PECHAN September 2007 

 46 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

Table III-8. Percentage Reductions Associated with Federal Locomotive 

Standards 

Large Line Haul Large Switch Small Railroads Passenger Commuter 

Year 

Revised 

Baseline 

% 

Reduction 

Revised 

Baseline 

% 

Reduction 

Revised 

Baseline 

% 

Reduction 

Revised 

Baseline 

% 

Reduction 

Volatile Organic Compounds 

2006 

2009 46,014 8.7% 5,769 3.8% 3,032 0.0% 1,687 8.4% 

2012 48,258 25.6% 6,051 11.3% 3,180 0.0% 1,770 26.5% 

2018 53,080 55.5% 6,655 23.9% 3,498 0.0% 1,947 60.4% 

PM-2.5 

2006 

2009 28,403 16.7% 2,309 10.4% 951 8.5% 1,040 17.2% 

2012 29,788 30.6% 2,422 17.2% 998 8.6% 1,091 32.4% 

2018 32,765 55.7% 2,664 28.8% 1,097 9.7% 1,200 61.2% 

PM-10 

2006 

2009 29,281 16.7% 2,381 10.4% 981 8.5% 1,073 17.2% 

2012 30,709 30.6% 2,497 17.2% 1,028 8.6% 1,125 32.4% 

2018 33,777 55.7% 2,746 28.9% 1,131 9.7% 1,238 61.2% 

Oxides of Nitrogen 

2006 

2009 817,877 8.1% 91,097 3.4% 39,528 0.0% 40,342 19.8% 

2012 857,766 19.3% 95,540 9.3% 41,456 0.0% 42,310 38.7% 

2018 943,477 35.6% 105,087 19.5% 45,599 2.8% 46,537 58.1% 

SCC(s) 2285002006 2285002010 2285002007 2285002008; 2285002009 

Note: emissions reported in short tons. 

Analogous control factor calculations to those described above for locomotives were used to 

compute total CMV emission reduction values representing the effects of both existing and 

proposed emission standards. Table III-9 presents the EPA baseline emissions, Pechan’s revised 

baseline emissions (computed using EPA’s 0.9 percent annual growth assumption), EPA’s 

controlled emissions, and the percentage reduction estimates applied in this analysis. For 

example, the CMV standards are expected to reduce VOC emissions by 33.9 percent in 2018. 
PECHAN September 2007 

 47 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

Table III-9. Percentage Reductions Associated with Federal CMV Standards 

Emissions (short tons) 

Year Baseline

Revised 

Baseline Controlled

% 

Reduction 

Volatile Organic Compounds 

2005 17,295 

2009 16,870 17,926 16,863 5.9% 

2012 16,495 18,414 16,344 11.2% 

2018 16,034 19,431 12,851 33.9% 

PM-2.5 

2005 30,042 

2009 27,327 31,138 27,324 12.2% 

2012 26,657 31,987 26,582 16.9% 

2018 22,553 33,753 19,308 42.8% 

PM-10 

2005 30,972 

2009 28,172 32,102 28,169 12.3% 

2012 27,481 32,977 27,403 16.9% 

2018 23,251 34,798 19,905 42.8% 

Oxides of Nitrogen 

2005 825,229 

2009 781,105 855,341 781,105 8.7% 

2012 743,915 878,643 742,453 15.5% 

2018 686,966 927,171 591,991 36.2% 

Sulfur Dioxide 

2005 82,543 

2009 46,838 85,555 46,839 45.3% 

2012 42,515 87,886 42,515 51.6% 

2018 6,054 92,740 5,630 93.9% 

Carbon Monoxide 

2005 153,499 

2009 149,966 159,100 149,966 5.7% 

2012 146,227 163,434 146,227 10.5% 

2018 140,443 172,461 140,443 18.6% 

For commercial marine diesel engines, the RIA examines expected rule emission benefits for 

four different engine types/sizes. The total CMV emission benefits in each year were used and 

applied equally to most of the affected SCCs in the 2005 inventory. However, Pechan applied 

rule penetration (RP) values to two CMV SCCs based on an ENVIRON table indicating RP 

values of less than 100 percent for these SCCs (see Table III-10). 
PECHAN September 2007 

 48 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

Table III-10. Commercial Marine Vessel Rule Penetration Values 

Percentage of Engines Affected by Proposed EPA Standards Source 

Category 

Code (SCC) 

Source 

Definition Purpose 

Geographic 

Area NOx PM-10 HC CO SOx 

2280002023 Push Boats Barge Freight River Traffic 100% 100% 100% 100% 100%

Lake Traffic 100% 100% 100% 100% 100%

2280002021 Tugs Vessel assist 

and support 

functions 

Near port 100% 100% 100% 100% 100%

2280003200 Mid-Great 

Lakes 

85% 81% 86% 86% 77%

2280003100 

Deep draft Laker and 

ocean-going 

large vessels Near port 81% 71% 87% 83% 63%

2280002022 Ferries River or lake 

ferrying 

Regular routes 100% 100% 100% 100% 100%

2280002024 Other 

Commercial 

Vessels 

Excursion 

boats 

primarily 

Near dock 100% 100% 100% 100% 100%

2280002025 Dredges Dredging 

projects 

Varies 100% 100% 100% 100% 100%

2280002029 Support 

Vessels 

General work 

boats 

Near port 100% 100% 100% 100% 100%

2280002030, 

22800040301

Commercial 

Fishing 

Market 

fishing 

Great Lakes 100% 100% 100% 100% 100%

2280002040, 

22800040401

Military Coast Guard 

and Navy 

Great Lakes 100% 100% 100% 100% 100%
PECHAN September 2007 

 49 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

SECTION IV. PREPARATION OF GROWTH AND CONTROL 

FILES 

This section describes the contents of the growth and control factor files submitted to LADCO 

earlier this month. The first subsection discusses the preparation of the point and area source/

MAR factor file and the revised NONROAD model growth file. The final subsection describes 

the contents of the control factor files. 

Table IV-1 presents the RPO Data Exchange Protocol Format for reporting emission growth and 

control data. Pechan utilized this format to create growth and control factor files for LADCO. 

Because the growth factors (unlike the control factors) do not differ by pollutant, Pechan 

developed a separate file containing only the point and area source/MAR growth factors. Pechan 

revised the growth packet portion of the NONROAD model growth file (NATION.GRW) to 

replace the default model equipment population growth rates with growth rates based on more 

recent/more region-specific information. Two sets of control factor files were prepared: one for 

area source/MAR categories and one for point source categories. The point and area 

source/MAR growth and control files were developed in fixed field ascii format. The format of 

the default NONROAD model growth file was retained in the revised version prepared for 

LADCO. The following subsections describe the contents of the growth and control factor files. 

A. GROWTH FACTORS 

Pechan compiled the LADCO region growth factor information into the file 

$LADCO_2005_GF_Final_RPO.txt. Table IV-2 displays the RPO Data Exchange Protocol 

Format fields and identifies the fields that were populated in this file. The file contains separate 

records for each SCC/state for each year between 2006 and 2018 (population-based growth 

indicator records are reported by SCC/state/county because population projections were available 

at the county-level). 

Pechan revised the input file used by the NONROAD model (NATION.GRW) to reflect 

historical equipment population changes and to estimate future equipment population changes. 

In particular, Pechan incorporated LADCO state-specific records to the GROWTH packet 

portion of this file. The fixed field format of the data in this packet is as follows: 

Characters Description

1-5 FIPS code (00000 = applies to entire nation; ss000 = applies to all of state ss) 

6-10 subregion code (left blank) 

11-15 year of estimate (4-digit year) 

17-20 indicator code (alphanumeric code identified within NONROAD) 

26-45 value for indicator 

 
PECHAN September 2007 

 50 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

Table IV-1. RPO Data Exchange Protocol Format for Growth/Control Data 

Field Name Field Description

Field 

Length

RECORD TYPE A code that identifies the type of record (G for growth, C for 

control)

2

COUNTRY CODE A code that identifies the country (US = United States) 2

STATE PROVINCE TRIBAL CODE The code for the state/province/tribe 4

COUNTY FIPS The FIPS code for the county 3

SIC 4-digit SIC, or 2 digit SIC with remaining digits blank (not zero) 4

SCC EPA source classification code or a fraction of the code 10

SITE ID Unique state/local/tribal ID reported consistently over time 15

EMISSION UNIT ID Unique state/local/tribal ID reported consistently over time 6

EMISSION RELEASE POINT ID State/ local/tribal ID for point /location where emissions are 

released to ambient air

6

POLLUTANT CODE Pollutant code 9

PROCESS ID Unique state/local/tribal ID reported consistently over time 6

BASE DATE Date that the control strategy comes into effect 6

FUTURE DATE Future date that the control strategy affects 6

PRIMARY CONTROL EQUIPMENT CODE Primary control equipment code 10

BASE DATE CONTROL EFFICIENCY Base year % control efficiency(60% reduction = 60) 6

FUTURE DATE CONTROL EFFICIENCY Future year % control efficiency(60% reduction = 60) 6

FUTURE DATE GROWTH FACTOR Growth factor based on changes in throughput, economic 

growth (unrelated to controls). This is an absolute growth rate 

not an annual growth rate.

11

CONTROL TYPE MACT, RACT, LAER, SIPCALL, BART, etc 10

FUTURE DATE CHEMICAL SPECIATION 

PROFILE

Code matching speciate chemical speciation profile unless in 

base year

6

ALLOWABLE EMISSIONS CAP Allowable emissions cap units must be in TONS/day 10

MARKET PENETRATION OF NEW 

SPECIATION PROFILE

Fraction of future year emissions using new speciation profile 6

RESERVED FOR FUTURE USE FIELD 3 (Field used to enter future year control efficiency value where 

available)

10

RESERVED FOR FUTURE USE FIELD 2 (Field used to enter future year rule effectiveness value where 

available)

10

RESERVED FOR FUTURE USE FIELD 1 (Field used to enter future year RP value where available) 10

CONTROL DESCRIPTION A text description of the control 80

PRIMARY CONTACT Email address of the primary contact/developer of this record 30
PECHAN September 2007 

 51 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

Table IV-2. Fields Populated in Growth Factor File 

Field Name Populated in Growth Factor File?

RECORD TYPE Yes 

COUNTRY CODE Yes 

STATE PROVINCE TRIBAL CODE Yes 

COUNTY FIPS Yes (with “000” except for population data) 

SIC No 

SCC Yes 

SITE ID No 

EMISSION UNIT ID No 

EMISSION RELEASE POINT ID No 

POLLUTANT CODE No 

PROCESS ID No 

BASE DATE Yes 

FUTURE DATE Yes 

PRIMARY CONTROL EQUIPMENT CODE No 

BASE DATE CONTROL EFFICIENCY No 

FUTURE DATE CONTROL EFFICIENCY No 

FUTURE DATE GROWTH FACTOR Yes 

CONTROL TYPE No 

FUTURE DATE CHEMICAL SPECIATION PROFILE No 

ALLOWABLE EMISSIONS CAP No 

MARKET PENETRATION OF NEW SPECIATION PROFILE No 

RESERVED FOR FUTURE USE FIELD 3 (future year CE) No 

RESERVED FOR FUTURE USE FIELD 2 (future year RE) No 

RESERVED FOR FUTURE USE FIELD 1 (future year RP) No 

CONTROL DESCRIPTION No 

PRIMARY CONTACT Yes 

B. CONTROL FACTORS 

Pechan compiled control factors for the LADCO states in two sets of ascii files: one set for point 

source controls (LADCO 2005 Base Year Point Control File.txt), and the other set for area 

source/MAR controls (LADCO 2005 Base Year Area Source and MAR Control File.txt). 

1. Point Source Control Factors 

The LADCO 2005 Base Year Point Control File.txt file reports control information at the 

Process ID-level and for the specific date that each control is expected to be implemented. Note 

that the Base Date Control Efficiency field is populated with a zero for every record because 

Pechan did not have any base year control information other than that reported in the base year 

inventory supplied by LADCO. LADCO should rely on the control information in the base year 

inventory to identify the base year level of control. For MACT standards, the point source 

control factors are incremental to base year control levels. Because all other point source control 
PECHAN September 2007 

 52 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

factors represent absolute control levels, LADCO should subtract any existing 2005 inventory 

level of control from the control factor level of control to determine net reductions for nonMACT controls. Pechan found very few point source records with control information, so 

LADCO should expect very little control overlap between the 2005 inventory and the control 

file. Table IV-3 identifies the RPO Data Exchange Protocol fields that are populated in the point 

source control file. 

2. Area Source and MAR Control Factors 

Pechan compiled the area source and MAR control factor information into a single ascii file that 

reports the level of control for each year of interest (2009, 2012, and 2018). In cases where there 

is no change in emission reduction after the initial implementation year, the level of control is 

repeated for each year. For controls where emission reductions increase over time (due to 

increased levels of RP), the level of control increases for each successive modeling year. Except 

for the single control for which emission reductions are county-specific (Stage II Vehicle 

Refueling), the area source and MAR control factor file is expressed at the state-level. In cases 

where it was feasible to do so, Pechan populated the 5th, 4th, and 3rd fields from the end of each 

control factor file (“RESERVED FOR FUTURE USE” in the RPO Data Exchange Protocol 

Format) with future year CE, RE, and RP values, respectively (the field “FUTURE DATE 

CONTROL EFFICIENCY” was populated with the overall percentage emission reduction). 

Table IV-4 identifies the RPO Data Exchange Protocol fields that are populated in this file. 
PECHAN September 2007 

 53 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

Table IV-3. Fields Populated in Point Source Control Factor File 

RPO Data Exchange Protocol Format Field Name

Populated in Point 

Source Control 

Factor File

RECORD TYPE Yes 

COUNTRY CODE Yes 

STATE PROVINCE TRIBAL CODE Yes 

COUNTY FIPS Yes 

SIC Yes 

SCC Yes 

SITE ID Yes 

EMISSION UNIT ID Yes 

EMISSION RELEASE POINT ID Yes 

POLLUTANT CODE Yes 

PROCESS ID Yes 

BASE DATE Yes 

FUTURE DATE1 Yes 

PRIMARY CONTROL EQUIPMENT CODE No 

BASE DATE CONTROL EFFICIENCY2 Yes 

FUTURE DATE CONTROL EFFICIENCY3 Yes 

FUTURE DATE GROWTH FACTOR No 

CONTROL TYPE Yes 

FUTURE DATE CHEMICAL SPECIATION PROFILE No 

ALLOWABLE EMISSIONS CAP No 

MARKET PENETRATION OF NEW SPECIATION PROFILE No 

RESERVED FOR FUTURE USE FIELD 3 (future year CE) No 

RESERVED FOR FUTURE USE FIELD 2 (future year RE) No 

RESERVED FOR FUTURE USE FIELD 1 (future year RP) No 

CONTROL DESCRIPTION Yes 

PRIMARY CONTACT Yes 

1

 Represents date that control is first implemented. 2

 All records populated with “0" - LADCO should rely on control information reported in base year inventory. 

3

 Populated with overall percentage emission reduction. 
PECHAN September 2007 

 54 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

Table IV-4. Fields Populated in Area Source/MAR Control Factor File 

RPO Data Exchange Protocol Format Field Name

Populated in Area 

Source/MAR Control 

Factor File 

RECORD TYPE Yes 

COUNTRY CODE Yes 

STATE PROVINCE TRIBAL CODE Yes 

COUNTY FIPS Yes 

SIC No 

SCC Yes 

SITE ID No 

EMISSION UNIT ID No 

EMISSION RELEASE POINT ID No 

POLLUTANT CODE Yes 

PROCESS ID No 

BASE DATE Yes 

FUTURE DATE Yes 

PRIMARY CONTROL EQUIPMENT CODE No 

BASE DATE CONTROL EFFICIENCY Yes 

FUTURE DATE CONTROL EFFICIENCY1 Yes 

FUTURE DATE GROWTH FACTOR No 

CONTROL TYPE No 

FUTURE DATE CHEMICAL SPECIATION PROFILE No 

ALLOWABLE EMISSIONS CAP No 

MARKET PENETRATION OF NEW SPECIATION PROFILE No 

RESERVED FOR FUTURE USE FIELD 3 (future year CE) Yes2

RESERVED FOR FUTURE USE FIELD 2 (future year RE) Yes2

RESERVED FOR FUTURE USE FIELD 1 (future year RP) Yes2

CONTROL DESCRIPTION Yes 

PRIMARY CONTACT Yes 

1 Populated with overall percentage emission reduction (product of CE, RE, and RP). 

2

 Not populated for Federal locomotive standards or Stage II Vehicle Refueling control program.
PECHAN September 2007 

 55 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

SECTION V. REFERENCES 

BLS, 2007: U.S. Bureau of Labor Statistics, “State Occupational Employment Projections, 

Long-Term,” accessed from http://www.projectionscentral.com/projections.asp, Office of 

Employment Projections, Washington, DC. Accessed May 2007. 

DOE, 2007a: U.S. Department of Energy, “Annual Energy Outlook 2007, with Projections 

through 2030,” DOE/EIA-0383(2007), Energy Information Administration, Office of 

Integrated Analysis and Forecasting, Washington, DC. February 2007. 

DOE, 2007b: U.S. Department of Energy, “State Energy Consumption, Price, and Expenditure 

Estimates (SEDS),” accessed from http://www.eia.doe.gov/emeu/states/_seds.html, 

Energy Information Administration, Office of Integrated Analysis and Forecasting, 

Washington, D.C. Accessed April 2007. 

ENVIRON, 2007a: ENVIRON International Corporation, “Draft LADCO 2005 Commercial 

Marine Emissions,” prepared for Lake Michigan Air Directors Consortium, Des Plaines, 

IL, March 2, 2007. 

ENVIRON, 2007b: ENVIRON International Corporation, “Draft LADCO 2005 Locomotive 

Emissions,” prepared for Lake Michigan Air Directors Consortium, Des Plaines, IL, 

February 2007. 

EPA, 2004: U.S. Environmental Protection Agency, “National Emission Inventory—Ammonia 

Emissions from Animal Husbandry Operations, Draft Report,” (no further identifying 

information available). January 2004. 

EPA, 2007a: U.S. Environmental Protection Agency, “Clean Watersheds Needs Survey 2000,” 

data for LADCO states accessed from http://www.epa.gov/owm/mtb/cwns/index.htm,

Office of Wastewater Management, Washington, DC. Accessed May 2007. 

EPA, 2007b: U.S. Environmental Protection Agency, “Draft Regulatory Impact Analysis: 

Control of Emissions of Air Pollution from Locomotive Engines and Marine 

Compression-Ignition Engines Less than 30 Liters per Cylinder – Chapter 3: Emission 

Inventory,” Assessment and Standards Division, Office of Transportation and Air 

Quality, EPA420-D-07-001, March 2007. 

FAA, 2007: U.S. Federal Aviation Administration, “Terminal Area Forecast System,” data for 

LADCO states accessed from http://www.apo.data.faa.gov/main/taf.asp, Office of 

Aviation Policy and Plans, Washington, DC. Accessed March 2007. 

Freedonia, 2006: The Freedonia Group, Inc., “Solvents to 2010, U.S. Industry Study with 

Forecasts to 2010 & 2015,” Study #2055, Cleveland, OH, April 2006. 
PECHAN September 2007 

 56 Development of 2005 Base Year Growth and 

Control Factors for LADCO - Final Report 

Harnett, 2007: William T. Harnett, “Guidance for Estimating VOC and NOx Emission Changes 

from MACT Standards,” Memorandum to Regional Air Division Directors, U.S. 

Environmental Protection Agency, Research Triangle Park, NC, May 11, 2007. 

Metra, 2007: Metra, “2007 Metra Program and Budget,” accessed from 

http://metrarail.com/Budget/2007BudgetBook.pdf, Chicago, IL, May 2007. 

Page, 2007: Stephen D. Page, “Emission Reduction Credit for Three Federal Rules for 

Categories of Consumer and Commercial Products under Section 183(e) of the Clean Air 

Act,” Memorandum to Air Division Directors, U.S. Environmental Protection Agency, 

Research Triangle Park, NC, May 30, 2007. 

Pechan, 2004: E.H. Pechan & Associates, Inc., “Development of Growth and Control Factors 

for Lake Michigan Air Directors Consortium (LADCO) – Final Report,” Durham, NC, 

prepared for Lake Michigan Air Directors Consortium, Des Plaines, IL, December 15, 

2004. 

Pechan, 2005: E.H. Pechan & Associates, Inc., “Development of Updated Growth and Control 

Factors for Lake Michigan Air Directors Consortium (LADCO) – Draft Report,” 

Durham, NC, prepared for Lake Michigan Air Directors Consortium, Des Plaines, IL, 

December 29, 2005. 
Documentation of the 

Base G2 and 

Best & Final 

2002 Base Year, 

2009 and 2018 

Emission Inventories 

for VISTAS

Prepared by:

MACTEC, Inc.

Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS 

MACTEC, Inc. i 

Table of Contents 

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

1.0 2002 BASE YEAR INVENTORY DEVELOPMENT ........................................................................................9

1.1 POINT SOURCES...........................................................................................................................................9

1.1.1 Development of 2002 Point Source Inventory .......................................................................................9

1.1.1.1 Data Sources .............................................................................................................................................. 10

1.1.1.2 Initial Data Evaluation ............................................................................................................................... 11

1.1.1.3 PM Augmentation...................................................................................................................................... 12

1.1.1.4 EGU Analysis ............................................................................................................................................ 15

1.1.1.5 QA Review of Base F Inventory................................................................................................................ 16

1.1.1.6 Additional Base G Updates and Corrections.............................................................................................. 17

1.1.1.7 Summary of Best & Final 2002 Inventory ................................................................................................. 19

1.1.2 Development of Typical Year EGU inventory......................................................................................23

1.2 AREA SOURCES .........................................................................................................................................25

1.2.1 Development of a “typical” year fire inventory ..................................................................................26

1.2.2 Development of non-fire inventory ......................................................................................................35

1.2.3 2002 Base G inventory updates ...........................................................................................................38

1.2.3.1 Changes resulting from State review and comment ................................................................................... 38

1.2.4 Ammonia and paved road emissions....................................................................................................41

1.2.5 Global Changes Made for Base G.......................................................................................................42

1.2.6 Quality Assurance steps.......................................................................................................................43

1.3 MOBILE SOURCES .....................................................................................................................................44

1.3.1 Development of on-road mobile source input files and VMT estimates...............................................45

1.3.1.1 Emissions from on-road mobile sources .................................................................................................... 47

1.3.2 Development of non-road emission estimates......................................................................................49

1.3.2.1 Emissions from NONROAD model sources.............................................................................................. 49

1.3.2.2 Emissions from Commercial Marine Vessels, Locomotives, and Airplanes.............................................. 65

Base G Revisions: ..............................................................................................................................................81

1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio .............................................. 87

1.3.3 Quality Assurance steps.......................................................................................................................89

2.0 PROJECTION INVENTORY DEVELOPMENT............................................................................................90

2.1 POINT SOURCES.........................................................................................................................................90

2.1.1 EGU Emission Projections ..................................................................................................................90

2.1.1.1 Chronology of the Development of EGU Projections................................................................................ 90

2.1.1.2 VISTAS IPM runs for EGU sources.......................................................................................................... 95

2.1.1.3 Post-Processing of IPM Parsed Files ......................................................................................................... 95

2.1.1.4 Eliminating Double Counting of EGU Units ............................................................................................. 97

2.1.1.5 Quality Assurance Steps ............................................................................................................................ 99

2.1.1.6 S/L Adjustments to IPM Modeling Results for Base G Projections........................................................... 99

2.1.1.7 S/L Adjustments to IPM Modeling Results for Base G2 2018 Projections.............................................. 100

2.1.1.8 S/L Adjustments to IPM Modeling Results for Best & Final Projections................................................ 109

2.1.1.9 Conversion of MRPO BaseM 2009 EGU Data to SMOKE Input Format ............................................... 112

2.1.1.10 Summary of 2009/2018 EGU Point Source Inventories .......................................................................... 112

2.1.2 Non-EGU Emission Projections ........................................................................................................116
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS 

MACTEC, Inc. ii 

2.1.2.1 Growth assumptions for non-EGU sources.............................................................................................. 116

2.1.2.2 Source Shutdowns.................................................................................................................................... 118

2.1.2.3 Control Programs applied to non-EGU sources ....................................................................................... 120

2.1.2.4 Quality Assurance steps........................................................................................................................... 123

2.1.2.5 Additional Base G Updates and Corrections............................................................................................ 123

2.1.2.6 Additional Best & Final Updates and Corrections................................................................................... 126

2.1.2.7 Conversion of MRPO BaseM 2009 non-EGU Data to SMOKE Input Format ........................................ 127

2.1.2.8 Summary of the 2009/2018 non-EGU Point Source Inventories ............................................................. 127

2.2 AREA SOURCES .......................................................................................................................................131

2.2.1 Stationary area sources .....................................................................................................................131

2.2.1.1 Stationary area source controls ................................................................................................................ 132

2.2.1.2 Stationary area source growth.................................................................................................................. 134

2.2.1.3 Differences between 2009/2018............................................................................................................... 135

2.2.2 Agricultural area sources ..................................................................................................................135

2.2.2.1 Control assumptions for agricultural area sources ................................................................................... 136

2.2.2.2 Growth assumptions for agricultural area sources ................................................................................... 136

2.2.3 Changes to Prescribed Fire for 2009/2018 Base G...........................................................................141

2.2.4 Quality Assurance steps.....................................................................................................................146

2.3 MOBILE SOURCES ...................................................................................................................................146

2.3.1 Development of on-road mobile source input files............................................................................149

2.3.1.1 Preparation of revised 2018 input data files............................................................................................. 149

2.3.1.2 Preparation of initial 2009 input data files ............................................................................................... 152

2.3.2 VMT Data ..........................................................................................................................................153

2.3.3 Base G Revisions ...............................................................................................................................158

2.3.4 Development of non-road emission estimates....................................................................................158

2.3.4.1 NONROAD model sources...................................................................................................................... 158

2.3.4.2 Non-NONROAD model sources.............................................................................................................. 161

2.3.4.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio ............................................ 196

2.3.4.4 Differences between 2009/2018............................................................................................................... 196

2.3.5 Quality Assurance steps.....................................................................................................................197

Appendix A: State Emission Totals by Pollutant and Sector 

Appendix B: State VMT totals 

Appendix C: State Tier 1 Emission Totals 

Appendix D: VISTAS Tier 1 Emission Totals

Appendix E: Aircraft PM Excerpt from 2001 Tucson Report

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

Appendix G: Conversion of MRPO Base M Point Source Data to SMOKE Input Format 

Appendix H: EGU Controls for Coal and Oil/gas Units for the Base G/G2 Inventory 

Appendix I: EGU Controls for Coal and Oil/gas Units for the B&F Inventory
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. iii 

List of Tables 

Table I-1 Inventory Version in Use by Year and Source Sector Through B&F - 2002 

Table I-2 Inventory Version in Use by Year and Source Sector Through B&F - 2009 

Table I-3 Inventory Version in Use by Year and Source Sector Through B&F - 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 / B&F 2002 VISTAS Point Source Inventory for SO2 (tons/year). 

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

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

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

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

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

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

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

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

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

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

Base F Inventory 

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

Emissions Inventory. 

Table 1.3-1 Representative day mapping for January episode 

Table 1.3-2 Summary of Base F NONROAD Modeling Revisions 

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

Table 1.3-4 Summary of Base G NONROAD Modeling Revisions 

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

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

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

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

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

Table 1.3-9 Non-Corresponding Aircraft Emissions Records 

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

Emissions with Modified Aircraft PM Emission Rates (annual tons) 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. iv 

List of Tables (continued) 

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

Modifications. 

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

Table 1.3-13 Calculated Emission Ratios for VA. 

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

Emissions (tons/year) 

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

Table 1.3-16 Base F Comparison of Aircraft Emissions 

(Airports with Aircraft NOx > 200 tons per year) 

Table 1.3-17 Base G VA Aircraft Records Updates 

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

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

Marine Emissions (tons/year) 

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

Relative to Base F Inventory 

Table 1.3-21 Base G Comparison of Aircraft Emissions 

(Airports with Aircraft NOx > 200 tons per year) 

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

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

for the Base G/G2 2009/2018 EGU Inventories. 

Table 2.1-2 Other Adjustments to IPM Results Specified by S/L Agencies 

for the Base G/G2 2009/2018 EGU Inventories. 

Table 2.1-3 Additional Adjustments to IPM Results Specified by S/L Agencies 

for the B&F 2009/2018 EGU Inventories. 

Table 2.1-4 EGU Point Source SO2 Emission Comparison for 2002/2009/2018. 

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

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

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

Table 2.1-8 EGU Point Source PM10-PRI Emission Comparison for 2002/2009/2018. 

Table 2.1-9 EGU Point Source PM2.5 -PRI Emission Comparison for 2002/2009/2018. 

Table 2.1-10 EGU Point Source NH3 Emission Comparison for 2002/2009/2018. 

Table 2.1-11 Summary of Source Shutdowns Incorporated in Base G Inventory. 

Table 2.1-12 Non-EGU Point Source Control Programs Included in 

2009/2018 Projection Inventories. 

Table 2.1-13 Summary of Updates and Corrections Incorporated into the 

Base G 2009/2018 Non-EGU Inventories. 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. 

v 

List of Tables (continued) 

Table 2.1-14 Summary of Updates and Corrections Incorporated into the 

B&F 2009/2018 Non-EGU Inventories. 

Table 2.1-15 Non-EGU Point Source SO2 Emission Comparison for 2002/2009/2018. 

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

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

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

Table 2.1-19 Non-EGU Point Source PM10-PRI Emission Comparison for 2002/2009/2018. 

Table 2.1-20 Non-EGU Point Source PM25-PRI Emission Comparison for 2002/2009/2018. 

Table 2.1-21 Non-EGU Point Source NH3 Emission Comparison for 2002/2009/2018. 

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

(based on actual emissions). 

Table 2.2-2 2009 Projection Year Emissions and Percentage Difference for Base F and 

Base G (based on actual emissions). 

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

G (based on actual emissions). 

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

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

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

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

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

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

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

(annual tons, as of the fall of 2004) 

Table 2.3-7 Locally Generated Growth Factors for North Carolina 

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

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

Year Values 

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

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

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

Table 2.3-13 Growth Options based on CAIR Data 

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

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

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

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

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

Growth Using 1996 and 2020 EPA Inventories) 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. vi 

List of Tables (continued) 

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 G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. vii 

List of Figures 

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

Base G, and 2002 Typical Base G Inventories. 

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

Actual Base G and 2002 Typical Base G Inventories. 

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

Base G and 2002 Typical Base G Inventories. 

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

Base G and 2002 Typical Base G Inventories. 

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

Figure 2.3-1 Impacts of the Apparent CAIR Inventory Discrepancy 

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

Figure 2.3-3 Locomotive CO Emissions (Base F) 

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

Figure 2.3-5 Locomotive NOx Emissions (Base F) 

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

Figure 2.3-7 Locomotive PM10 Emissions (Base F) 

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

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

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

Figure 2.3-11 Locomotive SO2 Emissions (Base F) 

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

Figure 2.3-13 Locomotive VOC Emissions (Base F) 

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

Figure 2.3-15 Locomotive CO Emissions (Base G) 

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

Figure 2.3-17 Locomotive NOx Emissions (Base G) 

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

Figure 2.3-19 Locomotive PM10 Emissions (Base G) 

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

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

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

Figure 2.3-23 Locomotive SO2 Emissions (Base G) 

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

Figure 2.3-25 Locomotive VOC Emissions (Base G) 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. viii 

Acronyms and Abbreviations 

AEO Annual Energy Outlook 

AF&PA American Forest and Paper Association 

APCD Air Pollution Control District 

ATP Anti-Tampering Program 

BLRID Boiler Identification (Boiler ID) 

CAA Clean Air Act 

CAIR Clean Air Interstate Rule 

CEM Continuous Emissions Monitoring 

CAMD Clean Air Markets Division 

CERR Consolidated Emissions Reporting Rule 

CMU Carnegie Mellon University 

CMV commercial marine vessels 

CE Control Efficiency 

CO carbon monoxide 

DENR North Carolina Department of Environment and Natural Resources 

DHEC South Carolina Department of Health and Environmental Control 

EDMS Emissions Data Management Systems 

ESD Emissions Standards Division 

EPA Environmental Protection Agency 

EGU Electric Generating Unit 

ICF ICF International, Inc. 

FIP Federal Implementation Plan 

FLM Federal Land Manager 

FTP File transfer protocol 

FR Federal Register 

FS Forest Service 

HDD Heavy Duty Diesel 

HDD RULE Heavy Duty Diesel Rule 

ICF ICF International, Inc. 

ID Identification 

I/M Inspection and Maintenance 

IPM® Integrated Planning Model®

IAQTR Interstate Air Quality Transport Rule 

LTO Landing and take off 

MACT Maximum achievable control technology 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. ix 

Acronyms and Abbreviations (continued) 

MACTEC MACTEC Engineering and Consulting, Inc. 

MOBILE 6 MOBILE emissions estimation model version 6 

MRPO Midwest Regional Planning Organization 

NH3 Ammonia 

NEI National Emission Inventory 

NIF National Emission Inventory Format 

NLEV National Low Emission Vehicle regulation 

NMIM National Mobile Inventory Model 

NONROAD no acronym (model name) 

NOx Oxides of nitrogen 

NWR National Wildlife Refuge 

OTB On the books 

OTW On the way 

ORIS Office of Regulatory Information Systems 

OTAQ Office of Transportation and Air Quality 

OTC Ozone Transport Commission 

PFC Portable fuel containers 

PM Particulate matter 

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

captured on a filter 

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

both the filterable and condensable components of particulate matter 

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

captured on a filter 

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

both the filterable and condensable components of particulate matter 

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

particulates, usually less than 2.5 microns in diameter 

ppmW parts per million by weight 

PRI Primary 

QA/QC Quality Assurance/Quality Control 

QAPP Quality Assurance Project Plan 

REMI Regional Economic Models, Inc. 

RFG Reformulated gasoline 

RVP Reid Vapor Pressure 
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x 

Acronyms and Abbreviations (continued) 

SCC Source Classification Code 

SIP State Implementation Plan 

SIWG Special Interest Workgroup 

S/L/T State/Local/Tribal 

SMOKE Sparse Matrix Operator Kernel Emissions Modeling System 

S/L State and Local 

SO2 Oxides of Sulfur 

T4 Tier 4 

VISTAS Visibility Improvement State and Tribal Association of the Southeast 

VMT Vehicle Miles Traveled 

VOC Volatile organic compounds 

WRAP Western Regional Air Partnership 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

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Documentation of the Base G2 and Best & Final 

2002 Base Year, 2009 and 2018, Emission Inventories for VISTAS 

Introduction

Base G2 document was delivered final in Aug (?) 2007. In fall 2007 states updated 

specific point source EGU and non-EGU facility record in Best and Final (B&F) 

inventories for 2009 and 2018 to account for BART controls, consent decrees, corrections 

to Base G2, and source specific controls. Only EGU and non-EGU point source records 

were changed. Area, non-road, on-road remained the same as Base G2. In this report all 

records for area, non-road, and on-road were used in B&F modeling the same as Base 

G2. This report has been updated from the Base G2 report submitted in July 2007 just for 

B&F changes to EGU and non-EGU sources. A history of the development of the 

VISTAS inventory follows. Specific sections of the document detail the modifications 

made as the inventory progressed from Base F through B&F. 

The Base G2 inventory included changes in 2018 controls on specific electric generating 

units in GA, FL, NC, and WV. There were no changes in 2009 controls for EGU and no 

changes between the Base G and Base G2 inventories for non-EGU point, on-road, nonroad, or area sources in 2009 or 2018. The Base G2 modeling run included changes for 

2018 EGU controls plus corrections in 2002 typical, 2009, and 2018 for errors in 

emissions processing in Base G. These corrections in emissions processing are not seen 

when comparing the Base G and G2 inventory files. 

Base G and Base G2 inventories represent two separate model runs, as does the B&F. 

Since Base G2 supersedes Base G, VISTAS will maintain only the Base G2 and B&F 

model files since both were used in State Implementation Plan submittals. 

History of VISTAS Base and Projection Year Emission Inventory Development 

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

projection year inventories provided to the Visibility Improvement State and Tribal 

Association of the Southeast (VISTAS) and the Association for Southeast Integrated 

Planning (ASIP). Through the various iterations, the inventories that have been 

developed have typically had version numbers provided by the contractors who 

developed the inventories and to a certain extent these were also based on their purpose. 

Different components of the 2002 base year inventories have been supplied by 

E.H. Pechan and Associates, Inc. (Pechan), MACTEC Engineering and Consulting, Inc. 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. 2

(MACTEC), and by Alpine Geophysics, Inc. (AG). The projection year inventories were 

developed by MACTEC and AG. 

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

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

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

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

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

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

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

information on temperatures and fuel characteristics were obtained from VISTAS States 

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

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

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

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

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

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

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

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

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

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

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

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

all projected to 2002 using appropriate growth surrogates from Economic Growth 

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

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

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

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

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

Section 1.1.1.3 of this document. 

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

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

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

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

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

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

State forestry agencies provided data for these calculations at least for wild and 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. 3

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

found at: 

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

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

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

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

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

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

solely prepared by MACTEC. The October 2004 inventory incorporated 2002 

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

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

3.1 of the VISTAS inventory. 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

EGU emissions. 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. 4

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

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

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

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

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

inventory. 

Following release of the Base G inventory in early 2007, four States specified additional 

changes to reflect their best estimates of EGU emission levels and controls in 2018. The 

resulting 2018 EGU emission inventory is referred to as Base G2, which was released in 

July 2007. 

The current version of the VISTAS inventory is referred to as the “Best and Final (B&F)” 

inventory. States specified additional changes to the point source inventory to reflect 

improved knowledge of EGU emission levels and controls in 2009 and 2018. States also 

specified changes to nonEGU sources reflecting new information on anticipated controls 

and shutdowns. No changes to any other source sector (e.g., area, fire, nonroad, onroad) 

were made for the B&F inventory. The 2018 B&F inventory was released in October 

2007, and the 2009 B&F inventory was released in December 2007. 

This document details the development of the Base G/G2/B&F inventories for 2002, 

2009 and 2018. The information that follows describes the development of the VISTAS 

inventory by sector from Base F forward. Unless specific updates were made to an 

inventory sector, the methods used for Base F were retained. Table I-1 through Table I-3 

indicate roughly which version of the inventory is in use for each sector of the inventory 

as of the B&F inventory. 

Under a separate contract, AG was asked to obtain and convert emission inventory data 

for the five states that make up the Midwest Regional Planning Organization (MRPO) for 

use by VISTAS/ASIP modelers. Details of this effort are documented in an Appendix to 

this report. 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

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Table I-1 Inventory Version in Use by Year and Source Sector Through B&F - 2002 

Source AL FL GA KY MS NC SC TN VA WV 

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

Non-EGU 

Point 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Base F with 

some source 

specific 

revisions in 

Base G 

Area1 Base F for 

ammonia 

sources 

(CMU 

Model) and 

for some area 

sources, Base 

G for selected 

sources 

updated by 

the State with 

State 

supplied data 

Base F except 

for some 

emissions 

zeroed out 

(and records 

removed) for 

some 

southern FL 

counties for 

Base G. 

Base F Base F Base F Base F for 

ammonia 

sources 

(CMU 

Model) and 

for some area 

sources, Base 

G for selected 

sources 

updated by 

the State with 

State 

supplied data. 

Some 

corrections 

applied by 

MACTEC to 

correct PM 

values 

Base F Base F Base F for 

ammonia 

Sources 

(CMU 

Model) and 

for some area 

sources, Base 

G for selected 

sources 

updated by 

the State with 

State 

supplied data. 

Base F 

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

Non-road Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources, 

except 

aircraft and 

locomotives 

updated for 

Base G. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

except for 

aircraft in 

Cincinnati/N. 

KY Int. 

Airport, 

which are 

Base G. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. NC 

moved from 

Southern to 

Mid-Atlantic 

State in 

seasonal 

adjustment 

file. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources, 

except for 

aircraft 

emissions 

which are 

Base G. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F for 

nonNONROAD 

model 

sources 

Fires Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Base F 

Typical 

Notes: 

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

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

States based on OTAQ report. 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

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Table I-2 Inventory Version in Use by Year and Source Sector Through B&F - 2009 

Source AL FL GA KY MS NC SC TN VA WV 

EGU1 Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final 

Non-EGU 

Point2

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Area Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Some 

specific 

source 

categories 

updated using 

State 

supplied file 

to override 

projected 

values. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

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

Non-road Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

except for 

aircraft in 

Cincinnati/N. 

KY Int. 

Airport, 

which are 

Base G using 

State 

supplied 

growth 

factors. 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for all 

sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Fires Base F 

typical except 

for Rx fires 

Base F 

typical 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Base F 

typical except 

for Rx fires 

Notes: 

1. All EGU emissions updated with new IPM runs in Base G; additional EGU-specific changes specified by States for Best & Final. 

2. Revised growth factors from DOE AEO2006 fuel use projections 
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Table I-3 Inventory Version in Use by Year and Source Sector Through B&F - 2018 

Source AL FL GA KY MS NC SC TN VA WV 

EGU1 Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final Best & Final 

Non-EGU 

Point2

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

Base G2 and 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

Base G2 and 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

Base G2 and 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

B&F 

Base F 

methodology 

but with 

revised 

growth 

factors for 

fuel fired 

sources in 

Base G and 

sourcespecific 

changes in 

Base G2 and 

B&F 

Area Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Some 

specific 

source 

categories 

updated 

using State 

supplied file 

to override 

projected 

values. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

Base F with 

updated AEO 

growth 

factors for 

fuel fired 

sources. 

Agricultural 

ammonia 

sources from 

CMU model. 

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

Non-road Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources. 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

except for 

aircraft in 

Cincinnati/N. 

KY Int. 

Airport, 

which are 

Base G using 

State 

supplied 

growth 

factors. 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Base G for 

all sources 

included in 

the 

NONROAD 

model. 

Base F 

projection 

methodology 

used for nonNONROAD 

model 

sources 

Fires Base F 

typical 

except for Rx 

fires 

Base F 

typical 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Base F 

typical 

except for Rx 

fires 

Notes: 

1. All EGU emissions updated with new IPM runs in Base G; additional EGU-specific changes specified by States for Base G2 and 

B&F. 

2. Revised growth factors from DOE AEO2006 fuel use projections 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

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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) States and local (S/L) agencies to the United States 

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

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

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

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

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

completing quality assurance reviews for each component of the point source inventory, and 6) 

updating the database with corrections or new information from S/L agencies based on their 

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

the first portion of this section. 

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

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

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

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

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

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

typical year EGU inventory. 

1.1.1 Development of 2002 Point Source Inventory 

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

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

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

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

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

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

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

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

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

additional Quality assurance/Quality control (QA/QC) checks. 
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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 next 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. Note that no changes to the Base G 2002 point source 

inventory were made during the Base G2 and B&F update cycles (in other words, for the 2002 

actual and typical inventories, Base G = Base G2 = B&F). 

The following subsections document the data sources for the Base G/B&F inventory, the checks 

made on the CERR submittals, the process for augmenting the inventory with PM10 and PM2.5

emissions, the evaluation of EGU emissions, other QA/QC checks, and other Base G updates. 

The final subsection summarizes the Base G/B&F 2002 inventory by state, pollutant, and sector 

(EGU and non-EGU). 

1.1.1.1 Data Sources 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

detailed review of the Base F inventory. Additional updates and corrections to the Base F 
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MACTEC, Inc. 11

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. No additional changes to the Base G 

inventory were made as part of the Base G2/B&F round of updates. 

