## Technical Support Document: Preparation of Emissions Inventor ies
f or the Version 4 .1 , 2005

- based Platform

March 201 1

U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Air Quality Assessment Division

Contacts: Madeleine Strum, Rich Mason, Alison Eyth, Marc Houyoux

,ii 

## TABLE OF CONTENTS

ACRONYMS

................................ ................................ ................................ ................................ ............................. III

LIST OF TABLES

................................ ................................ ................................ ................................ ...................... V

LIST OF FIGURES

................................ ................................ ................................ ................................ .................. VI

LIST OF APPENDICES

................................ ................................ ................................ ................................ .......... VI

1 INTRODUCTION

................................ ................................ ................................ ................................ .............. 1

2 2005 EMISSION INVENT ORIES AND APPROACHES

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

2.1 2005 NEI P OINT SOURCES ( PTIPM AND PTNONIPM )

................................ ................................ ........................ 11

2.1.1 IPM sector (ptipm)

................................ ................................ ................................ ............................... 16

2.1.2 Non

- IPM sector (ptnonipm)

................................ ................................ ................................ ................. 16

2.2 2005 N ONPOINT SOURCES ( AFDUST

, AG

, NONPT )

................................ ................................ ............................ 18

2.2.1 Area Fugitive dust sector (afdust)

................................ ................................ ................................ ........ 19

2.2.2 Agricultural Ammonia sector (ag)

................................ ................................ ................................ ....... 20

2.2.3 Other nonpoint sources (nonpt)

................................ ................................ ................................ ........... 23

2.3 F IRES ( AVEFIRE )

................................ ................................ ................................ ................................ ............. 25

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)

................................ ................................ ................................ ................................ ................................ . 28

2.5.1 Onroad mobile MOVES cold

- start exhaust sources requiring temperature adjustments (on_moves_startpm)

................................ ................................ ................................ ................................ ........... 30

2.5.2 Onroad mobile MOVES running exhaust source s requiring temperature adjustments (on_moves_runpm)

................................ ................................ ................................ ................................ ............. 33

2.5.3 Onroad no

- adjustments mobile sources (on_noadj)

................................ ................................ ............ 34

2.5.4 Nonroad mobile sources

– NMIM

- based nonroad (nonroad)

................................ ............................. 35

2.5.5 Nonroad mobile sources: locomotive and non

- C3 commercial marine (alm_no_c3)

........................ 36
2.5.6 Nonroad mobile sources: C3 commercial marine (seca_c3)

................................ .............................. 38

2.6 E MISSIONS FROM C ANADA

, M EXICO AND O FFSHORE D RILLING P LATFORMS ( OTHPT

, OTHAR

, OTHON

, OTHPT

_ HG

, AND OTHAR

_ HG )

................................ ................................ ................................ ................................ ... 40

2.7 SMOKE

- READY NON

- ANTHROPOGENIC INVENT ORIES FOR MERCURY AN D CHLORINE

................................ ... 43

2.7.1 Mercury

................................ ................................ ................................ ................................ ............... 43

2.7.2 Chlorine

................................ ................................ ................................ ................................ ............... 44

3 EMISSIONS MODELI NG SUMMARY

................................ ................................ ................................ ........ 44

3.1 K EY EMISSIONS MODELIN G SETTINGS

................................ ................................ ................................ ............. 45

3.1.1 Spatial configuration

................................ ................................ ................................ ........................... 46

3.1.2 Chemical speciation configuration

................................ ................................ ................................ ...... 48

3.1.3 Temporal processing configuration

................................ ................................ ................................ ..... 56

3.2 E MISSIONS MODELING AN CILLARY FILES

................................ ................................ ................................ ....... 58

3.2.1 Spatial Allocation Data

................................ ................................ ................................ ....................... 58

3.2.2 Chemical speciation ancillary files

................................ ................................ ................................ ...... 63

3.2.3 Temporal allocation ancillary files

................................ ................................ ................................ ...... 68

4 REFERENCES

................................ ................................ ................................ ................................ ................. 76iii 

## 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 Commun ity Multiscale Air Quality
CMV Commercial marine vessel
CO Carbon monoxide
EGU Electric generating units

EPA Environmental Protection Agency
EMFAC Emission Factor (California ‘s on road mobile model)

EEZ Exclusive Economic Zone

FAA Federal Aviation Administration
FCCS Fuel Characteristic Classification System
FIPS Federal Information Processing Standards

HAP Hazardous Air Pollutant
HC L Hydrochloric acid

H g Mercury
HGNRVA Natural recycled, volcanic and anthropogenic Hg
HMS Hazard Mapping System
ICR Information Collection Request
IMO International Marine Organization

IPM Integrated Planning Model

ITN Itinerant
MACT Maximum Achievable Control Technology
MOBILE OT AQ‘s model for estimation of on road mobile emissions factors
MOVES Motor Vehicle Emissions Simulator

-- OTAQ‘s model for estimation of onroad mobile

emissions

– replaces the use of the MOBILE model
NEEDS National Electric Energy Database System

NEI National Emission Inventory
NESHAP National Emission Standards for Hazardous Air Pollutants

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 emissions
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 controls
PFC Portable Fuel Containeriv

PM 2.5 Particulate matter less than or equal to 2.5 microns

PM 10 Particulate matter less than or equal to 10 microns

RIA Regulatory Impact Analysis
RFS2 Revised Annual Renewable Fuel Standard

RRF Relative Response Factor
RWC Residential Wood Combustion
RPO Regional Planning Organization
SCC Source Classification Code
SMARTFIRE Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation
SMOKE Sparse Matrix Operator Kernel Emissions
SO 2 Sulfur dioxide
SOA Secondary Organic Aerosol
SPPD Sector Policies and Programs Division

TAF Terminal Area Forecast TCEQ Texas Commission on Environmental Quality
TSD Technical support document
VOC Volatile organic compounds

VMT Vehicle miles traveled
WRAP Western Regional Air Partnershipv 

## List of Tables

Table 2

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

........ 4
Table 2

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

................ 7
Table 2

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

................. 10
Table 2

- 4. Summaries o f Hg (speciated), HCL and CL2*

................................ .......................... 11
Table 2

- 5. Summaries of the non

- anthropogenic mercury across the modeling domain

............ 11
Table 2

- 6. Hg changes made to the 2005 NATA Hg inventory (June 18, 2010 version) for the 2005 ptnonipm, ptipm, and nonpt sectors.

................................ ................................ ............ 14
Table 2

- 7

. SCCs in the afdust platform sector

................................ ................................ ............. 20
Table 2

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

....................... 21
Table 2

- 9. Fertilizer SCCs extracted from the 2002 NEI for inclusion in the ―ag‖ sector

.......... 23
Table 2

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

......................... 24
Table 2

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

................................ .. 25
Table 2

- 12. Changes to Oklahoma oil and gas emissions

................................ ........................... 25
Table 2

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

................................ ........ 26
Table 2

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

................................ ....... 27
Table 2

- 15. Pollutants covered by MOVES2010 as used in the 2005v4.1 pl atform 1

.................. 29
Table 2

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

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

................................ ................................ ................................ ................................ 39
Table 2

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

.......................... 40
Table 2

- 19. Summary of the othpt, othpt_hg, othar, othar_hg, and othon sectors changes from the 2002 platform

................................ ................................ ................................ .................. 42
Table 3

- 1. Key emissions modeling steps by sector.

................................ ................................ ... 46
Table 3

- 2. Descriptions of the 2005

- based platform grids

................................ .......................... 47
Table 3

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

................................ ................................ ................................ ................................ ............... 49
Table 3

- 4. Integration status of benzene, acetaldehyde, formaldehyde and methanol (BAFM) for each platform sector

................................ ................................ ................................ .............. 53
Table 3

- 5. Source

- cate gory specific criteria for integrating nonpt SCCs for categories comprising 80% of the nonpoint VOC emissions

................................ ................................ . 54
Table 3

- 6. Tempo ral settings used for the platform sectors in SMOKE, v4.1 platform

.............. 57
Table 3

- 7. U.S. Surrogates available for the 2005v4.1 plat form.

................................ ................ 59
Table 3

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

................. 61
Table 3

- 9. Canadian Spatial Surrogates for 2005

- based platform Canadian Emissions (v4.1 unchanged from v4)

................................ ................................ ................................ .............. 62
Table 3

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

............ 65
Table 3

- 11. Differences between two profiles used for coal combustion

................................ .... 66
Table 3

- 12: PM 2.5 speci ation profile updates assignments for the v4 platform

............................ 66
Table 3

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

........................... 67
Table 3

- 14. Speciation of Mercury

................................ ................................ .............................. 67
Table 3

- 15. Summary of spatial surrogates, temporal profiles, and speciation profiles used by gasoline vehicle types for the onroad parking area

- related SCCs.

................................ ....... 71
Table 3

- 16. Summary of spatial surrogates, temporal profiles, and speciation profiles used by diesel vehicle types for the onroad parking area

- related SCCs from MOVES2010.

............ 73vi 

## List of Figures

Figure 2

- 1. MOVES exhaust temperature adjustment functions.

................................ ................ 32 Figure 3

- 1. CMAQ modeling domains

................................ ................................ ......................... 47 Figure 3

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

....................... 52 Figure 3

- 3. Diurn al Profiles based on road type (use local for ―start‖) and whether the road is

urban versus rural

................................ ................................ ................................ .................. 69 Figure 3

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

...................... 70



## List of Appendic es

Appendix A: Revisions to PTIPM Sector SO2 and NOX emissions from V4 to V4.1 Appendix B: Creation of the modeling file (―ORL point file‖) parameters from the Boiler

MA CT ICR unit level emissions Appendix C: Pollutants in the onroad emission sectors generated from NMIM or MOVES2010 Appendix D: Approach to develop CMAQ PM2.5 species from Partially

- speciated MOVES2010

EXHAUST PM2.5 for the 2005 Platform, version 4.11



## 1 Introduction

The U.S. Environmental Protection Agency (EPA), here after referred to as ―we,‖ has developed

a n updated version of the 2005

- based air quality modeling platform , version 4.1 . This document
describes the emissions i nventory and emissions modeling for this version, focusing on the changes made from version 4 . The version 4 platform is documented at the emissions modeling clearinghouse website, http://www.epa.gov/ttn/ch ief/emch/ , under the section entitled ―2005

- Based Modeling Platform‖ and the subsection entitled ―CAP

- Hg

- BAFM 2005

- Based Platform
Version 4.1 ‖.

The platform consist s of Criteria Air Pollutants (CAPs) and the following select Hazardous Air Pollutants (HAPs ) : mercury (Hg)

, chlorine (C L2 ), hydrochloric acid or hydrogen chloride (HC L ) and benzene, acetaldehyde, formaldehyde and methanol. The latter four are also denoted BAFM

. This platform is called the ― CAP

- Hg

- BAFM 2005

- Based Platform, V ersion 4 .1 ‖ platform (we
will use the shortened name ―2005v4.1‖ in this documentation )

. This platform supports the Regulatory Impact Analysis for National Emission Standards for Hazardous Air Pollutants (NESHAP) for Industrial, Commercial, and Institutional Boilers and Proces s Heaters (a

. k

. a

. ―Boiler MACT‖) and the proposal for the Toxics rule

.

The underlying 2005 inventories used are: 1) the 2005 National Emission Inventory (NEI), version 2 ( http://www.epa.gov/ttn/chief/net/2005inventory.html ), 2) the 2005 National Air Toxics Assessment (NATA) mercury inventory from June 20 10, and 3) an inventory of Hg developed from the Boiler MACT Information Collection Request (ICR) for the National
Emissio n Standards for Major Sources: Industrial/Commercial/Institutional Boilers and Process Heaters (http://www.epa.gov/ttn/atw/boiler/boilerpg.html)

. This document describes the approach and data used to produce the emission inputs to the air quality model us ed in the

2005 v4.1 platform

.

Emissions preparation for the 2005 v 4.1 platform supports the Community Multiscale Air Quality (CMAQ) model ( http://www.epa.gov/AMD/CMAQ/ ) and (2) the Comprehensive Air Quality Model, with extensions (CAM X ) ( http://www.camx.com/ ) . Both models support modeling ozone (O 3 ), particulate matter (PM) and mercury (Hg)

, and require hourly and gridded emissions of
chemical species from the following inventory pollutants: carbon monoxide (CO), nitrogen oxides (NO X ), volatile organic compounds (VOC), sulfur dioxide (SO 2 ), ammonia (NH 3 ), particulate matter less than or equal to 10 microns (PM 10 ), individual component species for particulate matter less than or eq ual to 2.5 microns (PM 2.5 ) and individual component species of gaseous and particulate mercury (Hg). In addition, the CMAQ Carbon Bond 05 ( CB05 )
chemical mechanism with chlorine chemistry, which is part of the ―base‖ version of CMAQ, allows explicit treat ment of BAFM and includes HAP emissions of HC L and C L2

. The platform
BAFM emissions come from either the NEI values for benzene, formaldehyde, acetaldehyde and methanol (BAFM) or via speciation of NEI VOC into the component species

.

The effort to create t he emission inputs for the 2005v 4.1 platform included : ( 1 ) modification of emission inventories used for the 2005 v4 base case

, ( 2 ) updates to the emissions modeling ancillary files used with the emissions modeling tools,
and2

( 3 ) application of the emissions modeling tools.

The primary emissions modeling tool used to create the CMAQ model

- ready emissions was the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system ( http://www.smoke

model.org/index.cfm ) . We used SMOKE version 2.6 to create emissions files for a 36

- km national grid, a 12

- km Eastern grid and a 12

- km Western grid for a 2005 base case (also known as the ―2005cr_hg_05b‖ case for purposes of our directory structure). The purpose of this case is to provide a 2005 case that is consistent with the methods used in the future

- year base case and control cases. For regulatory applications, this case is included in the relative response factor ( RRF ) calculations.

Unlike the version 4 (v4) platform, t his platform includes only a base case; it does not include a model evaluation case. The evaluation case in the 2005 v4 platform uses 2005

- specific fire
emissions and 2005 hour

- specific continuous emission monitoring (CEM) data for electr ic generating units (EGUs) whereas the 2005 base case includes an ―average year‖ scenario for

fires and a illustrative (rather than year

- specific) temporal allocation approach for EGUs to allocate annual 2005 emissions to days and hours . This approach to temporal allocation was
used for all base an d control cases modeled to provide a temporal consistency that is intended to be a conceivable temporal allocation without tying the approach to a single year.

The 2005v4.1 platform was developed using the concepts, tools and emissions modeling data
from EPA‘s 2005v4 platform , documented by: ftp://ftp.epa.gov/EmisInventory/2005v4/2005_emissions_tsd_07jul2010.pdf (main document)

, ftp://ftp.epa.gov/EmisInventory/2005v4/2005_emissions_tsd_appendices_11may2010.pdf (appendices to the main document), and http://www.epa.gov/ttn/chief/emch/transport/tr_proposal_emissions_tsd.pdf (future year).

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

.

This document contains five sections and fo ur appendices. Section 2 describes the 2005 inventories input to SMOKE. Section 3 describes the emissions modeling and the ancillary files
used with the emission inventories. The development of the 20 16 inventor y (projected from 2005) is provided through technical support documents for the specific modeling applications

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

.

Electronic copies of the data used with SMOKE for the 2005 platform are available at the emissions modeling clearinghouse, http://www.epa.gov/ttn/chief/emch/ , under the section
entitled ―2005

- Based Modeling Platform‖ and the subsection entitled ―CAP

- Hg

- BAFM 2005

- Based Platform , Version 4.1 ‖

. This is referred to as the ―2005 v4 .1 web site‖ throughout this

document. In addition, this data is provided to the electronic docket in support of the Toxics
Rule.3



## 2 2005 emission inventories and approaches

This section describes the 2005 emissions data created for input to SMOKE. As with the 2005v4 platform, t he primary basis for the 2005 stationary source emission inputs is the 2005 National Emission Inventory (NEI), version 2, which includes emissions of CO, NO X , VOC, SO 2 , NH 3 , PM 10 , PM 2.5 and hazardous air pollutants (HAPs). The HAPs we used from this inventory are

mercury , chlorine (CL2), hydrogen chloride (HCL) , benzene, acetaldehyde, formaldehyde, and
methanol. We began with the same SMOKE

- formatted inventory inputs as the 2005v4 platform (case name: 2005ck_05b) and made changes described here

.

For mercury , the 2005v4 .1 platform uses a later version of the 2005 v2 NEI inventory prepared for the 2005 National Air Toxics Assessment (NATA) . It uses the June 18, 2010 version of the

2005 NATA inventory , with the exception of emissions from commercial, institutional and
indu strial boilers from the major source information co llection request (ICR) database and other changes described later

. The NATA inventory started with the 2005 v2 NEI, and was updated with data collected for some source categories

, which resulted in major update s to mercury
emissions for Portland c ement and h azardous waste combust ion. The NATA inventory was also revised as a result of comments received as part of the state, local and tribal review.

Documentation for the 2005 NEI can be found at: http://www.epa.gov/ttn/chief/net/2005inventory.html#documentation . For inventories outside of the United States, which include Canada and Mexico, we used the latest available bas e

- year inventories as discussed in Section 2.6

.

The 2005 NEI includes five sectors: nonpoint (formerly called ―stationary area‖) sources, point sources, nonroad mobile sources, onroad mobile sources, and fires. Because the 2005v 4.1 platform includes jus t a base case, the available day

- specific wildfires and prescribed burning

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

.

For purposes of preparing the air quality model

- ready emissions, we used the same split of the 2005 emissions inventory into ―platform‖ sector s for use in emissions modeling as was used in
the 2005v4 platform . The significance of an emissions modeling or ―platform‖ sector is that it is run through all of the SMOKE programs except the final merge (Mrggrid) independently from the other sectors. The final merge program combines the sector

- specific gridded, speciated and hourly emissions together to create the CMAQ

- ready emission inputs , which can be converted t o emissions that can be used by CAM X when needed

.

Similarly to 2005v4, we added sectors for biogenic emissions, emissions from the Canadian and Mexican inventories, and augmented with other emissio ns data to be explained below.

Table 2

- 1 presents the sectors in the 2005 platform . The sector abbreviations are provided in italics; these abbreviations are used in the SMOKE modeling scripts and inventory file names, and througho ut the remainder of this document. Updates from th e 200 5 v4 platform are
discussed in Table 2

- 2

.4

Table 2

- 1

. Platform se ctors used in emissions modeling for the 2005 platform , v ersion 4.1

Platform Sector 2005 NEI

Sector Description and resolution of the data input to SMOKE

EGU sector (also

called the IPM sector) : ptipm Point For all pollutants other than mercury (Hg): 2005v2 NEI point source EGUs mapped to the Integrated Planning Model (IPM) model using
the National Electric Energy Database System (NEEDS) 2006 version
4.10 database. A few revisions were made to the 2005v2 NEI annual

emission estimates as discussed in Table 2

- 2

. For Hg : 6/18/2010 version of the inventory used for the 2005 National Air Toxics Assessment (NATA) mapped to IPM using NEEDS
version 4.10. The NATA inventory is an update to the 2005v2 NEI
and was divided into EGU and non

- EGU sectors consistent with the other pollutants ( w e did not actually map the NATA inventory to IPM, but rather applied the mapping that was done to the 2005 NEIv2 to the

N ATA Hg inventory) . We additionally removed Hg from sources
from the National Emission Standards for Hazardous Air Pollutants
for Industrial, Commercial, and Institutional Boilers and Process

Heaters (aka ―Boiler MACT ‖ ) Information Collection Request (ICR)
database because we included these emissions in the non

- EGU sector.
For both: Day

- specific emissions created for input into SMOKE.

Non

- EGU sector (also called the

non
- IPM sector ) : ptnonipm Point For all pollutants other than Hg: All 2005v2 NEI point source records not matched to the ptipm sector. Includes all aircraft emissions. Additionally updated inventory to remove duplicates, improve estimates from ethanol plants, and reflect new information collected from industry from the ICR for the B oiler MACT

. I ncludes point source fugitive dust emissions for which county

- specific PM transportable fractions were applied. For Hg: The 6/18/2010 version of NATA inventory was used except for modifications to gold mine emissions and removal of Hg from facilities that closed prior to 2005. In addition, Hg emissions developed for the Boiler MACT were used
For both: Annual resolution

. Average

- fire

sector: avefire Not

applicable Average

- year wildfire and prescribed fire emissions

, unchanged from

the 2005v4 platform ; county and annual resolution. Agricultural

sector: ag Nonpoint NH 3 emissions from NEI nonpoint livestock and fertilizer application, county and annual resolution. Unchanged from the 2005v4 platform. Area fugitive dust

sector: afdust Nonpoint PM 10 and PM 2.5 from fugitive dust sources from the NEI nonpoint inventory after application of county

- specific PM transportable
fractions. Includes building construction, road construction, paved roads, unpaved roads, agricultural dust), county and annual resolution. Remaining nonpoint sector:
nonpt Nonpoint Primarily 2002 NE I nonpoint sources not otherwise included in other

SMOKE sectors ; county and annual resolution. Also includes updated Residential Wood Combustion emissions, year 2005 non

California WRAP oil and gas Phase II inventory and year 2005 Texas and Oklahoma oil and gas emissions. Removed Hg emissions from
boilers to avoid d ouble counting with Hg emissions added to the non

EGU sector from the Boiler MACT ICR

. Nonroad sector:
nonroad Mobile:

Nonroad Monthly nonroad emissions from the National Mobile Inventory

Model (NMIM) using NON ROAD2005 version nr05c

- BondBase, which is equivalent to NONROAD2008a, since it incorporated Bond5

Platform Sector 2005 NEI

Sector Description and resolution of the data input to SMOKE

rule revisions to some of the base case inputs and the Bond rule
controls did not take effect until later.
NMIM was used for all states except California. M onthly emissions for California created from annual emissions submitted by the California Air Resources Board (CARB) for the 2005v2 NEI

. locomotive, and

non
- C3
commercial
marine: alm_no_c3 Mobile:

Nonroad 2002 NEI non

- rail maintenance locomotives, and category 1 and

category 2 commercial marine vessel (CMV) emissions sources, county and annual resolution. Aircraft emissions are included in the

Non

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

conta ined in the seca_c3 sector

C3 commercial
marine: seca_c3 Mobile :

Nonroad Annual point source

- formatted

, year 2005 category 3 (C3) CMV

emissions, developed for the rule called ― Control of Emissions from New Marine Compression

- Ignition Engines at or Above 30 Liters per Cylinder‖, usually described as the Emissions Control Area (ECA) study ( http://www.epa.gov/otaq/oceanvessels.htm ). Utilized final projections from 2002

, developed for the C3 ECA proposal to the International Maritime Organization (EPA

- 420

- F

- 10

- 041, August 2010).

