Option 3) to represent the 2009 and 2018 EGU forecasts of emissions for the OTB and OTW cases. During the call, Alabama and Georgia specified that they did not wish to use Sout hern Company provided emissions forecasts of 2009 and 2018 to represent the sources in their States. Mississippi decided to utilize the Southern Company projections to represent activity at Southern Company facilities in Mississippi. After the call, Florida decided against using Southe rn Company provided emissions forecasts of 2009 and 2018 to represent the sources in their State. Thus, Southern Company data was used only for Southern Company units in Mississippi for both the Base F and Base G projections.

The Option 3 IPM modeling resulted from a joint agreement by VISTAS and MRPO to work together to develop future year utility emissions based on IPM modeling. The decision to use IPM modeling was based in part on a study of utility forecast methods by E.H. Pechan and Associates, Inc. (Pechan) for MRPO, which recommended IPM as a viable methodology (see Electricity Generating Unit {EGU} Growth Modeling Method Task 2 Evaluation , February 11,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 support their rulemaking for the Clean Air Interstate Rule (CAIR), VIST AS stakeholders felt that certain model inputs needed to be improved. Thus, VISTAS and MRPO decided to hire contractors to conduct new IPM modeling and to post-process the IPM results. Southern Company projections in 2009 were roughly comparable with IPM. For 2018, Southern Company projections were generally less than IPM because of assumptions made by Southern Company on which units would be
economical to control and incorrect data in the NEEDS database which feeds IPM.

In August 2004, VISTAS contracted with ICF International, Inc., to run IPM to provide utility forecasts for 2009 and 2018 under two future scenarios – Base Case and CAIR Case. The Base Case represents the current operation of the power system under currently known laws and regulations (as known at the time the run was made), including those that come into force in the study horizon. The CAIR Case is the Base Case with the proposed CAIR rule superimposed. The run results were parsed at the unit level for the 2009 and 2018 run years. Also in August 2004, MRPO contracted with E.H. Pechan to post-pr ocess the IPM outputs generated by ICF to provide model-ready emission files. The IPM output files were delivered by ICF to VISTAS in November ( Future Year Electricity Generating Sect or Emission Inventory Development Using the Integrated Planning Model (IPM ® 

### ) in Support of Fine Particulate Mass and Visibility Modeling in the VISTAS and Midwest RPO Regions , January 2005), and the post-processed data files were delivered by Pechan to the MRPO in December 2004 ( LADCO IPM Model Parsed File Post-Processing Methodology and File Preparation , February 8, 2005).

On March 10, 2005, EPA issued the final Clean Air Interstate Rule. VISTAS and MRPO, in conjunction with other RPOs, conducted another round of IPM modeling which reflected changes to control assumptions based on the final CAIR as well as additional changes to model inputs based on S/L agency and stakeholder comments. Several conference calls were conducted in the spring of 2005 to discuss and provide comments on IPM assumptions related to six main topics: power system operation, generating resources, emission control technologies, set-up parameters and rule, financial assumptions, and fuel assumptions. Based on these discussions, VISTAS sponsored a new set of IPM runs to reflect the final CAIR requirements as well as certain changes to IPM assumptions that were agreed to by the VISTAS states. This set of IPM
runs is documented in Future Year Electricity Generating Sector Emission Inventory Development Using the Integrated Planning Model (IPM ® 

### ) in Support of Fine Particulate Mass and Visibility Modeling in the VISTAS and Midwest RPO Regions , April 2005 (these runs are referred to as the VISTAS Phase I analysis).

Further refinements to the IPM inputs and assumptions were made by the RPOs, and ICF performed the following four runs using IPM dur ing the summer of 2005 (these 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 supply curves adjusted for AEO 2005 reference case price and volume relationships.

• Strategy Case with EPA 2.1.9 coal, gas and oil price assumptions.

• Strategy Case with EPA 2.1.9 coal and gas supply curves adjusted for AEO 2005 reference case price and volume relationships.

The above runs were parsed for 2009 and 2018 run years. The above four runs were based on VISTAS Phase I and the EPA 2.1.9 assumptions. The changes that were implemented in the
above four runs are summarized below:

• Unadjusted AEO 2005 electricity demand projections were incorporated in the above
four runs.

• The gas supply curves were adjusted for AEO 2005 reference case price and volume relationships. The EPA 2.1.9 gas supply curves were scaled such that IPM will solve for AEO 2005 gas prices when the power sector gas demand in IPM is consistent with AEO 2005 power sector gas demand projections.

• The coal supply curves used in EPA 2.1.9 were scaled in such a manner that the average mine mouth coal prices that the IPM is solving in aggregated coal supply regions are comparable to AEO 2005. Due to the fact that the coal grades and supply regions between AEO 2005 and the EPA 2.1.9 are not directly comparable, this was an approximate approach and had to be performed in an iterative fashion. The coal transportation matrix was not updated with EIA assumptions due to significant differences between the EPA 2.1.9 and EIA AEO 2005 coal supply and coal demand region configurations.

• The cost and performance of new units were updated to AEO 2005 reference case levels
in all of the above four funs.

• The run years 2008, 2009, 2012, 2015, 2018, 2020 and 2026 were modeled.

• The AEO 2005 life extension costs for fossil and nuclear units were incorporated in the
above runs.

• The extensive NEEDS comments provided by VISTAS, MRPO, CENRAP and MANEVU were incorporated into the VISTAS Phase I NEEDS.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 state regulations in the northeast were incorporated.

• Renewable Portfolio Standards (RPS) in the northeast was modeled based on the Regional Greenhouse Gas Initiative analysis. A single RPS cap was modeled for MA, RI, NY, NJ, MD and CT. These states could buy credits from NY, PJM and New England model regions.

• The investments required under the Illinoi s power, Mirant and First Energy NSR settlements were incorporated in the above runs.

For the VISTAS/CENRAP Phase II set of IPM runs , ICF generated two different parsed files. One file includes all fuel burning units (fossil, biomass, landfill gas) as well as non-fuel burning units (hydro, wind, etc.). The second file cont ains just the fossil-fuel burning units (e.g., emissions from biomass and landfill gas are omitted). The RPOs decided to use the fossil-only file for modeling to be consistent with EPA, since EPA used the fossil only results for CAIR analyses. For the 10 VISTAS states, non-fossil fuels accounted for only 0.13 percent of the NOx emissions and 0.04 percent of the 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 inve ntory. S/L agencies 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 latest 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 IPM results were made to specific units with any new information they had as part of the permitting process or other contact with the industry that
indicates which units will install controls as a result of CAIR and when these new controls will come on-line. Mississippi decided to continue to use the Southern Company projections instead of the IPM projections to represent emissions at Southern Company facilities in Mississippi. The state-specified changes to the VISTAS/CENRAP Ph ase II set of IPM runs were used to create the Base G projection inventory (and are documented later in Section 2.1.1.6).

2.1.1.2 VISTAS IPM runs for EGU sources
The following general summary of the VISTAS IPM ® 

### modeling is based on ICF’s
documentation Future Year Electricity Generating Sector Emission Inventory Development Using the IPM ® 

### in Support of Fine Particulate Mass and Visibility Modeling in the VISTAS and Midwest RPO Regions , April 2005. The ICF documentation is to be used as an extension to EPA's proposed CAIR modeling runs documented in Documentation Supplement for EPA Modeling Applications (V.2.1.6) Using the IPM , EPA 430/R-03-007, July 2003.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, electricity dispatch, and emission control strategies for meeting energy demand a nd environmental, transmission, dispatch, and reliability constraints.” The underlying database in this modeling is U.S. EPA’s National Electric Energy Data System (NEEDS) released with the CAIR Notice of Data Availability (NODA). The NEEDS database contains the existing and planned/committed unit data in EPA modeling applications of IPM. NEEDS includes basic geographic, operating, air emissions, and other data on these generating units. VISTAS St ates and stakeholders provided changes for:

• NO x 

### post-combustion control 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 rules or enforcement settlements

The years 2009 and 2018 were explicitly modeled.

2.1.1.3 Post-Processing of IPM Parsed Files
The following summary of the VISTAS/Midwest Regional Planning Organization (MRPO) IPM modeling is based on Pechan’s documentation LADCO IPM Model Parsed File Post-Processing Methodology and File Preparation , February 8, 2005. The essence of the IPM model postprocessing methodology is to take an initial IPM model output file and transform it into air quality model input files. ICF via VISTAS/MRPO provides an initial spreadsheet file containing
unit-level records of both

(1) “existing” units and

(2) committed or new generic aggregates.

All records have unit and fuel type data; existing, retrofit (for 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 FI PS code. Existing units also have county FIPS code, a unique plant identifier (ORISPL) and unit ID (also called boiler ID) (BLRID); generic units do not have these data. The processing includes estimating various types of emissions and adding in control efficiencies, stack paramete rs, latitude-longitude coordinates, and State identifiers (plant ID, point ID, stack ID, process ID). Additionally, the generic units are sited in a county and given appropriate IDs. This processing is described in more detail below.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 generic aggregates into units similar to the existing units in terms of the available data. The generic aggregates are split into smaller generic units based on their unit types and capacity, are provided a dummy ORIS unique plant and boiler ID, and are given a county FIPS code based on an algorithm that sites each generic by assigning a sister plant that is in a county based on its attainment/nonattainment status. Within a State, plants (in county then ORIS plant code order) in attainment counties are used first as sister sites to generic units, followed by plants in PM nonattainment counties, followed by plants in 8-hour
ozone nonattainment counties. Note that no LADCO or VISTAS States provided blackout counties that would not be considered when siting generics, so this process is identical to the one used for EPA IPM post-processing.

SCCs were assigned for all units; unit/fuel/firing/bottom type data were used for existing units’assignments, while only unit and fuel type were used for generic units’ assignments. Latitudelongitude coordinates were assigned, first using the EPA-provided data files, secondly using the September 17, 2004 Pechan in-house latitude-longitude file, and lastly using county centroids. These data were only used when the data were not provided in the 2002 NIF files. Stack parameters were attached, first using the EPA-provided data files, secondly using a March 9, 2004 Pechan in-house stack parameter file based on previous EIA-767 data, and lastly using an EPA June 2003 SCC-based default stack parameter file. These data were only used when the data were not provided in the 2002 NIF files.

Additional data were required for estimating VOC, CO, filterable primary PM 10 

### and PM2.5, 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 PM10 and
PM2.5 efficiencies were obtained from th e 2002 EGU NEI that were based on 2002 EIA-767 control data and the PM Calculator program (a default of 99.2 percent is used for coal units if necessary); fuel use was back calculated from the given heat input and a default SCC-based heat content; and emission factors were obtained from an EPA-approved October 7, 2004 Pechan
emission factor file based on AP-42 emission factor s. Note that this updated file is not the one used for estimating emissions for previous EPA post-processed IPM files. Emissions for 28 temporal-pollutant combinations were estimated since there are seven pollutants (VOC, CO, primary 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 with the identifiers in VISTAS 2002 inventory. A
crosswalk file was used to obtain FIPS State a nd 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-processed files in NIF 3.0 format. Two sets of tables were developed : “NIF files” for IPM units that have a crosswalk match and are in the 2002 VISTAS inventory,
and “NoNIF files” for IPM units that are not in the 2002 VISTAS inventory (which includes existing units with or without a crosswalk match as well as generic units).

For Base F and Base G projections, VISTAS reviewed the PM and NH 3 

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

### emission factors that are “the most recent EPA approved uncontrolled emission factors” for estimating 2009/2018 emissions. These factors are most likely not the same emission factors used by States for estimating these emissions in 2002 for EGUs in the VISTAS domain. Thus, the emission increase from 2002 to 2009/2018 was simply an artifact of the change in emission factor, not anything to do with changes in activity or control technology application. Also, VISTAS identified an inconsistent use of SCCs for determining emission factors between the base and future years.

VISTAS resolution of the PM and 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 condensable component of emissions was calculated and added to the resulting PM primary estimations. The resulting emissions were then adjusted by any control efficiency factors reported in the CERR or VISTAS data collection effort. The second adjustment was to the future year inventories. Alpine Geophysics updated the SCCs in the future year inventory to assign the same base year SCC. Using the same methods as described for the 2002 revisions, those non-IPM generated pollutants were estimated using IPM predicted fuel characteristics and base year 2002 SCC assignments.

2.1.1.4 Eliminating Double Counting of EGU Units
The following procedures were used to avoid double counting of EGU emissions in the 2009/2018 point source inventory. The 2002 VISTAS point source emission inventory contains both EGUs and non-EGUs. Since this file contains both EGUs and non-EGU point sources, and EGU emissions are projected using the IPM, it was necessary to split the 2002 point source file into two components. The first component contains those emission units accounted for in the IPM forecasts. The second component contains all other point sources not accounted for in IPM.

As described in the previous section, Pechan developed 2009/2018 NIF files for EGUs from the IPM parsed files. All IPM matched units were initially removed from the 2009/2018 point 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 matches IPM emission unit identifiers (ORISPL plant code and BLRID emission unit code) to VISTAS NIF emission unit identifiers (FIPSST state code, FIPSCNTY county code, State Plant ID, State Point ID). When there was a match between
the IPM ORISPL/BLRID and the VISTAS 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 files created by Pechan from the IPM output, the corresponding unit was removed from the initial 2009/2018 point source inventory. The NIF 2009/2018 EGU files from the IPM parsed files were then merged with the non-EGU 2009/2018 files to create the 2009/2018 Base F point source files.

Next, we prepared several ad-hoc QA/QC queries to verify that there was no double-counting of
emissions in the EGU and non-EGU inventories:

• We reviewed the IPM parsed files {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 theVISTAS cross-reference table to verify that units accounted for in IPM were not doublecounted in the non-EGU inventory. As a result of this comparison, we made a few adjustments in the cross-reference table to add emission units for four plants to ensure these units accounted for in IPM were moved to the EGU inventory.

• We reviewed the non-EGU inventory to identify remaining emission units with an Standard Industrial Classification (SIC) c ode of “4911 Electrical Services” or Source
Classification Code of “1-01-xxx-xx External Combustion Boiler, Electric Generation”. We compared the list of sources meeting these selection criteria to the IPM parsed file to
ensure that these units were not double-counted.

S/L agencies also reviewed the 2009/2018 point source inventory to verify whether there was any double counting of EGU emissions. In two 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 the EGU component of the VISTAS revised 2009/2018 EGU inventory:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

2. Provided facility level emission summaries for 2009/2018 for both the base case and
CAIR case to the VISTAS EGU SIWG to ensure that emissions were consistent and that there were no missing sources.

3. Compared, at the State-level, emissions from the IPM parsed files and the post-processed NIF files to verify that the post-processed NIF files were consistent with the IPM parsed
file results.

VISTAS requested S/L review of these files – the changes specified by states as a result of this review are documented in the following subsection.

2.1.1.6 S/L Adjustments to IPM Modeling Results for Base G Projections
After S/L agency review of the final set of IPM r uns (as incorporated into the Base F inventory), S/L agencies specified a number of changes to the IPM results to better reflect current information on when and where future controls would occur. These changes to the IPM results primarily involved S/L agency addition or subtraction future emission controls based on the best available data from state rules, enforcement agreements, compliance plans, permits, and discussions/commitments from individual companies.

For example, Dominion Virginia Power released their company-wide plan to reduce emission to meet the requirements of CAIR and other programs. This plan varies substantially from the IPM results both in terms current and future controls and timing of these controls. As a result, VA DEQ developed their best estimates of future 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 projections from the Duke Energy and Progress Energy compliance plan. NC DENR elected to use the IPM results for 2018.

Some S/L agencies specified changes to the controls assigned by IPM to reflect their best estimates of emission controls. The changes specified by the S/L agencies are summarized in Table 2.1-1. These changes involved either 1) adding selective catalytic reduction (SCR) or scrubber controls to units where IPM did not predict SCR or scrubber controls, or 2) removing IPM-assigned SCR or scrubber controls at units where the S/L agency indicated their were no firm plans for controls at those units. We used a scrubber control efficiency of 90 percent when adding or removing SO 2 

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

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

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### NO x 

### SCR controls at gas-fired plants, a nd 35 percent when adding or removing NO x 

### SNCR controls.

In addition to the changes to the IPM-assigned controls, the S/L agencies also specified other types of changes to the IPM results. These other specific changes to the IPM results are
summarized in Table 2.1-2.

S/L agencies provided information and/or comment on changes in stack parameters from the 2002 inventory for 2009/2018 inventory. Changes to st ack parameters were also made in cases where new controls are scheduled to be installed. In cases where 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 are not far enough along in the design process to have specific design details. For those units, the VISTAS EGU SIWG made the following assumptions: 1) the scrubber is a wet scrubber; 2) keep the current stack height the same; 3) keep the current flow rate the same, and 4) change the stack exit temperature to 169 degrees F (this is the virtual temperature derived from a wet temp erature of 130 degrees F). VISTAS determined that exit temperature (wet) of 130 degrees F +/- 5 degrees F is representative of different size units and wet scrubber technology.

2.1.1.7 Summary of Base F and Base G 2009/2018 EGU Point Source Inventories
Tables 2.1-3 through 2.1-9 compare the Base G 2002 base year inventory to the Base F4 and Base G 2009/2018 projection inventories. The Base F4 projections rely primarily on the results of the IPM, while the Base G projections include the adjustments to the IPM results specified by the S/L agencies in the previous section.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.99Table 2.1-1 Adjustments to IPM Control Determinations Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories.NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateAL James H. MillerORISID=60021 & 2 SCRduringozoneseasonSCRprobableyear rounddue toCAIRSCRduringozoneseasonSCRprobableyear rounddue toCAIRNone None None Scrubber3 & 4 SCRduringozoneseasonSCR yearround fromConsentDecreeSCRduringozoneseasonSCR yearround fromConsentDecreeNone None None ScrubberBarry1, 2, 3 None SNCR SCR SNCR None None None NoneORISID=3 4 None SNCR SCR SNCR None None Scrubber Scrubber5 None None SCR SCRNone None Scrubber ScrubberE C Gaston1 - 4 SCR None SCRNone None None Scrubber ScrubberORISID=26 5 SCR SCR SCR SCRScrubber None Scrubber ScrubberGorgas6 & 7 None None NoneNone None None None NoneORISID=88 & 9 None None NoneNone None Scrubber None Scrubber10 SCR SCR SCR SCR NoneScrubber Scrubber ScrubberCharles R. Lowman 1 None None None None None Scrubber None ScrubberORISID=56 2 & 3 SCR SCR SCR SCRScrubber Scrubber Scrubber ScrubberGA Bowen 1BLR SCR SCR SCR SCRNone Scrubber ScrubberORISID=703 2BLR SCR SCR SCR SCRNone Scrubber Scrubber3BLR SCR SCR SCR SCRScrubber Scrubber Scrubber4BLR SCR SCR SCR SCRIPM hadretrofitscrubbersbut littleemissionreductionsScrubber Scrubber ScrubberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.100Table 2.1-1 (continued)NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateGA Wansley 1 SCR SCR SCR SCRScrubber Scrubber ScrubberORISID=6052 2 SCR SCR SCR SCRIPM hadretrofitscrubbersbut littleemissionreductionsNone Scrubber ScrubberKraft1, 2 None None NoneNone None None None NoneORISID=733 3 None None SCRNone None None None NoneMcIntoshORISID=61241 None None SCR NoneNone None None NoneYates 1 None None None NoneScrubber Scrubber Scrubber ScrubberORISID=728 2, 3 None None NoneNone None None None None4 – 7 None None SCR SCR None None Scrubber NoneHammond 1 None None SCR SCRNone 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 Scrubber Scrubber Scrubber ScrubberKY Ghent 1 None SCR SCR SCR Scrubber Scrubber Scrubber ScrubberORISID=1356 2 None None SCR SCR None Scrubber Scrubber Scrubber3, 4 None SCR SCR SCR None Scrubber 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 Scrubber Scrubber Scrubber ScrubberDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.101Table 2.1-1 (continued)NOxEmission ControlsSO2Emission ControlsStatePlant Name and IDUnit2009201820092018IPMStateIPMStateIPMStateIPMStateKY E W Brown 1 None None None None None Scrubber None ScrubberORISID=1355 2 None None SCR SCR None Scrubber Scrubber Scrubber3 None None SCR SCR None Scrubber Scrubber ScrubberSC Jeffries 3 SCR None SCR None None None None NoneORISID=3319 4 None None NoneNone None None None NoneWateree WAT1 SCR SCR SCR SCR None Scrubber None ScrubberORISID=3297 WAT2 SCR SCR SCR SCR None Scrubber Scrubber ScrubberCanadys CAN1 None None NoneNone None None None NoneORISID=3280 CAN2 None None NoneNone None None None NoneCAN3 None None None NoneNone Scrubber None ScrubberRainey CT1A None SCR None SCR None None None NoneORISID=7834 CT1B None SCR NoneSCR None None None NoneTN Kingston1 – 8 SCR SCR SCRSCR 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 SCR Scrubber None Scrubber ScrubberORISID=3946Kammer1 -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 (ORIS10333) is a duplicate entry. This is point 18 in Florida Crushed Stone (12-053-0530021). Removed IPM emissions for Central Power and Lime. Cedar Bay Generating ORISID=10672 GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this facility and the cogeneration facility should not grow faster than the underlying industry. Cedar Bay is connected to Stone Container (12-031-0310067). Replaced IPM emissions with 2002 emissions for Cedar Bay (12-031-0310337) times the growth factors for Stone Container. Indiantown Cogeneration ORISID=50976 GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this facility and the cogeneration facility should not grow faster than the underlying industry. Indiantown is connected to Louis Dreyfus Citrus (12-085- 0850002). Replaced IPM emissions with 2002 emissions for Indiantown (12-085-0850102) times the growth factors for Louis Drefus Citrus.

GA Bowen
ORISID=703 1BLR 2BLR 3BLR 4BLR IPM indicated retrofit scrubbers on all 4 units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect scrubbers on 3BLR and 4BLR by 2009. Wansley
ORISID=6052 1, 2 IPM indicated retrofit scrubbers on both units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect one scrubber on Unit 1 by 2009.

Riverside
ORISID=734 4 All of plant Riverside was retired from service June 1, 2005; emissions set to zero in 2009 and 2018.

McIntosh
ORISID=727 CT10A CT10B CT11A CT11B The McIntosh Combined 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 emission 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 results with emission projections from Duke Power’s NC Clean Air Compliance Plan for 2006. Used IPM results for 2018

Asheville (2706) Cape Fear (2708) Lee (2709) Mayo (6250) Roxboro (2712) Sutton (2713) Weatherspoon (2716) All Replaced all IPM 2009 results with emission projections from Progress Energy’s NC Clean Smokestacks Act Calendar Year 2005 Progress Report. Used IPM results for 2018

Dwayne Collier Battle Cogeneration Facility
ORISID=10384 GEN1
GEN2 Dwayne Collier Battle is a duplicate entry. This is 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; Upgrade ESP from 0.38 to 0.03 lb/mmBTU by Dec. 31, 2008 Unit 2: Replace scrubber with one that meets 95 percent removal efficiency from 45 percent by Dec. 31, 2008; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2008 Unit 3: Upgrade scrubber from 70 percent to 90 percent removal efficiency by Dec. 31, 2012; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2012 Unit 4: Upgrade scrubber from 70 percent to 90 percent removal efficiency by Dec. 31, 2007; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2007
Recalculated SO 2 and PM emissions based on upgrade in control efficiencies.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.1-2 (continued)

State Plant Name and ID Unit Nature of Update/Correction

SC Dolphus Grainger
ORISID=3317 1, 2 Unit 1: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 95 percent based on change in allowable emission rate
Unit 2: Install low NO x burners that meet 0.46 lb/mmBTU from 0.9 by May 1, 2004. Recalculated NO x emissions using 0.46/lbs/mmBtu and IPM heat input Unit 2: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 95 percent based on change in allowable emission rate

SC Jeffries
ORISID=3319 3, 4 Unit 3: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 94.44 percent based on change in allowable emission rate Unit 4: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 94.44 percent based on change in allowable emission rate

W S Lee
ORISID=3264 1, 2 IPM does not indicate that these units are installing SOFA NO x control technology by April 30, 2006 to meet 0.27 lb/mmBTU, down from 0.45 lb/mmBtu. Calculated NO x emissions using IPM heat input and 0.27 lbs/mmBtu

Generic Unit
ORISID=900545 All All predictions for generic units appear reasonable with the exception of Plant ID ORIS900545 Point ID GSC45 which was modeled in Georgetown Count y. It will be very difficult to add new generation this close to the Cape Romain Class I area. Santee Cooper has no plans for future generation in Georgetown County, but does have plans for new future generation in Florence County. This unit was moved to coordinates specified in Florence County.

VA AEP Clinch River
ORISID=3775 1, 2, 3 Used IPM results for 2009; replaced all 2018 IPM results with VADEQ’s growth and control estimates (no SCR or scrubbers). AEP Glen Lyn
ORISID=3776 51, 52, 6 Used 2009/2018 IPM results for units 51 and 52; used 2009 IPM for unit 6; replaced 2018 IPM for unit 6 with VADEQ’s growth and control estimates (nor SCR or scrubber).

Dominion Clover
ORISID=7213 1, 2 Used 2009/2018 IPM results.

Dominion Bremo
ORISID=3796 3, 4 Used 2009/2018 IPM results.

Dominion Chesterfield
ORISID=3797 3, 4, 5, 6 Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates.

Dominion Yorktown
ORISID=3809 1, 2, 3 Units 1, 2: Used 2009/2018 IPM results for NOx and used VADEQ’s growth and control estimates for SO2. Unit 3: IPM predicts zero heat input for this 880 MW #6 oil fired unit. Dominion plans to continue to operate Unit 3. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates.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 sp ecified that the permitted emission rates should be used, which equates to 3,066 tons in 2009 and 2018.
Unit 5: IPM had zero heat input. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Unit 6: Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates.

Potomac River
ORISID=3788 1 - 5 Units 1&2: IPM retired these units. Mirant has no plans at this time to retire any units. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Units 3, 4, 5: Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. WV Albright
ORISID=3942 1, 2 IPM predicted early retirement for these units. AEP indicated there are no plans for early retirement. For 2009, used 2002 actual emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement.

Rivesville
ORISID=3945 7, 8 IPM predicted early retirement for these units. AEP indicated there are no plans for early retirement. For 2009, used 2002 actual emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement.

Willow Island
ORISID=3946 1, 2 Unit 1: IPM predicted early retirement for these units. AEP indicated there are no plans for early retirement. For 2009, used 2002 emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement. Unit 2: IPM predicted SCR and scrubber for 2009. These controls will not be in place by 2009.

North Branch Power Station
ORISID=7537 1A, 1B SO 2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. Used SO 2 Permit Rate of 0.678 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 2018

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

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

### Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS

BaseG Base F4
IPM Based Base G
IPM Based

with S/L Adjustments Base F4
IPM Based Base G
IPM Based

with S/L Adjustments

AL 447,828 340,194 378,052 190,099 305,262

FL 453,631 195,790 186,055 141,551 132,177

GA 514,952 534,469 417,449 180,178 230,856

KY 484,057 371,944 290,193 229,603 226,062

MS 67,429 85,629 76,579 27,230 15,146

NC 477,990 205,018 242,286 110,382 108,492

SC 206,399 171,206 124,608 121,694 93,274

TN 334,151 255,400 255,410 112,662 112,672

VA 241,204 169,714 225,653 90,935 140,233

WV 516,084 226,127 277,489 124,466 115,324
Total 3,743,725 2,555,491 2,473,774 1,328,800 1,479,498

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.



### Table 2.1-4 EGU Point Source NO x 

### Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS

BaseG Base F4
IPM Based Base G
IPM Based

with S/L Adjustments Base F4
IPM Based Base G
IPM Based

with S/L Adjustments

AL 161,038 70,852 82,305 42,769 64,358

FL 257,677 89,610 86,165 77,080 73,125

GA 147,517 97,146 98,497 58,095 75,717

KY 198,817 107,890 92,021 64,378 64,378

MS 43,135 11,475 36,011 8,945 10,271

NC 151,854 66,431 66,522 60,914 62,353

SC 88,241 43,817 46,915 48,346 51,456

TN 157,307 41,767 66,405 31,725 31,715

VA 86,886 63,220 66,219 49,420 75,594

WV 230,977 63,510 86,328 51,241 51,241
Total 1,523,449 655,718 727,388 492,913 560,208

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

2002 2009 2018

State 2002 VISTAS

BaseG Base F4
IPM Based Base G
IPM Based

with S/L Adjustments Base F4
IPM Based Base G
IPM Based

with S/L Adjustments

AL 2,295 2,441 2,473 2,952 2,952

FL 2,524 1,867 1,910 2,324 2,376

GA 1,244 1,571 2,314 1,903 2,841

KY 1,487 1,369 1,369 1,426 1,426

MS 648 406 404 1,124 1,114

NC 988 974 954 1,272 1,345

SC 470 660 660 906 906

TN 926 932 932 977 976

VA 754 685 778 903 996

WV 1,180 1,342 1,361 1,387 1,387
Total 12,516 12,247 13,155 15,174 16,319

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.


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

2002 2009 2018

State 2002 VISTAS

BaseG Base F4
IPM Based Base G
IPM Based

with S/L Adjustments Base F4
IPM Based Base G
IPM Based

with S/L Adjustments

AL 11,279 14,948 14,986 24,342 24,342

FL 57,113 45,391 35,928 63,673 53,772

GA 9,712 20,066 23,721 32,744 44,476

KY 12,619 15,812 15,812 17,144 17,144

MS 5,303 5,078 5,051 15,364 15,282

NC 13,885 15,141 14,942 19,612 20,223

SC 6,990 11,135 11,135 14,786 14,786

TN 7,084 7,221 7,213 7,733 7,723

VA 6,892 11,869 12,509 14,755 15,420

WV 10,341 11,328 11,493 11,961 11,961
Total 141,218 157,989 152,790 222,114 225,129

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

### -PRI Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS

BaseG Base F4
IPM Based Base G
IPM Based

with S/L Adjustments Base F4
IPM Based Base G
IPM Based

with S/L Adjustments

AL 7,646 6,959 6,969 7,822 7,822

FL 21,387 9,384 9,007 10,310 9,953

GA 11,224 17,088 17,891 18,329 20,909

KY 4,701 6,463 6,463 6,694 6,694

MS 1,633 5,487 4,957 7,624 7,187

NC 22,754 22,888 22,152 33,742 37,376

SC 21,400 28,650 19,395 37,864 28,826

TN 14,640 15,608 15,608 15,941 15,941

VA 3,960 4,479 5,508 12,744 13,775

WV 4,573 5,471 5,657 6,349 6,349
Total 113,918 122,477 113,607 157,419 154,832

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.



