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Emissions Inventory Final Rule Technical
Support Document
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EPA-454/B-20-005
July 2011
Emissions Inventory Final Rule Technical Support Document
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Air Quality Assessment Division
Research Triangle Park, NC
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TABLE OF CONTENTS
ACRONYMS IV
LIST OF TABLES VI
LIST OF FIGURES VII
LIST OF APPENDICES VIII
1 INTRODUCTION 1
2 2005 EMISSION INVENTORIES AND APPROACHES 4
2.1 2005 NEI POINT SOURCES (PTIPM AND PTNONIPM) 10
2.1.1 1PM sector (ptipm) 11
2.1.2 Non-IPM sector (ptnonipm) 13
2.2 2005 NONPOINT SOURCES (AFDUST, AG, NONPT) 15
2.2.1 Area fugitive dust sector (afdust) 15
2.2.2 Agricultural ammonia sector (ag) 16
2.2.3 Other nonpoint sources (nonpt) 19
2.3 Fires (avefire) 21
2.4 Biogenic sources (biog) 22
2.5 2005 MOBILE SOURCES (ON_NOADJ, ON_MOVES_RUNPM, ON_MOVES_STARTPM, NONROAD, ALM_NO_C3,
SECA_C3) 22
2.5.1 Onroad gasoline exhaust cold-start mode PM (on moves startpm) 25
2.5.2 Onroad gasoline exhaust running mode PM (onmovesrunpm) 27
2.5.3 Onroad mobile with no adjustments for daily temperature (onnoadj) 28
2.5.4 Nonroad mobile sources: NMlM-based (nonroad) 28
2.5.5 Nonroad mobile sources: locomotive and non-C3 commercial marine (alm_no_c3) 29
2.5.6 Nonroad mobile sources: C3 commercial marine (seca_c3) 31
2.6 Emissions from Canada, Mexico and offshore drilling platforms (othpt, othar, othon) 34
2.7 SMOKE-ready non-anthropogenic inventories for chlorine 36
3 EMISSIONS MODELING SUMMARY 37
3.1 Key emissions modeling settings 38
3.1.1 Spatial configuration 39
3.1.2 Chemical speciation configuration 41
3.1.3 Temporal processing configuration 50
3.2 Emissions modeling ancillary files 52
3.2.1 Spatial allocation data 52
3.2.2 Chemical speciation ancillary files 57
3.2.3 Temporal allocation ancillary files 61
4 DEVELOPMENT OF 2012 AND 2014 BASE-CASE EMISSIONS 69
4.1 Stationary source projections: EGU sector (ptipm) 75
4.2 Stationary source projections: non-EGU sectors (ptnonipm, nonpt, ag, afdust) 75
4.2.1 Livestock emissions growth (ag, afdust) 76
4.2.2 Residential wood combustion growth (nonpt) 77
4.2.3 Gasoline Stage II growth and control (nonpt, ptnonipm) 78
4.2.4 Portable fuel container growth and control (nonpt) 79
4.2.5 Aircraft growth (ptnonipm) 80
4.2.6 Stationary source control programs, consent decrees & settlements, and plant closures (ptnonipm,
nonpt) 81
4.2.7 Oil and gas projections in TX, OK, and non-California WRAP states (nonpt) 86
4.2.8 Future-year VOC Speciation for gasoline-related sources (ptnonipm, nonpt) 87
4.3 Mobile source projections 87
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4.3.1 Onroadmobile (onnoadj, onmovesrunpm, onmoves startpm) 87
4.3.2 Nonroad mobile (nonroad) 89
4.3.3 Locomotives and Class 1 & 2 commercial marine vessels (alm_no_c3) 90
4.3.4 Class 3 commercial marine vessels (seca_c3) 91
4.3.5 Future-year VOC Speciation (on noadj, nonroad) 92
4.4 Canada, Mexico, and Offshore sources (othar, othon, and othpt) 94
5 SOURCE APPORTIONMENT 95
6 REMEDY CASE 95
7 EMISSION SUMMARIES 99
8 REFERENCES 112
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Acronyms
BAFM
Benzene, Acetaldehyde, Formaldehyde and Methanol
BEIS
Biogenic Emissions Inventory System
C3
Category 3 (commercial marine vessels)
CAIR
Clean Air Interstate Rule
CAMD
The EPA's Clean Air Markets Division
CAMx
Comprehensive Air Quality Model with Extensions
CAP
Criteria Air Pollutant
CARB
California Air Resources Board
CEM
Continuous Emissions Monitoring
CHIEF
Clearinghouse for Inventories and Emissions Factors
CI
Chlorine
CMAQ
Community Multiscale Air Quality
CMV
Commercial marine vessel
CO
Carbon monoxide
EGU
Electric generating units
EPA
Environmental Protection Agency
EMFAC
Emission Factor (California's onroad mobile model)
EEZ
Exclusive Economic Zone
FAA
Federal Aviation Administration
FCCS
Fuel Characteristic Classification System
FIPS
Federal Information Processing Standards
HAP
Hazardous Air Pollutant
HC1
Hydrochloric acid
Hg
Mercury
HGNRVA
Natural recycled, volcanic and anthropogenic Hg
HMS
Hazard Mapping System
ICI
Industrial/Commercial/Institutional (boilers and process heaters)
ICR
Information Collection Request
IMO
International Marine Organization
IPM
Integrated Planning Model
ITN
Itinerant
MACT
Maximum Achievable Control Technology
MMS
Minerals Management Service (now known as the Bureau of Energy Management,
Regulation and Enforcement (BOEMRE)
MOBILE
OTAQ's model for estimation of onroad mobile emissions factors
MOVES
Motor Vehicle Emissions Simulator ~ OTAQ's model for estimation of onroad
mobile emissions - replaces the use of the MOBILE model
MSAT2
Mobile Source Air Toxics Rule
NEEDS
National Electric Energy Database System
NEI
National Emission Inventory
NESHAP
National Emission Standards for Hazardous Air Pollutants
nh3
Ammonia
nm
nautical mile
NMIM
National Mobile Inventory Model
NOAA
National Oceanic and Atmospheric Administration
NODA
Notice of Data Availability
NONROAD
OTAQ's model for estimation of nonroad mobile emissions
NOx
Nitrogen oxides
OAQPS
The EPA's Office of Air Quality Planning and Standards
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OTAQ The EPA's Office of Transportation and Air Quality
ORD The EPA's Office of Research and Development
ORL One Record per Line
PF Projection Factor, can account for growth and/or controls
PFC Portable Fuel Container
PM2.5 Particulate matter less than or equal to 2.5 microns
PM10 Particulate matter less than or equal to 10 microns
ppm Parts per million
RIA Regulatory Impact Analysis
RRF Relative Response Factor
RWC Residential Wood Combustion
RPO Regional Planning Organization
SCC Source Classification Code
SMARTFIRE Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation
SMOKE Sparse Matrix Operator Kernel Emissions
SO2 Sulfur dioxide
SOA Secondary Organic Aerosol
SPPD Sector Policies and Programs Division
TAF Terminal Area Forecast
TCEQ Texas Commission on Environmental Quality
TSD Technical support document
VOC Volatile organic compounds
VMT Vehicle miles traveled
WRAP Western Regional Air Partnership
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List of Tables
Table 1-1. List of cases run in support of the Final Transport Rule air quality modeling 1
Table 2-1. Platform sectors used in emissions modeling for the 2005 platform, version 4.2 4
Table 2-2. Summary of significant changes between v4 and v4.2 platforms by sector 7
Table 2-3. 2005 Emissions by Sector: VOC, NOx, CO, S02, NH3, PMio, PM25 9
Table 2-4. SCCs in the afdust platform sector 16
Table 2-5. Livestock SCCs extracted from the 2002 NEI to create the ag sector 17
Table 2-6. Fertilizer SCCs extracted from the 2002 NEI for inclusion in the "ag" sector 19
Table 2-7. Additional TCEQ oil and gas emissions added to the 2005v2 NEI 20
Table 2-8. SCCs provided with Oklahoma oil and gas sector emissions 21
Table 2-9. Changes to Oklahoma oil and gas emissions 21
Table 2-10. Data sources for onroad mobile sources in the 2005v4 and 2005v4.2 platforms1... 23
Table 2-11. SCCs in the 2005 alm_no_c3 inventory compared to the 2002 platform aim sector30
Table 2-12. Adjustment factors to update the 2005 seca_c3 sector emissions for the v4.2
platform 33
Table 2-13. Contiguous U.S. C3 CMV emissions in the 2005v4 and 2005v4.2 platforms 34
Table 2-14. Summary of the othpt, othar, and othon sectors changes from the 2002 platform... 35
Table 3-1. Key emissions modeling steps by sector 38
Table 3-2. Descriptions of the 2005-based platform grids 41
Table 3-3. Model species produced by SMOKE for CB05 with SOA for CMAQ4.7 and CAMx*
42
Table 3-4. Integration status of benzene, acetaldehyde, formaldehyde and methanol (BAFM) for
each platform sector 47
Table 3-5. Source-category specific criteria for integrating nonpt SCCs for categories
comprising 80% of the nonpoint VOC emissions 48
Table 3-6. Temporal settings used for the platform sectors in SMOKE, v4.2 platform 51
Table 3-7. U.S. Surrogates available for the 2005v4.2 platform 53
Table 3-8. Surrogate assignments to new mobile categories in the 2005v4 platform 54
Table 3-9. Canadian Spatial Surrogates for 2005-based platform Canadian Emissions (v4.2
unchanged from v4) 55
Table 3-10. Differences between two profiles used for commercial marine residual oil 59
Table 3-11. Differences between two profiles used for coal combustion 59
Table 3-12: PM2.5 speciation profile updates assignments for the v4 platform 59
Table 3-13. Summary of VOC speciation profile approach by sector for 2005 60
Table 3-14. Summary of spatial surrogates, temporal profiles, and speciation profiles used by
gasoline vehicle types for the onroad parking area-related SCCs 64
Table 3-15. Summary of spatial surrogates, temporal profiles, and speciation profiles used by
diesel vehicle types for the onroad parking area-related SCCs from MOVES2010 66
Table 4-1. Control strategies and growth assumptions for creating the 2012 and 2014 base-case
emissions inventories from the 2005 base case 72
Table 4-2. Growth factors from year 2005 to future years for Animal Operations 77
Table 4-3. Projection Factors for growing year 2005 Residential Wood Combustion Sources.. 78
Table 4-4. Factors used to project 2005 base-case aircraft emissions to future years 80
Table 4-5. Summary of Non-EGU Emission Reductions Applied to the 2005 Inventory due to
Unit and Plant Closures 81
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Table 4-6. Future-year ISIS-based cement industry annual reductions (tons/yr) for the non-EGU
(ptnonipm) sector 84
Table 4-7. State-level non-MACT Boiler Reductions from ICR Data Gathering 84
Table 4-8. National Impact of RICE Controls on 2012 and 2014 Non-EGU Projections 85
Table 4-9. Impact of Fuel Sulfur Controls on 2014 Non-EGU Projections 86
Table 4-10. Oil and Gas NOx and SO2 Emissions for 2005, 2012, and 2014 including additional
reductions due to the RICE NESHAP 86
Table 4-11. Factors applied to year 2005 emissions to project locomotives and Class 1 and Class
2 Commercial Marine Vessel Emissions 90
Table 4-12. NOx, SO2, and PM2.5 Factors to Project Class 3 Commercial Marine Vessel
emissions to 2012 and 2014 92
Table 4-13. Future-year Profiles for Mobile Source Related Sources 93
Table 6-1. Transport Rule Status of States 97
Table 7-1. State-level Total NOx Emissions for each Transport Rule Modeling Case in 48 States
and Washington, D.C 100
Table 7-2. State-level Total SO2 Emissions for each Transport Rule Modeling Case in 48 States
and Washington, D.C 102
Table 7-3. State-level Electric Generating Unit Sector NOx Emissions for each Transport Rule
Modeling Case in 48 States and Washington, D.C 104
Table 7-4. State-level Electric Generating Unit Sector SO2 Emissions for each Transport Rule
Modeling Case in 48 States and Washington, D.C 106
Table 7-5. Group 1 and Group 2 States NOx Total Emissions for each Transport Rule Modeling
Case 108
Table 7-6. Group 1 and Group 2 States SO2 Total Emissions for each Transport Rule Modeling
Case 109
Table 7-7. Group 1 and Group 2 States NOx EGU Sector Emissions for each Transport Rule
Modeling Case 110
Table 7-8. Group 1 and Group 2 States SO2 EGU Sector Emissions for each Transport Rule
Modeling Case Ill
Table 7-9. 26-State Total and Electric Generating Unit Sector Summer NOx Emissions for each
Transport Rule Modeling Case Ill
List of Figures
Figure 2-1. MOVES exhaust temperature adjustment functions 26
Figure 3-1. Air quality modeling domains 40
Figure 3-2. Process of integrating BAFM with VOC for use in VOC Speciation 46
Figure 3-3. Diurnal Profiles based on road type (use local for "start") and whether the road is
urban versus rural 63
Figure 3-4. Diurnal temporal profile for HDDV 2B through 8B at Parking areas 63
Figure 4-1. MOVES exhaust temperature adjustment functions for 2005, 2012, and 2014 89
Figure 4-2. Tier 2 Fraction of Light Duty Vehicles 93
Figure 6-1. States Covered by the Final Transport Rule 96
Figure 6-2. Group 1 and Group 2 States Covered by the Annual PM Component of the Final
Transport Rule 97
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List of Appendices
Appendix A: Revisions to 2005 Inventories from Version 4 to Version 4.2
Appendix B: Ancillary Input Data and Parameter Differences between 2005 and Future-year
Scenarios
Appendix C: SMOKE Input Inventory Data Files used for each Transport Rule Modeling Case
Appendix D: Summary of Future Base Case Transport Rule Non-EGU Control Programs,
Closures and Projections
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1 Introduction
This technical support document (TSD) provides the details of emissions data processing done in support of
the Environmental Protection Agency's (EPA) final rulemaking effort for the Federal Transport Rule
(hereafter referred to as Transport Rule). The Transport Rule air quality modeling results were evaluated
with respect to the 1997 annual and 2006 24-hour National Ambient Air Quality Standards (NAAQS) for
particulate matter less than 2.5 microns (PM2.5), as well as the 1997 8-hour ozone NAAQS.
The emissions and modeling effort for Transport Rule consists of four 'complete' emissions cases: 2005 base
case, 2012 base case, 2014 base case, and 2014 remedy (i.e., "control") case. Table 1-1 provides more
information on these emissions cases. The purpose of 2005 base case is to provide a 2005 case that is
consistent with the methods used in the future-year base cases and remedy case. For regulatory applications,
this case is used with the outputs from the 2012 base case in the relative response factor (RRF) calculations
to identify future nonattainment and maintenance. For more information on the use of RRFs, please see the
Air Quality Modeling Final Rule TSD. The outputs of the 2014 remedy case were compared to the outputs
from the 2014 base case to quantify the benefits of the rule. Not listed in Table 1-1 are source apportionment
runs that were based on the 2012 base case and used to quantify the contributions of emissions in upwind
states to the annual average 24-hour PM2.5 and 8-hour ozone concentrations in other states in 2012. For more
information on the benefits of this rulemaking, please see the Regulatory Impact Assessment for the
Transport Rule NFR.
Table 1-1. List of cases run in support of the Final Transport Rule air quality modeling
Case Name
Internal EPA
Abbreviation
Description
2005 base case
2005cs
2005 case created using average-year fires data and an average-
year temporal allocation approach for Electrical Generating
Units (EGUs); used for computing relative response factors with
2012 and 2014 scenarios.
2005 evaluation
case
2005as
2005 case created for air quality model performance evaluation
that uses actual 2005 and 2005 continuous emissions monitoring
(CEM) data for EGUs.
2012 base case
2012cs
2012 "baseline" scenario, representing the best estimate for the
future year without implementation of EGU remedy controls.
2014 base case
2014cs
2014 "baseline" scenario, representing the best estimate for the
future year without implementation of EGU remedy controls.
2014 Remedy
case
2014cs trl remedy
2014 EGU remedy or "control" scenario to address significant
contribution for the 1997 ozone and annual PM standards, and
2006 daily PM standard.
The air quality modeling platform consists of all the emissions inventories and input ancillary files, along
with the meteorological, initial condition, and boundary condition files needed to run the air quality model.
The platform for this rule uses all Criteria Air Pollutants (CAPs) and the following select Hazardous Air
Pollutants (HAPs): chlorine (CL2), hydrochloric acid or hydrogen chloride (HC1) and benzene, acetaldehyde,
formaldehyde and methanol. The latter four are also denoted 'BAFM'. The Final Transport Rule modeling
platform is called the "CAP-BAFM 2005-Based Platform, Version 4.2" platform (we will use the shortened
name "2005v4.2" in this documentation).
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The data used in the 2005 emissions base case are an updated version of the 2005-based air quality modeling
platform that was used for the Transport Rule Proposal (2005v4). This TSD describes the emissions
inventory and emissions modeling for the 2005v4.2 version of the platform used for the Final Transport Rule
and focuses on the changes made since the 2005v4 platform. The 2005v4 platform is documented at the
emissions modeling clearinghouse website under the section entitled "2005-Based Modeling Platform" and
the subsection entitled "CAP-BAFM 2005-Based Platform Version 4 (do not use for Mercury)". It should be
noted that this 2005v4.2 platform includes all non-mercury (Hg) updates reflected in the 2005v4.1 platform,
which is under the section entitled "CAP-Hg-BAFM 2005-Based Platform Version 4.1 (use for Mercury)".
The 2005v4.2 platform includes both the evolutionary platform changes between 2005v4 and 2005v4.2, as
well as implementation of inventory changes resulting from the incorporation of comments on the Transport
Rule Proposal. For details on the emissions inventory-related comments received on the Transport Rule NPR
and the EPA's responses to those, see the document "Emissions Inventories Response to Comments for the
Transport Rule NFR". This document is in the Transport Rule docket (EPA-HQ-OAR-2009-0491) and is
posted on the emissions modeling clearinghouse website listed above. For simplicity, this TSD refers to the
cumulative changes in both the 2005v4.1 and 2005v4.2 platforms, thus any comparisons made in this
document will be against data in the 2005v4 platform used in the Transport Rule Proposal. For more
information on the emissions inventories used for the Transport Rule Proposal, see the document "Federal
Transport Rule Emissions Inventory for Air Quality Modeling Technical Support Document", available in
the Transport Rule docket and on the emissions modeling clearinghouse website specified above.
The underlying 2005 inventories used are most significantly defined by: 1) for point sources: the 2005
National Emission Inventory (NEI) version 2, and 2) for onroad mobile sources: the Motor Vehicle
Emissions Simulator with database corrections for diesel toxics (MOVES2010). This document describes
the approach and data used to produce the emission inputs to the air quality model used in the 2005v4.2
platform for the 2005 and future-year scenarios.
Emissions preparation for the 2005v4.2 platform supports both the Community Multiscale Air Quality
(CMAQ) model and the Comprehensive Air Quality Model, with extensions (CAMx). Both models support
modeling ozone (O3), and particulate matter (PM), and require hourly and gridded emissions of chemical
species from the following inventory pollutants: carbon monoxide (CO), nitrogen oxides (NOx), volatile
organic compounds (VOC), sulfur dioxide (SO2), ammonia (NH3), particulate matter less than or equal to 10
microns (PM10), and individual component species for particulate matter less than or equal to 2.5 microns
(PM2.5). In addition, the CMAQ Carbon Bond 05 (CB05) chemical mechanism with chlorine chemistry,
which is part of the "base" version of CMAQ, allows explicit treatment of BAFM and includes HAP
emissions of HC1 and CL2. In the platform, BAFM emissions come from either the NEI values for benzene,
formaldehyde, acetaldehyde and methanol (BAFM) or via speciation of NEI VOC into the component
species. For the Transport Rule air quality modeling, only the CAMx model was used.
The creation of emission inputs for the 2005v4.2 platform included:
(1) modifying the emission inventories used for the 2005v4 base case,
(2) updating the emissions modeling ancillary files used by the emissions modeling tools, and
(3) applying the emissions modeling tools.
The primary emissions modeling tool used to create the air quality model-ready emissions was the Sparse
Matrix Operator Kernel Emissions (SMOKE) modeling system. We used SMOKE version 2.6 to create
emissions files for a 36-km national grid, and a 12-km Eastern grid for the 2005 base case (also known as the
"2005cs_05b" case).
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The 2005v4.2 platform includes a base case for 2005 (2005cs) and a traditional model evaluation case
(2005as). The evaluation case is identical to the base case except that it uses 2005-specific fire emissions
and 2005 hour-specific continuous emission monitoring (CEM) data for electric generating units (EGUs).
The 2005 base case in the 2005v4.2 platform includes an "average year" scenario for fires and an illustrative
(rather than year-specific) temporal allocation approach for EGUs to allocate annual 2005 emissions to days
and hours. This approach to temporal allocation of emissions was used for all base and control cases
modeled to provide temporal consistency between the years. It is intended to be a conceivable representation
of temporal allocation of the emissions without tying the approach to a single year. For example, each year
has different days and different locations with large fires, unplanned EGU shutdowns, and periods of high
electricity demand. By using a base-case approach such as the one used on 2005v4.2, the temporal and
spatial aspects of the inventory for these sources are maintained into the future-year modeling. This avoids
potentially spurious year-specific artifacts in the air quality modeling estimates. The 2005v4.2 platform
biogenic emissions data is the same as the 2005v4 platform and was held constant between the 2005 case and
all future-year cases.
The 2005v4.2 platform was developed using the concepts, tools and emissions modeling data from the
EPA's 2005v4 platform, documented by: main document, appendices to the main document and future year.
The future-year inventories, ancillary files, and detailed projection data used for this modeling are available
in the Transport Rule docket at EPA-HQ-OAR-2009-0491 as part of the Final Transport Rulemaking. Since
the data are large, the data files themselves are not posted with online access through the docket. A more
convenient access location is the 2005 platform section of the EPA Emissions Modeling Clearinghouse. The
Final Transport Rule data files are provided as a subheading under this main link.
In the remainder of this document, we provide a description of the approaches taken for the emissions
modeling in support of air quality modeling for the Transport Rule. In Section 2, we review the 2005 base-
case inventory (2005cs_05b) and provide high-level emissions summaries. Section 3 describes the
emissions modeling and the ancillary files used with the emission inventories. In Section 4, we describe the
development of the future year 2012 (2012cs_05b) and 2014 (2014cs_05b) base cases. The 2012 Source
Tagging scenarios are described in Section 5. The 2014 EGU Transport Rule Remedy (Control) case
(2014cs_trlremedy_05b) is discussed in Section 6. In Section 7 we provide data summaries comparing the
modeling cases, followed by the technical references for this document. Appendices A through D provide
additional details about specific technical methods. Some additional emission summaries are also provided
in the Final Transport Rule Regulatory Impact Analysis, Chapter 3.
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2 2005 Emission Inventories and Approaches
This section describes the 2005 emissions data created for input to SMOKE that is part of the 2005v4.2
platform. As with the 2005v4 platform, the primary basis for the 2005 stationary source emission inputs is
the 2005 National Emission Inventory (NEI), version 2, which includes emissions of CO, NOx, VOC, SO2,
NH3, PM10, PM2.5 and hazardous air pollutants (HAPs). The HAPs we used from this inventory are
mercury, chlorine (CL2), hydrogen chloride (HC1), benzene, acetaldehyde, formaldehyde, and methanol. We
began with the same SMOKE-formatted inventory inputs as the 2005v4 platform (the EPA case name:
2005ck_05b) and made the changes described below.
Documentation for the 2005 NEI. and for inventories outside of the United States, which include Canada and
Mexico, we used the latest available base-year inventories as discussed in Section 2.6. The 2005 NEI
includes five sectors: nonpoint (formerly called "stationary area") sources, point sources, nonroad mobile
sources, onroad mobile sources, and fires. Because the 2005v4.2 platform includes only a base case as
opposed to a model evaluation case, the day-specific wildfire and prescribed burning data from the 2005 NEI
was not used; rather an average fire inventory is used for both base and future years. In addition to the NEI
data, biogenic emissions and emissions from the Canadian and Mexican inventories are included in the
2005v4.2 platform. Some inventories are augmented with other emissions data as explained below.
For the purposes of preparing the air quality model-ready emissions, we split the 2005 emissions inventory
into "platform" sectors in the same way as was done in the 2005v4 platform. The significance of an
emissions modeling or "platform" sector is that the data is run through all of the SMOKE programs except
the final merge (Mrggrid) independently from the other sectors. The final merge program then combines the
sector-specific gridded, speciated and hourly emissions together to create CMAQ-ready emission inputs.
These inputs are then converted into emissions that can be used by CAMx, as was needed for the Transport
Rule modeling.
Table 2-1 presents the sectors in the 2005 platform. The sector abbreviations are provided in italics; these
abbreviations are used in the SMOKE modeling scripts and inventory file names, and throughout the
remainder of this document. Table 2-1 does not describe in specific detail the updates in the 2005v4.2
platform from those in the 2005v4 platform. The specific updates to the 2005v4.2 platform as compared to
the 2005v4 platform are highlighted in Table 2-2 and discussed in detail later in this section.
Table 2-1. Platform sectors used in emissions modeling for the 2005 platform, version 4.2
Platform Sector:
short name
2005 NEI
Sector
Description and resolution of the data input to SMOKE
EGU (also called
the IPM sector):
ptipm
Point
2005v2 NEI point source EGUs mapped to the Integrated Planning
Model (IPM) model using the National Electric Energy Database
System (NEEDS) 2006 version 4.10. Day-specific emissions created
for input into SMOKE. Includes updates from Transport Rule
comments and evolutionary improvements from 2005v4.
Non-EGU (also
called the non-
IPM sector):
ptnonipm
Point
All 2005v2 NEI point source records not matched to the ptipm sector.
Includes all aircraft emissions and point source fugitive dust emissions
for which county-specific PM transportable fractions were applied.
Annual resolution. Includes updates from Transport Rule comments
and evolutionary improvements from 2005v4.
Average-fire:
avefire
Not
applicable
Average-year wildfire and prescribed fire emissions, unchanged from
the 2005v4 platform; county and annual resolution.
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Platform Sector:
short name
2005 NEI
Sector
Description and resolution of the data input to SMOKE
Agricultural: ag
Nonpoint
NH3 emissions from NEI nonpoint livestock and fertilizer application,
county and annual resolution. Unchanged from the 2005v4 platform.
Area fugitive dust:
afdust
Nonpoint
PM10 and PM2 5 from fugitive dust sources from the NEI nonpoint
inventory after application of county-specific PM transportable
fractions. Includes building construction, road construction, paved
roads, unpaved roads, agricultural dust), county and annual resolution.
Unchanged from the 2005v4 platform.
Remaining
nonpoint: nonpt
Nonpoint
Primarily 2002 NEI nonpoint sources not otherwise included in other
SMOKE sectors; county and annual resolution. Also includes
updated Residential Wood Combustion emissions, year 2005 non-
California WRAP oil and gas Phase II inventory, year 2005 Texas and
Oklahoma oil and gas inventories, and updates resulting from
Transport Rule comments.
Nonroad:
nonroad
Mobile:
Nonroad
Monthly nonroad emissions from the National Mobile Inventory
Model (NMIM) using NONROAD2005 version nr05c-BondBase,
which is equivalent to NONROAD2008a, since it incorporated Bond
rule revisions to some of the base-case inputs and the Bond rule
controls did not take effect until later.
NMIM was used for all states except California. Monthly emissions
for California created from annual emissions submitted by the
California Air Resources Board (CARB) for the 2005v2 NEI.
locomotive, and
non-C3
commercial
marine:
alm_no_c3
Mobile:
Nonroad
Primarily 2002 NEI non-rail maintenance locomotives, and category 1
and category 2 commercial marine vessel (CMV) emissions sources,
county and annual resolution. Aircraft emissions are included in the
Non-EGU sector (as point sources) and category 3 CMV emissions are
contained in the seca_c3 sector. Includes updates resulting from
Transport Rule comments.
C3 commercial
marine: seca_c3
Mobile :
Nonroad
Annual point source-formatted, year 2005 category 3 (C3) CMV
emissions, developed for the rule called "Control of Emissions from
New Marine Compression-Ignition Engines at or Above 30 Liters per
Cylinder", usually described as the Emissions Control Area (ECA)
study. Utilized final projections from 2002. developed for the C3
ECA Proposal to the International Maritime Organization
(EPA-420-F-10-041, August 2010). Includes updates resulting from
Transport Rule comments.
Onroad
California,
NMIM-based, and
MOVES sources
not subject to
temperature
adjustments:
onnoadj
Mobile:
onroad
Three, monthly, county-level components:
1) California onroad, created using annual emissions for all pollutants,
submitted by CARB for the 2005v2 NEI. NH3 (not submitted by
CARB) from MOVES2010.
2) Onroad gasoline and diesel vehicle emissions from MOVES2010
not subject to temperature adjustments: exhaust CO, NOx, VOC,
NH3, benzene, formaldehyde, acetaldehyde, 1,3-butadiene,
acrolein, naphthalene, brake and tire wear PM, and evaporative
VOC, benzene, and naphthalene.
3) Onroad emissions for Hg from NMIM using MOBILE6.2, other
than for California.
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Platform Sector:
short name
2005 NEI
Sector
Description and resolution of the data input to SMOKE
Onroad cold-start
gasoline exhaust
mode vehicle from
MOVES subject
to temperature
adjustments:
on moves startpm
Mobile:
onroad
Monthly, county-level MOVES2010-based onroad gasoline emissions
subject to temperature adjustments. Limited to exhaust mode only for
PM species and naphthalene. California emissions not included. This
sector is limited to cold start mode emissions that contain different
temperature adjustment curves from running exhaust (see
on_moves_runpm sector).
Onroad running
gasoline exhaust
mode vehicle from
MOVES subject
to temperature
adjustments:
on moves runpm
Mobile:
onroad
Monthly, county-level draft MOVES2010-based onroad gasoline
emissions subject to temperature adjustments. Limited to exhaust
mode only for PM species and naphthalene. California emissions not
included. This sector is limited to running mode emissions that
contain different temperature adjustment curves from cold start
exhaust (see on_moves_startpm sector).
Biogenic: biog
Not
applicable
Hour-specific, grid cell-specific emissions generated from the
BEIS3.14 model, including emissions in Canada and Mexico.
Unchanged from the 2005v4 platform.
Other point
sources not from
the NEI: othpt
Not
applicable
Point sources from Canada's 2006 inventory and Mexico's Phase III
1999 inventory, annual resolution. Also includes annual U.S. offshore
oil 2005v2 NEI point source emissions. Unchanged from the 2005v4
platform.
Other nonpoint
and nonroad not
from the NEI:
othar
Not
applicable
Annual year 2006 Canada (province resolution) and year 1999 Mexico
Phase III (municipio resolution) nonpoint and nonroad mobile
inventories. Unchanged from the 2005v4 platform.
Other onroad
sources not from
the NEI: othon
Not
applicable
Year 2006 Canada (province resolution) and year 1999 Mexico Phase
III (municipio resolution) onroad mobile inventories, annual
resolution. Unchanged from the 2005v4 platform.
The emission inventories in SMOKE input format for the 2005 base case are available at the 2005v4.2
website (see the end of Section 1). The "readme" file provided indicates the particular zipped files associated
with each platform sector.
Before discussing the specific components of the 2005v4.2 emissions platform, we provide in Table 2-2 a
summary of the significant differences between the 2005v4 emissions platform and the 2005v4.2 platform.
The sectors that did not change between 2005v4.2 and 2005v4 are not included in the table and are the
following: average fire, agriculture, area fugitive dust, biogenic sources, and "other" (i.e. non-US) point,
nonpoint, nonroad, and onroad sources.
6
-------
Table 2-2. Summary of significant changes between v4 and v4.2 platforms by sector
Platform Sector
Summary of Significant Inventory Differences from V4 to V4.2
IPM sector: ptipm
1) Added or changed ORIS Boiler IDs to some units with missing or incorrect
values, and for a subset of these, recomputed annual emissions of NOx, SO2 or
both using 2005 CEM data. Only replaced emissions if 2005 CEM data were
confirmed to be for the entire year (since some CEMs only run for the summer
season). A facilitv-level summarv of these changes is provided in Appendix A.
Table A-l of the 2005v4.1 TSD.
2) Moved several stacks and units from the ptnonipm sector, assigning ORIS
facility and boiler codes and matching stack parameters to those provided in
the future-year IPM emissions. These edits ensure future-year EGUs are not
double counted and that base year and future-year stack parameters are similar.
Affected plants are listed in Appendix A, Table A-l.
3) Deleted several units from the inventory that were found to be either double
counts or closed. Affected plants are listed in Appendix A, Table A-2.
Non-IPM sector:
ptnonipm
1) Revised 2005 emissions to remove duplicates, improve estimates from
ethanol plants, and reflect new emissions and controls information
collected from industry and a state through the Boiler MACT
Information Collection Request (ICR).
2) Moved several stacks and units from the ptnonipm sector to the ptipm sector
(Appendix A, Table A-l). This edit prevents double counting of EGU
emissions in the future years.
3) Deleted several units from the inventory that were found to be either double
counts or closed. Affected plants are listed in Appendix A, Table A-2.
4) Revised emissions in several states using improved information obtained
from Transport Rule comments.
Remaining
nonpoint sector:
nonpt
1) Added: year 2005 oil and gas data for Texas and Oklahoma provided by these
states. Replaced previous Oklahoma oil and gas emissions from this sector
(SCC 2310000000). No removals for Texas since the new oil and gas
emissions only cover oil rig emissions that are in the nonroad sector. The
nonroad sector emissions were not removed because they were very small
compared to the newer Texas oil and gas emissions added to this sector and the
possibility of double counting was not able to be confirmed by the EPA.
2) Changed pesticide category to "no-integrate," thereby using VOC speciation
(rather than the HAP emissions) to compute the BAFM emissions.
3) Incorporation of Transport Rule comments including: i) replacing Delaware
fuel combustion, residential wood burning, and open burning, ii) removing
South Carolina residual oil emissions from industrial boilers, iii) replacing
Nebraska industrial fuel combustion emissions. State level changes that
include these impacts are shown in Appendix A, Table A-3.
Nonroad sector:
nonroad
Added PM to 7 California counties which were found to be 0 in the 2005v4
platform. Data used came from an earlier version of the 2005 inventory provided
by CARB, which had the same PM values as the 2005v2 NEI other than in the
missing counties, for which nonzero PM values were provided.
locomotive, and
non-C3
commercial
marine:
aim no c3
Updated diesel fuel commercial marine vessel emissions in Delaware per Transport
Rule comments. The impacts of these changes are shown in Appendix A, Table
A-3.
C3 commercial
marine: seca c3
1) Revised 2005 emissions reflect the final projections from 2002 developed for
the category 3 commercial marine vessel Emissions Control Area (ECA)
7
-------
Platform Sector
Summary of Significant Inventory Differences from V4 to V4.2
Proposal to the International Maritime Organization (EPA-420-F-10-041,
August 2010).
2) Projected Canada as part of the ECA rather than an "outside the ECA" region,
using region-specific growth rates. For example, British Columbia emissions
were projected the same as "North Pacific" growth and control used in
Washington. Therefore the v4.2 seca_c3 inventories contain Canadian
province codes.
3) Updated Delaware emissions per Transport Rule comments.
4) Redefined the spatial extent of state boundaries off-shore from up to 200
nautical miles to under 10 miles based on Mineral Management Service
(MMS) state-federal water boundaries data. This item did not change
emissions, but it drastically reduces areas that are assigned to states.
Onroad
California,
NMIM-based, and
MOVES sources
not subject to
temperature
adjustments:
onnoadj
1) For all states except California: All pollutants and modes (exhaust, tire and
brake wear) from all vehicle types are now from MOVES2010. In the 2005v4
platform, only exhaust mode onroad gasoline vehicles, other than motorcycles,
were included from MOVES in this sector and the rest had been from
MOBILE6.
2) For California: Replaced NMIM-based NH3 with MOVES2010 emissions for
California because California does not provide NH3 in its onroad inventory.
For the 2005v4 platform, we used NH3 from NMIM but since MOVES
generates all criteria pollutants, we now use MOVES.