Onroad California,

NMIM

- based, and
MOVES sources not subject to temperature adjustments: on_noadj Mobile:

onroad Three, monthly, county

- level components:

1) California onroad, created using annual emissions for all pollutants, submitted by CARB for the 2005 NEI version 2

. NH 3 (not submitted by CARB) from MOVES2010. 2) Onroad gasoline and diesel vehicle emissions from MOVES2010 not subject to temperature adjustments: exhaust CO, N O X , VOC, NH3, benzene, formaldehyde, acetaldehyde, 1,3

- butadiene, acrolein, naphthalene, brake and tirewear PM, and evaporative VOC, benzene, and naphthalene

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

Onroad cold

- start gasoline exhaust
mode vehicle from MOVES subject to temperature adjustments:
on_moves_startpm Mobile:

onroad Monthly, county

- level MOVES 2010

- based onroad gasoline emissions

subject to temperature adjustments. Limited to exhau s t mode only for PM species and n aphthalene. California emissions not included. This

sector is limited to cold start mode emissions that contain different temperature adjustment curves from running exhaust (see on_moves_runpm sector).

Onroad running gasoline exhaust
mode vehicle from MOVES subject to temperature adjustments:

on_moves_runpm Mobile:

onroad Monthly, county

- level draft MOVES 2010

- based onroad gasoline

emissions subject to temperature adjustments. Limited to exhaust mode only for PM species and Naphthalene. California emissions not included. This sector is limited to running mode emissions that contain different temperature adju stment curves from cold start exhaust (see on_moves_startpm sector).

Biogenic: biog Not

applicable Hour

- specific, grid cell

- specific emissions gen erated from the

BEIS3.14 model, including emissions in Canada and Mexico. Other point
sources not from

the NEI: othpt Not

applicable Point sources from Canada‘s 2006 inventory and Mexico‘s Phase III

1999 inventory, annual resolution. Also includes annual U.S. offshore oil 2005v2 NEI point source emissions.6

Platform Sector 2005 NEI

Sector Description and resolution of the data input to SMOKE

Other point
sources not from the NEI, Hg only: othp t_hg Not

applicable Annual year 2000 Canada speciated mercury point source emissions.

Other nonpoint

and nonroad not
from the NEI:

ot har Not

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

Phase III (municipio resolution) nonpoint and nonroad mobile
inventories.

Other nonpoint
sources not from the NEI, Hg only: othar_hg Not

applicable Annual year 2000 Canada speciated mercury from nonpoint sources.

Other o nroad
sources not from

the NEI: othon Not

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

III (municipio resolution) onroad mobile inventories, annual
resolution.

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

2005 v4 .1 web site (see the end of Section 1 )

. The ―readme‖ file provided indicates the particular zipped files associated with each platform sector.

Before discussing the specific components of the 2005 v4.1 emissions platform, we provide in
Table 2

- 2 a summary of the significant differences between the 200 5v4 emissions platform and
this 2005v4 .1 platform.7

Table 2

- 2

. Summary of s ignificant c hanges between v4 and v 4.1 p latform s by s ector

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

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

values, and for a subset of these, recomput ed annual emissions of NO X , SO 2 or both using 2005 CEM data , resulting in lower NO X and/or SO 2 for CA, MA, NY, SC and increasing for MS and WV as sho wn below

CA NOX down 75.4 tons ; SO2 down 21.1 tons
MA NOX down 483 tons ; SO2 down 1533.4 tons

NY NOX down 149.3 tons
SC NOX down 1166.2, tons SO2 down 1.3 tons
MS SO2 up 929.7 tons

WV NOX up 142.5 tons Appendix A , Table A

- 1 provides a facility

- level summar y of these changes. Only replaced emissions if 2005 CEM data were confirmed to be for the entire year (some CEM is only for the summer season)

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

ver sion of the NATA 2 005 inventory except for units matched to the Boiler
MACT ICR database. Hg emissions for units matched to units in the Boiler MACT ICR database were
removed ( summing to 0. 045 tons Hg) . The Boiler MACT ICR database Hg
emi ssions were used for these in place of the NATA Hg values, but were included in the ptnonipm sector.

Non

- IPM sector: ptnonipm Revised 2005 emissions for many point sources other than EGUs to

remove duplicates, improve estimates from ethanol plants, and reflect new
emissions and controls information collected from industry and a state through the Boiler MACT ICR

. A summary of these NOx, SO2, and
PM2.5 emissions from v4 to v4.1 are listed:

State NOX change
v4 to v4.1 SO2 change

v4 to v4.1 PM2.5 change

v4 to v4.1

Cal ifornia 30 39 1
Georgia

- 1,242

- 1,614

- 28

Indiana

- 4,941

- 7,379

- 1,291

Iowa 2,519 3,206 100

Kansas 73 93 3
Kentucky 121 154 5

Nebraska 31 39 1

New Mexico 182 231 7

North Carolina

- 6,701 0

North Dakota 128 220 13

Ohio

- 366

- 3,303 0
Pennsylvania 101

- 2,035

South Dakota 236 301 10

Tennessee

- 6,098

- 11,046

- 760

Hg emissions changed to use NATA inventory. Updated NATA inventory to remove closed plants and also replaced boiler Hg with for units mapped to Boiler MACT ICR database with the ICR Hg emissions. Average

- fire

sector: avefire Unchanged from 2005v4 platform8

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

sector: ag Unchanged from 2005v4 platform

Area fugitive dust

sector: afdust Unchanged from 2005v4 platform

Remaining nonpoint sector:
nonpt Added : year 2005 oil and gas data f or Texas and Oklahoma provided by these

s tates. Re placed previous Oklahoma oil and gas emissions from this sector ( SCC 2310000000)

. No removals for Texas since the new oil and gas emissions only

cover oil rig emissions that are in the nonroad sector. The nonroad sector
emissions were not removed because they were very small compared to the newer

Texas oi l and gas emissions added to this sector and the possibility of double counting was not able to be confirmed by EPA. Changed pesticide category to

― no

- integrate,‖ thereby using VOC speciation (rather tha n the HAP emissions) to compute the BAFM emissions.

Nonroad sector:
nonroad Added PM to 7 California counties which were found to be 0 in the 2005v4

platform

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

, which had the s ame PM values as the 2005v2 NEI other than in the missing counties, for which nonzero PM values were provided. locomotive, and

non
- C3
commercial
marine: alm_no_c3 Unchanged from 2005v4 platform

C3 commercial
marine: seca_c3 Revised 2005 emissions from the category 3 commercial marine sector to reflect

the final projections from 2002 developed for the category 3 commercial marine Emissions Control Area (ECA) proposal to the International Maritime Organization (EPA

- 420

- F

- 10

- 041, August 2010)

. Also project ed Canada as part of the ECA rather than an ―outside the ECA‖ region

, using region

- specific growth rates . For example, British Columbia emissions were projected the same as ―North Pacific‖ growth and control used in Washington.

Therefore the v4.1 seca_c3 inventories contain Canadian province codes. Hg was not used in the 2005v4.1 platform due to uncertainties in the values.

Onroad California,

NMIM

- based, and
MOVES sources not subject to temperature adjustments: on_noadj For all states except California: All pollutants and modes (exhaust, tire and brake

wear) from all vehicle types are now from MOVES2010 except for Hg. Hg is from
2005v2 NEI, based on the MOBILE6 model. In the 2005v4 platform, only exhaust

mode onroad gasoline vehicles, other than motorcycles, were included from
MOVES in this sector and the rest had been from MOBILE6.

For California: Replaced NMIM

- based NH 3 with MOVES2010 emissions for
California b ecause California does not provide NH 3 in its onroad inventory

. For
the 2005v 4 platform, w e used NH 3 from NMIM but since MOVES generates all criteria pollutants, we now use MOVES.

Onroad cold

- start gasoline exhaust
mode vehicle from MOVES subject to temperature adjustments:
on_moves_startpm For the 2005v 4.1 platform , this sector uses MOVES2010 based emissions for all

exhaust mode onroad gasoline vehicle types including motorcycles. In the v 4 version, motorcycle exhaust mode PM emissions relied on NMIM and were therefore in the on_noadj sector

, and other exhaust mode gasoline vehicle PM
emissions used the draft version of MOVES. As with v 4, the se PM and naphthalene cold start mode emissions are subject to grid cell and hourly temperature adjustments. Onroad running Same change as ― on_moves_startpm ”9

Platform Sector Summary of Significant Inventory Differences from V4 to V4.1 gasoline exhaust
mode vehicle from
MO VES subject to temperature adjustments:

on_moves_runpm Biogenic: biog Unchanged from 2005v4 platform Other point
sources not from

the NEI: othpt Unchanged from 2005v4 platform

Other point
sources not from the NEI, Hg only: othpt_hg Unchanged from 2005v4 platform

Other nonpoint

and nonroad not
from the NEI:
othar Unchanged from 2005v4 platform

Other nonpoint
sources not from the NEI, Hg only: othar_hg Unchanged from 2005v4 platform

Other onroad
sources not from

the NEI: othon Unchanged from 2005v4 platform

Annual emission summaries for 2005 v4.1 , with comparisons to 2005v4 CAPs emissions by emissions modeling sector are provided in Table 2

- 3

. VOC totals are before BAFM speciation (i.e., they are inventory VOC emissions, and not the sum of VOC emissions after BAFM speciation )

. Summaries of Hg (speciated), HCL and CL2 are provided in Table 2

- 4 , and Table

2

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

The emission inventories for input to SMOKE for the 2005 base case are available at the 2005v4
web site (see the end of Section 1 ) under the link ―Data Files‖ (see the ―2005emis‖ directory). The inventories ―readme‖ file indicates the particular zipped files associated with each platform

sector10 Table 2

- 3

. 2005 Emissions by Sector: VOC, NOX, CO, SO2, NH3, PM10, PM2.5

Sector 2005

VOC [ tons/yr] 2005 NOX [tons/yr] 2005 CO [tons/yr] 2005 SO2 [tons/yr] 2005 NH3 [tons/yr] 2005 PM10 [tons/yr] 2005 PM2_5 [tons/yr]

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

a fdust 8,858,992 same 1,030,391 same

ag 3,251,990 same alm_no_c3 67,690 same 1,924,925 same 270,007 same 154,016 same 773 same 59,366 same 56,687 same seca_c3 ( US component) 44,990 22,367 647,884 642,088 54,049 53,746 420,110 417,312 53,918 53,580 49,541 49,294

seca_c3 (non

US component) 18,367 18,241 532,181 526,760 43,267 42,959 321,414 319,200 43,326 43014 39,810 39,574

n onpt 7,530,564 7,474,512 1,699,532 1,683,490 7,413,762 7,376,314 1,259,635 1,252,645 134,080 134,080 1,354,638 1,349,685 1,081,816 1,076,954

nonroad 2,691,844 same 2,115,408 same 19,502,718 same 197,341 same 1,972 same 211,807 209,100 201,138 198,734 on_noadj 3,949,362 3,123,642 9,142,274 7,203,876 43,356,130 41,647,066 177,977 144,216 156,528 295,203 308,497 170,554 236,927 115,991

on_moves

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

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

ptipm 40, 950 same 3,726,459 3,728,190 601,564 same 10,380,786 10,381,411 21,684 same 615,095 same 508,903 same ptnonipm 1,310,784 1,310,085 2,238,002 2,247,228 3,221,388 3,222,221 2,089,836 2,117,649 158,837 159,003 653,048 653,957 440,714 442,656

avefire 1 ,958,992 same 189,428 same 8,554,551 same 49,094 same 36,777 same 796,229 same 684,035 same
Canada ot har 1 1,281,095 same 734,587 same 3,789,362 same 95,086 same 546,034 same 1,666,188 same 432,402 same Canada othon 270,872 same 524,837 same 4,403,745 same 5,309 same 21,312 same 14,665 same 10,395 same
Ca nada othpt 447,313 same 857,977 same 1,270,438 same 1,664,040 same 21,268 same 117,669 same 68,689 same
Me xico othar 586,842 same 249,045 same 644,733 same 101,047 same 486,484 same 143,816 same 92,861 same
Me xico othon 183,429 same 147,419 same 1,455,121 same 8,270 same 2,547 same 6,955 same 6,372 same
Me xico othpt 113,044 same 258,510 same 88,957 same 980,359 same 0 same 125,385 same 88,132 same off shore othpt 51,240 same 82,581 same 89,812 same 1,961 same 0 same 839 same 837 same
1. Canada provided 2006 fires but we did not use them in the 2005 platform (for neither v4.1 nor v4)11 Table 2

- 4

. Summaries of Hg (speciated), HC L and CL2 *

2005 HGIIGAS (divalent gaseous

mercury ) [tons/yr] 2005 HGNRVA

(elemental

mercury ) [tons/yr] 2005 PHGI

(particulate

mercury ) [tons/yr] 2005

HCL [tons/yr] 2005

CL2 [tons/yr]

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

alm_no_c3 0.0411 same 0.0793 same 0.0212 same 1.38 same

seca_c3 ** 0.0002 ** 0.0004 ** 0.0001

seca_c3 non

- US ** 0.0001 ** 0.00018 ** 0.00007

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

N onroad 0.1041 same 0.2105 same 0.0533 0.0533

on_noadj 0.1402 same 0.5036 same 0.0599 0.0599

P tipm 21.096 21.1757 30.1986 30.318 1.6596 1.6136 351,592 same 99 same

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

Canada othar

_hg 1.08 0.86 0.34

Canada oth pt_hg 1.72 3.59 0 .5
* The sectors afdust, ag, avefire, on_moves_runpm, and on_moves_startpm have no Cl or Hg emissions

** Due to uncertainty in mercury emissions from this sector, they were removed from the inventories and not used for the V4.1

Platform . The amount removed from the 2005 data was the 2005v4 values, and summed to approximately 0.001 tons total mercury for the sum of U.S. and non

- U.S. components

In addition to the anthropogenic sec tors, we include speciated hourly emissions for the geogenic categories listed in Table 2

- 5

. These are the same as had been used in the previous platforms except for the land

- direct emissions which were reduced by 90% based on updated information
from the literature as described in Section 2.7

.
Table 2

- 5

. Summaries of the non

- anthropogenic mercury across the modeling domain

Region Species Land

direct [tons/yr] Land

recycled [tons/yr] Ocean

D irect [tons/yr] Ocean

R ecycled [tons/yr] V olcanic

[tons/yr]

Domain

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

The remainder of Section 2 provides details of the data contained in each of the 2005 platform sectors. Different levels of detail are provided for different sectors depending on the availability

of reference information for the data, the degree of changes or manipulation of the data needed for preparing it for i nput to SMOKE, and whether the 2005 v4.1 platform emissions changed appreciably since the previously

- documented 200 5v4 platform.



### 2.1 2005 NEI Poi

nt sources (ptipm and ptnonipm)

Point sources are sources of emissions for which specific geographic coordinates (e.g., latitude/longitude) are specified, as in the case of an individual facility. A facility may have12

multiple emission points, which may be characterized as units such as boilers, reactors, spray booths, kilns, etc. A unit may have multiple processes (e.g., a boiler that sometimes burns residual oil and sometimes burns natural gas). Note that this section describes only NEI point

sources wi thin the contiguous United States . The offshore oil platform (othpt sector) and category 3 CMV emissions (seca_c3 sector ) are also point source format ted inventories that are discussed in Section 2.6

.

After removing offshore oil platforms (othpt sector), we created two platform sectors from the remaining 2005v2 NEI point sources for input into SMOKE: the EGU sector

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

- EGU sector

– also called the

non

- IPM sector ( i.e., ptnonipm). This split facilitates the use of different SMOKE temporal processing and future year projection techniques for each of these sectors. The inventory pollutant s processed through SMOKE for both ptipm and ptnonipm sectors were: CO, NO X , VOC, SO 2 , NH 3 , PM 10 , PM 2.5 and the following HAPs: HC L (pollutant code = 7647010 ) , CL2 ( code = 7782505 ) and mercury (codes: 199, 200, 201, 202, 22967926, 593748, 62384, 7439976

, and 7487947) . We did not utilize BAFM from these sectors as we chose to speciate VOC without any use (i.e., integration) of VOC HAP pollutants from the inventory (integration is
discussed in detail in Section 3.1.2.1 ). We utilized Hg from the NATA Hg point source
inventories with the modifications discussed below

.

The ptnonipm emissions were provided to SMOKE as annual emissions. The ptipm emissions
for the base case were input to SMOKE as daily emissions.

D ocumentation for the developme nt of the 2005 point source NEI v2, is at: http://www.epa.gov/ttn/chief/net/2 005inventory.html#documentation . A summary of this
documentation describes these data as follows:

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

EPA' s Acid Rain Program for Continuous Emissions Monitoring System (CEMS ) reporting . The following approach applied to units in the 2002 NEI that matched to 2005 CEMS units. For pollutants covered by the CEMS, the 2005 CEMS data were used. For CEMS units with pollutants not covered by CEMS (e.g., VOC, PM 2.5 , HCL) unit

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

estimates.

2. Non

- EGU stationary s ource development for the 2005 NEI focused on improving the following sectors:

a. HAP data received from States and industry to support t he MACT program, including the recent Risk a nd Technology Review rulemaking
b. 2005 State, local, and tribal data submitted to EPA under the C onsolidated Emissions Reporting Rule (CERR)

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

p ollutants
d. Off

- shore platform data from Mineral Management Services (MMS)13

The changes made to the 2005v2 NEI non

- EGU point inventory prior to modeling are as follows:

The tribal data, which do not use state/county Federal Information Processing Standards (FIPS) codes in the NEI, but rather use the tribal code, were assigned a state/county FIPS code of 88XXX, where XXX is the 3

- digit tribal code in the NEI. We made this change because SMOKE requires the 5

- digit state/county FIPS code.

We defaulted stack parameters for some point sources when modeling in SMOKE. SMOKE uses an ancillary file, called the PSTK file, which provides default stack parameters by SCC code to either gap fill stack parameters if they are missing in the NEI or to correct stack p arameters if they are outside the ranges specified in SMOKE as acceptable values. The SMOKE PSTK file is contained in the ancillary file directory of
the 2005 v4 web site (see the end of Section 1 )

. We applied a transport fraction to all SCCs that we identified as PM fugitive dust, to prevent the overestimation of fugitive dust impacts in the grid modeling as described in
Section 2

. 2

. 1.

We also made a changes to the 2005 NATA Hg inventory (June 18 , 2010 version) prior to its use in modeling . We removed sources that were discovered to have closed prior to 2005 . We
modified gold mine emissions based on information collected as part of the data gathering for the

propo sed gold mine rule. We replaced Hg emissions with values in the Boiler MACT ICR
database. Of the 1607 facilities in the Boiler MACT ICR database, all except for 184 facilities (0.177 tons Hg) were matched to inventory (NATA inventory, NEI v2 inventory o r both) facilities based on the NEI_UNIQUE_ID code. The 184 facilities without NEI_UNIQUE_IDs were not used in our 2005 Hg inventory for the platform. Since the ICR database contained only emissions by unit and the fuel type, we needed to assign the geographic coordinates and stack parameters needed to transform the Boiler MACT ICR database into a modeling file. We used geographic coordinates and stack parameters from the NATA Hg inventory (or NEI v2 if not in the NATA inventory) by matching the facility and then choosing the parameters from the process/unit that matched the fuel type in the ICR . If more than one unit matched, we used the stack parameters from the unit with the highest emissions. Where there were no fuel matches,
we used defaul t parameters. Additional information on these changes is provided in Table 2

- 6
below. Further d etails of this procedure, and the other fields we populated to constru ct the modeling file are provided in Appendix B.

Because the NATA Hg point source emissions were not separated into ptnonipm and ptipm, we applied the same point splits (via the field IPM_YN) to the NATA Hg inventory as were applied
to the 2005v2 NEI

.14

Table 2

- 6

. Hg changes made to the 2005 NATA Hg inventory (June 18, 2010 version) for the 2005 ptnonipm

, ptipm

, and nonpt sectors

. Change Incorporate d Boiler MACT
ICR emissions Added 4.66 tons Hg from ICR unit

- level emissions data. Generated modeling parameters (latitudes/longitudes, stack

p arameters) from the NATA Hg or NEI inventories, by matching ICR facilities/fuel information to matching facility identifiers (the NEI_UNIQUE_ID) and fuel types in thes e other modeling
inventories.

Removed 0.045 tons Hg from ptipm which is the sum of Hg from sources that and matched a facility in the ICR based on the NEI_UNIQUE_ID and either (1) had a design capacity of less than 25 MW and matched a facility in the ICR o r (2) had no design capacity listed had a MACT code beginning with 0107 , which is the general code for identify industrial, commercial, institutional boilers and process heaters.

Removed 1.71 tons Hg from ptnonipm

- we used a crosswalk that
link combinatio ns of Maximum Achievable Control Technology (MACT) code, standard industrial code (SIC), NAICS (North American Industrial Classification System) code and source classification code (SCC ) to identify industrial, commercial,
institutional (ICI) boilers and process heaters, and removed all
records that matched the ICR facilities based on the NEI_UNIQUE_ID.

Removed 3.15 tons Hg from nonpt

– we used a crosswalk that link combinations of MACT and SCC to ICI boilers and process
heaters and removed all records 4. 68 to in the nonpt sector that
matched. Change d Gold Mine
Emissions , geographic
coordinates and stack
parameters Changed facility emissions for nine out of 19 facilities in the ptnonipm sector based on data collected for the proposed National
Emission Sta ndards for Hazardous Air Pollutants for Gold Mine Ore Processing and Production, provided by the EPA Sector Policies and Programs Division (SPPD) project lead Chuck
French. These changes are summarized below, and result in an overall total change of Hg emissions from Goldmines from 2.35 to 2.50

tons.

State facility ID Facility name Updated
Hg

emissions BASIS

89406KNNCT55MIL KENNECOTT RAWHIDE

MINING CO 0.02 based on 2007

emissions test data

89045SMKYV1SMOK SMOKY VALLEY COMMON

OPERATION 0.03 based on 2007

emissions test data

T$18242 RUBY HILL MINE 0.018 based on 2007

emissions test data

89418FLRDCEXIT1 STANDARD MINING INC 0.08 based on 2008

emissions test data15 89419CRRCH180EX COEUR ROCHESTER INC 0.069 based on 2007

emissions test data

89438NWMNTSTONE NEWMONT MINING CORP

LONE TREE MINE 0.311 based on 2006

emissions test data

89801JRRTT50MIL JERRITT CANYON MINE 0.23 is for the 2004

- 05

timeframe based on

the estimate

submitted to Nevada
DEP in response to
ICR survey sent to the company.