### Table 2.1-8 EGU Point Source PM 2.5 

### -PRI Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS

BaseG Base F4
IPM Based Base G
IPM Based

with S/L Adjustments Base F4
IPM Based Base G
IPM Based

with S/L Adjustments

AL 4,113 3,916 3,921 4,768 4,768

FL 15,643 6,250 5,910 7,171 6,843

GA 4,939 10,104 10,907 11,403 13,983

KY 2,802 4,279 4,279 4,434 4,434

MS 1,138 5,310 4,777 7,469 7,033

NC 16,498 16,514 15,949 26,966 29,792

SC 17,154 23,366 16,042 32,180 25,032

TN 12,166 13,092 13,092 13,387 13,387

VA 2,606 3,194 4,067 11,101 11,976

WV 2,210 2,850 2,940 3,648 3,648
Total 79,269 88,875 81,884 122,527 120,896

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

### Emission Comparison for 2002/2009/2018.

2002 2009 2018

State 2002 VISTAS

BaseG Base F4
IPM Based Base G
IPM Based

with S/L Adjustments Base F4
IPM Based Base G
IPM Based

with S/L Adjustments

AL 317 359 359 1,072 1,072

FL 234 1,659 1,631 3,004 2,976

GA 83 686 686 1,677 1,677

KY 326 400 400 476 476

MS 190 333 333 827 827

NC 54 423 445 691 663

SC 142 343 343 617 617

TN 204 227 227 241 241

VA 127 632 694 558 622

WV 121 330 330 180 180

Total 1,798 5,392 5,448 9,343 9,351

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.1.2 Non-EGU Emission Projections
The general approach for assembling future year data was to use growth and control data consistent with the data used in EPA’s Clean Air Interstate Rule analyses, supplement these data with available stakeholder input, and provide the results for stakeholder review to ensure credibility. We used the revised 2002 VISTAS base year inventory, based on the 2002 CERR submittals as the starting point for the non-EGU pr ojection inventories. As described in Section 2.1.1.4, we split the point source inventory into EGU and non-EGU components. MACTEC performed the following activities to apply growth and control factors to the 2002 inventory to generate the 2009 and 2018 projection inventories:

• 

### Obtained, reviewed, and applied the most current growth factors developed by EPA, based on forecasts from an updated Regional Economic Models, Inc. (REMI) model (version 5.5) and the latest Annual Energy Outlook published by the Department of Energy (DOE);

• 

### Obtained, reviewed, and applied any State-sp ecific or sector-specific growth factors submitted by stakeholders;

• 

### Obtained and incorporated information regarding sources that have shut down after 2002 and set the emissions to zero in the projection inventories;

• 

### Obtained, reviewed, and applied control assumptions for programs “on-the-books” and “on-the-way”;

• 

### Provided data files in NIF3.0 format and emission summaries in EXCEL format for review and comment; and

• 

### Updated the database with corrections or new information from S/L agencies based on their review of the Base F 2009/2018 inventories.
The following sections discuss each of these steps.
2.1.2.1 Growth assumptions for non-EGU sources
This section describes the growth factor data used in developing the Base F inventory for 2009 and 2018, as well as the changes to the growth factor data made for the Base G inventory.

The growth factor data used in developing the Base F inventory were consistent with EPA’s analyses for the CAIR rulemaking. These growth factors are fully documented in the reports
entitled Development of Growth Factors for Future Year Modeling Inventories (dated April 30, 2004) and CAIR Emission Inventory Overview (dated July 23, 2004). Three sources of data were used in developing the growth factors for the Base F inventory:

• 

### State-specific growth rates from the Regional Economic Model, Inc. (REMI) Policy Insight ® 

### model, version 5.5 (being used in the development of the EGAS Version 5.0). The REMI socioeconomic data (output by i ndustry 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) are available by 4-digit SIC code at the
State level.

• 

### Energy consumption data from the DOE’s Energy Information Administration’s (EIA) Annual Energy Outlook 2004, with Projections through 2025 for use in generating growth factors for non-EGU fuel combustion sources. These data include regional or national fuel-use forecast data that were mapped to specific SCCs for the non-EGU fuel use sectors (e.g., commercial coal, industrial natural gas). Growth factors for the residential natural gas combustion category, for example, are based on residential natural gas consumption forecasts that are reported at the Census division level. These Census divisions represent a group of States (e.g., the South Atlantic division includes eight
southeastern States and the District of Co lumbia). Although one would expect different growth rates in each of these States due to unique demographic and socioeconomic trends, EIA’s projects all States within each division using the same growth rate.

• 

### Specific changes for sectors (e.g., plastics, synthetic rubber, carbon black, cement manufacturing, primary metals, fabricated metals, motor vehicles and equipment) where the REMI-based rates were unrealistic or highly uncertain. Growth projections for these sectors were based on industry group forecasts, Bureau of Labor Statistics (BLS) projections and Bureau of Economic Analys is (BEA) historical growth from 1987-2002.

In addition to the growth data described above, we received two sets of growth projections from
VISTAS stakeholders.

The American Forest and Paper Association (AF&PA) supplied growth projections for the pulp and paper sector, which were applied to SIC 26xx Paper and Allied Products. The AF&PA projection factors are for the U.S. industry and apply to all States equally. The numbers come from the 15-year forecast for world pulp and recovered paper prepared by Resource Information Systems Inc. (RISI).

AF&PA Growth Factor SIC Code Sector 2002 to 2009 2002 to 2018 2611 Pulp Mills 1.067 1.169
2621 Paper Mills 1.067 1.169
2631 Paperboard Mills 1.067 1.169



### For both the Base F and Base G inventories, we used the above AF&PA growth factors by SIC instead of the factors obtained from EPA’s CAIR analysis.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 supplied recent projections for three key sectors in North Carolina where declining production was anticipated – SIC 22xx Textile Mill Products, 23xx Apparel and Other Fabrics, and 25xx Furniture and Fixtures. For the Base G inventory, NCDENR decided to use a growth factor of 1.0 for these SIC codes for both 2009 and 2018. Although NCDENR has data that shows a steady decline in these industries in NC, NCDENR
wanted to maintain the emission levels at 2002 levels so the future emission reduction credits were available in the event that they are needed for nonattainment areas. The specific growth
factors for these industrial sectors in North Carolina were:

NCDENR Growth Factors for Specific Industrial Sectors

2009 2018 SIC Code Industrial Sector Base F Base G Base F Base G

22xx Textile Mill Products 0.6239 1.00 0.2792 1.00

23xx Apparel and Other Fabrics 0.5867 1.00 0.2247 1.00

25xx Furniture and Fixtures 0.8970 1.00 0.7647 1.00



### For the Base G inventory, we made one additional change to the growth factors. The Base F inventory relied on DOE’s AEO2004 forecasts for projecting emissions for fuel-burning SCCs (applies mainly to ICI boilers 1-02-xxx-xx and 1-03-xxx-xx, as well as in-process fuel use). We replaced the AEO2004 data with the more recent AEO2006 forecasts (released in February 2006) to reflect changes in the energy market and to improve the emissions growth factors produced. We obtained the corresponding AEO2006 projection tables from DOE’s web site
located at http://www.eia.doe.gov/oiaf/aeo/supplement/supref.html 

### . We developed tables comparing the growth factors based on AEO2004 and AEO2006. These comparison tables were reviewed by the S/L agencies. Based on this review, VISTAS decided to use the AEO2006 growth factors for fuel burning SCCs.

We used the EPA’s EGAS model and updated the corresponding AEO2006 projection tables to create growth factors by SCC. We applied the updated growth factors to 2002 actual emissions and replaced the 2009 and 2018 emissions in NIF EM tables for the affected SCCs.

2.1.2.2 Source Shutdowns
A few states indicated that significant source shutdowns have occurred since 2002 and that
emissions from these sources should not be included in the future year inventories. These sources
are identified in Table 2.1-10.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 project ed 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 (now LaFarge) facility in downtown Atlanta will likely shut down before 2009. The facility has two cement k ilns, 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 fac ility will be completely 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 th e 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 fac ility – Celanese Acetate (45-091-2440-0010) in York County. TN Davidson County (Nashville) indi cated that significant source shut downs have occurred since data were submitted for the 2002 CERR. Source num ber 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 th e 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 both the 2009 and 2018 non-EGU point inventory. Two control scenarios were developed: on-the-books (OTB) controls and on-the-way (OTW) controls. The OTB control scenario accounts for post-2002 emission reductions from promulgated federal, State, local, and site-specific control programs. The OTW control scenario accounts for proposed (but not final) control programs that are reas onably anticipated to result in post-2002 emission reductions. The methodologies used to account for the emission reductions associated with these emission control programs are discussed in the following sections.

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

On-the-Books (Cut-off of July 1, 2004 for Base 1 adoption)

• Atlanta / Northern Kentucky / Birmingham 1-hr SIPs

• Industrial Boiler/Process Heater/RICE MACT

• 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-EGUs, 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 Report. 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 inventories. Since the NO x 

### SIP call allowances are given in terms of tons per ozone season (5 month period from May to September), we calculated annual emissions by multiplying the 5-month allowances by a factor of 12 divided by 5.

2.1.2.3.2 OTB - Industrial Boiler/Process Heater MACT


### EPA anticipates reductions in PM and SO 2 

### as a result of the Industrial Boiler/Process Heater
MACT standard. The methods used to account for these reductions are the same as those used for the CAIR analysis. Reductions were included for existing units firing solid fuel (coal, wood, waste, biomass) which had a design capacity greater than 10 mmBtu/hr. EPA prepared a list of SCCs for solid fuel industrial and commercial/ institutional boilers and process heaters. We identified boilers greater than 10 mmBtu/hr using either the boiler capacity from the VISTAS 2002 inventory, or if the boiler capacity was missing, a default capacity based on a methodology developed by EPA for assigning default capacities based on SCC. The applied MACT control efficiencies were 4 percent for SO 2 

### and 40 for percent for PM 10 

### and PM2.5 to account for the cobenefit from installation of acid gas scrubbers and other control equipment to reduce HAPs.

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


### Maximum achievable control technology (MACT) requirements were also applied, as documented in the report entitled Control Packet Development and Data Sources, dated July 14, 2004. The point source MACTs and associated emission reductions were designed from Federal Register (FR) notices and discussions with 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 Initiative. The refineries are: (1) the Chevron refinery in Pascagoula, MS; (2) the Ergon refinery in Vicksburg, MS; and (3) the Ergon refinery in Newell, WV.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 Chevron refineries in Richmond and El Segundo, CA; Pascagoula, MS; Salt Lake City, UT; and Kapolei, HI. Actions required under the Consent
Decree will reduce annual emissions of NO x 

### by 3,300 tons and SO 2 

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

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

### controls that meet at least an SNCR level of control. The refineries are to eliminate fuel oil burning in any combustion unit. The consent decree also requires reductions of
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 information 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 NEI). 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 Ergon-West Virginia refinery in Newell, WV; and the Ergon Refining facility in Vicksburg, MS. Th e consent 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 for 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 April 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 affected units using the same methodology as was used by EPA in the proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than 1 ton per day during 2002). The final rule reflects a control level of 82 percent for natural gas-fired IC engines and 90 percent for diesel or dual fuel cat egories. As shown later in Table 2.1-12, several S/L agencies provided move specific information on the anticipated controls at the compressor stations. This information was used in the Base G inventory instead of the default approach used by EPA in the proposed Phase II rule.

2.1.2.3.7 Clean Air Interstate Rule


### CAIR does not require or assume additional emission reductions from non-EGU boilers and
turbines.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 projection inventory data set to ensure that all corrections provided by the S/L agencies and stakeholders were correctly incorporated into the
S/L inventories and that there were no remaini ng QA issues that could be addressed during the duration of the project. After exporting the invent ory to ASCII text files in NIF 3.0, the EPA QA program was run on the ASCII files and the QA output was reviewed to verify that all QA issues
that could be addressed were resolved

Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, and to ensure that a full and complete inventory was developed for VISTAS. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the point source component of the VISTAS revised 2002 base year inventory:

1. Facility level emission summaries were prepared and evaluated to ensure that emissions were consistent and reasonable. The summaries included base year 2002 emissions, 2009/2018 projected emissions accounting only for growth, 2009/2018 projected emissions accounting for both gr owth and emission reductions from OTB and OTW controls. 2. State-level non-EGU comparisons (by pollutant) were developed for the base year 2002 emissions, 2009/2018 projected emissions accounting only for growth, 2009/2018 projected emissions accounting for both growth and emission reductions from OTB and OTW controls. 3. Data product summaries and raw NIF 3.0 data files were provided to the VISTAS Emission Inventory Technical Advisor and to the Point Source, EGU, and non-EGU Special Interest Work Group representatives for review and comment. Changes based on these comments were reviewed and approved by the S/L point source contact prior to implementing the changes in the files. 4. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from Base F1 to Base F2. 2.1.2.5 Additional Base G Updates and Corrections
Table 2.1-12 summarizes the updates and corrections to the Base F inventory that were requested by S/L agencies and incorporated into the Base G 2009/2018 inventories.

2.1.2.6 Summary of Revised 2009/2018 non-EGU Point Source Inventories
Tables 2.1-13 through 2.1-19 summarize th e revised 2009/2018 non-EGU point source inventories. The “growth only” column does not include the shutdowns (section 2.1.2.2) or control factors (section 2.1.2.3), only the growth factors described in section 2.1.2.1.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 applicati on 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 locati on coordinates at the stack level th at was used to replace the location coordinated in the ER file. There are several sources that have updated their emissions from their BART eligible units. most of these changes were for fairly small (<50 tpy) sources. NC Made several changes to Base F inventory to correct the following errors: 1. Corrected emissions at Hooker Furniture (Site ID: 37-081-3708100910), release point G-29, to use the corrected values in 2002 and carry those same numbers through to 2009 and 2018 since NCDENR assumes zero growth for furniture industry. 2. Identified many stack parameters in the ER file that were unrealistic. Several have zero for height, diameter, gas velocity, and flow rate. NC used the procedures outlined in Section 8 of the document ""National Emission Inventory QA and Augmentation Report" to correct unrealistic stack parameters. 3. Identified truncated latitude and longitude valu es 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 Apr il 2006 using the revised pollutant codes. These changes were reflected in the Base G 2009/2018 emission inventory. Specified that the Bowater In c. facility (45-091-2440-0005) in York County conducted an expansion in 2003/2004 and plans a future expansion. SC pr ovided 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 Bowater facility (47-107-0012) based on the facility’s updated 2002 emission inventory update. Replaced 2009/2018 data from Ham ilton County, Tennessee, using data from Hamilton County’s CERR submittal as contained in EPA’s 2002 NEI (in Base F, the inventory for Hamilton County was based on the draft VISTAS 2002 inventory, which in turn was based on the 1999 NEI); applied growth and control factors to revised 2002 inventor y to generate emission projections for 2009/2018. Updated 2009/2018 emissions for PCS Nitrogen Fertilizer LP (Site ID: 47-157-00146) based on the facility’s updated 2002 emi ssion inventory update. The 2002 NEI correctly reports 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- 00011, 51-137-00027, 51-143-00120) 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 a nd 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 emi ssion 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 Emission Comparison for 2002/2009/2018.

2002 2009 2018

State Base G Base F4 Base G Base F4 Base G

AL 47,037 46,660 46,644 54,268 54,291

FL 38,471 36,675 36,880 42,787 42,811

GA 33,709 34,082 34,116 40,267 40,282

KY 44,834 47,648 47,785 55,564 55,861

MS 43,204 37,921 37,747 45,769 45,338

NC 61,182 70,464 61,925 76,027 70,875

SC 38,458 38,273 35,665 44,545 43,656

TN 84,328 89,380 74,089 111,608 93,266

VA 43,152 43,620 43,726 53,065 53,186

WV 14,595 14,012 13,810 16,632 16,565
Total 448,970 458,735 432,387 540,532 516,131

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.


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

2002 2009 2018

State Base G Base F4 Base G Base F4 Base G

AL 174,271 176,899 180,369 194,280 201,794

FL 81,933 83,937 87,037 96,642 96,819

GA 130,850 147,362 147,427 168,570 167,904

KY 109,936 121,727 122,024 139,121 139,437

MS 54,568 58,023 57,748 67,764 66,858

NC 50,576 53,955 53,744 61,127 62,197

SC 56,315 62,144 60,473 71,318 68,988

TN 115,264 123,844 119,665 146,407 140,942

VA 63,796 67,046 68,346 74,364 76,998

WV 89,879 100,248 100,045 119,318 119,332
Total 927,388 995,185 996,878 1,138,911 1,141,269

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.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 PM25-PRI Emission Comparison for 2002/2009/2018.

2002 2009 2018

State Base G Base F4 Base G Base F4 Base G

AL 19,178 19,256 19,230 22,628 22,598

FL 30,504 33,387 33,946 39,436 39,430

GA 17,462 19,361 18,982 22,882 22,416

KY 11,372 11,680 11,686 13,734 13,739

MS 9,906 9,144 9,199 10,768 10,739

NC 10,500 11,192 10,458 11,927 11,825

SC 10,245 13,101 9,390 14,947 11,086

TN 27,807 29,302 27,577 35,750 33,532

VA 10,165 9,980 9,988 11,604 11,594

WV 13,313 13,364 12,769 16,474 16,516
Total 160,452 169,767 163,225 200,150 193,475

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx.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 approaches 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 St ates (via the Stationary Area Source SIWG) to obtain any State specific growth factors and/or future controls from the States to use in developing the projections.

3. MACTEC then back calculated uncontrolled emissions from the Base F 2002 base year inventory based on existing controls reported in the 2002 Base F base year inventory.

4. Controls (including control efficiency, rule effectiveness and rule penetration) provided by the States or originally developed for use in estimating projected emissions for U.S. EPA’s Heavy Duty Diesel (HDD) rulemaking 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 then used to calculate controlled emissions. State submitted controls had precedence over the U.S. EPA developed controls.

5. Growth factors supplied from the States or the U.S. EPA’s CAIR emission projections were then applied to project the controlled emissions to the appropriate year. In some cases EGAS Version 5 growth factors were used if no growth factor was available from either the States or the CAIR growth factor files. The use of EGAS Version 5 growth factors was on a case-by-case basis wherever State-supplied or CAIR factors were not available for SCCs found in the 2002 Base F inventory. Use of the EGAS factors was necessitated due to the CERR submittals used in constructing the Base F 2002 inventory. Use of the CERR data resulted in SCCs that were not found in the CAIR inventory and if no State-supplied growth factor was provided re quired the use of an EGAS growth factor.

6. MACTEC then provided the final draft Ba se F projection inventory for review and comment by the VISTAS States.

For Base F stationary area sources, no State-supplied growth or control factors were provided. Thus for all of the sources in this sector of the inventory, growth and controls for Base F were applied based on controls initially identified for the CAIR and growth factors identified for the CAIR projections.

For the Base G projections, the Base G 2002 base year inventory (see section 1.2.3) was used as a starting point. States provided some updated future controls but growth factors used were identical to those used for Base F. The revised controls for Base G were largely for new sources added as part of the 2002 Base F comments. The calculation of Base G projections was identical to the six steps outlined above with the exception of revisions made to prescribed fire for 2009 and 2018 and for the State of North Carolina. North Carolina provided 2009 and 2018 updated emission files used to update the emissions for each year for several source categories. However not all sources in the inventory were included in these NC updates. As a consequence, the final Base G 2009 and 2018 inventory for NC included 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 categories that had not initially been included in the Base F inventory. These growth factors were obtained from EGAS 5.0. Finally updates to growth factors from EGAS 5.0 were made for fuel fired emission sources. The updated growth factors reflected the most recent data from the Department of Energy’s Annual Energy Outlook (AEO). These data were used to reflect changes in energy efficiency resulting from new or updated fuel firing technologies.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 MACTEC for the HDD rulemaking were controls for the years 2007, 2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, control values for intermediate years were prepared using a strai ght line interpolation of control level between 2007 and 2020. The equation used to calculate the control level was as follows:

CE = (((2020 CE – 2007 CE)/13)*YRS) + 2007 CE

Where:

CE = Control Efficiency for either 2009 or 2018

2020 CE = HDD Control Efficiency value for 2020

2007 CE = HDD Control Efficiency value for 2007

13 = Number of years between 2020 and 2007

YRS = Number of years beyond 2007 to VISTAS Projection year

For 2009 the value of YRS would be two (2) and for 2018 the value would be eleven (11). Control efficiency values were determined for VOC, CO and PM. Rule penetration values for each year in the HDD controls tables obtained by MACTEC were always 100 percent so those values were maintained for the VISTAS projections.

Prior to performing the linear interpolation of the controls, MACTEC evaluated controls from the CAIR projections (NOTE: Initially the controls came from the IAQTR projections, however the controls used in CAIR were virtually identical to those in IAQTR). Those controls appeared to be identical to those used for the HDD rulemaking. In addition, MACTEC received some additional information on some controls for area source solvents (email from Jim Wilson, E.H. Pechan and Associates, Inc. to Gregory Stella , VISTAS Emission Inventory Technical Advisor, 3/5/04) that were used to check against the controls in the HDD rulemaking files. Where those controls proved to be more stringent than the HDD values, MACTEC updated the control file with those values (which were then used in the interpolation to develop 2009 and 2018 values). Finally, for VOC the HDD controls were initially provided at the State-county-SCC level. However, upon direction from the VISTAS Emi ssion Inventory Technical advisor, the VOC controls were consolidated at the SCC level and applied across all counties within the VISTAS region (email from Gregory Stella, Alpine Geophysics, 3/3/2004) to ensure that no controls were missed due to changes in county FIPS codes and/or SCC designations between the time the HDD controls were developed and 2002.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 

### RPVOC REVOC CEVOC xVOC 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 applied 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 supplied by U.S. EPA related to the CAIR growth factors indicated that growth values for those cat egories were derived from U.S. Department of Energy (DOE) and were felt to account for changes in growth and projected energy efficiency. For the Base G inventory, these energy efficiency factors were re-instituted and used in conjunction with EGAS 5.0 growth factors in a manner identical to that used for the pre-Base F inventories. The energy efficiency factors were derived from U.S. DOE’s Annual Energy Outlook report.

One significant difference between the Base F and Base G control factors was for counties and independent cities in northern Virginia. Several counties and independent cities in northern Virginia are subject to Ozone Transport Commission rules. For these counties and independent cities, controls for portable fuel containers, mobile equipment repair/refinishing, consumer products, solvent metal cleaning, and the architectural and industrial maintenance rules were added. The counties/independent cities (FIPS code) included in the changes for Base G were: Alexandria City (51510), Arlington (51013) , Fairfax City (51600), Fairfax (51059), Falls Church City (51610), Fredericksburg City (51630), Loudoun (51107), Manassas City (51683), Manassas Park City (51685), Prince William County (51153), Spotsylvania (51177), and Stafford (51179). Not all OTC rules applied to all counties/cities.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 Base F and Base G 2009 and 2018 inventories were obtained from the U.S. EPA and are linear interpolations of the growth factors used for the Clean Air Interstate Rule (CAIR) projections. The 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 Microsoft ExcelTM to calculate 2002, 2009 and 2018 values from the 2001, 2010 and 2015 values. The TREND function provides a linear interpolation of intermediate values from a known series of data points (in this case the 2001, 2010 and 2015 values) based on the equation for a straight line. These values were calculated at the State and SCC level with the exception of paved road emissions (SCC = 2294000000). The growth factors for paved roads were available in the CAIR data set at the State, county and SCC level so they were applied at that level.

Prior to utilizing the growth factors from the CAIR projections, MACTEC confirmed that all SCCs found in the VISTAS 2002 base year inventory were in the CAIR file (for Base F the starting point was the version 3.1 2002 base year inventory, for Base G the starting point was the Base F 2002 base year inventory). Some SCCs we re not found in the CAIR file. For those SCCs, the growth factors used were derived in one of five ways. First where possible, they were taken from a beta version of EGAS 5.0. In other cases, the growth factor was set to one (i.e., no growth). In other cases, a similar SCC that had a CAIR growth factor was used. In a few cases a growth factor based on an average CAIR growth at the 6 digit SCC level was calculated. Finally a number of records used population as the growth surrogate. For the Base G inventory, CAIR growth factors for fuel fired area sources were replaced with EGAS 5.0 growth factors (used in conjunction with AEO fuel efficiency factors). A comment field in the growth factor file was
used to mark those records that were not taken di rectly from the CAIR projection growth factors.

2.2.1.3 Differences between 2009/2018
Methodologically, there was no difference in the way that 2009 and 2018 emissions were calculated for stationary area sources. The indivi dual control and growth factors were different (due to the linear interpolation used to calculate the values) but the calculation methods were identical. This applies to both Base F and Base G.

The only exception to this is for the State of North Carolina for Base G. North Carolina provided an emissions update file used to override calculated projections for a number of area source categories. The values in these files (provided for both 2009 and 2018) were used to overwrite the calculated projected emissions in the final NIF file.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 projected emissions for agricultural 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 uncontrolled, and no future controls for these sources were identified, MACTEC projected the agricultural emissions using State-specific growth if available, otherwise the U.S. EPA’s Interstate Air Quality Transport Rule (IAQTR)/Ammonia inventory was used to devel op the growth factors used to project the revised 2002 base year inventory to 2009 or 2018. Since the IAQTR inventory was only used to construct growth factors rather than using the emissions directly, no updated growth factors were prepared from the CAIR inventory values.

4. MACTEC then provided the final draft inventory for review and comment by the
VISTAS States.

No change in the agricultural area source emission projections were made between Base F and Base G other than the removal of wild animal and human perspiration as a result of their removal from the 2002 base year file for Base G.

2.2.2.1 Control assumptions for agricultural area sources
No controls were identified either by the individual VISTAS States or in the information provided in the EPA’s IAQTR or CAIR Ammoni a inventory documents. Thus all projected emissions for agricultural area sources represent simple growth with no controls.

2.2.2.2 Growth assumptions for agricultural area sources
Growth for several agricultural area source livestock categories was developed using the actual emission estimates developed by the EPA as part of the NEI. That work included projections for the years 2002, 2010, 2015, 2020, and 2030. The actual emissions themselves were not used other than to develop growth factors since the 2002 NEI upon which the growth projections were based was prepared prior to the release of the 2002 Census of Agriculture data which was included in the CMU model (version 3.6) used to develop the Base F 2002 VISTAS base year inventory. Thus VISTAS Agricultural Sources 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 inventory and projections can be found at:

http://www.epa.gov/ttn/chief/ap42/ch09/related/nh3inventorydraft_jan2004.pdf . The actual data files for the projected emissions can be found at:

http://www.epa.gov/ttn/chief/ap42/ch09/related/nh3output01_23_04.zip

. In order to use the NEI projected emissions as growth factors, several steps were required. These steps were as follows:

1. NEI projected emissions were only available for the years 2002, 2010, 2015, 2020, and 2030, thus the first task was to calculate intermediate year emissions for 2009 and 2018. These values were calculated based on linear interpolation of the existing data.

2. Once the intermediate emissions were calculated, MACTEC developed emission ratios to provide growth factors for 2009 and 2018. Ratios of emissions were
established relative to the 2002 NEI emissions.

3. Once the growth factors were established, MACTEC then evaluated whether or not all agricultural SCCs within the revised 2002 base year inventory had corresponding growth factors. MACTEC established that not all SCCs within the base year inventory had growth factors. These SCCs fell into one of two categories:

a. SCCs that had multiple entries in the NEI but only a single SCC in the 2002 VISTAS base year inventory. The NEI was established using a process model and for some categories of animals, emissions were calculated for several aspects of the process. The CMU model version 3.6 which was the basis for the VISTAS 2002 Base F inventory did not use a process model. As a consequence a mapping of SCCs in the NEI projections and corresponding SCCs in the CMU inventory was made and for those SCCs an average growth factor was calculated from the NEI projections for use with the corresponding SCC in the CMU based 2002 Base F inventory.

b. There were also State, county, SCC trios in the 2002 VISTAS Base F inventory which had no corresponding emissions in the NEI files. For these instances, MACTEC first developed State level average growth factors from the NEI projections for use in growing these records. Even after developing State level average growth factors there were still some State/SCC pairs that did not have matching growth. For these records, MACTEC developed VISTAS regional average growth factors at the SCC level from the NEI data.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 developed, they were used to project the emissions to 2009 and 2018. Growth factors were first applied at the State, county and SCC level. Then remaining records were grown with the State/SCC specific growth factors. Finally, any remaining ungrown records were projected at the SCC level using the VISTAS regional growth factor.

For the livestock categories, the NEI emission projections only had data for beef and dairy cattle, poultry and swine. Thus for other livestock categories and for fertilizers alternative growth factors were required.

The growth factors for other livestock categories and fertilizers were obtained from growth factors used for the IAQTR projections made by the U.S. EPA. The methodology for these categories was identical to that used for dairy, beef, poultry and swine with the exception that State/SCC and VISTAS/SCC growth factors were not required for these categories since the IAQTR data contained State, county and SCC level growth factors. The IAQTR data provided growth factors for 1996, 2007, 2010, 2015 and 2020. Linear interpolation was used to develop the growth factors for the intermediate years 2009 and 2018 required for the VISTAS projections.

There were a few exceptions to the methods used for projecting agricultural sources for the VISTAS projections. These exceptions were:

1. All swine emissions for North Carolina were maintained at 2002 levels for each projection year to capture a moratorium on swine production in that State.

2. Ammonia growth factors for a few categories (mainly feedlots) were assigned to be the same as growth factors for PM emissions from the NEI projections. This assignment was made because the CMU model showed emissions from these categories but the NEI projections did not show ammonia em issions but did show PM emissions.

3. No growth factors were found for horse a nd pony emissions. These emissions were held
constant at 2002 levels.

There was no change in this method between Base F and Base G. Thus Base F and Base G agricultural emissions are the same in each 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 growth factors that may be more recent than the EPA inventory used to develop growth 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 growth factors were different (due to the linear interpolation used to calculate the values) but the calculation methods were identical. In addition
there was no difference between Base F and Base G for this category. Thus Base F and Base G agricultural emissions are the same in each inventory.

Tables 2.2-1 show the differences between Base F and Base G emissions for all area sources (including agricultural sources but excluding fires) for the 2002 base year and 2009 and 2018 by State and pollutant.

Table 2.2-1 2002 Base Year Emissions and Percentage Difference for Base F and Base G (based on actual emissions).

Actual Area 2002 - Base G State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC AL 83,958 58,318 23,444 393,588 56,654 52,253 182,674 FL 71,079 37,446 28,872 443,346 58,878 40,491 404,302 GA 108,083 80,913 36,142 695,414 103,794 57,559 299,679 KY 66,752 51,135 39,507 233,559 45,453 41,805 95,375 MS 37,905 58,721 4,200 343,377 50,401 771 131,808 NC 345,315 161,860 36,550 280,379 64,052 5,412 237,926 SC 113,714 28,166 19,332 260,858 40,291 12,900 161,000 TN 89,828 34,393 17,844 212,554 42,566 29,917 153,307 VA 155,873 43,905 51,418 237,577 43,989 105,890 174,116 WV 39,546 9,963 12,687 115,346 21,049 11,667 60,443 Base F AL 83,958 59,486 23,444 393,093 73,352 47,074 196,538 FL 105,849 44,902 29,477 446,821 81,341 40,537 439,019 GA 107,889 84,230 36,105 695,320 133,542 57,555 309,411 KY 66,752 51,097 39,507 233,559 52,765 41,805 100,174 MS 37,905 59,262 4,200 343,377 63,135 771 135,106 NC 373,585 164,467 48,730 303,492 69,663 7,096 346,060 SC 113,714 29,447 19,332 260,858 51,413 12,900 187,466 TN 89,235 35,571 17,829 211,903 49,131 29,897 161,069 VA 155,873 46,221 51,418 237,577 52,271 9,510 129,792 WV 39,546 10,779 12,687 115,346 25,850 11,667 61,490 Percentage Difference (negative values mea ns 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 mea ns 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 mea ns Base G increased from Base F) AL 6.50% 1.95% 12.96% -0.02% 24.41% -0.58% 8.86% FL 46.61% 18.96% 12.38% 0.74% 28.88% 35.51% 8.10% GA 10.69% 3.87% 2.20% 0.07% 24.54% 2.33% 6.81% KY 15.98% 0.26% 2.74% 0.19% 16.57% -4.40% -1.34% MS 39.33% 0.93% 14.28% 0.12% 22.12% 10.19% -0.51% NC 11.30% 1.79% 26.98% 8.68% 16.18% 26.45% 19.05% SC 6.91% 4.52% 8.34% 0.23% 24.16% 0.44% 18.14% TN 15.30% 4.02% 6.36% -0.15% 16.19% -2.95% 3.57% VA 5.69% 5.37% 0.90% 0.16% 19.68% -852.83% -17.76% WV 21.83% 7.15% 1.66% 0.34% 20.66% 4.46% 2.28%



### 2.2.3 Changes to Prescribed Fire for 2009/2018 Base G
Just prior to release of version 3.1 of the VIST AS inventory. several Federal agencies indicated that they had plans for increased prescribed fire burning in future years and that the “typical” fire inventory would likely not adequately capture those increases (memo from Bill Jackson and Cindy Huber, August 13, 2004). However data were not readily available to incorporate those changes up through the Base F inventory. As a consequence MACTEC worked with Federal Land Managers to acquire the data necessary to provide 2009 and 2018 specific projections for the prescribed fire component of the Base G fire inventory. The 2009 and 2018 projections developed using the method described below are being used by VISTAS as the 2009 and 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 future prescribed burning practices. The “typical” fire projection is the 2002 base prescribed fire projection.