Onroad cold-start
gasoline exhaust
mode vehicle from
MOVES subject
to temperature
adjustments:
on moves startpm
For the 2005v4.2 platform, this sector uses MOVES2010 based emissions for all
exhaust mode onroad gasoline vehicle types including motorcycles. In the v4
version, motorcycle exhaust mode PM emissions relied on NMIM and were
therefore in the on_noadj sector, and other exhaust mode gasoline vehicle PM
emissions used the draft version of MOVES. As with v4, these PM and
naphthalene cold start mode emissions are subject to grid cell and hourly
temperature adjustments.
Onroad running
gasoline exhaust
mode vehicle from
MOVES subject
to temperature
adjustments:
on moves runpm
Same change as "on moves startpm "
Annual emission summaries for 2005v4.2, with comparisons to 2005v4 CAPs emissions by emissions
modeling sector are provided in Table 2-3. VOC totals are before BAFM speciation (i.e., they are inventory
VOC emissions, and not the sum of VOC emissions after BAFM speciation.
The emission inventories for input to SMOKE for the 2005 base case are available at the 2005v4 website
(see the end of Section 1) under the link "Data Files" (see the "2005emis" directory). The inventories
"readme" file indicates the particular zipped files associated with each platform sector.
8
-------
Table 2-3. 2005 Emissions by Sector: VOC, NOx, CO, S02, NH3, PMio, PM2.5
Sector short
name
2005
VOC ftons/yrl
2005
NOX ftons/yrl
2005
CO ftons/yrl
2005
S02 ftons/yrl
2005
NH3 ftons/yrl
2005
PM10 ftons/yrl
2005
PM2 5 ftons/yrl
V4.2
V4
V4.2
V4
V4.2
V4
V4.2
V4
V4.2
V4
V4.2
V4
V4.2
V4
afdust
8,858,992
same
1,030,391
same
ag
3,251,990
same
aim no c3
67,690
same
1,922,723
1,924,925
270,007
same
153,068
154,016
773
same
59,342
59,366
56,666
56,687
seca_c3 (US
component)
4,580
22,367
130,164
642,088
11,862
53,746
97.485
417,312
11,628
53,580
10,673
49,294
seca c3 (non-
US
component)
62,132
18,241
1,801,699
526,760
146,027
42,959
1,085,894
319,200
146,312
43,014
134,604
39,574
nonpt
7,530,578
7,474,512
1,696,902
1,683,490
7,410,946
7,376,314
1,216,362
1,252,645
133,962
134,080
1,349,639
1,349,685
1,079,906
1,076,954
nonroad
2,691,844
same
2,115,408
same
19,502,718
same
197,341
same
1,972
same
211,807
209,100
201,138
198,734
on noadi
3,949,362
3,123,642
9,142,274
7,203,876
43,356,130
41,647,066
177,977
144,216
156,528
295,203
308,497
170,554
236,927
115,991
on_moves
runpm
54,071
46,430
49,789
42,753
on_moves_
startpm
22,729
23,607
20,929
21,738
ptipm
41,089
40,950
3,729,161
3,728,190
603,788
601,564
10,380,883
10,381,411
21,995
21,684
602,236
615,095
496,877
508,903
ptnonipm
1,309,895
1,310,085
2,226,250
2,247,228
3,214,833
3,222,221
2,082,159
2,117,649
158,524
159,003
646,373
653,957
433,381
442,656
avefire
1,958,992
same
189,428
same
8,554,551
same
49,094
same
36,777
same
796,229
same
684,035
same
Canada othar1
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
Canada othpt
447,313
same
857,977
same
1,270,438
same
1,664,040
same
21,268
same
117,669
same
68,689
same
Mexico othar
586,842
same
249,045
same
644,733
same
101,047
same
486,484
same
143,816
same
92,861
same
Mexico othon
183,429
same
147,419
same
1,455,121
same
8,270
same
2,547
same
6,955
same
6,372
same
Mexico othpt
113,044
same
258,510
same
88,957
same
980,359
same
0
same
125,385
same
88,132
same
offshore othpt
51,240
same
82,581
same
89,812
same
1,961
same
0
same
839
same
837
same
1. Canada provided 2006 fires, but we did not use them in the 2005 platform (for neither v4.2 nor v4)
9
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The remainder of Section 2 provides details about the data contained in each of the 2005
platform sectors. Different levels of detail are provided for different sectors depending on the
availability of reference information for the data, the degree of changes or manipulation of the
data needed for preparing it for input to SMOKE, and whether the 2005v4.2 platform emissions
changed appreciably since the previously-documented 2005v4 platform.
2.1 2005 NEI point sources (ptipm and ptnonipm)
Point sources are sources of emissions for which specific geographic coordinates (e.g.,
latitude/longitude) are specified, as in the case of an individual facility. A facility may have
multiple emission points, which may be characterized as units such as boilers, reactors, spray
booths, kilns, etc. A unit may have multiple processes (e.g., a boiler that sometimes burns
residual oil and sometimes burns natural gas). Note that this section describes only NEI point
sources within the contiguous United States. The offshore oil platform (othpt sector) and
category 3 CMV emissions (seca_c3 sector) are also point source formatted inventories that are
discussed in Section 2.6 .
After removing offshore oil platforms (othpt sector), we created two platform sectors from the
remaining 2005v2 NEI point sources for input into SMOKE: the EGU sector - also called the
Integrated Planning Model (IPM) sector (i.e., ptipm) and the non-EGU sector - also called the
non-IPM sector (i.e., ptnonipm). This split facilitates the use of different SMOKE temporal
processing and future-year projection techniques for each of these sectors. The inventory
pollutants processed through SMOKE for both ptipm and ptnonipm sectors were: CO, NOx,
VOC, SO2, NH3, PM10, and PM2.5 and the following HAPs: HCl (pollutant code = 7647010),
and CL2 (code = 7782505). We did not utilize BAFM from these sectors as we chose to speciate
VOC without any use (i.e., integration) of VOC HAP pollutants from the inventory (integration
is discussed in detail in Section 3.1.2.1).
The ptnonipm emissions were provided to SMOKE as annual emissions. The ptipm emissions
for the base case were input to SMOKE as daily emissions.
Documentation for the development of the 2005 point source NEI v2. A summary of this
documentation describes these data as follows:
1. Electric generating unit (EGU) emissions are obtained from emissions/heat input from
the EPA's Acid Rain Program for Continuous Emissions Monitoring System (CEMS)
reporting. The following approach applied to units in the 2002 NEI that matched to 2005
CEMS units. For pollutants covered by the CEMS, the 2005 CEMS data were used. For
CEMS units with pollutants not covered by CEMS (e.g., VOC, PM2.5, HCl) unit-specific
ratios of 2005 to 2002 heat input were applied to 2002v3 NEI emissions to obtain 2005
estimates.
2. Non-EGU stationary source development for the 2005 NEI focused on improving the
following sectors:
10
-------
a. HAP data received from States and industry to support the MACT program,
including the recent Risk and Technology Review rulemaking
b. 2005 State, local, and tribal data submitted to the EPA under the Consolidated
Emissions Reporting Rule (CERR)
c. HAP data from Toxic Release Inventory (TRI) for missing facilities and
pollutants
d. Off-shore platform data from Mineral Management Services (MMS)
The changes made to the 2005v2 NEI point inventory prior to modeling 2005v4 are as follows:
The tribal data, which do not use state/county Federal Information Processing Standards
(FIPS) codes in the NEI, but rather use the tribal code, were assigned a state/county FIPS
code of 88XXX, where XXX is the 3-digit tribal code in the NEI. We made this change
because SMOKE requires the 5-digit state/county FIPS code.
Stack parameters were defaulted for some point sources when modeling in SMOKE.
SMOKE uses an ancillary file, called the PSTK file that provides default stack
parameters by SCC code to either gap fill stack parameters if they are missing in the NEI,
or to correct stack parameters if they are outside the ranges specified in SMOKE as
acceptable values. The SMOKE PSTK file is contained in the ancillary file directory of
the 2005v4 website (see the end of Section 1).
We applied a transport fraction to all SCCs that we identified as PM fugitive dust, to
prevent the overestimation of fugitive dust impacts in the grid modeling as described in
Section 2.2.1.
There are several changes made to the ptipm and ptnonipm sectors for the 2005v4.2 platform that
were briefly discussed in Table 2-2. One of these changes involved reassigning stacks, units and
facilities from the ptnonipm sector to the ptipm sector because it was determined that these
sources were reflected in the future-year IPM data. By moving these sources from ptnonipm to
ptipm, we prevent their being double counted in future-year emissions processing. These
changes and other updates in the ptipm and ptnonipm sectors for 2005v4.2 are discussed in the
following sections.
2.1.1 IPM sector (ptipm)
The ptipm sector contains emissions from EGUs in the 2005v2 NEI point inventory that we were
able match to the units found in the NEEDS database. While we originally used version 3.02 of
NEEDS to split out the ptipm sector for v4 of the platform, there were no changes to the
mapping when we moved to NEEDs version 4.10. The IPM model provides future-year
emission inventories for the universe of EGUs contained in the NEEDS database. As described
below, this matching was done (1) to provide consistency between the 2005 EGU sources and
future-year EGU emissions for sources which are forecasted by IPM and (2) to avoid double
counting in projecting point source emissions.
The 2005v4 platform document provides additional details on how the 2005 NEI point source
inventory was split into the ptipm and ptnonipm sectors.
11
-------
Creation of temporally resolved emissions for the ptipm sector
Another reason we separated the ptipm sources from the other sources was due to the difference
in the temporal resolution of the data input to SMOKE. For the base-case 2005 run, the ptipm
sector uses daily emissions input into SMOKE. The daily emissions are computed from the
annual emissions. First, we allocate annual emissions to each month (this process occurs outside
of SMOKE). To do this, we created state-specific, three-year averages of 2004-2006 CEM data.
These average annual-to-month factors were assigned to sources by state. To allocate the
monthly emissions to each day, we used the 2005 CEM data to compute state-specific month-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.
The development of these diurnal ptipm-specific profiles, which are considered ancillary data for
SMOKE, is described in Section 3.2.3.
Ptipm updates from the 2005v4 platform used in creating the 2005v4.2 platform
We started with the same ptipm/ptnonipm split as was used for the v4 platform; however,
we changed some emissions values based on updates we made to some ORIS identifiers
in the ptipm file. For a subset of the units for which we added or changed ORIS
identifiers, we recomputed annual emissions for SO2, NOx or both using the CEMS data
available at the EPA's data and maps website.2 Facility-level impacts of these changes
are provided in Appendix A, Table A-l of the 2005v4.1 TSD.
Several sources in the 2005v4 ptnonipm inventory were found to be EGU emissions that
were either found in the future-year IPM inventories or determined to have closed
between 2005 and the future years. If these emissions were retained in the ptnonipm
sector, then future-year projections would either double-count these EGU emissions, or
incorrectly not close these units; in both cases, future-year EGU emissions were inflated
in the 2005v4 platform. Therefore, we reassigned these known EGU emissions to the
ptipm sector. In situations where emissions were moved from ptnonipm to ptipm and
these sources were not closed in the future (they were in the future-year IPM inventories),
facility, and unit identifier codes were changed to match IPM codes, and more
importantly, ORIS facility and boiler identifier codes were also changed to match IPM
codes and hence, the CEMS data base. Facilities and units that were moved from the
ptnonipm to ptipm sector for 2005v4.2 are provided in Appendix A, Table A-l.
Several units and facilities in the 2005v4 ptipm inventory were found to be either double
counts or were determined to have closed prior to 2005. In most cases, these deletions
were for closures at facilities reported in the 2002 NEI that were not updated in the 2005
NEI as closed. These changes are detailed in Appendix A, Table A-2.
2 http://camddataandmaps.epa.gov/gdm/index. cfm?fuseaction=emissions.wizard
12
-------
2.1.2 Non-IPM sector (ptnonipm)
The non-IPM (ptnonipm) sector contains all 2005v2 NEI point sources that we did not include in
the IPM (ptipm) sector.3 The ptnonipm sector contains fugitive dust PM emissions from
vehicular traffic on paved or unpaved roads at industrial facilities or coal handling at coal
mines.4 Prior to input to SMOKE, we reduced the fugitive dust PM emissions to estimate the
emissions that remain aloft by applying county-specific fugitive dust transportable fraction
factors. This is discussed further in Section 2.2.1.
For some geographic areas, some of the sources in the ptnonipm sector belong to source
categories that are contained in other sectors. This occurs in the inventory when states, tribes or
local programs report certain inventory emissions as point sources because they have specific
geographic coordinates for these sources. They may use point source SCCs (8-digit) or non-
point, onroad or nonroad (10-digit) SCCs. In the 2005 NEI, examples of these types of sources
include: aircraft emissions in all states, waste disposal emissions in several states, firefighting
training in New Mexico, several industrial processes and solvent utilization sources in North
Carolina and Tennessee, livestock (i.e., animal husbandry) in primarily Kansas and Minnesota,
and petroleum product working losses.
The modifications between the published 2005v2 NEI and the 2005v4 ptnonipm inventory we
used for modeling are summarized here:
Ptnonipm changes from the original 2005v2 inventory for the v4 platform development
Removed duplicate annual records. We did not delete some apparent duplicates because
they were in fact covering different parts of the year (i.e., the emissions in the inventory
file were sub-annual).
Removed a source with a state/county FIPS code of 30777; the "777" county FIPS
represents portable facilities that move across counties, but, is not currently a valid
state/county FIPS code in the SMOKE ancillary file "COSTCY". This Montana FIPS
code was located in northern Wyoming and contained very small emissions.
Dropped sources with coordinates located well into the oceans or lakes.
Fixed the coordinates for several larger sources that had a state/county FIPS code
mismatch with their inventory coordinates greater than 10 km and emissions greater than
10 tons per year of either NOx, VOC, SO2, or 5 tons/yr of PM2.5. These corrections were
limited to a small number of plants in Arizona, Indiana, Kentucky, Ohio, and Virginia.
In addition to the ptnonipm inventory updates implemented in the 2005v4 platform, we applied
the following updates in the 2005v4.2 ptnonipm sector:
3 Except for the offshore oil and day-specific point source fire emissions data which are included in separate sectors,
as discussed in sections 2.6 and 2.3.1, respectively.
4Point 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.
13
-------
Ptnonipm updates from 2005v4 platform used in creating the 2005v4.2 platform
As discussed in Section 2.1.1, several sources in the 2005v4 ptnonipm inventory were
found to be EGU emissions that were either found in the future-year IPM inventories or
determined to have closed between 2005 and the future years. Therefore, we reassigned
these known EGU emissions to the ptipm sector; these are provided in Appendix A,
Table A-1.
Several units and facilities in the 2005v4 ptnonipm inventory were found to be either
double counts or were determined to have closed prior to 2005. In most cases, these
deletions were for closures at facilities reported in the 2002 NEI that were not updated in
the 2005 NEI as closed.
Evolutionary inventory updates and updates from the Transport Rule comments were
applied to several facilities. A list of all facilities with updated or deleted ptnonipm
emissions between 2005v4 and 2005v4.2 is provided in Appendix A. One of the most
significant evolutionary updates was incorporating the PM condensable portion of
emissions to the Clarion Steel Plant in Allegheny County Pennsylvania
(PLANTID=4200300032), where by-product Coke Manufacturing, quenching PM
condensable emissions were augmented, increasing total plant-level PM2.5 emissions
from under 500 annual tons in the 2005v4 platform to approximately 2,000 annual tons in
the 2005v4.2 platform.
We added the North Dakota ADM facility (FIPS code = 38067) that was in the 2005vl
NEI but was missing from the 2005v2 NEI and was not determined to have shut down.
The 2002-based emissions were added to the ptnonipm file, since 2005 data were not
available.
We added an inventory of 2005 ethanol plants using plant names and data provided by
the EPA's Office of Transportation and Air Quality for use in a previous modeling effort
(Renewable Fuel Standards 2), which included these with the 2005vl inventory. The list
below includes only the ethanol plants that were used in the previous modeling effort but
were missing from the 2005v2 NEI.
CO
NOX
PM10
PM2.5
S02
VOC
State/County FIPS
(tons/yr
(tons/yr
(tons/yr
(tons/yr
(tons/yr
(tons/yr
code
Plant Name
)
)
)
)
)
)
06065
Golden Cheese Company of CA
10
30
12
1
39
14
Wind Gap Farms (Anheuser/Miller
13205
Brewery)
1
2
1
0
3
1
19033
Golden Grain Energy LLC
147
424
170
15
540
201
19035
Little Sioux Corn Processors
184
534
213
19
679
252
19055
Permeate Refining
3
9
4
0
12
4
19057
Big River Resources, LLC
109
315
126
13
401
149
19083
Hawkeye Renewables, LLC
115
333
133
14
424
158
19093
Quad-County Corn Processors
57
164
65
7
208
77
19167
Siouxland Energy & Livestock Coop (SELC)
209
606
243
26
772
287
21047
Commonwealth Agri-Energy, LLC
46
133
53
5
170
63
31047
Cornhusker Energy Lexington (CEL)
25
73
29
3
93
34
31145
SW Energy, LLC.
42
121
49
5
154
57
35041
Abengoa Bioenergy Corporation
10
30
12
1
39
14
46005
Heartland Grain Fuels, LP
0
1
0
0
1
0
14
-------
46109
North Country Ethanol (NCE)
63
182
73
7
231
86
19109
Global Ethanol
29
85
34
3
108
40
20055
Reeve Agri-Energy
52
152
61
6
193
72
TOTAL TONS
1,104
3,195
1,278
127
4,066
1,510
2.2 2005 nonpoint sources (afdust, ag, nonpt)
The 2005v2 NEI typically used the same values for nonpoint emissions as were found in the
2002 NEI. This modeling platform took a similar approach, with a couple of notable exceptions
discussed in Section 2.2.3. We created several sectors from the 2002 nonpoint NEI. We
removed the nonpoint tribal-submitted emissions to prevent possible double counting with the
county-level emissions. Because the tribal nonpoint emissions are small, we do not anticipate
these omissions having an impact on the results at the 36-km and 12-km scales used for this
modeling. The documentation for the nonpoint sector of the 2005 NEI.
In the rest of this section, we describe in more detail each of the platform sectors into which we
separated the 2005 nonpoint NEI, and the changes we made to these data. We will refer to the
2002 platform documentation for sectors that did not change.
2.2.1 Area fugitive dust sector (afdust)
The emissions for this sector are unchanged from the 2005v4 platform, and the documentation is
repeated here for convenience. However, we changed the temporal allocation of the emissions to
account for day-of-week variation. In particular, we used updated dust profiles that are
consistent with the activity related to non-dust profiles for similar processes. The processes and
profiles updated are provided in Pouliot, et. al., 2010. In previous modeling, all days within the
same month had the same emissions.
The area-source fugitive dust (afdust) sector contains PMio and PM2.5 emission estimates for
2002 NEI nonpoint SCCs identified by the EPA staff as dust sources. This sector is separated
from other nonpoint sectors to make it easier to apply a "transport fraction," which reduces
emissions to reflect observed diminished transport from these sources at the scale of our
modeling. Application of the transport fraction prevents the overestimation of fugitive dust
impacts in the grid modeling as compared to ambient samples. Categories included in this sector
are paved roads, unpaved roads and airstrips, construction (residential, industrial, road and total),
agriculture production and all of the mining 10-digit SCCs beginning with the digits "2325." It
does not include fugitive dust from grain elevators because these are elevated point sources.
We created the afdust sector from the 2002 NEI based on SCCs and pollutant codes (i.e., PM10
and PM2.5) that are considered "fugitive". A complete list of all possible fugitive dust SCCs
(including both 8-digit point source SCCs and 10-digit nonpoint SCCs). However, not all of the
SCCs in this file are present in the 2002 NEI. The SCCs included in the 2002 NEI that comprise
the 2005 (and 2002) platform afdust sector (which are a subset of the SCCs in the web link) are
provided in Table 2-4.
15
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Table 2-4. SCCs in the afdust platform sector
see
SCC Description
2275085000
Mobile Sources;Aircraft;Unpaved Airstrips;Total
2294000000
Mobile Sources;Paved Roads;All Paved Roads;Total: Fugitives
2296000000
Mobile Sources;Unpaved Roads;All Unpaved Roads;Total: Fugitives
2296005000
Mobile Sources;Unpaved Roads;Public Unpaved Roads;Total: Fugitives
2296010000
Mobile Sources;Unpaved Roads;Industrial Unpaved Roads;Total: Fugitives
2311000000
Industrial Processes;Construction: SIC 15 - 17;A11 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;A11 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. 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. Here is an electronic
version of the county-level transport fractions.
The 2002 platform documentation describes an error in which the transportable fraction
application for PM2.5 was not applied. This error was fixed for the 2005v4.2 platform, and 2005
PM2.5 afdust emissions are therefore correctly about 43% less than those in the 2002 platform.
2.2.2 Agricultural ammonia sector (ag)
This sector is unchanged from the 2005v4 platform; the documentation is repeated here for
completeness.
The agricultural NH3 "ag" sector is comprised of livestock and agricultural fertilizer application
emissions from the nonpoint sector of the 2002 NEI. This sector is unchanged in the 2005
platform. The rest of this section documentation is therefore very similar to that in the 2002
documentation.
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In building this sector we extracted livestock and fertilizer emissions based on the SCC. The
livestock SCCs are listed in Table 2-5, and the fertilizer SCCs are listed in Table 2-6.
Table 2-5. Livestock SCCs extracted from the 2002 NEI to create the ag sector
SCC
SCC Description*
2805000000
Agriculture - Livestock;Total
2805001100
Beef cattle - finishing operations on feedlots (drylots);Confinement
2805001200
Beef cattle - finishing operations on feedlots (drylots);Manure handling and storage
2805001300
Beef cattle - finishing operations on feedlots (drylots);Land application of manure
2805002000
Beef cattle production composite;Not Elsewhere Classified
2805003100
Beef cattle - finishing operations on pasture/range;Confinement
2805007100
Poultry production - layers with dry manure management systems;Confinement
2805007300
Poultry production - layers with dry manure management systems;Land application of manure
2805008100
Poultry production - layers with wet manure management systems;Confinement
2805008200
Poultry production - layers with wet manure management systems;Manure handling and storage
2805008300
Poultry production - layers with wet manure management systems;Land application of manure
2805009100
Poultry production - broilers;Confinement
2805009200
Poultry production - broilers ;Manure handling and storage
2805009300
Poultry production - broilers;Land application of manure
2805010100
Poultry production - turkeys;Confinement
2805010200
Poultry production - turkeys;Manure handling and storage
2805010300
Poultry production - turkeys;Land application of manure
2805018000
Dairy cattle composite;Not Elsewhere Classified
2805019100
Dairy cattle - flush dairy;Confinement
2805019200
Dairy cattle - flush dairy;Manure handling and storage
2805019300
Dairy cattle - flush dairy;Land application of manure
2805020001
Cattle and Calves Waste Emissions;Milk Cows
2805020002
Cattle and Calves Waste Emissions;Beef Cows
2805020003
Cattle and Calves Waste Emissions;Heifers and Heifer Calves
2805020004
Cattle and Calves Waste Emissions;Steers, Steer Calves, Bulls, and Bull Calves
2805021100
Dairy cattle - scrape dairy;Confinement
2805021200
Dairy cattle - scrape dairy;Manure handling and storage
2805021300
Dairy cattle - scrape dairy;Land application of manure
2805022100
Dairy cattle - deep pit dairy;Confmement
2805022200
Dairy cattle - deep pit dairy;Manure handling and storage
2805022300
Dairy cattle - deep pit dairy;Land application of manure
2805023100
Dairy cattle - drylot/pasture dairy;Confinement
2805023200
Dairy cattle - drylot/pasture dairy;Manure handling and storage
2805023300
Dairy cattle - drylot/pasture dairy;Land application of manure
2805025000
Swine production composite;Not Elsewhere Classified (see also 28-05-039, -047, -053)
2805030000
Poultry Waste Emissions;Not Elsewhere Classified (see also 28-05-007, -008, -009)
2805030001
Poultry Waste Emissions;Pullet Chicks and Pullets less than 13 weeks old
2805030002
Poultry Waste Emissions;Pullets 13 weeks old and older but less than 20 weeks old
2805030003
Poultry Waste Emissions;Layers
2805030004
Poultry Waste Emissions;Broilers
2805030007
Poultry Waste Emissions;Ducks
2805030008
Poultry Waste Emissions;Geese
2805030009
Poultry Waste Emissions;Turkeys
2805035000
Horses and Ponies Waste Emissions;Not Elsewhere Classified
2805039100
Swine production - operations with lagoons (unspecified animal age);Confinement
2805039200
Swine production - operations with lagoons (unspecified animal age);Manure handling and storage
2805039300
Swine production - operations with lagoons (unspecified animal age);Land application of manure
17
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SCC
SCC Description*
2805040000
Sheep and Lambs Waste Emissions;Total
2805045000
Goats Waste Emissions;Not Elsewhere Classified
2805045002
Goats Waste Emissions;Angora Goats
2805045003
Goats Waste Emissions;Milk Goats
2805047100
Swine production - deep-pit house operations (unspecified animal age) Confinement
2805047300
Swine production - deep-pit house operations (unspecified animal age);Land application of manure
2805053100
Swine production - outdoor operations (unspecified animal age) Confinement
* All SCC Descriptions begin "Miscellaneous Area Sources;Agriculture Production - Livestock"
The "ag" sector includes all of the NH3 emissions from fertilizer from the NEI. However, the
"ag" sector does not include all of the livestock ammonia emissions, as there are also significant
NH3 emissions from livestock in the point source inventory that we retained from the 2002 NEI.
Note that in these cases, emissions were not also in the nonpoint inventory for counties for which
they were in the point source inventory; therefore no double counting occurred. Most of the
point source livestock NH3 emissions were reported by the states of Kansas and Minnesota. For
these two states, farms with animal operations were provided as point sources using the
following SCCs5:
30202001: Industrial Processes; Food and Agriculture; Beef Cattle Feedlots; Feedlots
General
30202101: Industrial Processes; Food and Agriculture; Eggs and Poultry Production;
Manure Handling: Dry
30203099: Industrial Processes; Food and Agriculture; Dairy Products; Other Not
Classified
There are also livestock NH3 emissions in the point source inventory with SCCs of 39999999
(Industrial Processes; Miscellaneous Manufacturing Industries; Miscellaneous Industrial
Processes; Other Not Classified) and 30288801 (Industrial Processes; Food and Agriculture;
Fugitive Emissions; Specify in Comments Field). We identified these sources as livestock NH3
point sources based on their facility name. The reason why we needed to identify livestock NH3
in the ptnonipm sector was to properly implement the emission projection techniques for
livestock sources, which cover all livestock sources, not only those in the ag sector, but also
those in the ptnonipm sector.
5 These point source emissions are also identified by the segment ID, which is one of the following: "SWINE"
"CATTLE", "DAIRY", or "PLTRY".
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Table 2-6. Fertilizer SCCs extracted from the 2002 NEI for inclusion in the "ag" sector
2002 SCC
2002 SCC Description*
2801700001
Anhydrous Ammonia
2801700002
Aqueous Ammonia
2801700003
Nitrogen Solutions
2801700004
Urea
2801700005
Ammonium Nitrate
2801700006
Ammonium Sulfate
2801700007
Ammonium Thiosulfate
2801700010
N-P-K (multi-grade nutrient fertilizers)
2801700011
Calcium Ammonium Nitrate
2801700012
Potassium Nitrate
2801700013
Diammonium Phosphate
2801700014
Monoammonium Phosphate
2801700015
Liquid Ammonium Polyphosphate
2801700099
Miscellaneous Fertilizers
* All descriptions include "Miscellaneous Area Sources; Agriculture
Production - Crops; Fertilizer Application" as the beginning of the
description.
2.2.3 Other nonpoint sources (nonpt)
Nonpoint sources that were not subdivided into the afdust, ag, or avefire sectors were assigned to
the "nonpt" sector.
The 2002 platform documentation describes the creation of the 2002 nonpt sector in great detail,
but the rest of this section will simply document what has changed for the 2005v4.2 platform.
Below is a list of changes made from the 2002 platform both for the v4 platform and for the v4.2
platform. Details on the changes to 2002 for the version 4 platform are in the v4 documentation.
Updates to the nonpt sector from 2002 platform made for creation of the nonpt sector of
the 2005v4 platform
The 2005 platform replaces 2002v3 NEI non-California Western Regional Air
Partnership (WRAP) oil and gas emissions (SCCs beginning with "23100") with WRAP
year 2005 Phase II oil and gas emissions.
Residential wood combustion (RWC) emissions were replaced with data for Oregon and
New York. This update is consistent with the 2005v2 NEI.
RWC VOC emissions were recalculated for all states except California to reflect an
updated emissions factor for VOC from RWC sources. This update is consistent with the
2005v2 NEI.
We utilized benzene, formaldehyde, acetaldehyde and methanol (BAFM) emissions from
sources that met the HAP-CAP integration criteria discussed in Section 3.1.2.1 (i.e., the
"integrate" sources). We removed BAFM from sources that did not meet the integration
criteria (i.e., the "no-integrate" sources) so that BAFM would not be double counted with
the BAFM generated via speciation of VOC.
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Updates from 2005v4 platform used in creating the 2005v4.2 platform
We changed the integration status for pesticide emissions from using the "integrate" case
to using the "no-integrate" case. The main reason is that there were significant benzene
emissions from this category in the NEI that was considered incorrect. The NEI benzene
came from solvent utilization data (Fredonia) for "other markets" for the year 1998. Since
benzene no longer allowed in pesticides, we chose to eliminate the use of these HAP data
and use a VOC speciation profile that did not include benzene emissions to be more
consistent with the changed regulations.
We replaced Delaware fuel combustion (all industrial, commercial, and residential),
residential wood combustion, and open burning with revised state estimates for NOX,
S02, and PM. The impact of this inventory change is shown in Appendix A, Table A-3.
We removed South Carolina residual oil emissions from industrial boilers. We
determined that these nonpoint emissions were a double count from those in the point
inventory. Removing these emissions is consistent with the preliminary 2008 NEI data
submittal. The impact of this inventory change is shown in Appendix A, Table A-3.
We replaced Nebraska industrial fuel combustion emissions with 2005 Central Regional
Air Planning Association (CENRAP) dataset, version G. The impact of this inventory
change is shown in Appendix A, Table A-3.
We added oil and gas emissions for Texas and replaced oil and gas emissions with
updated 2005 data from Oklahoma.
TCEQ Oil and Gas Emissions
The Texas Commission on Environmental Quality (TCEQ) provided 2005 oil and gas emissions
which we added to the nonpt sector. The emissions were for a single SCC: 2310000220
Industrial Processes; Oil and Gas Exploration and Production; All Processes; Drill Rigs. The
TCEQ indicated that these should replace emissions in the nonroad inventory from the
NONROAD model (drill rigs: SCC=2270010010). Because the nonroad emissions are
significantly less than the updated nonpt emissions, we did not remove the nonroad emissions.
Both the TCEQ and related nonroad emissions from the 2005 NEI are summarized in Table 2-7.
Table 2-7. Additional TCEQ oil and gas emissions added to the 2005v2 NEI
Pollutant
TCEQ Emissions 2005,
added to nonpt
(tons/yr)
NEI 2005 Emissions (nonroad
inventory), not subtracted
(tons/yr)
CO
15,878
1,396
nh3
3
NOx
42,854
4,704
PMio
3,036
275
PM2.5
2,945
267
S02
5,977
573
VOC
4,337
340
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Oklahoma Oil and Gas Emissions
The state of Oklahoma provided and emissions replacement for their 2005 oil and gas sector
emissions. These data added emissions for the SCCs shown in Table 2-8.
Table 2-8. SCCs provided with Oklahoma oil and gas sector emissions
SCC
SCC Description
31000103
Crude Oil Production;Wells: Rod Pumps*
31000122
Crude Oil Production:Drilling and Well Completion*
31000203
Natural Gas Production;Compressors*
31000215
Natural Gas Production;Flares Combusting Gases >1000 BTU/scf
31000222
Natural Gas Production;Drilling and Well Completion*
31000227
Gas Production;Glycol Dehydrator Reboiler Still Stack*
31000228
Natural Gas Production;Glycol Dehydrator Reboiler Burner*
31000403
Industrial Processes;Oil and Gas Production;Process Heaters;Crude Oil
31000404
Industrial Processes;Oil and Gas Production;Process Heaters;Natural Gas
31088811
Industrial Processes;Oil and Gas Production;Fugitive Emissions;Fugitive Emissions
* These SCC descriptions start with the preface "Industrial Processes;Oil and Gas Production"
In addition, this update removed emissions for SCC 2310000000, which is "Industrial
Processes;Oil and Gas Production: SIC 13;A11 Processes;Total: All Processes."
The resultant Oklahoma emissions are shown below in Table 2-9. Note that Oklahoma
instructed that PMio emissions were size PM2.5, and therefore no coarse PM (PMC) was
generated and PM10 is the same as PM2.5
Table 2-9. Changes to Oklahoma oil and gas emissions
2005 Oklahoma Oil and gas
2005 Oklahoma Oil and
emissions 2005, removed
gas emissions, added to
Pollutant
from nonpt (tons/yr)
nonpt (tons/yr)
CO
11,251
32,821
voc
104,193
155,908
NOx
66,480
39,668
S02
0
1,014
PM10 = PM2.5
0
1,918
2.3 Fires (avefire)
The purpose of the avefire sector is to represent emissions for a typical year's fires for use in
projection year inventories, since the location and degree of future-year fires are not known.
This approach keeps the fires information constant between the 2005 base case and future-year
cases to eliminate large and uncertain differences between those cases that would be caused by
changing the fires. Using an average of multiple years of data reduces the possibility that a
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single-year's high or low fire activity would unduly affect future-year model-predicted
concentrations.
The avefire sector contains wildfire and prescribed burning emissions. It excludes agricultural
burning and other open burning sources, which are included in the nonpt sector. Generally, their
year-to-year impacts are not as variable as wildfires and non-agricultural prescribed/managed
burns.
We use this sector for the 2005 base case, and all future-year cases. Emissions are annual and
county-level. The same emissions are used in the v4 and v4.2 versions of the 2005-based
platform. Refer to the 2005v4 platform documentation for more information.
2.4 Biogenic sources (biog)
This sector is unchanged from the 2005v4 platform; the documentation is repeated here for
completeness.
The biogenic emissions were computed based on 2005 meteorology data using the BEIS3.14
model within SMOKE. The 2002 platform used the BEIS3.13 model; otherwise, all underlying
land use data and parameters are unchanged for the 2005 platform.
The BEIS3.14 model creates gridded, hourly, model-species emissions from vegetation and soils.
It estimates CO, VOC, and NOx emissions for the U.S., Mexico, and Canada. The BEIS3.14
model.
The inputs to BEIS include:
Temperature data at 2 meters which were obtained from the meteorological input files to
the air quality model,
Land-use data from the Biogenic Emissions Landuse Database, version 3 (BELD3).
BELD3 data provides data on the 230 vegetation classes at 1-km resolution over most of
North America, which is the same land-use data were used for the 2002 platform.
2.5 2005 mobile sources (onnoadj, on_moves_runpm,
on_moves_startpm, nonroad, aim_no_c3, seca_c3)
For the 2005 platform, as indicated in Table 2-2, we separated the 2005 onroad emissions into
three sectors: (1) "on moves startpm"; (2) "on moves runpm"; and (3) "on noadj". The
onmovesstartpm and on moves runpm sectors are processed separately because these sectors
contain gasoline exhaust PM emissions that are subject to mode-specific (start versus running)
hourly temperature adjustments during SMOKE processing. All pollutants and sources in the
on noadj sector are not subject to hourly temperature adjustments. The aircraft, locomotive, and
commercial marine emissions are divided into two nonroad sectors: "alm_no_c3" and "seca_c3",
and as previously mentioned, the aircraft emissions are in the non-EGU (ptnonipm) point
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inventory. The seca_c3 emissions are treated as point emissions with an elevated release
component while all other nonroad emissions are treated as county-specific low-level emissions.
The onroad emissions were primarily based on the publicly released 12/21/2009 version of the
Motor Vehicle Emissions Simulator (MOVES201Q). MOVES was run with a state/month
aggregation using county-average fuels for each state, state/month-average temperatures, and
national default vehicle age distributions. 2005 Vehicle Miles Travelled (VMT), consistent with
the 2005v2 NEI, were used.