89803BLDMN70MIL BALD MOUNTAIN MINE 0.14 based on 2008

emissions test data

89803BRRCK27MIL BARRICK GOLDSTRIKE MINES

INC 0.35 based on 2007

emissions test data

Also changed geographic coordinates and stack parameters for

10 facilities based on information provided by Chuck French that was used in local scale modeling done in support of the NESHAP in early 2010.

Facility Name

GLAMIS MARIGOLD MINE Refinery building operations

NEWMONT MINING CORP
CARLIN SOUTH Refinery and roasting operations

NEWMONT MINING CORP
TWIN CREEKS MINE Refinery and autoclave operations

SMOKY VALLEY COMMON
OPERATION Refinery building operations

CORTEZ GOLD MINES Refinery building operations

RUBY HILL Refinery building operations

BARRICK GOLDSTRIKE Refinery, autoclave & roasting operations

WESTERN MESQUITE MINES Refinery building operations

CRIPPLE CREEK COLORADO Refinery building operations

GREENS CREEK WA Refinery building operations

Removed Hg emissions for
sources closed or not operating in 2005 Removed 0.342 tons, most of which (0.337 tons) is associated with the removal of Northwestern Steel & Wire Co, Illinois ( NEI_UNIQUE_ID NEIIL1955ABD), which shut down prior to
2005. Other removals were: Arkwright, Georgia (NEI12787) CPSG Gould Street, Maryland (NEI7008) State sent article
written in 2008 ( http://www.thefreelibrary.com/Constellation+ Energy+Restarts+Gould+Street+Power+Plant+in+Baltimore.

- a0179900776 ) that said it had been shut down for the last 5 years and would be re

- opening as a gas fired plant onl y. Midwest Generation LLC, Illinois (NEIIL0638266). Northwestern Steel & Wire Co, Illinois (NEIIL1955ABD)16



### 2.1.1 IPM sector (ptipm)

Th e ptipm sector contains emissions from EGUs in the 2005v2 NEI point inventory that we were
able match to the units found in the NEEDS database . While we originally used version 3.02 of

NEED S to split out the ptipm sector for v4 of the platform, there were no changes to the mapping when we moved to NEEDs version 4.10 ( http://www.epa.gov/airmarkets/progsregs/epa

- ipm/index.html ). The IPM model provides
future

- year emission inventories for the universe of EGUs contained in the NEEDS database. As described below, this matching was done to (1) provide consiste ncy between the 2005 EGU sources and future year EGU emissions for sources which are forecasted by IPM and (2) avoid double counting in projecting point source emissions.

The 2005v4 platform document provides additional details on how the 2005 NEI point s ource inventory was split into the ptipm and ptnonipm sectors.

Although we used the same ptipm split as was used for the v4 platform, we change d some emissions values based o n updates we made to some ORIS i dentifiers in the ptipm file. For a
subset of the units for which we added or changed ORIS i dentifiers, we recomputed annual
emissions for SO 2 , NO X or both using the CEMS data available at the EPA‘s data and maps
website. 2 The impact of these changes is summarized in Table 2

- 2 and detailed changes are provided in Appendix A.

Creation of temporally resolved emissions for the ptipm sector

Another reason we separated the ptipm sources from the other sources was due to the difference in the temporal resolution of the data input to SMOKE. For the base case 2005 run, the ptipm sector uses daily emissions input into SMOKE. The daily emissions are computed from the annual emissions. First, we allocate annual emissions to each month (this process occurs outside of SMOKE). To do this, we created state

- specific, three

- year averages of 2004

- 2006 CEM data. These average annual

- to

- month factors were assigned to sources by state. To allocate the monthly emissions to each d ay, we used the 2005 CEM data to compute state

- specific month

- to

day factors, averaged across all units in each state. The resulting daily emissions were input into SMOKE. The daily

- to

- hourly allocation was performed with SMOKE using diurnal profiles.

T he development of these diurnal ptipm

- specific profiles, which are considered ancillary data for SMOKE, is described in Section 3.2.3

.



### 2.1.2 Non

- IPM sector (ptnonipm)

The non

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

. 3 The ptnonipm sector contains fugitive dust PM emissions from vehicular traffic on paved or unpaved roads at industria l facilit ies or coal handling at coal mine s

. 4
Prior to input to SMOKE, we reduced the fugitive dust PM emissions to estimate the emissions

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

3 Except for the offshore oil and day

- specific point source fire emissions data which are included in separate secto rs, as discussed in sections 2.6 and 2.3.1, respectively.

4 Point source fugitive dust emissions, which represent a very small amount of PM, were treated the same way in the 2002 platform but were treated as a separate sector in the 2001 Platform.17

that remain aloft by applying county

- specific fugitive dust transportable fraction factors. This is

discussed furth er in Section 2.2.1.

For some geographic areas, some of the sources in the ptnonipm sector belong to source categories that are contained in other sectors. This occurs in the inventory when states, tribes or local programs report certain inventory emissi ons as point sources because they have specific geographic coordinates for these sources. They may use point source SCCs (8

- digit) or non

point, onroad or nonroad (10

- digit) SCCs. In the 2005 NEI, examples of these types of sources
include: aircraft emi ssions in all states, waste disposal emissions in several states, firefighting training in New Mexico, several industrial processes and solvent utilization sources in North Carolina and Tennessee, livestock (i.e., animal husbandry) in primarily Kansas and Minnesota, and petroleum product w orking losses

.

The modifications between the published 2005v2 NEI and the 2005 inventory we used for modeling are summarized here:

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

Removed duplicate annual records. We did not delete some apparent duplicates because they were in fact covering different parts of the year (i.e., the emissions in the inventory
file were sub

- annual).

Removed a source with a state/county FIPS code of 3077 7; the ―777‖ county FIPS represents portable facilities that move across counties, but is not currently a valid state/county FIPS code in the SMOKE ancillary file ―COSTCY‖. This Montana FIPS code was located in northern Wyoming and contained very small em issions.

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

Fixed the coordinates for several larger sources that had a state/county FIPS code mismatch with their inventory coordinates greater than 10 km and emissions greater than

10 t ons per year of either NOX, VOC, SO2, or 5 tons/yr of PM2.5. These corrections were limited to a small number of plants in Arizona, Indiana, Kentucky, Ohio, and Virginia.

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

Found a nd removed additional duplicate records. These records were duplicates caused by records from both 2002 and 2005 being in the inventory. These were caught after ignoring leading zeroes in the plant IDs, point IDs, etc. that were present for only one of t he years of data. There were a total of 175 records removed. A summary of the emissions removed is provided below. Due to the small mass of duplicate HAP records and the fact that most were not being used in the platform, no HAP records were removed.

CO 3,520 tons
NH 3 166 tons
NO X 13,421 tons
PM 10 3,858 tons
PM 2.5 3,444 tons
SO 2 21,061 tons
VOC 1,504 tons18

Removed duplicate emissions for Blue Ridge Paper (FIPS=37087). For the same unitid,
stackid and SCC there were two records for the same pollutant with different data source codes but similar emissions values. They appeared to be duplicates so they were removed.

Updated boiler emissions at Domtar Paper/Johnsonburg Mill (FIPS code =42047), which
included 2002 emissions values to 2005 emissi ons values based on information provided by the Department of Environmental Protection in Pennsylvania. They had put on scrubbers between 2002 and 2005 and that was not reflected in the platform 2002

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

2005. Note: We only changed NO X , SO 2 and HCL even though the facility representative send information for all pollutants plant because of the effort involved with converting the information provided into a form usa ble for modeling.

Removed unit

- level emissions from plants for units determined to have shut down between 2002 and 2005. In all situations, the state inventory representative was contacted to confirm that the unit actually shut down. Plants impacted were : LaFarge Cement Plant in Atlanta Georgia, Domtar Paper, Tennessee, FIPS=47163 and P. H. Glatfelter Company in Chillicothe, Ohio.

Added North Dakota ADM facility (FIPS code = 38067) that was in the 2005v1 NEI but was missing from the 2005v2 NEI and was no t determined to have shut down. Added the

2002

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

Added an inventory of 2005 ethanol plants using plant names and data provided by EPA‘s Office of Transportation and Air Quality for use in a previous modeling effort (Renewable Fuel Standards 2), which included these with the 2005v1 inventory. The list below includes only the ethanol plants that were used in the previous modeling effort but were missing from the 2005v2 NEI

.

State/Coun ty
FIPS code Plant Name CO (tons /yr ) NOX

(tons /yr ) PM10

(tons /yr ) PM2_5

(tons /yr ) SO2

(tons /yr ) VOC

(tons /yr )

0 6065 Golden Cheese Company of CA 10.47 30.31 12.13 1.29 38.58 14.33

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

19033 Golden Grain Energy LLC 146.60 424.38 169.75 15.33 540.12 200.62

19035 Little Sioux Corn Processors 184.30 533.51 213.40 19.27 679.01 252.20

19055 Permeate Refining 3.14 9.09 3.64 0.39 11.57 4.30

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

19083 Hawkeye Renewables, LLC 115.19 333.44 133.38 14.21 424.38 157.63

19093 Quad

- County Corn Processors 56.55 163.69 65.48 6.97 208.33 77.38

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

21047 Commonwealth Agri

- Energy, LLC 46.08 133.38 53.35 4.82 169.75 63.05

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

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

35041 Abengoa Bioenergy Corporation 10.47 30.31 12.13 1.09 38.58 14.33

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

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

19109 Global Ethanol 29.32 84.88 33.95 3.07 108.02 40.12

20055 Reeve Agri

- Energy 52.36 151.57 60.63 6.46 192.90 71.65

TOTAL TONS 1103.73 3195.00 1278.00 127.13 4066.36 1510.36



### 2.2 2005 Nonpoint sources (afdust, ag, nonpt)

The 2005v2 NEI generally did not include updated nonpoint emissions from values used in the 2002 NEI, and this modeling platform took a similar approach. Consequently, w e created several sectors from the 2002 nonpoint NEI. We removed the nonpoint tribal

- submitted19

emis sions to prevent possible double count ing with the county

- level emissions . Because the tribal nonpoint emissions are small, we do not anticipate these omissions having an impact on the
results at the 36

- km and 12

- km scales used for modeling

. This omission also eliminated the need for us to develop spatial surrogate data for allocation of tribal data to grid cells during the SMOKE processing , with little expected impact

.

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

In the rest of this section, we describe in more detail each of the platform sectors into which we separated the 2005 nonpoint NEI, and the changes we made to these data. We will refer to the 2002 platform documentation for sectors that did not change.



### 2.2.1 Area Fugitive dust sector (afdust)

The emissions for this sec tor are unchanged from the 2005v4 platform, and the documentation is repeated here for convenience. However, we changed the temporal allocation of the emissions to account for day

- of

- week variation . In particular, we used updated dust profiles that are

c onsistent with the activity related to non

- dust profiles for similar processes. The processes and profiles updated are provided in Pouliot, et. al., 2010. Previously, all days within the same
month had the same emissions.

The area

- source fugitive dust ( afdust) sector contains PM 10 and PM 2.5 emission estimates for 2002 NEI nonpoint SCCs identified by EPA staff as dust sources. This sector is separated from other nonpoint sectors to make it easier to apply a ―transport fraction

, ‖ which reduces emissions

t o reflect observed diminished transport from these sources at the scale of our modeling. Application of the transport fraction prevents the overestimation of fugitive dust impacts in the grid modeling as compared to ambient samples. Categories included i n this sector are paved roads, unpaved roads and airstrips, construction (residential, industrial, road and total)

, agriculture production and all of the mining 10

- digit SCCs beginning with the digits ―2325.‖ It does not include fugitive dust from grain e levators because these are elevated point sources.

We created the afdust sector from the 2002 NEI based 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

- digit nonpoint SCCs) is provided at: http://www.epa.gov/ttn/chief/emch/dustfractions/tf_scc_list2002nei_v2.xls . However, not all of the SCCs in this file are present in the 2002 NEI. The SCCs included in the 2002 NEI that comprise the 2005 ( and 2002) platform afdust sector (which are a subset of the SCCs in the web link) are provided in Table 2

- 7

.20 Table 2

- 7

. SCCs in the afdust platform sector

SCC SCC Description

2275085000 Mobile Sources;Aircraft;Unpaved Airstrips;Total

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

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

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

2296010000 Mobile Sources;Unpaved Roads;Industr ial Unpaved Roads;Total: Fugitives

2311000000 Industrial Processes;Construction: SIC 15

- 17;All Processes;Total

2311010000 Industrial Processes;Construction: SIC 15

- 17;Residential;Total

2311010040 Industrial Processes;Construction: SIC 15

- 17;Residential;Ground Excavations

2311010070 Industrial Processes;Construction: SIC 15

- 17;Residential;Vehicle Traffic

2311020000 Industrial Processes;Construction: SIC 15

- 17;Industrial/Commercial/Institutional;Total

2311020040 Industrial Processes;Construction: SIC 15

- 17;Industrial/Commercial/Institutional;Ground

Excavations

2311030000 Industrial Processes;Construction: SIC 15

- 17;Road Construction;Total

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

2801000000 Miscellaneous Area Sources;Agriculture Production

- Crops;Agriculture

- Crops;Total

2801000002 Miscellaneous Area Sources;Agriculture Production

- Crops;Agriculture

- Crops;Planting

2801000003 Miscellaneous Area Sources;Agriculture Production

- Crops;Agriculture

- Crops;Tilling

2801000005 Miscellaneous Area Sources;Agriculture Production

- Crops;Agriculture

- Crops;Harvesting

2801000007 Miscellaneous Area Sources;Agriculture Production

- Crops;Agriculture

- Crops;Loading

2805000000 Miscellaneous Area Sources;Agriculture Production

- Livestock;Agriculture

- Livestock;Total

2805001000 Miscellaneous Area Sources;Agriculture Production

- Livestock;Beef cattle

- finishing

operations on feedlots (drylots);Dust Kicked

- up by Hooves (use 28

- 05

- 020,

- 001,

- 002, or

- 003 for Waste

Our approach was to apply the transportable fractions by county such that all afdust SCCs in the same county receive the same factor. The approach used to calculate the county

- specific transportable fractions is based on land use data and is described by : http://www.epa.gov/ttn/chief/emch/dustfractions/transportable_fraction_080305_rev.pdf

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

, which would be expected due to seasonal changes in vegetative cover. Further, the variability due to soil moisture, precipitation, and wind speeds is not accounted for by the methodology. An electronic version of the county

- level transport fractions can be found at: http://www.epa.gov/ttn/chief/emch/dustfractions/transportfrac tions052506rev.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 2005v4 .1 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)

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

co mpleteness

.

The agricultural NH 3 ―ag‖ s ector is comprised of livestock and agricultural fertilizer application emissions from the nonpoint sector of the 2002 NEI. This sector is unchanged in the 200521

platform. The rest of this section documentation is therefore very similar to that in the 200 2
documentation.

In building this sector we extracted livestock and fertilizer emissions based on the SCC. The
livestock SCCs are listed in Table 2

- 8

, and the fertil izer SCCs are listed in Table 2

- 9

.
Table 2

- 8

. Livestock SCCs extracted from the 2002 NEI to create the ag sector

SCC SCC Description*

2805000000 Agriculture

- Livestock;Total

2805001100 Beef cattle

- finishing operations on feedlots (drylots);Confinement

2805001200 Beef cattle

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

2805001300 Beef cattle

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

2805002000 Beef cattle production composite;Not Elsewhere Classified

2805003100 Beef cattle

- finishing operations on pasture/range;Confinement

2805007100 Poultry production

- layers with dry manure management systems;Confinement

2805007300 Poultry production

- layers with dry manure management systems;Land application of manure

2805008100 Poultry production

- layers with wet manure management systems;Confinement

2805008200 Poultry production

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

2805008300 Poultry production

- layers with wet manure management systems;Land application of manure

2805009100 Poultry production

- broilers;Confinement

2805009 200 Poultry production

- broilers;Manure handling and storage

2805009300 Poultry production

- broilers;Land application of manure

2805010100 Poultry production

- turkeys;Confinement

2805010200 Poultry production

- turkeys;Manure handling and storage

2805010300 Poultry production

- turkeys;Land application of manure

2805018000 Dairy cattle composite;Not Elsewhere Classified

2805019100 Dairy cattle

- flush dairy;Confinement

2805019200 Dairy cattle

- flush dairy;Manure handling and storage

2805019300 Dairy cattle

- flush dairy;Land application of manure

2805020001 Cattle and Calves Waste Emissions;Milk Cows

2805020002 Cattle and Calves Waste Emissions;Beef Cows

2805020003 Cattle and Calves Waste Emissions;Heifers and Heifer Calves

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

2805021100 Dairy cattle

- scrape dairy;Confinement

2805021200 Dairy cattle

- scrape dairy;Manure handling and storage

2805021300 Dairy cattle

- scrape dairy;Land application of manure

2805022100 Dairy cattle

- deep pit dairy;Confinement

2805022200 Dairy cattle

- deep pit dairy;Manure handling and storage

2805022300 Dairy cattle

- deep pit dairy;Land application of manure

2805023100 Dairy cattle

- drylot/pasture dairy;Confinement

2805023200 Dairy cattle

- drylot/pasture dairy;Manure handling and storage

2805023300 Dairy cattle

- drylot/pasture dairy;Land application of manure

2805025000 Swine production composite;Not Elsewhere Classified (see also 28

- 05

- 039,

- 047,

- 053)

2805030000 Poultry Waste Emissions;Not Elsewhere Classified (see also 28

- 05

- 007,

- 008,

- 009)

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

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

2805030003 Poultry Waste Emissions;Layers

2805030004 Poultry Waste Emissions;Broilers

2805030007 Poultry Waste Emissions;Ducks

2805030008 Poultry Waste Emissions;Geese

2805030009 Poultry Waste Emissions;Turkeys

2805035000 Horses and Ponies Waste Emissions;Not Elsewhere Classified22

SCC SCC Description*

2805039100 Swine production

- operations with lagoons (unspecified animal age);Confinement

2805039200 Swine production

- operations with lagoons (unspecified animal age);Manure handlin g and storage

2805039300 Swine production

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

2805040000 Sheep and Lambs Waste Emissions;Total

2805045000 Goats Waste Emissions;Not Elsewhere Classified

2805045002 Goats Waste Emissions;Angora Goats

2805045003 Goats Waste Emissions;Milk Goats

2805047100 Swine production

- deep

- pit house operations (unspecified animal age);Confinement

2805047300 Swine production

- deep

- pit house operations (unspecified animal age);Land application of manure

2805053100 Swine production

- outdoor operations (unspecified animal age);Confinement * All SCC Descriptions begin ―Miscellaneous Area Sources;Agriculture Production

– Livestock‖

The ―ag‖ sector includes all of the NH 3 emissions from fertilizer from the NEI. However, the ―ag‖ sector does not include all of the livestock ammonia emissions, as there are also significant

NH 3 emissions from livestock in the point source inventory that we retained from the 2002 NEI

. Note t hat in these cases, emissions were not also in the nonpoint inventory for counties for which they were in the point source inventory; therefore no double counting occurred. Most of the point source livestock NH 3 emissions were reported by the states of K ansas and Minnesota. For these two states, farms with animal operations were provided as point sources using the following SCCs 5 :

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

General

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

Manure Handling: Dry

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

Classified

There are also livestock NH 3 emissions in the point source inventory with SCCs of 3999999 9 ( Industrial Processes; Miscellaneous Manufacturing Industries; Miscellaneous Industrial Processes; Other Not Classified ) and 30288801 ( Industrial Processes; Food and Agriculture; Fugitive Emissions; Specify in Comments Field ). We identified these source s as livestock NH 3 point sources based on their facility name. The reason why we needed to identify livestock NH 3 in the ptnonipm sector was to properly implement the emission projection techniques for livestock sources, which cover all livestock sources, not only those in the ag sector, but also those in the ptnonipm sector.

5 These point source emissions are also identified by the segment ID, which is one of the following: ―SWINE‖, ―CATTLE‖, ―DAIRY‖

, or ―PLTRY‖.23

Table 2

- 9

. Fertilizer SCCs extracted from the 2002 NEI for inclusion in the ―ag‖ sector

2002 SCC 2002 SCC Description*

2801700001 Anhydrous Ammonia

2801700002 Aqueous Ammonia

2801700003 Nitrogen Solutions

2801700004 Urea

2801700005 Ammonium Nitrate

2801700006 Ammonium Sulfate

2801700007 Ammonium Thiosulfate

2801700010 N

- P

- K (multi

- grade nutrient fertilizers)

2801700011 Calcium Ammonium Nitrate

2801700012 Potassium Nitrate

2801700013 Diammonium Phosphate

2801700014 Monoammonium Phosphate

2801700015 Liquid Ammonium Polyphosphate

2801700099 Miscellaneous Fertilizers

* All descriptions include ―Miscellaneous Area Sources; Agriculture

Production

– Crops; Fertilizer Application ‖ as the beginning of the description.



### 2.2.3 Other nonpoint sources (nonpt)

Nonpoint sources that were not subdivided into the afdust, ag, or avefire sectors were assigned to the ―nonpt‖ sector.

The 2002 platform documentation describes the creation of the 2002 nonpt sector in great detail, but the rest of this section will simply document what has changed for the 2005v4 .1 platform.
Below is a list of changes made from the 2002 platform both for the v4 platform and for the v4.1 platform. Details on the changes to 2002 for the version 4 platform are in the v4 documentation.

Updates to the nonpt sector from 2002 p latform made for creation of the nonpt sector of

the 2005v4 platform

The 2005 platf

orm replaces 2002v3 NEI non

- California Western Regional Air Partnership (WRAP) oil and gas emissions (SCCs beginning with ―23100‖) with WRAP year 2005 Phase II oil and gas emissions. Residential wood combustion (RWC) emissions were replaced with data for O regon and New York. This update is consistent with the 2005 NEIv2 NEI. RWC VOC emissions were recalculated for all states except California to reflect an updated emissions factor for VOC from RWC sources. This update is consistent with the

2005 NEIv2 NEI

. We utilized benzene, formaldehyde, acetaldehyde and methanol (BAFM) emissions from
sources that met the HAP

- CAP integration criteria discussed in Section 3.1.2.1 (i.e., the ―integrate‖ sources). We removed BAFM from sources that did not meet the integr ation criteria (i.e., the ―no

- integrate‖ sources) so that BAFM would not be double counted with the BAFM generated via speciation of VOC.24

Updates from 2005v4 p latform used in creating the 2005v4 .1 p latform

We changed the integration status for pesticide emissions from using the ―integrate‖ case to using the ―no

- integrate‖ case. The main reason is that there were significant benzene emissions from this category in the NEI that was considered incorrect. The NEI benzene came from solvent utilization data ( Fredonia) for "other markets" for the year 1998. Since benzene no longer allowed in pesticides, we chose to eliminate the use of these HAP data and use a VOC speciation profile that did not include benzene emissions to be more consistent with the changed r egulations. We added oil and gas emissions for Texas and replaced oil and gas emissions with updated 2005 data from Oklahoma.