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

State / Local Program Point Source Emissions Data Source 

AL C 

FL B 

GA B 

KY C 

MS B 

NC C 

SC C 

TN C 

VA B 

WV B 

Davidson County, TN B 

Hamilton County, TN D 

Memphis/Shelby County, TN B 

Knox County, TN B 

Jefferson County, AL B 

Jefferson County, KY B 

Buncombe County, NC B 

Forsyth County, NC B 

Mecklenburg County, NC B 

Key 

A = Draft VISTAS 2002 

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

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

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

1.1.1.2 Initial Data Evaluation 

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

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

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

associated with the CERR data: 

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

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

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

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

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

point source inventory were included in the CERR area source inventory. 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

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

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

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

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

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

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

PM pollutants is discussed later in Section 1.1.1.3) 

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

emission summaries using consistent units. 

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

2002 base year. 

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

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

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

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

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

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

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

emissions analysis is discussed later in Section 1.1.1.4) 

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

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

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

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

facility level emissions for reasonableness and accuracy. 

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

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

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

1.1.1.3 PM Augmentation 

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

PM Category Description 

PM-PRI Primary PM (includes filterable and condensable) 
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PM-CON Primary PM, condensable portion 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 

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

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

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

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

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

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

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

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

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

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

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

augmentation procedure includes the following five steps: 

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

 Step 2: Develop and Apply Source-Specific Conversion Factors 

 Step 3: Prepare Factors from PM Calculator 

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

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

Information. 

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

procedures. 

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

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

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

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

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

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

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

Base F inventory and for South Carolina in the Base G inventory. 
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Table 1.1-2 Comparison of Particulate Matter Emissions from the S/L Data Submittals 

and the Base G 2002 VISTAS Point Source Inventory 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

PM augmentation methodologies described in this document. 

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

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

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

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

changes were reflected in the Base F emission inventory. 

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

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

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

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

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

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

in the Base G emission inventory. 

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

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

after the PM augmentation was performed as discussed in Section 1.1.1.6. 
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After the PM augmentation process was performed, we executed a series of checks to identify 

potential inconsistencies in the PM inventory. These checks included: 

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

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

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

 PM10-FIL less than PM2.5 -FIL; 

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

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

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

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

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

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

process level pollutant corrections. 

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

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

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

1.1.1.4 EGU Analysis 

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

agencies CERR submittals and EPA’s Clean Air Markets Division (CAMD) CEM database to 

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

are subject to CEM reporting requirements of the NOx State Implementation Plan (SIP) Call rule 

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

level, and we compared these annual CEM emissions to those in the S/L inventories. The 2002 

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

the EPA CAMD web site (www.epa.gov/airmarkets). 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

in the S/L inventories. 

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

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

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

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

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

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

The final step was to compare the SO2 and NOx emissions for select Southern Company units in 

the VISTAS region. Southern Company is a super-regional company that owns EGUs in four 

VISTAS States – Alabama, Florida, Georgia, and Mississippi – and participates in VISTAS as an 

industry stakeholder. Southern Company independently provided emission estimates for 2002 as 

part of the development of the preliminary VISTAS 2002 inventory. In most cases, these 

estimates were reviewed by the States and incorporated into the States CERR submittal. The 

exception to this was a decision made by Georgia’s Department of Environmental Protection 

(GDEP) to utilize CEM-based emissions for the actual 2002 emissions inventory for sources 

within the State when Southern Company also provided data. There were no major 

inconsistencies between the Southern Company data, the CAMD data, and the S/L CERR data. 

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

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

units in S/L CERR submittals where CAMD listed each unit individually. We compared SO2 and 

NOx emissions on a unit by unit basis and did not find any major inconsistencies. 

1.1.1.5 QA Review of Base F Inventory 

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

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

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

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

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

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

revised 2002 base year inventory: 

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

emissions were consistent and that there were no missing sources. 

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

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

NEI Version 2 inventory. 

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

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

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

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

to implementing the changes in the files. 

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

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

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

1.1.1.6 Additional Base G Updates and Corrections 

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

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

incorporated into the Base G inventory. 

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

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

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

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

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

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

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

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

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

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

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

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

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

State Point Source Contacts and VISTAS EGU Special Interest Workgroup, June 13, 2005. 
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Table 1.1-3 Summary of Updates and Corrections to the Base F 2002 Inventory 

Incorporated into the 2002 Base G Inventory. 

Affected 

State(s) Nature of Update/Correction 

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

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

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

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

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

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

ranges typically termed "acceptable" for AQ modeling. 

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

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

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

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

coordinated in the ER file. 

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

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

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

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

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

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

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

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

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

two decimal places were not corrected. 

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

tons VOCs instead of 2819.19 tons in 2002 

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

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

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

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

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

reflected in the Base G emission inventory. 

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

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

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

2002 emission inventory update. 

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

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

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

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

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

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

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

that do not appear to fall into the ranges typically termed "acceptable" for AQ modeling. 
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1.1.1.7 Summary of B&F 2002 Inventory 

Tables 1.1-4 through 1.1-10 summarize the B&F 2002 base year inventory. All values are in 

tons. Note that no changes to the Base G 2002 point source inventory were made during the Base 

G2 and B&F update cycles (in other words, Base G = Base G2 = B&F) 

For the purposes of Tables 1.1-4 through 1.1-10, EGU emissions include the emissions from all 

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

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

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

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

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

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

the VISTAS inventory that are not in CAMD’s 2002 CEM database or the IPM forecasted 

emissions. The minor inconsistencies result in a less than 2 percent difference between the 

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

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

State All Point Sources EGUs Non-EGUs 

AL 544,309 447,828 96,481 

FL 518,721 453,631 65,090 

GA 568,731 514,952 53,778 

KY 518,086 484,057 34,029 

MS 103,388 67,429 35,960 

NC 522,113 477,990 44,123 

SC 259,916 206,399 53,518 

TN 413,755 334,151 79,604 

VA 305,106 241,204 63,903 

WV 570,153 516,084 54,070 

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

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 
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Table 1.1-5 Base G / B&F 2002 VISTAS Point Source Inventory for NOx (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 244,348 161,038 83,310 

FL 302,834 257,677 45,156 

GA 196,767 147,517 49,251 

KY 237,209 198,817 38,392 

MS 104,661 43,135 61,526 

NC 196,782 151,854 44,928 

SC 130,394 88,241 42,153 

TN 221,652 157,307 64,344 

VA 147,300 86,886 60,415 

WV 277,589 230,977 46,612 

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

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

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

State All Point Sources EGUs Non-EGUs 

AL 49,332 2,295 47,037 

FL 40,995 2,524 38,471 

GA 34,952 1,244 33,709 

KY 46,321 1,487 44,834 

MS 43,852 648 43,204 

NC 62,170 988 61,182 

SC 38,927 470 38,458 

TN 85,254 926 84,328 

VA 43,906 754 43,152 

WV 15,775 1,180 14,595 

Total 461,484 12,516 448,970 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 
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Table 1.1-7 Base G / B&F 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 / B&F 2002 VISTAS Point Source Inventory for PM10-PRI (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 32,886 7,646 25,240 

FL 57,243 21,387 35,857 

GA 32,834 11,224 21,610 

KY 21,326 4,701 16,626 

MS 21,106 1,633 19,472 

NC 36,592 22,754 13,838 

SC 35,542 21,400 14,142 

TN 49,814 14,640 35,174 

VA 17,211 3,960 13,252 

WV 22,076 4,573 17,503 

Total 326,630 113,918 212,714 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 
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Table 1.1-9 Base G / B&F 2002 VISTAS Point Source Inventory for PM2.5 -PRI (tons/year). 

State All Point Sources EGUs Non-EGUs 

AL 23,291 4,113 19,178 

FL 46,148 15,643 30,504 

GA 22,401 4,939 17,462 

KY 14,173 2,802 11,372 

MS 11,044 1,138 9,906 

NC 26,998 16,498 10,500 

SC 27,399 17,154 10,245 

TN 39,973 12,166 27,807 

VA 12,771 2,606 10,165 

WV 15,523 2,210 13,313 

Total 239,721 79,269 160,452 

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

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

State All Point Sources EGUs Non-EGUs 

AL 2,200 317 1,883 

FL 1,657 234 1,423 

GA 3,697 83 3,613 

KY 1,000 326 674 

MS 1,359 190 1,169 

NC 1,234 54 1,180 

SC 1,553 142 1,411 

TN 1,817 204 1,613 

VA 3,230 127 3,104 

WV 453 121 332 

Total 18,200 1,798 16,402 

Note: EGU emissions include SCCs 1-01-xxx-xx and 2-01-xxx-xx; non-EGU has all other SCCs. 
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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) period and was used to determine the 

regional haze reasonable progress goals. Actual 2002 emissions were used when comparing the 

CMAQ modeling results to the 2002 measurements in the model performance evaluation. A 

detailed discussion of how the actual and typical year EGU inventories were used for modeling 

is contained in the Technical Support Document for VISTAS Emissions and Air Quality Modeling 

to Support Regional Haze State Implementation Plans located on the VISTAS web site 

(http://www.vistas-sesarm.org ) 

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

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

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

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

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

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

actual 2002 heat input and the average heat input for the 5-year period from 2000-2004 as the 

normalization factor, as follows: 

Normalization Factor: 2000-2004 average heat input 

 2002 actual heat input

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

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

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

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

Typical Emissions = 2002 actual emissions x Normalization Factor 

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

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

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

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

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

emissions. 

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

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

Further documentation of how Southern Company created the typical year inventory for their 
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units can be found in Developing Southern Company Emissions and Flue Gas Characteristics 

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

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

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

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

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

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

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

the Base F inventory). 

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

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

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

the Base G inventory. 

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

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

were about 1.6 percent higher than the typical year emissions. The differences on a state-be-state 

basis ranged from actual emissions being 2.3 percent lower in Kentucky to 10.9 percent higher in 

Mississippi. For the entire VISTAS region, actual 2002 NOx emissions were about 1.7 percent 

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

actual emissions being 1.6 percent lower in Kentucky to 6.3 percent higher in Mississippi. 

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

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

State Actual 2002 Typical 2002 Percentage 

Difference Actual 2002 Typical 2002 Percentage Difference 

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

FL 453,631 444,383 2.0 257,677 255,678 0.8 

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 3,683,968 1.6 1,523,449 1,497,864 1.7 

Note: a negative percentage difference indicates actual emissions are less than the typical year emissions. 
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1.2 Area Sources 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

1.2.1 Development of a “typical” year fire inventory 

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

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

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

of calculating actual fire emissions. 

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

Land Clearing 9 9 9 9 

Ag Burning 9 9 9 9 

Wildfires 9 9 9 9 9 9 9 9 9 9

Prescribed 9 9 9 9 9 9 9 9 9

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

VISTAS State. A minimum of three or more years of data were used to develop the ratios. Those 
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data were then used to develop a ratio for each county based on the number of acres burned in 

each county for each fire type relative to 2002. 

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

acreage ratio of: 

2002 actual county levelRx acreage

Long term average county levelRx acres Ratio =

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 

13063 Clayton County 

13083 Dade County 

13089 Dekalb County 

13097 Douglas County 

13121 Fulton County 

13135 Gwinnett County 

13137 Habersham County 

13215 Muscogee County 

13227 Pickens County 

13241 Rabun County 

13247 Rockdale County 

13311 White County 

13059 Clarke County 

13083 Dade County 

13089 Dekalb County 

13097 Douglas County 

13121 Fulton County 

13123 Gilmer County 

13135 Gwinnett County 

13139 Hall County 

13215 Muscogee County 

13241 Rabun County 

13247 Rockdale County 
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Land Clearing Agricultural Fires Prescribed Burning 

FIPS COUNTY FIPS COUNTY FIPS COUNTY 

13151 Henry County 

13169 Jones County 

13215 Muscogee County 

13237 Putnam County 

13241 Rabun County 

13291 Union County 

13311 White County 

There were three exceptions to this method. 

Exception 1: Use of State Ratios for Wildfires 

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

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

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

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

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

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

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

Exception 2: Correction for Blackened Acres on Forest Service Lands 

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

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

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

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

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

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

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

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

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

to all values reported for Forest Service managed lands. 

Exception 3: Missing/Non-reported data 

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

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

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

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

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

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

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

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

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

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

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

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

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

year values. 

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

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

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

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

distribution of fires in the example plots. 
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Table 1.2-1 Emissions from Fires in the VISTAS Region – Comparison between Original Base Year 2002 

Actual and Typical Year Base G Emissions. 

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

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

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

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

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

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

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

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

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

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

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

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

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

change in methodology for Base F and Base G) for 2002. 
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Figure 1.2-1 CO Emissions from Agricultural Burning for the Original Base Year, 2002 Actual Base G, 

Base G Inventories.

CO Emissions

0.00

20,000.0040,000.0060,000.0080,000.00

100,000.00120,000.00140,000.00160,000.00

AL FL GA KY MS NC SC TN VA 

tons

Ag Burning - 2002 Actual Ag Burning - Typical Ag Burning - VISTAS 3.1
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Figure 1.2-2 CO Emissions from Land Clearing Burning for the Original Base Year, 2002 Actual Base G 

Base G Inventories. 

CO Emissions

0.00

20,000.0040,000.0060,000.0080,000.00

100,000.00120,000.00140,000.00160,000.00180,000.00

AL FL GA KY MS NC SC TN 

tons

Land Clearing - 2002 Actual Land Clearing - Typical Land Clearing - VISTAS 
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Figure 1.2-3 CO Emissions from Prescribed Burning for the Original Base Year, 2002 Actual Base G and 

Inventories. 

CO Emissions

0.00

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

AL FL GA KY MS NC SC TN 

tons

Prescribed - 2002 Actual Prescribed - Typical Prescribed - VISTAS 3.1
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Figure 1.2-4 CO Emissions from Wildfire Burning for the Original Base Year, 2002 Actual Base G an

Base G Inventories.

CO Emissions

0.00

50,000.00

100,000.00150,000.00200,000.00250,000.00

AL FL GA KY MS NC SC TN VA 

tons

Wildfires - 2002 Actual Wildfires - Typical Wildfires - VISTAS 3.1
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1.2.2 Development of non-fire inventory 

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

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

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

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

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

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

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

CERR data as part of Base F. 

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

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

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

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

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

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

not include PM emissions from paved roads. Each of those categories was estimated separately. 

Data on the CERR submittals was obtained from EPA’s Draft NEI download file transfer 

protocol (FTP) site where the data are stored after they’ve been processed for review. The data 

submitted in National Emission Inventory Format (NIF) was downloaded from that site. Once all 

of the files were obtained, MACTEC ran the files through the EPA NIF Format and Content 

checking tool to ensure that the files were submitted in standard NIF format and that there were 

no issues with those files. In a couple of cases small errors were found. For example, in one case 

a county FIPs code that was no longer in use was found. MACTEC contacted each VISTAS 

State area source contact person to resolve the issues with the files and corrections were made. 

Once all corrections to the native files were completed, MACTEC continued with the 

incorporation of the data into the VISTAS area source files. 

Our general assumption was that unless we determined otherwise, the CERR submittals 

represented full and complete inventories. Where a State submitted a complete inventory, our 

plan was to simply delete the previous 2002 base year data and replace it with the CERR 

submittal. Prior to this replacement however, we stripped out the following emissions: 

1. All wildfire, prescribed burning, land clearing and agricultural burning emissions 

submitted to EPA by the States as part of the CERR process were removed since they 

were to be replaced with emissions estimated using methods described earlier. 

2. All fertilizer and agricultural ammonia emission records submitted to EPA by the 

States as part of the CERR process were removed. These were replaced with the 

estimates developed using the CMU Ammonia model. 
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3. All emissions from paved roads submitted to EPA by the States as part of the CERR 

process were removed. These emissions were replaced with updated emissions 

developed by U.S. EPA as part of their 2002 NEI development effort. 

This approach was used for most State and Local emission submittals to prepare the Base F 

inventory. There were a few cases where alternative data were used to prepare the Base F 

inventory. In general, these alternatives involved submittal of alternative files to the CERR data 

by S/L agencies. Table 1.2-2 below summarizes the data used to prepare the Base F inventory. In 

general the data were derived from one of the following sources: 

1. CERR submittal obtained from EPA FTP site as directed by VISTAS States; 

2. State submitted file (either revised from CERR submittal or separate format); 

3. VISTAS original 2002 base year (VISTAS version 3.1 base year file); or 

4. EPA’s preliminary 2002 NEI. 

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

Base F Inventory 

State / Local Program Area Source Emissions Data Source 

AL B 

FL B 

GA C 

KY A 

MS B 

NC C 

SC B 

TN B 

VA B 

WV A/C 

Davidson County, TN B 

Hamilton County, TN C 

Memphis/Shelby County, TN A 

Knox County, TN B 

Jefferson County, AL * so B from State 

Jefferson County, KY B 

Buncombe County, NC * so C from State 

Forsyth County, NC * so C from State 

Mecklenburg County, NC * so C from State 

A = VISTAS 2002 (version 3.1) 

B = CERR Submittal from EPA's ftp site 

C = Other (CERR or other submittal sent directly from State to MACTEC) 

* = No response 
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In order to track the sources of data in the final Base F and Base G NIF files, a field was added to 

the NIF format files developed for VISTAS to track each data source. A field named 

Data_Source was added to the EM table. A series of codes were added to this field to mark the 

source of each emissions value in the Base F and Base G inventories. Values in this field are 

detailed in Table 1.2-3. 

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

Emissions Inventory. 

Data Source Codes Data Source 

Base F Codes 

CMU Model CMU Ammonia model v 3.6 

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

EPA Paved EPA Paved Road emissions estimates 

EPAPRE02NEI EPA Preliminary 2002 NEI 

STATEFILE State submitted file 

VISTBASYR31 VISTAS 2002 Base Year version 3.1 

VISTRATIO Developed from VISTAS Ratios (used only 

for missing pollutants) 

Additional Base G Codes 

ALBASEGFILE Base G update file provided by AL 

NCBASEGFILE Base G update file provided by NC 

OTAQRPT Portable Fuel Container Emissions from 

OTAQ Report 

STELLA Revised data provided by VISTAS EI Advisor 

Greg Stella 

VABASEGFILE Base G update file provided by VA 

VAStateFile Revisions/additions to Base G update file 

provided by VA 

Most States submitted complete inventories for Base F. Virginia’s inventory required a two stage 

update. Virginia’s CERR submittal only contained ozone precursor pollutants (including CO). 

For Virginia, MACTEC’s original plan was to maintain the previous 2002 VISTAS base year 

emissions for non-ozone pollutants and then do a simple replacement for ozone pollutants. 

However during the QA phase of the work, MACTEC discovered that there were categories that 

had ozone precursor or CO emissions in the submittal that weren’t in the original 2002 VISTAS 

base year inventory that should have PM or SO2 emissions. For those records, MACTEC used an 
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emissions ratio to build records for emissions of these pollutants. Data for Virginia PM and SO2

emissions were generated by developing SCC level ratios to NOx from the VISTAS 2002 base 

year inventory (version 3.1) or from emission factors and then calculating the emissions based on 

that ratio. 

1.2.3 2002 Base G inventory updates 

After the Base F inventory was submitted and used for modeling, VISTAS States were provided 

an opportunity for further review and comment on the Base F inventory. As a result of this 

review and comment period, several VISTAS States provided revisions to the Base F inventory. 

In addition to and as an outgrowth of some of the comments provided by the States during the 

review process, some of the changes made to the inventory were made globally across the entire 

VISTAS region. This section discusses the specific State changes followed by the global changes 

made to the area source component of the inventory for all VISTAS States. 

1.2.3.1 Changes resulting from State review and comment 

Alabama

Alabama suggested several changes and had questions concerning a few categories in the Base F 

inventory. The changes/questions were: 

1. For Source Classification Code (SCC) 2102005000 (Industrial Boilers: 

Residual Oil) and SCC 2103007000 (Institutional/Commercial Heating: 

Liquefied Petroleum Gas) the Alabama noted that the Base F VISTAS 

inventory had values for NOx, VOC and CO for the State, but no values for 

SO2, PM10 or PM2.5. 

MACTEC evaluated this information and found that there were actually emissions for two 

counties in AL for that SCC that had either SO2 and/or PM emissions. The data used to develop 

the 2002 Base F inventory for AL came from the preliminary 2002 CERR submittals (see above) 

which should have included SO2 and PM but did not except for two counties. According to 

MACTEC’s protocol for use of these files, the files received from EPA were to be used “as is” 

unless the States provided comments during the Base F comment period to correct the CERR 

submittal. No comments were received from AL on the CERR submittal used for Base F. For 

2002 Base G, AL provided an updated database file for these SCCs for all counties in the State 

that provided revised values for emissions and included SO2 and PM. The revised file was used 

to update the Base F data for Base G. 

2. AL noted that the Base F inventory included SCC 2401002000 (Solvent 

Utilization, Surface Coating, Architectural Coatings - Solvent-based, Total: 

All Solvent Types) and 2401003000 (Solvent Utilization, Surface Coating, 
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Architectural Coatings - Water-based, Total: All Solvent Types) as well as 

SCC 2401001000 (Solvent Utilization, Surface Coating, Architectural 

Coatings, Total: All Solvent Types). This resulted in double counting of the 

emissions for this category. AL suggested removal of the breakdown SCCs 

and use of the total SCC. 

MACTEC deleted records for the breakdown SCCs and retained the total all solvents 

SCC emissions. 

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

SCC 

VOC 

Emissions SCC Description 

2401025000 1139.91 Surface Coatings: Metal Furniture, all coating types 

2401030000 425.27 Surface Coatings: Paper, all coating types 

2401065000 344.08 Surface Coatings: Electronic and Other Electrical, all coating 

types 

2430000000 504.29 Solvent Utilization, Rubber/Plastics, All Processes, Total: All 

Solvent Types 

2440020000 3043.78 Solvent Utilization, Miscellaneous Industrial, Adhesive 

(Industrial) Application, Total: All Solvent Types 

Total for AL 5457.32 

MACTEC found that the emissions for these SCCs were included in the Base F inventory, but 

with slightly different total emissions. AL provided an updated county-level emissions file for 

use in updating the Base G inventory. That file was used to update the NIF records for AL for 

those SCCs. 

4. AL noted that emissions in the Base F inventory were found for SCC 

2465000000 and SCCs 2465100000, 2465200000, 2465400000, 2465600000, 

and 2465800000. These last five SCCs represent a subset of the emissions in 

the 246500000 SCC resulting in potential double counting of emissions. 

MACTEC deleted all emissions associated with the Total SCC 2465000000 and retained the 

subset SCCs for the Base G inventory. 

Florida

Florida provided comments indicating that they felt that emissions from the following sources 

and counties were too high, especially for CO and PM and were likely zero: 
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 motor vehicle fire - Palm Beach County 

 woodstoves - Miami Dade, Hillsborough, Orange, Polk, Ft Myers, Pasco and Sarasota 

Counties 

 fireplaces - Miami Dade and Hillsborough Counties 

Emissions from these sources in the counties specified were set to zero by MACTEC for the 

Base G inventory. 

North Carolina

North Carolina provided corrected emission files for 2002 Base F. A text file with emission 

values was provided and used to update the Base F emissions to Base G. The updated emissions 

were applied directly to the Base F NIF file. The file provided was similar to the “EM” NIF 

table. An update query was used to update the data supplied in the text file to the Access 

database NIF file. All changes were implemented. 

South Carolina

South Carolina had two issues concerning the Base F inventory. These issues related to 1) 

additional SCCs that were in BASE F 2009 and 2018, but not in 2002 Base F and 2) SCCs that 

were in the U.S. EPA 2002 NEI inventory, but not in the VISTAS 2002, 2009, or 2018 Base F 

inventory. 

MACTEC investigated the additional SCCs found in 2009 and 2018 Base F and found that the 

SCCs actually were not missing in the 2002 Base F inventory but only had emissions for PM. 

Thus the emissions were maintained as they were provided in Base F. 

With respect to the SCCs that were found in the U.S. EPA 2002 NEI, MACTEC investigated and 

found that they were not included in the Base F inventory because they were not included in the 

2002 CERR submittal used to produce the Base F updates. The SCCs were apparently added by 

EPA later in the NEI development process. In addition, MACTEC also evaluated whether or not 

the SCCs were found in other VISTAS States Base F inventories. MACTEC found that some 

States included them and some did not, there was no consistency between the States. MACTEC 

also found that typically emissions for these SCCs were low in emissions, generally with 

emissions of only a few tons to tens of tons per year. The decision was made with South Carolina 

concurrence not to add these SCCs to the Base G inventory. These SCCs were: 210205000, 

2102011000, 2103007000, 2103011000, 2104007000, 2104011000, 2302002100, 2302002200, 

2302003100, 2302003200, 2610000500, 2810001000, and 281001500. 
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Virginia

Virginia provided an updated 2002 base year emissions file. The data in that file were used to 

update the Base F inventory emission values to those for Base G. In addition, Virginia provided 

information on several source categories that required controls for future year projections since 

the sources were located in counties/cities in northern Virginia and were subject to future year 

Ozone Transport Commission (OTC) regulations. MACTEC added in the base year control 

levels to the Base G inventory file for these categories so that they could be estimated correctly 

in future years. The controls added were for mobile equipment repair/refinishing sources, 

architectural and industrial maintenance coating sources, consumer products sources, and solvent 

metal cleaning sources. Minor errors were found in some entries for the initial file provided and 

VA provided a revised file with corrections and minor additions. 

1.2.4 Ammonia and paved road emissions 

The final component of the Base F inventory development was estimation of NH3 emission 

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

estimates for livestock and fertilizers we used version 3.6 of the CMU NH3 model 

(http://www.cmu.edu/ammonia/). Results from this model were used for all VISTAS States. The 

CMU model version 3.6 was used in large part because it had been just recently been updated to 

include the latest (2002) Census of Agriculture animal population statistics. Prior to inclusion of 

the CMU model estimates, MACTEC removed any ammonia records for agricultural livestock or 

fertilizer emissions from the VISTAS 2002 initial base year inventory. MACTEC also generated 

emissions from human perspiration and from wildlife using the CMU model and added those 

emissions for each State. 

For the Base G ammonia inventory, MACTEC removed all wildlife and human perspiration 

emissions. VISTAS decided to remove these emissions from the inventory. Human perspiration 

was dropped due to a discrepancy in the units used for the emission factor that was not resolved 

prior to preparing the estimates and wildlife was dropped because VISTAS felt the activity data 

was too uncertain. Thus all emissions from these two categories were deleted in the Base G 

2002 inventory. 

For the paved road PM Base F emissions, we used the most recent estimates developed by EPA 

as part of the NEI development effort (Roy Huntley, U.S. EPA, email communication, 

8/30/2004). EPA had developed an improved methodology for estimating paved road emissions 

for 2002 and had used that method to calculate emissions for that source category. MACTEC 

obtained those emissions from EPA and those values were substituted directly into the inventory 

after receiving consensus from all of the VISTAS States to perform the replacement. These files 

were obtained in March of 2005 in NIF format from the EPA FTP site. 
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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. 

1.2.5 Global Changes Made for Base G 

There were three global changes made between the Base F and the Base G inventory (beyond the 

removal of wildlife and human perspiration NH3 emissions). These changes were: 

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

sector of the inventory, 

2. Adjustment of fugitive dust PM2.5 emissions, and 

3. Addition of emissions from portable fuel containers. 

As part of the Base F review process, several VISTAS States had expressed surprise that the 

Stage II refueling emission estimates were in the area source component of the inventory. This 

decision had been made with SIWG agreement early on in the inventory development process 

because 1) some States had included it in their CERR submittals and 2) because the non-road and 

on-road mobile estimates had differing activity factor units and could not be easily combined. 

However for Base G, the VISTAS States all agreed, especially in light of the different ways in 

which the emissions were reported in the CERR, to remove the Stage II refueling emissions from 

the area source inventory and include them in the non-road and on-road sectors. Thus all records 

related to Stage II refueling were removed from the area source component of the Base 

G inventory. 

PM2.5 emissions from several fugitive dust sources were also updated for Base G. The Western 

Regional Air Partnership (WRAP) and U.S. EPA had been investigating overestimation of the 

PM2.5 / PM10 ratio in several fugitive dust categories and U.S. EPA was in the process of making 

revisions to AP-42 for several categories during preparation of the Base G inventory. Based on 

data received from U.S. EPA, VISTAS decided to revise the PM2.5 emissions from construction, 

paved roads and unpaved road sources. PM2.5 emissions in Base F were multiplied by 0.67, 0.6, 

and 0.67 for construction, paved roads and unpaved roads respectively to produce the values 

found in Base G. No changes were made to PM10, only to PM2.5. 

Finally, as part of Virginia’s comments on the Base F inventory, emissions from portable fuel 

containers were mentioned as being absent from the inventory. MACTEC was tasked with 

developing a methodology that could be used to add these emissions to the Base G area source 

inventory. In investigating options for a method of estimating emissions, MACTEC found that 

the U.S. EPA had prepared a national inventory of emissions by State for portable fuel 
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containers. Data on emissions from this source prepared by U.S. EPA were presented in, 

“Estimating Emissions Associated with Portable Fuel Containers (PFCs), Draft Report, Office of 

Transportation and Air Quality, United States Environmental Protection Agency, Report # 

EPA420-D-06-003, February 2006”. 

State-level emission estimates for 2005 derived from Appendix Table B-2 of the PFCs report 

were used as the starting point for developing 2002 county-level emissions estimates. State 

emissions were derived from that table by using all of the emission estimates in that table with 

the exception of values for vapor displacement and spillage from refueling operations. Those 

components of the State emissions were left out of the State-level emissions to avoid double 

counting refueling emissions in the non-road sector. For the purposes of 2002 emission estimates 

for Base G, the 2005 values were assumed equal to 2002 values. 

The 2005 State-level estimates minus the refueling component from Appendix Table B-2 of the 

report were summed for each State and then allocated to the county-level. The county-level 

allocation was based on the fuel usage information obtained from the NONROAD 2005 model 

runs conducted as part of the Base G inventory development effort (see the 2002 base year Base 

G non-road section below). MACTEC used the spillage file from the NONROAD model 

(normally located in the DATA\EMSFAC directory in a standard installation of NONROAD) to 

determine the SCCs that used containers for refueling. The spillage file contains information by 

SCC and horsepower indicating whether or not the refueling occurs using a container or a pump. 

All SCC and horsepower classes using containers were extracted from the file and crossreferenced with the fuel usage by county for those SCC/horsepower combinations from the 

appropriate year model runs (2002, 2009 or 2018). Then the fuel usages by county from the 

NONROAD 2005 runs prepared for VISTAS were summed for those SCCs by county. The 

county level fuel use was then divided by the State total fuel use for the same SCCs to determine 

the fraction of total State fuel usage and that fraction was used to allocate the State-level 

emissions to the county. 

1.2.6 Quality Assurance steps 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, and to ensure that a full and complete 

inventory was developed for VISTAS. Quality assurance was an important component to the 

inventory development process and MACTEC performed the following QA steps on the area 

source component of the 2002 Base F inventory: 

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

Format and Content checking software. 
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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. 

4. Fields were either added or used within each NIF data table to track the sources of 

data for each emission record. 

5. Data product summaries were provided to both the VISTAS Emission Inventory 

Technical Advisor and to Area Source and Fires SIWG representatives for review and 

comment. Changes based on these comments were implemented in the files. 

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

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

example, a major change would result in a version going from 1.0 to 2.0. A minor 

change would cause a version number to go from 1.0 to 1.1. Minor changes resulting 

from largely editorial changes would result in a change from 1.00 to 1.01. 

In addition, for the fires inventory, data related to fuel loading and fuel consumption was 

reviewed and approved by the VISTAS Fire SIWG to ensure that values used for each type of 

fire and each individual fire were appropriate. Members of the VISTAS Fire SIWG included 

representatives from most State Divisions of Forestry (or equivalent) as well as U.S. Forest 

Service and National Park Service personnel. 

For Base G, similar QA steps to those outlined above for Base F were undertaken. In addition, all 

final NIF files were checked using the EPA Format and Content checking software and summary 

information by State and pollutant were prepared comparing the Base F and Base G inventories. 

1.3 Mobile Sources 

This section describes the revisions made to the initial 2002 VISTAS Base Year emission 

inventory on-road mobile source input files. For this work actual emission estimates were not 

made, rather data files consistent with Mobile Emissions Estimation Model Version 6 

(MOBILE6) were developed and provided to the VISTAS modeling contractor. These input data 

files were then run during the VISTAS modeling to generate on-road mobile source emissions 

using episodic and meteorological specific conditions configured in the sparse matrix operator 

Kernel Emissions modeling system (SMOKE) emissions processor. 

During initial discussions with the VISTAS Mobile Source SIWG, some States indicated a desire 

to use CERR mobile source emissions data in place of the VISTAS 2002 inventories generated 

by E.H. Pechan and Associates, Inc. (the initial VISTAS 2002 Base Year inventory files). 
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However, the CERR emissions data by itself were not sufficient for an inventory process that 

includes both base and future year inventories. MACTEC needed to be able to replicate the 

CERR data rather than simply obtain CERR emissions estimates. The reason for this is that only 

input files were being prepared to provide revised 2002 estimates during the VISTAS modeling 

process, rather than the actual emission estimates and that the 2002 input data files would be 

used as a starting point for the projected emission estimates. This meant that the appropriate 

vehicle miles traveled (VMT), MOBILE6, and/or NONROAD model input data needed to be 

provided. If these data were provided with the CERR emissions estimates we used it as the 

starting point for revision of the 2002 Base Year inventory. However MACTEC did not have 

access to the on-road mobile CERR submissions from EPA, so re-submittal of these data directly 

to MACTEC was requested in order to begin compiling the appropriate input file data. 

In those cases where States did not provide CERR on-road mobile source input data files, our 

default approach was to maintain the data input files and VMT estimates for the initial 2002 Base 

Year inventory prepared by Pechan. 

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

Development of the 2002 on-road input files and VMT was a multi-step process depending upon 

what the State mobile source contacts instructed us to use as their data. Information provided 

below provides incremental revisions made to on-road mobile source inventories or inputs in 

series from one inventory version to the next. In general the process involved one of three steps 

from the original 2002 on-road mobile source data. 

Base F Revisions 

1. The first step was to evaluate the initial 2002 base year files and make any nonsubstantive changes (i.e., changes only to confirm that the files posted for 2002 by 

Pechan were executable and that all the necessary external files needed to run MOBILE6 

were present). This approach was taken for AL, FL, GA, MS, SC, and WV. For these 

States the determination was made that the previous files would be okay to use as 

originally prepared. For SC, the VMT file was updated, but that did not affect the 

MOBILE6 input files. 

2. For other States, modification to the input files was required. The information below 

indicates what changes were made for other States in the VISTAS region. 

KY – For Kentucky, the Inspection and Maintenance (I/M) records in the input files for Jefferson 

County were updated in order to better reflect the actual I/M program in the Louisville 

metropolitan area. 
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NC - Substantial revisions were implemented to these input files based on input from the State. 

The modifications necessary to reflect the desires of the State led to complete replacement of the 

previous input files. Among the changes made were: 

 The regrouping of counties (including the movement of some counties from one county 

group to another and the creation of new input files for previously grouped counties). 

There were originally 32 input files; after the changes there were 49. The pointer file was 

corrected to reflect these changes. 

 Travel speeds were updated in over 3000 scenarios. 

 All I/M records were updated. 

 All registration distributions were updated. 

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

 VMT estimates were updated (which has no direct effect on the MOBILE6 input files but 

does ultimately affect emissions). 

3. VA and TN – For these States, new input files were provided due to substantive changes 

that the State wanted to make relative to the 2002 initial base year input files. In addition, 

revised VMT data were developed for each State. 

Base G Revisions

For the production of the VISTAS 2002 Base G inventory, VISTAS states reviewed the Base F 

inputs, and provided corrections, updates and supplemental data. 

For all states modeled, the Base G updates include: 

Adding Stage II refueling emissions calculations to the SMOKE processing. 

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

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

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

NC – revised VMT and registration distributions. 

TN - revised VMT and vehicle registration distributions for selected counties. 

VA – revised winter RFG calculations in Mobile 6 inputs. 

WV – revised VMT input data. 
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AL, FL, and GA did not provide updates for Base G and therefore the Base F inputs were used 

for these States. 

1.3.1.1 Emissions from on-road mobile sources 

The MOBILE6 module of the Sparse Matrix Operator Kernel Emissions (SMOKE) model was 

used to develop the on-road mobile source emissions estimates for CO, NOX, NH3, SO2, PM, and 

VOC emissions. The MOBILE6 parameters, vehicle fleet descriptions, and VMT estimates are 

combined with gridded, episode-specific temperature data to calculate the gridded, temporalized 

emission estimates. The MOBILE6 emissions factors are based on episode-specific temperatures 

predicted by the meteorological model. Further, the MOBILE6 emissions factors model accounts 

for the following: 

 Hourly and daily minimum/maximum temperatures; 

 Facility speeds; 

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

 Adjustments for running losses; 

 Splitting of evaporative and exhaust emissions into separate source categories; 

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

The primary input to MOBILE6 is the MOBILE shell file. The MOBILE shell contains the 

various options (e.g. type of inspection and maintenance program in effect, type of oxygenated 

fuel program in effect, alternative vehicle mix profiles, RVP of in-use fuel, operating mode) that 

direct the calculation of the MOBILE6 emissions factors. The shells used in these runs were 

based on VISTAS Base F modeling inputs as noted in the previous section. 

For this analysis, the on-road mobile source emissions were produced using selected weeks 

(seven days) of each month and using these days as representative of the entire month. This 

selection criterion allows for the representation of day-of-the-week variability in the on-road 

motor vehicles, and models a representation of the meteorological variability in each month. The 

modeled weeks were selected from mid-month, avoiding inclusion of major holidays. 

The parameters for the SMOKE runs are as follows: 

 Episodes: 

 2002 Initial Base Year, and 

2009 and 2018 Future years, using 2009/2018 inventories and modeled using the 

same meteorology and episode days as 2002. 
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 Episode represented by the following weeks per month: 

 January 15-21 

 February 12-18 

 March 12-18 

 April16-22 

 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, NO2, ALD2, ETH, FORM, ISOP, NR, OLE, PAR, TERPB, TOL, 

XYL, NH3, SO2, SULF, PEC, PMFINE, PNO3, POA, PSO4, and PMC. 
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 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. 

The reconstructed emissions based on the representative week run were calculated by mapping 

each day of week (Mon, Tue, Wed, etc.) from the modeled month to the same day of week 

generated in the representative week run. In the case of holidays, these days were mapped to 

representative week Sundays. An example of this mapping for the January episode is presented 

in Table 1.3-1 below. Note that although the emissions were generated for individual calendar 

years (2002, 2009 and 2018) the meteorology is based on 2002. 

Table 1.3-1 Representative day mapping for January episode 

(Highlighted representative week) 

Modeled Representative Modeled Representative Modeled Representative 

Date Day Date Day Date Day 

1/1/2002* 1/20/2002 1/11/2002 1/18/2002 1/22/2002 1/15/2002 

1/2/2002 1/16/2002 1/12/2002 1/19/2002 1/23/2002 1/16/2002 

1/3/2002 1/17/2002 1/13/2002 1/20/2002 1/24/2002 1/17/2002 

1/4/2002 1/18/2002 1/14/2002 1/21/2002 1/25/2002 1/18/2002 

1/5/2002 1/19/2002 1/15/2002 1/15/2002 1/26/2002 1/19/2002 

1/6/2002 1/20/2002 1/16/2002 1/16/2002 1/27/2002 1/20/2002 

1/7/2002 1/21/2002 1/17/2002 1/17/2002 1/28/2002 1/21/2002 

1/8/2002 1/15/2002 1/18/2002 1/18/2002 1/29/2002 1/15/2002 

1/9/2002 1/16/2002 1/19/2002 1/19/2002 1/30/2002 1/16/2002 

1/10/2002 1/17/2002 1/20/2002 1/20/2002 1/31/2002 1/17/2002 

 1/21/2002 1/21/2002 

* Modeled holiday 

1.3.2 Development of non-road emission estimates 

Emissions from non-road sources were estimated in two steps. First, emissions for non-road 

sources that are included in the NONROAD model were developed. Second, emissions from 

sources not included in the NONROAD model were estimated. The sections below detail the 

procedures used for each group of sources. 

1.3.2.1 Emissions from NONROAD model sources 

An initial 2002 base year emissions inventory for non-road engines and equipment covered by 

the EPA NONROAD model was prepared for VISTAS in early 2004. The methods and 

assumptions used to develop the inventory are presented in a February 9, 2004 report 

“Development of the VISTAS Draft 2002 Mobile Source Emission Inventory (February 2004 

Version)” as prepared by E.H. Pechan & Associates, Inc. Except as otherwise stated below, all 
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aspects of the preparation methodology documented in that report continue to apply to the 

revised NONROAD modeling discussed in this section. 

Revisions to the initial 2002 NONROAD emissions inventory were implemented to ensure that 

the latest State and local data were considered, as well as to more accurately reflect gasoline 

sulfur contents for 2002 and correct other State-specific discrepancies. Those revisions comprise 

the Base F VISTAS non-road inventory. This section details the specific revisions made to the 

NONROAD model input files for the Base F and Base G VISTAS base year inventories, and 

provides insight into some key differences between the versions of the NONROAD model 

employed for the Base F and Base G inventories and the previous version employed for the 

initial 2002 base year inventory prepared by Pechan. 

Revisions to the initial 2002 emissions inventory prepared by Pechan were actually implemented 

in two stages. An initial set of revisions was implemented in the fall of 2004. Those revisions 

resulted in the Base F inventory. These were followed by a second set of revisions in the spring 

of 2006. Those estimates produced the Base G base year inventory. To accurately document the 

combined effects of both sets of revisions, each set is discussed separately below. Unless 

otherwise indicated, all revisions implemented in Base F were carried directly into the Base G 

revision process without change. Thus, the inventories that resulted from the Base F revisions 

served as the starting point for the Base G revisions. 

For Base F, three VISTAS States provided detailed data revisions for consideration in 

developing revised model inputs. These States were: 

1. North Carolina 

2. Tennessee (including a separate submission for Davidson County), and 

3. Virginia. 

The remaining seven VISTAS States indicated that the initial 2002 VISTAS input files prepared 

by Pechan continued to reflect the most recent data available. These States were: 

1. Alabama, 

2. Florida, 

3. Georgia, 

4. Kentucky, 

5. Mississippi, 

6. South Carolina, and 

7. West Virginia. 

However, it should be recognized that the NONROAD input files for all ten VISTAS States were 

updated to reflect gasoline sulfur content revisions for the Base F 2002 base year inventory (as 
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discussed below). The original files prepared by Pechan are available on their FTP site in the 

/pub/VISTAS/MOB_0104/ directory. 

Before presenting the specific implemented revisions, it is important to note that the Base F 2002 

base year inventory utilized a newer release of the NONROAD model than was used for the 

initial 2002 base year inventory (prepared by Pechan). The Base F 2002 base year inventory, as 

developed in spring 2004, was based on the Draft NONROAD2004 model, which was released 

by the EPA in May of 2004. This model is no longer available on EPA’s website. The initial 

2002 base year inventory (prepared by Pechan) was based on the Draft NONROAD2002a 

version of the model (which is also no longer available on EPA’s website). Key differences 

between the models are as follows: 

 Draft NONROAD2004 included the effects of the Tier 4 non-road engine and equipment 

standards (this did not impact the Base F 2002 inventory estimates, but did affect Base F 

future year forecasts). 