The major changes between v4.2 and v4 versions of the 2005-based platform are that (1) we used
a publicly released version of MOVES (MOVES2010), rather than a draft version of MOVES;
(2) we used the MOVES emissions for all vehicle types and modes (as opposed to non-
motorcycle gasoline exhaust vehicles only); (3) MOVES2010 emissions cover all criteria
pollutants and criteria pollutant precursors (as opposed to draft MOVES that covered only
exhaust mode PM2.5, VOC, NOx and CO); and (4) we used NH3 from MOVES for California (as
opposed to NH3 from NMIM) since California-supplied emissions in the 2005v2 NEI do not
include NH3. It should also be noted that the exhaust PM2.5 from diesel vehicles, which had
previously come from NMIM but in v4.2 comes from MOVES, are not impacted by cold
temperatures. In addition, PM brake wear and tire wear mode emissions are now provided in
MOVES in v4.2; these emissions for both gasoline and diesel vehicles are also not impacted by
cold temperatures.
Table 2-10 lists the data source for all pollutants, vehicle types, and modes (e.g., exhaust,
evaporative, brake and tire wear) for all pollutants in the 2005v4 and 2005v4.2 emissions
modeling platform. Naphthalene, 1-3-butadiene, and acrolein are also provided by MOVES2010
but were not included in our 2005v4.2 platform.
Table 2-10. Data sources for onroad mobile sources in the 2005v4 and 2005v4.2 platforms1
Pollutants/vehicles/modes
2005v4
2005v4.2
PM2.5; gasoline exhaust, partially speciated2
Draft MOVES
MOVES2010
PM2.5; diesel exhaust, partially speciated2
NMIM
MOVES2010
PM2.5, brake and tirewear, unspeciated
NMIM
MOVES2010
VOC, Benzene (except refueling); gasoline
Draft MOVES
MOVES2010
VOC, Benzene (except refueling); diesel
NMIM
MOVES2010
CO, NOx, SO2, NH3, Acetaldehyde,
Formaldehyde; gasoline
Draft MOVES
MOVES2010
CO, NOx, SO2, NH3, Acetaldehyde,
Formaldehyde; diesel
NMIM
MOVES2010
1 For California, 2005v4 and 2005v4.2 use draft MOVES and MOVES2010 (respectively) only for NH3.
2 Exhaust mode PM2 5 species from MOVES consist of: PEC, PSO4 and the difference between PM2 5 and PEC
(named as "PM250C"). Procedures to produce the species needed are provided in Appendix D of the 2005v4.1
TSD. Diesel partially speciated emissions are not impacted by cold temperatures and do not need to be adjusted by
gridded temperature as do the gasoline exhaust particulate emissions. Brake wear and tire wear PM2 5 emissions
were not pre-speciated.
Similar to the v4 platform, we used the MOVES data to create emissions by state and month (and
SCC) and then allocated to counties based on 2005 NMIM-based county-level data. The reason
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for using the state resolution was due to (a) run time issues that made a county run for the entire
nation infeasible in the timeframe required and (b) incomplete efforts to create a national
database of county-specific inputs to MOVES. For 2005v4.2, no pollutants are obtained from
the 2005 NMIM runs.
The 2005v2 NEI does not contain the MOVES data that we use for the 2005 platform. Instead, it
contains onroad and nonroad mobile emissions that we generated using NMIM (EPA, 2005a) for
all of the U.S. except for California.6 The NMIM data was used only to allocate California-
submitted data to road types, to allocate the state-month-SCC MOVES data to counties, and for
some of the nonroad mobile sources. NMIM relies on calculations from the MOBILE6 and
NONROAD2005 models as described below, and in the NEI documentation. Inputs to NMIM
are posted with the 2005 Emission Inventory.
NMIM creates the onroad and nonroad emissions on a month-specific basis that accounts for
temperature, fuel types, and other variables that vary by month. Inventory documentation for the
2005v2 NEI onroad and nonroad sectors is also posted with other 2005 NEI documentation.
The residual fuel commercial marine vessel (CMV), also referred to as Category 3 (C3) from the
2002 platform were replaced with a set of approximately 4-km resolution point source format
emissions; these were modeled separately as point sources in the "seca_c3" sector for the 2005
platform. They were updated for v4.2 by using revised 2005 emissions from the category 3
commercial marine vessel sector to reflect the final projections from 2002 developed for the
category 3 commercial marine Emissions Control Area (ECA) Proposal to the International
Maritime Organization (EPA-420-F-10-041, August 2010). Unlike for the v4 platform, we
projected Canada as part of the ECA, using region-specific growth rates; thus the v4.2 seca_c3
inventories contain Canadian province codes for near shore emissions.
The nonroad sector, based on NMIM did not change for the v4.2 platform other than for
California, for which missing PM2.5 emissions for 7 counties was discovered. We corrected
these PM2.5 emissions by using an earlier version of the 2005 submittal which California had
provided values for the 7 counties.
The mobile sectors are compiled at a county and SCC resolution, with the exception of the
seca_c3 sector that uses point sources to map the pre-gridded data to the modeling domain.
Similar to v4, in v4.2, tribal data from the alm_no_c3 sector have been dropped because we do
not have spatial surrogate data, and the emissions are small; these data were removed from the
SMOKE input inventories for 2005.
Most mobile sectors use the HAP portion on the inventory to provide benzene, acetaldehyde,
formaldehyde and/or methanol to the modeling inputs through HAP VOC "integration", as
described in Section 3.1.2.1. A few categories of nonroad sources (CNG and LPG-fueled
equipment) do not have the BAFM pollutants in the inventory and therefore utilize the "no-
6 Although OTAQ generated emissions using NMIM for California, these were not used in the 2005 NEI version 2,
but rather were replaced by state-submitted emissions. Since California did not submit NH3, values from MOVES
were used.
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integrate", "no-hap-use" case, which means VOC from these sources is speciated to provide
BAFM.
2.5.1 Onroad gasoline exhaust cold-start mode PM (on_moves_startpm)
This sector contains MOVES2010 emissions for PM and naphthalene7 for non-California onroad
gasoline cold-start exhaust. These emissions (and the onmovesrunpm sector discussed in the
next section) are processed separately from the remainder of the onroad mobile emissions
because they are subject to hourly temperature adjustments, and these temperature adjustments
are different for cold-start and running exhaust modes.
Temperature adjustments were applied to account for the strong sensitivity of PM and
naphthalene exhaust emissions to temperatures below 72°F. Because it was not feasible to run
MOVES directly for all of the gridded, hourly temperatures needed for modeling, we created
emissions of PM and naphthalene exhaust at 72°F and applied temperature adjustments after the
emissions were spatially and temporally allocated. The PM2.5 (and naphthalene) adjustment
factors were different for starting and running exhaust because these two processes respond
differently to temperature as shown in Figure 2-1 which shows how these emissions increase
with colder temperatures. The temperature adjustment factor in this figure is defined in terms of
primary elemental carbon (PEC) as follows:
PEC = Adjustment Factor x PEC 72
Where:
PEC = PEC at Temperatures below 72°F
PEC 72 = PEC at 72°F or higher
As seen in the figure, start exhaust emissions increase more than running exhaust emissions as
temperatures decrease from 72°F.
Figure 2-1 also shows that the actual adjustments are different for start exhaust and running
exhaust emissions. The method for applying these adjustments was the same for both start and
running exhaust sectors: They were applied to SMOKE gridded, hourly intermediate files, based
upon the gridded hourly temperature data (these same data are also input to the air quality
model). One result of this approach is that inventory summaries based on the raw SMOKE
inputs for the onmovesstartpm and on moves runpm sectors will not be valid because they
will not include the temperature adjustments. As a result, the post-processing for temperature
adjustments included computing the emissions totals at state, county, and month resolution to use
for summaries.
7 Naphthalene is not used in the 2005v4 CAP-B AFM platform, but it is contained in the MOVES emissions.
25
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Figure 2-1. MOVES exhaust temperature adjustment functions.
80 n
70 \
\
60 Y
Run Exhaust
Start Exhaust
o rrTTTT~
-20 -10 1 11 21 31 41 51 61 71
Temperature (F)
The MOVES output data required pre-processing to develop county-level monthly ORL files for
input to SMOKE. As stated earlier, the resolution of the MOVES data was state-SCC totals, and
the state level data were allocated to county level prior to input into SMOKE. An additional pre-
processing step was for the exhaust PM2.5, for which emissions from MOVES were partially
speciated. To retain the speciated elemental carbon and sulfate emissions from MOVES, the
speciation step that is usually done in SMOKE was performed prior to SMOKE, and it was
modified to allow the temperature adjustments to be applied to only the species affected by
temperature as described in the list below. Finally, because the start exhaust emissions were
broken out separately from running exhaust emissions, they were assigned to new SCCs (urban
and rural parking areas) that allowed for the appropriate spatial and temporal profiles to be
applied in SMOKE.
A list of the procedures performed to prepare the MOVES data for input into SMOKE is
provided here.
i. We allocated state-level emissions to counties using state-county emission ratios by
SCC, pollutant, month, and emissions mode (e.g., evaporative, exhaust, brake wear,
and tire wear) for each month. The ratios were computed using NMIM 2005 data
(same data included in the 2005v2 NEI).
ii. We assigned these start exhaust emissions to urban and rural SCCs based on the
county-level ratio of emissions from urban versus rural local roads from the NMIM
onroad gasoline exhaust mode data. For example, we split light duty gasoline vehicle
(LDGV) start emissions in the state-total MOVES data (assigned SCC 2201001000)
into urban (2201001370) and rural (2201001350) based on the ratio of LDGV urban
(2201001330) and rural (2201001210) local roads.
26
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iii. We converted MOVES-based PM2.5 species at 72°F to SMOKE-ready PM species.
The SMOKE-ready species are listed below and the speciation technique used to
obtain the SMOKE-ready species is further discussed in Appendix D of the 2005v4.1
TSD.
NAPHTH72: unchanged from MOVES-based file, subject to temperature
adjustment below 72°F.
PEC72: unchanged from MOVES-based PM25EC, subject to temperature
adjustment below 72°F.
POC 72: modified MOVES-based PM250C to remove metals, PN03 (computed
from MOVES-based PM25EC), NH4 (computed from MOVES-based PM25S04
and PN03) and MOVES-based PM25S04. Subject to temperature adjustment
below 72°F.
PS04: unchanged from MOVES-based PM25S04, not subject to temperature
adjustment.
PN03: computed from MOVES-based PM25EC, not subject to temperature
adjustment.
OTHER: sum of computed metals (fraction of MOVES-based PM25EC) and
NH4 (computed from PN03 and PS04), not subject to temperature adjustment.
PMFINE 72: Computed from OTHER and fraction of POC 72. Subject to
temperature adjustment below 72 °F.
PMC 72: Computed as fraction of sum of PMFINE_72, PEC_72, POC_72,
PS04, and PN03. Subject to temperature adjustment below 72 °F.
The total MOVES PM emissions are conserved during allocation from states to counties, and
from the generic total "start" SCCs to the two new parking SCCs that end in "350" and "370".
PEC and PS04 components of PM2.5 emissions are also conserved as they are simply renamed
from the MOVES species "PM25EC" and "PM25S04". However, as seen above, POC, PN03,
and PMFINE components involve multiplying the MOVES PM species by components of an
onroad gasoline exhaust speciation profile described in Appendix D of the 2005v4.1 TSD.
2.5.2 Onroad gasoline exhaust running mode PM (on_moves_runpm)
This sector is identical to the onmovesstartpm sector discussed in Section 2.5.1, but, contains
running exhaust emissions instead of cold-start exhaust emissions. The same pollutants are in
this sector, and allocation from the MOVES state-level to county-level inventory is a simple
match by SCC and month to NMIM state-county ratios. The only reason this sector is separated
from on moves startpm is because the temperature adjustments are less extreme for these
running emissions at colder temperatures when compared to the curve for cold-start emissions
(Figure 2-1).
27
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2.5.3 Onroad mobile with no adjustments for daily temperature (on_noadj)
This sector consists of the bulk of the onroad mobile emissions, which are not covered by the
onmovesstartpm and onmovesrunpm sectors. These emissions did not receive any
temperature adjustments in our processing. There are four sources of data that are pre-processed
to create two sets of monthly inventories for this sector.
1. MOVES-based onroad gasoline and diesel: These are the MOVES-based emissions
monthly (not including gasoline exhaust mode PM and naphthalene) consisting of the
following:
a. Gasoline Exhaust: VOC, NOx, CO, SO2, NH3, 1,3-butadiene (106990),
acetaldehyde (75070), acrolein (107028), benzene (71432), formaldehyde
(50000), and brake and tire wear PM2.5;
b. Diesel Exhaust: Partially-speciated PM2.5 (that were fully speciated prior to input
into SMOKE (via Appendix D of the 2005v4.1 TSDl VOC, NOx, CO, S02, NH3,
1,3-butadiene (106990), acetaldehyde (75070), acrolein (107028), benzene
(71432), formaldehyde (50000), and brake and tire wear PM2.5. Because diesel
exhaust PM does not require the same intermediate temperature adjustments as
gasoline exhaust PM, diesel exhaust PM can therefore be processed with the
remaining onroad mobile emissions.
c. Evaporative: Non-refueling VOC, benzene, and naphthalene (91203).
For the pollutants listed, these non-California MOVES emissions encompass the same
sources as the on moves startpm and on moves runpm sectors: light duty gasoline
vehicles, light duty gasoline trucks (1 & 2), and heavy duty gasoline vehicles, but they do
not require the same intermediate temperature adjustments and can therefore be
processed with the remaining onroad mobile emissions. These emissions contain both
running and parking sources and they are pre-processed from state-level to county-level
much like the on moves startpm and on moves runpm sectors already discussed. The
preprocessing for the non-PM emissions did not require species calculations because the
raw MOVES emissions translated directly to SMOKE inventory species.
2. California onroad inventory: California 2005v2 NEI complete CAP/HAP onroad
inventory. California monthly onroad emissions are year 2005 and are based on
September 2007 California Air Resources Board (CARB) data from Chris Nguyen. NH3
emissions are from MOVES2010 runs for California. We retained only those HAPs that
are also estimated by NMIM for onroad mobile sources; all other HAPs provided by
California were dropped. The California onroad inventory does not use the SCCs for
Heavy Duty Diesel Vehicles (HDDV) class 6 & 7 (2230073XXX) emissions. California
does not specify road types, so we used NMIM-based California ratios to break out
vehicle emissions to the match the more detailed NMIM level.
2.5.4 Nonroad mobile sources: NMIM-based (nonroad)
This sector includes monthly exhaust, evaporative and refueling emissions from nonroad engines
(not including commercial marine, aircraft, and locomotives) that are derived from NMIM for all
states except California, which were corrected due to an inadvertent omission of PM2.5 from
seven counties. Thus, except for seven counties in California, emissions from this sector did not
28
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change between the v4 and v4.2 platform versions, and we repeat the documentation here for
completeness.
NMIM relied on the version of the NONROAD2005 model (NR05c-BondBase) used for the
marine spark ignited (SI) and small SI engine final rule, published May 2009 (EPA, 2008). For
2005, the NONROAD2005 model (NR05c-BondBase) is equivalent to NONROAD2008a, since
it incorporated Bond rule revisions to some of the base-case inputs and the Bond rule controls
did not take effect until future years. As with the onroad emissions, NMIM provides nonroad
emissions for VOC by three emission modes: exhaust, evaporative and refueling. Unlike the
onroad sector, refueling emissions nonroad sources are not dropped from processing for this
sector.
The EPA/OTAQ ran NMIM to create county-SCC emissions for the 2005v2 NEI nonroad
mobile CAP/HAP inventory, and similar to on noadj, we removed California NMIM emissions
that were submitted separately by California. Emissions were converted from monthly totals to
monthly average-day based on the number of days in each month. Similar to onroad NMIM
emissions, the EPA default inputs were replaced by state inputs where provided. The NMIM
inventory documentation describes this and all other details of the NMIM nonroad emissions
development.
California nonroad
California monthly nonroad emissions are year 2005 and are based on September 2007
California Air Resources Board (CARB) data from Chris Nguyen, other than for the PM2.5
missing from 7 counties, which used the March 2007 version. In addition, NH3 emissions are
from NMIM runs for California because these were not included in the California NEI submittal.
HAP emissions were estimated by applying HAP-to-CAP ratios computed from California data
provided in the 2005v2 NEI submittal. We retained only those HAPs that are also estimated by
NMIM for nonroad mobile sources; all other HAPs were dropped.
The CARB-based nonroad data did not have mode-specific data for VOC (exhaust, evaporative,
and refueling). To address this inconsistency with other states, we split the annual total
California data into monthly, mode-specific nonroad emissions for California using the NMIM
results. Details on this process are documented separately (Strum, 2007). Nonroad refueling
emissions for California were computed as Gasoline Transport (SCC=2505000120) emissions
multiplied by a factor of 0.46 (to avoid double counting with portable fuel container (PFC)
emissions in the nonpt sector) and were allocated to the gasoline equipment types based on ratios
of evaporative-mode VOC. The factor of 0.46 was computed by dividing the NMIM-derived
California refueling for 2005 by the sum of portable fuel container emissions and NMIM-derived
refueling for 2005.
2.5.5 Nonroad mobile sources: locomotive and non-C3 commercial marine
(alm_no_c3)
The alm_no_c3 sector contains CAP and HAP emissions from locomotive and commercial
marine vessel (CMV) sources, except for category 3/residual-fuel (C3) CMV and railway
maintenance. In modeling platforms prior to the 2005v4 platform, this sector also contained
aircraft emissions. Point-source airports were included in the non-EGU point sector (ptnonipm)
29
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through the 2005v2 NEI point source inventory. The C3 CMV emissions are in the seca_c3
sector. We note that the "a" in the "alm_no_c3" sector name is now misleading because aircraft
are no longer in this sector. With the exception of revised Delaware CMV emissions from the
Transport Rule comments, this sector is unchanged from the v4 platform.
The remaining emissions in the alm_no_c3 sector are year 2002 emissions unchanged from the
2002 platform; we repeat the 2005v4 documentation for completeness. The SCCs in the
aim no c3 sector are listed in Table 2-11.
Table 2-11. SCCs in the 2005 alm_no_c3 inventory compared to the 2002 platform aim sector
see
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;Underwav 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;Underwav 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
30
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The documentation of the 2002 NEI for the category 1 and 2 (C1/C2) commercial marine and
locomotive emissions.
For modeling purposes, the following additional changes were made to the NEI data for the
2005v4 platform:
For the 2005v4 platform, we removed C3 CMV SCCs (residual fuel) and aircraft SCCs.
Removed railway maintenance emissions (SCCs 2285002015, 2285004015, and
2285006015) because these are included in the nonroad NMIM monthly inventories.
This change was made for the 2002 platform and is retained here in the 2005 platform.
For the purpose of CAP-HAP VOC integration as discussed in Section 3.1.2.1, we
removed benzene, formaldehyde, and acetaldehyde for all sources that we did not
integrate these HAPs with VOC. As discussed in Section 3.1.2.1, sources are considered
no-integrate when the source of data between VOC and VOC HAPs is inconsistent or
VOC analysis of VOC and VOC HAPs indicates the source is not integrated. Although
our CAP-HAP integration approach also required the removal of methanol for 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.
The 2002 platform documentation goes into greater detail on the locomotives and C1/C2 CMV
emissions in this sector.
2.5.6 Nonroad mobile sources: C3 commercial marine (seca_c3)
The raw seca_c3 sector emissions data were developed in an ASCII raster format used since the
Emissions Control Area-International Marine Organization (ECA-IMO) project began in 2005,
then known as the Sulfur Emissions Control Area (SECA). These emissions consist of large
marine diesel engines (at or above 30 liters/cylinder) that until very recently, were allowed to
meet relatively modest emission requirements, often burning residual fuel. The emissions in this
sector are comprised of primarily foreign-flagged ocean-going vessels, referred to as Category 3
(C3) CMV ships. The seca_c3 (ECA) inventory includes these ships in several intra-port modes
(cruising, hoteling, reduced speed zone, maneuvering, and idling) and underway mode and
includes near-port auxiliary engines. An overview of the ECA-IMO project and future-year
goals for reduction of NOx, SO2, and PM C3 emissions.
The resulting coordinated strategy, including emission standards under the Clean Air Act for new
marine diesel engines with per-cylinder displacement at or above 30 liters, and the establishment
of Emission Control Areas.
The raw ECA inventory started as a set of ASCII raster datasets at approximately 4-km
resolution that we converted to SMOKE point-source ORL input format.
In summary, this paper describes how the ASCII raster dataset was converted to latitude-
longitude, mapped to state/county FIPS codes that extend up to 200 nautical miles (nm) from the
coast, assigned stack parameters, and how the monthly ASCII raster dataset emissions were used
31
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to create monthly temporal profiles. Counties in 2005v4 were assigned as extending up to
200nm from the coast because of this was the distance to the edge of the Exclusive Economic
Zone (EEZ), a distance that would be used to define the outer limits of ECA-IMO controls for
these vessels.
The base year ECA inventory is 2002 and consists of these CAPs: PMio, CO, CO2, NH3, NOx,
SOx (assumed to be SO2), and Hydrocarbons (assumed to be VOC). The EPA developed
regional growth (activity-based) factors that we applied to create the v4 platform 2005 inventory
from the 2002 data.
We computed HAPs directly from the CAP inventory and the calculations are therefore
consistent; therefore, the entire seca_c3 sector utilizes CAP-HAP VOC integration to use the
VOC HAP species directly, rather than VOC speciation profiles.
For the v4.2 platform, we chose only to include some HAPs in the seca_c3 sector: benzene,
formaldehyde, and acetaldehyde. We projected these HAPs using the same VOC factors as used
in 2005v4:
Benzene = VOC * 9.795E-06
Acetaldehyde = VOC * 2.286E-04
Formaldehyde = VOC * 1.5672E-03
We converted the emissions to SMOKE point source ORL format, allowing for the emissions to
be allocated to modeling layers above the surface layer. We also corrected FIPS code
assignments for one county in Rhode Island. All non-US emissions (i.e., in waters considered
outside of the 200nm EEZ, and hence out of the U.S. and Canadian ECA-IMO controllable
domain) are simply assigned a dummy state/county FIPS code=98001. The SMOKE-ready data
have also been cropped from the original ECA-IMO data to cover only the 36-km air quality
model domain, which is the largest domain used for this effort.
Seca_c3 updates from 2005v4 platform used in creating 2005v4.2 platform
There are several updates to the seca_c3 emissions from 2005v4 to 2005v4.2:
1) Delaware provided updated county total emissions in the Transport Rule comments.
There are several other changes that impact Delaware state total emissions discussed
below.
2) Region-specific and pollutant-specific growth factors were updated for the v4.2 platform
as compared to the v4 platform to be consistent with the final projections from 2002,
developed for the C3 ECA Proposal to the International Maritime Organization (EPA-
420-F-10-041, August 2010). The exception to this is Delaware, where county totals
were modified to match those provided in Transport Rule comments. The updated
factors that we used to project from 2002 to 2005 are presented in Table 2-12. These
updated 2002 to 2005 projection factors for 2005v.2 are approximately 1% higher for all
pollutants nationally.
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Table 2-12. Adjustment factors to update the 2005 seca_c3 sector emissions for the v4.2
platform.
2005 Adjustments Relative to 2002
Region
NOx
PM10
PM25
VOC (HC)
CO
S02
East Coast (EC)1
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
North Pacific (NP)
1.07254
1.11354
1.09817
1.11358
1.11318
1.11339
South Pacific (SP)
1.12539
1.17416
1.17257
1.17055
1.17012
1.17565
Great Lakes (GL)
1.04397
1.06264
1.06241
1.06341
1.06280
1.06251
Outside ECA
1.08654
1.13186
1.13186
1.13186
1.13186
1.13186
1 -Delaware emissions were provided for 2005 from Transport Rule comments.
3) In addition to the updated values, near-shore Canadian emissions are now assigned to
regions whereas previously Canadian sources used the "Outside ECA" factors. Canada
uses North Pacific, Great Lakes and East Coast depending on where the emissions are.
For example, near-shore emissions around Vancouver British Columbia are projected
from 2002 using North Pacific (NP) factors rather than "Outside ECA" factors.
4) One of the most significant comments from the Transport Rule Proposal was the
assignment in 2005v4 of state boundaries that extended to the 200nm EEZ distance
offshore. This had potentially unrealistic impacts on source apportionment modeling (see
Section 5) because large emissions from shipping lanes far from shore were attributable
to states whose coastlines were up to 200nm away. For 2005v4.2, we obtained state-
federal water boundaries data from the Mineral Management Service (MMS) that
extended only 3 to 10 miles off shore. It is important to note that the emission values did
not change as a result of this update, only the state to which those emissions from 3 to
200 miles offshore were assigned. We retained separate dummy "FIPS" for these
offshore emissions to ensure that they were projected to future years based on the
appropriate regional-based factors in Table 2-12.
5) The 2005v4 ECA-based C3 inventory did not delineate between ports and underway (or
other C3 modes such as hoteling, maneuvering, reduced-speed zone, and idling)
emissions; therefore, we assigned these emissions to the broad ("total") SCC for C3
CMV (2280003000). For 2005v4.2, we used a U.S. ports spatial surrogate dataset to
simply map the seca_c3 emissions ports or underway SCCs. This had no effect on
temporal allocation or speciation compared to existing profiles for underway and port C3
emissions (2280003100 and 2280003200).
The net impact of all the 2005v4.2 changes to U.S. total NOx, SO2, and PM2.5 seca_c3 emissions
are shown in Table 2-13. Again, with the exceptions of NOx, PM2.5, and most notably, SO2 in
Delaware, approximately 99% of these differences are solely attributable to reclassification of
U.S. states to the 3-10 mile MMS boundaries in 2005v4.2 rather than the 200nm EEZ boundaries
in 2005v4.
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Table 2-13. Contiguous U.S. C3 CMV emissions in the 2005v4 and 2005v4.2 platforms
Pollutant
2005v4
2005v4.2
NOx
642,000
130,000
PM2.5
49,000
11,000
S02
417,000
97,000
2.6 Emissions from Canada, Mexico and offshore drilling platforms
(othpt, othar, othon)
These sectors are unchanged from the 2005v4 platform; the documentation is included here for
completeness. The emissions from Canada, Mexico, and Offshore Drilling platforms are
included as part of five sectors: othpt, othar, and othon.
The "oth" refers to the fact that these emissions are "other" than those in the 2005 NEI, and the
third and fourth characters provide the SMOKE source types: "pt" for point, "ar" for "area and
nonroad mobile", and "on" for onroad mobile. All "oth" emissions are CAP-only inventories.
Mexico's emissions are unchanged from the 2002 platform with one exception -one stack
diameter was updated (recomputed from stack velocity and flowrate) in the Mexico border states
point inventory.
For Canada we updated the emissions from the 2002 platform, migrating the data from year 2000
inventories to year 2006 inventories for the 2005 platform. We migrated to these 2006 Canadian
emissions despite not receiving future-year emissions, as we were advised by Canada that the
improvement in the 2006 inventory over the 2000 inventory was more significant than the
undesirable effect of retaining these 2006 emissions for all future-year modeling. We applied
several modifications to the 2006 Canadian inventories:
i. We did not include wildfires, or prescribed burning because Canada does not include
these inventory data in their modeling.
ii. We did not include in-flight aircraft emissions because we do not include these for the
U.S., and we do not have an appropriate approach to include in our modeling.
iii. We applied a 75% reduction ("transport fraction") to PM for the road dust, agricultural,
and construction emissions in the Canadian "afdust" inventory. This approach is more
simplistic than the county-specific approach used for the U.S., but a comparable approach
was not available for Canada.
iv. We did not include speciated VOC emissions from the ADOM chemical mechanism.
v. Residual fuel CMV (C3) SCCs (22800030X0) were removed because these emissions are
included in the seca_c3 sector, which covers not only emissions close to Canada but also
emissions far at sea. Canada was involved in the inventory development of the seca_c3
sector emissions.
vi. Wind erosion (SCC=2730100000) and cigarette smoke (SCC=2810060000) emissions
were removed from the nonpoint (nonpt) inventory; these emissions are also absent from
our U.S. inventory.
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vii. Quebec PM2.5 emissions (2,000 tons/yr) were removed for one SCC (2305070000) for
Industrial Processes, Mineral Processes, Gypsum, Plaster Products due to corrupt fields
after conversion to SMOKE input format. This error should be corrected in a future
inventory.
viii. Excessively high CO emissions were removed from Babine Forest Products Ltd (British
Columbia SMOKE plantid='5188') in the point inventory. This change was made at our
discretion because the value of the emissions was impossibly large.
ix. The county part of the state/county FIPS code field in the SMOKE inputs were modified
in the point inventory from "000" to "001" to enable matching to existing temporal
profiles.
For Mexico we continued to use emissions for 1999 (Eastern Research Group Inc., 2006) which
were developed as part of a partnership between Mexico's Secretariat of the Environment and
Natural Resources (Secretaria de Medio Ambiente y Recursos Naturales-SEMARNAT) and
National Institute of Ecology (Instituto Nacional de Ecologia-INE), the U.S. EPA, the Western
Governors' Association (WGA), and the North American Commission for Environmental
Cooperation (CEC). This inventory includes emissions from all states in Mexico.
The offshore emissions include point source offshore oil and gas drilling platforms. We used
updated emissions from the 2005v2 NEI point source inventory. The offshore sources were
provided by the Mineral Management Services (MMS).
Table 2-14 summarizes the data in the "oth" sectors and indicates where these emissions have
been updated from the 2002 platform.
Table 2-14. Summary of the othpt, othar, and othon sectors changes from the 2002 platform
Sector
Components
Changes from 2002 platform
othpt
Mexico, 1999, point
None
Canada, 2006, point
Uses emissions from 2006 National Pollutant
Release Inventory (NPRI), 3 components:
1) upstream oil and gas sector emissions for
all CAPs except VOC;
2) VOC sources pre-speciated to CB05
speciation except for benzene;
3) Remaining point source emissions.
Offshore, 2005, point
Uses emissions from 2005 v2 point inventory
othar
Mexico, 1999, nonpoint
None
Mexico, 1999, nonroad
None
Canada, 2006, nonpoint
Uses 2006 Canadian aircraft (landing and take-offs
only), agricultural NH3, fugitive dust, and
remaining nonpoint inventories.
Canada, 2006, nonroad
Uses 2006 Canadian nonroad mobile, non-C3
marine, and locomotives inventories.
othon
Mexico, 1999, onroad
None
35
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Sector
Components
Changes from 2002 platform
Canada, 2006, onroad
Uses 2006 Canadian onroad inventory. Emissions
are given at vehicle type resolution only (i.e., does
not include road types).
2.7 SMOKE-ready non-anthropogenic inventories for chlorine
For the ocean chlorine, we used the same data as in the CAP and HAP 2002-based platform.
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3 Emissions Modeling Summary
Both the CMAQ and CAMx models require hourly emissions of specific gas and particle species
for the horizontal and vertical grid cells contained within the modeled region (i.e., modeling
domain). To provide emissions in the form and format required by the model, it is necessary to
"pre-process" the "raw" emissions (i.e., emissions input to SMOKE) for the sectors described
above in Section 2. In brief, the process of emissions modeling transforms the emissions
inventories from their original temporal resolution, pollutant resolution, and spatial resolution
into the resolution hourly, speciated, gridded resolution required by the air quality model.
As seen in Section 2, the temporal resolution of the emissions inventories input to SMOKE for
the 2005 platform varies across sectors, and may be hourly, monthly, or annual total emissions.
The spatial resolution, which also can be different for different sectors, may be individual point
sources or county totals (province totals for Canada, municipio totals for Mexico). The pre-
processing steps involving temporal allocation, spatial allocation, pollutant speciation, and
vertical allocation of point sources are referred to as emissions modeling. This section provides
some basic information about the tools and data files used for emissions modeling as part of the
2005 platform. Since we devoted Section 2 to describing the emissions inventories, we have
limited the descriptions of data in this section to the ancillary data SMOKE uses to perform the
emissions modeling steps. Note that all SMOKE inputs for the 2005v4.2 platform emissions are
available at the 2005v4.2 website (see the end of Section 1).
We used SMOKE version 2.6 to pre-process the raw emissions to create the emissions inputs for
CMAQ and then converted those to inputs suitable for CAMx. The emissions processing steps
and ancillary data for v4.2 were very similar to those done for v4. A summary of the revisions is
as follows:
We updated the ancillary files to handle additional MOVES SCCs related to parking area
emissions and to make some changes to the temporal and spatial approaches that were
originally assigned to parking area SCCs.
We changed speciation profiles for headspace vapor (VOC).
We changed the PM2.5 speciation profile for category 3 commercial marine vessels
burning residual oil.
We updated the list of state-county names to include "dummy" seca_c3 FIPS for
emissions outside of U.S. MMS-base state boundaries but within the 200nm EEZ (see
section 2.5.6). These dummy FIPS were used for internal projections of regional offshore
emissions in the ECA-IMO control area that extended up to 200nm offshore.
We used an updated county-to-cell spatial surrogate for U.S. oil and gas emissions.
We changed the temporal allocation approach to use: 1) profiles that vary by day of week
and to use new temporal profiles for the afdust sector, 2) CENRAP-based state-specific
agricultural burning profiles that vary monthly for the nonpt sector, and 3) residential
natural gas combustion and commercial propane and kerosene combustion from uniform
monthly to a profile that varies for the nonpt sector.
37
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We also utilized the feature in SMOKE (updated in version 2.5) to create combination speciation
profiles that could vary by state/county FIPS code and by month; we used this approach for some
mobile sources as described in Section 3.1.2. For sectors that have plume rise, we used the in-
line emissions capability of the air quality model to create source-based emissions files, rather
than created the much larger 3-dimensional files. The air quality model-ready emissions were
first created in a form appropriate for CMAQ and were then converted to a form usable by
CAMx using a FORTRAN converter called 'inline2camx\ This program generates the gridded
surface level 2-dimensional emissions and elevated point source files necessary for CAMx, and it
also renames certain emissions species to the names needed by CAMx. Emissions totals by
specie for the entire model domain are output as reports that are then compared to reports
generated by SMOKE to ensure mass is not lost or gained during this conversion process.
3.1 Key emissions modeling settings
Each sector is processed separately through SMOKE, until the final merge program (Mrggrid) is
run to combine the model-ready, sector-specific emissions across sectors. The SMOKE settings
in the run scripts and the data in the SMOKE ancillary files control the approaches used for the
individual SMOKE programs for each sector. Table 3-1 summarizes the major processing steps
of each platform sector. The "Spatial" column shows the spatial approach: "point" indicates that
SMOKE maps the source from a point location (i.e., latitude and longitude) to a grid cell;
"surrogates" indicates that some or all of the sources use spatial surrogates to allocate county
emissions to grid cells; and "area-to-point" indicates that some of the sources use the SMOKE
area-to-point feature to grid the emissions (further described in Section3.2.1.2). The
"Speciation" column indicates that all sectors use the SMOKE speciation step, though biogenics
speciation is done within BEIS3 and not as a separate SMOKE step. The "Inventory resolution"
column shows the inventory temporal resolution from which SMOKE needs to calculate hourly
emissions.
Finally, the "plume rise" column indicates the sectors for which the "in-line" approach is used.
These sectors are the only ones which will have emissions in aloft layers, based on plume rise.
The term "in-line" means that the plume rise calculations are done inside of the air quality model
instead of being computed by SMOKE. The height of the plume rise determines the model layer
into which the emissions are placed. For the 2005v4 and 2005v4.2 platforms, we did not have
SMOKE compute the vertical plume rise. Instead, this was done in the air quality model using
the stack data and the hourly air quality model inputs found in the SMOKE output files for each
model-ready sector. The seca_c3 sector is the only sector with only "in-line" emissions,
meaning that all of the entire emissions occur in aloft layers and there are no emissions in the
two-dimensional, layer-1 files created by SMOKE.
Table 3-1. Key emissions modeling steps by sector.