TCEQ Oil and Gas Emissions

The Texas Commission on Environmental Quality (TCEQ) provided 2005 oil and gas emissions
which we a dded to the nonpt sector. The emissions were for a single SCC: 2310000220 Industrial Processes; Oil and Gas Exploration and Produc tion; All Processes; Drill Rigs. The TCEQ indicated that these should replace emissions in the nonroad inventory from the

NONROAD model ( drill rigs: SCC=2270 0 10010)

. Because the nonroad emissions are significantly less than the updated nonpt emissions, w e did not remove the nonroad emissions. Both the TCEQ and related nonroad emissions from the 2005 NEI are summarized in Table 2

- 10

.
Table 2

- 10

. Additional TCEQ oil and gas emissions added to the 2005v2 NEI

Pollutant TCEQ Emissions 2005,

added to nonpt (tons /yr ) NEI 2005 Emissions (nonroad

inventory)
, not subtracted (tons /yr )

CO 15,878 1,396

NH 3 3

NO X 42,854 4,704

PM 10 3,036 275

PM 2. 5 2,945 267

SO 2 5,977 573

VOC 4,337 340

Oklahoma Oil and Gas Emissions

The state of Oklahoma provided and emissions replacement for their 2005 oil and gas sector
emissions. The se data added e missions for the SCCs shown in Table 2

- 11

.25 Table 2

- 11

. SCCs provided with Oklahoma oil and gas sector emissions

SCC SCC Description

31000103 Crude Oil Production;Wells: Rod Pumps *

31000122 Crude Oil Production;Drilling and Well Completion *

31000203 Natural Gas Production;Compressors *

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

31000222 Natural Gas Production;Drilling and Well Completion *

31000227 Gas Production;Glycol Dehydrator Reboiler Still Stack *

31000228 Natural Gas Production;Glycol Dehydrator Reboiler Burner *

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

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

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

* These SCC d escriptions start with the preface ― Industrial Processes;Oil and Gas Production‖

In addition, this update removed emissions for SCC 2310000000, which is ― Industrial Processes;Oil and Gas Production: SIC 13;All Processes;Total: All Processes .‖

The resultant Oklahoma emissions are shown below in Table 2

- 12

. Note that Oklahoma
instructed that PM 10 emissions were size PM 2.5 , and therefore no coarse PM (PMC) are generated
and PM 10 is the same as PM2.5

Table 2

- 12

. Changes to Oklahoma oil and gas emissions

Pollutant 2005 Oklahoma Oil and gas

emissions 2005, removed from nonpt (tons/yr) 2005 Oklahoma Oil and gas emissions
, added to nonpt (tons/yr)

CO 11,251 32,821

VOC 104,193 155,908

NO X 66,480 39,668

SO 2 0 1, 014

PM 10 = PM 2.5 0 1,918



### 2.3 Fires (avefire)

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

The purpose of the avefire sector is to represent emissions for a typical year‘s fires for use in projection year inventories, since the location and degree of future year fires are not known. This approach keeps the fires information constant between the 2005 base case and future

- year cases to eliminate large and uncertain differences between those cases that would be caused by changing the fires. Using an average of multiple years of data reduces the possibility that a single

- year's high or low fire act ivity would unduly affect future year model

- predicted
concentrations.26

The avefire sector contains w ildfire and prescribed burning emissions . It exclude s agricultural burning and other open burning sources , which are included in the nonpt sector. Gener ally, their

year

- to

- year impacts are not as variable as wildfires and non

- agricultural prescribed/managed
burns.

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

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

- based platform.

We created the average

- fires inventory based on the 2001 (1999 NEI

- based) fire emissions data. The average fire sector is comprised of a 1996

- 2002 average fire inventory for wildfires and prescribed burning. We calculated the average wildfire and prescribed burning inventories using the following formula for all pollutants:

The average acres

- burned was calculated base on 1996 through 2002 data; therefore, the average fire inventory represent aver age fires from 1996 through 2002, with the assumption of 2001 emissions rates and a spatial distribution of emissions to counties based on fires from 2001. This approach is the same as that used for our previous emissions modeling platforms used to model 2001 and 2002 base years, with some differences described here.

The 2005 platform avefire sector differs from the avefire sector in the 2002 platform in the following ways :

a. We recomputed VOC as a function of CO: VOC = CO * 0.229 at the suggestion
of EPA fire inventory expert who reviewed the VOC emissions and found them too high (Tom Pace , personal communication ).

b. We created HAP emissions records by applying emission ratios to 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 for CO and PM 2.5 are unchanged and are provided
for reference.

Table 2

- 13

. Average fire VOC changes from 2002 to 2005 platform

.

SCC S CC Description * 2002 VOC (tons/yr) 2005 VOC

(tons/yr) CO

(tons/yr) PM 2.5

(tons/yr)

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

2810005000 Managed Burning, Slash (Logging

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

2810015000 Prescribed Burning for Forest

Management;Total 84,784 399,880 1,746,208 147,298 * all SCC descriptions begin with ―Miscellaneous Area Sources; Other Combustion‖27

The 2005 HAP emissions records w ere created by multiplying PM 2.5 emissions by the emission

factors in Table 2

- 14 . The HAP factors are the same for all source types. Because we chose not to integrate criteria and HAP VOCs for the avefire sector, the HAPs contained in the avefire inventory were not used to generate air quality modeling inputs for the 2005 platform

.

Table 2

- 14

. HAP emission factors applied to avefire 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 0.0001
Benzo[g,h,i,]Perylene 191242 0.00018

Benzo[k]Fluoranthene 207089 0.00009
Carbonyl sulfide 463581 0.00002
Chrysene 218019 0.00022

Fluoranthene 206440 0.00024
Formaldehyde 50000 0.0936

Hexane 110543 0.00059

Indeno[1,2,3

- c,d]Pyrene 193395 0.00012
Methyl chloride 74873 0.00464
Methylanthracene 26914181 0.0003
Methylbenzopyrene 65357699 0.00011
Methylchrysene 41637905 0.00029

O

- xylene 95476 0.001932554

M

- xylene 108383 0.005392065

P

- xylene 106423 0.00145538
Perylene 198550 0.00003

Phenanthrene 85018 0.00018
Pyrene 129000 0.00034

Toluene 108883 0.020628



### 2.4 Biogenic sources (biog)

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

T he biogenic emissions were computed based on 2005 meteorology data using the BEIS3.14
model within SMOKE. The 2002 platform used the BEIS3.13 model; otherwise, all underlying land use data and parameters are unchanged for the 2005 platform.

The BEIS3.14 model creates gridded, hourly, model

- species emissions from vegetation an d soils. It estimates CO, VOC, and NO X emissions for the U.S., Mexico, and Canada. The BEIS3.14
model is described further in: http://www.cmascenter.org/conference/ 2008/slides/pouliot_tale_two_cmas08.ppt

The inputs to BEIS include:

T emperature data at 2 meters which were obtained from the CMAQ meteorological input files,

L and

- use data from the Biogenic Emissions Landuse Database, version 3 (BELD3). BELD3 data provi des data on the 230 vegetation classes at 1

- km resolution over most of
North America , which is the same land

- use data were used for the 2002 platform.



### 2.5 2005 Mobile sources (on_noadj, on_moves_runpm, on_moves_startpm, nonroad, alm_no_c3, seca_c3)

F or the 2 005 platform, as indicated in Table 2

- 2 , we separated the 2005 onroad emissions into
three sectors: (1) ― on_moves_startpm‖ ; (2) ―on_moves_runpm‖ ; and (3) ―on_noadj‖

. The aircraft, locomotive, and commercial marine emissions are divided into two nonroad sectors : ―alm_no_c3‖ and ―seca_c3‖ , and as previously mentioned, the aircraft emissions are in the non

EGU (ptnonipm) point inventory.

The major change s between v4.1 and v4 versions of the 2005

- based platform are that (1) we used a final version of MOVES, MOVES2010, rather than a draft version of MOVES ; (2) we used the MOVES emissions for all vehicle types and modes (as opposed to non

- motorcycle gasoline exhaust veh icles only) ; (3) MOVES2010 emissions cover all criteria pollutants and criteria pollutant precursors (as opposed to only exhaust mode PM 2.5 , VOC, NO X and CO) ; ( 4 )
we used NH 3 from MOVES for California (as opposed to NH 3 from NMIM) since California

suppli ed emissions in the 2005v2 NEI do not include NH 3

. It should also be noted that the
exhaust PM 2.5 from diesel vehicles, which had previously come from NMIM but in v4.1 come from MOVES, are not impacted by cold temperatures. In addition, PM brake wear and tire wear mode emissions are now provided in MOVES in v4.1; these emissions for both gasoline and diesel vehicles are also not impacted by cold temperatures.

The onroad emissions were primarily based on the 12/21/2009 version of the Motor Vehicle
Emissio ns Simulator (MOVES2010) ( http://www.epa.gov/otaq/models/moves/ ). MOVES was29

run with a s tate/ m onth aggregation using county

- average fuels for each state, state/month

average temperatures, and national de fault vehicle age distributions. 2005 VMT, consistent with
the 2005v2 NEI , were used.

Table 2

- 15 lists the pollutants in the onroad sector based on MOVES2010 versus NMIM. A full
list of the NMIM HAPs (most of which are not used in the v4.1 p latform) is provided in Appendix C.

Table 2

- 15

. Pollutants covered by MOVES2010 as used in the 2005v4 .1 p latform 1

Used in the 2005v4 .1 p latform from

MOVES2010 Available from MOVES2010, but not
used in the 2005v4 .1

p latform Used in the 2005v4 .1

p latform from NMIM

PM 2.5 ; exhaust, partially speciated 2 Naphthalene Elemental mercury

PM 2.5 , brake and tirewear, unspeciated 1,3 butadiene Divalent gaseous mercury VOC; except refueling Acrolein Particulate Mercury CO, NO X , SO 2 , NH 3 Benzene; except refueling Formaldehyde Acetaldehyde

1 MOVES data were not used for any California onroad emissions other than NH 3 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‖)

. Procedures to produce the species needed are provided in Appendix D. Diesel partially speciated emissions are not impacted by cold temperatures and do not need to be adjusted by gridded temperature as do the gasoline exhaust particulate emissions. Brake wear and tire wear PM 2.5 emissions were not pre

- speciated.

Similar to the v4 platform

, we used the MOVES data to create emissions by state and month (and SCC) and then allocated to counties based on 2005 NMIM

- based county

- level data. The reason
for using the state resolution was due to (a) run time issues that made a county run for the entire nation infeasible in the timeframe required and (b) in complete efforts to create a national database of county

- specific inputs to MOVES. The emissions that did not come from the MOVES model were obtained from the 2005 NMIM runs, which are consistent with the 2005 v2

NEI

.

The 2005v2 NEI does not contain the MOVES data that we use for the 2005 platform. Instead, it
contains onroad and nonroad mobile emissions that we generated using NMIM (EPA, 2005b) for all of the U.S. except for California. 6 The NMIM data was used for the mercury emissions , to
allocate California

- submitted data to road types, to allocate the state

- month

- SCC MOVES data to counties, and for so me of the nonroad mobile sources. NMIM relies on calculations from the MOBILE6 and NONROAD2005 models as described below, and in the NEI documentation. Inputs to NMIM are posted with the 2005 Emission Inventory. The direct link is: ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile_sector/ncd/ncd20080522.zip

.

6 Although OTAQ generated emissions using NMIM for California, these were not used in the 2005 NEI version 2,
but rather were replaced by state

- submitted emissions. Since California did not submit NH 3 , values from MOVES
were used.30

NMIM creates the onroad and nonroad emissions on a month

- specific basis that accounts for temperature, fuel typ es, and other variables that vary by month. Inventory documentation for the

2005v2 NEI onroad and nonroad sectors is also posted with other 2005 NEI documentation; the
direct link is: ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/2005_mobile_nei_version_2_report.pdf

The residual fuel commercial marine vessel (CMV), also referred to as Category 3 ( C3 ) from the 2002 platform have been replaced with a new s et of approximately 4

- km resolution point source format emissions; these were modeled separately as point sources in the ―seca_c3‖ sector for the 2005 platform. They were updated for v4.1 by using revised 2005 emissions from the category 3
commercial mari ne sector to reflect the final projectio ns from 2002 developed for the category 3 commercial marine Emissions Control Area (ECA) proposal to the International Maritime Organization (EPA

- 420

- F

- 10

- 041, August 2010). Unlike for the v4 platform, we projected Canada as part of the ECA, using region

- specific growth rates; thus the v4.1 seca_c3 inventories contain Canadian province codes for near shore emissions

.

The nonroad sector, based on NMIM did not change for the v4.1 platform other than for California, for which missing PM 2.5 emissions for 7 counties was discovered. We corrected
the se PM 2.5 emissions by using an earlier version of the 2005 submittal which California had provided values for the 7 counties

.

The mobile sectors are compiled at a county and SCC resolution, with the exception of the seca_c3 sector that uses point source s to map the pre

- gridded data to the modeling domain. Similar to v4, in v4.1, t ribal data from the alm_no_c3 s ector have been dropped because we do not have spatial surrogate data, and the emissions are small; these data were removed from the SMOKE input inventories for 2005.

Most mobile sectors use the HAP portion on the inventory to provide benze ne, acetaldehyd e, formaldehyde and/ or methanol to the modeling inputs through HAP VOC ―integration‖ , as described in Section 3.1.2.1

. A few categories of nonroad sources (CNG an d LPG

- fueled equipment) do not have the BAFM pollutants in the inventory and therefore utilize the ―no

integrate‖, ―no

- hap

- use‖ case

, which means VOC from these sources is speciated to provide

BAFM.



### 2.5.1 Onroad mobile MOVES cold

- start exhaust sources requiring temperature adjustments (on_moves_startpm)

This sector contains MOVES 2010 emissions for PM and naphthalene 7 for non

- California onroad gasoline cold

- start exhaust. These emissions (and the on_moves_runpm sector discussed in the next section) are processed separately from the remainder of the onroad mobile emissions because they are subject to hourly temperature adjustments, and these temperature adjustments
are different for cold

- start and running exhaust modes.

7 Naphthalene is not used in the 2005v4 CAP

- BAFM platform, but it is contained in the MOVES emissions.31

Temperature adjustments were applied to account for the strong sensitivity of PM and naphthalene exhaust emissions to temperatures below 72oF. Because it was not feasible to run MOVES directly for all of the gridded, hourly temperatures needed for modeling, we created emissions of PM and naphthalene exhaust at 72oF and applied temperature adjustments after the emissions were spatially and temporally all ocated. The PM 2.5 (and naphthalene) adjustment factors were different for starting and running exhaust because these two processes respond differently to temperature as shown in Figure 2

- 1 which shows how these emissions increase with colder temperatures. The temperature adjustment factor in this figure is defined in terms of primary elemental carbon (PEC) as follows:

PEC = Adjustment Factor x PEC_72

Where:

PEC = PEC at Temperature s below 72oF PEC_72 = PEC at 72oF or higher

As seen in the figure, start exhaust emissions increase more than running exhaust emissions as temperatures decrease from 72oF.

Figure 2

- 1 also shows that the actual adjustments a re different for start exhaust and running exhaust emissions. The method for applying these adjustments was the same for both start and running exhaust sectors: T hey were applie d to SMOKE gridded, hourly intermediate files , based upon the gridded hourly temperature data ( these same data are also input to t he air quality model). One result of this approach is that inventory summaries based on the raw SMOKE inputs for the on_moves_startpm and on_moves_runpm sectors will not be valid because they will not include the temperature adjustments. As a result, the post

- processing for temperature adjustments included computing the emissions totals at state, county, and month resol ution to use
for summaries.32 Figure 2

- 1

. MOVES exhaust temperature adjustment functions.

T he MOVES output data required pre

- processing to develop county

- level monthly ORL files for input to SMOKE. As sta ted earlier, the resolution of the MOVES data was state

- SCC totals, and
the state level d ata were allocated to county level prior to input into SMOKE. An additional pre

processing step was for the exhaust PM 2.5 , for which emissions from MOVES were partially speciated. T o retain the speciated element al carbon and sulfate emissions from MOVES, the speciation step that is usually done in SMOKE was performed prior to SMOKE

, and it was modified to allow the temperature adjustm ents to be applied to only the species affected by
temperature as described in the list below

. Finally, because the start exhaust emissions were broken out separately from running exhaust emissions, they were assigned to new SCCs (urban and rural parking areas) that allow ed for the appropriate spatial and temporal profiles to be applied in SMOKE.

A list of the procedures performed to prepare the MOVES data for input into SMOKE is provided here

.

i. We allocated s tate

- level emissions to count ies using state

- county emission ratios by SCC, pollutant

, month, and emissions mode (e.g., evaporative, exhaust , brake wear,
and tire wear ) for each month. The ratios were computed using NMIM 2005 data (same data included in the 2005 v2 NEI ).

ii. We assigned t hese start exhau st emissions to urban and rural SCCs based on the
county

- level ratio of emissions from urban versus rural local road s from the NMIM onroad gasoline exhaust mode data

. For example, we split light duty gasoline vehicle (LDGV) start emissions in the state

- to tal MOVES data ( assigned SCC 2201001000) into urban (2201001370) and rural (2201001350) based on the ratio of LDGV urban (2201001330) and rural (2201001210) local roads.33

iii. We converted MOVES

- based PM 2.5 species at 72 oF to SMOKE

- ready PM species.
The SMOKE

- ready species are listed below and the speciation technique used to
obtain the SMOKE

- ready species is further discussed in Appendix D

.

NAPHTH_72: unchanged from MOVES

- based file, subject to temperature adjustment be low 72 oF

. PEC_72: unchanged from MOVES

- based PM25EC, subject to temperature adjustment below 72 oF

. POC_72: modified MOVES

- based PM25OC to remove metals, PNO3 (computed
from MOVES

- based PM25EC), NH 4 (computed from MOVES

- based PM25SO4 and PNO3), and MOVES

- based PM25SO4. Subject to temperature 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

- based PM25EC) and

NH 4 (computed from PNO3 and PSO4), not subject to temperature adjustment.
PMFINE_72: Computed from OTHER and fraction of POC_72. Subject to temperature adjustment below 72 oF

. PMC_72: Computed as fraction of sum of PM FINE_72, PEC_72, POC_72, PSO4, and PNO3

– described in Appendix D . Subject to temperature adjustment
below 72 oF

.

The result of these preprocessing steps is SMOKE

- ready PM emissions that do not exactly match what MOVES provides. The emissions are conserv ed during allocation from the state to county and from the generic total ―start‖ SCCs to the two new parking SCCs that end in ―350‖ and
―370‖. PEC and PSO 4 components of PM 2.5 emissions are also conserved as they are simply renamed from the MOVES specie s ―PM25EC‖ and ―PM25SO4‖ . However, as 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 Appendix D

.



### 2.5.2 Onroad mobile MOVES running exhaust sources requiring temperature adjustments (on_moves_runpm)

This sector is identical to the on_moves_startp m sector discussed in S ection 2.5.1, but contains running exhaust emissions instead of cold

- start exhaust emissions. The same pollutants are in this sector, and allocation from the MOVES state

- level to county

- level inventory is a simple match by SCC and month to NMIM state

- county ratios. The only reason this sector is separated from on_moves_startpm is because the temperature adjustments are less extreme for these running emissions at colder temperatures when compared to the curve for cold

- start emissions ( Figure 2

- 1 ).34



### 2.5.3 Onroad no

- adjustments mobile sources (on_noadj)

Th is sector consists of the bulk of the onroad mobile emissions , which are not covered by the on_moves_startpm and on_moves_runpm sectors . These emissions did not receive any temperature adjustments in our processing . There are four sources of data that ar e pre

- processed to create three sets of monthly inventories for this sector.

1. MOVES

- based onroad gasoline and diesel : These are the monthly (does not include gasoline exhaust mode PM and naphthalene ) MOVES

- based emissions from t hree
MOVES inventories:

a. Gaso line Exhaust: VOC, NO X , CO, SO 2 , NH 3

, 1,3

- butadiene (106990), acetaldehyde (75070), acrolein (107028), benzene (71432), formaldehyde (50000) , and brake and tire wear PM 2.5 ;

b. Diesel Exhaust: Partially

- speciated PM 2.5 (that were fully speciated prior to input into SMOKE (via Appendix D), VOC, NO X , CO, SO 2 , NH 3

, 1,3

- butadiene (106990), acetaldehyde (75070), acrolein (107028), benzene (71432), formaldehyde (50000)

, and brake and tire wear PM 2.5 . Because diesel exhaust

PM does not require the same intermediate temperature adjustments as gasoline exhaust PM, diesel exhaust PM can therefore be processed with the remaining
onroad mobile emissions

.

c. Evaporative: Non

- refueling VOC, benzene, and naphthalene (91203 )

.

For the pol lutants listed, t hese non

- California MOVES emissions encompass the same sources as the on_moves_startpm and on_moves_runpm sectors : light duty gasoline vehicles, light duty gasoline trucks ( 1 & 2) , and heavy duty gasoline vehicles, but they do not require the same intermediate temperature adjustments and can therefore be processed with the remaining onroad mobile emissions. These emissions contain both running and parking sources and are pre

- processed from state

- level to county

- level much like the on_moves _startpm and on_moves_runpm sectors already discussed. The preprocessing for the non

- PM emissions did not require species calculations because the
raw MOVES emissions translated directly to SMOKE inventory species.

2. California onroad inventory: California 2005v2 NEI complete CAP/HAP onroad inventory. California monthly onroad emissions are year 2005 and are based on September 2007 California Air Resources Board (CARB) data from Chris Nguyen. NH 3 emissions are from MOVES2010 runs for California. We r etai ned only those HAP s that are also estimated by NMIM for onroad mobile sources; all other HAP s provided by
California were dropped . The California onroad inventory does not use the SCCs for Heavy Duty Diesel Vehicles (HDDV) class 6 & 7 (2230073XXX) emissio ns. California does not specify road types, so we used NMIM

- based California ratios to break out
vehicle emissions to the match the more detailed NMIM level.

