Technical Support Document: 

Preparation of Emissions Inventories 

for the Version 4, 2005-based Platform 

July 7, 2010 

U.S. Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Air Quality Assessment Division 

Contacts: 

Rich Mason, Madeleine Strum, 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..............................................................................2

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

2.1.1 IPM sector (ptipm)...............................................................................................................................12

2.1.2 Non-IPM sector (ptnonipm).................................................................................................................14

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

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

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

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

2.3 FIRES (PTFIRE AND AVEFIRE).....................................................................................................................22

2.3.1 Day-specific point source fires (ptfire) ................................................................................................22

2.3.2 Average fires (avefire) .........................................................................................................................26

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).................................................................................................................................................................29

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

(on_moves_startpm)...........................................................................................................................................31

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) ....42

2.7 SMOKE-READY NON-ANTHROPOGENIC INVENTORIES FOR MERCURY AND CHLORINE ..............................44

2.7.1 Mercury ...............................................................................................................................................44

2.7.2 Chlorine ...............................................................................................................................................45

3 EMISSIONS MODELING SUMMARY........................................................................................................45

3.1 KEY EMISSIONS MODELING SETTINGS........................................................................................................46

3.1.1 Spatial configuration ...........................................................................................................................47

3.1.2 Chemical speciation configuration ......................................................................................................49

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

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

3.2.1 Spatial allocation ancillary files..........................................................................................................58

3.2.2 Chemical speciation ancillary files......................................................................................................62

3.2.3 Temporal allocation ancillary files......................................................................................................66

4 DEVELOPMENT OF FUTURE YEAR EMISSION INVENTORIES.......................................................69

5 REFERENCES.................................................................................................................................................70
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 

IMO International Marine Organization 

IPM Integrated Planning Model 

ITN Itinerant 

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 

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

PM10 Particulate matter less than or equal to 10 microns
iv

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 

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 ........................... 3 

Table 2-2. Summary of significant changes between 2002 and 2005 Platforms by sector ........... 6 

Table 2-3. Summaries by sector of 2002 and 2005 Platform base year CAPs-only emissions for 

the continental United States (48 states + District of Columbia)............................................ 9 

Table 2-4. Summaries by sector for the other (“oth” –Canada, Mexico, and offshore- 2002 and 

2005 Platform base year CAPs-only emissions within the 36km domain............................ 10 

Table 2-5. SCCs in the afdust platform sector............................................................................. 16 

Table 2-6. Livestock SCCs extracted from the 2002 NEI to create the ag sector ....................... 17 

Table 2-7. Fertilizer SCCs extracted from the 2002 NEI for inclusion in the “ag” sector .......... 19 

Table 2-8. Oil and gas production nonpoint emissions in WRAP states in 2002 and 2005 

platforms. Emissions provided in short tons/year................................................................. 20 

Table 2-9. New SCCs from the Phase II WRAP Oil and Gas Inventory..................................... 20 

Table 2-10. RWC Emissions Changes for CAPs between 2002 and 2005 platforms. Emissions 

values provided in short tons/year. ....................................................................................... 21 

Table 2-11. 2005 NEI SCCs representing emissions in the ptfire and avefire modeling sectors 22 

Table 2-12. SCCs in the ptfire sector........................................................................................... 23 

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

short tons/year....................................................................................................................... 27 

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

Table 2-15. Pollutants covered by the draft MOVES model in the 2005 Platform1

.................... 29 

Table 2-16. SCCs in the 2005 alm_no_c3 inventory compared to the 2002 platform alm sector36 

Table 2-17. Regional growth factors used to project 2002 C3 emissions to 2005 ....................... 40

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

Table 2-19. HAP emission ratios for generation of HAP emissions from criteria emissions for 

C3 commercial marine vessels.............................................................................................. 41 

Table 2-20. Summary of the othpt, othpt_hg, othar, othar_hg, and othon sectors in the 2005 

Platform................................................................................................................................. 43 

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

Table 3-2. Descriptions of the 2005-based Platform Grids ......................................................... 48 

Table 3-3. Model Species produced by SMOKE for CB05 with SOA for CMAQ4.7................ 50 

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................................... 57 

Table 3-7. U.S. Surrogates Available for the 2002 and 2005 Platforms ..................................... 59 

Table 3-8. Surrogate assignments to new mobile categories in the 2005 Platform..................... 60

Table 3-9. Canadian Spatial Surrogates for 2005-based platform Canadian Emissions .............. 61 

Table 3-10. Differences between two profiles used for coal combustion.................................... 64 

Table 3-11. Summary of VOC speciation profile approach by sector for 2005.......................... 65

Table 3-12. Temporal Profiles Assigned to New Onroad SCC from the Draft MOVES model: 

Parking Areas........................................................................................................................ 68 
vi

List of Figures 

Figure 2-1. SMARTFIRE System ............................................................................................... 24 

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

Figure 3-1. CMAQ modeling domains ......................................................................................... 48 

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

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

road is urban versus rural...................................................................................................... 69 

List of Appendices 

Appendix A. Methodology to Revise VOC from Residential Wood Combustion 

Appendix B. Methodology to Speciate Partially-Speciated MOVES PM2.5 Emissions
1

1 Introduction 

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

2005-based air quality modeling platform. This document describes the emissions inventory and 

emissions modeling for a version of the platform consisting of Criteria Air Pollutants (CAPs) and 

the following select Hazardous Air Pollutants (HAPs: mercury (Hg), chlorine (Cl), hydrochloric 

acid (HCl) and benzene, acetaldehyde, formaldehyde and methanol. The latter four are also 

denoted BAFM. This platform is called the “CAP-BAFM 2005-Based Platform, Version 4” 

platform, since it is primarily a CAP platform, with BAFM and Hg included. The reason it is 

“Version 4” is that it has been updated from the 2002-based platform, version 3. It is based on 

the 2005 National Emission Inventory (NEI), version 2 

(http://www.epa.gov/ttn/chief/net/2005inventory.html). From this point on, we refer to it simply 

as the “2005 Platform.” This document describes the approach and data used to produce the 

emission inputs to the air quality models used in the 2005 Platform. A version of the 2005-based 

platform that contains additional HAPs is documented as part of the Revised Annual Renewable 

Fuel Standard (RFS2) rule (EPA, 2010). 

Emissions preparation for the 2005 Platform supports two air quality models: (1) 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) and particulate matter (PM) and require hourly and gridded 

emissions of chemical species from the following inventory pollutants: carbon monoxide (CO), 

nitrogen oxides (NOX), volatile organic compounds (VOC), sulfur dioxide (SO2), ammonia 

(NH3), particulate matter less than or equal to 10 microns (PM10), and individual component 

species for particulate matter less than or equal to 2.5 microns (PM2.5). In addition, the CMAQ 

CB05 with chlorine chemistry, which is part of the “base” version of CMAQ, allows explicit 

treatment of BAFM and includes anthropogenic HAP emissions of HCl and Cl. Readers may 

note that the base version of CMAQ targeted by the 2005 Platform described here does not 

support Hg, but that this modeling platform does include Hg for 2005. 

The effort to create the emission inputs for the 2005 Platform included 

(1) development of emission inventories for a 2005 model evaluation case, 

(2) development of emission inventories for a 2005 base case and projected years consistent 

with that base, 

(3) updates to the emissions modeling tools, 

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

(5) application of the tools. 

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

Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system. We used this tool to 

create emissions files for a 36-km national grid, a 12-km Eastern grid and a 12-km Western grid 

for the following cases: 

• 2005 evaluation (also known as the “2005ak” case): The purpose of this case is to 

compare the air quality model results to ambient air observations to assess the ability of 

the air quality model to estimate ambient air concentrations of ozone and PM2.5 levels. 
2

For regulatory applications, this case is not included in the relative response factor (RRF) 

calculations. 

• 2005 base case (also known as the “2005ck” case): 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 RRF calculations. 

A final version of this documentation will also contain sections on the development of the 2020 

(2020ck) base case. 

Other 2005 and future-year base case emissions have been developed but are associated with 

specific regulatory actions and are therefore documented as part of those rules (e.g., RFS2, Light 

Duty Greenhouse Gas Rule). 

There are two differences between the 2005 evaluation and the 2005 base case. The evaluation 

case uses 2005-specific fire emissions and 2005 hour-specific continuous emission monitoring 

(CEM) data for electric generating units (EGUs). The 2005 base case includes an “average year” 

scenario for fires, described in Section 2.3.2. For EGUs, the base case allocates the 2005 

emissions to days and hours using a different approach; this method is also used when creating 

the future-year emissions. 

The version 4 2005-based Platform builds upon the concepts, tools and emissions modeling data 

from EPA’s version 3 2002-based Platform, documented by: 

http://www.epa.gov/scram001/reports/Emissions%20TSD%20Vol1_02-28-08.pdf

A summary of the key differences between the 2005 Platform and the 2002 Platform are 

provided in Table 2-1. 

This document contains five sections and two 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. Section 4, to be added in a future version of this document, 

describes the development of the 2020 inventory (projected from 2005). Section 5 provides 

references. Appendices A and B 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-BAFM 2005-Based 

Platform”. This is referred to as the “2005v4 website” throughout this document. 

2 2005 emission inventories and approaches 

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

for the 2005 emission inputs for the version 4 Platform 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 2005 platform utilizes select HAPs: the base version 

includes chlorine, HCl, Hg, benzene, acetaldehyde, formaldehyde, and methanol. The RFS2 
3

version of the platform (EPA, 2010) utilized the following additional HAPs: acrolein, 1,3-

butadiene, naphthalene, toluene and xylenes (m,o,p and mixed). 

Documentation for the 2005 NEI can be found at: 

http://www.epa.gov/ttn/chief/net/2005inventory.html#documentation. Version 2 of the 2005 

NEI was used for the 2005 Platform. 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. The fires portion of the 

inventory includes emissions from wildfires and prescribed burning computed as hour-specific 

point sources. For purposes of preparing the CMAQ-ready emissions, we split the 2005 

emissions inventory into several additional “platform” sectors for use in emissions modeling, and 

we added biogenic emissions, emissions from the Canadian and Mexican inventories, and 

augmented with other emissions data to be explained below. 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 temporalized emissions together to create the CMAQ 

or CAMx emission inputs. 

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. We did not use all sectors for all modeling 

cases; in particular, we used the ptfire platform sector only for the 2005 model performance 

evaluation. We used the avefire platform sector for all modeling cases except for the model 

performance evaluation. The rationale for using average fires in the 2005 base case and futureyear cases rather than the 2005 year-specific fires (ptfire) is described in Section 2.3.2. Updates 

from the 2002 platform are discussed in Table 2-2. 

Table 2-1. Platform sectors used in emissions modeling for the 2005 Platform

Platform Sector 2005 NEI 

Sector 

Description and resolution of the data input to SMOKE 

IPM sector: ptipm Point 2005v2 NEI point source EGUs mapped to the Integrated Planning 

Model (IPM) model using the National Electric Energy Database 

System (NEEDS, 2006 version 3.02) database. Hourly files for 

continuous emission monitoring (CEM) sources are included only for 

the 2005 evaluation case. Day-specific emissions for non-CEM 

sources created for input into SMOKE. 

Non-IPM sector: 

ptnonipm

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

annual resolution. Includes all aircraft emissions. 

Point source fire 

sector: ptfire 

Fires Point source day-specific wildfires and prescribed fires for 2005. This 

sector used only for the 2005 evaluation case. 

Average-fire 

sector: avefire 

N/A Average-year wildfire and prescribed fire emissions derived from the 

2002 Platform avefire sector, county and annual resolution. Used for 

the 2005 base year and the future base model runs, but not for the 

model evaluation case. 
4

Platform Sector 2005 NEI 

Sector 

Description and resolution of the data input to SMOKE 

Agricultural 

sector: ag

Nonpoint NH3 emissions from NEI nonpoint livestock and fertilizer application, 

county and annual resolution.

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. 

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 and year 2005 nonCalifornia Western Regional Air Partnership (WRAP) oil and gas 

“Phase II” inventory. 