Platform sector
Spatial
Speciation
Inventory
resolution
Plume rise
ptipm
Point
Yes
daily & hourly
in-line
ptnonipm
Point
Yes
annual
in-line
othpt
Point
Yes
annual
in-line
38
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Platform sector
Spatial
Speciation
Inventory
resolution
Plume rise
nonroad
surrogates &
area-to-point
Yes
monthly
othar
Surrogates
Yes
annual
seca c3
Point
Yes
annual
in-line
aim no c3
surrogates &
area-to-point
Yes
annual
on noad]
Surrogates
Yes
monthly
on noadj
Surrogates
Yes
monthly
on moves startpm
Surrogates
Yes
monthly
on moves runpm
Surrogates
Yes
monthly
othon
surrogates
Yes
annual
nonpt
surrogates &
area-to-point
Yes
annual
ag
surrogates
Yes
annual
afdust
surrogates
Yes
annual
biog
pre-gridded
landuse
in BEIS3 .14
hourly
avefire
surrogates
Yes
annual
In addition to the above settings, we used the PELVCONFIG file, which can be optionally used
to group sources so that they would be treated as a single stack by SMOKE when computing
plume rise. For the 2005v4.2 platform we chose to have no grouping, which is a difference the
2005v4 platform. We changed this because grouping done for "in-line" processing will not give
identical results as "offline" (i.e., processing whereby SMOKE creates 3-dimensional files). The
only way to get the same results between in-line and offline is to choose to have no grouping.
3.1.1 Spatial configuration
For the 2005v4.2 platform in support of the Transport Rule, we ran SMOKE followed by CAMx
for the 36-km CONtinental United States "CONUS" modeling domain and the eastern US 12-km
modeling domain (EUS) shown in Figure 3-1. Figure 3-1 also shows the 12-km western domain
(WUS), but this domain was not used for Transport Rule modeling. Note that these domains
were also used in the 2005v4 and 2002 platforms.
39
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Figure 3-1. Air quality modeling domains
12km West Domain Boundary
^
12km East Domain Boundary |
All three grids use a Lambert-Conformal projection, with Alpha = 33°, Beta = 45° and Gamma
= -97°, with a center of X = -97° and Y = 40°. Table 3-2 describes the grids for the three
domains.
40
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Table 3-2. Descriptions of the 2005-based platform grids
Common
Name
Grid
Cell Size
Description
(see Figure 3-1)
Grid name
Parameters listed in SMOKE grid
description (GRIDDESC) file:
projection name, xorig, yorig,
xcell, ycell, ncols, nrows, nthik
US 36 km or
CONUS-36
36 km
Entire conterminous
US plus some of
Mexico/Canada
US36KM 148X1
12
'LAM 40N97W', -2736.D3, -2088.D3,
36.D3, 36.D3, 148, 112, 1
Big East 12
km
12 km
Goes west to
Colorado, covers
some Mexico/Canada
EUS12_279X240
'LAM 40N97W', -1008.D3 , -1620.D3,
12.D3, 12.D3, 279, 240, 1
West 12 km
12 km
Goes east to
Oklahoma, covers
some of
Mexico/Canada
US12_213X192
'LAM 40N97W', -2412.D3 , -972.D3,
12.D3, 12.D3, 213, 192, 1
Section 3.2.1 provides the details on the spatial surrogates and area-to-point data used to
accomplish spatial allocation with SMOKE.
3.1.2 Chemical speciation configuration
The emissions modeling step for chemical speciation creates "model species" needed by the air
quality model for a specific chemical mechanism. These model species are either individual
chemical compounds or groups of species, called "model species." The chemical mechanism
used for the 2005 platform is the CB05 mechanism (Yarwood, 2005). The same base chemical
mechanism is used with CMAQ and CAMx, but the implementation differs slightly between the
two models. For details of the chemical mechanism as it is implemented in CAMx 5.2. The
specific versions of CMAQ and CAMx used in applications of this platform include secondary
organic aerosol (SOA) and HONO enhancements.
From the perspective of emissions preparation, the CB05 mechanism is the same as was used in
the 2002 platform except that additional input model species are needed to support the nitrous
acid (HONO) chemistry enhancements and additional input model species are needed to support
SOA. Table 3-3 lists the model species produced by SMOKE for use in CMAQ and CAMx; the
only three input species that were not in the CAP 2002-Based platform are nitrous acid (HONO),
BENZENE and sesquiterpenes (SESQ). It should be noted that the BENZENE model species is
not part of CB05 in that the concentrations of BENZENE do not provide any feedback into the
chemical reactions (i.e., it is not "inside" the chemical mechanism). Rather, benzene is used as a
reactive tracer and as such is impacted by the CB05 chemistry. BENZENE, along with several
reactive CB05 species (such as TOL and XYL) plays a role in SOA formation.
41
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Table 3-3. Model species produced by SMOKE for CB05 with SOA for CMAQ4.7 and CAMx*
42
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Inventory Pollutant
Model Species
Model species description
CL2
CL2
Atomic gas-phase chlorine
HC1
HCL
Hydrogen Chloride (hydrochloric acid) gas
CO
CO
Carbon monoxide
NOx
NO
Nitrogen oxide
N02
Nitrogen dioxide
HONO
Nitrous acid
S02
S02
Sulfur dioxide
SULF
Sulfuric acid vapor
nh3
NH3
Ammonia
voc
ALD2
Acetaldehyde
ALDX
Propionaldehyde and higher aldehydes
BENZENE
Benzene (not part of CB05)
ETH
Ethene
ETHA
Ethane
ETOH
Ethanol
FORM
Formaldehyde
IOLE
Internal olefin carbon bond (R-C=C-R)
ISOP
Isoprene
MEOH
Methanol
OLE
Terminal olefin carbon bond (R-C=C)
PAR
Paraffin carbon bond
TOL
Toluene and other monoalkyl aromatics
XYL
Xylene and other polyalkyl aromatics
Various additional
SESQ
Sesquiterpenes
VOC species from
the biogenics model
TERP
Terpenes
which do not map to
the above model
species
PM10
PMC
Coarse PM >2.5 microns and <10 microns
PM2.5
PEC
Particulate elemental carbon <2.5 microns
PN03
Particulate nitrate < 2.5 microns
POC
Particulate organic carbon (carbon only) <2.5
microns
PS04
Particulate Sulfate < 2.5 microns
PMFINE
Other particulate matter <2.5 microns
Sea-salt species (non
PCL
Particulate chloride
-anthropogenic
PNA
Particulate sodium
emissions)
43
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*The same species names are used for the CAMX model with exceptions as follows:
1. CL2 is not used in CAMX
2. CAMX particulate sodium is NA (in CMAQ it is PNA)
3. CAMx uses different names for species that are both in CB05 and SOA for the following: TOLA=TOL,
XYLA=XYL, ISP=ISOP, TRP=TERP. They are duplicate species in CAMx that are used in the SOA chemistry.
CMAQ uses the same names in CB05 and SOA for these species.
4. CAMx uses a different name for sesquiterpenes: CMAQ SESQ = CAMX SQT
5. CAMx uses particulate species uses different names for organic carbon, coarse particulate matter and other
particulate mass as follows: CMAQ POC = CAMx POA, CMAQ PMC = CAMx CPRM, and CMAQ PMFINE=
CAMxFPRM
The approach for speciating PM2.5 emissions in v4.2 is the same as v4 except that in addition to
the onmovesstartpm and onmovesrunpm sectors, exhaust PM from diesel is provided to
SMOKE as speciated emissions. Thus, the only PM species requiring speciation in SMOKE
from the onroad sector are the brake and tirewear PM2.5. Canada point sources have an SCC of
3999999999 and all use the Speciation profile '92037' which is the "Industry Manufacturing
Avge profile." While this had not changed between v4 and v4.2, the documentation for v4
incorrectly stated that the Canadian point inventory (othpt sector) was pre-speciated. The
Canadian point source inventory is pre-speciated for VOC but not for PM2.5. One other
difference in PM2.5 speciation is that we used a new profile ('92200') called "simplified profile -
Marine Vessel - Main Boiler - Heavy Fuel Oil - Simplified." At the time that this profile was
used, we anticipated its release with SPECIATE4.3.
The approach for speciating VOC emissions from non-biogenic sources is the same for the v4.2
platform as for the v4 platform, though there are some differences in the data files used. The
approach is that:
1. For some sources, HAP emissions are used in the speciation process to allow integration
of VOC and HAP emissions in the NEI. This has the result of modifying the speciation
profiles based on the HAP emission estimates which are presumed to be more accurate
than the speciated VOC results for the HAPs; and,
2. For some mobile sources, "combination" profiles are specified by county and month and
emission mode (e.g., exhaust, evaporative). SMOKE computes the resultant profile using
the fraction of each specific profile assigned by county, month and emission mode. A
new feature and new profile file in SMOKE (the GSPRO COMBO file) allowed the use
of this approach for the 2005v4 platform, and its use continues here.
The VOC speciation data files are different because we added another part of the nonpt sector to
exclude from HAP VOC integration: the category of pesticide application. Additionally, the
v4.2 platform used a new headspace profile representative of E0 gasoline, profile code 8762:
"Gasoline Headspace Vapor using 0% Ethanol - Composite Profile". This profile is part of
SPECIATE4.3 and was used in place of the SPECIATE4.0 profile 8737 (Composite Profile -
Non-oxygenated Gasoline Headspace Vapor), which was used in the v4 platform. The new
headspace profile was used for the same sources as was the previous headspace profile: year
2005 refueling and other ambient temperature evaporative gasoline processes (portable fuel
containers and any evaporation of gasoline associated with gasoline storage and distribution
sources).
44
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The below subsections provide a further description of the HAP/CAP integration and use of
combination profiles. Section 3.2.2 provides the details about the data files used to accomplish
these speciation processing steps.
3.1.2.1 The combination of HAP BAFM (benzene, acetaldehyde, formaldehyde
and methanol) and VOC for VOC speciation
The VOC speciation approach for the 2005v4.2 platform differed from the 2002 platform in that
we included, for some of the U.S. platform sectors, HAP emissions from the NEI in the
speciation process. That is, instead of speciating VOC to generate all of the species listed in
Table 3-3 as we did for the 2002 platform, we integrated emissions of the 4 HAPs, benzene,
acetaldehyde, formaldehyde and methanol (BAFM) from the NEI with the NEI VOC. The
integration process (described in more detail below) combines the BAFM HAPs with the VOC in
a way that does not double count emissions and uses the BAFM directly in the speciation
process. We believe that generally, the HAP emissions from the NEI are more representative of
emissions of these compounds than their generation via VOC speciation.
We chose these HAPs because, with the exception of BENZENE, they are the only explicit VOC
HAPs in the base version of CMAQ 4.7 (CAPs only with chlorine chemistry) model. By
"explicit VOC HAPs," we mean model species that participate in the modeled chemistry using
the CB05 chemical mechanism. We denote the use of these HAP emission estimates along with
VOC as "HAP-CAP integration". BENZENE was chosen because it was added as a model
species in the base version of CMAQ 4.7, and there was a desire to keep its emissions consistent
between multi-pollutant and base versions of CMAQ.
The integration of HAP VOC with VOC is a feature available in SMOKE for all inventory
formats other than PTDAY (the format used for the ptfire sector). SMOKE allows the user to
specify the particular HAPs to integrate and the particular sources to integrate. The particular
HAPs to integrate are specified in the INVTABLE file, and the particular sources to integrate are
based on the NHAPEXCLUDE file (which actually provides the sources that are excluded from
integration8). For the "integrate" sources, SMOKE subtracts the "integrate" HAPs from the
VOC (at the source level) to compute emissions for the new pollutant "NONHAPVOC." The
user provides NONHAPVOC-to-NONHAPTOG factors and NONHAPTOG speciation profiles.
SMOKE computes NONHAPTOG and then applies the speciation profiles to allocate the
NONHAPTOG to the other air quality model VOC species not including the integrated HAPs.
This process is illustrated in Figure 3-2. Note that we did not need to remove BAFM from
no-integrate sources in a sector where all sources are no-integrate because this is accomplished
by through use of a SMOKE ancillary "INVTABLE" which essentially drops all BAFM in that
sector.
8 In SMOKE version 2.6 the options to specify sources for integration are expanded so that a user can specify the
particular sources to include or exclude from integration, and there are settings to include or exclude all sources
within a sector. We did not take advantage of this new flexibility in processing v4.2 emissions or v4 emissions, but
the user will now have the ability for easier inclusion of specific sources to get the same result.
45
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Figure 3-2. Process of integrating BAFM with VOC for use in VOC Speciation
Step 1: Analyze Inventory to determine which sources will be "integrate" sources
NHAPEXCLUDE
Ancillary file
Readyfor SMOKE
1$ Sector
Partially
integrated?
Emissions readyfor
SMOKE
Create list of
'no-integrate'
sources
Remove B,F,A,M from
all sources that will
NOT be integrated
For each Sector,
Examine Emissions
Sources of VOC and
B,A,F,M
Determine which sources
will not be Integrated (either
whole sector or some
sources within a sector)
based on "Integration
Criteria"
Emissions ready for
SMOKE
Step 2: Run SMOKE
Emissions ready for SMOKE
SMOKE
list of "no-integrate"
sources (NHAPEXCLUDE)
Speciation Cross
Reference File (GSREF)
Assign speciation profile code to each emission source «¦
Compute: NONHAPTOG emissions from NONHAPVOCfor
each integrate source
Compute: TOG emissions from VOC for each no-integrate
source
VOC-to-TOG factors
NONHAPVOC-to-NONHAPTOG
factors (GSCNV)
Compute moles of each CB05 model species.
Use NONHAPTOG profiles applied to NONHAPTOG
emissions and B, F, A, M emissions for integrate sources.
Use TOG profiles applied to TOG for no-integratesources
TOG and NONHAPTOG
speciation factors
(GSPRO)
Compute NONHAPVOC= VOC- (B + F + A+M)
emissions for each integrate source
Retain VOC emissions for each no-integrate source
Speciated Emissions for VOC species
46
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We considered CAP-HAP integration for all sectors and developed "integration criteria" for
some of those. Table 3-4 summarizes the integration approach for each platform sector used in
Step 1 of Figure 3-2.
Table 3-4. Integration status of benzene, acetaldehyde, formaldehyde and methanol (BAFM) for
each platform sector
Platform Sector
Approach for Integrating NEI emissions of Benzene (B), Acetaldehyde (A),
Formaldehyde (F) and Methanol (M)
ptipm
No integration because emissions of BAFM are relatively small fortius 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
aim no c3
Partial integration; details provided below table
seca c3
Full integration
onroad
Full integration
biog
N/A - sector contains no inventory pollutant "VOC"; but rather specific VOC species
othpt
No integration - not the NEI
othar
No integration - not the NEI
othon
No integration - not the NEI
For the nonpt sector, we used the following integration criteria to determine the sources to
integrate (Step 1):
1. Any source for which BAFM emissions were from the 1996 NEI were not integrated
(data source code contains a "96").
2. Any source for which the sum of BAFM is greater than the VOC was not integrated,
since this clearly identifies sources for which there is an inconsistency between VOC and
VOC HAPs. This includes some cases in which VOC for a source is zero.
3. For certain source categories (those that comprised 80% of the VOC emissions), we
chose to integrate sources in the category per the criteria specified in the first column in
Table 3-5. For most of these source categories, we allow sources to be integrated if they
had the minimum combination of BAFM specified in the first column. For a few source
categories, we designated all sources as "no-integrate". The one change we made from
Table 3-5 for the v4.2 platform is highlighted: we changed pesticides application to "no-
integrate."
4. For source categories not covered in Table 3-5 (i.e., that do not comprise the top 80% of
VOC emissions), then as long as the source has emissions of one of the BFAM
pollutants, then it can be integrated.
47
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Table 3-5. Source-category specific criteria for integrating nonpt SCCs for categories
comprising 80% of the nonpoint VOC emissions
minimum
HAP(s)
needed
SCC Tier 3
SCC Tier 3 Description
Comments
BFA
2104008000
Stationary Source Fuel
Combustion;Residential;Wood
B
2501060000
Storage and Transport;Petroleum and Petroleum
Product Storage;Gasoline Service Stations
BM
2440000000
Solvent Utilization;Miscellaneous Industrial;All
Processes
Speciation profile: 3144 has no benzene but
most records have it and they're from the EPA
(and Calif)
FAM
2401001000
Solvent Utilization;Surface Coating;Architectural
Coatings
B
2310001000
Industrial Processes;Oil and Gas Production: SIC
13 ;A11 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 ;A11 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-
inlcgrale
(change
from v4
platform)
2461850000
Solvent Utilization;Miscellaneous Non-industrial:
Commercial;Pesticide Application: Agricultural
Profile has no benzene. Inventory benzene
came from solvent utilization data (Fredonia)
for "other markets" for the year 1998. Since
benzene no longer allowed in pesticides, use
of a no-benzene profile would give more
accurate results. Note that this is a change
from the v4 platform, where this sector was
"integrate."
BFA
2630020000
Waste Disposal, Treatment, and
Recovery;Wastewater Treatment;Public Owned
profile BFA 2002 (wastewater treatment
plants). No methanol in profile. No
methanol mentioned in POTW National
Emissions Standards for Hazardous Air
Pollutants (NESHAP). Acetaldehyde and
Formaldehyde were in profile but not
NESHAP. Methanol in NEI documentation.
no-
integrate
2461021000
Solvent Utilization;Miscellaneous Non-industrial:
Commercial;Cutback Asphalt
profile 1007 has none of these HAP. Only
Minnesota has a tiny amount.
no-
integrate
2401005000
Solvent Utilization;Surface Coating;Auto
Refinishing: SIC 7532
Only NY has benzene. Spec, profile is 2402
and has none of these HAP. Documentation
for NEI does not estimate this HAP.
use
Integrate
case
2301030000
Industrial Processes;Chemical Manufacturing: SIC
28;Process Emissions from Pharmaceutical Manuf
(NAPAP cat. 106)
profile 2462 - has nearly 8% benzene. Will
create a LOT of benzene with "no HAP use"
case.
48
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minimum
HAP(s)
needed
SCC Tier 3
SCC Tier 3 Description
Comments
M
2460200000
Solvent Utilization;Miscellaneous Non-industrial:
Consumer and Commercial;All Household Products
profile is 3146 contains only nonzero
methanol.
any 1 HAP
2415000000
Solvent Utilization;Degreasing;All Processes/All
Industries
profile 8745 (non-legacy but composite made
up of a bunch of E-rated profiles )has M, B.
M
2401002000
Solvent Utilization;Surface Coating;Architectural
Coatings - Solvent-based
profile 3139 has only M
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,
Freedonia was used for M.
M
2465200000
Solvent Utilization;Miscellaneous Non-industrial:
Consumer;Household Products
M
2415300000
Solvent Utilization;Degreasing;All Industries: Cold
Cleaning
profile 8745 (non-legacy but composite made
up of a bunch of E-rated profiles )has M, B.
any 1 HAP
2401040000
Solvent Utilization;Surface Coating;Metal Cans:
SIC 341
profile 2408 has none. - no HAPs in NEI so
this SCC will not have any integrated sources
any 1 HAP
2401050000
Solvent Utilization;Surface Coating;Miscellaneous
Finished Metals: SIC 34 - (341 + 3498)
SPEC PROFILE 3127 has none - no HAPs in
NEI so this SCC will not have any integrated
sources
any 1 HAP
2401200000
Solvent Utilization;Surface Coating;Other Special
Purpose Coatings
profile 3138 has methanol. Not legacy.
0.11% aerosol coatings.
B
2461800000
Solvent Utilization;Miscellaneous Non-industrial:
Commercial;Pesticide Application: All Processes
3001 is speciation profile (not legacy) "D"
rating 2004. Calif. Testing for speciation
profile from 2000. Has NO benzene!
Benzene came from solvent utilization data
(Fredonia) for "other markets" for the year
1998.
M
2460800000
Solvent Utilization;Miscellaneous Non-industrial:
Consumer and Commercial;All FIFRA Related
Products
3145 has M only and iust a 0.01%
49
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For the alm_no_c3 sector, the integration criteria were (1) that the source had to have at least one
of the 4 HAPs and (2) that the sum of BAFM could not exceed the VOC emissions. The criteria
for this sector were less complex than the nonpt sector because it has much fewer source
categories.
We used the SMOKE feature to compute speciation profiles from mixtures of other profiles in
user-specified proportions. The combinations are specified in the GSPRO COMBO ancillary
file by pollutant (including pollutant mode, e.g., EXH VOC), state and county (i.e.,
state/county FIPS code) and time period (i.e., month).
We used this feature for onroad and nonroad mobile and gasoline-related related stationary
sources whereby the emission sources use fuels with varying ethanol content, and therefore the
speciation profiles require different combinations of gasoline, E10 an E85 profiles. Since the
ethanol content varies spatially (e.g., by state or county), temporally (e.g., by month) and by
modeling year (future years have more ethanol) the feature allows combinations to be specified
at various levels for different years.
3.1.3 Temporal processing configuration
Table 3-6 summarizes the temporal aspect of the emissions processing configuration. It
compares the key approaches we used for temporal processing across the sectors. We control the
temporal aspect of SMOKE processing through (a) the scripts L TYPE (temporal type) and
M TYPE (merge type) settings and (b) the ancillary data files described in Section 3.2.3. The
one change made from the v4 to the v4.2 platform is the treatment of the afdust sector. In the v4
platform we used "aveday" settings and no use of holidays such that every day in a specific
month had the same emissions. In the v4.2 platform, we used "week" settings and holidays and
used profiles which were day-of-week dependent for some categories, such as road dust and
tilling, where non-uniform profiles were being used for other pollutants associated with these
processes.
50
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Table 3-6. Temporal settings used for the platform sectors in SMOKE, v4.2 platform
Platform sector
short name
(see Table 2-1)
Inventory
resolution
Monthly
profiles
used?
Daily
temporal
approach 12
Merge
processing
approach 13
Process
Holidays as
separate days?
ptipm
daily &
hourly
all
all
yes
ptnonipm
annual
yes
mwdss
all
yes
othpt
annual
yes
mwdss
all
nonroad
monthly
mwdss
mwdss
yes
othar
annual
yes
mwdss
mwdss
aim no c3
annual
yes
mwdss
mwdss
seca c3
annual
yes
mwdss
mwdss
on noadj
monthly
week
week
yes
on_moves_startpm
monthly
week
week
yes
on moves runpm
monthly
week
week
yes
othon
annual
yes
week
week
nonpt
annual
yes
mwdss
mwdss
yes
ag
annual
yes
aveday
aveday
afdust
annual
yes
week
week
yes
biog
hourly
n/a
n/a
avefire
annual
yes
aveday
aveday
1 Definitions for processing resolution:
all = hourly emissions computed for every day of the year, inventory is already daily
week = hourly emissions computed for all days in one "representative" week, representing all weeks for each
month, which means emissions have day-of-week variation, but not week-to-week variation within the
month
mwdss= hourly emissions for one representative Monday, representative weekday, representative Saturday
and representative Sunday for each month, which means emissions have variation between Mondays,
other weekdays, Saturdays and Sundays within the month, but not week-to-week variation within the
month. Also Tuesdays, Wednesdays and Thursdays are treated the same.
aveday = hourly emissions computed for one representative day of each month, which means emissions for
all days of each month are the same.
2 Daily temporal approach refers to the temporal approach for getting daily emissions from the inventory
using the Temporal program. The values given are the values of the L TYPE setting.
3 Merge processing approach refers to the days used to represent other days in the month for the merge
step. If not "all", then the SMOKE merge step just run for representative days, which could include holidays
as indicated by the rightmost column. The values given are the values of the M TYPE setting.
In addition to the resolution, temporal processing includes a ramp-up period for several days
prior to January 1, 2005, which is intended to mitigate the effects of initial condition
concentrations. The same procedures were used for all grids, but with different ramp-up periods
for each grid:
36 km: 10 days (Dec 22 - Dec 31)
12 km (East): 3 days (Dec 29 - Dec 31)
For most sectors, our approach used the emissions from December 2005 to fill in surrogate
emissions for the end of December 2004. In particular, we used December 2005 emissions
51
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(representative days) for December 2004. For biogenic emissions, we processed December 2004
emissions using 2004 meteorology.
3.2 Emissions modeling ancillary files
In this section we summarize the ancillary data that SMOKE used to perform spatial allocation,
chemical speciation, and temporal allocation for the 2005v4.2 platform. The ancillary data files,
particularly the cross-reference files, provide the specific inventory resolution at which spatial,
speciation, and temporal factors are applied. For the 2005v4.2 platform, we generally applied
spatial factors by country/SCC, speciation factors by pollutant/SCC or (for combination profiles)
state/county FIPS code and month, and temporal factors by some combination of country, state,
county, SCC, and pollutant.
For the v4.2 platform, we updated the 2005v4 ancillary files in a few major areas:
1. We used new data for spatially allocating oil and gas emission sources
2. We assigned spatial, temporal and speciation profiles to parking area emissions for
additional vehicle types (new data from MOVES2010) and updated previous assignments
for some vehicle types (summarized in Table 3-14 and Table 3-155).
3. We updated the headspace VOC speciation profile we used for refueling.
4. We used a new profile for speciating PM2.5 from C3 marine emissions.
3.2.1 Spatial allocation data
As described in Section 3.1.1, we performed spatial allocation for a national 36-km domain, and
an Eastern 12-km domain. To do this, SMOKE used national 36-km and 12-km spatial
surrogates and a SMOKE area-to-point data file. For the U.S. and Mexico, we used the same
spatial surrogates as were used for the 2002v3 platform. For Canada we used a set of Canadian
surrogates provided by Environment Canada. The spatial data files we used can be obtained
from the files listed below; these are available from the 2002v3CAP (for US and Mexico) and
the 2005v4 CAP-BAFM (for Canada) platform websites listed at the end of Section 1. The oil
and natural gas surrogate files are posted at the 2005v4.1 website. For the v4.2 platform, all of
the relevant surrogate files can be found in a single consolidated zip file:
gridding_suirogates_2005v4_2.zip. This zip file contains the following information:
U.S. and Mexican surrogate files at 36-km spatial resolution
U.S. and Mexican surrogate files for surrogate files at 12 km spatial resolution
Canadian surrogate files at 36-km spatial resolution
Canadian surrogate files at 12-km spatial resolution
Updated oil and gas surrogate files at 36-km and 12-km spatial resolutions for the new oil
and gas surrogate (US) developed for the v4.1 platform
Additional information related to spatial allocation is found in this file:
ancillary_2005v4_2_smokeformat.zip: contains spatial related data included are the
grid description (GRIDDESC), surrogate description (SRGDESC), surrogate cross
reference file (AGREF), and area-to-point (ARTOPNT) file. This data is provided on the
2005v4.2 website under "2005 Emissions Data Files".
52
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The U.S., Mexican, and Canadian 12-km surrogates cover the entire CONUS domain, though
they are used directly as inputs for the two separate Eastern and Western Domains shown in
Figure 3-1. The SMOKE model windowed the Eastern and Western grids while it created these
emissions. The remainder of this subsection provides further detail on the origin of the data used
for the spatial surrogates and the area-to-point data.
3.2.1.1 Surrogates for U.S. emissions
There are 67 spatial surrogates available for spatially allocating U.S. county-level emissions to
the 36-km and 12-km grid cells used by the air quality model; 66 are the same as for the v4
platform, and one new surrogate, "Oil & Gas Wells, IHS Energy, Inc. and USGS" was added for
v4.2 which is discussed below. As described in Section 3.2.1.2, an area-to-point approach
overrides the use of surrogates for some sources. Table 3-7 lists the codes and descriptions of
the surrogates.
Table 3-7. U.S. Surrogates available for the 2005v4.2 platform.
Code
Surrogate Description
Code
Surrogate Description
N/A
Area-to-point approach (see 3.3.1.2)
515
Commercial plus Institutional Land
100
Population
520
Commercial plus Industrial plus Institutional
Golf Courses + Institutional +Industrial +
110
Housing
525
Commercial
120
Urban Population
527
Single Family Residential
130
Rural Population
530
Residential - High Density
Residential + Commercial + Industrial +
137
Housing Change
535
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
0.5 Residential Heating - Wood plus 0.5 Low
Professional/Technical plus General
165
Intensity Residential
555
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 J
585
Metals and Minerals Industrial
230
Rural Secondary Road Miles ;|
590
Heavy Industrial
240
Total Road Miles
595
Light Industrial
250
Urban Primary plus Rural Primary
596
Industrial plus Institutional plus Hospitals
255
0.75 Total Roadway Miles plus 0.25 Population
600
Gas Stations
260
Total Railroad Miles
650
Refineries and Tank Farms
270
Class 1 Railroad Miles
675
Refineries and Tank Farms and Gas Stations
Oil & Gas Wells, IHS Energy, Inc. and
280
Class 2 and 3 Railroad Miles
680
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
53
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Code
Surrogate Description
1 Code
Surrogate Description
330
Strip Mines/Quarries J
807
Navigable Waterway Miles
340
Land 1
810
Navigable Waterway Activity
350
Water
850
Golf Courses
400
Rural Land Area
860
Mines
500
Commercial Land
870
Wastewater Treatment Facilities
505
Industrial Land
880
Drycleaners
510
Commercial plus Industrial
890
Commercial Timber
We did not use all of the available surrogates to spatially allocate sources in the v4.2 platform;
that is, some surrogates in Table 3-7 were not assigned to any SCCs.
The creation of surrogates and shapefiles for the U.S. via the Surrogate Tool was discussed in the
2002v3 platform documentation and is not repeated here. This same tool was used for the new
surrogate 680. "Oil & Gas Wells, IHS Energy, Inc. and USGS"
The new surrogate "Oil & Gas Wells, IHS Energy, Inc. and USGS" was developed for oil and
gas SCCs, which had previously (in the v4 platform) used surrogate 585. The data reflect data
through 10/1/2005. The underlying data for this surrogate is a grid of one-quarter square mile
cells containing an attribute to indicate whether the wells within the cell are predominantly oil-
producing, gas-producing, both oil- and gas-producing, or the wells are dry, or their production
status is unknown. The well information was initially retrieved from IHS Inc.'s PI/Dwights
PLUS Well Data on CD-ROM, which is a proprietary commercial database containing
information for most oil and gas wells in the U.S. Cells were developed as a graphic solution to
overcome the problem of displaying proprietary well data. No proprietary data are displayed or
included in the cell maps and oil and gas quarter mile cell maps.
The spatial cross-reference file was also updated to assign onroad off-network (parking area)
emissions from the MOVES2010 model, new to the 2005v4 platform, were allocated as shown in
Table 3-8.
Table 3-8. Surrogate assignments to new mobile categories in the 2005v4 platform
SCC Description
SlIITOUillC
2201001350 Light Duty Gas Vehicles- parking areas rural
2201002350 Light Duty Gas Trucks 1&2- parking areas rural
2201004350 Light Duty Gas Trucks 3&4- parking areas rural
Rural population (same as rural
local roads), code= 130
2201001370 Light Duty Gas Vehicles- parking areas urban
2201002370 Light Duty Gas Trucks 1&2- parking areas urban
2201004370 Light Duty Gas Trucks 3&4- parking areas urban
Urban population (same as urban
local roads), code =120
2201070350 Heavy Duty Gasoline Vehicles 2B through 8B & Buses
(HDGV)- parking areas rural
2201070370 Heavy Duty Gasoline Vehicles 2B through 8B & Buses
(HDGV)- parking areas urban
Commercial plus Industrial plus
Institutional, code = 520
54
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3.2.1.2 Allocation method for airport-related sources in the U.S.
There are numerous airport-related emission sources in the 2005 NEI, such as aircraft, airport
ground support equipment, and jet refueling. Unlike the 2002v3 platform in which most of these
emissions were contained in sectors with county-level resolution - aim (aircraft), nonroad
(airport ground support) and nonpt (jet refueling), the 2005 platform includes the aircraft
emissions as point sources. As shown in Table 2-1, aircraft emissions are part of the ptnonipm
sector, since the 2005v2 inventory included them as point sources.
Thus, for the 2005 platform, we used the SMOKE "area-to-point" approach for only airport
ground support equipment (nonroad sector), and jet refueling (nonpt sector). The approach is
described in detail in the 2002 platform documentation.
We used nearly the same ARTOPNT file to implement the area-to-point approach as was used
for the CAP and HAP-2002-Based platform. This was slightly updated from the CAP-only 2002
platform by further allocating the Detroit-area airports into multiple sets of geographic
coordinates to support finer scale modeling that was done under a different project. We chose to
retain the updated file for the 2005 platform. This approach is the same in the v4.2 and v4
platforms.
3.2.1.3 Surrogates for Canada and Mexico emission inventories
We used an updated set of surrogates for Canada to spatially allocate the 2006 Canadian
emissions for the 2005v4 platform. The updated set completely replaced the 2002v3 platform
surrogates for allocating the 2006 province-level Canadian emissions.
The updated surrogate data provided in the 2005v4 zip files and described in Table 3-9 came
from Environment Canada. They provided the surrogates and cross references; the surrogates
they provided were outputs from the Surrogate Tool (previously referenced). Per Environment
Canada, the surrogates are based on 2001 Canadian census data. We changed the 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 '984' (construction industries) were changed to '907'
(construction services) because the surrogate fractions in 984, 978 and 985 did not sum to 1. We
also changed codes for surrogates other than population that did not begin with the digit "9".
The same surrogates were used for the 12-km domains as were used for the 36-km domain.
Table 3-9. Canadian Spatial Surrogates for 2005-based platform Canadian Emissions (v4.2
unchanged from v4)
Surrogate
description
Filename of 2005
Platform Surrogate
Surrogate
description
Filename of 2005
Platform Surrogate
Population
CA 100 NOFILL.txt
asphalt
CA 951 NOFILL.txt
Total dwelling
CA 901 NOFILL.txt
cement
CA 952 NOFILL.txt
Agriculture and
Forestry and Fishing
CA_902_NOFILL.txt
chemical
CA 953 NOFILL.txt
Waste Management
Service
CA_903_NOFILL.txt
commfuelcomb
CA 954 NOFILL.txt
55
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Surrogate
description
Filename of 2005
Platform Surrogate
Surrogate
description
Filename of 2005
Platform Surrogate
Upstream Oil and Gas
(UOG)
CA_904_NOFILL.txt
downstream petroleum
CA 955 NOFILL.txt
Mining and Oil and Gas
services
CA_905_NOFILL.txt
egu
CA 956 NOFILL.txt
Manufacturing services
CA 906 NOFILL.txt
grain
CA 957 NOFILL.txt
Construction services
CA 907 NOFILL.txt
manufacturing
CA 958 NOFILL.txt
Transportation of
Passengers and goods
CA_908_NOFILL.txt
mining
CA 959 NOFILL.txt
Electric and Gas and
Water utilities
CA_909_NOFILL.txt
oilgas distibution
CA 960 NOFILL.txt
Wholesaling
Merchandise services
CA_910_NOFILL.txt
smelting
CA 961 NOFILL.txt
Retailing Merchandise
services
CA_911_NOFILL.txt
waste
CA 962 NOFILL.txt
Government Services
CA 915 NOFILL.txt
wood
CA 963 NOFILL.txt
All Sales
CA 920 NOFILL.txt
asphalt industries
CA 971 NOFILL.txt
Intersection of
AGRFORFISH and
MANUFACT
CA_921_NOFILL.txt
cement industries
CA 972 FILL.txt
Intersection of Forest
and Housing
CA_922_NOFILL.txt
chemical industries
CA 973 FILL.txt
Intersection of
MININGOILG and
MANUFACT
CA_923_NOFILL.txt
commercial fuel
combustion
CA 974 FILL.txt
Intersection of
UTILITIES and
DWELLING
CA_924_NOFILL.txt
downstream petroleum
industries
CA 975 FILL.txt
Intersection of
CONSTRUCTION and
DWELLING
CA_925_NOFILL.txt
Electric utilities
CA 976 FILL.txt
Intersection of
PUBADMIN and
DWELLING
CA_926_NOFILL.txt
grain industries
CA 977 FILL.txt
Commercial Marine
Vessels
CA_928_NOFILL.txt
manufacturing
industries1
CA 978 FILL.txt
HIGHJET
CA 929 NOFILL.txt
mining industries
CA 979 FILL.txt
LOWMEDJET
CA 930 NOFILL.txt
smelting industries
CA 981 FILL.txt
OTHERJET
CA 931 NOFILL.txt
waste management
CA 982 NOFILL.txt
CANRAIL
CA 932 NOFILL.txt
construction industries1
CA 984 NOFILL.txt
LDGV
CA_934_NOFILL.txt
construction and
mining1
CA 985 NOFILL.txt
PAVED ROADS
CA 941 NOFILL.txt
TOTALBEEF2
CA 986 NOFILL.txt2
UNPAVED ROADS
CA_942_NOFILL.txt
TOTALPOUL2
CA 987 NOFILL.txt2
Oil Sands
CA 950 NOFILL.txt
TOTALSWIN2
CA 988 NOFILL.txt2
TOTALFERT2
CA 989 NOFILL.txt2
1: Not used because fractions did not sum to 1;
2: Surrogates 986, 987, 988 and 989 were originally numbered by Canada as 611, 615, 620 and 65, respectively. We changed the
numbers so that all Canadian surrogates would begin with "9".