3. Remaining NMIM

- based onroad inventory: The remainder of the non

- California onroad inventory that was not replaced by MOVES. This includes monthly emissions the three species of mercury (divalent gas, elemental and particulate) as well as a number of other HAPs not used by the platform

. The NMIM county database is NCD200 8 0 52 2 ; this is an update of N CD20070912 in which state/ local and tribal inputs replace EPA default inputs35

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



### 2.5.4 Nonroad mobile sources

– NMIM

- based nonroad (nonroad)

This sector i ncludes mont hly exhaust, evaporative and refueling emissions from nonroad engines (not including commercial marine, aircraft, and locomotives) derived from NMIM for all states except California

, which were corrected due to an inadvertent o mission of PM 2.5 from 7 counties. Thus, except for California, e missions from this sector did not change between the v4 and v4.1 platform versions, and we repeat the documentation here for completeness.

The NMIM relied on the version of the NONROAD2005 model ( NR05c

- Bond Base) used for the marine spark ignited ( SI ) and small SI engine proposed rule, published May 18, 2007 (EPA, 2007c). For 2005, the NONROAD2005 model (NR05c

- BondBase) is equivalent to NONROAD2008a, since it incorporated Bond rule revisions to some of the b ase case inputs and
the Bond rule controls did not take effect until future years

. As with the onroad e missions, NMIM provides nonroad emissions for VOC by three emission modes: exhaust, evaporative and refueling. Unlike the onroad sector, refueling emissions nonroad sources are not dropped from processing for this sector

.

Similar to the on_noadj pre

- proc essing for evaporative emissions , we also reassigned NMIM evaporative and refueling xylene to the various isomers of xylene . We use the same percentages for refueling as for evaporative emissions as follows: we converted compound XYL or CAS=EVP__1330207, RFL__1330207) into MXYL (CAS=EVP__108383, RFL__108383) and OXYL (CAS=EVP__95476, RFL__95476) using a 68% and32% ratio to both evaporative and refueling XYL, respectively. We also split NMIM exhaust xylene (CAS=EXH__1330207) into MXYL (CAS=EXH__108383) an d OXYL (CAS=EXH__95476) using a 74% and 26% ratio to XYL, respectively.

EPA/OTAQ ran NMIM to create county

- SCC emissions for the NEI 2005v2 nonroad mobile

CAP/HAP inventory

, and similar to on_noadj, we removed California NMIM emissions that
were submitted separately by California

. Emissions were converted from monthly totals to monthly average

- day based on the number of days in each month. Similar to onroad NMIM emissions, EPA default inputs were replaced by state inputs where provided. The NMIM
invento ry documentation describes this and all other details of the NMIM nonroad emissions development: ftp://ftp.epa.gov/EmisInventory/2005_nei/mobile/2005_mobile_ nei_version_2_report.pdf

California nonroad California monthly nonroad emissions are year 2005 and are based on September 2007 California Air Resources Board (CARB) data from Chris Nguyen

, other than for the PM 2.5 missing from 7 counties, which used the M arch 2007 version

. In addition, NH 3 emissions are
from NMIM runs for California because these were not included in the California NEI submittal

. HAP emissions were estimated by applying HAP

- to

- CAP ratios computed from Calif ornia data
in the NEI 2005 v2 submittal . We r etained only those HAP s that are also estimated by NMIM for nonroad mobile sources; all other HAP s were dropped

.36

The CARB

- based nonroad data did not have mode

- specific data for VOC (exhaust, evaporative, and refueling). To address this inconsistency with other states, w e split the annual total
California data into monthly, mode

- specific nonroad emissions for California using the NMIM results. Details on this process are documented separately (Strum, 2007). Nonroad refueling
emissions f

or California were computed as Gasoline Transport (SCC=2505000120) emissions multiplied by a factor of 0.46 (to avoid double counting with portable fuel container ( PFC ) emissions in the nonpt sector) and were allocated to the gasoline equipment types based on ratios of evaporative

- mode VOC. The factor o f 0.46 was computed by dividing the NMIM

- derived
California refueling for 2005 by the sum of portable fuel container emissions and NMIM

- derived refueling for 2005.



### 2.5.5 Nonroad mobile sources: locomotive and no n
- C3 commercial marine (alm_no_c3)

The alm_no_c3 sector contains CAP and HAP emissions from locomotive and commercial marine sources, except for category 3/residual

- fuel (C3) commercial marine vessels and railway
maintenance . In modeling platforms prior t o the 2005v4 platform , this sector also contained
aircraft emissions . P oint

- source airports were included in the non

- EGU point sector (ptnonipm) through the 2005v2 NEI point source inventory. The C3 commercial marine vessel emissions are in the seca_c3 s ector. We note that the ―a‖ in th e ―alm_no_c3‖ sector name is now misleading because aircraft are no longer in this sector. This sector is unchanged from the v4 platform; we repeat the documentation for completeness.

The remaining emissions in the alm_n o_c3 sector are year 2002 emissions unchanged from the 2002 platform. The SCCs in the alm_no_c3 sector are listed in Table 2

- 16

.37

Table 2

- 16

. SCCs in the 2005 alm_no_c3 inventory compared to the 2002 platform alm sector

SCC Action SCC Description

2275000000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: All Aircraft Types and Operations: Total

2275001000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: Military Aircraft: Total

2275020000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: Commercial Aircraft: Total: All Types

2275050000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: General Aviation:
Total

2275060000 Emissions removed and replaced by

aircraft in ptnonipm sector for 2005 platform Mobile Sources; Aircraft: Air Taxi: Total

2280002100 Retained from 2002 platform Mobile Sources;Marine Vessels, Commercial;Diesel;Port emissions

2280002200 Retained from 2002 platform Mobile Sources;Marine Vessels, Commercial;Diesel;Underway emissions

2280003100 Emissions removed and replaced by

seca_c3 inventories for 2005 platform Mobile Sources;Marine Vessels, Commercial;Residual;Port emissions

2280003200 Emissions removed and replaced by

seca_c3 inventories for 2005 platform Mobile Sources;Marine Vessels, Commercial;Residual;Underway emissions

2280004000 Retained from 2002 platform Mobile Sources;Marine Vessels, Commercial;Gasoline;Total, All Vessel Types

2285002006 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations

2285002007 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations

2285002008 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak)

2285002009 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Line
Haul Locomotives: Commuter Lines

2285002010 Retained from 2002 platform Mobile Sources;Railroad Equipment;Diesel;Yard
Locomotives

The documentation of the 2002 NEI for the category 1 and 2 (C1/C2) commericial marine and
locomotive emissions is available at: http://www.epa.gov/ttn/chief/net/2002inventory.html#documentation

For modeling purposes, the following additi onal changes were made to the NEI data for the 2005 platform:

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

.38

R emoved railway maintenance emissions ( SCCs 2285002015, 2285004015, and
2285006015 ) because these are included i n the nonroad NMIM monthly inventories. This change was made for the 2002 platform and is retained here in th e 2005 platform.

For the purpose of CAP

- HAP VOC integration as discussed in Section 3.1.2.1 , we removed benzene, formaldehyde, and acetaldehyde for all sources that we did not integrate these HAPs with VOC. As discussed in Section 3.1.2.1 , sources are considered

no

- integrate when the source of data between VOC and VOC HAPs is inconsistent or VOC analysis of VOC and VOC HAPs indicates the source is not integrated. Although

our CAP

- HAP i ntegration approach also required the removal of methanol for no

integrate sources, the only sources in this sector that included methanol were in California, where we used the integrate approach for all sources and therefore did not
need to remove it.

Th e 2002 platform documentation goes into greater detail on the locomotives and C1/C2 CMV
emissions in this sector.



### 2.5.6 Nonroad mobile sources: C3 commercial marine (seca_c3)

The raw seca_c3 sector emissions data were developed in an ASCII raster format used since the
Emissions Control Area

- International Marine Organization ( ECA

- IMO ) project began in 2005

, then known as the Sulfur Emissions Control Area (SECA)

. These emissions consist of large marine diesel engines (at or above 30 liters/cylinder) that until very recently

, were allowed to meet relatively modest emission requirements, often burning residual fuel. The emissions in this sector are comprised of primarily foreign

- flagged ocean

- going vessels, referred to as Category 3 (C3) ships. The seca_c3 (ECA ) inventory includes these ships in several intra

- port modes (cruising, hoteling, reduced speed zone, maneuvering, and idling) and underway mode and
includes near

- port auxiliary engines. An overview of the ECA

- IMO project and future year goals for reducti on of NO X , SO 2 , and PM C3 emissions can be found at:

http://www.epa.gov/oms/regs/nonroad/marine/ci/420f09015.htm

The resulting coordinated strategy, including emission standards un der the Clean Air Act for new marine diesel engines with per

- cylinder displacement at or above 30 liters , and the establishment
of Emission Control Areas is at: http://www.epa.gov/oms/oceanvessels.htm

The base year ECA inventory is 2002 and consists of these CAPs: PM 10 , CO, CO 2 , NH 3 , NO X , SO X ( assumed to be SO 2 ), and Hydrocarbons ( assumed to be VOC). EPA developed regional growth (activity

- based) factors that we applied to create the v4 .1 platform 2005 inventory from
the 2002 data

.

These region

- specific and pollutant

- specific growth factors were updated for the v4.1 platform as compared to the v4 platform to be consistent with the final projections from 2002, developed for the C3 ECA proposal to the International Maritime Organization (EPA

- 420

- F

- 10

- 041, August 2010).

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

- 17

.39

Table 2

- 17

. Adjustment f actors to update the 2005 seca_c3 sector e missions for the v 4.1

p latform.

2005 Adjustments Relative to 2002
Region NO X PM 10 PM 2.5 VOC ( HC ) CO SO2
Alaska East (AE) 1.08561 1.10440 1.10350 1.10453 1.10411 1.10438
Alaska West (AW) 1.04671 1.06382 1.06404 1.06389 1.06391 1.06386
East Coast (EC) 1.10524 1.15242 1.15383 1.15256 1.15238 1.15244
Gulf Coast (GC) 1.04056 1.08521 1.08269 1.08467 1.08536 1.08530
Hawaii East (HE) 1.09054 1.13429 1.13258 1.13352 1.13429 1.13422
Hawaii West (HW) 1.09108 1.13402 1.13289 1.13443 1.13399 1.13428
North Pacific (NP) 1.07254 1.11354 1.09817 1.11358 1.11318 1.11339
South Pacific (SP) 1.12539 1.17416 1.17257 1.17055 1.17012 1.17565
Great Lakes (GL) 1.04397 1.06264 1.06241 1.06341 1.06280 1.06251

Outside ECA 1.08654 1.13186 1.13186 1.13186 1.13186 1.13186

In addition to the updated values, near

- shore Canadian emissions are now assigned to regions whereas previously Canadian sources used the ― Outside ECA ‖ factors. Canada uses North Pacific, Great Lakes and East Coast depending on where the emissions are . For example, near

shore emissions around Vancouver British Columbia are projected from 2002 using North Pacific (NP) factors rather than ―Outside ECA‖ factors

.

The raw ECA inventory started as a set of ASCII raster datasets at approximately 4

- km resolution that we converted to SMOKE point

- source ORL i nput format as described in http:// www.epa.gov/ttn/chief/conference/ei17/session6/mason.pdf

.

In summary, t his paper describes how the ASCII raster dataset was converted to latitude

longitude, mapped to state / county FIPS codes that extend up to 200 n autical m iles (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 Exclu sive Economic Zone (EEZ), a distance
that would be used to define the outer limits of ECA

- IMO controls for these vessels.

The 2005 ECA

- based C3 inventory also does not delineate between ports and underway (or other C3 modes such as hoteling, maneuvering, reduced

- speed zone, and idling) emissions; therefore, we assigned these emissions to the broad (―total‖) SCC for C3 CMV (2280003000). This has no effect on temporal allocation or speciation compared to existing profiles for underway and port
C3 emissions (2280003100 and 2280003200). The C3 CMV emissions in the 2002 and 2005 platforms are shown in Table 2

- 18.40

Table 2

- 18

. Contiguous U.S. C3 CMV emissions in 2002 and 2005 platforms

Pollutant 2002 platform

(ton s /yr ) 2005v4

platform (tons /yr ) 2005v4 .1

platform (tons /yr )

CO 28,195 53,746 54,049

NH 3 131 0 0

NO X 244,988 642,089 647,884

PM 10 13,687 53,581 53,918

PM 2.5 12,620 49,294 49,541

SO 2 150,532 417,307 420,110

VOC 7,377 22,367 44,990

For the v 4.1 platform, we chose only to include some HAPs in the seca_c3 sector: benzene, formaldehyde

, and acetaldehyde

. We projected the se HAPs using the following VOC factors :

Benzene = VOC * 9.795E

- 06 Acetaldehyde = VOC * 2.286E

- 04 Formaldehyde = VOC * 1.5672E

- 03

Because we computed HAPs directly from the CAP inventory and the calculations are therefore consistent, the entire seca_c3 sector utilizes CAP

- HAP VOC integration to use the VOC HAP species directly, rather than VOC speciation profiles.

Mercur y was not included due to uncertainties in the emissions.

We converted the emissions to SMOKE point source ORL format

, allowing for the emissions to be allocated to modeling layers above the surface layer. We also corrected FIP S 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, t he CAP emissions are in one
ORL file and the HAP emissions are split into 6 separate ORL files. The SMOKE

- ready data
have also been cropped from the original ECA

- IMO data to cover only the 36

- km air quality
model domain , which is the largest domain used f or this effort

.



### 2.6 Emissions from Canada, Mexico and Offshore Drilling Platforms (othpt, othar, othon , othpt_hg, and othar_hg )

These sectors are unchanged from the 2005v4 platform; the documentation is included here for completeness.

The emissions from Cana da, Mexico, and Offshore Drilling platform s are included as part of five sectors: othpt, othpt_hg, othar, other_hg, and othon.

The ―oth‖ refers to the fact that these emissions are ―other‖ than those in the 2005 NEI, and the

third and fourth characters p rovide the SMOKE source types: ―pt‖ for point, ―ar‖ for ―area and41

nonroad mobile ‖, and ―on‖ for onroad mobile. The othpt_hg and oth a r_hg sectors contain year 2000 Canadian speciated mercury emissions for point and area inventories. They were used with

t he EPA‘s 2002v3 multi

- pollutant platform posted at http://www.epa.gov/ttn/chief/emch/index.html#2002 (see ―CAP and HAP 2002

- Based Platform,
Version 3 ‖). All other ―oth‖ emissions are CAP

- only inventories. Mexico‘s emissions are unchanged from the 2002 p latform with one exception

– one stack diameter was updated ( recomputed from stack velocity and flowrate ) in the Mexico border states point inventory.

For Canada we updated the emissions from the 2002 platform, migrating the non

- Hg data from year 2000 inve ntories to year 2006 inventories for the 2005 platform. We migrated to these 2006 Canadian emissions despite not receiving future year emissions, as we were advised by Canada that the improvement in the 2006 inventory over the 2000 inventory w as more sign ificant than
the undesirable effect of retaining these 2006 emissions for all future year modeling. We applied
several modifications to the 2006 Canadian inventories:

i. We did not include wildfires, or prescribed burning because Canada does not include
the se inventor y data in their modeling.

ii. We did not include in

- flight aircraft emissions because we do not include these for the U.S. and we do not have an appropriate approach to include in our modeling.

iii. We applied a 75% reduction (―transport fraction‖) to PM for the road dust, agricultural,
and construction emissions in the Can a dian ―afdust‖ inventory. This approach is more simplistic than the county

- specific approach used for the U.S., but a comparable approach
was not available for Canada.

iv. We did not inclu de speciated VOC emissions from the ADOM chemical mechanism.

v. Residual fuel CMV (C3) SCCs (22800030X0) were removed because these emissions are included in the seca_c3 sector , w hich covers not only emissions close to Canada but also
emissions far at sea. C anada was involved in the inventory development of the seca_c3
sector emissions

. vi. Wind erosion (SCC=2730100000) and cigarette smoke (SCC=2810060000) emissions were removed from the nonpoint (nonpt) inventory; these emissions are also absent from
our U.S. in ventory.

vii. Quebec PM 2.5 emissions (2,000 tons/yr) were removed for one SCC (2305070000) for Industrial Processes, Mineral Processes, Gypsum, Plaster Products due to corrupt fields after conversion to SMOKE input format. This error should be corrected in a f uture inventory.

viii. Excessively high CO emissions were removed from Babine Forest Products Ltd (British
Columbia SMOKE plantid=‘5188‘) in the point inventory. This change was made at our discretion because the value of the emissions was impossibly large.

ix. The county part of the state/count y FIPS code field in the SMOKE inputs were modified in the point inventory from ―000‖ to ―001‖ to enable matching to existing temporal profiles.

x. Fixed coordinates for facility ―ON105803‖ in the othpt_hg inventory to match tho se in the National Pollutant Release Inventory (NPRI) othpt sector.42

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

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

For Mexico we continued to use emissions for 1999 (Eastern Research Group Inc., 2006) which were developed as part of a partnership between Mexico's Secretariat of the Environment and Natural Resources (Secretaría de Medio Ambiente y Recursos Naturales

- SEMARNAT) and

Nat ional Institute of Ecology (Instituto Nacional de Ecología

- INE), the U.S. EPA, the Western Governors' Association (WGA), and the North American Commission for Environmental Cooperation (CEC). This inventory includes emissions from all states in Mexico.

T he offshore emissions include point source offshore oil and gas drilling platforms. We used updated emissions from the 2005v2 NEI point source inventory. The offshore sources were provided by the Mineral Management Services (MMS).

Table 2

- 19 summarizes the data in the ―oth‖ sectors and indicates where these emissions have been updated from the 2002 platform.

Table 2

- 19

. Summary of the othpt, othpt_hg, othar, otha r_hg, and othon s ectors changes from
the 2002 platform

Sector Components Changes from 200 2 platform othpt Mexico, 1999, point None

Canada, 2006, point Uses emissions from 2006 National Pollutant
Release Inventory (NPRI), 3 components: 1) upstream oil and gas sector emissions for all CAPs except VOC; 2) VOC sources pre

- speciated to CB05 speciation except for benzene; 3) Remaining point source emissions. Offshore, 2005, point Uses emissions from 2005 v2 point inve ntory othpt_hg Canada, 2000, mercury

point Uses speciated mercury point source year 2000 inventory.

othar Mexico, 1999, nonpoint None

Mexico, 1999, nonroad None Canada, 2006, nonpoint Uses 2006 Canadian aircraft (landing and take

- offs only), agricultural NH 3 , fugitive dust, and remaining nonpoint inventories. Canada, 2006, nonroad Uses 2006 Canadian nonroad mobile, non

- C3 marine, and locomotives inventories.

o th a r_hg Canada, 2000, mercury

nonpoint Uses speciated mercury nonpoint source ye ar 2000 inventory.

othon Mexico, 1999, onroad None

Canada, 2006, onroad Uses 2006 Canadian onroad inventory. Emissions are given at vehicle type resolution only (i.e., does not include road types)

.43



### 2.7 SMOKE

- ready non

- anthropogenic inventories for mercury and
chlorine

We generated elemental mercury from natural ( N ), recycled ( R ) and volcanic ( V ) emissions, which we added to anthropogenic ( A ) elemental mercury processed from the inventories
discussed above , to provide the elemental mercury species ― HG NRVA ‖ required by the multi

pollutant version of CMAQ. This model species is intended to include the sum of elemental mercury emissions from these sources. For the ocean chlorine, we used the same data as in the

CA P and HAP 2002

- based platform

. S ee ftp://ftp.epa.gov/EmisInventory/2002v3CAPHAP/documentation for details.

A new recycled mercury file was developed for 2005 since the scaling factors applied to temporally allocate th e annual natural and recycled emissions from oceans and land are based on solar radiation and skin temperature from the 2005 meteorology files. The annual files (prior to temporal allocation) differed from those of the 2002 platform only in that we reduce d emissions of the natural emissions from land by 90% based on literature (Gustin, et. al., 2008) , which
indicated that the emissions are 10

- 12 tons per year as opposed to the 120 tons we had been using previously.



### 2.7.1 Mercury

As discussed in the CAP and HAP 2002 v3

- based platform documentation ( ftp://ftp.epa.gov/EmisInventory/2002v3CAPHAP/documentation ) , the initial data for natural mercury, provided by Atmospheric and Environmental Research, Incorporated ( AER ) , consisted of three existing global inventories containing annual flux rates of elemental mercury, gridded to 1 degree by 1 degree resolution:

mercury emissions from oceans

— direct + recycled mercury emissions from land

— direct + recycled mercury emissions from volcanoes

– direct

As indicated earlier, we reduced the direct land mercury emissions by 90%, based on literature (Gustin, et. all, 2008) indicating that the emissions are 10

- 12 tons per year as opposed to the 120 tons we had been using previously.

Annual fluxes of recyc led elemental mercury for 2001 were created using the deposition results from a CMAQ 4.5.1 run. The approaches assumed that all recycled mercury emissions are in the form of elemental mercury gas. It is necessary to treat these recycled emissions wheneve r a version of CMAQ is used that also treats dry deposition of elemental mercury gas. The total deposition (wet plus dry) of all forms of mercury was used as the basis for the recycled emission

estimates. A fraction equal to one

- half the total deposition flux was used as the estimate for recycled emissions based on previous model calibrations done by AER.

Natural and recycled emissions from oceans and land (but not volcanic emissions) were allocated to hourly values based on the meteorological variable s of solar radiation and temperature, which are shown to be positively correlated with the evasion of elemental mercury from water surfaces soils and vegetation. While the correlation is widely variable for each of these surfaces , simple44

scaling functions for land and ocean developed for the 2001 applications were used for the 2002 and were repeated again for the 2005 v4 and v4.1 p latform s , but using 2005

- specific factors :

Ocean: or exactly zero for SFCTMP < 273 K

Land: 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 the Meteorology Chemistry Interface

Processor (MCIP) output.

The same sequence of steps were performed apply the hourly gridded scaling factors to create hourly gridded files for recycled and natural mercury based on 2005 meteorological data. No changes were made to the 2002 volcano mercury data



### 2.7.2 Chl orine

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

2002 platform

.



