## 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 Houyouxii 

## 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 P OINT SOURCES ( PTIPM AND PTNONIPM ) .................................................. .................................10
2.1.1 IPM sector (ptipm).................................

................................................... ...........................................12
2.1.2 Non-IPM sector (ptnonipm)..........................

................................................... ....................................14
2.2 2005 N ONPOINT 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 F IRES ( PTFIRE AND AVEFIRE )..................................................

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

................................................... ..................................22
2.3.2 Average fires (avefire) ............................

................................................... ..........................................26
2.4 B IOGENIC SOURCES ( BIOG )..................................................

................................................... ...................28
2.5 2005 M OBILE SOURCES ( ON

_ NOADJ

, ON

_ MOVES

_ RUNPM

, ON

_ MOVES

_ STARTPM

, NONROAD

, ALM

_ NO

_ C 3,

SECA

_ C 3).................................................

................................................... ................................................... ..........29
2.5.1 Onroad mobile MOVES cold-start exhaust sources requ iring temperature adjustments (on_moves_startpm).................................

................................................... ................................................... ....31
2.5.2 Onroad mobile MOVES running exhaust sources requiri ng 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 comm ercial marine (alm_no_c3) ........................36
2.5.6 Nonroad mobile sources: C3 commercial marine (seca _c3)............................................... ...............38
2.6 E MISSIONS FROM C ANADA

, M EXICO AND O FFSHORE D RILLING P LATFORMS ( 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 K EY 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 E MISSIONS 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.........................................

................................................... ................................................... ..70iii 

## 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
CAM X 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 emissi ons factors
MOVES Motor Vehicle Emissions Simulator -- OTAQ’s model f or 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 Pollu tants NH 3 Ammonia

nm nautical mile
NMIM National Mobile Inventory Model
NOAA National Oceanic and Atmospheric Administration
NONROAD OTAQ’s model for estimation of nonroad mobile emiss ions
NO X 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 co ntrols
PFC Portable Fuel Container
PM 2.5 Particulate matter less than or equal to 2.5 micron s PM 10 Particulate matter less than or equal to 10 micronsiv

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 Fir e Incident Reconciliation
SMOKE Sparse Matrix Operator Kernel Emissions
SO 2 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 Partnershipv 

## List of Tables

Table 2-1. Platform sectors used in emissions mode ling 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 Pl atform 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 ....................... 1 7
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 emissio ns 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 i n 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 avefir e PM 2.5 emissions ....................................... 27 Table 2-15. Pollutants covered by the draft MOVES model in the 2005 Platform 1 .................... 29 Table 2-16. SCCs in the 2005 alm_no_c3 inventory c ompared 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 20 02 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 CB0 5 with SOA for CMAQ4.7................ 50 Table 3-4. Integration status of benzene, acetalde hyde, formaldehyde and methanol (BAFM) for each platform sector...............................

................................................... ............................ 53 Table 3-5. Source-category specific criteria for i ntegrating 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 cat egories in the 2005 Platform..................... 60 Table 3-9. Canadian Spatial Surrogates for 2005-bas ed platform Canadian Emissions .............. 61 Table 3-10. Differences between two profiles used for coal combustion................................ .... 64 Table 3-11. Summary of VOC speciation profile appr oach by sector for 2005.......................... 65 Table 3-12. Temporal Profiles Assigned to New Onro ad SCC from the Draft MOVES model: Parking Areas......................................

................................................... ............................... 68vi 

## List of Figures

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

................................................... ...................... 24 Figure 2-2. MOVES exhaust temperature adjustment f unctions........................................... ...... 32 Figure 3-1. CMAQ modeling domains ..................

................................................... .................... 48 Figure 3-2. Process of integrating BAFM with VOC f or use in VOC Speciation....................... 52 Figure 3-3. Diurnal Profiles are based only on roa d type (use local for “start”) and whether the
road is urban versus rural.........................

................................................... .......................... 69



## List of Appendices

Appendix A. Methodology to Revise VOC from Residen tial Wood Combustion Appendix B. Methodology to Speciate Partially-Spec iated MOVES PM2.5 Emissions1



## 1 Introduction

The U.S. Environmental Protection Agency (EPA), her eto referred to as “we,” has developed a 2005-based air quality modeling platform. This doc ument describes the emissions inventory and emissions modeling for a version of the platform co nsisting 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-BAF M 2005-Based Platform, Version 4” platform, since it is primarily a CAP platform, wit h BAFM and Hg included. The reason it is “Version 4” is that it has been updated from the 20 02-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 t he approach and data used to produce the emission inputs to the air quality models used in t he 2005 Platform. A version of the 2005-based platform that contains additional HAPs is documente d as part of the Revised Annual Renewable Fuel Standard (RFS2) rule (EPA, 2010).

Emissions preparation for the 2005 Platform support s 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 (C AMx) ( http://www.camx.com/ ). Both models support modeling ozone (O 3 ) and particulate matter (PM) and require hourly an d gridded emissions of chemical species from the following in ventory pollutants: carbon monoxide (CO), nitrogen oxides (NO X ), volatile organic compounds (VOC), sulfur dioxide (SO 2 ), ammonia (NH 3 ), particulate matter less than or equal to 10 micr ons (PM 10 ), and individual component species for particulate matter less than or equal t o 2.5 microns (PM 2.5 ). 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 em issions 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 in clude Hg for 2005.

The effort to create the emission inputs for the 20 05 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 fil es 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) mod eling 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 ai r observations to assess the ability of the air quality model to estimate ambient air conce ntrations of ozone and PM 2.5 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): T he purpose of this case is to provide
a 2005 case that is consistent with the methods use d in the future-year base case and control cases. For regulatory applications, this c ase is included in the RRF calculations.

A final version of this documentation will also con tain 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 docum ented as part of those rules (e.g., RFS2, Light Duty Greenhouse Gas Rule).

There are two differences between the 2005 evaluati on and the 2005 base case. The evaluation case uses 2005-specific fire emissions and 2005 hou r-specific continuous emission monitoring (CEM) data for electric generating units (EGUs). T he 2005 base case includes an “average year” scenario for fires, described in Section 2.3.2. F or EGUs, the base case allocates the 2005 emissions to days and hours using a different appro ach; this method is also used when creating the future-year emissions.

The version 4 2005-based Platform builds upon the c oncepts, tools and emissions modeling data from EPA’s version 3 2002-based Platform, documente d by: http://www.epa.gov/scram001/reports/Emissions%20TSD %20Vol1_02-28-08.pdf

A summary of the key differences between the 2005 P latform and the 2002 Platform are provided in Table 2-1.

This document contains five sections and two append ices. Section 2 describes the 2005 inventories input to SMOKE. Section 3 describes th e 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 (pr ojected 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 t he 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 sub section entitled “CAP-BAFM 2005-Based
Platform”. This is referred to as the “2005v4 webs ite” throughout this document.



## 2 2005 emission inventories and approaches

This section describes the 2005 emissions data crea ted for input to SMOKE. The primary basis for the 2005 emission inputs for the version 4 Plat form is the 2005 National Emission Inventory (NEI), version 2, which includes emissions of CO, N O X , VOC, SO 2 , NH 3 , PM 10 , PM 2.5 and hazardous air pollutants (HAPs). The 2005 platform utilizes select HAPs: the base version includes chlorine, HCl, Hg, benzene, acetaldehyde, formaldehyde, and methanol. The RFS23

version of the platform (EPA, 2010) utilized the fo llowing 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 inventorie s outside of the United States, which include Canada and Mexico, we used the latest available bas e-year inventories as discussed in Section
2.6

.

The 2005 NEI includes five sectors: nonpoint (form erly called “stationary area”) sources, point sources, nonroad mobile sources, onroad mobile sour ces, and fires. The fires portion of the inventory includes emissions from wildfires and pre scribed burning computed as hour-specific point sources. For purposes of preparing the CMAQ- ready emissions, we split the 2005 emissions inventory into several additional “platfo rm” sectors for use in emissions modeling, and we added biogenic emissions, emissions from the Can adian 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 thr ough 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 temporal ized 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 s ector only for the 2005 model performance evaluation. We used the avefire platform sector fo r all modeling cases except for the model performance evaluation. The rationale for using av erage 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 SMO KE

IPM sector: ptipm Point 2005v2 NEI point source EGUs mapped to the In tegrated Planning Model (IPM) model using the National Electric Energ y Database System (NEEDS, 2006 version 3.02) database. Hourly files for continuous emission monitoring (CEM) sources are in cluded only for the 2005 evaluation case. Day-specific emissions f or non-CEM sources created for input into SMOKE.

Non-IPM sector: ptnonipm Point All 2005v2 NEI point source records not match ed to the ptipm sector,
annual resolution. Includes all aircraft emissions

. Point source fire

sector: ptfire Fires Point source day-specific wildfires and presc ribed fires for 2005. This sector used only for the 2005 evaluation case. Average-fire

sector: avefire N/A Average-year wildfire and prescribed fire emiss ions derived from the 2002 Platform avefire sector, county and annual res olution. 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 SMO KE

Agricultural

sector: ag Nonpoint NH 3 emissions from NEI nonpoint livestock and fertiliz er application, county and annual resolution. Area fugitive dust

sector: afdust Nonpoint PM 10 and PM 2.5 from fugitive dust sources from the NEI nonpoint inventory (e.g., building construction, road constr uction, paved roads, unpaved roads, agricultural dust), county and annua l resolution. Remaining nonpoint sector: nonpt Nonpoint Primarily 2002 NEI nonpoint sources not ot herwise 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-BondBa se for all states except California. Monthly emissions fo r California created from annual emissions submitted by the California A ir 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 cat egory 1 and

category 2 commercial marine vessel (CMV) emissions sources, county and annual resolution. Unlike prior platfor ms, aircraft emissions are now included in the ptnonipm sector a nd category 3 CMV emissions are now contained in the seca_c3 sect or C3 commercial
marine: seca_c3 Mobile :

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

emissions, developed for the EPA rule called “Contr ol of Emissions from New Marine Compression-Ignition Engines at or Above 30 Liters per Cylinder”, usually described as the Emis sion Control Area (ECA) study, originally called SO 2 (“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 t han
for California. 2) California onroad, created using annual emissions s ubmitted by CARB for the 2005v2 NEI. 3) Onroad gasoline non-motorcycle vehicle emissions fr om draft MOVES not subject to temperature adjustments: exha ust CO,
NO X , 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 adjustmen ts. 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 adjust ment 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 adjustmen ts. 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 adjust ment curves from cold start exhaust (see on_moves_startpm sector).5

Platform Sector 2005 NEI

Sector Description and resolution of the data input to SMO KE

Biogenic: biog N/A Hour-specific, grid cell-specific emissions gen erated from the
BEIS3.14 model -includes emissions in Canada and Me xico. 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 a nnual 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) a nd year 1999 Mexico Phase III (municipio resolution) nonpoint and nonro ad 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 inventorie s, 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 Sec tion 1) under the link “Data Files” (see “2005emis”directory). The “readme” file provided i ndicates the particular zipped files associated with each platform sector.

