i

Technical Support Document (TSD)

for the final Transport Rule

Docket ID No. EPA-HQ-OAR-2009-0491

Emissions Inventory Final Rule TSD

June 28, 2011

U.S. Environmental Protection Agency

Office of Air and Radiation

Office of Air Quality Planning and Standards

Air Quality Assessment Division

Contacts: 

Rich Mason, Alison Eyth, Alexis Zubrow
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TABLE OF CONTENTS

ACRONYMS......................................................................................................................................................IV

LIST OF TABLES..............................................................................................................................................VI

LIST OF FIGURES.......................................................................................................................................... VII

LIST OF APPENDICES .................................................................................................................................VIII

1 INTRODUCTION....................................................................................................................................... 1

2 2005 EMISSION INVENTORIES AND APPROACHES.......................................................................... 4

2.1 2005 NEI POINT SOURCES (PTIPM AND PTNONIPM) .................................................................................... 10

2.1.1 IPM sector (ptipm)......................................................................................................................... 11

2.1.2 Non-IPM sector (ptnonipm) ........................................................................................................... 13

2.2 2005 NONPOINT SOURCES (AFDUST, AG, NONPT) ....................................................................................... 15

2.2.1 Area fugitive dust sector (afdust).................................................................................................... 15

2.2.2 Agricultural ammonia sector (ag) .................................................................................................. 16

2.2.3 Other nonpoint sources (nonpt)...................................................................................................... 19

2.3 FIRES (AVEFIRE)...................................................................................................................................... 21

2.4 BIOGENIC SOURCES (BIOG)....................................................................................................................... 22

2.5 2005 MOBILE SOURCES (ON_NOADJ, ON_MOVES_RUNPM, ON_MOVES_STARTPM, NONROAD, ALM_NO_C3,

SECA_C3)......................................................................................................................................................... 22

2.5.1 Onroad gasoline exhaust cold-start mode PM (on_moves_startpm)................................................ 25

2.5.2 Onroad gasoline exhaust running mode PM (on_moves_runpm)..................................................... 27

2.5.3 Onroad mobile with no adjustments for daily temperature (on_noadj)............................................ 28

2.5.4 Nonroad mobile sources: NMIM-based (nonroad)......................................................................... 28

2.5.5 Nonroad mobile sources: locomotive and non-C3 commercial marine (alm_no_c3)....................... 29

2.5.6 Nonroad mobile sources: C3 commercial marine (seca_c3)........................................................... 31

2.6 EMISSIONS FROM CANADA, MEXICO AND OFFSHORE DRILLING PLATFORMS (OTHPT, OTHAR, OTHON).......... 34

2.7 SMOKE-READY NON-ANTHROPOGENIC INVENTORIES FOR CHLORINE........................................................ 36

3 EMISSIONS MODELING SUMMARY................................................................................................... 37

3.1 KEY EMISSIONS MODELING SETTINGS ....................................................................................................... 38

3.1.1 Spatial configuration ..................................................................................................................... 39

3.1.2 Chemical speciation configuration................................................................................................. 41

3.1.3 Temporal processing configuration................................................................................................ 49

3.2 EMISSIONS MODELING ANCILLARY FILES .................................................................................................. 51

3.2.1 Spatial allocation data................................................................................................................... 51

3.2.2 Chemical speciation ancillary files................................................................................................. 56

3.2.3 Temporal allocation ancillary files................................................................................................. 60

4 DEVELOPMENT OF 2012 AND 2014 BASE-CASE EMISSIONS......................................................... 68

4.1 STATIONARY SOURCE PROJECTIONS: EGU SECTOR (PTIPM)....................................................................... 74

4.2 STATIONARY SOURCE PROJECTIONS: NON-EGU SECTORS (PTNONIPM, NONPT, AG, AFDUST) ....................... 75

4.2.1 Livestock emissions growth (ag, afdust) ......................................................................................... 75

4.2.2 Residential wood combustion growth (nonpt)................................................................................. 76

4.2.3 Gasoline Stage II growth and control (nonpt, ptnonipm)................................................................. 77

4.2.4 Portable fuel container growth and control (nonpt)........................................................................ 78

4.2.5 Aircraft growth (ptnonipm)............................................................................................................ 79

4.2.6 Stationary source control programs, consent decrees & settlements, and plant closures (ptnonipm, 

nonpt) 80

4.2.7 Oil and gas projections in TX, OK, and non-California WRAP states (nonpt) ................................. 85

4.2.8 Future-year VOC Speciation for gasoline-related sources (ptnonipm, nonpt).................................. 86

4.3 MOBILE SOURCE PROJECTIONS ................................................................................................................. 86
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4.3.1 Onroad mobile (on_noadj, on_moves_runpm, on_moves_startpm) ................................................. 87

4.3.2 Nonroad mobile (nonroad)............................................................................................................. 88

4.3.3 Locomotives and Class 1 & 2 commercial marine vessels (alm_no_c3)........................................... 89

4.3.4 Class 3 commercial marine vessels (seca_c3)................................................................................. 91

4.3.5 Future-year VOC Speciation (on_noadj, nonroad) ......................................................................... 92

4.4 CANADA, MEXICO, AND OFFSHORE SOURCES (OTHAR, OTHON, AND OTHPT)............................................... 93

5 SOURCE APPORTIONMENT ................................................................................................................ 94

6 REMEDY CASE ....................................................................................................................................... 94

7 EMISSION SUMMARIES........................................................................................................................ 98

8 REFERENCES........................................................................................................................................ 111
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Acronyms

BAFM Benzene, Acetaldehyde, Formaldehyde and Methanol

BEIS Biogenic Emissions Inventory System

C3 Category 3 (commercial marine vessels)

CAIR Clean Air Interstate Rule

CAMD The EPA‟s Clean Air Markets Division

CAMX Comprehensive Air Quality Model with Extensions

CAP Criteria Air Pollutant

CARB California Air Resources Board

CEM Continuous Emissions Monitoring

CHIEF Clearinghouse for Inventories and Emissions Factors

Cl Chlorine

CMAQ Community Multiscale Air Quality

CMV Commercial marine vessel

CO Carbon monoxide

EGU Electric generating units

EPA Environmental Protection Agency

EMFAC Emission Factor (California‟s onroad mobile model)

EEZ Exclusive Economic Zone

FAA Federal Aviation Administration

FCCS Fuel Characteristic Classification System

FIPS Federal Information Processing Standards

HAP Hazardous Air Pollutant

HCl Hydrochloric acid

Hg Mercury

HGNRVA Natural recycled, volcanic and anthropogenic Hg

HMS Hazard Mapping System

ICI Industrial/Commercial/Institutional (boilers and process heaters)

ICR Information Collection Request 

IMO International Marine Organization

IPM Integrated Planning Model

ITN Itinerant 

MACT Maximum Achievable Control Technology

MMS Minerals Management Service (now known as the Bureau of Energy Management, 

Regulation and Enforcement (BOEMRE)

MOBILE OTAQ‟s model for estimation of onroad mobile emissions factors

MOVES Motor Vehicle Emissions Simulator -- OTAQ‟s model for estimation of onroad mobile 

emissions – replaces the use of the MOBILE model

MSAT2 Mobile Source Air Toxics Rule

NEEDS National Electric Energy Database System

NEI National Emission Inventory

NESHAP National Emission Standards for Hazardous Air Pollutants

NH3 Ammonia

nm nautical mile

NMIM National Mobile Inventory Model

NOAA National Oceanic and Atmospheric Administration

NODA Notice of Data Availability

NONROAD OTAQ‟s model for estimation of nonroad mobile emissions

NOX Nitrogen oxides

OAQPS The EPA‟s Office of Air Quality Planning and Standards
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OTAQ The EPA‟s Office of Transportation and Air Quality

ORD The EPA‟s Office of Research and Development

ORL One Record per Line

PF Projection Factor, can account for growth and/or controls

PFC Portable Fuel Container

PM2.5 Particulate matter less than or equal to 2.5 microns

PM10 Particulate matter less than or equal to 10 microns

ppm Parts per million

RIA Regulatory Impact Analysis

RRF Relative Response Factor

RWC Residential Wood Combustion

RPO Regional Planning Organization

SCC Source Classification Code

SMARTFIRE Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation

SMOKE Sparse Matrix Operator Kernel Emissions

SO2 Sulfur dioxide

SOA Secondary Organic Aerosol

SPPD Sector Policies and Programs Division

TAF Terminal Area Forecast 

TCEQ Texas Commission on Environmental Quality

TSD Technical support document

VOC Volatile organic compounds

VMT Vehicle miles traveled

WRAP Western Regional Air Partnership
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List of Tables

Table 1-1. List of cases run in support of the Final Transport Rule air quality modeling .............1

Table 2-1. Platform sectors used in emissions modeling for the 2005 platform, version 4.2 ........4

Table 2-2. Summary of significant changes between v4 and v4.2 platforms by sector.................7

Table 2-3. 2005 Emissions by Sector: VOC, NOX, CO, SO2, NH3, PM10, PM2.5 ........................9

Table 2-4. SCCs in the afdust platform sector...........................................................................16

Table 2-5. Livestock SCCs extracted from the 2002 NEI to create the ag sector .......................17

Table 2-6. Fertilizer SCCs extracted from the 2002 NEI for inclusion in the “ag” sector ..........19

Table 2-7. Additional TCEQ oil and gas emissions added to the 2005v2 NEI...........................20

Table 2-8. SCCs provided with Oklahoma oil and gas sector emissions....................................21

Table 2-9. Changes to Oklahoma oil and gas emissions............................................................21

Table 2-10. Data sources for onroad mobile sources in the 2005v4 and 2005v4.2 platforms1....23

Table 2-11. SCCs in the 2005 alm_no_c3 inventory compared to the 2002 platform alm sector30

Table 2-12. Adjustment factors to update the 2005 seca_c3 sector emissions for the v4.2 

platform.............................................................................................................................33

Table 2-13. Contiguous U.S. C3 CMV emissions in the 2005v4 and 2005v4.2 platforms .........34

Table 2-14. Summary of the othpt, othar, and othon sectors changes from the 2002 platform ...35

Table 3-1. Key emissions modeling steps by sector. .................................................................38

Table 3-2. Descriptions of the 2005-based platform grids.........................................................40

Table 3-3. Model species produced by SMOKE for CB05 with SOA for CMAQ4.7 and CAMX*

..........................................................................................................................................42

Table 3-4. Integration status of benzene, acetaldehyde, formaldehyde and methanol (BAFM) for 

each platform sector ..........................................................................................................46

Table 3-5. Source-category specific criteria for integrating nonpt SCCs for categories 

comprising 80% of the nonpoint VOC emissions...............................................................47

Table 3-6. Temporal settings used for the platform sectors in SMOKE, v4.2 platform..............50

Table 3-7. U.S. Surrogates available for the 2005v4.2 platform. ...............................................52

Table 3-8. Surrogate assignments to new mobile categories in the 2005v4 platform .................53

Table 3-9. Canadian Spatial Surrogates for 2005-based platform Canadian Emissions (v4.2 

unchanged from v4)...........................................................................................................55

Table 3-10. Differences between two profiles used for commercial marine residual oil ............58

Table 3-11. Differences between two profiles used for coal combustion ...................................58

Table 3-12: PM2.5 speciation profile updates assignments for the v4 platform............................58

Table 3-13. Summary of VOC speciation profile approach by sector for 2005...........................59

Table 3-14. Summary of spatial surrogates, temporal profiles, and speciation profiles used by 

gasoline vehicle types for the onroad parking area-related SCCs........................................63

Table 3-15. Summary of spatial surrogates, temporal profiles, and speciation profiles used by 

diesel vehicle types for the onroad parking area-related SCCs from MOVES2010.............65

Table 4-1. Control strategies and growth assumptions for creating the 2012 and 2014 base-case 

emissions inventories from the 2005 base case ..................................................................71

Table 4-2. Growth factors from year 2005 to future years for Animal Operations.....................76

Table 4-3. Projection Factors for growing year 2005 Residential Wood Combustion Sources...77

Table 4-4. Factors used to project 2005 base-case aircraft emissions to future years .................79

Table 4-5. Summary of Non-EGU Emission Reductions Applied to the 2005 Inventory due to 

Unit and Plant Closures.....................................................................................................81
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Table 4-6. Future-year ISIS-based cement industry annual reductions (tons/yr) for the non-EGU 

(ptnonipm) sector ..............................................................................................................83

Table 4-7. State-level non-MACT Boiler Reductions from ICR Data Gathering .......................83

Table 4-8. National Impact of RICE Controls on 2012 and 2014 Non-EGU Projections...........84

Table 4-9. Impact of Fuel Sulfur Controls on 2014 Non-EGU Projections................................85

Table 4-10. Oil and Gas NOX and SO2 Emissions for 2005, 2012, and 2014 including additional 

reductions due to the RICE NESHAP ................................................................................86

Table 4-11. Factors applied to year 2005 emissions to project locomotives and Class 1 and Class 

2 Commercial Marine Vessel Emissions............................................................................89

Table 4-12. NOX, SO2, and PM2.5 Factors to Project Class 3 Commercial Marine Vessel 

emissions to 2012 and 2014...............................................................................................91

Table 4-13. Future-year Profiles for Mobile Source Related Sources........................................92

Table 6-1. Transport Rule Status of States................................................................................96

Table 7-1. State-level Total NOX Emissions for each Transport Rule Modeling Case in 48 States 

and Washington, D.C. .......................................................................................................99

Table 7-2. State-level Total SO2 Emissions for each Transport Rule Modeling Case in 48 States 

and Washington, D.C. .....................................................................................................100

Table 7-3. State-level Electric Generating Unit Sector NOX Emissions for each Transport Rule 

Modeling Case in 48 States and Washington, D.C. ..........................................................102

Table 7-4. State-level Electric Generating Unit Sector SO2 Emissions for each Transport Rule 

Modeling Case in 48 States and Washington, D.C. ..........................................................104

Table 7-5. Group 1 and Group 2 States NOX Total Emissions for each Transport Rule Modeling 

Case ................................................................................................................................106

Table 7-6. Group 1 and Group 2 States SO2 Total Emissions for each Transport Rule Modeling 

Case ................................................................................................................................108

Table 7-7. Group 1 and Group 2 States NOX EGU Sector Emissions for each Transport Rule 

Modeling Case ................................................................................................................109

Table 7-8. Group 1 and Group 2 States SO2 EGU Sector Emissions for each Transport Rule 

Modeling Case ................................................................................................................110

Table 7-9. 26-State Total and Electric Generating Unit Sector Summer NOX Emissions for each 

Transport Rule Modeling Case ........................................................................................110

List of Figures

Figure 2-1. MOVES exhaust temperature adjustment functions. ...............................................26

Figure 3-1. Air quality modeling domains.................................................................................40

Figure 3-2. Process of integrating BAFM with VOC for use in VOC Speciation ......................45

Figure 3-3. Diurnal Profiles based on road type (use local for “start”) and whether the road is 

urban versus rural..............................................................................................................62

Figure 3-4. Diurnal temporal profile for HDDV 2B through 8B at Parking areas......................62

Figure 4-1. MOVES exhaust temperature adjustment functions for 2005, 2012, and 2014 ........88

Figure 4-2. Tier 2 Fraction of Light Duty Vehicles...................................................................93

Figure 6-1. States Covered by the Final Transport Rule ............................................................95

Figure 6-2. Group 1 and Group 2 States Covered by the Annual PM Component of the Final 

Transport Rule...................................................................................................................96
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List of Appendices

Appendix A:Revisions to 2005 Inventories from Version 4 to Version 4.2

Appendix B: Ancillary Input Data and Parameter Differences between 2005 and Future-year 

Scenarios

Appendix C: SMOKE Input Inventory Data Files used for each Transport Rule Modeling Case

Appendix D: Summary of Future Base Case Transport Rule Non-EGU Control Programs, 

Closures and Projections
1

1 Introduction

This technical support document (TSD) provides the details of emissions data processing done in support of 

the Environmental Protection Agency‟s (EPA) final rulemaking effort for the Federal Transport Rule 

(hereafter referred to as Transport Rule). The Transport Rule air quality modeling results were evaluated 

with respect to the 1997 annual and 2006 24-hour National Ambient Air Quality Standards (NAAQS) for 

particulate matter less than 2.5 microns (PM2.5), as well as the 1997 8-hour ozone NAAQS. 

The emissions and modeling effort for Transport Rule consists of four „complete‟ emissions cases: 2005 base 

case, 2012 base case, 2014 base case, and 2014 remedy (i.e., “control”) case. Table 1-1 provides more 

information on these emissions cases. The purpose of 2005 base case is to provide a 2005 case that is 

consistent with the methods used in the future-year base cases and remedy case. For regulatory applications, 

this case is used with the outputs from the 2012 base case in the relative response factor (RRF) calculations 

to identify future nonattainment and maintenance. For more information on the use of RRFs, please see the 

Air Quality Modeling Final Rule TSD. The outputs of the 2014 remedy case were compared to the outputs 

from the 2014 base case to quantify the benefits of the rule. Not listed in Table 1-1 are source apportionment 

runs that were based on the 2012 base case and used to quantify the contributions of emissions in upwind 

states to the annual average 24-hour PM2.5 and 8-hour ozone concentrations in other states in 2012. For more 

information on the benefits of this rulemaking, please see the Regulatory Impact Assessment for the 

Transport Rule NFR. 

Table 1-1. List of cases run in support of the Final Transport Rule air quality modeling

Case Name

Internal EPA 

Abbreviation Description

2005 base case 2005cs 2005 case created using average-year fires data and an averageyear temporal allocation approach for Electrical Generating Units 

(EGUs); used for computing relative response factors with 2012 

and 2014 scenarios.

2005 evaluation 

case

2005as 2005 case created for air quality model performance evaluation 

that uses actual 2005 and 2005 continuous emissions monitoring 

(CEM) data for EGUs.

2012 base case 2012cs 2012 “baseline” scenario, representing the best estimate for the 

future year without implementation of EGU remedy controls.

2014 base case 2014cs 2014 “baseline” scenario, representing the best estimate for the 

future year without implementation of EGU remedy controls.

2014 Remedy case 2014cs_tr1remedy 2014 EGU remedy or “control” scenario to address significant 

contribution for the 1997 ozone and annual PM standards, and 

2006 daily PM standard.

The air quality modeling platform consists of all the emissions inventories and input ancillary files, along 

with the meteorological, initial condition, and boundary condition files needed to run the air quality model. 

The platform for this rule uses all Criteria Air Pollutants (CAPs) and the following select Hazardous Air 

Pollutants (HAPs): chlorine (CL2), hydrochloric acid or hydrogen chloride (HCl) and benzene, acetaldehyde, 

formaldehyde and methanol. The latter four are also denoted „BAFM‟. The Final Transport Rule modeling 

platform is called the “CAP-BAFM 2005-Based Platform, Version 4.2” platform (we will use the shortened 

name “2005v4.2” in this documentation). 
2

The data used in the 2005 emissions base case are an updated version of the 2005-based air quality modeling 

platform that was used for the Transport Rule Proposal (2005v4). This TSD describes the emissions 

inventory and emissions modeling for the 2005v4.2 version of the platform used for the Final Transport 

Rule, and focuses on the changes made since the 2005v4 platform. The 2005v4 platform is documented at 

the emissions modeling clearinghouse website, http://www.epa.gov/ttn/chief/emch/, under the section 

entitled “2005-Based Modeling Platform” and the subsection entitled “CAP-BAFM 2005-Based Platform

Version 4 (do not use for Mercury)”. It should be noted that this 2005v4.2 platform includes all nonmercury (Hg) updates reflected in the 2005v4.1 platform, which is under the section entitled “CAP-HgBAFM 2005-Based Platform Version 4.1 (use for Mercury)”. 

The 2005v4.2 platform includes both the evolutionary platform changes between 2005v4 and 2005v4.2, as 

well as implementation of inventory changes resulting from the incorporation of comments on the Transport 

Rule Proposal. For details on the emissions inventory-related comments received on the Transport Rule NPR 

and the EPA‟s responses to those, see the document “Emissions Inventories Response to Comments for the 

Transport Rule NFR”. This document is in the Transport Rule docket (EPA-HQ-OAR-2009-0491) and is 

posted on the emissions modeling clearinghouse website listed above. For simplicity, this TSD refers to the 

cumulative changes in both the 2005v4.1 and 2005v4.2 platforms, thus any comparisons made in this 

document will be against data in the 2005v4 platform used in the Transport Rule Proposal. For more 

information on the emissions inventories used for the Transport Rule Proposal, see the document “Federal 

Transport Rule Emissions Inventory for Air Quality Modeling Technical Support Document”, available in 

the Transport Rule docket and on the emissions modeling clearinghouse website specified above.

The underlying 2005 inventories used are most significantly defined by: 1) for point sources: the 2005 

National Emission Inventory (NEI) version 2, and 2) for onroad mobile sources: the Motor Vehicle 

Emissions Simulator with database corrections for diesel toxics (MOVES2010)

(http://www.epa.gov/otaq/models/moves/index.htm). This document describes the approach and data used to 

produce the emission inputs to the air quality model used in the 2005v4.2 platform for the 2005 and futureyear scenarios.

Emissions preparation for the 2005v4.2 platform supports both the Community Multiscale Air Quality 

(CMAQ) model and the Comprehensive Air Quality Model, with extensions (CAMX). Both models support 

modeling ozone (O3), and particulate matter (PM), and require hourly and gridded emissions of chemical 

species from the following inventory pollutants: carbon monoxide (CO), nitrogen oxides (NOX), volatile 

organic compounds (VOC), sulfur dioxide (SO2), ammonia (NH3), particulate matter less than or equal to 10 

microns (PM10), and individual component species for particulate matter less than or equal to 2.5 microns 

(PM2.5). In addition, the CMAQ Carbon Bond 05 (CB05) chemical mechanism with chlorine chemistry, 

which is part of the “base” version of CMAQ, allows explicit treatment of BAFM and includes HAP 

emissions of HCl and CL2. In the platform, BAFM emissions come from either the NEI values for benzene, 

formaldehyde, acetaldehyde and methanol (BAFM) or via speciation of NEI VOC into the component 

species. For the Transport Rule air quality modeling, only the CAMX model was used.

The creation of emission inputs for the 2005v4.2 platform included:

(1) modifying the emission inventories used for the 2005v4 base case,

(2) updating the emissions modeling ancillary files used by the emissions modeling tools, and

(3) applying the emissions modeling tools.

The primary emissions modeling tool used to create the air quality model-ready emissions was the Sparse 

Matrix Operator Kernel Emissions (SMOKE) modeling system (http://www.smoke-model.org/index.cfm). 
3

We used SMOKE version 2.6 to create emissions files for a 36-km national grid, and a 12-km Eastern grid 

for the 2005 base case (also known as the “2005cs_05b” case). 

The 2005v4.2 platform includes a base case for 2005 (2005cs) and a traditional model evaluation case

(2005as). The evaluation case is identical to the base case except that it uses 2005-specific fire emissions 

and 2005 hour-specific continuous emission monitoring (CEM) data for electric generating units (EGUs).

The 2005 base case in the 2005v4.2 platform includes an “average year” scenario for fires and an illustrative 

(rather than year-specific) temporal allocation approach for EGUs to allocate annual 2005 emissions to days 

and hours. This approach to temporal allocation of emissions was used for all base and control cases 

modeled to provide temporal consistency between the years. It is intended to be a conceivable representation 

of temporal allocation of the emissions without tying the approach to a single year. For example, each year 

has different days and different locations with large fires, unplanned EGU shutdowns, and periods of high 

electricity demand. By using a base-case approach such as the one used on 2005v4.2, the temporal and 

spatial aspects of the inventory for these sources are maintained into the future-year modeling. This avoids 

potentially spurious year-specific artifacts in the air quality modeling estimates. The 2005v4.2 platform 

biogenic emissions data is the same as the 2005v4 platform and was held constant between the 2005 case and 

all future-year cases.

The 2005v4.2 platform was developed using the concepts, tools and emissions modeling data from the 

EPA‟s 2005v4 platform, documented by:

ftp://ftp.epa.gov/EmisInventory/2005v4/2005_emissions_tsd_07jul2010.pdf (main document) , 

ftp://ftp.epa.gov/EmisInventory/2005v4/2005_emissions_tsd_appendices_11may2010.pdf (appendices to 

the main document), and http://www.epa.gov/ttn/chief/emch/transport/tr_proposal_emissions_tsd.pdf (future 

year).

The future-year inventories, ancillary files, and detailed projection data used for this modeling are available 

in the Transport Rule docket at EPA-HQ-OAR-2009-0491 as part of the Final Transport Rulemaking. Since 

the data are large, the data files themselves are not posted with online access through the docket. A more 

convenient access location is the 2005 platform section of the EPA Emissions Modeling Clearinghouse 

website (http://www.epa.gov/ttn/chief/emch/index.html#2005). The Final Transport Rule data files are 

provided as a subheading under this main link.

In the remainder of this document, we provide a description of the approaches taken for the emissions

modeling in support of air quality modeling for the Transport Rule. In Section 2, we review the 2005 basecase inventory (2005cs_05b) and provide high–level emissions summaries. Section 3 describes the 

emissions modeling and the ancillary files used with the emission inventories. In Section 4, we describe the 

development of the future year 2012 (2012cs_05b) and 2014 (2014cs_05b) base cases. The 2012 Source 

Tagging scenarios are described in Section 5. The 2014 EGU Transport Rule Remedy (Control) case 

(2014cs_tr1remedy_05b) is discussed in Section 6. In Section 7 we provide data summaries comparing the 

modeling cases, followed by the technical references for this document. Appendices A through D provide 

additional details about specific technical methods. Some additional emission summaries are also provided 

in the Final Transport Rule Regulatory Impact Analysis, Chapter 3.
4

2 2005 Emission Inventories and Approaches

This section describes the 2005 emissions data created for input to SMOKE that is part of the 2005v4.2 

platform. As with the 2005v4 platform, the primary basis for the 2005 stationary source emission inputs is 

the 2005 National Emission Inventory (NEI), version 2, which includes emissions of CO, NOX, VOC, SO2, 

NH3, PM10, PM2.5 and hazardous air pollutants (HAPs). The HAPs we used from this inventory are 

mercury, chlorine (CL2), hydrogen chloride (HCl), benzene, acetaldehyde, formaldehyde, and methanol. We 

began with the same SMOKE-formatted inventory inputs as the 2005v4 platform (the EPA case name: 

2005ck_05b) and made the changes described below.

Documentation for the 2005 NEI can be found at: 

http://www.epa.gov/ttn/chief/net/2005inventory.html#documentation. For inventories outside of the United 

States, which include Canada and Mexico, we used the latest available base-year inventories as discussed in 

Section 2.6. The 2005 NEI includes five sectors: nonpoint (formerly called “stationary area”) sources, point 

sources, nonroad mobile sources, onroad mobile sources, and fires. Because the 2005v4.2 platform includes 

only a base case as opposed to a model evaluation case, the day-specific wildfire and prescribed burning data 

from the 2005 NEI was not used; rather an average fire inventory is used for both base and future years. In 

addition to the NEI data, biogenic emissions and emissions from the Canadian and Mexican inventories are 

included in the 2005v4.2 platform. Some inventories are augmented with other emissions data as explained 

below. 

For the purposes of preparing the air quality model-ready emissions, we split the 2005 emissions inventory 

into “platform” sectors in the same way as was done in the 2005v4 platform. The significance of an 

emissions modeling or “platform” sector is that the data is run through all of the SMOKE programs except 

the final merge (Mrggrid) independently from the other sectors. The final merge program then combines the 

sector-specific gridded, speciated and hourly emissions together to create CMAQ-ready emission inputs. 

These inputs are then converted into emissions that can be used by CAMX, as was needed for the Transport 

Rule modeling.

Table 2-1 presents the sectors in the 2005 platform. The sector abbreviations are provided in italics; these 

abbreviations are used in the SMOKE modeling scripts and inventory file names, and throughout the 

remainder of this document. Table 2-1 does not describe in specific detail the updates in the 2005v4.2 

platform from those in the 2005v4 platform. The specific updates to the 2005v4.2 platform as compared to 

the 2005v4 platform are highlighted in Table 2-2 and discussed in detail later in this section.

Table 2-1. Platform sectors used in emissions modeling for the 2005 platform, version 4.2

Platform Sector: 

short name

2005 NEI 

Sector

Description and resolution of the data input to SMOKE

EGU (also called 

the IPM sector): 

ptipm 

Point 2005v2 NEI point source EGUs mapped to the Integrated Planning 

Model (IPM) model using the National Electric Energy Database 

System (NEEDS) 2006 version 4.10. Day-specific emissions created 

for input into SMOKE. Includes updates from Transport Rule 

comments and evolutionary improvements from 2005v4.

Non-EGU (also 

called the nonIPM sector): 

ptnonipm

Point All 2005v2 NEI point source records not matched to the ptipm sector. 

Includes all aircraft emissions and point source fugitive dust emissions

for which county-specific PM transportable fractions were applied. 

Annual resolution. Includes updates from Transport Rule comments 

and evolutionary improvements from 2005v4.
5

Platform Sector: 

short name

2005 NEI 

Sector

Description and resolution of the data input to SMOKE

Average-fire: 

avefire 

Not 

applicable

Average-year wildfire and prescribed fire emissions, unchanged from 

the 2005v4 platform; county and annual resolution.

Agricultural: ag Nonpoint NH3 emissions from NEI nonpoint livestock and fertilizer application, 

county and annual resolution. Unchanged from the 2005v4 platform.

Area fugitive dust: 

afdust

Nonpoint PM10 and PM2.5 from fugitive dust sources from the NEI nonpoint 

inventory after application of county-specific PM transportable 

fractions. Includes building construction, road construction, paved 

roads, unpaved roads, agricultural dust), county and annual resolution. 

Unchanged from the 2005v4 platform.

Remaining 

nonpoint: nonpt

Nonpoint Primarily 2002 NEI nonpoint sources not otherwise included in other 

SMOKE sectors; county and annual resolution. Also includes 

updated Residential Wood Combustion emissions, year 2005 nonCalifornia WRAP oil and gas Phase II inventory, year 2005 Texas and 

Oklahoma oil and gas inventories, and updates resulting from 

Transport Rule comments. 

Nonroad: 

nonroad

Mobile: 

Nonroad

Monthly nonroad emissions from the National Mobile Inventory 

Model (NMIM) using NONROAD2005 version nr05c-BondBase, 

which is equivalent to NONROAD2008a, since it incorporated Bond

rule revisions to some of the base-case inputs and the Bond rule 

controls did not take effect until later.

NMIM was used for all states except California. Monthly emissions 

for California created from annual emissions submitted by the 

California Air Resources Board (CARB) for the 2005v2 NEI.

locomotive, and 

non-C3 

commercial 

marine: 

alm_no_c3

Mobile: 

Nonroad

Primarily 2002 NEI non-rail maintenance locomotives, and category 1 

and category 2 commercial marine vessel (CMV) emissions sources, 

county and annual resolution. Aircraft emissions are included in the 

Non-EGU sector (as point sources) and category 3 CMV emissions are 

contained in the seca_c3 sector. Includes updates resulting from 

Transport Rule comments.

C3 commercial 

marine: seca_c3

Mobile : 

Nonroad

Annual point source-formatted, year 2005 category 3 (C3) CMV 

emissions, developed for the rule called “Control of Emissions from 

New Marine Compression-Ignition Engines at or Above 30 Liters per 

Cylinder”, usually described as the Emissions Control Area (ECA) 

study (http://www.epa.gov/otaq/oceanvessels.htm). Utilized final 

projections from 2002, developed for the C3 ECA Proposal to the 

International Maritime Organization 

(EPA-420-F-10-041, August 2010). Includes updates resulting from 

Transport Rule comments.

Onroad 

California, 

NMIM-based, and 

MOVES sources 

not subject to 

temperature 

adjustments: 

on_noadj

Mobile: 

onroad

Three, monthly, county-level components:

1) California onroad, created using annual emissions for all pollutants, 

submitted by CARB for the 2005v2 NEI. NH3 (not submitted by 

CARB) from MOVES2010.

2) Onroad gasoline and diesel vehicle emissions from MOVES2010 

not subject to temperature adjustments: exhaust CO, NOX, VOC, 

NH3, benzene, formaldehyde, acetaldehyde, 1,3-butadiene, 

acrolein, naphthalene, brake and tirewear PM, and evaporative 

VOC, benzene, and naphthalene.

3) Onroad emissions for Hg from NMIM using MOBILE6.2, other 

than for California. 
6

Platform Sector: 

short name

2005 NEI 

Sector

Description and resolution of the data input to SMOKE

Onroad cold-start 

gasoline exhaust 

mode vehicle from 

MOVES subject 

to temperature 

adjustments: 

on_moves_startpm

Mobile: 

onroad

Monthly, county-level MOVES2010-based onroad gasoline emissions 

subject to temperature adjustments. Limited to exhaust mode only for 

PM species and naphthalene. California emissions not included. This 

sector is limited to cold start mode emissions that contain different 

temperature adjustment curves from running exhaust (see 

on_moves_runpm sector).

Onroad running 

gasoline exhaust 

mode vehicle from 

MOVES subject 

to temperature 

adjustments: 

on_moves_runpm

Mobile: 

onroad

Monthly, county-level draft MOVES2010-based onroad gasoline 

emissions subject to temperature adjustments. Limited to exhaust 

mode only for PM species and naphthalene. California emissions not 

included. This sector is limited to running mode emissions that 

contain different temperature adjustment curves from cold start 

exhaust (see on_moves_startpm sector).

Biogenic: biog Not 

applicable

Hour-specific, grid cell-specific emissions generated from the 

BEIS3.14 model, including emissions in Canada and Mexico. 

Unchanged from the 2005v4 platform.

Other point 

sources not from 

the NEI: othpt

Not 

applicable

Point sources from Canada‟s 2006 inventory and Mexico‟s Phase III 

1999 inventory, annual resolution. Also includes annual U.S. offshore 

oil 2005v2 NEI point source emissions. Unchanged from the 2005v4 

platform.

Other nonpoint 

and nonroad not 

from the NEI: 

othar

Not 

applicable

Annual year 2006 Canada (province resolution) and year 1999 Mexico 

Phase III (municipio resolution) nonpoint and nonroad mobile 

inventories. Unchanged from the 2005v4 platform.

Other onroad 

sources not from 

the NEI: othon

Not 

applicable

Year 2006 Canada (province resolution) and year 1999 Mexico Phase 

III (municipio resolution) onroad mobile inventories, annual 

resolution. Unchanged from the 2005v4 platform.

The emission inventories in SMOKE input format for the 2005 base case are available at the 2005v4.2

website (see the end of Section 1). The “readme” file provided indicates the particular zipped files associated 

with each platform sector.

Before discussing the specific components of the 2005v4.2 emissions platform, we provide in Table 2-2 a 

summary of the significant differences between the 2005v4 emissions platform and the 2005v4.2 platform. 

The sectors that did not change between 2005v4.2 and 2005v4 are not included in the table and are the 

following: average fire, agriculture, area fugitive dust, biogenic sources, and “other” (i.e. non-US) point, 

nonpoint, nonroad, and onroad sources. 
7

Table 2-2. Summary of significant changes between v4 and v4.2 platforms by sector

Platform Sector Summary of Significant Inventory Differences from V4 to V4.2

IPM sector: ptipm 1) Added or changed ORIS Boiler IDs to some units with missing or incorrect 

values, and for a subset of these, recomputed annual emissions of NOX, SO2 or 

both using 2005 CEM data. Only replaced emissions if 2005 CEM data were 

confirmed to be for the entire year (since some CEMs only run for the summer 

season). A facility-level summary of these changes is provided in Appendix A, 

Table A-1 of the 2005v4.1 TSD: 

http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf.

2) Moved several stacks and units from the ptnonipm sector, assigning ORIS 

facility and boiler codes and matching stack parameters to those provided in 

the future-year IPM emissions. These edits ensure future-year EGUs are not 

double counted and that base year and future-year stack parameters are similar. 

Affected plants are listed in Appendix A, Table A-1.

3) Deleted several units from the inventory that were found to be either double 

counts or closed. Affected plants are listed in Appendix A, Table A-2.

Non-IPM sector: 

ptnonipm

1) Revised 2005 emissions to remove duplicates, improve estimates from 

ethanol plants, and reflect new emissions and controls information 

collected from industry and a state through the Boiler MACT 

Information Collection Request (ICR).

2) Moved several stacks and units from the ptnonipm sector to the ptipm sector

(Appendix A, Table A-1). This edit prevents double counting of EGU 

emissions in the future years. 

3) Deleted several units from the inventory that were found to be either double 

counts or closed. Affected plants are listed in Appendix A, Table A-2.

4) Revised emissions in several states using improved information obtained 

from Transport Rule comments. 

Remaining 

nonpoint sector: 

nonpt

1) Added: year 2005 oil and gas data for Texas and Oklahoma provided by these 

states. Replaced previous Oklahoma oil and gas emissions from this sector 

(SCC 2310000000). No removals for Texas since the new oil and gas 

emissions only cover oil rig emissions that are in the nonroad sector. The

nonroad sector emissions were not removed because they were very small 

compared to the newer Texas oil and gas emissions added to this sector and the 

possibility of double counting was not able to be confirmed by the EPA. 

2) Changed pesticide category to “no-integrate,” thereby using VOC speciation 

(rather than the HAP emissions) to compute the BAFM emissions.

3) Incorporation of Transport Rule comments including: i) replacing Delaware 

fuel combustion, residential wood burning, and open burning, ii) removing 

South Carolina residual oil emissions from industrial boilers, iii) replacing 

Nebraska industrial fuel combustion emissions. State level changes that 

include these impacts are shown in Appendix A, Table A-3.

Nonroad sector: 

nonroad

Added PM to 7 California counties which were found to be 0 in the 2005v4 

platform. Data used came from an earlier version of the 2005 inventory provided 

by CARB, which had the same PM values as the 2005v2 NEI other than in the 

missing counties, for which nonzero PM values were provided.

locomotive, and 

non-C3 

commercial 

marine: 

alm_no_c3

Updated diesel fuel commercial marine vessel emissions in Delaware per Transport 

Rule comments. The impacts of these changes are shown in Appendix A, Table 

A-3.
8

Platform Sector Summary of Significant Inventory Differences from V4 to V4.2

C3 commercial 

marine: seca_c3

1) Revised 2005 emissions reflect the final projections from 2002 developed for 

the category 3 commercial marine vessel Emissions Control Area (ECA) 

Proposal to the International Maritime Organization (EPA-420-F-10-041, 

August 2010).