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. 

locomotive, and 

non-C3 

commercial 

marine: 

alm_no_c3

Mobile: 

Nonroad 

Year 2002 non-rail maintenance locomotives, and category 1 and 

category 2 commercial marine vessel (CMV) emissions sources, 

county and annual resolution. Unlike prior platforms, aircraft 

emissions are now included in the ptnonipm sector and category 3 

CMV emissions are now 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 EPA rule called “Control of Emissions 

from New Marine Compression-Ignition Engines at or Above 30 

Liters per Cylinder”, usually described as the Emission Control Area 

(ECA) study, originally called SO2 (“S”) ECA. 

Onroad 

California, 

NMIM-based, and 

MOVES sources 

not subject to 

temperature 

adjustments: 

on_noadj

Mobile: 

onroad 

Three, monthly, county-level components: 

1) Onroad emissions from NMIM using MOBILE6.2, other than 

for California. 

2) California onroad, created using annual emissions submitted 

by CARB for the 2005v2 NEI. 

3) Onroad gasoline non-motorcycle vehicle emissions from draft 

MOVES not subject to temperature adjustments: exhaust CO, 

NOX, VOC, some VOC HAPs, and evaporative VOC and 

some VOC Hazardous Air Pollutants (HAPs). 

Onroad cold-start 

gasoline exhaust 

mode vehicle from 

MOVES subject 

to temperature 

adjustments: 

on_moves_startpm

Mobile: 

onroad 

Monthly, county-level draft MOVES-based onroad non-motorcycle 

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 MOVES-based onroad non-motorcycle 

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). 
5

Platform Sector 2005 NEI 

Sector 

Description and resolution of the data input to SMOKE 

Biogenic: biog N/A Hour-specific, grid cell-specific emissions generated from the 

BEIS3.14 model -includes emissions in Canada and Mexico. 

Other point 

sources not from 

the NEI: othpt

N/A 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

N/A Annual year 2000 Canada speciated mercury point source emissions. 

Other nonpoint 

and nonroad not 

from the NEI: 

othar

N/A Annual year 2006 Canada (province resolution) and year 1999 Mexico 

Phase III (municipio resolution) nonpoint and nonroad mobile 

inventories, annual resolution. 

Other nonpoint 

sources not from 

the NEI, Hg only: 

othar_hg

N/A Annual year 2000 Canada speciated mercury from nonpoint sources. 

Other onroad 

sources not from 

the NEI: othon

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

III (municipio resolution) onroad mobile inventories, annual 

resolution. 

The emission inventories for input to SMOKE for the 2005 base and evaluation case are 

available at the 2005v4 website (see the end of Section 1) under the link “Data Files” (see 

“2005emis”directory). The “readme” file provided indicates the particular zipped files 

associated with each platform sector. 

Before discussing the specific components of the 2005 emissions platform, we provide a 

summary of the significant differences between the 2002 V3 emissions platform and this 2005 

platform. Table 2-2 shows the emissions inventory updates from 2002 V3 to this 2005 platform. 

New sectors appear in the 2005 platform and some sources migrate to different sectors. Table 

2-2 does not discuss the modifications to these inventories for emissions modeling; these details 

are provided in the sections that follow. 
6

Table 2-2. Summary of significant changes between 2002 and 2005 Platforms by sector

Platform Sector Summary of Significant Inventory Differences in 2005 Platform 

IPM sector: ptipm − Updated from 2002 NEI version 3 to 2005 NEI version 2 point inventory. 

− Updated hourly CEM data from 2002 to 2005. 

− Updated day-specific CEM and non-CEM data using temporal information based 

on years 2004 through 2006, rather than 2001 through 2003. 

− Updated NEEDS database to NEEDS 2006, version 3.02.

− EGUs from 2002 platform assigned to ptnonipm sector have been reassigned to 

the ptipm sector. 

Non-IPM sector: 

ptnonipm

− Updated from 2002 NEI version 3 to 2005 NEI version 2 point inventory. 

− Now includes all aircraft emissions (no longer in alm_no_c3 sector). 

− EGUs from 2002 platform assigned to ptnonipm sector have been reassigned to 

the ptipm sector. 

Point source fire 

sector: ptfire 

− Updated to include all wildfire and prescribed burning emissions for 2005. The 

2002 platform contained some county-level monthly prescribed burning 

emissions that were included in the nonptfire sector. In contrast, all 2005 fires 

data used for modeling are resolved as point sources at day-specific temporal 

resolution. Therefore, there is no nonptfire sector in the 2005 platform. 

− This sector uses BAFM emissions from the inventory for BAFM model species 

as part of VOC speciation (as opposed to getting BAFM model species from 

solely speciating VOC as was done in the 2002 CAP-only platform) 

Average-fire 

sector: avefire 

Same as 2002 Platform with the following exceptions: 

1) VOC revised higher, now as a factor of CO; 

2) Avefire inventory data contains HAPs, computed as factor from PM2.5; 

however, these data were not used during processing of the emissions (they 

are provided in the inventory files) 

Agricultural 

sector: ag

Unchanged from 2002 Platform. 

Area fugitive dust 

sector: afdust

Transport fraction for PM2.5, inadvertently not applied in the original 2002 

platform, is correctly applied in 2005 platform. 

Remaining 

nonpoint sector: 

nonpt

Similar to the 2002 Platform except for the following: 

1) Replaced non-California WRAP oil and gas emissions with WRAP Phase 

II oil and gas emissions; 

2) Residential Wood Combustion (RWC) emissions updated for PM and 

VOC for Oregon and New York, VOC emissions factor corrected for all 

states except California, and, VOC HAPs computed; 

3) HCl corrections made to GA, UT, and VA for Industrial and 

Commercial/Institutional coal-fueled boilers; 

4) Use BAFM emissions from the inventory as part of VOC speciation for 

some sources in this sector.1

Nonroad sector: 

nonroad

2002 platform emissions replaced with 2005 NEI version 2 emissions. 

1) California 2002v3 emissions replaced with CARB-submitted 2005v2 

emissions with NH3 and some HAPs computed separately. 

2) The remaining states emissions simply replaced with 2005v2 NMIM. 

Use BAFM as part of VOC speciation for the nearly the entire sector1

 (only LPG 

and CNG fueled sources did not have BAFM emissions; these were the only 

sources for which we did not use BAFM.) 
7

Platform Sector Summary of Significant Inventory Differences in 2005 Platform 

locomotive, and 

non-C3 

commercial 

marine: 

alm_no_c3

Locomotives, and Category 1 and Category 2 CMV emissions are the same as 

2002 Platform alm sector. 2005 Platform does not include these emissions in this 

sector: 

1) aircraft –these are in the 2005 ptnonipm sector; 

2) Category 3 CMV –these are replaced by 2005 seca_c3 sector inventory; 

3) Tribal data removed due to lack of spatial surrogates. 

Use BAFM emissions from the inventory as part of VOC speciation for some 

sources in this sector.1

C3 commercial 

marine: seca_c3 

New sector for 2005 Platform. These point source C3 CMV emissions replace a 

subset of the 2002 Platform alm sector emissions, specifically, port and underway 

residual fuel C3 county-level emissions. 

Use BAFM emissions from the inventory as part of VOC speciation for all sources 

in this sector.1

Onroad 

California, 

NMIM-based, and 

MOVES sources 

not subject to 

temperature 

adjustments: 

on_noadj

2002 platform emissions replaced with updated 2005 emissions as follows: 

1) California –2005 CAP and HAP emissions. Supplied by CARB, gap-filled 

with NMIM NH3 and allocated to road types using NMIM –based ratios. 

2) Draft MOVES (except for California) onroad gasoline emissions for 

exhaust and evaporative mode for all vehicle types except motorcycles for 

the pollutants NOX, VOC, CO, benzene, acetaldehyde, formaldehyde, 1,3-

butadiene, acrolein, and naphthalene. 

3) All other emissions not covered by (1) and (2) above used the 2005 NEI 

version 2 emissions, except for PM10 and PM2.5 emissions included in the 

on_moves_startpm and on_moves_runpm sectors, as described below. 

Use BAFM emissions from the inventory as part of VOC speciation for all sources 

in this sector.1

Onroad cold-start 

gasoline exhaust 

mode vehicle from 

MOVES subject 

to temperature 

adjustments: 

on_moves_startpm

For the 2005 platform, this new sector includes the draft MOVES onroad gasoline, 

non-motorcycle PM and naphthalene cold start mode emissions subject to grid cell 

and hourly temperature adjustments. Temperature adjustments for cold starts 

(here) are different than running mode emissions, hence the need to separate these 

emissions into these new sectors, on_moves_startpm and on_moves_runpm. 

Onroad running 

gasoline exhaust 

mode vehicle from 

MOVES subject 

to temperature 

adjustments: 

on_moves_runpm

For the 2005 platform, this new sector includes the draft MOVES onroad gasoline, 

non-motorcycle PM and naphthalene running mode emissions subject to grid cell 

and hourly temperature adjustments. Temperature adjustments for running mode 

(here) are different than cold start mode emissions, hence the need to separate these 

emissions into these new sectors, on_moves_startpm and on_moves_runpm. 

Biogenic: biog Updated from BEIS3.13 in the 2002 platform to BEIS3.14 in the 2005 platform. 

Underlying land use data was not updated. Domains in both 2002 and 2005 

platforms are the same: U.S., Canada, and Mexico. 

Other point 

sources not from 

the NEI: othpt

New offshore oil emissions from 2005 NEI version 2 point inventory. 

Canadian emissions updated from year 2000 to 2006, and using point-specific 

speciated emissions and facility-specific temporal allocation. 

Other point 

sources not from 

the NEI, Hg only: 

othpt_hg

This sector was not in the “CAP-only” version of the 2002 Platform, but it was in 

the multi-pollutant version. It contains the same data as in the 2002 multi-pollutant 

platform: year 2000 Canadian point source mercury emissions. 
8

Platform Sector Summary of Significant Inventory Differences in 2005 Platform 

Other nonpoint 

and nonroad not 

from the NEI: 

othar

Canadian emissions updated from year 2000 to 2006. 

Other nonpoint 

sources not from 

the NEI, Hg only: 

othar_hg

New sector in the 2005 platform, contains year 2000 Canadian point source 

mercury emissions. 

Other onroad 

sources not from 

the NEI: othon

Canadian emissions updated from year 2000 to 2006. 

1 Section 3.1.2.1 details the use of BAFM emissions from the inventory as part of VOC speciation; this is 

one of the changes between the 2005 Platform and the 2002 Platform for several sectors.

Annual emission summaries for 2005, with comparisons to 2002 CAPs emissions by emissions 

modeling sector are provided in Table 2-3. VOC totals are before BAFM speciation; they are 

inventory VOC emissions, and not the sum of VOC emissions after BAFM speciation. Table 2-4 

provides a summary of emission changes for CAPs only for Canada and off shore oil between 

the 2002 and 2005 platforms. The Mexico emissions are unchanged from 2002 platform. 

