Technical Support Document: 

Preparation of Emissions Inventories 

for the Version 4.1, 2005-based Platform 

DRAFT 

March 4, 2011 

U.S. Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Air Quality Assessment Division 

Contacts: 

Madeleine Strum, Rich Mason, Alison Eyth, Marc Houyoux, 
ii

TABLE OF CONTENTS

ACRONYMS ............................................................................................................................................................. III

LIST OF TABLES ...................................................................................................................................................... V

LIST OF FIGURES .................................................................................................................................................. VI

LIST OF APPENDICES .......................................................................................................................................... VI

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

2 2005 EMISSION INVENTORIES AND APPROACHES .............................................................................. 3

2.1 2005 NEI POINT SOURCES (PTIPM AND PTNONIPM) ........................................................................................ 11

2.1.1 IPM sector (ptipm) ............................................................................................................................... 16

2.1.2 Non-IPM sector (ptnonipm) ................................................................................................................. 16

2.2 2005 NONPOINT SOURCES (AFDUST, AG, NONPT)............................................................................................ 18

2.2.1 Area Fugitive dust sector (afdust) ........................................................................................................ 19

2.2.2 Agricultural Ammonia sector (ag) ....................................................................................................... 20

2.2.3 Other nonpoint sources (nonpt) ........................................................................................................... 23

2.3 FIRES (AVEFIRE) ............................................................................................................................................. 25

2.4 BIOGENIC SOURCES (BIOG) ............................................................................................................................. 28

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

SECA_C3) ................................................................................................................................................................. 28

2.5.1 Onroad mobile MOVES cold-start exhaust sources requiring temperature adjustments 

(on_moves_startpm) ........................................................................................................................................... 30

2.5.2 Onroad mobile MOVES running exhaust sources requiring temperature adjustments 

(on_moves_runpm) ............................................................................................................................................. 33

2.5.3 Onroad no-adjustments mobile sources (on_noadj) ............................................................................ 34

2.5.4 Nonroad mobile sources – NMIM-based nonroad (nonroad) ............................................................. 35

2.5.5 Nonroad mobile sources: locomotive and non-C3 commercial marine (alm_no_c3) ........................ 36

2.5.6 Nonroad mobile sources: C3 commercial marine (seca_c3) .............................................................. 38

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

OTHPT_HG, AND OTHAR_HG) ................................................................................................................................... 40

2.7 SMOKE-READY NON-ANTHROPOGENIC INVENTORIES FOR MERCURY AND CHLORINE ................................... 43

2.7.1 Mercury ............................................................................................................................................... 43

2.7.2 Chlorine ............................................................................................................................................... 44

3 EMISSIONS MODELING SUMMARY ........................................................................................................ 44

3.1 KEY EMISSIONS MODELING SETTINGS............................................................................................................. 45

3.1.1 Spatial configuration ........................................................................................................................... 46

3.1.2 Chemical speciation configuration ...................................................................................................... 48

3.1.3 Temporal processing configuration ..................................................................................................... 56

3.2 EMISSIONS MODELING ANCILLARY FILES ....................................................................................................... 58

3.2.1 Spatial Allocation Data ....................................................................................................................... 58

3.2.2 Chemical speciation ancillary files ...................................................................................................... 63

3.2.3 Temporal allocation ancillary files ...................................................................................................... 67

4 REFERENCES ................................................................................................................................................. 75
iii

Acronyms 

BAFM Benzene, Acetaldehyde, Formaldehyde and Methanol

BEIS Biogenic Emissions Inventory System

C3 Category 3 (commercial marine vessels)

CAIR Clean Air Interstate Rule

CAMD 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

ICR Information Collection Request 

IMO International Marine Organization

IPM Integrated Planning Model

ITN Itinerant 

MACT Maximum Achievable Control Technology

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 

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

NONROAD OTAQ’s model for estimation of nonroad mobile emissions

NOX Nitrogen oxides

OAQPS EPA’s Office of Air Quality Planning and Standards

OTAQ EPA’s Office of Transportation and Air Quality

ORD 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
iv

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

PM10 Particulate matter less than or equal to 10 microns

RIA Regulatory Impact Analysis

RFS2 Revised Annual Renewable Fuel Standard

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
v

List of Tables 

Table 2-1. Platform sectors used in emissions modeling for the 2005 platform, version 4.1........ 4

Table 2-2. Summary of significant changes between v4 and v4.1 platforms by sector ................ 7

Table 2-3. 2005 Emissions by Sector: VOC, NOX, CO, SO2, NH3, PM10, PM2.5 ................ 10

Table 2-4. Summaries of Hg (speciated), HCL and CL2* .......................................................... 11

Table 2-5. Summaries of the non-anthropogenic mercury across the modeling domain ............ 11

Table 2-6. Hg changes made to the 2005 NATA Hg inventory (June 18, 2010 version) for the 

2005 ptnonipm, ptipm, and nonpt sectors. ............................................................................ 14

Table 2-7. SCCs in the afdust platform sector ............................................................................. 20

Table 2-8. Livestock SCCs extracted from the 2002 NEI to create the ag sector ....................... 21

Table 2-9. Fertilizer SCCs extracted from the 2002 NEI for inclusion in the “ag” sector .......... 23

Table 2-10. Additional TCEQ oil and gas emissions added to the 2005v2 NEI ......................... 24

Table 2-11. SCCs provided with Oklahoma oil and gas sector emissions .................................. 25

Table 2-12. Changes to Oklahoma oil and gas emissions ........................................................... 25

Table 2-13. Average fire VOC changes from 2002 to 2005 platform. ........................................ 26

Table 2-14. HAP emission factors applied to avefire PM2.5 emissions ....................................... 27

Table 2-15. Pollutants covered by MOVES2010 as used in the 2005v4.1 platform1 .................. 29

Table 2-16. SCCs in the 2005 alm_no_c3 inventory compared to the 2002 platform alm sector 37

Table 2-17. Adjustment factors to update the 2005 seca_c3 sector emissions for the v4.1 

platform. ................................................................................................................................ 39

Table 2-18. Contiguous U.S. C3 CMV emissions in 2002 and 2005 platforms .......................... 40

Table 2-19. Summary of the othpt, othpt_hg, othar, othar_hg, and othon sectors changes from 

the 2002 platform .................................................................................................................. 42

Table 3-1. Key emissions modeling steps by sector. ................................................................... 46

Table 3-2. Descriptions of the 2005-based platform grids .......................................................... 47

Table 3-3. Model species produced by SMOKE for CB05 with SOA for CMAQ4.7 ................ 49

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

each platform sector .............................................................................................................. 53

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

comprising 80% of the nonpoint VOC emissions................................................................. 54

Table 3-6. Temporal settings used for the platform sectors in SMOKE, v4.1 platform .............. 57

Table 3-7. U.S. Surrogates available for the 2005v4.1 platform. ................................................ 59

Table 3-8. Surrogate assignments to new mobile categories in the 2005v4 platform ................. 61

Table 3-9. Canadian Spatial Surrogates for 2005-based platform Canadian Emissions (v4.1 

unchanged from v4) .............................................................................................................. 62

Table 3-10. Differences between two profiles used for commercial marine residual oil ............ 65

Table 3-11. Differences between two profiles used for coal combustion .................................... 66

Table 3-12: PM2.5 speciation profile updates assignments for the v4 platform ............................ 66

Table 3-13. Summary of VOC speciation profile approach by sector for 2005 ........................... 67

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

gasoline vehicle types for the onroad parking area-related SCCs. ....................................... 70

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............. 72
vi

List of Figures 

Figure 2-1. MOVES exhaust temperature adjustment functions. ................................................ 32

Figure 3-1. CMAQ modeling domains ......................................................................................... 47

Figure 3-2. Process of integrating BAFM with VOC for use in VOC Speciation....................... 52

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

urban versus rural .................................................................................................................. 69

Figure 3-4. Diurnal temporal profile for HDDV 2B through 8B at Parking areas ...................... 69

List of Appendices 

Appendix A: Revisions to PTIPM Sector SO2 and NOX emissions from V4 to V4.1 

Appendix B: Creation of the modeling file (“ORL point file”) parameters from the Boiler 

MACT ICR unit level emissions 

Appendix C: Pollutants in the onroad emission sectors generated from NMIM or MOVES2010 

Appendix D: Approach to develop CMAQ PM2.5 species from Partially-speciated 

MOVES2010 EXHAUST PM2.5 for the 2005 Platform, version 4.1 
1

1 Introduction 

The U.S. Environmental Protection Agency (EPA), hereafter referred to as “we,” has developed 

an updated version of the 2005-based air quality modeling platform, version 4.1. This document 

describes the emissions inventory and emissions modeling for this version, focusing on the 

changes made from version 4. The version 4 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-Hg-BAFM 2005-Based Platform 

Version 4.1”. 