2) Projected Canada as part of the ECA rather than an “outside the ECA” region, 

using region-specific growth rates. For example, British Columbia emissions 

were projected the same as “North Pacific” growth and control used in 

Washington. Therefore the v4.2 seca_c3 inventories contain Canadian 

province codes.

3) Updated Delaware emissions per Transport Rule comments. 

4) Redefined the spatial extent of state boundaries off-shore from up to 200 

nautical miles to under 10 miles based on Mineral Management Service 

(MMS) state-federal water boundaries data. This item did not change 

emissions but it drastically reduces areas that are assigned to states.

Onroad 

California, 

NMIM-based, and 

MOVES sources 

not subject to 

temperature 

adjustments: 

on_noadj

1) For all states except California: All pollutants and modes (exhaust, tire and 

brake wear) from all vehicle types are now from MOVES2010. In the 2005v4 

platform, only exhaust mode onroad gasoline vehicles, other than motorcycles, 

were included from MOVES in this sector and the rest had been from 

MOBILE6.

2) For California: Replaced NMIM-based NH3 with MOVES2010 emissions for 

California because California does not provide NH3 in its onroad inventory. 

For the 2005v4 platform, we used NH3 from NMIM but since MOVES 

generates all criteria pollutants, we now use MOVES. 

Onroad cold-start 

gasoline exhaust 

mode vehicle from 

MOVES subject 

to temperature 

adjustments: 

on_moves_startpm

For the 2005v4.2 platform, this sector uses MOVES2010 based emissions for all 

exhaust mode onroad gasoline vehicle types including motorcycles. In the v4 

version, motorcycle exhaust mode PM emissions relied on NMIM and were 

therefore in the on_noadj sector, and other exhaust mode gasoline vehicle PM 

emissions used the draft version of MOVES. As with v4, these PM and 

naphthalene cold start mode emissions are subject to grid cell and hourly 

temperature adjustments.

Onroad running 

gasoline exhaust 

mode vehicle from 

MOVES subject 

to temperature 

adjustments: 

on_moves_runpm

Same change as “on_moves_startpm”

Annual emission summaries for 2005v4.2, with comparisons to 2005v4 CAPs emissions by emissions 

modeling sector are provided in Table 2-3. VOC totals are before BAFM speciation (i.e., they are inventory 

VOC emissions, and not the sum of VOC emissions after BAFM speciation.

The emission inventories for input to SMOKE for the 2005 base case are available at the 2005v4 website 

(see the end of Section 1) under the link “Data Files” (see the “2005emis” directory). The inventories 

“readme” file indicates the particular zipped files associated with each platform sector.
9

Table 2-3. 2005 Emissions by Sector: VOC, NOX, CO, SO2, NH3, PM10, PM2.5

Sector short 

name

2005 

VOC [tons/yr]

2005

NOX [tons/yr]

2005 

CO [tons/yr]

2005 

SO2 [tons/yr]

2005

NH3 [tons/yr]

2005

PM10 [tons/yr]

2005

PM2_5 [tons/yr]

V4.2 V4 V4.2 V4 V4.2 V4 V4.2 V4 V4.2 V4 V4.2 V4 V4.2 V4

afdust 8,858,992 same 1,030,391 same

ag 3,251,990 same

alm_no_c3 67,690 same 1,922,723 1,924,925 270,007 same 153,068 154,016 773 same 59,342 59,366 56,666 56,687

seca_c3 (US 

component) 4,580 22,367 130,164 642,088 11,862 53,746 97.485 417,312 11,628 53,580 10,673 49,294

seca_c3 (nonUS 

component)

62,132 18,241 1,801,699 526,760 146,027 42,959 1,085,894 319,200 146,312 43,014 134,604 39,574

nonpt 7,530,578 7,474,512 1,696,902 1,683,490 7,410,946 7,376,314 1,216,362 1,252,645 133,962 134,080 1,349,639 1,349,685 1,079,906 1,076,954

nonroad 2,691,844 same 2,115,408 same 19,502,718 same 197,341 same 1,972 same 211,807 209,100 201,138 198,734

on_noadj 3,949,362 3,123,642 9,142,274 7,203,876 43,356,130 41,647,066 177,977 144,216 156,528 295,203 308,497 170,554 236,927 115,991

on_moves

_runpm

54,071 46,430 49,789 42,753

on_moves_

startpm 22,729 23,607 20,929 21,738

ptipm 41,089 40,950 3,729,161 3,728,190 603,788 601,564 10,380,883 10,381,411 21,995 21,684 602,236 615,095 496,877 508,903

ptnonipm 1,309,895 1,310,085 2,226,250 2,247,228 3,214,833 3,222,221 2,082,159 2,117,649 158,524 159,003 646,373 653,957 433,381 442,656

avefire 1,958,992 same 189,428 same 8,554,551 same 49,094 same 36,777 same 796,229 same 684,035 same

Canada othar11,281,095 same 734,587 same 3,789,362 same 95,086 same 546,034 same 1,666,188 same 432,402 same

Canada othon 270,872 same 524,837 same 4,403,745 same 5,309 same 21,312 same 14,665 same 10,395 same

Canada othpt 447,313 same 857,977 same 1,270,438 same 1,664,040 same 21,268 same 117,669 same 68,689 same

Mexico othar 586,842 same 249,045 same 644,733 same 101,047 same 486,484 same 143,816 same 92,861 same

Mexico othon 183,429 same 147,419 same 1,455,121 same 8,270 same 2,547 same 6,955 same 6,372 same

Mexico othpt 113,044 same 258,510 same 88,957 same 980,359 same 0 same 125,385 same 88,132 same

offshore othpt 51,240 same 82,581 same 89,812 same 1,961 same 0 same 839 same 837 same

1. Canada provided 2006 fires but we did not use them in the 2005 platform (for neither v4.2 nor v4)
10

The remainder of Section 2 provides details about the data contained in each of the 2005 

platform sectors. Different levels of detail are provided for different sectors depending on the 

availability of reference information for the data, the degree of changes or manipulation of the 

data needed for preparing it for input to SMOKE, and whether the 2005v4.2 platform emissions 

changed appreciably since the previously-documented 2005v4 platform.

2.1 2005 NEI point sources (ptipm and ptnonipm)

Point sources are sources of emissions for which specific geographic coordinates (e.g., 

latitude/longitude) are specified, as in the case of an individual facility. A facility may have 

multiple emission points, which may be characterized as units such as boilers, reactors, spray 

booths, kilns, etc. A unit may have multiple processes (e.g., a boiler that sometimes burns 

residual oil and sometimes burns natural gas). Note that this section describes only NEI point 

sources within the contiguous United States. The offshore oil platform (othpt sector) and 

category 3 CMV emissions (seca_c3 sector) are also point source formatted inventories that are 

discussed in Section 2.6 .

After removing offshore oil platforms (othpt sector), we created two platform sectors from the 

remaining 2005v2 NEI point sources for input into SMOKE: the EGU sector – also called the 

Integrated Planning Model (IPM) sector (i.e., ptipm) and the non-EGU sector – also called the 

non-IPM sector (i.e., ptnonipm). This split facilitates the use of different SMOKE temporal 

processing and future-year projection techniques for each of these sectors. The inventory 

pollutants processed through SMOKE for both ptipm and ptnonipm sectors were: CO, NOX, 

VOC, SO2, NH3, PM10, and PM2.5 and the following HAPs: HCl (pollutant code = 7647010), 

and CL2 (code = 7782505). We did not utilize BAFM from these sectors as we chose to speciate 

VOC without any use (i.e., integration) of VOC HAP pollutants from the inventory (integration 

is discussed in detail in Section 3.1.2.1).

The ptnonipm emissions were provided to SMOKE as annual emissions. The ptipm emissions 

for the base case were input to SMOKE as daily emissions. 

Documentation for the development of the 2005 point source NEI v2, is at: 

http://www.epa.gov/ttn/chief/net/2005inventory.html#documentation. A summary of this 

documentation describes these data as follows:

1. Electric generating unit (EGU) emissions are obtained from emissions/heat input from 

the EPA's Acid Rain Program for Continuous Emissions Monitoring System (CEMS) 

reporting. The following approach applied to units in the 2002 NEI that matched to 2005 

CEMS units. For pollutants covered by the CEMS, the 2005 CEMS data were used. For 

CEMS units with pollutants not covered by CEMS (e.g., VOC, PM2.5, HCl) unit-specific 

ratios of 2005 to 2002 heat input were applied to 2002v3 NEI emissions to obtain 2005 

estimates.

2. Non-EGU stationary source development for the 2005 NEI focused on improving the 

following sectors: 
11

a. HAP data received from States and industry to support the MACT program, 

including the recent Risk and Technology Review rulemaking

b. 2005 State, local, and tribal data submitted to the EPA under the Consolidated 

Emissions Reporting Rule (CERR) 

c. HAP data from Toxic Release Inventory (TRI) for missing facilities and 

pollutants 

d. Off-shore platform data from Mineral Management Services (MMS)

The changes made to the 2005v2 NEI point inventory prior to modeling 2005v4 are as follows:

The tribal data, which do not use state/county Federal Information Processing Standards

(FIPS) codes in the NEI, but rather use the tribal code, were assigned a state/county FIPS 

code of 88XXX, where XXX is the 3-digit tribal code in the NEI. We made this change 

because SMOKE requires the 5-digit state/county FIPS code.

Stack parameters were defaulted for some point sources when modeling in SMOKE. 

SMOKE uses an ancillary file, called the PSTK file that provides default stack 

parameters by SCC code to either gap fill stack parameters if they are missing in the NEI,

or to correct stack parameters if they are outside the ranges specified in SMOKE as 

acceptable values. The SMOKE PSTK file is contained in the ancillary file directory of 

the 2005v4 website (see the end of Section 1).

We applied a transport fraction to all SCCs that we identified as PM fugitive dust, to 

prevent the overestimation of fugitive dust impacts in the grid modeling as described in 

Section 2.2.1.

There are several changes made to the ptipm and ptnonipm sectors for the 2005v4.2 platform that 

were briefly discussed in Table 2-2. One of these changes involved reassigning stacks, units and 

facilities from the ptnonipm sector to the ptipm sector because it was determined that these 

sources were reflected in the future-year IPM data. By moving these sources from ptnonipm to 

ptipm, we prevent their being double counted in future-year emissions processing. These 

changes and other updates in the ptipm and ptnonipm sectors for 2005v4.2 are discussed in the 

following sections.

2.1.1 IPM sector (ptipm)

The ptipm sector contains emissions from EGUs in the 2005v2 NEI point inventory that we were 

able match to the units found in the NEEDS database. While we originally used version 3.02 of 

NEEDS to split out the ptipm sector for v4 of the platform, there were no changes to the 

mapping when we moved to NEEDs version 4.10

(http://www.epa.gov/airmarkets/progsregs/epa-ipm/index.html). The IPM model provides 

future-year emission inventories for the universe of EGUs contained in the NEEDS database. As 

described below, this matching was done (1) to provide consistency between the 2005 EGU 

sources and future-year EGU emissions for sources which are forecasted by IPM and (2) to avoid 

double counting in projecting point source emissions.

The 2005v4 platform document provides additional details on how the 2005 NEI point source 

inventory was split into the ptipm and ptnonipm sectors. 
12

Creation of temporally resolved emissions for the ptipm sector

Another reason we separated the ptipm sources from the other sources was due to the difference 

in the temporal resolution of the data input to SMOKE. For the base-case 2005 run, the ptipm 

sector uses daily emissions input into SMOKE. The daily emissions are computed from the 

annual emissions. First, we allocate annual emissions to each month (this process occurs outside 

of SMOKE). To do this, we created state-specific, three-year averages of 2004-2006 CEM data. 

These average annual-to-month factors were assigned to sources by state. To allocate the 

monthly emissions to each day, we used the 2005 CEM data to compute state-specific month-today factors, averaged across all units in each state. The resulting daily emissions were input into 

SMOKE. The daily-to-hourly allocation was performed with SMOKE using diurnal profiles. 

The development of these diurnal ptipm-specific profiles, which are considered ancillary data for 

SMOKE, is described in Section 3.2.3.

Ptipm updates from the 2005v4 platform used in creating the 2005v4.2 platform

We started with the same ptipm/ptnonipm split as was used for the v4 platform; however, 

we changed some emissions values based on updates we made to some ORIS identifiers 

in the ptipm file. For a subset of the units for which we added or changed ORIS 

identifiers, we recomputed annual emissions for SO2, NOX or both using the CEMS data 

available at the EPA‟s data and maps website.2 Facility-level impacts of these changes 

are provided in Appendix A, Table A-1 of the 2005v4.1 TSD: 

http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf.

Several sources in the 2005v4 ptnonipm inventory were found to be EGU emissions that 

were either found in the future-year IPM inventories or determined to have closed 

between 2005 and the future years. If these emissions were retained in the ptnonipm 

sector, then future-year projections would either double-count these EGU emissions, or 

incorrectly not close these units; in both cases, future-year EGU emissions were inflated 

in the 2005v4 platform. Therefore, we reassigned these known EGU emissions to the 

ptipm sector. In situations where emissions were moved from ptnonipm to ptipm and 

these sources were not closed in the future (they were in the future-year IPM inventories), 

facility, and unit identifier codes were changed to match IPM codes, and more 

importantly, ORIS facility and boiler identifier codes were also changed to match IPM 

codes and hence, the CEMS data base. Facilities and units that were moved from the 

ptnonipm to ptipm sector for 2005v4.2 are provided in Appendix A, Table A-1.

Several units and facilities in the 2005v4 ptipm inventory were found to be either double 

counts, or were determined to have closed prior to 2005. In most cases, these deletions 

were for closures at facilities reported in the 2002 NEI that were not updated in the 2005 

NEI as closed. These changes are detailed in Appendix A, Table A-2.

 

2

http://camddataandmaps.epa.gov/gdm/index.cfm?fuseaction=emissions.wizard
13

2.1.2 Non-IPM sector (ptnonipm)

The non-IPM (ptnonipm) sector contains all 2005v2 NEI point sources that we did not include in 

the IPM (ptipm) sector.

3

 The ptnonipm sector contains fugitive dust PM emissions from 

vehicular traffic on paved or unpaved roads at industrial facilities or coal handling at coal mines.

4

 

Prior to input to SMOKE, we reduced the fugitive dust PM emissions to estimate the emissions 

that remain aloft by applying county-specific fugitive dust transportable fraction factors. This is 

discussed further in Section 2.2.1.

For some geographic areas, some of the sources in the ptnonipm sector belong to source 

categories that are contained in other sectors. This occurs in the inventory when states, tribes or 

local programs report certain inventory emissions as point sources because they have specific 

geographic coordinates for these sources. They may use point source SCCs (8-digit) or nonpoint, onroad or nonroad (10-digit) SCCs. In the 2005 NEI, examples of these types of sources 

include: aircraft emissions in all states, waste disposal emissions in several states, firefighting 

training in New Mexico, several industrial processes and solvent utilization sources in North 

Carolina and Tennessee, livestock (i.e., animal husbandry) in primarily Kansas and Minnesota, 

and petroleum product working losses.

The modifications between the published 2005v2 NEI and the 2005v4 ptnonipm inventory we 

used for modeling are summarized here: 

Ptnonipm changes from the original 2005v2 inventory for the v4 platform development

Removed duplicate annual records. We did not delete some apparent duplicates because 

they were in fact covering different parts of the year (i.e., the emissions in the inventory 

file were sub-annual).

Removed a source with a state/county FIPS code of 30777; the “777” county FIPS 

represents portable facilities that move across counties, but is not currently a valid 

state/county FIPS code in the SMOKE ancillary file “COSTCY”. This Montana FIPS 

code was located in northern Wyoming and contained very small emissions.

Dropped sources with coordinates located well into the oceans or lakes.

Fixed the coordinates for several larger sources that had a state/county FIPS code 

mismatch with their inventory coordinates greater than 10 km and emissions greater than 

10 tons per year of either NOX, VOC, SO2, or 5 tons/yr of PM2.5. These corrections were 

limited to a small number of plants in Arizona, Indiana, Kentucky, Ohio, and Virginia.

In addition to the ptnonipm inventory updates implemented in the 2005v4 platform, we applied 

the following updates in the 2005v4.2 ptnonipm sector:

 

3 Except for the offshore oil and day-specific point source fire emissions data which are included in separate sectors, 

as discussed in sections 2.6 and 2.3.1, respectively. 

4

Point source fugitive dust emissions, which represent a very small amount of PM, were treated the same way in the 

2002 platform but were treated as a separate sector in the 2001 Platform. 
14

Ptnonipm updates from 2005v4 platform used in creating the 2005v4.2 platform

As discussed in Section 2.1.1, several sources in the 2005v4 ptnonipm inventory were 

found to be EGU emissions that were either found in the future-year IPM inventories or 

determined to have closed between 2005 and the future years. Therefore, we reassigned 

these known EGU emissions to the ptipm sector; these are provided in Appendix A, 

Table A-1.

Several units and facilities in the 2005v4 ptnonipm inventory were found to be either 

double counts, or were determined to have closed prior to 2005. In most cases, these 

deletions were for closures at facilities reported in the 2002 NEI that were not updated in 

the 2005 NEI as closed. 

Evolutionary inventory updates and updates from the Transport Rule comments were 

applied to several facilities. A list of all facilities with updated or deleted ptnonipm 

emissions between 2005v4 and 2005v4.2 is provided in Appendix A. One of the most 

significant evolutionary updates was incorporating the PM condensable portion of 

emissions to the Clarion Steel Plant in Allegheny County Pennsylvania 

(PLANTID=4200300032), where by-product Coke Manufacturing, quenching PM 

condensable emissions were augmented, increasing total plant-level PM2.5 emissions 

from under 500 annual tons in the 2005v4 platform to approximately 2,000 annual tons in 

the 2005v4.2 platform.

We added the North Dakota ADM facility (FIPS code = 38067) that was in the 2005v1 

NEI but was missing from the 2005v2 NEI and was not determined to have shut down. 

The 2002-based emissions were added to the ptnonipm file, since 2005 data were not 

available.

We added an inventory of 2005 ethanol plants using plant names and data provided by 

the EPA‟s Office of Transportation and Air Quality for use in a previous modeling effort 

(Renewable Fuel Standards 2), which included these with the 2005v1 inventory. The list 

below includes only the ethanol plants that were used in the previous modeling effort but 

were missing from the 2005v2 NEI.

State/County FIPS 

code Plant Name

CO 

(tons/yr

)

NOX 

(tons/yr

)

PM10 

(tons/yr

)

PM2.5 

(tons/yr

)

SO2 

(tons/yr

)

VOC 

(tons/yr

)

06065 Golden Cheese Company of CA 10 30 12 1 39 14

13205

Wind Gap Farms (Anheuser/Miller 

Brewery) 1 2 1 0 3 1

19033 Golden Grain Energy LLC 147 424 170 15 540 201

19035 Little Sioux Corn Processors 184 534 213 19 679 252

19055 Permeate Refining 3 9 4 0 12 4

19057 Big River Resources, LLC 109 315 126 13 401 149

19083 Hawkeye Renewables, LLC 115 333 133 14 424 158

19093 Quad-County Corn Processors 57 164 65 7 208 77

19167 Siouxland Energy & Livestock Coop (SELC) 209 606 243 26 772 287

21047 Commonwealth Agri-Energy, LLC 46 133 53 5 170 63

31047 Cornhusker Energy Lexington (CEL) 25 73 29 3 93 34

31145 SW Energy, LLC. 42 121 49 5 154 57

35041 Abengoa Bioenergy Corporation 10 30 12 1 39 14

46005 Heartland Grain Fuels, LP 0 1 0 0 1 0
15

46109 North Country Ethanol (NCE) 63 182 73 7 231 86

19109 Global Ethanol 29 85 34 3 108 40

20055 Reeve Agri-Energy 52 152 61 6 193 72

TOTAL TONS 1,104 3,195 1,278 127 4,066 1,510

2.2 2005 nonpoint sources (afdust, ag, nonpt)

The 2005v2 NEI typically used the same values for nonpoint emissions as were found in the 

2002 NEI. This modeling platform took a similar approach, with a couple of notable exceptions 

discussed in Section 2.2.3. We created several sectors from the 2002 nonpoint NEI. We 

removed the nonpoint tribal-submitted emissions to prevent possible double counting with the 

county-level emissions. Because the tribal nonpoint emissions are small, we do not anticipate 

these omissions having an impact on the results at the 36-km and 12-km scales used for this 

modeling. The documentation for the nonpoint sector of the 2005 NEI is available at: 

http://www.epa.gov/ttn/chief/net/2005inventory.html 

In the rest of this section, we describe in more detail each of the platform sectors into which we 

separated the 2005 nonpoint NEI, and the changes we made to these data. We will refer to the 

2002 platform documentation for sectors that did not change.

2.2.1 Area fugitive dust sector (afdust)

The emissions for this sector are unchanged from the 2005v4 platform, and the documentation is 

repeated here for convenience. However, we changed the temporal allocation of the emissions to 

account for day-of-week variation. In particular, we used updated dust profiles that are 

consistent with the activity related to non-dust profiles for similar processes. The processes and 

profiles updated are provided in Pouliot, et. al., 2010. In previous modeling, all days within the 

same month had the same emissions.

The area-source fugitive dust (afdust) sector contains PM10 and PM2.5 emission estimates for 

2002 NEI nonpoint SCCs identified by the EPA staff as dust sources. This sector is separated 

from other nonpoint sectors to make it easier to apply a “transport fraction,” which reduces 

emissions to reflect observed diminished transport from these sources at the scale of our 

modeling. Application of the transport fraction prevents the overestimation of fugitive dust 

impacts in the grid modeling as compared to ambient samples. Categories included in this sector 

are paved roads, unpaved roads and airstrips, construction (residential, industrial, road and total),

agriculture production and all of the mining 10-digit SCCs beginning with the digits “2325.” It 

does not include fugitive dust from grain elevators because these are elevated point sources.

We created the afdust sector from the 2002 NEI based on SCCs and pollutant codes (i.e., PM10

and PM2.5) that are considered “fugitive”. A complete list of all possible fugitive dust SCCs 

(including both 8-digit point source SCCs and 10-digit nonpoint SCCs) is provided at: 

http://www.epa.gov/ttn/chief/emch/dustfractions/tf_scc_list2002nei_v2.xls. However, not all of 

the SCCs in this file are present in the 2002 NEI. The SCCs included in the 2002 NEI that 

comprise the 2005 (and 2002) platform afdust sector (which are a subset of the SCCs in the web 

link) are provided in Table 2-4.
16

Table 2-4. SCCs in the afdust platform sector

SCC SCC Description

2275085000 Mobile Sources;Aircraft;Unpaved Airstrips;Total

2294000000 Mobile Sources;Paved Roads;All Paved Roads;Total: Fugitives

2296000000 Mobile Sources;Unpaved Roads;All Unpaved Roads;Total: Fugitives

2296005000 Mobile Sources;Unpaved Roads;Public Unpaved Roads;Total: Fugitives

2296010000 Mobile Sources;Unpaved Roads;Industrial Unpaved Roads;Total: Fugitives

2311000000 Industrial Processes;Construction: SIC 15 - 17;All Processes;Total

2311010000 Industrial Processes;Construction: SIC 15 - 17;Residential;Total

2311010040 Industrial Processes;Construction: SIC 15 - 17;Residential;Ground Excavations

2311010070 Industrial Processes;Construction: SIC 15 - 17;Residential;Vehicle Traffic

2311020000 Industrial Processes;Construction: SIC 15 - 17;Industrial/Commercial/Institutional;Total

2311020040 Industrial Processes;Construction: SIC 15 - 17;Industrial/Commercial/Institutional;Ground 

Excavations

2311030000 Industrial Processes;Construction: SIC 15 - 17;Road Construction;Total

2325000000 Industrial Processes;Mining and Quarrying: SIC 14;All Processes;Total

2801000000 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Total

2801000002 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Planting

2801000003 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Tilling

2801000005 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Harvesting

2801000007 Miscellaneous Area Sources;Agriculture Production - Crops;Agriculture - Crops;Loading

2805000000 Miscellaneous Area Sources;Agriculture Production - Livestock;Agriculture - Livestock;Total

2805001000 Miscellaneous Area Sources;Agriculture Production - Livestock;Beef cattle - finishing 

operations on feedlots (drylots);Dust Kicked-up by Hooves (use 28-05-020, -001, -002, or -

003 for Waste

Our approach was to apply the transportable fractions by county such that all afdust SCCs in the 

same county receive the same factor. The approach used to calculate the county-specific 

transportable fractions is based on land use data and is described by: 

http://www.epa.gov/ttn/chief/emch/dustfractions/transportable_fraction_080305_rev.pdf

As this paper mentions, a limitation of the transportable fraction approach is the lack of monthly 

variability, which would be expected due to seasonal changes in vegetative cover. Further, the 

variability due to soil moisture, precipitation, and wind speeds is not accounted for by the 

methodology. An electronic version of the county-level transport fractions can be found at: 

http://www.epa.gov/ttn/chief/emch/dustfractions/transportfractions052506rev.xls

The 2002 platform documentation describes an error in which the transportable fraction 

application for PM2.5 was not applied. This error was fixed for the 2005v4.2 platform, and 2005 

PM2.5 afdust emissions are therefore correctly about 43% less than those in the 2002 platform.

2.2.2 Agricultural ammonia sector (ag)

This sector is unchanged from the 2005v4 platform; the documentation is repeated here for 

completeness.

The agricultural NH3 “ag” sector is comprised of livestock and agricultural fertilizer application 

emissions from the nonpoint sector of the 2002 NEI. This sector is unchanged in the 2005 
17

platform. The rest of this section documentation is therefore very similar to that in the 2002 

documentation.

In building this sector we extracted livestock and fertilizer emissions based on the SCC. The 

livestock SCCs are listed in Table 2-5, and the fertilizer SCCs are listed in Table 2-6.

Table 2-5. Livestock SCCs extracted from the 2002 NEI to create the ag sector

SCC SCC Description*

2805000000 Agriculture - Livestock;Total

2805001100 Beef cattle - finishing operations on feedlots (drylots);Confinement

2805001200 Beef cattle - finishing operations on feedlots (drylots);Manure handling and storage

2805001300 Beef cattle - finishing operations on feedlots (drylots);Land application of manure

2805002000 Beef cattle production composite;Not Elsewhere Classified

2805003100 Beef cattle - finishing operations on pasture/range;Confinement

2805007100 Poultry production - layers with dry manure management systems;Confinement

2805007300 Poultry production - layers with dry manure management systems;Land application of manure

2805008100 Poultry production - layers with wet manure management systems;Confinement

2805008200 Poultry production - layers with wet manure management systems;Manure handling and storage

2805008300 Poultry production - layers with wet manure management systems;Land application of manure

2805009100 Poultry production - broilers;Confinement

2805009200 Poultry production - broilers;Manure handling and storage

2805009300 Poultry production - broilers;Land application of manure

2805010100 Poultry production - turkeys;Confinement

2805010200 Poultry production - turkeys;Manure handling and storage

2805010300 Poultry production - turkeys;Land application of manure

2805018000 Dairy cattle composite;Not Elsewhere Classified

2805019100 Dairy cattle - flush dairy;Confinement

2805019200 Dairy cattle - flush dairy;Manure handling and storage

2805019300 Dairy cattle - flush dairy;Land application of manure

2805020001 Cattle and Calves Waste Emissions;Milk Cows

2805020002 Cattle and Calves Waste Emissions;Beef Cows

2805020003 Cattle and Calves Waste Emissions;Heifers and Heifer Calves

2805020004 Cattle and Calves Waste Emissions;Steers, Steer Calves, Bulls, and Bull Calves

2805021100 Dairy cattle - scrape dairy;Confinement

2805021200 Dairy cattle - scrape dairy;Manure handling and storage

2805021300 Dairy cattle - scrape dairy;Land application of manure

2805022100 Dairy cattle - deep pit dairy;Confinement

2805022200 Dairy cattle - deep pit dairy;Manure handling and storage

2805022300 Dairy cattle - deep pit dairy;Land application of manure

2805023100 Dairy cattle - drylot/pasture dairy;Confinement

2805023200 Dairy cattle - drylot/pasture dairy;Manure handling and storage

2805023300 Dairy cattle - drylot/pasture dairy;Land application of manure

2805025000 Swine production composite;Not Elsewhere Classified (see also 28-05-039, -047, -053)

2805030000 Poultry Waste Emissions;Not Elsewhere Classified (see also 28-05-007, -008, -009)

2805030001 Poultry Waste Emissions;Pullet Chicks and Pullets less than 13 weeks old

2805030002 Poultry Waste Emissions;Pullets 13 weeks old and older but less than 20 weeks old

2805030003 Poultry Waste Emissions;Layers

2805030004 Poultry Waste Emissions;Broilers

2805030007 Poultry Waste Emissions;Ducks

2805030008 Poultry Waste Emissions;Geese

2805030009 Poultry Waste Emissions;Turkeys

2805035000 Horses and Ponies Waste Emissions;Not Elsewhere Classified
18

SCC SCC Description*

2805039100 Swine production - operations with lagoons (unspecified animal age);Confinement

2805039200 Swine production - operations with lagoons (unspecified animal age);Manure handling and storage

2805039300 Swine production - operations with lagoons (unspecified animal age);Land application of manure

2805040000 Sheep and Lambs Waste Emissions;Total

2805045000 Goats Waste Emissions;Not Elsewhere Classified

2805045002 Goats Waste Emissions;Angora Goats

2805045003 Goats Waste Emissions;Milk Goats

2805047100 Swine production - deep-pit house operations (unspecified animal age);Confinement

2805047300 Swine production - deep-pit house operations (unspecified animal age);Land application of manure

2805053100 Swine production - outdoor operations (unspecified animal age);Confinement

* All SCC Descriptions begin “Miscellaneous Area Sources;Agriculture Production – Livestock”

The “ag” sector includes all of the NH3 emissions from fertilizer from the NEI. However, the 

“ag” sector does not include all of the livestock ammonia emissions, as there are also significant 

NH3 emissions from livestock in the point source inventory that we retained from the 2002 NEI. 

Note that in these cases, emissions were not also in the nonpoint inventory for counties for which 

they were in the point source inventory; therefore no double counting occurred. Most of the 

point source livestock NH3 emissions were reported by the states of Kansas and Minnesota. For 

these two states, farms with animal operations were provided as point sources using the 

following SCCs5:

30202001: Industrial Processes; Food and Agriculture; Beef Cattle Feedlots; Feedlots 

General

30202101: Industrial Processes; Food and Agriculture; Eggs and Poultry Production;

Manure Handling: Dry

30203099: Industrial Processes; Food and Agriculture; Dairy Products; Other Not 

Classified

There are also livestock NH3 emissions in the point source inventory with SCCs of 39999999

(Industrial Processes; Miscellaneous Manufacturing Industries; Miscellaneous Industrial 

Processes; Other Not Classified) and 30288801 (Industrial Processes; Food and Agriculture;

Fugitive Emissions; Specify in Comments Field). We identified these sources as livestock NH3

point sources based on their facility name. The reason why we needed to identify livestock NH3

in the ptnonipm sector was to properly implement the emission projection techniques for 

livestock sources, which cover all livestock sources, not only those in the ag sector, but also 

those in the ptnonipm sector. 

 

5 These point source emissions are also identified by the segment ID, which is one of the following: “SWINE”, 

“CATTLE”, “DAIRY”, or “PLTRY”. 
19

Table 2-6. Fertilizer SCCs extracted from the 2002 NEI for inclusion in the “ag” sector

2002 SCC 2002 SCC Description*

2801700001 Anhydrous Ammonia

2801700002 Aqueous Ammonia

2801700003 Nitrogen Solutions

2801700004 Urea

2801700005 Ammonium Nitrate

2801700006 Ammonium Sulfate

2801700007 Ammonium Thiosulfate

2801700010 N-P-K (multi-grade nutrient fertilizers)

2801700011 Calcium Ammonium Nitrate

2801700012 Potassium Nitrate

2801700013 Diammonium Phosphate

2801700014 Monoammonium Phosphate

2801700015 Liquid Ammonium Polyphosphate

2801700099 Miscellaneous Fertilizers

* All descriptions include “Miscellaneous Area Sources; Agriculture 

Production – Crops; Fertilizer Application” as the beginning of the 

description.

2.2.3 Other nonpoint sources (nonpt)

Nonpoint sources that were not subdivided into the afdust, ag, or avefire sectors were assigned to 

the “nonpt” sector. 

The 2002 platform documentation describes the creation of the 2002 nonpt sector in great detail, 

but the rest of this section will simply document what has changed for the 2005v4.2 platform. 

Below is a list of changes made from the 2002 platform both for the v4 platform and for the v4.2

platform. Details on the changes to 2002 for the version 4 platform are in the v4 documentation.

Updates to the nonpt sector from 2002 platform made for creation of the nonpt sector of 

the 2005v4 platform

The 2005 platform replaces 2002v3 NEI non-California Western Regional Air 

Partnership (WRAP) oil and gas emissions (SCCs beginning with “23100”) with WRAP 

year 2005 Phase II oil and gas emissions.

Residential wood combustion (RWC) emissions were replaced with data for Oregon and 

New York. This update is consistent with the 2005v2 NEI. 

RWC VOC emissions were recalculated for all states except California to reflect an 

updated emissions factor for VOC from RWC sources. This update is consistent with the 

2005v2 NEI.

We utilized benzene, formaldehyde, acetaldehyde and methanol (BAFM) emissions from 

sources that met the HAP-CAP integration criteria discussed in Section 3.1.2.1 (i.e., the 

“integrate” sources). We removed BAFM from sources that did not meet the integration 

criteria (i.e., the “no-integrate” sources) so that BAFM would not be double counted with 

the BAFM generated via speciation of VOC.
20

Updates from 2005v4 platform used in creating the 2005v4.2 platform

We changed the integration status for pesticide emissions from using the “integrate” case 

to using the “no-integrate” case. The main reason is that there were significant benzene 

emissions from this category in the NEI that was considered incorrect. The NEI benzene 

came from solvent utilization data (Fredonia) for "other markets" for the year 1998. Since 

benzene no longer allowed in pesticides, we chose to eliminate the use of these HAP data 

and use a VOC speciation profile that did not include benzene emissions to be more 

consistent with the changed regulations.

We replaced Delaware fuel combustion (all industrial, commercial, and residential), 

residential wood combustion, and open burning with revised state estimates for NOX, 

SO2, and PM. The impact of this inventory change is shown in Appendix A, Table A-3.

We removed South Carolina residual oil emissions from industrial boilers. We 

determined that these nonpoint emissions were a double count from those in the point 

inventory. Removing these emissions is consistent with the preliminary 2008 NEI data 

submittal. The impact of this inventory change is shown in Appendix A, Table A-3.

We replaced Nebraska industrial fuel combustion emissions with 2005 Central Regional 

Air Planning Association (CENRAP) dataset, version G. The impact of this inventory 

change is shown in Appendix A, Table A-3.

We added oil and gas emissions for Texas and replaced oil and gas emissions with 

updated 2005 data from Oklahoma.

TCEQ Oil and Gas Emissions

The Texas Commission on Environmental Quality (TCEQ) provided 2005 oil and gas emissions 

which we added to the nonpt sector. The emissions were for a single SCC: 2310000220 

Industrial Processes; Oil and Gas Exploration and Production; All Processes; Drill Rigs. The 

TCEQ indicated that these should replace emissions in the nonroad inventory from the 

NONROAD model (drill rigs: SCC=2270010010). Because the nonroad emissions are 

significantly less than the updated nonpt emissions, we did not remove the nonroad emissions. 

Both the TCEQ and related nonroad emissions from the 2005 NEI are summarized in Table 2-7.

Table 2-7. Additional TCEQ oil and gas emissions added to the 2005v2 NEI

Pollutant

TCEQ Emissions 2005, 

added to nonpt

(tons/yr)

NEI 2005 Emissions (nonroad 

inventory), not subtracted

(tons/yr)

CO 15,878 1,396

NH3 3

NOX 42,854 4,704

PM10 3,036 275

PM2.5 2,945 267

SO2 5,977 573

VOC 4,337 340
21

Oklahoma Oil and Gas Emissions

The state of Oklahoma provided and emissions replacement for their 2005 oil and gas sector 

emissions. These data added emissions for the SCCs shown in Table 2-8. 

Table 2-8. SCCs provided with Oklahoma oil and gas sector emissions

SCC SCC Description

31000103 Crude Oil Production;Wells: Rod Pumps*

31000122 Crude Oil Production;Drilling and Well Completion*

31000203 Natural Gas Production;Compressors*

31000215 Natural Gas Production;Flares Combusting Gases >1000 BTU/scf*

31000222 Natural Gas Production;Drilling and Well Completion*

31000227 Gas Production;Glycol Dehydrator Reboiler Still Stack*

31000228 Natural Gas Production;Glycol Dehydrator Reboiler Burner*

31000403 Industrial Processes;Oil and Gas Production;Process Heaters;Crude Oil

31000404 Industrial Processes;Oil and Gas Production;Process Heaters;Natural Gas

31088811 Industrial Processes;Oil and Gas Production;Fugitive Emissions;Fugitive Emissions

* These SCC descriptions start with the preface “

Industrial Processes;Oil and Gas Production”

In addition, this update removed emissions for SCC 2310000000, which is “Industrial 

Processes;Oil and Gas Production: SIC 13;All Processes;Total: All Processes.”

The resultant Oklahoma emissions are shown below in Table 2-9. Note that Oklahoma 

instructed that PM10 emissions were size PM2.5, and therefore no coarse PM (PMC) was 

generated and PM10 is the same as PM2.5

Table 2-9. Changes to Oklahoma oil and gas emissions

Pollutant

2005 Oklahoma Oil and gas 

emissions 2005, removed 

from nonpt (tons/yr)

2005 Oklahoma Oil and 

gas emissions, added to 

nonpt (tons/yr)

CO 11,251 32,821

VOC 104,193 155,908

NOX 66,480 39,668

SO2 0 1,014

PM10 = PM2.5 0 1,918

2.3 Fires (avefire)

The purpose of the avefire sector is to represent emissions for a typical year‟s fires for use in 

projection year inventories, since the location and degree of future-year fires are not known. 

This approach keeps the fires information constant between the 2005 base case and future-year 

cases to eliminate large and uncertain differences between those cases that would be caused by 

changing the fires. Using an average of multiple years of data reduces the possibility that a 
22

single-year's high or low fire activity would unduly affect future-year model-predicted 

concentrations. 

The avefire sector contains wildfire and prescribed burning emissions. It excludes agricultural 

burning and other open burning sources, which are included in the nonpt sector. Generally, their 

year-to-year impacts are not as variable as wildfires and non-agricultural prescribed/managed 

burns.