 Draft NONROAD2004 included the exhaust emission impacts of the large spark-ignition 

engine standards; the evaporative impacts of these standards are not incorporated (this 

does not impact 2002 inventory estimates, but does affect future year forecasts). 

 Draft NONROAD2004 included revised equipment population estimates. 

 The PM2.5 fraction for diesel equipment in Draft NONROAD2004 had been updated from 

0.92 to 0.97. 

 Draft NONROAD2004 included revisions to recreational marine activity, useful life, and 

emission rates. 

To the extent that these revisions affect 2002 emissions estimates, they will be reflected as 

differentials between the initial and Base F 2002 VISTAS base year inventories. It is perhaps 

important to identify that, at the time of the Base F inventory revisions; the EPA recognized the 

Draft NONROAD2004 model as an appropriate mechanism for SIP development. Although the 

model was designated as a draft update, it reflected the latest and most accurate NONROAD 

planning data at that time, as evidenced by the EPA’s use of that version for the Tier 4 

Final Rulemaking. 

Prior to the Base G inventory revisions implemented in 2006, the EPA released another updated 

version of the NONROAD model, designated as Final NONROAD2005 (which can be 

downloaded from: http://www.epa.gov/OMSWWW/nonrdmdl.htm#model). This version 

ostensibly represents the final version of the model, although certain components of it have been 

updated since its first release in December 2005. For the Base G inventory developed in the first 
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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. 

 Final NONROAD2005 includes emission estimates for a range of evaporative emissions 

categories not included in Draft NONROAD2004 (tank and hose permeation, hot soak, 

and running loss emissions). 

 Final NONROAD2005 includes a revised diurnal emissions algorithm. 

 Final NONROAD2005 includes a revised equipment scrappage algorithm. 

 Final NONROAD2005 includes revised state and county equipment allocation data. 

 Final NONROAD2005 allows separate sulfur content inputs for marine and land-based 

diesel fuel. 

 Final NONROAD2005 includes revised conversion factors for hydrocarbon emissions. 

 Final NONROAD2005 includes the evaporative emission impacts of the large 

spark-ignition engine standards (this does not impact 2002 inventory estimates, but does 

affect future year forecasts). 

Unfortunately, due to the extensive revisions associated with Final NONROAD2005, input files 

created for use with Draft NONROAD2004 (e.g., Base F input files) and earlier versions of the 

model cannot be used directly with Final NONROAD2005 (used for Base G). This created a 

rather significant impact in that the VISTAS NONROAD modeling process involves the 

consideration of over 200 unique sets of input data. To avoid creating new input files for each of 

these datasets, a conversion process was undertaken wherein each of the Draft NONROAD2004 

(Base F) input data files were converted into the proper format required for proper execution in 

Final NONROAD2005 (Base G).1

 This process consisted of the following steps: 

 Revise the Draft NONROAD2004 (Base F) input files to include the following two line 

EPA-developed comment at the end of the input file header (this is a nonsubstantive 

change implemented solely for consistency with input files produced directly using Final 

NONROAD2005): 

 

1

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

graphical user interfaces for both Draft NONROAD2004 and Final NONROAD2005. The differences between the 

input files indicated the specific revisions necessary to convert existing VISTAS input files into Final 

NONROAD2005 format. 
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9/2005 epa: Add growth & tech years to OPTIONS packet 

 and Counties & Retrofit files to RUNFILES packet.

 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
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 Revise the Draft NONROAD2004 (Base F) input files to include the following two 

command lines after the “EPS2 AMS” command in the RUNFILES packet: 

US COUNTIES FIPS : c:\non-road\data\allocate\fips.dat 

RETROFIT :

 Revise the Draft NONROAD2004 (Base F) input files to include the following command 

line after the “Rec marine outbrd” command in the ALLOC FILES packet: 

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

Where “XX” varies across input files. For any given file, “XX” is the two digit 

abbreviation of the state associated with the scenario being modeled (e.g., for Alabama 

modeling, XX=AL). 

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

line: 

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

with the eight command lines: 

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

TANK PERM : c:\non-road\data\emsfac\evtank.emf 

NON-RM HOSE PERM : c:\non-road\data\emsfac\evhose.emf 

RM FILL NECK PERM : c:\non-road\data\emsfac\evneck.emf 

RM SUPPLY/RETURN : c:\non-road\data\emsfac\evsupret.emf 

RM VENT PERM : c:\non-road\data\emsfac\evvent.emf 

HOT SOAKS : c:\non-road\data\emsfac\evhotsk.emf 

RUNINGLOSS : c:\non-road\data\emsfac\evrunls.emfEVP

 Revise the Draft NONROAD2004 (Base F) input files to include the following command 

line after the “PM exhaust” command in the DETERIORATE FILES packet: 

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

Once revised in this format, the VISTAS non-road input files developed for use with Draft 

NONROAD2004 (Base F) were executable under the Final NONROAD2005 model (Base G). 

The only additional revisions implemented to develop a Final NONROAD2005-based inventory 

(Base G) involved elimination of non-default equipment allocation files for North Carolina and 

West Virginia. Due to concerns about improper equipment allocation across counties under the 

Draft NONROAD2004 model (used for Base F), as well as for earlier versions of the 

NONROAD model, North Carolina had produced alternative allocation data files indicating the 
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number of employees in air transportation by county, the number of wholesale establishments by 

county, and the number of employees in landscaping services by county. For the same reason, 

West Virginia had produced alternative equipment allocation files indicating the number of 

employees in air transportation by county, the tonnage of underground coal production by 

county, the number of golf courses and country clubs by county, the number of wholesale 

establishments by county, the number of employees in logging operations by county, the number 

of employees in landscaping services by county, the number of employees in manufacturing 

operations by county, the number of employees in oil and gas drilling and extraction operations 

by county, and the number of recreational vehicle parks and campgrounds by county. These 

alternative equipment allocation files were used for all VISTAS inventory modeling conducted 

prior to the release of Final NONROAD2005 (i.e., through Base F). However, both North 

Carolina and West Virginia determined that the default allocation file revisions associated with 

the release of Final NONROAD2005 were appropriate to address the concerns that led to the 

development of the alternative allocation files. As a result, all alternative allocation file 

commands were removed from VISTAS NONROAD2005 (Base G) input files for North 

Carolina and West Virginia, so that the entire region under the Base G inventory is now modeled 

using the default allocation files provided with NONROAD2005. 

In addition to the alternative equipment allocation files, North Carolina had previously 

developed an alternative seasonal adjustment file that was used for the Base F inventory in place 

of the default file provided with Draft NONROAD2004 (and earlier model versions). The 

alternative data file implemented a single change, namely reclassifying North Carolina as a 

southeastern state rather than a mid-Atlantic state (as identified in the default data file). Since 

Final NONROAD2005 continues to identify North Carolina as a mid-Atlantic state, North 

Carolina requested that the southeastern reclassification be continued for all NONROAD2005 

modeling (Base G). To ensure that any other revisions associated with the seasonal adjustment 

file released with NONROAD2005 were not overlooked, the previously developed alternative 

seasonal adjustment file for North Carolina was scrapped and a new alternative file was created 

from the default seasonal adjustment file provided with Final NONROAD2005 for Base G 

inventory development. The alternative file, which was used for all North Carolina modeling, 

reclassifies North Carolina from a mid-Atlantic to a southeastern state. This represents the only 

non-default data file used for VISTAS NONROAD2005-based (Base G) modeling. 

The remainder of this section documents all changes to the originally established VISTAS input 

file values as documented in the February 9, 2004 report “Development of the VISTAS Draft 

2002 Mobile Source Emission Inventory (February 2004 Version)” as prepared by E.H. Pechan 

& Associates, Inc. Unless specifically stated below, all values from that report continue to be 

used without change in the latest VISTAS modeling. 
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Base F Revisions:

For the initial 2002 base year inventory (developed by Pechan), all NONROAD modeling runs 

for VISTAS were performed utilizing a gasoline sulfur content of 339 ppmW and a diesel sulfur 

content of 2,500 ppmW. Although the EPA-recommended non-road diesel fuel sulfur content for 

2002 is 2,283 ppmW, the 2,500 ppmW sulfur content used for the initial 2002 base year VISTAS 

inventory was designed to remove the effect of lower non-road diesel fuel sulfur limits 

applicable only in California. (The EPA recommended inputs can be found in “Diesel Fuel 

Sulfur Inputs for the Draft NONROAD2004 Model used in the 2004 Non-road Diesel Engine 

Final Rule,” EPA, April 27, 2004.) This correction is appropriate and was retained for the Base F 

2002 inventory. Thus, the Base F inventory continued to assume a diesel fuel sulfur content of 

2,500 ppmW across the VISTAS region. 

However, 339 ppmW is not the EPA recommended 2002 gasoline sulfur content for either 

eastern conventional gasoline areas or Federal Reformulated Gasoline (RFG) areas. The 

recommended sulfur content for eastern conventional gasoline is 279 ppmW year-round, while 

the recommended sulfur content for RFG areas is 129 ppmW during the summer season and 279 

ppmW during the winter season. (Conventional gasoline and RFG sulfur contents for 2002 can 

be found in “User’s Guide to MOBILE6.1 and MOBILE6.2, Mobile Source Emission Factor 

Model,” EPA420-R-03-010, U.S. EPA, August 2003 [pages 149-155] (available at link at 

http://www.epa.gov/otaq/m6.htm) and in the source code for MOBILE6.2 at Block Data BD05.) 

Given the differences in the EPA-recommended values and the value used to generate the initial 

2002 base year inventory, the input files for Base F for all VISTAS areas were updated to reflect 

revised gasoline sulfur content assumptions. 

Since the VISTAS NONROAD modeling is performed on a seasonal basis, and since gasoline 

sulfur content in RFG areas varies with the RFG season, seasonally-specific gasoline sulfur 

content values were estimated for use in RFG area modeling. In addition, 25 counties in Georgia 

are subject to a summertime gasoline sulfur limit of 150 ppmW, so that seasonal sulfur content 

estimates were also estimated for these counties. The initial 2002 base year NONROAD 

inventory (prepared by Pechan) for these Georgia counties was based on a year-round 339 

ppmW gasoline sulfur content, but that oversight was corrected in the Base F 2002 base year 

inventory. Based on the seasonal definitions employed in the NONROAD model, monthly sulfur 

contents were averaged to estimate seasonal gasoline sulfur contents as follows: 
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Month/Season RFG Areas 

Conventional 

Gasoline Areas 

Georgia Gasoline 

Control Areas 

March 279 ppmW 279 ppmW 279 ppmW 

April 279 ppmW 279 ppmW 279 ppmW 

May 129 ppmW 279 ppmW 150 ppmW 

Spring 229 ppmW 279 ppmW 236 ppmW 

June 129 ppmW 279 ppmW 150 ppmW 

July 129 ppmW 279 ppmW 150 ppmW 

August 129 ppmW 279 ppmW 150 ppmW 

Summer 129 ppmW 279 ppmW 150 ppmW 

September 129 ppmW 279 ppmW 150 ppmW 

October 279 ppmW 279 ppmW 279 ppmW 

November 279 ppmW 279 ppmW 279 ppmW 

Fall 229 ppmW 279 ppmW 236 ppmW 

December 279 ppmW 279 ppmW 279 ppmW 

January 279 ppmW 279 ppmW 279 ppmW 

February 279 ppmW 279 ppmW 279 ppmW 

Winter 279 ppmW 279 ppmW 279 ppmW 

Note that the seasonal data are based on simple arithmetic averages and do not consider any 

monthly variation in activity (and fuel sales), and that the transition between summer and winter 

seasons is also not considered. Additionally, the summer fuel control season is treated as though 

it applies from May through September, while the summer RFG season actually ends on 

September 15 and the Georgia fuel control season does not officially begin until June 1. This 

treatment is consistent with the treatment of both fuel control programs in the VISTAS on-road 

vehicle modeling. Each of these influences will result in some error in the estimated sulfur 

content estimates, but it is expected that this error is small relative to the overall correction from 

a year-round sulfur content estimate of 339 ppmW. 

All NONROAD modeling revisions made as part of the Base F inventory preparation process are 

presented in Table 1.3-2. Due to more involved updates in several areas, the number of 

NONROAD input files as well as sequence numbers used to represent these files was also 

updated in a few instances (as compared to the files used to create the initial 2002 VISTAS nonroad inventory, as documented in the February 9, 2004 report “Development of the VISTAS Draft 

2002 Mobile Source Emission Inventory (February 2004 Version)” as prepared by E.H. Pechan 

& Associates, Inc. These structural revisions are presented in Table 1.3-3, and are provided 
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solely for the benefit of NONROAD modelers as the indicated revisions have no impact on 

generated emission estimates. 

Table 1.3-2 Summary of Base F NONROAD Modeling Revisions

State Revisions Implemented 

AL (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

FL (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

GA 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all seasons for conventional 

gasoline counties. 

(2) Gasoline sulfur content changed from 339 ppmW to 150 ppmW in the summer for all gasoline 

control counties. 

(3) Gasoline sulfur content changed from 339 ppmW to 236 ppmW in the spring and fall for all gasoline 

control counties. 

(4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control 

counties. 

Gasoline control counties: Barrow, Bartow, Butts, Carroll, Cherokee (a), Clayton (a), Cobb (a), 

Coweta (a), Dawson, De Kalb (a), Douglas (a), Fayette (a), Forsyth (a), Fulton (a), Gwinnett 

(a), Hall, Haralson, Henry (a), Jackson, Newton, Paulding (a), Pickens, Rockdale (a), Spalding, 

and Walton 

KY 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all seasons for conventional 

gasoline counties. 

(2) Gasoline sulfur content changed from 339 ppmW to 129 ppmW in the summer for all gasoline 

control counties. 

(3) Gasoline sulfur content changed from 339 ppmW to 229 ppmW in the spring and fall for all gasoline 

control counties. 

(4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control 

counties. 

Gasoline control counties: Boone, Bullitt (b), Campbell, Jefferson, Kenton, and Oldham (b) 

MS (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

NC 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

(2) Utilize revised (i.e., local) allocation files for three equipment categories. 

(3) Utilize revised (i.e., local) seasonal activity data. 

SC (1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

TN 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

(2) Gasoline Reid Vapor Pressure (RVP) values changed in accordance with local recommendations. 

(3) Temperature data changed in accordance with local recommendations. 

(4) Counties regrouped in accordance with local recommendations. 
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Table 1.3-2. Summary of Base F NONROAD Modeling Revisions (continued) 

State Revisions Implemented 

VA 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all seasons for conventional 

gasoline counties. 

(2) Gasoline sulfur content changed from 339 ppmW to 129 ppmW in the summer for all gasoline 

control counties. 

(3) Gasoline sulfur content changed from 339 ppmW to 229 ppmW in the spring and fall for all gasoline 

control counties. 

(4) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in the winter for all gasoline control 

counties. 

(5) Gasoline RVP values changed in accordance with local recommendations. 

(6) Counties regrouped in accordance with local recommendations. 

(7) The control effectiveness for counties subject to Stage II controls revised to 77 percent in accordance 

with local recommendations. 

Gasoline control counties: Arlington Co., Fairfax Co., Loudoun Co., Prince William Co., 

Stafford Co., Alexandria City, Fairfax City, Falls Church City, Manassas City, Manassas Park 

City, Chesterfield Co., Hanover Co., Henrico Co., Colonial Heights City, Hopewell City, 

Richmond City, James City, York Co., Chesapeake City, Hampton City, Newport News City, 

Norfolk City, Poquoson City, Portsmouth City, Suffolk City, Virginia Beach City, and 

Williamsburg City (c) 

WV 

(1) Gasoline sulfur content changed from 339 ppmW to 279 ppmW in all counties and all seasons (all 

are conventional gasoline areas). 

(2) Continue to utilize local allocation files for nine equipment categories. 

Notes: 

(a) County is subject to local control currently, but is scheduled to join the RFG program in January 2005. 

(b) Control area is a portion of the county, but modeling is performed as though the control applies countywide. 

(c) The EPA also lists Charles City County as an RFG area, but local planners indicate that Charles City County is a conventional gasoline 

area and it is modeled as such. 
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Table 1.3-3 Base F NONROAD Input File Sequence and Structural Revisions

State 

Initial 2002 Base Year 

Inventory 

Input File 

Sequence Numbers 

Revised 2002 

Inventory 

Input File 

Sequence Numbers 

Reason(s) for Change 

Number of 

Revised 2002 Inventory 

NONROAD Input Files 

AL 01-08 01-08 No Structural Changes 32 (at 8 per season) 

FL 09-10 09-10 No Structural Changes 8 (at 2 per season) 

GA 11-13 11-13 No Structural Changes 12 (at 3 per season) 

KY 14-22 14-22 No Structural Changes 36 (at 9 per season) 

MS 48 48 No Structural Changes 4 (at 1 per season) 

NC 23-25 23-25 No Structural Changes 12 (at 3 per season) 

SC 26-32 26-32 No Structural Changes 28 (at 7 per season) 

TN 33-34 33-34, 49-52 Counties Regrouped 24 (at 6 per season) 

VA 35-43 35-38, 40-43 Counties Regrouped 32 (at 8 per season) 

WV 44-47 44-47 No Structural Changes 16 (at 4 per season) 

All 01-48 01-38, 40-52 204 (at 51 per season) 

Note: (1) All files include internal revisions to reflect the data changes summarized in Table 1.3-3 above. This table is intended to present 

structural revisions that are of interest in assembling the NONROAD model input files into a complete VISTAS region inventory. 

The indicated revisions do not (in and of themselves) result in emission estimate changes. 

 (2) The NONROAD model imposes an eight digit input file name limit, so all input files for the revised 2002 base year inventory 

follow a modified naming convention to allow each to be distinguished from the input files for the initial 2002 base year inventory. 

For the initial 2002 base year inventory, the naming convention was: 

ss02aaqq, where: ss = the two character State abbreviation, 

 aa = a two character season indicator as follows: AU = autumn, 

WI = winter, SP = spring, and SU = summer, and 

 qq = the two digit sequence number indicated above. 

For the revised 2002 inventory, the naming convention was modified to: 

ss02aFqq, where: ss = the two character State abbreviation, 

 a = a one character season indicator as follows: A = autumn, 

W = winter, S = spring, and X = summer, and 

 qq = the two digit sequence number indicated above. 
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Base G Revisions:

As described above, the primary modeling revision implemented for the Base G 2002 inventory 

was the use of the Final NONROAD2005 model (in place of the Base F use of Draft 

NONROAD2004). However, there were other minor revisions implemented for 13 Georgia 

counties and somewhat more significant revisions implemented for Tennessee. In Georgia, Stage 

II refueling control was assumed for 13 counties that previously were modeled as having no 

refueling control under Base F. In addition, to accommodate this Stage II change as well as 

forecast year changes in gasoline vapor pressure, corresponding changes in the structure and 

sequence of Georgia NONROAD input files were made. With the exception of the minor Stage 

II impacts, these structural and sequence changes have no impact on 2002 emission estimates, 

but allow for consistency between 2002 and forecast year input file structure and sequence. In 

Tennessee, more significant changes were implemented to gasoline vapor pressure assumptions, 

as well as similar minor changes in Stage II refueling control assumptions. 

In accordance with instructions from Georgia regulators, Stage II refueling control was assumed 

in the following 13 Georgia counties at a control efficiency value of 81 percent for the 

Base G inventory: 

Cherokee, Clayton, Cobb, Coweta, DeKalb, Douglas, Fayette, Forsyth, Fulton, 

Gwinnett, Henry, Paulding, and Rockdale. 

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

Tennessee regulators provided revised monthly values for gasoline vapor pressure. Based on the 

seasonal definitions employed in the NONROAD model, monthly vapor pressures were averaged 

to estimate seasonal vapor pressures as follows: 
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Month/Season Nashville Area Memphis Area 

Remainder of 

Tennessee 

March 13.5 psi 13.5 psi 13.5 psi 

April 13.5 psi 13.5 psi 13.5 psi 

May 9.0 psi 9.0 psi 9.0 psi 

Spring 12.0 psi 12.0 psi 12.0 psi 

June 7.8 psi 7.8 psi 9.0 psi 

July 7.8 psi 7.8 psi 9.0 psi 

August 7.8 psi 7.8 psi 9.0 psi 

Summer 7.8 psi 7.8 psi 9.0 psi 

September 1-15 7.8 psi 7.8 psi 9.0 psi 

September 16-30 11.5 psi 11.5 psi 11.5 psi 

October 13.5 psi 13.5 psi 13.5 psi 

November 13.5 psi 13.5 psi 13.5 psi 

Fall 12.2 psi 12.2 psi 12.4 psi 

December 15.0 psi 15.0 psi 15.0 psi 

January 15.0 psi 15.0 psi 15.0 psi 

February 13.5 psi 13.5 psi 13.5 psi 

Winter 14.5 psi 14.5 psi 14.5 psi 

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

area consists of Shelby County. 

As with the Base F revisions, the seasonal data are based on simple arithmetic averages and do 

not consider any monthly variation in activity (and fuel sales), nor is the transition between 

summer and winter seasons considered. Additionally, a monthly average of the September 1-15 

and September 16-30 data is calculated prior to averaging the September-November data to 

estimate a fall average vapor pressure, so that the month of September is weighted identically to 

the months of October and November. 

Tennessee regulators also indicated that Stage II vapor recovery was not in effect in Shelby 

County, so the Base F NONROAD input files for the county (which assumed Stage II was in 

place) were revised accordingly. 

All Base G NONROAD modeling revisions are presented in Table 1.3-4. As indicated above, the 

differentiation of inputs across previously grouped counties also required revision to the overall 

number and sequence of VISTAS NONROAD input files (as compared to the files used to create 

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 
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documented above. These structural revisions are presented in Table 1.3-5, and are provided 

solely for the benefit of NONROAD modelers as the indicated revisions have no impact on 

generated emission estimates. 

Table 1.3-4 Summary of Base G NONROAD Modeling Revisions

State Revisions Implemented 

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

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

GA 

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

(2) Stage II refueling vapor recovery implemented in 13 counties at an efficiency of 81 percent. 

(3) Counties regrouped to accommodate base and forecast year data differentiations. 

Stage II control counties: Cherokee, Clayton, Cobb, Coweta, De Kalb, Douglas, Fayette, 

Forsyth, Fulton, Gwinnett, Henry, Paulding, and Rockdale 

KY (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

MS (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

NC 

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

(2) Revert to default equipment allocation files for all equipment categories. 

(3) Utilize revised (i.e., local) seasonal activity data. 

SC (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

TN 

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

(2) Gasoline RVP values changed in accordance with local recommendations. 

(3) Stage II vapor recovery eliminated from Shelby County modeling. 

VA (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

WV (1) Marine diesel sulfur content changed from 2500 ppmW to 2638 ppmW in all counties and seasons. 

(2) Revert to default equipment allocation files for all equipment categories. 
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Table 1.3-5 Spring 2006 NONROAD Input File Sequence and Structural Revisions

State 

2002 Inventory 

Input File 

Sequence Numbers 

(Fall 2004) 

2002 Inventory 

Input File 

Sequence Numbers 

(Spring 2006) 

Reason(s) for Change 

Number of 

Final 2002 Inventory 

NONROAD Input Files 

AL 01-08 01-08 No Structural Changes 32 (at 8 per season) 

FL 09-10 09-10 No Structural Changes 8 (at 2 per season) 

GA 11-13 11-13, 53-54 Counties Regrouped 20 (at 5 per season) 

KY 14-22 14-22 No Structural Changes 36 (at 9 per season) 

MS 48 48 No Structural Changes 4 (at 1 per season) 

NC 23-25 23-25 No Structural Changes 12 (at 3 per season) 

SC 26-32 26-32 No Structural Changes 28 (at 7 per season) 

TN 33-34, 49-52 33-34, 49-52 No Structural Changes 24 (at 6 per season) 

VA 35-38, 40-43 35-38, 40-43 No Structural Changes 32 (at 8 per season) 

WV 44-47 44-47 No Structural Changes 16 (at 4 per season) 

All 01-38, 40-52 01-38, 40-54 212 (at 53 per season) 

Note: (1) All files include internal revisions to reflect the data changes summarized in Table 1.3-5 above. This table is intended to present 

structural revisions that are of interest in assembling the NONROAD model input files into a complete VISTAS region inventory. 

The indicated revisions do not (in and of themselves) result in emission estimate changes. 

 (2) The NONROAD model imposes an eight digit input file name limit, so all input files for the revised 2002 base year inventory 

follow a modified naming convention to allow each to be distinguished from the input files for the initial 2002 and fall 

2004-revised 2002 base year inventory. For the initial 2002 base year inventory, the naming convention was: 

ss02aaqq, where: ss = the two character State abbreviation, 

 aa = a two character season indicator as follows: AU = autumn, 

WI = winter, SP = spring, and SU = summer, and 

 qq = the two digit sequence number indicated above. 

For the fall 2004-revised 2002 inventory, the naming convention was modified to: 

ss02aFqq, where: ss = the two character State abbreviation, 

 a = a one character season indicator as follows: A = autumn, 

W = winter, S = spring, and X = summer, and 

 qq = the two digit sequence number indicated above. 

For the spring 2006-revised 2002 inventory, the naming convention was modified to: 

ss02aCqq, where: ss = the two character State abbreviation, 

 a = a one character season indicator as follows: A = autumn, 

W = winter, S = spring, and X = summer, and 

 qq = the two digit sequence number indicated above. 
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1.3.2.2 Emissions from Commercial Marine Vessels, Locomotives, and Airplanes 

An initial 2002 base year emissions inventory for aircraft, locomotives, and commercial marine 

vessels (CMV) was prepared for VISTAS in early 2004. The methods and data used to develop 

the inventory are presented in a February 9, 2004 report “Development of the VISTAS Draft 2002 

Mobile Source Emission Inventory (February 2004 Version)” as prepared by E.H. Pechan & 

Associates, Inc. A summary of the initial 2002 base year emissions inventory is presented in 

Table 1.3-6. Except as otherwise stated below, all aspects of the preparation methodology 

continue to apply to the Base F and Base G emission inventories. 

Revisions to the initial 2002 emissions inventory (prepared by Pechan) were implemented to 

ensure that the latest State and local data were incorporated as well as to correct an 

overestimation of PM emissions from aircraft. Revisions were actually implemented in two 

stages. An initial set of revisions was implemented in the fall of 2004. Those revisions constitute 

the Base F inventory. These were followed by a second set of revisions in 2006, which constitute 

the Base G inventory. To accurately document the combined effects of both sets of revisions, 

each set is discussed separately below. Unless otherwise indicated, all revisions implemented for 

Base F were carried directly into the Base G revision process without change. Thus, the 

inventories that resulted from the Base F revisions served as the starting point for the Base G 

revisions. 

Base F Revisions:

Revisions to the initial 2002 base year emissions inventory were implemented to ensure that the 

latest State and local data were incorporated as well as to correct an overestimation of PM 

emissions from aircraft. Seven of the ten VISTAS States provided revised inventory data in the 

form of emissions reported to the EPA under the CERR. States providing CERR data were 

Alabama, Georgia, Mississippi, North Carolina, Tennessee (excluding Davidson, Hamilton, 

Knox, and Shelby Counties), Virginia, and West Virginia. 

In many cases, the CERR data were only marginally different than the initial 2002 base year 

inventory data, but there were several instances where significant updates were evident. The 

remaining three VISTAS States (Florida, Kentucky, and South Carolina), plus Davidson, 

Hamilton, Knox, and Shelby counties in Tennessee, indicated that the initial 2002 VISTAS 

inventory continued to reflect the most recent data available. Florida did provide updated aircraft 

emissions data for one county (Miami-Dade) and these data were incorporated into the Base F 

2002 inventory as described below. 

Since several States recommended retaining the initial 2002 base year inventory data for Base F, 

the initial step toward revising the 2002 inventory consisted of modifying the estimated aircraft 

PM emissions of the initial inventory. The overestimation of aircraft PM became evident shortly 
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after the release of the initial 2002 base year inventory, when it was determined that VISTAS 

region airports would constitute the top seven, and 11 of the top 15, PM sources in the nation. 

Moreover, PM emissions for one airport (Miami International) were a full order of magnitude 

larger than all other modeled elemental carbon PM emission sources. In addition, unexpected 

relationships across airports were also observed, with emissions for Atlanta’s Hartsfield 

International being substantially less than those of Miami International, even though Atlanta 

handles over twice as many aircraft operations annually. Given the pervasiveness of this 

problem, and since the CERR data submitted by States was based on the initial 2002 VISTAS 

inventory data, aircraft PM emissions for the entire VISTAS region were recalculated. 
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Table 1.3-6 Initial 2002 Base Year Aircraft, Locomotive, and Non-Recreational Marine 

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

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 3,787 175 688 475 17 196 

FL 28,518 11,955 46,352 31,983 1,050 3,703 

GA 3,175 992 3,919 2,704 94 353 

KY 2,666 657 2,597 1,792 63 263 

MS 1,593 140 553 381 13 96 

NC 6,088 1,548 6,115 4,219 148 613 

SC 6,505 515 452 312 88 863 

TN 6,854 2,665 7,986 5,510 225 920 

VA 17,676 5,607 14,476 9,988 234 3,229 

WV 1,178 78 310 214 8 66 

Aircraft 

(2275) 

Total 78,040 24,332 83,448 57,578 1,940 10,302 

AL 1,195 9,217 917 843 3,337 736 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,874 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,687 43,233 1,903 1,750 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 4,129 31,397 1,390 1,278 5,753 980 

VA 1,198 3,426 929 855 3,258 596 

WV 2,094 15,882 668 614 720 497 

Commercial 

Marine 

(2280) 

Total 29,503 218,760 10,858 9,989 40,146 7,779 

Military Marine VA 136 387 28 26 30 59 

(2283) Total 136 387 28 26 30 59 

AL 3,490 26,339 592 533 1,446 1,354 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 4,530 44,793 1,110 999 2,689 1,805 

VA 1,928 19,334 1,407 1,266 3,443 798 

WV 1,105 11,150 277 249 681 436 

Locomotives 

(2285) 

Total 21,980 211,588 6,118 5,505 14,947 8,738 

Grand Total 129,659 455,067 100,452 73,099 57,062 26,877 
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Aircraft do emit PM while operating. However, official EPA inventory procedures for aircraft 

generally do not include PM emission factors and, therefore, aircraft PM is generally erroneously 

reported as zero. In an effort to overcome this deficiency, the developers of the initial VISTAS 

2002 base year aircraft inventory (Pechan) estimated PM emission rates for aircraft using 

estimated NOx emissions and an unreported PM-to-NOx ratio (i.e., PM = NOx times a 

PM-to-NOx ratio). According to the initial 2002 base year inventory documentation, this 

approach was applied only to commercial aircraft NOx, but a review of that inventory indicates 

that the technique was also applied to military, general aviation, and air taxi aircraft in many, but 

not all, instances. Although there is nothing inherently incorrect with this approach, the accuracy 

and inconsistent application of the assumed PM-to-NOx ratio results in grossly overestimated 

aircraft PM. 

Through examination of the initial 2002 base year aircraft inventory (prepared by E.H. Pechan 

and Associates, Inc.), it is apparent that the commercial aircraft PM-to-NOx ratio used to 

generate PM emission estimates was approximately equal to 3.95 (i.e., PM = NOx times 3.95). 

While the majority of observed commercial aircraft PM-to-NOx ratios in that inventory are equal 

to 3.95, a few range as low as 3.00. If all aircraft estimates are included (i.e., commercial plus 

military, general aviation, and air taxi), observed PM-to-NOx ratios range from 0 to 123.0, and 

average 3.43 as illustrated in Table 1.3-7 

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

Aircraft Type Average 

PM-to-NOx

Range of 

PM-to-NOx

Average 

PM2.5 / PM10

Range of 

PM2.5 / PM10

Undefined (1) 0.046 0-0.062 0.690 0.690-0.690 

Military 0.073 0-92.3 0.688 0.333-1.000 

Commercial 3.953 3.00-3.953 0.690 0.667-0.696 

General Aviation 2.059 0-9.00 0.689 0.500-1.000 

Air Taxi 2.734 0-123.0 0.690 0.500-1.000 

Aggregate 3.427 0-123.0 0.690 0.333-1.000 

Note: (1) Two counties report aircraft emissions as SCC 2275000000 “all aircraft.” 

As indicated, the aggregate PM-to-NOx ratio is similar in magnitude to the ratio for commercial 

aircraft. This results from the dominant nature of commercial aircraft NOx emissions relative to 

NOx from other aircraft types. It is surmised that ratios that deviate from 3.95 are based on PM 

emission estimates generated by local planners, which were retained without change in the PM 

estimation process (although a considerable number of unexplained “zero PM” records also exist 
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in the initial 2002 base year inventory dataset). Regardless, based on previous statistical analyses 

performed in support of aircraft emissions inventory development outside the VISTAS region, a 

PM-to-NOx ratio of 3.95 is too large by over an order of magnitude. 

In analyses performed for the Tucson, Arizona planning area, PM-to-NOx ratios for aircraft over 

a standard aircraft landing and takeoff (LTO) cycle are shown in Table 1.3-8. Data for this table 

is taken from “Emissions Inventories for the Tucson Air Planning Area, Volume I., Study 

Description and Results,” prepared for the Pima Association of Governments, Tucson, AZ, 

November 2001. Pages 4-40 through 4-42 of that report, which document the statistical 

derivation of these ratios, are included in this report as Appendix E. 

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

Aircraft Type PM-to-NOx

Commercial Aircraft 0.26 

Military Aircraft 0.88 

Air Taxi Aircraft 0.50 

General Aviation Aircraft 1.90 

Note: 

The PM and NOx emission estimates presented in the Tucson study are for local aircraft operating mode times. For this work, emission 

estimates for Tucson were recalculated for a standard LTO cycle, so that the ratios presented are applicable to the standard LTO cycle and 

not a Tucson-specific cycle. Thus, the ratios presented herein vary somewhat from those associated with the emission estimates presented in 

the Tucson study report. 

In reviewing these data, it should be considered that they apply to a standard (i.e., EPA-defined) 

commercial aircraft LTO cycle.2 Aircraft PM-to-NOx ratios vary with operating mode, so that 

aircraft at airports with mode times that differ from the standard cycle will exhibit varying ratios. 

However, conducting an airport-specific analysis for all airports in the VISTAS region was 

beyond the scope of this work. While local PM-to-NOx ratios could vary somewhat from the 

indicated standard cycle ratios, any error due to this variation will be significantly less than the 

order of magnitude error associated with the 3.95 commercial aircraft ratio used for the initial 

2002 base year inventory. 

It should be recognized that while the Tucson area is far removed from the VISTAS region, the 

data analyzed to generate the PM-to-NOx ratios is standard aircraft emission factor data routinely 

employed for inventory purposes throughout the United States (as encoded in models such as the 

 

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

commercial aircraft LTO cycle consists of 4 minutes of approach time, 26 minutes of taxi (7 minutes in plus 19 

minutes out), 0.7 minutes of takeoff, and 2.2 minutes of climbout time (approach and climbout times being based 

on a 3000 foot mixing height).
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Federal Aviation Administration’s Emissions Data Management Systems [EDMS]). With the 

exception of aircraft operating conditions, there are no inherent geographic implications 

associated with the use of data from the Tucson study. As indicated above, issues associated with 

local operating conditions have been eliminated by recalculating the Tucson study ratios for a 

standard LTO cycle. 

To implement the revised PM-to-NOx ratios in the Base F inventory, all aircraft PM records were 

removed from the initial 2002 base year inventory (prepared by Pechan). This includes records 

for which local planners may have estimated PM emissions. This approach was taken for two 

reasons. First, there is no way to distinguish which records may have been generated by local 

planners. Second, the data available to local planners may be no better than that used to generate 

the presented PM-to-NOx ratio data, so the consistent application of these data to the entire 

VISTAS region was determined to be the most appropriate approach to generating consistent 

inventories throughout the region. In undertaking this removal, it became apparent that there was 

an imbalance in the aircraft NOx and PM records in the initial 2002 base year inventory. Whereas 

there were 1,531 NOx records in the NIF emission data sets for this source category, there were 

only 1,212 PM records. The imbalance was distributed between three States, South Carolina, 

Tennessee, and Virginia as follows: 

Table 1.3-9 Non-Corresponding Aircraft Emissions Records 

 Aircraft NOx records with no corresponding PM record:

Aircraft Type South Carolina Virginia Total 

Military Aircraft 8 100 108 

General Aviation Aircraft 14 94 108 

Air Taxi Aircraft 5 99 104 

Aggregate 27 293 320 

 Aircraft PM records with no corresponding NOx record:

Aircraft Type Tennessee Total 

Air Taxi Aircraft 1 1 

Aggregate 1 1 

The unmatched PM record was for Hamilton County (Chattanooga), Tennessee and when 

removed, was not replaced since there was no corresponding NOx record with which to estimate 

revised PM emissions. It is unclear how this orphaned record originated, but clearly there can be 

no air taxi PM emissions without other combustion-related emissions. Thus, the removal of the 

PM10 and PM2.5 records for Hamilton County permanently reduced the overall size of the 2002 

initial base year inventory database used as a starting point for Base F by two records. 
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Of the 320 unmatched NOx records, 269 were records for which the reported emission rate was 

zero. Therefore, even though associated PM records were missing, the overall inventory was not 

affected. However, the 51 missing records for which NOx emissions were non-zero, did impact 

PM estimates for the overall inventory. 

Replacement PM10 records were calculated for all aircraft NOx records using the PM-to-NOx

ratios presented above. Aircraft type-specific ratios were utilized in all cases, except for two 

counties where aircraft emissions were reported under the generic aircraft SCC 2275000000. For 

these counties (Palm Beach County, Florida and Davidson County, Tennessee), the commercial 

aircraft PM-to-NOx ratio was applied since both contain commercial airports (Palm Beach 

International and Nashville International). 

Replacement aircraft PM2.5 records were also developed. The initial 2002 base year inventory 

assumed that aircraft PM2.5 was 69 percent of aircraft PM10. The origin of this fraction is not 

clear, but it is very low for combustion related PM. The majority of internal combustion engine 

related PM is typically 1 micron or smaller (PM1.0), so that typical internal combustion engine 

PM2.5 fractions approach 100 percent. For example, the EPA NONROAD model assumes 

92 percent for gasoline engine particulate and 97 percent for diesel engine particulate. Based on 

recent correspondence from the EPA, it appears that the agency is preparing to recommend a 

PM2.5 fraction of 98 percent for aircraft. (August 12, 2004 e-mail correspondence from U.S. EPA 

to Gregory Stella of Alpine Geophysics.) This is substantially more consistent with expectations 

based on emissions test data for other internal combustion engine sources and was used as the 

basis for the recalculated aircraft PM2.5 emission estimates in the Base F inventory. 

Although a substantial portion of the initial 2002 base year inventory was ultimately replaced 

with data prepared by State and local planners under CERR requirements in developing the Base 

F inventory, it was necessary to first revise the initial 2002 base year aircraft inventory as 

described so that records extracted from the inventory for areas not supplying CERR data for the 

Base F update would be accurate. Therefore, in no case is the aggregated State data reported for 

the Base F inventory identical to that of the initial 2002 base year inventory. Even areas relying 

on the initial 2002 base year inventory will reflect updates in Base F due to changes in emissions 

of PM10 and PM2.5 from aircraft. 

Table 1.3-10 presents the updated initial 2002 base year inventory estimates. These estimates do 

not reflect any changes related to modifications made to incorporate the CERR data, but instead 

indicate the impacts associated solely with the recalculation of aircraft PM emissions alone to 

apply the more appropriate PM to NOx ratios. Table 1.3-11 presents a summary of the net 

impacts of these changes, where an over 90 percent reduction in aircraft PM is observed for all 

VISTAS areas except South Carolina and Virginia. The reasons for the lesser changes in these 

two States is that the overall aircraft NOx inventories for both include a large share of military 
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aircraft NOx to which no (or very low) particulate estimates were assigned in the initial 2002 

base year inventory. Since these operations are assigned non-zero PM emissions under the 

revised approach, the increase in military aircraft PM offsets a portion of the reduction in 

commercial aircraft PM. In Virginia, zero (or near zero) PM military operations were responsible 

for about 35 percent of total aircraft NOx, while the corresponding fraction in South Carolina was 

almost 70 percent. As indicated, aggregate aircraft, locomotive, and commercial marine vessel 

PM is 70-75 percent lower in the updated 2002 base year inventory. 

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

Emissions with Modified Aircraft PM Emission Rates (annual tons)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 3,787 175 64 62 17 196 

FL 28,518 11,955 3,193 3,129 1,050 3,703 

GA 3,175 992 269 264 94 353 

KY 2,666 657 179 175 63 263 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 6,854 2,665 707 692 225 920 

VA 17,676 5,607 2,722 2,667 234 3,229 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 78,040 24,332 8,030 7,870 1,940 10,302 

AL 1,195 9,217 917 843 3,337 736 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,874 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,687 43,233 1,903 1,750 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 4,129 31,397 1,390 1,278 5,753 980 

VA 1,198 3,426 929 855 3,258 596 

WV 2,094 15,882 668 614 720 497 

Commercial 

Marine 

(2280) 

Total 29,503 218,760 10,858 9,989 40,146 7,779 

Military Marine VA 136 387 28 26 30 59 

(2283) Total 136 387 28 26 30 59 

AL 3,490 26,339 592 533 1,446 1,354 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 4,530 44,793 1,110 999 2,689 1,805 

VA 1,928 19,334 1,407 1,266 3,443 798 

WV 1,105 11,150 277 249 681 436 

Locomotives 

(2285) 

Total 21,980 211,588 6,118 5,505 14,947 8,738 

Grand Total 129,659 455,067 25,034 23,390 57,062 26,877 
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Table 1.3-11 Change in Initial 2002 Base Year Emissions due to Aircraft PM Emission Rate 

Modifications.

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 0% 0% -91% -87% 0% 0% 

FL 0% 0% -93% -90% 0% 0% 

GA 0% 0% -93% -90% 0% 0% 

KY 0% 0% -93% -90% 0% 0% 

MS 0% 0% -92% -89% 0% 0% 

NC 0% 0% -93% -90% 0% 0% 

SC 0% 0% -9% +29% 0% 0% 

TN 0% 0% -91% -87% 0% 0% 

VA 0% 0% -81% -73% 0% 0% 

WV 0% 0% -92% -89% 0% 0% 

Aircraft 

(2275) 

Total 0% 0% -90% -86% 0% 0% 

AL 0% 0% 0% 0% 0% 0% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA 0% 0% 0% 0% 0% 0% 

WV 0% 0% 0% 0% 0% 0% 

Commercial 

Marine 

(2280) 

Total 0% 0% 0% 0% 0% 0% 

Military Marine VA 0% 0% 0% 0% 0% 0% 

(2283) Total 0% 0% 0% 0% 0% 0% 

AL 0% 0% 0% 0% 0% 0% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA 0% 0% 0% 0% 0% 0% 

WV 0% 0% 0% 0% 0% 0% 

Locomotives 

(2285) 

Total 0% 0% 0% 0% 0% 0% 

Grand Total 0% 0% -75% -68% 0% 0% 

As indicated above, for the Base F 2002 base year inventory, data for all or portions of seven 

VISTAS States were replaced with corresponding data from recent (as of the fall of 2004) CERR 

submissions for 2002. Before replacing these data, however, an analysis of the CERR data was 

performed to ensure consistency with VISTAS inventory methods. It should perhaps also be 

noted that three of the CERR datasets provided for the Base F 2002 base year inventory 

(specifically those for Tennessee, Virginia, and West Virginia) included both annual and daily 

emissions data. Only the annual data were used. Daily values were removed. 
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Several important observations resulted from this analysis. First, it was clear that all of the 

CERR data continued to rely on the inaccurate aircraft PM estimation approach employed for the 

initial 2002 base year inventory. Therefore, an identical aircraft PM replacement procedure as 

described above for updating the initial 2002 base year inventory was undertaken for CERR 

supplied data. As a result, the CERR data for all VISTAS States has been modified for inclusion 

in the Base F 2002 VISTAS base year inventory due to PM replacement procedures. 