The Mexican emissions and single surrogate (population) are the same in the v4.2 platform as
were used in the 2005v4 and 2002 platforms.
56
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3.2.2 Chemical speciation ancillary files
The following data files, provided at the 2005v4.2 website (see the end of Section 1), contain the
SMOKE inputs used for chemical speciation of the inventory species to the air quality model
species. SMOKE environment variable names, used in the file names, are shown using capital
letters in parentheses:
ancillary_2005v4_2_smokeformat.zip: inventory table (INVTABLE), NONHAPVOC
emissions calculation exclusions file (NHAPEXCLUDE), speciation cross references
(GSREF), speciation VOC-to-TOG conversion factors (GSCNV), speciation profiles
(GSPRO), and combined, monthly speciation profiles (GSPROCOMBO).
ancillary_2005v4_2_futureyear_smokeformat.zip: speciation-related files associated
with the future-year speciation changes.
The following subsections explain these SMOKE input files.
3.2.2.1 INVABLE and NHAPEXCLUDE
The INVTABLE and NHAPEXCLUDE SMOKE input files have a critical function in the VOC
speciation process for emissions modeling cases utilizing HAP-CAP integration, as is done for
the 2005v4.2 platform.
We prepared two different INVTABLE files to use with different sectors of the platform. For
sectors in which we chose no integration across the entire sector (see Table 3-5), we created a
"no HAP use" INVTABLE that set the "KEEP" flag to "N" for B AFM pollutants. Thus, any
BAFM pollutants in the inventory input into SMOKE would be dropped. This approach both
avoids double-counting of these species and assumes that the VOC speciation is the best
available approach for these species for the sectors using the approach. The second INVTABLE,
used for sectors in which one or more sources are integrated, causes SMOKE to keep the BAFM
pollutants and indicates that they are to be integrated with VOC (by setting the "VOC or TOG
component" field to "V" for all four HAP pollutants.
We also prepared sector-specific NHAPEXCLUDE files that provide the specific sources that
are excluded from integration (see Table 3-5).
3.2.2.2 GSPRO, GSPRO_COMBO, GSREF and GSCNV
For VOC speciation, we generated the following SMOKE-ready profiles for the CB05 chemical
mechanism using the Speciation Tool (Eyth, 2006):
TOG-to-model species (used only for no-integrate sources)
NONHAPTOG-to-model species (used only for the integrate sources)
TOG-to-BENZENE (used only for no-integrate sources)
We added speciation profile entries that simply map NEI emissions of benzene, acetaldehyde,
formaldehyde and methanol to the model species BENZENE, ALD2, FORM and METHANOL,
respectively. These profiles were used only for the integrate sources. Note that we process the
integrate and no-integrate sources using the same GSREF and GSPRO files. Thus, to avoid
double counting of these HAP species, we removed BAFM pollutants for all no-integrate sources
57
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in the inventory. If the entire sector was no-integrate, then we were able to remove these in
SMOKE (by using "N" in the INVTABLE) but if a sector was partially integrated, then we
needed to remove these HAPS from the actual inventory input to SMOKE, but only for the no
HAP use, no-integrate sources.
In addition to the speciation profiles, the Speciation Tool generates the SMOKE-ready speciation
conversion files (GSCNV). We generated two of these: one containing profile-specific VOC-to-
TOG conversion factors and the other containing profile-specific NONHAPVOC-to-
NONHAPTOG conversion factors.
The TOG and PM2.5 speciation factors that are the basis of the chemical speciation approach
were developed from the SPECIATE4.2 database which is the EPA's repository of TOG and PM
speciation profiles of air pollution sources. However, a few of the profiles we used in the v4.2
platform will be published in SPECIATE4.3 after the release of this documentation.
The SPECIATE database development and maintenance is a collaboration involving the EPA's
ORD, OTAQ, and the EPA's Office of Air Quality Planning and Standards (OAQPS), and
Environment Canada (EPA, 2006a). The SPECIATE database contains speciation profiles for
TOG, speciated into individual chemical compounds, VOC-to-TOG conversion factors
associated with the TOG profiles, and speciation profiles for PM2.5. The database also contains
the PM2.5 speciated into both individual chemical compounds (e.g., zinc, potassium, manganese,
lead), and into the "simplified" PM2.5 components used in the air quality model. These
simplified components are:
PS04 : primary particulate sulfate
PN03: 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 v4.2 platform we updated the PM2.5 profile used for category 3
marine vessels burning residual oil to use the profile: Marine Vessel - Main Engine - Heavy
Fuel Oil which will be published in SPECIATE4.3. This profile was compiled from data
published in Emission Measurements from a Crude Oil Tanker at Sea, Environ. Sci. Technol.
2008, 42, 7098-7103. Previously the Draft Residual Oil Combustion - Simplified (92072) was
used. The SCCs affected were:
2280003000 Mobile Sources;Marine Vessels, Commercial;Residual;Total, All Vessel Types
2280003010 Mobile Sources;Marine Vessels, Commercial;Residual;Ocean-going Vessels
2280003100 Mobile Sources;Marine Vessels, Commercial;Residual;Port emissions
2280003200 Mobile Sources;Marine Vessels, Commercial;Residual;Underway emissions
The difference between the two profiles is provided in Table 3-10, and shows that the new
profile produces much more organic carbon and less elemental carbon, sulfate, and other PM2.5.
58
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Table 3-10. Differences between two profiles used for commercial marine residual oil
Pollutant
Species
Split factors new c3 profile
92200 used for v4.2
Split factors residual oil
combustion
92072, used for v4
PM2 5
PEC
0.005
0.01
PM2 5
PMFINE
0.5022
0.54
PM2 5
PN03
0
0
PM2 5
POC
0.1125
0.01
PM2 5
PS04
0.3803
0.44
We also updated the bituminous coal profile, 92095, which we had previously used for only a
single nonpoint SCC (2101002000) with the sub-bituminous profile 92084, which was used for
all other coal combustion SCCs. We replaced profile 92095 with 92084 for consistency. Table
3-11 shows the differences are shown below, though these are quite small and represent only a
minor change to the SMOKE results:
Table 3-11. Differences between two profiles used for coal combustion
Pollutant
Species
Split factors sub-
bituminous 92084
Split factors
bituminous 92095
PM2 5
PEC
0.0188
0.01696
PM2 5
PMFINE
0.8266
0.827928
PM2 5
PN03
0.0016
0.00208
PM2 5
POC
0.0263
0.026307
PM2 5
PS04
0.1267
0.126725
We made other updates to profile assignments for the SCCs shown in Table 3-12 below as
compared to the 2002 platform. These updates were kept for the v4.2 platform.
Table 3-12: PM2.5 speciation profile updates assignments for the v4 platform
SCC
New
Profile
Code
Pollutant
Profile Name
39900501
92025
PM25
Distillate Oil Combustion Source Type: Distillate Oil
Combustion
49090021
92025
PM25
Distillate Oil Combustion Source Type: Distillate Oil
Combustion
30890002
92072
PM25
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/S02 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
59
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Key changes to the TOG profiles for the v4.2 platform from the 2005v4 platform are as follows:
Used new headspace profiles for EO (no ethanol gasoline) and E10 (10% ethanol
gasoline), which will be published in SPECIATE4.3. Profile 8762 is Gasoline Headspace
Vapor using 0% Ethanol - Composite Profile and Profile 8763 is Gasoline Headspace
Vapor using 10% Ethanol - Composite Profile. In 2005, only the E0 profile is used. This
was an oversight since we could have used the same combinations of profiles of E0
exhaust E10 exhaust (which are also the same combinations of E10 evaporative and E10
evaporative) that we used for 2005. We did, however use consistent combinations
(E0/E10) in future-year modeling for the headspace profiles as the evaporative and
exhaust combinations.
Added the fuel-specific VOC profiles for the new parking area SCCs generated due to the
fact that MOVES2010 was used for all vehicle types in the v4.2 platform. A summary of
the assignments of all profiles (speciation, temporal and spatial surrogates) is provided in
Table 3-14 for gasoline vehicles and Table 3-155 for diesel vehicles.
Table 3-13 provides a summary of the 2005 speciation approach for mobile and other fuel-
related sources. It shows the updated profiles that form the 2005 combinations. The headspace
profile, 8762 is a new profile for the v4.2 platform, and, is used for other nonroad refueling and
other fuel-related stationary source emission categories in 2005.
Table 3-13. Summary of VOC speciation profile approach by sector for 2005
Inventory
type and
mode
VOC speciation
approach
for fuels
VOC
Profile
Codes
2005
sectors
Mobile onroad and nonroad
Exhaust
E0 and E10
combinations
(excludes Tier 2)
8750
8751
onnoadj
nonroad
Mobile onroad and nonroad
Evaporative
E0 and E10
combinations
8753
8754
onnoadj
nonroad
Mobile nonroad Refueling
Stationary (no mode assigned
to VOC): Portable Fuel
Containers, bulk plant -to-
pump, refinery-to-bulk
terminal
E0
8762
Nonroad
nonpt
In future years, different profile combinations and a different headspace profile is used, due to
the influx of greater quantities of ethanol in fuels. Changes to the above profiles for future-year
scenarios will be discussed in more detail in the documentation of future-year emissions
development for the rule or application of interest. In summary, we utilized additional profiles in
the combinations that is appropriate. The profiles we added were Tier 2 profiles for E0 and E10
and an E10 headspace profile.
60
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Speciation profiles for use with BEIS are not included in SPECIATE. The 2005 platform uses
BEIS3.14, which includes a new species (SESQ) that was not in BEIS3.13 (the version used for
the 2002 platform). Thus we added this species (it is mapped to the model species SESQT) to
the set of profiles that we had been using in the 2002 platform. The profile code associated with
BEIS3.14 profiles for use with CB05 uses the same as in the 2002 platform: "B10C5."
3.2.3 Temporal allocation ancillary files
The emissions modeling step for temporal allocation creates the 2005 hourly emission inputs for
the air quality model by adjusting the emissions from the inventory resolution (annual, monthly,
daily or hourly) that are input into SMOKE. The temporal resolution of each of the platform
sectors prior to their input into SMOKE is included in the sector descriptions from Table 2-1 and
repeated in the discussion of temporal settings in Table 3-6.
The monthly, weekly, and diurnal temporal profiles and associated cross references used to
create the 2005 hourly emissions inputs for the air quality model were generally based on the
temporal allocation data used for the 2002v3 platform. For the v4 and v4.2 platforms, we added
new profile assignments for SCCs in the 2005 inventory that were not in the 2002 inventory, and
we updated the profiles used for ptipm sources without CEM data to represent the year 2005.
The following data file, provided at the 2005v4 website (see the end of Section 1), contains the
files used for temporal allocation of the inventory emissions. SMOKE environmental variable
names, used in the file names, are shown in capital letters in parentheses:
ancillary_2005v4_2_smokeformat.zip: includes temporal cross reference files used
across all inventory sectors (ATREF, MTREF, and PTREF) and for ptipm sector (used
for electric generating units) for the evaluation case (PTREF) and, temporal profiles
(ATPRO, MTPRO, and PTPRO)
The starting point for our temporal profiles was the 2002 platform. The remainder of this section
discusses the development of the new temporal profiles or profile assignments used in the
2005v4 platform.
Canadian emissions
The profiles assignments for the Canadian 2006 inventory were provided by Environment
Canada along with the inventory. They provided profile assignments that rely on the existing set
of temporal profiles in the 2002 platform. For point sources, they provided profile assignments
by PLANTID.
WRAP Oil and Gas Inventory Profiles
The WRAP 2005 oil and gas inventory SCCs utilized uniform monthly and day of week profiles
(codes 262 and 7, respectively) and an hourly profile (code 26) that put emissions in every hour,
but, weighted towards the day light hours.
61
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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 whole year and all units in each state.
We calculated the diurnal factors using CEM SO2 and NOx emissions and heat input. We
computed SO2 and NOx-specific factors from the CEM data for these pollutants. All other
pollutants used factors created from the hourly heat input data. We assigned the resulting
profiles by state and pollutant.
Area Fugitive Dust Profiles (afdust)
The monthly and day of week temporal profiles for several fugitive dust sources were changed
from uniform in the v4 platform (code 262 and 7 respectively) to a summer peak/winter
minimum (monthly code 22) and weekend minimum (code 18) in the v4.2 platform. These
sources include fugitive dust from industrial unpaved roads and construction, residential and
industrial/commercial/institutional construction, road construction, mining and quarrying, and
agricultural production (planting, tilling, harvesting, and loading).
Diurnal weekday and weekend temporal profiles were changed from a simple bell curve profile
(code 26) for all categories in v4 to a more dynamic profile with a morning and afternoon peak
(code 2013) for paved and unpaved road dust in v4.2. Diurnal temporal profiles were changed to
a zero nighttime, daytime plateau profile (code 27) for all agricultural production sources in v4.2.
Agricultural Burning Profiles in CENRAP States (nonpt)
The uniform monthly, day of week, and diurnal profiles (codes 262, 7, and 24 respectively) in
the v4 platform for all agricultural burning emissions were modified in the v4.2 platform to state-
specific monthly, day of week, and diurnally-varying profiles for these CENRAP region states:
Arkansas, Iowa, Kansas, Louisiana, Minnesota, North Dakota, Nebraska, Oklahoma, and Texas.
Residential and Commercial/Institutional Natural Gas. LPG. and Kerosene Combustion (nonpt)
Uniform monthly (code 262) profiles in platform v4 for residential and commercial/institutional
liquified petroleum gas (LPG), natural gas, and kerosene sources were changed to monthly
varying with a strong winter peak in platform v4.2.
Onroad Parking Area Profiles
The SCCs and descriptions, along with the assignments chosen are shown in Table 3-14
(gasoline vehicles) and Table 3-155 (diesel vehicles). Figure 3-3 and Figure 3-4 show the
diurnal profiles referred to in the tables.
62
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Figure 3-3. Diurnal Profiles based on road type (use local for "start") and whether the road is
urban versus rural
Weekend Diurnal (same codes)
0.9
0.7
0.6
0.5
0.4
0.3
0.2
0 2 4 6 8 10 12 14 16 18 20 22
Rural Local: code = 2006
Weekday Diurnal
Urban Local: code = 2012
0.9
0.7
0.6
0.5
0.4
0.3
0.2
o 2
4 6
8 10 12 14 16 18 20 22
Hour of Day
Figure 3-4. Diurnal temporal profile for HDDV 2B through 8B at Parking areas
700
Weekend and Weekday diurnal profiles used for HDDV
{exce pt school/transit b uses)
At urban and rural parking areas (i.e., idling emissions)
profile code =3000
600
500
400
300
200
100
hrO hrl hr2 hr3 hr4 hr5 hr6 hr7 hr8 hr9 hrlO hrll hrl2 hrl3 hrl4 hrl5 hrl6 hrl7 hrl8 hrl9 hr20 hr21 hr22 hr23
63
-------
Table 3-14. Summary of spatial surrogates, temporal profiles, and speciation profiles used by gasoline vehicle types for the onroad
parking area-related SCCs.
a\soi.ini: m:iik i.i: n pi s
1 emporul
Profile:
Monthly
Variation
lemporul Profile:
li'inporul Profile:
Speciation Profile
2201001350
Rural
Not
Use same as profile
Use same speciation profiles as what is used for LD GAS
Light Duty Gas
Population
applicable
RURAL LD values are:
as rural local
vehicles on the other roadway types. *
Vehicles- parking
(same as
-
Mon-Fri 12.1% 12.1%
roads
i.e.:
areas rural
rural local
inventory
12.1% 12.1% 18.3%
(Rdtype=210).
EVP__VOC: COMBO of 8753 (Gasoline Vehicle -
roads)
contains
Sat/Sun: 15.3% 18.3%
Code = 2006 (see
Evaporative emission - Reformulated gasoline) & 8754
2201020350 Light
130
monthly
Figure 3-3, reddish
(Gasoline Vehicle - Evaporative emission - E10 ethanol
Duty Gas Trucks
emissions
curve)
gasoline) Note that these are the combinations used in
1&2- parking areas
Weekly code (for
2005. In some cases, future-year profiles may also include
rural
SMOKE) =20021
8755 (Gasoline Vehicle - Evaporative emission - E85)
EXH__VOC: COMBO of 8750&8751 These
2201040350 Light
combinations are used in 2005. In some cases, future-year
Duty Gas Trucks
profiles may also include combinations of 8752 (E85),
3&4- parking areas
8756 (tier 2 exhaust, E0), 8757 (tier 2 exhaust, E10)
rural
EXH PM2.5 not needed because OTAQ supplies pre-
2201080370
speciated emissions
Motorcycles (MC) -
BRK_PM2.5 and TIR_PM2.5 use same as other roadways
parking areas rural
(92009 and 92087, respectively)
2201001370
Urban
Not
URBAN LD values are:
Use same as profile
Same as above
Light Duty Gas
Population
applicable
Mon-Fri
as urban local
Vehicles- parking
(same as
-
14.8% 14.8% 14.8% 14.8%
roads.
areas urban
urban local
inventory
16.0%
(Rdtype=330).
roads)
contains
Sat Sun 13.4% and 11.6%
2201020370 Light
120
monthly
Code = 2012 (see
Duty Gas Trucks
emissions
Weekly code (for
Figure 3-3, yellow
1&2- parking areas
SMOKE) =20031
curve)
urban
2201040370 Light
Duty Gas Trucks
3&4- parking areas
urban
64
-------
c;\soi.ini: \t.iik i.i: n pi s
Temporal
Prc.llk-:
Mon(hl\
1i iii|kii .il I'lnIlk':
1 ciiipiiral Piulik-:
2201080370
Motorcycles (MC) -
parking areas rural
2201070350
Heavy Duty
Gasoline Vehicles
2B through 8B &
Buses (HDGV)-
parking areas rural
Commercial
plus
Industrial
plus
Institutional
(code = 520)
Not
applicable
inventory
contains
monthly
emissions
RURAL HD values are:
Mon-Fri
16.8% 16.8% 16.8% 16.8%
15.9%
Sat Sun 8.8% and 8.8%
Weekly code (for
SMOKE) =20022
Use same as profile
rural local roads.
Code = 2006 (see
Figure 3-3, reddish
curve)
Same as above
2201070370
Heavy Duty
Gasoline Vehicles
2B through 8B &
Buses (HDGV)-
parking areas urban
Same as
above
Not
applicable
inventory
contains
monthly
emissions
URBAN HD values are:
Mon-Fri
17.7% 17.7% 17.7% 17.7%
17.7%
Sat Sun 7% and 5%
Weekly code (for
SMOKE) =20032
Use same as profile
on urban local
roads.
Code = 2012 (see
Figure 3-3, yellow
curve)
Same as above
65
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Table 3-15. Summary of spatial surrogates, temporal profiles, and speciation profiles used by diesel vehicle types for the onroad
parking area-related SCCs from MOVES2010.
mr.sr.i.NT.iiK 1.1: n pi s
Temporal
Profile:
Muni lil\
\ .iri.ilmii
Temporal Profile:
Temporal Profile:
Diurnal variation
2230001350 Light Duty Diesel
Vehicles (LDDV)- parking areas
rural
2230060350 Light Duty Diesel
Trucks 1 through 4 (M6) (LDDT)
)- parking areas rural
Rural
Population
(same as rural
local roads)
130
Not
applicable
- inventory
contains
monthly
emissions
RURAL LD values are:
Mon-Fri 12.1% 12.1%
12.1% 12.1% 18.3%
Sat/Sun: 15.3% 18.3%
Weekly code (for SMOKE)
=20021
Rationale: choose same
weekend/weekday variation
for all Light Duty Vehicles
on all rural road types
Use same as profile as
rural local roads
(Rdtype=210).
Code = 2006 (see Figure
3-3, reddish curve)
Rationale: choose same
diurnal profile for all
vehicles (except HDDV
2B to 8B) for all rural
parking areas (which is the
profile used for rural local
roads)
Use same speciation profiles as what is used for LD
DIESEL vehicles, irrespective of road type,
i.e.:
EVP VOC: ZERO emissions (placeholder profile is
required by SMOKE: 4547 (Gasoline Headspace Vapor
- Circle K Diesel - adjusted for oxygenates)
EXH VOC: 4674 (Diesel Exhaust - Medium Duty
Trucks)
PM2.5 : ZERO emissions ->not needed since OTAQ
supplies pre-speciated emissions. Placeholder profile is
required by SMOKE: 92042 (LDDV Exhaust -
Simplified)
BRK_PM2.5 and TIR_PM2.5 use same as other
roadways (92009 and 92087, respectively)
2230001370 Light Duty Diesel
Vehicles (LDDV)- parking areas
urban
2230060370 Light Duty Diesel
Trucks 1 through 4 (M6) (LDDT)
)- parking areas urban
URBAN
Population
(same as
urban local
roads)
120
Not
applicable
- inventory
contains
monthly
emissions
URBAN LD values are:
Mon-Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%
Weekly code (for SMOKE)
=20031
Rationale: choose same
weekend/weekday variation
for all Light Duty Vehicles
on urban road types
Use same as profile as
urban local roads.
(Rdtype=330).
Code = 2012 (see Figure
3-3, yellow curve
Rationale: choose same
diurnal profile for all
vehicles (except HDDV
2B to 8B) for all rural
parking areas (which is the
profile used for rural local
roads)
Same as above
66
-------
miM I. YI IIK 1.1.
n pis
**11 rriiii-H*."
Temporal
Profile:
Miuillih
\ .i ri.i I ii hi
Tempo nil Profile:
Temporal Profile:
Diurnal variation
2230071350 Heavv Dutv 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 & SB-
parking areas rural
Rural primary
roads
code=210
Rationale:
most idling
will occur at
truckstops
Not
applicable
- inventory
contains
monthly
emissions
RURAL HD values are:
Mon-Fri
16.8% 16.8% 16.8% 16.8%
15.9%
Sat Sun 8.8% and 8.8%
Weekly code (for SMOKE)
=20022
Construct new profile
CODE=3000 which is low
at daytime and high at
night-time (11pm to 2am)
See Figure 3-4
Use same speciation profiles as what is used for HD
DIESEL vehicles, irrespective of road type.
i.e.:
EVP VOC: ZERO emissions (placeholder profile is
required by SMOKE: 4547 (Gasoline Headspace Vapor
- Circle K Diesel - adjusted for oxygenates)
EXH VOC: 4674 (Diesel Exhaust - Medium Duty
Trucks)
PM2.5: ZERO emissions ->not needed since OTAQ
supplies pre-speciated emissions. Placeholder profile is
required by SMOKE: 92035 (HDDV Exhaust -
Simplified)
BRK_PM2.5 and TIR_PM2.5 use same as other
roadways (92009 and 92087, respectively)
2230071370 Heavy Duty Diesel
Vehicles (HDDV) Class 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
URBAN
primary roads
code=200
Rationale:
most idling
will occur at
truckstops
Not
applicable
- inventory
contains
monthly
emissions
URBAN LD values are:
Mon-Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%
Weekly code (for SMOKE)
=20031
Construct new profile
CODE=3000 which is low
at daytime and high at
night-time (11pm to 2am)
See Figure 3-4
Same as above
2230074370 Heavy Duty Diesel
Vehicles (HDDV) Class 8A & SB-
parking areas urban
67
-------
diim i n i nk i.i: n pi s
S('('».V. Description
Surrogate
Tempo nil
Profile:
Monthly
Variation
Temporal Profile:
l);i\ ol°Week Yiiriiilion
Temporal Profile:
Diurnal \arialion
Speciation Profile
2230075350 Heavy Duty Diesel
Buses (School & Transit) - parking
areas rural
Rural
Population
(same as rural
local roads)
130
Not
applicable
- inventory
contains
monthly
emissions
USE URBAN LD values:
Mon-Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%
Weekly code (for SMOKE)
=20031
Rationale: these vehicles
follow profile of LD vehicles
better than HD; day of week
variation should more
closely follow urban (higher
weekday than weekend)
Use same as profile as
rural local roads
(Rdtype=210).
Code = 2006 (see Figure
3-3, reddish curve)
Rationale: choose same
diurnal profile for all
vehicles (except HDDV
2B to 8B) for all rural
parking areas (which is the
profile used for rural local
roads)
Same as above
2230075370 Heavy Duty Diesel
Buses (School & Transit) - parking
areas urban
URBAN
Population
(same as
urban local
roads)
120
Not
applicable
- inventory
contains
monthly
emissions
USE URBAN LD values:
Mon-Fri
14.8% 14.8% 14.8% 14.8%
16.0%
Sat Sun 13.4% and 11.6%
Weekly code (for SMOKE)
=20031
Use same as profile as
urban local roads.
(Rdtype=330).
Code = 2012 (see Figure
3-3, yellow curve
Rationale: choose same
diurnal profile for all
vehicles (except HDDV
2B to 8B) for all rural
parking areas (which is the
profile used for rural local
roads)
Same as above
68
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4 Development of 2012 and 2014 Base-Case Emissions
This section describes the methods we used for developing the 2012 and 2014 future-year base-case
emissions. The year 2012 source apportionment scenarios and the 2014 EGU remedy (i.e., "control") case
are discussed in Sections 5 and 6, respectively. The ancillary input data in the future-year scenarios are very
similar to those used in the 2005 base case except for the speciation profiles used for gasoline-related
sources, which change in the future to account for increased ethanol usage in gasoline. Table B-l of
Appendix B is a table of differences between these ancillary input data between the 2005 base case and these
future-year scenarios. Appendix B also provides the values for the main parameters used in the emissions
modeling cases in Table B-2. The specific speciation profile changes are discussed in Sections 4.2.8 and
4.3.5. A list of inventory datasets used for this and all cases is provided in Appendix C.
The future base-case projection methodologies vary by sector. The 2012 and 2014 base cases represent
predicted emissions in the absence of any further controls beyond those Federal and State measures already
promulgated before emissions processing on the Transport Rule began in December, 2010. For EGU
emissions (ptipm sector), the emissions reflect state rules and federal consent decrees through December 1,
2010. For mobile sources (on noadj, onmovesrunpm, and onmovesstartpm sectors), all national
measures for which data were available at the time of modeling have been included. The future base-case
scenarios do reflect projected economic changes and fuel usage for EGU and mobile sectors. For nonEGU
point (ptnonipm sector) and nonpoint stationary sources (nonpt, ag, and afdust sectors), local control
programs that might have been necessary for areas to attain the 1997 PM2.5 NAAQS annual standard, 2006
PM NAAQS (24-hour) standard, and the 1997 ozone NAAQS are generally not included in the future base-
case projections for most states. One exception are some NOx and VOC reductions associated with the New
York, Virginia, and Connecticut State Implementation Plans (SIP), which were added as part of the
comments received from the Transport Rule Proposal and a larger effort to start including more local control
information on stationary non-EGU sources; this is described further in Section 4.2. The following bullets
summarize the projection methods used for sources in the various sectors, while additional details and data
sources are given in Table 4-1.
IPM sector (ptipm): Unit-specific estimates from IPM, version 4.10.
Non-IPM sector (ptnonipm): Projection factors and percent reductions reflect Transport Rule
comments and emission reductions due to control programs, plant closures, consent decrees and
settlements, and 1997 and 2001 ozone State Implementation Plans in NY, CT, and VA. We also used
projection approaches for point-source livestock, and aircraft and gasoline stage II emissions that are
consistent with projections used for the sectors that contain the bulk of these emissions. Terminal
area forecast (TAF) data aggregated to the national level were used for aircraft to account for
projected changes in landing/takeoff activity. Year-specific speciation was applied to some portions
of this sector and is discussed in Section 4.2.8.
Average fires sector (avefire): No growth or control.
Agricultural sector (ag): Projection factors for livestock estimates based on expected changes in
animal population from 2005 Department of Agriculture data; no growth or control for NH3
emissions from fertilizer application.
Area fugitive dust sector (afdust): Projection factors for dust categories related to livestock estimates
based on expected changes in animal population; no growth or control for other categories in this
sector.
69
-------
Remaining Nonpoint sector (nonpt): Projection factors that implement Transport Rule Proposal
comments and reflect emission reductions due to control programs. Residential wood combustion
projections based on growth in lower-emitting stoves and a reduction in higher emitting stoves. PFC
projection factors reflecting impact of the final Mobile Source Air Toxics (MSAT2) rule. Gasoline
stage II projection factors based on National Mobile Inventory Model (NMIM)-estimated VOC
refueling estimates for future years. Oil and gas projection estimates are provided for the non-
California WRAP states as well as Oklahoma and Texas. Year-specific speciation was applied to
some portions of this sector and is discussed in Section 4.2.8.
Nonroad mobile sector (nonroad): Other than for California, this sector uses data from a run of
NMIM that utilized the NR05d-Bond-final version of NONROAD (which is equivalent to
NONROAD2008a), using future-year equipment population estimates and control programs to the
years 2012 and 2015 and using national level inputs. Year 2014 emissions were created by
interpolating 2012 and 2015 emissions. Final controls from the final locomotive-marine and small
spark ignition OTAQ rules are included. California-specific data provided by the state of California,
except NH3 used 2012 and 2014 (interpolated) NMIM. Year-specific speciation was applied to some
portions of this sector and is discussed in Section 4.3.5.
Locomotive, and non-Class 3 commercial marine sector (alm_no_c3): Projection factors for Class 1
and Class 2 commercial marine and locomotives which reflect Transport Rule comments and activity
growth and final locomotive-marine controls.
Class 3 commercial marine vessel sector (seca_c3): Base-year 2005 emissions grown and controlled
to 2012 and 2014, incorporating Transport Rule comments and controls based on Emissions Control
Area (ECA) and International Marine Organization (IMO) global NOx and SO2 controls.
Onroad mobile sector with no adjustment for daily temperature (on noadj): MOVES2010 run (state-
month) for 2012 and 2014 with results disaggregated to the county level in proportion to NMIM 2012
and NMIM 2015 emissions estimates. Temperature impacts at the monthly average resolution.
California-specific data provided by the state of California, except NH3 which was obtained from
MOVES2010. VOC speciation uses different future-year values to take into account both the
increase in ethanol use, and the existence of Tier 2 vehicles that use a different speciation profile.
Other than California, this sector includes all non-refueling onroad mobile emissions (exhaust,
evaporative, brake wear and tire wear modes) except exhaust mode gasoline PM and naphthalene
emissions that are provided in the onmovesstartpm and onmovesrunpm sectors.
Onroad PM gasoline running mode sector (on moves startpm): Running mode MOVES2010 year
2012 and 2014 future-year state-month estimates for PM and naphthalene, apportioned to the county
level using NMIM 2012 and NMIM 2015 state-county ratios matched to vehicle and road types. Use
future-year temperature adjustment file for adjusting the 72°F emissions to ambient temperatures (for
elemental and organic carbon) based on grid cell hourly temperature (note that lower temperatures
result in increased emissions).
Onroad PM gasoline start mode sector (on moves startpm): Cold start MOVES2010 future-year
2012 and 2014 state-month estimates for PM and naphthalene, apportioned to the county level using
NMIM 2012 and NMIM 2015 state-county ratios of local urban and rural roads by vehicle type. Use
future-year temperature adjustment file for adjusting the 72°F emissions (for elemental and organic
carbon) to ambient temperatures based on grid cell hourly temperatures (lower temperatures result in
increased emissions).
Other nonroad/nonpoint (othar): No growth or control.
Other onroad sector (othon): No growth or control.
Other nonroad/nonpoint (othar): No growth or control.
70
-------
Other point (othpt): No growth or control.
Biogenic: 2005 emissions used for all future-year scenarios.
Table 4-1 summarizes the control strategies and growth assumptions by source type that were used to create
the 2012 and 2014 base-case emissions from the 2005v4.2 base-case inventories. All Mexico, Canada, and
offshore oil emissions are unchanged in all future cases from those in the 2005 base case. Emission
summaries by sector for 2005 and future years are provided in Section 7. Note that mercury (Hg) is listed in
the pollutant's column; however, we did not include Hg in our v4.2 modeling. Note that a few controls are
not fully promulgated by 2012 but are by 2014. For example the Maximum Achievable Control Technology
(MACT) rule "Boat Manufacturing" has a compliance date in year 2013; therefore the VOC control
associated with this MACT rule is not reflected in the 2012 base case but is reflected in the 2014 base and
control cases.
Lists of the control, closures, projection packets (datasets) used to create Transport Rule 2012 and 2014
future year base-case scenario inventories from the 2005 base case are provided in Appendix D. Additional
summaries on the emissions changes resulting from these various control programs that were too large to
include in this section can be found in Appendix D, and the following files are provided with the Transport
Rule final emissions data. TransportRuleFinal_2012_Projection_info.xlsx and
TransportRuleFinal_2014_Proj ectioninfo.xlsx.
The remainder of this section is organized either by source sector or by specific emissions category within a
source sector for which a distinct set of data were used or developed for the purpose of projections for the
Transport Rule. This organization allows consolidation of the discussion of the emissions categories that are
contained in multiple sectors, because the data and approaches used across the sectors are consistent and do
not need to be repeated. Sector names associated with the emissions categories are provided in parentheses.
71
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Table 4-1. Control strategies and growth assumptions for creating the 2012 and 2014 base-case emissions
inventories from the 2005 base case
Control Strategies and/or growth assumptions
(grouped by affected pollutants or standard and approach used to
apply to the inventory)
Pollutants
affected
Approach/
Reference
\on-K(il Point (ptnoilipin sector) projection ;ippro;ichcs curried lor\\;iril
I'roin the Proposed Transport Rule
MACT rules, national. VOC: national aoolicd bv SCC. MACT
Boat Manufacturing (promulgated in year 2013, thus not reflected in the 2012 base
casej
Wood Building Products Surface Coating
Generic MACT II: Spandex Production, Ethylene manufacture
Large Appliances
Miscellaneous Organic NESHAP (MON): Alkyd Resins, Chelating Agents,
Explosives, Phthalate Plasticizers, Polyester Resins, Polymerized Vinylidene
Chloride
Reinforced Plastics
Asphalt Processing & Roofing
Iron & Steel Foundries
Metal: Can, Coil
Metal Furniture
Miscellaneous Metal Parts & Products
Municipal Solid Waste Landfills
Paper and Other Web
Plastic Parts
Plywood and Composite Wood Products
Carbon Black Production
Cyanide Chemical Manufacturing
Friction Products Manufacturing
Leather Finishing Operations
Miscellaneous Coating Manufacturing
Organic Liquids Distribution (Non-Gasoline)
Refractory Products Manufacturing
Sites Remediation
VOC
EPA, 2007a
Consent decrees on companies (based on information from the Office of Enforcement
and Compliance Assurance - OECA) apportioned to plants owned/operated by the
companies
VOC, CO, NOx,
PM, SO2
1
DO J Settlements: plant SCC controls for:
Alcoa, TX
Premcor (formerly Motiva), DE
All
2
Refinery Consent Decrees: plant/SCC controls (a few of these controls are promulgated
in year 2013, and thus are not reflected in the 2012 base case)
NOx, PM, S02
3
Hazardous Waste Combustion
PM
4
Municipal Waste Combustor Reductions -plant level
PM
5
Hospital/Medical/Infectious Waste Incinerator Regulations
NOx, PM, S02
EPA, 2005b
Large Municipal Waste Combustors - growth applied to specific plants
All (including Hg)
5
MACT rules, plant-level, VOC: Auto Plants
VOC
6
MACT rules, plant-level, PM & SO2: Lime Manufacturing
PM, S02
7
MACT rules, plant-level, PM: Taconite Ore
PM
8
Additional projections used in the liiiiil Tmnsport Rule
modeling lor non-IKil point sources (ptnonipni sector)
\l !SI 1 \l». I'orikmd (.'email (U'H)1) |(i; plain lev el based on Industrial Sector
Integrated Solutions (ISIS) policy emissions in 2013. The ISIS results are from the
ISIS-Cement model runs for the NESHAP and NSPS analysis of July 28, 2010 and
include closures, (promulgated in year 2013, thus only known closures and new units
1 is, \<> so:.