## 3 Emissions modeling summary

The CMAQ and CAM X model s require hourly emissions of specific gas and particle species for the horizontal and vertical grid cells contained within the modeled region (i.e., modeling domain). T o provide emissions in the form and format required by the model

, it is necessary to ―pre

- proces s‖ the ―raw‖ emissions (i.e., emissions input to SMOKE) for the sectors described
above in Section 2 . In brief, this processing step transforms the se emissions fro m their original temporal resolution, pollutant resolution, and spatial resolution into the data required by the air quality model . As seen in Section 2 , the temp oral resolution of the emissions input to SMOKE
for the 200 5 platform varies across sectors, and may be hourly, monthly, or annual total
emissions . The spatial resolution, which also can be different for different sectors, may be individual point sources or co unty totals ( province totals for Canada, municipio totals for
Mexico ). T he pre

- processing steps involving temporal allocation, spatial allocation, pollutant speciation , and vertical allocation of point sources are referred to as emissions modeling

. This section provides some basic information about the tools and data files used for emissions modeling as part of the 200 5 platform

. Since we devoted Section 2 t o describing the emissions inventories, we have limited this section‘s descriptions of data to the ancillary data SMOKE uses to perform the emissions modeling steps

All SMOKE inputs for the 2005v4 .1 platform emissions are available at the 2005v4 .1 website (see the end of Section 1 )

.

We used SMOKE version 2.6 to pre

- process the raw emissions to create the emissions inputs for CMAQ and CAM X

. The emissions processing steps and ancillary data for v4.1 were very45

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

We u pdated the ancillary files to handle additional MOVES SCCs related to parking area
emissions and to make some changes to the temporal and spatial approaches that were originally assigned to parking area SCCs

. W e change d speciation prof iles for headspace vapor (VOC)

. W e changed the PM 2.5 speciation profile for category 3 commercial marine vessels burning residual oil

. W e use d an updated county

- to

- cell spatial surrogate for U.S. oil and gas emissions

. W e change d the temporal allocation approach to use profiles that vary by day of week
and to use new temporal profiles for the afdust sector.

We also utilized the feature in SMOKE (updated in version 2.5) to create combination speciation profiles that could vary by state/county FIPS code and by month; we used this approach for some
mobile sources as described in Section 3.1.2. As with the v4 pl atform, we used the CMAQ and

CAM X in

- line emissions capability to create source

- based emissions files rather than the 3

- dimensional files for sectors that have plume rise. When CAM X was used, the emissions were first created in a form appropriate for CMAQ , and were converted to a form usable by CMAQ using a Fortran convertor called  ̳inline2camx‘. In addition to generating the gridded surface

level 2

- dimensional emissions and elevated point source files necessary for CAM X , the program
renames certain emiss ions species to the names needed by CAM X . Emissions totals by specie for the entire model domain are output as reports that are then compared to reports generated by SMOKE to ensure mass is not lost or gained during this conversion process.



### 3.1 Key emissions m odeling settings

Each sector is processed separately through SMOKE, up until the final merge program (Mrggrid)

, which combines the model

- ready

, sector

- specific emissions across sectors. The SMOKE settings in the run scripts and the data in the SMOKE ancil lary files control the approaches used for the individual SMOKE programs for each sector. Table 3

- 1 summarizes the major processing steps of each platform sector. The ― Spatial ‖ column shows the spatial approach: ―point‖ indicates that SMOKE maps the source from a point (i.e., latitude and longitude) location to a grid cell, ―surrogates‖ indicates that some or all of the sources use spatial surrogates to allocate county emissions to grid cells, and ―area

- to

- point‖ indicates that some of

the sources use the SMOKE area

- to

- point feature to gri d the emissions (further described in
Section 3.2.1.2 T he ―Speciation‖ column indicates that all sectors use the SMOKE speciation step, though biogenics speciation i s done within BEIS3 an d not as a separate SMOKE step. The ―Inventory resolution‖ column shows the inventory temporal resolution from which SMOKE

needs to calculate hourly emissions.

Finally, the ―plume rise‖ column indicates the sectors for which the in

- line approach is used

. These sectors are the only ones which will have emissions in aloft layers, based on plume rise.
For the 2005v4 and v4.1 p latform s , we did not have SMOK E compute vertical plume rise ; this was done in the air quality model using stac k data found in the SMOKE output files for each
model

- ready sector. The one sector with ―in

- line‖ only, seca_c3, was processed so that the entire emissions would be in aloft layers. Thus, there were no seca_c3 emissions in the 2

- dimensional

,46

layer

- 1 files created by SMOKE. Rather

, the speciated and hourly source

- based CMAQ and

CAM X inputs for seca_c3 were used for the vertical allocation.

Table 3

- 1

. Key emissions modeling steps by sector

.

Platform s ector Spatial Speciation Inventory
resolution Plume rise ptipm p oint Yes daily & hourly in

- line ptnonipm p oint Yes annual in

- line othpt p oint Yes annual in

- line othpt_hg p oint Yes annual in

- line

nonroad surrogates &

area

- to

- point Yes monthly

othar surrogates Yes annual seca_c3 p oint Yes annual in

- line

a lm _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 s urrogates Yes annual

nonpt surrogates &

area

- to

- point Yes annual

ag s urrogates Yes annual

afdust s urrogates Yes annual

biog pre

- gridded
landuse in BEIS 3.14 hourly

avefire surrogates Yes annual

In addition to the above settings, we used the PELVCONFIG file , which can be optionally used to group sources so that they would be treated as a single stack by SMOKE when computing plume rise. For the 2005 v 4.1 platform we chose to have no grouping , which is a difference the

2005v 4 platform . We changed this because grouping done for ― in

- line ‖ processing will not give
identical results as ―offline‖ (i.e., processing whereby SMOKE creates 3

- dimensional files)

. The only way to get the same results between in

- line and offline is to choose to ha ve no grouping.



### 3.1.1 S patial configuration

For the 200 5 v4.1 platform

, we ran SMOKE and CM AQ or CAM X (depending on the application) for modeling domains with 36

- km and 12

- km spatial resolution. These are the same
domains as were used for the 2005v4 and 2002 p latform

. 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).47 Figure 3

- 1

. CMAQ modeling domain s

All three grids use a Lambert

- Conformal projection, with Alpha = 33 o , Beta = 45 o and Gamma =

- 97 o , with a center of X =

- 97 o and Y = 40 o

. Table 3

- 2 describes t he grids for the three domains.

Table 3

- 2

. Descriptions of the 200 5

- based platform g rids

Common

Name Grid

Cell Size Description

(see Figure 3

- 1) Grid name Parameters listed in SMOKE grid description (GRIDDESC) file:

p rojection 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, 148

Section 3.2.1 provides the details on the spatial surrogates and area

- to

- point data used to accomplish spatial allocation with SMOKE.



### 3.1.2 Chemical speciation configuration

The emissions modeling step for chemical speciation creates ― model species ‖ needed by the air quality model for a specific chemical mechanism. These model species are either individual
chemical compo unds or groups of species, called ―model species

. ‖ The chemical mechanism
used for the 200 5 platform is the CB05 mechanism (Yarwood, 2005) . The same base chemical mechanism is used with CMAQ and CAM X , but the implementation differs slightly between the
two models

. For details of the chemical mechanism as it i s implemented in CAM X , see the CAMx 5.2 user‘s guide available from http://www.camx.com

. The specific version of CMAQ
used included secondary organic a erosol (SOA) and HONO enhancements as described in http://www.cmascenter.org/help/model_docs/cmaq/4.7/RELEASE_NOTES.txt

. This is unchanged from the CMAQ applications of the v4 platform.

From the perspec tive of emissions preparation, the CMAQ CB05 mechanism is the same as was used in the 2002 platform except that additional input model species are needed to support the nitrous acid (HONO) chemistry enhancements and addition al input model species are neede d to support SOA

. Table 3

- 3 lists the model species produced by SMOK E for use in CMAQ and

CAM X ; the only three input species that were not in the CAP 2002

- Based plat form described in
2002 ―CAP

- only‖ platform ( http://www.epa.gov/scram001/reports/Emissions%20TSD%20Vol1_02

- 28

- 08.pdf ) are nitrous acid ( HONO ) , BENZENE and s esquiterpene s ( SESQ )

. It should be noted that the BENZENE model species is not part of CB05 in that the concentrations of BENZENE do not provide any
feedback into the chemical reactions (i.e., it is not ―inside‖ the chemical mechanism) . Rather

, benzene is used as a rea ctive tracer and as such is impacted by the CB05 chemistry. BENZENE, along with several reactive CBO5 species (such as TOL and XYL) plays a role in SOA formation in CMAQ4.7.49

Table 3

- 3

. Model s pecies produced by SMOKE for CB05 with SOA for CMAQ4.7 and CAM X *

Inventory Pollutant Model Species Model species description

CL2 CL2 Atomic gas

- phase chlorine

HCL HCL Hydrogen Chloride (hydrochloric acid) gas

CO CO Carbon monoxide

NO X NO Nitrogen oxide

NO2 Nitrogen dioxide

HONO Nitrous acid

SO 2 SO2 Sulfur dioxide

SULF Sulfuric acid vapor

NH 3 NH3 Ammonia

VOC ALD2 Acetaldehyde

ALDX Propionaldehyde and higher aldehydes

BENZENE Benzene (not part of CB05)

ETH Ethene

ETHA Ethane

ETOH Ethanol

FORM Formaldehyde

IOLE Internal olefin carbon bond (R

- C=C

- R)

ISOP Isoprene

MEOH Methanol

OLE Terminal olefin carbon bond (R

- C=C)

PAR Paraffin carbon bond

TOL Toluene and other monoalkyl aromatics

XYL Xylene and other polyalkyl aromatics

Various additional VOC species from the biogenics model
which do not map to
the above model species SESQ S esquiterpene s

TERP Terpenes

PM 10 PMC Coarse PM > 2.5 microns and 10 microns

PM 2.5 PEC Particulate elemental carbon 2.5 microns

PNO3 Particulate nitrate 2.5 microns

POC Particulate organic carbon (carbon only) 2.5

microns

PSO4 Particulate Sulfate 2.5 microns

PMFINE Other particulate matter 2.5 microns

Sea

- salt species (non

– anthropogenic emissions) PCL Particulate chloride

PNA Particulate sodium

*The same species names are used for the CAM X model with exceptions as follows:

1. CL2 is not used in CAM X 2. CAM X mercury species are HG0 (gaseous elemental), HG2 (divalent gas) and HGP (particulate mercury)

3. CAM X particulate sodium is NA (in CMAQ it is PNA)50

4. CAM X uses different names for species that are both in CBO5 and SOA for the following: TOLA=TOL,

XYLA=X YL, ISP=ISOP, TRP=TERP. They are duplicate species in CAM X that are used in the SOA chemistry. CMAQ uses the same names in CB05 and SOA for these species.

5. CAM X uses a different name for sesquiterpenes: CMAQ SESQ = CAM X SQT

6

. CAM X uses particulate s pecies uses different names for organic carbon, coarse particulate matter and other particulate mass as follows: CMAQ POC = CAM X POA, CMAQ PMC = CAM X C PR M

, and CMAQ PMFINE=

CAM X FPRM

The approach for speciating PM 2.5 emissions in v4.1 is the same as v4 except that in addition to the on_moves_startpm and on_moves_runpm sectors, exhaust PM from diesel is provided to SMOKE as speciated emissions. Thus, the only PM species requiring speciation in SMOKE
from the onroad sector are t he brake and tirewear PM2.5. Canada point sources have an SCC of 3999999999 and all use the Speciation profile  ̳92037‘ which is the ―Industry Manufacturing Avge profile.‖ While this had not changed between v4 and v4.1, the documentation for v4
incorrectl y stated that the Canadian point inventory (othpt sector) was pre

- speciated . The Canadian point source inventory is pre

- speciated for VOC but not for PM 2.5 . One other
difference in PM 2.5 speciation is that we used a new profile ( ̳92200‘) called ― simplifi ed profile

- Marine Vessel

– Main Boiler

- Heavy Fuel Oil

– Simplified .‖ At the time that this profile was used, we anticipated its release with SPECIATE4.3.

The approach for speciating VOC emissions from non

- biogenic sources is the same for the v4.1 platform as for the v4 platform, though there are some differences in the data files used. The approach is that:

1. F or some sources, HAP emissions are used in the speciation process to allow integration
of VOC and HAP emissions in the NEI. This has the r esult of modifying the speciation profiles based on the HAP emission estimates which are presumed to be more accurate than the speciated VOC results for the HAPs ; and,

2. F or some mobile sources, ―combination‖ profiles are specified by county and month and emission mode (e.g.

, exhaust, evaporative). SMOKE computes the resultant profile using the fraction of each specific profile assigned by county, month and emission mode. A
new feature and new profile file in SMOKE (the GSPRO_COMBO file ) allowed the use

o f this approach for the 2005v4 platform, and its use continues here

.

The VOC speciation data files are different because we added another part of the nonpt sector to
exclude from HAP VOC integration : t he category of pesticide application . Additionally, the v4.1 platform used a new headspace profile representative of E0 gasoline, profile code 8762 :

― Gasoline Headspace Vapor using 0% Ethanol

- Composite Profile ―

. This profile is part of

SPECIATE4.3 and was used in place of the SPECIATE4.0 profile 8737 ( Composite Profile

- Non

- oxygenated Gasoline Headspace Vapor ), which was used in the v4 platform. The new headspace profile was used for the same sources as was the previous headspace profile: year 2005 refueling and other ambient temperature evaporativ e gasoline processes (portable fuel containers and any evaporation of gasoline associated with gasoline storage and distribution sources).

The below subsections provide a further description of the HAP/CAP integration and use of combination profiles. Sec tion 3.2.2 provides the details about the data files used to accomplish these speciation processing steps.51

3.1.2.1 The Combination of HAP BAFM (benzene, acetaldehyde, forma ldehyde and methanol) and VOC for VOC Speciation
The VOC speciation approach for the 2005 v4.1 platform differed from the 2002 platform in that we included, for some of the U.S. platform sectors, HAP emissions from the NEI in the speciation process

. That i s, i nstead of speciating VOC to generate all of the species listed in
Table 3

- 3 as we did for the 2002 platform , we integrated emissions of the 4 HAPs, benzene, acetaldehyde, formaldehyde and methanol ( BAFM ) from the NEI with the NEI VOC

. The integration process (described in more detail below) combines the BAFM HAPs with the VOC in a way that does n o t double count emissions and uses the BAFM directly in the speciation

process. We believe that generally, the HAP emissions from the NEI are more representative of
emissions of these compounds than their generation via VOC speciation.

We chose these HAPs because , with the exception of BENZENE, they are the only explicit VOC

HAPs in the base version of CMAQ 4.7 ( CAPs only with chlorine chemistry) model. By ―explicit VOC HAPs,‖ we mean model species that participate in the modeled chemistry using

the CB05 chemical mechanism. We denote the use of these HAP emission estimates along wit h
VOC as ―HAP

- CAP integration‖. BENZENE was chosen because it was added as a model species in the base version of CMAQ 4.7, and there was a desire to keep its emissions consistent
between multi

- pollutant and base versions of CMAQ.

The integration of HAP VOC with VOC is a feature available in SMOKE for all inventory formats other than PTDAY (the format used for the ptfire sector). SMOKE allows the user to specify the particular HAPs to integrate and the particular sources to integrate. The particular

HAP s to integrate are specified in the INVTABLE file, and the particular sources to integrate are based on the NHAPEXCLUDE file (which actually provides the sources that are excluded from integration 8 ). For the ―integrate‖ sources, SMOKE subtracts the ―integ rate‖ HAPs from the VOC (at t he source level) to compute emissions for the new pollutant ―NONHAPVOC.‖ The user provides NONHAPVOC

- to

- NONHAPTOG factors and NONHAPTOG speciation profiles

. SMOKE computes NONHAPTOG and then applies the speciation profiles to allocate the

NONHAPTOG to the other air quality model VOC species not including the integrated HAPs. This proce ss is illustrated in Figure 3

- 2

. Note t hat we did not need to remove B AFM from

no

- integrate sources in a sector where all sources are no

- integrate because this is accomplished by through use of a SMOKE ancillary ―INVTABLE‖ which essential ly drops all BAFM in that

sector.

8 In SMOKE version 2.6 the options to spe cify sources for integration are expanded so that a user can specify the particular sources to include or exclude from integration, and there are settings to include or exclude all sources within a sector. We did not take advantage of this new flexibility in processing v4.1 emissions or v4 emissions, but the user will now have the ability for easier inclusion of specific sources to get the same result.52

Figure 3

- 2

. Process of integrating BAFM with VOC for use in VOC Speciation53

We considered CAP

- HAP integration for all sectors and developed ― integration criteria‖ for

some of those. Table 3

- 4 summarizes the integration approach for each platform sector used in Step 1 of Figure 3

- 2.

Table 3

- 4

. Integration status of benzene, acetaldehyde, formaldehyde and methanol (BAFM) for each platform sector

Platform Sector Approach for Integrating NEI emissions of Benzene (B), Acetaldehyde (A),

Formaldehyde (F) and Methano l (M) ptipm No integration because emissions of BAFM are relatively small for this sector ptnonipm No integration because emissions of BAFM are relatively small for this sector and it is not

expected that criteria for integration would be met by a significant number of sources

avefire No integration

ag N/A

– sector contains no VOC

afdust N/A

– sector contains no VOC
nonpt Partial integration ; details provided below table

nonroad For other than California: Partial integration

– did not integrate CNG or LPG sources (SCC

beginning with 2268 or 2267 ) because NMIM computed only VOC and not any HAPs for
these SCCs. For California: Full integration alm_no_c3 Partial integration; details provided below table
seca_c3 Full integration

onroad Full integration biog N/A

– sector contains no inventory pollutant "VOC"; but rather specific VOC species othpt No integration

– not the NEI

othar No integration

– not the NEI

othon No integration

– not the NEI

For the nonpt sector, we used the following integration criteria to determine the sources to integrate (Step 1) :

1. Any source for which B AFM emissions were from the 1996 NEI were not integrated ( data source code contains a ―96‖ ).

2. An y source for which the sum of B A F M is greater than the VOC was not integrated

, since this clearly identifies sources for which there is an inconsistency between VOC and

VOC HAPs

. This includes some cases in which VOC for a source is zero

.

3. For certain source categories (those t hat comprised 80% of the VOC emissions), we chose to integrate sources in th e category per the criteria specified in the first c olumn in
Table 3

- 5 . For most of these source categories, we allow sources to be integrated if they
had the minimum combination of B AF M specified in the first column. For a few source categories, we designated all sources as ―no

- integrate‖

. The one change we made from

Table 3

- 5 for the v4.1 platform is highlighted : we change d pesticides application to ―no

integrate.‖

4. For source categories not covered in Table 3

- 5 (i.e., that do n o t comprise the top 80% of
VOC emissions ) , then as long as the source has emissions of one of the BFAM pollutants , then it can be integrated.54

Table 3

- 5

. Source

- category specific criteria for integrating nonpt SCCs for categories

co mprising 80% of the nonpoint VOC emissions

minimum

HAP (s)

needed SCC Tier 3 SCC Tier 3 Description C omments

BFA 2104008000 Stationary Source Fuel Combustion;Residential;Wood

B 2501060000 Storage and Transport;Petroleum and Petroleum

Product Storage;Gasoline Service Stations

BM 2440000000 Solvent Utilization;Miscellaneous Industrial;All

Processes Speciation profile: 3144 has no benzene but most records have it and they're from EPA (and Calif)

FAM 2401001000 Solvent Utilization;Surface Coating;Architectural Coatings

B 2310001000 Industrial Processes;Oil and Gas Production: SIC 13;All Processes : On

- shore

M 2460000000 Solvent Utilization;Miscellaneous Non

- industrial: Consumer and Commercial;All Processes

B 2501011000 Storage and Transport;Petroleum and Petroleum Product Storage;Residential Portable Gas Cans

M 2425000000 Solvent Utilization;Graphic Arts;All Processes

M 2465000000 Solvent Utilization;Miscellaneous Non

- industrial: Consumer;All Products/Processes 3144 is profile, and it does have methanol (but no BFA).

BFA 2801500000 Miscellaneous Area Sources;Agriculture Production

- Crops;Agricultural Field Burning

- whole field set

on fire 8746 is speciation profile and has BFA

M 2440020000 Solvent Utilization;Miscellaneous Industrial;Adhesive (Industrial) Application 3142 is speciation profile which has methanol (.32%) and 0 form (and no acetald, benz)

B 2501050000 Storage and Transport;Petroleum and Petroleum Product Storage;Bulk Terminals: All Evaporative

Losses

B 2310000000 Industrial Processes;Oil and Gas Production: SIC 13;All Processes

M 2465400000 Solvent Utilization;Miscellaneous Non

- industrial: Consumer;Automotive Aftermarket Products 8520 is speciation profile which doesn't have benz but does have methanol. OR is only state with benzene which is negligible

No

integrate (change
from v4 platform) 2461850000 Solvent Utilization;Miscellaneous Non

- industrial: Commercial;Pesticide Application: Agricultural P rofile has no benzene. Inventory b enzene came from solvent utilization data (Fredonia) for "other markets" for the year 1998. S ince benzene no longer allowed in pesticides , use of a no

- benzene profile would give more
accurate results. Note that this is a change

from t he v4 plat form, where this sector was ―integrate.‖

BFA 2630020000 Waste Disposal, Treatment, and Recovery;Wastewater Treatment;Public Owned profile BFA 2002 ( wastewater treatment plants). No methanol in profile. No methanol mentioned in POTW NESHAP (nor were A,F). Methanol in NEI documentation

.

no

integrate 2461021000 Solvent Utilization;Miscellaneous Non

- industrial: Commercial;Cutback Asphalt profile 1007 has none o f these HAP. Only

M innesota has a tiny amount.

no

integrate 2401005000 Solvent Utilization;Surface Coating;Auto Refinishing: SIC 7532 Only NY has b en z ene . Spec

. profile is 2402

and has none of these HAP. D ocumentation
for NEI does not estimate this HAP.

use Integrate

case 2301030000 Industrial Processes;Chemical Manufacturing: SIC 28;Process Emissions from Pharmaceutical Manuf (NAPAP cat. 106) profile 2462

- has nearly 8% benzene. Will
create a LOT of benzene with "no HAP use"

case.

M 2460200000 Solvent Utilization;Miscellaneous Non

- industrial: Consumer and Commercial;All Household Products profile is 3146 contains only nonzero
methanol.55

minimum

HAP (s)

needed SCC Tier 3 SCC Tier 3 Description C omments

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 prof ile 3139 has only M

no

integrate 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,

F reedonia 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 leg a cy) "D" rating 2004. Calif. Testing for speciation profile from 2000. Has NO benzene!
Benzene came from solvent utilization data (Fredonia) for "other markets" for the year
1998.

M 2460800000 Solvent Utilization;Miscellaneous Non

- industrial: Consumer and Commercial;All FIFRA Related
Products 3145 has M only and just a 0.01%56

For the alm_no_c3 sector , the integration criteria were (1) that the source had to have at least one

of the 4 HAPs and (2) that the sum of BAFM could not exceed the VOC emissions. The criteria for this sector were less complex than the nonpt sector because it has much fewer sourc e categories.