One of the biggest issues in preparing the projection was how best to incorporate the data. Two agencies submitted data: Fish and Wildlife Service (FWS) and Forest Service (FS). FWS submitted annual acreage data by National Wildlife Refuge (NWR) and county with estimates of acres burned per day for each NWR. FS provide d 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 typical inventories. Thus MACTEC had to develop a method that could use the county level data submitted by FWS.

In addition, despite the fact that the FS submitted fire-by-fire data for the 2002 actual inventory and had mapped the projections to current burn days in the 2002 actual inventory, MACTEC could not do a simple replacement of those records with the 2009/2018 projections. This situation was created because several VISTAS States run a prescribed fire permitting program. To avoid double counting, only State data was used in those States for the 2002 actual inventory. Thus there were no Federal data in those States since the Federal data could have potentially duplicated State-supplied prescribed fire data. In VISTAS States without permit programs, the FS supplied data for 2002 was used and those records were marked in database. Thus for those States, the FS supplied 2009/2018 data could be directly substituted for the 2002 data.

The method used by MACTEC to include the FS data applied a county level data approach for FS data where a State had a prescribed fire 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 each data set is discussed below.

For the FWS data MACTEC summed the annual acres burned supplied by the FWS across all NWRs in a county. We then subtracted out 2002 acreage for that county from the FWS projected acreage annual total to avoid double counting. The remaining acreage was then multiplied by 0.8 to account for blackened acres instead of the total perimeter acres that were reported. The revised total additional FWS acreage was then added to the total county “typical” acreage to determine future acreage burned for either 2009 or 2018. MACTEC then allocated the increased acreage to current modeling days. The average daily acres burned data provided by FWS per NWR/county was used to allocate the acreage to the correct number of days required to burn all of the acres. Guidance supplied by FWS indicated that up to three times the average daily acres burned could potentially be allocated to any one day. Thus if the estimated acreage per day were 100 acres then up to 300 acres could actually be allocated to a particular day. This approach (use of up to three times the average daily acres burned) was 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 available. If that wasn’t sufficient then we used three times the average daily acres burned to allocate the acreage. We applied the highest increases to days in the database that already had the highest acreage burned since we felt those days were most likely to represent days with representative conditions for conducting prescribed burns.

The approach used by MACTEC for the FS was slightly different. For States that had permit programs, we used similar approach to the FWS county level approach. First we summed the FS data at county level, we then added that value to the typical acreage and then we allocated the acres to current modeling days. The mapping to current modeling days was performed by Bill Jackson of the USFS and provided to MACTEC. For States that do not have a prescribed fire permit program, MACTEC simply replaced the current fire-by-fire records in the database with fire-by-fire records from the FS and recalculated emissions based on fuel model and fuel loading. We also applied the same 0.8 correction for blackened acres applied to all FS supplied acreage as the supplied values represented perimeter acres.

An additional problem with developing year-speci fic prescribed fire projections was how to adequately capture the temporal profile for those fires. In the 2002 actual fire inventory, fires occur on same days as state/FLM records. In the 2002 “typical” year inventory, fire acreage increased or decreased from acreage on the same fire days as were in the 2002 actual inventory, since the acres were simply increased for each day based on a multiplier used to convert from actual to typical.

When prescribed fires acreage was added to a future year, MACTEC added acreage to individual fire days proportional to the annual increase (if acreage on a day is 10 percent of annual, add 10 percent of projected increase to that same day).

The table below shows how the FWS data for Okefenokee NWR were allocated for 2009 for Clinch County (Okefenokee NWR is located in four different counties). You can see that the total additional acres for the Clinch County portion of Okefenokee NWR was 1,956 acres. Two hundred eighty (280) acres were the estimated av erage daily acres burned for that NWR/county combination. Thus to allocate the entire 1,956 acres would require almost 7 burn days (1,956 divided by 280). However only 5 burn days were f ound for Clinch County in the 2002 actual fire database. Thus we allocated twice the average acreage to the burn day with the most acres burned in the 2002 actual fire database (since our method allowed us to increase the average daily acres burned up to three times the recommended level). Thus the first burn day received 560 acres and all others received 280 except the final day which received 276 to make the total equal to the required 1,956 acres. The table also indicates that the increased acres 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

/ 2 0 0 2

2

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/2

0 0 2

4

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# Date of Fire EventAcres Typical
FWS Add
USFS Add 

### provided increases of from 10-48 percent in the acres burned on the individual burn days and an average of approximately 14 percent for the year as a whole.

CLINCH COUNTY 3/1/2002 4/1/2002 2/1/2002 1/1/2002 11/1/2002 12/1/2002 Total Annual
Acres (typical) 3,757 2,612 1,996 1,801 616 472 11,764
Add on FWS Projection 560 280 280 280 280 276 1,956

Total 4,316 2,891 2,276 2,080 895 747 13,720

Percent Increase 14.9% 10.7% 14.0% 15.6% 45.5% 58.5% 14.3%



### The figure below shows the increases for prescribed burning in the four counties that comprise the Okefenokee NWR area (which also includes FS land). In this figure you can see the additional acreage added for the burn days from FWS and the individual day increases caused by projected increases in prescribed burning based on FS data. It should be noted that while the emissions represent 2009, all fire event dates listed are for 2002 to match up with the base year meteorology used in modeling exercises.

Table 2.2-4 shows the percentage difference between the 2009 and 2018 projections developed
for Base F and Base G. Base G includes the revised prescribed burning estimates described above. Values are calculated using Base F as the basis for change, thus negative values imply an
increase in emissions for Base G.

Figure 2.2-1 Prescribed Fire Projection for Okeefenokee NWR for 2009Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.137Table 2.2-4 Percentage Difference Between BaseF and Base G Fire Emissions by StateStateCONH3NOXPM10-PRIPM25-PRISO2VOCCONH3NOXPM10-PRIPM25-PRISO2VOC2009 Fires Base G2018 Fires Base GAL 534,873 2,050 11,901 52,851 46,543 2,681 27,502 535,658 2,054 11,918 52,927 46,608 2,686 27,539FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 88,756 4,129 51,527GA 637,177 2,229 14,243 63,973 57,116 2,914 34,710 637,177 2,229 14,243 63,973 57,116 2,914 34,710KY 31,810 143 682 3,093 2,653 187 1,497 33,296 150 714 3,237 2,777 196 1,567MS 48,160 217 1,033 4,683 4,016 283 2,266 50,037 225 1,073 4,865 4,173 294 2,355NC 96,258 433 2,065 9,359 8,027 566 4,530 111,266 501 2,387 10,819 9,279 655 5,236SC 282,307 1,039 5,899 29,153 25,955 1,359 16,045 282,307 1,039 5,899 29,153 25,955 1,359 16,045TN 17,372 78 373 1,689 1,449 102 817 18,860 85 405 1,834 1,573 111 888VA 21,130 95 453 2,054 1,762 124 994 26,923 121 578 2,618 2,245 158 1,267WV 3,949 18 85 384 329 23 186 5,013 23 108 487 418 29 2362009 Fires Base F2018 Fires Base FAL 514,120 1,957 11,456 50,833 44,812 2,559 26,526 514,120 1,957 11,456 50,833 44,812 2,559 26,526FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 88,756 4,129 51,527GA 620,342 2,153 13,882 62,336 55,712 2,815 33,918 620,342 2,153 13,882 62,336 55,712 2,815 33,918KY 56,686 110 1,460 6,667 6,310 136 3,338 56,686 110 1,460 6,667 6,310 136 3,338MS 128,471 177 3,328 14,693 13,680 100 13,625 128,471 177 3,328 14,693 13,680 100 13,625NC 200,564 324 5,005 20,488 19,491 423 12,499 200,564 324 5,005 20,488 19,491 423 12,499SC 253,005 908 5,270 26,304 23,511 1,187 14,666 253,005 908 5,270 26,304 23,511 1,187 14,666TN 78,370 46 2,232 8,875 8,730 59 5,153 78,370 46 2,232 8,875 8,730 59 5,153VA 19,159 159 978 18,160 17,361 99 912 19,159 159 978 18,160 17,361 99 912WV 32,656 12 944 3,276 3,239 16 2,184 32,656 12 944 3,276 3,239 16 2,184Percentage Difference (negative number means an increase in Base G emissions)AL -4.04% -4.77% -3.89% -3.97% -3.86% -4.77% -3.68% -4.19% -4.95% -4.03% -4.12% -4.01% -4.95% -3.82%FL 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%GA -2.71% -3.52% -2.60% -2.63% -2.52% -3.52% -2.34% -2.71% -3.52% -2.60% -2.63% -2.52% -3.52% -2.34%KY 43.88% -29.52% 53.25% 53.61% 57.96% -37.90% 55.15%41.26% -35.57% 51.07% 51.44% 56.00% -44.34% 53.06%MS 62.51% -22.07% 68.95% 68.13% 70.64% -183.85% 83.37%61.05% -26.83% 67.74% 66.89% 69.50% -194.91% 82.72%NC 52.01% -33.75% 58.74% 54.32% 58.82% -33.75% 63.76%44.52% -54.60% 52.31% 47.19% 52.40% -54.60% 58.11%SC -11.58% -14.52% -11.93% -10.83% -10.39% -14.52% -9.40%-11.58% -14.52% -11.93% -10.83% -10.39% -14.52% -9.40%TN 77.83% -69.40% 83.30% 80.97% 83.41% -74.42% 84.14%75.93% -83.92% 81.87% 79.34% 81.98% -89.36% 82.78%VA -10.29% 40.36% 53.67% 88.69% 89.85% -25.40% -9.03%-40.53% 24.00% 40.97% 85.59% 87.07% -59.79% -38.93%WV 87.91% -48.65% 91.03% 88.28% 89.83% -49.46% 91.49%84.65% -88.70% 88.61% 85.12% 87.09% -89.73% 89.20%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### 2.2.4 Quality Assurance steps
Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, to ensure that a full and complete inventory was developed for VISTAS, and to ma ke sure that projection calculations were working correctly. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on the stationary and agricultural area source components of the 2009 and revised 2018 projection inventories:

1. All final files were run through EPA’s Format and Content checking software.

2. SCC level emission summaries were prepared and evaluated to ensure that emissions were consistent and that there were no missing sources.

3. Tier comparisons (by pollutant) were developed between the 2002 base year inventory and the 2009 and 2018 projection inventories. In addition, total VISTAS pollutant summaries were prepared to compare total emissions by pollutant between versions of the inventory (e.g., between Base F and Base G).

4. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to the SIWG representatives for review and comment. Changes based on these comments were implemented in the files.

5. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.

2.3 Mobile Sources
Our general approach for assembling data was to use as much existing data from the pre-Base F preliminary projections as possible for these inventories, supplement these data with easily available stakeholder input, and provide the results for stakeholder review to ensure credibility. To develop the “base case” projections, MACTEC originally assembled data to develop two 2009 and 2018 base case inventories: 1) an inve ntory that included all “on-the-books” controlprograms and 2) an “on-the-way” inventory that included controls that were likely to be “on-theway”. For the Base F and Base G emission forecasts to the mobile source sector, “on-the-books” and “on-the-way” are defined with the same st rategies and therefore only a single projection scenario was developed for each forecast year.

To ensure consistency across evaluation years, the 2009 and 2018 base case inventories were developed, to the maximum extent practical, using methodologies identical to those employed 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 consultation with the Mobile Source Special Interest Workgroup (MSSIWG). Generally, modifications were only made to properly account for actual changes expected in the intervening period (i.e., between 2002 and 2009 and between 2002 and 2018), but the underlyi ng inventory development methodology was identical, except to the extent requested by VISTAS or the MSSIWG.

MACTEC developed a preliminary 2018 inventor y in early 2004. That inventory was designed to 1) be used for modeling sensitivity evaluations and 2) help establish the methods that would be used for the final 2018 inventory and the initial 2009 inventory. Since that work took place prior to the revision of the 2002 base year invent ory data files, MACTEC provided a review of the data and methods used to develop on-road mobile source input files for the initial 2002 base year inventory prior to developing the pr eliminary 2018 inventory. Through this review, MACTEC determined the following:

• On-road VMT. Most States provided local data for 2002 (or a neighboring year that was converted to 2002 using appropriate VMT growth surrogates such as population). Since these data were not applicable to 2018 due to intervening growth, input for2018 was solicited from the MSSIWG. At the same time we researched countyspecific growth rate data utilized for recent national rulemakings as a backstop approach to State supplied VMT projections.

• Modeling Temperatures. Actual 2002 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 type). A mix of State, local, and quasi MOBILE6 default (i.e., MOBILE6 defaults normalized to better reflect local conditions) data were used for the 2002 initial base year inventory. Forecast data were
solicited from the States.

• Diesel Sales Fractions. As with the VMT mix data, the diesel sales fraction data employed for the 2002 initial base year inventory represents a mix of State, local, and quasi MOBILE6 default data. The issues related to updating these data to 2018 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 across time. Once again, we solicited any local projections, with a fallback position that we would keep the data for 2002 and earlier model years constant for the forecast inventory, supplemented with MOBILE6 default data for 2003 and newer model years.

• State/Local Fuel Standards. For the 2002 initial base year inventory, these data were based on appropriate local requirements and updated data for 2018 was only required if changes were expected between 2002 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 reflected in the 2018 inventory in the absence of more stringent local fuel controls. Expected changes in local fuel control programs were solicited.

• Vehicle Standards. The 2002 initial base year inventory assumed NLEV applicability. This was altered to reflect Tier 2 for 2018, unless a State indicated a specific plan to adopt the California LEV II program. If so, we made the required changes to implement those plans for the preliminary 2018 inventory.

• Other Local Controls. This includes vehicle emissions inspection (i.e., I/M) programs, Stage II vapor recovery programs, anti tampering programs, etc. By nature, the assumptions used for the 2002 initial base year inventory vary across the VISTAS region, but our presumption is that these data accurately reflected each State’s situation as it existed in 2002. If a State had no plans to change program requirements between 2002 and 2018, we proposed to maintain the 2002 program descriptions without change. However, if a State planned changes, we requested information on those plans. In the final implementation of the Base F and earlier inventories, Stage II controls were exercised in the area source component of the inventory, since the units used to develop Stage II refueling estimates are different between MOBILE6 and the NONROAD models. However, in the Base G inventories, Stage II refueling was
moved to the on-road and non-road sectors.

Once the preliminary 2018 (pre-Base F) base case projection inventory data were compiled,MACTEC applied the data and methods selected and proceeded to develop the preliminary (prebase F) base case 2018 projection inventories. The resulting inventories were provided to the MSSIWG in a user-friendly format for review. After stakeholder review and comment, the final preliminary 2018 base case inventories and input files were provided to VISTAS in formats identified by the VISTAS Technical Advisor (in this case, MOBILE input files and VMT, NONROAD input files and annual inventory f iles 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 preliminary version of the 2018 base case mobile inventory input data files. These files were then updated to provide a final set of 2018 base case inventory input data files as well as a set of input files for 2009. The information below describes the updates performed on the preliminary 2018 files and the development of the 2009 input
data files for Base F emission estimation.

Our default approach to preparing the revise d 2018 and initial 2009 projection inventories for onroad mobile sources was to estimate the emissions by using either:

1. the revised 2002 data provided by each State coupled with the projection methods employed for the preliminary 2018 inventory, or

2. the same data and methods used to generate the preliminary 2018 inventory.

We also investigated whether or not there was more recent VMT forecasting data available (e.g., from the CAIR and if appropriate revised the default VMT growth rates accordingly. This did not affect any State that provided local VM T 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 inventories coupled with any changes/revisions provided by the States during th e review of the revised 2002 base year and the 2018 preliminary inventories. Therefore, as was the case for 2018, we obtained from the States any input data revisions, methodological revisions , and local control program specifications (to the extent that they differed from 2002/2018).

2.3.1.1 Preparation of revised 2018 input data files
Preparation of the revised 2018 inventories required the following updates:

1. The evaluation year was updated to 2018 in all files.

2. The diesel fuel sulfur content was revised from 500 ppm to 11 ppm, consistent with
EPA data for 2018 in all files.

3. Since the input data is model year, rather than age, specific for diesel sales fractions (with data for the newest 25 model years required), we updated all files that 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 included would reflect model years 1994- 2018. To forecast the 2002 data, MACTEC took the data for 1994-2002 from the 2002 files and added data for 2003-2018. To estimate the data for these years, we employed the assumption employed by "default" in MOBILE6 -- namely that diesel sales fractions for 1996 and later are constant. Therefore, we set the diesel sales
fractions for 2003-2018 at the same value as 2002.

4. VMT mix fractions must be updated to reflect expected changes in sales patterns between 2002 and 2018. If explicit VMT mix fractions are not provided, these changes are handled internally by MOBILE6 or externally through absolute VMT distributions. However, files that include explicit VMT mix fractions override the default MOBILE6 update and may or may not be consistent with external VMT distributions. MACTEC updated the VMT mix in such files as follows:

First, we calculated the VMT fractions for LDV, LDT1, LDT2, HDV, and MC from the external VMT files for 2018. This calculation was performed in
accordance with section 5.3.2 of the MOBILE6 Users Guide which indicates:

LDV = LDGV + LDDV

LDT1 = LDGT1 + LDDT

LDT2 = LDGT2

HDV = HDGV + HDDV

MC = MC
The resulting five VMT fractions were then split into the 16 fractions required by MOBILE6 using the distributions for 2018 provided in Appendix D of the MOBILE6 Users Guide. This approach ensures that explicit input file VMT fractions are consistent with the absolute VMT distributions prepared by MACTEC. These changes were made to all files that included VMT mixes.

5. All other input data were retained at 2002 values, except as otherwise instructed by the States. This includes all control program descriptions (I/M, Anti-Tampering Program [ATP], Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all other vehicle descriptive data (registrations age distributions, etc.), and all scenario descriptive data. The State-specific updates performed are described below.

Kentucky: MACTEC revised the 2018 input files for the Louisville, Kentucky area (Louisville Air Pollution Control District [APCD]) based on comments received relative to several components 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 VMT" and "Registration Age Distribution" file pointers were updated to reflect revised 2002 files provided by the Louisville APCD.
c) The "VMT Mix" data, which was previously based on the default approach of "growing" 2002 data, was replaced by 2018-specific data provided by the Louisville
APCD.

North Carolina:
North Carolina provided a wide range of revised input data, including complete MOBILE6 input files for July modeling. MACTEC did not use the provided input files directly as they did not match the 2002 NC input files for critical elements such as temperature distributions and gasoline RVP (while they were close, they were slightly different). To maintain continuity between 2002 and 2018 modeling, MACTEC instead elected to revise the 2002 input files to reflect all control program and vehicle-related changes implied by the new 2018 files, while retaining the basic temperature and gasoline RVP assumptions at their 2002 values. Under this approach, the following changes were made:

a) NC provided a county cross reference file specific to 2018 that differed from that used for 2002. We removed files that were referenced in the 2002 input data and replaced those files with those referenced in the 2018 data. In addition, since NC only provided 2018 input files for July, we estimated the basic data for these new files for the other months by cross referencing the target files for 2002 by county against the target files for 2018 by county.
b) We then revised the 2002 version of each input file to reflect the 2018 "header" data included in the NC-provided 2018 files. These data are exclusively limited to I/M and ATP program descriptions, so that the 2002 I/M and ATP data were replaced with
2018 I/M and ATP data.
c) We retained the registration age fractions at their 2002 "values" (external file pointers) as per NC instructions.
d) We retained all scenario-specific data (i.e., temperatures, RVP, etc.) at 2002 values, which (as indicated above), were slightly different in most cases from data included in the 2018 files provided by NC. We believe these differences were due to small deviations between the data assembled to support VISTAS 2002 and the process used to generate the 2018 files provided by NC, and that revising the VISTAS 2002 data 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 resulting inconsistencies that
would be reflected between VISTAS 2002 and VISTAS 2018.
e) NC also provided non-I/M versions of th e 2018 input files that would generally be used to model the non-I/M portion of VMT. While these files were retained they were not used for the 2018 input data preparation.
Finally, NC also provided a speed profile file and a speed profile cross reference file for 2018. We did not use these in our updates as they have no bearing on the MOBILE6 input files, but they were maintained in case they needed to be included in SMOKE control files for a future year control strategy scenario.

Virginia:
In accordance with instructions from VA, the input files that referenced an external I/M descriptive program file (VAIM02.IM) were revised to reference an alternative external file (VAIM05.IM). This change was to make the I/M program more relevant to the year 2018.

One additional important difference was made with respect to the revised 2018 and initial 2009 on-road mobile source input data files for all States. MACTEC developed updated SMOKE ready input files rather than MOBILE6 files so 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-road input files was based on forecasting the previously developed revised 2002 base year input files and is identical to that previously described for the revised 2018 methodology except as follows:
1. The evaluation year was updated to 2009.
2. Diesel fuel sulfur content was revised from 500 ppm to 29 ppm. The 29 ppm value was derived from an EPA report entitled "Summary and Analysis of the Highway Diesel Fuel 2003 Pre-compliance Reports" (EPA420-R-03-013, October 2003), which includes the Agency's estimates for the year-to-year fuel volumes associated with the transition from 500 ppm to 15 ppm diesel fuel. According to Table 2 of the report, there will be 2,922,284 barrels per day of 15 ppm diesel distributed in 2009 along with 110,488 barrels per day of 500 ppm diesel. Treating the 15 ppm diesel as 11 ppm on average (consistent with EPA assumptions and assumptions employed for the 2018 input files) and sales weighting the two sulfur content fuels results in an average 2009 diesel fuel sulfur content estimate of 29 ppm.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 identically to 2018 except that the diesel sales fractions for 2003-2009 were set at the same value as those for 2002 (rather than 2003-2018).
4. VMT mix fractions were updated to 2009 using an identical method to that described
for 2018.
5. All other input data were retained at 2002 values, except as otherwise instructed by individual States (see below). This includes all control program descriptions (I/M, ATP, Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all other vehicle descriptive data (registration age distributions, etc.), and all scenario descriptive data.
In addition to the updates described above that were applied to all VISTAS-region inputs, the following additional State-specific updates were performed:

KY – Identical changes to those made for 2018 (but specific to 2009) were made for the 2009 input files.

NC – Identical changes to those made for 2018 (but specific to 2009) were made for the 2009 input files.

VA – Identical changes to those made for 2018 were made for 2009.

2.3.2 VMT Data
The basic methodology used to generate the 2009 and 2018 VMT for use in estimating on-road
mobile source emissions was as follows:
1. All estimates start from the final VMT estimates used for the 2002 revised base year inventory.
2. Initial 2009 and 2018 VMT estimates were based on linear growth rates for each State, county, and vehicle type as derived from th e VMT data assembled by the U.S. EPA for their most recent HDD (heavy duty diesel) rulemaking. The methodology used to derive the growth factors is identical to that employed for the preliminary 2018 VMT estimates (which is described in the next section).
3. For States that provided no independent forecast data, the estimates derived in step 2 are also the final estimates. These States are: Alabama, Florida, Georgia, Kentucky, Mississippi, and West Virginia. For States th at provided forecast data, the provided data were used to either replace or augment the forecast data based on the HDD rule. These States, and the specific approaches employed, are detailed following the growth method description.
The steps involved in performing the growth estimates for VMT were as follows: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 information to the MSSIWG, the decision was made to use linear growth factors instead of nonlinear).
2. Estimates were developed at the vehicle class (i.e., LDGV, LDGT1, LDGT2, etc.) level of detail since the base year 2002 estimates were presented at that level of resolution. In effect, the county and vehicle class specific growth factors were applied to the 2002
VMT estimates for each vehicle and road class.
3. Overall county-specific VMT estimates for each year (developed by summing the vehicle and road class specific forecasts) were then compared to overall county-specific growth. Since overall county growth is a more appropriate controlling factor as it includes the combined impacts of all vehicle classes, the initial year-specific vehicle and road class VMT forecasts were normalized so that they matched the overall county VMT growth. Mathematically, this process is as follows:
(Est_rv_f) = (Est_rv_i) * (C_20XX / Sum(Est_rv_i))
where: Est_rv_f = the final road/vehicle class-specific estimates, Est_rv_i = the initial road/vehicle class-specific estimates, and C_20XX = the county-specific growth target for year 20XX. Table 2.3-1 presents a basic summary of the forecasts for the preliminary 2018 inventory for illustrative purposes:

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

State 2002 2018 Growth Factor
Alabama 55,723 72,966 1.309
Florida 178,681 258,191 1.445 Georgia 106,785 148,269 1.388 Kentucky 51,020 66,300 1.299 Mississippi 36,278 46,996 1.295
North Carolina 80,166 110,365 1.377
South Carolina 47,074 63,880 1.357

Tennessee 68,316 91,647 1.342

Virginia 76,566 102,971 1.345 West Virginia 19,544 24,891 1.274Documentation 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 for ecast data for VMT. The information presented below indicates how those data were processe d by MACTEC for use in the VISTAS projection
inventories.

Kentucky:
Revised 2009 and 2018 VMT mix data were provided by the Louisville APCD. Therefore, the distribution of Jefferson County VMT by vehicle type within the KY VMT file was revised to reflect the provided mix. This did not affect th e total forecasted VMT for either Jefferson County or the State, but does alter the fraction of that VMT accumulated by each of the eight vehicle types reflected in the VMT file. The following procedure was employed to make the VMT estimates consistent with the provided 2009/2018 VMT mix:

a) The 16 MOBILE6 VMT mix fractions were a ggregated into the following five vehicle types: LDV, LDT1, LDT2, HDV, and MC.

b) The 8 VMT mileage classes were aggregated into the same five vehicle types (across all roadway types) and converted to fractions by normalizing against the total Jefferson County VMT.

c) The ratio of the "desired" VMT fraction (i.e., that provided in the Louisville APCD VMT mix) to the "forecasted" VMT fraction (i.e., that calculated on the basis of the forecasted VMT data) was calculated for each of the five vehicle classes.

d) All forecasted VMT data for Jefferson County were multiplied by the applicable ratio from step c as follows:

new LDGV = old LDGV * LDV ratio
new LDGT1 = old LDGT1 * LDT1 ratio
new LDGT2 = old LDGT2 * LDT2 ratio
new HDGV = old HDGV * HDV ratio
new LDDV = old LDDV * LDV ratio
new LDDT = old LDDT * LDT1 ratio
new HDDV = old HDDV * HDV ratio
new MC = old MC * MC ratio

The total forecasted VMT for Jefferson County was then checked to ensure that it was unchanged.

North Carolina:

North Carolina provided both VMT and VMT mix data by county and roadway type for 2018. Therefore, these data replaced the data developed for North Carolina using HDD rule 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 submitted for 2009. Table 2.3-2 presents the resulting
VMT estimates which differ from the "default" HDD rule estimates as follows:

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

North Carolina
2002 106,795

State Data HDD Data
2009 123,396 124,626
2018 129,552 146,989 

### As indicated, there are substantial reductions in the State-provided forecast data relative to that derived from the HDD rule. The growth rates for both 2009 and 2018 are only about half that implied by the HDD data (1.15 versus 1.17 for 2009 and 1.21 versus 1.38 for 2018). The resulting growth rates are the lowest in the VISTAS region.

NC did not provide VMT mix data for 2009. Theref ore, the VMT mix fractions estimated using the "default" HDD rule growth rates were applied to the State-provided VMT estimates to generate vehicle-specific VMT. Essentia lly, 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 the State-provided VMT data at the county and road type level of detail to generate VMT data at the county-road type-vehicle type level of detail. The one exception was for county 063, road 110, for which no VMT da ta were included in the HDD rule. For this single county/road combination, State-aggregate VMT mix fractions (using the HDD growth methodology) were applied to the county/road VMT data. The difference between road 110 VMT fractions across all NC counties is minimal, so there is no effective difference in utilizing this more aggregate approach vis-à-vis the more resolved county/road approach.

South Carolina:
South Carolina provided county and roadway type-specific VMT data for several future years.
Data for 2018 was included and was used dir ectly. 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 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 2.3-3 VMT and HDD Rule Estimates for South Carolina (million miles per year)

South Carolina
2002 47,074

State Data HDD Data
2009 55,147 54,543
2018 65,133 63,880



### Tennessee:
In general, Tennessee estimates are based on the HDD rule growth rate as described in step two. However, Knox County provided independent VMT estimates for 2018 and these were used in place of the HDD rule-derived estimates. The Knox County estimates were total county VMT data only, so these were disaggregated into roadway and vehicle-type VMT using the distributions developed for Knox County in step two using the HDD rule VMT growth rates. No data for Knox County were provided for 2009, so the estimates derived using the HDD rule growth factors were adjusted by the ratio of "Knox County provided 2018 VMT" to "Knox County HDD Rule-derived 2018 VMT." Table 2.3-4 presents the resulting VMT estimates
which differ from the "default" HDD rule estimates as follows:

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

Tennessee
2002 68,316

State Data HDD Data
2009 78,615 78,813
2018 91,417 91,647 

### Virginia:
Virginia provided county and roadway type-specific annual VMT growth rates and these data were applied to Virginia -provided VMT data for 2002 to estimate VMT in both 2009 and 2018. Virginia provided VMT mix data for 2002, but not 2009 or 2018. Therefore, the estimated VMT data for both 2009 and 2018 were disaggregated into vehicle type-specific VMT using the VMT mixes developed for VA using the HDD rule VMT growth rates. Table 2.3-5 presents the resulting VMT estimates which differ from the "default" HDD rule estimates as follows: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 provided corrections, updates and supplemental data as
noted below.

For all states modeled, the Base G updates include:

• Adding Stage II refueling emissions calculations to the SMOKE processing.

• Revised the HDD compliance. (REBUILD EFFECTS = .1)

• Revised Diesel sulfur values in 2009 to 43 ppm and 2018 to 11 ppm

In addition to the global changes, individual VISTAS states made the following updates:

KY – updated VMT and M6 input values for selected counties

NC – revised VMT estimates, speeds and vehicle distributions and updated registration
distributions for Mobile 6.

TN - revised VMT and vehicle registrati on distributions for selected counties.

WV – revised VMT input data

AL, FL, and GA and VA did not provide updates for 2009/2018 Base G, and the Base F inputs
were used for these States.

2.3.4 Development of non-road emission estimates
The sections that follow describe the projection process used to develop 2009 and 2018 non-road projection estimates, as revised through the spring of 2006, for sources found in the NONROAD model and those sources estimated outside of the model (locomotives, airplanes and commercial marine vessels).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 year inventory input files available at the time the forecasts were developed, with appropriate updates for the projection years. Generally, this means that the Base F 2002 base year input files (as updated through the fall of 2004) were used as the basis for Base F projection year i nput file development and Base G 2002 base year input files as updated through the spring of 2006 we re used as the basis for Base G projection year input file development. Thus, all base year revisions are inherently incorporated into the associated projection year revisions. Other specific updates for the projection years for
NONROAD model sources consist of:

1. Revise the emission inventory year in the model (as well as various output file naming commands) to be reflective of the projection year. 2. Revise the fuel sulfur content for gasoline and diesel powered equipment. 3. Implement a limited number of local control program charges (national control program changes are handled internally within the NONROAD model, so explicit input file changes are not required). All equipment population growth and fleet turnover impacts are also handled internally within the NONROAD model, so that explicit changes input file changes are not required.