PM, HC1
13; EPA,
2010
72
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through year 2009 were included for year 2012 -ISIS-based future-year projections
included only for 2014)
New York ozone SIP controls
VOC, NOx,
HAP VOC
14
Additional plant and unit closures provided by state, regional, and the EPA agencies and
additional consent decrees. Includes updates from Transport Rule comments.
All
Appendix D
Emission reductions resulting from controls put on specific boiler units (not due to
MACT) after 2005, identified through analysis of the control data gathered from the
Information Collection Request (ICR) from the Industrial/Commercial/Institutional
Boiler NESHAP.
NOx, S02, HC1
Section 4.2.6
Reciprocating Internal Combustion Engines (RICE) NESHAP: (SO 2 controls for RICE
are not effective until after 2012, but are applied in 2014)
NOx, CO, PM,
S02
15
Replaced 2005 with 2008 emissions for Corn Products International, Cook County,
Illinois, due to the shutdown of 3 boilers and addition of a new boiler (subject to
Prevention of Significant Deterioration and Requirements). Agency Identifier:
031012ABI (ILEPA)
All
16
Slalc fuel sulfur coiileiil rules for fuel oil r//r> ii\v uiilv m Mtinc Yrn Yuri 111 2^14
SO
r
Nonpoinl (nonpl sector) projection ;ippro;iches citi i icd forward from (ho Proposed Transport Rule
Municipal Waste Landfills: projection factor of 0.25 applied
All
EPA, 2007a
Livestock Emissions Growth from year 2002 to year 2012 and 2014
NH3, PM
9
Residential Wood Combustion Growth and Change-outs from year 2005 to year 2012
and 2014
All
10
Gasoline Stage II growth and control from year 2005 to year 2012 and 2014
VOC
11
Portable Fuel Container Mobile Source Air Toxics Rule 2 (MSAT2) inventory growth
and control from year 2005 to year 2012 and 2014
VOC
12
Ailclitioiiiil projections used in (lie liiud Tninsport Rule modeling lor Nonpoinl sou ices (nonpl sector)
RICE NESHAP: (SO 2 controls for RICE are not effective until after 2012, but are
applied in 2014)
NOx, CO, VOC,
PM, S02
15
Use Phase II WRAP 2005 Oil and Gas, but apply year 2012- and year 2014-specific
RICE controls to these emissions
VOC, S02, NOx,
CO
Section 3.2.7
Use 2008 Oklahoma and Texas Oil and Gas, and, apply year 2012- and year 2014-
specific RICE controls to these emissions.
VOC, S02, NOx,
CO, PM
Section 3.2.7
New York, Connecticut, and Virginia ozone SIP controls
VOC
14, 18
State fuel sulfur content rules for fuel oil -effective only in Maine and New York in 2014
S02
17
APPROACHES/REFERENCES- Stationary Sources:
1. Appendix B in the Proposed Toxics Rule TSD
2. For Alcoa consent decree, used http:// cfpub.epa.gov/compliance/cases/index.cfm; for Motiva: used information sent by
State of Delaware
3. Used data provided by the EPA, OAQPS, Sector Policies and Programs Division (SPPD).
4. Obtained from Anne Pope, the US EPA - Hazardous Waste Incinerators criteria and hazardous air pollutant controls
carried over from 2002 Platform, v3.1.
5. Used data provided by the EPA, OAQPS SPPD expert.
6. Percent reductions and plants to receive reductions based on recommendations by rule lead engineer, and are consistent
with the reference: EPA, 2007a
7. Percent reductions recommended are determined from the existing plant estimated baselines and estimated reductions as
shown in the Federal Register Notice for the rule. SO2 percent reduction are computed by 6,147/30,783 = 20% and
PM10 and PM2.5 reductions are computed by 3,786/13,588 = 28%
8. Same approach as used in the 2006 Clean Air Interstate Rule (CAIR), which estimated reductions of "PM emissions by
10,538 tpy, a reduction of about 62%." Used same list of plants as were identified based on tonnage and SCC from
CAIR.
9. Except for dairy cows and turkeys (no growth), based on animal population growth estimates from the US Department
of Agriculture (USDA) and the Food and Agriculture Policy and Research Institute. See Section 3.2.1.
73
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10. Growth and Decline in woodstove types based on industry trade group data, See Section.
11. VOC emission ratios of year 2016 (linear interpolation between 2015 and 2020) -specific from year 2005 from the
National Mobile Inventory Model (NMIM) results for onroad refueling including activity growth from VMT, Stage II
control programs at gasoline stations, and phase in of newer vehicles with onboard Stage II vehicle controls.
12. VOC and benzene emissions for year 2016 (linear interpolation between 2015 and 2020) from year 2002 fromMSAT2
rule (EPA, 2007b)
13. Data files for the cement sector provided by Elineth Torres, the EPA-SPPD, from the analysis done for the Cement
NESHAP: The ISIS documentation and analysis for the cement NESHAP/NSPS is in the docket of that rulemaking-
docket # EPA-HQ-OAR-2002-005. The Cement NESHAP is in the Federal Register: September 9, 2010 (Volume 75,
Number 174, Page 54969-55066
14. New York NOx and VOC reductions obtained from Appendix J in NY Department of Environmental Conservation
Implementation Plan for Ozone (February 2008). Located in Section 3.2.6.
15. Appendix F in the Proposed Toxics Rule TSD
16. The 2008 data used came from Illinois' submittal of 2008 emissions to the NEI.
17. Based on available, enforceable state sulfur rules as of November, 2010: ILTA: An Act To Improve Maine's Air Quality
and Reduce Regional Haze at Acadia National Park and Other Federally Designated Class I Areas. NRDC. New York
Times.
18. VOC reductions in Connecticut and Virginia obtained from Transport Rule comments.
Onroiul mobile sind iionronri mobile controls
(list includes nil key mobile control slrsilegies bill is not exhaustive)'
National Onroad Rules:
Tier 2 Rule: Signature date February, 2000
2007 Onroad Heavy-Duty Rule: February, 2009
Final Mobile Source Air Toxics Rule (MSAT2): February, 2007
Renewable Fuel Standard: March, 2010
all
1
Local Onroad Programs:
National Low Emission Vehicle Program (NLEV): March, 1998
Ozone Transport Commission (OTC) LEV Program: January, 1995
VOC
2
National Nonroad Controls:
Clean Air Nonroad Diesel Final Rule - Tier 4: June, 2004
Control of Emissions from Nonroad Large-Spark Ignition Engines and Recreational
Engines (Marine and Land Based): "PentathalonRule": November, 2002
Clean Bus USA Program: October, 2007
Control of Emissions of Air Pollution from Locomotives and Marine Compression-Ignition
Engines Less than 30 Liters per Cylinder: October, 2008
all
3,4,5
Aircraft:
Itinerant (ITN) operations at airports to year 2012 and year 2014
all
6
Locomotives:
Energy Information Administration (EIA) fuel consumption projections for freight rail
Clean Air Nonroad Diesel Final Rule - Tier 4: June 2004
Locomotive Emissions Final Rulemaking, December 17, 1997
Control of Emissions of Air Pollution from Locomotives and Marine: May 2008
all
EPA, 2009;
3; 4; 5
Commercial Marine:
Category 3 marine diesel engines Clean Air Act and International Maritime Organization
standards (April, 30, 2010) -also includes Transport Rule comments.
EIA fuel consumption projections for diesel-fueled vessels
OTAQ ECA C3 Base 2020 inventory for residual-fueled vessels
Clean Air Nonroad Diesel Final Rule - Tier 4
Emissions Standards for Commercial Marine Diesel Engines, December 29, 1999
Tier 1 Marine Diesel Engines, February 28, 2003
all
7, 3; EPA,
2009
a. These control programs are the same as were used in the Proposed Transport Rule except for the C3 marine standards of
April 2010, which are included in the Toxics Rule but were not included in the Proposed Transport Rule.
74
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APPROACHES/REFERENCES - Mobile Sources
1. Vehicles and Engines
2. Only for states submitting these inputs: Transportation. Air Pollution, and Climate Change
3. Regulations for Emissions from Vehicles and Engines
4. Clean School Bus http://www.epa.gov/cleanschoolbus/
5. Office of Transportation and Air Quality Contacts
6. Federal Aviation Administration (FAA) Terminal Area Forecast (TAF) System. December 2008:
7. International Standards to Reduce Emissions from marine Diesel Engines and Their Fuels
4.1 Stationary source projections: EGU sector (ptipm)
The future-year data for the ptipm sector used in the air quality modeling were created by version 4.10
(v4.10) of the Integrated Planning Model (TPM). The IPM is a multiregional, dynamic, deterministic linear
programming model of the U.S. electric power sector. Version 4.10 reflects state rules and consent decrees
through December 1, 2010 and incorporates information on existing controls collected through the
Information Collection Request (ICR), and information from comments received on the IPM-related Notice
of Data Availability (NOD A) published on September 1, 2010. IPM v4.10 Final included the addition of
over 20 GW of existing Activated Carbon Injection (ACI) reported to the EPA via the ICR. Units with SO2
or NOx advanced controls (e.g., scrubber, SCR) that were not required to run for compliance with Title IV,
New Source Review (NSR), state settlements, or state-specific rules were modeled by IPM to either operate
those controls or not based on economic efficiency parameters.
Updates to IPM 4.10 (with respect to the version released in the IPM NODA version) include adjustments to
assumptions regarding the performance of acid gas control technologies, new costs imposed on fuel-
switching (e.g., bituminous to sub-bituminous), correction of lignite availability to some plants,
incorporation of additional planned retirements, a more inclusive implementation of the scrubber upgrade
option, and the availability of a scrubber retrofit to waste-coal fired fluidized bed combustion units without
an existing scrubber. Further details on the future-year EGU emissions inventory used for this rule can be
found in the incremental documentation of the IPM v.4.10 platform. Note that the Transport Rule future-
year base cases do not include the Toxics Rule, which was proposed on March 16, 2011. In addition, the
Boiler MACT was not represented in the final Transport Rule modeling because the rule was not final at the
time the modeling was performed.
IPM is run in 5 year increments beyond year 2015. IPM results were generated for 2012 and 2015. The IPM
2015 results are valid for representing 2014, 2015, and 2016. As explained in the Transport Rule IPM TSD,
additional steps were taken to ensure that the results were valid for use in a 2014, 2015 (or 2016) model run.
Directly emitted PM emissions (i.e., PM2.5 and PM10) from the EGU sector are computed via a post
processing routine which applies emission factors to the IPM-estimated fuel throughput based on fuel,
configuration and controls to compute the filterable and condensable components of PM. This methodology
is documented in the IPM TSD.
4.2 Stationary source projections: non-EGU sectors (ptnonipm, nonpt, ag,
afdust)
To project U.S. stationary sources other than the ptipm sector, we applied growth factors and/or controls to
certain categories within the ptnonipm, nonpt, ag and afdust platform sectors. This subsection provides
75
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details on the data and projection methods used for these sectors. In estimating future-year emissions, we
assumed that emissions growth does not track with economic growth for many stationary non-IPM sources.
This "no-growth" assumption is based on an examination of historical emissions and economic data. While
we are working toward improving the projection approach in future emissions platforms, we are still using
the no-growth assumption for the 2005, v4.2 platform. More details on the rationale for this approach can be
found in Appendix D of the Regulatory Impact Assessment for the PM NAAQS rule (EPA, 2006b).
The starting point was the emission projections done for the 2005v4 platform for the Proposed Transport
Rule. The 2012 and 2014 projection factors developed for the Transport Rule Proposal were updated for
these 2012 and 2014 baseline projections. Several additional National Emission Standards for Hazardous
Air Pollutants (NESHAPs) were promulgated since emission projections were done for the Proposed
Transport Rule, and these were included for the 2012 and 2014 base cases. Also included in the 2012 and
2014 base cases are numerous future-year projection data from the Transport Rule comments; these data are
described in the following sections.
Year-specific projection factors for years 2012 and 2014 were used for creating the 2012 and 2014 base
cases unless noted otherwise. Growth factors (and control factors) are provided in the following sections
where feasible. However, some sectors used growth or control factors that varied geographically, and their
contents could not be provided in the following sections (e.g., gasoline distribution varies by county and
pollutant and has thousands of records). If the growth or control factors for a sector are not provided in a
table in this document, they are available as a "projection" or "control" packet for input to SMOKE on the
v4.2 platform website (see the end of Section).
4.2.1 Livestock emissions growth (ag, afdust)
Growth in ammonia (NH3) and dust (PM10 and PM2.5) emissions from livestock in the ag and afdust and
ptnonipm sectors was based on projections of growth in animal population. While there are a very small
amount of livestock emissions in the ptnonipm sector as compared to the ag sector, the livestock growth
projection packet was inadvertently not applied to the ptnonipm that sector. This results in an underestimate
of NH3 in the ptnonipm sector of roughly 1,160 tons in 2012 and 1,390 tons in 2014 (primarily in Kansas and
Minnesota for which the NH3 were reported at specific farms in the point source inventory), and for PM2.5
the ptnonipm sector underestimates are 3 tons in both 2012 and 2014. These omissions are expected to have
a negligible impact on the air quality PM and ozone results and these omissions were made in both the future
base case and Transport Rule policy case.
Table 4-2 provides the growth factors from the 2005 base-case emissions to 2012 and 2014 for animal
categories applied to the ag and afdust sectors for livestock-related SCCs. For example, year 2014 beef
emissions are 1.7% larger than the 2005 base-case emissions. Except for dairy cows and turkey production,
the animal projection factors are derived from national-level animal population projections from the U.S.
Department of Agriculture (USDA) and the Food and Agriculture Policy and Research Institute (FAPRI).
For dairy cows and turkeys, we assumed that there would be no growth in emissions. This assumption was
based on an analysis of historical trends in the number of such animals compared to production rates.
Although productions rates have increased, the number of animals has declined. Thus, we do not believe
that production forecasts provide representative estimates of the future number of cows and turkeys;
therefore, we did not use these forecasts for estimating future-year emissions from these animals. In
particular, the dairy cow population is projected to decrease in the future as it has for the past few decades;
however, milk production will be increasing over the same period. Note that the ammonia emissions from
dairies are not directly related to animal population but also nitrogen excretion. With the cow numbers going
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down and the production going up we suspect the excretion value will be changing, but we assumed no
change because we did not have a quantitative estimate.
The inventory for livestock emissions used 2002 emissions values therefore, our projection method projected
from 2002 rather than from 2005.
Appendix E in the 2002v3 platform documentation provides the animal population data and regression
curves used to derive the growth factors. Appendix F in the same document provides the cross references of
livestock sources in the ag, afdust and ptnonipm sectors to the animal categories in Table 4-2.
Table 4-2. Growth factors from year 2005 to future years for Animal Operations
Animal Category
Projection Factors
2012
2014
Dairy Cow
1.000
1.000
Beef
1.014
1.017
Pork
1.060
1.071
Broilers
1.230
1.275
Turkeys
1.000
1.000
Layers
1.160
1.193
Poultry Average
1.178
1.214
Overall Average
1.0623
1.075
4.2.2 Residential wood combustion growth (nonpt)
We projected residential wood combustion emissions based on the expected increase in the number of low-
emitting wood stoves and the corresponding decrease in other types of wood stoves. As newer, cleaner
woodstoves replace older, higher-polluting wood stoves, there will be an overall reduction of the emissions
from these sources. The approach cited here was developed as part of a modeling exercise to estimate the
expected benefits of the woodstoves change-out program. Details of this approach can be found in Section
2.3.3 of the PM NAAQS Regulatory Impact Analysis (EPA, 2006b).
The specific assumptions we made were:
¦ Fireplaces, SCC=2104008001: increase 1%/year
¦ Old woodstoves, SCC=2104008002, 2104008010, or 2104008051: decrease 2%/year
¦ New woodstoves, SCC=2104008003, 2104008004, 2104008030, 2104008050, 2104008052 or
2104008053: increase 2%/year
For the general woodstoves and fireplaces category (SCC 2104008000) we computed a weighted average
distribution based on 19.4% fireplaces, 71.6% old woodstoves, 9.1% new woodstoves using 2002v3
Platform (these emissions have not been updated for the 2005v4 platform used for the Transport Rule
Proposal 2005v4) emissions for PM2.5. These fractions are based on the fraction of emissions from these
processes in the states that did not have the "general woodstoves and fireplaces" SCC in the 2002v3 NEI.
This approach results in an overall decrease of 1.056% per year for this source category.
Table 4-3 presents the projection factors used to project the 2005 base case (2002 emissions) for residential
wood combustion.
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Table 4-3. Projection Factors for growing year 2005 Residential Wood Combustion Sources
SCC
SCC Description
Projection Factors
2012
2014
2104008000
Total: Woodstoves and Fireplaces
0.8944
0.8733
2104008001
Fireplaces: General
1.10
1.12
2104008070
Outdoor Wood Burning Equipment
2104008002
Fireplaces: Insert; non-EPA certified
0.80
0.76
2104008010
Woodstoves: General
2104008051
Non-catalytic Woodstoves: Non-EPA certified
2104008003
Fireplaces: Insert; EPA certified; non-catalytic
1.20
1.24
2104008004
Fireplaces: Insert; EPA certified; catalytic
2104008030
Catalytic Woodstoves: General
2104008050
Non-catalytic Woodstoves: EPA certified
2104008052
Non-catalytic Woodstoves: Low Emitting
2104008053
Non-catalytic Woodstoves: Pellet Fired
4.2.3 Gasoline Stage II growth and control (nonpt, ptnonipm)
Emissions from Stage II gasoline operations in the 2005 base case are contained in both nonpt and ptnonipm
sectors. The only SCC in the nonpt inventory used for gasoline Stage II emissions is 2501060100 (Storage
and Transport; Petroleum and Petroleum Product Storage; Gasoline Service Stations; Stage II: Total). The
following SIC and SCC codes are associated with gasoline Stage II emissions in the ptnonipm sector:
¦ SIC 5541 (Automotive Dealers & Service Stations, Gasoline Service Stations, Gasoline service
stations)
¦ SCC 40600401 (Petroleum and Solvent Evaporation;Transportation and Marketing of Petroleum
Products;Filling Vehicle Gas Tanks - Stage II;Vapor Loss w/o Controls)
¦ SCC 40600402 (Petroleum and Solvent Evaporation;Transportation and Marketing of Petroleum
Products;Filling Vehicle Gas Tanks - Stage II;Liquid Spill Loss w/o Controls)
¦ SCC 40600403 (Petroleum and Solvent Evaporation;Transportation and Marketing of Petroleum
Products;Filling Vehicle Gas Tanks - Stage II;Vapor Loss w/o Controls)
¦ SCC 40600499 (Petroleum and Solvent Evaporation;Transportation and Marketing of Petroleum
Products;Filling Vehicle Gas Tanks - Stage II;Not Classified
We used a consistent approach across nonpt and ptnonipm to project these gasoline stage II emissions. The
approach involved computing state-level VOC-specific projection factors from the state-level MOVES2010-
based results for onroad refueling, using ratios of future-year 2012 and 2014 refueling emissions to 2005
base-case emissions. The approach accounts for three elements of refueling growth and control: (1) activity
growth (due to VMT growth as input into MOVES2010), (2) emissions reductions from Stage II control
programs at gasoline stations, and (3) emissions reductions resulting from the phase-in over time of newer
vehicles with onboard Stage II vehicle controls. We assumed that all areas with Stage II controls in 2005
continue to have Stage II controls in 2012 and 2014. This approach is an update from the 2005v4 platform
projections in the Proposed Transport Rule; in that platform, NMIM refueling projections were used instead
of MOVES2010.
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We computed VOC, benzene and naphthalene projection factors at a county-specific, annual resolution as
shown below; note that naphthalene, while provided by MOVES2010, is not used in the Transport Rule:
PF_VOC[state, future year] = VOC_RFL[state, future year]/VOC_RFL[state, 2005],
PF_BENZENE[state, future year] = BENZENE_RFL[state, future year]/ BENZENE _RFL[state, 2005], and
PF_NAPHTHALENE[state, future year] = PF_VOC [state, future year]
where VOC RFL is the VOC refueling emissions for onroad sources from MOVES2010, and
BENZENE RFL is the BENZENE refueling emissions for onroad sources from MOVES2010
We applied these projection factors to both nonpt and ptnonipm sector gasoline stage II sources.
Chemical speciation uses certain VOC HAPs for some sources, specifically, benzene, acetaldehyde,
formaldehyde, and methanol (BAFM). The VOC HAPs are used for sources that have consistent VOC and
VOC HAPs using various criteria as described in the Section3.1.2.1, and these sources are called
"integrated" sources. The nonpoint gasoline stage II emissions are an integrated source, and so the VOC
HAPs are also projected based on ratios of future-year and base-year VOC. The only two VOC HAPs
emitted from refueling are benzene and naphthalene, and both of these were projected consistently with
VOC. However, naphthalene was not used in the chemical speciation (it is not B,A,F or M) and was
therefore not used for this effort. Benzene was used as part of the speciation for the nonpt sector gasoline
stage II sources. The ptnonipm is a "no-integrate" sector, so ptnonipm gasoline stage II sources did not use
the projected benzene as part of the speciation, but rather used VOC speciation to estimate benzene.
4.2.4 Portable fuel container growth and control (nonpt)
We obtained future-year VOC emissions from Portable Fuel Containers (PFCs) from inventories developed
and modeled for the EPA's MSAT2 rule (EPA, 2007a). The 10 PFC SCCs are summarized below (note that
the full SCC descriptions for these SCCs include "Storage and Transport; Petroleum and Petroleum Product
Storage" as the beginning of the description).
2501011011 Residential Portable Fuel Containers:
2501011012 Residential Portable Fuel Containers:
2501011013 Residential Portable Fuel Containers:
2501011014 Residential Portable Fuel Containers:
2501011015 Residential Portable Fuel Containers:
2501012011 Commercial Portable Fuel Containers
2501012012 Commercial Portable Fuel Containers
2501012013 Commercial Portable Fuel Containers
2501012014 Commercial Portable Fuel Containers
2501012015 Commercial Portable Fuel Containers
Permeation
Evaporation
Spillage During Transport
Refilling at the Pump: Vapor Displacement
Refilling at the Pump: Spillage
: Permeation
: Evaporation
: Spillage During Transport
: Refilling at the Pump: Vapor Displacement
: Refilling at the Pump: Spillage
Additional information on the PFC inventories is available in Section 2.2.3 of the documentation for the
2002 Platform.
The future-year emissions reflect projected increases in fuel consumption, state programs to reduce PFC
emissions, standards promulgated in the MSAT2 rule, and impacts of the Renewable Fuel Standard (RFS) on
gasoline volatility. Future-year emissions for PFCs were available for 2010, 2015, 2020, and 2030. In
creating the inventories for 2012 and 2014, we linearly interpolated year 2010 and year 2015 inventories.
Benzene and other VOC HAP future-year PFC emissions were also included in the interpolation. Benzene
79
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was used in VOC speciation for the air quality model through the modification of VOC speciation profiles
calculations (no other BAFM HAPs are emitted from PFCs).
4.2.5 Aircraft growth (ptnonipm)
As with the 2005v4 platform, aircraft emissions are contained in the ptnonipm inventory. These 2005 point-
source emissions are projected to future years by applying activity growth using data on itinerant (ITN)
operations at airports. The ITN operations are defined as aircraft take-offs whereby the aircraft leaves the
airport vicinity and lands at another airport, or aircraft landings whereby the aircraft has arrived from outside
the airport vicinity. We used projected ITN information available from the Federal Aviation
Administration's (FAA) Terminal Area Forecast (TAF) System (publication date December 2008). This
information is available for approximately 3,300 individual airports, for all years up to 2025. We aggregated
and applied this information at the national level by summing the airport-specific (U.S. airports only) ITN
operations to national totals by year and by aircraft operation, for each of the four available operation types:
commercial, general, air taxi, military. We computed growth factors for each operation type by dividing
future-year ITN by 2005-year ITN. We assigned factors to inventory SCCs based on the operation type.
The methods that the FAA used for developing the ITN data in the TAF.
Table 4-4 provides the national growth factors for aircraft; all factors are applied to year 2005 emissions.
For example, year 2012 commercial aircraft emissions are 1.9% higher than year 2005 emissions.
Table 4-4. Factors used to project 2005 base-case aircraft emissions to future years
SCC
SCC Description
Projection Factor
2012
2014
2275001000
Military aircraft
0.967
0.968
2275020000
Commercial aircraft
1.019
1.066
2275050000
General aviation
0.962
0.977
2275060000
Air taxi
0.872
0.897
27501015
Internal Combustion Engines;Fixed Wing Aircraft L & TO
Exhaust;Military;Jet Engine: JP-5
0.967
0.968
27502001
Internal Combustion Engines;Fixed Wing Aircraft L & TO
Exhaust;Commercial;Piston Engine: Aviation Gas
1.019
1.066
27502011
Internal Combustion Engines;Fixed Wing Aircraft L & TO
Exhaust;Commercial;Jet Engine: Jet A
1.019
1.066
27505001
Internal Combustion Engines;Fixed Wing Aircraft L & TO
Exhaust;Civil;Piston Engine: Aviation Gas
0.962
0.977
27505011
Internal Combustion Engines;Fixed Wing Aircraft L & TO
Exhaust;Civil;Jet Engine: Jet A
0.962
0.977
27601014
Internal Combustion Engines;Rotary Wing Aircraft L & TO
Exhaust;Military;Jet Engine: JP-4
0.967
0.968
27601015
Internal Combustion Engines;Rotary Wing Aircraft L & TO
Exhaust;Military;Jet Engine: JP-5
0.967
0.968
We did not apply growth factors to any point sources with SCC 27602011 (Internal Combustion Engines;
Rotary Wing Aircraft L & TO Exhaust; Commercial; Jet Engine: Jet A) because the facility names
associated with these point sources appeared to represent industrial facilities rather than airports. This SCC
is only in one county, Santa Barbara, California (State/County FIPS 06083).
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None of our aircraft emission projections account for any control programs. We considered the NOx
standard adopted by the International Civil Aviation Organization's (ICAO) Committee on Aviation
Environmental Protection (CAEP) in February 2004, which is expected to reduce NOx by approximately 2%
in 2015 and 3% in 2020. However, this rule has not yet been adopted as an EPA (or U.S.) rule; therefore, the
effects of this rule were not included in the future-year emissions projections.
4.2.6 Stationary source control programs, consent decrees & settlements, and plant
closures (ptnonipm, nonpt)
We applied emissions reduction factors to the 2005 emissions for particular sources in the ptnonipm and
nonpt sectors to reflect the impact of stationary-source control programs including consent decrees,
settlements, and plant closures. Some of the controls described in this section were obtained from comments
on the Transport Rule proposal. Here we describe the contents of the controls and closures for the 2012 and
2014 base cases. Detailed summaries of the impacts of the control programs are provided in Appendix D.
Controls from the NOx SIP call were assumed to have been implemented by 2005 and captured in the 2005
base case (2005v2 point inventory). This assumption was confirmed by review of the 2005 NEI that showed
reductions from Large Boiler/Turbines and Large Internal Combustion Engines in the Northeast states
covered by the NOx SIP call. The future-year base controls consist of the following:
We did not include MACT rules where compliance dates were prior to 2005, because we assumed
these were already reflected in the 2005 inventory. The EPA OAQPS Sector Policies and Programs
Division (SPPD) provided all controls information related to the MACT rules, and this information is
as consistent as possible with the preamble emissions reduction percentages for these rules.
Various emissions reductions from the Transport Rule comments, including but not limited to: fuel
switching at units, shutdowns, future-year emission limits, ozone SIP VOC controls for some sources
in Virginia and Connecticut, and state and local control programs.
Evolutionary information gathering of plant closures (i.e., emissions were zeroed out for future years)
were also included where information indicated that the plant was actually closed after the 2005 base
year and prior to Transport Rule modeling that began in the fall of 2010. We also applied unit and
plant closures received from the Transport Rule comments. However, plants projected to close in the
future (post-2010) were not removed in the future years because these projections can be inaccurate
due to economic improvements. We also applied cement kiln (unit) and cement plant closures
discussed later in Section 4.2.6.1. More detailed information on the overall state-level impacts of all
control programs and projection datasets, including units and plants closed in the 2012 and 2014
base-case ptnonipm inventories are provided in Appendix D. The magnitude of all unit and plant
closures on the non-EGU point (ptnonipm) sector 2005 base-case emissions is shown in Table 4-5
below.
Table 4-5. Summary of Non-EGU Emission Reductions Applied to the 2005 Inventory due to Unit and
Plant Closures
State
CO
(tons)
nh3
(tons)
NOx
(tons)
PMio
(tons)
pm25
(tons)
so2
(tons)
VOC
(tons)
Alabama
10,680
6
4,104
2,543
2,257
1,912
870
Arizona
509
0
1,524
161
65
7
28
Arkansas
1,110
0
3,994
401
129
920
271
California
2,684
0
6,675
1,121
444
1,161
23
Delaware
93
6
1,495
350
326
5,409
391
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State
CO
(tons)
nh3
(tons)
NOx
(tons)
PMio
(tons)
pm25
(tons)
so2
(tons)
VOC
(tons)
Florida
4,136
230
7,869
1,049
577
8,547
246
Georgia
7,435
21
2,678
1,187
765
2,688
2,295
Idaho
625
6
461
14
6
17
1
Illinois
10,175
0
11,605
1,996
1,267
23,830
716
Indiana
1,058
0
4,794
486
207
8,468
157
Iowa
461
0
1,939
230
48
4,787
15
Kansas
989
4
1,624
84
48
329
52
Louisiana
3,035
127
1,878
521
337
4,114
4,061
Maine
256
13
1,906
467
212
3,767
310
Maryland
107
22
1,634
168
83
1,137
6
Massachusetts
45
7
518
114
68
1,909
55
Michigan
7,995
73
10,900
2,274
1,076
14,598
2,083
Mississippi
0
0
69
5
5
96
Missouri
17
4
23
2
2
0
310
Nevada
204
0
2,817
212
74
175
66
New Hampshire
109
0
287
113
103
681
291
New Jersey
9
0
31
24
24
0
996
New York
5
1
48
16
11
217
14
North Carolina
12
1
94
25
17
379
7
Ohio
340
4,238
610
299
7,128
69
Oklahoma
103
4
1,757
531
184
1,498
17
Pennsylvania
1,415
4
6,117
1,293
683
6,852
116
South Carolina
1,666
4
2,115
441
266
1,052
302
Tennessee
106
0
2,229
242
146
5,407
9,065
Texas
5,395
20
9,664
1,264
642
9,216
507
Virginia
3,161
1
3,737
1,355
1,029
11,102
2,188
West Virginia
59,321
55
5,257
1,244
830
13,410
783
Wisconsin
479
28
1,953
436
297
7,672
349
Grand Total
123,735
637
106,034
20,979
12,527
148,485
26,660
In addition to plant closures, we included the effects of the Department of Justice Settlements and
Consent Decrees on the non-EGU (ptnonipm) sector emissions. We also included estimated impacts
of HAP standards per Section 112, 129 of the Clean Air Act on the non-EGU (ptnonipm) and
nonpoint (nonpt) sector emissions, based on expected CAP co-benefits to sources in these sectors.
Numerous controls have compliance dates beyond 2008; these include refinery and the Office of
Compliance and Enforcement (OECA) consent decrees, Department of Justice (DOJ) settlements, as
well as most national VOC MACT controls. Additional OECA consent decree information is
provided in Appendix B of the Proposed Toxics Rule TSD. The detailed data used are available at
the website listed in Section 1. Several of these consent decrees and national NESHAP rules such as
RICE and cement have compliance dates that are between 2012 and 2014; therefore, there are several
differences in controls applied to the 2012 and 2014 base cases.
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Refinery consent decrees controls at the facility and SCC level (collected through internal
coordination on refineries by the EPA).
Fuel sulfur fuel limits were enforceable in 2014 (not 2012) for Maine and New York. These fuel
limits were incremental and not applicable until after 2012. Because we only apply controls that are
applicable before July 1, 2014, more stringent sulfur fuel controls and additional states with controls
in later years were not applied.
Criteria air pollutant (cap) reductions a cobenefit to RICE NESHAP controls. SO2 RICE cobenefit
controls are not applied in 2012.
Most of the control programs were applied as replacement controls, which means that any existing
percent reductions ("baseline control efficiency") reported in the NEI were removed prior to the
addition of the percent reductions due to these control programs. Exceptions to replacement controls
are "additional" controls, which ensure that the controlled emissions match desired reductions
regardless of the baseline control efficiencies in the NEI. We used the "additional controls" approach
for many permit limits, settlements and consent decrees where specific plant and multiple-plant-level
reductions/targets were desired and at municipal waste landfills where VOC was reduced 75% via a
MACT control using projection factors of 0.25.
We applied New York State Implementation Plan available controls for the 1997 8-hour Ozone
standard for non-EGU point and nonpoint NOx and VOC sources based on NY State Department of
Environmental Conservation February 2008 guidance. These reductions are found in Appendix J,
located in Section 3.2.6.
4.2.6.1 2014 base-case reductions from the Portland Cement NESHAP
As indicated in Table 4-1, the Industrial Sectors Integrated Solutions (ISIS) model (EPA, 2010) was used to
project the cement industry component of the ptnonipm emissions modeling sector to 2014. This approach
provided reductions of criteria and hazardous air pollutants, including mercury. The ISIS cement emissions
were developed in support for the Portland Cement NESHAPs and the NSPS for the Portland cement
manufacturing industry.
The ISIS model produced a Portland Cement NESHAP policy case of multi-pollutant emissions for
individual cement kilns (emission inventory units) that were relevant for years 2013 through 2017. These
ISIS-based emissions included information on new cement kilns, facility and unit-level closures, and updated
policy case emissions at existing cement kilns. The units that opened or closed before 2010 were included in
the 2012 base case. The ISIS-based policy case predictions of emissions reductions and activity growth were
only included in the 2014 base case and not in the 2012 base case.
The ISIS model results for the future show a continuation of the recent trend in the cement sector of the
replacement of lower capacity, inefficient wet and long dry kilns with bigger and more efficient preheater
and precalciner kilns. Multiple regulatory requirements such as the NESHAP and NSPS currently apply to
the cement industry to reduce CAP and HAP emissions. Additionally, state and local regulatory
requirements might apply to individual cement facilities depending on their locations relative to ozone and
PM2.5 nonattainment areas. The ISIS model provides the emission reduction strategy that balances: 1)
optimal (least cost) industry operation, 2) cost-effective controls to meet the demand for cement, and 3)
emission reduction requirements over the time period of interest. Table 4-6 shows the magnitude of the
ISIS-based cement industry reductions in the future-year emissions that represent 2014, and the impact that
these reductions have on total stationary non-EGU point source (ptnonipm) emissions.
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Table 4-6. Future-year ISIS-based cement industry annual reductions (tons/yr)
for the non-EGU (ptnonipm) sector
Pollutant
Cement Industry
emissions in 2005
Decrease in cement
industry emissions
in 2014 vs 2005
% decrease in
ptnonipm from
cement reduction
NOx
193,000
56,740
2.4%
PM2.5
14,400
7,840
1.8%
S02
128,400
106,000
5.0%
VOC
6,900
5,570
0.4%
HC1
2,900
2,220
4.5%
4.2.6.2 Boiler reductions not associated with the MACT rule
The Boiler MACT ICR collected data on existing controls. We used an early version of a data base
developed for that rulemaking entitled "survey_database_2008_results2.mdb" (EPA-HQ-OAR-2002-0058-
0788) which is posted under the Technical Information for the Boiler MACT major source rule. We
extracted all controls that were installed after 2005, determined a percent reduction, and verified with source
owners that these controls were actively in use. In many situations we learned that the controls were on site
but were not in use. A summary of the plant-unit specific reductions that were verified to be actively in use
are summarized in Table 4-7.