We use this sector for the 2005 base case, and all future-year cases. Emissions are annual and 

county-level. The same emissions are used in the v4 and v4.2 versions of the 2005-based 

platform. Refer to the 2005v4 platform documentation for more information.

2.4 Biogenic sources (biog)

This sector is unchanged from the 2005v4 platform; the documentation is repeated here for 

completeness.

The biogenic emissions were computed based on 2005 meteorology data using the BEIS3.14 

model within SMOKE. The 2002 platform used the BEIS3.13 model; otherwise, all underlying 

land use data and parameters are unchanged for the 2005 platform.

The BEIS3.14 model creates gridded, hourly, model-species emissions from vegetation and soils. 

It estimates CO, VOC, and NOX emissions for the U.S., Mexico, and Canada. The BEIS3.14 

model is described further in: 

http://www.cmascenter.org/conference/2008/slides/pouliot_tale_two_cmas08.ppt

The inputs to BEIS include:

Temperature data at 2 meters which were obtained from the meteorological input files to 

the air quality model,

Land-use data from the Biogenic Emissions Landuse Database, version 3 (BELD3). 

BELD3 data provides data on the 230 vegetation classes at 1-km resolution over most of 

North America, which is the same land-use data were used for the 2002 platform.

2.5 2005 mobile sources (on_noadj, on_moves_runpm, 

on_moves_startpm, nonroad, alm_no_c3, seca_c3)

For the 2005 platform, as indicated in Table 2-2, we separated the 2005 onroad emissions into 

three sectors: (1) “on_moves_startpm”; (2) “on_moves_runpm”; and (3) “on_noadj”. The 

on_moves_startpm and on_moves_runpm sectors are processed separately because these sectors 

contain gasoline exhaust PM emissions that are subject to mode-specific (start versus running) 

hourly temperature adjustments during SMOKE processing. All pollutants and sources in the 

on_noadj sector are not subject to hourly temperature adjustments. The aircraft, locomotive, and 

commercial marine emissions are divided into two nonroad sectors: “alm_no_c3” and “seca_c3”, 
23

and as previously mentioned, the aircraft emissions are in the non-EGU (ptnonipm) point 

inventory. The seca_c3 emissions are treated as point emissions with an elevated release 

component while all other nonroad emissions are treated as county-specific low-level emissions.

The onroad emissions were primarily based on the publicly released 12/21/2009 version of the

Motor Vehicle Emissions Simulator (MOVES2010) (http://www.epa.gov/otaq/models/moves/). 

MOVES was run with a state/month aggregation using county-average fuels for each state, 

state/month-average temperatures, and national default vehicle age distributions. 2005 Vehicle 

Miles Travelled (VMT), consistent with the 2005v2 NEI, were used.

The major changes between v4.2 and v4 versions of the 2005-based platform are that (1) we used 

a publicly released version of MOVES (MOVES2010), rather than a draft version of MOVES;

(2) we used the MOVES emissions for all vehicle types and modes (as opposed to nonmotorcycle gasoline exhaust vehicles only); (3) MOVES2010 emissions cover all criteria 

pollutants and criteria pollutant precursors (as opposed to draft MOVES that covered only 

exhaust mode PM2.5, VOC, NOX and CO); and (4) we used NH3 from MOVES for California (as 

opposed to NH3 from NMIM) since California-supplied emissions in the 2005v2 NEI do not 

include NH3. It should also be noted that the exhaust PM2.5 from diesel vehicles, which had 

previously come from NMIM but in v4.2 comes from MOVES, are not impacted by cold 

temperatures. In addition, PM brake wear and tire wear mode emissions are now provided in 

MOVES in v4.2; these emissions for both gasoline and diesel vehicles are also not impacted by 

cold temperatures.

Table 2-10 lists the data source for all pollutants, vehicle types, and modes (e.g., exhaust, 

evaporative, brake and tire wear) for all pollutants in the 2005v4 and 2005v4.2 emissions 

modeling platform. Naphthalene, 1-3-butadiene, and acrolein are also provided by MOVES2010 

but were not included in our 2005v4.2 platform.

Table 2-10. Data sources for onroad mobile sources in the 2005v4 and 2005v4.2 platforms

1

Pollutants/vehicles/modes 2005v4 2005v4.2

PM2.5; gasoline exhaust, partially speciated2 Draft MOVES MOVES2010

PM2.5; diesel exhaust, partially speciated2 NMIM MOVES2010

PM2.5, brake and tirewear, unspeciated NMIM MOVES2010

VOC, Benzene (except refueling); gasoline Draft MOVES MOVES2010

VOC, Benzene (except refueling); diesel NMIM MOVES2010

CO, NOX, SO2, NH3, Acetaldehyde, 

Formaldehyde; gasoline

Draft MOVES MOVES2010

CO, NOX, SO2, NH3, Acetaldehyde, 

Formaldehyde; diesel

NMIM MOVES2010

1

For California, 2005v4 and 2005v4.2 use draft MOVES and MOVES2010 (respectively) only for NH3.

2 Exhaust mode PM2.5 species from MOVES consist of: PEC, PSO4 and the difference between PM2.5 and PEC 

(named as “PM25OC”). Procedures to produce the species needed are provided in Appendix D of the 2005v4.1 

TSD: http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf. Diesel partially speciated emissions are 

not impacted by cold temperatures and do not need to be adjusted by gridded temperature as do the gasoline exhaust 

particulate emissions. Brake wear and tire wear PM2.5 emissions were not pre-speciated.
24

Similar to the v4 platform, we used the MOVES data to create emissions by state and month (and 

SCC) and then allocated to counties based on 2005 NMIM-based county-level data. The reason 

for using the state resolution was due to (a) run time issues that made a county run for the entire 

nation infeasible in the timeframe required and (b) incomplete efforts to create a national

database of county-specific inputs to MOVES. For 2005v4.2, no pollutants are obtained from 

the 2005 NMIM runs.

The 2005v2 NEI does not contain the MOVES data that we use for the 2005 platform. Instead, it 

contains onroad and nonroad mobile emissions that we generated using NMIM (EPA, 2005a) for 

all of the U.S. except for California.6 The NMIM data was used only to allocate Californiasubmitted data to road types, to allocate the state-month-SCC MOVES data to counties, and for 

some of the nonroad mobile sources. NMIM relies on calculations from the MOBILE6 and 

NONROAD2005 models as described below, and in the NEI documentation. Inputs to NMIM 

are posted with the 2005 Emission Inventory. 

NMIM creates the onroad and nonroad emissions on a month-specific basis that accounts for 

temperature, fuel types, and other variables that vary by month. Inventory documentation for the 

2005v2 NEI onroad and nonroad sectors is also posted with other 2005 NEI documentation; the 

direct link is: 

ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/2005_mobile_nei_version_2_report.pdf

The residual fuel commercial marine vessel (CMV), also referred to as Category 3 (C3) from the 

2002 platform were replaced with a set of approximately 4-km resolution point source format 

emissions; these were modeled separately as point sources in the “seca_c3” sector for the 2005 

platform. They were updated for v4.2 by using revised 2005 emissions from the category 3 

commercial marine vessel sector to reflect the final projections from 2002 developed for the 

category 3 commercial marine Emissions Control Area (ECA) Proposal to the International 

Maritime Organization (EPA-420-F-10-041, August 2010). Unlike for the v4 platform, we 

projected Canada as part of the ECA, using region-specific growth rates; thus the v4.2 seca_c3 

inventories contain Canadian province codes for near shore emissions.

The nonroad sector, based on NMIM did not change for the v4.2 platform other than for 

California, for which missing PM2.5 emissions for 7 counties was discovered. We corrected 

these PM2.5 emissions by using an earlier version of the 2005 submittal which California had 

provided values for the 7 counties.

The mobile sectors are compiled at a county and SCC resolution, with the exception of the 

seca_c3 sector that uses point sources to map the pre-gridded data to the modeling domain. 

Similar to v4, in v4.2, tribal data from the alm_no_c3 sector have been dropped because we do 

not have spatial surrogate data, and the emissions are small; these data were removed from the 

SMOKE input inventories for 2005.

 

6 Although OTAQ generated emissions using NMIM for California, these were not used in the 2005 NEI version 2, 

but rather were replaced by state-submitted emissions. Since California did not submit NH3, values from MOVES 

were used.
25

Most mobile sectors use the HAP portion on the inventory to provide benzene, acetaldehyde, 

formaldehyde and/or methanol to the modeling inputs through HAP VOC “integration”, as 

described in Section 3.1.2.1. A few categories of nonroad sources (CNG and LPG-fueled 

equipment) do not have the BAFM pollutants in the inventory and therefore utilize the “nointegrate”, “no-hap-use” case, which means VOC from these sources is speciated to provide 

BAFM.

2.5.1 Onroad gasoline exhaust cold-start mode PM (on_moves_startpm)

This sector contains MOVES2010 emissions for PM and naphthalene7for non-California onroad 

gasoline cold-start exhaust. These emissions (and the on_moves_runpm sector discussed in the 

next section) are processed separately from the remainder of the onroad mobile emissions 

because they are subject to hourly temperature adjustments, and these temperature adjustments 

are different for cold-start and running exhaust modes.

Temperature adjustments were applied to account for the strong sensitivity of PM and 

naphthalene exhaust emissions to temperatures below 72oF. Because it was not feasible to run 

MOVES directly for all of the gridded, hourly temperatures needed for modeling, we created 

emissions of PM and naphthalene exhaust at 72oF and applied temperature adjustments after the 

emissions were spatially and temporally allocated. The PM2.5 (and naphthalene) adjustment 

factors were different for starting and running exhaust because these two processes respond 

differently to temperature as shown in Figure 2-1 which shows how these emissions increase 

with colder temperatures. The temperature adjustment factor in this figure is defined in terms of 

primary elemental carbon (PEC) as follows:

PEC = Adjustment Factor x PEC_72

Where: 

PEC = PEC at Temperatures below 72oF

PEC_72 = PEC at 72oF or higher

As seen in the figure, start exhaust emissions increase more than running exhaust emissions as 

temperatures decrease from 72oF. 

Figure 2-1 also shows that the actual adjustments are different for start exhaust and running 

exhaust emissions. The method for applying these adjustments was the same for both start and 

running exhaust sectors: They were applied to SMOKE gridded, hourly intermediate files, based 

upon the gridded hourly temperature data (these same data are also input to the air quality 

model). One result of this approach is that inventory summaries based on the raw SMOKE 

inputs for the on_moves_startpm and on_moves_runpm sectors will not be valid because they 

will not include the temperature adjustments. As a result, the post-processing for temperature 

adjustments included computing the emissions totals at state, county, and month resolution to use 

for summaries.

 

7 Naphthalene is not used in the 2005v4 CAP-BAFM platform, but it is contained in the MOVES emissions.
26

Figure 2-1. MOVES exhaust temperature adjustment functions.

The MOVES output data required pre-processing to develop county-level monthly ORL files for 

input to SMOKE. As stated earlier, the resolution of the MOVES data was state-SCC totals, and

the state level data were allocated to county level prior to input into SMOKE. An additional preprocessing step was for the exhaust PM2.5, for which emissions from MOVES were partially 

speciated. To retain the speciated elemental carbon and sulfate emissions from MOVES, the 

speciation step that is usually done in SMOKE was performed prior to SMOKE, and it was 

modified to allow the temperature adjustments to be applied to only the species affected by 

temperature as described in the list below. Finally, because the start exhaust emissions were 

broken out separately from running exhaust emissions, they were assigned to new SCCs (urban 

and rural parking areas) that allowed for the appropriate spatial and temporal profiles to be 

applied in SMOKE.

A list of the procedures performed to prepare the MOVES data for input into SMOKE is 

provided here. 

i. We allocated state-level emissions to counties using state-county emission ratios by

SCC, pollutant, month, and emissions mode (e.g., evaporative, exhaust, brake wear, 

and tire wear) for each month. The ratios were computed using NMIM 2005 data 

(same data included in the 2005v2 NEI).

ii. We assigned these start exhaust emissions to urban and rural SCCs based on the 

county-level ratio of emissions from urban versus rural local roads from the NMIM

onroad gasoline exhaust mode data. For example, we split light duty gasoline vehicle

(LDGV) start emissions in the state-total MOVES data (assigned SCC 2201001000) 

into urban (2201001370) and rural (2201001350) based on the ratio of LDGV urban 

(2201001330) and rural (2201001210) local roads.

0

10

20

30

40

50

60

70

80

-20 -10 1 11 21 31 41 51 61 71

Temperature (F)

Adjustment Factor

Run Exhaust

Start Exhaust
27

iii. We converted MOVES-based PM2.5 species at 72oF to SMOKE-ready PM species. 

The SMOKE-ready species are listed below and the speciation technique used to 

obtain the SMOKE-ready species is further discussed in Appendix D of the 2005v4.1 

TSD: http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf.

NAPHTH_72: unchanged from MOVES-based file, subject to temperature 

adjustment below 72oF.

PEC_72: unchanged from MOVES-based PM25EC, subject to temperature 

adjustment below 72oF.

POC_72: modified MOVES-based PM25OC to remove metals, PNO3 (computed 

from MOVES-based PM25EC), NH4 (computed from MOVES-based PM25SO4 

and PNO3), and MOVES-based PM25SO4. Subject to temperature adjustment 

below 72oF.

PSO4: unchanged from MOVES-based PM25SO4, not subject to temperature 

adjustment.

PNO3: computed from MOVES-based PM25EC, not subject to temperature 

adjustment.

OTHER: sum of computed metals (fraction of MOVES-based PM25EC) and 

NH4 (computed from PNO3 and PSO4), not subject to temperature adjustment.

PMFINE_72: Computed from OTHER and fraction of POC_72. Subject to 

temperature adjustment below 72 oF.

PMC_72: Computed as fraction of sum of PMFINE_72, PEC_72, POC_72, 

PSO4, and PNO3. Subject to temperature adjustment below 72 oF.

The total MOVES PM emissions are conserved during allocation from states to counties, and 

from the generic total “start” SCCs to the two new parking SCCs that end in “350” and “370”. 

PEC and PSO4 components of PM2.5 emissions are also conserved as they are simply renamed 

from the MOVES species “PM25EC” and “PM25SO4”. However, as seen above, POC, PNO3, 

and PMFINE components involve multiplying the MOVES PM species by components of an 

onroad gasoline exhaust speciation profile described in Appendix D of the 2005v4.1 TSD.

2.5.2 Onroad gasoline exhaust running mode PM (on_moves_runpm)

This sector is identical to the on_moves_startpm sector discussed in Section 2.5.1, but contains 

running exhaust emissions instead of cold-start exhaust emissions. The same pollutants are in 

this sector, and allocation from the MOVES state-level to county-level inventory is a simple 

match by SCC and month to NMIM state-county ratios. The only reason this sector is separated 

from on_moves_startpm is because the temperature adjustments are less extreme for these 

running emissions at colder temperatures when compared to the curve for cold-start emissions 

(Figure 2-1). 
28

2.5.3 Onroad mobile with no adjustments for daily temperature (on_noadj)

This sector consists of the bulk of the onroad mobile emissions, which are not covered by the 

on_moves_startpm and on_moves_runpm sectors. These emissions did not receive any 

temperature adjustments in our processing. There are four sources of data that are pre-processed 

to create two sets of monthly inventories for this sector.

1. MOVES-based onroad gasoline and diesel: These are the MOVES-based emissions

monthly (not including gasoline exhaust mode PM and naphthalene) consisting of the 

following:

a. Gasoline Exhaust: VOC, NOX, CO, SO2, NH3, 1,3-butadiene (106990), 

acetaldehyde (75070), acrolein (107028), benzene (71432), formaldehyde 

(50000), and brake and tire wear PM2.5;

b. Diesel Exhaust: Partially-speciated PM2.5 (that were fully speciated prior to input 

into SMOKE (via Appendix D of the 2005v4.1 TSD: 

http://www.epa.gov/ttn/chief/emch/toxics/2005v4.1_appendices.pdf), VOC, NOX, 

CO, SO2, NH3, 1,3-butadiene (106990), acetaldehyde (75070), acrolein (107028), 

benzene (71432), formaldehyde (50000), and brake and tire wear PM2.5. Because 

diesel exhaust PM does not require the same intermediate temperature 

adjustments as gasoline exhaust PM, diesel exhaust PM can therefore be 

processed with the remaining onroad mobile emissions.

c. Evaporative: Non-refueling VOC, benzene, and naphthalene (91203).

For the pollutants listed, these non-California MOVES emissions encompass the same 

sources as the on_moves_startpm and on_moves_runpm sectors: light duty gasoline 

vehicles, light duty gasoline trucks (1 & 2), and heavy duty gasoline vehicles, but they do 

not require the same intermediate temperature adjustments and can therefore be 

processed with the remaining onroad mobile emissions. These emissions contain both 

running and parking sources and they are pre-processed from state-level to county-level 

much like the on_moves_startpm and on_moves_runpm sectors already discussed. The

preprocessing for the non-PM emissions did not require species calculations because the 

raw MOVES emissions translated directly to SMOKE inventory species.

2. California onroad inventory: California 2005v2 NEI complete CAP/HAP onroad 

inventory. California monthly onroad emissions are year 2005 and are based on 

September 2007 California Air Resources Board (CARB) data from Chris Nguyen. NH3

emissions are from MOVES2010 runs for California. We retained only those HAPs that 

are also estimated by NMIM for onroad mobile sources; all other HAPs provided by 

California were dropped. The California onroad inventory does not use the SCCs for 

Heavy Duty Diesel Vehicles (HDDV) class 6 & 7 (2230073XXX) emissions. California 

does not specify road types, so we used NMIM-based California ratios to break out 

vehicle emissions to the match the more detailed NMIM level.

2.5.4 Nonroad mobile sources: NMIM-based (nonroad)

This sector includes monthly exhaust, evaporative and refueling emissions from nonroad engines

(not including commercial marine, aircraft, and locomotives) that are derived from NMIM for all 

states except California, which were corrected due to an inadvertent omission of PM2.5 from 
29

seven counties. Thus, except for seven counties in California, emissions from this sector did not 

change between the v4 and v4.2 platform versions, and we repeat the documentation here for 

completeness.

NMIM relied on the version of the NONROAD2005 model (NR05c-BondBase) used for the 

marine spark ignited (SI) and small SI engine final rule, published May 2009 (EPA, 2008). For 

2005, the NONROAD2005 model (NR05c-BondBase) is equivalent to NONROAD2008a, since 

it incorporated Bond rule revisions to some of the base-case inputs and the Bond rule controls 

did not take effect until future years. As with the onroad emissions, NMIM provides nonroad 

emissions for VOC by three emission modes: exhaust, evaporative and refueling. Unlike the 

onroad sector, refueling emissions nonroad sources are not dropped from processing for this 

sector.

The EPA/OTAQ ran NMIM to create county-SCC emissions for the 2005v2 NEI nonroad 

mobile CAP/HAP inventory, and similar to on_noadj, we removed California NMIM emissions

that were submitted separately by California. Emissions were converted from monthly totals to 

monthly average-day based on the number of days in each month. Similar to onroad NMIM 

emissions, the EPA default inputs were replaced by state inputs where provided. The NMIM

inventory documentation describes this and all other details of the NMIM nonroad emissions 

development:

ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/2005_mobile_nei_version_2_report.pdf

California nonroad

California monthly nonroad emissions are year 2005 and are based on September 2007 

California Air Resources Board (CARB) data from Chris Nguyen, other than for the PM2.5

missing from 7 counties, which used the March 2007 version. In addition, NH3 emissions are 

from NMIM runs for California because these were not included in the California NEI submittal. 

HAP emissions were estimated by applying HAP-to-CAP ratios computed from California data 

provided in the 2005v2 NEI submittal. We retained only those HAPs that are also estimated by 

NMIM for nonroad mobile sources; all other HAPs were dropped.

The CARB-based nonroad data did not have mode-specific data for VOC (exhaust, evaporative, 

and refueling). To address this inconsistency with other states, we split the annual total 

California data into monthly, mode-specific nonroad emissions for California using the NMIM 

results. Details on this process are documented separately (Strum, 2007). Nonroad refueling 

emissions for California were computed as Gasoline Transport (SCC=2505000120) emissions 

multiplied by a factor of 0.46 (to avoid double counting with portable fuel container (PFC)

emissions in the nonpt sector) and were allocated to the gasoline equipment types based on ratios 

of evaporative-mode VOC. The factor of 0.46 was computed by dividing the NMIM-derived 

California refueling for 2005 by the sum of portable fuel container emissions and NMIM-derived 

refueling for 2005. 

2.5.5 Nonroad mobile sources: locomotive and non-C3 commercial marine 

(alm_no_c3)

The alm_no_c3 sector contains CAP and HAP emissions from locomotive and commercial 

marine vessel (CMV) sources, except for category 3/residual-fuel (C3) CMV and railway 
30

maintenance. In modeling platforms prior to the 2005v4 platform, this sector also contained 

aircraft emissions. Point-source airports were included in the non-EGU point sector (ptnonipm) 

through the 2005v2 NEI point source inventory. The C3 CMV emissions are in the seca_c3 

sector. We note that the “a” in the “alm_no_c3” sector name is now misleading because aircraft 

are no longer in this sector. With the exception of revised Delaware CMV emissions from the 

Transport Rule comments, this sector is unchanged from the v4 platform.

The remaining emissions in the alm_no_c3 sector are year 2002 emissions unchanged from the 

2002 platform; we repeat the 2005v4 documentation for completeness. The SCCs in the 

alm_no_c3 sector are listed in Table 2-11.

Table 2-11. SCCs in the 2005 alm_no_c3 inventory compared to the 2002 platform alm sector

SCC Action SCC Description

2275000000 Emissions removed and replaced by 

aircraft in ptnonipm sector for 2005 

platform

Mobile Sources; Aircraft: All Aircraft Types and 

Operations: Total

2275001000 Emissions removed and replaced by 

aircraft in ptnonipm sector for 2005 

platform

Mobile Sources; Aircraft: Military Aircraft: Total

2275020000 Emissions removed and replaced by 

aircraft in ptnonipm sector for 2005 

platform

Mobile Sources; Aircraft: Commercial Aircraft: 

Total: All Types

2275050000 Emissions removed and replaced by 

aircraft in ptnonipm sector for 2005 

platform

Mobile Sources; Aircraft: General Aviation: 

Total

2275060000 Emissions removed and replaced by 

aircraft in ptnonipm sector for 2005 

platform

Mobile Sources; Aircraft: Air Taxi: Total

2280002100 Retained from 2002 platform Mobile Sources;Marine Vessels, 

Commercial;Diesel;Port emissions

2280002200 Retained from 2002 platform Mobile Sources;Marine Vessels, 

Commercial;Diesel;Underway emissions

2280003100 Emissions removed and replaced by 

seca_c3 inventories for 2005 platform

Mobile Sources;Marine Vessels, 

Commercial;Residual;Port emissions

2280003200 Emissions removed and replaced by 

seca_c3 inventories for 2005 platform

Mobile Sources;Marine Vessels, 

Commercial;Residual;Underway emissions

2280004000 Retained from 2002 platform Mobile Sources;Marine Vessels, 

Commercial;Gasoline;Total, All Vessel Types

2285002006 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line 

Haul Locomotives: Class I Operations

2285002007 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line 

Haul Locomotives: Class II / III Operations

2285002008 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line 

Haul Locomotives: Passenger Trains (Amtrak)

2285002009 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line 

Haul Locomotives: Commuter Lines

2285002010 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Yard 

Locomotives
31

The documentation of the 2002 NEI for the category 1 and 2 (C1/C2) commercial marine and 

locomotive emissions is available at: 

http://www.epa.gov/ttn/chief/net/2002inventory.html#documentation

For modeling purposes, the following additional changes were made to the NEI data for the 

2005v4 platform:

For the 2005v4 platform, we removed C3 CMV SCCs (residual fuel) and aircraft SCCs.

Removed railway maintenance emissions (SCCs 2285002015, 2285004015, and 

2285006015) because these are included in the nonroad NMIM monthly inventories. 

This change was made for the 2002 platform and is retained here in the 2005 platform.

For the purpose of CAP-HAP VOC integration as discussed in Section 3.1.2.1, we

removed benzene, formaldehyde, and acetaldehyde for all sources that we did not 

integrate these HAPs with VOC. As discussed in Section 3.1.2.1, sources are considered 

no-integrate when the source of data between VOC and VOC HAPs is inconsistent or 

VOC analysis of VOC and VOC HAPs indicates the source is not integrated. Although 

our CAP-HAP integration approach also required the removal of methanol for nointegrate sources, the only sources in this sector that included methanol were in 

California, where we used the integrate approach for all sources and therefore did not 

need to remove it.

The 2002 platform documentation goes into greater detail on the locomotives and C1/C2 CMV 

emissions in this sector.

2.5.6 Nonroad mobile sources: C3 commercial marine (seca_c3)

The raw seca_c3 sector emissions data were developed in an ASCII raster format used since the 

Emissions Control Area-International Marine Organization (ECA-IMO) project began in 2005, 

then known as the Sulfur Emissions Control Area (SECA). These emissions consist of large 

marine diesel engines (at or above 30 liters/cylinder) that until very recently, were allowed to 

meet relatively modest emission requirements, often burning residual fuel. The emissions in this 

sector are comprised of primarily foreign-flagged ocean-going vessels, referred to as Category 3 

(C3) CMV ships. The seca_c3 (ECA) inventory includes these ships in several intra-port modes 

(cruising, hoteling, reduced speed zone, maneuvering, and idling) and underway mode and 

includes near-port auxiliary engines. An overview of the ECA-IMO project and future-year

goals for reduction of NOX, SO2, and PM C3 emissions can be found at:

http://www.epa.gov/oms/regs/nonroad/marine/ci/420f09015.htm

The resulting coordinated strategy, including emission standards under the Clean Air Act for new 

marine diesel engines with per-cylinder displacement at or above 30 liters, and the establishment

of Emission Control Areas is at: http://www.epa.gov/oms/oceanvessels.htm.

The raw ECA inventory started as a set of ASCII raster datasets at approximately 4-km 

resolution that we converted to SMOKE point-source ORL input format as described in 

http://www.epa.gov/ttn/chief/conference/ei17/session6/mason.pdf.
32

In summary, this paper describes how the ASCII raster dataset was converted to latitudelongitude, mapped to state/county FIPS codes that extend up to 200 nautical miles (nm) from the 

coast, assigned stack parameters, and how the monthly ASCII raster dataset emissions were used 

to create monthly temporal profiles. Counties in 2005v4 were assigned as extending up to 

200nm from the coast because of this was the distance to the edge of the Exclusive Economic 

Zone (EEZ), a distance that would be used to define the outer limits of ECA-IMO controls for 

these vessels.

The base year ECA inventory is 2002 and consists of these CAPs: PM10, CO, CO2, NH3, NOX, 

SOX (assumed to be SO2), and Hydrocarbons (assumed to be VOC). The EPA developed

regional growth (activity-based) factors that we applied to create the v4 platform 2005 inventory

from the 2002 data.

We computed HAPs directly from the CAP inventory and the calculations are therefore 

consistent; therefore, the entire seca_c3 sector utilizes CAP-HAP VOC integration to use the 

VOC HAP species directly, rather than VOC speciation profiles.

For the v4.2 platform, we chose only to include some HAPs in the seca_c3 sector: benzene, 

formaldehyde, and acetaldehyde. We projected these HAPs using the same VOC factors as used 

in 2005v4:

Benzene = VOC * 9.795E-06

Acetaldehyde = VOC * 2.286E-04

Formaldehyde = VOC * 1.5672E-03

We converted the emissions to SMOKE point source ORL format, allowing for the emissions to 

be allocated to modeling layers above the surface layer. We also corrected FIPS code 

assignments for one county in Rhode Island. All non-US emissions (i.e., in waters considered 

outside of the 200nm EEZ, and hence out of the U.S. and Canadian ECA-IMO controllable 

domain) are simply assigned a dummy state/county FIPS code=98001. The SMOKE-ready data 

have also been cropped from the original ECA-IMO data to cover only the 36-km air quality 

model domain, which is the largest domain used for this effort.

Seca_c3 updates from 2005v4 platform used in creating 2005v4.2 platform

There are several updates to the seca_c3 emissions from 2005v4 to 2005v4.2:

1) Delaware provided updated county total emissions in the Transport Rule comments. 

There are several other changes that impact Delaware state total emissions discussed 

below.

2) Region-specific and pollutant-specific growth factors were updated for the v4.2 platform 

as compared to the v4 platform to be consistent with the final projections from 2002, 

developed for the C3 ECA Proposal to the International Maritime Organization (EPA420-F-10-041, August 2010). The exception to this is Delaware, where county totals 
33

were modified to match those provided in Transport Rule comments. The updated 

factors that we used to project from 2002 to 2005 are presented in Table 2-12. These 

updated 2002 to 2005 projection factors for 2005v.2 are approximately 1% higher for all 

pollutants nationally.

Table 2-12. Adjustment factors to update the 2005 seca_c3 sector emissions for the v4.2

platform.

2005 Adjustments Relative to 2002

Region NOX PM10 PM2.5 VOC (HC) CO SO2

East Coast (EC)11.10524 1.15242 1.15383 1.15256 1.15238 1.15244

Gulf Coast (GC) 1.04056 1.08521 1.08269 1.08467 1.08536 1.08530

North Pacific (NP) 1.07254 1.11354 1.09817 1.11358 1.11318 1.11339

South Pacific (SP) 1.12539 1.17416 1.17257 1.17055 1.17012 1.17565

Great Lakes (GL) 1.04397 1.06264 1.06241 1.06341 1.06280 1.06251

Outside ECA 1.08654 1.13186 1.13186 1.13186 1.13186 1.13186

1 –Delaware emissions were provided for 2005 from Transport Rule comments.

3) In addition to the updated values, near-shore Canadian emissions are now assigned to 

regions whereas previously Canadian sources used the “Outside ECA” factors. Canada 

uses North Pacific, Great Lakes and East Coast depending on where the emissions are. 

For example, near-shore emissions around Vancouver British Columbia are projected 

from 2002 using North Pacific (NP) factors rather than “Outside ECA” factors. 

4) One of the most significant comments from the Transport Rule Proposal was the 

assignment in 2005v4 of state boundaries that extended to the 200nm EEZ distance 

offshore. This had potentially unrealistic impacts on source apportionment modeling (see 

Section 5) because large emissions from shipping lanes far from shore were attributable 

to states whose coastlines were up to 200nm away. For 2005v4.2, we obtained statefederal water boundaries data from the Mineral Management Service (MMS) that 

extended only 3 to 10 miles off shore. It is important to note that the emission values did 

not change as a result of this update, only the state to which those emissions from 3 to 

200 miles offshore were assigned. We retained separate dummy “FIPS” for these 

offshore emissions to ensure that they were projected to future years based on the 

appropriate regional-based factors in Table 2-12.

5) The 2005v4 ECA-based C3 inventory did not delineate between ports and underway (or 

other C3 modes such as hoteling, maneuvering, reduced-speed zone, and idling) 

emissions; therefore, we assigned these emissions to the broad (“total”) SCC for C3 

CMV (2280003000). For 2005v4.2, we used a U.S. ports spatial surrogate dataset to 

simply map the seca_c3 emissions ports or underway SCCs. This had no effect on 

temporal allocation or speciation compared to existing profiles for underway and port C3 

emissions (2280003100 and 2280003200).

The net impact of all the 2005v4.2 changes to U.S. total NOX, SO2, and PM2.5 seca_c3 emissions 

are shown in Table 2-13. Again, with the exceptions of NOX, PM2.5, and most notably, SO2 in 

Delaware, approximately 99% of these differences are solely attributable to reclassification of 

U.S. states to the 3-10 mile MMS boundaries in 2005v4.2 rather than the 200nm EEZ boundaries 

in 2005v4.
34

Table 2-13. Contiguous U.S. C3 CMV emissions in the 2005v4 and 2005v4.2 platforms

Pollutant 2005v4 2005v4.2

NOX 642,000 130,000

PM2.5 49,000 11,000

SO2 417,000 97,000

2.6 Emissions from Canada, Mexico and offshore drilling platforms 

(othpt, othar, othon)

These sectors are unchanged from the 2005v4 platform; the documentation is included here for 

completeness. The emissions from Canada, Mexico, and Offshore Drilling platforms are 

included as part of five sectors: othpt, othar, and othon. 

The “oth” refers to the fact that these emissions are “other” than those in the 2005 NEI, and the 

third and fourth characters provide the SMOKE source types: “pt” for point, “ar” for “area and 

nonroad mobile”, and “on” for onroad mobile. All “oth” emissions are CAP-only inventories. 

Mexico‟s emissions are unchanged from the 2002 platform with one exception –one stack 

diameter was updated (recomputed from stack velocity and flowrate) in the Mexico border states 

point inventory.

For Canada we updated the emissions from the 2002 platform, migrating the data from year 2000 

inventories to year 2006 inventories for the 2005 platform. We migrated to these 2006 Canadian 

emissions despite not receiving future-year emissions, as we were advised by Canada that the

improvement in the 2006 inventory over the 2000 inventory was more significant than the 

undesirable effect of retaining these 2006 emissions for all future-year modeling. We applied 

several modifications to the 2006 Canadian inventories:

i. We did not include wildfires, or prescribed burning because Canada does not include 

these inventory data in their modeling.

ii. We did not include in-flight aircraft emissions because we do not include these for the 

U.S. and we do not have an appropriate approach to include in our modeling.

iii. We applied a 75% reduction (“transport fraction”) to PM for the road dust, agricultural, 

and construction emissions in the Canadian “afdust” inventory. This approach is more 

simplistic than the county-specific approach used for the U.S., but a comparable approach 

was not available for Canada.

iv. We did not include speciated VOC emissions from the ADOM chemical mechanism.

v. Residual fuel CMV (C3) SCCs (22800030X0) were removed because these emissions are 

included in the seca_c3 sector, which covers not only emissions close to Canada but also 

emissions far at sea. Canada was involved in the inventory development of the seca_c3 

sector emissions.

vi. Wind erosion (SCC=2730100000) and cigarette smoke (SCC=2810060000) emissions 

were removed from the nonpoint (nonpt) inventory; these emissions are also absent from 

our U.S. inventory.
35

vii. Quebec PM2.5 emissions (2,000 tons/yr) were removed for one SCC (2305070000) for 

Industrial Processes, Mineral Processes, Gypsum, Plaster Products due to corrupt fields 

after conversion to SMOKE input format. This error should be corrected in a future 

inventory.

viii. Excessively high CO emissions were removed from Babine Forest Products Ltd (British 

Columbia SMOKE plantid=‟5188‟) in the point inventory. This change was made at our 

discretion because the value of the emissions was impossibly large.

ix. The county part of the state/county FIPS code field in the SMOKE inputs were modified 

in the point inventory from “000” to “001” to enable matching to existing temporal 

profiles.

For Mexico we continued to use emissions for 1999 (Eastern Research Group Inc., 2006) which 

were developed as part of a partnership between Mexico's Secretariat of the Environment and 

Natural Resources (Secretaría de Medio Ambiente y Recursos Naturales-SEMARNAT) and 

National Institute of Ecology (Instituto Nacional de Ecología-INE), the U.S. EPA, the Western 

Governors' Association (WGA), and the North American Commission for Environmental 

Cooperation (CEC). This inventory includes emissions from all states in Mexico.

The offshore emissions include point source offshore oil and gas drilling platforms. We used 

updated emissions from the 2005v2 NEI point source inventory. The offshore sources were 

provided by the Mineral Management Services (MMS).

Table 2-14 summarizes the data in the “oth” sectors and indicates where these emissions have 

been updated from the 2002 platform.

Table 2-14. Summary of the othpt, othar, and othon sectors changes from the 2002 platform

Sector Components Changes from 2002 platform

othpt Mexico, 1999, point None

Canada, 2006, point Uses emissions from 2006 National Pollutant 

Release Inventory (NPRI), 3 components:

1) upstream oil and gas sector emissions for all 

CAPs except VOC;

2) VOC sources pre-speciated to CB05 

speciation except for benzene;

3) Remaining point source emissions.

Offshore, 2005, point Uses emissions from 2005 v2 point inventory

othar Mexico, 1999, nonpoint None

Mexico, 1999, nonroad None

Canada, 2006, nonpoint Uses 2006 Canadian aircraft (landing and take-offs 

only), agricultural NH3, fugitive dust, and 

remaining nonpoint inventories.

Canada, 2006, nonroad Uses 2006 Canadian nonroad mobile, non-C3 

marine, and locomotives inventories. 

othon Mexico, 1999, onroad None
36

Sector Components Changes from 2002 platform

Canada, 2006, onroad Uses 2006 Canadian onroad inventory. Emissions 

are given at vehicle type resolution only (i.e., does 

not include road types).

2.7 SMOKE-ready non-anthropogenic inventories for chlorine 

For the ocean chlorine, we used the same data as in the CAP and HAP 2002-based platform. See 

ftp://ftp.epa.gov/EmisInventory/2002v3CAPHAP/documentation for details. 
37

3 Emissions Modeling Summary

Both the CMAQ and CAMX models require hourly emissions of specific gas and particle species 

for the horizontal and vertical grid cells contained within the modeled region (i.e., modeling 

domain). To provide emissions in the form and format required by the model, it is necessary to 

“pre-process” the “raw” emissions (i.e., emissions input to SMOKE) for the sectors described 

above in Section 2. In brief, the process of emissions modeling transforms the emissions

inventories from their original temporal resolution, pollutant resolution, and spatial resolution 

into the resolution hourly, speciated, gridded resolution required by the air quality model. 

As seen in Section 2, the temporal resolution of the emissions inventories input to SMOKE for 

the 2005 platform varies across sectors, and may be hourly, monthly, or annual total emissions. 

The spatial resolution, which also can be different for different sectors, may be individual point

sources or county totals (province totals for Canada, municipio totals for Mexico). The preprocessing steps involving temporal allocation, spatial allocation, pollutant speciation, and 

vertical allocation of point sources are referred to as emissions modeling. This section provides 

some basic information about the tools and data files used for emissions modeling as part of the 

2005 platform. Since we devoted Section 2 to describing the emissions inventories, we have 

limited the descriptions of data in this section to the ancillary data SMOKE uses to perform the 

emissions modeling steps. Note that all SMOKE inputs for the 2005v4.2 platform emissions are 

available at the 2005v4.2 website (see the end of Section 1).