Base F Input File Changes:

To correctly account for diesel fuel sulfur content differences between the base and projectionyears, two sets of input and output files were prepared for each forecast year, one set for landbased equipment and one set for marine equipment. This two-step projection process was required for Base F, because diesel fuel sulfur contents varied between land-based and marine-based non-road equipment and the Draft NONROAD2004 used for Base F allowed only a single diesel fuel sulfur input. Thus, the model was executed separately for land-based and marine-based equipment for Base F, and the associated outputs subsequently combined. The specific diesel fuel sulfur contents modeled were as follows:
Diesel S (ppm) 2002 2009 2018
Land-Based 2500 348 11
Marine-Based 2500 408 56
As indicated, the Draft NONROAD2004 model was r un 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 capable of handling separate diesel fuel sulfur inputs for land-based and marine-based non-road equipment in a single model execution. Therefore, the two step modeling process described above for Base F updates was no longer required. Instead, the differential diesel fuel sulfur values are assembled into a single NONROAD input file as follows:
Diesel S (ppm) 2002 2009 2018
Land-Based 2500 348 11
Marine-Based 2638 408 56
Additionally, revised gasoline vapor pressure da ta 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 either the 2009 or 2018 forecast years. Therefore, to correctly forecast emissions in these counties, the forecast year gasoline vapor pressure inputs were
revised to:
Gasoline RVP (psi) 2002 2009 2018 Spring 9.87 9.2 9.2
Summer 9.0 7.0 7.0
Fall 9.87 9.2 9.2
Winter 12.5 12.5 12.5
The summer vapor pressure was simply set equal to the 2003 control value, while the spring and fall vapor pressures were adjusted to reflect a single month of the reduced volatility limit. The winter volatility was assumed to be unaffected by the summertime control requirement.

2.3.4.1.1 Differences between 2009/2018


### Other than diesel fuel sulfur content and the year of the projections, there are no differences in the methodology used to estimate emissions from NONROAD model sources. As indicated above, however the Base F 2009/2018 projecti ons were developed using Draft NONROAD2004, while the Base G 2009/2018 projections were made using Final NONROAD2005.

5 The specific counties are: Banks, Chattooga, Clarke, Floyd, Gordon, Heard, Jasper, Jones, Lamar, Lumpkin,

Madison, Meriwether, Monroe, Morgan, Oconee, Pike, Polk, Putnam, Troup, and Upson.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 for aircraft, locomotives, and commercial marine vessels (CMV) prepared as described earlier in this document, corresponding emission projections for 2009 and 2018 were developed in both the fall of 2004 (Base F) and the spring of 2006 (Base G). This section describes the procedur es employed in developing those inventories. The information presented is intended to build off of that presented in the section describing the 2002 Base F base year inventory. It should be 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, all base year revisions (as described earlier in this document) are inherently incorporated into the associated projection year revisions.

Base F Revisions:

Table 2.3-6 shows the 2002 base year emissions for each State in the VISTAS region for aircraft, locomotives and CMV (as they existed prior to Base F development).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, locomotives, and CMV is identical to that used earlier to develop preliminary 2018 Base 1 (“On the Books”) and 2018 Base 2 (“On the Way”) inventories. Briefly, the methodology relies on gr owth and control factors developed from inventories used in support of recent EPA rulemakings, and consists of the following steps:

(a) Begin with the 2002 base year emission estimates for aircraft, locomotive, and CMV as described above (at the State-county-SCC-pollutant level of detail).

(b) Detailed inventory data (both before and after controls) for these same emission sources for 1996, 2010, 2015, and 2020 were obtained from the EPA's Clean Air Interstate Rule (CAIR) Technical Support Document (which can be found at http://www.epa.gov/cair/pdfs/finaltech01.pdf). Using these data, combined growth and control factors for the period 2002-2009 and 2002-2018 were estimated using straight line interpolation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the State-county-SCC-pollutant level of detail.

(c) The EPA growth and control data are matched against the 2002 VISTAS base year data using State-county-SCC-pollutant as the matc h key. Ideally, there would be a one-to-one match and the process would end at this point. Unfortunately, actual match results were not always ideal, so additional matching criteria were required. For subsequent reference, this initial (highest resolution) matching criterion is denoted as the “CAIR-Primary”
criterion.

(d) A second matching criterion is applied that utilizes a similar, but higher-level SCC (lower resolution) matching approach. For example, SCC 2275020000 (commercial aircraft) in the 2002 base year inventory data would be matched with SCC 2275000000 (all aircraft) in the CAIR data. This criterion is applied to records in the 2002 base year emissions file that are not matched using the “CAIR-Primary” criterion, and is also performed at the State-county-SCC-pollutant level of detail. For subsequent reference, this is denoted as the “CAIR-Secondary” criterion. At the end of this process, a number of unmatched records remained, so a third level matching criterion was required.

(e) In the third matching step, the most frequently used SCC in the EPA CAIR files for each of the aircraft, locomotive, and commercial marine sectors was averaged at the State level to produce a “default” State and pollutant-specific growth and control factor for the sector. The resulting factor is used as a “default” growth factor for all unmatched county-SCC-pollutant level data in each State. In effect, State-specific growth data are applied to county level data for which an explicit match between the VISTAS 2002 base year data and EPA CAIR data could not be developed. The default growth and 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 sector. Matches made using this criterion are denoted as “CAIR-Tertiary” matches.

(f) According to EPA documentation, the CAIR baseline emissions include the impacts of the (then proposed) Tier 4 (T4) non-road diesel rulemaking, which implements a low sulfur fuel requirement that affects both future CMV and locomotive emissions. However, the impacts of this rule were originally intended to be excluded from the initial VISTAS 2018 forecast, which was to include only “on-the-books” controls. (The T4 rule was finalized subsequent to the development of the preliminary 2018 inventory in March of 2004.) Given its final status, T4 impacts were moved into the “on the books” inventory for non-road equipment. In addition, since there are no other proposed rules affecting the non-road sector between 2002 and 2018, there is no difference between the 2018 “on the books” and 2018 “on the way” inventories for the sector; so that only a single forecast inventory (for each evaluati on year) was developed. Nevertheless, since the algorithms developed to produce the VISTAS forecasts were developed when there was a distinction between the “on the books” and “on the way” inventories, the distinct algorithms used to produce the two inventories have been maintained even though the conceptual distinctions have been lost. This approach was taken for two reasons. First, it allowed the previously developed algorithms to be utilized without change. Second, it allowed for separate treatment of the T4 emissions impact which was important as those impacts changed between the proposed and final T4 rules. Thus, previous EPA inventories that include the proposed T4 impacts would not be accurate. Therefore, the procedural discussion continues to reflect the distinctions between non-T4 and T4 emissions, as these distinctions continue to be intrinsically important to the forecasting process. Therefore, a second set of EPA CA IR files that excluded the Tier 4 diesel impacts was obtained and the same matching exercise described above in steps (b) through (e) was performed using these “No T4” files. It is important to note that the matching exercise described in steps (b) through (e) cannot simply be replaced because the “No T4” files obtained from the EPA include only those SCCs specifically affected by the T4 rule (i.e., diesel CMV and locomotives). So in effect, the matching exercise was augmented (rather than replaced) with an additional three criteria analogous to those described in steps (c) through (e), and these are denoted as the “No T4-Primary,” “No T4-Secondary,” and “No T4-Tertiary” criteria. Because they exclude the impacts of the proposed T4 rule, matches using the “No T4” criteria supersede matches made using the basic CAIR criteria (as described in steps (c) through (e) above).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 provided these forecasts, as that State has provided specific growth factors for airport emissions in four counties. Because the provided data were based on forecasted changes in landings and takeoffs at major North Carolina airports, the factors were applied only to commercial (SCC 2275020000) and air taxi (SCC 2275060000) emissions. Emissions forecasts for military and general aviation aircraft operations, as well as all aircraft operations in counties other than the four identified in the North Carolina growth factor submission, continued to utilize the growth factors developed according to steps (b) through (f) above. Table 2.3-7 presents the locally generated growth factors applied in North Carolina.

Table 2.3-7 Locally Generated Growth Factors for North Carolina

FIP 2009 Factor 2018 Factor

37067 0.71 0.84

37081 0.97 0.89

37119 1.15 1.01

37183 0.88 0.81

Note:
Growth factor = Year Emissions/2002 Emissions. Under CAIR approach, 2009 = 1.16 to 1.17 for all 4 counties. Under CAIR approach, 2018 = 1.36 to 1.37 for all 4 counties.



### (h) Using this approach, each State-county-SCC-pollutant was assigned a combined growth and control factor using the EPA CAIR forecast or locally provided data. The 22,838 data records for aircraft, locomotives, and CMV in the 2002 revised base year emissions file were assigned growth factors in accordance with the following breakdown:

48 records matched State-provided growth factors, 4,179 records matched using the CAIR-Primary criterion, 240 records matched using the CAIR-Secondary criterion, 7,463 records matched using the CAIR-Tertiary criterion, 720 records matched using the No T4-Primary criterion, 3,858 records matched using the No T4-Secondary criterion, and 6,330 records matched using the No T4-Tertiary criterion.

(i) Finally, the impacts of the T4 rule as adopted were applied to the grown “non T4” emission estimates. The actual T4 emission standards do not affect aircraft, locomotive, or CMV directly, but associated diesel fuel sulfur requirements do affect locomotives and
CMV. Lower fuel sulfur content affects both 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 evaluation year from the EPA technical support document for the final T4 rule ( Final Regulatory Analysis: Control of Emissions from Non-road Diesel Engines , EPA420-R-04-007, May 2004). According to that document, the average diesel fuel sulfur content for locomotives and CMV is expected to be 408 ppmW in 2009 and 56 ppmW in 2018. These compare to expected non-T4 fuel sulfur levels of 2599 ppmW in 2009 and 2336 ppmW in 2018. Table 2.3-8 uses calculated
emissions estimates for base and T4 control scenarios to estimate emission reduction impacts.

Table 2.3-8 Estimated Emission 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 content assumed for the 2002 VISTAS base year inventory, upon which both the 2009 and 2018 inventories were based, is 2500 ppmW, a small adjustment to the emission reduction multipliers calculated from the T4 rule is appropriate since they are measured relative to modestly different sulfur contents (2599 ppmW for 2009 and 2336 ppmW for 2018). Correcting for these modest differences produces the emission reduction impact estimates relative to forecasts based on the VISTAS 2002 inventory shown in Table 2.3-9.

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

2009 2018
CMV 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 County, Florida, where CMV emissions are reported as “all fuels” rather than separately by residual and diesel fuel components. To estimate T4 impacts in Palm Beach County, the ratio of diesel CMV emissions to 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 estimates for diesel engines, as presented above, yields the following impact adjustment factors for Palm Beach County:

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

GROWTH BASIS

2009 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 devel oped through linear interpolation of the 2015 and 2020 inventories. Growth factors for 2009 and 2018 were then estimated as the ratios of the CAIR 2009 and 2018 inventories to the CAIR 2002 inventory.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 VISTAS inventory in March 2004, this process yielded reasonable results and exhibited no particular systematic concerns. However, when the 2009 Base F inventory was developed, significant concerns related to 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 emission inventories (as compared to the 1996 and 2020 CAIR inventories) that were masked during the construction of the “longer-term” 2018 inventory.

The apparent inconsistencies are best illustrated by looking at the actual data extracted from the CAIR inventory files. Note that although a limited example is being presented, the same general issue applies throughout the CAIR files. For FIP 01001 (Autauga County, Alabama) and SCC 2285002000 (Diesel Rail), the CAIR inventories indicate SO 2 

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

Table 2.3-12 SO 2 

### Emissions for Diesel Rail in Autauga County, AL from the CAIR Projections

YEAR TONS
1996: 15.3445
2010: 2.7271
2015: 2.8178
2020: 16.6232



### Clearly, there is a major drop in emissions between 1996 and 2010, followed by a major increase in emissions between 2015 and 2020. Several observations regarding these changes are important. First, the CAIR data were reported to exclude the T4 rule, so that the drop in emissions should be related to something other than simply a change in diesel fuel sulfur content. Second, if the T4 rule impacts were “accidentally” included in the estimates, there should be a resultant 90 percent drop in diesel sulfur between 2010 and 2015; so such inclusion is unlikely. Third, the rate of growth between 2015 and 2020 (43 percent per year compound or 97 percent

per year linear) is well beyond any reasonable expectations for rail service; and fuel sulfur content during this period is constant both with and without T4. In short, there appeared to be no rational explanation for the data, yet the same 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 occur, 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 fuel 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 presented 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 the markers labeled “i” and “ii.” Interpolated data for 2018, based on 2015 and 2020 CAIR data is depicted by the marker labeled “iii.” The relationship between marker “iii” and marker “i” is exactly the relationship used to construct the preliminary (e.g., pre-Base F) 2018 VISTAS invent ory (i.e., a linear growth rate equal to 0.7 percent per year). Thus, it is easy to see that although there is a major “dip and rise” between 2002 and 2018, it is essentially masked unless data for intervening years are examined. Since no intervening year was examined for the preliminary 2018 inventory, the “dip and rise” was not discovered. However, upon the development of the 2009 inventory forecast, the issue became obvious, as the marker labeled “ii” readily illustrates. In effect, the 2009 inventory reflected very low negative “growth rates” for some SCCs and pollutants relative to the 2002 inventory, while the 2018 inventory reflected very high and positive growth rates for those same SCCs and pollutants. In effect, the path between 2002 and 2018 that previously looked like the dotted line connecting markers “i” and “iii,” now looks like the solid line connecting markers “i”, “ii,” and “iii.” For reference purposes, this path is hereafter referred to as the 1996, 2010, 2015, and 2020 growth basis, since all interpolated data is based on CAIR data for those four years.

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

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

1990 1995 2000 2005 2010 2015 2020 2025


### 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 inherent in the 1996, 2010, 2015, and 2020 growth basis data and the inconsistencies its use would impart into the 2009 and 2018 VISTAS inventories, a secondary forecasting method was developed. This second method relies on the apparent consistency between the 1996 and 2020 non-T4 CAIR inventories, interpolating equivalent 2002, 2009, and 2018 inventories solely from these two inventories. In effect, the CAIR inventories for 2010 and 2015 are ignored. In Figure 2.3-1, this secondary approach is depicted by the data points that lie along the lines connecting markers A and D. Markers A and D represent the 1996 and 2020 CAIR inventories, and the markers labeled 1, 2, and 3 represent the interpolated 2002, 2009, and 2018 CAIR equivalent inventories. The growth rate between 2009 and 2002 is then equal to the ratio of the 2009 and 2002 CAIR inventories, while that between 2018 and 2002 is equal to the ratio of the 2018 and 2002 CAIR inventories. For the example data, the resulting linear growth estimate is 0.3 percent per year. For reference purposes, this path is hereafter referred to as the 1996-2020 growth basis, since all interpolated data are based on CAIR data for only those two years.

It is perhaps worth noting that the only elements of Figure 2.3-1 that have any bearing on the VISTAS inventories are the growth rates. The absolute CAIR data are of importance only in determining those rates, as all VISTAS 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 records that are virtually identical from a growth viewpoint.

While forecast inventories for aircraft, locomotives, and CMV were developed for 2009 and 2018 using both growth methods, it was ultimately decided to utilize the 1996-2020 growth basis for Base F since it provided more reasonable growth rates for 2009. Tables 2.3-14 and 2.3-15 present a summary of each Base F inventory, while Tables 2.3-16 and 2.3-17 present the associated change in emissions for each Base F forecast inventory relative to the Base F 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### base year VISTAS inventory. 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 this has been checked and is attributable to a high diesel contribution to total CMV SO 2 

### in
the 2002 inventories for these two States.

Figures 2.3-2 through 2.3-13 graphically depict the relationships between the various Base F inventories and preliminary 2002 and 2018 projections prepared prior to Base F. There are two figures for each pollutant, the first of which presents a comparison of total VISTAS regional emission estimates for aircraft, locomotives, and CMV, and the second of which presents total VISTAS region emission estimates for locomotives only. This two figure approach is intended to provide a more robust illustration of the differences between the various inventories, as some of the differences are less distinct when viewed through overall aggregate emissions totals. All of the figures include the following emissions estimates:

• The 2002 Base F base year VISTAS emi ssions 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 growth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2009”),

• The Base F 2018 VISTAS emissions inventor y developed using growth 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 (the initial 2002 VISTAS inventory) and the 2002 Base F emission estimates. This reduction generally results from emission updates reflected in the State 2002 CERR submittals used to develop the Base F 2002 base year inventory, although the major differences in aggregate PM emission estimates are driven to a greater extent by modifications in the methodology used to estimate aircraft PM in the Base F 2002 base year inventory (as documented under the base year inventory section of this report).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-14. Base F 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 4,178 202 278 102 19 217 FL 29,258 10,316 2,812 2,756 928 4,235 GA 7,635 6,233 1,712 1,678 523 512 KY 3,075 762 207 203 73 304 MS 1,765 162 51 50 16 108 NC 6,551 1,601 436 427 153 644 SC 7,372 559 446 437 98 975 TN 8,020 3,096 824 807 268 1,050 VA 10,994 3,094 1,239 1,214 907 2,892 WV 1,312 91 28 28 9 74 Aircraft (2275)

Total 80,159 26,116 8,033 7,704 2,993 11,011 AL 1,280 8,888 872 802 2,753 768 FL 6,236 43,198 1,838 1,691 5,864 1,467 GA 1,097 7,599 317 291 974 256 KY 7,087 48,039 2,158 1,985 8,350 1,649 MS 6,074 41,437 1,821 1,676 6,587 1,415 NC 634 4,386 184 169 584 148 SC 1,133 7,796 326 300 1,012 264 TN 3,887 26,333 1,168 1,074 4,512 904 VA 1,042 2,662 312 286 61 506 WV 1,638 11,073 455 419 89 381 Commercial

Marine (2280)

Total 30,109 201,412 9,450 8,693 30,786 7,759
VA 118 299 23 21 5 50 Military Marine (2283) Total 118 299 23 21 5 50 AL 3,648 23,529 452 406 242 1,279 FL 1,052 8,905 189 170 101 382 GA 2,769 24,398 507 456 271 1,003 KY 2,264 19,597 415 374 221 819 MS 2,406 20,785 441 397 239 849 NC 1,712 14,741 313 282 167 618 SC 1,213 10,443 222 200 119 437 TN 2,745 23,924 483 435 240 984 VA 1,236 11,134 1,167 1,050 608 467 WV 1,369 12,177 251 226 135 489 Locomotives (2285)

Total 20,412 169,635 4,440 3,995 2,343 7,328
Grand Total 130,798 397,462 21,946 20,413 36,126 26,148Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-15. Base F 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 4,681 236 345 122 23 245 FL 34,178 12,147 3,312 3,246 1,093 4,976 GA 8,939 7,340 2,016 1,976 616 601 KY 3,602 898 244 239 86 357 MS 1,986 190 60 58 18 122 NC 6,728 1,454 400 392 139 615 SC 8,487 616 493 484 112 1,119 TN 9,009 3,519 939 921 309 1,187 VA 12,578 3,528 1,370 1,342 1,063 3,358 WV 1,484 106 33 33 10 85 Aircraft (2275)

Total 91,670 30,035 9,213 8,814 3,468 12,666 AL 1,388 8,464 880 809 2,715 809 FL 6,684 41,117 1,853 1,705 6,248 1,543 GA 1,174 7,246 319 293 976 269 KY 7,703 45,174 2,199 2,023 8,383 1,752 MS 6,571 39,129 1,850 1,702 6,556 1,498 NC 679 4,179 185 170 596 155 SC 1,217 7,406 329 303 1,027 278 TN 4,225 24,763 1,190 1,095 4,808 960 VA 1,133 2,517 314 289 9 537 WV 1,781 10,412 459 422 13 404 Commercial

Marine (2280)

Total 32,554 190,407 9,578 8,811 31,330 8,205
VA 128 282 23 21 1 53 Military Marine (2283) Total 128 282 23 21 1 53 AL 3,850 19,917 381 343 34 1,183 FL 1,110 7,538 159 143 14 353 GA 2,917 21,395 427 385 38 932 KY 2,389 16,751 352 317 31 757 MS 2,540 17,594 372 335 34 785 NC 1,807 12,478 264 237 24 571 SC 1,280 8,840 187 168 17 404 TN 2,897 21,735 407 367 34 910 VA 1,300 10,173 983 885 86 436 WV 1,444 10,831 212 190 19 453 Locomotives (2285)

Total 21,534 147,252 3,744 3,368 333 6,785
Grand Total 145,885 367,975 22,557 21,015 35,132 27,709Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-16. Change in Emissions between 2009 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC
AL +10% +15% +23% +18% +16% +11%
FL +15% +16% +16% +16% +16% +16%
GA +15% +16% +16% +16% +16% +16%
KY +15% +16% +16% +16% +16% +16%
MS +11% +16% +15% +15% +16% +12%
NC +8% +3% +4% +4% +3% +5%
SC +13% +9% +9% +9% +12% +13%
TN +11% +12% +12% +12% +14% +11%
VA +13% +12% +9% +9% +15% +14%
WV +11% +16% +15% +15% +16% +12% Aircraft (2275)

Total +13% +14% +14% +13% +15% +14%
AL +7% -4% -5% -5% -18% +4%
FL +6% -4% -5% -5% -12% +4%
GA +6% -3% -5% -5% -17% +4%
KY +7% -4% -4% -4% -13% +5%
MS +7% -4% -4% -4% -15% +5%
NC +6% -4% -5% -5% -15% +4%
SC +6% -4% -5% -5% -16% +4%
TN +7% -4% -4% -4% -9% +5%
VA +7% -4% -7% -7% -83% +5%
WV +7% -4% -7% -7% -83% +5% Commercial

Marine (2280)

Total +7% -4% -5% -5% -15% +5%
VA +7% -4% -7% -7% -83% +5% Military Marine (2283) Total +7% -4% -7% -7% -83% +5%
AL +5% -11% -24% -24% -83% -6%
FL +5% -11% -24% -24% -83% -6%
GA +4% -9% -24% -24% -83% -5%
KY +5% -10% -23% -23% -83% -6%
MS +5% -11% -24% -24% -83% -6%
NC +5% -11% -24% -24% -83% -6%
SC +5% -11% -24% -24% -83% -6%
TN +5% -7% -24% -24% -83% -6%
VA +4% -6% -24% -24% -83% -5%
WV +4% -8% -24% -24% -83% -5% Locomotives (2285)

Total +4% -9% -24% -24% -83% -5%
Grand Total +10% -5% -4% -4% -32% +5%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### Table 2.3-17. Change in Emissions between 2018 and 2002 Base F Inventories (Based on Growth Using 1996 and 2020 EPA Inventories)

Source State CO NO x PM 10 PM 2.5 SO 2 VOC
AL +24% +35% +53% +41% +36% +25%
FL +34% +37% +37% +37% +37% +36%
GA +35% +37% +37% +37% +37% +36%
KY +35% +37% +37% +37% +37% +36%
MS +25% +36% +35% +35% +36% +27%
NC +10% -6% -5% -5% -6% 0%
SC +30% +20% +21% +21% +27% +30%
TN +24% +27% +28% +28% +31% +26%
VA +29% +28% +20% +20% +35% +33%
WV +26% +36% +35% +35% +36% +28% Aircraft (2275)

Total +29% +31% +30% +30% +33% +31%
AL +16% -8% -4% -4% -19% +10%
FL +14% -8% -4% -4% -7% +9%
GA +13% -8% -5% -5% -17% +9%
KY +17% -10% -2% -2% -13% +12%
MS +16% -9% -3% -3% -15% +11%
NC +13% -8% -4% -4% -14% +9%
SC +14% -9% -4% -4% -15% +10%
TN +17% -10% -2% -2% -3% +12%
VA +17% -9% -6% -6% -98% +11%
WV +17% -10% -6% -6% -98% +12% Commercial

Marine (2280)

Total +15% -9% -3% -3% -14% +11%
VA +17% -10% -6% -6% -98% +12% Military Marine (2283) Total +17% -10% -6% -6% -98% +12%
AL +10% -24% -36% -36% -98% -13%
FL +10% -24% -36% -36% -98% -13%
GA +10% -20% -36% -36% -98% -12%
KY +10% -23% -35% -35% -98% -13%
MS +10% -24% -36% -36% -98% -13%
NC +10% -24% -36% -36% -98% -13%
SC +10% -24% -36% -36% -98% -13%
TN +10% -15% -36% -36% -98% -13%
VA +10% -14% -36% -36% -98% -11%
WV +10% -18% -36% -36% -98% -12% Locomotives (2285)

Total +10% -21% -36% -36% -98% -12%
Grand Total +23% -12% -1% -1% -34% +11%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

129,659 159,122

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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

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

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

395,049

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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187,044
169,635

147,252 211,588

167,783

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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

### Emissions (Base F)

Figure 2.3-5. Locomotive NO x 

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

MACTEC, Inc. 170 22,823 21,946 22,557 100,452 128,715

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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5,815

4,440

3,744 6,118

3,947

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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

### Emissions (Base F)

Figure 2.3-7. Locomotive PM 10 

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

MACTEC, Inc. 171 5,232

3,995

3,368 5,505

3,552

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000

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

### Emissions (Base F)

Figure 2.3-9. Locomotive PM 2.5 

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

MACTEC, Inc. 172 14,022

2,343

333 14,947

1,553

0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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36,126 35,132 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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### Figure 2.3-10. Total Aircraft, Locomotive, and CMV SO 2 

### Emissions (Base F)

Figure 2.3-11. Locomotive SO 2 

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

MACTEC, Inc. 173 7,750 7,328 6,785 8,738

7,544

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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

Figure 2.3-13. Locomotive VOC Emissions (Base F)Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 174 

### Base G Revisions:

Table 2.3-18 shows the Base G 2002 base year emissions for each State in the VISTAS region for aircraft, locomotives and CMV. Although some of these data are updated relative to those used as the basis of the Base F emissions forecasts, the methodology used to develop 2009 and 2018 emissions forecasts for aircraft, locomotives, and CMV for Base G is identical to that used for Base F (as documented above). The only exceptions are as follows:

(a) As indicated in the discussion of the Base F forecasts, the CAIR (growth rate) matching criteria were overridden for any record for which States provided local growth data. For Base F, only North Carolina provided such data. However, for Base G, Kentucky regulators provided growth data for aircraft emissions associated with Cincinnati/Northern Kentucky Internationa l Airport (located in Boone County, Kentucky). These data were applied to all pollutants and all aircraft types (i.e., military aircraft (SCC 2275001000), commercial aircraft (SCC 2275020000), general aviation aircraft (SCC 2275050000), and air taxi airc raft (SCC 2275060000)). Emissions forecasts for all aircraft operations in counties other than Boone continued to utilize the growth factors developed according to the CAIR matching criteria. Table 2.3-19 presents the locally generated growth factors applied in Kentucky. It should be recognized that although the locally provided growth factors presented in the table are significantly greater than those that would apply under the CAIR matching criteria, this is to be expected as local regulators noted a very significant decline in activity at the Cincinnati/Northern Kentucky International Airport in 2002 (relative to activity in preceding years). Moreover, this downward spike seems to have been alleviated since 2002, so that the provided growth factors represent not only “routine” growth expected between 2002 and the two forecast years, but growth required to offset the temporary
decline observed in 2002.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 175 

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

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 5,595 185 238 99 18 276 FL 25,431 8,891 2,424 2,375 800 3,658 GA 6,620 5,372 1,475 1,446 451 443 KY 5,577 925 251 246 88 397 MS 1,593 140 44 43 13 96 NC 6,088 1,548 419 411 148 613 SC 6,505 515 409 401 88 863 TN 7,251 2,766 734 719 235 943 VA 11,873 3,885 2,010 1,970 272 2,825 WV 1,178 78 25 24 8 66 Aircraft (2275)

Total 77,712 24,305 8,029 7,734 2,121 10,179 AL 1,196 9,218 917 844 3,337 737 FL 5,888 44,817 1,936 1,781 6,683 1,409 GA 1,038 7,875 334 307 1,173 246 KY 6,607 50,267 2,246 2,066 9,608 1,569 MS 5,688 43,233 1,903 1,751 7,719 1,351 NC 599 4,547 193 178 690 142 SC 1,067 8,100 343 316 1,205 253 TN 3,624 27,555 1,217 1,120 4,974 860 VA 972 2,775 334 307 359 483 WV 1,528 11,586 487 448 525 362 Commercial

Marine (2280)

Total 28,207 209,972 9,911 9,118 36,275 7,413
VA 110 313 25 23 27 48 Military Marine (2283) Total 110 313 25 23 27 48 AL 3,518 26,623 592 533 1,446 1,365 FL 1,006 9,969 247 222 605 404 GA 2,654 26,733 664 598 1,622 1,059 KY 2,166 21,811 542 488 1,321 867 MS 2,302 23,267 578 520 1,429 899 NC 1,638 16,502 410 369 1,001 654 SC 1,160 11,690 291 261 710 462 TN 2,626 25,627 633 570 1,439 1,041 VA 1,186 11,882 1,529 1,375 3,641 492 WV 1,311 13,224 329 296 808 517 Locomotives (2285)

Total 19,568 187,328 5,815 5,232 14,022 7,761
Grand Total 125,597 421,918 23,780 22,107 52,444 25,401Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 176 

### Table 2.3-19 Locally Generated Growth Factors for Kentucky

FIP 2009 Factor 2018 Factor

21015 1.31 1.81

Note:
Growth factor = Year Emissions/2002 Emissions. Under CAIR approach, 2009 = 0.99 to 1.17. Under CAIR approach, 2018 = 0.97 to 1.40.



### (b) Because of the additional emissions records added in Alabama, as discussed in the Base G 2002 base year inventory section of this report, the total number of emissions records in the Base G 2009 and 2018 forecasts increased to 23,042 (as compared to 22,838 for Base F). The 23,042 data records for aircraft, locomotives, and CMV were assigned growth factors in accordance with the following breakdown:

72 records matched State-provided growth factors, 4,287 records matched using the CAIR-Primary criterion, 240 records matched using the CAIR-Secondary criterion, 7,511 records matched using the CAIR-Tertiary criterion, 720 records matched using the No T4-Primary criterion, 3,858 records matched using the No T4-Secondary criterion, and 6,354 records matched using the No T4-Tertiary criterion.