Table 4-7. State-level non-MACT Boiler Reductions from ICR Data Gathering
Pre-controlled
Controlled
Percent
Emissions
Emissions
Reductions
Reduction
State
Pollutant
(tons)
(tons)
(tons)
%
Michigan
NOx
907
544
363
40
North Carolina
S02
652
65
587
90
Virginia
SO2
3379
338
3041
90
Washington
S02
639
383
256
40
North Carolina
HC1
31
3
28
90
4.2.6.3 RICE NESHAP
There are three rulemakings for National Emission Standards for Hazardous Air Pollutants (NESHAP) for
Reciprocating Internal Combustion Engines (RICE). These rules reduce HAPs from existing and new RICE
sources. In order to meet the standards, existing sources with certain types of engines will need to install
controls. In addition to reducing HAPs, these controls also reduce CAPs, specifically, CO, NOx, VOC, PM,
and SO2. In 2014 and beyond, compliance dates have passed for all three rules; thus all three rules are
included in the emissions projection. In 2012 only the earliest rule's compliance date has passed so only one
rule is included.
The rules and are listed below:
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National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion
Engines; Final Rule (69 FR 33473) published 06/15/04
National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion
Engines; Final Rule (FR 9648 ) published 03/03/10
National Emission Standards for Hazardous Air Pollutants for Reciprocating Internal Combustion
Engines; Final Rule (75 FR 51570) published 08/20/2010
The difference among these three rules is that they focus on different types of engines, different facility types
(major for HAPs, versus area for HAPs) and different engine sizes based on horsepower (HP). In addition,
they have different compliance dates. We project CAPs from the 2005 NEI RICE sources, based on the
requirements of the rule for existing sources only because the inventory includes only existing sources and
the current projection approach does not estimate emissions from new sources.
A complete discussion on the methodology to estimate year 2012 and year 2014 RICE controls is provided in
Appendix F in the Proposed Toxics Rule TSD. Impacts of the RICE controls on stationary non-EGU
emissions (nonpt and ptnonipm sectors), excluding WRAP, Texas, and Oklahoma oil and gas emissions (see
Section 4.2.7) are provided in Table 4-8.
Table 4-8. National Impact of RICE Controls on 2012 and 2014 Non-EGU Projections
Pollutant
2012 Reductions
2014 Reductions
CO
18,987
124,516
NOX
30,250
123,662
PM2.5
0
1,368
PM10
0
1,595
S02
0
23,368
VOC
1,069
15,934
4.2.6.4 Fuel sulfur rules
Fuel sulfur rules that were signed and implemented by June 30, 2014 are limited to Maine and New York.
No fuel sulfur rule reductions were available in other states and compliance dates for 2012. As standard
practice we have used June 30th as the cut-off date for all control programs to be included in a calendar year.
For example, a control program with a compliance (effective) date of June 30, 2012 would be included in the
2012 projected emissions; however, a control program effective July 1, 2012 would not be included in 2012
projections. Several other states have fuel sulfur rules that were in development but not finalized prior to
Transport Rule emissions processing.
The fuel sulfur content for all home heating oil SCCs in 2005 is assumed to by 3000 part per million (ppm).
Effective July 1, 2012, New York requires all heating oil sold in New York to contain no more than 15ppm
of sulfur, thus reducing SO2 emissions by 99.5% for 2014 projections (and no reduction for 2012). These
New York sulfur content reductions are further discussed at NRDC.
The Maine fuel sulfur rule effective January 1, 2014 reduces sulfur to 500ppm, resulting in an 83.33%
reduction from 3000 ppm. These Maine sulfur content reductions.
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Further reductions in NY, ME, and other states effective after June 30, 2014 are not included. The impact of
these fuel sulfur content reductions on S02 is shown in Table 4-9.
Table 4-9. Impact of Fuel Sulfur Controls on 2014 Non-EGU Projections
State
SO2 Reductions
Maine
7,053
New York
54,431
4.2.7 Oil and gas projections in TX, OK, and non-California WRAP states (nonpt)
For the 2005v4.2 platform, we incorporated updated 2005 oil and gas emissions from Texas and Oklahoma.
For Texas oil and gas production, we used 2012 and 2014 estimates from the Texas Commission of
Environmental Quality (TCEQ).
We also received 2008 data for Oklahoma that we used as the best available data to represent 2012 and 2014.
As with the 2005 v4 platform, the v4.2 platform utilizes the Phase II WRAP oil and gas emissions data for
the non-California Western Regional Air Partnership (WRAP) states for 2005. WRAP 2018 Phase II
emissions were also available but determined to be inappropriate for use in 2012 and 2014. Consequently,
we started with the base year emissions for Oklahoma and the WRAP states and applied these additional
reductions related to the RICE NESHAP.
For Oklahoma and WRAP oil and gas emissions, we applied CO, NOx, and VOC emissions reductions from
the Stationary Reciprocating Internal Combustion Engine (RICE) NESHAP, which we assumed has some
applicability to this industry (Appendix F in the Proposed Toxics Rule TSD). SO2 reductions associated
with the RICE NESHAP were also included for these same data for the year 2014 projection. Table 4-10
shows the 2005, 2012, and 2014 NOX and S02 emissions including RICE reductions for Oklahoma and the
WRAP states.
Table 4-10. Oil and Gas NOx and SO2 Emissions for 2005, 2012, and 2014 including additional reductions
due to the RICE NESHAP
NOX (tons)
S02 (tons)
State
2005
2012
2014
2005
2012
2014
Alaska
836
811
732
62
62
31
Arizona
13
12
12
Colorado
32,188
31,806
30,625
350
350
176
Montana
10,617
10,456
9,957
640
640
321
Nevada
71
69
62
1
1
0
New Mexico
61,674
60,317
56,119
369
369
188
North Dakota
6,040
5,861
5,306
688
688
355
Oklahoma
39,668
44,362
42,402
1,014
2
2
Oregon
61
60
55
South Dakota
566
550
502
43
43
21
Texas
42,854
46,251
39,462
5,977
43
38
Utah
6,896
6,777
6,409
149
149
75
Wyoming
36,172
35,505
33,442
541
541
272
Grand Total
237,656
242,837
225,085
9,834
2,888
1,479
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4.2.8 Future-year VOC Speciation for gasoline-related sources (ptnonipm, nonpt)
To account for the future projected increase in the ethanol content of fuels, we used different future-year
VOC speciation for certain gasoline-related emission sources. Such sources include gasoline stage II
(refueling vehicles), portable fuel containers (PFCs), and finished fuel storage and transport-related sources
related to bulk terminals (where the ethanol may be mixed) and downstream to the pump. We identified this
last group of sources as "btp" (from bulk terminals to pumps). While most of these sources are in the nonpt
sector, there are also some in the ptnonipm sector. In the 2005 base year, we used zero percent ethanol (E0)
fuel profiles. For the 2012 and 2014 profiles, we used combinations of E0 and ten percent ethanol (E10) fuel
profiles. The fuel type fraction was developed based on the Department of Energy Annual Energy Outlook
(AEO) 2007 projections of ethanol fuels for the year 2022. In the AEO 2007 data, the proportions of E0 and
E10 fuels are the same for 2012 and years beyond (even though the quantities of the two fuels change over
these years). The national level proportions were allocated to counties across the country using fuel
modeling at the EPA Office of Transportation and Air Quality. All gasoline stage II and "btp" sources used
the same combination of E0 and E10 headspace profiles as were used for exhaust and evaporative profiles.
4.3 Mobile source projections
Mobile source monthly inventories of onroad and nonroad mobile emissions were created for 2012 and 2014
using a combination of the NMIM and MOVES2010 models. Future-year emissions reflect onroad mobile
control programs including the Light-Duty Vehicle Tier 2 Rule, the Onroad Heavy-Duty Rule, and the
Mobile Source Air Toxics (MSAT2) final rule. Nonroad mobile emissions reductions for these years include
reductions to locomotives, various nonroad engines including diesel engines and various marine engine
types, fuel sulfur content, and evaporative emissions standards.
Onroad mobile sources are comprised of several components and are discussed in the next subsection (4.3.1).
Monthly nonroad mobile emission projections are discussed in subsection 4.3.2. Locomotives and Class 1
and Class 2 commercial marine vessel (C1/C2 CMV) projections are discussed in subsection 4.3.3, and Class
3 (C3) CMV projected emissions are discussed in subsection 4.3.4.
4.3.1 Onroad mobile (on_noadj, on_moves_runpm, on_moves_startpm)
The onroad emissions were primarily based on the 2010 version of the Motor Vehicle Emissions Simulator
(MOVES2010) - the same version as was used for 2005. The same MOVES-based PM2.5 temperature
adjustment factors were applied as were used in 2005 for running mode emissions; however, cold start
emissions used year-specific temperature adjustment factors. The temperature adjustments have the minor
limitation that they were based on the use of MOVES national default inputs rather than county-specific
inputs. This was because a county-specific database for input to MOVES was not available at the time this
approach was needed. However, the PM2.5 temperature adjustments are fairly insensitive to the county-
specific inputs, which is why this is only a minor limitation.
California onroad (on noadj)
Like year 2005 emissions, future-year California NH3 emissions are from MOVES runs for California,
disaggregated to the county level using NMIM. For all other pollutants, we did not use MOVES to generate
future-year onroad emissions for California, because the 2005 base year emissions were provided by
CARET s Emission Factors mobile model (EMFAC), outputs of which CARB submitted for the 2005 NEI.
For California, we chose an approach that would maintain consistency between the 2005 and 2012 and 2014
emissions. This approach involved computing projection factors from a consistent set of future and 2005-
year data provided by CARB based on the EMFAC2007 model. For 2012 emissions, we generated
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projection factors by dividing the EMFAC2007-based emissions for 2012 (linearly interpolated between year
2009 and year 2014) by the EMFAC2007-based emissions for 2005. These EMFAC-based emissions were
provided in March 2007. California does not specify road types, so we first used NMIM California ratios to
break out vehicle emissions to the match the more detailed NMIM level before projecting to 2012.
HAP emissions were computed as 2005v2-based HAP-CAP ratios applied to 2012 and 2014 CAP emissions
at the pollutant and Level 3 SCC (first 7 characters). HAPs were scaled to either of three pollutants: exhaust
PM2.5 (e.g., metals), exhaust VOC (e.g., exhaust mode VOC HAPs such as acetaldehyde and formaldehyde),
or evaporative VOC (e.g., evaporative mode VOC HAPs such as benzene).
Onroad mobile sector with no adjustment for daily temperature (on noadj)
As discussed in Section 2, the MOVES2010 model was used for all vehicles, road types, and pollutants.
Vehicle Miles Travelled (VMT) were projected using growth rates from the Department of Energy's
AE02009. We used MOVES2010 to create emissions by state, SCC, pollutant, emissions mode and month.
We then allocated these emissions to counties using ratios based on 2012 and 2015 NMIM county-level data
by state, SCC, pollutant, and emissions mode. 2014 NMIM data were not available for this effort, but the
2015 NMIM can reasonably be expected to be sufficient for 2014 state-county allocations for this purpose.
While the EPA intends to replace this approach with a county-specific implementation of MOVES for use in
future regulatory actions, this approach was the best approach available at the time of this modeling.
Onroad PM gasoline running and cold start mode sectors (onmovesstartpm and onmovesrunpm)
MOVES-based cold start and running mode emissions consist of gasoline exhaust speciated PM and
naphthalene. These pre-temperature-adjusted emissions at 72°F are projected to years 2012 and 2014 from
year 2005 inventories using the 2012- and 2014-specific runs of MOVES2010. VMT were projected using
growth rates from the AE02009. As with the on_noadj sector, the 2012 and 2014 MOVES2010 data were
created at the state-month level, and the 2012 and 2015 NMIM results were used to disaggregate the state
level results to the county level.
MOVES-based temperature adjustment factors were applied to gridded, hourly emissions using gridded,
hourly meteorology. As seen in Figure 4-1, for year 2012, we used the same temperature adjustment factors
as the 2005 base case for both start and running modes. However, cold start temperature adjustment factors
decrease slightly in future years, and for year 2014 processing, we updated the temperature adjustment
curves for these cold start emissions. These have little impact, reducing cold-start mode temperature-
adjusted PM and naphthalene by under 4% for temperatures down to 0 °F. Note that running exhaust
temperature adjustment factors are the same for all years. Also, these running mode exhaust mode emissions
are considerably larger than cold start mode emissions.
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Figure 4-1. MOVES exhaust temperature adjustment functions for 2005, 2012, and 2014
¦Run Exhaust:
All Years
1 Start Exhaust:
2005 & 2012
1 Start Exhaust:
2014
^ ^ ^ Q ^
Temperature (F)
4.3.2 Nonroad mobile (nonroad)
This sector includes monthly exhaust, evaporative and refueling emissions from nonroad engines (not
including commercial marine, aircraft, and locomotives) derived from NMIM for all states except California.
Like the onroad emissions, NMIM provides nonroad emissions for VOC by three emission modes: exhaust,
evaporative and refueling. Unlike the onroad sector, nonroad refueling emissions for nonroad sources are
not included in the nonpoint (nonpt) sector and so are retained in this sector.
With the exception of California, U.S. emissions for the nonroad sector (defined as the equipment types
covered by NMIM) were created using a consistent NMIM-based approach as was used for 2005, but
projected for 2012 and 2015. The 2012 and 2015 NMIM runs utilized the NR05d-Bond-final version of
NONROAD (which is equivalent to NONROAD2008a). Similar to the onroad mobile NMIM inventories,
year 2014 NMIM emissions were created by interpolating year 2012 and year 2015 NMIM inventories.
These future-year emissions account for increases in activity (based on NONROAD model default growth
estimates of future-year equipment population) and changes in fuels and engines that reflect implementation
of national regulations and local control programs that impact each year differently due to engine turnover.
The national regulations incorporated in the modeling are those promulgated prior to December 2009 and
beginning about 1990. Recent rules include:
"Clean Air Nonroad Diesel Final Rule - Tier 4": (http://www.epa.gov/nonroaddiesel/2004fr.htm ),
published June 29, 2004, and,
Control of Emissions from Nonroad Large Spark-Ignition Engines, and Recreational Engines (Marine
and Land-Based), November 8, 2002 ("Pentathalon Rule").
OTAQ's Locomotive Marine Rule
OTAQ's Small Engine Spark Ignition ("Bond") Rule
We have not included voluntary programs such as programs encouraging either no refueling or evening
refueling on Ozone Action Days and diesel retrofit programs. NMIM version 20071009, with county
database NCD20070912, and NONROAD model version NONROAD2008a was used to create NMIM
inventories for 2012 and 2015.
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California nonroad emissions
Similar to onroad mobile, NMIM was not used to generate future-year nonroad emissions for California,
other than for NH3. We used NMIM for California future nonroad NH3 emissions because CARB did not
provide these data for any nonroad vehicle types. As we did for onroad emissions, we chose a projection
approach that would maintain consistency between the base year and future-year emissions for nonroad
emissions in California.
California year 2014 nonroad CAP emissions are similar to those used in the 2002v3 projected inventory.
However, similar to onroad mobile, California nonroad HAPs were computed as ratios to select CAPs using
2005 NMIM CAP-HAP ratios.
California year 2012 nonroad CAP emissions were computed by linearly interpolating year 2009 and 2014
inventories. And 2012 HAP emissions were also computed using the same 2005-based CAP-HAP ratios
used to create 2014 HAP emissions.
4.3.3 Locomotives and Class 1 & 2 commercial marine vessels (alm_no_c3)
Future locomotive and Class 1 and Class 2 commercial marine vessel (CMV) emissions were calculated
using projection factors that were computed based on national, annual summaries of locomotive emissions in
2002 and future years. These national summaries were used to create national by-pollutant, by-SCC
projection factors; these factors include final locomotive-marine controls and are provided in Table 4-11.
Table 4-11. Factors applied to year 2005 emissions to project locomotives and Class 1 and Class 2
Commercial Marine Vessel Emissions
see
SCC Description
Pollutant
Projection Factor
2012
2014
2280002X00
Marine Vessels, Commercial;Diesel;Underway & port emissions
CO
0.972
0.968
2280002X00
Marine Vessels, Commercial;Diesel;Underway & port emissions
nh3
1.094
1.114
2280002X00
Marine Vessels, Commercial;Diesel;Underway & port emissions
NOx
0.851
0.792
2280002X00
Marine Vessels, Commercial;Diesel;Underway & port emissions
PM10
0.875
0.762
2280002X00
Marine Vessels, Commercial;Diesel;Underway & port emissions
pm25
0.890
0.775
2280002X00
Marine Vessels, Commercial;Diesel;Underway & port emissions
S02
0.531
0.278
2280002X00
Marine Vessels, Commercial;Diesel;Underway & port emissions
voc
0.951
0.897
2285002006
Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations
CO
1.232
1.272
2285002006
Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations
nh3
1.223
1.262
2285002006
Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations
NOx
0.732
0.711
2285002006
Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations
PM10
0.768
0.696
2285002006
Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations
pm25
0.778
0.705
2285002006
Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations
S02
0.166
0.005
2285002006
Railroad Equipment;Diesel;Line Haul Locomotives: Class I Operations
VOC
0.839
0.748
2285002007
Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations
CO
0.303
0.313
2285002007
Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations
nh3
1.223
1.262
2285002007
Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations
NOx
0.339
0.350
2285002007
Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations
PM10
0.283
0.286
2285002007
Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations
PM25
0.286
0.288
2285002007
Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations
S02
0.038
0.001
2285002007
Railroad Equipment;Diesel;Line Haul Locomotives: Class II / III Operations
VOC
0.291
0.300
2285002008
Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak)
CO
1.030
1.046
2285002008
Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak)
nh3
1.223
1.262
2285002008
Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak)
NOx
0.667
0.598
2285002008
Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak)
PM10
0.660
0.576
2285002008
Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak)
pm25
0.662
0.578
90
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SCC
SCC Description
Pollutant
Pro jection Factor
2012
2014
2285002008
Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak)
S02
0.156
0.005
2285002008
Railroad Equipment;Diesel;Line Haul Locomotives: Passenger Trains (Amtrak)
VOC
0.738
0.633
2285002009
Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines
CO
1.015
1.032
2285002009
Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines
nh3
1.223
1.262
2285002009
Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines
NOx
0.658
0.590
2285002009
Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines
PM10
0.650
0.568
2285002009
Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines
PM25
0.651
0.568
2285002009
Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines
S02
0.155
0.005
2285002009
Railroad Equipment;Diesel;Line Haul Locomotives: Commuter Lines
VOC
0.728
0.625
2285002010
Railroad Equipment;Diesel;Yard Locomotives
CO
1.239
1.279
2285002010
Railroad Equipment;Diesel;Yard Locomotives
nh3
1.223
1.262
2285002010
Railroad Equipment;Diesel;Yard Locomotives
NOx
1.133
1.127
2285002010
Railroad Equipment;Diesel;Yard Locomotives
PM10
0.942
0.919
2285002010
Railroad Equipment;Diesel;Yard Locomotives
PM25
0.962
0.938
2285002010
Railroad Equipment;Diesel;Yard Locomotives
S02
0.183
0.005
2285002010
Railroad Equipment;Diesel;Yard Locomotives
VOC
1.548
1.526
The future-year locomotive emissions account for increased fuel consumption based on Energy Information
Administration (EIA) fuel consumption projections for freight rail, and emissions reductions resulting from
emissions standards from the Final Locomotive-Marine rule (EPA. 2009). This rule lowered diesel sulfur
content and tightened emission standards for existing and new locomotives and marine diesel emissions to
lower future-year PM, SO2, and NOx, and is documented at. Voluntary retrofits under the National Clean
Diesel Campaign are not included in our projections.
We applied HAP factors for VOC HAPs by using the VOC projection factors to obtain 1,3-butadiene,
acetaldehyde, acrolein, benzene, and formaldehyde.
Class 1 and 2 CMV gasoline emissions (SCC = 2280004000) were not changed for future-year processing.
C1/C2 diesel emissions (SCC = 2280002100 and 2280002200) were projected based on the Final
Locomotive Marine rule national-level factors provided in Table 4-11. Similar to locomotives, VOC HAPs
were projected based on the VOC factor.
Delaware provided updated future-year NOx, SO2, and PM emission estimates for C1/C2 CMV as part of the
Transport Rule comments. These updated emissions were applied to the 2012 and 2014 inventories and
override the C1/C2 projection factors in Table 4-11.
4.3.4 Class 3 commercial marine vessels (seca_c3)
The seca_c3 sector emissions data were provided by OTAQ in an ASCII raster format used since the SO2
Emissions Control Area-International Marine Organization (ECA-IMO) project began in 2005. The (S)ECA
Category 3 (C3) commercial marine vessel 2002 base-case emissions were projected to year 2005 for the
2005 base case and to years 2012 and 2014 for the future base cases. Both future base cases include ECA-
IMO controls. An overview of the ECA-IMO project and future-year goals for reduction of NOx, SO2, and
PM C3 emissions.
The resulting coordinated strategy, including emission standards under the Clean Air Act for new marine
diesel engines with per-cylinder displacement at or above 30 liters, and the establishment of Emission
Control Areas.
91
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These projection factors vary depending on geographic region and pollutant; where VOC HAPs are assigned
the same growth rates as VOC. The projection factors used to create the 2012 and 2014 seca_c3 sector
emissions are provided in Table 4-12. Note that these factors are relative to 2002. Factors relative to 2005
can be computed from the 2002-2005 factors.
The geographic regions are described in the ECA Proposal technical support document. These regions extend
up to 200 nautical miles offshore, though less at international boundaries. North and South Pacific regions
are divided by the Oregon-Washington border, and East Coast and Gulf Coast regions are divided east-west
by roughly the upper Florida Keys just southwest of Miami.
Delaware provided updated future-year NOx, SO2, and PM emission estimates for the C3 CMV as part of the
Transport Rule comments. These updated emissions were applied to the 2012 and 2014 inventories and
override the C3 projection factors in Table 4-12.
The factors to compute HAP emission are based on emissions ratios discussed in the 2005v4 documentation.
As with the 2005 base case, this sector uses CAP-HAP VOC integration.
Table 4-12. NOx, SO2, and PM2.5 Factors to Project Class 3 Commercial Marine Vessel emissions to 2012
and 2014
NOx
SO2
PM2.5
2012
2014
2012
2014
2012
2014
Alaska East
1.26234
1.32620
0.52912
0.56462
0.52433
0.55951
Alaska West
1.28461
1.35119
1.33532
1.42491
1.33555
1.42515
East Coast
1.33102
1.39686
0.55987
0.61140
0.51862
0.56635
Gulf Coast
1.12285
1.14364
0.47456
0.50248
0.43526
0.46087
Hawaii East
1.37239
1.45513
0.61127
0.67392
0.54920
0.60550
Hawaii West
1.45767
1.54847
1.59605
1.75964
1.59408
1.75748
North Pacific
1.19916
1.23653
0.54159
0.57792
0.47330
0.50506
South Pacific
1.40836
1.49931
0.64318
0.71344
0.54825
0.60797
Great Lakes
1.08304
1.10302
0.42239
0.43687
0.39684
0.41045
Outside ECA
1.37211
1.44085
1.52102
1.65818
1.52102
1.65818
4.3.5 Future-year VOC Speciation (on_noadj, nonroad)
We used speciation profiles for VOC in the nonroad and on noadj sectors that account for the increase in
ethanol content of fuels in future years. The same future-year profiles were used for 2012 and 2014. The
combination profiles use proportions of E0 and E10 expected in the future based on AEO 2007 projections of
E10 and E0 fuel use. The proportions of E0 and E10 are the same for 2012 and years beyond (even though
the quantities of the two fuels change over these years). The national proportions were allocated to counties
across the country using the same fuel modeling done for the stationary source gasoline speciation, as
discussed in Section 4.2.8.
The speciation of onroad exhaust VOC additionally accounts for a portion of the vehicle fleet meeting Tier 2
standards; different exhaust profiles are available for pre-Tier 2 versus Tier 2 vehicles. Thus for exhaust
VOC, a combination of pre-Tier 2 E0, pre-Tier 2 E10, Tier 2 E0 and Tier 2 E10 profiles are used. Figure 4-2
shows the Tier 2 fraction of Light Duty Vehicles for different future years in terms of different metrics. For
previous modeling applications, we based the fraction on the population of vehicles. However, since these
vehicles emit a smaller portion of VOC, a more appropriate metric for use in weighting the speciation
profiles is the fraction of exhaust total hydrocarbons (THC) which is used in the 2012 case described here.
92
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The fraction of Tier 2 emissions used here for 2012 is 0.182. We erroneously used this same fraction for
2014; the correct fraction of Tier 2 emissions for 2014 should have been 0.261.
Table 4-13 summarizes the profiles combined for the source categories and VOC emission modes used.
Table 4-13. Future-year Profiles for Mobile Source Related Sources
Sector
Type of profile
Profile Codes Combined for the Future-year Speciation
Stationary
headspace
8762: Composite Profile - Gasoline Headspace Vapor using 0% Ethanol
8763: Composite Profile - Gasoline Headspace Vapor using 10% Ethanol
Nonroad
exhaust
Pre-Tier 2 vehicle
exhaust
8750: Gasoline Exhaust - Reformulated gasoline
8751: Gasoline Exhaust - E10 ethanol gasoline
Onroad and
Nonroad
evap*
Evaporative
8753: Gasoline Vehicle - Evaporative emission - Reformulated gasoline
8754: Gasoline Vehicle - Evaporative emission - E10 ethanol gasoline
Nonroad
refueling
headspace
Same as Stationary
Onroad
exhaust
Pre-Tier 2 vehicle
exhaust and Tier 2
vehicle exhaust
8750: Gasoline Exhaust - Reformulated gasoline
8751: Gasoline Exhaust - E10 ethanol gasoline
8756: Composite Profile - Gasoline Exhaust - Tier 2 light-duty vehicles using
0% Ethanol
8757: Composite Profile - Gasoline Exhaust - Tier 2 light-duty vehicles using
10% Ethanol
E0 and E10 combinations are based on AE02007 projections of E0 and E10 fuel
Tier 2 and pre-Tier 2 combinations are based on the 2012 contribution of Tier 2 exhaust emissions
Figure 4-2. Tier 2 Fraction of Light Duty Vehicles
¦Exhaust THC
Vehicle Miles Traveled
Population
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
Calendar Year
93
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4.4 Canada, Mexico, and Offshore sources (othar, othon, and othpt)
Emissions for Canada, Mexico, and offshore sources were not projected to future years, and are therefore the
same as those used in the 2005 base case. Therefore, the Mexico emissions are based on year 1999, offshore
oil is based on year 2005, and Canada is based on year 2006. For both Mexico and Canada, their responsible
agencies did not provide future-year emissions that were consistent with the base year emissions.
94
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5 Source Apportionment
The EPA prepared special emissions inputs for the CAMx model to allow CAMx to be used for source
apportionment modeling. Source apportionment modeling was used to quantify the impact of emissions in
specific upwind states on projected downwind nonattainment and maintenance receptors for both PM2.5 and
8-hour ozone. To prepare these emissions, the EPA prepared special tagging input files called GSTAG files
for the SMOKE speciation processor.
The tagging input files and custom SMOKE scripts implemented tagging by state of all source emissions
except for biogenic and wildfire emissions for all ozone and PM2.5 precursors. Separate tagging runs were
done for ozone and PM2.5 precursors. Biogenic and wildfire emissions were not tagged by state because they
are generally considered not feasible for emissions controls, but these were tagged as "other sources" and
their contributions could be tracked in total without association with individual states. Prescribed burning
and agricultural burning were included in the tagged emissions. The states the EPA analyzed using source
apportionment for ozone and for PM2.5 are: Alabama, Arkansas, Connecticut, Delaware, Florida, Georgia,
Illinois, Indiana, Iowa, Kansas, Kentucky, Louisiana, Maine, Maryland, Massachusetts, Michigan,
Minnesota, Mississippi, Missouri, Nebraska, New Hampshire, New Jersey, New York, North Carolina,
North Dakota, Ohio, Oklahoma, Pennsylvania, Rhode Island, South Carolina, South Dakota, Tennessee,
Texas, Vermont, Virginia, West Virginia, Washington D.C., and Wisconsin. There were also several other
states that are only partially contained within the 12 km modeling domain (i.e., Colorado, Montana, New
Mexico, and Wyoming). However, the EPA did not individually track the emissions or assess the
contribution from emissions in these states
6 Remedy Case
The 2014 Remedy Case for the Transport Rule represents the implementation of SO2, annual NOx, and
ozone-season NOx emission reductions to address upwind state emissions that contribute significantly to
nonattainment in, or, interfere with maintenance by downwind states with respect to the existing ozone and
PM2.5 NAAQS standards in the eastern U.S. The final Transport Rule requires SO2 and/or NOx reductions
from EGUs in 27 states starting in 2012. For the remedy case modeling, the emissions for all sectors were
unchanged from the base-case modeling except for those from EGUs (the ptipm sector). The EPA used the
IPM model to project the 2014 remedy case EGU emissions. The changes in EGU SO2 and NOx emissions
as a result of the control case for the lower 48 states are summarized in Section 7. Section 7 also provides
state-specific summaries of EGU NOx and SO2 for the lower 48 states. Additional details on the changes
that resulted from the remedy case are provided in the Transport Rule Final Regulatory Impact Analysis
(RIA), Chapter 7 (Cost, Economic, and Energy Impacts), which describes the modeling conducted to
estimate the cost, economic, and energy impacts to the power sector.
The 23 states covered by the annual SO2 and NOx reduction requirements for the annual and/or 24-hour
PM2.5 standards in the remedy case are colored in blue and green in Figure 6-1. Figure 6-2 distinguishes
between the "Group 1" states (in red) and the "Group 2" states (in orange); the Group 1 states are subject to a
second, more stringent phase of SO2 reductions starting in 2014 (sections VI and VII of the preamble to the
final Transport Rule discuss the SO2 groups in detail). All states covered for the annual and/or 24-hour
PM2.5 standards are in one annual NOx tier with uniform stringency beginning in 2012. Table 6-1 shows the
groups in which each state is included, including whether the state is included in the Eastern modeling
domain. Section 7 provides annual SO2 and NOx summaries for these selected groups/tiers of states.
95
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The 20 states required to make ozone-season NOx reductions to address the 8-hour ozone standard in the
final Transport Rule are shown in green and yellow in Figure 6-1. In these states, ozone-season NOx
reductions begin with the 2012 ozone season. As discussed in section III of the preamble, the EPA issued a
supplemental proposal to provide the opportunity for public comment on inclusion of six additional states in
the Transport Rule ozone-season program: Iowa, Kansas, Michigan, Missouri, Oklahoma, and Wisconsin.
These six states are also shown in green or yellow in Figure 6-1. Section 7 provides ozone-season NOx
emissions summaries for the states required in the final Transport Rule to make ozone-season NOx
reductions and the six additional states addressed in the supplemental proposal. Figure 6-1 shows for each of
the contiguous 48 states the components of the rule they fall under, and whether they are included in the
Eastern modeling domain. Tribal land emissions are not associated with particular states; those few tribal
emissions in the eastern domain are very small and are not associated with existing units covered by the
Transport Rule.
The emissions, cost, air quality, and benefits analyses done for the Transport Rule are from a modeling
scenario that requires annual SO2 and NOx reductions in the 23 states covered for the PM2.5 standards, and
ozone season NOx requirements in the 20 states covered for the ozone standard and the six states addressed
by the supplemental proposal (26 states total) as shown in Figure 6-1.
Figure 6-1. States Covered by the Final Transport Rule
(Figure 6-1 includes six states--IA, KS, MI, MO, OK, and WI~not covered for ozone-season requirements in the final rule, for
which the EPA issued a supplemental proposal to require ozone-season reductions.)
~ Slates controlled for both fine panicles {annual S02 and NOx) and ozone (ozone season NOx) (21 States)
~ States controlled for fine particles only (annual S02 and NOx) (2 States)
States controlled for ozone only (ozone season NOx) (5 States)
States not covered by the Transport Rule
96
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Figure 6-2. Group 1 and Group 2 States Covered by the Annual PM Component of the
Final Transport Rule
| Group 1 States (16 States)
| Group 2 States (7 States)
| States not covered by the annual Transport Rule
Table 6-1. Transport Rule Status of States
State
State
EPA
Region
Covered for
PlVh.s-
Group 1
SO2
Covered for
PM2.5 -
Group 2
SO2
Covered
for Ozone
in
Transport
Rule
Covered for
Ozone in
Supplemental
Proposal
Total
State
Coverage
In
Eastern
Domain
Wester
n State
ALABAMA
AL
4
0
1
1
0
1
1
0
ARIZONA
AZ
9
0
0
0
0
0
0
1
ARKANSAS
AR
6
0
0
1
0
1
1
0
CALIFORNIA
CA
9
0
0
0
0
0
0
1
COLORADO
CO
8
0
0
0
0
0
0
1
CONNECTICUT
CT
1
0
0
0
0
0
1
0
DELAWARE
DE
3
0
0
0
0
0
1
0
DISTRICT OF
COLUMBIA
DC
3
0
0
0
0
0
1
0
FLORIDA
FL
4
0
0
1
0
1
1
0
GEORGIA
GA
4
0
1
1
0
1
1
0
IDAHO
ID
10
0
0
0
0
0
0
1
97
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State
State
EPA
Region
Covered for
PlVh.s-
Group 1
SO2
Covered for
PM2.5 -
Group 2
SO2
Covered
for Ozone
in
Transport
Rule
Covered for
Ozone in
Supplemental
Proposal
Total
State
Coverage
In
Eastern
Domain
Wester
n State
ILLINOIS
IL
5
1
0
1
0
1
1
0
INDIANA
IN
5
1
0
1
0
1
1
0
IOWA
IA
7
1
0
0
1
1
1
0
KANSAS
KS
7
0
1
0
1
1
1
0
KENTUCKY
KY
4
1
0
1
0
1
1
0
LOUISIANA
LA
6
0
0
1
0
1
1
0
MAINE
ME
1
0
0
0
0
0
1
0
MARYLAND
MD
3
1
0
1
0
1
1
0
MASSACHUSETTS
MA
1
0
0
0
0
0
1
0
MICHIGAN
Ml
5
1
0
0
1
1
1
0
MINNESOTA
MN
5
0
1
0
0
1
1
0
MISSISSIPPI
MS
4
0
0
1
0
1
1
0
MISSOURI
MO
7
1
0
0
1
1
1
0
MONTANA
MT
8
0
0
0
0
0
1
NEBRASKA
NE
7
0
1
0
0
1
1
0
NEVADA
NV
9
0
0
0
0
0
1
NEW HAMPSHIRE
NH
1
0
0
0
0
0
1
0
NEW JERSEY
NJ
2
1
0
1
0
1
1
0
NEW MEXICO
NM
6
0
0
0
0
0
1
NEW YORK
NY
2
1
0
1
0
1
1
0
NORTH CAROLINA
NC
4
1
0
1
0
1
1
0
NORTH DAKOTA
ND
8
0
0
0
0
0
1
0
OHIO
OH
5
1
0
1
0
1
1
0
OKLAHOMA
OK
6
0
0
0
1
1
1
0
OREGON
OR
10
0
0
0
0
0
1
PENNSYLVANIA
PA
3
1
0
1
0
1
1
0
RHODE ISLAND
Rl
1
0
0
0
0
0
1
0
SOUTH CAROLINA
SC
4
0
1
1
0
1
1
0
SOUTH DAKOTA
SD
8
0
0
0
0
0
1
0
TENNESSEE
TN
4
1
0
1
0
1
1
0
TEXAS
TX
6
0
1
1
0
1
1
0
TRIBAL
0
0
0
0
0
1
0
UTAH
UT
8
0
0
0
0
0
1
VERMONT
VT
1
0
0
0
0
0
1
0
VIRGINIA
VA
3
1
0
1
0
1
1
0
WASHINGTON
WA
10
0
0
0
0
0
1
WEST VIRGINIA
WV
3
1
0
1
0
1
1
0
WISCONSIN
Wl
5
1
0
0
1
1
1
0
WYOMING
WY
8
0
0
0
0
0
0
1
98
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Covered
Covered for
Covered for
for Ozone
Covered for
PM2.5-
PM2.5 -
in
Ozone in
Total
In
EPA
Group 1
Group 2
Transport
Supplemental
State
Eastern
Wester
State
State
Region
SO2
SO2
Rule
Proposal
Coverage
Domain
n State
TOTAL COUNT
16
7
26
6
28
39
11
7 Emission Summaries
The following tables summarize emissions differences between the 2005 base case, 2012 base case, 2014
base case, and 2014 EGU control case at various levels of geographic, temporal, and emission sector
resolution.