Before discussing the specific components of the 20 05 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 so urces migrate to different sectors. Table
2-2 does not discuss the modifications to these inv entories for emissions modeling; these details are provided in the sections that follow.6

Table 2-2. Summary of significant changes between 2002 and 200 5 Platforms by sector

Platform Sector Summary of Significant Inventory Di fferences 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 tem poral information based on years 2004 through 2006, rather than 2001 throug h 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 a lm_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 burn ing emissions for 2005. The

2002 platform contained some county-level monthly p rescribed burning emissions that were included in the nonptfire secto r. In contrast, all 2005 fires data used for modeling are resolved as point source s at day-specific temporal resolution. Therefore, there is no nonptfire secto r 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 BA FM model species from solely speciating VOC as was done in the 2002 CAP-o nly 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 f actor from PM 2.5 ; 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 PM 2.5 , 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 followi ng: 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 c orrected for all states except California, and, VOC HAPs computed; 3) HCl corrections made to GA, UT, and VA for Industri al and Commercial/Institutional coal-fueled boilers; 4) Use BAFM emissions from the inventory as part of VO C speciation for
some sources in this sector. 1

Nonroad sector:
nonroad 2002 platform emissions replaced with 2005 NEI vers ion 2 emissions. 1) California 2002v3 emissions replaced with CARB-subm itted 2005v2
emissions with NH 3 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 t he entire sector 1 (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 Di fferences in 2005 Platform locomotive, and
non-C3
commercial
marine: alm_no_c3 Locomotives, and Category 1 and Category 2 CMV emis sions are the same as

2002 Platform alm sector. 2005 Platform does not i nclude 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 surrogat es. Use BAFM emissions from the inventory as part of VO C speciation for some
sources in this sector. 1

C3 commercial
marine: seca_c3 New sector for 2005 Platform. These point source C 3 CMV emissions replace a

subset of the 2002 Platform alm sector emissions, s pecifically, port and underway residual fuel C3 county-level emissions. Use BAFM emissions from the inventory as part of VO C 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 b y CARB, gap-filled
with NMIM NH 3 and allocated to road types using NMIM –based rati os. 2) Draft MOVES (except for California) onroad gasoline emissions for exhaust and evaporative mode for all vehicle types except motorcycles for the pollutants NO X , VOC, CO, benzene, acetaldehyde, formaldehyde, 1,3

- butadiene, acrolein, and naphthalene. 3) All other emissions not covered by (1) and (2) abov e used the 2005 NEI version 2 emissions, except for PM 10 and PM 2.5 emissions included in the on_moves_startpm and on_moves_runpm sectors, as des cribed below. Use BAFM emissions from the inventory as part of VO C 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 e missions subject to grid cell and hourly temperature adjustments. Temperature ad justments for cold starts (here) are different than running mode emissions, h ence 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 emis sions subject to grid cell and hourly temperature adjustments. Temperature ad justments 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 th e 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 e missions.8

Platform Sector Summary of Significant Inventory Di fferences 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 f rom the inventory as part of VOC speciation; this i s one of the changes between the 2005 Platform and th e 2002 Platform for several sectors.

Annual emission summaries for 2005, with comparison s to 2002 CAPs emissions by emissions modeling sector are provided in Table 2-3. VOC tot als are before BAFM speciation; they are inventory VOC emissions, and not the sum of VOC emi ssions after BAFM speciation. Table 2-4 provides a summary of emission changes for CAPs onl y 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 Sec tion 1) under the link “Data Files” (see the “2005emis” directory). The inventories “readme” fi le 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]

NO X [tons/yr]

CO [tons/yr]

SO 2 [tons/yr]

NH 3 [tons/yr]

PM 10 [tons/yr]

PM 2.5 afdust 8,858,989 1,830,273 ag 3,251,990
alm 1,2 123,458 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
onroad 3 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+nonptfire 4 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_c3 1,2 67,690 1,924,925 270,007 154,016 773 59,366 56,687 seca_c3 1,2,5 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_noadj 3 3,123,642 7,203,876 41,647,066 144,216 295,203 170,554 115,991

on_moves_runpm 3 46,430 42,753
on_moves_startpm 3 23,607 21,738 ptipm 40,950 3,728,190 601,564 10,381,411 21,684 615,095 508,903 ptnonipm 2 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%

alm 1,2 -27% 14% -60% 83% -14% 16% 22%
nonpt -6% 10% -2% 0% -1% -2% -2%

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

onroad 3 -36% -7% -30% -40% 2% 20% 24% ptipm -3% -19% -1% 0% -28% 1% 1% ptnonipm 2 -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 consis ts of onroad from 2002 platform and aggregates on_n oadj, on_moves_runpm, and on_moves_startpm from the 2005 platform. 4 – nonptfire emissions are in the 2002 platform on ly; these are covered by the ptfire sector in the 2 005 platform. 5 – only U.S. state/county seca_c3 emissions are in cluded here; emissions outside the (up to) 200nm of fshore boundary and international boundaries, while includ ed in our modeling, are not included in these summa ries.10

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

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

Year Sector [tons/yr]
VOC [tons/yr]

NO X [tons/yr]

CO [tons/yr]

SO 2 [tons/yr]

NH 3 [tons/yr]

PM 10 [tons/yr]

PM 2.5 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 othar 1 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 othar 1 -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 i nclude 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 f or different sectors depending on the availability of reference information for the data, the degree o f changes or manipulation of the data needed for preparing it for input to SMOKE, and whether th ese 2005 platform emissions changed appreciably since the previously-documented 2002 pl atform.



### 2.1 2005 NEI Point sources (ptipm and ptnonipm)

Point sources are sources of emissions for which sp ecific geographic coordinates (e.g., latitude/longitude) are specified, as in the case o f an individual facility. A facility may have multiple emission points, which may be characterize d as units such as boilers, reactors, spray booths, kilns, etc. A unit may have multiple proce sses (e.g., a boiler that sometimes burns residual oil and sometimes burns natural gas). Not e that this section describes only contiguous11

U.S. NEI point sources. The offshore oil platform (othpt sector) and category 3 CMV emissions (seca_c3 sector) are point source formatted invento ries, 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 (ptnoni pm). This split facilitates the use of different SMOKE temporal processing and future year projection techniques for these sectors. The inventory pollutants processed through SMOKE fo r both ptipm and ptnonipm sectors were: CO, NO X , VOC, SO 2 , NH 3 , PM 10 , PM 2.5 and the following HAPs: HCl, Hg and Cl. We did n ot utilize BAFM from these sectors as we chose to spec iate 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 an nual emissions. The ptipm emissions
used in 2005 were different for the model evaluatio n case and for the base case. For the model evaluation case, those ptipm sector sources with CE M data (that we could match to the NEI) used hourly SO 2 and NO X emissions and annual emissions of all other pollut ants. The hourly data also contained heat input, which was used to a llocate 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 d aily 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 obtain ed from emissions/heat input from EPA'S Acid Rain Program. The following approach ap plied 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,

PM 2.5 , HCL) unit-specific ratios of 2005 to 2002 heat in put were applied to 2002 NEI v3

emissions to obtain 2005 estimates.

2. Non-EGU Stationary Source enhancements focused on i mproving the following sectors:

a. HAP data received from States and industry to suppo rt the MACT program, including the recent Risk and Technology Review rul emaking
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 mis sing facilities and pollutants
d. Off-shore platform data from Mineral Management Ser vices (MMS)

The changes made to the NEI point sources prior to modeling are as follows:

• The tribal data, which do not use state/county Fede ral Information Processing Standards (FIPS) codes in the NEI, but rather use the tribal code, were assigned a state/county FIPS12

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 source s 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 par ameters 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 containe d 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 th e 2005 NEI version 2 point inventory that
we were able match to the units found in the 2006 N EEDS database, version 3.02 ( http://www.epa.gov/airmarkets/progsregs/epa-ipm/ind ex.html ), which is used by the IPM, version 3.02. The IPM model provides future year e mission 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 sou rces and future year EGU emissions for sources which are forecasted by IPM and (2) avoid d ouble counting in projecting point source
emissions.

The 2005 NEI point source inventory contains emissi ons estimates for both EGU and non-EGU sources. The IPM is used to predict the future yea r emissions for the EGU sources. The remaining non-EGU point sources are projected by ap plying 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) thos e that are not. This procedure prevents double-counting or dropping significant emissions w hen creating the future-year emissions. The matching process relies on imperfect data; conseque ntly, 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 bec ause 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 sp lits identified for the 2002 NEI (step 1) and then included additional steps to apply these to th e 2005 NEI.

Methodology to split the EGU from the non-EGU sourc es

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 docum entation previously referenced. Since
some source identifiers are held constant between t he 2002 and 2005 NEI, particularly “NEI13

Unique ID”, we were able to more easily compare the two inventories to ensure that we made improvements in the 2005 matching rather than inadv ertent omissions.

Step 2: Create the 2005 NEI v2 point modeling inve ntory 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 follo ws are the issues and how we resolved them, and these represent differences between the publish ed 2005 v2 NEI and what we used for modeling.