We used the SMOKE feature to compute speciation profiles from mixtures of other profiles in

user

- specified proportions. The combinations ar e specified in the GSPRO _COMBO ancillary
file by pollutant (including pollutant mode, e.g., E XH__VOC), state and county (i.e., state/county FIPS code ) and time period (i.e., month).

We used this feature for onroad a nd nonroad mobile and gasoline

- related related stationary

sources where by 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 sta te 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 cre ated model

- ready mercury species by speciating any of the mercury in the NEI that was n o t provided as divalent gaseous, elemental or divalent particulate

mercury

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

For the EGU sector (ptipm), all emissions except for 0.9 7 tons of the 52.9 tons of total 2005 Hg was provided in the inventory as speciated emissions. The unspeciated Hg are primarily
associated with oil

- fired units. The speciation of the coal units was retained from the 2002 inventory , since 2005 EGU emissions were based on applying a 2005

- to

- 2002 heat input ratio to
the 2002 EGU emissions.



### 3.1.3 Temporal processing configuration

Table 3

- 6 summarizes the temporal aspect of the emissions processing configuration

. It

compares the key approaches we used for temporal processing across the sectors

. We control the temporal aspect o f SMOKE processing through (a) the scripts L _TYPE ( temporal type) and M_TYPE (m erge type) settings and (b) the ancillary data files described in Section 3.2.3

. The one change made from the v4 to the v4.1 platform is the treatment of the afdust sector. In the v4 platform we used ―aveday‖ settings and no use of holidays such that every day in a specific month had the same emissions. In the v4.1 platf orm , we used ―week‖ settings and holidays and used profiles which were day

- of

- week dependent for some categories, such as road dust and tilling, where non

- uniform profiles were being used for other pollutants associated with these

processes

.57

Table 3

- 6

. Temporal s ettings u sed for the platform s ectors in SMOKE , v4.1 platform

Platform sector Inventory

resolution Monthly

profiles
used? Daily

temporal approach 1,2 Merge

processing approach 1,3 Process

Holidays as separate days?

p tipm daily & hourly all all yes

ptnonipm annual yes mwdss all yes

o thpt annual yes mwdss all

o thpt_hg annual yes mwdss all

nonroad monthly mwdss mwdss yes

o thar annual yes mwdss mwdss alm_no_c3 annual yes mwdss mwdss
seca_c3 annual yes mwdss mwdss on_noadj monthly week week yes
on_moves_startpm monthly week week yes

on_moves_runpm monthly week week yes othon annual yes week week
nonpt annual yes mwdss mwdss yes

ag annual yes aveday aveday

afdust annual yes week week yes biog hourly n/a n/a

avefire annual yes aveday aveday

1 Definitions for processing resolution: all = hourly emissions computed for every day of the year, inventory is already daily week = hourly emissions computed for all days in one ―representative‖ week , representing all weeks for each month, which means emissions have day

- of

- week variation, but not week

- to

- week variation within the

month mwdss= hourly emissions for one representative Monday, representative weekday, representative Sa turday and representative Sunday for each month, which means emissions have variation between Mondays, other weekdays, Saturdays and Sundays within the month, but not week

- to

- week variation within the month. Also Tuesdays, Wednesdays and Thursdays are tre ated the same. aveday = hourly emissions computed for one representative day of each month, which means emissions for all days of each month are the same.

2 Daily temporal approach refers to the temporal approach for getting daily emissions from the invent ory using the Temporal program . T he values given are the values of the L _TYPE setting.

3 Merge processing approach refers to the days used to represent other days in the month for the merge step. If not ―all‖, then the SMOKE merge step just run for represe ntative days, which could include holidays as indicated by the rightmost column . The values given are the values of the M_TYPE setting.

In addition to the resolution, temporal processing includes a ramp

- up period for severa l days prior to January 1, 200 5 , which is intended to mitigate the effects of initial condition

concentrations. The same procedures were used for all grids, but with different ramp

- up periods for each grid:

36 km: 10 days (Dec 22

- Dec 31) 12 km (East): 3 days (Dec 29

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

- Dec 31)58

For most sectors, our approach used the emissions from December 2005 to fill in surrogate emissions for the end of December 2004. In particular, we used December 2005 emissions (representative days) for December 200 4. For biogenic emissions, we processed December 2004 emissions using 2004 meteorology

.



### 3.2 Emissions modeling ancillary files

In this section we summarize the ancillary data that SMOKE used to perform spatial allocation, chemical speciation, and temporal all ocation for the 200 5 v4.1 platform

. The ancillary data files

, particularly the cross

- reference files, provide the specific inventory resolution at which spatial

, speciation, and temporal factors are applied. For the 200 5 v4.1 platform , we generally applied spatial factors by count r y/SCC, speciation factors by pollutant/SCC or (for combination profiles) state/county FIPS code and month

, and temporal factors by some combination of country, state, county, SCC, and pollutant.

For the v4.1 platform, w e updated the 2005v4 ancillary files in two major areas:

1. We used new data for spatially allocating oil and gas emission sources

2. We assigned spatial, temp oral and speciation profiles to parking area emissions for
additional veh icle types (new data from MOVES 2010) an d updated previous assignments for some vehicle types (summarized in Table 3

- 15 and Table 3

- 16 ).

3. We updated the headspace VOC speciation profile we used for refueling.

4. We used a new profile for speciating PM 2.5 from C3 marine emissions.



### 3.2.1 Spatial Allocation Data

As described in Section 3.1.1 , we performed spatial allocation for a national 36

- km domain, an

Eastern 12

- km domain, and a Western 12

- km domain. To do this, SMOKE used national 36

- km

and 12

- km spatial surrogates and a SM OKE area

- to

- point data file

. For the U.S. and Mexico, we used the same spatial surrogates as were used for the 2002 v3 platform . For Canada we used a

new set of Canadian surrogates provided by Environment Canada. T he spatial data files we used
can be obt ained from the files listed below; these are available from the 2002v3CAP (for US and Mexico) and 2005v4CAP

- BAFM (for Canada) platform web site s (see the end of Section 1 )

. The oil and natural gas surrogate files are posted at the 2005v4.1 website. The following list of seven files provides descriptions of each of their contents and intended uses for the v4.1 platform.

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

36

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

2005

- based platform except for the year 2000 mercury data which is contained in the sector othpt )

12km_surg_2002v3mpCAP_smokeformat.zip : U.S. and Mexican surrogate files for surrogate files for 12 km spatial resolution (Canadian data contained in this zip file was
not used for the 2005

- based platform except for the year 2000 mercury data which is
contained in the sector oth ar )

new 36km_surg_200 5v4 _smokeformat.zip : Canadian surrogate files for 36

- km spatial resolution for Canadian surrogates59

new 12km_surg_200 5 v 4 _smokeformat.zip : Canadian surrogate files for 12

- km spatial
resolution for Canadian surrogates

new_oilgas_surg_2005v4_1_smokeformat.zip : Oil and gas surrogate files for 36

- km spatial resolution and 12

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

ancillary_200 5v4.1 _smokeformat.zip : spatial related data includ ed are the grid description (GRIDDESC), surrogate description (SRGDESC), surrogate cross reference file (AGREF), and area

- to

- point (ARTOPNT) file

The U.S., Mexican

, and Canadian 12

- km surrogates cover the entire CONUS domain, though they are used directl y as inputs for the two separate Eastern and Western Domains shown in Figure 3

- 1

. The SMOKE model windowed the Eastern and Western grids while it created these
emissions. The remainder of this sub section provides further detail on the origin of the data used for the spa tial surrogates and the area

- to

- point data.

3.2.1.1 Surrogates for U.S. Emissions

There are 6 7 spatial surrogates available for spatially allocating U.S. county

- level emissions to
the 36

- km and 12

- km grid cells used by the air quality model ; 66 are the same as for the v4 platform , and one new surrogate, ― Oil & Gas Wells, IHS Energy, Inc. and USGS‖ was added for

v4.1 which is discussed below. As described in Section 3.2.1.2 , an area

- to

- point approach overrides the use of surrogates for some sources. Table 3

- 7 lists t he codes and descriptions of
the surrogates

.

Table 3

- 7

. U.S. Surrogates available for the 2005v4 .1 p latform

.

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 Hospitals60

Code Surrogate Description Code Surrogate Description

255 0.75 Total Roadway Miles plus 0.25 Population 600 Gas Stations

260 Total Railroad Miles 650 Refineries and Tank Farms

270 Class 1 Railroad Miles 675 Refineries and Tank Farms and Gas Stations

280 Class 2 and 3 Railroad Miles 680 Oil & Gas Wells, IHS Energy, Inc. and

USGS

300 Low Intensity Residential 700 Airport Areas

310 Total Agriculture 710 Airport Points

312 Orchards/Vineyards 720 Military Airports

320 Forest Land 800 Marine Ports

330 Strip Mines/Quarries 807 Navigable Waterway Miles

340 Land 810 Navigable Waterway Activity

350 Water 850 Golf Courses

400 Rural Land Area 860 Mines

500 Commercial Land 870 Wastewater Treatment Facilities

505 Industrial Land 880 Drycleaners

510 Commercial plus Industrial 890 Commercial Timber

We did not use all of the available surrogates to spatially allocate sources in the v4 .1 p latf orm; that is, some surrogates in Table 3

- 7 were not assigned to any SCCs.

The c reation of surrogates and shapefiles for the U.S. via the Surrogate To ol was discussed in the

2002 v3 platform documentation and is not repeated here. The tool and u pdated documentation
for it is available at http://www.ie.unc.edu/cempd/projects/mims/spatial/ and http://www.cmascenter.org/help/documentation.cfm?MODEL=spatial_allocator&VERSION=3. 6&temp_id=99999

. This same tool was used for the new s urrogate 680, ― Oil & Gas Wells, IHS Energy, Inc. and USGS‖

The new surrogate ―Oil & Gas Wells, IHS Energy, Inc. and USGS‖ was developed for oil and gas SCCs, which had previously (in the v4 platform) used surrogate 585. The data reflect data through 10/1 /2005. The underlying data for thi s surrogate is a grid of one

- quarter square mile
cells contai ning an attribute to indicate whether the we lls within the cell are predominantly oil

producing, gas

- producing, both oil

- and gas

- producing, or the wells are dr y or their production
status is unknown. The well information was initially retrieved from IHS Inc.'s PI/Dwights
PLUS Well Data on CD

- ROM, which is a proprietary commercial database containing information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to overcome the problem of displaying proprietary well data. No proprietary data are displayed or included in the cell maps. More information can be obtained from http://pubs.usgs.gov/dds/dds

069/dds

- 069

- q/text/layer.htm and http://certmapper.cr.usgs.gov/rooms/uti lities/layer_info.jsp?docId={A90AF432

- 612F

- 41F9

- A315

- 7329FD933FB3}&type=download&docURL=http://certmapper.cr.usgs.gov/data/noga00/natl/sp atial/doc/uscells05g.htm61

The spatial cross

- reference file was also updated to assign onroad off

- network ( parking area )
emissions from the MOVES 2010 model , new to the 2005 v4 platform, were allocated as shown in
Table 3

- 8

.

Table 3

- 8

. Surrogate assignments to new mobile categories in the 2005 v4 platform

SCC & Description Surrogate 2201001350 Light Duty Gas Vehicles

- parking areas rural 2201002350 Light Duty Gas Trucks 1&2

- parking areas rural 2201004350 Light Duty Gas Trucks 3&4

- parking areas rural Rural population (same as rural local roads), code= 130

2201001370 Light Duty Gas Vehicles

- parking areas urban 2201002370 Light Duty Gas Trucks 1&2

- parking areas urban 2201004370 Light Duty Gas Trucks 3&4

- parking areas urban Urban population (same as urban local roads), code =120

2201070350 Heavy Duty Gasoline Vehicles 2B thr ough 8B & Buses

(HDGV)

- parking areas rural 2201070370 Heavy Duty Gasoline Vehicles 2B thr ough 8B & Buses

(HDGV)

- parking areas urban Commercial plus Industrial plus

Institutional

, code = 520

3.2.1.2 Allocation Method for Airport

- Related Source s in the U.S.
There are numerous airport

- related emission sources in the 200 5 NEI, such as aircraft, airport ground support equipment

, and jet refueling. Unlike the 2002 v3 platform in which most of these
emissions we re contained in sectors with county

- level resolution

– alm (aircraft), nonroad (airport ground suppo rt) and nonpt (jet refueling), the 2005 platform includes the aircraft emissions as point sources . As sh own 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 use d the SMOKE ―area

- to

- point‖ approach for only airport ground support equipment (nonroad sector), and jet refueling (nonpt sector). The approach is
described in detail in the 2002 platform documentation : http://www.epa.gov/scram001/reports/Emissions%20TSD%20Vol1_02

- 28

- 08.pdf

.

We used nearly the same ARTOPNT file to implement the area

- to

- point approach as was used
for the CAP and HAP

- 2002

- Based platform . This was slightly updated from the CAP

- only 2002 platform by further allocating the Detroit

- area airports into multiple sets of geographic coordinates to support finer scale modeling that was done under a different project. We chose to retain the updat ed file for the 2005 platform

. This approach is the same in the v4.1 and v4 platforms.

3.2.1.3 Surrogates for Canada and Mexico Emission Inventories

We used an updated set of s urrogates for Canad a to spatially allocate the 2006 Canadian
emissions for the 200 5 v4 platform with the exception of the nonpoint Canadian mercury
emissions. The updated set completely replaced the 2002 v3 platform surrogates for allocating the 2006 province

- level Canadian emissions. The 2002 v3 platform surrogates for Canada were used for the mercury data in the sector other_hg because Canada did not provide updated mercury data with its 2006 inventory.62

The updated surrogate data provided in the 2005v4 zip files and described in Table 3

- 9 came from Environment Canada. They provided the surrogates and cross references ; the surrogates they provided were outputs from the Surrogate T ool (previously referenced)

. Per Environment Canada, the surrogate s are based on 2001 Canadian census data

. We changed the cross

references that Canada originally provided as follows: all assignments to surrogate '978' (manufacturing industries) were changed to '906' (manufacturing services )

, and all assignments

to '985 ' (construction and mining) and  ̳9 8 4‘ (construction industries) were changed to '907' (construction services) because the surrogate fractions in 984, 978 and 985 did not sum to 1

. We also changed codes for surrogates other than population that did not beg in with the digit ―9‖.

The same surrogates were used for the 12

- km domains as were used for the 36

- km domain

.

Table 3

- 9

. Canadian Spatial Surrogates for 2005

- based platform Canadian Emissions (v4.1 unchanged from v4)

Surrogate description Filename of 2005

Platform Surrogate Surrogate description Filename of 2005

Platform Surrogate Population CA_100_NOFILL.txt asphalt CA_951_NOFILL.txt Total dwelling CA_901_NOFILL.txt cement CA_952_NOFILL.txt Agriculture and Forestry and Fishing CA_902_NOFILL.txt
chemical CA_953_NOFILL.txt Waste Management
Service CA_903_NOFILL.txt
commfuelcomb CA_954_NOFILL.txt

U pstream O il and G as (UOG) CA_904_NOFILL.txt downstream_petroleum CA_955_NOFILL.txt Mining and Oil and Gas
services CA_905_NOFILL.txt

egu CA_956_NOFILL.txt Manufacturing services CA_906_NOFILL.txt grain CA_957_NOFILL.txt

Construction services CA_907_NOFILL.txt manufacturing CA_958_NOFILL.txt Transportation of Passengers and goods CA_908_NOFILL.txt mining CA_959_NOFILL.txt

Electric and Gas and

Water utilities CA_909_NOFILL.txt oilgas_distibution CA_960_NOFILL.txt Wholesaling
Merchandise services CA_910_NOFILL.txt smelting CA_961_NOFILL.txt Retailing Merchandise
services CA_911_NOFILL.txt

waste CA_962_NOFILL.txt

Government Services CA_915_NOFILL.txt wood CA_963_NOFILL.txt

All Sales CA_920_NOFILL.txt asphalt industries CA_971_NOFILL.txt

Intersection of
AGRFORFISH and

MANUFACT CA_921_NOFILL.txt

cement industries CA_972_FILL.txt

Intersection of Forest and Housing CA_922_NOFILL.txt

chemical industries CA_973_FILL.txt

Intersection of
MININGOILG and

MANUFACT CA_923_NOFILL.txt
commercial fuel

combustion CA_974_FILL.txt

Intersection of
UTILITIES and

DWELLING CA_924_NOFILL.txt downstream petroleum

industries CA_975_FILL.txt

Intersection of
CONSTRUCTION and CA_925_NOFILL.txt

Electric utilities CA_976_FILL.txt63

Surrogate description Filename of 2005

Platform Surrogate Surrogate description Filename of 2005

Platform Surrogate

DWELLING

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 originally numbered by Canada as 611, 615, 620 and 65, respectively. We changed the numbers so that all Canadian surrogates would begin with ―9‖.

The Mexican emissions and single surrogate (population) are the same in the v4.1 platform as were used in the 2005v4 and 2002 platform s

.



### 3.2.2 Chemical speciation ancillary files

The following data file s , provided at the 200 5v4 website (see the end of Section 1 )

, contain the SMOKE inputs used for chemical speciation of the inventory species to the CMAQ model species. SMOKE environmental variable names, used in the file names, are shown using capita l letters in parentheses:

ancillary_200 5 v 4 .1 _smokeformat.zip: inventory table (INVTABLE), NONHAPVOC
emissions calculation exclusions file (NHAPEXCLUDE), speciation cross reference s (GSREF), speciation VOC

- to

- TOG conversion factors (GSCNV)

, speciation pro files (GSPRO)

, and combined, monthly speciation profiles (GSPRO_COMBO)

. ancillary_2005v4 .1 _futureyear_ smokeformat.zip: speciation

- related files associated with the future year speciation changes.

The following subsections explain these SMOKE input files.

3.2.2.1 INVABLE and NHAPEXCLUDE

T he INVTABLE and NHAPEXCLUDE SMOKE input files have a critical function in the VOC speciation process for emissions modeling cases utilizing HAP

- CAP integration, as is done for
the 2005v4 .1 p latform.

We prepared two diffe rent INV TABLE files to use with different sectors of the platform. For sectors in which we chose no integration across the entire sector (see Table 3

- 5 ), we created a
―no HA P use‖ INVTABLE that set the ―KEEP‖ flag to ―N‖ for BAFM pollutants . Thus, any

BAFM pollutants in the inventory input into SMOKE would be dropped. This approach both64

avoids double

- counting of these species and assumes that the VOC speciation is the best available approach for these species for the sectors using the approach. The second INVTABLE, used for sectors in which one or more sources are integrated, causes SMOKE to keep the BAFM pollutants and indicates that they are to be integrated with VOC (by setting the ― VOC or TOG
component ‖ field to ―V‖ for all fou r HAP pollutants.

We also prepared sector

- specific NHAP EXCLUDE files that provide the specific sources that are excluded from integration (see Table 3

- 5 ).

3.2.2.2 GSPRO, GSPRO_ COMBO , GSREF and GSCNV,
For VOC speciation, we generated the following SMOKE

- ready profiles for the CB05 chemical mechanism using the Speciation Tool (Eyth, 200 6 ) :

TOG

- to

- mo del species (used only for no

- integrate sources)

NONHAPTOG

- to

- model species (used only for the integrate sources)

TOG

- to

- BENZENE (used only for no

- integrate sources)

We added speciation profile entries that simply map NEI emissions of benzene, acetaldehyd e, formaldehyde and methanol to the model species BENZENE, ALD2, FORM and METHANOL, respectively. These profiles were used only for the integrate sources. Note that we process the integrate and no

- integrate sources using the same GSREF and GSPRO files. Thus, to avoid double counting of these HAP species, we removed BAFM pollutants for all no

- integrate sources in the inventory. If the entire sector was no

- integrate, then we were able to remove these in SMOKE (by using ―N‖ in the INVTABLE) but if a sector was partially integrated, then we

needed to remove these HAPS from the actual inventory input to SMOKE, but only for the no HAP us e, no

- integrate sources.

In addition to the speciation profiles, the Speciation Tool generates the SMOKE

- ready speciation
conversion files (GSCNV)

. We generated two of these: one containing profile

- specific VOC

- to

TOG conversion factors and the other containing profile

- specific NONHAPVOC

- to

NONHAPTOG conversion factors

.

The TOG and PM 2.5 speciation factors that are the basis of the chemical speciation approach were developed from the SPECIATE4. 2 database ( http://www.epa.gov/ttn/chief/software/speciate/index.html ) which is EPA's repository of TOG
and PM speciation profiles of air pollution sources. However, a few of the profiles we used in the v4.1 platform will be published in SPECIATE4.3 after the release of this documentation

.

The SPECIATE database development and maintenance i s a collaboration involving EPA ‘s

ORD , OTAQ, and EPA ‘s Office of Air Quality Planning and Standards (OAQPS) , and Environment Canada (EPA, 2006c). The SPECIATE database contains speciation profiles for TOG, speciated into individual chemical compounds, VOC

- to

- TOG conversion factors associated with the TOG profiles, and speciation profiles for PM 2.5 . The databa se 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:65

PSO4 : primary particulate sulfate PNO3: primary particulate nitrate PEC: primary particulate elemental carbon POC: primary particulate organic carbon PMFINE: other primary particulate, less than 2.5 micrograms in diameter

As discussed earlier, for the v4.1 platform we updated the PM 2.5 profile used for category 3 marine vessels burning residual oil to use the profile: Marine Vessel

- Main Engine

- Heavy Fuel Oil which will be published in SPECIATE4.3. This profile was compiled from data published in Emission Measurements fro m a Crude Oil Tanker at Sea, Environ. Sci. Technol. 2008, 42, 7098

– 7103. Previously the Draft Residual Oil Combustion

– Simplified (92072) was
used. The SCCs affected were:

2280003000 Mobile Sources;Marine Vessels, Commercial;Residual;Total, All Vessel Types
2280003010 Mobile Sources;Marine Vessels, Commerci al;Residual;Ocean

- going Vessels

2280003100 Mobile Sources;Marine Vessels, Commercial;Residual;Port emissions

2280003200 Mobile Sources;Marine Vessels, Commercial;Residual;Underway emissions

The difference between the two profiles is provided in Table 3

- 10 , and shows that the new profile produces much more organic carbon and less elemental carbon, sulfate, and other PM 2.5

.
Table 3

- 10

. Differences between two profiles used for c ommercial m arine r esidual o il

P ollutant S pecies Split factors new c3 profile
92 200 used for v4.1 S plit factors residual oil
combustion
92072 , used for v4

PM2_5 PEC 0.0 05 0.01

PM2_5 PMFINE 0. 5022 0. 54

PM2_5 PNO3 0 0

PM2_5 POC 0. 1125 0. 01

PM2_5 PSO4 0. 3803 0. 44

We also updated the bituminous coal profile, 92095, which we had previously used for only a single nonpoint SCC (2101002000) with the sub

- bituminous profile 92084, which was used for
all other coal combustion SCCs. We replaced profile 92095 with 92084 for consistency. Table

3

- 11 shows the differences are shown below , though these are quite small and represent only a minor change to the SMOKE results :66 Table 3

- 11

. Differences between two profiles used for coal combustio n

P ollutant S pecies Split factors sub

bituminous 92084 S plit factors
bituminous 920 9 5

PM2_5 PEC 0.0188 0.01696

PM2_5 PMFINE 0.8266 0.827928

PM2_5 PNO3 0.0016 0.00208

PM2_5 POC 0.0263 0.026307

PM2_5 PSO4 0.1267 0.126725

We made other updates to profile assignments for the SCCs shown in Table 3

- 12 below as compared to the 2002 platform . These updates were kept for the v4.1 platform

.