The platform consists of Criteria Air Pollutants (CAPs) and the following select Hazardous Air 

Pollutants (HAPs): mercury (Hg), chlorine (CL2), hydrochloric acid or hydrogen chloride (HCL) 

and benzene, acetaldehyde, formaldehyde and methanol. The latter four are also denoted BAFM. 

This platform is called the “CAP-Hg-BAFM 2005-Based Platform, Version 4.1” platform (we 

will use the shortened name “2005v4.1” in this documentation). This platform supports the 

Regulatory Impact Analysis for National Emission Standards for Hazardous Air Pollutants 

(NESHAP) for Industrial, Commercial, and Institutional Boilers and Process Heaters (a.k.a. 

“Boiler MACT”) and the proposal for the Toxics rule. 

The underlying 2005 inventories used are: 1) the 2005 National Emission Inventory (NEI), 

version 2 (http://www.epa.gov/ttn/chief/net/2005inventory.html), 2) the 2005 National Air 

Toxics Assessment (NATA) mercury inventory from June 2010, and 3) an inventory of Hg 

developed from the Boiler MACT Information Collection Request (ICR) for the National 

Emission Standards for Major Sources: Industrial/Commercial/Institutional Boilers and Process 

Heaters (http://www.epa.gov/ttn/atw/boiler/boilerpg.html). This document describes the 

approach and data used to produce the emission inputs to the air quality model used in the 

2005v4.1 platform. 

Emissions preparation for the 2005v4.1 platform supports the Community Multiscale Air Quality 

(CMAQ) model (http://www.epa.gov/AMD/CMAQ/) and (2) the Comprehensive Air Quality 

Model, with extensions (CAMx) (http://www.camx.com/). Both models support modeling ozone 

(O3), particulate matter (PM) and mercury (Hg), 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), individual component species for 

particulate matter less than or equal to 2.5 microns (PM2.5) and individual component species of 

gaseous and particulate mercury (Hg). 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. 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. 

The effort to create the emission inputs for the 2005v4.1 platform included: 

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

(2) updates to the emissions modeling ancillary files used with the emissions modeling tools, 

and 
2

(3) application of the emissions modeling tools. 

The primary emissions modeling tool used to create the CMAQ model-ready emissions was the 

Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system (http://www.smokemodel.org/index.cfm). We used SMOKE version 2.6 to create emissions files for a 36-km 

national grid, a 12-km Eastern grid and a 12-km Western grid for a 2005 base case (also known 

as the “2005cr_hg_05b” case for purposes of our directory structure). The purpose of this case is 

to provide a 2005 case that is consistent with the methods used in the future-year base case and 

control cases. For regulatory applications, this case is included in the relative response factor 

(RRF) calculations. 

Unlike the version 4 (v4) platform, this platform includes only a base case; it does not include a 

model evaluation case. The evaluation case in the 2005v4 platform uses 2005-specific fire 

emissions and 2005 hour-specific continuous emission monitoring (CEM) data for electric 

generating units (EGUs) whereas the 2005 base case includes an “average year” scenario for 

fires and a illustrative (rather than year-specific) temporal allocation approach for EGUs to 

allocate annual 2005 emissions to days and hours. This approach to temporal allocation was 

used for all base and control cases modeled to provide a temporal consistency that is intended to 

be a conceivable temporal allocation without tying the approach to a single year. 

The 2005v4.1 platform was developed using the concepts, tools and emissions modeling data 

from 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). 

Section 2 provides a summary of the key differences between the two versions of the emissions 

platform. 

This document contains five sections and four appendices. Section 2 describes the 2005 

inventories input to SMOKE. Section 3 describes the emissions modeling and the ancillary files 

used with the emission inventories. The development of the 2016 inventory (projected from 

2005) is provided through technical support documents for the specific modeling applications. 

Section 4 provides references. Appendices A through D provide additional details about specific 

technical methods. 

Electronic copies of the data used with SMOKE for the 2005 platform are available at the 

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

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

Based Platform, Version 4.1”. This is referred to as the “2005v4.1 website” throughout this 

document. In addition, this data is provided to the electronic docket in support of the Toxics 

Rule. 
3

2 2005 emission inventories and approaches 

This section describes the 2005 emissions data created for input to SMOKE. 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 

(case name: 2005ck_05b) and made changes described here. 

For mercury, the 2005v4.1 platform uses a later version of the 2005v2 NEI inventory prepared 

for the 2005 National Air Toxics Assessment (NATA). It uses the June 18, 2010 version of the 

2005 NATA inventory, with the exception of emissions from commercial, institutional and 

industrial boilers from the major source information collection request (ICR) database and other 

changes described later. The NATA inventory started with the 2005v2 NEI, and was updated 

with data collected for some source categories, which resulted in major updates to mercury 

emissions for Portland cement and hazardous waste combustion. The NATA inventory was also 

revised as a result of comments received as part of the state, local and tribal review. 

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 2005v4.1 

platform includes just a base case, the available day-specific wildfires and prescribed burning 

data from the 2005 NEI was not used; rather an average fire inventory that is used for both base 

and future years was used. 

For purposes of preparing the air quality model-ready emissions, we used the same split of the 

2005 emissions inventory into “platform” sectors for use in emissions modeling as was used in 

the 2005v4 platform. The significance of an emissions modeling or “platform” sector is that it is 

run through all of the SMOKE programs except the final merge (Mrggrid) independently from 

the other sectors. The final merge program combines the sector-specific gridded, speciated and 

hourly emissions together to create the CMAQ-ready emission inputs, which can be converted to 

emissions that can be used by CAMx when needed. 

Similarly to 2005v4, we added sectors for biogenic emissions, emissions from the Canadian and 

Mexican inventories, and augmented with other emissions data to be explained below. 

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. Updates from the 2005v4 platform are 

discussed in Table 2-2. 
4

Table 2-1. Platform sectors used in emissions modeling for the 2005 platform, version 4.1

Platform Sector 2005 NEI 

Sector 

Description and resolution of the data input to SMOKE

EGU sector (also 

called the IPM 

sector): ptipm 

Point For all pollutants other than mercury (Hg): 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 database. A few revisions were made to the 2005v2 NEI annual 

emission estimates as discussed in Table 2-2. 

For Hg: 6/18/2010 version of the inventory used for the 2005 National 

Air Toxics Assessment (NATA) mapped to IPM using NEEDS 

version 4.10. The NATA inventory is an update to the 2005v2 NEI 

and was divided into EGU and non-EGU sectors consistent with the 

other pollutants (we did not actually map the NATA inventory to IPM, 

but rather applied the mapping that was done to the 2005 NEIv2 to the 

NATA Hg inventory). We additionally removed Hg from sources 

from the National Emission Standards for Hazardous Air Pollutants 

for Industrial, Commercial, and Institutional Boilers and Process 

Heaters (aka “Boiler MACT”) Information Collection Request (ICR) 

database because we included these emissions in the non-EGU sector. 

For both: Day-specific emissions created for input into SMOKE. 

Non-EGU sector 

(also called the 

non-IPM sector): 

ptnonipm

Point For all pollutants other than Hg: All 2005v2 NEI point source records 

not matched to the ptipm sector. Includes all aircraft emissions. 

Additionally updated inventory to remove duplicates, improve 

estimates from ethanol plants, and reflect new information collected 

from industry from the ICR for the Boiler MACT. 

For Hg: The 6/18/2010 version of NATA inventory was used except 

for modifications to gold mine emissions and removal of Hg from 

facilities that closed prior to 2005. In addition, Hg emissions 

developed for the Boiler MACT were used 

For both: Annual resolution. 

Average-fire 

sector: avefire 

Not 

applicable

Average-year wildfire and prescribed fire emissions, unchanged from 

the 2005v4 platform; county and annual resolution. 

Agricultural 

sector: ag

Nonpoint NH3 emissions from NEI nonpoint livestock and fertilizer application, 

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

Area fugitive dust 

sector: afdust

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

inventory (e.g., building construction, road construction, paved roads, 

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

Unchanged from the 2005v4 platform. 

Remaining 

nonpoint sector: 

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 and year 2005 Texas 

and Oklahoma oil and gas emissions. Removed Hg emissions from 

boilers to avoid double counting with Hg emissions added to the nonEGU sector from the Boiler MACT ICR. 

Nonroad sector: 

nonroad

Mobile: 

Nonroad 

Monthly nonroad emissions from the National Mobile Inventory 

Model (NMIM) using NONROAD2005 version nr05c-BondBase 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. 
5

Platform Sector 2005 NEI 

Sector 

Description and resolution of the data input to SMOKE 

locomotive, and 

non-C3 

commercial 

marine: 

alm_no_c3

Mobile: 

Nonroad 

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

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). 

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 2005 NEI version 2. 

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. 

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. 

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.

Other point 

sources not from 

the NEI, Hg only: 

othpt_hg

Not 

applicable

Annual year 2000 Canada speciated mercury point source emissions.