1) We identified facilities added with HAP emissions r ecords that were clearly EGUs, but had not been flagged as “IPM” sources. These facil ities had facility identifiers (i.e., plant IDs) beginning with “EGU”. We further confirmed th at these records were EGU emissions; and therefore, we moved these units to t he ptipm sector.

2) We found one additional unit with HAP emissions rec ords 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 an d 2005 and had not initially been removed in the development of the 2005v2 NEI; we re moved these based on a list from the NEI developers.

4) Inspection of CEM and 2005 NEI v2 point inventory r evealed some duplication of sources with state and non-state reported data. Th is can occur because EPA created the EGU records in the 2005 NEI, but the states sometim es still submitted these emissions records. We removed these duplicates.

5) ORIS facility and boiler codes (used to match to th e CEM hourly data) were unintentionally dropped between a preliminary and f inal 2005 NEI v2 point dataset. We completely repopulated these ORIS facility and boil er codes based on what we had in
hand.

Creation of temporally resolved emissions for the p tipm 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 SMO KE. The ptipm sector uses the available hourly CEM data via a method first implemented in t he 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 website 2

. The SMOKE modeling system matches the ORIS Facility and Boiler IDs in the NEI SMOKEready file to the same fields in the CEM data. Thi s allowed us to use the hourly SO 2 and NO X 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?fusea ction=emissions.wizard14

data to allocate the NEI annual values for all othe r pollutants from CEM sources, because hourly data for these other pollutants are not available w ith the hourly CEM data.

For sources not matching the CEM data (“non-CEM” so urces), we computed daily emissions from the NEI annual emissions using a structured qu ery 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 fac tors, 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 dev elopment of these diurnal ptipm-specific profiles, which are considered ancillary data for S MOKE, 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 t o 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) sector 3 . The ptnonipm sector contains fugitive dust PM em issions from vehicular traffic on paved or unpaved roads at indu strial facilities or coal handling at coal mines 4

. Prior to input to SMOKE, we reduced the fugitive du st PM emissions to estimate the emissions that remain aloft by applying county-specific fugit ive dust transportable fraction factors. This is
discussed further in Section 2.2.1.

For some geographic areas, some of the sources in t he ptnonipm sector belong to source categories that are contained in other sectors. Th is occurs in the inventory when states, tribes or local programs report certain inventory emissions a s 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 2 005 NEI, examples of these types of sources include: aircraft emissions in all states, waste d isposal emissions in several states, firefighting training in New Mexico, several industrial processe s and solvent utilization sources in North Carolina and Tennessee, livestock (i.e., animal hus bandry) in primarily Kansas and Minnesota, and petroleum product working losses.

The most significant changes we made to the ptnonip m emissions involved moving some HAP records that should have been flagged as IPM into t he ptipm sector (discussed in section 2.1.1). The other modifications are listed here and represe nt 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 s eparate sectors, as discussed in sections 2.6 and 2.3.1, respectivel y.
4 Point source fugitive dust emissions, which represe nt 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 3 0777; the “777” county FIPS represents portable facilities that move across cou nties, 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 th at had a state/county FIPS code mismatch with their inventory coordinates greater t han 10 km and emissions greater than 10 tons per year of either NO X , VOC, SO 2 , or 5 tons/yr of PM 2.5 . These corrections were limited to a small number of plants in Arizona, Ind iana, 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 rem oved 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 anti cipate 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 dat a for allocation of tribal data to grid cells during the SMOKE processing, with little expected i mpact.

The documentation for the nonpoint sector of the 20 05 NEI is available at: http://www.epa.gov/ttn/chief/net/2005inventory.html

In the rest of this section, we describe in more de tail 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 no t change.



### 2.2.1 Area Fugitive dust sector (afdust)
The area-source fugitive dust (afdust) sector conta ins PM 10 and PM 2.5 emission estimates for 2002 NEI nonpoint SCCs identified by EPA staff as d ust 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. Cate gories included in this sector are paved roads, unpaved roads and airstrips, construction (r esidential, industrial, road and total), agriculture production and all of the mining 10-dig it 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 base d on SCCs and pollutant codes (i.e., PM 10 and PM 2.5 ) that are considered “fugitive”. A complete list of all possible fugitive dust SCCs (including both 8-digit point source SCCs and 10-di git 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 that16

comprise the 2005 (2002) platform afdust sector (wh ich 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 Airstrip s;Total
2294000000 Mobile Sources;Paved Roads;All Paved Roa ds;Total: Fugitives 2296000000 Mobile Sources;Unpaved Roads;All Unpaved Roads;Total: Fugitives 2296005000 Mobile Sources;Unpaved Roads;Public Unpa ved Roads;Total: Fugitives 2296010000 Mobile Sources;Unpaved Roads;Industrial Unpaved Roads;Total: Fugitives
2311000000 Industrial Processes;Construction: SIC 1 5 - 17;All Processes;Total
2311010000 Industrial Processes;Construction: SIC 1 5 - 17;Residential;Total
2311010040 Industrial Processes;Construction: SIC 1 5 - 17;Residential;Ground Excavations
2311010070 Industrial Processes;Construction: SIC 1 5 - 17;Residential;Vehicle Traffic
2311020000 Industrial Processes;Construction: SIC 1 5 - 17;Industrial/Commercial/Institutional;Total 2311020040 Industrial Processes;Construction: SIC 1 5 - 17;Industrial/Commercial/Institutional;Ground

Excavations
2311030000 Industrial Processes;Construction: SIC 1 5 - 17;Road Construction;Total 2325000000 Industrial Processes;Mining and Quarryin g: SIC 14;All Processes;Total 2801000000 Miscellaneous Area Sources;Agriculture P roduction - Crops;Agriculture - Crops;Total 2801000002 Miscellaneous Area Sources;Agriculture P roduction - Crops;Agriculture - Crops;Planting 2801000003 Miscellaneous Area Sources;Agriculture P roduction - Crops;Agriculture - Crops;Tilling 2801000005 Miscellaneous Area Sources;Agriculture P roduction - Crops;Agriculture - Crops;Harvesting 2801000007 Miscellaneous Area Sources;Agriculture P roduction - Crops;Agriculture - Crops;Loading 2805000000 Miscellaneous Area Sources;Agriculture P roduction - Livestock;Agriculture - Livestock;Total 2805001000 Miscellaneous Area Sources;Agriculture P roduction - 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 fractio ns 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 a nd is described by: http://www.epa.gov/ttn/chief/emch/dustfractions/tra nsportable_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, prec ipitation, and wind speeds is not accounted for by the methodology. An electronic version of the c ounty-level transport fractions can be found

at: http://www.epa.gov/ttn/chief/emch/dustfractions/tra nsportfractions052506rev.xls

The 2002 platform documentation describes an error in which the transportable fraction application for PM 2.5 was not applied. This error was fixed for the 200 5 platform, and 2005

PM 2.5 afdust emissions are therefore correctly about 43% less than those in the 2002 platform.



### 2.2.2 Agricultural Ammonia sector (ag)
The agricultural NH 3 “ag” sector is comprised of livestock and agricult ural fertilizer application emissions from the nonpoint sector of the 2002 NEI. This sector is unchanged in the 200517

platform. The rest of this section documentation i s 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 fer tilizer SCCs are listed in Table 2-7.

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

SCC SCC Description*

2805000000 Agriculture - Livestock;Total
2805001100 Beef cattle - finishing operations on feedlots (dry lots);Confinement

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

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

2805002000 Beef cattle production composite;Not Elsewhere Clas sified

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

2805007100 Poultry production - layers with dry manure managem ent systems;Confinement

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

2805008100 Poultry production - layers with wet manure managem ent systems;Confinement

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

2805008300 Poultry production - layers with wet manure managem ent systems;Land application of manure
2805009100 Poultry production - broilers;Confinement
2805009200 Poultry production - broilers;Manure handling and s torage
2805009300 Poultry production - broilers;Land application of m anure 2805010100 Poultry production - turkeys;Confinement

2805010200 Poultry production - turkeys;Manure handling and st orage 2805010300 Poultry production - turkeys;Land application of ma nure 2805018000 Dairy cattle composite;Not Elsewhere Classified
2805019100 Dairy cattle - flush dairy;Confinement
2805019200 Dairy cattle - flush dairy;Manure handling and stor age 2805019300 Dairy cattle - flush dairy;Land application of manu re 2805020001 Cattle and Calves Waste Emissions;Milk Cows

2805020002 Cattle and Calves Waste Emissions;Beef Cows

2805020003 Cattle and Calves Waste Emissions;Heifers and Heife r Calves

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

2805021100 Dairy cattle - scrape dairy;Confinement

2805021200 Dairy cattle - scrape dairy;Manure handling and sto rage 2805021300 Dairy cattle - scrape dairy;Land application of man ure 2805022100 Dairy cattle - deep pit dairy;Confinement

2805022200 Dairy cattle - deep pit dairy;Manure handling and s torage
2805022300 Dairy cattle - deep pit dairy;Land application of m anure 2805023100 Dairy cattle - drylot/pasture dairy;Confinement

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

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

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

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

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

2805030002 Poultry Waste Emissions;Pullets 13 weeks old and ol der 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 Cla ssified18

SCC SCC Description*

2805039100 Swine production - operations with lagoons (unspeci fied animal age);Confinement
2805039200 Swine production - operations with lagoons (unspeci fied animal age);Manure handling and storage
2805039300 Swine production - operations with lagoons (unspeci fied 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 (unspe cified animal age);Confinement

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

2805053100 Swine production - outdoor operations (unspecified animal age);Confinement * All SCC Descriptions begin “Miscellaneous Area So urces;Agriculture Production – Livestock”

The “ag” sector includes all of the NH 3 emissions from fertilizer from the NEI. However, the “ag” sector does not include all of the livestock a mmonia emissions, as there are also significant
NH 3 emissions from livestock in the point source inven tory that we retained from the 2002 NEI. Note that in these cases, emissions were not also i n 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 NH 3 emissions were reported by the states of Kansas an d Minnesota. For these two states, farms with animal operations were provided as point sources using the following SCCs 5 :

• 30202001: Industrial Processes; Food and Agricultu re; Beef Cattle Feedlots; Feedlots

General

• 30202101: Industrial Processes; Food and Agricultu re; Eggs and Poultry Production;

Manure Handling: Dry

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

Classified

There are also livestock NH 3 emissions in the point source inventory with SCCs of 39999999 (Industrial Processes; Miscellaneous Manufacturing Industries; Miscellaneous Industrial Processes; Other Not Classified) and 30288801 (Indu strial Processes; Food and Agriculture; Fugitive Emissions; Specify in Comments Field). We identified these sources as livestock NH 3 point sources based on their facility name. The re ason why we needed to identify livestock NH 3 in the ptnonipm sector was to properly implement th e emission projection techniques for livestock sources, which cover all livestock source s, not only those in the ag sector, but also those in the ptnonipm sector. This will be discuss ed further in Section 4 in the final version of
this documentation.