Tables 2.3-20 and 2.3-21 present a summary of the resulting Base G 2009 and 2018 inventories, while Tables 2.3-22 and 2.3-23 present the associated change in emissions for each forecast inventory relative to the Base G 2002 base year VISTAS. As was the case with Base F, the larger
reduction in CMV 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 attributable 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 which presents total VISTAS region emission estimates for locomotives only. This two figure approach is intended to provide a more robust illustration of the differences between the various inventories, as some of the differences are less distinct when viewed through overall aggregate emissions totals. All of the figures include the following emissions estimates:Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 177 

### • The Base G 2002 base year VISTAS emi ssions 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 growth rates derived from 1996 and 2020 EPA CAIR data (labeled as “2009”),

• The Base G 2018 VISTAS emissions inventor y developed using growth 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 methodology used to estimate aircraft PM in the Base F revisions to the 2002 Base F base year invent ory (as documented under the base year inventory section of this report).Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 178 

### Table 2.3-20. Base G 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NO x PM 10 PM 2.5 SO 2 VOC AL 6,265 213 292 116 21 309 FL 29,258 10,316 2,812 2,756 928 4,235 GA 7,635 6,233 1,712 1,678 523 512 KY 6,959 1,135 307 301 108 487 MS 1,765 162 51 50 16 108 NC 6,991 1,795 486 477 171 709 SC 7,372 559 446 437 98 975 TN 8,020 3,096 824 807 268 1,050 VA 13,141 4,244 2,124 2,082 306 3,153 WV 1,312 91 28 28 9 74 Aircraft (2275)

Total 88,716 27,844 9,083 8,732 2,447 11,612 AL 1,280 8,888 872 802 2,753 768 FL 6,236 43,198 1,838 1,691 5,864 1,467 GA 1,097 7,599 317 291 974 256 KY 7,087 48,039 2,158 1,985 8,350 1,649 MS 6,074 41,437 1,821 1,676 6,587 1,415 NC 634 4,386 184 169 584 148 SC 1,133 7,796 326 300 1,012 264 TN 3,887 26,333 1,168 1,074 4,512 904 VA 1,042 2,662 312 286 61 506 WV 1,638 11,073 455 419 89 381 Commercial

Marine (2280)

Total 30,108 201,412 9,450 8,693 30,786 7,759
VA 118 299 23 21 5 50 Military Marine (2283) Total 118 299 23 21 5 50 AL 3,677 23,783 452 406 242 1,289 FL 1,052 8,905 189 170 101 382 GA 2,769 24,398 507 456 271 1,003 KY 2,264 19,597 415 374 221 819 MS 2,406 20,785 441 397 239 849 NC 1,690 14,662 311 279 165 613 SC 1,213 10,443 222 200 119 437 TN 2,745 23,924 483 435 240 984 VA 1,236 11,134 1,167 1,050 608 467 WV 1,369 12,177 251 226 135 489 Locomotives (2285)

Total 20,420 169,808 4,437 3,993 2,341 7,333
Grand Total 139,362 399,364 22,994 21,440 35,578 26,754Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 179 

### Table 2.3-21. Base G 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions (annual tons) -- Based on Growth Using 1996 and 2020 EPA Inventories

Source State CO NO x PM 10 PM 2.5 SO 2 VOC
AL 7,126 249 361 139 24 352
FL 34,178 12,147 3,312 3,246 1,093 4,976
GA 8,939 7,340 2,016 1,976 616 601
KY 9,078 1,446 391 383 138 623
MS 1,986 190 60 58 18 122
NC 8,150 2,114 572 561 202 831
SC 8,487 616 493 484 112 1,119
TN 9,009 3,519 939 921 309 1,187
VA 14,770 4,706 2,271 2,226 349 3,574
WV 1,484 106 33 33 10 85 Aircraft (2275)

Total 103,206 32,435 10,450 10,027 2,871 13,472
AL 1,388 8,464 880 809 2,715 809
FL 6,684 41,117 1,853 1,705 6,248 1,543
GA 1,174 7,246 319 293 976 269
KY 7,703 45,174 2,199 2,023 8,383 1,752
MS 6,571 39,129 1,850 1,702 6,556 1,498
NC 678 4,179 185 170 596 155
SC 1,217 7,406 329 303 1,027 278
TN 4,225 24,763 1,190 1,095 4,808 960
VA 1,133 2,517 314 289 9 537
WV 1,781 10,412 459 422 13 404 Commercial

Marine (2280)

Total 32,554 190,407 9,578 8,811 31,330 8,205
VA 128 282 23 21 1 53 Military Marine (2283) Total 128 282 23 21 1 53
AL 3,881 20,131 381 343 34 1,192
FL 1,110 7,538 159 143 14 353
GA 2,917 21,395 427 385 38 932
KY 2,389 16,751 352 317 31 757
MS 2,540 17,594 372 335 34 785
NC 1,782 12,539 263 237 23 570
SC 1,280 8,840 187 168 17 404
TN 2,897 21,735 407 367 34 910
VA 1,300 10,173 983 885 86 436
WV 1,444 10,831 212 190 19 453 Locomotives (2285)

Total 21,539 147,527 3,743 3,368 332 6,792
Grand Total 157,427 370,651 23,794 22,227 34,534 28,522Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 180 

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

Source State CO NO x PM 10 PM 2.5 SO 2 VOC
AL +12% +15% +23% +18% +16% +12%
FL +15% +16% +16% +16% +16% +16%
GA +15% +16% +16% +16% +16% +16%
KY +25% +23% +23% +23% +23% +23%
MS +11% +16% +15% +15% +16% +12%
NC +15% +16% +16% +16% +16% +16%
SC +13% +9% +9% +9% +12% +13%
TN +11% +12% +12% +12% +14% +11%
VA +11% +9% +6% +6% +12% +12%
WV +11% +16% +15% +15% +16% +12% Aircraft (2275)

Total +14% +15% +13% +13% +15% +14%
AL +7% -4% -5% -5% -18% +4%
FL +6% -4% -5% -5% -12% +4%
GA +6% -3% -5% -5% -17% +4%
KY +7% -4% -4% -4% -13% +5%
MS +7% -4% -4% -4% -15% +5%
NC +6% -4% -5% -5% -15% +4%
SC +6% -4% -5% -5% -16% +4%
TN +7% -4% -4% -4% -9% +5%
VA +7% -4% -7% -7% -83% +5%
WV +7% -4% -7% -7% -83% +5% Commercial

Marine (2280)

Total +7% -4% -5% -5% -15% +5%
VA +7% -4% -7% -7% -83% +5% Military Marine (2283) Total +7% -4% -7% -7% -83% +5%
AL +5% -11% -24% -24% -83% -6%
FL +5% -11% -24% -24% -83% -6%
GA +4% -9% -24% -24% -83% -5%
KY +5% -10% -23% -23% -83% -6%
MS +5% -11% -24% -24% -83% -6%
NC +3% -11% -24% -24% -83% -6%
SC +5% -11% -24% -24% -83% -6%
TN +5% -7% -24% -24% -83% -6%
VA +4% -6% -24% -24% -83% -5%
WV +4% -8% -24% -24% -83% -5% Locomotives (2285)

Total +4% -9% -24% -24% -83% -6%
Grand Total +11% -5% -3% -3% -32% +5%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 181 

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

Source State CO NO x PM 10 PM 2.5 SO 2 VOC
AL +27% +35% +52% +41% +36% +28%
FL +34% +37% +37% +37% +37% +36%
GA +35% +37% +37% +37% +37% +36%
KY +63% +56% +56% +56% +56% +57%
MS +25% +36% +35% +35% +36% +27%
NC +34% +37% +36% +36% +37% +36%
SC +30% +20% +21% +21% +27% +30%
TN +24% +27% +28% +28% +31% +26%
VA +24% +21% +13% +13% +28% +27%
WV +26% +36% +35% +35% +36% +28% Aircraft (2275)

Total +33% +33% +30% +30% +35% +32%
AL +16% -8% -4% -4% -19% +10%
FL +14% -8% -4% -4% -7% +9%
GA +13% -8% -5% -5% -17% +9%
KY +17% -10% -2% -2% -13% +12%
MS +16% -9% -3% -3% -15% +11%
NC +13% -8% -4% -4% -14% +9%
SC +14% -9% -4% -4% -15% +10%
TN +17% -10% -2% -2% -3% +12%
VA +17% -9% -6% -6% -98% +11%
WV +17% -10% -6% -6% -98% +12% Commercial

Marine (2280)

Total +15% -9% -3% -3% -14% +11%
VA +17% -10% -6% -6% -98% +12% Military Marine (2283) Total +17% -10% -6% -6% -98% +12%
AL +10% -24% -36% -36% -98% -13%
FL +10% -24% -36% -36% -98% -13%
GA +10% -20% -36% -36% -98% -12%
KY +10% -23% -35% -35% -98% -13%
MS +10% -24% -36% -36% -98% -13%
NC +9% -24% -36% -36% -98% -13%
SC +10% -24% -36% -36% -98% -13%
TN +10% -15% -36% -36% -98% -13%
VA +10% -14% -36% -36% -98% -11%
WV +10% -18% -36% -36% -98% -12% Locomotives (2285)

Total +10% -21% -36% -36% -98% -12%
Grand Total +25% -12% +0% +1% -34% +12%Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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

129,659 159,122

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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

395,049

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

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. 184 23,780 22,994 23,794 100,452 128,715

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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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. 185 22,107 21,440 22,227 73,099 92,207

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 100,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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5,232

3,993

3,368 5,505

3,552

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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

### Emissions (Base G)

Figure 2.3-21. Locomotive PM 2.5 

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

MACTEC, Inc. 186 52,444

35,578 34,534 57,062

41,284

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

2002 2009 2018 2002 Prelim 2018 Prelim T

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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. 187 25,401 26,754 28,522 26,877 29,228

0 5,000 10,000 15,000 20,000 25,000 30,000 35,000

2002 2009 2018 2002 Prelim 2018 Prelim T

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7,761 7,333 6,792 8,738

7,544

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000

2002 2009 2018 2002 Prelim 2018 Prelim T

o

n

s

p

e

r

Y

e

a

r 

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

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

MACTEC, Inc. 188 

### 2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio
Base G projection inventories for 2009 and 2018 for NONROAD model sources in the states of Illinois, Indiana, and Ohio were produced using a methodology identical to that employed to develop a Base G 2002 base year inventory for the same states (as documented earlier in this report). This method consists of the extraction of a complete set of county-level input data applicable to each of the three states (in each of the two projection years) from the latest version of the EPA’s NMIM model. This includes appropriate consideration of all non-default NMIM input files generated by the Midwest Regional Planning Organization as documented earlier in the discussion of the Base G 2002 base year 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 gasoline vapor pressure, gasoline sulfur content, and diesel sulfur content in most counties. All temperature data (minimum, maximum, and average daily temperatures) was constant across years.

As described in the discussion of the Base G 2002 base year inventory, counties in the three states were grouped for modeling purposes using a temperature aggregation scheme that allowed for county-specific temperature variations of no more that 2 oF from group average temperatures (for all temperature inputs). The same grouping sc heme was applied to projection year modeling, so that Illinois emissions were modeled using 12 county groups, Indiana emissions were modeled using 9 county groups, and Ohio emissions were modeled using 10 county groups. Thus, 31 iterations of NONROAD2002 were required per season per projection year, as compared to the 53 iterations per season per projection year required for the VISTAS region.

As was also described in the discussion of the Base G 2002 base year inventory, several non-default equipment population, growth, activity, seasonal distribution, and county allocation files are assigned by NMIM model inputs for these counties. As was the case for the base year inventory development, these same non-default assignments were retained for both projection inventories.

2.3.4.4 Differences between 2009/2018
Methodologically, there was no difference in the way that 2009 and 2018 emissions were calculated for non-road mobile sources. The actual value of the growth factors were different for each type of mobile source considered, but the calculation methods were identical.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 189 

### 2.3.5 Quality Assurance steps
Throughout the inventory development process, quality assurance steps were performed to ensure that no double counting of emissions occurred, to ensure that a full and complete inventory was developed for VISTAS, and to ma ke sure that projection calculations were working correctly. Quality assurance was an important component to the inventory development process and MACTEC performed the following QA steps on mobile source components of the 2009 and revised 2018 projection inventories:

1. All final files (NONROAD only) were run through EPA’s Format and Content checking software. Input data files for MOBILE and VMT growth estimates were reviewed by the corresponding SIWG and by the VISTAS Emission Inventory
Technical Advisor.

2. SCC level emission summaries were prepared and evaluated to ensure that emissions
were consistent and that there were no missing sources (NONROAD only).

3. Tier comparisons (by pollutant) were developed between the 2002 base year inventory and the 2009 and 2018 projecti on inventories (NONROAD only). Total VISTAS level summaries by pollutant were developed for these sources to compare
Base F and Base G emission levels.

4. Data product summaries were provided to both the VISTAS Emission Inventory Technical Advisor and to the SIWG representatives for review and comment. Changes based on these comments were implemented in the files.

5. Version numbering was used for all inventory files developed. The version numbering process used a decimal system to track major and minor changes. For example, a major change would result in a version going from 1.0 to 2.0. A minor change would cause a version number to go from 1.0 to 1.1. Minor changes resulting from largely editorial changes would result in a change from 1.00 to 1.01.Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 190 

### APPENDIX A:

STATE EMISSION TOTALS BY POLLUTANT AND SECTORDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.191Annual CO Emissions by Source Sector01,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,000 A L F L G A K Y M S 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

MACTEC, Inc. 192 

### Annual CO Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 11,279 174,271 1,366,056 414,385 83,958 474,959 2002 Actual 11,460 174,260 942,793 414,385 83,958 514,120 2002 Typical AL 14,986 180,369 942,793 454,686 66,654 534,873 2009 24,342 201,794 797,966 488,924 59,626 535,658 2018

57,113 81,933 4,693,893 1,920,729 71,079 790,620 2002 Actual 55,899 81,928 3,446,095 1,920,729 71,079 923,310 2002 Typical FL 35,928 87,037 3,446,095 2,104,920 57,011 923,310 2009 53,772 96,819 3,086,330 2,323,327 53,903 923,310 2018

9,712 130,656 2,833,468 791,158 108,083 654,411 2002 Actual 9,650 130,656 2,053,694 791,158 108,083 620,342 2002 Typical GA 23,721 147,215 2,053,694 882,970 94,130 637,177 2009 44,476 167,644 1,765,020 973,872 93,827 637,177 2018

12,619 109,936 1,260,682 325,993 66,752 8,703 2002 Actual 12,607 109,937 942,350 325,993 66,752 24,900 2002 Typical KY 15,812 122,024 942,350 357,800 57,887 31,810 2009 17,144 139,437 782,423 381,215 54,865 33,296 2018

5,303 54,568 894,639 236,752 37,905 13,209 2002 Actual 5,219 54,567 628,151 236,752 37,905 14,353 2002 Typical MS 5,051 57,748 628,151 257,453 27,184 48,160 2009 15,282 66,858 528,898 270,726 22,099 50,037 2018

13,885 50,531 3,176,811 808,231 345,315 34,515 2002 Actual 14,074 50,531 2,184,901 808,231 345,315 71,970 2002 Typical NC 14,942 53,696 2,184,901 887,605 301,163 96,258 2009 20,223 62,145 1,510,848 960,709 290,809 111,266 2018

6,990 56,315 1,275,161 413,964 113,714 248,341 2002 Actual 6,969 56,315 912,280 413,964 113,714 253,005 2002 Typical SC 11,135 60,473 912,280 448,625 90,390 282,307 2009 14,786 68,988 800,619 481,332 83,167 282,307 2018

7,084 114,681 1,967,658 505,163 89,828 4,302 2002 Actual 6,787 114,681 1,361,408 505,163 89,828 10,124 2002 Typical TN 7,214 119,039 1,361,408 554,121 74,189 17,372 2009 7,723 140,138 1,150,516 593,100 68,809 18,860 2018

6,892 63,796 2,170,508 660,105 155,873 15,625 2002 Actual 6,797 63,784 1,495,771 660,105 155,873 12,611 2002 Typical VA 12,509 68,346 1,495,771 726,815 128,132 21,130 2009 15,420 76,998 1,310,698 797,683 121,690 26,923 2018

10,341 89,879 560,717 133,113 39,546 6,738 2002 Actual 10,117 89,878 385,994 133,113 39,546 2,652 2002 Typical WV 11,493 100,045 385,994 152,862 31,640 3,949 2009 11,961 119,332 319,030 167,424 28,773 5,013 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.193Annual NH3Emissions by Source Sector050,000100,000150,000200,000250,000 A L F L G A K Y M S 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

MACTEC, Inc. 194 

### Annual NH 3 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 317 1,883 5,576 33 58,318 1,689 2002 Actual 239 1,883 6,350 33 58,318 1,957 2002 Typical AL 359 2,132 6,350 36 64,268 2,050 2009 1,072 2,464 7,296 42 71,915 2,054 2018

234 1,423 18,078 134 37,446 3,102 2002 Actual 222 1,423 21,737 134 37,446 3,157 2002 Typical FL 1,631 1,544 21,737 148 38,616 3,157 2009 2,976 1,829 26,154 171 40,432 3,157 2018

83 3,613 10,524 60 80,913 2,578 2002 Actual 86 3,613 12,660 60 80,913 2,153 2002 Typical GA 686 3,963 12,660 68 89,212 2,229 2009 1,677 4,797 14,871 79 99,885 2,229 2018

326 674 5,044 31 51,135 39 2002 Actual 321 674 5,795 31 51,135 112 2002 Typical KY 400 760 5,795 34 53,005 143 2009 476 901 6,584 40 55,211 150 2018

190 1,169 3,577 23 58,721 59 2002 Actual 198 1,169 4,026 23 58,721 65 2002 Typical MS 334 668 4,026 25 63,708 217 2009 827 764 4,565 29 69,910 225 2018

54 1,179 10,455 65 161,860 155 2002 Actual 55 1,179 12,637 65 161,860 324 2002 Typical NC 445 1,285 12,637 72 170,314 433 2009 663 1,465 13,077 83 180,866 501 2018

142 1,411 4,684 33 28,166 980 2002 Actual 141 1,411 5,510 33 28,166 908 2002 Typical SC 343 1,578 5,510 36 30,555 1,039 2009 617 1,779 6,472 41 33,496 1,039 2018

204 1,542 6,616 43 34,393 19 2002 Actual 197 1,542 7,738 43 34,393 46 2002 Typical TN 227 1,764 7,738 48 35,253 78 2009 241 2,115 8,962 55 36,291 85 2018

127 3,104 7,837 48 43,905 70 2002 Actual 130 3,104 9,066 48 43,905 57 2002 Typical VA 694 3,049 9,066 53 46,639 95 2009 622 3,604 10,757 61 50,175 121 2018

121 332 1,933 9 9,963 30 2002 Actual 121 332 2,183 9 9,963 12 2002 Typical WV 330 341 2,183 11 10,625 18 2009 180 413 2,484 13 11,504 23 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.195Annual NOx Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S 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

MACTEC, Inc. 196 

### Annual NO x 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 161,038 83,310 158,423 65,366 23,444 10,728 2002 Actual 154,704 83,302 101,323 65,366 23,444 11,456 2002 Typical AL 82,305 69,409 101,323 56,862 23,930 11,901 2009 64,358 78,318 46,222 43,799 25,028 11,918 2018

257,677 45,156 466,098 180,627 28,872 15,942 2002 Actual 282,507 45,150 314,307 180,627 28,872 19,791 2002 Typical FL 86,165 46,020 314,307 163,794 28,187 19,791 2009 73,125 51,902 154,611 127,885 30,708 19,791 2018

147,517 49,214 308,013 97,961 36,142 14,203 2002 Actual 148,126 49,214 208,393 97,961 36,142 13,882 2002 Typical GA 98,497 50,312 208,393 85,733 37,729 14,243 2009 75,717 55,775 99,821 64,579 41,332 14,243 2018

198,817 38,392 154,899 104,571 39,507 187 2002 Actual 201,928 38,434 97,912 104,571 39,507 534 2002 Typical KY 92,021 37,758 97,912 94,752 42,088 682 2009 64,378 41,034 42,104 79,392 44,346 714 2018

43,135 61,526 111,791 88,787 4,200 283 2002 Actual 40,433 61,553 69,949 88,787 4,200 308 2002 Typical MS 36,011 56,398 69,949 80,567 4,249 1,033 2009 10,271 61,533 29,717 68,252 4,483 1,073 2018

151,850 44,881 341,198 84,284 36,550 740 2002 Actual 148,809 44,881 207,648 84,284 36,550 1,544 2002 Typical NC 66,517 34,719 207,648 70,997 39,954 2,065 2009 62,346 37,750 81,706 49,046 43,865 2,387 2018

88,241 42,153 140,428 50,249 19,332 4,932 2002 Actual 88,528 42,153 91,696 50,249 19,332 5,270 2002 Typical SC 46,915 40,019 91,696 43,235 19,360 5,899 2009 51,456 44,021 42,354 31,758 20,592 5,899 2018

157,307 64,331 233,324 96,827 17,844 92 2002 Actual 152,137 64,331 147,757 96,827 17,844 217 2002 Typical TN 66,405 57,869 147,757 86,641 18,499 373 2009 31,715 63,435 65,242 70,226 19,597 405 2018

86,886 60,415 219,602 63,219 51,418 335 2002 Actual 85,081 60,390 133,170 63,219 51,418 271 2002 Typical VA 66,219 51,046 133,170 54,993 52,618 453 2009 75,594 55,945 61,881 40,393 56,158 578 2018

230,977 46,612 59,612 33,239 12,687 145 2002 Actual 222,437 46,618 36,049 33,239 12,687 57 2002 Typical WV 86,328 38,031 36,049 30,133 13,439 85 2009 51,241 43,359 16,274 25,710 14,828 108 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.197Annual PM10Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S 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

MACTEC, Inc. 198 

### Annual PM 10 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 7,646 25,240 3,898 4,787 393,588 47,237 2002 Actual 7,845 25,239 3,188 4,787 393,588 50,833 2002 Typical AL 6,969 25,421 3,188 4,027 413,020 52,851 2009 7,822 29,924 2,488 3,041 445,256 52,927 2018

21,387 35,857 11,253 18,281 443,346 85,263 2002 Actual 21,391 35,856 9,953 18,281 443,346 98,470 2002 Typical FL 9,007 39,872 9,953 15,613 503,230 98,470 2009 9,953 46,456 8,489 12,497 578,516 98,470 2018

11,224 21,516 7,236 8,618 695,414 65,227 2002 Actual 11,467 21,516 6,103 8,618 695,414 62,336 2002 Typical GA 17,891 22,997 6,103 7,521 776,411 63,973 2009 20,909 27,143 4,995 6,015 880,199 63,973 2018

4,701 16,626 3,720 6,425 233,559 846 2002 Actual 4,795 16,626 3,002 6,425 233,559 2,421 2002 Typical KY 6,463 17,174 3,002 5,544 242,177 3,093 2009 6,694 20,153 2,283 4,556 256,052 3,237 2018

1,633 19,472 2,856 5,010 343,377 1,284 2002 Actual 1,706 19,469 2,290 5,010 343,377 1,396 2002 Typical MS 4,957 19,245 2,290 4,270 356,324 4,683 2009 7,187 22,859 1,688 3,452 375,495 4,865 2018

22,754 13,785 6,905 7,348 280,379 3,356 2002 Actual 22,994 13,785 5,861 7,348 280,379 6,998 2002 Typical NC 22,152 13,855 5,861 6,055 292,443 9,359 2009 37,376 15,678 4,299 4,298 315,294 10,819 2018

21,400 14,142 3,446 4,152 260,858 25,968 2002 Actual 21,827 14,142 2,878 4,152 260,858 26,304 2002 Typical SC 19,395 13,370 2,878 3,471 278,299 29,153 2009 28,826 15,139 2,258 2,617 304,251 29,153 2018

14,640 34,534 5,338 6,819 212,554 418 2002 Actual 13,866 34,534 4,238 6,819 212,554 984 2002 Typical TN 15,608 34,145 4,238 5,877 226,098 1,689 2009 15,941 41,397 3,199 4,672 246,252 1,834 2018

3,960 13,252 4,537 8,728 237,577 1,519 2002 Actual 3,892 13,252 3,760 8,728 237,577 1,226 2002 Typical VA 5,508 13,048 3,760 7,510 252,488 2,054 2009 13,775 15,112 3,343 6,208 275,351 2,618 2018

4,573 17,503 1,395 1,850 115,346 655 2002 Actual 4,472 17,503 1,096 1,850 115,346 258 2002 Typical WV 5,657 17,090 1,096 1,640 115,089 384 2009 6,349 21,735 844 1,292 121,549 487 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.199Annual PM2.5Emissions by Source Sector050,000100,000150,000200,000250,000 A L F L G A K Y M S 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

MACTEC, Inc. 200 

### Annual PM 2.5 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 4,113 19,178 2,794 4,502 56,654 42,041 2002 Actual 4,176 19,177 2,049 4,502 56,654 44,812 2002 Typical AL 3,921 19,230 2,049 3,776 58,699 46,543 2009 4,768 22,598 1,262 2,835 62,323 46,608 2018

15,643 30,504 7,852 17,415 58,878 75,717 2002 Actual 15,575 30,504 6,216 17,415 58,878 88,756 2002 Typical FL 5,910 33,946 6,216 14,866 64,589 88,756 2009 6,843 39,430 4,242 11,868 72,454 88,756 2018

4,939 17,394 5,158 8,226 103,794 57,293 2002 Actual 5,070 17,394 3,869 8,226 103,794 55,712 2002 Typical GA 10,907 18,906 3,869 7,175 112,001 57,116 2009 13,983 22,323 2,517 5,730 123,704 57,116 2018

2,802 11,372 2,693 6,046 45,453 726 2002 Actual 2,847 11,372 1,941 6,046 45,453 2,076 2002 Typical KY 4,279 11,686 1,941 5,203 46,243 2,653 2009 4,434 13,739 1,160 4,256 47,645 2,777 2018

1,138 9,906 2,109 4,690 50,401 1,102 2002 Actual 1,147 9,902 1,522 4,690 50,401 1,197 2002 Typical MS 4,777 9,199 1,522 3,985 51,661 4,016 2009 7,033 10,739 876 3,203 53,222 4,173 2018

16,498 10,455 4,816 7,005 64,052 2,878 2002 Actual 16,623 10,455 3,643 7,005 64,052 6,002 2002 Typical NC 15,949 10,411 3,643 5,760 69,457 8,027 2009 29,791 11,775 2,158 4,069 71,262 9,279 2018

17,154 10,245 2,496 3,945 40,291 22,953 2002 Actual 17,521 10,245 1,870 3,945 40,291 23,511 2002 Typical SC 16,042 9,390 1,870 3,294 41,613 25,955 2009 25,032 11,086 1,154 2,474 44,319 25,955 2018

12,166 27,345 3,919 6,458 42,566 359 2002 Actual 11,491 27,345 2,782 6,458 42,566 844 2002 Typical TN 13,092 27,079 2,782 5,557 44,124 1,449 2009 13,387 32,893 1,643 4,403 46,692 1,573 2018

2,606 10,165 3,090 8,288 43,989 1,303 2002 Actual 2,650 10,165 2,254 8,288 43,989 1,052 2002 Typical VA 4,067 9,988 2,254 7,136 44,514 1,762 '2009 11,976 11,594 1,641 5,891 46,697 2,245 2018

2,210 13,313 1,003 1,728 21,049 562 2002 Actual 2,163 13,313 703 1,728 21,049 221 2002 Typical WV 2,940 12,769 703 1,528 20,664 329 2009 3,648 16,516 428 1,198 21,490 418 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.201Annual SO2Emissions by Source Sector0100,000200,000300,000400,000500,000600,000700,000 A L F L G A K Y M S 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

MACTEC, Inc. 202 

### Annual SO 2 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 447,828 96,481 6,885 7,584 52,253 2,208 2002 Actual 423,736 96,481 635 7,584 52,253 2,559 2002 Typical AL 378,052 101,246 635 3,471 48,228 2,681 2009 305,262 113,224 720 2,818 50,264 2,686 2018

453,631 65,090 20,872 20,614 40,491 4,057 2002 Actual 483,590 65,090 2,120 20,614 40,491 4,129 2002 Typical FL 186,055 65,511 2,120 8,967 36,699 4,129 2009 132,177 75,047 2,533 7,536 38,317 4,129 2018

514,952 53,774 12,155 9,005 57,559 3,372 2002 Actual 517,633 53,774 1,254 9,005 57,559 2,815 2002 Typical GA 417,449 53,983 1,254 2,725 57,696 2,914 2009 230,856 59,343 1,458 1,709 59,729 2,914 2018

484,057 34,029 5,974 14,043 41,805 51 2002 Actual 495,153 34,029 585 14,043 41,805 146 2002 Typical KY 290,193 36,418 585 9,180 43,087 187 2009 226,062 40,682 651 8,592 44,186 196 2018

67,429 35,960 4,604 11,315 771 78 2002 Actual 60,086 35,954 397 11,315 771 84 2002 Typical MS 76,579 25,564 397 7,191 753 283 2009 15,146 39,221 441 6,638 746 294 2018

477,990 44,103 13,343 7,693 5,412 203 2002 Actual 478,488 44,103 1,311 7,693 5,412 423 2002 Typical NC 242,286 42,516 1,311 1,892 5,751 566 2009 108,492 46,292 1,323 905 6,085 655 2018

206,399 53,518 5,958 4,866 12,900 1,281 2002 Actual 210,272 53,518 556 4,866 12,900 1,187 2002 Typical SC 124,608 48,325 556 1,701 13,051 1,359 2009 93,274 53,577 643 1,198 13,457 1,359 2018

334,151 79,584 9,184 10,441 29,917 25 2002 Actual 320,146 79,584 831 10,441 29,917 60 2002 Typical TN 255,410 70,657 831 5,651 30,577 102 2009 112,672 77,219 944 5,207 31,962 111 2018

241,204 63,903 7,218 8,663 105,890 92 2002 Actual 233,691 63,900 900 8,663 105,890 74 2002 Typical VA 225,653 62,560 900 1,707 105,984 124 2009 140,233 68,909 1,059 507 109,380 158 2018

516,084 54,070 2,489 2,112 11,667 40 2002 Actual 500,381 54,077 227 2,112 11,667 16 2002 Typical WV 277,489 55,973 227 359 12,284 23 2009 115,324 62,193 255 56 12,849 29 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.203Annual VOC Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,0001,400,000 A L F L G A K Y M S 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

MACTEC, Inc. 204 

### Annual VOC Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR 2,295 47,037 119,790 60,487 182,674 25,278 2002 Actual 2,288 47,035 72,848 60,487 182,674 26,526 2002 Typical AL 2,473 46,644 72,848 50,249 143,454 27,502 2009 2,952 54,291 47,296 40,407 153,577 27,539 2018

2,524 38,471 495,225 272,072 404,302 42,724 2002 Actual 2,531 38,471 323,290 272,072 404,302 51,527 2002 Typical FL 1,910 36,880 323,290 209,543 420,172 51,527 2009 2,376 42,811 216,620 183,452 489,975 51,527 2018

1,244 33,157 267,378 85,965 299,679 33,979 2002 Actual 1,256 33,157 184,239 85,965 299,679 33,918 2002 Typical GA 2,314 33,444 184,239 67,686 272,315 34,710 2009 2,841 39,485 105,507 56,761 319,328 34,710 2018

1,487 44,834 98,311 44,805 95,375 410 2002 Actual 1,481 44,834 63,258 44,805 95,375 1,172 2002 Typical KY 1,369 47,786 63,258 38,558 94,042 1,497 2009 1,426 55,861 39,084 30,920 103,490 1,567 2018

648 43,204 82,810 41,081 131,808 622 2002 Actual 629 43,203 49,670 41,081 131,808 675 2002 Typical MS 404 37,747 49,670 36,197 124,977 2,266 2009 1,114 45,338 30,734 28,842 140,134 2,355 2018

988 60,496 253,374 94,480 237,926 1,624 2002 Actual 986 60,496 163,803 94,480 237,926 3,387 2002 Typical NC 954 61,207 163,803 74,056 187,769 4,530 2009 1,345 70,100 88,620 61,327 189,591 5,236 2018

470 38,458 106,792 55,016 161,000 14,202 2002 Actual 470 38,458 67,281 55,016 161,000 14,666 2002 Typical SC 660 35,665 67,281 43,061 146,107 16,045 2009 906 43,656 44,700 36,131 161,228 16,045 2018

926 77,304 169,914 66,450 153,307 202 2002 Actual 890 77,304 108,200 66,450 153,307 476 2002 Typical TN 932 66,538 108,200 55,358 154,377 817 2009 976 83,573 64,665 45,084 182,222 888 2018

754 43,152 144,684 74,866 174,116 735 2002 Actual 747 43,152 89,678 74,866 174,116 593 2002 Typical VA 778 43,726 89,678 57,009 147,034 994 2009 997 53,186 60,454 49,052 150,919 1,267 2018

1,180 14,595 40,066 18,566 60,443 317 2002 Actual 1,140 14,595 23,907 18,566 60,443 125 2002 Typical WV 1,361 13,810 23,907 18,069 55,288 186 2009 1,387 16,565 15,463 14,086 60,747 236 2018Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.205Annual CO Emissions by Source Sector01,000,0002,000,0003,000,0004,000,0005,000,0006,000,0007,000,0008,000,000 A L F L G A K Y M S N C S C T N V A W V