Table 7-1 and
Table 7-2 provide NOx and SO2 emissions, respectively (including average fire emissions and excluding
biogenic emissions) by state for the 2005 base case, 2012 base case, 2014 base case, and 2014 EGU control
cases, as well as differences and percent differences between these cases. Note that the average fire
emissions are the same for all emissions cases. Table 7-3 and Table 7-4 provide EGU sector (ptipm) NOx
and SO2 emissions (respectively) by state for the 2005 base case, 2012 base case, 2014 base case, and 2014
EGU control cases, as well as differences and percent differences between these cases.
Table 7-5 and Table 7-6 provide NOx and SO2 emissions, respectively (including average fire emissions and
excluding biogenic emissions) for the "group 1" states, "group 2" states, and cumulative totals for all states
included in the Transport Rule for PM. See Figure 6-2 for a map of the group 1 and group 2 states.
Emissions are provided for the 2005 base case, 2012 base case, 2014 base case, and 2014 EGU remedy
cases, as well as differences and percent differences between these cases. We also provide summaries for all
"Eastern Modeling Domain" states and "All Western States". The western states are defined as Arizona,
California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming.
States in the eastern modeling domain are defined as the rest of the contiguous (lower 48 states) U.S. plus the
District of Columbia.
Table 7-7 and Table 7-8 provide EGU sector only (ptipm) NOx and SO2 emissions (respectively) for the
"group 1" states, "group 2" states, and cumulative totals for all states included in the Transport Rule for PM.
See Figure 6-2 for a map of the group 1 and group 2 states. Emissions are provided for the 2005 base case,
2012 base case, 2014 base case, and 2014 EGU remedy case, as well as differences and percent differences
between these cases. Summaries for the eastern modeling domain states and western states are also
provided.
Table 7-9 provides summer (defined as May through September) EGU and Total Anthropogenic NOx for the
states that the Transport Rule covers for ozone. See Figure 6-2 for a map of these states. Emissions are
provided for the 2005 base case, 2012 base case, 2014 base case, and 2014 EGU control ("remedy") cases, as
well as differences and percent differences between these cases.
Additional information and pollutants are provided in the accompanying workbook:
TransportRuleFinal_EmissionsSummaries.xls.
99
-------
Table 7-1. State-level Total NOx Emissions for each Transport Rule Modeling Case in 48 States and Washington, D.C.
State
2005 Base
2012 Base
2014 Base
2014
Remedy
2012 Base minus 2005
Base
2014 Base minus 2012
Base
2014 Remedy minus
2014 Base
Difference
% Diff.
Difference
% Diff
Difference
% Diff.
Alabama
484,282
343,206
321,975
315,155
-141,076
-29.1%
-21,231
-6.2%
-6,820
-2.1%
Arizona
400,774
274,608
248,574
248,570
-126,166
-31.5%
-26,034
-9.5%
-4
0.0%
Arkansas
264,979
205,673
193,670
194,964
-59,306
-22.4%
-12,002
-5.8%
1,293
0.7%
California
1,333,571
1,030,864
942,254
942,157
-302,706
-22.7%
-88,610
-8.6%
-97
0.0%
Colorado
334,635
253,291
237,296
237,246
-81,344
-24.3%
-15,995
-6.3%
-50
0.0%
Connecticut
129,736
88,660
80,787
80,793
-41,076
-31.7%
-7,873
-8.9%
6
0.0%
Delaware
58,486
35,549
31,729
31,744
-22,936
-39.2%
-3,820
-10.7%
15
0.0%
District of
Columbia
16,802
11,040
9,773
9,773
-5,762
-34.3%
-1,267
-11.5%
0
0.0%
Florida
1,056,174
683,733
638,227
616,154
-372,441
-35.3%
-45,506
-6.7%
-22,073
-3.5%
Georgia
662,673
456,393
403,691
395,764
-206,280
-31.1%
-52,702
-11.5%
-7,927
-2.0%
Idaho
122,228
105,888
101,710
101,710
-16,340
-13.4%
-4,178
-3.9%
0
0.0%
Illinois
865,139
583,602
546,467
540,361
-281,537
-32.5%
-37,135
-6.4%
-6,107
-1.1%
Indiana
673,669
455,325
431,342
424,250
-218,344
-32.4%
-23,983
-5.3%
-7,092
-1.6%
Iowa
331,034
238,425
223,390
217,221
-92,608
-28.0%
-15,036
-6.3%
-6,169
-2.8%
Kansas
387,554
271,578
248,692
240,384
-115,976
-29.9%
-22,886
-8.4%
-8,308
-3.3%
Kentucky
482,262
318,048
294,262
286,806
-164,214
-34.1%
-23,786
-7.5%
-7,456
-2.5%
Louisiana
626,542
494,774
466,089
466,098
-131,768
-21.0%
-28,686
-5.8%
9
0.0%
Maine
86,094
66,633
61,657
61,657
-19,461
-22.6%
-4,975
-7.5%
0
0.0%
Maryland
312,230
197,441
181,909
181,533
-114,789
-36.8%
-15,533
-7.9%
-375
-0.2%
Massachusetts
283,638
189,620
175,275
175,316
-94,018
-33.1%
-14,345
-7.6%
41
0.0%
Michigan
718,454
481,684
449,343
442,544
-236,770
-33.0%
-32,341
-6.7%
-6,798
-1.5%
Minnesota
506,905
364,052
345,483
338,438
-142,853
-28.2%
-18,568
-5.1%
-7,045
-2.0%
Mississippi
324,595
232,009
216,438
216,224
-92,587
-28.5%
-15,571
-6.7%
-214
-0.1%
Missouri
563,356
374,298
357,846
352,631
-189,059
-33.6%
-16,451
-4.4%
-5,216
-1.5%
Montana
149,429
97,575
92,723
92,627
-51,854
-34.7%
-4,852
-5.0%
-96
-0.1%
Nebraska
263,714
197,887
186,408
169,571
-65,827
-25.0%
-11,479
-5.8%
-16,836
-9.0%
Nevada
151,905
86,487
81,041
81,017
-65,418
-43.1%
-5,446
-6.3%
-24
0.0%
New Hampshire
73,325
50,415
47,637
47,482
-22,910
-31.2%
-2,778
-5.5%
-156
-0.3%
100
-------
State
2005 Base
2012 Base
2014 Base
2014
Remedy
2012 Base minus 2005
Base
2014 Base minus 2012
Base
2014 Remedy minus
2014 Base
Difference
% Diff.
Difference
% Diff
Difference
% Diff.
New Jersey
341,376
230,816
210,127
209,841
-110,559
-32.4%
-20,690
-9.0%
-286
-0.1%
New Mexico
343,139
281,341
264,414
264,502
-61,798
-18.0%
-16,926
-6.0%
88
0.0%
New York
688,109
491,308
459,087
457,927
-196,800
-28.6%
-32,221
-6.6%
-1,160
-0.3%
North Carolina
554,183
352,649
321,544
317,230
-201,534
-36.4%
-31,106
-8.8%
-4,314
-1.3%
North Dakota
182,289
133,332
127,125
127,127
-48,956
-26.9%
-6,207
-4.7%
2
0.0%
Ohio
906,327
560,718
522,450
508,054
-345,609
-38.1%
-38,268
-6.8%
-14,396
-2.8%
Oklahoma
434,284
344,447
328,683
305,859
-89,837
-20.7%
-15,764
-4.6%
-22,823
-6.9%
Oregon
240,218
189,886
179,324
179,371
-50,332
-21.0%
-10,563
-5.6%
48
0.0%
Pennsylvania
781,647
565,051
529,673
514,563
-216,596
-27.7%
-35,378
-6.3%
-15,110
-2.9%
Rhode Island
28,381
20,756
18,808
18,808
-7,625
-26.9%
-1,948
-9.4%
0
0.0%
South Carolina
314,276
216,883
204,389
202,118
-97,393
-31.0%
-12,494
-5.8%
-2,271
-1.1%
South Dakota
91,336
70,618
65,498
65,500
-20,717
-22.7%
-5,121
-7.3%
3
0.0%
Tennessee
527,027
338,047
302,103
293,339
-188,980
-35.9%
-35,944
-10.6%
-8,764
-2.9%
Texas
2,006,916
1,501,170
1,372,735
1,368,612
-505,746
-25.2%
-128,435
-8.6%
-4,123
-0.3%
Tribal
13,400
13,304
13,137
13,137
-96
-0.7%
-167
-1.3%
0
0.0%
Utah
216,810
179,535
170,840
170,840
-37,275
-17.2%
-8,696
-4.8%
0
0.0%
Vermont
25,696
23,142
22,824
22,824
-2,554
-9.9%
-318
-1.4%
0
0.0%
Virginia
488,263
359,907
334,720
333,985
-128,355
-26.3%
-25,187
-7.0%
-735
-0.2%
Washington
357,674
268,870
249,322
249,322
-88,804
-24.8%
-19,548
-7.3%
0
0.0%
West Virginia
308,655
172,143
166,094
155,245
-136,512
-44.2%
-6,049
-3.5%
-10,849
-6.5%
Wisconsin
401,226
279,465
262,201
254,989
-121,760
-30.3%
-17,264
-6.2%
-7,212
-2.8%
Wyoming
236,894
191,051
183,726
184,297
-45,843
-19.4%
-7,325
-3.8%
571
0.3%
Grand Total
21,152,309
14,973,199
13,924,510
13,725,678
-6,179,110
-29.2%
-1,048,689
-7.0%
-198,832
-1.4%
101
-------
Table 7-2. State-level Total SO2 Emissions for each Transport Rule Modeling Case in 48 States and Washington, D.C.
State
2005 Base
2012 Base
2014 Base
2014
Remedy
2012 Base minus 2005
Base
2014 Base minus 2012
Base
2014 Remedy minus 2014
Base
Difference
% Diff.
Difference
% Diff.
Difference
% Diff.
Alabama
589,408
574,045
534,700
290,925
-15,363
-2.6%
-39,345
-6.9%
-243,775
-45.6%
Arizona
92,231
65,046
65,792
65,792
-27,185
-29.5%
746
1.1%
0
0.0%
Arkansas
115,087
129,337
139,599
146,873
14,250
12.4%
10,262
7.9%
7,274
5.2%
California
164,217
136,846
119,268
119,268
-27,371
-16.7%
-17,579
-12.8%
0
0.0%
Colorado
82,213
63,748
72,227
83,980
-18,465
-22.5%
8,479
13.3%
11,753
16.3%
Connecticut
34,576
24,455
24,618
24,727
-10,121
-29.3%
163
0.7%
109
0.4%
Delaware
71,449
10,703
9,311
9,311
-60,746
-85.0%
-1,392
-13.0%
0
0.0%
District of
Columbia
3,961
2,289
2,230
2,230
-1,672
-42.2%
-59
-2.6%
0
0.0%
Florida
596,729
247,550
280,233
284,700
-349,179
-58.5%
32,683
13.2%
4,468
1.6%
Georgia
744,119
511,422
274,332
197,251
-232,697
-31.3%
-237,090
-46.4%
-77,080
-28.1%
Idaho
27,166
24,326
24,248
24,248
-2,840
-10.5%
-79
-0.3%
0
0.0%
Illinois
518,531
608,867
260,031
251,073
90,336
17.4%
-348,835
-57.3%
-8,959
-3.4%
Indiana
1,040,947
929,162
863,923
331,182
-111,785
-10.7%
-65,239
-7.0%
-532,740
-61.7%
Iowa
225,451
206,314
198,747
149,491
-19,136
-8.5%
-7,567
-3.7%
-49,256
-24.8%
Kansas
196,515
116,861
117,050
92,971
-79,654
-40.5%
189
0.2%
-24,078
-20.6%
Kentucky
573,604
580,849
547,085
176,007
7,244
1.3%
-33,764
-5.8%
-371,078
-67.8%
Louisiana
307,340
249,655
261,579
282,552
-57,685
-18.8%
11,924
4.8%
20,973
8.0%
Maine
35,129
27,598
20,642
20,642
-7,531
-21.4%
-6,956
-25.2%
0
0.0%
Maryland
371,166
128,360
120,089
107,531
-242,806
-65.4%
-8,271
-6.4%
-12,558
-10.5%
Massachusetts
138,551
53,866
57,914
57,913
-84,686
-61.1%
4,049
7.5%
-1
0.0%
Michigan
492,106
362,718
364,035
257,233
-129,388
-26.3%
1,317
0.4%
-106,802
-29.3%
Minnesota
155,736
109,940
112,099
90,784
-45,796
-29.4%
2,158
2.0%
-21,315
-19.0%
Mississippi
121,397
63,330
64,156
65,293
-58,066
-47.8%
825
1.3%
1,137
1.8%
Missouri
423,253
483,607
511,664
308,275
60,354
14.3%
28,057
5.8%
-203,388
-39.8%
Montana
39,518
25,621
26,678
34,058
-13,897
-35.2%
1,057
4.1%
7,379
27.7%
Nebraska
100,026
87,120
85,799
84,065
-12,906
-12.9%
-1,321
-1.5%
-1,734
-2.0%
Nevada
73,018
29,694
30,112
30,112
-43,325
-59.3%
418
1.4%
0
0.0%
102
-------
State
2005 Base
2012 Base
2014 Base
2014
Remedy
2012 Base minus 2005
Base
2014 Base minus 2012
Base
2014 Remedy minus 2014
Base
Difference
% Diff.
Difference
% Diff.
Difference
% Diff.
New
Hampshire
63,614
13,401
16,391
16,680
-50,213
-78.9%
2,990
22.3%
289
1.8%
New Jersey
91,898
49,252
61,455
28,841
-42,646
-46.4%
12,203
24.8%
-32,614
-53.1%
New Mexico
50,755
25,254
26,507
28,575
-25,501
-50.2%
1,253
5.0%
2,068
7.8%
New York
386,707
232,727
163,302
135,575
-153,980
-39.8%
-69,425
-29.8%
-27,727
-17.0%
North Carolina
609,652
231,489
208,652
151,982
-378,163
-62.0%
-22,837
-9.9%
-56,670
-27.2%
North Dakota
160,082
118,490
119,385
119,375
-41,592
-26.0%
895
0.8%
-9
0.0%
Ohio
1,274,427
999,536
966,938
294,714
-274,890
-21.6%
-32,598
-3.3%
-672,224
-69.5%
Oklahoma
167,918
178,504
175,459
175,550
10,586
6.3%
-3,045
-1.7%
91
0.1%
Oregon
44,438
36,494
37,175
37,175
-7,945
-17.9%
681
1.9%
0
0.0%
Pennsylvania
1,172,555
638,071
645,278
261,173
-534,483
-45.6%
7,207
1.1%
-384,105
-59.5%
Rhode Island
7,366
6,391
6,385
6,385
-975
-13.2%
-6
-0.1%
0
0.0%
South Carolina
275,871
231,565
258,231
145,737
-44,306
-16.1%
26,666
11.5%
-112,494
-43.6%
South Dakota
29,083
42,688
42,453
42,453
13,605
46.8%
-235
-0.6%
0
0.0%
Tennessee
378,676
419,588
378,878
159,131
40,912
10.8%
-40,710
-9.7%
-219,747
-58.0%
Texas
927,857
712,582
704,311
517,627
-215,275
-23.2%
-8,271
-1.2%
-186,685
-26.5%
Tribal
1,515
1,510
677
677
-4
-0.3%
-833
-55.2%
0
0.0%
Utah
53,893
46,929
45,947
46,417
-6,965
-12.9%
-981
-2.1%
469
1.0%
Vermont
7,078
6,631
6,614
6,614
-446
-6.3%
-18
-0.3%
0
0.0%
Virginia
337,752
181,472
162,611
136,499
-156,280
-46.3%
-18,861
-10.4%
-26,112
-16.1%
Washington
57,580
38,581
38,062
38,062
-18,999
-33.0%
-519
-1.3%
0
0.0%
West Virginia
534,392
585,385
546,702
132,539
50,993
9.5%
-38,683
-6.6%
-414,163
-75.8%
Wisconsin
264,315
204,473
198,795
118,394
-59,842
-22.6%
-5,678
-2.8%
-80,401
-40.4%
Wyoming
123,503
74,547
80,419
87,133
-48,956
-39.6%
5,872
7.9%
6,714
8.3%
Grand Total
14,354,370
10,928,889
10,078,786
6,275,795
-3,425,481
-23.9%
-850,103
-7.8%
-3,802,991
-37.7%
103
-------
Table 7-3. State-level Electric Generating Unit Sector NOx Emissions for each Transport Rule Modeling Case in 48 States and Washington,
DC.
State
2005 Base
2012 Base
2014 Base
2014
Remedy
2012 Base minus 2005
Base
2014 Base minus 2012
Base
2014 Remedy minus 2014
Base
Difference
% Diff.
Difference
% Diff.
Difference
% Diff.
Alabama
133,051
83,037
76,012
69,192
-50,014
-37.6%
-7,025
-8.5%
-6,820
-9.0%
Arizona
79,776
40,365
35,616
35,613
-39,412
-49.4%
-4,748
-11.8%
-4
0.0%
Arkansas
35,407
33,540
36,347
37,640
-1,867
-5.3%
2,807
8.4%
1,293
3.6%
California
6,925
25,101
26,874
26,776
18,176
262.5%
1,773
7.1%
-97
-0.4%
Colorado
73,909
48,464
49,381
49,331
-25,445
-34.4%
917
1.9%
-50
-0.1%
Connecticut
6,865
2,603
2,854
2,860
-4,262
-62.1%
251
9.7%
6
0.2%
Delaware
11,917
2,639
1,701
1,717
-9,278
-77.9%
-937
-35.5%
15
0.9%
District of
Columbia
492
0
0
0
-492
-100.0%
0
0
Florida
217,282
91,072
100,581
78,508
-126,210
-58.1%
9,509
10.4%
-22,073
-21.9%
Georgia
111,281
67,682
49,411
41,484
-43,599
-39.2%
-18,271
-27.0%
-7,927
-16.0%
Idaho
19
608
608
608
589
3062.5%
0
0.0%
0
0.0%
Illinois
127,940
52,481
55,269
49,162
-75,459
-59.0%
2,788
5.3%
-6,107
-11.0%
Indiana
213,588
120,593
117,832
110,740
-92,995
-43.5%
-2,761
-2.3%
-7,092
-6.0%
Iowa
72,806
46,105
48,400
42,231
-26,701
-36.7%
2,295
5.0%
-6,169
-12.7%
Kansas
90,220
37,240
32,637
24,328
-52,981
-58.7%
-4,603
-12.4%
-8,308
-25.5%
Kentucky
164,783
88,195
83,544
76,088
-76,588
-46.5%
-4,651
-5.3%
-7,456
-8.9%
Louisiana
64,987
30,453
31,573
31,582
-34,534
-53.1%
1,120
3.7%
9
0.0%
Maine
1,100
4,864
5,402
5,402
3,764
342.2%
538
11.1%
0
0.0%
Maryland
62,574
16,706
17,566
17,190
-45,868
-73.3%
860
5.1%
-375
-2.1%
Massachusetts
25,134
4,954
6,992
7,033
-20,181
-80.3%
2,038
41.1%
41
0.6%
Michigan
120,026
63,266
67,705
60,907
-56,761
-47.3%
4,440
7.0%
-6,798
-10.0%
Minnesota
84,304
39,400
41,474
34,429
-44,904
-53.3%
2,074
5.3%
-7,045
-17.0%
Mississippi
45,166
23,655
26,294
26,080
-21,510
-47.6%
2,639
11.2%
-214
-0.8%
Missouri
127,431
55,633
57,318
52,103
-71,798
-56.3%
1,685
3.0%
-5,216
-9.1%
Montana
39,858
18,302
19,399
19,303
-21,555
-54.1%
1,096
6.0%
-96
-0.5%
Nebraska
52,426
44,496
45,047
28,211
-7,930
-15.1%
551
1.2%
-16,836
-37.4%
104
-------
State
2005 Base
2012 Base
2014 Base
2014
Remedy
2012 Base minus 2005
Base
2014 Base minus 2012
Base
2014 Remedy minus 2014
Base
Difference
% Diff.
Difference
% Diff.
Difference
% Diff.
Nevada
47,297
13,294
14,074
14,050
-34,003
-71.9%
780
5.9%
-24
-0.2%
New Hampshire
8,827
4,068
5,126
4,971
-4,759
-53.9%
1,059
26.0%
-156
-3.0%
New Jersey
30,142
7,534
8,006
7,720
-22,608
-75.0%
472
6.3%
-286
-3.6%
New Mexico
75,483
64,264
64,745
64,833
-11,220
-14.9%
481
0.7%
88
0.1%
New York
63,315
20,909
21,689
20,528
-42,406
-67.0%
779
3.7%
-1,160
-5.4%
North Carolina
111,576
54,463
49,322
45,008
-57,113
-51.2%
-5,141
-9.4%
-4,314
-8.7%
North Dakota
76,381
52,968
53,265
53,267
-23,414
-30.7%
297
0.6%
2
0.0%
Ohio
258,944
103,192
104,149
89,753
-155,751
-60.1%
957
0.9%
-14,396
-13.8%
Oklahoma
86,204
66,365
66,966
44,143
-19,839
-23.0%
601
0.9%
-22,823
-34.1%
Oregon
9,383
8,875
9,584
9,632
-508
-5.4%
709
8.0%
48
0.5%
Pennsylvania
176,891
130,738
134,092
118,981
-46,153
-26.1%
3,354
2.6%
-15,110
-11.3%
Rhode Island
545
449
442
442
-96
-17.6%
-7
-1.6%
0
0.0%
South Carolina
52,657
35,395
39,018
36,747
-17,262
-32.8%
3,623
10.2%
-2,271
-5.8%
South Dakota
15,650
14,269
14,270
14,273
-1,381
-8.8%
1
0.0%
3
0.0%
Tennessee
102,934
37,694
29,276
20,512
-65,240
-63.4%
-8,418
-22.3%
-8,764
-29.9%
Texas
176,170
137,128
142,087
137,964
-39,043
-22.2%
4,960
3.6%
-4,123
-2.9%
Tribal
78
32
11
11
-46
-58.6%
-21
-64.9%
0
0.0%
Utah
65,261
67,429
67,434
67,434
2,168
3.3%
5
0.0%
0
0.0%
Vermont
297
379
455
455
82
27.6%
76
20.2%
0
0.0%
Virginia
62,793
38,820
40,469
39,734
-23,973
-38.2%
1,649
4.2%
-735
-1.8%
Washington
17,634
12,565
13,322
13,322
-5,069
-28.7%
757
6.0%
0
0.0%
West Virginia
159,947
62,434
64,824
53,975
-97,513
-61.0%
2,390
3.8%
-10,849
-16.7%
Wisconsin
72,170
40,062
40,750
33,537
-32,108
-44.5%
687
1.7%
-7,212
-17.7%
Wyoming
89,315
69,911
70,207
70,778
-19,404
-21.7%
296
0.4%
571
0.8%
Grand Total
3,729,161
2,084,689
2,089,422
1,890,590
-1,644,472
-44.1%
4,733
0.2%
-198,832
-9.5%
105
-------
Table 7-4. State-level Electric Generating Unit Sector SO2 Emissions for each Transport Rule Modeling Case in 48 States and Washington,
DC.
State
2005 Base
2012 Base
2014 Base
2014
Remedy
2012 Base minus 2005
Base
2014 Base minus 2012
Base
2014 Remedy minus 2014
Base
Difference
% Diff.
Difference
% Diff.
Difference
% Diff.
Alabama
460,123
455,825
417,340
173,566
-4,298
-0.9%
-38,485
-8.4%
-243,775
-58.4%
Arizona
52,733
34,734
35,601
35,601
-17,999
-34.1%
867
2.5%
0
0.0%
Arkansas
66,384
87,241
99,411
106,685
20,857
31.4%
12,170
13.9%
7,274
7.3%
California
601
6,763
7,350
7,350
6,162
1025.3%
587
8.7%
0
0.0%
Colorado
64,174
52,963
62,105
73,858
-11,211
-17.5%
9,143
17.3%
11,753
18.9%
Connecticut
10,356
3,355
3,774
3,883
-7,001
-67.6%
419
12.5%
109
2.9%
Delaware
32,378
3,641
2,172
2,172
-28,738
-88.8%
-1,468
-40.3%
0
0.0%
District of
Columbia
1,082
0
0
0
-1,082
-100.0%
0
0
Florida
417,321
110,687
143,601
148,069
-306,634
-73.5%
32,914
29.7%
4,468
3.1%
Georgia
616,063
406,279
170,288
93,208
-209,784
-34.1%
-235,991
-58.1%
-77,080
-45.3%
Idaho
0
182
182
182
182
106823.2%
0
0.0%
0
0.0%
Illinois
330,382
489,140
141,606
132,647
158,758
48.1%
-347,534
-71.0%
-8,959
-6.3%
Indiana
878,979
789,116
727,786
195,046
-89,863
-10.2%
-61,330
-7.8%
-532,740
-73.2%
Iowa
130,264
127,102
133,083
83,827
-3,162
-2.4%
5,981
4.7%
-49,256
-37.0%
Kansas
136,520
68,541
69,819
45,740
-67,978
-49.8%
1,277
1.9%
-24,078
-34.5%
Kentucky
502,731
520,546
488,005
116,927
17,815
3.5%
-32,541
-6.3%
-371,078
-76.0%
Louisiana
109,875
103,835
118,230
139,204
-6,040
-5.5%
14,395
13.9%
20,973
17.7%
Maine
3,887
2,203
2,355
2,355
-1,684
-43.3%
152
6.9%
0
0.0%
Maryland
283,205
49,942
42,926
30,368
-233,263
-82.4%
-7,016
-14.0%
-12,558
-29.3%
Massachusetts
84,234
8,581
13,364
13,363
-75,653
-89.8%
4,783
55.7%
-1
0.0%
Michigan
349,877
255,038
269,434
162,632
-94,840
-27.1%
14,396
5.6%
-106,802
-39.6%
Minnesota
101,678
67,816
70,937
49,622
-33,862
-33.3%
3,121
4.6%
-21,315
-30.0%
Mississippi
75,047
29,336
30,972
32,109
-45,711
-60.9%
1,636
5.6%
1,137
3.7%
Missouri
284,384
383,313
390,287
186,899
98,930
34.8%
6,973
1.8%
-203,388
-52.1%
Montana
19,715
13,641
15,447
22,826
-6,074
-30.8%
1,806
13.2%
7,379
47.8%
Nebraska
74,955
71,904
73,073
71,339
-3,050
-4.1%
1,169
1.6%
-1,734
-2.4%
106
-------
State
2005 Base
2012 Base
2014 Base
2014
Remedy
2012 Base minus 2005
Base
2014 Base minus 2012
Base
2014 Remedy minus 2014
Base
Difference
% Diff.
Difference
% Diff.
Difference
% Diff.
Nevada
53,363
13,486
14,416
14,416
-39,876
-74.7%
930
6.9%
0
0.0%
New Hampshire
51,445
3,332
6,453
6,742
-48,113
-93.5%
3,121
93.7%
289
4.5%
New Jersey
57,044
26,346
38,856
6,243
-30,698
-53.8%
12,511
47.5%
-32,614
-83.9%
New Mexico
30,628
9,895
11,857
13,926
-20,734
-67.7%
1,963
19.8%
2,068
17.4%
New York
180,847
56,461
42,887
15,160
-124,386
-68.8%
-13,574
-24.0%
-27,727
-64.7%
North Carolina
512,231
148,606
126,048
69,377
-363,625
-71.0%
-22,558
-15.2%
-56,670
-45.0%
North Dakota
137,371
101,946
103,633
103,624
-35,425
-25.8%
1,688
1.7%
-9
0.0%
Ohio
1,116,095
882,559
851,199
178,975
-233,536
-20.9%
-31,359
-3.6%
-672,224
-79.0%
Oklahoma
110,081
135,972
137,981
138,072
25,891
23.5%
2,009
1.5%
91
0.1%
Oregon
12,304
10,197
11,336
11,336
-2,107
-17.1%
1,139
11.2%
0
0.0%
Pennsylvania
1,002,203
495,463
509,649
125,545
-506,740
-50.6%
14,186
2.9%
-384,105
-75.4%
Rhode Island
176
0
0
0
-176
-100.0%
0
#DIV/0!
0
South Carolina
218,781
186,355
213,281
100,788
-32,426
-14.8%
26,927
14.4%
-112,494
-52.7%
South Dakota
12,215
29,711
29,711
29,711
17,495
143.2%
0
0.0%
0
0.0%
Tennessee
266,148
324,377
284,468
64,721
58,229
21.9%
-39,909
-12.3%
-219,747
-77.2%
Texas
534,949
446,006
453,332
266,648
-88,944
-16.6%
7,326
1.6%
-186,685
-41.2%
Tribal
3
0
0
0
-3
-100.0%
0
#DIV/0!
0
Utah
34,813
33,828
33,498
33,968
-985
-2.8%
-330
-1.0%
469
1.4%
Vermont
9
219
263
263
209
2218.6%
44
20.2%
0
0.0%
Virginia
220,287
92,468
77,256
51,144
-127,819
-58.0%
-15,212
-16.5%
-26,112
-33.8%
Washington
3,409
3,225
3,430
3,430
-183
-5.4%
205
6.3%
0
0.0%
West Virginia
469,456
536,695
498,507
84,344
67,239
14.3%
-38,188
-7.1%
-414,163
-83.1%
Wisconsin
180,200
135,827
130,538
50,137
-44,373
-24.6%
-5,290
-3.9%
-80,401
-61.6%
Wyoming
89,874
45,112
51,817
58,530
-44,762
-49.8%
6,705
14.9%
6,714
13.0%
Grand Total
10,380,883
7,859,810
7,159,569
3,356,577
-2,521,072
-24.3%
-700,242
-8.9%
-3,802,991
-53.1%
107
-------
Table 7-5. Group 1 and Group 2 States NOx Total Emissions for each Transport Rule Modeling Case
2005 Base
Year
2012 Base
Case
2014 Base
Case
2014
Remedy
2014
Remedy -
2012 Base
Case
Percent
Change:
2014
Remedy
vs 2012
Base
Case
2014
Remedy
-2014
Base
Case
Percent
Change:
2014
Remedy
vs 2014
Base Case
Annual Total NOx Emissions for States in
Group 1
8,942,956
5,998,929
5,592,557
5,490,517
-508,412
-8.5%
-102,039
-1.8%
Annual Total NOx Emissions for States in
Group 2
4,626,321
3,351,169
3,083,373
3,030,042
-321,127
-9.6%
-53,331
-1.7%
Annual Total NOx for all States included for
PM
13,569,277
9,350,098
8,675,929
8,520,559
-829,539
-8.9%
-155,370
-1.8%
Annual Total NOx Emissions for All States
Fully within the Eastern Modeling Domain
17,265,033
12,013,803
11,173,286
10,974,018
-1,039,784
-8.7%
-199,268
-1.8%
Annual Total NOx Emissions for All Western
States
3,887,276
2,959,396
2,751,224
2,751,659
-207,737
-7.0%
435
0.0%
Total NOx
21,152,309
14,973,199
13,924,510
13,725,678
-1,247,521
-8.3%
-198,832
-1.4%
108
-------
Table 7-6. Group 1 and Group 2 States SO2 Total Emissions for each Transport Rule Modeling Case
2005 Base
Year
2012 Base
Case
2014 Base
Case
2014
Remedy
2014
Remedy -
2012 Base
Case
Percent
Change:
2014
Remedy
vs 2012
Base
Case
2014
Remedy -
2014 Base
Case
Percent
Change:
2014
Remedy
vs 2014
Base Case
Annual Total S02 Emissions for States in
Group 1
8,695,431
6,841,869
6,198,185
2,999,641
-3,842,228
-56.2%
-3,198,544
-51.6%
Annual Total S02 Emissions for States in
Group 2
2,989,533
2,343,536
2,086,522
1,419,361
-924,175
-39.4%
-667,161
-32.0%
Annual Total S02 for all States included for
PM
11,684,964
9,185,405
8,284,707
4,419,002
-4,766,403
-51.9%
-3,865,705
-46.7%
Annual Total S02 Emissions for All States
Fully within the Eastern Modeling Domain
13,545,837
10,361,804
9,512,351
5,680,977
-4,680,826
-45.2%
-3,831,374
-40.3%
Annual Total S02 Emissions for All Western
States
808,533
567,085
566,435
594,818
27,733
4.9%
28,383
5.0%
Total S02
14,354,370
10,928,889
10,078,786
6,275,795
-4,653,094
-42.6%
-3,802,991
-37.7%
109
-------
Table 7-7. Group 1 and Group 2 States NOx EGU Sector Emissions for each Transport Rule Modeling Case
2005 Base
Year
2012 Base
Case
2014 Base
Case
2014
Remedy
2014
Remedy -
2012 Base
Case
Percent
Change:
2014
Remedy
vs 2012
Base
Case
2014
Remedy
-2014
Base
Case
Percent
Change:
2014
Remedy
vs 2014
Base Case
Annual EGU NOx Emissions for States in
Group 1
1,927,858
938,824
940,211
838,171
-100,653
-10.7%
-102,039
-10.9%
Annual EGU NOx Emissions for States in
Group 2
700,110
444,377
425,686
372,355
-72,022
-16.2%
-53,331
-12.5%
Annual EGU NOx for all States included for
PM
2,627,967
1,383,201
1,365,897
1,210,527
-172,674
-12.5%
-155,370
-11.4%
Annual EGU NOx Emissions for All States
Fully within the Eastern Modeling Domain
3,224,300
1,715,510
1,718,178
1,518,910
-196,600
-11.5%
-199,268
-11.6%
Annual EGU NOx Emissions for All Western
States
504,861
369,180
371,244
371,680
2,500
0.7%
435
0.1%
Total EGU NOx
3,729,161
2,084,689
2,089,422
1,890,590
-194,099
-9.3%
-198,832
-9.5%
110
-------
Table 7-8. Group 1 and Group 2 States SO2 EGU Sector Emissions for each Transport Rule Modeling Case
2005 Base
Year
2012 Base
Case
2014 Base
Case
2014
Remedy
2014
Remedy -
2012 Base
Case
Percent
Change:
2014
Remedy
vs 2012
Base
Case
2014
Remedy -
2014 Base
Case
Percent
Change:
2014
Remedy
vs 2014
Base Case
Annual EGU S02 Emissions for States in
Group 1
6,764,335
5,313,000
4,752,537
1,553,993
-3,759,007
-70.8%
-3,198,544
-67.3%
Annual EGU S02 Emissions for States in
Group 2
2,143,069
1,702,727
1,468,071
800,910
-901,816
-53.0%
-667,161
-45.4%
Annual EGU S02 for all States included for
PM
8,907,403
7,015,726
6,220,608
2,354,903
-4,660,823
-66.4%
-3,865,705
-62.1%
Annual EGU S02 Emissions for All States
Fully within the Eastern Modeling Domain
10,019,270
7,635,785
6,912,529
3,081,155
-4,554,630
-59.6%
-3,831,374
-55.4%
Annual EGU S02 Emissions for All Western
States
361,613
224,026
247,039
275,422
51,397
22.9%
28,383
11.5%
EGU S02
10,380,883
7,859,810
7,159,569
3,356,577
-4,503,233
-57.3%
-3,802,991
-53.1%
Table 7-9. 26-State Total and Electric Generating Unit Sector Summer NOx Emissions for each Transport Rule Modeling Case
Percent
Percent
Change:
2014
Change:
2014
2014
Remedy
2014
Remedy
Remedy
2012
2014
-2012
Remedy
-2014
vs 2014
2005 Base
Base
Base
2014
Base
vs 2012
Base
Base
Year
Case
Case
Remedy
Case
Base Case
Case
Case
Summer EGU NOx Emissions for States Included for
Ozone
1,001,600
671,939
668,513
593,833
-78,106
-11.6%
-74,680
-11.2%
Summer Total NOx Emissions for States Included
for Ozone
6,153,473
4,455,600
4,128,792
4,054,111
-401,489
-9.0%
-74,680
-1.8%
111
-------
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Agency Research Triangle Park, NC
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