5 These point source emissions are also identified b y the segment ID, which is one of the following: “S WINE”, “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 Source s; 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-Californ ia Western Regional Air Partnership (WRAP) oil and gas emissions (SCCs begi nning with “23100”) with WRAP year 2005 Phase II oil and gas emissions.

• Residential wood combustion (RWC) emissions were re placed with data for Oregon and New York. This update is consistent with the 2005 N EIv2.

• 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 d iscussed 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 creat ion of the 2002 nonpt sector in great detail, but the rest of this section will simply document w hat has changed for the 2005 platform.

2005 Phase II WRAP oil and gas inventory20

NEI 2002 Industrial Processes, Oil and Gas Producti on 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 2 002 NEI oil and gas nonpt emissions were limited to VOC in Arizona, Montana, Nevada, New Mex ico, North and South Dakota, and Wyoming, and negligible CO and NO X emissions in New Mexico. In contrast, the 2005 WR AP oil and gas inventory contains much higher emission s, 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/2007-1 0_Phase_II_O&G_Final)Report(v10- 07%20rev.s).pdf

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

platforms. Emissions provided in short tons/year.

Pollutant 2002 2005
CO 1 53,784
NOx 31 155,133
SO 2 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 a verage 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, NO X , SO 2 , and VOC. The first two SCC Tier descriptions “Industrial Process es, 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/Workin g/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, Dehydrators21

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/Wo rking/Breathing, Uncontrolled
2310030220 Natural Gas Liquids, Tanks - Flashing & Standing/Wo rking/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 chang es 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 PM 2.5 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 w ood) for fireplaces, which we have subsequently determined overestimated VOC by over a n 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 (M ARAMA) study (Marama, 2006) of 18.9 lbs VOC/ton wood burned, using a series of conditio nal analyses detailed in Appendix A. The conditional part of the changes was required becaus e 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 recal culation on annual national emission totals between the 2002 and 2005 platform is shown in Tabl e 2-10.

Table 2-10. RWC Emissions Changes for CAPs between 2002 and 200 5 platforms.

Emissions values provided in short tons/year.

Pollutant 2002 2005 % Change VOC 1,476,756 40,754 -97.2% NO X 40,707 38,369 -5.7% CO 3,061,043 2,857,985 -6.6% SO 2 5,705 5,307 -7.0%
NH 3 8,700 7,238 -16.8%
PM 2.5 405,777 382,192 -5.8%
PM 10 416,488 384,295 -7.7%

The 2005 platform also contains corrected HCl emiss ions for Stationary Source Fuel Combustion
Coal fired Industrial and Commercial/Institutional boilers (SCCs 2102002000 and 2103002000). The EPA Office of Research and Development (ORD) id entified overestimated HCl in the 2002 platform nonpt sector and provided revised HCl emis sions in Georgia, Utah, and Virginia that lowered these emissions by approximately 100,000 to ns/year.22



### 2.3 Fires (ptfire and avefire)

Wildfire and prescribed burning emissions are conta ined 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. T he ptfire sector has emissions provided at geographic coordinates (point locations) and has da ily emissions values, whereas the avefire sectors are county-summed inventories and have annu al total emissions values. For the 2005 evaluation case, we modeled 2005 year-specific fire s using the emissions from the ptfire sector. For the 2005 base case, the ptfire sector was repla ced 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 Ar ea Sources;”

Both the ptfire and avefire sectors for the 2005 Pl atform exclude agricultural burning and other open burning sources, which are included in the non pt 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 s ector (as described in 2.3.3). Additionally, their year-to-year impacts are not as variable as w ildfires and non-agricultural prescribed/managed burns.



### 2.3.1 Day-specific point source fires (ptfire)
The ptfire sector includes wildfire and prescribed 6 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 se ctor. We did not include emissions from this sector in the 2005 base case or any of the future y ear cases. This sector includes emissions for all 2005 wildfires and many prescribed burns with d aily 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 lo ad, 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 a lso 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 Ar ea Sources;”

The use of point source and day-specific data for f ires was a new feature to EPA’s modeling for the 2002 platform and is described in the 2002 plat form documentation.

The point source day-specific emission estimates fo r 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) H azard Mapping System (HMS) fire location information as input combined with CONSUME v3.0 (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 inform ation 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 rep orts is described in an Air and Waste Management Association report (Raffuse, et al., 200 7).

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

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 s ector is significantly different than that described in the 2002 platform documentation. Firs t, the fire locations are satellite-based instead of ground-based. This means that many more fires a re 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 prescrib ed burn is not as precise as with ground-based methods. Third, the fire size was based on the num ber of satellite pixels and a nominal fire size of 100 acres/pixel was assumed for a significant nu mber of fire detections when the first detections were not matched to ICS 209 reports. Th is means that the fire size information is not as precise as ground based methods. Finally, becau se the HMS satellite product from NOAA is based on daily detections, the emission inventory r epresents a time-integrated emission estimate. For example, a large smoldering fire will show up o n satellite for many days and would count as acres burned on a daily basis whereas a ground-base d 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 System25

The SMOKE-ready “ORL” files created from the raw da ily fires contain both CAPs and HAPs. The HAPs were generated using the same emission fac tors 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/docume ntation )

2.3.1.1 Speciation of “isomers of xylenes” in ptfir e 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 Isom ers)” emissions present in the raw daily fires files, represented only by pollutant code 133 0207 by apportioning the emissions to mxylene (108383), o-xylene (95476) and p-xylene (106 423). 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 et hylbenzene. 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 1330 207 emissions using the following percentages: 61.41% m-xylene, 16.58% p-xylene and 2 2.01% o-xylene. These were derived from measurements of the flaming and smoldering xyl ene emission rate (Lee, et. al, 2005) and the assumption that 75% of the emissions are flamin g and 25% smoldering 7

.
2.3.1.2 Creation of “NONHAPVOC” in ptfire
We used the BAFM HAP emissions from the inventory r ather 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 li mited to computing
NONHAPVOC for annual emissions data but not the dai ly data we used for fires. Daily NONHAPVOC for each fire was computed for each sourc e 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 a pproach 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 ha d no impact on the base case used in RRF calculations because ptfire was not used in the bas e case. The limitations are listed below.

(1) Benzene (Pollutant code and CAS =71432): Emissi ons 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 e qual flaming and smoldering fraction was used by mi stake, a 75/25 split would have resulted in the following pe rcentages: 59.07, 19.25 and 21.68 for m, p, and o-x ylene, respectively.26

(3) Benzo[k]Fluoranthene (Pollutant code and CAS= 2 07089): 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 5683 2736) 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 HA Ps that are not used in the modeling, but
that are included with incorrect emissions values i n the data we posted at the 2005v4 website (see the end of Section 1). The first error, howev er, 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 c ritical 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 BA FM.



### 2.3.2 Average fires (avefire)
The average fire sector includes emissions from wil dfires, prescribed burning, and managed burning. We used this sector for the 2005 base cas e, and all future year cases. As noted above, avefire emissions are annual, county-level emission s.

The purpose of the avefire sector is to represent e missions for a typical or average year’s fires for use in projection year inventories, since the locat ion and degree of future year fires are not known. This approach keeps the fires information c onstant 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 a ctivity 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 wild fire and prescribed burning inventories using the following formula for all pollutants:

The average acres-burned was calculated base on 199 6 through 2002 data; therefore, the average fire inventory represent average fires from 1996 th rough 2002, with the assumption of 200127

emissions rates and a spatial distribution of emiss ions 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 des cribed here.

The 2005 platform avefire sector differs from the a vefire 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 e missions and found them too high (Tom Pace, personal communication).

b. We created HAP emissions records by applying emissi on ratios to PM 2.5

.

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 fo r CO and PM 2.5 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 PM 2.5 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 Ar ea Sources; Other Combustion”

The 2005 HAP emissions records were created by mult iplying PM 2.5 emissions by the emission
factors in Table 2-14. The HAP factors are the sam e 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 mod eling inputs for the 2005 Platform.

Table 2-14. HAP emission factors applied to avefire PM 2.5 emissions

Pollutant Description CAS PM 2.5 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 0.000128 Pollutant Description CAS PM 2.5 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 unchang ed for the 2005 platform.

The BEIS3.14 model creates gridded, hourly, model-s pecies emissions from vegetation and soils. It estimates CO, VOC, and NO X emissions for the U.S., Mexico, and Canada. The B EIS3.14
model is described further in: http://www.cmascenter.org/conference/2008/slides/po uliot_tale_two_cmas08.ppt

The inputs to BEIS include:

• Temperature data at 2 meters which were obtained fr om the CMAQ meteorological input files,

• Land-use data from the Biogenic Emissions Landuse D atabase, version 3 (BELD3). BELD3 data provides data on the 230 vegetation clas ses 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 emission s between the 2002 and 2005 platforms are (1) the apportioning of the emissions into addition al platform sectors to allow for processing differences among the sectors; (2) the use of new e missions methods and data sets, particularly
the use of a draft version of the Motor Vehicle Emi ssions Simulator (MOVES) model including temperature affects on gasoline PM 2.5 exhaust emissions; and (3) the update of most of t he data to 2005. A summary of these differences is present ed below; details are provided in the
subsections that follow.

For the 2005 platform, as indicated in Table 2-2, w e 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_run pm”; 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 mentio ned, the aircraft emissions are now in the nonEGU point inventory.