The emission inventories for input to SMOKE for the 2005 base and evaluation 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 provided indicates the particular zipped 

files associated with each platform sector. 
9

Table 2-3. Summaries by sector of 2002 and 2005 Platform base year CAPs-only emissions for 

the continental United States (48 states + District of Columbia) 

Year Sector 

[tons/yr]

VOC 

[tons/yr] 

NOX

[tons/yr] 

CO 

[tons/yr] 

SO2

[tons/yr]

NH3

[tons/yr]

PM10

[tons/yr]

PM2.5

afdust 8,858,989 1,830,273

ag 3,251,990 

alm1,2 123,458 2,258,985 806,170 312,180 904 96,981 86,719

nonpt 7,929,917 1,531,603 7,526,721 1,250,266 135,542 1,377,055 1,100,884

nonroad 2,873,623 2,176,159 21,386,058 187,284 1,859 227,875 216,658

onroad3 4,847,990 7,786,709 59,810,864 242,379 290,708 200,686 146,003

ptipm 42,378 4,618,946 605,147 10,359,117 29,991 608,708 501,999

ptnonipm 1,425,158 2,368,988 3,195,465 2,249,548 154,180 600,355 372,330

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

2002 

ptfire+nonptfire4 1,825,284 82,613 8,039,286 67,229 123,414 742,980 629,635

2002 non-fires Total 17,242,523 20,741,388 93,330,425 14,600,775 3,865,173 11,970,649 4,254,865

afdust 8,858,992 1,030,391

ag 3,251,990 

alm_no_c31,2 67,690 1,924,925 270,007 154,016 773 59,366 56,687

seca_c31,2,5 22,336 641,228 53,677 416,793 53,519 49,237

nonpt 7,474,512 1,683,490 7,376,314 1,252,645 134,080 1,349,685 1,076,954

nonroad 3,480,959 2,115,408 19,502,718 197,341 1,972 209,100 198,734

on_noadj3 3,123,642 7,203,876 41,647,066 144,216 295,203 170,554 115,991

on_moves_runpm3 46,430 42,753

on_moves_startpm3 23,607 21,738

ptipm 40,950 3,728,190 601,564 10,381,411 21,684 615,095 508,903

ptnonipm2 1,310,085 2,247,228 3,222,221 2,117,649 159,003 653,957 442,656

avefire 451,127 189,428 8,554,551 49,094 36,777 796,229 684,035

2005 

ptfire 2,962,421 193,371 12,529,792 101,012 206,081 1,294,651 1,097,162

2005 non-fires Total 15,520,175 19,544,345 72,673,566 14,664,071 3,864,706 12,040,304 3,544,046

afdust 0% -44%

ag 0% 

alm1,2 -27% 14% -60% 83% -14% 16% 22%

nonpt -6% 10% -2% 0% -1% -2% -2%

nonroad 21% -3% -9% 5% 6% -8% -8%

onroad3

-36% -7% -30% -40% 2% 20% 24%

ptipm -3% -19% -1% 0% -28% 1% 1%

ptnonipm2

-8% -5% 1% -6% 3% 9% 19%

avefire -77% 0% 0% 0% 0% 0% 0%

% 

Difference 

(2005 - 

2002) 

/2002 

Emissions 

ptfire 62% 134% 56% 50% 67% 74% 74%

% Difference non-fires 

Total -10% -6% -22% 0% 0% 1% -17%

1 –alm sector in % Difference calculation consists of alm from 2002 platform and aggregated alm_no_c3 and 

seca_c3 from the 2005 platform. 

2- Note: aircraft in 2005 platform is contained in the ptnonipm sector. 

3 –onroad sector in % Difference calculation consists of onroad from 2002 platform and aggregates on_noadj, 

on_moves_runpm, and on_moves_startpm from the 2005 platform. 

4 – nonptfire emissions are in the 2002 platform only; these are covered by the ptfire sector in the 2005 platform. 

5 – only U.S. state/county seca_c3 emissions are included here; emissions outside the (up to) 200nm offshore 

boundary and international boundaries, while included in our modeling, are not included in these summaries. 
10

Table 2-4. Summaries by sector for the other (“oth” –Canada, Mexico, and offshore- 2002 and 

2005 Platform base year CAPs-only emissions within the 36km domain. 

Year Sector [tons/yr]

VOC 

[tons/yr]

NOX

[tons/yr]

CO 

[tons/yr]

SO2

[tons/yr]

NH3

[tons/yr]

PM10

[tons/yr]

PM2.5

Canada othar 1,878,996 1,060,097 4,282,782 227,942 569,738 1,462,643 400,493

Canada othon 410,981 874,564 5,810,763 26,376 18,332 19,692 18,071

Canada othpt 308,286 654,803 1,155,470 2,115,572 23,866 241,081 129,342

Canada Subtotal 2,598,262 2,589,464 11,249,016 2,369,890 611,937 1,723,417 547,906

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

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

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

Mexico Subtotal 883,314 654,974 2,188,811 1,089,676 489,031 276,156 187,366

2002 

Off-shore othpt 70,329 26,628 6,205 0 0 0 0

2002 Total 3,551,905 3,271,066 13,444,032 3,459,566 1,100,967 1,999,573 735,271

Canada othar1 1,281,095 734,587 3,789,362 95,086 546,034 1,666,188 432,402

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

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

Canada Subtotal 1,999,279 2,117,402 9,463,544 1,764,434 588,614 1,798,523 511,486

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

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

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

Mexico Subtotal 883,314 654,974 2,188,811 1,089,676 489,031 276,156 187,366

2005 

Off-shore othpt 51,240 82,581 89,812 1,961 0 839 837

2005 Total 2,933,833 2,854,957 11,742,168 2,856,070 1,077,645 2,075,518 699,688

Canada othar1 -32% -31% -12% -58% -4% 14% 8%

Canada othon -34% -40% -24% -80% 16% -26% -42%

Canada othpt 45% 31% 10% -21% -11% -51% -47%

Canada Subtotal -23% -18% -16% -26% -4% 4% -7%

Mexico othar 0% 0% 0% 0% 0% 0% 0%

Mexico othon 0% 0% 0% 0% 0% 0% 0%

Mexico othpt 0% 0% 0% 0% 0% 0%

Mexico Subtotal 0% 0% 0% 0% 0% 0% 0%

Percent 

Difference 

(2005 – 

2002)/2002 

emissions 

Off-shore othpt -27% 210% 1348% 

% Difference Total -17% -13% -13% -17% -2% 4% -5%

1- Canada provided year 2006 fires but we did not include them in our 2005 platform. 

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 these 2005 platform emissions changed 

appreciably since the previously-documented 2002 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 contiguous 
11

U.S. NEI point sources. The offshore oil platform (othpt sector) and category 3 CMV emissions 

(seca_c3 sector) are point source formatted inventories, but they are discussed later in Section 2. 

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

remaining 2005 point source NEI, v2 for input into SMOKE: the Integrated Planning Model 

(IPM) sector (ptipm) and the non-IPM sector (ptnonipm). This split facilitates the use of 

different SMOKE temporal processing and future year projection techniques for 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, Hg and Cl. We did not 

utilize BAFM from these sectors as we chose to speciate VOC without any integration of VOC 

HAP (integration is discussed in detail in Section 3.1.2.1). 

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

used in 2005 were different for the model evaluation case and for the base case. For the model 

evaluation case, those ptipm sector sources with CEM data (that we could match to the NEI) 

used hourly SO2 and NOX emissions and annual emissions of all other pollutants. The hourly 

data also contained heat input, which was used to allocate the annual emissions to hourly values. 

For the non-CEM sources, we created daily emissions using an approach described in Section 

2.1.1, and applied state-specific diurnal profiles to create hourly emissions. Finally, for the base 

case, all sources (both CEM and non-CEM) used the daily emissions and diurnal profiles 

approach. 

Full 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. 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 2002 NEI v3 

emissions to obtain 2005 estimates.

2. Non-EGU Stationary Source enhancements 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 NEI point sources 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 
12

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

because SMOKE requires the 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 for 

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. 

2.1.1 IPM sector (ptipm) 

The ptipm sector contains emissions from EGUs in the 2005 NEI version 2 point inventory that 

we were able match to the units found in the 2006 NEEDS database, version 3.02 

(http://www.epa.gov/airmarkets/progsregs/epa-ipm/index.html), which is used by the IPM, 

version 3.02. 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 in order 

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 2005 NEI point source inventory contains emissions estimates for both EGU and non-EGU 

sources. The IPM is used to predict the future year emissions for the EGU sources. The 

remaining non-EGU point sources are projected by applying projection and control factors to the 

base year emissions. It was therefore necessary to identify and separate into two sectors: (1) all 

sources that are projected via the IPM and (2) those that are not. This procedure prevents 

double-counting or dropping significant emissions when creating the future-year emissions. The 

matching process relies on imperfect data; consequently, we experienced a small degree of 

dropped and/or double-counted emissions for sources that we could not match. We believe that 

the unmatched units are small emissions sources because we have reviewed both the NEI and the 

NEEDS database to ensure that all significant EGUs have been captured in the matching process. 

The methodology that follows describes how we split the point inventory into the ptipm and 

ptnonipm sectors. The approach started with the splits identified for the 2002 NEI (step 1) and 

then included additional steps to apply these to the 2005 NEI. 

Methodology to split the EGU from the non-EGU sources

Step 1: Obtain facilities and units identified as EGUs from the 2002 NEI 

We identified 2002 NEI units as IPM units using the 2006 NEEDS 3.0 database. This 

methodology is described in the 2002 Platform documentation previously referenced. Since 

some source identifiers are held constant between the 2002 and 2005 NEI, particularly “NEI 
13

Unique ID”, we were able to more easily compare the two inventories to ensure that we made 

improvements in the 2005 matching rather than inadvertent omissions. 

Step 2: Create the 2005 NEI v2 point modeling inventory from the 2005v2 NEI and impacts on 

EGU matching 

We further enhanced the published 2005 NEI v2 point inventory to improve the ptipm and 

ptnonipm splits and make other udpates. What follows are the issues and how we resolved them, 

and these represent differences between the published 2005 v2 NEI and what we used for 

modeling. 

1) We identified facilities added with HAP emissions records that were clearly EGUs, but 

had not been flagged as “IPM” sources. These facilities had facility identifiers (i.e., plant 

IDs) beginning with “EGU”. We further confirmed that these records were EGU 

emissions; and therefore, we moved these units to the ptipm sector. 

2) We found one additional unit with HAP emissions records not flagged as an EGU, but 

that we confirmed were representing emissions from a facility for which we had 

identified CAP records as ptipm sector records. We moved this unit (South Mississippi 

Electric Power, plantid = 2807300021, unitid = 012, NEI_UNIQUE_ID=NEI409) into 

the ptipm inventory. 

3) Several facilities and units closed between 2002 and 2005 and had not initially been 

removed in the development of the 2005v2 NEI; we removed these based on a list from 

the NEI developers. 

4) Inspection of CEM and 2005 NEI v2 point inventory revealed some duplication of 

sources with state and non-state reported data. This can occur because EPA created the 

EGU records in the 2005 NEI, but the states sometimes still submitted these emissions 

records. We removed these duplicates. 

5) ORIS facility and boiler codes (used to match to the CEM hourly data) were 

unintentionally dropped between a preliminary and final 2005 NEI v2 point dataset. We 

completely repopulated these ORIS facility and boiler codes based on what we had in 

hand. 

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. The ptipm sector uses the available 

hourly CEM data via a method first implemented in the 2002 platform that was also used for the 

2005 platform. For sources with CEMs, we used the actual hourly CEM data for the 2005 

evaluation case. The hourly CEM data were obtained from the CAMD Data and Maps website2. 

The SMOKE modeling system matches the ORIS Facility and Boiler IDs in the NEI SMOKEready file to the same fields in the CEM data. This allowed us to use the hourly SO2 and NOX

CEM emissions directly from the CEM data file. We used the heat input from the hourly CEM 

 

2

 http://camddataandmaps.epa.gov/gdm/index.cfm?fuseaction=emissions.wizard 
14

data to allocate the NEI annual values for all other pollutants from CEM sources, because hourly 

data for these other pollutants are not available with the hourly CEM data. 

For sources not matching the CEM data (“non-CEM” sources), we computed daily emissions 

from the NEI annual emissions using a structured query language (SQL) program and stateaverage CEM data. To allocate annual emissions to each month, we created state-specific, threeyear averages of 2004-2006 CEM data. These average annual-to-month factors were assigned to 

non-CEM sources by state. To allocate the monthly emissions to each day, we used the 2005 

CEM data to compute state-specific month-to-day factors, averaged across all units in each state. 

The resulting daily emissions were input into SMOKE. The daily-to-hourly allocation was 

performed in 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. 

For the 2005 base case, we do not use year-specific CEM data, and for future-year scenarios, 

there are no CEM data available for specific units. Thus, for the base and future-year cases, we 

used the same procedures as for “non-CEM” sources to compute daily emissions for input to 

SMOKE for all ptipm sources. 

2.1.2 Non-IPM sector (ptnonipm)

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

in the IPM (ptipm) sector3

. The ptnonipm sector contains fugitive dust PM emissions from 

vehicular traffic on paved or unpaved roads at industrial facilities or coal handling at coal mines4. 