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

MACTEC, Inc. 206 

### Annual CO Emissions by Source Sector

Name AREA EGU FIRES NONEGU NONROAD ONROAD YEAR Basis 83,958 10,812 514,120 174,306 367,038 1,366,056 2002 OTB - Typical 2002 68,882 16,494 514,120 177,145 408,424 942,793 2009 OTB - Typical 2002 AL 68,882 19,205 514,120 177,145 408,424 942,793 2009 OTW - Typical 2002 63,773 26,600 514,120 194,801 443,100 797,966 2018 OTB - Typical 2002 63,773 29,893 514,120 194,801 443,100 797,966 2018 OTW - Typical 2002

105,849 51,165 923,310 84,920 1,731,519 4,693,893 2002 OTB - Typical 2002 101,356 40,642 923,310 98,325 1,934,550 3,446,095 2009 OTB - Typical 2002 FL 101,356 40,641 923,310 98,325 1,934,550 3,446,095 2009 OTW - Typical 2002 100,952 59,793 923,310 113,923 2,179,296 3,086,330 2018 OTB - Typical 2002 100,952 57,759 923,310 113,923 2,179,296 3,086,330 2018 OTW - Typical 2002

107,889 8,098 620,342 131,417 700,427 2,833,468 2002 OTB - Typical 2002 103,579 19,170 620,342 147,835 783,990 2,053,694 2009 OTB - Typical 2002 GA 103,579 20,024 620,342 147,835 783,990 2,053,694 2009 OTW - Typical 2002 105,059 27,152 620,342 169,156 868,018 1,765,020 2018 OTB - Typical 2002 105,059 28,895 620,342 169,156 868,018 1,765,020 2018 OTW - Typical 2002

66,752 12,888 56,686 110,141 289,967 1,260,682 2002 OTB - Typical 2002 64,806 15,273 56,686 121,981 306,884 942,350 2009 OTB - Typical 2002 KY 64,806 15,119 56,686 121,981 306,884 942,350 2009 OTW - Typical 2002 65,297 16,974 56,686 139,395 349,285 782,423 2018 OTB - Typical 2002 65,297 14,954 56,686 139,395 349,285 782,423 2018 OTW - Typical 2002

37,905 3,831 128,471 57,711 213,779 894,639 2002 OTB - Typical 2002 37,161 6,714 128,471 60,709 237,297 628,151 2009 OTB - Typical 2002 MS 37,161 6,954 128,471 60,709 237,297 628,151 2009 OTW - Typical 2002 36,425 10,553 128,471 70,454 252,658 528,898 2018 OTB - Typical 2002 36,425 12,928 128,471 70,454 252,658 528,898 2018 OTW - Typical 2002

373,585 12,027 200,564 52,542 725,734 3,176,811 2002 OTB - Typical 2002 332,443 11,091 200,564 54,791 797,360 2,184,901 2009 OTB - Typical 2002 NC 332,443 11,170 200,564 54,791 797,360 2,184,901 2009 OTW - Typical 2002 327,871 13,482 200,564 63,699 863,536 1,510,848 2018 OTB - Typical 2002 327,871 13,777 200,564 63,699 863,536 1,510,848 2018 OTW - Typical 2002

113,714 3,675 253,005 59,605 367,575 1,275,161 2002 OTB - Typical 2002 95,826 6,316 253,005 65,612 402,871 912,280 2009 OTB - Typical 2002 SC 95,826 6,526 253,005 65,612 402,871 912,280 2009 OTW - Typical 2002 89,343 10,175 253,005 75,209 438,027 800,619 2018 OTB - Typical 2002 89,343 10,671 253,005 75,209 438,027 800,619 2018 OTW - Typical 2002

89,235 6,339 78,370 119,405 451,480 1,967,658 2002 OTB - Typical 2002 82,196 6,750 78,370 121,420 500,186 1,361,408 2009 OTB - Typical 2002 TN 82,196 6,651 78,370 121,420 500,186 1,361,408 2009 OTW - Typical 2002 81,242 7,074 78,370 143,845 540,143 1,150,516 2018 OTB - Typical 2002 81,242 6,509 78,370 143,845 540,143 1,150,516 2018 OTW - Typical 2002

155,873 5,958 19,159 62,534 595,311 2,170,508 2002 OTB - Typical 2002 133,738 9,811 19,159 69,822 661,295 1,495,771 2009 OTB - Typical 2002 VA 133,738 10,245 19,159 69,822 661,295 1,495,771 2009 OTW - Typical 2002 129,037 14,788 19,159 77,590 734,294 1,310,698 2018 OTB - Typical 2002 129,037 14,839 19,159 77,590 734,294 1,310,698 2018 OTW - Typical 2002

39,546 9,927 32,656 89,928 119,089 560,717 2002 OTB - Typical 2002 37,704 12,622 32,656 100,292 138,999 385,994 2009 OTB - Typical 2002 WV 37,704 12,328 32,656 100,292 138,999 385,994 2009 OTW - Typical 2002 36,809 13,064 32,656 119,367 152,932 319,030 2018 OTB - Typical 2002 36,809 12,992 32,656 119,367 152,932 319,030 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.207Annual NH3Emissions by Source Sector050,000100,000150,000200,000250,000 A L F L G A K Y M S N C S C T N V A W V

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

MACTEC, Inc. 208 

### Annual NH 3 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 89 1,883 5,576 32 59,486 1,957 2002 OTB - Typical 2002 1,128 2,112 6,350 35 65,441 1,957 2009 OTB - Typical 2002 AL 1,344 2,112 6,350 35 65,441 1,957 2009 OTW - Typical 2002 1,909 2,456 7,296 40 73,346 1,957 2018 OTB - Typical 2002 2,173 2,456 7,296 40 73,346 1,957 2018 OTW - Typical 2002

53 1,383 18,078 108 44,902 3,157 2002 OTB - Typical 2002 2,524 1,605 21,737 119 46,950 3,157 2009 OTB - Typical 2002 FL 2,524 1,605 21,737 119 46,950 3,157 2009 OTW - Typical 2002 4,022 1,905 26,154 138 49,889 3,157 2018 OTB - Typical 2002 3,865 1,905 26,154 138 49,889 3,157 2018 OTW - Typical 2002

5 3,613 10,524 54 84,230 2,153 2002 OTB - Typical 2002 1,305 3,963 12,660 60 92,838 2,153 2009 OTB - Typical 2002 GA 1,376 3,963 12,660 60 92,838 2,153 2009 OTW - Typical 2002 1,912 4,799 14,871 71 103,911 2,153 2018 OTB - Typical 2002 2,057 4,799 14,871 71 103,911 2,153 2018 OTW - Typical 2002

0 674 5,044 28 51,097 110 2002 OTB - Typical 2002 717 733 5,795 30 53,023 110 2009 OTB - Typical 2002 KY 710 733 5,795 30 53,023 110 2009 OTW - Typical 2002 763 839 6,584 36 55,356 110 2018 OTB - Typical 2002 771 839 6,584 36 55,356 110 2018 OTW - Typical 2002

97 1,169 3,577 23 59,262 177 2002 OTB - Typical 2002 388 667 4,026 26 64,289 177 2009 OTB - Typical 2002 MS 407 667 4,026 26 64,289 177 2009 OTW - Typical 2002 686 761 4,565 30 70,565 177 2018 OTB - Typical 2002 872 761 4,565 30 70,565 177 2018 OTW - Typical 2002

35 1,171 10,455 61 164,467 324 2002 OTB - Typical 2002 577 1,255 12,637 68 173,187 324 2009 OTB - Typical 2002 N C 574 1,255 12,637 68 173,187 324 2009 OTW - Typical 2002 740 1,412 13,077 79 184,167 324 2018 OTB - Typical 2002 781 1,412 13,077 79 184,167 324 2018 OTW - Typical 2002

0 1,411 4,684 29 29,447 908 2002 OTB - Typical 2002 409 1,578 5,510 32 31,966 908 2009 OTB - Typical 2002 SC 422 1,578 5,510 32 31,966 908 2009 OTW - Typical 2002 702 1,779 6,472 37 35,082 908 2018 OTB - Typical 2002 742 1,779 6,472 37 35,082 908 2018 OTW - Typical 2002

0 1,620 6,616 41 35,571 46 2002 OTB - Typical 2002 406 1,861 7,738 45 36,578 46 2009 OTB - Typical 2002 TN 400 1,861 7,738 45 36,578 46 2009 OTW - Typical 2002 427 2,240 8,962 53 37,812 46 2018 OTB - Typical 2002 394 2,240 8,962 53 37,812 46 2018 OTW - Typical 2002

122 3,097 7,837 44 46,221 159 2002 OTB - Typical 2002 396 3,057 9,066 48 49,173 159 2009 OTB - Typical 2002 VA 439 3,057 9,066 48 49,173 159 2009 OTW - Typical 2002 759 3,620 10,757 57 53,023 159 2018 OTB - Typical 2002 783 3,620 10,757 57 53,023 159 2018 OTW - Typical 2002

12 331 1,933 10 10,779 12 2002 OTB - Typical 2002 691 342 2,183 11 11,461 12 2009 OTB - Typical 2002 WV 673 342 2,183 11 11,461 12 2009 OTW - Typical 2002 722 416 2,484 13 12,390 12 2018 OTB - Typical 2002 719 416 2,484 13 12,390 12 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.209Annual NOx Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S N C S C T N V A W V

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

MACTEC, Inc. 210 

### Annual NO x 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 153,349 83,868 158,423 64,891 23,444 11,456 2002 OTB - Typical 2002 131,988 80,738 101,323 55,494 26,482 11,456 2009 OTB - Typical 2002 AL 132,323 70,644 101,323 55,494 26,482 11,456 2009 OTW - Typical 2002 135,010 91,052 46,222 42,573 28,754 11,456 2018 OTB - Typical 2002 39,942 80,031 46,222 42,573 28,754 11,456 2018 OTW - Typical 2002

247,099 59,517 466,098 150,519 29,477 19,791 2002 OTB - Typical 2002 148,522 67,533 314,307 136,851 31,821 19,791 2009 OTB - Typical 2002 FL 147,801 67,533 314,307 136,851 31,821 19,791 2009 OTW - Typical 2002 159,004 77,551 154,611 111,959 35,047 19,791 2018 OTB - Typical 2002 59,446 77,551 154,611 111,959 35,047 19,791 2018 OTW - Typical 2002

120,785 52,425 308,013 91,386 36,105 13,882 2002 OTB - Typical 2002 131,901 53,008 208,393 79,049 38,876 13,882 2009 OTB - Typical 2002 GA 119,425 53,008 208,393 79,049 38,876 13,882 2009 OTW - Typical 2002 128,938 59,005 99,821 60,650 42,260 13,882 2018 OTB - Typical 2002 65,559 59,005 99,821 60,650 42,260 13,882 2018 OTW - Typical 2002

209,802 38,460 154,899 101,261 39,507 1,460 2002 OTB - Typical 2002 178,930 37,960 97,912 90,803 42,122 1,460 2009 OTB - Typical 2002 KY 177,272 37,201 97,912 90,803 42,122 1,460 2009 OTW - Typical 2002 182,192 41,776 42,104 77,295 45,597 1,460 2018 OTB - Typical 2002 64,674 40,948 42,104 77,295 45,597 1,460 2018 OTW - Typical 2002

27,254 76,906 111,791 90,686 4,200 3,328 2002 OTB - Typical 2002 38,911 70,463 69,949 81,780 4,789 3,328 2009 OTB - Typical 2002 MS 38,978 70,463 69,949 81,780 4,789 3,328 2009 OTW - Typical 2002 38,355 76,738 29,717 68,781 5,230 3,328 2018 OTB - Typical 2002 11,206 76,738 29,717 68,781 5,230 3,328 2018 OTW - Typical 2002

144,730 50,393 341,198 81,448 48,730 5,005 2002 OTB - Typical 2002 66,598 46,242 207,648 66,382 53,550 5,005 2009 OTB - Typical 2002 N C 67,051 46,242 207,648 66,382 53,550 5,005 2009 OTW - Typical 2002 64,537 50,044 81,706 45,146 60,073 5,005 2018 OTB - Typical 2002 59,917 50,044 81,706 45,146 60,073 5,005 2018 OTW - Typical 2002

85,555 44,123 140,428 46,789 19,332 5,270 2002 OTB - Typical 2002 50,433 43,799 91,696 39,544 20,852 5,270 2009 OTB - Typical 2002 SC 50,128 42,944 91,696 39,544 20,852 5,270 2009 OTW - Typical 2002 55,103 48,314 42,354 29,512 22,467 5,270 2018 OTB - Typical 2002 36,264 47,403 42,354 29,512 22,467 5,270 2018 OTW - Typical 2002

155,028 73,384 233,324 95,968 17,829 2,232 2002 OTB - Typical 2002 106,979 62,435 147,757 85,084 19,148 2,232 2009 OTB - Typical 2002 TN 104,528 61,176 147,757 85,084 19,148 2,232 2009 OTW - Typical 2002 112,411 69,374 65,242 69,093 20,928 2,232 2018 OTB - Typical 2002 32,411 67,999 65,242 69,093 20,928 2,232 2018 OTW - Typical 2002

82,911 61,528 219,602 58,524 51,418 978 2002 OTB - Typical 2002 64,950 64,298 133,170 50,120 53,344 978 2009 OTB - Typical 2002 VA 62,810 60,027 133,170 50,120 53,344 978 2009 OTW - Typical 2002 56,716 71,480 61,881 36,970 56,668 978 2018 OTB - Typical 2002 40,045 66,931 61,881 36,970 56,668 978 2018 OTW - Typical 2002

222,090 46,715 59,612 34,442 12,687 944 2002 OTB - Typical 2002 173,977 42,140 36,049 31,148 13,816 944 2009 OTB - Typical 2002 WV 174,572 40,469 36,049 31,148 13,816 944 2009 OTW - Typical 2002 170,522 46,846 16,274 26,279 15,079 944 2018 OTB - Typical 2002 42,227 44,944 16,274 26,279 15,079 944 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.211Annual PM10Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,000 A L F L G A K Y M S N C S C T N V A W V

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

MACTEC, Inc. 212 

### Annual PM 10 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 5,737 24,957 3,898 5,331 393,093 50,833 2002 OTB - Typical 2002 29,053 25,161 3,188 4,597 411,614 50,833 2009 OTB - Typical 2002 AL 23,250 25,161 3,188 4,597 411,614 50,833 2009 OTW - Typical 2002 31,815 29,278 2,488 3,690 445,168 50,833 2018 OTB - Typical 2002 20,450 29,278 2,488 3,690 445,168 50,833 2018 OTW - Typical 2002

33,182 28,882 11,253 17,692 446,821 98,470 2002 OTB - Typical 2002 25,779 27,531 9,953 15,630 507,515 98,470 2009 OTB - Typical 2002 FL 24,493 27,531 9,953 15,630 507,515 98,470 2009 OTW - Typical 2002 27,320 31,890 8,489 13,827 582,832 98,470 2018 OTB - Typical 2002 22,204 31,890 8,489 13,827 582,832 98,470 2018 OTW - Typical 2002

5,447 22,058 7,236 8,295 695,320 62,336 2002 OTB - Typical 2002 39,580 23,861 6,103 7,368 776,935 62,336 2009 OTB - Typical 2002 GA 28,118 23,861 6,103 7,368 776,935 62,336 2009 OTW - Typical 2002 41,221 28,177 4,995 6,068 880,800 62,336 2018 OTB - Typical 2002 26,905 28,177 4,995 6,068 880,800 62,336 2018 OTW - Typical 2002

6,000 15,613 3,720 6,389 233,559 6,667 2002 OTB - Typical 2002 32,406 15,858 3,002 5,312 242,345 6,667 2009 OTB - Typical 2002 KY 29,606 15,858 3,002 5,312 242,345 6,667 2009 OTW - Typical 2002 33,784 18,587 2,283 4,602 256,544 6,667 2018 OTB - Typical 2002 25,733 18,587 2,283 4,602 256,544 6,667 2018 OTW - Typical 2002

4,783 19,680 2,856 5,551 343,377 14,693 2002 OTB - Typical 2002 5,864 19,439 2,290 4,754 356,516 14,693 2009 OTB - Typical 2002 MS 5,883 19,439 2,290 4,754 356,516 14,693 2009 OTW - Typical 2002 6,268 23,145 1,688 3,873 375,931 14,693 2018 OTB - Typical 2002 6,459 23,145 1,688 3,873 375,931 14,693 2018 OTW - Typical 2002

22,689 14,507 6,905 7,449 303,492 20,488 2002 OTB - Typical 2002 23,028 14,301 5,861 6,210 317,847 20,488 2009 OTB - Typical 2002 N C 21,459 14,301 5,861 6,210 317,847 20,488 2009 OTW - Typical 2002 21,417 16,002 4,299 4,474 345,275 20,488 2018 OTB - Typical 2002 20,258 16,002 4,299 4,474 345,275 20,488 2018 OTW - Typical 2002

23,492 18,149 3,446 4,211 260,858 26,304 2002 OTB - Typical 2002 18,023 17,368 2,878 3,593 278,852 26,304 2009 OTB - Typical 2002 SC 17,493 17,368 2,878 3,593 278,852 26,304 2009 OTW - Typical 2002 19,290 20,272 2,258 2,889 304,940 26,304 2018 OTB - Typical 2002 19,182 20,272 2,258 2,889 304,940 26,304 2018 OTW - Typical 2002

14,537 35,982 5,338 7,145 211,903 8,875 2002 OTB - Typical 2002 17,735 33,838 4,238 6,218 225,650 8,875 2009 OTB - Typical 2002 TN 17,159 33,838 4,238 6,218 225,650 8,875 2009 OTW - Typical 2002 19,103 41,466 3,199 5,019 245,893 8,875 2018 OTB - Typical 2002 12,432 41,466 3,199 5,019 245,893 8,875 2018 OTW - Typical 2002

3,790 12,799 4,537 7,928 237,577 18,160 2002 OTB - Typical 2002 15,343 13,470 3,760 6,763 252,924 18,160 2009 OTB - Typical 2002 VA 12,804 13,470 3,760 6,763 252,924 18,160 2009 OTW - Typical 2002 14,390 15,661 3,343 5,564 275,790 18,160 2018 OTB - Typical 2002 12,653 15,661 3,343 5,564 275,790 18,160 2018 OTW - Typical 2002

7,145 14,866 1,395 2,072 115,346 3,276 2002 OTB - Typical 2002 36,442 14,926 1,096 1,819 115,410 3,276 2009 OTB - Typical 2002 WV 31,780 14,926 1,096 1,819 115,410 3,276 2009 OTW - Typical 2002 37,425 18,433 844 1,381 121,964 3,276 2018 OTB - Typical 2002 24,253 18,433 844 1,381 121,964 3,276 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.213Annual PM2.5Emissions by Source Sector050,000100,000150,000200,000250,000300,000 AL FL GA KY M S N C SC TN VA W V

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

MACTEC, Inc. 214 

### Annual PM 2.5 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 3,131 19,016 2,794 4,877 73,352 44,812 2002 OTB - Typical 2002 24,875 19,184 2,049 4,144 76,248 44,812 2009 OTB - Typical 2002 AL 19,190 19,184 2,049 4,144 76,248 44,812 2009 OTW - Typical 2002 27,280 22,268 1,262 3,231 82,449 44,812 2018 OTB - Typical 2002 16,279 22,268 1,262 3,231 82,449 44,812 2018 OTW - Typical 2002

25,761 24,569 7,852 16,739 81,341 88,756 2002 OTB - Typical 2002 19,307 23,063 6,216 14,786 90,487 88,756 2009 OTB - Typical 2002 FL 18,186 23,063 6,216 14,786 90,487 88,756 2009 OTW - Typical 2002 20,848 26,622 4,242 13,044 101,872 88,756 2018 OTB - Typical 2002 16,278 26,622 4,242 13,044 101,872 88,756 2018 OTW - Typical 2002

2,137 17,893 5,158 7,899 133,542 55,712 2002 OTB - Typical 2002 33,111 19,562 3,869 7,014 146,691 55,712 2009 OTB - Typical 2002 GA 22,163 19,562 3,869 7,014 146,691 55,712 2009 OTW - Typical 2002 34,361 23,110 2,517 5,769 163,925 55,712 2018 OTB - Typical 2002 20,549 23,110 2,517 5,769 163,925 55,712 2018 OTW - Typical 2002

3,605 10,729 2,693 5,998 52,765 6,310 2002 OTB - Typical 2002 26,640 10,837 1,941 4,978 54,397 6,310 2009 OTB - Typical 2002 KY 23,915 10,837 1,941 4,978 54,397 6,310 2009 OTW - Typical 2002 27,857 12,738 1,160 4,289 57,110 6,310 2018 OTB - Typical 2002 19,915 12,738 1,160 4,289 57,110 6,310 2018 OTW - Typical 2002

4,384 10,187 2,109 5,200 63,135 13,680 2002 OTB - Typical 2002 5,511 9,459 1,522 4,440 65,321 13,680 2009 OTB - Typical 2002 MS 5,530 9,459 1,522 4,440 65,321 13,680 2009 OTW - Typical 2002 5,919 11,068 876 3,597 68,338 13,680 2018 OTB - Typical 2002 6,110 11,068 876 3,597 68,338 13,680 2018 OTW - Typical 2002

16,428 11,204 4,816 7,079 69,663 19,491 2002 OTB - Typical 2002 17,449 10,888 3,643 5,889 75,570 19,491 2009 OTB - Typical 2002 N C 16,034 10,888 3,643 5,889 75,570 19,491 2009 OTW - Typical 2002 15,636 12,136 2,158 4,215 85,018 19,491 2018 OTB - Typical 2002 14,702 12,136 2,158 4,215 85,018 19,491 2018 OTW - Typical 2002

19,238 13,565 2,496 3,985 51,413 23,511 2002 OTB - Typical 2002 14,471 12,977 1,870 3,396 54,230 23,511 2009 OTB - Typical 2002 SC 14,079 12,977 1,870 3,396 54,230 23,511 2009 OTW - Typical 2002 15,601 15,092 1,154 2,718 58,441 23,511 2018 OTB - Typical 2002 15,509 15,092 1,154 2,718 58,441 23,511 2018 OTW - Typical 2002

11,918 29,130 3,919 6,756 49,131 8,730 2002 OTB - Typical 2002 15,770 27,313 2,782 5,873 51,753 8,730 2009 OTB - Typical 2002 TN 15,228 27,313 2,782 5,873 51,753 8,730 2009 OTW - Typical 2002 17,103 33,502 1,643 4,724 55,712 8,730 2018 OTB - Typical 2002 10,514 33,502 1,643 4,724 55,712 8,730 2018 OTW - Typical 2002

2,559 9,868 3,090 7,486 52,271 17,361 2002 OTB - Typical 2002 13,451 10,368 2,254 6,388 54,587 17,361 2009 OTB - Typical 2002 VA 11,237 10,368 2,254 6,388 54,587 17,361 2009 OTW - Typical 2002 12,366 12,062 1,641 5,241 58,141 17,361 2018 OTB - Typical 2002 10,755 12,062 1,641 5,241 58,141 17,361 2018 OTW - Typical 2002

3,356 12,154 1,003 1,941 25,850 3,239 2002 OTB - Typical 2002 29,773 12,138 703 1,699 25,835 3,239 2009 OTB - Typical 2002 WV 25,251 12,138 703 1,699 25,835 3,239 2009 OTW - Typical 2002 30,628 15,045 428 1,284 27,088 3,239 2018 OTB - Typical 2002 17,548 15,045 428 1,284 27,088 3,239 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.215Annual SO2Emissions by Source Sector0100,000200,000300,000400,000500,000600,000700,000800,000 A L A L A L F L F L F L G A G A G A K Y K Y K Y M S M S M S N C N C N C S C S C S C T N T N T N V A V A V A W V W V W V

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

MACTEC, Inc. 216 

### Annual SO 2 

### Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis AL 421,734 96,447 6,885 7,539 47,074 2,559 2002 OTB - Typical 2002 AL 465,576 100,845 635 3,463 17,818 2,559 2009 OTB - Typical 2002 AL 314,841 100,845 635 3,463 17,818 2,559 2009 OTW - Typical 2002 AL 375,305 112,771 720 2,815 49,975 2,559 2018 OTB - Typical 2002 AL 226,506 112,771 720 2,815 49,975 2,559 2018 OTW - Typical 2002

FL 443,152 70,165 20,872 17,023 40,537 4,129 2002 OTB - Typical 2002 FL 219,072 76,851 2,120 8,380 52,390 4,129 2009 OTB - Typical 2002 FL 199,834 76,851 2,120 8,380 52,390 4,129 2009 OTW - Typical 2002 FL 215,177 87,065 2,533 7,511 59,413 4,129 2018 OTB - Typical 2002 FL 126,280 87,065 2,533 7,511 59,413 4,129 2018 OTW - Typical 2002

GA 433,513 62,032 12,155 8,145 57,555 2,815 2002 OTB - Typical 2002 GA 582,078 63,348 1,254 2,588 57,377 2,815 2009 OTB - Typical 2002 GA 394,425 63,348 1,254 2,588 57,377 2,815 2009 OTW - Typical 2002 GA 554,013 70,386 1,458 1,702 61,155 2,815 2018 OTB - Typical 2002 GA 221,615 70,386 1,458 1,702 61,155 2,815 2018 OTW - Typical 2002

KY 508,139 34,026 5,974 13,739 41,805 136 2002 OTB - Typical 2002 KY 483,235 35,479 585 9,092 40,779 136 2009 OTB - Typical 2002 KY 342,670 35,479 585 9,092 40,779 136 2009 OTW - Typical 2002 KY 429,418 38,816 651 8,536 42,326 136 2018 OTB - Typical 2002 KY 225,772 38,816 651 8,536 42,326 136 2018 OTW - Typical 2002

MS 57,263 36,071 4,604 11,551 771 100 2002 OTB - Typical 2002 MS 76,855 35,028 397 7,232 637 100 2009 OTB - Typical 2002 MS 76,855 35,028 397 7,232 637 100 2009 OTW - Typical 2002 MS 74,505 40,318 441 6,638 831 100 2018 OTB - Typical 2002 MS 23,768 40,318 441 6,638 831 100 2018 OTW - Typical 2002

N C 472,192 51,049 13,343 7,207 7,096 423 2002 OTB - Typical 2002 N C 182,356 52,693 1,311 1,798 7,607 423 2009 OTB - Typical 2002 N C 132,054 52,693 1,311 1,798 7,607 423 2009 OTW - Typical 2002 N C 133,691 58,671 1,323 838 8,273 423 2018 OTB - Typical 2002 N C 78,205 58,671 1,323 838 8,273 423 2018 OTW - Typical 2002

SC 203,978 56,329 5,958 4,449 12,900 1,187 2002 OTB - Typical 2002 SC 163,560 53,746 556 1,633 12,945 1,187 2009 OTB - Typical 2002 SC 143,492 53,746 556 1,633 12,945 1,187 2009 OTW - Typical 2002 SC 178,938 60,300 643 1,195 13,517 1,187 2018 OTB - Typical 2002 SC 152,457 60,300 643 1,195 13,517 1,187 2018 OTW - Typical 2002

TN 325,779 90,374 9,184 10,413 29,897 59 2002 OTB - Typical 2002 TN 436,453 85,275 831 5,649 29,787 59 2009 OTB - Typical 2002 TN 279,931 85,275 831 5,649 29,787 59 2009 OTW - Typical 2002 TN 323,654 92,396 944 5,205 31,047 59 2018 OTB - Typical 2002 TN 103,602 92,396 944 5,205 31,047 59 2018 OTW - Typical 2002

VA 234,714 68,038 7,218 8,796 9,510 99 2002 OTB - Typical 2002 VA 220,686 76,081 900 2,248 10,619 99 2009 OTB - Typical 2002 VA 140,665 76,081 900 2,248 10,619 99 2009 OTW - Typical 2002 VA 181,338 85,351 1,059 1,217 11,479 99 2018 OTB - Typical 2002 VA 115,987 85,351 1,059 1,217 11,479 99 2018 OTW - Typical 2002

WV 497,991 54,045 2,489 2,305 11,667 16 2002 OTB - Typical 2002 WV 598,555 54,701 227 392 12,156 16 2009 OTB - Typical 2002 WV 246,851 54,701 227 392 12,156 16 2009 OTW - Typical 2002 WV 482,959 60,141 255 56 13,450 16 2018 OTB - Typical 2002 WV 111,937 60,141 255 56 13,450 16 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.217Annual VOC Emissions by Source Sector0200,000400,000600,000800,0001,000,0001,200,0001,400,000 A L F L G A K Y M S N C S C T N V A W V

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

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### Annual VOC Emissions by Source Sector

Name EGU NONEGU ONROAD NONROAD AREA FIRES YEAR Basis 1,501 47,893 119,790 44,978 196,538 26,526 2002 OTB - Typical 2002 1,261 47,600 72,848 35,498 157,405 26,526 2009 OTB - Typical 2002 AL 1,312 47,600 72,848 35,498 157,405 26,526 2009 OTW - Typical 2002 1,574 55,373 47,296 26,338 168,507 26,526 2018 OTB - Typical 2002 1,612 55,373 47,296 26,338 168,507 26,526 2018 OTW - Typical 2002

2,362 36,301 495,225 201,960 439,019 51,527 2002 OTB - Typical 2002 1,562 39,255 323,290 144,749 462,198 51,527 2009 OTB - Typical 2002 FL 1,559 39,255 323,290 144,749 462,198 51,527 2009 OTW - Typical 2002 2,052 46,049 216,620 128,131 533,141 51,527 2018 OTB - Typical 2002 1,988 46,049 216,620 128,131 533,141 51,527 2018 OTW - Typical 2002

984 33,753 267,378 63,337 309,411 33,918 2002 OTB - Typical 2002 1,497 34,153 184,239 46,722 294,204 33,918 2009 OTB - Typical 2002 GA 1,499 34,153 184,239 46,722 294,204 33,918 2009 OTW - Typical 2002 1,794 40,354 105,507 36,014 342,661 33,918 2018 OTB - Typical 2002 1,790 40,354 105,507 36,014 342,661 33,918 2018 OTW - Typical 2002

1,518 44,854 98,311 34,156 100,174 3,338 2002 OTB - Typical 2002 1,594 47,733 63,258 23,980 94,253 3,338 2009 OTB - Typical 2002 KY 1,580 47,733 63,258 23,980 94,253 3,338 2009 OTW - Typical 2002 1,635 55,729 39,084 20,795 102,117 3,338 2018 OTB - Typical 2002 1,616 55,729 39,084 20,795 102,117 3,338 2018 OTW - Typical 2002

696 43,401 82,810 32,401 135,106 13,625 2002 OTB - Typical 2002 584 38,119 49,670 27,650 125,382 13,625 2009 OTB - Typical 2002 MS 590 38,119 49,670 27,650 125,382 13,625 2009 OTW - Typical 2002 766 45,966 30,734 20,576 139,419 13,625 2018 OTB - Typical 2002 827 45,966 30,734 20,576 139,419 13,625 2018 OTW - Typical 2002

1,043 72,856 253,374 71,378 346,060 12,499 2002 OTB - Typical 2002 1,100 70,146 163,803 52,430 252,553 12,499 2009 OTB - Typical 2002 NC 1,093 70,146 163,803 52,430 252,553 12,499 2009 OTW - Typical 2002 1,183 75,985 88,620 40,576 234,207 12,499 2018 OTB - Typical 2002 1,172 75,985 88,620 40,576 234,207 12,499 2018 OTW - Typical 2002

438 38,493 106,792 41,374 187,466 14,666 2002 OTB - Typical 2002 601 36,410 67,281 30,531 176,104 14,666 2009 OTB - Typical 2002 SC 626 36,410 67,281 30,531 176,104 14,666 2009 OTW - Typical 2002 745 44,586 44,700 24,989 196,946 14,666 2018 OTB - Typical 2002 754 44,586 44,700 24,989 196,946 14,666 2018 OTW - Typical 2002