Other nonpoint 

and nonroad not 

Not 

applicable

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

Phase III (municipio resolution) nonpoint and nonroad mobile 
6

Platform Sector 2005 NEI 

Sector 

Description and resolution of the data input to SMOKE 

from the NEI: 

othar

inventories.

Other nonpoint 

sources not from 

the NEI, Hg only: 

othar_hg

Not 

applicable

Annual year 2000 Canada speciated mercury from nonpoint sources.

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. 

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

2005v4.1 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 2005v4.1 emissions platform, we provide in 

Table 2-2 a summary of the significant differences between the 2005v4 emissions platform and 

this 2005v4.1 platform. 
7

Table 2-2. Summary of significant changes between v4 and v4.1 platforms by sector

Platform Sector Summary of Significant Inventory Differences from V4 to V4.1 

IPM sector: ptipm − 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, resulting in lower NOX and/or SO2 for CA, MA, NY, 

SC and increasing for MS and WV as shown below 

CA NOX down 75.4 tons; SO2 down 21.1 tons 

MA NOX down 483 tons ; SO2 down 1533.4 tons 

NY NOX down 149.3 tons 

SC NOX down 1166.2, tons SO2 down 1.3 tons 

MS SO2 up 929.7 tons 

WV NOX up 142.5 tons 

− Appendix A, Table A-1 provides a facility-level summary of these changes. 

Only replaced emissions if 2005 CEM data were confirmed to be for the entire 

year (some CEM is only for the summer season). 

− Hg emissions from 2005v2 were replaced with Hg emissions from the June 2010 

version of the NATA 2005 inventory except for units matched to the Boiler 

MACT ICR database. 

− Hg emissions for units matched to units in the Boiler MACT ICR database were 

removed (summing to 0.045 tons Hg). The Boiler MACT ICR database Hg 

emissions were used for these in place of the NATA Hg values, but were 

included in the ptnonipm sector. 

Non-IPM sector: 

ptnonipm

− Revised 2005 emissions for many point sources other than EGUs 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 ICR. A summary of these NOx, SO2, and 

PM2.5 emissions from v4 to v4.1 are listed:

State 

NOX change 

v4 to v4.1 

SO2 change 

v4 to v4.1 

PM2.5 change 

v4 to v4.1 

California 30 39 1 

Georgia -1,242 -1,614 -28 

Indiana -4,941 -7,379 -1,291

Iowa 2,519 3,206 100

Kansas 73 93 3 

Kentucky 121 154 5

Nebraska 31 39 1 

New Mexico 182 231 7

North Carolina -6,701 0

North Dakota 128 220 13

Ohio -366 -3,303 0 

Pennsylvania 101 -2,035 

South Dakota 236 301 10 

Tennessee -6,098 -11,046 -760 

− Hg emissions changed to use NATA inventory. Updated NATA inventory to 

remove closed plants and also replaced boiler Hg with for units mapped to Boiler 

MACT ICR database with the ICR Hg emissions. 

Average-fire 

sector: avefire 

Unchanged from 2005v4 platform
8

Platform Sector Summary of Significant Inventory Differences from V4 to V4.1 

Agricultural 

sector: ag

Unchanged from 2005v4 platform

Area fugitive dust 

sector: afdust

Unchanged from 2005v4 platform

Remaining 

nonpoint sector: 

nonpt

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 EPA. Changed pesticide category to 

“no-integrate,” thereby using VOC speciation (rather than the HAP emissions) to 

compute the BAFM emissions. 

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

Unchanged from 2005v4 platform

C3 commercial 

marine: seca_c3 

Revised 2005 emissions from the category 3 commercial marine 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). 

Also 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 v4.1 seca_c3 inventories contain Canadian province codes. 

Onroad 

California, 

NMIM-based, and 

MOVES sources 

not subject to 

temperature 

adjustments: 

on_noadj

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

wear) from all vehicle types are now from MOVES2010 except for Hg. Hg is from 

2005v2 NEI, based on the MOBILE6 model. 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. 

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 2005v4.1 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 

Same change as “on_moves_startpm”
9

Platform Sector Summary of Significant Inventory Differences from V4 to V4.1 

mode vehicle from 

MOVES subject 

to temperature 

adjustments: 

on_moves_runpm

Biogenic: biog Unchanged from 2005v4 platform

Other point 

sources not from 

the NEI: othpt

Unchanged from 2005v4 platform

Other point 

sources not from 

the NEI, Hg only: 

othpt_hg

Unchanged from 2005v4 platform

Other nonpoint 

and nonroad not 

from the NEI: 

othar

Unchanged from 2005v4 platform

Other nonpoint 

sources not from 

the NEI, Hg only: 

othar_hg

Unchanged from 2005v4 platform

Other onroad 

sources not from 

the NEI: othon

Unchanged from 2005v4 platform

Annual emission summaries for 2005v4.1, 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). Summaries of Hg (speciated), HCL and CL2 are provided in Table 2-4, and Table 

2-5 provides a summary of natural mercury sources for the modeling domain. 

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
10

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

Sector 

2005 

VOC [tons/yr] 

2005 

NOX [tons/yr] 

2005 

CO [tons/yr] 

2005 

SO2 [tons/yr] 

2005 

 NH3 [tons/yr] 

2

 PM10 

V4.1 V4 V4.1 V4 V4.1 V4 V4.1 V4 V4.1 V4 V4.1 

afdust 8,858,992 

ag 3,251,990 same

alm_no_c3 67,690 same 1,924,925 same 270,007 same 154,016 same 773 same 59,366 

seca_c3 (US 

component) 44,990 22,367 647,884 642,088 54,049 53,746 420,110 417,312 53,918 

seca_c3 (nonUS 

component)

18,367 18,241 532,181 526,760 43,267 42,959 321,414 319,200 43,326 

nonpt 7,530,564 7,474,512 1,699,532 1,683,490 7,413,762 7,376,314 1,259,635 1,252,645 134,080 134,080 1,354,638 

nonroad 2,691,844 same 2,115,408 same 19,502,718 same 197,341 same 1,972 same 211,807 

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 

on_moves

_runpm 54,071 

on_moves_

startpm 22,729 

ptipm 40,950 same 3,726,459 3,728,190 601,564 same 10,380,786 10,381,411 21,684 same 615,095 

ptnonipm 1,310,784 1,310,085 2,238,002 2,247,228 3,221,388 3,222,221 2,089,836 2,117,649 158,837 159,003 653,048 

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

Canada othar1 1,281,095 same 734,587 same 3,789,362 same 95,086 same 546,034 same 1,666,188 Canada othon 270,872 same 524,837 same 4,403,745 same 5,309 same 21,312 same 14,665 Canada othpt 447,313 same 857,977 same 1,270,438 same 1,664,040 same 21,268 same 117,669 Mexico othar 586,842 same 249,045 same 644,733 same 101,047 same 486,484 same 143,816 Mexico othon 183,429 same 147,419 same 1,455,121 same 8,270 same 2,547 same 6,955 Mexico othpt 113,044 same 258,510 same 88,957 same 980,359 same 0 same 125,385 offshore othpt 51,240 same 82,581 same 89,812 same 1,961 same 0 same 839 

1. Canada provided 2006 fires but we did not use them in the 2005 platform (for neither v4.1 nor v4) 
11 

Table 2-4. Summaries of Hg (speciated), HCL and CL2*

2005 HGIIGAS 

(divalent gaseous 

mercury) 

[tons/yr] 

2005 HGNRVA 

(elemental 

mercury) 

 [tons/yr] 

2005 PHGI 

(particulate 

mercury) 

[tons/yr] 

2005 

HCL [tons/yr] 

2005 

CL2 [tons/yr] 

V4.1 V4 V4.1 V4 V4.1 V4 V4.1 V4 V4.1 V4 

alm_no_c3 0.0411 same 0.0793 same 0.0212 same 1.38 same 

seca_c3 0.0002 same 0.0004 same 0.0001 same 

seca_c3 non-US 0.0001 same 0.00018 same 0.00007 same

Nonpt 1.0605 1.9901 3.1034 4.6528 1.2722 0.6524 29,001 29,364 2,135 same 

Nonroad 0.1041 same 0.2105 same 0.0533 0.0533 

on_noadj 0.1402 same 0.5036 same 0.0599 0.0599 

Ptipm 21.096 21.1757 30.1986 30.318 1.6596 1.6136 351,592 same 99 same 

Ptnonipm 10.4687 16.4756 29.5686 23.7646 7.4707 6.1291 48,630 48,664 4,174 same 

Canada othar_hg 1.08 0.86 0.34 

Canada othpt_hg 1.72 3.59 0.5 

* The sectors afdust, ag, avefire, on_moves_runpm, and on_moves_startpm have no Cl or Hg emissions 

In addition to the anthropogenic sectors, we include speciated hourly emissions for the geogenic 

categories listed in Table 2-5. 