We used SMOKE version 2.6 to pre-process the raw emissions to create the emissions inputs for 

CMAQ and then converted those to inputs suitable for CAMX. The emissions processing steps

and ancillary data for v4.2 were very similar to those done for v4. A summary of the revisions is 

as follows:

We updated the ancillary files to handle additional MOVES SCCs related to parking area 

emissions and to make some changes to the temporal and spatial approaches that were 

originally assigned to parking area SCCs.

We changed speciation profiles for headspace vapor (VOC).

We changed the PM2.5 speciation profile for category 3 commercial marine vessels 

burning residual oil.

We updated the list of state-county names to include “dummy” seca_c3 FIPS for 

emissions outside of U.S. MMS-base state boundaries but within the 200nm EEZ (see 

section 2.5.6). These dummy FIPS were used for internal projections of regional offshore 

emissions in the ECA-IMO control area that extended up to 200nm offshore.

We used an updated county-to-cell spatial surrogate for U.S. oil and gas emissions.

We changed the temporal allocation approach to use: 1) profiles that vary by day of week

and to use new temporal profiles for the afdust sector, 2) CENRAP-based state-specific 

agricultural burning profiles that vary monthly for the nonpt sector, and 3) residential 

natural gas combustion and commercial propane and kerosene combustion from uniform 

monthly to a profile that varies for the nonpt sector. 
38

We also utilized the feature in SMOKE (updated in version 2.5) to create combination speciation 

profiles that could vary by state/county FIPS code and by month; we used this approach for some 

mobile sources as described in Section 3.1.2. For sectors that have plume rise, we used the inline emissions capability of the air quality model to create source-based emissions files, rather 

than created the much larger 3-dimensional files. The air quality model-ready emissions were 

first created in a form appropriate for CMAQ, and were then converted to a form usable by 

CAMX using a FORTRAN convertor called „inline2camx‟. This program generates the gridded 

surface level 2-dimensional emissions and elevated point source files necessary for CAMX, and it 

also renames certain emissions species to the names needed by CAMX. Emissions totals by 

specie for the entire model domain are output as reports that are then compared to reports 

generated by SMOKE to ensure mass is not lost or gained during this conversion process.

3.1 Key emissions modeling settings

Each sector is processed separately through SMOKE, until the final merge program (Mrggrid) is 

run to combine the model-ready, sector-specific emissions across sectors. The SMOKE settings 

in the run scripts and the data in the SMOKE ancillary files control the approaches used for the 

individual SMOKE programs for each sector. Table 3-1 summarizes the major processing steps 

of each platform sector. The “Spatial” column shows the spatial approach: “point” indicates that 

SMOKE maps the source from a point location (i.e., latitude and longitude) to a grid cell;

“surrogates” indicates that some or all of the sources use spatial surrogates to allocate county 

emissions to grid cells; and “area-to-point” indicates that some of the sources use the SMOKE 

area-to-point feature to grid the emissions (further described in Section3.2.1.2). The 

“Speciation” column indicates that all sectors use the SMOKE speciation step, though biogenics 

speciation is done within BEIS3 and not as a separate SMOKE step. The “Inventory resolution” 

column shows the inventory temporal resolution from which SMOKE needs to calculate hourly 

emissions.

Finally, the “plume rise” column indicates the sectors for which the “in-line” approach is used. 

These sectors are the only ones which will have emissions in aloft layers, based on plume rise. 

The term “in-line” means that the plume rise calculations are done inside of the air quality model 

instead of being computed by SMOKE. The height of the plume rise determines the model layer 

into which the emissions are placed. For the 2005v4 and 2005v4.2 platforms, we did not have 

SMOKE compute the vertical plume rise. Instead, this was done in the air quality model using 

the stack data and the hourly air quality model inputs found in the SMOKE output files for each 

model-ready sector. The seca_c3 sector is the only sector with only “in-line” emissions, 

meaning that all of the entire emissions occur in aloft layers and there are no emissions in the

two-dimensional, layer-1 files created by SMOKE. 

Table 3-1. Key emissions modeling steps by sector.

Platform sector Spatial Speciation

Inventory

resolution Plume rise

ptipm Point Yes daily & hourly in-line

ptnonipm Point Yes annual in-line

othpt Point Yes annual in-line
39

Platform sector Spatial Speciation

Inventory

resolution Plume rise

nonroad surrogates &

area-to-point

Yes monthly

othar Surrogates Yes annual

seca_c3 Point Yes annual in-line

alm_no_c3 surrogates &

area-to-point

Yes annual

on_noadj Surrogates Yes monthly

on_noadj Surrogates Yes monthly

on_moves_startpm Surrogates Yes monthly

on_moves_runpm Surrogates Yes monthly

othon surrogates Yes annual

nonpt

surrogates &

area-to-point

Yes annual

ag surrogates Yes annual

afdust surrogates Yes annual

biog pre-gridded 

landuse in BEIS3.14 hourly

avefire surrogates Yes annual

In addition to the above settings, we used the PELVCONFIG file, which can be optionally used 

to group sources so that they would be treated as a single stack by SMOKE when computing 

plume rise. For the 2005v4.2 platform we chose to have no grouping, which is a difference the 

2005v4 platform. We changed this because grouping done for “in-line” processing will not give 

identical results as “offline” (i.e., processing whereby SMOKE creates 3-dimensional files). The 

only way to get the same results between in-line and offline is to choose to have no grouping. 

3.1.1 Spatial configuration

For the 2005v4.2 platform in support of the Transport Rule, we ran SMOKE followed by CAMX

for the 36-km CONtinental United States “CONUS” modeling domain and the eastern US 12-km 

modeling domain (EUS) shown in Figure 3-1. Figure 3-1 also shows the 12-km western domain 

(WUS), but this domain was not used for Transport Rule modeling. Note that these domains 

were also used in the 2005v4 and 2002 platforms. 
40

Figure 3-1. Air quality modeling domains

All three grids use a Lambert-Conformal projection, with Alpha = 33o, Beta = 45o and Gamma =

-97o, with a center of X = -97o and Y = 40o. Table 3-2 describes the grids for the three domains.

Table 3-2. Descriptions of the 2005-based platform grids

Common 

Name

Grid 

Cell Size

Description 

(see Figure 3-1) Grid name

Parameters listed in SMOKE grid 

description (GRIDDESC) file:

 projection name, xorig, yorig, 

 xcell, ycell, ncols, nrows, nthik

US 36 km or 

CONUS-36 36 km

Entire conterminous 

US plus some of 

Mexico/Canada

US36KM_148X1

12

„LAM_40N97W', -2736.D3, -2088.D3, 

36.D3, 36.D3, 148, 112, 1

Big East 12 

km 12 km

Goes west to 

Colorado, covers 

some Mexico/Canada

EUS12_279X240 „LAM_40N97W', -1008.D3 , -1620.D3, 

12.D3, 12.D3, 279, 240, 1

West 12 km 12 km

Goes east to 

Oklahoma, covers 

some of 

Mexico/Canada

US12_213X192 'LAM_40N97W', -2412.D3 , -972.D3, 

12.D3, 12.D3, 213, 192, 1

36km Domain Boundary

12km East Domain Boundary

12km West Domain Boundary
41

Section 3.2.1 provides the details on the spatial surrogates and area-to-point data used to 

accomplish spatial allocation with SMOKE.

3.1.2 Chemical speciation configuration

The emissions modeling step for chemical speciation creates “model species” needed by the air 

quality model for a specific chemical mechanism. These model species are either individual 

chemical compounds or groups of species, called “model species.” The chemical mechanism 

used for the 2005 platform is the CB05 mechanism (Yarwood, 2005). The same base chemical 

mechanism is used with CMAQ and CAMX, but the implementation differs slightly between the 

two models. For details of the chemical mechanism as it is implemented in CAMX 5.2. The 

specific versions of CMAQ and CAMx used in applications of this platform include secondary 

organic aerosol (SOA) and HONO enhancements. 

From the perspective of emissions preparation, the CB05 mechanism is the same as was used in 

the 2002 platform except that additional input model species are needed to support the nitrous 

acid (HONO) chemistry enhancements and additional input model species are needed to support

SOA. Table 3-3 lists the model species produced by SMOKE for use in CMAQ and CAMX; the 

only three input species that were not in the CAP 2002-Based platform are nitrous acid (HONO), 

BENZENE and sesquiterpenes (SESQ). It should be noted that the BENZENE model species is

not part of CB05 in that the concentrations of BENZENE do not provide any feedback into the 

chemical reactions (i.e., it is not “inside” the chemical mechanism). Rather, benzene is used as a 

reactive tracer and as such is impacted by the CB05 chemistry. BENZENE, along with several 

reactive CBO5 species (such as TOL and XYL) plays a role in SOA formation.
42

Table 3-3. Model species produced by SMOKE for CB05 with SOA for CMAQ4.7 and CAMX*

Inventory Pollutant Model Species Model species description

CL2 CL2 Atomic gas-phase chlorine

HCl HCL Hydrogen Chloride (hydrochloric acid) gas

CO CO Carbon monoxide

NOX NO Nitrogen oxide

NO2 Nitrogen dioxide

HONO Nitrous acid

SO2 SO2 Sulfur dioxide

SULF Sulfuric acid vapor

NH3 NH3 Ammonia

VOC ALD2 Acetaldehyde

ALDX Propionaldehyde and higher aldehydes

BENZENE Benzene (not part of CB05)

ETH Ethene

ETHA Ethane

ETOH Ethanol

FORM Formaldehyde

IOLE Internal olefin carbon bond (R-C=C-R)

ISOP Isoprene

MEOH Methanol

OLE Terminal olefin carbon bond (R-C=C)

PAR Paraffin carbon bond

TOL Toluene and other monoalkyl aromatics

XYL Xylene and other polyalkyl aromatics

Various additional 

VOC species from 

the biogenics model 

which do not map to 

the above model 

species

SESQ Sesquiterpenes

TERP Terpenes

PM10 PMC Coarse PM > 2.5 microns and 10 microns

PM2.5 PEC Particulate elemental carbon 2.5 microns

PNO3 Particulate nitrate 2.5 microns

POC Particulate organic carbon (carbon only) 2.5 

microns

PSO4 Particulate Sulfate 2.5 microns

PMFINE Other particulate matter 2.5 microns

Sea-salt species (non 

–anthropogenic 

emissions)

PCL Particulate chloride

PNA Particulate sodium

*The same species names are used for the CAMX model with exceptions as follows:

1. CL2 is not used in CAMX

2. CAMX particulate sodium is NA (in CMAQ it is PNA)

3. CAMX uses different names for species that are both in CBO5 and SOA for the following: TOLA=TOL, 
43

XYLA=XYL, ISP=ISOP, TRP=TERP. They are duplicate species in CAMX that are used in the SOA chemistry. 

CMAQ uses the same names in CB05 and SOA for these species.

4. CAMX uses a different name for sesquiterpenes: CMAQ SESQ = CAMX SQT

5. CAMX uses particulate species uses different names for organic carbon, coarse particulate matter and other 

particulate mass as follows: CMAQ POC = CAMX POA, CMAQ PMC = CAMX CPRM, and CMAQ PMFINE= 

CAMX FPRM

The approach for speciating PM2.5 emissions in v4.2 is the same as v4 except that in addition to 

the on_moves_startpm and on_moves_runpm sectors, exhaust PM from diesel is provided to 

SMOKE as speciated emissions. Thus, the only PM species requiring speciation in SMOKE 

from the onroad sector are the brake and tirewear PM2.5. Canada point sources have an SCC of 

3999999999 and all use the Speciation profile „92037‟ which is the “Industry Manufacturing 

Avge profile.” While this had not changed between v4 and v4.2, the documentation for v4 

incorrectly stated that the Canadian point inventory (othpt sector) was pre-speciated. The 

Canadian point source inventory is pre-speciated for VOC but not for PM2.5. One other 

difference in PM2.5 speciation is that we used a new profile („92200‟) called “simplified profile -

Marine Vessel – Main Boiler - Heavy Fuel Oil – Simplified.” At the time that this profile was 

used, we anticipated its release with SPECIATE4.3.

The approach for speciating VOC emissions from non-biogenic sources is the same for the v4.2

platform as for the v4 platform, though there are some differences in the data files used. The 

approach is that: 

1. For some sources, HAP emissions are used in the speciation process to allow integration 

of VOC and HAP emissions in the NEI. This has the result of modifying the speciation 

profiles based on the HAP emission estimates which are presumed to be more accurate 

than the speciated VOC results for the HAPs; and,

2. For some mobile sources, “combination” profiles are specified by county and month and 

emission mode (e.g., exhaust, evaporative). SMOKE computes the resultant profile using

the fraction of each specific profile assigned by county, month and emission mode. A 

new feature and new profile file in SMOKE (the GSPRO_COMBO file) allowed the use 

of this approach for the 2005v4 platform, and its use continues here. 

The VOC speciation data files are different because we added another part of the nonpt sector to 

exclude from HAP VOC integration: the category of pesticide application. Additionally, the 

v4.2 platform used a new headspace profile representative of E0 gasoline, profile code 8762:

“Gasoline Headspace Vapor using 0% Ethanol - Composite Profile“. This profile is part of 

SPECIATE4.3 and was used in place of the SPECIATE4.0 profile 8737 (Composite Profile -

Non-oxygenated Gasoline Headspace Vapor), which was used in the v4 platform. The new 

headspace profile was used for the same sources as was the previous headspace profile: year 

2005 refueling and other ambient temperature evaporative gasoline processes (portable fuel 

containers and any evaporation of gasoline associated with gasoline storage and distribution 

sources).

The below subsections provide a further description of the HAP/CAP integration and use of 

combination profiles. Section 3.2.2 provides the details about the data files used to accomplish 

these speciation processing steps.
44

3.1.2.1 The combination of HAP BAFM (benzene, acetaldehyde, formaldehyde 

and methanol) and VOC for VOC speciation

The VOC speciation approach for the 2005v4.2 platform differed from the 2002 platform in that 

we included, for some of the U.S. platform sectors, HAP emissions from the NEI in the 

speciation process. That is, instead of speciating VOC to generate all of the species listed in 

Table 3-3 as we did for the 2002 platform, we integrated emissions of the 4 HAPs, benzene, 

acetaldehyde, formaldehyde and methanol (BAFM) from the NEI with the NEI VOC. The 

integration process (described in more detail below) combines the BAFM HAPs with the VOC in 

a way that does not double count emissions and uses the BAFM directly in the speciation 

process. We believe that generally, the HAP emissions from the NEI are more representative of 

emissions of these compounds than their generation via VOC speciation.

We chose these HAPs because, with the exception of BENZENE, they are the only explicit VOC 

HAPs in the base version of CMAQ 4.7 (CAPs only with chlorine chemistry) model. By 

“explicit VOC HAPs,” we mean model species that participate in the modeled chemistry using 

the CB05 chemical mechanism. We denote the use of these HAP emission estimates along with 

VOC as “HAP-CAP integration”. BENZENE was chosen because it was added as a model 

species in the base version of CMAQ 4.7, and there was a desire to keep its emissions consistent 

between multi-pollutant and base versions of CMAQ. 

The integration of HAP VOC with VOC is a feature available in SMOKE for all inventory 

formats other than PTDAY (the format used for the ptfire sector). SMOKE allows the user to 

specify the particular HAPs to integrate and the particular sources to integrate. The particular 

HAPs to integrate are specified in the INVTABLE file, and the particular sources to integrate are 

based on the NHAPEXCLUDE file (which actually provides the sources that are excluded from 

integration8). For the “integrate” sources, SMOKE subtracts the “integrate” HAPs from the 

VOC (at the source level) to compute emissions for the new pollutant “NONHAPVOC.” The 

user provides NONHAPVOC-to-NONHAPTOG factors and NONHAPTOG speciation profiles. 

SMOKE computes NONHAPTOG and then applies the speciation profiles to allocate the 

NONHAPTOG to the other air quality model VOC species not including the integrated HAPs. 

This process is illustrated in Figure 3-2. Note that we did not need to remove BAFM from 

no-integrate sources in a sector where all sources are no-integrate because this is accomplished 

by through use of a SMOKE ancillary “INVTABLE” which essentially drops all BAFM in that 

sector.

 

8

In SMOKE version 2.6 the options to specify sources for integration are expanded so that a user can specify the 

particular sources to include or exclude from integration, and there are settings to include or exclude all sources 

within a sector. We did not take advantage of this new flexibility in processing v4.2 emissions or v4 emissions, but 

the user will now have the ability for easier inclusion of specific sources to get the same result.
45

Figure 3-2. Process of integrating BAFM with VOC for use in VOC Speciation

Emissions ready for SMOKE

list of “no-integrate” 

sources (NHAPEXCLUDE)

Compute NONHAPVOC= VOC – (B + F + A+M) 

emissions for each integrate source

Retain VOC emissions for each no-integrate source

Assign speciation profile code to each emission source 

Compute: NONHAPTOG emissions from NONHAPVOC for 

each integrate source 

Compute: TOG emissions from VOC for each no-integrate 

source

TOG and NONHAPTOG 

speciation factors

(GSPRO)

Speciation Cross 

Reference File (GSREF)

SMOKE

Compute moles of each CBO5 model species. 

Use NONHAPTOG profiles applied to NONHAPTOG 

emissions and B, F, A, M emissions for integrate sources.

Use TOG profiles applied to TOG for no-integrate sources

Speciated Emissions for VOC species 

VOC-to-TOG factors

NONHAPVOC-to-NONHAPTOG 

factors (GSCNV)

Step 2: Run SMOKE
46

We considered CAP-HAP integration for all sectors and developed “integration criteria” for 

some of those. Table 3-4 summarizes the integration approach for each platform sector used in 

Step 1 of Figure 3-2.

Table 3-4. Integration status of benzene, acetaldehyde, formaldehyde and methanol (BAFM) for 

each platform sector

Platform Sector

Approach for Integrating NEI emissions of Benzene (B), Acetaldehyde (A), 

Formaldehyde (F) and Methanol (M)

ptipm No integration because emissions of BAFM are relatively small for this sector 

ptnonipm No integration because emissions of BAFM are relatively small for this sector and it is not 

expected that criteria for integration would be met by a significant number of sources

avefire No integration 

ag N/A – sector contains no VOC 

afdust N/A – sector contains no VOC

nonpt Partial integration; details provided below table

nonroad For other than California: Partial integration – did not integrate CNG or LPG sources (SCC

beginning with 2268 or 2267) because NMIM computed only VOC and not any HAPs for 

these SCCs. For California: Full integration

alm_no_c3 Partial integration; details provided below table

seca_c3 Full integration

onroad Full integration

biog N/A – sector contains no inventory pollutant "VOC"; but rather specific VOC species

othpt No integration – not the NEI

othar No integration – not the NEI

othon No integration – not the NEI

For the nonpt sector, we used the following integration criteria to determine the sources to 

integrate (Step 1): 

1. Any source for which BAFM emissions were from the 1996 NEI were not integrated 

(data source code contains a “96”).

2. Any source for which the sum of BAFM is greater than the VOC was not integrated, 

since this clearly identifies sources for which there is an inconsistency between VOC and 

VOC HAPs. This includes some cases in which VOC for a source is zero.

3. For certain source categories (those that comprised 80% of the VOC emissions), we 

chose to integrate sources in the category per the criteria specified in the first column in

Table 3-5. For most of these source categories, we allow sources to be integrated if they 

had the minimum combination of BAFM specified in the first column. For a few source 

categories, we designated all sources as “no-integrate”. The one change we made from 

Table 3-5 for the v4.2 platform is highlighted: we changed pesticides application to “nointegrate.”

4. For source categories not covered in Table 3-5 (i.e., that do not comprise the top 80% of 

VOC emissions), then as long as the source has emissions of one of the BFAM

pollutants, then it can be integrated.
47

Table 3-5. Source-category specific criteria for integrating nonpt SCCs for categories 

comprising 80% of the nonpoint VOC emissions

minimum

HAP(s)

needed SCC Tier 3 SCC Tier 3 Description Comments

BFA 2104008000

Stationary Source Fuel 

Combustion;Residential;Wood

B 2501060000

Storage and Transport;Petroleum and Petroleum 

Product Storage;Gasoline Service Stations

BM 2440000000

Solvent Utilization;Miscellaneous Industrial;All 

Processes

Speciation profile: 3144 has no benzene but 

most records have it and they're from the EPA

(and Calif)

FAM 2401001000

Solvent Utilization;Surface Coating;Architectural 

Coatings

B 2310001000

Industrial Processes;Oil and Gas Production: SIC 

13;All Processes : On-shore

M 2460000000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer and Commercial;All Processes

B 2501011000

Storage and Transport;Petroleum and Petroleum 

Product Storage;Residential Portable Gas Cans

M 2425000000 Solvent Utilization;Graphic Arts;All Processes

M 2465000000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer;All Products/Processes

3144 is profile, and it does have methanol 

(but no BFA). 

BFA 2801500000

Miscellaneous Area Sources;Agriculture Production 

- Crops;Agricultural Field Burning - whole field set 

on fire 8746 is speciation profile and has BFA

M 2440020000

Solvent Utilization;Miscellaneous 

Industrial;Adhesive (Industrial) Application

3142 is speciation profile which has methanol 

(.32%) and 0 form (and no acetald, benz)

B 2501050000

Storage and Transport;Petroleum and Petroleum 

Product Storage;Bulk Terminals: All Evaporative 

Losses

B 2310000000

Industrial Processes;Oil and Gas Production: SIC 

13;All Processes

M 2465400000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer;Automotive Aftermarket Products

8520 is speciation profile which doesn't have 

benz but does have methanol. OR is only 

state with benzene which is negligible

Nointegrate

(change 

from v4 

platform) 2461850000

Solvent Utilization;Miscellaneous Non-industrial: 

Commercial;Pesticide Application: Agricultural

Profile has no benzene. Inventory benzene 

came from solvent utilization data (Fredonia) 

for "other markets" for the year 1998. Since 

benzene no longer allowed in pesticides, use 

of a no-benzene profile would give more 

accurate results. Note that this is a change 

from the v4 platform, where this sector was 

“integrate.” 

BFA 2630020000

Waste Disposal, Treatment, and 

Recovery;Wastewater Treatment;Public Owned

profile BFA 2002 (wastewater treatment 

plants). No methanol in profile. No 

methanol mentioned in POTW National 

Emissions Standards for Hazardous Air 

Pollutants (NESHAP). Acetaldehyde and 

Formaldehyde were in profile but not 

NESHAP. Methanol in NEI documentation.

nointegrate 2461021000

Solvent Utilization;Miscellaneous Non-industrial: 

Commercial;Cutback Asphalt

profile 1007 has none of these HAP. Only 

Minnesota has a tiny amount.

nointegrate 2401005000

Solvent Utilization;Surface Coating;Auto 

Refinishing: SIC 7532

Only NY has benzene. Spec. profile is 2402 

and has none of these HAP. Documentation 

for NEI does not estimate this HAP.

use 

Integrate 

case 2301030000

Industrial Processes;Chemical Manufacturing: SIC 

28;Process Emissions from Pharmaceutical Manuf 

(NAPAP cat. 106)

profile 2462 - has nearly 8% benzene. Will 

create a LOT of benzene with "no HAP use" 

case.
48

minimum

HAP(s)

needed SCC Tier 3 SCC Tier 3 Description Comments

M 2460200000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer and Commercial;All Household Products

profile is 3146 contains only nonzero 

methanol.

any 1 HAP 2415000000

Solvent Utilization;Degreasing;All Processes/All 

Industries

profile 8745 (non legacy but composite made 

up of a bunch of E-rated profiles )has M, B. 

M 2401002000

Solvent Utilization;Surface Coating;Architectural 

Coatings - Solvent-based profile 3139 has only M

nointegrate 2401020000

Solvent Utilization;Surface Coating;Wood 

Furniture: SIC 25 profile 2405 has no HAP

B 2505040000

Storage and Transport;Petroleum and Petroleum 

Product Transport;Pipeline

any 1 HAP 2610030000

Waste Disposal, Treatment, and Recovery;Open 

Burning;Residential profile 0121 is old and has only hexane.

any 1 HAP 2610000000

Waste Disposal, Treatment, and Recovery;Open 

Burning;All Categories profile 0121 is old and has only hexane.

FAM 2401003000

Solvent Utilization;Surface Coating;Architectural 

Coatings - Water-based profile 3140 has FAM

M 2460100000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer and Commercial;All Personal Care 

Products

profile (3247, nonlegacy based on CARB 

1997 survey) has no M or B. However, 

Freedonia was used for M.

M 2465200000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer;Household Products

M 2415300000

Solvent Utilization;Degreasing;All Industries: Cold 

Cleaning

profile 8745 (non legacy but composite made 

up of a bunch of E-rated profiles )has M, B. 

any 1 HAP 2401040000

Solvent Utilization;Surface Coating;Metal Cans: 

SIC 341

profile 2408 has none. - no HAPs in NEI so 

this SCC will not have any integrated sources

any 1 HAP 2401050000

Solvent Utilization;Surface Coating;Miscellaneous 

Finished Metals: SIC 34 - (341 + 3498)

SPEC PROFILE 3127 has none - no HAPs in 

NEI so this SCC will not have any integrated 

sources

any 1 HAP 2401200000

Solvent Utilization;Surface Coating;Other Special 

Purpose Coatings

profile 3138 has methanol. Not legacy. 

0.11% aerosol coatings. 

B 2461800000

Solvent Utilization;Miscellaneous Non-industrial: 

Commercial;Pesticide Application: All Processes

3001 is speciation profile (not legacy) "D" 

rating 2004. Calif. Testing for speciation 

profile from 2000. Has NO benzene! 

Benzene came from solvent utilization data 

(Fredonia) for "other markets" for the year 

1998.

M 2460800000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer and Commercial;All FIFRA Related 

Products 3145 has M only and just a 0.01%
49

For the alm_no_c3 sector, the integration criteria were (1) that the source had to have at least one 

of the 4 HAPs and (2) that the sum of BAFM could not exceed the VOC emissions. The criteria 

for this sector were less complex than the nonpt sector because it has much fewer source 

categories.

We used the SMOKE feature to compute speciation profiles from mixtures of other profiles in 

user-specified proportions. The combinations are specified in the GSPRO_COMBO ancillary 

file by pollutant (including pollutant mode, e.g., EXH__VOC), state and county (i.e., 

state/county FIPS code) and time period (i.e., month).

We used this feature for onroad and nonroad mobile and gasoline-related related stationary 

sources whereby the emission sources use fuels with varying ethanol content, and therefore the 

speciation profiles require different combinations of gasoline, E10 an E85 profiles. Since the 

ethanol content varies spatially (e.g., by state or county), temporally (e.g., by month) and by 

modeling year (future years have more ethanol) the feature allows combinations to be specified 

at various levels for different years.

3.1.3 Temporal processing configuration

Table 3-6 summarizes the temporal aspect of the emissions processing configuration. It 

compares the key approaches we used for temporal processing across the sectors. We control the 

temporal aspect of SMOKE processing through (a) the scripts L_TYPE (temporal type) and 

M_TYPE (merge type) settings and (b) the ancillary data files described in Section 3.2.3. The 

one change made from the v4 to the v4.2 platform is the treatment of the afdust sector. In the v4 

platform we used “aveday” settings and no use of holidays such that every day in a specific 

month had the same emissions. In the v4.2 platform, we used “week” settings and holidays and 

used profiles which were day-of-week dependent for some categories, such as road dust and 

tilling, where non-uniform profiles were being used for other pollutants associated with these 

processes.
50

Table 3-6. Temporal settings used for the platform sectors in SMOKE, v4.2 platform

Platform sector

short name

(see Table 2-1)

Inventory

resolution

Monthly

profiles

used?

Daily

temporal

approach 1,2

Merge 

processing 

approach 1,3

Process 

Holidays as 

separate days?

ptipm daily & 

hourly all all yes

ptnonipm annual yes mwdss all yes

othpt annual yes mwdss all

nonroad monthly mwdss mwdss yes

othar annual yes mwdss mwdss

alm_no_c3 annual yes mwdss mwdss

seca_c3 annual yes mwdss mwdss

on_noadj monthly week week yes

on_moves_startpm monthly week week yes

on_moves_runpm monthly week week yes

othon annual yes week week

nonpt annual yes mwdss mwdss yes

ag annual yes aveday aveday

afdust annual yes week week yes

biog hourly n/a n/a

avefire annual yes aveday aveday

1 Definitions for processing resolution:

all = hourly emissions computed for every day of the year, inventory is already daily

week = hourly emissions computed for all days in one “representative” week, representing all weeks for each 

month, which means emissions have day-of-week variation, but not week-to-week variation within the 

month

mwdss= hourly emissions for one representative Monday, representative weekday, representative Saturday 

and representative Sunday for each month, which means emissions have variation between Mondays, 

other weekdays, Saturdays and Sundays within the month, but not week-to-week variation within the 

month. Also Tuesdays, Wednesdays and Thursdays are treated the same.

aveday = hourly emissions computed for one representative day of each month, which means emissions for 

all days of each month are the same.

2 Daily temporal approach refers to the temporal approach for getting daily emissions from the inventory 

using the Temporal program. The values given are the values of the L_TYPE setting.

3 Merge processing approach refers to the days used to represent other days in the month for the merge 

step. If not “all”, then the SMOKE merge step just run for representative days, which could include holidays 

as indicated by the rightmost column. The values given are the values of the M_TYPE setting.

In addition to the resolution, temporal processing includes a ramp-up period for several days 

prior to January 1, 2005, which is intended to mitigate the effects of initial condition 

concentrations. The same procedures were used for all grids, but with different ramp-up periods 

for each grid:

36 km: 10 days (Dec 22 - Dec 31)

12 km (East): 3 days (Dec 29 - Dec 31)

For most sectors, our approach used the emissions from December 2005 to fill in surrogate 

emissions for the end of December 2004. In particular, we used December 2005 emissions 
51

(representative days) for December 2004. For biogenic emissions, we processed December 2004 

emissions using 2004 meteorology.

3.2 Emissions modeling ancillary files

In this section we summarize the ancillary data that SMOKE used to perform spatial allocation, 

chemical speciation, and temporal allocation for the 2005v4.2 platform. The ancillary data files, 

particularly the cross-reference files, provide the specific inventory resolution at which spatial, 

speciation, and temporal factors are applied. For the 2005v4.2 platform, we generally applied

spatial factors by country/SCC, speciation factors by pollutant/SCC or (for combination profiles) 

state/county FIPS code and month, and temporal factors by some combination of country, state, 

county, SCC, and pollutant.

For the v4.2 platform, we updated the 2005v4 ancillary files in a few major areas:

1. We used new data for spatially allocating oil and gas emission sources

2. We assigned spatial, temporal and speciation profiles to parking area emissions for 

additional vehicle types (new data from MOVES2010) and updated previous assignments 

for some vehicle types (summarized in Table 3-14 and Table 3-155).

3. We updated the headspace VOC speciation profile we used for refueling.

4. We used a new profile for speciating PM2.5 from C3 marine emissions.

3.2.1 Spatial allocation data

As described in Section 3.1.1, we performed spatial allocation for a national 36-km domain, and 

an Eastern 12-km domain. To do this, SMOKE used national 36-km and 12-km spatial 

surrogates and a SMOKE area-to-point data file. For the U.S. and Mexico, we used the same 

spatial surrogates as were used for the 2002v3 platform. For Canada we used a set of Canadian 

surrogates provided by Environment Canada. The spatial data files we used can be obtained 

from the files listed below; these are available from the 2002v3CAP (for US and Mexico) and 

the 2005v4 CAP-BAFM (for Canada) platform websites listed at the end of Section 1. The oil 

and natural gas surrogate files are posted at the 2005v4.1 website. For the v4.2 platform, all of 

the relevant surrogate files can be found in a single consolidated zip file: 

gridding_surrogates_2005v4_2.zip. This zip file contains the following information:

U.S. and Mexican surrogate files at 36-km spatial resolution 

U.S. and Mexican surrogate files for surrogate files at 12 km spatial resolution

Canadian surrogate files at 36-km spatial resolution 

Canadian surrogate files at 12-km spatial resolution

Updated oil and gas surrogate files at 36-km and 12-km spatial resolutions for the new oil 

and gas surrogate (US) developed for the v4.1 platform

Additional information related to spatial allocation is found in this file:

ancillary_2005v4_2_smokeformat.zip: contains spatial related data included are the 

grid description (GRIDDESC), surrogate description (SRGDESC), surrogate cross 

reference file (AGREF), and area-to-point (ARTOPNT) file. This data is provided on the 
52

2005v4.2 website under “2005 Emissions Data Files” at: 

ftp://ftp.epa.gov/EmisInventory/2005v4.2/ancillary_smoke/.

The U.S., Mexican, and Canadian 12-km surrogates cover the entire CONUS domain, though 

they are used directly as inputs for the two separate Eastern and Western Domains shown in

Figure 3-1. The SMOKE model windowed the Eastern and Western grids while it created these 

emissions. The remainder of this subsection provides further detail on the origin of the data used 

for the spatial surrogates and the area-to-point data.

3.2.1.1 Surrogates for U.S. emissions

There are 67 spatial surrogates available for spatially allocating U.S. county-level emissions to 

the 36-km and 12-km grid cells used by the air quality model; 66 are the same as for the v4

platform, and one new surrogate, “Oil & Gas Wells, IHS Energy, Inc. and USGS” was added for 

v4.2 which is discussed below. As described in Section 3.2.1.2, an area-to-point approach 

overrides the use of surrogates for some sources. Table 3-7 lists the codes and descriptions of 

the surrogates.

Table 3-7. U.S. Surrogates available for the 2005v4.2 platform.

Code Surrogate Description Code Surrogate Description

N/A Area-to-point approach (see 3.3.1.2) 515 Commercial plus Institutional Land

100 Population 520 Commercial plus Industrial plus Institutional

110 Housing 525

Golf Courses + Institutional +Industrial +

Commercial

120 Urban Population 527 Single Family Residential

130 Rural Population 530 Residential - High Density

137 Housing Change 535

Residential + Commercial + Industrial + 

Institutional + Government

140 Housing Change and Population 540 Retail Trade 

150 Residential Heating - Natural Gas 545 Personal Repair 

160 Residential Heating - Wood 550 Retail Trade plus Personal Repair 

165

0.5 Residential Heating - Wood plus 0.5 Low 

Intensity Residential 555

Professional/Technical plus General 

Government 

170 Residential Heating - Distillate Oil 560 Hospital 

180 Residential Heating - Coal 565 Medical Office/Clinic 

190 Residential Heating - LP Gas 570 Heavy and High Tech Industrial 

200 Urban Primary Road Miles 575 Light and High Tech Industrial 

210 Rural Primary Road Miles 580 Food, Drug, Chemical Industrial

220 Urban Secondary Road Miles 585 Metals and Minerals Industrial 

230 Rural Secondary Road Miles 590 Heavy Industrial 

240 Total Road Miles 595 Light Industrial 

250 Urban Primary plus Rural Primary 596 Industrial plus Institutional plus Hospitals

255 0.75 Total Roadway Miles plus 0.25 Population 600 Gas Stations

260 Total Railroad Miles 650 Refineries and Tank Farms

270 Class 1 Railroad Miles 675 Refineries and Tank Farms and Gas Stations

280 Class 2 and 3 Railroad Miles 680

Oil & Gas Wells, IHS Energy, Inc. and 

USGS

300 Low Intensity Residential 700 Airport Areas
53

Code Surrogate Description Code Surrogate Description

310 Total Agriculture 710 Airport Points

312 Orchards/Vineyards 720 Military Airports

320 Forest Land 800 Marine Ports

330 Strip Mines/Quarries 807 Navigable Waterway Miles

340 Land 810 Navigable Waterway Activity

350 Water 850 Golf Courses

400 Rural Land Area 860 Mines

500 Commercial Land 870 Wastewater Treatment Facilities

505 Industrial Land 880 Drycleaners

510 Commercial plus Industrial 890 Commercial Timber

We did not use all of the available surrogates to spatially allocate sources in the v4.2 platform; 

that is, some surrogates in Table 3-7 were not assigned to any SCCs. 

The creation of surrogates and shapefiles for the U.S. via the Surrogate Tool was discussed in the 

2002v3 platform documentation and is not repeated here. The tool and updated documentation 

for it is available at http://www.ie.unc.edu/cempd/projects/mims/spatial/ and 

http://www.cmascenter.org/help/documentation.cfm?MODEL=spatial_allocator&VERSION=3.

6&temp_id=99999. This same tool was used for the new surrogate 680, “Oil & Gas Wells, IHS 

Energy, Inc. and USGS”

The new surrogate “Oil & Gas Wells, IHS Energy, Inc. and USGS” was developed for oil and 

gas SCCs, which had previously (in the v4 platform) used surrogate 585. The data reflect data 

through 10/1/2005. The underlying data for this surrogate is a grid of one-quarter square mile 

cells containing an attribute to indicate whether the wells within the cell are predominantly oilproducing, gas-producing, both oil- and gas-producing, or the wells are dry or their production 

status is unknown. The well information was initially retrieved from IHS Inc.'s PI/Dwights 

PLUS Well Data on CD-ROM, which is a proprietary commercial database containing 

information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to 

overcome the problem of displaying proprietary well data. No proprietary data are displayed or 

included in the cell maps. More information can be obtained from http://pubs.usgs.gov/dds/dds069/dds-069-q/text/layer.htm and 

http://certmapper.cr.usgs.gov/rooms/utilities/layer_info.jsp?docId={A90AF432-612F-41F9-

A315-

7329FD933FB3}&type=download&docURL=http://certmapper.cr.usgs.gov/data/noga00/natl/sp

atial/doc/uscells05g.htm

The spatial cross-reference file was also updated to assign onroad off-network (parking area)

emissions from the MOVES2010 model, new to the 2005v4 platform, were allocated as shown in

Table 3-8.

Table 3-8. Surrogate assignments to new mobile categories in the 2005v4 platform

SCC & Description Surrogate
54

SCC & Description Surrogate

2201001350 Light Duty Gas Vehicles- parking areas rural

2201002350 Light Duty Gas Trucks 1&2- parking areas rural

2201004350 Light Duty Gas Trucks 3&4- parking areas rural

Rural population (same as rural 

local roads), code= 130

2201001370 Light Duty Gas Vehicles- parking areas urban

2201002370 Light Duty Gas Trucks 1&2- parking areas urban

2201004370 Light Duty Gas Trucks 3&4- parking areas urban

Urban population (same as urban 

local roads), code =120

2201070350 Heavy Duty Gasoline Vehicles 2B through 8B & Buses 

(HDGV)- parking areas rural

2201070370 Heavy Duty Gasoline Vehicles 2B through 8B & Buses 

(HDGV)- parking areas urban

Commercial plus Industrial plus 

Institutional, code = 520

3.2.1.2 Allocation method for airport-related sources in the U.S.

There are numerous airport-related emission sources in the 2005 NEI, such as aircraft, airport 

ground support equipment, and jet refueling. Unlike the 2002v3 platform in which most of these 

emissions were contained in sectors with county-level resolution – alm (aircraft), nonroad 

(airport ground support) and nonpt (jet refueling), the 2005 platform includes the aircraft 

emissions as point sources. As shown in Table 2-1, aircraft emissions are part of the ptnonipm 

sector, since the 2005v2 inventory included them as point sources.