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

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

discussed further in Section 2.2.1. 

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

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

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

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

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

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

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

and petroleum product working losses. 

The most significant changes we made to the ptnonipm emissions involved moving some HAP 

records that should have been flagged as IPM into the ptipm sector (discussed in section 2.1.1). 

The other modifications are listed here and represent differences between the published 2005 

NEI v2 and the 2005 inventory we used for modeling:

1) Removed duplicate annual records. We correctly did not delete sub-annual, nonrepeating records. 

 

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. 
15

2) 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. 

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

4) 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. 

2.2 2005 Nonpoint sources (afdust, ag, nonpt) 

The 2005 NEI v2 generally did not included 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 

emissions to prevent possible double counting with the county-level emissions. Because the 

tribal nonpoint emissions are small, we do not anticipate these omissions as 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 costly 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 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 
16

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

are provided in Table 2-5. 

Table 2-5. 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 the approach 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 2005 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) 

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

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

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

documentation. 

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

livestock SCCs are listed in Table 2-6, and the fertilizer SCCs are listed in Table 2-7. 

Table 2-6. Livestock SCCs extracted from the 2002 NEI to create the ag sector 

SCC SCC Description*

2805000000 Agriculture - Livestock;Total 

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

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

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

2805002000 Beef cattle production composite;Not Elsewhere Classified 

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

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

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

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

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

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

2805009100 Poultry production - broilers;Confinement 

2805009200 Poultry production - broilers;Manure handling and storage 

2805009300 Poultry production - broilers;Land application of manure 

2805010100 Poultry production - turkeys;Confinement 

2805010200 Poultry production - turkeys;Manure handling and storage 

2805010300 Poultry production - turkeys;Land application of manure 

2805018000 Dairy cattle composite;Not Elsewhere Classified 

2805019100 Dairy cattle - flush dairy;Confinement 

2805019200 Dairy cattle - flush dairy;Manure handling and storage 

2805019300 Dairy cattle - flush dairy;Land application of manure 

2805020001 Cattle and Calves Waste Emissions;Milk Cows 

2805020002 Cattle and Calves Waste Emissions;Beef Cows 

2805020003 Cattle and Calves Waste Emissions;Heifers and Heifer Calves 

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

2805021100 Dairy cattle - scrape dairy;Confinement 

2805021200 Dairy cattle - scrape dairy;Manure handling and storage 

2805021300 Dairy cattle - scrape dairy;Land application of manure 

2805022100 Dairy cattle - deep pit dairy;Confinement 

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

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

2805023100 Dairy cattle - drylot/pasture dairy;Confinement 

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

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

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

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

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

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

2805030003 Poultry Waste Emissions;Layers 

2805030004 Poultry Waste Emissions;Broilers 

2805030007 Poultry Waste Emissions;Ducks 

2805030008 Poultry Waste Emissions;Geese 

2805030009 Poultry Waste Emissions;Turkeys 

2805035000 Horses and Ponies Waste Emissions;Not Elsewhere Classified 
18

SCC SCC Description*

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

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

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

2805040000 Sheep and Lambs Waste Emissions;Total 

2805045000 Goats Waste Emissions;Not Elsewhere Classified 

2805045002 Goats Waste Emissions;Angora Goats 

2805045003 Goats Waste Emissions;Milk Goats 

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

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

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

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

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

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

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

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

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

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

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

following SCCs5: 

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

General

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

Manure Handling: Dry 

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

Classified 

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

(Industrial Processes; Miscellaneous Manufacturing Industries; Miscellaneous Industrial 

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

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

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

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

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

those in the ptnonipm sector. This will be discussed further in Section 4 in the final version of 

this documentation. 

 

5

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

“CATTLE”, “DAIRY”, or “PLTRY”. 
19

Table 2-7. 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. This sector is similar to the nonpt sector in the 2002 Platform, which uses the 

2002 NEI v3 emissions. The differences are that: 

• The 2005 platform replaces 2002 NEI v3 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. 

• 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. 

• 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. 

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 2005 platform. 

2005 Phase II WRAP oil and gas inventory
20

NEI 2002 Industrial Processes, Oil and Gas Production emissions (SCC=2310000000) were 

removed from all non-California WRAP states and the WRAP 2005 Phase II oil and gas 

emissions were added. As seen in Table 2-8, the 2002 NEI nonpt inventory contains a very 

small amount of emissions for this category. The 2002 NEI oil and gas nonpt emissions were 

limited to VOC in Arizona, Montana, Nevada, New Mexico, North and South Dakota, and 

Wyoming, and negligible CO and NOX emissions in New Mexico. In contrast, the 2005 WRAP 

oil and gas inventory contains much higher emissions, reflecting greatly improved information 

on the activity and equipment and emission factors for this sector for all WRAP states except for 

California (and Washington): AK, AZ, CO, MT, NV, NM, ND, OR, SD, UT, WY. The 

motivation and development of the Phase II WRAP oil and gas emissions is described in this 

report: 

http://www.wrapair.org/forums/ogwg/documents/2007-10_Phase_II_O&G_Final)Report(v10-

07%20rev.s).pdf

Table 2-8. Oil and gas production nonpoint emissions in WRAP states in 2002 and 2005 

platforms. Emissions provided in short tons/year.

Pollutant 2002 2005 

CO 1 53,784

NOx 31 155,133

SO2 0 2,842

VOC 2,184 480,252

Table 2-9 lists the new area source SCCs that were created to describe the new WRAP oil and 

gas emissions inventory. We converted the WRAP’s average day “IDA”-formatted inventory to 

the SMOKE annual “ORL” (one record per line) format and retained only non-zero emissions, 

leaving us with the following pollutants (also seen in Table 2-8): CO, NOX, SO2, and VOC. The 

first two SCC Tier descriptions “Industrial Processes, Oil and Gas Production” are not repeated 

in this table. 

Table 2-9. New SCCs from the Phase II WRAP Oil and Gas Inventory 

SCC Description 

2310000220 All Processes, Drill Rigs 

2310000330 All Processes, Artificial Lift 

2310000440 All Processes, Saltwater disposal engines 

2310010100 Crude Petroleum, Heaters 

2310010200 Crude Petroleum, Tanks - Flashing & Standing/Working/Breathing 

2310010300 Crude Petroleum, Pneumatic Devices 

2310010700 Crude Petroleum, Fugitives 

2310010800 Crude Petroleum, Truck Loading 

2310020600 Natural Gas, Compressor Engines 

2310020700 Natural Gas, Fugitives 

2310020800 Natural Gas, Truck Loading 

2310021100 Natural Gas, Heaters 

2310021300 Natural Gas, Pneumatic Devices 

2310021400 Natural Gas, Dehydrators 
21

SCC Description 

2310021500 Natural Gas, Completion - Flaring & Venting 

2310021600 Natural Gas, Venting 

2310023000 Natural Gas, CBM - Dewatering pump engines 

2310030210 Natural Gas Liquids, Tanks - Flashing & Standing/Working/Breathing, Uncontrolled 

2310030220 Natural Gas Liquids, Tanks - Flashing & Standing/Working/Breathing, Controlled 

Updates RWC emissions

The updates for RWC emissions were done between the 2002 v3 and 2005 v2; no additional 

updates were made for the platform. Currently the documentation of RWC changes is not 

available on the website so we document these changes here. First, emissions were replaced for 

Oregon and New York, because these areas submitted changes to their 2002 v3 emissions that 

they indicated were improvements. Second, analysis of PM2.5 and VOC for RWC indicated that, 

with the exception of California, states and local agencies that submitted emissions, used the AP42-based VOC emissions factor (229 lb VOC per ton wood) for fireplaces, which we have 

subsequently determined overestimated VOC by over an order of magnitude. Therefore, we 

replaced the AP-42-based VOC factor of 229 lbs VOC/ton wood burned with a factor from a 

Mid-Atlantic Regional Air Management Association (MARAMA) study (Marama, 2006) of 18.9 

lbs VOC/ton wood burned, using a series of conditional analyses detailed in Appendix A. The 

conditional part of the changes was required because many states included fireplaces together 

with woodstoves or did not include VOC with all RWC-related SCCs. 

The net effect of the RWC updates and the VOC recalculation on annual national emission totals 

between the 2002 and 2005 platform is shown in Table 2-10. 

Table 2-10. RWC Emissions Changes for CAPs between 2002 and 2005 platforms. 

Emissions values provided in short tons/year.

Pollutant 2002 2005 % Change 

VOC 1,476,756 40,754 -97.2%

NOX 40,707 38,369 -5.7%

CO 3,061,043 2,857,985 -6.6%

SO2 5,705 5,307 -7.0%

NH3 8,700 7,238 -16.8%

PM2.5 405,777 382,192 -5.8%

PM10 416,488 384,295 -7.7%

The 2005 platform also contains corrected HCl emissions for Stationary Source Fuel Combustion 

Coal fired Industrial and Commercial/Institutional boilers (SCCs 2102002000 and 2103002000). 

The EPA Office of Research and Development (ORD) identified overestimated HCl in the 2002 

platform nonpt sector and provided revised HCl emissions in Georgia, Utah, and Virginia that 

lowered these emissions by approximately 100,000 tons/year. 
22

2.3 Fires (ptfire and avefire) 

Wildfire and prescribed burning emissions are contained in the ptfire and avefire sectors. The 

nonptfire sector in the 2002 platform is not needed for the 2005 platform because the 2005 

platform ptfire sector contains these emissions. The ptfire sector has emissions provided at 

geographic coordinates (point locations) and has daily emissions values, whereas the avefire 

sectors are county-summed inventories and have annual total emissions values. For the 2005 

evaluation case, we modeled 2005 year-specific fires using the emissions from the ptfire sector. 

For the 2005 base case, the ptfire sector was replaced by the avefire sector. 

For the 2005 Platform, the following SCCs from the 2005 NEI are considered “fires” (note that 

the actual SCC description includes “Miscellaneous Area Sources” as the first tier level 

description). 

Table 2-11. 2005 NEI SCCs representing emissions in the ptfire and avefire modeling sectors

SCC SCC Description * 

2810001000 Other Combustion;Forest Wildfires;Total 

2810015000 Other Combustion;Prescribed Burning for Forest Management;Total 

2810005000 Managed Burning, Slash (Logging Debris);Total 

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

Both the ptfire and avefire sectors for the 2005 Platform exclude agricultural burning and other 

open burning sources, which are included in the nonpt sector. We chose to keep agricultural 

burning and other open burning sources in the nonpt sector because these categories were not 

factored into the development of the average fire sector (as described in 2.3.3). Additionally, 

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

prescribed/managed burns. 

2.3.1 Day-specific point source fires (ptfire) 

The ptfire sector includes wildfire and prescribed6 burning emissions occurring in 2005, which 

were used for the 2005 model evaluation case. Note that Agricultural Burning is not included in 

the ptfire sector as it is included in the nonpt sector. We did not include emissions from this 

sector in the 2005 base case or any of the future year cases. This sector includes emissions for 

all 2005 wildfires and many prescribed burns with daily estimates of each fire’s emissions. It 

includes a satellite derived latitude/longitude of the fire’s origin and other parameters associated 

with the emissions such as acres burned and fuel load, which allow estimation of plume rise. 

The SCCs in the ptfire sector are listed in Table 2-12. 

 

6

 For purposes of this document prescribed burning also includes managed burning, i.e., “Other Combustion; 

Managed Burning, Slash (Logging Debris)”
23

Table 2-12. SCCs in the ptfire sector 

SCC SCC Description * 

2810001000 Other Combustion;Forest Wildfires;Total 

2810005000 Other Combustion;Managed Burning, Slash (Logging Debris);Total 

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

The use of point source and day-specific data for fires was a new feature to EPA’s modeling for 

the 2002 platform and is described in the 2002 platform documentation. 