While the previous EPA platforms have used NMIM for the onroad and nonroad sectors 8 , some of the onroad emissions in the 2005 platform were b ased on a draft version 9 of the MOVES model run for the year 2005. We used this draft MO VES model to make sure to include the

PM 2.5 emissions from onroad gasoline vehicles, which inc lude temperature effects and are much larger than previous versions of onroad PM 2.5 . 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-l evel 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 n ot come from the MOVES model were obtained from the 2005 NMIM runs, which are consist ent with the 2005 NEI v2.

Table 2-15. Pollutants covered by the draft MOVES model in the 2005 Platform 1

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

PM 2.5 ; exhaust, partially speciated 2 Naphthalene 3
VOC; except refueling 1,3 butadiene 4

CO Acrolein 4

NO X Benzene; except refueling Formaldehyde Acetaldehyde

1 Draft MOVES data were used only for onroad gasolin e vehicles with the exception of motorcycles. Draf t MOVES

8 Other than California which were provided by CARB and were based on the mobile models used by Califor nia, EMFAC and OFFROAD, for onroad and nonroad emissions , respectively.

9 As of December 2009, this draft version was replac ed by the publicly released MOVES2010 version at www.epag.gov/otaq/models/moves/30

data were not used for any California onroad emissi ons
2 Exhaust mode PM 2.5 species from MOVES consist of: PEC, PSO 4 and the difference between PM 2.5 and PEC (named as “PM25OC”). Brake wear and tire wear PM 2.5 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 platf orm

The 2005 v2 NEI does not contain the draft MOVES da ta that we use for the 2005 platform. Instead, it contains onroad and nonroad mobile emis sions 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 model s 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_sec tor/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 v ary by month. Inventory documentation for the 2005 NEI v2 onroad and nonroad sectors is also post ed with other 2005 NEI documentation; the
direct link is: ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/200 5_mobile_nei_version_2_report.pdf

The residual fuel commercial marine vessel (CMV), a lso 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 w ith 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 s ector, the mobile sectors are at county and SCC resolution. Tribal data from the alm_no_c3 sec tor 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” fo r input into the air quality model, as described in Section 3.1.2.1. A few categories of nonroad so urces (CNG and LPG-fueled equipment) do not have BAFM and therefore utilize the “no-integra te”, “no-hap-use” case which means VOC from these sources is speciated to provide BAFM.

10 Although OTAQ generated emissions using NMIM for C alifornia, these were not used in the 2005 NEI vers ion 2, but rather were replaced by state-submitted emissio ns.31



### 2.5.1 Onroad mobile MOVES cold-start exhaust source s requiring temperature adjustments (on_moves_startpm)

This sector contains draft MOVES emissions for PM a nd naphthalene 11 for non-California onroad gasoline cold-start exhaust except for motor cycles. 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 th ey 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 tempe ratures needed for modeling, we created emissions of PM and naphthalene exhaust at 72 oF an d applied temperature adjustments after the emissions were spatially and temporally allocated. The PM 2.5 (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 invento ry 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 w ith colder temperatures and
how start exhaust emissions increase more than runn ing exhaust emissions.

11 Naphthalene is not used in the 2005 CAP-BAFM platf orm, but it is contained in the MOVES-based inputs and was used in the version of the 2005 platform used f or 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 a dditional processing to develop countylevel monthly ORL files for SMOKE. As stated earli er, 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 PM 2.5 emissions from MOVES were partially speciated. To retain the speciated elemental carbon and sulfate emissions fr om 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 spec ies affected by temperature. Finally, because the start emissions were broken out separat ely 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 SMOK E.

A list of the procedures performed to prepare the M OVES data for input into SMOKE is provided below.

i. We allocated state-level emissions to counties usin g state-county emission ratios by SCC, pollutant, and emissions mode (e.g., evaporati ve, exhaust) for each month. The ratios were computed using NMIM 2005 data (same dat a included in the 2005 NEI v2).

ii. We assigned these start emissions to urban and rura l SCCs based on the county-level
ratio of emissions from urban versus rural local ro ads from the NMIM onroad gasoline data. For example, we split LDGV start em issions in the state-total MOVES data (assigned SCC 2201001000) into urban (22010013 70) and rural (2201001350) based on the ratio of LDGV urban (2201001330) and r ural (2201001210) local roads.33

iii. We converted MOVES-based PM 2.5 species at 72 oF to SMOKE-ready PM species. The SMOKE-ready species are listed below and the sp eciation technique used to obtain the SMOKE-ready species is further discussed in Appendix B.

• NAPHTH_72: unchanged from MOVES-based file, subjec t 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 meta ls, PNO3 (computed from MOVES-based PM25EC), NH 4 (computed from MOVES-based PM25SO4 and PNO3), and MOVES-based PM25SO4. Subject to tem perature adjustment
below 72 oF.

• PSO 4 : unchanged from MOVES-based PM25SO4, not subject to temperature adjustment.

• PNO 3 : computed from MOVES-based PM25EC, not subject to temperature adjustment.

• OTHER: sum of computed metals (fraction of MOVES-b ased PM25EC) and
NH 4 (computed from PNO3 and PSO4), not subject to temp erature 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-re ady PM emissions that do not exactly match what MOVES provides. The emissions are conserved d uring 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 PSO 4 components of PM 2.5 emissions are also conserved as they are simply renamed from the MOVES specie “PM25EC”. However, a s seen above, POC, PNO 3 , and PMFINE components involve multiplying the MOVES PM species by components of an onroad gasoline exhaust speciation profile described in Ap pendix B.



### 2.5.2 Onroad mobile MOVES running exhaust sources r equiring temperature adjustments (on_moves_runpm)
This sector is identical to the on_moves_startpm se ctor discussed in Section 2.5.1, but contains running exhaust emissions instead of cold-start exh aust emissions. The same pollutants are in this sector, and allocation from the MOVES state-le vel 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 adjustm ents are less extreme for these running emissions at colder temperatures when compared to t he curve for cold-start emissions (Figure 2-2).34



### 2.5.3 Onroad no-adjustments mobile sources (on_noad j)
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 a re four sources of data that are pre-processed to create three sets of monthly inventories for thi s 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, NO X , CO, 1,3-butadiene (106990), acetaldehyde (75070), acrolein (107028), benzene (71432), and formaldehyde (50000) ; and

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

For these pollutants listed, these non-California M OVES 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 interm ediate temperature adjustments and can therefore be processed with the remaining o nroad mobile emissions. These emissions contain both running and parking sources and are pre-processed from statelevel to county-level much like the on_moves_startp m and on_moves_runpm sectors already discussed. The preprocessing for these emi ssions did not require species
calculations because the raw MOVES emissions transl ated 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. NH 3 emissions are from NMIM runs for California. We re tained only those HAPs that are also estimated by NMIM for nonroad mobile sources; all other HAPs provided by California were dropped. The California onroad inv entory does not use the SCCs for Heavy Duty Diesel Vehicles (HDDV) class 6 & 7 (2230 073XXX) emissions. California does not specify road types, so we used NMIM Califo rnia ratios to break out vehicle
emissions to the match the more detailed NMIM level

. 3. Remaining NMIM-based onroad inventory: The remaind er of the non-California onroad inventory that was not replaced by MOVES. This inc ludes monthly emissions for all onroad diesel, all motorcycles, all refueling, and onroad LDGV, LDGT1, LDGT2, and HDGV emissions for pollutants not covered by the dr aft MOVES used for this platform (e.g., SO 2 , NH 3 , and most HAPs). The NMIM county database is NCD2 0080522; this is an update of NCD20070912 in which state/local and t ribal inputs replace EPA default inputs where provided.

The remainder of this section discusses the pre-pro cessing 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 M6023ChcOxF ixNMIM. We then removed the CO 2 emissions and emissions of dioxins and furans, as w ell as emissions that were replaced by
MOVES and California-submitted data. We also remov ed onroad refueling emissions since the NEI treats onroad refueling as a stationary source that is included in the nonpt sector (gasoline35

distribution, Stage II, SCC=2501060100), and in lim ited 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, Col orado, Kentucky, and North Carolina).

Emissions were converted from monthly totals to mon thly average-day based the on number of days in each month. Furthermore, this sector inclu des exhaust, evaporative, brake wear and tire wear emissions from onroad sources, which allowed u s to use speciation profiles that are specific to each of these processes.

Similar to nonroad pre-processing, we reassigned NM IM evaporative xylene (compound XYL or CAS=EVP__1330207) into MXYL (CAS=EVP__108383) and O XYL (CAS=EVP__95476,) using a 68% and 32% ratio to evaporative XYL, respe ctively. We also split NMIM exhaust xylene (CAS=EXH__1330207) into MXYL (CAS=EXH__10838 3) and OXYL (CAS=EXH__95476) using a 74% and 26% ratio to XYL, respectively.

The 2005 VMT database was based on 2002 VMT grown t o 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 fut ure year 2020 VMT used in the projections
and will be discussed in a future version of this d ocumentation) is available at: ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/200 5_mobile_nei_version_2_report.pdf



### 2.5.4 Nonroad mobile sources –NMIM-based nonroad (n onroad)
This sector includes monthly exhaust, evaporative a nd refueling emissions from nonroad engines (not including commercial marine, aircraft, and loc omotives) 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) an d small SI engine proposed rule, published May 18, 2007 (EPA, 2007c). For 2005, the NONROAD20 05 model (NR05c-BondBase) is equivalent to NONROAD2008a, since it incorporated B ond 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 documen t) 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 emissio n modes: exhaust, evaporative and refueling. Unlike the onroad sector, refueling emi ssions for nonroad sources are not dropped from processing for this sector.