As was the case with the initial VISTAS 2002 base year inventory, there were a substantial 

number of aircraft NOx records without corresponding PM records, so that the number of 

recalculated PM records added to the CERR dataset is greater than the number of PM records 

removed. The aggregated CERR inventory data, reflecting data for all or parts of seven States, 

consisted of 13,656 records, of which 1,211 were aircraft NOx records. However, the number of 

corresponding aircraft PM records was 662 (662 PM10 records and 662 PM2.5 records). This 

imbalance was distributed as follows: 

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

Aircraft Type Georgia Tennessee Virginia Total 

Military Aircraft 136 136 

Commercial Aircraft 4 136 140 

General Aviation Aircraft 1 136 137 

Air Taxi Aircraft 136 136 

Aggregate 1 4 544 549 

From this tabulation, it is clear that virtually the entire imbalance is associated with the Virginia 

CERR submission, with minor imbalances in Georgia and Tennessee. Of the 549 unmatched 

NOx records, 461 were records for which the reported emission rate was zero. Therefore, even 

though the associated PM records were missing, the overall inventory was not affected. 

However, the 88 missing records for which NOx emissions were non-zero do impact PM 

emission estimates for the overall inventory. 

Replacement aircraft PM records (both PM10 and PM2.5) were generated for the CERR dataset 

using procedures identical to those described above for the updated initial 2002 base 

year inventory. 

Further analysis revealed that the CERR data for Virginia included only VOC, CO, and NOx

emissions for all aircraft, locomotives, and non-recreational marine vessels. Since SO2, PM10, 

and PM2.5 records are included in the 2002 VISTAS inventory, an estimation method was 

developed for these emission species and applied to the Virginia CERR data. For PM, the 
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developed methodology was only employed for locomotive and marine vessel data since aircraft 

PM was estimated using the PM-to-NOx ratio methodology described above. 

Consideration was given to simply adding the Virginia SO2 and non-aircraft PM records from the 

initial 2002 VISTAS inventory dataset, but it is very unlikely that either the source distribution 

or associated emission rates are identical across the CERR and initial VISTAS inventories. This 

was confirmed through a comparative analysis of dataset CO records. Therefore, an estimation 

methodology was developed using Virginia source-specific SO2/CO, PM10/CO, and PM2.5/PM10

ratios from the initial 2002 base year VISTAS inventory. The calculated ratios were then applied 

to the source-specific CERR CO emission estimates to derive associated source-specific SO2, 

PM10, and PM2.5 emissions for the Base F inventory. 

Initially, the development of the emissions ratios from the initial 2002 base year inventory was 

performed at the State (i.e., Virginia), county, and SCC level of detail. However, it readily 

became clear that there were substantial inconsistencies in ratios for identical SCCs across 

counties. For example, in one county, the SO2/CO ratio might be 0.2, while in the next county it 

would be 2.0. Since the sources in question are virtually identical (e.g., diesel locomotives) and 

since the fueling infrastructure for these large non-road equipment sources is regional as opposed 

to local in nature, such variations in emission rates are not realistic. Therefore, a more aggregated 

approach was employed in which SCC-specific emission ratios were developed for the State as a 

whole. Through this approach county-to-county variation in emission ratios is eliminated, but the 

underlying variation in CO emissions does continue to influence the resulting aggregate emission 

estimates. The applied emission ratios are as follows: 

Table 1.3-13 Calculated Emission Ratios for VA.

Source SCC SO2/CO PM10/CO PM2.5/CO PM2.5/PM10

Military Aircraft 2275001000 0.0215 

Commercial Aircraft 2275020000 0.3292 

General Aviation Aircraft 2275050000 0.0002 

Air Taxi Aircraft 2275060000 0.0015 

Emissions estimated using 

PM-to-NOx ratios as 

described previously. 

Aircraft Refueling 2275900000 0.0000 0.0000 0.0000 

Diesel Commercial Marine 2280002000 0.3697 0.3434 0.3157 0.92 

Residual Commercial Marine 2280003000 0.3697 0.3434 0.3157 0.92 

Diesel Military Marine 2283002000 0.2422 0.2248 0.2068 0.92 

Line Haul Locomotives 2285002005 3.2757 1.2999 1.1696 0.90 

Yard Locomotives 2285002010 2.2908 1.2461 1.1205 0.90 
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It is important to recognize that the inconsistency of emissions ratios across Virginia counties for 

sources of virtually identical design, which utilize a regional rather than local fueling 

infrastructure, has potential implications for other VISTAS States. There is no immediately 

obvious reason to believe that such inconsistencies would be isolated to Virginia. 

One final revision to the CERR dataset was undertaken as part of the Base F effort, and that was 

the removal of two records for unpaved airstrip particulate (SCC 2275085000) in Alabama. 

Otherwise identical records for these emissions were reported both in terms of filterable and 

primary particulate. The filterable particulate records were removed as all other particulate 

emissions in the VISTAS inventories are in terms of primary particulate. It is also perhaps worth 

noting that a series of aircraft refueling records (SCC 2275900000) for Virginia were left in 

place, even through typically such emissions would be reported under SCC 2501080XXX in the 

area source inventory. If additional VISTAS aircraft refueling emissions are reported under SCC 

2501080XXX, then it may be desirable to recode these records. 

Finally, data for areas of the VISTAS region not represented in the CERR dataset were added to 

the CERR data by extracting the appropriate records from the initial 2002 base year inventory 

(with revisions for aircraft PM to NOx ratios). Specifically, records applicable to the States of 

Florida, Kentucky, South Carolina, and the Tennessee counties of Davidson, Hamilton, Knox, 

and Shelby were extracted from the revised initial 2002 inventory and added to the CERR 

dataset to establish the 2002 Base F inventory. 

Following this aggregation, one last dataset revision was implemented to complete the 

development of the 2002 Base F inventory. As indicated in the introduction of this section, the 

initial 2002 base year emission estimates for Miami International Airport were determined to be 

excessive. Although the reason for this inaccuracy was not apparent, revised estimates for 

aircraft emissions in Miami-Dade County were obtained from Florida planners and used to 

overwrite the erroneous estimates. (Aircraft emission estimates were provided in an August 10, 

2004 e-mail transmittal from Bruce Coward of Miami-Dade County to Martin Costello of the 

Florida Department of Environmental Protection.) 

Table 1.3-14 presents a summary of the resulting Base F VISTAS 2002 base year inventory 

estimates for aircraft, locomotives, and non-recreational marine vessels. Table 1.3-15 provides a 

comparison of the Base F 2002 base year inventory estimates to those of the initial 2002 base 

year inventory. As indicated, total emissions for VOC, CO, NOx, and SO2 are generally within 

10 percent, but final PM emissions are reduced by 70-80 percent due to the approximate 90 

percent reductions in aircraft PM estimates. In addition, the significant changes in Georgia 

aircraft emissions are due to the CERR correction of Atlanta Hartsfield International Airport 

emissions, which were significantly underestimated in the initial 2002 base year inventory. The 
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reduction in Florida aircraft emissions due to the correction of Miami International estimates is 

also apparent. 

Lastly, Table 1.3-16 provides a direct comparison of emission estimates from the initial and Base 

F 2002 base year inventories for all 16 VISTAS region airports with estimated annual aircraft 

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

The table entries are sorted in order of decreasing NOx and once again, the dramatic reduction in 

PM emissions is evident. However, in addition, the appropriate reversal of the relationship 

between Atlanta’s Hartsfield and Miami International Airport is also depicted. As a rough 

method of quality assurance, Table 1.3-15 also includes a gross estimate of expected airport NOx

emissions using detailed NOx estimates developed for Tucson International Airport in 

conjunction with the ratio of local to Tucson LTOs. (The Tucson NOx estimates are revised to 

reflect a standard LTO cycle rather than the Tucson-specific LTO cycle. This should provide for 

a more realistic comparison to VISTAS estimates.) This is not meant to serve as anything other 

than a crude indicator of the propriety of the developed VISTAS estimates, and it is clear that the 

range of estimated-to-expected NOx emissions has been substantially narrowed in the Base F 

2002 base year inventory. Whereas estimated-to-expected ratios varied from about 0.2 to over 

3.5 in the initial 2002 base year inventory, the range of variation is tightened on both ends, from 

about 0.5 to 1.75 for the Base F 2002 base year inventory. In effect, all estimates are now within 

a factor of two of the expected estimates, which is quite reasonable given likely variation in local 

and standard LTO cycles and variations in aircraft fleet mix across airports. 

It is perhaps important to note that some shifting in county emissions assignments is evident 

between the initial and Base F 2002 base year aircraft inventories. For example, for the initial 

2002 base year inventory, Atlanta Hartsfield estimates were assigned to Fulton County (FIP 

13121), while they are assigned to Clayton County (FIP 13063) for the Base F 2002 base year 

inventory. Similarly, Dulles International Airport emissions were assigned solely to Fairfax 

County, Virginia (FIP 51059) in the initial 2002 base year inventory, but are split between 

Fairfax and Loudoun County (FIP 51107) for Base F. Such shifts reflect local planner 

decision-making and are not an artifact of the revisions described above. 

 

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

International Airport to the group of airports with aircraft operations generating at least 200 tons of NOx. These 

revisions are discussed below, including the addition of an appropriately modified version of the aircraft 

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

Emissions (tons/year)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 3,787 175 226 87 17 196 

FL 25,431 8,891 2,424 2,375 800 3,658 

GA 6,622 5,372 1,475 1,446 451 443 

KY 2,666 657 179 175 63 263 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 7,251 2,766 734 719 235 943 

VA 9,763 2,756 1,137 1,115 786 2,529 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 70,884 22,899 7,072 6,797 2,607 9,670 

AL 1,196 9,218 917 844 3,337 737 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,875 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,688 43,233 1,903 1,751 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 3,624 27,555 1,217 1,120 4,974 860 

VA 972 2,775 334 307 359 483 

WV 1,528 11,586 487 448 525 362 

Commercial 

Marine 

(2280) 

Total 28,207 209,972 9,911 9,118 36,275 7,413 

Military Marine VA 110 313 25 23 27 48 

(2283) Total 110 313 25 23 27 48 

AL 3,490 26,339 592 533 1,446 1,354 

FL 1,006 9,969 247 222 605 404 

GA 2,725 27,453 682 614 1,667 1,086 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 2,626 25,627 633 570 1,439 1,041 

VA 1,186 11,882 1,529 1,375 3,641 492 

WV 1,311 13,224 329 296 808 517 

Locomotives 

(2285) 

Total 19,611 187,764 5,833 5,248 14,066 7,777 

Grand Total 118,812 420,948 22,841 21,186 52,976 24,908 
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Table 1.3-15 Change in 2002 Emissions, Base F Inventory Relative to Initial Inventory

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 0% 0% -67% -82% 0% 0% 

FL -11% -26% -95% -93% -24% -1% 

GA +109% +442% -62% -47% +379% +26% 

KY 0% 0% -93% -90% 0% 0% 

MS 0% 0% -92% -89% 0% 0% 

NC 0% 0% -93% -90% 0% 0% 

SC 0% 0% -9% +29% 0% 0% 

TN +6% +4% -91% -87% +4% +2% 

VA -45% -51% -92% -89% +236% -22% 

WV 0% 0% -92% -89% 0% 0% 

Aircraft 

(2275) 

Total -9% -6% -92% -88% +34% -6% 

AL +0% +0% +0% +0% +0% +0% 

FL 0% 0% 0% 0% 0% 0% 

GA +0% +0% +0% +0% +0% +0% 

KY 0% 0% 0% 0% 0% 0% 

MS +0% +0% +0% +0% +0% +0% 

NC +0% +0% +0% +0% +0% +0% 

SC 0% 0% 0% 0% 0% 0% 

TN -12% -12% -12% -12% -14% -12% 

VA -19% -19% -64% -64% -89% -19% 

WV -27% -27% -27% -27% -27% -27% 

Commercial 

Marine 

(2280) 

Total -4% -4% -9% -9% -10% -5% 

Military Marine VA -19% -19% -12% -12% -12% -19% 

(2283) Total -19% -19% -12% -12% -12% -19% 

AL 0% 0% 0% 0% 0% 0% 

FL 0% 0% 0% 0% 0% 0% 

GA +3% +3% +3% +3% +3% +3% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN -42% -43% -43% -43% -46% -42% 

VA -38% -39% +9% +9% +6% -38% 

WV +19% +19% +19% +19% +19% +19% 

Locomotives 

(2285) 

Total -11% -11% -5% -5% -6% -11% 

Grand Total -8% -7% -77% -71% -7% -7% 
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Table 1.3-16 Base F Comparison of Aircraft Emissions 

(Airports with Aircraft NOx > 200 tons per year)

Airport FIP CO NOx PM10 PM2.5 SO2 VOC Approx. 

LTOs 

Predicted

NOx

VISTAS

to 

Predicted

Initial 2002 Base Year Inventory 

Miami 12086 9,757 5,997 23,706 16,357 525 1,641 150,000 1,680 3.57 

Orlando 12095 3,456 2,170 8,578 5,919 204 642 150,000 1,680 1.29 

Memphis 47157 3,462 1,934 7,645 5,275 185 603 125,000 1,400 1.38 

Reagan 51013 3,892 1,806 7,138 4,925 164 302 100,000 1,120 1.61 

Hampton 51650 2,690 1,705 0 0 0 611 Military 

Dulles 51059 2,032 1,330 5,246 3,620 0 272 75,000 840 1.58 

Orlando-Sanford 12117 3,615 1,225 4,837 3,337 100 351 

Atlanta 13121 1,457 913 3,608 2,490 86 274 420,000 4,704 0.19 

Fort Lauderdale 12011 1,930 809 3,196 2,206 75 257 75,000 840 0.96 

Charlotte 37119 1,643 788 3,113 2,148 75 255 150,000 1,680 0.47 

Tampa 12057 1,399 785 3,101 2,140 74 240 75,000 840 0.93 

Nashville 47037 1,819 653 40 28 33 239 60,000 672 0.97 

Raleigh 37183 1,584 592 2,338 1,613 56 204 75,000 840 0.70 

Louisville 21111 1,073 468 1,851 1,277 45 155 60,000 672 0.70 

Jacksonville 12031 871 325 1,284 886 31 112 30,000 336 0.97 

Palm Beach 12099 1,156 226 0 0 1 132 30,000 336 0.67 

Aggregate 41,836 21,724 75,682 52,220 1,655 6,290 0.19-3.57 

Base F 2002 Base Year Inventory 

Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 

Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 

Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 

Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 

Orlando-Sanford 12117 3,615 1,225 338 332 100 351 

Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 

Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 

Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 

Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 

Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 

Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 

Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 

Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 

Hampton 51650 858 535 471 461 18 305 Military 

Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 

Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 

Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 

Aggregate 37,829 20,550 5,838 5,721 2,312 5,793 0.47-1.75 

Net Change -10% -5% -92% -89% +40% -8% 

Note: For the Base F inventory, Dulles International Airport emissions are split between two Virginia counties. 

 Predicted NOx is based on the ratio of airport LTOs to test airport (Tucson International Airport) LTOs and NOx. 

 This is not a rigorous comparison, but rather an approximate indicator of expected magnitude. 
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Base G Revisions: 

Further revisions to the 2002 base year emissions inventory were implemented in response to 

additional state data submittals in the spring of 2006. The inventories developed through the 

Base F revision process (as described above) served as the starting point for the 2006 revisions. 

Thus, unless otherwise indicated below, all documented Base F revisions continue to apply to the 

Base G-revised 2002 base year inventory. 

As part of the Base G review and update process, Virginia regulators provided 443 updated 

emission records for aircraft. These records reflected revisions to aircraft VOC, CO, and NOx, 

and in a few cases SO2, emissions records that were already in the Base F VISTAS 2002 

inventory (as opposed to the addition of previously unreported data). The specific revisions 

broke down as follows: 

Table 1.3-17 Base G VA Aircraft Records Updates 

Aircraft Type VOC CO NOx SO2 Total 

Military Aircraft 9 9 9 1 28 

Commercial Aircraft 12 12 12 17 53 

General Aviation Aircraft 65 66 66 0 197 

Air Taxi Aircraft 56 56 53 0 165 

Aggregate 142 143 140 18 443 

Emissions values for each of the 443 records in the Base F 2002 VISTAS inventory were 

updated for Base G to reflect the revised data. However, as described above for the Base F 

revisions, all aircraft SO2, PM10, and PM2.5 emissions in Virginia are estimated on the basis of 

CO (in the case of SO2) and NOx emissions (in the cases of PM10 and PM2.5). Therefore, since 

Virginia regulators did not provide updated SO2 emissions for all updated CO emissions records, 

or updated PM10 or PM2.5 emissions for all updated NOx emissions records, it was necessary to 

re-estimate aircraft SO2, PM10, and PM2.5 emissions in all cases where updated CO or NOx

emissions were provided for Base G (and explicit SO2 and/or PM10 and PM2.5 emissions 

were not). 

The procedure used to estimate the SO2, PM10, and PM2.5 emissions revisions was identical to 

that described above for the Base F inventory revisions, except that revised SO2-to-CO emissions 

ratios were calculated for commercial aircraft, where 12 pairs of revised CO and SO2 emissions 

estimates were available. Although a single pair of revised CO and SO2 emissions records was 

available for military aircraft, this was deemed an insufficient sample with which to replace the 

military aircraft SO2-to-CO emissions ratios previously calculated in Base F. However, it is 

worth noting that the SO2-to-CO emissions ratio for the revised military aircraft emissions pair 
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was within 16 percent of the previously calculated ratio, so any error associated with retention of 

the Base F ratio will be minor. Table 1.3-18 presents the emissions ratios. 

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

Source SCC 

SO2/CO 

(fall 2004) 

SO2/CO 

(spring 2006)

SO2/CO 

(used in 2006) PM10/NOx PM2.5/PM10

Military Aircraft 2275001000 0.0215 0.0180 0.0215 0.88 0.98 

Commercial Aircraft 2275020000 0.3292 0.0696 0.0696 0.26 0.98 

General Aviation Aircraft 2275050000 0.00016 n/a 0.00016 1.9 0.98 

Air Taxi Aircraft 2275060000 0.0015 n/a 0.0015 0.5 0.98 

Application of the SO2-to-CO emissions ratios to the 130 revised aircraft CO records, for which 

no corresponding SO2 emission revisions were provided, resulted in an additional 130 aircraft 

SO2 emission records updates for Virginia. Similarly, application of the PM10-to-NOx emissions 

ratios to the 140 revised aircraft NOx records for which no corresponding PM10 emission 

revisions were provided, resulted in an additional 140 aircraft PM10 emission records updates for 

Virginia. Application of the PM2.5-to-PM10 emissions ratios to the 140 revised aircraft PM10

records resulted in an additional 140 aircraft PM2.5 emission records updates for Virginia. Thus, 

in total, 853 (443+130+140+140) Virginia aircraft emissions records were updated for Base G. 

Also as part of the Base G review and update process, Alabama regulators provided 178 updated 

PM emission records for aircraft (89 records for PM10 and 89 records for PM2.5), 42 additional 

emissions records for locomotives (14 records for VOC, 14 records for CO, and 14 records for 

NOx), and 179 additional emission records for aircraft (30 records for VOC, 30 records for CO, 

30 records for NOx, 29 records for SO2, 30 records for PM10, and 30 records for PM2.5). After 

review, it was determined that the 178 updated PM emission records for aircraft actually 

reflected the original (overestimated) aircraft PM data that was replaced universally throughout 

the VISTAS region for Base F. Implementing these latest revisions would, in effect, “undo” the 

Base F aircraft PM revisions. Following discussions with Alabama regulators, it was determined 

that the 178 aircraft PM records would not be updated for the Base G revisions. 

The 42 additional emissions records for locomotives were determined to correspond exactly to 

existing SO2, PM10, and PM2.5 emissions records already in the Base F VISTAS 2002 inventory. 

It is not clear why these existing records contained no corresponding data for VOC, CO, and 

NOx, but those data are now reflected through the additional 42 records that have now been 

added to the Base G 2002 VISTAS inventory for Alabama. 

After examining the 179 additional aircraft emissions records in conjunction with Alabama 

regulators, it was determined that 17 of the records (commercial aircraft records in Dale, 
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Limestone, and Talladega counties) were erroneous and should be excluded from the update. The 

remaining 162 records reflected additional general aviation, air taxi, and military aircraft activity 

in 20 counties and were specifically comprised of 27 records each for VOC, CO, NOx, SO2, 

PM10, and PM2.5. There were no further issues with the VOC, CO, NOx, and SO2 records and 

these were added to the Base G 2002 VISTAS inventory without change. It was, however, 

apparent that the PM10 and PM2.5 records reflected an overestimation of aircraft PM similar to 

that which was previously corrected throughout the VISTAS region for Base F (as documented 

above). To overcome this overestimation, the additional aircraft PM10 and PM2.5 records 

provided by Alabama regulators were replaced with revised emission estimates developed on the 

basis of the PM10-to-NOx and PM2.5-to-PM10 ratios documented under the Base F revisions 

above. So although 27 aircraft PM10 records and 27 aircraft PM2.5 records were added to the 

2002 Alabama inventory, they reflected different emissions values than those provided directly 

by Alabama regulators. 

In total, 204 additional emissions records (42 for locomotives and 162 for aircraft) were added to 

the Base G 2002 Alabama inventory. 

Finally, as part of the Base G review and update process, Kentucky regulators provided 12 

updated aircraft emission records for Boone County, to correct previously underestimated 

aircraft emissions associated with the Cincinnati/Northern Kentucky International Airport. VOC, 

CO, and NOx emissions data were provided for military, commercial, general aviation, and air 

taxi aircraft. No associated updates for SO2, PM10, or PM2.5 emissions were provided. 

Corresponding PM10 emission estimates were developed by applying the PM10-to-NOx ratios 

presented in Table 1.3-17 above to the updated NOx emission estimates. PM2.5 emission 

estimates were developed by applying the PM2.5-to-PM10 ratios from that same table to the 

estimated PM10 emissions. SO2 emission estimates were developed by applying the SO2-to-PM10

ratios developed from the older data (i.e., the data being replaced) for Boone County aircraft to 

the updated PM10 emissions. Thus, a total of 24 inventory records for Kentucky were updated 

(VOC, CO, NOx, SO2, PM10, and PM2.5 for four aircraft types). 

Upon implementation of the universe of updates, 877 existing emission records were revised 

(853 in Virginia and 24 in Kentucky) and 204 additional emission records (all in Alabama) were 

added to the 2002 VISTAS inventory. The total number of aircraft, locomotive, and commercial 

marine inventory records thus changed from 22,838 records in Base F to 23,042 records in 

Base G. 

Table 1.3-19 presents a summary of the resulting Base G VISTAS 2002 base year inventory 

estimates for aircraft, locomotives, and non-recreational marine vessels. Table 1.3-20 provides a 

comparison of the Base G 2002 base year inventory estimates to those of the Base F 2002 base 
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year inventory. As indicated, total emissions for VOC, CO, NOx, and SO2 are generally within 

about 5 percent, with changes restricted to the states of Alabama, Kentucky, and Virginia. 

Lastly, Table 1.3-21 provides an updated comparison of emission estimates from the Base F and 

Base G 2002 base year inventories for all 17 VISTAS region airports with estimated annual 

aircraft NOx emissions of 200 tons or greater. As compared to Table 1.3-16, the table reflects the 

Base G addition of the Cincinnati/Northern Kentucky International Airport. Aircraft emission 

estimates for the other 16 airports are unchanged from their Base F values. 

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

Marine Emissions (tons/year)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 5,595 185 238 99 18 276 

FL 25,431 8,891 2,424 2,375 800 3,658 

GA 6,620 5,372 1,475 1,446 451 443 

KY 5,577 925 251 246 88 397 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 7,251 2,766 734 719 235 943 

VA 11,873 3,885 2,010 1,970 272 2,825 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 77,712 24,305 8,029 7,734 2,121 10,179 

AL 1,196 9,218 917 844 3,337 737 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,875 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,688 43,233 1,903 1,751 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 3,624 27,555 1,217 1,120 4,974 860 

VA 972 2,775 334 307 359 483 

WV 1,528 11,586 487 448 525 362 

Commercial 

Marine 

(2280) 

Total 28,207 209,972 9,911 9,118 36,275 7,413 

Military Marine VA 110 313 25 23 27 48 

(2283) Total 110 313 25 23 27 48 

AL 3,518 26,623 592 533 1,446 1,365 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 2,626 25,627 633 570 1,439 1,041 

VA 1,186 11,882 1,529 1,375 3,641 492 

WV 1,311 13,224 329 296 808 517 

Locomotives 

(2285) 

Total 19,568 187,328 5,815 5,232 14,022 7,761 

Grand Total 125,597 421,918 23,780 22,107 52,444 25,401 
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Table 1.3-20 Change in 2002 Emissions, Base G Inventory 

Relative to Base F Inventory

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL +48% +6% +5% +14% +7% +41% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY +109% +41% +40% +40% +41% +51% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA +22% +41% +77% +77% -65% +12% 

WV 0% 0% 0% 0% 0% 0% 

Aircraft 

(2275) 

Total +10% +6% +14% +14% -19% +5% 

AL 0% 0% 0% 0% 0% 0% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA 0% 0% 0% 0% 0% 0% 

WV 0% 0% 0% 0% 0% 0% 

Commercial 

Marine 

(2280) 

Total 0% 0% 0% 0% 0% 0% 

Military Marine VA 0% 0% 0% 0% 0% 0% 

(2283) Total 0% 0% 0% 0% 0% 0% 

AL +1% +1% 0% 0% 0% +1% 

FL 0% 0% 0% 0% 0% 0% 

GA 0% 0% 0% 0% 0% 0% 

KY 0% 0% 0% 0% 0% 0% 

MS 0% 0% 0% 0% 0% 0% 

NC 0% 0% 0% 0% 0% 0% 

SC 0% 0% 0% 0% 0% 0% 

TN 0% 0% 0% 0% 0% 0% 

VA 0% 0% 0% 0% 0% 0% 

WV 0% 0% 0% 0% 0% 0% 

Locomotives 

(2285) 

Total +0% +0% 0% 0% 0% +0% 

Grand Total +6% +0% +4% +4% -1% +2% 
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Table 1.3-21 Base G Comparison of Aircraft Emissions 

(Airports with Aircraft NOx > 200 tons per year)

Airport FIP CO NOx PM10 PM2.5 SO2 VOC Approx. 

LTOs 

Predicted

NOx

VISTAS

to 

Predicted

Base F 2002 Base Year Inventory 

Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 

Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 

Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 

Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 

Orlando-Sanford 12117 3,615 1,225 338 332 100 351 

Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 

Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 

Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 

Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 

Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 

Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 

Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 

Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 

Hampton 51650 858 535 471 461 18 305 Military 

Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 

Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 

Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 

Cincinnati 21015 467 144 38 37 14 54 50,000 560 0.26 

Aggregate 38,296 20,694 5,876 5,758 2,326 5,847 0.26-1.75 

Base G 2002 Base Year Inventory 

Atlanta 13063 4,121 5,288 1,435 1,406 443 337 420,000 4,704 1.12 

Miami 12086 6,670 2,933 805 789 274 1,596 150,000 1,680 1.75 

Orlando 12095 3,456 2,170 568 556 204 642 150,000 1,680 1.29 

Memphis 47157 3,462 1,934 506 495 185 603 125,000 1,400 1.38 

Orlando-Sanford 12117 3,615 1,225 338 332 100 351 

Fort Lauderdale 12011 1,930 809 217 212 75 257 75,000 840 0.96 

Charlotte 37119 1,643 788 206 202 75 255 150,000 1,680 0.47 

Tampa 12057 1,399 785 206 202 74 240 75,000 840 0.93 

Nashville 47037 1,819 653 170 166 33 239 60,000 672 0.97 

Reagan 51013 1,269 635 171 168 193 97 100,000 1,120 0.57 

Dulles 1 51107 1,807 595 164 161 252 153 37,500 420 1.42 

Raleigh 37183 1,584 592 156 153 56 204 75,000 840 0.70 

Dulles 2 51059 1,095 591 156 153 252 115 37,500 420 1.41 

Hampton 51650 858 535 471 461 18 305 Military 

Louisville 21111 1,073 468 123 121 45 155 60,000 672 0.70 

Cincinnati 21015 3,378 411 110 107 39 187 50,000 560 0.73 

Jacksonville 12031 871 325 87 85 31 112 30,000 336 0.97 

Palm Beach 12099 1,156 226 59 58 1 132 30,000 336 0.67 

Aggregate 41,207 20,961 5,947 5,828 2,352 5,981 0.47-1.75 

Net Change +8% +1% +1% +1% +1% +2% 

Note: For the revised inventory, Dulles International Airport emissions are split between two Virginia counties. 

 Predicted NOx is based on the ratio of airport LTOs to test airport (Tucson International Airport) LTOs and NOx. 

 This is not a rigorous comparison, but rather an approximate indicator of expected magnitude. 
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1.3.2.3 Emissions from NONROAD Model Sources in Illinois, Indiana, and Ohio 

As part of the Base G update process, VISTAS requested that emissions estimates for 2002 be 

produced for the states of Illinois, Indiana, and Ohio. These estimates were to be produced at the 

same spatial (i.e., county level by SCC) and temporal resolution as estimates for the 

VISTAS region. 

The requested estimates were produced by extracting a complete set of county-level input data 

applicable to each of the three states from the latest version of the EPA’s NMIM (National 

Mobile Inventory Model) model. This included appropriate consideration of all non-default 

NMIM input files generated by the Midwest Regional Planning Organization (MRPO), as 

described below. These input data were then assembled into appropriate input files for the Final 

NONROAD2005 model and emission estimates were produced using the same procedure 

employed for the VISTAS region as part of the Base G updates. 

A complete set of monthly input data was developed for each county in Illinois, Indiana, and 

Ohio by extracting data from the following NMIM database files (using the NMIM MySQL 

query browser): 

county, countrynrfile, countyyear, countyyearmonth, countyyearmonthhour, 

gasoline, diesel, and natural gas 

The database files: 

countrynrfile, countyyear, countyyearmonth, and gasoline 

were non-default database files provided to VISTAS by the MRPO, and are intended to reflect 

the latest planning data being used by MRPO modelers. 

From these files, monthly data for gasoline vapor pressure, gasoline oxygen content, gasoline 

sulfur content, diesel sulfur content for land-based equipment, diesel sulfur content for 

marine-based equipment, natural gas sulfur content, minimum daily temperature, maximum daily 

temperature, and average daily temperature were developed. In addition, the altitude and Stage II 

refueling control status of each county, as well as the identity of the associated equipment 

population, activity, growth, allocation, and seasonal distribution files, was determined. These 

data were then assembled into Final NONROAD2005 input files on a seasonal basis, with 

monthly data being arithmetically averaged to produce seasonal equivalents as follows: 

Winter = Average of December, January, and February 

Spring = Average of March, April, and May 

Summer = Average of June, July, and August, 

Fall = Average of September, October, and November 
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Unlike the VISTAS Base G approach, this approach results in the use of the following 

non-default data files during the Final NONROAD2005 modeling process: 

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

Data File Illinois Indiana Ohio 

Activity File 1700002.act 1800002.act 3900002.act 

Growth File 17000.grw 18000.grw 39000.grw 

Population File 17000.pop 18000.pop 39000.pop 

Season File 17000.sea 18000.sea 39000.sea 

Inboard Marine 

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

Outboard Marine 

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

Specific Fuel 

Consumption 

MRPO-specific file provided by MRPO modelers (arbitrarily 

named “mrpoBSFC.emf” for this work) 

One compromise was made relative to the level of resolution that is available through the basic 

approach described above, that being the treatment of ambient temperature data. Because NMIM 

offers a unique temperature profile for every U.S. county -- developed by aggregating 

temperature data from included and surrounding weather stations on the basis of their distances 

from the county population centroid -- it is not possible to explicitly group counties with 

otherwise identical input streams. Ungrouped however, there would be 1,128 distinct input 

streams to be processed (102 Illinois counties plus 92 Indiana counties plus 88 Ohio counties at 

four seasons each), or over five times the number of files processed for the entire 

VISTAS region. 

To surmount this problem and allow counties with similar temperature profiles to be grouped an 

approach was employed wherein counties were considered groupable if all temperature inputs4

are within ± 2 oF of the corresponding group average. This criterion is quite stringent in that it 

results in less tolerant grouping than that employed for VISTAS modeling, which uses 

temperature data from the nearest meteorological station as opposed to "unique" meteorological 

 

4

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

fall minimum, winter maximum, spring maximum, summer maximum, fall maximum, winter average, spring 

average, summer average, and fall average.
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data for each county. Under this approach, the actual deviation for grouped counties is much less 

that ± 2o F for the overwhelming majority of the 12 grouped temperature inputs. 

In addition to the required temperature consistency, all other input data for counties to be 

grouped had to be identical for all four seasons. Using this criterion, Illinois emissions were 

modeled using 12 county groups, Indiana emissions were modeled using 9 county groups, and 

Ohio emissions were modeled using 10 county groups. Thus, 31 iterations of NONROAD2002 

were required per season, as compared to the 53 iterations per season required for the 

VISTAS region. 

It should be noted that a potential quality assurance issue was noted in assembling the 

NONROAD2005 input data for a number of Indiana counties. Specifically, the gasoline vapor 

pressure for most Indiana counties reflects a value of 9.0 psi in all spring, summer, fall, and 

winter months. This is likely to indicate a problem with the accuracy of the NMIM databases for 

these counties, but these data were used as defined for this work. 

1.3.3 Quality Assurance steps 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, and to ensure that a full and complete 

inventory was developed for VISTAS. Quality assurance was an important component to the 

inventory development process and MACTEC performed the following QA steps on the area 

source component of the 2002 base year revised: 

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

Format and Content checking software. 

2. SCC level emission summaries were prepared and evaluated to ensure that emissions 

were consistent and that there were no missing sources. 

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

inventory and the initial base year inventory. 

4. Data product summaries were provided to both the VISTAS Emission Inventory 

Technical Advisor and to Mobile Source SIWG representatives for review and 

comment. Changes based on these comments were implemented in the files. 

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

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

example, a major change would result in a version going from 1.0 to 2.0. A minor 

change would cause a version number to go from 1.0 to 1.1. Minor changes resulting 

from largely editorial changes would result in a change from 1.00 to 1.01. 
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2.0 Projection Inventory Development 

2.1 Point Sources 

We used different approaches for different sectors of the point source inventory: 

 For the EGUs, VISTAS relied primarily on the Integrated Planning Model® (IPM®) to 

project future generation as well as to calculate the impact of future emission control 

programs. The IPM results were adjusted based on S/L agency knowledge of planned 

emission controls at specific EGUs. 

 For non-EGUs, we used recently updated growth and control data consistent with the data 

used in EPA’s CAIR analyses, and supplemented these data with available S/L agency 

knowledge of planned emission controls or other changes at specific non-EGUs 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 non-EGU federal control programs as 

of July 1, 2004; the final Clean Air Interstate Rule (CAIR); and State, local, and site-specific 

control programs as of October 1, 2007. Section 2.1.1 discusses the EGU projection inventory 

development, while Section 2.1.2 discusses the non-EGU projection inventory development. 

2.1.1 EGU Emission Projections 

The following subsections discuss the following specific aspects of the development of the EGU 

projections. First, we present a chronology of the EGU development process and discuss key 

decisions in selecting the final methods for performing the emissions projections. Next, we 

describe the development of the final set of IPM runs that are included in the VISTAS Base G 

inventory. Next, we describe the process of transforming the IPM parsed files into NIF format. 

Fourth, we discuss the process for ensuring that units accounted for in IPM were not doublecounted in the non-EGU inventory. Fifth, we describe the QA/QC checks that were made to 

ensure that the IPM results were properly incorporated into the VISTAS inventory. Sixth, we 

document the changes to the IPM results that S/L agencies specified they wanted included in the 

VISTAS inventory based on new information that were not accounted for in the IPM runs. 

Finally, we present summaries of the B&F projected EGU emissions by year, state, and 

pollutant. 

2.1.1.1 Chronology of the Development of EGU Projections 

At the beginning of the EGU inventory development process, VISTAS considered three options 

for developing the VISTAS 2009 and 2018 projection inventories for EGUs: 
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 Option 1 – Use the results of IPM modeling conducted in support of the proposed Clean 

Air Interstate Rule (CAIR) base and control case analyses as the starting point and refine 

the projections with readily available inputs from stakeholders; these IPM runs were 

conducted for 2010 and 2015, which VISTAS would use to represent projected emissions 

in 2009 and 2018 respectively. 

 Option 2 – Use the VISTAS 2002 typical year as the starting point, apply growth factors 

from the Energy Information Administration, and refine future emission rates with 

stakeholder input regarding utilization rates, capacity, retirements, and new unit 

information. 

 Option 3 – Use the results of a new round of IPM modeling sponsored by VISTAS and 

the Midwest Regional Planning Organization (MRPO). These runs incorporated VISTAS 

specific unit and regulation modified parameters, and generate results for 2009 and 2018 

explicitly. 

An additional consideration for each of the three options was the inclusion of emission 

projections developed by the Southern Company specifically for their units. Southern Company 

is a super-regional company which owns EGUs in Alabama, Florida, Georgia, and Mississippi 

and participates in VISTAS as an industry stakeholder. Southern Company used their energy 

budget forecast to project net generation and heat input for every existing and future Southern 

Company EGU for the years 2009 and 2018. Further documentation of how Southern Company 

generated the 2009/2018 inventory for their units can be found in Developing Southern Company 

Emissions and Flue Gas Characteristics for VISTAS Regional Haze Modeling (April 2005, 

presented at 14th International Emission Inventory Conference). 

Each of these three options and the Southern Company projections were discussed in a series of 

conference calls with the VISTAS EGU Special Interest Work Group (SIWG) during the fall of 

2004. During a conference call on December 6, 2004, the VISTAS EGU SIWG approved the use 

of the latest VISTAS/MRPO sponsored IPM runs (Option 3) to represent the 2009 and 2018 

EGU forecasts of emissions for the OTB and OTW cases. During the call, Alabama and Georgia 

specified that they did not wish to use Southern Company provided emissions forecasts of 2009 

and 2018 to represent the sources in their States. Mississippi decided to utilize the Southern 

Company projections to represent activity at Southern Company facilities in Mississippi. After 

the call, Florida decided against using Southern Company provided emissions forecasts of 2009 

and 2018 to represent the sources in their State. Thus, Southern Company data was used only for 

Southern Company units in Mississippi for both the Base F and Base G projections. 

The Option 3 IPM modeling resulted from a joint agreement by VISTAS and MRPO to work 

together to develop future year utility emissions based on IPM modeling. The decision to use 
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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, 

2004). Although IPM results were available from EPA’s modeling to support their rulemaking 

for the Clean Air Interstate Rule (CAIR), VISTAS stakeholders felt that certain model inputs 

needed to be improved. Thus, VISTAS and MRPO decided to hire contractors to conduct new 

IPM modeling and to post-process the IPM results. Southern Company projections in 2009 were 

roughly comparable with IPM. For 2018, Southern Company projections were generally less 

than IPM because of assumptions made by Southern Company on which units would be 

economical to control and incorrect data in the NEEDS database which feeds IPM. 

In August 2004, VISTAS contracted with ICF International, Inc., to run IPM to provide utility 

forecasts for 2009 and 2018 under two future scenarios – Base Case and CAIR Case. The Base 

Case represents the current operation of the power system under currently known laws and 

regulations (as known at the time the run was made), including those that come into force in the 

study horizon. The CAIR Case is the Base Case with the proposed CAIR rule superimposed. The 

run results were parsed at the unit level for the 2009 and 2018 run years. Also in August 2004, 

MRPO contracted with E.H. Pechan to post-process the IPM outputs generated by ICF to provide 

model-ready emission files. The IPM output files were delivered by ICF to VISTAS in 

November (Future Year Electricity Generating Sector Emission Inventory Development Using 

the Integrated Planning Model (IPM®) in Support of Fine Particulate Mass and Visibility 

Modeling in the VISTAS and Midwest RPO Regions, January 2005), and the post-processed data 

files were delivered by Pechan to the MRPO in December 2004 (LADCO IPM Model Parsed 

File Post-Processing Methodology and File Preparation, February 8, 2005). 

On March 10, 2005, EPA issued the final Clean Air Interstate Rule. VISTAS and MRPO, in 

conjunction with other RPOs, conducted another round of IPM modeling which reflected 

changes to control assumptions based on the final CAIR as well as additional changes to model 

inputs based on S/L agency and stakeholder comments. Several conference calls were conducted 

in the spring of 2005 to discuss and provide comments on IPM assumptions related to six main 

topics: power system operation, generating resources, emission control technologies, set-up 

parameters and rule, financial assumptions, and fuel assumptions. Based on these discussions, 

VISTAS sponsored a new set of IPM runs to reflect the final CAIR requirements as well as 

certain changes to IPM assumptions that were agreed to by the VISTAS states. This set of IPM 

runs is documented in Future Year Electricity Generating Sector Emission Inventory 

Development Using the Integrated Planning Model (IPM®) in Support of Fine Particulate Mass 

and Visibility Modeling in the VISTAS and Midwest RPO Regions, April 2005 (these runs are 

referred to as the VISTAS Phase I analysis). 
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Further refinements to the IPM inputs and assumptions were made by the RPOs, and ICF 

performed the following four runs using IPM during the summer of 2005 (these runs are referred 

to as the VISTAS/CENRAP Phase II analysis): 

 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. 
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 The extensive NEEDS comments provided by VISTAS, MRPO, CENRAP and MANEVU were incorporated into the VISTAS Phase I NEEDS. 

 MANE-VU’s comments in regards to the state regulations in the northeast were 

incorporated. 

 Renewable Portfolio Standards (RPS) in the northeast was modeled based on the 

Regional Greenhouse Gas Initiative analysis. A single RPS cap was modeled for MA, RI, 

NY, NJ, MD and CT. These states could buy credits from NY, PJM and New England 

model regions. 

 The investments required under the Illinois power, Mirant and First Energy NSR 

settlements were incorporated in the above runs. 

For the VISTAS/CENRAP Phase II set of IPM runs, ICF generated two different parsed files. 

One file includes all fuel burning units (fossil, biomass, landfill gas) as well as non-fuel burning 

units (hydro, wind, etc.). The second file contains just the fossil-fuel burning units (e.g., 

emissions from biomass and landfill gas are omitted). The RPOs decided to use the fossil-only 

file for modeling to be consistent with EPA, since EPA used the fossil only results for CAIR 

analyses. For the 10 VISTAS states, non-fossil fuels accounted for only 0.13 percent of the NOx 

emissions and 0.04 percent of the SO2 emissions in the 2009 IPM runs. 