The point source day-specific emission estimates for 2005 fires rely on Sonoma Technology, 

Inc.’s Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation 

(SMARTFIRE) system (Sullivan, et al., 2008). This system involves the use the National 

Oceanic and Atmospheric Administration’s (NOAA’s) Hazard Mapping System (HMS) fire 

location information as input combined with CONSUMEv3.0 (Joint Fire Science Program, 2009)

and the Fuel Characteristic Classification System (FCCS) fuel-loading database to estimate fire 

emissions from wildfires and prescribed burns on a daily basis. The method involves the 

reconciliation of ICS-209 reports (Incident Status Summary Reports) with satellite-based fire 

detections to determine spatial and temporal information about the fires. The ICS-209 reports 

for each large wildfire are created daily to enable fire incident commanders to track the status 

and resources assigned to each large fire (100 acre timber fire or 300 acre rangeland fire). The 

SMARTFIRE system of reconciliation with ICS-209 reports is described in an Air and Waste 

Management Association report (Raffuse, et al., 2007). 

Figure 2-1 shows a functional diagram of the SMARTFIRE process. 

Once the fire reconciliation process is completed, the emissions are calculated using the U.S. 

Forest Service’s CONSUMEv3.0 fuel consumption model and the FCCS fuel-loading database 

in the Bluesky Framework (Ottmar, et. al., 2007), 

This method of estimating emissions in the ptfire sector is significantly different than that 

described in the 2002 platform documentation. First, the fire locations are satellite-based instead 

of ground-based. This means that many more fires are detected in space and time. Fires that 

could be matched in space and time with an ICS-209 report were designated as wildfires; all 

other fires were designated as prescribed burning. This point leads to the second difference from 

2002: the distinction between wildfire and prescribed burn is not as precise as with ground-based 

methods. Third, the fire size was based on the number of satellite pixels and a nominal fire size 

of 100 acres/pixel was assumed for a significant number of fire detections when the first 

detections were not matched to ICS 209 reports. This means that the fire size information is not 

as precise as ground based methods. Finally, because the HMS satellite product from NOAA is 

based on daily detections, the emission inventory represents a time-integrated emission estimate. 

For example, a large smoldering fire will show up on satellite for many days and would count as 

acres burned on a daily basis whereas a ground-based method would count the area burned only 

once even it burns over many days. 

Additional references for this method are provided in (McKenzie, et al., 2007), (Ottmar, et al., 

2003), (Ottmar, et al., 2006), and (Anderson et al., 2004).
24

Figure 2-1. SMARTFIRE System
25

The SMOKE-ready “ORL” files created from the raw daily fires contain both CAPs and HAPs. 

The HAPs were generated using the same emission factors as were used in the 2002 Platform 

and described in Section 2.3 of the CAP and HAP 2002-Based Platform, Version 3 

(ftp://ftp.epa.gov/EmisInventory/2002v3CAPHAP/documentation) 

2.3.1.1 Speciation of “isomers of xylenes” in ptfire 

Although xylenes are not HAPs that are used in the 2005 CAP-BAFM platform, they are used in 

the RFS2 version. We modified “Xylenes (Mixed Isomers)” emissions present in the raw daily 

fires files, represented only by pollutant code 1330207 by apportioning the emissions to mxylene (108383), o-xylene (95476) and p-xylene (106423). We did this because pollutant code 

1330207 (representing “Xylenes (Mixed Isomers)”) is mapped (during the speciation process 

that occurs in SMOKE) to m, o, and p, xylene and ethylbenzene. The mapping (developed by 

the chemical mechanism developers) treats pollutant code 1330207 as a solvent as opposed to a 

combustion byproduct. We apportioned the code 1330207 emissions using the following 

percentages: 61.41% m-xylene, 16.58% p-xylene and 22.01% o-xylene. These were derived 

from measurements of the flaming and smoldering xylene emission rate (Lee, et. al, 2005) and 

the assumption that 75% of the emissions are flaming and 25% smoldering7

. 

2.3.1.2 Creation of “NONHAPVOC” in ptfire 

We used the BAFM HAP emissions from the inventory rather than from VOC speciation in this 

sector (though it is listed as a limitation below). To accomplish this, we computed the 

NONHAPVOC as an input to SMOKE, because SMOKE is limited to computing 

NONHAPVOC for annual emissions data but not the daily data we used for fires. Daily 

NONHAPVOC for each fire was computed for each source by subtracting the fire’s daily BAFM 

mass from the daily VOC mass. We also then dropped the pollutant “VOC” from the data files 

since it was no longer needed and if we had kept it, then we would be double counting emissions. 

2.3.1.3 Limitations of the ptfire data in the 2005 platform 

There were several limitations of the ptfire data approach that we identified after the data were 

prepared and modeled. Only the first issue listed affects a species that was modeled, and that 

issue only affects the model evaluation case; it had no impact on the base case used in RRF 

calculations because ptfire was not used in the base case. The limitations are listed below. 

(1) Benzene (Pollutant code and CAS =71432): Emissions were inadvertently dropped during 

format conversion. Raw data annual total = 58,346 tons/yr and ORL file annual total = 263.47 

tons/yr.

(2) Benzo[g,h,i,]Perylene (Pollutant code and CAS= 191242): A portion of the emissions were 

inadvertently dropped during format conversion. Raw data annual total = 263 tons and ORL file 

annual total = 266.58 tons. 

 

7

 When reviewing the calculations, it turns out an equal flaming and smoldering fraction was used by mistake, a 

75/25 split would have resulted in the following percentages: 59.07, 19.25 and 21.68 for m, p, and o-xylene, 

respectively. 
26

(3) Benzo[k]Fluoranthene (Pollutant code and CAS= 207089): Emissions were missing from the 

ORL file. Raw data annual total = 134.84 tons and ORL file annual total = 0 tons. 

(4) Benzofluoranthenes (Pollutant code and CAS 56832736) double counts emissions of CAS= 

203338 (Benzo(a)Fluoranthene) and CAS= 207089 Benzo[k]Fluoranthene). Therefore this 

pollutant should not have been in the file. 

As noted earlier, items 2 through 4 above impact HAPs that are not used in the modeling, but 

that are included with incorrect emissions values in the data we posted at the 2005v4 website 

(see the end of Section 1). The first error, however, impacts the modeling results because 

benzene emissions were integrated with the VOC and used as part of the speciation approach 

described in Section 3.1.2.1. 

Finally, our use of the HAP emissions to “integrate” the HAP VOCs with the VOC (described in 

Section 2.3.1.2) was an approach that we have since dropped in favor of using VOC speciation 

without BAFM integration. Due to the introduction (in this platform) of a new speciation 

profile (5560) that is based on a compilation and critical evaluation of a large variety of species 

emitted from biomass fires (Andrae, 2001), we have not established whether or not HAP 

emissions from the NEI are more or less accurate. Therefore in subsequent modeling, we will 

choose to use the “no-integrate”, “no-hap-use” case which means VOC from these sources is 

speciated to provide all model species including BAFM. 

2.3.2 Average fires (avefire) 

The average fire sector includes emissions from wildfires, prescribed burning, and managed 

burning. We used this sector for the 2005 base case, and all future year cases. As noted above, 

avefire emissions are annual, county-level emissions. 

The purpose of the avefire sector is to represent emissions for a typical or average 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 changing 

the fires would otherwise cause. 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 modelpredicted concentrations. 

We created the average-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 

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 
27

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 in the 

following ways: 

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

of EPA fire inventory expert who reviewed the VOC emissions and found them 

too high (Tom Pace, personal communication). 

b. We created HAP emissions records by applying emission ratios to PM2.5. 

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 PM2.5 are unchanged and are provided 

for reference. 

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

short tons/year

SCC SCC Description * 2002 VOC 2005 VOC CO PM2.5

2810001000 Forest Wildfires;Total 386,997 1,883,230 8,223,736 685,783

2810005000 Managed Burning, Slash (Logging 

Debris);Total 67,664 105,661 461,404 7,460

2810015000 Prescribed Burning for Forest 

Management;Total 84,784 399,880 1,746,208 147,298

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

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
28

Pollutant Description CAS PM2.5 factor 

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

2.4 Biogenic sources (biog) 

For CMAQ, we computed the biogenic emissions based on 2005 meteorology data using the 

BEIS3.14 model from 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. 
29

2.5 2005 Mobile sources (on_noadj, on_moves_runpm, 

on_moves_startpm, nonroad, alm_no_c3, seca_c3) 

The biggest differences in the U.S. mobile emissions between the 2002 and 2005 platforms are 

(1) the apportioning of the emissions into additional platform sectors to allow for processing 

differences among the sectors; (2) the use of new emissions methods and data sets, particularly 

the use of a draft version of the Motor Vehicle Emissions Simulator (MOVES) model including 

temperature affects on gasoline PM2.5 exhaust emissions; and (3) the update of most of the data 

to 2005. A summary of these differences is presented below; details are provided in the 

subsections that follow. 

For the 2005 platform, as indicated in Table 2-2, we have separated the previous 2002 sectors 

“onroad” and “alm”. The result is the 2005 onroad emissions are now broken out into three 

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

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

“alm_no_c3” and “seca_c3”, and as previously mentioned, the aircraft emissions are now in the 

nonEGU point inventory. 

While the previous EPA platforms have used NMIM for the onroad and nonroad sectors8

, some 

of the onroad emissions in the 2005 platform were based on a draft version9 of the MOVES 

model run for the year 2005. We used this draft MOVES model to make sure to include the 

PM2.5 emissions from onroad gasoline vehicles, which include temperature effects and are much 

larger than previous versions of onroad PM2.5. The onroad gasoline emissions, except for 

motorcycles, were based on MOVES for the pollutants listed in Table 2-15. Unlike our use of 

NMIM, we used the MOVES data to create emissions by state and month and then allocated 

these to counties based on 2005 NMIM-based county-level data. The reason for the state 

resolution was due to (a) run time issues that made a county run done for the nation infeasible in 

the timeframe required and (b) uncompleted efforts to create a national database of countyspecific 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 2005 NEI v2. 

Table 2-15. Pollutants covered by the draft MOVES model in the 2005 Platform1

Used in the 2005 CAP-BAFM Platform Available from draft MOVES, but not used 

in 2005 CAP-BAFM Platform 

PM2.5; exhaust, partially speciated2 Naphthalene3 

VOC; except refueling 1,3 butadiene4 

CO Acrolein4 

NOX

Benzene; except refueling 

Formaldehyde 

Acetaldehyde 

1

 Draft MOVES data were used only for onroad gasoline vehicles with the exception of motorcycles. Draft MOVES 

 

8

 Other than California which were provided by CARB and were based on the mobile models used by California, 

EMFAC and OFFROAD, for onroad and nonroad emissions, respectively. 

9

 As of December 2009, this draft version was replaced by the publicly released MOVES2010 version at 

www.epag.gov/otaq/models/moves/ 
30

data were not used for any California onroad emissions 

2

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

(named as “PM25OC”). Brake wear and tire wear PM2.5 emissions were not available from draft MOVES. 

3

 Used for the RFS2 version of the platform 

4

 Used for the RFS2 and LD GHG versions of the platform 

The 2005 v2 NEI does not contain the draft 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.10 The NMIM data was used for all of the 

remaining onroad mobile sources 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. 

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 

2005 NEI v2 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 are now modeled separately as point sources in the new “seca_c3” sector 

for the 2005 platform. 

The nonroad sector is the only 2002 mobile sector with U.S. emissions that was left intact and is 

still based on NMIM; however, for the 2005 platform, NMIM was run for 2005. 

California onroad and nonroad emissions, which use neither MOVES nor NMIM, are based on 

an updated submittal to the NEI for 2005. 

With the exception seca_c3 point source-formatted sector, the mobile sectors are at county and 

SCC resolution. 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. 

All mobile sectors that have benzene, acetaldehyde, formaldehyde or methanol present in the 

inventory data, use these HAPs via “integration” for input into the air quality model, as described 

in Section 3.1.2.1. A few categories of nonroad sources (CNG and LPG-fueled equipment) do 

not have BAFM and therefore utilize the “no-integrate”, “no-hap-use” case which means VOC 

from these sources is speciated to provide BAFM. 