Table 3

- 12 : PM 2.5 speciation profile updates assignments for the v4 platform

SCC New

Profile
Code Pollutant Profile Name

39900501 92025 PM2_5 Distillate Oil Combustion Source Type: Distillate Oil Combustion

49090021 92025 PM2_5 Distillate Oil Combustion Source Type: Distillate Oil Combustion

30890002 92072 PM2_5 Residential Oil Combustion Source Type: Residential Oil
Combustion

10100912 92091 PM2_5 Wood Fired Boiler Source Type: Wood/Bark Combustion

10102018 92057 PM2_5 PM/SO2 controlled lignite combustion: Waste Coal Combustion

50410563 92082 PM2_5 Solid Waste Combustion Source Type: Solid Waste Combustion

10100692 92048 PM2_5 Natural Gas Combustion Source Type: Natural Gas Combustion

50100511 92086 PM2_5 Tire Burning Source Type: Tire Burning

50100512 92082 PM2_5 Solid Waste Combustion: Solid Waste Combustion

2810040000 92035 PM2_5 HDDV Source Type: Aircraft Engines

Key changes to the TOG profiles for the v4.1 platform from the 2005v4 platform are as follows:

Used new headspace profiles for E0 (no ethanol gasoline) and E10 (10% ethanol gasoline) , which will be published in SPECIATE4.3

. Profile 8762 is Gasoline Headspace Vapor using 0% Ethanol

- Composite Profile and Profile 8763 is Gas oline Headspace Vapor using 10% Ethanol

- Composite Profile . In 2005, only the E0 profile is used. This was an oversight since we could have used the same combinations of profiles of E0 exhaust E10 exhaust (which are also the same combinations of E10 ev aporative and E10 evaporative) that we used for 2005. We did, however use consistent combinations (E0/E10) in future year modeling for the headspace profiles as the evaporative and

exhaust combinations.

Added the fuel

- specific VOC profiles for the new parking area SCCs generated due to the fact that MOVES2010 was used for all vehicle types in the v4.1 platform . A summary of the assignments of all profiles (speciation, temporal and spatial surrogates) is provided in
Table 3

- 15 for gasoline vehicles and Table 3

- 16 for diesel vehicl es.

Table 3

- 13 provides a summary of the 2005 speciation approach for mobile and other fuel

related sources. It shows the updated profiles that form the 2005 combina tions. The headspace67

profile , 87 62 is a new profile for the v4.1 platform , and is used for other nonroad refueling and

other fuel

- related stationary source emission categories in 2005.

Table 3

- 13

. Summary of VOC speciation profile approach by sector for 2005

Inventory type and

mode VOC speciation approach
for fuels VOC

Profile
Codes 2005

sectors

Mobile onroad and nonroad
Exhaust E0 and E10
combinations (excludes Tier 2) 8750

8751 on_noadj

nonroad

Mobile onroad and nonroad Evaporative E0 and E10

combinations 8753

8754 on_noadj

nonroad

Mobile nonroad R efueling Stationary (no mode assigned to VOC) : P ortable F uel Containers, bulk plant

- to

pump, refinery

- to

- bulk
terminal E0 87 62 Nonroad
nonpt

In future years, different profile combinations and a different headspace profile is used, due to the influx of greater quantities of ethanol in fuels. Changes to the above profiles for future

- year scenarios will be discussed in more detail in the documentat ion of futu re year emissions development for the rule or application of interest

. In summary , we utilized additional profiles in
the combinations that is appropriate . The profiles we added were Tier 2 profiles for E0 and E10 and an E10 headspace profile.

Mercury speciation was done for sources that were not already provided as elemental (HGNRVA), divalent gas (HGIIGAS) and particulate (PHGI). The vast majority of the IPM
sector was pre

- speciated in the 2005 NATA inventory, and thus did not require the application of profiles. Mercury emissions from NMIM were also pre

- speciated. Table 3

- 14 shows the data profiles we used to speciate any inventory mercury reported as unspeciated mercury. These are the same profiles as were used in the CAP and HAP 2002

- based platform , Version 3 ( http://www.epa.gov/ttn/chief/emch/index.html#2002 )

. The actual specia tion profiles used also converted the mass of gaseous mercury to moles by dividing by the molecular weight of

mercury. Profiles were assigned to the inventory on the basis of MACT code, SCC code and/or SIC code. The cross reference file is provided in the ancillary files ( ancillary_2005v4.1_smokeformat.zip).

Table 3

- 14

. Spe ciation of Mercury

Source Category Particulate
Divalent % Gaseous

Divalent % Elemental

Gaseous % Profile

code

Portland Cement 12 13 75 HGCEM
Mercury Cell Chlor

- Alkali Plants 0 5 95 HGCHL

combustion or default 20 30 50 HGCMB68 Source Category Particulate
Divalent % Gaseous

Divalent % Elemental

Gaseous % Profile

code
all other nonpoint categories; gold mining 0 0 100 HGGLD

I ncin eration/

- waste disposal 20 58 22 HGINC

Industrial Processes non
combustion/incin 10 10 80 HGIND

mobile diesel (onroad and nonroad) 15 29 56 HGMD
mobile gasoline (onroad and nonroad) 0.4 8.6 91 HGMG

Medical Waste Incineration 20 75 5 HGMWI

Speciation profiles for use with BEIS are not included in SPECIATE. The 2005 platform uses BEIS3.14

, which includes a new species (SESQ) that was not in BEIS3.13 (the version used for
the 2002 platform ). Thus we added this species (it is mapped to the CMAQ species SESQT) to the set of profiles that we had been using in the 2002 platform

. The profile code associated with

BEIS3.1 4 profiles for use with CB05 uses the same as in the 2002 platform : ―B10C5. ‖



### 3.2.3 Temporal allocation ancillary files
The emissions modeling step for temporal allocation creates the 200 5 hourly emission inputs for the air quality model by adjusting the emissions from the inventory resolution (annual, monthly, daily or hourly) that are input into SMOKE. The temporal resolution of each of the platform

sectors prior to their input into SMOKE is included in the sector descriptions from Table 2

- 1 and

r epeated 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 200 5 hourly emissions inputs for the air quality model were generally based on the temporal allocation data used for the 200 2 v3 platform

. For the v4 and v4.1 platforms, w e added new profile assignments for SCCs in the 2005 inventory that were not in the 200 2 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 inventory species to the air quality model species. SMOKE environmental variable names, used in the file names, are shown in capital letters in parentheses:

ancil lary_2005v4 .1 _smokeformat.zip: includes temporal cross reference files used across all inventory sectors (ATREF, MTREF, and PTREF) and for ptipm sector (used for electric generating units) for the evaluation case (PTREF) and, temporal profiles (ATPRO, MTPR O, and PTPRO)

The starting point for our temporal profiles was the 2002 platform

. The remainder of this section
discusses the development of the new temporal profiles or profile assignments used in the

2005 v4 platform

.

Canadian emissions69

The profiles assignments for the Canadian 2006 inventory were provided by Environment Canada along with the inventory. They provided profile assignments that rely on the existing set of temporal profiles in the 2002 platform . For point sources, they prov ided p rofile assignments by PLANTID.

WRAP Oil and Gas Inventory Profiles

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

Diurnal Profiles for Electric Generating Units (ptipm)

We updated the state

- specific and pollutant

- specific diurnal profiles for use in allocating the day

specific emissions for non

- CEM sources in the ptipm sector. We used the 2005 CEM data to

create state

- specific, day

- to

- hour factors, averaged over the whol e 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 pollutants. All other pollutants used factors created from the hou rly heat input data. We assigned the resulting profiles by state and pollutant.

Onroad Parking Area Profiles

The SCCs and d escriptions, along with the assignments chosen are shown in Table 3

- 15 (ga soline vehicles) and Table 3

- 16 (diesel vehicles)

. Figure 3

- 3 and Figure 3

- 4 show the diurnal profiles referred to in the table s

.

Figure 3

- 3

. Diurnal Profiles based on road type (use local for ―start‖) and whether the road is
urban v ersus rural70

Figure 3

- 4

. Diurnal temporal profile for HDDV 2B through 8B at Parking areas71

Table 3

- 15

. Summary of s patial s urrogates

, t emporal p rofiles

, and s peciation profiles used by gasoline vehicle t ype s for the onroad

p arking area

- related SCCs.

GASOLINE VEHICLE TYPES

SCC&Description Surrogate Temporal
Profile: Monthly
Variation Temporal Profile:

Day of Week Variation Temporal Profile:
Diurnal variation Speciation Profile

2201001350 Light Duty Gas
Vehicles

- parking

areas rural

2201020350 Light Duty Gas Trucks

1&2

- parking areas

rural

2201040350 Light Duty Gas Trucks

3&4

- parking areas

rural

2201080370 Motorcycles (MC)

- parking areas rural Rural

Population (same as
rural local roads)

130 Not

applicable

– inventory
contains monthly

emissions RURAL LD values are:

Mon

– Fri 12.1% 12.1%
12.1% 12.1% 18.3%
Sat/Sun: 15.3% 18.3%

Weekly_code (for SMOKE) =20021 Use same as profile

as rural local

roads (Rdtype=210)

. Code = 2006 (see Figure 3

- 3 , reddish curve) Use same speciation profiles as what is used for LD GAS

vehicles on the other roadway types. *
i.e.: EVP__VOC: COMBO of 8753 (Gasoline Vehicle

- Evaporative emission

- Reformulated gasoline) & 8754 (Gasoline Vehicle

- Evaporative emission

- E10 ethanol gasoline) Note that these are the combinations used in 2005. In some cases future year profiles may also include 8755 (Gasoline Vehicle

- Evaporative emission

- E85) EXH__VOC: COMBO of 8750&8751 These combinations

are used in 2005. In some cases future year profiles may also include combinations of 8752 (E85) , 8756 (tier 2 exhaust, E0), 8757 (tier 2 exhaust, E10)

EXH__PM2.5 not needed because OTAQ supplies pre

speciated emissions BRK_PM2.5 and TIR_PM2.5 use same as other roadways (92009 and 92087, respectively)

2201001370 Light Duty Gas
Vehicles

- parking

areas urban

2201020370 Light Duty Gas Trucks

1&2

- parking areas

urban

2201040370 Light Duty Gas Trucks

3&4

- parking areas

urban

2201080370 Urban

Population (same as

urban local roads)

120 Not

applicable

– inventory
contains monthly
emissions URBAN LD values are:

Mon

- Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%

Weekly_code (for SMOKE) =20031 Use same as profile

as urban local

roads

. (Rdtype=330)

.

Code = 2012 (see Figure 3

- 3 , yellow curve) Same as above72 GASOLINE VEHICLE TYPES

SCC&Description Surrogate Temporal
Profile: Monthly
Variation Temporal Profile:

Day of Week Variation Temporal Profile:
Diurnal variation Speciation Profile Motorcycles (MC)

- parking areas rural

2201070350 Heavy Duty
Gasoline Vehicles

2B thr ough 8B & Buses (HDGV)

- parking areas rural Commercial

plus

Industrial plus
Institutional (code = 520) Not

applicable

– inventory
contains monthly
emissions RURAL HD values are:

Mon

- Fri
16.8% 16.8% 16.8% 16.8%
15.9%
Sat Sun 8.8% and 8.8%

Weekly_code (for SMOKE) =20022 Use same as profile

rural local roads

. Code = 2006 (see Figure 3

- 3 , reddish curve) Same as above

2201070370 Heavy Duty
Gasoline Vehicles
2B thr ough 8B & Buses (HDGV)

- parking areas urban Same as

above Not

applicable

– inventory
contains monthly

emissions URBAN HD values are:

Mon

- Fri
17.7% 17.7% 17.7% 17.7%
17.7%
Sat Sun 7% an d 5%

Weekly_code (for SMOKE) =20032 Use same as profile

on urban local

roads

. Code = 2012 (see Figure 3

- 3 , yellow curve) Same as above73

Table 3

- 16

. Summary of s patial s urrogates

, temporal p rofiles

, and s peciation profiles used by diesel vehicle t ype s for the onroad

p arking area

- related SCCs from MOVES2010

.

DIESEL VEHICLE TYPES

SCC&Description Surrogate Temporal
Profile: Monthly
Variation Temporal Profile:

Day of Week Variation Temporal Profile:
Diurnal variation Speciation Profile 2230001350 Light Duty Diesel Vehicles (LDDV)

- parking areas

rural

2230060350 Light Duty Diesel
Trucks 1 thr ough 4 (M6) (LDDT) )

- parking areas rural Rural Population (same as rural local roads)

130 Not

applicable

– inventory
contains monthly
emissions RURAL LD values are:

Mon

– Fri 12.1% 12.1%
12.1% 12.1% 18.3%
Sat/Sun: 15.3% 18.3%

Weekly_code (for SMOKE)

=20021

Rationale: choose same weekend/weekday variation for all Light Duty Veh icles on all rural road types Use same as profile as

rural local roads (Rdtype=210)

. Code = 2006 (see Figure

3

- 3 , reddish curve)

Rationale: choose same diurnal profile for all vehicles (except HDDV 2B to 8B) for all rural parking areas (which is the

pro file used for rural local roads) Use same speciation profiles as what is used for LD DIESEL vehicles, irrespective of road type.
i.e.: EVP__VOC: ZERO emissions (placeholder profile is required by SMOKE: 4547 (Gasoline Headspace Vapor

- Circle K Diesel

- adjusted for oxygenates) EXH__VOC: 4674 (Diesel Exhaust

- Medium Duty Trucks)

PM2.5 : ZERO emissions  not needed since OTAQ supplies pre

- speciated emissions. Placeholder profile is required by SMOKE: 92042 (LDDV Exhaust

– Simplified)

BRK_PM2.5 and TIR_PM2.5 use same as other roadways (92009 and 92087, respectively) 2230001370 Light Duty Diesel Vehicles (LDDV)

- parking areas

urban

2230060370 Light Duty Diesel
Trucks 1 thr ough 4 (M6) (LDDT) )

- parking areas urban URBAN Population (same as
urban local roads)

120 Not

applicable

– inventory
contains monthly
emissions URBAN LD values are:

Mon

- Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%

Weekly_code (for SMOKE)

=20031

Rationale: choose same weekend/weekday variation
for all Light Duty Vehicles on urban road types Use same as profile as

urban local roads

. (Rdtype=330)

.

Code = 2012 (see Figure

3

- 3 , yellow curve

Rationale: choose same diurnal profile for all vehicles (except HDDV 2B to 8B) for all rural parking areas (which is the profile used for rural local roads) Same as above74 DIESEL VEHICLE TYPES

SCC&Description Surrogate Temporal
Profile: Monthly
Variation Temporal Profile:

Day of Week Variation Temporal Profile:
Diurnal variation Speciation Profile 2230071350 Heavy Duty Diesel Vehicles (HDDV) Class 2B

parking areas rural

2230072350 Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, & 5

- parking areas rural

2230073350 Heavy Duty Diesel Vehicles (HDDV) Class 6 & 7

- parking areas rural

2230074350 Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B

parking areas rural Rural primary
roads
code=210

Rationale: most idling
will occur at truckstops Not

applicable

– inventory
contains monthly
emi ssions RURAL HD values are:

Mon

- Fri
16.8% 16.8% 16.8% 16.8%
15.9%
Sat Sun 8.8% and 8.8%

Weekly_code (for SMOKE)

=20022 Construct new profile
CODE=3000 which is low at daytime and high at night

- time (11pm to 2am) See Figure 3

- 4 Use same speciation profiles as what is used for HD DIESEL vehicles, irrespective of road type.
i.e.: EVP__VOC: ZERO emissions (placeholder profile is required by SMOKE: 4547 (Gasoline Headspace Vapor

- Circle K Diesel

- adjusted for oxygenates) EXH__VOC: 4674 (Diesel Exh aust

- Medium Duty Trucks)

PM2.5 : ZERO emissions  not needed since OTAQ supplies pre

- speciated emissions. Placeholder profile is required by SMOKE: 92035 (HDDV Exhaust

– Simplified)

BRK_PM2.5 and TIR_PM2.5 use same as other roadways (92009 and 92087, respectively) 2230071370 Heavy Duty Diesel Vehicles (HDDV) Class 2B

parking areas urban

2230072370 Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, & 5

- parking areas urban

2230073370 Heavy Duty Diesel Vehicles (HDDV) Class 6 & 7

- parking areas urban

2230074370 Heavy Duty Diesel Vehicles (HDDV) Class 8A & 8B

parking areas urban URBAN primary roads
code=200

Rationale: most idling
will occur at truckstops Not

applicable

– inventory
contains monthly
emissions URBAN LD values are:

Mon

- Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%

Weekly_code (for SMOKE)

=20031 Construct new profile
CODE=3000 which is low at daytime and high at night

- time (11pm to 2am) See Figure 3

- 4 Same as above75 DIESEL VEHICLE TYPES

SCC&Description Surrogate Temporal
Profile: Monthly
Variation Temporal Profile:

Day of Week Variation Temporal Profile:
Diurnal variation Speciation Profile 2230075350 Heavy Duty Diesel Buses (School & Transit)

- parking

areas rural Rural Population (same as rural local roads)

130 Not

applicable

– inventory
contains monthly
emissions USE URBAN LD values:

Mon

- Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%

Weekly_code (for SMOKE)

=20031

Rationale: these vehicles follow profile of LD vehicles better than HD; day of week

variation should more closely follow urban (higher weekday than weekend) Use same as profile as

rural local roads (Rdtype=210)

. Code = 2006 (see Figure

3

- 3 , reddish curve )

Rationale: choose same diurnal profile for all vehicles (except HDDV 2B to 8B) for all rural parking areas (which is the profile used for rural local roads) Same as above

2230075370 Heavy Duty Diesel Buses (School & Transit)

- parking

areas urban UR BAN Population (same as
urban local roads)

120 Not

applicable

– inventory
contains monthly

emissions USE URBAN LD values:

Mon

- Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%

Weekly_code (for SMOKE)

=20031 Use same as profile as

urban local roads

. (Rdtype=330)

.

Code = 2012 (see Figure

3

- 3 , yellow curve

Rationale: choose same diurnal profile for all vehicles (except HDDV 2B to 8B) for all rural parking areas (which is the profile used for rural local roads) Same as above76



## 4 References

Eastern Research Group, Mexico National Emissions Inventory, 1999: Final , prepared for
Secratariat of the Environment and Natural Resources and the National Institute of Ecology, Mexico, October 11, 2006. Available at: http://www.epa.gov/ttn/chief/net/mexico/1999_mexico_nei_final_report.pdf

EPA, 2005b. EPA’s National Inventory Model (NMIM), A Consolidated Emissions Modeling System for M OBILE6 and NONROAD , U.S. Environmental Protection Agency, Office of Transportation and Air Quality, Assessment and Standards Division. Ann Arbor, MI 48105, EPA420

- R

- 05

- 024

, December 2005 . Available at http://www.epa.gov/otaq/models/nmim/420r05024.pdf

.
EPA 2006 c. SPECIATE 4.0, Speciation Database Development Document

, Final Report

, U.S. Environmental Protection Agency, Office of Research and Development

, National Risk Management Research Laboratory, Research Triangle Park, NC 27711

, EPA 600

- R

- 06

- 161 , February 2006. Available at http://www.epa.gov/ttn/c hief/software/speciate/speciate4/documentation/speciatedoc_120 6.pdf

. EPA, 2007c. Draft Regulatory Impact Analysis: Control of Emissions from Marine SI and Small SI Engines, Vessels, and Equipment , U.S. Environmental Protection Agency, Office of Transporta tion and Air Quality, Office of Transportation and Air Quality

, Assessment and Standards Division, Ann Arbor, MI 48105, EPA420

- D

- 07

- 004, April 2007. Available at
ht tp://www.epa.gov/otaq/regs/nonroad/marinesi

- equipld/420d07004

- chapters.htm

. Eyth

, A

., L. Ran, R. Partheepan, G. Yarwood, M. Jimenez, S. Rao. (2006) ― New Tools to Generate Spatial Surrogate and Speciation Profile Inputs to SMOKE

. ‖ International Emission Inventory Conference, New Orleans

, LA. Available at http://www.epa.gov/ttn/chief/conference/ei15/session9/eyth.pdf

.
Gustin

, M

. S .; Lind berg, S

. E, and Weisbe rg, P.J. (2008). An update on the natural sources and sinks of atmospheric mercury. Applied Geochemistry , 23(3), 482

- 493.

Pouliot

, G

., H. Simon, P. Bhave, D. Tong, D. Mobley, T. Pace, and T. Pierce . (2010) ― Assessing the Anthropogenic Fugitive Dust Emission Inventory and Temporal Allocation Using an Updated Speciation of Particulate Matter.‖ International Emission Inventory Conference,
San Antonio

, TX. Available at http: //www.epa.gov/ttn/chief/conference/ei19/session9/pouliot.pdf

. Strum, M., D. Mintz, L. Driver, C. Harvey, H. Michaels, R. Mason. (2007) ― Estimating the Monthly Variation in California's Nonroad Equipment Emissions for the 2002 Emissions and Air Quality Modeling Platform

. ‖ International Emission Inventory Conference, Raleigh, NC . Available at http://www.epa.gov/ttn/chief/conference/ei16/session4/strum.pdf

. Yarwood, G., S. Rao, M. Yocke, and G. Whitten, 2005: Updates to the Carbon Bond Chemical Mechanism: CB05. Final Report to the US EPA, RT

- 0400675. Available at http://www.camx.com/publ/pdfs/CB05_Final_Report_120805.pdf

.