Similar to the on_noadj pre-processing, we also rea ssigned 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 rea ssigned refueling xylene. We use the same percentages for refueling as for evaporative emissi ons as follows: we converted compound XYL or CAS=EVP__1330207, RFL__1330207) into MXYL (CAS=E VP__108383, RFL__108383) and OXYL (CAS=EVP__95476, RFL__95476) using a 68% a nd32% ratio to both evaporative and refueling XYL, respectively. We also split NMI M exhaust xylene (CAS=EXH__1330207) into MXYL (CAS=EXH__108383) and OXYL (CAS=EXH__9547 6) using a 74% and 26% ratio to XYL, respectively.36

EPA/OTAQ ran NMIM to create county-SCC emissions fo r the NEI 2005v2 nonroad mobile CAP/HAP inventory, and similar to on_noadj, we remo ved 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 stat e inputs where provided. The NMIM inventory documentation describes this and all othe r details of the NMIM nonroad emissions development: ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/200 5_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 Chr is Nguyen. NH 3 emissions are from
NMIM runs for California because these were not inc luded 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 tho se HAPs that are also estimated by NMIM for nonroad mobile sources; all other HAPs were dro pped.

The CARB-based nonroad data did not have mode-speci fic data for VOC (exhaust, evaporative, and refueling). We split the annual total Californ ia data into monthly, mode-specific nonroad emissions for California using the NMIM results. D etails on this process are documented separately (Strum, 2007). Nonroad refueling emissi ons for California were computed as Gasoline Transport (SCC=2505000120) emissions multi plied 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 C alifornia refueling for 2005 by the sum of portable fuel container emissions and NMIM-deriv ed refueling for 2005.



### 2.5.5 Nonroad mobile sources: locomotive and non-C 3 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 airc raft emissions, but here we have removed aircraft emissions from the sector because point-so urce 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 ar e listed in Table 2-16.

Table 2-16. SCCs in the 2005 alm_no_c3 inventory compared to th e 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: Total37

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 V essels, Commercial;Diesel;Port emissions
2280002200 Retained from 2002 Platform Mobile Sources;Marine V essels, 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 V essels, 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 secto r is available at: http://www.epa.gov/ttn/chief/net/2002inventory.html #documentation

For modeling purposes, the following additional cha nges were made to the data for the 2005 platform:

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

• Removed railway maintenance emissions (SCCs 2285002 015, 2285004015, and 2285006015) because these are included in the nonro ad NMIM monthly inventories. This change was made for the 2002 platform and is r etained here in the 2005 platform.

• For the purpose of CAP-HAP VOC integration as discu ssed 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 Sec tion 3.1.2.1, sources are considered38

no-integrate when the source of data between VOC an d VOC HAPs is inconsistent or VOC analysis of VOC and VOC HAPs indicates the sour ce 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 fo r all sources and therefore did not
need to remove it.

The 2002 platform documentation goes into greater d etail 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 develope d in an ASCII raster format used since the Emissions Control Area-International Marine Organiz ation (ECA-IMO) project began in 2005, then known as the Sulfur Emissions Control Area (SE CA). These emissions consist of large marine diesel engines (at or above 30 liters/cylind er) 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 o cean-going vessels, referred to as Category 3 (C3) ships. The seca_c3 (ECA) inventory includes t hese 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 NO X , SO 2 , and PM C3 emissions can be found at:

http://www.epa.gov/oms/regs/nonroad/marine/ci/420f0 9015.htm

The base year ECA inventory is 2002 and consists of these CAPs: PM 10 , CO, CO 2 , NH 3 , NO X , SO X (assumed to be SO 2 ), and Hydrocarbons (assumed to be VOC). EPA devel oped regional growth (activity-based) factors that we applied to create a 2005 inventory from the 2002 data. These growth factors are provided in39

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

http://www.epa.gov/oms/regs/nonroad/marine/ci/420r0 9007-chap2.pdf

These growth factors are the same for all pollutant s except NO X which includes a Tier 1
Standard.40

Table 2-17

. Regional growth factors used to project 2002 C3 emi ssions 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 ras ter 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/sessio n6/mason.pdf

This paper describes how the ASCII raster dataset w as converted to latitude-longitude, mapped to state/county FIPS codes that extend up to 200 na utical 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 Exclus ive 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 i ncrease from the 2002 v3 platform (from the old methods used in the NEI) and this 2005 v4 p latform. Note that the 2002 NEI-based C3 emissions are confined to the immediate coast and p orts, whereas the 2005 C3 emissions cover most of the northern hemisphere Atlantic and Pacifi c 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 o ther C3 modes such as hoteling, maneuvering, reduced-speed zone, and idling) emissi ons; 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 und erway and port C3 emissions (2280003100 and 2280003200).

Table 2-18

. Contiguous U.S. C3 CMV emissions in 2002 and 2005 p latforms

Pollutant 2002 platform 2005 platform % Change CO 28,195 53,746 91%

NH 3 131 0 -100%
NO X 244,988 642,089 162%

PM 10 13,687 53,581 291%

PM 2.5 12,620 49,294 291%
SO 2 150,532 417,307 177% VOC 7,377 22,367 203%41

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

PM 2.5 to obtain HAP emissions values. Table 2-19 below shows these factors and whether they were applied to VOC, PM 2.5 , or PM 10 . Because we computed HAPs directly from the CAP inventory and the calculations are therefore consis tent, the entire seca_c3 sector utilizes CAPHAP VOC integration to use the VOC HAP species dire ctly, 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 PM 2.5 56553 5.674E-07 Benzo[a]Pyrene PM 2.5 50328 1.844E-07
Benzo[b]Fluoranthene PM 2.5 205992 1.56E-07
Benzo[k]Fluoranthene PM 2.5 207089 1.56E-07 Chrysene PM 2.5 218019 9.929E-08 Indeno[1,2,3-c,d]Pyrene PM 2.5 193395 1.418E-08
Acenaphthene PM 2.5 83329 3.404E-07 Acenaphthylene PM 2.5 208968 5.248E-07

Anthracene PM 2.5 120127 5.248E-07 Benzo[g,h,i,]Perylene PM 2.5 191242 1.277E-07

Fluoranthene PM 2.5 206440 3.12E-07

Fluorene PM 2.5 86737 6.95E-07
Naphthalene PM 2.5 91203 1.987E-05

Phenanthrene PM 2.5 85018 7.943E-07 Pyrene PM 2.5 129000 5.532E-07 Beryllium PM 10 7440417 5.459E-07

Cadmium PM 10 7440439 7.642E-06

Chromium VI PM 10 18540299 2.948E-06

Chromium III PM 10 16065831 1.343E-05

Lead PM 10 7439921 3.002E-05 Manganese PM 10 7439965 5.732E-05

Nickel PM 10 7440020 0.0016377

Selenium PM 10 7782492 1.337E-05

We converted the emissions to SMOKE point source OR L format, allowing for the emissions to be allocated to modeling layers above the surface l ayer. We also corrected FIPs code assignments for one county in Rhode Island. All no n-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 sep arate ORL files. The SMOKE-ready data42

have also been cropped from the original ECA-IMO da ta to cover only the 36-km CMAQ domain, which is the largest domain used for this e ffort.



### 2.6 Emissions from Canada, Mexico and Offshore Dril ling Platforms (othpt, othar, othon)

The emissions from Canada, Mexico, and Offshore Dri lling Platforms are included as part of five sectors: othpt, othpt_hg, othar, other_hg, and otho n. The “oth” refers to the fact that these emissions are “other” than those in the 2005 NEI, a nd 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 plat form, othpt_hg and othar_hg. These sectors contain year 2000 Canadian speciated mercury emissi ons for point and area inventories. All other “oth” emissions are CAP-only inventories. Me xico’s emissions are unchanged from the 2002 Platform with one exception –one stack diamete r was updated (recomputed from stack velocity and flowrate) in the Mexico border states point inventory.

For Canada we updated the emissions from the 2002 p latform, 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 yea r 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 emis sions for all future year modeling (discussed in a future version of this documentation). We applie d 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 bec ause 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”) t o 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 f or 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 remov ed because these emissions are included in the seca_c3 sector, which covers not on ly emissions close to Canada but also
emissions far at sea. Canada was involved in the in ventory 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; t hese emissions are also absent from our U.S. inventory.

vii. Quebec PM 2.5 emissions (2,000 tons/yr) were removed for one SCC (2305070000) for Industrial Processes, Mineral Processes, Gypsum, Pl aster 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 Bab ine Forest Products Ltd (British Columbia plantid=’5188’) in the point inventory. T his change was made at our
discretion because the value of the emissions was i mpossibly 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 m atching to existing temporal profiles.

x. Fixed coordinates for facility “ON105803” in the ot hpt_hg inventory to match those in the National Pollutant Release Inventory (NPRI) oth pt sector.

xi. Nonpoint speciated mercury emissions duplicate emis sions summed and state/county FIPS code field changed from Nunavut (62) to NW Ter ritories (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 Mex ico's Secretariat of the Environment and Natural Resources (Secretaría de Medio Ambiente y R ecursos Naturales-SEMARNAT) and National Institute of Ecology (Instituto Nacional d e Ecología-INE), the U.S. EPA, the Western Governors' Association (WGA), and the North America n Commission for Environmental Cooperation (CEC). This inventory includes emissio ns from all states in Mexico.

The offshore emissions include point source offshor e 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, an d othon

sectors in the 2005 Platform

Sector Components Changes from 2002 Platform

Mexico, 1999, point None Canada, 2006, point Uses emissions from 2006 Nation al 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 p oint 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 NH 3 , fugitive dust, and remaining nonpoint inventories. othar

Canada, 2006, nonroad Uses 2006 Canadian nonroad mo bile, 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. Mexico, 1999, onroad None othon Canada, 2006, onroad Uses 2006 Canadian onroad inve ntory. Emissions are given at vehicle type resolution only (i.e., do es not include road types).