 

10 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. 
31

2.5.1 Onroad mobile MOVES cold-start exhaust sources requiring 

temperature adjustments (on_moves_startpm) 

This sector contains draft MOVES emissions for PM and naphthalene11 for non-California 

onroad gasoline cold-start exhaust except for motorcycles. These emissions (and the 

on_moves_runpm sector discussed in the next section) are processed separately from the 

remainder of the onroad mobile emissions because they are subject to hourly temperature 

adjustments, and these temperature adjustments are different for cold-start and running exhaust 

modes. 

Temperature adjustments were applied to account for the strong sensitivity of PM and 

naphthalene exhaust emissions to temperatures below 72 oF. 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 72 oF and applied temperature adjustments after the 

emissions were spatially and temporally allocated. The PM2.5 (and naphthalene for RFS2) 

adjustments were different for starting and running exhaust and applied to SMOKE gridded, 

hourly intermediate files using the gridded hourly temperature data also input to the CMAQ 

model. One result of this approach is that inventory summaries based from 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. 

Figure 2-2 shows how PM (and naphthalene) emissions increase with colder temperatures and 

how start exhaust emissions increase more than running exhaust emissions. 

 

11 Naphthalene is not used in the 2005 CAP-BAFM platform, but it is contained in the MOVES-based inputs and 

was used in the version of the 2005 platform used for RFS2 (EPA, 2010) 
32

Figure 2-2. MOVES exhaust temperature adjustment functions. 

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

A number of features of the MOVES output required additional processing to develop countylevel monthly ORL files for SMOKE. As stated earlier, the spatial resolution of the MOVES 

data was at the state level and data were allocated to county level prior to input into SMOKE. In 

addition, the exhaust PM2.5 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 done only on the species affected by temperature. Finally, 

because the start 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 below. 

i. We allocated state-level emissions to counties using state-county emission ratios by 

SCC, pollutant, and emissions mode (e.g., evaporative, exhaust) for each month. The 

ratios were computed using NMIM 2005 data (same data included in the 2005 NEI 

v2). 

ii. We assigned these start 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 data. For example, we split 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. 
33

iii. We converted MOVES-based PM2.5 species at 72 oF 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 B. 

• NAPHTH_72: unchanged from MOVES-based file, subject to temperature 

adjustment below 72 oF. 

• PEC_72: unchanged from MOVES-based PM25EC, subject to temperature 

adjustment below 72 oF. 

• 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 72 oF. 

• PSO4: unchanged from MOVES-based PM25SO4, not subject to temperature 

adjustment. 

• PNO3: computed from MOVES-based PM25EC, not subject to temperature 

adjustment. 

• OTHER: sum of computed metals (fraction of MOVES-based PM25EC) and 

NH4 (computed from PNO3 and PSO4), not subject to temperature adjustment. 

• PMFINE_72: Computed from OTHER and fraction of POC_72. Subject to 

temperature adjustment below 72 oF. 

• PMC_72: Computed as fraction of sum of PMFINE_72, PEC_72, POC_72, 

PSO4, and PNO3. Subject to temperature adjustment below 72 oF. 

The 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 specie “PM25EC”. 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 B. 

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 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 

2-2). 
34

2.5.3 Onroad no-adjustments mobile sources (on_noadj) 

This sector consists of the remaining onroad mobile emissions 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, non-motorcycle, non-PM: These are the monthly nonPM, non-naphthalene MOVES-based emissions from two MOVES inventories: 

a. Exhaust: VOC, NOX, CO, 1,3-butadiene (106990), acetaldehyde (75070), acrolein 

(107028), benzene (71432), and formaldehyde (50000); and 

b. Evaporative: Non-refueling VOC, benzene, and naphthalene (91203) 

For these pollutants listed, these non-California MOVES emissions encompass the same 

sources as the on_moves_startpm and on_moves_runpm sectors -LDGV, LDGT1, 

LDGT2, and HDGV- but 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 statelevel to county-level much like the on_moves_startpm and on_moves_runpm sectors 

already discussed. The preprocessing for these emissions did not require species 

calculations because the raw MOVES emissions translated directly to SMOKE inventory 

species. 

2. California onroad inventory: California year 2005 v2 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 NMIM runs for California. We retained only those HAPs that are 

also estimated by NMIM for nonroad 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 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 for all 

onroad diesel, all motorcycles, all refueling, and onroad LDGV, LDGT1, LDGT2, and 

HDGV emissions for pollutants not covered by the draft MOVES used for this platform 

(e.g., SO2, NH3, and most HAPs). The NMIM county database is NCD20080522; this is 

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

inputs where provided. 

The remainder of this section discusses the pre-processing required to create monthly ORL files 

for the remainder of the on_noadj sector (#3 above). 

EPA/OTAQ created the NMIM 2005v2 onroad mobile CAP/HAP emissions for all states and 

sources using the MOBILE6 model version M6023ChcOxFixNMIM. We then removed the CO2

emissions and emissions of dioxins and furans, as well as emissions that were replaced by 

MOVES and California-submitted data. We also removed onroad refueling emissions since the 

NEI treats onroad refueling as a stationary source that is included in the nonpt sector (gasoline 
35

distribution, Stage II, SCC=2501060100), and in limited appearance in the point sector in a 

handful of states (gasoline distribution Stage II; vapor loss or unclassified, SCC=40600401, 

40600402, 40600403, and 40600499 in California, Colorado, Kentucky, and North Carolina). 

Emissions were converted from monthly totals to monthly average-day based the on number of 

days in each month. Furthermore, this sector includes exhaust, evaporative, brake wear and tire 

wear emissions from onroad sources, which allowed us to use speciation profiles that are specific 

to each of these processes. 

Similar to nonroad pre-processing, we reassigned NMIM evaporative xylene (compound XYL or 

CAS=EVP__1330207) into MXYL (CAS=EVP__108383) and OXYL (CAS=EVP__95476,) 

using a 68% and 32% ratio to evaporative 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. 

The 2005 VMT database was based on 2002 VMT grown to 2005 based on Federal Highway 

Administration (FWHA) data unless replaced by state-provided VMT. A summary of the 2005 

vehicle miles traveled (VMT) inputs (along with future year 2020 VMT used in the projections 

and will be discussed in a future version of this documentation) is available at: 

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

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. The NMIM relied on the version of the NONROAD2005 model (NR05cBondBase) 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. Future year nonroad 

emissions (to be added to Section 4 of this document) used the NR05d-Bond-final version of 

NONROAD which incorporates the Bond rule revisions. 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 for nonroad sources are not dropped 

from processing for this sector. 

Similar to the on_noadj pre-processing, we also reassigned NMIM evaporative xylene. Since for 

nonroad sources we kept the refueling emissions in the nonroad sector (unlike onroad, these are 

not in any other part of the inventory) we also reassigned refueling 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. 
36

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 the on 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. 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. 

The CARB-based nonroad data did not have mode-specific data for VOC (exhaust, evaporative, 

and refueling). 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. In previous 

modeling platforms, this sector also contained aircraft emissions, but here we have removed 

aircraft emissions from the sector because point-source airports were provided in the 2005 NEI 

v2 point source inventory, and we chose to include them with other point sources in the 

ptnonipm sector. (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. 

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. 

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 

Mobile Sources; Aircraft: All Aircraft Types and 

Operations: Total 
37

SCC Action SCC Description 

platform 

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 alm sector is available at: 

http://www.epa.gov/ttn/chief/net/2002inventory.html#documentation

For modeling purposes, the following additional changes were made to the data for the 2005 

platform: 

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

• Removed railway maintenance emissions (SCCs 2285002015, 2285004015, and 

2285006015) because these are included in the nonroad NMIM monthly inventories. 

This change was made for the 2002 platform and is retained here in the 2005 platform. 

• For the purpose of CAP-HAP VOC integration as discussed in Section 3.1.2.1, we 

removed benzene, formaldehyde, and acetaldehyde for all sources that we did not 

integrate these HAPs with VOC. As discussed in Section 3.1.2.1, sources are considered 
38

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 ports 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 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 a 2005 inventory from the 2002 data. 

These growth factors are provided in 
39

Table 2-17 and are mapped and documented in the following report: 

http://www.epa.gov/oms/regs/nonroad/marine/ci/420r09007-chap2.pdf

These growth factors are the same for all pollutants except NOX which includes a Tier 1 

Standard. 
40

Table 2-17. Regional growth factors used to project 2002 C3 emissions to 2005 

Region NOx All_other pollutants 

Alaska 1.054 1.102

East Coast 1.091 1.141

Gulf Coast 1.042 1.090

Hawaii 1.107 1.158

North Pacific (Washington) 1.054 1.102

South Pacific (Oregon and California 1.107 1.158

Great Lakes 1.047 1.052

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 this 

conference paper: 

http://www.epa.gov/ttn/chief/conference/ei17/session6/mason.pdf

This paper describes how the ASCII raster dataset was converted to latitude-longitude, 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. 

Table 2-18 shows how these C3 emissions generally increase from the 2002 v3 platform (from 

the old methods used in the NEI) and this 2005 v4 platform. Note that the 2002 NEI-based C3 

emissions are confined to the immediate coast and ports, whereas the 2005 C3 emissions cover 

most of the northern hemisphere Atlantic and Pacific oceans, including the Great Lakes/St. 

Lawrence seaway and Gulf of Mexico. The conference paper also shows gridded emissions 

maps comparing the 2002 NEI and 2002 ECA datasets. 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). 

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

Pollutant 2002 platform 2005 platform % Change 

CO 28,195 53,746 91%

NH3 131 0 -100%

NOX 244,988 642,089 162%

PM10 13,687 53,581 291%

PM2.5 12,620 49,294 291%

SO2 150,532 417,307 177%

VOC 7,377 22,367 203%
41

We applied factors to compute HAP emissions (based on emissions ratios) to either VOC or 

PM2.5 to obtain HAP emissions values. Table 2-19 below shows these factors and whether they 

were applied to VOC, PM2.5, or PM10. Because we computed HAPs directly from the CAP 

inventory and the calculations are therefore consistent, the entire seca_c3 sector utilizes CAPHAP VOC integration to use the VOC HAP species directly, rather than VOC speciation 

profiles. 

Table 2-19. HAP emission ratios for generation of HAP emissions from criteria emissions for 

C3 commercial marine vessels

Pollutant Apply to Pollutant Code Factor 

Acetaldehyde VOC 75070 0.0002286 

Benzene VOC 71432 9.795E-06 

Formaldehyde VOC 50000 0.0015672 

Benz[a]Anthracene PM2.5 56553 5.674E-07 

Benzo[a]Pyrene PM2.5 50328 1.844E-07 

Benzo[b]Fluoranthene PM2.5 205992 1.56E-07 

Benzo[k]Fluoranthene PM2.5 207089 1.56E-07 

Chrysene PM2.5 218019 9.929E-08 

Indeno[1,2,3-c,d]Pyrene PM2.5 193395 1.418E-08 

Acenaphthene PM2.5 83329 3.404E-07 

Acenaphthylene PM2.5 208968 5.248E-07 

Anthracene PM2.5 120127 5.248E-07 

Benzo[g,h,i,]Perylene PM2.5 191242 1.277E-07 

Fluoranthene PM2.5 206440 3.12E-07 

Fluorene PM2.5 86737 6.95E-07 

Naphthalene PM2.5 91203 1.987E-05 

Phenanthrene PM2.5 85018 7.943E-07 

Pyrene PM2.5 129000 5.532E-07 

Beryllium PM10 7440417 5.459E-07 

Cadmium PM10 7440439 7.642E-06 

Chromium VI PM10 18540299 2.948E-06 

Chromium III PM10 16065831 1.343E-05 

Lead PM10 7439921 3.002E-05 

Manganese PM10 7439965 5.732E-05 

Nickel PM10 7440020 0.0016377 

Selenium PM10 7782492 1.337E-05 

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 
42

have also been cropped from the original ECA-IMO data to cover only the 36-km CMAQ 

domain, which is the largest domain used for this effort. 

2.6 Emissions from Canada, Mexico and Offshore Drilling Platforms 

(othpt, othar, othon) 

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 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 (discussed in 

a future version of this documentation). 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. 
43

viii. Excessively high CO emissions were removed from Babine Forest Products Ltd (British 

Columbia 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/count 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. 