Thus, for the 2005 platform, we used the SMOKE “area-to-point” approach for only airport 

ground support equipment (nonroad sector), and jet refueling (nonpt sector). The approach is 

described in detail in the 2002 platform documentation: 

http://www.epa.gov/scram001/reports/Emissions%20TSD%20Vol1_02-28-08.pdf.

We used nearly the same ARTOPNT file to implement the area-to-point approach as was used 

for the CAP and HAP-2002-Based platform. This was slightly updated from the CAP-only 2002 

platform by further allocating the Detroit-area airports into multiple sets of geographic 

coordinates to support finer scale modeling that was done under a different project. We chose to 

retain the updated file for the 2005 platform. This approach is the same in the v4.2 and v4 

platforms.

3.2.1.3 Surrogates for Canada and Mexico emission inventories

We used an updated set of surrogates for Canada to spatially allocate the 2006 Canadian 

emissions for the 2005v4 platform. The updated set completely replaced the 2002v3 platform

surrogates for allocating the 2006 province-level Canadian emissions.

The updated surrogate data provided in the 2005v4 zip files and described in Table 3-9 came 

from Environment Canada. They provided the surrogates and cross references; the surrogates 

they provided were outputs from the Surrogate Tool (previously referenced). Per Environment 

Canada, the surrogates are based on 2001 Canadian census data. We changed the crossreferences that Canada originally provided as follows: all assignments to surrogate '978' 

(manufacturing industries) were changed to '906' (manufacturing services), and all assignments 

to '985' (construction and mining) and „984‟ (construction industries) were changed to '907' 

(construction services) because the surrogate fractions in 984, 978 and 985 did not sum to 1. We 
55

also changed codes for surrogates other than population that did not begin with the digit “9”. 

The same surrogates were used for the 12-km domains as were used for the 36-km domain.

Table 3-9. Canadian Spatial Surrogates for 2005-based platform Canadian Emissions (v4.2

unchanged from v4)

Surrogate 

description 

Filename of 2005 

Platform Surrogate

Surrogate 

description 

Filename of 2005 

Platform Surrogate

Population CA_100_NOFILL.txt asphalt CA_951_NOFILL.txt

Total dwelling CA_901_NOFILL.txt cement CA_952_NOFILL.txt

Agriculture and 

Forestry and Fishing

CA_902_NOFILL.txt

chemical CA_953_NOFILL.txt

Waste Management 

Service

CA_903_NOFILL.txt

commfuelcomb CA_954_NOFILL.txt

Upstream Oil and Gas 

(UOG)

CA_904_NOFILL.txt

downstream_petroleum CA_955_NOFILL.txt

Mining and Oil and Gas 

services

CA_905_NOFILL.txt

egu CA_956_NOFILL.txt

Manufacturing services CA_906_NOFILL.txt grain CA_957_NOFILL.txt

Construction services CA_907_NOFILL.txt manufacturing CA_958_NOFILL.txt

Transportation of 

Passengers and goods

CA_908_NOFILL.txt 

mining CA_959_NOFILL.txt

Electric and Gas and 

Water utilities

CA_909_NOFILL.txt

oilgas_distibution CA_960_NOFILL.txt

Wholesaling 

Merchandise services

CA_910_NOFILL.txt

smelting CA_961_NOFILL.txt

Retailing Merchandise 

services

CA_911_NOFILL.txt

waste CA_962_NOFILL.txt

Government Services CA_915_NOFILL.txt wood CA_963_NOFILL.txt

All Sales CA_920_NOFILL.txt asphalt industries CA_971_NOFILL.txt

Intersection of 

AGRFORFISH and 

MANUFACT

CA_921_NOFILL.txt

cement industries CA_972_FILL.txt

Intersection of Forest 

and Housing

CA_922_NOFILL.txt

chemical industries CA_973_FILL.txt

Intersection of 

MININGOILG and 

MANUFACT

CA_923_NOFILL.txt

commercial fuel 

combustion CA_974_FILL.txt

Intersection of 

UTILITIES and 

DWELLING

CA_924_NOFILL.txt

downstream petroleum 

industries CA_975_FILL.txt

Intersection of 

CONSTRUCTION and 

DWELLING

CA_925_NOFILL.txt

Electric utilities CA_976_FILL.txt

Intersection of 

PUBADMIN and 

DWELLING

CA_926_NOFILL.txt

grain industries CA_977_FILL.txt

Commercial Marine 

Vessels

CA_928_NOFILL.txt manufacturing 

industries1 CA_978_FILL.txt

HIGHJET CA_929_NOFILL.txt mining industries CA_979_FILL.txt

LOWMEDJET CA_930_NOFILL.txt smelting industries CA_981_FILL.txt

OTHERJET CA_931_NOFILL.txt waste management CA_982_NOFILL.txt

CANRAIL CA_932_NOFILL.txt construction industries1 CA_984_NOFILL.txt

LDGV CA_934_NOFILL.txt construction and CA_985_NOFILL.txt
56

Surrogate 

description 

Filename of 2005 

Platform Surrogate

Surrogate 

description 

Filename of 2005 

Platform Surrogate

mining1

PAVED ROADS CA_941_NOFILL.txt TOTALBEEF2 CA_986_NOFILL.txt 2 

UNPAVED ROADS

CA_942_NOFILL.txt

TOTALPOUL2 CA_987_NOFILL.txt2

Oil Sands CA_950_NOFILL.txt TOTALSWIN2 CA_988_NOFILL.txt2

TOTALFERT2 CA_989_NOFILL.txt2

1: Not used because fractions did not sum to 1; 

2: Surrogates 986, 987, 988 and 989 were originally numbered by Canada as 611, 615, 620 and 65, respectively. We changed the 

numbers so that all Canadian surrogates would begin with “9”.

The Mexican emissions and single surrogate (population) are the same in the v4.2 platform as 

were used in the 2005v4 and 2002 platforms.

3.2.2 Chemical speciation ancillary files

The following data files, provided at the 2005v4.2 website (see the end of Section 1), contain the 

SMOKE inputs used for chemical speciation of the inventory species to the air quality model 

species. SMOKE environment variable names, used in the file names, are shown using capital 

letters in parentheses:

ancillary_2005v4_2_smokeformat.zip: inventory table (INVTABLE), NONHAPVOC 

emissions calculation exclusions file (NHAPEXCLUDE), speciation cross references

(GSREF), speciation VOC-to-TOG conversion factors (GSCNV), speciation profiles 

(GSPRO), and combined, monthly speciation profiles (GSPRO_COMBO).

ancillary_2005v4_2_futureyear_smokeformat.zip: speciation-related files associated 

with the future-year speciation changes.

The following subsections explain these SMOKE input files. 

3.2.2.1 INVABLE and NHAPEXCLUDE

The INVTABLE and NHAPEXCLUDE SMOKE input files have a critical function in the VOC

speciation process for emissions modeling cases utilizing HAP-CAP integration, as is done for

the 2005v4.2 platform.

We prepared two different INVTABLE files to use with different sectors of the platform. For 

sectors in which we chose no integration across the entire sector (see Table 3-5), we created a 

“no HAP use” INVTABLE that set the “KEEP” flag to “N” for BAFM pollutants. Thus, any 

BAFM pollutants in the inventory input into SMOKE would be dropped. This approach both 

avoids double-counting of these species and assumes that the VOC speciation is the best 

available approach for these species for the sectors using the approach. The second INVTABLE, 

used for sectors in which one or more sources are integrated, causes SMOKE to keep the BAFM 

pollutants and indicates that they are to be integrated with VOC (by setting the “VOC or TOG 

component” field to “V” for all four HAP pollutants. 

We also prepared sector-specific NHAPEXCLUDE files that provide the specific sources that 

are excluded from integration (see Table 3-5).
57

3.2.2.2 GSPRO, GSPRO_COMBO, GSREF and GSCNV

For VOC speciation, we generated the following SMOKE-ready profiles for the CB05 chemical 

mechanism using the Speciation Tool (Eyth, 2006):

TOG-to-model species (used only for no-integrate sources)

NONHAPTOG-to-model species (used only for the integrate sources)

TOG-to-BENZENE (used only for no-integrate sources)

We added speciation profile entries that simply map NEI emissions of benzene, acetaldehyde, 

formaldehyde and methanol to the model species BENZENE, ALD2, FORM and METHANOL, 

respectively. These profiles were used only for the integrate sources. Note that we process the 

integrate and no-integrate sources using the same GSREF and GSPRO files. Thus, to avoid 

double counting of these HAP species, we removed BAFM pollutants for all no-integrate sources 

in the inventory. If the entire sector was no-integrate, then we were able to remove these in 

SMOKE (by using “N” in the INVTABLE) but if a sector was partially integrated, then we 

needed to remove these HAPS from the actual inventory input to SMOKE, but only for the no 

HAP use, no-integrate sources.

In addition to the speciation profiles, the Speciation Tool generates the SMOKE-ready speciation 

conversion files (GSCNV). We generated two of these: one containing profile-specific VOC-toTOG conversion factors and the other containing profile-specific NONHAPVOC-toNONHAPTOG conversion factors.

The TOG and PM2.5 speciation factors that are the basis of the chemical speciation approach 

were developed from the SPECIATE4.2 database 

(http://www.epa.gov/ttn/chief/software/speciate/index.html) which is the EPA's repository of 

TOG and PM speciation profiles of air pollution sources. However, a few of the profiles we 

used in the v4.2 platform will be published in SPECIATE4.3 after the release of this 

documentation.

The SPECIATE database development and maintenance is a collaboration involving the 

EPA‟s ORD, OTAQ, and the EPA‟s Office of Air Quality Planning and Standards (OAQPS), 

and Environment Canada (EPA, 2006 a). The SPECIATE database contains speciation 

profiles for TOG, speciated into individual chemical compounds, VOC-to-TOG conversion 

factors associated with the TOG profiles, and speciation profiles for PM2.5. The database also 

contains the PM2.5 speciated into both individual chemical compounds (e.g., zinc, potassium, 

manganese, lead), and into the “simplified” PM2.5 components used in the air quality model. 

These simplified components are: 

PSO4 : primary particulate sulfate

PNO3: primary particulate nitrate

PEC: primary particulate elemental carbon

POC: primary particulate organic carbon

PMFINE: other primary particulate, less than 2.5 micrograms in diameter
58

As discussed earlier, for the v4.2 platform we updated the PM2.5 profile used for category 3 

marine vessels burning residual oil to use the profile: Marine Vessel - Main Engine - Heavy 

Fuel Oil which will be published in SPECIATE4.3. This profile was compiled from data 

published in Emission Measurements from a Crude Oil Tanker at Sea, Environ. Sci. Technol. 

2008, 42, 7098–7103. Previously the Draft Residual Oil Combustion – Simplified (92072) was 

used. The SCCs affected were:

2280003000 Mobile Sources;Marine Vessels, Commercial;Residual;Total, All Vessel Types

2280003010 Mobile Sources;Marine Vessels, Commercial;Residual;Ocean-going Vessels

2280003100 Mobile Sources;Marine Vessels, Commercial;Residual;Port emissions

2280003200 Mobile Sources;Marine Vessels, Commercial;Residual;Underway emissions

The difference between the two profiles is provided in Table 3-10, and shows that the new 

profile produces much more organic carbon and less elemental carbon, sulfate, and other PM2.5.

Table 3-10. Differences between two profiles used for commercial marine residual oil

Pollutant Species

Split factors new c3 profile 

92200 used for v4.2

Split factors residual oil 

combustion

92072, used for v4

PM2_5 PEC 0.005 0.01

PM2_5 PMFINE 0.5022 0.54

PM2_5 PNO3 0 0

PM2_5 POC 0.1125 0.01

PM2_5 PSO4 0.3803 0.44

We also updated the bituminous coal profile, 92095, which we had previously used for only a 

single nonpoint SCC (2101002000) with the sub-bituminous profile 92084, which was used for 

all other coal combustion SCCs. We replaced profile 92095 with 92084 for consistency. Table 

3-11 shows the differences are shown below, though these are quite small and represent only a 

minor change to the SMOKE results:

Table 3-11. Differences between two profiles used for coal combustion

Pollutant Species

Split factors subbituminous 92084Split factors 

bituminous 92095

PM2_5 PEC 0.0188 0.01696

PM2_5 PMFINE 0.8266 0.827928

PM2_5 PNO3 0.0016 0.00208

PM2_5 POC 0.0263 0.026307

PM2_5 PSO4 0.1267 0.126725

We made other updates to profile assignments for the SCCs shown in Table 3-12 below as 

compared to the 2002 platform. These updates were kept for the v4.2 platform.

Table 3-12: PM2.5 speciation profile updates assignments for the v4 platform

SCC New Pollutant Profile Name
59

Profile 

Code

39900501 92025 PM2_5 Distillate Oil Combustion Source Type: Distillate Oil Combustion

49090021 92025 PM2_5 Distillate Oil Combustion Source Type: Distillate Oil Combustion

30890002 92072 PM2_5 Residential Oil Combustion Source Type: Residential Oil 

Combustion

10100912 92091 PM2_5 Wood Fired Boiler Source Type: Wood/Bark Combustion

10102018 92057 PM2_5 PM/SO2 controlled lignite combustion: Waste Coal Combustion

50410563 92082 PM2_5 Solid Waste Combustion Source Type: Solid Waste Combustion

10100692 92048 PM2_5 Natural Gas Combustion Source Type: Natural Gas Combustion

50100511 92086 PM2_5 Tire Burning Source Type: Tire Burning

50100512 92082 PM2_5 Solid Waste Combustion: Solid Waste Combustion

2810040000 92035 PM2_5 HDDV Source Type: Aircraft Engines

Key changes to the TOG profiles for the v4.2 platform from the 2005v4 platform are as follows:

Used new headspace profiles for E0 (no ethanol gasoline) and E10 (10% ethanol 

gasoline), which will be published in SPECIATE4.3. Profile 8762 is Gasoline Headspace 

Vapor using 0% Ethanol - Composite Profile and Profile 8763 is Gasoline Headspace 

Vapor using 10% Ethanol - Composite Profile. In 2005, only the E0 profile is used. This 

was an oversight since we could have used the same combinations of profiles of E0 

exhaust E10 exhaust (which are also the same combinations of E10 evaporative and E10 

evaporative) that we used for 2005. We did, however use consistent combinations 

(E0/E10) in future-year modeling for the headspace profiles as the evaporative and 

exhaust combinations.

Added the fuel-specific VOC profiles for the new parking area SCCs generated due to the 

fact that MOVES2010 was used for all vehicle types in the v4.2 platform. A summary of 

the assignments of all profiles (speciation, temporal and spatial surrogates) is provided in 

Table 3-14 for gasoline vehicles and Table 3-155 for diesel vehicles.

Table 3-13 provides a summary of the 2005 speciation approach for mobile and other fuelrelated sources. It shows the updated profiles that form the 2005 combinations. The headspace 

profile, 8762 is a new profile for the v4.2 platform, and is used for other nonroad refueling and 

other fuel-related stationary source emission categories in 2005. 

Table 3-13. Summary of VOC speciation profile approach by sector for 2005

Inventory

type and

mode

VOC speciation 

approach

for fuels

VOC

Profile

Codes

2005 

sectors

Mobile onroad and nonroad

Exhaust

E0 and E10 

combinations 

(excludes Tier 2)

8750

8751

on_noadj

nonroad

Mobile onroad and nonroad

Evaporative

E0 and E10 

combinations

8753

8754

on_noadj

nonroad
60

Inventory

type and

mode

VOC speciation 

approach

for fuels

VOC

Profile

Codes

2005 

sectors

Mobile nonroad Refueling

Stationary (no mode assigned 

to VOC): Portable Fuel 

Containers, bulk plant -topump, refinery-to-bulk 

terminal 

E0 8762 Nonroad

nonpt

In future years, different profile combinations and a different headspace profile is used, due to 

the influx of greater quantities of ethanol in fuels. Changes to the above profiles for future-year 

scenarios will be discussed in more detail in the documentation of future-year emissions 

development for the rule or application of interest. In summary, we utilized additional profiles in 

the combinations that is appropriate. The profiles we added were Tier 2 profiles for E0 and E10

and an E10 headspace profile. 

Speciation profiles for use with BEIS are not included in SPECIATE. The 2005 platform uses 

BEIS3.14, which includes a new species (SESQ) that was not in BEIS3.13 (the version used for 

the 2002 platform). Thus we added this species (it is mapped to the model species SESQT) to 

the set of profiles that we had been using in the 2002 platform. The profile code associated with 

BEIS3.14 profiles for use with CB05 uses the same as in the 2002 platform: “B10C5.”

3.2.3 Temporal allocation ancillary files

The emissions modeling step for temporal allocation creates the 2005 hourly emission inputs for 

the air quality model by adjusting the emissions from the inventory resolution (annual, monthly, 

daily or hourly) that are input into SMOKE. The temporal resolution of each of the platform 

sectors prior to their input into SMOKE is included in the sector descriptions from Table 2-1 and 

repeated in the discussion of temporal settings in Table 3-6.

The monthly, weekly, and diurnal temporal profiles and associated cross references used to 

create the 2005 hourly emissions inputs for the air quality model were generally based on the 

temporal allocation data used for the 2002v3 platform. For the v4 and v4.2 platforms, we added 

new profile assignments for SCCs in the 2005 inventory that were not in the 2002 inventory, and 

we updated the profiles used for ptipm sources without CEM data to represent the year 2005.

The following data file, provided at the 2005v4 website (see the end of Section 1) contains the 

files used for temporal allocation of the inventory emissions. SMOKE environmental variable 

names, used in the file names, are shown in capital letters in parentheses:

ancillary_2005v4_2_smokeformat.zip: includes temporal cross reference files used 

across all inventory sectors (ATREF, MTREF, and PTREF) and for ptipm sector (used 

for electric generating units) for the evaluation case (PTREF) and, temporal profiles 

(ATPRO, MTPRO, and PTPRO) 
61

The starting point for our temporal profiles was the 2002 platform. The remainder of this section 

discusses the development of the new temporal profiles or profile assignments used in the 

2005v4 platform. 

Canadian emissions

The profiles assignments for the Canadian 2006 inventory were provided by Environment 

Canada along with the inventory. They provided profile assignments that rely on the existing set 

of temporal profiles in the 2002 platform. For point sources, they provided profile assignments 

by PLANTID.

WRAP Oil and Gas Inventory Profiles

The WRAP 2005 oil and gas inventory SCCs utilized uniform monthly and day of week profiles 

(codes 262 and 7, respectively) and an hourly profile (code 26) that put emissions in every hour, 

but weighted towards the day light hours. 

Diurnal Profiles for Electric Generating Units (ptipm)

We updated the state-specific and pollutant-specific diurnal profiles for use in allocating the dayspecific emissions for non-CEM sources in the ptipm sector. We used the 2005 CEM data to 

create state-specific, day-to-hour factors, averaged over the whole year and all units in each state. 

We calculated the diurnal factors using CEM SO2 and NOX emissions and heat input. We 

computed SO2 and NOX-specific factors from the CEM data for these pollutants. All other 

pollutants used factors created from the hourly heat input data. We assigned the resulting 

profiles by state and pollutant. 

Area Fugitive Dust Profiles (afdust)

The monthly and day of week temporal profiles for several fugitive dust sources were changed 

from uniform in the v4 platform (code 262 and 7 respectively) to a summer peak/winter 

minimum (monthly code 22) and weekend minimum (code 18) in the v4.2 platform. These 

sources include fugitive dust from industrial unpaved roads and construction, residential and 

industrial/commercial/institutional construction, road construction, mining and quarrying, and 

agricultural production (planting, tilling, harvesting, and loading).

Diurnal weekday and weekend temporal profiles were changed from a simple bell curve profile 

(code 26) for all categories in v4 to a more dynamic profile with a morning and afternoon peak 

(code 2013) for paved and unpaved road dust in v4.2. Diurnal temporal profiles were changed to 

a zero nighttime, daytime plateau profile (code 27) for all agricultural production sources in v4.2.

Agricultural Burning Profiles in CENRAP States (nonpt)

The uniform monthly, day of week, and diurnal profiles (codes 262, 7, and 24 respectively) in 

the v4 platform for all agricultural burning emissions were modified in the v4.2 platform to statespecific monthly, day of week, and diurnally-varying profiles for these CENRAP region states: 

Arkansas, Iowa, Kansas, Louisiana, Minnesota, North Dakota, Nebraska, Oklahoma, and Texas. 
62

Residential and Commercial/Institutional Natural Gas, LPG, and Kerosene Combustion (nonpt)

Uniform monthly (code 262) profiles in platform v4 for residential and commercial/institutional 

liquified petroleum gas (LPG), natural gas, and kerosene sources were changed to monthly 

varying with a strong winter peak in platform v4.2. 

Onroad Parking Area Profiles

The SCCs and descriptions, along with the assignments chosen are shown in Table 3-14

(gasoline vehicles) and Table 3-155 (diesel vehicles). Figure 3-3 and Figure 3-4 show the 

diurnal profiles referred to in the tables.

Figure 3-3. Diurnal Profiles based on road type (use local for “start”) and whether the road is 

urban versus rural

Figure 3-4. Diurnal temporal profile for HDDV 2B through 8B at Parking areas

Weekday Diurnal

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 2 4 6 8 10 12 14 16 18 20 22

Hour of Day

Rural Local: code = 2006

Urban Local: code = 2012

Weekend Diurnal (same codes)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 2 4 6 8 10 12 14 16 18 20 22

0

100

200

300

400

500

600

700

hr0 hr1 hr2 hr3 hr4 hr5 hr6 hr7 hr8 hr9 hr10 hr11 hr12 hr13 hr14 hr15 hr16 hr17 hr18 hr19 hr20 hr21 hr22 hr23

Weekend and Weekday diurnal profiles used for HDDV 

(except school/transit buses)

At urban and rural parking areas (i.e., idling emissions)

profile code =3000
63

Table 3-14. Summary of spatial surrogates, temporal profiles, and speciation profiles used by gasoline vehicle types for the onroad 

parking area-related SCCs.

GASOLINE VEHICLE TYPES

SCC&Description Surrogate

Temporal 

Profile: 

Monthly 

Variation

Temporal Profile:

Day of Week Variation

Temporal Profile: 

Diurnal variation Speciation Profile

2201001350

Light Duty Gas 

Vehicles- parking 

areas rural

2201020350 Light 

Duty Gas Trucks 

1&2- parking areas 

rural

2201040350 Light 

Duty Gas Trucks 

3&4- parking areas 

rural

2201080370 

Motorcycles (MC) -

parking areas rural

Rural 

Population 

(same as 

rural local 

roads)

130

Not 

applicable 

–

inventory 

contains 

monthly 

emissions

RURAL LD values are:

Mon –Fri 12.1% 12.1% 

12.1% 12.1% 18.3% 

Sat/Sun: 15.3% 18.3% 

Weekly_code (for 

SMOKE) =20021

Use same as profile 

as rural local 

roads 

(Rdtype=210).

Code = 2006 (see 

Figure 3-3, reddish 

curve)

Use same speciation profiles as what is used for LD GAS 

vehicles on the other roadway types. *

i.e.: 

EVP__VOC: COMBO of 8753 (Gasoline Vehicle -

Evaporative emission - Reformulated gasoline) & 8754 

(Gasoline Vehicle - Evaporative emission - E10 ethanol 

gasoline) Note that these are the combinations used in 2005. 

In some cases, future-year profiles may also include 8755 

(Gasoline Vehicle - Evaporative emission - E85)

EXH__VOC: COMBO of 8750&8751 These combinations 

are used in 2005. In some cases, future-year profiles may 

also include combinations of 8752 (E85) , 8756 (tier 2 

exhaust, E0), 8757 (tier 2 exhaust, E10)

EXH__PM2.5 not needed because OTAQ supplies prespeciated emissions 

BRK_PM2.5 and TIR_PM2.5 use same as other roadways 

(92009 and 92087, respectively)

2201001370

Light Duty Gas 

Vehicles- parking 

areas urban

2201020370 Light 

Duty Gas Trucks 

1&2- parking areas 

urban

2201040370 Light 

Duty Gas Trucks 

3&4- parking areas 

urban

2201080370 

Urban 

Population 

(same as 

urban local 

roads)

120

Not 

applicable 

–

inventory 

contains 

monthly 

emissions

URBAN LD values are:

Mon-Fri 

14.8% 14.8% 14.8% 14.8% 

16.0%

Sat Sun 13.4% and 11.6% 

Weekly_code (for 

SMOKE) =20031

Use same as profile 

as urban local 

roads.

(Rdtype=330).

Code = 2012 (see 

Figure 3-3, yellow

curve)

Same as above 
64

GASOLINE VEHICLE TYPES

SCC&Description Surrogate

Temporal 

Profile: 

Monthly 

Variation

Temporal Profile:

Day of Week Variation

Temporal Profile: 

Diurnal variation Speciation Profile

Motorcycles (MC) -

parking areas rural

2201070350

Heavy Duty 

Gasoline Vehicles 

2B through 8B & 

Buses (HDGV)-

parking areas rural

Commercial 

plus 

Industrial 

plus 

Institutional 

(code = 520)

Not 

applicable 

–

inventory 

contains 

monthly 

emissions

RURAL HD values are:

Mon-Fri 

16.8% 16.8% 16.8% 16.8% 

15.9%

Sat Sun 8.8% and 8.8% 

Weekly_code (for 

SMOKE) =20022

Use same as profile 

rural local roads.

Code = 2006 (see 

Figure 3-3, reddish 

curve)

Same as above 

2201070370

Heavy Duty 

Gasoline Vehicles 

2B through 8B & 

Buses (HDGV)-

parking areas urban

Same as 

above

Not 

applicable 

–

inventory 

contains 

monthly 

emissions

URBAN HD values are:

Mon-Fri 

17.7% 17.7% 17.7% 17.7% 

17.7%

Sat Sun 7% and 5% 

Weekly_code (for 

SMOKE) =20032

Use same as profile 

on urban local 

roads.

Code = 2012 (see 

Figure 3-3, yellow

curve)

Same as above 
65

Table 3-15. Summary of spatial surrogates, temporal profiles, and speciation profiles used by diesel vehicle types for the onroad 

parking area-related SCCs from MOVES2010.

DIESEL VEHICLE TYPES

SCC&Description Surrogate

Temporal 

Profile: 

Monthly 

Variation

Temporal Profile:

Day of Week Variation

Temporal Profile: 

Diurnal variation Speciation Profile

2230001350 Light Duty Diesel 

Vehicles (LDDV)- parking areas 

rural

2230060350 Light Duty Diesel 

Trucks 1 through 4 (M6) (LDDT) 

)- parking areas rural

Rural 

Population 

(same as rural 

local roads)

130

Not 

applicable 

– inventory 

contains

monthly 

emissions

RURAL LD values are:

Mon –Fri 12.1% 12.1% 

12.1% 12.1% 18.3% 

Sat/Sun: 15.3% 18.3% 

Weekly_code (for SMOKE) 

=20021

Rationale: choose same 

weekend/weekday variation 

for all Light Duty Vehicles 

on all rural road types

Use same as profile as 

rural local roads 

(Rdtype=210).

Code = 2006 (see Figure 

3-3, reddish curve)

Rationale: choose same 

diurnal profile for all 

vehicles (except HDDV 

2B to 8B) for all rural 

parking areas (which is the 

profile used for rural local 

roads)

Use same speciation profiles as what is used for LD 

DIESEL vehicles, irrespective of road type.

i.e.: 

EVP__VOC: ZERO emissions (placeholder profile is 

required by SMOKE: 4547 (Gasoline Headspace Vapor 

- Circle K Diesel - adjusted for oxygenates)

EXH__VOC: 4674 (Diesel Exhaust - Medium Duty 

Trucks)

PM2.5 : ZERO emissions not needed since OTAQ 

supplies pre-speciated emissions. Placeholder profile is 

required by SMOKE: 92042 (LDDV Exhaust –

Simplified)

BRK_PM2.5 and TIR_PM2.5 use same as other 

roadways (92009 and 92087, respectively)

2230001370 Light Duty Diesel 

Vehicles (LDDV)- parking areas 

urban

2230060370 Light Duty Diesel 

Trucks 1 through 4 (M6) (LDDT) 

)- parking areas urban

URBAN 

Population 

(same as 

urban local 

roads)

120

Not 

applicable 

– inventory 

contains 

monthly 

emissions

URBAN LD values are:

Mon-Fri 

14.8% 14.8% 14.8% 14.8% 

16.0%

Sat Sun 13.4% and 11.6% 

Weekly_code (for SMOKE) 

=20031

Rationale: choose same 

weekend/weekday variation 

for all Light Duty Vehicles 

on urban road types

Use same as profile as 

urban local roads.

(Rdtype=330).

Code = 2012 (see Figure 

3-3, yellow curve

Rationale: choose same 

diurnal profile for all 

vehicles (except HDDV 

2B to 8B) for all rural 

parking areas (which is the 

profile used for rural local 

roads)

Same as above
66

DIESEL VEHICLE TYPES

SCC&Description Surrogate

Temporal 

Profile: 

Monthly 

Variation

Temporal Profile:

Day of Week Variation

Temporal Profile: 

Diurnal variation Speciation Profile

2230071350 Heavy Duty Diesel 

Vehicles (HDDV) Class 2Bparking areas rural

2230072350 Heavy Duty Diesel 

Vehicles (HDDV) Class 3, 4, & 5-

parking areas rural

2230073350 Heavy Duty Diesel 

Vehicles (HDDV) Class 6 & 7-

parking areas rural

2230074350 Heavy Duty Diesel 

Vehicles (HDDV) Class 8A & 8Bparking areas rural

Rural primary 

roads 

code=210

Rationale: 

most idling 

will occur at 

truckstops

Not 

applicable 

– inventory 

contains 

monthly 

emissions

RURAL HD values are:

Mon-Fri 

16.8% 16.8% 16.8% 16.8% 

15.9%

Sat Sun 8.8% and 8.8% 

Weekly_code (for SMOKE) 

=20022

Construct new profile 

CODE=3000 which is low 

at daytime and high at 

night-time (11pm to 2am)

See Figure 3-4

Use same speciation profiles as what is used for HD 

DIESEL vehicles, irrespective of road type.

i.e.: 

EVP__VOC: ZERO emissions (placeholder profile is 

required by SMOKE: 4547 (Gasoline Headspace Vapor 

- Circle K Diesel - adjusted for oxygenates)

EXH__VOC: 4674 (Diesel Exhaust - Medium Duty 

Trucks)

PM2.5: ZERO emissions not needed since OTAQ 

supplies pre-speciated emissions. Placeholder profile is 

required by SMOKE: 92035 (HDDV Exhaust –

Simplified)

BRK_PM2.5 and TIR_PM2.5 use same as other 

roadways (92009 and 92087, respectively)

2230071370 Heavy Duty Diesel 

Vehicles (HDDV) Class 2Bparking areas urban

2230072370 Heavy Duty Diesel 

Vehicles (HDDV) Class 3, 4, & 5-

parking areas urban

2230073370 Heavy Duty Diesel 

Vehicles (HDDV) Class 6 & 7-

parking areas urban

2230074370 Heavy Duty Diesel 

Vehicles (HDDV) Class 8A & 8Bparking areas urban

URBAN 

primary roads 

code=200

Rationale: 

most idling 

will occur at 

truckstops

Not 

applicable 

– inventory 

contains 

monthly 

emissions

URBAN LD values are:

Mon-Fri 

14.8% 14.8% 14.8% 14.8% 

16.0%

Sat Sun 13.4% and 11.6% 

Weekly_code (for SMOKE) 

=20031

Construct new profile 

CODE=3000 which is low 

at daytime and high at 

night-time (11pm to 2am)

See Figure 3-4

Same as above
67

DIESEL VEHICLE TYPES

SCC&Description Surrogate

Temporal 

Profile: 

Monthly 

Variation

Temporal Profile:

Day of Week Variation

Temporal Profile: 

Diurnal variation Speciation Profile

2230075350 Heavy Duty Diesel 

Buses (School & Transit) - parking 

areas rural

Rural 

Population 

(same as rural 

local roads)

130

Not 

applicable 

– inventory 

contains 

monthly 

emissions

USE URBAN LD values:

Mon-Fri 

14.8% 14.8% 14.8% 14.8% 

16.0%

Sat Sun 13.4% and 11.6% 

Weekly_code (for SMOKE) 

=20031

Rationale: these vehicles

follow profile of LD vehicles 

better than HD; day of week 

variation should more 

closely follow urban (higher 

weekday than weekend)

Use same as profile as 

rural local roads 

(Rdtype=210).

Code = 2006 (see Figure 

3-3, reddish curve)

Rationale: choose same 

diurnal profile for all 

vehicles (except HDDV 

2B to 8B) for all rural 

parking areas (which is the 

profile used for rural local 

roads)

Same as above

2230075370 Heavy Duty Diesel 

Buses (School & Transit) - parking 

areas urban

URBAN 

Population 

(same as 

urban local 

roads)

120

Not 

applicable 

– inventory 

contains 

monthly 

emissions

USE URBAN LD values:

Mon-Fri 

14.8% 14.8% 14.8% 14.8% 

16.0%

Sat Sun 13.4% and 11.6% 

Weekly_code (for SMOKE) 

=20031

Use same as profile as 

urban local roads.

(Rdtype=330).

Code = 2012 (see Figure 

3-3, yellow curve

Rationale: choose same 

diurnal profile for all 

vehicles (except HDDV 

2B to 8B) for all rural 

parking areas (which is the 

profile used for rural local 

roads)

Same as above
68

4 Development of 2012 and 2014 Base-Case Emissions

This section describes the methods we used for developing the 2012 and 2014 future-year base-case

emissions. The year 2012 source apportionment scenarios and the 2014 EGU remedy (i.e., “control”) case 

are discussed in Sections 5 and 6, respectively. The ancillary input data in the future-year scenarios are very 

similar to those used in the 2005 base case except for the speciation profiles used for gasoline-related 

sources, which change in the future to account for increased ethanol usage in gasoline. Table B-1 of 

Appendix B is a table of differences between these ancillary input data between the 2005 base case and these 

future-year scenarios. Appendix B also provides the values for the main parameters used in the emissions 

modeling cases in Table B-2. The specific speciation profile changes are discussed in Sections 4.2.8 and 

4.3.5. A list of inventory datasets used for this and all cases is provided in Appendix C.

The future base-case projection methodologies vary by sector. The 2012 and 2014 base cases represent 

predicted emissions in the absence of any further controls beyond those Federal and State measures already 

promulgated before emissions processing on the Transport Rule began in December, 2010. For EGU 

emissions (ptipm sector), the emissions reflect state rules and federal consent decrees through December 1, 

2010. For mobile sources (on_noadj, on_moves_runpm, and on_moves_startpm sectors), all national 

measures for which data were available at the time of modeling have been included. The future base-case 

scenarios do reflect projected economic changes and fuel usage for EGU and mobile sectors. For nonEGU 

point (ptnonipm sector) and nonpoint stationary sources (nonpt, ag, and afdust sectors), local control 

programs that might have been necessary for areas to attain the 1997 PM2.5 NAAQS annual standard, 2006 

PM NAAQS (24-hour) standard, and the 1997 ozone NAAQS are generally not included in the future basecase projections for most states. One exception are some NOx and VOC reductions associated with the New 

York, Virginia, and Connecticut State Implementation Plans (SIP), which were added as part of the 

comments received from the Transport Rule Proposal and a larger effort to start including more local control 

information on stationary non-EGU sources; this is described further in Section 4.2. The following bullets 

summarize the projection methods used for sources in the various sectors, while additional details and data 

sources are given in Table 4-1.

IPM sector (ptipm): Unit-specific estimates from IPM, version 4.10.

Non-IPM sector (ptnonipm): Projection factors and percent reductions reflect Transport Rule 

comments and emission reductions due to control programs, plant closures, consent decrees and 

settlements, and 1997 and 2001 ozone State Implementation Plans in NY, CT, and VA. We also used

projection approaches for point-source livestock, and aircraft and gasoline stage II emissions that are 

consistent with projections used for the sectors that contain the bulk of these emissions. Terminal 

area forecast (TAF) data aggregated to the national level were used for aircraft to account for 

projected changes in landing/takeoff activity. Year-specific speciation was applied to some portions 

of this sector and is discussed in Section 4.2.8.

Average fires sector (avefire): No growth or control.

Agricultural sector (ag): Projection factors for livestock estimates based on expected changes in 

animal population from 2005 Department of Agriculture data; no growth or control for NH3

emissions from fertilizer application.

Area fugitive dust sector (afdust): Projection factors for dust categories related to livestock estimates 

based on expected changes in animal population; no growth or control for other categories in this 

sector.
69

Remaining Nonpoint sector (nonpt): Projection factors that implement Transport Rule Proposal 

comments and reflect emission reductions due to control programs. Residential wood combustion

projections based on growth in lower-emitting stoves and a reduction in higher emitting stoves. PFC 

projection factors reflecting impact of the final Mobile Source Air Toxics (MSAT2) rule. Gasoline 

stage II projection factors based on National Mobile Inventory Model (NMIM)-estimated VOC 

refueling estimates for future years. Oil and gas projection estimates are provided for the nonCalifornia WRAP states as well as Oklahoma and Texas. Year-specific speciation was applied to 

some portions of this sector and is discussed in Section 4.2.8.

Nonroad mobile sector (nonroad): Other than for California, this sector uses data from a run of 

NMIM that utilized the NR05d-Bond-final version of NONROAD (which is equivalent to 

NONROAD2008a), using future-year equipment population estimates and control programs to the 

years 2012 and 2015 and using national level inputs. Year 2014 emissions were created by 

interpolating 2012 and 2015 emissions. Final controls from the final locomotive-marine and small 

spark ignition OTAQ rules are included. California-specific data provided by the state of California, 

except NH3 used 2012 and 2014 (interpolated) NMIM. Year-specific speciation was applied to some 

portions of this sector and is discussed in Section 4.3.5.