Table 2-5. Summaries of the non-anthropogenic mercury across the modeling domain 

Region Species 

Landdirect

[tons/yr]

Landrecycled

[tons/yr]

Ocean 

Direct

[tons/yr]

Ocean 

Recycled

[tons/yr]

Volcanic 

[tons/yr] 

Domain-wide Elemental Mercury (HGNRVA) 12.077 158.01 7.27 56.51 0.02

The remainder of Section 2 provides details of 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 2005v4.1 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 
12 

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, PM2.5 and the following HAPs: HCL (pollutant code = 7647010), CL2 

(code = 7782505) and mercury (codes: 199, 200, 201, 202, 22967926, 593748, 62384, 7439976, 

and 7487947). 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). We utilized Hg from the NATA Hg point source 

inventories with the modifications discussed below. 

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 

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: 

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 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 non-EGU point inventory prior to modeling 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 
13 

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. 

• We defaulted stack parameters for some point sources when modeling in SMOKE. 

SMOKE uses an ancillary file, called the PSTK file, which 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. 

We also made a changes to the 2005 NATA Hg inventory (June 18, 2010 version) prior to its use 

in modeling. We removed sources that were discovered to have closed prior to 2005. We 

modified gold mine emissions based on information collected as part of the data gathering for the 

proposed gold mine rule. We replaced Hg emissions with values in the Boiler MACT ICR 

database. Of the 1607 facilities in the Boiler MACT ICR database, all except for 184 facilities 

(0.177 tons Hg) were matched to inventory (NATA inventory, NEI v2 inventory or both) 

facilities based on the NEI_UNIQUE_ID code. The 184 facilities without NEI_UNIQUE_IDs 

were not used in our 2005 Hg inventory for the platform. Since the ICR database contained only 

emissions by unit and the fuel type, we needed to assign the geographic coordinates and stack 

parameters needed to transform the Boiler MACT ICR database into a modeling file. We used 

geographic coordinates and stack parameters from the NATA Hg inventory (or NEI v2 if not in 

the NATA inventory) by matching the facility and then choosing the parameters from the 

process/unit that matched the fuel type in the ICR. If more than one unit matched, we used the 

stack parameters from the unit with the highest emissions. Where there were no fuel matches, 

we used default parameters. Additional information on these changes is provided in Table 2-6 

below. Further details of this procedure, and the other fields we populated to construct the 

modeling file are provided in Appendix B. 

Because the NATA Hg point source emissions were not separated into ptnonipm and ptipm, we 

applied the same point splits (via the field IPM_YN) to the NATA Hg inventory as were applied 

to the 2005v2 NEI. 
14 

Table 2-6. Hg changes made to the 2005 NATA Hg inventory (June 18, 2010 version) for the 

2005 ptnonipm, ptipm, and nonpt sectors.

Change 

Incorporated Boiler MACT 

ICR emissions 

Added 4.66 tons Hg from ICR unit-level emissions data. 

Generated modeling parameters (latitudes/longitudes, stack 

parameters) from the NATA Hg or NEI inventories, by matching 

ICR facilities/fuel information to matching facility identifiers (the 

NEI_UNIQUE_ID) and fuel types in these other modeling 

inventories. 

Removed 0.045 tons Hg from ptipm which is the sum of Hg from 

sources that and matched a facility in the ICR based on the 

NEI_UNIQUE_ID and either (1) had a design capacity of less than 25 

MW and matched a facility in the ICR or (2) had no design capacity 

listed had a MACT code beginning with 0107, which is the general 

code for identify industrial, commercial, institutional boilers and 

process heaters.

Removed 1.71 tons Hg from ptnonipm - we used a crosswalk that 

link combinations of Maximum Achievable Control Technology 

(MACT) code, standard industrial code (SIC), NAICS (North 

American Industrial Classification System) code and source 

classification code (SCC) to identify industrial, commercial, 

institutional (ICI) boilers and process heaters, and removed all 

records that matched the ICR facilities based on the 

NEI_UNIQUE_ID. 

Removed 3.15 tons Hg from nonpt – we used a crosswalk that 

link combinations of MACT and SCC to ICI boilers and process 

heaters and removed all records 4.68 to in the nonpt sector that 

matched. 

Changed Gold Mine 

Emissions, geographic 

coordinates and stack 

parameters 

Changed facility emissions for nine out of 19 facilities in the 

ptnonipm sector based on data collected for the proposed National 

Emission Standards for Hazardous Air Pollutants for Gold Mine 

Ore Processing and Production, provided by the EPA Sector 

Policies and Programs Division (SPPD) project lead Chuck 

French. 

These changes are summarized below, and result in an overall 

total change of Hg emissions from Goldmines from 2.35 to 2.50 

tons. 

State facility ID Facility name

Updated 

Hg 

emissions

BASIS

89406KNNCT55MIL 

KENNECOTT RAWHIDE 

MINING CO 0.02 

based on 2007 

emissions test data 

89045SMKYV1SMOK 

SMOKY VALLEY COMMON 

OPERATION 0.03 

based on 2007 

emissions test data 

T$18242 RUBY HILL MINE 0.018

based on 2007 

emissions test data

89418FLRDCEXIT1 STANDARD MINING INC 0.08

based on 2008 

emissions test data
15 

89419CRRCH180EX COEUR ROCHESTER INC 0.069 

based on 2007 

emissions test data 

89438NWMNTSTONE 

NEWMONT MINING CORP 

LONE TREE MINE 0.311 

based on 2006 

emissions test data 

89801JRRTT50MIL JERRITT CANYON MINE 0.23

 is for the 2004-05 

timeframe based on 

the estimate 

submitted to Nevada 

DEP in response to 

ICR survey sent to 

the company. 

89803BLDMN70MIL BALD MOUNTAIN MINE 0.14 

based on 2008 

emissions test data 

89803BRRCK27MIL 

BARRICK GOLDSTRIKE MINES 

INC 0.35 

based on 2007 

emissions test data 

 Also changed geographic coordinates and stack parameters for 

10 facilities based on information provided by Chuck French that 

was used in local scale modeling done in support of the NESHAP 

in early 2010. 

 

Facility Name 

GLAMIS MARIGOLD MINE Refinery building operations 

NEWMONT MINING CORP 

CARLIN SOUTH Refinery and roasting operations 

NEWMONT MINING CORP 

TWIN CREEKS MINE Refinery and autoclave operations 

SMOKY VALLEY COMMON 

OPERATION Refinery building operations 

CORTEZ GOLD MINES Refinery building operations 

RUBY HILL Refinery building operations 

BARRICK GOLDSTRIKE Refinery, autoclave & roasting operations 

WESTERN MESQUITE MINES Refinery building operations 

CRIPPLE CREEK COLORADO Refinery building operations 

GREENS CREEK WA Refinery building operations 

Removed Hg emissions for 

sources closed or not 

operating in 2005 

Removed 0.342 tons, most of which (0.337 tons) is associated 

with the removal of Northwestern Steel & Wire Co, Illinois 

(NEI_UNIQUE_ID NEIIL1955ABD), which shut down prior to 

2005. Other removals were: 

• Arkwright, Georgia (NEI12787) 

• CPSG Gould Street, Maryland (NEI7008) State sent article 

written in 2008 

(http://www.thefreelibrary.com/Constellation+

Energy+Restarts+Gould+Street+Power+Plant+in+Baltimore.-

a0179900776 ) that said it had been shut down for the last 5 

years and would be re-opening as a gas fired plant only. 

• Midwest Generation LLC, Illinois (NEIIL0638266). 

• Northwestern Steel & Wire Co, Illinois (NEIIL1955ABD) 
16 

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 to (1) provide consistency between the 2005 EGU 

sources and future year EGU emissions for sources which are forecasted by IPM and (2) 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. 

Although we used the same ptipm split as was used for the v4 platform, 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 The impact of these changes is summarized in Table 2-2 and detailed changes are 

provided in Appendix A. 

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. 

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 

 

2

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

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. 
17 

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 2005 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. 

Ptnonipm updates from 2005v4 platform used in creating the 2005v4.1 platform 

Found and removed additional duplicate records. These records were duplicates caused by 

records from both 2002 and 2005 being in the inventory. These were caught after ignoring 

leading zeroes in the plant IDs, point IDs, etc. that were present for only one of the years of data. 

There were a total of 175 records removed. A summary of the emissions removed is provided 

below. Due to the small mass of duplicate HAP records and the fact that most were not being 

used in the platform, no HAP records were removed. 

CO 3,520 tons

NH3 166 tons

NOX 13,421 tons

PM10 3,858 tons

PM2.5 3,444 tons

SO2 21,061 tons

VOC 1,504 tons
18 

• Removed duplicate emissions for Blue Ridge Paper (FIPS=37087). For the same unitid, 

stackid and SCC there were two records for the same pollutant with different data source 

codes but similar emissions values. They appeared to be duplicates so they were removed. 