S/L agencies reviewed the results of the VISTAS/CENRAP Phase II set of IPM runs, which were 

incorporated into the VISTAS Base F inventory. S/L agencies primarily reviewed and 

commented on the IPM results with respect to IPM decisions on NOx post-combustion controls 

and SO2 scrubbers. S/L agencies provided the latest information on when and where new SO2

and NOx controls are planned to come online. S/L agencies also reviewed the IPM results to 

verify that existing controls and emission rates were properly reflected in the IPM runs. As 

directed by the S/L agencies, adjustments to the IPM results were made to specific units with any 

new information they had as part of the permitting process or other contact with the industry that 

indicates which units will install controls as a result of CAIR and when these new controls will 

come on-line. Mississippi decided to continue to use the Southern Company projections instead 

of the IPM projections to represent emissions at Southern Company facilities in Mississippi. The 

initial set of state-specified changes to the VISTAS/CENRAP Phase II set of IPM runs were used 

to create the Base G projection inventory (and are documented later in Section 2.1.1.6). The 

second set of state specified changes were made only for the 2018 inventory, resulting in the 

Base G2 2018 inventory (documented later in Section 2.1.1.7). The final set of state specified 

changes applied to both the 2009 and 2018 inventories and were used to create the B&F 2009 

and 2018 inventories (documented later in Section 2.1.1.8). 
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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. 

IPM provides “forecasts of least-cost capacity expansion, electricity dispatch, and emission 

control strategies for meeting energy demand and environmental, transmission, dispatch, and 

reliability constraints.” The underlying database in this modeling is U.S. EPA’s National Electric 

Energy Data System (NEEDS) released with the CAIR Notice of Data Availability (NODA). 

The NEEDS database contains the existing and planned/committed unit data in EPA modeling 

applications of IPM. NEEDS includes basic geographic, operating, air emissions, and other data 

on these generating units. VISTAS States and stakeholders provided changes for: 

 NOx post-combustion control on existing units 

 SO2 scrubbers on existing units 

 SO2 emission limitations 

 PM controls on existing units 

 Summer net dependable capacity 

 Heat rate for existing units 

 SO2 and NOx control plans based on State rules or enforcement settlements 

The years 2009 and 2018 were explicitly modeled. 

2.1.1.3 Post-Processing of IPM Parsed Files 

The following summary of the VISTAS/Midwest Regional Planning Organization (MRPO) IPM 

modeling is based on Pechan’s documentation LADCO IPM Model Parsed File Post-Processing 

Methodology and File Preparation, February 8, 2005. The essence of the IPM model postprocessing methodology is to take an initial IPM model output file and transform it into air 

quality model input files. ICF via VISTAS/MRPO provides an initial spreadsheet file containing 

unit-level records of both 

(1) “existing” units and 

(2) committed or new generic aggregates. 

All records have unit and fuel type data; existing, retrofit (for SO2 and NOx), and separate NOx

control information; annual SO2 and NOx emissions and heat input; summer season (MaySeptember) NOx and heat input; July day NOx and heat input; coal heat input by coal type; 
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nameplate capacity megawatt (MW), and State FIPS code. Existing units also have county FIPS 

code, a unique plant identifier (ORISPL) and unit ID (also called boiler ID) (BLRID); generic 

units do not have these data. The processing includes estimating various types of emissions and 

adding in control efficiencies, stack parameters, latitude-longitude coordinates, and State 

identifiers (plant ID, point ID, stack ID, process ID). Additionally, the generic units are sited in a 

county and given appropriate IDs. This processing is described in more detail below. 

The data are prepared by transforming the generic aggregates into units similar to the existing 

units in terms of the available data. The generic aggregates are split into smaller generic units 

based on their unit types and capacity, are provided a dummy ORIS unique plant and boiler ID, 

and are given a county FIPS code based on an algorithm that sites each generic by assigning a 

sister plant that is in a county based on its attainment/nonattainment status. Within a State, plants 

(in county then ORIS plant code order) in attainment counties are used first as sister sites to 

generic units, followed by plants in PM nonattainment counties, followed by plants in 8-hour 

ozone nonattainment counties. Note that no LADCO or VISTAS States provided blackout 

counties that would not be considered when siting generics, so this process is identical to the one 

used for EPA IPM post-processing. 

SCCs were assigned for all units; unit/fuel/firing/bottom type data were used for existing units’ 

assignments, while only unit and fuel type were used for generic units’ assignments. Latitudelongitude coordinates were assigned, first using the EPA-provided data files, secondly using the 

September 17, 2004 Pechan in-house latitude-longitude file, and lastly using county centroids. 

These data were only used when the data were not provided in the 2002 NIF files. Stack 

parameters were attached, first using the EPA-provided data files, secondly using a March 9, 

2004 Pechan in-house stack parameter file based on previous EIA-767 data, and lastly using an 

EPA June 2003 SCC-based default stack parameter file. These data were only used when the 

data were not provided in the 2002 NIF files. 

Additional data were required for estimating VOC, CO, filterable primary PM10 and PM2.5, PM 

condensable, and NH3 emissions for all units. Thus, ash and sulfur contents were assigned by 

first using 2002 EIA-767 values for existing units or SCC-based defaults; filterable PM10 and 

PM2.5 efficiencies were obtained from the 2002 EGU NEI that were based on 2002 EIA-767 

control data and the PM Calculator program (a default of 99.2 percent is used for coal units if 

necessary); fuel use was back calculated from the given heat input and a default SCC-based heat 

content; and emission factors were obtained from an EPA-approved October 7, 2004 Pechan 

emission factor file based on AP-42 emission factors. Note that this updated file is not the one 

used for estimating emissions for previous EPA post-processed IPM files. Emissions for 28 

temporal-pollutant combinations were estimated since there are seven pollutants (VOC, CO, 

primary PM10 and PM2.5, NH3, SO2 and NOx) and four temporal periods (annual, summer season, 

winter season, July day). 
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The next step was to match the IPM unit IDs with the identifiers in VISTAS 2002 inventory. A 

crosswalk file was used to obtain FIPS State and county, plant ID (within State and county), and 

point ID. If the FIPS State and county, plant ID and point ID are in the 2002 VISTAS NIF tables, 

then the process ID and stack ID are obtained from the NIF; otherwise, defaults, described 

above, were used. 

Pechan provided the post-processed files in NIF 3.0 format. Two sets of tables were developed : 

“NIF files” for IPM units that have a crosswalk match and are in the 2002 VISTAS inventory, 

and “NoNIF files” for IPM units that are not in the 2002 VISTAS inventory (which includes 

existing units with or without a crosswalk match as well as generic units). 

For Base F and Base G projections, VISTAS reviewed the PM and NH3 emissions from EGUs as 

provided by Pechan and identified significantly higher emissions in 2009/2018 than in 2002. 

VISTAS determined that Pechan used a set of PM and NH3 emission factors that are “the most 

recent EPA approved uncontrolled emission factors” for estimating 2009/2018 emissions. These 

factors are most likely not the same emission factors used by States for estimating these 

emissions in 2002 for EGUs in the VISTAS domain. Thus, the emission increase from 2002 to 

2009/2018 was simply an artifact of the change in emission factor, not anything to do with 

changes in activity or control technology application. Also, VISTAS identified an inconsistent 

use of SCCs for determining emission factors between the base and future years. 

VISTAS resolution of the PM and NH3 problem is fully documented in EGU Emission Factors 

and Emission Factor Assignment, memorandum from Greg Stella to VISTAS State Point Source 

Contacts and VISTAS EGU Special Interest Workgroup, June 13, 2005. The first step was the 

adjustment of the 2002 base year emissions inventory. Using the latest “EPA-approved” 

uncontrolled emission factors by SCC, Alpine Geophysics utilized CERR or VISTAS reported 

annual heat input, fuel throughput, heat, ash and sulfur content to estimate annual uncontrolled 

emissions for units identified as output by IPM. This step was conducted for non-CEM pollutants 

(CO, VOC, PM, and NH3) only. For PM emissions, the condensable component of emissions 

was calculated and added to the resulting PM primary estimations. The resulting emissions were 

then adjusted by any control efficiency factors reported in the CERR or VISTAS data collection 

effort. The second adjustment was to the future year inventories. Alpine Geophysics updated the 

SCCs in the future year inventory to assign the same base year SCC. Using the same methods as 

described for the 2002 revisions, those non-IPM generated pollutants were estimated using IPM 

predicted fuel characteristics and base year 2002 SCC assignments. 

2.1.1.4 Eliminating Double Counting of EGU Units 

The following procedures were used to avoid double counting of EGU emissions in the 

2009/2018 point source inventory. The 2002 VISTAS point source emission inventory contains 

both EGUs and non-EGUs. Since this file contains both EGUs and non-EGU point sources, and 
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EGU emissions are projected using the IPM, it was necessary to split the 2002 point source file 

into two components. The first component contains those emission units accounted for in the 

IPM forecasts. The second component contains all other point sources not accounted for in IPM. 

As described in the previous section, Pechan developed 2009/2018 NIF files for EGUs from the 

IPM parsed files. All IPM matched units were initially removed from the 2009/2018 point source 

inventory to create the non-EGU inventory (which was projected to 2009/2018 using the nonEGU growth and control factors described in Section 2.1.2). This was done on a unit-by-unit 

basis based on a cross-reference table that matches IPM emission unit identifiers (ORISPL plant 

code and BLRID emission unit code) to VISTAS NIF emission unit identifiers (FIPSST state 

code, FIPSCNTY county code, State Plant ID, State Point ID). When there was a match between 

the IPM ORISPL/BLRID and the VISTAS emission unit ID, the unit was assigned to the EGU 

inventory; all other emission units were assigned to the non-EGU inventory. 

If an emission unit was contained in the NIF files created by Pechan from the IPM output, the 

corresponding unit was removed from the initial 2009/2018 point source inventory. The NIF 

2009/2018 EGU files from the IPM parsed files were then merged with the non-EGU 2009/2018 

files to create the 2009/2018 Base F point source files. 

Next, we prepared several ad-hoc QA/QC queries to verify that there was no double-counting of 

emissions in the EGU and non-EGU inventories: 

 We reviewed the IPM parsed files {VISTASII_PC_1f_AllUnits_2009 (To Client).xls and 

VISTASII_PC_1f_AllUnits_2018 (To Client).xls} to identify EGUs accounted for in 

IPM. We compared this list of emission units to the non-EGU inventory derived from the 

VISTAS cross-reference table to verify that units accounted for in IPM were not doublecounted in the non-EGU inventory. As a result of this comparison, we made a few 

adjustments in the cross-reference table to add emission units for four plants to ensure 

these units accounted for in IPM were moved to the EGU inventory. 

 We reviewed the non-EGU inventory to identify remaining emission units with an 

Standard Industrial Classification (SIC) code of “4911 Electrical Services” or Source 

Classification Code of “1-01-xxx-xx External Combustion Boiler, Electric Generation”. 

We compared the list of sources meeting these selection criteria to the IPM parsed file to 

ensure that these units were not double-counted. 

S/L agencies also reviewed the 2009/2018 point source inventory to verify whether there was 

any double counting of EGU emissions. In two instances, S/L agencies provided corrections 

where an emission unit was double counted. 
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2.1.1.5 Quality Assurance Steps 

Quality assurance was an important component to the inventory development process. The 

following QA steps on the EGU component of the VISTAS revised 2009/2018 EGU inventory: 

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. 

2. Provided facility level emission summaries for 2009/2018 for both the base case and 

CAIR case to the VISTAS EGU SIWG to ensure that emissions were consistent and that 

there were no missing sources. 

3. Compared, at the State-level, emissions from the IPM parsed files and the post-processed 

NIF files to verify that the post-processed NIF files were consistent with the IPM parsed 

file results. 

VISTAS requested S/L review of these files – the changes specified by states as a result of this 

review are documented in the following subsection. 

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

After S/L agency review of the final set of IPM runs (as incorporated into the Base F inventory), 

S/L agencies specified a number of changes to the IPM results to better reflect current 

information on when and where future controls would occur. These changes to the IPM results 

primarily involved S/L agency addition or subtraction future emission controls based on the best 

available data from state rules, enforcement agreements, compliance plans, permits, and 

discussions/commitments from individual companies. 

For example, Dominion Virginia Power released their company-wide plan to reduce emission to 

meet the requirements of CAIR and other programs. This plan varies substantially from the IPM 

results both in terms current and future controls and timing of these controls. As a result, VA 

DEQ developed their best estimates of future controls on EGUs in Virginia. Also, Duke Energy 

and Progress Energy have updated their plans for complying with North Carolina’s Clean 

Smokestack Act. These plans vary substantially from the IPM results both in terms current and 

future controls and timing of these controls. As a result, NC DENR replaced the IPM emission 

projections for 2009 with projections from the Duke Energy and Progress Energy compliance 

plan. NC DENR elected to use the IPM results for 2018. 

Some S/L agencies specified changes to the controls assigned by IPM to reflect their best 

estimates of emission controls. 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 generally used a control 
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efficiency of 90 percent when adding or removing SO2 scrubber controls (unless a different 

control efficiency was provided by the State). We generally used a control efficiency of 90 

percent when adding or removing NOx SCR controls at coal-fired plants, 80 percent when adding 

or removing NOx SCR controls at gas-fired plants, and 35 percent when adding or removing NOx

SNCR controls (unless a different control efficiency was provided by the State). The changes 

specified by the S/L agencies are summarized in Table 2.1-1. A comparison of the IPM and 

VISTAS control assumptions for all coal-fired EGUs in the Base G/G2 inventories are 

summarized in Appendix H. In addition to the changes to the IPM-assigned controls, the S/L 

agencies also specified other types of changes to the IPM results. These other specific changes to 

the IPM results are summarized in Table 2.1-2. 

S/L agencies provided information and/or comment on changes in stack parameters from the 

2002 inventory for 2009/2018 inventory. Changes to stack parameters were also made in cases 

where new controls are scheduled to be installed. In cases where an emission unit projected to 

have a SO2 scrubber in either 2009 or 2018, some states were able to provide revised stack 

parameters for some units based on design features for the new control system. Other units 

projected to install scrubbers by 2009 or 2018 are not far enough along in the design process to 

have specific design details. For those units, the VISTAS EGU SIWG made the following 

assumptions: 1) the scrubber is a wet scrubber; 2) keep the current stack height the same; 3) keep 

the current flow rate the same, and 4) change the stack exit temperature to 169 degrees F (this is 

the virtual temperature derived from a wet temperature of 130 degrees F). VISTAS determined 

that exit temperature (wet) of 130 degrees F +/- 5 degrees F is representative of different size 

units and wet scrubber technology. 

2.1.1.7 S/L Adjustments to IPM Modeling Results for Base G2 2018 Projections 

Following release of the Base G inventory, four States specified additional changes to reflect 

their best estimates of emission controls in 2018. These additional changes are marked with an 

“*” in Tables 2.1-1 and 2.1-2. The following changes were requested and implemented in the 

VISTAS 2018 Base G2 EGU emissions and modeling inventories: 

 Florida - Removed scrubbers from Smith units 1 & 2. Added scrubbers to Crist units 4, 

5, & 6. Forecast emissions (from 2002 base) using growth factors for Northside units 1A 

and 2A. These units were estimated to be non operational in the IPM base case run. 

 Georgia - Added scrubbers to Plant Scherer (Units 1-4) and Plant Yates (Units 6 & 7). 

 North Carolina - Remove scrubber from F Lee unit 3. 

 West Virginia - Pleasants Units 1 and 2 had SO2 emissions reduced to account for the 

facility's inclusion of previously bypassed 15% effluent stream to the scrubber and the 

control efficiency and emissions will reflect a change from 79.9% to 95% control. 
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Table 2.1-1 Adjustments to IPM Control Determinations Specified by S/L Agencies 

for the Base G/G2 2009/2018 EGU Inventories. 

NOx Retrofit Emission Controls SO2 Retrofit Emis

State Plant Name and ID Unit 2009 2018 2009 

IPM State IPM State IPM State 

AL James H. Miller 

ORISID=6002 

1 & 2 SCR 

during ozone season 

SCR probable year round due to CAIR 

SCR during ozone season 

SCR probable year round due to CAIR 

None None N

 3 & 4 SCR 

during ozone season 

SCR year round from Consent Decree 

SCR during ozone season 

SCR year round from Consent Decree 

None None N

 Barry 1, 2, 3 None SNCR SCR SNCR None None N ORISID=3 4 None SNCR SCR SNCR None None S 5 None None SCR SCR None None S E C Gaston 1 - 4 SCR None SCR None None None S ORISID=26 5 SCR SCR SCR SCR Scrubber None S Gorgas 6 & 7 None None None None None None N ORISID=8 8 & 9 None None None None None Scrubber N 10 SCR SCR SCR SCR None Scrubber S Charles R. Lowman 1 None None None None None Scrubber N ORISID=56 2 & 3 SCR SCR SCR SCR Scrubber Scrubber S

FL Lansing Smith 1 None None SCR SCR None None S

 ORISID=643 2 None None SCR SCR None None S Northside 

ORISID=667 

1A & 

1B 

No operation 

No operation 

No operation 

No control, emissions forecasted using growth rates* 

No operation 

No operation 

No
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Table 2.1-1 (continued) 

NOx Retrofit Emission Controls SO2 Retrofit Emis

State Plant Name and ID Unit 2009 2018 2009 

IPM State IPM State IPM State 

FL Crist 4 None None None None None None N

 ORISID=641 5 None None None None None None N 6 None None None None None None N

GA Bowen 1BLR SCR SCR SCR SCR None S

 ORISID=703 2BLR SCR SCR SCR SCR None S 3BLR SCR SCR SCR SCR Scrubber S 4BLR SCR SCR SCR SCR 

IPM had retrofit scrubbers but little emission reductions 

Scrubber S

 Wansley 1 SCR SCR SCR SCR Scrubber S ORISID=6052 2 SCR SCR SCR SCR 

IPM had retrofit scrubbers but little emission reductions 

None S

 Kraft 1, 2 None None None None None None N ORISID=733 3 None None SCR None None None N McIntosh 

ORISID=6124 

1 None None SCR None None None N

 Yates 1 None None None None Scrubber Scrubber S ORISID=728 2, 3 None None None None None None N 4, 5 None None SCR SCR None None S 6, 7 None None SCR SCR None None S
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Table 2.1-1 (continued) 

NOx Retrofit Emission Controls SO2 Retrofit Emis

State Plant Name and ID Unit 2009 2018 2009 

IPM State IPM State IPM State 

GA Hammond 1 None None SCR SCR None Scrubber S

 ORISID=708 2 None None SCR SCR None Scrubber S 3 None None SCR SCR None Scrubber S 4 SCR SCR SCR SCR Scrubber Scrubber S Scherer 1 None None None None None None N ORISID=6257 2 None None None None None None N 3 None None None None None None N 4 None None None None None None N

KY Ghent 1 None SCR SCR SCR Scrubber Scrubber S

 ORISID=1356 2 None None SCR SCR None Scrubber S 3, 4 None SCR SCR SCR None Scrubber S Coleman C1 None None SCR SCR None Scrubber S ORISID=1381 C2 None None SCR SCR None Scrubber S C3 None None SCR SCR None Scrubber S HMP&L Station 2 H1 SCR SCR SCR SCR Scrubber Scrubber S H2 None SCR SCR SCR Scrubber Scrubber S E W Brown 1 None None None None None Scrubber N ORISID=1355 2 None None SCR SCR None Scrubber S 3 None None SCR SCR None Scrubber S

SC Jeffries 3 SCR None SCR None None None N

 ORISID=3319 4 None None None None None None N Wateree WAT1 SCR SCR SCR SCR None Scrubber N ORISID=3297 WAT2 SCR SCR SCR SCR None Scrubber S
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Table 2.1-1 (continued) 

NOx Retrofit Emission Controls SO2 Retrofit Emis

State Plant Name and ID Unit 2009 2018 2009 

IPM State IPM State IPM State 

SC Canadys CAN1 None None None None None None N

 ORISID=3280 CAN2 None None None None None None N CAN3 None None None None None Scrubber N Rainey CT1A None SCR None SCR None None N ORISID=7834 CT1B None SCR None SCR None None N

TN Kingston 1 – 8 SCR SCR SCR SCR None None S

 ORISID=3407 9 None SCR SCR SCR None None S Johnsonville 1 – 10 SCR None SCR SCR None None N ORISID=3406 

WV Willow Island 2 SCR None SCR SCR Scrubber None S

 ORISID=3946  Kammer 1 -3 SCR None SCR SCR Scrubber None S ORISID=3947 

Note: See Appendix H for a complete list of IPM and VISTAS control determinations for all coal and oil/gas units. 
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Table 2.1-2 Other Adjustments to IPM Results Specified by S/L Agencies 

for the Base G/G2 2009/2018 EGU Inventories. 

State Plant Name and ID Unit Nature of Update/Correction 

FL Central Power and Lime 

ORISID= 10333 

GEN1 Central Power and Lime (ORIS10333) is a duplicate entry. 

This is point 18 in Florida Crushed Stone (12-053-0530021). 

Removed IPM emissions for Central Power and Lime. 

 Cedar Bay Generating 

ORISID=10672 

GEN1 FLDEP disagrees with IPM projections - no knowledge of 

expansion of this facility and the cogeneration facility 

should not grow faster than the underlying industry. Cedar 

Bay is connected to Stone Container (12-031-0310067). 

Replaced IPM emissions with 2002 emissions for Cedar Bay 

(12-031-0310337) times the growth factors for Stone 

Container. 

 Indiantown Cogeneration 

ORISID=50976 

GEN1 FLDEP disagrees with IPM projections - no knowledge of 

expansion of this facility and the cogeneration facility 

should not grow faster than the underlying industry. 

Indiantown is connected to Louis Dreyfus Citrus (12-085-

0850002). Replaced IPM emissions with 2002 emissions for 

Indiantown (12-085-0850102) times the growth factors for 

Louis Drefus Citrus. 

GA Bowen 

ORISID=703 

1BLR 

2BLR 

3BLR 

4BLR 

IPM indicated retrofit scrubbers on all 4 units in 2009, but 

the IPM emissions showed little reductions from 2002 

levels. Changed emissions to reflect scrubbers on 3BLR and 

4BLR by 2009. 

 Wansley 

ORISID=6052 

1, 2 IPM indicated retrofit scrubbers on both units in 2009, but 

the IPM emissions showed little reductions from 2002 

levels. Changed emissions to reflect one scrubber on Unit 1 

by 2009. 

 Riverside 

ORISID=734 

4 All of plant Riverside was retired from service June 1, 2005; 

emissions set to zero in 2009 and 2018. 

 McIntosh 

ORISID=727 

CT10A 

CT10B 

CT11A 

CT11B 

The McIntosh Combined Cycle facility became commercial 

June 1, 2005. Added 346 tons of NOx and 121 tons of SO2

per unit to the 2009 and 2018 inventories. 

 Longleaf Energy Station 1, 2 Longleaf Energy Station is being proposed by LS Power 

Development, Inc. GA specified that the emissions from this 

proposed plant be included in the 2018 projections. Boilers 1 

and 2 added 1,882 tons of NOx and 3,227 tons of SO2 per 

unit to the 2018 inventory. 

 Duke Murray (55382) 1 Corrected coordinates to 34.7189 and -84.9353 

MS R D Morrow 

ORISID=6061 

1, 2 Revised the 2018 emissions to reflect controls not indicated 

by IPM. The SO2 emissions are much lower than IPM, but 

their expected NOx emissions are actually higher than IPM. 

The controls will be coming online 2009 or 2010, so the 

2009 inventory did not change. 

 Jack Watson (2049) 

Victor J Daniel (6073) 

Chevron Oil (2047) 

All MS DEQ specified that the emission projections provided by 

the Southern Company for their units in Mississippi were to 

be used instead of the IPM results. 
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Table 2.1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

NC G G Allen (2718) 

Belews Creek (8042)1 

Buck (2720) 

Cliffside (2721) 

Dan River (2723) 

Marshall (2727) 

Riverbend (2732) 

All Replaced all IPM 2009 results with emission projections 

from Duke Power’s NC Clean Air Compliance Plan for 

2006. Used IPM results for 2018 

 Asheville (2706) 

Cape Fear (2708) 

Lee (2709) 

Mayo (6250) 

Roxboro (2712) 

Sutton (2713) 

Weatherspoon (2716) 

All Replaced all IPM 2009 results with emission projections 

from Progress Energy’s NC Clean Smokestacks Act 

Calendar Year 2005 Progress Report. Used IPM results for 

2018, except for Lee #3* where IPM projected a retrofit 

scrubber but NC specified that no scrubber was to be 

applied. 

 Dwayne Collier Battle 

Cogeneration Facility 

ORISID=10384 

GEN1 

GEN2 

Dwayne Collier Battle is a duplicate entry. This is Cogentrix 

of Rocky Mount (37-065-3706500146, stacks G-26 and G27). Duplicate entries were removed both the 2009 and 2018 

inventories. 

 Kannapolis Energy 

Partners 

ORISID=10626 

GEN2 

GEN3 

Kannapolis Energy emissions are being used as credits for 

another facility. IPM emissions from this facility (37-025-

ORIS10626) were removed from the EGU inventory for 

2009 and 2018. Emissions from Kannapolis Energy (37-025-

3702500113) were carried forward in the 2009/2018 

inventory. 

SC Cross 

ORISID=130 

1, 2 Unit 1: upgrade scrubber from 82 percent to 95 percent 

removal efficiency by June 30, 2006. Recalculate emissions 

based on upgrade in control efficiency. 

Unit 2: upgrade scrubber from 70 percent to 87 percent 

removal efficiency by June 30, 2006. Recalculate emissions 

based on upgrade in control efficiency. 

 Winyah 

ORISID=6249 

1 – 4 Unit 1: Install scrubber that meets 95 percent removal 

efficiency by Dec. 31, 2008; Upgrade ESP from 0.38 to 0.03 

lb/mmBTU by Dec. 31, 2008 

Unit 2: Replace scrubber with one that meets 95 percent 

removal efficiency from 45 percent by Dec. 31, 2008; 

Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 

2008 

Unit 3: Upgrade scrubber from 70 percent to 90 percent 

removal efficiency by Dec. 31, 2012; Upgrade ESP from 

0.10 to 0.03 lb/mmBTU by Dec. 31, 2012 

Unit 4: Upgrade scrubber from 70 percent to 90 percent 

removal efficiency by Dec. 31, 2007; Upgrade ESP from 

0.10 to 0.03 lb/mmBTU by Dec. 31, 2007 

Recalculated SO2 and PM emissions based on upgrade in 

control efficiencies. 
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Table 2.1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

SC Dolphus Grainger 

ORISID=3317 

1, 2 Unit 1: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 95 

percent based on change in allowable emission rate 

Unit 2: Install low NOx burners that meet 0.46 lb/mmBTU 

from 0.9 by May 1, 2004. Recalculated NOx emissions using 

0.46/lbs/mmBtu and IPM heat input 

Unit 2: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 95 

percent based on change in allowable emission rate 

 Jeffries 

ORISID=3319 

3, 4 Unit 3: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 

94.44 percent based on change in allowable emission rate 

Unit 4: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 

94.44 percent based on change in allowable emission rate 

 W S Lee 

ORISID=3264 

1, 2 IPM does not indicate that these units are installing SOFA 

NOx control technology by April 30, 2006 to meet 0.27 

lb/mmBTU, down from 0.45 lb/mmBtu. Calculated NOx

emissions using IPM heat input and 0.27 lbs/mmBtu 

 Generic Unit 

ORISID=900545 

All All predictions for generic units appear reasonable with the 

exception of Plant ID ORIS900545 Point ID GSC45 which 

was modeled in Georgetown County. It will be very difficult 

to add new generation this close to the Cape Romain Class I 

area. Santee Cooper has no plans for future generation in 

Georgetown County, but does have plans for new future 

generation in Florence County. This unit was moved to 

coordinates specified in Florence County. 

VA AEP Clinch River 

ORISID=3775 

1, 2, 3 Used IPM results for 2009; replaced all 2018 IPM results 

with VADEQ’s growth and control estimates (no SCR or 

scrubbers). 

 AEP Glen Lyn 

ORISID=3776 

51, 52, 

6 

Used 2009/2018 IPM results for units 51 and 52; used 2009 

IPM for unit 6; replaced 2018 IPM for unit 6 with VADEQ’s 

growth and control estimates (nor SCR or scrubber). 

 Dominion Clover 

ORISID=7213 

1, 2 Used 2009/2018 IPM results. 

 Dominion Bremo 

ORISID=3796 

3, 4 Used 2009/2018 IPM results. 

 Dominion Chesterfield 

ORISID=3797 

3, 4, 

5, 6 

Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

 Dominion Yorktown 

ORISID=3809 

1, 2, 3 Units 1, 2: Used 2009/2018 IPM results for NOx and used 

VADEQ’s growth and control estimates for SO2. 

Unit 3: IPM predicts zero heat input for this 880 MW #6 oil 

fired unit. Dominion plans to continue to operate Unit 3. 

Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 
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Table 2.1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

VA Dominion Chesapeake 

ORISID=3803 

1 – 4 Unit 1: Used 2009/2018 IPM for NOx; used 2009 IPM for 

SO2; used VADEQ’s growth and control estimates for SO2 

(added scrubber that IPM did not have) 

Unit 2: Used 2009/2018 IPM for NOx; used 2009 IPM for 

SO2; used VADEQ’s growth and control estimates for SO2 

(added scrubber that IPM did not have) 

Unit 3: Used VA DEQ’s growth and control estimates for 

2009 NOx (added SCR that IPM did not have); used IPM 

result for 2018 NOx; Used 2009/2018 IPM for SO2. 

Unit 4: Used VA DEQ’s growth and control estimates for 

2009 NOx (added SCR that IPM did not have); used IPM 

result for 2018 NOx; Used 2009/2018 IPM for SO2. 

 Dominion Possum Point 

ORISID=3804 

3 & 4 

5 

6 

Unit 3&4: IPM had 137 tons of NOx for these units in 2009 

and 111 tons in 2018. VA DEQ specified that the permitted 

emission rates should be used, which equates to 3,066 tons 

in 2009 and 2018. 

Unit 5: IPM had zero heat input. Replaced all 2009/2018 

IPM results using VADEQ’s growth and control estimates. 

Unit 6: Replaced all 2009/2018 IPM results using VADEQ’s 

growth and control estimates. 

 Potomac River 

ORISID=3788 

1 - 5 Units 1&2: IPM retired these units. Mirant has no plans at 

this time to retire any units. Replaced all 2009/2018 IPM 

results using VADEQ’s growth and control estimates. 

Units 3, 4, 5: Replaced all 2009/2018 IPM results using 

VADEQ’s growth and control estimates. 

WV Albright 

ORISID=3942 

1, 2 IPM predicted early retirement for these units. AEP 

indicated there are no plans for early retirement. For 2009, 

used 2002 actual emissions as these units are not likely to 

retire by 2009. For 2018, used IPM prediction of retirement. 

 Rivesville 

ORISID=3945 

7, 8 IPM predicted early retirement for these units. AEP 

indicated there are no plans for early retirement. For 2009, 

used 2002 actual emissions as these units are not likely to 

retire by 2009. For 2018, used IPM prediction of retirement. 

 Willow Island 

ORISID=3946 

1, 2 Unit 1: IPM predicted early retirement for these units. AEP 

indicated there are no plans for early retirement. For 2009, 

used 2002 emissions as these units are not likely to retire by 

2009. For 2018, used IPM prediction of retirement. 

Unit 2: IPM predicted SCR and scrubber for 2009. These 

controls will not be in place by 2009. 

 North Branch 

ORISID=7537 

1A, 1B SO2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. 

Used SO2 Permit Rate and IPM predicted total fuel used to 

calculate SO2 emissions in 2009 and 2018 

 Mt. Storm 

ORISID=3954 

1, 2, 3 SO2 Permit Rate was corrected from 2.7 to 0.15 lb/MMBtu. 

Used SO2 Permit Rate of 0.15 lb/MMBtu and IPM predicted 

total fuel used to calculate SO2 emissions in 2009 and 2018 

 Pleasants Power Station 

ORISID=6004 

1, 2 IPM applied a scrubber with a 79.9% control efficiency; WV 

indicated that the control efficiency should be 95%. 
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2.1.1.8 S/L Adjustments to IPM Modeling Results for B&F Projections 

For the B&F inventory, the S/L agencies were asked to review the Base G2 inventory with 

respect to the following items: 

 Identify any updates needed to better reflect current information on when and where 

future controls would occur based on the best available data from state rules, enforcement 

agreements, compliance plans, permits, and discussions/commitments from individual 

companies; 

 Identify any updates needed to change the IPM determination that most oil/gas steam 

units would either retire early or have no operation in 2009 or 2018; and 

 Identify any updates needed to change the IPM assignment and VISTAS post-processing 

of generic units with specific information on new capacity. 

The changes specified by the S/L agencies are summarized in Table 2.1-3. A comparison of the 

IPM and VISTAS control assumptions for all coal-fired EGUs in the B&F inventories are 

summarized in Appendix I. 

Table 2.1-3 Additional Adjustments to IPM Results Specified by S/L Agencies 

for the B&F 2009/2018 EGU Inventories. 

State Plant Name and ID Unit Nature of Update/Correction 

FL Cape Canaveral 

Indian River 

Port Everglades 

Turkey Point 

Manatee 

Martin 

Riviera 

Anclote 

CD McIntosh 

Northside B 

Suwannee River 

1, 2 

1, 2, 3 

1 – 4 

1, 2 

1, 2 

1, 2 

3, 4 

1, 2 

1 

3 

3 

The IPM 2009/2018 solution has either shut-down these oilfired units or converted them to natural gas only. FLDEP has 

reason to believe that these units may continue to operate 

using oil. For some of these units, the owner or operator of 

the units have provided (and FLDEP approved) an estimate 

of how the units will be operated in 2009/2018. For others, 

to be conservative, FLDEP assumed that the oil-fired units 

will operate in 2009/2018 exactly as they operated in 2002. 

 Gulf Power Schultz 

ORISID=643 

1 - 4 Plant is expected to shut down and was taken out of the 2018 

projection. 

 Northside 

ORISID=667 

1A, 1B These units were estimated to be non operational by IPM in 

2009 and 2018. FLDEP believes these units will continue to 

operate. Emissions were estimated using the 2002 base case 

emissions and growth factors for Northside units 1A and 2A. 

The changes for 2009 were made in the B&F inventory; the 

changes for 2018 were made in the Base G2 inventory. 

 Crist 

ORISID=641 

4, 5 

6, 7 

IPM did not assign scrubbers to these units. Scrubbers are 

currently being installed and should be operational in 2009. 

SO2 emissions reduced by 90%. 

GA Mitchell 

ORISID=727 

SG03 GADNR provided new emission projections for 2018. 
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Table 2.1-3 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

GA Kraft 

ORISID=733 

SG03 GADNR provided new emission projections for 2018. 

 McIntosh 

ORISID=6124 

SG01 GADNR provided new emission projections for 2018. 

 Bowen 

ORISID=703 

SG03 

SG04 

GADNR provided new SO2 emission projections for 2009 

and 2018 based on a 95% control efficiency instead of 90%. 

 Hammond 

ORISID=708 

SG01 to 

SG04 

GADNR provided new SO2 emission projections for 2009 

and 2018 based on a 95% control efficiency instead of 90%. 

 Wansley 

ORISID=6052 

SG01 GADNR provided new SO2 emission projections for 2009 

and 2018 based on a 95% control efficiency instead of 90%. 

KY John Sherman Cooper 

ORISID=1384 

1 IPM did not assign a scrubber to this unit in 2018. KDAQ 

believes that a scrubber should be assigned for 2018. 

 John Sherman Cooper 

ORISID=1384 

2 IPM assigned SCR in 2009. KDAQ does not expect SCR by 

then; emissions changed to reflect low-NOx burner. 

 Spurlock Station 

ORISID=6041 

1, 2 IPM did not assign scrubbers to these units in 2009. Per a 

consent decree and for BART, KDAQ specified a 90% 

reduction in SO2 emissions from SO2 controls. 

 Big Sandy 

ORISID=1353 

BSU1 IPM assigned a scrubber and SCR in 2009. KDAQ does not 

expect scrubber or SCR controls to be operational in 2009. 

MS Entergy Delta 

Entergy Rex Brown 

Entergy Baxter Wilson 

Entergy Gerald Andrus 

1, 2 

3, 4 

1, 2 

1 

The IPM 2009/2018 solution has either shut-down these oilfired units or converted them to natural gas only. MSDEQ 

has reason to believe that these units may continue to 

operate using oil. To be conservative, MSDEQ assumed that 

the oil-fired units will operate in 2009/2018 exactly as they 

operated in 2002. 

NC Cliffside 

ORISID=2721 

7 Removed Unit 7 from the 2018 inventory since the NC 

Utilities Commission disapproved the permit application. 

 Cape Fear 

ORISID=2798 

1, 2 IPM assigned scrubbers to both units in 2018; NCDENR 

indicated that the facility projected Furnace Sorbent 

Injection. Increased SO2 emissions to reflect change in 

control efficiency. 

SC 99 Oil-fired Units The IPM 2009/2018 solution has either shut-down 99 oilfired units or converted them to natural gas only. SCDHEC 

has reason to believe that these units may continue to 

operate using oil. To be conservative, SCDHEC assumed 

that the oil-fired units will operate in 2009/2018 exactly as 

they operated in 2002. 

SC Santee Cooper Cross 

ORISID=130 

4 For both 2009 and 2018, added in a new 660 MW Unit 4 

(not in IPM) that is identical to the new Unit 3 (which was in 

IPM). Used the new Unit 4 to replace the IPM-generated 500 

MW coal-fired Generic Unit (ORIS900545) located in the 

adjacent county. 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

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Table 2.1-3 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

SC New Santee Cooper Units 

Planned for Florence 

County 

1, 2 Santee Cooper is planning two new coal burning units in 

Florence County, each at 660 MW. These units were not 

explicitly identified in IPM. Used these new units to replace 

three IPM-generated 500 MW coal-fired Generic Units 

(ORIS900145, ORIS900245, ORIS900345) in Darlington 

and Colleton Counties. 

 USDOE SRS Area D 

ORISID=7652 

1 Facility is replacing coal-fired boilers with three biomass 

boilers. Recalculated emissions for 2018 using emission 

factors for biomass combustion and IPM heat inputs. 

VA Dominion Chesapeake 

ORISID=3803 

1 - 4 Changed SO2 emissions in 2009 and 2018 to reflect 

information from the facility on project SO2 controls. 

 Dominion Southwest 

Virginia Project 

1 For 2018, replace the IPM generated Generic Unit located in 

Russell county (ORISID=900251) to Wise County to reflect 

the planned Dominion facility going into Wise County. Used 

the potential to emit for the Dominion facility. 

 Clinch River 

ORISID=3775 

1, 2, 3 Changed emissions in 2018 to reflect requirements of 

Consent Order. The CO requires SNCR by 12/31/2009; IPM 

assigned SCR in 2018. The CO caps SO2 emissions at 

16,300 tpy starting Jan 1, 2015. 

WV Pleasants Power Station 

ORISID=6004 

1, 2 For both 2009 and 2018, Units 1 and 2 had SO2 emissions 

reduced to account for the facility's inclusion of previously 

bypassed 15% effluent stream to the scrubber. The control 

efficiency and emissions changed from 79.9% to 95% 

control. 

 Nine Generic Units 

Generated by IPM 

 IPM placed 746 MW of new fossil fuel-fired generation in 

West Virginia - 173 MW coal-fired, 24 MW IGCC, and the 

remainder gas-fired. A 600 MW pulverized coal-fired EGU 

is under construction, scheduled to be online in 2010 

[Longview]; a 98 MW CFB co-generation unit is permitted 

and expected to be built [Western Greenbrier]; and a 600 

MW IGCC plant is currently in the permitting process 

[Mountaineer IGCC]. WVDEP decided to replace the IPM 

generic units in WV with the 3 units mentioned above. 

 Longview 

Site ID: 54- 061-0134 

1 For 2018 inventory, added Longview which is permitted, 

under construction, and scheduled to be online in 2010. The 

unit is a 600 MW pulverized coal-fired unit with baghouse, 

LNB, SCR, and wet FGD as required controls. Used 

permitted emission rates for 2018. 

WV Western Greenbriar 

Site ID: 54-025-0066 

1 For 2018 inventory, added Western Greenbrier, which is 

permitted but not under construction. The unit is a 98 MW 

coal-fired CFB burning waste coal. Used permitted emission 

rates for 2018. 

 Mountaineer IGCC 

Site ID: 54-053-00063 

1 For 2018 inventory, added Mountaineer IGCC, which has 

applied for a permit to construct a nominal 600 MW IGCC. 

Used emission rates from the permit application for 2018. 
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2.1.1.9 Conversion of MRPO BaseM 2009 EGU Data to SMOKE Input Format 

To support ASIP PM2.5 CAMx modeling of the future year 2009, Alpine Geophysics obtained 

and processed an emission inventory for the 5 MRPO states (Illinois, Indiana, Michigan, 

Wisconsin, and Ohio). Appendix x details the technical steps that were made as part of the 

conversion of the MRPO BaseM EGU files into IDA format for ASIP PM-2.5 CAMx modeling 

of the future year 2009. 

2.1.1.10 Summary of 2009/2018 EGU Point Source Inventories 

Tables 2.1-4 through 2.1-10 compare the Base G 2002 base year inventory to the Base F, Base 

G/G2 and B&F 2009/2018 projection inventories. The Base F projections rely primarily on the 

results of the IPM, while the Base G and B&F projections include the adjustments to the IPM 

results specified by the S/L agencies in the previous section. 