### 2.7 SMOKE-ready non-anthropogenic inventories for m ercury 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 s pecies “HGNRVA ” required by the multipollutant version of CMAQ. This model species is i ntended to include the sum of elemental mercury emissions from these sources. For the ocea n chlorine, we used the same data as in the
CAP and HAP 2002-based Platform. See ftp://ftp.epa.gov/EmisInventory/2002v3CAPHAP/docume ntation for details. A new recycled mercury file was developed for 2005 since the scali ng 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 Enviro nmental Research, Incorporated (AER), consisted of three existing global inventories cont aining 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 200 1 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 deposi tion of elemental mercury gas. The total deposition (wet plus dry) of all forms of mercury w as 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 calibrat ions done by AER. This fraction is subject to future adjustment as the processes controlling t he 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 variab les of solar radiation and temperature, which are shown to be positively correlated with the evas ion of elemental mercury from water surfaces soils and vegetation. While the correlation is wid ely variable for each of these surfaces, simple45

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 SFCTMP SOLRAD SFCTMP SOLRAD
)] 273 ( [ )

273 ( or exactly zero for SFCTMP < 273 K

Land: 

## ∑

− ∗ − ∗

allhrs hr

hr SFCTMP SOLRAD SFCTMP SOLRAD
)] 253 ( [ )

253 ( or exactly zero for SFCTMP < 253K

where SOLRAD is the solar radiation in W/m 2 and SFCTMP is the skin temperature (Kelvin), both from the 2-dimensional meteorology file from t he 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 mercu ry 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 th e same as those used in the CAP and HAP
2002 Platform.



## 3 Emissions modeling summary

The CMAQ model requires hourly emissions of specifi c 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 require d 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 resol ution into the data required by CMAQ. As seen in Section 2, the temporal resolution of the emissi ons 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 differe nt sectors, may be individual point sources or county totals (province totals for Canada, municipi o 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 allo cation of point sources are referred to as emissions modeling. This section provides some bas ic information about the tools and data files used for emissions modeling as part of the 2005 Pla tform. Since we devoted Section 2 to describing the emissions inventories, we have limit ed 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 c reate the emissions inputs for CMAQ. Although we used SMOKE version 2.5, the SMOKE versi on 2.6 source code and executables46

can be used to reproduce our emissions modeling, an d 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 profi les 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-s pecific emissions across sectors. The SMOKE settings in the run scripts and the data in t he SMOKE ancillary files control the approaches used for the individual SMOKE programs f or each sector. Table 3-1 summarizes the major processing steps of each platform sector. Th e “Spatial” column shows the spatial approach: “point” indicates that SMOKE maps the so urce from a point (i.e., latitude and longitude) location to a grid cell, “surrogates” in dicates that some or all of the sources use spatial surrogates to allocate county emissions to grid cel ls, 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 BE IS3 and not as a separate SMOKE step. The “Inventory resolution” column shows the inventory t emporal resolution from which SMOKE needs to calculate hourly emissions.

Finally, the “plume rise” column indicates the sect ors for which the in-line approach is used. These sectors are the only ones which will have emi ssions in aloft layers, based on plume rise. For the 2005 Platform, we did not have SMOKE comput e vertical plume rise; this was done in CMAQ using stack data in SMOKE output files for eac h 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-dime nsional, 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 monthly47

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-l ine processing, the PELVCONFIG file cannot allow grouping, otherwise the “inline” versu s “offline” (i.e., processing whereby SMOKE creates 3-dimensional files) will not give identica l 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 mo deling domains with 36-km and 12-km spatial resolution. These are the same domai ns as were used for the 2002 Platform. Figure 3-1 shows the 36-km CON tinental U nited S tates “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, 149

Section 3.2.1 provides the details on the spatial s urrogates 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. T hese model species are either individual chemical compounds or groups of species, called “mo del species.” The chemical mechanism used for the 2005 Platform is the Carbon Bond 05 (C B05) mechanism (Yarwood, 2005) with secondary organic aerosol (SOA) and HONO enhanceme nts 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 sam e mechanism used in the 2002 Platform except that additional input model species are needed to s upport 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; th e only three input species that were not
in the CAP 2002-Based Platform described in 2002 “C AP-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 conce ntrations of BENZENE do not provide any feedback into the chemical reactions (i.e., it is n ot “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 T OL and XYL) plays a role in SOA formation in CMAQ4.7.50

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

Inventory Pollutant Model Species Model species des cription

CO CO Carbon monoxide

NO Nitrogen oxide NO2 Nitrogen dioxide NO X

HONO Nitrous acid

SO2 Sulfur dioxide SO 2 SULF Sulfuric acid vapor

NH 3 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

SESQ Sesquiterpenes Various additional VOC species from the biogenics model which do not map to
the above model species TERP Terpenes

PM 10 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 PM 2.5

PMFINE Other particulate matter ≤ 2.5 microns

The approach for speciating PM 2.5 emissions is the same as that described for the 200 2 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 all ow integration of VOC and HAP emissions in the NEI. This has the result of modifying the spec iation profiles based on the HAP emission estimates which are presumed to be more accurate th an the speciated VOC results for the HAPs; and, 2) for some mobile sources, “combination” prof iles are specified by county and month and51

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 GSPR O_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 d etails about the data files used to accomplish these speciation processing steps.

3.1.2.1 The Combination of HAP BAFM (benzene, aceta ldehyde, formaldehyde and methanol) and VOC for VOC Speciation
The VOC speciation approach for the 2005 Platform d iffered from the 2002 Platform in that we included, for some of the U.S. platform sectors, HA P emissions from the NEI in the speciation process. That is, instead of speciating VOC to gen erate all of the species listed in Table 3-3 as we did for the 2002 platform, we integrated emissio ns 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 direct ly 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 wit h chlorine chemistry) model. By “explicit VOC HAPs,” we mean model species that par ticipate 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 b ecause 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 av ailable in SMOKE for all inventory formats other than PTDAY (the format used for the p tfire sector). SMOKE allows the user to specify the particular HAPs to integrate and the pa rticular sources to integrate. The particular HAPs to integrate are specified in the INVTABLE fil e, and the particular sources to integrate are based on the NHAPEXCLUDE file (which actually provi des the sources that are excluded from integration 12 ). For the “integrate” sources, SMOKE subtracts th e “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 NO NHAPTOG speciation profiles. SMOKE computes NONHAPTOG and then applies the speci ation profiles to allocate the NONHAPTOG to the other CMAQ VOC species not includi ng 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 source s for integration are expanded so that a user can s pecify the particular sources to include or exclude from integ ration, and there are settings to include or exclud e 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 sou rce

Compute: NONHAPTOG emissions from NONHAPVOC for each integrate source Compute: TOG emissions from VOC for each no-integr ate

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 s ources. Use TOG profiles applied to TOG for no-integrate so urces

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 a nd developed “integration criteria” for some of those. Table 3-4 summarizes the integratio n approach for each platform sector used in Step 1 of Figure 3-2.

Table 3-4. Integration status of benzene, acetaldehyde, formal dehyde 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 a re 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 comput ed outside of SMOKE since SMOKE cannot

do this calculation for the day-specific fire forma tted files) avefire No integration ag N/A – sector contains no VOC
afdust N/A – sector contains no VOC nonpt Partial integration; details provided below t able nonroad For other than California: Partial integr ation – 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 bel ow 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 integra tion criteria to determine the sources to integrate (Step 1):

1. Any source for which B, A, F or M emissions were fr om 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 gr eater than the VOC was not integrated, since this clearly identifies sources f or 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 specifie d 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 emis sions of one of the B, F, A or M pollutants, then it can be integrated.

Table 3-5. Source-category specific criteria for integrating n onpt 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 se t 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 no t exceed the VOC emissions. The criteria for this sector were less complex than the nonpt se ctor because it has much fewer source categories.

We used the SMOKE feature to compute speciation pro files from mixtures of other profiles in user-specified proportions. The combinations are s pecified 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., mont h).

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 me rcury species by speciating any of the mercury in the NEI that was not provided as divalen t 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 emi ssions processing configuration. It compares the key approaches we used for temporal pr ocessing 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 th e year, inventory is already daily week = hourly emissions computed for all days in on e “representative” week, representing all weeks for each month, which means emissions have day-of-week varia tion, but not week-to-week variation within the
month mwdss= hourly emissions for one representative Mond ay, representative weekday, representative Saturday and representative Sunday for each month, which mea ns emissions have variation between Mondays, other weekdays, Saturdays and Sundays within the mo nth, but not week-to-week variation within the month. Also Tuesdays, Wednesdays and Thursdays are treated the same. aveday = hourly emissions computed for one represen tative 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 e missions from the inventory using the Temporal program. The values given are th e 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 ho lidays as indicated by the rightmost column. The values gi ven 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 miti gate 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 f rom December 2005 to fill in surrogate emissions for the end of December 2004. In particu lar, we used December 2005 emissions (representative days) for December 2004. For bioge nic emissions, we processed December 2004 emissions using 2004 meteorology.



### 3.2 Emissions modeling ancillary files

In this section we summarize the ancillary data tha t SMOKE used to perform spatial allocation, chemical speciation, and temporal allocation for th e 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 pollu tant/SCC or (for combination profiles) state/county FIPS code and month, and temporal fact ors 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-po int data file. For the U.S. and Mexico, we used the same spatial surrogates as were used for t he 2002 Platform. For Canada, for which we used a 2006 inventory, we used a new set of Canadia n surrogates provided by Environment Canada along with their emissions data. The spatia l data files we used can be obtained from the files listed below; these are available from the 20 02v3CAP (for US and Mexico) and 2005v4CAP-BAFM (for Canada) websites (see the end o f Section 1).

• 36km_surg_2002v3mpCAP_smokeformat.zip : U.S. and Mexican surrogate files for 36-km spatial resolution (Canadian data contained i n this zip file was not used for the 2005-based platform except for the year 2000 mercur y 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 (Canad ian 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 (SRGD ESC), surrogate cross reference file (AGREF), and area-to-point (ARTOPNT) file

The U.S., Mexican, and Canadian 12-km surrogates co ver the entire CONUS domain, though they are used directly as inputs for the two separa te Eastern and Western Domains shown in Figure 3-1. The SMOKE model windowed the Eastern a nd Western grids while it created these59

emissions. The remainder of this subsection provid es further detail on the origin of the data used for the spatial surrogates and the area-to-point da ta.

3.2.1.1 Surrogates for U.S. Emissions
There are 66 spatial surrogates available for spati ally allocating U.S. county-level emissions to the CMAQ 36-km and 12-km grid cells; they are the s ame as for the 2002 Platform. As described in Section 3.3.1.2, an area-to-point appr oach overrides the use of surrogates for some sources. Table 3-7 lists the codes and description s of the surrogates.