Locomotive, and non-Class 3 commercial marine sector (alm_no_c3): Projection factors for Class 1 

and Class 2 commercial marine and locomotives which reflect Transport Rule comments and activity 

growth and final locomotive-marine controls.

Class 3 commercial marine vessel sector (seca_c3): Base-year 2005 emissions grown and controlled 

to 2012 and 2014, incorporating Transport Rule comments and controls based on Emissions Control 

Area (ECA) and International Marine Organization (IMO) global NOX and SO2 controls.

Onroad mobile sector with no adjustment for daily temperature (on_noadj): MOVES2010 run (statemonth) for 2012 and 2014 with results disaggregated to the county level in proportion to NMIM 2012 

and NMIM 2015 emissions estimates. Temperature impacts at the monthly average resolution. 

California-specific data provided by the state of California, except NH3 which was obtained from 

MOVES2010. VOC speciation uses different future-year values to take into account both the 

increase in ethanol use, and the existence of Tier 2 vehicles that use a different speciation profile. 

Other than California, this sector includes all non-refueling onroad mobile emissions (exhaust, 

evaporative, brake wear and tire wear modes) except exhaust mode gasoline PM and naphthalene 

emissions that are provided in the on_moves_startpm and on_moves_runpm sectors.

Onroad PM gasoline running mode sector (on_moves_startpm): Running mode MOVES2010 year 

2012 and 2014 future-year state-month estimates for PM and naphthalene, apportioned to the county 

level using NMIM 2012 and NMIM 2015 state-county ratios matched to vehicle and road types. Use 

future-year temperature adjustment file for adjusting the 72°F emissions to ambient temperatures (for 

elemental and organic carbon) based on grid cell hourly temperature (note that lower temperatures 

result in increased emissions).

Onroad PM gasoline start mode sector (on_moves_startpm): Cold start MOVES2010 future-year 

2012 and 2014 state-month estimates for PM and naphthalene, apportioned to the county level using 

NMIM 2012 and NMIM 2015 state-county ratios of local urban and rural roads by vehicle type. Use 

future-year temperature adjustment file for adjusting the 72°F emissions (for elemental and organic 

carbon) to ambient temperatures based on grid cell hourly temperatures (lower temperatures result in 

increased emissions).

Other nonroad/nonpoint (othar): No growth or control. 

Other onroad sector (othon): No growth or control.

Other nonroad/nonpoint (othar): No growth or control.
70

Other point (othpt): No growth or control.

Biogenic: 2005 emissions used for all future-year scenarios.

Table 4-1 summarizes the control strategies and growth assumptions by source type that were used to create 

the 2012 and 2014 base-case emissions from the 2005v4.2 base-case inventories. All Mexico, Canada, and 

offshore oil emissions are unchanged in all future cases from those in the 2005 base case. Emission 

summaries by sector for 2005 and future years are provided in Section 7. Note that mercury (Hg) is listed in 

the pollutants column; however, we did not include Hg in our v4.2 modeling. Note that a few controls are 

not fully promulgated by 2012 but are by 2014. For example the Maximum Achievable Control Technology 

(MACT) rule “Boat Manufacturing” has a compliance date in year 2013; therefore the VOC control 

associated with this MACT rule is not reflected in the 2012 base case but is reflected in the 2014 base and 

control cases.

Lists of the control, closures, projection packets (datasets) used to create Transport Rule 2012 and 2014 

future year base-case scenario inventories from the 2005 base case are provided in Appendix D. Additional 

summaries on the emissions changes resulting from these various control programs that were too large to 

include in this section can be found in Appendix D, and the following files are provided with the Transport 

Rule final emissions data on http://www.epa.gov/ttn/chief/emch/index.html: 

TransportRuleFinal_2012_Projection_info.xlsx and TransportRuleFinal_2014_Projection_info.xlsx.

The remainder of this section is organized either by source sector or by specific emissions category within a 

source sector for which a distinct set of data were used or developed for the purpose of projections for the 

Transport Rule. This organization allows consolidation of the discussion of the emissions categories that are 

contained in multiple sectors, because the data and approaches used across the sectors are consistent and do 

not need to be repeated. Sector names associated with the emissions categories are provided in parentheses.
71

Table 4-1. Control strategies and growth assumptions for creating the 2012 and 2014 base-case emissions 

inventories from the 2005 base case

Control Strategies and/or growth assumptions

(grouped by affected pollutants or standard and approach used to 

apply to the inventory)

Pollutants 

affected

Approach/ 

Reference

Non-EGU Point (ptnonipm sector) projection approaches carried forward 

from the Proposed Transport Rule

MACT rules, national, VOC: national applied by SCC, MACT

Boat Manufacturing (promulgated in year 2013, thus not reflected in the 2012 base 

case)

Wood Building Products Surface Coating

Generic MACT II: Spandex Production, Ethylene manufacture

Large Appliances

Miscellaneous Organic NESHAP (MON): Alkyd Resins, Chelating Agents, Explosives, 

 Phthalate Plasticizers, Polyester Resins, Polymerized Vinylidene Chloride

Reinforced Plastics

Asphalt Processing & Roofing

Iron & Steel Foundries

Metal: Can, Coil

Metal Furniture

Miscellaneous Metal Parts & Products

Municipal Solid Waste Landfills

Paper and Other Web

Plastic Parts

Plywood and Composite Wood Products

Carbon Black Production

Cyanide Chemical Manufacturing

Friction Products Manufacturing

Leather Finishing Operations

Miscellaneous Coating Manufacturing

Organic Liquids Distribution (Non-Gasoline)

Refractory Products Manufacturing

Sites Remediation

VOC EPA, 2007a

Consent decrees on companies (based on information from the Office of Enforcement 

and Compliance Assurance – OECA) apportioned to plants owned/operated by the 

companies

VOC, CO, NOx, 

PM, SO2

1

DOJ Settlements: plant SCC controls for:

Alcoa, TX 

Premcor (formerly Motiva), DE

All 2

Refinery Consent Decrees: plant/SCC controls (a few of these controls are promulgated 

in year 2013, and thus are not reflected in the 2012 base case) NOx, PM, SO2

3

Hazardous Waste Combustion PM 4

Municipal Waste Combustor Reductions –plant level PM 5

Hospital/Medical/Infectious Waste Incinerator Regulations NOX, PM, SO2 EPA, 2005b

Large Municipal Waste Combustors – growth applied to specific plants All (including Hg) 5

MACT rules, plant-level, VOC: Auto Plants VOC 6

MACT rules, plant-level, PM & SO2: Lime Manufacturing PM, SO2 7

MACT rules, plant-level, PM: Taconite Ore PM 8

Additional projections used in the final Transport Rule

modeling for non-EGU point sources (ptnonipm sector)

NESHAP: Portland Cement (09/09/10) – plant level based on Industrial Sector 

Integrated Solutions (ISIS) policy emissions in 2013. The ISIS results are from the ISISCement model runs for the NESHAP and NSPS analysis of July 28, 2010 and include 

closures. (promulgated in year 2013, thus only known closures and new units through 

year 2009 were included for year 2012 –ISIS-based future-year projections included only 

Hg, NOX, SO2, 

PM, HCl 13; EPA,

2010
72

for 2014)

New York ozone SIP controls VOC, NOX,

HAP VOC 14

Additional plant and unit closures provided by state, regional, and the EPA agencies and 

additional consent decrees. Includes updates from Transport Rule comments.

All Appendix D

Emission reductions resulting from controls put on specific boiler units (not due to 

MACT) after 2005, identified through analysis of the control data gathered from the 

Information Collection Request (ICR) from the Industrial/Commercial/Institutional 

Boiler NESHAP.

NOX, SO2, HCl

Section 4.2.6

Reciprocating Internal Combustion Engines (RICE) NESHAP: (SO2 controls for RICE 

are not effective until after 2012, but are applied in 2014)

NOX, CO, PM, 

SO2

15

Replaced 2005 with 2008 emissions for Corn Products International, Cook County, 

Illinois, due to the shutdown of 3 boilers and addition of a new boiler (subject to 

Prevention of Significant Deterioration and Requirements). Agency Identifier: 

031012ABI (ILEPA) 

All

16

State fuel sulfur content rules for fuel oil –effective only in Maine and New York in 2014 SO2 17

Nonpoint (nonpt sector) projection approaches carried forward from the Proposed Transport Rule

Municipal Waste Landfills: projection factor of 0.25 applied All EPA, 2007a

Livestock Emissions Growth from year 2002 to year 2012 and 2014 NH3, PM 9

Residential Wood Combustion Growth and Change-outs from year 2005 to year 2012 

and 2014

All 10

Gasoline Stage II growth and control from year 2005 to year 2012 and 2014 VOC 11

Portable Fuel Container Mobile Source Air Toxics Rule 2 (MSAT2) inventory growth 

and control from year 2005 to year 2012 and 2014

VOC 12

Additional projections used in the final Transport Rule modeling for Nonpoint sources (nonpt sector)

RICE NESHAP: (SO2 controls for RICE are not effective until after 2012, but are 

applied in 2014)

NOX, CO, VOC, 

PM, SO2

15

Use Phase II WRAP 2005 Oil and Gas, but apply year 2012- and year 2014-specific 

RICE controls to these emissions

VOC, SO2, NOX, 

CO

Section 3.2.7

Use 2008 Oklahoma and Texas Oil and Gas, and apply year 2012- and year 2014-

specific RICE controls to these emissions.

VOC, SO2, NOX, 

CO, PM

Section 3.2.7

New York, Connecticut, and Virginia ozone SIP controls VOC 14, 18

State fuel sulfur content rules for fuel oil –effective only in Maine and New York in 2014 SO2 17

APPROACHES/REFERENCES- Stationary Sources:

1. Appendix B in the Proposed Toxics Rule TSD: 

http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf

2. For Alcoa consent decree, used http:// cfpub.epa.gov/compliance/cases/index.cfm; for Motiva: used information sent by 

State of Delaware

3. Used data provided by the EPA, OAQPS, Sector Policies and Programs Division (SPPD).

4. Obtained from Anne Pope, the US EPA - Hazardous Waste Incinerators criteria and hazardous air pollutant controls 

carried over from 2002 Platform, v3.1. 

5. Used data provided by the EPA, OAQPS SPPD expert .

6. Percent reductions and plants to receive reductions based on recommendations by rule lead engineer, and are consistent 

with the reference: EPA, 2007a

7. Percent reductions recommended are determined from the existing plant estimated baselines and estimated reductions as 

shown in the Federal Register Notice for the rule. SO2 percent reduction are computed by 6,147/30,783 = 20% and 

PM10 and PM2.5 reductions are computed by 3,786/13,588 = 28%

8. Same approach as used in the 2006 Clean Air Interstate Rule (CAIR), which estimated reductions of “PM emissions by 

10,538 tpy, a reduction of about 62%.” Used same list of plants as were identified based on tonnage and SCC from 

CAIR: http://www.envinfo.com/caain/June04updates/tiop_fr2.pdf

9. Except for dairy cows and turkeys (no growth), based on animal population growth estimates from the US Department 

of Agriculture (USDA) and the Food and Agriculture Policy and Research Institute. See Section 3.2.1.
73

10. Growth and Decline in woodstove types based on industry trade group data, See Section. 

11. VOC emission ratios of year 2016 (linear interpolation between 2015 and 2020) -specific from year 2005 from the 

National Mobile Inventory Model (NMIM) results for onroad refueling including activity growth from VMT, Stage II 

control programs at gasoline stations, and phase in of newer vehicles with onboard Stage II vehicle controls.

12. VOC and benzene emissions for year 2016 (linear interpolation between 2015 and 2020) from year 2002 from MSAT2

rule (EPA, 2007b)

13. Data files for the cement sector provided by Elineth Torres, the EPA-SPPD, from the analysis done for the Cement 

NESHAP: The ISIS documentation and analysis for the cement NESHAP/NSPS is in the docket of that rulemakingdocket # EPA-HQ-OAR-2002-005. The Cement NESHAP is in the Federal Register: September 9, 2010 (Volume 75, 

Number 174, Page 54969-55066

14. New York NOX and VOC reductions obtained from Appendix J in NY Department of Environmental Conservation 

Implementation Plan for Ozone (February 2008): http://www.dec.ny.gov/docs/air_pdf/NYMASIP7final.pdf. See 

Section 3.2.6.

15. Appendix F in the Proposed Toxics Rule TSD: 

http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf

16. The 2008 data used came from Illinois‟ submittal of 2008 emissions to the NEI.

17. Based on available, enforceable state sulfur rules as of November, 2010: 

http://www.ilta.org/LegislativeandRegulatory/MVNRLM/NEUSASulfur%20Rules_09.2010.pdf , 

http://www.mainelegislature.org/legis/bills/bills_124th/billpdfs/SP062701.pdf , 

http://switchboard.nrdc.org/blogs/rkassel/governor_paterson_signs_new_la.html , 

http://green.blogs.nytimes.com/2010/07/20/new-york-mandates-cleaner-heating-oil/

18. VOC reductions in Connecticut and Virginia obtained from Transport Rule comments.

Onroad mobile and nonroad mobile controls 

(list includes all key mobile control strategies but is not exhaustive)a

National Onroad Rules:

Tier 2 Rule: Signature date February, 2000

2007 Onroad Heavy-Duty Rule: February, 2009

Final Mobile Source Air Toxics Rule (MSAT2): February, 2007

Renewable Fuel Standard: March, 2010

all 1

Local Onroad Programs:

National Low Emission Vehicle Program (NLEV): March, 1998

Ozone Transport Commission (OTC) LEV Program: January,1995

VOC 2

National Nonroad Controls:

Clean Air Nonroad Diesel Final Rule – Tier 4: June, 2004

Control of Emissions from Nonroad Large-Spark Ignition Engines and Recreational 

Engines (Marine and Land Based): “Pentathalon Rule”: November, 2002

Clean Bus USA Program: October, 2007

Control of Emissions of Air Pollution from Locomotives and Marine Compression-Ignition 

Engines Less than 30 Liters per Cylinder: October, 2008

all 3,4,5

Aircraft:

Itinerant (ITN) operations at airports to year 2012 and year 2014 all 6

Locomotives:

Energy Information Administration (EIA) fuel consumption projections for freight rail

Clean Air Nonroad Diesel Final Rule – Tier 4: June 2004

Locomotive Emissions Final Rulemaking, December 17, 1997

Control of Emissions of Air Pollution from Locomotives and Marine: May 2008

all EPA, 2009; 

3; 4; 5

Commercial Marine:

Category 3 marine diesel engines Clean Air Act and International Maritime Organization 

standards (April, 30, 2010) –also includes Transport Rule comments.

EIA fuel consumption projections for diesel-fueled vessels

OTAQ ECA C3 Base 2020 inventory for residual-fueled vessels

Clean Air Nonroad Diesel Final Rule – Tier 4

Emissions Standards for Commercial Marine Diesel Engines, December 29, 1999

Tier 1 Marine Diesel Engines, February 28, 2003

all 7, 3; EPA, 

2009
74

a. These control programs are the same as were used in the Proposed Transport Rule except for the C3 marine standards of 

April 2010, which are included in the Toxics Rule but were not included in the Proposed Transport Rule.

APPROACHES/REFERENCES – Mobile Sources

1. http://epa.gov/otaq/hwy.htm

2. Only for states submitting these inputs: http://www.epa.gov/otaq/lev-nlev.htm

3. http://www.epa.gov/nonroad-diesel/2004fr.htm

4. http://www.epa.gov/cleanschoolbus/

5. http://www.epa.gov/otaq/marinesi.htm

6. Federal Aviation Administration (FAA) Terminal Area Forecast (TAF) System, December 2008: 

http://www.apo.data.faa.gov/main/taf.asp

7. http://www.epa.gov/otaq/oceanvessels.htm

4.1 Stationary source projections: EGU sector (ptipm)

The future-year data for the ptipm sector used in the air quality modeling were created by version 4.10 

(v4.10) of the Integrated Planning Model (IPM) (http://www.epa.gov/airmarkt/progsregs/epaipm/index.html). The IPM is a multiregional, dynamic, deterministic linear programming model of the U.S. 

electric power sector. Version 4.10 reflects state rules and consent decrees through December 1, 2010 and 

incorporates information on existing controls collected through the Information Collection Request (ICR), 

and information from comments received on the IPM-related Notice of Data Availability (NODA) published 

on September 1, 2010. IPM v4.10 Final included the addition of over 20 GW of existing Activated Carbon 

Injection (ACI) reported to the EPA via the ICR. Units with SO2 or NOX advanced controls (e.g., scrubber, 

SCR) that were not required to run for compliance with Title IV, New Source Review (NSR), state 

settlements, or state-specific rules were modeled by IPM to either operate those controls or not based on 

economic efficiency parameters.

Updates to IPM 4.10 (with respect to the version released in the IPM NODA version) include adjustments to 

assumptions regarding the performance of acid gas control technologies, new costs imposed on fuelswitching (e.g., bituminous to sub-bituminous), correction of lignite availability to some plants, 

incorporation of additional planned retirements, a more inclusive implementation of the scrubber upgrade 

option, and the availability of a scrubber retrofit to waste-coal fired fluidized bed combustion units without 

an existing scrubber. Further details on the future-year EGU emissions inventory used for this rule can be 

found in the incremental documentation of the IPM v.4.10 platform, available at 

http://www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev410.html. Note that the Transport Rule futureyear base cases do not include the Toxics Rule, which was proposed on March 16, 2011. In addition, the 

Boiler MACT was not represented in the final Transport Rule modeling because the rule was not final at the 

time the modeling was performed.

IPM is run in 5 year increments beyond year 2015. IPM results were generated for 2012 and 2015. The IPM 

2015 results are valid for representing 2014, 2015, and 2016. As explained in the Transport Rule IPM TSD, 

additional steps were taken to ensure that the results were valid for use in a 2014, 2015 (or 2016) model run.

Directly emitted PM emissions (i.e., PM2.5 and PM10) from the EGU sector are computed via a post 

processing routine which applies emission factors to the IPM-estimated fuel throughput based on fuel, 

configuration and controls to compute the filterable and condensable components of PM. This methodology 

is documented in the IPM TSD.
75

4.2 Stationary source projections: non-EGU sectors (ptnonipm, nonpt, ag, 

afdust)

To project U.S. stationary sources other than the ptipm sector, we applied growth factors and/or controls to 

certain categories within the ptnonipm, nonpt, ag and afdust platform sectors. This subsection provides 

details on the data and projection methods used for these sectors. In estimating future-year emissions, we 

assumed that emissions growth does not track with economic growth for many stationary non-IPM sources. 

This “no-growth” assumption is based on an examination of historical emissions and economic data. While 

we are working toward improving the projection approach in future emissions platforms, we are still using 

the no-growth assumption for the 2005, v4.2 platform. More details on the rationale for this approach can be 

found in Appendix D of the Regulatory Impact Assessment for the PM NAAQS rule (EPA, 2006b). 

The starting point was the emission projections done for the 2005v4 platform for the Proposed Transport 

Rule. The 2012 and 2014 projection factors developed for the Transport Rule Proposal (see 

http://www.epa.gov/ttn/chief/emch/index.html#transport) were updated for these 2012 and 2014 baseline 

projections. Several additional National Emission Standards for Hazardous Air Pollutants (NESHAPs) were 

promulgated since emission projections were done for the Proposed Transport Rule, and these were included 

for the 2012 and 2014 base cases. Also included in the 2012 and 2014 base cases are numerous future-year

projection data from the Transport Rule comments; these data are described in the following sections.

Year-specific projection factors for years 2012 and 2014 were used for creating the 2012 and 2014 base 

cases unless noted otherwise. Growth factors (and control factors) are provided in the following sections 

where feasible. However, some sectors used growth or control factors that varied geographically and their 

contents could not be provided in the following sections (e.g., gasoline distribution varies by county and 

pollutant and has thousands of records). If the growth or control factors for a sector are not provided in a 

table in this document, they are available as a “projection” or “control” packet for input to SMOKE on the 

v4.2 platform website (see the end of Section Error! Reference source not found.). 

4.2.1 Livestock emissions growth (ag, afdust)

Growth in ammonia (NH3) and dust (PM10 and PM2.5) emissions from livestock in the ag and afdust and 

ptnonipm sectors was based on projections of growth in animal population. While there are a very small 

amount of livestock emissions in the ptnonipm sector as compared to the ag sector, the livestock growth 

projection packet was inadvertently not applied to the ptnonipm that sector. This results in an underestimate 

of NH3 in the ptnonipm sector of roughly 1,160 tons in 2012 and 1,390 tons in 2014 (primarily in Kansas and 

Minnesota for which the NH3 were reported at specific farms in the point source inventory), and for PM2.5

the ptnonipm sector underestimates are 3 tons in both 2012 and 2014. These omissions are expected to have 

a negligible impact on the air quality PM and ozone results and these omissions were made in both the future 

base case and Transport Rule policy case.

Table 4-2 provides the growth factors from the 2005 base-case emissions to 2012 and 2014 for animal 

categories applied to the ag and afdust sectors for livestock-related SCCs. For example, year 2014 beef 

emissions are 1.7% larger than the 2005 base-case emissions. Except for dairy cows and turkey production, 

the animal projection factors are derived from national-level animal population projections from the U.S. 

Department of Agriculture (USDA) and the Food and Agriculture Policy and Research Institute (FAPRI). 

For dairy cows and turkeys, we assumed that there would be no growth in emissions. This assumption was 

based on an analysis of historical trends in the number of such animals compared to production rates. 

Although productions rates have increased, the number of animals has declined. Thus, we do not believe 

that production forecasts provide representative estimates of the future number of cows and turkeys; 

therefore, we did not use these forecasts for estimating future-year emissions from these animals. In 
76

particular, the dairy cow population is projected to decrease in the future as it has for the past few decades; 

however, milk production will be increasing over the same period. Note that the ammonia emissions from 

dairies are not directly related to animal population but also nitrogen excretion. With the cow numbers going 

down and the production going up we suspect the excretion value will be changing, but we assumed no 

change because we did not have a quantitative estimate.

The inventory for livestock emissions used 2002 emissions values therefore, our projection method projected 

from 2002 rather than from 2005. 

Appendix E in the 2002v3 platform documentation provides the animal population data and regression 

curves used to derive the growth factors: 

http://www.epa.gov/scram001/reports/Emissions%20TSD%20Vol2_Appendices_01-15-08.pdf. Appendix F 

in the same document provides the cross references of livestock sources in the ag, afdust and ptnonipm 

sectors to the animal categories in Table 4-2.

Table 4-2. Growth factors from year 2005 to future years for Animal Operations

Animal Category

Projection Factors

2012 2014

Dairy Cow 1.000 1.000

Beef 1.014 1.017

Pork 1.060 1.071

Broilers 1.230 1.275

Turkeys 1.000 1.000

Layers 1.160 1.193

Poultry Average 1.178 1.214

Overall Average 1.0623 1.075

4.2.2 Residential wood combustion growth (nonpt)

We projected residential wood combustion emissions based on the expected increase in the number of lowemitting wood stoves and the corresponding decrease in other types of wood stoves. As newer, cleaner 

woodstoves replace older, higher-polluting wood stoves, there will be an overall reduction of the emissions 

from these sources. The approach cited here was developed as part of a modeling exercise to estimate the 

expected benefits of the woodstoves change-out program (http://www.epa.gov/burnwise). Details of this 

approach can be found in Section 2.3.3 of the PM NAAQS Regulatory Impact Analysis (EPA, 2006b).

The specific assumptions we made were:

 Fireplaces, SCC=2104008001: increase 1%/year

 Old woodstoves, SCC=2104008002, 2104008010, or 2104008051: decrease 2%/year

 New woodstoves, SCC=2104008003, 2104008004, 2104008030, 2104008050, 2104008052 or 

2104008053: increase 2%/year

For the general woodstoves and fireplaces category (SCC 2104008000) we computed a weighted average 

distribution based on 19.4% fireplaces, 71.6% old woodstoves, 9.1% new woodstoves using 2002v3 

Platform (these emissions have not been updated for the 2005v4 platform used for the Transport Rule

Proposal 2005v4) emissions for PM2.5. These fractions are based on the fraction of emissions from these 

processes in the states that did not have the “general woodstoves and fireplaces” SCC in the 2002v3 NEI. 

This approach results in an overall decrease of 1.056% per year for this source category.
77

Table 4-3 presents the projection factors used to project the 2005 base case (2002 emissions) for residential 

wood combustion. 

Table 4-3. Projection Factors for growing year 2005 Residential Wood Combustion Sources

SCC SCC Description

Projection Factors

2012 2014

2104008000 Total: Woodstoves and Fireplaces 0.8944 0.8733

2104008001 Fireplaces: General 1.10 1.12 2104008070 Outdoor Wood Burning Equipment

2104008002 Fireplaces: Insert; non-EPA certified

2104008010 Woodstoves: General 0.80 0.76

2104008051 Non-catalytic Woodstoves: Non-EPA certified

2104008003 Fireplaces: Insert; EPA certified; non-catalytic

1.20 1.24

2104008004 Fireplaces: Insert; EPA certified; catalytic

2104008030 Catalytic Woodstoves: General

2104008050 Non-catalytic Woodstoves: EPA certified

2104008052 Non-catalytic Woodstoves: Low Emitting

2104008053 Non-catalytic Woodstoves: Pellet Fired

4.2.3 Gasoline Stage II growth and control (nonpt, ptnonipm)

Emissions from Stage II gasoline operations in the 2005 base case are contained in both nonpt and ptnonipm 

sectors. The only SCC in the nonpt inventory used for gasoline Stage II emissions is 2501060100 (Storage 

and Transport; Petroleum and Petroleum Product Storage; Gasoline Service Stations; Stage II: Total). The 

following SIC and SCC codes are associated with gasoline Stage II emissions in the ptnonipm sector:

 SIC 5541 (Automotive Dealers & Service Stations, Gasoline Service Stations, Gasoline service 

stations)

 SCC 40600401 (Petroleum and Solvent Evaporation;Transportation and Marketing of Petroleum 

Products;Filling Vehicle Gas Tanks - Stage II;Vapor Loss w/o Controls)

 SCC 40600402 (Petroleum and Solvent Evaporation;Transportation and Marketing of Petroleum 

Products;Filling Vehicle Gas Tanks - Stage II;Liquid Spill Loss w/o Controls)

 SCC 40600403 (Petroleum and Solvent Evaporation;Transportation and Marketing of Petroleum 

Products;Filling Vehicle Gas Tanks - Stage II;Vapor Loss w/o Controls)

 SCC 40600499 (Petroleum and Solvent Evaporation;Transportation and Marketing of Petroleum 

Products;Filling Vehicle Gas Tanks - Stage II;Not Classified

We used a consistent approach across nonpt and ptnonipm to project these gasoline stage II emissions. The 

approach involved computing state-level VOC-specific projection factors from the state-level MOVES2010-

based results for onroad refueling, using ratios of future–year 2012 and 2014 refueling emissions to 2005 

base-case emissions. The approach accounts for three elements of refueling growth and control: (1) activity 

growth (due to VMT growth as input into MOVES2010), (2) emissions reductions from Stage II control 

programs at gasoline stations, and (3) emissions reductions resulting from the phase-in over time of newer 

vehicles with onboard Stage II vehicle controls. We assumed that all areas with Stage II controls in 2005 

continue to have Stage II controls in 2012 and 2014. This approach is an update from the 2005v4 platform 
78

projections in the Proposed Transport Rule; in that platform, NMIM refueling projections were used instead 

of MOVES2010.

We computed VOC, benzene and naphthalene projection factors at a county-specific, annual resolution as 

shown below; note that naphthalene, while provided by MOVES2010, is not used in the Transport Rule:

PF_VOC[state, future year] = VOC_RFL[state, future year]/VOC_RFL[state, 2005],

PF_BENZENE[state, future year] = BENZENE_RFL[state, future year]/ BENZENE _RFL[state, 2005], and 

PF_NAPHTHALENE[state, future year] = PF_VOC[state, future year]

where VOC_RFL is the VOC refueling emissions for onroad sources from MOVES2010, and

BENZENE_RFL is the BENZENE refueling emissions for onroad sources from MOVES2010

We applied these projection factors to both nonpt and ptnonipm sector gasoline stage II sources.

Chemical speciation uses certain VOC HAPs for some sources, specifically, benzene, acetaldehyde, 

formaldehyde, and methanol (BAFM). The VOC HAPs are used for sources that have consistent VOC and 

VOC HAPs using various criteria as described in the Section3.1.2.1, and these sources are called 

“integrated” sources. The nonpoint gasoline stage II emissions are an integrated source, and so the VOC 

HAPs are also projected based on ratios of future-year and base-year VOC. The only two VOC HAPs 

emitted from refueling are benzene and naphthalene, and both of these were projected consistently with 

VOC. However, naphthalene was not used in the chemical speciation (it is not B,A,F or M) and was 

therefore not used for this effort. Benzene was used as part of the speciation for the nonpt sector gasoline 

stage II sources. The ptnonipm is a “no-integrate” sector, so ptnonipm gasoline stage II sources did not use 

the projected benzene as part of the speciation, but rather used VOC speciation to estimate benzene.

4.2.4 Portable fuel container growth and control (nonpt)

We obtained future-year VOC emissions from Portable Fuel Containers (PFCs) from inventories developed 

and modeled for the EPA‟s MSAT2 rule (EPA, 2007a). The 10 PFC SCCs are summarized below (note that 

the full SCC descriptions for these SCCs include “Storage and Transport; Petroleum and Petroleum Product 

Storage” as the beginning of the description). 

2501011011 Residential Portable Fuel Containers: Permeation

2501011012 Residential Portable Fuel Containers: Evaporation

2501011013 Residential Portable Fuel Containers: Spillage During Transport

2501011014 Residential Portable Fuel Containers: Refilling at the Pump: Vapor Displacement

2501011015 Residential Portable Fuel Containers: Refilling at the Pump: Spillage

2501012011 Commercial Portable Fuel Containers: Permeation

2501012012 Commercial Portable Fuel Containers: Evaporation

2501012013 Commercial Portable Fuel Containers: Spillage During Transport

2501012014 Commercial Portable Fuel Containers: Refilling at the Pump: Vapor Displacement

2501012015 Commercial Portable Fuel Containers: Refilling at the Pump: Spillage

Additional information on the PFC inventories is available in Section 2.2.3 of the documentation for the 

2002 Platform (http://www.epa.gov/ttn/chief/emch/index.html#2002). 

The future-year emissions reflect projected increases in fuel consumption, state programs to reduce PFC 

emissions, standards promulgated in the MSAT2 rule, and impacts of the Renewable Fuel Standard (RFS) on 
79

gasoline volatility. Future-year emissions for PFCs were available for 2010, 2015, 2020, and 2030. In 

creating the inventories for 2012 and 2014, we linearly interpolated year 2010 and year 2015 inventories. 

Benzene and other VOC HAP future-year PFC emissions were also included in the interpolation. Benzene 

was used in VOC speciation for the air quality model through the modification of VOC speciation profiles 

calculations (no other BAFM HAPs are emitted from PFCs).

4.2.5 Aircraft growth (ptnonipm)

As with the 2005v4 platform, aircraft emissions are contained in the ptnonipm inventory. These 2005 pointsource emissions are projected to future years by applying activity growth using data on itinerant (ITN) 

operations at airports. The ITN operations are defined as aircraft take-offs whereby the aircraft leaves the 

airport vicinity and lands at another airport, or aircraft landings whereby the aircraft has arrived from outside 

the airport vicinity. We used projected ITN information available from the Federal Aviation 

Administration‟s (FAA) Terminal Area Forecast (TAF) System: http://www.apo.data.faa.gov/main/taf.asp

(publication date December 2008). This information is available for approximately 3,300 individual airports, 

for all years up to 2025. We aggregated and applied this information at the national level by summing the 

airport-specific (U.S. airports only) ITN operations to national totals by year and by aircraft operation, for 

each of the four available operation types: commercial, general, air taxi, military. We computed growth 

factors for each operation type by dividing future-year ITN by 2005-year ITN. We assigned factors to 

inventory SCCs based on the operation type. 

The methods that the FAA used for developing the ITN data in the TAF are documented in:

http://www.faa.gov/data_research/aviation/aerospace_forecasts/2009-

2025/media/2009%20Forecast%20Doc.pdf

Table 4-4 provides the national growth factors for aircraft; all factors are applied to year 2005 emissions. 

For example, year 2012 commercial aircraft emissions are 1.9% higher than year 2005 emissions. 

Table 4-4. Factors used to project 2005 base-case aircraft emissions to future years

SCC SCC Description

Projection Factor

2012 2014

2275001000 Military aircraft 0.967 0.968

2275020000 Commercial aircraft 1.019 1.066

2275050000 General aviation 0.962 0.977

2275060000 Air taxi 0.872 0.897

27501015 Internal Combustion Engines;Fixed Wing Aircraft L & TO 

Exhaust;Military;Jet Engine: JP-5

0.967 0.968

27502001 Internal Combustion Engines;Fixed Wing Aircraft L & TO 

Exhaust;Commercial;Piston Engine: Aviation Gas

1.019 1.066

27502011 Internal Combustion Engines;Fixed Wing Aircraft L & TO 

Exhaust;Commercial;Jet Engine: Jet A

1.019 1.066

27505001 Internal Combustion Engines;Fixed Wing Aircraft L & TO 

Exhaust;Civil;Piston Engine: Aviation Gas

0.962 0.977

27505011 Internal Combustion Engines;Fixed Wing Aircraft L & TO 

Exhaust;Civil;Jet Engine: Jet A

0.962 0.977

27601014 Internal Combustion Engines;Rotary Wing Aircraft L & TO 

Exhaust;Military;Jet Engine: JP-4

0.967 0.968

27601015 Internal Combustion Engines;Rotary Wing Aircraft L & TO 

Exhaust;Military;Jet Engine: JP-5

0.967 0.968
80

We did not apply growth factors to any point sources with SCC 27602011 (Internal Combustion Engines; 

Rotary Wing Aircraft L & TO Exhaust; Commercial; Jet Engine: Jet A) because the facility names 

associated with these point sources appeared to represent industrial facilities rather than airports. This SCC 

is only in one county, Santa Barbara, California (State/County FIPS 06083).

None of our aircraft emission projections account for any control programs. We considered the NOX

standard adopted by the International Civil Aviation Organization‟s (ICAO) Committee on Aviation 

Environmental Protection (CAEP) in February 2004, which is expected to reduce NOX by approximately 2% 

in 2015 and 3% in 2020. However, this rule has not yet been adopted as an EPA (or U.S.) rule; therefore, the 

effects of this rule were not included in the future-year emissions projections.

4.2.6 Stationary source control programs, consent decrees & settlements, and plant 

closures (ptnonipm, nonpt)

We applied emissions reduction factors to the 2005 emissions for particular sources in the ptnonipm and 

nonpt sectors to reflect the impact of stationary-source control programs including consent decrees, 

settlements, and plant closures. Some of the controls described in this section were obtained from comments 

on the Transport Rule proposal. Here we describe the contents of the controls and closures for the 2012 and 

2014 base cases. Detailed summaries of the impacts of the control programs are provided in Appendix D.

Controls from the NOX SIP call were assumed to have been implemented by 2005 and captured in the 2005 

base case (2005v2 point inventory). This assumption was confirmed by review of the 2005 NEI that showed 

reductions from Large Boiler/Turbines and Large Internal Combustion Engines in the Northeast states 

covered by the NOx SIP call. The future-year base controls consist of the following:

We did not include MACT rules where compliance dates were prior to 2005, because we assumed 

these were already reflected in the 2005 inventory. The EPA OAQPS Sector Policies and Programs 

Division (SPPD) provided all controls information related to the MACT rules, and this information is 

as consistent as possible with the preamble emissions reduction percentages for these rules.

Various emissions reductions from the Transport Rule comments, including but not limited to: fuel 

switching at units, shutdowns, future-year emission limits, ozone SIP VOC controls for some sources 

in Virginia and Connecticut, and state and local control programs.

Evolutionary information gathering of plant closures (i.e., emissions were zeroed out for future years) 

were also included where information indicated that the plant was actually closed after the 2005 base 

year and prior to Transport Rule modeling that began in the fall of 2010. We also applied unit and 

plant closures received from the Transport Rule comments. However, plants projected to close in the 

future (post-2010) were not removed in the future years because these projections can be inaccurate 

due to economic improvements. We also applied cement kiln (unit) and cement plant closures 

discussed later in Section 4.2.6.1. More detailed information on the overall state-level impacts of all 

control programs and projection datasets, including units and plants closed in the 2012 and 2014 

base-case ptnonipm inventories are provided in Appendix D. The magnitude of all unit and plant 

closures on the non-EGU point (ptnonipm) sector 2005 base-case emissions is shown in Table 4-5

below.
81

Table 4-5. Summary of Non-EGU Emission Reductions Applied to the 2005 Inventory due to Unit and 

Plant Closures

State

CO

(tons)

NH3

(tons)

NOX

(tons)

PM10 

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Alabama 10,680 6 4,104 2,543 2,257 1,912 870

Arizona 509 0 1,524 161 65 7 28

Arkansas 1,110 0 3,994 401 129 920 271

California 2,684 0 6,675 1,121 444 1,161 23

Delaware 93 6 1,495 350 326 5,409 391

Florida 4,136 230 7,869 1,049 577 8,547 246

Georgia 7,435 21 2,678 1,187 765 2,688 2,295

Idaho 625 6 461 14 6 17 1

Illinois 10,175 0 11,605 1,996 1,267 23,830 716

Indiana 1,058 0 4,794 486 207 8,468 157

Iowa 461 0 1,939 230 48 4,787 15

Kansas 989 4 1,624 84 48 329 52

Louisiana 3,035 127 1,878 521 337 4,114 4,061

Maine 256 13 1,906 467 212 3,767 310

Maryland 107 22 1,634 168 83 1,137 6

Massachusetts 45 7 518 114 68 1,909 55

Michigan 7,995 73 10,900 2,274 1,076 14,598 2,083

Mississippi 0 0 69 5 5 96

Missouri 17 4 23 2 2 0 310

Nevada 204 0 2,817 212 74 175 66

New Hampshire 109 0 287 113 103 681 291

New Jersey 9 0 31 24 24 0 996

New York 5 1 48 16 11 217 14

North Carolina 12 1 94 25 17 379 7

Ohio 340 4,238 610 299 7,128 69

Oklahoma 103 4 1,757 531 184 1,498 17

Pennsylvania 1,415 4 6,117 1,293 683 6,852 116

South Carolina 1,666 4 2,115 441 266 1,052 302

Tennessee 106 0 2,229 242 146 5,407 9,065

Texas 5,395 20 9,664 1,264 642 9,216 507

Virginia 3,161 1 3,737 1,355 1,029 11,102 2,188

West Virginia 59,321 55 5,257 1,244 830 13,410 783

Wisconsin 479 28 1,953 436 297 7,672 349

Grand Total 123,735 637 106,034 20,979 12,527 148,485 26,660

In addition to plant closures, we included the effects of the Department of Justice Settlements and 

Consent Decrees on the non-EGU (ptnonipm) sector emissions. We also included estimated impacts 

of HAP standards per Section 112, 129 of the Clean Air Act on the non-EGU (ptnonipm) and 

nonpoint (nonpt) sector emissions, based on expected CAP co-benefits to sources in these sectors.
82

Numerous controls have compliance dates beyond 2008; these include refinery and the Office of 

Compliance and Enforcement (OECA) consent decrees, Department of Justice (DOJ) settlements, as 

well as most national VOC MACT controls. Additional OECA consent decree information is 

provided in Appendix B of the Proposed Toxics Rule TSD: 

http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf. The detailed data 

used are available at the website listed in Section 1. Several of these consent decrees and national 

NESHAP rules such as RICE and cement have compliance dates that are between 2012 and 2014; 

therefore, there are several differences in controls applied to the 2012 and 2014 base cases.