• Updated boiler emissions at Domtar Paper/Johnsonburg Mill (FIPS code =42047), which 

included 2002 emissions values to 2005 emissions values based on information provided 

by the Department of Environmental Protection in Pennsylvania. They had put on 

scrubbers between 2002 and 2005 and that was not reflected in the platform 2002-based 

emissions. Rather than apply the reductions, we updated the emissions to better reflect 

2005. Note: We only changed NOX , SO2 and HCL even though the facility representative 

send information for all pollutants plant because of the effort involved with converting the 

information provided into a form usable for modeling. 

• Removed unit-level emissions from plants for units determined to have shut down 

between 2002 and 2005. In all situations, the state inventory representative was contacted 

to confirm that the unit actually shut down. Plants impacted were: LaFarge Cement Plant 

in Atlanta Georgia, Domtar Paper, Tennessee, FIPS=47163 and P. H. Glatfelter Company 

in Chillicothe, Ohio. 

• Added 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. Added the 

2002-based emissions to the ptnonipm file, since 2005 data were not available. 

• Added an inventory of 2005 ethanol plants using plant names and data provided by 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 10.47 30.31 12.13 1.29 38.58 14.33

13205 Wind Gap Farms (Anheuser/Miller Brewery) 0.84 2.43 0.97 0.10 3.09 1.15

19033 Golden Grain Energy LLC 146.60 424.38 169.75 15.33 540.12 200.62

19035 Little Sioux Corn Processors 184.30 533.51 213.40 19.27 679.01 252.20

19055 Permeate Refining 3.14 9.09 3.64 0.39 11.57 4.30

19057 Big River Resources, LLC 108.91 315.26 126.10 13.43 401.23 149.03

19083 Hawkeye Renewables, LLC 115.19 333.44 133.38 14.21 424.38 157.63

19093 Quad-County Corn Processors 56.55 163.69 65.48 6.97 208.33 77.38 

19167 Siouxland Energy & Livestock Coop (SELC) 209.44 606.26 242.50 25.83 771.60 286.60

21047 Commonwealth Agri-Energy, LLC 46.08 133.38 53.35 4.82 169.75 63.05

31047 Cornhusker Energy Lexington (CEL) 25.13 72.75 29.10 3.10 92.59 34.39

31145 SW Energy, LLC. 41.89 121.25 48.50 5.17 154.32 57.32

35041 Abengoa Bioenergy Corporation 10.47 30.31 12.13 1.09 38.58 14.33

46005 Heartland Grain Fuels, LP 0.21 0.61 0.24 0.03 0.77 0.29

46109 North Country Ethanol (NCE) 62.83 181.88 72.75 6.57 231.48 85.98

19109 Global Ethanol 29.32 84.88 33.95 3.07 108.02 40.12

20055 Reeve Agri-Energy 52.36 151.57 60.63 6.46 192.90 71.65

TOTAL TONS 1103.73 3195.00 1278.00 127.13 4066.36 1510.36

2.2 2005 Nonpoint sources (afdust, ag, nonpt) 

The 2005v2 NEI generally did not include updated nonpoint emissions from values used in the 

2002 NEI, and this modeling platform took a similar approach. Consequently, we created 

several sectors from the 2002 nonpoint NEI. We removed the nonpoint tribal-submitted 
19 

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 modeling. This omission also eliminated the need 

for us to develop spatial surrogate data for allocation of tribal data to grid cells during the 

SMOKE processing, with little expected impact. 

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. Previously, 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 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 2-7. 
20 

Table 2-7. 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 2005v4.1 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 
21 

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 2-8, and the fertilizer SCCs are listed in Table 2-9. 

Table 2-8. 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 
22 

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”. 
23 

Table 2-9. 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 2005v4.1 platform. 

Below is a list of changes made from the 2002 platform both for the v4 platform and for the v4.1 

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 2005 NEIv2 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 

2005 NEIv2 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. 
24 

Updates from 2005v4 platform used in creating the 2005v4.1 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 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 2-10. 

Table 2-10. 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 

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 2-11. 
25 

Table 2-11. 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 2-12. Note that Oklahoma 

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

and PM10 is the same as PM2.5 

Table 2-12. 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) 

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

completeness. 

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 

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

burning and other open burning sources

year-to-year impacts are not as variable as wildfires and non

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 

platform. 

We created the average-fires inventory based on the 2001 (1999 NEI

The average fire sector is comprised of a 1996

prescribed burning. We calculated the average wildfire and prescribed burning inventories using 

the following formula for all pollutants:

The average acres-burned was calculated base on 1996 through 2002 data; therefore, the average 

fire inventory represent average fires from 1996 through 2002, with the assumption of 2001 

emissions rates and a spatial distribution of emissions to counties based on fires from 2001. This 

approach is the same as that used for our previous emissions modeling platforms used to model 

2001 and 2002 base years, with some differences described here.

The 2005 platform avefire sector differs from the avefire sector in the 2002 platform

following ways: 

a. We recomputed 

of EPA fire inventory expert 

too high (Tom Pace

b. We created HAP 

Table 2-13 provides the VOC differences between the 2002 and 2005 platforms for each of the 

types of fires in the avefire sector. Emissions for CO and PM

for reference. 

Table 2-13. Average fire VOC changes from 2002 to 2005 platform

SCC SCC Description

2810001000 Forest Wildfires;Total

2810005000 Managed Burning, Slash (Logging 

Debris);Total 

2810015000 Prescribed Burning for Forest 

Management;Total

* all SCC descriptions begin with “Miscellaneous Area Sources; Other 

26 

ildfire and prescribed burning emissions. It exclude

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

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

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

level. The same emissions are used in the v4 and v4.1 versions of the 2005

fires inventory based on the 2001 (1999 NEI-based) fire emissions data. 

The average fire sector is comprised of a 1996-2002 average fire inventory for wildfires and 

burning. We calculated the average wildfire and prescribed burning inventories using 

the following formula for all pollutants:

burned was calculated base on 1996 through 2002 data; therefore, the average 

age fires from 1996 through 2002, with the assumption of 2001 

emissions rates and a spatial distribution of emissions to counties based on fires from 2001. This 

approach is the same as that used for our previous emissions modeling platforms used to model 

2001 and 2002 base years, with some differences described here.

avefire sector differs from the avefire sector in the 2002 platform

We recomputed VOC as a function of CO: VOC = CO * 0.229 at the suggestion 

fire inventory expert who reviewed the VOC emissions and found them 

(Tom Pace, personal communication). 

HAP emissions records by applying emission ratios to PM

provides the VOC differences between the 2002 and 2005 platforms for each of the 

types of fires in the avefire sector. Emissions for CO and PM2.5 are unchanged and are provided 

Average fire VOC changes from 2002 to 2005 platform

CC Description * 

2002 VOC

(tons/yr) 

2005 VOC

(tons/yr) 

Forest Wildfires;Total 386,997 1,883,230

Managed Burning, Slash (Logging 

67,664 105,661

Prescribed Burning for Forest 

Management;Total 84,784 399,880

* all SCC descriptions begin with “Miscellaneous Area Sources; Other Combustion”

excludes agricultural 

in the nonpt sector. Generally, their 

agricultural prescribed/managed 

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

the v4 and v4.1 versions of the 2005-based 

based) fire emissions data. 

2002 average fire inventory for wildfires and 

burning. We calculated the average wildfire and prescribed burning inventories using 

burned was calculated base on 1996 through 2002 data; therefore, the average 

age fires from 1996 through 2002, with the assumption of 2001 

emissions rates and a spatial distribution of emissions to counties based on fires from 2001. This 

approach is the same as that used for our previous emissions modeling platforms used to model 

avefire sector differs from the avefire sector in the 2002 platform in the 

VOC as a function of CO: VOC = CO * 0.229 at the suggestion 

who reviewed the VOC emissions and found them 

by applying emission ratios to PM2.5. 

provides the VOC differences between the 2002 and 2005 platforms for each of the 

are unchanged and are provided 

Average fire VOC changes from 2002 to 2005 platform.

CO 

(tons/yr) 

PM2.5

(tons/yr) 

8,223,736 685,783

461,404 7,460

1,746,208 147,298

Combustion”
27 

The 2005 HAP emissions records were created by multiplying PM2.5 emissions by the emission 

factors in Table 2-14. The HAP factors are the same for all source types. Because we chose not 

to integrate criteria and HAP VOCs for the avefire sector, the HAPs contained in the avefire 

inventory were not used to generate air quality modeling inputs for the 2005 platform. 