819 87,975 169,914 49,056 161,069 5,153 2002 OTB - Typical 2002 866 89,128 108,200 38,686 160,265 5,153 2009 OTB - Typical 2002 TN 854 89,128 108,200 38,686 160,265 5,153 2009 OTW - Typical 2002 899 111,372 64,665 28,667 188,977 5,153 2018 OTB - Typical 2002 826 111,372 64,665 28,667 188,977 5,153 2018 OTW - Typical 2002

672 42,589 144,684 57,050 129,792 912 2002 OTB - Typical 2002 546 44,359 89,678 40,897 120,022 912 2009 OTB - Typical 2002 VA 503 44,359 89,678 40,897 120,022 912 2009 OTW - Typical 2002 694 53,968 60,454 34,412 128,160 912 2018 OTB - Typical 2002 674 53,968 60,454 34,412 128,160 912 2018 OTW - Typical 2002

1,128 14,599 40,066 14,805 61,490 2,184 2002 OTB - Typical 2002 1,442 14,015 23,907 14,249 57,082 2,184 2009 OTB - Typical 2002 WV 1,397 14,015 23,907 14,249 57,082 2,184 2009 OTW - Typical 2002 1,471 16,636 15,463 9,500 62,164 2,184 2018 OTB - Typical 2002 1,456 16,636 15,463 9,500 62,164 2,184 2018 OTW - Typical 2002Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX B:

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

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### State VMT Totals

Million Miles Per Year

2002 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL AL 31,982 12,728 4,347 1,630 63 69 4,709 196 55,723 FL 105,340 40,835 13,945 5,079 206 220 12,465 591 178,681 GA 61,660 24,394 8,331 3,103 121 132 8,673 371 106,785 KY 28,751 12,189 3,366 1,606 55 55 4,827 171 51,020 MS 23,933 6,724 439 1,025 330 125 3,610 92 36,278 NC 51,189 30,339 10,787 4,119 230 230 9,440 461 106,795 SC 26,672 10,750 3,671 1,395 52 58 4,306 171 47,074 TN 30,809 20,272 6,922 2,943 52 111 6,810 397 68,316 VA 36,336 24,784 8,667 2,148 61 139 4,969 369 77,472 WV 9,010 5,931 2,028 732 25 37 1,664 117 19,544

2009 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL AL 30,638 18,598 5,511 2,069 65 72 5,976 249 63,178 FL 107,641 62,449 18,697 6,820 215 230 16,743 794 213,590 GA 61,569 36,641 10,933 4,077 126 137 11,374 487 125,343 KY 28,006 16,984 4,428 1,983 58 57 5,983 231 57,729 MS 23,641 10,131 573 1,341 356 135 4,719 120 41,017 NC 48,495 43,484 15,122 4,576 40 224 10,928 527 123,396 SC 26,451 16,119 4,796 1,824 55 61 5,617 223 55,147 TN 28,775 28,650 8,521 3,627 52 111 8,391 490 78,615 VA 33,663 34,814 10,597 2,624 61 137 6,073 451 88,419 WV 8,128 8,205 2,427 878 25 37 1,995 140 21,835

2018 LDGV LDGT1 LDGT2 HDDV LDDV LDDT HDDV MC TOTAL AL 31,706 23,562 6,990 2,634 67 84 7,607 317 72,966 FL 116,576 83,385 24,996 9,156 221 301 22,491 1,066 258,191 GA 65,214 47,687 14,245 5,332 129 171 14,853 637 148,269 KY 29,353 21,058 5,558 2,463 60 66 7,454 288 66,300 MS 24,787 12,984 736 1,727 372 159 6,076 155 46,996 NC 42,247 51,568 18,260 4,985 279 279 11,396 553 129,566 SC 27,930 20,880 6,220 2,375 57 75 7,306 290 65,133 TN 29,253 35,702 10,629 4,538 52 130 10,500 613 91,417 VA 35,030 44,438 13,543 3,358 62 164 7,770 578 104,944 WV 8,130 10,025 2,969 1,078 25 41 2,451 172 24,891Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### APPENDIX C:

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

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC AL 2002 01 FUEL COMB. ELEC. UTIL. 11,460 239 154,704 7,845 4,176 423,736 2,288 AL 2002 02 FUEL COMB. INDUSTRIAL 67,121 234 51,527 6,729 3,791 40,918 2,237 AL 2002 03 FUEL COMB. OTHER 70, 498 169 19,237 6,411 5,528 39,606 56,120 AL 2002 04 CHEMICAL & ALLIED PRODUCT 5,721 35 2,032 1,220 888 12,770 7,273 AL 2002 05 METALS PROCESSING 38,247 376 6,011 9,107 7,803 14,039 3,299 AL 2002 06 PETROLEUM & RELATED 13,606 0 878 194 155 22,991 4,024 AL 2002 07 OTHER INDUSTRIAL PROCESSE S 47,676 1,468 25,252 22, 689 9,516 17,904 25,304 AL 2002 08 SOLVENT UTILIZATION 216 0 226 149 126 3 108,437 AL 2002 09 STORAGE & TRANSPORT 174 0 230 1,086 636 13 16,522 AL 2002 10 WASTE DISPOSAL & RECYCL ING 86,302 10 3,465 13,960 13,073 489 11,334 AL 2002 11 HIGHWAY VEHICLES 1,366, 056 5,576 158,423 3,898 2,794 6,885 119,790 AL 2002 12 OFF-HIGHWAY 414,385 33 65,366 4,787 4,502 7,584 60,487 AL 2002 14 MISCELLANEOUS 442,778 59,864 9,343 408,115 79,127 2,559 21,686 2002 Total 2,564,239 68,005 496, 695 486,190 132,115 589,499 438,800

AL 2009 01 FUEL COMB. ELEC. UTIL. 14,986 359 82,305 6,969 3,921 378,052 2,473 AL 2009 02 FUEL COMB. INDUSTRIAL 68,146 274 36,301 6,140 3,438 40,651 2,191 AL 2009 03 FUEL COMB. OTHER 52, 256 158 19,514 5,904 5,104 36,048 31,403 AL 2009 04 CHEMICAL & ALLIED PRODUCT 6,118 38 2,273 1,257 912 13,660 6,613 AL 2009 05 METALS PROCESSING 38,969 500 6,021 9,062 7,756 16,629 3,305 AL 2009 06 PETROLEUM & RELATED 13,241 0 858 221 177 22,495 3,336 AL 2009 07 OTHER INDUSTRIAL PROCESSE S 52,004 1,571 26,340 24, 196 10,197 19,383 26,519 AL 2009 08 SOLVENT UTILIZATION 247 0 257 165 139 4 92,631 AL 2009 09 STORAGE & TRANSPORT 192 0 253 1,146 584 14 17,738 AL 2009 10 WASTE DISPOSAL & RECYCL ING 87,225 11 3,634 14,504 13,485 590 11,207 AL 2009 11 HIGHWAY VEHICLES 942, 793 6,350 101,323 3,188 2,049 635 72,848 AL 2009 12 OFF-HIGHWAY 454,686 36 56,862 4,027 3,776 3,471 50,249 AL 2009 14 MISCELLANEOUS 463,498 65,899 9,788 428,698 82,679 2,681 22,657 2009 Total 2,194,361 75,195 345, 729 505,475 134,217 534,314 343,169

AL 2018 01 FUEL COMB. ELEC. UTIL. 24,342 1,072 64,358 7,822 4,768 305,262 2,952 AL 2018 02 FUEL COMB. INDUSTRIAL 69,198 275 38,781 6,462 3,613 43,170 2,295 AL 2018 03 FUEL COMB. OTHER 43, 744 164 20,185 5,641 4,818 37,162 21,215 AL 2018 04 CHEMICAL & ALLIED PRODUCT 7,384 46 2,804 1,523 1,106 16,509 8,040 AL 2018 05 METALS PROCESSING 49,770 674 7,519 11,036 9,423 21,824 4,234 AL 2018 06 PETROLEUM & RELATED 13,002 0 848 258 207 22,242 3,421 AL 2018 07 OTHER INDUSTRIAL PROCESSE S 60,452 1,732 30,831 27, 727 11,812 21,843 30,267 AL 2018 08 SOLVENT UTILIZATION 301 0 317 200 169 4 112,412 AL 2018 09 STORAGE & TRANSPORT 234 0 307 1,366 699 17 18,900 AL 2018 10 WASTE DISPOSAL & RECYCL ING 88,758 13 3,867 15,343 14,143 718 11,938 AL 2018 11 HIGHWAY VEHICLES 797, 966 7,296 46,222 2,488 1,262 720 47,296 AL 2018 12 OFF-HIGHWAY 488,924 42 43,799 3,041 2,835 2,818 40,407 AL 2018 14 MISCELLANEOUS 464,235 73,529 9,803 458,551 85,538 2,686 22,686 2018 Total 2,108,311 84,843 269, 643 541,458 140,394 474,974 326,063Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC FL 2002 01 FUEL COMB. ELEC. UTIL. 55,899 222 282,507 21,391 15,575 483,590 2,531 FL 2002 02 FUEL COMB. INDUSTRIAL 64,794 131 45,153 20,442 18,547 42,524 4,219 FL 2002 03 FUEL COMB. OTHER 49, 230 99 11,593 8,464 8,074 20,031 16,123 FL 2002 04 CHEMICAL & ALLIED PRODUCT 745 1,101 2,221 1,868 1,488 34,462 3,542 FL 2002 05 METALS PROCESSING 1,404 1 194 449 334 882 82 FL 2002 06 PETROLEUM & RELATED 1,070 0 560 259 129 470 724 FL 2002 07 OTHER INDUSTRIAL PROCE SSES 18,586 19 12,325 23, 419 11,844 6,515 27,024 FL 2002 08 SOLVENT UTILIZATION 0 0 1 128 110 0 304,582 FL 2002 09 STORAGE & TRANSPORT 161 0 561 1,645 720 38 79,281 FL 2002 10 WASTE DISPOSAL & RECYCL ING 175,989 351 6,123 22,142 21,604 659 17,449 FL 2002 11 HIGHWAY VEHICLES 4,693, 893 18,078 466,098 11,253 7,852 20,872 495,225 FL 2002 12 OFF-HIGHWAY 1,920,729 134 180,627 18,281 17,415 20,614 272,072 FL 2002 14 MISCELLANEOUS 764,337 40,324 15,083 498,855 115,287 4,129 41,274 2002 Total 7,746,839 60,460 1,023,045 628,597 218,979 634,786 1,264,128

FL 2009 01 FUEL COMB. ELEC. UTIL. 35,928 1,631 86,165 9,007 5,910 186,055 1,910 FL 2009 02 FUEL COMB. INDUSTRIAL 69,972 146 44,480 16,265 14,827 38,225 4,473 FL 2009 03 FUEL COMB. OTHER 33, 014 100 10,800 7,555 7,174 19,882 10,907 FL 2009 04 CHEMICAL & ALLIED PRODUCT 901 1,231 2,461 1,908 1,526 34,961 3,821 FL 2009 05 METALS PROCESSING 1,545 1 176 361 251 993 82 FL 2009 06 PETROLEUM & RELATED 1,190 0 612 304 156 519 748 FL 2009 07 OTHER INDUSTRIAL PROCE SSES 18,593 26 13,521 33, 084 19,357 6,881 26,413 FL 2009 08 SOLVENT UTILIZATION 0 0 1 132 113 0 319,723 FL 2009 09 STORAGE & TRANSPORT 187 0 621 1,661 727 50 83,880 FL 2009 10 WASTE DISPOSAL & RECYCL ING 177,953 342 6,251 22,971 22,364 698 17,241 FL 2009 11 HIGHWAY VEHICLES 3,446, 095 21,737 314,307 9,953 6,216 2,120 323,290 FL 2009 12 OFF-HIGHWAY 2,104,920 148 163,794 15,613 14,866 8,967 209,543 FL 2009 14 MISCELLANEOUS 764,004 41,471 15,075 557,331 120,796 4,129 41,290 2009 Total 6,654,301 66,833 658,265 676,145 214,282 303,479 1,043,321

FL 2018 01 FUEL COMB. ELEC. UTIL. 53,772 2,976 73,125 9,953 6,843 132,177 2,376 FL 2018 02 FUEL COMB. INDUSTRIAL 76,847 156 47,835 17,808 16,255 40,443 4,892 FL 2018 03 FUEL COMB. OTHER 27, 094 110 12,344 7,254 6,852 20,975 8,878 FL 2018 04 CHEMICAL & ALLIED PRODUCT 1,200 1,448 3,119 2,367 1,907 41,395 4,739 FL 2018 05 METALS PROCESSING 1,973 2 225 466 323 1,325 106 FL 2018 06 PETROLEUM & RELATED 1,513 0 778 387 198 659 918 FL 2018 07 OTHER INDUSTRIAL PROCE SSES 20,748 35 15,855 39, 871 23,301 7,741 29,716 FL 2018 08 SOLVENT UTILIZATION 0 0 1 158 135 0 387,657 FL 2018 09 STORAGE & TRANSPORT 226 0 690 2,008 879 58 87,732 FL 2018 10 WASTE DISPOSAL & RECYCL ING 180,730 418 6,486 24,140 23,427 769 18,335 FL 2018 11 HIGHWAY VEHICLES 3,086, 330 26,154 154,611 8,489 4,242 2,533 216,620 FL 2018 12 OFF-HIGHWAY 2,323,327 171 127,885 12,497 11,868 7,536 183,452 FL 2018 14 MISCELLANEOUS 763,701 43,251 15,068 628,984 127,364 4,129 41,338 2018 Total 6,537,461 74,720 458, 023 754,381 223,592 259,739 986,760Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC GA 2002 01 FUEL COMB. ELEC. UTIL. 9,650 86 148,126 11,467 5,070 517,633 1,256 GA 2002 02 FUEL COMB. INDUSTRIAL 59,492 27 53,039 12,037 7,886 88,791 3,956 GA 2002 03 FUEL COMB. OTHER 63, 314 17 14,465 10,142 10,057 10,740 27,226 GA 2002 04 CHEMICAL & ALLIED PRODUCT 5,387 920 2,277 391 305 2,721 2,668 GA 2002 05 METALS PROCESSING 330 0 60 147 94 0 70 GA 2002 06 PETROLEUM & RELATED 41 0 3 69 44 68 175 GA 2002 07 OTHER INDUSTRIAL PROCESSE S 27,960 2,666 12,215 39, 630 13,073 8,701 26,999 GA 2002 08 SOLVENT UTILIZATION 4 0 22 13 13 0 234,744 GA 2002 09 STORAGE & TRANSPORT 39 0 6 583 360 0 26,334 GA 2002 10 WASTE DISPOSAL & RECYCL ING 203,892 16 6,872 29,227 28,311 312 18,964 GA 2002 11 HIGHWAY VEHICLES 2,833,468 10,524 308,013 7,236 5,158 12,155 267,378 GA 2002 12 OFF-HIGHWAY 791,158 60 97,961 8,618 8,226 9,005 85,965 GA 2002 14 MISCELLANEOUS 498,622 83, 032 10,279 687,028 116,756 2,815 25,618 2002 Total 4,493,357 97,349 653, 338 806,587 195,354 652,942 721,352

GA 2009 01 FUEL COMB. ELEC. UTIL. 23,721 686 98,497 17,891 10,907 417,449 2,314 GA 2009 02 FUEL COMB. INDUSTRIAL 63,067 28 53,726 11,206 7,390 89,850 4,163 GA 2009 03 FUEL COMB. OTHER 45, 184 17 15,347 8,496 8,400 10,981 15,683 GA 2009 04 CHEMICAL & ALLIED PRODUCT 6,044 1,032 2,531 436 341 2,743 2,814 GA 2009 05 METALS PROCESSING 363 0 61 159 100 0 47 GA 2009 06 PETROLEUM & RELATED 50 0 4 83 54 82 154 GA 2009 07 OTHER INDUSTRIAL PROCESSE S 29,976 2,902 12,528 45, 339 14,758 7,662 28,441 GA 2009 08 SOLVENT UTILIZATION 4 0 25 14 14 0 216,248 GA 2009 09 STORAGE & TRANSPORT 45 0 7 649 401 0 27,821 GA 2009 10 WASTE DISPOSAL & RECYCL ING 218,460 18 7,419 31,955 30,900 360 18,711 GA 2009 11 HIGHWAY VEHICLES 2,053,694 12,660 208,393 6,103 3,869 1,254 184,239 GA 2009 12 OFF-HIGHWAY 882,970 68 85,733 7,521 7,175 2,725 67,686 GA 2009 14 MISCELLANEOUS 515,329 91, 406 10,637 765,043 125,665 2,914 26,388 2009 Total 3,838,907 108,817 494, 908 894,896 209,973 536,020 594,708
GA 2018 01 FUEL COMB. ELEC. UTIL. 44, 476 1,677 75,717 20,909 13,983 230,856 2,841 GA 2018 02 FUEL COMB. INDUSTRIAL 67,067 30 57,232 11,755 7,769 94,403 4,424 GA 2018 03 FUEL COMB. OTHER 39, 440 17 17,801 7,722 7,622 11,958 11,482 GA 2018 04 CHEMICAL & ALLIED PRODUCT 7,076 1,208 2,982 517 405 3,436 3,524 GA 2018 05 METALS PROCESSING 421 0 76 185 118 0 55 GA 2018 06 PETROLEUM & RELATED 63 0 5 105 68 104 191 GA 2018 07 OTHER INDUSTRIAL PROCESSE S 33,611 3,559 14,460 55, 130 17,899 8,748 33,333 GA 2018 08 SOLVENT UTILIZATION 5 0 30 22 22 0 264,326 GA 2018 09 STORAGE & TRANSPORT 54 0 9 764 470 0 29,409 GA 2018 10 WASTE DISPOSAL & RECYCL ING 235,690 22 8,120 35,280 34,038 423 20,411 GA 2018 11 HIGHWAY VEHICLES 1,765,020 14,871 99,821 4,995 2,517 1,458 105,507 GA 2018 12 OFF-HIGHWAY 973,872 79 64,579 6,015 5,730 1,709 56,761 GA 2018 14 MISCELLANEOUS 515,220 102, 075 10,635 859,835 134,730 2,914 26,368 2018 Total 3,682,015 123,537 351,467 1,003,235 225,372 356,010 558,631Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC KY 2002 01 FUEL COMB. ELEC. UTIL. 12,607 321 201,928 4,795 2,847 495,153 1,481 KY 2002 02 FUEL COMB. INDUSTRIAL 14,110 182 60,716 2,155 1,463 41,825 1,566 KY 2002 03 FUEL COMB. OTHER 40,806 55 4,997 7,679 7,352 9,647 12,711 KY 2002 04 CHEMICAL & ALLIED PRODUCT 176 214 296 774 581 2,345 3,462 KY 2002 05 METALS PROCESSING 89,197 6 1,082 3,396 2,720 12,328 1,508 KY 2002 06 PETROLEUM & RELATED 4,304 335 2,519 308 205 5,747 2,895 KY 2002 07 OTHER INDUSTRIAL PROCESSES 6,493 78 6,518 31,429 10,394 3,333 25,388 KY 2002 08 SOLVENT UTILIZATION 0 10 9 317 241 1 61,834 KY 2002 09 STORAGE & TRANSPORT 33 8 15 1,920 1,177 3 18,853 KY 2002 10 WASTE DISPOSAL & RECYCLING 20,622 8 1,768 7,229 6,476 606 7,927 KY 2002 11 HIGHWAY VEHICLES 1,260,682 5,044 154,899 3, 720 2,693 5,974 98,311 KY 2002 12 OFF-HIGHWAY 325,993 31 104,571 6,425 6,046 14,043 44,805 KY 2002 14 MISCELLANEOUS 25,849 51,026 556 197,402 28,291 146 5,238 2002 Total 1,800,871 57,318 539, 873 267,547 70,486 591,151 285,977

KY 2009 01 FUEL COMB. ELEC. UTIL. 15,812 400 92,021 6,463 4,279 290,193 1,369 KY 2009 02 FUEL COMB. INDUSTRIAL 14,986 195 61,683 2,105 1,456 42,433 1,476 KY 2009 03 FUEL COMB. OTHER 30,045 54 5,178 7,035 6,725 10,123 9,148 KY 2009 04 CHEMICAL & ALLIED PRODUCT 179 249 300 851 633 2,384 3,635 KY 2009 05 METALS PROCESSING 99,428 7 1,156 3,246 2,550 13,735 1,772 KY 2009 06 PETROLEUM & RELATED 4,818 377 2,828 344 230 6,460 3,052 KY 2009 07 OTHER INDUSTRIAL PROCESSES 7,212 84 6,674 32,194 10,912 3,634 27,548 KY 2009 08 SOLVENT UTILIZATION 0 10 11 371 283 1 62,595 KY 2009 09 STORAGE & TRANSPORT 38 9 18 2,064 1,268 3 20,038 KY 2009 10 WASTE DISPOSAL & RECYCLING 22,388 9 1,979 7,770 6,925 733 7,725 KY 2009 11 HIGHWAY VEHICLES 942,350 5,795 97,912 3,002 1,941 585 63,258 KY 2009 12 OFF-HIGHWAY 357,800 34 94,752 5,544 5,203 9,180 38,558 KY 2009 14 MISCELLANEOUS 32,627 52,915 702 206,463 29,601 187 6,335 2009 Total 1,527,684 60,137 365, 214 277,453 72,006 379,651 246,509

KY 2018 01 FUEL COMB. ELEC. UTIL. 17,144 476 64,378 6,694 4,434 226,062 1,426 KY 2018 02 FUEL COMB. INDUSTRIAL 15,692 205 64,533 2,203 1,528 43,772 1,555 KY 2018 03 FUEL COMB. OTHER 24,764 53 5,550 6,469 6,169 9,947 7,479 KY 2018 04 CHEMICAL & ALLIED PRODUCT 219 317 367 1,054 781 2,884 4,384 KY 2018 05 METALS PROCESSING 114,470 9 1,508 3,898 3,065 15,800 2,343 KY 2018 06 PETROLEUM & RELATED 5,495 434 3,244 392 262 7,426 3,394 KY 2018 07 OTHER INDUSTRIAL PROCESSES 8,303 93 7,872 35,349 12,377 4,141 31,394 KY 2018 08 SOLVENT UTILIZATION 0 12 14 464 352 1 73,525 KY 2018 09 STORAGE & TRANSPORT 44 10 21 2,408 1,481 4 21,196 KY 2018 10 WASTE DISPOSAL & RECYCLING 24,677 11 2,256 8,481 7,518 894 8,392 KY 2018 11 HIGHWAY VEHICLES 782,423 6,584 42,104 2,283 1,160 651 39,084 KY 2018 12 OFF-HIGHWAY 381,215 40 79,392 4,556 4,256 8,592 30,920 KY 2018 14 MISCELLANEOUS 33,931 55,118 729 218,725 30,626 196 7,254 2018 Total 1,408,378 63,361 271, 967 292,975 74,010 320,369 232,347Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

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### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC MS 2002 01 FUEL COMB. ELEC. UTIL. 5,219 198 40,433 1,706 1,147 60,086 629 MS 2002 02 FUEL COMB. INDUSTRIAL 22,710 28 48,726 5,007 3,634 9,740 8,023 MS 2002 03 FUEL COMB. OTHER 36,752 34 4,502 5,445 5,414 789 22,923 MS 2002 04 CHEMICAL & ALLIED PRODUCT 15,410 361 1,725 849 440 1,663 2,375 MS 2002 05 METALS PROCESSING 1,031 0 115 122 58 36 371 MS 2002 06 PETROLEUM & RELATED 975 20 1,187 790 335 15,560 20,788 MS 2002 07 OTHER INDUSTRIAL PROCESSES 13,884 747 9,219 27,617 8,051 8,866 15,525 MS 2002 08 SOLVENT UTILIZATION 45 7 105 219 178 1 80,760 MS 2002 09 STORAGE & TRANSPORT 74 0 80 124 38 40 23,327 MS 2002 10 WASTE DISPOSAL & RECYCLING 1,414 9 89 447 324 31 886 MS 2002 11 HIGHWAY VEHICLES 894,639 3,577 111,791 2,856 2,109 4,604 82,810 MS 2002 12 OFF-HIGHWAY 236,752 23 88,787 5,010 4,690 11,315 41,081 MS 2002 14 MISCELLANEOUS 14,529 58,746 312 323,622 43,028 84 708 2002 Total 1,243,435 63,753 307, 072 373,815 69,446 112,814 300,206

MS 2009 01 FUEL COMB. ELEC. UTIL. 5,051 334 36,011 4,957 4,777 76,579 404 MS 2009 02 FUEL COMB. INDUSTRIAL 24,607 30 44,095 3,728 2,787 7,388 8,007 MS 2009 03 FUEL COMB. OTHER 26,023 33 4,514 5,278 5,245 751 17,445 MS 2009 04 CHEMICAL & ALLIED PRODUCT 16,141 405 1,955 941 488 1,880 2,614 MS 2009 05 METALS PROCESSING 1,098 0 128 129 62 37 402 MS 2009 06 PETROLEUM & RELATED 1,101 23 1,262 894 379 7,926 13,317 MS 2009 07 OTHER INDUSTRIAL PROCESSES 14,181 197 8,376 31,381 8,629 8,254 16,282 MS 2009 08 SOLVENT UTILIZATION 50 8 118 239 194 1 80,393 MS 2009 09 STORAGE & TRANSPORT 92 0 100 172 59 49 23,494 MS 2009 10 WASTE DISPOSAL & RECYCLING 1,486 10 95 473 339 32 743 MS 2009 11 HIGHWAY VEHICLES 628,151 4,026 69,949 2,290 1,522 397 49,670 MS 2009 12 OFF-HIGHWAY 257,453 25 80,567 4,270 3,985 7,191 36,197 MS 2009 14 MISCELLANEOUS 48,314 63,886 1,037 337,018 46,695 283 2,295 2009 Total 1,023,747 68,978 248, 207 391,770 75,160 110,767 251,261

MS 2018 01 FUEL COMB. ELEC. UTIL. 15,282 827 10,271 7,187 7,033 15,146 1,114 MS 2018 02 FUEL COMB. INDUSTRIAL 27,056 33 46,929 4,093 3,058 8,169 8,559 MS 2018 03 FUEL COMB. OTHER 20,900 32 4,767 4,964 4,928 726 14,670 MS 2018 04 CHEMICAL & ALLIED PRODUCT 20,175 475 2,337 1,132 588 2,242 3,290 MS 2018 05 METALS PROCESSING 1,357 0 167 160 79 48 461 MS 2018 06 PETROLEUM & RELATED 1,267 26 1,438 1,010 430 19,028 14,407 MS 2018 07 OTHER INDUSTRIAL PROCESSES 16,267 216 9,996 38,494 10,494 9,657 20,301 MS 2018 08 SOLVENT UTILIZATION 60 9 141 301 244 1 98,354 MS 2018 09 STORAGE & TRANSPORT 115 0 124 210 73 62 24,537 MS 2018 10 WASTE DISPOSAL & RECYCLING 1,638 12 114 533 372 34 870 MS 2018 11 HIGHWAY VEHICLES 528,898 4,565 29,717 1,688 876 441 30,734 MS 2018 12 OFF-HIGHWAY 270,726 29 68,252 3,452 3,203 6,638 28,842 MS 2018 14 MISCELLANEOUS 50,160 70,096 1,076 352,321 47,869 294 2,377 2018 Total 953,900 76,320 175,329 415,546 79,246 62,486 248,517Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 227 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC NC 2002 01 FUEL COMB. ELEC. UTIL. 14,074 55 148,809 22,994 16,623 478,488 986 NC 2002 02 FUEL COMB. INDUSTRIAL 23,578 301 48,590 5,596 4,334 33,395 2,540 NC 2002 03 FUEL COMB. OTHER 217,008 2,318 16,460 31,777 26,746 3,971 87,985 NC 2002 04 CHEMICAL & ALLIED PRODUCT 13,952 535 859 866 538 5,736 4,313 NC 2002 05 METALS PROCESSING 5,876 60 201 564 467 1,010 2,512 NC 2002 06 PETROLEUM & RELATED 461 0 174 104 52 283 140 NC 2002 07 OTHER INDUSTRIAL PROCESSES 8,552 480 7,380 25,328 8,924 3,426 18,025 NC 2002 08 SOLVENT UTILIZATION 130 307 229 524 484 26 151,383 NC 2002 09 STORAGE & TRANSPORT 66 46 53 639 354 1 16,120 NC 2002 10 WASTE DISPOSAL & RECYCLING 125,528 247 7,482 2,239 2,218 1,666 15,568 NC 2002 11 HIGHWAY VEHICLES 3,176,811 10,455 341,198 6,905 4,816 13,343 253,374 NC 2002 12 OFF-HIGHWAY 808,231 65 84,284 7,348 7,005 7,693 94,480 NC 2002 14 MISCELLANEOUS 72,673 159,069 1,561 233,551 36,414 423 3,528 2002 Total 4,466,940 173,937 657, 279 338,434 108,975 549,463 650,954

NC 2009 01 FUEL COMB. ELEC. UTIL. 14,942 445 66,517 22,152 15,949 242,286 954 NC 2009 02 FUEL COMB. INDUSTRIAL 24,871 312 38,160 5,159 3,871 30,788 2,509 NC 2009 03 FUEL COMB. OTHER 158,837 2,723 18,441 25,334 19,467 4,060 49,819 NC 2009 04 CHEMICAL & ALLIED PRODUCT 14,732 599 933 981 607 6,286 4,925 NC 2009 05 METALS PROCESSING 6,358 67 207 627 528 1,130 2,790 NC 2009 06 PETROLEUM & RELATED 556 0 212 127 64 349 162 NC 2009 07 OTHER INDUSTRIAL PROCESSES 9,211 507 8,061 28,524 9,788 3,712 18,144 NC 2009 08 SOLVENT UTILIZATION 142 335 246 549 506 28 136,114 NC 2009 09 STORAGE & TRANSPORT 75 51 55 696 380 1 17,367 NC 2009 10 WASTE DISPOSAL & RECYCLING 139,518 307 8,354 2,774 2,750 1,913 17,331 NC 2009 11 HIGHWAY VEHICLES 2,184,901 12,637 207,648 5,861 3,643 1,311 163,803 NC 2009 12 OFF-HIGHWAY 887,605 72 70,997 6,055 5,760 1,892 74,056 NC 2009 14 MISCELLANEOUS 96,825 167,131 2,080 250,912 49,956 566 4,648 2009 Total 3,538,573 185,185 421, 913 349,750 113,268 294,321 492,624