Table 3-7. U.S. Surrogates Available for the 2002 and 2005 Pla tforms

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 Timber60

Code Surrogate Description Code Surrogate Description

510 Commercial plus Industrial

We did not use all of the available surrogates to s patially allocate sources in the 2002 Platform; that is, some surrogates in Table 3-7 were not assi gned 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?MO DEL=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 cat egories in the 2005 Platform

SCC & Description Surrogate 2201001350 Light Duty Gas Vehicles- parking areas r ural 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 u rban 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 Sourc es 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. Unlik e the 2002 platform in which most of these emissions were contained in sectors with county-lev el 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 “are a-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 documentat ion: http://www.epa.gov/scram001/reports/Emissions%20TSD %20Vol1_02-28-08.pdf

.

We used nearly the same ARTOPNT file to implement t he 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 air ports into multiple sets of geographic61

coordinates to support finer scale modeling that wa s 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 I nventories
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 Platfo rm surrogates for allocating the 2006 province-level Canadian emissions. The 2002 Platfo rm 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 z ip files and described in Table 3-9 came from Environment Canada. They provided the surroga tes 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 c ensus data. We changed the crossreferences that Canada originally provided as follo ws: all assignments to surrogate '978' (manufacturing industries) were changed to '906' (m anufacturing services), and all assignments to '985' (construction and mining) and ‘984’ (const ruction industries) were changed to '907' (construction services) because the surrogate fract ions in 984, 978 and 985 did not sum to 1. We also changed codes for surrogates other than popula tion 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_NOFI LL.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_9 57_NOFILL.txt Construction services CA_907_NOFILL.txt manufacturi ng 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_N OFILL.txt All Sales CA_920_NOFILL.txt asphalt industries CA_9 71_NOFILL.txt Intersection of CA_921_NOFILL.txt cement industries CA_972_FILL.txt62

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
industries 1 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 industries 1 CA_984_NOFILL.txt

LDGV CA_934_NOFILL.txt construction and mining 1 CA_985_NOFILL.txt PAVED ROADS CA_941_NOFILL.txt TOTALBEEF 2 CA_986_NOFILL.txt 2

UNPAVED ROADS CA_942_NOFILL.txt TOTALPOUL 2 CA_987_NOFILL.txt 2

Oil Sands CA_950_NOFILL.txt TOTALSWIN 2 CA_988_NOFILL.txt 2

TOTALFERT 2 CA_989_NOFILL.txt 2

1: Not used because fractions did not sum to 1; 2: Surrogates 986, 987, 988 and 989 were originall y numbered by Canada as 611, 615, 620 and 65, respe ctively. We changed the numbers so that all Canadian surrogates would begin with “9”.

The Mexican emissions and single surrogate (populat ion) 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 web site (see the end of Section 1), contains the SMOKE inputs used for chemical speciation of the in ventory 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 uti lizing HAP-CAP integration, as is done for
the 2005 Platform.

We prepared two different INVTABLE files to use wit h 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 i s the best available approach for these species for the sectors using the approach. The se cond 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 N HAPEXCLUDE file even for sectors for which we integrate all sources in the sector. In t his case, we included a source in the file that was not contained in the inventory (this SMOKE limi tation has since been resolved).

3.2.2.2 GSPRO, GSPRO_COMBO, GSREF and GSCNV,
For VOC speciation, we generated the following SMOK E-ready profiles for the CB05 chemical mechanism using the Speciation Tool (Eyth, 2006):

• TOG-to-model species (used only for no-integrate so urces)

• NONHAPTOG-to-model species (used only for the integ rate 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 BENZ ENE, ALD2, FORM and METHANOL, respectively. These profiles were used only for th e integrate sources. Note that we process the integrate and no-integrate sources using the same G SREF 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-integr ate, then we were able to remove these in SMOKE (by using “N” in the INVTABLE) but if a secto r was partially integrated, then we
needed to remove these HAPS from the actual invento ry input to SMOKE, but only for the no HAP use, no-integrate sources.

In addition to the speciation profiles, the Speciat ion Tool generates the SMOKE-ready speciation conversion files (GSCNV). We generated two of thes e: one containing profile-specific VOC-toTOG conversion factors and the other containing pro file-specific NONHAPVOC-toNONHAPTOG conversion factors.

The TOG and PM 2.5 speciation factors that are the basis of the chemi cal speciation approach were developed from the SPECIATE4.2 database64

( http://www.epa.gov/ttn/chief/software/speciate/inde x.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 no t impact the PM 2.5 profiles we used with the 2005-based platform; they were the same as those us ed 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 Standa rds (OAQPS) at Research Triangle Park, NC, and Environment Canada (EPA, 2006c). The SPECI ATE database contains speciation profiles for TOG, speciated into individual chemica l compounds, VOC-to-TOG conversion factors associated with the TOG profiles, and speci ation profiles for PM 2.5 . The database also
contains the PM 2.5 speciated into both individual chemical compounds (e.g., zinc, potassium, manganese, lead), and into the “simplified” PM 2.5 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 m icrograms in diameter

One minor issue we found with the PM 2.5 speciation which was similarly an issue with the 20 02- based platform is that we used a bituminous coal co mbustion 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 combus tion we used the sub-bituminous coal combustion profile (92084). Table 3-10 shows the d ifferences are shown below, though these are quite small and represent only a minor change t o the SMOKE results:

Table 3-10. Differences between two profiles used for coal comb ustion

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 Platf orm are as follows:

• Updated the profile for aircraft from 1098 (Aircraf t Landing/Takeoff (LTO) – Commercial) which is from SPECIATE3.2 and has a pro file date of 1989, to 5565 (Aircraft Exhaust), which has a profile date of 8/2 008 and is based on testing conducted in 2005).65

• Updated the profile for forest fires from 0307 (Mis cellaneous Burning - Forest Fires) which was from SPECIATE3.2 and has a profile date o f 1989) to 5560 (Biomass Burning - Extratropical Forest, dated 2/2008 and was based on testing conducted in 2001)

• Changed the assignment of residential wood combusti on (including woodstove and fireplace emissions) and other profiles that former ly used 4641 (Fireplace wood combustion-oak wood) to 4642 (Fireplace wood combus tion-pine wood) because of all three woods tested in the study (oak, pine and euca lyptus), the most complete testing was done for the pine wood (for example, benzene was on ly 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 8752 13 : Gasoline Exhaust – E85 ethanol gasoline

o 8753: Gasoline Vehicle - Evaporative emission - Re formulated gasoline

o 8754: Gasoline Vehicle - Evaporative emission - E1 0 ethanol gasoline

o 8755 9 : Gasoline Vehicle - Evaporative emission - E85 et hanol gasoline

o 8756 9,14 : Composite Profile for Tier 2 vehicles E0, exhaus t

o 8757 9,10 : Composite Profile for Tier 2 vehicles E10, exhaus t

• Utilized combination profiles comprised of the abov e updated exhaust and evaporative profiles to match the average ethanol content of fu els used by different counties and for different months of the year. Combinations were cr eated based on the fuel properties data in the NMIM county database.

Table 3-11 provides a summary of the 2005 speciatio n approach for mobile and other fuelrelated sources. It shows the updated profiles tha t form the 2005 combinations. The headspace profile, 8737 is the same as was used in the 2002 P latform, 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 secto r 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), p er OTAQ documentation, profiles were created Octobe r 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 FuelContainers, 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 fuel s. Changes to the above profiles for future year
scenarios will be discussed in more detail in a sub sequent 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 fu ture 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 inclu ded in SPECIATE. The 2005 Platform uses BEIS3.14 which includes a new species (SESQ) that w as 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 2 002 Platform. The profile code associated with BEIS3.14 profiles for use with CB05 uses the same a s 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 re solution 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 we re generally based on the temporal
allocation data used for the 2002 Platform. We add ed 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 web site (see the end of Section 1), contains the SMOKE inputs used for chemical speciation of the in ventory 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 for67

electric generating units) for the evaluation case (PTREF) and, temporal profiles (ATPRO, MTPRO, and PTPRO)

The starting point for our temporal profiles was th e 2002 Platform. The remainder of this section discusses the development of the new temporal profi les or profile assignments used in the 2005
Platform.

Canadian emissions

The profiles assignments for the Canadian 2006 inve ntory were provided by Environment Canada along with the inventory. They provided pro file assignments that rely on the existing set of temporal profiles in the 2002 Platform. For po int sources, they provided profile assignments by PLANTID.

WRAP Oil and Gas Inventory Profiles

The WRAP 2005 oil and gas inventory SCCs 15 utilized uniform monthly and day of week profiles (codes 262 and 7, respectively) and an hou rly profile (code 26) that put emissions in every hour, but weighted towards the day light hour s.

Diurnal Profiles for Electric Generating Units (pti pm)

We updated the state-specific and pollutant-specifi c 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, average d over the whole year and all units in each state. We calculated the diurnal factors using CEM SO 2 and NO X emissions and heat input. We computed SO 2 and NO X -specific factors from the CEM data for these pollu tants. All other pollutants used factors created from the hourly hea t input data. We assigned the resulting profiles by state and pollutant.

Onroad Parking Area Profiles

The new SCCs and descriptions, along with the assig nments chosen are shown in Table 3-12. Figure 3-3 shows the diurnal profiles referred to i n the table.

15 See Table 2-9: 2310000220, 2310000330, 2310000440, 2310010100, 231 0010200, 2310010300, 2310010700, 2310010800, 2310020600, 2310020700, 2310020800, 231 0021100, 2310021300, 2310021400, 2310021500, 231002 1600, 2310023000, 2310030210, 231003022068

Table 3-12. Temporal Profiles Assigned to New Onroad SCC from t he Draft MOVES model: Parking Areas

SCC & Description Temporal Profile: Monthly
Variation Temporal Profile:

Day of Week Variation Temporal Profile:
Diurnal variation

2201001350Light 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 rural Figure 3-3, reddish curve)

2201001370Light 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 l ocal 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. P lease also see rule-specific documentation, such as the Transport Rule’s Emission Inventory Technica l Support Document.70



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