Table 2.1-4 EGU Point Source SO2 Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

Actual 

Base G 

Base F 

IPM 

Based 

Base G 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

Base F 

IPM 

Based 

Base G2 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

AL 447,828 340,194 378,052 378,052 190,099 135,851 135,851 

FL 453,631 195,790 186,055 291,831 141,551 138,340 194,028 

GA 514,952 534,469 417,449 408,679 180,178 79,430 68,515 

KY 484,057 371,944 290,193 271,669 229,603 226,062 222,102 

MS 67,429 85,629 76,579 76,646 27,230 15,146 15,213 

NC 477,990 205,018 242,286 242,286 110,382 114,771 120,165 

SC 206,399 171,206 124,608 129,122 121,694 93,274 95,377 

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

VA 241,204 169,714 193,112 174,777 90,935 114,255 98,988 

WV 516,084 226,127 277,489 268,952 124,466 105,935 106,199 

3,743,725 2,555,491 2,441,233 2,497,423 1,328,800 1,135,736 1,169,110 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 
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Table 2.1-5 EGU Point Source NOx Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

Actual 

Base G 

Base F 

IPM 

Based 

Base G 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

Base F 

IPM 

Based 

Base G2 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

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

FL 257,677 89,610 86,165 132,535 77,080 74,640 87,645 

GA 147,517 97,146 98,497 98,497 58,095 75,717 69,856 

KY 198,817 107,890 92,021 97,263 64,378 64,378 64,378 

MS 43,135 11,475 36,011 47,276 8,945 10,271 21,535 

NC 151,853 66,431 66,522 66,521 60,914 62,353 61,110 

SC 88,241 43,817 46,915 48,668 48,346 51,456 51,751 

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

VA 86,886 63,220 62,547 64,358 49,420 66,074 64,344 

WV 230,977 63,510 86,328 85,476 51,241 51,241 51,474 

1,523,448 655,718 723,717 789,304 492,913 552,203 568,166 

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

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

2002 2009 2018 

State 

Actual 

Base G 

Base F 

IPM 

Based 

Base G 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

Base F 

IPM 

Based 

Base G2 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

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

FL 2,524 1,867 1,910 2,730 2,324 2,422 3,047 

GA 1,244 1,571 2,314 2,314 1,903 2,841 2,816 

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

MS 648 406 404 564 1,124 1,114 1,274 

NC 988 974 954 954 1,272 1,345 1,302 

SC 470 660 660 723 906 906 931 

TN 926 932 932 932 977 976 976 

VA 754 685 778 788 903 1,014 980 

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

12,516 12,247 13,155 14,208 15,174 16,383 17,091 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 
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Table 2.1-7 EGU Point Source CO Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

Actual 

Base G 

Base F 

IPM 

Based 

Base G 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

Base F 

IPM 

Based 

Base G2 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

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

FL 57,113 45,391 35,928 71,072 63,673 54,146 85,495 

GA 9,712 20,066 23,721 23,721 32,744 44,476 44,269 

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

MS 5,303 5,078 5,051 7,116 15,364 15,282 17,348 

NC 13,885 15,141 14,942 14,942 19,612 20,223 19,870 

SC 6,990 11,135 11,135 11,643 14,786 14,786 14,975 

TN 7,084 7,221 7,213 7,214 7,733 7,723 7,723 

VA 6,892 11,869 12,509 12,535 14,755 15,564 18,850 

WV 10,341 11,328 11,493 11,493 11,961 11,961 12,397 

141,218 157,989 152,790 190,535 222,114 225,647 262,413 

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

Table 2.1-8 EGU Point Source PM10-PRI Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

Actual 

Base G 

Base F 

IPM 

Based 

Base G 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

Base F 

IPM 

Based 

Base G2 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

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

FL 21,387 9,384 9,007 20,182 10,310 10,022 12,791 

GA 11,224 17,088 17,891 17,891 18,329 20,909 20,732 

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

MS 1,633 5,487 4,957 5,182 7,624 7,187 7,412 

NC 22,754 22,888 22,152 22,152 33,742 37,376 35,275 

SC 21,400 28,650 19,395 20,041 37,864 28,826 27,640 

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

VA 3,960 4,479 5,508 5,606 12,744 13,832 12,551 

WV 4,573 5,471 5,657 5,657 6,349 6,349 5,784 

113,918 122,477 113,607 125,750 157,419 154,958 152,642 

Note: Emission summaries above are based on SCCs 1-01-xxx-xx and 2-01-xxx-xx. 
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Table 2.1-9 EGU Point Source PM2.5 -PRI Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

Actual 

Base G 

Base F 

IPM 

Based 

Base G 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

Base F 

IPM 

Based 

Base G2 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

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

FL 15,643 6,250 5,910 14,790 7,171 6,886 9,417 

GA 4,939 10,104 10,907 10,907 11,403 13,983 13,881 

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

MS 1,138 5,310 4,777 4,996 7,469 7,033 7,252 

NC 16,498 16,514 15,949 15,949 26,966 29,792 28,137 

SC 17,154 23,366 16,042 16,548 32,180 25,032 23,794 

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

VA 2,606 3,194 4,067 4,165 11,101 11,976 10,773 

WV 2,210 2,850 2,940 2,940 3,648 3,648 3,116 

79,269 88,875 81,884 91,587 122,527 120,939 118,959 

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

Table 2.1-10 EGU Point Source NH3 Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State 

Actual 

Base G 

Base F 

IPM 

Based 

Base G 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

Base F 

IPM 

Based 

Base G2 

IPM with 

State/local 

Updates 

B&F 

IPM with

Additional

State/local

Updates 

AL 317 359 359 359 1,072 1,072 1,072 

FL 234 1,659 1,631 1,629 3,004 2,976 2,976 

GA 83 686 686 686 1,677 1,677 1,677 

KY 326 400 400 400 476 476 476 

MS 190 333 333 334 827 827 827 

NC 54 423 445 445 691 663 663 

SC 142 343 343 370 617 617 625 

TN 204 227 227 227 241 241 241 

VA 127 632 694 694 558 622 606 

WV 121 330 330 330 180 180 143 

1,798 5,392 5,448 5,474 9,343 9,351 9,306 

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

The general approach for assembling future year data was to use growth and control data 

consistent with the data used in EPA’s Clean Air Interstate Rule analyses, supplement these data 

with available stakeholder input, and provide the results for stakeholder review to ensure 

credibility. We used the revised 2002 VISTAS base year inventory, based on the 2002 CERR 

submittals as the starting point for the non-EGU projection inventories. As described in Section 

2.1.1.4, we split the point source inventory into EGU and non-EGU components. MACTEC 

performed the following activities to apply growth and control factors to the 2002 inventory to 

generate the 2009 and 2018 projection inventories: 

 Obtained, reviewed, and applied the most current growth factors developed by EPA, 

based on forecasts from an updated Regional Economic Models, Inc. (REMI) model 

(version 5.5) and the latest Annual Energy Outlook published by the Department of 

Energy (DOE); 

 Obtained, reviewed, and applied any State-specific or sector-specific growth factors 

submitted by stakeholders; 

 Obtained and incorporated information regarding sources that have shut down after 2002 

and set the emissions to zero in the projection inventories; 

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

“on-the-way”; 

 Provided data files in NIF3.0 format and emission summaries in EXCEL format for 

review and comment; and 

 Updated the database with corrections or new information from S/L agencies based on 

their review of the Base F 2009/2018 inventories. 

The following sections discuss each of these steps. 

2.1.2.1 Growth assumptions for non-EGU sources 

This section describes the growth factor data used in developing the Base F inventory for 2009 

and 2018, as well as the changes to the growth factor data made for the Base G inventory. 

The growth factor data used in developing the Base F inventory were consistent with EPA’s 

analyses for the CAIR rulemaking. These growth factors are fully documented in the reports 

entitled Development of Growth Factors for Future Year Modeling Inventories (dated April 30, 

2004) and CAIR Emission Inventory Overview (dated July 23, 2004). Three sources of data were 

used in developing the growth factors for the Base F inventory: 

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

Insight® model, Version 5.5 (being used in the development of the EGAS Version 5.0). 

The REMI socioeconomic data (output by industry sector, population, farm sector value 
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added, and gasoline and oil expenditures) are available by 4-digit SIC code at the 

State level. 

 Energy consumption data from the DOE’s Energy Information Administration’s (EIA) 

Annual Energy Outlook 2004, with Projections through 2025 for use in generating 

growth factors for non-EGU fuel combustion sources. These data include regional or 

national fuel-use forecast data that were mapped to specific SCCs for the non-EGU fuel 

use sectors (e.g., commercial coal, industrial natural gas). Growth factors for the 

residential natural gas combustion category, for example, are based on residential natural 

gas consumption forecasts that are reported at the Census division level. These Census 

divisions represent a group of States (e.g., the South Atlantic division includes eight 

southeastern States and the District of Columbia). Although one would expect different 

growth rates in each of these States due to unique demographic and socioeconomic 

trends, EIA’s projects all States within each division using the same growth rate. 

 Specific changes for sectors (e.g., plastics, synthetic rubber, carbon black, cement 

manufacturing, primary metals, fabricated metals, motor vehicles and equipment) where 

the REMI-based rates were unrealistic or highly uncertain. Growth projections for these 

sectors were based on industry group forecasts, Bureau of Labor Statistics (BLS) 

projections and Bureau of Economic Analysis (BEA) historical growth from 1987-2002. 

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

VISTAS stakeholders. 

The American Forest and Paper Association (AF&PA) supplied growth projections for the pulp 

and paper sector, which were applied to SIC 26xx Paper and Allied Products. The AF&PA 

projection factors are for the U.S. industry and apply to all States equally. The numbers come 

from the 15-year forecast for world pulp and recovered paper prepared by Resource Information 

Systems Inc. (RISI). 

AF&PA Growth Factor 

SIC Code Sector 

2002 to 2009 2002 to 2018 

2611 Pulp Mills 1.067 1.169 

2621 Paper Mills 1.067 1.169 

2631 Paperboard Mills 1.067 1.169 

For both the Base F and Base G inventories, we used the above AF&PA growth factors by SIC 

instead of the factors obtained from EPA’s CAIR analysis. 
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For the Base F inventory, the NCDENR supplied recent projections for three key sectors in 

North Carolina where declining production was anticipated – SIC 22xx Textile Mill Products, 

23xx Apparel and Other Fabrics, and 25xx Furniture and Fixtures. For the Base G inventory, 

NCDENR decided to use a growth factor of 1.0 for these SIC codes for both 2009 and 2018. 

Although NCDENR has data that shows a steady decline in these industries in NC, NCDENR 

wanted to maintain the emission levels at 2002 levels so the future emission reduction credits 

were available in the event that they are needed for nonattainment areas. The specific growth 

factors for these industrial sectors in North Carolina were: 

NCDENR Growth Factors for Specific Industrial Sectors 

2009 2018 

SIC Code Industrial 

Sector Base F Base G Base F Base G 

22xx Textile Mill 

Products 0.6239 1.00 0.2792 1.00 

23xx Apparel and 

Other Fabrics 0.5867 1.00 0.2247 1.00 

25xx Furniture and 

Fixtures 0.8970 1.00 0.7647 1.00 

For the Base G inventory, we made one additional change to the growth factors. The Base F 

inventory relied on DOE’s AEO2004 forecasts for projecting emissions for fuel-burning SCCs 

(applies mainly to ICI boilers 1-02-xxx-xx and 1-03-xxx-xx, as well as in-process fuel use). We 

replaced the AEO2004 data with the more recent AEO2006 forecasts (released in February 

2006) to reflect changes in the energy market and to improve the emissions growth factors 

produced. We obtained the corresponding AEO2006 projection tables from DOE’s web site 

located at http://www.eia.doe.gov/oiaf/aeo/supplement/supref.html. We developed tables comparing 

the growth factors based on AEO2004 and AEO2006. These comparison tables were reviewed 

by the S/L agencies. Based on this review, VISTAS decided to use the AEO2006 growth factors 

for fuel burning SCCs. 

We used the EPA’s EGAS model and updated the corresponding AEO2006 projection tables to 

create growth factors by SCC. We applied the updated growth factors to 2002 actual emissions 

and replaced the 2009 and 2018 emissions in NIF EM tables for the affected SCCs. 

2.1.2.2 Source Shutdowns 

A few states indicated that significant source shutdowns have occurred since 2002 and that 

emissions from these sources should not be included in the future year inventories. These sources 

are identified in Table 2.1-11. 
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Table 2.1-11 Summary of Source Shutdowns Incorporated in Base G Inventory. 

State Description of Source Shutdowns 

AL None specified. 

FL The following facilities are shutdown and projected emissions were set to zero in 2009/2018. 

 0570075 CORONET INDUSTRIES, INC. 

 1050050 U S AGRI-CHEMICALS CORP. 

 1050051 U.S. AGRI-CHEMICALS CORPORATION 

These facilities emitted 2,417 tons of SO2 and 113 tons of NOx in 2002. 

GA Georgia indicated that the former Blue Circle (now LaFarge) facility in downtown Atlanta will likely 

shut down before 2009. The facility has two cement kilns, one of which is already shut down. The 

second kiln will continue to operate until the new facility in Alabama has enough milling capacity, 

after which the entire Atlanta facility will be completely closed down. This facility emitted 1,617 tons 

of SO2 and 587 tons of NOx in 2002. 

KY None specified. 

MS AF&PA indicated that the International Paper Natchez Mill (28-001-2800100010) has shut down. 

This facility emitted 1,398 tons of SO2 and 1,773 tons of NOx in 2002. 

 The Magnolia Resources - Pachuta Harmony Gas Plant (28-023-00031) is out of business and no 

longer holds an air permit. This facility emitted 2,257 tons of SO2and 134 tons of NOx in 2002. 

NC In Base F, two paper mills were identified as being shut down in the 2018 inventory. NCDENR 

indicated that these mills are not expected to close. The two facilities are Ecusta Business 

Development (37-175-3717500056) and International Paper (37-083-00007). Their emissions were 

added back into the Base G 2018 inventory. 

 BASF Corporation (37-021-724) in Buncombe County is currently operating but has plans to shut 

down in 2007. This facility emitted 461 tons of SO2 and 266 tons of NOx in 2002. 

SC South Carolina provided a list of facilities that were identified as closing down on or after Jan. 1, 

2003. The emissions for these facilities were set to zero in the 2009 and 2018 projection inventories. 

Emissions from these plants in 2002 were: 6,195 tons of SO2, 2,994 tons of NOx, and 2,836 tons of 

VOC. Most of the emissions were from one facility – Celanese Acetate (45-091-2440-0010) in York 

County. 

TN Davidson County (Nashville) indicated that significant source shutdowns have occurred since data 

were submitted for the 2002 CERR. Source number 47-037-00002 (Dupont) shut down a portion of 

their facility, which was permanently taken out of service. Source 47-037-00050 (Nashville Thermal 

Transfer Corp.) shut down their municipal waste combustors and replaced them with natural gas fired 

boilers with propane stand by. 

 Weyerhaeuser (AKA Willamette) Power Boiler 7 (47-163-0022, EU ID = 017) is being shut down. 

This emission unit emitted 4,297 tons of SO2 and 1,443 tons of NOx in 2002. 

 Liberty Fibers (47-063-0197) in Hamblen County has recently shut down. This facility emitted 5,377 

tons of SO2; 2,057 tons of NOx; and 9,059 tons of VOC in 2002. 

VA Rock-Tenn (51-680-00097) received a permit dated 9/13/2003 which required the shutdown of units 1 

and 2 by 2/27/2004. This permit was part of a netting exercise that allowed the installation of a new 

NG/DO boiler. These two units emitted 507 tons of SO2 and 276 tons of NOx in 2002. 

WV None specified. 
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2.1.2.3 Control Programs applied to non-EGU sources 

We used the same control programs for both the 2009 and 2018 non-EGU point inventory. Two 

control scenarios were developed: on-the-books (OTB) controls and on-the-way (OTW) controls. 

The OTB control scenario accounts for post-2002 emission reductions from promulgated federal, 

State, local, and site-specific control programs. The OTW control scenario accounts for proposed 

(but not final) control programs that are reasonably anticipated to result in post-2002 emission 

reductions. The methodologies used to account for the emission reductions associated with these 

emission control programs are discussed in the following sections. 

Table 2.1-12 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 (see Section 2.1.2.3.2) 

 NOx RACT in 1-hr NAA SIPs 

 NOx SIP Call (Phase I- except where States have adopted II already e.g. NC) 

 Petroleum Refinery Initiative (October 1, 2003 notice; MS & WV) 

 RFP 3 percent Plans where in place for one hour plans 

 VOC 2-, 4-, 7-, and 10-year maximum achievable control technology (MACT0 

Standards 

 Combustion Turbine MACT 

On-the-Way 

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

2.1.2.3.1 OTB - NOx SIP Call (Phase I) 

Phase I of the NOx SIP call applies to certain large non-EGUs, including large industrial boilers 

and turbines, and cement kilns. States in the VISTAS region affected by the NOx SIP call have 

developed rules for the control of NOx emissions that have been approved by EPA. We reviewed 

the available State rules and guidance documents to determine the affected sources and ozone 

season allowances. We also obtained and reviewed information in the EPA’s CAMD NOx

Allowance Tracking System – Allowances Held Report. Since these controls are to be in effect 

by the year 2007, we capped the emissions for NOx SIP call affected sources at 2007 levels and 

carried forward the capped levels for the 2009/2018 future year inventories. Since the NOx SIP 

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

of 12 divided by 5. 

2.1.2.3.2 OTB - Industrial Boiler/Process Heater MACT 

EPA anticipates reductions in PM and SO2 as a result of the Industrial Boiler/Process Heater 

MACT standard. The methods used to account for these reductions are the same as those used 

for the CAIR analysis. Reductions were included for existing units firing solid fuel (coal, wood, 

waste, biomass) which had a design capacity greater than 10 mmBtu/hr. EPA prepared a list of 

SCCs for solid fuel industrial and commercial/ institutional boilers and process heaters. We 

identified boilers greater than 10 mmBtu/hr using either the boiler capacity from the VISTAS 

2002 inventory, or if the boiler capacity was missing, a default capacity based on a methodology 

developed by EPA for assigning default capacities based on SCC. The applied MACT control 

efficiencies were 4 percent for SO2 and 40 for percent for PM10 and PM2.5 to account for the cobenefit from installation of acid gas scrubbers and other control equipment to reduce HAPs. On 

June 8, 2007, the U.S. Court of Appeals for the District of Columbia Circuit vacated and 

remanded the NESHAP for Industrial, Commercial and Institutional Boilers and Process Heaters. 

VISTAS States decided to leave the emission reductions in place since they envision using a 

112(j) strategy (e.g., the “MACT hammer”) to obtain similar levels of control) 

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

Maximum achievable control technology (MACT) requirements were also applied, as 

documented in the report entitled Control Packet Development and Data Sources, dated July 14, 

2004. The point source MACTs and associated emission reductions were designed from Federal 

Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD) staff. We 

did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, 

assuming that the effects of these controls are already accounted for in the 2002 inventories 

supplied by the States. Emission reductions were applied only for MACT standards with an 

initial compliance date of 2002 or greater. 

2.1.2.3.4 OTB Combustion Turbine MACT 

The projection inventories do not include the NOx co-benefit effects of the MACT regulations 

for Gas Turbines or stationary Reciprocating Internal Combustion Engines, which EPA estimates 

to be small compared to the overall inventory. 

2.1.2.3.5 OTB - Petroleum Refinery Initiative (MS and WV) 

Three refineries in the VISTAS region are affected by two October 2003 Clean Air Act 

settlements under the EPA Petroleum Refinery Initiative. The refineries are: (1) the Chevron 
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refinery in Pascagoula, MS; (2) the Ergon refinery in Vicksburg, MS; and (3) the Ergon refinery 

in Newell, WV. 

The first consent decree pertained to Chevron refineries in Richmond and El Segundo, CA; 

Pascagoula, MS; Salt Lake City, UT; and Kapolei, HI. Actions required under the Consent 

Decree will reduce annual emissions of NOx by 3,300 tons and SO2 by 6,300 tons. The consent 

decree requires a program to reduce NOx emissions from refinery heaters and boilers through the 

installation of NOx controls that meet at least an SNCR level of control. The refineries are to 

eliminate fuel oil burning in any combustion unit. The consent decree also requires reductions of 

NOx and SO2 from the fluid catalytic cracking unit and control of acid gas flaring incidents. The 

consent decree does not provide sufficient information to calculate emission reductions for the 

FCCU or flaring at the Pascagoula refinery. Therefore, we calculated a general percent reduction 

for NOx and SO2 by dividing the expected emission reductions at the five Chevron refineries by 

the total emissions from these five refineries (as reported in the 1999 NEI). This resulted in 

applying percent reductions of 45 percent for SO2 and 28 percent for NOx to FCCU and flaring 

emissions at the Chevron Pascagoula refinery. 

The second consent decree pertained to the Ergon-West Virginia refinery in Newell, WV; and 

the Ergon Refining facility in Vicksburg, MS. The consent decree requires the two facilities to 

implement a 6-year program to reduce NOx emission from all heaters and boilers greater than 40 

mmBtu/hr, and to eliminate fuel oil burning in any combustion unit (except during periods of 

natural gas curtailment). Specifically, ultra low NOx burners are required on Boilers A and B at 

Newell, a low NOx-equivalent level of control for heater H-101 at Newell and heaters H-1 and 

H-3 at Vicksburg, and an ultra low NOx burner level of control for heater H-451 at Vicksburg. 

2.1.2.3.6 OTW - NOx SIP Call (Phase II) 

The final Phase II NOx SIP call rule was finalized on April 21, 2004. States had until April 21, 

2005, to submit SIPs meeting the Phase II NOx budget requirements. The Phase II rule applies to 

large IC engines, which are primarily used in pipeline transmission service at compressor 

stations. We identified affected units using the same methodology as was used by EPA in the 

proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than 1 ton per 

day during 2002). The final rule reflects a control level of 82 percent for natural gas-fired IC 

engines and 90 percent for diesel or dual fuel categories. As shown later in Table 2.1-12, several 

S/L agencies provided move specific information on the anticipated controls at the compressor 

stations. This information was used in the Base G inventory instead of the default approach used 

by EPA in the proposed Phase II rule. 
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2.1.2.3.7 Clean Air Interstate Rule 

CAIR does not require or assume additional emission reductions from non-EGU boilers and 

turbines. 

2.1.2.4 Quality Assurance steps 

Final QA checks were run on the revised projection inventory data set to ensure that all 

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

S/L inventories and that there were no remaining QA issues that could be addressed during the 

duration of the project. After exporting the inventory to ASCII text files in NIF 3.0, the EPA QA 

program was run on the ASCII files and the QA output was reviewed to verify that all QA issues 

that could be addressed were resolved 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, and to ensure that a full and complete 

inventory was developed for VISTAS. Quality assurance was an important component to the 

inventory development process and MACTEC performed the following QA steps on the point 

source component of the VISTAS revised 2002 base year inventory: 

Facility level emission summaries were prepared and evaluated to ensure that emissions 

were consistent and reasonable. The summaries included base year 2002 emissions, 

2009/2018 projected emissions accounting only for growth, 2009/2018 projected 

emissions accounting for both growth and emission reductions from OTB and OTW 

controls. 

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. 

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. 

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 2.1-13 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. 
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Table 2.1-13 Summary of Updates and Corrections Incorporated into the 

Base G 2009/2018 Non-EGU 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). 

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

into the ranges typically termed "acceptable" for AQ modeling. 

FL Corrected 2009/2018 emission values for the Miami Dade RRF facility (Site ID: 12-086-0250348) 

based on revised 2002 emissions and application of growth control factors for 2009/2018. 

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

SB9 and was deleted. This removes about 6,000 tons of SO2 from the 2009/2018 inventories. 

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

coordinated in the ER file. 

 There are several sources that have updated their emissions from their BART eligible units. most of 

these changes were for fairly small (<50 tpy) sources. 

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

1. Corrected emissions at Hooker Furniture (Site ID: 37-081-3708100910), release point G-29, to use 

the corrected values in 2002 and carry those same numbers through to 2009 and 2018 since NCDENR 

assumes zero growth for furniture industry. 

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

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

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

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

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

with only two decimal places were not corrected. 

4. Corrected 2018 VOC emissions for International Paper (3709700045) Emission Unit ID, G-12, to 

reflect changes to the 2002 inventory. 

 There are three Transcontinental Natural Gas Pipeline facilities in NC that are subject to the NOx SIP 

call. NCDENR took 2004 emissions and grew them to 2009 & 2018 and capped those units that are 

subject to the NOx SIP Call Rule. These facility IDs are 37-057-3705700300, 37-097-3709700225, 

and 37-157-3715700131. 

 NCDENR applied NOx RACT to a two facilities located in the Charlotte nonattainment area. 

NCDENR provided 2009 & 2018 emissions for Philip Morris USA (37-025-3702500048) and 

Norandal USA (37-159-3715900057). 

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

matter emissions using the PM-FIL, PM10-FIL, and PM2.5 -FIL pollutant codes. In August 2005, SC 

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

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

performed a subsequent PM augmentation in April 2006 using the revised pollutant codes. These 

changes were reflected in the Base G 2009/2018 emission inventory. 

 Specified that the Bowater Inc. facility (45-091-2440-0005) in York County conducted an expansion 

in 2003/2004 and plans a future expansion. SC provided updated emissions for 2009 and 2018 for this 

facility. 
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Table 2.1-13. Continued. 

State Nature of Update/Correction 

TN Updated 2009/2018 emissions for Eastman Chemical (47-163-0003) based on final (Feb. 2005) 

BART rule. 

 Updated 2009/2018 emission inventory for the Bowater facility (47-107-0012) based on the facility’s 

updated 2002 emission inventory update. 

 Replaced 2009/2018 data from Hamilton County, Tennessee, using data from Hamilton County’s 

CERR submittal as contained in EPA’s 2002 NEI (in Base F, the inventory for Hamilton County was 

based on the draft VISTAS 2002 inventory, which in turn was based on the 1999 NEI); applied 

growth and control factors to revised 2002 inventory to generate emission projections for 2009/2018. 

 Updated 2009/2018 emissions for PCS Nitrogen Fertilizer LP (Site ID: 47-157-00146) based on the 

facility’s updated 2002 emission inventory update. 

 The 2002 NEI correctly reports the actual emissions for CEMEX (47-093-0008) after the NOx SIP 

call. There is no reason to suspect that that rate would change in 2008, 2009, or 2018. Emissions for 

2009/2018 were set equal to 2002 emissions. 

 In the Base F 2009/2018 inventories, NOx controls were applied for two units at Columbia Gulf 

Transmission (47-111-0004). There are no plans for controls at these units, EO3 and EO4. The 

assumed control efficiency of 82 percent was backed out in the 2009/2018 inventories. 

VA VADEQ provided 2009/2018 NOx emission estimates for NOx Phase II gas transmission sources at 

three Transco facilities (51-011-00011, 51-137-00027, 51-143-00120) which were used to replace the 

default NOx Phase II control assumptions for these facilities. 

 VADEQ provided updated 2009/2018 NOx and SO2 emissions based on new controls required by a 

November 2005 permit modification and netting exercise. The entire power plant facility is limited to 

213 tons of NOx and 107 tons of SO2 per year. The permit also allowed the installation of 3 new 

boilers, also under the 213 tons of NOx /year cap. 

WV Updated 2009/2018 emissions for Steel of West Virginia (Site ID: 54-011-0009) based on the 

facility’s updated 2002 emission inventory update. 

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

 Base F emissions were much too high for Weirton Steel (54-021-0029). WV believes that the source 

is very unlikely to emit the NOx SIP Call budgeted amounts in 2009 or 2018. WV provided revised 

emission estimates based on EGAS for 2009/2018. 

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

parameters that do not appear to fall into the ranges typically termed "acceptable" for AQ modeling. 
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2.1.2.6 Additional B&F Updates and Corrections 

Table 2.1-14 summarizes the updates and corrections to the Base G non-EGU inventory that 

were requested by S/L agencies and incorporated into the B&F 2009/2018 non-EGU inventories. 

The changes were primarily related to better information on anticipated BART controls for 

specific facilities and emission units. 

Table 2.1-14 Summary of Updates and Corrections Incorporated into the 

B&F 2009/2018 Non-EGU Inventories. 

State Nature of Update/Correction 

AL For 2018, incorporated emission changes due to BART controls at Exxon Mobil (Site ID: 01-053-

0007), International Paper (Site ID: 01-079-0001), and Solutia (Site ID: 01-103-0010). International 

Paper (Site ID: 01-079-0001) Unit 004 to be shutdown in the 2018 inventory. 

FL For both 2009 and 2018, incorporated emission changes due to BART controls at Georgia Pacific 

(Site ID: 12-107-1070005) Unit 15. 

MS For 2018 only, changed SO2 emission estimate for Pursue Energy (Site ID: 28-121-00036) based on 

the facility’s estimates of the gas reserve at the site. 

 For 2018 only, changed emission estimates for all pollutants at several emission units at the Chevron 

Pascagoula Refinery (Site ID: 28-059-00058) to reflect BART source reductions. 

SC For both 2009 and 2018, identified 15 facilities that have permanently closed. Emissions from these 

facilities set to zero for all pollutants. 

TN For both 2009 and 2018, identified seven facilities that have permanently closed. Emissions from 

these facilities were set to zero for all pollutants. 

 For both 2009 and 2018, identified three emission units that have permanently closed. Emissions 

from these units were set to zero for all pollutants. 47-009-0130-002 (APAC – TN, Inc.-Harrison 

Construction – Asphalt plant), 47-009-0130-003 (APAC – TN, Inc.-Harrison Construction – Asphalt 

crusher), and 47-139-0004-001 (Intertrade - Number 6 acid plant) 

 The following individual source will be shut down in 2010: 47-001-0020-002 (DOE, Y-12 – Boilers 

1-4). For the 2018 inventory only, emissions from this unit were set to zero for all pollutants. 

 A portion of 47-163-0003-020101 (Eastman, B-83-1 Stoker Boilers). This source previously 

consisted of 14 boilers (Boilers 11-24). Boilers 11-17 have been removed from service. Emissions for 

both 2009 and 2018 were reduced by 26.64%, based on the portion of the heat input capacity that is 

being removed from service. 

 SO2 emissions in 2018 from 47-163-0003-021520 (Eastman, B-253-1 Tangential PC Boilers) were 

reduced by 90% to reflect anticipated BART controls. 

 Reduced SO2 emissions at 47-157-00475 (Lucite International) in Shelby County as a result of a 

consent decree with U.S. EPA. 

VA Changed SO2 emissions in 2009 and 2018 for thirteen facilities to reflect updated information from 

VADEQ regarding projected SO2 controls. 

WV Weirton Steel (54-029-00001) and Wheeling Pittsburgh Steel (54-009-00002) have undergone 

significant, permanent process changes since 2002. WV DEP staff have consulted with facility staff 

and determined that calendar year 2004 emissions represent a better basis for future year emissions 

estimates. Therefore, WVDEP compiled emissions data from the 2004 inventory for these sources 

and applied the most current VISTAS growth factors to estimate emissions in 2009 and 2018. 
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2.1.2.7 Conversion of MRPO BaseM 2009 non-EGU Data to SMOKE Input Format 

To support ASIP PM2.5 CAMx modeling of the future year 2009, Alpine Geophysics obtained 

and processed an emission inventory for the 5 MRPO states (Illinois, Indiana, Michigan, 

Wisconsin, and Ohio). Appendix x details the technical steps that were made as part of the 

conversion of the MRPO BaseM non-EGU files into IDA format for ASIP PM-2.5 CAMx 

modeling of the future year 2009. 

2.1.2.8 Summary of the 2009/2018 non-EGU Point Source Inventories 

Tables 2.1-15 through 2.1-21 summarize the revised 2009/2018 non-EGU point source 

inventories. The “growth only” column does not include the shutdowns (section 2.1.2.2) or 

control factors (section 2.1.2.3), only the growth factors described in section 2.1.2.1. 

Table 2.1-15 Non-EGU Point Source SO2 Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F Base G B&F Base F Base G B&F 

AL 96,481 100,744 101,246 101,246 112,703 113,224 103,303 

FL 65,090 68,549 65,511 62,651 79,015 75,047 71,810 

GA 53,778 61,535 53,987 53,987 68,409 59,349 59,349 

KY 34,029 35,470 36,418 36,418 38,806 40,682 40,682 

MS 35,960 27,488 25,564 25,564 40,195 26,678 25,674 

NC 44,123 48,751 42,536 42,536 50,415 46,314 46,314 

SC 53,518 55,975 48,324 47,193 56,968 53,577 52,410 

TN 79,604 89,149 70,678 64,964 96,606 77,247 56,682 

VA 63,903 63,075 62,560 58,039 69,776 68,909 57,790 

WV 54,070 54,698 55,973 55,598 60,137 62,193 61,702 

580,556 605,434 562,797 548,196 673,030 623,220 575,716 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 
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Table 2.1-16 Non-EGU Point Source NOx Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F Base G B&F Base F Base G B&F 

AL 83,310 69,676 69,409 69,409 79,101 78,318 77,960 

FL 45,156 44,859 46,020 47,125 50,635 51,902 52,959 

GA 49,251 51,556 50,353 50,353 57,323 55,824 55,824 

KY 38,392 36,526 37,758 37,758 40,363 41,034 41,034 

MS 61,526 55,877 56,397 56,398 62,132 61,533 61,252 

NC 44,929 44,877 34,767 34,768 47,200 37,801 37,802 

SC 42,153 42,501 40,019 39,368 44,480 44,021 43,331 

TN 64,344 63,431 57,883 57,514 70,313 63,453 62,519 

VA 60,415 51,335 51,046 51,001 56,876 55,945 55,734 

WV 46,612 40,433 38,031 38,023 44,902 43,359 43,280 

536,088 501,071 481,683 481,715 553,325 533,190 531,695 

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

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

2002 2009 2018 

State Base G Base F Base G B&F Base F Base G B&F 

AL 47,037 46,660 46,644 46,644 54,268 54,291 54,290 

FL 38,471 36,675 36,880 36,882 42,787 42,811 42,813 

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

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

MS 43,204 37,921 37,747 37,747 45,769 45,338 45,335 

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

SC 38,458 38,273 35,665 34,403 44,545 43,656 41,987 

TN 84,328 89,380 74,089 73,498 111,608 93,266 92,456 

VA 43,152 43,620 43,726 43,725 53,065 53,186 53,186 

WV 14,595 14,012 13,810 13,043 16,632 16,565 15,582 

 448,970 458,735 432,387 429,768 540,532 516,131 512,667 

Note: Emission summaries above include all SCCs except 1-01-xxx-xx and 2-01-xxx-xx. 
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Table 2.1-18 Non-EGU Point Source CO Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F Base G B&F Base F Base G B&F 

AL 174,271 176,899 180,369 180,369 194,280 201,794 201,663 

FL 81,933 83,937 87,037 87,661 96,642 96,819 97,438 

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

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

MS 54,568 58,023 57,748 57,749 67,764 66,858 65,884 

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

SC 56,315 62,144 60,473 59,934 71,318 68,988 68,415 

TN 115,264 123,844 119,665 119,216 146,407 140,942 140,556 

VA 63,796 67,046 68,346 68,326 74,364 76,998 76,846 

WV 89,879 100,248 100,045 93,839 119,318 119,332 111,302 

927,388 995,185 996,878 990,289 1,138,911 1,141,269 1,131,642 

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

Table 2.1-19 Non-EGU Point Source PM10-PRI Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F Base G B&F Base F Base G B&F 

AL 25,240 25,450 25,421 25,421 29,973 29,924 29,889 

FL 35,857 39,363 39,872 39,947 46,573 46,456 46,492 

GA 21,610 23,509 23,103 23,103 27,781 27,273 27,273 

KY 16,626 17,164 17,174 17,174 20,142 20,153 20,153 

MS 19,472 19,200 19,245 19,244 22,952 22,859 22,837 

NC 13,838 14,738 13,910 13,910 15,816 15,737 15,737 

SC 14,142 17,631 13,370 12,959 20,197 15,139 14,674 

TN 35,174 37,040 34,833 34,581 45,168 42,280 41,999 

VA 13,252 13,043 13,048 13,046 15,150 15,112 15,111 

WV 17,503 17,723 17,090 11,882 21,699 21,735 14,202 

 212,714 224,861 217,066 211,267 265,451 256,668 248,367 

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

Table 2.1-20 Non-EGU Point Source PM25-PRI Emission Comparison for 2002/2009/2018. 
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2002 2009 2018 

State Base G Base F Base G B&F Base F Base G B&F 

AL 19,178 19,256 19,230 19,230 22,628 22,598 22,584 

FL 30,504 33,387 33,946 34,019 39,436 39,430 39,486 

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

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

MS 9,906 9,144 9,199 9,199 10,768 10,739 10,719 

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

SC 10,245 13,101 9,390 9,048 14,947 11,086 10,699 

TN 27,807 29,302 27,577 27,367 35,750 33,532 33,293 

VA 10,165 9,980 9,988 9,988 11,604 11,594 11,605 

WV 13,313 13,364 12,769 7,638 16,474 16,516 9,124 

160,452 169,767 163,225 157,615 200,150 193,475 185,490 

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

Table 2.1-21 Non-EGU Point Source NH3 Emission Comparison for 2002/2009/2018. 

2002 2009 2018 

State Base G Base F Base G B&F Base F Base G B&F 

AL 1,883 2,132 2,132 2,132 2,464 2,464 2,464 

FL 1,423 1,544 1,544 1,544 1,829 1,829 1,829 

GA 3,613 3,963 3,963 3,963 4,799 4,797 4,797 

KY 674 733 760 760 839 901 901 

MS 1,169 667 668 668 761 764 764 

NC 1,180 1,288 1,285 1,285 1,422 1,466 1,466 

SC 1,411 1,578 1,578 1,578 1,779 1,779 1,779 

TN 1,613 1,861 1,841 1,840 2,240 2,214 2,213 

VA 3,104 3,050 3,049 3,045 3,613 3,604 3,604 

WV 332 341 341 314 416 413 378 

16,402 17,157 17,161 17,129 20,162 20,231 20,195 

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

This section describes the methodology used to develop the 2009 and 2018 projection Base F 

and Base G projection inventories. This section describes two approaches to these projections. 

Separate methods for projecting emissions were used for non-agricultural (stationary area) and 

agricultural area sources (predominantly NH3 emissions). The two methods used for these 

sectors are described in the sections that follow. 

2.2.1 Stationary area sources 

The general approach used to calculate Base F projected emissions for stationary area sources 

was as follows: 

1. Use the VISTAS Base F 2002 base year inventory as the starting point for projections. 

2. MACTEC then worked with the VISTAS States (via the Stationary Area Source SIWG) 

to obtain any State specific growth factors and/or future controls from the States to use in 

developing the projections. 

3. MACTEC then back calculated uncontrolled emissions from the Base F 2002 base year 

inventory based on existing controls reported in the 2002 Base F base year inventory. 

4. Controls (including control efficiency, rule effectiveness and rule penetration) provided 

by the States or originally developed for use in estimating projected emissions for U.S. 

EPA’s Heavy Duty Diesel (HDD) rulemaking emission projections and used in the Clean 

Air Interstate Rule (CAIR) projections were then used to calculate controlled emissions. 

State submitted controls had precedence over the U.S. EPA developed controls. 

5. Growth factors supplied from the States or the U.S. EPA’s CAIR emission projections 

were then applied to project the controlled emissions to the appropriate year. In some 

cases EGAS Version 5 growth factors were used if no growth factor was available from 

either the States or the CAIR growth factor files. The use of EGAS Version 5 growth 

factors was on a case-by-case basis wherever State-supplied or CAIR factors were not 

available for SCCs found in the 2002 Base F inventory. Use of the EGAS factors was 

necessitated due to the CERR submittals used in constructing the Base F 2002 inventory. 

Use of the CERR data resulted in SCCs that were not found in the CAIR inventory and if 

no State-supplied growth factor was provided required the use of an EGAS growth factor. 

6. MACTEC then provided the final draft Base F projection inventory for review and 

comment by the VISTAS States. 

For Base F stationary area sources, no State-supplied growth or control factors were provided. 

Thus for all of the sources in this sector of the inventory, growth and controls for Base F were 
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applied based on controls initially identified for the CAIR and growth factors identified for the 

CAIR projections. 

For the Base G projections, the Base G 2002 base year inventory (see section 1.2.3) was used as 

a starting point. States provided some updated future controls but growth factors used were 

identical to those used for Base F. The revised controls for Base G were largely for new sources 

added as part of the 2002 Base F comments. The calculation of Base G projections was identical 

to the six steps outlined above with the exception of revisions made to prescribed fire for 2009 

and 2018 and for the State of North Carolina. North Carolina provided 2009 and 2018 updated 

emission files used to update the emissions for each year for several source categories. However 

not all sources in the inventory were included in these NC updates. As a consequence, the final 

Base G 2009 and 2018 inventory for NC included emissions updated using the NC supplied files 

and emissions developed using growth and control factors as outlined above. 

In a few cases, additional growth factors had to be added for source categories that had not 

initially been included in the Base F inventory. These growth factors were obtained from EGAS 

5.0. Finally updates to growth factors from EGAS 5.0 were made for fuel fired emission sources. 

The updated growth factors reflected the most recent data from the Department of Energy’s 

Annual Energy Outlook (AEO). These data were used to reflect changes in energy efficiency 

resulting from new or updated fuel firing technologies. 

2.2.1.1 Stationary area source controls 

The controls obtained by MACTEC for the HDD rulemaking were controls for the years 2007, 

2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, control values for 

intermediate years were prepared using a straight line interpolation of control level between 2007 

and 2020. The equation used to calculate the control level was as follows: 

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

Where: 

CE = Control Efficiency for either 2009 or 2018 

2020 CE = HDD Control Efficiency value for 2020 

2007 CE = HDD Control Efficiency value for 2007 

13 = Number of years between 2020 and 2007 

YRS = Number of years beyond 2007 to VISTAS Projection year 
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For 2009 the value of YRS would be two (2) and for 2018 the value would be eleven (11). 

Control efficiency values were determined for VOC, CO and PM. Rule penetration values for 

each year in the HDD controls tables obtained by MACTEC were always 100 percent so those 

values were maintained for the VISTAS projections. 

Prior to performing the linear interpolation of the controls, MACTEC evaluated controls from 

the CAIR projections (NOTE: Initially the controls came from the IAQTR projections, however 

the controls used in CAIR were virtually identical to those in IAQTR). Those controls appeared 

to be identical to those used for the HDD rulemaking. In addition, MACTEC received some 

additional information on some controls for area source solvents (email from Jim Wilson, E.H. 

Pechan and Associates, Inc. to Gregory Stella, VISTAS Emission Inventory Technical Advisor, 

3/5/04) that were used to check against the controls in the HDD rulemaking files. Where those 

controls proved to be more stringent than the HDD values, MACTEC updated the control file 

with those values (which were then used in the interpolation to develop 2009 and 2018 values). 

Finally, for VOC the HDD controls were initially provided at the State-county-SCC level. 

However, upon direction from the VISTAS Emission Inventory Technical advisor, the VOC 

controls were consolidated at the SCC level and applied across all counties within the VISTAS 

region (email from Gregory Stella, Alpine Geophysics, 3/3/2004) to ensure that no controls were 

missed due to changes in county FIPS codes and/or SCC designations between the time the HDD 

controls were developed and 2002. 

The equation below indicates how VOC emissions were projected for stationary area sources. 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ ⎟

⎠

⎞ ⎜

⎝

⎛

⎟

⎠

⎞ ⎜

⎝

⎛

⎟

⎠

⎞ ⎜

⎝

⎛ = − 100

_

100

_

100

_ 1 2018 2018 2018

2018 2002

VOC CE VOC RE VOC RP VOC VOC x

 Where: 

 VOC2018 = VOC emissions for 2018 

 VOC2002 = Uncontrolled VOC emissions for 2002 

 VOC_CE2018 = Control Efficiency for VOC (in this example for 2018) 

 VOC_RE2018 = Rule Effectiveness for VOC (in this example for 2018) 

 VOC_RP2018 = Rule Penetration for VOC (in this example for 2018) 

A similar equation could be constructed for either PM or CO. It should be noted that the control 

efficiencies calculated based on the HDD rulemaking were only applied if they were greater than 

any existing 2002 base year controls. No controls were found for SO2 or NOx area sources. 
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In the pre-Base F 2018 emission estimates, an energy efficiency factor was applied to energy 

related stationary area sources. The energy efficiency factor was applied along with the growth 

factor to account for both growth and changes in energy efficiency. That factor was not applied 

to the Base F projections since information supplied by U.S. EPA related to the CAIR growth 

factors indicated that growth values for those categories were derived from U.S. Department of 

Energy (DOE) and were felt to account for changes in growth and projected energy efficiency. 

For the Base G inventory, these energy efficiency factors were re-instituted and used in 

conjunction with EGAS 5.0 growth factors in a manner identical to that used for the pre-Base F 

inventories. The energy efficiency factors were derived from U.S. DOE’s Annual Energy 

Outlook report. 

One significant difference between the Base F and Base G control factors was for counties and 

independent cities in northern Virginia. Several counties and independent cities in northern 

Virginia are subject to Ozone Transport Commission rules. For these counties and independent 

cities, controls for portable fuel containers, mobile equipment repair/refinishing, consumer 

products, solvent metal cleaning, and the architectural and industrial maintenance rules 

were added. The counties/independent cities (FIPS code) included in the changes for Base G 

were: Alexandria City (51510), Arlington (51013), Fairfax City (51600), Fairfax (51059), Falls 

Church City (51610), Fredericksburg City (51630), Loudoun (51107), Manassas City (51683), 

Manassas Park City (51685), Prince William County (51153), Spotsylvania (51177), and 

Stafford (51179). Not all OTC rules applied to all counties/cities. 

2.2.1.2 Stationary area source growth 

As indicated above, growth factors for the Base F and Base G 2009 and 2018 inventories were 

obtained from the U.S. EPA and are linear interpolations of the growth factors used for the Clean 

Air Interstate Rule (CAIR) projections. The growth factors for the CAIR obtained by MACTEC 

were developed using a base year of 2001 and provided growth factors for 2010 and 2015. 