NC 2018 01 FUEL COMB. ELEC. UTIL. 20,223 663 62,346 37,376 29,791 108,492 1,345 NC 2018 02 FUEL COMB. INDUSTRIAL 26,872 341 40,897 5,594 4,222 32,507 2,702 NC 2018 03 FUEL COMB. OTHER 131,365 2,857 20,027 21,847 16,231 4,050 34,104 NC 2018 04 CHEMICAL & ALLIED PRODUCT 18,463 702 1,105 1,175 726 7,414 6,113 NC 2018 05 METALS PROCESSING 7,576 76 255 771 657 1,335 3,516 NC 2018 06 PETROLEUM & RELATED 712 0 272 162 82 448 207 NC 2018 07 OTHER INDUSTRIAL PROCESSES 10,675 559 9,259 34,339 11,601 4,357 20,978 NC 2018 08 SOLVENT UTILIZATION 169 375 277 588 540 31 152,979 NC 2018 09 STORAGE & TRANSPORT 91 59 67 808 430 2 19,511 NC 2018 10 WASTE DISPOSAL & RECYCLING 156,599 387 9,456 3,502 3,474 2,234 19,789 NC 2018 11 HIGHWAY VEHICLES 1,510,848 13,077 81,706 4,299 2,158 1,323 88,620 NC 2018 12 OFF-HIGHWAY 960,709 83 49,046 4,298 4,069 905 61,327 NC 2018 14 MISCELLANEOUS 111,705 177,474 2,399 273,030 54,376 655 5,333 2018 Total 2,956,008 196,655 277, 112 387,788 128,356 163,752 416,523Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 228 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC SC 2002 01 FUEL COMB. ELEC. UTIL. 6,969 141 88,528 21,827 17,521 210,272 470 SC 2002 02 FUEL COMB. INDUSTRIAL 31,771 97 38,081 5,308 3,641 44,958 1,338 SC 2002 03 FUEL COMB. OTHER 75,800 65 4,367 6,261 6,166 4,318 49,171 SC 2002 04 CHEMICAL & ALLIED PRODUCT 2,526 173 25 501 318 59 8,784 SC 2002 05 METALS PROCESSING 13,833 0 450 639 408 4,160 660 SC 2002 06 PETROLEUM & RELATED 248 0 283 120 71 170 114 SC 2002 07 OTHER INDUSTRIAL PROCESSES 9,502 1,237 15,145 15,224 6,981 12,128 16,342 SC 2002 08 SOLVENT UTILIZATION 0 1 1 78 60 0 88,878 SC 2002 09 STORAGE & TRANSPORT 10 0 4 1,025 626 0 21,009 SC 2002 10 WASTE DISPOSAL & RECYCLING 67,908 10 4,063 9,172 8,641 625 15,291 SC 2002 11 HIGHWAY VEHICLES 1,275,161 4,684 140,428 3,446 2,496 5,958 106,792 SC 2002 12 OFF-HIGHWAY 413,964 33 50,249 4,152 3,945 4,866 55,016 SC 2002 14 MISCELLANEOUS 221,436 28,903 4,335 262,974 47,136 1,187 12,535 2002 Total 2,119,129 35,343 345, 960 330,728 98,009 288,701 376,401

SC 2009 01 FUEL COMB. ELEC. UTIL. 11,135 343 46,915 19,395 16,042 124,608 660 SC 2009 02 FUEL COMB. INDUSTRIAL 33,201 105 35,660 3,307 2,370 37,792 1,414 SC 2009 03 FUEL COMB. OTHER 49,914 63 4,551 5,264 5,183 4,359 25,073 SC 2009 04 CHEMICAL & ALLIED PRODUCT 2,798 173 26 543 345 60 7,409 SC 2009 05 METALS PROCESSING 15,632 0 449 631 378 4,856 663 SC 2009 06 PETROLEUM & RELATED 302 0 340 145 86 200 131 SC 2009 07 OTHER INDUSTRIAL PROCESSES 10,241 1,403 15,069 18,267 8,045 13,443 15,697 SC 2009 08 SOLVENT UTILIZATION 1 1 1 90 69 0 95,538 SC 2009 09 STORAGE & TRANSPORT 13 0 5 569 352 0 21,989 SC 2009 10 WASTE DISPOSAL & RECYCLING 70,379 11 4,215 9,526 8,977 666 15,998 SC 2009 11 HIGHWAY VEHICLES 912,280 5,510 91,696 2,878 1,870 556 67,281 SC 2009 12 OFF-HIGHWAY 448,625 36 43,235 3,471 3,294 1,701 43,061 SC 2009 14 MISCELLANEOUS 250,690 31,416 4,962 282,480 51,151 1,359 13,906 2009 Total 1,805,210 39,061 247, 124 346,565 98,163 189,601 308,820

SC 2018 01 FUEL COMB. ELEC. UTIL. 14,786 617 51,456 28,826 25,032 93,274 906 SC 2018 02 FUEL COMB. INDUSTRIAL 36,105 113 37,333 4,037 2,855 39,714 1,525 SC 2018 03 FUEL COMB. OTHER 39,627 65 5,135 4,791 4,711 4,469 16,391 SC 2018 04 CHEMICAL & ALLIED PRODUCT 3,296 212 32 664 423 74 9,107 SC 2018 05 METALS PROCESSING 18,853 0 587 773 476 5,920 868 SC 2018 06 PETROLEUM & RELATED 389 0 438 186 110 258 166 SC 2018 07 OTHER INDUSTRIAL PROCESSES 12,136 1,566 17,507 20,215 9,044 15,863 18,636 SC 2018 08 SOLVENT UTILIZATION 1 1 1 116 89 0 120,433 SC 2018 09 STORAGE & TRANSPORT 16 0 6 1,380 842 0 22,742 SC 2018 10 WASTE DISPOSAL & RECYCLING 73,403 13 4,512 10,038 9,443 735 17,167 SC 2018 11 HIGHWAY VEHICLES 800,619 6,472 42,354 2,258 1,154 643 44,700 SC 2018 12 OFF-HIGHWAY 481,332 41 31,758 2,617 2,474 1,198 36,131 SC 2018 14 MISCELLANEOUS 250,637 34,345 4,961 306,342 53,367 1,359 13,896 2018 Total 1,731,198 43,446 196,081 382,244 110,019 163,509 302,665Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 229 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC TN 2002 01 FUEL COMB. ELEC. UTIL. 6,787 197 152,137 13,866 11,491 320,146 890 TN 2002 02 FUEL COMB. INDUSTRIAL 15,257 6 44,510 8,015 6,649 74,146 2,021 TN 2002 03 FUEL COMB. OTHER 77,857 25 15,568 7,967 7,549 16,253 18,346 TN 2002 04 CHEMICAL & ALLIED PRODUCT 36,920 1,518 1,772 3,246 2,201 6,516 24,047 TN 2002 05 METALS PROCESSING 41,371 14 1,182 7,620 7,030 5,818 6,898 TN 2002 06 PETROLEUM & RELATED 543 0 331 314 243 383 1,850 TN 2002 07 OTHER INDUSTRIAL PROCESSES 9,420 44 11,794 30,484 12,867 5,845 27,336 TN 2002 08 SOLVENT UTILIZATION 275 1 5,066 2,103 1,818 58 110,872 TN 2002 09 STORAGE & TRANSPORT 22 24 105 1,249 736 134 21,962 TN 2002 10 WASTE DISPOSAL & RECYCLING 22,143 31 1,839 7,068 6,469 349 15,505 TN 2002 11 HIGHWAY VEHICLES 1,967,658 6,616 233,324 5,338 3,919 9,184 169,914 TN 2002 12 OFF-HIGHWAY 505,163 43 96,827 6,819 6,458 10,441 66,450 TN 2002 14 MISCELLANEOUS 10,824 34,318 225 180,006 25,193 60 2,252 2002 Total 2,694,242 42,836 564, 680 274,095 92,622 449,332 468,342

TN 2009 01 FUEL COMB. ELEC. UTIL. 7,214 227 66,405 15,608 13,092 255,410 932 TN 2009 02 FUEL COMB. INDUSTRIAL 15,943 7 37,369 7,195 6,004 63,511 1,915 TN 2009 03 FUEL COMB. OTHER 61,443 27 14,793 7,134 6,786 16,955 12,781 TN 2009 04 CHEMICAL & ALLIED PRODUCT 35,440 1,719 1,958 3,519 2,400 7,056 15,594 TN 2009 05 METALS PROCESSING 45,183 15 1,245 7,337 6,823 6,537 7,676 TN 2009 06 PETROLEUM & RELATED 615 0 373 356 276 435 1,433 TN 2009 07 OTHER INDUSTRIAL PROCESSES 9,911 62 12,635 32,661 13,737 6,240 28,598 TN 2009 08 SOLVENT UTILIZATION 309 1 5,984 2,431 2,095 65 112,312 TN 2009 09 STORAGE & TRANSPORT 26 31 12 1,218 733 42 23,687 TN 2009 10 WASTE DISPOSAL & RECYCLING 23,810 35 1,993 7,618 6,968 393 14,922 TN 2009 11 HIGHWAY VEHICLES 1,361,408 7,738 147,757 4,238 2,782 831 108,200 TN 2009 12 OFF-HIGHWAY 554,121 48 86,641 5,877 5,557 5,651 55,358 TN 2009 14 MISCELLANEOUS 17,921 35,200 379 192,464 26,830 102 2,814 2009 Total 2,133,342 45,108 377, 545 287,655 94,083 363,228 386,222

TN 2018 01 FUEL COMB. ELEC. UTIL. 7,723 241 31,715 15,941 13,387 112,672 976 TN 2018 02 FUEL COMB. INDUSTRIAL 17,038 7 38,908 7,693 6,447 65,823 2,054 TN 2018 03 FUEL COMB. OTHER 54,486 30 15,503 6,757 6,412 18,091 10,269 TN 2018 04 CHEMICAL & ALLIED PRODUCT 45,455 2,053 2,424 4,443 3,044 9,088 20,071 TN 2018 05 METALS PROCESSING 52,834 17 1,589 9,579 8,953 7,790 9,956 TN 2018 06 PETROLEUM & RELATED 715 0 430 416 324 508 1,636 TN 2018 07 OTHER INDUSTRIAL PROCESSES 10,946 88 14,157 38,250 16,286 7,286 35,587 TN 2018 08 SOLVENT UTILIZATION 380 1 7,675 3,155 2,718 79 140,793 TN 2018 09 STORAGE & TRANSPORT 33 41 14 1,572 939 49 25,493 TN 2018 10 WASTE DISPOSAL & RECYCLING 26,712 42 2,326 8,562 7,828 468 17,530 TN 2018 11 HIGHWAY VEHICLES 1,150,516 8,962 65,242 3,199 1,643 944 64,665 TN 2018 12 OFF-HIGHWAY 593,100 55 70,226 4,672 4,403 5,207 45,084 TN 2018 14 MISCELLANEOUS 19,210 36,213 408 209,058 28,209 111 3,293 2018 Total 1,979,148 47,749 250, 619 313,294 100,592 228,116 377,408Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 230 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC VA 2002 01 FUEL COMB. ELEC. UTIL. 6,797 130 85,081 3,892 2,650 233,691 747 VA 2002 02 FUEL COMB. INDUSTRIAL 64,386 100 75,807 18,480 8,453 137,448 5,332 VA 2002 03 FUEL COMB. OTHER 98,788 13 15,648 11,572 11,236 5,508 54,496 VA 2002 04 CHEMICAL & ALLIED PRODUCT 321 2,158 8,062 449 393 2,126 1,530 VA 2002 05 METALS PROCESSING 3,580 0 937 1,575 1,349 5,251 513 VA 2002 06 PETROLEUM & RELATED 23,384 0 182 255 153 170 501 VA 2002 07 OTHER INDUSTRIAL PROCESSES 12,002 726 9,279 33,409 9,795 17,702 13,086 VA 2002 08 SOLVENT UTILIZATION 0 4 0 225 210 2 111,511 VA 2002 09 STORAGE & TRANSPORT 16 7 11 745 505 0 26,121 VA 2002 10 WASTE DISPOSAL & RECYCLING 16,566 109 1,866 3,152 1,277 1,581 4,065 VA 2002 11 HIGHWAY VEHICLES 2,170,508 7,837 219,602 4,537 3,090 7,218 144,684 VA 2002 12 OFF-HIGHWAY 660,105 48 63,219 8,728 8,288 8,663 74,866 VA 2002 14 MISCELLANEOUS 13,225 43,948 285 182,193 21,835 74 706 2002 Total 3,069,678 55,080 479, 980 269,212 69,233 419,436 438,158

VA 2009 01 FUEL COMB. ELEC. UTIL. 12,509 694 66,219 5,508 4,067 225,653 778 VA 2009 02 FUEL COMB. INDUSTRIAL 67,422 105 67,263 18,346 8,345 135,612 5,483 VA 2009 03 FUEL COMB. OTHER 66,037 14 15,966 10,062 9,742 5,258 28,063 VA 2009 04 CHEMICAL & ALLIED PRODUCT 286 2,082 7,790 477 413 1,996 1,419 VA 2009 05 METALS PROCESSING 3,397 0 827 1,563 1,332 4,813 390 VA 2009 06 PETROLEUM & RELATED 26,288 0 197 275 169 187 557 VA 2009 07 OTHER INDUSTRIAL PROCESSES 12,471 733 9,425 33,961 9,984 18,871 13,394 VA 2009 08 SOLVENT UTILIZATION 0 5 0 248 231 3 110,127 VA 2009 09 STORAGE & TRANSPORT 17 7 12 797 544 0 26,456 VA 2009 10 WASTE DISPOSAL & RECYCLING 20,109 119 2,174 3,823 1,515 1,805 4,789 VA 2009 11 HIGHWAY VEHICLES 1,495,771 9,066 133,170 3,760 2,254 900 89,678 VA 2009 12 OFF-HIGHWAY 726,815 53 54,993 7,510 7,136 1,707 57,009 VA 2009 14 MISCELLANEOUS 21,582 46,719 464 198,040 23,990 124 1,077 2009 Total 2,452,703 59,596 358, 500 284,369 69,721 396,929 339,219

VA 2018 01 FUEL COMB. ELEC. UTIL. 15,420 622 75,594 13,775 11,976 140,233 997 VA 2018 02 FUEL COMB. INDUSTRIAL 72,218 114 70,343 19,248 8,892 140,995 5,861 VA 2018 03 FUEL COMB. OTHER 53,171 14 17,852 9,427 9,086 5,369 18,603 VA 2018 04 CHEMICAL & ALLIED PRODUCT 338 2,462 9,211 579 502 2,291 1,708 VA 2018 05 METALS PROCESSING 4,034 0 1,017 1,861 1,592 5,948 469 VA 2018 06 PETROLEUM & RELATED 30,284 0 228 315 194 217 642 VA 2018 07 OTHER INDUSTRIAL PROCESSES 14,029 877 10,836 37,553 11,276 21,294 15,636 VA 2018 08 SOLVENT UTILIZATION 0 6 0 314 293 3 127,953 VA 2018 09 STORAGE & TRANSPORT 21 8 15 949 648 0 27,357 VA 2018 10 WASTE DISPOSAL & RECYCLING 24,293 141 2,595 4,694 1,828 2,171 5,821 VA 2018 11 HIGHWAY VEHICLES 1,310,698 10,757 61,881 3,343 1,641 1,059 60,454 VA 2018 12 OFF-HIGHWAY 797,683 61 40,393 6,208 5,891 507 49,052 VA 2018 14 MISCELLANEOUS 27,223 50,279 584 218,141 26,225 158 1,322 2018 Total 2,349,413 65,342 290, 549 316,406 80,044 320,246 315,875Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 231 

### State Tier 1 Emission Totals

State Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC WV 2002 01 FUEL COMB. ELEC. UTIL. 10,117 121 222,437 4,472 2,163 500,381 1,140 WV 2002 02 FUEL COMB. INDUSTRIAL 8,685 97 33,831 1,583 1,332 37,118 1,097 WV 2002 03 FUEL COMB. OTHER 29, 480 13 15,220 3,814 3,683 3,990 9,275

WV 2002 04 CHEMICAL & ALLIED PRODUCT MFG 50,835 80 1,627 950 831 9,052 5,755

WV 2002 05 METALS PROCESSING 28,837 143 1,570 8,749 7,515 5,619 1,393

WV 2002 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,086 475 475 7,550 2,163

WV 2002 07 OTHER INDUSTRIAL PROCE SSES 2,003 56 5,347 18, 751 5,567 2,316 1,803 WV 2002 08 SOLVENT UTILIZATION 15 0 18 49 44 0 35,989 WV 2002 09 STORAGE & TRANSPORT 15 0 3 1,952 947 0 12,432 WV 2002 10 WASTE DISPOSAL & RECYCLING 9,395 8 599 4,153 3,731 100 5,098 WV 2002 11 HIGHWAY VEHICLES 560, 717 1,933 59,612 1,395 1,003 2,489 40,066 WV 2002 12 OFF-HIGHWAY 133,113 9 33,239 1,850 1,728 2,112 18,566 WV 2002 14 MISCELLANEOUS 2,811 9,909 61 92,633 10,458 16 157 2002 Total 836,024 12,371 374,650 140,825 39,478 570,742 134,936
WV 2009 01 FUEL COMB. ELEC. UTIL. 11,493 330 86,328 5,657 2,940 277,489 1,361 WV 2009 02 FUEL COMB. INDUSTRIAL 9,296 104 27,094 1,415 1,220 36,912 998 WV 2009 03 FUEL COMB. OTHER 21, 558 13 14,229 3,351 3,216 4,047 6,824

WV 2009 04 CHEMICAL & ALLIED PRODUCT MFG 58,271 82 1,804 987 864 10,166 5,426

WV 2009 05 METALS PROCESSING 30,939 142 1,517 7,985 6,724 5,971 1,380

WV 2009 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,221 535 535 8,495 2,172

WV 2009 07 OTHER INDUSTRIAL PROCE SSES 2,288 59 4,995 19, 228 5,899 2,570 2,064 WV 2009 08 SOLVENT UTILIZATION 17 0 20 52 47 0 32,305 WV 2009 09 STORAGE & TRANSPORT 17 0 3 2,062 1,003 0 12,997 WV 2009 10 WASTE DISPOSAL & RECYCLING 9,131 8 583 4,050 3,632 97 4,898 WV 2009 11 HIGHWAY VEHICLES 385,994 2,183 36,049 1,096 703 227 23,907 WV 2009 12 OFF-HIGHWAY 152,862 11 30,133 1,640 1,528 359 18,069 WV 2009 14 MISCELLANEOUS 4,116 10,574 89 92,900 10,624 23 219 2009 Total 685,983 13,508 204,064 140,956 38,933 346,356 112,621
WV 2018 01 FUEL COMB. ELEC. UTIL. 11,961 180 51,241 6,349 3,648 115,324 1,387 WV 2018 02 FUEL COMB. INDUSTRIAL 9,917 111 28,710 1,493 1,290 38,531 1,072 WV 2018 03 FUEL COMB. OTHER 18, 891 16 17,254 3,160 3,024 4,065 6,270

WV 2018 04 CHEMICAL & ALLIED PRODUCT MFG 70,252 99 2,183 1,188 1,041 12,280 6,560

WV 2018 05 METALS PROCESSING 36,850 183 2,061 10,944 9,372 7,182 1,790

WV 2018 06 PETROLEUM & RELATED INDUSTRIES 1 0 1,407 616 616 9,786 2,338

WV 2018 07 OTHER INDUSTRIAL PROCE SSES 2,756 68 5,949 21, 347 6,794 3,101 2,561 WV 2018 08 SOLVENT UTILIZATION 20 0 24 61 55 0 38,023 WV 2018 09 STORAGE & TRANSPORT 19 0 4 2,522 1,225 0 13,394 WV 2018 10 WASTE DISPOSAL & RECYCLING 9,237 10 592 4,134 3,692 98 5,272 WV 2018 11 HIGHWAY VEHICLES 319,030 2,484 16,274 844 428 255 15,463 WV 2018 12 OFF-HIGHWAY 167,424 13 25,710 1,292 1,198 56 14,086 WV 2018 14 MISCELLANEOUS 5,175 11,453 112 98,307 11,316 29 268 2018 Total 651,532 14,617 151,521 152,256 43,699 190,706 108,484

CO NH3 NOX PM10 PM2.5 SO2 VOC VISTAS 2002 31,034,756 666,451 5,442,572 3,916,030 1,094,698 4,858,865 5,079,25 VISTAS 2009 25,854,812 722,418 3,721,469 4,155,033 1,119,806 3,454,666 4,118,4 7 VISTAS 2018 24,357,364 790,588 2,692,309 4,559,582 1,205,324 2,539,907 3,873,2 7Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 232 

### APPENDIX D:

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

MACTEC, Inc. 233 

### VISTAS Tier 1 Emission Totals

Year TIER1 TIER 1 NAME CO NH3 NOX PM10 PM2.5 SO2 VOC

2002 01 FUEL COMB. ELEC. UTIL. 139,579 1, 710 1,524,690 114,256 79, 263 3,723,175 12,417

2002 02 FUEL COMB. INDUSTRIAL 371, 905 1,204 499,981 85,353 59,731 550,864 32,330

2002 03 FUEL COMB. OTHER 759,534 2,810 122,058 99,532 91,805 114,852 354,375

2002 04 CHEMICAL & ALLIED PRODUCT MF G 131,993 7,093 20,896 11, 114 7,982 77,450 63,748

2002 05 METALS PROCESSING 223,705 601 11,801 32,367 27,778 49,143 17,306

2002 06 PETROLEUM & RELATED INDUSTR IES 44,633 355 7,204 2, 887 1,863 53,392 33,374

2002 07 OTHER INDUSTRIAL PROCESSES 156,077 7,520 114,474 267, 980 97,013 86,736 196,831

2002 08 SOLVENT UTILIZATION 687 331 5,677 3,805 3,284 90 1,288,990
2002 09 STORAGE & TRANSPORT 610 85 1,069 10,968 6,100 230 261,959

2002 10 WASTE DISPOSAL & RECYCLING 729,760 801 34,165 98,788 92,125 6,418 112,088

2002 11 HIGHWAY VEHICLES 20,199,593 74,325 2,193,387 50,584 35,929 88,684 1,778,345

2002 12 OFF-HIGHWAY 6,209,596 477 865,130 72,019 68,302 96,336 813,788

2002 14 MISCELLANEOUS 2, 067,084 569,139 42,039 3,066, 378 523,524 11,494 113,703
2002 Total 31,034,756 666,451 5,442,572 3,916,030 1,094,698 4,858,865 5,079,254

2009 01 FUEL COMB. ELEC. UTIL. 152,790 5,449 727,384 113,607 81, 884 2,473,773 13,155
2009 02 FUEL COMB. INDUSTRIAL 391, 510 1,305 445,832 74,864 51,709 523,163 32,629
2009 03 FUEL COMB. OTHER 544,310 3,201 123,331 85,412 77,042 112,463 207,146
2009 04 CHEMICAL & ALLIED PRODUCT MF G 140,910 7,611 22,031 11, 898 8,528 81,191 54,270
2009 05 METALS PROCESSING 242,911 732 11,788 31,098 26,505 54,700 18,507
2009 06 PETROLEUM & RELATED INDUSTR IES 48,161 399 7,908 3, 283 2,124 47,147 25,061
2009 07 OTHER INDUSTRIAL PROCESSES 166,088 7,545 117,625 298, 836 111,304 90,649 203,100
2009 08 SOLVENT UTILIZATION 771 360 6,662 4,290 3,690 100 1,257,986
2009 09 STORAGE & TRANSPORT 702 98 1,087 11,035 6,051 160 275,466
2009 10 WASTE DISPOSAL & RECYCLING 770,459 869 36,697 105,463 97,855 7,287 113,566
2009 11 HIGHWAY VEHICLES 14,353,436 87,703 1,408,206 42,370 26,848 8,817 1,146,174
2009 12 OFF-HIGHWAY 6,827,857 530 767,707 61,528 58,279 42,845 649,786
2009 14 MISCELLANEOUS 2, 214,906 606,617 45,212 3,311, 350 567,986 12,370 121,629
2009 Total 25,854,812 722,418 3,721,469 4,155,033 1,119,806 3,454,666 4,118,474

2018 01 FUEL COMB. ELEC. UTIL. 225,129 9,351 560,200 154,832 120, 895 1,479,499 16,318

2018 02 FUEL COMB. INDUSTRIAL 418, 010 1,384 471,501 80,386 55,928 547,527 34,938

2018 03 FUEL COMB. OTHER 453,482 3,358 136,418 78,031 69,853 116,812 149,363

2018 04 CHEMICAL & ALLIED PRODUCT MF G 173,857 9,023 26,564 14, 641 10,522 97,612 67,534

2018 05 METALS PROCESSING 288,138 961 15,006 39,673 34,058 67,170 23,798

2018 06 PETROLEUM & RELATED INDUSTR IES 53,442 460 9,088 3, 846 2,491 60,676 27,321

2018 07 OTHER INDUSTRIAL PROCESSES 189,922 8,793 136,722 348, 275 130,883 104,030 238,409

2018 08 SOLVENT UTILIZATION 936 404 8,480 5,378 4,618 119 1,516,454
2018 09 STORAGE & TRANSPORT 855 119 1,258 13,988 7,686 192 290,271

2018 10 WASTE DISPOSAL & RECYCLING 821,737 1,068 40,324 114,708 105,763 8,545 125,525

2018 11 HIGHWAY VEHICLES 12,052,347 101,223 639,931 33,884 17,080 10,027 713,143

2018 12 OFF-HIGHWAY 7,438,312 612 601,040 48,648 45,927 35,166 546,062

2018 14 MISCELLANEOUS 2, 241,196 653,831 45,776 3,623, 293 599,620 12,532 124,137
2018 Total 24,357,364 790,588 2,692,309 4,559,582 1,205,324 2,539,907 3,873,273Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS

MACTEC, Inc. 234 

### APPENDIX E:

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

MACTEC, Inc. 235 

### APPENDIX F:

COMPARISON OF BASE F AND BASE G ON-ROAD MOBILE EMISSIONSDocumentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.236Base G Onroad Mobile Emissions (Annual Tons)FIPSST 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018 2002 2009 2018AL 125,768 76,065 44,503 156,460 100,693 42,622 1,303,508 902,469 594,725 6,827 802 654 3,861 3,136 2,193 2,768 2,010 1,085 5,530 6,298 6,630FL 520,757 336,707 199,050 460,503 312,321 136,040 4,493,820 3,308,863 2,263,190 20,687 2,584 2,302 11,148 9,801 7,516 7,779 6,104 3,671 17,922 21,549 23,778GA279,975 192,773 99,464 304,309 207,024 92,113 2,699,650 1,956,263 1,303,529 12,043 1,568 1,325 7,165 6,005 4,406 5,110 3,797 2,166 10,436 12,554 13,511KY102,362 73,142 42,810 154,634 100,025 46,993 1,214,191 950,912 711,211 6,238 751 694 3,682 2,944 2,348 2,667 1,899 1,158 5,003 5,737 7,095MS86,811 51,600 28,699 110,672 69,952 27,620 853,774 602,257 394,247 4,566 532 401 2,828 2,250 1,479 2,089 1,491 746 3,549 3,995 4,147NC260,895 166,844 91,720 323,606 199,281 79,433 2,839,283 1,966,195 1,207,391 12,286 1,487 1,346 6,505 5,510 3,994 4,571 3,453 1,931 9,601 11,702 12,776SC114,861 71,781 41,866 138,940 91,471 39,348 1,226,555 878,825 588,536 5,909 713 584 3,414 2,831 1,986 2,473 1,834 988 4,646 5,466 5,878TN177,943 114,032 61,339 235,869 150,179 62,446 1,893,704 1,320,562 863,682 9,127 1,065 862 5,312 4,160 2,813 3,904 2,720 1,405 6,556 7,702 8,196VA157,989 95,694 55,992 219,835 132,699 57,192 2,136,288 1,435,359 954,463 8,196 1,067 949 4,499 3,706 2,922 3,067 2,216 1,404 7,770 8,990 9,653WV41,703 24,570 14,652 58,340 35,234 15,530 526,841 360,865 243,683 2,438 276 231 1,366 1,057 747 984 676 369 1,889 2,126 2,268VISTAS 1,869,063 1,203,208 680,096 2,163,168 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 3,195 2,488 2,799 2,053 1,262 5,586 6,362 7,296FL 438,761 293,423 192,096 402,099 284,737 134,465 4,022,000 3,090,443 2,306,759 18,802 1,911 2,289 10,185 9,027 7,691 7,126 5,653 3,848 16,183 19,553 23,595GA 265,972 187,102 104,678 306,998 208,568 100,707 2,712,473 2,044,169 1,474,029 12,182 1,256 1,458 7,252 6,116 4,995 5,169 3,877 2,517 10,545 12,685 14,870KY96,202 63,210 38,814 154,093 97,731 43,014 1,195,656 932,296 669,8915,988 587 651 3,728 3,008 2,283 2,699 1,946 1,160 5,055 5,807 6,584MS81,701 49,986 30,337 110,242 69,949 29,829 849,049 624,575 445,150 4,614 398 441 2,863 2,296 1,688 2,114 1,525 876 3,585 4,035 4,565NC272,594 167,894 87,718 290,873 207,670 83,399 2,677,118 2,192,253 1,238,802 12,482 1,314 1,323 6,733 5,874 4,299 4,754 3,651 2,158 9,711 12,663 13,077SC107,236 69,026 44,121 139,403 91,832 42,641 1,220,825 921,308 663,597 5,972 558 643 3,454 2,884 2,258 2,502 1,874 1,154 4,694 5,522 6,472TN168,389 109,716 63,916 233,324 147,591 66,879 1,881,893 1,359,880 961,929 9,202 833 944 5,349 4,247 3,199 3,927 2,788 1,643 6,629 7,753 8,962VA143,969 91,230 59,737 222,830 133,039 64,079 1,996,287 1,483,125 1,091,5467,234 902 1,059 4,546 3,768 3,343 3,097 2,258 1,641 7,852 9,084 10,757WV39,581 23,914 15,375 60,335 36,000 16,940 533,258 379,272 273,900 2,495 228 255 1,399 1,099 844 1,005 705 428 1,938 2,188 2,484VISTAS 1,733,382 1,128,638 683,942 2,077,822 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 -666FL81,997 43,284 6,955 58,404 27,584 1,575 471,820 218,420 -43,569 1,885 672 14 963 774 -175 653 451 -177 1,738 1,996 183GA14,003 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 -1,359KY6,160 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 512MS5,110 1,613 -1,638 4303 -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 -302SC7,625 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 -594TN9,554 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 -766VA14,020 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 -1,104WV2,122 656 -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 -29,215 798,301 -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%MS6% 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%SC7% 4% -5% 0% 0% -8%0% -5% -11% -1% 28% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%TN6% 4% -4% 1% 2% -7%1% -3% -10% -1% 28% -9% -1% -2% -12% -1% -2% -14% -1% -1% -9%VA10% 5% -6% -1% 0% -11%7% -3% -13% 13% 18% -10% -1% -2% -13% -1% -2% -14% -1% -1% -10%WV5% 3% -5% -3% -2% -8% -1% -5% -11% -2% 21% -9% -2% -4% -12% -2% -4% -14% -3% -3% -9%VISTAS8% 7% -1% 4% 1% -5%4% -2% -7% 3% 26% -4% 1% 0% -8% 1% 0% -11% 2% 1% -5%VOCNOxCOSO2PM-10PM-2.5NH3VOCNOxCOSO2PM-10PM-2.5NH3VOCNOxCOSO2PM-10PM-2.5NH3VOCNOxCOSO2PM-10PM-2.5NH3Documentation of the Base G 2002 Base Year, 2009 and 2018, Emission Inventories for VISTASMACTEC, Inc.237Annual Onroad Emissions Comparison0100,000200,000300,000400,000500,000600,000AL FL GA KY MS NC SC TN VA WV

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

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

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

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

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

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

Annual NH3 Emissions (Tons)2002 BaseG2002 BaseF2009 BaseG2009 BaseF2018 BaseG2018 BaseFAtmospheric 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 PLANT CT7M ST7M 1 20100101 2010020113115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANT SG01 ST1 1 10100212 1010020213115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANTSG02 ST1 1 10100212 1010020213115 11500003GEORGIA POWER COMPANY, HAMMOND STEAM-ELECTRICGENERATING PLANT SG03 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 PLANT SG01 ST1 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANT SG02 ST2 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANTSG03 ST3 1 10100212 1010022613207 20700008GEORGIA POWER COMPANY, SCHERER STEAM-ELECTRICGENERATING PLANT SG04 ST4 1 10100212 1010022613237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANT SG01 ST1 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANTSG02 ST1 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANT SG03 ST2 1 10100212 1010020213237 23700008GEORGIA POWER COMPANY, BRANCH STEAM-ELECTRICGENERATING PLANT SG04 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