Refinery consent decrees controls at the facility and SCC level (collected through internal

coordination on refineries by the EPA).

Fuel sulfur fuel limits were enforceable in 2014 (not 2012) for Maine and New York. These fuel 

limits were incremental and not applicable until after 2012. Because we only apply controls that are 

applicable before July 1, 2014, more stringent sulfur fuel controls and additional states with controls 

in later years were not applied.

Criteria air pollutant (cap) reductions a cobenefit to RICE NESHAP controls. SO2 RICE cobenefit 

controls are not applied in 2012.

Most of the control programs were applied as replacement controls, which means that any existing 

percent reductions (“baseline control efficiency”) reported in the NEI were removed prior to the 

addition of the percent reductions due to these control programs. Exceptions to replacement controls 

are “additional” controls, which ensure that the controlled emissions match desired reductions 

regardless of the baseline control efficiencies in the NEI. We used the “additional controls” approach 

for many permit limits, settlements and consent decrees where specific plant and multiple-plant-level 

reductions/targets were desired and at municipal waste landfills where VOC was reduced 75% via a 

MACT control using projection factors of 0.25.

We applied New York State Implementation Plan available controls for the 1997 8-hour Ozone 

standard for non-EGU point and nonpoint NOX and VOC sources based on NY State Department of 

Environmental Conservation February 2008 guidance. These reductions are found in Appendix J in: 

http://www.dec.ny.gov/docs/air_pdf/NYMASIP7final.pdf. See Section 3.2.6.

4.2.6.1 2014 base-case reductions from the Portland Cement NESHAP

As indicated in Table 4-1, the Industrial Sectors Integrated Solutions (ISIS) model (EPA, 2010) was used to 

project the cement industry component of the ptnonipm emissions modeling sector to 2014. This approach 

provided reductions of criteria and hazardous air pollutants, including mercury. The ISIS cement emissions 

were developed in support for the Portland Cement NESHAPs and the NSPS for the Portland cement 

manufacturing industry.

The ISIS model produced a Portland Cement NESHAP policy case of multi-pollutant emissions for 

individual cement kilns (emission inventory units) that were relevant for years 2013 through 2017. These 

ISIS-based emissions included information on new cement kilns, facility and unit-level closures, and updated 

policy case emissions at existing cement kilns. The units that opened or closed before 2010 were included in 

the 2012 base case. The ISIS-based policy case predictions of emissions reductions and activity growth were 

only included in the 2014 base case and not in the 2012 base case.

The ISIS model results for the future show a continuation of the recent trend in the cement sector of the 

replacement of lower capacity, inefficient wet and long dry kilns with bigger and more efficient preheater 
83

and precalciner kilns. Multiple regulatory requirements such as the NESHAP and NSPS currently apply to 

the cement industry to reduce CAP and HAP emissions. Additionally, state and local regulatory 

requirements might apply to individual cement facilities depending on their locations relative to ozone and 

PM2.5 nonattainment areas. The ISIS model provides the emission reduction strategy that balances: 1) 

optimal (least cost) industry operation, 2) cost-effective controls to meet the demand for cement, and 3) 

emission reduction requirements over the time period of interest. Table 4-6 shows the magnitude of the 

ISIS-based cement industry reductions in the future-year emissions that represent 2014, and the impact that 

these reductions have on total stationary non-EGU point source (ptnonipm) emissions.

Table 4-6. Future-year ISIS-based cement industry annual reductions (tons/yr) 

for the non-EGU (ptnonipm) sector

Pollutant

Cement Industry 

emissions in 2005

Decrease in cement 

industry emissions 

in 2014 vs 2005

% decrease in 

ptnonipm from 

cement reduction

NOX 193,000 56,740 2.4%

PM2.5 14,400 7,840 1.8%

SO2 128,400 106,000 5.0%

VOC 6,900 5,570 0.4%

HCl 2,900 2,220 4.5%

4.2.6.2 Boiler reductions not associated with the MACT rule

The Boiler MACT ICR collected data on existing controls. We used an early version of a data base 

developed for that rulemaking entitled “survey_database_2008_results2.mdb” (EPA-HQ-OAR-2002-0058-

0788) which is posted under the Technical Information for the Boiler MACT major source rule 

(http://www.epa.gov/ttn/atw/boiler/boilerpg.html). We extracted all controls that were installed after 2005,

determined a percent reduction, and verified with source owners that these controls were actively in use. In 

many situations we learned that the controls were on site but were not in use. A summary of the plant-unit 

specific reductions that were verified to be actively in use are summarized in Table 4-7.

Table 4-7. State-level non-MACT Boiler Reductions from ICR Data Gathering

State Pollutant

Pre-controlled 

Emissions 

(tons)

Controlled 

Emissions 

(tons)

Reductions 

(tons)

Percent 

Reduction 

%

Michigan NOX 907 544 363 40

North Carolina SO2 652 65 587 90

Virginia SO2 3379 338 3041 90

Washington SO2 639 383 256 40

North Carolina HCl 31 3 28 90

4.2.6.3 RICE NESHAP

There are three rulemakings for National Emission Standards for Hazardous Air Pollutants (NESHAP) for 

Reciprocating Internal Combustion Engines (RICE). These rules reduce HAPs from existing and new RICE 
84

sources. In order to meet the standards, existing sources with certain types of engines will need to install 

controls. In addition to reducing HAPs, these controls also reduce CAPs, specifically, CO, NOX, VOC, PM, 

and SO2. In 2014 and beyond, compliance dates have passed for all three rules; thus all three rules are 

included in the emissions projection. In 2012 only the earliest rule‟s compliance date has passed so only one 

rule is included. 

The rules can be found at http://www.epa.gov/ttn/atw/rice/ricepg.html and are listed below:

National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion 

Engines; Final Rule (69 FR 33473) published 06/15/04

National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion 

Engines; Final Rule (FR 9648 ) published 03/03/10

National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion 

Engines; Final Rule (75 FR 51570) published 08/20/2010

The difference among these three rules is that they focus on different types of engines, different facility types 

(major for HAPs, versus area for HAPs) and different engine sizes based on horsepower (HP). In addition, 

they have different compliance dates. We project CAPs from the 2005 NEI RICE sources, based on the 

requirements of the rule for existing sources only because the inventory includes only existing sources and 

the current projection approach does not estimate emissions from new sources.

A complete discussion on the methodology to estimate year 2012 and year 2014 RICE controls is provided in 

Appendix F in the Proposed Toxics Rule TSD: 

http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf. Impacts of the RICE 

controls on stationary non-EGU emissions (nonpt and ptnonipm sectors), excluding WRAP, Texas, and 

Oklahoma oil and gas emissions (see Section 4.2.7) are provided in Table 4-8.

Table 4-8. National Impact of RICE Controls on 2012 and 2014 Non-EGU Projections

Pollutant 2012 Reductions 2014 Reductions

CO 18,987 124,516

NOX 30,250 123,662

PM2.5 0 1,368

PM10 0 1,595

SO2 0 23,368

VOC 1,069 15,934

4.2.6.4 Fuel sulfur rules

Fuel sulfur rules that were signed and implemented by June 30, 2014 are limited to Maine and New York. 

No fuel sulfur rule reductions were available in other states and compliance dates for 2012. As standard 

practice we have used June 30th as the cut-off date for all control programs to be included in a calendar year. 

For example, a control program with a compliance (effective) date of June 30, 2012 would be included in the 

2012 projected emissions; however, a control program effective July 1, 2012 would not be included in 2012 

projections. Several other states have fuel sulfur rules that were in development but not finalized prior to 
85

Transport Rule emissions processing: 

http://www.ilta.org/LegislativeandRegulatory/MVNRLM/NEUSASulfur%20Rules_09.2010.pdf. 

The fuel sulfur content for all home heating oil SCCs in 2005 is assumed to by 3000 part per million (ppm). 

Effective July 1, 2012, New York requires all heating oil sold in New York to contain no more than 15ppm 

of sulfur, thus reducing SO2 emissions by 99.5% for 2014 projections (and no reduction for 2012). These 

New York sulfur content reductions are further discussed here:

http://switchboard.nrdc.org/blogs/rkassel/governor_paterson_signs_new_la.html.

The Maine fuel sulfur rule effective January 1, 2014 reduces sulfur to 500ppm, resulting in an 83.33% 

reduction from 3000 ppm. These Maine sulfur content reductions are discussed here: 

http://www.mainelegislature.org/legis/bills/bills_124th/billpdfs/SP062701.pdf.

Further reductions in NY, ME, and other states effective after June 30, 2014 are not included. The impact of 

these fuel sulfur content reductions on SO2 is shown in Table 4-9.

Table 4-9. Impact of Fuel Sulfur Controls on 2014 Non-EGU Projections

State SO2 Reductions

Maine 7,053

New York 54,431

4.2.7 Oil and gas projections in TX, OK, and non-California WRAP states (nonpt)

For the 2005v4.2 platform, we incorporated updated 2005 oil and gas emissions from Texas and Oklahoma. 

For Texas oil and gas production, we used 2012 and 2014 estimates from the Texas Commission of 

Environmental Quality (TCEQ) and used them as described in: 

http://www.tceq.state.tx.us/assets/public/implementation/air/am/contracts/reports/ei/5820783985FY0901-

20090715-ergi-Drilling_Rig_EI.pdf.

We also received 2008 data for Oklahoma that we used as the best available data to represent 2012 and 2014. 

As with the 2005 v4 platform, the v4.2 platform utilizes the Phase II WRAP oil and gas emissions data for 

the non-California Western Regional Air Partnership (WRAP) states for 2005. WRAP 2018 Phase II 

emissions were also available but determined to be inappropriate for use in 2012 and 2014. Consequently, 

we started with the base year emissions for Oklahoma and the WRAP states and applied these additional 

reductions related to the RICE NESHAP.

For Oklahoma and WRAP oil and gas emissions, we applied CO, NOX, and VOC emissions reductions from 

the Stationary Reciprocating Internal Combustion Engine (RICE) NESHAP, which we assumed has some 

applicability to this industry (see Appendix F in the Proposed Toxics Rule TSD: 

http://www.epa.gov/ttn/chief/emch/toxics/proposed_toxics_rule_appendices.pdf). SO2 reductions associated 

with the RICE NESHAP were also included for these same data for the year 2014 projection. Table 4-10

shows the 2005, 2012, and 2014 NOX and SO2 emissions including RICE reductions for Oklahoma and the 

WRAP states.
86

Table 4-10. Oil and Gas NOX and SO2 Emissions for 2005, 2012, and 2014 including additional reductions 

due to the RICE NESHAP

NOX (tons) SO2 (tons)

State 2005 2012 2014 2005 2012 2014

Alaska 836 811 732 62 62 31

Arizona 13 12 12

Colorado 32,188 31,806 30,625 350 350 176

Montana 10,617 10,456 9,957 640 640 321

Nevada 71 69 62 1 1 0

New Mexico 61,674 60,317 56,119 369 369 188

North Dakota 6,040 5,861 5,306 688 688 355

Oklahoma 39,668 44,362 42,402 1,014 2 2

Oregon 61 60 55

South Dakota 566 550 502 43 43 21

Texas 42,854 46,251 39,462 5,977 43 38

Utah 6,896 6,777 6,409 149 149 75

Wyoming 36,172 35,505 33,442 541 541 272

Grand Total 237,656 242,837 225,085 9,834 2,888 1,479

4.2.8 Future-year VOC Speciation for gasoline-related sources (ptnonipm, nonpt)

To account for the future projected increase in the ethanol content of fuels, we used different future-year 

VOC speciation for certain gasoline-related emission sources. Such sources include gasoline stage II

(refueling vehicles), portable fuel containers (PFCs), and finished fuel storage and transport-related sources 

related to bulk terminals (where the ethanol may be mixed) and downstream to the pump. We identified this 

last group of sources as “btp” (from bulk terminals to pumps). While most of these sources are in the nonpt 

sector, there are also some in the ptnonipm sector. In the 2005 base year, we used zero percent ethanol (E0) 

fuel profiles. For the 2012 and 2014 profiles, we used combinations of E0 and ten percent ethanol (E10) fuel 

profiles. The fuel type fraction was developed based on the Department of Energy Annual Energy Outlook 

(AEO) 2007 projections of ethanol fuels for the year 2022. In the AEO 2007 data, the proportions of E0 and 

E10 fuels are the same for 2012 and years beyond (even though the quantities of the two fuels change over 

these years). The national level proportions were allocated to counties across the country using fuel 

modeling at the EPA Office of Transportation and Air Quality. All gasoline stage II and “btp” sources used 

the same combination of E0 and E10 headspace profiles as were used for exhaust and evaporative profiles. 

4.3 Mobile source projections

Mobile source monthly inventories of onroad and nonroad mobile emissions were created for 2012 and 2014

using a combination of the NMIM and MOVES2010 models. Future-year emissions reflect onroad mobile 

control programs including the Light-Duty Vehicle Tier 2 Rule, the Onroad Heavy-Duty Rule, and the 

Mobile Source Air Toxics (MSAT2) final rule. Nonroad mobile emissions reductions for these years include 

reductions to locomotives, various nonroad engines including diesel engines and various marine engine 

types, fuel sulfur content, and evaporative emissions standards.

Onroad mobile sources are comprised of several components and are discussed in the next subsection (4.3.1). 

Monthly nonroad mobile emission projections are discussed in subsection 4.3.2. Locomotives and Class 1 
87

and Class 2 commercial marine vessel (C1/C2 CMV) projections are discussed in subsection 4.3.3, and Class 

3 (C3) CMV projected emissions are discussed in subsection 4.3.4.

4.3.1 Onroad mobile (on_noadj, on_moves_runpm, on_moves_startpm)

The onroad emissions were primarily based on the 2010 version of the Motor Vehicle Emissions Simulator 

(MOVES2010) – the same version as was used for 2005. The same MOVES-based PM2.5 temperature 

adjustment factors were applied as were used in 2005 for running mode emissions; however, cold start 

emissions used year-specific temperature adjustment factors. The temperature adjustments have the minor 

limitation that they were based on the use of MOVES national default inputs rather than county-specific 

inputs. This was because a county-specific database for input to MOVES was not available at the time this 

approach was needed. However, the PM2.5 temperature adjustments are fairly insensitive to the countyspecific inputs, which is why this is only a minor limitation.

California onroad (on_noadj)

Like year 2005 emissions, future-year California NH3 emissions are from MOVES runs for California, 

disaggregated to the county level using NMIM. For all other pollutants, we did not use MOVES to generate 

future-year onroad emissions for California, because the 2005 base year emissions were provided by

CARB‟s Emission Factors mobile model (EMFAC), outputs of which CARB submitted for the 2005 NEI. 

For California, we chose an approach that would maintain consistency between the 2005 and 2012 and 2014

emissions. This approach involved computing projection factors from a consistent set of future and 2005-

year data provided by CARB based on the EMFAC2007 model. For 2012 emissions, we generated 

projection factors by dividing the EMFAC2007-based emissions for 2012 (linearly interpolated between year 

2009 and year 2014) by the EMFAC2007-based emissions for 2005. These EMFAC-based emissions were 

provided in March 2007. California does not specify road types, so we first used NMIM California ratios to 

break out vehicle emissions to the match the more detailed NMIM level before projecting to 2012.

HAP emissions were computed as 2005v2-based HAP-CAP ratios applied to 2012 and 2014 CAP emissions 

at the pollutant and Level 3 SCC (first 7 characters). HAPs were scaled to either of three pollutants: exhaust 

PM2.5 (e.g., metals), exhaust VOC (e.g., exhaust mode VOC HAPs such as acetaldehyde and formaldehyde), 

or evaporative VOC (e.g., evaporative mode VOC HAPs such as benzene).

Onroad mobile sector with no adjustment for daily temperature (on_noadj)

As discussed in Section 2, the MOVES2010 model was used for all vehicles, road types, and pollutants. 

Vehicle Miles Travelled (VMT) were projected using growth rates from the Department of Energy‟s 

AEO2009. We used MOVES2010 to create emissions by state, SCC, pollutant, emissions mode and month. 

We then allocated these emissions to counties using ratios based on 2012 and 2015 NMIM county-level data 

by state, SCC, pollutant, and emissions mode. 2014 NMIM data were not available for this effort, but the 

2015 NMIM can reasonably be expected to be sufficient for 2014 state-county allocations for this purpose. 

While the EPA intends to replace this approach with a county-specific implementation of MOVES for use in 

future regulatory actions, this approach was the best approach available at the time of this modeling.

Onroad PM gasoline running and cold start mode sectors (on_moves_startpm and on_moves_runpm)

MOVES-based cold start and running mode emissions consist of gasoline exhaust speciated PM and 

naphthalene. These pre-temperature-adjusted emissions at 72°F are projected to years 2012 and 2014 from 

year 2005 inventories using the 2012- and 2014-specific runs of MOVES2010. VMT were projected using 

growth rates from the AEO2009. As with the on_noadj sector, the 2012 and 2014 MOVES2010 data were 
88

created at the state-month level, and the 2012 and 2015 NMIM results were used to disaggregate the state 

level results to the county level.

MOVES-based temperature adjustment factors were applied to gridded, hourly emissions using gridded, 

hourly meteorology. As seen in Figure 4-1, for year 2012, we used the same temperature adjustment factors 

as the 2005 base case for both start and running modes. However, cold start temperature adjustment factors 

decrease slightly in future years, and for year 2014 processing, we updated the temperature adjustment 

curves for these cold start emissions. These have little impact, reducing cold-start mode temperatureadjusted PM and naphthalene by under 4% for temperatures down to 0 F. Note that running exhaust 

temperature adjustment factors are the same for all years. Also, these running mode exhaust mode emissions 

are considerably larger than cold start mode emissions.

Figure 4-1. MOVES exhaust temperature adjustment functions for 2005, 2012, and 2014

4.3.2 Nonroad mobile (nonroad)

This sector includes monthly exhaust, evaporative and refueling emissions from nonroad engines (not 

including commercial marine, aircraft, and locomotives) derived from NMIM for all states except California. 

Like the onroad emissions, NMIM provides nonroad emissions for VOC by three emission modes: exhaust, 

evaporative and refueling. Unlike the onroad sector, nonroad refueling emissions for nonroad sources are 

not included in the nonpoint (nonpt) sector and so are retained in this sector.

With the exception of California, U.S. emissions for the nonroad sector (defined as the equipment types 

covered by NMIM) were created using a consistent NMIM-based approach as was used for 2005, but 

projected for 2012 and 2015. The 2012 and 2015 NMIM runs utilized the NR05d-Bond-final version of 

NONROAD (which is equivalent to NONROAD2008a). Similar to the onroad mobile NMIM inventories, 

year 2014 NMIM emissions were created by interpolating year 2012 and year 2015 NMIM inventories. 

These future-year emissions account for increases in activity (based on NONROAD model default growth 

estimates of future-year equipment population) and changes in fuels and engines that reflect implementation 

of national regulations and local control programs that impact each year differently due to engine turnover.

0

10

20

30

40

50

60

70

80

-20-10

0

10203040506070

Temperature (F)

Adjustment Factor

Run Exhaust:

All Years

Start Exhaust:

2005 & 2012

Start Exhaust:

2014
89

The national regulations incorporated in the modeling are those promulgated prior to December 2009, and 

beginning about 1990. Recent rules include:

“Clean Air Nonroad Diesel Final Rule - Tier 4”: (http://www.epa.gov/nonroaddiesel/2004fr.htm ), 

published June 29, 2004, and,

Control of Emissions from Nonroad Large Spark-Ignition Engines, and Recreational Engines (Marine 

and Land-Based), November 8, 2002 (“Pentathalon Rule”).

OTAQ‟s Locomotive Marine Rule: (http://www.epa.gov/otaq/regs/nonroad/420f08004.htm)

OTAQ‟s Small Engine Spark Ignition (“Bond”) Rule: (http://www.epa.gov/otaq/equip-ld.htm)

We have not included voluntary programs such as programs encouraging either no refueling or evening 

refueling on Ozone Action Days and diesel retrofit programs. NMIM version 20071009, with county 

database NCD20070912, and NONROAD model version NONROAD2008a (see 

http://www.epa.gov/otaq/nonrdmdl.htm#model) was used to create NMIM inventories for 2012 and 2015.

California nonroad emissions

Similar to onroad mobile, NMIM was not used to generate future-year nonroad emissions for California, 

other than for NH3. We used NMIM for California future nonroad NH3 emissions because CARB did not

provide these data for any nonroad vehicle types. As we did for onroad emissions, we chose a projection 

approach that would maintain consistency between the base year and future-year emissions for nonroad 

emissions in California.

California year 2014 nonroad CAP emissions are similar to those used in the 2002v3 projected inventory. 

However, similar to onroad mobile, California nonroad HAPs were computed as ratios to select CAPs using 

2005 NMIM CAP-HAP ratios.

California year 2012 nonroad CAP emissions were computed by linearly interpolating year 2009 and 2014

inventories. And 2012 HAP emissions were also computed using the same 2005-based CAP-HAP ratios 

used to create 2014 HAP emissions.

4.3.3 Locomotives and Class 1 & 2 commercial marine vessels (alm_no_c3)

Future locomotive and Class 1 and Class 2 commercial marine vessel (CMV) emissions were calculated 

using projection factors that were computed based on national, annual summaries of locomotive emissions in 

2002 and future years. These national summaries were used to create national by-pollutant, by-SCC 

projection factors; these factors include final locomotive-marine controls and are provided in Table 4-11.

Table 4-11. Factors applied to year 2005 emissions to project locomotives and Class 1 and Class 2 

Commercial Marine Vessel Emissions

SCC SCC Description Pollutant

Projection Factor

2012 2014

2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions CO 0.972 0.968

2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions NH3 1.094 1.114

2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions NOX 0.851 0.792

2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions PM10 0.875 0.762

2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions PM2.5 0.890 0.775

2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions SO2 0.531 0.278

2280002X00 Marine Vessels, Commercial;Diesel;Underway & port emissions VOC 0.951 0.897

2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations CO 1.232 1.272

2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations NH3 1.223 1.262

2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations NOX 0.732 0.711
90

SCC SCC Description Pollutant

Projection Factor

2012 2014

2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations PM10 0.768 0.696

2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations PM2.5 0.778 0.705

2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations SO2 0.166 0.005

2285002006 Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations VOC 0.839 0.748

2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations CO 0.303 0.313

2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations NH3 1.223 1.262

2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations NOX 0.339 0.350

2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations PM10 0.283 0.286

2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations PM2.5 0.286 0.288

2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations SO2 0.038 0.001

2285002007 Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations VOC 0.291 0.300

2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) CO 1.030 1.046

2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) NH3 1.223 1.262

2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) NOX 0.667 0.598

2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) PM10 0.660 0.576

2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) PM2.5 0.662 0.578

2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) SO2 0.156 0.005

2285002008 Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak) VOC 0.738 0.633

2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines CO 1.015 1.032

2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines NH3 1.223 1.262

2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines NOX 0.658 0.590

2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines PM10 0.650 0.568

2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines PM2.5 0.651 0.568

2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines SO2 0.155 0.005

2285002009 Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines VOC 0.728 0.625

2285002010 Railroad Equipment;Diesel;Yard Locomotives CO 1.239 1.279

2285002010 Railroad Equipment;Diesel;Yard Locomotives NH3 1.223 1.262

2285002010 Railroad Equipment;Diesel;Yard Locomotives NOX 1.133 1.127

2285002010 Railroad Equipment;Diesel;Yard Locomotives PM10 0.942 0.919

2285002010 Railroad Equipment;Diesel;Yard Locomotives PM2.5 0.962 0.938

2285002010 Railroad Equipment;Diesel;Yard Locomotives SO2 0.183 0.005

2285002010 Railroad Equipment;Diesel;Yard Locomotives VOC 1.548 1.526

The future-year locomotive emissions account for increased fuel consumption based on Energy Information 

Administration (EIA) fuel consumption projections for freight rail, and emissions reductions resulting from 

emissions standards from the Final Locomotive-Marine rule (EPA, 2009). This rule lowered diesel sulfur

content and tightened emission standards for existing and new locomotives and marine diesel emissions to 

lower future-year PM, SO2, and NOX, and is documented at: 

http://www.epa.gov/otaq/regs/nonroad/420f08004.htm. Voluntary retrofits under the National Clean Diesel 

Campaign (http://www.epa.gov/otaq/diesel/index.htm) are not included in our projections.

We applied HAP factors for VOC HAPs by using the VOC projection factors to obtain 1,3-butadiene, 

acetaldehyde, acrolein, benzene, and formaldehyde.

Class 1 and 2 CMV gasoline emissions (SCC = 2280004000) were not changed for future-year processing. 

C1/C2 diesel emissions (SCC = 2280002100 and 2280002200) were projected based on the Final 

Locomotive Marine rule national-level factors provided in Table 4-11. Similar to locomotives, VOC HAPs 

were projected based on the VOC factor.
91

Delaware provided updated future-year NOX, SO2, and PM emission estimates for C1/C2 CMV as part of the 

Transport Rule comments. These updated emissions were applied to the 2012 and 2014 inventories and 

override the C1/C2 projection factors in Table 4-11.

4.3.4 Class 3 commercial marine vessels (seca_c3)

The seca_c3 sector emissions data were provided by OTAQ in an ASCII raster format used since the SO2

Emissions Control Area-International Marine Organization (ECA-IMO) project began in 2005. The (S)ECA 

Category 3 (C3) commercial marine vessel 2002 base-case emissions were projected to year 2005 for the 

2005 base case and to years 2012 and 2014 for the future base cases. Both future base cases include ECAIMO controls. An overview of the ECA-IMO project and future-year goals for reduction of NOX, SO2, and 

PM C3 emissions can be found at: http://www.epa.gov/oms/regs/nonroad/marine/ci/420f09015.htm

The resulting coordinated strategy, including emission standards under the Clean Air Act for new marine 

diesel engines with per-cylinder displacement at or above 30 liters, and the establishment of Emission 

Control Areas is at: http://www.epa.gov/oms/oceanvessels.htm

These projection factors vary depending on geographic region and pollutant; where VOC HAPs are assigned 

the same growth rates as VOC. The projection factors used to create the 2012 and 2014 seca_c3 sector 

emissions are provided in Table 4-12. Note that these factors are relative to 2002. Factors relative to 2005 

can be computed from the 2002-2005 factors.

The geographic regions are described in the ECA Proposal technical support document: 

http://www.epa.gov/oms/regs/nonroad/marine/ci/420r09007-chap2.pdf. These regions extend up to 200 

nautical miles offshore, though less at international boundaries. North and South Pacific regions are divided 

by the Oregon-Washington border, and East Coast and Gulf Coast regions are divided east-west by roughly 

the upper Florida Keys just southwest of Miami.

Delaware provided updated future-year NOX, SO2, and PM emission estimates for the C3 CMV as part of the 

Transport Rule comments. These updated emissions were applied to the 2012 and 2014 inventories and 

override the C3 projection factors in Table 4-12.

The factors to compute HAP emission are based on emissions ratios discussed in the 2005v4 documentation. 

As with the 2005 base case, this sector uses CAP-HAP VOC integration.

Table 4-12. NOX, SO2, and PM2.5 Factors to Project Class 3 Commercial Marine Vessel emissions to 2012 

and 2014

NOX SO2 PM2.5

2012 2014 2012 2014 2012 2014

Alaska East 1.26234 1.32620 0.52912 0.56462 0.52433 0.55951

Alaska West 

(AW)

1.28461 1.35119 1.33532 1.42491 1.33555 1.42515

East Coast 1.33102 1.39686 0.55987 0.61140 0.51862 0.56635

Gulf Coast 1.12285 1.14364 0.47456 0.50248 0.43526 0.46087

Hawaii East 

(HE)

1.37239 1.45513 0.61127 0.67392 0.54920 0.60550

Hawaii West 

(HW)

1.45767 1.54847 1.59605 1.75964 1.59408 1.75748

North Pacific 

(NP)

1.19916 1.23653 0.54159 0.57792 0.47330 0.50506

South Pacific 

(SP)

1.40836 1.49931 0.64318 0.71344 0.54825 0.60797

Great Lakes 

(GL)

1.08304 1.10302 0.42239 0.43687 0.39684 0.41045

Outside ECA 1.37211 1.44085 1.52102 1.65818 1.52102 1.65818
92

4.3.5 Future-year VOC Speciation (on_noadj, nonroad)

We used speciation profiles for VOC in the nonroad and on_noadj sectors that account for the increase in 

ethanol content of fuels in future years. The same future-year profiles were used for 2012 and 2014. The 

combination profiles use proportions of E0 and E10 expected in the future based on AEO 2007 projections of 

E10 and E0 fuel use. The proportions of E0 and E10 are the same for 2012 and years beyond (even though 

the quantities of the two fuels change over these years). The national proportions were allocated to counties 

across the country using the same fuel modeling done for the stationary source gasoline speciation, as 

discussed in Section 4.2.8. 

The speciation of onroad exhaust VOC additionally accounts for a portion of the vehicle fleet meeting Tier 2 

standards; different exhaust profiles are available for pre-Tier 2 versus Tier 2 vehicles. Thus for exhaust 

VOC, a combination of pre-Tier 2 E0, pre-Tier 2 E10, Tier 2 E0 and Tier 2 E10 profiles are used. Figure 4-2

shows the Tier 2 fraction of Light Duty Vehicles for different future years in terms of different metrics. For 

previous modeling applications, we based the fraction on the population of vehicles. However, since these 

vehicles emit a smaller portion of VOC, a more appropriate metric for use in weighting the speciation 

profiles is the fraction of exhaust total hydrocarbons (THC) which is used in the 2012 case described here. 

The fraction of Tier 2 emissions used here for 2012 is 0.182. We erroneously used this same fraction for 

2014; the correct fraction of Tier 2 emissions for 2014 should have been 0.261.

Table 4-13 summarizes the profiles combined for the source categories and VOC emission modes used.

Table 4-13. Future-year Profiles for Mobile Source Related Sources

Sector Type of profile Profile Codes Combined for the Future-year Speciation

Stationary headspace 8762: Composite Profile - Gasoline Headspace Vapor using 0% Ethanol 

8763: Composite Profile - Gasoline Headspace Vapor using 10% Ethanol

Nonroad 

exhaust

Pre-Tier 2 vehicle 

exhaust

8750: Gasoline Exhaust - Reformulated gasoline

8751: Gasoline Exhaust - E10 ethanol gasoline

Onroad and 

Nonroad 

evap*

Evaporative 8753: Gasoline Vehicle - Evaporative emission - Reformulated gasoline 

8754: Gasoline Vehicle - Evaporative emission - E10 ethanol gasoline

Nonroad 

refueling

headspace Same as Stationary

Onroad 

exhaust

Pre-Tier 2 vehicle 

exhaust and Tier 2 

vehicle exhaust

8750: Gasoline Exhaust - Reformulated gasoline

8751: Gasoline Exhaust - E10 ethanol gasoline 

8756: Composite Profile - Gasoline Exhaust - Tier 2 light-duty vehicles using 

0% Ethanol

8757: Composite Profile - Gasoline Exhaust - Tier 2 light-duty vehicles using 

10% Ethanol

E0 and E10 combinations are based on AEO2007 projections of E0 and E10 fuel

Tier 2 and pre-Tier 2 combinations are based on the 2012 contribution of Tier 2 exhaust emissions
93

Figure 4-2. Tier 2 Fraction of Light Duty Vehicles

4.4 Canada, Mexico, and Offshore sources (othar, othon, and othpt)

Emissions for Canada, Mexico, and offshore sources were not projected to future years, and are therefore the 

same as those used in the 2005 base case. Therefore, the Mexico emissions are based on year 1999, offshore 

oil is based on year 2005, and Canada is based on year 2006. For both Mexico and Canada, their responsible 

agencies did not provide future-year emissions that were consistent with the base year emissions.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Fraction of Light Duty Vehicles

Calendar Year

Exhaust THC

Vehicle Miles Traveled

Population
94

5 Source Apportionment

The EPA prepared special emissions inputs for the CAMX model to allow CAMX to be used for source 

apportionment modeling. Source apportionment modeling was used to quantify the impact of emissions in 

specific upwind states on projected downwind nonattainment and maintenance receptors for both PM2.5 and 

8-hour ozone. To prepare these emissions, the EPA prepared special tagging input files called GSTAG files 

for the SMOKE speciation processor.

The tagging input files and custom SMOKE scripts implemented tagging by state of all source emissions 

except for biogenic and wildfire emissions for all ozone and PM2.5 precursors. Separate tagging runs were 

done for ozone and PM2.5 precursors. Biogenic and wildfire emissions were not tagged by state because they 

are generally considered not feasible for emissions controls, but these were tagged as “other sources” and 

their contributions could be tracked in total without association with individual states. Prescribed burning 

and agricultural burning were included in the tagged emissions. The states the EPA analyzed using source 

apportionment for ozone and for PM2.5 are: Alabama, Arkansas, Connecticut, Delaware, Florida, Georgia, 

Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan, 

Minnesota, Mississippi, Missouri, Nebraska, New Hampshire, New Jersey, New York, North Carolina, 

North Dakota, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee, 

Texas, Vermont, Virginia, West Virginia, Washington D.C., and Wisconsin. There were also several other 

states that are only partially contained within the 12 km modeling domain (i.e., Colorado, Montana, New 

Mexico, and Wyoming). However, the EPA did not individually track the emissions or assess the 

contribution from emissions in these states

6 Remedy Case

The 2014 Remedy Case for the Transport Rule represents the implementation of SO2, annual NOX, and 

ozone-season NOX emission reductions to address upwind state emissions that contribute significantly to 

nonattainment in, or interfere with maintenance by downwind states with respect to the existing ozone and 

PM2.5 NAAQS standards in the eastern U.S. The final Transport Rule requires SO2 and/or NOX reductions 

from EGUs in 27 states starting in 2012. For the remedy case modeling, the emissions for all sectors were 

unchanged from the base-case modeling except for those from EGUs (the ptipm sector). The EPA used the 

IPM model to project the 2014 remedy case EGU emissions. The changes in EGU SO2 and NOX emissions 

as a result of the control case for the lower 48 states are summarized in Section 7. Section 7 also provides 

state-specific summaries of EGU NOX and SO2 for the lower 48 states. Additional details on the changes 

that resulted from the remedy case are provided in the Transport Rule Final Regulatory Impact Analysis 

(RIA), Chapter 7 (Cost, Economic, and Energy Impacts), which describes the modeling conducted to 

estimate the cost, economic, and energy impacts to the power sector.

The 23 states covered by the annual SO2 and NOX reduction requirements for the annual and/or 24-hour 

PM2.5 standards in the remedy case are colored in blue and green in Figure 6-1. Figure 6-2 distinguishes 

between the “Group 1” states (in red) and the “Group 2” states (in orange); the Group 1 states are subject to a 

second, more stringent phase of SO2 reductions starting in 2014 (sections VI and VII of the preamble to the 

final Transport Rule discuss the SO2 groups in detail). All states covered for the annual and/or 24-hour 

PM2.5 standards are in one annual NOX tier with uniform stringency beginning in 2012. Table 6-1 shows the 

groups in which each state is included, including whether the state is included in the Eastern modeling 

domain. Section 7 provides annual SO2 and NOX summaries for these selected groups/tiers of states.
95

The 20 states required to make ozone-season NOX reductions to address the 8-hour ozone standard in the 

final Transport Rule are shown in green and yellow in Figure 6-1. In these states ozone-season NOX

reductions begin with the 2012 ozone season. As discussed in section III of the preamble, the EPA issued a 

supplemental proposal to provide the opportunity for public comment on inclusion of six additional states in 

the Transport Rule ozone-season program: Iowa, Kansas, Michigan, Missouri, Oklahoma, and Wisconsin. 

These six states are also shown in green or yellow in Figure 6-1. Section 7 provides ozone-season NOX

emissions summaries for the states required in the final Transport Rule to make ozone-season NOX

reductions and the six additional states addressed in the supplemental proposal. Figure 6-1 shows for each of 

the contiguous 48 states the components of the rule they fall under, and whether they are included in the 

Eastern modeling domain. Tribal land emissions are not associated with particular states; those few tribal 

emissions in the eastern domain are very small and are not associated with existing units covered by the 

Transport Rule.

The emissions, cost, air quality, and benefits analyses done for the Transport Rule are from a modeling 

scenario that requires annual SO2 and NOx reductions in the 23 states covered for the PM2.5 standards, and 

ozone season NOX requirements in the 20 states covered for the ozone standard and the six states addressed 

by the supplemental proposal (26 states total) as shown in Figure 6-1. 