MACTEC used the TREND function in Microsoft ExcelTM to calculate 2002, 2009 and 2018 

values from the 2001, 2010 and 2015 values. The TREND function provides a linear 

interpolation of intermediate values from a known series of data points (in this case the 2001, 

2010 and 2015 values) based on the equation for a straight line. These values were calculated at 

the State and SCC level with the exception of paved road emissions (SCC = 2294000000). The 

growth factors for paved roads were available in the CAIR data set at the State, county and SCC 

level so they were applied at that level. 

Prior to utilizing the growth factors from the CAIR projections, MACTEC confirmed that all 

SCCs found in the VISTAS 2002 base year inventory were in the CAIR file (for Base F the 

starting point was the version 3.1 2002 base year inventory, for Base G the starting point was the 

Base F 2002 base year inventory). Some SCCs were not found in the CAIR file. For those SCCs, 
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the growth factors used were derived in one of five ways. First where possible, they were taken 

from a beta version of EGAS 5.0. In other cases, the growth factor was set to one (i.e., no 

growth). In other cases, a similar SCC that had a CAIR growth factor was used. In a few cases a 

growth factor based on an average CAIR growth at the 6 digit SCC level was calculated. Finally 

a number of records used population as the growth surrogate. For the Base G inventory, CAIR 

growth factors for fuel fired area sources were replaced with EGAS 5.0 growth factors (used in 

conjunction with AEO fuel efficiency factors). A comment field in the growth factor file was 

used to mark those records that were not taken directly from the CAIR projection growth factors. 

2.2.1.3 Differences between 2009/2018 

Methodologically, there was no difference in the way that 2009 and 2018 emissions were 

calculated for stationary area sources. The individual control and growth factors were different 

(due to the linear interpolation used to calculate the values) but the calculation methods were 

identical. This applies to both Base F and Base G. 

The only exception to this is for the State of North Carolina for Base G. North Carolina provided 

an emissions update file used to override calculated projections for a number of area source 

categories. The values in these files (provided for both 2009 and 2018) were used to overwrite 

the calculated projected emissions in the final NIF file. 

2.2.2 Agricultural area sources 

The general approach used to calculate projected emissions for agricultural area sources 

(predominantly NH3 emission sources) was as follows: 

1. MACTEC used the version 3.1 2002 base year inventory data (which was based on 

the CMU ammonia model version 3.6). 

2. MACTEC worked with the VISTAS States (via the Agricultural Sources SIWG) to 

obtain any State specific growth and/or future controls from the States for agricultural 

sources. 

3. Since the base year emissions were uncontrolled, and no future controls for these 

sources were identified, MACTEC projected the agricultural emissions using Statespecific growth if available, otherwise the U.S. EPA’s Interstate Air Quality 

Transport Rule (IAQTR)/Ammonia inventory was used to develop the growth factors 

used to project the revised 2002 base year inventory to 2009 or 2018. Since the 

IAQTR inventory was only used to construct growth factors rather than using the 

emissions directly, no updated growth factors were prepared from the CAIR 

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

VISTAS States. 

No change in the agricultural area source emission projections were made between Base F and 

Base G other than the removal of wild animal and human perspiration as a result of their removal 

from the 2002 base year file for Base G. 

2.2.2.1 Control assumptions for agricultural area sources 

No controls were identified either by the individual VISTAS States or in the information 

provided in the EPA’s IAQTR or CAIR Ammonia inventory documents. Thus all projected 

emissions for agricultural area sources represent simple growth with no controls. 

2.2.2.2 Growth assumptions for agricultural area sources 

Growth for several agricultural area source livestock categories was developed using the actual 

emission estimates developed by the EPA as part of the NEI. That work included projections for 

the years 2002, 2010, 2015, 2020, and 2030. The actual emissions themselves were not used 

other than to develop growth factors since the 2002 NEI upon which the growth projections were 

based was prepared prior to the release of the 2002 Census of Agriculture data which was 

included in the CMU model (version 3.6) used to develop the Base F 2002 VISTAS base year 

inventory. Thus VISTAS Agricultural Sources SIWG decided to use the NEI ammonia inventory 

projected emissions to develop the 2009 and revised 2018 growth factors used to project 

emission for VISTAS. Details on the NEI inventory and projections can be found at: 

http://www.epa.gov/ttn/chief/ap42/ch09/related/nh3inventorydraft_jan2004.pdf. The actual data 

files for the projected emissions can be found at: 

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

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

steps were as follows: 

1. NEI projected emissions were only available for the years 2002, 2010, 2015, 2020, 

and 2030, thus the first task was to calculate intermediate year emissions for 2009 and 

2018. These values were calculated based on linear interpolation of the existing data. 

2. Once the intermediate emissions were calculated, MACTEC developed emission 

ratios to provide growth factors for 2009 and 2018. Ratios of emissions were 

established relative to the 2002 NEI emissions. 

3. Once the growth factors were established, MACTEC then evaluated whether or not 

all agricultural SCCs within the revised 2002 base year inventory had corresponding 
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growth factors. MACTEC established that not all SCCs within the base year 

inventory had growth factors. These SCCs fell into one of two categories: 

b. 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. 

c. 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. 

1. 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. 
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There were a few exceptions to the methods used for projecting agricultural sources for the 

VISTAS projections. These exceptions were: 

1. All swine emissions for North Carolina were maintained at 2002 levels for each 

projection year to capture a moratorium on swine production in that State. 

2. Ammonia growth factors for a few categories (mainly feedlots) were assigned to be 

the same as growth factors for PM emissions from the NEI projections. This 

assignment was made because the CMU model showed emissions from these 

categories but the NEI projections did not show ammonia emissions but did show PM 

emissions. 

3. No growth factors were found for horse and pony emissions. These emissions were 

held constant at 2002 levels. 

There was no change in this method between Base F and Base G. Thus Base F and Base G 

agricultural emissions are the same in each inventory. Future efforts on the agricultural emissions 

category should look at any changes made to the CMU model to reflect the model farm approach 

used by EPA in their inventory plus any updated growth factors that may be more recent than the 

EPA inventory used to develop growth estimates for Base F/G. 

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

(based on actual emissions). 

Actual Area 2002 - Base G 

State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC 

AL 83,958 58,318 23,444 393,588 56,654 52,253 182,674 

FL 71,079 37,446 28,872 443,346 58,878 40,491 404,302 

GA 108,083 80,913 36,142 695,414 103,794 57,559 299,679 

KY 66,752 51,135 39,507 233,559 45,453 41,805 95,375 

MS 37,905 58,721 4,200 343,377 50,401 771 131,808 

NC 345,315 161,860 36,550 280,379 64,052 5,412 237,926 

SC 113,714 28,166 19,332 260,858 40,291 12,900 161,000 

TN 89,828 34,393 17,844 212,554 42,566 29,917 153,307 

VA 155,873 43,905 51,418 237,577 43,989 105,890 174,116 

WV 39,546 9,963 12,687 115,346 21,049 11,667 60,443 

Base F 

AL 83,958 59,486 23,444 393,093 73,352 47,074 196,538 

FL 105,849 44,902 29,477 446,821 81,341 40,537 439,019 

GA 107,889 84,230 36,105 695,320 133,542 57,555 309,411 

KY 66,752 51,097 39,507 233,559 52,765 41,805 100,174 

MS 37,905 59,262 4,200 343,377 63,135 771 135,106 

NC 373,585 164,467 48,730 303,492 69,663 7,096 346,060 

SC 113,714 29,447 19,332 260,858 51,413 12,900 187,466 

TN 89,235 35,571 17,829 211,903 49,131 29,897 161,069 

VA 155,873 46,221 51,418 237,577 52,271 9,510 129,792 

WV 39,546 10,779 12,687 115,346 25,850 11,667 61,490 

Percentage Difference (negative values means Base G increased from Base F) 

AL 0.00% 1.96% 0.00% -0.13% 22.76% -11.00% 7.05% 

FL 32.85% 16.61% 2.05% 0.78% 27.62% 0.12% 7.91% 

GA -0.18% 3.94% -0.10% -0.01% 22.28% -0.01% 3.15% 

KY 0.00% -0.07% 0.00% 0.00% 13.86% 0.00% 4.79% 

MS 0.00% 0.91% 0.00% 0.00% 20.17% 0.00% 2.44% 

NC 7.57% 1.59% 24.99% 7.62% 8.05% 23.74% 31.25% 

SC 0.00% 4.35% 0.00% 0.00% 21.63% 0.00% 14.12% 

TN -0.67% 3.31% -0.09% -0.31% 13.36% -0.07% 4.82% 

VA 0.00% 5.01% 0.00% 0.00% 15.84% -1013.45% -34.15% 

WV 0.00% 7.57% 0.00% 0.00% 18.57% 0.00% 1.70% 
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Table 2.2-2 2009 Projection Year Emissions and Percentage Difference for Base F and 

Base G (based on actual emissions). 

Actual Area 2009 - Base G 

State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC 

AL 66,654 64,268 23,930 413,020 58,699 48,228 143,454 

FL 57,011 38,616 28,187 503,230 64,589 36,699 420,172 

GA 94,130 89,212 37,729 776,411 112,001 57,696 272,315 

KY 57,887 53,005 42,088 242,177 46,243 43,087 94,042 

MS 27,184 63,708 4,249 356,324 51,661 753 124,977 

NC 301,163 170,314 39,954 292,443 69,457 5,751 187,769 

SC 90,390 30,555 19,360 278,299 41,613 13,051 146,107 

TN 74,189 35,253 18,499 226,098 44,124 30,577 154,377 

VA 128,132 46,639 52,618 252,488 44,514 105,984 147,034 

WV 31,640 10,625 13,439 115,089 20,664 12,284 55,288 

Base F 

AL 68,882 65,441 26,482 411,614 76,248 17,818 157,405 

FL 101,356 46,950 31,821 507,515 90,487 52,390 462,198 

GA 103,579 92,838 38,876 776,935 146,691 57,377 294,204 

KY 64,806 53,023 42,122 242,345 54,397 40,779 94,253 

MS 37,161 64,289 4,789 356,516 65,321 637 125,382 

NC 332,443 173,187 53,550 317,847 75,570 7,607 252,553 

SC 95,826 31,966 20,852 278,852 54,230 12,945 176,104 

TN 82,196 36,578 19,148 225,650 51,753 29,787 160,265 

VA 133,738 49,173 53,344 252,924 54,587 10,619 120,022 

WV 37,704 11,461 13,816 115,410 25,835 12,156 57,082 

Percentage Difference (negative values means Base G increased from Base F) 

AL 3.24% 1.79% 9.64% -0.34% 23.02% -170.67% 8.86% 

FL 43.75% 17.75% 11.42% 0.84% 28.62% 29.95% 9.09% 

GA 9.12% 3.91% 2.95% 0.07% 23.65% -0.56% 7.44% 

KY 10.68% 0.03% 0.08% 0.07% 14.99% -5.66% 0.22% 

MS 26.85% 0.90% 11.27% 0.05% 20.91% -18.10% 0.32% 

NC 9.41% 1.66% 25.39% 7.99% 8.09% 24.41% 25.65% 

SC 5.67% 4.41% 7.16% 0.20% 23.27% -0.82% 17.03% 

TN 9.74% 3.62% 3.39% -0.20% 14.74% -2.65% 3.67% 

VA 4.19% 5.15% 1.36% 0.17% 18.45% -898.09% -22.51% 

WV 16.08% 7.29% 2.73% 0.28% 20.02% -1.06% 3.14% 
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Table 2.2-3 2018 Projection Year Emissions and Percentage Difference for Base F and Base 

G (based on actual emissions). 

Actual Area 2018 - Base G 

State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC 

AL 59,626 71,915 25,028 445,256 62,323 50,264 153,577 

FL 53,903 40,432 30,708 578,516 72,454 38,317 489,975 

GA 93,827 99,885 41,332 880,199 123,704 59,729 319,328 

KY 54,865 55,211 44,346 256,052 47,645 44,186 103,490 

MS 22,099 69,910 4,483 375,495 53,222 746 140,134 

NC 290,809 180,866 43,865 315,294 71,262 6,085 189,591 

SC 83,167 33,496 20,592 304,251 44,319 13,457 161,228 

TN 68,809 36,291 19,597 246,252 46,692 31,962 182,222 

VA 121,690 50,175 56,158 275,351 46,697 109,380 150,919 

WV 28,773 11,504 14,828 121,549 21,490 12,849 60,747 

Base F 

AL 63,773 73,346 28,754 445,168 82,449 49,975 168,507 

FL 100,952 49,889 35,047 582,832 101,872 59,413 533,141 

GA 105,059 103,911 42,260 880,800 163,925 61,155 342,661 

KY 65,297 55,356 45,597 256,544 57,110 42,326 102,117 

MS 36,425 70,565 5,230 375,931 68,338 831 139,419 

NC 327,871 184,167 60,073 345,275 85,018 8,273 234,207 

SC 89,343 35,082 22,467 304,940 58,441 13,517 196,946 

TN 81,242 37,812 20,928 245,893 55,712 31,047 188,977 

VA 129,037 53,023 56,668 275,790 58,141 11,479 128,160 

WV 36,809 12,390 15,079 121,964 27,088 13,450 62,164 

Percentage Difference (negative values means Base G increased from Base F) 

AL 6.50% 1.95% 12.96% -0.02% 24.41% -0.58% 8.86% 

FL 46.61% 18.96% 12.38% 0.74% 28.88% 35.51% 8.10% 

GA 10.69% 3.87% 2.20% 0.07% 24.54% 2.33% 6.81% 

KY 15.98% 0.26% 2.74% 0.19% 16.57% -4.40% -1.34% 

MS 39.33% 0.93% 14.28% 0.12% 22.12% 10.19% -0.51% 

NC 11.30% 1.79% 26.98% 8.68% 16.18% 26.45% 19.05% 

SC 6.91% 4.52% 8.34% 0.23% 24.16% 0.44% 18.14% 

TN 15.30% 4.02% 6.36% -0.15% 16.19% -2.95% 3.57% 

VA 5.69% 5.37% 0.90% 0.16% 19.68% -852.83% -17.76% 

WV 21.83% 7.15% 1.66% 0.34% 20.66% 4.46% 2.28% 

2.2.3 Changes to Prescribed Fire for 2009/2018 Base G 

Just prior to release of version 3.1 of the VISTAS inventory several Federal agencies indicated 

that they had plans for increased prescribed fire burning in future years and that the “typical” fire 

inventory would likely not adequately capture those increases (memo from Bill Jackson and 

Cindy Huber, August 13, 2004). However data were not readily available to incorporate those 

changes up through the Base F inventory. As a consequence MACTEC worked with Federal 

Land Managers to acquire the data necessary to provide 2009 and 2018 specific projections for 

the prescribed fire component of the Base G fire inventory. The 2009 and 2018 projections 

developed using the method described below are being used by VISTAS as the 2009 and 2018 
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base case inventories for all States except FL. For FL the supplied data from the FLMs is not 

being used as FL felt that their data adequately reflected current and future prescribed burning 

practices. The “typical” fire projection is the 2002 base prescribed fire projection. 

One of the biggest issues in preparing the projection was how best to incorporate the data. Two 

agencies submitted data: Fish and Wildlife Service (FWS) and Forest Service (FS). FWS 

submitted annual acreage data by National Wildlife Refuge (NWR) and county with estimates of 

acres burned per day for each NWR. FS provided fire-by-fire acreage estimates based on 

mapping projected burning acreage to current 2002 modeling days. However, FWS did not 

submit data for VISTAS original base year preparation process, thus there was no known FWS 

data in the 2002 actual or typical inventories. Thus MACTEC had to develop a method that 

could use the county level data submitted by FWS. 

In addition, despite the fact that the FS submitted fire-by-fire data for the 2002 actual inventory 

and had mapped the projections to current burn days in the 2002 actual inventory, MACTEC 

could not do a simple replacement of those records with the 2009/2018 projections. This 

situation was created because several VISTAS States run a prescribed fire permitting program. 

To avoid double counting, only State data was used in those States for the 2002 actual inventory. 

Thus there were no Federal data in those States since the Federal data could have potentially 

duplicated State-supplied prescribed fire data. In VISTAS States without permit programs, the 

FS supplied data for 2002 was used and those records were marked in database. Thus for those 

States, the FS supplied 2009/2018 data could be directly substituted for the 2002 data. 

The method used by MACTEC to include the FS data applied a county level data approach for 

FS data where a State had a prescribed fire permitting program and a fire-by-fire replacement for 

FS data in States without permit programs. MACTEC used a county level approach for all of the 

FWS data. The approach used for each data set is discussed below. 

For the FWS data MACTEC summed the annual acres burned supplied by the FWS across all 

NWRs in a county. We then subtracted out 2002 acreage for that county from the FWS projected 

acreage annual total to avoid double counting. The remaining acreage was then multiplied by 0.8 

to account for blackened acres instead of the total perimeter acres that were reported. The revised 

total additional FWS acreage was then added to the total county “typical” acreage to determine 

future acreage burned for either 2009 or 2018. MACTEC then allocated the increased acreage to 

current modeling days. The average daily acres burned data provided by FWS per NWR/county 

was used to allocate the acreage to the correct number of days required to burn all of the acres. 

Guidance supplied by FWS indicated that up to three times the average daily acres burned could 

potentially be allocated to any one day. Thus if the estimated acreage per day were 100 acres 

then up to 300 acres could actually be allocated to a particular day. This approach (use of up to 

three times the average daily acres burned) was used if there were an insufficient number of 2002 
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modeling days available to account for all of the acreage increase. MACTEC used an 

incremental approach to using the increase above the base average daily acres. First we used 

twice the average daily acreage if that was sufficient to completely allocate the increased acreage 

over the total number of days available. If that wasn’t sufficient then we used three times the 

average daily acres burned to allocate the acreage. We applied the highest increases to days in 

the database that already had the highest acreage burned since we felt those days were most 

likely to represent days with representative conditions for conducting prescribed burns. 

The approach used by MACTEC for the FS was slightly different. For States that had permit 

programs, we used similar approach to the FWS county level approach. First we summed the FS 

data at county level, we then added that value to the typical acreage and then we allocated the 

acres to current modeling days. The mapping to current modeling days was performed by Bill 

Jackson of the USFS and provided to MACTEC. For States that do not have a prescribed fire 

permit program, MACTEC simply replaced the current fire-by-fire records in the database with 

fire-by-fire records from the FS and recalculated emissions based on fuel model and fuel loading. 

We also applied the same 0.8 correction for blackened acres applied to all FS supplied acreage as 

the supplied values represented perimeter acres. 

An additional problem with developing year-specific prescribed fire projections was how to 

adequately capture the temporal profile for those fires. In the 2002 actual fire inventory, fires 

occur on same days as state/FLM records. In the 2002 “typical” year inventory, fire acreage 

increased or decreased from acreage on the same fire days as were in the 2002 actual inventory, 

since the acres were simply increased for each day based on a multiplier used to convert from 

actual to typical. 

When prescribed fires acreage was added to a future year, MACTEC added acreage to individual 

fire days proportional to the annual increase (if acreage on a day is 10 percent of annual, add 10 

percent of projected increase to that same day). 

The table below shows how the FWS data for Okefenokee NWR were allocated for 2009 for 

Clinch County (Okefenokee NWR is located in four different counties). You can see that the 

total additional acres for the Clinch County portion of Okefenokee NWR was 1,956 acres. Two 

hundred eighty (280) acres were the estimated average daily acres burned for that NWR/county 

combination. Thus to allocate the entire 1,956 acres would require almost 7 burn days (1,956 

divided by 280). However only 5 burn days were found for Clinch County in the 2002 actual fire 

database. Thus we allocated twice the average acreage to the burn day with the most acres 

burned in the 2002 actual fire database (since our method allowed us to increase the average 

daily acres burned up to three times the recommended level). Thus the first burn day received 

560 acres and all others received 280 except the final day which received 276 to make the total 

equal to the required 1,956 acres. The table also indicates that the increased acres burned 
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0

2000

4000

6000

8000

10000

12000

14000

16000

1/1/2002

2/1/2002

3/1/2002

4/1/2002

5/1/2002

6/1/2002

7/1/2002

8/1/2002

9/1/2002

10/1/2002

11/1/2002

12/1/2002

Date of Fire Event

Acres

Typical

FWS Add

USFS Add

provided increases of from 10-48 percent in the acres burned on the individual burn days and an 

average of approximately 14 percent for the year as a whole. 

CLINCH COUNTY 3/1/2002 4/1/2002 2/1/2002 1/1/2002 11/1/2002 12/1/2002 

Total 

Annual

Acres (typical) 3,757 2,612 1,996 1,801 616 472 11,764

Add on FWS Projection 560 280 280 280 280 276 1,956

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

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

The figure below shows the increases for prescribed burning in the four counties that comprise 

the Okefenokee NWR area (which also includes FS land). In this figure you can see the 

additional acreage added for the burn days from FWS and the individual day increases caused by 

projected increases in prescribed burning based on FS data. It should be noted that while the 

emissions represent 2009, all fire event dates listed are for 2002 to match up with the base year 

meteorology used in modeling exercises. 

Table 2.2-4 shows the percentage difference between the 2009 and 2018 projections developed 

for Base F and Base G. Base G includes the revised prescribed burning estimates described 

above. Values are calculated using Base F as the basis for change, thus negative values imply an 

increase in emissions for Base G. 

Figure 2.2-1 Prescribed Fire Projection for Okeefenokee NWR for 2009 
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Table 2.2-4 Percentage Difference Between Base F and Base G Fire Emissions by State 

State CO NH3 NOX PM10-PRI PM25-PRI SO2 VOC CO NH3 NOX PM10-PRI 

2009 Fires Base G 2018 Fires Base G AL 534,873 2,050 11,901 52,851 46,543 2,681 27,502 535,658 2,054 11,918 52,927 FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 GA 637,177 2,229 14,243 63,973 57,116 2,914 34,710 637,177 2,229 14,243 63,973 KY 31,810 143 682 3,093 2,653 187 1,497 33,296 150 714 3,237 MS 48,160 217 1,033 4,683 4,016 283 2,266 50,037 225 1,073 4,865 NC 96,258 433 2,065 9,359 8,027 566 4,530 111,266 501 2,387 10,819 SC 282,307 1,039 5,899 29,153 25,955 1,359 16,045 282,307 1,039 5,899 29,153 TN 17,372 78 373 1,689 1,449 102 817 18,860 85 405 1,834 VA 21,130 95 453 2,054 1,762 124 994 26,923 121 578 2,618 WV 3,949 18 85 384 329 23 186 5,013 23 108 487 2009 Fires Base F 2018 Fires Base F 

AL 514,120 1,957 11,456 50,833 44,812 2,559 26,526 514,120 1,957 11,456 50,833 FL 923,310 3,157 19,791 98,470 88,756 4,129 51,527 923,310 3,157 19,791 98,470 GA 620,342 2,153 13,882 62,336 55,712 2,815 33,918 620,342 2,153 13,882 62,336 KY 56,686 110 1,460 6,667 6,310 136 3,338 56,686 110 1,460 6,667 MS 128,471 177 3,328 14,693 13,680 100 13,625 128,471 177 3,328 14,693 NC 200,564 324 5,005 20,488 19,491 423 12,499 200,564 324 5,005 20,488 SC 253,005 908 5,270 26,304 23,511 1,187 14,666 253,005 908 5,270 26,304 TN 78,370 46 2,232 8,875 8,730 59 5,153 78,370 46 2,232 8,875 VA 19,159 159 978 18,160 17,361 99 912 19,159 159 978 18,160 WV 32,656 12 944 3,276 3,239 16 2,184 32,656 12 944 3,276 

Percentage Difference (negative number means an increase in Base G emissions) 

AL -4.04% -4.77% -3.89% -3.97% -3.86% -4.77% -3.68% -4.19% -4.95% -4.03% -4.12% FL 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% GA -2.71% -3.52% -2.60% -2.63% -2.52% -3.52% -2.34% -2.71% -3.52% -2.60% -2.63% KY 43.88% -29.52% 53.25% 53.61% 57.96% -37.90% 55.15% 41.26% -35.57% 51.07% 51.44% MS 62.51% -22.07% 68.95% 68.13% 70.64% -183.85% 83.37% 61.05% -26.83% 67.74% 66.89% NC 52.01% -33.75% 58.74% 54.32% 58.82% -33.75% 63.76% 44.52% -54.60% 52.31% 47.19% SC -11.58% -14.52% -11.93% -10.83% -10.39% -14.52% -9.40% -11.58% -14.52% -11.93% -10.83% TN 77.83% -69.40% 83.30% 80.97% 83.41% -74.42% 84.14% 75.93% -83.92% 81.87% 79.34% VA -10.29% 40.36% 53.67% 88.69% 89.85% -25.40% -9.03% -40.53% 24.00% 40.97% 85.59% WV 87.91% -48.65% 91.03% 88.28% 89.83% -49.46% 91.49% 84.65% -88.70% 88.61% 85.12% 
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2.2.4 Quality Assurance steps 

Throughout the inventory development process, quality assurance steps were performed to 

ensure that no double counting of emissions occurred, to ensure that a full and complete 

inventory was developed for VISTAS, and to make sure that projection calculations were 

working correctly. Quality assurance was an important component to the inventory development 

process and MACTEC performed the following QA steps on the stationary and agricultural area 

source components of the 2009 and revised 2018 projection inventories: 

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

2. SCC level emission summaries were prepared and evaluated to ensure that emissions 

were consistent and that there were no missing sources. 

3. Tier comparisons (by pollutant) were developed between the 2002 base year 

inventory and the 2009 and 2018 projection inventories. In addition, total VISTAS 

pollutant summaries were prepared to compare total emissions by pollutant between 

versions of the inventory (e.g., between Base F and Base G). 

4. Data product summaries were provided to both the VISTAS Emission Inventory 

Technical Advisor and to the SIWG representatives for review and comment. 

Changes based on these comments were implemented in the files. 

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

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

example, a major change would result in a version going from 1.0 to 2.0. A minor 

change would cause a version number to go from 1.0 to 1.1. Minor changes resulting 

from largely editorial changes would result in a change from 1.00 to 1.01. 

2.3 Mobile Sources 

Our general approach for assembling data was to use as much existing data from the pre-Base F 

preliminary projections as possible for these inventories, supplement these data with easily 

available stakeholder input, and provide the results for stakeholder review to ensure credibility. 

To develop the “base case” projections, MACTEC originally assembled data to develop two 

2009 and 2018 base case inventories: 1) an inventory that included all “on-the-books” control 

programs and 2) an “on-the-way” inventory that included controls that were likely to be “on-theway”. For the Base F and Base G emission forecasts to the mobile source sector, “on-the-books” 

and “on-the-way” are defined with the same strategies and therefore only a single projection 

scenario was developed for each forecast year. 

To ensure consistency across evaluation years, the 2009 and 2018 base case inventories were 

developed, to the maximum extent practical, using methodologies identical to those employed in 
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developing the 2002 on-road portion of the revised 2002 VISTAS base year inventory. All 

modifications to the 2002 inventory methods were developed in consultation with the Mobile 

Source Special Interest Workgroup (MSSIWG). Generally, modifications were only made to 

properly account for actual changes expected in the intervening period (i.e., between 2002 and 

2009 and between 2002 and 2018), but the underlying inventory development methodology was 

identical, except to the extent requested by VISTAS or the MSSIWG. 

MACTEC developed a preliminary 2018 inventory in early 2004. That inventory was designed 

to 1) be used for modeling sensitivity evaluations and 2) help establish the methods that would 

be used for the final 2018 inventory and the initial 2009 inventory. Since that work took place 

prior to the revision of the 2002 base year inventory data files, MACTEC provided a review of 

the data and methods used to develop on-road mobile source input files for the initial 2002 base 

year inventory prior to developing the preliminary 2018 inventory. Through this review, 

MACTEC determined the following: 

 On-road VMT. Most States provided local data for 2002 (or a neighboring year that was 

converted to 2002 using appropriate VMT growth surrogates such as population). Since 

these data were not applicable to 2018 due to intervening growth, input for 2018 was 

solicited from the MSSIWG. At the same time we researched county-specific growth rate 

data utilized for recent national rulemakings as a backstop approach to State supplied 

VMT projections. 

 Modeling Temperatures. Actual 2002 temperatures were used for the initial 2002 base 

year inventory. 

 Vehicle Registration Mix (age fractions by type of vehicle). A mix of State, local, and 

MOBILE6 default data were used for the 2002 initial base year inventory. Forecast data 

were solicited from the States, with a fallback position that we hold the fractions constant 

at their 2002 values. 

 Vehicle Speed by Roadway Type. For the 2002 initial base year inventory, speeds 

varying by vehicle and road type were used. 

 VMT Mixes (fraction of VMT by vehicle type). A mix of State, local, and quasi 

MOBILE6 default (i.e., MOBILE6 defaults normalized to better reflect local conditions) 

data were used for the 2002 initial base year inventory. Forecast data were solicited from 

the States. 

 Diesel Sales Fractions. As with the VMT mix data, the diesel sales fraction data 

employed for the 2002 initial base year inventory represents a mix of State, local, and 

quasi MOBILE6 default data. The issues related to updating these data to 2018 are also 
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similar, but are complicated by the fact that MOBILE6 treats diesel sales fraction on a 

model year, rather than age specific basis. Therefore, diesel sales fractions generally 

cannot be held constant across time. Once again, we solicited any local projections, with 

a fallback position that we would keep the data for 2002 and earlier model years constant 

for the forecast inventory, supplemented with MOBILE6 default data for 2003 and newer 

model years. 

 State/Local Fuel Standards. For the 2002 initial base year inventory, these data were 

based on appropriate local requirements and updated data for 2018 was only required if 

changes were expected between 2002 and 2018. There are some national changes in 

required fuel quality for both on-road and non-road fuels that are expected to occur 

between 2002 and 2018 and these would be reflected in the 2018 inventory in the absence 

of more stringent local fuel controls. Expected changes in local fuel control programs 

were solicited. 

 Vehicle Standards. The 2002 initial base year inventory assumed NLEV applicability. 

This was altered to reflect Tier 2 for 2018, unless a State indicated a specific plan to 

adopt the California LEV II program. If so, we made the required changes to implement 

those plans for the preliminary 2018 inventory. 

 Other Local Controls. This includes vehicle emissions inspection (i.e., I/M) programs, 

Stage II vapor recovery programs, anti tampering programs, etc. By nature, the 

assumptions used for the 2002 initial base year inventory vary across the VISTAS region, 

but our presumption is that these data accurately reflected each State’s situation as it 

existed in 2002. If a State had no plans to change program requirements between 2002 

and 2018, we proposed to maintain the 2002 program descriptions without change. 

However, if a State planned changes, we requested information on those plans. In the 

final implementation of the Base F and earlier inventories, Stage II controls were 

exercised in the area source component of the inventory, since the units used to develop 

Stage II refueling estimates are different between MOBILE6 and the NONROAD 

models. However, in the Base G inventories, Stage II refueling was moved to the on-road 

and non-road sectors. 

Once the preliminary 2018 (pre-Base F) base case projection inventory data were compiled, 

MACTEC applied the data and methods selected and proceeded to develop the preliminary (prebase F) base case 2018 projection inventories. The resulting inventories were provided to the 

MSSIWG in a user-friendly format for review. After stakeholder review and comment, the final 

preliminary 2018 base case inventories and input files were provided to VISTAS in formats 

identified by the VISTAS Technical Advisor (in this case, MOBILE input files and VMT, 

NONROAD input files and annual inventory files for NONROAD in NIF 3.0 format). Annual 
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inventory files for MOBILE were not developed as part of this work, only input files and VMT 

forecasts. MOBILE emissions were calculated by VISTAS air quality modeling contractor using 

the provided files. 

2.3.1 Development of on-road mobile source input files 

As indicated above, MACTEC prepared a preliminary version of the 2018 base case mobile 

inventory input data files. These files were then updated to provide a final set of 2018 base case 

inventory input data files as well as a set of input files for 2009. The information below describes 

the updates performed on the preliminary 2018 files and the development of the 2009 input 

data files for Base F emission estimation. 

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

1. the revised 2002 data provided by each State coupled with the projection methods 

employed for the preliminary 2018 inventory, or 

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

We also investigated whether or not there was more recent VMT forecasting data available (e.g., 

from the CAIR and if appropriate revised the default VMT growth rates accordingly. This did 

not affect any State that provided local VMT forecasting data, but would alter the VMT 

estimates used for other areas. 

Since no preliminary 2009 inventory was developed there did not exist an option (2) above for 

2009. As a consequence, MACTEC crafted the 2009 initial inventory for on-road mobile sources 

using methods identical to those employed for the 2018 preliminary inventories coupled with any 

changes/revisions provided by the States during the review of the revised 2002 base year and the 

2018 preliminary inventories. Therefore, as was the case for 2018, we obtained from the States 

any input data revisions, methodological revisions, and local control program specifications (to 

the extent that they differed from 2002/2018). 

2.3.1.1 Preparation of revised 2018 input data files 

Preparation of the revised 2018 inventories required the following updates: 

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

2. The diesel fuel sulfur content was revised from 500 ppm to 11 ppm, consistent with 

EPA data for 2018 in all files. 

3. Since the input data is model year, rather than age, specific for diesel sales fractions 

(with data for the newest 25 model years required), we updated all files that included 
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diesel sales fractions. In the revised 2002 base year files, the data included applied to 

model years 1978-2002. For 2018, the data included would reflect model years 1994-

2018. To forecast the 2002 data, MACTEC took the data for 1994-2002 from the 

2002 files and added data for 2003-2018. To estimate the data for these years, we 

employed the assumption employed by "default" in MOBILE6 -- namely that diesel 

sales fractions for 1996 and later are constant. Therefore, we set the diesel sales 

fractions for 2003-2018 at the same value as 2002. 

4. VMT mix fractions must be updated to reflect expected changes in sales patterns 

between 2002 and 2018. If explicit VMT mix fractions are not provided, these 

changes are handled internally by MOBILE6 or externally through absolute VMT 

distributions. However, files that include explicit VMT mix fractions override the 

default MOBILE6 update and may or may not be consistent with external VMT 

distributions. MACTEC updated the VMT mix in such files as follows: 

First, we calculated the VMT fractions for LDV, LDT1, LDT2, HDV, and MC 

from the external VMT files for 2018. This calculation was performed in 

accordance with section 5.3.2 of the MOBILE6 Users Guide which indicates: 

LDV = LDGV + LDDV 

LDT1 = LDGT1 + LDDT 

LDT2 = LDGT2 

HDV = HDGV + HDDV 

MC = MC 

The resulting five VMT fractions were then split into the 16 fractions required by 

MOBILE6 using the distributions for 2018 provided in Appendix D of the 

MOBILE6 Users Guide. This approach ensures that explicit input file VMT 

fractions are consistent with the absolute VMT distributions prepared by 

MACTEC. These changes were made to all files that included VMT mixes. 

5. All other input data were retained at 2002 values, except as otherwise instructed by 

the States. This includes all control program descriptions (I/M, Anti-Tampering 

Program [ATP], Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all 

other vehicle descriptive data (registrations age distributions, etc.), and all scenario 

descriptive data. The State-specific updates performed are described below. 

Kentucky:

MACTEC revised the 2018 input files for the Louisville, Kentucky area (Louisville Air Pollution 

Control District [APCD]) based on comments received relative to several components of 
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MOBILE input data. Based on these comments, the input files for Jefferson County, Kentucky 

were updated accordingly as follows: 

a) I/M and tampering program definitions were removed since the program was 

discontinued at the end of 2003. 

b) The "Speed VMT", "Facility VMT" and "Registration Age Distribution" file pointers 

were updated to reflect revised 2002 files provided by the Louisville APCD. 

c) The "VMT Mix" data, which was previously based on the default approach of 

"growing" 2002 data, was replaced by 2018-specific data provided by the Louisville 

APCD. 

North Carolina:

North Carolina provided a wide range of revised input data, including complete MOBILE6 input 

files for July modeling. MACTEC did not use the provided input files directly as they did not 

match the 2002 NC input files for critical elements such as temperature distributions and 

gasoline RVP (while they were close, they were slightly different). To maintain continuity 

between 2002 and 2018 modeling, MACTEC instead elected to revise the 2002 input files to 

reflect all control program and vehicle-related changes implied by the new 2018 files, while 

retaining the basic temperature and gasoline RVP assumptions at their 2002 values. Under this 

approach, the following changes were made: 

a) NC provided a county cross reference file specific to 2018 that differed from that 

used for 2002. We removed files that were referenced in the 2002 input data and 

replaced those files with those referenced in the 2018 data. In addition, since NC only 

provided 2018 input files for July, we estimated the basic data for these new files for 

the other months by cross referencing the target files for 2002 by county against the 

target files for 2018 by county. 

b) We then revised the 2002 version of each input file to reflect the 2018 "header" data 

included in the NC-provided 2018 files. These data are exclusively limited to I/M and 

ATP program descriptions, so that the 2002 I/M and ATP data were replaced with 

2018 I/M and ATP data. 

c) We retained the registration age fractions at their 2002 "values" (external file 

pointers) as per NC instructions. 

d) We retained all scenario-specific data (i.e., temperatures, RVP, etc.) at 2002 values, 

which (as indicated above), were slightly different in most cases from data included 

in the 2018 files provided by NC. We believe these differences were due to small 

deviations between the data assembled to support VISTAS 2002 and the process used 

to generate the 2018 files provided by NC, and that revising the VISTAS 2002 data to 
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reflect these variations was not appropriate given the resulting inconsistencies that 

would be reflected between VISTAS 2002 and VISTAS 2018. 

e) NC also provided non-I/M versions of the 2018 input files that would generally be 

used to model the non-I/M portion of VMT. While these files were retained they were 

not used for the 2018 input data preparation. 

Finally, NC also provided a speed profile file and a speed profile cross reference file for 2018. 

We did not use these in our updates as they have no bearing on the MOBILE6 input files, but 

they were maintained in case they needed to be included in SMOKE control files for a future 

year control strategy scenario. 

Virginia:

In accordance with instructions from VA, the input files that referenced an external I/M 

descriptive program file (VAIM02.IM) were revised to reference an alternative external file 

(VAIM05.IM). This change was to make the I/M program more relevant to the year 2018. 

One additional important difference was made with respect to the revised 2018 and initial 2009 

on-road mobile source input data files for all States. MACTEC developed updated SMOKE 

ready input files rather than MOBILE6 files so that the input data could be used directly by the 

VISTAS modeling contractor to estimate on-road mobile source emissions during modeling runs. 

2.3.1.2 Preparation of initial 2009 input data files 

The methodology used to develop the 2009 on-road input files was based on forecasting the 

previously developed revised 2002 base year input files and is identical to that previously 

described for the revised 2018 methodology except as follows: 

1. The evaluation year was updated to 2009. 

2. Diesel fuel sulfur content was revised from 500 ppm to 29 ppm. The 29 ppm value 

was derived from an EPA report entitled "Summary and Analysis of the Highway 

Diesel Fuel 2003 Pre-compliance Reports" (EPA420-R-03-013, October 2003), 

which includes the Agency's estimates for the year-to-year fuel volumes associated 

with the transition from 500 ppm to 15 ppm diesel fuel. According to Table 2 of the 

report, there will be 2,922,284 barrels per day of 15 ppm diesel distributed in 2009 

along with 110,488 barrels per day of 500 ppm diesel. Treating the 15 ppm diesel as 

11 ppm on average (consistent with EPA assumptions and assumptions employed for 

the 2018 input files) and sales weighting the two sulfur content fuels results in an 

average 2009 diesel fuel sulfur content estimate of 29 ppm. 
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3. Diesel sales fractions were updated identically to 2018 except that the diesel sales 

fractions for 2003-2009 were set at the same value as those for 2002 (rather than 

2003-2018). 

4. VMT mix fractions were updated to 2009 using an identical method to that described 

for 2018. 

5. All other input data were retained at 2002 values, except as otherwise instructed by 

individual States (see below). This includes all control program descriptions (I/M, 

ATP, Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all other vehicle 

descriptive data (registration age distributions, etc.), and all scenario descriptive data. 

In addition to the updates described above that were applied to all VISTAS-region inputs, the 

following additional State-specific updates were performed: 

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

2009 input files. 

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

input files. 

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

2.3.2 VMT Data 

The basic methodology used to generate the 2009 and 2018 VMT for use in estimating on-road 

mobile source emissions was as follows: 

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

inventory. 

2. Initial 2009 and 2018 VMT estimates were based on linear growth rates for each 

State, county, and vehicle type as derived from the VMT data assembled by the U.S. 

EPA for their most recent HDD (heavy duty diesel) rulemaking. The methodology 

used to derive the growth factors is identical to that employed for the preliminary 

2018 VMT estimates (which is described in the next section). 

3. For States that provided no independent forecast data, the estimates derived in step 2 

are also the final estimates. These States are: Alabama, Florida, Georgia, Kentucky, 

Mississippi, and West Virginia. For States that provided forecast data, the provided 

data were used to either replace or augment the forecast data based on the HDD rule. 

These States, and the specific approaches employed, are detailed following the 

growth method description. 

The steps involved in performing the growth estimates for VMT were as follows: 
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1. Linear growth estimates were used (although MACTEC investigated the potential use 

of nonlinear factors and presented that information to the MSSIWG, the decision was 

made to use linear growth factors instead of nonlinear). 

2. Estimates were developed at the vehicle class (i.e., LDGV, LDGT1, LDGT2, etc.) 

level of detail since the base year 2002 estimates were presented at that level of 

resolution. In effect, the county and vehicle class specific growth factors were applied 

to the 2002 VMT estimates for each vehicle and road class. 

3. Overall county-specific VMT estimates for each year (developed by summing the 

vehicle and road class specific forecasts) were then compared to overall countyspecific growth. Since overall county growth is a more appropriate controlling factor 

as it includes the combined impacts of all vehicle classes, the initial year-specific 

vehicle and road class VMT forecasts were normalized so that they matched the 

overall county VMT growth. Mathematically, this process is as follows: 

(Est_rv_f) = (Est_rv_i) * (C_20XX / Sum(Est_rv_i)) 

where: 

Est_rv_f = the final road/vehicle class-specific estimates, 

Est_rv_i = the initial road/vehicle class-specific estimates, and 

C_20XX = the county-specific growth target for year 20XX. 

Table 2.3-1 presents a basic summary of the forecasts for the preliminary 2018 inventory for 

illustrative purposes: 

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

State 2002 2018 Growth Factor 

Alabama 55,723 72,966 1.309 

Florida 178,681 258,191 1.445 

Georgia 106,785 148,269 1.388 

Kentucky 51,020 66,300 1.299 

Mississippi 36,278 46,996 1.295 

North Carolina 80,166 110,365 1.377 

South Carolina 47,074 63,880 1.357 

Tennessee 68,316 91,647 1.342 

Virginia 76,566 102,971 1.345 

West Virginia 19,544 24,891 1.274 
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The following States provided some types of forecast data for VMT. The information presented 

below indicates how those data were processed by MACTEC for use in the VISTAS projection 

inventories. 