Table 2-14. HAP emission factors applied to avefire PM2.5 emissions 

Pollutant Description CAS PM2.5 factor 

1,3-butadiene 106990 0.0147

1-Methylpyrene 2381217 0.00033

Acetaldehyde 75070 0.0148

Acrolein 107028 0.0154

Antracene 120127 0.00018

Benz[a]Anthracene 56553 0.00022

Benzene 71432 0.041

Benzo(a)fluoranthene 203338 0.00009

Benzo(c)phenanthrene 195197 0.00014

Benzo[a]Pyrene 50328 0.00005

Benzo[e]Pyrene 192972 0.0001

Benzo[g,h,i,]Perylene 191242 0.00018

Benzo[k]Fluoranthene 207089 0.00009

Carbonyl sulfide 463581 0.00002

Chrysene 218019 0.00022

Fluoranthene 206440 0.00024

Formaldehyde 50000 0.0936

Hexane 110543 0.00059

Indeno[1,2,3-c,d]Pyrene 193395 0.00012

Methyl chloride 74873 0.00464

Methylanthracene 26914181 0.0003

Methylbenzopyrene 65357699 0.00011

Methylchrysene 41637905 0.00029

O-xylene 95476 0.001932554

M-xylene 108383 0.005392065

P-xylene 106423 0.00145538

Perylene 198550 0.00003

Phenanthrene 85018 0.00018

Pyrene 129000 0.00034

Toluene 108883 0.0206
28 

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 CMAQ meteorological input 

files, 

• 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 

aircraft, locomotive, and commercial marine emissions are divided into two nonroad sectors: 

“alm_no_c3” and “seca_c3”, and as previously mentioned, the aircraft emissions are in the nonEGU (ptnonipm) point inventory. 

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

used a final 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 non-motorcycle 

gasoline exhaust vehicles only); (3) MOVES2010 emissions cover all criteria pollutants and 

criteria pollutant precursors (as opposed to only exhaust mode PM2.5, VOC, NOX and CO); (4) 

we used NH3 from MOVES for California (as opposed to NH3 from NMIM) since Californiasupplied 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 v4.1 come 

from MOVES, are not impacted by cold temperatures. In addition, PM brake wear and tire wear 

mode emissions are now provided in MOVES in v4.1; these emissions for both gasoline and 

diesel vehicles are also not impacted by cold temperatures. 

The onroad emissions were primarily based on the 12/21/2009 version of the Motor Vehicle 

Emissions Simulator (MOVES2010) (http://www.epa.gov/otaq/models/moves/). MOVES was 
29 

run with a state/month aggregation using county-average fuels for each state, state/monthaverage temperatures, and national default vehicle age distributions. 2005 VMT, consistent with 

the 2005v2 NEI, were used. 

Table 2-15 lists the pollutants in the onroad sector based on MOVES2010 versus NMIM. A full 

list of the NMIM HAPs (most of which are not used in the v4.1 platform) is provided in 

Appendix C. 

Table 2-15. Pollutants covered by MOVES2010 as used in the 2005v4.1 platform1

Used in the 2005v4.1 platform from 

MOVES2010 

Available from 

MOVES2010, but not 

used in the 2005v4.1 

platform 

Used in the 2005v4.1 

platform from NMIM 

PM2.5; exhaust, partially speciated2 Naphthalene Elemental mercury 

PM2.5, brake and tirewear, unspeciated 1,3 butadiene Divalent gaseous mercury 

VOC; except refueling Acrolein Particulate Mercury 

CO, NOX, SO2, NH3

Benzene; except refueling 

Formaldehyde 

Acetaldehyde 

1

 MOVES data were not used for any California onroad emissions other than 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. 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. 

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. The emissions that did not come from the 

MOVES model were obtained from the 2005 NMIM runs, which are consistent with the 2005v2 

NEI. 

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, 2005b) for 

all of the U.S. except for California.6

 The NMIM data was used for the mercury emissions, to 

allocate California-submitted 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. The direct link is: 

ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile_sector/ncd/ncd20080522.zip. 

 

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. 
30 

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 have been replaced with a new 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 v4.1 by using revised 2005 emissions from the category 3 

commercial marine 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 v4.1 seca_c3 inventories 

contain Canadian province codes for near shore emissions. 

The nonroad sector, based on NMIM did not change for the v4.1 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 v4.1, 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. 

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 mobile MOVES cold-start exhaust sources requiring 

temperature adjustments (on_moves_startpm) 

This sector contains MOVES2010 emissions for PM and naphthalene7 for 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. 

 

7

 Naphthalene is not used in the 2005v4 CAP-BAFM platform, but it is contained in the MOVES emissions. 
31 

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. 
32 

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
33 

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. 

• 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 –described in Appendix D. Subject to temperature adjustment 

below 72 oF. 

The result of these preprocessing steps is SMOKE-ready PM emissions that do not exactly match 

what MOVES provides. The emissions are conserved during allocation from the state to county 

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. 

2.5.2 Onroad mobile MOVES running exhaust sources requiring 

temperature adjustments (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). 
34 

2.5.3 Onroad no-adjustments mobile sources (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 three sets of monthly inventories for this sector. 

1. MOVES-based onroad gasoline and diesel: These are the monthly (does not include 

gasoline exhaust mode PM and naphthalene) MOVES-based emissions from three 

MOVES inventories: 

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), 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 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. 

3. Remaining NMIM-based onroad inventory: The remainder of the non-California onroad 

inventory that was not replaced by MOVES. This includes monthly emissions the three 

species of mercury (divalent gas, elemental and particulate) as well as a number of other 

HAPs not used by the platform. The NMIM county database is NCD20080522; this is an 

update of NCD20070912 in which state/local and tribal inputs replace EPA default inputs 
35 

where provided. These emissions are identical to those in the v4 platform and are not 

described further here. 

2.5.4 Nonroad mobile sources – NMIM-based nonroad (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, which were corrected due to an inadvertent omission of PM2.5 from 7 counties. 

Thus, except for California, emissions from this sector did not change between the v4 and v4.1 

platform versions, and we repeat the documentation here for completeness. 

The NMIM relied on the version of the NONROAD2005 model (NR05c-BondBase) used for the 

marine spark ignited (SI) and small SI engine proposed rule, published May 18, 2007 (EPA, 

2007c). 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. 

Similar to the on_noadj pre-processing for evaporative emissions, we also reassigned NMIM 

evaporative and refueling xylene to the various isomers of xylene. We use the same percentages 

for refueling as for evaporative emissions as follows: we converted compound XYL or 

CAS=EVP__1330207, RFL__1330207) into MXYL (CAS=EVP__108383, RFL__108383) and 

OXYL (CAS=EVP__95476, RFL__95476) using a 68% and32% ratio to both evaporative and 

refueling XYL, respectively. We also split NMIM exhaust xylene (CAS=EXH__1330207) into 

MXYL (CAS=EXH__108383) and OXYL (CAS=EXH__95476) using a 74% and 26% ratio to 

XYL, respectively. 

EPA/OTAQ ran NMIM to create county-SCC emissions for the NEI 2005v2 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, 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 

in the NEI 2005 v2 submittal. We retained only those HAPs that are also estimated by NMIM 

for nonroad mobile sources; all other HAPs were dropped. 
36 

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 sources, except for category 3/residual-fuel (C3) commercial marine vessels and railway 

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 commercial marine vessel 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. This sector is unchanged from the v4 

platform; we repeat the documentation for completeness. 

The remaining emissions in the alm_no_c3 sector are year 2002 emissions unchanged from the 

2002 platform. The SCCs in the alm_no_c3 sector are listed in Table 2-16. 
37 

Table 2-16. 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 

The documentation of the 2002 NEI for the category 1 and 2 (C1/C2) commericial 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 2005 

platform: 

• For the 2005 platform, we removed C3 CMV SCCs (residual fuel) and aircraft SCCs. 
38 

• 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) 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 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). EPA developed regional 

growth (activity-based) factors that we applied to create the v4.1 platform 2005 inventory from 

the 2002 data. 

These region-specific and pollutant-specific growth factors were updated for the v4.1 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 (EPA-420-F-10-041, August 

2010). 

The updated factors that we used to project from 2002 to 2005 are presented in Table 2-17. 
39 

Table 2-17. Adjustment factors to update the 2005 seca_c3 sector emissions for the v4.1 

platform. 

2005 Adjustments Relative to 2002 

Region NOX PM10 PM2.5 VOC (HC) CO SO2 

Alaska East (AE) 1.08561 1.10440 1.10350 1.10453 1.10411 1.10438 

Alaska West (AW) 1.04671 1.06382 1.06404 1.06389 1.06391 1.06386 

East Coast (EC) 1.10524 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 

Hawaii East (HE) 1.09054 1.13429 1.13258 1.13352 1.13429 1.13422 

Hawaii West (HW) 1.09108 1.13402 1.13289 1.13443 1.13399 1.13428 

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 

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, nearshore emissions around Vancouver British Columbia are projected from 2002 using North 

Pacific (NP) factors rather than “Outside ECA” factors. 

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. 