Figure 6-1. States Covered by the Final Transport Rule

(Figure 6-1 includes six states--IA, KS, MI, MO, OK, and WI--not covered for ozone-season requirements in the final rule, for 

which the EPA issued a supplemental proposal to require ozone-season reductions.)
96

Figure 6-2. Group 1 and Group 2 States Covered by the Annual PM Component of the 

Final Transport Rule

Table 6-1. Transport Rule Status of States 

State State

EPA 

Region

Covered for 

PM2.5 –

Group 1 

SO2

Covered for 

PM2.5 –

Group 2 

SO2

Covered 

for Ozone

in 

Transport 

Rule

Covered for 

Ozone in 

Supplemental 

Proposal

Total 

State 

Coverage

In 

Eastern 

Domain

Western 

State

ALABAMA AL 4 0 1 1 0 1 1 0

ARIZONA AZ 9 0 0 0 0 0 0 1

ARKANSAS AR 6 0 0 1 0 1 1 0

CALIFORNIA CA 9 0 0 0 0 0 0 1

COLORADO CO 8 0 0 0 0 0 0 1

CONNECTICUT CT 1 0 0 0 0 0 1 0

DELAWARE DE 3 0 0 0 0 0 1 0

DISTRICT OF 

COLUMBIA DC 3 0 0 0 0 0 1 0

FLORIDA FL 4 0 0 1 0 1 1 0

GEORGIA GA 4 0 1 1 0 1 1 0

IDAHO ID 10 0 0 0 0 0 0 1
97

State State

EPA 

Region

Covered for 

PM2.5 –

Group 1 

SO2

Covered for 

PM2.5 –

Group 2 

SO2

Covered 

for Ozone

in 

Transport 

Rule

Covered for 

Ozone in 

Supplemental 

Proposal

Total 

State 

Coverage

In 

Eastern 

Domain

Western 

State

ILLINOIS IL 5 1 0 1 0 1 1 0

INDIANA IN 5 1 0 1 0 1 1 0

IOWA IA 7 1 0 0 1 1 1 0

KANSAS KS 7 0 1 0 1 1 1 0

KENTUCKY KY 4 1 0 1 0 1 1 0

LOUISIANA LA 6 0 0 1 0 1 1 0

MAINE ME 1 0 0 0 0 0 1 0

MARYLAND MD 3 1 0 1 0 1 1 0

MASSACHUSETTS MA 1 0 0 0 0 0 1 0

MICHIGAN MI 5 1 0 0 1 1 1 0

MINNESOTA MN 5 0 1 0 0 1 1 0

MISSISSIPPI MS 4 0 0 1 0 1 1 0

MISSOURI MO 7 1 0 0 1 1 1 0

MONTANA MT 8 0 0 0 0 0 0 1

NEBRASKA NE 7 0 1 0 0 1 1 0

NEVADA NV 9 0 0 0 0 0 0 1

NEW HAMPSHIRE NH 1 0 0 0 0 0 1 0

NEW JERSEY NJ 2 1 0 1 0 1 1 0

NEW MEXICO NM 6 0 0 0 0 0 0 1

NEW YORK NY 2 1 0 1 0 1 1 0

NORTH CAROLINA NC 4 1 0 1 0 1 1 0

NORTH DAKOTA ND 8 0 0 0 0 0 1 0

OHIO OH 5 1 0 1 0 1 1 0

OKLAHOMA OK 6 0 0 0 1 1 1 0

OREGON OR 10 0 0 0 0 0 0 1

PENNSYLVANIA PA 3 1 0 1 0 1 1 0

RHODE ISLAND RI 1 0 0 0 0 0 1 0

SOUTH CAROLINA SC 4 0 1 1 0 1 1 0

SOUTH DAKOTA SD 8 0 0 0 0 0 1 0

TENNESSEE TN 4 1 0 1 0 1 1 0

TEXAS TX 6 0 1 1 0 1 1 0

TRIBAL 0 0 0 0 0 1 0

UTAH UT 8 0 0 0 0 0 0 1

VERMONT VT 1 0 0 0 0 0 1 0

VIRGINIA VA 3 1 0 1 0 1 1 0

WASHINGTON WA 10 0 0 0 0 0 0 1

WEST VIRGINIA WV 3 1 0 1 0 1 1 0

WISCONSIN WI 5 1 0 0 1 1 1 0

WYOMING WY 8 0 0 0 0 0 0 1
98

State State

EPA 

Region

Covered for 

PM2.5 –

Group 1 

SO2

Covered for 

PM2.5 –

Group 2 

SO2

Covered 

for Ozone

in 

Transport 

Rule

Covered for 

Ozone in 

Supplemental 

Proposal

Total 

State 

Coverage

In 

Eastern 

Domain

Western 

State

TOTAL COUNT 16 7 26 6 28 39 11

7 Emission Summaries

The following tables summarize emissions differences between the 2005 base case, 2012 base case, 2014 

base case, and 2014 EGU control case at various levels of geographic, temporal, and emission sector 

resolution.

Table 7-1 and 

Table 7-2 provide NOX and SO2 emissions, respectively (including average fire emissions and excluding 

biogenic emissions) by state for the 2005 base case, 2012 base case, 2014 base case, and 2014 EGU control 

cases, as well as differences and percent differences between these cases. Note that the average fire

emissions are the same for all emissions cases. Table 7-3 and Table 7-4 provide EGU sector (ptipm) NOX

and SO2 emissions (respectively) by state for the 2005 base case, 2012 base case, 2014 base case, and 2014 

EGU control cases, as well as differences and percent differences between these cases. 

Table 7-5 and Table 7-6 provide NOX and SO2 emissions, respectively (including average fire emissions and 

excluding biogenic emissions) for the “group 1” states, “group 2” states, and cumulative totals for all states 

included in the Transport Rule for PM. See Figure 6-2 for a map of the group 1 and group 2 states. 

Emissions are provided for the 2005 base case, 2012 base case, 2014 base case, and 2014 EGU remedy 

cases, as well as differences and percent differences between these cases. We also provide summaries for all 

“Eastern Modeling Domain” states and “All Western States”. The western states are defined as Arizona, 

California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. 

States in the eastern modeling domain are defined as the rest of the contiguous (lower 48 states) U.S. plus the 

District of Columbia.

Table 7-7 and Table 7-8 provide EGU sector only (ptipm) NOX and SO2 emissions (respectively) for the 

“group 1” states, “group 2” states, and cumulative totals for all states included in the Transport Rule for PM. 

See Figure 6-2 for a map of the group 1 and group 2 states. Emissions are provided for the 2005 base case, 

2012 base case, 2014 base case, and 2014 EGU remedy case, as well as differences and percent differences 

between these cases. Summaries for the eastern modeling domain states and western states are also 

provided. 

Table 7-9 provides summer (defined as May through September) EGU and Total Anthropogenic NOX for the 

states that the Transport Rule covers for ozone. See Figure 6-2 for a map of these states. Emissions are 

provided for the 2005 base case, 2012 base case, 2014 base case, and 2014 EGU control (“remedy”) cases, as 

well as differences and percent differences between these cases.

Additional information and pollutants are provided in the accompanying workbook: 

TransportRuleFinal_EmissionsSummaries.xls.
99

Table 7-1. State-level Total NOX Emissions for each Transport Rule Modeling Case in 48 States and Washington, D.C.

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 

Base

2014 Base minus 2012 

Base

2014 Remedy minus 

2014 Base

Difference % Diff. Difference % Diff Difference % Diff.

Alabama 484,282 343,206 321,975 315,155 -141,076 -29.1% -21,231 -6.2% -6,820 -2.1%

Arizona 400,774 274,608 248,574 248,570 -126,166 -31.5% -26,034 -9.5% -4 0.0%

Arkansas 264,979 205,673 193,670 194,964 -59,306 -22.4% -12,002 -5.8% 1,293 0.7%

California 1,333,571 1,030,864 942,254 942,157 -302,706 -22.7% -88,610 -8.6% -97 0.0%

Colorado 334,635 253,291 237,296 237,246 -81,344 -24.3% -15,995 -6.3% -50 0.0%

Connecticut 129,736 88,660 80,787 80,793 -41,076 -31.7% -7,873 -8.9% 6 0.0%

Delaware 58,486 35,549 31,729 31,744 -22,936 -39.2% -3,820 -10.7% 15 0.0%

District of 

Columbia 16,802 11,040 9,773 9,773 -5,762 -34.3% -1,267 -11.5% 0 0.0%

Florida 1,056,174 683,733 638,227 616,154 -372,441 -35.3% -45,506 -6.7% -22,073 -3.5%

Georgia 662,673 456,393 403,691 395,764 -206,280 -31.1% -52,702 -11.5% -7,927 -2.0%

Idaho 122,228 105,888 101,710 101,710 -16,340 -13.4% -4,178 -3.9% 0 0.0%

Illinois 865,139 583,602 546,467 540,361 -281,537 -32.5% -37,135 -6.4% -6,107 -1.1%

Indiana 673,669 455,325 431,342 424,250 -218,344 -32.4% -23,983 -5.3% -7,092 -1.6%

Iowa 331,034 238,425 223,390 217,221 -92,608 -28.0% -15,036 -6.3% -6,169 -2.8%

Kansas 387,554 271,578 248,692 240,384 -115,976 -29.9% -22,886 -8.4% -8,308 -3.3%

Kentucky 482,262 318,048 294,262 286,806 -164,214 -34.1% -23,786 -7.5% -7,456 -2.5%

Louisiana 626,542 494,774 466,089 466,098 -131,768 -21.0% -28,686 -5.8% 9 0.0%

Maine 86,094 66,633 61,657 61,657 -19,461 -22.6% -4,975 -7.5% 0 0.0%

Maryland 312,230 197,441 181,909 181,533 -114,789 -36.8% -15,533 -7.9% -375 -0.2%

Massachusetts 283,638 189,620 175,275 175,316 -94,018 -33.1% -14,345 -7.6% 41 0.0%

Michigan 718,454 481,684 449,343 442,544 -236,770 -33.0% -32,341 -6.7% -6,798 -1.5%

Minnesota 506,905 364,052 345,483 338,438 -142,853 -28.2% -18,568 -5.1% -7,045 -2.0%

Mississippi 324,595 232,009 216,438 216,224 -92,587 -28.5% -15,571 -6.7% -214 -0.1%

Missouri 563,356 374,298 357,846 352,631 -189,059 -33.6% -16,451 -4.4% -5,216 -1.5%

Montana 149,429 97,575 92,723 92,627 -51,854 -34.7% -4,852 -5.0% -96 -0.1%

Nebraska 263,714 197,887 186,408 169,571 -65,827 -25.0% -11,479 -5.8% -16,836 -9.0%

Nevada 151,905 86,487 81,041 81,017 -65,418 -43.1% -5,446 -6.3% -24 0.0%

New Hampshire 73,325 50,415 47,637 47,482 -22,910 -31.2% -2,778 -5.5% -156 -0.3%
100

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 

Base

2014 Base minus 2012 

Base

2014 Remedy minus 

2014 Base

New Jersey 341,376 230,816 210,127 209,841 -110,559 -32.4% -20,690 -9.0% -286 -0.1%

New Mexico 343,139 281,341 264,414 264,502 -61,798 -18.0% -16,926 -6.0% 88 0.0%

New York 688,109 491,308 459,087 457,927 -196,800 -28.6% -32,221 -6.6% -1,160 -0.3%

North Carolina 554,183 352,649 321,544 317,230 -201,534 -36.4% -31,106 -8.8% -4,314 -1.3%

North Dakota 182,289 133,332 127,125 127,127 -48,956 -26.9% -6,207 -4.7% 2 0.0%

Ohio 906,327 560,718 522,450 508,054 -345,609 -38.1% -38,268 -6.8% -14,396 -2.8%

Oklahoma 434,284 344,447 328,683 305,859 -89,837 -20.7% -15,764 -4.6% -22,823 -6.9%

Oregon 240,218 189,886 179,324 179,371 -50,332 -21.0% -10,563 -5.6% 48 0.0%

Pennsylvania 781,647 565,051 529,673 514,563 -216,596 -27.7% -35,378 -6.3% -15,110 -2.9%

Rhode Island 28,381 20,756 18,808 18,808 -7,625 -26.9% -1,948 -9.4% 0 0.0%

South Carolina 314,276 216,883 204,389 202,118 -97,393 -31.0% -12,494 -5.8% -2,271 -1.1%

South Dakota 91,336 70,618 65,498 65,500 -20,717 -22.7% -5,121 -7.3% 3 0.0%

Tennessee 527,027 338,047 302,103 293,339 -188,980 -35.9% -35,944 -10.6% -8,764 -2.9%

Texas 2,006,916 1,501,170 1,372,735 1,368,612 -505,746 -25.2% -128,435 -8.6% -4,123 -0.3%

Tribal 13,400 13,304 13,137 13,137 -96 -0.7% -167 -1.3% 0 0.0%

Utah 216,810 179,535 170,840 170,840 -37,275 -17.2% -8,696 -4.8% 0 0.0%

Vermont 25,696 23,142 22,824 22,824 -2,554 -9.9% -318 -1.4% 0 0.0%

Virginia 488,263 359,907 334,720 333,985 -128,355 -26.3% -25,187 -7.0% -735 -0.2%

Washington 357,674 268,870 249,322 249,322 -88,804 -24.8% -19,548 -7.3% 0 0.0%

West Virginia 308,655 172,143 166,094 155,245 -136,512 -44.2% -6,049 -3.5% -10,849 -6.5%

Wisconsin 401,226 279,465 262,201 254,989 -121,760 -30.3% -17,264 -6.2% -7,212 -2.8%

Wyoming 236,894 191,051 183,726 184,297 -45,843 -19.4% -7,325 -3.8% 571 0.3%

Grand Total 21,152,309 14,973,199 13,924,510 13,725,678 -6,179,110 -29.2% -1,048,689 -7.0% -198,832 -1.4%

Table 7-2. State-level Total SO2 Emissions for each Transport Rule Modeling Case in 48 States and Washington, D.C.

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 

Base

2014 Base minus 2012 

Base

2014 Remedy minus 2014 

Base

Difference % Diff. Difference % Diff. Difference % Diff.

Alabama 589,408 574,045 534,700 290,925 -15,363 -2.6% -39,345 -6.9% -243,775 -45.6%

Arizona 92,231 65,046 65,792 65,792 -27,185 -29.5% 746 1.1% 0 0.0%
101

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 

Base

2014 Base minus 2012 

Base

2014 Remedy minus 2014 

Base

Arkansas 115,087 129,337 139,599 146,873 14,250 12.4% 10,262 7.9% 7,274 5.2%

California 164,217 136,846 119,268 119,268 -27,371 -16.7% -17,579 -12.8% 0 0.0%

Colorado 82,213 63,748 72,227 83,980 -18,465 -22.5% 8,479 13.3% 11,753 16.3%

Connecticut 34,576 24,455 24,618 24,727 -10,121 -29.3% 163 0.7% 109 0.4%

Delaware 71,449 10,703 9,311 9,311 -60,746 -85.0% -1,392 -13.0% 0 0.0%

District of 

Columbia 3,961 2,289 2,230 2,230 -1,672 -42.2% -59 -2.6% 0 0.0%

Florida 596,729 247,550 280,233 284,700 -349,179 -58.5% 32,683 13.2% 4,468 1.6%

Georgia 744,119 511,422 274,332 197,251 -232,697 -31.3% -237,090 -46.4% -77,080 -28.1%

Idaho 27,166 24,326 24,248 24,248 -2,840 -10.5% -79 -0.3% 0 0.0%

Illinois 518,531 608,867 260,031 251,073 90,336 17.4% -348,835 -57.3% -8,959 -3.4%

Indiana 1,040,947 929,162 863,923 331,182 -111,785 -10.7% -65,239 -7.0% -532,740 -61.7%

Iowa 225,451 206,314 198,747 149,491 -19,136 -8.5% -7,567 -3.7% -49,256 -24.8%

Kansas 196,515 116,861 117,050 92,971 -79,654 -40.5% 189 0.2% -24,078 -20.6%

Kentucky 573,604 580,849 547,085 176,007 7,244 1.3% -33,764 -5.8% -371,078 -67.8%

Louisiana 307,340 249,655 261,579 282,552 -57,685 -18.8% 11,924 4.8% 20,973 8.0%

Maine 35,129 27,598 20,642 20,642 -7,531 -21.4% -6,956 -25.2% 0 0.0%

Maryland 371,166 128,360 120,089 107,531 -242,806 -65.4% -8,271 -6.4% -12,558 -10.5%

Massachusetts 138,551 53,866 57,914 57,913 -84,686 -61.1% 4,049 7.5% -1 0.0%

Michigan 492,106 362,718 364,035 257,233 -129,388 -26.3% 1,317 0.4% -106,802 -29.3%

Minnesota 155,736 109,940 112,099 90,784 -45,796 -29.4% 2,158 2.0% -21,315 -19.0%

Mississippi 121,397 63,330 64,156 65,293 -58,066 -47.8% 825 1.3% 1,137 1.8%

Missouri 423,253 483,607 511,664 308,275 60,354 14.3% 28,057 5.8% -203,388 -39.8%

Montana 39,518 25,621 26,678 34,058 -13,897 -35.2% 1,057 4.1% 7,379 27.7%

Nebraska 100,026 87,120 85,799 84,065 -12,906 -12.9% -1,321 -1.5% -1,734 -2.0%

Nevada 73,018 29,694 30,112 30,112 -43,325 -59.3% 418 1.4% 0 0.0%

New Hampshire 63,614 13,401 16,391 16,680 -50,213 -78.9% 2,990 22.3% 289 1.8%

New Jersey 91,898 49,252 61,455 28,841 -42,646 -46.4% 12,203 24.8% -32,614 -53.1%

New Mexico 50,755 25,254 26,507 28,575 -25,501 -50.2% 1,253 5.0% 2,068 7.8%

New York 386,707 232,727 163,302 135,575 -153,980 -39.8% -69,425 -29.8% -27,727 -17.0%

North Carolina 609,652 231,489 208,652 151,982 -378,163 -62.0% -22,837 -9.9% -56,670 -27.2%

North Dakota 160,082 118,490 119,385 119,375 -41,592 -26.0% 895 0.8% -9 0.0%
102

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 

Base

2014 Base minus 2012 

Base

2014 Remedy minus 2014 

Base

Ohio 1,274,427 999,536 966,938 294,714 -274,890 -21.6% -32,598 -3.3% -672,224 -69.5%

Oklahoma 167,918 178,504 175,459 175,550 10,586 6.3% -3,045 -1.7% 91 0.1%

Oregon 44,438 36,494 37,175 37,175 -7,945 -17.9% 681 1.9% 0 0.0%

Pennsylvania 1,172,555 638,071 645,278 261,173 -534,483 -45.6% 7,207 1.1% -384,105 -59.5%

Rhode Island 7,366 6,391 6,385 6,385 -975 -13.2% -6 -0.1% 0 0.0%

South Carolina 275,871 231,565 258,231 145,737 -44,306 -16.1% 26,666 11.5% -112,494 -43.6%

South Dakota 29,083 42,688 42,453 42,453 13,605 46.8% -235 -0.6% 0 0.0%

Tennessee 378,676 419,588 378,878 159,131 40,912 10.8% -40,710 -9.7% -219,747 -58.0%

Texas 927,857 712,582 704,311 517,627 -215,275 -23.2% -8,271 -1.2% -186,685 -26.5%

Tribal 1,515 1,510 677 677 -4 -0.3% -833 -55.2% 0 0.0%

Utah 53,893 46,929 45,947 46,417 -6,965 -12.9% -981 -2.1% 469 1.0%

Vermont 7,078 6,631 6,614 6,614 -446 -6.3% -18 -0.3% 0 0.0%

Virginia 337,752 181,472 162,611 136,499 -156,280 -46.3% -18,861 -10.4% -26,112 -16.1%

Washington 57,580 38,581 38,062 38,062 -18,999 -33.0% -519 -1.3% 0 0.0%

West Virginia 534,392 585,385 546,702 132,539 50,993 9.5% -38,683 -6.6% -414,163 -75.8%

Wisconsin 264,315 204,473 198,795 118,394 -59,842 -22.6% -5,678 -2.8% -80,401 -40.4%

Wyoming 123,503 74,547 80,419 87,133 -48,956 -39.6% 5,872 7.9% 6,714 8.3%

Grand Total 14,354,370 10,928,889 10,078,786 6,275,795 -3,425,481 -23.9% -850,103 -7.8% -3,802,991 -37.7%

Table 7-3. State-level Electric Generating Unit Sector NOX Emissions for each Transport Rule Modeling Case in 48 States and Washington, 

D.C.

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 

Base

2014 Base minus 2012 

Base

2014 Remedy minus 2014 

Base

Difference % Diff. Difference % Diff. Difference % Diff.

Alabama 133,051 83,037 76,012 69,192 -50,014 -37.6% -7,025 -8.5% -6,820 -9.0%

Arizona 79,776 40,365 35,616 35,613 -39,412 -49.4% -4,748 -11.8% -4 0.0%

Arkansas 35,407 33,540 36,347 37,640 -1,867 -5.3% 2,807 8.4% 1,293 3.6%

California 6,925 25,101 26,874 26,776 18,176 262.5% 1,773 7.1% -97 -0.4%

Colorado 73,909 48,464 49,381 49,331 -25,445 -34.4% 917 1.9% -50 -0.1%

Connecticut 6,865 2,603 2,854 2,860 -4,262 -62.1% 251 9.7% 6 0.2%
103

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 

Base

2014 Base minus 2012 

Base

2014 Remedy minus 2014 

Base

Delaware 11,917 2,639 1,701 1,717 -9,278 -77.9% -937 -35.5% 15 0.9%

District of 

Columbia 492 0 0 0 -492 -100.0% 0 0

Florida 217,282 91,072 100,581 78,508 -126,210 -58.1% 9,509 10.4% -22,073 -21.9%

Georgia 111,281 67,682 49,411 41,484 -43,599 -39.2% -18,271 -27.0% -7,927 -16.0%

Idaho 19 608 608 608 589 3062.5% 0 0.0% 0 0.0%

Illinois 127,940 52,481 55,269 49,162 -75,459 -59.0% 2,788 5.3% -6,107 -11.0%

Indiana 213,588 120,593 117,832 110,740 -92,995 -43.5% -2,761 -2.3% -7,092 -6.0%

Iowa 72,806 46,105 48,400 42,231 -26,701 -36.7% 2,295 5.0% -6,169 -12.7%

Kansas 90,220 37,240 32,637 24,328 -52,981 -58.7% -4,603 -12.4% -8,308 -25.5%

Kentucky 164,783 88,195 83,544 76,088 -76,588 -46.5% -4,651 -5.3% -7,456 -8.9%

Louisiana 64,987 30,453 31,573 31,582 -34,534 -53.1% 1,120 3.7% 9 0.0%

Maine 1,100 4,864 5,402 5,402 3,764 342.2% 538 11.1% 0 0.0%

Maryland 62,574 16,706 17,566 17,190 -45,868 -73.3% 860 5.1% -375 -2.1%

Massachusetts 25,134 4,954 6,992 7,033 -20,181 -80.3% 2,038 41.1% 41 0.6%

Michigan 120,026 63,266 67,705 60,907 -56,761 -47.3% 4,440 7.0% -6,798 -10.0%

Minnesota 84,304 39,400 41,474 34,429 -44,904 -53.3% 2,074 5.3% -7,045 -17.0%

Mississippi 45,166 23,655 26,294 26,080 -21,510 -47.6% 2,639 11.2% -214 -0.8%

Missouri 127,431 55,633 57,318 52,103 -71,798 -56.3% 1,685 3.0% -5,216 -9.1%

Montana 39,858 18,302 19,399 19,303 -21,555 -54.1% 1,096 6.0% -96 -0.5%

Nebraska 52,426 44,496 45,047 28,211 -7,930 -15.1% 551 1.2% -16,836 -37.4%

Nevada 47,297 13,294 14,074 14,050 -34,003 -71.9% 780 5.9% -24 -0.2%

New Hampshire 8,827 4,068 5,126 4,971 -4,759 -53.9% 1,059 26.0% -156 -3.0%

New Jersey 30,142 7,534 8,006 7,720 -22,608 -75.0% 472 6.3% -286 -3.6%

New Mexico 75,483 64,264 64,745 64,833 -11,220 -14.9% 481 0.7% 88 0.1%

New York 63,315 20,909 21,689 20,528 -42,406 -67.0% 779 3.7% -1,160 -5.4%

North Carolina 111,576 54,463 49,322 45,008 -57,113 -51.2% -5,141 -9.4% -4,314 -8.7%

North Dakota 76,381 52,968 53,265 53,267 -23,414 -30.7% 297 0.6% 2 0.0%

Ohio 258,944 103,192 104,149 89,753 -155,751 -60.1% 957 0.9% -14,396 -13.8%

Oklahoma 86,204 66,365 66,966 44,143 -19,839 -23.0% 601 0.9% -22,823 -34.1%

Oregon 9,383 8,875 9,584 9,632 -508 -5.4% 709 8.0% 48 0.5%

Pennsylvania 176,891 130,738 134,092 118,981 -46,153 -26.1% 3,354 2.6% -15,110 -11.3%
104

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 

Base

2014 Base minus 2012 

Base

2014 Remedy minus 2014 

Base

Rhode Island 545 449 442 442 -96 -17.6% -7 -1.6% 0 0.0%

South Carolina 52,657 35,395 39,018 36,747 -17,262 -32.8% 3,623 10.2% -2,271 -5.8%

South Dakota 15,650 14,269 14,270 14,273 -1,381 -8.8% 1 0.0% 3 0.0%

Tennessee 102,934 37,694 29,276 20,512 -65,240 -63.4% -8,418 -22.3% -8,764 -29.9%

Texas 176,170 137,128 142,087 137,964 -39,043 -22.2% 4,960 3.6% -4,123 -2.9%

Tribal 78 32 11 11 -46 -58.6% -21 -64.9% 0 0.0%

Utah 65,261 67,429 67,434 67,434 2,168 3.3% 5 0.0% 0 0.0%

Vermont 297 379 455 455 82 27.6% 76 20.2% 0 0.0%

Virginia 62,793 38,820 40,469 39,734 -23,973 -38.2% 1,649 4.2% -735 -1.8%

Washington 17,634 12,565 13,322 13,322 -5,069 -28.7% 757 6.0% 0 0.0%

West Virginia 159,947 62,434 64,824 53,975 -97,513 -61.0% 2,390 3.8% -10,849 -16.7%

Wisconsin 72,170 40,062 40,750 33,537 -32,108 -44.5% 687 1.7% -7,212 -17.7%

Wyoming 89,315 69,911 70,207 70,778 -19,404 -21.7% 296 0.4% 571 0.8%

Grand Total 3,729,161 2,084,689 2,089,422 1,890,590 -1,644,472 -44.1% 4,733 0.2% -198,832 -9.5%

Table 7-4. State-level Electric Generating Unit Sector SO2 Emissions for each Transport Rule Modeling Case in 48 States and Washington, 

D.C.

State 2005 Base 2012 Base 2014 Base

2014 

Remedy

2012 Base minus 2005 Base 2014 Base minus 2012 Base

2014 Remedy minus 2014 

Base

Difference % Diff. Difference % Diff. Difference % Diff.

Alabama 460,123 455,825 417,340 173,566 -4,298 -0.9% -38,485 -8.4% -243,775 -58.4%

Arizona 52,733 34,734 35,601 35,601 -17,999 -34.1% 867 2.5% 0 0.0%

Arkansas 66,384 87,241 99,411 106,685 20,857 31.4% 12,170 13.9% 7,274 7.3%

California 601 6,763 7,350 7,350 6,162 1025.3% 587 8.7% 0 0.0%

Colorado 64,174 52,963 62,105 73,858 -11,211 -17.5% 9,143 17.3% 11,753 18.9%

Connecticut 10,356 3,355 3,774 3,883 -7,001 -67.6% 419 12.5% 109 2.9%

Delaware 32,378 3,641 2,172 2,172 -28,738 -88.8% -1,468 -40.3% 0 0.0%

District of 

Columbia 1,082 0 0 0 -1,082 -100.0% 0 0

Florida 417,321 110,687 143,601 148,069 -306,634 -73.5% 32,914 29.7% 4,468 3.1%
105

State 2005 Base 2012 Base 2014 Base

2014 

Remedy 2012 Base minus 2005 Base 2014 Base minus 2012 Base

2014 Remedy minus 2014 

Base

Georgia 616,063 406,279 170,288 93,208 -209,784 -34.1% -235,991 -58.1% -77,080 -45.3%

Idaho 0 182 182 182 182 106823.2% 0 0.0% 0 0.0%

Illinois 330,382 489,140 141,606 132,647 158,758 48.1% -347,534 -71.0% -8,959 -6.3%

Indiana 878,979 789,116 727,786 195,046 -89,863 -10.2% -61,330 -7.8% -532,740 -73.2%

Iowa 130,264 127,102 133,083 83,827 -3,162 -2.4% 5,981 4.7% -49,256 -37.0%

Kansas 136,520 68,541 69,819 45,740 -67,978 -49.8% 1,277 1.9% -24,078 -34.5%

Kentucky 502,731 520,546 488,005 116,927 17,815 3.5% -32,541 -6.3% -371,078 -76.0%

Louisiana 109,875 103,835 118,230 139,204 -6,040 -5.5% 14,395 13.9% 20,973 17.7%

Maine 3,887 2,203 2,355 2,355 -1,684 -43.3% 152 6.9% 0 0.0%

Maryland 283,205 49,942 42,926 30,368 -233,263 -82.4% -7,016 -14.0% -12,558 -29.3%

Massachusetts 84,234 8,581 13,364 13,363 -75,653 -89.8% 4,783 55.7% -1 0.0%

Michigan 349,877 255,038 269,434 162,632 -94,840 -27.1% 14,396 5.6% -106,802 -39.6%

Minnesota 101,678 67,816 70,937 49,622 -33,862 -33.3% 3,121 4.6% -21,315 -30.0%

Mississippi 75,047 29,336 30,972 32,109 -45,711 -60.9% 1,636 5.6% 1,137 3.7%

Missouri 284,384 383,313 390,287 186,899 98,930 34.8% 6,973 1.8% -203,388 -52.1%

Montana 19,715 13,641 15,447 22,826 -6,074 -30.8% 1,806 13.2% 7,379 47.8%

Nebraska 74,955 71,904 73,073 71,339 -3,050 -4.1% 1,169 1.6% -1,734 -2.4%

Nevada 53,363 13,486 14,416 14,416 -39,876 -74.7% 930 6.9% 0 0.0%

New Hampshire 51,445 3,332 6,453 6,742 -48,113 -93.5% 3,121 93.7% 289 4.5%

New Jersey 57,044 26,346 38,856 6,243 -30,698 -53.8% 12,511 47.5% -32,614 -83.9%

New Mexico 30,628 9,895 11,857 13,926 -20,734 -67.7% 1,963 19.8% 2,068 17.4%

New York 180,847 56,461 42,887 15,160 -124,386 -68.8% -13,574 -24.0% -27,727 -64.7%

North Carolina 512,231 148,606 126,048 69,377 -363,625 -71.0% -22,558 -15.2% -56,670 -45.0%

North Dakota 137,371 101,946 103,633 103,624 -35,425 -25.8% 1,688 1.7% -9 0.0%

Ohio 1,116,095 882,559 851,199 178,975 -233,536 -20.9% -31,359 -3.6% -672,224 -79.0%

Oklahoma 110,081 135,972 137,981 138,072 25,891 23.5% 2,009 1.5% 91 0.1%

Oregon 12,304 10,197 11,336 11,336 -2,107 -17.1% 1,139 11.2% 0 0.0%

Pennsylvania 1,002,203 495,463 509,649 125,545 -506,740 -50.6% 14,186 2.9% -384,105 -75.4%

Rhode Island 176 0 0 0 -176 -100.0% 0 #DIV/0! 0

South Carolina 218,781 186,355 213,281 100,788 -32,426 -14.8% 26,927 14.4% -112,494 -52.7%

South Dakota 12,215 29,711 29,711 29,711 17,495 143.2% 0 0.0% 0 0.0%
106

State 2005 Base 2012 Base 2014 Base

2014 

Remedy 2012 Base minus 2005 Base 2014 Base minus 2012 Base

2014 Remedy minus 2014 

Base

Tennessee 266,148 324,377 284,468 64,721 58,229 21.9% -39,909 -12.3% -219,747 -77.2%

Texas 534,949 446,006 453,332 266,648 -88,944 -16.6% 7,326 1.6% -186,685 -41.2%

Tribal 3 0 0 0 -3 -100.0% 0 #DIV/0! 0

Utah 34,813 33,828 33,498 33,968 -985 -2.8% -330 -1.0% 469 1.4%

Vermont 9 219 263 263 209 2218.6% 44 20.2% 0 0.0%

Virginia 220,287 92,468 77,256 51,144 -127,819 -58.0% -15,212 -16.5% -26,112 -33.8%

Washington 3,409 3,225 3,430 3,430 -183 -5.4% 205 6.3% 0 0.0%

West Virginia 469,456 536,695 498,507 84,344 67,239 14.3% -38,188 -7.1% -414,163 -83.1%

Wisconsin 180,200 135,827 130,538 50,137 -44,373 -24.6% -5,290 -3.9% -80,401 -61.6%

Wyoming 89,874 45,112 51,817 58,530 -44,762 -49.8% 6,705 14.9% 6,714 13.0%

Grand Total 10,380,883 7,859,810 7,159,569 3,356,577 -2,521,072 -24.3% -700,242 -8.9% -3,802,991 -53.1%

Table 7-5. Group 1 and Group 2 States NOX Total Emissions for each Transport Rule Modeling Case

2005 Base 

Year

2012 Base 

Case

2014 Base 

Case

2014 

Remedy

2014 

Remedy -

2012 Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base 

Case 

2014 

Remedy 

- 2014 

Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2014 

Base Case 

Annual Total NOX Emissions for States in 

Group 1 8,942,956 5,998,929 5,592,557 5,490,517 -508,412 -8.5% -102,039 -1.8%

Annual Total NOX Emissions for States in 

Group 2 4,626,321 3,351,169 3,083,373 3,030,042 -321,127 -9.6% -53,331 -1.7%

Annual Total NOX for all States included for 

PM 13,569,277 9,350,098 8,675,929 8,520,559 -829,539 -8.9% -155,370 -1.8%

Annual Total NOX Emissions for All States 

Fully within the Eastern Modeling Domain 17,265,033 12,013,803 11,173,286 10,974,018 -1,039,784 -8.7% -199,268 -1.8%

Annual Total NOX Emissions for All Western 

States 3,887,276 2,959,396 2,751,224 2,751,659 -207,737 -7.0% 435 0.0%

Total NOX 21,152,309 14,973,199 13,924,510 13,725,678 -1,247,521 -8.3% -198,832 -1.4%
107
108

Table 7-6. Group 1 and Group 2 States SO2 Total Emissions for each Transport Rule Modeling Case

2005 Base 

Year

2012 Base 

Case

2014 Base 

Case

2014 

Remedy

2014 

Remedy -

2012 Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base 

Case 

2014 

Remedy -

2014 Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2014 

Base Case 

Annual Total SO2 Emissions for States in 

Group 1 8,695,431 6,841,869 6,198,185 2,999,641 -3,842,228 -56.2% -3,198,544 -51.6%

Annual Total SO2 Emissions for States in 

Group 2 2,989,533 2,343,536 2,086,522 1,419,361 -924,175 -39.4% -667,161 -32.0%

Annual Total SO2 for all States included for 

PM 11,684,964 9,185,405 8,284,707 4,419,002 -4,766,403 -51.9% -3,865,705 -46.7%

Annual Total SO2 Emissions for All States 

Fully within the Eastern Modeling Domain 13,545,837 10,361,804 9,512,351 5,680,977 -4,680,826 -45.2% -3,831,374 -40.3%

Annual Total SO2 Emissions for All Western 

States 808,533 567,085 566,435 594,818 27,733 4.9% 28,383 5.0%

Total SO2 14,354,370 10,928,889 10,078,786 6,275,795 -4,653,094 -42.6% -3,802,991 -37.7%
109

Table 7-7. Group 1 and Group 2 States NOX EGU Sector Emissions for each Transport Rule Modeling Case

2005 Base 

Year

2012 Base 

Case

2014 Base 

Case

2014 

Remedy

2014 

Remedy -

2012 Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base 

Case 

2014 

Remedy 

- 2014 

Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2014 

Base Case 

Annual EGU NOX Emissions for States in 

Group 1 1,927,858 938,824 940,211 838,171 -100,653 -10.7% -102,039 -10.9%

Annual EGU NOX Emissions for States in 

Group 2 700,110 444,377 425,686 372,355 -72,022 -16.2% -53,331 -12.5%

Annual EGU NOX for all States included for 

PM 2,627,967 1,383,201 1,365,897 1,210,527 -172,674 -12.5% -155,370 -11.4%

Annual EGU NOX Emissions for All States 

Fully within the Eastern Modeling Domain 3,224,300 1,715,510 1,718,178 1,518,910 -196,600 -11.5% -199,268 -11.6%

Annual EGU NOX Emissions for All Western 

States 504,861 369,180 371,244 371,680 2,500 0.7% 435 0.1%

Total EGU NOX 3,729,161 2,084,689 2,089,422 1,890,590 -194,099 -9.3% -198,832 -9.5%
110

Table 7-8. Group 1 and Group 2 States SO2 EGU Sector Emissions for each Transport Rule Modeling Case

2005 Base 

Year

2012 Base 

Case

2014 Base 

Case

2014 

Remedy

2014 

Remedy -

2012 Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base 

Case 

2014 

Remedy -

2014 Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2014 

Base Case 

Annual EGU SO2 Emissions for States in 

Group 1 6,764,335 5,313,000 4,752,537 1,553,993 -3,759,007 -70.8% -3,198,544 -67.3%

Annual EGU SO2 Emissions for States in 

Group 2 2,143,069 1,702,727 1,468,071 800,910 -901,816 -53.0% -667,161 -45.4%

Annual EGU SO2 for all States included for 

PM 8,907,403 7,015,726 6,220,608 2,354,903 -4,660,823 -66.4% -3,865,705 -62.1%

Annual EGU SO2 Emissions for All States 

Fully within the Eastern Modeling Domain 10,019,270 7,635,785 6,912,529 3,081,155 -4,554,630 -59.6% -3,831,374 -55.4%

Annual EGU SO2 Emissions for All Western 

States 361,613 224,026 247,039 275,422 51,397 22.9% 28,383 11.5%

EGU SO2 10,380,883 7,859,810 7,159,569 3,356,577 -4,503,233 -57.3% -3,802,991 -53.1%

Table 7-9. 26-State Total and Electric Generating Unit Sector Summer NOX Emissions for each Transport Rule Modeling Case

2005 Base 

Year

2012 

Base 

Case

2014 

Base 

Case

2014 

Remedy

2014 

Remedy 

- 2012 

Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2012 

Base Case 

2014 

Remedy 

- 2014 

Base 

Case 

Percent 

Change: 

2014 

Remedy 

vs 2014 

Base Case 

Summer EGU NOx Emissions for States Included for 

Ozone 1,001,600 671,939 668,513 593,833 -78,106 -11.6% -74,680 -11.2%

Summer Total NOx Emissions for States Included for 

Ozone 6,153,473 4,455,600 4,128,792 4,054,111 -401,489 -9.0% -74,680 -1.8%
111

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