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 2005 NEI v2 point source inventory. The offshore sources were 

provided by the Mineral Management Services (MMS).

Table 2-20summarizes the data in the “oth” sectors and indicates where these emissions have 

been updated from the 2002 platform. 

Table 2-20. Summary of the othpt, othpt_hg, othar, othar_hg, and othon 

sectors in the 2005 Platform

Sector Components Changes from 2002 Platform 

Mexico, 1999, point None 

Canada, 2006, point Uses emissions from 2006 National Pollut ant 

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. 

othpt 

Offshore, 2005, point Uses emissions from 2005 v2 point inventory 

othpt_hg Canada, 2000, mercury 

point 

Uses speciated mercury point source year 2000 

inventory. 

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. 

othar 

Canada, 2006, nonroad Uses 2006 Canadian nonroad mobile, non-C3 

marine, and locomotives inventories. 
44

Sector Components Changes from 2002 Platform 

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). 

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 temporalize 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 were the same as were used in 

the 2002 Platform. 

2.7.1 Mercury 

As discussed in the CAP and HAP 2002-based Platform 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 CMAQ4.5.1 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. This fraction is subject 

to future adjustment as the processes controlling the recycling of mercury are better understood. 

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 
45

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

and were repeated again for the 2005 Platform, but using 2005-specific factors: 

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 model requires 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 CMAQ, 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 CMAQ. 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 pollutants for all 

sectors except for biogenics, natural, recycled and volcanic mercury and ocean chlorine are those 

inventoried for the NEI. 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 (and scripts, at a later date) for the 2005 Platform emissions are available at 

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

We used SMOKE to pre-process the raw emissions to create the emissions inputs for CMAQ. 

Although we used SMOKE version 2.5, the SMOKE version 2.6 source code and executables 
46

can be used to reproduce our emissions modeling, and these are available from the Community 

Multiscale Analysis System (CMAS) Center at http://www.cmascenter.org. The scripts used for 

running the 2002 platform in SMOKE are available on the CHIEF website provided at the end of 

Section 1. The 2005 scripts will be provided at a later date. 

One of the largest processing differences compared to the 2002v3 platform is the use of the 

CMAQ in-line emissions capability, which we used to create source-based emissions files rather 

than the 3-dimensional files for sectors that have plume rise. SMOKE was also 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. 

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 

Section 3.2.1). 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 2005 Platform, we did not have SMOKE compute vertical plume rise; this was done in 

CMAQ using stack data in 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 temporalized source-based CMAQ inputs for seca_c3 were used for the 

vertical allocation. The in-line approach was not done for the 2002 Platform, as this was a new 

feature in CMAQ and SMOKE that was not available at that time. 

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 
47

Platform sector Spatial Speciation 

Inventory 

resolution Plume rise 

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 BEIS hourly 

ptfire point Yes daily in-line 

nonptfire surrogates Yes annual 

avefire surrogates Yes annual 

One of the issues we found was that when using in-line processing, the PELVCONFIG file 

cannot allow grouping, otherwise the “inline” versus “offline” (i.e., processing whereby SMOKE 

creates 3-dimensional files) will not give identical results. Since we used a PELVCONFIG file 

with grouping, anyone wanting to exactly replicate our results should use the “inline” approach. 

3.1.1 Spatial configuration 

For the 2005 Platform, we ran SMOKE and CMAQ for modeling domains with 36-km and 

12-km spatial resolution. These are the same domains as were used for the 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). 
48

Figure 3-1. CMAQ modeling domains

36km Domain Boundary

12km East Domain Boundary

12km West Domain Boundary

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 
49

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 Carbon Bond 05 (CB05) mechanism (Yarwood, 2005) with 

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

http://www.cmascenter.org/help/model_docs/cmaq/4.7/RELEASE_NOTES.txt From the 

perspective of emissions preparation, it is the same mechanism 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 “CAP-only” 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. 
50

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 

NO Nitrogen oxide 

NO2 Nitrogen dioxide 

NOX

HONO Nitrous acid 

SO2 SO2 Sulfur dioxide 

SULF Sulfuric acid vapor 

NH3 NH3 Ammonia 

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 

VOC 

XYL Xylene and other polyalkyl aromatics 

Various additional SESQ Sesquiterpenes 

VOC species from 

the biogenics model 

which do not map to 

the above model 

species 

TERP Terpenes 

PM10 PMC Coarse PM > 2.5 microns and ≤ 10 microns 

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 

PM2.5

PMFINE Other particulate matter ≤ 2.5 microns 

The approach for speciating PM2.5 emissions is the same as that described for the 2002 platform 

except that two of the onroad sectors, and Canadian emissions contained pre-speciated PM 

emissions which were not further speciated in SMOKE . The approach for speciating VOC 

emissions from non-biogenic sources is different in two major ways: 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 
51

emission mode (e.g., exhaust, evaporative). SMOKE computes the resultant profile on the fly 

given the fraction of each specific profile to use for the 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 2005 Platform. 

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 2005 Platform differed from the 2002 Platform in that we 

included, for some of the U.S. platform sectors, HAP emissions from the NEI in the speciation 

process. That is, instead of speciating VOC to generate all of the species listed in Table 3-3 as 

we did for the 2002 platform, we integrated emissions of the 4 HAPs, benzene, acetaldehyde, 

formaldehyde and methanol (BAFM) from the NEI with the NEI VOC. The integration process 

(described in more detail below) combines the BAFM HAPs with the VOC in a way that does 

not double count emissions and uses the BAFM directly in the speciation process. We believe 

that generally, the HAP emissions from the NEI are more representative of emissions of these 

compounds than their generation via VOC speciation.

We chose these HAPs because, with the exception of BENZENE, they are the only explicit VOC 

HAPs in the base version of CMAQ 4.7 (CAPs only with chlorine chemistry) model. By 

“explicit VOC HAPs,” we mean model species that participate in the modeled chemistry using 

the CB05 chemical mechanism. We denote the use of these HAP emission estimates along with 

VOC as “HAP-CAP integration”. BENZENE was chosen because it was added as a model 

species in the base version of CMAQ 4.7, and there was a desire to keep its emissions consistent 

between multi-pollutant and base versions of CMAQ. 

The integration of HAP VOC with VOC is a feature available in SMOKE for all inventory 

formats other than PTDAY (the format used for the ptfire sector). SMOKE allows the user to 

specify the particular HAPs to integrate and the particular sources to integrate. The particular 

HAPs to integrate are specified in the INVTABLE file, and the particular sources to integrate are 

based on the NHAPEXCLUDE file (which actually provides the sources that are excluded from 

integration12). 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 CMAQ VOC species not including the integrated HAPs. This 

process is illustrated in Figure 3-2. Note that we did not need to remove B,A,F,M from nointegrate 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 B,A,F,M in that 

sector. 

 

12 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. 
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 

ptfire Full integration (However, NONHAPVOC computed outside of SMOKE since SMOKE cannot 

do this calculation for the day-specific fire formatted files) 

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 B, A, F or M emissions were from the 1996 NEI were not 

integrated (data source code contains a “96”), 

2. Any source for which the sum of B, A, F, or M 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 B,A,F and M specified in the first column. For a few 

source categories, we designated all sources as “no-integrate”. 
54

4. For source categories not covered in Table 3-5 (i.e., that don’t comprise the top 80% of 

VOC emissions), then as long as the source has emissions of one of the B, F, A or M 

pollutants, then it can be integrated. 

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 

B 2461850000

Solvent Utilization;Miscellaneous Non-industrial: 

Commercial;Pesticide Application: Agricultural 

profile has no benzene. Benzene came from 

solvent utilization data (Fredonia) for "other 

markets" for the year 1998. Consider 

changing this to no-integrate in the future 

since benzene no longer allowed in pesticides.

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. 
55

minimum 

HAP(s) 

needed 

SCC Tier 3 SCC Tier 3 Description Comments 

M 2460200000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer and Commercial;All Household Products

profile is 3146 contains only nonzero 

methanol. 

any 1 HAP 2415000000

Solvent Utilization;Degreasing;All Processes/All 

Industries 

profile 8745 (non legacy but composite made 

up of a bunch of E-rated profiles )has M, B. 

M 2401002000

Solvent Utilization;Surface Coating;Architectural 

Coatings - Solvent-based profile 3139 has only M 

nointegrate 2401020000

Solvent Utilization;Surface Coating;Wood 

Furniture: SIC 25 profile 2405 has no HAP 

B 2505040000

Storage and Transport;Petroleum and Petroleum 

Product Transport;Pipeline 

any 1 HAP 2610030000

Waste Disposal, Treatment, and Recovery;Open 

Burning;Residential profile 0121 is old and has only hexane. 

any 1 HAP 2610000000

Waste Disposal, Treatment, and Recovery;Open 

Burning;All Categories profile 0121 is old and has only hexane. 

FAM 2401003000

Solvent Utilization;Surface Coating;Architectural 

Coatings - Water-based profile 3140 has FAM 

M 2460100000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer and Commercial;All Personal Care 

Products 

profile (3247, nonlegacy based on CARB 

1997 survey) has no M or B. However, 

Freedonia was used for M. 

M 2465200000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer;Household Products 

M 2415300000

Solvent Utilization;Degreasing;All Industries: Cold

Cleaning 

profile 8745 (non legacy but composite made 

up of a bunch of E-rated profiles )has M, B. 

any 1 HAP 2401040000

Solvent Utilization;Surface Coating;Metal Cans: 

SIC 341 

profile 2408 has none. - no HAPs in NEI so 

this SCC will not have any integrated sources

any 1 HAP 2401050000

Solvent Utilization;Surface Coating;Miscellaneous 

Finished Metals: SIC 34 - (341 + 3498) 

SPEC PROFILE 3127 has none - no HAPs in 

NEI so this SCC will not have any integrated 

sources 

any 1 HAP 2401200000

Solvent Utilization;Surface Coating;Other Special 

Purpose Coatings 

profile 3138 has methanol. Not legacy. 

0.11% aerosol coatings. 

B 2461800000

Solvent Utilization;Miscellaneous Non-industrial: 

Commercial;Pesticide Application: All Processes 

3001 is speciation profile (not legacy) "D" 

rating 2004. Calif. Testing for speciation 

profile from 2000. Has NO benzene! 

Benzene came from solvent utilization data 

(Fredonia) for "other markets" for the year 

1998. 

M 2460800000

Solvent Utilization;Miscellaneous Non-industrial: 

Consumer and Commercial;All FIFRA Related 

Products 3145 has M only and just a 0.01% 
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 2002 platform. 

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. 
57

Table 3-6. Temporal Settings Used for the Platform Sectors in SMOKE

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 aveday aveday 

biog hourly n/a n/a 

ptfire daily all all 

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 2005 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 2005 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. 

3.2.1 Spatial allocation ancillary files 

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 2002 Platform. For Canada, for which we 

used a 2006 inventory, we used a new set of Canadian surrogates provided by Environment 

Canada along with their emissions data. 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) websites (see the end of Section 1). 