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 were assigned as extending up to 200nm from the 

coast because of this was the distance through the Exclusive Economic Zone (EEZ), a distance 

that would be used to define the outer limits of ECA-IMO controls for these vessels. 

The 2005 ECA-based C3 inventory also does 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). This has no 

effect on temporal allocation or speciation compared to existing profiles for underway and port 

C3 emissions (2280003100 and 2280003200). The C3 CMV emissions in the 2002 and 2005 

platforms are shown in Table 2-18. 
40 

Table 2-18. Contiguous U.S. C3 CMV emissions in 2002 and 2005 platforms 

Pollutant 

2002 platform 

(tons/yr) 

2005v4 

platform 

(tons/yr) 

2005v4.1 

platform 

(tons/yr) 

CO 28,195 53,746 54,049

NH3 131 0 0

NOX 244,988 642,089 647,884

PM10 13,687 53,581 53,918

PM2.5 12,620 49,294 49,541

SO2 150,532 417,307 420,110

VOC 7,377 22,367 44,990

For the v4.1 platform, we chose only to include some HAPs in the seca_c3 sector: benzene, 

formaldehyde, and acetaldehyde. We projected these HAPs using the following VOC factors: 

Benzene = VOC * 9.795E-06 

Acetaldehyde = VOC * 2.286E-04 

Formaldehyde = VOC * 1.5672E-03 

Because we computed HAPs directly from the CAP inventory and the calculations are therefore 

consistent, the entire seca_c3 sector utilizes CAP-HAP VOC integration to use the VOC HAP 

species directly, rather than VOC speciation profiles. 

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. territory) are simply assigned a dummy 

state/county FIPS code=98001. Due the huge size of these data, the CAP emissions are in one 

ORL file and the HAP emissions are split into 6 separate ORL files. 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. 

2.6 Emissions from Canada, Mexico and Offshore Drilling Platforms 

(othpt, othar, othon, othpt_hg, and othar_hg) 

These sectors are unchanged from the 2005v4 platform; the documentation is repeated here for 

completeness. 

The emissions from Canada, Mexico, and Offshore Drilling platforms are included as part of five 

sectors: othpt, othpt_hg, othar, other_hg, 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. There are two new sectors in the 2005 platform, 

othpt_hg and othar_hg. These sectors contain year 2000 Canadian speciated mercury emissions 
41 

for point and area inventories. All other “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 non-Hg 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. 

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. 

x. Fixed coordinates for facility “ON105803” in the othpt_hg inventory to match those in 

the National Pollutant Release Inventory (NPRI) othpt sector. 

xi. Nonpoint speciated mercury emissions duplicate emissions summed and state/county 

FIPS code field changed from Nunavut (62) to NW Territories (61) to match surrogates. 
42 

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 2-19 summarizes the data in the “oth” sectors and indicates where these emissions have 

been updated from the 2002 platform. 

Table 2-19. Summary of the othpt, othpt_hg, othar, othar_hg, 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 

othpt_hg Canada, 2000, mercury 

point 

Uses speciated mercury point source year 2000 

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. 

othar_hg Canada, 2000, mercury 

nonpoint 

Uses speciated mercury nonpoint source year 2000 

inventory. 

othon Mexico, 1999, onroad None 

Canada, 2006, onroad Uses 2006 Canadian onroad inventory. Emissions 

are given at vehicle type resolution only (i.e., does 

not include road types). 
43 

2.7 SMOKE-ready non-anthropogenic inventories for mercury and 

chlorine 

We generated elemental mercury from natural (N), recycled (R) and volcanic (V) emissions, 

which we added to anthropogenic (A) elemental mercury processed from the inventories 

discussed above, to provide the elemental mercury species “HGNRVA” required by the multipollutant version of CMAQ. This model species is intended to include the sum of elemental 

mercury emissions from these sources. 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. 

A new recycled mercury file was developed for 2005 since the scaling factors applied to 

temporally allocate the annual natural and recycled emissions from oceans and land are based on 

solar radiation and skin temperature from the 2005 meteorology files. The annual files (prior to 

temporal allocation) differed from those of the 2002 platform only in that we reduced emissions 

of the natural emissions from land by 90% based on literature (Gustin, et. al., 2008), which 

indicated that the emissions are 10-12 tons per year as opposed to the 120 tons we had been 

using previously. 

2.7.1 Mercury 

As discussed in the CAP and HAP 2002v3-based platform documentation 

(ftp://ftp.epa.gov/EmisInventory/2002v3CAPHAP/documentation), the initial data for natural 

mercury, provided by Atmospheric and Environmental Research, Incorporated (AER), consisted 

of three existing global inventories containing annual flux rates of elemental mercury, gridded to 

1 degree by 1 degree resolution: 

• mercury emissions from oceans 

• mercury emissions from land 

• mercury emissions from volcanoes 

Annual fluxes of recycled elemental mercury for 2001 were created using the deposition results 

from a CMAQ 4.5.1 run. The approaches assumed that all recycled mercury emissions are in the 

form of elemental mercury gas. It is necessary to treat these recycled emissions whenever a 

version of CMAQ is used that also treats dry deposition of elemental mercury gas. The total 

deposition (wet plus dry) of all forms of mercury was used as the basis for the recycled emission 

estimates. A fraction equal to one-half the total deposition flux was used as the estimate for 

recycled emissions based on previous model calibrations done by AER. 

Natural and recycled emissions from oceans and land (but not volcanic emissions) were allocated 

to hourly values based on the meteorological variables of solar radiation and temperature, which 

are shown to be positively correlated with the evasion of elemental mercury from water surfaces 

soils and vegetation. While the correlation is widely variable for each of these surfaces, simple 

scaling functions for land and ocean developed for the 2001 applications were used for the 2002 

and were repeated again for the 2005v4 and v4.1 platforms, but using 2005-specific factors: 
44 

Ocean: ∑ ∗ −

∗ −

allhrs

hr hr

SOLRAD SFCTMP

SOLRAD SFCTMP

[ ( 273)]

( 273)

 or exactly zero for SFCTMP < 273 K 

Land: ∑ ∗ −

∗ −

allhrs

hr hr

SOLRAD SFCTMP

SOLRAD SFCTMP

[ ( 253)]

( 253)

 or exactly zero for SFCTMP < 253K 

where SOLRAD is the solar radiation in W/m2 and SFCTMP is the skin temperature (Kelvin), 

both from the 2-dimensional meteorology file from the Meteorology Chemistry Interface 

Processor (MCIP) output. 

The same sequence of steps were performed apply the hourly gridded scaling factors to create 

hourly gridded files for recycled and natural mercury based on 2005 meteorological data. No 

changes were made to the 2002 volcano mercury data 

2.7.2 Chlorine 

The oceanic chlorine gas emission estimates were the same as those used in the CAP and HAP 

2002 platform. 

3 Emissions modeling summary 

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, this processing step transforms these emissions from their original 

temporal resolution, pollutant resolution, and spatial resolution into the data required by the air 

quality model. As seen in Section 2, the temporal resolution of the emissions 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 pre-processing 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 this section’s descriptions of data to the ancillary data SMOKE uses 

to perform the emissions modeling steps 

All SMOKE inputs for the 2005v4.1 platform emissions are available at the 2005v4.1 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 CAMx. The emissions processing steps and ancillary data for v4.1 were very 

similar to those done for v4. A summary of the revisions is as follows: 
45 

• 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 used an updated county-to-cell spatial surrogate for U.S. oil and gas emissions. 

• We changed the temporal allocation approach to use profiles that vary by day of week 

and to use new temporal profiles for the afdust sector. 

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. As with the v4 platform, we used the CMAQ and 

CAMX in-line emissions capability to create source-based emissions files rather than the 3-

dimensional files for sectors that have plume rise. When CAMx was used, the emissions were 

first created in a form appropriate for CMAQ, and were converted to a form usable by CMAQ 

using a Fortran convertor called ‘inline2camx’. In addition to generating the gridded surface 

level 2-dimensional emissions and elevated point source files necessary for CAMx, the program 

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, up until the final merge program 

(Mrggrid), which combines 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 (i.e., latitude and 

longitude) location 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. 

For the 2005v4 and v4.1 platforms, we did not have SMOKE compute vertical plume rise; this 

was done in the air quality model using stack data found in the SMOKE output files for each 

model-ready sector. The one sector with “in-line” only, seca_c3, was processed so that the entire 

emissions would be in aloft layers. Thus, there were no seca_c3 emissions in the 2-dimensional, 

layer-1 files created by SMOKE. Rather, the speciated and hourly source-based CMAQ and 

CAMX inputs for seca_c3 were used for the vertical allocation. 
46 

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 

othpt_hg point Yes annual in-line

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 2005v4.1 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 2005v4.1 platform, we ran SMOKE and CMAQ or CAMx (depending on the 

application) for modeling domains with 36-km and 12-km spatial resolution. These are the same 

domains as were used for the 2005v4 and 2002 platform. Figure 3-1 shows the 36-km 

CONtinental United States “CONUS” modeling domain, the 12-km eastern domain (EUS), and 

the 12-km western domain (WUS). 
47 

Figure 3-1. CMAQ 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
48 

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, see the 

CAMx 5.2 user’s guide available from http://www.camx.com. The specific version of CMAQ 

used included secondary organic aerosol (SOA) and HONO enhancements as described in 

http://www.cmascenter.org/help/model_docs/cmaq/4.7/RELEASE_NOTES.txt. This is 

unchanged from the CMAQ applications of the v4 platform. 