Kentucky: 

Revised 2009 and 2018 VMT mix data were provided by the Louisville APCD. Therefore, the 

distribution of Jefferson County VMT by vehicle type within the KY VMT file was revised to 

reflect the provided mix. This did not affect the total forecasted VMT for either Jefferson County 

or the State, but does alter the fraction of that VMT accumulated by each of the eight vehicle 

types reflected in the VMT file. The following procedure was employed to make the 

VMT estimates consistent with the provided 2009/2018 VMT mix: 

a) The 16 MOBILE6 VMT mix fractions were aggregated into the following five vehicle 

types: LDV, LDT1, LDT2, HDV, and MC. 

b) The 8 VMT mileage classes were aggregated into the same five vehicle types (across all 

roadway types) and converted to fractions by normalizing against the total Jefferson 

County VMT. 

c) The ratio of the "desired" VMT fraction (i.e., that provided in the Louisville APCD VMT 

mix) to the "forecasted" VMT fraction (i.e., that calculated on the basis of the forecasted 

VMT data) was calculated for each of the five vehicle classes. 

d) All forecasted VMT data for Jefferson County were multiplied by the applicable ratio 

from step c as follows: 

new LDGV = old LDGV * LDV ratio 

new LDGT1 = old LDGT1 * LDT1 ratio 

new LDGT2 = old LDGT2 * LDT2 ratio 

new HDGV = old HDGV * HDV ratio 

new LDDV = old LDDV * LDV ratio 

new LDDT = old LDDT * LDT1 ratio 

new HDDV = old HDDV * HDV ratio 

new MC = old MC * MC ratio 

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

unchanged. 

North Carolina: 

North Carolina provided both VMT and VMT mix data by county and roadway type for 2018. 

Therefore, these data replaced the data developed for North Carolina using HDD rule growth 
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rates in their entirety. Similar data were submitted for 2009. Table 2.3-2 presents the resulting 

VMT estimates which differ from the "default" HDD rule estimates as follows: 

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

North Carolina 

2002 106,795 

State Data HDD Data 

2009 123,396 124,626 

2018 129,552 146,989 

As indicated, there are substantial reductions in the State-provided forecast data relative to that 

derived from the HDD rule. The growth rates for both 2009 and 2018 are only about half that 

implied by the HDD data (1.15 versus 1.17 for 2009 and 1.21 versus 1.38 for 2018). The 

resulting growth rates are the lowest in the VISTAS region. 

NC did not provide VMT mix data for 2009. Therefore, the VMT mix fractions estimated using 

the "default" HDD rule growth rates were applied to the State-provided VMT estimates to 

generate vehicle-specific VMT. Essentially, the default HDD methodology produces VMT 

estimates at the county-road type-vehicle type level of detail, and these data can be converted 

into VMT fractions at that same level of detail. Note that these are not HDD VMT fractions, but 

VMT fractions developed from 2002 NC data using HDD vehicle-specific growth rates. In 

effect, they are 2002 NC VMT fractions "grown" to 2009. 

The default VMT mix fraction was applied to the State-provided VMT data at the county and 

road type level of detail to generate VMT data at the county-road type-vehicle type level of 

detail. The one exception was for county 063, road 110, for which no VMT data were included in 

the HDD rule. For this single county/road combination, State-aggregate VMT mix fractions 

(using the HDD growth methodology) were applied to the county/road VMT data. The difference 

between road 110 VMT fractions across all NC counties is minimal, so there is no effective 

difference in utilizing this more aggregate approach vis-à-vis the more resolved county/road 

approach. 

South Carolina: 

South Carolina provided county and roadway type-specific VMT data for several future years. 

Data for 2018 was included and was used directly. Data for 2009 was not included, but was 

linearly interpolated from data provided for 2007 and 2010. The data were disaggregated into 

vehicle type-specific VMT using the VMT mixes developed for South Carolina using the HDD 

rule VMT growth rates. Table 2.3-3 presents the resulting VMT estimates which differ from the 

"default" HDD rule estimates as follows: 
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Table 2.3-3 VMT and HDD Rule Estimates for South Carolina (million miles per year) 

South Carolina 

2002 47,074 

State Data HDD Data 

2009 55,147 54,543 

2018 65,133 63,880 

Tennessee: 

In general, Tennessee estimates are based on the HDD rule growth rate as described in step two. 

However, Knox County provided independent VMT estimates for 2018 and these were used in 

place of the HDD rule-derived estimates. The Knox County estimates were total county VMT 

data only, so these were disaggregated into roadway and vehicle-type VMT using the 

distributions developed for Knox County in step two using the HDD rule VMT growth rates. No 

data for Knox County were provided for 2009, so the estimates derived using the HDD rule 

growth factors were adjusted by the ratio of "Knox County provided 2018 VMT" to "Knox 

County HDD Rule-derived 2018 VMT." Table 2.3-4 presents the resulting VMT estimates which 

differ from the "default" HDD rule estimates as follows: 

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

Tennessee 

2002 68,316 

State Data HDD Data 

2009 78,615 78,813 

2018 91,417 91,647 

Virginia: 

Virginia provided county and roadway type-specific annual VMT growth rates and these data 

were applied to Virginia -provided VMT data for 2002 to estimate VMT in both 2009 and 2018. 

Virginia provided VMT mix data for 2002, but not 2009 or 2018. Therefore, the estimated VMT 

data for both 2009 and 2018 were disaggregated into vehicle type-specific VMT using the VMT 

mixes developed for VA using the HDD rule VMT growth rates. Table 2.3-5 presents the 

resulting VMT estimates which differ from the "default" HDD rule estimates as follows: 
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Table 2.3-5 VMT and HDD Rule Estimates for Virginia (million miles per year) 

Virginia 

2002 77,472 

State Data HDD Data 

2009 88,419 89,196 

2018 104,944 104,164 

2.3.3 Base G Revisions 

For the development of the VISTAS 2009 and 2018 Base G inventories and input files, VISTAS 

states reviewed the Base F inputs, and provided corrections, updates and supplemental data as 

noted below. 

For all states modeled, the Base G updates include: 

 Adding Stage II refueling emissions calculations to the SMOKE processing. 

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

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

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

KY – updated VMT and M6 input values for selected counties 

NC – revised VMT estimates, speeds and vehicle distributions and updated registration 

distributions for Mobile 6. 

TN - revised VMT and vehicle registration distributions for selected counties. 

WV – revised VMT input data 

AL, FL, and GA and VA did not provide updates for 2009/2018 Base G, and the Base F inputs 

were used for these States. 

2.3.4 Development of non-road emission estimates 

The sections that follow describe the projection process used to develop 2009 and 2018 non-road 

projection estimates, as revised through the spring of 2006, for sources found in the NONROAD 

model and those sources estimated outside of the model (locomotives, airplanes and commercial 

marine vessels). 

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 
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time the forecasts were developed, with appropriate updates for the projection years. Generally, 

this means that the Base F 2002 base year input files (as updated through the fall of 2004) were 

used as the basis for Base F projection year input file development and Base G 2002 base year 

input files as updated through the spring of 2006 were used as the basis for Base G projection 

year input file development. Thus, all base year revisions are inherently incorporated into the 

associated projection year revisions. Other specific updates for the projection years for 

NONROAD model sources consist of: 

1. Revise the emission inventory year in the model (as well as various output file 

naming commands) to be reflective of the projection year. 

2. Revise the fuel sulfur content for gasoline and diesel powered equipment. 

3. Implement a limited number of local control program charges (national control 

program changes are handled internally within the NONROAD model, so explicit 

input file changes are not required). 

All equipment population growth and fleet turnover impacts are also handled internally within 

the NONROAD model, so that explicit changes input file changes are not required. 

Base F Input File Changes: 

To correctly account for diesel fuel sulfur content differences between the base and projection 

years, two sets of input and output files were prepared for each forecast year, one set for landbased equipment and one set for marine equipment. This two-step projection process was 

required for Base F, because diesel fuel sulfur contents varied between land-based and 

marine-based non-road equipment and the Draft NONROAD2004 used for Base F allowed only 

a single diesel fuel sulfur input. Thus, the model was executed separately for land-based and 

marine-based equipment for Base F, and the associated outputs subsequently combined. The 

specific diesel fuel sulfur contents modeled were as follows: 

Diesel S (ppm) 2002 2009 2018 

 Land-Based 2500 348 11 

 Marine-Based 2500 408 56 

As indicated, the Draft NONROAD2004 model was run with both sets of input files and the 

output file results were then combined to produce a single NONROAD output set. 

To correctly account for the national reduction in gasoline sulfur content (a national control not 

explicitly handled by the NONROAD model), all NONROAD input files for both 2009 and 2018 

were revised to reflect a gasoline fuel sulfur content of 30 ppmW. 
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Base G Input File Changes: 

With the release of Final NONROAD2005 that was used for the Base G projection year 

inventory development, the NONROAD model is capable of handling separate diesel fuel sulfur 

inputs for land-based and marine-based non-road equipment in a single model execution. 

Therefore, the two step modeling process described above for Base F updates was no longer 

required. Instead, the differential diesel fuel sulfur values are assembled into a single 

NONROAD input file as follows: 

Diesel S (ppm) 2002 2009 2018 

 Land-Based 2500 348 11 

 Marine-Based 2638 408 56 

Additionally, revised gasoline vapor pressure data were provided by Georgia regulators for 20 

counties5 where reduced volatility requirements were established in 2003. Since this requirement 

began after the 2002 base year, the vapor pressure values in the base year input files for these 

counties are not correct for either the 2009 or 2018 forecast years. Therefore, to correctly 

forecast emissions in these counties, the forecast year gasoline vapor pressure inputs were 

revised to: 

Gasoline RVP (psi) 2002 2009 2018 

 Spring 9.87 9.2 9.2 

 Summer 9.0 7.0 7.0 

 Fall 9.87 9.2 9.2 

 Winter 12.5 12.5 12.5 

The summer vapor pressure was simply set equal to the 2003 control value, while the spring and 

fall vapor pressures were adjusted to reflect a single month of the reduced volatility limit. The 

winter volatility was assumed to be unaffected by the summertime control requirement. 

2.3.4.1.1 Differences between 2009/2018 

Other than diesel fuel sulfur content and the year of the projections, there are no differences in 

the methodology used to estimate emissions from NONROAD model sources. As indicated 

above, however the Base F 2009/2018 projections were developed using Draft NONROAD2004, 

while the Base G 2009/2018 projections were made using Final NONROAD2005. 

 

5

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

Madison, Meriwether, Monroe, Morgan, Oconee, Pike, Polk, Putnam, Troup, and Upson. 
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2.3.4.2 Non-NONROAD model sources 

Using the 2002 base year emissions inventory for aircraft, locomotives, and commercial marine 

vessels (CMV) prepared as described earlier in this document, corresponding emission 

projections for 2009 and 2018 were developed in both the fall of 2004 (Base F) and the spring of 

2006 (Base G). This section describes the procedures employed in developing those inventories. 

The information presented is intended to build off of that presented in the section describing the 

2002 Base F base year inventory. It should be recognized that for both the Base F and Base G 

inventories, the base year inventory used to develop the emission forecasts was the latest 

available at the time of forecast development. Generally, this means that the 2002 base year 

inventory as updated through the fall of 2004 was used as the basis for the Base F projection year 

inventory development, and the Base F 2002 base year inventory was used as the basis for Base 

G projection year inventory development. Thus, all base year revisions (as described earlier in 

this document) are inherently incorporated into the associated projection year revisions. 

Base F Revisions: 

Table 2.3-6 shows the 2002 base year emissions for each State in the VISTAS region for aircraft, 

locomotives and CMV (as they existed prior to Base F development). 
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Table 2.3-6 Pre-Base F 2002 Aircraft, Locomotive, and Non-Recreational 

Marine Emissions 

(annual tons, as of the fall of 2004)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 3,787 175 226 87 17 196 

FL 25,431 8,891 2,424 2,375 800 3,658 

GA 6,620 5,372 1,475 1,446 451 443 

KY 2,666 657 179 175 63 263 

MS 1,593 140 44 43 13 96 

NC 6,088 1,548 419 411 148 613 

SC 6,505 515 409 401 88 863 

TN 7,251 2,766 734 719 235 943 

VA 9,763 2,756 1,137 1,115 786 2,529 

WV 1,178 78 25 24 8 66 

Aircraft 

(2275) 

Total 70,882 22,899 7,072 6,797 2,607 9,670 

AL 1,196 9,218 917 844 3,337 737 

FL 5,888 44,817 1,936 1,781 6,683 1,409 

GA 1,038 7,875 334 307 1,173 246 

KY 6,607 50,267 2,246 2,066 9,608 1,569 

MS 5,688 43,233 1,903 1,751 7,719 1,351 

NC 599 4,547 193 178 690 142 

SC 1,067 8,100 343 316 1,205 253 

TN 3,624 27,555 1,217 1,120 4,974 860 

VA 972 2,775 334 307 359 483 

WV 1,528 11,586 487 448 525 362 

Commercial 

Marine 

(2280) 

Total 28,207 209,972 9,911 9,118 36,275 7,413 

Military Marine VA 110 313 25 23 27 48 

(2283) Total 110 313 25 23 27 48 

AL 3,490 26,339 592 533 1,446 1,354 

FL 1,006 9,969 247 222 605 404 

GA 2,654 26,733 664 598 1,622 1,059 

KY 2,166 21,811 542 488 1,321 867 

MS 2,302 23,267 578 520 1,429 899 

NC 1,638 16,502 410 369 1,001 654 

SC 1,160 11,690 291 261 710 462 

TN 2,626 25,627 633 570 1,439 1,041 

VA 1,186 11,882 1,529 1,375 3,641 492 

WV 1,311 13,224 329 296 808 517 

Locomotives 

(2285) 

Total 19,540 187,044 5,815 5,232 14,022 7,750 

Grand Total 118,739 420,228 22,823 21,170 52,931 24,881 
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Although some of the data utilized was updated, the methodology used to develop the Base F 

2009 and 2018 emissions forecasts for aircraft, locomotives, and CMV is identical to that used 

earlier to develop preliminary 2018 Base 1 (“On the Books”) and 2018 Base 2 (“On the Way”) 

inventories. Briefly, the methodology relies on growth and control factors developed from 

inventories used in support of recent EPA rulemakings, and consists of the following steps: 

(a) Begin with the 2002 base year emission estimates for aircraft, locomotive, and CMV as 

described above (at the State-county-SCC-pollutant level of detail). 

(b) Detailed inventory data (both before and after controls) for these same emission sources 

for 1996, 2010, 2015, and 2020 were obtained from the EPA's Clean Air Interstate Rule 

(CAIR) Technical Support Document (which can be found at 

http://www.epa.gov/cair/pdfs/finaltech01.pdf). Using these data, combined growth and 

control factors for the period 2002-2009 and 2002-2018 were estimated using straight 

line interpolation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This 

is done at the State-county-SCC-pollutant level of detail. 

(c) The EPA growth and control data are matched against the 2002 VISTAS base year data 

using State-county-SCC-pollutant as the match key. Ideally, there would be a one-to-one 

match and the process would end at this point. Unfortunately, actual match results were 

not always ideal, so additional matching criteria were required. For subsequent reference, 

this initial (highest resolution) matching criterion is denoted as the “CAIR-Primary” 

criterion. 

(d) A second matching criterion is applied that utilizes a similar, but higher-level SCC (lower 

resolution) matching approach. For example, SCC 2275020000 (commercial aircraft) in 

the 2002 base year inventory data would be matched with SCC 2275000000 (all aircraft) 

in the CAIR data. This criterion is applied to records in the 2002 base year emissions file 

that are not matched using the “CAIR-Primary” criterion, and is also performed at the 

State-county-SCC-pollutant level of detail. For subsequent reference, this is denoted as 

the “CAIR-Secondary” criterion. At the end of this process, a number of unmatched 

records remained, so a third level matching criterion was required. 

(e) In the third matching step, the most frequently used SCC in the EPA CAIR files for each 

of the aircraft, locomotive, and commercial marine sectors was averaged at the State level 

to produce a “default” State and pollutant-specific growth and control factor for the 

sector. The resulting factor is used as a “default” growth factor for all unmatched 

county-SCC-pollutant level data in each State. In effect, State-specific growth data are 

applied to county level data for which an explicit match between the VISTAS 2002 base 

year data and EPA CAIR data could not be developed. The default growth and control 
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SCCs are 2275020000 (commercial aircraft) for the aircraft sector, 2280002000 

(commercial marine diesel total) for the CMV sector, and 2285002000 (railroad 

equipment diesel total) for the locomotive sector. Matches made using this criterion are 

denoted as “CAIR-Tertiary” matches. 

(f) According to EPA documentation, the CAIR baseline emissions include the impacts of 

the (then proposed) Tier 4 (T4) non-road diesel rulemaking, which implements a low 

sulfur fuel requirement that affects both future CMV and locomotive emissions. 

However, the impacts of this rule were originally intended to be excluded from the initial 

VISTAS 2018 forecast, which was to include only “on-the-books” controls. (The T4 rule 

was finalized subsequent to the development of the preliminary 2018 inventory in March 

of 2004.) Given its final status, T4 impacts were moved into the “on the books” inventory 

for non-road equipment. In addition, since there are no other proposed rules affecting the 

non-road sector between 2002 and 2018, there is no difference between the 2018 “on the 

books” and 2018 “on the way” inventories for the sector; so that only a single forecast 

inventory (for each evaluation year) was developed. Nevertheless, since the algorithms 

developed to produce the VISTAS forecasts were developed when there was a distinction 

between the “on the books” and “on the way” inventories, the distinct algorithms used to 

produce the two inventories have been maintained even though the conceptual 

distinctions have been lost. This approach was taken for two reasons. First, it allowed the 

previously developed algorithms to be utilized without change. Second, it allowed for 

separate treatment of the T4 emissions impact which was important as those impacts 

changed between the proposed and final T4 rules. Thus, previous EPA inventories that 

include the proposed T4 impacts would not be accurate. Therefore, the procedural 

discussion continues to reflect the distinctions between non-T4 and T4 emissions, as 

these distinctions continue to be intrinsically important to the forecasting process. 

Therefore, a second set of EPA CAIR files that excluded the Tier 4 diesel impacts was 

obtained and the same matching exercise described above in steps (b) through (e) was 

performed using these “No T4” files. It is important to note that the matching exercise 

described in steps (b) through (e) cannot simply be replaced because the “No T4” files 

obtained from the EPA include only those SCCs specifically affected by the T4 rule (i.e., 

diesel CMV and locomotives). So in effect, the matching exercise was augmented (rather 

than replaced) with an additional three criteria analogous to those described in steps (c) 

through (e), and these are denoted as the “No T4-Primary,” “No T4-Secondary,” and “No 

T4-Tertiary” criteria. Because they exclude the impacts of the proposed T4 rule, matches 

using the “No T4” criteria supersede matches made using the basic CAIR criteria (as 

described in steps (c) through (e) above). 
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(g) The CAIR matching criteria were overridden for any record for which States provided 

local growth data. Only North Carolina provided these forecasts, as that State has 

provided specific growth factors for airport emissions in four counties. Because the 

provided data were based on forecasted changes in landings and takeoffs at major North 

Carolina airports, the factors were applied only to commercial (SCC 2275020000) and air 

taxi (SCC 2275060000) emissions. Emissions forecasts for military and general aviation 

aircraft operations, as well as all aircraft operations in counties other than the four 

identified in the North Carolina growth factor submission, continued to utilize the growth 

factors developed according to steps (b) through (f) above. Table 2.3-7 presents the 

locally generated growth factors applied in North Carolina. 

Table 2.3-7 Locally Generated Growth Factors for North Carolina 

FIP 2009 Factor 2018 Factor 

37067 0.71 0.84 

37081 0.97 0.89 

37119 1.15 1.01 

37183 0.88 0.81 

Note: 

Growth factor = Year Emissions/2002 Emissions. 

Under CAIR approach, 2009 = 1.16 to 1.17 for all 4 counties. 

Under CAIR approach, 2018 = 1.36 to 1.37 for all 4 counties. 

(h) Using this approach, each State-county-SCC-pollutant was assigned a combined growth 

and control factor using the EPA CAIR forecast or locally provided data. The 22,838 data 

records for aircraft, locomotives, and CMV in the 2002 revised base year emissions file 

were assigned growth factors in accordance with the following breakdown: 

 48 records matched State-provided growth factors, 

 4,179 records matched using the CAIR-Primary criterion, 

 240 records matched using the CAIR-Secondary criterion, 

 7,463 records matched using the CAIR-Tertiary criterion, 

 720 records matched using the No T4-Primary criterion, 

 3,858 records matched using the No T4-Secondary criterion, and 

 6,330 records matched using the No T4-Tertiary criterion. 

(i) Finally, the impacts of the T4 rule as adopted were applied to the grown “non T4” 

emission estimates. The actual T4 emission standards do not affect aircraft, locomotive, 

or CMV directly, but associated diesel fuel sulfur requirements do affect locomotives and 

CMV. Lower fuel sulfur content affects both SO2 and PM emissions. Expected fuel sulfur 
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contents were obtained for each evaluation year from the EPA technical support 

document for the final T4 rule (Final Regulatory Analysis: Control of Emissions from 

Non-road Diesel Engines, EPA420-R-04-007, May 2004). According to that document, 

the average diesel fuel sulfur content for locomotives and CMV is expected to be 408 

ppmW in 2009 and 56 ppmW in 2018. These compare to expected non-T4 fuel sulfur 

levels of 2599 ppmW in 2009 and 2336 ppmW in 2018. Table 2.3-8 uses calculated 

emissions estimates for base and T4 control scenarios to estimate emission 

reduction impacts. 

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

2009 2018

CMV SO2 = Non-T4 SO2 × 0.1569 0.0241

Locomotive SO2 = Non-T4 SO2 × 0.1569 0.0241

CMV PM = Non-T4 PM × 0.8962 0.8762

Locomotive PM = Non-T4 PM × 0.8117 0.7734

However, since the diesel fuel sulfur content assumed for the 2002 VISTAS base year 

inventory, upon which both the 2009 and 2018 inventories were based, is 2500 ppmW, a 

small adjustment to the emission reduction multipliers calculated from the T4 rule is 

appropriate since they are measured relative to modestly different sulfur contents (2599 

ppmW for 2009 and 2336 ppmW for 2018). Correcting for these modest differences 

produces the emission reduction impact estimates relative to forecasts based on the 

VISTAS 2002 inventory shown in Table 2.3-9. 

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

Year Values 

2009 2018

CMV SO2 = Non-T4 SO2 × 0.1632 0.0225

Locomotive SO2 = Non-T4 SO2 × 0.1632 0.0225

CMV PM = Non-T4 PM × 0.9004 0.8685

Locomotive PM = Non-T4 PM × 0.8187 0.7610

These factors were applied directly to the non-T4 emission forecasts to produce the final 

VISTAS 2009 and 2018 emissions inventories for aircraft, locomotive, and CMV. 

The only exception is for Palm Beach County, Florida, where CMV emissions are 

reported as “all fuels” rather than separately by residual and diesel fuel components. To 

estimate T4 impacts in Palm Beach County, the ratio of diesel CMV emissions to total 
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CMV emissions in the remainder of Florida was calculated and the T4 impact estimates 

for Palm Beach County were adjusted to reflect that ratio. Table 2.3-10 shows the 

calculated diesel CMV ratios. 

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

GROWTH BASIS SO2 PM

2009 (1996, 2020 Growth Basis) 0.2410 0.7861 

2009 (1996, 2010, 2015, and 2020 Growth Basis) 0.1279 0.7875 

2018 (1996, 2020 Growth Basis) 0.2432 0.7925 

2018 (1996, 2010, 2015, and 2020 Growth Basis) 0.2624 0.7918 

The differences between the growth bases are discussed in detail below. 

Combining these ratios with the T4 impact estimates for diesel engines, as presented 

above, yields the following impact adjustment factors for Palm Beach County: 

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

GROWTH BASIS

2009 SO2 (19, 20 Growth Basis) 0.7894 [0.1632×0.2410+(1-0.2410)]

2009 SO2 (96, 10, 15, and 20 Growth Basis) 0.8930 [0.1632×0.1279+(1-0.1279)] 

2018 SO2 (96, 20 Growth Basis) 0.7623 [0.0225×0.2432+(1-0.2432)] 

2018 SO2 (96, 10, 15, and 20 Growth Basis) 0.7436 [0.0225×0.2624+(1-0.2624)] 

2009 PM (19, 20 Growth Basis) 0.9217 [0.9004×0.7861+(1-0.7861)] 

2009 PM (96, 10, 15, and 20 Growth Basis) 0.9216 [0.9004×0.7875+(1-0.7875)] 

2018 PM (96, 20 Growth Basis) 0.8958 [0.8685×0.7925+(1-0.7925)] 

2018 PM (96, 10, 15, and 20 Growth Basis) 0.8959 [0.8685×0.7918+(1-0.7918)]

The differences between the growth bases are discussed in detail below.

Utilizing this approach, emission inventory forecasts for both 2009 and 2018 were developed. As 

indicated in step (b) above, basic growth factors were developed using EPA CAIR inventory data 

for 1996, 2010, 2015, and 2020. From these data, equivalent EPA CAIR inventories for 2002 and 

2009 were developed through linear interpolation of the 1996 and 2010 inventories, while an 

equivalent CAIR inventory for 2018 was developed through linear interpolation of the 2015 and 

2020 inventories. Growth factors for 2009 and 2018 were then estimated as the ratios of the 

CAIR 2009 and 2018 inventories to the CAIR 2002 inventory. 

During the development of the preliminary 2018 VISTAS inventory in March 2004, this process 

yielded reasonable results and exhibited no particular systematic concerns. However, when the 

2009 Base F inventory was developed, significant concerns related to SO2 and PM were 

encountered. Essentially, what was revealed by the Base F 2009 forecast was a series of apparent 
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inconsistencies in the CAIR 2010 and 2015 emission inventories (as compared to the 1996 and 

2020 CAIR inventories) that were masked during the construction of the “longer-term” 

2018 inventory. 

The apparent inconsistencies are best illustrated by looking at the actual data extracted from the 

CAIR inventory files. Note that although a limited example is being presented, the same general 

issue applies throughout the CAIR files. For FIP 01001 (Autauga County, Alabama) and SCC 

2285002000 (Diesel Rail), the CAIR inventories indicate SO2 emission estimates as shown in 

Table 2.3-12. 

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

CAIR Projections 

YEAR TONS 

1996: 15.3445 

2010: 2.7271 

2015: 2.8178 

2020: 16.6232 

Clearly, there is a major drop in emissions between 1996 and 2010, followed by a major increase 

in emissions between 2015 and 2020. Several observations regarding these changes are 

important. First, the CAIR data were reported to exclude the T4 rule, so that the drop in 

emissions should be related to something other than simply a change in diesel fuel sulfur content. 

Second, if the T4 rule impacts were “accidentally” included in the estimates, there should be a 

resultant 90 percent drop in diesel sulfur between 2010 and 2015; so such inclusion is unlikely. 

Third, the rate of growth between 2015 and 2020 (43 percent per year compound or 97 percent 

per year linear) is well beyond any reasonable expectations for rail service; and fuel sulfur 

content during this period is constant both with and without T4. In short, there appeared to be no 

rational explanation for the data, yet the same basic relations are observed for thousands of CAIR 

inventory records. 

For the most part, the issue seems to be centered on SO2 and PM records, which are those 

records primarily affected by the T4 rule. But, as noted above, there does not seem to be any 

pattern of consistency that would indicate that either inclusion or exclusion of T4 rule impacts is 

the underlying cause. Moreover, where they occur, the observed growth extremes generally 

affect both SO2 and PM equally, while one would expect PM effects to be buffered if the T4 rule 

was the underlying cause, since changes in diesel fuel sulfur content will only affect a fraction of 

PM (i.e., sulfate), while directly reducing SO2. 
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The data presented in Figure 2.3-1 illustrates what this meant to the VISTAS forecasting process. 

Figure 2.3-1 depicts the same data presented above for Autauga County, Alabama, but 

normalized so that the interpolated 2002 CAIR emissions estimate equals unity. The “raw” CAIR 

data is depicted by the markers labeled A, B, C, and D. Interpolated data for 2002 and 2009, 

based on 1996 and 2010 CAIR data, is depicted by the markers labeled “i” and “ii.” Interpolated 

data for 2018, based on 2015 and 2020 CAIR data is depicted by the marker labeled “iii.” The 

relationship between marker “iii” and marker “i” is exactly the relationship used to construct the 

preliminary (e.g., pre-Base F) 2018 VISTAS inventory (i.e., a linear growth rate equal to 0.7 

percent per year). Thus, it is easy to see that although there is a major “dip and rise” between 

2002 and 2018, it is essentially masked unless data for intervening years are examined. Since no 

intervening year was examined for the preliminary 2018 inventory, the “dip and rise” was not 

discovered. However, upon the development of the 2009 inventory forecast, the issue became 

obvious, as the marker labeled “ii” readily illustrates. In effect, the 2009 inventory reflected very 

low negative “growth rates” for some SCCs and pollutants relative to the 2002 inventory, while 

the 2018 inventory reflected very high and positive growth rates for those same SCCs and 

pollutants. In effect, the path between 2002 and 2018 that previously looked like the dotted line 

connecting markers “i” and “iii,” now looks like the solid line connecting markers “i”, “ii,” and 

“iii.” For reference purposes, this path is hereafter referred to as the 1996, 2010, 2015, and 2020 

growth basis, since all interpolated data is based on CAIR data for those four years. 

Figure 2.3-1 Impacts of the Apparent CAIR Inventory Discrepancy 

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

1990 1995 2000 2005 2010 2015 2020 2025

Year

Emissions

1

iii

ii

i

D

B C

A

3 2

A,B,C,D = EPA CAIR Data.

i,ii,iii = 96-10-15-20 Interpolations.

1,2,3 = 96-20 Interpolations.

All indicated growth is linear.

i to ii = -9.1%/yr ii to iii = 22.9%/yr

i to iii = 0.7%/yr

1 to 2 to 3 = 0.3%/yr
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In light of the apparent discrepancies inherent in the 1996, 2010, 2015, and 2020 growth basis 

data and the inconsistencies its use would impart into the 2009 and 2018 VISTAS inventories, a 

secondary forecasting method was developed. This second method relies on the apparent 

consistency between the 1996 and 2020 non-T4 CAIR inventories, interpolating equivalent 2002, 

2009, and 2018 inventories solely from these two inventories. In effect, the CAIR inventories for 

2010 and 2015 are ignored. In Figure 2.3-1, this secondary approach is depicted by the data 

points that lie along the lines connecting markers A and D. Markers A and D represent the 1996 

and 2020 CAIR inventories, and the markers labeled 1, 2, and 3 represent the interpolated 2002, 

2009, and 2018 CAIR equivalent inventories. The growth rate between 2009 and 2002 is then 

equal to the ratio of the 2009 and 2002 CAIR inventories, while that between 2018 and 2002 is 

equal to the ratio of the 2018 and 2002 CAIR inventories. For the example data, the resulting 

linear growth estimate is 0.3 percent per year. For reference purposes, this path is hereafter 

referred to as the 1996-2020 growth basis, since all interpolated data are based on CAIR data for 

only those two years. 

It is perhaps worth noting that the only elements of Figure 2.3-1 that have any bearing on the 

VISTAS inventories are the growth rates. The absolute CAIR data are of importance only in 

determining those rates, as all VISTAS inventories were developed on the basis of the VISTAS 

2002 base year inventory, not any of the CAIR inventories. So referring to Figure 2.3-1, the two 

growth options are summarized in Table 2.3-13. 

Table 2.3-13 Growth Options based on CAIR Data 

GROWTH BASIS PERCENT PER YEAR 

1996, 2010, 2015, 2020 Growth Basis: -9.1% per year (linear) between 2002 and 2009 

1996-2020 Growth Basis: +0.3% per year (linear) between 2002 and 2009 

1996, 2010, 2015, 2020 Growth Basis: +22.9% per year (linear) between 2009 and 2018 

1996-2020 Growth Basis: +0.3% per year (linear) between 2009 and 2018 

1996, 2010, 2015, 2020 Growth Basis: +0.7% per year (linear) between 2002 and 2018 

1996-2020 Growth Basis: +0.3% per year (linear) between 2002 and 2018 

Of course, these specific rates are applicable only to the example case (i.e., diesel rail SO2 in 

Autauga County, Alabama), but there are thousands of additional CAIR records that are virtually 

identical from a growth viewpoint. 

While forecast inventories for aircraft, locomotives, and CMV were developed for 2009 and 

2018 using both growth methods, it was ultimately decided to utilize the 1996-2020 growth basis 

for Base F since it provided more reasonable growth rates for 2009. Tables 2.3-14 and 2.3-15 

present a summary of each Base F inventory, while Tables 2.3-16 and 2.3-17 present the 

associated change in emissions for each Base F forecast inventory relative to the Base F 2002 

base year VISTAS inventory. The larger reduction in CMV SO2 emissions in 2009 and 2018 
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(relative to 2002) for Virginia and West Virginia is notable relative to the other VISTAS States, 

but this has been checked and is attributable to a high diesel contribution to total CMV SO2 in 

the 2002 inventories for these two States. 

Figures 2.3-2 through 2.3-13 graphically depict the relationships between the various Base F 

inventories and preliminary 2002 and 2018 projections prepared prior to Base F. There are two 

figures for each pollutant, the first of which presents a comparison of total VISTAS regional 

emission estimates for aircraft, locomotives, and CMV, and the second of which presents total 

VISTAS region emission estimates for locomotives only. This two figure approach is intended to 

provide a more robust illustration of the differences between the various inventories, as some of 

the differences are less distinct when viewed through overall aggregate emissions totals. All of 

the figures include the following emissions estimates: 

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

 The 2002 pre-Base F base year VISTAS emissions inventory (labeled as “2002 

Prelim”), 

 The Base F 2009 VISTAS emissions inventory developed using growth rates derived 

from 1996 and 2020 EPA CAIR data (labeled as “2009”), 

 The Base F 2018 VISTAS emissions inventory developed using growth rates derived 

from 1996 and 2020 EPA CAIR data (labeled as “2018”), and 

 The pre-Base F 2018 VISTAS emissions inventory estimates as developed using 

growth rates derived from 1996, 2010, 2015, and 2020 EPA CAIR data (labeled as 

“2018 Prelim”). 

All 12 figures generally illustrate a reduction in emissions estimates between the 2002 pre-Base 

F emission estimates published in February 2004 (the initial 2002 VISTAS inventory) and the 

2002 Base F emission estimates. This reduction generally results from emission updates reflected 

in the State 2002 CERR submittals used to develop the Base F 2002 base year inventory, 

although the major differences in aggregate PM emission estimates are driven to a greater extent 

by modifications in the methodology used to estimate aircraft PM in the Base F 2002 base year 

inventory (as documented under the base year inventory section of this report). 
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Table 2.3-14 Base F 2009 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

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

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 4,178 202 278 102 19 217 

FL 29,258 10,316 2,812 2,756 928 4,235 

GA 7,635 6,233 1,712 1,678 523 512 

KY 3,075 762 207 203 73 304 

MS 1,765 162 51 50 16 108 

NC 6,551 1,601 436 427 153 644 

SC 7,372 559 446 437 98 975 

TN 8,020 3,096 824 807 268 1,050 

VA 10,994 3,094 1,239 1,214 907 2,892 

WV 1,312 91 28 28 9 74 

Aircraft 

(2275) 

Total 80,159 26,116 8,033 7,704 2,993 11,011 

AL 1,280 8,888 872 802 2,753 768 

FL 6,236 43,198 1,838 1,691 5,864 1,467 

GA 1,097 7,599 317 291 974 256 

KY 7,087 48,039 2,158 1,985 8,350 1,649 

MS 6,074 41,437 1,821 1,676 6,587 1,415 

NC 634 4,386 184 169 584 148 

SC 1,133 7,796 326 300 1,012 264 

TN 3,887 26,333 1,168 1,074 4,512 904 

VA 1,042 2,662 312 286 61 506 

WV 1,638 11,073 455 419 89 381 

Commercial 

Marine 

(2280) 

Total 30,109 201,412 9,450 8,693 30,786 7,759 

Military Marine VA 118 299 23 21 5 50 

(2283) Total 118 299 23 21 5 50 

AL 3,648 23,529 452 406 242 1,279 

FL 1,052 8,905 189 170 101 382 

GA 2,769 24,398 507 456 271 1,003 

KY 2,264 19,597 415 374 221 819 

MS 2,406 20,785 441 397 239 849 

NC 1,712 14,741 313 282 167 618 

SC 1,213 10,443 222 200 119 437 

TN 2,745 23,924 483 435 240 984 

VA 1,236 11,134 1,167 1,050 608 467 

WV 1,369 12,177 251 226 135 489 

Locomotives 

(2285) 

Total 20,412 169,635 4,440 3,995 2,343 7,328 

Grand Total 130,798 397,462 21,946 20,413 36,126 26,148 
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Table 2.3-15 Base F 2018 Aircraft, Locomotive, and Non-Recreational Marine Emissions 

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

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL 4,681 236 345 122 23 245 

FL 34,178 12,147 3,312 3,246 1,093 4,976 

GA 8,939 7,340 2,016 1,976 616 601 

KY 3,602 898 244 239 86 357 

MS 1,986 190 60 58 18 122 

NC 6,728 1,454 400 392 139 615 

SC 8,487 616 493 484 112 1,119 

TN 9,009 3,519 939 921 309 1,187 

VA 12,578 3,528 1,370 1,342 1,063 3,358 

WV 1,484 106 33 33 10 85 

Aircraft 

(2275) 

Total 91,670 30,035 9,213 8,814 3,468 12,666 

AL 1,388 8,464 880 809 2,715 809 

FL 6,684 41,117 1,853 1,705 6,248 1,543 

GA 1,174 7,246 319 293 976 269 

KY 7,703 45,174 2,199 2,023 8,383 1,752 

MS 6,571 39,129 1,850 1,702 6,556 1,498 

NC 679 4,179 185 170 596 155 

SC 1,217 7,406 329 303 1,027 278 

TN 4,225 24,763 1,190 1,095 4,808 960 

VA 1,133 2,517 314 289 9 537 

WV 1,781 10,412 459 422 13 404 

Commercial 

Marine 

(2280) 

Total 32,554 190,407 9,578 8,811 31,330 8,205 

Military Marine VA 128 282 23 21 1 53 

(2283) Total 128 282 23 21 1 53 

AL 3,850 19,917 381 343 34 1,183 

FL 1,110 7,538 159 143 14 353 

GA 2,917 21,395 427 385 38 932 

KY 2,389 16,751 352 317 31 757 

MS 2,540 17,594 372 335 34 785 

NC 1,807 12,478 264 237 24 571 

SC 1,280 8,840 187 168 17 404 

TN 2,897 21,735 407 367 34 910 

VA 1,300 10,173 983 885 86 436 

WV 1,444 10,831 212 190 19 453 

Locomotives 

(2285) 

Total 21,534 147,252 3,744 3,368 333 6,785 

Grand Total 145,885 367,975 22,557 21,015 35,132 27,709 
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Table 2.3-16 Change in Emissions between 2009 and 2002 Base F Inventories (Based on 

Growth Using 1996 and 2020 EPA Inventories)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL +10% +15% +23% +18% +16% +11% 

FL +15% +16% +16% +16% +16% +16% 

GA +15% +16% +16% +16% +16% +16% 

KY +15% +16% +16% +16% +16% +16% 

MS +11% +16% +15% +15% +16% +12% 

NC +8% +3% +4% +4% +3% +5% 

SC +13% +9% +9% +9% +12% +13% 

TN +11% +12% +12% +12% +14% +11% 

VA +13% +12% +9% +9% +15% +14% 

WV +11% +16% +15% +15% +16% +12% 

Aircraft 

(2275) 

Total +13% +14% +14% +13% +15% +14% 

AL +7% -4% -5% -5% -18% +4% 

FL +6% -4% -5% -5% -12% +4% 

GA +6% -3% -5% -5% -17% +4% 

KY +7% -4% -4% -4% -13% +5% 

MS +7% -4% -4% -4% -15% +5% 

NC +6% -4% -5% -5% -15% +4% 

SC +6% -4% -5% -5% -16% +4% 

TN +7% -4% -4% -4% -9% +5% 

VA +7% -4% -7% -7% -83% +5% 

WV +7% -4% -7% -7% -83% +5% 

Commercial 

Marine 

(2280) 

Total +7% -4% -5% -5% -15% +5% 

Military Marine VA +7% -4% -7% -7% -83% +5% 

(2283) Total +7% -4% -7% -7% -83% +5% 

AL +5% -11% -24% -24% -83% -6% 

FL +5% -11% -24% -24% -83% -6% 

GA +4% -9% -24% -24% -83% -5% 

KY +5% -10% -23% -23% -83% -6% 

MS +5% -11% -24% -24% -83% -6% 

NC +5% -11% -24% -24% -83% -6% 

SC +5% -11% -24% -24% -83% -6% 

TN +5% -7% -24% -24% -83% -6% 

VA +4% -6% -24% -24% -83% -5% 

WV +4% -8% -24% -24% -83% -5% 

Locomotives 

(2285) 

Total +4% -9% -24% -24% -83% -5% 

Grand Total +10% -5% -4% -4% -32% +5% 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. 175

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

Growth Using 1996 and 2020 EPA Inventories)

Source State CO NOx PM10 PM2.5 SO2 VOC 

AL +24% +35% +53% +41% +36% +25% 

FL +34% +37% +37% +37% +37% +36% 

GA +35% +37% +37% +37% +37% +36% 

KY +35% +37% +37% +37% +37% +36% 

MS +25% +36% +35% +35% +36% +27% 

NC +10% -6% -5% -5% -6% 0% 

SC +30% +20% +21% +21% +27% +30% 

TN +24% +27% +28% +28% +31% +26% 

VA +29% +28% +20% +20% +35% +33% 

WV +26% +36% +35% +35% +36% +28% 

Aircraft 

(2275) 

Total +29% +31% +30% +30% +33% +31% 

AL +16% -8% -4% -4% -19% +10% 

FL +14% -8% -4% -4% -7% +9% 

GA +13% -8% -5% -5% -17% +9% 

KY +17% -10% -2% -2% -13% +12% 

MS +16% -9% -3% -3% -15% +11% 

NC +13% -8% -4% -4% -14% +9% 

SC +14% -9% -4% -4% -15% +10% 

TN +17% -10% -2% -2% -3% +12% 

VA +17% -9% -6% -6% -98% +11% 

WV +17% -10% -6% -6% -98% +12% 

Commercial 

Marine 

(2280) 

Total +15% -9% -3% -3% -14% +11% 

Military Marine VA +17% -10% -6% -6% -98% +12% 

(2283) Total +17% -10% -6% -6% -98% +12% 

AL +10% -24% -36% -36% -98% -13% 

FL +10% -24% -36% -36% -98% -13% 

GA +10% -20% -36% -36% -98% -12% 

KY +10% -23% -35% -35% -98% -13% 

MS +10% -24% -36% -36% -98% -13% 

NC +10% -24% -36% -36% -98% -13% 

SC +10% -24% -36% -36% -98% -13% 

TN +10% -15% -36% -36% -98% -13% 

VA +10% -14% -36% -36% -98% -11% 

WV +10% -18% -36% -36% -98% -12% 

Locomotives 

(2285) 

Total +10% -21% -36% -36% -98% -12% 

Grand Total +23% -12% -1% -1% -34% +11% 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. 176

118,739

130,798

145,885

129,659

159,122

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

180,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

19,540 20,412

21,534 21,980

23,849

0

5,000

10,000

15,000

20,000

25,000

30,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

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

Figure 2.3-3 Locomotive CO Emissions (Base F)
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. 177

420,228

397,462

367,975

455,067

395,049

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

187,044

169,635

147,252

211,588

167,783

0

50,000

100,000

150,000

200,000

250,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

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

Figure 2.3-5 Locomotive NOx Emissions (Base F) 
Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories 

MACTEC, Inc. 178

22,823 21,946 22,557

100,452

128,715

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

5,815

4,440

3,744

6,118

3,947

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

2002 2009 2018 2002 Prelim 2018 Prelim

T

o

n

s

p

e

r

Y

e

a

r

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

Figure 2.3-7 Locomotive PM10 Emissions (Base F)