• 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 

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

resolution for Canadian surrogates 

• ancillary_2005v4_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 
59

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 66 spatial surrogates available for spatially allocating U.S. county-level emissions to 

the CMAQ 36-km and 12-km grid cells; they are the same as for the 2002 Platform. As 

described in Section 3.3.1.2, 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 2002 and 2005 Platforms 

Code Surrogate Description Code Surrogate Description 

N/A Area-to-point approach (see 3.3.1.2) 515 Commercial plus Institutional Land 

100 Population 520 Commercial plus Industrial plus Institutional 

110 Housing 525

Golf Courses + Institutional +Industrial + 

Commercial 

120 Urban Population 527 Single Family Residential 

130 Rural Population 530 Residential - High Density 

137 Housing Change 535

Residential + Commercial + Industrial + 

Institutional + Government 

140 Housing Change and Population 540 Retail Trade 

150 Residential Heating - Natural Gas 545 Personal Repair 

160 Residential Heating - Wood 550 Retail Trade plus Personal Repair 

165

0.5 Residential Heating - Wood plus 0.5 Low 

Intensity Residential 555

Professional/Technical plus General 

Government 

170 Residential Heating - Distillate Oil 560 Hospital 

180 Residential Heating - Coal 565 Medical Office/Clinic 

190 Residential Heating - LP Gas 570 Heavy and High Tech Industrial 

200 Urban Primary Road Miles 575 Light and High Tech Industrial 

210 Rural Primary Road Miles 580 Food, Drug, Chemical Industrial 

220 Urban Secondary Road Miles 585 Metals and Minerals Industrial 

230 Rural Secondary Road Miles 590 Heavy Industrial 

240 Total Road Miles 595 Light Industrial 

250 Urban Primary plus Rural Primary 596 Industrial plus Institutional plus Hospitals 

255 0.75 Total Roadway Miles plus 0.25 Population 600 Gas Stations 

260 Total Railroad Miles 650 Refineries and Tank Farms 

270 Class 1 Railroad Miles 675 Refineries and Tank Farms and Gas Stations 

280 Class 2 and 3 Railroad Miles 700 Airport Areas 

300 Low Intensity Residential 710 Airport Points 

310 Total Agriculture 720 Military Airports 

312 Orchards/Vineyards 800 Marine Ports 

320 Forest Land 807 Navigable Waterway Miles 

330 Strip Mines/Quarries 810 Navigable Waterway Activity 

340 Land 850 Golf Courses 

350 Water 860 Mines 

400 Rural Land Area 870 Wastewater Treatment Facilities 

500 Commercial Land 880 Drycleaners 

505 Industrial Land 890 Commercial Timber 
60

Code Surrogate Description Code Surrogate Description 

510 Commercial plus Industrial 

We did not use all of the available surrogates to spatially allocate sources in the 2002 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 

2002 Platform documentation and is not be 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. 

The new onroad off-network (parking area) emissions from the MOVES model, new to the 2005 

platform, were allocated as shown in Table 3-8. 

Table 3-8. Surrogate assignments to new mobile categories in the 2005 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 thru 8B & Buses 

(HDGV)- parking areas rural 

2201070370 Heavy Duty Gasoline Vehicles 2B thru 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 2002 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 
61

coordinates to support finer scale modeling that was done under a different project. We chose to 

retain the updated file for the 2005 Platform. 

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 2005 Platform with the exception of the nonpoint Canadian mercury emissions. 

The updated set completely replaced the 2002 Platform surrogates for allocating the 2006 

province-level Canadian emissions. The 2002 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 

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 CA_921_NOFILL.txt cement industries CA_972_FILL.txt 
62

Surrogate 

description 

Filename of 2005 

Platform Surrogate 

Surrogate 

description 

Filename of 2005 

Platform Surrogate 

AGRFORFISH and 

MANUFACT 

Intersection of Forest 

and Housing 

CA_922_NOFILL.txt 

chemical industries CA_973_FILL.txt 

Intersection of 

MININGOILG and 

MANUFACT 

CA_923_NOFILL.txt 

commercial fuel 

combustion CA_974_FILL.txt 

Intersection of 

UTILITIES and 

DWELLING 

CA_924_NOFILL.txt 

downstream petroleum 

industries CA_975_FILL.txt 

Intersection of 

CONSTRUCTION and 

DWELLING 

CA_925_NOFILL.txt 

Electric utilities CA_976_FILL.txt 

Intersection of 

PUBADMIN and 

DWELLING 

CA_926_NOFILL.txt 

grain industries CA_977_FILL.txt 

Commercial Marine 

Vessels 

CA_928_NOFILL.txt manufacturing 

industries1 CA_978_FILL.txt 

HIGHJET CA_929_NOFILL.txt mining industries CA_979_FILL.txt 

LOWMEDJET CA_930_NOFILL.txt smelting industries CA_981_FILL.txt 

OTHERJET CA_931_NOFILL.txt waste management CA_982_NOFILL.txt 

CANRAIL CA_932_NOFILL.txt construction industries1 CA_984_NOFILL.txt 

LDGV 

CA_934_NOFILL.txt construction and 

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) were the same as were used in the 

2002 Platform. 

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_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). 
63

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 2005 Platform. 

We prepared two different INVTABLE files to use with different sectors of the platform. For 

sectors in which we chose no integration across the entire sector (see Table 3-5), we created a 

“no HAP use” INVTABLE that set the “KEEP” flag to “N” for BAFM. Thus, any BAFM 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 Error! Reference source not found.sector-specific NHAPEXCLUDE files 

that provide the specific sources that are excluded from integration (see Table 3-5). Due to a 

limitation with SMOKE2.4, we needed to provide an NHAPEXCLUDE file even for sectors for 

which we integrate all sources in the sector. In this case, we included a source in the file that 

was not contained in the inventory (this SMOKE limitation has since been resolved). 

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 B, A, F and M 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 
64

(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. The 2002-based platform utilized an earlier 

version, SPECIATE4.0. Note that this update did not impact the PM2.5 profiles we used with the 

2005-based platform; they were the same as those used for the 2002-based platform. 

As with SPECIATE4.0, SPECIATE 4.2 development was a collaboration involving EPA’s ORD 

and EPA’s Office of Air Quality Planning and Standards (OAQPS) at Research Triangle Park, 

NC, 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, 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 

One minor issue we found with the PM2.5 speciation which was similarly an issue with the 2002-

based platform is that we used a bituminous coal combustion profile (92095) that is applicable to 

numerous inventory sources, but we used it for only a single nonpoint SCC (2101002000). For 

the other SCCs pertaining to bituminous coal combustion we used the sub-bituminous coal 

combustion profile (92084). Table 3-10 shows the differences are shown below, though these 

are quite small and represent only a minor change to the SMOKE results: 

Table 3-10. 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

Another issue is that profile 92095 appears to have been inadvertently left out of SPECIATE4.2 

(and 4.0); we obtained it from EPA ORD staff using it in their modeling applications. 

Key changes to the TOG profiles from the 2002 Platform are as follows: 

• Updated the profile for aircraft from 1098 (Aircraft Landing/Takeoff (LTO) – 

Commercial) which is from SPECIATE3.2 and has a profile date of 1989, to 5565 

(Aircraft Exhaust), which has a profile date of 8/2008 and is based on testing conducted 

in 2005). 
65

• Updated the profile for forest fires from 0307 (Miscellaneous Burning - Forest Fires) 

which was from SPECIATE3.2 and has a profile date of 1989) to 5560 (Biomass Burning 

- Extratropical Forest, dated 2/2008 and was based on testing conducted in 2001) 

• Changed the assignment of residential wood combustion (including woodstove and 

fireplace emissions) and other profiles that formerly used 4641 (Fireplace wood 

combustion-oak wood) to 4642 (Fireplace wood combustion-pine wood) because of all 

three woods tested in the study (oak, pine and eucalyptus), the most complete testing was 

done for the pine wood (for example, benzene was only measured for pine) 

• Updated the profiles for mobile onroad and nonroad sources to use more up-to-date test 

data. The updated profiles are: 

o 8750: Gasoline Exhaust – Reformulated gasoline 

o 8751: Gasoline Exhaust – E10 ethanol gasoline 

o 875213: Gasoline Exhaust – E85 ethanol gasoline 

o 8753: Gasoline Vehicle - Evaporative emission - Reformulated gasoline 

o 8754: Gasoline Vehicle - Evaporative emission - E10 ethanol gasoline 

o 87559

: Gasoline Vehicle - Evaporative emission - E85 ethanol gasoline 

o 87569,14: Composite Profile for Tier 2 vehicles E0, exhaust 

o 87579,10: Composite Profile for Tier 2 vehicles E10, exhaust 

• Utilized combination profiles comprised of the above updated exhaust and evaporative 

profiles to match the average ethanol content of fuels used by different counties and for 

different months of the year. Combinations were created based on the fuel properties 

data in the NMIM county database. 

Table 3-11 provides a summary of the 2005 speciation approach for mobile and other fuelrelated sources. It shows the updated profiles that form the 2005 combinations. The headspace 

profile, 8737 is the same as was used in the 2002 Platform, and is used for other nonroad 

refueling and other fuel-related stationary source emission categories. 

Table 3-11. 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 

 

13 Profile not used in 2005, but used in future years built off of the 2005 base year. 

14 Profile not included in SPECIATE4.2 (Nov. 2008), per OTAQ documentation, profiles were created October 

2008, by OTAQ with EPAct Phase 1 data, 22 out of 22 valid test cycles. Three vehicles tested: Honda Civic, 

Toyota Sienna, Chevy Silverado. Composite emission factors calculated using straight weighting for an LA92 drive 

cycle (1.19 miles, 8.63 miles, 1.19 miles for Bags 1,2 and 3, respectively). 
66

Inventory 

type and 

mode 

VOC speciation 

approach 

for fuels 

VOC 

Profile 

Codes 

2005 

sectors 

Mobile nonroad Refueling 

Stationary (no mode assigned 

to VOC): Portable Fuel 

Containers, bulk plant -topump, refinery-to-bulk 

terminal 

E0 

8737 (Composite 

Profile – Nonoxygenated 

Gasoline 

Headspace 

Vapor) 

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 a subsequent version of this document. In summary, 

we utilized additional profiles in the combinations. The profiles we added were E85 and Tier 2 

profiles for E0 and E10. One error (affecting the 2012, 2022 and 2030 future years) is that we 

used the same onroad and nonroad profiles in the future years. The nonroad profiles in future 

years should not include any Tier2 vehicles (since Tier 2 impacts only onroad) and should not 

include any E85. 

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 

CMAQ 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 CMAQ were generally based on the temporal 

allocation data used for the 2002 Platform. We added new profile assignments for SCCs in the 

2005 inventory that were not in the 2002 inventory, and we updated the profiles used for ptipm 

sources without CEM data to represent the year 2005. 

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

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 in capital 

letters in parentheses: 

• ancillary_2005v4_smokeformat.zip: includes temporal cross reference files used across

all inventory sectors (ATREF, MTREF, and PTREF) and for ptipm sector (used for 
67

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 2005 

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 SCCs15 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 new SCCs and descriptions, along with the assignments chosen are shown in Table 3-12. 

Figure 3-3 shows the diurnal profiles referred to in the table. 

 

15 See Table 2-9: 2310000220, 2310000330, 2310000440, 2310010100, 2310010200, 2310010300, 2310010700, 

2310010800, 2310020600, 2310020700, 2310020800, 2310021100, 2310021300, 2310021400, 2310021500, 2310021600, 

2310023000, 2310030210, 2310030220
68

Table 3-12. Temporal Profiles Assigned to New Onroad SCC from the Draft MOVES model: 

Parking Areas 

SCC & Description Temporal Profile: 

Monthly 

Variation 

Temporal Profile: 

Day of Week Variation 

Temporal Profile: 

Diurnal variation 

2201001350 

Light Duty Gas Vehiclesparking areas rural 

2201002350 Light Duty 

Gas Trucks 1&2- parking 

areas rural 

2201004350 Light Duty 

Gas Trucks 3&4- parking 

areas rural

Not applicable – 

will be receiving 

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. 

Code = 2006 (see 

Figure 3-3. 

Diurnal Profiles 

are based only on 

road type (use 

local for “start”) 

and whether the 

road is urban 

versus ruralFigure 

3-3, reddish curve) 

2201001370 

Light Duty Gas Vehiclesparking areas urban 

2201002370 Light Duty 

Gas Trucks 1&2- parking 

areas urban

2201004370 Light Duty 

Gas Trucks 3&4- parking 

areas urban

Not applicable – 

will be receiving 

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. 

Code = 2012 (see 

Figure 3-3, yellow 

curve) 

2201070350 

Heavy Duty Gasoline 

Vehicles 2B thru 8B & 

Buses (HDGV)- parking 

areas rural 

Not applicable – 

will be receiving 

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) 

2201070370 

Heavy Duty Gasoline 

Vehicles 2B thru 8B & 

Buses (HDGV)- parking 

areas urban 

Not applicable – 

will be receiving 

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) 
69

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

road is urban versus rural 

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

4 Development of Future Year Emission Inventories 

This section will be completed at a later date. Please also see rule-specific documentation, such 

as the Transport Rule’s Emission Inventory Technical Support Document. 
70

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