From the perspective of emissions preparation, the CMAQ 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; the 

only three input species that were not in the CAP 2002-Based platform described in 2002 “CAPonly” platform (http://www.epa.gov/scram001/reports/Emissions%20TSD%20Vol1_02-28-

08.pdf) 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 in CMAQ4.7. 
49 

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

Inventory Pollutant Model Species Model species description 

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 

The approach for speciating PM2.5 emissions in v4.1 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 v4.1, 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 
50 

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 v4.1 

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 

v4.1 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. 

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 2005v4.1 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 
51 

“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 v4.1 emissions or v4 emissions, but 

the user will now have the ability for easier inclusion of specific sources to get the same result. 
52 

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
53 

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 v4.1 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. 
54 

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 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 NESHAP (nor 

were A,F). 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. 

M 2460200000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer and Commercial;All Household Products

profile is 3146 contains only nonzero 

methanol.
55 

minimum 

HAP(s) 

needed SCC Tier 3 SCC Tier 3 Description Comments 

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% 
56 

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. 

3.1.2.2 Creation of model-ready mercury species 

As part of 2005 platform, we created model-ready mercury species by speciating any of the 

mercury in the NEI that was not provided as divalent gaseous, elemental or divalent particulate 

mercury. The same speciation approach was used in the CAP and HAP 2002v3 platform. 

For the EGU sector (ptipm), all emissions except for 0.87 tons of the 52.9 tons of total 2005 Hg 

was provided in the inventory as speciated emissions. 

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 v4.1 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 v4.1 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. 
57 

Table 3-6. Temporal settings used for the platform sectors in SMOKE, v4.1 platform

Platform sector 

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

othpt_hg 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) 

• 12 km (West): 3 days (Dec 29 - Dec 31) 
58 

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 

(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 2005v4.1 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 2005v4.1 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 v4.1 platform, we updated the 2005v4 ancillary files in two 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 3-15). 

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, an 

Eastern 12-km domain, and a Western 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 

new 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 2005v4CAP-BAFM (for Canada) platform websites (see the end of Section 1). The 

oil and natural gas surrogate files are posted at the 2005v4.1 website. The following list of seven 

files provides descriptions of each of their contents and intended uses for the v4.1 platform. 

• 36km_surg_2002v3mpCAP_smokeformat.zip: U.S. and Mexican surrogate files for 

36-km spatial resolution (Canadian data contained in this zip file was not used for the 

2005-based platform except for the year 2000 mercury data which is contained in the 

sector othpt) 

• 12km_surg_2002v3mpCAP_smokeformat.zip: U.S. and Mexican surrogate files for 

surrogate files for 12 km spatial resolution (Canadian data contained in this zip file was 

not used for the 2005-based platform except for the year 2000 mercury data which is 

contained in the sector othar) 

• new36km_surg_2005v4_smokeformat.zip: Canadian surrogate files for 36-km spatial 

resolution for Canadian surrogates 
59 

• new12km_surg_2005v4_smokeformat.zip: Canadian surrogate files for 12-km spatial 

resolution for Canadian surrogates 

• oil_and_gas36km_surg_2005v4.1_smokeformat.zip: Oil and gas surrogate files for 

36-km spatial resolution for oil and gas surrogate (US) 

• oil_and_gas12km_surg_2005v4.1_smokeformat.zip: Oil and gas surrogate files for 

12-km spatial resolution for oil and gas surrogate (US) 

• ancillary_2005v4.1_smokeformat.zip: spatial related data included are the grid 

description (GRIDDESC), surrogate description (SRGDESC), surrogate cross reference 

file (AGREF), and area-to-point (ARTOPNT) file 

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 

v4.1 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 2005v4.1 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 
60 

Code Surrogate Description Code Surrogate Description 

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 

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 v4.1 platform; 

that is, some surrogates in Table 3-7 were not assigned to any SCCs. Appendix B provides the 

U.S. emissions assigned by the available surrogates for the CONUS domain region. 

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-
61 

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

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 v4.1 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 with the exception of the nonpoint Canadian mercury 

emissions. The updated set completely replaced the 2002v3 platform surrogates for allocating 
62 

the 2006 province-level Canadian emissions. The 2002v3 platform surrogates for Canada were 

used for the mercury data in the sector other_hg because Canada did not provide updated 

mercury data with its 2006 inventory. 

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 

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 (v4.1 

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 CA_924_NOFILL.txt downstream petroleum CA_975_FILL.txt 
63 

Surrogate 

description 

Filename of 2005 

Platform Surrogate 

Surrogate 

description 

Filename of 2005 

Platform Surrogate 

UTILITIES and 

DWELLING 

industries 

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 

mining1 CA_985_NOFILL.txt 

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 v4.1 platform as 

were used in the 2005v4 and 2002 platforms. 

3.2.2 Chemical speciation ancillary files 

The following data file, provided at the 2005v4 website (see the end of Section 1), contains the 

SMOKE inputs used for chemical speciation of the inventory species to the CMAQ model 

species. SMOKE environmental variable names, used in the file names, are shown using capital 

letters in parentheses: 

• ancillary_2005v4.1_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). 

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 2005v4.1 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 
64 

“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). 

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 EPA's repository of TOG 

and PM speciation profiles of air pollution sources. However, a few of the profiles we used in 

the v4.1 platform will be published in SPECIATE4.3 after the release of this documentation. 

The SPECIATE database development and maintenance is a collaboration involving EPA’s 

ORD, OTAQ, and EPA’s Office of Air Quality Planning and Standards (OAQPS), and 

Environment Canada (EPA, 2006c). 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, 
65 

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 

As discussed earlier, for the v4.1 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 v4.1 

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: 
66 

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

Pollutant Species 

Split factors subbituminous 92084 Split 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 v4.1 platform. 

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

SCC 

New 

Profile 

Code Pollutant Profile Name 

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 v4.1 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 v4.1 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 3-15 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 
67 

profile, 8762 is a new profile for the v4.1 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 

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 CMAQ 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 v4.1 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. 
68 

The following data file, provided at the 2005v4 website (see the end of Section 1) contains the 

SMOKE inputs used for chemical speciation of the inventory species to the air quality model 

species. SMOKE environmental variable names, used in the file names, are shown in capital 

letters in parentheses: 

• ancillary_2005v4.1_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) 

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. 

Onroad Parking Area Profiles

The SCCs and descriptions, along with the assignments chosen are shown in Table 3-14 

(gasoline vehicles) and Table 3-15 (diesel vehicles). Figure 3-3 and Figure 3-4 show the diurnal 

profiles referred to in the tables. 
69 

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
70 

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

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 

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 

vehicles on the other roadway ti.e.: EVP__VOC: COMBO of 875Evaporative emission - Reform(Gasoline Vehicle - Evaporativgasoline) Note that these are thIn some cases future year profil(Gasoline Vehicle - EvaporativEXH__VOC: COMBO of 875are used in 2005. In some casealso include combinations of 87

exhaust, E0), 8757 (tier 2 exhauEXH__PM2.5 not needed becaspeciated emissions BRK_PM2.5 and TIR_PM2.5 u(92009 and 92087, respectively

2201001370 Light Duty Gas Vehicles- parking areas urban 2201020370 Light Duty Gas Trucks 1&2- parking areas urban2201040370 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 
71 

GASOLINE VEHICLE TYPES 

SCC&Description Surrogate 

Temporal 

Profile: 

Monthly 

Variation 

Temporal Profile: 

Day of Week Variation 

Temporal Profile: 

Diurnal variation Speciation 

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 
72 

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

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 

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 saDIESEi.e.: EVP_

requir- CircEXH_TruckPM2.5 

suppli

requirSimplBRK_roadw

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 
73 

DIESEL VEHICLE TYPES 

SCC&Description Surrogate 

Temporal 

Profile: 

Monthly 

Variation 

Temporal Profile: 

Day of Week Variation 

Temporal Profile: 

Diurnal variation 

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 saDIESEi.e.: EVP_

requir- CircEXH_TruckPM2.5

suppli

requirSimplBRK_roadw

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 
74 

DIESEL VEHICLE TYPES 

SCC&Description Surrogate 

Temporal 

Profile: 

Monthly 

Variation 

Temporal Profile: 

Day of Week Variation 

Temporal Profile: 

Diurnal variation 

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 

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 
75 

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